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https://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC12822238&blobtype=pdf
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# Integrated Genomic and Epidemiological Surveillance to Monitor SARS-CoV-2 Variants in Italy: Insights From the JN.1 Case Study (2023-2024)
Mattia Manica, Emanuela Giombini, Martina Manso, Carla Grané, | Luigina, Antonino Bella, Angela Di Martino, Daniele Petrone, Flavia Riccardo, Piero Poletti, | Patrizio Pezzotti, Anna Palamara, Stefano Merler, Paola Stefanelli
## Abstract
The epidemiology of SARS-CoV-2 is marked by the continuous emergence of new lineages. Early detection and assessment of their transmissibility can be challenging for surveillance systems that rely solely on case time series data. Genomic surveillance, focusing on identifying and characterizing circulating variants, can provide early insights into their epidemiological impact. Phylogenetic and phylodynamic methods were applied to sequence data collected between October 2023 and January 2024 to study the transmission of the JN.1 variant in Italy. The genomic surveillance encompassed two data flows: flash surveys estimating variant prevalence and continuous sampling to identify emerging variants. We estimated the effective reproduction number (R e ) of JN.1 using a phylodynamic birth-death model. Results were compared with the daily net reproduction number (R t ) of SARS-CoV-2 estimated from time series of hospital admissions recorded through epidemiological surveillance. We traced back the appearance of JN.1 in Italy to October 2023, with subvariants emerging and co-circulating shortly thereafter. JN.1 became dominant nationwide by the end of 2023. According to phylodynamic analysis, the R e of JN.1 was 1.73 (95% CI: 1.36-2.28) in mid-November, and its transmissibility declined over the following months. This trend aligned with R t estimates from epidemiological surveillance, encompassing all co-circulating lineages. The high transmissibility of JN.1 anticipated the rise in its prevalence in the population and showed a temporal correlation with a transient increase in COVID-19 hospitalizations. Integrating genomic and epidemiological surveillance enhances pathogen monitoring and the assessment of new lineages' transmissibility, providing complementary evidence to patterns observed through standard surveillance.
## 1 | Introduction
The evolution of SARS-CoV-2 has become a highly dynamic process, marked by the relentless emergence of new variants and subvariants [1,2]. The selective pressure exerted on the circulating lineages can favor mutations enhancing the viral transmissibility and/or immune evasion, thereby promoting their spread [3][4][5]. The epidemiology of SARS-CoV-2 infections has been characterized by successive waves of COVID-19 cases of varying intensity and associated with potentially different morbidity rates, driven by the genetic characteristics of the spreading variants.
A standard approach for monitoring viral transmissibility relies on estimating the net reproduction number by applying the renewal equation to the time series of cases that test positive for the infection, exhibit symptoms, or are hospitalized [6,7]. However, intensive surveillance efforts are costly and may not be sustainable in the long term. As a result, under conditions of relatively low disease burden and stable pressure on the healthcare system, surveillance efforts are typically scaled back and adapted to monitor warning signs of changing conditions, rather than continuously tracking every detectable case. Additionally, estimates based on the time series of confirmed cases can be strongly affected by fluctuations in case reporting, often biased towards more severe cases, and are unable to provide separate transmissibility estimates for cocirculating variants due to the availability of genetic characterization only for a limited set of identified infections.
Since 2021, genomic surveillance has been successfully applied to monitor SARS-CoV-2 variants. Genetic, phylogenetic, and phylodynamic analyses have enabled public health systems to rapidly identify and characterize emerging variants [8][9][10], as well as trace their origins and patterns of spread [11]. These efforts have contributed to the development of effective mitigation and containment strategies to counter new epidemic waves [8,12]. In Italy, surveillance of SARS-CoV-2 is currently conducted through two complementary data flows: epidemiological and genomic.
In this study, we investigated how genetic and phylodynamic methods can successfully integrate the epidemiological analysis of new emerging SARS-CoV-2 variants. To this aim, as a proof of concept, we focused on the emergence and spread of the JN.1 variant in Italy, between 16 October 2023 and 31 January 2024. Internationally, the first confirmed case of JN.1 variant was identified in France in August 2023 [13]. The variant rapidly spread across American and European countries, eventually becoming prevalent globally at the beginning of 2024. JN.1 is a descendant of the Omicron lineage's BA.2.86 subvariant, characterized by more than 30 distinctive mutations in the spike protein [14]. JN.1 has subsequently given rise to multiple sublineages that dominate the current global circulation of .
During the study period, genomic surveillance of SARS-CoV-2 virus was conducted following two sequencing flows: 1) genomic surveys (hereafter denoted as "flash surveys") aimed at estimating variant prevalence by sequencing a representative sample of ascertained cases across the national territory on a given week of the month; and 2) continuous sequencing, applied to a subset of hospitalized patients with confirmed SARS-CoV-2 infection, enabling the early detection of variants or mutations. We analyzed the emergence of the JN.1 variant and its descendants, which together we refer to as JN.1*, as identified according to the Pango designation criteria as of 16 May 2024. The analysis of its temporal dynamics serves as an illustrative example of how the spread of new SARS-CoV-2 lineages can be assessed by integrating data from epidemiological and genomic surveillance.
## 2 | Materials and Methods
## 2.1 | Epidemiological Surveillance
Since February 2020, Italy notifies all laboratory-confirmed SARS-CoV-2 human infections to a national case-based surveillance system (hereby indicator-based surveillance) as previously described in Riccardo et al. [16]. The surveillance collects also the date of eventual hospitalization admissions. We analyzed the epidemiology of SARS-CoV-2 in Italy in the period September 2023-January 2024. We extracted epidemiological records, consolidated as of 27 May 2024, and we calculated the number of hospital admissions by day and week during the study period. We then estimated the net reproduction number (R t ) as previously described in [6] at national and at Region/ Autonomous Province (AP) levels. Estimates of R t assume that the generation time of newly emerging variants is comparable to that of pre-circulating variants and consistent across different lineages. During the study period, three flash surveys were conducted: 13-19 November 2023, 11-17 December 2023, and 15-21 January 2024. Out of 820, 913, and 433 sequences collected in the three surveys, 52 (6.3%), 372 (40.7%), and 333 (76.9%) were identified as belonging to the JN.1* lineage (including JN.1 and its subvariants), respectively. A generalized linear model with a binomial distribution was applied to estimate the increase in JN.1* prevalence over time (day of the year).
## 2.2 | Genomic Surveillance
Genomes collected through both flash surveys and continuous sequencing of COVID-19 hospitalized patients, covering all variants circulating between 16 October 2023 and 31 January 2024, were uploaded to GISAID [17]. From this dataset, we selected all sequences belonging to the JN.1* lineage that met minimal quality criteria, which included the absence of sporadic insertions or deletions and a coverage (i.e., the percentage of the genome sequenced) > 90%. The resulting dataset consisted of 1217 genomes, which were further analyzed using genomic modeling approaches.
## 2.3 | Genomic Diversity and Phylogenetic Analysis
To calculate the genetic diversity within and between JN.1 and JN.1 subvariants, the selected genomes were aligned using MAFFT V.7.520 [18]. Pairwise genetic distances were calculated using the p-distance model and 500 bootstrap repetitions with Mega 11. The distribution of JN.1 and JN.1 subvariants across the Italian regions were evaluated by means of a maximum likelihood phylogenetic tree constructed using IQ-TREE v1.6.9 [19]. The phylogenetic tree included all the JN.1* genomes that met our inclusion criteria and was rooted to reference 'BA.2.86' (using the Nextclade reference Wuhan-Hu-1 with BA.2.86 SNPs), with bootstrap support values calculated from 1,000 replicates. The tree was built using the best substitution model (GTR + F) as identified through ModelFinder and visualized using TVBOT [20].
## 2.4 | Phylodynamic Analysis
To provide quantitative epidemiological insights on the new emerging variant, we performed a Bayesian phylodynamic analysis of the JN.1 sequences, using a birth-death skyline model (BDSKY) [21]. We used the BEAST2 software (v2.7.5) for the phylodynamic analysis and the R package "beastio" to inspect the parameter posterior distributions and assess convergence and sufficient sampling (effective sample size > 200).
This modeling approach enabled us to estimate key epidemiological indicators, including the variant specific reproduction number (R e ), representing its transmissibility potential; the 'uninfectious rate', which directly relates to the variant-specific generation time; the 'time of most recent common ancestor', informing on the time of initial (potentially unobserved) variant emergence; and the 'sampling proportion', which provides insights into the overall number of individuals infected by the variant during the study period. The phylodynamic model assumes a general time reversible (GTR) + G4 nucleotide substitution model and an uncorrelated, lognormally distributed, relaxed molecular clock, implying that every branch in a phylogenetic tree may evolve at different evolutionary rates. To investigate temporal changes of the variant's transmissibility, we assumed a prior Gamma-distributed R e (shape = 2, scale = 1) to be piecewise constant over five intervals. For the uninfectious rate parameter, we assumed a lognormal prior distribution with a mean of 90 and a standard deviation of 0.4; for the origin parameter, we assumed a uniform prior distribution ranging from 0 to 5 years. Finally, for the sampling proportion, we assumed a Beta distributed prior (alpha = 1, beta = 3).
We applied the model to JN.1 sequences collected in Italy between 16 October 2023 and 31 January 2024. Specifically, based on the results of genomic diversity and phylogenetic analyses, JN.1 subvariant sequences were excluded from our baseline phylodynamic analysis to reduce computational time and complexity. To assess the model's robustness under this approach while accounting for computational constraints, we conducted a sensitivity analysis by comparing results from one illustrative Italian region using either all JN.1* sequences or only JN.1 sequences (i.e., with and without JN.1 subvariants).
To do this, we selected the Veneto region because it shared the highest number of sequences and accounted for approximately one third (31.2%, n = 380) of all JN.1* sequences collected in Italy (Figure 1). An additional sensitivity analysis was conducted by considering that every branch in a phylogenetic tree evolves according to the same evolutionary rate, assuming a strict molecular clock with uninformative uniform prior. For each analysis, we carried out 100 million independent MCMC runs, sampling every 1000 steps and discarding 10% of the initial iterations to account for the burn-in period. Finally, we compared the estimated reproductive number (R e ) of the JN.1 variant obtained from the phylodynamic model to the overall SARS-CoV-2 reproduction number (R t ), as inferred from the time series of hospitalized COVID-19 cases during the same period.
## 3 | Results
During the study period, 49089 hospitalizations were reported to the Italian National surveillance of SARS-CoV-2 infections. The median age was 79 (IQR: 67-86) and 49.2% (n = 24152) were women. Weekly cases almost steadily increased up to the middle of December 2023 and then continuously decreased at the minimum level in the last week of January 2024 (Figure 2). Figure S1 shows the temporal distribution of hospitalizations by Region/Autonomous province. In all cases, the peak was observed in December, with most of them showing a temporal trend similar to the one observed at the national level.
The JN.1 variant was first detected through the genomic flash survey in November 2023, with a point prevalence of 5.97% at the national level, when adjusted by the number of cases by region (see Figure 2). According to data collected through the flash surveys, JN.1 became the predominant SARS-CoV-2 variant circulating in Italy by the end of 2023, reaching a 77% national point-prevalence in the third week of January 2024 (see Figure 2).
Based on analyzed genomic data collected in Italy during the study period and shared on GISAID, according to the lineage assignment confirmed using Nextclade (accessed 16 May 2024) we retrospectively traced back the earliest JN.1 sequence to a case sampled on 16 October 2023 (Figure 1), before the official identification of the JN.1 variant through the national surveys. However, only later, during the week of 23-29 October 2023, distinct subvariants of JN.1 (i.e. with a limited number of mutations from JN.1 [22]) emerged and began to co-circulate with the original JN.1 (Table S1 for a complete list of JN.1 subvariants).
The proportion of JN.1 among JN.1* sequences remained approximately constant throughout the study period (Figure 3), resulting in 635 (52.1%) JN.1 sequences out of the 1217 JN.1* sequences analyzed.
All analyzed sequences reported the region of collection (Figure 1, Figure S2), while information regarding the age class and the admission in hospital of the sequenced cases was available for 75.8% (n = 922) and 43.2% (n = 526) of sequences, respectively. Similar percentages were observed between JN.1 and JN.1 subvariants (age class: 489 out of 635, 77.0% JN.1 vs 433 out of 582, 74.4% JN.1 subvariants; hospitalization: 276 out of 635, 43.5% JN.1 vs 250 out of 582, 43.0% JN.1 subvariants). Almost half of the sequenced cases for which the age class was reported were between 70 and 90 years of age; no differences were observed between JN.1 and JN.1 subvariants (Figure S3).
To evaluate the genetic distance between genomes belonging to JN.1 and JN.1 subvariants and to determine to what extent they should be considered as two distinct groups, inter and intragroup distances were calculated. The JN.1 group exhibited an internal distance with a standard deviation of 2.3 × 10 -4 ± 1.5 × 10 -5 , while the JN.1 subvariants group had a slightly higher internal distance of 3.3 × 10 -4 ± 3.5 × 10 -5 . The inter-group distance between JN.1 and JN.1 subvariants was calculated to be 3.0 × 10 -4 ± 2.8 × 10 -5 . This overall similarity among sequences is further supported by the phylogenetic tree, where only small clusters with significant bootstrap values (> 80) were identified. Additionally, Figure 4 shows how all sequences from different regions are interspersed and to what extent sequences from individual regions contributing a substantial number of sequences (e.g. the Veneto region corresponding to orange interconnections) are mixed with those of other regions without forming a distinct cluster.
Results from the phylodynamic model revealed a relatively high transmissibility of JN.1 during mid-November, with an estimated R e of . This finding aligns with evidence coming from flash surveys conducted at the same time, showing a progressive increase in the prevalence of JN.1 (see Figure 2). R t estimates obtained from epidemiological surveillance records collected in the same period show a downward trend lasting until October 2023, followed by a sharp upsurge in November (from 0.98 to 1.22). A similar dynamic was observed in the number of hospital admissions associated with SARS-CoV-2 infection (see Figure 2). R e estimates obtained from the phylodynamic model show a decline in transmissibility in December 2023, reaching estimated values below the epidemic threshold (0.95, 95% CI: 0.91-0.99) at the beginning of 2024. This pattern coincided with JN.1* becoming the predominant SARS-CoV-2 variant circulating in Italy by the end of 2023 (Figure 2). The increased prevalence of JN.1, coupled with an estimated decrease in its reproduction number, correlated with a decline in R t based on hospitalized cases. Specifically, R t dropped below the epidemic threshold towards the end of 2023 and ranged between 0.61 and 0.82 in January 2024 (Figure 2).
The phylodynamic model also yielded a mean estimated duration of infectiousness of 5.4 days (95% CI: 2.9-9.2 days), which is consistent with available estimates for previous Omicron lineages (mean estimates ranging between 5.7 and 8.6 days [23]). The time to the most recent common ancestor (tMRCA) was estimated to fall between 15 August and 24 September 2023, in line with the emergence of JN.1 in Europe [13]. Our analysis also suggests that analyzed sequences represented the 0.22% (95% CI: 0.06%-0.58%) of all JN.1 infections occurred in the country during the reconstructed epidemic, suggesting that as of 31 January 2024, the circulation of the JN.1 variant might have caused approximately 110-1095 thousand SARS-CoV-2 infections in Italy. Similar estimates were obtained under the assumption of a strict molecular clock, with a mean duration of infectiousness of 5.38 days, a tMRCA falling between 15 August and 24 September, and approximately 113-985 thousand JN.1 infections occurring during the study period (Table S2). The temporal dynamics of the JN.1 reproduction number were also consistent, showing a peak of approximately 1.72 in early December, followed by a decrease in transmissibility that led to Re estimates below 1 in early February (Figure S4). A considerable overlap in the estimated trajectory of transmissibility was found when restricting the analysis to the sequences obtained from the Veneto region, either including or not JN.1 subvariants (see Figure S5 and Table S1).
## 4 | Discussion
In Italy, JN.1 and its subvariants rapidly became predominant between December 2023 and January 2024, almost replacing previously circulating variants. Our analysis reveals a high degree of genetic homogeneity among all JN.1* genomes analyzed, including both JN.1 and its subvariants. Although, as expected, the JN.1 group exhibited slightly lower diversity compared to the JN.1 subvariants, the phylogenetic tree analysis did not reveal well-supported bootstrap clusters, likely due to the high sequence similarity. This suggests an ongoing evolutionary process marked by a high degree of genetic relatedness among circulating variants. These findings support the assumption that JN.1 can serve as a representative of the entire JN.1* group for phylodynamic analyses, thereby reducing computational constraints.
The rapid spread of JN.1* observed over a relatively short period -about 1 month and a half from emergence to dominanceunderscores its high transmissibility compared to pre-circulating strains. We found that the temporal expansion of JN.1* correlates with a swift, albeit brief, wave of hospital admissions detected by monitoring epidemic trends from epidemiological surveillance data. This surge was relatively short-lived, with the variant's specific transmissibility peaking in early November and subsiding within a couple of months. In principle, the increasing prevalence of JN.1* and the high transmissibility we estimated for JN.1 in early November could also be associated with the development of new immune escape mechanisms or an increased ability to infect specific niches of susceptible individuals [13,24,25]. During the 2023-2024 season, the Italian Ministry of Health recommended administration of the updated monovalent XBB.1.5 mRNA vaccine as a booster for individuals aged ≥ 60 years and for younger people with high frailty due to underlying medical conditions, with priority given to those aged ≥ 80 years, residents of long-term care facilities, and individuals with chronic diseases [26]. However, vaccination coverage among the elderly remained modest, with 11.7% of individuals aged 70-79 years and 15.8% of those aged ≥ 80 years receiving a booster between September 2023 and July 2024 [27]. Although vaccination may have partially influenced transmission dynamics, its overall impact was likely limited. During this period, no age-specific social distancing measures were in place, and most COVID-19-related restrictions in Italy had already been lifted. Given the complex epidemiological landscape associated with SARS-CoV-2, including uncertainties surrounding the current levels of both natural and vaccine-induced immunity within the considered population, it is not possible to draw definitive conclusions about the factors driving the temporary epidemiological success of JN.1 based only on the results presented here. Multiple lines of evidence -such as results from immune surveillance and severity data -would be required to provide a robust interpretation of the observed pattern.
Our estimates suggest that, following its rapid surge, the transmissibility of JN.1 began to decrease significantly. This pattern aligns well with the temporal qualitative trajectory of the (overall) SARS-CoV-2 net reproduction number, as estimated from the time series of hospitalized patients. However, our analysis reveals that transmissibility estimates differ significantly when comparing a phylogenetic approach applied to the spread of JN.1 (average R e ~1.7) with the assessment of overall SARS-CoV-2 transmissibility encompassing all co-circulating lineages based on epidemiological data (average R t ~1.2). This underscores the value of integrating diverse approaches to characterize the spread of new variants. The observed progressive decrease in the transmission potential of JN.1 could be due to several alternative or coexisting factors [28][29][30]. Firstly saturation, i.e. the reduction of susceptible because of acquired immunity. Secondly competition, i.e. the emergence or persistence of other circulating variants limiting the component of overall SARS-CoV-2 transmission due to JN.1. Thirdly, since we are measuring this decrease among hospitalized patients, the observed reduction in severity might reflect decreased JN.1 circulation only within hospitalized cases, and not necessarily in the general population or be a distinctive seasonal recurring pattern in SARS-CoV-2 epidemiology in Italy [31].
Moreover, limited evidence suggest that JN.1* exhibits either increased or reduced pathogenicity compared to other circulating variants [32]. Accurately characterizing specific SARS-CoV-2 variants in terms of transmissibility and attack rates remains a significant challenge due to the availability of samples eligible for the sequencing and the testing policy. However, phylodynamic analyses may effectively integrate and increase the granularity to data collected through epidemiological surveillance. Here we show that combining these two sources can provide valuable insights into transmission patterns by allowing the production of estimates that are associated with specific lineages significantly reducing uncertainties underlying complex epidemiological dynamics. For instance, by leveraging the estimated sampling proportion, we also derived an approximate estimate of the infection attack rate of JN.1 during the considered period. Despite the uncertainty of the obtained estimates, such a result is well beyond what can be estimated using data collected only through routine epidemiological surveillance [8]. More in general, when testing is predominantly limited to hospitalized patients -as in the case for SARS-COV-2 in Italy in 2024combining genetic and phylodynamic methods with standard analyses of epidemiological surveillance data may become essential for monitoring complex epidemiological patterns and epidemic trends occurring in the general population.
Nonetheless, several limitations need to be considered when interpreting our results. First, we neglected any geographical pattern in the spread of the infection and therefore considered the progressive expansion of JN.1 as an epidemic occurred at national scale. This may have introduced a bias in our analysis due to potentially different sampling efforts carried out across regions, different local transmission patterns, or the likely heterogeneous representativeness of collected samples of the viral diversity cocirculating during the study period. However, the phylogenetic tree of full-length genomes of JN.1 and JN.1 subvariants demonstrated that circulating variants were not geographically restricted but rather exhibited a uniform distribution across different regions. This supports the idea that individual regions contributing a substantial number of sequences may serve as arbitrary yet representative proxies of nationally circulating variants when applying phylodynamic approaches, which are computationally intensive and may become impractical when applied to very large sequence datasets. Specifically, as an illustrative example, we show that phylodynamic analyses conducted using samples exclusively from one region yielded estimates consistent with those obtained when including data from all regions. Second, we should acknowledge that genetic epidemiology is highly dynamic, with the classification of variants and their subvariants being continuously revised as new information becomes available. This means that estimates obtained from sequencing data should be progressively and carefully revised over time. Although our results highlight the potential of phylodynamic approaches in providing complementary evidence on the epidemiological patterns detected through standard surveillance of cases, non-negligible computational challenges may still arise from the analysis of large datasets of sequences gathered during large and widespread epidemics.
The approach described here will be valuable in illustrating the spread mechanisms of SARS-CoV-2 variants that may emerge in the future, during a time when the virus is no longer considered pandemic but endemic. Given the complex and everevolving immunity landscape associated with SARS-CoV-2, maintaining and enhancing the integration of different surveillance systems is required to equip public health systems with multiple and adaptive strategies to control and monitor new variants as they emerge.
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110. Ou, Yang, Zhang (2024) "Evolving Immune Evasion and Transmissibility of SARS-CoV-2: The Emergence of JN.1 Variant and Its Global Impact" *Drug Discoveries & Therapeutics*
111. Liu, Zhao, Shi (2024) "Lineage-Specific Pathogenicity, Immune Evasion, and Virological Features of SARS-CoV"
112. "Indicazioni e raccomandazioni per la campagna di vaccinazione autunnale/invernale 2023/2024 anti COVID-19"
113. (2024) "COVID-19 Vaccination Coverage in the EU/EEA During the 2023-24 Season Campaigns"
114. Del Rio, Omer, Malani (2022) "Winter of Omicron-The Evolving COVID-19 Pandemic" *Journal of the American Medical Association*
115. Rochman, Wolf, Faure et al. (2021) "Ongoing Global and Regional Adaptive Evolution of SARS-CoV-2" *Proceedings of the National Academy of Sciences*
116. Otto, Day, Arino (2021) "The Origins and Potential Future of SARS-CoV-2 Variants of Concern in the Evolving COVID-19 Pandemic" *Current Biology*
117. Marziano, Guzzetta, Menegale (2023) "Estimating SARS-CoV-2 Infections and Associated Changes in COVID-19 Severity and Fatality" *Influenza and Other Respiratory Viruses*
118. Levy, Chilunda, Davis (2024) "Reduced Likelihood of Hospitalization With the JN.1 or HV.1 Severe Acute Respiratory Syndrome Coronavirus 2 Variants Compared With the EG.5 Variant" *Journal of Infectious Diseases*
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# P-748. Chronic wounds and xylazine exposure among people who use drugs in Baltimore and Washington, DC: prevalence, preferences, and testing methods
Edward Traver, ; Onyinyechi Ogbumbadiugha-Weekes, Meredith Zoltick, Claire Tindula, Dnp, Fnp-C, Tina Liu, Sabina Ghale, Meghan Derenoncourt, Miriam Jones, Ashley Davis, Dorcas Salifu, Lydia Mitchell, Meghan Anderson, Rahwa Eyasu, Emade Ebah, Elana Rosenthal, Sarah Kattakuzhy
Background. Chronic wounds in people who use drugs (PWUD) are frequently infected and may progress to severe, life-threatening infections. Such wounds may be caused by xylazine, a non-opioid adulterant of illicit fentanyl and avoidance of xylazine may decrease wound incidence and infection. Xylazine test strips (XTS, BTNX Inc.) are commercially available to check illicit drugs for xylazine, but more data is needed on xylazine prevalence and knowledge among PWUD, and it is unknown if XTS can be used to detect xylazine in urine. Methods. We surveyed patients at two clinics in Baltimore and Washington, DC that provide multidisciplinary care to PWUD. Patients were included if they reported non-prescribed opioids, cocaine, or methamphetamine in the past 30 days. Urine was tested for xylazine with XTS and standard liquid chromatography-mass spectroscopy S572 • OFID 2026:13 (Suppl 1) • Poster Abstracts (LC-MS). We measured associations between wound prevalence, xylazine urine positivity, and other demographic and clinical factors with Fischer's exact test for categorical variables and Mann Whitney for continuous variables. We estimated the sensitivity and specificity of XTS to detect xylazine in urine compared to LC-MS and calculated 95% confidence intervals with the Wilson-Brown method. Results. 119 participants were included; 27 (23%) who had ever had a wound (Table 1). Xylazine was detected by LC-MS in urine from 56 (47%) participants. People with wounds were more likely to be recruited from Baltimore (p=.002) and White or Caucasian race (p< .001). Wounds were not associated with injection drug use or xylazine detection in urine. People with wounds were more likely to be knowledgeable about xylazine (Table 2). XTS had a low sensitivity but high specificity for urine xylazine detection compared to LC-MS (Figure 1).
Conclusion. Xylazine exposure at a single timepoint in PWUD in Baltimore and Washington was common but not associated with lifetime history of wounds, potentially due to variable exposure and detection over time. People with wounds were more familiar with xylazine. PWUD are interested in using XTS but the vast majority have not, suggesting residual structural barriers. XTS are have useful positive predictive value but low negative predictive value when used on urine.
Disclosures. All Authors: No reported disclosures
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# Retraction RETRACTION: Expression of Factor X in BHK-21 Cells Promotes Low Pathogenic Influenza Viruses Replication Advances in Virology
Te retraction has been agreed following an investigation of the concerns raised by Actinopolyspora biskrensis on PubPeer [1], which identifed several concerns related to Figure 3.
More specifcally, the images of BHK-21/FX and BHK-21/trypsin cells at 24 and 72-hour marks contain overlapping features, despite representing diferent experimental conditions.
As a result of the investigation, the data and conclusions of this article are considered unreliable.
Te authors disagree with this retraction.
## References
1. (2024) "Expression of Factor X in BHK-21 Cells Promotes Low Pathogenic Infuenza Viruses Replication, PubPeer"
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# Clinical Phenotypes of Critically Ill Patients with COVID-19 Infected with Omicron: A Nationwide Prospective Cohort Study
Etienne Audureau, Pierre Bay, Sébastien Préau, Raphaël Favory, Aurélie Guigon, Nicholas Heming, Elyanne Gault, Tài Pham, Amal Chaghouri, Matthieu Turpin, Laurence Morand-Joubert, Sébastien Jochmans, Aurélia Pitsch, Sylvie Meireles, Damien Contou, Amandine Henry, Damien Roux, Quentin Le Hingrat, Antoine Kimmoun, Cédric Hartard, Frédéric Pène, Anne-Sophie L'honneur, Antoine Guillon, Lynda Handala, Fabienne Tamion, Alice Moisan, Thomas Daix, Sébastien Hantz, Flora Delamaire, Vincent Thibault, Cédric Darreau, Jean Thomin, Jean-Michel Pawlotsky, Slim Fourati, A.-S L'honneur, J.-M Pawlotsky
## Abstract
Introduction: The clinical presentation of critically ill patients with coronavirus disease 2019 (COVID-19) has evolved significantly with the emergence of the Omicron variant. Current intensive care unit (ICU) admissions involve patients with diverse comorbidities and immune statuses, highlighting the need to redefine homogeneous phenotypic subgroups within this population. This study aimed to characterize distinct clinical phenotypes among critically ill patients with COVID-19 and acute respiratory failure. Methods: This multicenter prospective substudy of the SEVARVIR cohort included adult patients from 39 French ICUs between December 2021 and October 2024 with acute Etienne Audureau and Pierre Bay have contributed equally as first authors.clusters 5 and 7 had the highest requirements for organ support, with frequent use of invasive mechanical ventilation, vasopressors (cluster 6), and renal replacement therapy (cluster 7). Dexamethasone and tocilizumab were most commonly prescribed in cluster 4 (91.3% and 30.2%, respectively). Mortality at day 28 varied significantly across clusters, ranging from 13.1% in cluster 3 to 41.1% in cluster 6.
Conclusions:This clustering analysis highlights, for the first time, the clinical heterogeneity of critically ill patients infected with Omicron, identifying seven distinct clusters with varying clinical presentations, management strategies and outcomes. These findings underscore the relevance of a phenotype-driven approach to support personalized treatment strategies and guide future clinical trials. Trial Registration: Clinicaltrials.gov, NCT05162508.
respiratory failure and infected with the Omicron variant. Clustering analysis was conducted using Kohonen's self-organizing maps (SOMs) and validated with ClinTrajan, two unsupervised clustering methods, to identify homogeneous patient phenotypes. Results: During the study period, 777 patients with Omicron infection were included, and 7 distinct clinical clusters were identified. Clusters 1 and 2 included patients with metabolic and cardiovascular comorbidities. Cluster 3 featured younger, mildly ill patients with isolated chronic respiratory failure, while cluster 4 comprised older male patients with isolated respiratory failure. Cluster 5 included patients with isolated hematologic malignancies, cluster 6 patients with multiorgan failure, and cluster 7 organ transplant recipients, with high severity scores and impaired renal function. ICU management varied substantially across clusters. Patients in Clinical presentations of critically ill patients with COVID-19 have evolved substantially in the Omicron era. These patients present with a greater burden of comorbidities, including a higher prevalence of immunosuppression.
There are very limited data describing the clinical heterogeneity of critically ill patients infected with Omicron.
Most therapeutic evidence originates from earlier waves of the pandemic and may not be fully applicable to the population in the Omicron era.
This nationwide prospective study, including 777 critically ill patients infected with Omicron across 39 French intensive care units (ICU), aimed to explore phenotypic heterogeneity using unsupervised clustering analysis.
## What was learned from the study?
Seven distinct clinical phenotypes were identified, each characterized by markedly different demographic, comorbidity, and severity profiles.
Therapeutic management varied substantially between clusters, particularly regarding the use of dexamethasone, tocilizumab, and organ support strategies.
Clinical outcomes differed significantly, with 28-day mortality ranging from 13.1% to 41.1%.
These results support a phenotype-driven approach for personalized care and future trial design.
## INTRODUCTION
Although the period of overwhelming intensive care unit (ICU) admissions due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia appears to be over, coronavirus disease 2019 (COVID-19) remains a common reason for ICU admission, particularly among vulnerable patients with increasingly heterogeneous clinical profiles [1]. The course of successive epidemic waves, the emergence of new variants, and the development of natural and vaccine-induced immunity have profoundly changed the pandemic landscape [2].
The early waves of the COVID-19 pandemic were marked by a relatively uniform clinical presentation among patients in ICUs. The majority of these were male, with a median age of around 60 years, presenting with moderate cardiovascular comorbidities, including hypertension, diabetes, or obesity [3]. However, the emergence of the Omicron variant, which has been the dominant lineage since 2022, has led to significant changes in the clinical profile of critically ill patients. These individuals tend to be older, with a greater burden of comorbidities, including a higher prevalence of immunosuppression [4].
The clinical presentation of critically ill patients infected with Omicron has become increasingly heterogeneous, with evolving sublineages, the acquisition of vaccine-and infection-induced immunity, and novel therapeutic strategies. As with other respiratory viruses, severe SARS-CoV-2 infection is no longer merely a viral pneumonia, but can also precipitate an exacerbation of preexisting comorbidities such as chronic heart failure (CHF) or chronic obstructive pulmonary disease (COPD) [5,6]. Immunocompromised patients may experience prolonged respiratory symptoms that persist for several weeks due to impaired viral clearance [7]. In addition, accurately assessing the true impact of SARS-CoV-2 in some critically ill patients remains challenging, particularly in cases of multiorgan failure where the virus is detected but its exact contribution to the patient's clinical condition is unclear.
Notwithstanding these changes, pharmacological management remains principally based on immunomodulatory therapies (e.g., corticosteroids, anti-IL-6 receptor, baricitinib) that have been evaluated in the pre-Omicron era patient population [8]. A number of studies have sought to delineate subgroups of patients with homogeneous clinical phenotypes by employing a wide spectrum of methodologies [9][10][11][12]. However, the majority of these studies were conducted prior to the emergence of the Omicron variant, thereby missing the full spectrum of clinical heterogeneity currently observed among critically ill patients with COVID-19 infected with Omicron.
The objective of this study is to investigate the phenotypic heterogeneity of patients with acute hypoxemic respiratory failure due to SARS-CoV-2 infection requiring ICU admission by identifying homogeneous clinical phenotypes in the Omicron era.
## METHODS
## Patients and Clinical Data
This is a substudy of the prospective, multicenter observational SEVARVIR cohort study [4][5][6]13]. Patients admitted to one of the 39 participating ICUs (including 18 from the Greater Paris area, see Table S1 for the list of participating centers) between 7 December 2021 and 10 October 2024 were eligible for inclusion in the SEVARVIR cohort study (NCT05162508) if they met the following inclusion criteria: age ≥ 18 years, SARS-CoV-2 infection confirmed by a positive reverse transcriptase-polymerase chain reaction (RT-PCR) in nasopharyngeal swab samples, admission to the ICU for acute respiratory failure (i.e., peripheral oxygen saturation (SpO 2 ) ≤ 90% and need for supplemental oxygen or any kind of ventilator support), patient or next of kin informed of study inclusion. Patients with SARS-CoV-2 infection but no acute respiratory failure, or whose nasopharyngeal swabs had an RT-PCR cycle threshold (Ct) value > 32, were not included. For this substudy focused on the Omicron variant, we included patients who had been confirmed to have the Omicron variant or who were admitted after 1 May 2022, since only the Omicron variant was circulating in France after that date [4,14].
Demographic, clinical, and laboratory variables were recorded upon ICU admission and during their stay in the ICU. Patients' frailty was assessed using the Clinical Frailty Scale [15]. The disease severity at ICU admission was evaluated using the World Health Organization (WHO) ten-point ordinal scale [16], the sequential organ failure assessment (SOFA) score [17], and the simplified acute physiology score (SAPS) II score [18]. Acute respiratory distress syndrome (ARDS) was defined in accordance with the Berlin definition [19]. Table S2 lists variables with ≥ 10% missing data. The use of corticosteroids and tocilizumab was recorded on the basis of whether these treatments were administered at any point during the patient's stay in the ICU. Whether to initiate dexamethasone, other steroids, or anti-IL-6 agents was at the discretion of the attending physician and was thus not standardized.
## Ethical Approval
The study was approved by the Comité de Protection des Personnes Sud-Méditerranée I (N° EudraCT/ ID-RCB: 2021-A02914-37). Informed consent was obtained from all patients or their relatives. The study was conducted in accordance with the 1964 Declaration of Helsinki and subsequent amendments.
## SARS-CoV-2 Variant Determination
The full-length SARS-CoV-2 genomes of all the patients included in the study were sequenced using next-generation sequencing. In brief, viral RNA was extracted from nasopharyngeal swabs in viral transport medium using NucliSENS® easyMAG kit on EMAG device (bioMérieux, Marcy-l'Étoile, France). Sequencing was performed using Illumina® COVIDSeq Test (Illumina, San Diego, California), which employs 98-target multiplex amplifications across the entire SARS-CoV-2 genome. The libraries were then sequenced with NextSeq 500/550 High Output Kit v2.5 (75 Cycles) on a NextSeq 500 device (Illumina). The sequences were demultiplexed and assembled into full-length genomes using the DRAGEN COVIDSeq Test Pipeline on a local DRAGEN server (Illumina). Lineages and clades were interpreted using Pangolin and NextClade, before submission to the GISAID international database (https:// www. gisaid. org).
## Statistical Analyses
Descriptive results are presented as means (± standard deviation [SD]) or medians (first-third quartiles) for continuous variables, and as numbers with percentages for categorical variables.
An unsupervised clustering analysis was conducted to explore the heterogeneity of the population by identifying typical profiles with contrasting characteristics. The following clinical or biological variables considered as relevant for this analysis were demographics (age, sex), comorbidities (CHF, hypertension, obesity, chronic respiratory failure, chronic renal failure, immunosuppression), severity, and biological features upon ICU admission (time from first symptoms to ICU admission, SAPS II score, SOFA score, PaO 2 /FiO 2 ratio, arterial lactate levels, blood leukocytes, lymphocytes and platelets count, serum urea level, and serum creatinine level).
The main clustering analysis was conducted using the Kohonen's self-organized map (SOM) methodology [20], which enabled us to build two-dimensional maps from multidimensional datasets. In a nutshell, the SOM algorithm divided each map into districts in which patients are located on the basis of their characteristics. Patients with similar features are located close to each other on the maps, while patients with distinct profiles are located farther apart. This allows us to identify key differences Table 1 continued Manual adjustments were then applied to refine the delimitation of clusters, and the final number of clusters was guided by clinical expertise.
To evaluate the robustness of the SOM analysis findings, a sensitivity analysis was performed using the ClinTrajan method [24], which reduces multidimensional phenotypic data to a twodimensional space following a tree-like structure. This method uses the elastic principal tree (EPT) algorithm, a nonlinear generalization of principal component analysis (PCA), to model the complex geometry of clinical data as an array of diverging trajectories [25,26]. The EPT constructs a principal tree, which is defined as a set of interconnected principal curves arranged in a tree-like topology. Branching points represent key divergences in clinical states. Clusters are identified as unbranched segments of the tree that group together patients with similar clinical patterns. This approach improves interpretability because individuals with the most distinct or characteristic profiles tend to be located at the 0.004 extremities of the branches, while those with more typical or milder profiles tend to be found near the root. Cluster solutions obtained from the SOM and ClinTrajan analyses were compared using a Sankey plot created with the alluvial and easyalluvial R packages. Global unadjusted comparisons according to the cluster status were performed using chi-squared or Fisher's exact tests for categorical variables, and analysis of variance (ANOVA) or Kruskal-Wallis tests for continuous variables, as appropriate. The aim of conducting statistical comparisons between clusters was not to formally test hypotheses, but rather to emphasize the key clinical and biological features that distinguish the phenotypes identified by unsupervised clustering. Survival analyses were performed to assess the prognostic significance of the various subgroups identified with respect to overall survival. The Kaplan-Meier method was used to plot survival curves, and log-rank tests were used to assess significance for group comparison.
To minimize the impact of potential selection bias arising from complete-case analyses, all clustering analyses were performed after missing data imputation using the missForest algorithm, a nonparametric method based on random forest imputation that can handle nonlinearities and interactions [27], as implemented in the R package missRanger [28]. Descriptive analyses and graphs were performed using GraphPad Prism, version 8 (GraphPad Software), R 4.2.0 (R Foundation for Statistical Computing, Vienna, Austria) for imputing missing data, performing comparative and survival analyses, and conducting clustering analyses using the SOM approach. Clustering analyses were also performed using the ClinTrajan algorithm in Python 3.12.7.
## RESULTS
## Population
During the study period, a total of 931 patients were admitted to one of the 39 participating ICUs and included in the study, of whom 777 were infected with the Omicron variant (Fig. 1). Within the overall cohort, 274 patients (35.3%) were female, with a median age of 69.1 years (59.9; 75.4). The most prevalent comorbidities were hypertension, immunosuppression status, diabetes, and obesity. During their ICU stay, 282 patients (38.5%) were treated with invasive mechanical ventilation, 564 (77.6%) received dexamethasone, and 147 (20.1%) received tocilizumab for COVID-19. The day 28 mortality rate was 26.8% (N = 193/777).
## Clustering Analysis
As shown in Fig. 2, the SOM method was employed to conduct a clustering analysis, displaying polarized distributions of patient characteristics across the maps. This analysis yielded seven clusters of patients with homogeneous phenotypes. The delineation of cluster boundaries is illustrated in Fig. 2. The characteristics of patients at the time of ICU admission are presented in Table 1 and shown in Fig. 3A. The Omicron sublineage infecting each patient, according to their cluster assignment, is shown in Fig. S1. The management of patients with severe SARS-CoV-2 infection during their ICU stay is presented in Table 2 and shown in Fig. 3B,C. The patient-imputed characteristics at ICU admission and the management during the ICU stay are provided in Table S3 and Table S4, respectively.
## Cluster 1 (N = 78/777,10%)
This cluster includes elderly patients with a median age of 72.5 years (66.5; 76.8) and is characterized by a pronounced metabolic and cardiovascular comorbidity profile, including a high prevalence of chronic heart failure, diabetes, and obesity. These patients also exhibited the highest median frailty score and were frequently treated with noninvasive ventilation (NIV) or high-flow oxygen (HFO) therapy.
## Cluster 2 (N = 78, 10%)
The patient population in this cluster is predominantly female (78.2%), and it is characterized by a marked metabolic profile, including a high prevalence of diabetes and obesity, but no chronic heart failure. It is noteworthy that this cluster had the highest use of NIV as initial ventilatory support at ICU admission.
## Cluster 3 (N = 160, 21%)
Cluster 3 comprises the youngest individuals (median age of 59.9 years (50.0; 69.4)) and is primarily characterized by isolated chronic respiratory failure. Patients in this cluster exhibited the lowest vaccination rate and the lowest severity scores (SAPS II and SOFA). Furthermore, these subjects exhibited the highest median PaO 2 / FiO 2 ratio (159 mmHg (102; 251)) and mainly received NIV or HFO therapy.
## Cluster 4 (N = 132, 17%)
This cluster is almost exclusively male and includes the oldest patients, with a median age of 74.2 years (67.3; 79.7). The patients in question had a low number of comorbidities and a low vaccination rate. They predominantly presented with isolated acute hypoxemic respiratory failure, characterized by the lowest PaO 2 / FiO 2 ratio (91 mmHg (69; 138)), with HFO therapy as the predominant mode of ventilatory support. The requirement for vasopressor support was minimal.
## Cluster 5 (N = 95, 12%)
This cluster exhibited the highest proportion of immunocompromised patients (82.2%), primarily due to oncohematological malignancies. Immunosuppression was the only comorbidity. HFO therapy was the most frequently used mode of ventilatory support.
## Cluster 6 (N = 129, 13%)
Patients in this cluster had relatively few comorbidities but presented with the highest severity of illness at admission, as reflected by Fig. 4 Day 28 mortality according to clusters. A Day 28 mortality; B survival curves for day 28 overall survival are plotted by clusters using the Kaplan-Meier method. Num-bers of patients at risk and number of events are presented in the risk table below the graph the highest SAPS II and SOFA scores, elevated lactate levels, and the lowest platelet counts. A majority of patients required both invasive mechanical ventilation (55.3%) and vasopressor support (65.6%) at the time of ICU admission. Notably, this group also exhibited the highest rate of bacterial co-infection (32.6%).
## Cluster 7 (N = 134, 17%)
This cluster also included a high proportion of immunocompromised patients (71%), predominantly comprising solid organ transplant recipients, with a marked prevalence of chronic renal failure. Furthermore, this group had the highest vaccination rate and presented with severe illness, as reflected by elevated SAPS II and SOFA scores. Notably, these patients presented with pronounced lymphopenia and significant renal impairment at ICU admission.
## Sensitivity Analysis
Complementary clustering analysis was performed using the Clinical Trajectory Analysis (ClinTrajan) method, which also identified seven distinct patient clusters with homogeneous phenotypes. The distribution of patients within these clusters is illustrated by the branching tree structure in Fig. S2. The characteristics of patients at ICU admission and the management during the ICU stay are presented in Table S5 and Table S6. Figure S3 shows the results of the 28-day survival analysis grouped by the clusters obtained from the ClinTrajan method. The correspondence between patient classifications from both clustering methods is shown in Fig. S4 as a Sankey diagram, illustrating the overlap and transitions between clusters. Overall, the two clustering approaches exhibited a satisfactory degree of consistency and alignment.
## Management of Patients During Their Stay in the Intensive Care Unit
There were significant variations in the management of organ failure between clusters. Clusters 6 and 7 had the highest proportions of patients treated with IMV (62.8% and 44.3%, respectively). Furthermore, patients in cluster 6 were the most likely to require vasopressor support (66.7%). Conversely, patients in cluster 7 demonstrated the highest propensity for renal replacement therapy (37.4%). The pharmacological management of COVID-19 also differed between the identified clusters. The highest rate of dexamethasone administration (91.3%) was observed in patients in cluster 4, while the lowest rate (64.4%) was observed in patients in cluster 3. There were no substantial disparities in the use of alternative systemic corticosteroids between groups (p = 0.08). Tocilizumab was most commonly prescribed in cluster 4 (30.2%) and least commonly prescribed in cluster 6 (7.5%).
## Outcome of Patients
Figure 4 shows the results of the 28-day survival analysis grouped by the clusters obtained from the SOMs. There was a significant difference in survival between clusters (p < 0.001), with the best outcomes observed among patients in clusters 2 and 3, and the worst among those in clusters 6 and 7. Patients in clusters 1, 4, and 5 exhibited intermediate outcomes.
## DISCUSSION
To the best of our knowledge, this is the largest cohort study to use clustering analysis to identify homogeneous subgroups of critically ill patients with COVID-19 infected with the Omicron variant. Seven distinct clusters were identified, each characterized by contrasting clinical presentations, management strategies during the ICU stay, and outcomes. The main characteristics of the patients in each cluster are summarized below. Clusters 1 and 2 comprise patients with metabolic and/or cardiovascular comorbidities. Cluster 1 comprises older patients with chronic heart failure and high frailty, who are primarily treated with HFO/NIV therapy. Cluster 2 comprises predominantly female patients with obesity and no chronic heart failure who require the highest use of NIV at ICU admission. Cluster 3 comprises the youngest patients, with isolated chronic respiratory failure, low severity scores, limited corticosteroid use, and a favorable prognosis. Cluster 4 includes older male patients with isolated respiratory failure. Cluster 6 comprises patients with multiorgan failure and poor outcomes, and a low prevalence of preexisting comorbidities. Clusters 5 and 7 encompass patients for whom immunosuppression is a major feature. Notably, the distribution of Omicron sublineages did not differ across the identified clusters. This finding suggests that the observed clinical heterogeneity was primarily driven by patient-specific characteristics rather than virological factors. Given the exploratory nature of our analysis, we described this heterogeneity using unadjusted comparisons between clusters. As detailed in the Methods section, we did not apply corrections for multiple testing when comparing characteristics across clusters, consistent with the exploratory purpose of our clustering analysis. Consequently, the reported p-values should not be interpreted as confirmatory evidence of effects. Rather, they serve only as indicators of which features differ across clusters and help to characterize the clusters descriptively.
The phenotypic approach is becoming increasingly popular for identifying homogeneous subgroups of patients within heterogeneous populations. This strategy has been shown to be effective in a variety of clinical settings. It enables more accurate diagnoses and the early identification of patients at risk of deterioration who could benefit from tailored interventions [29][30][31]. In the ICU setting, this approach aligns with the broader movement toward precision medicine, which has become essential to improving patient care [32]. Several studies have previously attempted to identify phenotypic subgroups among critically ill patients with COVID-19 using various clustering methods. These efforts have consistently demonstrated considerable heterogeneity in disease presentation and outcomes, as was recently summarized in a narrative review [33]. These studies incorporated clinical and biological variables [9][10][11][12], and, in certain instances, immunoinflammatory biomarkers, including transcriptomic signatures [34]. The consistent presence of homogeneous phenotypes with significant variations in clinical, biological, and immunoinflammatory characteristics was emphasized. Notably, these phenotypes were associated with distinct outcomes, and in certain studies, varied responses to corticosteroid therapy [9]. However, all previous clustering studies were conducted on hospitalized patients during the initial waves of the pandemic, primarily the first wave. Consequently, these studies included patients infected with the ancestral SARS-CoV-2 strain. The clinical presentation of these patients therefore differs significantly from that of patients with COVID-19 currently requiring ICU admission [4,35,36]. The disease landscape has evolved significantly due to widespread community immunity, whether induced by vaccination or acquired through natural infection, as well as due to the emergence of the Omicron variant and its sublineages. Compared with patients with COVID-19 admitted to the ICU during the early waves of the pandemic, critically ill patients infected with Omicron are typically older and have a higher prevalence of comorbidities, particularly immunosuppression and cardiovascular disease [4,36]. Their management has also evolved over time, with an increased use of noninvasive respiratory support (e.g., NIV, HFO therapy) and changes in pharmacological strategies, including more selective use of corticosteroids [4], decreased prescription of tocilizumab, and withdrawal of monoclonal antibodies due to viral resistance associated with Omicron mutations [37]. In the Omicron era, COVID-19 can no longer be considered a homogeneous disease characterized solely by severe viral pneumonia, as was initially described. Instead, the disease spectrum encompasses a wide range of clinical presentations, from acute decompensation of preexisting cardiorespiratory conditions in elderly patients with multiple comorbidities to prolonged viral pneumonia in profoundly immunocompromised individuals. [4][5][6][7]. The phenotypic subgroups identified in our cohort demonstrate this clinical heterogeneity and are representative of the contemporary ICU population with Omicron infection.
In our study, the therapeutic management of critically ill patients with COVID-19-including both pharmacological treatments and organ support-varied significantly between clusters. Notably, there was significant heterogeneity in the use of dexamethasone, despite it being theoretically indicated for all patients included in the study [8]. While dexamethasone was administered to almost all patients in cluster 4 (91.3%), it was only prescribed to 64.4% of patients in cluster 3. Although the benefits of corticosteroids were clearly demonstrated in the first wave for severe cases of COVID-19 [38,39], their efficacy for older patients with more comorbidities-particularly cardiovascular disease and immunosuppression-and less severe respiratory involvement remains uncertain. Previous studies have suggested that the efficacy of corticosteroids may depend on the clinical profile of the patient, with the greatest benefit seen in those exhibiting a stronger inflammatory response [9,12]. However, the lack of robust evidence supporting an individualized approach to dexamethasone use in critically ill patients, particularly in the Omicron era, has probably contributed to significant variability in its prescription. Although dexamethasone remains the cornerstone of corticosteroid therapy for treating patients with severe COVID-19 [8,38], there is evidence to suggest that alternatives such as hydrocortisone [40] or methylprednisolone [41] could also be beneficial. Clinicians may therefore have tailored their choice of corticosteroid to the patient's condition-for instance, hydrocortisone may have been favored for treating severe circulatory failure, while prednisone or methylprednisolone would have been preferred for patients with obstructive airway disease. Similarly, tocilizumab prescriptions varied significantly between clusters. Evidence on interleukin (IL)-6 receptor antagonists has enabled a more targeted approach, with the greatest benefits observed in patients with significant systemic inflammation (CRP ≥ 75 mg/L) [8,42]. However, concerns about infectious complications, particularly COVID-19-associated pulmonary aspergillosis [43,44], have led to a more cautious use of tocilizumab, as observed in our study in intubated patients with multiorgan failure (cluster 6). Finally, we observed significant variability in the management of organ failure, which is likely due to differences in the initial presentation of patients, their underlying comorbidities, and disease severity. Patients with a cardiometabolic profile (clusters 1 and 2) and those with chronic respiratory failure (cluster 3) were particularly likely to receive NIV support. Conversely, patients in cluster 7, including solid organ transplant recipients and those with chronic renal failure, were more likely to receive renal replacement therapy during their ICU stay. This variability in management highlights the urgent need for clinical trials that stratify patients on the basis of their phenotype. Such trials would validate personalized disease management in real-world clinical settings and refine treatment strategies tailored to specific patient subgroups. In addition, the ongoing evaluation of novel therapeutic options, such as immunomodulators and antivirals, will expand the range of tools available for the precision-based management of severe viral respiratory infections [45].
The day 28 mortality rate observed in our cohort (26.7%) is consistent with that reported in other similar studies of critically ill patients infected with the Omicron variant [4,46]. In addition to the previously discussed differences, patients in different clusters exhibited significantly divergent outcomes, with day 28 mortality rates ranging from 13.1% in cluster 3 to 41.1% in cluster 6. These differences are largely explained by the underlying comorbidities and patient severity at the time of ICU admission. Nevertheless, these findings will help clinicians to make more accurate prognoses for each clinical profile, enabling them to manage and tailor therapeutic strategies more precisely on the basis of each patient's severity and specific characteristics.
Our study has several limitations. This prospective study was conducted only in France, which may limit the generalizability of the findings to other regions. To validate the identified clusters, an external large prospective cohort would be needed. In addition, the statistical comparisons between clusters should be interpreted with caution, as these analyses were exploratory and performed to help describe and distinguish the phenotypes generated by the unsupervised clustering process. Furthermore, we did not include data on immune and inflammatory parameters across the different clusters, which could provide additional insight into the underlying pathophysiology. In addition, patients without acute respiratory failure were excluded, which may limit our ability to explore the full range of clinical presentations of SARS-CoV-2 infection in the ICU. Nevertheless, the study also presents important strengths. It involved a unique, large-scale, prospective, multicenter cohort of critically ill patients infected with Omicron enabling robust characterization of clinical phenotypes. The clusters were validated using two independent methods and the use of these clustering analyses allowed to derive homogeneous and clinically meaningful phenotypes from a highly heterogeneous critically ill population. Together, these findings offer novel insights into the evolving landscape of critical illness in the Omicron era.
## CONCLUSIONS
We conducted a clustering analysis on a large database of patients infected with Omicron variant requiring ICU admission for acute respiratory failure. The patients had different demographics, comorbidities, therapeutic management strategies, and outcomes. We identified seven distinct clinical presentations. Our findings help to improve our understanding of the current heterogeneity of COVID- Data Availability. The clinical datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request (N.D.P.). Ethical Approval. The study was approved by the Comité de Protection des Personnes Sud-Méditerranée I (no. EudraCT/ID-RCB: 2021-A02914-37). Informed consent was obtained from all patients or their relatives. The study was conducted in accordance with the 1964 Declaration of Helsinki and subsequent amendments.
## Declarations
Open Access. This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by-nc/4. 0/.
## References
1. Markov, Ghafari, Beer et al. (2023) "The evolution of SARS-CoV-2" *Nat Rev Microbiol*
2. Carabelli, Peacock, Thorne et al. (2023) "SARS-CoV-2 variant biology: immune escape, transmission and fitness" *Nat Rev Microbiol*
3. Covid-Icu (2021) "Group on behalf of the REVA Network and the COVID-ICU Investigators. Clinical characteristics and day-90 outcomes of 4244 critically ill adults with COVID-19: a prospective cohort study" *Intensive Care Med*
4. De Prost, Audureau, Heming et al. (2022) "Clinical phenotypes and outcomes associated with SARS-CoV-2 variant Omicron in critically ill French patients with COVID-19" *Nat Commun*
5. De Prost, Audureau, Préau et al. (2023) "Clinical phenotypes and outcomes associated with SARS-CoV-2 Omicron variants BA.2, BA.5 and BQ.1.1 in critically ill patients with COVID-19: a prospective, multicenter cohort study" *Intensive Care Med Exp*
6. De Prost, Audureau, Guillon et al. (2022) "Clinical phenotypes and outcomes associated with SARS-CoV-2 Omicron sublineage JN.1 in critically ill COVID-19 patients: a prospective, multicenter cohort study in France" *Ann Intensive Care*
7. Machkovech, Hahn, Wang et al. (2024) "Persistent SARS-CoV-2 infection: significance and implications" *Lancet Infect Dis*
8. "IDSA Guidelines on the Treatment and Management of Patients with COVID-19"
9. Bruse, Motos, Van Amstel et al. (2024) "Clinical phenotyping uncovers heterogeneous associations between corticosteroid treatment and survival in critically ill COVID-19 patients" *Intensive Care Med*
10. Legrand, Phillips, Malenica et al. (2021) "Differences in clinical deterioration among three sub-phenotypes of COVID-19 patients at the time of first positive test: results from a clustering analysis" *Intensive Care Med*
11. Gutiérrez-Gutiérrez, Toro, Borobia et al. (2021) "Identification and validation of clinical phenotypes with prognostic implications in patients admitted to hospital with COVID-19: a multicentre cohort study" *Lancet Infect Dis*
12. Sinha, Furfaro, Cummings et al. (2021) "Latent class analysis reveals COVID-19-related acute respiratory distress syndrome subgroups with differential responses to corticosteroids" *Am J Respir Crit Care Med*
13. Bay, Audureau, Préau et al. (2024) "COVID-19 associated pulmonary aspergillosis in critically-ill patients: a prospective multicenter study in the era of Delta and Omicron variants" *Ann Intensive Care*
14. (2025) "Coronavirus : chiffres clés et évolution de la COVID-19 en France et dans le Monde"
15. Rockwood, Song, Macknight et al. (2005) "A global clinical measure of fitness and frailty in elderly people" *CMAJ*
16. (2020) "WHO Working Group on the Clinical Characterisation and Management of COVID-19 infection. A minimal common outcome measure set for COVID-19 clinical research" *Lancet Infect Dis*
17. Vincent, Moreno, Takala et al. (1996) "The SOFA (Sepsisrelated Organ Failure Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine" *Intensive Care Med*
18. Gall, Lemeshow, Saulnier (1993) "A new Simplified Acute Physiology Score (SAPS II) based on a European/North American multicenter study" *JAMA*
19. Ranieri, Rubenfeld, Thompson (2012) "Ferguson ND, Caldwell E, ARDS Definition Task Force, et al. Acute respiratory distress syndrome: the Berlin Definition" *JAMA*
20. Kohonen, Somervuo (2002) "How to make large selforganizing maps for nonvectorial data" *Neural Netw*
21. Gao, Mutter, Casey et al. (2019) "Numero: a statistical framework to define multivariable subgroups in complex population-based datasets" *Int J Epidemiol*
22. Van De Velden, Iodice, Enza (2019) "Distance-based clustering of mixed data" *WIREs Comput Stat*
23. Chavent, Kuentz-Simonet, Labenne et al. (2023) "Multivariate Analysis of Mixed Data: The R Package PCAmixdata"
24. Golovenkin, Bac, Chervov et al. (2020) "Trajectories, bifurcations, and pseudo-time in large clinical datasets: applications to myocardial infarction and diabetes data" *GigaScience*
25. Gorban, Sumner, Zinovyev (2007) "Topological grammars for data approximation" *Appl Math Lett*
26. Gorban, Zinovyev, Gorban et al. (2025) "Principal Graphs and Manifolds"
27. Stekhoven, Bühlmann (2012) "MissForest-Non-parametric missing value imputation for mixed-type data" *Bioinformatics*
28. Mayer, Missranger (2024) "Fast Imputation of Missing Values"
29. Seymour, Kennedy, Wang et al. (2019) "Derivation, validation, and potential treatment implications of novel clinical phenotypes for sepsis" *JAMA*
30. Bonnefous, Kharoubi, Bézard et al. (2021) "Assessing cardiac amyloidosis subtypes by unsupervised phenotype clustering analysis" *J Am Coll Cardiol*
31. Famous, Delucchi, Ware et al. (2017) "Acute respiratory distress syndrome subphenotypes respond differently to randomized fluid management strategy" *Am J Respir Crit Care Med*
32. Murugan (2015) "Movement towards personalised medicine in the ICU" *Lancet Respir Med*
33. Scherger, Gomez, Abbas et al. (2009) "Decoding COVID-19: phenotypes and the pursuit of precision medicine" *Clin Microbiol Infect*
34. López-Martínez, Martín-Vicente, De et al. (2023) "Transcriptomic clustering of critically ill COVID-19 patients" *Eur Respir J*
35. Vieillard-Baron, Flicoteaux, Salmona et al. (2022) "Omicron variant in the critical care units of Paris Metropolitan Area the reality research group" *Am J Respir Crit Care Med*
36. Corriero, Ribezzi, Mele et al. (2022) "COVID-19 variants in critically ill patients: a comparison of the Delta and Omicron variant profiles" *Infect Dis Rep*
37. Arora, Kempf, Nehlmeier et al. (2023) "Omicron sublineage BQ.1.1 resistance to monoclonal antibodies" *Lancet Infect Dis*
38. Horby, Lim, Emberson et al. "Dexamethasone in hospitalized patients with Covid-19"
39. (2021) *N Engl J Med*
40. (2020) "The WHO Rapid Evidence Appraisal for COVID-19 Therapies (REACT) Working group. association between administration of systemic corticosteroids and mortality among critically ill patients with COVID-19: a meta-analysis" *JAMA*
41. Angus, Derde, Al-Beidh et al. (2020) "Effect of hydrocortisone on mortality and organ support in patients with severe COVID-19: the REMAP-CAP COVID-19 corticosteroid domain randomized clinical trial" *JAMA*
42. Salton, Confalonieri, Meduri et al. (2020) "Prolonged low-dose methylprednisolone in patients with severe COVID-19 pneumonia" *Open Forum Infect Dis*
43. Abani, Abbas, Abbas et al. (2021) "Tocilizumab in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial" *Lancet*
44. Gangneux, Dannaoui, Fekkar et al. "Fungal infections in mechanically ventilated patients with COVID-19 during the first wave: the French multicentre MYCOVID study" *Lancet Respir Med*
45. Gioia, Walti, Orchanian-Cheff et al. (2024) "Risk factors for COVID-19-associated pulmonary aspergillosis: a systematic review and meta-analysis" *Lancet Respir Med*
46. Watkins (2022) "Using precision medicine for the diagnosis and treatment of viral pneumonia" *Adv Ther*
47. Chang, Huang, Shen et al. (2024) "Characteristics and outcomes of ICUadmitted COVID-19 patients in the Omicron and Alpha-dominated periods" *J Formos Med Assoc*
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# Isolation and complete genome sequence analysis of an Echovirus 29 strain isolated from a patient of Acute Flaccid Paralysis in India
Madhuri Joshi, Rishabh Waghchaure, Pooja Umare, Abhijeet Jadhav, Alfia Ashraf, Sarah Cherian, Naveen Kumar, Babasaheb Tandale, Mallika Lavania, John Dennehy
## Abstract
Echovirus 29 (E29) was identified in a fecal specimen of a 15-month-old girl with acute flaccid paralysis from Akola city, Maharashtra, India. The complete genome sequence of the E29 strain, isolated using rhabdomyosarcoma cells, is being reported from India. KEYWORDS enterovirus, echovirus, outbreak, acute flaccid paralysis, India, genome analysis E chovirus 29 (E29), a non-enveloped RNA virus of family Picornaviridae, is associated with illnesses ranging from asymptomatic infection to meningitis, encephalitis, acute flaccid paralysis, and respiratory disease (1). E29 has been previously detected in India during polio surveillance and is considered relevant to paralysis (2, 3). During the post-GBS outbreak investigation in Bhavanipura (Akola, Maharashtra), E29 was detected in an AFP patient's fecal sample by qPCR and VP1 sequencing, and subsequently isolated in RD cells following WHO protocols (4). RD cells were cultured in MEM with 10% FBS and antibiotics; infected cultures showing CPE were harvested and passaged to P8. Wholegenome sequencing of the P4_E29 isolate was conducted on the Illumina MiniSeq platform (5). Viral RNA was extracted from culture supernatant using the QIAamp Viral RNA Mini Kit. After quantification, host rRNA was removed with the NEBNext depletion kit, and the RNA was purified and measured using Qubit. Libraries were prepared with the TruSeq Stranded mRNA kit (Illumina, USA) and assessed using Tapestation. Sequenc ing was performed on the Illumina MiniSeq (High Output Kit), and FASTQ files were analyzed with CLC Genomics Workbench v20. Raw paired-end whole-genome Illumina reads were assembled de novo using SPAdes genome assembler v3.15.5 (6) with default parameters, producing a single genome contig of 7,413 bp with 47.88% GC content. Genotyping using the Enterovirus Genotyping Tool identified the Indian isolate as E29.Although the assembled genome length (7,413 nt) matched the reference sequence, the exact 5′ and 3′ ends could not be confirmed without RACE, so it is reported as a near-complete genome. Genome annotation was performed using VAPiD (v1.6.7) with default settings and submitted to GenBank via BankIt. Sequence similarity analysis of the consensus genome using BLASTn (NCBI) revealed 99% query coverage and 86.76% nucleotide identity to Enterovirus B (E29) strain from Nepal (GenBank accession number PX230757). A maximum likelihood phylogenetic tree was generated from complete E29 genomes, aligned with MAFFT and analyzed in IQ-TREE using the BIC-selected substitution model with 1,000 ultrafast bootstraps, then visualized in iTOL.
. It showed 79% nucleotide and 96% amino acid identity with the USA 1958 prototype, indicating marked nucleotide divergence but conserved proteins. Compared with genomes from Guatemala, Haiti, Nepal, and Brazil (2014), it showed 78-82% nucleotide similarity, while sharing only ~30-32% identity with two highly divergent Brazilian strains (2014-2015) that formed a separate lineage.
A comprehensive mutation analysis at the amino acid level performed using nine whole-genome sequences available in the GenBank showed presence of 20 unique non-synonymous substitutions in the P4_E29 strain of the study. Among the 20 amino acid substitutions, 11 were in structural proteins (Table 1). The nucleotide sequence of FIG 1 Maximum likelihood phylogenetic tree based on complete genome sequences of the E29 strain and reference sequences retrieved from the GenBank database (accession ID: prototype USA 1958 strain, AY302552.1). The sequences were aligned using MAFFT v7.5266 with default parameters. The phylogenetic tree was constructed using IQ-TREE v2.2.0 under the maximum likelihood method, with the best-fit substitution model automatically selected according to the Bayesian information criterion (BIC). Tree robustness was evaluated using 1,000 ultrafast bootstrap replicates. The final tree was visualized and annotated using Interactive Tree of Life (iTOL v6). The E29 isolate from India (NIV2415257/IND/2025) is highlighted in red font color and shows clustering with PP461528.1/Nepal/ 2023 strain (highlighted with light blue font color).
## References
1. Oyero, Adu, Ayukekbong (2014) "Molecular characterization of diverse species enterovirus-B types from children with acute flaccid paralysis and asymptomatic children in Nigeria" *Virus Res*
2. Rao, Yergolkar, Shankarappa (2007) "Antigenic diversity of enteroviruses associated with nonpolio acute flaccid paralysis, India" *Emerg Infect Dis*
3. Maan, Dhole, Chowdhary (2019) "Identification and characteriza tion of nonpolio enterovirus associated with nonpolio-acute flaccid paralysis in polio endemic state of Uttar Pradesh, Northern India" *PLoS One*
4. (2004) "Polio laboratory manual. 4th edition. Department of Immunization, Vaccines and Biologicals Family and Community Health"
5. Tikute, Deshmukh, Chavan et al. (2022) "Emergence of recombinant subclade D3/Y in coxsackievirus A6 strains in hand-foot-and-mouth disease (HFMD) outbreak in India" *Microorganisms*
6. Bushmanova, Antipov, Lapidus et al. (2019) "rnaSPAdes: a de novo transcriptome assembler and its application to RNA-Seq data" *Gigascience*
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# Special Issue "Viral Infections: Physiology, Pathophysiology, Pathogenesis, Diagnosis and Treatment"
Barbara Bażanów, Dominika Stygar
## Abstract
Viral infections remain one of the most significant challenges to global health, affecting humans and animals alike and posing continuous threats due to their high transmissibility, genetic variability, and capacity to disrupt host homeostasis at multiple biological levels [1]. Despite remarkable advances in molecular biology, immunology, and antiviral therapy, viral diseases continue to cause substantial morbidity, mortality, and socioeconomic burden worldwide [2]. The complexity of virus-host interactions, together with the dynamic evolution of viral populations, necessitates integrated research approaches that span from fundamental molecular mechanisms to applied diagnostic and therapeutic strategies [3].This Special Issue, "Viral Infections: Physiology, Pathophysiology, Pathogenesis, Diagnosis and Treatment", was conceived to provide a comprehensive overview of current advances in the field of virology, highlighting how viral infections influence cellular physiology, host defense mechanisms, microbial ecosystems, and population-level dynamics. The contributions collected in this issue reflect the multifaceted nature of viral diseases and emphasize the importance of interdisciplinary research in understanding viral pathogenesis and improving disease management.At the most fundamental level, viral infections initiate a cascade of intracellular events that determine whether the host cell successfully restricts viral replication or becomes permissive to disease progression. These early responses form the basis upon which subsequent host-virus interactions unfold, ultimately shaping disease outcomes at the organismal and population levels.
Cellular Stress Responses and Antiviral Defense MechanismsAt the cellular level, viral infections profoundly alter host metabolic pathways and stress responses, which in turn shape the outcome of infection. One of the key processes implicated in viral pathophysiology is oxidative stress, resulting from an imbalance between reactive oxygen species production and antioxidant defenses [4]. In this Special Issue, Ba żanów et al. (contribution 1) investigated the effects of different respiratory viruses on oxidative stress markers using an in vitro lung cell model. Their findings demonstrate that viral infection induces distinct oxidative stress profiles depending on both the viral agent and the cellular context. Notably, non-enzymatic oxidative stress markers were more prominently affected in lung carcinoma cells, whereas both enzymatic and nonenzymatic parameters were altered in lung fibroblasts. These observations underscore the importance of host cell type in shaping virus-induced oxidative responses and suggest that oxidative stress may contribute differently to viral pathogenesis in normal versus transformed cells.
## Complementing these observations, Ou et al. (contribution 2) explored antiviral defense mechanisms mediated by heme oxygenase-1 (HO-1) during dengue virus infection.
Their study revealed that sofalcone, a clinically used gastroprotective drug, suppresses dengue virus replication by activating the Nrf2/HO-1 pathway and restoring antiviral interferon responses. By linking oxidative stress regulation to innate immune signaling, this work highlights HO-1 as a critical node connecting cellular stress responses with antiviral immunity and identifies a promising candidate for drug repurposing in dengue therapy.
However, cellular antiviral responses do not operate in isolation, as infected cells are embedded within complex biological environments that can profoundly modulate host susceptibility and immune defense.
## Virus-Host Interactions within Biological Ecosystems
Beyond the intracellular level, viral infections unfold within host-associated ecosystems that include diverse microbial communities and their metabolic products. Increasing evidence indicates that the microbiome plays a crucial role in modulating host susceptibility to viral infections, immune responses, and disease severity [5]. This aspect is comprehensively addressed by Hao et al. (contribution 3) in their systematic review and analysis of respiratory microbiomes in influenza compared with other respiratory infections. By synthesizing data from multiple studies, the authors demonstrate that influenza is associated with characteristic patterns of microbiome dysbiosis, including reduced microbial diversity and enrichment of specific bacterial taxa. Importantly, both shared and distinct microbiome signatures were identified across different respiratory infections, age groups, and disease severities, highlighting the bidirectional relationship between viral infection and microbial ecology.
Extending the concept of microbiome-virus interactions to antiviral intervention, Danova et al. (contribution 4) investigated the antiviral properties of Lactobacilli-derived postmetabolites against phylogenetically distant herpesviruses. Their in vitro results show that these postbiotics exert broad-spectrum antiviral effects by interfering with viral adsorption, extracellular virions, and intracellular replication stages. The study provides compelling evidence that microbial metabolites may serve as natural antiviral agents and supports the exploration of postbiotics as adjunctive or alternative strategies in the prevention and treatment of viral infections.
Beyond shaping host responses, these biological environments also influence viral replication dynamics and selective pressures, ultimately contributing to viral diversity and evolution.
## Viral Diversity, Evolution, and Molecular Surveillance
The rapid evolution and genetic diversification of viruses necessitate equally dynamic and sensitive diagnostic tools capable of tracking viral variants across both clinical and population levels. High mutation rates and genomic plasticity present major challenges for disease control, diagnostics, and vaccination strategies, making molecular surveillance an essential component of modern virology. In this Special Issue, Tao et al. (contribution 5) addressed these challenges in the context of porcine reproductive and respiratory syndrome virus by developing a multiplex RT-qPCR assay capable of simultaneous virus identification and lineage typing. The assay demonstrated high sensitivity, specificity, and applicability to large numbers of clinical samples, offering a practical and efficient tool for surveillance and control of PRRSV in the swine industry. This work highlights the importance of advanced molecular diagnostics in managing viral diseases of veterinary significance. At the population level, Costa et al. (contribution 6) explored the dynamics of SARS-CoV-2 mutations using wastewater-based epidemiology. By combining nested PCR with next-generation sequencing of selected spike gene regions, the authors successfully de-tected and quantified variant-associated mutations in wastewater samples. Notably, some mutations corresponding to variants of concern were identified prior to their widespread detection in clinical samples, underscoring the value of environmental surveillance as an early warning system for emerging viral variants.
Accurate detection and surveillance of viral variants not only inform epidemiological control but also provide critical guidance for the development and application of effective antiviral therapies.
## Antiviral Strategies and Therapeutic Targeting
The continuous emergence of drug-resistant viral strains and the limited availability of effective antiviral therapies underscore the urgent need for new antiviral agents with novel mechanisms of action [6]. Several contributions to this Special Issue address this challenge by exploring diverse antiviral strategies that target both viral components and host pathways. Cho and Ma (contribution 7) demonstrated the antiviral activity of conessine, a steroidal alkaloid of plant origin, against influenza A virus. Their results indicate that conessine interferes with early stages of viral infection, including viral attachment and entry, and exhibits a direct virus-eradicating effect. By targeting host-virus interactions rather than viral enzymes alone, conessine represents a promising candidate for the development of alternative anti-influenza therapies. Together with the mechanistic insights provided by Ou et al. on HO-1-mediated antiviral responses, these studies highlight the diversity of therapeutic strategies currently being explored, ranging from natural compounds to host-directed antiviral interventions. As the search for novel antiviral strategies intensifies, the reliability of experimental models and analytical tools becomes increasingly critical to ensure that therapeutic advances are built on robust and reproducible data.
## Methodological Challenges in Virology Research
Robust methodology and critical data interpretation are fundamental to advancing virology research. In this Special Issue, Ripa et al. (contribution 8) address an important methodological concern related to the use of LC3 immunofluorescence as a marker of autophagy in herpes simplex virus type 1-infected cells. Their work demonstrates that polyclonal LC3B antibodies can produce non-specific nuclear staining, potentially leading to misinterpretation of autophagy activation during viral infection. By systematically validating their observations using complementary approaches, the authors underscore the necessity of methodological rigor and cross-validation in experimental virology. This contribution serves as an important reminder that careful evaluation of experimental tools is essential to ensure the reliability and reproducibility of conclusions drawn from virological studies. Together, these considerations highlight that progress in virology depends not only on innovative concepts and technologies, but also on careful validation and critical interpretation of experimental evidence.
## Conclusions and Future Perspectives
The articles collected in this Special Issue provide a multifaceted view of viral infections, spanning cellular stress responses, host-microbiome interactions, viral evolution, diagnostic innovation, therapeutic development, and methodological considerations. These interconnected processes are summarized schematically in Figure 1, which illustrates viral infections as dynamic, multi-layered phenomena extending from intracellular events to population-level surveillance and intervention strategies. Future research in virology will benefit from increasingly integrative approaches that combine basic and translational science, leverage advanced molecular technologies, and emphasize methodological robustness. By bridging physiology, pathophysiology, diagnostics, and treatment, the studies presented in this Special Issue contribute valuable insights that advance our understanding of viral infections and support the development of more effective strategies for their control and management.
## References
1. Ba Żanów, Michalczyk, Kafel et al. (2024) "The Effects of Different Respiratory Viruses on the Oxidative Stress Marker Levels in an In Vitro Model: A Pilot Study" *Int. J. Mol. Sci*
2. Ou, Chen, Yen et al. (2025) "Sofalcone Suppresses Dengue Virus Replication by Activating Heme Oxygenase-1-Mediated Antiviral Interferon Responses" *Int. J. Mol. Sci*
3. Hao, Lee, Yap et al. (2025) "Comparison of Respiratory Microbiomes in Influenza Versus Other Respiratory Infections: Systematic Review and Analysis" *Int. J. Mol. Sci*
4. Danova, Dobreva, Mancheva et al. (2025) "Lactobacilli-Derived Postmetabolites Are Broad-Spectrum Inhibitors of Herpes Viruses In Vitro" *Int. J. Mol. Sci*
5. Tao, Zhu, Huang et al. (2024) "Development of a Multiplex RT-qPCR Method for the Identification and Lineage Typing of Porcine Reproductive and Respiratory Syndrome Virus" *Int. J. Mol. Sci*
6. Costa, Simas, Da Costa et al. (2025) "Dynamics of SARS-CoV-2 Mutations in Wastewater Provide Insights into the Circulation of Virus Variants in the Population" *Int. J. Mol. Sci*
7. Cho, Ma (2025) "Anti-Viral Activity of Conessine Against Influenza a Virus" *Int. J. Mol. Sci*
8. Ripa, Andreu, Galdo et al. (2025) "Polyclonal LC3B Antibodies Generate Non-Specific Staining in the Nucleus of Herpes Simplex Virus Type 1-Infected Cells: Caution in the Interpretation of LC3 Staining in the Immunofluorescence Analysis of Viral Infections" *Int. J. Mol. Sci*
9. (2026) "Evolving viral threats" *Nat. Rev. Microbiol*
10. Li, Zhang, Zhang et al. (2024) "Global burden of viral infectious diseases of poverty based on Global Burden of Diseases Study 2021" *Infect. Dis. Poverty*
11. Domingo (2020) "Interaction of virus populations with their hosts"
12. Kayesh, Kohara, Tsukiyama-Kohara "Effects of oxidative stress on viral infections: An overview" *Viruses*
13. Kim, Ndwandwe, Devotta et al. (2025) "Role of the microbiome in regulation of the immune system" *Allergol. Int*
14. Kleandrova, Speck-Planche "The urgent need for pan-antiviral agents: From multitarget discovery to multiscale design" *Future Med. Chem. 2021*
15. "The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods"
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# P-319. Discordance Between Objective and Perceived Risk for Contracting HIV and Association with PrEP Engagement in Transgender Individuals
Meghan Anderson, Meredith Zoltick, Rahwa Eyasu, Emade Ebah, Phyllis Bijole, Miriam Jones, Dorcas Salifu, ; Habib Omari, Ashley Davis, Sarah Kattakuzhy, Elana Rosenthal
Fisher's exact test and Cohen's Kappa statistic were used for statistical analysis. Results. Of 98 enrolled participants, 37 were HIV-and attended more than 1 visit, for a total of 151 visits.
At baseline, EE were more likely than NE to have been offered PrEP (100% vs 37%, p < 0.01), have taken PrEP (90% vs 22%, p < 0.01), identify as a trans-female (80% vs 33%, p = 0.02), endorse transactional sex (50% vs 15%, p = 0.04), and to have been diagnosed with a bacterial STI (70% vs 19%, p < 0.01). (Table 1) Among EE, CDC PrEP eligibility and endorsement of HIV risk varied across time points and was discrepant. (Fig 1)
Across all timepoints, there was only a fair agreement between CDC recommendation to use PrEP and endorsed HIV risk (Kappa statistic of 34.2% 95% CI (19.1 -49.2)).
At timepoints when participants met CDC criteria for PrEP, endorsing HIV risk was significantly associated with being on PrEP compared to those who did not endorse (72% vs 19%, p = 0.02). (Table 2) Among those not on PrEP or starting PrEP, 86% reported interest in taking PrEP in the future if they felt they were at risk for HIV.
Conclusion. Among transgender participants, we found significant discordance between perceptions of HIV risk and PrEP eligibility based on CDC criteria, with selfperception of risk more significantly associated with PrEP engagement. Given high rates of willingness to engage in PrEP if they perceive HIV risk, better understanding this discrepancy and how to educate patients about HIV risk may be critical to improving PrEP uptake. Further, given frequently changing HIV risk based on CDC criteria and self-report, newer long-acting PrEP formulations may help to provide sustained protection against HIV in patients with fluctuating risk.
Disclosures. Phyllis Bijole, BA, MA, GILEAD: HIPS had a grant from Gilead to perform community testing services that ended Janary 31, 2024. It paid a portion of my salary
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# David Baltimore: Scientist, leader, and mentor
Nancy Andrews, George Daley
## Abstract
Fifty years ago, at the remarkably young age of 37, David Baltimore received the Nobel Prize (with Howard Temin and Renato Dulbecco) for "discoveries concerning the interaction between tumor viruses and the genetic material of the cell." David was a prolific scientist whose work spanned many topics, but he was first and foremost a virologist. His recent passing invites us to reflect on a remarkable intellectual trajectory that began with seminal discoveries in virology, broadened to encompass major advances in cancer biology and immunology, and culminated in a legacy-sustained by the many scientists he trained-that will continue to shape modern biomedicine for years to come.
In his 1975 Nobel Lecture, David remarked that "a virologist is among the luckiest of biologists because he can see into his chosen pet down to the details of all of its molecules." He had completed his PhD in 2 years with Richard Franklin at The Rockefeller Institute (later Rockefeller University), having transferred from MIT after hearing Franklin speak at the Cold Spring Harbor course on animal virology. At that time, the complexity of mammalian cells seemed unapproachable, and viruses offered tractable tools to probe their inner workings. David embraced this opportunity, making fundamental discoveries about his chosen "pets" and following where they led. Because Franklin's laboratory studied mengovirus and polio, David initially focused on RNA viruses. It was at first reassuringly straightforward: Positive-strand picornavirus genomes could serve directly as mRNA to produce the proteins they encoded. David continued working on poliovirus until the early 1990s, and it became the PhD dissertation topic for Victor Ambros, a student in David's laboratory who would win the Nobel Prize in 2024 for the discovery of microRNAs. As David launched his own independent program, he and his then-postdoc and future wife, Alice Huang, turned to viruses with negative-sense RNA genomes-initially vesicular stomatitis virus (VSV), which Alice had studied as a doctoral student at Johns Hopkins. They inferred that an RNA-dependent RNA polymerase must exist to generate positive strands competent for translation and, drawing on their strength in biochemistry, they rapidly identified this activity.
As Alice continued to pursue VSV in her own laboratory at Harvard Medical School, David sought a new challenge in RNA tumor viruses. He obtained Rous sarcoma virus (RSV) from Peter Vogt, and building on his experience with VSV, initially searched for a viral RNA polymerase but found none. Aware that Howard Temin and others had suggested an essential role for DNA in RNA tumor virus replication, David shifted strategy to seek an RNA-dependent DNA polymerase, an enzyme not previously described. Using murine leukemia virus prepared at the National Cancer Institute and confirming the findings with RSV, he demonstrated that such an enzyme exists and is packaged in the virion together with the RNA genome. Temin independently identified the same activity in RSV and avian myeloblastosis virus, and the two laboratories published back-to-back papers in Nature in June 1970, prompting the description of this process as the "central dogma reversed" and the naming of the enzyme "reverse transcriptase." The discovery of reverse transcriptase provided crucial insight into how retroviruses cause cancer and yielded an indispensable tool for molecular biology and biotechnology, leading to the award of the Nobel Prize just five years later.
Baltimore and Temin's work opened the door to understanding another retrovirus, now known as Human Immuno deficiency Virus (HIV), which emerged as a smoldering pandemic in the early 1980s. David did not participate directly in the discovery of HIV or in delineating every step of its replication cycle, but reverse transcriptase became the first therapeutic target, enabling the development of highly effective antiviral agents such as AZT. David's laboratory went on to show how HIV exploits host transcriptional machinery, linking immune activation to HIV gene expression. His work clarified how integrated proviral DNA can remain transcriptionally silent yet replication-competent, and it highlighted how chromatin state, transcription factors, and thresholds of cellular activation govern the establishment and reversal of latency. David's engagement with HIV research helped secure the field's legitimacy within mainstream biomedicine during a time of fear and stigma. He co-chaired the 1986 National Academies committee on a National Strategy for AIDS, becoming a forceful advocate for federal investment in HIV research and vaccine development.
David Baltimore's pursuit of virology ultimately carried him into cancer biology and immunology, yielding a multifaceted scientific career that established several of the conceptual and technical pillars supporting modern oncology and immune science. Baltimore pioneered the study of Abelson murine leukemia virus, a replication-defective retrovirus that rapidly induces B-lineage leukemias in mice. His group demonstrated that Abelson virus can directly transform fetal liver-derived hematopoietic precursors in vitro, generating continuously proliferating lymphoid cultures and showing that the virus perturbs the growth and differentiation of B-cell progenitors. Subsequent work identified a viral protein, v-Abl, that his laboratory showed to be a transforming tyrosine kinase, establishing one of the first direct links between a specific tyrosine kinase oncogene and acute leukemia. The Baltimore lab's focus on v-Abl presaged and informed the understanding of human leukemias driven by ABL-family tyrosine kinases. Later studies from Baltimore and others clarified key distinctions between v-Abl and BCR-ABL, emphasizing that constitutive tyrosine kinase activity, altered subcellular localization, and distinctive signaling outputs underlie transformation in both the murine model and human chronic myeloid leukemia. Baltimore's body of cancer research helped lay foundations for precision oncology, including the development of kinase inhibitors such as imatinib directed against BCR-ABL. Baltimore's use of Abelson-immortalized B-lineage cells catalyzed a decisive turn toward immunology, enabling deep genetic and biochemical analysis of B-cell ontogeny. His laboratory helped define discrete stages of B-cell development and, leveraging these systems together with emerging molecular cloning approaches, uncovered the machinery of antigen-receptor recombination, including the RAG1 and RAG2 recombination-activating genes that are indispensable for assembling immunoglobulin and T cell receptor genes. Another pivotal contribution was the identification and characterization of NF-κB as the nuclear factor binding the κ light-chain enhancer in B lymphocytes. By demonstrating that NF-κB is inducible and integrates signals from pathogens, cytokines, and antigen receptors, Baltimore's group placed this transcription factor at the center of innate and adaptive immune activation. The NF-κB story became perhaps Baltimore's most powerful bridge from immunology back to cancer biology. NF-κB is now recognized as a central hub in inflammation, innate immunity, and malignancy, with persistent NF-κB signaling contributing to lymphomas, myelomas, and many solid tumors and with NF-κB target genes encompassing cytokines, adhesion molecules, and antiapoptotic factors. Subsequent work on microRNAs in immune cells and tumors extended the logic of transcriptional control into post-transcriptional regulatory networks, revealing how small RNAs influence differentiation, tolerance, and malignant transformation.
## Baltimore Academic Family Tree 1965-2018
Across this rich scientific arc, Baltimore's career followed a consistent theme: Questions rooted in virology repeatedly yielded answers that reshaped cancer biology and immunology. A recent photograph shows David as we will all remember him (Fig. 1). David's influence on biomedicine was amplified by the many scientists he trained over more than five decades at the Salk Institute, MIT, the Whitehead Institute, Rockefeller University, and Caltech (Fig. 2). As former trainees, we remember David as an unparalleled scientist, leader, and mentor. He taught that the highest achievements in science are inseparable from responsibility-to truth, to colleagues, and to society. His blend of vision and humanity set a standard that continues to guide our own leadership in academic medicine. David Baltimore's life stands as an invitation to think boldly, act ethically, and never stop searching for answers.
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# Mallika Lavania and Pooja Umare contributed equally as first author
Mallika Lavania, Pooja Umare, Rishabh Waghchaure, Manoj Vedpathak, Rajlakshmi Vishwanathan, Pradnya Shinde, Upendra Singh Maholiya, Yash Kokarde, Prathamesh Bagewadi, Vijaykumar Chincholkar, Babasaheb Tandale, Naveen Kumar
## Abstract
Norovirus (NoV) is a major global cause of acute viral gastroenteritis, responsible for both sporadic infections and widespread outbreaks affecting individuals across all age groups. Although typically self-limiting, gastrointestinal illness, characterized by nausea, vomiting, and diarrhea, recent evidence points to its potential role in causing nonintestinal complications. Central nervous system (CNS) manifestations such as febrile seizures, convulsions, and encephalopathy have been increasingly associated with norovirus, albeit infrequently. During a large Guillain-Barré Syndrome (GBS) outbreak in January-March 2025 in the southwestern region of Pune, India, a 40-year-old male developed progressive weakness of the limbs beginning on January 18th and was admitted to a tertiary care center in a nearby town for evaluation. Molecular testing of stool samples confirmed the presence of Norovirus Group II RNA, while screening for other enteric pathogens, including Campylobacter jejuni (C. jejuni), the most recognized infectious trigger for GBS, was negative. While C. jejuni remains the primary pathogen linked to GBS, our findings support growing speculation about norovirus as an emerging, albeit rare, trigger. Further studies are needed to investigate the underlying mechanisms and to clarify the role of norovirus in GBS pathogenesis, particularly during community outbreaks.
## Introduction
Norovirus (NoV) is a non-enveloped enteric virus belonging to the Caliciviridae family [1]. It is one of the leading pathogens responsible for gastroenteritis outbreaks across all age groups [2]. Infection typically presents with diarrhea, vomiting, nausea, abdominal pain, headache, and myalgia, sometimes accompanied by mild fever. Symptoms usually resolve within a few days, and most individuals recover fully [3,4]. However, severe cases can require hospitalization or lead to death, particularly in young children under five, the elderly above 65, and immunocompromised individuals [5].
Beyond gastrointestinal illness, several studies have linked NoV infection to convulsions associated with gastroenteritis and, in rare cases, to acute encephalitis or encephalopathy in both children and adults [6][7][8][9]. The pathogenesis of norovirus-related neurological complications remains unclear. Researchers suggest that, in rare instances, immune responses to certain viral antigens may inadvertently attack components of the nervous system, leading to neurological syndromes such as GBS. Although C. jejuni is the most common precipitating agent, several viruses, including enteroviruses, Epstein-Barr virus, and cytomegalovirus, have also been associated with GBS.
Norovirus-associated GBS may often go unrecognized due to limited neurological testing during gastroenteritis outbreaks. This underscores the need for a multidisciplinary public health approach. Co-occurrence of gastrointestinal and neurological symptoms should prompt a comprehensive diagnostic evaluation, including stool and cerebrospinal fluid (CSF) testing, serology, and neuroimaging. Strengthening surveillance, laboratory capacity, and clinical awareness is essential. Preventive measures such as sanitation, hygiene, and rapid diagnostics remain key to outbreak control.
Although GBS linked to norovirus has not been previously reported in India, this paper presents a fatal adult case during a major norovirus outbreak in Pune, Maharashtra (January-March 2025), suggesting that norovirus may act as a rare trigger for GBS in susceptible individuals., a 40-year-old male from a nearby town was admitted to a tertiary care hospital on January 18 with progressive limb weakness. He had experienced acute gastroenteritis with diarrhea on January 11, about a week before neurological symptoms began. He had visited the GBS outbreak-affected area in southwest Pune at this time. He remained afebrile and had no chronic illnesses, immunosuppression, or recent travel history.
## Methods
## Clinical investigations
The patient was diagnosed with GBS and started on IVIg (2 g/kg over five days). Despite initial worsening and respiratory involvement, he showed slight improvement by day 5. On day 6, he developed recurrent diarrhea and sudden respiratory distress, requiring ICU transfer. He rapidly declined with severe hypotension and suffered two cardiac arrests, leading to his death on day 7 (Fig. 1). Given the unexpected and rapid progression leading to fatal outcome, a clinical post-mortem was performed to investigate the underlying cause of death and to determine cause of death after consent of the next-of-kin as per the local clinical and public health requirements. The clinical antemortem and post-mortem specimens were collected and referred for testing to our laboratories to investigate the cause of illness/death, as a requirement exempt from consent, as per the outbreak investigation component for investigation and testing as per the national guidelines.
## Viral RNA extraction and detection
Samples collected included stool from the second episode of dysentery (January 20th, 2025), antemortem cerebrospinal fluid (CSF), and post-mortem intestinal tissue, all transported under a maintained cold chain for testing. Viral RNA was extracted from 30% (w/v) fecal suspensions prepared in phosphate-buffered saline (PBS; pH 7.4) using the MagMAX™ Viral RNA Extraction Kit (Thermo Fisher Scientific, USA), following the manufacturer's instructions. Extracted RNA was tested via realtime PCR on the Thermo Fisher platform. A broad panel of viral and bacterial pathogens was screened, including Norovirus (GI and GII), Rotavirus A, Epstein-Barr virus, Campylobacter jejuni, and others. Stool samples were further tested for norovirus using qRT-PCR targeting the ORF1-ORF2 junction region [10].
Genotypic classification was performed using the Norovirus Genotyping Tool ( h t t p s : / / c a l i c i v i r u s t y p i n g t o o l . c d c . g o v / b c t y p i n g . c g i), which assigns G-and P-types based on the VP1 (capsid) and RdRp gene regions, respectively. Reference sequences for phylogenetic analysis were retrieved in February 2025 from the CDC's curated Human Caliciviruses Typing Tool database ( h t t p s : / / c a l i c i v i r u s t y p i n g t o o l . c d c . g o v / b e c e r a n c e . c g i).
## Full genome sequencing and annotation
All three norovirus-positive samples were amplified using the SuperScript™ III One-Step RT-PCR System with Platinum™ Taq High Fidelity DNA Polymerase (Thermo Fisher, USA) on a GeneAmp PCR System 9700. PCR products were purified with AMPure XP beads (Beckman, USA), eluted in 45 µl of nuclease-and protease-free water, and quantified using a Qubit 2.0 Fluorometer with the dsDNA HS Assay Kit. DNA libraries were prepared with the Illumina DNA Library Prep Kit (10 pM input) and sequenced on the Illumina MiSeq platform (RPIP Panel, USA). Raw reads were assembled using CLC Genomics Workbench (Qiagen), and genome annotation was performed with the VAPiD v1.6.7 pipeline under default settings. Annotated sequences were submitted to GenBank (accession number PV394762).
## Results
## Observations from nerve conduction testing
On admission (January 18th, 2025), the patient had rapid-onset quadriparesis, dysphagia, and areflexia, suggestive of acute peripheral neuropathy. Nerve conduction studies showed absent motor and sural sensory responses in the lower limbs and absent F-waves, indicating diffuse sensorimotor polyradiculoneuropathy with axonal and demyelinating features consistent with GBS.
## Laboratory findings of biochemical tests from urine, blood and CSF
Urine analysis on admission (January 18th, 2025) showed normal physical and chemical characteristics, with clear, pale-yellow urine, mildly acidic pH, and no protein, glucose, bilirubin, or bile salts. Microscopy revealed 1-2 pus cells/hpf (reference: 0-5/hpf ) and absence of RBCs, casts, or yeast cells, ruling out urinary tract infection or renal involvement.
Biochemical monitoring (21st -25th January 2025) indicated evolving electrolyte imbalances. Serum sodium levels progressively declined, consistent with hyponatremia, while potassium levels fluctuated within the normal range, occasionally showing mild hypokalemia. Chloride levels decreased by the fourth day of hospitalization. These abnormalities likely contributed to neuromuscular weakness and autonomic instability. On Day 10 of illness, serum procalcitonin was markedly elevated (36.40 ng/ mL), suggesting severe systemic infection and possible septic shock. (Suppl Table 1).
Microscopic examination of CSF (antemortem) showed reddish and turbid appearance with RBC (30-40/h.p.f.), a few ependymal and nucleated cells (400/h.p.f.), neutrophils comprising 70% lymphocytes 30%. Collectively, these investigations provided a clear picture of a severe, rapidly progressive GBS case complicated by systemic infection and evolving metabolic derangement (Suppl Table 1).
## Molecular diagnosis for etiological investigations
A comprehensive pathogen screening was performed, including Norovirus (GI and GII), Rotavirus A, Epstein-Barr virus, and Campylobacter jejuni. qRT-PCR targeting the ORF1-ORF2 junction detected only Norovirus Group II, with lower Ct values observed in stool compared to intestinal tissue, indicating a higher viral load in stool. No Norovirus RNA was detected in the cerebrospinal fluid (Fig. 2). The presence of Norovirus GII in stool was further confirmed by full-genome sequencing. Subsequent genotypic analysis identified the strain as Norovirus GII.16 [P16]. The clinical presentation, along with the exclusion of other common enteric pathogens such as Campylobacter jejuni and other viruses, supported a diagnosis of Norovirus-related illness.
## Discussion
Enteric viruses, typically associated with gastrointestinal symptoms, are increasingly recognized for causing complications in the central nervous system (CNS). Though direct neuroinvasion is rare, viruses like rotavirus have been occasionally associated with CNS issues such as nonfebrile seizures and encephalopathy, mainly in children. A review by Dickey et al. [11] found only 24 confirmed rotavirus-related CNS cases, highlighting their rarity but possible occurrence. These findings underscore the importance of considering viral causes in neurological cases that lack typical signs of infection.
Noroviruses, RNA viruses belonging to the Caliciviridae family, are a leading cause of non-bacterial gastroenteritis worldwide, including in India, where they account for up to 50% of outbreaks [12]. Diagnosis relies mainly on clinical symptoms during outbreaks, with RT-PCR of stool samples being the most reliable lab test; serological tests are less commonly used due to limited availability.
Neurological complications of norovirus have been under-recognized but are increasingly reported. Benign convulsions in young children are the most common and usually resolve completely [13]. However, more severe neurological manifestations including GBS, Miller Fisher Syndrome and encephalopathy with seizures or motor deficits have also been described [12,14]. In infants and young children, severe encephalopathy with status epilepticus and white matter changes has been documented. Fatal outcomes involving meningoencephalitis and disseminated intravascular coagulation have also been reported, while variable responses to steroids and intravenous immunoglobulin (IVIg) suggest an immunemediated pathogenesis.
An increase in GBS cases was noted in the third week of January 2025, as reported by several tertiary care hospitals in Pune City, as well as through ongoing Acute Flaccid Paralysis (AFP) surveillance among children. All hospitalized and outpatient GBS cases reported between December 1 st, 2024, and March 23rd, 2025, were investigated. The present fatal case was referred for investigation following the patient's death on January 25th, 2025. The previously healthy adult male developed progressive weakness following a brief gastrointestinal illness. Norovirus RNA was detected in stool and post-mortem intestinal tissue, while other common GBS triggers, including Campylobacter jejuni, were ruled out. Based on the clinical presentation, temporal association, and exclusion of other pathogens, Norovirus GII.16 [P16] was considered the likely trigger. This represents only the second documented case of Norovirus-associated GBS, the first being reported from Ireland in 2012 [12].
Norovirus-associated GBS remains exceedingly rare despite the global prevalence of the virus. This may reflect underdiagnoses due to limited molecular testing, mild preceding symptoms, and delayed onset of neurological manifestations, which complicate establishing temporal links. Host immune factors may also contribute to individual susceptibility. The proposed mechanism involves molecular mimicry, where antibodies generated against viral antigens cross-react with components of the peripheral nervous system, leading to immune-mediated demyelination.
Despite the strength of clinical, epidemiological, and molecular evidence, several limitations should be acknowledged. Norovirus RNA was not detected in the CSF, limiting direct evidence of neuroinvasion. Undetected or transient co-infections bacterial or viral cannot be fully excluded and may have acted as confounding factors. Moreover, establishing causality from a single case report is inherently challenging, as temporal association does not confirm a direct etiological link.
Nevertheless, the findings underscore the importance of maintaining high clinical suspicion during norovirus outbreaks and expanding surveillance to include neurological manifestations. Further studies involving larger cohorts, serial sampling, and immunological profiling are needed to elucidate the pathogenic mechanisms linking norovirus infection and GBS, and to enhance diagnostic and preventive strategies.
## References
1. Kapikian, Wyatt, Dolin et al. (1972) "Visualization by immune electron microscopy of a 27-nm particle associated with acute infectious nonbacterial gastroenteritis" *J Virol*
2. Glass, Noel, Ando et al. (2000) "The epidemiology of enteric caliciviruses from humans: A reassessment using new diagnostics" *J Infect Dis*
3. Cdc, Outbreaks, Norovirus (2025)
4. Rockx, De Wit, Vennema et al. (2002) "Natural history of human calicivirus infection: a prospective cohort study" *Clin Infect Dis*
5. O'brien, Donaldson, Iturriza-Gomara et al. (2016) "Age-specific incidence rates for Norovirus in the community and presenting to primary healthcare facilities in the United Kingdom" *J Infect Dis*
6. Ito, Takeshita, Nezu et al. (2006) "Norovirus-associated encephalopathy" *Pediatr Infect Dis J*
7. Chan, Chan, Ma (2011) "Norovirus as cause of benign convulsion associated with gastro-enteritis" *J Paed Chil Health*
8. Deb, Mondal, Lahiri et al. (2023) "Norovirus-associated neurological manifestations: summarizing the evidence" *J Neurovirol*
9. Sánchez-Fauquier, González-Galán, Arroyo et al. (2015) "Norovirus-associated encephalitis in a previously healthy 2-year-old girl" *Pediatr Infect Dis J*
10. Trujillo, Mccaustland, Zheng et al. (2006) "Use of TaqMan real-time reverse transcription-PCR for rapid detection, quantification, and typing of Norovirus" *J Clin Microbiol*
11. Dickey, Jamison, Michaud et al. (2009) "Rotavirus meningoencephalitis in a previously healthy child and a review of the literature" *Pediatr Infect Dis J*
12. Eltayeb, Crowley (2012) "Guillain-Barre syndrome associated with Norovirus infection" *BMJ Case Rep*
13. Miyagi, Sasano (2023) "Laboratory findings of benign convulsions with mild gastroenteritis: a meta-analysis" *Cureus*
14. Kimura, Goto, Migita et al. (2010) "An adult norovirus-related encephalitis/encephalopathy with mild clinical manifestation" *BMJ Case Rep*
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# Complete genome sequences of two Cressdnaviricota viruses identified in respiratory tract samples from forest musk deer in China
Qing Zhang, Xiaojie Jiang, Yuan Xi, Xiao Ma, Wen Zhang
## Abstract
We identified two circular single-stranded DNA viruses from forest musk deer in China through metagenomic analysis. Phylogenetic results suggest they represent unclassified Cressdnaviricota lineages. This study highlights the diversity of the deer's respiratory virome and underscores the importance of wildlife virus surveillance for conservation and public health. KEYWORDS Cressdnaviricota, forest musk deer, viral metagenomics, respiratory virome T he forest musk deer (Moschus berezovskii) is a nationally protected Class I wildlife species in China, threatened by habitat loss and poaching (1). To investigate its respiratory virome, we performed viral metagenomic analysis on nasal swabs collected from 30 individuals in Anhui Province in 2017. The samples were pooled into three groups and processed for high-throughput sequencing. Among the viruses identified, two circular single-stranded DNA viruses were affiliated with the phylum Cressdnaviri cota, which includes highly diverse viruses infecting a broad range of hosts (2).Samples were collected using sterile polyester swabs and stored at -80°C. Each pool of 10 swabs was suspended in calcium-and magnesium-free DPBS, vortexed, centrifuged, and filtered through 0.45 µm membranes to eliminate residual eukaryotic cells and bacteria (3). The filtrates were treated with DNase and RNase enzymes to remove unprotected nucleic acids (4). Total viral nucleic acids were extracted using the QIAamp Viral RNA Mini Kit (Qiagen). Reverse transcription and double-stranded DNA synthesis were carried out using SuperScript IV (Invitrogen) and Klenow fragment (New England Biolabs), respectively. Sequencing libraries were prepared using the Nextera XT DNA Library Preparation Kit (Illumina) and sequenced on an Illumina MiSeq plat form (250 bp paired-end reads). Reads were quality-filtered (Q10, Phred v1.0.0), and host reads were removed using Bowtie 2 (v2.3.4.1) against the M. berezovskii genome (GCF_022376915.1). Assembly was performed with EnsembleAssembler v1.0.0(5) and refined in Geneious Prime v2019.0.5(6). Contigs were screened for vector contamination via VecScreen (UniVec). Viral candidates were identified via DIAMOND BLASTx (v2.0.15) against a curated NVNR database and validated using NCBI Viral RefSeq v219 (7). Remote homologs were detected using vFam v1. 1 and HMMER3 v3.3.2(8). Open reading frame (ORFs) were predicted in Geneious; taxonomy was assigned with MEGAN v6.21.16. Circular genomes were confirmed by overlapping reads. All tools ran with default settings.The two complete viral genomes are circular, measuring 4,171 bp and 4,325 bp in length, with GC contents of 45.8% and 43.4%, respectively. Each genome contains a capsid protein ORF and a replication-associated protein (Rep) ORF, the hallmark of Cressdnaviricota. The average coverage depths were 19.3× and 33.1×, respectively, indicating sufficient sequencing depth to support high-confidence assembly. Cress1
clustered with a 2021 yak gut sequence from Qingdao, China (GenBank: OR370344) at 94.89% identity, while Cress2 shared 99.90% identity with a 2016 forest musk deer sequence (GenBank: MN621479). Phylogenetic analysis of Rep sequences places them in an unclassified clade within the phylum, distinct from known families. Phyloge netic analysis showed that the two newly identified Cressdnaviricota viruses belong to unclassified but evolutionarily distinct lineages, suggesting taxa (Fig. 1). In summary, this study identified two Cressdnaviricota viruses in respiratory tract samples from forest musk deer using high-throughput viromic analysis, highlighting their genomic diversity and evolutionary relationships. Red-colored nodes indicate novel viral sequences identified in this study. We used the MUSCLE algorithm in MEGA (v11.0.13) with default parameters (9).
Phylogenetic reconstruction was performed using MrBayes (v3.2.7) based on Bayesian inference with the model set to lset nst=6 rates=invgamma to account for variable substitution patterns and rate heterogeneity (10). Two independent Markov chain Monte Carlo (MCMC) runs were conducted until the average standard deviation of split frequencies dropped below 0.01, indicating convergence and robustness of the analysis (11).
with corresponding Sequence Read Archive (SRA) accession numbers SRR33980742-SRR33980744. The complete viral genomes are available under GenBank accession numbers PV854197 and PV854198. All data are publicly accessible without restrictions.
## References
1. Singh, Saud, Jiang et al. (2022) "Himalayan musk deer (Moshcus leucogaster) behavior at latrine sites and their implica tions in conservation" *Ecol Evol*
2. Krupovic, Varsani, Kazlauskas et al. (2020) "Cressdnaviricota: a virus phylum unifying seven families of repencoding viruses with single-stranded, circular DNA genomes" *J Virol*
3. Conceição-Neto, Zeller, Lefrère et al. (2015) "Modular approach to customise sample preparation procedures for viral metagenomics: a reproducible protocol for virome analysis" *Sci Rep*
4. Jiang, Liu, Xi et al. (2023) "Virome of high-altitude canine digestive tract and genetic characterization of novel viruses potentially threatening human health" *mSphere*
5. Deng, Naccache, Ng et al. (2015) "An ensemble strategy that significantly improves de novo assembly of microbial genomes from metagenomic next-generation sequencing data" *Nucleic Acids Res*
6. Zhang, Yang, Shan et al. (2017) "Virome comparisons in wild-diseased and healthy captive giant pandas" *Microbiome*
7. Liu, Jiang, Lei et al. (2024) "Differences between the intestinal microbial communities of healthy dogs from plateau and those of plateau dogs infected with Echinococcus" *Virol J*
8. Finn, Clements, Eddy (2011) "HMMER web server: interactive sequence similarity searching" *Nucleic Acids Res*
9. Kumar, Stecher, Li et al. (2018) "MEGA X: molecular evolutionary genetics analysis across computing platforms" *Mol Biol Evol*
10. Ronquist, Teslenko, Van Der Mark et al. (2012) "MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space" *Syst Biol*
11. Shan, Yang, Wang et al. (2022) "Virome in the cloaca of wild and breeding birds revealed a diversity of significant viruses" *Microbiome*
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# Announcement of two complete coding genomes of mink coronavirus and one partial coding genome of mink enteric calicivirus from mink in Denmark
Christina Lazov, Lars Larsen, Camille Johnston, Thomas Rasmussen, Charlotte Hjulsager
## Abstract
Two complete coding genomes of mink coronavirus and one partial coding genome of the sapovirus mink enteric calicivirus were assembled from metagenomic sequencing data from mink on different farms with diarrhea outbreaks in 2015 in Denmark.KEYWORDS mink coronavirus, sapovirus, metagenome, mink enteric calicivirus, diarrhea M ink coronaviruses (MCoVs) belonging to the species Alphacoronavirus neovisontis, family Coronaviridae has previously been associated with gastrointestinal disorders in farmed mink (Neogale vison) (1). Few complete sequences of MCoV strains and even fewer and only partial genome sequences of mink enteric calicivirus (MEC), belonging to the genus Sapovirus (genotype GXII) in the Caliciviridae family, appear presently in GenBank. This virus has also been linked to disease, as it has been isolated from diarrheic mink (2), and the replication and location of mink sapovirus in the crypts and basis of the villi of the small intestine from diarrheic mink kits has been visualized by in situ hybridization (3).This report describes the detection and sequencing of complete coding genomes of MCoV strains and a partial coding genome of MEC from two minks on different farms sampled in 2015 in Denmark.Mink feces samples, from farms experiencing problems with diarrhea, were collected in July 2015. The samples were diluted in PBS to 10% and homogenized in a TissueLyser II (QIAGEN, Denmark). Nucleic acids were extracted using the QIAsymphony DSP Virus/ Pathogen Mini Kit (QIAGEN, Denmark) on a QIAsymphony (QIAGEN, Denmark). The presence of coronavirus was tested with a broadly reactive panCoV RT-qPCR assay (4, 5). Two RNA samples testing positive for coronavirus were selected for sequencing using a non-targeted metagenomic protocol as previously described (6). Briefly, dsDNA was generated using the NEBNext mRNA second strand synthesis kit (New England Biolabs), library preparation performed with the Nextera-XT DNA library Preparation kit, and sequencing done on a MiSeq machine with Reagent Kit v3 600 bp (Illumina Inc, San Diego, CA, USA).Taxonomic identification on read level was performed with Kaiju (7) (Table 1), read quality assessed using FastQC (8), and trimming performed with BBDuk (9) (default parameters) using Geneious Prime (10). Trimmed reads were de novo assembled using the SPAdes plugin v. 3.10.0 for metagenomic data (default parameters) (11). A single contig covering the complete coding genome of MCoV was generated for each of the two samples 11917-2 and 11918-1, as well as a single contig with the partial coding genome of MEC in sample 11917-2 (Table 1). Contigs were polished using trimmed reads,
and consensus sequences were extracted after visual evaluation. These were queried by BLASTn, aligned to the highest scoring reference genomes, and annotated.
The MCoV shared 91% nucleotide identity and 92% amino acid identity, indicating two different strains. Concerning the MEC, conserved motifs previously described for sapoviruses (12,13) were used to roughly identify the different non-structural and structural viral protein CDS in the genome. Hereby, it was possible to determine that the 5′-end of ORF1 encoding the polyprotein and 3′-end of ORF2 encoding VP2 were missing. MEC reads identified in publicly available metagenomic data from farmed mink in Denmark (14) were used to confirm the MEC sequence assembly. Assembly and read information are shown in Table 1.
## Parameters
## References
1. Vlasova, Halpin, Wang et al. (2011) "Molecular characterization of a new species in the genus Alphacoronavirus associated with mink epizootic catarrhal gastroenteritis" *J Gen Virol*
2. Guo, Evermann, Saif (2001) "Detection and molecular characteri zation of cultivable caliciviruses from clinically normal mink and enteric caliciviruses associated with diarrhea in mink" *Arch Virol*
3. Birch, Leijon, Nielsen et al. (2021) "Visualization of intestinal infections with astro-and sapovirus in mink (Neovison vison) kits by in situ hybridization"
4. Escutenaire, Mohamed, Isaksson et al. (2007) "SYBR Green real-time reverse transcriptionpolymerase chain reaction assay for the generic detection of coronavi ruses" *Arch Virol*
5. Lazov, Chriél, Baagøe et al. (2018) "Detection and characterization of distinct alphacoronaviruses in five different bat species in Denmark" *Viruses*
6. Lazov, Belsham, Bøtner et al. (2021) "Full-genome sequences of Alphacoronaviruses and astroviruses from myotis and pipistrelle bats in Denmark" *Viruses*
7. Menzel, Ng, Krogh (2016) "Fast and sensitive taxonomic classification for metagenomics with Kaiju" *Nat Commun*
8. Andrews (2018) "FastQC v"
9. Bushnell (2015) "BBDuk Trimmer v. 1.0. Biomatters Ltd"
10. (2019) *Geneious Prime v*
11. Nurk, Meleshko, Korobeynikov et al. (2017) "metaSPAdes: a new versatile metagenomic assembler" *Genome Res*
12. Oka, Lu, Phan et al. (2016) "Genetic characterization and classification of human and animal sapoviruses" *PLoS One*
13. Oka, Wang, Katayama et al. (2015) "Comprehensive review of human sapoviruses" *Clin Microbiol Rev*
14. Birch, Ullman, Struve et al. (2018) "Investigation of the viral and bacterial microbiota in intestinal samples from mink (Neovison vison) with pre-weaning diarrhea syndrome using next generation sequencing" *PLoS One*
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# Genome sequences of human coronavirus NL63 diagnosed in southern France
Houmadi Hikmat, Céline Boschi, Sarah Aherfi, Aurélie Morand, Bernard Scola, Philippe Colson
## Abstract
We report here 17 human coronavirus NL63 genomes from France. They were obtained from residues of respiratory samples collected from patients for diagnostics in southern France, using an in-house multiplex PCR amplification system followed by next-generation sequencing with Illumina technology. Sixteen genomes belong to subgenotype C2 and one to subgenotype B1. KEYWORDS coronavirus, human coronavirus-NL63, genome, phylogenomics, genomic surveillance H uman coronavirus NL63 (HCoV-NL63), discovered in 2003 (1), belongs to the genus Alphacoronavirus (2) and likely has a zoonotic origin from bats (3). It has a sin gle-stranded positive-sense RNA genome of ≈28 kilobases that encodes 16, 4, and 1 nonstructural, structural (spike, envelope, matrix, and nucleocapsid), and accessory proteins, respectively (4). Its cell receptor is angiotensin-converting enzyme 2 (5). HCoV-NL63 is ubiquitous worldwide (6, 7), causing respiratory tract infections, mostly in children, usually mild but potentially severe and life-threatening (8-12). A total of 345 genomes (>90% coverage of KY073745.1) were released in GenBank (https:// www.ncbi.nlm.nih.gov/genbank/) as of 17 July 2025, obtained from patients sampled between 1983 and 2025, in 24% of the cases since 2020, mostly from the USA (31%), UK (28%), and China (21%). Three genotypes A-C and eight subgenotypes were delineated (12)(13)(14).Here, HCoV-NL63 genomes were obtained from residues of HCoV-NL63 RNA-positive respiratory samples collected in 2021 from patients for routine diagnostic by multiplex qPCR (15). RNA was extracted with the MagMAX Viral/Pathogen Nucleic Acid Isolation kit on a KingFisher Flex system (Thermo Fisher Scientific). Thirty-five PCR primer pairs (Table 1) were designed with GEMI ( 16) and then used to pre-amplify HCoV-NL63 genomes with the SuperScript III One-Step RT-PCR kit with Platinum Taq DNA polymer ase (Thermo Fisher Scientific), as previously described (15). Next-generation sequencing was performed as previously described (15) using Illumina technology and the COVIDSeq protocol (Illumina Inc.), with replacement of ARTIC COVID-19 primers with primers designed here. Library preparation and sequencing of 2 × 250 paired-end reads on a MiSeq instrument (Illumina Inc.) were performed following the manufacturer's instruc tions. There were, on average, 7,353,541 ± 5,020,276 reads generated per sample (range, 264,636-17,879,700). The Genome Detective web application (https://www.genomede tective.com/) (17) performed a trimming and quality control of reads, then the assem bly, annotation, and taxonomic classification of viral genomes with default settings. Phylogeny was performed using IQ-TREE 2 (18).Seventeen HCoV-NL63 genomes, 27,322-27,465 nucleotides long, were obtained. Mean coverage relative to genome NC_005831.2 dating back to 2003 was 98.0% (range, 90.0-99.9%). Coverage <100% was due to amplification defects of some regions, mostly 5′ and 3′ genome ends. Phylogeny identified subgenotypes C2 and B1 in 16 and one
case, respectively (Fig. 1). Subgenotype C2 genomes exhibited a similarity of 98.3% on average between each other and of 90.5% with the subgenotype B1 genome. The closest relatives according to BLAST searches into GenBank and to phylogeny were obtained from the USA, Japan, UK, China, and Switzerland between 2017-2024; mean similarity was 97.3% with the best hits. Substitution I507L, located in the spike receptor binding domain and suspected to promote viral entry into host cells (12), was present in all subgenotype C2 genomes but absent in the subgenotype B1 genome. In summary, the HCoV-NL63 genomes provided here from France account for around a fifth of those available worldwide since 2020. They evidence that at least subgenotypes C2 and B1 circulated in our geographical area. Prior evidence of expanding diversity and of frequent recombinations (19,20) warrants intensifying HCoV-NL63 genome sequenc ing retrospectively and prospectively to get a more detailed picture of the epidemiology, diversity, and evolution of this virus.
## References
1. Van Der Hoek, Pyrc, Jebbink et al. (2004) "Identification of a new human coronavirus" *Nat Med*
2. Zhou, Qiu, Ge (2021) "The taxonomy, host range and pathogenicity of coronaviruses and other viruses in the Nidovirales order"
3. Tang, Liu, Chen (2022) "Human coronaviruses: origin, host and receptor" *J Clin Virol*
4. Brant, Tian, Majerciak et al. (2021) "SARS-CoV-2: from its discovery to genome structure, transcription, and replication" *Cell Biosci*
5. Milewska, Nowak, Owczarek et al. (2018) "Entry of human coronavirus NL63 into the cell" *J Virol*
6. Gaunt, Hardie, Claas et al. (2010) "Epidemiology and clinical presentations of the four human coronavi ruses 229E, HKU1, NL63, and OC43 detected over 3 years using a novel multiplex real-time PCR method" *J Clin Microbiol*
7. Hodinka (2016) "Respiratory RNA viruses" *Microbiol Spectr*
8. Faye, Barry, Jallow et al. (2020) "Epidemiol ogy of non-SARS-CoV2 human coronaviruses (HCoVs) in people presenting with influenza-like illness (ILI) or severe acute respiratory infections (SARI) in Senegal from 2012 to" *Viruses*
9. Cabeça, Granato, Bellei (2013) "Epidemiological and clinical features of human coronavirus infections among different subsets of patients" *Influenza Other Respir Viruses*
10. Konca, Korukluoglu, Tekin et al. (2017) "The first infant death associated with human coronavirus NL63 infection" *Pediatr Infect Dis J*
11. Oosterhof, Christensen, Sengeløv (2010) "Fatal lower respiratory tract disease with human corona virus NL63 in an adult haematopoietic cell transplant recipient" *Bone Marrow Transplant*
12. Wang, Li, Liu et al. (2018) "Discovery of a subgenotype of human coronavirus NL63 associated with severe lower respiratory tract infection in China" *Emerging Microbes & Infections*
13. Ye, Gong, Cui et al. (2023) "Continuous evolution and emerging lineage of seasonal human coronaviruses: a multicenter surveillance study" *J Med Virol*
14. Mcclure, Tsoleridis, Hill et al. (2025) "Vivaldi": an amplicon-based whole-genome sequencing method for the four seasonal human coronaviruses, 229E, NL63, OC43 and HKU1, alongside SARS-CoV-2" *Microb Genom*
15. Hikmat, Targa, Boschi et al. (2025) "Five-year (2017-2022) evolutionary dynamics of human coronavirus HKU1 in southern France with emergence of viruses harboring spike h512r substitution" *J Med Virol*
16. Sobhy, Colson (2012) "Gemi: PCR primers prediction from multiple alignments" *Comp Funct Genomics*
17. Vilsker, Moosa, Nooij et al. (2019) "Genome detective: an automated system for virus identification from high-throughput sequencing data" *Bioinformatics*
18. Minh, Schmidt, Chernomor et al. (2020) "IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era" *Mol Biol Evol*
19. Shao, Zhang, Dong et al. (2022) "Molecular evolution of human coronavirus-NL63, -229E, -HKU1 and -OC43 in hospitalized children in China" *Front Microbiol*
20. Tao, Shi, Chommanard et al. (2017) "Surveillance of bat coronaviruses in Kenya identifies relatives of human coronaviruses NL63 and 229E and their recombination history" *J Virol*
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# Oral VV261 administration protects mice from lethal Crimean-Congo hemorrhagic fever virus challenge
Xi Wang, Huan Xu, Liushuai Li, Fan Wu, Jiang Li, Jingshan Shen, Gengfu Xiao, Wei Zheng, Leike Zhang, Zhihong Hu, Manli Wang
## Abstract
KEYWORDS Crimean-Congo hemorrhagic fever virus, nucleoside analog, VV261, oral administration C rimean-Congo hemorrhagic fever virus (CCHFV), a member of the family Nairoviridae within the class Bunyaviricetes (1), is distributed across more than 30 countries and poses a significant threat to global health. CCHFV infection causes acute viral hemorrha gic fever with a high case fatality rate (10-40%) (2, 3). No FDA-approved therapeutics exist, prompting the WHO to list it as a priority pathogen for research and development since 2017. While some antiviral compounds like T-705 (favipiravir) (4), H44 (5), and baloxavir sodium (6) have shown promise in animal models, drug development for CCHFV needs acceleration.VV261, an oral double prodrug of 4′-fluorouridine (4′-FU), exhibits improved stability and pharmacokinetics. It has demonstrated efficacy against related bunyaviruses such as Severe fever with thrombocytopenia syndrome virus (7). VV261 has entered phase I clinical trials in China. Given that 4′-FU targets the RNA-dependent RNA polymerase (RdRp) and shows broad-spectrum anti-RNA virus activity (8-13), we evaluated the antiviral potential of VV261 against CCHFV.We first tested the anti-CCHFV activity of VV261 in vitro. In human umbilical vein endothelial cells (HUVECs), VV261 potently inhibited CCHFV infection with a median effective concentration (EC 50 ) value of 2.72 ± 0.28 µM (Fig. 1A). It showed negligible cytotoxicity as the 50% cytotoxicity concentration (CC 50 ) value is greater than 200 µM, resulting in a high selective index (SI > 73.53) (Fig. 1A). These data demonstrated that VV261 is a potent inhibitor against CCHFV in vitro.We next performed a time-of-addition assay to investigate which stage of the viral life cycle VV261 targets to inhibit CCHFV infection. Treatment during the post-entry phase or for the full duration nearly completely suppressed progeny virus production (Fig. 1B) and viral nucleoprotein (NP) expression (Fig. 1C). Some inhibition during the entry stage was likely attributed to the residual compound retained within the cells. Taken together, these results indicate that VV261 mainly targets the post-entry stage of CCHFV infection.To further investigate the inhibitory activity of VV261 against viral transcription and replication machinery-specifically, the RdRp, a previously established mini-replicon system was employed (6). We found that VV261 dose-dependently reduced GFP expression by approximately 20%, 38%, and 59% at concentrations of 2, 10, and 50 µM, respectively (Fig. 1D), suggesting the inhibition of RdRp activity, consistent with its mechanism as a nucleoside analog.The anti-CCHFV efficiency of VV261 was further evaluated in vivo using A129 mice, which are deficient in IFNα/β receptor and are highly susceptible to lethal CCHFV challenge (14). Mice were challenged intraperitoneally (i.p.) with 10 TCID 50 CCHFV. One hour post-infection, different doses of VV261 (1, 5, and 10 mg/kg/day [mpk]) were administered orally (Fig. 2A). Mice in the negative control group received the drug
vehicle orally, while the positive control group was treated with T-705 (300 mpk) via i.p. injection. Following the initial administration, the treatment continued for 6 days.
Vehicle-treated mice lost weight at 2 days post-infection (Fig. 2B) and ultimately succumbed to the virus infection within 5 days (Fig. 2C). In contrast, mice receiving 10 or 5 mpk VV261 or T-705 showed no significant weight loss or clinical signs (Fig. 2B), and all survived (Fig. 2C). The low-dose VV261 (1 mpk) delayed weight loss and extended survival (Fig. 2B andC), although it did not provide full protection. Viral loads in the livers of mice treated with T-705, VV261 (5 mpk), and VV261 (10 mpk) were nearly undetectable (Fig. 2D), suggesting potent suppression of viral replication in vivo. We also got similar viral load results in spleen tissue (Fig. S1). In contrast, the 1 mpk dose of VV261 was ineffective (Fig. 2D; Fig. S1), which aligns with the pharmacokinetic data (7) showing its maximum concentration (C max ~ 2.70 µM) barely reaches its EC 50 value (2.72 µM).
Pathology examination of major target organs (15) showed that T-705, 5 mpk, and 10 mpk VV261 treatments remarkably alleviated tissue damage, reducing hepatocellular necrosis (white arrows) and lymphocyte filtration (black arrows) in the liver, as well as less disruption of splenic structure in spleen (Fig. 2E).
In summary, we have demonstrated that VV261 inhibits CCHFV replication efficiently in vitro and in vivo. Its mechanism involves targeting RdRp transcription activity. A dosage of 5-10 mpk of VV261 conferred 100% protection in a lethal mouse model, comparable to a higher dose of T-705 (300 mpk). However, this study has several limitations worthy of further research. For instance, evaluating the drug's efficacy when administering at different infection stages, extending the observation period to monitor potential disease rebound, using immunocompetent animal models will better inform the clinical translation of VV261. In addition, whether CCHFV would develop resistance to VV261 as reported in other viruses (16,17) remains under investigation. Nevertheless, with its oral bioavailability and favorable dosing regimen, VV261 represents a promising candidate for treating CCHFV infection.
## References
1. Kuhn, Alkhovsky, Avšič-Županc et al. (2024) "ICTV virus taxonomy profile: nairoviridae 2024" *J Gen Virol*
2. Ergönül (2006) "Crimean-Congo haemorrhagic fever" *Lancet Infect Dis*
3. Hawman, Feldmann (2023) "Crimean-Congo haemorrhagic fever virus" *Nat Rev Microbiol*
4. Hawman, Haddock, Meade-White et al. (2018) "Favipiravir (T-705) but not ribavirin is effective against two distinct strains of Crimean-Congo hemorrhagic fever virus in mice" *Antiviral Res*
5. Wang, Cao, Li et al. (2022) "In vitro and in vivo efficacy of a novel nucleoside analog H44 against Crimean-Congo hemorrhagic fever virus" *Antiviral Res*
6. Liu, Li, Liu et al. (2024) "Discovery of baloxavir sodium as a novel anti-CCHFV inhibitor: biological evaluation of in vitro and in vivo" *Antiviral Res*
7. Cheng, Zheng, Dong et al. (2025) "Design and development of a novel oral 4'-fluorouridine double prodrug VV261 against SFTSV" *J Med Chem*
8. Lieber, Aggarwal, Yoon et al. "2023. 4'-Fluorouridine mitigates lethal infection with pandemic human and highly pathogenic avian influenza viruses" *PLoS Pathog*
9. Sourimant, Lieber, Aggarwal et al. "2022. 4'-Fluorouridine is an oral antiviral that blocks respiratory syncytial virus and SARS-CoV-2 replication" *Science*
10. Wang, Wang, Zhu et al. (2025) "Effectiveness of nucleoside analogs against Wetland virus infection" *Antiviral Res*
11. Westover, Jung, Mao et al. (2025) "Oral 4'-fluorouridine rescues mice from advanced lymphocytic choriomeningitis virus infection" *Antiviral Res*
12. Yin, May, Lello et al. "2024. 4'-Fluorouridine inhibits alphavirus replication and infection in vitro and in vivo"
13. Welch, Spengler, Westover et al. (2024) "Delayed low-dose oral administration of 4'-fluorouridine inhibits pathogenic arenaviruses in animal models of lethal disease" *Sci Transl Med*
14. Hawman, Meade-White, Haddock et al. (2019) "Crimean-Congo hemorrhagic fever mouse model recapitulating human convalescence" *J Virol*
15. Zhang, Jiang, Liao et al. (2025) "A mouse model of Crimean-Congo hemorrhagic fever virus-induced coagulop athy" *Virol Sin*
16. Lieber, Kang, Aggarwal et al. (2024) "Influenza A virus resistance to 4'-fluorouridine coincides with viral attenuation in vitro and in vivo" *PLoS Pathog*
17. Yin, Sobolik, May et al. (2025) "Mutations in chikungunya virus nsP4 decrease viral fitness and sensitivity to the broad-spectrum antiviral 4′-fluorouridine" *PLoS Pathog*
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biology
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# Isolation and near-complete genome of human enterovirus B4 (Coxsackie virus B4) strain isolated from a nasopharyngeal swab of a 5-year-old male child with severe hand, foot, and mouth disease in Mizoram, India
Basavaraj Mathapati, Swagnik Roy, Vikas Sharma, Mallika Lavania, Souvik Mitra, Lalremruata Chenhrang, Dinesh Singh, Sanket Sonawane, Ratnadeep More, Naveen Kumar
## Abstract
We report the near-complete genome sequence of Coxsackievirus B4 (CVB4) isolate BSM-25-005 (GenBank accession no. PX021639.1), collected in 2024 from a nasopharyngeal swab of a 5-year-old child with severe hand, foot, and mouth disease in Mizoram, India. Phylogenetic and sequence analyses identified the virus as CVB4 subgenotype D.
H uman enterovirus B4 (Coxsackievirus B4, CVB4) is one of the more than 150 enteroviruses in the genus Enterovirus of the family Picornaviridae, causing hand, foot, and mouth disease (HFMD) predominantly in children below 5 years of age (1). It causes acute infection with fever, mouth ulcers, and vesicular eruptions on hands, feet, and the ventral abdomen. It is responsible for several syndromes like myocarditis, meningoencephalitis, pleurodynia, hepatitis, pancreatitis, and respiratory illnesses. The infection can be severe, particularly in high-risk groups such as neonates and immuno compromised individuals (2,3). HFMD is endemic in many parts of Asia (4) and has caused multiple outbreaks over the past decades. The BSM-25-005 strain of CVB4 was isolated from a nasopharyngeal swab of a 5-year-old male child with severe clinical manifestations of HFMD with existing Down Syndrome (trisomy 21) from Mizoram, India, in 2024. The clinical sample positive for a pan-enterovirus species-specific RT-PCR (4) was inoculated and isolated on Vero CCL-81 cells (5).
Viral RNA was extracted from the cell culture supernatant using the QIAamp Viral RNA Mini Kit (Qiagen, Germany), following the manufacturer's protocol. Sequencing was performed using the Illumina Viral Surveillance Panel v2 (Illu mina VSP v2 https://sapac.illumina.com/products/by-type/sequencing-kits/library-prepkits/viral-surveillance-panel.html). Library preparation was done with the Illumina RNA Prep with Enrichment Kit (Illumina USA), in which libraries were enriched using VSP v2 probes through a hybrid-capture method, followed by on-bead tagmentation. The enriched libraries were then subjected to paired-end RNA sequencing on the Illumina NovaSeq 6000 platform (Illumina, USA). A total of 193,287 paired-end raw reads were quality-checked using FastQC (version 0.12.1). Low-quality sequences and adapters were trimmed using Fastp (version 0.23.4) (6).
The cleaned reads were assembled using two methods: de novo using rnaSPAdes (version 4.0.0) (7) and reference-based assembly through a custom pipeline. For reference-based assembly, reads were aligned to the reference genome (PP461541.1) using BWA-MEM (version 0. for BAM conversion, sorting, indexing, and coverage calculation. Variant calling was performed with BCFtools (version 1.21), and a consensus genome was generated using bcftools consensus. The final assembled genome was 7,382 bp in length, with 47.4% GC content and an average depth of coverage of 2,572×. Although the assembled genome length (7,382 nt) matched that of the reference (PP461541.1), the genuine 5′ and 3′ termini could not be confirmed due to the absence of RACE; hence, the sequence is described as a near-complete genome. The assembled genome was annotated using VAPiD (version 1.6.7) (10), with default parameters against the RefSeq Viral Database (downloaded from NCBI FTP on 30 July 2024). The annotated genome was submitted to GenBank through the BankIt submission tool. Genotyping was performed using the Enterovirus Genotyping Tool (https://mpf.rivm.nl/mpf/typingtool/enterovirus/job/ 1599235367/), which identified the Indian isolated strain as CVB4. A BLASTn search against the NCBI NR database (accessed on 05 August 2025) revealed the closest match (88.59% nucleotide identity and 100% query coverage) to a CVB4 genome of Enterovirus B strain CVB4/Thailand/ENV036/2023 (PP461541.1) from Thailand, collected in 2023. An ML phylogenetic tree (Fig. 1) based on the VP1 gene confirmed this relatedness, placing the Indian CVB4 isolate within the CVB4 subgenotype D clade.
## References
1. Machado, Tavares, Sousa (2024) "Global landscape of coxsackieviruses in human health" *Virus Res*
2. Bissel, Winkler, Deltondo et al. (2014) "Coxsackievirus B4 myocarditis and meningoencephalitis in newborn twins" *Neuropathology*
3. Hunt, Schneider, Menticoglou et al. (2012) "Antenatal and postnatal diagnosis of Coxsackie B4 infection: case series" *Am J Perinatol Rep*
4. Van Tu, Thao, Perera et al. (2005) "Epidemiologic and virologic investigation of hand, foot, and mouth disease, southern Vietnam" *Emerg Infect Dis*
5. Rai, Ammi, Anes-Boulahbal et al. (2024) "Molecular amplification and cell culturing efficiency for enteroviruses' detection in cerebrospinal fluids of Algerian patients suffering from meningitis" *Viruses*
6. Chen, Zhou, Chen et al. (2018) "Fastp: an ultra-fast all-in-one FASTQ preprocessor" *Bioinformatics*
7. Bushmanova, Antipov, Lapidus et al. (2019) "rnaSPAdes: a de novo transcriptome assembler and its application to RNA-Seq data"
8. Li (2013) "Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM"
9. Danecek, Bonfield, Liddle et al. (2021) "Twelve years of SAMtools and BCFtools. Gigascience 10:giab008"
10. Shean, Makhsous, Stoddard et al. (2019) "VAPiD: a lightweight cross-platform viral annotation pipeline and identification tool to facilitate virus genome submissions to NCBI GenBank" *BMC Bioinformatics*
11. Katoh, Standley (2014) "MAFFT: iterative refinement and additional methods" *Methods Mol Biol*
12. Minh, Schmidt, Chernomor et al. (2020) "IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era" *Mol Biol Evol*
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# BMC Medical Education
Vincent Sulla, Vincent Portet Sulla, Stephane Marot, Marion Dutkiewicz, Valentine Berti, Anaïs Grimal, Théo Ghelfenstein-Ferreira, Morgane Solis, Caroline Charre, Maud Salmona, Vincent Thibault, Charlotte Pronier, Nicolas Pineros, Mathilde Lescat, Juliette Besombes, Christelle Vauloup-Fellous
## Abstract
Introduction Medical virology requires students to master complex concepts in a limited timeframe, yet traditional lectures often struggle to sustain engagement and ensure long-term retention. Serious games have emerged as promising tools to promote active learning. Building on the success of BacteriaGame, ViroGame was developed to reinforce virology knowledge through gamification. This study evaluated its effectiveness in enhancing student engagement, knowledge mobilization, and supervisor-perceived feasibility for curricular integration. Materials and methods A total of 318 learners participated in ViroGame sessions during the 2023-2024 academic year. Of these, 266 students/residents completed a structured questionnaire assessing with likert scale [1-5] gameplay fluidity, knowledge consolidation, perceived difficulty and potential integration with BacteriaGame. Nine supervisors also provided evaluations on rule clarity, session management and educational value. Data were analyzed using descriptive statistics, Mann-Whitney U tests and Chi-squared tests, with qualitative feedback examined thematically.
ResultsResidents rated gameplay fluidity significantly higher than students (4.4/5 vs. 4.1/5; p = 0.039). Both groups reported high knowledge mobilization scores (students 4.5/5; residents 4.3/5; p = 0.378). Nearly half perceived some content as exceeding expected knowledge, despite alignment with national standards (47.4% vs. 41.8%; p = 0.482). A greater proportion of students than residents reported difficulties with virological concepts (78.9% vs. 60.3%; p = 0.021), particularly regarding diagnostic methods and viral structures. Supervisors rated the game positively, endorsing its use primarily as a revision tool.Discussion ViroGame is a well-received, effective and engaging tool for teaching medical virology. It promotes active learning, collaboration and knowledge retention while addressing the inherent complexity of virology. Further controlled studies are planned to evaluate its long-term impact on learning outcomes and exam performance.
## Introduction
Teaching medical virology is challenging due to the fundamental concepts that students must acquire in a limited time. Traditional lecture-based teaching methods, while comprehensive, often struggle to maintain student engagement and facilitate long-term retention of knowledge. Research in educational sciences has shown that disengagement in learning environments can lead to reduced motivation, poorer academic performance and increased cognitive fatigue [1] . The issue of student boredom in academic settings is well documented and alternative pedagogical strategies are necessary to promote active participation and better comprehension [2,3].
One innovative approach to improve engagement and learning outcomes in medical education is the use of serious games [4,5]. Gamification, defined as the integration of game elements into non-game contexts, has proven effective across various educational fields including medical and microbiology training where active learning methods are increasingly valued [6][7][8][9]. Examples include AntibioGame®, designed to teach appropriate antibiotic use, and Septris, a simulation game to improve sepsis management, both of which have demonstrated increased student engagement and improved knowledge retention [5,10]. Reviews indicate that combining features in serious games such as scoring, challenges and feedback can significantly improve student participation, motivation and knowledge retention [8,11]. In addition to promoting engagement, these strategies support clinical reasoning by providing safe and interactive environments for practice and reflection [12]. From a theoretical perspective, Cognitive Load Theory (CLT) offers a useful framework for understanding the benefits of serious games. CLT emphasizes managing working memory demands to prevent overload and facilitate the development of long-term knowledge structures. Structured and interactive formats, such as serious games, help reduce excessive cognitive load and promote schema development (i.e., the organization of related knowledge into structured mental frameworks) particularly for novice learners [13,14]. Beyond cognitive considerations, serious games also build on the principles of active learning, which encourage participation and knowledge construction through interactive activities. These approaches have been shown to improve long-term retention and deepen conceptual understanding in medical education [11,15]. For instance, BacteriaGame, designed for medical bacteriology training, demonstrated that interactive learning through gamification enhances engagement and improves knowledge acquisition compared to traditional lectures [12]. Students reported higher motivation, a better understanding of complex bacterial concepts and improved knowledge retention when using the game [12]. ViroGame was developed as an adaptation of BacteriaGame for the specific purpose of virology education. ViroGame aims to turn abstract and technical information into a structured learning experience, bridging the gap between theory and practice. The game's main learning objectives are to help students consolidate fundamental virology concepts, including viral structure, replication mechanisms, diagnostic approaches and therapeutic decision-making. Fundamental concepts of virology are complex but essential to better understand the pathophysiology of infections and the associated diagnostic procedures. Although the diagnosis of these infections generally does not involve the use of antiviral treatment, it helps to discontinue the antibiotic therapy that is often started. Therefore, early knowledge of viruses in medical studies could improve the appropriate use of antibiotics and may prevent the emergence of resistance [10]. A prototype of the ViroGame was presented at the "Journées Francophones de Virologie" in Brussels in April 2024 and at the "Microbes" conference of the French Society for Microbiology (SFM) in October 2024. ViroGame was edited, published and it has been available for purchase since October 2024 (available for purchase (French version, soon to be translated in English and Spanish) on the website of the French Society for Microbiology, link in reference [13]).
This article aims to present the development and evaluation of ViroGame, tailored for learners at different stages of medical training, in different academic settings. The evaluation aimed to assess the game's effectiveness in enhancing virology education by analyzing student engagement, knowledge mobilization and perceived difficulties. On the other hand, we also assessed the supervisors of the game sessions through a questionnaire that focused on their experience with ViroGame. This included evaluating the clarity of the game rules, the ease of supervision, the perceived educational value and the feasibility of integrating the game into virology teaching. Additionally, we explored areas for improvement suggested by participants, such as expanding the virus selection, refining game mechanics and examining the feasibility of integrating ViroGame with BacteriaGame as a unified microbiology educational tool.
## Materials and methods
## Game design
ViroGame was developed for third-year French medical and pharmacy students but can also serve as a revision tool for microbiology and infectious diseases residents. The objective is to facilitate the acquisition and reinforcement of virological knowledge through an engaging and interactive format. Players are invited to associate "virus" cards (Table 1) with corresponding "characteristics" cards (Table 2) and to deduce which viruses other players hold. A total of 20 medically relevant viruses were selected based on their inclusion in the national medical curriculum. These are associated with standardized features including genome structure, transmission mode, clinical manifestations, diagnostics, treatment and vaccine availability. All virological content in the game was reviewed and validated by experts from the Virology Section of the French Society for Microbiology (SFM), with each virus profile individually examined by the national SFM specialist responsible for that specific virus. The content was also aligned with the pedagogical classification used in French medical education, notably for the EDN ("Épreuves Dématérialisées Nationales" or National Digital Exams). The EDN is a nationwide standardized examination introduced in 2023 to assess medical students' theoretical knowledge at the end of the core curriculum (6th year of medical school). This framework distinguishes levels of expected medical knowledge. Viro-Game focuses specifically on:
• Rank A: essential knowledge required for clinical practice and national assessment. • Rank B: additional knowledge offering more in-depth understanding, though not mandatory for all students.
At the beginning of each ViroGame session, players receive two virus cards and draw four characteristics cards. On each turn, they attempt to correctly associate the characteristics with their viruses before drawing new cards. Gameplay proceeds clockwise. Players can also challenge others by guessing their viruses using limited joker tokens. Correct associations and successful challenges earn points, while incorrect ones lead to penalties. A reference booklet summarizing the characteristics of each virus is available to verify associations during the game. Sessions last 30 min (extendable for beginners) and accommodate 3 to 10 players. Bonus questions are included and ranked by difficulty: beginner, basic, and expert. The visual design of the cards highlights key virological features (e.g., envelope structure, transmission route, reservoir), enhancing memorization and cognitive association (Figs. 1, 2 and 3). The questionnaire (Fig. 5) was designed to assess:
## Study design
## Students
• Age, genre, academic level.
• Question 1 (Q1). Binary Yes/No questions regarding whether some virological characteristics were harder to handle than others were. Open-ended fields for students to specify which concepts they found challenging.
• Question 6 (Q6). Integration with BacteriaGame: A Yes/No question on whether the two games could be combined without disrupting the gameplay.
## Supervisors
Twelve supervisors oversaw the sessions (including hospital practitioners (HP), associate professors (AP), university hospital assistants (AHU) and residents) and nine responded to the questionnaire. The questionnaire (Fig. 6) was designed to assess:
• Age, gender, and academic position (HP, AP, AHU, resident). • Question 1 (Q1). Previous experience with BacteriaGame supervision (Yes/No).
• Question 2 (Q2). Clarity of game rules: A Likert scale (1 to 5) was used to evaluate how easy the rules were to explain to students. • Question 3 (Q3). Ease of session management/ supervision: Assessed on a Likert scale (1 to 5). • Question 4 (Q4). Student engagement: Did students quickly grasp the game mechanics? (Likert scale 1 to 5). • Question 5 (Q5). Perceived educational value:
Likert scale (1 to 5) evaluating whether the game helps students mobilize virology knowledge. Open-ended responses on the game's strengths and weaknesses as a teaching tool.
• Question 6 (Q6). Potential integration of ViroGame into virology courses (Yes/No).
## If Yes, in what context?
As a replacement for tutorial sessions.
As a revision session (after lectures and tutorials).
• Question 7 (Q7). Combination with BacteriaGame: Do you think both games could be merged? (Yes/ No). If Yes, suggestions for how to integrate them. • Question 8 (Q8). Suggestions for improvement:
Open-ended responses on ways to enhance ViroGame or improve session management.
## Data analysis
• Likert scale responses were analyzed using mean score calculations to assess:
Game mechanics fluidity. Perceived relevance to virology education. Difficulty of specific virological concepts.
• Yes/No questions were summarized in percentage distributions.
## Results
## Students evaluation results
The responses to the questionnaires from the 266 students were included in the study. Respondents were 208 third-year medical students and 58 residents (53 residents in microbiology, 5 in infectiology). The average age of third-year students was 21.0 years, while the average age for residents was 26.2 years. In terms of gender distribution, 65.3% of third-year students and 54.5% of residents were women (Table 3). Among the participants, 6.7% of third-year students (14/208) and 29.3% of residents (17/58) reported having prior experience with Bac-teriaGame (Q1) (Table 4; Fig. 7). The fluidity of game mechanics (Q2) was rated 4.1/5 by third-year students and 4.4/5 by residents. The game's ability to mobilize virology knowledge (Q3) scored 4.5/5 for third-year students and 4.3/5 for residents. Additionally, 47.4% (92/194) of third-year students and 41.8% (23/55) of interns reported that some concepts exceeded expected knowledge levels (Q4), while 78.9% (157/199) of third-year students and 60.3% (35/58) of residents found certain viral characteristics or card categories challenging (Q5), particularly those related to diagnostic methods, virus structure (enveloped vs. non-enveloped virus, RNA vs. DNA) and transmission pathways (Table 4; Figs. 7 and8). Very few students responded (n = 12 for third-year However, for open-ended Q5 (difficulties encountered with the game), 33.4% (89/266) participants provided a response, while 64.4% (172/266) did not respond or explicitly stated they had no difficulties. For Q6, the majority of participants supported integrating ViroGame with BacteriaGame, with 86.5% of students and 91.4% of residents responding "Yes. " (Table 4; Fig. 7).
Statistical comparisons were conducted to assess differences in responses between third-year medical students and residents. Residents were significantly more likely to have prior experience with BacteriaGame (Q1: 29.3% vs. 6.7%; χ² = 20.66, p < 0.001, Chi-squared test).
Residents rated the fluidity of gameplay (Q2) higher than students (mean 4.4 vs. 4.1; p = 0.007, Mann-Whitney U test). In contrast, students gave significantly higher ratings for the game's ability to mobilize virology knowledge (Q3) compared to residents (mean 4.5 vs. 4.3; p = 0.004, Mann-Whitney U test). Regarding the perception that some content exceeded expected knowledge (Q4), no significant difference was found between students and residents (47.4% vs. 41.8%; χ² = 0.34, p = 0.56, Chi-squared test). However, a significantly larger proportion of students reported encountering difficulties with certain virological concepts (Q5) compared to residents (78.9% vs. 60.3%; χ² = 7.23, p = 0.007, Chi-squared test). For Q6, both groups expressed strong support for integrating ViroGame with BacteriaGame, with 86.5% of students and 91.4% of residents responding "Yes, " and no statistically significant difference observed between the groups (χ² = 0.83, p = 0.36, Chi-squared test).
The main difficulties reported by third-year students were related to virus identification and diagnostic aspects (15 mentions), including challenges in associating viruses with their corresponding characteristics and interpreting diagnostic clues. Additionally, 10 mentions highlighted difficulties with card interactions, suggesting that some players struggled with understanding specific game elements or their relationships. Structural and genomic aspects were reported as a challenge by 4 third-year students. Among residents, 20 mentions focused on viral structure and genome, particularly regarding the differentiation of enveloped and non-enveloped viruses. Specific viruses such as Parvovirus B19 and Dengue virus were also cited as difficult by 4 residents.
Open-ended responses Q7 and Q8 highlighted an interest in adding additional viruses, with 37 virus suggestions recorded across both groups: HHV-8 (n = 14), HHV-6 (n = 13), Ebola (n = 6), Zika virus (n = 7), Chikungunya and HTLV (n = 4), Adenovirus (n = 3), Influenza virus (n = 2), West Nile Virus (n = 2), Astrovirus (n = 2), Marburg virus (n = 1), MERS-CoV (n = 1). Residents also suggested a digital adaptation of the game, while thirdyear students emphasized the need for clearer rules. Finally, 5.6% (15/266) participants left unsolicited positive feedback such as "perfect, release the game, I want to play it!", "fun way to learn", "great for revision!", and "good but quite challenging, you need to know your course well". These comments highlight the positive reception of the game and its perceived value in engaging students, reinforcing virology concepts and making learning enjoyable.
## Supervisor evaluation results
The responses from the 9 supervisors were included in the study. Their evaluation of ViroGame provided positive feedback on both the clarity of the game and its educational impact. The average age of the supervisors was 33.8 years, with varying levels of teaching experience in virology: four supervisors had more than eight years of experience, three had between one and four years of experience, and two had no prior experience in virology teaching. Additionally, five out of nine supervisors had previously supervised BacteriaGame. The supervisors found the rules clear and easy to explain, rating them 3.9/5. The management of a ViroGame session was considered relatively easy, with a score of 4.4/5. Regarding student engagement, they rated how easily students grasped the game mechanics at 4.2/5. In terms of pedagogical effectiveness, the supervisors agreed that Viro-Game effectively mobilizes virology knowledge, awarding it an average score of 4.1/5. They unanimously supported the integration of ViroGame into virology courses (100% approval). When asked about the best way to integrate ViroGame into curricula, seven supervisors suggested using it as a revision tool, while two recommended replacing tutorial sessions with the game. Building on this positive feedback, supervisors also offered suggestions to further enhance ViroGame and optimize its use in virology education. To improve gameplay dynamics, they recommended increasing the number of Joker cards to boost student engagement, particularly for those with limited virology knowledge. Some also proposed introducing new mechanics, such as allowing players to exchange virus characteristics, to encourage deeper reasoning. Regarding the potential integration with Bacte-riaGame, supervisors advised maintaining separate card decks to ensure clarity while balancing the inclusion of both viruses and bacteria. They also noted that while non-virology experts can lead the game, prior training or co-facilitation with a virology expert would maximize its educational impact.
## Discussion
Serious games have increasingly been recognized as effective tools in medical education, promoting engagement, motivation, and active learning [4,8]. To date, only a limited number of gamified interventions have been developed for microbiology, and even fewer for virology. This scarcity of comparable tools underlines the innovative contribution of ViroGame in addressing a clear gap in virology education. In this study, ViroGame was positively received by both third-year medical students and clinical biology residents, underlining its perceived educational value across different academic levels. Residents rated the fluidity of game mechanics significantly higher than students (4.4 vs. 4.1; p = 0.039, Mann-Whitney U test), a difference likely explained by their greater familiarity with BacteriaGame (29.3% vs. 6.7%; p < 0.001, Chisquared test) [12]. This prior exposure may have enabled them to adapt more easily to ViroGame's format, focusing on virological content rather than on the mechanics themselves. In contrast, third-year students, less accustomed to this type of activity, may have required more time to adjust, which could explain their slightly lower ratings. Nevertheless, both groups gave high scores for the game's ability to consolidate virology knowledge (4.5 vs. 4.3; p = 0.378, Mann-Whitney U test), confirming its effectiveness as a learning tool.
From a theoretical perspective, these findings are consistent with cognitive load theory (CLT), which emphasizes the importance of managing working memory demands to prevent overload and support the development of long-term knowledge structures (15). Viro-Game's structured gameplay, supported by visual aids and guided associations, likely reduced unnecessary cognitive demands and optimized intrinsic load, enabling learners to better integrate complex virological concepts. Beyond CLT, the interactive nature of the game also reflects the principles of active learning, which have been shown to improve long-term retention and deepen conceptual understanding [11,15].
Interestingly, nearly half of the participants reported that some concepts exceeded their expected knowledge level (47.4% of students vs. 41.8% of residents; p = 0.482, Chi-squared test). Yet, all content included in the game corresponded to Rank A or B in the French EDN framework, suggesting that this perception may stem from a lack of familiarity with the classification system rather than content design. Similarly, a significantly higher proportion of third-year students reported difficulties with certain virological concepts compared to residents (78.9% vs. 60.3%; p = 0.021, Chi-squared test). These challenges primarily concerned diagnostic methods, viral structure and transmission pathways. This likely reflects residents' more advanced virology knowledge, highlighting the inherent complexity of the subject for less advanced learners rather than flaws in the game's design.
Despite these challenges, 33.4% of participants provided specific qualitative feedback, indicating that students often struggled with virus identification and card interactions, while residents more frequently mentioned difficulties distinguishing enveloped from non-enveloped viruses. These findings underline the potential of integrating ViroGame into both third-year practical sessions and resident revision programs, where structured repetition could help strengthen retention and application.
Our results are consistent with prior evidence that serious games can equal or even surpass traditional teaching methods in knowledge acquisition and learner engagement [16,17]. Games that combine assessment features such as scoring or feedback with challenge elements like competition or limited resources are particularly effective in sustaining attention and improving learning outcomes [8]. ViroGame appears to leverage these mechanisms successfully, offering a safe and interactive environment where learners can apply knowledge, test ideas and learn from mistakes. Support for integrating ViroGame with BacteriaGame was strong across both groups (86.5% of students vs. 91.4% of residents; p = 0.341, Chi-squared test), reinforcing the relevance of a unified gamified microbiology tool regardless of training level.
Supervisors confirmed its educational value, reporting that the rules were clear, sessions easy to manage and students quickly engaged. They recommended using the game primarily as a revision tool, especially for beginners and suggested minor adjustments such as increasing the number of Joker tokens to enhance inclusivity.
While promising, this study has limitations. Participation was voluntary, which may have introduced selection bias. Outcomes were based on self-reported perceptions rather than objective knowledge assessments and no control group or longitudinal follow-up was included to measure knowledge retention over time. Future studies should address these limitations by including pre-and post-tests, controlled comparisons and longer-term evaluations, particularly regarding the potential impact of ViroGame on exam performance.
Altogether, our findings indicate that ViroGame is a valuable complement to traditional virology teaching methods, effectively reinforcing key concepts through an engaging, student-centered approach. Planned developments, including expanding virus coverage, translating the game into English and Spanish, and designing a digital version, could further broaden its accessibility and pedagogical impact.
## Conclusion
ViroGame demonstrates strong potential as an innovative and engaging tool for teaching medical virology. By promoting active learning, critical thinking and peer collaboration, it complements traditional teaching methods and helps address the inherent complexity of virology. Further controlled studies are planned to evaluate its long-term impact on learning outcomes and exam performance.
