pmid stringlengths 8 8 | pmcid stringlengths 8 11 ⌀ | source stringclasses 2
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26823630 | PMC4713113 | pmc | 9,720 | {
"abstract": "Dark septate endophytes (DSE) are distributed worldwide as root-colonising fungi, and frequent in environments with strong abiotic stress. DSE is not a taxon, but constitutes numerous fungal taxa belonging to several orders of Ascomycota . In this study we investigate three unidentified DSE lineages belonging to Pleosporales that were found previously in semiarid sandy grasslands. For molecular phylogenetic studies seven loci (ITS, partial 18S nrRNA, 28S nrRNA, actin, calmodulin, transcription-elongation factor 1- α and ß -tubulin genes) were amplified and sequenced. Based on morphology and the resulting molecular phylogeny these isolates were found to represent three novel genera within the Pleosporales , namely Aquilomyces , Flavomyces and Darksidea , with eight novel species. Molecular data revealed that monotypic Aquilomyces belongs to Morosphaeriaceae , monotypic Flavomyces represents an incertae sedis lineage related to Massarinaceae , and Darksidea , with six new species, is allied to the Lentitheciaceae . During this study we tested numerous conditions to induce sporulation, and managed for the first time to induce several DSE to form their sexual morphs.",
"conclusion": "Conclusions DSE fungi constitute a polyphyletic form-group of fungi representing several orders of the Pezizomycotina . Not only are their functional contributions to ecosystems ‘elusive’ ( Mandyam & Jumpponen 2005 ), but also, their taxonomic diversity is far from known. The three genera described from a semiarid sandy region in the present study illustrate that even distinct new lineages of DSE can still be identified. These well-defined and formally described DSE lineages from distantly related families can be useful in future comparative studies focusing on whether these endophytes have functional similarities, or whether the eponymous morphological characteristics are the only similarities. Since root-associated pleosporalean fungi, including Darksidea species, seem to be common in arid and semiarid regions of different continents (e.g. Porras-Alfaro et al. 2008 , Su et al. 2010 , Knapp et al. 2012 ), they can be used in experiments aimed at broadening our understanding the function of DSE fungi in arid and semiarid environments.",
"introduction": "INTRODUCTION Dark septate endophytes (DSE) compose a form-group of root associated fungi (RAF) ( Jumpponen & Trappe 1998a ), which generally have melanised hyphae, colonise the root epidermis and the cortex inter- and intracellularly and form densely septated intracellular structures, called microsclerotia ( Jumpponen & Trappe 1998a , Barrow & Aaltonen 2001 , Yu et al. 2001 , Addy et al. 2005 , Mandyam & Jumponnen 2008 , Peterson et al. 2008 ). DSE fungi occur in all climate regions and major biome types ( Mandyam & Jumponnen 2005 , Rodriguez et al. 2009 , Porras-Alfaro & Bayman 2011 ) and are relatively frequent in extreme and nutrient-limited environments such as arid and semiarid areas ( Kovács & Szigetvári 2002 , Rodriguez et al. 2009 , Khidir et al. 2010 ). Although there is an increasing research interest in DSE, our knowledge on the diversity and function of these fungi is limited, especially compared to mycorrhizal fungi. No sexual morph of DSE is known and their sexual relations are not completely understood ( Jumpponen & Trappe 1998a , Grünig et al. 2008 , Rodriguez et al. 2009 ). Even conidiogenesis is infrequent and conidiogenous processes have only been induced in a minority of isolates after specific treatments ( Jumpponen & Trappe 1998a , Sieber & Grünig 2006 ). Dark septate endophytes represent a group of fungal endophytes from different ascomycete lineages forming similar structures ( Jumpponen & Trappe 1998a ). They generally belong to numerous orders of phylum Ascomycota (e.g. Capnodiales , Chaetothyriales , Eurotiales , Helotiales , Hypocreales , Micro-ascales , Pleosporales , Sordariales , Xylariales – see e.g. Jumpponen & Trappe 1998a , Addy et al. 2005 , Newsham 2011 , Knapp et al. 2012 , Andrade-Linares & Franken 2013 ). The majority of our knowledge on DSE fungi has thus far been gained through studies of fungi in the Helotiales (class Leotiomycetes ) focusing on several DSE fungi e.g. Cadophora finlandica (≡ Phialophora finlandica ) and the widely studied Phialocephala fortinii s.l. – Acephala applanata species complex (PAC) (e.g. Fernando & Currah 1996 , Jumpponen & Trappe 1998b , Caldwell et al. 2000 , Tellenbach et al. 2011 , Reininger et al. 2012 ). Pleosporales , which is the largest order of Dothideomycetes ( Schoch et al. 2009 , Zhang et al. 2012 ), is one of the most represented orders in DSE communities of semiarid areas ( Porras-Alfaro et al. 2008 , Knapp et al. 2012 ). In a previous study, the compositional diversity of DSE fungi colonising native and invasive plants of semiarid sandy areas on the Great Hungarian Plain was investigated ( Knapp et al. 2012 ). Based on an in vitro resynthesis assay, isolates of 14 lineages were considered as DSE fungi, several groups of which could not be identified. Three of these groups (DSE-4, DSE-8 and DSE-7 sensu Knapp et al. 2012 ) clustered in the Pleosporales . In case of DSE-4, no similar sequences of either cultured or uncultured fungi were found in public databases. Although group DSE-7 was found to be the third most frequent DSE clade ( Knapp et al. 2012 ), and similar findings were obtained in other studies ( Porras-Alfaro et al. 2008 , Khidir et al. 2010 , Herrera et al. 2010 ), the identity and phylogenetic placement of this taxon and other DSE fungi in the Pleosporales remained unclear. The main aim of our study was therefore to conduct a taxonomic study of the pleosporalean DSE groups originating from semiarid sandy areas ( Knapp et al. 2012 ). We further aimed to collect more isolates of group DSE-7 to study the intragroup heterogeneity, and conduct a multi-locus molecular phylogenetic and morphological comparison of isolates.",
"discussion": "DISCUSSION In spite of the increasing general interest in DSE, our knowledge on the diversity and distribution of these fungi is still limited. Only c. 30 DSE species have been described to date ( Wang & Wilcox 1985 , Jumpponen & Trappe 1998a , Knapp et al. 2012 , Andrade-Linares & Franken 2013 , Walsh et al. 2014 ). Further-more, only a fraction of these DSE species have been well-defined and tested to determine if they really fulfil the definition of DSE. To the best of our knowledge the Pleosporales includes several DSE fungi: Rhizopycnis vagum ( Andrade-Linares et al. 2011 , DSE-3 in Knapp et al. 2012 ), ‘ Phoma’ sp. ( Junker et al. 2012 ), Periconia macrospinosa ( Mandyam et al. 2010 , Knapp et al. 2012 ), ‘Unknown 1 d ’ and ‘Unknown 2 e ’ isolates (sensu Jumpponen & Trappe 1998a ), Alternaria sp. (DSE-5), Setophoma sacchari (DSE-6), Embellisia sp. (DSE-9), Curvularia sp. (DSE-10) and the eight new species of Aquilomyces , Flavomyces and Darksidea described in the present study. Although finding discriminating morphological features would have been preferred, this was not possible for all taxa, and thus we employed genealogical concordance of several loci to aid us in the description of these taxa. The three new genera described here nested in the suborder Massarineae in Pleosporales , which comprises mostly saprobic species of terrestrial or aquatic environments ( Zhang et al. 2012 ). The new genus Darksidea belongs to the Lentitheciaceae ( Zhang et al. 2009 ), although this family is still poorly resolved. The morphological features of Darksidea make the Lentitheciaceae even more diverse, suggesting that there is a lack of reliable, unique morphological features for the family ( Zhang et al. 2012 ). Lentitheciaceae comprises saprobic fungi living in freshwater and wet habitats, occurring on angiosperm debris ( Zhang et al. 2009 ). However, species belonging to Darksidea originated from roots of grasses and soils from arid and semiarid environments. Zhang et al. (2009) reported that the Lentitheciaceae was split into two subclades based on molecular phylogenetic data, with species in subclade ‘V-A’ occurring exclusively on monocotyledons, while species in subclade ‘V-B’ were associated with dicotyledonous woody substrates in freshwater environments. However, the growing number of sampled taxa changed and masked these differences ( Zhang et al. 2012 ), and it was further supported by our findings. Sexual morphs in Lentitheciaceae have lenticular ascomata, trabeculate to broadly cellular pseudoparaphyses, cylindrical to clavate asci with short pedicels, uni-, tri- to multiseptate, fusiform or filiform ascospores ( Zhang et al. 2009 ). Tingoldiago \n graminicola , the sister group of genus Darksidea , is a freshwater ascomycete characterised by flattened, globose, immersed to erumpent ascomata, and numerous cellular pseudoparaphyses ( Hirayama et al. 2010 ). The ascomata, asci and pseudoparaphyses of Darksidea support it as pleosporalean ( Zhang et al. 2009 , 2012 ), although morphologically it is clearly distinct from the Lentitheciaceae , a family in which it clusters. Aquilomyces clusters in the Morosphaeriaceae , representing a new basal genus among the genera Heliascus , Kirschsteiniothelia , Morosphaeria , Pithomyces and Asteromassaria ( A . pulchra ), albeit the latter is just ‘tentatively assigned’ in Morosphaeriaceae ( Zhang et al. 2012 ). The Morosphaeriaceae was introduced by Suetrong et al. (2009) as one of the current five families of Massarineae ( Zhang et al. 2012 ), and represents a well-supported clade including the genera Morosphaeria , Helicascus and Kirschsteiniothelia ( Suetrong et al. 2009 ). This family includes mostly marine species with subglobose ascomata and 8-septate ascospores in thick-walled, fissitunicate asci. Flavomyces fulophazii formed a well-supported clade with Massarina igniaria , Periconia macrospinosa and Noosia banksiae , but this clade did not form a monophyletic group with the other members of family Massarinaceae including the type species Massarina eburnea . Massarina igniaria nested as a basal lineage to the family in previous phylogenetic analyses encompassing more loci and a smaller set of related taxa ( Zhang et al. 2009 , 2012 ). After the addition of Flavomyces fulophazii , Noosia banksiae and P. macrospinosa , these taxa clustered separately, representing an apparently unknown family. The genus Darksidea described in this study has been reported from several countries according to previous publications and GenBank entries. The first representative of Darksidea was detected from a root of Stipa hymenoides originating from a semiarid grassland in Utah, USA (GenBank AY929107, Hawkes et al. 2006 ). Sánchez-Márquez et al. (2008 ) also isolated a strain (Unidentified Pleosporales B, GenBank AM921730) from a rhizome of Ammophila arenaria in sand dunes of the northern coast of Galicia (Spain). Green et al. (2008) gained ITS sequences of Darksidea from roots of a dominant grass species, Bouteloua gracilis , from rhizosphere soil and from biological soil crusts from semiarid grassland in central New Mexico, USA. In their study on soil fungal communities in the same semiarid grassland, Porras-Alfaro et al. (2011) obtained further Darksidea sequences from biological soil crusts. In a previous study focusing on the root-associated fungal community of B. gracilis , Porras-Alfaro et al. (2008 ) found that the RAF community was dominated by a novel group of dark septate fungi within the order Pleosporales , named ‘clade A’, including ‘subclade B’ and ‘subclade C’. Analyses of those ITS sequences with those of our isolates show that subclade B