## References
1. Ferrière, Morin-Messabel, L'ennui (2012) "En contexte scolaire: effets de variation et typologie de représentations Chez Les futurs professeurs des écoles, Selon Le Sexe de l'élève et son Niveau scolaire" *Bull Psychol*
2. Lavrijsen, Camerman, Kuppens et al. (2025) "Who likes the going when the going gets tough? Need for cognition moderates associations between class difficulty and students' engagement" *J Educ Psychol*
3. Muñoz-Losa, Corbacho-Cuello (1007) "Impact of interactive science workshops participation on primary school children's emotions and attitudes towards science" *Int J of Sci and Math Educ*
4. Garris, Ahlers, Driskell (2002) "Games, Motivation, and learning: A research and practice model" *Simul Gaming*
5. Evans, Daines, Tsui et al. (2015) "Septris: a novel, mobile, online, simulation game that improves sepsis recognition and management" *Acad Med J Assoc Am Med Coll*
6. Ghelfenstein-Ferreira, Beaumont, Dellière et al. (2021) "An educational game evening for medical residents: A proof of concept to evaluate the impact on learning of the use of games" *J Microbiol Biol Educ*
7. Gorbanev, Agudelo-Londoño, González et al. (2018) "A systematic review of serious games in medical education: quality of evidence and pedagogical strategy" *Med Educ Online*
8. Van Gaalen, Brouwer, Schönrock-Adema et al. (2021) "Gamification of health professions education: a systematic review" *Adv Health Sci Educ Theory Pract*
9. Walker, Heudebert, Patel et al. (2022) "Leveraging technology and gamification to engage learners in a microbiology curriculum in undergraduate medical education" *Med Sci Educ*
10. Tsopra, Courtine, Sedki et al. (2020) "AntibioGame®: A serious game for teaching medical students about antibiotic use" *Int J Med Inf*
11. Freeman, Eddy, Mcdonough et al. (2014) "Active learning increases student performance in science, engineering, and mathematics" *Proc Natl Acad Sci*
12. Pineros, Tenaillon, Marin et al. (2023) "Using gamification to improve engagement and learning outcomes in medical microbiology: the case study of 'BacteriaGame'" *FEMS Microbiol Lett*
13. Virogame, Société Française De Microbiologie (2025)
14. Si (2024) "Using cognitive load theory to tailor clinical reasoning training for preclinical medical students" *BMC Med Educ*
15. Prince (2004) "Does active learning work? A review of the research" *J Eng Educ*
16. Gentry, Gauthier, Ehrstrom et al. (2019) "Serious gaming and gamification education in health professions: systematic review" *J Med Internet Res*
17. Krishnamurthy, Selvaraj, Gupta et al. (2022) "Benefits of gamification in medical education" *Clin Anat*
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# Characterization of near-complete hepatitis E virus genomes of genotype 1e and 4b detected from humans in Cameroon
Abdou Modiyinji, Pierre Cappy, Arnaud Ly, Aristide Mounchili-Njifon, Moise Henri, Yifomnjou Moumbeket, Huguette Simo, Abanda Ngu, Richard Njouom
## Abstract
Hepatitis E virus (HEV) is an important public health concern, especially in developing countries. Complete genomes of HEV strains circulating in Cameroon are not available. Here, we report five nearly complete strains of HEV in Cameroon. These strains share a high identity with human African and swine Asian isolates.
KEYWORDS hepatitis E virus, genome, genotype, CameroonH epatitis E virus (HEV) is probably the most common cause of acute hepatitis in humans worldwide (1). HEV is a single-stranded, positive-sense RNA virus with a genome size of approximately 7.2 kb (2). Human HEV belongs to the genus Paslahepe virus, subfamily Orthohepevirinae, and the family Hepeviridae. The members of species Paslahepevirus balayani have been classified into eight genotypes (HEV-1 to 8), of which five are well recognized as human pathogens (HEV-1 to 4 and HEV-7) (2). HEV-1 and 2 are transmitted by the fecal-oral route and are responsible for significant waterborne outbreaks in developing countries (2). HEV-3 and 4 are mainly transmitted zoonotically and are responsible for sporadic infections in developed countries (2). HEV-7 was associated with chronic infection in a liver transplant recipient from the Middle East (3). Some of these eight genotypes can be divided into subtypes (4).It has been reported that HEV-1e was responsible for a large outbreak in sub-Saharan Africa (5). However, prior to our recent study (6), HEV-4b strain has never been reported in Africa. To date, no complete HEV genome is available from Cameroon. We report the near full-length genome sequences of an HEV-1e and HEV-4b from Cameroon. The viruses were detected in our previous study from icteric patients suspected of having yellow fever in two regions of Cameroon (6). Plasma samples from these patients were negative for yellow fever virus, and molecular tests using partial sequencing of the ORF2 region identified HEV-1e and 4b. We selected five plasma samples collected in 2022 for complete genome characterization using metagenomics followed by hybridcapture enrichment, as previously described (7). Briefly, total nucleic acid extractions were performed using the QIAsymphony DSP DNA Midi kit (Qiagen, Hilden, Germany), according to the manufacturer's instructions. From the extracted nucleic acids, we performed cDNA synthesis, tagmentation, PCR indexing, purification, and normalization of the libraries produced. Then, we proceeded to the hybridization of biotinylated capture probes and to the capture of probe-library hybrids using magnetic beads coupled with streptavidin. After washing and elution, we proceeded to the re-amplification of the libraries and the clean-up of the final library. Mixed DNA/RNA libraries were sequenced on a NovaSeq 6000 sequencer (Illumina). The raw data were demulti plexed using BCLConvert on a Dragen server, and Fastq files were then analyzed on the BaseSpace cloud (Illumina), using Dragen Microbial Enrichment Plus software, to obtain HEV consensus sequences.
A total of five near-complete sequences were obtained. Three strains form a cluster with African HEV-1e strains (Fig. 1). These HEV-1e strains shared the highest identity (>95%) with the NG/17-0503 strain from Nigeria. Our strains have been identified in the Far North region of Cameroon, bordering Nigeria. This observation strongly suggests cross-border circulation of this virus. Two strains shared the highest identity (>95%) with the HEV-4b strains identified in swines in China (Fig. 1). This observation reinforces the hypothesis of zoonotic transmission of HEV in Cameroon (Table 1). In conclusion, these five near-complete HEV genomes from Cameroon will be an important resource for future epidemiological research in Africa.
## References
1. Aslan, Balaban (2020) "Hepatitis E virus: epidemiology, diagnosis, clinical manifestations, and treatment" *World J Gastroenterol*
2. Purdy, Drexler, Meng et al. (2022) "ICTV virus taxonomy profile: Hepeviridae 2022" *J Gen Virol*
3. Lee, Tan, Teo et al. (2016) "Chronic infection with camelid hepatitis E virus in a liver transplant recipient who regularly consumes camel meat and milk" *Gastroenterology*
4. Smith, Izopet, Nicot et al. (2020) "Update: proposed reference sequences for subtypes of hepatitis E virus (species Orthohepevirus A)" *J Gen Virol*
5. Akanbi, Harms, Wang et al. (2017) "Complete genome sequence of a hepatitis E virus genotype 1e strain from an outbreak in Nigeria"
6. Modiyinji, Tankeu, Monamele et al. (2024) "Hepatitis E virus infections among patients with acute febrile jaundice in two regions of Cameroon: first molecular characteriza tion of hepatitis E virus genotype 4" *PLoS One*
7. Gendreau, Coupry, Cappy et al. (2025) "Severe parvovirus B19 infection in patients with sickle cell disease hospitalized in intensive care unit. Blood Adv:bloodadvan ces"
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https://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC12697092&blobtype=pdf
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# Whole-genome sequencing data from long-term serial passaging of 11 SARS-CoV-2 isolates
Charles Foster, Gregory Walker, Tyra Jean, Maureen Wong, Sonia Isaacs, Yonghui Lyu, William Rawlinson
## Abstract
Serial passaging is useful for investigating the evolutionary trajectory of viruses in vitro, allowing comparison with evolutionary trends in the real-world human population. We announce here a 2020-2023 longitudinal data set comprising ampliconbased whole-genome sequencing from 11 severe acute respiratory syndrome coronavi rus 2 (SARS-CoV-2) isolates carried through a range of 33-100 passages.KEYWORDS SARS-CoV-2, whole-genome sequencing, serial passaging W e recently investigated the accumulation of mutations in SARS-CoV-2 (Corona viridae: Betacoronavirus) in a long-term serial passaging study, scanning for any instances of convergent evolution among passage lines and compared to global clinical isolates (1). Eleven isolates of SARS-CoV-2 were selected, representing nine distinct SARS-CoV-2 lineages, ranging from earlier (A.2.2) to later (Omicron: BA.1) in the coronavirus disease 2019 (COVID-19) pandemic, prioritizing variants of concern and variants under investigation, as designated by the World Health Organization. Isolates originated from remnant human nasopharyngeal swabs collected during routine diagnostic testing in the Southeastern Sydney Local Health District, NSW, Australia. After spin-filtration of swabs in virus-transport media, 100 µL of virus-containing flow-through was used to inoculate Vero E6 cells (ECACC #85020206) maintained in Gibco Minimum Essential Medium (Thermo Fisher, Massachusetts, USA) supplemented with 10% fetal bovine serum and 1× penicillin-streptomycin-glutamine (MEM-10), and incubated at 37°C, 5% CO 2 . Each passage interval spanned 3-4 days until cytopathic effect was observed, then harvested cultured virus inoculated the next passage, described fully in reference 1. The goal was a minimum of 33 serial passages per passage line, with earlier passage lines continued further (e.g., B.1.319: 100 passages).Our whole-genome sequencing strategy was (where possible) to sequence the original clinical isolate (passage 0), passages 1-6, then every third passage onward. Some passage 0 samples were from urgent clinical cases sequenced via rapid Oxford Nanopore Technology approaches, but this Announcement focuses on the remaining majority short-read sequencing data, generated as described previously (1, 2). Briefly, nucleic acids were extracted using the MagNA Pure 96 system (Roche Diagnostics, Mannheim, Germany); RNA extracts were reverse-transcribed with the SuperScript IV VILO Master Mix (Thermo Fisher); cDNA was amplified using 1,200 nt tiled amplicons per the "Midnight" protocol (3); amplicon products were prepared for short-read sequencing using the Illumina DNA Prep Kit (Illumina, San Diego, CA, USA); and 150 bp paired-end sequencing was conducted using an Illumina Miseq (Reagent Kit v.2). Each of these steps was conducted as per the respective manufacturers' protocols. The resulting 231 sets of paired-end sequencing reads were analyzed using an in-house bioinformatics pipeline with default parameters (4), as described in reference 1, yielding a mean genome coverage of >99%, sequencing depth of ~1,372×, and ~279,000 (range: 11,533-731,494) reads per sample, with relative consistency among passage lines (Fig. 1).
Following the trajectory of mutations within these data longitudinally reveals important insights into pathogen evolution and broader evolutionary mechanisms, such as convergent evolution, adaptation, and genetic drift (1). For example, many mutations SRR26083382). All metrics were estimated using the default parameters of an in-house bioinformatics pipeline (4), with low quality sequencing reads and residual sequencing adapters removed using fastp v.0.23.2 (5), read mapping against the SARS-CoV-2 reference genome (NC_045512.2: 29903 nt, ~38% GC) performed using bwa mem v.0.7.17-r1188 (6), soft clipping of amplicon primer regions using ivar v.1.3.1 (7), and genome coverage estimation using bedtools v.2.30.0 (8). Labels on the x-axis refer to in-house identifiers for passage lines, matching those given to the sets of sequencing reads uploaded to National Center for Biotechnology Information's Sequence Read Archive (PRJNA1018257). that arose de novo throughout serial passaging are known to drive changes in cell entry mechanisms (9), especially in Vero E6 cells (10), and are linked to clinically significant phenomena like altered therapeutic effectiveness (11). Additionally, we demonstrated that SARS-CoV-2 can be passaged up to 100 times without any obvious signs of impaired fitness or attenuation (1). We anticipate that these sequencing data will be a useful resource for the microbiology community interested in SARS-CoV-2 evolution and experimental evolution more generally.
## References
1. Foster, Walker, Jean et al. (2025) "Long-term serial passaging of SARS-CoV-2 reveals signatures of convergent evolution" *J Virol*
2. Foster, Stelzer-Braid, Deveson et al. (2022) "Assessment of inter-laboratory differences in SARS-CoV-2 consensus genome assemblies between public health laboratories in Australia"
3. Freed, Vlková, Faisal et al. (2020) "Rapid and inexpensive whole-genome sequencing of SARS-CoV-2 using 1200 bp tiled amplicons and Oxford nanopore rapid barcoding" *Biol Methods Protoc*
4. Foster (2023) "Covid-illumina-snakemake: a pipeline to facilitate genomic surveillance of SARS-CoV-2"
5. Chen, Zhou, Chen et al. (2018) "Fastp: an ultra-fast all-in-one FASTQ preprocessor" *Bioinformatics*
6. Li (2013) "Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM"
7. Grubaugh, Gangavarapu, Quick et al. (2019) "An amplicon-based sequencing framework for accurately measuring intrahost virus diversity using PrimalSeq and iVar" *Genome Biol*
8. Quinlan, Hall (2010) "BEDTools: a flexible suite of utilities for comparing genomic features" *Bioinformatics*
9. Escalera, Gonzalez-Reiche, Aslam et al. (2022) "Mutations in SARS-CoV-2 variants of concern link to increased spike cleavage and virus transmission" *Cell Host Microbe*
10. Ogando, Dalebout, Zevenhoven-Dobbe et al. (2020) "SARS-coronavirus-2 replication in Vero E6 cells: replication kinetics, rapid adaptation and cytopathology" *J Gen Virol*
11. Wang, Zhou, Muecksch et al. (2022) "Memory B cell responses to Omicron subvariants after SARS-CoV-2 mRNA breakthrough infection in humans" *J Exp Med*
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https://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC12697201&blobtype=pdf
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# Complete genome sequence of a highly pathogenic H5N1 avian influenza virus from recent poultry outbreak in Bangladesh
Raduyan Farazi, Md Touki, Tahamid Tusar, Chonda Roy, Roni Mia, Anandha Mozumder, Anupam Das, Jebin Tasmin, S Nazmul Hasan, Md Alam, Sharmin Akter, Sukumar Saha, Tofazzal Islam, Md Golzar Hossain, Md Hossain
## Abstract
Highly pathogenic avian influenza virus (H5N1) continues to cause substantial losses in the poultry industry of Bangladesh, with ongoing genetic evolution. This report presents the complete genome sequence of an H5N1 subtype of avian influenza A virus isolated from a recent outbreak on a commercial layer chicken farm in Bangladesh.KEYWORDS highly pathogenic avian influenza virus, H5N1 subtype, complete genome, Bangladesh A vian influenza A viruses (AIVs) are significant pathogens causing respiratory infections in birds and humans (1). They belong to the family Orthomyxoviridae and have a segmented, single-stranded, negative-sense RNA genome (2) comprising eight segments that encode 10 or 11 proteins (2). AIVs are classified into 19 hemagglutinin and 11 neuraminidase subtypes (3). In Bangladesh, highly pathogenic avian influenza H5N1 and low-pathogenic avian influenza H9N2 dominate in chickens; novel H5N1 reassortants highlight the need for whole-genome sequencing-based surveillance to track viral evolution (4-6).In this study, nine chickens from commercial layer farms in Gazipur, Bangladesh, were collected during a suspected AIV outbreak, exhibiting respiratory and gastroin testinal signs. Brain tissues were collected from dead chickens, and 10% tissue homo genates were prepared in phosphate-buffered solution. RNA was extracted using the QIAamp Viral RNA Mini Kit (Qiagen, Hilden, Germany), and cDNA was synthesized using the PrimeScript II 1st Strand cDNA Synthesis Kit (Takara Bio Inc., Shiga, Japan), with random hexamers. Samples were screened using reverse transcription PCR (RT-PCR) with both universal and H5N1-specific primers (7-9). An H5N1 strain was isolated from one representative positive sample by inoculating 10-day-old embryonated chicken eggs via the allantoic cavity and incubating at 37°C for 72 hours (10,11).Genomic RNA was extracted from allantoic fluid containing the single virus isolate, and cDNA synthesis and RT-PCR were performed following established protocols (12). The complete genome was sequenced using the Oxford Nanopore MinION platform. Amplicons were purified from the RT-PCR amplified products with AMPure XP magnetic beads (a 0.7× bead-to-sample ratio removed shorter products and residual primers) (12) without further gel-or instrument-based size selection. Libraries were prepared using the Oxford Nanopore Native Barcoding Kit 96 v.14 (SQK-NBD114.96) according to the manufacturer's instructions, quantified using the Qubit 1× dsDNA Broad Range Assay Kit and Qubit 4 Fluorometer (Invitrogen), and approximately 50 fmol of DNA was loaded onto an R10.4.1 flow cell (FLO-MIN114) using the MinION MK1C (12). Real-time base calling was performed using Guppy v.4.3.4 (13) in MinKNOW (fast base-calling mode), which also handled demultiplexing. Quality filtering used a default Q score threshold
of 8. Barcode adapters were trimmed using Porechop v.0.2.3 (https://github.com/rrwick/ Porechop).
The sequencing run yielded a total of 250,000 raw reads. High-quality reads were assembled into consensus sequences using IRMA v.1.2.0 FLU module (auto-selected, reference-guided approach) which meticulously captured 5′ and 3′ terminal ends (14,15). The average sequencing coverage across all eight segments of the genome was determined to be greater than 1,000×. The genes were identified and annotated using IRMA's built-in alignment features, which align assembled contigs to reference sequences (14)(15)(16). The pipeline addresses viral variation by iteratively optimizing read gathering and enabling "on-the-fly" reference editing and correction, thereby increasing read depth and breadth without the need for additional reference selection. Default parameters were used for all software unless otherwise noted.
This virus is a reassortant subtype of H5N1 with the PB1 segment of H9N2, consistent with previous reports (17,18) with genome size 13,076 bp in length, comprising eight segments (Table 1). The complete genome sequence of this H5N1 avian influenza virus from a recent outbreak in Bangladesh will contribute to ongoing surveillance efforts and enhance the understanding of the virus's genetic evolution, supporting the development of effective control strategies.
## References
1. Zhang, Lei (2024) "The Alarming situation of highly pathogenic avian influenza viruses in 2019-2023" *Global Medical Genetics*
2. Sangsiriwut, Uiprasertkul, Payungporn et al. (2018) "Complete genomic sequences of highly pathogenic H5N1 avian influenza viruses obtained directly from human autopsy specimens" *Microbiol Resour Announc*
3. Luczo, Spackman (2025) "Molecular evolution of the H5 and H7 highly pathogenic avian influenza virus haemagglutinin cleavage site motif" *Rev Med Virol*
4. Goraichuk, Risalvato, Pantin-Jackwood et al. (2024) "Improved influenza A whole-genome sequencing protocol" *Front Cell Infect Microbiol*
5. Hassan, Dutta, Islam et al. (2023) "The one health epidemiology of avian influenza infection in Bangladesh: lessons learned from the past 15 years" *Transbound Emerg Dis*
6. Nooruzzaman, Mumu, Hasnat et al. (2019) "A new reassortant clade 2.3.2.1a H5N1 highly pathogenic avian influenza virus causing recent outbreaks in ducks, geese, chickens and turkeys in Bangladesh" *Transbound Emerg Dis*
7. Cattoli, Drago, Maniero et al. (2004) "Comparison of three rapid detection systems for type A influenza virus on tracheal swabs of experimentally and naturally infected birds" *Avian Pathol*
8. Islam, Haque, Giasuddin et al. (2012) "New introduction of clade 2.3.2.1 avian influenza virus (H5N1) into Bangladesh" *Transbound Emerg Dis*
9. Fouchier, Bestebroer, Herfst et al. (2000) "Detection of influenza A viruses from different species by PCR amplification of conserved sequences in the matrix gene" *J Clin Microbiol*
10. Vreman, Kik, Germeraad et al. (2023) "Zoonotic mutation of highly pathogenic avian influenza H5N1 virus identified in the brain of multiple wild carnivore species" *Pathogens*
11. Khatun, Giasuddin, Islam et al. (2013) "Surveillance of avian influenza virus type A in semi-scavenging ducks in Bangladesh" *BMC Vet Res*
12. Miah, Hossain, Hasan et al. (2023) "Culture-independent workflow for nanopore MinION-based sequencing of influenza A virus" *Microbiol Spectr*
13. Technologies (2023)
14. Shepard, Meno, Bahl et al. (2016) "Viral deep sequencing needs an adaptive approach: IRMA, the iterative refinement meta-assembler" *BMC Genomics*
15. Nabakooza, Pastusiak, Kateete et al. (2022) "Whole-genome analysis to determine the rate and patterns of intra-subtype reassortment among influenza type-A viruses in Africa" *Virus Evol*
16. Lee (2020) "Complete genome sequencing of influenza A viruses using next-generation sequencing"
17. Monne, Yamage, Dauphin et al. (2013) "Reassortant avian influenza A(H5N1) viruses with H9N2-PB1 gene in poultry" *Bangladesh. Emerg Infect Dis*
18. Marinova-Petkova, Shanmuganatham, Feeroz et al. (2013) "The continuing evolution of H5N1 and H9N2 influenza viruses in Bangladesh between"
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# Near-complete genome sequences of a rice necrosis mosaic virus isolate infecting rice in Argentina
V Solís, M Bangratz, M Brugo Carivali, A Comte, C Luciani, S Lacombe, M Fontana, D Filloux, M Pachecoy, E Fernandez, P Dirchwolf, J Ayala, C Julian, R Kruger, E Hébrard, F Fernandez, M Perotto, P Roumagnac, S Gutiérrez, N Poulicard, M Celli
## Abstract
While rice necrosis mosaic virus (RNMV) has only been described in Asia, we identified this virus on a rice plant from Argentina using a viral metagenomic approach. We further confirmed this result by RT-PCR and small-RNA Illumina sequencing to obtain the near-complete genome and to confirm actual infection by RNMV.
A mong the viruses reported to infect rice worldwide, only rice hoja blanca virus (species Tenuivirus oryzalbae, family Phenuiviridae), rice stripe necrosis virus (RSNV; Benyvirus oryzae, Benyviridae), and Mal de Rio Cuarto virus (Fijivirus cuartoense, Spinareo viridae) have been reported in South America (1,2). In this study, we used a virion-associ ated nucleic acids, Illumina HiSeq (2×150-nucleotide paired-end reads) approach (3-5) on twelve symptomatic rice (Oryza sativa) plants collected in 2018 in the provinces of Corrientes and Santa Fe. A total of 3,780,924 trimmed reads generated by Illumina sequencing (from 34,418 to 580,084 reads per sample) were de novo assembled using CAP3 (6) and viral contigs were identified by BLASTn and BLASTx. We detected RSNV in two samples from plants with necrosis, wrinkled leaves, and panicle deformation. From one plant sample (Arg1) showing necrotic leaves and collected at Berón de Astrada (Corrientes), we obtained 87 contigs up to 1,946 nucleotides in size and sharing a mean of 93.4% nucleotide identity with the rice necrosis mosaic virus (RNMV; Bymovirus oryzae, Potyviridae) reference genome (LC055681.1 and LC060925.1 for RNA1 and RNA2, respectively) characterized in Japan (7). RNMV infection was confirmed after total RNA extraction with TRIzol Reagent (Thermo Fisher Scientific) according to the manufactur er's protocol, RT-PCR using specific primers (RNMV-R1-F-5′ and RNMV-R1-R-3′ (8) and Sanger sequencing of the 613 bp amplicon. Small RNA (sRNA) library preparation (NEB Next Multiplex Small-RNA Library Prep Set) and Illumina sequencing (NovaSeq 6000 SP Reagent Kit, SE50) was performed by Novogene on the same RNA extraction. In the 18nt-28 nt size fraction, we obtained 25,326,985 trimmed reads, of which 110,304 reads (i.e. 0.44%) mapped to the RNMV reference genome with Geneious v.9.1 (Biomat ters). De novo assembly was performed using Bowtie1.3.1 and Samtools1.18 to obtain the near-complete genome of the RNMV isolate Arg1 (RNA1: 7126 nucleotides, mean coverage of 285.9, 202.5 sense, and 83.5 antisense; RNA2: 3587nt, mean coverage of 364.7, 232.3 sense, and 132.4 antisense; Fig. 1A andB) characterized by a G + C content of 44.2% and 41.7% for RNA1 and RNA2. Among the 18-28nt sRNAs mapped to RNMV, a predominance of 21nt and 22nt sRNAs was observed (Fig. 1C), which is consistent with the production of small interfering (si)RNAs resulting from the gene silencing defense mechanism set up by plant cells in response to RNA virus infection (9). The Arg1 genome showed high nucleotide (nt) and amino acid (aa) identities with RNMV (nt: 79.5% and 95.1%; aa: 93.7%, and 96.9%; for RNA1 and RNA2, respectively) and much lower with other species of the genus Bymovirus (nt: >61.4% and >65.4%; aa: >55.0% and >37.4%; for RNA1 and RNA2, respectively). These results were supported by phylogenetic reconstructions (Fig. 1D andE). Specifically, the coat protein of the Arg1 isolate shared respectively 81.4% and 94.7% nt identity with LC055681.1 and U95205, the only two RNMV sequences deposited in the GenBank database (7,11), 91.3% and 99.0% at the aa level. These values exceed the species demarcation threshold established for the family Potyviridae (12). Thus, while RNMV has only been reported in Asia (1,7,11,13), our results demonstrate that this virus is also present in rice fields in Argentina.
## References
1. Wang, Liu, Lyu et al. (2022) "A review of vector-borne rice viruses" *Viruses*
2. Solís, Luciani, Carivali et al. (2023) "First report of Mal de Rio Cuarto virus and a picorna-like virus naturally infecting rice (Oryza sativa) in Argentina" *Plant Disease*
3. François, Filloux, Frayssinet et al. (2018) "Increase in taxonomic assignment efficiency of viral reads in metagenomic studies" *Virus Res*
4. Moubset, François, Maclot et al. (2022) "Virion-associated nucleic acid-based metagenomics: a decade of advances in molecular characterization of plant viruses" *Phytopathology*
5. Palanga, Filloux, Martin et al. (2016) "Metagenomic-based screening and molecular characterization of cowpea-infecting viruses in Burkina Faso" *PLoS One*
6. Huang, Madan (1999) "CAP3: a DNA sequence assembly program" *Genome Res*
7. Wagh, Kobayashi, Yaeno et al. (2016) "Rice necrosis mosaic virus, a fungal transmitted bymovirus: complete nucleotide sequence of the genomic RNAs and subgrouping of bymoviruses" *J Gen Plant Pathol*
8. Mdm, Nakamura, Ichikawa et al. (2015) "Overexpression of OsHAP2E for a CCAAT-binding factor confers resistance to cucumber mosaic virus and rice necrosis mosaic virus" *J Gen Plant Pathol*
9. Pooggin (2018) "Small RNA-omics for plant virus identification, virome reconstruction, and antiviral defense characterization" *Front Microbiol*
10. Kumar, Stecher, Suleski et al. (2024) "MEGA12: molecular evolutionary genetic analysis version 12 for adaptive and green computing" *Mol Biol Evol*
11. Badge, Kashiwazaki, Lock et al. (1997) "A bymovirus PCR primer and partial nucleotide sequence provides further evidence for the recognition of rice necrosis mosaic virus as a bymovirus" *Eur J Plant Pathol*
12. Adams, Antoniw, Fauquet (2005) "Molecular criteria for genus and species discrimination within the family potyviridae" *Arch Virol*
13. Ghosh (1980) *Rice necrosis mosaic. Proceedings: Plant Sciences*
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# Abstract citation ID: ofaf695.958 P-747. Predictive Factors of Poor Outcomes in Non-Necrotizing Bacterial Dermohypodermitis: A Retrospective Study
Amal Chakroun, Ben Mounir, Jemaa
Background. Non-necrotizing bacterial dermohypodermitis (NBDH) is a common cause of hospitalization, typically responding well to appropriate antibiotic therapy. However, in some cases, the course may be complicated by local or systemic infectious events, potentially affecting prognosis. We aimed to describe the clinical course and identify predictive factors of unfavorable outcomes in patients hospitalized with NBDH.
Methods. We conducted a retrospective study including adult patients admitted for NBDH in the Infectious Diseases Department of Hedi Chaker University Hospital (Sfax, Tunisia) between January 2015 and December 2024. A favorable outcome was defined by defervescence within 72 hours and improvement or resolution of local signs within 5 days. An unfavorable outcome was defined as lack of clinical improvement after 5 days, or the occurrence of complications (e.g., sepsis, necrosis, abscess) or death
Results. A total of 115 patients were included (mean age: 59 ± 16 years; 52.2% female). A cutaneous portal of entry was identified in 47% of cases. Empirical antibiotic therapy was mainly based on amoxicillin-clavulanate plus clindamycin (34.8%). Microbiologically guided adjustment was required in 8 cases. Surgical intervention was necessary in 5 cases. Mean antibiotic duration was 14 ± 7.2 days. Overall, 82.6% of patients had a favorable outcome. Independent predictors of unfavorable outcome included age >65 years (p=0.0056), obesity (p=0.008), and chronic venous insufficiency (p=0.052). Female sex (p=0.63), diabetes (p=0.523), and prior episodes of NBDH (p=0.413) were not significantly associated. Recurrence occurred in 9.9% of cases.
Conclusion. Early identification of risk factors such as advanced age, obesity, and venous insufficiency is essential for optimizing NBDH management and improving patient outcomes
Disclosures. All Authors: No reported disclosures
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# Correction: Yehia et al. Rapid Detection Assay for Infectious Bronchitis Virus Using Real-Time Reverse Transcription Recombinase-Aided Amplification. Viruses 2025, 17, 1172
Nahed Yehia, Ahmed El Wahed, Abdelsatar Arafa, Dalia Said, Ahmed Abd, Elhalem Mohamed, Samah Eid, Mohamed Shalaby, Rea Maja Kobialka, Uwe Truyen, Arianna Ceruti
## Abstract
In the original publication [1], there was a mistake in Figure 5 as published. The x-axis displays erroneously formatted values. The corrected Figure 5 appears below. The authors state that the scientific conclusions are unaffected. This correction was approved by the Academic Editor. The original publication has also been updated.
## References
1. Yehia, Abd El Wahed, Arafa et al. (1172) "Rapid Detection Assay for Infectious Bronchitis Virus Using Real-Time Reverse Transcription Recombinase-Aided Amplification" *Viruses*
2. "The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods"
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# Complete genome sequence of the hepatitis B virus from hemodialysis patients with occult infection in Bangladesh
Roni Mia, Anandha Mozumder, Parsa Disha, Nashid Sultana Ishi, S Nazmul Hasan, Anupam Das, Chirojit Debnath, Jebin Tasmin, M Rahman, Mohammad Imtiaj, Uddin Bhuiyan, Sharmin Akter, S Rashed, Ul Islam, Muzahed Ahmed, Chitta Debnath, Md Golzar Hossain, Md Hossain
## Abstract
Hepatitis B virus (HBV) can cause occult infections and has been associated with kidney diseases, particularly in patients undergoing hemodialysis. Here, we report the complete genome sequence of an HBV strain identified in a hemodialysis patient with occult HBV infection in Bangladesh.
H epatitis B virus (HBV) infection remains a major global health concern, capable of causing occult hepatitis B infection (OBI). It is also linked to kidney diseases, particularly among patients undergoing hemodialysis (1). HBV belongs to the family Hepadnaviridae, genus Orthohepadnavirus, and contains a partially double-stranded circular DNA genome of approximately 3.2 kb (2). The virus exhibits substantial genetic diversity and is classified into 10 genotypes (A-J), with further subdivision into subgeno types (3). Previous report showed a high prevalence of OBI among hemodialysis patients with end-stage renal disease (4). Although HBV infections have been documented in this patient group, and OBI is considered endemic in hospitalized populations, to date, no complete genome sequence of HBV from hemodialysis patients with OBI in Bangladesh has been published (5).
A serum sample was collected from an HBsAg-negative hemodialysis patient with confirmed OBI. Total DNA was extracted using the QIAamp DNA Mini Kit (Qiagen, Germany). The overlapping open reading frames (ORFs) P, S, C, and X were amplified using previously described gene-specific primers (6). Amplified PCR products were purified using a DNA purification kit (GL Sciences, Inc., Tokyo, Japan). The purified products were pooled and subjected to whole-genome sequencing using Illumina technology. Shotgun metagenomic libraries were prepared using a modified iNextEra protocol. DNA tagmentation was performed with Illumina bead-linked transposomes (Illumina DNA Library Prep, Illumina, Inc.), and pooled libraries were sequenced on an Illumina NovaSeq X Plus platform (2 × 150 bp; Novogene, USA). The initial sequenc ing yielded 22.4 million total reads. Raw paired-end reads were quality-trimmed, and adapters were removed using Trimmomatic (v.0.39), retaining reads >50 bp. Quality control was assessed using FastQC (v.0.11.9). Reads were mapped against the HBV reference genome (GenBank accession no. NC_003977.2; genome length: 3182 bp) using BWA-MEM (v.0.7.17) (7). Resulting alignments were processed using Samtools (v.1.12) (8), FreeBayes (v.1.3.5) (9), and bcftools (v.1.12) (10) to generate a consensus sequence. The sequence provides 100% coverage of the viral genome at a mean depth of 563,787×. The genomes were annotated, and overlapping ORFs were identified by aligning with the reference genome (GenBank accession no. OR769214.1) in Prokka (v.1.14.6) and CLC sequence viewer (v.8). Genotype and subtype were determined using Geno2pheno (https://hbv.geno2pheno.org/) and previously published methods (11). All tools were used with default parameters unless otherwise specified.
The identified full-length circular HBV genome (MGH_HBV-104) was 3,182 bp and contained four overlapping ORFs: P (2,499 bp), S (1,170 bp), C (639 bp), and X (465 bp). The GC content was 48.8%. BLAST analysis showed 99.69% and 99.50% identity to previously reported Bangladeshi HBV strains MGH_HBV-14 (OR769214.1) and BD-HBV08 (MF925364.1), respectively. The strain was classified as genotype D (D2), subtype "ayw. "
This complete genome sequence from hemodialysis patients with occult infection provides important data for understanding HBV genetic diversity in Bangladesh and supports future efforts in antiviral resistance monitoring and molecular epidemiological studies.
## References
1. Eslami, Poortahmasebi, Sadeghi et al. (2022) "Occult hepatitis B infection among hemodialysis in Tabriz, Northwest of Iran: prevalence and mutations within the S region" *Can J Infect Dis Med Microbiol*
2. Karayiannis (2017) "Hepatitis B virus: virology, molecular biology, life cycle and intrahepatic spread" *Hepatol Int*
4. Hossain, Mahmud, Rahman et al. (2020) "Complete genome sequence of a precore-defective hepatitis B virus genotype D2 strain isolated in Bangladesh" *Microbiol Resour Announc*
5. Shrestha, Tiwari, Pradhan (2021) "Occult hepatitis B infection in end-stage renal disease patients starting maintenance hemodialysis at a tertiary care hospital: a descriptive cross-sectional study" *JNMA J Nepal Med Assoc*
6. Chowdhury, Mcnaughton, Amin et al. (2021) "Endemic HBV among hospital inpatients in Bangladesh, including evidence of occult infection" *J Gen Virol*
7. Hossain, Islam, Jeba et al. (2024) "Complete genome sequence of hepatitis B virus identified from a patient suffering from chronic kidney disease in Bangladesh" *Microbiol Resour Announc*
8. Li (2013) "Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM"
9. Li, Handsaker, Wysoker et al. (2009) "1000 Genome Project Data Processing Subgroup"
10. Garrison, Marth (2012) "Haplotype-based variant detection from short-read sequencing"
11. Danecek, Bonfield, Liddle et al. (2021) "Twelve years of SAMtools and BCFtools. Gigascience 10:giab008"
12. Lusida, Nugrahaputra, Soetjipto et al. (2008) "Novel subgenotypes of hepatitis B virus genotypes C and D in Papua, Indonesia" *J Clin Microbiol*
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# First Brazilian Symposium on Viruses of Microorganisms (BrVoM 2025)
Jônatas Santos, Felipe Luiz, Leomil Coelho, Amanda Stéphanie, Arantes Witt, Ana Da Nóbrega, Nunes Alves, Anna Dias, Soares Guimarães, Stehling Bárbara, Silva Ramos, Bruna Neiva, Bruno Fernandes De Oliveira, Jamile Dias, João Rodrigues, Pessoa Carvalho, Letícia Pereira Lopes, Matheus Felipe, Reis Rodrigues, Matheus Gomes Barcelos, Nidia Esther, Colquehuanca Arias, Poliane Zerbini, Lucia Dos Vera, Santos, Ambrosio Caio, Leal-Dutra, Savio Torres De Farias, Rodrigo Araujo, Lima Rodrigues, Juliana Reis Cortines, Henrique Otavio, Thiemann, Paulo Boratto, Marcelo Aguiar De Freitas, Gabriel Magno De Freitas Almeida
## Abstract
In recent decades, there has been an increased interest in viruses of microorganisms (VoM) and international efforts to gather researchers interested in them. Here, we describe the 1st Brazilian Symposium on Viruses of Microorganisms (BrVoM), held on 1 August 2025 at the Federal University of Minas Gerais (UFMG, Belo Horizonte, Brazil) with institutional support from the Federal University of Alfenas (UNIFAL) and the Brazilian Society for Virology (SBV). The symposium greatly surpassed expectations, gathering nearly 300 attendees from all Brazilian geographical regions. The scientific program included
## 1. Introduction
Viruses are the most abundant organisms on Earth, found wherever life is present [1]. Most of the virosphere is composed of viruses that infect microbial life, collectively called viruses of microorganisms (VoM). This diverse viral group is composed of viruses of prokaryotes (phages) and viruses of unicellular eukaryotes (mycoviruses, large viruses of microalgae and giant viruses of protists) [2]. Although the discipline of virology has had an anthropocentric bias, in recent decades, the study of VoMs is increasingly gaining traction worldwide. Among the reasons are the importance of VoMs for the environment [3], for understanding microbial evolution [4], as tools for biotechnology [5] and for clinical purposes [6].
The VoM research field is broadly divided into two main focus areas, phages and viruses of unicellular eukaryotes. There has been an international effort into gathering virologists working with VoMs. The International Society for Viruses of Microorganisms (ISVM) has already organized eight international Viruses of Microbes conferences since 2010. These conferences took place in European countries, Georgia and more recently in Australia. Local VoM groups are being formed, such as the Belgian Society for Viruses of Microbes (BSVoM) founded in 2022 and the Danish Viruses of Microbes Network founded in 2025. However, besides the Africa Phage Forum, a collaborative network for phage research in Africa [7], and the Phages for Global Health [8] initiative, most of these networks are hosted and focused on the Global North.
South America has interesting ties to VoMs. From a historical and applied perspective, Brazil was a hotspot and reference for South American phage therapy between the 1920s to 1940s [9]. The efforts of Dr. Jose da Costa Cruz and the Oswaldo Cruz Institute at the time were so successful that they were even used as examples by Dr. George Eliava himself while asking for funds to expand his own Institute in Tbilisi in the 1930s [10]. After the gap in phage therapy created by the widespread use of antibiotics, phage research is growing in South America despite the lack of modern clinical cases. One exception is a single documented case of personalized phage therapy in Uruguay [11]. A recent systematic review show that Brazil leads the South American output of phage research, being responsible for 39% of the scientific publications in the region from 1989-2024 [12]. From an ecological perspective, the large biological diversity of Brazilian biomes is being shown to be true also to the Brazilian virosphere by efforts of The Giant Viruses Study Group [13], founded in 2011 at the Federal University of Minas Gerais [14]. Although Brazil has a strong virology community clustered within the Brazilian Society of Virology (SBV) [15] founded in 1986, traditionally the focus of the community has been on medically relevant viruses. Here, we report the initiative to gather Brazilian VoM researchers under the 1st Brazilian Symposium on Viruses of Microorganisms (BrVoM) in 2025. This successful event attracted a remarkable diversity of participants and consolidated a research community with similar interests and desire to keep the Brazilian VoM cluster alive in the upcoming years.
## 2. First Brazilian Symposium on Viruses of Microorganisms Organization
In the context described above, Brazilian virologists interested in VoMs organized the first edition of the Brazilian Symposium on Viruses of Microorganisms (BrVoM), held at the Federal University of Minas Gerais (UFMG), Belo Horizonte, with support from the Federal University of Alfenas (UNIFAL) and the Brazilian Society for Virology (SBV) (Figure 1). The event took place on 1 August 2025 from 9:30 to 17:30. The organization committee opted to not charge any registration fee, making the event accessible to all and not excluding low-income students. The event language choice was Portuguese, another measure taken not to exclude any local participant. A small funding obtained from local biotech companies (Biocell/Molecular) was used to cover the preparation of participant tags, flyers and prizes given to the audience. These companies were present at the event in booths at the lobby to showcase their products and connect to the audience.
The event was advertised online, locally at the UFMG, and by the speakers within their own research networks. The local invited speakers participated on a voluntary basis, covering their own expenses, which underscores the strong sense of collaboration and commitment in this scientific field. The speakers were chosen based on their contributions to the VoM field and were all established early or mid-career researchers. The agenda for the event is shown in Table 1. The event exceeded all expectations: initially planned for a modest audience of 50 participants, it ultimately brought together almost 300 researchers, students, professionals and even participants from the general public, making it one of the most significant virology events in Brazil in 2025. The participants who registered for the event represented 15 Brazilian states, covering all five regions of the Country, and were associated with 51 different Brazilian institutions. A large proportion of early career attendees was noted, pointing out that the VoM field will have a long impact in the next generation of Brazilian virologists.
## 3. First Brazilian Symposium on Viruses of Microorganisms Report
## 3.1. The Start of the Event
The meeting was opened with a round table composed of representants from the organizing committee (Professor Jonatas dos Santos Abrahao from UFMG and Professor Luiz Felipe Leomil Coelho from UNIFAL), the head of the Microbiology Department of the UFMG (Professor Daniel Assis Santos) and Professor Betania Paiva Drummond representing the Brazilian Society for Virology.
The first talk was a keynote lecture by associate Professor Gabriel Magno de Freitas Almeida (Arctic University of Norway), entitled One Hundred Years of Phage Therapy and the Revival of Its Prophylactic Character in Contemporary Times. His presentation revisited the historical development of phage therapy, including the role Brazil had in the first half of the 20th century [9], ending with the perspective of applying phage-bacteriamucin dynamics [16,17] as a mean to revive a prophylactic approach to phage use in the present. He mentioned the lack of opportunities to start phage projects while an early career researcher in Brazil a decade ago, which made him go abroad to pursue it.
## 3.2. Bacteriophage Biology Session
Professor Luiz Felipe Leomil Coelho (UNIFAL-MG) discussed Phage-based strategies to control Pseudomonas aeruginosa, presenting results from phages isolated by his research group which were tested in vivo with a rational prophylactic approach based on mucosal dynamics [18]. Two similar Brazilian phages were compared, showing that phage VAC3 demonstrated superior replication in P. aeruginosa exposed to mucin in vitro and showed a stronger retention within the respiratory tract of C57BL/6 mice. Importantly, pre-exposure to VAC3 protected mice from an otherwise lethal challenge with P. aeruginosa, whereas phage VAC1 failed to confer such protection. These findings highlight that phages adapted to mucosal environments hold potential as prophylactic agents against ESKAPE pathogens.
Professor Poliane Zerbini (Federal University of Viçosa, UFV) provided an overview of ongoing efforts to characterize the natural diversity and evolutionary dynamics of phages infecting Ralstonia species, responsible for bacterial wilt, an important constraint to global crop production. Her group has been uncovering how phage-host interactions influence the population structure, adaptability, and persistence of Ralstonia species in diverse environments, contributing to a broader understanding of viral roles in shaping the ecology of phytopathogenic bacteria and in driving the coevolutionary processes that define host-virus relationships in the soil microbiome. In addition, she emphasized the translational potential of this research for sustainable agriculture using phage-based biocontrol formulations aimed at suppressing Ralstonia populations in the field, bridging fundamental and applied virology.
Professor Vera Lúcia dos Santos (UFMG) delivered a lecture on the use of phages as sustainable alternatives for controlling biofilms in industrial systems, with a particular focus on cooling water systems. She addressed the operational and environmental challenges associated with biofilm formation, including corrosion of infrastructure, reduced heat exchange efficiency, increased reliance on chemical biocides, and the emergence of antimicrobial-resistant communities. Complementing the molecular and microbiological data, Dr. Santos presented results from controlled pilot-scale reactor systems that reproduce industrial conditions. By integrating microbial ecology, biotechnology, and process engineering, her work positions phage-based interventions as promising, scalable, and environmentally responsible alternatives to conventional chemical control approaches.
## 3.3. Fungal Viruses Session
Dr. Caio Leal-Dutra (UFMG/University of Copenhagen, Denmark) presented Silent Viruses in a Symbiosis That Challenges Time, exploring the ecological relevance of fungal viruses and their impact on symbiotic systems inspired by the classic discovery of mycoviruses in Yellowstone endophytic fungi [19] and by evidence of viral sequences hidden in fungal transcriptomes [20]. Combining transmission electron microscopy with nextgeneration sequencing, the team characterized two novel +ssRNA mycoviruses cohabiting the domesticated fungus of leafcutter ants, Leucoagaricus gongylophorus tymo-like virus 1 (LgTlV1) and Leucoagaricus gongylophorus magoulivirus 1 (LgMV1) [21]. He concluded by discussing ongoing efforts to understand how these viruses shape the stability of one of nature's most remarkable symbioses, potentially acting as neutral passengers, detrimental agents, or even hidden mutualists.
## 3.4. Discovery and Characterization of Viruses of Unicellular Eukaryotes Session
The afternoon sessions were dedicated to giant viruses. Professor Jônatas Abrahão (UFMG) spoke about Brazilian contributions to the study of giant amoebal viruses. The talk focused on the biology and evolution of giant amoeba-infecting viruses, highlighting the research conducted by his group in Brazil since 2011. Among the most impactful results, he mentioned the discovery of Tupanvirus [22] and Yaravirus [23], two unique representatives that have significantly expanded our understanding of the diversity and biological peculiarities of these microorganisms. He also emphasized how the contributions of the international scientific community have been transforming the perception of the limits of the virosphere. In this context, studies on giant viruses not only challenge traditional concepts in virology but also raise new questions about the origin, evolution, and ecological roles of these viruses, strengthening the relevance of this emerging field of research.
Professor Sávio Torres (UFPB) discussed Recent Insights into Yaravirus biology. Intrigued by the lack of similarity Yaravirus proteins have to other deposited sequences, his group decided to reanalyze the proteome of Yaravirus in an attempt to uncover possible clues about the functions encoded in its genome. By using a similarity search based on three-dimensional structures and not on primary amino acid sequences, allowing to match the modelled proteins from Yaravirus to matches with known function. It was proposed that Yaravirus exhibits a modular genomic organization, in which different genes encode parts of a protein, which are then reorganized at the protein level to restore full functionality. Many proteins were matched to functions related to the Krebs cycle and energy metabolism, highlighting that idiosyncrasies of Yaravirus lie not only in its size or mysterious genome but also in the unique ways its genome functions.
Professor Rodrigo Rodrigues (UFMG) concluded the session by discussing the hidden diversity of microalgal viruses in continental waters. Among the known algal viruses, the chloroviruses are the most studied, having large dsDNA viruses and infecting Chlorellalike algae [24]. His presentation highlighted the importance of isolating and genomically characterizing chloroviruses from new environments. These works have enabled the establishment of classification criteria for chloroviruses, revealing the existence of 20 viral species grouped into three subgenera based on multiple lines of evidence, including host range, phylogeny, and comparative genomics [25][26][27]. The search for new chloroviruses in Brazilian biomes led to the isolation and characterization of the first microalgal viruses in Brazil, opening new avenues for discovery and advances in the field of aquatic giant viruses.
## 3.5. Giant Viruses-Host Interactions Session
Professor Juliana Cortines (Federal University of Rio de Janeiro, UFRJ/University of Connecticut, USA) spoke about the Role of Transition Metals in the Replication of Mimiviruses. She outlined a continuum of studies beginning with cryo-electron microscopy of mimiviruses and proteomic analysis of the viral components released inside their Acanthamoeba hosts upon infection [28]. Among the identified proteins, those with metalbinding capacity were particularly significant, prompting further investigation into the role of metals during mimivirus infection [29]. Building on this, she presented evidence that iron acts as an enhancer of infectivity: intracellular iron levels increase as infection progresses, and viral titers rise in the presence of supplemental iron [30].
Professor Otavio Thiemann (University of São Paulo, USP) then presented his findings on Niemeyer virus viral factories using X-ray imaging techniques. He used synchrotron beamlines to investigate the structure of the viral factories (VF) of amoeba infected by Niemeyervirus. Soft X-ray Tomography (Cryo-SXT) of the Mistral beamline (ALBA synchrotron, Spain) revealed the formation of immature and mature capsids from the internal region of the VF to the exterior. Nanotomography Ptychography (CXDI) experiments at the Cateretê beamline (SIRIUS, Brazil) highlighted significant structural changes during the infection and viral biosynthesis in its native three-dimensional form. These techniques contribute to a better understanding of the role of the viral factory and the changes in host cell architecture during infection, with minimal interference with the native structure of the cells and target complexes.
Dr. Paulo Boratto (Brazilian Center for Research in Energy and Materials, CNPEM) discussed amoeba chemical signaling to resist giant virus infections. He used the longstanding host-parasite relationship between amoebae and giant viruses as a framework to investigate ancestral immune strategies in eukaryotes. By employing amoebozoan species and some Nucleocytoviricota viruses as model representatives of ancient hosts and pathogens, he demonstrated that viral infection triggers the amoebae to release extracellular alarm signals, which induce neighboring cells to rapidly undergo encystment and thereby establish resistance against giant virus infection.
## 3.6. Event Closure
The symposium concluded with a closing lecture by Dr. Marcelo Henrique Aguiar de Freitas (Embrapa), entitled Deposit of Microorganisms in the Embrapa Genetic Bank and International Instruments. He addressed the regulatory and biosafety aspects related to the deposition of microbial strains in national and international collections, a highly relevant topic for researchers working with VoMs. He introduced the Germplasm Curation System [31] and the Curation of Microorganisms [32] from Embrapa, which contains 10 large biological collections with different thematic axes and more than 15 associated biological collections, which has been improving to increase the provision of services to society, such as: the use of the Alelo Platform for managing RGs, the deposit of biological material of microorganisms and the implementation of an International Depository Authority (IDA) to comply with the Budapest Treaty.
The event ended with acknowledgments to the participating institutions, speakers, students, and the organizing committee. A prize draw was made to give books, coffee mugs and memberships to the Brazilian Society of Virology to the audience. Feedback from the speakers and audience is being positive, and plans for a follow-up meeting are being made.
## 4. Conclusions
The 1st Brazilian Symposium on Viruses of Microorganisms was a landmark event for the Brazilian virology community. By bringing together nearly 300 participants in a free and fully collaborative initiative, the symposium demonstrated the growing relevance of microbial virology in Brazil and created a new platform for scientific discussion, networking, and training. The breadth of topics covered-from bacteriophages to giant viruses-reflects the diversity and strength of research in the country. The overwhelming success of this first edition sets the stage for the BrVoM to become a recurring scientific meeting, fostering further integration of the Brazilian and international communities dedicated to the study of viruses of microorganisms.
GMFA is funded by the Centre for New Antibacterial Strategies (CANS) of the Arctic University of Norway (project ID #2520855). Several authors are CNPq researchers.
## References
1. Suttle (2005) "Viruses in the sea" *Nature*
2. Koonin, Kuhn, Dolja et al. (2024) "Megataxonomy and global ecology of the virosphere" *ISME J*
3. Suttle (2007) "Marine viruses-Major players in the global ecosystem" *Nat. Rev. Microbiol*
4. Koonin, Wolf (2012) "Evolution of microbes and viruses: A paradigm shift in evolutionary biology?" *Front. Cell. Infect. Microbiol*
5. Schieferecke, Kuxhausen Ralph, Schaffer (2025) "The Application of DNA Viruses to Biotechnology" *Viruses*
6. Skurnik, Alkalay-Oren, Boon et al. (2025) *Nat. Rev. Methods Primers*
7. Nnadi, Nakayinga, Makumi et al. (2022) "The Africa Phage Forum: A New Collaborative Network for Bacteriophage Research in Africa"
8. Phages For, Health, Website (2025)
9. Almeida, Sundberg (2025) "The Forgotten Tale of Brazilian Phage Therapy-The Lancet Infectious Diseases"
10. Myelnikov (2018) "An Alternative Cure: The Adoption and Survival of Bacteriophage Therapy in the USSR, 1922-1955" *J. Hist. Med. Allied Sci*
11. Iraola, Puig, Grill et al. (2025) "Eradication of extensively drug resistant Pseudomonas aeruginosa causing ventilator-associated pneumonia in acute lymphoblastic leukemia patient using phage therapy" *Res. Sq*
12. Najjar, De Paula Siqueira, Marcelino Santos et al. "Phage research in South America: A descriptive overview of trends and gaps"
13. (2025) "The Giant Viruses Study Group, Brazil. The Giant Viruses Study Group"
14. Boratto, Serafim, Witt et al. (2022) "A Brief History of Giant Viruses" *Studies in Brazilian Biomes. Viruses*
15. Virologia (2025)
16. Barr, Auro, Furlan et al. (2013) "Bacteriophage adhering to mucus provide a non-host-derived immunity" *Proc. Natl. Acad. Sci*
17. Almeida, Laanto, Ashrafi et al. (2019) "Bacteriophage Adherence to Mucus Mediates Preventive Protection against Pathogenic Bacteria"
18. Coelho, De Souza Terceti, Neto et al. (2025) "Mucosal-adapted bacteriophages as a preventive strategy for a lethal Pseudomonas aeruginosa challenge in mice" *Commun. Biol*
19. Márquez, Redman, Rodriguez et al. (2007) "A Virus in a Fungus in a Plant: Three-Way Symbiosis Required for Thermal Tolerance" *Science*
20. Jo, Choi, Chu et al. (2022) "Unveiling Mycoviromes Using Fungal Transcriptomes" *Int. J. Mol. Sci*
21. Rødsgaard-Jørgensen, Leal-Dutra, De Santana et al. (2024) "Two +ssRNA mycoviruses cohabiting the fungal cultivar of leafcutter ants" *Virol. J*
22. Abrahão, Silva, Silva et al. (2018) "Tailed giant Tupanvirus possesses the most complete translational apparatus of the known virosphere" *Nat. Commun*
23. Boratto, Oliveira, Machado et al. (2020) "Yaravirus: A novel 80-nm virus infecting Acanthamoeba castellanii" *Proc. Natl. Acad. Sci*
24. Van Etten, Agarkova, Dunigan et al. (2020) *Viruses*
25. Carvalho, Carlson, Ghosh et al. "Genomics and evolutionary analysis of Chlorella variabilis-infecting viruses demarcate criteria for defining species of giant viruses" *J*
26. Henriques, Botelho, Carlson et al. (2025) "Revealing the hidden diversity of Chlorella heliozoae-infecting giant viruses" *NPJ Viruses*
27. Souza, Henriques, Carlson et al. (1096) "New Isolates of Betachloroviruses Shed Light on the Diversity and Biological Complexity of an Unexplored Group of Giant Algal Viruses" *Viruses*
28. Schrad, Abrahão, Cortines et al. (2020) "Structural and Proteomic Characterization of the Initiation of Giant Virus Infection" *Cell*
29. Cortines, Bridges, Subramanian et al. "Transition metals and oxidation reactions trigger stargate opening during the initial stages of the replicative cycle of the giant Tupanvirus" *mBio*
30. Oliveira, Dick, Nunes et al. (2025) "Intracellular iron positively modulates the replicative cycle of mimiviruses, increasing virus production" *J. Virol*
31. (2025) *Portal Alelo Recursos Genéticos. Available online*
32. Microbiana (2025)
33. "The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods"
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# Report of the draft genome sequences of human sapovirus from children with acute gastroenteritis in Malawi, Southern Africa
Flywell Kawonga, Ernest Matambo, End Chinyama, Chimwemwe Mhango, Clara Majengo, Josephine Msowoya, Prisca Benedicto-Matambo, Benjamin Kumwenda, Celeste Donato, Arox Kamng'ona, Milton Mogotsi, Nkosazana Shange, Ayodeji Ogunbayo, Francis Dennis, Martin Nyaga, Chrispin Chaguza, Khuzwayo Jere
## Abstract
Human sapoviruses are increasingly recognized as a cause of acute gastroenteritis in children worldwide but remain poorly studied, particularly in African settings. Here, we report the four draft genome sequences of human sapovirus from Malawi, Southern Africa, collected from children with acute gastroenteritis. KEYWORDS human sapovirus (SaV), acute gastroenteritis, genome sequencing, Malawi, SACEV, Caliciviridae, enteric viruses H uman sapovirus (SaV), a member of the Caliciviridae family, is a significant cause of acute pediatric viral gastroenteritis, particularly in low-and middle-income countries (LMICs). There are at least 19 SaV genogroups, four of which infect humans (genogroups GI, GII, GIV, and GV) (1). SaVs have a single-stranded, positive sense ribonucleic acid (RNA) genome of approximately 7.5 kb, typically comprising two or three open reading frames (ORFs), namely ORF1, ORF2, and sometimes ORF3 (2, 3). SaVs are recognized as a major cause of childhood diarrhea (4, 5) but remain genomically under-characterized in Africa. Malawi, a low-income country with a high SaV burden (6), still lacks sufficient sequence data. This study presents four draft genome sequences of SaV isolated from children under 5 years of age with acute gastroenteritis at two hospitals in Blantyre, Malawi, between 2012 and 2024, as part of a project aimed at sequencing and characterizing the antigenic diversity of enteric viruses in Africa.Selected stool samples collected each month were screened for SaV and other enteric viruses using customized real-time PCR-based TaqMan Array Cards (TACs), as previously described (7). Total RNA was extracted from SaV-positive samples with PCR threshold (Ct) <35 using the QIAamp Viral RNA Mini Kit (Qiagen, Germany). Complementary DNA (cDNA) was synthesized using QIAseq FX Single Cell RNA Library Kit (Qiagen, Germany). The SaV genomes described here were generated by shotgun metagenomic sequencing, which produces genomic sequences of all the genetic material present in the sample. Genomic libraries were prepared using the Illumina DNA Prep kit (Illumina, USA) before being sequenced on Illumina NextSeq 2000 platform using a P1 flow cell and 300-cycle reagent kit (2 × 150 bp paired-end reads). Quality control of the sequenced genomes was performed using FastQC v0.11.7 (https://www.bioinformatics.babraham.ac.uk/projects/ fastqc/).Low-quality reads were trimmed using Trimmomatic (v0.39) (8). To eliminate contaminating human reads, the trimmed sequences were aligned against the human genome (Homo_sapiens.GRCh38.dna.primary_assembly.fa, NCBI accession ID: GCA_000001405.15) using Bowtie2 v2.5.4 (9). The non-human reads were mapped to the reference genomes listed in Table 1 using the Burrows-Wheeler Aligner (BWA, version 0.7.18-88 r1243-dirty) (10). Using iVar (version 1.4.4), high-confidence bases were called from the aligned sequence reads to produce the consensus genomes (11).
Genome assemblies were subsequently annotated using Prokka (version 1.14.6) (12). BLASTn analysis showed that CQA1ACS1, CHX11FS1, BTY12GF1, and BID18VS2 shared 96.70%, 93.91%, 96.75%, and 95.04% nucleotide identity with reference genomes as depicted in Table 1, respectively. Genome assembly depth was assessed using Samtools (v1.21). (https://www.htslib.org/). Table 1 summarizes the read and assembly characteris tics, highlighting key genomic features for all sequenced samples. Genome assembly identity was confirmed as SaV using Genome Detective (https://www.genomedetec tive.com/app/typingtool/virus/). Genotyping was performed using the Human Calicivirus Typing (HuCaT) tool (13), which classified the Malawian SaV genomes into genogroups GII.1, GII.5, GI.2, and GII.5. Phylogenetic analysis revealed that two Malawian GII.5 strains clustered together, while GI.2 and GII.1 strains clustered with genomes from Brazil and India, respectively (Fig. 1). All analyses were carried out using default settings unless otherwise specified.
## ACKNOWLEDGMENTS
The Sequencing and Antigenic Cartography of Enteric Viruses (SACEV) project was funded by the Gates Foundation (Investment ID: INV-046917).
The investigators declare no conflict of interest, and the funders had no role in the study design, data collection, interpretation, or decision to submit the manuscript for publication. The authors did not receive any financial support or other forms of reward related to the development of the manuscript. The findings and conclusions presented in this report are solely those of the authors and do not necessarily reflect the views of the funders.
Shotgun metagenomic sequencing for the SACEV study was conducted at the University of the Free State-Next Generation Sequencing (UFS-NGS) Unit.
We sincerely acknowledge the UFS-NGS team for their essential contribution in producing high-quality sequencing data, which played a pivotal role in the study. Their technical expertise and support were instrumental to the successful execution of this research.
## References
1. Oka, Wang, Katayama et al. (2015) "Comprehensive review of human sapoviruses" *Clin Microbiol Rev*
2. Chang, Sosnovtsev, Belliot et al. (2005) "Reverse genetics system for porcine enteric calicivirus, a prototype sapovirus in the Caliciviridae" *J Virol*
3. Schuffenecker, Ando, Thouvenot et al. (2001) "Genetic classification of "sapporo-like viruses" *Arch Virol*
4. Becker-Dreps, González, Bucardo (2020) "Sapovirus: an emerging cause of childhood diarrhea" *Curr Opin Infect Dis*
5. Li, Huang, Wu et al. (2023) "The outbreak of acute gastroenteritis caused by sapovirus at a school in Shenzhen" *Front Public Health*
6. Iturriza-Gómara, Jere, Hungerford et al. (2019) "Etiology of diarrhea among hospitalized children in blantyre, Malawi, following rotavirus vaccine introduction: a case-control study" *J Infect Dis*
7. Liu, Gratz, Amour et al. (2013) "A laboratorydeveloped TaqMan array card for simultaneous detection of 19 enteropathogens" *J Clin Microbiol*
8. Bolger, Lohse, Usadel (2014) "Trimmomatic: a flexible trimmer for Illumina sequence data" *Bioinformatics*
9. Langmead, Salzberg (2012) "Fast gapped-read alignment with Bowtie 2" *Nat Methods*
10. Li, Durbin (2009) "Fast and accurate short read alignment with burrows-wheeler transform" *Bioinformatics*
11. Grubaugh, Gangavarapu, Quick et al. (2019) "An amplicon-based sequencing framework for accurately measuring intrahost virus diversity using PrimalSeq and iVar" *Genome Biol*
12. Seemann (2014) "Prokka: rapid prokaryotic genome annotation" *Bioinformatics*
13. Tatusov, Chhabra, Diez-Valcarce et al. (2021) "Human calicivirus typing tool: a web-based tool for genotyping human norovirus and sapovirus sequences" *J Clin Virol*
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# A Tribute to Professor Andrew Otis Jackson
Fangfang Li, Jonathan Griffiths, Xueping Zhou, Aiming Wang
## Abstract
It is with profound sadness and a deep sense of loss that we mourn the passing of Professor Andrew Otis Jackson on 6 July 2025. Andy was a towering figure in plant virology, whose pioneering research on plant RNA viruses, particularly hordeiviruses and rhabdoviruses, fundamentally reshaped our understanding of viral replication, movement, and pathogenesis. This tribute from a few of the countless virologists he either directly mentored, or supported and inspired, aims to honor his immense scientific legacy. Just as importantly, this Special Issue is meant to celebrate his unparalleled generosity as a mentor, colleague, and friend.
His faculty appointments at Purdue University and later at the University of California, Berkeley, catalyzed his most influential work. Andy's lab pioneered the molecular characterization of barley stripe mosaic virus (BSMV), establishing it as the type member of the Hordeivirus genus [2][3][4][5][6][7]. His team meticulously mapped the tripartite genome of BSMV, identified the roles of the triple gene block (TGB) proteins in viral movement, and uncovered the multifunctional nature of the γb protein as an RNA silencing suppressor and pathogenesis factor. This body of work provided a foundational model for understanding virus-host interactions in monocot plants.
Simultaneously, he embarked on a decades-long quest to unravel the complexities of plant rhabdoviruses, using sonchus yellow net virus (SYNV) as his primary model. Overcoming immense technical challenges, his lab sequenced the entire SYNV genome, demonstrated nuclear replication-a key distinction from cytoplasmic animal-infecting counterparts-and characterized SYNV structural proteins [8][9][10]. The crowning achievement of this endeavor was the development of the first reverse genetics system for a plant negative-strand RNA virus [11][12][13][14]. This breakthrough, achieved through ingenious agroinfiltration-based strategies, allowed for the rescue of infectious recombinant SYNV, opening up entirely new avenues for studying virus morphogenesis, movement, and host adaptation [15,16]. In addition to laying the groundwork for infectious clones of other negative-strand RNA viruses including barley yellow striate mosaic virus and tomato spotted wilt virus [17,18], his pioneering system was successfully adapted for other complex plant viruses. His early exploratory work thus provided an indispensable foundation for subsequent advances in the field, cementing his status as a visionary in the field.
## 2. The Heart of a Mentor: Nurturing Generations of Scientists
While his scientific publications form an enduring legacy, Andy's most profound impact was perhaps on the people he guided. He was a mentor in the truest sense, investing not just in projects, but in the personal and professional development of every student, postdoc, and colleague who crossed his path.
His approach to mentorship was holistic. He was deeply committed to imparting scientific knowledge and cultivating rigorous experimental habits. In the lab, he emphasized the importance of meticulous note-taking, a practice he admired in his first graduate student, Gary Gustafson, and encouraged in all who followed. He fostered critical academic thinking by engaging in lively, impromptu discussions, challenging assumptions, and pushing to design elegant, definitive experiments.
The process of manuscript and grant writing under his guidance was a masterclass in scientific communication. Andy would provide repeated, thorough, and critically constructive revisions. He had an uncanny ability to identify logical gaps and strengthen narratives. For early-career scientists, facing the anxiety of a manuscript submission or a grant decision, his guidance was a steadying force. He normalized this "feeling of insecurity," reassuring that it was a universal experience and, more importantly, a driving force that "prompts you to continuously correct, refine, and discover new questions." This perspective transformed professional vulnerability into a catalyst for growth.
His support extended far beyond the lab bench. Andy was a powerful advocate, providing strong, compelling recommendation letters for postdoctoral positions and faculty jobs. He took a genuine interest in the career planning for these that need his help, particularly young plant virologists and pathologists and graduate students, offering sage advice on navigating the academic landscape. His generosity knew no borders: he facilitated collaborations, secured funding for young Chinese scientists to work in his Berkeley lab and to attend key international conferences, and even offered personal financial and life assistance to those in need. He believed in paying forward the mentorship he had received from figures like Dean Meraz, Myron Brakke, and Albert Siegel.
Andy's love for people was evident in his joy for conversation and friendship. He was a natural storyteller and during his lectures he would often weave in "relevant personal interest stories" to invigorate the material and captivate his audience. This approach was especially impactful in his interactions with Chinese graduate students. At China Agricultural University and Zhejiang University, where he spent extended periods teaching and mentoring, Andy was known for his heuristic and encouraging teaching style. He did not just impart knowledge; he asked probing questions that stimulated critical thinking and gently guided his students to discover solutions on their own. He made a point of celebrating their progress, building their confidence as much as their expertise. His connection to China was particularly special. With a 10-year visa in hand, he had eagerly planned several return trips before 2028 to continue these fruitful academic exchanges and, as he put it, "to see old friends." This collaborative spirit, rooted in genuine mentorship and mutual respect, left an indelible mark on the field of plant virology in China and inspired a new generation of scientists.
## 3. Concluding Remarks
In his autobiographical reflection [1], Andy wrote, "These mentoring activities have been gratifying for me as they provide a feeling of reciprocation to those who were so critical to encouraging my early career activities." This sentiment captures the essence of the man. He built not just a research program, but a global family of scientists who cherished his wisdom, his warmth, and his unwavering belief in their potential.
Looking back, the "chip" that was Andrew Otis Jackson did not merely float passively; it navigated with purpose, charting new scientific territories and guiding countless other chips along the stream. His scientific rigor, his innovative spirit, and his profound humanity have left a blueprint for excellence and mentorship that will inspire generations to come.
Thank you, Andy, for everything. You will be profoundly missed, but your legacy will continue to flourish in the work of all those you touched.
## References
1. Jackson (2021) "Reflections on a Career in Plant Virology: A Chip Floating on a Stream" *Annu. Rev. Virol*
2. Jackson, Brakke (1973) "Multicomponent properties of barley stripe mosaic virus ribonucleic acid" *Virology*
3. Palomar, Brakke, Jackson (1977) "Base sequence homology in the RNAs of barley stripe mosaic virus" *Virology*
4. Gustafson, Milner, Mcfarland et al. (1982) "Investigation of the complexity of barley stripe mosaic virus RNAs with recombinant dna clones" *Virology*
5. Lawrence, Jackson (2001) "Interactions of the TGB1 Protein during Cell-to-Cell Movement of Barley Stripe Mosaic Virus" *J. Virol*
6. Lim, Bragg, Ganesan et al. (2008) "Triple Gene Block Protein Interactions Involved in Movement of Barley Stripe Mosaic Virus" *J. Virol*
7. (2026) *Viruses*
8. Jackson, Lim, Bragg et al. (2009) "Hordeivirus Replication, Movement, and Pathogenesis" *Annu. Rev. Phytopathol*
9. Jackson, Christie (1977) "Purification and some physicochemical properties of sonchus yellow net virus" *Virology*
10. Jackson (1978) "Partial characterization of the structural proteins of sonchus yellow net virus" *Virology*
11. Jackson, Dietzgen, Goodin et al. (2005) "Biology of Plant Rhabdoviruses" *Annu. Rev. Phytopathol*
12. Ganesan, Bragg, Deng et al. (2013) "Construction of a Sonchus Yellow Net Virus Minireplicon: A Step toward Reverse Genetic Analysis of Plant Negative-Strand RNA Viruses" *J. Virol*
13. Wang, Ma, Qian et al. (2015) "Rescue of a Plant Negative-Strand RNA Virus from Cloned cDNA: Insights into Enveloped Plant Virus Movement and Morphogenesis" *PLoS Pathog*
14. Jackson, Dietzgen, Goodin et al. (2018) "Development of Model Systems for Plant Rhabdovirus Research" *Adv. Virus Res*
15. Jackson, Li (2016) "Developments in Plant Negative-Strand RNA Virus Reverse Genetics" *Annu. Rev. Phytopathol*
16. Sun, Zhou, Lin et al. (2018) "Matrix-glycoprotein interactions required for budding of a plant nucleorhabdovirus and induction of inner nuclear membrane invagination" *Mol. Plant Pathol*
17. Zhou, Lin, Sun et al. (2019) "Specificity of Plant Rhabdovirus Cell-to-Cell Movement" *J. Virol*
18. Gao, Xu, Yan et al. (2019) "Rescue of a plant cytorhabdovirus as versatile expression platforms for planthopper and cereal genomic studies" *New Phytol*
19. Feng, Cheng, Chen et al. "Rescue of tomato spotted wilt virus entirely from complementary DNA clones"
20. "The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods"
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# Congenital Viral Infection Risk: The Role of Parvovirus B19 and Cytomegalovirus Molecular Genetic Testing
Stefka Krumova, Ivelina Trifonova, Mariela Hristova-Savova, Lora Veleva, Radostina Stefanova, Petia Genova-Kalou, Petya Chaveeva, Vasil Kalev, Tanya Tilkova, Tsvetoslav Vassilev, Ivanka Dimova
## Abstract
Parvovirus B19 and cytomegalovirus are significant causes of congenital infections that can lead to adverse pregnancy outcomes. The present study aimed to investigate the infection of B19V and CMV in pregnant women with fetal anemia, effusions and intrauterine growth restriction and determine the utility of routine laboratory screening in pregnancy follow-up. Thirteen women with such pathological pregnancy complications attending an antenatal clinic from April 2024 to March 2025 were tested. Three types of clinical material were examined: maternal blood, amniotic fluid and umbilical cord serum. Participants underwent molecular and serological testing for both B19V and CMV. Demographic data, obstetric histories, and pregnancy outcomes were recorded and analyzed. Our results indicate that three participants showed evidence of either current infection with CMV and seven with B19V. Pregnant women with active infections required further follow-up and fetal surveillance. A stillbirth was reported in one woman with CMV infection. For seven samples that tested positive for B19V DNA, viral sequences were obtained and clustered with genotype 1a reference strains. The findings of this study highlight the significant contribution of B19V and CMV infections during pregnancy, particularly in cases complicated by fetal anemia, effusions, and intrauterine growth restriction.
## 1. Introduction
Viral infections during pregnancy are a significant cause of severe complications and mortality for both mothers and fetuses worldwide, even in high-income countries. Infectious agents can reach the fetus in several ways, transplacentally, perinatally (through vaginal secretions or blood), or postnatally (via breast milk), and can adversely affect the health of the pregnant woman, the fetus, or the newborn [1][2][3][4]. Generally, the risk of neonatal infections is inversely proportional to the gestational age at acquisition [1,5].
Parvovirus B19 (B19V) and cytomegalovirus (CMV) are pathogens that may be transmitted prenatally through the transplacental route or perinatally through blood or vaginal secretions and can lead to serious complications, including anemia, spontaneous abortion, premature birth, and stillbirth. Both viruses are present worldwide, and there are currently no specific vaccines available for either. Additionally, B19V re-emerged across Europe and Bulgaria in 2024, raising concerns about vertical transmission and neonatal morbidity [6,7].
B19V is a single-stranded DNA virus from the Parvoviridae family and Erythrovirus genus, primarily causing erythema infectiosum, commonly called fifth disease. While a significant percentage of adults may experience asymptomatic infections, the consequences of B19V infection during pregnancy can be severe, including fetal anemia, hydrops fetalis and intrauterine fetal death [1]. B19V particles can cross the placenta and inhibit fetal erythropoiesis, leading to aplastic crisis and subsequent congestive anemia, hypoxia, and heart failure [1,[8][9][10]. The probability of experiencing these complications after 20 weeks of gestation is approximately 2.3% [11,12]. Research indicates that between 50% and 65% of women of reproductive age have developed immunity to this virus [8][9][10]. During epidemic outbreaks, it is estimated that 20% to 30% of seronegative women (those who have not previously been exposed to the virus) will contract the infection.
CMV is a double-stranded DNA virus that belongs to the family Orthoherpesviridae, (subfamily Betaherpesvirinae, genus Cytomegalovirus), and is one of the most common congenital viral infections, presenting with a range of clinical manifestations. In most cases, CMV infection is asymptomatic (90%), but it can occasionally present as a mild febrile illness with nonspecific symptoms such as fatigue, myalgia, rhinitis, pharyngitis, and headache [13]. Among pregnant individuals, CMV has a seroprevalence of 42.3-68.3% in developed countries. In addition to the main clinical manifestations of the disease, the virus can also lead to anemia and alterations in serum iron metabolism [14][15][16]. The risk of transmission of the infection to the fetus is highest during primary infection, estimated at 30-40% [17].
The gold standard in diagnosing fetal anemia is the measurement of the middle cerebral artery peak systolic velocity (MCA-PSV) during 18-35 weeks' gestation. MCA-PSV Doppler is a standard (routine-in-risk) test in specialized prenatal/maternal-fetal medicine units, primarily for pregnancies with known or suspected risk of fetal anemia, such as alloantibodies in the mother, maternal viral infection, abnormal fetal heart rate, etc. Laboratory diagnosis and established methods for confirming B19V and CMV infections rely on serological and molecular techniques. Testing for specific B19V and CMV IgM antibodies, combined with the presence of viral DNA, provides definitive evidence of acute infection, which is particularly important for monitoring cases of pathological pregnancy [17]. To study the dynamics of viral evolution and their epidemiological distribution, next-generation sequencing (NGS) techniques are increasingly utilized.
Taking all of this into consideration, the present study aimed to investigate the infection of B19V and CMV in pregnant women with fetal anemia, effusions and intrauterine growth restriction, evaluate the utility of routine molecular and serological viral screening, and investigate its role in pregnancy follow-up.
## 2. Results
Over a period of twelve months, 13 pregnant women with fetal anemia, effusions, and intrauterine growth restriction were screened for two of the most common viral agents that can cause congenital infections if transmitted from a pregnant woman to her baby: B19V and CMV.
## 2.1. B19V Infection
In 7 patients (54%), B19V infection was confirmed. The main reported clinical complications included fetal anemia, ascites, and hydrops fetalis. All confirmed patients are in the second trimester of pregnancy. The virus was detected in all clinical specimens using PCR, while serological methods (ELISA for IgM and IgG) confirmed the infection in four cases. In four instances, follow-up clinical samples were collected from both the fetus in utero and the mother. Notably, positivity was detected at a very early cycle, with cycle threshold (Ct) values ranging from 13 to 19 in samples taken in utero. A mostly favorable outcome of the pregnancies was reported (see Table 1). During pregnancy, when B19V infection was diagnosed, an intrauterine blood transfusion was performed. This procedure successfully controlled congenital anemia and ensured the normal development of the fetus in the monitored women. Normal fetal development and live births were observed in five of the patients studied who were confirmed to have B19V infection. In the remaining two patients, control of fetal anemia was also noted; however, they were not followed up because they continued their care in other gynecological offices.
Whole-genome sequencing was performed in seven B19V-positive samples using the NGS method. All Bulgarian sequences were associated with genotype 1a by phylogenetic analysis. Therefore, genotype 1a of B19V was detected in clinical materials from both the mother and the fetus. The Bulgarian sequences showed the closest phylogenetic similarity to those from the Netherlands and Italy in 2024 (see Figure 1). Figure 1. A phylogenetic analysis of B19V was conducted, focusing on the NC-VP1u protein and the complete viral genome. The phylogeny tree was generated by the ML method with 1000 bootstrap replicates. The phylogenetic tree was constructed based on these measurements. Sequences from reference strains that represent known genotypes were obtained from GenBank, along with their corresponding identification numbers. Bulgarian sequences were highlighted in blue. The tree was rooted using the strain GQ243610 HBoV as a reference point.
## 2.2. CMV Infection
In the study, 3 out of the 13 pregnant women (23%) were confirmed with CMV infection. The ages of these patients were 19, 28 and 32. The most frequently reported complications included fetal growth restriction, as evidenced by changes in the brain, heart, and intestines. CMV infection was validated through real-time PCR in clinical samples, including amniotic fluid and umbilical cord serum. Unfortunately, one of these patients experienced stillbirth during the pregnancy (see Table 2). In one patient, who was pregnant in the third trimester (30 weeks gestation), CMV IgM and IgG antibodies were detected by serological methods (ELISA), but she refused to have an amniocentesis and CMV infection was not confirmed by PCR. No sequencing was performed on the CMV-positive samples since all had a Ct value above 30.
In two of the thirteen (2/13, 15%) monitored pregnant women, no B19V or CMV infection was detected, and the cause of the developed pathology is likely due to another factor.
## 3. Discussion
The present study underscores the clinical relevance of maternal molecular genetic screening for B19V and CMV as key determinants of congenital infection risk. B19V is not regarded as a teratogenic agent that affects embryogenesis during the first 8-10 weeks of gestation; therefore, it is not an indication for pregnancy termination. However, it is recognized as a human pathogen that can infect the placenta [16]. Reports suggest that B19V infection during pregnancy occurs in about 1-5% of women, with the estimated rate of vertical transmission during maternal infection ranging from 17% to 33% [18]. Data in the literature suggest that when a seronegative mother becomes infected, the fetus has a favorable outcome in 85% of cases [19]. The effects of B19V infection on the fetus can vary widely, ranging from asymptomatic carrier status to spontaneous abortion, hydrops fetalis, congenital anemia, and intrauterine fetal death [20]. Since early 2024, several European countries have reported an increase in B19V infections, particularly among pregnant women and children. This trend emphasizes the need for enhanced epidemiological surveillance, especially given the limitations of routine monitoring and the potential impacts of COVID-19-related immunity gaps in the post-pandemic period [6,7,21]. In Bulgaria, where an overall increase in B19V incidence was noted during this study, thirteen women with pathological pregnancies were screened. Our results indicated that all confirmed B19V patients experienced favorable pregnancy outcomes following primary B19V infection. However, this was associated with a heightened risk of vertical transmission and reported conditions such as fetal anemia, hydrops, or ascites. All women with B19V in our study were diagnosed with anemia, which was managed during their pregnancies. Intravenous blood transfusions were performed to manage congenital anemia, leading to normal fetal development [6]. Targeted serological testing during B19V outbreaks, combined with weekly Doppler surveillance of fetuses with confirmed maternal infection, remains the most evidence-based approach to preventing hydrops and optimizing the timing of intrauterine transfusions [6,22]. B19V was successfully isolated from maternal and intrauterine fetal blood samples, with serum PCR assays detecting high levels of viremia. This study marks the first time that sequencing of B19V from clinical samples taken in utero has been conducted in the country. The comprehensive NGS analysis confirms the presence of the B19V 1a genotype in the examined cohort. Similar studies from 2024 indicate that genotype 1a is the dominant strain in Europe among various groups of infected individuals [7,23,24]. Due to the uniform genetic affiliation of the B19V genetic sequences we isolated, we did not detect any evolutionary advantage in terms of genotype and clinical complications. Previous studies on the circulation of B19V in Bulgaria, particularly among patients with fever rash syndrome and those with hematological disorders, have confirmed that genotype 1a continues to persist within the country's territory [25,26].
CMV can be transmitted vertically at any stage of pregnancy. The most severe effects on the fetus are associated with infections that occur during the first trimester, with the severity of the disease decreasing as gestational age increases. The highest risk of transmitting the infection to the fetus occurs during primary infection, and in 0.2% to 2.5% of seropositive pregnant women, premature birth may happen [17]. Statistics indicate that 30% of newborns with severe congenital CMV infection do not survive [16]. Among those who survive, more than half will ultimately develop neurological complications. Congenital CMV infection remains one of the most prevalent causes of non-genetic hearing loss and developmental delay, affecting 0.5-2% of all live births globally [27,28]. In our follow-up of women with CMV infection, one case of stillbirth was documented.
One limitation of our study is the small number of patients screened, as well as the missing information on pregnancy outcomes for five of the pregnant women confirmed to have B19V and CMV infections.
Molecular methods, such as PCR assay and NGS, have shown greater sensitivity and specificity compared to traditional serology. Detection of viral DNA in maternal plasma or amniotic fluid confirms active infection and can be integrated into prenatal screening programs [29]. These results reinforce the need for proactive maternal monitoring, especially in populations with high exposure risk or limited access to serological testing.
## 4. Materials and Methods
## 4.1. Patients and Study Design
Over a twelve-month period, from April 2024 to March 2025, a total of 17 clinical samples from 13 women with pathological pregnancies, particularly those with fetal anemia, effusions, and intrauterine growth restriction, were collected at the prenatal clinic of Dr. Shterev Hospital in Sofia and were studied prospectively. The patients' ages ranged from 19 to 41 years, with a median age of 31 ± 5.45 years. Women who were tested were between 19 and 30 gestational weeks (10 in second and 3 in third gestational trimester) pregnant. For the purposes of the study, clinical materials from pregnant women: maternal blood (n = 7) and amniotic fluid (n = 5), and from the fetus, umbilical cord serum (n = 5), were examined. These specimens were analyzed at the National Reference Laboratory for Measles, Mumps, and Rubella, which is part of the National Centre of Infectious and Parasitic Diseases in Sofia, Bulgaria, as well as at the Medical Complex "Dr. Shterev" in Sofia.
## 4.2. Enzyme-Linked Immunosorbent Assay (ELISA)
Blood samples collected from the mothers and from baby-in-uterus were tested for the presence of anti-CMV/B19V immunoglobuline G (IgG) and M (IgM) antibodies using Euroimmun ELISA kits (EUROIMMUN Medizinische Labordiagnostika AG, Lübeck, Germany).
Positive, negative, and cut-off controls were included in all runs, and results were and the results were interpreted qualitatively as positive, negative, and borderline, according to the manufacturer's instructions.
## 4.3. DNA Extraction and Real-Time PCR for Viral Amplification
Viral DNA was extracted from all specimens using the PureLink Viral RNA/DNA Mini Kit (Thermo Fisher Scientific Inc., Waltham, MA, USA). Real-time polymerase chain reaction (qPCR) by ViroReal Kit Parvovirus B19, Ingenetix GmbH, Vienna, Austria, and CMV REAL-TIME PCR Detection Kit, "DNA-Technology Research & Production", Moscow Region, Russia, for CMV were used. Positive and negative controls were included in each real-time PCR run. Samples testing positive for B19V with a Ct value below 30 were selected for NGS.
## 4.4. Sequencing and Phylogenetic Analysis
## •
Next-Generation Sequencing
The targeted NGS method utilizing the Viral Surveillance Panel v2 Kit was employed to simultaneously isolate the genomes of viruses involved in mixed infections. This kit, developed by Illumina in San Diego, CA, USA, was used to characterize over 200 different viruses. NGS was conducted using the Illumina MiSeq system, Illumina, Inc., San Diego, CA, USA equipped with the 600-cycle v3 reagent kit.
Following sequencing, DNA libraries were analyzed for fragment size distribution with the QIAxcel Advanced capillary electrophoresis system (Qiagen Hilden, Germany). Library normalization was performed using the Qubit 4 Fluorometer along with the Invitro-gen™ Quant-iT™ 1X High-Sensitivity (HS) Broad-Range (BR) dsDNA Assay Kit (Thermo Fisher Scientific in Waltham, MA, USA).
## • Genomic and phylogenetic analyses
We used the DRAGEN Microbial Enrichment Plus (DME+) software (version 1.1.1), available on the BaseSpace platform from Illumina (Cambridge, UK), for sequence assembly and FASTA file extension extraction. The B19V genetic sequences have been deposited in the GenBank sequence databases (accession numbers: PX647871, PX647872, PX647873, PX647874, PX647875, PX647876 and PX647877). BLAST searches were performed using the online NCBI BLAST tool (BLAST+ version 2.14.1) in multiple databases to retrieve references and closely related sequences. We used Geneious Prime 10.6.1 (GraphPad Software, LLC, Boston, MA, USA) for alignment, while the MEGA11 (Molecular Evolutionary Genetics Analysis) software, developed in the United States at Pennsylvania State University, was used to construct the phylogenetic tree and its overall design.
## 5. Conclusions
The findings of this study highlight the significant contribution of B19V and CMV infections during pregnancy, particularly in cases complicated by fetal anemia, effusions, and intrauterine growth restriction. A considerable proportion of the examined pregnant women showed evidence of active or recent infection, with B19V detected more frequently than CMV. This is related to the reported increased B19V circulation in 2024 in Bulgaria and Europe. The identification of B19V genotype 1a among positive samples is consistent with its known global circulation. These results support the potential benefit of implementing routine or targeted screening strategies for B19V and CMV during pregnancy follow-up, especially in high-risk cases, to enable early detection, appropriate clinical management, and improved pregnancy outcomes.
## References
1. Madrid, Varo, Maculuve et al. (2018) "Congenital Cytomegalovirus, Parvovirus and Enterovirus Infection in Mozambican Newborns at Birth: A Cross-Sectional Survey"
2. Adams Waldorf, Mcadams (2013) "Influence of Infection During Pregnancy on Fetal Development" *Reproduction*
3. Del Pizzo (2011) "Focus on Diagnosis: Congenital Infections (TORCH)" *Pediatr. Rev*
4. Neu, Duchon, Zachariah et al. (2015) *Clin. Perinatol*
5. Akhtar, Hashmi, Manzoor (2025) "The Synergistic Tapestry: Unraveling the Interplay of Parvovirus B19 with Other Viruses" *Int. J. Infect. Dis*
6. Betta, Leonardi, Mattia et al. (2025) "Congenital Parvovirus B19 During the 2024 European Resurgence: A Prospective Single-Centre Cohort Study"
7. Beligni, Alessandri, Cusi (2025) "Genotypic Characterization of Human Parvovirus B19 Circulating in the 2024 Outbreak in Tuscany, Italy. Pathogens"
8. Ornoy, Ergaz (2017) "Parvovirus B19 Infection During Pregnancy and Risks to the Fetus" *Birth Defects Res*
9. Kielaite, Paliulyte (2022) "Parvovirus (B19) Infection During Pregnancy: Possible Effect on the Course of Pregnancy and Rare Fetal Outcomes. A Case Report and Literature Review"
10. Bonvicini, Puccetti, Salfi et al. (2011) "Gestational and Fetal Outcomes in B19 Maternal Infection: A Problem of Diagnosis" *J. Clin. Microbiol*
11. Dittmer, Guimarães, Peixoto et al. (2024) "Parvovirus B19 Infection and Pregnancy: Review of the Current Knowledge" *J. Pers. Med*
12. Kagan, Hoopmann, Geipel et al. (2024) "Prenatal Parvovirus B19 Infection" *Arch. Gynecol. Obstet*
13. Syggelou, Iacovidou, Kloudas et al. (1205) "Congenital Cytomegalovirus Infection" *Ann. N. Y. Acad. Sci*
14. De Paschale, Agrappi, Manco et al. (2009) "Incidence and Risk of Cytomegalovirus Infection During Pregnancy in an Urban Area of Northern Italy" *Infect. Dis. Obstet. Gynecol*
15. Enders, Daiminger, Lindemann et al. (1996) "Cytomegalovirus (CMV) Seroprevalence in Pregnant Women, Bone Marrow Donors and Adolescents in Germany" *Med. Microbiol. Immunol*
16. Gao, Gao, He et al. (2018) "Infection Status of Human Parvovirus B19, Cytomegalovirus and Herpes Simplex Virus-1/2 in Women with First-Trimester Spontaneous Abortions in Chongqing, China" *Virol. J*
17. Ornoy, Diav-Citrin (2006) "Fetal Effects of Primary and Secondary Cytomegalovirus Infection in Pregnancy" *Reprod. Toxicol*
18. Malutan, Ormindean, Diculescu et al. (1667) "Parvovirus B19 in Pregnancy-Do We Screen for Fifth Disease or Not?" *Life*
19. Crane, Mundle, Boucoiran (2014) "Maternal Fetal Medicine Committee. Parvovirus B19 Infection in Pregnancy" *J. Obstet. Gynaecol. Can*
20. Papadatou, Tologkos, Deftereou et al. (2023) "Viral-Induced Inflammation Can Lead to Adverse Pregnancy Outcomes" *Folia Med*
21. (2024) "Risks Posed by Reported Increased Circulation of Human Parvovirus B19 in the EU/EEA" *ECDC Report*
22. Gigi, Anumba (2021) "Parvovirus B19 Infection in Pregnancy-A Review" *Eur. J. Obstet. Gynecol. Reprod. Biol*
23. Bichicchi, Guglietta, Rocha Alves et al. (2023) "Next Generation Sequencing for the Analysis of Parvovirus B19 Genomic Diversity" *Viruses*
24. Alves, Amado (2025) "A Retrospective Analysis of Clinical and Epidemiological Aspects of Parvovirus B19 in Brazil: A Hidden and Neglected Virus Among Immunocompetent and Immunocompromised Individuals" *Viruses*
25. Ivanova, Mihneva, Toshev et al. (2004) "Insights into Epidemiology of Human Parvovirus B19 and Detection of an Unusual Genotype 2 Variant" *Eurosurveillance*
26. Krumova, Andonova, Stefanova et al. "Primate Erythroparvovirus 1 Infection in Patients with Hematological Disorders" *Pathogens*
27. Rawlinson, Boppana, Fowler et al. (2017) "Congenital Cytomegalovirus Infection in Pregnancy and the Neonate: Consensus Recommendations for Prevention"
28. Boppana, Ross, Fowler (2013) "Congenital Cytomegalovirus Infection: Clinical Outcome" *Clin. Infect. Dis*
29. Gilad, Agrawal, Philippopoulos et al. (2024) "Is a Higher Amniotic Fluid Viral Load Associated with a Greater Risk of Fetal Injury in Congenital Cytomegalovirus Infection-A Systematic Review and Meta-Analysis" *J. Clin. Med*
30. "The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods"
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# Local and introduced lineages drive MERS-CoV recombination in Egyptian camels
Mokhtar Gomaa, Kimberly Edwards, Ruixuan Wang, Ahmed El Taweel, Yassmin Moatasim, Omnia Kutkat, Mina Kamel, Hamdy El-Nagar, Vijaykrishna Dhanasekaran, Mohamed Ali, Ghazi Kayali, Rabeh El-Shesheny
## Abstract
Dromedary camels are the primary reservoir for Middle East respiratory syndrome coronavirus (MERS-CoV), a zoonotic coronavirus responsible for sporadic human infections. While clade B predominates in the Arabian Peninsula and is fre quently linked to zoonotic outbreaks and household secondary transmission, clade C circulates primarily in African camels, with limited evidence of human infections. The extent of MERS-CoV transmission, genetic diversity, and cross-species potential in North Africa remains poorly characterized. Here, we investigate MERS-CoV incidence, seropre valence, and genomic recombination in dromedary camels and sympatric livestock across slaughterhouses and farms in Egypt. MERS-CoV was detected in 12% of camels sampled at slaughterhouses, with no evidence of infection in cattle, buffalo, sheep, or goats. Seroprevalence was higher in slaughtered camels (79%) than camels on farms (12%). Phylogenetic analyses of MERS-CoV genomes obtained from dromedary camels revealed an introduction of clade B into Egypt, originating from the Arabian Peninsula. Furthermore, we identified recombination events between clades B and C, in addition to events within each clade. This included at least one clade C virus that acquired multiple genomic regions from the newly introduced clade B viruses. These findings suggest that newly introduced MERS-CoV strains can recombine with locally circulating viruses, generating novel variants with potential zoonotic implications and challenging assumptions of limited cross-regional exchange. Enhanced surveillance, targeted control measures, and a One Health approach are crucial to mitigating MERS-CoV transmission and the emergence of recombinant strains. IMPORTANCE This study highlights the importance of monitoring Middle East respiratory syndrome coronavirus (MERS-CoV) in dromedary camels, which are the main animal source of this virus that can occasionally infect humans. While most human cases have been linked to strains in the Arabian Peninsula, this research focused on Egypt, where the virus is less understood. Among surveyed dromedary camels and associated livestock, a significant number of camels at slaughterhouses were infected, and many had antibodies showing past exposure. Importantly, we discovered that a strain common in the Arabian Peninsula had recently entered Egypt and mixed genetically with local strains. This mixing, or recombination, can lead to new virus versions that may pose new risks to humans. The findings challenge the belief that MERS-CoV strains in different regions do not interact and highlight the need for stronger monitoring and prevention strategies. A One Health approach, linking animal, human, and environmental health, is key to managing future risks.
reservoir (1). Zoonotic infection primarily occurs through direct or indirect contact with infected dromedary camels (2). Secondary human-to-human transmission has been reported among household members, healthcare workers, and other patients in close contact with infected individuals (3). Since its emergence in 2012, a total of 2,613 confirmed MERS-CoV cases have been reported globally, resulting in 943 deaths (case fatality rate ~36%, as of May 2024). These cases occurred across all WHO epidemiological regions in 27 countries. Saudi Arabia remains the epicenter, with 2,204 cases and 862 fatalities (39%), including four fatal cases reported in 2024 (4).
MERS-CoV has evolved into three distinct clades (A, B, and C) with clear geographic associations. Clade B has largely displaced clade A in the Arabian Peninsula and frequently causes zoonotic infections, whereas clade C circulates primarily among camels in Africa (5,6). The zoonotic potential of MERS-CoV differs between clades B and C due to a combination of viral genetics and human behavior (7). Human seroprevalence rates vary depending on contact type, ranging from 0.15% in the general Saudi population to 2%-14% in high-risk groups such as farm workers, slaughterhouse workers, and camel racing workers (8,9).
The dipeptidyl peptidase 4 (DPP4) receptor, the cellular entry point for MERS-CoV, is conserved across multiple mammalian species, raising concerns about interspecies transmission (10). MERS-CoV RNA and antibodies have been detected in animals with direct camel contact, including sheep, goats, cattle, and donkeys (11)(12)(13), but their role in viral maintenance is unclear. Understanding transmission dynamics, genetic diversity, and viral recombination in regions with frequent camel trade, such as North Africa, is essential for assessing zoonotic risk.
Here, we investigate MERS-CoV incidence, seroprevalence, and genomic diversity and recombination in dromedary camels and sympatric livestock across slaughterhouses and farms in Egypt. We assess the role of live animal markets in viral transmission, character ize the evolutionary relationships between local and introduced MERS-CoV lineages, and evaluate the potential for interspecies transmission. Our findings provide critical insights into MERS-CoV epidemiology in North Africa and inform strategies for surveillance and risk mitigation.
## MATERIALS AND METHODS
## Study design and sample collection
Between May 2023 and February 2024, nasal swabs (n = 270) and blood samples (n = 202) were collected from dromedary camels and co-housed livestock (cattle, water buffalo, sheep, and goats) to determine MERS-CoV incidence and seroprevalence. Samples were collected from live animals on farms in Marsa Matruh Governorate (northwestern coast) and from slaughtered animals at two abattoirs in Giza Governorate (Greater Cairo, central north). Camels and accompanying livestock were co-housed at both sampling sites. Swabs were placed on ice in viral transport medium (Dulbecco's Modified Eagle Medium [DMEM]) supplemented with 4% fetal bovine serum and 5% antibiotic-antimycotic mix (Gibco, Life Technologies). Blood samples were drawn from the jugular vein using 20-gauge needles and vacuum serum gel tubes, centrifuged at 1,500 × g for 5 minutes, and sera were stored at -20°C.
## MERS-CoV detection
Nasal swabs were tested for MERS-CoV using WHO guidelines for laboratory testing (14). Viral nucleic acids were extracted with the MagMAX Viral/Pathogen Nucleic Acid Isolation Kit (Applied Biosystems) on a KingFisher Flex Purification System. RNA extracts (200 µL per nasal swab sample, 50 µL elution) were tested using real-time RT-PCR targeting upstream of the envelope gene (upE) (AgPath-ID One-Step RT-PCR Kit, Applied Biosystems). Positive samples underwent confirmatory ORF1a real-time RT-PCR (15).
## Microneutralization assay for anti-MERS-CoV antibodies
MERS-CoV MN assay using live virus was performed in a class III biosafety cabinet. Neutralizing antibodies were assessed using MERS-CoV/dromedary camel/Egypt/NC270 (16). Sera were heat-inactivated at 56°C for 30 minutes and serially diluted twofold starting at 1:10 in DMEM with 4% BSA and 1% antibiotic-antimycotic. Diluted sera were incubated with 100 TCID 50 of the virus and incubated for 1 hour at 37°C. Vero-E6 cells in 96-well plates were inoculated with 50 µL per well and incubated for 90 minutes at 37°C. The inoculum was removed, the cells were supplemented with 150 µL DMEM per well, and plates were incubated for 3 days at 37°C with 5% CO 2 . The highest serum dilution inhibiting the viral cytopathic effect was recorded as the neutralizing titer, and animals with titers ≥20 were considered seropositive.
## Genome sequencing
cDNA synthesis was performed using the SuperScript IV First-Strand System (Invitrogen, MA, USA) with random hexamers. MERS-CoV genomes were amplified by multiplex PCR (Q5 High-Fidelity DNA Polymerase, New England Biolabs) using two in-house-designed primer pools (Table S1) to generate ~800 bp overlapping fragments. Amplicons were purified (GFX PCR DNA and Gel Band Purification Kit, GE Healthcare), and sequencing libraries were prepared using the Nextera XT DNA Library Prep Kit (Illumina). Libraries were sequenced on an Illumina MiniSeq with 150 bp paired-end reads. Sequence contigs were assembled using CLC Genomic Workbench (CLC Bio, Qiagen). Ten complete MERS-CoV genome sequences from this study were deposited into GenBank (Table S2).
## Phylogenetic analysis and recombination detection
MERS-CoV genomes from dromedary camels were analyzed alongside publicly available nucleotide sequences >20 kb in length with complete collection dates from 2018 to 2023 inclusive, downloaded from GenBank on 12 May 2025. Two to three sequences were selected from each transmission cluster (where sequence metadata indicated the same collection date and location), and identical sequences were removed. Accession numbers and strain names of sequences used for recombination analysis are provided in Table S3.
Sequences were aligned with MAFFT v.7.520 (17), and recombination was initially assessed with Recombination Detection Program 5 (RDP5) v.5.64 (18) using the following tools: RDP, GENECONV (for deep divergence), MaxChi (sensitive for small breakpoints), and 3SEQ (useful for recent events). Bonferroni correction was applied to reduce false positives. Breakpoints were further assessed with Genetic Algorithms for Recombination Detection (GARD) in HyPhy (19) under the GTR + Γ nucleotide substitution model, which uses phylogenetic incongruence and stepwise model selection to infer the number and location of breakpoints across the genome based on AICc. Recombination events involving the 2023 Egyptian camel strains were considered significant if corroborated by two or more detection methods.
To contextualize topology discordance, the nucleotide alignment was split at probable breakpoints, and maximum-likelihood trees were constructed using IQ-TREE2 (20), with 1,000 bootstrap replicates. SimPlot++ v. 1.3 (21) was used to illustrate the inferred clade B and C recombination events. For each breakpoint-free region, tempo ral signal was confirmed via root-to-tip regression of genetic distance against sample collection date in TempEst v.1.5.3 (22). Time-scaled phylogenies were then constructed using TreeTime v.0.11.3 (23), and phylogenies with the best temporal signals (Fig. S1) were used to estimate the timing of recombination events.
## RESULTS
## Demographics of camels and sympatric livestock
A total of 270 animals were sampled to assess MERS-CoV prevalence and seroprevalence (Table 1). The majority of camels (n = 130; 81%) were sampled at slaughterhouses in Giza Governorate, while the remainder were sampled on farms in Matruh Governorate. Cattle, water buffalo, and 37% of sheep (n = 19/51) were sampled at slaughterhouses, while the remaining sheep (n = 32/51) and all goats were sampled on farms (Table 1).
Most camels were adults (n = 149, median age = 10 years), with a small number of juveniles (n = 6, <2 years) and subadults (n = 9, 3-4 years). Accompanying animals included cattle (n = 36), water buffalo (n = 6), sheep (n = 51), and goats (n = 13) (Table 1). All cattle, water buffalo, and sheep were adults. Among goats, seven were adults (2-4 years) and six were subadults (~1 year). The majority of camels (80%) and all cattle were male, while most sheep (78%), water buffalo (67%), and all goats were female.
## MERS-CoV incidence and seroprevalence
During two sampling visits, 15 days apart in late 2023, 12.2% (n = 20/164) of dromedary camels sampled at slaughterhouses in the Giza Governorate tested positive for MERS-CoV. In November, 56.5% (13/23) of adult male camels tested positive, decreasing to 29.2% (7/24) in December. MERS-CoV was not detected from the nasal swabs of camels sampled on farms, and the nasal swabs of all co-housed livestock also tested negative by real-time RT-PCR.
Overall, 60% of camels had neutralizing antibodies to MERS-CoV (titers ≥20). Seroprevalence was significantly lower in camels on farms (n = 4/34; 12%) than in slaughterhouse camels (79%; P < 0.0001) (Table 2). Among accompanying animals, 17% (n = 4/24) of bulls at the slaughterhouse were seropositive, including three with titers of 20 and one with a titer of 160. Two sheep at the slaughterhouse also tested seropositive (titers: 20, 80), while all five water buffaloes were seronegative. All sheep and goats sampled on farms in Matruh Governorate were seronegative for MERS-CoV antibodies (Table 2).
## MERS-CoV recombination in dromedary camels
Ten MERS-CoV viruses were sequenced from dromedary camel nasal swabs (Table S2). An initial maximum-likelihood phylogeny indicated that 9 of the 10 camel isolates clustered with West African clade C camel strains, while MERS-CoV/dromedary camel/ Although only a partial genome sequence could be recovered from the recombinant Egyptian camel isolate MERS-CoV/dromedary camel/Egypt/STM0184/2023 (STM0184), RDP5 tools identified multiple portions of its genome that were acquired from the newly introduced clade B strain, STM0244, including portions of ORF1ab, spike, and nucleocap sid proteins (Table 3; Fig. S2). Additional clade B and C recombination events were detected in the spike of STM0184 and ORF1ab of strain STM0186, but with insufficient statistical support (Table S4). Egyptian camel strains STM0185, STM0186, STM0189, and STM0199 showed evidence of historical recombination within clade C, but these events also lacked sufficient statistical backing (Table S4).
GARD, which identifies recombination based on phylogenetic incongruence, detected significant phylogenetic recombination in the 36-sequence MERS-CoV alignment (30,051 sites). The best-fitting model contained nine breakpoints, at positions 4090, 6241, 8314, 10627, 16570, 17910, 21684, 24470, 27278, and 29427. There was strong evidence for recombination (ΔAICc = 35.73 compared to the single-tree model), indicating a significantly better fit with recombination. To visualize recombination patterns across the genome, the sequence similarity was then compared against clade B and C reference groups using SimPlot++ (Fig. 1A).
Across nearly all of the genomic regions analyzed, the clade B isolate, STM0244, shared common ancestry with Saudi Arabian camel strains isolated in November and December of 2023 (Fig. 1C). However, a historical recombination among clade B strains was detected around positions 17910-24468, presumably involving a strain ancestral to STM0244 and the 2023 Saudi Arabian camel isolates (Table 3). Time-measured phylogenetic estimates suggest the clade B recombination occurred around January 2022 (90% CI: May 2021-October 2022) (Fig. 2B). S2 andS3. To examine topological discordance and infer the evolutionary history of the interclade recombination, genomic regions were selected based on the breakpoint estimates and their confidence intervals, while accounting for gaps in the recombinant sequence, STM0184 (Fig. S2). Blocks with the strongest temporal signals were used to infer timing of recombination events (Fig.
## DISCUSSION
This study provides critical insights into the prevalence, seroprevalence, and evolutionary dynamics of MERS-CoV among dromedary camels and associated livestock in Egypt.
Consistent with previous studies identifying dromedary camels as the primary MERS-CoV reservoir, our findings revealed significantly higher viral prevalence in camels sampled at slaughterhouses compared to farms. Besides the fact that anti-coronavirus antibod ies wane over time (24,25), the sampled farm implemented a quarantine policy for adding new animals. On the other hand, slaughterhouses usually aggregate animals from diverse geographic origins within Egypt and those imported from other countries, likely serving as hubs for viral mixing and amplification and increasing the potential for zoonotic spillover (26)(27)(28)(29)(30)(31). This pattern parallels findings from other livestock-associated viruses, such as H7N9 influenza virus, where trade hubs and live markets have served as critical nodes for viral dissemination (32). In contrast, the absence of MERS-CoV among farmed camels and accompanying livestock highlights the protective effect of controlled environments and restricted animal movement. These results emphasize the role of slaughterhouses and live animal markets in amplifying MERS-CoV transmission along the supply chain, reinforcing the importance of biosecurity measures to limit inter-herd contact and viral spread. It is important to note that a very small number of non-camelid mammals were included in this study, and the results may not reflect the true incidence or prevalence of MERS-CoV. Genomic analyses identified multiple recombination events, both within and among clades B and C, reflecting the well-documented role of recombination in coronavirus evolution (33). Recombination can generate viral variants with altered phenotypic traits, as seen in the emergence of MERS-CoV, in which the ancestral receptor binding domain was replaced by that of another merbecovirus lineage, modifying receptor usage (34). The identification of recombinant MERS-CoV strains in this study suggests that interna tional camel trade is a key driver of viral diversity. Given the potential for recombination to produce strains with increased zoonotic potential, sustained regional and interna tional surveillance is essential to monitor evolutionary trends and emerging risks.
The precise timing and breakpoint positions of these recombination events remain uncertain due to the limited number of contemporary MERS-CoV sequences, miss ing bases in the sequenced genomes, and frequency of coronavirus recombination. Additionally, there was some discordance among the tools used to infer breakpoints, attributable to differences in their underlying algorithms, sensitivity, and specificity. Genetic distance-based methods (i.e., 3SEQ and RDP) have a high false-positive rate and are more sensitive to recent, minor recombination events, whereas tools that infer recombination based on topological discordance, such as GARD, are better suited to examine deep discordance and interclade recombination. We therefore only considered breakpoints that were corroborated by strong statistical support from multiple detection tools.
The dissemination of potentially zoonotic clade B viruses into North Africa and interclade recombination is cause for concern. Time-scaled phylogenetic analyses suggest that the clade B and C recombinant may have circulated undetected for several months. These findings highlight the urgent need for sustained surveillance in animals to better understand MERS-CoV evolutionary dynamics and the zoonotic potential of emerging strains. Although MERS-CoV elimination remains unfeasible due to its endemicity in dromedary camels and logistical barriers to large-scale interventions, targeted control strategies offer pathways to mitigate future zoonotic spillover. A One Health framework-integrating veterinary, human, and environmental health surveil lance-will be crucial for managing MERS-CoV risks. Key strategies include enhanced biosecurity in high-risk settings and public awareness campaigns focused on reducing human-animal contact.
In conclusion, this study underscores the interconnected roles of viral evolution, international trade, and supply chain dynamics in shaping MERS-CoV epidemiology. The observed recombination events and prevalence patterns reinforce the need for coordinated, regional surveillance to detect emerging variants and mitigate public health risks. Strengthened biosecurity measures, targeted interventions, and sustained One Health efforts will be essential to minimize MERS-CoV transmission and reduce the risk of future outbreaks.
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5. Kiambi, Corman, Sitawa et al. (2017) "Detection of distinct MERS-Coronavirus strains in dromedary camels from Kenya" *Emerg Microbes Infect*
6. Sabir, Lam, Ahmed et al. (2016) "Co-circulation of three camel coronavirus species and recombination of MERS-CoVs in Saudi Arabia" *Science*
7. Chu, Hui, Perera et al. (2018) "MERS coronaviruses from camels in Africa exhibit region-dependent genetic diversity" *Proc Natl Acad Sci*
8. Müller, Corman, Jores et al. (1983) "MERS coronavirus neutralizing antibodies in camels, Eastern Africa"
9. Reusken, Haagmans, Müller et al. (2013) "Middle East respiratory syndrome coronavirus neutralising serum antibodies in dromedary camels: a comparative serological study" *Lancet Infect Dis*
10. Peck, Burch, Heise et al. (2015) "Coronavirus host range expansion and Middle East respiratory syndrome coronavirus emergence: biochemical mechanisms and evolutionary perspectives" *Annu Rev Virol*
11. Kasem, Qasim, Al-Hufofi et al. (2018) "Cross-sectional study of MERS-CoV-specific RNA and antibodies in animals that have had contact with MERS patients in Saudi Arabia" *J Infect Public Health*
12. Ali, El-Shesheny, Kandeil et al. (2015) "Cross-sectional surveillance of Middle East respiratory syndrome coronavirus (MERS-CoV) in dromedary camels and other mammals in Egypt" *Euro Surveill*
13. Kandeil, Gomaa, Shehata et al. (2018) "Middle East respiratory syndrome coronavirus infection in non-camelid domestic mammals" *Emerg Microbes Infect*
14. Organization (2018) "Laboratory testing for Middle East respiratory syndrome coronavirus: interim guidance (revised)"
15. Corman, Eckerle, Bleicker et al. (2012) "Detection of a novel human coronavirus by real-time reversetranscription polymerase chain reaction" *Euro Surveill*
16. Perera, Wang, Gomaa et al. (2013) "Seroepidemiology for MERS coronavirus using microneutralisation and pseudoparticle virus neutralisation assays reveal a high prevalence of antibody in dromedary camels in Egypt" *Euro Surveill*
17. Katoh, Standley (2013) "MAFFT multiple sequence alignment software version 7: improvements in performance and usability" *Mol Biol Evol*
18. Martin, Varsani, Roumagnac et al. (2021) "RDP5: a computer program for analyzing recombination in, and removing signals of recombination from, nucleotide sequence datasets" *Virus Evol*
19. Pond, Posada, Gravenor et al. (2006) "Automated phylogenetic detection of recombination using a genetic algorithm" *Mol Biol Evol*
20. Minh, Schmidt, Chernomor et al. (2020) "IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era" *Mol Biol Evol*
21. Samson, Lord, Makarenkov (2022) "SimPlot++: a Python application for representing sequence similarity and detecting recombination" *Bioinformatics*
22. Rambaut, Lam, Carvalho et al. (2016) "Exploring the temporal structure of heterochronous sequences using TempEst (formerly Path-O-Gen)" *Virus Evol*
23. Sagulenko, Puller, Neher (2018) "TreeTime: maximum-likelihood phylodynamic analysis" *Virus Evol*
24. Alroqi, Barhoumi, Masuadi et al. (2024) "Durability of COVID-19 humoral immunity post infection and different SARS-COV-2 vaccines" *J Infect Public Health*
25. Choe, Perera, Park et al. (2015) "MERS-CoV antibody responses 1 year after symptom onset, South Korea" *Emerg Infect Dis*
26. Ali, Shehata, Gomaa et al. (2017) "Systematic, active surveillance for Middle East respiratory syndrome coronavirus in camels in Egypt" *Emerg Microbes Infect*
27. Abdelazim, Abdelkader, Ali et al. (2023) "A longitudinal study of Middle East respiratory syndrome coronavirus (MERS-CoV) in dromedary Full-Length Text Journal of Virology December"
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29. Chu, Poon, Gomaa et al. (2014) "MERS coronaviruses in dromedary camels" *Egypt. Emerg Infect Dis*
30. Wu, Mcgoogan (2020) "Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72 314 cases from the Chinese center for disease control and prevention" *JAMA*
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Anass Abbad, Brian Lerman, Jordan Ehrenhaus, Brian Monahan, Gagandeep Singh, Adria Wilson, Stefan Slamanig, Ashley Aracena, Neko Lyttle, Jessica Nardulli, Keith Farrugia, Zain Khalil, Ana Silvia Gonzalez-Reiche, Mia Sordillo, Weina Sun, Harm Van Bakel, Viviana Simon, Florian Krammer, Viviana 75n93021c00014, Simon
## Abstract
The evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in antigenically distinct variants that challenge vaccine-induced immunity. The KP.2 monovalent mRNA vaccine was deployed in 2024 to address immune escape by emerging SARS-CoV-2 subvariants. We assessed neutralizing antibody responses in 56 adults with varied exposure histories following KP.2 vacci nation against emerging variants including LP.8.1, LF.7.1, NB.1.8.1, XFG, and BA.3.2. While KP.2 vaccination enhanced neutralization against homologous variants, substantial reductions in neutralizing activity were observed against emerging Omicron variants across all exposure groups. Exposure history showed some influence on neutraliza tion breadth, with self-reported vaccination-only participants exhibiting better crossneutralization compared to individuals with hybrid immunity. Antigenic cartography revealed substantial antigenic distances between KP.2 and emerging variants, highlight ing significant immune escape potential that threatens vaccine protection. IMPORTANCE Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to evolve, producing variants that escape vaccine-induced immunity. The current work shows that KP.2 monovalent vaccination provides limited protection against antigeni cally distant Omicron variants (LP.8.1, LF.7.1, NB.1.8.1, XFG and BA.3.2). These findings highlight the ongoing challenge of maintaining vaccine effectiveness against evolving SARS-CoV-2 variants and argue for continuous updating of vaccines.
The Icahn School of Medicine at Mount Sinai has filed patent applications regarding influenza virus vaccines on which F.K. is listed as inventor. The Icahn School of Medicine at Mount Sinai has filed patent applications relating to SARS-CoV-2 serological assays, NDV-based SARS-CoV-2 vaccines, influenza virus vaccines, and influenza virus therapeutics which list F.K. as co-inventor. V.S. is also listed on the SARS-CoV-2 serological assays patent. F.K. has received royalty payments from some of these patents. Mount Sinai has spun out a company, Castlevax, to develop SARS-CoV-2 vaccines. F.K. is a co-founder and scientific advisory board member of Castlevax. F.K. has consulted for Merck, GSK, Sanofi, Curevac, Gritstone, Seqirus, and Pfizer and is currently consulting for 3rd Rock Ventures and Avimex. The Krammer laboratory is also collaborating with Dynavax on influenza vaccine development. The Simon and van Bakel labs collaborate with Sanofi Pasteur on pathogen surveillance.
See the funding table on p. 6. vaccination soon after an infection), and complex hybrid immunity (n = 29, ≥2 infections plus ≥3 vaccine doses) (Table S1). Serum samples were collected an average of 29 days post-vaccination. We measured neutralizing antibodies against the ancestral WA.1 strain, vaccine-matched KP.2, JN.1, and emerging variants including LP.8.1, LF.7.1, NB.1.8.1, XFG, and BA.3.2 using live and pseudotyped virus microneutralization assays. The tested variants harbor distinct mutation patterns in key antigenic sites (Fig. 1). BA.3.2, a saltation variant with >50 mutations relative to BA.3, was originally identified in South Africa but has subsequently been detected globally (e.g., Germany, the Netherlands, California, and Australia), reflecting its capacity for transmission despite antigenic divergence (2,3). FLiRT (named for the key F456L and R346T mutations) variants contain critical mutations including R346T, F456L, and Q498R that enhance both angiotensin converting enzyme 2 (ACE2) binding and antibody evasion.
KP.2 vaccination enhanced neutralization against homologous KP.2 (GMT: 315) and closely related JN.1 (GMT: 203) variants (Fig. 2A through D). However, post-KP.2 vaccine sera showed substantially reduced neutralization against FLiRT variants across all exposure groups, with 12-fold reductions for LP.8.1, eightfold for LF.7.1, 18-fold for NB.1.8.1, and 25-fold for XFG compared to WA.1. Neutralizing titers against WA.1 (GMT: 733) significantly exceeded those against LP.8.1 (GMT: 60, P < 0.0001), LF.7.1 (GMT: 92, P < 0.0001), NB.1.8.1 (GMT: 40, P < 0.0001), and XFG (GMT: 29, P < 0.0001). BA.3.2 showed intermediate neutralization (GMT: 197), representing a 3-fold reduction compared to the ancestral strain.
Exposure history influenced neutralization breadth (Fig. 2E). Participants with selfreported vaccination-only immunity exhibited the most potent and broad responses, with highest titers against KP.2 (GMT: 461), JN.1 (GMT: 298), and better neutralization of FLiRT variants compared to other groups (Fig. 2B). Conversely, post-infection boosted participants exhibited lower cross-neutralization against LP.8.1 (GMT: 39), LF.7.1 (GMT: 76), NB.1.8.1 (GMT: 29), and XFG (GMT: 17) (Fig. 2D). Participants with complex hybrid immunity showed intermediate patterns across all variants (Fig. 2C). Importantly, it is unclear if these differences are big enough to be biologically meaningful, and they could also be an artifact of a small number of subjects tested. For these reasons, they should not be over-interpreted and require confirmation.
Antigenic cartography quantified these escape patterns (4, 5), revealing that emerg ing variants occupy distant positions in antigenic space relative to KP.2 (Fig. 2F). FLiRT variants clustered at antigenic distances exceeding three units from KP.2 (representing >8-fold neutralization reductions), while BA.3.2 occupied an intermediate but distinctly separate position. This spatial organization directly correlates with neutralization data and shows substantial immune escape potential that threatens protection.
Our findings reveal significant challenges posed by continued SARS-CoV-2 antigenic evolution. The substantial reduction in neutralizing activity against FLiRT variants, driven by mutations in critical antigenic sites, highlights the enhanced immune escape capabilities of these variants. The unexpected finding that vaccination-only participants showed better cross-neutralization compared to individuals with hybrid immunity challenges conventional assumptions about hybrid immunity advantages. However, this finding should not be over-interpreted as the differences were small and it is not clear if they represent biologically meaningful differences. Despite being NP antibody negative (Fig. S1) and having no self-reported infections, these individuals could of course have had asymptomatic/undetected infections. Furthermore, the finding could also be an artifact due to the small sample size.
Only an intermediate neutralization reduction was observed for BA.3.2, despite its extensive mutation profile. Our finding here is in contrast to another report (3) that shows more drastic reduction in neutralization. This difference may be explained by different assay settings. Specifically, we used an assay that assesses multicycle replication in the presence of serum, while other reports essentially only looked at initial entry inhibition. The results are in better agreement with a study from Germany (2), even though the variant comparisons are not exactly the same. Our results may explain why this variant has not achieved high transmission rates globally. This could reflect a balance between immune escape and viral fitness costs associated with extensive mutations.
These data highlight the need for adaptive vaccine approaches. While our study focused on humoral immunity, SARS-CoV-2-specific T-cell responses exhibit substantial cross-reactivity across Omicron variants, recognizing conserved epitopes less affected by spike mutations (6,7). This preserved cellular immunity likely contributes to continued protection against severe COVID-19 despite reduced neutralizing antibody titers. Future strategies should consider targeting conserved epitopes or employing alternative delivery methods such as intranasal vaccination to enhance mucosal protection (8). Continuous antigenic surveillance and rapid vaccine updates will be essential as SARS-CoV-2 continues evolving in immunologically experienced populations.
This study has several limitations. The sample size, while adequate for detecting major differences, may limit detection of subtle variations between subgroups. The pseudo type system used for BA.3.2 testing may not fully recapitulate live virus neutralization. Additionally, the durability of these responses beyond the measured time point remains unknown. Furthermore, pre-vaccination sera were not tested, limiting assessment of fold-change increases following KP.2 vaccination. Here, only serological responses were evaluated; cellular immunity, which may significantly contribute to protection, was not assessed. Despite these limitations, the observed trends in immune escape and antibody quality remain relevant for informing ongoing vaccine updates and public health strategies.
## References
1. Link-Gelles, Chickery, Webber et al. (2024) "Interim estimates of 2024-2025 COVID-19 vaccine effectiveness among adults aged ≥18 years -VISION and IVY networks" *MMWR Morb Mortal Wkly Rep*
2. Zhang, Kempf, Nehlmeier et al. (2025) "Host cell entry and neutralisation sensitivity of SARS-CoV-2 BA.3.2. Lancet Microbe"
3. Guo, Yu, Liu et al. (2025) "Antigenic and virological characteristics of SARS-CoV-2 variants BA.3.2, XFG, and NB.1.8.1" *Lancet Infect Dis*
4. Wilks, Mühlemann, Shen et al. (2023) "Mapping SARS-CoV-2 antigenic relationships and serological responses" *Science*
5. Smith, Lapedes, De Jong et al. (2004) "Mapping the antigenic and genetic evolution of influenza virus" *Science*
6. Keeton, Tincho, Ngomti et al. (2022) "T cell responses to SARS-CoV-2 spike cross-recognize Omicron" *Nature*
7. Tarke, Coelho, Zhang et al. (2022) "SARS-CoV-2 vaccination induces immunological T cell memory able to cross-recognize variants from Alpha to Omicron" *Cell*
8. Slamanig, González-Domínguez, Chang et al. (2024) "Intranasal SARS-CoV-2 Omicron variant vaccines elicit humoral and cellular mucosal immunity in female mice" *EBioMedicine*
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# Stimulation of Human Adenovirus Infection Modulated by Emerging Micropollutants
Paula Catielen, Pa, Yasmin Ferreira, Souza Hoffmann, Lucas Zanchetta, Paula Rogovski, Gislaine Fongaro
## Abstract
Among the various classes of micropollutants, pharmaceutical residues such as carbamazepine, ciprofloxacin, sulfamethoxazole, and trimethoprim are of particular interest because of their high detection frequency and potential to promote antimicrobial resistance (Gupta et al., 2024). Similarly, MPs have gained attention not only for their physical accumulation but also for their capacity to act as carriers of a wide range of environmental contaminants, including persistent organic pollutants, pharmaceuticals such as antibiotics and neuroactive drugs, pesticides, and endocrinedisrupting chemicals, that readily adsorb to their surfaces (Fu et al., 2021). Once internalized by organisms, these contaminant-loaded particles can interfere with cellular processes, such as inducing oxidative stress through ROS overproduction, disrupting membrane integrity, impairing protein processing, and altering key physiological functions including photosynthesis in algae and metabolic homeostasis in animal cells. The complex physicochemical interactions between MNPs, their adsorbed pollutants, and biological systems highlight the importance of comprehensive toxicity assessments that consider both particle-specific effects and the enhanced toxicity arising from co-exposure to associated chemicals.
## Introduction
In recent decades, the widespread detection of micropollutants in aquatic environments has raised growing concerns regarding their ecological and human health impacts. These substances, ranging from pharmaceuticals and personal care products to micro and nanoplastics (MNPs), are continuously released into surface waters through domestic, hospital, and industrial wastewater, often without complete removal by conventional treatment systems (Tumwesigye et al., 2023). Due to their chemical persistence and biological activity, even low concentrations of these compounds can induce subtle but significant biological effects in exposed organisms (Moghadam et al., 2023).
Despite the recognized importance of viruses in aquatic environments, the potential interactions between viruses and micropollutants remain largely unexplored. Emerging evidence suggests that chemical contaminants such as pharmaceuticals and microplastics (MP) could influence viral stability, infectivity, and replication, either by direct physicochemical interactions or indirectly by altering host cell responses (Li et al., 2024). Understanding these interactions is crucial, as they may affect virus persistence and transmission, ultimately impacting public health and environmental safety.
Viruses are ubiquitous in the environment and play critical roles in ecosystem dynamics as well as public health. Among them, human adenoviruses are frequently detected in water bodies contaminated with sewage effluents and are considered important indicators of viral pollution due to their resistance to environmental degradation and disinfection processes (Rachmadi et al., 2020). Adenoviruses can cause a range of diseases, from mild respiratory infections to more severe illnesses in immunocompromised individuals, making their monitoring in environmental matrices essential for assessing viral contamination risks (Suraka et al., 2022). HAdV-5 was specifically chosen for this study because it is one of the most environmentally persistent adenovirus types and is also one of the most extensively characterized viral models in vitro. Its well-established replication kinetics, robust growth in A549 cells, and wide use in virology studies strengthen its suitability for controlled mechanistic evaluations, which aligns with the in vitro design of the present work.
The primary objective of this study was to evaluate the interactions between selected micropollutants and human adenovirus during in vitro cultivation. We specifically investigated whether exposure to environmentally relevant concentrations of micropollutants alters adenovirus replication dynamics in cultured cells. This work aims to provide novel insights into how chemical contaminants may modulate viral behavior, contributing to a more comprehensive understanding of environmental virology and pollutant impacts.
## Methodology
## Cells and Viruses
In vitro assays were conducted using the human lung adenocarcinoma cell line A549 (ATCCCCL-185), cultured in Minimum Essential Medium (MEM) supplemented with fetal bovine serum (FBS), under standard conditions (37 °C, 5% CO₂, humidified atmosphere). The viral model used was human adenovirus type 5 (HAdV-5), with viral stocks prepared according to Simões et al. (1999) and titrated via the TCID₅₀ method. Viral suspensions were stored at -80 °C until use.
## Micropollutants
The selected CECs represented a range of micropollutants commonly detected in wastewater and aquatic environments. These included antibiotics (ciprofloxacin, trimethoprim, sulfamethoxazole, and amoxicillin), neuroactive pharmaceuticals (fluoxetine and sertraline), and carbamazepine. All pharmaceuticals were originally purchased from Sigma-Aldrich and kindly donated for this study by the Resource Recovery in Sanitation Systems Study Group (RReSSa/UFSC). In addition, two types of MNPs were included: polyester microfibers (classified as microplastics, ranging from 44.7 μm to 911.0 μm) (Lins et al., 2024) and polystyrene/aluminum oxide nanoparticle suspensions (classified as nanoplastics, average diameter 90.1 ± 4.9 nm) (Vicentini et al., 2019). These MNPs were produced inhouse and provided by the Laboratory of Aquatic Contamination Biomarkers and Immunochemistry (LABCAI/ UFSC). All CECs used in this study were obtained through collaborations with UFSC research groups, reinforcing the methodological reliability and traceability of the materials employed.
## Analytical Validations
## Cytotoxicity Assays
Cytotoxicity of the pharmaceutical compounds was evaluated via the sulforhodamine B (SRB) colorimetric assay (Vichai & Kirtikara, 2006). A549 cells were exposed to compound concentrations (Table 1) based on literature and human serum levels, followed by 72 h incubation. Fixation was performed with trichloroacetic acid, SRB staining applied, and absorbance read at 510 nm. CC₅₀ values were calculated according to the analytical approach outlined by Vichai & Kirtikara, using dose-response curves generated from the normalized absorbance data. For MNPs, a customized environmental cytotoxicity assay previously developed by our group was employed (Rigotto et al., 2005). Cells were exposed to three concentrations of MNPs for 1 h, followed by medium replacement and 72 h incubation. Cell viability was assessed via naphthol black staining.
## Methodological Validation of RT-qPCR
To ensure the reliability of RT-qPCR quantification in the presence of micropollutants, a methodological validation assay was performed. Based on the cytotoxicity results, four different concentrations were selected for each micropollutant of interest (Table 2). These concentrations represented subcytotoxic levels and were within the range commonly detected in environmental and biological matrices.
Each micropollutant was directly added to a suspension containing the purified genetic material of HAdV-5, in the absence of host cells. The resulting mixture was then transferred to an RT-qPCR reaction plate prepared with the appropriate master mix and primers targeting HAdV-5, in accordance with Sect. 2.5. An RT-qPCR kit was used to maintain the same conditions applied for mRNA quantification, without DNase I treatment. The cycling conditions followed the protocol established for viral quantification in this study (session 2.5).
This assay aimed to evaluate whether the selected micropollutants interfered with the amplification efficiency or detection of the viral genome, either by inhibiting enzymatic reactions, altering fluorescence signals, or interacting with nucleic acids. The results from this control experiment were used to validate the absence of analytical artifacts and to support the interpretation of downstream experiments involving viral replication in cell culture.
## HAdV-5 Replication Under Micropollutant Exposure
To investigate the impact of CECs on HAdV-5 replication, a series of in vitro assays were originally developed for this study, rather than adapted from previously published protocols, in order to simulate distinct exposure scenarios across the viral replication cycle (Fig. 1). The A549 cell line was used throughout, and all infections were performed with HAdV-5 at a concentration of 10 4 TCID₅₀/mL, with incubation at 37 °C and 5% CO₂ in a humidified atmosphere. The micropollutants were tested at environmentally relevant and biologically tolerable concentrations (Table 3). All essays included viral control (positive control, with HAdV-5 suspension only) and a cell control (negative control, cells with medium only).
## Pre-Exposure of Cells to Micropollutants
This assay aimed to evaluate whether prior contact of CECs with host cells could modulate susceptibility to viral infection. A549 cells were exposed to CECs for 1 h at 37 °C. After this incubation, the medium containing CECs was carefully aspirated, and the cells were washed with phosphate-buffered saline (PBS) to remove any residual compounds. Subsequently, cells were infected with HAdV-5 and incubated for 1 h to allow virus adsorption. After infection, the viral inoculum was removed, and fresh MEM supplemented with FBS was added. Cells were incubated for 24 h to allow viral replication before being harvested for downstream analysis.
## Post-Infection Exposure to Micropollutants
In this protocol, designed to assess whether CECs interferes with viral replication after successful entry, cells were first infected with HAdV-5 for 1 h. Following adsorption, the viral suspension was aspirated and replaced with medium containing the test MP. After 1 h of exposure, fresh medium (without removing the MP) was added, and the cells were incubated for an additional 24 h. This allowed evaluation of CECs effects on intracellular stages of viral replication and progeny virus production.
## Interference During Viral Adsorption
To investigate whether CECs interfere directly with the virus-cell binding step, a pre-exposure of A549 cells to CECs was carried out for 1 h, followed by infection with HAdV-5 for 1 h. Immediately after infection, plates were transferred to 4 °C for 15 min to inhibit endocytosis and stabilize the adsorption phase. This temperature shift selectively halts virus entry by increasing membrane rigidity and preventing fusion, while allowing viral adsorption to proceed (Aboud, Shoor, Salzberg;1979;White et al., 2023), enabling assessment of CECs effects on early attachment processes. Cells were then harvested for nucleic acid analysis.
## Progeny Virus Reinfection Assay
To determine the biological relevance of changes in viral replication, an in vitro reinfection assay was performed.
Supernatants from the co-exposure assay were collected after 24 h and transferred to fresh A549 monolayers, which were then incubated for an additional 24 h. Viral load was quantified as HAdV-5 mRNA, ensuring that only actively replicating virus was measured. This approach allowed us to assess whether prior exposure to CECs resulted in increased or decreased production of infectious progeny, providing insight into longer-term effects on viral fitness. Each experimental condition was compared against its respective viral and cell-only controls. After incubation, samples were processed for RNA extraction and ICC-RT-qPCR quantification of HAdV-5 mRNA, as described below.
## Nucleic Acid Extraction and RT-qPCR
Adenoviral replication was quantified through integrated cell culture coupled with reverse-transcription quantitative PCR (ICC-RT-qPCR), following the approach described by Fongaro et al. (2013). This method ensures that only actively replicating virus is detected, since quantification is based on viral mRNA transcribed during infection, rather than on residual input viral DNA.
## Virus-Micropollutant Co-Incubation
This assay assessed whether CECs interacts directly with viral particles, potentially altering infectivity. HAdV-5 was mixed with each CEC at a 1:1 ratio (50 µL of HAdV-5 suspension and 50 µL of the CEC solution, both diluted in MEM) and incubated for 2 min at room temperature; an identical mixture was incubated at 37 °C to assess potential temperature-dependent differences. The mixture was then diluted in culture medium containing 2% FBS and applied to A549 cells. After 1 h, the inoculum was removed, and fresh medium was added. Cells were incubated for 24 h to allow replication of any virus that retained infectivity. This assay mimics environmental or physiological scenarios of simultaneous exposure.
## Results
## Control Assays: Cytotoxicity and Methodological Validation of qPCR
To ensure robustness and accurate interpretation of the experimental results, two preliminary control assays were performed. First, the cytotoxicity of all selected micropollutants was assessed in A549 cells using the SRB assay to confirm that the concentrations applied did not compromise cell viability through nonspecific cellular damage. Second, a methodological control was conducted to evaluate potential interference of the micropollutants with the RT-qPCR assay itself. This step was critical to exclude any direct effects of the tested compounds on enzymatic amplification or fluorescence detection, thereby ensuring that observed variations in viral replication truly reflect biological phenomena rather than analytical artifacts.
Table 6 summarizes the CC 50 values obtained from the SRB assay to the micropollutants classified as pharmaceuticals, which are consistent with the literature and informed the selection of concentrations for subsequent experiments. Unlike the tested pharmaceuticals, MNPs do not have a defined chemical structure and do not act as soluble bioactive agents. As solid particles or colloidal dispersions, their interactions with cells do not follow classic dose-dependent toxicity mechanisms typically observed with chemical compounds. Therefore, the calculation of the CC₅₀ (the concentration that reduces cell viability by 50%) is not suitable or applicable to these types of materials. Instead, cytotoxicity After cell infection and incubation, nucleic acids were extracted using the RNAdvance Viral XP kit (Beckman Coulter). To eliminate any remaining adenoviral genomic DNA, all extracts were treated with DNase I (1 U; Invitrogen) prior to amplification. This step prevents background amplification from contaminating DNA and guarantees that downstreamdetection reflects only RNA-derived products.
RT-qPCR was performed using the QuantiNova Probe RT-PCR Kit (Qiagen), which incorporates the reverse-transcription step within the qPCR reaction. Although the primers and probe target the conserved hexon gene, commonly used for adenoviral DNA detection, their use is also fully appropriate for mRNA quantification. This is because the hexon transcript is one of the most abundant and conserved early-to-late mRNAs produced during adenovirus infection, and its sequence is identical in both RNA and DNA templates. Consequently, once genomic DNA is removed by DNase treatment, hexon-specific oligonucleotides reliably amplify only viral mRNA, serving as a robust transcriptional marker of active replication. Cycling conditions and oligonucleotide sequences used in this assay are detailed in Tables 4 and5.
## Statistical Analysis
To ensure consistency across all experimental conditions, the same viral stock (a single production batch of HAdV-5) was used throughout the study. This stock was previously quantified by qPCR to determine the genome copy number and verify uniformity of the inoculum, resulting in an HAdV-5 input of 4.94 × 10⁴ GC/mL in each assay. In addition, infectious titers were independently assessed by TCID₅₀, which confirmed the same pattern of consistency across experiments, reinforcing the reliability of the viral input used in all assays.
For all ICC-PCR analyses, genome copy numbers obtained from duplicate cell populations were converted to was added directly to samples containing HAdV-5 genetic material, in the absence of cells, to assess potential PCR inhibition or enhancement. Interestingly, at a concentration of 5 µg/mL, both sulfamethoxazole and amoxicillin caused a decrease in detected viral load, suggesting possible inhibition of the RT-qPCR reaction at this concentration. Conversely, polyester microfibers (MPs) induced an increase in detected viral load at the same concentration, which may be related to nonspecific adsorption of viral DNA, matrix effects, or the release of PCR-enhancing substances. Before selecting the concentrations for the RT-qPCR interference assessment, it is important to note that any PCR-inhibitory effect from the micropollutants would be expected only at levels substantially higher than those initially tested (maximum 5 µg/mL). Moreover, based on the results obtained, interference with HAdV-5 quantification was detected only at concentrations exceeding 5 µg/mL for a subset of micropollutants, and none of these interfering levels approached the concentrations actually used in the experimental assays. It should also be emphasized that the concentrations added to the cell culture do not remain the same throughout the experimental workflow, as the final RT-qPCR input corresponds to the extracted sample, in which the original micropollutant concentrations are considerably was assessed qualitatively based on cell viability observations at different concentrations (20, 10 and 5 µg/mL), without generating dose-response curves typically used for pharmacological substances. The non-cytotoxic concentration observed for CECs was 10 µg/mL, which was therefore used for the following assays.
As part of the analytical validation, an additional control assay was carried out to determine whether the micropollutants interfere with the RT-qPCR reaction used for adenovirus quantification (Fig. 2). In this assay, each compound 2 RT-qPCR control to assess potential interactions between micropollutants and the method that could affect quantification of HAdV-5. Reactions were performed in technical duplicates on the RT-qPCR plate, and the values shown follow the same normalization approach used for the in vitro assays, in which the viral control is set to 1 and relative increases or decreases are expressed accordingly significantly alter the bioavailable fraction. Collectively, these considerations highlight the complexity of interpreting in vitro exposure models and support the use of conservative concentrations within physiologically relevant ranges.
$$FAM-C C G G G C T C A G G T A C T C C G A G G C G T C C T-TAMRA$$
## Interactions in Replicative Cycle
The effect of CECs on HAdV-5 replication was evaluated under various exposure protocols simulating different moments of the viral replication cycle. Notably, no significant differences were observed in HAdV-5 mRNA levels when cells were exposed to CECs either prior to infection (cellular pre-exposure, Fig. 3a) nor after infection (postexposure, Fig. 3b) and during viral adsorption (cellular preexposure, Fig. 3c). These findings suggest that the tested CECs, under the concentrations used, do not interfere with cellular susceptibility to viral entry nor with intracellular diluted. In the in vitro cytotoxicity assays, adverse effects were observed only at concentrations far above 5 µg/mL. Therefore, the higher, non-cytotoxic concentrations used in the cell culture experiments (Table 3) were selected for subsequent assays because they better approximate the serum levels reported in humans following therapeutic drug administration. These reference values were obtained from literature review, which describe minimum-maximum serum concentrations under standard dosing regimens. This approach was necessary due to the limited availability of studies quantifying bioaccumulation of these compounds in human tissues at levels directly relevant to viral infection models, making serum-based benchmarks a more practical and biologically meaningful basis for experimental design. Furthermore, the concentrations applied in vitro do not directly correspond to intracellular levels, as processes such as uptake, metabolism, and macromolecular binding can
## Discussion
The temperature-dependent effects observed in this study are particularly relevant for environmental virology. While room temperature reflects many natural freshwater and surface water conditions, wastewater systems influenced by thermal discharges, seasonal warming, or industrial effluents can reach or approach 30-37 °C (Yan et al., 2023). Under such conditions, interactions between viruses and CECs may be favored, potentially enhancing viral persistence or infectivity in environmentswhere high concentrations of micropollutants are continuously released through human waste. Previous work has shown that microplastics colonized by biofilms can serve as protective microenvironments that reduce viral inactivation rates (Moresco et al., 2022), and that chronic pharmaceutical exposure may influence host-virus interactions (Kong et al., 2021;Previšić et al., 2021), supporting the broader implications of the present findings.
When compared to reinfection at room temperature, HAdV-5 replication was significantly reduced across all micropollutant conditions (Fig. 5b). In the co-exposure assays performed at room temperature, the pronounced decline in viral concentrations in the progeny suggests that micropollutants may inactivate newly produced HAdV-5 particles under environmental conditions. This finding aligns with the possibility that CECs interfere not only with early infection steps but also with late events such as virion assembly, capsid stability, or maturation efficiency.
replication steps such as transcription or assembly. It is likely that the exposure conditions applied did not induce significant physiological changes in the host cells that could impair HAdV-5 replication.
## Simultaneous Exposition Promotes Replication of Adenovirus
A significant improvement in viral replication was observed when the co-exposure occurred at 37 °C, indicating that temperature plays a critical role in enhancing interactions between CECs and viral particles, particularly for carbamazepine, fluoxetine, sulfamethoxazole, amoxicillin, and MPs (Fig. 4a). Notably, the enhancement of viral replication under these conditions surpassed 1.5 log₁₀ compared to the viral control, highlighting a biologically relevant increase in viral yield triggered by very short-term interactions. In contrast, no significant changes in viral replication were observed when co-exposure occurred at room temperature (RT) (Fig. 4b).
In the reinfection assay, supernatants obtained from the 37 °C co-exposure experiment were used to infect fresh A549 monolayers. No significant differences were detected in the replication of the progeny virus compared to the viral control (Fig. 5a). At room temperature, progeny virus levels were significantly lower than the control across all evaluated CECs (Fig. 5b). pharmaceuticals undergo extensive metabolism, resulting in a variety of active or inactive metabolites that may differ significantly in their physicochemical properties and biological activity (Yan et al., 2023). In this context, it remains unclear whether the effects observed in vitro are primarily driven by the parent compound or by its metabolites, which may be present in higher concentrations in excreta and environmental matrices (Han & Lee, 2017). Future studies should aim to differentiate between the direct impact of the original pharmaceutical molecule and that of its biotransformation products, especially considering that some metabolites may retain, enhance, or even reverse the biological effects of the parent drug. This distinction is critical to improve the environmental relevance of experimental models and to more accurately predict the fate and influence of pharmaceutical residues in natural and engineered ecosystems.
The interaction between viruses and micropollutants, particularly MPs, is an emerging field with important implications for environmental virology. As highlighted by Yang et al. (2023), MPs can serve as carriers or scaffolds for various microorganisms, including viruses, potentially altering their environmental persistence, modes of host entry, and interactions with immune defenses. This biotic-abiotic interface can influence not only viral stability but also the cellular mechanisms of viral uptake and replication. In the present study, we observed changes in adenovirus replication when co-exposed to micropollutants during cell culture assays, supporting the hypothesis that chemical contaminants may modulate viral dynamics. Although the exact mechanisms of such interactions remain unclear, our findings reinforce The temperature-dependent differences further suggest that CEC exposure may influence the quality, not only the quantity, of progeny virions. At lower temperatures, incomplete virion maturation, altered protein processing, or impaired capsid stabilization may render new particles more susceptible to environmental degradation (Sharma et al., 2020). Conversely, at 37 °C the same micropollutants appear to enhance viral replication, indicating that their effects may depend on the physiological state of the host cell and on specific viral morphogenesis pathways that are temperature sensitive.
Another interpretation is that CECs may alter the ratio between infectious and non-infectious particles, as adenovirus infections naturally produce large numbers of defective virions. If micropollutants disrupt late-stage folding or genome packaging, the progeny produced at room temperature may contain a higher proportion of incomplete or defective particles, explaining the reduced reinfection efficiency observed.
Despite the relevance of these findings, several limitations must be acknowledged. First, all experiments were conducted under controlled laboratory conditions, which do not fully capture the complexity of environmental systems or human physiology. An important limitation of this study is the uncertainty regarding the exact chemical or physical form responsible for the observed effects. At physiological temperature, increased molecular motion could facilitate binding, adsorption, or even partial encapsulation of viral particles by CECs, impairing their ability to interact with cellular receptors. Moreover, in real biological systems, underscores the urgent need for integrative mechanistic studies to elucidate how environmental factors, such as temperature, chemical co-contaminants, and the structural complexity of plastisphere communities, interact to modulate viral persistence, infectivity, and dissemination in contaminated ecosystems.
Together, these findings highlight the importance of exposure timing and environmental conditions (notably temperature and time of exposition) in shaping the interaction between micropollutants and viral particles.
## Conclusion
In conclusion, our findings demonstrate that exposure to selected CECs significantly enhances HAdV-5 replication in vitro, indicating that micropollutants can directly modulate viral infectivity under physiologically relevant conditions. When considered together with environmental evidence showing that microplastics and their biofilms can protect viruses and prolong their persistence in aquatic systems (Moresco et al., 2022), as well as recent insights that plastispheres may influence viral ecology (Shruti et al., 2024), our results reinforce the emerging view that contaminated environments may actively shape viral behavior. These observations highlight an important and previously underrecognized dimension of viral-pollutant interactions. Overall, this study emphasizes the need to incorporate chemical and physical co-contaminants into future viral risk assessments, and points to the importance of mechanistic investigations to fully understand how environmental micropollutants affect viral persistence, infectivity, and potential dissemination.
the relevance of considering the combined effects of physical particles and chemical pollutants on viral infectivity and replication. These insights emphasize the need for integrative approaches in risk assessment of contaminated matrices, especially in the context of waterborne viruses and environmental health.
Recent studies have demonstrated that MPs can enhance viral infection and facilitate the adsorption of viruses onto MPs (Lu et al., 2022). Wang et al. (2023) used confocal fluorescence microscopy to reveal co-localization between polystyrene PS particles and the nucleoprotein of Influenza A Virus (IAV), indicating that PS particles act as carriers, enriching viral particles and promoting their uptake via endocytosis. Beyond facilitating entry, PS exposure suppressed critical antiviral mechanisms, including the RIG-I-like receptor (RLR) signaling pathway, by inhibiting the phosphorylation of TBK1 and IRF3, downregulating the expression of IFN-β, and significantly reducing the levels of IFITM3, a key protein that restricts viral membrane fusion and replication. In the present study, although focused on human adenovirus, we similarly observed alterations in viral replication patterns following exposure to environmental micropollutants in cell culture. These findings suggest that, as with IAV, chemical contaminants may influence not only the entry but also the replication efficiency of viruses, either directly or through modulation of host cell pathways. While the exact molecular mechanisms remain to be elucidated for adenovirus, our results reinforce the hypothesis that micropollutants may compromise cellular defenses and promote viral replication, highlighting the importance of further investigating these interactions across different viral models and environmental contaminants.
The findings by Moresco et al. (2022) demonstrate that MPs colonized by biofilm constitute a favorable microenvironment for viral adsorption and protection, reducing viral inactivation rates and thereby enhancing stability, persistence, and potential dissemination of infectious viruses, both enveloped and non-enveloped, in aquatic ecosystems. Complementarily, our in vitro study shows that co-exposure to micropollutants, including MPs, under physiological temperature conditions (37 °C), markedly enhances viral replication, indicating a synergistic modulation of viral infectivity by chemical and physical factors. This perspective is further substantiated by the recent review by Shruti et al. (2024), who highlight emerging research demonstrating that plastispheres influence viral population dynamics, diversity, and functions, and that viral interactions with MPs may alter host-associated environments. The authors frame these findings within an evolving paradigm wherein plastispheres are viewed as dynamic microhabitats with the potential to shape viral ecology, drive evolutionary processes, and impact public health. Collectively, this synthesis
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# The 16th national virology symposium concludes: Sustaining academic exchanges and innovations in China's virology
Jiali Si, Ying Wu
## Abstract
The national virology symposium of China, co-hosted biennially by the society and local research institutions, has now entered its 16th iteration. The 16th session, jointly hosted by Chinese Society for Virology -the virology division of the Chinese Society for Microbiology and the first hospital of Jilin University, took place in Changchun from August 15 to 17, 2025. More than 800 participants attended the event, including renowned experts, scholars, and young scientists from institutions across the country (Fig. 1).The symposium commenced on the morning of August 16 with warm welcome addresses by Professors Yu Xianghui, Lv Guoyue, Guo Deyin, and Jin Ningyi. It then moved into a traditional session honoring virology pioneers of China. Professor Yuan Zhenghong, director of the virology division of the Chinese Society for Microbiology, highlighted the extraordinary contributions of Professor Zhu Jiming, a founding figure in China's medical virology and biological products. Following this, Professors Gao Fu, Chen Hualan, Xia Ningshao, Chang Junbiao, and Niu Junqi delivered keynote lectures, focusing on cutting-edge advancements in virology and critical issues related.From the afternoon of August 16 through the entire day of August 17, four parallel sessions were held, featuring 127 oral presentations to facilitate academic exchanges. These presentations focused on four major themes: "virus-host interactions", "viral pathogenesis and immunity", "diagnostics, vaccines, and antivirals", and "etiology, epidemiology and evolution". Additionally, a special session entitled "digital intelligent display of virology and disciplinary development in virology"
took place on the afternoon of August 17. Furthermore, a poster exhibition session was incorporated over these two days, providing a broader platform for young scholars and encouraged the collision and integration of diverse research ideas and findings. Five poster presenters were selected for awards and received their honors at the closing ceremony.
This national virology symposium seires has long served as a vital platform for sharing the latest research findings and enhancing collaboration and connectivity among various research teams, and galvanizing greater efforts for the innovative advancement of virology in China.
Chinese Society for Microbiology was founded in 1952, while the virology division (Chinese Society for Virology) was founded in 1979. The first symposium, held in Tianjin from July 15-19, 1986, was organized by the virology division in collaboration with the Beijing Institute of Microbiology and Epidemiology, Tianjin Medical College and Tianjin Second Medical College (朱关福, 1986; 范中善, 1986; 田玲, 1987). With participants from 225 institutions across 27 provinces, nearly 500 attendees gathered to present over 490 papers spanning medical, veterinary, plant, insect, and bacteriophage virology. This event marked the first large-scale, systematic showcase of China's virology achievements since the founding of the People's Republic of China.
Five years later, the second symposium took place in Wuhan from June 25-29, 1991, with the focus on medical virology and molecular virology (张德礼, 1991). This transition highlighted the rapid progress With the vigorous development of virology research in China and the continuous growth of its young and talented researchers, the Youth Committee of Chinese Society for Virology was established in 2013. In the following year, the first national symposium for young virologists was held in Shanghai from September 25 to 27, 2014. Since then, the youth symposium has been held biennially, with past editions taking place in Shenzhen (2016), Fuzhou (2018), Guangzhou (2020), Shenzhen (2022), and Chongqing (2024). The main symposium and the youth symposium are held on an alternating annual basis. Table 1 presents summary information for the symposium series since 2007.
These gatherings have attracted an increasing number of researchers and become as the most prominent academic events hosted by the Chinese Society for Virology. Beyond facilitating collaboration, they have served as a platform for up-and-coming virologists, propelling many to national recognition and enabling their contributions to the field's advancement.
The enduring success of these symposia reflects the broader maturation of China's virology community, bridging foundational science with practical applications in public health, medical science, and other related domains and beyond. As research continues to thrive and academic networks grow stronger, the national symposium series remain a vital pillar for knowledge exchange and innovation in the virology field of China.
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# Cell-cell fusion limits activation of the unfolded protein response induced by the Nipah virus glycoproteins
Paula Jordan, Sören Heyer, Julian Hüther, Ilka Fischer, Nico Becker, Andrea Maisner
## Abstract
The productive replication of highly pathogenic Nipah virus (NiV) relies on the host cell for the synthesis and correct folding of the viral glycoproteins, which can cause ER stress and activation of the unfolded protein response (UPR). While the UPR can exert proviral functions by restoring ER homeostasis, it can also have antiviral effects. Here, we show that irreversible ER stress induced by thapsigargin resulted in broad expression of UPR target genes and potently inhibited NiV infection. The finding that UPR target gene upregulation was not detectable in NiV-infected cells at 18 h p.i., raised the question of how NiV regulates UPR activation to prevent thapsigargin-like antiviral effects. To address this, we analyzed the effects of NiV glycoprotein expression on UPR activation and found that both NiV glycoproteins F and G, like many other viral glycoproteins, activated the highly conserved IRE1/XBP1 branch of the UPR. Interestingly, upon coexpression of both NiV glycoproteins and thereby induced cell-cell fusion, the activation did not increase. Instead, UPR activation relatively decreased with increasing syncytium formation, an effect that was not observed if cell-cell fusion was blocked. These results support the idea that syncytium formation limits UPR activation despite ongoing viral glycoprotein synthesis. This as yet undescribed mechanism is likely a fusion-dependent countermeasure to prevent an overload of the ER folding capacity by dilution and suggests that NiV-induced syncytium formation not only is an important way to promote NiV spread from cell-to-cell but also regulates ER stress to limit potential UPR-induced antiviral responses.
IMPORTANCEThe unfolded protein response (UPR) is a cellular signaling pathway to counteract ER stress. Many enveloped viruses, which force the infected cell to synthesize high amounts of viral surface glycoproteins, induce the UPR but regulate its activation by diverse strategies to prevent UPR-mediated antiviral effects. To date, nothing is known about UPR activation in infections with Nipah virus (NiV), a highly pathogenic member of the Paramyxoviridae family. Here, we demonstrate that NiV glycoproteins activate the IRE1/XBP1 branch of the UPR. However, this activation is limited by the cell-cell fusion mediated by the glycoproteins, probably due to dilution effects. This study is the first to investigate the interplay between NiV and UPR activation and proposes a novel strategy by which fusogenic viruses may limit the ER stress responses triggered by their glycoproteins.
NiV is an enveloped virus with a negative-sense, single-stranded RNA genome which encodes for six structural proteins. The nucleoprotein (N), the phosphoprotein (P), and the RNA-dependent RNA polymerase (L) encapsidate the viral RNA and form the helical nucleocapsid. The matrix protein (M) at the inner leaflet of the virus envelope interacts with the viral nucleocapsid and the two surface glycoproteins (6,7). The NiV glycopro tein G, a type II transmembrane protein, is responsible for binding to the host cell receptors ephrin-B2/B3 (8)(9)(10), while the NiV fusion protein (F), a type I transmembrane glycoprotein, mediates fusion of the viral envelope with the host cell membrane during virus entry (11). In infected cells, the NiV surface glycoproteins are synthesized, folded, glycosylated, and oligomerized in the endoplasmic reticulum (ER). The newly synthesized NiV F and G proteins are then transported to the plasma membrane via the secretory pathway. The fusion-inactive precursor F 0 is subsequently endocytosed to be proteolyti cally cleaved by cathepsin B/L at an acidic pH in endosomes to generate fusion-active F 1/2 , which is subsequently retransported to the plasma membrane (12,13). Surfaceexpressed NiV glycoprotein complexes formed by fusogenic F 1/2 and receptor-binding G proteins (F/G complexes) are incorporated into virus particles and induce pH-independ ent cell-cell fusion and syncytium formation. The formation of multinucleated cells allows a rapid spread of NiV from cell-to-cell and is a hallmark of NiV infection in vitro and in vivo (14,15).
Viral infections often lead to the activation of cellular stress responses by overloading the cellular machinery for viral replication (16). One of the major stress inducers is the abundant de novo synthesis of viral glycoproteins in the ER, which exceeds the ER folding capacity. Since an accumulation of unfolded proteins in the ER leads to the recruitment of chaperones to enable their correct folding, the unfolded protein response (UPR) is activated (17,18). The sensing of ER stress occurs by three transmembrane stress transducers, the inositol-requiring enzyme 1 α (IRE1), the activating transcription factor 6 (ATF6), and the protein kinase R (PKR)-like ER kinase (PERK), with IRE1 being the most conserved UPR signal transducer that is induced by numerous viral glycoproteins (16,17,19). Upon the recruitment of ER chaperones such as BiP by an excess of unfolded or misfolded proteins, IRE1 undergoes oligomerization and autophosphorylation. This enables its activity as an endoribonuclease that specifically cleaves the X-box binding protein 1 (XBP1) mRNA at two consensus sites, leading to the excision of a 26-nucleo tide intron. The XBP1s (spliced isoform) mRNA is then translated into the transcription factor XBP1s, which translocates to the nucleus and can activate genes involved in ER-associated protein degradation (ERAD), ER chaperones and ER expansion. XBP1 is, thus, the key factor in alleviating ER stress by increasing the ER folding capacity. If the ER homeostasis cannot be reestablished, sustained UPR activation ultimately leads to apoptosis, which is primarily mediated by the PERK pathway of the UPR (17,18,20,21). To avoid such an UPR-related premature cell death, most pathogenic viruses that induce the UPR via viral glycoprotein-induced ER stress have evolved strategies to prevent or modulate UPR activation to ensure productive replication, or even hijack the UPR as a proviral factor (22)(23)(24)(25). Thus, ER stress regulation is often tightly linked to pathogenesis and virulence (16). As the specific regulatory interactions of highly pathogenic NiV and the host cell's ER stress machinery are yet unknown, this study aimed to elucidate the interplay between NiV and the UPR.
## RESULTS
## The ER stress inducer thapsigargin blocks NiV infection
To first determine whether UPR activation generally has a positive or negative effect on NiV replication, we tested the effect of thapsigargin (Tg), a chemical UPR inducer that irreversibly interrupts the tightly regulated calcium homeostasis of the ER and activates all three UPR branches (26)(27)(28). For this purpose, Vero76 cells were infected with NiV at a multiplicity of infection (MOI) of 0.1. 1 h post infection (p.i.), the virus inoculum was removed and replaced by media containing 0.05% DMSO (control) or 500 nM Tg, the optimal nontoxic Tg concentration for UPR induction in Vero cells (29). At 24 h p.i., supernatants were collected for virus titration and the infected cells were fixed and stained to visualize syncytium formation. Additionally, cell lysates were collected for RNA isolation and western blot analyses.
We found that Tg treatment significantly reduced viral titers in the supernatants of NiV infected cells (Fig. 1A). In cell lysates, NiV N mRNA levels measured by qPCR (Fig. 1B) and the amounts of viral proteins (Fig. 1C) were also massively reduced. This potent inhibitory effect also led to a decreased cell-cell fusion (Fig. 1D). While the total number of syncytia was not reduced (Fig. 1E), syncytium sizes were strongly decreased (Fig. 1F) indicating that Tg did not influence NiV entry but later replication steps such as RNA and/or protein synthesis. Taken together, these results indicate that sustained and irreversible ER stress and UPR activation as induced by Tg, had a pronounced antiviral effect.
## NiV glycoproteins induce the IRE1/XBP1 axis of the UPR
The finding that sustained ER stress inhibited NiV infection raised the question of how NiV ensures productive replication despite the massive synthesis of NiV glycoproteins in the ER, which must be assumed to at least activate the major IRE1/XBP1 branch of the UPR, as is the case for other viral glycoproteins (16,25,30). To address this question, we investigated the UPR induction in NiV-infected cells and in control cells treated with Tg by quantitating the upregulation of representative IRE1-, ATF6-, or PERK-dependent target genes (31). As expected, sustained and broad UPR induction by Tg led to a significant upregulation of all genes tested (Fig. 2A). In contrast to Tg, none of the UPR target genes were upregulated in NiV-infected cells at 18 h p.i. (Fig. 2B). As in Vero76 cells, Tg treatment also induced a pronounced UPR gene upregulation in human cerebral microvascular endothelial and lung epithelial cells (hCMEC/D3 and A549 cells), while these UPR target genes were not induced by NiV at 24 h p.i. (Fig. S1).
The lack of a detectable ER stress response in NiV-infected cells at a time point of infection when viral replication, protein synthesis, and cell-cell fusion have been ongoing for many hours raised the question of whether the synthesis of the NiV glycoproteins might not trigger an UPR response at all.
To address this question, we investigated whether the NiV glycoproteins, like many other viral glycoproteins (16,24,25,32), activate the most conserved and major axis of the UPR, the IRE1/XBP1 pathway. To determine whether one or both NiV glycoproteins can induce expression of the transcription factor XBP1s, the key factor in alleviating ER stress (31,33,34), we used an XBP1u-GFP reporter plasmid (25). Transcription of the reporter plasmid produces unspliced XBP1u mRNA, which in the absence of UPR activation, leads to the expression of a non-fluorescent XBP1u reporter protein. Upon ER stress and IRE1 activation, the XBP1u mRNA is spliced. The resulting frameshift leads to the generation of a spliced XBP1s mRNA encoding a fluorescent XBP1s-GFP fusion protein, which, after translation, is translocated to the nucleus (Fig. 3A). This allows to detect UPR activation and XBP1 splicing by monitoring nuclear XBP1s-GFP signal, as shown in Tg-treated cells expressing the XBP1u-GFP reporter plasmid (Fig. 3B). To monitor the activation of the IRE1/XBP1 pathway by the two NiV glycoproteins, cells transfected with the XBP1u-GFP reporter plasmid and HA-tagged NiV F or G protein were fixed at 20 h p.t. and immunostained with HA-specific antibodies. Like Tg, the expression of either NiV F or NiV G induced IRE1 activation and XBP1 splicing, as shown by nuclear XBP1s-GFP expression in NiV glycoprotein positive cells (Fig. 3C andD). Surprisingly, upon coexpression of NiV F and G (F/G), which resulted in cell-cell fusion and syncytium formation, nuclear XBP1s-GFP expression was less pronounced (Fig. 3E). Quantification of the XBP1 splicing activity (mean nuclear XBP1s-GFP fluorescence) in cells expressing NiV F or G or both glycoproteins (Fig. 3F) clearly confirmed the more limited UPR activation/ XBP1 splicing upon NiV glycoprotein coexpression and cell-cell fusion. Since the glycoprotein content did not differ in F-or G-and F/G-coexpressing cell cultures (Fig. 3G), the limited UPR activation in cells expressing both NiV glycoproteins could not be explained by reduced viral protein expression. This, together with the finding that nuclear XBP1s-GFP expression was even more reduced in larger syncytia at later time points (Fig. S2), suggested that F/G-mediated cell-cell fusion may play a role in regulating the UPR.
## Cell-cell fusion limits NiV glycoprotein-induced XBP1 splicing
To evaluate the idea that cell-cell fusion is responsible for the limited UPR activation in cells coexpressing NiV F and G, we inhibited syncytium formation using ammonium chloride (NH 4 Cl). This lysosomotropic weak base raises the pH in acidic vesicles and blocks NiV cell-cell fusion by preventing pH-dependent F 0 cleavage into fusion active F 1/2 by cathepsin L/B in endosomes (12,13,35). To control the functional effect of the NH 4 Cl treatment, Vero76 cells expressing HA-tagged NiV F and G were cultivated in the absence and presence of 20 mM NH 4 Cl. After 20 h, F cleavage and syncytium formation were analyzed by western blot analysis or Giemsa staining, respectively. As expected, treatment with NH 4 Cl did not affect NiV G or F expression but inhibited F 0 cleavage, as indicated by the lack of the F 1 cleavage product (Fig. 4A, + NH 4 Cl). In line with the lack of fusion-active F proteins, syncytium formation was not observed in NH 4 Cl treated cells (Fig. 4B). To analyze the effect of fusion inhibition on NiV F/G induced XBP1 splicing, Vero76 cells were transfected with the XBP1u-GFP reporter plasmid and plasmids encoding HA-tagged NiV F and G. At 4 h p.t., the cells were treated with 20 mM NH 4 Cl and the expression of nuclear XBP1s-GFP was analyzed as an indicator for UPR activation. As observed before, untreated cells showed syncytium formation with limited nuclear GFP signals (Fig. 4C, w/o). In contrast, if cell-cell fusion was blocked, nuclear XBP1s-GFP expression was consistently detected in NiV F/G expressing cells (Fig. 4C, + NH 4 Cl). This was also the case in F/G-expressing A549 cells (Fig. S3), or when syncy tium formation was blocked by neutralizing antibodies instead of adding NH 4 Cl (Fig. S4A). Quantification of the mean nuclear XBP1s-GFP expression in the NiV glycoprotein expressing cell populations (Fig. 4D, Fig. S4B) clearly supported the conclusion that UPR activation by the NiV glycoproteins is limited if syncytium formation can occur, whereas blocking cell-cell fusion leads to increased ER stress and XBP1u splicing.
## Cell-cell fusion and UPR activation negatively correlate
Since syncytium formation and UPR activation are dynamic processes (15,36), we aimed to monitor the correlation of XBP1u splicing and syncytium formation over time. For this, Vero76 cells expressing the XBP1u-GFP reporter and HA-tagged F and G were fixed at different time points (6-18 h p.t.) and monitored for syncytium formation and nuclear XBP1s-GFP expression. Quantification of cell-cell fusion (nuclei per syncytium) showed that syncytium sizes continuously increased over time (Fig. 5A). In contrast, UPR activa tion (nuclear XBP1s-GFP in NiV F/G positive cells) only increased until 10 h p.t., i.e., at time points when syncytium sizes were still very small (<5 nuclei/syncytium). After having reached a maximal fluorescent intensity of about 250 arbitrary units (a.u.), the mean nuclear XBP1s-GFP expression in NiV glycoprotein positive syncytia decreased again and stayed at a level of about 100 a.u. (Fig. 5B). The graph in Fig. 5C shows a negative correlation of syncytium sizes and UPR induction (XBP1u splicing). Supporting this correlation, no substantial decrease in nuclear XBP1s-GFP expression was observed when syncytium formation was inhibited by adding NH 4 Cl. Here, after reaching a maximum, the mean nuclear GFP signal remains on a level at 400-500 a.u. (Fig. 5D).
## DISCUSSION
Viruses hijacking the ER-associated protein synthesis machinery often induce adaptive host cell stress responses such as the IRE1/XBP1 pathway of the UPR to restore ER homeostasis. This initially allows the cell to survive the inordinate stress of de novo synthesis of high amounts of viral proteins by significantly increasing the ER folding capacity. However, if ER stress is not resolved by this cytoprotective UPR response, apoptosis can be initiated, which counteracts viral replication and spread. Thus, UPR activation represents a time-dependent pro-or antiviral factor that can influence the pathogenesis and virulence of a viral infection (16,37). In this study, we showed that sustained induction of all UPR branches by thapsigargin drastically reduced viral RNA and protein synthesis, NiV titers, and syncytium formation, demonstrating that extensive ER stress and irreversible activation of the UPR had clear antiviral effects. Like many other viral glycoproteins, the NiV glycoproteins activate the IRE1/XBP1 branch of the UPR although the induction appears to be temporally controlled. Our data suggest that the UPR activation and XBP1s expression are initially induced, likely to increase the ER folding capacity and support the production of correctly folded and processed F/G glycoproteins. These are subsequently expressed on the cell surface and limit further UPR activation by cell-cell fusion leading to glycoprotein and ER stress dilution. If syncytium formation is blocked, UPR activation in NiV glycoprotein-expressing cells continues to increase. The finding that UPR activation negatively correlates with syncytium size indicates that NiV utilizes cell-cell fusion as a way to limit the potential antiviral effects of excessive and sustained glycoprotein-induced UPR activation.
Given the critical role of the UPR in viral replication, recent studies have indicated that the ER stressor Tg exerts a potent antiviral effect against RNA viruses, including influenza and coronaviruses. Inhibition by Tg has also been reported for several viruses of the order Mononegavirales, such as Marburg virus, respiratory syncytial virus, or Newcastle disease virus (29,(38)(39)(40). The present study, which shows that the replication of NiV was also potently inhibited by this chemical ER stress inducer, expands the group of Tg-sensitive viruses and underlines the potential of Tg and its derivatives as broad-spectrum antivirals (41).
In contrast to Tg, which globally activates the UPR and effectively induced CHOP and GADD34 expression, key components of the PERK branch of the UPR responsible for translational shutdown and apoptosis (16,42), these UPR target genes were not upregulated in NiV-infected cells at 18 h p.i.. This suggests that NiV has evolved a way to avoid triggering potentially maladaptive UPR outcomes although the synthesis of its viral glycoproteins caused ER stress and induction of the IRE1/XBP1 pathway. This selective activation of the UPR likely supports proper folding of the viral glycoproteins, a strategy that has also been proposed for influenza A virus and tick-borne encephali tis virus glycoproteins (24,43,44). The initial NiV F/G-mediated ER stress leading to XBP1 mRNA splicing likely supports the restoration of the ER homeostasis allowing a timely expression of functional NiV glycoproteins on the cell surface, a prerequisite for infectious virus particle assembly and cell-cell fusion. The latter not only functions as a way to spread NiV infection within cell layers or tissues (15) but also serves as a regulatory mechanism to limit UPR activation by preventing sustained and unresolved ER stress despite ongoing viral glycoprotein synthesis. Figure 6 depicts our model suggesting that UPR activation in early infection phases is required to increase the ER folding capacity to support the expression of functional NiV glycoproteins, which then prevent further increasing UPR activation with potential antiviral effects by inducing cell-cell fusion. The finding that UPR can be induced by Tg when syncytia have already formed (Fig. S5) strengthens the idea that cell-cell fusion limits or dilutes UPR rather than preventing its onset.
By regulating the UPR through syncytium formation, NiV has evolved a strategy to limit UPR activation. Though it remains to be determined how fusion exactly mitigates ER stress and if there are additional compensatory or regulating effects of the ATF6 and PERK branches of the UPR, the finding that XBP1 splicing was also reduced in syncytia formed by the measles virus glycoproteins (Fig. S6) provides initial evidence that NiV might not be the only virus that limits UPR through cell-cell fusion. This as yet undescri bed strategy complements the mechanisms of UPR modulation developed by viruses such as cytomegalovirus, coronaviruses or Marburg virus to maintain beneficial aspects of the UPR and suppress deleterious ones (22,25,45).
The ER is a highly dynamic organelle, continuously undergoing rearrangements that include tubule branching and ER partitioning. These dynamic changes in ER morphology allow flexible physical adaptation to stress. The ER also has functional connections to other cellular organelles, with the plasma membrane associated ER sites supposed to be involved in phosphatidylinositol metabolism, non-vesicular transfer of sterols, and Ca 2+level regulation (46). These functionally important ER-plasma membrane contact sites, which are stabilized by proteins tethering the two membranes, are highly dynamic and constantly remodeled, for example during cell division (47). Considering that the formation of syncytia, like mitotic processes, leads to massive changes in cell shape and causes rearrangements in the plasma membrane, NiV-mediated cell-cell fusion probably also triggers dynamic ER remodeling to meet the altered needs of the cell. These adaptations may allow the redistribution of ER stress-inducing proteins (NiV glycopro teins) across the expanded ER volume of fused cells. Continued cell-cell fusion and the resulting increase in ER capacity could subsequently help to mitigate further ER stress and limit the UPR. This idea is supported by our finding that no reduction in UPR activation was observed if syncytium formation was blocked and NiV glycoprotein expression, and thus ER stress, was confined to a single cell.
NiV has a broad cell tropism in vitro and in vivo. Epithelial and microvascular endothelial cells in lung, spleen, and kidney are the major cell types infected by NiV in vivo, with infection of microvascular endothelial cells in the CNS being regarded as the major basis for the development of NiV encephalitis (48,49). Syncytium formation is not only observed in NiV-infected endothelial cells cultures (Fig. S7) but also found in histopathological specimens from natural or experimental infections (48,50). The fact that syncytium formation is frequently observed in NiV infections both in vitro and in vivo (15) underlines the potential importance of cell-cell fusion-mediated UPR regulation for productive NiV infection. However, quantitative differences across various cell types and tissues have been noted, likely due to cell-specific variations in NiV receptor expression or other host factors such as membrane cholesterol (51). These variations in syncytium formation would be expected to influence fusion-dependent UPR regulation, which, in addition to affecting the direct spread of NiV between cells in the absence of particle release, may play a crucial role in determining the efficiency of NiV replication in different cell types.
In summary, this study provides first evidence that syncytium formation reduces or dilutes the NiV glycoprotein-induced ER stress to prevent sustained and potentially antiviral UPR activation. This suggests that NiV-induced syncytium formation is not only an important way to mediate viral spread from cell to cell but also limits activation of cellular stress responses. Since syncytium formation is also induced by other viruses (15,52,53), studies on the influence of syncytium formation on ER stress upon infection with fusogenic viruses could provide valuable insight regarding the dynamic interplay of viral and host cell factors, and the extent cell-cell fusion contributes to the complex modulation of cellular stress responses.
## MATERIALS AND METHODS
## Virus infection
Infection experiments with NiV were conducted under biosafety level 4 (BSL-4) conditions at the Institute of Virology, University Marburg. The NiV Malaysia (NiV) isolate that was used for this study has been described previously (54). Vero76 cells (CRL-1587, ATCC) were cultivated in Dulbecco's modified Eagle's medium (DMEM, Gibco) with 10% fetal calf serum (FCS, Gibco), 100 U penicillin mL -1 (Gibco), 0.1 mg streptomycin mL 1 (Gibco), and 4 mM L-glutamine (Gibco). Confluent Vero76 cells grown in 12-wells (5 × 10 5 cells) or on cover glasses in 24-wells (2.5 × 10 5 cells) were infected with NiV at an MOI of 0.1 for 1 h at 37 °C. After virus adsorption, cells were washed five times with DMEM 2% FCS and incubated in DMEM 2% FCS containing 500 nM thapsigargin (Tg; Sigma), 20 mM NH 4 Cl (Merck), or DMSO (Wak-Chemie) for 18-24 h. To determine infectious viral titers, the cell-free supernatants of infected cells were collected and quantified by serial dilution on Vero76 cells. 50% tissue culture infectious dose (TCID 50 /mL) was calculated using the Reed-Muench method.
## Plasmids and transfection
pCG and pCAGGS-vector based expression plasmids encoding NiV-M, HA-tagged NiV-F, and HA-tagged NiV-G have been described previously (13,55). The reporter plasmid pCAGGS-XBP1-GFP was provided by C. Rohde (25)
## Antibodies and reagents
The following antibodies were obtained commercially: NiV N (Alpha Diagnostic, NiV21-A), NiV F (AntibodySystem, PVV08101), NiV G (AntibodySystem, PVV07901), HA-tag (Sigma, H6908), biotinylated anti-rabbit IgG (Cytiva, RPN1004V), biotinylated anti-mouse IgG (Cytiva, RPN1001V), peroxidase-conjugated streptavidin (Cytiva, RPN1051V), Alexa Fluor 568-conjugated anti-rabbit IgG (Invitrogen). Polyclonal anti-NiV guinea pig serum (gp3) was kindly provided by H. Feldmann. Polyclonal anti-NiV M rabbit serum (IG1321) was produced by ImmunoGlobe. Nuclei were stained with 4,6-diamidino-2-phenylindole (DAPI, Invitrogen).
## Immunofluorescence microscopy
Immunofluorescence staining was performed as described previously (56). Vero76 cells grown on glass coverslips were fixed at indicated time points with 4% paraformaldehyde (PFA, Merck). PFA was quenched with 0.1 M glycine (Roth); cells were permeabilized with ice-cold 1:1 methanol (Sigma)/acetone (Roth) and incubated for 1 h in blocking buffer (2% BSA (Serva), 5% glycerol (Roth), 0.2% Tween20 (Sigma), and 0.05% NaN3 (Merck). After staining with primary antibodies and incubation with Alexa Fluor-conjuga ted secondary antibodies for 1 h, coverslips were embedded in mowiol (Calbiochem).
Confocal images were acquired on a Leica TCS SP5 II or Stellaris 8 confocal laser scanning microscope with a 63×/1.4 NA oil objective. For quantification, widefield fluorescence images were captured on a Leica Thunder Cell Imager using a 20×/0.40 NA objective to generate large tile scans containing more than 5,000 cells per sample. ImageJ (https:// imagej.net/ij) was used to define ROIs containing the glycoprotein-expressing cells (Alexa Fluor 568 channel). Nuclei in these ROIs were identified using the DAPI channel and average GFP intensity within the nuclear area was measured after background-sub traction (GFP channel). The mean nuclear GFP fluorescence intensity is given in arbitrary units (a.u.) and served as a quantitative measure of UPR activation.
## Crystal violet and Giemsa staining
NiV-infected cells were fixed with 4% PFA for 48 h and stained with 0.1% crystal violet (Sigma). The total number of syncytia was counted manually using a light microscope (AMG AMEX 1100 Cell Imager). For quantification of syncytium sizes, complete wells (n=3) were imaged using the Bio-Rad ChemiDoc Touch Imaging System and the area covered by syncytia was analyzed by ImageJ.
To visualize syncytium formation in transfected cells, Vero 76 cells coexpressing the NiV glycoproteins were fixed with ethanol at 20 h post transfection and stained with 1:10 diluted Giemsa staining solution (Sigma) for 30 min.
## SDS-PAGE and western blot
Cells were lysed with RIPA buffer (1% Triton (Roth), 1% deoxycholic acid (Sigma), 0.1% sodium dodecyl sulfate (SDS, Roth), 0.15 M NaCl (Roth), 20 mM Tris/HCl pH 7.5 (Roth, Merck), 10 mM EDTA (Sigma) containing 1:25 cOmplete protease inhibitor (Merck). NiV-infected cells (samples from the BSL-4 facility) were harvested and inactivated in phosphate-buffered saline (PBS) containing 1% SDS and heated two times for 10 min at 100°C. Lysates were then mixed with 2× sample buffer (20% glycerol (Roth), 100 mM Tris pH 6.8 (Roth), 0.04% bromophenol blue (Merck), 3-4% SDS (Roth), 4% β-mercaptoe thanol (Sigma), heated for 10 min at 100°C, and subjected to SDS-PAGE under reducing conditions. Proteins were transferred to nitrocellulose membranes. After blocking with 5% skim milk, membranes were incubated with primary antibodies followed by staining with biotinylated secondary antibodies and horseradish peroxidase (HRP)-conjugated streptavidin. Chemiluminescence was detected with SuperSignal West Dura substrate (ThermoFisher) using the BioRad ChemiDoc Touch Imaging System. Quantification was performed using the ImageLab software (BioRad).
## Quantitative real-time polymerase chain reaction
Total RNA was isolated using the RNeasy Kit (Qiagen) and reverse-transcribed with oligo(dT) 18 primers using the RevertAid First Strand cDNA Synthesis Kit (ThermoFisher) following the manufacturer's instructions. PCRs were performed using 50 ng of cDNA together with 2× Maxima SYBR Green qPCR Master Mix (ThermoFisher) and 60 pmol of the respective forward and reverse primers in a total volume of 25 µL. Amplification was carried out using a StepOne Real-Time PCR System (Applied Biosystems) or a qTOWER³ (Analytik Jena) as follows: 10 min at 95°C, followed by 40 cycles of 15 s at 95°C, 15 s at 53°C, and 30 s at 72°C. Specificity of the amplification was confirmed using a melting curve analysis. To determine mRNA expression levels, ct values were normalized to the internal housekeeping gene by subtraction (Δct) and represented as 2 -Δct or addition ally normalized to the untreated/uninfected control (ΔΔct) and represented as 2 -ΔΔct (fold change over untreated/mock). Gene-specific primers were custom-synthesized and purchased from Eurofins Genomics. The following primers were used in this study: tubulin for GGCCGTGTTTGTAGACTTGG, tubulin rev CTTCCTTGCCTGTGATGAGC, NiV N for ATCAATCGTGGTTATCTTGA, NiV N rev CAGCCAGTTCTGCAACTTGATC, RPS18 for GCGGCG GAAAATAGCCTTTG, RPS18 rev GATCACACGTTCCACCTCATC, GADD34 for AAACACTGGGC CTGAAAACCA, GADD34 rev GCTGGTTGCTTCTTGCTCACT, Calreticulin for GAGCAGAACAT CGACTGTGGG, Calreticulin rev GGCCACAGATATCAGGACCAAA, CHOP for CTCCTGGAAATG AAGAGGAAGAATC, CHOP rev GCTTGTGACCTCTGCTCGTT, Herpud1 for AACGGCATGTGTT GCATCTGGT, Herpud1 rev CTGTGGATTCAGCCACCTTGG, BiP for AGGCTTATTTGGGAAAGA AGGTTAC, BiP rev GATCCTCATAACATTTAGGCCAGC.
## Quantification and statistical analysis
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# Complete genome sequence of a Kayfunavirus bacteriophage identified in Blantyre, Malawi
Chimwemwe Mhango, Wanangwa Ndovie, Allan Zuza, End Chinyama, Flywell Kawonga, Ernest Matambo, Benjamin Kumwenda, Arox Kamng'ona, Chrispin Chaguza, Martin Nyaga, Celeste Donato, Khuzwayo Jere
## Abstract
We report a bacteriophage from Malawi recovered during rotavirus RNA sequencing. It shares 84.3% nucleotide identity with MH400309, a Kayfunavirus bacteriophage. This incidental finding shows RNA virus sequencing can also detect bacteriophages, offering insights into the broader viral diversity in clinical and environ mental samples.
The predicted genes were annotated using Bakta v.2.14.1 (17). Additionally, Life Cycle Classifier v.1.6.0 in phageAI (18) was employed to assign the phage's lifestyle (Table 1). Comparative analyses using taxMyPhage v.0.3.5 (19) revealed an average nucleotide identity of 83.9% between the assembled genome and MH400309, a Kayfunavirus genus.
The discovery of this bacteriophage highlights the hidden diversity of organisms within the gut virome and underscores the importance of using unbiased assem bly pipelines to explore viral diversity. Future work will focus on recovering this bacteriophage from the fecal material and characterizing its biological properties.
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9. Mwangi, Page, Seheri et al. (2003) "Evolutionary changes between pre-and post-vaccine South African group A G2P[4] rotavirus strains" *Microb Genom*
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14. "from high-throughput sequencing data" *Bioinformatics*
15. Nayfach, Camargo, Schulz et al. (2021) "CheckV assesses the quality and completeness of metagenomeassembled viral genomes" *Nat Biotechnol*
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18. Schwengers, Jelonek, Dieckmann et al. (2021) "Bakta: rapid and standardized annotation of bacterial genomes via alignment-free sequence identification" *Microb Genom*
19. Tynecki, Guziński, Kazimierczak et al. (2020) "PhageAI -bacteriophage life cycle recognition with machine learning and natural language processing" *bioRxiv*
20. Millard, Denise, Lestido et al. (2025) "taxMyPhage: automated taxonomy of dsdna phage genomes at the genus and species level" *PHAGE (New Rochelle)*
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# Correction: Systematic review and meta-analysis of virome profiles and quantification of Torque teno virus load in blood of acute febrile illness patients
Chaichan Angwong, Chamsai Pientong, Tipaya Ekalaksananan, Ati Burassakarn, Panwad Tongchai, Hans Overgaard, Sirinart Aromseree
The original Article has been corrected.
## Open Access
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# Role of g5Rp in African swine fever virus replication: disruption of host translation and autophagy
Chunmei Xu, Ruiying Liang, Yongqiang Zhang, Xinyue Zhang, Xiangyin Zhang, Xinru Luo, Dahu Liu, Shaohua Hou, Jiabo Ding, Xinming Tang, Lin Liang, Lingling Chang, Jinming Li, Changjiang Weng, Zhiliang Wang, Xiaomin Zhao
## Abstract
African swine fever (ASF), caused by the African swine fever virus (ASFV), is one of the most severe viral diseases affecting swine. ASFV employs sophisticated strategies to subvert host immune responses; however, the function of the viral protein g5Rp in viral pathogenesis remains incompletely defined. In this study, we demonstrate that g5Rp plays a critical role in viral replication by impairing host translation and autophagy. Overexpression of g5Rp enhanced viral replication and increased p30 protein levels, whereas siRNA-mediated knockdown of g5Rp suppressed both, underscoring its essential proviral function. Proteomic profiling of infected porcine macrophages (3D4/21 cells) revealed that g5Rp dysregulated 122 host proteins, predominantly involved in translation, autophagy, and apoptosis pathways. Mechanistically, g5Rp directly interacted with eIF5A and RPS15, disrupting their complex formation and thereby inhibiting translation initiation and autophagic flux. Structural analyses identified key residues (SER¹¹⁸, SER²⁰⁶, and ASN⁶¹) critical for this interference. Mutation of these residues abrogated g5Rp activity. Furthermore, virtual screening identified 9″-methyl salvianolate B as a potent g5Rp inhibitor, which restored eIF5A hypusination, promoted autophagy, and suppressed ASFV replication in vitro. Collectively, our findings establish g5Rp as a pivotal regulator of ASFV pathogenesis and a promising target for antiviral drug development.IMPORTANCE ASFV has caused significant economic losses to the global pork industry, and no effective treatment or prevention currently exists. In this study, the interaction of g5Rp with the host proteins eIF5A and RPS15 was identified for the first time, and its crucial role in the viral life cycle was clarified. Resolving the crystal structure of g5Rp revealed its binding site to the host protein, which provides a new target for developing antiviral strategies against g5Rp. Additionally, the screened 9″-methyl salvianolate B, a small-molecule inhibitor, has shown the potential to effectively reduce viral replication and restore host protein synthesis. These findings not only deepen our understanding of the mechanism of ASFV infection but also lay the foundation for developing effective anti-ASFV treatment strategies in the future, which has important scientific implications.
progressively, g5Rp cleaves the 5′ cap moiety to facilitate mRNA destabilization, thereby promoting host cellular shutoff and viral replication (6)(7)(8)(9). However, a critical limitation challenges the physiological relevance of this mechanism. Current characterization of g5Rp's decapping activity relies exclusively on its cleavage of cap 0 (m⁷GpppN), using actin mRNA as the sole substrate (7). This contrasts starkly with the natural context: both mammalian and ASFV mRNAs predominantly utilize cap 1 (m⁷GpppNm) structures, with ASFV transcripts overwhelmingly (92%) bearing cap 1 modifications (10)(11)(12). Thus, ASFV likely employs specialized molecular mechanisms, distinct from mRNA decapping, to effectively inhibit host protein synthesis.
Recently, host-pathogen interaction omics studies have revealed how viruses hijack cellular machines through molecular mimicry. Specifically, DNA viruses frequently target ribosomal components and translational initiation factors to preferentially synthesize viral proteins. For example, ASFV pCP312R interacts with the host RPS27A, inhibits host protein translation, and promotes viral replication (13). The Epstein-Barr virus vDUB hindered the Ubiquitin-fold Modifier 1 Modification (UFMylation) of RPL26 and inhibited reticulophagy (14). ASFV UBCv1 binds to eIF4G1 and RPS23 to regulate host translation (15). Recent studies have shown that ASFV pE66L, MGF110-7L, EP152R, and RNA polymerase subunits C315R and H359L induce the closure of host translation via the PKR/eIF2α pathway (16)(17)(18)(19).
Autophagy is a conserved "clearance" mechanism in eukaryotic cells that maintains cellular homeostasis and orderly life activities by degrading and recycling intracellular components. Viral infections frequently induce autophagy to degrade viral components and virions. During ASFV infection, many viral proteins interact with the host proteins to regulate autophagy. For example, the ASFV MGF300-4L protein is associated with viral pathogenicity by promoting the autophagic degradation of IKKβ and improving the stability of IκBα (20). ASFV MGF_360-4L inhibits interferon signaling by recruiting the mitochondria-selective autophagy receptor SQSTM1, thereby degrading antagonis tic innate immune responses (21). ASFV p17 facilitates mitophagy by promoting the interaction between SQSTM1 and TOMM70, which in turn regulates innate immunity (22). ASFV E199L promotes autophagy by interacting with PYCR2 (23). ASFV K205R induces ER stress, which activates autophagy and the NF-κB signaling pathway (24). However, it remains unclear whether ASFVg5Rp regulates autophagy.
In this study, we explored a novel function of ASFV g5Rp and found that g5Rp interacts with eukaryotic translation initiation factor 5A (eIF5A) and ribosomal protein S15 (RPS15) to reduce host protein synthesis. It also downregulates eIF5A and inhibits TFEB, thus suppressing autophagy. Additionally, a small-molecule inhibitor targeting g5Rp, 9″-methyl salvianolate B, effectively alleviated g5Rp-induced inhibition of protein synthesis and autophagy. Our data elucidate multiple regulatory functions of g5Rp during ASFV replication, showing that g5Rp can evade host immune surveillance and attenuate the host cell response to viral infection by inhibiting autophagy.
## RESULTS g5Rp promoted ASFV replication and modulated host pathways
The g5Rp protein facilitates ASFV replication and influences various host cellular pathways. To elucidate the role of g5Rp in ASFV replication, we first examined the dynamics of endogenous g5Rp expression. Low expression levels during the first 0-4 h post-infection (hpi) (Fig. S1A) suggested minimal involvement in the early stages of infection. Based on this observation, we constructed a pCAGGS-Flag-g5Rp overex pression plasmid. Overexpression of g5Rp enhanced viral replication and increased p30 expression (Fig. 1A andC), whereas siRNA-mediated knockdown of g5Rp reduced both (Fig. 1B andD). Comparative proteomics of g5Rp-overexpressing cells revealed significant alterations in the host proteome (Fig. S1B andC; Dataset S1). Gene Ontology (GO) enrichment analysis identified significant changes in translation factor activity, transmembrane transport, and antioxidant activity (Fig. 1E). KEGG pathway analysis linked g5Rp to autophagy, lysosomal function, ferroptosis, and apoptosis regulation (Fig. 1F). Collectively, these findings indicate that g5Rp promotes ASFV replication by remodeling multiple host cellular pathways.
## g5Rp interacted with eIF5A and RPS15 to promote ASFV replication
To elucidate how g5Rp enhances ASFV replication, we identified its interacting proteins via immunoprecipitation-mass spectrometry (IP-MS) (Table S1), focusing on the eukaryotic translation initiation factor 5A (eIF5A) and ribosomal protein S15 (RPS15). These interactions were confirmed under ASFV infection by co-immunoprecipitation (Co-IP) and proximity ligation assay (PLA) (Fig. 2A through D) and were validated in HEK293T cells through co-transfection (Fig. 2E andF). We further found that g5Rp significantly downregulated eIF5A protein levels and inhibited its hypusination, thereby compromising eIF5A's antiviral restriction activity (Fig. S2A). Functionally, eIF5A knockdown enhanced viral replication and p30 expression, while its overexpression suppressed both (Fig. 2G andI; Fig. S2B). Although g5Rp did not alter total RPS15 levels, it significantly reduced the association of RPS15 with the 40S ribosomal subunit (Fig. S2C through E), indicating impaired ribosomal localization and function. Consistently, RPS15 overexpression further enhanced viral replication (Fig. 2H andJ; Fig. S2F). Thus, g5Rp remodeled the host translational machinery by (i) inhibiting eIF5A-medi ated antiviral restriction and (ii) disrupting RPS15 ribosomal localization and function, thereby preferentially promoting viral protein synthesis and enhancing ASFV replication efficiency.
g5Rp disrupted the interaction between eIF5A and RPS15 and inhibited host translation eIF5A and ribosome binding are the basis of host translation (25). Therefore, we examined whether g5Rp inhibits host translation by directly disrupting the eIF5A-RPS15 complex. Using Co-IP and PLA, we demonstrated that g5Rp disrupts eIF5A-RPS15 interaction (Fig. 3A andB). In host cells, g5Rp overexpression exhibited dose-depend ent and time-dependent suppression of global protein synthesis, as quantified by the puromycin incorporation assay (Fig. 3C andD; Fig. S3A andB). Concurrently, ASFV p30 protein accumulation correlated with increased viral genome replication (Fig. 3C andD; Fig. S3C through E). Furthermore, eIF5A or RPS15 knockdown phenocopied this translational inhibition and induced cell cycle arrest (Fig. 3E; Fig. S3F). Conversely, expression of an eIF5A-RPS15 fusion protein that maintains complex integrity fully restored translation (Fig. 3F). These findings establish the disruption of the eIF5A-RPS15 complex as a key mechanism for g5Rp-mediated enhancement of ASFV replication. We first determined that g5Rp overexpression significantly increased p62 accumulation and decreased the LC3-II/I ratio (Fig. 4A; Fig. S4A), indicating impaired autophagic flux.
During ASFV infection, eIF5A protein levels progressively declined (Fig. 4B; Fig. S4B). The eIF5A inhibitor GC7 phenocopied these changes and reduced eIF5A hypusination (Fig. 4C; Fig. S4C). Impaired eIF5A function directly caused autophagic dysregulation, as eIF5A knockdown or GC7 treatment phenocopied g5Rp overexpression, resulting in p62 accumulation and reduced autophagosome formation (Fig. 4D; Fig. S4D andE). Immunofluorescence assay confirmed that eIF5A knockdown blocked starvationinduced TFEB nuclear translocation (Fig. 4E). g5Rp downregulated eIF5A expression and hypusination, thereby disrupting TFEB-mediated autophagy and impairing autophagic flux.
## Identification of key interaction sites in g5Rp for eIF5A or RPS15 binding
To identify the specific amino acid binding sites of the three, we determined that g5Rp forms a stable, symmetric homodimer (Fig. S5A and B; Table S2), which not only supports catalytic activity but also serves as a platform for protein interaction. Molecular docking revealed a hydrogen bond-mediated ternary network centered on g5Rp residues SER¹¹⁸, SER²⁰⁶, and ASN⁶¹: eIF5A-ASN⁸³ and RPS15-ARG⁸¹ competed for g5Rp-SER¹¹⁸, while eIF5A-ARG²⁶ and RPS15-ARG⁴⁴ competed for g5Rp-ASN⁶¹ (Fig. S5C through F). Functional analysis showed that alanine (ALA) substitution at SER¹¹⁸, SER²⁰⁶, and ASN⁶¹ (g5Rp mutant) abolished g5Rp-eIF5A binding and attenuated g5Rp-RPS15 interaction (Fig. 5A and B). This restored physiological eIF5A-RPS15 binding (Fig. 5C andD), confirming these residues as critical interaction sites. Consequently, g5Rp lost its wild-type viral promotion capacity (Fig. 5E and F; Fig. S5G andH), indicating that g5Rp's proviral activity requires an intact eIF5A or RPS15-binding interface.
## 9″-methyl salvianolate B binds ASFV g5Rp and modulates eIF5A and RPS15 interaction
Based on the binding site identified by molecular docking, virtual screening identified 9″-methyl salvianolate B as a high-affinity g5Rp inhibitor (Table S3). Molecular docking demonstrated its stable binding to the hydrophobic pocket of g5Rp (Fig. 6A), and surface plasmon resonance (SPR) confirmed strong binding kinetics (Fig. 6B; Fig. S6A andB). The CC50 in 3D4/21 cells was 16.22 µM, with viability exceeding 80% at 10 µM, indicating optimal conditions for functional studies (Fig. S6C andD). Co-IP and PLA showed that g5Rp binding to eIF5A or RPS15 was reduced (Fig. 6C through F), leading to restored eIF5A and RPS15 interactions (Fig. 6G andH).
## 9″-methyl salvianolate B restored host function and inhibited ASFV replica tion
To verify whether 9″-methyl salvianolate B has the function of restoring host translation and autophagy, we first verified its effect on eIF5A hypusination, and the results showed that 9″-methyl salvianolate B could restore eIF5A hypusination (Fig. 7A; Fig. S7A). This compound partially restored host cell protein synthesis (Fig. 7B) and alleviated cell cycle arrest at the G0/G1 phase (Fig. S7B andC). Critically, it promoted TFEB nuclear translocation (Fig. 7C; Fig. S7D), leading to increased LC3-II/LC3-I ratios, reduced p62 levels (Fig. 7D; Fig. S7E), and elevated lysosomal biogenesis (Fig. S7F), which indicates restored autophagic flux. In ASFV-infected cells, 9″-methyl salvianolate B reduced viral p30 protein expression (Fig. 7E and F; Fig. S7G) and suppressed viral replication, even upon g5Rp overexpression (Fig. 7G). These findings establish 9″-methyl salvianolate B as a candidate therapeutic that targets g5Rp to restore eIF5A and RPS15 interactions, reactivate host protein synthesis, and reactivate the autophagy pathway to inhibit ASFV replication.
## DISCUSSION
ASFV causes a highly contagious hemorrhagic disease, incurring catastrophic economic losses globally due to the absence of vaccines or antivirals (26). This therapeutic gap reflects persistent knowledge deficits regarding viral pathogenesis, specifically how ASFV subverts host machinery. Here, we identify the viral protein g5Rp as a key virulence factor that hijacks host translation and autophagy. This dual mechanism advances our understanding of ASFV pathogenesis and nominates g5Rp as a therapeutic target (Fig. 8). The integration of proteomics and virology has advanced our understanding of viral replication, host antiviral responses, and viral subversion mechanisms (27). In ASFV research, proteomics revealed virus-host interaction dynamics. Infection significantly remodels the host proteome, disrupting biological processes and signaling pathways (28,29). In this study, proteomics screened the key host factors eIF5A and RPS15 that interact with g5Rp and synergistically regulated host cell translation and autophagy, which provided a theoretical basis for the design of antiviral targets to elucidate a new strategy for efficient replication of ASFV g5Rp by regulating eIF5A and RPS15.
Translation factor-ribosome interactions (e.g., eIF5A binds via its N-and C-termi nal domains to address ribosomal arrest and promote viral IRES activity) have been recognized as central to protein homeostasis (30)(31)(32)(33). Our study uncovered that g5Rp acts as a viral disruptor by competitively binding both eIF5A and RPS15. This disman tled their functional complex, impairing ribosome assembly, suppressing translation, and inducing G0/G1 arrest-effects that synergize with g5Rp-mediated autophagy dysregulation to drive ASFV-induced proteostasis collapse. This mechanism, distinct from prior reports on isolated translation factors (34,35) or ribosomal proteins (36)(37)(38), positioned g5Rp as a master coordinator of host translational hijacking, offering a molecular lens through which to reinterpret multifactor-ribosome states in viral pathogenesis.
eIF5A maintains autophagic flux by facilitating the translation of autophagy regulators containing polyproline motifs, such as TFEB (39,40). TFEB serves as the core effector, whose overexpression reverses autophagy impairment caused by eIF5A inhibition, although this regulatory axis exhibits significant context dependency (39,41). Hypusinated eIF5A participates broadly in viral replication. It functions not only as a critical regulator of Ebola virus gene expression (involving polyamine-dependent mechanisms specific to hypusinated eIF5A) (42), but also contributes to the replica tion of pathogens, including Marburg virus (MARV) and HIV (41). We therefore inves tigated whether g5Rp exploits this post-translational modification. Critically, g5Rp downregulated both total and hypusinated eIF5A, inhibiting protein synthesis and autophagy to facilitate ASFV replication. This aligns with established reports that hypusination promotes replication of Kaposi's sarcoma-associated herpesvirus (KSHV) and Coxsackievirus (32,43). Although ASFV's impact on polyamine metabolism requires further investigation, g5Rp-mediated eIF5A reduction sufficiently suppresses autophagy independently of canonical pathways.
Current ASFV inhibitor development focuses on essential enzymes, including the pS273R cysteine protease and dUTPase, providing key foundations for antiviral drug discovery (44)(45)(46).
Here, through structure-guided virtual screening coupled with molecular dynamics simulations (47), we identify 9″-methyl salvianolate B-a phenolic compound from Radix Salvia miltiorrhizae with established anti-inflammatory properties (48,49)-as the first g5Rp protease-specific inhibitor. Mechanistically, it formed stable hydrogen-bonding networks to suppress enzymatic activity, significantly reducing ASFV replication efficacy. This work validated g5Rp as a novel druggable target and delivered a key candidate molecule for anti-ASFV lead optimization.
While this study established g5Rp's role in vitro, several questions remain. First, the in vivo efficacy of 9″-methyl salvianolate B requires validation in porcine models, particu larly regarding pharmacokinetic optimization for tissue-specific delivery. Second, the interplay between g5Rp and other ASFV immune evasion proteins warrants further investigation, as synergistic interactions may amplify viral pathogenicity. Third, our structural data do not fully explain how g5Rp binding to RPS15 modulates ribosome function, a question addressed by cryo-EM studies of g5Rp-ribosome complexes.
In conclusion, we proposed a model wherein g5Rp acts as a central hub coordinating host translational shutdown and autophagy inhibition to promote ASFV replication. The integration of proteomic, structural, and pharmacological approaches in this study bridges the critical gap between ASFV biology and therapeutic development. Our study not only redefines g5Rp as a multifunctional virulence factor but also pioneers a host-directed antiviral strategy with broad implications for combating complex DNA viruses.
## MATERIALS AND METHODS
## Cells and virus
Porcine alveolar macrophage-derived 3D4/21 cells (ATCC CRL-2843) and HEK293T cells (ATCC 73451) were maintained in DMEM supplemented with 10% FBS, 100 U/mL penicillin, and 100 µg/mL streptomycin at 37°C with 5% CO₂. The ASFV strain China/ LN2018/1 was propagated in 3D4/21 cells and stored at -80°C. Viral titers were determined by TCID₅₀. All ASFV-related experiments were performed in a BSL-3 facility.
## Co-immunoprecipitation (Co-IP)
3D4/21 cells were transfected with plasmids and infected with ASFV (MOI = 1, 24 h). Cells were collected and lysed in lysis buffer (50 mM Tris-HCl, pH 7.4, 150 mM NaCl, 5 mM MgCl₂, 1 mM EDTA, 1% Triton X-100, and 10% glycerol) containing 1 mM phenylmethyl sulfonyl fluoride (PMSF) and 1× protease inhibitor cocktail (Roche, Basel, Switzerland). Cell lysates were centrifuged (12,000 × g, 10 min), and supernatants were pre-cleared by incubation with protein A/G agarose (Sigma) at 4°C for 1 h. The pre-cleared supernatants were then incubated with anti-Flag (M2) agarose beads or with protein G plus agarose beads (MedChemExpress) pre-bound with 1 µg of control IgG antibody overnight at 4°C on a roller. The immunoprecipitation complexes were captured by the beads and subsequently washed five times with the cell lysis buffer. Captured complexes were then analyzed by immunoblotting.
## LC-MS/MS analysis
LC-MS/MS was conducted on a Q Exactive HF-X system (Thermo Fisher) as descri bed (Thermo Fisher Scientific) (50). Briefly, IP-precipitated proteins were separated by SDS-PAGE. Gel bands were treated with reduction/alkylation buffer (10 mM TCEP, 60 mM iodoacetamide, 50 mM NH₄HCO₃) and digested with trypsin (2 µg in 50 mM NH₄HCO₃), and peptides were desalted using C18 tips (Pierce). Samples were lyophilized, dissolved in 0.1% formic acid, and analyzed by LC-MS/MS. Data were processed via Proteome Discoverer 2.2 (FDR <1%, ≥2 unique peptides, fold change ≥2 vs IgG, P < 0.05). in PBS, ≤0.2% DMSO) was injected at 25°C. The equilibrium dissociation constant (KD = 117 nM) was calculated using Biacore Evaluation Software.
## Statistical analysis
Proteomics data were analyzed using the "ClusterProfiler" R package (55). The SPSS software package (SPSS for Windows v13.0; SPSS Inc., Chicago, IL) was used to perform statistical analysis of the data obtained during the experiment. After normality testing, all data conformed to a normal distribution (Shapiro-Wilk test P > 0.05). Differences between the experimental and control groups were analyzed by Student's t-test or one-way ANOVA with Tukey's test using Prism 10 (GraphPad Software, San Diego, CA). Values are expressed in graph bars or a line graph as the mean ± SD of at least three independent biological replicates. *, P < 0.05; **, P < 0.01; and ***, P < 0.001 were considered statistically significant. ns, no significant difference.
For other methods, such as antibody information, plasmid construction, qPCR, and Western blotting, refer to the supplemental material.
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# Near-complete genome of two genotype II African swine fever viruses recovered from domestic pigs in Tanzania
Jean Hakizimana, Clara Yona, Charles Kayuki, Mariam Makange, Ester Adamson, Amanda Warr, Christine Tait- Burkard, Hans Nauwynck, Gerald Misinzo
## Abstract
Two near-complete genomes of genotype II African swine fever viruses (ASFV) recovered from domestic pigs in Mbozi district, Tanzania, in 2017 were generated using tiled amplicon Oxford nanopore sequencing. These two ASFV genomes described in this study were closely related to other genotype II isolates reported worldwide. KEYWORDS African swine fever virus, complete genome sequencing, Oxford nanopore, Tanzania A frican swine fever (ASF) is a transboundary animal disease with a mortality rate reaching 100% (1). Whole genome sequencing of ASF virus (ASFV) provides insights for the design of control strategies. The ASFV is an enveloped, double-stran ded DNA virus belonging to the family Asfarviridae, genus Asfivirus (2). To overcome ASFV sequencing challenges, including the dominance of host DNA, a tiled amplicon sequencing approach has been developed (3, 4).Tissue samples, including spleen and mesenteric lymph nodes, collected during the 2017 ASF outbreak in Mbozi district in southern Tanzania (ASFV/TAN/17/Mbozi/1 and ASFV/TAN/17/Mbozi/2) were tested for ASFV and clustered within ASFV genotype II as previously described (5). The DNA was extracted using the QIAamp DNA purifi cation kit (Qiagen, Hilden, Germany), followed by polymerase chain reaction (PCR) amplification as previously described (3). A total of 32 tiled primer pairs were used to amplify fragments of about 7 kb with overlaps of 1 kb between adjacent ampli cons using PCR Bio VeriFi Hot Start highfidelity DNA polymerase. Amplicon size was verified by 1% agarose gel electrophoresis (Gel DocTM EZ Imager, Bio-Rad, Hercules, CA). The amplicons were pooled for library preparation using the ligation sequencing kit (SQK-LSK109, Oxford Nanopore Technologies, Oxford, UK) and sequenced on an R9.4.1 flow cell using MinION MK1c with basecalling and demultiplexing performed by Guppy v5.0.14 (Oxford Nanopore Technologies, Oxford, UK). The Lilo pipeline (https:// github.com/amandawarr/Lilo) was used for data analysis. Lilo uses a reference to sort the amplicons and separate reads into amplicons by alignment position using bedtools v2.30.0, followed by polishing against the highest quality reads, while primer sequences are removed using Porechop v0.2.3, and assembly is performed with Scaffold_builder v2.3. In this study, the Lilo pipeline was modified due to some misassembly caused by chimeric amplicons in the sequencing data. In the rule "assign", bedtools intersect command parameters were edited to include "-F 0.85 f 0.85" to limit the selection to sequences that contained only the target amplicon, while allowing flexibility for real indels. The resulting assemblies were evaluated using the Quality Assessment Tool (QUAST) version 5.0.2 (6).The nucleotide sequences of the assembled ASFV strains had a genome size of 172,585 and 167,022 base pairs (bp), average coverage of 2,500 and 4,370 reads per nucleotide, and a GC content of 38.95 and 39.17% for the strains ASFV/TAN/17/Mbozi/1
and ASFV/TAN/17/Mbozi/2, respectively (Table 1). After the NCBI GenBank database search and phylogenetic reconstruction (Fig. 1), the sequences described in this study were closely related to the TAN/01/2011 ASFV isolate (OQ434234) (7) belonging to genotype II with a nucleotide identity of 99.82% and a query coverage of 100%. In addition to the lack of the highly repetitive 3′-and 5′ telomeric regions for the two sequences, indels were observed along the alignment after comparison with the ASFV genotype II reference genome Georgia2007/1 (FR682468.2), including a deletion of fragments of 5,465 and 5,220 bp at positions 16,190-21,665 and 169,120-174,340, respectively, leading to the truncation of the MGF 360-1Lb CDS and ASFV G ACD 01980 CDS in both ASFV strains described in this study.
## References
1. Pikalo, Zani, Hühr et al. (2019) "Pathogenesis of African swine fever in domestic pigs and European wild boar -Lessons learned from recent animal trials" *Virus Res*
2. Alonso, Borca, Dixon et al. (2018) "ICTV virus taxonomy profile: Asfarviridae" *J Gen Virol*
3. Warr, Newman, Craig et al. (2021) "No part gets left behind: tiled nanopore sequencing of whole ASFV genomes stitched together using Lilo" *bioRxiv*
4. (2022) "PCR Tiling of African Swine Fever (ASF) Virus (SQK-LSK109 with EXP-NBD104 or EXP-NBD114)"
5. Yona, Vanhee, Simulundu et al. (2015) "Persistent domestic circulation of African swine fever virus in Tanzania" *BMC Vet Res*
6. Gurevich, Saveliev, Vyahhi et al. (2013) "QUAST: quality assessment tool for genome assemblies" *Bioinformatics*
7. Mthombeni, Bastos, Van Schalkwyk et al. (2023) "Phylogenomic comparison of seven African swine fever genotype II outbreak viruses (1998-2019) reveals the likely African origin of Georgia 2007/1" *Pathogens*
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# Systems Virology at Scale
Cameron Griffiths, Andrew Sweatt, Kevin Janes
## Abstract
Today's subcellular and multicellular models of infection are poised to tackle bigger questions about virus-host interactions and the determinants of susceptibility. This opportunity comes from increased computing power, improved model architectures, and comprehensive datasets collected from virus-infected hosts. Here we summarize recent advances in viral modeling and data science that illustrate how systems models have successfully traversed increasing time-length scales, levels of detail, and ranges of biological context. The latest progress is encouraging, but recent findings just scratch the surface given how many different viruses exist or could someday emerge -the scale of the effort should align with the scale of the challenge. Abstraction of molecular and cellular networks by systems virology complements public-health models of viral transmission that are widely applied to human populations.
## Introduction
Viral infections are a Goldilocks perturbation for systems biology-complicated enough to expose the limits of single-gene thinking, but simple enough that mathematical models of core processes are achievable. SARS-CoV-2 highlighted a gap in research that created new paths for systems virology [1]. Genetic data on viruses were always plentiful, but the pandemic triggered additional collection of proteomics [2], phospho-proteomics [3], and protein-protein interaction maps both measured [4] and curated [5]. Analogous resources are now available for other viruses and the associated host response [6][7][8]. It is time for systems biologists to fully exploit them.
There is precedent for intertwining big data and systems thinking in the research of noninfectious diseases such as cancer. DepMap [9] and The Cancer Genome Atlas [10] provide rich multi-modal data that are as indispensable to systems biologists as their own RNA sequencing and immunoblots. For viruses, improvements are coming from the bottom upthere are better models of infection that go beyond proof-of-concept and are ready to be deployed at a cancer research-like scale. In this Primer article, we summarize how systems virology models are broader, longer, larger, and deeper than ever before.
## Broader systems virology-more viruses, hosts, simulations
The most granular view of viral infection is like that of a snowflake, where no two infections are exactly the same. The coarsest view conceives of all viruses as foreign replicons that enter host cells, multiply, and release. In between is where systems biology should thrive in identifying quantitative themes with molecular detail that recur in multiple viral species [11,12] (Figure 1A). Analogously, all host cells are not created equal [13], and systems virology models are an ideal platform for examining what-if infections of "digital twins" [14] with individualized susceptibilities (Figure 1B). Recent advances in data generation and computing power have broadened the ambition of what systems models of virus infection can accomplish along these lines.
Zitzmann et al. [15]•• recognized that the rate processes of positive-strand RNA viruses have a remarkably similar connectivity and asked whether a generic model could accommodate all of them (Figure 1A). The authors constrained about half of the parameters with virusspecific kinetic rates or host-cell rates shared by all models. The other half were fitted to three positive-strand viruses (hepatitis C virus, dengue virus, and coxsackievirus B3) that were experimentally profiled in the same hepatoma cell line (Huh7). Differences in infection kinetics among species suggested distinct sensitivities to drug intervention at different points in the viral life cycle, such as entry and replication. Although experimental tests await, the study raised the exciting possibility that general life-cycle architectures could extend their reach to the growing number of RNA viruses that infect humans [16].
Viral replication varies among infected cell types in a tissue [17] and disrupts proliferationdifferentiation relationships of normal homeostasis [18]. Raach et al. [19]•• built a multicell model of the human airway infected with SARS-CoV-2 based on cell type-specific parameters gleaned from single-cell transcriptomes measured over time. The model captured the importance of cell death and regeneration at different airway sites during infection and investigated the effect of prior cigarette smoke exposure on viral pathogenesis. Lord and Bonsall [20] extended the pursuit of conditional viral kinetics to models of non-vertebrate hosts for arthropod-borne viruses. Using a stochastic model of mosquito infection after a bloodmeal, the authors found that the initial rate of midgut cell infection determined whether or not a mosquito would subsequently transmit virus to a human. As single-cell information continues to expand, so should multi-cell type-specific models.
Systems virologists often must be pragmatic when defining host contexts (Figure 1B). Sweatt et al. [21]•• built 1489 digital-twin [14] models of coxsackievirus B3 infection by estimating receptor protein copy numbers from public transcriptomics by using genespecific regressions trained in hundreds of cancer cell lines. Using the inferred abundances of two relevant viral receptors as initial conditions for a systems model of the coxsackievirus B3 life cycle [22], the group identified cases that fell into resistant, low, medium, or high classes of susceptibility. Although infection involves both receptors [23,24], these classes were based on abundance of one receptor but not the other, illustrating how parameter sensitivity is conditioned on individual variation.
## Longer and larger systems virology-time and length scales of infection
Compared to other diseases in which cellular damage accumulates over several years, viral infection is fast and its growth effectively unlimited across spatial scales (Figure 2). Basic kinetic models of viral infection have a considerable history [25], as do susceptibleinfected-recovered (SIR) models for population-scale outbreaks [26]. Systems biologists have adopted a "middle-out" strategy [27] that begins with the host cell, overlaying cellautonomous antiviral responses and non-cell autonomous immune feedback at the multiscale (Figure 2). Bulk RNA-seq of cells and tissues is a good source of evidence for pruning model parameters in a principled way. Adam et al. [28]• harnessed an RNA-seq time course to define 34 antiviral genes that robustly respond to SARS-CoV-2 infection and then trained a minimalistic mathematical model that included this antiviral signature. The model was refined by adding or subtracting biologically supported feedbacks, ultimately revealing that viral protein production was saturated at small total amounts of viral transcripts, possibly as a result of an auto-repression loop mediated by a SARS-CoV-2 nonstructural protein. Chaturvedi et al. [12]• found by model and experiment that breaking this auto-repression loop leads to an over-accumulation of cytotoxic viral proteins and host-cell apoptosis. Scaling from virions to host cells (Figure 2) requires a delicate stoichiometric balance of viral products during replication that is accounted for in detailed models of infection [22]. For instance, Larkin et al. [29]• found in a detailed model of Eastern equine encephalitis virus that constraining the ratio of sense:antisense genomes created collateral requirements on polysome loading to capture the measured time course of infection. Not all viruses follow the unfettered growth trajectory shown in Figure 2. For example, infections of the heart occasionally progress to a chronic state that causes long-term tissue damage [30]. Taking inspiration from the viral prospecting in pan-cancer datasets [31], Griffiths et al. [32]• agglomerated RNA-seq transcriptomes from 979 independent heart samples and searched for evidence of undiagnosed infection within the unaligned reads. The study identified 189 cases (19%) that separated into three robust host-cell profiles associated with chronic heart infection. These three groups provide simplified, data-informed estimates of different host-cell contexts for future modeling efforts (Figure 1B).
Authentic tissue models of infection must recognize the focal nature of infection [33] and the immune cell influx that is triggered from hours to days (Figure 2). Multiscale models of this kind are most advanced for respiratory infections. Using a "cellularized" [34] model of influenza in the lung, Sego et al. [35] found that a patchy infection required ~1000-fold more virus locally to elicit the same outcomes as a spatially uniform infection. An analogous conclusion was reached by Gianlupi et al. [36] when considering cell-to-cell heterogeneity in drug metabolism. Their agent-based model of SARS-CoV-2 infection predicted that a 25% coefficient of variation in net drug uptake among cells would result in a ~two-fold reduction in remdesivir potency. Another source of self-reinforcing heterogeneity over time is the cell-intrinsic antiviral response [37], which has been modeled before [38] and is worthy of future consideration in tissue settings.
Elsewhere, multiscale models have served as imputation engines, yielding information about viral progression that might otherwise be difficult or impossible to obtain. Kitagawa et al. [39]• built an age-variant model of hepatitis B infection that combined intracellular and intercellular processes occurring over several weeks. The model provided reasonable estimates for abundance of closed-circular viral DNA in hepatocytes given serum biomarkers, which is highly desirable considering the alternative of serial liver biopsies. Another historically inaccessible window of infection on the opposite end of the length-time spectrum is the immediate-early stage after viral entry. For positive-strand RNA viruses, fixed imaging snapshots and emerging live-cell approaches have begun to fill in the gaps one stage at a time [40,41]. Given single-molecule data synchronized by the onset of viral entry, there are open avenues for systems models to connect the early stochastic phase of infection with later phases that are adequately framed as bulk rate processes. This includes categorizing mechanisms of infection failure and recovery when genomes are not translated productively, which may be useful in devising strategies for prevention or interception after exposure.
## Deeper systems virology-mechanistic detail
Early viral infection or reactivation involves a small number of viral particles or genomes, and their intrinsic stochasticity alters system properties compared to bulk-averaged models [42][43][44][45]. Likewise, oft-lumped steps in viral infection may yield new predictions when the molecular mechanisms are elaborated where quantitative information is available (Figure 3A,B). A linear cascade of steps is not worth enumerating unless some or most of the parameters are constrained, but lumped processes with feedbacks and multiplicities create non-intuitive behaviors [22], as highlighted here.
One principle that is perhaps more compelling for viruses [22] than for cells [46] is modularity-a characteristic of interchangeable components with well-defined inputs and outputs that connect to perform a prescribed function. The compact genomes of many viruses and their evolution by recombination argue for a plug-and-play architecture of infection modules that are built and later repurposed. Artcibasova et al. [47]•• pursued this strategy in modeling the escape of influenza A viral genomes by capsid breakage (Figure 3A). The authors discriminated between three potential biochemical models for interactions among viral capsid protein and dynein-myosin motors by integrating reaction biochemistry with a biophysical model of the motor-dependent mechanical forces on the viral capsid. The best model suggested that a key enzyme directly binds viral capsid to dynein but requires a host ubiquitin chain intermediate to link to myosin. Further, ~fivefold fewer dynein interactions (relative to myosin interactions) were predicted to maximize capsid breakage. The details of endosome escape differ among viruses [48], but common themes at the family level warrant future computational modularization.
Antiviral pathways from sensors to effectors are too numerous [49] to study without model-guided simplifications (Figure 3B). Korwek et al. [50]• developed a mathematical model of the positive and negative feedback loops among nonself RNA sensing; STAT1/2 transcription of effectors; PKR-RNase L activity; and NF-κB, IRF3, and interferon β (IFNβ) signaling. They found that STAT1/2 activity was repressed in favor of NF-κB-IRF3 activation when IFNβ-prestimulated cells encountered nonself RNA due to rapid degradation of the type I IFN receptor upon stimulation. Others have delved more deeply into the stochasticity of the type I interferon response [51] or contextualized nonself RNA more broadly as part of the integrated stress response [52]. By moving vertically and horizontally, these models provide different starting points for how antiviral circuits will impact the success of viral infection.
## Outlook
Reaching systems virology at scale will not happen unless we anticipate modeling frameworks grand enough to leverage big data as they become available. For example, one recognized determinant of viral outcomes is host-cell variability, both before infection [53] and during its early stages [37,54]. However, single-cell observations are usually taken at face value rather than as a template for executable models that are more general and possibly more useful [55]. The challenge is further exaggerated by spatial heterogeneity of cell types and states in host tissues [56]. Multiscale models of systems virology (Figure 2) might one day cooperate with generative models of host-tissue organization like those emerging in cancer [55,57] to create testbeds for infection.
Another ever-moving goalpost is the number of host-cell factors that intersect with viral pathogenesis. Viral-host interactomes [58] are expanding but remain far from saturation, and protein-gene interactions are also prevalent [59]. Functional screens in primary cells [60] and single cells [61] narrow the field somewhat, but they do not connect the dots in ways needed for systems models. We envision "topology tests" that distinguish whether a new dependency can remain lumped within an existing reaction (Figure 3) or requires new regulatory wiring instead. Such tests would likely combine theory and targeted experiments guided by the working model. Lastly, we see future opportunities for systems biology in special cases of infection where repeated longitudinal sampling is possible. Options will be limited to individualized SIR-type models when given time-resolved measurements of viral load alone, as in [62]. However, more modeling possibilities will become available if samples are additionally profiled by low-pass RNA sequencing [63] as a cost-effective supplement. For unique pathogens where human-challenge studies are permitted, such as rhinovirus [64], longitudinal sampling before peak viral load is predicted to constrain dynamical models strongly [65]. Differences in infection dynamics among individuals is a systems challenge that will require good models to decipher (Figure 1B).
There are hundreds of human-infectious viruses [16], but only about a dozen bona fide viral models with molecular resolution in the BioModels database [66] (Figure 2). Systems biologists must step up and address this gap in preparation for the next pandemic. Identifying strategies for useful abstractions of all viral pathogens will position society to respond better when a new one emerges.
## References
1. "Papers of particular interest, published within the period of review, have been highlighted as: • of special interest •• of outstanding interest"
2. Getz, Wang, An et al. "Iterative community-driven development of a SARS-CoV-2 tissue simulator" *bioRxiv*
3. Demichev, Tober-Lau, Lemke et al. (2021) "A time-resolved proteomic and prognostic map of COVID-19" *Cell Syst*
4. Pellegrina, Bahcheli, Krassowski et al. (2022) "Human phospho-signaling networks of SARS-CoV-2 infection are rewired by population genetic variants" *Mol Syst Biol*
5. Shah, Beesabathuni, Fishburn et al. "Systems Biology of Virus-Host Protein Interactions: From Hypothesis Generation to Mechanisms of Replication and Pathogenesis" *Annu Rev Virol*
6. Ostaszewski, Niarakis, Mazein et al. (2021) "COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms" *Mol Syst Biol*
7. Justice, Reed, Phelan et al. (2024) "DNA-PK and ATM drive phosphorylation signatures that antagonistically regulate cytokine responses to herpesvirus infection or DNA damage" *Cell Syst*
8. Olson, Assaf, Brettin et al. (2023) "Introducing the Bacterial and Viral Bioinformatics Resource Center (BV-BRC): a resource combining PATRIC, IRD and ViPR" *Nucleic Acids Res*
9. Galanti, Patino-Galindo, Morita et al. (2024) "Virome Data Explorer: A web resource to longitudinally explore respiratory viral infections, their interactions with other pathogens and host transcriptomic changes in over 100 people" *PLoS Biol*
10. Tsherniak, Vazquez, Montgomery et al. (2017) "Defining a Cancer Dependency Map" *Cell*
11. Hutter, Zenklusen (2018) "The Cancer Genome Atlas: Creating Lasting Value beyond Its Data" *Cell*
12. Andreu-Moreno, Bou, Sanjuan (2020) "Cooperative nature of viral replication" *Sci Adv*
13. Chaturvedi, Wolf, Rosas-Rivera et al. (2022) "PubMed: 35561685] This study illustrates the importance of negative feedback loops on viral infection by breaking negative feedback and measuring decreased viral progeny due to host cell apoptosis despite increases in viral replication and translation" *Cell*
14. Sapiens, Jones, Karkanias et al. (2022) "The Tabula Sapiens: A multiple-organ, single-cell transcriptomic atlas of humans"
15. Laubenbacher, Sluka, Glazier (2021) "Using digital twins in viral infection" *Science*
16. Zitzmann, Dachert, Schmid et al. (2023) "Mathematical modeling of plusstrand RNA virus replication to identify broad-spectrum antiviral treatment strategies" *PLoS Comput Biol*
17. Zhang, Chase-Topping, Guo et al. (2020) "Global discovery of human-infective RNA viruses: A modelling analysis" *PLoS Pathog*
18. Krause, Cepko (2024) "Abortive and productive infection of CNS cell types following in vivo delivery of VSV" *Proc Natl Acad Sci U S A*
19. Nigg, Castello-Sanjuan, Blanc et al. (2024) "Viral infection disrupts intestinal homeostasis via Sting-dependent NF-kappaB signaling in Drosophila" *Curr Biol*
20. Raach, Bundgaard, Haase et al. (2023) "Graw F: Influence of cell type specific infectivity and tissue composition on SARS-CoV-2 infection dynamics within human airway epithelium"
21. Lord, Bonsall (2023) "Mechanistic modelling of within-mosquito viral dynamics: Insights into infection and dissemination patterns" *PLoS Comput Biol*
22. Sweatt, Griffiths, Groves et al. (2024) "PubMed: 39333715] This method builds 1489 virtual-twin models of coxsackievirus B3 infection to predict classes of susceptibility from data-driven estimates of viral receptor" *Mol Syst Biol*
23. Lopacinski, Sweatt, Smolko et al. (2021) "Modeling the complete kinetics of coxsackievirus B3 reveals human determinants of host-cell feedback" *Cell Syst*
24. Bergelson, Cunningham, Droguett et al. (1997) "Isolation of a common receptor for Coxsackie B viruses and adenoviruses 2 and 5" *Science*
25. Shafren, Bates, Agrez et al. (1995) "Coxsackieviruses B1, B3, and B5 use decay accelerating factor as a receptor for cell attachment" *J Virol*
26. Yin, Redovich (2018) "Kinetic Modeling of Virus Growth in Cells" *Microbiol Mol Biol Rev*
27. Kermack, Mckendrick "Contribution to the mathematical theory of epidemics"
28. Brenner (2010) "Sequences and consequences" *Philos Trans R Soc Lond B Biol Sci*
29. Adam, Stanifer, Springer et al. (2023) "This article defines a set of 34 antiviral genes that are induced by SARS-CoV-2 infection and modulate the simulated dynamics of SARS-CoV-2 infection" *Sci Signal*
30. Larkin, Dunn, Shoemaker et al. (2025) "PubMed: 40465541] This article builds a rule-based model of Eastern equine encephalitis virus infection and uses Bayesian parameter estimation to investigate relationships between model parameters not constrained by experiments" *PLoS Comput Biol*
31. Kuhl, Pauschinger, Seeberg et al. (2005) "Viral persistence in the myocardium is associated with progressive cardiac dysfunction" *Circulation*
32. Zapatka, Borozan, Brewer et al. (2020) "The landscape of viral associations in human cancers" *Nat Genet*
33. Griffiths, Shah, Shao et al. (2024) "PubMed: 39536108] This article finds RNAseq evidence for undiagnosed viral heart infections in 189 of 979 human heart samples and reports that infected hearts respond to" *Sci Adv*
34. Mantri, Hinchman, Mckellar et al. "De Vlaminck I: Spatiotemporal transcriptomics reveals pathogenesis of viral myocarditis" *Nat Cardiovasc Res*
35. Sego, Aponte-Serrano, Gianlupi et al. (2021) "Generation of multicellular spatiotemporal models of population dynamics from ordinary differential equations, with applications in viral infection" *BMC Biol*
36. Sego, Mochan, Ermentrout et al. (2022) "A multiscale multicellular spatiotemporal model of local influenza infection and immune response" *J Theor Biol*
37. Ferrari Gianlupi, Mapder, Sego et al. (2022) "Multiscale Model of Antiviral Timing, Potency, and Heterogeneity Effects on an Epithelial Tissue Patch Infected by SARS-CoV-2. Viruses"
38. Bruurs, Muller, Schipper et al. (2023) "Antiviral responses are shaped by heterogeneity in viral replication dynamics" *Nat Microbiol*
39. Aponte-Serrano, Weaver, Sego et al. (2021) "Multicellular spatial model of RNA virus replication and interferon responses reveals factors controlling plaque growth dynamics" *PLoS Comput Biol*
40. Kitagawa, Kim, Iwamoto et al. (2024) "Multiscale modeling of HBV infection integrating intra-and intercellular viral propagation to analyze extracellular viral markers" *PLoS Comput Biol*
41. Singer, Ambrose, Danino et al. (2021) "Quantitative measurements of early alphaviral replication dynamics in single cells reveals the basis for superinfection exclusion" *Cell Syst*
42. Boersma, Rabouw, Bruurs et al. (2020) "Translation and Replication Dynamics of Single RNA Viruses" *Cell*
43. Arkin, Ross, Mcadams (1998) "Stochastic kinetic analysis of developmental pathway bifurcation in phage lambda-infected Escherichia coli cells" *Genetics*
44. Mcadams, Shapiro (1995) "Circuit simulation of genetic networks" *Science*
45. King, Berezin, Peccoud (2024) "Stochastic model of vesicular stomatitis virus replication reveals mutational effects on virion production" *PLoS Comput Biol*
46. Bullock, Moreno-Martinez, Miller-Jensen (2022) "A transcriptional cycling model recapitulates chromatin-dependent features of noisy inducible transcription" *PLoS Comput Biol*
47. Hartwell, Hopfield, Leibler et al. (1999) "From molecular to modular cell biology" *Nature*
48. Artcibasova, Wang, Anchisi et al. (2023) "biochemical interactions between influenza A capsid protein and dynein-myosin motors with a biophysical model of mechanical forces exerted on a capsid during uncoating" *Cell Rep*
49. Staring, Raaben, Brummelkamp (2018) "Viral escape from endosomes and host detection at a glance" *J Cell Sci*
50. Hubel, Urban, Bergant et al. (2019) "A protein-interaction network of interferon-stimulated genes extends the innate immune system landscape" *Nat Immunol*
51. Korwek, Czerkies, Jaruszewicz-Blonska et al. (1173) "PubMed: 38085817] This study models the host-cell network response to non-self RNA during viral infection and proposes a mechanism for switching cells from responders to producers of interferon β" *Sci Signal*
52. Maier, Aguilera, Sahle et al. (2022) "Stochastic dynamics of Type-I interferon responses"
53. Klein, Kallenberger, Roth et al. (2022) "Temporal control of the integrated stress response by a stochastic molecular switch" *Sci Adv*
54. Reffsin, Miller, Ayyanathan et al. (2023) "Single cell susceptibility to SARS-CoV-2 infection is driven by variable cell states"
55. Zanini, Pu, Bekerman et al. (2018) "Single-cell transcriptional dynamics of flavivirus infection"
56. Johnson, Bergman, Rocha et al. (2025) "Human interpretable grammar encodes multicellular systems biology models to democratize virtual cell laboratories" *Cell*
57. Kojima, Mii, Hayashi et al. (2024) "Single-cell colocalization analysis using a deep generative model" *Cell Syst*
58. Dolezal, Wolk, Hieromnimon et al. (2023) "Deep learning generates synthetic cancer histology for explainability and education" *NPJ Precis Oncol*
59. Haas, Mcgregor, Bouhaddou et al. (2023) "Proteomic and genetic analyses of influenza A viruses identify pan-viral host targets" *Nat Commun*
60. Ludwig, Thurm, Morgens et al. (2023) "High-throughput discovery and characterization of viral transcriptional effectors in human cells" *Cell Syst*
61. Hiatt, Hultquist, Mcgregor et al. (2022) "A functional map of HIV-host interactions in primary human T cells"
62. Hein, Weissman (2022) "Functional single-cell genomics of human cytomegalovirus infection" *Nat Biotechnol*
63. Ke, Martinez, Smith et al. (2022) "Daily longitudinal sampling of SARS-CoV-2 infection reveals substantial heterogeneity in infectiousness" *Nat Microbiol*
64. Bush, Ray, Alvarez et al. (2017) "PLATE-Seq for genome-wide regulatory network analysis of high-throughput screens" *Nat Commun*
65. Heymann, Platts-Mills, Woodfolk et al. (2020) "Understanding the asthmatic response to an experimental rhinovirus infection: Exploring the effects of blocking IgE" *J Allergy Clin Immunol*
66. Zitzmann, Ke, Ribeiro (2024) "Perelson AS: How robust are estimates of key parameters in standard viral dynamic models?" *PLoS Comput Biol*
67. Chelliah, Juty, Ajmera et al. (2015) "BioModels: ten-year anniversary" *Nucleic Acids Res*
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# One confirmed and one potential human case of influenza A(H5N1) detected through an expanded subtyping protocol
Grant Higerd-Rusli, Abraar Karan, Seth Hoffman, Ingrid Morante, Chunhong Huang, Malaya Sahoo, Matthew Hernandez, Benjamin Pinsky
## Abstract
Current U.S. surveillance for highly pathogenic avian influenza A(H5N1) in humans prioritizes individuals with known animal exposures, potentially missing community-acquired infections. To address this gap, we implemented universal H5 subtyping of all influenza A-positive respiratory samples collected within our hospital system, regardless of patient exposure history. Between August 2024 and April 2025, we subtyped 4,488 influenza A-positive samples and identified two cases positive for H5 RNA in Alameda County, California, USA. The first case was a 14-month-old girl with mild respiratory symptoms and no H5N1 exposure risks; sequencing of the sample revealed an H5 gene closely related to clade 2.3.4.4b, genotype B3.13 viruses circulating in U.S. dairies. The second case was a 79-year-old male, also with no known exposures, whose sample reproducibly tested positive with a high cycle threshold value but could not be confirmed by public health laboratories. Both patients had evidence of co-infection with other common respiratory viruses. These findings, while requiring cautious interpreta tion due to low virus levels and the presence of potential confounding factors, highlight limitations in exposure-based testing and demonstrate the potential for cryptic H5N1 circulation. This report underscores that broader, geographically targeted surveillance may be a critical tool for early detection of potential community transmission of pandemic-capable pathogens.
H ighly pathogenic avian influenza A H5N1 has spread globally in wild birds and led to outbreaks in increasingly diverse mammalian species (1). Since March 2024, an outbreak of H5N1 clade 2.3.4.4b has spread among dairy cows across the United States (1). Given that there is little to no pre-existing immunity in the human population, acquisition of efficient human-to-human transmissibility by H5N1 could lead to rapid global dissemination, resulting in substantial morbidity and mortality (2,3). As of August 2025, 70 confirmed human cases have been detected in the United States, 65 of which have reported high-risk exposures to infected dairy cows or poultry and two of which reported exposure to backyard flocks, wild birds, or other mammals (4). There have been three reported infections in individuals without known exposures: one in Missouri, one in San Francisco, California, and another in British Columbia, Canada (1,5,6). There has been one fatal case in Louisiana (1).
Current influenza surveillance efforts in the United States include "routine surveil lance, " where a finite subset of human influenza A-positive samples undergo additional testing (7). This may include H5 testing but only for samples without an identifiable seasonal influenza A subtype (8). As of 18 August 2025, routine surveillance demonstra ted an H5 case positivity rate of ~0.003% (6/204,843) (4). Targeted subtyping for H5 is currently limited by strict testing criteria that prioritize individuals with known animal exposure (9,10). Consequently, human cases, particularly those arising from potential human-to-human spread, may be missed. To evaluate whether cases may be going undiagnosed, we implemented universal H5 subtype screening of all influenza A-positive samples within our hospital system, regardless of patient exposure history. Here we report that this expanded screening identified two cases of H5N1 in individuals with no known H5N1 exposure risk in Alameda County, CA.
## MATERIALS AND METHODS
## H5 subtyping protocol
Nasopharyngeal samples that tested positive for influenza A, collected within the Stanford Health Care system, were subtyped for influenza A H5 using a previously described, multiplex, dual-target H5 RT-qPCR that includes primer probes for pan-influenza A (matrix) and an internal control (human RNaseP) (11). This assay was previously validated using synthesized nucleic acids and genomic RNA from cultured avian and human influenza A virus isolates. Using genomic RNA from Kilbourne F181, A/duck/ Singapore/645/1997(H5N3) (BEI Resources NR-9682), the assay demonstrated a 95% lower limit of detection of 0.6 copies/µL for the H5 target and a 95% lower limit of detection of less than 0.5 copies per µL for the pan-influenza A matrix target. Given that the pan-influenza A target appeared more analytically sensitive than the H5 target, a pan-influenza A cycle threshold (C T ) value of less than 40 cycles was required to interpret the H5 result. Samples that were positive for H5 were re-extracted and re-tested to confirm the result.
## Sequencing
Partial sequencing of the hemagglutinin (HA) gene was performed on the resid ual total nucleic acid eluates from Case 1. Four reverse transcription PCR (RT-PCR) reactions were performed on each eluate using the following H5 primer pairs: H5HA-205-227-For(2010) + FluA_H5_v4_2R (~1,070 base pairs [bp]), H5HA-205-227-For(2014) + FluA_H5_v4_2R (~1,070 bp), FluA_H5_v4_2F + FluA_H5_v4_1R (~584 bp), and H5HA-205-227-For(2010) + FluA_H5_v4_1R (~1,510 bp). These primers were previously published (11,12). The primer sequences and final reaction concentrations are provided in Table 1.
RT-PCR was performed on an Applied Biosystems Veriti thermal cycler using the Invitrogen Superscript III Platinum One-Step qRT-PCR kit (Thermo Fisher Scientific, Waltham, MA). Each 25 µL reaction contained 12.5 µL of 2× buffer, 5 µL nuclease-free water, 0.5 µL of enzyme mix, 1 µL forward primer, 1 µL reverse primer, and 5 µL of nucleic acids. Cycling conditions were as follows: 52°C for 60 min, 94°C for 2 min, then 45 cycles of 94°C for 15 s, 55°C for 30 s, and 68°C for 2 min; finally, hold for 10 min at 68°C.
The amplification products were individually processed for sequencing using enzymatic fragmentation and NEBNext Ultra II reagents (New England Biolabs, Ipswich, MA), as previously described (13). Libraries were sequenced on an Illumina MiSeq using single-end 150-cycle sequencing using the MiSeq Reagent Kit (version 3).
Reads were aligned to reference sequence EPI_ISL_19531296 from the Global Initiative on Sharing All Influenza Data (GISAID) using Burrows-Wheeler Aligner (version 0.7.12). Reads with a mapping quality score of <10 were discarded. Individual BAM files were generated using SAMtools (version 1.12). The BAM files from each sequencing library representing the eight amplicons (two eluates amplified with four primer pairs) were then merged, and the consensus sequence was generated using Genome Analysis ToolKit (version 4.2.0.0). Any position with <2 reads was labeled as N. Only the region with a coverage of >500× encompassing positions 1,121-1,701 was submitted to GISAID (accession no. EPI3684158, isolate ID: EPI_ISL_19597300) and GenBank (PQ724474.1) per the Centers for Disease Control and Prevention (CDC) (14). This sequence is named A/ California/192/2024. To generate a phylogenetic tree, H5 gene sequences from human cases in North America were identified from the GISAID database using the following search criteria: type, A; H, 5; N, any; host, human; location, North America; collection dates, 1 January 2024 to 30 April 2025. A total of 63 sequences were obtained, including this case, and were aligned using Clustal X 2.1. All sequences were trimmed to match the boundaries of A/California/192/2024. We excluded sequences that did not cover the complete 581-base region sequenced in this case, as well as duplicate sequences from serial passages of the same isolates and sequences from cases lacking clear documentation of the type of animal exposure. Multiple sequence alignment was performed on the remaining 46 sequences using Clustal X 2.1 with the option "ignore gaps. " A phylogenetic tree using the neighbor-joining method was generated in Clustal X 2.1 and then rendered in Mega 11 with options "root at midpoint" and "arrange for balanced shape. "
## RESULTS
A total of 4,562 influenza A-positive nasopharyngeal swab samples collected within the Stanford Health Care system between 7 August 2024 and 12 April 2025 were reflexed to H5 subtyping. Of these, the pan-influenza A target was detected with a C T value of less than 40 cycles in 98.4% (4,488/4,562) of the samples, with a median C T value of 21.7 cycles (interquartile range 18.2-26.7). Of the remainder, there were 25 samples in which the pan-influenza A target C T value was detected but exceeded 40 cycles, 42 samples in which the pan-influenza A target was not detected and the internal control was detected, and 7 samples in which both the pan-influenza A target and internal control were not detected. H5 was detected in two samples, resulting in a positivity rate of 0.04% (2/4,488).
Case 1: 14-month-old girl A 14-month-old girl presented with her parent to an urgent care facility for evaluation of fever, congestion, and behaving "fussier than usual. " The patient had not consumed unpasteurized milk and did not have exposures to dairy farms or to sick animals, including cows, birds, or domestic pets. The patient had exposure to sick children at daycare, as well as to family members with similar symptoms.
The patient had a heart rate of 114 beats/min, respirations of 28 breaths/min, oxygen saturation of 98% (room air), and a rectal temperature of 36.8°C. The child was noted to be well appearing and not in distress. Conjunctiva and sclera were clear bilaterally. No rhinorrhea was noted, and the oropharynx was normal. Both tympanic membranes were erythematous with effusions bilaterally, consistent with acute otitis media, originally diagnosed in the prior month. The respiratory examination was unremarkable. The patient was discharged home on a 7-day course of oral amoxicillin (90 mg/kg/day).
A throat swab was negative for Group A Streptococcus by PCR. However, a nasophar yngeal swab was positive for influenza A using a 4-plex (Influenza A/B/RSV/SARS-CoV-2) respiratory virus RT-PCR (Cepheid, Sunnyvale, CA). The patient was started on a 5-day course of oseltamivir the following day. This patient's sample was positive for H5 with a C T value of 34.0; pan-influenza A was also positive with a C T value of 32.8. The sample was re-extracted and re-tested, and the H5 (C T = 32.7) and pan-influenza A (C T = 32.5) signals were reproducible. Further testing at the CADPH using the CDC Influenza A/H5 Subtyping Kit detected both the H5a and H5b targets (15). In-house partial sequencing of the HA gene revealed a sequence closely related to the H5 gene present in the clade 2.3.4.4b, genotype B3.13 influenza A(H5N1) viruses from California human cases (Fig. 1, GenBank PQ724474.1).
Retrospective testing using the BioFire Respiratory Panel 2.1 (bioMérieux, Marcyl'Étoile, France) revealed that the original sample was equivocal for influenza A, indicat ing that one of two pan-influenza A assays was positive, and the H1, H3, and H1-2009 assays were negative. This pattern is typically observed with low levels of virus (16). The respiratory panel was also positive for adenovirus and rhinovirus/enterovirus. The child was re-evaluated 3 days after initial presentation and was well appearing with normal vital signs. Nasopharyngeal swabs collected from two of the patients' family members were positive for adenovirus and rhinovirus and negative for influenza A.
## Case 2: 79-year-old male
A 79-year-old male with a history of hypertension, hyperlipidemia, type 2 diabetes mellitus, recurrent strokes, and presented to an urgent care facility for evaluation of 1 week of cough and shortness of breath. The patient lives in a singlefamily home with a caregiver and had no known exposures. The patient was afebrile, with oxygen saturation of 96% (room air). Conjunctiva, sclera, as well as breath sounds were clear bilaterally. Chest X-ray showed bilateral lung opacities and peribronchial wall thickening. A nasopharyngeal swab was positive for influenza A using the 4-plex RT-PCR described above (Cepheid). The patient was prescribed oral cefpodoxime (200 mg twice a day for 7 days) and doxycycline (100 mg twice a day for 7 days) for communityacquired pneumonia and discharged home. This patient's sample was positive for H5 with a C T value of 40.1; pan-influenza A was also positive with a C T value of 38.1. The sample was re-extracted, and both the original and re-extracted eluates were re-tested. Both the H5 (re-extracted eluate, C T = 37.3; original eluate, C T = 35.8) and pan-influenza A (re-extracted eluate, C T = 38.4; original eluate, C T = 36.0) signals were reproducible. Further testing at the CADPH and CDC was negative for both pan-influenza A and the H5 subtype. There was insufficient residual sample or eluate for sequencing.
One day after discharge, the patient re-presented with a blood pressure of 70/40. His white blood cell count was elevated (18.2 K/µL), though he remained afebrile. An expectorated sputum was positive for Escherichia coli and human rhinovirus/enterovirus, but negative for influenza A, as well as 23 other pathogens using the BioFire Pneumonia Panel (bioMérieux). The patient was admitted and treated with intravenous fluids, ceftriaxone (intravenous, 2 g daily for 3 days), azithromycin (intravenous, 500 mg daily for 3 days), and oseltamivir (oral, 75 mg twice daily for 5 days). The patient's condition improved, and he was discharged home 2 days after admission with a prescription for cefpodoxime (oral, 200 mg twice daily for 3 days).
## DISCUSSION
The lack of widespread H5N1 subtyping during the 2024 outbreak left open the possibil ity that animal-human spillovers, or human-to-human transmission events, were being missed by the public health surveillance system. However, the positivity rate of this universal H5 subtyping strategy in the San Francisco Bay Area during 2024-2025 was just 0.04%, identifying only two cases. These results confirm the lack of widespread H5N1 infection in low-risk individuals served by our healthcare system over this period. Nevertheless, detection of these outliers reveals possible blind spots in H5 surveillance which may lead to undetected outbreaks if further mammalian adaptation occurs (15).
These cases bear some similarities to other reported H5 cases without high-risk exposures; in particular, both our Case 1 and another case in San Francisco occurred in young children with mild symptoms and were found to contain virus related to the virus B3.13 genotype, which has circulated in U.S. dairy cows (6). In contrast, two severe cases were caused by genotype D1.1: one in British Columbia, Canada, and another in Louisi ana (1). However, it remains unclear whether the cases reported here reflect true infections. According to current CDC case definitions for novel influenza A infections, Case 1 meets criteria for a "confirmed" case, while Case 2 does not strictly meet criteria for the "confirmed, " "probable, " or "suspect" definitions (17). Neither of the patients exhibited symptoms typically associated with occupational exposure in the recent dairy-associated outbreak, such as conjunctivitis, and both experienced relatively mild symptoms with rapid recovery. Furthermore, neither patient had exposure to known human cases of H5N1 or sick animals or birds. While the RT-PCR results were reproducible and there was no laboratory evidence of contamination, the high cycle threshold values indicate very low levels of viral nucleic acids. This low-level detection is reflected in the inability of external laboratories to confirm the case in the 79-year-old male, which may have been the result of differences in assay sensitivity or RNA degradation (for example, due to additional freeze-thaws). Both cases were also found to be positive for other respiratory pathogens that could explain their clinical presentations. Studies have demonstrated that a substantial portion of the commercial milk supply contains H5 nucleic acids (18); therefore, we hypothesize that these patients may have consumed milk containing H5 RNA, which was detected in their nasopharynx at the time of sampling.
The strengths and weaknesses of a universal surveillance strategy merit careful consideration. The financial and logistical costs of increased testing must be weighed against the consequences of missing potential cryptic transmission and the benefit of early detection to allow intervention before an outbreak develops into an epidemic or pandemic. Given the findings described here, it may be beneficial to expand H5 subtyping beyond current testing criteria, with a focus on geographic areas with higher risk of zoonotic spillover. Notably, the positive cases we identified resided in an area that is adjacent to counties with high-density dairy farming operations. Thus, expan ded subtyping may prove beneficial if targeted toward influenza A-positive samples collected from patients residing in zip codes within or more proximal to higher-risk regions (for example, California's Central Valley). Innovations, including testing of pooled samples, may increase testing capacity while decreasing costs associated with additional surveillance.
In addition to expanded screening of clinical samples, implementing complemen tary strategies, including systematic testing of the commercial milk supply, targeted serological surveys, wastewater surveillance, and genomic monitoring for mutations of concern, may provide comprehensive, critical early warning for potential pandemic H5 threats. These approaches would help to shift our posture from pandemic response to pandemic prevention through early detection and targeted control measures.
## References
1. Krammer, Hermann, Rasmussen (2025) "Highly pathogenic avian influenza H5N1: history, current situation, and outlook" *J Virol*
2. Garretson, Liu, Li et al. (2025) "Immune history shapes human antibody responses to H5N1 influenza viruses" *Nat Med*
3. Cdc (2024) "Avian Influenza Bird Flu"
4. Cdc (2025) "H5 Bird Flu: current situation. Avian Influenza Bird Flu"
5. Cdc (2025) "Avian Influenza Bird Flu"
6. Tobolowsky, Morris, Castro et al. (2024) "Highly pathogenic avian influenza A(H5N1) virus infection in a child with no known exposure" *MMWR Morb Mortal Wkly Rep*
7. "CDC. 2025. U.S. influenza surveillance: purpose and methods. FluView"
8. Pinsky, Bradley (2024) "Opportunities and challenges for the U.S. laboratory response to highly pathogenic avian influenza A(H5N1)" *J Clin Virol*
9. Cdc (2025) "Interim guidance on specimen collection and testing for patients with suspected infection with novel influenza a viruses associated with severe disease or with the potential to cause severe disease in humans"
10. Cdc (2024) "Highly pathogenic avian influenza A(H5N1) virus in animals: interim recommendations for prevention, monitoring, and public health investigations. Avian Influenza Bird Flu"
11. Sahoo, Morante, Huang et al. (2024) "Multiplex dual-target reverse transcription PCR for subtyping avian Influenza A(H5) virus" *Emerg Infect Dis*
12. (2021) "Information for molecular diagnosis of influenza virus"
13. Wang, Miller, Verghese et al. (2021) "Multiplex SARS-CoV-2 genotyping reverse transcriptase PCR for population-level variant screening and epidemiologic surveillance" *J Clin Microbiol*
14. Cdc (2025) "Technical update: summary analysis of the genetic sequence of a highly pathogenic avian Influenza A(H5N1) virus identified in a child in California"
15. Zhu, Harriman, Liu et al. (2024) "Human cases of highly pathogenic avian Influenza A" *MMWR Morb Mortal Wkly Rep*
16. Berry, Zhen, Smith et al. (2022) "Multicenter evaluation of the BioFire respiratory panel 2.1 (RP2.1) for detection of SARS-CoV-2 in nasopharyngeal swab samples" *J Clin Microbiol*
17. Cdc (2024) "Novel Influenza A virus infections 2024 case definition"
18. Spackman, Jones, Mccoig et al. (2024) "Characterization of highly pathogenic avian influenza virus in retail dairy products in the US" *J Virol*
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# A new IRMA module for analyzing whole-genome sequences from human metapneumovirus
Emily Bendall, Adam Lauring, Adam 75d30122c14944, Lauring
## Abstract
The large amount of genetic diversity in human metapneumovirus makes reference-based alignments difficult. We created a new module for the Iterative Refinement Meta-Assembler (IRMA) that performs alignment and consensus sequence generation without requiring subtyping and can handle duplications in the glycoprotein. This module increases the feasibility of genomic surveillance.
H uman metapneumovirus (HMPV) causes a significant number of respiratory infections each year, especially in young children (1). HMPV is genetically diverse with two antigenically distinct lineages (A and B) that cocirculate (2,3). These two lineages have each split into two sublineages (A1, A2, B1, and B2), and A2 has further split into A2.1 and A2.2 (4). Most of the genetic diversity among subtypes is in G, the glycoprotein (5,6). G is also highly variable within subtypes, with strains containing either a 111 or 180 nucleotide duplication currently circulating within A2.2 (7,8).
There has been limited whole-genome sequencing of HMPV, despite potential public health benefits of genomic surveillance. One of the barriers to whole-genome sequenc ing is efficiently analyzing the sequence data due to the large amount of genetic diversity. Current library preparation methods do not require subtyping (9)(10)(11). However, the genetic diversity of HMPV hinders the ability to use a single reference to accurately assemble genomes for all samples.
To address this problem, we have developed an HMPV IRMA module. IRMA was developed for assembling highly variable RNA viruses (12). IRMA is reference-based, but it iteratively gathers reads and edits the reference genome, minimizing the effects of distance from the initial reference. It also allows for a different reference genome for each subtype, making prior subtyping unnecessary. To create the reference, we downloaded all whole genomes available on GenBank (accessed Oct. 18, 2024, "Metapneumovirus hominis"). Sequences were aligned using MAFFT v7 (13), and IQ-TREE 2 ( 14) was used to create a phylogeny. We used previously typed samples and the phylogeny to assign samples to A1, A2, A2.1, A2.2, A2.2 +111 nt duplication, A2.2 +180 nt duplication, B1, or B2 (Table 1). For each sublineage, we created a plurality consensus sequence using EMBL consensus generator (15) and a hidden Markov model using IRMA.
To test the IRMA pipeline, we sequenced 181 samples from the Investigating Respiratory Viruses in the Acutely Ill (IVY) study (November 2024-April 2025) (16,17) and from the Household Influenza Vaccine Effectiveness (HIVE ) study (2011-2022) (18). Nasal swabs were sequenced using the Respiratory Virus Oligos Panel v2 on an Illumina NextSeq 2000 (2 × 300, P1 chemistry).
The consensus sequences generated by IRMA were complete or nearly complete genomes (Fig. 1A). A2.1, A2.2, B1, and B2 lineages were present (19). Lineages were consistent with previous qPCR subtyping (A or B) (20). We were able to detect the 111-nt (42 samples) and 180-nt (11 samples) insertions in a subset of A2.2 samples, showing that the IRMA module can handle samples with or without a duplication. No systematic issues were detected in the alignments (Fig. 1B). The IRMA module is suitable for Illumina and Nanopore sequencing. For Nanopore sequencing, the config file would need to be altered (see Flu module in IRMA for example). For Illumina sequencing, read lengths shorter than 300 bp compromise accurate detection of duplications.
## AUTHOR AFFILIATIONS
## References
1. Akingbola, Adegbesan, Tundealao et al. (2025) "Human metapneumovirus: an emerging respiratory pathogen and the urgent need for improved diagnostics, surveillance, and vaccine development" *Infect Dis (Lond)*
2. Van Den Hoogen, Herfst, Sprong et al. (2004) "Antigenic and genetic variability of human metapneumoviruses" *Emerg Infect Dis*
3. Boivin, Mackay, Sloots et al. (2004) "Global genetic diversity of human metapneumovirus fusion gene" *Emerg Infect Dis*
4. Huck, Scharf, Neumann-Haefelin et al. (2006) "Novel human metapneumovirus sublineage" *Emerg Infect Dis*
5. Papenburg, Carbonneau, Isabel et al. (2013) "Genetic diversity and molecular evolution of the major human metapneumovirus surface glycoproteins over a decade" *J Clin Virol*
6. Ishiguro, Ebihara, Endo et al. (2004) "High genetic diversity of the attachment (G) protein of human metapneumovirus" *J Clin Microbiol*
7. Jcm (2004)
8. Piñana, Vila, Gimferrer et al. (2017) "Novel human metapneumovirus with a 180-nucleotide duplica tion in the G gene" *Future Microbiol*
9. Saikusa, Nao, Kawakami et al. (2017) "A novel 111-nucleotide duplication in the G gene of human metapneumovirus" *Microbiol Immunol*
10. Illumina (2020) "Detection and characterization of respiratory viruses, including SARS-CoV-2, using illumina RNA prep with enrichment"
11. Groen, Van Nieuwkoop, Bestebroer et al. (2021) "Whole genome sequencing of human metapneu moviruses from clinical specimens using MinION nanopore technology" *Virus Res*
12. Tulloch, Kok, Carter et al. (2021) "An amplicon-based approach for the whole-genome sequencing of human metapneumovi rus" *Viruses*
13. Shepard, Meno, Bahl et al. (2016) "Viral deep sequencing needs an adaptive approach: IRMA, the iterative refinement meta-assembler" *BMC Genomics*
14. Katoh, Standley (2013) "MAFFT multiple sequence alignment software version 7: improvements in performance and usability" *Mol Biol Evol*
15. Minh, Schmidt, Chernomor et al. (2020) "IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era" *Mol Biol Evol*
16. Madeira, Madhusoodanan, Lee et al. (2024) "The EMBL-EBI job dispatcher sequence analysis tools framework in 2024" *Nucleic Acids Res*
17. Surie, Yuengling, Decuir et al. (2024) "Severity of respiratory syncytial virus vs COVID-19 and influenza among hospital ized US adults" *JAMA Netw Open*
18. Us (2024) "Investigating respiratory viruses in the acutely Ill (IVY) network"
19. Bassiouni, Foster-Tucker, Callear et al. (2025) "A comparative profile of the burden of human metapneumovirus, respiratory syncytial virus, and influenza in the HIVE cohort, 2010-2022" *J Infect Dis*
20. Aksamentov, Roemer, Hodcroft et al. (2021) "Nextclade: clade assignment, mutation calling and quality control for viral genomes" *JOSS*
21. Sugimoto, Kawase, Suwa et al. (2023) "Develop ment of a duplex real-time RT-PCR assay for the detection and identification of two subgroups of human metapneumovirus in a single tube" *J Virol Methods*
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# Genome sequence of fowlpox virus from a field outbreak in Bangladesh
Anandha Mozumder, Shamima Akter, Roni Mia, S Nazmul Hasan, Anupam Das, Jebin Tasmin, A Hafizur, Rahman Mondal, M Rahman, Mohammad Imtiaj, Uddin Bhuiyan, Sharmin Akter, Sukumar Saha, Md Golzar Hossain, Md Hossain
## Abstract
We report the complete genome sequence of a fowlpox virus (FPV) isolate from a field outbreak in Bangladesh. This genomic data will aid in comparative analyses with currently available vaccine strains and support future efforts for effective prevention and control of FPV in poultry populations. KEYWORDS fowlpox virus, genome sequencing, Bangladesh F owlpox virus (FPV), a member of the Poxviridae family and Avipoxvirus genus, primarily infects chickens, pigeons, and turkeys. It causes significant economic losses in the poultry industry worldwide, including Bangladesh (1). FPV infections manifest in two clinical forms: the cutaneous (dry) form, characterized by lesions on non-feathered areas such as the legs, head, and body, and the diphtheritic (wet) form, involving lesions in the mucous membranes of the mouth and respiratory tract (2). The FPV genome consists of double-stranded DNA ranging from 260 to 309 kb pairs, making it larger than other known chordopoxvirus genomes (3). FPV has been reported in Bangladesh despite vaccination efforts. Several FPV vaccines are commercially available in the country, including Bangla Fowlpox Vac, Henpox Vet, and fowlpox vaccine. However, no complete genome sequence of FPV from field cases in Bangladesh has been available.Nodular skin lesions were aseptically collected using sterile scissors and forceps from a live commercial layer chicken flock in Gazipur District, Bangladesh, on 18 March 2025. Viral inoculum was prepared following a previously mentioned protocol (4). A 0.2 mL viral inoculum was inoculated onto the chorioallantoic membrane of 10-day-old embryonated eggs using a sterile 1 mL tuberculin syringe with a 1/2 inch needle. The shell openings and air sacs were sealed with melted wax, and the eggs were incubated horizontally at 37°C for 5-6 days. Viral genomic DNA was extracted using the TIANamp Virus DNA/RNA Kit (Tiangen, China). Shotgun whole-genome sequencing libraries were constructed using iNextEra, a modified Illumina library preparation protocol adapted from Jones et al. ( 5) with adjustments to input DNA, bead-linked transposase volume, and PCR cycles to optimize yield, diversity, and genome coverage (5). DNA tagmentation was performed with Illumina bead-linked transposomes (Illumina DNA Library Prep, Illumina, Inc.), and sequencing was conducted on the Illumina NovaSeq X Plus platform (2 × 150 bp; Novogene, USA). Raw paired-end reads were quality-checked with FastQC v.0.11.9 and quality-filtered with Trimmomatic v.0.39, which retained reads longer than 50 bp. The host DNA was depleted by aligning quality-filtered reads to the Gallus gallus reference genome (GCA_000002315.5, GRCg6a) using BBMap (6). The remaining reads were aligned to the FPV genome (GenBank accession number NC_002188.1) using BWA-MEM v.0.7.17 (7). Sorting and indexing were performed with SAMtools v.1.12 (8), and a high-confidence consensus genome was generated using BCFtools v.1.12 (9) and VCFtools v.4.1 (10). Genome annotation was performed using Prokka v.1.14.6, and the December 2025 Volume 14 Issue 12 10.
terminal ends were determined by comparing with the previously reported complete genomes (11,12). All software was used with default parameters.
Host DNA removal was effective, with 97.04% of reads aligning to the chicken reference genome and 2.96% retained as unmapped for downstream analysis. Subsequent alignment of host-filtered reads to the FPV reference genome produced a complete consensus sequence. A total of 25,945 reads mapped to the viral genome, covering 287,841 bases (99.76% of the reference sequence) with an average depth of ~11.9× . The mapped reads exhibited high base quality (mean base quality score 39.3) and mapping confidence (mean mapping quality 54.9), confirming robust consensus assembly. BLAST analysis revealed 99.70% nucleotide identity with previously reported FPV strains, including MH719203.1 (strain: FWPV-SD15-670.1, USA). The annotated complete genome contains 263 open reading frames, and identical inverted terminal repeats of 9.24 kbp were found at the 5′ and 3′ terminal regions, consistent with previous findings (11,12). This study presents the complete genome sequence of an FPV isolate from Bangladesh, providing essential genomic data that may facilitate future vaccine development and aid in the control of FPV outbreaks in poultry populations.
## References
1. Rahman, Islam, Islam et al. (2019) "Isolation and molecular detection of Avipoxvirus from field outbreaks in Mymensingh" *Bangladesh. J Adv Vet Anim Res*
2. Asif, 'rourke, Legione et al. (2021) "Whole-genome based strain identification of fowlpox virus directly from cutaneous tissue and propagated virus" *PLoS One*
3. Willis, Trautman, Cox et al. (2022) "Genome sequence of fowlpox virus-integrated reticuloendotheliosis virus from a Rio Grande wild Turkey (Meleagris gallopavo intermedia)" *Microbiol Resour Announc*
4. Hossain, Pathan, Hasan et al. (2024) "Molecular detection and genetic characterization of avian leukosis virus from field outbreaks in Bangladesh" *Vet Med Sci*
5. Jones, Stanley, Ferguson et al. (2023) "Cost-conscious generation of multiplexed short-read DNA libraries for whole-genome sequencing" *PLoS One*
6. Bushnell (2014) "BBMap: a fast, accurate, splice-aware aligner"
7. Li (2013) "Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM" *ArXiv*
8. Heng, Handsaker, Wysoker et al. (2009) "1000 Genome Project Data Processing Subgroup"
9. Garrison, Marth (2012) "Haplotype-based variant detection from short-read sequencing"
10. Danecek, Bonfield, Liddle et al. (2021) "Twelve years of SAMtools and BCFtools. Gigascience 10:giab008"
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# Structure and function of the nairovirus cap-snatching endonuclease
Wenhua Kuang, Zhenhua Tian, Gan Zhang, Fan Wu, Jinyue Li, Jingjing Tang, Huan Zhang, Xin Yue Zhuo, Zhihong Hu, Manli Wang, Haiyan Zhao, Zengqin Deng
## Abstract
Nairo viruses include se v eral human pathogens such as Crimean-Congo hemorrhagic fe v er virus (CCHFV) and Kasok ero vir us (KA S V). The capsnatching endonuclease (EN) domain of the viral polymerase is essential for transcription and represents a promising antiviral target. Ho w e v er, the str uct ural and functional mechanisms of nairovir us ENs remain poorly understood. Here, we describe biochemical and str uct ural st udies of the ENs from CCHFV and KA S V. Biochemical assa y s demonstrate that the RNA endonuclease activity of both ENs is activated by manganese ions and exhibits a preference for uridine-rich RNA substrates. This activity is inhibited by three metal-chelating inhibitors (DPBA, L-742,001, and BXA), with BXA displaying the highest binding affinity and inhibitory potency. We further determine nine crystal str uct ures of CCHFV and KA S V ENs in apo, metal ion-bound, and inhibitor-bound states. Comparative str uct ural analysis uncovers a t wo-met al-ion binding mode unique to nairovirus ENs, in which conserved residues coordinate two manganese ions via bridging water molecules. In the inhibitor-bound str uct ures of KA S V EN, BXA f orms additional stabilizing interactions with the enzyme, e xplaining its superior inhibitory effect. Functional assa y s further confirm that the t wo-met al-ion mechanism is critical for viral transcription. These findings provide a str uct ural foundation for the rational design of antivirals against CCHFV and related pathogens.
## Introduction
Nairoviruses are a large group of tick-borne bunyaviruses, including several highly pathogenic agents infecting humans and animals. Among them, the Crimean-Congo hemorrhagic fever virus (CCHFV) is the most important human pathogen. CCHFV is endemic in over 30 countries across Asia, Europe, and Africa. Infection with CCHFV can cause serious diseases such as acute fever, hemorrhagic symptoms, and multi-organ failure, with a case fatality rate of up to 40% [ 1 , 2 ]. Due to its high pathogenicity, and the lack of approved vaccines and antiviral drugs, CCHFV is classified as a Biosafety Level 4 (BSL-4) pathogen and has been listed by the World Health Organization (WHO) as a Priority Pathogen requiring urgent research to develop countermeasures [ 3 , 4 ]. Infections with other members of nairoviruses, Kasokero virus (KASV), Dugbe virus (DUGV), and Erve virus, can also cause symptoms in humans, including headache, rash, diarrhea, thrombocytopenia, and neurological disorders [ 5 -7 ]. In livestock, infection of Nairobi sheep disease virus (NSDV) causes hemorrhagic gastroenteritis. In recent years, an increasing number of emerging nairoviruses have been identified [ 8 -10 ], raising concerns about their potential biosecurity risks to public health.
Segmented negative-strand RNA viruses (sNSVs), including bunyaviruses and orthomyxoviruses, employ a cap-snatching mechanism to initiate transcription of their viral genomes. This process is mediated by the N-terminal endonuclease (EN) domain of RNA-dependent RNA polymerase (RdRP; also known as L protein in bunyaviruses), which cleaves hostderived capped RNA fragments to serve as primers for viral mRNA synthesis [ 11 , 12 ]. The cap-snatching EN domain is a metal ion-dependent nuclease characterized by a conserved PD… D/ExK catalytical motif. Structural and biochemical studies have classified viral ENs into two groups, His + ENs and His -ENs, based on their active site architecture and enzymatic activity [ 13 ] (Fig. 1 A). His + ENs, found in the families of Peribun y aviridae , Phenuiviridae , and Hantaviridae , and also in influenza viruses, contain a conserved histidine that coordinates the first metal ion, along with a flexible active-site loop harboring an acidic residue that binds the second metal ion [ 14 -19 ]. These enzymes exhibit robust in vitro endonuclease activity. By contrast, His -ENs, exclusive to Arenaviridae , substitute the histidine with glutamate or aspartate for metal ion coordination and possess a distal flexible loop that does not participate in metal ion coordination [ 18 , 20 , 21 ]. Strikingly, His -ENs demonstrate minimal enzymatic activity in in vitro assays.
Compared to His + ENs and His -ENs, the nairovirus ENs exhibit a hybrid active-site motif, integrating key features from both classes. Specifically, they retain a conserved glutamate residue, a hallmark of His -ENs, which is responsible for the first metal ion coordination, while also possessing a flexible loop region characteristic of His + ENs, which is likely involved in the second metal ion binding [ 22 ]. In addition to these hybrid features, nairovirus ENs differ from other bunyavirus ENs in both domain location and overall composition (Fig. 1 A). While most bunyavirus ENs are located at the Nterminus of the polymerase and comprise about 200 residues, the nairovirus ENs are positioned about 500-900 residues downstream from the N-terminus and span ∼350 residues. Moreover, nairovirus ENs contain one or two unique insertions (30-40 residues, insertion 1 and 2), predicted to form highly flexible loops that are absent in other viral ENs. Phy-logenetic analysis of bunyaviruses further highlights the distinctiveness of nairovirus ENs. Representative ENs from five human-infecting bunyavirus families cluster into three major clades (Fig. 1 B and Supplementary Table S1 ). One clade, which includes the Peribun y aviridae, Phenuiviridae, and Hantaviridae, aligns with the known His + ENs. Another clade, comprising Arenaviridae, corresponds to the His -ENs. Notably, nairovirus ENs form a separate clade, suggesting evolutionary divergence from these canonical groups. Collectively, these striking distinctions imply that nairovirus EN likely represents a group of viral endonucleases with different enzymatic and structural characteristics. However, the metal iondependent catalytic mechanism of nairovirus ENs remains unresolved, primarily due to the lack of high-resolution structural information and limited biochemical characterization of these ENs.
The cap-snatching endonuclease, a universally conserved feature among sNSVs, plays a pivotal role in viral transcription, making it an attractive target for antiviral development. Given the metal ion-dependent activity of ENs, a wealth of metal-chelating inhibitors has been explored to target ENs. Diketo acid compounds represent the first class of inhibitors developed to target the influenza virus EN. Among them, 2,4dioxo-4-phenylbutanoic acid (DPBA), the prototype of diketo acid compounds, inhibits the EN activity of influenza virus with a half-maximal inhibitory concentration (IC 50 ) at tens of micromolar levels [ 23 ]. Subsequently, a derivative of DPBA, L-742,001, emerged as a more potent compound, exhibiting strong inhibition of both endonuclease activity and cell-based virus replication at sub-micromolar concentrations [ 24 , 25 ]. More recently, baloxavir acid (BXA), has emerged as a highly potent inhibitor, demonstrating nanomolar antiviral activity in vitro and therapeutic efficacy in mouse models against influenza virus [ 26 -28 ]. Its prodrug, baloxavir marboxil, has been approved by the FDA as the first clinically available ENtargeting drug for influenza treatment [ 29 ]. Notably, DPBA, L-742,001, and BXA have also shown varying degrees of inhibitory effects against multiple bunyaviruses in enzymatic and cell-based assays, underscoring their potential as broadspectrum antivirals due to their conserved metal-chelating pharmacophore. Compared to their potency against influenza virus, these inhibitors demonstrate suboptimal efficacy against bunyaviruses, with IC 5 0 values ranging from several micromolar to several hundred micromolar [ 30 -33 ], highlighting the need for further optimization. However, the detailed molecular mechanisms underlying the action of these inhibitors remain poorly understood, posing a challenge to rational drug optimization and further antiviral development against bunyaviruses.
Currently, there is a gap in our understanding of the structure and function of nairovirus ENs, which is critical for comprehensively elucidating the catalytical mechanisms of viral ENs and developing effective antiviral strategies against CCHFV and related nairoviruses. In this study, we present the crystal structure of CCHFV EN in apo form and a series of high-resolution crystal structures of KASV EN in apo form, Mn 2 + -bound form, and in complex with three representative EN inhibitors. We biochemically characterized nairovirus ENs' metal ion-dependent endonuclease activity, investigated the functional roles of conserved active site residues in EN catalysis, and evaluated the inhibitors' binding affinity and inhibitory activity. Our findings reveal a two-metal-ion binding mode specific to the Nairoviridae family, which is The sequence boundaries of 51 EN domains from five Bunyaviridaes and influenza viruses were determined by aligning the L proteins or influenza virus polymerase PA subunit, using the characterized EN domain as the query sequence. Subsequently, the amino acid sequences of EN homologs were aligned using MAFFT [ 51 ]. Phylogenetic analysis was performed using IQ-TREE [ 52 ] based on the maximum likelihood (ML) method, with branch support e v aluated using SH-like approximate likelihood ratio test (SH-aLRT) and ultrafast bootstrap (UFBoot) with 10 0 0 replicates. Nodes with strong support (SH-aLRT ≥ 80% and UFBoot ≥ 95%) are marked by pink circles in the tree. The UniProt accession numbers and sequence boundaries for the 51 EN domains are listed in Supplementary Table S1 .
essential for achieving their full catalytic activity. Furthermore, we found that the FDA-approved inhibitor BXA exhibits potent inhibitory activity against nairovirus ENs and engages in more extensive interactions with the active site pocket of KASV EN than the other two inhibitors (DPBA and L-742,001). Our combined biochemical, structural, and functional analyses provide important insights into the catalytic and inhibitory mechanisms of nairovirus endonucleases, offering potential opportunities for structure-based drug design and optimization.
## Materials and methods
## Protein expression and purification
The fragments containing putative endonuclease domain were designed based on sequence alignment analysis and AlphaFold structure prediction [ 34 ]. DNA fragments encoding residues 585-898 of CCHFV L protein and 610-904 for KASV L protein were amplified by polymerase chain reaction (PCR) using synthesized gene sequences and subsequently cloned into the pGEX-6P-1 expression vector with an N-terminal GST tag. Single-point mutations were introduced by site-directed mutagenesis. Proteins were expressed in Esc heric hia coli strain BL21 (DE3) cultured in LB medium supplemented with 100 μg/ml ampicillin at 16 • C overnight after induction with 0.2 mM of isopropyl β-D-1-thiogalactopyranoside (IPTG). Cells were harvested, resuspended in lysis buffer (20 mM Tris-HCl, pH 8.0, 300 mM NaCl), and disrupted using a high-pressure cell crusher (Union-Biotech). The clarified lysate was loaded onto a column packed with Glutathione Resin, washed with 20 column volumes of lysis buffer, and subjected to on-column cleavage with PreScission protease at 4 • C overnight to remove the GST tag. The flow-through fraction containing target proteins was concentrated and further purified by size-exclusion chromatography using a Superdex 200 Increase 10/300 GL column (Cytiva) equilibrated with GF buffer (20 mM Tris-HCl, pH 8.0, 150 mM NaCl). Purified proteins were concentrated to 10-25 mg/ml, flash-frozen in liquid nitrogen and stored as aliquots at -80 • C for further use. Mutant proteins were prepared using the same purification strategy as the wildtype (WT) protein.
## Differential scanning fluorimetry
Differential scanning fluorimetry (DSF) thermal denaturation curves of purified KASV EN and its mutants were measured using a PSA-16 instrument (BEST Science & Technology, Beijing, China). Protein samples were diluted to 0.3 mg/ml in assay buffer (20 mM Tris-HCl, pH 7.5, 150 mM NaCl, 5% vol/vol glycerol) supplemented with 2 mM of various divalent metal ions, or with 0.2 mM of inhibitor (DPBA, L-742,001, and BXA) and 2 mM MnCl 2 . Intrinsic protein fluorescence intensity at 330 and 350 nm was monitored using a linear temperature ramp from 30 • C to 95 • C at a heating rate of 1 • C per minute. The melting temperature ( T m ) was calculated from the first derivative of the F350/F330 fluorescence ratio curve.
## Dynamic light scattering assay
The hydrodynamic size of KASV EN and mutants were determined by dynamic light scattering (DLS) on a Malvern Zetasizer Nano ZS (Malvern Instruments) using a ZEN0040 cuvette, and the parameters were 11 consecutive runs per sample, each with a measurement time of 40 s. Protein samples were diluted to 1 mg/ml in assay buffer (20 mM Tris-HCl, pH 7.5, 150 mM NaCl, 5% vol/vol glycerol) supplemented with 2 mM of various divalent metal ions. Before measurement, samples were filtered through a 0.22 μm membrane to remove impurities. For measurements conducted at 40 • C, protein samples were pre-incubated at 40 • C for 1 min before analysis under the same conditions.
## Isothermal titration calorimetry assay
Isothermal titration calorimetry (ITC) was performed on a Nano ITC (TA Instruments) to determine the binding affinity and thermodynamic parameters of Mn 2 + for KASV EN and its mutants. All protein and metal solutions were prepared in ITC buffer (20 mM Tris-HCl, pH 7.5, 150 mM NaCl, 10% vol/vol glycerol). For the WT protein, the sample cell contained 300 μM KASV EN, which was titrated with 32 μl injections of 3 mM Mn 2 + . Injections were spaced at 150 s intervals with a stirring speed of 300 rpm at 25 • C. The mutant proteins were titrated with 10 mM Mn 2 + under the same conditions. The heat of dilution was corrected by subtracting the data from control titrations of Mn 2 + into buffer alone. Data was fitted and analyzed using the NanoAnalyze software.
## In vitro EN activity assay
The 5'-FAM-labeled single-stranded RNA (ssRNA) substrates including 19-mer U-rich ssRNA (5'-A UUUUGUUUUUAA UA UUUC-3'), A-rich ssRNA (5'-UAAAA GAAAAA UUA UAAA C-3'), C-rich ssRNA (5'-A CCCCGCCCCCAA CA CCCA-3'), G-rich ssRNA (5'-A GGGGCGGGGGAA GA GGGA-3'), and 27-mer structured ssRNA (5'-GA UGA UGCUA UCA CCGCGCUCGUCGUC-3') were chemically synthesized (Shanghai Sangon Biotech Co., Ltd; Integrated DNA Technologies). For nuclease activity experiments, 1-4 μM of the EN was incubated with 0.2 μM 5'-FAM-labeled ssRNA substrates at 37 • C in assay buffer (5 mM Tris-HCl, pH 7.5, 150 mM NaCl, 1 U/ μl RNasin [Promega]), in the presence or absence of 2 mM divalent metal ions, 20 mM ethylenediaminetetraacetic acid (EDTA), or inhibitor at the indicated concentration. Reactions were terminated by adding 2 × stop loading buffer (95% formamide, 20 mM EDTA, 0.02% wt/vol bromophenol blue). Samples were heated at 100 • C for 1 min, resolved on 7 M urea, 20% polyacrylamide, Tris-borate-EDTA gel electrophoresis, and then visualized with Typhoon imager (GE Healthcare). The intensity of the ssRNA substrate in the images was quantified using ImageJ ( https:// imagej.nih.gov/ ij ), and the enzymatic activity is determined by calculating the percentage of substrate ssRNA degraded. The activity for the mutants is expressed relative to the WT EN (set at 100%). For activity inhibition assays, inhibition percentages were plotted against compound concentrations, and the dose-response curves were generated by nonlinear regression analysis using GraphPad Prism 9 to determine half-maximal inhibitory concentrations (IC 50 ).
## mAb generation
BALB/c mice were immunized three times at three-week intervals with CCHFV or KASV EN proteins. Following the final immunization, mice were euthanized and splenocytes were harvested for antigen-specific B cell sorting and antibody sequence identification. Briefly, isolated cells were stained with 0.5 μg/ml biotinylated EN proteins for 30 min at 4 • C. After washing with phosphate buffered saline (PBS), color conjugated secondary antibodies were added for 30 min at 4 • C: Dead 780-APC-Cy7, CD3/CD4/CD8-AmCyan, CD19-PE-Cy7, IgD-PerCP-Cy5.5, CD138-FITC, CD95-PE, and Streptavidin-APC (BD Pharmingen). After two additional washes, cells were sorted on a FACS Aria II (BD Biosciences) using the following gating strategy: Dead-, CD3/CD4/CD8-, CD19 + , IgD-, CD95 + , CD138 + and Streptavidin-APC + (EN-specific binding). Target cells were sorted into 96-well PCR plates (Bio-Rad), and the variable regions of antibody genes were amplified using established protocols [ 35 , 36 ]. The resulting sequences were cloned into mammalian expression vectors containing the human CH1 domain of the heavy chain and the constant region of the light chain for Fab expression, respectively.
For Fab production, paired heavy-and light-chain plasmids were co-transfected into Expi293 cells at a 1:1 molar ratio. Cell supernatants containing secreted Fabs were harvested 5-6 days post-transfection, filtered through 0.45 μm filters, and purified sequentially using Ni-NTA resin (GenScript, Cat# L00666) followed by size-exclusion chromatography on a Superdex 200 Increase 10/300 GL column equilibrated with GF buffer (20 mM Tris-HCl, pH 8.0, 150 mM NaCl).
## Crystallization and structure determination
The purified EN protein was mixed with Fab in a molar ratio of 1:1.2 and further purified to homogeneity via size-exclusion chromatography using Superdex 200 Increase 10/300 GL column. Crystallization trials of EN-Fab complex were conducted using a mosquito robot (TTP Labtech) with the sittingdrop vapor diffusion method at 16 • C. Typically, protein samples at concentrations of 8 or 10 mg/ml were mixed with the reservoir solution at a 1:1 volume ratio in 0.6μl droplets. CCHFV EN-G5 Fab complex crystallized in a reservoir solution containing 2% vol/vol Tacsimate TM pH 7.0, 0.1 M HEPES pH 7.5, and 20% wt/vol Polyethylene glycol 3350. Crystals of KASV EN-2E9 Fab complex were obtained in the condition of 25% vol/vol Jeffamine ED2003, 0.2 M NaCl, and 0.1 M MES-NaOH pH 6.0. The KASV EN-Mn 2 + bound crystals were obtained by soaking apo crystals in reservoir solution supplemented with 2.5 mM MnCl 2 for 6 h. KASV EN mutant crystals were grown under the same conditions as the WT protein, with the addition of 2.5 mM MnCl 2 . KASV ENinhibitor complex crystals were obtained by co-crystallization using protein solutions supplemented with 2.5 mM MnCl 2 and 0.5 mM of individual inhibitor. Apo and mutant crystals were flash-cooled in liquid nitrogen using cryoprotectant solutions consisting of reservoir supplemented with 15% vol/vol glycerol, with or without 2.5 mM MnCl 2 . For EN-inhibitor co-crystals, an additional 0.5 mM inhibitor was included in the cryoprotectant.
The X-ray diffraction data were collected at BL02U1 and BL10U2 beam lines of the Shanghai Synchrotron Radiation Facility (SSRF) with a wavelength of 0.979 Å and a temperature of 100 K. A full 360 degrees of data was collected in 0.4 • oscillation steps. The diffraction data were automatically processed at the beamlines using the XDS and Xia2 pipelines [ 37 , 38 ] and subsequently scaled with Aimless from the CCP4 suite [ 39 ]. The initial model was obtained by the molecular replacement program PHASER [ 40 ] using the predicted EN and Fab structures from AlphaFold [ 34 ] as search models. Structure refinement was carried out iteratively through manual model building in Coot [ 41 ] and automated refinement with PHENIX [ 42 ]. Data collection and refinement statistics for the final models are summarized in Supplementary Table S2 .
## Microscale thermophoresis assay
Binding affinities between ENs and inhibitors were measured using the Monolith NT.115 (NanoTemper Technologies). Nterminally GFP-tagged KASV EN and CCHFV EN were prepared and used in experiments for fluorescence-based detection. In each assay, 10 μl of 200 nM GFP-EN in buffer containing 20 mM Tris-HCl, pH 7.5, 150 mM NaCl, 2 mM MnCl 2 , 5% vol/vol dimethyl sulfoxide (DMSO), 0.05% vol/vol Tween-20, and 1 mg/ml bovine serum albumin was mixed with 10 μl of inhibitor solution (DPBA, L-742,001, or BXA) at various concentrations. After a 15-min incubation at room temperature, samples were loaded into capillaries (NanoT emper T echnologies), and temperature-induced fluorescence changes were recorded at 25 • C using 20% LED power and medium microscale thermophoresis (MST) power. Dissociation constants (Kd) were determined by nonlinear regression analysis of dose-response curves using MO.Affinity Analysis software.
## CCHFV mini-replicon assay
The transcription activities of L protein mutants were assessed using the T7 RNA polymerase-based CCHFV minireplicon system, as described previously [ 43 ]. Briefly, 0.5 μg each of the three plasmids pCAGGS-CCHFV-L (WT or mutants), pCAGGS-CCHFV -NP, and pT7-CCHFV -Lutr-eGFP were transfected into 1 × 10 5 BSR-T7/5 cells using Lipofectamine 3000 (Invitrogen), following the manufacturer's instructions. After transfection, cells were incubated at 37 • C with 5% CO 2 for 24 h, then fixed with 4% polyformaldehyde for 15 min. Subsequently, the cells were washed three times with PBS and stained with Hoechst 33258 (Beyotime) for 10 min to visualize nuclei. The total number of cells and the number of fluorescent cells were counted using a highcontent imaging system (HCS; PerkinElmer Operetta CLS, Tokyo, Japan), and the percentage of GFP-expressing cells relative to the total cells was calculated. The ratio of the mutant group was normalized to that of the WT group, which was set as 100%. Statistical analysis was performed using two-tailed Student's t tests.
To confirm the expression of all L protein mutants in BSR-T7/5 cells, transfections were performed using 1 μg of pCAGGS-CCHFV-L plasmid, which expresses C-terminally 3xFLAG-tagged L protein, in a 24-well plate (1 × 10 5 cells/well) with Lipofectamine 3000. At 24 h post transfection, cells were lysed, separated by 4%-12% sodium dodecyl sulphate-polyacrylamide gel electrophoresis, and transferred to polyvinylidene fluoride (PVDF) membrane. L protein was detected using a Mouse anti DDDDK-Tag mAb with a dilution of 1:3000 (Abclonal, Cat#AE005) and an HRPconjugated Goat anti-Mouse IgG (H + L) with a dilution of 1:5000 (Abclonal, Cat#AS003). Protein bands were visualized by ChemiScope 6100 (Clinx Science Instruments Co., Ltd; Shanghai, China).
## Results
## Biochemical and enzymatic characterization of KA S V EN
Both characterized His + and Hiscap-snatching endonucleases require divalent metal ions for catalytic activity. To identify the metal ion binding specificity of nairovirus EN, DSF was performed to monitor protein stability under varying conditions. KASV EN displays a typical thermal denaturation curve and has a melting temperature ( T m ) of 42.3 • C in the absence of metal ions. The addition of MnCl 2 or MgCl 2 increased the T m by 4.7 • C and 2.9 • C, respectively (Fig. 2 A), probably due to the metal ions binding in the active site. Abnormal thermal denaturation curves were observed in the presence of Co 2 + , Zn 2 + , or Ni 2 + ( Supplementary Fig. S1 A), presumably because these ions lead to protein aggregation or degradation. The DLS analysis showed that the addition of any of the three ions resulted in marked increase in the average hydrodynamic diameter of EN, indicating protein aggregation in the samples ( Supplementary Fig. S1 C andE). Further DSF assays were conducted in the presence of MnCl 2 and three known EN inhibitors. Both DPBA and L-742,001 induced an ∼10 • C increase in T m , surpassing the stabilization effect observed with MnCl 2 alone ( T m = 4.7 • C). Notably, BXA conferred the greatest stabilization effect on KASV EN, increasing the T m by 16.8 • C (Fig. 2 A). These results indicate that KASV EN can bind both Mn 2 + and Mg 2 + and might interact most strongly with BXA among the tested inhibitors.
To characterize the intrinsic nuclease activity of KASV EN, we conducted nucleic acid degradation assays with various metal ions and five distinct 5 -FAM-labeled ssRNA substrates. KASV EN showed apparent nuclease activity only with Mn 2 + when using the 19-mer U-rich ssRNA, whereas no detectable activity was observed with the other four tested metal ions, confirming a strong specificity for Mn 2 + (Fig. 2 B). Furthermore, the RNA substrate preference of KASV EN was characterized by comparing the EN activity on 19-mer U-rich, Arich, C-rich, and G-rich ssRNAs, as well as a 27-mer heterogeneously structured ssRNA. For the nucleotide-rich constructs, identical nucleotide positions were designed to ensure sequence uniformity across substrates. The results showed that the majority of U-rich ssRNA was digested into small fragments by KASV EN within 120 min, whereas the other four ssRNA substrates remained predominantly intact throughout the incubation period (Fig. 2 C). Complete and pronounced degradation was observed for 19-mer U-rich and the other three RNA constructs except for the 19-mer G-rich ssRNA at higher protein concentrations, indicative of KASV EN preference for uridine ssRNAs ( Supplementary Fig. S2 ). We also examined the activity of CCHFV EN under the same experimental conditions, which exhibited analogous RNA digestion profiles as those of KASV EN ( Supplementary Fig. S2 ), suggesting a common substrate preference across nairovirus ENs.
## Antibody-assisted crystallization of CCHFV and KA S V ENs
Initial attempts to crystallize the CCHFV and KASV ENs in apo form or in complex with metal ion and inhibitors were unsuccessful, likely due to the inherent conformational flexibility derived from the two insert regions. To address this challenge, we developed an innovative antibody-assisted crystallization strategy. Mice were immunized with EN proteins, and monoclonal antibodies (mAbs) specific to CCHFV EN (G5) and KASV EN (2E9) were successfully identified ( Supplementary Fig. S3 A). Enzymatic assays showed that both mAbs had no effects on the in vitro endonuclease activity of CCHFV or KASV ENs ( Supplementary Fig. S3 B). The complex formed between EN and the corresponding antigenbinding fragment (Fab) yielded large rod-like crystals for the CCHFV EN-G5 Fab complex and thin plate-like crystals for the KASV EN-2E9 Fab complex. The CCHFV EN-G5 Fab complex is crystalized with a unit cell containing two complex molecules arranged in a staggered manner with neighboring molecules, which adopt a herringbone packing motif within the crystal lattice. This ordered spatial organization is primarily driven by compact intermolecular interactions between the EN and Fab. The KASV EN-2E9 Fab complex crystal possesses a small-sized unit cell containing a single complex molecule. Within the crystal lattice, two neighboring complexes orient in opposite directions and assemble into extended two-dimensional parallel layers via Fab-Fab interactions ( Supplementary Fig. S3 C). Notably, in both complex structures the Fab binds specifically to flexible loop regions of EN and stabilizes the conformation of individual EN molecule ( Supplementary Fig. S3 C), indicating that Fabmediated interactions play an indispensable role in crystal packing.
## Overall structures of KA S V and CCHFV ENs
The apo and Mn 2 + -bound structures of KASV EN were solved at 1.90 Å and 1.98 Å resolution in space group P 2 1 , respectively. Clear electron density was visible for the entire protein except for residues 726-779, which coincided with the insertion 1, predicted to be a highly flexible loop. The apo structure of CCHFV EN was solved at 3.05 Å in space group P 2 1 2 1 2 1 , with two disorder regions corresponding to the insertion 1 (residues 703-729) and insertion 2 (residues 764-795), respectively. The Mn 2 + -bound structure of CCHFV EN could not be obtained due to poor diffraction quality of the complex crystals. Therefore, we focus our detailed analysis on the high-quality KASV EN structures.
Similar to previously reported EN structures, the KASV EN adopts a two-lobe architecture. One lobe includes the Nterminal four helix bundle ( α1-α3 and α9), and the other is composed of a central five-stranded β-sheet sandwiched by five helices, with the helices α4-α6 and α8 partially covering the β-sheet, while helix α7 places at the bottom of the β-sheet (Fig. 3 A). The active site lies between the two lobes and harbors two manganese ions coordinated by highly conserved acidic residues ( Supplementary Fig. S4 C). The flexible loop linking α3 and α4 (highlighted in green in Fig. 3 A, denoted as LoopE), bears a conserved acidic residue that is involved in manganese binding, and plays a similar function to that observed in the His + ENs. The CCHFV EN displays highly consistent global conformations as that of KASV EN, with a root-mean-square deviation (RMSD) value of 1.2 Å for all superimposable a -carbon atoms, except for two small helices situated at the two ends of the strand β3 (Fig. 3 and Supplementary Fig. S4 A).
Structural comparison shows that KASV EN shares a similar overall architecture with ENs from other bunyaviruses and influenza virus (RMSD 2.7-3.5 Å , 42%-63% residue coverage) (Fig. 3 A andB), despite their very low sequence homology (identity ranging from 11%-17%, similarity ranging from 16%-24%), suggesting conserved domain organization among viral cap-snatching endonucleases. Nevertheless, KASV and CCHFV ENs exhibit unique structural features compared to other viral ENs, including the α7 helix and one or two disorder insertions (insertions 1 and 2), which are exclusively presented in nairovirus ENs (Fig. 3 B). The α7 helix in both structures wraps the base of the central β-sheet, providing stable support to the overall structural module and partially sealing the bottom of the active site pocket. Insertion 1 locates between the β1 and β2 and is adjacent to the active site, which is relatively conserved and exists in nearly all nairoviruses. By contrast, insertion 2 follows α7 and connects to the outmost β3, positioned far away from the active site. This insertion is highly variable in length and sequence and is particularly large in CCHFV and several other nairoviruses, such as NSDV and DUGV ( Supplementary Fig. S4 C). Together, these unique structural elements in nairoviruses ENs might play specific functional roles, such as regulating EN activity, facilitating substrate binding, or establishing interactions with other functional domains of viral polymerase.
## The active site of KA S V EN exhibits a unique metal ion binding mode
The apo KASV EN structure shows no metal ions in the active site, whereas distinct electron density for two metal ions was observed in MnCl 2 -soaked crystals . In the Mn 2 + -bound structure, the active site features a conserved E 668 …E 682 …P 718 D 719 …E 831 …K 841 catalytic motif that binds two manganese ions (Fig. 4 A). Mn1 was octahedrally coordinated by the side chain of D719, the carbonyl group of V832, two discrete water molecules (W2 and W4), and two bridging water molecules (W1 and W3), which form hydrogen bonds with the side chains of E668 and E831. Similarly, Mn2 exhibits a predominantly solvent-mediated coordination sphere with D719 as its sole direct protein ligand. This coordination involves one discrete water molecule (W4), together with three bridging water molecules (W5, W6, and W7) interacting with the side chains of E831, E682, and E668. In addition, the putative catalytical residue K841 and the K848 associated with metal ion coordination via bridging water molecules (W3 and W8) (Fig. 4 A). Comparison of the apo and Mn 2 + -bound structures reveals subtle conformational changes in the active site residues upon metal ions binding, except for the E682 side chain in LoopE, which repositions toward the Mn2-binding site ( Supplementary Fig. S6 A). The apo structures of CCHFV and KASV ENs exhibit nearly identical active site conformations ( Supplementary Fig. S4 B). Sequence alignment analysis further reveals that the metal ioncoordination residues are strictly conserved among nairovirus ENs ( Supplementary Fig. S4 C), implying a common metal-ion binding configuration shared by nairovirus ENs.
Comparison with previously reported Mn 2 + -bound His + ENs and His -ENs structures reveals that KASV EN exhibits similar configurations for its active site residues. However, its metal ion binding mode is strikingly different compared to both enzyme classes (Fig. 4 A). First, KASV EN contains E668 (equivalent to His in His + ENs and Glu/Asp in His -ENs) which simultaneously participates in Mn1 and Mn2 coordination via bridging waters, whereas its counterparts exclusively bind Mn1 directly [ 14 , 15 , 18 , 19 ]. Second, LoopE in KASV EN maintains a closed conformation in both apo and Mn 2 +bound structures, the Mn2 coordination is mediated solely by conformational adjustments of the side chain of E682 positioned above it ( Supplementary Fig. S6 A). Differently, the flexible loop exists in two distinct conformations in the other two enzyme classes: in His + ENs, it undergoes an open-to-closed conformational transition upon metal ions or inhibitor binding [ 14 , 16 ], while in His -ENs, it adopts an open conformation incapable of metal coordination [ 18 , 20 ]. Third, with the exception of D719, which directly coordinates with both Mn1 and Mn2, all other conserved residues in KASV EN indirectly coordinate with the metal ions via bridging water molecules. By contrast, in the other two enzyme classes, all these residues are nearly directly involved in metal ion binding. Collectively, these observations suggest a specific metal ion binding mode in the active site of KASV EN and imply a unique catalytic mechanism within nairovirus ENs.
## Two metal ions are required to achieve full catalytic activity of KA S V EN
To corroborate our structural finding, we performed singlepoint alanine mutations at eight conserved active site residues to investigate their impacts on metal ion-induced protein stability and catalytic activity. As expected, mutating D719 completely abolished metal ion-induced stabilization ( T m = -0.7 • C), consistent with its direct coordination with both Mn1 and Mn2. Mutations at E668 and E682, which indirectly participate in binding both metal ions, also reduced the stabilization effect ( T m = 0.8, and 1.7 • C, respectively) compared to the WT ( T m = 5.1 • C), suggesting that these residues are essential for optimal metal binding. By contrast, mutations at P718, K841 and K848 had a minimal impact on Mn 2 +induced protein stability (Fig. 4 B and Table 1 ), likely due to their limited contribution to metal ion binding. The E831A and W849A mutants displayed noncanonical thermal denaturation curves ( Supplementary Fig. S1 B), presumably caused by protein aggregation or conformational instability during thermal ramping. This was corroborated by DLS assay, which showed a pronounced increase in particle size for both mutants at an elevated temperature (40 • C) compared with the WT ( Supplementary Fig. S1 D andE), indicative of aggregation during the heating process. We further detected the binding of Mn 2 + to WT, D668A, and D719A mutants using ITC ( Supplementary Fig. S5 ). The titration curve data for WT and D668A were satisfactorily fitted with a one-site binding model, yielding Kd values of 25.4 and 163.0 μM, respectively, while D719A showed complete loss of Mn 2 + binding. The reduced binding affinity observed for D668A compared to WT suggests this mutation disrupts the binding site. These observations are largely consistent with the results from the thermal stability assay and structural observation.
In parallel, we investigated the endonuclease activity of these mutants using the 19-mer U-rich ssRNA substrate in the presence of Mn 2 + . Mutation in the key metal ion-coordination residues (E668, E682, D719, and E831) dramatically reduced EN activity. While the putative catalytic residue K841A retained activity, albeit at a lower level than the WT, suggesting that it contributes to but is not essential for EN activity. Mutations at P718, K848, and W849 had no effect on EN activity (Fig. 4 C and Table 1 ), in line with their minimal or no involvement in metal ion coordination. Taken together, these findings indicate that the conserved residues involved in coordinating the two metal ions are critical for both metal ion binding and EN catalytic activity.
To get deeper structural insights into the relationship between metal ion binding and EN activity, we crystallized three key mutants (E668A, E682A, and D719A) and successfully determined their high-resolution structures. While the D719A mutant completely abolished metal ion binding in the active site, both E668A and E682A mutants retained with 1 μM WT or mutant protein in the presence of 2 mM MnCl 2 . As a negative control (NC), the ssRNA was incubated with WT protein in the absence of MnCl 2 . Some residual background activity may associate with sample contamination rather than KA S V EN activity. ( D ) Transcriptional activity of WT and mutant CCHFV L proteins. BSR-T7/5 cells were transfected with T7 RNA polymerase-driven mini-replicon system along with two helper plasmids. eGFP reporter gene expression was quantified and normalized to that of WT group (set as 100%). The statistical significance was determined by t wo-t ailed Student's t -tests. * * * * P < .0 0 01. Dat a represent the mean ± st andard error of the mean of t w o independent e xperiments ( n = 2 × 3, with two biological replicates, each consisting of three technical replicates). Immunoblot analysis of 3 × FLAG-tagged WT and mutant L proteins is shown.
T he β-actin w as used as an internal control.
binding to only a single metal ion, corresponding to Mn1 ( Supplementary Fig. S6 B). These structural observations are fully consistent with the biochemical data from thermal stability and EN activity assays. Together, the combined biochemical and structural data highlights D719 as a critical residue for coordinating both metal ions and for catalytic activity, supporting the notion that binding of both metal ions is essential for the full enzymatic function.
## The essential role of the KA S V EN active site in viral transcription
To assess the functional relevance of KASV EN in viral transcription, we further investigated the roles of the active site residues in the context of full-length RNA polymerase. Since no mini-replicon system is available for KASV, we used an established CCHFV mini-replicon system in which a GFP reporter gene serves as a readout of the transcription activity of the viral polymerase [ 43 ]. We selected D718 of CCHFV EN in insertion 1 as a positive control, which is located distal to the active site and is not conserved among nairoviruses. Both the WT and the D718E L proteins exhibited robust transcription activity. However, mutating the metal ion-coordination residues E642, E656, D693, E825, and K835 (homologous to KASV EN E668, E682, D719, E831, and K841) nearly abrogated the transcription activity, consistent with their impaired EN activity in vitro . Interestingly, mutations at the residues P692, K842, and W843 (homologous to KASV EN P718, K848, and W849) also caused a significant reduction in activity (Fig. 4 D and Table 1 ); although these residues are minimally implicated in metal ion binding and do not affect EN activity in vitro , implying their additional functional roles in transcription beyond EN activity . Collectively , these data suggest that transcription by the full-length RNA polymerase is highly dependent on the two-metal ion-dependent endonuclease activity.
Inhibition of KA S V and CCHFV endonuclease activity by DPBA, L-7 42,00 1, and BXA As described above, three representative inhibitors (DPBA, L-742,001, and BXA; Fig. 5 A), were shown to enhance the stability of KASV EN. To further evaluate their binding affinity and inhibitory potential against nairovirus ENs, we conducted MST assays and endonuclease activity experiments. KASV EN displayed the highest affinity to BXA, with a dissociation constant of Kd= 4.5 μM, which is about 15 and 30 times lower than those of DPBA (Kd= 70.7 μM) and L-742,001 (Kd = 140.1 μM), respectively (Fig. 5 B). In the EN activity assays, both L-742,001 and BXA efficiently inhibited KASV EN activity at concentrations of 400 and 200 μM, respectively, whereas DPBA showed no detectable inhibition at 400 μM under the tested conditions ( Supplementary Fig. S7 B). Dose-dependent assays revealed that L-742,001 had a halfmaximal inhibitory concentration (IC 50 ) of 176.5 μM for KASV EN, ∼10-100-fold higher than those reported for other bunyavirus ENs [ 17 , 31 , 44 ]. BXA exhibited pronounced higher inhibitory activity than L-742,001, with an IC 50 of 28 μM (Fig. 5 C). Nonetheless, its potency remains significantly lower than the nanomolar-range IC 50 reported for influenza virus ENs [ 26 ]. Parallel assays with CCHFV EN produced similar binding and inhibition profiles to those observed for KASV EN ( Supplementary Fig. S7 ). The MST and enzymatic activity data confirm that both L-742,001
and BXA can bind to and inhibit nairovirus ENs in vitro , with BXA exhibiting superior binding affinity and inhibitory efficacy.
## Binding modes of the inhibitors in KA S V EN
To elucidate the mechanisms of action of DPBA, L-742,001, and BXA against nairovirus ENs, we co-crystallized KASV EN with each inhibitor. The three co-crystal structures were determined at resolutions of 2.15 Å , 1.95 Å , and 2.16 Å , respectively. All three structures displayed unambiguous electron density for the compounds, which chelate the two manganese ions at the active site center via their respective head groups (diketo acid in DPBA, L-742,001, and an oxazinopyridotriazin-dione moiety in BXA) in a similar fashion (Fig. 6 A). In each complex, Mn1 and Mn2 are coordinated by the side chain of the central D719, two adjacent and planar oxygen from the inhibitor's head group, and bridging water molecules that interact with the conserved active site residues. Beyond the metal chelating moiety, the remaining portions of the inhibitors adopt distinct conformations. The phenyl group of DPBA makes no direct contact with the protein, and only weak electron density was observed for this group. In the L-742,001-complexed structure, the piperidine central ring is oriented perpendicular to the diketo acid group with well-defined electron density, while the phenyl and pchlorobenzene moieties appear disordered, possibly due to a lack of interactions with the surrounding residues. Notably, the BXA-bound structure exhibits well-resolved electron density across the entire molecule. In addition to coordinating the manganese ions, BXA's V-shaped tail group engages in additional interactions with residues distal to the catalytic center (Fig. 6 A and B). Specifically , R661 packs against the V -shaped tail group, forming a cationπ stacking with the aromatic ring of BXA, while L660 and G664 contribute hydrophobic contacts. These interacting residues are highly conserved among nairovirus ENs, highlighting their importance for further inhibitor exploration ( Supplementary Fig. S4 C). Protein-ligand interface area analysis shows that BXA forms an interface area of 539.8 Å 2 with EN, which is larger than those formed by DPBA (306.2 Å 2 ) and L-742,001 (376.9 Å 2 ). Together, these structural findings demonstrate that BXA establishes more extensive and stable interactions with KASV EN than DPBA and L-742,001, accounting for its superior binding affinity and inhibitory potency.
## Discussion
The cap-snatching endonucleases encoded by sNSVs belong to the PD-(D/E)xK nuclease superfamily that requires divalent metal ions for catalysis. Unlike other viral endonucleases that situated at the N terminus of the L protein, the nairovirus EN domain was previously predicted to be located around amino acids 700 in the L protein [ 20 ], and its function was first identified using a CCHFV virus-like particle system, in which the active-site signature residue D693 was shown to be necessary for mRNA transcription [ 45 ]. A subsequent study showed that the CCHFV and other related nairovirus ENs are enzymatically inactive in vitro , despite being capable of binding metal ions via conserved acidic residues (E642 and E656) [ 22 ]. In our study, we found the expressed CCHFV and KASV ENs only exhibited low in vitro activity toward 19-mer U-rich ssRNA, exclusively in the presence of Mn 2 + , this appears to slightly discrepancy with the previous results, which might be due to the different experimental conditions. The KASV EN can bind both Mn 2 + and Mg 2 + as indicated by the thermal stability assay (Fig. 2 A); however, no detectable enzymatic activity was observed in the presence of Mg 2 + (Fig. 2 B). These findings are consistent with the previous studies in which most viral ENs exhibit substantially higher activity with Mn 2 + than with Mg 2 + [ 14 , 16 , 18 , 19 ]. This preference may be attributed to the fact that Mn 2 + has a smaller ionic radius and less stringent coordination requirements than Mg 2 + [ 46 ], which might facilitate the formation of a coordination geometry favorable for catalysis and create greater flexibility for substrates binding. Nevertheless, the isolated nairovirus ENs show low activity in vitro even in the presence of Mn 2 + , suggesting that efficient EN activity likely requires the structural or functional context of the full-length RNA polymerase. Using the antibody-assisted crystallization strategy, we clearly depicted both the apo and metal ion-bound states of nairovirus endonuclease for the first time by determining highresolution structures of KASV and CCHFV EN. Unlike other known viral ENs, KASV EN exhibits a unique two-metal-ion binding mode (Fig. 4 A), in which the conserved D719 serves as the sole direct ligand coordinating both metal ions, while the remaining active site residues bind the metal ions indirectly via bridging water molecules. This particular metal ion coordination mode likely arises from the native active-site configuration, which is dictated by the spatial arrangement of the conserved residues. Notably, conservation analysis reveals that the active site architecture is highly conserved among nairovirus ENs, composed of residues that are evolutionarily conserved ( Supplementary Fig. S8 and Supplementary Table S3 ), strongly suggesting a shared metal ion binding mechanism within the Nairoviridae family. Our data also provide structural evidence that nairovirus ENs likely represent a distinct group of cap-snatching endonucleases, aligning with earlier proposals that they take a unique evolutionary position between His + and Hisendonucleases [ 22 ]. For sNSV-encoded endonucleases, the two-metal-ion catalysis mechanism was initially proposed for influenza virus EN and supported by our structural and enzymatic studies on the Ebinur Lake virus EN [ 15 , 19 ]. In this study, mutations at residues directly or indirectly involved in both manganese ions coordination impaired the KASV EN activity (Fig. 4 C), and the transcription activity in a CCHFV based mini-replicon system (Fig. 4 D). Structural analyses of the inactive mutants show either partial or complete loss of metal ion binding ( Supplementary Fig. S6 B). These findings indicate that EN activity is highly dependent on the binding of two metal ions, suggesting nairovirues ENs employ a two-metal-ion catalysis akin to other cap-snatching endonucleases, albeit through distinct metal ion coordination mode.
The two-metal-ion catalysis has been established as a general mechanism for many nucleases, with both metal ions (referred to as metal A and B) playing distinct roles in the catalytic cycle [ 46 -50 ]. On one hand, metal A can activate the hydroxyl nucleophile to facilitate nucleophile attack on the scissile phosphodiester of the nucleic acid substrates. Water molecules, bound to metal A, act as the most common nucleophiles and can be directly activated by the metal ion or deprotonated by a general base. On the other hand, both metal A and metal B stabilize the ground-state, transition-state, and post-reactive-state by interacting with the bridging or nonbridging oxygen atoms of the scissile phosphate. Remarkably, the two metal ions can reposition relative to each other during different reaction stages, adopting an optimal spatial coordination geometry that favors the nucleophile attack and product formation. The realization of the above-mentioned functions of the metal ions involves the dissociation of metal ions from the original ligands and the re-coordination with new ligands. Based on this, we postulate two functional roles of water molecules in the metal ion binding mode of KASV EN. First, one metal ion-bound water might serve as a nucleophile, especially the water bound with Mn1, which occupies a similar spatial position as metal A ( Supplementary Fig. S9 A). Second, the bridging water molecules between Mn 2 + and binding residues may reduce the free energy barrier of ligand binding by acting as a lubricant, thereby accelerating rapid ligand exchange to achieve efficient catalysis. To investigate the potential mechanism of RNA substrate recognition and cleavage, we generated an AlphaFold-predicted model of the KASV EN bound to two manganese ions and a 6-nt RNA fragment derived from the 19-nt U-rich ssRNA. The resulting model shows high confidence for the overall EN-RNA structure, except for the flexible insertion 1 and Loop 810-826 that interacts with the 2E9 Fab in our crystal structure ( Supplementary Fig. S9 B). In the predicted model, the RNA lies within the cleft formed by the two lobes of EN, with the 5 phosphate group occupying the two-metalion catalytic center and coordinating with the two manganese ions, while the remaining nucleotides form extensive interactions with surrounding residues, which resemble a product in post-cleavage state. Notably, the binding site of the RNA 5 nucleotide overlaps well with that of BXA in our crystal structure, suggesting that BXA inhibits EN activity by chelating metal ions and competing for substrate-binding site ( Supplementary Fig. S9 B).