unambiguously grouped into Darksidea and is most probably grouped with the four species described here. Khidir et al. (2010) also obtained several sequences belonging to the aforementioned ‘subclade B’, and hypothesised that the clade is a Paraphaeosphaeria species ( sensu Câmara et al. 2001 ). This taxonomic hypothesis – later used in Herrera et al. (2010) , too – cannot be supported, as Paraphaeosphaeria is unambiguously nested in Montagnulaceae ( Verkley et al. 2014 ). Herrera et al. (2010) compared the RAF communities of B. gracilis along a latitudinal gradient and concluded that the most consistent and common members of the RAF community belonged to this clade. Sequences of Darksidea were also gained from the dung of mammalian herbivores from two distinct grasslands ( Herrera et al. 2011a ), and from a root of S. cryptandrus in a rainfall manipulation experiment study ( Herrera et al. 2011b ). The genus was also found in the Eurasian Steppe Belt in both the western ( Knapp et al. 2012 , see above) and the eastern region ( Su et al. 2010 ). Su et al. (2010) investigated fungal endophytes of the grass Stipa grandis in the semiarid steppe zone of the Inner Mongolia Plateau, and one of the isolates obtained from a root of S. grandis (named Pleosporales sp. 3 (GenBank HM007086)) was conspecific with D. alpha . Based on this finding we assume that Darksidea is one of the common members of the core DSE community hypothesised to be shared by the semiarid grassland areas worldwide ( Knapp et al. 2012 ). Although our trials to induce sporulation were not consistent and reproducible, we could detect ascomata, and in several cases asci and ascospores. Although asexual sporulation is also rarely observed among many of the DSE fungi ( Jumpponen & Trappe 1998a ), it could be induced in culture (e.g. Sieber & Grünig 2006 ), e.g. extreme long incubation times at low temperatures ( Wang & Wilcox 1985 , Grünig et al. 2009 ). Previous studies hypothesised that the sexual stage of some DSE exists and/or existed (e.g. Grünig et al. 2004 ). Zaffarano et al. (2011) studied the MAT locus structure of thousands of strains of 19 PAC species from various hosts, continents and ecosystems and hypothesised that cryptic sexual reproduction regularly occurs in the PAC. Although data from population genetic studies, genome analysis and attribution of MAT genes could provide evidence of a possible sexual state (e.g. Zaffarano et al. 2011 ), inducing the sexual morph for DSE fungi has to date been unsuccessful. Although sterile ascocarpium-like structures with no ascospores were observed in studies investigating other DSE species in Acephala sp. (UAMH 6816, Currah et al. 1993 ), to our best knowledge, the present study is the first in which sexual morphs formed by DSE fungi were observed. This demonstrated capability for ascospore production in DSE fungi might help us to better understand the widespread and common occurrence of these root colonizing fungi. Conclusions DSE fungi constitute a polyphyletic form-group of fungi representing several orders of the Pezizomycotina . Not only are their functional contributions to ecosystems ‘elusive’ ( Mandyam & Jumpponen 2005 ), but also, their taxonomic diversity is far from known. The three genera described from a semiarid sandy region in the present study illustrate that even distinct new lineages of DSE can still be identified. These well-defined and formally described DSE lineages from distantly related families can be useful in future comparative studies focusing on whether these endophytes have functional similarities, or whether the eponymous morphological characteristics are the only similarities. Since root-associated pleosporalean fungi, including Darksidea species, seem to be common in arid and semiarid regions of different continents (e.g. Porras-Alfaro et al. 2008 , Su et al. 2010 , Knapp et al. 2012 ), they can be used in experiments aimed at broadening our understanding the function of DSE fungi in arid and semiarid environments."
} | 3,965 |
31515373 | null | s2 | 9,721 | {
"abstract": "No abstract available"
} | 5 |
27842347 | PMC5226080 | pmc | 9,722 | {
"abstract": "Microbes provide an intriguing system to study social interaction among individuals within a population. The short generation times and relatively simple genetic modification procedures of microbes facilitate the development of the sociomicrobiology field. To assess the fitness of certain microbial species, selected strains or their genetically modified derivatives within one population, can be fluorescently labelled and tracked using microscopy adapted with appropriate fluorescence filters. Expanding colonies of diverse microbial species on agar media can be used to monitor the spatial distribution of cells producing distinctive fluorescent proteins. Here, we present a detailed protocol for the use of green- and red-fluorescent protein producing bacterial strains to follow spatial arrangement during surface colonization, including flagellum-driven community movement (swarming), exopolysaccharide- and hydrophobin-dependent growth mediated spreading (sliding), and complex colony biofilm formation. Non-domesticated isolates of the Gram-positive bacterium, Bacillus subtilis can be utilized to scrutinize certain surface spreading traits and their effect on two-dimensional distribution on the agar-solidified medium. By altering the number of cells used to initiate colony biofilms, the assortment levels can be varied on a continuous scale. Time-lapse fluorescent microscopy can be used to witness the interaction between different phenotypes and genotypes at a certain assortment level and to determine the relative success of either.",
"introduction": "Introduction In the last decades, microbes have been recognized as social communities associated with various ecosystems on earth 1,2 . In contrast to planktonic cultures used in general laboratory practice, microbes in the environment show a diverse range of spatial community structures depending on the ecological setting. Simple microbial systems can be utilized to understand the consequence of spatial structures on the evolution of social interactions 3,4 . Publications in the last 2-3 years using both eukaryotic and prokaryotic model systems highlighted the impact of spatial structures on the stability of cooperation within microbial populations 5-8 . Additionally, obligate interactions among microbes, e.g. metabolic cross-feeding, might also alter the spatial distribution of interacting partners 9-11 . The influence of spatial structure in these studies is mostly examined using surface attached sessile cells inhabiting the so-called biofilms or in colonies growing on the surface of an agar medium. Genetic drift resulting in high spatial assortment can be observed in microbial colonies where nutrient depletion at the edge of a cell division mediated expansion results in series of genetic bottlenecks that causes high local fixation probability for certain clonal linages 12 . Genetic drift can be therefore employed to examine the role of spatial segregation in microbial colonies. In the environment, biofilms are multispecies communities surrounded by self-produced polymeric matrix 13 . Biofilm structure, function and stability depend on a complex network of social interactions where bacteria exchange signals, matrix components and resources, or compete for space and nutrients using toxins and antibiotics. Bacillus subtilis is a soil dwelling and root-colonizing bacterium that develops highly organized biofilm communities 14 . In analogy to social insects, B. subtilis cells employ a division of labor strategy, developing subpopulations of extracellular matrix producers and cannibals, motile cells, dormant spores and other cell types 15,16 . The differentiation process is dynamic and can be altered by environmental conditions 17,18 . Strategies of surface colonization by bacteria can be easily manipulated under laboratory conditions by modifying the agar concentration in the growth media. At low agar levels (0.2-0.3%), bacteria harboring active flagella are able to swim, while semi-solid agar (0.7-1% agar) facilitates flagellum driven community spreading, called swarming 19-21 . In the absence of flagellum, certain bacterial strains are able to move over semi-solid medium via sliding, i.e. growth dependent population expansion facilitated by exopolysaccharide matrix and other secreted hydrophobin compounds 22-24 . Finally, bacteria which are capable of biofilm development form architecturally complex colonies on hard agar medium (1.2-2%) 14,17,25 . While these traits are examined in the laboratory by precisely adjusting the conditions, in natural habitats these surface-spreading strategies might transit gradually from one to another depending on the environmental conditions 26 . While single cell based motility is critical during initiation of biofilm development at the air-liquid interface in both Gram-positive and -negative bacteria 27 , complex colony biofilms of B. subtilis are not affected by deletion of flagellar motility 28 . However, spatial organization during the development of B. subtilis colony biofilms depends on the density of the bacterial inoculum used to initiate the biofilm 8 . Here, we use B. subtilis to show that spatial segregation during surface colonization depends on the mechanism of population level motility ( i.e. swarming or sliding), and colony biofilm development depends on the founder cell density. We present a fluorescent microscopy tool that can be applied to continuously monitor microbial biofilm growth, surface colonization and assortment at the macro scale. Further, a quantification method is presented to determine the relative strain abundance in the population.",
"discussion": "Discussion The availability of a fluorescent toolbox for bacteria facilitates not only the study of heterogeneous gene expression 30,31 and protein localization 32 , but also the analysis of spatial distribution of strains within a population 8 . Fluorescent markers with sufficiently different excitation and emission wavelengths allow to distinctly localize two strains that otherwise are indistinguishable from each other when mixed. The described protocol can be employed for observing the population dynamics in mixed cultures, e.g. competition experiments or synergism between strains or species. The ability to determine the relative abundances of fluorescently labelled strains in a mixed population is not restricted to surface attached swarming, sliding, or biofilm colonies, but can also be used for other multicellular biofilm systems, including submerged, flow cell or air-medium interface biofilms 27,33-35 . While the presented technique is a powerful tool to detect spatial distribution of strains and design competition experiments, it also allows following gene expression heterogeneity in expanding colonies. The culturing conditions described here apply for B. subtilis and the exact parameters for expansion on agar media might require optimization for other species or strains 20 . Placing the samples in an incubation chamber while imaging permits the experimenter to follow the population dynamics in time, although attention should be given to the humidity level within the chamber during the incubation. The techniques described here also require the genetic modification of the examined bacterial strains so that the strains express fluorescent markers which can be distinguished from each other. Moreover, besides having distinct excitation and emission spectra, it is recommended that the two chosen fluorescent markers have similar quantum yields ( i.e. ratio of absorbed photons that are emitted) and are expressed in a comparable level. In addition, relative intensity changes in time can be measured and normalized to an early time-point of an experiment. The relative increase or decrease can be then compared between different fluorophores with different quantum efficiencies. For the presented experimental system, different green- and red-fluorescent proteins were tested previously 36,37 to select for the most optimal fluorescent pairs that can be detected in B. subtilis . The optimal exposure time should be determined for each fluorescent protein and sample. Certain cell densities or multiple layers of cells might be required to detect the signal efficiently within the population. Certain fluorescent proteins might have low intensities in the bacterial cells due to inefficient expression and/or translation of the protein and thus low quantum yield. Such inefficient fluorescent markers could reduce the sensitivity of the system and extend the time needed to detect the bacterial strains possibly resulting in cytotoxicity by the excitation light. The fluorescent intensities can be accordingly modified by altering the promoter used to express the fluorescent reporter coding gene. An expression level that is too high could result in unnecessary overproduction of the fluorescent protein leading to detrimental fitness costs for the bacterium. When performing competition experiments, one should consider the cost of particular fluorescent protein production in the cells. Control experiments, where the fluorescent markers are swapped between competed strains or where two isogenic strains differing only in their fluorescent markers are competed against each other, are always required to determine any bias toward one marker. The lifetimes of the fluorescent proteins within the cells might also affect the measured intensity. In addition, the autofluorescence of certain bacterial species might require the use of different fluorescent markers other than described here. To precisely determine the spatial distributions and abundances of the distinct bacterial strains, the background signal originating from the first fluorescent protein while using the fluorescence filter for the second fluorescent marker and vice versa should be individually tested on monoculture samples (containing bacteria producing only one marker). This allows the subtraction of overlapping fluorescent signal intensities. Importantly, as the stereomicroscope records the fluorescence signal from above the expanding colony, the presented protocol is convenient to determine the spatial arrangement in two dimensions. The architecture of the expanding bacterial population could result in varying fluorescence levels ( i.e. wrinkle-like structures might contain more cells displaying higher local fluorescence intensities). Therefore, the described analysis of the images determines the spatial distribution, but not the abundance of the strains within a certain location. Previous protocols described the sample preparation for swarming 20 or fluorescence imaging of population dynamics in bacterial colonies 38 , but our protocol combines these techniques. Other microscopy techniques that permit the observation of three dimensional resolution of the population structure ( e.g. confocal laser scanning microscopy 39,40 or structured illumination microscopy 41 ) can be applied for samples with increased structural complexities. These additional techniques also support single cell based detection of the strains 31 that is not available using stereomicroscopes."
} | 2,786 |
21803542 | null | s2 | 9,723 | {
"abstract": "The long short term memory (LSTM) is a second-order recurrent neural network architecture that excels at storing sequential short-term memories and retrieving them many time-steps later. LSTM's original training algorithm provides the important properties of spatial and temporal locality, which are missing from other training approaches, at the cost of limiting its applicability to a small set of network architectures. Here we introduce the generalized long short-term memory(LSTM-g) training algorithm, which provides LSTM-like locality while being applicable without modification to a much wider range of second-order network architectures. With LSTM-g, all units have an identical set of operating instructions for both activation and learning, subject only to the configuration of their local environment in the network; this is in contrast to the original LSTM training algorithm, where each type of unit has its own activation and training instructions. When applied to LSTM architectures with peephole connections, LSTM-g takes advantage of an additional source of back-propagated error which can enable better performance than the original algorithm. Enabled by the broad architectural applicability of LSTM-g, we demonstrate that training recurrent networks engineered for specific tasks can produce better results than single-layer networks. We conclude that LSTM-g has the potential to both improve the performance and broaden the applicability of spatially and temporally local gradient-based training algorithms for recurrent neural networks."
} | 389 |
36713315 | PMC9802271 | pmc | 9,724 | {
"abstract": "Abstract The intertwining of strands into 3D spirals is ubiquitous in biology, enabling functions from information storage to maintenance of cell structure and directed locomotion. In synthetic systems, entwined fibers can provide superior mechanical properties and act as artificial muscle or structural reinforcements. Unlike structures in nature, the entwinement of synthetic materials typically requires application of an external stimulus, such as mechanical actuation, light, or a magnetic field. Herein, we use computational modeling to design microscale sheets that mimic biology by transducing chemical energy into mechanical action, and thereby self-organize and interlink into 3D spirals, which spontaneously rotate. These flexible sheets are immersed in a fluid-filled microchamber that encompasses an immobilized patch of catalysts on the bottom wall. The sheets themselves can be passive or active (coated with catalyst). Catalytic reactions in the solution generate products that occupy different volumes than the reactants. The resulting density variations exert a force on the fluid (solutal buoyancy force) that causes motion, which in turn drives the interlinking and collective swirling of the sheets. The individual sheets do not rotate; rotation only occurs when the sheets are interlinked. This level of autonomous, coordinated 3D structural organization, intertwining, and rotation is unexpected in synthetic materials systems operating without external controls. Using physical arguments, we identify dimensionless ratios that are useful in scaling these ideas to other systems. These findings are valuable for creating materials that act as “machines”, and directing soft matter to undergo self-sustained, multistep assembly that is governed by intrinsic chemical reactions.",
"introduction": "Introduction To create synthetic materials that mimic the diversity of movement observed in nature, researchers are designing “active matter,” which consumes chemical energy to undergo motion ( 1–3 ). Active matter exhibits one of the hallmarks of living systems: chemo-mechanical transduction, where chemical reactions break down nutrients to fuel mechanical actions ( 4 ). Through these research efforts, scientists have fabricated a range of active microparticles that individually, or as a self-organized assembly, achieve biomimetic propulsion, i.e., autonomous movement in a straight line or specified direction ( 5–7 ). Rotation constitutes another fundamental component of movement, allowing organisms to change direction in an efficient manner ( 8 , 9 ). Isolated, active particles can rotate by spinning ( 10 ) and assemblies of these particles can form rotating microstructures ( 11 , 12 ). In most cases, the larger, rotating object is composed of rotating particles; there are few examples of active, rotating assemblies formed from units that do not spin ( 13–16 ). Furthermore, these rotating microstructures are typically 2D objects, like flat rotors ( 17 ) or gears ( 18 ), and do not assemble into more functional 3D forms. Recently, computational models were developed to examine active matter with greater structural diversity than hard particles; the systems encompassed active, 2D flexible sheets (from the μm to mm size scale) immersed in a fluid-filled chamber ( 19–21 ). The sheets and/or chamber walls were coated with catalysts and underwent chemo-mechanical transduction as the catalysts decomposed reactants (“nutrients”) into products and thereby “fueled” the motion of the fluid and flexible sheets. The studies revealed that the sheets spontaneously move and morph into a variety of controllable 3D shapes ( 22 , 23 ). Herein, we use computational modeling to design multiple sheets that self-organize into a rotating 3D spiral. Each sheet alone does not rotate, but clustered around a stationary catalytic patch, they rise upward, intertwine with one another, and form a vertical, revolving structure. The dynamic assembly of the sheets grossly resembles the biological interlinking of strands into a 3D helix, as in the formation of DNA, the assembly of microfilaments, and the coordination of flagella. The spontaneous 3D structural organization, intertwining, and rotation observed here, involving sequential coordinated steps, is not commonly evident in synthetic materials systems. This level of autonomous, self-sustained behavior is invaluable for creating materials systems that act as machines ( 24 ), advancing the development of soft robots ( 25 , 26 ), and more generally, providing insight into directing self-organization in nonequilibrium systems ( 27–30 ). The distinctive collective motion of the immersed sheets is initiated by adding appropriate chemical reactants to a liquid-filled chamber, which encompasses an immobilized catalytic patch on the bottom wall (Fig. 1A ). The reactants are catalyzed to generate the reaction products. If these products occupy different volumes than the reactants, then the reaction generates local density gradients, which exert a force on the fluid that propels its motion. (The force that arises from the density gradients is a solutal buoyancy force, as detailed further below.) The flowing fluid in turn drives the sheet upward in a tower-like configuration that experiences an instability. As a result, a new configuration develops where the sheets entwine or “self-link” and undergo the collective swirling shown in Fig. 1(C) . Fig. 1. Dynamic self-assembly and self-rotation of passive sheets. (A) Schematic view of a fluid-filled chamber containing a chemical pump (marked by red circular region of radius R ) and four passive elastic sheets (four different colors are guide to the eye). The inset shows the network of nodes (marked by yellow dots) that form the sheet and the flexible bonds between nodes (white lines). (B) and (C) Inward fluid flow generated by the catalytic patch drags sheets toward the center of the chamber to form a tower-like structure (B) that develops into an interlinked assembly (C). (D) and (E) The interlinked configuration rotates in the presence of convective fluid flow (see Movie S1, Supplementary Material ). (F) The temporal trajectory of the angle (θ) of the yellow sheet demonstrates the periodic rotation of the assembly. Times for the sheets configurations are marked in (F). Stretching and bending moduli of the sheet are \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\kappa _s} = 60\\,\\,{\\rm{pN}}$\\end{document} and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\kappa _b} = 2.25\\,\\,{\\rm{pN\\,\\,m}}{{\\rm{m}}^2}$\\end{document} , respectively. The radius and reaction rate of the