Cap-snatching endonucleases have emerged as promising targets for antiviral drug development. We systematically evaluated the efficacy of three representative inhibitors against KASV and CCHFV ENs. Our results show that BXA exhibits the highest binding affinity and the most potent inhibitory activity among the three tested compounds (Fig. 5 and Supplementary Fig. S7 ). Structural analyses of EN-inhibitor complexes further reveal that all three inhibitors chelate the two catalytic metal ions in a similar manner . However , BXA uniquely forms additional stabilizing interactions with the enzyme (Fig. 6 ), which likely contribute to its superior inhibitory efficacy. Despite its effectiveness, BXA inhibits both KASV and CCHFV ENs with micromolar IC 50 values, markedly less potent than its nanomolar-level inhibition of influenza virus EN. By comparing the binding mode of BXA in IAV and KASV EN, we observed that the IAV EN features a relatively compact and narrow active site pocket, enabling BXA to nearly fully occupy the pocket and form extensive interaction networks with surrounding residues ( Supplementary Fig. S10 ), resulting in an interface area of 809.9 Å 2 with EN. By contrast, the active site pocket of KASV and CCHFV ENs is relatively large and quite open, resulting in limited residue contacts and only partial occupancy by BXA, with an interface area of 539.8 Å 2 . This structural distinction in the binding pocket likely explains BXA's higher efficacy against IAV. Notably, the ENs of nairovirus and other bunyavirus families form a common open active site pocket, posing a challenge for inhibitor design. Nevertheless, a previous study has demonstrated that BXA can effectively inhibit CCHFV infection in cells with a IC 50 at the micromolar level, and its sodium form significantly improves survival rates in a mouse model [ 43 ], highlighting its potential as a drug candidate for anti-CCHFV. Given the spatial vacancy within the BXA binding pocket, future optimization efforts should focus on modifying the BXA scaffold to extend into adjacent sub-pockets and establish additional stabilizing interactions with the pocket-lining residues. Based on the EN-inhibitor complex structural information, four potential spatial sites within the active-site pocket were identified to accommodate BXA modifications for improving the potency ( Supplementary Fig. S10 ). Notably, site 1 likely aligns with the RNA substrate binding cleft and offers the greatest potential for introducing additional chemical groups to increase the inhibitory efficacy. In addition, site 2 may accommodate an extra hydrophobic group, while the placement of small hydrophilic groups at sites 3 and 4 may allow polar interactions with the EN.
In summary, our work offers the first atomic-resolution insight into nairovirus ENs. A series of high-resolution structures of CCHFV and KASV ENs reveal a distinctive two-metal-ion binding mode critical for enzymatic function. This unique coordination involves multiple bridging water molecules with specific implications for efficient catalysis and adaptation to diverse substrates or environmental conditions. Importantly, this two-metal-ion mode is conserved across nairovirus ENs and is susceptible to inhibition by existing endonuclease-targeting compounds. These findings provide a critical foundation for developing novel, potent, and broad-spectrum antivirals targeting CCHFV and other related nairoviruses.
National Natural Science Foundation of China (U22A20336) to Z.H., the National Natural Science Foundation of China (32400129), Hubei Province Natural Science Foundation (2022CFB881), and Natural Science Foundation of Wuhan (2024040801020249) to W.K. Funding to pay the Open Access publication charges for this article was provided by National Natural Science Foundation of China (32400129).
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# The pandemic gap of respiratory viruses during the COVID-19 pandemic
Viviana Simon, Daniel Floda, Charles Gleason, Ana Silvia Gonzalez-Reiche, Alberto Paniz-Mondolfi, Emilia Sordillo, Peter Palese
## Abstract
Respiratory viruses typically exhibit seasonal patterns, posing ongoing public health challenges. The coronavirus disease 2019 pandemic altered these patterns dramatically, with many common respiratory viruses disappearing from circulation for extended periods. Here we analyzed over three million diagnostic tests from a metropol itan healthcare system in New York City over 7 years, tracking severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and eight common respiratory viruses before and during the pandemic. Following the initial SARS-CoV-2 wave in the spring of 2020, influenza A/B, respiratory syncytial virus, seasonal coronaviruses, parainfluenza, and human metapneumoviruses were absent for months to years, a phenomenon that we termed the "pandemic gap. " This disruption likely resulted from public health meas ures and SARS-CoV-2-induced antiviral immune responses resembling trained immunity. These findings suggest that the pandemic has temporarily reshaped respiratory virus epidemiology, potentially affecting immune development and increasing susceptibility to future respiratory virus epidemics.
IMPORTANCEIn this retrospective study using millions of diagnostic tests over 7 years from patients at the Mount Sinai Health System in New York City, we show that when the coronavirus disease 2019 pandemic began in early 2020, many but not all common respiratory viruses disappeared from circulation. We observed prolonged absences ranging from 10 months to nearly 3 years for viruses such as influenza A/B viruses, respiratory syncytial viruses, seasonal coronaviruses, parainfluenza, and human metapneumoviruses. This unusual decline in enveloped respiratory RNA virus activities may have been linked to public health interventions like social distancing, wearing of masks, and lockdowns. Additionally, the rapid spread of severe acute respiratory syndrome coronavirus 2 may have triggered broad, pathogen-agnostic immune responses and the imprinting of antiviral signatures in innate immune cells that conferred temporary protection against other viruses. This phenomenon resembles "trained immunity, " a form of enhanced innate immune memory observed after certain infections or vaccinations.
The Icahn School of Medicine at Mount Sinai has filed patent applications relating to SARS-CoV-2 serological assays, Newcastle disease virus-based SARS-CoV-2 vaccines, influenza virus vaccines, and influenza virus therapeutics that list P.P. as coinventor. V.S. is listed on the serological assay patent application as co-inventor. Mount Sinai has spun out a company, Kantaro, to market serological tests for SARS-CoV-2 and another company, CastleVax, to develop SARS-CoV-2 vaccines. P.P. is a co-founder and member of the scientific advisory board of CastleVax and is currently consulting for Avimex.
See the funding table on p. 6.
The Mount Sinai Health System (MSHS) is one of the largest health care providers of the New York City (NYC) metropolitan area, which encompasses regions from New York, Connecticut, and New Jersey. NYC itself has about 8.1 million people (18-23 million in the larger metropolitan area), making Greater New York the most densely populated metropolitan area in the United States. It is a confluence of diverse human populations with a broad range of underlying medical conditions and is highly reliant on public transportation (7). It is also one of the major entry ports for infectious pathogens in general, especially respiratory viruses, due to extensive travel of its resident population and millions of incoming visitors. Indeed, New York emerged as an early epicenter of the coronavirus disease 2019 (COVID-19) pandemic (8,9) after sporadic introductions of SARS-CoV-2 in the spring of 2020 (10). During the first 3 months of the pandemic, more than 200,000 people living in New York City were infected, 26% of whom required hospitalization (11). Nine percent of those hospitalized in NYC during March/April of 2020 died (11).
We leveraged our health system-wide precision surveillance infrastructure to map the changes in frequency of SARS-CoV-2 and eight common respiratory viruses (influenza A/B viruses, RSV, seasonal coronaviruses [sCoV], parainfluenza viruses [PIV], human metapneumovirus [HMPV], adenoviruses, and rhino/enteroviruses [RV/EVs]) over 312 weeks spanning 7 years (September 2019-August 2025). More than three million nucleic acid amplification tests, performed within the MSHS during this time were queried, yielding over 193,000 positive test results (Fig. S1).
The epidemiological data for influenza A/B viruses have been robust and predictable over the last several decades until the outbreak of SARS-CoV-2 (1). The seasonality of SARS-CoV-2 initially differed drastically from that of other RNA-containing respiratory viruses: SARS-CoV-2 circulated year-round with notable peaks (waves) both in winter as well as summer starting in 2020 (Fig. 1). After in-house molecular testing for SARS-CoV-2 became available in the MSHS (mid-March 2020 corresponding to week 28 in the data set shown in Fig. 1 and2), there was not a single week without positive SARS-CoV-2 test results for the next 5.5 years (284 weeks, March 2020-August 2025).
The first SARS-CoV-2 wave in NYC coincided with rapid decreases followed by a prolonged absence of influenza A virus (83 weeks), influenza B virus (151 weeks), RSV (49 weeks), sCoV (52 weeks), PIV (57 weeks), and HMPV (67 weeks) (Fig. 1 and2). We refer to this disruption of seasonal patterns as the "pandemic gap" of respiratory viruses. Of note, the pandemic gap was specific for enveloped respiratory viruses since a near-continuous circulation was observed for adenoviruses (non-enveloped DNA viruses) and RV/EV (non-enveloped RNA viruses) (Fig. 2). These distinctive transmission patterns could be due to prolonged survival on fomites or result from differences in susceptibility to environmental factors such as temperature and humidity (2).
When the circulation of these viruses resumed, the timing was offset by months. Remarkably, the Yamagata lineage of influenza B viruses never reemerged, while viral strains of the Victoria lineage reappeared only in the winter of 2023. The winter season of 2024-2025 marked a notable return to pre-pandemic patterns. Despite the high-severity influenza season (12), SARS-CoV-2 infections remained below 10% test positivity through 2025 (Fig. 1). In addition, surges for sCoV, HMPV, and RV/EV were noted in the 2024-2025 fall/winter months. For the latter viral pathogens, we lack solid pre-pandemic comparisons as the multiplex respiratory diagnostic platforms that included these tests (e.g., BioFire Respiratory Panel) were infrequently ordered at MSHS prior to 2020.
This study provides data spanning the COVID-19 pandemic tracking the dynamics of respiratory viruses. It was shown previously that large health care systems such as MSHS are well suited to determine the prevalence of SARS-CoV-2 in a manner representative of large metropolitan areas (13,14). It is likely that the 2-to 3-year absence of influenza A viruses (late winter 2020 to early winter 2022) and influenza B viruses (late winter 2020 to late winter of 2023) will shape the immune imprinting of children born in this period (15). Future studies will provide insights into the impact of the pandemic gap on the susceptibility to respiratory viral pathogens.
The pandemic gap of respiratory viruses, described here, coincided with the appearance of SARS-CoV-2. One explanation for this phenomenon is that public health interventions aimed at breaking the chain of transmission, such as reduced person-toperson contacts (e.g., social distancing and closing of businesses and schools) and physical barriers (the wearing of face masks) contributed to the prolonged absence of these different respiratory pathogens (6). Whether any of these measures alone was a major factor in interrupting the circulation of respiratory viruses or whether several conditions synergistically contributed to this epidemiological pattern remains unclear at present.
Another contributing factor to the pandemic gap of respiratory viruses observed could be the presence of a high proportion of subclinical SARS-CoV-2 infections. People with asymptomatic infections may have exhibited an interferon-mediated antiviral state in their respiratory tracts, thereby lowering the reproduction number of other respiratory viruses in the broader population. In this respect, we note that the initial Omicron wave in NYC (December 2021-February 2022, weeks 122-127 in Fig. 1 and2) also coincided with a temporary reduction in detection of other respiratory viruses. This reduction was most pronounced for influenza A infections, resulting in a highly atypical influenza A virus bimodal winter peak (Fig. 1).
Significant reductions in the circulation of common respiratory viruses have also been seen in other parts of the world during the COVID-19 pandemic (4,6,16,17). In general, infectious diseases that are transmitted through the air were most severely affected by the pandemic (varicella, pertussis, mumps, invasive H. influenzae, and influenza A/B viruses [17]). While non-pharmaceutical interventions during the SARS-CoV-2 pandemic may have interrupted the circulation of respiratory viruses, the induction of antiviral interferons may have contributed to the disappearance of respiratory viruses. The latter phenomenon may be part of what is known as trained immunity (18). Infection by certain viruses and bacteria can lead to a long-term increase in the activation of innate immune cells, resulting in protection against heterologous pathogens. Specifi cally, immunization with Bacillus Calmette-Guerin, measles virus (in the measles, mumps, rubella vaccine), or the poliovirus vaccine has been demonstrated to lead to immun ity against unrelated pathogens (19)(20)(21). The disappearance of unrelated enveloped respiratory viruses during the initial overwhelming wave of SARS-CoV-2 may, thus, be due to the role of trained immunity. Further studies will be necessary to identify the precise mechanism by which this immune protection is induced and which cell types are involved.
This study has several limitations. First, the initial numbers for SARS-CoV-2 testing are likely an underestimate of the total number of positive cases seen in the system, given the limited availability of diagnostic tests early in the pandemic. Although our pathogen surveillance framework is focused on the MSHS, which comprises several hospitals serving the NY metropolitan area, the data also reflect the impact of successive epidemiological waves of SARS-CoV-2 and the widespread public health interventions such as masking, social distancing, lockdowns, and vaccination rollout in the highly populated NYC area during the first years of the pandemic. Given that the scope and timing of these measures varied by region and country, our findings may not be representative of what happened in other regions of the United States or the world at large.
## References
1. Moriyama, Hugentobler, Iwasaki (2020) "Seasonality of respiratory viral infections" *Annu Rev Virol*
2. Leung (2021) "Transmissibility and transmission of respiratory viruses" *Nat Rev Microbiol*
3. Monto (2004) "Occurrence of respiratory virus: time, place and person" *Pediatr Infect Dis J*
4. Zhao, Zhang, Guo et al. (2025) "Characterising the asynchronous resurgence of common respiratory viruses following the COVID-19 pandemic" *Nat Commun*
5. Quintero-Salgado, Briseno-Ramírez, Vega-Cornejo et al. (2024) "Seasonal shifts in influenza, respiratory syncytial virus, and other respiratory viruses after the COVID-19 pandemic: an eight-year retrospective study in Jalisco" *Viruses*
6. Chow, Uyeki, Chu (2023) "The effects of the COVID-19 pandemic on community respiratory virus activity" *Nat Rev Microbiol*
7. Balk, Mcphearson, Cook et al. (2024) "NPCC4: concepts and tools for envisioning New York City's futures" *Ann N Y Acad Sci*
8. Gonzalez-Reiche, Hernandez, Sullivan et al. (2020) "Introductions and early spread of SARS-CoV-2 in the New York City area" *Science*
9. Bushman, Alroy, Greene et al. (2020) "Detection and genetic characterization of community-based SARS-CoV-2 infections -New York City" *Morbid Mortal Wkly Rep*
11. Hernandez, Gonzalez-Reiche, Alshammary et al. (2021) "Molecular evidence of SARS-CoV-2 in New York before the first pandemic wave" *Nat Commun*
12. Thompson, Baumgartner, Pichardo et al. (2020) "COVID-19 outbreak" *Morbid Mortal Wkly Rep*
13. O'halloran, Habeck, Gilmer et al. (2025) "Influenzaassociated hospitalizations during a high severity season -influenza hospitalization surveillance network, United States, 2024-25 influenza season" *Morbid Mortal Wkly Rep*
14. Stadlbauer, Tan, Jiang et al. (2021) "Repeated cross-sectional sero-monitoring of SARS-CoV-2 in New York City" *Nature*
15. Carreño, Mendu, Simon et al. (2021) "Longitudinal analysis of severe acute respiratory syndrome coronavirus 2 seroprevalence using multiple serology platforms"
16. Gostic, Bridge, Brady et al. (2019) "Childhood immune imprinting to influenza A shapes birth year specific risk during seasonal H1N1 and H3N2 epidemics" *PLoS Pathog*
17. Perofsky, Hansen, Burstein et al. (2024) "Impacts of human mobility on the citywide transmission dynamics of 18 respiratory viruses in pre-and post-COVID-19 pandemic years" *Nat Commun*
18. Brett, Rohani (2025) "Collateral effects of COVID-19 pandemic control on the US infectious disease landscape" *Science*
19. Netea, Ziogas, Benn et al. (2023) "The role of trained immunity in COVID-19: Lessons for the next pandemic" *Cell Host Microbe*
20. Benn, Fisker, Whittle et al. (2016) "Revaccination with live attenuated vaccines confer additional beneficial nonspecific effects on overall survival: a review" *EBioMedicine*
21. Domínguez-Andrés, Van Crevel, Divangahi et al. (2020) "Designing the next generation of vaccines: relevance for future pandemics" *mBio*
22. Ziogas, Netea (2022) "Trained immunity-related vaccines: innate immune memory and heterologous protection against infections" *Trends Mol Med*
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# Correction to: Current status of human adenovirus infection in China
Nai-Ying Mao, Zhen Zhu, Yan Zhang, Wen-Bo Xu
## Abstract
In the original publication, the author has missed to include the reference 20 "Fu Y, Tang Z, Ye Z, Mo S, Tian X, Ni K, et al. Human adenovirus type 7 infection causes a more severe disease than type 3. BMC Infect Dis. 2019;19:36" in the reference list.The original article has been corrected.
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# Complete genome sequence of a virulent duck enteritis virus isolated from Northern part of Bangladesh
Layla Yasmin, Md Siddique, Towhidul Islam, Mohammad Rahman, Md Rahman, Shuponkor Ghosh, Mohammad Ferdousur, Rahman Khan, Marzia Rahman, Md Rahman, Md Rahman
## Abstract
This study reports the complete genome sequencing of the duck enteritis virus strain YLBRDP_11 isolated from liver tissue of ducks during a local outbreak in Netrokona district, Northern part of Bangladesh. The viral genome consists of 161,633 bp encoding 74 proteins with a GC content of 44.9%. KEYWORDS complete genome, DEV, GC content, genome size, Illumina, NextSeq 2000 D uck viral enteritis (DVE), commonly known as Duck plague, is a severe and highly contagious disease of waterfowl, including ducks, geese, and swans (1). DEV is a member of the Orthohervisviridae family, subfamily Alphaherpesvirinae, genus Mardi virus, species Mardivirus anatidalpha1, also known as Anatid herpesvirus 1 (2). It is an enveloped virus with linear double-stranded DNA (dsDNA) genome consisting of 158, 091-162,175 bp (3-5).Duck plague is documented worldwide, including Bangladesh, and causes significant economic impact due to its high morbidity and fatality rates (6). During a natural outbreak in Netrokona district (24°47″ to 24°58″ N and 90°38″ to 90°50″E) of Bangladesh in 2023, we collected liver samples from dead ducks and preserved them at -80°C until further processing. Homogenization of liver samples was performed to prepare a 10% suspension in 1× phosphate-buffered saline and centrifuged at 4,000 rpm for 10 min (1). The supernatant was treated with gentamicin for sterility testing. Sterile samples were used for DNA extraction employing QIAamp DNA Mini Kit (7) (QIAGEN, Germany) as per the instructions of manufacturer and confirmation by PCR for DNA polymerase gene (446 bp) (8). The DEV-positive sample was propagated in 11-day-old embryonated duck eggs (EDEs) via chorioallantoic membrane (CAM) route up to 10th passage (9), followed by pathogenicity test in adult ducks to assess the virulence of the virus (8).Genomic DNA was extracted from the DEV-positive CAM of EDE using the previ ously mentioned kit. DNA concentration and quality were evaluated by NanoDrop One (Thermo Scientific, Canada) (10). A DNA library was constructed by NEBNext Ultra II DNA library prep kit for Illumina (NEB, USA) and sequenced on the NextSeq 2000 system, producing 2 × 150 bp paired-end reads at the Genomics Laboratory, Child Health Research Foundation, Bangladesh (11). The sequencing run produced 45,447,254 reads exhibiting an average quality score of Q33, indicating a base call accuracy of 99. 95%, assessed by BUSCO v5.12 (12).Genome assembly and annotation were performed using Geneious Prime (v2025.1.3). The raw FASTQ read files were imported as paired read sets. The reads underwent quality trimming and filtering via BBDuk (BBDuk Adapter/Quality Trimming v38.84) plugin of Geneious Prime, where the adapters and low-quality (30 nt) reads at both ends were trimmed, additionally discarding short reads (<30 nt) (13,14). After trimming the data set, error correction and normalization were done by BBNorm v38.84 (15). Genome assembly was performed by mapping normalized reads to reference genome of CHv
strain of Anatid alphaherpesvirus 1 (GenBank assembly number GCA_027935785.1). Reads were mapped using Geneious algorithm (medium-low sensitivity/fast settings), results were saved as consensus sequence used as the final genome.
Out of 45,447,254 generated reads, 37,155,624 were used for alignment. Using Geneious Prime (v2025.1.3), 421,887 normalized reads were aligned to the reference genome (GCA_027935785.1), generating a 161,633 bp consensus sequence covering 99.67% (161,633 of 162,175 bp) of the genome (Fig. 1). The complete genome of YLBRDP_11 spans 161,633 bp, encoding 74 genes, GC content of 44.9%. BLASTn analysis exhibited up to 99.99% nucleotide similarity with other DEV isolates in the NCBI database (16).
## References
1. Soma, Nazir, Rahman et al. (2018) "Isolation and molecular detection of duck plague virus for the development of vaccine seed" *Asian Australas J Biosci Biotechnol*
2. (2025) "The ICTV report on virus classification and taxon nomenclature"
3. Li, Liu, Kong (2006) "Characterization of the genes encoding UL24, TK and gH proteins from duck enteritis virus (DEV): a proof for the classification of DEV" *Virus Genes*
4. Wu, Cheng, Wang et al. (2012) "Complete genomic sequence of Chinese virulent duck enteritis virus" *J Virol*
5. Dandapat, Bindu, Sharma et al. (2022) "Complete genome sequence of a virulent duck enteritis virus (DEV/India/IVRI-2016) isolated from Southern India" *Microbiol Resour Announc*
6. Khan, Saha, Hossain et al. (2018) "Epidemiological investigation of recurrent outbreaks of duck plague in selected haor (wetland) areas of Bangladesh" *J Adv Vet Anim Res*
7. Qiagen (2006) "QIAamp DNA mini and blood mini handbook"
8. Ahamed, Hossain, Rahman et al. (2015) "Molecular characterization of duck plague virus isolated from Bangladesh" *J Adv Vet Anim Res*
9. Jahan, Rahman, Ahmed et al. (2021) "Molecular characterization of duck plague virus for determination of TCID 50" *Res Agric Livest Fish*
10. Popy, Hoque, Khan et al. (2024) "Draft genome sequencing of a multidrug-resistant Salmonella enterica subspecies enterica serovar Typhimurium strain isolated from chicken in Bangladesh" *Microbiol Resour Announc*
11. Biolabs (2018) "Ultra II DNA library prep kit for Illumina E7645/E7103"
12. Wu, Liu, Hu et al. (2022) "High-quality genome assembly and annotation resource of three Botryosphaeria pathogens causing Chinese Hickory canker" *Mol Plant Microbe Interact*
13. De Oliveira, Garrido, Padilla (2025) "Decontamination of DNA sequences from a Streptomyces genome for optimal genome mining" *Braz J Microbiol*
14. Karademir, Teber, Kulig et al. (2023) "Complete mitochondrial genome analyses of Forcipomyia pulchrithorax (Diptera: Ceratopogonidae): genome orientation and phylogenetic implications" *Kafkas Univ Vet Fak Derg*
15. Podowski, Forrester, Yaqub et al. (2025) "Genomic reconstruction of Bacillus anthracis from complex environmental samples enables high-throughput identification and lineage assignment in Pakistan" *Microb Genom*
16. Zhang, Schwartz, Wagner et al. (2000) "A greedy algorithm for aligning DNA sequences" *J Comput Biol*
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# Cell line bias in virus research: implications for viral propagation and biological interpretation
Ji-Young Kim, Bradley Pickering, Sara Cosby, Sharmada Swaminath
## Abstract
Cell lines are essential tools in virology for propagating viruses for characterization studies. However, reliance on a few historically popular linessuch as Vero, BHK-21, and MDCK-can introduce bias and obscure important aspects of viral biology, such as entry mechanisms and replication dynamics. A review of over 6,000 publications revealed that a small number of cell lines are used disproportionately, often due to historical precedence and general permissiveness for viral infection. Gene expression analysis showed that while these lines are enriched for pro-viral process genes, many underutilized cell lines from diverse tissue types also exhibit similar profiles. This review calls for a more strategic, molecularly informed approach to cell line selection, including the development of molecular databases for non-human cell lines, identification of virologically relevant traits, and broader use of biologically diverse panels. Such a data-driven strategy is especially vital for studying emerging and zoonotic viruses, where accurate modeling of host-virus interactions is important. Expanding and refining cell line use will improve reproducibility and yield more accurate insights into viral pathogenesis. KEYWORDS cell line use in virology, virus propagation, virus characterization, cell line expression, cell line bias Frontiers in Cellular and Infection Microbiology frontiersin.org 01
## Introduction
In virus research, cell lines serve as the primary platform for viral propagation, enabling the study and characterization of viruses through various downstream applications. Despite their important role, little attention is paid to the impact of the choice of cell line. There are known examples that highlight how the choice of cell line can bias experimental outcomes and hinder accurate understanding of viral pathogens.
For instance, early Human immunodeficiency virus (HIV) research relied heavily on established T-cell lines such as H9 and MT-4 (Pauwels et al., 1987;Popovic et al., 1984). These cell lines selectively supported the growth of T-cell-tropic HIV variants, while failing to propagate macrophage-tropic strains that are predominant during early infection. This cellular bias delayed the recognition of C-C chemokine receptor 5 (CCR5) as a key co-receptor and inadvertently shaped research focus toward T-celltropic variants (Littman, 1998). Only after diversifying cellular models did the field begin to capture the full spectrum of HIV transmission, tissue tropism, latency and pathogenesis.
SARS-CoV-2 research presents a more recent example of how cell line selection affects viral characteristics. During the early pandemic phase, Vero E6 cells were widely adopted for viral isolation due to their availability and general permissiveness. However, these cells lack Transmembrane serine protease 2 (TMPRSS2), which is present in human airway epithelial cells and affects viral entry pathways (Matsuyama et al., 2020). Additionally, propagation in Vero E6 cells induced mutations in the spike protein that altered properties relevant to immune escape and pathogenesis (Liu et al., 2021). Recognition of these limitations prompted researchers to adopt more physiologically relevant systems, including human airway and intestinal epithelial cell lines, which better preserved viral characteristics.
In our own work with Rift Valley fever virus, we observed that a 78 kDa glycoprotein can only be observed in virus propagated in the mosquito-derived C6/36 cells and not in those grown in mammalian Vero E6 cells (Weingartl et al., 2014). This glycoprotein is suspected to play a role in vector-host transmission. This observation highlights that cellular environments can influence viral protein expression and potentially affect virus behaviors that could be important for zoonotic transmission.
These examples demonstrate that cell lines can introduce systematic biases and obscure important biological aspects of viral behavior. While testing multiple virus-cell line combinations could address these limitations, such approach is often impractical and costly. An optimal strategy should balance the efficiency of standardized systems with sufficient biological diversity to capture an array of virus behavior.
In this review, we examine commonly used cell lines for virus propagation and analyze their gene expressions, and compare them to other well established cell lines for permissiveness to viral infection. We argue that strategic selection of cell lines-based on both their ability to support virus growth and biological diversitycan improve the accuracy and relevance of virology studies without significantly increasing operational burden.
## Results
## Popular cell lines of choice for growing viruses
The American Type Culture Collection (ATCC) catalogs over 4000 cell lines commercially available for research. However, their utilization and preference is likely not equally distributed. This was true for cell lines being used to grow viruses. Through a literature review, we identified 625 unique cell lines used to propagate 518 virus species. Among these, Vero cell line was most frequently used, while influenza virus was the most extensively studied (Figure 1B). For this analysis, all sublineages of Vero cell lines such as E6 and 76 were treated as one grou A more detailed analysis revealed virusspecific preferences for certain cell lines. For instance, MDCK cells showed strong association with influenza research, while Vero cells demonstrated broader utilization across diverse virus species, indicating their general permissiveness for viral propagation (data not shown).
We further examined studies that directly compared virus amplification efficiency across two or more cell lines. While such comparative analyses were uncommon and often involved limited cell line selections, several patterns emerged from available data. Cell lines such as Vero, BHK-21, and C6/36 consistently produced higher viral yields in more than half of the comparative studies in which they were evaluated (Figure 1C). Interestingly, HeLa cells consistently showed poorer performance across all eight publications that included this cell line in comparative analyses.
## Attributes of the popularly used cell lines
To assess whether those popularly used cell lines truly provide superior support for viral growth, we analyzed expressions of genes associated with viral processes in Vero E6, BHK-21 and MDCK. Using publicly available RNA expression datasets, we compared Vero E6, BHK-21, and MDCK cells to other well established human kidney cell lines. Kidney datasets were used as comparators because all three of the popularly used cell lines were also originated from kidneys in non-human organisms. C6/36 cells were excluded from this analysis due to difficulties in mapping Aedes albopictus gene expression data to human orthologs.
We found that popular cell lines were enriched for genes involved in the positive regulation of viral processes, such as viral entry and release (Figure 2A). In contrast, we did not observe any statistical difference in enrichment for genes associated with negative regulation of viral growth between the popular and comparator cell lines. This observation may reflect the fact that the expression dataset used here was derived from baseline, unstimulated conditions, where antiviral responses were not engaged and therefore not detectable.
## Discussion
Despite the widespread use of established cell lines in virus research, our understanding of how these systems influence virus characteristics remains limited. Addressing this knowledge gap presents several opportunities to strengthen the rigor, efficiency, and biological relevance of future studies.
## Expanding molecular datasets for nonhuman cell lines
A significant limitation in current approaches is the lack of comprehensive molecular datasets for non-human cell lines, such as those derived from pigs, birds, or insects, which are frequently used for propagating zoonotic viruses. In other fields, resources like the Connectivity Map (cMAP), Human Protein Atlas (HPA), and Cancer Genomic Atlas Program (TCGA) have propelled research by providing accessible, queryable molecular datasets. A similar infrastructure for virology would enable researchers to select cell lines based on biological suitability for the virus of interest. Such databases would be particularly valuable for zoonotic pathogens, where species-specific differences can significantly impact virus behavior and experimental outcomes.
## Characterizing cell line attributes that promote viral growth
Characterizing the attributes of cell lines that influence viral growth is essential for more rational experimental design. Cell lines are often selected based on precedent or convenience rather than on traits that make them suitable for a specific virus. Developing a classification system that summarizes these traits would help researchers choose cell lines aligned with their experimental goals. Some of these attributes are known, including entry receptor expression, tolerance to cell-cycle subversion mechanisms, and absence of interferon-I response. For instance, Vero cells, which lack a type I interferon response, have historically been used in virology because this deficiency contributes to their permissiveness (Emeny and Morgan, 1979). Similarly, some retroviruses such as HIV-1 are known to arrest cell cycle in the G2/M phase (See review in Fan et al., 2018), and cell lines that can tolerate cellular stress or burden from this prolonged arrest would be ideal for growing these viruses.
In the present work, we were unable to identify datasets suitable for evaluating these cellular attributes. The expression dataset used here was derived from unstimulated, baseline cell lines, which limits interpretation-particularly because type I interferon activity is a well-characterized factor in viral infection and growth. Addressing these gaps by moving away from sporadic, incomplete datasets toward more systematic and accessible data-collection practices would enable researchers to match cell line selection with specific research aims more effectively, reduce trial-and-error, and ultimately yield more accurate biological insights.
## Leveraging biological diversity through multi-cell line approaches
As described above, optimal virus-cell line pairing depends on many factors and often requires engineering the host cell. However, when working with a poorly characterized virus with the goal of simply to amplify the virus and establish basic characteristics, starting with cell lines that are generally permissive to a broad range of viruses is a practical first ste For this reason, the field has largely converged on a few such cell lines, which has led to bias and inaccurate experimental outcomes.
One solution to this problem is identifying additional cell lines that are generally permissive for virus growth. Especially if these cell lines span different tissue types or species, researchers can select cell lines that closely match the virus's likely biological target tissue types and reduce artifacts caused by mismatched tropism at the outset. Better yet, researchers may also choose to use multiple biologically diverse set of cell lines for those initial characterization in order to increases the probability of detecting infection and helps uncover unexpected viral phenotypes or host-specific behaviors earlier on.
To this end, we conducted an initial analysis identifying several underutilized cell lines with gene expression profiles similar to those of popular cell lines (Figure 2B). We selected one cell line that exhibited the most favorable combination of attributes: overall expression similarity to the popular cell lines, comparable receptor coverage, confirmed commercial availability, and documented use in the literature.
By incorporating a biologically diverse panel of permissive cell lines rather than relying on a single default cell line, researchers can more reliably capture early viral behaviors and avoid overlooking critical aspects of viral biology.
## Conclusion
Choosing cell lines to grow viruses is often the first decision made in studying viruses. While historically popular cell lines such as Vero, BHK-21 and MDCK have enabled critical discoveries, reliance on a limited set of models introduces bias and may obscure important aspects of viral biology. This concern is especially relevant for emerging and zoonotic viruses, where host-specific factors are poorly understood or unknown. To address these limitations, we propose a more systematic and diversified approach to cell line selection based on molecular characterization and biological relevance. We advocate for building molecular databases for cell lines from diverse organisms, understanding virologically relevant attributes, and encouraging the use of biologically diverse panel of cell lines. Such efforts will not only improve the reproducibility and interpretability of virology studies but also enhance our ability to identify unknown viral phenotypes, better understand viral pathogens, and ultimately prepare more effectively for emerging infectious diseases.
## Methods
## Literature review
All publications included in the literature review were retrieved from PubMed on June 23, 2023, using the search terms: cell line AND virus AND (propagation OR amplification). This search yielded 6553 articles. Abstracts were screened using the PubTator tool to identify direct mentions of both a virus and a cell line, resulting in 2024 relevant publications. These abstracts were then further analyzed using ChatGPT (models GPT-3.5, GPT-4, and GPT-4o) to assess whether the primary focus of each article involved the use of cell lines for virus amplification. This process identified 1044 relevant publications. Among these, 141 publications mentioned two or more cell lines and were manually reviewed. Of those, 47 were confirmed to involve direct comparisons of virus amplification across multiple cell lines. An overview of the literature review and screening process is shown in Figure 1A.
## Use of external and reference datasets
For enrichment analysis, gene sets were obtained from the C5 collection of the Molecular Signatures Database (MSigDB) from the Gene Set Enrichment Analysis (GSEA) resource. From the 16228 total gene sets in this collection, 52 virus-related gene sets (by selecting gene set names containing virus or viral) containing a total of 710 genes were selected for downstream analysis.
Cell line expression data were sourced from the Human Protein Atlas (HPA; https://www.proteinatlas.org/) Specifically, the dataset labeled "RNA expression in 1206 cell lines" was downloaded, and normalized expression values (nTPM) were used for all subsequent analyses.
## References
1. (1979) "RNA-seq datasets for three popular cell lines (Vero E6, BHK-21, and MDCK) were retrieved from the NCBI Gene Expression Omnibus (GEO) under the following accession numbers: GSE178942, GSE93045, and GSE290599, respectively. Only samples labeled as controls were included to ensure baseline expression comparisons. Raw sequence data were downloaded from the Sequence Read Archive"
2. Fan, Sanyal, Bruzzone (2018) "Breaking bad: how viruses subvert the cell cycle" *Front. Cell. infection Microbiol*
3. Littman (1998) "Chemokine receptors: keys to AIDS pathogenesis?" *Cell*
4. Liu, Vanblargan, Bloyet et al. (2021) "Identification of SARS-CoV-2 spike mutations that attenuate monoclonal and serum antibody neutralization" *Cell Host Microbe*
5. Matsuyama, Nao, Shirato et al. (2020) "Enhanced isolation of SARS-CoV-2 by TMPRSS2-expressing cells" *Proc. Natl. Acad. Sci*
6. Pauwels, De Clercq, Desmyter et al. (1984) "Detection, isolation, and continuous production of cytopathic retroviruses (HTLV-III) from patients with AIDS and pre-AIDS" *J. Virological Methods*
7. Valero-Rello, Baeza-Delgado, Andreu-Moreno et al. (2024) "Cellular receptors for mammalian viruses" *PloS Pathog*
8. Weingartl, Zhang, Marszal et al. (2014) "Rift Valley Fever Virus Incorporates the 78 kDa Glycoprotein into Virions Matured in Mosquito C6/36 Cells" *PloS One*
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# Complete genome sequence of a lumpy skin disease virus from a calf in the mid-northeastern region of Bangladesh
Anandha Mozumder, Zakaria Al Noman, Roni Mia, S Nazmul, Hasan Siam, M Rahman, Mohammad Imtiaj, Uddin Bhuiyan, M Hossain, Sharmin Akter, Sukumar Saha, Tofazzal Islam, Md Golzar Hossain, Md Hossain
## Abstract
Lumpy skin disease virus (LSDV) is currently causing significant mortality in young calves and presenting with distinct clinical features in Bangladesh. Here, we report the complete genome sequence of an LSDV strain from a calf in the mid-northeastern region of the country.
L umpy skin disease virus (LSDV) is a highly contagious pathogen responsible for lumpy skin disease, which affects cattle and water buffaloes of all ages. The virus is transmitted primarily through arthropod vectors and causes severe infections character ized by fever and multifocal cutaneous nodules (1). LSDV is a brick-shaped, enveloped double-stranded DNA virus belonging to the Capripoxvirus genus within the Poxviridae family. It measures approximately 293-299 nm in length and 262-273 nm in width, with a surface covered in tubular structures (2). The viral genome is approximately 151 kbp and encodes 156 proteins (3).
LSDV was first reported in Bangladesh in 2019 and has since become a significant burden on the livestock sector (4). Recently, distinct clinical and pathological features have been observed in affected cattle in Bangladesh (5). In this study, we performed whole-genome sequencing of the LSDV/Fulbaria-25-MGH-BD, obtained from a field outbreak in Fulbaria, Mymensingh, Bangladesh (24.6250° N, 90.2667° E).
A calf on the farm exhibited characteristic LSDV signs, including large nodules on various parts of the body. A sample from the necrotic skin nodule was collected using sterile surgical instruments and immediately transported to the laboratory under appropriate cold chain conditions. Viral inoculum was prepared by tissue homogeniza tion following our previously published protocol and stored at -80°C (5). Viral DNA was extracted using the TIANamp Virus DNA/RNA Kit (Tiangen, China) per the manufacturer's instructions. Next-generation sequencing was performed using the Illumina NovaSeq X Plus platform. Metagenomic libraries were prepared following the iNextEra protocol, including DNA tagmentation with Illumina bead-linked transposomes, adapter ligation, and limited-cycle PCR for indexing (6). The libraries were purified with AMPure XP beads, quantified using Qubit Flex, and sequenced to generate 2 × 150 bp paired-end reads at Novogene.
A total of 31 million reads were generated. Quality control of the FASTQ files was performed using FastQC (v0.11.6) (7). Adapter trimming and low-quality read removal were performed using Trimmomatic (v0.39) (8), employing a sliding window size of 4, a minimum average quality score of 20, and a minimum read length of 40 bp. Host DNA was depleted by aligning quality-filtered reads to the Bos taurus reference genome (ARS-UCD2.0) using BBMap (9), and the remaining unmapped reads were aligned to the LSDV reference genome (NC_003027; genome size: 150,773 bp) using BWA-MEM v0.7.17. Sorting and indexing were performed with SAMtools v1.12 (10), and the consensus genome was generated using BCFtools v1.12 and VCFtools v4.1 (11). The final consensus was derived from the de novo assembly of all host-filtered reads using Unicycler v 0.5.1, with the reference mapping serving as a validation guide to confirm genuine singlenucleotide polymorphisms (SNPs). While highly consistent with the reference-based mapping, which showed deep coverage (789×) with 856,749 reads mapped to the viral genome, covering more than 99.95% of the reference genome, minor differences were observed. These were resolved by manually inspecting each variant in a genome viewer, and genome annotation was completed with Prokka (v1.14.6) using default parameters (12). All tools were executed with default parameters in the Linux operating system, unless otherwise specified. The completeness of the assembled genome was confirmed by the presence of terminal repeat structures and raw read evidence spanning the contig ends. Genome annotation predicted 156 open reading frames (ORFs), encompassing the full complement of genes typical for an LSDV strain.
The final assembly resulted in a single contig of 150,723 nucleotides, representing a complete LSDV genome (LSDV/Fulbaria-25-MGH-BD). The assembled genome shares 99.90% and 99.89% identity with the reference genome (NC_003027) and a previously reported Bangladeshi strain (PP756497.1), respectively, as performed using the BLASTn. The GC content was 25.90%. This genome provides critical genetic information from a recent LSDV outbreak in northeastern Bangladesh and may contribute to the develop ment of effective vaccines and control strategies.
## References
1. Sanz-Bernardo, Haga, Wijesiriwardana et al. (2020) "Lumpy skin disease is characterized by severe multifocal dermatitis with necrotizing fibrinoid vasculitis following experimental infection" *Vet Pathol*
2. Makalo, Settypalli, Meki et al. (2024) "Genetic characterization of lumpy skin disease viruses circulating in lesotho cattle" *Viruses*
3. Kumar, Venkatesan, Kushwaha et al. (2023) "Genomic characterization of lumpy skin disease virus (LSDV) from India: circulation of Kenyan-like LSDV strains with unique kelch-like proteins" *Acta Trop*
4. Das, Chowdhury, Akter et al. (2021) "An updated review on lumpy skin disease: a perspective of Southeast Asian countries" *J Adv Biotechnol Exp Ther*
5. Mou, Hasan, Mozumder et al. (2025) "Distinct amino acid substitutions in the EEV glycoprotein and DNA-dependent RNA polymerase of lumpy skin disease virus identified in wetland areas of Bangladesh" *Res Vet Sci*
6. (1016)
7. Jones, Stanley, Ferguson et al. (2023) "Cost-conscious generation of multiplexed short-read DNA libraries for whole-genome sequencing" *PLoS One*
8. De Sena Brandine, Smith (2019) "Falco: high-speed FastQC emulation for quality control of sequencing data" *F1000Res*
9. Bolger, Lohse, Usadel (2014) "Trimmomatic: a flexible trimmer for Illumina sequence data" *Bioinformatics*
10. Bushnell (2014) "BBMap: a fast, accurate, splice-aware aligner"
11. Li, Durbin (2009) "Fast and accurate short read alignment with Burrows-Wheeler transform" *Bioinformatics*
12. Danecek, Mccarthy (2017) "BCFtools/csq: haplotype-aware variant consequences" *Bioinformatics*
13. Seemann (2014) "Prokka: rapid prokaryotic genome annotation" *Bioinformatics*
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# Complete genome sequence of a Capillovirus infecting Citrus medica L. in China
Yaqin Wang, Yuheng Zhang, Shi Wu, Xiaojun Zhou, Xiaochan He, Xueping Zhou, Zhanqi Wang, Liyan Zhu
## Abstract
Apple stem grooving virus (ASGV) can infect various fruit and herbaceous plants. Here, we report an isolate of ASGV from Citrus medica in Jinhua City, Zhejiang Province, China, and reveal that it belongs to the genus Capillovirus within the family Betaflexiviridae.
the primer pairs listed in Table 1. The results showed that the complete genome of ASGV-JH comprised 6,515 nt, including a 27-nt poly(A) tail, and had a GC content of 40.92%. Comparative analysis revealed that it exhibited the highest nucleotide sequence similarity of 94.6% with CTLV-TL (GenBank accession number MZ330115). ORFfinder prediction showed that the ASGV-JH genome consisted of two overlapping ORFs, with the 5′-untranslated region (5′-UTR) and the 3′-UTR measuring 28 and 142 nt in length,
## TABLE 1 List of primers used in this study
## Primer name
Primer sequence Purpose
respectively (Fig. 1C). ORF1 (from 29 to 6,346) encodes a polyprotein with a molecular weight of 241.7 kDa, whereas ORF2 (from 4,780 to 5,742) encodes a movement protein with a molecular weight of 36.2 kDa (Fig. 1C).
$$ASGV-F 5′-ATGAGTTTGGAAGACGTGCTT-3′ ASGV detection ASGV-R 5′-CCCTTTTTGTCCTTCAGTACG-3′ Actin-F 5′-CAGACCGTATGAGCAAGGAA-3′ Internal control Actin-R 5′-GCTTAGGGATGCGAGGATAG-3′ UPM 5′-CTAATACGACTCACTATAGGGC-3′ 3′/5′-RACE ASGV-5PF 5′-CAGCGCTTAATTTCCGCGCATTACGTCAATG-3′ 5′-RACE ASGV-5PR 5′-CACTGCTGAAGCTGCGTTTG-3′ ASGV-F1F 5′-TTTGATAGGGGGAGGGCCTG-3′ F1 amplification ASGV-F1R 5′-GCCATCTCTTTGAAATCAGAAG-3′ ASGV-F2F 5′-CAATTTCTGCACATCTTGGG-3′ F2 amplification ASGV-F2R 5′-TTCTGGTTGGCATGTTTATCAG-3′ ASGV-F3F 5′-TTTGGACAAGACACATGAAATAG-3′ F3 amplification ASGV-F3R 5′-GCTAGAATCACGTGGTCTTGG-3′ ASGV-F4F 5′-TGCTTTCCTGAGGAGTTGTGG-3′ F4 amplification ASGV-F4R 5′-GATACACTCCTACCCGGTGG-3′ ASGV-3PF 5′-ATGAGTTTGGAAGACGTGCTT-3′ 3′-RACE ASGV-3PR 5′-TGAGAGGACAAACTCTAGACTCTAGAAAAACC-3′$$
## References
1. Canales, Morán, Olmos et al. (2021) "First detection and molecular characterization of apple stem grooving virus, apple chlorotic leaf spot virus, and apple hammerhead viroid in loquat in Spain" *Plants (Basel)*
2. Shokri, Shujaei, Gibbs et al. (2023) "Evolution and biogeography of apple stem grooving virus" *Virol J*
3. Bhardwaj, Awasthi, Prakash et al. (2017) "Molecular evidence of natural occurrence of apple stem grooving virus on bamboos" *Trees (Berl West)*
4. Zhao, Hao, Liu et al. (2012) "Complete sequence of an apple stem grooving virus (ASGV) isolate from China" *Virus Genes*
5. Xuan, Zhang, Li et al. (2022) "Apple stem grooving virus is associated with leaf yellow mottle mosaic disease on Citrus grandis cv" *Huangjinmiyou in China. J Integr Agric*
6. Suman, Rishi, Dhir et al. (2023) "Molecular characteri zation and variability analyses of apple stem pitting virus and apple stem grooving virus isolates infecting apple in Kashmir" *India. Indian Phytopathol*
7. Wang, Song, Wang et al. (2020) "Discovery and characterization of a novel ampelovirus on firespike" *Viruses*
8. Li, Wu, Liu et al. (2023) "Identification and Molecular Characterization of a Novel Carlavirus Infecting Chrysanthemum morifolium in China" *Viruses*
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# Correction to "Application of Nested Multiplex Polymerase Chain Reaction Respiratory and Pneumonia Panels in Children With Severe Community-Acquired Pneumonia"
Yen Ty, Chen Jf, Lu Cy, Wang Wu, Lu Cc, Huang Fl, Chang Lm, Ting-Yu Yen, Jian-Fu Chen, Chun-Yi Lu, En-Ting Wu, Ching-Chia Wang, Phd² Frank, Leigh Lu, Li-Min Huang, Luan-Yin Chang
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# Bact eriophag e deplo ys a RecA-dependent nuclease t o inhibit Staphylococcus aureus replication and promote phag e propag ation
Qi Xu, Neng Xu, Li Tang, Xindi Huang, Wei Tang, Mengke Li, Yangbo Hu, Yong Zhang, Shiyun Chen
## Abstract
B acteriophages ha v e e v olv ed div erse strategies to manipulate host processes, y et the molecular mechanisms emplo y ed b y phage-encoded effector proteins remain poorly understood. Here, we identify Gp16, an early -e xpressed protein from Staphylococcus aureus phage NM1, as a RecA-dependent nuclease that plays a dual role in host inhibition and phage propagation. Gp16 is rapidly expressed upon infection, and its o v ere xpression alone is sufficient to inhibit bacterial growth where deletion of gp16 se v erely impairs phage DNA replication, progeny production, and host cell lysis, underscoring its essential role in the phage life cycle. Str uct ural modeling predicts Gp16 is a nuclease, and its o v ere xpression induces DNA condensation in vivo . Biochemical and cellular analyses show that Gp16 interacts with the host RecA protein to inhibit growth, and functions as a nickase in vitro , requiring the catalytic cysteine C181 for DNA cleavage. RecA further enhances its cleavage activity. During phage infection, R ecA activ ation is required f or efficient phage propagation, while Gp16 concurrently suppresses host DNA replication and promotes DNA condensation, thereby facilitating phage replication. Together, these findings reveal a previously unrecognized strategy in which a phage-encoded nuclease exploits the host RecA machinery to couple host suppression with productive phage propagation.
## Introduction
Bacteria and their phages engage in a continuous evolutionary arms race, in which host defense systems evolve to restrict phage infection, while phages develop countermeasures to overcome these barriers [ 1 ]. Bacteria employ various nucleic-acid-based immune systems, including restrictionmodification (RM) [ 2 ], CRISPR-Cas [ 3 ], Gabija [ 4 ], and cyclic oligonucleotide-based anti-phage signaling systems (CBASS) [ 5 ], to degrade foreign DNA or trigger abortive infection responses. In response, phages have evolved diverse strategies to evade or suppress these defenses, such as genome modification, anti-CRISPR proteins [ 6 , 7 ], and nucleases that directly target host defense components [ 8 , 9 ]. These molecular conflicts continuously fuel the diversification of both bacterial and phage genomes, shaping their coevolutionary landscape.
Beyond mere counter-defense, bacteriophages have evolved diverse mechanisms to reprogram host physiology during infection, ensuring efficient replication within bacterial cells [ 10 , 11 ]. A major target of this is reprogramming host nucleic acid metabolism. By degrading or modifying bacterial DNA and RNA, phages redirect nucleotide pools toward their own genome synthesis while suppressing host replication, transcription, and repair systems [ 12 -14 ]. Such interference not only conserves energy for phage propagation but also dis-rupts cellular defenses, allowing the phage to dominate the host's molecular machinery [ 15 ]. However, it remains unclear whether these observed alterations in bacterial physiology result directly from phage-encoded effectors, and how these changes ultimately favor the phage.
Phage-encoded nucleases play pivotal roles in these processes by mediating nucleic acid degradation, recombination, and genome processing [ 16 ]. Among them, HNH endonucleases are particularly widespread and functionally diverse. In many double-stranded DNA (dsDNA) phages, they act in concert with the large terminase subunit (TerL) to introduce precise nicks or double-stranded breaks during genome packaging, ensuring accurate DNA encapsulation and virion assembly [ 17 , 18 ]. The HNH-type nuclease gp74 of bacteriophage HK97 exemplifies this role by promoting site-specific cleavage during head maturation [ 19 , 20 ]. Beyond these packaging functions, certain HNH nucleases exploit host recombination machinery. For instance, the Ref protein of bacteriophage P1, a RecA-dependent HNH endonuclease, targets D-loop structures formed by RecA and introduces directed doublestrand breaks. This represents a host-assisted mechanism of phage DNA processing, although its physiological roles are still poorly characterized [ 21 -23 ]. Phage-encoded endonucleases can also participate in molecular conflicts. For example, ICP1 phages deploy a chimeric nuclease that counteracts Vibrio cholerae phage-inducible chromosomal islands, reflecting their adaptive role in host-phage coevolution [ 24 ]. Moreover, thermophilic phages such as Geobacillus virus E2 encode highly stable HNH endonucleases (GVE2 HNHE) with metal-dependent double-stranded DNA cleavage activity, emphasizing the evolutionary versatility of these enzymes across diverse ecological niches [ 25 ]. However, the substrate specificity, timing of action, and regulatory mechanisms of many nucleases remain poorly characterized.
Here, we characterize the Staphylococcus aureus phage protein Gp16, which promotes phage infection by interacting with the host protein RecA and concurrently inhibits host DNA replication. Our findings demonstrate that Gp16 possesses DNA cleavage activity, leading to the arrest of chromosomal replication by obstructing replication fork progression and suppressing the transcription of genes associated with replication. The elucidated mechanism offers new insights into the molecular strategies employed by phages to manipulate and exploit host cells. Our results uncover a previously unrecognized mechanism by which a phage protein modulates host DNA metabolism, shedding light on phage-host evolutionary dynamics and underscoring the potential of phage proteins as novel antibacterial targets.
## Materials and methods
## Bacterial strains and growth conditions
Bacterial strains used in this study are listed in Supplementary Table S1 . Staphylococcus aureus was cultured in tryptic soy broth (TSB, Difco) with shaking or on tryptic soy agar (TSA, Difco) at 37 • C. Esc heric hia coli strains were grown in Luria-Bertani (LB) medium and incubated at 37 • C for amplifying plasmids or at 20 • C for protein expression. Erythromycin (10 μg ml -1 ) or chloramphenicol (10 μg ml -1 ) was supplemented to the medium when needed for S. aureus and ampicillin (100 μg ml -1 ) or kanamycin (50 μg ml -1 ) for E. coli . To induce gene expression in S. aureus , 0.1 mM isopropyl β-d -1-thiogalactopyranoside (IPTG) or 10 ng ml -1 anhydrotetracycline (aTc) were added to the cultures.
## Plasmid constructions
All plasmids used in this study are listed in Supplementary Table S1 , and all primers and synthesized gene sequences are listed in Supplementary Table S2 . Genes were cloned into plasmids using either a ClonExpress II one-step cloning kit (Vazyme, China) or restriction enzymes (NEB, USA). The gene expression plasmid pTAS in S. aureus contains an aTcinducible promoter. For protein expression and purification in E. coli , genes were cloned into pET28a or pET21 vector. Bacterial two-hybrid (BATCH) assays were performed using either a pUT18 or pKT 25 vector [ 26 ]. The gene knockout plasmid pSA-IPTG contains IPTG-inducible Cas9 and two Bsa I sites for sgRNA cloning. For gene complementation, the plasmid pCI was used [ 27 ].
## Mutant construction and complementation of recA in S. aureus
The CRISPR-Cas9 system was used to construct a recA deletion mutant. First, the single strand of small guide RNA (sgRNA) was synthesized, and the polymerase chain reaction (PCR) products were ligated to the pSA-IPTG vector at the Bsa I site by T4 DNA ligase. Next, after annealing, 1 kb upstream and downstream fragments of the recA ORF were amplified from S. aureus RN4220 genomic DNA (gDNA) and then subcloned into the pSA vector at the EcoR I and BamH I sites. The resulting deletion plasmid pSA-IPTG-recA was subsequently used to transform RN4220. Cells were plated on TSA with 1 mM IPTG, and the correct deletion colonies were screened. For gene complementation, recA with its 1 kb upstream fragment was cloned into the plasmid pCI and then used to transform S. aureus . The complementary strains were selected by plating on TSA containing 10 μg ml -1 chloramphenicol.
## Knockout of gp16 in the NM1 phage
The gp16 -deficient strain NM1 gp16 was generated by CRISPR-Cas9 system. As described above, the Cas9 and sgRNA expression was induced by IPTG from the spacregulated promoter system. Specifically, 10 μl NM1 was mixed with 100 μl RN4220 transformed with pSA-IPTG-gp16 and incubated at room temperature for 10 min. Next, 5 ml of 0.7% top agar was added to the mixture, and then the suspensions were plated on a TSA plate containing 1mM IPTG. After incubation at 37
## Plaque and efficiency of plating assay
Plaque assays were performed by mixing 100 μl of log-phase S. aureus culture (OD 600 = 0.6) with 10 μl of diluted phage suspension and 5 ml of 0.7% TSA top agar, overlaying the mixture onto TSA plates, and incubating overnight at 37 • C for plaque formation. For efficiency of plating (EOP) determination, 100 μl of log-phase bacterial culture (OD 600 = 0.6) was mixed with 5 ml of 0.7% TSA top agar and poured onto TSA plates. Two microliters of serial 10-fold phage dilutions were spotted on the double-layer agar plates and then incubated for 18 h at 37
## Phage infection assay in liquid culture
Phage liquid infection was performed as described [ 28 ]. Overnight cultures of S. aureus were diluted 1:100 in fresh TSB containing a final concentration of 5 mM CaCl 2 to OD 600 of 0.2, and 200 μl of cells were added to each well of a 96-well plate. NM1 WT or NM1 gp16 phages were immediately added to each well at the indicated multiplicity of infection (MOI) of 0.01, 1, and 10, respectively. After phage infection, growth was measured every 15 min at 37 • C using a shaking plate reader (Biotek, USA). The growth curve experiment was replicated at least three times independently.
For quantification of plaque forming unit (PFU) and colony-forming unit (CFU), overnight cultures were diluted to an OD 600 of 0.1 in 20 ml of TSB and incubated at 37 • C with shaking (200 rpm) for 2 h. Phage infection was initiated at an MOI of 0.01 in the presence of 5 mM CaCl 2 . At the indicated time points, 200 μl of the samples were collected and centrifuged at 12 000 × g for 2 min at 4 • C. The supernatant was used for phage titration by plaque assay. The cell pellet was washed once with phosphate-buffered saline (PBS), resuspended in 150 μl of TSB, serially diluted 10-fold, and plated on TSA. Plates were incubated overnight at 37 • C, and colonies were counted the following day.
## Phage lysogens generation
NM1 and NM1 gp16 lysogens were obtained as described [ 29 ]. Briefly, phages were spotted onto 0.7% top agar overlays seeded with S. aureus RN4220 and incubated overnight at 37 • C. Material from the center of a lysis zone was collected with a sterile inoculation loop and streaked onto TSA plates. After 12 h of incubation at 37 • C, colonies were screened for prophage integration by PCR using primer pairs attL -F/ attL -R and attR -F/ attR -R to amplify the attL and attR junctions, respectively. A verified lysogen was retained in SM buffer (50 mM Tris-HCl, pH 7.5, 10 mM MgSO 4 , 200 mM NaCl) for subsequent experiments.
## Construction of NM1-Erm or NM1 gp16-Erm
The NM1-Erm R and NM1 gp16 -Erm R mutants were constructed using a CRISPR-Cas9-mediated allelic exchange system. A single-stranded sgRNA was synthesized and cloned into the pSA-IPTG vector at the BsaI site using T4 DNA ligase. The ∼1-kb homology arm flanking the NM1 integration site was amplified from NM1 gDNA using primer pairs ermup-F/ erm -up-R and erm -dn-F/ erm -dn-R. The ∼1.25 kb ermC resistance cassette was amplified from plasmid pTAS with primers erm -F/ erm -R. The three fragments ( ∼3.25 kb in total) were assembled by overlap PCR using external primers ermup-F and erm -dn-R, and attB adapter sequences were added to enable directional cloning into pSA-IPTG. For mutant construction, 10 μl of NM1 phage lysate was mixed with 100 μl of S. aureus RN4220 cells harboring pSA-IPTG -erm , and the mixture was incubated at room temperature for 10 min. The mixture was then overlaid with 5 ml of 0.7% top agar and poured onto TSA plates containing 1 mM IPTG. After incubation at 37
## Quantification of erythromycin-resistant lysogens
As previously described [ 30 ], overnight cultures of S. aureus RN4220 were started from single colonies in TSB and subsequently diluted 1:100 into fresh TSB supplemented with 5 mM CaCl 2 before incubation at 37 • C with shaking for 1 h. Cells were then exposed to either NM1-Erm or NM1 gp16 -Erm at an MOI of ∼10 and incubated on ice for 30 min to facilitate adsorption. Next, cultures were transferred to 37 • C and incubated with aeration for 4 h. Serial dilutions were subsequently plated onto TSA plates containing 5 mM CaCl 2 with or without erythromycin, and lysogen formation was quantified by colony counts.
## Predicted protein structure
The primary sequences of Gp16 and RecA were submitted to AlphaFold3 (AF3) for structure prediction [ 31 ]. To model the Gp16-RecA complex, the sequences of both proteins were provided as input to AF3 using the multimer mode to predict the protein-protein complex. Structural comparisons and visualizations were performed in PyMOL ( https:// pymol.org/ ).
## Microscopy and image analysis
Overnight cultures of S. aureus cells were diluted 1:100 into TSB containing 10 ng ml -1 aTc and grown at 37 • C by shaking at 200 rpm. Cells were harvested every 2 h by centrifugation at 5000 rpm for 3 min, and then washed twice and resuspended in 10 μl PBS. Cells were mounted on glass slides and observed under an Olympus inverted microscope with a 100 × oil immersion phase contrast objective. Images were analyzed using ImageJ [ 32 ].
## Nucleoid staining
The nucleoid staining was performed as described [ 33 ]. In brief, cells were stained with 10 μM 4 ,6-diamidino-2phenylindole (DAPI) for 10 min at room temperature. Next, 2 μl of the mixture was flipped on to a microscope glass slide for imaging. The labeled cells were observed using phase contrast and the DAPI channel on an Olympus microscope.
## Protein pull-down in S. aureus and LC-MS
The Gp16 protein carrying a C-terminal twin-Strep tag was expressed in S. aureus . Cultures were induced with aTc and incubated at 37 • C for 6 h with shaking at 200 rpm. Cells were harvested by centrifugation at 4000 × g for 15 min at 4 • C, frozen in liquid nitrogen, and ground into fine powder. The cell powder was resuspended in lysis buffer (100 mM Tris-HCl, pH 8.0, 150 mM NaCl, 1 mM EDTA, 1 mM Phenylmethylsulfonyl fluoride (PMSF)) and lysed by sonication. The lysate was clarified by centrifugation (12 000 × g , 20 min, 4 • C) and applied to a Strep-Tactin Sepharose column (Cytiva, USA) preequilibrated with wash buffer. After extensive washing, bound proteins were eluted with buffer containing 50 mM biotin. Eluted fractions were concentrated and subjected to Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS)based proteomic analysis using an EASY-nLC 1200 UHPLC system coupled to an Orbitrap Q Exactive HF-X mass spectrometer (Thermo Fisher Scientific, USA) operating in datadependent acquisition mode. Peptides were separated on a C18 analytical column using a linear gradient of 5%-100% acetonitrile in 0.1% formic acid at a flow rate of 600 nl/min. MS/MS spectra were searched against the S. aureus protein database to identify Gp16-interacting proteins.
## His-tag pull-down assay
Gp16 was fused to a His-tagged SUMO and cloned into pET28a, while RecA was tagged with an N-terminal Flag tag and cloned into pET21a. Both plasmids were used to cotransform E. coli BL21 (DE3). Protein expression was induced with 1 mM IPTG when the cell culture reached an OD 600 of 0.4. The culture was further incubated for 16 h at 25 • C and then harvested by centrifugation at 4000 × g for 10 min. The cell pellets were resuspended in lysis buffer (40 mM Tris, pH 8.0, 300 mM NaCl, 10% glycerin, and 10 mM imidazole) and lysed by sonication, followed by centrifugation for 30 min at 12 000 rpm at 4 • C. The supernatant was filtered through a 0.22μm membrane and incubated with Ni-NTA resin (Beyotime, China). After binding, the resin was washed with wash buffer (40 mM Tris, pH 8.0, 300 mM NaCl, 10% glycerin, and 30 mM imidazole). The His-Sumo-Gp16 and the interacting proteins were eluted with elution buffer (40 mM Tris, pH 8.0, 300 mM NaCl, 10% glycerin, and 250 mM imidazole). Elution fractions were analyzed by sodium dodecyl sulfatepolyacrylamide gel electrophoresis (SDS-PAGE), and stained with Coomassie Brilliant Blue R.
## Western blot
Samples from His-tag pull-down assay were loaded onto a 10% polyacrylamide gel, resolved by SDS-PAGE, and transferred to a polyvinylidene fluoride membrane (Bio-Rad, Hercules, C A, US A). Following transfer, membranes were blocked in 5% nonfat dry milk (Bio-Rad) for 1 h at room temperature and then incubated overnight at 4 • C with a Flag antibody (1:2000; Sigma). After washing with PBST buffer for three times for 5 min each time at room temperature, the membrane was incubated with a horseradish peroxidase-labeled goat anti-mouse IgG (1:10 000; Beyotime) as the secondary antibody. Enhanced chemiluminescence reagent (Bio-Rad) was used to generate the signal. Image detection and collection are performed using a ChemiDoc imaging system, and the images are analyzed using ImageJ [ 32 ].
## Bacterial two-hybrid assay
Protein interactions were analyzed by the BACTH assay [ 26 ]. In brief, the "bait protein" and "prey protein" were fused to the pKT25 and pUT18. pKT25 and pUT18 expressing T18 and T25 fusion proteins were co-transformed into E. coli BTH101. The transformants were incubated at 30 • C for ∼48 h before inspection. To quantify protein interactions, cotransformants were picked and cultured with shaking at 30 • C for 16 h in LB containing 0.5 mM IPTG, and β-galactosidase activities were determined using the standard Miller assay. Results are representative of at least three independent replicates.
## Protein expression and purification
Gp16 and RecA proteins were expressed in E. coli BL21 (DE3) . The gene encoding gp16 was cloned into a pET28a vector with a TEV-cleavable N-terminal His 6 -SUMO tag. The recA gene was cloned separately into pET28a with a TEVcleavable N-terminal His 6 tag. Each plasmid was transformed into E. coli BL21. A single colony was amplified in 10 ml LB medium containing kanamycin (50 μg ml -1 ) for 12 h at 37 • C with shaking. Cultures were diluted 1:100 into LB medium (50 μg ml -1 kanamycin) and cultured at 200 rpm at 37 • C until OD 600 reached ∼0.5. Protein expression was induced with 0.3 mM IPTG and grown at 20 • C, 200 rpm for 16 h. The culture was centrifuged, and the pellet was resuspended in lysis buffer (20 mM Tris-HCl, pH 8.0, 300 mM NaCl, and 10 mM imidazole). The cells were homogenized and centrifuged at 10 000 × g for 20 min at 4 • C. The precipitate was incubated with a His-Tag purification resin column (GE Healthcare, USA), followed by protein elution with elution buffer (20 mM Tris-HCl, pH 8.0, 300 mM NaCl, 300 mM imidazole). The His 6 -SUMO tag was cleaved by Tev and removed by passing the samples over Ni-NTA resin (Beyotime, China). The purified protein was dialyzed and the buffer was finally replaced with PBS. Samples were assessed by SDS-PAGE. Protein concentrations were determined by Nanodrop 2000.
## Electrophoretic mobility shift assay
Electrophoretic mobility shift assay (EMSA) was performed using 200 ng of M13mp18 circular single-stranded DNA (ss-DNA) or linear double-stranded DNA as substrates. Reactions (20 μl) were carried out in a buffer [25 mM Tris-HCl, pH 7.6, 3 mM potassium glutamate, 10 mM magnesium acetate, and 5% (w/v) glycerin] with increasing concentrations of purified Gp16 protein (0-500 nM). After incubation at 37 • C for 40 min, 2 μl of 10 × DNA loading buffer was added to each reaction. Samples were resolved on 0.8% agarose gels in 1 × TAE buffer at 150 V for 30 min and visualized by nucleic acid staining.
## DNA cleavage assay
DNA substrates included gDNA from S. aureus RN4220, gDNA from phage NM1, single-stranded and circular double-stranded DNA from phage M13, and plasmid DNA (pET28a and pUC19). DNA substrates were prepared using extraction kits according to the manufacturers' instructions, including a bacterial gDNA extraction kit (Tiangen, China), a phage gDNA extraction kit (Zoman Biotechnology, China), and a plasmid extraction kit (Vazyme, China). As described [ 34 ], DNA cleavage experiments were carried out in 15 μl reaction volumes containing 200 ng DNA substrate and Gp16 or its mutant protein Gp16 C181A (0, 37.5, 75, 150, 300, 600, 1200, or 2400 nM) in a reaction buffer [25 mM Tris-HCl, pH 8.0, 5 mM MgCl 2 , 1 mM DTT, 0.5 mM ATP, and 5% (w/v) glycerin]. Reactions were carried out at 37 • C for 0, 10, 30, 60, or 120 min, and then terminated by adding 100 mM EDTA and 2 μl of 10 × DNA loading buffer. Reaction products were analyzed by electrophoresis on 0.8% agarose gels in 1 × TAE buffer at 150 V for 30 min and visualized by nucleic acid staining. The signal intensity of the initial DNA substrate was quantified using ImageJ software [ 32 ]. To calculate the proportion of degraded DNA, the band intensity of the intact substrate in each sample lane was normalized to that of the intact DNA band in the protein-free control. Quantification results are presented as bar graphs showing the mean values from three independent experiments, with error bars indicating the standard error of the mean.
## Determination of oriC/ter ratio in S. aureus
The oriC/ter ratio was determined as previously described [ 35 ]. Staphylococcus aureus strains harboring an empty vector (Vec), a Gp16 expression plasmid, or the Gp16 mutant C181A plasmid were grown overnight in TSB medium supplemented with the appropriate antibiotics at 37 • C and diluted 1:100 into fresh medium to OD 600 of 0.4-0.6. Protein expression was induced with aTc (10 ng ml -1 ) for 1-2 h. As a positive control, empty vector (Vec) cells were exposed to 0.5 μg ml -1 trimethoprim at OD 600 of 0.5 to inhibit DNA synthesis. Stationary-phase cultures (OD 600 = 0.8) were used as reference control. Cells at OD 600 of 1 were harvested and gDNA was extracted using a Genomic DNA extract kit (Tiangen, China).
Quantitative PCR (qPCR) was performed using 15 ng gDNA in 20 μl reactions containing 0.6 pmol of each primer and 10 μl of 2 × SYBR Green Supermix (Bio-Rad) with the following cycling conditions: 95 • C for 3 min; 40 cycles of 95 • C for 30 s, 60 • C for 30 s, and 72 • C for 30 s; followed by melt-curve analysis. Primer efficiencies were determined from 5-point, 10-fold serial dilutions of gDNA as E = 10 -1/slope . oriC/ter ratios were calculated using efficiencycorrected Ct relative to stationary phase controls:
where E o and E t are the efficiencies of the oriC-and terproximal primer pairs, and CT values are from control (C) and sample (S). Values represent the mean of three biological replicates with technical triplicates.
$$oriC ter = E o ( CT c ,o -CT s ,o ) E t ( CT c ,t -CT s ,t ) ,$$
## Quantitati ve rever se transcription PCR
Total RNA of S. aureus cells was extracted using Trizol (Invitrogen, USA) following the manufacturer's protocol. RNA concentration was quantified by Nanodrop 2000 (Thermo Fisher Scientific, USA) and agarose gel electrophoresis. gDNA in the RNA sample was removed with Genomic DNA Eraser (Promega, USA). For complementary DNA (cDNA) synthesis, 1 μg of total RNA was reverse-transcribed with random primers using the PrimeScript RT Enzyme Reagent Kit (Promega, USA) in a 20μl reaction. No-RT controls were included to verify the absence of gDNA contamination. Synthesized cDNA samples were diluted five times prior to RT-qPCR. RT-qPCR was accomplished using the SYBR Green (Bio-Rad) following the program: 3 min at 95 • C, followed by 40 cycles of 30 s at 95 • C, 30 s at 55 • C, and 15 s at 72 • C. Each 20 μl reaction contained 10 μl SYBR Green mix, 0.4 μM of each primer, and 2 μl of diluted cDNA. Melting curve analysis was conducted to confirm primer specificity. The primers are listed in Supplementary Table S2 . Relative transcript levels were calculated using the CT(2 -CT ) method, and the 16S RNA was monitored to allow for sample normalization.
## Phage copy number quantification
Quantification of phage copy numbers following infection was performed as previously described [ 36 ]. Staphylococcus aureus cultures were infected with either NM1 or NM1 gp16 at an MOI of 5. At 0, 10, 30, and 60 min postinfection, cells at OD 600 of 1 were collected from each time point by centrifugation at 4000 × g for 10 min at 4 • C. gDNA was extracted from the resulting pellets using the TIANamp Bacteria DNA Kit (Tiangen, China) according to the manufacturer's instructions. qPCR was performed on a CFX96 Real-Time PCR Detection System (Bio-Rad) using 10 ng of total gDNA per reaction with SYBR Green Master Mix (Bio-Rad) and primer pairs specific for the phage terminase large sub-unit gene ( gp38 ) and the S. aureus housekeeping gene tuf [ 37 ]. Reaction efficiencies for all primer pairs ranged from 95% to 105%, as determined by standard curve analysis. The tuf gene served as an internal reference for normalization. Relative phage genome copy numbers were determined by calculating the gp38 / tuf ratio in each sample and normalizing it to the 0 min time point, which was defined as 1. This analysis allowed the determination of fold changes in phage genome copy numbers throughout infection.
## Statistical analysis
GraphPad Prism 8 software was used for statistical analysis of the data. Student's t -test and one-way ANOVA were used to analyze the differences between two or more groups. A Pvalue < .05 was considered statistically significant.
## Results
## Gp16 inhibits S. aureus cell growth and promotes phage infectivity
Previously, we performed a comprehensive screen for earlygene products of NM1 (GenBank accession DQ530359.1) [ 38 ] that inhibit cell growth in S. aureus . A small membrane protein named Gp11 was characterized to block S. aureus cell division by inhibiting peptidoglycan biosynthesis [ 27 ]. In addition, another protein named Gp16 (Protein ID ABF73046.1) was found to inhibit cell growth. As shown in Fig. 1 A, compared with the empty vector control, overexpression of Gp16 resulted in growth arrest in S. aureus . By plating the cultures on TSA plates, inducible overexpression of gp16 inhibited colony formation (Fig. 1 B).
To investigate the role of gp16 , we generated a gp16 deletion mutant of phage ФNM1 ( ФNM1 gp16 ). ФNM1 gp16 formed plaques in sizes similar to those of the wild-type phage (Fig. 1 C), but its infectivity on double-layer agar plates was reduced with an ∼10-fold decrease, as reflected by a significant decrease in EOP (Fig. 1 D). This apparent discrepancy likely reflects a reduced probability of productive infection in the absence of gp16 , whereas infections that successfully proceed through the lytic cycle can still form plaques with morphology comparable to the wild type; and the defect could be complemented in trans , since infection of S. aureus strains carrying a plasmid-borne gp16 restored the EOP to wild-type levels (Fig. 1 D). These findings indicate that although gp16 is dispensable for plaque formation, it is required for efficient infection of S. aureus .
## Gp16 expressed immediately after phage infection and is important to phage fitness
Since gp16 deletion affected infection efficiency, we next asked at which stage gp16 is expressed and how it contributes to phage propagation. gp16 transcripts were detected 5 min postinfection at levels comparable to the early gene gp104 [ 39 ], confirming that gp16 is an early gene, whereas gp42 [ 40 ], which is required for phage particle assembly and is expressed late in the infection cycle, was transcribed after 1 h of infection (Fig. 2 A).
To assess the functional consequences of gp16 deletion, we compared host survival and phage propagation in liquid culture. Growth curve analyses across a range of MOIs revealed that wild-type ФNM1 caused a rapid and substantial decline in optical density, whereas ФNM1 gp16 infection allowed a much larger fraction of the population to persist ( Supplementary Fig. S1 ). At an MOI of 0.01, the OD 600 profile of ФNM1 gp16 -infected cultures was nearly indistinguishable from that of uninfected controls. More detailed measurements at this MOI showed that, beginning at 3 h post-infection, cultures infected with wild-type ФNM1 exhibited a pronounced loss of cell density relative to ФNM1 gp16 (Fig. 2 B). Viable cell counts were reduced ∼25-fold in the wild-type infection compared with the mutant at 6 h (Fig. 2 C). In line with this, despite the higher host survival, ФNM1 gp16 produced nearly 100-fold fewer progeny phages than wild-type ФNM1 in 6 h after infection (Fig. 2 D), highlighting a critical role of gp16 in virion production.
In addition, treatment of lysogens with MMC to induce prophage resulted in significantly different phage yields between wild-type and mutant strains. Following MMC treatment, infective phages were detected 0.5 h after induction and reached ∼3.2 × 10 7 PFU/ml for wild-type ФNM1, whereas ФNM1 gp16 yielded only ∼1.65 × 10 4 PFU/ml, demonstrating that although viable, the mutant was severely impaired in virion release (Figs 2 E and 3 F). To enable quantification of lysogens carrying a stably integrated prophage, an erythromycin resistance gene ( ermC ) was introduced into NM1 and NM1 gp16 ( Supplementary Fig. S2 A). The effect of ermC insertion on phage infectivity was assessed. Infections of S. aureus at MOIs of 0.01 and 10 yielded trends consistent with those observed for phages lacking ermC ( Supplementary Figs S1 andS2 ), demonstrating that the insertion did not impair phage infectivity . Notably , cultures infected with NM1 gp16 -Erm produced a greater number of lysogens compared with NM1 at MOI = 10 (Fig. 2 G). Since loss of gp16 diminishes phage replication efficiency, the infection outcome becomes biased toward lysogeny, explaining the increased formation of lysogens observed here. Taken together, these results indicate that, although gp16 is dispensable for plaque formation, it contributes to efficient phage induction, virion release, and robust inhibition of host growth, thereby enhancing overall phage fitness.
## Gp16 is a member of the HNH-endonuclease family
To further explore the function of Gp16, we next performed a PSI-BLAST search using the gp16 sequence as a query. Our results revealed that Gp16 contains a CXXC motif (Cys145-Val146-Ile147-Cys148) and a CXXH motif (Cys181-Arg182-Glu183-His184), which is found in HNH endonucleases of subclass 6. However, this analysis did not reveal any such characterized proteins. To investigate the conformational dynamics of Gp16, we used AlphaFold 3 to predict its potential alternate structures [ 31 , 41 ]. The predicted structure of Gp16 consists of two distinct domains: the N-terminal domain shows a strong structural resemblance to the homologous recombination mediator NinB (PDB: 1PC6) [ 42 ], while the C-terminal domain resembles the HNH nuclease IscB (PDB: 8CSZ) [ 43 ] (Fig. 3 A). Notably, the C-terminal nuclease domain contains conserved HNH zinc-finger and nuclease center motifs revealed by structural alignment (Fig. 3 B andC).
The predicted structural model suggested that Gp16 contains a conserved HNH nuclease domain, prompting us to examine its functional contribution. To this end, we generated single amino acid substitutions in residues predicted to coordinate zinc ions (C148A, C181A, and H184A) within the HNH-type zinc-finger motif and in catalytic residues (H157A, H185A, and H189A) within the nuclease center, which are highly conserved among IscB-like endonucleases (Fig. 3 D). Expression of wild-type Gp16 inhibited S. aureus cell growth, whereas mutations in the zinc-finger motif (C148A, C181A, and H184A) completely abolished the growth inhibition (Fig. 3 E). The H157A substitution in the HNH nuclease motif did not affect the growth inhibition, while substitutions at the nuclease center (H185A and H189A) only partially relieved growth inhibition, suggesting that the catalytic residues are important but not solely responsible for the inhibitory phenotype (Fig. 3 E).
Given its putative nuclease structure, we next examined whether Gp16 expression affects nucleoid organization within the cell. Overexpression of wild-type Gp16 caused a subpopulation of cells to enlarge, as visualized by phase-contrast microscopy. DAPI staining revealed pronounced DNA condensation within these enlarged cells, consistent with previous observations [ 35 ], even in cells with no nucleus (Fig. 3 F). In contrast, the C148A, C181A, and H184A mutants did not induce DNA condensation and displayed cell morphologies comparable to the control, consistent with their inability to inhibit bacterial growth (Fig. 3 F). Substitutions at the HNH nuclease center (H185A and H189A) partially alleviated growth inhibition but still induced DNA condensation, whereas the H157A mutation did not affect bacterial growth yet retained the DNAcondensed phenotype, indicating that disruption of these catalytic residues weakens but does not abolish the nucleasemediated effects (Fig. 3 F). Collectively, these results demonstrate that the catalytic integrity of the HNH nuclease domain is essential for Gp16-induced inhibition of S. aureus growth and perturbation of nucleoid organization.
## Gp16 functions as a nickase in vitro
Structural prediction analysis indicated that the C-terminal HNH domain of Gp16, with conserved zinc-finger motifs, may facilitate nucleic acid binding. To test this, we performed EMSA using M13mp18 ssDNA and dsDNA substrates at 0-500 nM Gp16. No binding was observed with ssDNA, whereas dsDNA exhibited clear gel shifts with increasing Gp16 concentrations (Fig. 4 A), demonstrating selective ds-DNA binding. Having demonstrated that the catalytic integrity of the HNH domain is essential for Gp16-mediated inhibition of S. aureus cell growth and DNA condensation in vivo , we therefore sought to directly assess its nuclease activity in vitro . Gp16 was tested against various DNA substrates and showed a strong preference for plasmid DNA, indicating plasmid-biased nuclease activity (Fig. 4 B).
To further characterize this activity, the plasmid substrate pET28a was incubated with increasing concentrations of purified Gp16. At 150 nM, the supercoiled plasmid was largely converted into its linear form, while higher concentrations resulted in progressive accumulation of nicked and degraded DNA species, with extensive degradation observed at 2.4 μM (Fig. 4 C). Quantification showed that ∼70% of the plasmid DNA was cleaved at 300 nM Gp16 ( Supplementary Fig. S3 A). In contrast, the catalytic mutant Gp16 C181A exhibited no detectable nuclease activity toward plasmid DNA under identical conditions (Fig. 4 C), and its cleavage efficiency did not vary with protein concentration ( Supplementary Fig. S3 A). When linearized plasmid DNA was used as the substrate, 300 nM Gp16 induced only slight degradation after 1 h, whereas higher concentrations caused extensive di- gestion (Fig. 4 D), with ∼60% of the DNA degraded at 2.4 μM ( Supplementary Fig. S3 B). Time-course assays further revealed that Gp16 rapidly cleaved plasmid DNA in a timedependent manner, converting supercoiled DNA to its linear form within 10 min and causing progressive degradation with prolonged incubation (Fig. 4 E). After 2-h incubation with 150 nM Gp16, ∼95% of the supercoiled plasmid was cleaved, whereas Gp16 C181A remained inactive throughout ( Supplementary Fig. S3 C). Collectively, these results demonstrate that Gp16 functions as a nickase whose activity depends on both protein concentration and reaction time, and that its catalytic cysteine residue (C181) is essential for DNA cleavage.
## Host protein RecA is required for Gp16 mediated growth arrest
To identify the cellular target of Gp16, an in vivo pulldown assay was performed. Proteins co-purified with Gp16 were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS), which revealed RecA as a potential Gp16-interacting partner. To confirm this interaction, an in vitro His pull-down assay was conducted. Following Ni-NTA affinity chromatography, Flag-RecA was detected in the elution fraction only in the presence of His-SUMO-Gp16, confirming a specific interaction between Gp16 and RecA (Fig. 5 A).
To gain further insight into the molecular basis of this interaction, AlphaFold3 was employed to predict the interaction of Gp16-RecA complex ( Supplementary Fig. S4 ). The structural model generated by AlphaFold3 revealed an extensive interaction surface between the two proteins with a high confidence score of 0.81, supporting the reliability of the predicted complex (Fig. 5 B). Consistent with these results, a BATCH assay further verified the interaction of Gp16-RecA, whereas neither the N-terminal nor the C-terminal truncations of Gp16 retained binding activity, suggesting that both termini are required for complex formation (Fig. 5 C). Guided by the structural model, point mutations were introduced into several residues of RecA to assess their contribution to Gp16 binding. As shown in Fig. 5 D, substitutions at K7, E17, K215, R224, K247, and N248 markedly reduced interaction with Gp16, identifying these residues as critical determinants of binding.
Since RecA is nonessential for bacterial growth, Gp16 must inhibit growth by co-opting, rather than merely inactivating, RecA. We therefore tested whether Gp16 requires a functional RecA protein for its activity. Indeed, Gp16 expression failed to inhibit the growth of a recA mutant, but inhibition was restored upon complementation with wild-type recA (Fig. 5 E andF). The RecA N248A mutant was introduced as this residue lies closest to Gp16 in the predicted interface (distance ≈ 3.6 Å ) (Fig. 5 B). Crucially, this growth inhibition was abolished in a strain expressing a RecA variant (RecA N248A ) that is defective in Gp16 binding (Fig. 5 F), demonstrating that the physical interaction between Gp16 and RecA is essential. This RecA-dependent mechanism is further supported by in vitro findings that RecA enhances the DNA cleavage activity of Gp16 (Fig. 4 F), suggesting that the RecA interaction not only mediates cellular growth arrest but also potentiates Gp16's enzymatic function.
## Gp16 promotes phage infection via RecA and suppresses host replication
To investigate the role of RecA during phage infection, we first measured recA expression at 10 min post-infection, a time point corresponding to the onset of robust gp16 transcription. The phage infection significantly upregulated recA compared to uninfected cells (Fig. 6 A). The importance of RecA was fur- ther supported by the EOP assay: deletion of recA markedly resulted in an ∼10-fold reduction in EOP during NM1 infection, whereas complementation restored it to wild-type levels (Fig. 6 B). In line with these observations, knocking out gp16 significantly reduced EOP; however, this reduction was reversed when RecA was absent, indicating that Gp16 depends on RecA to function (Fig. 6 B). This reversal supports a model in which Gp16 acts through RecA during early infection to modulate host processes in favor of phage replication.
Cell elongation and DNA condensation are hallmarks of replication arrest [ 44 ]. To test whether Gp16 disrupts DNA replication, we measured the oriC/ter ratio of the S. aureus chromosome by real-time PCR. As a positive control, cells treated with the DNA synthesis inhibitor ciprofloxacin [ 45 ], which showed an ∼two-fold increase in the oriC/ter ratio (Fig. 6 C). Likewise, Gp16 expression resulted in a significant increase in the oriC/ter ratio compared with the vector control, whereas the C181A mutant showed no effect (Fig. 6 C), indicating that Gp16 blocks replication fork progression and prevents completion of chromosomal replication. qPCR analysis further confirmed that gp16 overexpression suppresses the transcription of key replication-associated genes, including dnaA , dnaE , dnaN , gyrA , gyrB , parC , and sirA (Fig. 6 D). To examine the physiological role of Gp16 during phage infection, we sampled cells 10 min after infection at an MOI of 10, when Gp16 is rapidly expressed. Notably, deletion of gp16 resulted in a significant increase in the transcription of replication-associated genes, consistent with the inhibitory ef-fect observed upon gp16 overexpression (Fig. 6 E). Together, these findings demonstrate that gp16 is expressed immediately upon infection, where it suppresses host DNA replication and promotes host DNA condensation.
To determine whether Gp16-mediated suppression of host replication benefits phage propagation, we monitored phage replication. Deletion of gp16 reduced phage replication by ∼1.9-fold at 30 min and 5.8-fold at 1 h post-infection ( Supplementary Fig. S5 ). Consequently, Gp16-mediated shutdown of host replication and recruitment of RecA not only inhibit host growth but also enhance phage replication. This dual activity underscores how Gp16 simultaneously suppresses the host and promotes phage infection.
## Discussion
The evolutionary arms race between bacteria and their phages is driven by early phage genes that facilitate host takeover and host defenses that counteract this process [ 46 , 47 ]. Although most early phage genes are nonessential, they are thought to fine-tune infection or function under specific conditions, yet the majority of these remain functionally uncharacterized [ 48 ]. In this study, we identify Gp16 as an early gene product that enhances phage fitness while inducing growth arrest in S. aureus . Unlike previously described phage proteins that directly target essential bacterial factors [ 27 ], Gp16 employs an indirect strategy by co-opting the nonessential host protein RecA to favor phage replication. Our findings reveal that Gp16 promotes phage propagation through RecA while simultaneously suppressing host DNA replication, thereby providing a mechanistic framework for phage exploitation of host functions and offering new insights into the evolutionary dynamics of phage-host interactions.
Building upon these findings, Gp16 illustrates the functional role of phage-encoded nucleases in manipulating host DNA metabolism to optimize infection outcomes. Our characterization of Gp16 aligns with recent studies highlighting nucleases as pivotal players in the molecular arms race between bacteria and their phages. While bacterial nucleases, such as the Class 1 OLD family nuclease Vc OLD from V. cholerae , act as defense effectors to restrict phage replication, an effect counteracted by the ICP1-encoded inhibitor Oad1 [ 49 ], Gp16 represents a distinct paradigm. Unlike bacterial immunity functions, Gp16, a phage-encoded nuclease, relies on the host RecA protein to promote phage replication, showcasing a cooperative interaction between a phage effector and a host DNA repair factor. This mechanism contrasts sharply with bacterial RM and CBASS-associated nucleases, which aim to protect the host by targeting invading phage genomes [ 2 ]. These findings collectively underscore the dual roles that nucleases play in the conflict between bacteria and phages, acting either as host defense components or as phage-encoded effectors that modify host DNA metabolism. This duality broadens the conceptual framework of nucleasemediated interactions and illustrates how phages exploit host DNA maintenance machinery to coordinate host suppression with efficient phage propagation. Given that NM1 is a temperate phage [ 38 ], we explored how Gp16 modulates the infection outcome between lysis and lysogeny. Temperate phages can follow either a lysogenic or the lytic lifestyle [ 50 ]. The deletion of gp16 significantly impairs phage replication and increases the frequency of lysogen formation, suggesting that Gp16 biases the infection outcome toward the lytic cycle. This bias is critical for phage fitness as it ensures efficient progeny production; conversely, the absence of Gp16 supports stable prophage integration. Prophages are known to drive lysogenic conversion, altering host phenotypes such as virulence [ 51 ], and contributing to genome diversification and adaptive evolution by disrupting key functions or facilitating horizontal gene transfer [ 52 ]. Therefore, changes in lysogeny frequency can profoundly impact host-phage interactions. By adjusting the balance between lysis and lysogeny, Gp16 not only enhances phage reproductive success but may also indirectly shape the long-term evolutionary path of its bacterial host.
To gain mechanistic insight into how Gp16 influences host growth and phage replication, we analyzed its structural features, identifying it as a canonical HNH-like nuclease. Gp16 and its homologs in related Dubowirus phages constitute a conserved early-gene strategy that inhibits Staphylococcus growth and biases infection toward the lytic cycle, thereby enhancing phage replication efficiency and progeny production. The widespread conservation of gp16 -like genes suggests that such host-targeting mechanisms provide a competitive advantage and may contribute to the evolutionary success of the genus. HNH-like proteins exhibit an evolutionarily conserved structural and functional organization, consisting of two modules: an N-terminal α-helical structure and a more conserved C-terminal DNA binding domain and catalytic domain [ 53 ]. The predicted structure of the Gp16 C-terminal domain, resembling that of IscB, displays an active site architecture characteristic typical of HNH endonucleases with the canonical ββ-α fold. Site-directed mutagenesis of residues within this active site abolished growth inhibition mediated by Gp16, suggesting that the C-terminal HNH nuclease domain, and particularly its zinc-finger motif, is essential for its nuclease activity. AlphaFold modeling further suggests that the N-terminal region of Gp16 adopts a fold similar to NinB. Given that NinB acts as a recombination mediator that antagonizes RecFOR and facilitates RecA filament formation on SSB-coated ssDNA [ 54 ], it is plausible that the N-terminal domain of Gp16 plays a similar role in modulating host recombination processes, potentially coordinating DNA nicking with RecA-dependent pathways, though this hypothesis requires experimental validation.
During phage infection, RecA is activated in response to replication stress and DNA damage, initiating homologous recombination and DNA repair pathways [ 55 ]. Our data reveal that gp16 is transcribed immediately after the onset of infection, ensuring that Gp16 is present alongside RecA activation. Beyond its canonical role in host repair, RecA also facilitates the cleavage of phage-encoded repressors, allowing transcription from early promoters and initiating the lytic cycle [ 56 ]. Gp16 appears to alter this early activation event by interacting with RecA, redirecting its activity from host DNA repair to phage genome replication and recombination. Concurrently, Gp16 exploits RecA to suppress host growth, further shifting the intracellular balance toward phage propagation. This dual functionality underscores the critical role of RecA availability in determining the infection outcome, as reduced RecA activity significantly diminishes phage DNA replication and phage yield [ 57 ]. Together, these findings highlight how ФNM1 ensures a productive infection by coupling early gp16 expression with RecA-dependent reprogramming of host cellular pathways. Gp16 interacts with the host RecA and simultaneously functions as a nuclease, embodying a multifunctional strategy to modulate host DNA metabolism. Among RecA-dependent nucleases, the P1 Ref protein serves as a well-characterized example: although it has inherently weak endonuclease activity, its endonuclease activity is greatly enhanced when recruited to ssDNA by RecA filaments, leading to programmable doublestrand breaks [ 21 -23 ]. In contrast, Gp16 possesses intrinsic nuclease activity and is capable of cleaving plasmid DNA in vitro independent of RecA. While Ref protein enhances RecAdependent recombination in vivo through an unknown mechanism [ 58 ], Gp16 stands out by inhibiting host growth and markedly impairing phage genome replication and progeny production. This reveals a broader physiological role that connects RecA interaction to host inhibition and efficient phage propagation. Functionally, Gp16 resembles the phage protein 015, which introduces DNA nicks that block replication fork progression and suppress host cell growth [ 15 ]. Our findings suggest that Gp16 exerts a similar activity, consistent with its role in perturbing bacterial DNA metabolism. However, whether Gp16 cleaves specific targeting oligonucleotides at preferred sites remains to be determined, leaving open questions for future studies.
Phages can also conserve energy for infection by shutting off host processes, such as host replication and cell division [ 39 , 59 ]. Our data indicate that Gp16 contributes to this strategy by inducing condensation of host DNA, a phenotype likely to impede replication. Although Gp16 displays nuclease activity independently of RecA in vitro , its inhibitory effect in vivo seems to rely on host factors, underscoring how the phage exploits the cellular environment to maximize DNA degradation. Mechanistically, overexpression of Gp16 increases the oriC/ter ratio, indicating replication fork collapse and subsequent DNA condensation. This effect is similar to the action of antibiotics such as ciprofloxacin and trimethoprim, which disrupt replication by uncoupling initiation from elongation, leading to stalled forks and elevated origin-proximal copy numbers [ 15 , 35 ].
By rapidly halting host replication, Gp16 may prevent competition for critical resources such as dNTPs and replication enzymes, while simultaneously preempting host repair pathways from counteracting DNA damage. This DNA condensation represents a defensive preemptive strategy by which the phage ensures early control over host chromosome metabolism to favor phage replication. Several phage proteins have been shown to directly target bacterial replication machinery. For example, the N4 gp8 protein inhibits the clamp loader subunit of DNA polymerase II, whereas phage LUZ24 Igy protein targets the DNA gyrase subunit B of Pseudomonas aeruginosa [ 12 , 39 , 59 ], but the precise role of these inhibitors during phage replication remains elusive. Instead, Gp16 employs an indirect, RecA-dependent mechanism, highlighting a distinct route through which phages reprogram host replication.
In summary, our findings uncover a distinct mechanism by which a phage-encoded nuclease exploits a host regulatory hub to coordinate bacterial shutdown with phage propagation. By engaging RecA, a central component of bacterial stress signaling, Gp16 couples host replication arrest with phage genome amplification, exemplifying functional integration between phage and host systems. This dual control not only enhances phage fitness but also highlights the evolutionary versatility of phage effectors in rewiring essential bacterial pathways. More broadly, our study provides a conceptual framework for identifying phage-encoded modulators that alter bacterial physiology, offering new insights into microbial interactions and potential targets for antibacterial innovation.
## A c kno wledg ements
We thank Vincent A. Fischetti for providing S. aureus Newman strain, Wenyan Jiang for providing pLM9 plasmid, Quanjiang Ji for providing pCasSA plasmid, Hang Yang for providing the M13 phage. We acknowledge the Core Facility and Technical Support of Wuhan Institute of Virology for technical assistance.
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36. Ronayne, Wan, Boudreau (2016) "P1 Ref endonuclease: a molecular mechanism for phage-enhanced antibiotic lethality" *PLoS Genet*
37. Cheng, Huang, Wu (2021) "A nucleotide-sensing endonuclease from the Gabija bacterial defense system" *Nucleic Acids Res*
38. Slager, Kjos, Attaiech (2014) "Antibiotic-induced replication stress triggers bacterial competence by increasing gene dosage near the origin" *Cell*
39. Yao, Coleman, Nguyen (2021) "Bacteriophage self-counting in the presence of viral replication" *Proc Natl Acad Sci*
40. Shan, Jia, Teulieres (2021) "Targeting multicopy prophage genes for the increased detection of Borrelia burgdorferi sensu lato (s.l.), the causative agents of Lyme disease, in blood" *Front Microbiol*
41. Bae, Baba, Hiramatsu (2006) "Prophages of Staphylococcus aureus Newman and their contribution to virulence" *Mol Microbiol*
42. Liu, Dehbi, Moeck (2004) "Antimicrobial drug discovery through bacteriophage genomics" *Nat Biotechnol*
43. Kongari, Ray, Lehman (2024) "The transcriptional program of Staphylococcus aureus phage K is affected by a host rpoC mutation that confers phage K resistance" *Viruses*
44. Jumper, Evans, Pritzel (2021) "Highly accurate protein structure prediction with AlphaFold" *Nature*
45. Maxwell, Reed, Zhang (2005) "Functional similarities between phage lambda Orf and Esc heric hia coli RecFOR in initiation of genetic exchange" *Proc Natl Acad Sci*
46. Schuler, Hu, Ke (2022) "Structural basis for RNA-guided DNA cleavage by IscB-omegaRNA and mechanistic comparison with Cas9" *Science*
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# Southern African Journal of Infectious Diseases
Mark Cotton, Andrew White, Ute Hallbauer, Colleen Bamford, Wolfgang Preiser, Nishi Prabdials
The Southern African Journal of Infectious Diseases (SAJID) publishes manuscripts on infectious diseases especially those relevant to our region. With a Web of Science impact factor of 1.3 for 2024, SAJID is an appropriate journal for both emerging and established researchers. The integrity and excellence of our journal's output depend on the quality of the submitted manuscripts and the quality of the peer review process. For manuscript quality, we rely on the authors. While most work is usually undertaken by the first author, the supervision and input provided by the senior authors are vital, especially for manuscripts where the first author is a new or emerging researcher.
The first scientific journals, Journal de sçavans and Philosophical Transactions of the Royal Society, were published in 1665, without peer review. 1,2 The history of pre-publication peer review began in 1731. The editor of Medical Essays and Observations, published by the Royal Society of Edinburgh, submitted essays to individuals he considered most suitable to review. The journal stated that peer review did not guarantee truthfulness or accuracy, which depended on the authors. The adoption of peer review was somewhat haphazard. The Royal Society established a prepublication review committee to determine whether a manuscript should be published in 1752. 3 The Lancet considered peer review unimportant until 1976, and the Journal of the American Medical Association mainly used internal review and only occasionally outside experts until the mid-1950s. 4 The British Medical Journal, however, sent all submitted manuscripts to a recognised expert, starting in 1893. Only since the late 20th century was peer review adopted by most biomedical journals. 5 We consider it of utmost importance.
The SAJID uses a double-blinded peer review process where the identities of both authors and reviewers are concealed to avoid bias. We require a minimum of two reviewers per submission. Once an article passes this review process, often supplemented by additional input from the editorial team, the manuscript is published and contributes to scientific knowledge. A published manuscript not only represents the authors' hard work but also the time and effort spent by the reviewers, editorial team and journal administrative staff. 6 Identifying reviewers is a major challenge for SAJID as for most scientific journals. This difficulty is exacerbated by the plethora of new journals. The directory of open access journals currently has 398 indexed medical journals. Overall, from 2003 to 2023, there has been a nearly 200% increase in citable research documents from 1 515 000 to 4 793 000. 7 Reviewer fatigue is now a widely recognised problem. 8 We have had the experience of searching for and asking up to 10 people to review a publication. Potential reviewers have 2 weeks to respond to an invitation from SAJID. Even though difficult, we encourage reviewers to respond sooner so that we can invite someone else if they decline. Responding either late or not at all significantly increases the overall time taken to review a manuscript to completion, which is currently 92 days on average. Fortunately, most reviews are good and useful, improving the quality of the manuscripts. As reviewing a manuscript requires between 3 and 8 h of work, depending on its length and complexity, it is challenging to integrate this task into one's daily professional life. Most reviews are conducted by colleagues in academic practice who have multiple competing obligations. These include, in addition to busy professional lives, their own research projects, seeking funding and writing manuscripts. With the proliferation of medical journals, one can be easily overburdened with requests. Some members of the SAJID editorial team receive several review requests per week from different journals, with each acceptance carrying its own burden of time management.
What are the benefits of reviewing for SAJID? We believe there are many. Firstly, one is advancing locally relevant knowledge about infectious diseases. Secondly, one is growing the capacity of emerging and established researchers to communicate their findings. Thirdly, reviewers increase http://www.sajid.co.za Open Access their own knowledge and learn about academic activities in infectious diseases. Fourthly, reviewers are eligible for continuing education units (CEUs) as part of continuing professional development (CPD). 9 Fifthly, peer review activities are increasingly recognised as evidence of scholarly activity and should be included in one's curriculum vitae. We welcome their inclusion in academic performance assessments by universities and hope this will expand. Open Researcher and Contributor ID (ORCID) allows curating one's reviewing activity. With a planned upgrade in process, SAJID will soon export reviewer activity to ORCID. Some journals already report reviewing activity to ORCID.
The editorial team are extremely grateful to all reviewers who accept invitations and contribute to the journal. We encourage you to accept invitations when the topic is within your field of expertise and contribute to the ongoing improvement of the research published in the journal. Should you find yourself unable to comply with a request to review or the topic does not match your area of expertise, we are grateful for suggestions of whom might be a suitable reviewer.
## References
1. *Journal of the Learned*
2. Partridge (1666) "Celebrating 350 years of philosophical transactions: Life sciences papers" *Philos Trans R Soc Lond B Biol Sci*
3. Drozdz, Ladomery (2024) "The peer review process: Past, present, and future" *Br J Biomed Sci*
4. Mousawi (2020) "A brief history of peer review. F1000blog"
5. Benos, Bashari, Chaves (2007) "The ups and downs of peer review" *Adv Physiol Educ*
6. Jackson, Smith, Cleary (2025) "The privilege and power of peer review: Advancing science with integrity, vigilance and fairness" *J Adv Nurs*
7. Dhand (2025) "Is there a strain on peer review? -It's more complicated than you think"
8. Adam (2025) "How to fix peer review" *Nature*
9. "What is the process for obtaining CEU for my review report from the HPCSA?"
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# Emerging adaptation of BJ/94 lineage H9N2 viruses to waterfowl: insights into enhanced replication and immune activation in the host cells
Junyi Wu, Peiwen Chen, Liwei Liu, Dan Er Wei, Wenshan Hong, Huachen Zhu, Tommy Tsan, Yuk Lam, Yi Guan, Jia Wang
## Abstract
H9N2 influenza viruses have adapted to terrestrial avian hosts via prolonged circulation in domestic chicken populations across South and Southeast Asia. Recent surveys have documented an increased incidence of H9N2 infections in domestic ducks and geese; however, it remains unresolved whether these infections are transient spillover events from incidental chicken exposure or indicate sustained infectivity and transmissibility among waterfowl species. To address this, we performed a comprehensive characterization of H9N2 viruses detected from wild aquatic birds and farmed ducks. Surveillance revealed sporadic H9N2 infections in wild aquatic birds, as well as transient outbreaks within farmed duck flocks following viral introduction. Phylogenetic and molecular analyses revealed that these viruses shared high homology with contemporaneous chicken-circulating strains and retained chicken-adapted signatures. Notably, a phenotypic shift in recent BJ/94 lineage isolates (post-2021) was uncovered: whereas early BJ/94 lineage strains (pre-2021) exhibited preferential replication in chicken embryo fibroblasts (CEF), recent isolates displayed significantly enhanced replication efficiency in duck embryo fibroblasts (DEF)-a replication profile analogous to that of the aquatic bird-adapted Y439 lineage. Furthermore, recent isolates induced robust innate immune activation and pronounced upregulation of proinflammatory cytokines in DEF, characterized by elevated expression of key sensors (LGP2 and MDA5), adaptors (STING), transcription factors (IRF7 and NF-κB), and inflammatory cytokines (IL-2, IL-6 and IL-8). Thus, our findings indicate the recent BJ/94 lineage H9N2 has heightened waterfowl cell infectivity and immune responses, signaling emerging waterfowl adaptation. This may disrupt the evolutionary stasis of H9N2 viruses and potentially drive the emergence of novel viral variants with interspecies transmissibility.
## Introduction
Wild waterfowl are the natural reservoir for influenza A viruses and exhibit tolerance to infection, as evidenced by the absence of clinical symptoms. Multiple viral subtypes can coexist within wild waterfowl populations, facilitating the generation of diverse genotypic progeny. Consequently, wild waterfowl function as a genetic reservoir for influenza A viruses. Transmission within these populations predominantly occurs via the fecal-oral route in aquatic habitats, while global viral dispersal depends on migratory behavior.
Geographical constraints on migratory bird movements result in the H9 subtype influenza virus of North America and Eurasia exhibiting relatively independent epidemiological profiles and evolutionary histories, despite occasional intercontinental transmission. In North America, H9 subtype influenza viruses persist within wild bird populations and coexist with other influenza subtypes (Jackwood et al., 2007). Conversely, in Eurasia, the H9 viruses not only continue to circulate among wild waterfowl but have also been introduced into poultry populations in South Korea and China. Extended circulation within poultry in these regions has given rise to independent evolutionary branches, such as the Y439, G1, and BJ/94 lineages. Particularly, the BJ/94 lineage has persistently impacted hundreds of millions of domestic chickens in China over three decades. Since 2013, the ZJ/HJ-like genotype (represented by A/Chicken/Zhejiang/HJ/2007) has become dominant in chickens (Pu et al., 2014;Li et al., 2017;Guo et al., 2021). Despite extensive vaccination programs, the prevalence of H9 virus in domestic chickens remains elevated (Bi et al., 2020;Yang et al., 2025), thereby facilitating potential viral spillover into wild waterfowl.
Since 2014, BJ/94 lineage H9N2 viruses have been identified in wild waterfowl inhabiting lake and wetland reserves across China (Zhang et al., 2021;Yao et al., 2022). Surveillance efforts targeting overwintering migratory birds demonstrate a low prevalence of H9 viruses, with detection rates ranging from 0.01 % to 0.04 % (Tan et al., 2025). The H9 viruses detected in these populations either maintain a poultry-like genotypic profile or incorporate gene segments derived from the wild waterfowl influenza gene pool (Ye et al., 2016;Ge et al., 2018;Yao et al., 2022;Yang et al., 2024). At the molecular level, these wild bird H9 viruses predominantly exhibit features of contemporary chicken H9 viruses, including the hemagglutinin (HA) cleavage motif PSRSSR↓G, a 3-amino-acid deletion in the neuraminidase (NA) associated with terrestrial poultry adaptation, leucine at position 226 conferring sialic acid α2,6-galactose (SAα2,6-Gal) preference, and mutations in the non-structural protein 1, such as 149A and E227K, which are implicated in antagonizing interferon induction in chicken embryo fibroblasts (CEF) (Ye et al., 2016;Ge et al., 2018;Yao et al., 2022;Zhang et al., 2022;Yang et al., 2024). In the evaluation of the risk posed by these wild bird H9 isolates in terms of mammalian infection, the infectivity and transmissibility of the virus in mice, guinea pigs, and ferrets were found to be comparable to those of the H9N2 virus currently circulating within chicken populations (Zhang et al., 2022). In recent years, longitudinal epidemiological surveillance of poultry in China has documented a rising prevalence of H9N2 viruses in ducks and geese: prior to 2015, the detection rate of H9 viruses in ducks was below 2 % (Zhou et al., 2012;Deng et al., 2013;Wu et al., 2015); however, between 2020 and 2024, certain regions reported annual detection rates exceeding 15 % in ducks and over 10 % in geese (Bi et al., 2020;He et al., 2022;Yang et al., 2025). This increasing incidence of H9N2 viruses, which are adapted to terrestrial poultry yet infect waterfowl hosts, creates ecological and evolutionary conditions conducive to viral readaptation within waterfowl populations.
Owing to the host barrier separating waterfowl from terrestrial poultry, only influenza viruses that have acquired adaptive changes subsequent to their transmission from natural waterfowl reservoirs to terrestrial poultry are able to maintain long-term persistence within terrestrial poultry populations. Notable adaptive features include alterations in the NA stalk region and receptor-binding characteristics (Sun et al., 2013;Arai et al., 2020). However, such adaptations may diminish the virus's capacity for replication and transmission in waterfowl hosts (Li et al., 2010). It remains unclear whether BJ/94 lineage H9 viruses, which are highly adapted to terrestrial poultry, have evolved through repeated infections in waterfowl in recent years to efficiently replicate in their cells, or whether rapid viral clearance mechanisms activated in these cells inhibit the establishment of sustained viral transmission within waterfowl populations. To address these questions, we first conducted an epidemiological survey of H9N2 virus in wild waterfowl and farmed ducks to clarify the prevalence of H9N2 in waterfowl hosts. Subsequently, using H9N2 isolates from both wild waterfowl and farmed ducks, we assessed their infection and replication capacities in terrestrial and aquatic poultry cells. Drawing on these epidemiological and cytological findings, we further examined the differential immune responses elicited by early BJ/94 lineage viruses (isolated before 2021) versus recent viruses (isolated in 2021 and thereafter) in waterfowl cells.
## Materials and methods
## Surveillance on influenza a virus in wild birds and farmed ducks
Influenza surveillance was conducted in wild birds (2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018)(2019)(2020)(2021)(2022)(2023) and farmed ducks (2017-2023) around Poyang Lake. Fecal (wild birds) and cloacal (farmed ducks) swabs were transported in medium containing antibiotics, maintained at 4 • C, and transferred to the laboratory. After inoculation into 9-to 10-day-old embryonated chicken eggs and incubation at 35 • C for 48 hours, allantoic fluids with HA activity were harvested for hemagglutination inhibition assay using a panel of WHO reference antisera to determine the subtype.
## Host identification of H9 AIV-positive wild bird specimens
Total DNA was extracted from fecal samples using the QIAamp® Fast DNA Stool Mini Kit (Qiagen, Cat no. 51604). A fragment of the Cytochrome Oxidase I gene was amplified by nested PCR with primers adopted based on the sequences reported in (Cheung et al., 2009). The PCR products were electrophoresed, and bands of the expected sizes were Sanger sequenced (Sangon Biotech). Contigs were assembled in SeqMan (DNASTAR) and compared against BOLD SYSTEMS V5.0 (https ://boldsystems.org/) for species identification.
## Whole-genome sequencing
Viral RNA was extracted (QIAamp Viral RNA Mini Kit, Cat no.52904) and reverse-transcribed into cDNA (PrimeScript II 1st Strand cDNA Synthesis Kit, Cat no.6210A). Sequencing libraries were prepared with the TruePrep DNA Library Prep Kit V2 for Illumina (Vazyme) and sequenced on the Illumina MiSeq platform using MiSeq Reagent Kits V3. Reads were assembled into contigs in GS De Novo Assembler V2.6. The resulting contigs were compared to GenBank influenza A virus sequences via BLASTn, and the best-matched sequence was used as the reference for reassembly in MIRA V5. The nucleotide sequence data reported in this paper have been submitted to GenBank with accession numbers PX480460 to PX480571.
## Phylogenetic analysis
Complete genomic sequences of influenza A viruses were retrieved from the GISAID EpiFlu™ database (http://www.gisaid.org) as of 13 May 2025. The retrieved sequences, together with those from this study, were aligned by gene segment using MAFFT V7.526. Robust maximumlikelihood phylogenies were then reconstructed with IQ-TREE V1.7 under the GTR+I + G4 substitution model, and branch support was estimated using 10,000 ultrafast bootstrap replicates.
## Viruses, cells and cytology experiment
This research employed six distinct viral strains, comprising two viruses from the Y439 lineage, designated as A/Mallard/Jiangxi/6120/ 2007 (MD6120) and A/Duck/Jiangxi/23466/2017 (DK23466), and four viruses from the BJ/94 lineage, labeled as A/Black-crowned Night Heron/Jiangxi/29577/2014 (BCNH29577), A/Eurasian Wigeon/ Jiangxi/25725/2023 (EW25725), A/Duck/Jiangxi/6490/2013 (DK6490), and A/Duck/Jiangxi/17502/2021 (DK17502). Viruses were propagated in 9-to 10-day-old embryonated chicken eggs, quantified using the TCID 50 assay, and stored at -80 • C before use.
CEF and duck embryo fibroblasts (DEF) cells were prepared from 9day-old specific pathogen-free embryonated eggs as previously described (Tian et al., 2019;Kim et al., 2024). The prepared cells were subjected to species identification, confirmation of fibroblast purity (> 99 %), assessment of cell viability, and exclusion of mycoplasma contamination. The experiment was approved by the Animal Welfare and Ethical Committee of Shantou University Medical College (Approval No. SUMCSY2025-001).
Confluent monolayers of CEF or DEF in 6-well plates were infected with each virus strain at a multiplicity of infection (MOI) of 0.01. Supernatants were collected at 0, 12, 24, 36, 48, 60, and 72 hours postinfection (hpi) and viral titers were determined by TCID 50 assay on MDCK cells. The experiment was performed with four replicates.
## Immune gene expression analysis
Total RNA from virus-infected or mock-infected cells was extracted using the QIAGEN RNA Mini kit (Cat no.74104). The expression of immune-related genes and the reference gene (GAPDH) was determined by qRT-PCR with the UniPeak U+ One Step RT-qPCR SYBR Green Kit (Vazyme, Cat no.Q226-01). Gene-specific primers were designed in Primer-BLAST and their sequences are listed in Supplementary Table 1. All reactions were performed in triplicate. The relative mRNA expression levels were calculated using the 2^(-ΔΔCt) method and normalized to GAPDH.
## Statistics
Statistical analyses were performed using GraphPad Prism V9.0. Data normality was verified by Shapiro-Wilk test. Two-group comparisons used unpaired two-tailed Student's t-test. For multiple group/time comparisons, two-way ANOVA followed by Tukey's multiple comparisons test was applied. A p-value < 0.05 was considered significant.
## Results
## Prevalence of the H9N2 virus in wild birds and farmed ducks
Terrestrial and aquatic poultry interact frequently during transportation and commercial distribution. High viral load in these dense populations raises ducks' and geese's susceptibility to chicken-origin H9N2 virus. Moreover, the interval between poultry transportation and subsequent sale or slaughter is comparatively short. Consequently, although market surveys often reveal a substantial incidence of H9N2 among aquatic poultry, it remains challenging to ascertain whether the detected H9N2 virus in these species is directly transmitted from terrestrial poultry or arises from limited intra-species transmission within the aquatic poultry population. This ambiguity complicates efforts to determine the potential for H9N2 virus to become transmissible among waterfowl populations. Thus, we investigate the infectivity and transmissibility of the H9N2 virus in aquatic poultry by monitoring its prevalence in both wild birds and farmed ducks.
To assess the prevalence of influenza viruses in wild avian populations, fecal samples were collected from wild birds at Poyang Lake over migratory bird seasons (October to February) covering the period from 2007 to 2023. Eight strains of the H9 subtype influenza virus were isolated from 186,658 samples. The H9 virus exhibited sporadic transmission patterns and demonstrated the capacity to infect a wide range of wild bird species, including migratory and resident birds. These isolates were detected from avian species belonging to three taxa: Anatidae [including Mallards (Anas platyrhynchos), Eurasian Wigeons (Mareca penelope), and Common Teals (Anas crecca)], Charadriiformes [including Wilson's Snipes (Gallinago delicata) and Temminck's Stints (Calidris temminckii)], and Pelecaniformes [represented by Black-crowned Night Herons (Nycticorax nycticorax)] (Table 1). These infected birds may serve as the local temporary reservoirs or long-distant carriers for the spread of H9 viruses in waterfowl. Notably, three H9N2 strains were isolated from black-crowned night herons on November 4 and 8, 2014, indicating that these viruses may have the capacity for intraspecies transmission within this population. Additionally, the presence of coinfection involving both H9 and H5 subtypes was observed in the fecal sample of common teal, implying the potential for the generation of offspring that could promote the spread of H9 in waterfowl.
Surveillance of farmed ducks was carried out in two farms located along the shoreline of Poyang Lake, each exclusively engaged in duck rearing. One of these farms, Ruihong Farm, becomes an isolated island during the high-water season (May to October). The other farm, Hengfeng Farm, is situated entirely on land and is surrounded by other duck farms. From 2017 to 2023, biweekly sampling was conducted at both sites. Among a total of 62,403 cloacal swab specimens analyzed, 404 were found to contain H9 influenza viruses, corresponding to an overall detection rate of 0.65 % (Supplementary Table 2). Analysis of the virus detection timelines indicates that the H9 virus manifested as multiple isolated outbreaks within farmed duck populations. Among nine monitored outbreaks, four exhibited an H9 detection rate exceeding 10 %, with the highest reaching 93.5 % (Fig. 1). Given the absence of viral detection in subsequent sampling events, it is inferred that the transmission period did not extend beyond two weeks.
## Evolutionary Origins of the H9N2 Virus in Wild Birds and Farmed Ducks
The HA gene phylogenetic tree exhibits three major evolutionary lineages circulating in Eurasia: Y439, G1, and BJ/94. Within the Y439 lineage, it includes the earliest wild bird H9N6 virus (MD6120) we detected from Poyang Lake. Additionally, H9N2 viruses obtained from Hengfeng Farm in October 2017 and Ruihong Farm in August 2018 cluster closely, forming sister branches (Fig. 2a). The external branches of MD6120 and the viruses from these two farm outbreaks correspond to early Eurasian wild waterfowl H9Nx viruses. The internal genes of these isolates originated from the Eurasian gene pool and demonstrated substantial homology (Fig. 2b to 2g and Supplementary Figure 1). These findings indicate that the two waves of H9N2 virus infections at the respective farms were likely caused by a single-source virus, which was introduced into the farms and subsequently disseminated among the duck populations.
In the HA phylogenetic tree, the remaining seven H9 viruses detected in wild waterfowl, along with the majority of H9N2 viruses isolated from farmed ducks, clustered together with the contemporaneous chicken H9N2 viruses within the BJ/94 lineage. Further analysis showed that the internal gene segments of these viruses all originated and diverged from ZJ/HJ-like viruses (Fig. 2b to 2g and Supplementary Figure 1). These findings suggest that although BJ/94 lineage H9N2 viruses predominantly circulate within chicken populations, they are capable of repeated transmission into relatively isolated farmed ducks as well as wild waterfowl populations. Notably, three H9N2 virus strains isolated from Black-crowned Night Herons formed a distinct cluster on a phylogenetic branch. These viruses demonstrated a high sequence homology of up to 99.8 %, and the remaining six genes similarly exhibited a substantial degree of evolutionary homology (Fig. 2 and Supplementary Figure 1). These findings suggest the Night Herons were a feasible
## Molecular characteristics of the H9N2 virus in wild birds and farmed ducks
The H9N2 virus has been endemic in chicken populations for an extended period, during which it has acquired adaptations to chicken hosts. To elucidate the origin of H9N2 viruses in farmed ducks and wild birds, we conducted a comparative analysis between these viruses and BJ/94 lineage virus focusing on molecular determinants associated with host specificity, infectivity, and transmissibility (Supplementary Table 3). Our analysis showed that the HA genes of these viruses harbor residues (e.g., 101Y, 194 L) that enhance affinity for SAα2,6-Gal receptors (predominant in terrestrial bird airways) and potential glycosylation sites (e.g., N-X-S/T motif at positions 21-24), both matching those in chicken-origin H9 viruses. Additionally, the polymerase complex (PB2-627E, PB1-368 V, and PA-409 N) and the NA gene (e.g., 3amino-acid deletion in the stalk region, a terrestrial bird adaptation trait), consistent with chicken-adapted H9 viruses. Collectively, these results indicate that H9N2 viruses introduced into farmed ducks and wild birds generally retain the molecular characteristics of terrestrial bird-adapted H9N2 viruses.
## Infectivity of the H9N2 virus from wild birds and farmed ducks in CEF and DEF cells
To investigate replication preferences, we selected H9 virus strains isolated from farmed ducks and wild birds of the BJ/94 lineage and compared their replication capacities with those of waterfowl-derived viruses from the Y439 lineage in both CEF and DEF cells. The wild bird MD6120 and the farmed duck DK23466 of the Y439 lineage showed significantly higher replication efficiency and peak level in DEF cells compared to CEF (p < 0.01) (Fig. 3a and3b), indicating preferential replication in waterfowl-derived environments. In contrast, two BJ/94 lineage viruses, DK6490 and BCNH29577, isolated in 2013 and 2014 respectively, displayed a replicative advantage in CEF cells. Viral titers were consistently sustained at significantly higher levels in CEF than in DEF cells, with a pronounced difference of nearly 100-fold at the peak (p < 0.01; Fig. 3c and3d), indicating replication dynamics adapted to terrestrial avian cells. However, the recent BJ/94 viruses, specifically DK17502 and EW25725, isolated in 2021 and 2023 respectively, demonstrated enhanced replication efficiency in DEF relative to CEF cells, analogous to Y439 lineage virus profiles (Fig. 3e and3f). These data demonstrate that initial sporadic incursions of the BJ/94 lineage into waterfowl maintained a replication preference for terrestrial poultry cells, whereas recent isolates exhibited enhanced replication ability in waterfowl cells Fig. 4
## Innate immune response induced by the H9N2 virus infection in DEF cells
Given that multiple epidemiological surveys in China have shown an increased detection rate of H9N2 in ducks and geese since 2020 (Yang et al., 2025), and our experimental data have revealed that the BJ/94 lineage H9N2 viruses isolated in 2021 and 2023 display distinct growth preferences in DEF cells compared to the BJ/94 lineage virus isolated in 2014, we further investigated the characteristics and differences in the activation of the innate immune response in DEF cells induced by viruses isolated before 2021 (early viruses) and those isolated in 2021 and thereafter (recent viruses).
The infection of H9N2 influenza virus in DEF cells triggers the activation of the RIG-I-like receptor-MAVS/STING-interferon/inflammatory cytokine signaling axis response. MD6120 (Y439 lineage) and BCNH29577 (an early virus of BJ/94 lineage) exhibited no significant differences in the activation timing, upregulation magnitude, and duration of mRNA expression for immune molecules including LGP2, RIG-I, MAVS, STING, TRIM25, TRIM27, IFN-β, TRAF2, NF-κB, IL-2, IL-6, and IL-8 (p > 0.05). However, compared with MD6120, infection with BCNH29577 led to a distinct increase in two key immune molecules: the pattern recognition receptor MDA5 and the transcription factor IRF7. At 4 hpi, MDA5 level triggered by BCNH29577 was already markedly greater than that induced by MD6120 (p < 0.05), and this gap continued to expand over the next 8 to 12 hours. Regarding IRF7, its upregulation caused by BCNH29577 at 4 hpi was over four times higher than that caused by MD6120. This marked increase in MDA5 and IRF7 likely contributed to the later production of IFN-α (at 8 hpi) and IFN-γ (between 8 and 12 hpi) following BCNH29577 infection, which was notably stronger than the response seen with MD6120.
In comparison to the early virus BCNH29577, the recent virus DK17502 triggered a stronger expression of factors involved in the RIG- I-like receptor-mediated interferon and inflammatory cytokine pathways. This was evidenced by substantially higher levels of LGP2 (at 8-12 hours), MDA5 (at 4 and 12 hours), STING (at 8-12 hours), TRIM25 (at 4 hours), IRF7 (at 8 hours), and NF-κB (at 8-12 hours) (p < 0.01). Importantly, the expression of LGP2 and MDA5 at 12 hours after infection showed even greater differences compared to BCNH29577 (p < 0.01). Additionally, unlike the early virus and the Y439 lineage MD6120 virus, DK17502 caused a considerable increase in STING expression (p < 0.01), which likely affected downstream NF-κB activity, leading to a more pronounced and progressively increasing upregulation of NF-κB compared to the early virus (p < 0.01). This upregulation not only resulted in high expression of IFN-α and IFN-γ but also significantly elevated the inflammatory cytokines IL-2, IL-6, and IL-8. The data showed that the upregulation of these inflammatory cytokines began at 8 hours post-infection and continued through 12 hours. Overall, these results suggest that the recent BJ/94 virus more effectively activates the RIG-I-like pathway and, through stimulation of STING and NF-κB, induces a markedly stronger innate immune and inflammatory response.
## Discussion
Our epidemiological investigation revealed that the BJ/94 lineage H9 virus, which has been well adapted to terrestrial birds, is capable of transmission to both farmed ducks and wild waterfowl. waterfowl populations (Li et al., 2003). Between 2006 and 2014, the prevalence of H9 subtype influenza virus in ducks from farms and markets located around Dongting Lake, Zhejiang Province, and Shanghai was recorded at a mere 0.06 % (Zhou et al., 2012;Deng et al., 2013;Wu et al., 2015). This lower detection rate indicates that during that period, the frequency of BJ/94 lineage virus infecting waterfowl was relatively low. In contrast, post-2016 data show a remarkable increase in H9N2 virus detection among ducks and geese (Bi et al., 2020;He et al., 2022;Yang et al., 2025), suggesting significantly escalated transmission to aquatic poultry in recent years. This impact has clearly extended to wild waterfowl: between 2014 and 2021, the BJ/94 lineage H9N2 virus was intermittently identified in wild birds inhabiting the Dongting Lake, Poyang Lake, and Yangtze River Delta aquatic ecosystems in China (Ge et al., 2018;Wang et al., 2021;Yao et al., 2022). Furthermore, in 2020, the BJ/94 lineage Y280-like viruses were first detected in poultry across two geographically separated regions of South Korea, presumably from wild birds migrating from China (Youk et al., 2022). Although the BJ/94 lineage virus has been introduced into wild waterfowl with increasing frequency, our observations over two consecutive sampling periods in farm ducks revealed that the H9N2 outbreak did not persist into the subsequent sampling interval. Additionally, within the phylogenetic framework, no monophylogenetic branch comprising clusters of waterfowl-derived H9 viruses has been identified to date. These findings provide further evidence that introduced H9N2 viruses cannot sustain transmission in waterfowl.
In animal studies utilizing BJ/94 viruses isolated from 1994 to 2012, researchers observed that virus shedding in ducks was characterized by low titers, short duration, and predominant upper respiratory tract involvement (SJCEIRS H9 Working Group, 2013;Wang et al., 2019;Kye et al., 2021). These results indicate that the viruses circulating during this timeframe exhibited substantially restricted infectivity in waterfowl. Additionally, infection with the H9N2 virus isolated in 2020 did not result in viral replication or the production of serum antibodies in ducks (Kye et al., 2021). In this study, viruses belonging to the Y439 lineage exhibited a tropism for waterfowl-derived cells. In contrast, the replication preferences of viruses from the BJ/94 lineage varied according to the time of isolation. Specifically, the early virus of the BJ/94 lineage showed significantly higher replication efficiency in CEF cells, whereas the recent viruses from this lineage displayed a pronounced replication capacity in DEF cells. Previous studies have demonstrated that intranasal infection of ducks with duck-adapted H9N2 virus results in viral shedding via the intestinal tract, with a prolonged duration of cloacal viral excretion observed in ducks relative to chickens (Wang et al., 2014). This observation aligns with our epidemiological data, which identified the presence of H9 virus in cloacal specimens from ducks, as well as with findings from cytological experiments. Collectively, these results suggest that following successive transmissions of the H9N2 virus among waterfowl, the recent virus has broadened its tissue tropism in ducks and exhibits enhanced infectivity compared to earlier viral strains.
The variation in host restriction observed between aquatic and terrestrial avian species can be partially attributed to differences in their immune response mechanisms to influenza viruses. A prominent distinction in the antiviral immune responses of ducks compared to chickens is the presence of the RIG-I mediated innate immune pathway in ducks (Barber et al., 2010). Our study on how the H9N2 virus triggers immune responses in DEF showed that viruses from the BJ/94 lineage, especially the latest strains, provoke a stronger immune reaction when infecting waterfowl cells. As a result, the virus is eliminated more effectively. This may explain field reports of brief outbreaks in duck populations, with infections lasting under two weeks. Furthermore, recent BJ/94 lineage viruses induce higher pro-inflammatory cytokines (IL-6, IL-8) than early ones. Notably, while low-pathogenic influenza rarely elevates duck IL-8, recent BJ/94 viruses trigger IL-8 responses similar to highly pathogenic H5N1 (Cheung et al., 2002;Chan et al., 2005). The production of IL-8 may be associated with STING upregulation. Evidence indicates that overexpression of STING in DEF increases pro-inflammatory cytokines (IL-1β and IL-8) expression (Cheng et al., 2019), and promotes duck interferon regulatory factor 1 (IRF1), which interacts with duck myeloid differentiation factor 88 (duMyD88) to activate the transcription of interferon-stimulated genes (ISGs) in DEF (Qian et al., 2018).
Given that the introduction of the H9 virus into farmed duck populations and wild waterfowl predominantly occurs through isolated events, and that viruses originating from distinct introduction incidents exhibit genetic variations, it remains challenging to definitively identify the molecular features of the H9 virus that differentiate those introduced into farmed duck flocks and wild waterfowl from the strains circulating within terrestrial poultry.
Our findings suggest that the H9 viruses, which are well adapted to terrestrial poultry, may have progressively developed enhanced infectivity toward waterfowl through successive infection events. However, viral replication in waterfowl is effectively restricted by host immune response, thereby preventing its long-term colonization in waterfowl populations. At present, there is a new equilibrium between the virus's increased ability to infect waterfowl cells and the stronger immune response it triggers. This balance explains the epidemiological observation that the virus can frequently enter waterfowl populations yet fails to establish stable viral lineages therein. Nevertheless, the nature of this balance means there is always a potential risk that it could be disturbed. In wild waterfowl populations, the H9N2 virus has the potential to evolve into novel strains that can disseminate among wild birds. This evolution may occur through additional adaptation to waterfowl species or via genetic reassortment with other influenza subtypes already adapted to waterfowl. Such processes present a significant risk for the global spread of the BJ/94 lineage of the H9N2 virus.
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11. Guo, Wang, Zhao et al. (2021) "Molecular characterization, receptor binding property, and replication in chickens and mice of H9N2 avian influenza viruses isolated from chickens, peafowls, and wild birds in eastern China" *Emerg. Microbes. Infect*
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13. Jackwood, Stallknecht (2007) "Molecular epidemiologic studies on North American H9 avian influenza virus isolates from waterfowl and shorebirds"
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# A community-based focal serosurvey for West Nile virus infection following a surge in cases in 2024 in Kerala, India: a cross-sectional analysis
Chandhu Balachandran, Sakib Pattassery, Babasaheb Tandale, Vijay Parashramji Bondre, Veetilakath Jithesh, Mohammed Jaman, Bhavya Fernandez, S Harikumar, R Balasubramanian, Anisha Pulinchani, B Prema, Datta Butte, Abhijeet Jadhav
## Abstract
Background: From January to May of 2024, 27 cases of neuroinvasive disease due to West Nile Virus (WNV) were confirmed from Kerala. The number of cases were more than those seen over past three years combined. Cases were not clustered geographically and were primarily reported from four districts, viz, Kozhikode, Thrissur, Malappuram and Ernakulum. To understand the circulation of WNV, a focal serosurvey was conducted in the regions from where cases were reported. Methods: A cross-sectional study was done in four districts of Kerala. Patients, family members and immediate neighbours were recruited at each case location. From 27 clusters across 26 villages/localities, 751 blood samples were collected. Due to cross-reactivity of WNV antibodies and that of Japanese Encephalitis (JE) virus, a microneutralization assay was done against both these viruses for all the samples. Results: The seropositivity of WNV infection was found to be 29.96 % (26.68-33.24). Males had higher seropositivity than females, though the difference was not statistically significant. The overall seropositivity was higher compared to previously published studies. There was no significant difference in seropositivity across agegroups and sex. Seropositivity of JE infection was 1.86 % (0.90-2.83). Discussion: Though a smaller proportion of infected get neurological involvement, WNV seropositivity among considerable number of people in a wide geography of the state is a public health concern. Conclusion: To deal with this concern, more studies on bird-human interaction and larger serosurveys might be needed. Close monitoring and intervention planning are warranted to control possible future WNV spread.
## 1. Introduction
West Nile virus (Orthoflavivirus nilense) belongs to the genus Orthoflavivirus, Flaviviridae family [1]. The genome of West Nile virus (WNV) is a single-stranded, positive-sense RNA of about 11 kb in length. Globally circulating WNV isolates are grouped into nine lineages [2], with Indian isolates classified as lineage 5 [3]. WNV is a re-emerging virus maintained in an enzootic cycle among the birds primarily and Culex genus mosquitoes. Mammals, including humans and horses, are dead-end hosts [4]. Clinically, 80 % of all WNV infections are asymptomatic, while 20 % cases show West Nile Fever (WNF) with mild symptoms including fever, headache, fatigue and rash. A small proportion of cases (one in 150 cases) develop severe disease involving the nervous system, called WNV Neuroinvasive Disease (WNND) with features of meningitis, encephalitis or acute flaccid paralysis [5]. Currently, there are no specific antivirals or vaccines licensed for human use [6].
There are no pathognomonic signs or symptoms of WNF, and the diagnosis is primarily based on laboratory tests. Nucleic acid detection methods, including RT-PCR with good sensitivity and specificity [6] are available. However, these are useful only in samples collected in the early stage of the disease and hence, diagnosis is usually done by the detection of WNV-specific IgM antibodies in serum or cerebrospinal fluid [7]. Serological assays are challenging to interpret in areas with co-circulation of antigenically related flaviviruses, due to extensive cross-reactivity [8,9]. This makes differentiation of flaviviral infections difficult in India, due to co-circulation of Japanese encephalitis (JE) virus, Dengue virus, Zika virus and WNV [10,11].
The first serological evidence of WNV circulation in India was reported in 1952 [12]. Since then, multiple cases have been reported from Indian states including Maharashtra, Karnataka, Tamil Nadu, Kerala, Andhra Pradesh, West Bengal, Madhya Pradesh, Gujarat, Orissa, Rajasthan and Assam [13][14][15][16][17]. Among these, the 2011 outbreak in Kerala was peculiar due to the detection of lineage 1 of WNV [18]. Since 2011, large-scale outbreaks of WNV infection have not been reported from Kerala, even though the circulation of the virus was detected among ducks in the region [19]. In 2024 (January-May) a surge of WNND cases was reported (27 cases) by the Directorate of Health Services, Government of Kerala [20] mainly from four districts, and throughout the year 2024, 36 such cases were reported from seven districts.
By, May 2024, the higher occurrence of WNND was clear and there was a concern among state health officials and experts. Hence, a focal serosurvey was undertaken in the most affected districts till then, i.e. Kozhikode, Thrissur, Malappuram and Ernakulum, to understand the concealed circulation of WNF in this region.
## 2. Materials and methods
## 2.1. Study design and sampling
A cross-sectional study was adopted to carry out the focal serosurvey. Efforts were made to visit all possible households of all 27 patients that were reported from January to May 2024, with an aim to collect around 25 serum samples from each locality. Blood samples were collected from 06 to 15 Oct 2024. After obtaining written, informed consent, 5 mL blood sample was collected from each participant in serum separator tubes (BD Biosciences, 367986), from patients, family members and neighbours of West Nile Fever/neuroinvasive disease confirmed patients. The selection criteria for neighbours was the families sharing a border with the confirmed patient's house or in its immediate vicinity. Samples were transported to the nearby Government health facility, allowed to sit undisturbed at room temperature for 30 min, centrifuged at 2000g for 15 min and the separated serum, transferred to cryovials (Tarsons, 523184) before shipping to the Encephalitis laboratory at the ICMR-National Institute of Virology, Pune. Samples were shipped using dry ice shipment and on receipt at the laboratory, stored at -80 • C before processing.
## 2.2. Serological assays
Exposure to WNV was confirmed by using the microneutralization assay [21]. Briefly, two-fold serial dilutions of heat-inactivated sera (from 1:10-1:1280) were incubated with two log-50 % tissue culture infective dose (TCID 50 ) of Vero-cell adapted WNV isolate (NIV KLU181), for an hour at 37 • C. The virus-serum mixture was then added to a monolayer of Vero cells (ATCC-CCL-81) in 96 well flat-bottomed tissue culture plates (Corning, 3596) and incubated at 37 • C with 5 % CO 2 for 96 h. Ten-fold serial dilutions of the virus without serum (virus control) and mouse polyclonal anti-WNV serum (positive control) served as assay controls. In parallel, the samples were tested for the presence of neutralizing antibodies against Japanese encephalitis virus (JEV) using isolate (NIV 733913) and mouse polyclonal anti-JEV serum as positive control. Neutralizing titre was expressed as the reciprocal of the serum dilution showing 100 % neutralization of the virus. Samples with titre ≥1:40 was considered positive. Samples showing a titre above forty and equal for both JEV and WNV were considered to be equivocal, indicating the person is exposed to both the viruses.
Ethics statement: The study was approved by the Institutional Ethics Committee of the Indian Council of Medical Research-National Institute of Virology [ICMR-NIV] [No: NIV/IEC/January/2025/D-1] and Kerala State Health authorities.
## 3. Results
For this focal sero-survey, a total 751 blood samples were collected. All the NDDW 27 cases during the surge of cases from Jan to May 2024 were considered for investigation. The households and locations of 27 cases were visited by the investigation team. Serum samples were obtained from 19 cases, 49 family members and 683 neighbours. Two patients had succumbed to the disease, while two children were unwilling to provide samples. Four of the confirmed cases were out of station during the period of sample collection. From each patient cluster, 17 to 43 samples were collected, depending upon the family size, number of neighbouring households and willing population. The geographical distribution of the selected clusters is shown in Fig. 1.
Out of the 751 samples, 225 were confirmed positive for WNV neutralizing antibodies [29.96 % (C.I. 26.68-33.24 %)]. Table 1 gives the descriptive findings of sero-positivity. In Ernakulum district seropositivity was highest, which could be due to the fact that only two clusters and 31 people were covered in that district. Next were Thrissur, Kozhikode and Malappuram in decreasing order of sero-positivity. Table 2 gives sex-wise sero-positivity rates for WNV and JE virus. Of the 751 samples, 247 were males (87 positives) and 504 were females (138 positives). The higher proportion of women participants (67.11 %) may be attributed to the timing of the survey, which was conducted during daytime hours.
The maximum proportion of WNV sero-positives was in the agegroup of 41-60 years, followed by 61 and above age-group. (Table 3). Among all the samples, 14 samples [1.86 % (C.I. 0.90-2.83)] were positive for Japanese encephalitis virus neutralizing antibodies, with 8 (3.24 %) men and 6 (1.19 %) women. 3 samples were positive for both, indicating exposure to both WNV and JE viruses. Out of the total samples, 515 samples were found to be negative for both WNV and JE virus neutralizing antibodies [66.58 % (C.I. 65.26-71.90)].
West Nile virus serostatus was analyzed using a Generalized Linear Mixed Model (GLMM) with a random intercept for each of the 27 patient clusters, allowing for the fact that individuals within the same cluster may share similar exposures or environments and therefore may not be statistically independent. To quantify how strongly serostatus results tended to resemble one another within the same cluster, the intra-cluster correlation coefficient (ICC) was estimated. It gave a moderate ICC value of 0.372 (SE 0.08185; 95 % CI 0.204-0.519). This indicates that a meaningful proportion of the remaining variability in sero-positivity is explained by shared, cluster-level influences such as local ecological or socio-environmental factors, even after accounting for individual-level characteristics like age and sex.
## 4. Discussion
The current study was undertaken in response to a WNV outbreak in different districts of Kerala [20]. Following the first outbreak of West Nile virus in Kerala in 2011 [18], the state surveillance systems have been continuously reporting sporadic cases, with the annual maximum number of cases (n = 16) reported in 2023 [22]. This makes the 2024 outbreak with 36 cases the largest in over a decade. This focal sero-survey was carried out to understand the hidden circulation of WNV in the affected districts. Focal surveys are helpful in the context of emerging and re-emerging infections by producing evidence of the presence of a pathogen, its spread, concealed circulation, identification of geographical areas with virus circulation, and assessment of sub-clinical infections. The study identified a WNV sero-positivity rate of 29.96 % among the participants, which is higher than the previous reports of sero-prevalence [21]. Among the age group of '10 years or less', 10 children (55.56 %) out of 18, were positive. Both these findings indicate a continued circulation of WNV in different parts of Kerala.
Kerala state at the southern tip of India, has been facing an increased incidence of zoonotic diseases including scrub typhus, Nipah virus, Lyme disease and leptospirosis. This has been attributed to various factors including increasing urbanization, population movement, climate change, and changes in agricultural practices, leading to increased stress on the local ecosystems [23]. The state has a unique geography with vast areas covered by coastal wetlands where paddy cultivation and duck rearing happen simultaneously [24]. The state also lies along the central Asian flyway of winter bird migration pathways with multiple lakes and wetlands that serve as wintering grounds for many species of migratory birds and there are some bird sanctuaries as well in the state [25]. The state also has an abundance of mosquito vectors, particularly belonging to Culex genus which constitute more than 70 % of the mosquito catch in coastal areas of Kerala [26]. This creates a favourable environment for the exchange of pathogens, including WNV and highly pathogenic avian influenza virus, between migratory birds and domestic ducks [27]. Previous studies have identified wide spread of WNV circulation among ducks [19] and wild birds [28] from Southern India. However, recent attempts to detect WNV in mosquitoes have been unsuccessful [29]. The continuing circulation of West Nile virus, as evidenced by high sero-positivity, along with the presence of an epidemic-prone lineage 1a virus reported recently [30] and an abundant vector mosquito population, in a conducive ecological setting, highlights the risk of future outbreaks.
The study highlights the importance of integrating focal serosurveys into routine outbreak response activities as a cost-effective option for emerging infections compared to large-scale community-based serological surveys. Focal serosurveys are also a time-efficient, logistically feasible approach with minimal strain on existing public health system, to generate critical, preliminary data that can inform the design of larger community-wide sero-epidemiological studies as well as immediate public health interventions. Nonetheless, integrated surveillance approaches combining stakeholders involved in human health, vector and animal health sectors is the need of the hour. Implementing event-based or syndromic surveillance for acute encephalitis syndrome [31], strengthening laboratory capacity to detect human and animal infections and improving vector surveillance systems are critical to prevent future outbreaks and to minimize the public health impact of emerging or re-emerging viral infections.
## CRediT authorship contribution statement
## References
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26. Shil, Balasubramanian (2017) "Meteorological parameters and mosquito species diversity and abundance along the Arabian Sea coastline of Alappuzha district, India: a year-round study" *J Mosq Res*
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# Development of a dual-target measles virus PCR assay and testing trends at a national reference laboratory
Cole Anderson, Megha Rawal, Weston Hymas, Patricia Slev, Benjamin Bradley
## Abstract
In 2025, measles cases in the United States have reached their highest level since the disease was officially declared eliminated in 2000. Molecular assays may assist in the early diagnosis of measles and improve contact tracing efforts. In this manuscript, we describe the validation of a real-time PCR assay on the Hologic Panther Fusion Open Access system for the detection of measles virus (MeV) and differentiation between wild-type and vaccine strains. After implementation, we examined 3 months of clinical testing data to understand testing trends and utilization. Over the study period, a total of 525 tests from 491 patients were performed. MeV was detected in 16 specimens with 6 wild-type and 10 vaccine strain identifications. Children less than 10 years old constitu ted the largest proportion of tested individuals (54.3%) and vaccine strain detections (9/10, median age 1.2 years), while wild-type infections were observed in individuals aged 20-50 (6/6, median age 32.6 years). Those with vaccine strain detected had significantly higher Ct values for the pan-measles target versus wild-type infections (33.6 vs 28.3; P-value < 0.05). Only 4.2% of patients in our cohort received paired serologic and molecular measles testing. When paired data were available, PCR had a positive agreement of 25% and a negative agreement of 98% with IgM results. Molecular testing for MeV with the ability to differentiate wild-type strains from vaccine strains is a helpful tool in the response to measles re-emergence.
IMPORTANCEThe 2025 U.S. measles outbreak comes at a challenging time for public health in America. As vaccine hesitancy increases and resources are withdrawn from national and state public health laboratories, historically low incidence diseases develop into nationwide outbreaks that require increased testing capacity. In response to this need, our national reference laboratory developed a measles PCR assay that allows for the detection and separation of vaccine from wild-type strains. The assay was launched on the Hologic Panther fusion system to improve throughput and reduce turnaround times. In this research article, we describe the design of our assay, validation results, and early clinical performance. KEYWORDS measles, PCR, assay development, vaccine strain, genotype A M easles was declared eliminated from the United States nearly 30 years ago, after sustained high two-dose coverage with the measles-mumps-rubella (MMR) vaccine was achieved. Since then, national vaccination rates have ranged between 90% and 93%, below the recommended 95% threshold for sustaining elimination, with considerable variation at the state and county levels (1). For example, in New York and Idaho, the two-dose MMR vaccine coverage rates during the 2023-2024 school year were 97.7% and 79.6%, respectively (2). Disruptions caused by the COVID-19 pandemic and an upsurge in vaccine misinformation and hesitancy have been attributed to declining vaccination rates. As a result, the United States has seen over 1,600 measles cases to date in 2025, the highest number since measles was declared eliminated in the United States
in 2000 (3)(4)(5). Many of these cases have been associated with a large outbreak in Gaines County, Texas (6).
Clinically, measles presents as a febrile rash with cough, coryza, or conjunctivitis. In non-outbreak settings, these clinical findings have a low positive predictive value and can be difficult to distinguish from other common infections, thus highlighting the need for laboratory confirmation (7). The detection of measles virus-specific IgM antibodies is often used for confirming measles infection; however, certain performance limitations must be considered. There is known cross-reactivity of IgM between other common febrile rash illnesses, such as parvovirus B19, rubella, Epstein-Barr virus, and cytomega lovirus (8). In low-incidence settings, where measles has been eliminated, the positive predictive value of IgM serology is exceedingly low (9). Furthermore, a quarter of measles patients do not have detectable IgM antibodies within the first 72 h after rash onset, nor can it be used to distinguish between vaccine-induced rashes and wild-type infections. Considering these limitations, current Centers for Disease Control and Prevention (CDC) guidelines recommend PCR and IgM testing for diagnosis of acute measles (10).
Measles virus (MeV) RNA can be detected by reverse transcription real-time PCR (RT-PCR) from properly collected and transported respiratory and urine specimens, ideally obtained as early as possible after rash onset. One of the first published RT-PCR assays was a pan-measles assay that could detect but not differentiate between vaccine (genotype A) and wild-type strains (11). In regions that have eliminated endemic measles, the ability to distinguish wild-type infections from vaccine-induced rash is critical as vaccine strain MeV is not considered contagious and patients do not require airborne precautions. It is estimated that 5% of individuals will develop some form of rash following measles vaccination (12). Historically, separation of wild type from vaccine strain MeV was performed via Sanger sequencing (10). However, sequencing can take several days to perform and is only available through select public health laboratories and the CDC, thus limiting the clinical actionability of these results. Newer PCR assays with the ability to specifically detect the vaccine strain have since been developed. Roy and colleagues designed an assay (MeVA) that relies upon a 23-base sequence that is shared across all vaccine strains but differs by 1-5 nucleotides within the highly conserved N gene amino terminus of wild-type strains (13). A similar assay has also been described for use on the Hologic Panther Fusion System, which is a fully automated, random access, and continuous loading system with a run time of approximately 3 h (14). Platforms that support high-throughput random-access testing improve turnaround times and support surge testing requirements often seen in outbreak settings (15).
In this study, we describe the analytical validation of a qualitative, dual-target RT-PCR assay (dt-MeV) that utilizes the Hologic Panther Fusion Open Access channel to detect MeV RNA with the ability to distinguish between vaccine and wild-type strains. We further examine clinical testing data and test utilization during the first 3 months of implementation at a national reference laboratory.
## MATERIALS AND METHODS
## Primers and probes
Primer and probe sequences from previously published assays were used to detect measles virus and the vaccine strain (11,13) (Table S1). The Hummel assay, referred to as the MeV target, will detect both vaccine and wild-type strains. The Roy assay, referred to as the MeVA target, is specific for vaccine strain only. Hologic internal control primers and probes were used to monitor for sample inhibition. Samples were reported as "measles virus detected" when the MeV (pan-measles) target was detected and the MeVA (vaccine) target was not detected. For purposes of this study, we categorized any MeV+/MeVA-samples as positive for wild-type measles, though this result could also be observed for vaccine strain samples with low viral load. Samples were reported as "measles virus, vaccine strain detected" when both the MeV and MeVA targets were detected. Interpretive result comments are provided in Table S2.
## Validation testing
Sample preparation and RNA extraction were performed as previously described for the Hologic Panther Fusion System (14). Optimized reagent concentrations and thermocy cling conditions are shown in Tables S1 andS3. Limit of detection (LoD) and accuracy were determined using positive culture material for vaccine strain and genotype B3 (wild type) which were quantified by droplet-digital PCR. Fivefold serial dilutions of the quantified cultures were made in VTM and urine samples. The lowest concentra tion where all six replicates amplified was established as the limit of detection, which was confirmed by performing an additional 20 replicates. For the vaccine strain, LoD determination required positive detection in both MeV and MeVA channels. To assess accuracy, a total of 80 samples-40 respiratory swabs (15 vaccine strain positive, 15 wild-type positive, and 10 negative) and 40 urine samples (15 vaccine strain positive, 15 wild-type positive, and 10 negative)-were tested. Performance was evaluated at low (10× LoD, n = 10), medium (100× LoD, n = 3), and high (1,000× LoD, n = 2) analyte concentrations. To evaluate the specificity of MeV and MeVA primers/probes, in silico analysis was performed against 18 clinically relevant pathogens. Previously tested clinical samples and control material were also used to evaluate cross-reactivity. Six different measles genotypes (D4, D8, D9, G3, H1, and B3) from cell culture material were tested to evaluate inclusivity (provided courtesy of Dr. Ryan Relich of Indiana University).
## Clinical data
Clinical data were obtained from an in-house database that included PCR and IgM/IgG results and patient demographics. For serological testing, measles IgG was performed by a chemiluminescent immunoassay (Diasorin Inc., Stillwater, MN), while IgM was performed by enzyme-linked immunosorbent assay (Awareness Technology, Quest International, Doral, FL). This study was performed under University of Utah IRB00007275.
## Statistical analysis
Graphing and related statistics were performed using GraphPad Prism (Version 10.5.0). Turnaround times, defined as time from sample receipt to reported result, were analyzed using Tukey's multiple comparisons test. Probit analysis was conducted to determine LoD using MedCalc (Version 23.1.7). Continuous variables were analyzed using the Mann-Whitney test, and data are reported as medians and 25%-75% interquartile ranges (IQRs).
## RESULTS
Validation studies of the dt-MeV assay demonstrated acceptable performance character istics. The estimated LoD in copies/mL for genotype B3 (wild type) and vaccine strain (genotype A) in respiratory samples was 3,039.8 (95% CI: 1,722.0-10,634.9) and 689.8 (95% CI: 398.5-2,178.2), respectively, as calculated by Probit analysis (Table 1; Fig. S1). Similar LoDs were observed using a manual approach with nucleic acid extraction on the Chemagic MSM I (Perkin Elmer) and amplification on the QuantStudio 12K Flex (Thermo Fisher Scientific) RT-PCR instrument (Table S4). All contrived specimens with spiked-in vaccine and wild-type strains at various multiples of the LoD (10-1,000×) were detected by the dt-MeV assay for an analytical sensitivity of 100% (Table S5). Similarly, measles RNA was not detected in negative specimens, and cross-reactivity was not observed when tested against 18 clinically relevant viruses (Table S6). Inclusivity was assessed against six wild-type genotypes (D4, D8, D9, G3, H1, and B3), including genotype D8 which has been responsible for the majority of U.S. measles cases in 2025. All wild-type isolates were appropriately detected in the MeV channel and not detected in the MeVA channel.
From April to July 2025, 525 measles PCR tests were ordered for 491 patients (Fig. 1A). Daily PCR test volume averaged 5.7 (range, 1-14) tests per day during this period, while combined IgM only and IgM/IgG averaged 51.7 (range, 0-110) tests per day. Over 85% (n = 449) of the specimens submitted for PCR were from a respiratory source (Fig. 1B). In 14 patients, urine was the only specimen submitted, while 27 patients had both urine and respiratory samples tested. The average turnaround time (in lab to verified result) for measles PCR and IgM was 27.0 and 30.3 h, respectively (Fig. 1C).
Of the individuals tested by PCR, 54.3% (n = 267) were 0-10 years old, including 20.6% (n = 101) aged 0-1 years old (Fig. 2A). Other age groups ranged from 1.2% to 9.4%. Measles was detected in 16 patients by PCR. The vaccine strain was detected in 10 of these patients, while wild-type virus was detected in 6. Invalid results due to internal control failure occurred in eight patients (1.5% of testing volume). Of the vaccineassociated cases, 90% (9/10) were identified in 0-10 year olds with a single vaccine case identified in an individual 70-80 years old (Fig. 2B). All wild-type cases were in patients 20-50 years old (n = 6). The median age for vaccine-associated cases was 1.2 (IQR 1.1, 1.8) years, while the median age for wild-type cases was 32.6 (IQR 16.7, 37.0) years (Fig. 2C). Cycle threshold (Ct) values for the pan-MeV target were significantly higher in vaccine cases than in wild-type cases (33.6 vs 28.3; P-value < 0.05) (Fig. 2D). For vaccine-associ ated cases, the mean MeVA Ct was slightly higher than the MeV Ct, though this did not reach statistical significance (31.7 vs 31.0; n.s.).