catalytic patch respectively are \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$R = 0.5{\\rm{\\,\\,mm}}$\\end{document} and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{patch}}} = 90{\\rm{\\,\\,}} \\mu\\, {\\rm{mol\\,\\,}}{{\\rm{m}}^{ - 2}}{{\\rm{s}}^{ - 1}}$\\end{document} . Eventually, all the reactants are consumed in this energy transducing, dissipative system. The solution, however, can be refueled and the entire process can be revived with the addition of new chemicals to the fluid. Such chemically driven self-linking, self-rotating elastic sheets constitute new modes of dynamic self-assembly and can provide new functionality to microfluidic devices, all without the need for mechanical or electrical pumps. Below, we describe our model for simulating these interconnected dynamic events and detail how various control parameters (e.g., the stiffness and chemical reactivity of the sheets) affect the global behavior of the system. It is worth noting that experimentalists are beginning to examine the behavior of flexible sheets that are coated with catalytic patches and immersed in fluid-filled microchambers. Recent studies ( 31 ) experimentally validated our earlier prediction ( 20 ) that sheets coated with enzymes (catalase) can undergo directed motion and shape-changing when the appropriate reactant (hydrogen peroxide) is added to the solution. The researchers note that the observed behavior can be rationalized in terms of the solutal buoyancy mechanism (described below), as we had predicted ( 32 ) through our computational modeling of chemically active sheets. Hence, the experiments support our observation that the system undergoes chemo-mechanical transduction, where catalytic reactions drive the mechanical deformation of the immersed active layers ( 20 , 21 ). The latter agreement between experiments and modeling gives credence to the new predictions detailed below.",
"discussion": "Results and Discussion Self-linking and rotation of passive elastic sheets We first focus on the dynamic self-assembly and self-rotation of passive elastic sheets in a fluid-filled chamber of lateral dimension \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$4\\,\\,{\\rm{mm}} \\times 4\\,\\,{\\rm{mm}}$\\end{document} and height \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$1.5\\,\\,{\\rm{mm}}$\\end{document} . Figure 1(A) shows the four passive sheets placed symmetrically about a centrally located circular patch, which is coated with the enzyme catalase and acts as the chemical pump. All four sheets are identical in size. The length and width of the sheets are respectively \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$1.95\\,\\,{\\rm{mm}}$\\end{document} and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$0.3\\,\\,{\\rm{mm}}$\\end{document} and the thickness of the sheets is \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$0.26\\,\\,{\\rm{mm}}$\\end{document} . Initially, the sheets are placed parallel to the bottom wall (at height of \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$1.2{r_0}$\\end{document} above the wall) and assume a flat configuration. When hydrogen peroxide ( \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${{\\rm{H}}_2}{{\\rm{O}}_2}$\\end{document} ) is added to the chamber, catalase decomposes hydrogen peroxide into less dense products, water ( \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${{\\rm{H}}_2}{\\rm{O}}$\\end{document} ), and oxygen ( \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${{\\rm{O}}_2}$\\end{document} ) ( 33 , 35 )\n (6) \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$$\\begin{equation*}\n{{\\rm{H}}_2}{{\\rm{O}}_2}\\mathop \\to \\limits^{\\,\\,{\\rm{catalase\\,\\,}}\\,\\,} {{\\rm{H}}_2}{\\rm{O}} + \\frac{1}{2}{{\\rm{O}}_2}.\n\\end{equation*}\n$$\\end{document} Since the solutal expansion coefficient for oxygen is approximately an order of magnitude smaller than that for the hydrogen peroxide, we neglect its contribution to the density variation in the solution ( 35 ). In the systems investigated here, the formation of \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${{\\rm{O}}_2}$\\end{document} bubbles is also ignored ( 40 ) since experiments at comparable conditions showed little or no bubble formation during the catalase-activated decomposition of hydrogen peroxide ( 40 ) Since the product of the reaction is less dense than \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${{\\rm{H}}_2}{{\\rm{O}}_2}$\\end{document} , the product-rich lighter fluid rises upward and generates inward fluid flow toward the center of the patch along the bottom of the chamber. This inward fluid flow acts on the elastic sheets at the center of the patch and drags them upward, against gravity, to form a 3D tower-like assembly (Fig. 1B and Figure S1, Supplementary Material ). The tower can only rise to a particular height until the sheets experience the flow oriented parallel to the top surface (and orthogonal to the vertical line going through the center of the tower). With time, the tower structure becomes unstable and forms an interlinked configuration (see Fig. 1C and Movie S1, Supplementary Material ). The dynamics of the interlinking are analogous to the domino effect. Namely, local fluctuations (numerical in the simulation and thermal in the physical system) cause one of the sheets to preferentially bend downward (breaking the symmetry of the system). Due to steric and hydrodynamic interactions, the bending of the first sheet causes its neighbor to bend; the latter sheet drives the bending of the next until all four sheets are interlinked. This interlinking process and the final steady-state configuration result from the fluid–structure interactions, gravity, and steric repulsion between the sheets. As the first sheet is perturbed sideways, the fluid–structure interactions are no longer completely symmetric and the latter symmetry breaking initiates the motion of the assembly. In the interlinked state, an individual sheet assumes a helical configuration (Fig. 1D and E ). Consequently, the convective flow generates a net torque on the sheet and drives the assembly to rotate about the vertical axis that goes through the center of the patch (Fig. 1D and E ; the formation of the rotating structure can be visualized by viewing Movie S1.) The angle of rotation (θ), measured between the x -axis and the lateral line connecting the center of the patch and the center of the yellow sheet shows periodic motion over time (Fig. 1F ), and thus the assembly has a well-defined angular velocity. This rotating state is stable until the reactant is consumed (corresponding to a few hours in real time, as indicated in Fig. 1F ). Given the initial symmetric placement of the sheets (Fig. 1A ), both directions of rotation (clockwise or counterclockwise) are equally probable, and the direction of rotation determines how the sheets are intertwined. The Gauss linking number ( 41 , 42 ) serves as an order parameter that characterizes the degree of entanglement between two curves. The linking number, \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$Ln$\\end{document} , of two 3D curves \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${c_1}$\\end{document} and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${c_2}$\\end{document} are defined as\n (7) \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$$\\begin{equation*}\nLn\\left( {{c_1},\\,\\,{c_2}} \\right) = {\\smallint _{{c_1}}}{\\smallint _{{c_2}}}\\left( {d{\\boldsymbol{ r}_1} \\times d{\\boldsymbol{ r}_2}} \\right) \\cdot \\frac{{{\\boldsymbol{ r}_2} - {\\boldsymbol{ r}_1}}}{{|{\\boldsymbol{ r}_2} - {\\boldsymbol{ r}_1}{|^3}}}\\,\n,\n\\end{equation*}\n$$\\end{document} where \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\boldsymbol{ r}_1}$\\end{document} and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\boldsymbol{ r}_2}$\\end{document} are the position vectors on the curves \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${c_1}$\\end{document} and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${c_2}$\\end{document} , respectively. We use the central line along the long axis of the sheets to compute the linking number (see Supplementary Information for details). Figure 2(A) and (C) shows the linking number between the yellow and green sheets as a function of time for two different initial configurations of the sheets (at a fixed value of the reaction rate at the catalytic patch). In both cases, the sheets are placed symmetrically about the patch, but at different distances from the patch center ( Figure S2, Supplementary Material ). The assembly begins to rotate when the linking number becomes nonzero. The magnitude of the linking numbers for both cases are the same (since the reaction rate is fixed; see below); however, the sign of the linking number can be either positive or negative. The entwined assembly rotates clockwise for the positive value of the linking number (Fig. 2B ) and counterclockwise for the negative values (Fig. 2C ). Fig. 2. Direction and angular speed of rotating assembly, and vorticity of the flow. (A) Gauss linking number ( \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$Ln$\\end{document} ) between yellow and green sheets are plotted for two different initial configurations, where the sheets are initially placed symmetrically about the patch, but at different distances from the center of the patch ( Figure S2, Supplementary Material ). (B) and (C) The direction of rotation depends on the sign of the linking number. For clockwise (B) and counterclockwise (C) rotation, the linking number is positive and negative, respectively. (D) The maximum magnitude of the z -component of vorticity ( \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$|{\\omega _{\\rm{z}}}{|_{{\\rm{max}}}}$\\end{document} ) in the chamber as a function of time. The exponential fit (red line) indicates that \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$|{\\omega _{\\rm{z}}}{|_{{\\rm{max}}}}$\\end{document} increases exponentially from its minimum value (at t = 53.3 min) to a stable value, corresponding to a steady rotating state. (E) The mean angular speed increases with the reaction rate of the patch. The error bar denotes the standard deviation from five initial configurations; inset shows the typical configuration of the rotating assembly. Stretching and bending moduli of the sheets are the same as Fig. 1 . The reaction rates of the catalytic patch in (A–D) are the same as Fig. 1 . The transition from the nearly vertical tower structure of the assembly (Fig. 1B ) to the rotating state (Fig. 1D ) is marked by a linear instability, as can be seen from Fig. 2(D) . In particular, we compute the component of the vorticity of the fluid along the z direction, \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\omega _{\\rm{z}}} = {( {\\boldsymbol{ \\nabla} \\times \\boldsymbol{ u}} )_{\\rm{z}}}$\\end{document} and plot the maximum magnitude of the z -component of the fluid vorticity vector, \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$|{\\omega _{\\rm{z}}}{|_{{\\rm{max}}}}$\\end{document} , as a function of time. At time t = 53.3 min, \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$|{\\omega _{\\rm{z}}}{|_{{\\rm{max}}}}$\\end{document} displays an exponential increase from its minimum value to the value at the assembly of the rotating state. The exponential evolution is typical of a linear instability in the regime that precedes the formation of the rotating state ( 43 ). The magnitudes of the fluid vorticity in the chamber for different times are shown in Figure S3 (Supplementary Material) . The plots show that magnitude of the fluid vorticity around the elastic sheets affects the rotational behavior of the assembly. From the vorticity, we can obtain the angular speed of the rotating assembly and determine parameters that affect the speed. Figure 2(E) reveals a pronounced dependence of the mean angular velocity (Ω; averaged over five initial configurations) on the reaction rate at the catalytic patch, with Ω increasing with increases in the reaction rate. As the rate of reaction increases, the magnitude of the fluid flow also increases ( Figure S4A, Supplementary Material ), which leads to an increase in Ω. Thus, the angular speed (or frequency) of the rotating assembly can be tuned by varying the reaction rate of the patch (i.e., by preparing systems with a higher or lower areal concentration of the enzyme). The state diagram in Fig. 3 further details the influence of the reaction rate on the rotating assembly. We anticipate that the stability of the rotating state is likely to depend on the elasticity of the sheets, reasoning that a stiff sheet would be less sensitive to the flow field than a flexible one. Hence, the state diagram is plotted with the bending modulus of the sheet on the vertical axis and the reaction rate at the patch on the horizontal axis. The diagram indicates regions where the rotating state is stable and where the rotating structure is not formed. To obtain the stable rotating state, the catalytic reaction rate (and thus magnitude of the fluid flow in the chamber) must be above a critical value so that the forces from the fluid flow can morph the sheet to the interlinked configuration (Fig. 3B ) for a sustained period of time. The temporal behavior (Fig. 3D ) for the configuration in Fig. 3(B) shows that the center of each sheet undergoes regular spatial oscillations in the rotating state. Here, the initial concentration of reactant was chosen so that the sheets’ rotational motion is stable for hours, allowing us to carefully focus on this behavior. (As shown in Figure S4B (Supplementary Material) , the duration of stable rotation depends on the initial concentration of the reactants.) Fig. 3 State diagram of the rotating and nonrotating states of passive elastic sheets. (A) State diagram of passive elastic sheets as a function of bending modulus of the sheets and reaction rate of the catalytic patch. The rotating and nonrotating states are marked by squares and circles, respectively. The colors are guide to the eye. (B) The configuration of the sheets in the rotating state is a stable interlinked structure. (C) The typical configuration in the nonrotating state is an irregular one and changes with time (see Movie S1, Supplementary Material ). (D) and (E) The temporal evolution of height of the top of sheets ( \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${z_{\\rm{s}}}$\\end{document} ) are shown for the rotating (D) and nonrotating state. (F) The magnitude of the linking number between adjacent sheets and diagonally opposite sheets are shown as a function of time. Here, the stretching modulus of the sheets is the same as in Fig. 1 . The bending modulus of the sheets in (B)–(F) is the same as in Fig. 1 . The reaction rates of the catalytic patch in (B), (D), and (F) and in (C) and (E) are respectively \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$90{\\rm{\\,\\,}} \\mu\\, {\\rm{mol\\,\\,}}{{\\rm{m}}^{ - 2}}{{\\rm{s}}^{ - 1}}$\\end{document} and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$111{\\rm{\\,\\,}} \\mu\\, {\\rm{mol\\,\\,}}{{\\rm{m}}^{ - 2}}{{\\rm{s}}^{ - 1}}$\\end{document} . For a higher reaction rate ( \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{patch}}}{\\rm{\\,\\,}} > 95 \\mu { \\rm{mol\\,\\,}}{{\\rm{m}}^{ - 2}}{{\\rm{s}}^{ - 1}}$\\end{document} ), the fluid flow is sufficiently large in magnitude that each sheet follows the closest convective rolls generated in the fluid and does not form the stable interlinked configuration (Fig. 3C ) that is necessary for the stable rotation of the assembly. In the nonrotating state, the sheets move irregularly within the chamber (Fig. 3E ; Figure S5 and Movie S1, Supplementary Material ). The temporal motion of the height of the top of sheets ( \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${z_{\\rm{s}}}$\\end{document} ) in Fig. 3(D) provides additional insight into the dynamics of the rotating assembly and symmetries in the conformations among the different sheets. After a relatively short time, all the curves for \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${z_{\\rm{s}}}$\\end{document} versus time exhibit pronounced oscillatory behavior. For a given curve, the transition from the nonoscillatory to oscillatory state reflects the structural transition from the stationary tower to the regularly rotating assembly. Notably, the oscillations of the yellow and blue sheets are approximately in phase, as are the oscillations between the green and purple sheets. Furthermore, the oscillations between the respective pairs are approximately out of phase. As seen in Fig. 1(A) , the blue and purple sheets lie adjacent to each other, as do the green and yellow. The green sheet lies diagonally across from the purple and the yellow sheet lies diagonally across from blue. Figure 3(F) shows the linking number between different pairs of sheets; Ln assumes two values, one for a pair of adjacent sheets and another for pairs of opposite sheets. Due to their closer proximity, the magnitude of the linking number between adjacent pairs of sheets is greater than that of between opposite pairs. The images in the panels of Fig. 2(B) and (C) allows visualization of the similarity in conformations having the same linking number. Additionally, the oscillations between the yellow and green lines in Fig. 3(F) indicate an out-of-phase difference in the motion of adjacent pairs; similar oscillations between the purple and brown lines indicate an out-of-phase difference in the motion between opposite pairs. These observations reveal the complementary motion between one pair of sheets and another. In addition to the reaction rate at the patch, the height of the sheets in the chamber can be tuned by varying the height of the chamber. Since the velocity of the fluid flow increases with the height of the chamber (H), the height of the sheets also increases with H ( Figure S6, Supplementary Material ). To probe the robustness of the interlinked, rotating state, we varied the length of the sheets, considering cases where \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$l{\\,\\,_s} = 1.35\\,\\,{\\rm{mm}},{\\rm{\\,\\,}}1.65{\\rm{\\,\\,mm\\,\\,, and\\,\\,}}1.95{\\rm{\\,\\,mm}}.$\\end{document} (All four sheets in a set are identical in size.) Here, the reaction rate at the patch is fixed to \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{patch}}} = 78{\\rm{\\,\\,}} \\mu\\, {\\rm{mol\\,\\,}}{{\\rm{m}}^{ - 2}}{{\\rm{s}}^{ - 1}}$\\end{document} . The top panels in Fig. 4 demonstrate that the rotating states can be achieved for all three lengths. The configuration of the assembly for the shortest length ( \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${l_s} = 1.35\\,\\,{\\rm{mm}}$\\end{document} ) is different from those for the other two lengths. Consequently, the linking number also depends on the sheet length. For the longer sheets \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$( {1.65\\,\\,{\\rm{mm\\,\\,and\\,\\,}}1.95{\\rm{\\,\\,mm}}} )$\\end{document} , the linking number between adjacent sheets in an assembly are all identical ( Figure S7 and Movie S2, Supplementary Material ). In contrast, for the shortest length, the linking numbers between adjacent sheets in the assembly exhibit two distinct values ( Figure S7, Supplementary Material ). As can be seen in Fig. 4(A)–(C) , the short sheets are not sufficiently long to show the same extent of interweaving possible with longer sheets. We do nevertheless observe stable rotation for assemblies with all three lengths ( Movie S2, Supplementary Material ). Fig. 4. Self-rotation of passive sheets of different lengths and widths. (A)–(C) The configuration of the rotating state of the passive sheets of lengths 1.35 mm, 1.65 mm, and 1.95 mm are respectively shown in A, B, and C. The width of the sheet is 0.3 mm and the reaction rate of the patch is \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{patch}}} = 78{\\rm{\\,\\,}} \\mu\\, {\\rm{mol\\,\\,}}{{\\rm{m}}^{ - 2}}{{\\rm{s}}^{ - 1}}$\\end{document} The snapshots in (A)–(C) are at 108 min after the start of the chemical reaction. (D) and (E) The typical snapshot of the rotating state of passive sheets of widths 0.3 mm, 0.45 mm, and 0.6 mm are shown in D, E, and F, respectively. The length of the sheet is 1.95 mm and the reaction rate of the patch is \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{patch}}} = 66{\\rm{\\,\\,}} \\mu\\, {\\rm{mol\\,\\,}}{{\\rm{m}}^{ - 2}}{{\\rm{s}}^{ - 1}}$\\end{document} . The configurations of the assembly are at 167 min. The sizes of the fluid chamber in (A)–(C) and (D) and (E) are \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$4\\,\\,{\\rm{mm}} \\times 4\\,\\,{\\rm{mm}} \\times 1.5\\,\\,{\\rm{mm}}$\\end{document} and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$6\\,\\,{\\rm{mm}} \\times 6\\,\\,{\\rm{mm}} \\times 2.0\\,\\,{\\rm{mm}}$\\end{document} , respectively. Stretching and bending moduli of the sheet are \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\kappa _s} = 60\\,\\,{\\rm{pN}}$\\end{document} and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\kappa _b} = 2.25\\,\\,{\\rm{pN\\,\\,m}}{{\\rm{m}}^2}$\\end{document} , respectively. To test the consistency of the observed phenomenon, we varied the widths of sheets, considering \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${w_{\\rm{s}}}$\\end{document} \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$= 0.3\\,\\,{\\rm{mm}},{\\rm{\\,\\,}}0.45{\\rm{\\,\\,mm\\,\\,, and\\,\\,}}0.6{\\rm{\\,\\,mm}}$\\end{document} . (The widths of all four sheets for a given value of \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${w_{\\rm{s}}}$\\end{document} are identical.) The bottom panels in Fig. 4 show the dynamic self-assembly and self-rotation of the sheets for all three widths. Rotating configurations shown in Fig. 4(D)–(F) are obtained with the same size of the fluid chamber ( \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$6\\,\\,{\\rm{mm}} \\times 6\\,\\,{\\rm{mm}} \\times 2.0\\,\\,{\\rm{mm}}$\\end{document} ) and with the same reaction rate at the patch, \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{patch}}} = 66{\\rm{\\,\\,}} \\mu\\, {\\rm{mol\\,\\,}}{{\\rm{m}}^{ - 2}}{{\\rm{s}}^{ - 1}}$\\end{document} . As the sheet width is increased, the bending deformation of the sheets due to fluid flow becomes less pronounced. Consequently, the magnitude of the linking number that characterizes the degree of intertwining decreases with the increases in \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${w_{\\rm{s}}}$\\end{document} ( Figure S8, Supplementary Material ; to obtain self-rotation with an even wider sheet, we would need to increase the size of the fluid chamber so that the bottom surface can accommodate four sheets without overlapping.) The interlinking and rotating of the sheets are sufficiently consistent that it is observed with eight passive sheets in the chamber, for two different reaction rates ( Figure S9 and Movie S3, Supplementary Material ). At each reaction rate, the sheets self-assemble into distinct interlinked configurations that spontaneously undergo rotation. The self-rotation can also be achieved for different shapes and sizes of catalytic patches. Figure S10 (Supplementary Material) shows the self-rotation of four passive sheets with a square catalytic patch. Since the area of the square catalytic region is different than the circular