Data were collected regarding potential measles diagnostic testing (IgM, IgM/IgG, and PCR) performed by our laboratory during the 3-month study period. Overall, IgM alone was the most commonly ordered test during this period (54.3%, n = 2,946), followed by IgM/IgG in combination (32.4%, n = 1,756). PCR constituted a minority of the overall patient testing volume at 9% (n = 491) with only 4.2% (n = 230) of patients in our cohort receiving orders for both serology (IgM ± IgG) and PCR (Fig. 2E). Of patients with both PCR and IgM results, 88% (n = 202) were negative. Both measles RNA and IgM were detected in six patients (three vaccine and three wild type), while four patients with negative IgM had detectable measles RNA (three vaccine and one wild type) (Table 2). Measles RNA was not detected in 18 patients with positive IgM serology (one invalid in a patient who received the MMR vaccine 1 month prior to sample collection) (Table S7).
When compared to IgM serology, measles PCR had a positive and negative percent agreement of 25% (95% CI: 0.12-0.45) and 98% (95% CI: 0.95-0.99), respectively.
## DISCUSSION
The public health response to measles outbreaks requires considerable resources to quickly identify exposed cases and to initiate MMR vaccination campaigns in nonimmune populations. The dt-MeV assay presented in this study is a rapid, highly sensitive, and specific assay to detect and differentiate vaccine-associated and wild-type measles strains. The limit of detection between the vaccine strain and genotype B3 (wild type) was within 1 log 10 (689.8 vs 3,039.8 copies/mL, respectively). We did note that Ct values were slightly higher for the MeVA target versus the MeV target. This replicates prior studies which found that the MeV target may be 10-fold more sensitive as compared to the MeVA target (11,13). This can potentially lead to a false-positive wild-type result when testing a specimen with a low concentration of vaccine strain virus if using our reporting criteria. For example, we identified a vaccine strain case with a subtle MeVA signal that was initially called "Not Detected" by the instrument software but on repeat testing generated a "Detected" result (Fig. S2). The patient in this case had received their first MMR dose 11 days prior to specimen collection. Immunization history was also available for two additional vaccine cases where patients had received the MMR vaccine at 11 and 39 days before specimen collection. The clinical impact of misidentifying a vaccine strain isolate as wild type could lead to unnecessary patient isolation and contact tracing (9,11). During the first 3 months of clinical testing, measles virus was detected in 16 patients with 10 vaccine-associated and six wild-type cases reported. Given the MMR vaccine schedule begins at 12 months, it is unsurprising that the majority (9/10) of vaccine detections occurred in children 0-1 years old with a median age of 1.2 years. This is in comparison to the wild-type cases which were detected at a median of 32.6 years. Interestingly, a single vaccine-associated case in the 70-to 80-year-old cohort occurred in an immunocompromised patient who received the MMR vaccine over 1 month before testing and subsequently developed severe pneumonia. In this case, the measles virus vaccine strain was detected from the patient's nasopharyngeal and bronchoalveolar lavage specimens. The MMR vaccine is contraindicated in immunosuppressed individu als, and vaccination may lead to pneumonia, encephalitis, or death (16).
In vaccine-associated cases, the MeV Ct value was significantly higher than that in wild-type cases, which is consistent with previously published reports on vaccine-associ ated cases. In an Ohio outbreak in 2022, Washam et al. reported a median Ct of 33.7 for vaccine cases versus 19.0 for wild-type cases (17). In our study, we saw similarly high MeV Ct values for vaccine cases at 34, but the difference when compared to MeV Ct values for wild-type cases, while statistically significant at Ct 27.8, was not as pronounced as the Washam study. One potential explanation for this is that our cohort included previously vaccinated patients who were experiencing breakthrough wild-type infections due to secondary vaccine failure, where protective immunity wanes over time. In these patients, clinical presentation is often mild, and measles RNA can be detected in the setting of an IgG response with a transient or absent IgM response (18). Studies suggest that individuals experiencing breakthrough measles infections will have higher Ct values (19). While vaccination histories were not available for all the wild-type infections in our cohort, in discussions with the treating physician, at least two were confirmed to have been vaccinated.
Measles vaccination is recommended as post-exposure prophylaxis for unvaccinated children who have been exposed to measles virus. Therefore, it is theoretically possible that a co-infection with vaccine and wild-type measles virus could occur. While no documented co-infections have been reported, our dt-MeV assay is not designed with a specific wild-type target. In the event of a co-infection, the sample would be reported as "Measles virus vaccine strain detected" based on positive MeV and MeVA signals. However, experimental mixing studies with vaccine and wild-type measles virus have shown that the difference between MeVA and MeV Ct values can potentially help identify co-infected patients. Specifically, a Ct difference of 3.54 between MeVA and MeV was shown to have a sensitivity and specificity of 90% and 98%, respectively, in identifying co-infections (20). Current CDC guidelines mention both molecular and serologic (IgM or IgM/IgG) testing as tools for the diagnosis of acute measles. In our study, we found limited PCR testing relative to serology. Over 85% of patients received IgM testing alone or in combination with IgG during the 3 months in which PCR was available. A minority of patients, 4.2%, had both PCR and IgM testing ordered at our laboratory. While we did not receive the clinical indication for testing, these data may suggest underutilization of PCR testing during our study. Reasons may include limited access during the first months of availability as the assay required client sites to build an orderable test in their electronic medical record, use a "miscellaneous" test order, or complete a faxed test requisition. Further, we cannot exclude that physician awareness of this testing option is low due to molecular measles testing being historically available only through public health laboratories and the CDC. The rapid turnaround time for our dt-MeV assay at 27 h was faster than serology and argues that complete diagnostic testing for measles can quickly be achieved during outbreaks.
There are several limitations of this study. As a national reference laboratory, we only had access to test results that were performed within our system. It is likely that patients included in this study had additional testing elsewhere and that the overall rate of co-testing by PCR and IgM was higher than reported here. Over one third of the IgM orders placed were part of a combined IgM/IgG order set. In these cases, the intent may have been to assess vaccination status rather than diagnose acute measles, even though IgM testing is not recommended for evaluating vaccination status. Furthermore, we did not have access to clinical or vaccination histories to help adjudicate PCR negative/IgM positive results. We did not place any restrictions on acceptable patient specimens and therefore may have experienced a higher number of vaccine detections as compared to public health laboratories, which often require an evaluation of epidemiological risk prior to measles testing. In the latter situation, inclusion of the MeVA target may be less essential as part of the testing algorithm.
Our study highlights the inherent difficulties commercial, reference, and clinical laboratories face in responding to emerging and re-emerging pathogens. One is a lack of clinical isolates for assay development and validation. We relied on contrived samples using cultured isolates during our validation as clinical isolates of measles were not readily available. This is a familiar challenge faced during early development efforts for SARS-CoV-2, monkeypox virus, and influenza A(H5) viruses (21)(22)(23). Second is a lack of confirmatory sequencing data from the positive cases we reported. Specimens positive for wild-type measles were sent to their respective state public health laboratories for confirmatory testing. Of the six wild-type cases, sequencing (genotype D8) data were returned for one of these cases, and PCR confirmation was returned for another. These limitations argue for increased interoperability between clinical and public health laboratories through sharing of clinical isolates for assay development and exchange of confirmatory testing data to help monitor assay performance.
In summary, we demonstrate the feasibility and clinical implementation of an automated dual-target, RT-PCR assay for the detection and differentiation of wild-type and vaccine strain measles virus. Laboratories interested in developing a similar assay should focus on stewardship to reduce unnecessary testing in recently vaccinated populations and build provider awareness about the availability and accuracy of molecular testing.
## References
1. Dong, Saiyed, Nearchou et al. (2025) "Trends in county-level MMR vaccination coverage in children in the United States" *JAMA*
2. Seither, Yusuf, Dramann et al. (2024) "Morbidity and mortality weekly report coverage with selected vaccines and exemption rates among children in kindergarten-United States, 2023-24 school year" *MMWR Morb Mortal Wkly Rep*
3. Lo, Hotez (2017) "Public health and economic consequences of vaccine hesitancy for measles in the United States" *JAMA Pediatr*
4. Kiang, Bubar, Maldonado et al. (2025) "Modeling reemergence of vaccine-eliminated infectious diseases under declining vaccination in the US" *JAMA*
5. Hill, Yankey, Elam-Evans et al. (2024) "Decline in vaccination coverage by age 24 months and vaccination inequities among children born in 2020 and 2021national immunization survey-child, United States, 2021-2023" *MMWR Morb Mortal Wkly Rep*
6. Mathis, Raines, Filardo et al. (2025) "Measles update -United States" *MMWR Morb Mortal Wkly Rep*
7. Strebel, Orenstein (2019) "Measles" *N Engl J Med*
8. Bellini, Helfand (2003) "The challenges and strategies for laboratory diagnosis of measles in an international setting" *J Infect Dis*
9. Bolotin, Lim, Dang et al. (2009) "The utility of measles and rubella IgM serology in an elimination setting" *PLoS One*
10. Gastañaduy, Redd, Measles (2023) "Manual for the surveillance of vaccine-preventable diseases" *CDC*
11. Hummel, Lowe, Bellini et al. (2006) "Development of quantitative gene-specific real-time RT-PCR assays for the detection of measles virus in clinical specimens" *J Virol Methods*
12. Gastañaduy, Haber, Rota et al. (2021) "Internet. Epidemiology and prevention of vaccine-preventable diseases. 14th ed. US Department of Health and Human Services" *CDC*
13. Roy, Mendoza, Hiebert et al. (2017) "Rapid identification of measles virus vaccine genotype by real-Time PCR" *J Clin Microbiol*
14. Grant, Atapattu, Dilcher et al. (2023) "Develop ment of real-time RT-PCR assays to detect measles virus on the Hologic Panther Fusion System" *J Clin Virol*
15. Zhen, Manji, Smith et al. (2020) "Comparison of Four Molecular In Vitro Diagnostic Assays for the Detection of SARS-CoV-2 in Nasophar yngeal Specimens" *J Clin Microbiol*
16. Jcm
17. Chang, Bisht, Faysman et al. (2021) "Vaccine-associated measles in a hematopoietic cell transplant recipient: case report and comprehensive review of the literature" *Open Forum Infect Dis*
18. Washam, Leber, Oyeniran et al. (2024) "Shedding of measles vaccine RNA in children after receiving measles, mumps and rubella vaccination" *J Clin Virol*
19. Hübschen, Bork, Muller et al. (2017) "Challenges of measles and rubella laboratory diagnostic in the era of elimination" *Clinical Microbiology and Infection*
20. Gibney, Attwood, Nicholson et al. (2008) "Emergence of attenuated measles illness among IgG-positive/IgM-negative measles cases: Victoria, Australia"
21. Stanoeva, Kohl, Bodewes (2021) "Co-detection of the measles vaccine and wild-type virus by real-time PCR: public health laboratory protocol" *Access Microbiol*
22. Greninger, Jerome (2020) "The first quarter of SARS-CoV-2 testing: the university of Washington medicine experience" *J Clin Microbiol*
23. Caldera, Gray, Garner et al. (2023) "FDA trial regulation of laboratory developed tests (LDTs): an academic medical center's experience with Mpox in-house testing" *J Clin Virol*
24. Pinsky, Bradley (2024) "Opportunities and challenges for the U.S. laboratory response to highly pathogenic avian influenza A(H5N1)" *J Clin Virol*
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# Genome sequence of a human monkeypox virus isolate from Central Europe during the 2022 outbreak
Gergely Ármin, Nagy, Ágota Ábrahám, István Prazsák, Balázs Kakuk, Brigitta Zana, Ágnes Nagy, Dóra Tombácz, Gábor Kemenesi, Zsolt Boldogkői
## Abstract
We report the genome sequence of a human monkeypox virus isolated from an early Central European case. The 197,993 bp genome was assembled from amplicons sequenced using the Oxford Nanopore method. It has a GC content of 32.9% and belongs to subclade IIb B.1.3.
T he human monkeypox virus (hMPXV) is a zoonotic virus in the Orthopoxvirus genus of the Poxviridae family (1,2), closely related to the smallpox-causing variola virus (3). In August 2024, the World Health Organization declared hMPXV a public health emergency of international concern, and it is now listed among emerging pathogens with pandemic potential (4,5).
To support a better understanding of hMPXV evolution, we sequenced the virus isolate MPXV_NRL_4279/2022, obtained in 2022, from a patient's skin lesion in Prague, Czechia.
The virus was propagated under BSL-4 conditions at the National Laboratory of Virology, University of Pécs, and passaged once in Vero cells (ATCC, CCL-81) to pro duce sufficient quantity of infectious material. DNA extraction was carried out using the Direct-zol RNA MiniPrep kit (Zymo Research, USA), following the manufacturer's instructions except for DNase I treatment.
A set of 22 multiplex PCR primer pairs was designed to generate ~10 kb overlapping amplicons covering the viral genome. Primer sequences along with the detailed protocol are available on protocols.io (6). Briefly, repliQa HiFi ToughMix (Quantabio) was used to amplify complex and repetitive genomic regions from fragments with 50-100 bp overlaps. Two distinct PCR rounds were performed, each targeting non-overlapping segments. PCR products were purified using SPRI beads (AmpureXP) following the manufacturer's instructions. Sequencing libraries were prepared with the SQK-LSK110 kit (Oxford Nanopore Technologies, ONT) and barcoded using the EXP-NBD196 kit. Sequencing was performed on a MinION Mk1B device with an R9.4.1 flow cell (FLO-MIN106), yielding 29,404 reads with an N50 of 9,556 (Table 1).
Basecalling using the super-accurate model and adapter trimming was performed with Guppy 6.5.7 (7), and low-quality reads were filtered out using NanoFilt2.8.0. De novo assembly using Raven 1.8.3 (8) produced two contigs, which were merged into a single sequence using RagTag 2.1.0 (9).
To determine the exact genomic termini, the results of an additional direct RNAsequencing of our isolate (10) were utilized to generate a consensus sequence using samtools (11). The consensus matched the termini of the closely related, highly accurate OXO44336.2 genome (12). The complete, assembled genome is 197,993 bp in length and has a 32.9% GC content. It shows no frameshift mutations or premature stop codons, indicating no major disruptions in protein-coding regions. Comparison with the reference genome (NC_063383) revealed four deletions totaling 33 bp, all located in intergenic regions. Five nucleotide substitutions were identified, three of which resulted in amino acid changes within the OPG055 (F11), OPG130 (A5L), and OPG016 (N3R) genes (Table 1). Additionally, seven insertions were detected: two at the terminal ends, three within variable number tandem repeat regions (VNTRs), and two small insertions (Table 1). Whole-genome phylogenetic analysis using Nextclade v3.10.2 (13) indicated that the MPXV_NRL_4279/2022 isolate belongs to Clade IIb B.1.3 of hMPXV. This genome, associated with the 2022 multi-country outbreak, provides valuable insight into the evolutionary dynamics of poxviruses.
## References
1. Lansiaux, Jain, Laivacuma et al. (2022) "The virology of human monkeypox virus (hMPXV): a brief overview" *Virus Res*
2. Elsayed, Bondy, Hanage (2022) "Monkeypox virus infections in humans" *Clin Microbiol Rev*
3. Izadi, Mirzaei, Bagherzadeh et al. (2024) "Discovering conserved epitopes of Monkeypox: novel immunoinfor matic and machine learning approaches"
4. (2024) "WHO Director-General declares mpox outbreak a public health emergency of international concern"
5. Ukoaka, Okesanya, Daniel et al. (2024) "Updated WHO list of emerging pathogens for a potential future pandemic: Implications for public health and global preparedness" *Infez Med*
6. Nagy, Ábrahám, Prazsák et al. (2025) "Amplicon based sequencing of a human monkeypox virus isolate"
7. Wick, Judd, Holt (2019) "Performance of neural network basecalling tools for Oxford Nanopore sequencing" *Genome Biol*
8. Vaser, Šikić (2021) "Time-and memory-efficient genome assembly with Raven" *Nat Comput Sci*
9. Alonge, Lebeigle, Kirsche et al. (2022) "Automated assembly scaffolding using RagTag elevates a new tomato system for high-throughput genome editing" *Genome Biol*
10. Kakuk, Dörmő, Csabai et al. (2023) "In-depth temporal transcriptome profiling of monkeypox and host cells using nanopore sequencing" *Sci Data*
12. Danecek, Bonfield, Liddle et al. (2021) "Twelve years of SAMtools and BCFtools. Gigascience 10:giab008"
13. Monzón, Varona, Negredo et al. (2024) "Monkeypox virus genomic accordion strategies" *Nat Commun*
14. Aksamentov, Roemer, Hodcroft et al. (2021) "Nextclade: clade assignment, mutation calling and quality control for viral genomes" *J Open Source Softw*
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# Viral surveillance of invasive mammals in New Zealand reveals unique viral lineages reflecting their introduction history
Rebecca French, Florian Pichlmueller, Stephanie Waller, Jeremy Dubrulle, Jess Tuxford, Andrew Veale, Jemma Geoghegan
## Abstract
Introduced mammalian species in Aotearoa New Zealand pose significant ecological risks and may serve as reservoirs for novel or emerging infectious disea ses. In this study, we present the first metatranscriptomic survey of viruses in five introduced mammals: ferrets (Mustela furo), stoats (Mustela erminea), weasels (Mustela nivalis), brushtail possums (Trichosurus vulpecula), and European hedgehogs (Erinaceus europaeus), sampled across both the North and South Islands. Through total RNA sequencing, we identified 11 mammalian-infecting viruses spanning eight viral families, including four novel virus species: Ferret mastadenovirus, Possum astrovirus, Ferret pestivirus, and Weasel jeilongvirus. Whole genomes were recovered for six of these viruses, enabling detailed phylogenetic analysis. Notably, we observed strong global geographic clustering in both Wobbly possum disease virus and Ferret hepatitis E virus, suggesting localized viral evolution following the introduction of their hosts into New Zealand. In addition, the detection of Human rotavirus A in hedgehogs highlights the possibility of reverse zoonotic transmission. Together, these findings broaden our understanding of the viral diversity harbored by New Zealand's introduced mammals and provide a critical foundation for future biocontrol and disease surveillance efforts. IMPORTANCE Introduced mammals in Aotearoa New Zealand not only threaten native biodiversity through predation and competition, but also represent a largely overlooked source of infectious disease risk. Viruses circulating in these species may spill over into native wildlife, livestock, or even humans, while human viruses can also establish in introduced animals and create new reservoirs. Understanding which viruses are present, and how they evolve in isolated host populations, is critical for anticipating future disease outbreaks, improving biosecurity, and guiding wildlife management strategies. This work provides foundational knowledge that links ecology, conservation, and health, highlighting the need to consider pathogens as part of the broader impact of invasive species.KEYWORDS metatranscriptomics, virome, RNA sequencing, Wobbly possum disease virus, Ferret hepatitis E virus, biosecurity W ild mammals are key reservoirs of zoonotic pathogens, posing significant risks to human health (1). These animals harbor a wide range of zoonotic and pathogenic viruses, including rabies virus (2), hantavirus (3, 4), morbillivirus (5), and coronaviruses (6). Due to their role in disease ecology, wild mammals have become a central focus of virological surveys, where hundreds of novel viruses have been uncovered across many hosts, including in bats, rodents, and shrews (7-9). These investigations have often identified viruses closely related to those that cause disease in humans or other animals (8), as well as uncovered novel viruses, many with zoonotic potential (1).
Largely isolated from the rest of the world for more than 50 million years, Aotearoa New Zealand has a unique ecosystem with only two species of bats as the only extant native terrestrial mammals (10). However, numerous mammalian species have been introduced into New Zealand, mainly by European settlers since the 19th century, including stoats, weasels, ferrets, hedgehogs, and possums (11). Invasions of mammalian species are one of the major causes of global biodiversity loss and ecosystem change (12), and in New Zealand, these mammalian pests have been responsible for both local and country-wide extinctions of many native animals due to predation (13). These mammals are also likely to harbor numerous viruses, either introduced via their native ranges or those that have emerged since their introduction. It is therefore likely that mammalian pests are reservoirs for a vast array of viruses, potentially posing a significant threat to endemic species with no prior exposure (14), as well as to public health. Biological control of pest animals, including the use of host-specific viruses, could be a key tool to eradicating mammalian pests in New Zealand (15,16).
Very little is known about viruses in New Zealand mammals, with the primary focus for viral surveillance being limited to domestic animals. Viruses have been identified in New Zealand's bats (17,18), sea lions (19), long-finned pilot whales (Globicephala melas) (20), fur seals (Arctocephalus forsteri) (21), and Maui dolphins (Cephalorhynchus hectori maui) (22). Pathogenic viruses have also been identified in some wild introduced species, including Rabbit hemorrhagic disease virus in rabbits (23) and Wobbly possum disease virus in brushtail possums (24), as well as serological evidence that stoats are infected with multiple viruses (25). Nevertheless, the total assemblage of viruses (i.e., the virome) of many mammalian pests in New Zealand remains unexplored.
Herein, we used total RNA sequencing to uncover the viruses harbored in five introduced mammals in New Zealand, including ferrets (Mustela furo), stoats (Mus tela erminea), weasels (Mustela nivalis), brushtail possums (Trichosurus vulpecula), and European hedgehogs (Erinaceus europaeus), sampled across both the North and South Islands. Since ferrets, stoats, and weasels belong to the Mustela genus (Fig. 1A) and geographically overlap (26), we hypothesize that there is frequent cross-species virus transmission between these species compared to brushtail possums and hedgehogs. As the first virome-scale survey of introduced mammals in New Zealand, this study offers new insights into the evolutionary relationships and geographic distribution of mammalian viruses.
## RESULTS
We generated a total of 1.6 billion sequencing reads, with an average of 68 million per library (±11.2 million SD, Fig. 2). The hedgehog library had the highest viral abundance (>36,000 reads per million [RPM], Fig. 2; Table S2), while other libraries with high viral abundance included the two possum libraries (>800 RPM, Fig. 2; Table S2) and one ferret library (>1,500 RPM, Table S2). No viruses were detected in stoats sampled here.
We identified 20 virus transcripts that are known to infect mammals, spanning 11 virus species from eight viral families (Table 1), varying in abundance from 1 RPM (Weasel jeilongvirus) to >35,000 RPM (Hedgehog hepatovirus). Of these 11 virus species, four were considered novel since they shared <90% amino acid sequence similarity to other known viruses within the most conserved region (i.e., the polymerase). We recovered complete viral genomes from six virus species. We now describe the different groups of viruses in turn.
## Double-stranded DNA viruses
We identified two non-overlapping adenovirus fragments in ferrets sampled from the North Island, which we assume belong to the same virus (Fig. S1A). This adenovirus belongs to the Mastadenovirus genus, which we have provisionally named Ferret mastadenovirus. This virus was most closely related to Polar bear adenovirus 1 (27), with 73% amino acid identity. In addition, a short fragment of Human rotavirus A from the Sedoreoviridae family was found in hedgehogs sampled from the South Island at low abundance (<5 RPM, Fig. S1D; Table 1). The virus could not be genotyped for G or P type due to the short fragment length (379 nucleotides); however, the closest known genetic relative was Human rotavirus A strain RVA/Human-tc/JPN/K8/1977/G1P [9] sampled in Japan, with 94% nucleotide sequence similarity. A small number of human transcripts were present in the hedgehog library (accounting for 1.33% of the total read count), thus it is possible that the detected rotavirus fragment originated from trace human contami nation rather than active infection of the hedgehog. This level of human contamination was similar to all other libraries (which ranged from 0.75% to 5.33% human reads) where no human-infecting viruses were found.
## Single-stranded RNA viruses
We identified an astrovirus in possums across two libraries sampled in the South Island, which we have provisionally named Possum astrovirus. A complete viral genome (6,363 nucleotides) as well as a near-complete genome (5,446 nucleotides) was obtained. These sequences were 86% similar at the nucleotide level, and the ORF1b proteins (containing the RNA-dependent RNA polymerase, RdRp) were 94% similar at the amino acid level. We therefore considered these sequences to be from the same virus species. Like other astroviruses, Possum astrovirus had an ORF1a (encoding the protease), ORF1b (RdRp), and ORF2 (capsid) (Fig. 3B; Fig. S2A). It also had the ribosomal frameshift (AAAAAAC) near the end of ORF1a, to create ORF1a/b. Possum astrovirus was most closely related to Tasmanian devil-associated astrovirus 1 (28), with 56% amino acid sequence similarity. These two viruses formed a clade basal to the classified Mamastrovirus genus, but with strong bootstrap support (100%) (Fig. 3A).
Five viruses across two viral species were found within the Flaviviridae in ferrets and possums. We identified four full genomes of a novel pestivirus in ferrets sampled from across the South Island, now termed Ferret pestivirus. These sequences were 93%-95% similar at the nucleotide level but were highly divergent from other pestiviruses with the closest known virus, Rhinolophus affinis pestivirus 1, sharing only between 42% and 47% amino acid sequence similarity (Fig. 4A). Like other pestiviruses, these genomes consisted of a single polyprotein approximately 11.4 kb in length (Fig. 4B). We also identified the whole genome of Possum hepacivirus at high abundance (>3,000 RPM, Table 1) with 96% amino acid and 85% nucleotide sequence similarity and the same genome structure (Fig. 4C) to the virus first identified in Australian brushtail possums (29).
Full genomes of Ferret hepatitis E virus were recovered from ferrets sampled from across the South Island, sharing between 92% and 98% amino acid sequence similarity with each other, and up to 92% similar to previously identified strains of this virus (Fig. 5). Phylogenetic analysis of the whole genome showed clear geographic clustering, with the New Zealand strains being most closely related to those sampled in Japan (30) (Fig. 5B). Within New Zealand, there appear to be two distinct strains (denoted strain 1 and 2), with 86%-88% nucleotide sequence similarity between strains, and 95%-96% nucleotide sequence similarity within the strains. Strain 1 was found in the lower and upper parts of the South Island (Southland and Marlborough), while strain 2 was found closer to the center of the South Island (Canterbury).
Within the Arteriviridae, we identified Hedgehog arterivirus, previously found in European hedgehogs in the United Kingdom (31), sharing 92% amino acid sequence similarity (Fig. 6A). We also found two whole genomes of Wobbly possum disease virus (WPDV) in possums sampled from the South Island, with 86% nucleotide sequence similarity to each other. These genomes had the same structure as other WPDV sequen ces, with a large ORF1a/b polyprotein and a frameshift at a ribosomal slippage site (Fig. 6C; Fig. S2E). Phylogenetic analysis of these viruses along with the seven already identified whole genomes showed that they clustered with WPDV previously identified in New Zealand in 1995, sharing 94%-96% amino acid with those previously identified (24) (Fig. 6B). The viruses we identified formed a clade with this New Zealand virus, while the WPDV found in Australia formed a sister clade (Fig. 6B). Two virus species belonging to the Picornaviridae were identified in hedgehogs and ferrets. We found Hedgehog hepatovirus in very high abundance (>35,000 RPM, Table 1), with 98% amino acid sequence similarity to the virus previously found in European hedgehogs in Germany (32) (Fig. S1C). We also identified a novel parechovirus in two libraries of ferret samples, which we have provisionally named Ferret Parechovirus 2. The sequences in the two libraries do not overlap, yet we have conservatively assumed they are the same virus species (Fig. S1C). These viruses are most closely related to Ferret parechovirus found in ferrets in the Netherlands (33) with 78% and 88% amino acid sequence similarity, and Parechovirus sp. QAPp32 is found in the common pipistrelle bat, Pipistrellus pipistrellus (80% and 74% amino acid sequence similarity).
Finally, a virus from the genus Jeilongvirus in the Paramyxoviridae family was found in weasels sampled in the North Island and has been provisionally named Weasel jeilongvirus. We recovered three non-overlapping fragments of this virus, which we have
## Full-Length Text
Journal of Virology conservatively assumed to be the same virus (Fig. S1B). These fragments are most closely related to Feline paramyxovirus 163 found in Japan (84%-89%).
## DISCUSSION
This study presents the first metatranscriptomic survey of viruses in five introduced mammalian species in New Zealand: ferrets, stoats, weasels, brushtail possums, and hedgehogs. We identified 11 mammalian-infecting viral species spanning eight viral families, including four novel virus species within the Adenoviridae, Astroviridae, Flaviviridae, and Paramyxoviridae. Viral abundance varied considerably across species, with the highest viral load observed in hedgehogs (driven by Hedgehog hepatovirus), followed by possums and select samples of ferrets. Notably, complete genomes were recovered for six viruses, underscoring the utility of metatranscriptomics for in-depth viral discovery. These findings expand our understanding of the mammalian virome in New Zealand and highlight previously unrecognized viral diversity in introduced hosts.
## Novel viruses
With the increasing use of metatranscriptomics, novel viruses are frequently being discovered, including in mammalian hosts (9). Four novel viruses were identified in this study: Ferret mastadenovirus, Possum astrovirus, Ferret pestivirus, and Weasel jeilongvi rus. These viruses were phylogenetically distinct from known genetic relatives and, in some cases, highly divergent, showing less than 60% amino acid sequence similarity, uncovering previously uncharacterized viral lineages. Genetic relatives of these viruses include known animal and zoonotic pathogens, such as Human astrovirus VA1/HMO-C associated with gastroenteritis, and closely related to bovine and mink astroviruses (34). While no clear zoonotic threats were identified in our data, these findings provide useful surveillance for public and animal health, particularly given the ecological overlap of these mammalian hosts and their proximity to humans, native wildlife, and domestic animals.
## Known viruses: historical introductions and long-term viral persistence
Several viruses identified in this study have been previously described, including WPDV, Possum hepacivirus, Ferret hepatitis E virus, and Hedgehog arterivirus, all sampled in animals from around the world (29,35,36). The detection of these viruses in New Zealand suggests long-term persistence following a single introduction along with their hosts in the 19th and 20th centuries. Population bottlenecks caused by small founding population sizes (37-39) could have eliminated many viruses from these mammal populations at the time of their introduction to New Zealand, but our results indicate that at least some viruses were introduced to New Zealand along with their hosts. Although these host populations are geographically isolated from their overseas counterparts, they often occur at high local densities within New Zealand (39), which would provide sufficient contact rates to maintain viral circulation over time. Notably, we also identified Human rotavirus A in a hedgehog sample, which raises the possibil ity of reverse zoonotic transmission, likely via environmental contamination. To our knowledge, Human rotavirus A has not been found in hedgehogs previously; however, hedgehogs are increasingly being recognized as potential reservoirs for zoonotic viruses (40), and their presence in urban or peri-urban environments could facilitate such spillovers. Human rotaviruses have occasionally been detected in non-human animals, including domestic animals and non-human primates (41,42), lending weight to the possibility that reverse zoonotic transmission has also occurred in this case. However, it is also possible that the Human rotavirus A detected in the hedgehog library reflects contamination during sample collection or processing, rather than true infection. The nature of our sampling method (sourcing animals from established trapping programs) meant that human contamination was unavoidable. Further sampling of hedgehogs coupled with targeted PCR, in situ hybridization, or serology would be necessary to determine whether active infection occurred. The phylogenetic patterns observed in both WPDV and Ferret hepatitis E virus revealed clear geographic clustering of New Zealand viruses. The WPDV genomes identified in this study clustered with the previously described New Zealand strain (24), forming a distinct clade sister to Australian WPDV lineages (29). This pattern is consistent with historical records of possum introductions, which occurred only in the early 1900s (11), and indicates that WPDV has likely been circulating and evolving within New Zealand possum populations since. Similarly, Ferret hepatitis E virus from New Zealand formed a well-supported clade most closely related to Japanese strains (30), suggesting a shared origin or common ancestral introduction. The distinct separation of these viruses by geographic region reflects host movement restrictions and ecological isolation, as well as evolutionary divergence following limited introduction events. Such patterns underscore the importance of localized viral surveillance and suggest that introduced mammalian species in New Zealand may harbor uniquely evolved viral lineages with potential implications for both animal health and biosecurity. These patterns also suggest that the strong biosecurity measures in New Zealand have successfully prevented further introductions of these mammals from overseas.
## Limited viral sharing among mustelid species
Despite the close evolutionary relationship and geographic overlap among mustelid species (26), we found no evidence of viral sharing between hosts. This result is surprising given the potential for cross-species viral transmission, particularly among mustelids (ferrets, stoats, and weasels). Evidence for spillover events of Aleutian Mink Disease Virus from mink (Neogale vision) was found in six other mustelid species in Poland (43) and eight in Finland (44), demonstrating the ability of some viruses to seemingly jump between mustelid species. The lack of evidence for cross-species viral transmission in our study may be an artifact of our opportunistic sampling, which included relatively few individuals from stoats and weasels compared to ferrets, reducing the probability of detecting low-frequency transmission events or shared virus species. Additionally, differences in habitat use (e.g., ecological niche separation [45]), behavior (solitary lifestyle [46]), or immune responses could contribute to barriers to viral exchange (47,48). More extensive and systematic sampling across all species and regions is required to fully assess the potential for viral spillover between these hosts.
## Implications for biocontrol
New Zealand has the ambitious goal of becoming free of mammalian predators by 2050 (49). Biological control of pest animals, such as those sampled in this study, could be a key tool for reaching this goal (15,16). Indeed, the discovery of host-specific viruses highlights intriguing possibilities for biological control. Nevertheless, for effective biocontrol, viruses need to be highly pathogenic, species-specific, and safe for non-target species-including humans, native wildlife, and domestic animals. All of the viruses we detected, including the novel pestivirus in ferrets and astrovirus in possums, were identified in apparently healthy individuals where no overt signs of disease were noted. The exception may be WPDV, which has been associated with neurological disease in brushtail possums (29), as well as Hedgehog arterivirus, associated with neurological disease and fatal encephalitis (35,50), although as above, no animals sampled had obvious signs of disease. Rigorous assessment of pathogenicity and species specificity is required prior to any future application. More broadly, the use of viruses as biocon trol agents remains contentious (51) and would require robust risk assessment and regulatory oversight, especially in a biodiverse and conservation-sensitive context like New Zealand.
Our findings highlight several promising avenues for future research. First, increasing the sample size and geographic coverage for underrepresented species, such as stoats, weasels, and hedgehogs, would allow for a more robust assessment of viral diversity and potential cross-species viral transmission. Second, functional studies of the novel viruses identified here could help elucidate their host range, transmission potential, and pathogenicity. Third, integrating ecological data, such as species movement, diet, and habitat overlap, could shed light on the mechanisms shaping viral communities. Finally, monitoring for known and novel viruses in native New Zealand wildlife is essential to assess the potential for spillover from introduced species, particularly as efforts to manage or eradicate invasive mammals continue. Together, these findings underscore the value of viral surveillance in introduced wildlife and provide a crucial foundation for understanding and mitigating emerging infectious disease risks in New Zealand's unique ecosystem.
## MATERIALS AND METHODS
## Sampling and RNA extraction
Kidney and liver samples were collected from 290 individuals from five introduced mammalian species: ferrets (Mustela furo), stoats (Mustela erminea), weasels (Mustela nivalis), brushtail possums (Trichosurus vulpecula), and European hedgehogs (Erinaceus europaeus), from the upper North Island and South Island of New Zealand in 2021 (Fig. 1). Animals were either live trapped and culled, kill trapped, or opportunistically collected as fresh roadkill. All animals that were trapped and killed were done so as part of already established pest control efforts. Upon collection, animals were frozen at -20°C and transferred to the University of Auckland (for North Island samples) or the University of Otago (for South Island samples). Before dissection, carcasses were thawed and checked for signs of decomposition to determine suitability for RNA extraction. Liver and kidney tissue samples were harvested and stored in RNALater (Thermo Fisher Scientific) at -80°C until RNA extraction using the Qiagen RNeasy Plus Mini kit (Qiagen) following the manufacturer's instructions. RNA from up to 30 individuals from each species was pooled per location and ribosomal RNA was removed using the Ribo-Zero-Gold Kit from Illumina, then sequenced using Illumina NovaSeq 6000 at the Australian Genome Research Facility (AGRF), Melbourne, Australia.
## Viral discovery
Sequencing reads were quality-trimmed using Trimmomatic (v0.38), with removal of adapter sequences and bases with a quality score below 5 using a sliding window of four bases (52). Additionally, low-quality bases (quality score <3) were trimmed from the ends of reads, and sequences shorter than 25 nucleotides were discarded. Following quality control, reads were de novo assembled into contigs using MEGAHIT (v1.2.9) (53). These contigs were then compared to the NCBI nucleotide (nt) and non-redundant protein (nr) databases using BLASTn (BLAST+ v2.13.0 [54]) and DIAMOND (DIAMOND v2.1.6 [55]) to identify viral sequences. To reduce false positives, similarity thresholds of 1 × 10 -5 for the nt database and 1 × 10 -10 for the nr database were applied. Virus abundance was estimated by mapping reads back to the assembled contigs using Bowtie2 (v2.4.5 [56]) and SAMtools (v1.9 [57]). Viral sequences present at read counts <0.1% of those in another library and >99% identical at the nucleotide level were considered likely cross-contamination due to index hopping and excluded from further analysis. The probable host origin of each virus was inferred based on phylogenetic relatedness to known viruses. Viruses that clustered with known mammalian viruses were subject to further evolutionary analysis. Viruses that were phylogenetically distinct from vertebrate host viruses were assumed to be more likely associated with diet, microbiome, or environmental sources.
## Phylogenetic analysis
Putative viral transcripts were first translated and then aligned with representative protein viral sequences from the same viral genus or family retrieved from GenBank. These representative sequences were chosen to capture diversity within each viral genus or family by selecting a small number of sequences from major clades and including all sequences closely related to the viruses identified in this study. Alignments were performed using MAFFT (v7.402) (58) with the E-INS-i or L-INS-i algorithms (Table S1) and subsequently trimmed using TrimAl (v1.4.1) (59). Phylogenetic trees for each viral family or genus were estimated using the maximum likelihood method in IQ-TREE (v1.6.12), with the program determining the best-fit substitution model using ModelFinder (60) and node robustness evaluated through the approximate likelihood ratio test with 1,000 replicates (61). Sequences found within the same library were considered to represent different viral species (rather than intra-species viral diversity) if overlapping aligned sequences had <90% amino acid identity. Phylogenetic trees were visualized using APE (v5.4) (62) and ggtree (v2.4.1) (63) in R (v4.0.5) (64).
Selected whole viral genomes were also further analyzed at the nucleotide level. Annotations were conducted using BLAST and the conserved domains database (65). Phylogenetic analysis was conducted at the nucleotide level using whole-genome sequences, aligning the sequences using MAFFT. Phylogenetic trees were estimated using the same methods as described above.
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61. Kalyaanamoorthy, Minh, Wong et al. (2017) "ModelFinder: fast model selection for accurate phylogenetic estimates" *Nat Methods*
62. Nguyen, Schmidt, Haeseler et al. (2015) "IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies" *Mol Biol Evol*
63. Paradis, Strimmer (2004) "APE: analyses of phylogenetics and evolution in R language" *Bioinformatics*
64. Yu, Smith, Zhu et al. (2017) "Ggtree: an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data" *Methods Ecol Evol*
65. (2013) "R: A language and environment for statistical computing"
66. Wang, Chitsaz, Derbyshire et al. (2023) "The conserved domain database in 2023" *Nucleic Acids Res*
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# Erratum: An enterovirus strain isolated from diabetic child belongs to a genetic subcluster of echovirus 11, but is also neutralised with monotypic antisera to coxsackievirus A9
Haider Al-Hello, Anja Paananen, Mervi Eskelinen, Petri Ylipaasto, Tapani Hovi, K Salmela, Alexander Lukashev, Shubhada Bopegamage, Merja Roivainen
## Abstract
The eighth author's name was spelled incorrectly in the published version of this article.Previously, it was spelled as Shubhada Bobegamage. It should have been rightly spelled as Shubhada Bopegamage.
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Yuto Fukuda, Takako Suzuki, Yoshitaka Sato, Ken-Ichi Iwata, Yusuke Okuno, Hiroshi Kimura, Yoshinori Ito, Jun-Ichi Kawada
## 4
Fujita Health University School of Medicine, Toyoake, Aichi, Japan Session: 222. Diagnostics: Other Wednesday, October 22, 2025: 12:15 PM Background. Hydroa vacciniforme-like lymphoproliferative disorder (HV-LPD) and severe mosquito bite allergy (SMBA) are cutaneous forms of chronic active Epstein-Barr virus (EBV) disease (CAEBV) characterized by clonal proliferation of EBV-infected T or natural killer (NK) cells. SMBA and HV-LPD can progress to systemic CAEBV infection; however, their pathogenesis remains unclear. Here, we performed single-cell RNA sequencing (scRNA-seq) analysis of patients with two types of cutaneous CAEBV.
Methods. This study included five patients with HV-LPD, four with SMBA, and two healthy adult controls. Peripheral blood mononuclear cells (PBMCs) were collected from each patient and used for scRNA-seq. In five cases, the EBER gene was enriched to enhance the detection efficiency of EBV-infected cells. ScRNA-seq data were processed and analyzed using Cell Ranger and Seurat. Monocle3 was used for the trajectory analysis.
Results. A total of 79,830 PBMCs were analyzed, with 2,233-13,487 cells per case. EBV gene expression was detected in 5,827 cells (SMBA; 4,343 cells, 12.7%, HV-LPD; 1,484 cells, 3.7%). In the SMBA cases, EBV-infected cells resided at earlier pseudo-time positions than uninfected cells, suggesting a more immature transcriptional state. Additionally, in cases that progressed to systemic CAEBV, EBV-positive cells were positioned earlier in the pseudo-time trajectory than in non-progressed cases.
Conclusion. By combining scRNA-seq analysis with EBV gene detection, EBV-infected cell populations were identified, and host gene expression profiles between infected and uninfected cells were compared at single-cell resolution. The accumulation of EBV-infected cells in transcriptionally immature states suggests a potential link between CAEBV progression.
Disclosures. All Authors: No reported disclosures
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# Draft genome sequences of human adenovirus F associated with acute gastroenteritis in Blantyre, Malawi
Flywell Kawonga, Ernest Matambo, End Chinyama, Chimwemwe Mhango, Clara Majengo, Josephine Msowoya, Benjamin Kumwenda, Celeste Donato, Arox Kamng'ona, Milton Mogotsi, Nkosazana Shange, Ayodeji Ogunbayo, Francis Dennis, Martin Nyaga, Chrispin Chaguza, Khuzwayo Jere
## Abstract
Human adenovirus F (HAdV-F), genotype 40/41, ranks as the second leading cause of pediatric viral gastroenteritis globally. Here, we report four draft genomes of HAdV-F from Malawi, obtained from children with acute gastroenteritis at Queen
0.7.18-r1243-dirty with default parameters (8). Consensus genomes were generated by calling high-confidence bases from aligned sequence reads using iVar (v1.4.4) with default parameters (9). The whole-genome assemblies were further annotated using Prokka 1.14.6 (10). The genome assemblies are considered drafts due to unconfirmed 5′ and 3′ terminal sequences, although all major coding regions were successfully recovered. BLASTn of the assembled genomes showed that BID128S1 had 99.89% nucleotide similarity to MK962807.1, whereas BID1NKS2, CQA14XS1, and CQA185S1 had 99.77%, 99.71% and 99.76% similarity to NC_001454.1, respectively. The depth of the genome assemblies was checked using samtools 1.21 (https://www.htslib.org/). The reads and assembly characteristics are summarized in Table 1.
The assembled genomes were identified as human mastadenovirus F using the Genome Detective Virus Tool (https://doi.org/10.1093/bioinformatics/bty695). Genotyp ing identified BID1NKS2, CQA14XS1, and CQA185S1 as HAdV-F40, and BID128S1 as HAdV-F41, based on the highest sequence similarity from BLASTn analysis. Figure 1
## References
1. Chandra, Lo, Mitra et al. (2021) "Genetic characterization and phylogenetic variations of human adenovirus-F strains circulating in eastern India during 2017-2020" *J Med Virol*
2. Lemiale, Haddada, Nabel et al. (2007) "Novel adenovirus vaccine vectors based on the enteric-tropic serotype 41" *Vaccine (Auckl)*
3. Van Loon, Ligtenberg, Reemst et al. (1987) "Structure and organization of the left-terminal DNA regions of fastidious adenovirus types 40 and 41" *Gene*
4. Iturriza-Gómara, Jere, Hungerford et al. (2019) "Etiology of diarrhea among hospitalized children in Blantyre, Malawi, following rotavirus vaccine introduction: a case-control study" *J Infect Dis*
5. Liu, Gratz, Amour et al. (2016) "Optimization of quantitative PCR methods for enteropathogen detection" *PLoS One*
6. Bolger, Lohse, Usadel (2014) "Trimmomatic: a flexible trimmer for Illumina sequence data" *Bioinformatics*
7. Langmead, Salzberg (2012) "Fast gapped-read alignment with Bowtie 2" *Nat Methods*
8. Li, Durbin (2009) "Fast and accurate short read alignment with Burrows-Wheeler transform" *Bioinformatics*
9. Grubaugh, Gangavarapu, Quick et al. (2019) "An amplicon-based sequencing framework for accurately measuring intrahost virus diversity using PrimalSeq and iVar" *Genome Biol*
10. Seemann (2014) "Prokka: rapid prokaryotic genome annotation" *Bioinformatics*
11. Paradis, Schliep (2019) "Ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R" *Bioinformatics*
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# Changes to virus taxonomy, the international code of virus classification and nomenclature, and the ICTV statutes ratified by the International Committee on Taxonomy of Viruses (2025)
Peter Simmonds, Evel Adriaenssens, Elliot Lefkowitz, Hanna Oksanen, Francisco Murilo Zerb, Poliane Alfenas-Zerb, Frank Aylw, Donald Dempse, Juliana Freitas-Astúa, Hendrick, Holly Hughes, Mart Krupovic, Jens Kuhn, Małgorzata Łobocka, Richard Mayne, Arc Mushegia, • Judit, J Penz, Alejandro Reyes Muñ, David Robert, Simon Roux, Luisa Rubino, Sea Sabanadzovi, Donald Smith, Nobuhiro Suzuki, Dann Turner, Koenraad Van Doorslaer, Arvind Varsani, Francisco Zerbini, Frank Aylward, Donald Dempsey, R Hendrickson, Alejandro Reyes Muñoz, David Robertson, Sead Sabanadzovic
## Abstract
The 56th meeting of the Executive Committee (EC) of the International Committee on Taxonomy of Viruses (ICTV) was held in Bari, Italy, in July/August, 2024, and 115 submitted taxonomy proposals were reviewed. A total of 112 were subsequently ratified by the ICTV membership. An additional 9 error correction proposals were also approved in August 2025. This article lists the taxonomy proposals that have now been incorporated into release 40 version v2 of the Master Species List (https://ictv.global/msl), the Virus Metadata Resource (https://ictv.global/vmr), and associated ICTV databases. In addition to the assignments of 1,563 new virus species, 243genera, 55 families, 11 orders, and 8 classes, there were substantial additions to higher taxonomic ranks. These include the creation of a new realm (Singelaviria), which is based on the recognition of a separate evolutionary origin for the hallmark capsid genes of members of the kingdom Helvetiavirae. These express capsid proteins forming a single jelly-roll fold that is structurally and evolutionarily distinct from those of members of the family Bamfordvirae, assigned to the realm Varidnaviria. Furthermore, the realm Varidnaviria underwent a major reorganization, including the addition of a new kingdom, Abadenavirae. Another notable change was the classification of the vertebrate-infecting single-stranded DNA anellovirids into a new phylum Commensaviricota (kingdom Shotokuvirae, realm Monodnaviria). Archaeal viruses infecting the hyperthermophilic Archaeoglobi were assigned to a new phylum Calorviricota, in the kingdom Trapavirae (realm Monodnaviria), whereas RNA viruses infecting hyperthermophilic bacteria were classified into a new phylum Artimaviricota (realm Riboviria). In recognition of his extensive and valuable contributions to virus taxonomic developments in Study Groups and over the period of his EC membership, Stuart Siddell was honoured as a new life member of the ICTV. The ICTV has created a new strategy for disseminating information on taxonomy advances through annual open-access publication of citeable taxonomy proposal summaries from each ICTV Subcommittee. A collective total of 354 co-authors of the seven summaries were drawn from members of each Subcommittee, the EC, and a very large number of contributors from the wider virology community.
## Introduction
The International Committee on Taxonomy of Viruses (ICTV) follows an annual cycle of taxonomy updating, in which changes and additions to virus taxonomy proposed by the virology community are considered and implemented through the concerted effort of ICTV Study Groups, Subcommittees, and the Executive Committee. The ICTV classification of viruses provides a framework for the taxonomic placement of viruses at ranks from species to realm and furthermore regulates their taxon names and typography. The ICTV Statutes ( h t t p s : / / i c t v . g l o b a l / a b o u t / s t a t u t e s) describe the process through which taxonomic proposals are submitted to the ICTV Executive Committee (EC) and undergo review with input from ICTV Study Groups and Subcommittees, other interested virologists, and the EC. After final approval by the EC, proposals are placed on the ICTV website (https://ictv.global) for evaluation by the full ICTV membership and ratification by online voting.
## Proposal discussion and ratification
The annual EC meeting of the ICTV was held in Bari, Italy, from July 31 to August 2, 2024. The EC reviewed a total of 112 taxonomy proposals from six of the seven Subcommittees and three general proposals (no proposals were received from the Animal ssRNA + Subcommittee). Proposals were submitted by a total of 354 co-authors representing a substantial engagement in taxonomy by the wider virology community outside of the ICTV.
For assessment, 50 proposals had been "streamlined" through review by at least two EC members, including the SC Chair, prior to the meeting, and the remaining 65 proposals were discussed and voted upon by the EC. At the meeting, three proposals were rejected, and 13 proposals were accepted conditional on substantial revision and a second vote by the EC in November, 2024. Along with updated proposals subject to minor revision, 112 taxonomy proposals were placed on the ICTV website (https://ictv.global) for viewing by the full ICTV membership and the general public.
All proposals were voted on by the 169 members of the ICTV from January 27 to February 28, 2025. Voting was performed using an Excel-based form rather than online survey with the aim of providing more information about the proposal, greater flexibility in responses (including "Abstain") and to discourage "Vote-for-All" responses often encountered in previous ratification votes. The voting form was accompanied by a summary of the taxonomy proposal in a single document (providing the title, authors, abstract, and tabulated taxonomy changes for each proposal) to facilitate review of the proposals when voting. A total of 106 out of 169 ICTV members (63%) voted on the proposals. Excluding seven erroneous votes against proposal 2024.001M.Alpharhabdovirinae_1ng_11nsp caused by a technical error on the form, proposals received a mean of 94.5 (range: 87-103) votes for acceptance, 11.5 (range: 3-19) abstentions, and 0.02 (only two votes) against. There was therefore an 89% vote for approval (range: 82-97%) or 100% (range: 99-100%) when abstentions were excluded. Following the vote of the membership, minor technical errors were identified in nine of the approved proposals. Using policies established by the EC, these errors were corrected, and the corrected proposals were approved and incorporated into Master Species List (MSL) 40 as version v2.
A summary of the taxonomy changes enacted by the proposals is provided in Table 1. Each proposal is cited and listed in the References [1-112] to acknowledge the authors' efforts and to provide links to the specific proposal on the ICTV website. These documents and those from previous years are permanently available to provide full access to the text and listing of taxonomy changes made in each proposal ( h t t p s : / / i c t v . g l o b a l / fi l e s / p r o p o s a l s / a p p r o v e d). All ratified proposals are furthermore published in a series of citeable summaries co-authored by all 354 contributors to the proposals [118, 122, 125 -27, 129, 132]. A description of their format and how to cite taxonomy changes in publications is provided in an accompanying review article co-authored by the EC [113].
## Principal changes to virus taxonomy
The greatest number of new assignments were made at the species rank, with a current total of 16,213 species, almost all of which possess binomial names. This represents an increase of 1,523 over the previous year, and continues steadily rising totals of 10,434 (2022), 11,273 (2023), and 14,690 (2024). There were substantial increases in the numbers of genera and families (+ 246 and + 54, respectively), with new taxa being primarily assigned to bacterial viruses; additionally, several new families were established for archaeal and fungal viruses.
Eight new classes were established, including Orpoviricetes for bi-segmented fungal RNA viruses with noncanonical RNA-directed RNA polymerase (RdRP) motifs [68]. This assignment is provisional pending a potential future reclassification to a new phylum or even higher rank given the structural distinctiveness of the group's RdRP hallmark gene. Several new classes were created as part of the re-organisation of the realm Varidnaviria (proposal 2024.010D.Varidnaviria_reorg; [58]) and the assignments of hakuzovirids, pleolipovirids, and anellovirids to new phyla ([4, 43, 59]; described below).
Higher rank changes included the addition of two subphyla, four phyla, one kingdom, and one realm, representing a substantial expansion in the diversity of classified viruses. A major change was the splitting of the established realm Varidnaviria to create a new realm, Singelaviria, now including the kingdom Helvetiavirae [58]. This was based on the recent recognition of independent evolutionary origins from cellular counterparts of double jelly-roll and single vertical jelly-roll major capsid proteins that are characteristic of double-stranded DNA viruses assigned to two kingdoms, Bamfordvirae and Helvetiavirae, respectively [114]. Furthermore, comparative analysis of the replication modules encoded by viruses in the realm Varidnaviria led to a major re-organization of this realm [114,115], with five virus orders originally assigned to the kingdom Bamfordvirae being moved to a new kingdom, Abadenavirae. Finally, two new classes were established within phylum Preplasmiviricota to accommodate members of the reassigned family Adenoviridae [116] and the previously unclassified, environmentally ubiquitous "polinton-like" viruses [117,118], and one new class was established within the phylum Nucleocytoviricota to accommodate small relatives of giant viruses [119,120].
Proposal 2024.012D.Shotokuvirae_newphylum [59] addressed the lack of higher-rank assignments for anellovirids, small, single-stranded DNA viruses infecting a wide range of vertebrates. Although anellovirids lack the Rep gene typical of circovirids and other members of the phylum Cressdnaviricota, it was found that they encode a single jelly-roll capsid protein typical of single-stranded DNA viruses of the kingdom Shotokuvirae (realm Monodnaviria) [121,122]. Accordingly, the newly created higherrank taxonomic assignments for anellovirids include the order Sanitavirales, class Cardeaviricetes, and phylum Commensaviricota.
Archaeal viruses producing enveloped pleomorphic virions and infecting hyperthermophile prokaryotes of the class Archaeoglobi are highly distinct from, yet evolutionarily related to, pleolipovirids in the kingdom Trapavirae (realm Monodnaviria) [123]. In proposal 2024.004A.Thalassapleoviridae_newphylum [4, 121], Archaeoglobus veneficus pleomorphic virus 1 (AvPV1)like viruses have been assigned to an entirely separate lineage comprising a new phylum, Calorviricota, in the kingdom Trapavirae, class Caminiviricetes, order Ageovirales, and family Thalassapleoviridae, with three genera and five species.
A new phylum, Artimaviricota, and included lower ranks (Furtirnaviricetes, Divaquavirales, Hakuzoviridae, Atsuirnavirus), was established in the kingdom Orthornavirae (realm Riboviria) for the hyperthermophilic, bi-segmented bacterial hot spring RNA virus 1 [43]. This assignment was based on its highly divergent RdRP sequence and deduced structure that groups phylogenetically apart from homologues in the other six currently assigned orthornavirian phyla [124].
Two new orders of bacterial viruses were established. The family Autographiviridae was elevated to the order Autographivirales and includes four newly created families [49]. The order encompasses bacterial viruses with podovirus morphology that encode a large single-subunit DNAdirected RNA polymerase. The Lak megaphages, which have been shown to be prevalent across a diversity of gut microbiomes through genome-resolved metagenomics, were assigned to a new order, Grandevirales [20]. These viruses possess some of largest known caudoviricete genomes and are characterised by an alternative genetic code in which the TAG stop codon is repurposed to encode glutamine. Among the three proposals in the General category, Professor Stuart Siddell was nominated as a Life Member of the ICTV [71], based on his long service as a member of ICTV Study Groups, Subcommittees, and the Executive Committee and his key role in helping to develop and modernize guiding principles used to create virus taxonomy.
## Implementation and access
The latest set of proposals approved by the EC was made available on the ICTV website in April, 2025 at h t t p s : / / i c t v . g l o b a l / fi l e s / p r o p o s a l s / a p p r o v e d (all proposals combined into a single zip file) and also in a directory at h t t p s : / / i c t v . g l o b a l / fi l e s / p r o p o s a l s / a p p r o v e d where links provide access to proposals indexed by virus group and Subcommittee.
Updated versions of the Master Species List (release 40 version v2), which lists all currently approved taxa (Table 1), can be accessed on the ICTV website at h t t p s : / / i c t v . g l o b a l / m s l . A similarly updated release 40 (March 27, 2025) of the Virus Metadata Resource (VMR) is located at h t t p s : / / i c t v . g l o b a l / v m r . This provides details of exemplar virus isolates for each species, including GenBank accession numbers.
Summaries of the ratified proposals (described in reference [113,120]) from six of the seven ICTV Subcommittees and for general proposals are available [125][126][127][128][129][130][131].
## References
1. Bejerman, Debat, Dietzgen et al. (2015) "Abolish one genus and create three new genera to include 98 new species in the subfamily Betarhabdovirinae (Mononegavirales: Rhabdoviridae)"
2. Bejerman, Debat, Dietzgen et al. (2024) "Create one new genus to include five new species in the subfamily Betarhabdovirinae (Mononegavirales: Rhabdoviridae)"
3. Scheets, Hernandez, Jordan et al. (2024)
4. Maclot, Massart (2018) "Create one new species in the genus Machlomovirus (Tolivirales: Tombusviridae)"
5. Fontdevila, Massart (2024) "Create one new species in the genus Velarivirus"
6. Krupovic, Fischer, Kuhn (2019) "Create one new unassigned order in realm Riboviria, including four new families for four currently unassigned genera of plant satellite viruses"
7. Nagata, Blouin, Candresse et al. (1922) "Rename two species in the genus Sobemovirus (family Solemoviridae)"
8. Hammond, Abrahamian, Bejerman et al. (2024)
9. Mayne, Simmonds, Smith et al. (2025) "Virus taxonomy proposal summaries: a searchable and citable resource to disseminate virus taxonomy advances" *J Gen Virol*
10. Krupovic, Makarova, Koonin (2022) "Cellular homologs of the double jelly-roll major capsid proteins clarify the origins of an ancient virus kingdom" *Proc Natl Acad Sci U S A*
11. Koonin, Fischer, Kuhn et al. (2024) "The polinton-like supergroup of viruses: evolution, molecular biology, and taxonomy" *Microbiol Mol Biol Rev*
12. Benko, Aoki, Arnberg et al. (2022) "ICTV Virus Taxonomy Profile: Adenoviridae 2022" *Ictv Report C*
13. Bellas, Hackl, Plakolb et al. (2023) "Large-scale invasion of unicellular eukaryotic genomes by integrating DNA viruses" *Proc Natl Acad Sci U S A*
14. Yang, Li, Zhang et al. (2024) "Create Emaravirus clematis as a new species in the genus Emaravirus, family Fimoviridae"
15. Abrahamian, Donaire, Candresse et al. (2002) "Create eight new species in the family Alphaflexiviridae"
16. Tomitaka, Shimomoto, Sasaya et al. (2003) "Create one new species in the genus Olpivirus (Hareavirales: Konkoviridae)"
17. Li, Zhang, Cao et al. (2006) "&. Create a new species in the genus Cilevirus and two in the genus Higrevirus, family Kitaviridae (Martellivirales)"
18. Roumagnac, Ascencio-Ibanez, Lett et al. (2007) "Create one new species in the genus Capulavirus (Geplafuvirales: Geminiviridae)"
19. Roumagnac, Ascencio-Ibanez, Lett et al. (2008) "Create two new species in the genus Citlodavirus (Geplafuvirales: Geminiviridae)"
20. Zerbini, Ascencio-Ibanez, Lett et al. (2001) "Create 19 new species in the genus Begomovirus (Geplafuvirales: Geminiviridae)"
21. Inoue-Nagata, Jordan, Kreuze et al. (2012) "Create one new species in the genus Alphanucleorhabdovirus, and one species in the genus Betanucleorhabdovirus, subfamily Betarhabdovirinae (Mononegavirales: Rhabdoviridae)"
22. *J Gen Virol*
23. Sabanadzovic, Abergel, Ayllón et al. (2025) "ICTV Taxonomy Summary Consortium (2025) Summary of taxonomy changes ratified by the International Committee on Taxonomy of Viruses (ICTV) from the Fungal and Protist Viruses Subcommittee" *J Gen Virol*
24. Turner, Adriaenssens, Amann et al. (2025)
25. Varsani, Abd-Alla, Arnberg et al. (2025) "ICTV Taxonomy Summary Consortium (2025) Summary of taxonomy changes ratified by the International Committee on Taxonomy of Viruses (ICTV) from the Animal DNA Viruses and Retroviruses Subcommittee" *J Gen Virol*
26. Zerbini, Crane, Kuhn et al. (2025) "ICTV Taxonomy Summary Consortium (2025) Summary of taxonomy changes ratified by the International Committee on Taxonomy of Viruses (ICTV) -General taxonomy proposals" *J Gen Virol*
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# Investigating the evolutionary dynamics and mutational pattern of SARS-CoV-2 spike gene on selected SARS-CoV-2 variants
Bachir Balech, Alessandra Presti, Claudia Telegrafo, Lucia Maisto, Emanuela Giombini, Angela Martino, Luigina Ambrosio, Apollonia Tullo, Paola Stefanelli
## Abstract
The continuous evolution of SARS-CoV-2 has led to the emergence of several variants representing significant challenges for public health. Many studies highlight the relevance of phylogenetic inference or mutational pattern analysis to understand the evolutionary relatedness of viral variants and to estimate the potential effect of new mutations on viral transmission, virulence and antigenicity. Here we describe an evolutionary investigation approach combined with mutational analyses of SARS-CoV-2 Spike gene to annotate and potentially track important amino acid site variation of specific functional domain relevant for viral survival. This approach was applied on XBB*, EG* and BA* and their sub-lineages (see materials and methods) available from GISAID. In addition, we considered the major variants of concern (Alpha, Delta, Omicron) and Wuhan-Hu-1 strain as references. Maximum likelihood phylogenetic tree was constructed from the complete dataset while selection pressure and mutational analyses were conducted on single variants separately. The obtained phylogenetic tree of Spike amino acid gene sequence showed a clear separation of viral variants as well as their expected appearance order. This result supported the significance of selection pressure analyses outcomes combined with amino acid mutational frequencies where in many cases they showed a linear and parallel trend. This allowed also to hypothesize the potential importance of low-frequency mutations in new potential virus variants. This study constitutes an asset of important insights to be considered in regular monitoring programs. In addition, the analysis framework described here introduces a starting point for further standardization, optimization and application on different data types and in large-scale studies.
## Introduction
The continuous evolution of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has led to the emergence of several variants, and distinct lineages and sub-lineages [1-3] representing significant challenges for public health and requiring a regular monitoring. XBB variant and its related sub-lineages replaced previously circulating Omicron variant in early 2023. XBB presents a strong capacity for crossing over the host immune system, surpassing the immune evasiveness of BA.5 [4]. The Omicron XBB.1.5 has become predominant in Italy starting from April 2023 [5]. It continued to evolve, yielding other main sub-lineages (i.e., XBB.1.9.1, XBB.1.9.2, XBB.1. 16, XBB.2.3, FE.1) which circulated and played a key role in viral infection and transmission. In August 2023, this variant was replaced by the EG.5, which became the most prevalent in the country [6]. In the same period the lineage named BA.2.86, has been detected in multiple countries, prompting its classification as a Variant of Interest (VOI) by the World Health Organization (WHO) (World Health Organization 2024 [7]). According to data reported from the Italian flash survey report [8], this viral strain was detected in Italy for the first time in September 2023. The reproductive efficiency of BA.2.86 is estimated to be similar or even higher that of XBB.1.5 and EG.5.1 [9]. Although BA.2.86 did not show substantial humoral immune escape and growth advantage compared to EG.5 and EG. 5.1 variants, it showed remarkably high ACE2 (angiotensin-converting enzyme 2) binding affinity [9][10][11][12][13]. Moreover, the defining and relevant mutations in the Spike of XBB.1.5*, XBB.1.9*, XBB.1.16*, XBB.2.3*, FE.1*, EG.5*, BA.2.86* described by the outbreak.info mutation tracker (reported and summarized in S1 Table ), represent the main reasons to monitor these variants [14], along with the ability to monitor the onset of possible additional mutations which can arise in specific strains over time.
Spike protein is one of the structural proteins of SARS-CoV-2. It has a crucial role in fusion with the host cell, viral pathogenicity and vaccine design [15,16]. Diving into Spike mutational pattern has been the central focus of many scientific studies to date as it is related directly to the viral fitness [15,16]. The structure of the Spike protein comprises a signal peptide (SP, amino acids residues: 1-13) and two subunits the S1 (residues: 14-685) and S2 (residues: 686-1273) [17]. The S1 subunit contains an N terminal (NTD, residues:14-305) and a C-terminal receptor binding subdomains (RBD, residues: 319-541). The NTD has a critical role in overall structural conformation of S protein, where mutations occurring in the NTD are linked to viral immune escape [18]. The RBD instead is responsible for the recognition of the angiotensin-converting enzyme 2 (ACE2) which acts as the receptor for SARS-CoV-2 viral entry [19]. The S2 subunit comprises the fusion peptide (FP, 788-806 residues), heptapeptide repeat sequence 1 (HR1, 912-984 residues), heptapeptide repeat sequence 2 (HR2, 1163-1213 residues), transmembrane (TM) domain (1213-1237 residues), and cytoplasm domain or C-terminal tail (CT, 1237-1273) [20]. HR1 and HR2 lead to membrane fusion and viral entry, while the TM assures the anchoring of S to the viral envelop and the C-terminal tail promotes S escape from the endoplasmic reticulum [21]. Mutational changes associated with SARS-CoV-2 Spike protein coding gene have gained important insights to study the related evolutionary dynamics of the virus. Many studies highlight the relevance of complete genomes phylogeny of SARS-CoV-2 to illustrate its relatedness with other viruses of the same family namely, SARS-CoV and MERS [22][23][24][25][26]. In parallel, in some cases it has been demonstrated the importance of phylogenetic analysis of Spike gene as a potential region to discriminate among variants of the virus and at the same time a relatively fast method to flag or detect the outbreak of new variants and/or the appearance of new mutations or indels [27,28].
In this context, monitoring the evolution of SARS-CoV-2 variants and the emergence of specific amino acid substitutions or indels is determinant to detect potential alterations in transmissibility, infection severity, and immune responsiveness, and to inform risk assessment and early warning models. This can be achieved through conducting a phylogeny inference to highlight newly emerging clade/s or by studying site-specific selection pressure [29]. Generally, the amino acid changes that increase virus fitness are generally maintained by positive selection.
Hereby, we endorsed a bioinformatic analytical approach to highlight important aspects of Spike gene related to the selection pressure, phylogenetic analysis and evolutionary dynamics in selected SARS-CoV-2 variants and their sublineages (details are provided in materials and methods section and S2 Table ), as a model. This allowed the evaluation of Spike gene evolution and its mutational pattern (substitutions and indels) as well as the sites subjected to positive and negative selection and their relationship with specific functional domains crucial in regular monitoring and treatments developing programs including vaccine design.
## Materials and Methods
## Source datasets
Three complete genome sequences datasets were downloaded from GISAID database (https://gisaid.org/) on 25 September 2023. A total of 3736 SARS-CoV-2 available genomes belonging to XBB.1.5, XBB.1.16, XBB.2.3, FE.1 (alias of XBB.1.18.1.1.1) and their sub-lineages in addition to XBB.1.9.1 and XBB.1.9.2 from Italy were downloaded. Lineage and sub-lineage assignment have been done with pangolin v.4.3.1 through GISAID. Spike gene identification and extraction were performed following the analysis process described in detail in the subsequent sections. Following the exclusion of low-quality sequences with more than 5% of ambiguous nucleotides (N) in the Spike (S) protein coding gene, a total of 3724 S sequences were retained to constitute the first dataset. The second dataset included 436 Italian SARS-CoV-2 S gene sequences belonging to EG.5 variant and its sub-lineages. The third contained global sequences of BA.2.86 lineage (sampled from 208 different countries) and the only BA.2.86.1 Italian genome which was available at the time of the dataset creation. The same Spike gene identification procedure and sequence quality check described above were also applied to the other two datasets. Details on the number of sequences of each lineage/sub-lineage are reported in S2 Table . For the sake of simplicity in the rest of this manuscript we will refer to the first Spike gene sequences dataset as XBB*, the second as EG* and the third as BA*.
## Construction of Spike gene datasets
Clinically relevant SARS-CoV-2 variants were mainly considered to build a reference sequence dataset to be used for Spike gene annotation of the above-described datasets. For that, representative viral complete genome sequences were explored and retrieved from COVID19 data portal hosted by the European Nucleotide Archive (available at [30] and described in [31]). The reference dataset included 202 sequences belonging to Alpha, Delta and Omicron variants and the original Wuhan-Hu-1 (NCBI Accession Number: NC_045512.2). Using a python script, the Spike gene nucleotide and the corresponding amino acid sequences were extracted from the reference genomes according to the gene name and annotation features provided in the flat files. Multiple amino acid reference sequence alignment was generated using muscle [32] and the corresponding Hidden Markov Model (HMM) multiple alignment profile was constructed by hmmpress algorithm (HMMer 3.3 package: http://hmmer.org/).
## Multiple sequence alignments and Phylogenetic analysis of Spike gene
Multiple sequence alignments (MSA) of the three Spike gene sequences datasets were conducted following the general schema of MSA-PAD 2.0 [33,34] with modified features accounting for the occurrence of unassigned nucleotides characters "N". In details, all DNA sequences of the three datasets (XBB*, EG*, BA*) were translated into amino acids using the universal genetic code and all six open reading frames. Using hmmsearch algorithm (HMMer 3.3 package), the amino acid sequences were searched against the Spike gene reference HMM profile generated in the previous step to annotate the relevant Spike region in genome sequences. The extracted amino acid Spike gene sequences were then aligned by hmmalign (HMMer 3.3 package) against the Wuhan-Hu-1 Spike gene reference. Amino acid multiple sequence alignments were then back-aligned into nucleotide multiple alignments using ad hoc python script (for more details see [33,34]) and used for selection pressure analysis (see section 5.5 -selection pressure analysis). To draw the evolutionary relationship between the SARS-CoV-2 variants under investigation and their reference, a single amino acid MSA was constructed by joining all the datasets described above. This MSA included either the representative reference sequences of the past variants and those relative to the retrieved sequences used in this study. In addition, to account for the excessive computational capacity needed in phylogeny construction, the number of sequences in the MSA was reduced to a minimum set of 685 where each retained sequence contains at least one amino acid substitution site compared to Wuhan-Hu-1 reference. In such way all amino acid substitutions were represented in the final MSA subset at least once.
Phylogenetic relationship among variants was inferred using the Maximum Likelihood method and the HIVw+F+I+G4 evolutionary model as implemented in IQTREE package [35]. The best evolutionary model was selected among 168 amino acid sequence evolutionary models tested with model finder algorithm available from IQTREE. Node supports were obtained from non-parametric ultrafast bootstrap [36] analysis with 1000 replicates while branch lengths were optimized using the NNI algorithm. The consensus phylogenetic tree was edited using iTOL web service [37] where clades representing the same variants (except for XBB* and EG*) were collapsed manually to improve tree rendering and interpretation.
## Amino acid substitutions, indels and their frequencies
The SARS-CoV-2 reference sequence Wuhan-Hu-1 (NC_045512.2) was used as reference for all individual datasets, including previous variants, to call the amino acid substitutions, deletions and insertions (indels). Their frequencies (%) were calculated based on the number of sequences of the same variant/lineage. This was achieved using ad hoc python script including standardized functions able to extract the mutational pattern either from single or multiple variants.
## Selection pressure analysis
To investigate the SARS-CoV-2 positively and negatively selected sites, selection pressure analysis was performed separately on the Spike gene nucleotide MSAs generated previously for XBB*, EG* and BA*. A positive diversifying selection was inferred on sites statistically significant for a value of non-synonymous/synonymous substitution ω > 1, while negative selection was inferred for ω < 1 [38]. On the contrary, neutrality was inferred if ω = 1 [38].
The models Fast Unconstrained Bayesian AppRoximation (FUBAR) [39,40], Fixed Effects Likelihood (FEL) [39], Single-Likelihood Ancestor Counting (SLAC) [39] and Mixed Effects Model of Evolution (MEME) [41] of the HYPHY and data monkey softwares available under Galaxy platform [39] were used. A posterior probability ≥ 0.95 for FUBAR and p-value ≤ 0.1 for FEL, SLAC and MEME were used to infer significant selection. Only sites found under significant selection were reported. The positions of the sites under selection and the amino acid substitutions type in all the tested datasets were referred according to the SARS-CoV-2 reference sequence Wuhan-Hu-1 (NC_045512.2).
## Spike protein stability prediction
In-silico prediction of amino acid mutations detected under selection pressure was conducted using Site Directed Mutator [42] (SDM: https://compbio.medschl.cam.ac.uk/sdm2/). It is a statistical framework that calculates a stability score, analogous to the free energy difference (ΔΔG) between wild-type and mutant protein. Each amino acid mutation detected in the above datasets was tested singularly against the wild-type available from Protein Data Bank (PDB: https://www. rcsb.org/) database (accession number: 7cwn). ΔΔG positive or negative values represent an increased or decreased stability effect of each mutation respectively.
## Results
## Phylogenetic analyses
Phylogeny was inferred on Spike gene amino acid sequences to show the evolutionary relationship and genetic distance based only on non-synonymous mutations that occurred since the first appearance of Sars-CoV-2 until September 25 th , 2023 (the date in which the present data was retrieved). Fig 1 shows a simplified phylogenetic tree collapsed per clades containing a single variant except for EG* and XBB* as they were found to share closer evolutionary distance within the same clade. All the other variants appeared in separated clades. The Wuhan-Hu-1 sequence was set as outgroup to infer the phylogenetic distance. This tree highlights the capacity of the Spike gene amino acid composition to discriminate almost all represented variants in our dataset with high statistical confidence shown from the bootstrap values. In addition, the tree shows the genetic distance as well as the appearance order of the different variants over time as follows: Alpha, Delta, Omicron, XBB*&EG* and BA*. The complete phylogenetic tree including all sub-lineages is available as S1 Fig.
## Spike amino acid substitutions and indels
Spike amino acid mutational pattern was identified taking the Wuhan-Hu-1 sequence as reference. A total of 662 substitutions (S3 Table ) were detected across all analysed datasets. In details, Alpha variant showed the lowest number of substitutions (10) followed by Omicron (42), Delta (87), BA* (82), EG* (124) and XBB* (532). As reported in Table 1 and shown in S2 Fig, 91 substitutions were prioritized across all datasets showing a frequency higher than 10% in at least one of the analysed variants. Almost 85% (77 out of 91) of the high frequency mutations fall in the S1 subunit and distributed as follows: 29 in the NTD subdomain, 37 in RBD and 11 between S1 and S2. The mutations in S2 subunit are mainly localized in the HR1 subdomain (6) followed by two mutations in the fusion peptide and one in HR2. Importantly, the substitutions N501Y and D614G were detected in all variants, while A27S and G142D are shared across five variants (except Alpha). Following the outbreak of Delta variant, the mutational pattern of Spike gene appeared increasingly variable with additional accumulative substitutions as most of them are shared among Omicron, EG*, XBB* and BA* lineages and their corresponding sub-lineages.
Beside the amino acid substitutions, the detected deletions and insertions were less frequent. A total of 33 deletions were found (S4 Table ), where most of them appeared to be specific for a single variant. Although the number of identified insertions appeared relatively low in all analysed datasets, their importance in viral evolution, survival and interaction with the host remains critical [43]. In total, three insertions within NTD S1 subdomain were detected with frequencies less than 50%, each belonging to single variant or sub-lineage (Table 2). The insertion 'MPLF' at site 17 was found in BA* dataset (45.7%), followed by 'PE' at site 215 (33.3%) in Omicron and 'SLG' in EG* (0.23%) at site 186.
## Selection pressure, a.a. frequencies, protein stability and host-immune response
The selection pressure analysis performed with HYPHY software evaluated the presence of diversifying and purifying selection in the three Spike protein coding gene datasets. A total of 122, 30 and 9 sites predicted under positive selection pressure are reported in Table 3 a, b, c for XBB*, EG* and BA* datasets respectively.
The XBB* dataset (Table 3a) revealed 71 significant positively selected sites, where 24 (24/71, 33.8%) are located in the RBD region (a. a. residues 319-541 according to [17]). 20 of the identified sites (20/71, 28.17%) were confirmed by three methods (SLAC/FUBAR/MEME) and 15 (21.13%) by two (FUBAR/MEME or SLAC/FUBAR). The amino acid replacements under positive selection appeared at different frequency intervals. In particular, 18% (20/122) were identified at frequency ≥ 90% (Table 3a) and 2.5% (3/122) between 70% and 74%. The remaining mutations showed frequencies between 0.023% and 5.2%. 56 were the significant negatively selected sites where 31 (55.3%) were confirmed by two methods (SLAC and FUBAR).
As shown in Table 3b, 25 positively selected sites were found in EG* dataset. 12% (3/25) were confirmed by at least three methods (sites 408 and 456 by FEL/SLAC/FUBAR/MEME and site 83 by FEL/FUBAR/MEME). 14 positively selected sites (14/25, 56%) are located inside the RBD, eight (32%) in NTD and three between S1/S2. These correspond to 30 amino acid substitutions, where 40% (12/30) were found at frequency ≥ 90% and 23,3% (7/30) between 70.4% and 88.3%. The remaining 11 mutations (11/30, 36.7%) appeared less frequent with values ranging between 0.23 and 4.8%. A total of 17 significant negatively selected sites were identified in this dataset, where 10 (58.8%) were confirmed by three methods (FEL/SLAC/FUBAR).
The BA* dataset indicated eight positively selected sites (Table 3c) where three were detected by FUBAR and five by MEME method. Four sites are located within RBD, three in NTD and one in HR1. In the positively selected sites of the BA* dataset 10 amino acid substitutions were identified. Two of which were detected at high frequency (≥ 90%), two (R21T, R403K) at frequencies of 77% and 70% respectively and the remaining between 0.5% and 3.4%. Evidence of supported negative selection was detected for nine sites, where four (44.4%) were reported by at least two methods.
The effect of the amino acid mutations under selection pressure on protein stability inferred from the Site-Directed Mutator (SDM) Model is also reported in Table 3 (a,b,c). Although most of the positively selected amino acids appear to confer a decreased stability to the Spike protein mainly in RBD region (i.e., in XBB*), many replacements refer to an opposite trend (mostly in BA*). However, almost all the reported values are not significantly distant from the baseline (zero), which strongly depends on the conformation of the crystalized protein 3D structure used to conduct the underneath simulations.
According to deep-mutational scanning data, most of the mutations under positive selection appear to have an Immune-Escape (IE) effect (30 sites in XBB*, 14 in EG*, 3 in BA*), while the others influence the binding affinity to ACE2 (7 sites in XBB*, 2 in EG*, 1 in BA*).
$$I I SLAC/FUBAR A A FUBAR Y Y SLAC/FUBAR W W FEL N N SLAC/FUBAR L L FUBAR L L SLAC/FUBAR I I SLAC/FUBAR Y Y SLAC/FUBAR D D SLAC/FUBAR N N SLAC/FUBAR (Continued)$$
$$+ N N SLAC/FUBAR M M FEL D D SLAC/FUBAR W W FEL M M FEL M M FEL Q Q SLAC/FUBAR HR1 M M FEL G G SLAC/FUBAR A A SLAC/FUBAR V V FUBAR Y Y SLAC/FUBAR D (D; H) SLAC/FUBAR 0.03 G G SLAC/FUBAR HR2 N N SLAC/FUBAR I I SLAC W W FEL W W FEL TM Y Y SLAC/FUBAR W W FEL A A FUBAR M M FEL D D SLAC CT S S SLAC/FUBAR T T FUBAR b)$$
## Discussion
The SARS-CoV-2 virus has evolved rapidly since its first appearance leading to the emergence of several variants. Its genome is characterized by a certain level of diversity and complexity, driven by an accelerated evolutionary rate, resulting in the onset of new mutations and variants over time [14,47] which were classified as VOCs or VOIs by WHO [7]. These concepts highlight the importance of investigating the evolutionary dynamic of SARS-CoV-2, to better decipher the genetic variations and the key mutations under selection pressure that may have an impact on diagnosis, effective treatment and vaccine development. Furthermore, to keep up with the rapid evolution of the virus, it is important to combine different expertise, methodologies and bioinformatic frameworks to monitor and quickly identify the emerging changes (i.e., non-synonymous mutations) and their prevalence over a short period of time or in certain geographical area.
This study illustrates a potential approach to assess the selection pressure, the amino acid mutational pattern (substitutions and indels) and the evolutionary dynamics of the Spike protein coding gene of selected SARS-CoV-2 lineages and sub lineages (XBB*, EG*, BA* described materials and methods section and in S2 Table ). Accordingly, the evolutionary relationship through phylogenetic analysis was investigated between the current (until September 25th, 2023, date of data retrieval) and the previous SARS-CoV-2 variants (Wuhan-Hu-1 strain, Alpha, Delta and Omicron). Although many studies illustrated the importance of phylogenetic reconstruction based on complete genome sequence information [22][23][24][25][26], here we explored the capacity of Spike gene alone, selecting a priori all the amino acid substitutions and indels, to draw the evolutionary relationship of SARS-CoV-2 variants since its first appearance in Wuhan. Despite the poor evolutionary resolution shown between XBB* and EG* derived sequences as they were placed in the same clade, Spike amino acid sequences alone provided a good tree topology showing a clear discrimination among the tested variants as well as their relative genetic distances (Fig 1). Based on these results, this well-known phylogenetic approach when applied on suitable genes (in our case Spike gene) or additional genomic region would represent a useful and accurate tool in monitoring programs of newly emergent variants without the need of the complete genome sequences. However, the complete genome information remains fundamental wherever the correct evolutionary resolution cannot be reached with single or multiple genes or a novel emerging pathogen is being analyzed. As shown in Table 3, selection pressure analysis conducted in this study revealed an interesting pattern which was enriched by mutational frequency, deep mutational scanning data (mined from the litterature) and protein stability simulation for advanced Spike protein coding gene behavioural interpretation. For instance, 20 mutations identified as positively selected sites, were common between the XBB* and EG* (V83A, G142D, Q183E, G252V, G339H, L368I, S371F, S375F, D405N, R408S, K417N, V445P, F456L, S477N, T478K, T478R, F486P, Y505H, V1122L, V1128L) and four between the XBB* and BA* (G339H, G339Y, S477N, S477D). Many of these mutations (11 shared across all datasets) were found also in JN.1* and sub-lineages, the variant of interest appeared right after the sampling conducted in this study. This may suggest the possibility to identify potential "marker sites" expressed as conserved mutation regardless the specific lineage to which they belong. Additional investigation on these sites would provide important implications for targeted vaccine formulations and viral monitoring programs.
In XBB* dataset, among the positively selected sites with a.a. replacements observed at high frequency (≥ 90%), five (V83A, G142D, H146K, Q183E, G252V) were in NTD, 12 (G339H, R346T, L368I, S371F, S375F, T376A, D405N, N440K, V445P, G446S, F486P, Y505H) in RBD and one in the S2 subunit (D796Y in Fusion Peptide). In EG* dataset four mutations (T19I, V83A, G142D, Q183E) were in NTD and eight in RBD (G339H, L368I, S371F, S375F, D405N, V445P, F486P, Y505H). In BA* dataset, only two a.a. replacement (positively selected sites at frequency ≥ 90%) were detected in RBD (G339H, S477N). These results indicate a higher variation and high evolutionary pressure related to RBD, impacting the strength of the virus and its interaction with its host and reinforcing the need for a constant monitoring focused on this subdomain [48].
Almost all the positively selected substitutions (21 out of 29) with frequency higher than 90%, were confirmed to be prevalent also in many other different and more recent sub-lineages (JN.1* and its 940 sub-lineages) according to data reported from outbreak.info [14] and shown in Table 3. In addition, according to deep mutational scanning data (summarized in Table 3) 17 high frequency (>90%) mutations provide an immune escape (IE) effect to the Spike protein while only four, located exclusively in the RBD subdomain, appear to influence ACE2 binding affinity. As mentioned above, this data supports the importance of identifying potential "marker sites" which are valid to cover numerous lineages with important implications for vaccine formulations and diagnostics mainly when it is backed up with experimentally proven results like the deep mutational scanning outcomes [13,[44][45][46][49][50][51][52][53][54][55][56][57]. It is important to mention that protein stability inferred in-silico provided additional input when combined with the other data (Table 3) as it could identify an increased or a decreased influence of each specific replacement when compared to the wild-type. However, the method could be considered as complementary asset to laboratory experiments as it is based on statistical assumptions in the protein three dimensional space and its crystalized conformation [58].
Similar variability was also observed from mutation occurrence and frequency overall trend in all datasets (Table 1), where RBD subdomain represented the highest number of shared mutations between Omicron, XBB*, EG* and BA* sub-lineages. In addition, RBD contained also one conserved mutation (N501Y) along all analysed variants, involved in immune evasion and in the binding affinity to ACE2 [59,60]. On the other hand, in NTD subdomain two mutations (A27S, G142D) became conserved with high frequency (>65%) eventhough their appearance in Delta variant seemed to be sporadic (frequency 0.5%). This highlights the importance of regularly monitor not only conserved mutations but also those less frequent mainly if they are involved in important function for virus survival. An additional important mutation shared by all variants is the D614G. Previous studies reported its multiple effects on Spike protein, including the enhancement of viral infectivity and transmission and its binding affinity to ACE2 by altering the conformation of the RBD subdomain [61,62]. In S2 subunit the prevalent high frequency mutations, appeared in Omicron and remained conserved in EG*, XBB* and BA* sub-lineages, fall either in HR1 subdomain (Q954H and N969K) associated with decreased protein stability [63] and S1in S2 subunit (N764K and D796Y) involved in an enhanced infectivity and transmission of the virus [64]. Many other a.a. substitutions here identified were also previously reported in literature. In particular, the V83A, R346T, together with N460K (the latter identified in our study at frequency of 72%) were reported to have a role in increasing fusogenicity and infectivity [28,65].
Importantly, two a.a. substitutions F486V and F486L in XBB*, previously reported to confer resistance to antiviral therapies in UK data (COG.UK), were found in our study at low frequency (0.05). This highlights the importance of monitoring even rare mutations especially if they are involved in drug resistance function. It is worth mentioning that in XBB* dataset a high number of low frequency mutations were detected (S3 Table) either due to the higher number of included sequences or to the higher variability of this variant as it is considered one of the variants most influencing the immune escape mechanism [4]. Accordingly, as reported in Table 3 many low frequency mutations were confirmed under positive selection pressure by different methods and at the same time they showed an important immune escape activity (22 in XBB*, two in EG*, two in BA*) and an enhanced binding affinity to ACE2 (five in XBB* and one in EG*) [44][45][46]. In addition, some known substitutions were not detected in Alpha, Delta and Omicron due to the relatively low number of sequences considered in this analysis as they consisted only of the representatives provided by the source database [30,31]. However, the elaboration and analysis of the a.a. changes already discovered in previous and well-studied variants falls out of the scope of this work.
Many deletions and insertions, either alone or in connection with specific mutations, could play an important role in virus survival. In this study, almost all indels were detected in the NTD subdomain (Fig 2 & Table 2). Although only few of these variations are well known [15,18,38,66,67] we assume that their function can be associated to the involvement of NTD in the viral immune escape and its binding affinity to ACE2 [15,16] and consequently an increased infectivity. However, additional investigations are needed to highlight the role of indels in the virus life cycle and their putative interactions with its host [56].
The approach here described constitutes an alternative method to explore not only SARS-CoV-2 variants, but it could be extended to many other disease-causing organisms as it includes key analytical process combining mutational pattern and evolutionary information. Accordingly, data processing pipeline can be tested, optimized and standardized to be executed on expanded computational infrastructures to satisfy the requisites to conduct large-scale studies needed to monitor new genomic data or to cope with newly appearing disease outbreak.
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# Corrigendum Corrigendum to "The Possible Mechanistic Basis of Individual Susceptibility to Spike Protein Injury"
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# Reply to Sheybani et al : Diagnostic criteria for Epstein-Barr virus-associated encephalitis: A comment on Liu et al
Yongzhao Zhou, Lei Chen, Zhu Liu, Anjiao Peng
after a comprehensive review of the medical records and a thoughtful discuss among authors. These patients were: (1) clinical diagnosis of EBV viral encephalitis; (2) absence of other pathogens (including bacteria, fungi, and other viruses such as herpes simplex virus, varicellazoster virus, and human herpesvirus-7) in CSF testing; and (3) clinical manifestations consistent with previously reported features of EBV encephalitis [2,[5][6][7].
Indeed, a minority of patients may present with coinfection of EBV and other pathogens, yet their clinical manifestations are often more complex and atypical. Therefore, this study included both patients with EBV virus alone and those with concurrent detection of EBV and other pathogens. These data will facilitate a more comprehensive elucidation of the relationship between EBV and encephalitis.
We sincerely appreciate the attention given to our study by Sheybani et al. [1]. We fully agree that the Epstein-Barr virus (EBV) load in cerebrospinal fluid (CSF), the CSF-toserum viral load ratio, and the status of intrathecal antibody production would contribute to confirming EBV's pathogenicity in encephalitis. However, due to the retrospective nature of this study, these tests were not available.
We agree that a higher viral load is more likely to be the causative factor of encephalitis. However, current understanding of the relationship between EBV and encephalitis remains limited. It is currently unclear whether low load of EBV plays a role in the pathological mechanism of encephalitis. Analyzing the relationship between all detected EBV and encephalitis will be helpful for us to gain a comprehensive understanding. Therefore, this study employs multiplex comparative analyses to advance the comprehension of EBV-associated encephalitis.
Currently, there is no gold standard for the diagnosis of EBV encephalitis [2][3][4]. For some of these patients, We cautiously used the concept of "EBV encephalitis"
## References
1. Sheybani, Haddad (2025) "Diagnostic criteria for Epstein-Barr virus-associated encephalitis: a comment on Liu et al" *Virol J*
2. Peuchmaur, Voisin, Vaillant (2023) "Epstein-Barr virus encephalitis: a review of case reports from the last 25 years. Microorganisms"
3. Andersen, Ernberg, Hedström (2023) "Treatment options for Epstein-Barr virus-related disorders of the central nervous system. Infect Drug Resist"
4. Yu, Zhuo, Xu (2024) "Diagnosis of an immunocompetent adult with acute headache and fever as Epstein-Barr virus encephalitis by mNGS of cerebrospinal fluid" *Diagn Microbiol Infect Dis*
5. Huang (2021) "Case report: Epstein-Barr virus encephalitis complicated with brain stem hemorrhage in an immune-competent adult" *Front Immunol*
6. Zhai (2025) "Post-kidney transplantation EBV-related brainstem encephalitis" *QJM Monthly J Assoc Phys*
7. Ridha (2021) "The spectrum of Epstein-Barr virus infections of the central nervous system after organ transplantation" *Virol J*
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# Severe fever with thrombocytopenia syndrome virus infection induces thymic atrophy in IFNAR -/-mice
Longda Ma, Hui Zhang, Manli Wang, Zhihong Hu, Yiwu Zhou, Jia Liu
## Abstract
Severe fever with thrombocytopenia syndrome virus (SFTSV) causes severe disease in humans, yet the pathogenesis remains poorly understood. A hallmark of fatal SFTS cases is the marked depletion of T cells. Previous studies on T cell depletion have predominantly focused on alterations in blood and peripheral lymphoid organs, while the thymus, a critical site for T cell development, has remained largely overlooked. In this study, we employed a lethal murine infection model to investigate the impact of SFTSV on thymic function. Our results revealed that SFTSV infected the thymus and induced severe cortical atrophy in type I interferon receptor-deficient (IFNAR -/-) mice, characterized by a dramatic depletion of CD4 + CD8 + double-positive (DP) thymocytes. Transcriptomic analysis indicated that thymic damage is likely attributable to impaired thymocyte proliferation and increased apoptosis, which may be a consequence of SFTSV-induced alterations in the thymic microenvironment. We found SFTSV-infected macrophages and dendritic cells in the thymus, which accumulated in the cortex and exhibited elevated secretion of IFN-γ, a cytokine commonly associated with acute thymic atrophy. These results demonstrate thymic atrophy caused by SFTSV infection and suggest potential therapeutic strategies for restoring thymic function and promoting T cell reconstitution.
## Introduction
Severe fever with thrombocytopenia syndrome virus (SFTSV) is an emerging tick-borne pathogen that causes hemorrhagic fever with a case fatality rate of up to 30%, particularly among immunocompromised individuals and elderly patients [1,2]. The major clinical manifestations of SFTS include fever, thrombocytopenia, and leukopenia [1][2][3]. SFTSV is endemic in several East Asian countries, including China, South Korea, Japan, Vietnam, Thailand, and Malaysia, highlighting the public health concern posed by SFTSV [2].
An impaired adaptive immune response is a hallmark of fatal SFTS cases [4]. Numerous studies have demonstrated that CD4 + and CD8 + T cells are markedly depleted in patients with SFTS and experimental animal models [5][6][7][8][9][10]. The counts of peripheral blood T cells are inversely correlated with disease severity [5,6,11]. The mechanism of T cell depletion in SFTS remains incompletely defined. Existing studies have primarily focused on the impact of SFTSV on mature peripheral T cells, demonstrating that SFTSV can infect secondary lymphoid organs, including the spleen and lymph nodes, potentially leading to T cell destruction within these tissues [10,[12][13][14]. Elevated T cell apoptosis is identified as one key contributor to this loss [8]. However, it remains unclear whether SFTSV infection may also target the thymus and consequently impairs the development of immature T cells.
The thymus, a primary lymphoid organ, serves as the central site for T cell development and differentiation. Within the thymus, bone marrow-derived lymphoid progenitor cells progress from CD4 -CD8 - double-negative (DN) cells to CD4 + CD8 + doublepositive (DP) cells and ultimately mature into CD4 + CD8 -or CD4 -CD8 + single-positive (SP) T cells [15,16]. T cell differentiation occurs as cells migrate through distinct thymic regions: DN and DP cells are primarily located in the cortex, whereas mature SP cells are predominantly found in the medulla [17]. This process is orchestrated by stromal cells within the thymic microenvironment, including epithelial cells, macrophages, dendritic cells, etc. These cells regulate thymocyte proliferation and differentiation via direct cell -cell contact or secretion of cytokines such as IL-1, IL-2, IL-6, and IFN-γ [17,18].
Studies have demonstrated that viral infections can lead to severe thymic atrophy through direct cytopathic effects or indirect disruption of the thymic microenvironment, as observed in human immunodeficiency virus (HIV), influenza virus, measles virus, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections [19][20][21][22][23][24]. For instance, the HIV-1 Tat protein directly perturbs the DN4-to-DP transition, resulting in a marked depletion of both DP and SP thymocytes [21]. Concurrently, HIV-1 infection also elevates intrathymic IFN-β and TNF-α levels, which upregulates sphingosine-1-phosphate receptors and induces the premature export of immature DP cells [25]. Similarly, severe influenza virus infection also triggers thymic atrophy and disrupts T cell development, primarily through activation of innate CD8 + CD44 high T cells that produce excessive IFN-γ [19]. Similar to SFTS, SARS-CoV-2 exhibits increased severity and mortality in elderly individuals, which is thought to be linked to age-related decline in thymic activity [16,26,27], and preservation of thymic function has been proposed as a potential strategy to improve outcomes [27][28][29].
Building on this evidence, we hypothesized that SFTSV infection may likewise induce thymic atrophy and disrupt T-cell development, leading to lymphopenia that critically contributes to severe SFTS. To test this, we utilized a lethal murine model and demonstrated that SFTSV directly infects the thymus, inducing severe thymic atrophy and depletion of DP thymocytes. Further mechanistic insights were pursued through transcriptomic analysis, flow cytometry, and molecular biology methods.
## Materials and methods
## Cells and virus
African green monkey kidney cells (Vero, ATCC CCL-81) were cultured in Dulbecco's modified Eagle's medium (DMEM, Gibco) supplemented with 10% fetal bovine serum (FBS, Gibco) at 37°C with 5% CO 2 . The SFTSV-HBMC5 strain, which was isolated from a patient with SFTS in Macheng, Hubei Province, China, was used in this study [30]. Vero cells at passage 5 were infected with SFTSV at a multiplicity of infection (MOI) of 0.01 under biosafety level 2 (BSL2) conditions. The cells were then cultured in DMEM containing 2% FBS for 72 h. The viral stock was harvested and stored at -80°C until use. The virus titer was determined using an endpoint dilution assay and calculated by the Reed-Muench method as described previously [31].
## Animal experiments
The animal experiments were conducted in two independent trials. The sample size of this study was determined based on relevant peer-reviewed literature related to SFTSV animal studies [31]. For hematoxylin and eosin staining (H&E), immunofluorescence assay (IFA), quantitative RT-PCR, steroid hormone detection and transcriptomics analysis, we conducted the first animal experiment to collect thymus tissues and blood specimens. 10 female 11-14-week-old type I interferon receptor-deficient (IFNAR -/-) C57BL/6J mice were randomly assigned into two groups and intraperitoneally administered with either 10 TCID 50 (50% tissue culture infectious dose), equivalent to 100 × 50% lethal dose (LD 50 ) of SFTSV [31], or an equal volume of PBS as a control (n = 5 per group). The mice were euthanized at 4 days post-infection (d.p.i.). Blood samples were collected for steroid hormone detection. Thymic tissues were harvested for H&E, IFA, RT-PCR, and transcriptomics analysis. For thymocyte counting and flow cytometry analysis, we conducted the second animal experiment to harvest blood, spleen, and thymus samples. 18 female 12-17-week-old IFNAR -/-C57BL/ 6J mice were randomly assigned into three groups (n = 6 per group). 12 mice were infected with 10 TCID 50 of SFTSV and euthanized at 3 or 4 d.p.i. And 6 mice injected with an equal volume of PBS as a control were euthanized at 4 d.p.i. Additionally, owing to the difficulty in collecting blood from infected mice, only 3 blood samples of 3 d.p.i. group and 4 blood samples of 4 d.p.i. group were obtained (Figure 5(E)). Mice were obtained from Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences and maintained under specificpathogen-free barrier conditions at the Animal Center of Wuhan Institute of Virology. All mice were confirmed as IFNAR -/-by genotyping before experiment. Mice were randomly assigned to experimental groups and housed in individually ventilated cages (IVCs) under controlled environmental conditions in BSL3 laboratory.
Mice successfully infected with SFTSV exhibited significant body weight loss. A reduction of more than 15% in body weight combined with clinical signs such as hunched posture, ruffled fur, sluggish movement, etc., was defined as the euthanasia endpoint. Following isoflurane (RWD) anesthesia, mice were euthanized by enucleation for exsanguination followed by cervical dislocation. The main experimental procedures were performed by a single operator to ensure consistency in the handling of experimental samples. All animal experimental procedures were evaluated and approved by the Institutional Animal Care and Use Committee of the Wuhan Institute of Virology (WIVAF01202201).
## H&E and immunofluorescence staining
Thymus samples from SFTSV-infected and control IFNAR -/-mice were harvested at 4 d.p.i. (n = 5 per group). Following fixation in 4% paraformaldehyde (Boster) for 7 days, tissues were embedded in paraffin and sectioned. 3-µm-thick serial sections were made and used for H&E staining or IFA as described previously [32]. For IFA, we treated sections with 0.1% Sudan Black B (Sigma-Aldrich) for 20 minutes to reduce autofluorescence and incubated them with primary antibodies against various markers (CD3/CD4/ CD8/CD68/CD11c/Ki67/CDK1/Caspase 1/Cleaved-Caspase 3) at 4°C overnight and a secondary antibody conjugated with Alexa Fluor (AF) 488 or 555 at room temperature for 1 h. Detailed information of the antibodies, including vendors and working concentrations, is provided in the Table S1.
## TUNEL staining
To evaluate apoptosis in thymus tissues, TUNEL staining was performed on thymus sections from control and infected mice at 4 d.p.i. (n = 5 per group). Following deparaffinization, the slices were treated with diluted Proteinase K solution (1:10, Servicebio) at 37°C for 20 min. After washing, the sections were incubated with 50 μL Equilibration Buffer (Servicebio) for 10 min at room temperature, and then labeled with TdT incubation buffer solution (Servicebio) at 37°C for 1 h. Finally, the slices were stained with DAPI (Biyuntian) and sealed with 70% glycerin (Sinopharm Chemical Reagent) and then scanned using a panoramic scanner (3DHISTECH).
## Flow cytometry
To further investigate changes in thymocyte number and phenotype, flow cytometry was performed on thymus, spleen, and blood samples collected from control and infected mice at 3 and 4 d.p.i. (n = 6 per group). For the spleen and thymus, single-cell suspensions were prepared by mechanically dissociating the whole spleen or thymus through 70 μm cell strainers (Absin), followed by red blood cell lysis buffer (BD Biosciences) treatment for erythrocyte removal. For peripheral blood lymphocytes, diluted mouse whole blood (1:1 in PBS) was carefully layered over room-temperature lymphocyte separation medium (Dakewei), centrifuged at 500 × g for 30 minutes without brake and the lymphocytes at the plasma-lymphocyte interface were harvested. 10 6 cells per sample were stained with FVS780 (BD Biosciences) and then labeled with different antibody cocktails against surface marker at 4°C for 20 minutes (Table S1). Following surface staining, cells were fixed and permeabilized at 4°C for 2 h using Cytofix/ Cytoperm (BD Biosciences) and then stained with intracellular markers (Caspase 1/Cleaved-Caspase 3/anti-SFTSV NP/IFN-γ, seen as Table S1) at 4°C for 1 h. In addition, for SFTSV NP staining, AF488conjugated goat anti-rabbit IgG antibody was used as a second antibody and incubated at 4°C for 1 h. The stained cells were detected by LSRFortessa Cell Analyzer (BD Biosciences). Owing to a procedural oversight during sample processing, one spleen sample from the 4 d.p.i. group designated for DP cell detection was unintentionally excluded from downstream analysis (Figure 5(E)). The data were analyzed using FlowJo_v10.8.1 software. Relevant gating strategies are shown in the Figure S1.
## Quantitative RT-PCR
Total RNA was extracted from thymus tissues of control and infected mice collected at 4 d.p.i. (n = 5 per group). Tissues were collected in sterile 1.5 mL Eppendorf tubes containing beads, and 1 mL of TRIzol (Takara) was added before storage at -80°C. After thawing, tissue samples were homogenized (4000 rpm, 30 s) using a Tissue Celldestroyer (NEWZONGKE), and total RNA was extracted from the tissue homogenate according to the manufacturer's protocol. RNA was converted to cDNA using PrimeScript™ RT reagent Kit with gDNA Eraser (Takara). Quantitative PCR was performed using SYBR Premix Ex Taq (Applied Biosystems) and specific primers targeting IFN-γ, TNF-α, IL-1a and IL-1b (as shown in Table S2). To quantify viral copy number, SFTSV S gene was amplified by PCR from the cDNA template, and then cloned into pMD-18 vector (Invitrogen) and used as the plasmid standard after its identity was confirmed by sequencing as described previously [31].
## Transcriptomics analysis
Transcriptome sequencing was performed at The Beijing Genomics Institute using total RNA isolated from thymus tissues of control and infected mice at 4 d.p.i. (n = 3 per group). First, the quality of RNA samples was analyzed using Qubit 4.0 (for concentration), Agilent 2100 (for integrity), and a spectrophotometer (for purity). Once RNA samples passed quality control assessments, sequencing libraries were prepared using the MGIEasy Fast RNA Library Prep Kit (MGI), and sequencing was performed on the DNBSEQ-T7 platform. Postsequencing, the data were analyzed using R and RStudio. Relevant information on the number of reads is shown in Table S3. We started with calculating the Pearson correlation coefficient for correlation analysis. Then, we employed DESeq2 to identify differentially expressed genes (DEGs), defined as those with |log2 fold change| ≥ 1 and Padj < 0.05. Subsequently, KEGG enrichment analysis of the DEGs was performed. Gene set enrichment analysis (GSEA) was performed on all genes from the DESeq2 results, ranked according to log2 fold change, using the clusterProfiler R package. Heatmaps were generated to visualize the expression patterns of top 30 significant DEGs in the selected pathways.
## Steroid hormone detection
To quantify hormone concentrations in the blood, liquid chromatography-tandem mass spectrometry (LC-MS) was conducted on peripheral blood samples from control and infected mice collected at 4 d.p.i. (n = 5 per group). The peripheral blood was centrifuged at 3000 rpm at 4°C for 15 minutes to isolate the serum. 200 μL of serum and 300 μL of methanol (Sinopharm Chemical Reagent) were mixed, vortexed, and then centrifuged at 14,000 rpm for 10 minutes. Subsequent extraction was performed on a solid-phase extraction plate and chromatographic separation was carried out using Ultra Performance Liquid Chromatography (Waters ACQUITY UPLC I-CLASS). Finally, mass spectrometry (Waters XEVO TQ-XS) was performed. The standard curve method was established to obtain quantitative results.
## Statistical analysis
Data were analyzed using GraphPad Prism 9.5 software and presented as mean ± standard deviation (SD). For continuous data that following a normal distribution, differences between two groups were analyzed using an unpaired two-tailed Student's t-test. For comparisons among three or more groups, ordinary one-way ANOVA was used to assess overall differences between groups, followed by Dunnett's test for comparisons between infected and control groups. Data that did not follow a normal distribution were analyzed using Mann-Whitney U test to compare differences between the two groups (Figure 3(B)). p < 0.05 was considered statistically significant. *, **, and *** indicate p < 0.05, p < 0.01, and p < 0.001, respectively.
## Results
## SFTSV infection caused severe thymic atrophy in IFNAR -/-mice
To determine whether severe SFTSV infection causes thymic damage, we infected C57BL/6J IFNAR -/-mice with 100× LD 50 of SFTSV. In all the infected mice, we observed severe thymic atrophy at 3 and 4 d.p.i. (Figure 1(A)), with thymic weights reduced by 43.1% and 37.6%, respectively (Figure 1(B)). Thymocyte counts also decreased, with 60.6% and 82.8% loss at 3 and 4 d.p.i., respectively (Figure 1(C)). H&E staining showed obvious depletion of thymocytes in the thymic cortex. Uninfected mice exhibited a thick, densely packed cortex and a distinct boundary between cortex and medulla, whereas infected mice showed a reduced cortex thickness and loss of cortical thymocytes (Figure 1(D)).
Flow cytometry revealed significant decreases in counts of lymphocytes, NK cells, and dendritic cells in the infected thymus, with lymphocytes being most affected, losing 65.0% and 84.6% at 3 and 4 d.p.i., respectively (Figure 1(E)). In contrast, monocytes and macrophages showed no significant changes in the thymus (Figure 1(E)). IFA also confirmed a marked reduction in CD3 + , CD4 + , and CD8 + T cells in the infected thymus, especially in the cortex (Figure 1(F)). These results suggest that SFTSV infection causes severe thymic atrophy in the cortical area and substantial depletion of lymphocytes.
## SFTSV infection caused dramatic depletion of D cells
Thymus is the place of T lymphocyte development. To elucidate whether SFTSV infection affects T cell development, we employed flow cytometry with markers CD8 and CD4 to analyze four key T cell subsets: DN, DP, CD4 + SP, and CD8 + SP cells (Figure 2(A)). In the thymus of uninfected mice, DP cells were the most prevalent (78.0% ± 3.5%), followed by CD4 + SP (13.8% ± 1.8%), DN (4.3% ± 1.1%), and CD8 + SP cells (3.6% ± 1.0%) (Figure 2(B)). SFTSV infection significantly altered the proportional distribution of thymocytes, particularly reducing DP cells while increasing CD4 + SP and CD8 + SP cells (Figure 2(A,B)). Notably, DP cells dropped from 78.0% ± 3.5% to 53.3% ± 15.7% at 3 d.p.i. and 12.9% ± 7.9% at 4 d.p.i. (Figure 2(B)), and DP cell counts plummeted from 2.2 × 10 7 to 0.6 × 10 6 cells at 4 d.p.i. Cell counts of DN cells also declined from 1.2 × 10 6 to 0.8 × 10 5 cells, while the numbers of CD4 + SP and CD8 + SP
## SFTSV mainly infected nonlymphoid cells in the thymus
To investigate whether T cell depletion was directly induced by SFTSV infection, we assessed the infection of SFTSV in the thymus. Using an anti-NP antibody, we found that at 4 d.p.i., viral antigens were present in the thymus, especially in the cortical area (Figure 3(A)). Viral RNA quantification confirmed SFTSV replication in the thymus (Figure 3(B)). Flow cytometry analysis revealed that approximately 0.9% of thymic cells were infected, mainly including macrophages (53.6% ± 9.9%) and dendritic cells (16.2% ± 3.3%) (Figure 3
## (C)).
To confirm the types of cells infected by SFTSV, dual immunofluorescence staining was conducted with anti-NP antibody and cellular markers. The results showed that viral NP protein largely colocalized with CD68 + macrophages and slightly with CD11c + dendritic cells, but lymphocytes marked by CD3 were rarely infected by SFTSV (Figure 3(D)). This suggests that the significant reduction in DP cells is not due to direct infection of SFTSV.
## Cell cycle and cell death pathways were regulated in infected thymus
To uncover the mechanisms behind thymic atrophy, transcriptome analysis was conducted on the thymus of the infected and control groups. The results showed that the infected and the control groups were well separated (Figure S2A) and a total of 3,284 DEGs were identified (Figure S2B). These DEGs were involved in pathways related to viral infections, immune response, signal transduction, and cell growth and death (Figure 4(A)). A further investigation of DEGs in the cell growth and death pathways showed significant alterations in cell cycle, apoptosis, and p53 signaling pathways (Figure 4(B)). GSEA revealed significant enrichment of apoptosis (NES: 1.76), ferroptosis (NES: 1.83), and necroptosis (NES: 1.49) pathways, along with marked suppression of cell cyclerelated gene sets (NES: -2.02), suggesting coordinated activation of programmed cell death coupled with cell cycle arrest (Figure S2C). The heat map of cell cycle genes revealed significant downregulation in essential mitotic factors like cyclins (Ccns), cyclin-dependent kinases (Cdks), and cell division cycle (Cdc) proteins, such as Ccna/b, Cdk1, and Cdc6/20/25/45, and upregulation in cyclin-dependent kinase inhibitors like Gadd45 and Cdkn1a (p21) after SFTSV infection (Figure 4(C)). The heat map of apoptotic genes revealed dramatic upregulation of pro-apoptotic genes such as Fas, Gzmb, Ctsb, and Prf1, as well as downregulation of anti-apoptotic genes including Pik3r3 and Birc5 (Figure 4(D)).
IFA confirmed the reduced expression of cell cycle and proliferation markers CDK1 and Ki67 in the thymus, while TUNEL staining revealed increased apoptosis in the thymic cortex (Figure S2D). These findings demonstrate reduced thymocyte proliferation and increased apoptosis following SFTSV infection, which may contribute to SFTSV-induced thymic atrophy.
## Apoptosis appeared to be one of the main reasons for dp depletion
TUNEL staining revealed that apoptotic cells in the infected thymus were mainly in the cortex, consistent with the significant loss of DP cells, which were typically found in cortical zones. Flow cytometry analysis using Apotracker, a probe for detecting apoptotic cells, showed an increase in apoptotic thymocytes from 2.2% ± 1.5% in controls to 14.7% ± 8.1% at 3 d.p.i. and 17.1% ± 3.6% at 4 d.p.i (Figure 5(A)). Over 32% of these Apotracker + thymocytes were DP cells at 3 d.p. i., followed by CD4 + SP (26.4% ± 7.4%) and CD8 + SP cells (7.1% ± 2.7%) (Figure 5(B)). The percentage of apoptotic DP cells rose from 1.5% ± 0.9% in uninfected mice to 13.7% ± 6.2% at 3 d.p.i. and 16.1% ± 6.6% at 4 d.p.i (Figure 5 Although MFI of Caspase 1, associated with pyroptosis, also showed an increase (from 34.9 to 57.4 and 132.5), IFA revealed significantly less pronounced upregulation compared to Cleaved-Caspase 3 (Figure 5(D), right panel, and Figure S3). Therefore, it appears that both apoptosis and pyroptosis contribute to DP cell depletion, with apoptosis being more predominant.
We also checked if migration of immature DP cells from the thymus to peripheral organs might be another cause for the DP cell decline. No significant increase of DP cells was found in peripheral blood or spleen (Figure 5(E)), indicating that premature migration of DP cells was not a cause of thymic atrophy. In conclusion, apoptosis, rather than premature migration, appears to be the primary cause of DP cell depletion.
## Infected macrophages and dendritic cells exhibited enhanced IFN-γ secretion
Hormones and some cytokines (like IFN-γ, TNF-α, and IL-1) secreted by thymic microenvironment cells, such as dendritic cells, macrophages, thymic epithelial cells, and mesenchymal stromal cells etc., play a crucial role in T cell differentiation. The serum levels of corticosterone (from 359.4 ng/ml to 472.6 ng/ml) and testosterone (from 0.05 ng/ml to 0.04 ng/ml) were determined, and no significant increase was found in infected mice (Figure 6(A)). The cytokines associated with thymic atrophy were analyzed using RT-qPCR, and a significant upregulation of IFN-γ, TNF-α, IL-1a, and IL-1b in the thymus of SFTSV-infected mice was identified (Figure 6(B)). The expression of IFN-γ was further assessed using flow cytometry, which showed a time-dependent increase at 3 and 4 d.p.i. (from 41.9 to 77.2 and 146.0, Figure 6(C)). Further analysis showed that expression of IFN-γ was significantly elevated across multiple thymic immune subsets, including macrophages (from 604.7 to 702.3 and 882.5), dendritic cells (from 150.3 to 132.0 and 456.2), NK cells (from 160.3 to 200.3 and 186.5), lymphocytes (from 103.5 to 122.5 and 158.2), etc (Figure 6(D)). And infected macrophages (from 296.5 to 681.7) and dendritic cells (from 76.6 to 260.0) showed a substantial increase in IFN-γ expression at 4 d.p.i (Figure 6(E)). These data suggest that SFTSV infection alters the thymic microenvironment, and infected macrophages and dendritic cells exhibited enhanced IFN-γ secretion.
Interestingly, although macrophage and dendritic cell numbers in the thymus did not increase (Figure 1 (E)), their distribution changed, with a more concentrated distribution in the cortex of infected thymus compared with a scattered distribution in controls (Figure 6(F)).
## Discussion
Previous immunological studies on SFTS have primarily focused on the effector immune response and alterations in blood and peripheral lymphoid organs, with limited attention given to the thymus [5][6][7][8][9][10][11][12][13][14]. Our study demonstrated that SFTSV infection led to severe thymic atrophy marked by a significant loss of lymphocytes, particularly DP cells (Figure 7(A)). This damage, manifested as reduced thymocyte proliferation and increased apoptosis, is likely attributable to SFTSVinduced alterations in the thymic microenvironment Despite the presence of the blood-thymus barrier, various viruses have been detected in the thymus, where they target distinct cell populations and can induce thymic atrophy. For example, HIV infects FoxP3 + CD3 high CD8 -thymic lymphocytes directly [33], porcine reproductive and respiratory syndrome virus (PRRSV) targets thymic CD14 + monocytes and macrophages [34], influenza A virus is detected in thymic dendritic cells [19], and SARS-CoV-2 infects thymic epithelial cells and thymocytes [35,36].
Interestingly, a common feature of severe thymic atrophy is the decline in DP cells, which are usually not directly infected by these viruses. This may be because the DP cells exhibit heightened sensitivity to apoptosis induced by certain factors compared with SP cells [37]. Our study revealed that SFTSV infection induces severe thymic atrophy with a pronounced loss of DP thymocytes. Paradoxically, the viral antigen was not detected in these diminishing cells but was instead found primarily in macrophages and dendritic cells (Figure 3). These findings suggest that SFTSV-induced thymic atrophy occurs via an indirect mechanism, in which infected macrophages and dendritic cells play a contributory role, a pattern also observed with other viruses.
Thymic atrophy in the context of infectious diseases is typically triggered by several key factors: impaired cell proliferation, increased cell death, and premature migration of thymocytes to peripheral lymphoid tissues [19]. In parasitic infections, thymic involution is commonly associated with reduced proliferation and premature egress. A key example is Trypanosoma cruzi infection, which disrupts S1P-related signaling to drive the premature exit of immature thymocytes [38]. Differently, viral infections -such as those caused by influenza virus, PRRSV, chicken anemia virus, and mouse hepatitis virus -more frequently induce thymic atrophy through elevated thymocyte death [19,[39][40][41].
In our study, we also did not observe evidence of premature DP cell migration to peripheral tissues (Figure 5). Instead, SFTSV infection induced cell cycle arrest and significant apoptosis in thymocytes (Figures 4 and5). These findings suggest that both suppression of cell proliferation and enhanced apoptosis play critical roles in SFTSV-induced thymic atrophy.
Although the precise mechanisms of acute infectioninduced thymic atrophy remain incompletely defined, hormones (including glucocorticoids and testosterone) and pro-inflammatory mediators such as IFN-γ, TNF-α, and IL-6 are recognized as established contributors [19,[42][43][44]. In our study, we found no change in testosterone and only a non-significant increase in corticosterone during SFTSV infection, suggesting that classic stress hormones are not the primary drivers of thymic atrophy in this model. Instead, we identified a pronounced induction of IFN-γ, predominantly produced by infected macrophages and dendritic cells (Figure 6(B-E)). Notably, these IFN-γ-producing cells accumulated in the thymic cortex -the region densely populated with DP thymocytes. This spatial redistribution likely establishes a localized microenvironment of high IFN-γ concentration, which we propose drives the observed DP cell apoptosis and suppression of proliferation [45]. This hypothesis is consistent with studies in influenza and SARS-CoV-2 infections, where IFN-γ neutralization has been shown to rescue DP cell loss [19,36].
A confusing issue is whether viral NP in thymic myeloid cells originates from active replication or phagocytic clearance. Our results revealed that myeloid cells constituted the vast majority (77.3%) of NP + cells at 4 d.p.i., whereas infection in other thymic populations was rarely observed (Figure 3 (C-D)). This distribution strongly argues against phagocytosis as the major source of NP. Instead, our findings support a model in which SFTSV directly infects thymic macrophages and dendritic cells, as observed in other studies [13,46,47]. Following infection, these cells not only amplify the virus but also produce inflammatory mediators such as IFN-γ, creating a localized inflammatory milieu that induces bystander apoptosis and impairs DP thymocyte proliferation, thereby exacerbating thymic atrophy.
This study has several limitations. Our conclusions are restricted to a murine model, specifically relying on IFNAR -/-mice due to the resistance of wild-type animals to SFTSV. This model carries an inherent limitation, as thymic development and immunity in this model are fundamentally shaped by the absence of IFN-I responses [48]. Furthermore, the rapid disease course in this model prevented us from studying potential thymic recovery after the initial injury. Finally, the critical role we propose for IFN-γ was not verified by in vivo neutralization experiments. Future work should prioritize developing immunocompetent murine models susceptible to SFTSV to validate the mechanisms of thymic atrophy and assess the therapeutic potential of targeting IFN-γ.
In conclusion, our study reveals severe thymic atrophy in SFTSV-infected IFNAR -/-mice. We found that SFTSV infects macrophages and dendritic cells within the thymus, enhanced their secretion of IFN-γ, and alters their distribution. These changes may lead to suppressed thymocyte proliferation and increased apoptosis, ultimately resulting in thymic atrophy. Thymic damage likely impairs the immune system in clearing the virus. Our findings shed light on the pathogenic mechanisms of SFTSV and suggest potential therapeutic approaches that aim at restoring thymic function for patients with severe SFTS.
## References
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11. Ji, Hu, Zhang (2024) "Inhibition of SFTSV replication in humanized mice by a subcutaneously administered anti-PD1 nanobody" *EMBO Mol Med*
12. Sakai, Mura, Kuwabara (2023) "Lethal severe fever with thrombocytopenia syndrome virus infection causes systemic germinal centre failure and massive T cell apoptosis in cats" *Front Microbiol*
13. Li, Zhang, Weng (2018) "Cd4 T cell loss and Th2 and Th17 bias are associated with the severity of severe fever with thrombocytopenia syndrome (SFTS)" *Clin Immunol*
14. Westover, Hickerson, Van Wettere (2019) "Vascular leak and hypercytokinemia associated with severe fever with thrombocytopenia syndrome virus infection in mice" *Pathogens*
15. Suzuki, Sato, Sano (2020) "Severe fever with thrombocytopenia syndrome virus targets B cells in lethal human infections" *J Clin Invest*
16. Takahashi, Maeda, Suzuki (2014) "The first identification and retrospective study of severe fever with thrombocytopenia syndrome in Japan" *J Infect Dis*
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21. Liu, Zhang, Deng (2014) "Severe influenza A (H1N1)pdm09 infection induces thymic atrophy through activating innate CD8(+)CD44(hi) T cells by upregulating IFN-γ" *Cell Death Dis*
22. Zhang, Li, Wang (2021) "Azvudine is a thymus-homing anti-SARS-CoV-2 drug effective in treating COVID-19 patients" *Signal Transduct Target Ther*
23. Fiume, Scialdone, Albano (2015) "Impairment of T cell development and acute inflammatory response in HIV-1 Tat transgenic mice" *Sci Rep*
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# Disulfiram inhibits poxvirus extracellular virus production by targeting the palmitoylation sites on F13
Ting Xu, Junwen Luan, Yao Hou, Leiliang Zhang
## Abstract
M pox virus (MPXV) has attracted significant attention due to its increasing occurrence since 2022. Tecovirimat (ST-246) is a well-known inhibitor that targets the poxvirus F13 protein family, effectively reducing the production of enveloped extracellular virus (EEV) but not intracellular mature virus (IMV) (1). A previous study has suggested that tecovirimat interacts with the phospholipase D enzymatic activity site of F13 (2). Recent findings indicate that tecovirimat functions as a molecular glue, promoting the dimerization of F13 (3). However, it remains unclear whether alternative targeting strategies for F13 exist.Poxvirus F13 is known to be palmitoylated at cysteine (Cys, C) residues 185 and 186 (4). Disulfiram is an FDA-approved drug used in the treatment of alcohol use disorder (AUD) (5). Previous studies have indicated that disulfiram targets the cysteine residues of HCV NS5A to inhibit HCV replication (6). Therefore, we investigated whether disulfiram could interact with cysteine residues in F13.We utilized AlphaFold3 to simulate the protein structures of palmitoylated MPXV F13, incorporating the palmitic acids on C185, C186, and C13 (predicted). Next, we employed AlphaFold3 to dock the interaction between palmitoylated F13 and disulfiram. Surprisingly, our analysis revealed that disulfiram interacts with the palmitic acids in F13 (Fig. 1A). Docking and visualization were performed using the Molecular Operating Environment (MOE) 2019. Disulfiram was observed to interact with leucine (Leu) 178, Cys181, serine (Ser) 182, palmitoylated Cys185, and palmitoylated Cys186 (Fig. 1B) in MPXV F13. Subsequently, we used AlphaFold3 to simulate the protein structures of MPXV F13 without palmitoylation and conducted docking studies between non-palmi toylated F13 and disulfiram (Fig. 1C). In this case, disulfiram was found to associate with phenylalanine (Phe) 52, Cys53, Cys120, Leu118, Ser135, threonine (Thr) 137, glycine (Gly) 139, Ser140, tryptophan (Trp) 279, and asparagine (Asp) 312 (Fig. 1D). Furthermore, we utilized AlphaFold3 to simulate the protein structures of palmitoylated vaccinia virus (VACV) F13, including the palmitic acids on Cys185 and Cys186 (Fig. 1E). Interestingly, disulfiram associated with alanine (Ala) 184, palmitoylated Cys185, and proline (Pro) 188 in VACV F13 (Fig. 1F).To investigate the interaction between MPXV F13 and disulfiram, we conducted a cellular thermal shift assay (CETSA). Our results demonstrate that disulfiram increased the stability of F13, whereas it did not affect the stability of the F13 C185/C186S mutant (Fig. 1G andH). These findings suggest a specific association between disulfiram and F13 at the C185/C186 sites.Next, we examined whether disulfiram inhibits VACV, which serves as a model system for studying poxviruses. Disulfiram significantly decreased the plaque size of the VACV Western Reserve (WR) strain in BSC-1 cells, with a calculated half maximal inhibitory concentration (IC 50 ) of 825.1 nmol/L (nM) (Fig. 2A). Cell Counting Kit-8 (CCK-8) assays demonstrated that the antiviral effects of disulfiram are not linked to cytotoxicity.
## FIG 1 Interaction between disulfiram and palmitoylated MPXV F13. (A)
The association between disulfiram and the palmitic acids at C185 and C186 of palmitoylated MPXV F13 was identified by AlphaFold3. The structures of F13 from MPXV_USA_2022_MA001 virus strain and its palmitoylated form at C13, C185, and C186 were predicted using AlphaFold3.
(B) Analysis of the specific binding sites of disulfiram to palmitoylated MPXV F13 using MOE2019. (C) The association between disulfiram and non-palmitoylated MPXV F13 was identified by AlphaFold3. (D) Analysis of the specific binding sites of disulfiram to non-palmitoylated MPXV F13 using MOE2019. (E) The association between disulfiram and the palmitic acids at C185 of palmitoylated VACV F13 was identified by AlphaFold3. The structures of F13 from the VACV WR strain and its palmitoylated form at C185 and C186 were predicted using AlphaFold3. (F) Analysis of the specific binding sites of disulfiram to palmitoylated VACV F13 using MOE2019. (G) 293T cells were transfected with GFP-MPXV F13 for 24 hours, after which the cells were harvested. Following three freeze-thaw cycles, the supernatant was collected by centrifugation, and 10 µM disulfiram or DMSO was added to the supernatant. The mixture was then heated to the specified temperatures before adding the loading buffer for western blot analysis (n = 3). Relative protein levels of GFP-MPXV F13 were quantified using ImageJ.
(H) 293T cells were transfected with GFP-MPXV F13 C185/C186S for 24 hours, and the cells were subsequently harvested. After (Continued on next page)
To further investigate the VACV life cycle, we concentrated on assessing the titers of IMV and EEV following disulfiram treatment. Notably, disulfiram inhibited EEV production (IC 50 = 7,125 nmol/L) without impacting IMV production in Huh7.5.1 cells (Fig. 2B). A similar inhibition of EEV production was observed in HeLa cells (IC 50 = 3,022 nmol/L) (Fig. 2C). undergoing three freeze-thaw cycles, the supernatant was obtained through centrifugation, to which either 10 µM disulfiram or DMSO was added. The mixture was then heated to the designated temperatures prior to the addition of loading buffer for western blot analysis (n = 3). The relative protein levels of GFP-MPXV F13 were quantified using ImageJ.
## FIG 2
Disulfiram inhibits the production of VACV EEV. (A) BSC-1 cells were infected with VACV WR, and after 2 h, fresh media containing different concentrations of disulfiram were added. Cells were collected 52 h post-infection and stained with 0.1% crystal violet. For the cell viability assay, BSC-1 cells were seeded in 96-well plates and grown to 50% confluence before treatment with various concentrations of disulfiram. After 52 h, CCK-8 reagent was added and incubated for 2 h. Absorbance was measured using a microplate reader, and IC 50 and CC 50 values were calculated using GraphPad Prism (n = 3). (B) Huh7.5.1 cells were infected with VACV WR (MOI = 3), and after 2 h, fresh media containing different concentrations of disulfiram were added for another 22 h. Supernatants and cells were collected to determine the viral titer and calculate the IC 50 value. Huh7.5.1 cells were seeded in 96-well plates and grown to 50% confluence before treatment with various concentrations of disulfiram. After 52 hours, CCK-8 reagent was added and incubated for 2 h. Absorbance was measured using a microplate reader (n = 3). Statistical analysis was conducted with GraphPad Prism (t-test). ns, P > 0.05. (C) HeLa cells were infected with VACV WR (MOI = 3), and after 2 h, fresh media containing different concentrations of disulfiram were added for another 22 h. Supernatants and cells were collected to determine the viral titer and calculate the IC 50 value. HeLa cells were seeded in 96-well plates and grown to 50% confluence before treatment with various concentrations of disulfiram.
After 52 h, CCK-8 reagent was added and incubated for 2 h. Absorbance was measured using a microplate reader (n = 3). Statistical analysis was conducted with GraphPad Prism (t-test). ns, P > 0.05. (D and E) Huh7.5.1 (D) or HeLa (E) cells were infected with VACV A4-YFP at an MOI of 3. After 2 h, the medium was replaced with fresh media containing 15 µmol/L disulfiram. Cells were collected 22 h later, fixed with 4% PFA, and stained for actin with a working concentration of 80 nmol/L of phalloidin. Arrows denote actin tails. Scale bar: 10 µm. Quantification was performed using ImageJ (n = 20), and statistical analysis was conducted with GraphPad Prism (t-test). ****, P < 0.0001. Considering the close relationship between EEV production and the dynamics of actin tails, which are crucial for viral egress, we evaluated the effects of disulfiram on actin tail lengths. Treatment with 15 µmol/L disulfiram led to a notable decrease in the lengths of actin tails in both Huh7.5.1 and HeLa cells (Fig. 2D andE). Although disulfiram may influence cellular pathways, our experiments show that the observed reduction in actin tail length correlates specifically with viral processes rather than broadly affecting host cell actin regulation. This specificity is further supported by our findings indicating that disulfiram's inhibitory effects on EEV formation do not result in widespread alterations to the overall structure of host cell actin.
Disulfiram is known to interact with thiol groups non-specifically. Although our findings indicate a specific association between disulfiram and F13, it is crucial to acknowledge that the observed effects may also stem from disulfiram's broader reactivity with thiol-containing molecules. Further studies are needed to elucidate the specific mechanisms underlying the observed inhibition and confirm that these effects are indeed mediated through the intended target, F13.
The F13 proteins of MPXV and VACV share 99% sequence identity (with only 3 amino acid differences among 372 residues), highlighting a high degree of structural conservation between these viral proteins. This significant conservation suggests that the mechanisms of action for disulfiram may be similar for both viruses. Given that disulfiram effectively interacts with VACV F13, it is likely that comparable interactions occur with MPXV F13. Our findings strongly justify the use of VACV in our functional assays while still addressing our hypothesis regarding MPXV F13.
In summary, our findings demonstrate that the FDA-approved drug disulfiram can interact with palmitic acids in poxvirus F13, inhibiting EEV formation. By elucidating the mechanisms underlying this inhibition, we can explore disulfiram's potential repurpos ing as an antiviral agent. Additionally, the insights gained from our study may inform the design of novel compounds that target the palmitoylation site on F13 or similar proteins in other viruses, ultimately advancing antiviral therapies. Our results indicate that targeting palmitic acids in poxvirus F13 represents a novel strategy against poxvirus, including MPXV. Further structural studies and clinical investigations are needed to translate our findings into actionable strategies for managing poxvirus outbreaks.
## Funder
## References
1. Li, Pan, Zhang (2025) "Tecovirimat: a journey from discovery to mechanistic insights in poxvirus inhibition" *PLoS Pathog*
2. Li, Liu, Li et al. (2022) "Targeting F13 from monkeypox virus and variola virus by tecovirimat: molecular simulation analysis" *J Infect*
3. Vernuccio, León, Poojari et al. (2025) "Structural insights into tecovirimat antiviral activity and poxvirus resistance" *Nat Microbiol*
4. Grosenbach, Ulaeto, Hruby (1997) "Palmitylation of the vaccinia virus 37-kDa major envelope antigen: identification of a conserved acceptor motif and biological relevance" *J Biol Chem*
5. Rothstein (1970) "Use of disulfiram (Antabuse) in alcoholism" *N Engl J Med*
6. Lee, Duh, Wang et al. (2016) "Using an old drug to target a new drug site: application of disulfiram to target the Znsite in HCV NS5A protein" *J Am Chem Soc*
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# Metagenomic detection of the complete coding regions of Tanay virus from mosquitoes (Armigeres subalbatus) in India
Arumugam Perumal, Desingu, Selvarayar Arunkumar, K Nagarajan, G Saikumar
## Abstract
So far, the Tanay virus has only been detected in the Philippines and China. Here, we report that a complete coding region-wide virus with 3.7-16.7% nucleotide diversity to the Tanay viruses identified in China and 25.2% nucleotide diversity to those identified in the Philippines is circulating in mosquitoes (Armigeres subalbatus) in India.
KEYWORDS Tanay virusC urrently, the Tanay virus (TANAV), which is classified within the genus Sandewavirus and is part of the newly proposed taxon Negevirus, has only been detected in the Philippines (1) and China (2, 3). In the Philippines, it was found in pools of Culex spp. and Armigeres spp. (1). In China, it was identified in Culex tritaeniorhynchus, Culex quinquefasciatus, and Anopheles sinensis (2, 3). In this study, we detected the complete coding regions of the TANAV from Armigeres subalbatus in India.In this study, we collected Armigeres subalbatus mosquitoes from Nagercoil (Putheri Lake) located in the Kanyakumari District of Tamil Nadu, India. We pooled 20 mosqui toes to create a single sample by homogenizing them in PBS for virus metagenomic sequencing. From this pooled sample, we extracted RNA using TRI reagent following a standardized protocol (4). Library preparation was performed with the TruSeq Stran ded Total RNA Kit (Illumina #15032618, Illumina #20020596), adhering to the manu facturer's guidelines. Additionally, the insert size of the library was measured using TapeStation 4150 (Agilent) with D1000 screentapes (Agilent #5067-5582) following the manufacturer's instructions. Finally, sequencing was conducted on Illumina NovaSeq 6000. In the paired-end sequencing, we generated 99,704,106 reads with a length of 150 bp. Subsequently, quality control and removal of low-quality and potential adapter sequences were conducted using FastQC (version 0.11.5) and Trimmomatic (5), respectively, following default parameters. The reads that passed quality control were filtered to virus-specific reads using the protein-based alignment method, DIAMOND (6), and the filtered reads were assembled de novo with metaSPAdes (7) using default settings. The assembled sequences were then analyzed with BLASTx and BLASTn against the National Center for Biotechnology Information (NCBI) RefSeq database to identify the viruses (8), and the virus-specific contig was aligned in the advanced genome aligner (AGA) (9) and the consensus variant caller GATK/BcfTools (10, 11), employing default parameters.In this virus-metagenomic analysis, we identified the complete coding regions of the TANAV, which is 9,556 bp long with a guanine and cytosine content of 36.83%. This virus has three open reading frames (ORFs) as follows: ORF1 from 60 to 6,707 nucleotide positions with 2,215 amino acids, ORF2 from 6,731 to 8,515 nucleotide positions with 594 amino acids, and ORF3 from 8,645 to 9,292 nucleotide positions with 215 amino acids.Our analysis has shown that the TANAV/India/2024 is closely related to a strain of the virus detected in Anopheles sinensis in China (MG673930.1) with the nucleotide identity of 95.76% in the NCBI BLAST analysis. Consequently, we categorized the TANAV into
three distinct clades based on the complete genome sequence: the Philippines clade, China clade-1, and China clade-2 (Fig. 1A andB). The TANAV/India/2024 has displayed the genetic divergence of 3.7, 16.7, and 25.2% with China clade-2, China clade-1, and Philippines clade, respectively (Fig. 1B). Overall, our results indicate that the TANAV related to the China genotype 2 found in Culex tritaeniorhynchus and A. sinensis in China is circulating in Armigeres subalbatus in India.
## References
1. Nabeshima, Inoue, Okamoto et al. (2014) "Tanay virus, a new species of virus isolated from mosquitoes in the Philippines" *J Gen Virol*
2. Wang, Wu, Li et al. (2018) "A new Tanay virus isolated from mosquitoes in Guangxi, China" *Arch Virol*
3. Zhao, Mwaliko, Atoni et al. (1963) "Characterization of a novel Tanay virus isolated from Anopheles sinensis mosquitoes in Yunnan, china" *Front Microbiol*
4. Desingu, Mishra, Dindi et al. (2023) "PARP1 inhibition protects mice against Japanese encephalitis virus infection" *Cell Rep*
5. Bolger, Lohse, Usadel (2014) "Trimmomatic: a flexible trimmer for Illumina sequence data" *Bioinformatics*
6. Buchfink, Xie, Huson (2015) "Fast and sensitive protein alignment using DIAMOND" *Nat Methods*
7. Bankevich, Nurk, Antipov et al. (2012) "SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing" *J Comput Biol*
8. Vilsker, Moosa, Nooij et al. (2019) "Genome Detective: an automated system for virus identification from high-throughput sequencing data" *Bioinformatics*
9. Deforche (2017) "An alignment method for nucleic acid sequences against annotated genomes" *bioRxiv*
10. "2025 GATK releases"
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# Historical evolution, research hotspots and emerging trends of pediatric hand, foot, and mouth disease: a bibliometric worldview since the 21st century
Jade Teng, Ni Zhu, Lei Liang, Yujing Zhang, Xinxin Zhang, Xuran Guo, Yongbin Yan, Chang Gung
## Abstract
Background: Hand, foot, and mouth disease (HFMD) poses a significant challenge to global public health. Primarily caused by enterovirus and coxsackievirus infections, the disease has a particularly pronounced impact in the Asia-Pacific region. However, systematic analysis and discussion regarding the developmental trajectory, core research entities, current status, key research directions, and future prospects of pediatric HFMD research remain lacking.Methods: This study collected and analyzed papers and reviews on pediatric HFMD published between January 1, 2000, and February 1, 2025, from the Web of Science Core Collection and PubMed. Key research indicators were analyzed through bibliometric visualization, using tools including Excel, CiteSpace, VOSviewer, and BibliomeTools (an R-based tool in R-Studio).Results: Since the start of the 21 st century, academic publications in pediatric HFMD have steadily increased, with a cumulative total of 2,034 papers published by February 1, 2025. Global research distribution exhibits uneven patterns, with China emerging as core contributors. Specifically, Lin, Tzou-Yien from China, has published the largest number of papers, while Chang, Luan-Yin is the co-cited author with the highest citation rate. Solomon T et al.'s "Virology," Epidemiology, Pathogenesis, and Control of Enterovirus 71" being the most cited study in the field. Research on pediatric HFMD is closely integrated with disciplines such as virology and epidemiology, forming core research themes around "HFMD," "enterovirus 71," and "enteroviruses." Recent research has focused on the pathogenesis, epidemiology, novel therapeutic discoveries and vaccine development for pediatric HFMD. Looking ahead, it is essential to delve deeper into the molecular mechanisms underlying the interaction between the human HFMD virus and its host, and to develop multivalent vaccines targeting multiple serotypes. Frontiers in Medicine 01 frontiersin.org Liang et al. 10.3389/fmed.2025.1722750 Conclusion: This study employs bibliometric methods to visualize research in the field of pediatric hand, foot, and mouth disease, revealing trends and frontiers in this area. It will provide valuable reference for scholars seeking key research questions and potential collaborators.
## 1 Introduction
Hand, foot and mouth disease is a common infectious disease in children caused by enterovirus infection. Children under 5 years of age, especially those under 3 years, have the highest incidence. Since its first report in New Zealand in 1957, HFMD has spread widely around the world (1). In most cases, the symptoms of HFMD are mild and manifest as fever and vesicular rashes on the hands, feet, and mouth, usually lasting less than a week (2). However, many patients exhibit critical symptoms, often severe neurological lesions and cardiopulmonary complications, and may experience long-term neurological sequelae after recovery (3). Therefore, HFMD is regarded as a serious public health problem globally. The disease is concentrated mainly in regions such as Asia, Africa, and South America. China is a major high-incidence area, which is related to the warm and humid climate in these regions, which is conducive to the survival and spread of enteroviruses (4). Moreover, in some developing countries, poor sanitation conditions, insuÿcient public health facilities, and low levels of health education also increase the risk of virus transmission. Recently, a tomato flu, also caused by an enterovirus, was discovered in India. Owing to its symptoms being similar to those of HFMD, people have once again focused on the epidemic of HFMD (5). In terms of virus types, various types of enteroviruses cause HFMD. Coxsackievirus A16 (CVA16) and enterovirus 71 (EV71) are the most common, and they are the main virus types causing severe cases and deaths (6). However, in recent years, the number of cases caused by Coxsackievirus A6 (CVA6) and Coxsackievirus A10 (CVA10) has shown an increasing trend in some regions (7). To date, many scholars have researched the pathogenesis (8), epidemiology (9), and related treatment and prevention measures (8,10) of HFMD. Vaccines against EV71 have also achieved remarkable results (11). However, with the publication of many research findings, there is a lack of systematic analysis of academic achievements and research status in this field from a global perspective. Moreover, systematic reviews and meta-analyses cannot predict the future development trend of a field, making it diÿcult for researchers to capture the current research hotspots, key and diÿcult points, and future trends.
Bibliometrics emerged in the 1960s. As an interdisciplinary science, it uses mathematical and statistical methods to conduct quantitative analysis of various knowledge carriers and is an important part of the information science system. Compared with systematic literature reviews, bibliometrics can provide more objective and reliable analysis results, eectively reducing potential biases caused by subjective intentions; thus, bibliometrics has been widely applied in academic research (12)(13)(14). In research related to pediatric HFMD, many previous clinical and basic studies have made significant contributions to the development of this field. However, bibliometric analysis in this field is relatively rare. Therefore, this study systematically collected and analyzed the academic literature related to pediatric HFMD in recent years in detail, aiming to comprehensively reveal the research trends and development trends in this field. This study used methods such as keyword co-occurrence analysis, citation analysis, and author-institution cooperation network analysis to explore the main themes, core researchers, key research institutions, and geographical distribution of research focused on the study of pediatric HFMD in detail. In addition, this study also evaluated the knowledge base and research frontiers of research in this field to provide valuable reference and guidance for future related research.
Flowchart of the literature screening process for pediatric hand, foot, and mouth disease included in this study.
## 2.2 Data analysis
After confirming the accuracy of the data, the screened and optimized original dataset was exported in the format of a.txt file. This dataset contains important information such as titles, authors, keywords, institutions, countries/regions, citations, journals, and publication dates. This study utilized tools such as Microsoft Oÿce Excel 2021, VOSviewer (version 1.6.18), CiteSpace (version 6.1. R6), and the R package "Bibliometrix" was used to conduct the data analysis and visualization.
As the core spreadsheet component within the Oÿce 2021 suite, Microsoft Oÿce Excel 2021 adapts to diverse data analysis and processing scenarios across multiple fields. This study imported bibliometric data and foundational literature information from the target field into Microsoft Oÿce Excel 2021. After data organization and classification, analytical tables required for the paper were generated. Furthermore, based on the aforementioned publication volume and citation data, Figure 2 was plotted using this software. Simultaneously, a polynomial fitting method was employed to conduct trend analysis on the annual cumulative publication volume data.
CiteSpace (18,19) was developed by Chaomei Chen et al. Its principle is to create a network map of a specific field, thereby obtaining key information about the research in that field, such as potential trends, research frontiers, and research directions. In this study, with the help of CiteSpace software, co-occurrence and cluster analyses were carried out for information such as authors, research institutions, and countries. The Citespace analysis parameters used in this study are as follows: Link Retaining Factor (LRF) = 3.0; Maximum Links Per Node (L/N) = 10; Look Back Years (LBY) = 5; Percentage of Nodes to Label = 1.0%; Threshold (k) = 25; Bibliometrix (22)(23)(24) is an R package developed by Aria, Cuccurullo et al. in and is mainly used for comprehensive bibliometric and scientometric analyses. In this study, we used Bibliometrix to analyze the evolutionary trends of keywords in the literature. Through the comprehensive use of the abovementioned tools, we achieved multidimensional analysis and visual display of the literature information, which not only adhered to academic norms but also ensured the scientific validity and eectiveness of the research.
## 3 Results
## 3.1 Publication and citation analysis
Changes in the volume of scientific literature at specific points in time can reveal the accumulation of knowledge within a particular research field, providing crucial parameters for quantitatively assessing its development. Figure 2A shows the trends in the number of publications and citation counts in the field of pediatric HFMD research from 2000 to 2025. In terms of the number of publications, before 2009, the number of publications in this field remained relatively low. From 2009 to 2014, the number of annual publications rapidly increased, reaching a maximum of 164 in 2019. The citation counts experienced rapid upward phases between 2009-2015 and 2017-2019, with a peak of 5,365 citations in 2021. Notably, the data collection for this study was completed in early February 2025, so the number of publications and citation counts for 2025 cannot be reflected, and the data for this year lack reference value to a certain extent.
In this work, polynomial fitting was also carried out on the annual cumulative number of publications, as shown in Figure 2B. The fitting formula is y = 0.0002x 6 -0.0158x 5 + 0.4367x 4 -5.125x 3 + 27.041x 2 -45.13x + 33.066, and the goodness of fit is R 2 = 0.9998. This fitted curve shows a favorable upward trend and has a high goodness of fit. This result fully demonstrates the broad development prospects of this research field.
## 3.2 Distribution of countries/regions
This study analyzes 78 countries and regions participating in pediatric HFMD research to identify key contributors and the distribution of academic centers in this field. Table 1 lists the top 10 countries and regions in terms of publication volume, citation count, and Total Link Strength in pediatric HFMD research. China holds an absolute dominant position in this field, leading significantly with 1,457 publications (71.63%) and 37,765 citations. This dominance is closely linked to the historical prevalence of HFMD in China. Beyond China, significant contributions from countries such as the USA (221 papers, 10.87%, 8,496 citations) and the UK (106 papers, 5.21%, 5,541 citations) have been crucial in advancing this research domain.
Figure 3A shows the academic achievements of various countries in the research field of pediatric HFMD and the academic cooperation network among countries. An analysis of the connecting lines clearly reveals that there are relatively close academic connections between China and the United States, between China and Australia, and between China and the United Kingdom. This strongly reflects that the activity and participation levels of these countries and regions in the research field of pediatric HFMD are relatively high. Figure 3B vividly and three-dimensionally presents the geographical distribution pattern of the main literature-producing countries in this field. China, the United States, the United Kingdom, and Australia clearly play crucial roles as academic hubs in this research field. They have established close academic connections with many other countries and play an important role in promoting academic development and exchanges in this field. In addition, Figure 3C shows in detail the number of papers produced by each country in the research field of pediatric HFMD and uses dierent colors to distinguish between studies published through transnational cooperation and those coauthored by domestic authors. In countries with a large number of published papers, such as China, the United States, and Singapore, although they have extensive cooperation with other countries, most of the published literature still comes from cooperation among domestic authors. In contrast, British authors tend to establish transnational cooperation in academic exchanges.
## 3.3 Distribution of institutions
To assess the academic influence and contributions of relevant institutions and reveal their collaborative networks and patterns, we compiled and analyzed data from 2,234 institutions engaged in research within this field. Table 2 lists the top 10 institutions by number of published papers and citation counts. Chinese Academy of Sciencess leads in publication volume with 120 papers, followed closely by the Chinese Center for Disease Control and Prevention with 118 papers. The latter also tops the citation list with 5,063 citations. Beyond these two institutions, Chang Gung University (76 papers) and Fudan University (74 papers) also rank highly in paper output. Outside of China, overseas institutions such as the National University of Singapore (67 papers, 2,598 citations) and the University of Oxford (55 papers, 2,578 citations) also made significant contributions in this field.
Furthermore, we used VOSviewer to generate Figure 4 to visually display the potential connections between research institutions. In Figure 4A, the cooperative relationships between these institutions show significant geographical characteristics. Institutions in the Taiwan Province of China are mainly concentrated in the blue cluster on the right side of the figure, including National Cheng Kung University and National Health Research Institutes. The clusters on the left side of the figure are mainly composed of institutions in mainland China. For example,
## 3.4 Distribution of authors and co-cited authors
Analyzing authors and co-cited authors helps us identify core contributors within a field, uncover academic connections and collaboration networks among authors, and reveal the knowledge base and academic lineage of the field. Table 3 lists the top 10 authors in terms of the number of published papers and cocitation counts. Among them, all the top 10 authors by the number of published papers are from China. Lin, Tzou-Yien from Kaohsiung Chang Gung Memorial Hospital published 40 papers; Liang, Zhenglun and Mao, Qunying from the National Institutes for Food and Drug Control published 37 and 36 papers, respectively. In terms of co-citation counts, Chang Ly from National Taiwan University has received the most attention, with 785 co-citations; followed by Wang Sm from National Cheng Kung University, with 700 co-citations; and Zhang Y from the Chinese Academy of Medical Sciences, with 666 co-citations. The above phenomena once again confirm the significant influence of China in the research field of pediatric HFMD. Supplementary Figure 1A shows the trends in the number of publications and total citation counts of key authors over time in the research field of pediatric HFMD. Among them, Lin, Tzou-Yie, who has the highest number of publications in this field, is also the author with the longest time span of creation.
Lotka's law, one of the earliest well-known laws in the field of bibliometrics, plays an important role in research (25). As shown in Supplementary Figure 1B, a comparison reveals that the proportion of authors with a small number of published papers is greater than the expected value. This indicates that in the research field of pediatric HFMD, the number of authors who have long been deeply engaged in and committed to research in this field is relatively limited.
The cooperative relationships among authors drawn by VOSviewer are presented in Figure 5A. On the basis of these cooperative relationships, authors in the research field of pediatric HFMD are divided into dierent clusters. The cyan, pink, and green clusters on the right side of the figure mainly include authors from the Taiwan Province of China, such as Lin, Tzou-Yien, Chang, Luan-Yin, Liu, and Ching-Chuan. Meanwhile, most of the authors on the left side of the figure are from mainland China, such as Liang, Zhenglun, Mao, Qunying, Zhu, Fengcai, Duan, and Guangcai. In addition, there are clusters representing Sino-foreign cooperation; for example, the brown cluster includes Chu, Justin Jang Hann, Perera, David, Meng, and Tao. Compared with the relatively independent clusters of authors from the Taiwan Province of China on the right side, the academic cooperative relationships among the clusters on the left side are more complex and diverse. Figure 5B shows that the small clusters with Yu, Hongjie, Liao, Qiaohong, Liu, Fengfeng, etc., as the core and those with Li, Dong, Chen, Shuaiyin, Chen, Yu, etc., as the core on the left side have the closest internal cooperative relationships.
The co-citation network among authors is shown as follows. Co-citation refers to the frequency with which two authors are simultaneously cited by a third-party author in the same literature. On the basis of this indirect citation relationship, the research relevance and article similarity among authors can be more intuitively revealed (26). In Figure 5C, the authors are divided into three dierent clusters according to the similarity of their research content. The red cluster, which is represented mainly by Zhang, Y, Zhu, Fc, Xing, and Wj, focuses on research on the application of biotechnology and applied microbiology in pediatric HFMD. Second, the green cluster, which includes authors such as Ooi, Mh, Ying-Chu Lin, Wang, and SM, is more inclined toward research in the immunology direction of this field. Finally, some authors who focus on virology, neuroscience, etc., are classified into the blue cluster, such as Solomon, T, McMinn, Pc, Liu, CC, etc.
## 3.5 Journal publication analysis
An analysis of 474 journals publishing research in this field was conducted to gain a better understanding of the current state of relevant publications. According to Table 4 and Supplementary Figure 2A, Plos One has the highest number of publications (117 articles), followed by BMC Infectious Diseases (64 articles), Scientific Reports (63 articles), and the Journal of Medical Virology (62 articles). Journal of Virology is the journal attracting the most attention, with a co-citation count of 3828 times, followed by Plos One (3332 times). Notably, among the top ten journals in terms of the number of published articles, nine are in the Q2 quartile or higher, with three in Q1. This feature is even more prominent in the co-citation ranking, where more than half of the journals are in Q1, including top-tier medical journals such as the New England Journal of Medicine (cited 1686 times, with an impact factor of 96.3). These findings indicate that the research trends and cutting-edge hotspots of pediatric HFMD have received extensive attention both within and outside the research field. Supplementary Figure 2B shows a correlation heatmap of journals. The heatmap visualizes the changes in the popularity of the journals that have made significant contributions to the research field of pediatric HFMD since 2000 through a time axis and classifies them according to the similarity of their research content (the dendrogram on the left). Before 2020, the research in this field was mostly confined to virology and epidemiology, corresponding to journals with higher popularity, such as the Journal of Clinical Virology, Epidemiology and Infection, Pediatric Infectious Disease Journal, etc. As time progressed, the research scope of this field expanded to broader and more diverse research fields, such as microbiology and public health, with journals such as the International Journal of Environmental Research and Public Health, Frontiers in Microbiology, BMC Public Health, etc.
The visualization results of the cooperative relationships among these journals are shown in Figure 6A. The yellow cluster includes journals focusing on research in the fields of public health, the environment, and health sciences (e.g., Plos One, Scientific Reports). The red cluster contains journals that focus mainly on infectious disease research (Journal of Infection, Lancet Infectious Diseases, etc.). Journals conducting in-depth basic research on virology are classified into the blue cluster (Archives of Virology, Virology, etc.). The green cluster, which is based on virology, further expands to include viral immunology, antiviral research, and molecular virology (Journal of Virological Methods, Viral Immunology, etc.). The last purple cluster is oriented toward vaccine development (Vaccine, Expert Review of Vaccines, etc.). As shown in Figure 6B, journals with relatively red dots, such as Frontiers in Microbiology and BMC Public Health, have been actively researched in this field in recent years. The co-citation relationships among journals are more intuitively presented in Figure 6C. These journals are briefly divided into five categories according to the similarity of research content reflected by the co-citation relationships between them. The red cluster includes journals focusing on basic virology research (Journal of Virology, Journal of General Virology, etc.). The green cluster covers most journals related to infectious diseases and public health (Epidemiology and Infection, BMC Infectious Diseases, etc.). Journals focusing on pediatric infectious diseases are classified into the blue cluster (Pediatric Infectious Disease Journal, Journal of Pediatrics, etc.). The yellow cluster involves mainly the fields of virology and infectious diseases (Virology Journal, Journal of Medical Virology, etc.). The last relatively small purple cluster includes journals focusing on the prevention and treatment of microbial infections (Vaccine, Microbes and Infection, etc.).