patch, we tuned the reaction rate of the patch to obtain the self-rotating state. Furthermore, the assembly and rotating behavior of the elastic sheets can be altered by introducing a ring-shaped catalytic patch ( Figure S11, Supplementary Material ). This collection of simulations indicates that self-rotating behavior is robust and can be achieved with the appropriate choice of reaction rate or elasticity of the sheets. Self-rotation of chemically active sheets The dynamic assembly and rotation of the sheets are altered when the sheets are active, i.e., coated with catalysts. The rotating state of four catalase-coated elastic sheets is shown in Fig. 5A (see Movie S3, Supplementary Material ). Now, the fluid flow in the chamber is generated by catalytic reactions on both the patch and sheets. Hence, for a fixed bending and stretching moduli, the state diagram (Fig. 5B ) of active sheets can be controlled by varying reaction rate of the patch ( \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{patch}}}),$\\end{document} as well as reaction rate of the sheets \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$( {r_m^{{\\rm{sheet}}}} )$\\end{document} . Since catalase-coated sheets also generate flow in the chamber, the \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{patch}}}$\\end{document} necessary to obtain the rotating state of the assembly decreases with an increase of the reaction rate of the sheet \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{sheet}}}$\\end{document} . Similarly, \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{patch}}}$\\end{document} required for the transition from rotating state to nonrotating states (at which sheets follow convective rolls and move irregularly) decreases with the increase of \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{sheet}}}$\\end{document} . For higher reaction rates at the sheets ( \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{sheet}}} > 15{\\rm{\\,\\,}} \\mu\\, {\\rm{mol\\,\\,}}{{\\rm{m}}^{ - 2}}{{\\rm{s}}^{ - 1}}$\\end{document} ), the fluid flow in the chamber is sufficiently large in magnitude that active sheets do not form stable rotating structures for all values of the patch reaction rates considered here. Fig. 5. Self-rotation of chemically active sheets. (A) Fluid flow generated by four catalase-coated elastic sheets and the chemical pump drives the elastic sheets into an interlinked configuration that spontaneously rotate. The reaction rate of the patch and sheets are respectively \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{patch}}} = 78\\,\\, \\mu\\, {\\rm{mol\\,\\,}}{{\\rm{m}}^{ - 2}}{{\\rm{s}}^{ - 1}}$\\end{document} and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{sheet}}} = 6.67\\,\\, \\mu\\, {\\rm{mol\\,\\,}}{{\\rm{m}}^{ - 2}}{{\\rm{s}}^{ - 1}}$\\end{document} . (B) State diagram of the chemically active sheets as a function of the catalytic reaction rate of the patch, \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{patch}}}$\\end{document} and catalytic reaction rate of the sheets, \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{sheet}}}$\\end{document} . Circle and square symbols represent the nonrotating and rotating state of the assembly. (C)–(F) Partially coated sheets are used to achieve stable rotation in a particular direction. The initial positions of the partially coated sheets in (C) and (E) always exhibit clockwise (D) and counterclockwise (F) rotation. The reaction rate of the patch and sheets in (C)–(F) are respectively \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{patch}}} = 78\\,\\, \\mu\\, {\\rm{mol\\,\\,}}{{\\rm{m}}^{ - 2}}{{\\rm{s}}^{ - 1}}$\\end{document} and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{sheet}}} = 2.67\\,\\, \\mu\\, {\\rm{mol\\,\\,}}{{\\rm{m}}^{ - 2}}{{\\rm{s}}^{ - 1}}$\\end{document} . Here, stretching and bending moduli of the sheets are the same as Fig. 1 . Unlike the case for passive sheets where clockwise or counterclockwise rotation is equally probable and cannot be controlled a priori, the directionality of the rotation can be achieved by just partially coating the sheets. Examples of this behavior are shown in Fig. 5(C)–(F) and Movie S4 (Supplementary Material) . The initial arrangement of the partially coated sheets in Fig. 5(C) (and in Fig. 5E ) breaks the rotational symmetry due to the patterning of the sheets and subsequent asymmetry in the fluid flow (with respect to the long axis of the sheet). Thus, the generated fluid flow for the case in Fig. 5(C) always drives the sheets to assemble into a right-handed helical structure (Fig. 5D ), while the case in Fig. 5(E) always yields the left-handed helical structure (Fig. 5F ). Hence, sheets always rotate in clockwise for the case in Fig. 5(C) and counterclockwise for the case in Fig. 5(E) . Influence of different variables on the swirling of the passive sheets Recall that the dynamics of the passive elastic sheets depends on a number of variables, such as reaction rate ( \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{patch}}}$\\end{document} ) and radius ( R ) of the catalytic patch; initial concentration ( \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${C_{10}}$\\end{document} ) and diffusivity ( D ) of the chemical; and density ( \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\rho _s}$\\end{document} ) and elastic properties ( \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\kappa _s}$\\end{document} and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\kappa _b}$\\end{document} ) of the sheet. We consider the size of the chamber and the sheets to be fixed. By analyzing the effects of the individual variables, we establish a dimensionless parameter that governs the dynamics of the sheets. To facilitate this analysis, we characterize the movement and reconfiguration of a sheet from its initial flat state through the order parameter, \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${z_m}$\\end{document} , which is the maximum height of the sheet over time (see Figure S1, Supplementary Material ). We examine the effect of the area of the catalytic patch on the sheet dynamics by varying the radius of the circular patch, R (while keeping all other parameters fixed). For a given reaction rate at the patch ( \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{patch}}}$\\end{document} ), an increase in R enables the patch to catalyze more hydrogen peroxide, leading to an increase in the magnitude of the fluid flow. The increased fluid flow lifts the sheets higher, resulting in higher values of \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${z_m}$\\end{document} for larger R (Fig. 6A ). Consequently, the magnitude of the fluid flow and the dynamics of the sheets is regulated by the parameter \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{patch}}}{R^2}$\\end{document} ( Figure S12A, Supplementary Material ). Fig. 6. Quantifying the effect of various physical parameters. (A) The maximum height of the sheet ( \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${z_m}$\\end{document} ), scaled with the height of the chamber as a function of catalytic reaction rate of the patch, \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{patch}}}$\\end{document} for different radius of the patch, R . All other parameters are kept constant (marked in the inset of E). (B)–(D) The scaled order parameter ( \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${z_m}/H$\\end{document} ) as a function of \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{patch}}}$\\end{document} for different initial concentration of the chemical ( \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${C_{10}}$\\end{document} ), the diffusivity of the chemical ( D ), and the density of the sheets ( \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\rho _s}$\\end{document} ) are plotted in (B), (C), and (D), respectively. \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$D = {D_1}$\\end{document} is the diffusivity of the hydrogen peroxide. (E) When the x -axis is rescaled to the dimensionless parameter, \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$\\tilde A$\\end{document} (Eq. 7 ) all the curves in (A)–(D) roughly collapse into one single curve. Here, stretching and bending moduli of the sheets are \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\kappa _s} = 60\\,\\,{\\rm{pN}}$\\end{document} and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\kappa _b} = 2.25\\,\\,{\\rm{pN\\,\\,m}}{{\\rm{m}}^2}$\\end{document} , respectively. Since an increase in \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${C_{10}}$\\end{document} effectively increases the chemical decomposition by a factor of \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$\\,\\,{C_{10}}/( {{K_M} + {C_{10}}} )$\\end{document} , the parameter \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${z_m}$\\end{document} increases with an increase of \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${C_{10}}$\\end{document} for a constant \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{patch}}}$\\end{document} (Fig. 6B ). Therefore, the parameter \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$\\,\\,r_m^{{\\rm{patch}}}{C_{10}}/( {{K_M} + {C_{10}}} )$\\end{document} also plays a key role in regulating the dynamics of the sheets ( Figure S12B, Supplementary Material ). In addition to initial concentration, the diffusivity of the chemicals contributes in developing the solutal buoyancy force, and hence the strength of the fluid flow. A more rapidly diffusing chemical creates a lower chemical gradient (and lower solutal buoyancy force) in the chamber. Therefore, the magnitude of the fluid flow is lower with higher diffusivity and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${z_m}$\\end{document} decreases with an increase of D for a constant \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{patch}}}$\\end{document} (Fig. 6C ). If the x -axis ( \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{patch}}}$\\end{document} ) is rescaled with the parameter \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{patch}}}/D$\\end{document} , then the order parameter \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${z_m}$\\end{document} for different diffusivities collapse into one curve ( Figure S12C, Supplementary Material ). While the physical parameters characterizing the catalytic patch ( \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{patch}}},R$\\end{document} ) and the chemicals ( \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${C_0},D$\\end{document} ) determine the strength of the fluid flow, which affects the upward motion of the sheets, gravity acting on the sheets (which is proportional to the density of the sheets) counteracts this upward motion. Figure 6(D) shows that the maximum height of the sheets, \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${z_m},$\\end{document} decreases with an increase in the density of the sheets (for a fixed \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{patch}}}$\\end{document} ). Therefore, when the x -axis is rescaled to \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$r_m^{{\\rm{patch}}}/({\\rho _s} - {\\rho _0})$\\end{document} , curves involving different sheet densities collapse onto a single curve ( Figure S12D, Supplementary Material ). The above observations reveal that the dynamics of elastic sheets (of the constant elastic modulus) effectively depend on two competing forces: the solutal buoyancy force and the gravitational force. The ratio of these two forces yields a dimensionless parameter that governs the dynamics of the sheets (see Supplementary Information for details)\n (7) \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$$\\begin{equation*}\n\\tilde A = \\frac{{{\\rho _0}{\\beta _1}{R^2}r_m^{{\\rm{patch}}}{C_{10}}}}{{b{D_1}\\left( {{\\rho _s} - {\\rho _0}} \\right)\\left( {{K_M} + {C_{10}}} \\right)}},\n\\end{equation*}\n$$\\end{document} where b is the thickness of the sheet. If the order parameter for various control parameters is plotted with respect to dimensionless parameter, \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$\\tilde A$\\end{document} , then all the data roughly collapse into one master curve (Fig. 6E ). The resulting master curve quantifies the effect of the different control parameters and provides insight into the competing forces acting on in the system. Namely, to obtain the upward motion of the sheets, the viscous stresses generated by the fluid flow must be greater than the gravitational force acting on the sheets. The generated viscous stresses also compete with elastic forces associated with the bending of the sheets. The corresponding dimensionless ratio for a sheet with flexural rigidity B is given by (see Supplementary Information )\n (8) \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$$\\begin{equation*}\n\\tilde B = \\frac{{B{D_1}\\left( {{K_M} + {C_{10}}} \\right)}}{{l_s^2{w_s}{\\rho _0}{\\beta _1}{R^2}r_m^{{\\rm{patch}}}{C_{10}}}}.