Figure 6D is a double-mapping overlay graph of journals, which can more intuitively present the citation relationships between various journals and the changes in research focus. The citation relationship is indicated by the citing journals on the left, with lines in the middle pointing to the cited journals on the right. The thicker yellow lines in the figure indicate that journals in the Molecular, Biology, Immunology directions mainly apply to the literature from journals in the Molecular, Biology, Genetics directions. Journals in the Medicine, Medical, and Clinical directions mostly cite literature from journals in the Molecular, Biology, Genetics and Health, Nursing, and Medicine directions.
## 3.6 Keyword analysis
As a guide to the research direction or a condensation of the research content of an article, keywords can usually highly summarize the main idea of the article. Therefore, keyword analysis is an important part of bibliometric analysis, which is highly important for understanding the current situation of a research field and predicting its development trend (27). The top 20 keywords in terms of occurrence frequency and total link strength are shown in Table 5. Among them, hfmd and enterovirus 71 are the core terms in this field, with occurrence frequencies of 698 and 575, The trend in the frequency of keywords over time from 20010 to 2024 is shown in Supplementary Figure 3A. The keywords "outbreak, " "disease, " "malaysia, " and other keywords emerged earlier and maintained their popularity for a long period of time. "hand, " "children, " "mouth-disease" and others were keywords that once received high attention in this field, whereas "associations, " "pollution" and "innate" have been popular keywords in recent years. In Supplementary Figure 3B, the popularity and development trends of the top 11 keyword clusters are compared horizontally and vertically in combination with the time axis. Each horizontal line represents a keyword group, with #0 being the largest cluster, and the size of the node on the horizontal axis is proportional to the co-citation frequency. For example, the earliest keyword in the largest cluster #0, "protein, " was "myocarditis, " and the "sequence" in #1, "aseptic meningitis, " and the "hand" in #2, "pulmonary edema, " also emerged relatively early. In contrast, #9 "pathological analysis" emerged relatively late, and "Chinese traditional medical" is a term that has attracted attention only recently. Notably, most of the keywords that emerged early in #2, "pulmonary edema, " had a relatively high co-citation frequency, indicating that this cluster might be a key research direction in the early stage of research on children's hand, foot and mouth disease.
The co-occurrence relationships among keywords related to pediatric HFMD are shown in Figures 7A,B. By analyzing these co-occurrence relationships, we can better understand the research directions and hot trends in this field. In the purple cluster of Figure 7A, "hfmd" with the highest co-citation count is the core keyword. In addition, there are terms such as "infectious disease, " "temperature", "relative humidity, " "meteorological factor, " and "air pollution, " which focus on the impact of meteorological factors on infectious diseases. Second, the keywords related to the pathogenic mechanism of enterovirus 71 are classified into the yellow cluster, which includes "enterovirus 71, " "viral replication, " "receptor, " "scarb2, " etc. The blue cluster focuses on children as the main research direction, paying attention to children's neurological diseases, and encompasses terms such as "children, " "encephalitis, " "aseptic meningitis, " "brainstem encephalitis, " etc. The red cluster includes keywords related to basic virology and research on multiple viruses, such as "enterovirus, " "coxsackievirus, " "phylogenic analysis, " "parechovirus." The green cluster, interspersed among multiple clusters, mainly consists of terms for research on virus-related infectious diseases, such as "acute flaccid myelitis, " "acute flaccid paralysis, " "picornavirus, " etc. The cyan cluster includes "coxsackievirus a10, " "coxsackievirus a6, " "human enterovirus, " etc., and tends to research human enteroviruses, seroepidemiology, etc. The remaining smaller pink and orange clusters focus on vaccine research and development, and the brown cluster emphasizes epidemiological research. As shown in Figure 7B, keywords such as "infectious disease, " "air pollution, " and "acute flaccid myelitis" have received increased attention in recent years, which may be highly important for exploring the occurrence and development mechanisms of pediatric HFMD, intervention measures, and new research methods.
The heatmap in Figure 8A shows a more in-depth and detailed analysis of the evolutionary trends of the abovementioned research hotspots. Before 2020, research directions such as "scarb2, " "picornavirus, " and "immunogenicity" received much attention, but in recent years, their research popularity has declined. Moreover, terms such as "meningitis, " "mouthdisease", and "autophagy" have gradually emerged. In the past 2 years, "phylogenetic tree, " "covid-19, " and "infectious disease" have become popular keywords. Figure 8B shows a heatmap analysis of keywords in the research field of pediatric HFMD. According to their correlation and popularity, they are divided into six main clusters. From top to bottom, the first cluster includes terms such as "coxsackievirus a16, " "poliovirus, " "picornavirus, " etc., which revolve around basic virology research.
The cluster below is related to the research and development of enterovirus vaccines, which include "vaccine, " "enterovirus, " and "coxsackievirus." The third cluster covers keywords such as "epidemiology, " "enterovirus 71, " "molecular epidemiology, " and "seroprevalence, " which focus on virology and epidemiology. Keywords concentrated in the fields of virology, infectious diseases, and public health, such as "viral replication, " "infectious diseases, " "basic reproduction number, " "public health, " and "relative humidity, " are classified into the fourth and fifth clusters. The last cluster mostly contains keywords related to medical research, such as "mouse model, " "temperature, " "surveillance, " and "mortality." Figure 9 shows the top 25 keywords with the strongest citation bursts. It is easy to find that several keywords that started to burst in 2000 have relatively long burst periods. Among them, the burst period of the "central nervous system" extends from 2000 to 2013, which is the keyword with the longest burst period. Moreover, its burst strength is relatively high, reaching 16.46. Among all the keywords, the one with the highest burst strength is "taiwan, " which is as high as 37.48. The high level of attention given to this term is likely related to the high incidence of pediatric HFMD in Taiwan Province of China. Of particular note are the keywords at the bottom of the figure whose burst periods continue to the present, including "childhood hand" (burst strength 12.52), "enterovirus a71" (burst strength 15.17), "eÿcacy" (burst strength 11.72), "enterovirus 71 vaccine" (burst strength 6.32), and "replication" (burst strength 6.09). These terms reflect the current main research directions in this field to some extent.
## 3.7 Highly cited reference analysis
To some extent, the citation count of an article can indirectly reflect its quality and visually present the degree of attention and influence it receives within its field. Conducting an indepth analysis of highly cited articles helps us eÿciently and comprehensively grasp the research hotspots in the corresponding field. The basic information of the top fifteen articles in terms of citation count is shown in Table 6. The most highly regarded article is "Virology, epidemiology, pathogenesis, and control of enterovirus 71, " published by Solomon, T et al. in in Lancet Infectious Diseases. This literature reviews the virological characteristics, epidemiology, pathogenesis, and prevention and control measures of enterovirus 71. EV71 causes mainly HFMD and neurological complications in children. The Asia-Pacific region is an area with a high incidence. EV71 has diverse genetic subtypes and has evolved rapidly. Currently, prevention and control mainly rely on public health interventions, and vaccine research and development are underway (28).
Figure 10A Figure 10C shows a visual representation of the potential correlations among these highly cited studies. We classified them into 16 dierent clusters according to their correlations. The largest cluster is enterovirus 71 #0, indicating that papers related to it have the highest number of citations. Next are #1 seroepidemiology and #2 meteorological factors, suggesting that seroepidemiology The diagram illustrates the 25 primary keywords characterized by pronounced bursts of citations, denoted by red spikes on the timeline. These bursts signify sudden surges in citation counts, signaling pivotal moments of emerging crucial questions or solutions within the field.
Supplementary Figure 4A presents the relationship between self-citations within the field and the total citation count of highly cited studies. For the paper "Risk factors for enterovirus 71 infection and associated HFMD/herpangina in children during an epidemic in Taiwan" published by Chang, LY et al. in in Pediatrics (35), its citations are mainly concentrated within the research field of pediatric HFMD. In contrast, studies with a lower LC/GC ratio have attracted widespread attention in the entire academic community. This means that the content of these studies has important reference value for multiple research directions. For example, "Human P-selectin glycoprotein ligand-1 is a functional receptor for enterovirus 71, " published by Nishimura, Y et al. in in Nature Medicine (36), and the research findings of Solomon, T et al. mentioned above (28), which ranks first in the number of citations.
Supplementary Figure 4B shows the citation burst situation. Among them, the article "Hand, foot and mouth disease in China, 2008-12: an epidemiological study" published by Xing, WJ et al. in in Lancet Infectious Disease is particularly notable (37). Although its burst period was short (from 2016 to 2019), its burst strength reached as high as 68.52, which fully demonstrates that its research content has attracted much attention in the academic community in a short period. In addition, the research of Ho Mt, Lum LCS, Huang CC and others had an early start of the burst period (38)(39)(40), playing a crucial role in promoting the development of early research in this field. Notably, for the article "The History of Enterovirus A71 Outbreaks and Molecular Epidemiology in the Asia-Pacific Region" published by Puenpa, J. et al. in in the Journal of Biomedical Science (41), its burst period continues to the present. This means that the research content and direction of this literature are likely to be the current focus of attention in this field.
## 4 Discussion
## 4.1 General distribution and global collaboration
This study employed bibliometric methods to conduct a systematic and comprehensive analysis of literature in the field of pediatric HFMD research from 2000 to early 2025. Data collection was completed on February 1, 2025. A total of 2,034 2). These advancements include, but are not limited to: molecular epidemiological studies of pathogens (42); vaccine development and deployment (42)(43)(44)(45); advances in rapid diagnostic technologies (46); exploration of antiviral therapies (47,48); disease surveillance and public health interventions (49)(50)(51); and investigations into neurological complications and host-pathogen interactions (52)(53)(54). It is worth noting that the current body of research predominantly consists of descriptive or cross-sectional studies, covering areas such as epidemiological surveys, etiological analyses, clinical characterization, and vaccine development. A key limitation lies in the relative scarcity of longitudinal cohort studies. For instance, while various vaccines have demonstrated short-term eectiveness in reducing incidence rates, their long-term protective eÿcacy remains inadequately validated and requires further investigation across dierent age groups and immune statuses. Moreover, research eorts have been largely concentrated in East Asia, particularly China and Southeast Asia. There is a pressing need to expand studies to other regions with distinct circulating viral strains, such as areas dominated by Coxsackievirus A, to inform comprehensive global prevention and control strategies. Additionally, more rigorous clinical trial designs are essential. Future trials should be multicenter and large-scale, incorporating participants of diverse ages, socioeconomic backgrounds, and geographic locations to validate the generalizability and eectiveness of new interventions.
China dominates the research landscape in this field, contributing 71.63% of global paper output. The core group of authors and leading research institutions are also predominantly based in China (Tables 2,3). This reveals the current uneven distribution of global research investment. Furthermore, analysis of global academic exchanges similarly exposes a significantly unbalanced pattern in scientific collaboration. Existing international cooperation networks are limited and primarily involve a handful of scientifically advanced countries, such as China, the United States, the United Kingdom, and Australia (Figures 3A,B). From the perspective of disciplinary development, establishing and strengthening extensive international academic exchange mechanisms is a prerequisite for advancing the field. In building these collaborative pathways, dierent economies can leverage their respective strengths for mutual benefit. As a key leader in South-South cooperation, China can deepen collaboration with neighboring developing countries through technology sharing (e.g., rapid HFMD diagnostic kit development), joint talent training programs, and collaborative research on regional transmission patterns. Developed countries like the United States and the United Kingdom can contribute on the resource supply side by providing specialized research funding, donating critical equipment, and sharing technical expertise such as epidemic surveillance models. Furthermore, leveraging transnational drug registration coordination mechanisms and technology transfer agreements can accelerate the global dissemination and application of high-quality research outcomes (55).
Another critical concern is the marginalization of low-and middle-income countries (LMICs) with high HFMD disease burdens but low research output, such as Pakistan and Indonesia. Challenges such as insuÿcient research funding, underdeveloped public health systems, shortages of research equipment and trained personnel, weak infrastructure (including transportation and communications), and inadequate accuracy and timeliness of surveillance data hinder their integration into core collaborative networks. In this context, international support from diverse stakeholders is crucial to address these disparities. Specifically: At the international organization level, the World Health Organization (WHO) can support LMICs through transnational capacity-building initiatives, assisting in the establishment of standardized viral specimen banks and genomic databases. Laboratory quality certification programs under frameworks like the Global Health Security Agenda (GHSA) can enhance laboratory testing capabilities and data reliability in LMICs (56). Regionally, cooperation frameworks such as the Association of Southeast Asian Nations (ASEAN) public health collaboration can foster synergy by integrating regional resources, enabling shared laboratory facilities, joint human resource training, and pooled funding mechanisms. Furthermore, active global researcher participation in initiatives like the Open Science Framework (OSF) and the Global Health Data Exchange (GHDx) should be encouraged (57). By adhering to standards for data security and intellectual property protection, these platforms can significantly enhance the accessibility and usability of relevant data.
## 4.2 Development, hotspots, and frontiers
Analyzing keywords in the research fields of pediatric HFMD can help us better grasp the frontiers and hotspots of research in this area. The main keywords used in current research include "hfmd, enterovirus 71, " "enterovirus, " "coxsackievirus a16, " "children, " "vaccine, " "epidemiology, " etc. These keywords highlight popular topics in the research fields of pediatric HFMD. On the basis of the cluster and heatmap analysis of keywords (Figures 7,8) and the cluster analysis of highly cited literature (Figure 10C), research related to pediatric HFMD has focused on four main directions: research on pathogenic mechanisms, epidemiological research, novel therapeutic discoveries and vaccine development.
## 4.2.1 Pathogenic mechanisms
In 1969, the EV71 virus was first isolated from fecal specimens of infants with central nervous system diseases in California, USA. Through cell culture and serological testing, researchers determined that while its morphology resembled known enteroviruses, its biological characteristics were distinct. This led to its oÿcial classification as a new enterovirus by the International Committee on Taxonomy of Viruses in 1979 (58). This initial research phase was predominantly dedicated to pathogen identification. Viruses such as CVA16 and EV71-both members of the Picornaviridae family-were recognized early on. However, EV71 rapidly became the primary research focus due to its strong propensity to cause severe neurological complications, such as brainstem encephalitis. Epidemiological studies established the generally self-limiting nature of HFMD, which typically resolves without sequelae. Nonetheless, recurrent outbreaks of EV71 in the Western Pacific Region prompted a swift research shift toward severe cases. This reorientation inadvertently reduced the representativeness of other strains like CVA16 in research agendas, despite CVA16 being identified early as a common causative agent (59,60). In recent years, studies have continued to aÿrm the polyviral etiology of HFMD, emphasizing that the disease is caused by multiple enteroviruses, including CVA6, CVA16, CVA10, and EV71. However, research investment into their respective pathogenic mechanisms remains highly uneven. For example, the introduction of an EV71 vaccine in China in 2016 further intensified focus on this particular strain. In contrast, the molecular mechanisms of other strains like CVA6 and CVA10-whose contribution to major HFMD outbreaks has been increasingly significant-have been comparatively underexplored (61)(62)(63). This imbalance can be partially attributed to the inertia of early research priorities, which has perpetuated the underrepresentation of non-EV71 strains in mechanistic studies.
As evidence of EV71's role in severe HFMD accumulated, research progressed into an animal model phase aimed at validating infection mechanisms. Early animal models, primarily using mice, were employed to understand EV71's neuroinvasive potential, including how it invades the central nervous system via the neuromuscular junction and leads to fatal neurological complications. These models were initially developed largely for EV71, driven by its association with severe disease phenotypes such as encephalitis and pulmonary edema. In comparison, research models for other strains like CVA16 and CVA6 were less developed and often faced limitations in fully recapitulating the diversity of human clinical manifestations (64,65). This disparity further amplified the research emphasis on EV71 and overlooked the emerging importance of CVA6 and CVA10 in outbreakswhere CVA6, for instance, has frequently been identified as a predominant pathogen. Recent animal model research has attempted to correct this imbalance by expanding to include multiple strains and refining model systems. For instance, while mouse models have been used to assess long-term sequelae of EV71 infection, they have also highlighted the significant roles CVA16 and CVA6 play in outbreaks-roles for which corresponding animal experiments to elucidate their specific mechanisms are still lacking. Some recent eorts have aimed to develop more human-relevant models to reduce reliance on traditional animal studies, but these initiatives remain predominantly centered on EV71. A case in point is a study utilizing a mouse model to test an EV71-targeting therapeutic peptide, which overlooked similar mechanistic explorations for other strains, thereby underscoring the persistent underrepresentation of CVA10 and CVA6 in experimental research (65,66).
The mainstream research direction subsequently shifted toward molecular and genomic exploration, focusing intently on molecular mechanisms and genetic variation. Early molecular investigations concentrated on EV71's characteristics as a singlestranded RNA virus, including its high mutation rate attributable to an error-prone RNA polymerase-which generates quasispecies and haplotype diversity-and how these mutations enhance viral virulence, particularly in neuroinvasion. This depth of investigation was especially pronounced for EV71, partly because circulating variants like the C4 subgenogroup in the Western Pacific Region became priority vaccine targets. Conversely, the molecular mechanisms of other strains, such as capsid loop structures in CVA16, received comparatively less attention (67)(68)(69). Recent molecular and genomic studies have substantially enriched our mechanistic understanding. For EV71, research has delved deeply into specific mechanisms, such as the dual role of the tribbles pseudokinase 3 (TRIB3) pseudokinase in promoting infection, antagonism of interferon signaling pathways, and how capsid protein mutations influence viral entry, alongside advancing antiviral target development, including the monoclonal antibody E1 (70-72). However, similar mechanistic studies for other strains like CVA6 and CVA10 remain limited. Despite CVA6 and CVA10 being key pathogens in HFMD outbreaks-particularly in recent epidemics in China-research on their molecular mechanisms, such as the impact of genetic recombination on pathogenicity, is notably underrepresented. For example, while a chimeric virus study attempted to compare the capsid loops of EV71 and CVA16, similar eorts have not been extended to CVA6 and CVA10, thereby constraining the development of broad-spectrum therapies eective against multiple co-circulating strains (69,73,74).
In summary, the historical evolution of HFMD pathogen research demonstrates a clear progression from pathogen identification, through animal model validation, to in-depth molecular exploration. However, the field has been predominantly shaped by an intensive focus on EV71, leading to significant imbalances in research scope and resource allocation. Although recent studies have begun to acknowledge the important roles of CVA6, CVA16, and CVA10 in outbreaks-particularly in the post-vaccine era where the prevalence of these non-EV71 strains has increased-their representation in mechanistic investigations remains inadequate. For instance, while molecular target identification and vaccine development for EV71 are well-established (75,76), research on genetic recombination and pathogenic mechanisms of CVA6 and related strains is relatively scarce (63,77). Future research must strive for a more balanced and comprehensive exploration of multiple enterovirus strains to eectively address the complex and dynamically evolving epidemiological landscape of HFMD.
## 4.2.2 Epidemiological studies
Asia is one of the regions with the highest incidence of HFMD, particularly in East and Southeast Asian countries, where the primary pathogenic strains are EV71 and CVA16. In Southeast Asia, multiple nationwide surveillance studies indicate that countries such as China, Vietnam, and India experience seasonal outbreaks (mostly occurring from late spring to early summer) nearly every year. Preschool children, especially those under 3 years old, constitute the most aected population (78)(79)(80). In China, the epidemiological characteristics of HFMD have undergone significant changes since the introduction of the EV71 vaccine in 2016. Both the incidence and severity rates associated with EV71 have markedly decreased. Meanwhile, the prevalence of strains such as CVA6, CVA10, and CVA16 has shown an upward trend across dierent regions (2,(81)(82)(83). In Europe, outbreaks of hand, foot, and mouth disease are relatively uncommon and primarily occur among young children. Compared to Asia, severe cases and mortality rates are lower. This may be related to dierences in the predominant viral strains. Reports indicate that CVA6, CVA10, and CVA16 are the primary causative strains of hand, foot, and mouth disease in Europe (84)(85)(86)(87). Reports of severe outbreaks dominated by EV71 are relatively scarce. The situation in the Americas and Oceania mirrors that in Europe, with relatively infrequent HFMD epidemics. However, outbreaks caused by CVA6 appear more prevalent (88)(89)(90)(91). A few severe outbreaks caused by EV71 have also been reported (92). Relevant reports from Africa are scarce. A study in Tunisia reported a Tunisian CVA24 strain with a high degree of sequence dierence in the VP1 coding region compared with other CVA24 strains. This is the first reported CVA24 strain that causes aseptic meningitis (93).
Regarding risk factors influencing the spread of HFMD, meteorological factors, air pollution, and behavioral factors have been extensively discussed by scholars. Among meteorological factors, relative humidity and temperature play a dominant role. Both relatively low and high humidity levels appear to be associated with increased HFMD incidence rates. A multicity study in mainland China revealed that the relationship between relative humidity and HFMD incidence approximates a U-shaped curve. The relative risk is the lowest when the relative humidity is 45%, and the highest when it is 20% or exceeds 85%. Moreover, there is spatial heterogeneity in this relationship (94). A study in the Sichuan Basin revealed that the relationship between relative humidity and the incidence of HFMD is J shaped. When the relative humidity exceeds 70%, the risk increases with increasing humidity, and the infection burden aected by high humidity is greater in the southern part of the basin (95). On the other hand, both low and high temperatures increase the risk of hand, foot, and mouth disease. The cumulative eect of high temperatures peaks at a lag of 0-10 days, while the cumulative eect of low temperatures peaks at a lag of 0-3 days (96). In Wuhan, there is a non-linear "M"-shaped relationship between temperature and the incidence of HFMD, with two peaks (4). In Shandong, the analysis of data from 2015 to 2019 via the multiscale geographically and temporally weighted regression (MGTWR) model revealed that temperature and humidity were positively correlated with the incidence of HFMD in spring and summer (97). Pearson, Dharshani et al., on the basis of relevant data from California, noted that in both the cold and warm seasons, an increase in temperature is associated with an increased risk of emergency department visits for HFMD. In coastal areas, the association is stronger in the cold season, possibly because mild and humid winter conditions are more conducive to the survival of pathogens (98).Additionally, factors such as daily sunshine duration, precipitation, and wind speed may also be associated with HFMD incidence (99).
In terms of air pollution, a study in Fuyang revealed that temperature and PM2.5 are the main risk factors for HFMD, and there is a synergistic eect between PM and meteorological factors. For example, the relative risk (RR) values related to the association between PM2.5 and HFMD vary significantly among dierent temperature groups. Children under 5 years of age, especially infants aged zero to 1 year, are more sensitive to environmental variables (100). An earlier study revealed that short-term exposure to PM2.5 and its components (especially black carbon, sulfate, ammonium, nitrate, and soil dust) is significantly associated with prolonged hospital stays in HFMD patients (101). A study in Zhejiang Province analyzed county-level data from 2013 to 2021 via a Bayesian spatiotemporal model. An increase in the concentrations of PM10 and NO 2 is significantly associated with an increased risk of HFMD, whereas O 3 , SO 2 , and CO are negatively correlated. Meteorological factors significantly aect the relationship between air pollutants and the incidence of HFMD, and the association is more significant under extreme weather conditions (102).
The primary mode of HFMD transmission is the fecaloral route. Additional transmission pathways include respiratory spread-through inhalation of droplets from coughing or sneezing, or contact with airborne particles contaminated by patient secretions-and direct contact transmission, which involves exposure to patients' nasal or oral secretions, skin blister fluid, feces, or contact with contaminated objects such as toys or clothing. Regarding behavioral factors influencing pediatric HFMD spread, Kindergarten size and class structure are significant behavioral transmission factors. Studies indicate that reducing class size substantially lowers HFMD transmission risk, with incidence increasing by approximately 11% for every 10-person increase in class size. Large-scale kindergartens (> 300 children) carry a 40% higher transmission risk than small-scale ones (< 150 children), directly linked to the frequency of close contact among children. Inter-class interactions (e.g., shared activity rooms) also accelerate cross-class transmission (103). Furthermore, poor personal and public hygiene practices-such as inadequate hand hygiene and insuÿcient disinfection of tableware-can also substantially increase the risk of infection (104). Vaccination represents a key intervention for HFMD prevention, particularly in high-risk regions. The administration of EV71 vaccines has been demonstrated to eectively reduce infection rates. However, vaccine dissemination remains influenced by regional development disparities and variations in public health education (105).
## 4.2.3 Novel therapeutic discoveries
The early symptoms of HFMD typically include fever, skin rash-commonly appearing on the hands, feet, and oral cavityas well as oral herpes or ulcers. These manifestations are generally self-limiting and resolve spontaneously in children (2,106). However, in severe cases, HFMD can lead to serious neurological complications and even mortality (107,108). Current clinical management relies predominantly on supportive care-aimed at alleviating symptoms-due to the absence of specific antiviral therapies. Available vaccines, such as inactivated EV71 vaccines, oer limited protection, primarily targeting specific strains (61,109,110) and failing to cover emerging or atypical viral variants (60,62). Consequently, there is a pressing need to develop novel therapeutic strategies.
Mechanism-based treatments targeting pathogen infection represent a prominent research direction, encompassing viral entry inhibitors and immunomodulatory approaches. In the realm of viral entry inhibition, certain molecules can block virus attachment to host cells. For instance, tannic acid derivatives such as chebulagic acid and punicalagin have been identified as potent broad-spectrum entry inhibitors eective against multiple viruses-including HFMD-associated pathogens-that utilize cell surface glycosaminoglycans (111). Furthermore, the mechanism of EV71 entry into human oral cells has been shown to be independent of classical pathways such as clathrin or caveolin, providing a foundation for designing specific inhibitors (112). Monoclonal antibodies targeting CVA16, including 9B5 and 8C4, have also been characterized as eective entry inhibitors capable of neutralizing the virus and reducing infection risk (113). Regarding immunomodulation, strategies aimed at regulating host immune responses to control infection severity are increasingly important. For example, toll-like receptor 7 (TLR7) recognizes viral RNA and plays a role in EV71 infection (114), and specific TLR polymorphisms are associated with HFMD severity, suggesting potential immunomodulatory targets (115). The interferon (IFN) signaling pathway is crucial in controlling EV71 and CVA16 infections; interferon-stimulated genes such as Cholesterol 25hydroxylase (CH25H) can eectively block replication of these viruses (70). Other mechanisms include the role of Ragulator proteins in mediating EV71-induced apoptosis and pyroptosis, and identifying such molecules provides a basis for developing immunomodulatory therapies (116). Additionally, macrophagemediated immune dysregulation may contribute to severe HFMD, supporting intervention through modulation of inflammatory responses (117).
Emerging therapeutic approaches are also focusing on novel molecular targets and alternative strategies, including RNAbased interventions and host-directed antivirals. In RNA-targeted therapy, methods such as siRNA screening have been employed to explore EV71 entry and replication mechanisms, identifying specific genes involved in membrane traÿcking as potential targets (118). RNA methylation (m6A) modifications have been found to regulate host responses to EV71, oering intervention opportunities by influencing viral replication and immune pathways (119). Moreover, mRNA vaccines are under development as a novel platform targeting non-enveloped viruses like EV-A71 (120). In the domain of alternative therapies and molecular targets, various host-directed molecules have shown promise as antiviral agents. For example, a compound named 14S-(2'-chloro-4'-nitrophenoxy)-8R/S, 17-epoxy andrographolide has demonstrated eÿcacy in inhibiting EV-A71 infection (121). Fucosylated chondroitin sulfates extracted from sea cucumbers also exhibit antiviral activity (122). Other alternative pathways, such as modulation of host genes via inflammasomes or prostaglandin E2 regulation, oer new therapeutic avenues (123). Although these studies primarily target other viruses, their underlying mechanisms may be applicable to HFMD. However, most of these findings remain at the research stage and require further validation and clinical translation.
## 4.2.4 Vaccine development
The development of vaccines for HFMD is an ongoing process that must contend with a complex and evolving pathogen landscape. To better control enterovirus diseases like HFMD, the Asia-Pacific Network for Enterovirus Surveillance (APNES) was established in 2017. Its mission is to assess the burden of enterovirus diseases, understand viral evolution, and promote the development of corresponding vaccines by coordinating laboratory diagnostics and data collection (124). APNES operates as a practical "surveillance-to-vaccine" model, emphasizing that an eective vaccination program relies not only on the vaccine itself but also on a robust and continuous epidemiological and virological surveillance system. This framework is crucial for controlling diseases like HFMD, which are caused by multiple, constantly evolving viruses.
In the initial phase of vaccine development, eorts were predominantly focused on creating monovalent vaccines targeting EV71, due to its strong association with severe neurological complications and fatalities (60,62,107). A key milestone in this phase was the approval and launch of three inactivated EV71 vaccines in China in 2016. Clinical trials confirmed these vaccines were highly eective, demonstrating a vaccine eÿcacy (VE) exceeding 90% against EV71-associated HFMD and a favorable safety profile (61,125). Subsequent real-world evidence further validated their public health value, showing that a two-dose regimen significantly reduced EV71-associated hospitalizations and mortality in pediatric populations (125,126).
However, the widespread administration of EV71 vaccines led to a significant shift in the HFMD epidemiological landscape. Non-EV71 enteroviruses, such as CVA6, CVA10, and CVA16, have increasingly become the dominant pathogens in outbreaks (62,77,127). This shift exposed a fundamental limitation of monovalent vaccines: their inability to provide cross-protection against multiple pathogenic serotypes. Consequently, the focus of vaccine R&D has pivoted toward developing multivalent formulations aimed at achieving broader protection from a single vaccine. Currently, bivalent, trivalent, and even quadrivalent vaccine candidates targeting combinations of EV71, CVA16, CVA10, and CVA6 are under active investigation (128,129). For instance, a trivalent inactivated vaccine targeting EV71, CVA16, and CVA10 has demonstrated broad passive protection against multiple viral challenges in mouse models (60). Furthermore, novel platforms like virus-like particles (VLPs), which mimic the native virus structure without containing genetic material, are considered ideal candidates for constructing these multivalent vaccines (130,131). The goal is to provide cross-serotype protection via a single preparation, enabling more comprehensive control of HFMD (110,131).
Despite this progress, several challenges persist in current vaccine development. First, strain coverage remains limited. Most existing multivalent vaccine candidates are still in experimental stages, and their eÿcacy in humans requires further validation and clinical translation (61,109,110). Second, continuous viral evolution poses a long-term threat. The high variability of enteroviruses, prone to genetic recombination and mutation, can lead to the emergence of novel variants capable of evading existing immunity. For example, CVA6, an emerging pathogen, is undergoing rapid evolution, which could compromise vaccine eectiveness and alter outbreak patterns (109). Concurrently, promising candidates like VLPs face stability challenges, such as a potential rapid decline in immunogenicity at high concentrations, adding complexity to multivalent design (130). These collective challenges underscore the urgent need for multivalent and adaptable vaccine platforms. On one hand, developing multivalent vaccines capable of covering currently dominant and emerging strains is considered a key strategy for eective HFMD management (110,126,129,132). On the other hand, it is imperative to leverage highly adaptable technological platforms-such as VLPs and mRNA vaccines-to enable rapid responses to viral evolution (120,130,131). Future vaccine design must therefore incorporate more advanced approaches, such as optimizing VLP stability or exploring rapidly adaptable mRNA platforms, to enhance both the breadth and durability of vaccine-induced protection.
## 4.3 Strengths and limitations
This study employs bibliometric methods to systematically review research on pediatric HFMD from 2000 to 2025, based on data from the WOSCC and PubMed. Using analytical tools such as CiteSpace, VOSviewer, and R-bibliometrix, an in-depth analysis of relevant literature was conducted across multiple dimensions, including publication volume, citation frequency, geographical distribution, contributions by authors and institutions, journal preferences, keywords, and cited references. The aim is to comprehensively present the developmental trends and research hotspots in this field. Compared to a bibliometric study on HFMD published in 2024 (133), this research covers a longer time span and integrates two major databases-WOSCC and PubMedthereby enhancing the comprehensiveness and timeliness of the data. Through more refined visual and analytical approaches, this study identifies current research priorities in pediatric HFMD, examines the distribution of scholarly eorts, and highlights underexplored areas. It also systematically reveals China's dominant role in global research and its patterns of international collaboration, while addressing issues such as the marginalization of low-income, high-burden countries within research networks. Furthermore, by synthesizing a wide range of recent studies, this paper provides a detailed exploration of four key research directions: pathogenic mechanisms, epidemiology, novel therapeutic strategies, and vaccine development. The findings oer more comprehensive and forward-looking bibliometric evidence to inform global strategies for the prevention and control of hand, foot, and mouth disease.
However, several limitations inherent to the bibliometric approach should be considered. Firstly, the restriction to Englishlanguage publications introduces potential language bias, as significant research published in other languages may have been overlooked. Secondly, the reliance solely on the WOSCC and PubMed, despite their prominence, means that studies indexed in other regional or specialized databases were excluded, limiting the comprehensiveness of the dataset. Furthermore, the temporal scope was constrained to literature published from 2000 onward due to database accessibility, thus omitting potentially influential earlier works. The cuto date for data collection (February 1, 2025) also results in incomplete coverage of publications from the full year. These common bibliometric constraints-language, database coverage, and temporal boundaries-may aect the generalizability of the findings. Future research could benefit from incorporating multilingual literature and expanding database sources to improve the representativeness and depth of analysis.
## 5 Conclusion
This bibliometric analysis comprehensively presents the development trends and research hotspots in the field of pediatric hand-foot-and-mouth disease by deeply examining 2,034 relevant papers published since the 21 st century (up to February 2025). It highlights China's leading contributions in this research domain while reflecting the global focus on its pathogenesis, epidemiology, novel therapeutic discoveries, and vaccine development. However, critical research gaps persist: excessive focus on EV71 at the expense of other highly prevalent serotypes like CVA6 and CVA10; insuÿcient international collaboration-particularly with low-income countries bearing high disease burdens; and inadequate coverage of multivalent vaccines. Future research should prioritize establishing equitable global partnerships, deepening comprehensive studies on multiple enterovirus serotypes, and accelerating the development of broadspectrum vaccines and targeted antiviral therapies to achieve eective global prevention and control of HFMD.
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# BMC Infectious Diseases
Faseeha Noordeen
## Abstract
Background Human coronaviruses (hCoVs) are frequently detected in nasopharyngeal samples from patients with acute respiratory tract infections (ARTIs). Interest in hCoVs increased following the severe acute respiratory syndrome coronavirus (SARS-CoV) outbreak in 2002. However, epidemiological data on seasonal coronaviruses (sCoVs) remain incomplete, particularly in settings where these viruses are not routinely tested in standard respiratory diagnostic panels. Limited surveillance of sCoVs may hinder early detection of emerging CoVs and pandemic preparedness.
MethodsIn the current study, a total of 1062 respiratory samples from patients with ARTIs were tested to detect 22 respiratory pathogens including sCoVs using a real time reverse transcription multiplex polymerase chain reaction (real time RT-multiplex PCR) from January 2020 to October 2022.
ResultsRespiratory pathogens were identified in 51.03% patients with the detection rate of 7% for sCoVs. Of the sCoV positive patients, 36 were hCoV-NL63/HKU1 infections; 29 were hCoV-229E infections and 9 were hCoV-OC43 infections. Fever, cough and sore throat were the most common symptoms detected in all three sCoV infections. hCoV-229E and hCoV-NL63/HKU1 were not detected in 2020. A major peak of hCoV-229E infection was noted in April 2021 with detection from January 2021 to July 2022. Major peaks of hCoV-NL63/HKU1 infections were noted in April 2021 and 2022. The least prevalent sCoV in the study was hCoV-OC43, which was detected in January to March in 2020 and the virus was not detected in 2021 and two hCoV-OC43 infections were detected in 2022. Conclusion Based on the present study findings, prevalence of sCoV infections among patients with ARTI was 6.96% with hCoV-NL63/HKU1 predominance. sCoVs were detected year-round, with peak incidence noted in January and February of 2021/2022. sCoVs distribution fluctuated along with SARS-CoV-2 infections during the pandemic.
Collection and processing of samplesNucleic acid extraction from the samples was done using QIA Symphony nucleic acid extraction system (Qiagen, Implementing a national sCoV surveillance system could enhance early detection and monitoring of sCoVs, aiding the tracking of emerging hCoVs.
Prevalence, clinical characteristics and pattern of distribution of seasonal corona virus associated acute respiratory tract infections among adults and children in the Central Province of Sri Lanka from January 2020 to October 2022 Shiyamalee Arunasalam 1 , Rohitha Muthugala 2 and Faseeha Noordeen 1*
## Background
Coronaviruses (CoVs) are members of the family Coronaviridae and subfamily Coronavirinae and the order Nidovirales [1]. CoVs cause respiratory and intestinal infections in animals and humans [2]. Based on the genomic structures and the phylogenetic relationship, the subfamily Coronavirinae has four genera including alpha (α), beta (β), gamma (γ) and delta (δ) CoVs. α-CoV and β-CoV infect only mammals while γ-CoV and δ-CoV infect birds and mammals [3]. CoVs are the largest known RNA viruses, with a single-stranded, positive-sense RNA genome ranging from 26 to 32 kb [3].
Human coronavirus (hCoV) belongs to α and β genera of the subfamily Coronavirinae. hCoV was initially discovered in 1960s as the agent of common cold and detected in nasopharyngeal samples from patients with respiratory tract infections [4]. The 2002 severe acute respiratory syndrome coronavirus (SARS-CoV) outbreak heightened research interest in CoVs, leading to the identification of new subtypes such as hCoV-NL63 and hCoV-HKU1 [5]. So far, seven types of hCoVs have been identified: hCoV-229E, hCoV-NL63, hCoV-OC43, hCoV-HKU1, SARS-CoV, Middle East respiratory syndrome CoV (MERS-CoV) and SARS-CoV-2. Apart from SARS-CoV, MERS-CoV and SARS-CoV-2, other hCoVs cause seasonal outbreaks and are called sCoVs [6].
Overall global prevalence of sCoVs in respiratory tract infections is between 0.5 and 18.4% [6]. sCoV infections are associated with acute respiratory tract infection/illness (ARTI), pneumonia and croup, eventually leading to hospitalization [5]. hCoV-229E and hCoV-OC43 are transmitted during winter season in temperate countries and cause common cold like illness in infected individuals [2]. hCoV-NL63 infections peak during summer, spring and winter and infected individuals present with coryza, conjunctivitis, fever and bronchitis [7]. hCoV-HKU1 is also associated with acute exacerbation of asthma in some individuals [8]. Although hCoVs such as hCoV-229E, hCoV-OC43, hCoV-NL63 and hCoV-HKU1 cause mild infections across a wide age range, severe disease has been reported in children, elderly and immunocompromised individuals leading to hospitalization [9].
Since the emergence of SARS-CoV-2, the pattern of common respiratory infections started to change and an atypical seasonality was noted for sCoV infections [10,11]. This change in the pattern of common respiratory infections can be partially attributed to the morphology of the virus, size, survival time on surfaces, antibody mediated cross-protection in the host, viral interference caused by interferon-stimulated immunity and COVID-19 restrictions [10]. Moreover, SARS-CoV-2 and sCoV co-infections were also noted during the pandemic [10,12].
There are a few long-term studies available on the prevalence, clinical characteristics and pattern of distribution of sCoV globally [13][14][15]. Hence, limited availability of evidence has led to an incomplete epidemiology and clinical characteristics data for sCoV infections. Using longitudinal studies, the pattern of circulation of sCoV subtypes can be identified. In this study, we examined the prevalence, clinical characteristics and distribution of hCoV-229E, hCoV-OC43 and hCoV-NL63/HKU1 in patients with ARTI across all ages for 34 months in the Central Province of Sri Lanka.
## Methods
## Study design and setting
This is a descriptive study conducted at the Virology Laboratory of the National Hospital, Kandy (NHK), Sri Lanka from January 2020 to October 2022 during the COVID-19 pandemic. All respiratory samples (nasopharyngeal / oropharyngeal swab samples) received from patients with ARTI symptoms (n = 1062) including fever ≥ 38 °C, cough, cold, sore throat and shortness of breath (SOB) within first 7 days of the illness were selected for the study. The samples were stored at -80 °C freezer and analyzed on a weekly basis. Of the 1062 samples, 1021 were prospectively collected from January 2021 to October 2022. The rest (n = 41) were retrospectively analyzed from the laboratory records. These 41 samples were collected from January to December 2020. In 2020, only 41 samples were received for common respiratory viral testing at the Virology Laboratory, NHK, and all these samples were included in the study.
Ethical approval for the study was obtained from the Ethical Review Committee of the Faculty of Medicine, University of Peradeniya, Sri Lanka (Permit No: 2021/ EC/21) and informed consent was obtained from all subjects and/or their legal guardian(s) prior to sample collection. All methods including data and sample collection for the study were carried out in accordance with relevant guidelines and regulations. Permission for conducting the research and data collection was also obtained from the Director, NHK, Sri Lanka.
Hilden, Germany). The nucleic acid extracts were tested for SARS-CoV-2 by real time RT-PCR (Bioneer, Catalog No: nSCV-2112, South Korea or Altona, Real Star, Cat No: 015,821, Germany) and other common respiratory pathogens [respiratory syncytial virus-A, B (RSV-A, B), influenza-A, B, H1N1 (inf-A, B, HINI pdm 09), human parainfluenza virus-1 to 4 (hPIV-1 to 4), hCoV (hCoV OC43,NL63/HKU1,hCoV 229E), Rhinovirus/Enterovirus (Rh/EnV), human adenovirus (hAdV), human metapneumovirus (hMPV), human bocavirus type-1 (hBoV-1) and four atypical bacteria including Mycoplasma pneumonia (M. pneumoniae), Chlamydophila pneumoniae (C. pneumoniae), Legionella pneumophila (L. pneumophila), Bordetella species (Bordetella spp)] by a commercial real time PCR assay (Respifinder2SMART, Catalog No: PF2600-2 S, Netherlands) as per manufacturer's instructions. Samples collected from January to December 2020 were tested only for common respiratory pathogens using commercial real time reverse transcriptase multiplex PCR assay (Respifinder 2SMART, Catalog No: PF2600-2 S, Netherlands).
## Principles of respifinder® 2SMART assay
The RespiFinder® 2SMART assay is based on the Smart-Finder® technology, which allows a highly complex analysis of up to 13 targets in a single PCR reaction. The assay contains 23 different 2SMART primer sets targeting pathogen specific genes combined with 15 fluorescent labelled SMART probes, which detects pathogens and controls (Additional file). This starts with a pre-amplification reaction, which combines a RT step with a PCR step to amplify the target cDNA (Tables 1 and2). Subsequently, a part of the pre-amplification reaction mixture is transferred to two PCR tubes and two separate SmartFinder® reactions are performed (Tables 3 and4). The final pathogen detection is performed using a melting curve analysis. RespiFinder® 2SMART uses a Rotor-Gene® instrument (Corbett Life Science, Australia) for the nucleic acid detection of pathogens. Three different channels are used for the acquisition of different fluorescent signals (ROX, Cy5 and FAM).
## Results
Of the 1062 patients' samples tested, 51.03% (542/1062) were positive for atleast one respiratory pathogen. Of the respiratory pathogen positive patients, 83.4% (452/542) had single infections and 16.6% (90/542) had co-infections. Of the 51.03% (542/1062) patients positive for any of the respiratory infections, 25.83% (140/542) had Rh/ EnV; 18.08% (98/542) had RSV-A/B and 10.14% (55/542) had SARS-CoV-2. In addition, 13.09% (71/542) had hPIV-1-4; 12.91% (70/542) had inf-A/B; 12.17% (66/542) had hBoV-1; 4.79% (26/542) had hAdV and 3.6% (20/542) had hMPV (Additional file). Moreover, 3.87% (21/542) had atypical bacteria (Bordetella spp / L. pneumophila / M. pneumoniae / C. pneumoniae). sCoVs (hCoV-229E/ NL63/ HKU1/ OC43) were detected in 13.65% (74/542) patients (Fig. 1).
The median age of sCoV-positive patients was 17 years, (IQR = 46) and all three sCoVs were commonly detected in adults compared to children with male predominance (Fishers exact test, p = 0.709) (Fig. 2). Of the sCoV positive patients, 48.64% (36/74) had hCoV-NL63/HKU1 infection, 39.18% (29/74) had hCoV-229E infection and 12.16% (9/74) had hCoV-OC43 infection. 68.91% patients (51/74) had sCoV single infection and 31.08% (23/74) had co-infections with any of the other respiratory pathogens tested. Rh/EnV and hAdV are the predominant viruses co-infecting with sCoVs. Moreover, 4 patients were coinfected with SARS-CoV-2 (Table 5). Fever was observed in 86.5% (64/74) of patients, cough in 75.7% (56/74), and sore throat in 48.6% (36/74), making them the most prevalent symptoms across all three sCoV infections. Shortness of breath (SOB) (30%) and diarrhoea (11%) were the least frequently reported symptoms. Eight patients had lower respiratory tract infection (LRTI) (11%, 8/74) and intensive care was needed for four patients (5.4%, 4/74) (Table 6). Figure 4 shows the distribution of sCoVs along with COVID-19 cases in the Central Province of Sri Lanka. hCoV-OC43 was detected before the COVID-19 waves (1st wave 27th of January to 3rd of October 2020; 2nd wave 4th of October 2020 to 14th of April 2021; 3rd wave 15th of April 2021 to 30th of September 2022) and during the declining stage of the pandemic in 2022. hCoV-OC43 was not detected between April 2020 and June 2022. hCoV-229E was the only sCoV subtype detected from May to September in 2021 when the major COVID-19 peak was noted. However, none of the sCoVs was detected in August 2021; hCoV-229E and hCoV-NL63 co-circulated in several months in 2021 and 2022.
## Discussion
The present study findings describe the prevalence, demographic patterns, and clinical presentation of sCoV infections in children and adults from January 2020 to October 2022. This is the first large scale study with sCoV subtypes (hCoV-229E, NL63/HKU1 and OC43) circulated in Sri Lanka during the study period.
The overall prevalence of sCoV infections in the study sample was 6.96%. This is considerably higher than previously reported rates in Sri Lanka, particularly before the COVID-19 pandemic in a few small scale studies [16,17]. The study by Saphiro et al. reported 1.7% prevalence for sCoV infections among adults and children in the Southern part of Sri Lanka from March 2013 to January 2015 [16]. Another study done by Jayaweera et al. in the North Central and Central provinces of Sri Lanka from March 2013 to August 2014 did not find sCoV infections in their study populations [17]. Our study found a significantly higher detection rate of sCoVs in alignment with the findings of Sathgurupathi et al. (2021), compared to pre-COVID-19 levels. Sathgurupathi et al. reported 40% prevalence of sCoV infections among 384 patients with ARTI using samples collected from January to March 2021 in the North Central part of Sri Lanka [18]. Increase in the prevalence of sCoV infections may be due to heightened surveillance, improved diagnostics, or changes in viral circulation dynamics.
## Total sCoV co-infections 23
EnV-Enterovirus, hAdV-Human adenovirus, hBoV-1-Human bocavirus- Among the sCoV-positive patients, males exhibited a higher prevalence, a trend consistent with previous reports on other respiratory viral infections [19][20][21]. In contrast to findings of the previous studies, sCoV infections were more prevalent among adults than children in our study [22][23][24].
It has to be noted that there is a substantial variation in the prevalence of sCoV subtypes in different epidemiological studies that included patients with ARTI [10,14,25,26]. The predominant sCoV detected in this study was hCoV-NL63/HKU1 followed by hCoV-229E and hCoV-OC43. However, hCoV-OC43 was the predominant sCoV detected in a previous study conducted in the Southern part of Sri Lanka and other parts of the world including the United Kingdom and Hong Kong before the COVID-19 pandemic [15,16,27]. A study done by Heimdal et al., before the COVID-19 pandemic among hospitalized Norwegian children with ARTI for nine years, also reveals that hCoV-OC43 was the most commonly detected subtype [28]. However, based on the observation during the pandemic, the prevalence rate of hCoV-OC43 has been reduced and this is supported by another small scale study done in Sri Lanka as well [18].
The varying prevalence of sCoVs may be attributed to several factors including the interference from the widely circulated SARS-CoV-2, non-pharmaceutical interventions implemented to control the spread of SARS CoV-2 and non-specific interference caused by interferon. Moreover, the number of samples tested during 2020 is less compared to that in 2021 and 2022 and this might be a reason for not detecting sCoVs like hCoV-229E and hCoV-NL63/HKU1 in 2020. Viral interference is one of the reasons for the shift in the prevalence between hCoV-OC43 and hCoV-NL63/HKU1. hCoV-NL63 and hCoV-HKU1 are less genetically related to SARS-CoV-2 than hCoV-OC43, possibly allowing them to co-circulate. Moreover, immune response induced by SARS-CoV-2 infection or vaccination derived temporary cross-immunity might have suppressed hCoV-OC43 than hCoV-NL63 or hCoV-HKU1.
Of the seven hCoVs, sCoVs cause symptoms similar to epidemic CoVs but with less disease severity [26,29,30]. However, there is some evidence to suggest that co-infection with endemic or epidemic hCoVs, sCoVs can cause severe disease [31,32]. In our study four patients were co-infected with SARS-CoV-2 including three children and one adult. Of these, the 50-year-old adult had severe respiratory symptoms and required mechanical ventilation. Of the four SARS-CoV-2 co-infected patients, two had hCoV-229E and SARS-CoV-2 co-infections and two had hCoV-NL63/HKU1 and SARS-CoV-2 co-infections. No hCoV-OC43 and SARS-CoV-2 co-infections were detected in our study, however, studies conducted in other parts of the world document hCoV-OC43 and SARS-CoV-2 co-infections [31,33]. The absence of hCoV-OC43 and SARS-CoV-2 co-infections in our study population might be due to very less number of hCoV-OC43 infections noted in our study during the study period from 2020 to 2022.
hCoVs are widespread globally and the pattern of distribution varies according to the region and seasonal factors [6,34,35]. However, sCoVs are usually detected throughout the year in tropical countries. In our study sCoVs were detected year-round with major peaks in January -February in 2021 and 2022. As our study period was within the COVID-19 pandemic, other than the seasonal factors, interference from the SARS-CoV-2, non-pharmaceutical interventions implemented to control the spread of SARS CoV-2 and non-specific interference caused by interferon may also have influenced the circulation of sCoVs [23]. In Sri Lanka, the first COVID-19 patient was identified in December 2019 and three COVID-19 waves (1st wave 27th of January to 3rd of October 2020; 2nd wave 4th of October 2020 to 14th of April 2021; 3rd wave 15th of April 2021 to 30th of September 2022) were reported by the Epidemiology Unit of Sri Lanka. During the first wave, a maximum of less than a thousand cases were reported per week and this was considerably lower than the cases reported subsequently in the next two waves. The detection rate of sCoV was less in the first wave compared to the next two years of our study (2021/2022), which mainly falls within the second and third waves. The prevalence of sCoV was higher in January and February in 2021 and this falls within the COVID-19 s wave in which increased number of COVID-19 cases were reported weekly [36].
Moreover, the prevalence of hCoV-OC43 was very low during the months when SARS-CoV-2 peak was noted. hCoV-229E and hCoV-NL63/HKU1 co-circulated during the second and third COVID-19 waves. However, hCoV-229E was the only sCoV circulated from May to September in 2021 when the most prominent SARS-CoV-2 pandemic peak was noted. No sCoVs were detected in August 2021 when the maximum number of SARS CoV-2 cases were recorded [36].
SARS-CoV-2 and sCoVs share more than 30% similarity in their genetic code within the S2 subunit and this may result in overlapping immune epitopes [37]. Studies suggest that either by vaccination or natural infection based protective immunity against the SARS-CoV-2 might have increased cross protection against sCoVs [38,39]. However, there is a disagreement among researchers as some argue that the antibodies may increase but not effectively prevent sCoVs infections or hospitalizations [40]. Frequent recombination and declining natural immunity against hCoV suggests that any cross-protection from infection or vaccination may not offer sufficient defense against future infections [36,41,42]. The current study findings reveal that the co-circulation of sCoVs and SARS-CoV-2 is possible and the pattern of sCoVs subtypes suggests the effects of viral interference or crossprotection among CoVs. Additional studies are needed to comprehensively understand how SARS-CoV-2 influences the circulation of sCoVs and the complex immune interactions between these viruses [10]. It is important to note that all hCoVs use different receptors in host cells for entry and sCoVs express the spike glycoprotein, which extends from the surface of the virus. There is a significant similarity between hCoV-229E and hCoV-NL63 spike glycoproteins and this is supported by our finding that hCoV-229E and hCoV-NL63/HKU1 co-circulated in most of the months [6]. Future directions to combat the limitations of the current study include, establishing multi-center surveillance studies across diverse climates including both symptomatic and asymptomatic individuals, employing specific molecular assays, to separately identify the prevalence of hCoV-NL63 and hCoV-HKU1 infections.
## Conclusion
The present study reports a 6.96% prevalence of sCoV infections in patients with ARTI. Of the respiratory pathogen-positive patients, sCoVs (hCoV-229E, NL63, HKU1, and OC43) were detected in 13.65% (74/542). The most frequently identified sCoV subtype was hCoV-NL63/HKU1. Fever, cough, and sore throat were the most commonly reported symptoms across all three sCoV infections. sCoVs were detected throughout the year, with increased detections in January and February of 2021 and 2022. Variation in the distribution of sCoVs and their subtypes was noted during the COVID-19 pandemic and this may reflect changes in virus circulation patterns during the pandemic period. Establishing a national sCoV surveillance system could support more consistent monitoring of sCoV activity and contribute to a better understanding of circulating hCoVs.
## References
1. Pal, Berhanu, Desalegn et al. (2020) "Severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2): an update. Cureus"
2. Huynh, Li, Yount et al. (2012) "Evidence supporting a zoonotic origin of human coronavirus strain NL63" *J Virol*
3. Santos, Reynaga, González et al. (2022) "Insights on the evolution of coronavirinae in general, and SARS-CoV-2 in particular, through innovative biocomputational resources" *PeerJ*
4. Hamre, Procknow (1966) "A new virus isolated from the human respiratory tract" *Exp Biol Med*
5. Dijkman, Jebbink, Gaunt et al. (2012) "The dominance of human coronavirus OC43 and NL63 infections in infants" *J Clin Virol*
6. Ljubin-Sternak, Meštrović, Lukšić et al. (2021) "Seasonal coronaviruses and other neglected respiratory viruses: A global perspective and a local snapshot"
7. Pyrc, Jebbink, Berkhout et al. (2004) "Genome structure and transcriptional regulation of human coronavirus NL63" *Virol J*
8. Abdul-Rasool, Fielding (2010) "Understanding human coronavirus HCoV-NL63" *Open Virol J*
9. Liu, Liang, Fung (2020) "Human Coronavirus-229E, -OC43, -NL63, and -HKU1 (Coronaviridae). Encycl Virol"
10. Heiskanen, Galipeau, Little et al. (2023) "Seasonal respiratory virus circulation was diminished during the COVID-19 pandemic" *Influenza Other Respi Viruses*
11. Shen, Vermeulen, Debeer et al. (2022) "Impact of COVID-19 on viral respiratory infection epidemiology in young children: a single-center analysis"
12. Dung, Phat, Vinh et al. (2024) "Development and validation of multiplex real-time PCR for simultaneous detection of six bacterial pathogens causing lower respiratory tract infections and antimicrobial resistance genes" *BMC Infect Dis*
13. Dare, Fry, Chittaganpitch et al. (2007) "Human coronavirus infections in rural thailand: A comprehensive study using real-time reverse-transcription polymerase chain reaction assays" *J Infect Dis*
14. Sloots, Mcerlean, Speicher et al. (2006) "Evidence of human coronavirus HKU1 and human bocavirus in Australian children" *J Clin Virol*
15. Lau, Woo, Yip et al. (2006) "Coronavirus HKU1 and other coronavirus infections in Hong Kong" *J Clin Microbiol*
16. Shapiro, Bodinayake, Nagahawatte et al. (2017) "Burden and seasonality of viral acute respiratory tract infections among outpatients in Southern Sri Lanka" *Am J Trop Med Hyg*
17. Jayaweera, Morel, Abeykoon et al. (2021) "Viral burden and diversity in acute respiratory tract infections in hospitalized children in wet and dry zones of Sri Lanka" *PLoS ONE*
18. Sathgurupathi, Wanniarachchi, Liyanapathirana et al. (2022) "A descriptive study on prevalence of respiratory viruses in patients with respiratory symptoms during SARS-CoV-2 pandemic in North central Province, Sri Lanka"
19. Rafeek, Divarathna, Morel et al. (2022) "Clinical and epidemiological characteristics of influenza virus infection in hospitalized children with acute respiratory infections in Sri Lanka" *PLoS ONE*
20. Divarathna, Rafeek, Morel et al. (2023) "Epidemiology and risk factors of respiratory syncytial virus associated acute respiratory tract infection in hospitalized children younger than 5 years from Sri Lanka" *Front Microbiol*
21. Khasawneh, Himsawi, Abu-Raideh et al. (2023) "Prevalence of SARS-COV-2 and other respiratory pathogens among a Jordanian subpopulation during Delta-to-Omicron transition: winter 2021/2022" *PLoS ONE*
22. Tillekeratne, Bodinayake, Nagahawatte et al. (2013) "An under-recognized influenza epidemic identified by rapid influenza testing, Southern Sri Lanka" *Am J Trop Med Hyg*
23. Nickbakhsh, Mair, Matthews et al. (2019) "Virus-virus interactions impact the population dynamics of influenza and the common cold" *Proc Natl Acad Sci U S A*
24. Hacker, Kuan, Vydiswaran et al. (2022) "Pediatric burden and seasonality of human metapneumovirus over 5 years in Managua" *Influenza Other Respi Viruses*
25. Zeng, Chen, Tan et al. (2018) "Epidemiology and clinical characteristics of human coronaviruses OC43, 229E, NL63, and HKU1: a study of hospitalized children with acute respiratory tract infection in Guangzhou, China" *Eur J Clin Microbiol Infect Dis*
26. Otieno, Murunga, Agoti et al. (2020) "Surveillance of endemic human coronaviruses (HCoV-NL63, OC43 and 229E) associated with childhood pneumonia in Kilifi" *Kenya. Wellcome Open Res*
27. Gaunt, Hardie, Claas et al. (2010) "Epidemiology and clinical presentations of the four human coronaviruses 229E, HKU1, NL63, and OC43 detected over 3 years using a novel multiplex real-time PCR method" *J Clin Microbiol*
28. Heimdal, Moe, Krokstad et al. (2019) "Human coronavirus in hospitalized children with respiratory tract infections: A 9-year population-based study from Norway" *J Infect Dis*
29. Rucinski, Binnicker, Thomas et al. (2020) "Seasonality of Coronavirus 229E, HKU1, NL63, and OC43 From 2014 to 2020" *Mayo Clin Proc*
30. Si, Zhao, Chen et al. (2020) "Epidemiological surveillance of common respiratory viruses in patients with suspected COVID-19 in Southwest China" *BMC Infect Dis*
31. To, Hung, Chan et al. (2013) "From SARS coronavirus to novel animal and human coronaviruses" *J Thorac Dis*
32. Kanwar, Selvaraju, Esper (2017) "Human coronavirus-HKU1 infection among adults in Cleveland" *Ohio. Open Forum Infect Dis*
33. Mponponsuo, Murthy, Kanji et al. (2023) "Coinfection of SARS-CoV-2 with human coronavirus OC43 in a patient with underlying lung disease: A case report" *J Assoc Med Microbiol Infect Dis Can*
34. Jevšnik, Steyer, Zrim et al. (2013) "Detection of human coronaviruses in simultaneously collected stool samples and nasopharyngeal swabs from hospitalized children with acute gastroenteritis" *Virol J*
35. Agca, Akalin, Saglik et al. (2021) "Changing epidemiology of influenza and other respiratory viruses in the first year of COVID-19 pandemic" *J Infect Public Health*
36. Unit, Sri Lanka (2022)
37. Ng, Faulkner, Cornish et al. (2020) "Preexisting and de Novo humoral immunity to SARS-CoV-2 in humans. Sci (80-)"
38. Kellam, Barclay (2020) "The dynamics of humoral immune responses following SARS-CoV-2 infection and the potential for reinfection" *J Gen Virol*
39. Song, He, Ting et al. (2021) "Crossreactive serum and memory B-cell responses to Spike protein in SARS-CoV-2 and endemic coronavirus infection" *Nat Commun*
40. Anderson, Goodwin, Verma et al. (2021) "Seasonal human coronavirus antibodies are boosted upon SARS-CoV-2 infection but not associated with protection" *Cell*
41. Edridge, Kaczorowska, Hoste et al. (2020) "Seasonal coronavirus protective immunity is short-lasting" *Nat Med*
42. Zhang, Li, Xiao et al. (2015) "Genotype shift in human coronavirus OC43 and emergence of a novel genotype by natural recombination" *J Infect*
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https://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC12793642&blobtype=pdf
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# Rhode Island
## Abstract
Background. Mpox is a zoonotic disease that is endemic to Nigeria and is caused by the Mpox virus, a member of the orthopoxvirus family. In humans, this virus can
produce a severe illness that may resemble chickenpox or smallpox, and it frequently results in co-infections with varicella-zoster viruses (VZV). The first occurrence in Imo State was reported in 2018 and resulted in death. Beginning on January 6, 2022, a rising number of instances signaled the beginning of the outbreak. We looked into the severity of the co-infections of Mpox and varicella-zoster (VZV) outbreaks in the state.
Methods. Using the accepted standard case definition for Mpox, which is defined as a person with an acute illness who has a fever >38.3 °C, a severe headache, lymphadenopathy, back pain, and rashes that spread to every part of the body, including the soles of the feet and palms of the hands. In order to create a line list, we gathered sociodemographic and clinical information. For laboratory validation utilizing reverse transcription polymerase chain reaction (RT-PCR), we collected swabs and blood samples. We computed ratios and rates.
Results. 357 suspected cases were found and investigated from January 2022 to March 2025, there were 56 laboratory-confirmed cases of Mpox-VZV coinfection with 2 deaths and the highest proportion of cases being reported from Owerri Municipal LGA (23.8%), males (69.0%), aged 0-5 years (21.4%), and family members as contacts (50.3%). With a case fatality rate of 3.6% and a positivity rate of 15.7%. Fever, palm, foot, and cheek rashes, as well as pustules, were present in all 56 patients.
Conclusion. During the response, we enhanced surveillance for active case search, which helped to identify more cases. In order to encourage early diagnosis and case treatment, there is a need to increase awareness of the condition and its risk factors for high levels of index suspicion. In Nigeria, the introduction of the Mpox and varicella-zoster viruses (VZV) infection vaccines is needed, especially for children under 5 years children because they are mostly infected.
Disclosures. All Authors: No reported disclosures
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# Cryptococcal Infection in a Patient With Chronic Lymphocytic Leukaemia Receiving Acalabrutinib, a Bruton's Tyrosine Kinase Inhibitor: A Case Report
Abdul-Razaq Al-Shaker, Ansh Agarwal, Muhammad Talha Saeed, Zena Marney
## Abstract
A male patient in his mid-sixties with chronic lymphocytic leukaemia (CLL), Binet stage B, receiving the Bruton's tyrosine kinase (BtK) inhibitor acalabrutinib, presented with fever and other non-specific systemic symptoms. Following the investigation, they were found to have Cryptococcal meningitis. Cryptococcal infections are known to occur in immunocompromised patients, but they are rarely encountered or thought about during the initial acute medical assessment. This case highlights the importance of considering the possibility of opportunistic infections and the atypical presentation of such infections in immunocompromised patients, including those on BtK inhibitors.
## Introduction
Chronic lymphocytic leukaemia (CLL) is the most common form of leukaemia and occurs more commonly with advancing age [1]. Bruton's tyrosine kinase (BtK) inhibitors such as acalabrutinib have revolutionised CLL management. However, these agents impair B-cell receptor signalling and alter immune responses, potentially predisposing patients to infections [2].
We present a case of cryptococcal infection in a patient with CLL treated with acalabrutinib, highlighting the need for vigilance for opportunistic infections and timely investigation in immunocompromised individuals receiving targeted therapies.
## Case Presentation
A male patient in his mid-sixties with CLL, Binet stage B, who had been started on acalabrutinib nine months before admission, presented with non-specific symptoms including fever, lethargy, increased night sweats and general malaise.
Initially, blood tests showed mild neutropenia and an elevated C-reactive protein (CRP) of 100 mg/L. During the investigation, cultures were obtained, and he was commenced on broad-spectrum antibiotics for febrile neutropenia; acalabrutinib was withheld. He was monitored closely and isolated in a cubicle; blood cultures subsequently returned positive for Cryptococcus.
Following discussion with a microbiologist, the patient was commenced on amphotericin B and flucytosine, and concern was raised regarding the possibility of cryptococcal meningitis despite the absence of meningism on clinical assessment. As a result, a lumbar puncture was performed, and CSF was sent for culture. The opening pressure was 11 cm H₂O, and the CSF cryptococcal antigen returned positive (Table 1). Following discussion with a microbiologist, the patient was felt well enough to be discharged on high-dose fluconazole, with regular outpatient follow-up, especially in view of improving CRP (Table 3). From a CLL perspective, following cessation of acalabrutinib, the patient became progressively anaemic, with a rising lymphocyte count (Table 3). He was therefore considered for alternative immunosuppressive treatment.
## Discussion
Chronic lymphocytic leukaemia CLL is the most common form of leukaemia and occurs more commonly with advancing age. Patients may be asymptomatic at the time of diagnosis, and as such diagnosis can be incidental when checking routine blood tests. Its prognosis depends upon multiple factors, including the clinical stage of the disease at the time of diagnosis, the patient's age and the pace of disease progression. Patients with CLL are more prone to infections due to functional neutropenia and immune failure due to reduced immunoglobulins [1].
Fungal infections are not typically observed in CLL in the absence of treatment with corticosteroids or other immunosuppressive therapy for autoimmune complications. Cryptococcal meningitis, pneumonia and fungaemia are well-recognised occurrences in patients with CLL and are associated with significant morbidity and mortality [3].
CLL treatment depends upon the stage of the disease at the time of diagnosis and is often treated expectantly in the early stages and immediately in the later stages. Treatment modalities include steroids and chemotherapy. Erythropoietin can be considered to avoid the need for transfusions. Immunoglobulin replacement and prophylactic antimicrobial treatment should also be considered [1].
More specific treatments such as chemotherapies and targeted immune therapies are considered according to the patient's genetic profile, comorbidities, functional status and patient's preferences. Examples of such treatments include BtK inhibitors such as acalabrutinib and ibrutinib, anti-CD20 antibodies such as obinutuzumab and rituximab, and purine inhibitors (fludarabine) given together with cyclophosphamide and rituximab [4].
## Tyrosine kinase and BtK and its inhibitors
Tyrosine kinase receptors (TKRs) are transmembrane immunoglobulin-like molecules; a mutation in this receptor can lead to accelerated cellular proliferation, extended cell survival, increased angiogenesis and cellular migration. Tyrosine kinase inhibitors (TKIs) are a group of medications that inhibit tyrosine kinase receptors (TKRs), leading to suppression of tumour growth and spread [5].
BtK is a non-receptor kinase that plays a crucial role in oncogenic signalling that is critical for the proliferation and survival of leukaemic cells in many B-cell malignancies. The orally administered irreversible BtK inhibitor ibrutinib is associated with high response rates [2].
Acalabrutinib is a second-generation BtK inhibitor with minimal off-target effects compared with ibrutinib, thereby limiting adverse events. Ongoing trials in high-risk relapsed CLL are comparing acalabrutinib with ibrutinib [3].
As acalabrutinib is a relatively new agent in the management of CLL, there are limited published case reports describing cryptococcal infection in patients receiving this treatment. We therefore believe this case report is valuable in highlighting the atypical presentation of this opportunistic infection.
## Conclusions
Targeted therapies, such as BTK inhibitors, have revolutionised the management of CLL. Acalabrutinib is a second-generation BTK inhibitor believed to have a more favourable adverse event profile compared with ibrutinib. This case describes a patient with CLL who presented with fever and non-specific symptoms. Investigations revealed cryptococcal meningitis, which was successfully treated with a prolonged course of antifungal therapy. This highlights the importance of considering opportunistic infections in this patient group, as well as the potential for atypical presentations.
## References
1. Sive, Foggo, Oncology et al. (2020)
2. Singh, Dammeijer, Hendriks (2018) "Role of Bruton's tyrosine kinase in B cells and malignancies" *Mol Cancer*
3. Awan, Byrd, Niederhuber et al. (2020) "Chronic Lymphocytic Leukemia. Abeloff's Clinical Oncology"
4. Barrientos, Rhodes (2025) "Chronic lymphocytic leukaemia" *BMJ Best Practice*
5. Byrd, Flynn, Niederhuber et al. (2014) "Chronic Lymphocytic Leukemia. Abeloff's Clinical Oncology"
6. *Cureus*
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https://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC12697116&blobtype=pdf
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# Metagenome-assembled complete genome of Bohxovirus, a virulent bacteriophage involved in the prediction of hospitalacquired pneumonia in intubated critically ill patients
Hussein Anani, Grégory Destras, Hadrien Regue, Simon Bulteau, Céline Bressollette-Bodin, Antoine Roquilly, Laurence Josset
## Abstract
We present the complete genome of a Bohxovirus species, a virulent phage targeting Prevotella jejuni, reconstructed from viral metagenomes in respiratory endotracheal aspirates of intubated critically ill patients. The 98-kbp bacteriophage, belonging to the Suoliviridae family, does not contain genes associated with antibiotic resistance or bacterial virulence.CLINICAL TRIALS ClinicalTrials.gov numbers: NCT02003196 and NCT04793568.
KEYWORDS bacteriophage genome, respiratory virome, viral metagenomicsH ospital-acquired pneumonia (HAP) is the most common nosocomial infection in intensive care unit (ICU) patients, leading to increased mortality (1). In a recent study, we characterized the endotracheal virome of ICU patients and revealed that respiratory virome was dominated by bacteriophages (2, 3). We identified a viral signature classifying patients into upcoming HAP or no HAP. In the previous study (3), we sampled 121 endotracheal aspirates from 87 patients to study the role of the respiratory virome in HAP pathogenesis.Total nucleic acids were extracted from samples using the Qiagen EZ1 Advanced XL extractor and amplified with the WTA2 Kit, followed by purification with QIAquick spin columns. Libraries were prepared using the Nextera-XT Kit and sequenced on Nova Seq-6000 with 2 × 100 bp paired-end reads. Raw data downloaded from the BioPro ject PRJNA1132989, were processed using viral_metagenomics_pipeline v1.0.0 (https:// github.com/genepii/HAP2-IBIS-Virome). Human reads were removed with SRAHuman Scrubber v2.2.1 (default parameters) (https://github.com/ncbi/sra-human-scrubber), followed by quality trimming using Cutadapt (4) v4.6 (default parameters). Taxonomic classification was performed with Kraken2 (5) v2.1.2 (k-mer-based assignment; min-hitgroups = 2, confidence = 0.1). Viral contigs from each sample were assembled individu ally using SPAdes (6) v.3.14.0 with the --meta parameter, dereplicated with cd-hit (7) v4.7, and quality checked with Checkv (8) v1.1.3, using the default parameters. Viral metagenomic sequencing yielded a total of 276 gigabases (Gb) of raw data for which 61 Gb were assigned as viral reads.Among the 66 viral and conserved operational taxonomical units (vcOTUs) reported in the HAP signature, the longest (98 kbp) vcOTU was a Caudoviricetes bacteriophage (vcOTU56 as reported in Anani and colleagues [3]). vcOTU56 was analyzed using Phabox2 v2.1.12 (9) with default parameters, which integrates several modules: Phatyp predicts whether a virus is virulent or temperate by analyzing genomic features and protein content. PhagCN predicts potential viral hosts by leveraging sequence similarity, k-mer patterns, and co-occurrence networks to identify bacterial hosts. Phamer performs December 2025 Volume 14 Issue 12 10.
gene-level annotation and clustering by comparing viral proteins against the most recent International Committee on Taxonomy of Viruses database release to assign taxonomic information. vcOTU56 was annotated as a Bohxovirus, classified within the Suoliviridae family, has a virulent lifestyle, and infects Prevotella jejuni, a bacterium that inhabits the human oral and gut microbiomes (10). vcOTU56, present in 29% of samples, with reads remapping (mean relative abun dance of 0.05%), has a complete circular genome of 98,381 bp with a sequencing depth of 2,372× and GC content of 33.06% (100% completeness and 0% contamination). Genome annotation using Prokka v1.14.6 (11) with the --kingdom Viruses parameter predicts 168 viral genes and 5 tRNA genes. vcOTU56 genome was visualized using PhageScope (12) (Fig. 1A). Phylogenetic analysis of vcOTU56 and the 10 closest BLASTnidentified sequences from nucleotide-NCBI database showed that vcOTU56 formed a separate group (Fig. 1B). Interestingly, all closest sequences, like vcOTU56, were predicted to belong to Bohxovirus (Table 1).
vcOTU56 exhibits a 92.70% ANI with its closest sequence (Caudoviricetes_sp_iso late_ctRU85, Fig. 1C). In accordance with the 95% species demarcation threshold, these data suggest that vcOTU56 is a new species of the genus Bohxovirus, which warrants further investigation.
## References
1. He, Wang, Zhu et al. (2021) "The epidemiology and clinical outcomes of ventilator-associated events among 20,769 mechanically ventilated patients at intensive care units: an observational study" *Crit Care*
2. Montassier, Kitsios, Radder et al. (2023) "Robust airway microbiome signatures in acute respiratory failure and hospital-acquired pneumonia" *Nat Med*
3. Anani, Destras, Bulteau et al. (2025) "Lung virome convergence precedes hospital-acquired pneumonia in intubated critically ill patients" *Cell Rep Med*
4. Martin (2011) "Cutadapt removes adapter sequences from highthroughput sequencing reads" *EMBnet j*
5. Lu, Rincon, Wood et al. (2022) "Metagenome analysis using the Kraken software suite" *Nat Protoc*
6. Nurk, Meleshko, Korobeynikov et al. (2017) "metaSPAdes: a new versatile metagenomic assembler" *Genome Res*
7. Fu, Niu, Zhu et al. (2012) "CD-HIT: accelerated for clustering the next-generation sequencing data" *Bioinformatics*
8. Nayfach, Camargo, Schulz et al. (2021) "CheckV assesses the quality and completeness of metagenome-assembled viral genomes" *Nat Biotechnol*
9. Shang, Peng, Liao et al. (2023) "PhaBOX: a web server for identifying and characterizing phage contigs in metagenomic data" *Bioinform Adv*
10. Webb, Olagoke, Baird et al. (2022) "Genomic diversity and antimicrobial resistance of Prevotella species isolated from chronic lung disease airways" *Microb Genom*
11. Seemann (2014) "Prokka: rapid prokaryotic genome annotation" *Bioinformatics*
12. Wang, Yang, Liu et al. (2024) "PhageScope: a well-annotated bacteriophage database with automatic analyses and visualizations" *Nucleic Acids Res*
13. Katoh, Standley (2013) "MAFFT multiple sequence alignment software version 7: improvements in performance and usability" *Mol Biol Evol*
14. Capella-Gutiérrez, Silla-Martínez, Gabaldón (2009) "trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses" *Bioinformatics*
15. Minh, Schmidt, Chernomor et al. (2020) "IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era" *Mol Biol Evol*
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# Recovering new viruses from New Mexico soils
Kelli Feeser, Reid Longley, La Gallegos-Graves, Michaeline Albright, Migun Shakya
## Abstract
Here, we utilized metagenomic and size-filtered virome sequencing to recover 4,157 medium, high, or complete quality viral genomes from soils taken from three high elevation sites in New Mexico, USA. Among recovered viral genomes, 90% were from size-filtered samples, indicating the importance of this enrichment in assessments of complex viromes. KEYWORDS soil microbiology, phage, metagenome, high altitude, virome V iral communities are diverse and play important roles in soil ecosystems; how ever, they remain undercharacterized (1). To assess previously uncharacterized viral communities, we collected four soil samples from similar elevations at each of three different high desert mountains in New Mexico (Table 1). A total of 30 g of soil was taken for each sample and was split for processing of bulk metagenomes and size-filtered viromes (n = 24, 12 viromes and 12 metagenomes). Soils were initially processed by 1:1 resuspension in protein supplemented phosphate-buffered saline (PPBS) elution buffer followed by shaking, centrifugation, and size filtration. Bulk metagenomic DNA was then extracted from 550 µL of 11-µm filtrate, while viromes were processed by extracting DNA from 0.22-µm filtrate. DNA was extracted using the DNeasy PowerSoil Kits (Qiagen, USA). DNA extractions were performed using a modified protocol from (2). The exact extraction protocol is available on protocols.io. Illumina libraries were prepared following manufacturer's instructions with the NEBNext Ultra DNA II Library Preparation Kit (New England Biolabs, USA), followed by sequencing with 151 bp paired-end reads on the Illumina NextSeq (Illumina, USA). Following sequencing, bioinformatic processing was performed with default parameters except where otherwise noted. Raw reads were quality controlled and had adapters removed using FaQCs v2.10 (3). Metagenomes were assembled using metaspades v3.12 with default parameters and k-mer lengths of 21, 33, 55, and 77 bp (4). Resulting contigs were classified to detect viruses using geNomad v1.9.0 and further checked for quality using checkV v1.0.3 (5, 6). Viruses identified as medium, high, or complete quality were retained for further analysis. Complete viral genomes were annotated with pharokka v1.7.0 (7). Viral genomes were then assessed using iPHoP v1.3.3 to predict their bacterial hosts (8). Viral sequences were clustered into species level vOTUs using blastn in BLAST +v2.16.0 according to the Minimum Information about an Uncultivated Virus Genome (MIUViG) specifications (9,10).Assembly sizes ranged between 3.8 Mb and 1,046.6 Mb (Table 1). From these assemblies, we recovered 4,157 viruses of medium, high, or complete quality. Filtered viromes consistently recovered higher numbers of viruses (average = 311) compared with metagenomes (average = 35) (Fig. 1A). Among the recovered viruses, 563 were identified as being complete, 995 were high quality, and 2,599 were medium quality (Fig. 1B). Clustering of the 4,157 viral genomes into species level vOTUs created 3,867 clusters, indicating that the majority of recovered viral genomes were unique. The majority (89%) of clusters were composed of viruses recovered only from viromes, indicating that size-filtered samples produced maximum diversity (Fig. 1C). Host analyses using iPHoP identified 124 complete or high-quality viruses, which could be assigned to a host
with >90% confidence. Phage sequences were associated with common soil bacterial genera, including Mycobacterium, Pseudomonas, and Streptomyces. Our results agree with previous studies, indicating that size filtration-based viral enrichment methods are a valuable tool to recover viral genomes from complex communities including soil (11,12). We expect that this data set will act as a valuable reference as the diversity of viruses in soil continues to be uncovered.
## References
1. Graham, Camargo, Wu et al. "Soil Virosphere Consortium. 2024. A global atlas of soil viruses reveals unexplored biodiversity and potential biogeochemical impacts" *Nat Microbiol*
2. Albright, Gallegos-Graves, Feeser et al. (2022) "Experimental evidence for the impact of soil viruses on carbon cycling during surface plant litter decomposition" *ISME Commun*
3. Lo, Chain (2014) "Rapid evaluation and quality control of next generation sequencing data with FaQCs" *BMC Bioinformatics*
4. Nurk, Meleshko, Korobeynikov et al. (2017) "metaSPAdes: a new versatile metagenomic assembler" *Genome Res*
5. Camargo, Roux, Schulz et al. (2024) "Identification of mobile genetic elements with geNomad" *Nat Biotechnol*
6. Nayfach, Camargo, Schulz et al. (2021) "CheckV assesses the quality and completeness of metagenomeassembled viral genomes" *Nat Biotechnol*
7. Bouras, Nepal, Houtak et al. (2023) "Pharokka: a fast scalable bacteriophage annotation tool" *Bioinformatics*
8. Roux, Camargo, Coutinho et al. (2023) "iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria" *PLoS Biol*
9. Camacho, Coulouris, Avagyan et al. (2009) "BLAST+: architecture and applications" *BMC Bioinformatics*
10. Roux, Adriaenssens, Dutilh et al. (2019) "Minimum information about an uncultivated virus genome (MIUViG)" *Nat Biotechnol*
11. Göller, Haro-Moreno, Rodriguez-Valera et al. (2020) "Uncovering a hidden diversity: optimized protocols for the extraction of dsDNA bacteriophages from soil" *Microbiome*
12. Santos-Medellin, Zinke, Horst et al. (2021) "Viromes outperform total metagenomes in revealing the spatiotemporal patterns of agricultural soil viral communities" *ISME J*
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https://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC12754524&blobtype=pdf
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# Detection of dengue virus encephalitis in central part of Sri Lanka
Inuri Perera, Achini Weerathunga, Nipuni Arachchige, Lakmali Rajamanthri, Sachini Fernando, Rohitha Muthugala, Sri Lanka
## Abstract
BACKGROUNDIn tropical Asia, arbovirus-induced encephalitis continues to be a serious public health issue. Encephalitis is caused by wide range of neurotropic pathogens, and flaviviruses are one of the main causative agents in the area. Sri Lanka reports a considerable number of central nervous system infections annually. Both dengue and Japanese encephalitis are endemic, and cases of Zika and West Nile virus infections were reported occasionally in Sri Lanka. Although reported number of Japanese encephalitis cases has reduced in the past, aetiological diagnosis in majority of encephalitis cases is still unknown.
AIMTo detect dengue virus (DENV) infections in individuals in the central region of Sri Lanka who were clinically suspected of having encephalitis. METHODS A retrospective observational analysis was conducted on 99 cerebrospinal fluid samples received to a virology laboratory from patients in the central part of Sri Lanka who were clinically suspected of having encephalitis. Samples were analyzed using reverse transcriptase polymerase chain reaction (RT-PCR) with universal flavivirus primers to detect flaviviral RNA followed by DENV serotyping real-time RT-PCR, and an immunoglobulin M (IgM) detection enzyme-linked immunosorbent assay to detect IgM antibodies indicative of a possible recent DENV infection. Perera I et al. DENV encephalitis in Sri Lanka WJV https://www.wjgnet.com 2 December 25, 2025 Volume 14 Issue 4
RESULTSDENV aetiology was detected in 6 (6.06%) cerebrospinal fluid samples, and all were confirmed as DENV infections.A single positive result (1.01%) was yielded through RT-PCR and was identified as DENV serotype 3. Serology testing detected 05 (5.05%) anti-dengue IgM positives and further investigation indicated probable DENV aetiology. Among positives 02 (33.33%) were children (aged less than 14 years), and rest were adults.
CONCLUSIONThese findings underscore the presence of DENV-associated central nervous system infections and highlight the need for broader surveillance and more advanced diagnostic approaches in the future.
## INTRODUCTION
Central nervous system (CNS) infections encompass a broad range of pathological conditions, including meningitis, encephalitis, and brain abscesses [1]. These infections represent a significant global health concern, with an estimated incidence of 389 cases per 100000 individuals reported between 1990 and 2016 [2]. In Sri Lanka, epidemiological data indicate that approximately 1000-1500 cases of meningitis and 150-250 cases of encephalitis are reported annually [3]. Notably, recent epidemiological reports highlight a considerable increase in the incidence of both conditions in 2023 [4].
Over 100 different pathogens, including bacteria, viruses, fungi, and parasites, have been reported to cause CNS infections [5]. Among these, viruses are recognized as the predominant causative agents of meningitis and encephalitis [3]. Viruses from all families possess the potential to invade the CNS [6]. A significant proportion of viral CNS infections are attributed to arthropod-borne viruses (arboviruses), a diverse group of viruses transmitted by vectors such as mosquitoes, ticks, and midges. Arboviruses comprise from approximately 534 known viruses, including both DNA and RNA viruses, classified under several viral families such as Bunyaviridae, Togaviridae, Flaviviridae, Reoviridae, Rhabdoviridae, and Orthomyxoviridae [7,8].
The family Flaviviridae comprises four genera: Flavivirus, Pestivirus, Hepacivirus, and Pegivirus [9]. Among these, the genus Flavivirus is responsible for some of the most severe arboviral infections known to affect humans [10]. Flaviviruses that have the ability to invade the CNS and cause infections are regarded as neurotropic [11]. Notable neuroinvasive flaviviruses include dengue virus (DENV), West Nile virus (WNV), Japanese encephalitis virus (JEV), Zika virus (ZIKV), and tick-borne encephalitis virus, all of which demonstrate the ability to cross the blood-brain barrier and establish infection within the CNS [12,13]. Among these, DENV stands out due to its high prevalence and public health impact in endemic regions, including Sri Lanka [10].
DENV is a mosquito-borne flavivirus that is primarily transmitted by Aedes species, which is classified into four distinct serotypes, DENV-1, DENV-2, DENV-3, and DENV-4 [14]. Among these, DENV-2 and DENV-3 are more frequently associated with neurotropism, exhibiting a greater propensity to invade the CNS [15]. Neurological manifestations of dengue infection include altered consciousness, seizures, headache, and meningeal signs [16].
Encephalitis and meningoencephalitis have been reported in approximately 4%-21% of dengue cases, which highlights the neuroinvasive potential of the virus. In Sri Lanka, dengue fever continues to pose a significant health burden, with the country recording its third-largest outbreak in 2023 (89799 cases and 62 deaths), following outbreaks in 2017 (186101 cases and 440 deaths) and 2019 (105049 cases and 157 deaths) [17]. Given the significant burden of dengue-related neurological diseases and other CNS infections, enhanced clinical awareness is essential.
Early and effective treatment of CNS infections depends on rapid and accurate diagnosis. However, clinical diagnosis is often challenging due to the non-specific and overlapping symptoms of CNS infections, which may be caused by a wide range of pathogens including viruses, bacteria, fungi, and protozoa. Clinical observations are not particularly useful in determining the specific CNS infection [18].
Therefore, laboratory-based investigations are essential [19]. These include molecular techniques such as polymerase chain reaction (PCR), cell culture of cerebrospinal fluid (CSF), and serological tests like enzyme-linked immunosorbent assay (ELISA) for detecting pathogen-specific immunoglobulin (Ig) M or IgG antibodies in CSF or serum [20]. Among these, CSF is the most widely used specimen type in the diagnosis of CNS infections [21]. In developing countries such as Sri Lanka where CNS infections are more prevalent, diagnosing them poses significant challenges. These are due to the limited access to rapid diagnostic facilities and lack of epidemiological data. Although nucleic acid-based diagnostics facilitate rapid and accurate diagnosis, they are not readily available in developing countries. In such contexts, preliminary diagnoses and treatment decisions often rely heavily on understanding local disease patterns. Unfortunately, comprehensive epidemiological data remains scarce. In Sri Lanka, information regarding the causes of CNS infections is limited. There is a clear need for national-level research into the aetiology of CNS infections. The objective of this study was to detect dengue and other flavivirus infections in clinically suspected patients with encephalitis.
## MATERIALS AND METHODS
## Study design
This was a retrospective, cross-sectional, observational study.
## Ethical approval
This study protocol was approved by the Research and Ethics Committee of the National Hospital Kandy, approval No. NHK/ERC/11/2021. Informed consent was waived due to retrospective nature of the study and data dissemination without any personal identification data.
## Samples and study population
This study was designed as a retrospective, observational analysis conducted at the Department of Molecular Biology, Medical Research Institute and National Hospital Kandy, Sri Lanka. The remaining portions of stored CSF samples received to the virology laboratory for routine diagnosis in central part of the country from patients with suspected CNS infections (meningitis and encephalitis) from January 2023 to December 2023 were utilized in this study.
During that period 211 CSF samples were received at the laboratory from clinically diagnosed patients with encephalitis for laboratory diagnosis. Of them only 198 samples had adequate remaining volume (at least 150 μL of volume), and every other sample was selected to the study based on laboratory serial number.
All the samples were stored at -80 °C under continuous temperature monitoring. The clinical diagnosis of CNS infections of the patients was made by specialists in neurology.
## Molecular detection of viral RNA
Reverse transcriptase PCR (RT-PCR) was performed on 99 CSF samples to detect flaviviral RNA according to the method described by Tanaka [22].
Viral RNA was extracted from CSF samples using the QIAamp Viral RNA Mini Kit (QIAGEN ® , Germany), a locally validated commercial kit, following the manufacturer's protocol. From each sample, 60 μL of RNA eluate was obtained and subsequently stored at -70 °C until further analysis.
Universal primers targeting flaviviruses were selected based on the published protocol by Tanaka [22] and synthesized by Integrated DNA Technologies, United States. The primer pair used in this study based on yellow fever (YF), YF-1 (5′-GGTCTCCTCTAACCTCTAG-3′) and YF-3 (5′-GAGTGGATGACCACGGAAGACATGC-3′) was originally designed to maximize homology across six flaviviruses (YF, MVE, JEV, DENV-2, DENV-3, and DENV-4) [22]. These primers were derived from the yellow fever virus 17D vaccine strain, based on the nucleotide sequence reported by Rice et al [23]. The primer binding region corresponds to a highly conserved sequence spanning the nonstructural protein 5 and the 3′untranslated region, specifically nucleotides 10709-10052 of the yellow fever virus genome [22].
In-house RT-PCR was performed in 25 μL reaction volumes using Promega reagents (Promega, United States) according to the manufacturer's instructions. The final concentration of each Flavivirus universal primer (YF-1 and YF-3) was 20 μM. Each reaction mixture contained 12.5 μL of 2 × qPCR Master Mix, 0.5 μL of GoScript Reverse Transcriptase, 1 μL each of the universal primers YF-1 and YF-3, 5 μL of nuclease-free water, and 5 μL of extracted RNA. Extracted Japanese encephalitis (JE) vaccine (27 infectious units per mL) was used as a positive control, while nuclease-free water served as the negative control in all reactions. Amplification was carried out using the Bio-Rad CFX 96 thermal cycler (Bio-Rad, United States), following a modified protocol from Tanaka [22]. The protocol was adapted by including an initial denaturation at 95 °C for 10 minutes, increasing the number of amplification cycles to 35, and adding a final extension at 72 °C for 5 minutes. The reaction was held at 4 °C until further analysis.
PCR products were analyzed by agarose gel electrophoresis. A 20 g/L agarose gel was prepared in Tris-borate-EDTA buffer. For each sample, 10 μL of PCR product was mixed with 2 μL of loading dye and loaded onto the gel alongside a 100 bp DNA ladder. Electrophoresis was performed at 100 V for 50 minutes, and DNA bands were visualized under UV illumination. Gel images were captured using a POLAR camera system (Bio-Rad, United States) and analyzed using Quantity One ® software.
The analytical sensitivity of the RT-PCR assay was evaluated using a serial dilution of the JE vaccine. The lowest detectable concentration was determined to be 2.7 × 10 -1 infectious units per mL. Analytical specificity was assessed using RNA and DNA from non-flaviviral viruses, including Measles, Mumps, Rubella, severe acute respiratory distress syndrome corona virus-2, and Human Bocavirus. No amplification was observed with these controls, confirming that the universal primers targeting the nonstructural protein 5 region of the flaviviral genome exhibited 100% specificity.
A real-time reverse transcription PCR assay was conducted to determine DENV serotypes in dengue-positive elutes using dengue-specific primers and probes. The final concentration of primers and probes was 20 μM. Each reaction was carried out in a total volume of 25 μL using Promega reagents (Promega, United States), according to the manufacturer's instructions. A volume of 5 μL of extracted RNA was added to the RT-real-time reverse transcription PCR mixture. Positive controls for each serotype (DENV-1 to DENV-4) and nuclease-free water as a negative control were included in each run. Amplification was conducted on a Bio-Rad CFX96 thermal cycler (Bio-Rad, United States) using a previously optimized thermal cycling protocol. The cycling conditions consisted of reverse transcription at 45 °C for 15 minutes, initial denaturation at 95 °C for 10 minutes, followed by 44 cycles of annealing at 95 °C for 0.15 minutes, and extension at 60 °C for 0.45 minutes. The reaction was held at 4 °C until further analysis.
## Dengue IgM capture ELISA
Commercial dengue IgM-capture ELISA (IgM-ELISA) was carried out on 68 CSF samples with adequate sample volume to detect IgM antibodies indicative of a possible recent dengue/flavivirus infection.
The SERION ELISA classic DENV superior IgM kit (Cat No. ESR114m, Serion Immunodiagnostica, Germany), a commercially available and locally validated assay, was used for this purpose. This kit has reduced cross -reactivity among other flaviviruses based on manufacturer's claim. Kit sensitivity of 96.2% and a specificity of 99.3%. Due to the welldocumented antigenic similarities among flaviviruses, the assay may detect cross-reactive IgM antibodies elicited by infections with related flaviviruses such as ZIKV, JEV, or WNV. Therefore, positive results were interpreted as indicative of probable recent DENV infection, but not necessarily specific to DENV. The remaining 68 CSF samples with sufficient volume were subjected to testing.
The assay was performed according to the manufacturer's protocol with modification to sample volume to accommodate CSF after local validation. Each sample (10 μL) was diluted 1:10 in dilution buffer (100 μL) and added to designated wells of a 96-well microtiter plate. Cut-off values were calculated as per the manufacturer's guidelines to determine positivity.
Clinical, laboratory and surveillance records of Dengue PCR and IgM positive samples were traced retrospectively and data was obtained. Only clinical diagnosis, age distribution (child or adult), resident district and microbiological investigation results analyzed anonymously.
## RESULTS
All selected CSF samples were collected from patients who had clinical features of encephalitis or both meningitis and encephalitis, according to the treating clinician. Of these patients, sixty were from pediatric (< 14 years) age group, and the remainder were from adults. Among the 99 CSF samples analyzed, probable DENV aetiology was identified in 6 samples (6.06%). Of these, one sample (1.01%) was confirmed by RT-PCR, while five samples (5.05%) were identified using IgM-ELISA. There was no overlap between the positive results of the two methods; the RT-PCR-positive sample tested negative by ELISA, and all five ELISA-positive samples were negative by RT-PCR. Positive cases were geographically concentrated in the Kandy and Matale districts (Figure 1). Among the six positive patients, two were pediatric cases and four were adults (Table 1).
The RT-PCR positive sample produced a distinct band between 500-600 base pairs on agarose gel electrophoresis (Figure 2), consistent with DENV amplification as reported by Tanaka [22].
Based on this observation, real-time RT-PCR was conducted on the same eluate using DENV-specific primers and probes targeting all four serotypes (DENV-1 to DENV-4) to confirm the presence of DENV and identify the specific serotype. A clear amplification curve was observed (Figure 3), with a quantification cycle value of 23.27, confirming the presence of DENV-3 as the causative agent of CNS infection in this case.
IgM-ELISA was conducted on 68 CSF samples selected from the original pool of 99, based on the availability of adequate sample volume. Samples with insufficient remaining volume were excluded from ELISA testing. Of the 68 samples tested, five (7.35%) were positive for anti-dengue IgM antibodies. Since there was no overlap between the ELISA and RT-PCR positive results, these five ELISA-positive cases were considered out of the 99 samples analyzed, corresponding to an overall positivity rate of 5.05%.
Based on the diagnostic laboratory data, those five samples were negative for Herpes Simplex virus, Varicella zoster virus, Cytomegalovirus, Epstein-Barr virus and alphavirus genome by PCR and bacterial cultures were negative. Under acute encephalitis syndrome, all suspected cases with encephalitis are investigated for JE by the National JE Surveillance Laboratory and Epidemiology Unit. Based on surveillance data, these five cases were excluded for JE.
## DISCUSSION
This study was conducted to identify the causative agents of CNS infections, with a particular focus on DENV due to their known role in viral meningitis and encephalitis globally, including in Sri Lanka. Notably, most published studies on flavivirus-associated CNS infections have focused on the Western Province. This study investigates the population in the Central Province, encompassing Kandy, Matale, and Nuwara Eliya districts, which collectively comprise the secondlargest population in the country. A notable increase in dengue cases was recorded in this region in 2023, ranking third highest number of reported dengue cases in Sri Lanka, underscoring the need for region specific research into neuroinvasive viral pathogens. A similar study by Lohitharajah et al [24] in Colombo identified a viral aetiology in 27.3% of patients, with flaviviruses accounting for 21.21%. This means that 78.79% of cases had no confirmed viral cause. Similarly, in the present study, flaviviral aetiology was identified in only 6.06% of samples. These discrepancies may reflect regional epidemiological variations, differences in the periods of data collection, or the use of different clinical samples and diagnostic methods. Across both developed and developing regions, a majority of meningitis and encephalitis cases remain without a confirmed cause, with undiagnosed proportions reported to exceed 50% and reach as high as 85% despite comprehensive diagnostic efforts [25,26] herpes simplex virus type 1 and type 2, varicella zoster virus, human bocavirus type 1, 2 and 3, human adenovirus type 41, Echovirus type 9 and 25, and Cytomegalovirus have been reported up to 2022 in patients with meningitis and encephalitis [3]. Given that a significant proportion of CNS infections remain undiagnosed, future research should prioritize the detection of other neurotropic viruses, particularly enteroviruses and alphaviruses. Autoimmune CNS diseases are also increasingly recognized, with one study from the United States reporting 26% of cases as immune-mediated [27]. The California Encephalitis Project also found a significant number of cases to be caused by anti-N-methyl-D-aspartate receptor antibodies rather than by viral agents, highlighting the importance of considering immune-mediated aetiologies in future studies [28].
In recent years, several molecular diagnostic techniques employing generic approaches have been developed for detecting flavivirus infections. Various research groups have proposed universal primer sets designed to amplify conserved regions particularly those encoding non-structural proteins across a broad range of flavivirus genomes [29,30]. Kuno [31] recommended a two-stage diagnostic strategy, an initial screening using broad-range, group-reactive primers to detect the presence of flaviviruses at the genus level, followed by the use of species-specific primers to accurately identify the infecting virus.
This two-step approach was adopted in the present study. Initial detection was performed using a conventional RT-PCR assay targeting conserved flavivirus genomic regions with universal primers, allowing broad-spectrum detection in a setting where multiple flaviviruses may co-circulate. Upon identification of a positive band, a second round of testing was carried out using real-time RT-PCR with DENV specific primers (targeting serotypes 1 to 4), which confirmed the presence of DENV-3. This sequential approach of broad-range detection followed by specific confirmation enhanced diagnostic sensitivity in the initial phase and improved specificity in the confirmatory step.
The patient who tested positive for DENV-3 was initially clinically diagnosed with suspected dengue fever and later developed encephalitis. This finding is consistent with previous research in Sri Lanka. In 2009, all four DENV serotypes co-circulate in the country, serotypes 2 and 3 have been the predominant causes of clinically apparent cases.
Although DENV-3 was the dominant strain prior to 2009, it was notably absent from surveillance data between 2009 and mid-2016. However, a resurgence of DENV-3 cases was observed from late 2019 onward [32]. A large-scale study conducted in western part of the country; among 1796 clinically suspected dengue patients between May 2019 and April 2021 revealed that 472 cases (37.97%) were due to DENV-3. Notably, all cases of dengue-associated encephalitis in that cohort were attributed to the DENV-3 serotype [33]. The findings of the current study align with this trend, further reinforcing the association between DENV-3 and neurological complications such as encephalitis.
This study used both RT-PCR and ELISA to identify DENV infections. RT-PCR targeted viral RNA while ELISA detected IgM antibodies. The RT-PCR-positive sample was negative in ELISA, and none of the ELISA-positive samples were confirmed by RT-PCR. These differences can be attributed to the distinct diagnostic windows of the two methods.
Although cross-reactivity with JEV was excluded through specific testing, the possibility of serological cross-reactivity with other flaviviruses such as ZIKV and WNV cannot be entirely ruled out. However, based on local epidemiological data, ZIKV infections show very low prevalence in Sri Lanka, with only a limited number of antibody positives reported in previous studies [34,35]. Similarly, WNV IgM detection in serum samples was reported once in Sri Lanka [36].
Flaviviruses typically exhibit a short viremic period, during which the virus can be detected in the serum or plasma of infected individuals, most often within the first 5 days after the onset of the disease. The likelihood of detection significantly decreases after the first week as viremia clears. The likelihood of detection significantly decreases after the first week as viremia clears. RT-PCR was likely unable to detect the virus in ELISA-positive cases because those samples were collected after the viremic phase had ended [37]. However, conducting RT-PCR during this brief viremic period is challenging and may not always be feasible.
In contrast, the decrease in viremia coincides with the appearance of IgM antibodies. Following the onset of symptoms, around 5-7 days into the infection, the body begins to mount an immune response against the invading virus. IgM antibodies are among the first antibodies to be produced during this immune response, and they reach their peak levels in the bloodstream around 15 days after the onset of symptoms. In some cases, such as with DENV infections, IgM antibodies may persist in the bloodstream for several months following the acute phase of the infection [38]. In other instances, such as WNV infection, IgM antibodies may persist in the bloodstream for even longer periods, lasting for years after the initial infection. The presence of IgM antibodies serves as a marker of recent or ongoing infection and can be detected through serological tests like ELISA [39]. Although IgM kit with less cross reactivity was used in this study, certain degree of cross reactivity cannot be ruled out without neutralization assays. Detection of IgM antibodies can serve as a valuable diagnostic tool for detecting flavivirus infections, particularly during the convalescent phase when viral RNA may no longer be detectable by PCR. These findings underscore the necessity of employing both serological and molecular methods in flavivirus diagnostics.
Although specific antiviral treatments for dengue and other flavivirus infections are currently unavailable, accurate diagnosis remains crucial for patient care and public health measures. Early identification enables timely supportive management, such as hydration, pain management, and supportive therapies to address neurological symptoms, which can significantly influence patient outcomes. Moreover, diagnosis of CNS infections of dengue facilitates better epidemiological understanding and informs region-specific surveillance and vector control strategies, particularly relevant in a country like Sri Lanka.
## CONCLUSION
This study demonstrates the presence of DENV-associated CNS infections in the Central Province of Sri Lanka, with a 6.06% positivity rate among suspected encephalitis cases. DENV-3 was identified as the causative agent in one patient, reinforcing its established association with neurological complications. The differences observed between RT-PCR and IgM-ELISA results underscore the importance of integrating both molecular and serological tools to improve diagnostic accuracy. These findings underscore the importance of sustained surveillance, advanced diagnostic capacity, and broader investigation into other viral and immune-mediated causes of CNS infections to reduce the proportion of CNS infections that remain undiagnosed and improve patient outcomes in Sri Lanka.
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# Cost-effectiveness of cervical cancer screening among women living with HIV in India: study protocol
Amit Pundalik Nirmalkar, Megha Mamulwar, Sheela Godbole, Mohammed Sheikh, Shahabuddin, Shilpa Bembalkar, Akashdeep Chauhan, Akashdeep Singh Chauhan
## Abstract
Introduction Women living with HIV (WLHIV) face a higher risk of developing cervical cancer. India carries a significant burden of HIV, with an estimated 2.5 million people living with HIV in 2023. While the introduction of more effective antiretroviral therapy has improved the life expectancy of WLHIV, it has also extended the risk window for persistent human papillomavirus (HPV) infection and cervical disease progression. Cervical cancer prevention through HPV vaccination and regular screening remains the cornerstone of public health efforts. This study specifically aims to evaluate the cost-effectiveness of various cervical cancer screening strategies (at different intervals) among WLHIV in India. Methods and analysis The study will be conducted in three interlinked components. First, a meta-analysis will be undertaken to evaluate the diagnostic accuracy of different screening strategies in detecting cervical lesions in WLHIV. Second, primary data collection will be carried out to estimate the treatment costs of cervical cancer and HIV among WLHIV. This phase will also include the collection of health-related quality of life (HRQoL) data, to inform utility estimates for the modelling component. A total of 135 participants will be enrolled for cost data assessment. Of these, a subset of 71 participants will also be included for HRQoL assessment. This data collection will be undertaken in four tertiary public sector hospitals located across four Indian states, that is, Mizoram, Maharashtra, Tamil Nadu and Karnataka. Lastly, a decision analytical model will be developed to simulate the process of screening, diagnosis and treatment for cervical cancer in a hypothetical cohort of WLHIV. A structured comprehensive review of literature will be undertaken to inform model input parameters related to the natural history of cervical disease, progression and mortality among WLHIV. Model calibration will be performed using a likelihood-based approach to ensure consistency with empirical epidemiological data. Probabilistic sensitivity analysis will also be conducted to assess the impact of joint parameter uncertainty on model outcomes.
## INTRODUCTION
Cervical cancer continues to pose a significant health challenge for women living with HIV (WLHIV), largely because they are more vulnerable to persistent human papillomavirus (HPV) infection and the development of related cervical lesions. 1 HIV-positive women have approximately 2.6 times higher relative risk of acquiring HPV and demonstrate a lower HR for HPV clearance, resulting in a sixfold increased risk of developing cervical cancer compared with the general population. 2 3 India carries a significant burden of HIV, with an estimated 2.5 million people living with HIV (PLHIV) in 2023. 4 Among them, approximately 68 000 were newly infected, and around 36 000 deaths were attributed to the disease that year. 4 Despite a significant
## STRENGTHS AND LIMITATIONS OF THIS STUDY
⇒ The study combines a meta-analysis, primary cost and health-related quality of life data, and a decision analytical modelling to assess the costeffectiveness of cervical cancer screening strategies among women living with HIV in India. ⇒ The use of real-world cost data and patient-incurred expenditures, along with likelihood-based model calibration, enhances the robustness of the study findings. ⇒ A component of cost data will be collected retrospectively and may be subject to recall bias, despite efforts to minimise this through structured interviews and short recall periods. ⇒ Although a societal perspective will be adopted, indirect costs will be limited to patients' and caregivers' time lost while accessing care.
Open access reduction in the incidence of HIV infection over the last two decades, India remains the third-highest country globally in terms of the absolute number of PLHIV. 5 Moreover, while the introduction of more effective antiretroviral therapy (ART) has improved the life expectancy of WLHIV, the increased lifetime has inadvertently increased the risk of exposure to persistent HPV infection and the likelihood of progression to invasive cancer over time. 6 Cervical cancer prevention through HPV vaccination and regular screening remains the cornerstone of public health efforts. While HPV vaccination offers primary prevention by reducing the risk of HPV infection, periodic screening facilitates early detection of cervical lesions, allowing for timely intervention. 7 In India, the national guidelines recommend population-based screening using visual inspection with acetic acid (VIA) every 5 years for women aged 30-65 years. 8 However, given the heightened risk profile of WLHIV, more intensive and frequent cervical cancer screening is required. 9 The WHO recommends that WLHIV undergo screening for cervical lesions every 3 years, beginning at age 25. 10 Likewise, Indian guidelines suggest that WLHIV should be screened every 3 years starting at ART initiation, with VIA as the primary screening method. 11 Considering India's concurrent burden of HIV and cervical cancer, there is a critical need to generate evidence on the most cost-effective cervical cancer screening modality tailored for WLHIV. While several studies from African settings have evaluated the cost-effectiveness of cervical cancer screening in WLHIV, [12][13][14][15] there is no evidence from India. Although the cost-effectiveness of screening and HPV vaccination has been studied for the general population in India, optimal screening strategies for WLHIV remain unexplored. 7 In this context, the present study aims to evaluate the cost-effectiveness of various cervical cancer screening strategies at different intervals among WLHIV in India. The screening modalities considered include VIA, Pap smear, HPV DNA testing, VIA followed by Pap smear, VIA followed by HPV DNA testing and Pap smear followed by HPV DNA testing. Each strategy will be assessed at four screening intervals: every 6 months, annually, biennially and triennially, to determine the optimal screening frequency. The findings from this study will provide critical evidence to inform policymakers in developing targeted and effective screening guidelines for cervical cancer prevention in WLHIV.
## METHODS AND ANALYSIS Overview
The study will be conducted in three interlinked components, as illustrated in figure 1. First, a systematic review and meta-analysis will be undertaken to evaluate the diagnostic accuracy of different screening strategies in detecting high grade cervical lesions in WLHIV. Second, primary data collection will be carried out to estimate the treatment costs of cervical cancer and HIV among WLHIV. This phase will also include the collection of health-related quality of life (HRQoL) data, both before and after cervical cancer treatment, to inform utility estimates for the modelling component. Lastly, a decision analytical model will be developed to simulate the process of screening, diagnosis and treatment for cervical cancer in a hypothetical cohort of WLHIV. The model will be populated with a wide range of parameters, including the effectiveness of screening methods, costs associated with screening and treatment, epidemiological data on the natural history of cervical disease, utility
## Systematic review and meta-analysis
This systematic review and meta-analysis aims to compare the diagnostic accuracy measures of various cervical cancer screening methods among WLHIV.
A computerised literature search on PubMed, Cochrane and Embase will be undertaken for the identification of relevant studies. An initial comprehensive search strategy will be developed using controlled vocabulary and keywords for PubMed and subsequently adapted for Cochrane and Embase to ensure consistency and completeness in study retrieval.
## Study selection criteria
Inclusion criteria include original, peer-reviewed research articles published in English that assess the diagnostic accuracy of screening for high grade cervical lesions in WLHIV. PICO framework would be followed to define the scope of the review. Population (P) will comprise HIVinfected women (WLHIV); intervention (I) will constitute various cervical cancer screening methods, used alone or in combination, including VIA, VILI, cytology and HPV DNA testing; comparator (C) will be biopsy or colposcopy-directed biopsy (as the reference standard) and outcomes (O) would consist of diagnostic accuracy measures including sensitivity, specificity and predictive values. We will include all types of diagnostic accuracy studies in the review, including cross-sectional studies, prospective and retrospective cohort studies, case-control and randomised or non-randomised trials that report a diagnostic component. Ecological studies, case series and studies reporting test positivity without disease verification will be excluded. Further, conference abstracts, oral or poster presentations, and studies not specifically focused on cervical cancer screening/diagnosis in WLHIV will also be excluded. No regional or country restrictions will be applied to maximise inclusion.
## Study selection and data extraction
The initial database search will generate a list of potentially relevant studies. Duplicate entries will be removed, and two independent reviewers will conduct the initial title and abstract screening to identify eligible articles. Any discrepancies between reviewers will be resolved through discussion and consensus. Studies with inaccessible full texts will be excluded, and all reasons for exclusion will be documented. Full-text screening will then be performed on the remaining articles by the same reviewers to ensure that inclusion and exclusion criteria are strictly applied. Additional studies identified through manual cross-referencing of reference lists of selected full-text articles will also be assessed for inclusion. All reporting will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (online supplemental annexure I). 16 Data extraction and risk of bias assessment will be conducted independently by two reviewers. The risk of bias will be assessed using the QUADAS-2 tool. 17 Data will be extracted using a predesigned data extraction form (online supplemental annexure II). Information collected will include the year of publication, study design, study population baseline characteristics, sample size, country, screening method/ tool, threshold for the definition of a positive screening result, outcomes and authors' conclusions. All screening decisions, extracted data and analysis files will be securely stored.
## Quantitative data extraction for meta-analysis
For each included study, data will be extracted on the diagnostic performance of each screening test, as defined by the histologically confirmed threshold. The extracted data will include the number of true positives (TP), false negatives (FN), false positives (FP) and true negatives (TN), as determined by the reference standard (biopsy or colposcopy-directed biopsy). In cases where studies do not directly report these values, they will be calculated based on the information provided in the articles. The extracted diagnostic data will be organised into 2×2 contingency tables for each screening modality. If data are suitable for quantitative synthesis, pooled estimates of sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) will be calculated using meta-analytic models.
## Statistical analysis
Pooled estimates of diagnostic accuracy including sensitivity, specificity, PPV and NPV will be calculated using a bivariate random-effects model. Forest plots would be generated for showing the overall pooled estimates and summary receiver operating characteristic curves will be generated to explore study-level variations and heterogeneity. Potential sources of heterogeneity will be explored through subgroup analyses. Statistical heterogeneity will be assessed using I² and explored through subgroup analyses. Publication bias will be assessed using funnel plots. Subgroup analyses (where sufficient data are available) will be undertaken stratified by country income levels, study design and risk of bias (high vs low risk). If quantitative synthesis is not appropriate due to Open access substantial heterogeneity or insufficient data, findings will be summarised using a narrative synthesis.
## Cost of cervical cancer treatment in WLHIV
As outlined above, primary data will be collected to estimate the costs incurred during cervical cancer and HIV treatment. This will include the assessment of both direct and indirect costs. Direct medical part will cover costs incurred on cancer diagnosis (such as biopsy, CT scan, X-ray and blood tests), treatment (including surgical hysterectomy, radiotherapy, chemotherapy, brachytherapy and palliative care), and HIV management (including routine diagnostics, outpatient consultations and ART medications). The direct non-medical component will estimate the expenses incurred on travel, boarding/lodging and food for seeking cancer/HIV treatment. Indirect costs will capture productivity loss incurred by patients and their caregivers.
## Study setting and design
Cost data will be collected through face-to-face interviews with WLHIV undergoing or initiating treatment for cervical cancer. The study will be conducted in the oncology departments of four tertiary-care public sector hospitals located in states of Mizoram, Maharashtra, Tamil Nadu and Karnataka. Two distinct methodologies will be employed for patient recruitment. Patients in the first group will be recruited on registration for cancer treatment and followed prospectively for a period of 9 months post-treatment. This group will be interviewed on a daily or weekly basis throughout the treatment period, followed by additional interviews at the 3rd, 6th and 9th month during follow-up visits.
The second group will include patients who have already completed their cancer treatment. They will be recruited during routine follow-up visits occurring between 3 and 9 months post-treatment. These participants will be interviewed retrospectively to collect information on treatment-related costs incurred prior to recruitment. Importantly, if the time since treatment completion is less than 9 months at the point of enrolment, these patients will be prospectively followed until completion of 9 months, identical to the follow-up period of the prospective group. These retrospective interviews may be prone to recall bias and susceptible to incomplete or inaccurate recall of past expenditures. To minimise this bias, the following two strategies will be employed. First, retrospective recruitment is limited to a relatively short recall window (maximum of 9 months post-treatment), which is expected to reduce memory decay. Second, participants will be encouraged to refer to medical bills, prescriptions, hospital records and other relevant documents wherever available during the interview. This design ensures a uniform time horizon for cost data collection across both groups.
Consecutive sampling will be employed, whereby all eligible women attending the participating centres during the data collection period will be approached until the required sample size is achieved. For the first group of patients, all new registrations during the data collection period will be approached daily for recruitment. For the second set, all postoperative cases visiting the outpatient department for follow-up will be invited to participate. Potential participants will be identified in coordination with the treating oncology team during routine outpatient visits. Eligible women will be approached by trained research staff, provided with detailed study information and invited to participate. Written informed consent will be obtained prior to enrolment. Interviews will be conducted in a private setting within the hospital, at a time convenient for the participant, to ensure confidentiality and comfort. Trained interviewers will administer the interview schedule.
## Data collection
The cost data will be collected using a pretested, semistructured interview schedule adapted from previously published costing studies. [18][19][20] The tool has been contextually modified to suit the study population and has been pilot tested among 10 HIV-positive women (diagnosed with cervical cancer) at a tertiary care hospital in Pune for clarity, relevance and feasibility. A copy of the interview schedule is included in online supplemental annexure III.
The schedule has been designed to capture information on socio-demographic details, disease profile, healthcare resource use and patient-incurred out-of-pocket (OOP) expenditures including the indirect costs. Data on resource use encompass information on the volume of healthcare services consumed during the course of treatment including diagnostics, outpatient visits, hospital admissions, surgical interventions, radiotherapy, chemotherapy, brachytherapy and supplies (including medications). Information on the type and quantity of resource use (during the treatment duration and follow-up period) will be verified from patient files and hospital records, where accessible.
OOP expenditure will capture any additional direct medical and non-medical expenses incurred during the course of treatment. These expenditures will be validated using payment receipts and bills available with the patients. The section on indirect costs will capture the productive time lost both by patients and their caregivers during the course of treatment.
## Sample size and data analysis
The sample size was calculated using the following
; where N=required sample size; µ₀=population mean; µ₁=expected mean in the study population; σ=SD deviation; α=type I error probability; β=type II error probability. Based on the reported mean expenditure of INR 35 741 18 incurred on the treatment for cervical cancer treatment, with an SD of INR 22 272, and an anticipated 15% increase in costs, the required sample size has been calculated to be 135 participants,
$$formula N = σ 2 ( Z 1-β +Z 1-α/2 ) 2 ( µ 0 -µ 1 )2$$
## Open access
based on a significance level of 0.05 and a power of 80%.
To achieve this target, the study will prioritise enrolling prospective patients during the first 6 months of data collection. After this 6-month period, any remaining sample will be enrolled retrospectively. This dual strategy will ensure timely data collection, while adhering to the study timelines. The data will be analysed using Microsoft Excel and STATA (V.12.1). For the valuation of healthcare resources (or services), the price (or unit cost) data will be assessed from various sources including the reimbursement package rates of Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (AB PM-JAY), 21 National Health System Cost Database (NHSCD) of India 22 and other published estimates. The reimbursement rates represent the amount reimbursed by the payer and are commonly used as a proxy for the opportunity cost of healthcare resources. OOP expenses, in contrast, will be captured directly from patients based on self-reported expenditures incurred while seeking care.
Specifically, the cost of primary treatment therapies (surgery, radiotherapy, brachytherapy and chemotherapy) will be assessed from the AB PM-JAY package rates. Unit costs for outpatient consultations, inpatient stays and daycare services (which are not specifically mentioned in AB PM-JAY package rates) will be sourced from the NHSCD or relevant published studies. The valuation of drugs and consumables will depend on the source of procurement. If borne by patients, these costs will be captured as part of OOP expenditures. If provided by the health system, reimbursement prices from the NHSCD will be used. For diagnostics, unit cost estimates from published literature will be applied.
Data from both prospective and retrospective patient groups will be combined to estimate mean (and median) cancer stage-specific treatment costs. Direct costs incurred over the 9-month follow-up period will be estimated both cumulatively and at specific time points-namely, at the end of treatment, and at 6 and 9 months post-treatment. Indirect costs will be calculated using the human capital approach, incorporating wage losses for both patients and caregivers during the treatment period and the 9-month follow-up. CIs will be derived using the bootstrap method. To examine cost variations across socioeconomic and disease-related characteristics, generalised linear models (GLMs) will be employed. 23 GLMs are particularly suitable for this analysis due to their ability to accommodate skewed distributions, heteroskedasticity and non-linear relationships between predictors and cost outcomes.
## Quality of life
The HIV patients recruited as a part of cost data collection will also be interviewed for assessing their QoL. These patients will be interviewed both before the start of the cancer treatment, on completion of treatment, and at 3 and 6 months post-treatment. These time points have been carefully selected to capture changes in QoL, reflecting both the immediate deterioration due to the side effects of chemo-radiotherapy and the subsequent stabilisation of QoL as the impact of treatment wears off. Eligibility criteria will include patients receiving treatment for histologically confirmed cervical cancer, classified between stages I and IVb according to the International Federation of Gynecology and Obstetrics (FIGO) classification. QoL will be assessed using the EuroQol 5 Dimension 5 Level questionnaire (EQ-5D-5L) and the EuroQol Visual Analogue Scale (EQ-VAS). The EQ-5D-5L tool (online supplemental annexure IV) has been used widely in cancer studies 24 and is considered the gold standard for measuring QoL and calculation of quality-adjusted lifeyears (QALY). The necessary rights to use the EQ-5D-5L instrument for assessing participants' HRQoL have been obtained from the EuroQol Research Foundation.
## Sample size and data analysis
The sample size is based on a previously estimated mean utility score of 0.70 (with SD of 0.21) in cervical cancer patients. 25 Given that our study focuses on an HIV plus cervical cancer population, we anticipate a 10% decrease in QoL with HIV infection. Considering this 10% decrease and based on a significance level of 0.05 and a power of 0.80, the sample size is estimated to be 71 using the following formula:
(where N=required sample size, µ₀=Population mean, µ₁=Expected mean in the study population, σ=SD deviation. α=type I error probability, β=type II error probability).
The utility scores will be estimated by applying the Indian tariffs, which are country-specific value sets used to translate health states captured through EQ-5D-5L into a single summary index representing the individual's health-related QoL in a particular. 26 A maximum utility score of 1 indicates full health, while a score of 0 represents death. Similar to cost data, stage-specific mean utility scores will be estimated for patients based on FIGO classification-stages I, II, III and IV.
$$N = σ 2 ( Z 1-β +Z 1-α/2 ) 2 ( µ 0 -µ 1 )2$$
## Decision analytical model
The study will adapt a previously published Markov model representing the natural history of HPV infection and cervical disease and will expand it to evaluate the cost-effectiveness of cervical cancer screening strategies among WLHIV in India. 7 This model will be modified to account for the natural history of HIV disease and characteristics of a high-risk HIV cohort. The model will incorporate inputs from frameworks developed by Goldie et al, Vaani et al and Campos et al, which have been extensively used to model cervical cancer outcomes among WLHIV. [27][28][29] The model will simulate the life course of a hypothetical cohort of WLHIV in India, beginning at approximately 25 years of age, which reflects the median age of HIV diagnosis among Indian females. Following diagnosis, these women will be assumed to initiate ART immediately and undergo regular cervical cancer screening in line with Indian guidelines. The model will run in 6-month Open access cycles over the cohort's lifetime. Future costs and health outcomes beyond the first year will be discounted at an annual rate of 3%. A societal perspective will be adopted, incorporating direct medical costs, direct non-medical expenses (as OOP expenses), and productivity losses attributable to time lost by patients and their caregivers while accessing healthcare.
## Model structure
The hypothetical cohort of the HIV-infected population will enter the model in health states defined by their HIV status and cervical disease. The natural history of cervical disease will be represented through the following health states: HPV infection, cervical intraepithelial neoplasia grade 1 (CIN 1), CIN 2 or CIN 3, and invasive cervical cancer (further stratified by FIGO stages I to IV) as shown in figure 2. Each of these health states will be further stratified by CD4 cell count, with three CD4 strata: >500 cells/ mm³, 200-500 cells/mm³ and <200 cells/mm³. In line with existing evidence, the present study will focus exclusively on HPV infections caused by high-risk HPV types, which are responsible for approximately 85% of cervical cancer cases in India.
The model will use 6 monthly transition probabilities to simulate the progression of women through different health states over time. At the beginning of each Markov cycle, depending on their current health state, women may die from HIV/AIDS (excess mortality risk from HIV), cervical cancer or other causes. Those who survive will face probabilities of disease progression (or regression) for both cervical and HIV disease. The probability of cervical disease progression will be influenced by the stage of HIV disease, with women having higher CD4 counts experiencing slower progression as compared with those with lower CD4 counts, representing that a more immune-compromised state will face higher progression rates.
Women will also be assumed to transition between CD4 count strata over time, with these transitions governed by probabilities influenced by factors such as adherence to ART, susceptibility to opportunistic infections and overall immune response. Within each CD4 stratum, all precancerous lesions will be assumed to result from persistent HPV infection, with the possibility of regression depending on the individual's immune status or treatment. For instance, women in CIN 2/3 may regress to CIN 1 or clear the HPV infection entirely, and those in CIN 1 may return to a state without HPV infection. However, persistent HPV infection may lead to an irreversible progression from CIN 2/3 to invasive cancer. Women who receive treatment for cervical cancer will be assumed to have stage-specific survival rates, with the model no longer tracking cancer progression post-treatment. Undiagnosed women will continue to progress to advanced stages, ultimately succumbing to the disease (or other cause), with cancer-specific mortality assumed to occur within the first year of stage IV cancer. Women treated for precancerous lesions will be considered treated for HPV infection and will be assumed to return to the HPV free state, but will be considered at risk for future disease based on the age specific incidence of HPV infection.
## Screening protocol
The primary value of screening lies in the early detection of precancerous lesions or early-stage cancers, when treatment is more effective and associated with significantly Open access better outcomes. It will be assumed that women in the precancerous stage can be identified only through screening, with the probability of detection dependent on the diagnostic accuracy of the specific screening modality. Invasive cancer, however, may be detected either through routine screening or following the onset of symptoms. The diagnostic accuracy of each screening modality will be defined by its sensitivity and specificity. Women with TN results will be retested according to the screening frequency. TP cases will receive appropriate treatment, while FP will incur additional costs of the confirmatory diagnostics. FN will continue to progress through the natural history of cervical disease until they are detected during the next screening cycle or on the appearance of symptoms.
Considering the current guidelines of cervical disease prevention among WLHIV, it will be assumed that women will first be referred from ART centres to designated secondary or tertiary care hospitals for screening. All screening protocols, along with confirmatory diagnostics, will be conducted at these facilities. Treatment for cervical disease and invasive cancer will take place at designated tertiary care hospitals. Although guidelines recommend screening for WLHIV every 3 years using VIA, the current scenario indicates that the coverage rates are extremely low and women are only referred if they present with symptoms suggestive of invasive disease.
The present study will evaluate six screening protocols: VIA, Pap smear, HPV DNA testing, VIA followed by Pap smear, VIA followed by HPV DNA testing, and Pap smear followed by HPV DNA testing. Each protocol will be assessed at four different screening intervalsevery 6 months, annually, biennially (every 2 years) and triennially (every 3 years). While the results of VIA will be assumed to be immediately available in the first visit, the results of Pap smear and HPV DNA testing will be assumed to take 2 weeks and require a follow-up second visit for result collection. Screening strategies involving triage will be assumed to involve three visits, with the third visit required for collection of triage results and referral for confirmatory diagnosis or treatment, if required. A confirmatory diagnosis will be performed using colposcopy and biopsy. Treatment for precancerous cervical lesions will follow standard treatment guidelines, which include cryotherapy, loop electrosurgical excision procedure or surgery, depending on the severity and spread of the lesion. Women diagnosed with invasive cervical cancer will be referred for appropriate stage-specific treatment, which may include surgery, chemotherapy and/or radiotherapy.
All six screening protocols (hereafter referred to as 'organised screening') will be compared against each other, as well as will be evaluated relative to the current scenario (hereafter referred to as 'unorganised screening') which primarily involves opportunistic screening, and where most patients are diagnosed symptomatically at advanced stages of cervical cancer. For the organised screening strategies, we will conservatively assume a base-case screening coverage rate of 50% at each specified screening interval. Additionally, we will incorporate an assumed 10% loss to follow-up at each step of the care cascade, including subsequent visits required for screening completion, confirmatory diagnosis and treatment initiation.
## Model parameters
To accurately capture the model input parameters, we will undertake a structured and comprehensive review of the literature using PubMed and Google Scholar. The review will focus on identifying studies that provide data on the burden of HIV and HPV (incidence and prevalence), disease progression and mortality rates among WLHIV. Priority will be given to studies conducted in India, as they offer the most contextually relevant insights. However, in the absence of sufficient local data, studies from other LMICs with similar HIV and HPV burden will be considered. In addition to published studies, efforts will be made to obtain data from international/national registries and reports, where available, to supplement the evidence base. All identified and relevant studies will be presented to an expert group comprising clinicians, infectious disease specialists, oncologists, programme managers and public health experts for review and approval of studies to be included for assessing the parameters. In cases where multiple studies meet the eligibility criteria, decisions regarding inclusion will be guided by a systematic assessment of factors such as sample size, follow-up duration, baseline characteristics of the study population and methodological rigour. Where appropriate, results from eligible studies will be pooled to strengthen the evidence base and provide a more robust understanding of the parameters necessary for the model. This rigorous approach will ensure that the final model reflects an accurate and comprehensive representation of the burden of HIV and HPV among WLHIV in India.
The diagnostic accuracy of the screening strategies will be informed by the above-mentioned meta-analysis. Utility values for the different health states will be derived from the primary data collection described earlier. Similarly, stage-specific treatment costs for cervical cancer and HIV, including OOP expenditures and productivity losses, will be estimated based on the analysis of primary data. Further, the cost of screening with HPV DNA test and PAP smear will be sourced from the reimbursement rate of Central Government Health Scheme. 30 The cost of the VIA test will be obtained from a previous costing study. 7 Follow-up costs beyond 1 year will be based on the normative costing based on standard treatment guidelines reflecting the resource use and frequency of follow-up visits beyond 12 months post treatment. If a woman dies because of cervical cancer, the treatment cost of advanced cancer and palliative care for their last year of life will be included. All cost estimates will be standardised in a common price year, and standard adjustments for inflation will be applied to ensure consistency across cost estimates.
## Open access
## Model calibration
To validate the model outcomes and ensure they accurately reflect the epidemiology of HIV and HPV coinfection among WLHIV in India, a rigorous model calibration process will be undertaken. As a first step, a set of plausible values for key parameters, particularly those governing the natural history of HPV progression stratified by CD4 count, will be identified from the literature along with their corresponding plausible ranges. The model will then be subjected to multiple simulations under a no-intervention scenario. In each simulation, a single random value for each parameter will be drawn from distribution within the plausible range and applied to the corresponding baseline probability, thereby generating a unique set of natural history input parameters.
To select the best input parameter value set, a goodnessof-fit score will be computed by summing the log likelihood of model-projected outcomes for each parameter set and comparing them against epidemiological calibration targets, including age-specific prevalence of HPV infection, CIN2/3 and the lifetime risk of developing cervical cancer.
## Sensitivity analyses
Univariate or one-way sensitivity analysis will be conducted by varying key parameters using their minimum and maximum values. Additionally, a threshold analysis will be performed to evaluate how changes in screening coverage levels and the diagnostic accuracy of screening modality impact the cost-effectiveness. To account for joint parameter uncertainty, probabilistic sensitivity analysis will be conducted.
## Model outcomes
Cost-effectiveness will be assessed using the incremental cost-effectiveness ratio (ICER). In addition to ICER, the model will also estimate the lifetime cost, reduction in cervical cancer incidence and mortality, gains in life years, QALYs and life expectancy associated with each screening modality at various frequencies. To compare the relative cost-effectiveness of different screening strategies, the concept of net monetary benefit (NMB) will be applied. NMB is calculated by converting health outcomes (ie, QALYs) into monetary terms using a specified willingnessto-pay threshold and then subtracting the total cost of the intervention. A cost-effectiveness threshold of one-time gross domestic product per capita of India will be used.
## DISCUSSION
Since the identification of AIDS in 1981, the disproportionately higher burden of cervical cancer among WLHIV has been well documented, particularly in LMICs, where disparities in cervical cancer incidence between women with and without HIV are most pronounced. 2 India, home to one of the largest populations of PLHIV in the world, has witnessed remarkable progress in reducing the incidence of HIV over the past two decades. Further, although the use of highly active ART has significantly improved the life expectancy of individuals with HIV, its impact on HPV infection and the risk of cervical cancer among WLHIV remains minimal. [31][32][33] This necessitates the need and implementation of specific preventive strategies, including timely and effective screening. However, in India, cervical cancer screening coverage among WLHIV remains suboptimal, with only 1.9% of Indian women undergoing regular screening, resulting in a high proportion of late-stage diagnoses. 34 This underscores the need for a systematic evaluation of organised screening protocols to guide evidence-based policy.
The proposed study addresses a critical gap in India's public health response by evaluating the cost-effectiveness of various cervical cancer screening modalities and their sequential combinations at varying frequencies. While evidence from African countries has provided valuable insights into the cost effectiveness of different screening approaches in WLHIV, 12 such findings may not be directly applicable to India, given its unique health system structure and epidemiological profile. By employing a robust decision-analytic model calibrated to epidemiological data, the study will simulate long-term health outcomes and costs associated with different screening strategies. Importantly, the inclusion of real world data on healthcare costs and patient-incurred expenditures, collected as a part of routine healthcare delivery, strengthens the relevance and validity of the economic analysis. The findings from this study have significant implications for India's national cancer control and HIV/AIDS programme. This study will provide critical evidence in identifying the most cost-effective screening strategy for the scale-up of organised cervical cancer screening among WLHIV in India.
## Potential limitations
This study has certain limitations. A component of cost data is collected retrospectively and may be subject to recall bias, despite efforts to minimise this through structured interviews and short recall periods. Second, the cost data is collected till a period of 9 months post-treatment, the estimates of follow-up costs beyond 1 year (for the cost effectiveness modelling) will be estimated using normative costing (based on STGs), which may not reflect the real world practice. However, given the practical constraints in following patients over longer durations, the use of normative costing represents a reasonable and pragmatic approach. Third, the inclusion of productivity costs raises the potential concern of double counting within a cost-utility analysis. This issue has been widely debated in the health economics literature. One view suggests that productivity (or indirect) costs are already captured within utility or QALY measures, 35 36 whereas others argue that QALYs do not adequately capture these costs. [37][38][39][40][41][42] In the present study, and consistent with a societal perspective, we will include indirect costs only related to patients' and caregivers' time lost in accessing and receiving care, which is generally considered methodologically uncontroversial. 35 36 However, we will not value
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27. Campos, Maza, Alfaro (2015) "The comparative and costeffectiveness of HPV-based cervical cancer screening algorithms in El Salvador" *Int J Cancer*
28. (2025) "30 CGHS: central government health scheme"
29. Sellors, Lewis, Kidula (2003) "Screening and management of precancerous lesions to prevent cervical cancer in low-resource settings" *Asian Pac J Cancer Prev*
30. Vuyst, Lillo, Broutet (2008) "HIV, human papillomavirus, and cervical neoplasia and cancer in the era of highly active antiretroviral therapy" *Eur J Cancer Prev*
31. Adler (2010) "The impact of HAART on HPV-related cervical disease" *Curr HIV Res*
32. Gopika, Prabhu, Thulaseedharan (2022) "Status of cancer screening in India: An alarm signal from the National Family Health Survey (NFHS-5)" *J Family Med Prim Care*
33. Gold, Siegel, Russell (1996) "Cost-Effectiveness in Health and Medicine"
34. Sittimart, Rattanavipapong, Mirelman (2024) "An overview of the perspectives used in health economic evaluations" *Cost Eff Resour Alloc*
35. Drummond, Sculpher, Claxton (2015) "Methods for the Economic Evaluation of Health Care Programmes. 4th edn"
36. Brouwer, Koopmanschap, Rutten (1997) "Productivity Costs Measurement Through Quality of Life? A Response to the Recommendation of the Washington Panel" *Health Econ*
37. Brouwer, Koopmanschap, Rutten (1997) "Productivity costs in cost-effectiveness analysis: numerator or denominator: a further discussion" *Health Econ*
38. Sculpher (2001) "The role and estimation of productivity costs in economic evaluation"
39. Olsen, Richardson (1999) "Production gains from health care: what should be included in cost-effectiveness analyses?" *Soc Sci Med*
40. Liljas (1998) "How to calculate indirect costs in economic evaluations" *Pharmacoeconomics*
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# P-746. Dalbavancin Reduces Readmissions and Nephrotoxicity in Skin and Soft Tissue Infections: Real-World Comparative Effectiveness
Ali Dehghani, Do, Joanna Henry, George Yendewa
## Abstract
Despite this eradication, rubella virus (RuV)-associated granulomas have been reported in the literature but are limited to case reports and series, with no reported prevalence rate. 2 This study aims to assess the prevalence of cutaneous RuV granulomas and to further characterize the disease.
Methods. Using TriNetX, we performed three retrospective, 1:1 propensitymatched cohort studies comparing dalbavancin to vancomycin (n=1,052), linezolid (n=989), and daptomycin (n=487) in adults with SSTIs. Matching included age, sex, race, comorbidities (e.g., diabetes, end-stage renal disease [ESRD], HIV), substance use and mental illness. We excluded patients with osteomyelitis, bacteremia, or ICU stays within one month of the index date. Outcomes were assessed within 90 days and included hospital/emergency department (ED) visits, infection-related readmissions, acute kidney injury (AKI), drug-induced liver injury (DILI), rhabdomyolysis, and cytopenias. Odds ratios (ORs) were estimated using multivariable logistic regression models. vancomycin (p < 0.0001), daptomycin (p = 0.001), and linezolid (p = 0.0031). Drug-induced liver injury (DILI) and rhabdomyolysis occurred exclusively in comparator groups (p = 0.0015 for each). No significant difference in cytopenia was observed between dalbavancin and linezolid (p = 0.688). Dashed vertical line indicates the null value (OR = 1.0); horizontal bars represent 95% confidence intervals.
Results. Across all matched cohorts, mean age was 54 years, with 52-58% male and 74-84% White. Dalbavancin was associated with significantly lower infectionrelated 90-day readmission rates compared to vancomycin (29.1% vs. 38.1%; OR 0.66, p< 0.0001), linezolid (30.3% vs. 41.6%; OR 0.62, p< 0.0001), and daptomycin (27.7% vs. 51.7%; OR 0.36, p< 0.0001). Hospitalization or ED visits were also reduced versus vancomycin (27.1% vs. 38.2%; OR 0.60, p< 0.0001). Dalbavancin had significantly lower AKI rates (< 1%) compared to vancomycin (5.3%), daptomycin (8.2%), and linezolid (3.5%; all p< 0.001). DILI and rhabdomyolysis occurred only in comparator groups. No significant cytopenia differences were observed.
Conclusion. Dalbavancin was associated with reduced 90-day readmissions and nephrotoxicity in real-world SSTI care. Its simplified dosing benefits patients with adherence barriers and supports value-based care models.
Disclosures. All Authors: No reported disclosures 1 2
1 2 1 1 2 1 Infectious Diseases Department, sfax, Sfax, Tunisia 2 Infectious Diseases Department, Hedi Chaker University Hospital, University of Sfax, Tunisia, Sfax, Sfax, Tunisia
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# Antibody-mediated control of anellovirus infection: evidence from people who inject drugs
Abraham Kandathil, Steven Clipman, Raghavendran Anantharam, Dylan Duchen, Andrea Cox, H Larman, David Thomas
## Abstract
Infections with viruses belonging to the family Anelloviridae are widespread among humans. Although generally considered a commensal, there is evidence to suggest that these infections may be controlled by host immune responses. However, the mechanism of immune control remains unclear. Previous research has also suggested a possible role of anellovirus capsid spikes in immune evasion. To investigate the role of antibodies in controlling infection, we used AnelloScan to profile plasma collected every 6 months over 2 years from 10 persons who inject drugs (PWID). Participants were selected based on viremia patterns: persistent (n = 6) versus intermittent (n = 4). Long-read metagenomic sequencing revealed a higher median number of alphator quevirus (TTV) species in participants with persistent viremia compared to those with intermittent viremia (P < 0.0001). AnelloScan detected TTV-specific antibodies among all study participants. No significant differences were observed between the two groups when all antibody-reactive peptides located in the capsid were included. However, among participants with intermittent viremia, antibodies were more frequently reactive to peptides located in the amino acid variable region of the capsid spike domain (P = 0.0429). These findings suggest that among PWID, antibodies targeting the sequence variable region of the spike domain appear to be associated with control of anellovirus infection. Additionally, anelloviruses might be susceptible to pre-existing immunity, and the amino acid variable region of the spike protein may play a role in viral infectivity. IMPORTANCE Anelloviruses are highly diverse and are recognized as the major component of the blood virome in healthy humans. Despite this, little is known about their interactions with their hosts. In this study, we found that anelloviruses can elicit antibody responses. Notably, antibodies that targeted a sequence variable region on spikes present on viral capsids were associated with truncation of plasma viremia. These data suggest a possible mechanism of immune control of anellovirus infections while also indicating a role of the capsid spikes in viral infectivity.
KEYWORDS plasma virome, anelloviruses, antibodiesM embers of the family Anelloviridae represent a major component of the blood virome in healthy humans, with infections detected as early as the first few months of life (1). While multiple modes of transmission have been suggested, there is direct evidence of blood-borne transmission among adults (2, 3). Their blood-borne mode of transmission contributes to a higher prevalence in certain populations, such as persons who inject drugs (PWID), due to repeated exposure to blood-borne viruses (4, 5). Longitudinal studies among PWID have shown that anellovirus infections follow a dynamic pattern of clearance and reinfection (4, 6). Higher anellovirus burdens among immunocompromised individuals, such as solid organ transplant recipients, further suggest the possibility of immune control of anellovirus infection (7). However, the
mechanisms underlying the control of infection remain poorly understood, and direct evidence of immunity to anellovirus is limited. A cross-sectional study using AnelloScan, a T7 phage library representing peptide sequences of more than 800 human anello viruses, revealed that many of the peptides are non-reactive (8). A recent cryogenic electron microscopy revealed that amino acid sequences exhibited on the spike domains of anellovirus capsids might contribute to immune evasion (9). Anellovirus capsids are composed of single jelly roll (JR) domains and spike domains (9,10). Based on amino acid sequence divergence, the spike domain can be divided into JR proximal region (P1) and a JR distal sequence variable region (P2) (9,10). The latter includes previously reported hypervariable regions (HVRs) that have been suggested to have a role in immune evasion (9,11).
In this study, we profiled the antibody response in plasma over time to determine the role of antibodies in infection control and compare responses within and outside the spike domain. Based on our previous observation that PWID are at greater risk of acquiring anellovirus infections, we selected longitudinal samples from 10 study participants from our injection drug use cohort with anellovirus infections (4,12). Each PWID was followed for 2 years and identified as having persistent (n = 6) or intermittent (n = 4) viremia. Long-read sequencing on the nanopore platform revealed a greater number of anellovirus species among individuals with persistent plasma viremia. Assessing antibody responses using AnelloScan, we observed that antibodies targeting the variable P2 region within the spike domain were associated with intermittent, rather than persistent, viremia. These findings suggest that among PWID, anellovirus infection might elicit neutralizing antibodies that have a role in controlling viremia. These results also demonstrate that the P2 region may contribute to viral infectivity.
## RESULTS
## Persistent anellovirus infections are characterized by higher viral richness
We selected 10 study participants (AS01-AS10) from a Baltimore-based PWID cohort in whom we had previously characterized plasma virome components over time (4). In the persistent group, the median age was 27 years (IQR 10), compared with 28 years (IQR 3) in the intermittent group. Women represented 67% of participants in the persistent group, whereas no women were enrolled in the intermittent group. Regarding race, all participants self-identified as White, except for AS10, who self-identified as Black. Race information was not available for AS06, and age was not available for AS09. Participants were selected based on an initial PCR-based screening to identify individuals with and without circulating anellovirus (13). Anellovirus-specific PCR was used for the initial screening as a targeted approach is more sensitive than metagenomic approaches for detecting low levels of viremia (14,15). For the present 2-year follow-up study, we included five plasma samples from each participant with a median time interval of 183 days (IQR 116) between two visits. Based on patterns of anellovirus detection over 2 years, participants were categorized into persistent (n = 6) and intermittent (n = 4) viremia. As PCR provided only genus-level information, visits with detectable anellovirus infections were further characterized using long-read metagenomic sequencing on the nanopore platform (16).
Species identification of nanopore reads was performed using reference species from the International Committee on the Taxonomy of Viruses (ICTV) Ninth Report (17). Across all sequenced visits, we observed significantly greater alphatorquevirus (TTV) richness, defined as the number of distinct TTV species, among individuals with persistent viremia (P < 0.0001, Fig. 1a). We observed a median of 8 (IQR 3.25) TTV species in participants with persistent viremia compared to 2.5 (IQR 2.5) in those with intermittent viremia (Fig. 1b). TTV species dynamics were also different between the two groups (Fig. S1 andS2).
## Peptide reactivity in the P2 region is associated with control of anellovirus infection
To assess if TTV-specific antibody profiles differed between intermittent and persistent groups, plasma from all time points was tested using the AnelloScan platform (8). AnelloScan is a phage-immunoprecipitation sequencing-based platform to characterize antibody responses to the human anellome (8,18). The comprehensive phage display library consists of over 32,000 anellovirus peptides representing 829 anellovirus genomes, of which 39.2% represent TTV genomes (8).
Antibodies to TTV peptides were detected at all five time points in all 10 study participants (Fig. S3). However, only a subset of TTV peptides was reactive at all time points. Except for AS01, who lacked peptides consistently reactive across visits, other participants had reactivity to a median of 11 peptides (IQR 10) across visits (Fig. S3). These peptides were distributed throughout the TTV genome (Fig. 2a), and no significant differences were observed between the two viremia groups with respect to the locations of these peptides within the capsid domain (P = 0.0905). In contrast, all participants with intermittent viremia exhibited persistent antibody reactivity to at least one TTV peptide between nucleotide positions 1,268-1,673 (P2 spike region) (10), whereas only one participant with persistent viremia showed similar responses in this region (P = 0.0429, Fig. 2b). The five study participants who maintained antibody reactivity to the P2 spike region across all time points were observed to have a lower TTV richness (P = 0.0003) (Fig. S4a andb). These results suggest that antibody responses targeting the sequence variable P2 region may contribute to controlling anellovirus infection and are more commonly associated with intermittent viremia.
## DISCUSSION
In this investigation, we detected antibodies to TTV in the blood of humans. Moreover, the locus of antibody reactivity was strongly correlated with the outcome of infection. Notably, antibodies to the P2 spike region were associated with viral clearance. These results suggest some of these "commensal" viruses trigger humoral immunity that contributes to infection control and that the P2 region may play a role in viral infectivity. Reports on immunity against anelloviruses are limited. Indirect evidence suggesting immune control of anelloviruses has been observed in transplant settings, where a higher anellovirus burden is indicative of immunosuppression (5). However, a meta-tran scriptomic analysis of human viruses in a variety of tissues in healthy individuals did not detect any upregulated interferon-stimulated gene transcription in tissues containing TTV transcripts (19). A cross-sectional study by Venkataraman et al. using AnelloScan revealed poor antibody reactivity toward most (85%) of the anellovirus peptides, with reactive peptides mostly localized in the C-terminal region of the capsid protein open reading frame 1 (8). The same study showed that among blood transfusion recipients, 11/40 transmitted anelloviruses were associated with antibody response (8). Notably, in all but one of these 11, the earliest antibody reactivities were first detected 100 days post-transfusion, indicating a limited and delayed antibody response (8).
Our data suggest that antibodies targeting the P2 region of the spike domain are associated with viral restriction. This indicates that the residues in P2 region of the spike domain may be involved in receptor binding and that antibodies might be neutralizing, i.e., interfering with viral entry (20,21). Receptor-binding regions have been identified in the HVRs of other viruses. For example, the HVR1 of hepatitis C virus (HCV) envelope proteins mediates viral entry and plays a key role in immune evasion (22,23). Studies in chimpanzees have also demonstrated that antibodies targeting HVR1 help prevent acute HCV infections (23). To evade immune responses, viruses often use sequence variations, such as in the P2 region, to outpace the development of effective immune responses (24). In HCV, antibodies targeting HVR1 have been suggested to drive sequence variation (23). Based on our observations, the P2 region may facilitate immune evasion while also influencing viral infectivity.
This study only included peptides represented in the AnelloScan platform. Additional antibody-reactive peptides might have been missed. In addition, the study likely failed to detect antibodies against conformational, discontinuous, and post-translationally modified epitopes that are not expressed by phage display systems (8). The study was also limited because the onset of exposure (inoculation) of the viruses was not known. Thus, the experience of persons with these viruses prior to our "baseline" was not known. Longer follow-up studies might reveal added insights into the host-virus interactions. Finally, in vitro replication models are needed to confirm findings and test hypotheses such as the presence and locus of neutralizing antibodies.
In summary, our data reveal that among PWID, antibodies targeting the sequence variable P2 region of the spike domain are associated with truncation of anellovirus infection and confer protection from infection. These results raise the possibility that susceptibility to anelloviruses varies among individuals and that immune responses may shape the course of infection. Understanding the outcome of these interactions may have broader implications for human health.
## MATERIALS AND METHODS
## Study participants
Study samples were drawn from a cohort of injection drug users located in Baltimore, MD, USA (12). At the time of recruitment, participants reported injecting drugs in the last 6 months and were negative for both HIV and HCV infections. Participants are then longitudinally followed with plasma and serum collected at each monthly visit. For this study, we identified 10 participants with and without plasma anellovirus using a PCR-based screening assay.
## Molecular detection and sequencing
## DNA extraction
Extraction of plasma RNA and DNA was as previously described (15). Briefly, the Quick-DNA/RNA Miniprep Plus Kit (Zymo Research, USA;Cat #D7003) was used to extract DNA and RNA from 200 µL of plasma. Pre-extraction steps included spinning the samples at 1,600 × g for 15 minutes at 4°C to remove debris (e.g., insoluble complexes) followed by filtration using 0.2 µM syringe filters (Thermo Fisher Scientific, USA; Cat #6778-1302).
## Anellovirus PCR
Previously established protocols were used to detect infection with alpha-, beta-, and gamma-torquevirus (13). Additionally, we enhanced the sensitivity of the PCR by incorporating a rolling circle amplification (RCA) based pre-amplification step, as previously reported (4). As described, RCA was carried out at 30°C for 18 h without the initial 95°C denaturation step using 2 μL of DNA as input. RCA was done using TempliPhi (Sigma Aldrich, USA; Cat #GE25-6400-10). For the PCR, a 1:5 dilution of RCA concatemers was taken for subsequent PCR reactions.
## Nanopore sequencing
Sequencing for species-level identification of anellovirus infection was done using Oxford Nanopore Sequencing. The RCA concatemers were linearized by an initial debranching step using non-primed Phi29 amplification followed by branch release using S1 endonuclease and a final DNA repair step using a combination of T4 DNA polymerase (Thermo Fisher Scientific, USA) and DNA polymerase I (NEB, USA) (25). Linearized DNA was sheared using a Bioruptor into 1,000-1,500 bp fragments. To obtain an average DNA fragment size of 1,000 bp on the Bioruptor, we used the following settings: 15 seconds on/30 seconds off for two cycles. The size distribution of the sheared DNA samples was visualized using a 2100 Bioanalyzer (Agilent Technologies, USA).
All libraries were prepared using a PCR barcoding protocol (SQK-PBK004, Oxford Nanopore Technologies, UK). Libraries were pooled (n = 5) and sequenced on the Oxford Nanopore Technologies GridION platform for 72 h using ~20 to 50 ng of the library on the recommended flow cell. Base calling from the nanopore platform was set to super-accurate mode (> 99% accuracy) with a Q score of 10 and no further read filtering.
## Identification of anellovirus species
We applied our previously described method to identify anellovirus species (16). Briefly, host read deconvolution was done using Minimap2 (26) by mapping them against a custom, selectively masked human reference genome (GRCh38.p14) containing alternate contigs, HLA sequences, and several bacterial contaminant genomes. This masking process prevents anellovirus reads from being inadvertently discarded during host deconvolution (27). Following removal of host sequences, anellovirus species identification was performed by alignment of deconvoluted reads against our in-house data base constructed using Anelloviridae sequences, as previously described (16). Species identification was based on analysis of ORF1 in its entirety, with a demarcation threshold cutoff of 69% nucleotide similarity (28). A species was considered present if at least five viral reads mapped to the corresponding ICTV reference with mapping quality ≥ 10 and cover ≥ 25% of the reference genome. To further mitigate potential cross-mapping and quantify certainty, we implemented a confidence score that integrates breadth and depth of coverage. Specifically, the score is calculated as:
where b 1 × is the breadth of coverage at ≥1× (fraction of reference positions with depth ≥1), b 5 × is the breadth of coverage at ≥5×, and d ¯ is the mean depth of coverage across the reference genome.
$$Score = b 1 × × b 5 × × log 10 1 + d ¯,$$
## AnelloScan
The AnelloScan protocol used in this study has been previously described in detail (8).
A peptide was defined as reactive when the hits fold change was ≤ 2. Values equal to 1 were classified as unenriched relative to mock immunoprecipitation conditions. For all analyses, only proteins encoded by the sense strand were considered.
## Statistical analyses
All statistical analyses were performed using GraphPad Prism 10 for macOS (version 10.4.2).
A non-parametric statistical test, the Mann-Whitney test, was applied because the data were not normally distributed. Results with a P value of <0.05 were deemed significantly different.
## References
1. Kaczorowska, Cicilionytė, Timmerman et al. (2022) "Early-life colonization by anelloviruses in infants" *Viruses*
2. Arze, Springer, Dudas et al. (2021) "Global genome analysis reveals a vast and dynamic anellovirus landscape within the human virome" *Cell Host Microbe*
3. Bernardin, Operskalski, Busch et al. (2010) "Transfusion transmission of highly prevalent commensal human viruses" *Transfusion*
4. Kandathil, Cox, Page et al. (2021) "Plasma virome and the risk of blood-borne infection in persons with substance use disorder" *Nat Commun*
5. Kandathil, Thomas (2024) "The blood virome: a new frontier in biomedical science" *Biomed Pharmacother*
6. Wilson, Umemura, Astemborski et al. (2001) "Dynamics of SEN virus infection among injection drug users" *J Infect Dis*
7. Vlaminck, Khush, Strehl et al. (2013) "Temporal response of the human virome to immuno suppression and antiviral therapy" *Cell*
8. Venkataraman, Swaminathan, Arze et al. (2022) "Comprehensive profiling of antibody responses to the human anellome using programmable phage display" *Cell Rep*
9. Liou, Boggavarapu, Cohen et al. (2024) "Structure of anellovirus-like particles reveal a mechanism for immune evasion" *Nat Commun*
10. Butkovic, Kraberger, Smeele et al. (2023) "Evolution of anelloviruses from a circoviruslike ancestor through gradual augmentation of the jelly-roll capsid protein" *Virus Evol*
11. Nishizawa, Okamoto, Tsuda et al. (1999) "Quasispecies of TT virus (TTV) with sequence divergence in hypervariable regions of the capsid protein in chronic TTV infection" *J Virol*
12. Cox, Netski, Mosbruger et al. (2005) "Prospective evaluation of community-acquired acute-phase hepatitis C virus infection" *Clin Infect Dis*
13. Ninomiya, Takahashi, Nishizawa et al. (2008) "Development of PCR assays with nested primers specific for differential detection of three human anelloviruses and early acquisition of dual or triple infection during infancy" *J Clin Microbiol*
14. Kandathil, Blair, Lu et al. (2024) "Metagenomic next generation sequencing of plasma RNA for diagnosis of unexplained, acute febrile illness in Uganda" *PLoS Negl Trop Dis*
15. Kandathil, Breitwieser, Sachithanandham et al. (2017) "Presence of human hepegivirus-1 in a cohort of people who inject drugs" *Ann Intern Med*
16. Anantharam, Duchen, Cox et al. (2024) "Long-read nanopore-based sequencing of anelloviruses" *Viruses*
17. Anonymous (2009) "ICTV ninth report; 2009 taxonomy release"
18. Larman, Zhao, Laserson et al. (2011) "Autoantigen discovery with a synthetic human peptidome" *Nat Biotechnol*
19. Kumata, Ito, Takahashi et al. (2020) "A tissue level atlas of the healthy human virome" *BMC Biol*
20. Burton (2023) "Antiviral neutralizing antibodies: from in vitro to in vivo activity" *Nat Rev Immunol*
21. Klasse (2014) "Neutralization of virus infectivity by antibodies: old problems in new perspectives" *Adv Biol*
22. Lindenbach, Rice (2013) "The ins and outs of hepatitis C virus entry and assembly" *Nat Rev Microbiol*
23. Prentoe, Bukh (2018) "Hypervariable region 1 in envelope protein 2 of hepatitis C virus: a linchpin in neutralizing antibody evasion and viral entry" *Front Immunol*
24. Finlay, Mcfadden (2006) "Anti-immunology: evasion of the host immune system by bacterial and viral pathogens" *Cell*
25. Mehta, Cornet, Hirsch-Hoffmann et al. (2020) "Full-length sequencing of circular DNA viruses and extrachromo somal circular DNA using CIDER-Seq" *Nat Protoc*
26. Li (2018) "Minimap2: pairwise alignment for nucleotide sequences" *Bioinformatics*
27. Constantinides, Hunt, Crook (2023) "Hostile: accurate decontami nation of microbial host sequences" *Bioinformatics*
28. Varsani, Opriessnig, Celer et al. (2021) "Taxonomic update for mammalian anelloviruses (family Anelloviridae)"
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# Human papillomavirus partial L2 gene variants in the Barrett's metaplasia-dysplasia-adenocarcinoma sequence
Kishen Rajendra, Aliakbar Khabiri, Shanmugarajah Rajendra, Mohammad Rabiei
## Abstract
High-risk human papillomavirus (HPV) genotypes 16 and 18 are associated with Barrett's dysplasia and esophageal adenocarcinoma. We sequenced 33 HPV partial L2 genes from Australian esophageal specimens. Phylogenetic analysis showed 32 were HPV-16 and one was HPV-18, underscoring the predominance and importance of HPV-16. KEYWORDS human papillomavirus (HPV), oesophageal adenocarcinoma (OAC), phylogenetic study O ncogenic viruses are responsible for a substantial percentage of global cancer cases (1). Human papillomavirus (HPV), a key player, is linked to approximately 30% of virus-related cancers (2). HPV is a small, double-stranded DNA virus that belongs to the Papillomaviridae family with an ~8 kb genome divided into early (E), late (L), and long control (LCR) regions; types are classified based on <90% L1 gene nucleotide similarity, subtypes on 90-98%, and variants on >98% similarity (3). The L2 gene was selected in this study because its partial conservation made it a suitable target for broad primers, while its higher divergence provided better variant discrimination than L1 (4).In esophageal adenocarcinoma (OAC), studies have indicated that high-risk HPV is associated with 25% of malignancies (5,6). In this study, we report the partial L2 genes of HPV strains detected from OAC cases from Bankstown-Lidcombe Hospital in Sydney, Australia, and compare them phylogenetically to previously reported strains. Viral genome sequences are essential for understanding the genetic diversity, evolution, and epidemiology of HPV.From 2012 to 2014, we collected 33 biopsies from patients with Barrett's metapla sia-dysplasia-adenocarcinoma (median age 46, range 42-79). Samples were homogen ized, and viral DNA was extracted using the DNeasy Blood & Tissue Kit (Qiagen, USA). DNA quality and concentration were assessed with a NanoDrop spectrophotometer. The partial L2 region was amplified by PCR with type-specific primers (Table 1), visualized on agarose gels, and purified (Qiagen, USA). Amplicons (90-100 bp) were sequenced bidirectionally by the Sanger method at the Ramaciotti Centre for Genomics (UNSW, Sydney). Consensus sequences were compared with GenBank references, showing >99% similarity, and the most closely related strains were used for phylogenetic analysis. A maximum likelihood tree was constructed in MEGA X to determine evolutionary relationships.Sequences showed >99% similarity with GenBank references. One sequence clustered with HPV-18 strains CU9 (Thailand) and Qv03132 (USA), while 32 clustered with HPV-16 strains CU2/CU4 (Thailand) and African-1 (USA) (Fig. 1).The predominance of HPV-16 among the samples aligns with global epidemiologi cal trends, highlighting its significant role in oncogenesis (8). The clustering patterns observed could inform future public health strategies and vaccination programs.
need for comprehensive screening and monitoring to address all high-risk HPV types effectively.
## References
1. Serrano-Pozo, Das, Hyman (2021) "APOE and alzheimer's disease: advances in genetics, pathophysiology, and therapeutic approaches" *Lancet Neurol*
2. Siegel, Miller, Wagle et al. (2023) "Cancer statistics, 2023" *CA Cancer J Clin*
3. Bernard, Burk, Chen et al. (2010) "Classification of papillomaviruses (PVs) based on 189 PV types and proposal of taxonomic amendments" *Virology (Auckl)*
4. Han, Wang, Mu et al. (2024) "Vaccination with a human papillomavirus L2 multimer provides broad protection against 17 human papillomavirus types in the mouse cervicovaginal challenge model" *Vaccines (Basel)*
6. Rajendra, Yang, Sharma et al. (2017) "Active human papillomavirus involvement in barrett's dysplasia and oesophageal adenocarcinoma is characterized by wild-type p53 and aberrations of the retinoblastoma protein pathway" *Int J Cancer*
7. Rajendra, Merrett, Sharma et al. (2018) "Survival rates for patients with Barrett high-grade Dysplasia and Esophageal adenocarcinoma with or without human papillomavirus infection" *JAMA Netw Open*
8. Tamura, Nei, Kumar (2004) "Prospects for inferring very large phylogenies by using the neighbor-joining method" *Proc Natl Acad Sci*
9. Milano, Guarducci, Nante et al. (2023) "Human papillomavirus epidemiology and prevention: is there still a gender gap?" *Vaccines (Basel)*
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# Herpes simplex virus 1 strain 17+ with R2 mutation in UL37 has residual retrograde transport
Marius Walter, Anoria Haick, Paola Massa, Lindsay Klouser, Laurence Stensland, Tracy Santo, Hong Xie, Keith Jerome
## Abstract
Herpes simplex virus 1 (HSV-1) causes lifelong recurrent infections. Following primary infection of the oral or genital mucosa, HSV-1 travels retrogradely through axons and establishes latency in the cell body of ganglionic neurons of the peripheral nervous system. Periodic reactivation in neurons and anterograde transport of virions back to peripheral regions cause oral or genital ulcerations. Many host and viral factors implicated in retrograde and anterograde transport of HSV-1 have been identified. In particular, studies reported that introducing five amino acid substitutions in the R2 region of the viral tegument protein UL37 was sufficient to completely eliminate retrograde transport of HSV-1 strain F. Here, we introduced the same R2 mutations in the highly neurovirulent HSV-1 strain 17+. We show that this R2 17 virus is highly attenuated in mice and acts as a potent vaccine that protects mice against acute HSV-1 infection. However, we report that the R2 17 virus has residual retrograde transport. We show that R2 17 can establish latency in mouse models of ocular and vaginal infection and reactivate. These results contradict published evidence and show that the R2 mutation is not sufficient to fully prevent retrograde transport of HSV-1. IMPORTANCE Herpes simplex virus 1 (HSV-1) is a ubiquitous pathogen without a cure or vaccine. HSV-1 travels through nerves between the oral and genital mucosa and the peripheral nervous system, where it establishes lifelong latency. Studies reported that introducing five amino acid substitutions in the R2 region of the viral tegument protein UL37 was sufficient to completely eliminate the retrograde transport of HSV-1 strain F from the mucosa to the nervous system. Here, we present contradictory findings. We report that an HSV-1 virus from strain 17+ with the same R2 mutation has residual retrograde transport. This shows that the R2 mutation is not sufficient to fully prevent the retrograde transport of HSV-1 in all settings. This finding may be particularly relevant for assessing the safety of prospective live-attenuated vaccines that include the R2 mutation.
KEYWORDS herpes simplex virus, retrograde transport, virologyH erpes simplex virus 1 (HSV-1) persistently infects close to 70% of the human population and causes oral and genital ulceration. After initial infection of epithelial tissues of the oral or genital mucosa, virions enter axons and are transported retro gradely to the cell bodies of sensory or autonomic neurons in peripheral ganglia, where the viral DNA genome remains latent for life. Periodic reactivation of the latent genome and anterograde transport of virions back to the mucosal periphery cause viral shedding and ulcers.Numerous studies have identified the mechanisms implicated in retrograde and anterograde transport of HSV virions, as reviewed in references 1-3. After viral entry in the axon tip, unenveloped capsids attach to dynein motors and are transported
retrogradely to neuronal cell bodies. Studies have shown that retrograde transport requires the viral inner tegument proteins UL36 and UL37. UL36 directly binds to the viral capsid and attaches to the dynein/dynactin microtubule motor complex, promoting the trafficking of the capsid toward the nucleus (4). UL37 is a protein deamidase that binds to UL36 and is also necessary for retrograde transport (5)(6)(7)(8). The UL37 N-terminus contains several domains evolutionarily conserved among related alphaherpesviruses, named R1, R2, and R3 (7,8). Studies have shown that introducing five alanine substi tutions in the R2 domain did not affect the overall protein structure of UL37 but rendered the virus avirulent (8). These defined substitutions, referred hereafter as the R2 mutation, were introduced in HSV-1 strain F as well as in the related pseudorabies virus (PRV) and bovine herpesvirus 1 (BoHV-1) (8)(9)(10)(11). In all cases, the R2 mutation appeared to completely eliminate retrograde transport. In particular, the HSV-1 R2 F virus replicated in the periphery but could not be detected in the trigeminal ganglia and dorsal root ganglia following ocular infection in mice and genital infection in guinea pigs, respectively. Similarly, the PRV R2 virus was not detected in the trigeminal ganglia after intranasal infection in mice or pigs, and the BoHV-1 R2 virus was not detected in the trigeminal ganglia after intranasal or ocular infection in calves (8)(9)(10)(11). Importantly, these studies demonstrated that R2 viruses acted as safe live-attenuated vaccines, protecting against subsequent challenge with wild-type HSV or PRV.
For unrelated vaccine studies, we wished to use a virus with no retrograde transport and compare it with other live-attenuated vaccine candidates that we are developing. We introduced the R2 mutation into HSV-1 strain 17+, a strain highly neurovirulent in mice, from which all our engineered viruses are derived. While testing this R2 17 virus side by side with other vaccine candidates, we noticed that R2 17 could establish latency in the ganglia after ocular or vaginal infection of mice. These observations show that R2 17 has residual retrograde transport, which contradicts the published studies mentioned above (8)(9)(10). In this manuscript, we report these findings as a standalone observation. They will be of interest to the field and show that the R2 mutation is not sufficient to fully prevent retrograde transport of HSV-1 in all settings.
## RESULTS AND DISCUSSION
We aimed to build an HSV-1 virus that would replicate efficiently in epithelial tissues but did not invade the nervous system. We thus incorporated the five R2 alanine substitutions (UL37-Q403A, E452A, Q455A, Q511A, R515A) into the genome of the highly neurovirulent HSV-1 strain 17+. The mutations were added by CRISPR-medi ated homologous recombination of a synthesized gene fragment containing the five mutations. As a recipient virus, we used an HSV-1 strain 17+ isolate that also carried a cyan fluorescent reporter (CFP) inserted between the US1 and US2 viral genes (12). Viral clones were plaque-purified and the presence of the R2 mutation was confirmed by Sanger sequencing (Fig. 1A). Shotgun sequencing of the viral stock showed that R2 17 included the UL37 mutations with no trace of wild-type sequences (Table S1). In addition, the R2 17 genome included 24 polymorphisms compared with the reference HSV1-17+ genome, with seven missense mutations of unknown effect in other protein-coding genes.
To use as a challenge virus from a different strain for vaccination studies, we also built a McKrae-YFP virus by adding a YFP reporter to the HSV-1 strain McKrae. Surprisingly, shotgun sequencing of this new virus revealed that it was a recombinant between McKrae and 17+ strains, with regions of the new virus originating from either genome (Fig. 1B). We traced the mistake to a contamination in the McKrae stock received from a collaborator. For the sake of clarity, we refer to this YFP-expressing McKrae/17+ recombi nant as McKrae-17 in the following paragraphs. Both R2 17 and McKrae-17 replicated well in cell culture, with no noticeable differences from their parental strains.
Our initial goal was to conduct vaccination studies and to compare R2 17 with other vaccine candidates. However, R2 17 did not behave as anticipated and did not represent the control treatment that we were expecting. In the following paragraphs, we present the results observed in the R2 17 arm of these studies as a standalone observation, since these contradictory findings could be of interest to researchers in the field. The rest of our vaccination studies will be presented elsewhere.
First, we tested if R2 17 could be used as a preventive vaccine to protect against HSV-1 ocular infection (Fig. 2A). Female Swiss Webster mice were inoculated ocularly after corneal scarification with R2 17 , at 10 6 plaque-forming units (PFU) per eye. In this model, infection with 10 5 PFU of wild-type HSV-1 strain 17+ typically causes extensive facial lesions and mortality before establishing latency in the trigeminal ganglia (TG) and other nervous areas (13)(14)(15). However, infection with R2 17 did not cause visible symptoms, and no mortality was observed. Four weeks after vaccination, mice were challenged ocularly with a high dose of McKrae-17 (10 7 PFU per eye). Unlike unvaccinated mice, vaccinated animals survived the challenge without symptoms (Fig. 2B). Together, these results aligned well with published studies. It showed that R2 17 was avirulent and acted as a potent vaccine that protected against HSV-1 acute infection.
Next, we tested if vaccination had protected against latency establishment and viral shedding. HSV-1 usually does not reactivate spontaneously in mice, but the virus can be artificially reactivated and detected in eye swabs by treating animals with the bromodomain inhibitor JQ1 (13)(14)(15). HSV-1 shedding is typically detected in 10%-50% of mice using this method. Four weeks after McKrae-17 challenge, mice were treated twice with JQ1, 2 weeks apart, and levels of reactivated viruses were quantified in eye swabs by qPCR (Fig. 2C). HSV-1 shedding was detected in 20%-25% of vaccinated mice. The reactivated swabs were genotyped using a duplex droplet digital (dd)PCR assay that distinguished between the CFP and YFP reporters present in the vaccine and challenge strains, respectively (Fig. 2D). Surprisingly, the CFP reporter present in R2 17 was detected in three swabs originating from three different mice (swab ID #56, #139 and #356). Sanger sequencing of the R2 region of these reactivated swabs showed that they carried the R2 mutation (Fig. 2F). By contrast, sequencing of two swabs expressing only the YFP reporter (swab ID #124 and #357) showed that they did not carry the R2 mutation but had SNPs specific to the McKrae strain, suggesting that McKrae-17 had reactivated in these mice. This unexpected result showed that R2 17 could reactivate, suggesting that it had established a latent infection.
To confirm this hypothesis, TG were collected, and the latent viral loads of the vaccine and challenge viruses were measured by duplex ddPCR (Fig. 2E). Surprisingly, both the CFP and YFP reporters were detected in the TG, indicating that both R2 17 and McKrae-17 had established a latent infection. R2 17 was detected in 22 out of 30 TG collected from 15 mice. Overall, the latent viral load of R2 17 was reduced by two orders of magnitude compared with infection of naive mice with wild-type HSV-1 strain 17+ at 10 5 PFU/ eyes (Fig. 2E, right panel). This showed that R2 17 could travel retrogradely to the TG to establish latency, albeit at reduced levels.
To confirm these results, we tested if vaccination with R2 17 could protect against HSV-1 infection during genital infection (Fig. 3A). Female Swiss-Webster mice were inoculated vaginally with 10 5 or 10 6 PFU of R2 17 . Vaginal infection with as low as 10 3-4 PFU of HSV-1 strain 17+ is usually highly lethal in mice, but no symptoms or mortality were observed after vaccination with R2 17 , confirming that the virus was avirulent. Four weeks later, mice were challenged vaginally with a high dose of McKrae-17 (10 7 PFU). All mice survived without symptoms, showing that R2 17 acted as an efficient vaccine (Fig. 3B). Five weeks after challenge, mice were treated twice with JQ1, 2 weeks apart, and HSV shedding levels were measured in vaginal swabs. This time, no mice reactivated HSV-1 (Fig. 3C). Dorsal root ganglia (DRG) were collected, and the latent viral loads of the vaccine and challenge viruses were measured by duplex ddPCR (Fig. 3D). Again, we found that R2 17 had established a latent infection. R2 17 was detected at low levels in 6 out of 10 DRG, while McKrae-17 could not be detected.
Altogether, our work confirmed that HSV strains with the R2 mutation were avirulent and could act as potent live-attenuated vaccines. However, we found that R2 17 had residual retrograde transport and could establish a latent infection after ocular or genital infection in mice. R2 17 retrograde transport appeared reduced compared to wild-type HSV-1 strain 17+. These unexpected results contradict published observations that showed that the R2 mutation completely eliminated retrograde transport of HSV-1 strain F and PRV (8-10). On the contrary, our findings suggest that the R2 domain of UL37 is implicated in retrograde transport but that other viral factors can compensate for its absence.
Several hypotheses could explain these differences. HSV-1 strain F is naturally less virulent than strain 17+ and high doses are necessary to establish a potent infection (16). It is possible that the R2 mutation in a viral strain that already has low virulence, like strain F, managed to fully eliminate retrograde transport, or at least pushed it below the limit of detection. It would be of interest to compare the R2 mutants of strain F and 17+ side by side to evaluate the differences. The R2 mutation also suppressed retrograde transport of PRV and BovHV-1 (8,11). PRV and BovHV-1 are Varicelloviruses, while HSV-1 belongs to the distinct genus of Simplexviruses, and the amino acids mutated in R2 PRV , R2 BovHV1 , and R2 HSV are only partially conserved (8). It is possible that Varicelloviruses and Simplexviruses, or at least, PRV, BovHV-1, and HSV-1, rely on slightly different viral factors for retrograde transport. Such a distinction is observed for anterograde transport, where knock-out of US9 in PRV fully eliminates anterograde transport, while US9-null mutants have residual anterograde transport with HSV-1.
## MATERIALS AND METHODS
## Cells and viruses
Viruses were propagated and engineered using African green monkey epithelial Vero cells. Vero cells were obtained from the ATCC and cultured in DMEM (Corning, Corning, NY, USA) supplemented with 10% FBS (Sigma-Aldrich, St-Louis, MO, USA). Cells were maintained at 37°C in a 5% CO 2 humidified incubator and frequently tested negative for mycoplasma contamination. Viral infections and plaque assays were conducted using DMEM with 2% FBS, as described previously (13).
R2 17 was generated by modifying HSV-1 strain 17+ expressing cyan fluorescent protein mTurquoise2 (HSV1-CFP), a gift from Matthew Taylor (12). A 592-bp gene fragment coding for the R2 mutation (UL37-Q403A, E452A, Q455A, Q511A, R515A) was purchased from IDT (USA) and introduced into HSV1-CFP genome by CRISPR-mediated homologous recombination. Specifically, confluent Vero cells in a six-well plate were first infected at MOI = 3 with HSV1-CFP. Three hours later, cells were detached from the plate using Trypsin. Then, 250,000 infected cells were transfected by nucleofection (Lonza, Basel, Switzerland), with 1 µg of the gene fragment and two Cas9 ribonucleoproteins (RNP) specific for the site of integration. The RNPs had a final concentration of 2 µM and were first reconstituted in 3 µL using Cas9 protein, tracrRNA, and crRNA purchased from IDT. We used two crRNA targeting UL37 to facilitate homologous recombination of the gene fragment (gRNA target sequences: CAATGCACCCAAAGAGCTGC, GGGCGTTCTAAGC CAGACGC). Transfected cells were plated in a single 24-well plate with fresh medium. Twenty-four hours later, serial dilutions of the supernatant containing recombinant viruses were plated into a fresh monolayer of Vero cells and overlaid with 1% methyl cellulose medium. After 3 days, viral clones were picked, screened by PCR and Sanger sequencing, and clones containing the expected mutation were isolated by three rounds of serial dilutions and plaque purification. Viral stocks were produced and titered by plaque assay.
McKrae-17 expressing mCitrine fluorescent reporter under a CMV promoter from the US1/US2 locus was constructed similarly by co-transfecting HSV-1 strain McKrae with a linearized plasmid and a Cas9 RNP targeting the site of integration (US1/2 gRNA target sequence: GTCTTAATGGCGGGAAGGG).
## HSV shotgun sequencing
DNA was extracted from viral stocks using Qiagen DNeasy kit. Shotgun libraries were prepared using Illumina DNA Prep kit and sequenced with Illumina Nextseq 2000, generating around 0.5 to 10 million 150 bp paired-end reads. Sequencing results were analyzed using Snippy (17) (https://github.com/tseemann/snippy), using the reference genomes of HSV-1 strain 17+ (Genbank JN555585). Genotypes are provided in Table S1.
## Mouse experiments
All animal procedures were approved by the Institutional Animal Care and Use Commit tee of the Fred Hutchinson Cancer Center, under protocol numbers 1865. This study was carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health ("The Guide"). Standard housing, diet, bedding, enrichment, and light/dark cycles were implemented under animal biosafety level 2 (ABSL2) containment. Female Swiss-Webster mice 5 to 6 weeks old were purchased from Charles River Laboratories.
## Ocular infection after corneal scarification
Mice were anesthetized by intraperitoneal injection of ketamine (100 mg/kg) and xylazine (10 mg/kg) and laid under a stereo microscope. Mice corneas were lightly scarified using a 28-gage needle, and 4 µL of viral inoculum was dispensed on both eyes. Following inoculation, ophthalmic drops of local analgesic (Diclofenac) were deposited on both eyes, and the analgesic Meloxicam was added to the drinking water ad libitum for 1-5 days following infection. From 5 to 15 days following primary infection, symptoms of infection were reported and scored using an in-house scoring system. Mice experiencing severe symptoms were humanely euthanized.
## Vaginal infection
Mice were treated with 2 mg of Depo-Provera injected subcutaneously. Five to 7 days later, mice were anesthetized by intraperitoneal injection of ketamine (100 mg/kg) and xylazine (10 mg/kg). The vaginal lumen was cleared with a Calginate swab, and 5 µL of viral inoculum was pipetted in the vagina. From 5 to 15 days following primary infection, symptoms of infection were reported and scored using an in-house scoring system. Mice experiencing severe symptoms were humanely euthanized.
## HSV reactivation and quantification of viral loads in swabs and tissues
HSV reactivation was performed by intraperitoneal injection of JQ1 (MedChemExpress, USA) at a dose of 50 mg/kg, as described previously (13)(14)(15). DNA extraction from swabs and HSV quantification by qPCR were performed as described previously. Total genomic DNA was isolated from ganglionic tissues using the DNeasy Blood and Tissues kit (Qiagen, Germantown, MD, USA) and eluted in 100 µL of EB buffer, per the manufac turer's protocol. Quantification of the YFP and CFP markers was measured by duplex ddPCR, as described previously (13).
## Statistics and reproducibility
Experiments were carried out in multiple replicates. Investigators were blinded when collecting swabs and analyzing DNA samples. No data were excluded. Statistical analyses were performed using GraphPad Prism version 10.1.1 for macOS (GraphPad Software, USA, www.graphpad.com).
## References
1. Taylor, Enquist (2015) "Axonal spread of neuroinvasive viral infections" *Trends Microbiol*
2. Diwaker, Wilson (2019) "Microtubule-dependent trafficking of alphaherpesviruses in the nervous system: the ins and outs" *Viruses*
3. Duraine, Johnson (2021) "Anterograde transport of α-herpesviruses in neuronal axons" *Virology (Auckl)*
4. Zaichick, Bohannon, Hughes et al. (2013) "The herpesvirus VP1/2 protein is an effector of dynein-mediated capsid transport and neuroinvasion" *Cell Host Microbe*
5. Krautwald, Fuchs, Klupp et al. (2009) "Translocation of incoming pseudorabies virus capsids to the cell nucleus is delayed in the absence of tegument protein pUL37" *J Virol*
6. Zhao, Zeng, Xu et al. (2016) "A viral deamidase targets the helicase domain of RIG-I to block RNA-induced activation" *Cell Host Microbe*
7. Pitts, Klabis, Richards et al. (2014) "Crystal structure of the herpesvirus inner tegument protein UL37 supports its essential role in control of viral trafficking" *J Virol*
8. Richards, Sollars, Pitts et al. (2017) "The pUL37 tegument protein guides alpha-herpesvirus retrograde axonal transport to promote neuroinvasion" *PLoS Pathog*
9. Bernstein, Cardin, Smith et al. (2020) "The R2 non-neuroinvasive HSV-1 vaccine affords protection from genital HSV-2 infections in a guinea pig model" *NPJ Vaccines*
10. Pickard, Brodersen, Sollars et al. (2020) "The pseudorabies virus R2 non-neuroinvasive vaccine: a proof-of-concept study in pigs" *Vaccine (Auckl)*
11. Stults, Sollars, Heath et al. (2022) "Bovine Herpesvirus 1 invasion of sensory neurons by retrograde axonal transport is dependent on the pUL37 region 2 effector" *J Virol*
12. Law, Herr, Cwick et al. (2018) "A new approach to assessing HSV-1 recombination during intercellular spread" *Viruses*
13. Walter, Haick, Riley et al. (2024) "Viral gene drive spread during herpes simplex virus 1 infection in mice" *Nat Commun*
14. Aubert, Strongin, Roychoudhury et al. (2020) "Gene editing and elimination of latent herpes simplex virus in vivo" *Nat Commun*
15. Aubert, Haick, Strongin et al. (2024) "Gene editing for latent herpes simplex virus infection reduces viral load and shedding in vivo" *Nat Commun*
16. Sedarati, Stevens (1987) "Biological basis for virulence of three strains of herpes simplex virus type 1" *J Gen Virol*
17. Seemann (2020) "Snippy: rapid haploid variant calling and core genome alignment" *GitHub*
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# P30 Impact of introducing antiviral stewardship reviews in a major acute teaching hospital
S Chong, S Zaidi, T Whitfield
## Abstract
® 2 AST-XN21 (bioMérieux, Marcy-l'Étoile, France)-for assessing the in vitro susceptibility of CRE strains to colistin, with broth microdilution (BMD) serving as the reference standard.® 25922, Pseudomonas aeruginosa ATCC ® 27853 and E. coli NCTC 13846.® 2 AST-XN21 method showed 96.8% CA, 89.1% EA, a VME rate of 1.06% (1/94) and an ME rate of 2.1% (2/94) (Table 1).® 2 AST-XN21 systems are reliable alternatives to the reference BMD method for colistin susceptibility testing in CRE isolates. However, further multicentre studies with larger sample sizes, incorporating molecular approaches to detect colistin resistance, are necessary to validate and expand upon these findings.
Background: All hospital trusts are required to have stewardship programmes to promote the judicious use of antimicrobials. These programmes have historically focused on antibiotics, although attention to antifungals has increased. However, few studies in the literature focused on antiviral stewardship (AVS). A shortage of parenteral aciclovir (ACV) arose in May 2024. During the contingency planning phase, we read of the success of virology stewardship reviews at University Hospitals Birmingham 1 and decided to introduce this locally.
Objectives: To introduce virology stewardship reviews at Salford Royal Hospital.; to reduce unnecessary usage of parenteral aciclovir ;and to promote good antiviral stewardship practice.
Methods: Virtual AVS reviews were performed by consultant virologist(s) and an antimicrobial pharmacist. Patients prescribed ACV IV were identified via the electronic prescribing system. Reviews were conducted biweekly initially then weekly for the last 2 weeks. Data was collected over 12 weeks between 9/5 and 31/7/24.
Results: A total of 41 reviews were performed for 19 patients The average time taken was 20 min per session. AVS recommendations were: continue (29), stop (6), dose modification (5) and oral switch (1). During the intervention period, mean monthly consumption of ACV IV in defined daily doses (DDDs) fell to 35.5 compared to 61.7 over the same period the previous year. Total expenditure on ACV IV over May-July 2024 was £950, a saving of £1299 compared to May-July 2023. Other Posters
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# Correction: The value of promoter methylation of fibroblast factor 21 (FGF21) in predicting the course of chronic hepatitis B and the occurrence of oxidative stress
Huihui Liu, Kai Wang, Xue Li, Pei Liu, Zhaohui Wang, Xuefei Wei, Shuai Gao, Yuchen Fan
## References
1. Li, Liu, Wang (2024) "The value of promoter methylation of fibroblast factor 21 (FGF21) in predicting the course of chronic hepatitis B and the occurrence of oxidative stress" *Virol J*
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# Potential Novel Genotype of "Bopivirus B" from Sheep in Türkiye: Epidemiology and Molecular Characterization
Hugo Ramírez-Álvarez, Ramsés Reina, Feray Alkan, İlke Karayel-Hacıo Glu, Selda Duran-Yelken, Fruzsina Tóth, Buket Pekşen, Ákos Boros
## Abstract
Various microbial agents have been found in the feces of both humans and animals, especially in newborns. While some of these agents are recognized as causing diarrhea, the role of others, specifically bopiviruses of the family Picornaviridae, in diarrhea remains uncertain. In this study, we conducted an analysis of 214 fecal samples from cattle (n = 114), sheep (n = 82), and goats (n = 18) with diarrhea, collected from farms across 17 different provinces in Türkiye. All samples were tested using RT-PCR targeting the 3D (RdRp) region of bopiviruses, and two samples from sheep (2.4%) tested positive. The 7303 nt-long complete coding sequence of Bopivirus/Sheep/KS-1M/2024/TUR and partial 3D (RdRp) , VP3, and 2A-2C sequences of Bopivirus/Sheep/ANK-K30/2017/TUR were determined by additional RT-PCR, 3 ′ RACE-PCR reactions and Sanger sequencing. Both strains show close sequence and phylogenetic relationship to members of species "Bopivirus B" of genus Bopivirus. Bopivirus/Sheep/KS-1M/2024/TUR is most closely related to a sheep Bopivirus B strain (sheep/14-73/2018/ITA) from Italy, but the phylogenetic separation, the low sequence identities and high p-distance values in VP1 to existing genotypes of "B1" and "B2" suggest that both strains could belong to novel genotypes ("B3" and "B4") in species "Bopivirus B", although additional closely related sequences are necessary for proper typing.
## 1. Introduction
The family Picornaviridae encompasses a large number of genera [1]. According to the International Committee on Taxonomy of Viruses (ICTV), this family currently includes 68 genera and 159 species [2]. Members of the genus Bopivirus have c.a. 7.8 kb-long positivesense single-stranded RNA genomes which contain a single open reading frame (ORF) flanked by 5 ′ and 3 ′ untranslated regions (UTRs) and a 3 ′ terminal poly(A)-tail [3,4]. The 5 ′ UTRs contain a type II internal ribosomal entry site (IRES) [3]. The ORF is organized as follows: VP4-VP2-VP3-VP1-2A-2C-3A-3D [3,4].
Currently, there is only a single officially accepted species (Bopivirus abovi, formerly called as Bopivirus A) in the genus Bopivirus, although the viruses temporarily named "ovipivirus" (from sheep) and "gopivirus" (from goats) in fecal samples collected from clinically healthy animals in Hungarian farms also belonged to this genus [3]. These viruses, which might belong to two genotypes ("B1" and "B2"), show only a distant genetic relationship to bovine bopiviruses of the species Bopivirus abovi and, based on ICTV classification criteria, have been proposed to represent a novel species, "Bopivirus B". Around the same time, a genetically distinct bopivirus (with 57-79% nucleotide similarity to previously reported bovine, ovine, and caprine bopiviruses) was identified in fecal samples from fallow deer and red deer in Australia. This novel virus was also proposed as a member of an additional novel species, "Bopivirus C" [4]. These findings reveal the presence of genetically highly diverse bopiviruses in both domestic and wild even-toed ungulates. In addition to reports from Hungary [3] and Australia [4], relevant studies involving domestic and wild animals have also been reported in Italy [5,6], USA (PV TCH6/2013/USA; GenBank accession no. KM589358, unpublished sequence), China [7,8], and New Zealand [9]. Although bopiviruses have been reported in various species, the virus-host relationship and geographic patterns of bopiviruses have not been fully elucidated. Therefore, studies on molecular characterization of new bopivirus strains from different hosts will provide valuable information about the origin, distribution, and diversity of these viruses.
This study aims to investigate the prevalence and genetic divergence of bopiviruses in sheep, goats, and cattle in Türkiye. By analyzing diagnostic enteric samples obtained from both healthy and diarrheic animals, this study also suggests the potential role of bopiviruses in diarrheal diseases and data on the species and bopivirus genetics.
## 2. Materials and Methods
## 2.1. Diagnostic Samples
This study analyzed 214 fecal samples from three ruminant species: cattle (n = 114), sheep (n = 82), and goats (n = 18). Samples were collected from diarrheic calves under six months of age, as well as from sheep and goats younger than two years, between 2009 and 2024 across 17 provinces. Among the sheep, the samples were obtained from diarrheic animals (n = 63) and clinically healthy animals (n = 19). For the goats, samples were collected from diarrheic (n = 12) and clinically healthy animals (n = 6). The geographical and species-specific distribution of these diagnostic materials is shown in Figure 1.
## 2.2. Ethical Considerations
This study was conducted with the approval of the Ethics Committee of Ankara University (Decision No: 2024-04-24).
## 2.3. Nucleic Acid Extraction and RT-PCR-Based Screening and Genome Determination Reactions
Viral RNA was extracted from 1:10 (w/v) fecal suspensions using the Biospin Virus DNA/RNA Extraction kit (BioFlux, Bioer, Hangzhou, China), in accordance with the manufacturer's protocol. All RNA extracts were stored at -80 • C until analysis. Reverse transcription was carried out using the RevertAid First Strand cDNA Synthesis Kit (Thermo Fisher Scientific, Waltham, MA, USA), following the manufacturer's instructions.
All fecal samples were initially screened by RT-PCR targeting the 3D (RdRp) gene region of bopiviruses, following the screening primers and protocol of László et al. [3], using DreamTaq DNA polymerase (Thermo Fisher Scientific) according to the manufacturer's recommendations (Table S1). Samples that tested positive were subsequently subjected to VP1-specific RT-PCR using a bopivirus-specific VP1 primer pair designed for all known bopivirus sequences [3] (Table S1). For the VP1-positive sample, the complete coding sequence was determined by combining multiple RT-PCR reactions with overlapping products and a primer-walking strategy (Table S1). The 3 ′ end of the genome was determined using the 3 ′ /5 ′ RACE (rapid amplification of cDNA ends) Kit, 2nd Generation (Roche Diagnostics, Mannheim, Germany). All primers used in this study, along with their genomic positions and expected amplicon sizes, are listed in Table S1. PCR products were sequenced by the Dye-terminator (Sanger) sequencing technique through a commercial service provided by Ankara University Rare Diseases Application and Research Center (Ankara, Türkiye). The complete coding sequence of Bopivirus/Sheep/KS-1M/2024/TUR and partial 3D (RdRp) sequence of Bopivirus/Sheep/ANK-K30/2017/TUR strains can be accessed in GenBank under accession numbers of PX610292 and PX610293.
## 2.4. Sequence and Phylogenetic Analyses
The generated sequence data were analyzed using the BLASTn service provided by the National Center for Biotechnology Information (NCBI). Sequences were aligned using AliView [10] and the MUSCLE algorithm [11]. Multiple sequence alignments were conducted with all available bopivirus sequences obtained from GenBank.
Phylogenetic analyses were performed using the Maximum Likelihood method with either MEGA X software [12] for partial 3D (RdRp) and complete P1, 2C and 3CD or IqTree [13] for VP1 sequences. The 'Find Best Model' tool was used to select the optimal evolutionary models, which were specified in the figure legends of the corresponding phylogenetic trees. All trees were generated with 1000 bootstrap replicates.
Nucleotide (nt) and amino acid (aa) identity comparisons were performed using the Sequence Identity and Similarity (SIAS) online tool (http://imed.med.ucm.es/Tools/sias. html; accession date: 13 November 2025). Pairwise distance (P-dist) matrix was calculated from the complete bopivirus VP1 nt alignment by MEGAX [12], and a frequency distribution histogram was created using Excel 2510 ver.16.0.19 of Microsoft 365. Recombination Detection Program (RDP) ver. 4.101 was applied for distance plot calculations using the Similarities model with a window size of 200 nt and a step size of 20 nt [14]. The potential secondary RNA structure of the 5 ′ UTR was generated by the Mfold software [15].
## 3. Results
## 3.1. Detection of Bopivirus Based on the 3D (RdRp) Region
Among the 214 diagnostic samples analyzed in this study, only two of the 82 sheep tested positive, corresponding to an overall positivity rate of 2.4% among sheep. The prevalence rate on the farm where Bopivirus/Sheep/KS-1M/2024/TUR was detected was 20% (1/5), whereas Sheep/ANK-K30/2017/TUR originated from a farm from which only a single sample had been collected. Although samples were collected from both diarrheic and clinically healthy sheep, bopivirus was detected exclusively in diarrheic lambs (2/63, 3.1%). The 587 bp-long fragments of the 3D (RdRp) share 97.44% nucleotide (nt) and 98.97% amino acid (aa) pairwise sequence identity. Additionally, based on BLASTnbased sequence analysis, they exhibited at least 95.22% nt and 96.41% aa identity with Bopivirus B viruses, with the highest percentage (≈98%) to an unpublished Bopivirus sp. isolate caprine/China/SWUN/B5 (OP272478) from China. In contrast, their sequence identities with the members of other Bopivirus species (Bopivirus abovi and "Bopivirus C") were significantly lower, with a maximum of 71.03% nt and 72.82% aa identity. Based on sample data, which includes host species, origin provinces, sample code, and year of collection, the viruses identified in this study were named as Bopivirus/Sheep/ANK-K30/2017/TUR (PX610293) and Bopivirus/Sheep/KS-1M/2024/TUR (PX610292).
Phylogenetic analysis of the partial 3D (RdRp) sequences indicates that the detected viruses clustered within the Bopivirus B lineage with bopiviruses from small ruminants (Figure 2), thereby supporting their classification within this recently described species ("Bopivirus B").
## 3.2. Complete Coding Sequence Analyses of Bopiviruses Detected
For further molecular characterization and genotype identification of the bopiviruses detected in this study-Bopivirus/Sheep/ANK-K30/2017/TUR and Bopivirus/Sheep/KS-1M/2024/TUR-multiple RT-PCR reactions with bopivirus-specific primer pairs (Table S1) generating overlapping products were performed. The generated PCR products were sequenced by Sanger sequencing with the primer walking method. With this technique, the 7303 nt-long (the c.a. 68 nt-long 5 ′ end is missing) complete coding sequence (CDS) of Bopivirus/Sheep/KS-1M/2024/TUR could be determined. Unfortunately, only a 359 nt-and a 710 nt-long partial VP3 and partial 2A-2C were successfully obtained from Bopivirus/Sheep/ANK-K30/2017/TUR which show 86.62% nt/92.43% aa and 94.67% nt/97.04% aa identity to the corresponding genome parts of Bopivirus/Sheep/KS-1M/2024/TUR, respectively.
The determined CDS of Bopivirus/Sheep/KS-1M/2024/TUR was predicted to contain a single open reading frame (ORF) and follows the general genome layout of bopiviruses:
The 620 nt-long partial 5 ′ UTR shows 97.27% nt identity to the most identical 5 ′ UTR of Bopivirus sp. strain ovine/TB14/2010-HUN (MW298057) and shows similar secondary RNA structure as the type II IRES of bopiviruses. The 77 nt-long 3 ′ UTR also shows the highest (97.4%) sequence identity to the corresponding genome part of ovine/TB14/2010-HUN.
The 6606 nt-long ORF encodes a 2201 aa-long single viral polyprotein which shows 91.89% nt and 95.32% aa pairwise identity to the closest match of Bopivirus/sheep/14-73/2018/ITA (ON497047) of species "Bopivirus B" identified by BLAST searches. Nucleotide distance plot of the complete CDS of study strain Bopivirus/Sheep/KS-1M/ 2024/TUR scanned against the representative members of species "Bopivirus B" including Bopivirus/sheep/14-73/2018/ITA show the relatively small sequence divergence ranged between 1.3% (at 5 ′ UTR) and 15.8% (at VP3) across the CDS of the study strain except the VP1 region where the divergence is up to 35.5% indicates that VP1 shows the highest divergence relative to other regions (Figure 3). The nt phylogenetic trees of complete 2C and 3CD non-structural regions also indicate a close relationship of the study Bopivirus/Sheep/KS-1M/2024/TUR strain to all the members of species "Bopivirus B" (Figure 4B,C), while in the P1 and VP1 capsid trees Bopivirus/Sheep/KS-1M/2024/TUR is located on a distinct lineage together with Bopivirus/sheep/14-73/2018/ITA among "Bopivirus B" viruses but also considerably separated from each other (Figures 4A and5). In the VP1 genomic region, Bopivirus/Sheep/KS-1M/2024/TUR also showed the highest sequence identity to Bopivirus strain sheep/14-73/2018/ITA (ON497047), with 82.51% nt and 86.31% aa identity. In contrast, its sequence identities with the other "Bopivirus B" strains are less than 76.87% and even lower (≤52.11%) with the members of Bopivirus abovi and "Bopivirus C" (Table 1). In the frequency distribution of pairwise VP1 nt distances, the lowest calculated p-distance of Bopivirus/Sheep/KS-1M/2024/TUR was 0.18 compared to the most closely related bopivirus strain sheep/14-73/2018/ITA (ON497047), which is higher than the intra-, but lower than the intergenotypic distance ranges proposed by Laszló et al. [3] (Figure 6). All other p-distances of Bopivirus/Sheep/KS-1M/2024/TUR are ≥0.23 which is in the range of intergenotypic p-distances. The p-distances of sheep/14-73/2018/ITA (≥0.21) are also within this range. Meanwhile, comparison of the full-length Bopivirus/Sheep/KS-1M/2024/TUR VP1 aa sequence to selected representatives of "Bopivirus B" genotypes, including the strain sheep/14-73/2018/ITA (ON497047), revealed various amino acid deletions and substitutions that set Sheep/KS-1M/2024/TUR and sheep/14-73/2018/ITA apart from genotypes of "B1" and "B2" like a four-amino acid deletion between S127 and G132 compared to strains of genotypes "B1" and "B2" (Figure 7). There are also aa substitutions which also make Sheep/KS-1M/2024/TUR different from sheep/14-73/2018/ITA (Figure 7). Interestingly the four-amino acid deletion between N184 and A188 previously reported in B2 genotype strains [7] is not observably in the corresponding genome region of the study strain.
$$5 ′ UTR-ORF: [VP4-VP2-VP3-VP1-2A-2B-2C-3A-3B-3C-3D]-3 ′ UTR.$$
## 4. Discussion
Although many Picornaviridae viruses are well characterized, several newly identified members-such as hunnivirus, kobuvirus, boosepivirus, and bopivirus-have been increasingly reported in recent years [3,[5][6][7][8][9][16][17][18]. Since the detection of the first bopivirus genome (Bopivirus A1; KM589358) in 2013, bopiviruses have been identified in a wide range of domestic and wild animal species in numerous countries [3][4][5][6][7][8][9]. Collectively, current evidence indicates that bovine strains belong to Bopivirus abovi, sheep and goat strains to "Bopivirus B", and deer strains to "Bopivirus C", highlighting the increasing diversity and host range within this emerging group of picornaviruses. Despite their widespread occurrence, there remains a need for comprehensive studies to elucidate their epidemiological patterns, the factors influencing their transmission, the genetic characteristics of these viruses and, their potential role as causative agents of diarrhea.
Studies on calf diarrhea in Türkiye have predominantly focused on rotaviruses and coronaviruses, reporting both their epidemiological roles and molecular characteristics [19][20][21]. Additional research has documented several other viral agents-including caliciviruses, picornaviruses, and astroviruses-in diarrheic calves [22][23][24][25]. In contrast, investigations targeting viral enteropathogens in sheep and goats remain scarce, with only a few reports available [16,26,27].
This study aimed to investigate the prevalence and genotype diversity of bopiviruses in sheep, goats, and cattle across a broad geographical range in Türkiye over an extended period (2009-2024), including retrospective fecal samples from numerous farms (Figure 1). Among the sheep samples analyzed, two (2.4%; 2/82) tested positive for bopivirus, thus providing the first evidence of bopivirus presence in Turkish sheep. However, the overall positivity rate was lower than reported in Italy (10.9%; 14/128) [5] and Hungary (36.2%; 17/47) [3], but the farm-level prevalence (20% in the farm of Bopivirus/Sheep/KS-1M/2024/TUR) is in the reported range. Variations in epidemiological data across countries are expected due to differences in husbandry practices, sampling criteria, and clinical status. Among the samples analyzed in the present study, none of the cattle and goat fecal samples tested positive by RT-PCR. Although these species were sampled in the same provinces as the positive sheep, limited information on sampling years, farm locations, and grazing practices prevents any inference about cross-species transmission. More extensive studies are required to better understand the epidemiology of bopivirus across different host species in Türkiye.
Bopivirus has been detected in both clinically healthy and diarrheic animals, with higher prevalence in young ruminants and lower apparent epidemiological significance in adults [3,5,7]. Notably, co-infections with other picornaviruses-such as caprine enterovirus, kobuvirus, and hunnivirus-have also been reported [7]. Overall, information on the biological significance and true prevalence of bopivirus remains limited. In the present study, bopivirus was found exclusively in samples from sheep suffering from diarrhea (2/63, 3.1%), and the two bopiviruses identified were detected in diarrheic lambs. Although the detection of positive cases exclusively in diarrheic lambs may suggest an age-related pattern, the low prevalence prevents any definitive conclusions. It should also be noted that the sample, in which Bopivirus/Sheep/ANK-K30/2017/TUR was identified, had been included in a previous study [26] and tested for additional viral pathogens. That sample was found to be positive for rotavirus and picobirnavirus, whereas the Bopivirus/Sheep/KS-1M/2024/TUR sample tested negative for rotavirus in a routine diagnostic screening.
Gastroenteritis severity reflects the interplay between the types of co-infecting agents, viral load and host immunity. High viral replication promotes epithelial damage and barrier dysfunction, while effective immune responses limit replication but may drive symptoms via inflammation. Based on current knowledge bopiviruses are widespread in ruminant species, as more data become available, the potential contribution of bopivirus-either alone or in mixed infections-to diarrheal disease will likely become clearer.
The 3D (RdRp) gene of picornavirus is relatively conserved, yet it also exhibits genetic diversity associated with geographic and host factors. These features make the 3D (RdRp) gene a suitable target for molecular epidemiological analyses. Phylogenetic analyses based on the 3D (RdRp) gene region (Figure 2), together with identity data-showing at least 95.22% nt and 96.41% aa identity with "Bopivirus B" viruses, whereas identities with other bopiviruses (Bopivirus abovi and "Bopivirus C") were at most 71.03% nt and 72.82% aa identity -indicate host-specific clustering of bopivirus genotypes [3,[5][6][7]. Consistent with these observations, the viruses detected in sheep in this study, Bopivirus/Sheep/ANK-K30/2017/TUR and Bopivirus/Sheep/KS-1M/2024/TUR, clustered within "Bopivirus B" (Figure 2).
Epidemiological investigations of circulating bopivirus genotypes will enhance current knowledge and inform assessments of interspecies transmission, host range restrictions, and clinical impacts, especially among small ruminants. László et al. [3] described two VP1 genotypes (B1 and B2) circulating among sheep and goats in Hungary, regardless of host species. The complete VP1 sequence obtained in this study is 921 bp long, slightly shorter than the B2 (924 bp) and B1 (933 bp) genotypes registered in GenBank. Yang et al. [7] reported a three-amino acid deletion between N184 and A188 in all Bopivirus B2 strains compared to the Bopivirus B1 genotypes. Our analysis indicate that this deletion is present exclusively in B2 genotype bopiviruses within Bopivirus B. Interestingly, both the Bopivirus/Sheep/KS-1M/2024/TUR and the Italian sheep/14-73/2018/ITA (ON497047) strains harbor a four-amino acid deletion between positions S127 and G132, distinguishing them from the "B1" and "B2" genotypes; however, the Bopivirus/Sheep/KS-1M/2024/TUR strain also contains multiple additional unique amino acid substitutions. Nucleotide and amino acid identity analyses (Table 1) show 82.51% and 86.31% identity between these two strains, respectively, while identity with other Bopivirus B genotypes does not exceed 76.87% nt and 82.08% aa. Bopivirus/Sheep/KS-1M/2024/TUR is most closely related to a sheep Bopivirus B strain (sheep/14-73/2018/ITA) from Italy (ON497047), but the phylogenetic separation, the low sequence identities and high p-distance values and several unique aa mutations in VP1 compared to existing genotypes of "B1" and "B2" suggest that both strains could belong to either a single ("B3") or two novel genotypes ("B3" and "B4") in species "Bopivirus B", although additional closely related sequences are necessary for proper typing.
In conclusion, this study demonstrated the presence of Bopivirus B in sheep in Türkiye and provided preliminary insights into its possible epidemiological characteristics. The findings also suggest two novel Bopivirus B genotypes, underscoring the VP1 genetic diversity observed in both the Bopivirus/Sheep/KS-1M/2024/TUR and a Bopivirus/sheep/14-73/2018/ITA (ON497047) from Italy. Further studies are warranted to elucidate the pathogenic potential and clinical significance of Bopivirus B in sheep and other ruminant species. Continued surveillance efforts, together with comprehensive molecular characterization and epidemiological investigations, will contribute to a better understanding of Bopivirus species and its implications for animal health.
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13. Trifinopoulos, Nguyen, Haeseler et al. (2016) "W-IQ-TREE: A fast online phylogenetic tool for maximum likelihood analysis" *Nucleic Acids Res*
14. Martin, Varsani, Roumagnac et al. (2021) "RDP5: A computer program for analyzing recombination in, and removing signals of recombination from, nucleotide sequence datasets" *Virus Evol*
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28. "The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods"
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# Correction: Immunogenicity of differentially glycosylated Marburg virus glycoproteins expressed in mammalian and insect cells
Guanying Zhang, Jie Li, Shaoyan Wang, Yue Cui, Liyuan Song, Zhenwei Song, Ping Huang, Xiangyang Chi, Ting Fang, Yunzhu Dong, Ruihua Li, Pengfei Fan, Yaoxing Wang, Lei Bi, Jianmin Li, Changming Yu
In this article [1], Guanying Zhang should have been denoted as a corresponding author. The original article has been corrected.
## References
1. Li, Wang, Cui (0288) "Immunogenicity of differentially glycosylated Marburg virus glycoproteins expressed in mammalian and insect cells" *Virol J*
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# False-negative CMV PCR results due to viral sequence variation: a diagnostic pitfall with the potential for serious consequences
Huanyu Wang, Monica Ardura, Sophonie Oyeniran, Amy Leber
## Abstract
Background Cytomegalovirus (CMV) continues to be a significant cause of morbidity and mortality in immunocompromised patients. Nucleic acid amplification tests (NAATs) are the preferred method for both diagnosing CMV infection and monitoring response to antiviral therapy in these patients. The use of a sensitive and specific CMV NAAT is essential to ensure early and reliable detection.Case Summary A 4-month-old patient with familial hemophagocytic lymphohistiocyto sis received an allogeneic hematopoietic cell transplant (HCT). Weekly CMV monitoring before and after HCT was performed using an in-house quantitative CMV PCR assay that targets the CMV UL54 gene. Review of the amplification curves of PCR runs raised concerns about potential false-negative results. Sequencing of the patient sample identified nucleotide mutations within the probe-binding site, confirming the cause of the assay failure. These false-negative results led to delayed detection of CMV DNAemia before HCT and delayed initiation of CMV preemptive antiviral therapy after transplant.
ConclusionThis case underscores the critical importance of rigorous and routine evaluation of CMV NAATs by clinical laboratories. Laboratories should recognize the limitations of NAATs and implement strategies to address them. In situations where laboratory findings conflict with clinical data, clinicians should critically assess a negative NAAT result. If CMV infection remains a concern, testing with an alternate PCR assay targeting a different gene should be considered. KEYWORDS transplant, CMV, NAAT, immunocompromised, false negative C ytomegalovirus (CMV), a beta-herpes virus, causes significant morbidity and mortality in immunocompromised patients and is the leading cause of congeni tal infection and hearing loss in children in industrialized countries (1). Nucleic acid amplification tests (NAATs) are preferred for diagnosis and monitoring response to CMV-directed therapy. Primers and/or probes typically target highly conserved regions of the genome, such as glycoprotein B (UL55), DNA polymerase (UL54), matrix phosphopro tein (UL83), or major immediate-early (MIE) gene (2-4). However, nucleotide variability within UL55 and MIE genes causing false-negative results has been reported (2, 5-7).The Clinical Microbiology Laboratories at Nationwide Children's Hospital has offered a laboratory-developed quantitative real-time PCR assay targeting a 61 bp fragment of the UL54 gene from plasma as the standard-of-care molecular assay since 2003 (SOC-PCR) (3). Here, we describe a pediatric hematopoietic cell transplant (HCT) patient in whom this assay produced false negatives due to mutations in UL54, delaying initiation of CMV therapy.
## CASE PRESENTATION
A 4-month-old patient with familial hemophagocytic lymphohistiocytosis (homozygous PRF1 mutation) received myeloablative conditioning and a 10/10 matched unrelated allogeneic HCT from a CMV-seropositive donor (recipient was CMV seropositive). Pre-HCT CMV NAAT testing was negative. The infant was considered at high risk of CMV reactivation, and per institutional protocol, preemptive prophylaxis management with twice-weekly CMV monitoring by SOC-PCR on plasma was performed post-transplant and was not detected.
Thirteen days post-HCT (D + 13), the patient developed respiratory failure requir ing intubation and progressive bilateral multifocal ground-glass opacities on imaging, consistent with alveolar hemorrhage and potential CMV pneumonitis. Infectious disease evaluation was negative, including blood cultures and adenovirus, herpes simplex virus, human herpes virus 6 PCRs and CMV-SOC PCR, respiratory tract secretions for bacterial cultures, adenovirus, HSV, Pneumocystis jirovecii PCRs and CMV-SOC PCR and multiplex respiratory panel (BioFire Respiratory Panel 2.0), as well as Aspergillus galactomannan (Platelia Aspergillus Ag). The evaluation was further expanded to include Legionella PCR, Aspergillus and Mucorales PCR on lower respiratory tract secretions with reflex to universal broad-range fungal PCR and Legionella urine antigen; all were negative. The patient achieved neutrophil engraftment on D + 21, and weekly CMV SOC-PCR monitoring remained negative (Fig. 1).
On D + 29, the patient's plasma exhibited an unusual amplification curve on the CMV SOC-PCR. The signal did cross the detection threshold and increased in amplitude slightly; it did not display logarithmic growth. Review of prior runs, although not crossing the threshold, showed similar atypical curves in samples previously reported as negative (Fig. 2A). These findings raised concern for false-negative results; therefore, the D + 29 sample was reported as indeterminate. The treating team was notified of this unusual result, and D + 29 plasma was sent to a reference laboratory using a PCR targeting the CMV US9 gene. On the following day (D + 30), the plasma again demonstrated the same unusual amplification curve and was reported as positive after review. On D + 31, the reference laboratory reported a viral load of 1,260,000 IU/mL (6.1 log 10 IU/mL) for the D + 29 sample, confirming our suspicion. Ganciclovir (5 mg/kg/dose every 12 hours) was started for CMV DNAemia (D + 31), and intravenous CMV immunoglobulin was given for possible CMV pneumonitis. Foscarnet (60 mg/kg/dose every 8 hours) was added to the treatment regimen. Weekly CMV monitoring was subsequently performed at the reference laboratory. Despite treatment, downtrending CMV PCR, and no evidence of hepatitis or retinitis, the patient remained critically ill. Plasma collected on D + 37 and D + 51 was sent to a reference laboratory to detect mutations within UL97 and UL54 genes by Sanger sequencing, and no mutations associated with ganciclovir or foscarnet resistance were found. On D + 51, the patient acutely developed refractory hypoxemia and asystolic cardiac arrest not responsive to resuscitation efforts.
The patient was CMV seropositive prior to the transplant; however, this was consid ered likely reflective of passive maternal antibody, and all CMV NAAT results pre-HCT were negative. To investigate further, we developed another CMV PCR targeting the US9 gene (US9-PCR) testing all available remnant specimens (Fig. 1). We detected CMV DNAemia pretransplant and rising DNAemia post-HCT, demonstrating that the SOC-PCR had repeatedly produced false-negative results. This led to delayed detection of CMV DNAemia and delayed initiation of CMV preemptive therapy by 16 days.
One of the patient's samples was sequenced in the region targeted by SOC-PCR, which revealed two C-T substitutions within the probe-binding site (Fig. 2B), confirming the false-negative results were due to sequence variation. Searches of publicly availa ble databases (NCBI, accessed 8 June 2025) revealed three reports of these mutations: Belgium (GenBank KP745705, submitted 2015), Germany (GenBank JX512203, 2016), and Czech Republic (KY490065, 2017).
## DISCUSSION
HCT recipients at risk of CMV disease (all CMV-seropositive recipients and CMV-seroneg ative recipients with a CMV-seropositive donor) are monitored closely for CMV. The preemptive therapy strategy, involving monitoring for CMV DNAemia during at-risk periods and initiating antivirals when the CMV load reaches a certain threshold, has been proven highly effective in preventing CMV end-organ disease (8,9). Furthermore, pretransplant CMV DNAemia is a strong risk factor for post-HCT CMV reactivation and associated complications (10,11). Antiviral therapy to clear CMV DNAemia pre-HCT reduces the risk of reactivation post-HCT (10). With the US9-PCR, we detected CMV DNAemia in pretransplant samples and rising in DNAemia post-HCT, demonstrating that the SOC-PCR had repeatedly produced false negatives.
NAATs are inherently susceptible to false-negative results due to sequence diversity in the target genome. Extensive variability in the CMV genome and demonstration of multiple variants coexisting in an individual make assay design challenging (12,13). In one prior report, it was found that samples from a leukemia patient undergoing antiviral therapy tested falsely negative on the COBAS assay (UL54 target) for a period of 2 months. Retrospective testing with a dual target PCR assay (UL54 and UL55) revealed high viral loads. These false-negative results delayed appropriate antiviral treatment. Although sequencing was not performed, the authors suggested that mutations within the primer/probe-binding regions were the probable cause (7). Additionally, a mismatch in the primer/probe region can lead to falsely low viral load. In the aforementioned study, viral loads for other samples tested were considerably lower for the UL55 assay than for the UL54 assay. Subsequent sequencing revealed a mismatch within the primer/probe for the UL55 assay (7).
Given the serious consequences of a false-negative CMV results, we implemented a surveillance program to screen SOC-PCR negative samples with the US9-PCR assay. Among >3,000 samples testing negative on the SOC-PCR that have been screened to date, four additional samples from four unique patients tested positive by US9-PCR assay. We sequenced one of these samples, revealing the same mutations as described in this case. This suggests that the primer/probe used in the SOC-PCR remains broadly inclusive and that strains carrying mutations compromising detection are relatively rare. Nevertheless, it is important for clinical laboratories and assay manufacturers to evaluate the inclusivity of their assays periodically. A 2009 study evaluating published CMV primers/probes identified a primer/probe set targeting UL54, which is the one used in our SOC-PCR, as one of the three most sensitive sets for CMV detection. In silico analysis revealed only one mismatch within the Towne strain (14). Our recent analysis of 462 published CMV sequences (NCBI, accessed 8 June 2025) identified 47 with at least one mismatch in the SOC-PCR binding region, although most involved a single mismatch unlikely to affect assay performance. This highlights the importance of ongoing evaluation of NAATs against newly submitted sequences. As mandated by the College of American Pathologists, clinical laboratories are required to evaluate laboratory-developed NAATs for compatibility with currently circulating microbial strains, thus ensuring continued diagnostic accuracy.
To enhance inclusivity, some CMV NAATs incorporate two distinct genomic targets as the likelihood of concurrent mutations in two conserved regions is low. Among eight FDA-approved CMV NAATs (Table 1), two utilize both UL34 and UL80.5 as targets. In one multicenter evaluation of the Alinity mCMV assay, only 8 of 336 positives were missed, and one discordant sample showed a higher load by Alinity than by a single-target reference PCR, suggesting target-region mismatch in the reference assay (15). Another study also demonstrated high agreement between the Alinity mCMV and a reference method (16). Single-target commercial assays have also shown high sensitivity and specificity (17-24) (Table 1), though rare false negatives do occur. A study of ARTUS CMV PCR demonstrated false lowering of viral loads with mismatches in the MIE target implicated as the cause (25). Notably, three FDA-approved assays use UL54 alone, but their proprietary primer/probe sequences preclude in silico inclusivity checks by users.
Although not clinically available at the time, metagenomic next-generation sequencing (mNGS) could have allowed for broad pathogen detection in blood and pulmonary fluid samples in this case (30) as mNGS is not susceptible to sequence diversity and can detect mutated pathogens as efficiently as the wild-type strains.
To the best of our knowledge, CMV UL54 mutations causing diagnostic failure have not been previously reported. Our case underscores the importance of rigorous and routine evaluation of CMV NAATs, even with well-characterized primer/probe sets. Laboratories should be aware of the limitations of NAATs and implement mitiga tion strategies, such as reviewing amplification curves for unusual patterns, periodic in silico analysis, thorough literature review, close communication with clinicians to identify potential false-negative cases, and considering use of multitarget assays. When laboratory findings conflict with clinical data, clinicians should critically assess a negative NAAT result and consider testing using an alternative gene target or mNGS for broader pathogen coverage.
## References
1. Leber (2024) "Maternal and congenital human cytomegalovirus infection: laboratory testing for detection and diagnosis" *J Clin Microbiol*
2. Novak, Chowdhury, Ross et al. (2011) "Diagnostic consequences of cytomegalovirus glycoprotein B polymor phisms" *J Clin Microbiol*
3. Sanchez, Storch (2002) "Multiplex, quantitative, real-time PCR assay for cytomegalovirus and human DNA" *J Clin Microbiol*
4. Boppana, Ross, Novak et al. "National Institute on Deafness and Other Communication Disorders CMV and Hearing Multicenter Screening (CHIMES) Study. 2010. Dried blood spot real-time polymerase chain reaction assays to screen newborns for congenital cytomegalovirus infection" *JAMA*
5. Lengerova, Racil, Volfova et al. (2007) "Real-time PCR diagnostics failure caused by nucleotide variability within exon 4 of the human cytomegalovirus major immediate-early gene" *J Clin Microbiol*
6. Nye, Leman, Meyer et al. (2005) "Sequence diversity in the glycoprotein B gene complicates real-time PCR assays for detection and quantification of cytomegalovirus" *J Clin Microbiol*
7. Herrmann, Larsson, Rubin et al. (2004) "Comparison of a duplex quantitative real-time PCR assay and the COBAS Amplicor CMV Monitor test for detection of cytomegalovirus" *J Clin Microbiol*
8. Boeckh, Ljungman (2009) "How we treat cytomegalovirus in hematopoietic cell transplant recipients" *Blood*
9. Gutierrez, Stanek, Ardura et al. (2024) "Cytomegalovirus viral load at initiation of pre-emptive antiviral therapy impacts cytomegalovi rus dynamics in pediatric allogeneic hematopoietic cell transplantation recipients" *Transpl Infect Dis*
10. Zamora, Xie, Sadowska-Klasa et al. (2024) "CMV reactivation during pretransplantation evaluation: a novel risk factor for posttransplantation CMV reactivation" *Blood Adv*
11. Fries, Riddell, Kim et al. (2005) "Cytomegalovirus disease before hematopoietic cell transplanta tion as a risk for complications after transplantation" *Biol Blood Marrow Transplant*
12. Ross, Novak, Pati et al. (2011) "Mixed infection and strain diversity in congenital cytomegalovirus infection" *J Infect Dis*
13. Schnepf, Dhédin, Mercier-Delarue et al. (2013) "Dynamics of cytomegalovirus populations harbouring mutations in genes UL54 and UL97 in a haematopoietic stem cell transplant recipient" *J Clin Virol*
14. Habbal, Monem, Gärtner (2009) "Comparative evaluation of published cytomegalovirus primers for rapid real-time PCR: which are the most sensitive" *J Med Microbiol*
15. Lee, Albert, Wessels et al. (2023) "Multicenter performance evaluation of the Alinity m CMV assay for quantifying cytomegalovirus DNA in plasma samples" *J Clin Microbiol*
16. Kostera, Hubbard, Jackson et al. (2024) "Evaluation of Alinity m CMV assay performance for detecting CMV in plasma, cerebrospinal fluid, and bronchoalveolar lavage specimens" *Diagn Microbiol Infect Dis*
17. Schneider, Kollender, Hilfrich et al. (2024) "Evaluation of an automated real-time transcription-mediated amplification (TMA) assay for detection and quantification of cytomegalovirus DNA in different clinical specimens" *J Clin Virol*
18. Fernholz, Vidal-Folch, Hasadsri (2023) "Rapid and direct detection of congenital cytomegalovirus using a commercial real-time PCR assay" *J Clin Microbiol*
19. Costa, Chibo, Soloczynskyj et al. (2025) "Evaluation and comparison of three high throughput assays (Alinity m CMV, Aptima CMV Quant and cobas CMV) for quantifying CMV DNA in plasma samples" *J Virol Methods*
20. Chiereghin, Pavia, Gabrielli et al. (2017) "Clinical evaluation of the new Roche platform of serological and molecular cytomegalovirus-specific assays in the diagnosis and prognosis of congenital cytomegalovirus infection" *J Virol Methods*
21. Pritt, Germer, Gomez-Urena et al. (2013) "Conversion to the COBAS AmpliPrep/COBAS TaqMan CMV Test for management of CMV disease in transplant recipients" *Diagn Microbiol Infect Dis*
22. Gantt, Goldfarb, Park et al. (2020) "Performance of the alethia CMV assay for detection of cytomegalovirus by use of neonatal saliva swabs" *J Clin Microbiol*
23. Sam, Rogers, Ingersoll et al. (2023) "Evaluation of performance characteristics of the aptima CMV quant assay for the detection and quantitation of CMV DNA in plasma samples" *J Clin Microbiol*
24. Lima, Healer, Rowe et al. (2023) "Performance evaluation of the Aptima CMV quant assay using plasma and non-plasma samples" *J Clin Virol*
25. Waggoner, Ho, Libiran et al. (2012) "Clinical significance of low cytomegalovirus DNA levels in human plasma" *J Clin Microbiol*
26. Schnepf, Scieux, Resche-Riggon et al. (2013) "Fully automated quantification of cytomegalovirus (CMV) in whole blood with the new sensitive Abbott RealTime CMV assay in the era of the CMV international standard" *J Clin Microbiol*
27. Tremblay, Rodrigue, Deschênes et al. (2015) "Cytomegalovirus quantification in plasma with Abbott RealTime CMV and Roche Cobas Amplicor CMV assays" *J Virol Methods*
28. Furione, Rognoni, Cabano et al. (2012) "Kinetics of human cytomegalovirus (HCMV) DNAemia in transplanted patients expressed in international units as determined with the Abbott RealTime CMV assay and an in-house assay" *J Clin Virol*
29. Michelin, Hadzisejdic, Bozic et al. (2008) "Detection of cytomegalovirus (CMV) DNA in EDTA whole-blood samples: evaluation of the quantitative artus CMV LightCycler PCR kit in conjunction with automated sample preparation" *J Clin Microbiol*
30. Zheng, Zou, Zou et al. (2025) "Diagnostic significance of metagenomic next-generation sequencing in immunocompromised patients with suspected pulmonary infection" *Immunology*
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# Complete genome sequence of turbot circovirus strain TurCV10LN-18/2021 from diseased Scophthalmus maximus
Xiao Wu, Boyin Jiang, Sang Choi, Yuanxing Zhang, Qiyao Wang, Yue Ma
## Abstract
We reported the complete genome sequence of turbot circovirus (TurCV) strain TurCV10LN-18/2021, detected in a diseased turbot (Scophthalmus maximus) in China. TurCV is responsible for the emerging acute hemorrhagic syndrome (EAHS) in farmed turbot. The availability of the complete genome sequence facilitates the investigation of circovirus epidemiology in turbot.
KEYWORDS circovirus, Scophthalmus maximus, viral pathogenesisT he viruses of the family Circoviridae are non-enveloped, single-stranded circular DNA viruses. They are the smallest known viruses infecting animals and plants, and the family includes two genera: Gyrovirus and Circovirus (1). Reports on circoviruses in fish are very limited. So far, complete circovirus genomes have only been detected in three fish species. In 2010, the fish circovirus sequence was discovered in barbel (Barbus barbus) in Hungary (2). Later, in 2012 and 2014, circoviruses were also reported in European catfish (Silurus glanis) and eel (Anguilla anguilla) (3, 4).We report the complete genome sequence of turbot circovirus (TurCV) strain TurCV10LN-18/2021, detected in heart, spleen, and kidney tissue of multiple diseased turbots (Scophthalmus maximus) in an EAHS outbreak in Liaoning, China. In detail, 2 g of mixed tissue samples of heart, spleen, and kidney from the diseased turbots was homogenized vigorously with beads in 10 mL PBS for 20 min. The homogenates were centrifuged at 4°C and 8,000 revolutions per minute (RPM) for 20 min, then the supernatants containing infectious virus were collected as a crude purified virus suspension.Complete genome sequencing was performed using strategies reported for other circoviruses (5-7). Genomic DNA was extracted from the 1 mL suspension using the TIANamp Genomic DNA extraction Kit (Tiangen Biotech, China) following the manual. Subsequently, nucleotide fragments were amplified by using the Pfu DNA polymerase (Tiangen Biotech, China). First-round PCR primers (Table 1) were designed targeting a 208 bp-conserved region revealed by multiple genome alignments of available circovirus (2-4), and further primer sets (Table 1) were designed for complete genome amplifi cation and primer-walking Sanger sequencing. Overlapping sequence reads covering the entire genome were generated. Then, ~1 µg PCR product was run on agarose electrophoresis and purified with a QIAquick gel extraction kit (QIAGEN) and cloned using the pMD18-T vector (TaKaRa) according to the manufacturer's instructions. Three positive clones for each fragment were sequenced by Sanger sequencer using M13 universal forward and reverse sequencing primers. Genomic reconstruction was done using DNASTAR software (version 5.0; DNASTAR Inc., Madison, WI). Default parameters were used except where otherwise noted.The complete circular genome of this isolate is 1,774 nucleotides in length, with a G + C content of 49.0%. Three open reading frames (ORFs) were predicted from the nucleotide sequence with DNASTAR and by comparing the results with the genome
organization and ORFs of other circoviruses. ORF1, stretching from 30 to 962 nt, encodes a classical replication-associated protein (Rep) of 310 amino acids (aa). ORF2 and ORF3 range from nt 1,073 to 1,768 and nt 1,580 to 105, encoding proteins of 231 and 99 aa, respectively.
Representative strains of circoviruses, such as PCV1, PCV2, GoCV, and DuCV, were selected. The results of the phylogenetic analysis showed that TurCV is divergent and only distantly related to other known circoviruses, displaying nucleotide identities 67.52%-72.50% to DuCV strains, in the phylogenetic tree (Fig. 1).
The report of a complete TurCV genome sequence is critical for further investigation of its molecular characteristics and pathogenic potential.
## AUTHOR CONTRIBUTIONS
Boyin Jiang, Data curation | Sang Ho Choi, Conceptualization, Funding acquisition.
## References
1. Breitbart, Delwart, Rosario et al. (2017) "ICTV virus taxonomy profile: Circoviridae" *J Gen Virol*
2. Lőrincz, Cságola, Farkas et al. (2011) "First detection and analysis of a fish circovirus" *J Gen Virol*
3. Lőrincz, Dán, Láng et al. (2012) "Novel circovirus in European catfish (Silurus glanis)" *Arch Virol*
4. Doszpoly, Tarján, Glávits et al. (2014) "Full genome sequence of a novel circo-like virus detected in an adult European eel Anguilla anguilla showing signs of cauliflower disease" *Dis Aquat Organ*
5. Li, Xu, Yuan et al. (2012) "Complete genome sequence of recombinant porcine circovirus type 2 strain SD-3" *J Virol*
6. Wen, He, Ni et al. (2012) "Complete genome sequence of the rearranged porcine circovirus type 2" *J Virol*
7. Wang, Guo, He (2025) "Aquatic circoviruses: emerging pathogens in global aquaculture-from discovery to disease management" *J Virol*
8. Tamura, Nei (1993) "Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees" *Mol Biol Evol*
9. Tamura, Stecher, Kumar (2021) "MEGA11: Molecular evolutionary genetics analysis version 11" *Mol Biol Evol*
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# P-1904. Training the Next Generation of Tropical Medicine Specialists: A 12-Year Analysis of One Center's Diploma of Tropical Medicine (DTM) Trainee Cohorts
Livia Frost, ; Huang, Eva Clark, Megan Duffey, Jill Weatherhead
Results. We evaluated 441 DTM trainees (Figure 1). Enrollment averaged 39 trainees/year between 2012-2017, then declined to 22/year between 2018-2020, and rebounded to 29 trainees in 2025. Most trainees (58%/year) were women. 2025 marked the first year that non-White groups (Asian 38%, Hispanic 17%, Black 14%) comprised the majority (69%) of trainees (Figure 2). Most trainees were medical students (36%) or physicians (32%), while physician assistant (PA) students emerged as a growing cohort (24% of the 2025 class, from 0% in 2011-2017) (Figure 3). DTM completion rates increased from a pre-2021 average of 44%/year to 76-80% in 2022-2024. Between 2020-2024, CTropMedÒ exam participation among DTM students remained stable (3-10 annually), with pass rates improving from 70% in 2020-2021 to 100% in 2022-2024 (Figure 4). Poster Abstracts • OFID 2026:13 (Suppl 1) • S1167
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# P-547. Single-Cell Transcriptomic Analysis of Severe Acute Encephalopathy/ Encephalitis Associated with SARS-CoV-2 Reveals HSPA1A and HSPB1 as Potential Markers
Takako Suzuki, Yoshitaka Sato, Motomasa Suzuki, Yuto Fukuda, Ken-Ichi Iwata, Makoto Yamaguchi, Yoshiki Kawamura, Tetsushi Yoshikawa, Yoshiyuki Takahashi, Hiroshi Kimura, Jun-Ichi Kawada, Yuka Torii
Background. Acute encephalopathy/encephalitis (AE) associated with SARS-CoV-2 has been increasingly reported since the emergence of the Omicron variant. Some patients developed acute fulminant cerebral edema (AFCE) or hemorrhagic shock encephalopathy syndrome (HSES) and had poor prognoses; however, the underlying pathogenesis of these conditions remains unclear. In this study, we performed single-cell RNA sequencing (scRNA-seq) on a patient with SARS-CoV-2-associated AE diagnosed with AFCE/HSES and compared the findings with those from patients with mild AE and febrile seizures caused by other pathogens. We also compared these cases with pediatric patients with COVID-19 without neurological complications.
Methods. Four pediatric patients were enrolled: one with SARS-CoV-2-associated AFCE/HSES, two with mild AE of different etiologies (influenza A and Epstein-Barr virus), and one with febrile seizures associated with HHV-6. Peripheral blood mononuclear cell (PBMC) samples were collected from each patient during the acute and convalescent phases. Single-cell RNA libraries were prepared using the 10x Chromium platform. The sequences were analyzed using Cell Ranger and Seurat. Publicly available scRNA-seq PBMC data for pediatric patients with COVID-19 were used for comparison.
Results. A total of 109,940 cells were analyzed in this study. In the acute phase of SARS-CoV-2-associated AFCE/HSES, the B-cell fraction was markedly increased. Enrichment analysis of upregulated genes in B cells showed activation of pathways associated with protein stabilization (GO:0050821), with particularly significant upregulation of HSPA1A and HSPB1. The gene expression levels of these heat shock proteins were low during the convalescent phases of SARS-CoV-2-associated AFCE/HSES, mild AE, and COVID-19. ELISA measurements of HSPA1A and HSPB1 in plasma and serum of the three AE cases revealed a marked increase during the SARS-CoV-2-associated AFCE/HSES acute phase.
Conclusion. Our findings suggest that HSPA1A and HSPB1 are potential markers of SARS-CoV-2-associated severe AE, although further studies are needed to validate their clinical utility.
Disclosures. All Authors: No reported disclosures
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# Identification of NS5B resistance-associated mutations in hepatitis C virus circulating in treatment-naïve Cameroonian patients
Aristide Mounchili-Njifon, Abdou Modiyinji, Rosereine Pretty, Mbouyap, Chavely Gwladys Monamele, Moise Moumbeket-Yifomnjou, Philipe Herman, Njitoyap Mfombouot, Gisele Machuetum, Pascal Toueyem, Simon Lissock, Paul Tagnouokam-Ngoupo, Jean Paul, Assam Assam, Richard Njouom
## Abstract
Objectives: NS5B polymerase inhibitors are essential in the treatment of hepatitis C virus (HCV) infection. Although direct-acting antivirals (DAAs) are generally effective, their efficacy can be compromised by resistance mutations, particularly in the NS5B protein. This research aimed to identify naturally occurring mutations in the NS5B gene linked to DAA resistance in treatment-naïve Cameroonian patients with chronic hepatitis C. Methods: Whole blood samples were collected from patients with chronic hepatitis C, from which plasma was subsequently separated and stored at -80°C for molecular analysis. The NS5B gene fragments were amplified using designated primers, and nucleotide sequences were acquired via the Sanger sequencing platform. Results: Analysis of sequences revealed three genotypes: genotype 4 (38.49%), genotype 1 (38.38%), and genotype 2 (23.14%). The most prevalent subtypes were 4f (22.05%) and 1e (17.84%). The clinically significant S282T mutation, which confers high-level resistance to sofosbuvir, was detected in one patient infected with HCV genotype 1e. Similarly, the C316N substitution, associated with reduced susceptibility to non-nucleoside NS5B inhibitors, was identified in 16 patients, all belonging to genotype 1e. The Q309R mutation was detected in 19 genotype 1 sequences, and the L320F mutation was found in one genotype 4f sequence. Conclusions: Our investigation revealed that HCV patients who had not previously received DAA therapy exhibited a variety of NS5B gene alterations. Consequently, future treatment failure may be more likely due to these alterations.
## Introduction
The hepatitis C virus (HCV) is a major public health problem with severe clinical consequences worldwide [ 1 ]. It is estimated that 50 million people are chronically infected with the HCV, and approximately 10 million new infections occur each year [ 2 ]. Since 2011, there has been a significant advancement in HCV treatment with the development of direct-acting antivirals (DAAs), which can achieve a sustained virological response [ 3 ]. These DAAs developed for the treatment of HCV target the NS3/4A protease, the NS5A protein, and the NS5B polymerase, which are viral proteins involved in HCV replication [ 4 ]. NS5B polymerase inhibitors are the cornerstone of current treatment for HCV infection because the NS5B region of the hepatitis C genome is essential for viral replication, encoding the RNA-dependent RNA polymerase [ 5 ].
Despite the efficacy of DAAs with a sustained virological response rate of over 90% [ 6 ], approximately 5-10% of HCV-infected individuals fail DAA treatment. This failure results from the rapid replication rate of the HCV life cycle, low polymerase fidelity, immune system pressure, and selective drug treatment, leading to the selection and emergence of drug-resistant variants within the HCV-infected population [ 7 ].
HCV is a member of the family Flaviviridae , further classified as the prototypical member of the genus Hepacivirus [ 8 ]. It has a single-stranded positive-sense RNA genome of approximately 9600 nucleotides, encoding a single polyprotein that is further processed by viral and cellular proteases into three structural proteins (core and envelope glycoproteins E1 and E2) and seven non-structural proteins (p7, NS2, NS3, NS4A and B, and NS5A and B) [ 9 ]. Due to its high genetic heterogeneity, genomic sequencing has revealed the presence of eight HCV genotypes (1)(2)(3)(4)(5)(6)(7)(8) and 105 subtypes that differ in nucleotide sequence by 30% and 15%, respectively [ 10 ].
Based on experience with other chronic viral infections, HCV antiviral medication resistance has emerged as a public health concern in the diagnosis and treatment of individuals with chronic hepatitis C. The characteristics of distinct resistance mutations have been widely established, based on previous clinical and laboratory evidence [ 11 ]. NS5B nucleotide inhibitors are associated with high resistance barriers [ 12 ]. The presence of resistance-associated variants in treatment-naïve patients has been reported in several countries [ 5 , 13-21 ]. Moreover, such studies of natural resistance mutations in treatment-naïve HCV patients may be of great importance [ 11 , 22 ]. However, the presence of resistance-associated mutations, particularly at the NS5B polymerase level, can reduce the efficacy of DAAs [ 17 ].
Few studies have been conducted in Cameroon to measure the frequency of mutations associated with resistance to HCV antiviral treatment. However, there are a limited reports on natural or treatmentnaïve mutations. This makes the current study important [ 23 , 24 ], as resistance-associated substitutions (RAS) can occur naturally in HCVinfected patients prior to the initiation of DAA therapy [ 25 ]. Therefore, there is an increasing need to improve treatment efficacy in individuals treated with different regimens for each infectious genotype, especially with the presence of natural HCV RAS in DAA-naïve patients [ 17 ]. Therefore, the purpose of this study was to look at whether Cameroonian patients who had not taken DAA had primary drug resistance mutations in the NS5B area of HCV. Furthermore, these data will aid in the better selection of suitable DAA regimens for upcoming HCV control and elimination initiatives involving the Cameroonian populace.
## Methods
## Research methodology
Between January 2013 and October 2023, a total of 1728 plasma samples from treatment-naïve HCV-RNA-positive patients were received at the Centre Pasteur du Cameroun (CPC). Among them, 925 (53.5%) samples were successfully amplified and sequenced in the NS5B region and were included in the final analysis. Blood samples were collected from treatment-naïve HCV-infected patients at the CPC as part of a nationwide retrospective cross-sectional descriptive study. The CPC is the national HCV control program's focal point and Cameroon's reference laboratory for a number of diseases, including viral hepatitis. HCV patients are frequently sent to the CPC for viral load and genotyping as part of this duty. There was no further testing done; the data shown here were gathered as part of standard HCV diagnostic procedures. This was a retrospective cross-sectional study including all treatment-naïve patients with detectable HCV RNA referred to the CPC for viral load measurement and genotyping over a 10-year period (2013-2023). No patient had ever received DAAs or interferon-based therapy. Genotyping was carried out through sequencing the NS5B region of the HCV genome. As directed by the manufacturer, we measured the HCV viral load using the Abbott Real-Time HCV assay and Abbott m2000 platforms (Abbott Molecular, Wiesbaden, Germany). Briefly, the procedure involves using the Abbott m2000sp to extract RNA from 0.5 ml plasma (separated from EDTA tubes), followed by amplification on the m2000rt at a detection limit of 12 IU/ml.
## Amplification of the NS5B region
Amplification, sequencing, and phylogenetic analysis of the 382 nucleotide sequences of the NS5B genomic region were used to carry out HCV genotyping and subtyping. In summary, a QIAamp Viral RNA mini kit was used to extract viral RNA from 140 μl of plasma from HCVpositive patients who had a detectable viral load, in accordance with the manufacturer's instructions (Qiagen, Courtaboeuf, France).
The reverse transcription polymerase chain reaction (RT-PCR) step was performed using a semi-nested RT-PCR targeting the 925 nucleotides of the NS5B region. A first RT-PCR was performed using the SuperScript TM III One-Step RT-PCR System with Platinum Taq (Invitrogen, Carlsbad, USA), Pr3 (5 ′ -TATGAYACCCGCTGYTTTGCTC-3 ′ ), and Pr4 (5 ′ -GCNGARTAYCTVGTCATAGCCTC-3 ′ ) as primers. Amplification started with cDNA synthesis at 50°C for 30 minutes, followed by five cycles at 93°C for 30 seconds, 60°C for 45 seconds, and 72°C for 1 minute. This was immediately followed by 35 cycles at 93°C for 30 seconds, 60°C with a drop of -0.3°C between each cycle, and an extension at 72°C for 1 minute. The final extension was at 72°C for 5 minutes. The second amplification step (semi-nested PCR) targeted 382 nucleotides of the NS5B region according to the protocol developed by Sandres-Sauné et al. [ 26 ]. The reaction mixture consisted of 5 μl of 10X buffer, 3.5 μl MgCl 2 , 1 μl dNTPs, 0.4 μM each of the inner primers Pr3 (forward) and Pr5 (reverse: 5 ′ -GCTAGTCATAGCCTCCGT-3 ′ ), and 0.25 μl of Taq polymerase enzyme. To the total reaction mixture, 2 μl of the first RT-PCR products were added. The thermal cycling conditions were as follows: one cycle at 95°C for 5 minutes, then 35 cycles at 95°C for 30 seconds, 55°C for 30 seconds, 72°C for 30 seconds, and a final extension at 72°C for 10 minutes. The expected amplicon size for the nested product was approximately 382 bp was visualized on 2% agarose gel electrophoresis.
## Sequencing and phylogenetic analyses
Using the Genome Lab DTCS-Quick Start kit, all nested PCR products of the NS5B region were sequenced using the Sanger technique (Beckman Coulter, Paris, France) in compliance with the guidelines provided by the manufacturer. Using the CLC Main Workbench software (version 5.5.2), forward and reverse sequences were manually edited before consensus sequences were produced. The HCVnet genotyping tool ( https://www.genomedetective.com/app/typingtool/hcv/ ) was used to assign the HCV genotype and subtype, and the tree was inferred using MEGA version 11 under the General Time Reversible model with gamma-distributed rate variation and a proportion of invariant sites (GTR + Γ + I), selected as the best-fitting model by jModelTest 2 according to the Bayesian information criterion. Branch support was assessed with 1000 bootstrap replicates; only bootstrap values ≥ 70% are displayed.
## Study of resistance-associated mutations in the HCV NS5B polymerase
To detect the various natural substitutions and assess their impact on resistance, all 925 NS5B sequences (from genotypes 1, 2, and 4) were subjected to Geno2pheno (hcv) 0.92, which provides a list of mutations and predictions of phenotypic resistance to antiviral drugs for each strain [ 3 ].
## Results
## Demographic characteristics Distribution and frequency of NS5B resistance-associated variants' genotype (subtype)
The study included 925 consecutive patients who satisfied the eligibility requirements, of whom 536 (57.95%) were women and 389 (42.05%) were men, resulting in a M/F sex ratio of 0.73. With a mean of 68.02 and a median of 70 years, the age ranged from 5 to 96 years.
Three genotypes were identified by sequencing the NS5B region in 925 blood samples from HCV-positive individuals: genotype 4 was the most common (38.49%), followed by genotype 1 (38.38%) and genotype 2 (23.14%). The predominant subtypes were 4f (22.05%) and 1e (17.84%) (see Table 1 and Figure 1 for complete genotype/subtype distribution).
The HCV nucleotide sequences described in this study have been submitted to the Genbank database under the following accession numbers: Un: unclassified.
OR477026-OR477034, OR477036, OR477038-OR477046, OR477048-OR477046, OR477048-OR477054, OR477056-OR477061, OR477063-OR477067, OR477069-OR477071, OR478291-OR478378, OR480599-OR480642, OR480646, OR490539-OR490588, OR520331, OR520333, OR520337, OR520340, OR520345-OR520374, OR765771-OR765774, OR765776-OR765810, OR765820, OR765823-OR765824, OR765826-OR765830, OR818228-OR818286, OR818288-OR818301, OR818302, OR818307, OR818312-OR818322, OR818329-OR818336, OR818341-OR818349, OR825140, OR825144, OR825146-OR825180, OR825183, OR825184-OR825305, OR825307-OR825321, OR837048, OR837051-OR837053, OR902261, OR902264-OR902271, OR923596, OR923662, OR923663-OR923680, OR923682-OR923692, OR923694, OR923696-OR923700, OR923704, OR923706-OR923713, PP484706-PP484712, PP484714-PP484746, PP484748, PP484750-PP484800, PP484802-PP484862, PP484864, PP484866-PP484867, PP484869, PP484871-PP484877, PP583866-PP583875, PP583877-PP583908, PP583910-PP583967, PP583969-PP584014.
## Frequency of mutations associated with natural NS5B resistance
In genotypes 1e, 2, and 4f, natural NS5B RASs were prevalent ( Table 2 ), with a significant frequency of S282T (1/165, 0.61%), Q309R (11.52%), D310N (6.1%), C316N (9.7%), and V321I (1.21%) in genotype 1e. In addition, several natural RAS were detected at different frequencies: E237G (45/204, 22.06%), S282L (0.49%), N310D (68.14%), N316C (34.80%), L320F (0.61%), and V321I (1.47%) in HCV genotype 4f. Four mutations were detected in genotype 2 at positions E237G, M289L, D310N, and V321I ( Table 1 ).
In different parts of the genome, resistance mutations and RAS arise naturally because the viral polymerase lacks the correcting exonuclease function. These mutations can occur throughout the viral genome, including NS3, NS5A, and NS5B [ 27 ]. These mutations have treatment implications by affecting the sensitivity of antiviral molecules. Among 925 patients, single NS5B inhibitor-resistant mutations were identified as spontaneous NS5B RAS, including E237G (5.19%), S282T (0.11%), M289L (1.08%), Q309R (2.05%), D310N (8.54%), C316N (1.73%), L320F (0.11%), V321I (0.76%), and V329I (0.43%). These frequencies represent the proportion within the total cohort (N = 925) ( Table 2 ). Among the 98 strains with ribavirin resistance associated with a single mutation, the HCV isolates with the Q309R and D310N mutations were 19/925 and 79/925, respectively. The S282T mutation, known to be highly resistant to sofosbuvir, was found in one HCV isolate, whereas the C316N mutation, known to be resistant to sofosbuvir, was found in 16/925 HCV isolates. The M289L and L320F mutations, known to confer reduced sensitivity to sofosbuvir, were present in 10/925 and 1/925 of the isolates in our study, respectively. Furthermore, one HCV strain exhibited a double mutation S282L + V321I in the NS5B region, which is known to confer high-level resistance to sofosbuvir. This combination was identified in a patient infected with genotype 4f and warrants particular attention due to its potential to cause treatment failure. All NS5B RAS common to DAAs were linked to ribavirin resistance in genotype 1e in our sample of patients at locations L159, N244I, T329I, and A333E (lower HCV sensitivity to ribavirin), with mutations detected in 98 HCV-infected patients. In patients with genotype 1a (14/16, 87.5%), simultaneous detection of RAS NS5B was more common than in patients with genotype 6a (2/16, 12.5%). Multiple NS5B RAS were identified in genotypes 1e and 4f, with genotype 4r containing S282R + V321I and genotype 1e, including E237G + S282R + Q309R + V321I.
## Discussion
One of the main causes of liver cirrhosis, hepatocellular cancer, and death is chronic HCV infection. In addition, it is estimated that approximately 40-70% of patients develop non-hepatic alterations during chronic infection [ 28 ]. Although interferon-free DAA therapy has been a major development in the treatment of HCV, the persistence of the virus under drug pressure and the persistence of a natural polymorphism that may correlate with DAA resistance are considered major challenges to the success of HCV therapy [ 5 ]. NS5B is the main target of DAAs, which directly prevent viral multiplication; several mutations that lessen the effectiveness of NS5B inhibitors have been documented and might be innate in patients who have not received treatment. These mutations arise due to the absence of the corrective exonuclease activity of the viral polymerase [ 16 ]. The incidence of NS5B mutations in HCV genotype 1, 2, and 4 patients in Cameroon who are new to DAA therapy is reported in this study.
Our study, which we believe is one of the few to have estimated natural NS5B RASs in DAA-naïve HCV patients in Cameroon to provide optimal treatment, was carried out in 925 treatment-naïve patients who were successfully amplified for the NS5B fragments under investigation. This is because Cameroonian data on HCV drug resistance is extremely limited.
Concerning the NS5B gene, a global analysis revealed that NS5B DAA resistance substitutions are rare [ 29 ]. Relevant natural amino acid polymorphisms were found in genotypes 1e, 1l, 2, 4f, 4t, 4p, and 4l in our investigation. Several studies have demonstrated the occurrence of natural mutations in the NS5B region. Two studies carried out in Cameroon, the first on 252 treatment-naïve patients in the NS5B region in 2016, had already presented several natural mutations, indicating the importance of monitoring and tracking resistance-associated mutations [ 24 ], whereas the other study on 190 HCV RNA-positive patients revealed the presence of a resistance-associated mutation in the NS5B region [ 23 ].
In addition, a study carried out in Egypt on 27 treatment-naïve HCVinfected patients and eight non-responders, multiple resistance mutations in the NS5B region were detected in several patients [ 5 ]. A study in South Africa on 42 HCV-infected and treatment-naïve patients also revealed the presence of multiple resistance mutations in the NS5B re-gion [ 15 ]. Furthermore, in a study of 108 HCV-1 patients in Argentina, resistance mutations in the NS5B region were detected in 6.3% of these patients [ 30 ]. The significant S282T mutation confers a high level of sofosbuvir resistance despite the low frequency of this mutation in the HCV NS5B region [ 24 ]. This S282T mutation was detected in our study in a patient with genotype 1e, consistent with several previous studies showing the low frequency of the S282T mutation in the NS5B region but inducing a high level of sofosbuvir resistance. A study carried out in 2024 in Egypt confirmed two cases of S282T mutations [ 31 ]; similarly, a study in Pakistan equally identified two cases of S282T mutations [ 21 ]. In addition, several previous studies have shown that patients who did not respond well to sofosbuvir-based treatment regimens had an S282T mutation [ 32 , 33 ]. However, several other studies in Cameroon, Africa, and even Europe did not detect the S282T mutation. This explains the low prevalence of this mutation in HCV patients [ 5 , 24 , 34 ].
The C316N mutation, including sofosbuvir, has been reported to confer resistance to DAA therapy [ 35 ]. This study showed that treatmentnaïve HCV patients in Cameroon had mutations that conferred resistance to HCV NS5B polymerase, i.e., genotype 1e, in 16 patients. Our results are in line with a study from Morocco showing that the C316N mutation was more prevalent in genotype 1 in DAA treatment-naïve patients [ 16 ]. A study conducted in Asia had also shown the high frequency of C316N mutations in treatment-naïve genotype 1b patients with chronic hepatitis C [ 20 ].
Mutations at locations Q309R, D244N, and A333E are linked to ribavirin resistance.
Our investigation revealed that 19 HCV patients who had not received therapy had a frequency of 2.05% Q309R mutations. Our findings are in line with recent research demonstrating the existence of numerous Q309R mutations in patients who have not received therapy, such as an Egyptian study that found that out of 27 drug-naïve HCV infections, the Q309R mutation had a frequency of 5.8% [ 5 ]. Another study in Brazil reported that among 69 drug-naïve individuals infected with HCV, the most common mutation was Q309R (29%) [ 36 ]. Nevertheless, our investigation did not find the D244N mutation, in agreement with a study conducted in Egypt in 2021, where this mutation was also not detected [ 5 ]. Conversely, the mutation at position 333 was detected in our study; however, with a different protein alteration, i.e., A333V, with a frequency of 4.32%.
Our study reported E237G mutations in two HCV strains, GT-4f and GT-2, from our HCV-naïve samples. This finding agrees to some extent with an Egyptian study of 27 treatment-naïve patients that found an E237G mutation in the NS5B region in the only non-susceptible GT-4o HCV strain, and E237G/A mutations in four other strains [ 5 ]. In another study of 333 treatment-experienced patients, 10 individuals experienced virological relapse, and at the time of relapse, two patients with genotypes 1a and 4d had an E237G mutation found in them (Manns et al ., 2016). Another study found the presence of an E237G substitution in a GT-4 patient without a significant therapeutic response [ 10 ].
The L320F polymerase mutation has been observed to confer low resistance to HCV polymerase inhibitors such as sofosbuvir in vivo [ 37 ]. Our study reported the presence of this mutation at L320F in a patient infected with HCV genotype 4f. These results are consistent with a study carried out in Brazil, where an L320F mutation was also identified in a treatment-naïve HCV-infected patient [ 13 ]. In addition, a study has shown that the M289L mutation reduces sensitivity to sofosbuvir by a factor of 2-20 [ 38 ], whereas our study reported the presence of this M289L mutation in 10 patients infected with HCV genotype 2.
It is still unknown how HCV resistance mutations affect the virus's capacity for in vivo replication. Therefore, more research is required to fully evaluate how each variation affects the degree of resistance or susceptibility to HCV medications. As a result, developing an HCV vaccine is not only important but also essential for the long-term management of HCV infection. Nowadays, DAA-based treatment plans are effective in curing almost all chronic HCV infections. Nonetheless, considering the astronomically high global infection rate and the continuous identification of novel HCV subtypes, some of which harbor pre-existing resistance mutations, the rise of multidrug-resistant viruses continues to be a serious worry.
The present study was limited to a single HCV region, NS5B, and only treatment-naïve, chronically infected patients were included. Future studies should focus on the prevalence of innate HCV antiviral resistance, as well as resistance acquired during HCV treatment. Therefore, the creation of an HCV vaccine is not only essential but also a priority for the future management of HCV infection. The results of this study could help determine which DAA treatment plan is optimal for HCV patients.
## Conclusion
Our research revealed that a number of mutations in the NS5B genes under analysis may raise the chance of treatment failure in Cameroonian HCV patients receiving regimens containing DAA. The high virological success rate of sofosbuvir-based regimens, the uncommon occurrence of RAS in non-responder patients, the lack of data developed for RAS in genotype 4 patients compared with other genotypes, and the overall difficulty of completely understanding the impact of some of these substitutions may all be factors linked to treatment failure in Cameroon. To investigate the link between the alterations found in our study and HCV resistance, more research is required.
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# | Virology | Perspective mGem: Noncanonical nucleic acid structures-powerful but neglected antiviral targets
Václav Brázda, Richard Bowater, Petr Pečinka, Martin Bartas
## Abstract
This perspective highlights the emerging significance of noncanonical nucleic acid structures-such as G-quadruplexes, Z-DNA/Z-RNA, and cruciforms-in viral genomes. Once considered structural oddities, these motifs are now recognized as critical regulators of viral replication, transcription, genome stability, and host-patho gen interactions. Despite mounting evidence of their functional relevance and thera peutic potential, these structures remain largely overlooked in virology and antiviral drug development. Their unique conformations offer highly specific molecular targets, with several small molecules already demonstrating the ability to modulate viral gene expression by stabilizing or destabilizing these motifs. The persistent underestimation of non-B DNA/RNA structures represents a missed opportunity in the fight against viral diseases. By synthesizing recent discoveries and emphasizing their biological and pharmacological promise, we aim to elevate awareness and catalyze interdisciplinary research. Harnessing the structural diversity of viral genomes could unlock novel antiviral strategies with high specificity and minimal off-target effects.
hairpins, pseudoknots, and i-motifs, are increasingly recognized as dynamic regulators of viral life cycles.
Recent advances in bioinformatics, structural biology, and chemical biology have enabled the identification and characterization of these noncanonical structures across a wide range of viral genomes (Fig. 1). These discoveries have revealed that such structures are not only present but also often conserved (13) and are functionally significant (14), influencing processes such as viral replication, transcription, translation, and immune evasion. For example, G4s have been identified in the genomes of HIV-1 (15), SARS-CoV-2 (16), Epstein-Barr virus (17), Rous sarcoma virus (18), hepatitis B (19,20) and hepatitis delta virus (21), retroviruses (22), and herpesviruses (23), and they have also been shown to modulate transcriptional activity, genome packaging, and to play vital roles in viral-host coevolution (20,24,25). Despite their presence in various functional regions, noncanonical nucleic acid structures in viruses remain largely neglected as therapeutic targets. This oversight is particularly striking given the growing body of evidence supporting their functional importance and druggability (26). Small molecules that selectively bind and stabilize or destabilize these structures have shown promise in modulating viral gene expression and replication (27,28). Moreover, the structural uniqueness of these motifs offers a level of specificity that is often difficult to achieve with traditional antiviral strategies.
## G-QUADRUPLEXES
G-quadruplexes, often abbreviated as G4s, are higher-order structures formed by guanine-rich sequences that stack into planar tetrads stabilized by Hoogsteen hydrogen bonding and monovalent cations (32). Recently, the G4 (Fig. 1) has been the most extensively studied noncanonical structure in viral genomes. G4s have been implicated in transcriptional regulation (33), genome replication (34), and recombination (35). In viruses, G4s have been shown to regulate the expression of key genes, including those involved in latency and immune evasion. For instance, in HIV-1, G4s in the long terminal repeat region modulate promoter activity, influencing viral latency and reactivation (36). Similarly, in herpesviruses, G4s are enriched in regulatory regions and may serve as epigenetic switches (37). More interestingly, it has been demonstrated that viruses that promote latent infections have a similar G4 propensity as the genome of their host (24,25). By contrast, viruses that promote acute infections usually have G4-poor genomes (24) but are abundant in inverted repeats that can form hairpin and cruciform structures. Several experimentally solved G4 structures are available, including rG4 from West Nile virus genome (31). Knowledge about the exact structural shape of these nucleic acids can greatly facilitate the development of low-molecular-weight compounds that target them.
## Z-DNA/Z-RNA
Another intriguing structure is Z-DNA/Z-RNA, a left-handed helical form of nucleic acids that can arise under physiological supercoiling or high salt conditions (38). Z-DNA/ Z-RNA has been implicated in innate immune sensing, particularly through interactions with Z-DNA binding protein 1 (ZBP1), which can trigger necroptosis in response to viral infection (39). However, coronaviruses have evolved efficient ways to evade ZBP1 sensing via utilizing their nsp15 protein, containing an endoribonuclease domain that cleaves viral RNA before it can be sensed by host ZBP1 (40). Studies have shown that some viruses, including Poxviridae and Asfarviridae families, encode proteins that bind Z-DNA/Z-RNA to evade immune detection (41). Recently, ZBPs were also identified to be encoded in the genomes of several giant viruses (42), and another recent study suggests that ZBP1 forms condensates with liquid-liquid phase separation properties upon viral infection (43). These findings suggest that Z-conformations are not only biologically relevant but are also actively targeted by viral countermeasures, underscoring their importance in host-pathogen dynamics.
## CRUCIFORMS AND HAIRPINS
Cruciform structures (and hairpins in the case of single-stranded genomes) can form within inverted repeat sequences, and these are another class of noncanonical motifs with potential relevance in virology. Cruciforms have been implicated in genome packaging, recombination, and transcriptional regulation in both prokaryotic and eukaryotic systems (44)(45)(46). In viruses, cruciforms may contribute to genome circulariza tion, replication origin activity, or structural transitions during infection cycles, although direct evidence for any role that impacts viral life cycles remains limited (47). It was also recently found that sites of inverted repeats are a natural source of hot spot mutations in SARS-CoV-2 ( 48) and monkeypox viruses (49). In addition, parvoviruses and adeno-asso ciated viruses use terminal hairpins as essential replication origins (50,51), underscoring the biological significance of these noncanonical DNA structures in viral life cycles.
## METHODOLOGICAL APPROACHES
The identification of potential noncanonical structures in viral genomes has been accelerated by both computational prediction tools and experimental approaches. Algorithms such as G4Hunter (52), pqsfinder (53), G4RNA screener (54), and deep learning approaches such as DeepZ ( 55) allow for large-scale prediction of sequence motifs capable of forming higher-order structures (56). Experimentally, circular dichroism spectroscopy, nuclear magnetic resonance, and crystallography provide structural validation. High-throughput techniques such as SHAPE-MaP (57) and G4-seq enable transcriptome-wide mapping of RNA secondary and tertiary structures, including rG4s (58). Together, these complementary methodologies expand the landscape of accessible structural motifs in viral genomes.
## CONCLUSIONS AND CHALLENGES
The therapeutic potential of targeting noncanonical structures is increasingly supported by the development of structure-specific ligands. Several ligands, such as TMPyP4 (59), BRACO-19 (60), CX-5461 (61), QN-302 (62), and metallohelices (63), have been demon strated to be able to bind (r)G4s and modulate gene expression in cancer and viral models (64). Importantly, some ligands exhibit selectivity for viral over host G4s, offering a promising avenue for antiviral drug development with a low level of off-target effects.
Clinically approved compounds such as Topotecan and Berbamine have recently been shown to stabilize rG4s in genes encoding host entry factors and block SARS-CoV-2 pseudovirus entry in vitro and in vivo (12). Given the space constraints of this minireview, we cannot illustrate chemical structures of ligands here, but representative structures of widely used G4 ligands are available in comprehensive reviews (64,65). Targeting Z-DNA/RNA is less advanced but equally promising: recent studies indicate that Korean red ginseng promotes cell death mediated by ZBP1, which helps to reduce the expres sion of viral proteins, thereby enhancing the host's defense against the influenza A virus (66). Moreover, the integration of computational prediction tools with high-throughput screening platforms has accelerated the discovery of novel ligands and binding motifs (64).
Currently, the analyses and potential exploitation of noncanonical structures in viral genomes face several challenges. First, the dynamic and context-dependent nature of noncanonical structures complicates their detection and functional valida tion. Second, the diversity of methodologies for structure prediction and (high-through put) ligand screening hinders cross-study comparisons. Third, the limited awareness of these structures among virologists has slowed their integration into mainstream antiviral research. Addressing these challenges will require interdisciplinary collabora tion, combining expertise in virology, structural biology, computational modeling, and medicinal chemistry.
Beyond well-studied examples such as HIV-1 and herpesviruses, the distribution and functional impact of noncanonical structures in plant viruses, bacteriophages, and giant viruses remain largely uncharted. Given their ecological and medical importance, systematic surveys across underexplored viral families could uncover new structural vulnerabilities.
Integrating cryo-EM, transcriptome-wide structure probing, interactome mapping, and machine learning-based predictions will be essential to build a comprehensive atlas of viral noncanonical motifs. While ligand development has so far focused on G4s, advances in small-molecule design, synthetic biology, and CRISPR-based programmable nucleic acid targeting suggest that Z-conformations, cruciforms, and hairpins may also become pharmacologically tractable. Importantly, the conservation of certain motifs across viral families points to the possibility of developing broad-spectrum antivirals that exploit structural commonalities rather than sequence similarity. Realizing this potential will require not only interdisciplinary collaboration but also the establishment of community-wide standards and databases to enable reproducibility and cross-viral comparisons.
Noncanonical nucleic acid structures represent a rich and largely untapped frontier in virology. Their functional relevance, structural uniqueness, and druggability make them compelling targets for therapeutic innovation. As the field moves toward more precision-based antiviral strategies, expanding the research and therapeutic focus to include noncanonical nucleic acids across diverse viral systems could provide a new conceptual and practical framework for precision antiviral strategies.
## FUNDING
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61. Artusi, Ruggiero, Nadai et al. (2021) "Antiviral activity of the G-quadruplex ligand TMPyP4 against herpes simplex virus-1" *Viruses*
62. Majee, Pattnaik, Sahoo et al. (2020) "Inhibition of Zika virus replication by G-quadruplex-binding ligands" *Mol Ther Nucleic Acids*
63. Xu, Antonio, Mckinney et al. (2017) "CX-5461 is a DNA G-quadruplex stabilizer with selective lethality in BRCA1/2 deficient tumours" *Nat Commun*
64. Tosoni, Naghshineh, Zanin et al. (2025) "The G-quadruplex experimental drug QN-302 impairs liposarcoma cell growth by inhibiting MDM2 expression and restoring p53 levels" *Nucleic Acids Res*
65. Sun, Zhao, Liu et al. (0199) "Screening of metallohelices for enantioselec tive targeting SARS-CoV-2 RNA G-quadruplex" *Nucleic Acids Res*
66. Ruggiero, Richter (2018) "G-quadruplexes and G-quadruplex ligands: targets and tools in antiviral therapy" *Nucleic Acids Res*
67. Monchaud (2024) "Translating G-quadruplex ligands from bench to bedside: a Stephen Neidle's legacy" *Med Chem Res*
68. Oh, Kim, Lee et al. (2025) "Korean red ginseng enhances ZBP1-mediated cell death to suppress viral protein expression in host defense against influenza A virus" *J Microbiol*
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biology
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Edward Traver, Seyed Shams, Meghan Derenoncourt, Hannah Flores, Elana Rosenthal, Sarah Kattakuzhy
Background. People who inject drugs (PWID) are at higher risk for severe bacterial infectious diseases (ID), which drive expensive hospitalizations. Identification of PWID allows for linkage to clinical interventions, such as multidisciplinary ID-addiction treatment teams, which improve clinical outcomes. Yet injection drug use (IDU) is often captured only in the text of clinical notes and is not easily queried. We sought to demonstrate text-based IDU classification by a large language model (LLM), a type of artificial intelligence. • OFID 2026:13 (Suppl 1) • S1205 Methods. Hospital encounters at an academic medical center between 2018 and 2022 were included if they featured ICD codes for both acute infections and opioid use. Encounters were reviewed by trained research assistants and classified as "IDU" or "non-IDU" based on clinical notes. A balanced sample of 100 encounters was selected randomly for the LLM classification. The hospital admission note was extracted from the electronic medical record (Epic). A zero-shot prompt instructed the LLM (LLaMA 3.3; Meta, 70B parameters) to label each encounter as "IDU" or "non-IDU" (Figure 1). LLM labels were compared to human classifications. Positive and negative predictive values (PPV, NPV) were estimated for varying IDU prevalence. 95% confidence intervals were estimated with the Wilson-Brown method. Results. Of the 50 IDU and 50 non-IDU encounters, the LLM labeling yielded 34 true positives, 16 false negatives, 40 true negatives, and 10 false positives (Figure 2). Sensitivity was 0.68 (95% CI 0.54-0.79); specificity 0.80 (95% CI 0.67-0.89; Figure 3). Accuracy of the LLM label was 0.74; F1-score 0.72. Estimates of PPV with IDU prevalence of 50%, 10%, and 1% were 0.77, 0.27, and 0.03; estimates of NPV were 0.71, 0.96, and >0.99 (Figure 4).
## Poster Abstracts
## Conclusion.
In this small pilot study, an LLM demonstrated moderate performance on identifying PWID. The performance would likely limit usability in screening cohorts with real-world prevalence of IDU (1-10%). Future work will seek improved performance by refining the LLM prompt, evaluating other LLMs, and examining additional data (eg, ID consultation notes). Additional validation is needed with larger, distinct datasets. LLMs holds promise to identify hospitalized PWID to improve health outcomes.
Disclosures. All Authors: No reported disclosures
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# Betaherpesvirus Incidence in Saliva Samples From Patients With Hematological Neoplasms: Frequency, Clinic and Diagnostic Insights
Ana Carolina, Silva Guimarães, Jéssica Pereira Gonçalves, | Nathália, Sousa Pereira, Flávia Freitas De Oliveira Bonfim, | Katrini, Guidolini Martinelli, Marla Amarante, | Sueli, Fumie Yamada-Ogatta, Laura Franco, | Ligia, Carla Faccin Galhardi, Vanessa Salete De Paula
## Abstract
Hematological neoplasms (HN) are disorders originating in blood cells that hold significant epidemiological importance. Treatments available for these conditions can induce immunosuppression, and it increases the risk of viral infections and reactivations, mainly by Human betaherpesviruses (HCMV, HHV-6, and HHV-7). Studies have suggested that these viruses play potential oncogenic role in hematological neoplasms, although results remain inconclusive. This study aimed to evaluate the frequency and viral load of betaherpesviruses in saliva samples from patients with hematological neoplasms, and to explore their relevance to clinicopathological characteristics. In total, 260 saliva samples collected from patients with Hodgkin lymphoma (HL) (n = 29), non-Hodgkin lymphoma (NHL) (n = 106), leukemia (n = 85) and multiple myeloma (MM) (n = 40) were analyzed in multiplex qPCR. The result was compared with control group samples from patients without hematological neoplasm (n = 159). HHV-7 was the most frequently detected betaherpesvirus, identified in 15.8% (41/260) of patients with hematological neoplasms. In comparison, HCMV and HHV-6 were detected in 12 (4.6%) and 11 (4.2%) patients, respectively. In the control group, HCMV was detected in 2 individuals (1.3%), HHV-6 in 6 (3.8%), and HHV-7 in 14 (8.8%). A statistically significant difference in HHV-7 detection was observed between patients and controls (p = 0.005). Additionally, HCMV detection showed a significant difference between patients with HL and MM (p = 0.036). The detection of betaherpesviruses, particularly HHV-7, was more frequent and viral in patients with hematologic malignancies compared to the control group, with statistically significant differences observed. In summary, HHV-7 was the most frequently detected virus, found in 15.8% of patients versus 8.8% of controls. However, its presence in saliva alone does not confirm disease association. Our findings reinforce the need for longitudinal studies to clarify the potential pathogenic role of HHV-7 and other betaherpesviruses in hematological neoplasms, and their possible impact on patient outcomes.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
## 1 | Introduction
Hematological neoplasms (NH) comprise disorders deriving from blood cells, such as myeloid or lymphocytic lineages. They account for 8%-9% of cancer cases diagnosed since 1960 [1,2]. These disorders encompass several diseases, among them, Hodgkin lymphoma (HL), non-Hodgkin lymphoma (NHL), leukemia, and multiple myeloma (MM), besides affecting individuals' senescence [3]. The etiology of these malignancies is multifaceted and remains poorly understood. Several risk factors have been identified, such as genetic predisposition, environmental exposure, and lifestyle-related factors [4].
It is understood that chemotherapy, and other treatments for cancer, can induce immunosuppression in patients with hematological malignancies, and it increases host susceptibility to viral infections or virus reactivation. Accordingly, Human betaherpesviruses are acquired early in life, with global seroprevalence close to 90%, which increases due to aging, immunological status, socioeconomic factors, and geographic location [5]. Human betaherpesviruses (Cytomegalovirus humanbeta 5-HCMV, Roseolovirus humanbet 6-HHV-6, and Roseolovirus humanbeta 7-HHV-7) can infect epithelial cells like monocytes and lymphocytes, which are components of peripheral blood mononuclear cells, and establish latent infections [5]. High viral loads can be detected in blood and serum samples during viral reactivations [5]. Furthermore, saliva is considered a route of transmission of herpesviruses, including betaherpesviruses, and the salivary gland is a particularly permissive site for replication of these viruses [6]. In addition, previous studies published by our group demonstrated the presence of betaherpesviruses in salivary glands tissues and saliva samples, suggesting a possibly tropism for these organs [7]. Other studies in literature recognize saliva samples as biologically relevant and noninvasive specimens for the detection of HCMV, HHV-6, and HHV-7 [8][9][10].
HCMV is one of the most significant viruses in this family, since its prevalence ranges from 60% to 70% in individuals living in developed countries and reaches ~100% in those leaving developing countries [11]. HCMV is an opportunistic pathogen associated with severe morbidity and mortality cases in immune-compromised populations, mainly in organ transplant recipients, in individuals with acquired immune deficiency syndrome and in cancer patients (breast, brain, colorectal cancer, and some lymphomas) [12,13]. Although HCMV is the leading cause of congenital infection, which leads to several birth defect types, such as sensorineural hearing loss and neurological impairments, in children [14]. HCMV infection has been linked to the progression and development of several types of cancer associated with oncogenes like IE, IE2, US28, and UL6 [12]. This virus plays a key role in hematological patients, since acute infection leads to significant morbidity and mortality rates in this population [15]. HHV-6 was first observed in the blood lymphocytes of adult individuals with lymphoproliferative diseases. This virus is ubiquitous in more than 90% of the human population and its infection takes place in individuals for the first 3 years of life [16]. Studies have shown that HHV-6 is oncogenic and destructive to autoimmune cells. In addition, its immunomodulatory capacity triggers chronic immunosuppressive and inflammatory pathways [17]. Although the chronic infection remains asymptomatic in the overall population, it is associated with Hodgin's disease, besides other malignancies, in immunocompromised patients [18].
More than 95% of adult humans are persistently infected with HHV-7 [19]. Overall, the infection caused by it does not lead to clinical complications, although, recently, an increasing number of studies have associated it with severe clinical syndromes, such as transplant complications, neurological impairments, febrile syndromes and dermatological lesions [19]. Despite these complications, some studies reported this virus in patients with hematological malignancies [20][21][22][23]. HHV-7 reactivation typically happens during immunosuppression periods, in comparison to other herpesviruses, although this virus is often detected in healthy individuals [19].
Although these herpesviruses are often detected in patients with hematological malignancies [15,17,[24][25][26][27], their association with these health issues remains inconclusive. Furthermore, studies reporting these infections and viral load remain scarce in the literature. Therefore, the aim of the current study was to assess the frequency and viral load of betaherpesviruses (HCMV, HHV-6, and HHV-7) in patients diagnosed with hematological malignancies, by analyzing their association with clinicopathological features.
## 2 | Methods
## 2.1 | Sample Collection and Processing
The current descriptive and retrospective study was approved by the Ethics Committee on Human Research of State University of Londrina (CAAE: 32492720.9.0000.5231).
Samples were collected from September to October 2022, samples were collected at the time of clinical evaluation, typically within 7 days before treatment, 7 days after chemotherapy, and 7 days with completed the treatment. In total, 260 patients from a reference hospital for cancer patients were invited to participate in the study. The control group consisted of 159 individuals without hematological neoplasms. Saliva samples were collected from individuals who accompanied the patients and agreed to participate in the study. All participants signed the informed consent form; legal guardians of underage patients signed the document on their behalf. Inclusion criteria comprised patients diagnosed with HL, NHL, leukemia and MM. On the other hand, exclusion criteria encompassed patients presenting two, or more neoplasms, or autoimmune diseases. Clinicopathological data such as age, sex, clinical diagnosis, survival and death cases, relapse, metastasis, and treatment type were collected from electronic medical records. Saliva samples were collected from patient oral cavity by using rayon swab (Inlab, São Paulo, Brazil) and placed in cryotubes filled with 2 mL of sterile phosphate-buffered saline solution (PBS 0.1 M, pH 7.3). Specialized thermal boxes were used to transport these samples to the Basic and Applied Virology Laboratory (LAVIR) at State University of Londrina, where they were stored at -80°C, until processing time.
Biological samples were separated in aliquots and sent by specialized transport to the Molecular Virology and Parasitology Laboratory at Oswaldo Cruz Foundation, Rio de Janeiro, Brazil, where the viral detection process was carried out.
## 2.2 | Viral Detection and Viral Load Quantification
Initially, 140 µL of samples were used for nucleic acids extraction by QIAamp DNA Mini kit (Qiagen, Hilden, Germany), according to the manufacturer's recommendations. The extracted samples were stored at -80°C until analysis time.
Quantitative Real-Time (qPCR) was performed based on using commercial TaqMan Universal PCR Master Mix (Thermo Fischer Scientific, Waltham, MA, USA), to confirm viral detection, as well as to measure viral load through HCMV, HHV-6, and HHV-7 target regions U54, U56, and U37, respectively. Multiplex qPCR was performed according to manufacture instruction: the reaction mixture comprising 1 µL 25x PCR Enzyme, 1 µL of each oligonucleotide (3 µM), 1 µL of each probe (0.4 µM), 12.5 µL of 1x PCR Buffer and 2.5 µL of DNA. Oligonucleotides, probes, and synthetic standard curves were previously described by Raposo et al. [28]. Synthetic standard curves ranging from 5 to 5 × 10 8 copies/µL were used for absolute viral DNA quantification. Ultrapure water and negative samples were used as negative control and positive samples were used as positive control.
To normalize viral DNA quantification, amplification of the human housekeeping gene GAPDH was performed using the TaqMan GAPDH Oligo Mix (20x) (Applied Biosystems, Foster City, CA, USA) in combination with the TaqMan Universal PCR Master Mix, following the manufacturer instructions. Each reaction contained 12.5 µL of Master Mix, 1.25 µL of the GAPDH reagent, 6.25 µL of nuclease-free water, and 5 µL of DNA. The normalized viral loads were calculated using the ΔCt method (Ct_viral -Ct_GAPDH).
## 2.3 | Statistical Analysis
Descriptive statistics applied to the qualitative variables were defined through absolute and relative frequencies, whereas the distribution of quantitative variables was analyzed through the Kolmogorov-Smirnov test. Mean and standard deviation values were used in the analysis due to normal distribution of normal quantitative variables. Inferential statistics used 5% error margin and 95% confidence interval in all the analyses. χ 2 test was used to compare different neoplasia types presenting viral detection and Betaherpesvirus incidence to clinicopathological parameters set for NHL. Furthermore, ANOVA and Tukey's post hoc test were used to assess differences in viral load among different neoplasia types. Finally, the association between HHV-7 viral load and clinicopathological parameters was tested through Student's t-test. Statistical analyses were carried out in the Statistical Package for Social Sciences, version 20.0 (SPSS Inc., Chicago, USA).
## 3 | Results
## 3.1 | Patients' Clinicopathological Features
In total, 53.1% of all 260 patients belonged to the male sex, whereas 46.9% belonged to the female sex. Most patients were White (77.7%) and older than 61 years (45.4%). They were followed by the age group 41-60 years (26.5%) and 13.8% of them were in the age group 19-40 years, on average (Table 1). Most individuals were diagnosed with NHL (40.8%). They were followed by individuals diagnosed with leukemia (32.7%), MM (15.4%), and HL (11.2%). Most of them survived (84.6%). More than 90% of patients did not undergo antiviral therapy. Although, a high rate of HHV-7 detection was observed in individuals. Clinicopathological features are shown in Table 1, based on hematological neoplasms.
## 3.2 | Detection of Betaherpesviruses and Their Association With Patients Clinicopathological Features
Median values about betaherpesviruses presence and absence and association with clinicopathological features are shown in Table 2. A rate of 50.0% of viral positivity was observed in NHL samples. Most patients before treatment presented a rate of
## 3.3 | HCMV, HHV-6, and HHV-7 Detection in Patients With Hematological Neoplasm
If one takes into consideration the hematological neoplasm subgroups, HHV-7 was the most detected betaherpesvirus, 15.8% of cases (41/260). Statistical significance was observed through HCMV detection between HL and MM (p = 0.036). HHV-7 detection was statistically significant in all hematological neoplasm cases (p = 0.005) (Table 3). In relation to the control group, 2 (1.25%) individuals were positive for HCMV, 6 (3.77%) for HHV-6, and 14 (8.80%) HHV-7.
## 3.4 | Human Betaherpesvirus Viral Load
HHV-6 recorded a viral load of 3.59 × 10 5 in the total number of analyzed samples, whereas HHV-7 recorded 1.44 × 10 5 , which was the highest viral load observed in these samples in comparison to HCMV (4.08 × 10 4 ) (Figure 1). HHV-6/HCMV 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0)
Based on the analysis applied to hematological neoplasms, HHV-6 recorded the highest viral load in patients with NHL, whereas HHV-7 presented the highest viral frequency in individuals with HL and Leukemia (Figure 2). Statistical significance was observed between HCMV's mean viral load between HL and NHL cases (p = 0.014).
The GAPDH quantification cycle (Ct) ranged between 34.341 and 39.515, which is within the expected range for low-input biological samples such as oral swabs. These Ct values, while high, were consistently detected across all samples, supporting the use of GAPDH as a reliable reference for normalization in this context. The GAPDH was detected in all samples, and the integrity of saliva samples was ensured.
## 3.5 | HHV-7 Viral Load and Patients' Clinicopathological Features
Comparative analysis between viral load and patients with clinicopathological features was carried out because HHV-7 was the most detected virus. Statistical significance and high viral load were observed in patients after chemotherapy for hematological neoplasms (2.63 × 10 5 ) (p = 0.020) and in those presenting metastasis (8.14 × 10 5 ) (p = 0.002).
## 4 | Discussion
The current study focused on detecting Human betaherpesvirus and on calculating the viral load of these viruses in saliva samples collected from patients with hematological neoplasms, as well as on correlating them with clinicopathological features presented by these individuals. There was a high HHV-7 detection rate with a high viral HHV-6 load in these samples. Some clinicopathological features, such as metastasis, were associated with high HHV-7 viral load. Although Human Herpesvirus 7 (HHV-7) is a ubiquitous virus capable of establishing latency in host cells, current evidence does not support a direct role in oncogenesis. Unlike other herpesviruses such as the Epstein-Barr virus (EBV) and Kaposi's sarcoma-associated herpesvirus (HHV-8), which are wellestablished oncogenic agents, HHV-7 has not been classified as carcinogenic. However, some studies suggest that HHV-7 may influence cellular processes related to tumorigenesis, including cell cycle regulation, immune evasion, cell-to-cell spread, cytokine modulation, and interference with DNA mismatch repair pathways [19,27,29]. While HHV-7 DNA has been detected in certain tumor tissues, these findings remain inconclusive and require further investigation. To date, definitive molecular mechanisms need to be investigated linking HHV-7 to cellular transformation or cancer development.
High HHV-7 detection rate was recorded for saliva samples collected from patients and they presented statistically significant with leukemia, myeloma, HL, and NHL. Other studies had previously reported betaherpesviruses in saliva samples collected from renal patients [28] and from neoplastic and nonneoplastic salivary gland tissues [7], and it evidenced viral activity in this organ and shedding of viral particles in these patients' saliva. Rizk and Darwish conducted a study with 60 children diagnosed with acute lymphoblastic leukemia who were tested for EBV, HHV-6, and HHV-7 by qPCR. They reported high HHV-7 incidence in these patients, a fact that corroborated findings in the current study [30]. Another study detected HHV-7 in bone marrow and peripheral blood samples collected from children with acute lymphoblastic leukemia [20]. However, none of these studies has evidenced an association between HHV-7 infection and this disease.
NHL was the most common neoplasm observed in samples collected from both women and men in the age group 41-61 years, in White individuals and in those presenting relapse rates. NHL is the most common hematological malignancy worldwide; it accounts for ~3% of cancer diagnoses and associated death cases [31]. In 2020, ~544 000 new NHL cases and 260 000 related death cases were recorded at global scale. This finding indicates that NHL accounted for ~2.6% of all cancer-related death cases in that year, worldwide [32]. Individuals with aggressive NHL, mainly children and teenagers, presented relapse/refractory disease with accurate rates < 30% [33].
High leukemia incidence rates were observed in patients in the age group 0-19 years. On the other hand, it was mostly diagnosed in black and brown individuals at the age of 41 who recorded high metastasis rates. Recent data have indicated ~643 579 new leukemia cases in 2019 and 334 592 death cases, worldwide. This finding reflected an increase in the number of leukemia diagnosis and death-related cases in comparison to previous years [34]. Another aspect observed in the current study was that HHV-6 recorded the highest viral load in the analyzed samples in comparison to HCMV and HHV-7 in patients with leukemia.
Based on the literature, HHV-6 is often asymptomatic or associated with febrile illness known as exanthema subitum, and it has potential to reactivate during immunosuppression [35].
High viral loads can lead to complications in some cases; some studies previously reported the association of high HHV-6 viral loads with delayed platelet engraftment and encephalitis [36,37]. Another study reported that high HHV-6 viral load increases mortality risk in patients undergoing allogeneic hematopoietic stem cell transplant [38]. These findings underscore the clinical significance of HHV-6 reactivation in immunosuppressed patients, besides emphasizing the need to carefully monitor this population. Furthermore, HHV-6 recorded the highest viral load in the NHL patients assessed in the present study. Kiani and colleagues tested 44 HL and NHL tissue samples for HHV-6A/B; all NHL samples tested positive for HHV-6A [39].
The current study observed high HHV-7 viral load in patients with metastasis and a high viral frequency found in patients after chemotherapy. HHV-7 is linked to several lymphoproliferative cancer types, as well as to pediatric lymphoma, NHL, HL, acute leukemia, basal cell carcinoma, and glioma [40]. HHV-7 can infect both primary CD4+ T lymphocytes and the SupT1 lymphoblastoid T-cell line [40]. This factor can contribute to cancer development due to cell accumulation in Gap 2/ mitosis phase, as well as to polyploidy and increased cell size [40]. However, literature lacks evidence of HHV-7 infection associated with hematological malignancies, such as leukemia.
Previous study reported high HHV-7 rate in HL and NHL biopsies, but its biological significance remains unclear [22].
Although, the detection of HHV-7 in saliva should be interpreted with caution, particularly in immunocompromised patients. While the presence of the virus may indicate viral reactivation, its high prevalence in healthy individuals and across various clinical conditions suggests that detection alone is insufficient to establish a direct pathological association with hematological disorders [41]. Recent studies have shown that HHV-7 is commonly found in the saliva of healthy individuals, and its frequency increases in immunocompromised populations, such as HIV-infected patients [6]. In our study, the frequency of HHV-7 in saliva was 15.8% (41/260) and in the control group 8.80% (14/159). Longitudinal studies including immunocompetent controls are warranted to better elucidate the potential pathogenic role of HHV-7.
HCMV is also not classified as oncogenic virus, although studies have shown the association of this virus with some human cancer types [21,[42][43][44]. HCMV can persist as latent infection on the host for a lifelong time and leads to a whole series of disorders [44]. HCMV associations with HL and NHL have been reported. Mehravan and colleagues reported the prevalence of HCMV latent infection in histological tissue collected from patients with HL and NHL. They detected UL138 protein and HCMV's IE1 replication gene in the analyzed tissue [44].
Bogner and Pecher conducted a study with patients with MM and tested their humoral response for HCMV. They used a recombinant immunoblot test and recorded 80% IgG immune response to HCMV; this finding has evidenced viral infection in the assessed patients [45]. The HCMV viral load observed was statistically significant in patients with HL and NHL. On the other hand, HCMV viral detection was statistically significant in individuals with HL and MM.
Diagnostic insights into HHV-6 and HHV-7 in hematologic malignancy cases have emphasized the importance of detecting viruses capable of reactivating. According to recent studies, high HHV-6 and HHV-7 levels were associated with clinical complications and with increased posttransplant mortality rates, a fact that reinforces the need to adopt diagnostic approaches capable of combining accurate viral load quantification to patients detailed clinical assessment. These insights not only improve scientific understanding about viral behavior in hematologic malignancies but also pave the way for personalized therapeutic strategies. Although, this study has some limitations that should be considered when interpreting the findings. Saliva samples were collected from patients at different stages of hematological neoplasm treatment, which may have influenced viral detection due to variations in immune status and treatment-related immunosuppression. Despite this heterogeneity, the detection of HCMV, HHV-6, and HHV-7 in patients with hematological malignancies is relevant for understanding viral reactivation and its potential implications for disease progression and clinical management. Notably, HHV-7 was the most frequently detected virus, observed in 15.8% of patients and 8.8% of controls. However, its presence in saliva alone is not sufficient to establish a causal relationship with disease. Few studies have evidenced association between HHV-7 viral detection and viral load quantification in hematological neoplasm cases. This factor can be explained by the fact that this virus is not seen as oncogenic; consequently, it is the least investigated virus in this context. Moreover, patients undergoing chemotherapy require attention regarding the reactivation of viruses, such as HHV-6, otherwise it can lead to a poor prognosis. These findings underscore the need for longitudinal studies to further elucidate the pathogenic potential of HHV-7 and other betaherpesviruses in hematologic disorders and to evaluate their possible impact on treatment outcomes.
In summary, HHV-7 was the most frequently detected virus found in 15.8% of patients versus 8.8% of controls. However, its presence in saliva alone does not confirm disease association. Our findings reinforce the need for longitudinal studies to clarify the potential pathogenic role of HHV-7 and other betaherpesviruses in hematological neoplasms, and their possible impact on patient outcomes.
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38. Winestone, Punn, Tamaresis (2018) "High Human Herpesvirus 6 Viral Load in Pediatric Allogeneic Hematopoietic Stem Cell Transplant Patients Is Associated With Detection in End Organs and High Mortality" *Pediatric Transplantation*
39. Kiani, Makvandi, Samarbafzadeh (2016) "Association of HHV-6 With Hodgkin and Non Hodgkin Lymphoma" *Iranian Journal of Microbiology*
40. Alibek, Baiken, Kakpenova (2014) "Implication of Human Herpesviruses in Oncogenesis Through Immune Evasion and Supression" *Infectious Agents and Cancer*
41. Li, Qu, Li et al. (2022) "Human Herpesvirus 7 Encephalitis in an Immunocompetent Adult and a Literature Review" *Virology Journal*
42. Yu, He, Zhu et al. (2023) "Human Cytomegalovirus in Cancer: The Mechanism of HCMV-Induced Carcinogenesis and Its Therapeutic Potential" *Frontiers in Cellular and Infection Microbiology*
43. Lepiller, Tripathy, Di et al. (2011) "Increased HCMV Seroprevalence in Patients With Hepatocellular Carcinoma" *Virology Journal*
44. Mehravaran, Makvandi, Zade (2017) "Association of Human Cytomegalovirus With Hodgkin's Disease and Non-Hodgkin's Lymphomas" *Asian Pacific Journal of Cancer Prevention*
45. Bogner, Pecher (2013) "Pattern of the Epitope-Specific IgG/IgM Response Against Human Cytomegalovirus in Patients With Multiple Myeloma" *Clinical and Vaccine Immunology*
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# Correction for Zhao et al., "IDO1 promotes CSFV replication by mediating tryptophan metabolism to inhibit NF-κB signaling"
Feifan Zhao, Yaoyao Huang, Junzhi Ji, Xueyi Liu, Xiaowen Li, Linke Zou, Keke Wu, Xiao Liu, Sen Zeng, Xinyan Wang, Wenshuo Hu, Yiwan Song, Zhimin Lu, Bolun Zhou, Peng Li, Weijun Wang, Mingqiu Zhao, Jinding Chen, Lin Yi, Shuangqi Fan
## Abstract
In Fig. 3A andC, "SCFV" should read "CSFV. " We apologize for these errors, which did not change the final result.
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# Microplastics and Nanoplastics as Carriers for Viral Transmission: Effects on Viral Properties, Infection, Immune Response, and Public Health
Cosmina Mija, Giuseppe Sberna, | Fabrizio
## Abstract
The extensive use of plastics since the industrial revolution has raised significant environmental and health concerns. Despite their advantages in terms of durability, affordability, and ease of production, the accumulation of plastics has resulted in considerable pollution. The SARS-CoV-2 pandemic further exacerbated plastic consumption, particularly in medical supplies, intensifying the plastic waste crisis. The majority of plastics are not recycled and eventually degrade into microplastics (MPs) and nanoplastics (NPs), which pose substantial risks to ecosystems and human health. MPs and NPs enter the body through inhalation, ingestion, or skin contact and have been found in biological samples such as blood, faeces, and lung fluids. Their presence has been linked to diseases affecting the lungs, cardiovascular system, and intestines, as well as cancer and viral infections. This review highlights how MPs and NPs contribute to the spread of infectious diseases by creating a habitat called the "plastisphere," which promotes microbial growth and serves as a reservoir for pathogens, emphasising their effects on viral persistence, infection dynamics, and immune modulation. Unlike previous reviews mainly focused on toxicological or microbiological aspects, this work integrates environmental, virological, and immunological evidence to outline how MPs/NPs may reshape virus-host interactions. By identifying critical knowledge gaps, such as the quantitative impact of MPs/NPs on viral stability and immune disruption, this review provides a background for future experimental and epidemiological research. This value-added perspective not only advances scientific understanding but also supports policy development in waste management.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
## 1 | Introduction
Since the industrial revolution, the use of plastics has increased significantly worldwide. The growing use of plastics is due to their properties in terms of durability and simple manufacturability, as well as the low production costs and low energy demand [1]Global consumption has increased from approximately 5 million tons in the early 1950s to 413.8 million tons in 2023, with Europe accounting for nearly 12.3% of the total global plastic production [2]. In this context, the SARS-CoV-2 pandemic had a significant impact, since the production of plastics drastically increased to meet the surging demand for disposable medical supplies, such as personal protective equipment and testing kits [3][4][5][6][7]. Unfortunately, only a tiny percentage of plastic waste is recycled [8] with most plastics being released into the environment [9] where they are exposed to physical and mechanical forces that degrade and eventually convert them into micro-and nanoscale-sized particles [10][11][12]. Based on the size difference, these particles are classified as microplastics (MPs) (1000-1 μm) and nanoplastics (NPs) (< 1 μm) [13][14][15]. MPs and NPs can be derived from numerous sources, such as urban transportation, industrial pollutants, and the manufacturing of different products (i.e., cosmetics, packing materials, and medical equipment), and they are categorised as primary or secondary plastics [16]. Primary MPs and NPs are intentionally manufactured and added to commercial products like cosmetics, personal care products, pharmaceuticals, detergents, and insecticides, while secondary MPs and NPs are unintentionally formed by the breakdown of larger plastic materials, such as plastic bags or plastic bottles [17]. These tiny plastic particles have a significant impact not only on the environment but also on human health [17] since they can easily enter the human body through different routes (i.e., inhalation, ingestion, or dermal contact) [1]. The presence of MPs and NPs in the human body is demonstrated by the detection of these particles in different types of biological samples, such as faeces [18][19][20], bronchoalveolar lavage fluid [21], sputum [22], saliva [23] and blood [24]. Depending on their shape, size, and quantity, MPs can have different consequences for human health, as they are able to alter several cellular and molecular mechanisms. Exposure to MPs and NPs has been demonstrated to be related to the occurrence of lung [22,25,26] cardiovascular [27][28][29] and intestinal diseases [30][31][32][33], as well as cancer development [34][35][36][37][38]. Furthermore, these nano-and micro-sized plastic particles can promote the occurrence of infectious diseases, as they can act as scaffolds for various biological agents (fungi, bacteria, and viruses) [39]. Over time, MPs and NPs get coated with organic materials such as proteins and other biomolecules, forming a structure known as "protein corona" or "eco corona" [40], thus creating a suitable substrate growth area for microbial communities. This new ecological habitat, named plastisphere, can threaten human health, as it facilitates the survival and dissemination of potentially pathogenic microorganisms [41]; the process of plastisphere formation is illustrated in Figure 1.
Considering the increasing focus on viral infections, also related to the recent SARS-CoV-2 pandemic, efforts are being made to clarify the ecological and clinical impact of the interaction between MPs/NPs and viruses. However, there is still little knowledge about this topic, highlighting the importance of further investigation. Several studies have discussed the environmental impacts of MPs/NPs and their toxicological consequences for human health. However, most of these works have either focused on the toxicity of MPs/NPs [16][17][18] or on their interactions with microbial communities [39][40][41], without a systematic evaluation of viral dynamics. Moreover, few studies have connected the environmental fate of MPs/NPs with their clinical implications for viral persistence and immune modulation [16,17,36].
In this regard, this review aims to provide a comprehensive overview of viruses in plastisphere habitats and examine the consequences of this interaction for human health. With this in mind, we report focused studies on plastispheres and viruses with a summary of the main findings from the current literature in order to provide solid information about (i) the factors that contribute to the interaction between MPs/NPs and viruses, (ii) the consequences of this interaction on viral characteristics, and (iii) the implications that this interaction has on the ability to cope with the infection. This novelty and relevance distinguish our work from previous reviews and provide a foundation for targeted future research.
## 2 | Methodology
This review was conducted following a structured approach to ensure transparency and reproducibility. Literature was retrieved from PubMed database, covering the period from January 2015 to March 2025. The following keywords and Boolean combinations were used: "microplastics/nanoplastics and virus", "microplastics/nanoplastics and viral infection", "plastisphere and pathogens", "microplastics/nanoplastics and immune response". Moreover, studies identified through citations in other articles were used.
The applied inclusion criteria were: peer-reviewed original research articles, reviews, and relevant reports in English; studies providing experimental, clinical, or epidemiological evidence on MPs/NPs interactions with viruses or immune systems; documents concerning the impact of plastics on health and the environment.
A total of 1526 records were initially identified, 327 were screened, of which 159 met inclusion criteria, and 74 were incorporated into this review. References were critically assessed to highlight consistencies, discrepancies, and research gaps.
## 3 | Plastisphere Formation
The wide distribution and high prevalence of viruses make it possible for them to easily interact with various substrates, including plastic surfaces [41]. Viruses can attach to MPs/NPs both through direct and indirect interactions. In case of direct contact, viruses adhere to naked abiotic surfaces through nonspecific electrostatic interactions and hydrophobic forces [42,43]; while in the case of indirect contact, they attach to plastics by interacting with microorganisms or binding to biomolecules, forming the eco corona of the plastic particle [41]. The mechanisms by which viruses can bind to biofilms on plastic surfaces are still poorly understood; nevertheless, there is scientific evidence highlighting the ability of some viruses to interact with other microorganisms [44] or to bind to macromolecules [45]; factors influencing the association between viruses and MPs/ NPs are summarised in Figure 2.
## 3.1 | Factors Influencing Viral Association to
## Plastisphere: Viral Characteristics
Viruses' stability in the environment, as well as their ability to interact with abiotic surfaces, are strongly influenced by characteristics related to the structure and composition of the viral particle. The viral strain, the capsid composition, and the presence or absence of an envelope are all factors contributing to the binding affinity between plastics and viruses [46]. An example of the influence of the viral strain in the interaction with plastics is reported by Zhang et al. who revealed that the affinity between MPs and SARS-CoV-2 was higher than the affinity between MPs and SARS-CoV-1 or Hepatitis B virus, regardless of the experimental conditions or the type of plastics tested [43]. The ability of viruses to bind to plastic particles is also related to the type of proteins forming the viral capsid. Cotten et al. highlighted how the positively charged viral capsid components of the SARS-CoV-2 virus may interact with negatively charged MPs [47]. As for the influence of the presence of an envelope, it has been observed that it can reduce the binding affinity between the viral particle and the plastic surface, thus suggesting that the presence of an envelope may limit virus interaction with the plastisphere [48]. In conclusion, the interaction between viruses and plastic particles is influenced by multiple structural factors, including the viral strain, capsid composition, and presence of an envelope. These findings highlight the complexity of virus-plastic interactions and their dependence on specific viral characteristics.
## 3.2 | Factors Influencing Viral Association to
## Plastisphere: Plastic Characteristics
The chemical and physical characteristics of plastic surfaces can alter the viral potential for adhesion and persistence in the plastisphere system [41,46]. Lu et al. showed that virus adsorption rates are dependent on MPs size with absorption levels being inversely proportional to the plastic surface area, and on MPs functional groups, with specific chemical groups being associated with a higher absorption rate [49]. Also, the colour of the plastic area can play a critical role in the plastisphere formation, as different colours may affect the UV light absorption capacity [50,51]. There are pigments that better absorb UV radiation with respect to others: plastic areas presenting such pigments (i) are more easily deteriorated, thus presenting a low probability for microbial colonisation, and (ii) could be responsible for an increased possibility of damaging the microbial genome. Therefore, on plastics containing pigments that have a high UV absorption capacity, there is a lower probability of plastisphere formation. Moreover, the composition of the microorganism community colonising plastisphere systems is also influenced by the charge, the hydrophobicity/hydrophilicity, and the roughness of the plastic surface [52].
## 3.3 | Factors Influencing Viral Association to
## Plastisphere: Environmental Characteristics
External factors, such as temperature, humidity, salinity, and PH conditions affect the stability of viruses [53][54][55][56][57][58][59], thus interfering with their ability to interact with plastic surfaces. Several studies reported that rising temperatures may affect the half-life of viruses, as well as their infectivity rate, pointing out that sensitivity to increasing temperature is strongly influenced by the type of virus [58,60]. As a matter of fact, while Biryukov et al. reported that a temperature of 35°C was sufficient to substantially reduce the SARS-CoV-2 half-life on different surfaces [58], Skelton et al. showed that a considerably higher temperature (90°C) is indeed required to denature Tomato Brown Rugose Fruit Virus, suggesting that viral ability to bind to plastic materials might be differently affected when increasing temperature [60]. Variability has also been observed when analysing how the humidity rate may influence viruses' persistence, with some viruses being more stable in high humidity conditions [61,62] and others in low humidity conditions [58]. Furthermore, it was reported that viruses' ability to resist the drying process was correlated to the type of surface, with plastic surfaces being the ones where the highest stability was detected [61,62]. Considering that salinity and pH conditions can also affect viral persistence and viability [63], it should be noted that the environmental factors influencing the plastisphere formation are many, and they can have different effects on different plastisphere systems. 4 | Impact of the Virus-MPs/NPs Interaction on
## Viral Properties
Widespread due to plastic pollution, MPs and NPs influence viral stability, transmission, and pathogenicity, acting as protective carriers that enhance viral persistence and spread. Tang et al. have demonstrated that MPs can act as carriers for viral particles, providing a protective environment that enhances viral persistence and facilitates their dissemination. Polystyrene nanoplastics (PS-NPs) have been shown to significantly alter viral behaviour. For instance, research on the vaccinia virus has revealed that PS-NPs accelerate migrasome formation, a process that enhances viral transmission by facilitating early viral entry into host cells and increasing lipid droplet accumulation [64].
In aquatic environments, MPs have been identified as potential vectors for viral pathogens, with studies showing that fish exposed to both MPs and viral infections exhibit increased mortality rates and compromised immune responses [65,66]. Moreover, Wang et al. have shown that MPs facilitate viral infections by weakening physical barriers such as the gill epithelium and intestinal lining, increasing viral loads and mortality rates in fish species like European sea bass and rainbow trout [67]. Similar findings have been observed in honeybees, where ingestion of PS-MPs has been linked to greater susceptibility to viral infections. Experimental evidence suggests that PS-MPs accumulate in the midgut, impair immune-related gene expression, and facilitate the systemic spread of viruses, thereby exacerbating infection severity [68].
Moreover, environmental virology research has suggested that MPs in terrestrial and aquatic ecosystems may prolong the survival of human enteric and respiratory viruses. Plastics provide surfaces for biofilm formation, creating microhabitats known as the "plastisphere," where viruses can adhere, persist, and potentially retain infectivity [41]. This raises concerns about the role of MPs as reservoirs for human pathogens, especially in wastewater systems, where the presence of MPs has been linked to the potential transmission of SARS-CoV-2 [69]. Studies have hypothesised that MPs, particularly polyvinyl chloride and polyethylene particles found in sewage, can serve as viral attachment sites, enhancing the stability of viral particles in open waters and increasing their potential for trophic transfer through the food chain [69].
The interaction between MPs/NPs and viruses is not limited to their role as passive carriers. Some studies indicate that exposure to MPs can actively modulate host immune responses, leading to increased viral replication and reduced antiviral defence mechanisms. For example, in marine organisms such as the orange-spotted grouper, PS-NPs have been found to downregulate toll-like receptor genes and interferon-related genes, which are crucial for antiviral immunity [67]. Similarly, in largemouth bass, exposure to PS-NPs has been associated with enhanced viral replication and inflammatory responses, further indicating that MPs/NPs may not only serve as vectors but also exacerbate the severity of infections [70].
So, as depicted above, the increasing presence of MPs/NPs in the environment, and especially their interaction with viral pathogens, presents a growing risk to both ecological and human health.
## 5 | Impact of the Virus-MPs/NPs Interaction on the Host's Immune Response
MPs and NPs can serve as vectors for viral particles, increasing their stability and persistence in various environments, which may enhance viral transmission and host exposure [70]. These small plastic particles, often present in water, soil, and even air, can adsorb viruses onto their surfaces, protecting them from environmental degradation and potentially extending their infectivity [39].
Once internalized, MPs and NPs can modulate the host's immune response through various mechanisms. They may disrupt normal antigen presentation by dendritic cells, impairing the adaptive immune system's ability to recognise and neutralise viral pathogens [39]. Additionally, the presence of MPs/NPs in biological systems has been linked to oxidative stress, inflammation, and immune dysregulation, which could exacerbate the severity of viral infections [39]. These particles can induce the excessive release of pro-inflammatory cytokines, leading to a hyperinflammatory state, commonly referred to as a "cytokine storm," which has been associated with severe outcomes in viral diseases [39]. In murine models of SARS-CoV-2, microplastics deposited in lung tissue were found to initially dampen the innate immune response, creating a window of vulnerability for viral replication. However, as the infection progressed, MPs triggered a hyperinflammatory state resembling cytokine storm syndrome, a key driver of severe COVID-19 cases in humans [71]. This dual effect (initial immune suppression followed by excessive inflammation) suggests that environmental MPs/NPs may act as immune disruptors, worsening viral disease outcomes and increasing susceptibility to emerging pathogens.
Furthermore, MPs and NPs may interfere with immune homoeostasis, either by overstimulating the immune system, by oxidative stress, or by suppressing key immune functions, making the host more susceptible to secondary infections [70,71]. Some studies suggest that these particles could provide a protective microenvironment for viral particles, shielding them from immune clearance and increasing their ability to evade host defences [39]. This interaction might also contribute to viral evolution, as prolonged environmental stability and reduced immune pressure could favour the emergence of more virulent or resistant viral strains [39]. For instance, experiments on rodents have shown that MP ingestion leads to prolonged inflammatory responses, exacerbating conditions such as viral arthritis [72]. Similarly, NPs have been observed to suppress antiviral defence mechanisms by downregulating the expression of key immune genes, including toll-like receptors (TLRs) and interferon-stimulated genes (ISGs), ultimately reducing the host's ability to mount an effective response against viral pathogens [71]. This immune suppression can lead to prolonged infections and increased disease severity, particularly in individuals already exposed to environmental stressors.
Given the widespread presence of MPs and NPs in the environment due to plastic pollution, understanding their role in viral pathogenesis is critical. Further research is needed to elucidate the full extent of their impact on immune responses and to develop strategies for mitigating potential health risks associated with chronic exposure to MPs and NPs [39].
## 6 | Discussion
The interaction between MPs/NPs with viruses represents a critical emerging concern for public health. As plastic pollution continues to rise, so does the potential for MPs and NPs to act as vectors for viral transmission, influencing viral stability, infectivity, and host immune responses [41]. Understanding these interactions is essential for developing effective public health strategies aimed at mitigating the risks associated with plastic pollution and viral infections.
One of the primary concerns is that MPs and NPs provide a protective environment for viruses, allowing them to persist in ecosystems for extended periods. Research has shown that certain viral strains exhibit increased affinity for plastic particles, enhancing their stability and potentially increasing their infectivity [43]. This phenomenon raises concerns about the role of MPs and NPs in prolonging the survival of pathogenic viruses in water bodies, soil, and even air, thereby increasing the likelihood of human exposure [69].
From a public health perspective, the implications are profound. The ingestion or inhalation of MPs and NPs carrying viral particles could lead to increased infection rates, particularly in vulnerable populations with pre-existing conditions or weakened immune systems [39]. Moreover, the ability of MPs to alter immune responses by inducing oxidative stress and inflammatory reactions suggests that plastic pollution may not only facilitate viral transmission but also exacerbate the severity of infections [71]. Studies have highlighted that microplastics can modulate immune responses by disrupting antigen presentation, impairing interferon signalling pathways, and even contributing to hyperinflammatory states, such as cytokine storms, which are linked to severe outcomes in viral diseases like COVID-19 [39].
Environmental factors further complicate this issue. Conditions such as temperature, humidity, and UV exposure can influence both viral persistence on plastic surfaces and the composition of microbial communities within the plastisphere [58,60]. These variables determine the extent to which MPs serve as reservoirs for viruses and other pathogens, reinforcing the need for comprehensive environmental monitoring and risk assessment [41].
To contextualise this work, a comparative analysis with existing reviews is provided in Table 1. Previous reviews have focused primarily on environmental occurrence and toxicological impacts of MPs/NPs [16][17][18]39], their sources and remediation strategies [17], or methodological aspects of monitoring marine litter [13]. Some reviews addressed health outcomes [16,35], while more recent work specifically examined viruses hosted in plastisphere systems [46]. However, these studies lacked an integrated virological and immunological perspective. The present review adds value by synthesising evidence on viral persistence, immune dysregulation, and clinical implications, thereby bridging the gap between environmental science, virology, and public health.
It is also important to highlight that microplastics could be useful for developing new systems for virus detection. This is precisely what Kim et al. experimented with the creation of porous charged polymer nanosheets, formed by removing microplastics from frozen ice, which are useful for virus filtration and detection [73].
Given these findings, immediate action is necessary to address the dual threats of plastic pollution and viral transmission. Policies aimed at reducing plastic waste, improving waste management systems, and regulating the use of MPs in consumer products should be prioritised. Additionally, further research is needed to elucidate the mechanisms by which MPs influence viral transmission and immune response, as well as to explore potential mitigation strategies [70].
## 7 | Conclusion
The interaction between MP/NPs and viruses represents a new and urgent concern for both environmental and biomedical sciences. This review provides an integrated perspective linking the environmental fate of MP/NPs with viral persistence, infection dynamics and immune system compromise, thus highlighting a scientific value that goes beyond previous analyses. The literature reports that MP/NP can act as viral vectors, prolonging the viability of pathogens and increasing the risk of transmission. However, their ability to modulate immune responses is still a poorly explored topic that requires further investigation, as it could influence the course of viral infections. From a practical point of view, the results described in the literature and reported in this review highlight the need for global action. It is therefore necessary to prioritise improving plastic waste management, reducing primary microplastics in consumer products, and more rigorous environmental monitoring of MP/NPs in water and atmospheric systems. Future research should focus on quantitative assessments, such as measuring the exact increase in viral survival on MPs and clarifying dose-response relationships in immune modulation.
Overall, this work frames MP/NP as emerging virological risk factors. Integrating environmental sustainability with infectious disease awareness is essential to mitigate the dual threat posed by plastic pollution and viral transmission.