\n\\end{equation*}\n$$\\end{document} The typical values of the dimensionless parameters corresponding to the simulation of Fig. 1 are \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$\\tilde A = 8$\\end{document} and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$\\tilde B = 0.0002.$\\end{document}\n\nDiscussion In summary, we demonstrated the spontaneous self-organization of millimeter-sized elastic sheets into interlinked, helical structures that undergo autonomous rotation. This distinctive behavior is due to the solutal buoyancy mechanism, where catalytic reactions on the bottom of the chamber (and on active sheets) generated density variations in the solution. The density variations produced a solutal buoyancy force that drove the fluid flows, which exerted forces on the flexible sheets. The sheets in turn exerted a force on the fluid. This dynamic feedback and the placement of the sheets around a central catalytic pump gave rise to the self-organization and rotation of the spiral assembly. The entire process involved biomimetic chemo-mechanical transduction as the chemical energy released from the reaction was converted into mechanical motion. The interlinking of the sheets into 3D spiral structures can also be viewed as biomimetic, since the 3D spiral resembles a common motif in nature, from the assembly of DNA to the coordinated movement of cilia and flagella. Notably, the isolated sheets do not undergo rotational motion; rotation was observed only when the sheets were interlinked. The latter property is distinct from the typical behavior for synthetic self-organized microrotors, where the individual components typically spin and have intrinsic angular momentum ( 44 , 45 ). In contrast, the individual flexible sheets in our system do not generate torque. The rotational motion of the interlinked sheets was sensitive to several variables. To determine the role of these different variables, we established the ratio of parameters and identified dimensionless numbers that characterize the system's behavior. Expressed in terms of these dimensionless numbers, we can relate the numbers used in our simulations to the relevant range of physical values and thereby guide future experimental studies. For example, the magnitude of the flow velocities is characterized by the ratio of the solutal buoyancy to viscous forces, expressed as a dimensionless Grashof number, \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$Gr = g{\\beta _1}c{L^3}/{\\nu ^2}$\\end{document} , where \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\beta _1}$\\end{document} is the coefficient of solutal expansion, and c is the characteristic chemical variation across the domain. In our studies, the assembly and rotation of the structures were observed for Grashof number \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$\\sim \\! 2.6 \\times {10^2}$\\end{document} . Alternatively, the flow can be characterized by the Reynolds number, \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$Re = uR/\\nu $\\end{document} , and Peclet number \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$Pe = uR/{D_1}$\\end{document} , where \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$R = 0.5\\,\\,{\\rm{mm}}$\\end{document} is the radius of the catalytic patch, and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$u = 33\\,\\,{\\rm{\\mu m}}/{\\rm{s}}$\\end{document} is typical fluid velocity in the chamber. In our simulations, the typical Reynolds number and Peclet number are respectively 0.016 and 11.5. The elastic properties of the sheet are characterized by the dimensionless flexural rigidity, \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$\\tilde B$\\end{document} (Eq. 8 ), which is the ratio of the bending stress to the viscous stress. The typical dimensionless flexural rigidity of the sheet considered in this study is \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$\\sim \\! 0.0002$\\end{document} . There in fact exist both synthetic and biological thin films that exhibit a flexural rigidity comparable to sheets in our model and, therefore, these materials could enable experimental realization of the assembly. For example, ultrathin flexible sheets of functionalized nanoparticles (NPs) ( 46 , 47 ), photo-crosslinkable polymer films ( 48 , 49 ), and sheets composed of oleosin surfactant proteins ( 50 ) can be utilized to form chemically active sheets by incorporating catalysts ( 49 , 51 ) into these films. The relative importance of the solutal buoyancy force relative to the density of the sheets is characterized by the dimensionless parameter \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$\\tilde A$\\end{document} (Eq. 7 ). The typical range of dimensionless parameters \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$\\tilde A$\\end{document} used in our simulations was \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$\\sim \\! 2 - 12.$\\end{document} Finally, this self-rotating system does not require any external input of electrical or mechanical energy. It can be instigated by adding a chemical reactant to the solution; once the reactant is consumed, the rotary motion can be maintained by adding more reactant. Hence, the design concepts presented here can be useful in creating soft robotic structures that display self-sustained action or motion ( 52 ). The self-linking, self-oscillatory systems presented here provide guidance for developing autonomous soft robots ( 53 ) that operate in solution and can work without any external source of energy. Additionally, the self-assembly of elastic sheets into 3D complex structures by chemically generated fluid flow provides new modes of dynamic self-organization."
} | 17,529 |
34325704 | PMC8320212 | pmc | 9,725 | {
"abstract": "Background The intracellular ATP level is an indicator of cellular energy state and plays a critical role in regulating cellular metabolism. Depletion of intracellular ATP in (facultative) aerobes can enhance glycolysis, thereby promoting end product formation. In the present study, we examined this s trategy in anaerobic ABE (acetone-butanol-ethanol) fermentation using Clostridium acetobutylicum DSM 1731. Results Following overexpression of atpAGD encoding the subunits of water-soluble, ATP-hydrolyzing F 1 -ATPase, the intracellular ATP level of 1731(pITF 1 ) was significantly reduced compared to control 1731(pIMP1) over the entire batch fermentation. The glucose uptake was markedly enhanced, achieving a 78.8% increase of volumetric glucose utilization rate during the first 18 h. In addition, an early onset of acid re-assimilation and solventogenesis in concomitant with the decreased intracellular ATP level was evident. Consequently, the total solvent production was significantly improved with remarkable increases in yield (14.5%), titer (9.9%) and productivity (5.3%). Further genome-scale metabolic modeling revealed that many metabolic fluxes in 1731(pITF 1 ) were significantly elevated compared to 1731(pIMP1) in acidogenic phase, including those from glycolysis, tricarboxylic cycle, and pyruvate metabolism; this indicates significant metabolic changes in response to intracellular ATP depletion. Conclusions In C. acetobutylicum DSM 1731, depletion of intracellular ATP significantly increased glycolytic rate, enhanced solvent production, and resulted in a wide range of metabolic changes. Our findings provide a novel strategy for engineering solvent-producing C. acetobutylicum , and many other anaerobic microbial cell factories. Supplementary Information The online version contains supplementary material available at 10.1186/s12934-021-01639-7.",
"conclusion": "Conclusions By overexpression of F 1 -ATPase, we significantly reduced the intracellular ATP level in C. acetobutylicum industrial strain DSM 1731. The overexpression strain 1731(pITF 1 ) exhibited higher cell density, enhanced glycolytic rate, early onset of solventogenesis, significant changes of many metabolic fluxes, and importantly, much improved solvent production than its vector control. Our study, for the first time, demonstrates that the glycolytic rate can be manipulated via altering ATP level in C. aceotbutylicum . This strategy can also be employed for metabolic engineering of other anaerobic fermentations.",
"discussion": "Discussion The biological production ABE process using anaerobe C. acetobutylicum recently attracts extensive interests from both academic and industry owing to the limited supply of petroleum fuel and mounting environmental concerns [ 23 , 24 ]. Many efforts have been done to improve solvent production, including trimming the competing butyrate biosynthesis pathways [ 25 ], overexpressing aldehyde/alcohol dehydrogenase ( adhE1 ) [ 18 ], and screening solvent tolerant mutants [ 26 ]; however, these studies either directly worked on ABE enzymes or purely relied on screening from random mutagenesis. Acid production is one of energy generation pathway of C. acetobutylicum ; hence, inactivation of butyrate production might impair energy production and result in slow growth and low cell density [ 25 ]. Overexpression of aldehyde/alcohol dehydrogenase may result in strong competition of carbon flow with acid biosynthesis, thereby affecting cell growth [ 18 ]. Enhancing cellular tolerance to solvent products is an alternative strategy, but it is in concomitant with rapid accumulation of many random mutations potentially with adverse effects [ 26 ]; this may be inappropriate for continuous industrial production. Here, we employed a rational strategy of enforcing glycolysis via decreasing intracellular ATP level. To the best of our knowledge, this is the first application of such strategy in ABE fermentation by C. acetobutylicum . Different strategies were applied in aerobic microorganisms to reduce intracellular ATP level and reinforce glycolysis; these include construction of ATP futile cycles by overexpression of pyruvate carboxylase and phosphoenolpyruvate carboxykinase in Saccharomyces cerevisiae for ethanol fermentation [ 27 ], and overexpression of phosphoenolpyruvate synthase and pyruvate kinase in E. coli for lactate production [ 28 ]. Notably, both pyruvate carboxylase and pyruvate kinase use pyruvate as a substrate, and ABE fermentation pathway starts with acetyl-CoA from pyruvate cleavage. Therefore, overexpression of these futile cycle enzymes may significantly disturb the flux through pyruvate towards ABE fermentation, thereby unlikely