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56. Edwards (2000) "Survival and Inactivation of Classical Swine Fever Virus" *Veterinary Microbiology*
57. Park, Son, Ryu et al. (2020) "Effects of Temperature, Humidity, and Diurnal Temperature Range on Influenza Incidence in a Temperate Region" *Influenza Other Respir Viruses*
58. Biryukov, Boydston, Dunning (2020) "Increasing Temperature and Relative Humidity Accelerates Inactivation of SARS-CoV-2 on Surfaces" *mSphere*
59. Romeo, Specchiarello, Mija (2024) "Heat Treatment as a Safe-Handling Procedure for Rift Valley Fever Virus" *Pathogens*
60. Skelton, Frew, Ward (2023) "Tomato Brown Rugose Fruit Virus: Survival and Disinfection Efficacy on Common Glasshouse Surfaces" *Viruses*
61. Qian, Morris, Avery (2023) "Variability in Donor Lung Culture and Relative Humidity Impact the Stability of 2009 Pandemic H1N1 Influenza Virus on Nonporous Surfaces" *Applied and Environmental Microbiology*
62. Wolff, Günther, Johne (2022) "Stability of Hepatitis E Virus After Drying on Different Surfaces" *Food and Environmental Virology*
63. Zhang, Fang, Li (2024) "Research Progress on Environmental Stability of SARS-CoV-2 and Influenza Viruses" *Frontiers in Microbiology*
64. Tang, Hou, Zhao et al. (2024) "Polystyrene Nanoplastics Enhance Poxvirus Preference for Migrasome-Mediated Transmission" *Biochemical and Biophysical Research Communications*
65. Seeley, Hale, Zwollo et al. (2023) "Microplastics Exacerbate Virus-Mediated Mortality in Fish" *Science of the Total Environment*
66. Yan, Yao, Wang et al. (2024) "Effect of Polypropylene Microplastics on Virus Resistance in Spotted Sea Bass (Lateolabrax maculatus)" *Environment and Pollution*
67. Wang, Duan, Huang (2021) "Polystyrene Nanoplastics Alter Virus Replication in Orange-Spotted Grouper (Epinephelus coioides) Spleen and Brain Tissues and Spleen Cells" *Journal of Hazardous Materials*
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# Characterization of two novel Negevirus strains and analysis of global Negevirus distribution and host diversity
Xiang Sun, Han Xia, Zhaolin Li, Feng Tian, Yi Huang, Doudou Huang, Fei Wang, Zhiming Yuan
## Abstract
Mosquitoes and mosquito-borne viruses pose a significant global public health concern. Furthermore, mosquitoes carry a wide range of insect-specific viruses (ISVs), and studying these ISVs is important due to their potential influence on mosquito behavior and the transmission of mosquito-borne viruses. In this study, we report the first isolation of two Negevirus strains from Aedes and Culex mosquitoes in Xinjiang, China: Dezidougou virus (DEZV, isolate XJ-ALT23-420-01) and Negev-like virus (NEGLV, isolate XJ-JH20-91-01). Phylogenetically, the nucleotide sequence of DEZV exhibits high similarity (98.96%) with the DEZV isolate 8345 from Germany but shows lower similarity (< 91.91%) with other DEZV strains. In contrast, the NEGLV isolate XJ-JH20-91-01 displays significant divergence from other Negevirus, sharing only 79.39% nucleotide similarity with the most closely related strain, NEGV BeAr805514. Both DEZV/XJ-ALT23-420-01 and NEGLV/XJ-JH20-91-01 replicated rapidly in mosquito cell lines (C6/36 and Aag2), reaching viral loads of up to 10 9-10 copies/mL, causing significant cytopathic effect (CPE) in these cell lines but failing to replicate in vertebrate cells. In addition, analysis of the location and potential hosts of all published Negevirus members indicated their wide distribution and diverse host range. These findings extend the current spectrum of Negevirus group and provide deeper insights into its geographical distribution and host diversity.
## Introduction
There are two major groups of viruses that circulated in mosquito: mosquito-borne viruses (MBV) and mosquitospecific viruses (MSV) [18]. MBV, a subset of arbovirus, can infect both mosquito and vertebrate, whereas MSV belong to the insect-specific virus (ISV) group and replicate exclusively in mosquito [24]. The first discovered ISV was Cell-fusing agent virus (CFAV), which was identified by Stollar and colleagues in 1975 from Aedes aegypti cell lines. With advances in high-throughput sequencing and the implementation of mosquito virome surveys, an increasing number of ISVs have since been discovered. ISVs are widely distributed across diverse viral taxonomic groups, such as Flaviviridae [2,8,21], Bunyaviridae [3],
Togaviridae [4], Mesoniviridae [14,25], Reoviridae [10,13], Rhabdoviridae [26], and new taxons such as Negevirus [5,7,20,27,30].
Research have demonstrated that the presence of MSVs can influence the replication and proliferation of MBVs. For example, Nhumirim virus (NHUV), isolated from mosquitoes in Brazil, significantly suppresses the amplification of West Nile virus (WNV), Japanese encephalitis virus (JEV), and St. Louis encephalitis virus (SLEV) when co-infecting C6/36 cells. The inhibitory effect was most pronounced against WNV and SLEV, with peak viral titers reduced by 10 6 PFU/mL and 10 4 PFU/mL, respectively [12]. These findings suggest that studying MSV-MBV interactions may offer novel strategies for controlling the spread of MBV. However, the mechanisms by which MSVs modulate MBV replication, dissemination, and transmission remain unclear.
Negevirus is a new taxon group of non-segmented, single-stranded positive-sense RNA viruses with wide geographic distribution. The genome size for Negevirus is around 9-10 kb, containing three open reading frames (ORFs), flanked by 5′ and 3′ untranslated regions (UTRs), and terminates in a 3′ poly (A) tail. The virus particles are ellipsoidal or spherical in shape, with a diameter of 45-55 nm [27]. The genus Negevirus has been classified into two distinct clades: Nelorpivirus and Sandewavirus [11] Based on genomic organization and phylogenetic analysis, which are distantly related to some plant viruses, such as Cileviruses, Higrevirus and Blunervirus. While primarily detected in mosquitoes, they have also been identified in sandflies, bees, and other arthropods.
In this study, during mosquito and virus surveillance conducted in Xinjiang, China, we isolated one strain of Dezidougou virus (DEZV) from Aedes vexans and one strain of Negev-like virus (NEGLV) from Culex pipiens. The genome sequencing, viral purification, growth characteristics, and phylogenetic relationships of these two Negevirus isolates were analyzed. Additionally, the global distribution patterns and host diversity of all known Negevirus members were investigated.
## Method
## Cells
The C6/36 and Aag2 (mosquito cell lines), VeroE6, BHK-21, SW13, and PK15 (vertebrate cell lines) were used in this study.
C6/36 and Aag2 cells were maintained in CO₂ incubator at 28 °C in Roswell Park Memorial Institute (RPMI) 1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin-streptomycin (PS). BHK-21, VeroE6, SW13, and PK15 cells were cultured in CO₂ incubator at 37 °C in Dulbecco's minimal essential medium (DMEM) containing 10% FBS and 1% PS.
## Mosquito collection and preparation
From June 2020 to July 2023, mosquito collections were conducted in Xinjiang Uygur Autonomous Region, China, focusing on the Ebinur Lake and Takeshiken Port area (SFigure 1). Mosquitoes were captured using CO₂baited traps and subsequently identified morphologically using taxonomic keys from Fauna Sinica, Insecta Vol. 8: Diptera, Culicidae [17].
Approximately 50-60 mosquitoes of the same species were pooled per sample and homogenized in RPMI 1640 medium supplemented with 2% PS. The homogenate was centrifuged at 4 °C and 15,000 g for 30 min, then the debris in the bottom was discarded and centrifuged again at 15,000 g for 10 min to get the supernatant.
## Virus isolation and purification
Cells were seeded into 24-well plates (C6/36: 2 × 10 5 cells/ well; VeroE6 and BHK-21: 1.6 × 10 5 cells/well). The supernatant acquired in the above step was used to inoculate cell monolayers in 24-well plates. After a 1-h incubation at 28 °C (C6/36) or 37 °C (VeroE6 and BHK-21), the inoculum was removed and replaced with maintenance medium (RPMI 1640 for C6/36 and DMEM for mammalian cells) containing 2% FBS. Cells were observed daily for 7 days to examine cytopathic effect (CPE), with all procedures replicated three times.
The supernatant from the well showing CPE was harvested for high-throuhput sequencing, assembly, and analysis. Virus-specific PCR primers (STable 1) were designed based on the sequencing results and were used for viral identification in cell culture. Samples in which only a single virus was detected were used for further plaque purification on C6/36 cells.
## Virus sequencing
Supernatant from infected cells were harvested for viral RNA extraction using an automated nucleic acid extraction system (NanoMagBio, S-48 and NMG0966-16). RNA sequencing libraries were developed by Institutional Center for Shared Technologies and Facilities of Wuhan Institute of Virology, CAS. Sequencing was performed at Center for Instrumental Analysis and Metrology of Wuhan Institute of Virology, CAS, using the Illumina Novaseq platform. A total of 16 Gb of data was generated and submitted to Sequence Read Archive (SRA) database (accession No. PRJNA1311797). The raw reads were quality-controlled using Trim Galore v0.6.10 prior to downstream analysis. The trimmed sequences were then assembled de novo with Trinity v2.15.2 [9] and subsequently compared against the NCBI core nucleotide database (core_nt) using BLASTn v2.17.0 to identifiy viral sequences.
Overlapping primers (STable 2 and STable 3) were designed according to the assembled contigs using Primalscheme [19] (https://primalscheme.com/). P u r i f i e d viral RNA was reverse transcribed and amplified by PCR, followed by purification of PCR products using the E.Z.N.A.® Gel Extraction Kit (Omega Bio-Tek, D2500-02). Missing terminal sequences were obtained using the HiScript-TS 5'/3' RACE Kit (Vazyme, RA101) according to the manufacturer's protocol. The complete viral genome was obtained through sequence splicing and assembly using DNASTAR Lasergene SeqMan Pro v7.1.
## Viral morphological characteristics
The virus was amplified using C6/36 cell lines. After 2 days of cultivation, the supernatant from samples exhibiting CPE was collected and purified by sucrose density gradient centrifugation (Beckman Coulter SW32, 4 °C, 32,000 rpm for 3 h). The supernatant was then discarded, and the precipitates were resuspended in 400 μL phosphate-buffered saline (PBS). Prior to ultracentrifugation, a sucrose gradient solution was prepared, and the viral supernatant was carefully layered onto it.
Ultracentrifugation was performed at 4 °C for 4 h using a Beckman MLS50 rotor at 45,000 rpm. After centrifugation, the position of the viral band in the centrifuge tube was observed and recorded. A 1 mL syringe was then inserted into the band to aspirate the target viral band. Excess sucrose was removed using an Amicon Ultra-0.5 Centrifugal Filter Unit (50 kDa), following the manufacturer's protocol, and this step was repeated five times.
The purified viruses were loaded onto Formvar carboncoated copper grid and negatively stained with 1% uranyl acetate. Morphological analysis was conducted using a Thermo Scientific Talos L120C transmission electron microscope operated at 120 kV.
## Plaque and TCID50 assay
Virus titration was performed as described by Vasilakis' team [27]. Viral progeny formed plaques on C6/36 cell monolayers in 24-well plates. The viral supernatant was serially diluted tenfold in culture medium. For each well, 100 μL of virus dilution in different fold was added, and the plates were incubated at 28 °C for 1 h, gently rocked every 15 min. Afterward, the supernatant was discarded and replaced with 100 μL of a medium consisting of a 1:1 mixture of 2% tragacanth suspension and 2 × RPMI with 5% FBS, 2% tryptose phosphate broth (TPB), and 2% PS. The cells were incubated at 28 °C for 2 days to allow plaque formation. After incubation, the overlay was discarded, and the cells were fixed with 10% formaldehyde for 1 h. Staining was done overnight at room temperature with 2% crystal violet and plaques were counted and recorded after removing excess stain under running water.
Viral titers were additionally quantified using the 50% tissue culture infectious dose (TCID50) endpoint dilution method. A monolayer of C6/36 cells was spread in a 96-well plate. The viral supernatant was serially diluted tenfold from 1 × 10⁻ 1 to 1 × 10⁻ 11 , repeated eight wells per gradient. For each column, 100 μl of the viral supernatant was added and incubated for 1 h. The plate was gently shaken every 15 min, then the supernatant was discarded, and the plate was replaced with 200 μL RPMI (2% FBS and 2% PS) medium for incubation at 28 °C. The cell growth status was monitored daily and quantified for each well.
## Virus grow kinetics
The growth kinetics of DEZV/XJ-ALT23-420-01 and NEGLV/XJ-JH20-91-01 were determined in two mosquito cell lines: C6/36 (Aedes albopictus) and Aag2 (Aedes aegypti), and four vertebrate cell lines: VeroE6 (monkey), BHK-21 (baby hamster), SW13 (human), and PK-15 (pig).
Briefly, cells were seeded into T-25 flasks (10 5-6 cells/ per flask). After cultivation for 24 h, the cells were incubated with virus at a ratio of viral RNA copies to cell number (R/C) from 0.001 to 1000. After incubation for 1 h, the inoculation was removed, washed three times with PBS, and replaced by fresh RPMI-1640 medium containing 2% FBS. Supernatant from the infected cell cultures were collected daily and stored at 80 ºC for viral RNA detection. The RNA template for qRT-PCR standard curve of NEGV and DEZV were produced by Takara In Vitro Transcription T7 kit and the designed primers (STable 4).
## Phylogenetic analysis, geographical distribution, and host diversity of Negevirus
RNA-dependent RNA polymerase (RdRp) sequences from both DEZV and NEGLV were predicted using NCBI's Conserved Domain Search ( h t t p s : / / w w w . n c b i . n l m . n i h . g o v / S t r u c t u r e / c d d / w r p s b . c g i). Subsequently, a maximum likelihood phylogenetic tree was constructed using the complete RdRp coding regions of: (1) selected Negevirus isolates, and (2) representative members of two phylogenetically related plant virus families (Kitaviridae and Virgaviridae). Phylogenetic analysis was performed in PhyloSuite v1.2.3 [29] with 1,000 standard bootstrap replicates. Trees were visualized and edited using Normal tree visualization software [28].
All available virus entries classified under the taxon "Negevirus" were retrieved from the NCBI Virus database ( h t t p s : / / w w w . n c b i . n l m . n i h . g o v / l a b s / v i r u s /) as of January 17, 2025. The initial dataset was then processed to remove redundant entries. Specifically, duplicated sequences were filtered out to ensure that each unique virus isolate was represented only once. Subsequently, the curated, non-redundant dataset was used to extract the associated metadata, which primarily included the country/region of discovery and the host organism for each virus. Sankey diagrams for distribution and host diversity analyses were generated using Origin 2024b.
## Results
## Virus isolation and morphology
Following the inoculation of C6/36 cells, three wells containing Aedes vexans homogenate and thirteen containing Culex pipiens homogenate tested positive for DEZV and NEGLV, respectively. From these, one strain of each virus was successfully isolated: the DEZV/XJ23-420-01 from a pool of Aedes vexans collected upstream of the Burgen River (near Takshiken Port, Xinjiang), in July 2023, and the NEGLV/XJ-JH20-91-01 from a pool of Culex pipiens collected in the Ebinur Lake region of Xinjiang, in June 2020. Both DEZV/XJ23-420-01 and NEGLV/XJ-JH20-91-01 induced prominent CPE in C6/36 cells at 2 days post-inoculation (Fig. 1A).
In NEGLV infected C6/36 monolayers, plaques displayed distinct edges and were readily quantifiable. In contrast, DEZV infected cells produced heterogeneous plaques with fuzzy, indistinct boundaries (Fig. 1B), making plaque-based titer determination unreliable. Therefore, titer for DEZV was quantified using the TCID assay. In C6/36 cells, the titer of DEZV can reach 7.9 × 10 7 TCID 50 /mL (equivalent to 8.94 × 10 12 copies/mL) (STable 5) (Spearman, 1908; Kärber, 1931) [15], and NEGLV was 5 × 10 6 PFU/mL (equivalent to 7.07 × 10 13 copies/mL).
In addition, electron microscopy revealed that both purified DEZV and NEGLV particles were exhibited elliptical shape (40-60 nm in diameter), with envelope (Fig. 1C).
## Viral replication in mosquito and vertebrate cell lines
In both C6/36 and Aag2 cells, DEZV/XJ23-420-01 and NEGLV/XJ-JH20-91-01 infection induced extensive CPE within 2 d.p.i whether low or high doses (Fig. 2A, 2B, 2D, and2E). Viral RNA copies in infected C6/36 cells increased rapidly by 1 d.p.i, reaching concentrations ≥ 10 8 copies/mL. In contrast, no significant CPE was observed in any vertebrate cell lines tested (Vero E6, SW13, BHK-21, PK-15) derived from human, monkey, hamster or pig, even at high infection doses (R/C = 10) (Fig. 2C and2 F).
## Viral sequencing and genome structure
The complete genomes of both viruses were obtained through next-generation sequencing (NGS) and rapid amplification of cDNA ends (RACE), and the sequences were deposited in GenBank under accession numbers PP908777 (DEZV/XJ-ALT23-420-01) and PQ493505 (NEGLV/XJ-JH20-91-01). The genome structure was predicted through NCBI Conserved Region Prediction Tool ( h t t p s : / / w w w . n c b i . n l m . n i h . DEZV/XJ-ALT23-420-01 possesses a 9,066 nt singlestranded, positive-sense RNA genome with a poly(A) tail. BLASTn analysis revealed 98.96% nucleotide identity to DEZV strain 8345 (from Germany), with high similarity. DEZV genome contains a 5' UTR of 69 bp and a 3' UTR from 8830 to 9052 bp, followed by a 14-nt poly(A) tail.
## Phylogenetic analysis
A maximum likelihood phylogenetic tree was constructed using the RdRp coding regions of representative members from Negevirus, Virgaviridae, and Kitaviridae, with branch support assessed by 1,000 bootstrap replicates (Fig. 4). The analysis revealed two distinct subgroup of Negevirus, Sandewavirus and Nelorpivirus.
DEZVs belong to Sandewavirus subgroup and formed into two clusters: our DEZV/XJ-ALT23-420-01 and German strain 8345 (WGH58589.1) in one cluster, and FIN/PP-2018/82 (UUV42173.1), Yakutsk_2023
## Geographical distribution and host diversity of Negevirus
Analysis of host diversity and geographic distribution of Negevirus group from all publicly available sequence data from NCBI Virus (data current as of 17 January 2025) revealed global occurrence across all continents except Antarctica. Most sequences (136/168; 81%) originated from mosquitoes, with Culex species representing the highest proportion (68/168; 40.5%). Negevirus members were also detected in other invertebrates including bees, aphids, and flies, and notably in flatworms (Platyhelminthes). Piura virus was the most prevalent viral species in Negevirus group (45/168; 26.8%), detected in multiple mosquito vectors including Culex and Anopheles species (Fig. 5).
## Discussion
Negevirus comprises two subgroups: Sandewavirus and Nelorpivirus. DEZV, classified within Sandewavirus, has been reported in Africa [22], Asia [23], and Europe [1]. In contrast, NEGV/NEGLV belongs to Nelorpivirus and has been detected in North America [27], South America [7], Africa, and Europe [6].
In this study, we report the first isolation of DEZV and NEGLV from mosquitoes in Xinjiang, China. Phylogenetic analysis revealed that DEZV/XJ-ALT23-420-01 clusters with German strain 8345 (98.96% nucleotide identity), while NEGLV/XJ-JH20-91-01 forms a distinct branch with only 79.39% identity to known Negevirus strains, suggesting it represents a novel species. Phenotypically, plaque morphology differed significantly: DEZV produced fuzzy, irregular plaques whereas NEGLV formed distinct plaques with well-defined edges. This observation aligns with our prior report that Tanay virus (same subgroup as DEZV) similarly exhibits fuzzy plaques [30].
Genome of both DEZV/XJ-ALT23-420-01 and NEGLV/XJ-JH20-91-01 contain an SP24 element in the ORF3, which is a putative membrane protein of plant or insect viruses. There are studies revealed the potential evolutionary relationship of Negevirus with two plant virus families (Kitaviridae and Virgaviridae) based on SP24 and CP proteins, suggesting that the plant viruses may have originated from the horizontal transmission of ancient Negevirus viruses that occurred [16]. Negevirus and the mentioned plant viruses may share a common ancestor capable of infecting both insects and plants. In future, identify the host range of Negevirus can help us to answer this evolutionary question.
DEZV/XJ-ALT23-420-01 and NEGLV/XJ-JH20-91-01 demonstrate vertebrate cell-restricted tropism, showing no replication in tested mammalian cell lines. In contrast, both achieve a high viral loads (> 10⁹ copies/ mL) in mosquito cells. Field studies confirm that DEZV naturally persists in multiple mosquito species and can coexist with medically important arbovirus such as Zika virus (ZIKV). Futermore, in vitro the co-infection experiment with Bunyamwera virus (BUNV), and Semliki Forest virus (SFV) showed that DEZV had minimal impact on BUNV or SFV replication [1,22]. Next studies should investigate DEZV or NEGLV co-infection with additional arbovirus, both in cell lines and mosquitoes, to explore their potential impacts on arbovirus transmission.
We explored the distribution and host diversity of Negeviruses based on sequences currently available in the NCBI Virus database-and indicated a higher prevalence in Culex mosquitoes. However, as it does not include sequences that have not yet been published, the presented results may be conservative. Therefore, the true host range and geographical distribution of Negevirues could be broader.
In summary, we isolated two new Negevirus strains, DEZV/XJ-ALT23-420-01 and NEGLV/XJ-JH20-91-01 and further investigated the global Negevirus distribution and host range. These findings expand our knowledge of this viral taxon.
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# Correction for Shao et al., "Polyubiquitination of APOBEC3G Is Essential for Its Degradation by HIV-1 Vif"
Qiujia Shao, Yudi Wang, James Hildreth, Bindong Liu
## Abstract
During figure assembly, the Western blot image for SIVtan Vif was inadvertently duplicated and also placed in the SIVmac Vif panel (panel B). This unintentional oversight has been corrected by inserting the correct SIVmac Vif image, and the densitometry analysis (panel C) has been revised accordingly. We also clarified panel A by adding a dividing line between the different Vifs to prevent any confusion.We sincerely regret this oversight. These clerical errors do not impact the data interpretation or the conclusions of the article.
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# Frontiers Editorial O ce, Frontiers Media SA, Switzerland *CORRESPONDENCE
Gulnaz Ilgekbayeva, © Zanilabdin, Valiyeva This, Makpal Zanilabdin, Bauyrzhan Otarbayev, Raikhan Nissanova, Gulzhan Mussayeva, Shinji Takai, Yasunori Suzuki, Tsutomu Kakuda, Serikzhan Kurman, Yerken Kassymov, Bayan Valiyeva
## Abstract
Integrated molecular and serological survey ofRhodococcus equi in horses from three regions of Kazakhstan.
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# Bat things come in threes: within-host dynamics of herpesvirus triple infection in bats
Samantha Aguillon, Magali Turpin, Gildas Le Minter, Camille Lebarbenchon, Axel Hoarau, Patrick Mavingui, Muriel Dietrich
## Abstract
Co-infections are a common feature of wildlife systems, yet the factors influencing within-host viral dynamics remain largely unclear. In bats, understanding viral community ecology is essential for elucidating shedding patterns and potential drivers of zoonotic spillover risk. In this study, we explore the genetic diversity and within-host dynamics of herpesviruses (HSV) in Mormopterus francoismoutoui, a tropical insectivorous bat endemic to Reunion Island. Over 3 consecutive years, we collec ted saliva samples from seven roosts, including samples from recaptured individuals. Illumina sequencing of HSV PCR-positive samples revealed a high diversity of strains (n = 20), belonging to alpha, beta, and gamma-HSV subfamilies. Co-infection was frequent, with 44% of bats shedding strains from all three subfamilies. While most shedding patterns appeared random across subfamilies, our results suggest that gamma-HSV negatively affects the probability of alpha-HSV co-shedding. We also demonstrated a lower HSV diversity in juveniles as compared to adults, while pregnancy appeared to increase viral diversity-although this requires further confirmation. Longitudinal recaptures revealed an accumulation of multiple HSV latent infections over life, as the probability to be infected with a new subfamily increased with time interval between recaptures. Within-host strain dynamics were highly variable, with 79% of bats either gaining or losing strains, consistent with latency and reactivation mechanisms. This study provides rare empirical insight into the within-host viral ecology of a natural reservoir host and can help uncover complex pathways by which viruses interact.IMPORTANCE Understanding viral dynamics in bats is critical for anticipating and mitigating zoonotic emergence. This study provides rare, longitudinal insight into herpesvirus co-shedding patterns in Mormopterus francoismoutoui, an endemic bat species on Reunion Island. Here, we revealed high strain diversity and frequent multisubfamily shedding, highlighting complex within-host viral ecology, shaped by host age, reproductive status, and infection history. Interactions between viral subfamilies suggest competitive dynamics that may influence shedding. These findings deepen our understanding of viral persistence and reactivation in bats and underscore the need to investigate how environmental and anthropogenic stressors may modulate co-shedding and increase the likelihood of spillover events. KEYWORDS Chiroptera, co-infection, herpesvirus, interaction, tropical island M ultiple infections with distinct virus populations within a single host are com mon in wildlife (1) and can occur either simultaneously (co-infection) or sequen tially (super-infection) (2). Such interactions among co-circulating viruses can modulate viral persistence, replication, and transmission, with implications for host health and pathogen evolution. Within-host interactions may be synergistic, by facilitating genetic exchanges, providing polymerase proteins, and enhancing host immune suppression (3).
Conversely, interactions can be antagonistic, by interfering with replication or trans mission, via resource competition or interferon-mediated immunity (4,5). The intensity of within-host competition is expected to be stronger between closely related parasites due, for example, to overlap in resource use and similarity in the elicited immune recognition profiles (2,6).
Understanding the ecological and functional consequences of within-host viral interactions is particularly important in reservoir species such as bats, which host high diversity of viruses, including many with zoonotic potential. Co-infections are frequent in wild bat populations, with reported prevalence averaging around 42% across multiple studies (7,8). By altering key epidemiologic factors such as host susceptibility and infection duration (9), co-infections could have important consequences for zoonotic spillovers and disease emergence. Understanding how bat viruses may form interactive communities has thus both significant evolutionary and epidemiological implications (7).
Herpesviruses (HSV) are a valuable model for studying within-host viral interactions due to their high prevalence in diverse host species and their capacity to establish infection shaped by latency phases and reactivation mechanisms (10). HSV family includes three subfamilies with different properties. In humans, alpha-herpesviruses (alpha-HSVs) are known for their rapid lytic replication and latency in non-divided cells (neurons), while beta-and gamma-herpesviruses (beta-HSV and gamma-HSV) establish latency in divided cells and have slower replication cycles, which can lead to persistent or chronic infections, especially in individuals with compromised immune systems (11). Moreover, the lytic cycle is the principal mechanism for alpha-and beta-HSVs, while for gamma-HSV, it is the latency that predominates (11). The ability of HSVs to establish chronic infection, with cycles of reactivation, supports large viral population sizes in the host and can lead to genetic diversification (12). These features make HSVs an ideal model for examining how within-host viral diversity is maintained and shaped over time.
In bats, frequent co-infections have already been reported, with multiple HSV strains and between different subfamilies (beta-HSV and gamma-HSV) (13)(14)(15)(16). In contrast, infection with alpha-HSV has only been described in a few bat species and only reported as single infection (17)(18)(19). Our recent work on Reunion free-tailed bat suggests that maternally derived antibody protection to HSV in juveniles wanes rapidly and that higher prevalence in male adult bats may be shaped by sex-specific behavior or physiology. Seasonal variation in HSV shedding has also been observed, with peaks occurring during the austral summer (20). However, most existing studies are based on cross-sectional prevalence data and do not assess how host factors and time shape the structure and turnover of within-host viral communities (21)(22)(23). In vampire bats (Desmodus rotundus) infected with multiple beta-HSV strains, it is suggested that non-competitive strains and latent infections coexist at the population level (21).
In this study, we investigate the genetic diversity and within-host dynamics of HSV in a tropical insectivorous bat, Mormopterus francoismoutoui, endemic to Reunion Island. A recent spatio-temporal study revealed that Reunion free-tailed bats are highly infec ted by HSV (prevalence of 87%, n = 3,981 bats) with probable latency mechanisms, explaining long-term viral shedding in saliva (20). In the present study, we cannot distinguish between co-and super-infection. We therefore use the more neutral term co-shedding to describe the co-detection of multiple HSV strains or subfamilies within individual bats. Using a longitudinal design with recaptured individuals over 3 years, we first tested the influence of individual factors (age, sex, and reproductive status) on viral diversity and potential interactions between the co-shedding HSV subfamilies. Within-host dynamics were then assessed, through the recapture of bats, by estimating the probability of changing shedding status (at the subfamily level) and measuring intra-subfamily diversification of HSV strains over time. By linking within-host processes to host traits and viral ecology, our study aims to shed light on the functional dynamics of co-shedding in a natural reservoir host.
## MATERIALS AND METHODS
## Field sampling
Longitudinal monitoring of M. francoismoutoui in Reunion Island has been ongoing since 2018 (24). Saliva samples used in this study were collected in 2018, 2019, and 2020 in seven roosts and included data from recaptured bats (totaling between four and five capture events over the 3 years investigated here).
Briefly, bat capture was performed during the dusk emergence as fully described in Aguillon et al. (24), by mainly using harp traps (Faunatech Ausbat) and Japanese mist nets (Ecotone). For each individual, we determined the sex visually and reproductively active status was recorded when females were pregnant and lactating, and in males, when they had large testes (see reference 24 for more details). In females, we recorded the development of nipples as M0 for non-visible nipples, M1 for visible nipples, and M2 for inflated nipples (lactating). Bats were classified as adults or juveniles by examining the epiphysis fusion in finger articulations. Juveniles were identified when articulations were unfused, a characteristic clearly visible up to 7 months of age in this bat species. Beyond this age, some older juveniles may have been mistakenly classified as adults, particularly females without developed nipples (M0). A sterile swab (Puritan Medical Products, USA) was carefully introduced in the corner of the lips to sample saliva and then placed in 250 µL of Eagle minimum essential medium. Samples were stored in a cool box in the field before being transferred the same night at -80°C to the laboratory. Finally, we tattooed bats on the right propatagium with an individual alphanumeric code before releasing them in the capture site. Handling of bats was performed using personal protective equipment, and gloves were disinfected between each individual bat and changed regularly, and all the equipment was disinfected between sites as well (see protocol in Aguillon et al. [24]).
## Molecular analysis and bioinformatics
DNA extraction from saliva samples and amplification of a fragment of HSV DNA polymerase (207 bp product) were mainly performed as part of Aguillon et al.'s study (20). A nested PCR was used to target a broad spectrum of HSVs, including alpha, beta, and gamma subfamilies (25). We took a subset of these data (n = 121 PCR-positive samples/3,981 tested bats) and added new samples (processed with the same protocol), to finally include PCR-positive samples from both sexes, from adults and juveniles, from bats in active or non-active reproductive stage, and from bats that have been recaptured several times. This corresponds to three biological periods: putative mating (from April to May, majority of males sampled), pregnancy (from October to December, majority of females sampled), and juvenile weaning (from January to March, majority of juveniles sampled). To prepare samples for Illumina sequencing, the second PCR of the nested protocol was repeated with Illumina adapters. PCR amplicons were then processed following an Illumina MiSeq 250 bp paired-end sequencing method at Macrogen Europe (the Netherlands, Amsterdam), using the Herculase II Fusion DNA polymerase Nextera XT Index V2 library kit.
Raw sequence reads were filtered, cleaned, and trimmed, removing primers and low-quality reads (unexpected length, missing base) using the FROGS 4.0 pipeline (26,27). Clustering of reads into operational taxonomic units (OTUs) was performed using the SWARM algorithm (28) with an aggregation distance of 5%, followed by the removing of chimeras and the filtering of low proportion OTUs (frequency below 0.005%). Resulting OTUs were considered as putative HSV strains, defined by a 5% nucleotide divergence, although no experimental validation was performed to test whether all OTUs represent biologically distinct strains. Finally, these OTUs were checked in GenBank using the Basic Local Alignment Search Tool (29) to verify their HSV identity. We checked for appropri ate sequencing depth per sample by verifying that the percentage of estimated strain diversity covered in each sample ranged between 95% and 100%, using the function depth.cov from the R package hilldiv (30). To assess the completeness of our sampling, we also created accumulation curves of strain diversity in each roost, with 95% confidence levels based on 1,000 bootstraps, using the R package iNEXT (31) (Fig. S1). Strain diversity was measured based on Hill numbers and q = 1, which considers both richness and evenness of taxa.
## Phylogenetic analysis
Taxonomic affiliations of HSV strains into the three subfamilies (alpha-, beta-, and gamma-HSVs) were performed using a Bayesian tree in BEAST v.2.6.4 (32). The tree was built using a Yule model and a Hasegawa, Kishino, Yano (HKY) site model with invariant and gamma distribution (33), after model selection using Bayesian information criterion (BIC) with JModelTest v2. 1.10 (34). We used a reference data set including sequences previously identified as bat-borne alpha-, beta-, and gamma-HSVs, retrieved from GenBank, ensuring to select a wide range of host bat families and a diversity of strains within each HSV subfamily. Sequence alignment was constructed using ClustalW (35) and MUSCLE (36) and then visually checked in CLC sequence Viewer 7.6.1 (Qiagen Aarhus A/S, Aarhus, Denmark). We used a strict molecular clock with a 100 million chain length and sampling every 10 3 steps and a burning of 10%. We ran three analyses and combined log outputs (removing 10% of burning for each output) using LogCombiner v2.6.4 (37). Traces of Markov Chain Monte Carlo were checked for convergence of the posterior using Tracer v1.7.1 (38). We combined tree outputs (removing 10% of burning for each output) to obtain a consensus tree using LogCombiner v2.6.4 (37) and then TreeAnnotator v2.6.4 (39) and finally visualized the consensus tree in FigTree v1.4.4 (40).
## Statistical analyses
To assess the effect of age (juveniles vs adults) and sex on HSV strain diversity, we performed generalized linear mixed models (GLMM) including age and sex (and their interaction) as fixed effects and the bat's ID as a random effect to account for the recapture of some bats. HSV diversity was measured at the strain level, using both the number of strains (modeled as a Poisson distribution, model M1 in Table S1) and Hill numbers (q = 1, modeled as a Gaussian distribution with log link, model M2 in Table S1). The analysis of variance function with χ tests was used to test the statistical significance of explanatory variables (and their interactions) by sequentially removing them from the full models. In addition, to assess strain composition differences between both age classes, we performed a permutational multivariate analysis of variance (PERMANOVA) with 10 3 permutations and visualized results with non-metric multidimensional scaling (NMDS) plot using Bray-Curtis dissimilarity index in FROGS 4.1 (26,27).
In order to evaluate the effect of reproductive status (active vs non-active) on HSV genetic diversity (Hill numbers, q = 1), we used a Gaussian GLMM (with log link) on a subset of data including adult bats during the mating and pregnancy periods. Reproductive status and sex (and their interaction) were included in the model as fixed effects and the bat's ID as a random effect (model M3 in Table S1). We re-ran the model after excluding non-pregnant females without developed nipples (M0) to avoid including potential misclassified female juveniles in this analysis (model M3bis). Finally, to investigate potential interactions between HSV subfamilies, we used binomial GLMMs on adult bats, modeling the presence/absence of each subfamily using a binomial distribution (see models M4, M5, and M6 in Table S1). Models included reproductive status and sex (and their interaction), as well as the two other subfamilies as fixed effects and the bat's ID as a random effect (with the exception of model M5 where bat's ID has been removed because of model failure to converge, and thus, a GLM was used instead).
We investigated within-host dynamics of shedding on a subset of bats (n = 11) that have been recaptured (n = 45 samples). Specifically, we estimated the probability of acquiring or losing HSV subfamilies through time, by fitting a multinomial logistic regression using the multinom function in the nnet package, using the R script from Streicker et al. (41). Conversion status was used as a nominal dependent variable with four levels (no changes, gain, loss, gain, and loss), and we defined the non-changing level as baseline outcome against which to compare other shedding status changes (model M7 in Table S1). Finally, we analyzed the evolution of HSV genetic diversity at the individual level, by plotting the intra-subfamily strain diversity (as Hill number q = 1) over time for each recaptured bat.
All models were constructed and analyzed in RStudio 1.4.1106 (42) using packages dplyr, effects, hilldiv, iNEXT, lme4, ggeffects, ggplot2, and nnet.
## RESULTS AND DISCUSSION
## Diversity and abundance of HSV strains and subfamilies
Based on the analysis of 121 saliva samples, we identified a high diversity of HSVs in M. francoismoutoui, including 20 strains belonging to the three subfamilies (Fig. 1a). A significant proportion of bats were shedding two (41%) and three (44%) subfamilies. Half of the sampled bats harbored between five and eight distinct strains, with a maximum of 15 strains observed in a single host (Fig. 1b; Fig. S2). These findings confirm that HSV co-infections are common in bats (7). To our knowledge, this study provides the first report of an alpha-HSV in an insectivorous bat (43) and documents the occurrence of triple HSV infection (i.e., co-shedding of three distinct HSV subfamilies) within a single bat species.
Beta-HSV was the most abundant (59% of total reads, Fig. 1a) and diversified (12 strains, Fig. S3) subfamily in M. francoismoutoui. Our beta-HSV sequences clustered in several groups closely related to viruses previously found in several molossid bat species, including Tadarida brasiliensis, Tadarida teniotis, and Molossus temminckii (Fig. 1c; 16,44). Gamma-HSV sequences (32% of total reads, Fig. 1a) grouped in a single cluster closely related to HSV from the mollosid bat species T. brasiliensis (16). Alpha-HSV sequences, which were the less abundant (9% of total reads, Fig. 1a), also grouped in a single cluster and were different from those previously found in different nectar-feeding and fruit bat species (no alpha-HSV reference sequences were available for comparison). The close genetic relationships with HSV from other members of the Mollosidae family (at least for beta and gamma subfamilies) illustrate the probable evolution of host specificity in bat HSVs (45,46). Low abundance of alpha-HSV could be explained by the distinct speed in lytic cycles and mechanisms of reactivation among subfamilies, which may reduce the probability of detecting alpha-HSV in saliva, due to their rapid lytic replication (11). This is coherent with a modeling study suggesting that active phases are much longer than latency phases for beta-HSV dynamics (22), which could explain the higher abundance and diversity of beta-HSV observed in M. francoismoutoui.
## Host-associated determinants of HSV strain and subfamily diversity
Our results reveal strong age-related patterns in within-host HSV diversity. Juvenile bats exhibited significantly lower strain richness and subfamily diversity compared to adults (model M1: χ² 1 = 20.221, P = 7 e-06 , Table S1; model M2: χ² 1 = 14.118, P = 2 e-04 , Table S1) (Fig. 2a; Fig. S4a). This pattern was further confirmed by differences in strain composition (PERMANOVA: F = 0.03, P < 0.01), with reduced diversity observed in juveniles (Fig. 2b). Indeed, the majority of juveniles (eight of nine) were shedding only one HSV subfamily (beta-or gamma-HSV, Fig. S4b) and a reduced mean number of strains (predicted mean = 2.51, Fig. 2a). Only one juvenile was shedding the three subfamilies (Fig. S4b). In comparison, almost half of adults were shedding the three subfamilies simultaneously (52 over 112, Fig. S4b) and a higher number of strains (predicted mean = 6.44, Fig. 2a). Interestingly, Griffiths et al. (21) did not find an effect of age on the number of HSV strains in D. rotundus. This contrasting result could be due to species-specific differences, or because our juvenile class was restricted to newborns up to 4-month-old bats, while Griffiths et al. ( 21) also included subadults. These subadult bats had probably been exposed to a higher HSV diversity, supported by a previous study on M. francoismoutoui from the same population and sampling years (our data set representing a subset), which showed that juveniles get infected rapidly (20). Thus, in addition to reduced HSV prevalence previously reported in juvenile bats (e.g., 13,47), including in M. francoismou toui (20), our findings revealed a reduced genetic HSV diversity in young juveniles, as compared to adult bats. This supports the hypothesis that maternal antibodies provide early protection, followed by multiple latent HSV infections accumulating over the bat's lifespan. S1). (b) NMDS plot of HSV strain composition according to bat's age. (c) Predicted strain diversity (Hill number, q = 1) according to sex and reproductive status of adult bats (model M3, Table S1). For females, strain diversity was also modeled after excluding non-pregnant females without visible nipples (M0) to avoid including potential misclassified female juveniles (model M3bis, Table S1). In adult bats, we did not detect a global effect of sex on HSV strain diversity (model M3: χ² 1 = 2.279, P = 0.131; Table S1). This is consistent with a recent study on D. rotundus (21), although others have shown that sex effect may be variable among bat species (48). However, we observed a positive effect of the reproductive status, dependent on the sex (model M3: χ² 1 = 9.186, P = 0.002; Table S1), as pregnant adult females were shedding a significantly higher HSV diversity compared to the non-pregnant ones (Fig. 2c). A similar pattern has been found in Puerto Rican bats (48), which suggests that reactivation of HSV shedding during pregnancy leads to a diversification of the within-host viral community. However, when excluding non-pregnant females with non-visible nipples (M0), the predicted strain diversity in non-reproductively active adult females increased, and the interaction between sex and reproductive status was no longer observed (model M3bis: χ² 1 = 3.668, P = 0.055; Table S1). This suggests that the pregnancy effect we detected in adult females may be more related to the age of bats, as some non-pregnant M0 females, classified as adults, could in fact be old juveniles (about 11 months old) that were still shedding a lower HSV diversity than true adults.
Across all sampled bats, alpha-HSV, beta-HSV, and gamma-HSV were detected in 63.6 ± 8.6%, 90.9 ± 5.1 %, and 73.6 ± 7.9% of individuals, respectively. When examining potential interactions among HSV subfamilies, we found no evidence for inhibitory effects of alpha-or gamma-HSV on beta-HSV co-shedding. Indeed, the prevalence of beta-HSV was not influenced by the co-occurrence of alpha-HSV (model M5: χ² 1 = 3.389, P = 0.066; Table S1) and gamma-HSV (model M5: χ² 1 = 1 e-05 , P = 0.997; Table S1). This indicates that patterns of co-shedding between beta-HSV and the two other subfamilies were random, supporting low levels of cross-protective immunity for these pairwise HSV combinations (21). However, adult bats shedding gamma-HSV had less probability to shed alpha-HSV at the same time (model M4: χ 1 = 4.137, P = 0.042; Table S1) (Fig. 3a). Such negative interaction has already been reported in bats but only for HSV strains within the beta-subfamily (49). Further functional investigations on the infection mechanisms of HSV in bats are needed to explore factors leading to these subfamily-specific interaction patterns.
## Within-host dynamics of HSV
Recapture data from 11 adult males over intervals ranging from 25 to 702 days revealed high temporal variability in within-host viral communities. Among them, only two were initially HSV-negative (including one being juvenile at the first capture), and all were then systematically shedding over recapture events. For the majority of individuals (52.86%), bats were shedding the same HSV subfamily over recapture events, although the gain of one or two subfamilies was also largely observed (38.57%). Therefore, we reported few losses or gain/loss events (8.57%). The different categories of transition in HSV shedding status had a different probability to occur over time (model M7: χ² 3 = 16.06, P < 0.001). Indeed, the probability that bats acquire a new HSV subfamily increased over time (Fig. 3b), while the probability to lose or gain/lose was low and stable over time (Fig. S5). These findings are consistent with the biology of HSVs, known for their capacity to establish long-term latency with intermittent reactivation. These results also support that HSV establishes latent infection in bats, as suggested by previous results on prevalence data with bats remaining positive through time (20,22).
At the HSV subfamily level, investigation of within-host evolution of genetic diversity revealed highly dynamic strain acquisition/release processes (Fig. S6). Indeed, 78.57% of bats both gained and lost strains between captures, and 14.29% of bats only gained strains over time. These frequent shifts are consistent with long-term HSV persistence and may be the result of latency phases and lytic reactivation (21), although it does not exclude the occurrence of clearance processes as well.
## Conclusion
Our work illustrates that HSVs provide an original study system to analyze within-host viral community dynamics in wildlife. The widespread occurrence of triple HSV infections
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# Correction: Antibacterial effects of coniferyl alcohol-derived dehydrogenation polymer on chlamydial infection in vitro
Anna Pfundner, Tamara Weinmayer, Nora Geissler, Ana Kovacevic, Dragica Spasojevic, Ksenija Radotic, Marijana Stojanovic, Irma Schabussova, Ursula Wiedermann, Aleksandra Inic-Kanada
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# Enterovirus 71 infection induces pyroptotic brain injury via synergistic activation of classical inflammasome and viral gasdermin D cleavage
Tianrun Liu, Baixin Wang, Yingyu Li, Shuming Tian, Xinlong Gao, Yuhan Fan, Xiaomeng Zhang, Limin Yang, Rui Wu, Lei Liu
## Abstract
Enterovirus 71 (EV71) is a viral pathogen responsible for causing hand, foot, and mouth disease, which can lead to severe neurological complications. This study aims to elucidate the pyroptosis mechanism underlying brain injury induced by EV71 infection. EV71-infected BALB/c suckling mice exhibited characteristic symptoms, including weight loss, lethargy, and limb weakness. Notably, elevated levels of the inflammatory proteins IL-1β and IL-18 were detected in the brain tissue of the infected mice. Research findings indicate that EV71 infection activates the NLRP3 inflammasome, resulting in an increased release of IL-1β and IL-18. Furthermore, upregulation of the expression of Caspase-1, Caspase-11, and the pyroptosis-related protein GSDMD was observed in the context of EV71 infection. Importantly, the administration of inhibi tors targeting Caspase-1 and Caspase-11 led to the downregulation of these protein expression levels and simultaneously reduced the severity of the inflammatory response in the brain tissue. These results highlight the critical regulatory role and cross-talk between Caspase-1 and Caspase-11 in EV71-induced brain injury, which involves inflammatory responses and pyroptosis. The significance of these findings enhances our understanding of the pathogenic mechanisms associated with EV71 infection and offers valuable insights for the development of new therapeutic strategies. IMPORTANCE This study elucidated the molecular mechanism underlying pyropto sis-mediated brain injury during EV71 infection in hand, foot, and mouth disease (HFMD), addressing a critical knowledge gap in neuroinflammatory pathogenesis. Using a BALB/c suckling mouse model, we demonstrated that EV71 infection induced a significant upregulation of the pro-inflammatory cytokines IL-1β and IL-18 in brain tissues. Mechanistically, the activation of the caspase-1/11-GSDMD axis was confirmed via Western blot analysis, which revealed an increase in cleaved GSDMD levels in the presence of EV71, indicating a definitive link between the virus and pyroptotic cell death, as supported by studies on GSDME's role in EV71-induced cell pyroptosis. Specific inhibitors targeting caspase-1/11 have been shown to effectively suppress protein expression, reduce neuroinflammatory markers, and improve survival rates, as demonstrated in studies involving acute pancreatitis, EAE, and non-canonical cell death. These findings not only advance the understanding of EV71 neuropathogenesis but also identify caspase-1/11 as promising therapeutic targets for mitigating HFMD-associated brain injury.
KEYWORDS Enterovirus 71, pyroptosis, inflammasomeE nterovirus 71 (EV71), a member of the Enterovirus genus within the Picornaviridae family, is a single-stranded positive-sense RNA virus with a genome length of approximately 7.5 kb (1). As a significant human pathogen, EV71 is well recognized as
a major etiological agent of hand, foot, and mouth disease (HFMD). While most HFMD cases caused by EV71 follow a self-limiting clinical course, severe complications (such as neurological disorders) can occur in some instances, highlighting its clinical relevance (2). However, it is crucial not to underestimate the potential for severe neurological complications linked to EV71 infection. The virus spreads through gastrointestinal and respiratory routes as well as via direct contact (3). EV71 is identified as the primary virus triggering neurological complications, such as neurogenic pulmonary edema, brainstem encephalitis, aseptic meningitis, and acute flaccid paralysis, particularly threatening the health of children (4,5). Currently, no specific drug or clinically proven effective treatment for HFMD caused by EV71 exists. Commonly employed treatment methods include symptomatic approaches, such as glucocorticoids and antibiotics (6).
Understanding the dynamics of the inflammatory response during EV71 infection is crucial for effective treatment. In the early stages of EV71 infection, the host initiates pyroptosis via an inflammatory response, a process that inhibits virus replication by activating Gasdermin D (GSDMD). Cleavage of GSDMD by Caspase-1 dimers follow ing inflammasome activation increases cell membrane permeability, leading to cell pyroptosis-an event that not only disrupts the virus's replication site (as cell lysis inherently impairs viral replication niches) but also directly lowers progeny virus yield due to the loss of viable host cells required for viral propagation (7)(8)(9). However, as the EV71 infection progresses, the inflammatory-triggered pyroptosis can overwhelm the host's compensatory capacity, causing damage to the host's tissues and organs.
In severe cases, it can lead to death. This parallels the pattern seen in conditions like COVID-19, where an excessive inflammatory response can lead to acute respira tory distress syndrome (ARDS). ARDS does not result directly from viral replication or infection, but rather from an immune system overreaction and an imbalance in inflammation triggered by the viral infection (10). During the immune response, the virus can co-evolve with the host, employing various mechanisms to regulate the inflammatory response. This adaptability allows the virus to develop in ways that evade the host cell's defense mechanisms (11,12). For instance, SARS-CoV-2, the virus that causes COVID-19, employs a variety of strategies to evade the immune system, including the manipulation of the innate immune response by reducing interferon (IFN) levels, as detailed in recent research. Patients with mild or moderate COVID-19 exhibit low levels of type I and type III IFNs in their sera (13). These findings highlight the significance of a dynamically balanced inflammatory response in the body, which exhibits antiviral properties. However, the specific mechanisms governing this delicate balance during EV71 infection remain unclear and warrant further investigation.
The activation of pyroptosis involves two distinct pathways: the classic pathway, dependent on Caspase-1, and the non-canonical pathway, dependent on Caspase-11, driven by different inflammatory caspases (14). In the classic pathway, Caspase-1 activation leads to the secretion of pro-inflammatory cytokines, including IL-1β and IL-18, into the extracellular space, thereby intensifying the inflammatory response (15). Caspase-1 specifically cleaves Gasdermin-D, releasing its N-terminal domain (16). The released N-terminal domain of Gasdermin-D binds to phospholipid molecules on the cell membrane, forming pores. These pores disrupt the osmotic balance of the cell, leading to swelling and the eventual rupture of the cell membrane, which results in pyroptotic cell death (17,18). The non-canonical pathway, dependent on Caspase-11, encompasses critical signaling molecules, including Gasdermin-D, Caspase-1, IL-1β, and IL-18. Upon stimulation by viral and other signals, activated Caspase-11 mediates cleavage of Gasdermin-D, thereby generating its N-terminal effector domain. This cleavage induces perforation and rupture of the cell membrane, releasing cellular contents and trigger ing an inflammatory response. Additionally, activated Caspase-11 can activate NLRP3/ Caspase-1, leading to the cleavage of IL-1β and IL-18 and further initiating an inflammatory response (19,20). These pathways elucidate the complex mechanisms through which Caspase-1 and Caspase-11 orchestrate pyroptosis, emphasizing their critical roles in the secretion of pro-inflammatory cytokines and the induction of cell membrane rupture, inflammatory cytokines, and inducing cell membrane disruption, ultimately contributing to the inflammatory response.
In the context of EV71 virus infection, the inflammatory response is pivotal not only to clearing the virus but also in preventing extensive tissue damage, as evidenced by studies linking EV71 to systemic inflammatory response syndrome (SIRS) and its potential to cause severe complications. Regulation of inflammatory signaling pathways is critical to maintaining the balance and stability of the host's internal environment (21). To investigate the pathogenesis of EV71-induced brain injury, we established an EV71 infection mouse model with Caspase-1/Caspase-11 blockade. This model enabled us to examine the interplay between the Caspase-1-dependent canonical pyroptosis pathway and the Caspase-11-dependent non-canonical pathway, offering a novel regulatory perspective to elucidate the immune mechanisms underlying EV71 infection.
## MATERIALS AND METHODS
## Cells and viruses
Human malignant embryonal rhabdomyosarcoma cells (RD) were cultured in DMEM medium (Nissui, Tokyo, Japan) containing the following components: heat-inactivated fetal bovine serum (FBS; Gibco, New York, USA), 100 U/mL penicillin, and 100 µg /mL streptomycin (Gibco, New York, USA). Cells were cultured at 37°C and 5% CO 2 .
EV71 (Genebank serial number: EU703812) virus strain was inoculated in RD cells. The Reed-Muench method was used to calculate the TCID 50 (tissue culture infectious dose 50%) of EV71 virus at 48 h.
## Animals
BALB/c mice weighing 18-22 g in this study were obtained from Changchun Yisi Experimental Animal Technology Co., Ltd. (SCXK (JI)-2020-0002; Changchun, China). Mice were housed in a temperature-controlled room (12 h dark/light cycle, 21-25°C, and 55 ± 5% relative humidity) and were provided with adequate food and water. Before the start of the experiment, the mice were allowed to acclimate to the environment for one week. During this period, BALB/c mice were housed in groups with a 2:1 male-to-female ratio. Pregnant female mice were placed individually in cages to await delivery. EV71 virus concentrate (25 µL/g) was used to infect 1-day-old BALB/c suckling mice via the intraperitoneal (ip) route, and the injections were given continuously for 3 days. Five time points, namely, days 3, 5, 7, 10, and 14, were selected to detect the expression of inflammatory proteins. Four hours prior to infection in suckling mice, the following were administered via ip: VX765 (50 µg/g, Selleckchem, USA) or Wedelolactone (30 µg/g, MCE, USA), both dissolved and diluted in DMEM medium; the control group received an equal volume of DMEM (the solvent used for diluting the inhibitors). The experiment on the infection of suckling mice was conducted under Animal Biosafety Level 2 conditions. All animals were managed following the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health, and the Animal Care and Use Committee of Jiamusi University approved all the procedures.
## Antibodies
The main antibodies used in this study were as follows: against mouse EV71 VP-
## Cytopathic effects
RD cells were cultured in DMEM medium containing 2% FBS at 37℃ and 5% CO 2 . When the cells adhered to 80% of the surface and grew to 80% confluence, the cells were rinsed once with PBS, and 100 TCID 50 of EV71 virus was inoculated. The effect of the EV71 virus on the growth status of RD cells was observed at 24 h, 48 h, and 72 h.
## Clinical symptom score
After EV71-infected BALB/c suckling mice, the weight and disease score of the suckling mice were recorded every day. The disease score evaluation method was as follows (Table 1):
## Histopathology
Samples were embedded in paraffin, cut into 4 µm sections, and stained with hematoxy lin and eosin (H&E) for histological evaluation. The sectioned slides were immersed in a hematoxylin staining solution and stained for a specific period to highlight the cell nuclei and other cellular nucleic acid components. The slides were then gently rinsed to remove any excess dye, followed by immersion in eosin staining solution for a specific period to highlight the cytoplasm and cell granules. After rinsing gently, the slides were mounted with neutral resin, and the morphological changes of mouse brain tissue were observed under a microscope.
## Immunofluorescence staining
Tissue samples were mounted on slides in paraffin blocks (4 µm sections), deparaffinized five times in xylene for 15 min each, and rehydrated in an ethanol gradient (95%, 70%, 50%, and 30%). Hydrogen peroxide and 10 mM citrate buffer (pH 6.0) were used for antigen retrieval. Nonspecific peroxidase activity was blocked with 30% bovine serum albumin (BSA) for 30 min. *Cycle 1 (iF488-TSA): *The primary antibody (1:100) was incubated overnight in a wet chamber at 4℃. An enzyme-labeled secondary antibody (1:200) was used, followed by iF488-TSA amplification. *Cycles 2-3 (IF555/iF647-TSA): *(IF555-TSA) and (iF647-TSA) staining were performed by repeating steps 4-6, with a stripping step between cycles. The sections were stained with DAPI, treated with a self-quenching fluorescence agent, and then sealed with an anti-quenching fluorescence mounting agent (Servicebio, Cat.No.: G1226-100T Wuhan, China). The co-localization was quantified using the Pearson correlation coefficient and Mander's overlap in ImageJ.
## Western blot analysis
After the tissue was lysed in radioimmunoprecipitation assay buffer containing a protease inhibitor cocktail for 20 min, the protein mixture was centrifuged at 13,000 rpm for 15 min at 4°C to obtain the supernatant. The supernatant was boiled with a corresponding volume of 5× sodium dodecyl sulfate (SDS) loading buffer, then fractionated by SDS-polyacrylamide gel electrophoresis (SDS-PAGE), and transferred to a polyvinylidene difluoride membrane. After the membrane was blocked with 5% skim milk powder for 1 h at room temperature, the membrane was incubated with primary antibodies (1:1,000) overnight at 4°C, followed by incubation with secondary antibodies (Beyotime) at the corresponding concentration (1:5,000), and finally detected by chemiluminescence.
## Statistical analysis
Experimental data were expressed as mean ± SD from at least three independent experiments. One-way ANOVA was used to compare the three groups, followed by post hoc multiple comparisons using the Student-Newman-Keuls test. The Mantel-Cox log-rank test was used to assess survival rates. P values < 0.05 were considered statisti cally significant.
## RESULTS
## EV71 induces an inflammatory response in the brain tissue of BALB/c suckling mice
Using the Reed-Muench method (22), we determined the 72-hour tissue culture infectious dose (TCID 50 ) of the EV71 virus, with a final value of 10 -4.12 /mL. Following EV71 infection of RD cells, distinct cytopathic effects (CPE) were observed over time. At 24 h post-infection (hpi), RD cells underwent a clear morphological change: they shifted from their typical spindle-like shape to rounded, bead-like structures and appeared in a scattered distribution. As the infection duration extended to 48 and 72 hpi, the proportion of cells exhibiting CPE increased markedly (Fig. S1). This progression was accompanied by pronounced cellular necrosis, and the affected cells eventually detached from the surface of the culture vessel.
Compared with the control, those BALB/c suckling mice infected with EV71 exhibi ted marked neurological deterioration. In the early stages of infection, affected mice showed progressive weight loss, lethargy, hind limb weakness, hunched posture, and decreased fur density (Fig. 1A). As the infection advanced, some mice succumbed during the middle and late stages. Prolonged EV71 infection was associated with persistent body weight loss, which correlated with a time-dependent increase in clinical symptom scores (Fig. 1B). VP1, the major structural and immunodominant capsid protein of EV71, was undetectable in the brain tissue of uninfected mice but was abundantly expressed following infection, with levels peaking on the tenth day post-infection and paralleling viral proliferation. Notably, EV71 infection led to the activation of the NLRP3 inflammasome and the subsequent upregulation of IL-1β and IL-18. The concentrations of IL-1β and IL-18 in brain tissue of infected mice increased significantly throughout infection, also reaching their maximum on day 10 (Fig. 1C). Therefore, brain tissue samples from day 10 post-infection were used for subsequent experiments.
Hematoxylin and eosin (H&E) staining revealed a marked decrease in neuronal density in the brain tissue of BALB/c suckling mice at day 10 following EV71 infection. Numerous neurons exhibited features of necrosis, and the brain parenchyma displayed prominent cribriform lesions, foci of tissue softening (encephalomalacia), neuronal edema, and conspicuous cytoplasmic vacuolation. These pathological changes under score the potent ability of EV71 to elicit inflammatory injury within the central nervous system of suckling mice. Consistent with these findings, Nissl staining demonstrated pronounced neuronal swelling in infected tissues at day 10 post-infection, accompanied by disintegration or dissolution of central Nissl bodies in the cytoplasm. Remnants of Nissl substance were often observed distributed around the periphery of neurons, appearing as a pale or grayish background (Fig. 1D).
## EV71 infection induces selective neuronal pyroptosis in the mouse brain
Quadruple immunofluorescence staining demonstrated a distinct pattern of VP-1 and NeuN co-localization across experimental groups (Fig. 2). Following EV71 infection, the co-localization rates of VP-1, GSDMD, and the neuronal marker NeuN increased significantly (Fig. 2A). By contrast, the co-localization of VP-1 and GSDMD with Myelin (an oligodendrocyte marker, Fig. 2B) and GFAP (an astrocyte marker, Fig. 2C) remained comparatively low. These findings indicate that EV71 infection primarily targets neurons and induces pyroptosis within neuronal populations. Treatment with VX765 and Wedelolactone reduced the extent of VP-1/NeuN/GSDMD co-localization, suggesting that inhibition of Caspase-1 and Caspase-11 pathways can attenuate EV71-induced neuronal pyroptosis. Notably, triple-label analysis further confirmed that the observed co-localization of VP-1, NeuN, and GSDMD within neurons is closely associated with the occurrence of pyroptosis following EV71 infection (Fig. 2A).
## Selective inhibition of Caspase-1 or Caspase-11 attenuates EV71-induced neuroinflammation and brain injury
Treatment with the Caspase-1 inhibitor VX765 and the Caspase-11 inhibitor Wedelolac tone markedly suppressed activation of their respective targets, resulting in a significant reduction in the levels of pro-IL-1β, cleaved IL-1β, and IL-18 in the tissues of EV71-infected suckling mice (Fig. 3). This decrease reflects an effective attenuation of the inflammatory response. Additionally, both VX765 and Wedelolactone led to a substantial reduction in VP-1 expression in the brain tissue of infected mice, accompa nied by significant increases in body weight and lower clinical disease scores (Fig. 4A). Furthermore, these treatments effectively alleviated brain tissue damage in suckling mice. HE staining showed that the treatment with Caspase-1 and Caspase-11 inhibitors significantly alleviated the pathological damage of brain tissue and reduced neuronal necrosis in BALB/c mice infected with EV71. The results of Nissl staining showed that the pathological damage of brain tissue in BALB/c mice induced by EV71 infection was significantly alleviated after treatment with Caspase-1 and Caspase-11 inhibitors, and the swelling of neuronal cells was recovered. Nissl bodies were polygonal, and the nucleus was located in the center (Fig. 4B). Collectively, these findings provide compelling, multi-dimensional evidence that selective inhibition of Caspase-1 and Caspase-11 not only suppresses EV71-induced neuroinflammation in a targeted manner but also exerts robust protective effects on brain tissue, with this dual outcome primarily mediated by blocking the maturation and extracellular release of the pro-inflammatory cytokines IL-1β and IL-18-an effect that disrupts the "viral infection-inflammation-pyroptosis" pathogenic cascade underlying EV71-associated neurological injury.
## Cross-talk between Caspase-1 and Caspase-11 signaling drives pyroptosis during EV71 infection
EV71 infection triggers a robust inflammatory response via the activation of IL-1β and IL-18, which is mediated by two main pyroptotic pathways: the classical Caspase-1dependent pathway and the non-classical Caspase-11-dependent pathway. In brain tissue of EV71-infected suckling mice, we observed a marked upregulation of pro-Cas pase-1, cleaved Caspase-1, pro-Caspase-11, cleaved Caspase-11, and GSDMD. Adminis tration of the Caspase-1 inhibitor VX765 or the Caspase-11 inhibitor Wedelolactone resulted in significant decreases in the expression of these proteins. These results were substantiated by colocalization analyses of Caspase-1, Caspase-11, and GSDMD, which were consistent with the Western blot findings. suppressed Caspase-11 expression and vice versa. In parallel, GSDMD expression in brain tissue was dramatically reduced following inhibition of either pathway (Fig. 5). These findings demonstrate a cross-regulatory interaction between the Caspase-1 and Caspase-11 pathways, indicating that inhibition of one pathway is sufficient to suppress the activity of both, ultimately attenuating pyroptosis. This newly identified reciprocal regulation between the two pathways may represent a critical mechanism for controlling pyroptotic cell death during EV71 infection.
## DISCUSSION
EV71, a significant cause of hand-foot-mouth disease, predominantly impacts children under 5 years of age. While most infections are self-limiting, severe cases can result in neurological complications, such as aseptic meningitis, acute flaccid paralysis, and brainstem encephalitis (6,23). In the present study, a neonatal mouse model of EV71 infection was established, displaying clinically relevant symptoms including weight loss, drowsiness, and limb weakness. Histopathological analysis revealed significant neuronal loss, necrosis, sieve-like softening foci, and dissolution of Nissl bodies, consistent with the clinical neuropathology. EV71 encodes four structural proteins (VP-1, VP-2, VP-3, and VP-4), among which VP-1 plays a pivotal role in immune evasion, viral proliferation, and disease progression (24,25). Our study confirmed increased VP-1 expression in brain tissue following intraperi toneal infection, as demonstrated by Western blot and immunofluorescence analyses, reinforcing the suitability of this model for investigating EV71 neuropathogenesis.
Viral infection triggers a rapid host immune response, characterized primarily by inflammation aimed at containing the spread of the virus (26)(27)(28). In severe infections, excessive activation of signaling pathways leads to a cytokine storm, exacerbating tissue injury (29,30). The inflammasome, particularly the NLRP3 complex, acts as a critical mediator of this response by activating Caspase-1, which in turn processes IL-1β and IL-18-key pro-inflammatory cytokines that drive pyroptotic cell death (31)(32)(33). In our model, EV71 infection resulted in elevated levels of pro-IL-1β, cleaved IL-1β, and IL-18 in brain tissue, peaking on day 10 post-infection. This time point was chosen for mechanis tic studies, as it represented the maximal inflammatory response.
Pyroptosis, a lytic and pro-inflammatory form of cell death, is now recognized as the principal mechanism underlying the secretion of IL-1β and IL-18 in response to microbial infection (34,35). Caspase-1 and Caspase-11 are central mediators of pyroptosis, but they have distinct yet overlapping roles. Caspase-1 directly cleaves pro-IL-1β and pro-IL-18, whereas Caspase-11 is required for non-canonical inflammasome activation and effective pyroptosis in response to certain pathogens, as well as for GSDMD cleavage and pore formation (36,37). EV71 can induce inflammatory responses through multiple pathways. For instance, its structural proteins (e.g., VP1) and non-structural proteins (e.g., 2A and 3C proteases) can activate Toll-like receptors (TLRs) or retinoic acid-inducible gene I (RIG-I)-like receptors (RLRs), thereby triggering NF-κB/MAPK signaling cascades. This activation ultimately leads to the induction of pro-inflammatory cytokines (e.g., TNF-α, IL-6) in an inflammasome-independent manner (38). Although EV71 elicits inflammation via diverse routes, our findings demonstrate that the Caspase-1/Caspase-11-gasdermin D (GSDMD) axis is critical for mediating IL-1β/IL-18-dependent brain injury. This highlights the axis as a promising therapeutic target for EV71-associated neurological complica tions. In subsequent studies, we will further investigate the mechanisms underlying EV71 infection-induced inflammatory responses.
Our results demonstrated that EV71 infection in the brain tissue of neonatal mice significantly upregulated both the pro-forms and cleaved forms of Caspase-1, Caspase-11, and GSDMD. Treatment with specific inhibitors (VX765 for Caspase-1 and Wedelolactone for Caspase-11) reduced these molecular markers and preven ted pyroptotic damage, supporting that EV-A71-driven inflammasome activation and downstream pyroptosis are sensitive to inhibition of either caspase pathway and reinforcing our conclusion regarding their cross-regulation in EV71-mediated injury.
Wedelolactone has activities beyond Caspase-11 inhibition: prior studies indicate it suppresses NF-κB (via inhibiting IκBα phosphorylation/degradation) and modulates kinases such as Akt and MAPKs, which regulate inflammation and may indirectly affect pyroptosis (39). Nevertheless, the molecular mechanism of Caspase-11 activa tion suggests that it is dependent on oligomerization induced by direct LPS bind ing, a critical step independent of NF-κB transcriptional regulation (40). Notably, in this study, Wedelolactone exerted a potent inhibitory effect on Caspase-11, indi rectly suggesting that it acted by interacting directly with Caspase-11 rather than indirectly regulating NF-κB. Future studies should complement NF-κB-related assays (such as IKK/IκBα phosphorylation, nuclear translocation of NF-κB p65) and integrate Caspase-11 knockdown cell models to elucidate whether the potential NF-κB regulation by Wedelolactone contributes to its Caspase-11 inhibition, and how this contributes to the full elucidation of its mechanisms. Specifically, Wedelolactone treatment was associated with reduced cleaved Caspase-11 (mirroring VX765's effect on Caspase-1), along with corresponding decreases in GSDMD (the key pyroptosis executor) and attenuated pyroptotic damage. Importantly, our results demonstrate that pharmacologi cal inhibition of either caspase led to a concomitant reduction in the activation of the other, as evidenced by decreased levels of cleaved Caspase-1, cleaved Caspase-11, and their shared downstream effector, cleaved GSDMD (Fig. 5). This interdependency could be interpreted through several non-mutually exclusive mechanisms. It may reflect an indirect, synergistic relationship within an amplified inflammatory signaling network, where the suppression of one pathway alleviates the overall inflammatory burden, thereby reducing the stimulus for the activation of the other. Alternatively, it might involve more direct, yet uncharacterized, regulatory crosstalk, such as the potential for Caspase-11 to upstream regulate the NLRP3/Caspase-1 axis (41), or the possibility that both pathways converge critically on GSDMD cleavage, creating a positive feedback loop that is disrupted when either arm is inhibited (42). Nevertheless, our findings robustly indicate that the pro-pyroptotic functions of Caspase-1 and Caspase-11 during EV71 infection are highly interdependent, and therapeutic targeting of either pathway can effectively disrupt this synergistic activation loop and mitigate pyroptotic brain injury. Multiplex immunofluorescence further revealed that EV71 preferentially targets neurons rather than glial cells, as indicated by the robust colocalization of VP-1, NeuN, and GSDMD. Conversely, myelin and GFAP showed minimal co-localization, suggesting that glial cells are less susceptible to direct viral invasion, although they may still undergo secondary inflammatory injury. Notably, pharmacological inhibition of Caspase-1 or Caspase-11 reduced neuronal pyroptosis and viral load, resulting in alleviated tissue damage and improved clinical outcomes in infected mice.
Pyroptosis appears to play a dual role in the context of EV71 infection. In the early stage, it can be protective by restricting viral replication and spread (43,44). However, excessive and sustained activation leads to overwhelming inflammation, neuronal loss, and severe neurological complications (10). The interaction between Caspase-1 and Caspase-11 amplifies this process, and disruption of either pathway is sufficient to prevent catastrophic tissue damage.
In summary, this study explored the mechanism of EV71-induced brain injury, focusing on pyroptosis-related pathways. In EV71-infected BALB/c suckling mice, we observed enhanced neuroinflammation (elevated IL-1β/IL-18) and upregulated Caspase-1, Caspase-11, and GSDMD in brain tissues. Pharmacological inhibition of Caspase-1 (VX765) or Caspase-11 (Wedelolactone) reduced pyroptosis-related mole cule activation, IL-1β/IL-18 release, neuronal damage, and improved clinical symptoms. Importantly, our results suggest a potential interactive relationship between Caspase-1 and Caspase-11 during EV71 infection-suppressing one pathway was associated with reduced activation of the other, mitigating pyroptotic brain injury-though the specific nature of this interaction remains unclear.
Future studies will further investigate the regulatory mechanisms underlying Caspase-1/Caspase-11 crosstalk in EV71 infection (e.g., via gene knockout models) to verify and clarify their relationship, which may deepen understanding of EV71-associated neurological pathogenesis and inform targeted therapeutic strategies (Fig. 6).
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# Charting the virosphere: computational synergies of AI and bioinformatics in viral discovery and evolution
Aia Sinno, Ruqaya Baghdadi, Ralph Narch, Serena Rayes, Sima Tokajian, Charbel Al Khoury
## Abstract
The advancement of metagenomic sequencing has revealed a vast viral diversity while simultaneously exposing limitations of homology-based tools such as BLAST and HMMER, which often fail to detect highly divergent viral genomes. The integration of artificial intelligence (AI) into viromics has transformed this land scape, introducing machine learning and deep learning models-including convolu tional neural networks (CNNs), recurrent neural networks (RNNs), and transformersthat extend viral discovery beyond sequence similarity constraints. Structure-based frameworks such as AlphaFold, ESMFold, and Foldseek further enable annotation of divergent viral proteins through conserved 3D folds, while graph neural networks (GNNs) model host-virus interaction and explainable AI enhances interpretability of prediction. Despite their high sensitivity and scalability, AI-driven approaches face notable challenges: computational burden, data set bias, limited explainability, and elevated false discovery rates. This review traces the evolution of computational virology from traditional methods to AI-based and hybrid frameworks. We examine landmark AI tools while underscoring the continuing importance of phylogenetics and functional annotation in contextualizing AI predictions. We propose an integrated workflow that combines AI pattern recognition with classical bioinformatics to enhance both scal ability and interpretability. By addressing the limitations of solely AI-driven or tradi tional approaches, this review presents a unified computational strategy to accelerate viral discovery, enhance evolutionary insights, and strengthen global preparedness for emerging infectious diseases. KEYWORDS virosphere, bioinformatics, artificial intelligence, hybrid workflows D eciphering the full extent of viral diversity remains a central challenge in virology (1, 2). Viral genetic plasticity, underpinned by rapid mutation and adaptive versatil ity, complicates detection, classification, and functional annotation (3, 4). Despite the impact of high-throughput sequencing (HTS) in surveying viral populations, methodo logical constraints continue to impede both resolution and scope (5). Metagenomics, which directly analyzes genetic material from environmental samples, has expanded the catalog of known viral diversity and ameliorated the detection of novel viral taxa across terrestrial, aquatic, and clinical environments (6). However, fundamental challenges persist: distinguishing viral sequences from host and microbial contaminants, the absence of standardized viral taxonomic frameworks, and substantial computa tional demands (7). Reliance on sequence homology-based annotation further limits the detection of novel species with minimal reference genome coverage (8). Artificial intelligence (AI) has assumed a transformative role in viromics. Within this framework lies machine learning (ML), a subset of AI comprising algorithms that autonomously improve performance through data-driven training, while deep learning (DL) represents a further specialized form of ML, distinguished by multilayered neural architectures capable of capturing complex processes (9). Convolutional neural networks (CNNs), recurrent neural
networks (RNNs), and transformer architecture represent the principal DL frameworks employed in viral genomics (9) (Fig. 1A). CNNs have been originally developed for image recognition that apply convolutional filters to capture local patterns and hierarchical features, rendering them highly effective for detecting sequence motifs in biological data (10). RNNs constitute models in which each computational step is conditioned on prior states, granting the architecture the capacity to preserve temporal or sequential dependencies and thus to compute long-range relationships in nucleotide or amino acid sequences (11) (Fig. 1B). Transformer architectures embody a distinct paradigm, employing multi-head self-attention mechanisms to compute pairwise dependencies across all sequence positions in parallel, thereby affording superior efficiency and scalability in the modeling of global context (12) (Fig. 1C). Together, these architectures constitute the foundation of DL approaches that now drive viral sequence identification, host virus interaction prediction, and the reconstruction of evolutionary trajectories (13). In parallel, structure-based AI methods such as AlphaFold, ESMFold, and Foldseek extend this capability into the structural domain, annotating highly divergent viral proteins through conserved 3D folds (14)(15)(16). Unlike traditional similarity-based tools (BLAST and HMMER), these models identify recurring signals in data to infer uncharacterized viral species and support scalable, real-time analysis with minimal reliance on reference genomes (13,17). Beyond sequence-centric architectures, emerging models such as graph neural networks (GNNs) capture relational information, supporting inference of host-virus interactions and ecological associations through graph-structured data (18) (Fig. 1D).
Building on these computational advances, this review traces the evolution of viral bioinformatics from early metagenomic methods to contemporary AI-driven approaches. We evaluate traditional and AI-based tools, highlighting issues of interpreta bility, false discovery, and reproducibility. We explore emerging frameworks for explaina ble AI (XAI) and multi-omics integration, emphasizing the complementary strengths of AI and traditional bioinformatics. Hybrid workflows integrating both approaches will be essential to achieve scalability without sacrificing evolutionary insight or mechanistic understanding, ultimately augmenting the accuracy, scope, and depth of viral diversity analysis beyond current capabilities.
## THE EVOLUTION OF VIRAL DISCOVERY
## Metagenomics: classical paradigms in viral discovery
For much of the 20th century, virology relied on culture-dependent methodologies, necessitating viral replication within host cells. Electron microscopy and serological assays facilitated morphological and antigenic characterization (19), yet these techni ques were inherently biased toward cultivable viruses, leaving large portions of the virosphere unexplored. The absence of molecular tools to investigate divergent taxa further limited detection and phylogenetic insight, rendering early viral discovery laborintensive, low-throughput, and constrained in scope (20,21). The advent of molecular sequencing in the 1990s, exemplified by BLAST for HTS comparison and phylogenetic inference, marked the beginning of a paradigm shift (22). These advances culminated in the 21st century with a paramount transition: previously unknown viral genomes became accessible directly from clinical samples, circumventing the necessity for viral cultivation. This was illustrated by the identification of human coronavirus HKU1 in nasopharyngeal aspirates through primer-guided Sanger sequencing (23). Early metagenomic efforts employed tools such as Phred, PHRAP, and ClustalW for quality control, assembly, and phylogenetic analysis, revealing unexpected viral diversity within host-associated microbiomes (24)(25)(26). A striking example was the recovery of novel viruses from human feces, including exogenous plant viruses within the human gut (27).
The emergence of HTS platforms marked an instrumental pivotal advancement. Early applications of 454 pyrosequencing revealed seven novel RNA viruses in honeybee colonies affected by Colony Collapse Disorder and enabled the characterization of Lujo virus, the first hemorrhagic fever-associated arenavirus identified in Africa (28,29). Subsequent adoption of Illumina sequencing rapidly eclipsed earlier platforms, owing to its superior base-calling accuracy, depth, and cost-effectiveness (30,31). In parallel, advances in de novo assembly algorithms such as MEGAHIT and SPAdes enabled nearcomplete reconstruction of viral genomes from highly complex metagenomic data sets, thereby extending virome research beyond fragmentary sequence recovery (32,33).
Computational pipelines have been equally transformative, converting raw HTS data into meaningful biological insights. Tools such as DIAMOND, BLASTX, and VirSorter2 enhanced sensitivity in homology-based detection, while taxonomic classifiers such as Kraken2 and Kaiju enabled systematic assignment of sequencing reads to known taxa (34)(35)(36). To reduce host-derived contamination, alignment-based filtering with Bowtie2 or specialized frameworks such as HoCoRT remained an essential preprocessing step (37,38). Yet, despite these advances, highly divergent genomes remain refractory to classification, constituting the vast majority of the virome "dark matter" (39,40). Beyond functional annotation challenges, metagenomic virology demands substantial memory resources and high-throughput processing, prompting the use of cloud-based platforms such as MGnify, IMG/VR, and ViPR for scalable, centralized management of global virome data sets (41)(42)(43).
Despite its constitutive role, metagenomics faces inherent constraints. Its depend ence on reference-based mapping impedes the detection of highly divergent or uncharacterized viruses, even as it remains indispensable for classifying well-character ized taxa. These computational and methodological confinements have prompted the development of complementary strategies that leverage pattern recognition rather than explicit sequence similarity. In this context, AI has emerged as a transformative approach, capable of detecting highly divergent sequences, inferring functional domains de novo, and enabling large-scale automated classification with unprecedented precision. The following sections explore AI's role in advancing virology beyond the constraints of conventional metagenomic methodologies.
## ML-based approaches
ML approaches have redefined the foundations of viromics by adopting predictive models based on intrinsic sequence features rather than homology-based taxono mies (44). Early applications relied on feature-engineered inputs, most notably k-mer frequency distributions, as probabilistic markers to distinguish viral from non-viral sequences. A fundamental contribution in this space was VirFinder, a logistic regres sion model trained on k-mer composition features, which outperformed BLAST-based methods in identifying highly divergent viral genomes, including lineages previously inaccessible to homology-dependent tools (45). By circumventing strict reliance on sequence homology, VirFinder facilitated the discovery of novel viral families, although its dependence on predefined feature spaces limited its generalizability to increasingly diverse virome data sets.
Subsequent efforts demonstrated that ML models need not be restricted to kmer profiles or handcrafted features. Tools such as MarVD2 and GRAViTy exemplify this flexibility, integrating heterogeneous genomic attributes for taxonomic prediction without explicit reliance on k-mers (46,47). Other ML-driven applications extend to viral binning, prophage prediction, and large-scale taxonomic assignment, highlighting the broader adaptability of ML classifiers across virome analysis (48,49). Importantly, ML approaches remain indispensable in specific research contexts. Compared to DL, ML classifiers offer greater interpretability and reduced computational burden, attributes that are particularly advantageous in metagenomic virome surveys and hypothesisdriven virological studies where biological transparency is as critical as predictive accuracy (50). In this respect, ML classifiers should not be viewed merely as historical precursors to DL architectures but as enduringly valuable tools that reconcile predictive performance with biological interpretability.
While ML-based approaches have expanded the analytical toolkit of viromics, they remain constrained by the availability of high-quality, labeled trained data sets, which are themselves derived from incomplete and often taxonomically biased viral reference collections (51). Consequently, these models tend to underperform when confronted with novel or ecologically atypical lineages, confining their capacity for broad gener alization across environments (52). Feature-engineered inputs, such as k-mer frequen cies, further introduce susceptibility to sequencing artifacts and compositional biases, potentially inflating false-positive rates in taxonomic assignments (53). Moreover, the predictive scope of these models frequently diminishes when applied to data sets with divergent nucleotide composition or read-length distributions, necessitating retraining or recalibration. Although ML frameworks are computationally lighter than contempo rary DL architectures, their reliance on handcrafted feature spaces and dataset-spe cific optimization restricts their scalability when deployed across the terabase-scale metagenomic landscapes that increasingly define modern viromics.
## DL FOR SEQUENCE-BASED CLASSIFICATION AND MULTI-OMICS INTEGRATION
DL architectures have fundamentally transformed viral sequence classification by autonomously learning hierarchical genomic features that are inaccessible to traditional bioinformatics and early ML models. Building upon prior ML frameworks, DL mod els construct hierarchical representations, where early layers detect simple sequence patterns, while later layers autonomously capture complex genomic patterns, thereby enabling the detection of evolutionary novel viral genomes (54).
## CNNs: local feature extraction
CNNs have proven indispensable in capturing proximal sequence motifs within genomic data (55). Through repeated scanning operations (convolutions) across defined sequence windows, CNNs progressively extract local features, facilitating the identification of conserved functional motifs and enhancing taxonomic resolution (10). A prominent example of this approach is DeepVirFinder, which employs multi-layered CNNs to detect fine-grained nucleotide patterns, achieving superior sensitivity in identifying highly divergent viral genomes with minimal sequence homology (13). This capability is particularly critical in metagenomic data sets, where conventional similarity-based tools, namely BLAST and HMMER, often fail to detect novel viral taxa.
Deep-sea metagenomic studies further illustrate the effectiveness of CNN-based approaches. Zhang et al. (56), building on the CNN framework from VirFinder, identi fied 85,059 viral operational taxonomic units (vOTUs)-the largest catalog of viral taxa reported to date. Eminently, 98.28% of these vOTUs remained unclassified, underscor ing the vast extent of viromic "dark matter" and affirming the power of AI-driven approaches to uncover previously unrecognized viral diversity (56). Such findings reveal the effectiveness of CNNs to detect novel viral lineages, particularly within extremophilic environments, such as deep-sea hydrothermal vents, hypersaline lakes, and permafrost, where viral diversity remains largely unexplored.
Despite these strengths, CNNs are inherently limited in modeling long-range dependencies due to their filters focusing only on small regions of a sequence at a time-a property known as the receptive field-and reliance on fixed-size convolutional filters (57). This obstruction is particularly consequential in viral genomes, wherein functional regulation and RNA structures often depend on distal interactions spanning thousands of nucleotides. Coronaviruses exemplify this phenomenon, where long-range RNA-RNA interactions between the 5′ and 3′ untranslated regions play indispensable roles in viral replication and transcription (58,59). Similarly, in retroviruses such as HIV-1, programmed ribosomal frameshifting is governed by structural and sequence elements separated by extensive nucleotide distances, mandating accurate modeling of distal dependencies (60).
Computational studies have explored strategies to address these limitations. Gupta and Rush (61) demonstrated that a modification called dilated convolutions markedly enlarged the receptive field while circumventing excessive parameter growth, markedly ameliorating the capture of distal genomic dependencies. More broadly, Eraslan et al. (54) emphasized that CNNs excel at proximal motif discovery but struggle to capture higher-order or distant positions in a sequence-so-called long-range dependencies, which instead require hybrid or attention-based architectures. A notable example is the DanQ model, which combines CNNs for local feature extraction with RNNs to integrate sequence-wide context, surpassing convolutional models in regulatory genomics tasks (57).
## RNNs and LSTM: sequential modeling
Building upon CNN architectures and mitigating their limitations, RNNs, particularly their advanced variant, Long Short-Term Memory (LSTM) models, emerged as a potent construct for capturing long-range sequential dependencies within complex viral genomes (62). While CNNs excel at detecting localized sequence features, RNNs process genomic data as continuous streams, enabling the capture of sequence-level variations across entire viral genomes (63). This sequential modeling is particularly important for classifying viruses with noncanonical genome architectures, where nonlinear configurations necessitate computational approaches capable of preserving long-range depend encies across extensive nucleotide spans. An early implementation of this approach, RNN-VirSeeker, leverages LSTM networks to model these long-range relationships, overcoming the structural and contextual fragmentation that often limits CNN perform ance when classifying highly mutational and discontinuous viral genomes (64). LSTM architectures progressively curtail the vanishing gradient problem-a training limita tion where simpler models gradually lose long-term information-thereby allowing the retention and propagation of critical evolutionary and structural information throughout the learning process.
The hierarchical design of this model has led to significant advancements in viral bioinformatics, particularly in three key areas: (i) retaining essential sequence informa tion over long genomic distances, enabling the identification of highly mutagenic viral taxa; (ii) characterizing genome-wide structural variations, which is critical for understanding viral recombination, antigenic drift, and host-specific adaptation; and (iii) improving recall accuracy for truncated viral contigs (<500 bp), where conventional CNN-based models often struggle due to the fragmented nature of metagenomic reads. Benchmarking studies have consistently demonstrated the superior performance of RNN-VirSeeker compared to its predecessor, VirFinder, establishing it as a leading AI-based model for the classification of truncated viral genomes (64). These findings highlight the importance of modeling temporal dependencies in viromic taxonomic classification, reinforcing the critical role of DL architectures in resolving the complexity of viral genome evolution and phylogenetic diversity.
The ongoing advancement of DL is expected to give rise to hybrid architectures in which CNNs and RNNs are complemented by attention-based or transformer mod ules, enabling the extraction of local motifs, sequence-wide dependencies, and global contextual relationships within viral genomes (65). Rather than supplanting CNNs or RNNs, these transformer-enhanced architectures build upon the strengths of existing models, integrating specialized modules for motif detection, sequential modeling, and long-range contextual inference (66). As metagenomic research continues to expand our understanding of the global virosphere, AI-driven tools are set to play a central role in pandemic forecasting, antiviral drug discovery, and tracking viral transmission, making them key elements of modern bioinformatics and computational virology.
## Transformer-based AI models: genome-wide contextual encoding
Transformer-based architectures represent a pivotal advancement in computational virology, overcoming the inherent limitations of CNNs and RNNs while complement ing their specialized capabilities by enabling comprehensive, genome-wide contex tual encoding with unparalleled efficiency and accuracy (67). Leveraging multi-head self-attention mechanisms, transformers capture long-range dependencies across viral genomes, permitting tasks such as viral taxonomy, host-virus interaction prediction, and the functional annotation of novel viral taxa (12). These competencies are particularly valuable in metagenomic virome analysis, where traditional classifiers often struggle to resolve fragmented genomes, disambiguate highly divergent lineages, or distinguish viral sequences from microbial contaminants. Unlike RNNs, which analyze sequences step by step, transformers employ parallel computation across all sequence positions at once, rendering them faster for large data sets (68). However, this advantage does not eliminate their considerable computational burden, which remains a critical bottleneck for applications such as AlphaFold2 and large-scale viromics studies (69,70).
At the forefront of transformer-based advances is LucaProt (2023), trained on an extensive 51-terabase metagenomic sequencing data sets and identified 161,979 novel virus species (12). Its innovation lies not in incremental performance metrics but in methodological shifts: utilizing self-supervised learning, where the model discovers patterns directly from raw data without the need for manual labeling; integrating proteomic sequences with structural topology; and eliminating reliance on manually aligned data sets (12). These features allow LucaProt to infer evolutionary lineages, detect cryptic homologous sequences, and annotate functional domains such as RNA-dependent RNA polymerase (RdRp) domains (12).
Beyond taxonomic classification, transformers have become central to hybrid AI-virology pipelines, supporting real-time surveillance, high-resolution epidemiologi cal forecasting, and mechanistic reconstruction of host-virus interactions (71). The integration with multi-omics technologies (metatranscriptomics, proteomics, and epitranscriptomics) enables functional characterization of viral genes, identification of novel RNA modifications, and prediction of host-viral interaction, thereby revealing the molecular underpinnings of viral evolution and cross-species transmission (Fig. 2). Transformers complement existing CNN and RNN modules, allowing hybrid pipelines to combine local motif detection, sequential modeling, and genome-wide attention for maximal analytical resolution.
Notwithstanding their transformative potential, transformer-based architectures are not without critical challenges. Their effectiveness is predicated upon access to massive training corpora-often measured in terabases of sequence data-which not only sustains prohibitive computational and financial costs but also risks embedding datasetspecific biases that skew downstream inference (72). These models, while offering unparalleled parallelization and scalability in principle, remain computationally intensive in practice, demanding high-performance GPU or TPU infrastructures that are inaccessi ble to many laboratories (72). Furthermore, the interpretability of transformer outputs remains limited; their self-attention mechanisms, though powerful, often operate as opaque black boxes (BBs), complicating efforts to trace predictive outcomes to biologi cally meaningful features (73). These constraints underscore a paradox intrinsic to transformers: while they scale efficiently to large data sets, their development and deployment are resource-intensive, and their predictions frequently necessitate comple mentary validation through phylogenetic or structural benchmarks to ensure biological plausibility.
While the sequence-based methods continue to dominate virological discovery, they capture only parts of AI's transformative impact; in parallel, a structural revolution, led by AlphaFold and its successors, has redefined protein fold prediction and extended viral annotation into the 3D domain.
## Structure-based AI in viromics: the rise of AlphaFold and successors
Structure-based AI has revolutionized protein conformation prediction, offering an orthogonal lens for functional inference in protein biology. Three key tools exemplify this shift: AlphaFold, which pioneered near-experimental accuracy in protein structure prediction from sequence alone (14); ESMFold, which scales this capability across millions of sequences using transformer-based language models (15); and Foldseek, which enables ultra-fast structural comparisons at the proteome scale (16). In viromics, these advances are particularly impactful as divergent viruses often evade detection due to minimal sequence similarity with known taxa. Yet, their encoded proteins frequently retain conserved structural scaffolds, such as the canonical folds of RdRp, helicases, and capsid proteins, that remain detectable through AI-driven structure prediction (74). This structural anchoring enables functional annotation and taxonomic placement of proteins that would otherwise remain uncharacterized. Already, such approaches have revealed previously unrecognized viral clades and expanded the known evolutionary diversity of RNA viruses.
Beyond taxonomy, structure-based AI unlocks mechanistic insights inaccessible to sequence-based methods. Predicted receptor-binding domains can offer early indicators of zoonotic potential, while structural reconstructions of polymerase active sites inform antiviral drug design (75,76). Crucially, ESMFold's capacity to scale across terabasescale metagenomic data sets, combined with Foldseek's rapid search capabilities, now makes it feasible to embed structure-based annotation into real-time viral surveillance pipelines-transforming how we interpret, classify, and respond to the virosphere. As these increasingly powerful models redefine viral discovery, an equally pressing challenge arises: ensuring that their predictions are interpretable, reproducible, and ethically accountable, a task addressed by XAI.
## XAI and ethical imperative in viromics
As structure-based AI tools become increasingly central to virological research, so too must our capacity to interrogate the rationale behind their predictions. This imperative has catalyzed the emergence of XAI, a set of frameworks designed to render DL models transparent, interpretable, and biologically trustworthy (77). While complex neural architectures have demonstrated remarkable predictive power, they often produce outputs devoid of explicit reasoning. This lack of interpretability can erode confidence in their biological validity-particularly in viromics, where such models are applied to taxonomic classification, virus discovery, and cross-species transmission analysis. In such contexts, opaque predictions risk misinterpretation and hinder downstream utility.
XAI addresses this challenge across multiple strata of model architecture. At the input level, attribution methods such as integrated gradients, DeepLIFT, and SHAP quantify the contribution of individual nucleotides or amino acids to a given prediction (78)(79)(80). Within intermediate layers, attention visualization and saliency mapping reveal which genomic or structural regions are emphasized during inference (81). At the decision layer, surrogate models and rule-extraction techniques distill complex outputs into simplified human-readable logic approximations (82). These interpretability tools not only clarify model behavior but also support error detection, hypothesis generation, and generaliza bility. For instance, feature attribution may expose overreliance on sequencing artifacts or dataset-specific biases; attention heatmaps can highlight previously uncharacterized genomic regions warranting functional investigation; and transparency in model focus helps ensure that insights generalize across data sets rather than reflect overfitting.
The ethical dimension of interpretability is equally critical. When AI-derived predic tions inform public health policy or real-time surveillance, stakeholders must be able to audit and reproduce results with confidence in their biological plausibility. Emerging XAI paradigms further extend interpretive capacity. Prototype-based networks and concept bottleneck models explicitly link internal representations to known viral functions (44), while counterfactual explanations reveal how perturbations to sequence or structure alter model outputs (83). Multimodal XAI approaches, which integrate sequence, structure, and host-interaction data, offer a more holistic interpretive framework suited to the complexity of viral systems (84). For XAI to fulfill its promise, however, the field must establish community standards and benchmark data sets for interpretabil ity, enabling rigorous cross-comparison and fostering trust among laboratories and applications.
With these explainability frameworks in place, AI models evolve from opaque predictors to interpretable systems-laying the groundwork for more advanced relational modeling. GNNs, which capture host-virus interactions and ecological relationships, represent a natural extension of this trajectory. Their integration of multi-omics and structural data benefits equally from the transparency afforded by XAI, enabling biologically grounded inference at network scale.
## GNNs: multi-omics and relational modeling
To overcome the limitations of feature-engineered models, GNNs, which treat viral and host data as networks of nodes and connections rather than isolated sequences, have emerged to capture the relational architecture of viral ecosystems. GNNs, with PhaGCN as a prominent exemplar, enable systems-level interpretation of the virome by leverag ing graph-theoretic embeddings-vector representations that capture viral and host features to model their relationships beyond the analytical scope of sequence-centric classifiers (85). Departing from conventional classifiers that evaluate viral sequences in isolation, GNNs embed viral genomes, host-derived sequences, ecological metadata, and taxonomic relationships within network representations. This design permits inference of latent functional associations and ecological interactions within host-virus relationships, thereby surmounting many limitations of linear sequence analysis (85). Such meth odological advances have proven especially valuable for zoonotic surveillance, where predicting cross-species transmission demands models that accommodate recombina tion, episodic host shifts, and the ecological context that obscures simple phylogenetic signals (86). Tools like PhaGCN demonstrate how genomic and ecological features can be integrated to improve host-viral interaction prediction relative to models that rely solely on sequence homology or phylogenetic proximity (85).
Beyond host prediction, GNNs have become instrumental for classifying viral ecological networks within complex metagenomic data sets drawn from marine, soil, and vector-borne communities (67). Applications of PhaGCN in global virome studies have revealed previously undetected host-virus associations across diverse ecosystems, underscoring the ability of graph-structured models to illuminate transmission dynamics and ecological modularity that elude linear sequence methods (85).
Although fully integrated virus-centric GNN pipelines that jointly assimilate viral/ host sequence embeddings with multi-omics layers are still nascent, there is a clear precedent in adjacent biomedical domains. Modality-aware GNN frameworks (MOTGNN) have successfully combined mRNA, miRNA, and DNA-methylation layers via interpretable graph embeddings to augment classification and biomarker discovery, demonstrating the technical feasibility of multi-omics + GNN integration (87). These methodological precedents provide a ready blueprint for analogous viromics efforts, where transcrip tomics, proteomics, and epitranscriptomics could be fused with sequence-derived embeddings to enhance host-specificity prediction, zoonotic risk scoring, and functional annotation.
Looking forward, GNNs, especially when complemented with transformer-derived sequences and other deep representations, promise to sharpen host-specificity prediction, reveal ecological drivers of transmission, and resolve phylogenetic connec tivity across the expanding virosphere. As metagenomic and multi-omics data sets continue to grow, graph-based DL will become an increasingly indispensable component of systems-level viromics, complementing sequence-based DL models and enabling richer inference of viral evolution and epidemiological emergence.
## BRIDGING AI AND TRADITIONAL BIOINFORMATICS IN VIROMICS: HYBRID WORKFLOWS
AI-driven methods and traditional bioinformatics constitute a scalable and groun ded framework as complementary components of integrated workflows. AI excels at detecting highly divergent viral sequences in large-scale metagenomic data sets, while traditional bioinformatics provides the evolutionary context needed to validate and interpret these validations (Table 1). A representative example is LucaProt, which has demonstrated the capacity to recover highly divergent RNA viruses from complex environmental metagenomes, revealing lineages inaccessible to conventional work flows (12,88). However, without rigorous phylogenetic reconstruction, the taxonomic classification of such sequences remains conjectural. Multiple sequence alignment programs (e.g., MAFFT and Clustal Omega) serve as indispensable preprocessing tools that generate homologous positional matrices for comparative analysis, yet they do not themselves constitute phylogenetic inference (89,90). Evolutionary reconstruc tion must instead be resolved with statistically robust tree-building algorithms, with IQ-TREE emerging as a de facto standard owing to its integrated model selection, likelihood optimization, and branch-support testing (91). Depending on data set scale and analytical practices, alternatives such as RaxML-N, PhyML, or FastTree 2 may be employed (92)(93)(94). Tool selection is also shaped by domain-specific contexts. For example, dedicated frameworks such as VIRIDIC-commonly employed in bacterio phage and archaeal virus taxonomy-provide complementary methodologies aligned with established community standards (95), while network-oriented frameworks such as vConTACT2 and VICTOR are widely used to interrogate complex viral assemblages (96,97).
By integrating AI-based predictions with classical tree-building methods, researchers can trace the evolutionary origins of newly identified viruses, thereby strengthening the accuracy of their taxonomic placement. In this complementary framework, AI functions as a discovery tool, while traditional bioinformatics serves as a taxonomic arbiter indispensable for refinement through phylogenetic inference and evolutionary contextualization (Fig. 3).
## AI AS A CATALYST FOR BIOINFORMATICS EFFICIENCY
A major limitation in conventional viromics lies in the substantial computational burden imposed by similarity-based search algorithms, a challenge amplified by the vast scale of modern metagenomic data sets. AI offers the capability to prioritize sequences for downstream bioinformatics analysis, thereby significantly reducing the time required for annotation workflows (Fig. 4A). Instead of applying BLAST indiscriminately across millions of reads, AI frameworks enable the preliminary curation of data, guiding traditional tools toward sequences of highest virological relevance. As an initial filter, a CNN-based classifier can remove bacterial and host-derived contaminants from raw sequencing reads, as it demonstrates promise in taxonomic classification of metagenomic reads (98). The refined data set is then subjected to domain annotation using HMM-based approaches and phylogenetic clustering, enabling the delineation of conserved domains and the inference of evolutionary relationships (99). This approach, both rigorous and targeted, ensures the strategic application of bioinformatics tools, enhancing computational efficiency while preserving analytical accuracy (Fig. 4B).
## IMPROVING AI INTERPRETABILITY USING BIOINFORMATICS BENCHMARKS
A key limitation of AI models lies in their interpretive opacity, the BB phenomenon, wherein the rationale behind predictive outputs remains inaccessible to human under standing. Training AI models on biologically curated data sets helps reduce this ambigu ity and enhances explanatory robustness. This hybrid framework, combining the predictive capacity of AI with the interpretability of evolutionary analysis, addresses the knowledge-based disconnect in BB models. For instance, transformer-based models such as LucaProt infer viral genes through contextual pattern recognition, enabling annota tion within genomically unexplored viral sequences (12). Yet in many cases, AI-predicted sequences remain functionally ambiguous, lacking empirical or mechanistic validation.
In such instances, a triad of bioinformatic tools (Pfam, InterProScan, and structural modeling via AlphaFold) becomes indispensable for determining whether these putative viral genes encode domains consistent with known viral functions (100)(101)(102). The reciprocal interplay between AI-driven discovery and bioinformatics-based validation systematically reduces misclassification, as the integration of biologically validated annotations progressively enhances the reliability of interpretation of AI models.
## STRENGTHENING FUNCTIONAL ANNOTATION THROUGH COMBINED APPROACHES
AI-driven models can predict functional domains in viral proteins by leveraging statistical patterns rather than evolutionary precedent. Yet such predictions, while computationally useful, often suffer from ambiguous or non-specific classifications. In contrast, traditional bioinformatic methodologies, anchored in rigorously curated domain taxonomies, offer clarity about the process but often falter when challenged with entirely novel viral proteins. By combining AI-based reasoning with function-based annotation, a hybrid approach supports more accurate and reliable predictions of protein function across different levels of biological understanding. For example, an AI-identified viral protein can be further examined using HMMs, where conserved motifs may reveal similarity to known functional domains (103). Should homology searches fail to uncover related sequences, protein structure modeling offers an alternative approach to understanding by aligning predicted folding architectures with those of known viral enzymes. Integrat ing AI-driven predictions with structural validation provides a strong foundation for assigning functions to previously unannotated viral proteins, such as polymerases, capsid components, and host-pathogen interaction factors.
## OPTIMIZING VIRUS-HOST INTERACTION PREDICTIONS WITH AI AND PHYLO GENETICS
Traditional approaches to predicting host-virus interactions have relied heavily on phylogenetic proximity or manually curated host-association data sets. While structurally sound, these methods are limited by their dependence on existing taxonomies and narrow genomic coverage. Recent advances, particularly through GNNs such as PhaGCN, have introduced network-based learning frameworks that extrapolate host range and transmission dynamics from hidden patterns in viral sequences (85). Nevertheless, these algorithmic predictions require molecular and evolutionary validation through experimental data. Combining AI-generated insights with independent phylogenetic analysis creates a stronger framework for understanding host-virus adaptation. For example, an AI model might flag a novel viral sequence as having zoonotic potential.
Validating this by comparing its receptor-binding regions to known host receptors adds structural evidence, linking AI predictions to real biological function (104).
## AI-DRIVEN MULTI-OMICS INTEGRATION: AIDING BIOINFORMATICS IN COMPLEXITY REDUCTION
Earlier viromic approaches relied mainly on genomic data, but AI-enabled systems have introduced a more integrated model, enabling combined analysis of metagenomic, transcriptomic, and proteomic data. Metatranscriptomics reveals viral gene activity within microbiomes, though separating viral from host RNA remains a major analytical challenge (105). By using AI algorithms to pre-classify viral reads, differential expression analysis becomes more targeted and effective in uncovering host-pathogen interactions. When workflows are designed to be iterative and connected, AI and bioinformatics work together as a unified system, making complex problems more manageable and turning large virome data sets into biologically meaningful insights (7) (Fig. 3).
## CONCLUSION
Progress in viromics relies not on choosing between AI and traditional bioinformatics but on combining their strengths within a shared framework. AI brings speed, sensitivity, and scalability, making it well-suited for identifying viral sequences in large, complex data sets. Yet, its real value unfolds when these predictions are validated and refined using established bioinformatics tools that provide evolutionary, structural, and functional context. This integration is essential: while AI can detect patterns that suggest novel viruses or host associations, bioinformatics methods are needed to interpret those signals and confirm their biological relevance. This combined approach enables a more complete and meaningful analysis of viral diversity and function.
Looking forward, several priorities ought to shape the field. First, hybrid workflows that incorporate both AI and bioinformatics will allow researchers to adapt as new tools and data emerge. The development of modular pipelines and community-endorsed benchmarks will ensure interoperability and reproducibility across laboratories. Second, interpretability frameworks-from feature attribution and saliency mapping to concept bottleneck models and counterfactual reasoning-will affirm that predictions remain transparent and biologically grounded. By clarifying which sequence motifs or struc tural domains drive model outputs, XAI strengthens biological plausibility and facili tates experimental validation. Third, the integration of structure-based AI methods will continue to expand viral annotation beyond sequence homology, enabling classification of highly divergent proteins through conserved 3D folds and illuminating mechanistic features critical for understanding viral function. Shared data sets and reproducible pipelines will promote collaboration and transparency, accelerate discovery and improve our ability to monitor and respond to viral threats.
Investment in comprehensive training programs will collectively certify accessibil ity, empowering researchers across diverse settings to leverage stated computational advances. Promoting collaborative consortia and advancing transparent data sharing will accelerate the translation of computational innovations into practical applications, including real-time viral surveillance, rapid pathogen identification, and the design of targeted antiviral therapeutics. Ultimately, these integrated and accountable approaches will not only advance fundamental virological research but also strengthen global capacity to monitor and respond to emerging viral threats. In this manner, the conver gence of AI and traditional bioinformatics promises to enrich our comprehension of viral evolution, host specificity, and the overarching architecture of the global virosphere, positioning computational viromics as an indispensable tool for both basic research and public health preparedness.
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# Optimised Neutralisation Strategies for Validating the Virucidal Efficacy of Micro-Chem Plus™ Against High-Containment Negative-Sense RNA Viruses
Xiaoxiao Gao, Cheng Peng, Chao Shan, Yanfeng Yao, Zhiming Yuan
## Abstract
Effective disinfectant validation is essential for ensuring biosafety in high-containment laboratories when lethal pathogens are being handled. Micro-Chem Plus™ (MCP) is widely used in high-containment facilities for pathogen disinfection and routine decontamination. However, it induces severe cytotoxicity in cell culture, which may lead to an overestimation of its virucidal efficacy during disinfectant validation assays. To resolve this problem, we systematically evaluated the effects of three neutralisation methods (dilution, chemical neutralisation, and chromatographic separation) on MCP. The results showed that a 400-fold dilution with assay medium completely neutralised MCP, but reliable detection required high viral titers (≥6 log 10 TCID 50 /mL). Chemical neutralisation using Dey-Engley broth showed inherent cytotoxicity, while chromatographic separation (MicroSpin S-400 HR/DetergentOUT™ columns) was the most effective but necessitated an additional 8-fold dilution. Validation in a BSL-4 facility with the risk group 4 (RG-4) agent Ebola virus confirmed MCP's concentration-and time-dependent virucidal activity, achieving a ≥6 log 10 TCID 50 reduction within 1-5 min. This study establishes an optimised framework for disinfectant validation in high-containment laboratories, addressing critical gaps in current protocols.
## 1. Introduction
Micro-Chem Plus™ (MCP), a dual quaternary ammonium compound (QAC)-based disinfectant, has been widely adopted in high-containment laboratories (Biosafety Levels 3 and 4, BSL-3/4) due to its material compatibility with chemical shower systems and proven efficacy against enveloped viruses [1][2][3][4][5][6][7]. Before implementation in BSL-4 facilities, disinfectants must undergo stringent validation to ensure reliable inactivation of high-risk pathogens. Current validation workflows face two major limitations: (i) the absence of standardised neutralisation protocols for dual-QAC formulations, where conventional chemical neutralisers (e.g., Dey-Engley broth) may exhibit cytotoxicity or produce assayinterfering byproducts, and (ii) cumbersome, expertise-dependent methods that impose impractical burdens on maximum-containment operations [8].
Neutralisation in disinfectant validation serves a dual purpose: quenching residual antimicrobial activity to prevent false-negatives and mitigating cytotoxicity to enable accurate viability assessment. While dilution, chemical neutralisation, and column-based techniques are widely employed, their comparative performance for dual-QAC formulations remains uncharacterised-a critical gap given the increasing use of MCP in high-containment settings [3,[9][10][11][12][13][14][15][16][17]. To address this, we systematically evaluated these neutralisation strategies using vesicular stomatitis virus (VSV), a BSL-2 surrogate for enveloped viruses, and validated their operational applicability under BSL-4 conditions with Ebola virus (EBOV) [18].
By integrating mechanistic validation with translational biosafety practices, this work establishes a standardised, resource-efficient framework for disinfectant testing in high-containment laboratories. Our data provide actionable protocols for regulatory compliance and risk mitigation, advancing the paradigm of virucidal efficacy testing for high-risk pathogens.
## 2. Materials and Methods
## 2.1. Cell Lines and Viruses
Vero E6 cells (African green monkey kidney epithelial cells), obtained from the National Virus Resource Center, Wuhan Institute of Virology, Chinese Academy of Sciences, were maintained in Dulbecco's Modified Eagle Medium (DMEM, Gibco, Thermo Fisher Scientific, Waltham, MA, USA) supplemented with 10% foetal bovine serum (FBS, Gibco, Thermo Fisher Scientific, Waltham, MA, USA). The cells were cultivated under humidified conditions with 5% CO 2 at 37 • C.
Recombinant vesicular stomatitis virus expressing green fluorescent protein (VSV-GFP) was kindly provided by Prof. Rongjuan Pei. Ebola virus (EBOV, Mayinga 1976 strain) was obtained from the National Virus Resource Center, Wuhan Institute of Virology, Chinese Academy of Sciences. All experiments containing EBOV were performed in biosafety level 4 (BSL-4) facilities of the National Biosafety Laboratory, Wuhan, Chinese Academy of Sciences, following approved standard operating procedures. The viruses were propagated in Vero E6 cells at a multiplicity of infection (MOI) of 0.01. All virus stocks were titrated using a 50% tissue culture infectious dose (TCID 50 ) assay, aliquoted, and stored at -80 • C until use.
## 2.2. Suspension Test
Micro-Chem Plus™ (MCP; National Chemical Laboratories, Inc., Philadelphia, PA, USA) was freshly diluted to the corresponding concentrations (v/v) with soft water. Equal volumes (100 µL) of virus stock and disinfectant were mixed and incubated at 22 ± 2 • C for predetermined contact times (1-5 min).
## 2.3. Neutralisation Methods
Three independent neutralisation strategies were evaluated to terminate MCP activity while preserving potential surviving virions.
## 2.3.1. Dilution-Based Neutralisation
Virus-disinfectant mixtures were immediately diluted in DMEM supplemented with 2% FBS (assay medium). This physical quenching method was selected to rapidly reduce the MCP concentration below the virucidal threshold.
## 2.3.2. Chemical Neutralisation
Samples were treated with Dey-Engley (D/E) neutralising broth (BD Difco™ and Huankai) at a 1:19 (v/v) ratio, achieved by mixing one volume of the virus-MCP mixture with nineteen volumes of the D/E neutralising broth. In a typical experiment, 50 µL of the virus-MCP mixture was added to 950 µL of D/E broth. Following 15 min of incubation at 22 ± 2 • C, the neutralised samples were subjected to secondary dilution to eliminate residual cytotoxicity from the neutraliser components.
## 2.3.3. Chromatographic Separation
Two column-based chromatographic methods were employed. Size-exclusion chromatography was carried out with MicroSpin™ S-400 HR columns (Cytiva, Marlborough, MA, USA), and detergent removal was performed using DetergentOUT™ GBS10-800 columns (G-Biosciences, St. Louis, MO, USA). All columns were pre-equilibrated with sterile water prior to sample loading. After applying the samples, centrifugation was performed at 700× g for 1 min. The collected eluates were immediately diluted in assay medium to eliminate any residual disinfectant activity.
## 2.4. Cytotoxicity Assay
Cell viability was quantified using a Cell Counting Kit-8 (CCK-8; Vazyme Biotech Co., Ltd., Nanjing, China) according to the manufacturer's specifications, and the absorbance was measured at 450 nm using a Tecan Infinite ® 200 PRO microplate reader. For each treatment, three biological replicates (n = 3) were analysed. The percentage of viable cells was calculated as follows: % viability = [(OD treatment -OD blank )/(OD control -OD blank )] × 100, where OD treatment = mean absorbance of treated cells; OD blank = mean absorbance of reagent blank (CCK-8 in medium without cells); and OD control = mean absorbance of untreated control cells.
## 2.5. Viral Titration
Serial 10-fold dilutions of neutralised samples were inoculated onto Vero E6 monolayers in 96-well plates (n = 6 wells/dilution). After 10 days of incubation, cytopathic effects were examined microscopically. The TCID 50 values were calculated using the Reed-Muench method.
## 2.6. Viral Inactivation Validation
Viral inactivation was assessed through three sequential blind passages in Vero E6 cells, during which at least half of the culture supernatant from each passage was used to inoculate fresh cells. This was followed by quantitative evaluation using probe-based qRT-PCR (HiScript ® II One-Step qRT-PCR Probe Kit, Vazyme Biotech). The following oligonucleotides were employed: forward primer 5 [19]. Complete inactivation was defined by the absence of cytopathic effects and undetectable genomic RNA (<10 copies/µL) in the third passage.
$$′ -ATTTGAATGGGGTCCAATTGCC- 3 ′ [EBOV-L-Q(F)], reverse primer 5 ′ -AAGCAGTRCCTATACTAGCCA-3 ′ [EBOV-L-Q(R)], and probe 5 ′ -FAM-AGTCCCTTAAAACGGCTACAAGAATGGGAC-BHQ1-3 ′ [EBOV-L- Q(P)]$$
## 2.7. Experimental Design
Cytotoxicity was evaluated using a tiered approach to assess both individual components and combined treatments, as detailed in Table 1. Following 3 h of treatment, cell viability was assessed using a previously described method.
To systematically evaluate the virucidal activity of MCP and the effectiveness of the neutralisation methods, we designed six experimental groups (Table 2). After the respective treatments, the VSV titers were quantified by a TCID 50 assay.
## 3. Results
## 3.1. Dilution-Based Neutralisation Achieves Complete MCP Inactivation
The neutralisation capacity of serial dilutions in DMEM supplemented with 2% FBS was systematically evaluated against the standard 5% MCP formulation following a 5 min contact time. Cytotoxicity assessment revealed a concentration-dependent response, with 400-fold dilution established as the minimum requirement for complete neutralisation (Figure 1A). Undiluted 5% MCP reduced Vero E6 cell viability to 2.1 ± 0.1%, while intermediate 200-fold dilution showed partial cytotoxicity (25.9% viability). Complete restoration of cellular viability (103.4 ± 4.9%) was achieved at 400-fold dilution. Morphological assessment through microscopic examination confirmed these findings, demonstrating the absence of cytotoxicity-related changes (cell rounding, shrinkage, detachment, and lysis) at this dilution threshold.
The subsequent neutralisation efficacy validation employed a multimodal assessment strategy combining fluorescence microscopy with TCID 50 titration. All viral titers were normalised to the same initial viral load. This approach yielded several critical findings (Figure 1B,C): (i) 5% MCP treatment alone resulted in complete inactivation of VSV (9.3 ± 0.2 log 10 TCID 50 /mL reduction), with no detectable fluorescence or replicative virus posttreatment; (ii) 400-fold diluted virus-disinfectant mixtures showed no evidence of infectivity restoration, confirming effective neutralisation; (iii) the dilution process itself had no measurable impact on viral infectivity (9.5 ± 0.1 log 10 TCID 50 /mL); and (iv) neutralised MCP solutions exhibited no intrinsic antiviral activity. The control groups confirmed the validity of the assay, establishing a 400-fold dilution as a reliable neutralisation method for suspension studies.
## 3.2. Chemical Neutralisation Reveals Formulation-Specific Limitations
Dey-Engley (D/E) broth is widely employed for neutralising conventional QACs, and the efficacy of two commercial preparations (BD Difco™ and Huankai) have been assessed for their efficacy in neutralising MCP. Initial cytotoxicity screening revealed that both D/E preparations exhibited intrinsic cytotoxicity, reducing Vero E6 cell viability to 26.5 ± 1.2% (BD Difco™) or 28.8 ± 1.8% (Huankai) after 3 h of exposure (Figure 2A). The cytotoxic effect was successfully eliminated through a 4-fold dilution with DMEM supplemented with 2% FBS, which was subsequently applied to the following chemical neutralisation experiments. The optimised neutralisation protocol involved (i) 1:19 (v/v) mixing of 5% MCP with D/E broth, (ii) a 15 min incubation at room temperature (22 ± 2 • C), and (iii) a 4-fold secondary dilution. This protocol completely abolished the cytotoxic effects of MCP while maintaining system integrity for subsequent assays. Validation studies using this protocol were performed with both fluorescence microscopy and TCID 50 assays. As illustrated in Figure 2B,C, the following key results were consistently observed: (i) 5% MCP treatment alone resulted in complete inactivation of VSV, with no detectable infectivity remaining after treatment; (ii) no restoration of viral infectivity was observed following D/E neutralisation after MCP treatment; (iii) D/E solution alone showed no adverse effects on viral infectivity; (iv) neutralised MCP mixtures resulted in no residual antiviral activity; and (v) all system controls performed within the expected parameters. Importantly, the neutralisation process did not interfere with the viral detection systems, confirming the specificity and reliability of these observations. Together, these findings indicate that the dual-QAC formulation of MCP likely requires alternative neutralisation strategies that extend beyond conventional D/E broth.
## 3.3. Chromatographic Methods Require Supplemental Dilution
Two column-based systems were systematically compared: size-exclusion chromatography (MicroSpin S-400 HR) and detergent-removal columns (DetergentOUT™ GBS10-800). Initial cytotoxicity assessment demonstrated that while both columns effectively reduced the MCP concentration, the eluates still retained significant cytotoxicity.
To eliminate the cytotoxicity of the eluate, it was diluted with assay medium after filtration. Take MicroSpin S-400 HR column as an example (Figure 3A). Quantitative analysis of postcolumn dilution effects revealed that (i) 2-fold diluted eluates maintained substantial cytotoxicity (41.9 ± 3.4% viability), (ii) 8-fold dilution achieved complete noncytotoxicity (108.2 ± 0.5% viability), and (iii) 32-fold dilution provided no additional benefit (102.1 ± 2.3% viability).
Based on these findings, an 8-fold dilution with assay medium was established for all subsequent neutralisation efficacy studies. Validation experiments demonstrated that (i) the 5% MCP solution effectively inactivated VSV; (ii) following treatment with either column to remove residual disinfectant, VSV failed to regain cellular infectivity; (iii) neither column exhibited any detectable effect on VSV infectivity; and (iv) the 8-fold diluted eluate showed neither inhibitory effects on VSV infection nor interference with the detection assay (Figure 3B,C).
Notably, both columns showed comparable performance, with complete neutralisation achieved only when combined with the 8-fold dilution. These results establish that while chromatographic separation significantly reduces the MCP concentration, subsequent dilution remains essential for complete neutralisation in disinfectant validation studies.
## 3.4. RG-4 Agent Validation Confirms Concentration-Dependent EBOV Inactivation
In accordance with the 2023 National Disease Control and Prevention Agency's testing standards (requiring ≥4.00 log 10 TCID 50 reduction with positive controls ≥ 5.00 log 10 TCID 50 /mL), we evaluated the virucidal efficacy of two MCP batches (D07D1 and D08D1) against EBOV (initial titer 7.3 log 10 TCID 50 /mL) [20]. Viral suspensions containing 6.0 log 10 TCID 50 EBOV were treated with varying concentrations of MCP (1%, 2.5%, and 5%) for different exposure times. Following treatment, the samples were processed through size-exclusion chromatography (MicroSpin S-400 HR columns), and the eluates were diluted 8-fold in assay medium before being inoculated onto Vero E6 cell monolayers. To rigorously assess viral inactivation, all samples underwent three sequential blind passages with concurrent monitoring for cytopathic effects and qRT-PCR analysis. As shown in Table 3, the results demonstrated concentration-and time-dependent virucidal activity, with complete inactivation of 6 log 10 TCID 50 EBOV achieved within (i) 5 min with 1% MCP, (ii) 2 min with 2.5% MCP, and (iii) 1 min with 5% MCP. The appropriate positive controls consistently maintained the expected viral infectivity throughout all the experimental procedures, confirming the validity of the inactivation results. This comprehensive evaluation revealed that both MCP batches meet and exceed the stringent requirements for high-level disinfection in BSL-4 facilities. The combination of rapid virucidal activity and reliable neutralisation protocols establishes MCP as an effective disinfectant for EBOV decontamination applications.
## 4. Discussion
This study systematically evaluated three neutralisation methods for the dualquaternary ammonium compound disinfectant Micro-Chem Plus™ (MCP), establishing an optimised validation framework for high-containment laboratories. Our findings demonstrate that a 400-fold dilution effectively eliminates cytotoxicity but requires high viral titers (≥6 log 10 TCID 50 /mL), whereas chromatographic separation coupled with supplemental dilution provides the most reliable neutralisation despite greater operational complexity. Validation using Ebola virus confirmed the potent virucidal activity of MCP, achieving a ≥6 log 10 TCID 50 reduction.
Each method has distinct advantages and limitations. Dilution is simple and consistent but reduces detection sensitivity; chemical neutralisation introduces cytotoxicity and requires extended incubation; chromatography achieves complete removal of disinfectant but is associated with increased costs and biosafety risks [21,22]. These trade-offs underscore the importance of selecting methods based on specific experimental and operational needs.
Several challenges remain. Current approaches lack standardised protocols for novel disinfectant formulations, and rapid kinetic assessment (e.g., within 1-2 min of exposure) remains problematic. Future work should prioritise the development of broad-spectrum neutralisers, harmonising validation standards across biosafety levels, and the incorporation of advanced detection technologies [23,24]. Furthermore, continuous evaluation against emerging viral threats is essential to sustain robust biosafety preparedness. Such advancements will improve accurate efficacy assessments against diverse pathogens and contribute to global health security.
This work provides a comprehensive and practical framework for validating disinfectant neutralisation methods at high-containment facilities. Our results enhance the understanding of dual-QAC disinfectant validation and offer actionable guidance for laboratory operations. As microbial threats continue to evolve, further refinement of these strategies will be critical to ensure reliable disinfection and maintain effective biosafety protocols.
## References
1. Leung, Cutts, Krishnan (2024) "Decontamination validation of the BSL-4 chemical disinfectant deluge shower system" *Appl. Biosaf*
2. Klaponski, Cutts, Gordon et al. (2011) "A Study of the Effectiveness of the Containment Level-4 (CL-4) Chemical Shower in Decontaminating Dover Positive-Pressure Suits" *Appl. Biosaf*
3. Zhang, Peng, Liu et al. (2018) "Evaluation of MICRO-CHEM PLUS as a Disinfectant for Biosafety Level 4 Laboratory in China" *Appl. Biosaf*
4. Uddowla, Clarkson, Ziegler et al. (2016) "Evaluation of Earth Sense ® Neutral Disinfectant Detergent as an Alternative to Micro-Chem Plus™ Detergent Disinfectant for Use in BSL-4 Laboratories using Vesicular Stomatitis Virus as a Surrogate" *Appl. Biosaf*
5. Chida, Goldstein, Lee et al. (2021) "Comparison of Zika virus inactivation methods for reagent production and disinfection methods" *J. Virol. Methods*
6. Li, Lv, Zeng et al. "Evaluation of Stability, Inactivation, and Disinfection Effectiveness of Mpox Virus" *Viruses*
7. Jiang, Sun, Fan et al. (2023) "Virucidal activity of MICRO-CHEM PLUS against African swine fever virus" *J. Integr. Agric*
8. Gerba (2015) "Quaternary ammonium biocides: Efficacy in application" *Appl. Environ. Microbiol*
9. Huang, Xiao, Song et al. (2022) "Efficacy of disinfectants for inactivation of Ebola virus in suspension by integrated cell culture coupled with real-time RT-PCR" *J. Hosp. Infect*
10. Huang, Xiao, Song et al. (2022) "Evaluation and comparison of three virucidal agents on inactivation of Nipah virus" *Sci. Rep*
11. Huang, Xiao, Song et al. (2022) "Evaluating the virucidal activity of four disinfectants against SARS-CoV-2" *Am. J. Infect. Control*
12. Dey, Engley (1994) "Neutralization of antimicrobial chemicals by recovery media" *J. Microbiol. Methods*
13. Sharma, Beuchat (2004) "Sensitivity of Escherichia coli O157:H7 to commercially available alkaline cleaners and subsequent resistance to heat and sanitizers" *Appl. Environ. Microbiol*
14. Park, Chen (2011) "Mitigating the antimicrobial activities of selected organic acids and commercial sanitizers with various neutralizing agents" *J. Food Prot*
15. Guo, Chen, Wang et al. (2021) "In vitro inactivation of SARS-CoV-2 by commonly used disinfection products and methods" *Sci. Rep*
16. Lloyd-Evans, Springthorpe, Sattar (1986) "Chemical disinfection of human rotavirus-contaminated inanimate surfaces" *Epidemiol. Infect*
17. Cutts, Nims, Rubino et al. (2023) "Efficacy of microbicidal actives and formulations for inactivation of Lassa virus in suspension" *Sci. Rep*
18. Amarasinghe, Ayllón, Bào et al. (2019) *Taxonomy of the order Mononegavirales: Update*
19. Dedkov, Magassouba, Safonova et al. (2016) "Development and evaluation of a real-time RT-PCR assay for the detection of Ebola virus (Zaire) during an Ebola outbreak in Guinea in 2014-2015" *J. Virol. Methods*
20. (2024) "National Disease Control and Prevention Administration of China"
21. Vater, Adamovic, Ruttensteiner et al. (2019) "Cytotoxicity of lecithin-based nanoemulsions on human skin cells and ex vivo skin permeation: Comparison to conventional surfactant types" *Int. J. Pharm*
22. Li, Xian, Kwon et al. (2020) "Comparison of three neutralizing broths for environmental sampling of low levels of Listeria monocytogenes desiccated on stainless steel surfaces and exposed to quaternary ammonium compounds" *BMC Microbiol*
23. Ebersohn, Coetzee, Venter (2014) "An improved method for determining virucidal efficacy of a chemical disinfectant using an electrical impedance assay" *J. Virol. Methods*
24. Zhang, Cheng, Li et al. (2025) "Challenges of quaternary ammonium antimicrobial agents: Mechanisms, resistance, persistence and impacts on the microecology" *Sci. Total Environ*
25. "The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods"
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# Biographical Feature: Diane E. Griffin and Ann Palmenbergluminaries in RNA virology
Robert Kalejta, Paul Friesen, Andrew Pekosz, Stacey Schultz-Cherry, Diane Griffin, Stacey Schultz
## Abstract
Two incredible virologists, mentors, and people who truly made an impact on science and the community.Dr. Diane Griffin, MD, PhD, was one of the most prominent scientific leaders of her generation. Her work was the first to demonstrate that measles virus infection causes death primarily by increasing susceptibility to other infections. She also showed that the measles virus leaves RNA particles after infection that may contribute to the lifelong protective immunity from measles. Diane also published seminal papers on how neurons were protected from death after virus infection and described non-lytic control of virus infection in neurons. During her decades at Johns Hopkins University, Diane was a leader in all that she did. She worked tirelessly for the research and public health communities leaving a tremendous legacy in the knowledge that she contributed to infectious diseases. Part of the legacy was the invaluable training she provided to the
next generation of scientists and physicians, where she was known as an incomparable teacher, mentor, scientist, leader, and human being. Common themes when people talk about Diane are kindness, civility, and work ethics. Throughout her career, Diane achieved many accolades, including being an elected fellow of the American Association for the Advancement of Science as well as the Infectious Diseases Society of America. She was a frequent participant in the National Institutes of Health study sections, chairing the Special AIDS Study Section and co-chairing the Board of Scientific Counselors at the National Institute of Allergy and Infectious Diseases, and was Vice President of the US National Academy of Sciences. She edited the Journal of Virology from 1994 to 2004, was a past president of the American Society for Virology (ASV) and the American Society for Microbiology, and was inducted into the Maryland Women's Hall of Fame in 2009. Read more about Dr. Griffin's work.
Dr. Ann Palmenberg, PhD, was a trailblazer in the field of RNA virology. Ann's humble description of her work as simply "taking viruses apart and putting them back together" fails to capture her scientific brilliance, influence on the field, and unrivaled support of junior faculty and women in science. A renowned expert on the biochemistry of picornaviruses, her work solved the atomic structure of human rhinovirus C, which paved the way for new therapies and antivirals against virus-induced asthma. Ann was also the first to describe a way to make new types of live virus vaccines using viral internal ribosome entry sites (IRES). The discovery of the IRES still serves as the manufacturing basis for numerous biotechnological and pharmaceutical products and made for an interesting, personalized license plate for her automobile. During her decades at the University of Wisconsin-Madison (UW) as a Professor of Biochemistry, Ann received numerous awards from the university and the Wisconsin Alumni Research Foundation. She served as the Director of UW's Institute for Molecular Virology for 15 years. She also enjoyed serving on the UW Athletic Board and was frequently found in the bleachers at Badger Big Ten football, basketball, and hockey games. She may be best recognized by the virology community for her dedication to the ASV, where she spent countless hours organizing memorable annual conferences. In 2007, Ann was elected ASV President and in recognition of her influential research and 30 years of devoted service to the Society, she received the 2024 Wolfgang & Patricia Joklik Distinguished Service Award from the ASV. Multiple awards were also established in her name during her lifetime, including
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# Integrative genomic analyses support the division of the extended Asfarviridae clade into multiple viral families
Thiago Mendonça-Santos, Jônatas Abrahão, Luiz-Eduardo Del-Bem
## Abstract
Giant viruses continue to challenge our understanding of virology, blurring boundaries of what a virus can be. The so-called "extended Asfarviridae"such as African swine fever virus, faustovirus, kaumoebavirus, pacmanvirus, and AbALV-has long puzzled taxonomists. By integrating comparative genomics, pangenomics, and phylogenomics, we show these lineages are deeply divergent, forming multiple families rather than one. This work underscores the huge unexplored diversity of giant viruses and demonstrates the value of integrative genomic analyses for proper taxonomic delineation.KEYWORDS phylogenomics, viral taxonomy, pangenomics, giant viruses G iant viruses, such as mimiviruses, exhibit unique characteristics, including virions visible under a light microscope, genomes larger than some unicellular organisms, and a diverse and unprecedented gene repertoire among viruses (1, 2). Their discovery revolutionized virology, challenging established concepts, underscoring the need to revisit conventional definitions, and highlighting the necessity for new isolation and sequencing studies to discover more of these long-overlooked viruses.The African swine fever virus (ASFV), one of the largest known DNA viruses before the discovery of other giant viruses, remained the sole representative of the Asfarviridae family for decades and is the causative agent of African swine fever (ASF). However, other genetically related viruses have been isolated and placed within the Asfarviridae clade, leading to the formation of the "extended Asfarviridae" group to include ASFV and genetically related viruses such as Faustovirus, Kaumoebavirus, Pacmanvirus, and Abalone asfar-like virus (AbALV). Faustovirus, isolated in 2015 from wastewater (3), and kaumoebavirus, discovered in 2016 (4), both infect Vermamoeba vermiformis. Pacmanvi rus, identified in 2017 from wastewater (5), replicates in Acanthamoeba castellanii. AbALV was first identified in 2020 and is known to infect abalones, causing high mortality rates (6).Despite the apparent genetic relationship, there is still uncertainty about the inclusion of these associated viruses within the family Asfarviridae due to highly divergent characteristics such as differences in host range, environmental niches, genome sizes, and gene repertoire. Questions persist about whether these viruses should remain grouped under a single family or if they represent lineages distinct enough to warrant classification as founding members of entirely new viral families.To address these issues, we performed comprehensive genomic and functional analyses and constructed a pangenome that reflects the gene content of the exten ded Asfarviridae. This approach provides an in silico framework for investigating the evolutionary relationships among these viruses, exploring their genetic similarities and differences, and characterizing their complex genomic architecture and functional diversity. By addressing this knowledge gap, our work contributes to a more precise
## Core gene phylogeny
Amino acid sequences for each of the identified core genes were aligned using MAFFT v7 (10) with the L-INS-i strategy. To enhance alignment quality, the resulting alignments were refined with Gblocks (11) to remove poorly aligned regions. These individual alignments were preserved for generating phylogenies of single core genes.
The alignments were then analyzed with IQ-TREE (12) to construct maximum likelihood phylogenetic trees. The LG+F+R4 substitution model, as recommended by ModelFinder (13) based on the Bayesian information criterion, was applied during tree construction. Branch support values (bootstrap) were calculated with 1,000 replicates. This step utilized resources from the Centro Nacional de Processamento de Alto Desempenho em São Paulo (CENAPAD-SP) and the Gloriosos clusters at the Laboratory of Genetics Biochemistry, UFMG.
To infer a consensus species tree while accounting for potential discordance among individual gene trees, we employed Weighted ASTRAL (wASTRAL v1.22.3.7) (14). This method improves phylogenomic inference by integrating both branch support values (bootstrap) and branch lengths to weight the contribution of quartets, effectively reducing the influence of low-confidence signals. Gene trees generated for each core gene by IQ-TREE were used as input. wASTRAL was executed with support-weighted and length-weighted hybrid criteria.
The phylogenetic tree was visualized in FigTree v1. 4.4 (https://tree.bio.ed.ac.uk/ software/figtree) and edited in Inkscape v1.2.1 (2022).
## Functional analysis of clustered predicted proteins
To predict the functions of clustered proteins, the amino acid sequences in their respective pangenomic groups were mapped to the Giant Virus Orthologous Groups (GVOGs) (15), a curated set of protein families specific to the Nucleocytoviricota. This mapping was performed using Hidden Markov Models (HMMs) with the hmmscan tool from the HMMER package (16). The hmmscan tool identifies the presence of conserved domains within protein sequences by comparing them to pre-built HMM profiles of known protein families. Subsequently, functional annotations were inferred from the GVOG descriptions, based on the Cluster of Orthologous Groups classification.
## Synteny analysis
The conservation of gene order is an important indicator of shared evolutionary history. For this analysis, the predicted protein sequences were used in an all-againstall BLASTp (1e-5). The resulting BLASTp table was filtered, selecting hits with pident ≥20% and ≥70%. MCScanX, a tool that detects gene collinearity in genome pairs (17), was then used for this purpose. MCScanX utilizes BLASTp outputs along with the GFF files generated by GeneMarkS containing the location of the predicted proteins to assess the presence of syntenic gene blocks among genome pairs. Two analyses were conducted, one for p-ident ≥20% and another for p-ident ≥70%. The results were used to create a synteny matrix, visualized and downloaded through Synvisio (18). The two matrices were then combined and edited in Inkscape v1.2.1.
## AAI and ANI calculation
To estimate the levels of similarity between genomes in terms of nucleotide and amino acid composition, the genomes and amino acid sequences, respectively, were submitted to the ANI/AAI calculator (19) to calculate average nucleotide identity (ANI) and average amino acid identity (AAI) values. This tool estimates the average identity of nucleotides and amino acids through BLAST using a bidirectional approach where best hits (oneway ANI/AAI) and reciprocal best hits (two-way AAI/ANI) between two sets of genomic protein data are computed.
Matrices were created with the pairwise values and submitted to R for heatmap generation with pheatmap v1.0.12 (20). Hierarchical clusters were then calculated with the hclust function in R, using the complete linkage method, and the genomes were reorganized into dendrograms with the dendsort package (21) and then plotted with ggplot2. For comparison purposes, average AAI values were also calculated for genomes from other NCLDV families (Table S1).
## GENOMIC DIVERSITY AND CONTENT PATTERNS REVEAL DISTINCT GROUP INGS WITHIN EXTENDED ASFARVIRIDAE
A search of the NCBI database for complete viral species genomes of extended Asfarviridae returned 39 complete genomes as of June 2023 (Table S2). All sequences were obtained in FASTA format. The analyzed attributes included genome length, architecture, and G + C content. Subsequently, the genomes were annotated for coding sequences using the GeneMarkS tool.
No statistically significant differences (Mann-Whitney P < 0.05) were found between the genome sizes of pacmanviruses and kaumoebaviruses, but significant divergences were found when comparing the other groups (Fig. S1A). It is noteworthy that there is a significant difference in genome length between ASFV and the faustoviruses, which possess the largest genomes within the clade. Faustoviruses have, on average, a genome 2.5 times larger than ASFV, which has the smallest genomic size in the group.
ASFV exhibits the lowest number of predicted proteins (Fig. S1B), whereas no statistically significant differences were observed among kaumoebaviruses, pacmanvi ruses, and faustoviruses. Although the genomes of kaumoebaviruses and pacmanviruses are slightly shorter, they still maintain a number of proteins similar to those of faustovi ruses, the group with the largest average genome size.
Faustoviruses and ASFV showed no significant differences in G + C content among their members (Fig. S1C). AbALV has the lowest G + C content in the group, almost 40% lower than the highest G + C content found in kaumoebavirus Sc. Faustoviruses are divided into clear three ranges of G + C content: faustovirus D5a, E12, E23, E24, Liban, and ST1, with an average of 36.3%; faustovirus D3, D5b, D6, and VV10, with an average of 37.7%; and faustovirus E9, LCD7, M6, S17, vv57, VV63, with an average of 39.5%.
## EXTENDED ASFARVIRIDAE PRESENTS AN EXTENSIVE OPEN PANGENOME AND A LIMITED CORE
The clustering process of protein sequences based on similarity resulted in a total of 2,483 clusters of orthologous proteins or singleton genes for extended Asfarviridae. Only 37 proteins are found in all the 39 genomes, while 973 proteins were considered singletons (Fig. 1A), part of the cloud group, meaning they were not found in two or more genomes.
For each lineage analyzed, the core genes corresponded to approximately 7%-8% of the total genes in faustoviruses, kaumoebaviruses, and pacmanviruses. However, the scenario is different for AbALV, where core genes represent 10% of the total genes, and in ASFV, where this proportion varies from 20% to 25% of the genome.
Conversely, when examining singleton genes, we observe significant variation in proportions across different lineages. Faustoviruses and ASFV display relatively low proportions, ranging from 0 to 5% and 0 to 6%, respectively. In contrast, AbALV exhibits a notably high proportion of 83% singleton genes. Pacmanviruses and kaumoebaviruses occupy an intermediate range, with proportions between 14% and 20% and 29% and 35%, respectively.
Gene-sharing patterns within this clade exhibit distinct group-specific dynamics (Fig. 1B). Intragroup variation in ASFVs and faustoviruses ranges from 41% to 49% and 32% to 50%, respectively. Kaumoebaviruses, despite their genetic proximity, share only 33% of proteins, representing the highest intergroup sharing. Pacmanviruses share slightly more proteins (41%), while AbALV shows greater proximity to ASFVs (10%-11%). All other intergroup comparisons reveal less than 10% shared proteins.
The sequential inclusion of genomes does not clearly show the formation of a plateau at the end of the curve, suggesting that new inclusions can still increase the number of new genes (Fig. 1C). After applying power regression (n = κN-α) to the total number of genes in different lineage combinations, the parameter α was estimated as 0.71. Since α < 1 and no plateau is observed, the Asfarviridae pangenome is considered open. It is important to note that the core gene curve stabilizes quickly. Unlike the pangenome curve, this core gene group appears conserved with little variation as new genomes are included.
When stratifying orthologous protein clusters according to their pangenomic group, that is, according to the level of protein sharing, the observed patterns are illustrated in Fig. 1D. The histogram depicts the gene frequency of orthologs in each genome, while the pie chart illustrates the proportion of total redundant proteins in each pangenomic group. The histogram indicates that most genes are present in a limited number of genomes (accessory genes), while few genes are present in all genomes (core genes), suggesting a high variation in the gene content of viruses in this clade. Additionally, there is a predominance of singleton/cloud proteins in the clusters, although shell proteins lead in terms of the total number of proteins in the pie chart.
Protein lengths within this clade vary significantly by pangenomic group (Fig. S2). Core group proteins are the largest, surpassing both other virus groups and the average protein length across the entire pangenome. This group is followed by soft core, shell, and cloud proteins. Statistical analysis (Mann-Whitney, P < 0.05) confirms significant differences in mean lengths between these groups. Notably, cloud group proteins are consistently the smallest.
## CHALLENGES IN FUNCTIONAL ANNOTATION AND MCP FRAGMENTATION IN EXTENDED ASFARVIRIDAE
Functional annotation was achieved for 100% of the orthologous clusters in the core and soft-core groups, while the shell and cloud groups showed lower annotation rates of 60% and 55%, respectively, likely reflecting the abundance of singleton genes in the latter. Proteins of unknown function represent the most common category across all groups, according to the GVOG classification (Fig. S3).
As expected, most of the identified core proteins are functionally associated with DNA maintenance processes, including replication, reinforcing the essential role of these functions in the core genome of the extended Asfarviridae. In the soft-core group, the most frequent category is associated with transcription, replication, recombination, and repair, emphasizing the continued importance of these processes even in a less conserved set of genes. The shell group exhibited the greatest functional diversity, with more functions related to metabolism and cellular processes beyond nucleic acids. Aside from the significant proportion of unknown functions, the most represented catego ries in the shell group are energy production and conversion, secondary metabolite biosynthesis, transport and catabolism, and cell wall/membrane/envelope biogenesis. In the cloud group, the predominant categories are replication, recombination, and repair, and secondary metabolite biosynthesis, transport, and catabolism. The absence of the structural protein Major Capsid Protein (MCP) in the results is noteworthy. MCP plays a crucial role in forming the viral capsid and is typically present in all viral genomes within the Bamfordvirae kingdom, which includes the NCLDVs. However, in faustoviruses, this gene is known to be fragmented across the genome (22), potentially impacting the clustering step. To confirm MCP's presence in faustoviruses, a targeted search using BLASTp was conducted, locating 43 transcripts corresponding to MCP in faustoviruses, with an average of 2.6 transcripts per genome. These genes were then aligned with MCP sequences from other members of the group using MAFFT v7 (L-INS-i strategy), and the resulting multiple alignment was visualized in AliView (23) (Fig. S4).
## PHYLOGENETIC ANALYSIS REVEALS HIGH GENETIC DIVERGENCE AMONG EXTENDED ASFARVIRIDAE GROUPS
The species tree (Fig. 2) was inferred using wASTRAL, based on 37 maximum like lihood core gene trees of the extended Asfarviridae group. This coalescent-based approach accounted for potential topological discordance among individual gene trees by integrating both branch support and branch length weighting. The resulting tree, rooted using kaumoebavirus as the basal lineage, revealed a well-resolved phylogenetic structure, with strong support for major clades. Faustovirus, pacmanvirus, ASFV, AbALV, and kaumoebavirus each formed strongly supported monophyletic groups, with high local posterior probabilities across internal nodes. Despite the shared ancestry among these viruses, the patristic distances separating the major clades were pronounced, typically exceeding 2.0 and reaching over 3.0 in several cases, indicating deep evolution ary divergence within the group.
## SYNTENY ANALYSIS REVEALS VARIATIONS IN GENE ORDER CONSERVATION
Synteny analyses using dot plots provide a comprehensive view of genomic organiza tion. BLASTp was used at two identity thresholds (20% and 70%) alongside MCScanX, a tool for detecting synteny. The results showed that gene order conservation varies for each virus group, even with reduced protein similarity. Intergroup comparisons revealed that only AbALV and ASFV showed gene collinearity through segmented gene blocks in the genome (Fig. 3A), especially with reduced protein similarity (p-ident).
Within groups, ASFVs demonstrated high gene order conservation, except for the group formed by ASFV BA71V, Benin 97/1, and E75, which showed no collinearity with the ASFV ken05/tk1, Kenya 1950, and ken06.Bus group. In contrast, faustoviruses showed variations in gene order conservation, ranging from a complete absence to full conserva tion, depending on the group members. In faustoviruses, genome sequence inversion is observed, as seen in diagonal lines from the bottom left to the top right. White boxes indicate a lack of similarity between the analyzed pairs.
## ANI AND AAI VARIABILITY DELINEATES POTENTIAL NEW SPECIES AND GENERA WITHIN EXTENDED ASFARVIRIDAE
Analyses of AAI and ANI were performed to compare the amino acid and nucleotide compositions between different viral specimens. The AAI matrix (Fig. 3B) highlights proximity and divergence between groups. Hierarchical clustering revealed distinct patterns of similarity, with ASFVs showing high internal AAI values (>95%) and significantly lower values (~30%) when compared to other groups. AbALV is the closest to ASFVs, with an AAI of 32%. Among faustoviruses, four clusters with high AAI (>95%) were identified: (i) E12, D5a, E23, and E24; (ii) ST1 and Liban; (iii) E9, M6, S17, LCD7, vv57, and VV63; and (iv) D6, D5b, D3, and VV10. AAI values between faustovirus clusters drop to 50%-60%, and comparisons with other groups are around 30%.
Pacmanviruses and kaumoebaviruses exhibited high AAI similarity within their respective groups, with kaumoebaviruses at 63% AAI and pacmanviruses at 83%. Comparisons between these viruses and ASFV, faustoviruses, and AbALV yielded lower AAI values, ranging from 29% to 35%. These AAI results suggest a closer relationship among faustoviruses, kaumoebaviruses, and pacmanviruses, as compared to ASFV and AbALV, while highlighting notable intragroup variation. The average AAI among the 39 members of the extended Asfarviridae was 37%, exceeding that of Ascoviridae (34% ± 3.49%), Iridoviridae (34% ± 4.37%), and Marseilleviridae (37% ± 8.07%), but lower than Mimiviridae (44% ± 13.22%). However, the extended Asfarviridae exhibit greater intragroup variability.
ANI analyses were performed individually due to methodological limitations with highly divergent groups. Organisms with over 95% ANI are frequently considered to belong to the same species. ASFV subgroups identified include the following: (i) ASFV Malawi 1983; (ii) ASFV ken05/tk1, Kenya 1950, ken06.Bus; (iii) ASFV Georgia 2007/1, Mkuzi 1979, Tengani 62, Warmbaths, Pretoriouskop/96/4, and Warthog; and (iv) other ASFVs, all with ANI above 95% (Fig. 3C).
Faustoviruses demonstrate higher divergence in ANI compared to ASFVs, with four distinct groups identified in both AAI and ANI analyses, each showing intragroup ANI above 98% (Fig. 3D), indicating the likely presence of four separate species within this group. Intergroup comparisons between faustoviruses and other viral groups reveal ANI values below 78%. Kaumoebavirus strains KLCC10 and Sc show a low ANI of 77.93%, while pacmanvirus strains A23 and S19 exhibit a slightly higher ANI at 85.64%, suggest ing closer genomic similarity among pacmanviruses than kaumoebaviruses, although both comparisons fall below the 95% ANI threshold. These findings further support the presence of two distinct species within both the pacmanvirus and kaumoebavirus groups.
## DISCUSSION
The term "extended Asfarviridae" emerged as a temporary classification to encompass a variety of giant viruses, including AbALV, faustovirus, kaumoebavirus, and pacmanvi rus, as well as potential other viruses yet to be discovered that exhibit some level of phylogenetic similarity with ASFV, the original member of this clade. The inclusion of these new members results in a broad biological diversity within the extended Asfarviridae. These viruses infect a wide range of hosts, from unicellular amoebae to multicellular organisms such as mollusks and vertebrates. While Asfarvirus (ASFV) and AbALV occur naturally in their respective hosts, the true host range of amoeba-associ ated members (e.g., faustovirus, kaumoebavirus, pacmanvirus) remains uncertain, as the reported hosts may represent systems of isolation.
Our genomic analysis highlights variability in features such as genome length, G + C content, and the number of predicted proteins, which aid in viral classification. Although G + C content is traditionally used in taxonomic descriptions, often varying by less than 1% between species (24), our findings, consistent with Witt et al. (25), suggest that it is not a reliable taxonomic marker at the family level within Nucleocytoviricota. Only Marseilleviridae shows notable uniformity in this aspect. Within the extended Asfarviri dae, faustoviruses are the closest group to ASFV, while others show greater divergence. Additionally, the division of faustovirus genomes into three distinct G + C content bands supports the presence of subgroups (3). Protein-coding patterns reflect that faustoviruses, pacmanviruses, and kaumoebaviruses each display a relatively stable gene count (26), whereas ASFV carries far fewer genes, reflecting its smaller genome. Crucially, comparable protein numbers can accompany different genome lengths, highlighting variable gene density. Yet, within an established viral family, genome size itself tends to remain consistent (27,28). In our analyses, viruses infecting unicellular eukaryotes (e.g., Vermamoeba, Acanthamoeba) cluster together and are genetically closer to each other, whereas those infecting multicellular hosts (e.g., abalones, swine) form a distinct, more compact group with smaller genomes. This pattern may reflect genome streamlining or gene loss associated with adaptation to more specialized host environments.
A previous analysis of the extended Asfarviridae pangenome by Karki et al. ( 29) primarily focused on investigating aquatic metagenomic-assembled genomes, without stratifying the pangenome into its various groups or calculating whether the pange nome was open or closed. We addressed this gap by applying the Heaps formula, proposed by Tettelin et al. (30,31), and by constructing a pangenomic accumulation curve to evaluate this aspect. The results indicate that the extended Asfarviridae pangenome is considered open. This categorization implies that the discovery and incorporation of new genomes tend to add new genes to the pangenome, suggesting that the diversity of extended Asfarviridae is not yet fully known. Unlike many viral groups whose pangenomes are closed due to the limited number of genes, NCLDVs may have genomes without this limitation, resulting in open pangenomes, as observed in this study. Examples of other viral groups with open pangenomes include pandoraviruses (32), the Herpesviridae family (33), and ASFVs at the species level (34).
The core genome of the extended Asfarviridae stabilizes rapidly at only 37 genes, a size close to the 47-gene ancestral NCLDV core (35) yet far below the 86-gene core of the more cohesive Asfivirus genus (34). This minimal, highly conserved set, set against a pangenome of 2,483 orthologous clusters, underscores the deep genomic divergence within the clade and suggests the core would expand if its members were more closely related. By comparison, other giant viruses retain much larger cores, such as the pandoravirus group ≈425 genes (15%-30% of each genome) and the families Mimiviridae 267 genes (22%-28%) and Marseilleviridae 202 genes (~44%) (32,36,37). Even the debated pithovirus clade (cedratvirus + orpheovirus) carries 52 core genes (38). Thus, extended Asfarviridae appears to sit near the minimal core boundary of NCLDVs, highlighting its exceptional heterogeneity. Core group proteins also tend to be longer than accessory ones, a feature linked to functional and evolutionary importance and possibly reflecting a more ancient origin (39). Natural selection is known to suppress changes in longer transcripts while promoting variation in shorter ones (40), which reinforces the stability of this minimal set. In contrast, cloud proteins are generally smaller, more prone to accumulate mutations, and likely represent younger, accessory functions, a pattern also observed in eukaryotes (41) and now evident in viruses.
A significant portion of proteins in the extended Asfarviridae pangenome lacks known functions, a recurring issue in NCLDV genomes, where over 80% of proteins can be uncharacterized (42). The core group has the highest proportion of identified proteins due to its conservation and essential genes, aiding functional identification. Core group genes, vital for basic biological functions, include many NCLDV housekeeping genes (35). The MCP gene, critical for all extended Asfarviridae, is absent from the core group due to fragmentation in faustoviruses and divergence in other viruses (22). This absence is not uncommon in core genomes; in various studies, it is also not detected in pandora viruses and some divergent pithoviruses (42). This reflects a limitation of pangenomic techniques in detecting atypical gene structures. Other pangenomic groups showed limited functional annotation due to the high proportion of unknown proteins.
Although these viruses share a common ancestry, the species tree inferred from multi-gene coalescent analysis revealed that kaumoebavirus, faustovirus, pacmanvirus, ASFV, and AbALV each form a highly supported and genetically cohesive clade. The patristic distances, that is, the summed branch lengths between taxa, separating these lineages were consistently high, reflecting levels of divergence comparable to those observed among the major clades in this data set. This degree of evolutionary separa tion, combined with robust monophyly and long internal branches, is inconsistent with a single-family classification.
To further investigate the taxonomic implications of these phylogenetic patterns, we integrated multiple genomic analyses, including phylogeny, AAI, ANI, and synteny. These analyses clearly support the delineation of multiple species within the extended Asfarviridae. The clade-wide mean AAI, a key metric for taxonomic classification, is just 37%, yet ASFV isolates share >95% AAI and minor syntenic differences, supporting three species: (i) ken05/tk1, Kenya 1950, and ken06.Bus; (ii) Malawi 1983; and (iii) the remaining 14 isolates. Faustoviruses resolve into four species based on congruent AAI/ANI values and phylogenetic topology: (i) E12, D5a, E23, E24; (ii) ST1 and Liban; (iii) E9, M6, S17, LCD7, vv57, VV63; and (iv) D6, D5b, D3, VV10. Pacmanviruses and kaumoebaviruses likely each encompass two species. AbALV lies below the Asfivirus AAI threshold, occupy ing an intermediate position. Collectively, these findings reveal substantial genomic divergence within the extended Asfarviridae, indicating evolutionary separations that support taxonomic revision.
Altogether, these findings suggest that these aggregated viruses likely do not belong to a single taxonomic family, especially when compared to the only official member, the Asfivirus genus. Instead, faustoviruses, kaumoebaviruses, pacmanviruses, and Abalone asfar-like virus represent a cluster of related yet genetically diverse species that may warrant classification into distinct families. Based on our analysis, the 16 faustoviruses likely comprise four species, the 18 ASFV three species, and the pairs of pacmanvi ruses and kaumoebaviruses two species each. The open nature of the pangenome underscores the vast unexplored diversity of these viruses. Additional viral sequences and further studies are essential to deepen our understanding of this clade's genomic complexity and its relationships with hosts.
## Taxonomic implications
Based on the strong phylogenetic, genomic, and pangenomic evidence presented, we propose the formal taxonomic reclassification of the so-called extended Asfarviridae clade. The deep divergence between ASFV, faustoviruses, kaumoebaviruses, pacmanvi ruses, and AbALV, evidenced by consistently low intergroup AAI values (29%-35%), high patristic distances, and limited gene sharing, exceeds the thresholds typically observed between established viral families. These lineages form well-supported, monophyletic clades with intra-group AAI and ANI values above 95% (consistent with species-level cohesion), while intergroup AAI falls below 40% (supporting family-level separation).
Following established thresholds for Nucleocytoviricota taxonomy and the ICTV's genome-based criteria, we propose that the extended Asfarviridae be reclassified into five distinct families:
## Demarcation criteria
Our proposal adheres to the quantitative and evolutionary benchmarks presented in Table 1.
This proposal is based on multiple complementary criteria:
• Monophyly with high branch support (>0.95 local posterior probabilities),
• AAI values between groups below 40%,
• ANI values between genera consistently below 70%,
• Patristic distances consistent with or exceeding those between established NCLDV families such as Marseilleviridae, Iridoviridae, and Mimiviridae.
Furthermore, each proposed family exhibits lineage-specific genomic features, including genome length, G + C content, pangenome structure, and functional gene content, that support their distinction at higher taxonomic ranks. These findings reinforce the need to revise the taxonomy of this clade and align with the ICTV's current standards for sequence-based virus classification.
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