resulting in a high yield of solvents. Whereas overexpression of F 1 -ATPase enforced ATP hydrolysis, without directly competing glycolytic metabolites or diverging glycolytic fluxes to other pathways; it is thus more suitable for metabolic engineering ABE fermentation pathway in C. acetobutylicum . In C. acetobutylicum strain DSM 1731, F 1 F o -ATP synthase is encoded by operon atpIBEFHAGDC . Previous studies has revealed that the membrane-bound proton channel F o is formed by three subunits with the stoichiometry ab 2 c 10–15 , while the soluble F 1 component consists of subunits α 3 β 3 γδε [ 7 , 8 , 15 ]. F 1 F o -ATP synthase catalyzes ATP synthesis using the energy released from proton influx via oxidative phosphorylation; whereas F 1 component has the secondary function of hydrolyzing cytosolic ATP through the action of a rotational mechanism. Overexpression of F 1 subunit genes atpAGD (Additional file 1 : Fig. S1) potentially resulted in accumulation of catalytic F 1 components and excessive intracellular ATPase activity. As expected, we observed a significantly reduced intracellular ATP level and decreased ATP/ADP ratio in C. acetobutylicum (Fig. 1 ), which is consistent with previous findings in aerobic or facultative microbes [ 10 , 12 ]. Previous works showed that the maximal specific growth rate was decreased in ATP depleted strains such as E. coli [ 6 ], B. subtilis [ 13 ] and C. glutamicum [ 14 ]. The unexpected increase of specific growth rate before 6 h in 1731(pITF 1 ) compared to control may be due to the hydrolyzed ATP was compensated by higher glycolytic (e.g. PYK) and acidogenetic fluxes (PYK, ACK, BUTK) (Fig. 4 a, c) which generated ATP in C. acetobutylicum . The traditional batch ABE fermentation suffers from low cell density and low reactor productivity, this could be due to the rapid accumulation of toxic byproducts (e.g. acetate, butyrate, acetone, ethanol and butanol) and/or the insufficient energy supply for bacterial growth [ 23 ]. Anaerobic C. acetobutylicum uses glycolysis, acid fermentation and membrane-bound F 1 F o -ATP synthase to produce ATP. In the present study, the significantly reduced ATP level resulted in substantially increased glucose consumption, fast growth (0–20 h, Fig. 2 ), and reduced acetate and butyrate accumulation (Fig. 3 ) compared to vector control. Consequently, strain 1731(pITF 1 ) had a 22.8% increase at maximal cell density compared to vector control 1731(pIMP 1 ) and a significantly improved solvent volumetric productivity which is necessary to develop effective continuous butanol production [ 29 ]. Clostridial ABE fermentation involves two physiological stages, namely acidogenesis and solventogenesis. In acidogenic phase, cells grow exponentially with the production of acetate and butyrate, thereby causing a dramatic decline of extracellular pH. Previous studies revealed that many factors including low pH, large amount of undissolved organic acids and significantly altered energy charge (ATP/ADP ratio) could induce the expression of solventogenic genes (e.g. adc , ctfA/B and adhE ) [ 30 , 31 ]. In the present study, strain 1731(pITF 1 ) started acid-assimilation and solventogenesis 6-h earlier than vector control. In addition, with metabolic modelling, we identified many elevated metabolic fluxes during acidogenesis and early induction of solventogenic fluxes in 1731(pITF 1 ) (Fig. 4 ). Overall, the performance of the entire ABE fermentation using 1731(pITF 1 ) was significantly improved with better cell growth and higher solvents titer, yield, productivity. High cost is a main limiting factor of commercializing ABE fermentation. The substrate consumption and solvent extraction account for > 30% of total fermentation cost [ 32 ]. The higher yield, titer and productivity developed here could significantly reduce the total cost of ABE fermentation. This work suggests that glycolysis via reducing intracellular ATP level is an effective approach to improve solvent production in clostridial cell factory."
} | 2,191 |
38824184 | PMC11144244 | pmc | 9,728 | {
"abstract": "Miniaturized passive fliers based on smart materials face challenges in precise control of shape-morphing for aerodynamics and contactless modulation of diverse gliding modes. Here, we present the optical control of gliding performances in azobenzene-crosslinked liquid crystal networks films through photochemical actuation, enabling reversible and bistable shape-morphing. First, an actuator film is integrated with additive constructs to form a rotating glider, inspired by the natural maple samara, surpassing natural counterparts in reversibly optical tuning of terminal velocity, rotational rate, and circling position. We demonstrate optical modulation dispersion of landing points for the photo-responsive microfliers indoors and outdoors. Secondly, we show the scalability of polymer film geometry for miniature gliders with similar light tunability. Thirdly, we extend the material platform to other three gliding modes: Javan cucumber seed-like glider, parachute and artificial dandelion seed. The findings pave the way for distributed microflier with contactless flight dynamics control.",
"introduction": "Introduction Stimuli-deformable materials, as a class of innovative substances, possess the unique ability to undergo programmable shape changes in response to specific external stimuli, such as heat, humidity, light, etc. 1 – 4 . In the realm of soft robotics, these materials hold great potential. Unlike traditional rigid robots, a single soft material actuator can morph and alter its shape through contracting, bending, or twisting modes 5 – 7 , allowing for multiple degrees of freedom in robotic operation and remote task execution 8 – 10 . In this context, the advancement of miniature robots, capable of versatile walking on diverse surfaces and environments 11 , 12 , swimming within narrow passages like blood vessels 13 , or executing jumps 14 , has sparked a wave of enthusiasm and pursuit for the next big challenge in the scope of micro-robotics research, that is, the flying robot. To achieve a hovering flying robot (active flight mode) with dimensions in the centimeter scale and weight of hundreds of milligrams, it is essential for the actuating materials to possess high power density and high bandwidth 15 . However, this necessitates the utilization of piezoelectric and dielectric materials that rely on electrical energy transfer, requiring either cables or onboard batteries 16 , 17 . For stimuli (e.g., light) field-deformed materials, despite their potential advantages in miniaturization and wireless control 18 , there are certain limitations that render them unsuitable for hovering robots. One such limitation is their inability to provide the required power output for sustained hovering without compromising other essential functionalities 19 . Additionally, the soft materials may exhibit instability in their response during flight, which could impact the lift generation 20 . Thus, researchers have begun exploring alternative flight options that offer favorability in energy consumption. Dispersal, as a strategy of continuous natural selection, is a crucial process that promotes the distribution and colonization of plant species 21 . In the natural kingdom, many seeds have evolved to utilize wind-assisted passive flight mechanisms effectively, allowing them to disperse to different locations. These mechanisms can be roughly divided into three categories 22 : (1) Seeds with a parachute-like structure, such as dandelions, have a filament structure that creates air resistance; (2) Seeds that can glide in the air, such as Javan cucumber that have wing-like structures, and (3) maple samara and similar species can autorotate in the air, generating lift through a helicopter-like mechanism. Extensive aerodynamic studies of these mechanisms have been conducted, drawing inspiration from natural examples 23 , and pioneering studies about artificial dispersers that work as passive fliers 24 – 26 . Today, artificial dandelions based on smart materials not only exhibit similar properties of separated vortex ring generation and dispersing stably in the air like natural ones but are also capable of light-controllable take-off and landing in response to external stimuli 27 . However, the fragility of the pappus of dandelions limits their load-carrying capacity 27 , 28 , posing challenges for certain propagations that require transporting heavier payloads or operating in harsh environments. For a quantitative comparison of load-carrying between helicopter-like and parachute-like fliers, see Supplementary Fig. 1 . The gliding mechanism, with robust structure and higher loading capacity, has sparked the development of bionic rotary passive fliers across different length scales 29 , 30 , and the creation of light-vapor-powered active robots capable of rotary flying movements while airborne 31 . Besides the aforementioned advantages, current glider-inspired research has also revealed its limitation in the inability to modify aerial gliding performance 32 . A recent development has successfully addressed several important issues in gliding robots 33 , i.e., fast actuation, self-powering, and control of the geometry mid-flight to modulate the aerodynamics while accessing functionalities using onboard sensors and wireless communication. Such an approach is based on a complex integration of multiple electronic elements within a miniaturized origami parachute. Alternately, optical shape morphing polymers set up an intriguing opportunity for controlling responsiveness from stand-off distances, contactlessly. Thus, setting up the question in the context of microfliers: Can light be a direct way to reconfigure the wing geometry and provide dynamic control of the gliding performance? Can a single piece of polymer be used to modulate responsiveness, instead of an integrated electromechanical system built on multiple materials? Furthermore, can this shape-morphing allow for facile tuning of the gliding to elicit a range of modalities and abilities to steer the trajectory? Here, we attempt to explore the aforementioned scientific questions by reporting light-deformable polymers that exhibit optically tuning in gliding performances in the air. It has reversible variations in altitude and rotational speed by altering the illumination between ultraviolet (UV) and visible light (460 nm). Additionally, we also demonstrate the opportunity for miniaturization, as well as the generalization of the concept to other gliding modes.",
"discussion": "Discussion Many microrobotic studies utilize materials that are deformed electrically and magnetically. Here, we emphasize the advantages of the utilization of light fields. Light, i.e., the laser, can propagate over long distances without significant dissipation. Furthermore, remotely directed actuation using light allows for sequestering the power source from the microrobot by eliminating the need for onboard electronics. This offers significant advantages for lightweight the overall structure while still allowing for modulation of its motility from a large stand-off distance. A particular challenge in the realm of sub-gram scale robotics is achieving sustained flight. State-of-the-art approaches rely on onboard electrical power to drive flapping-wing architectures, where advances in miniaturization of drive electronics and wing kinematics have enabled a range of biomimetic designs 16 , 45 , 46 . Intriguingly. photoactive liquid crystalline polymers have been shown to demonstrate actuation cycles that include flapping-like motion in the 10 0 -10 1 Hz scales 19 , 47 . The lift force ( F l ) scales as: F l ∝C L ρU 2 S f , where C L is the lift coefficient (typically ~ of the order of 10 −1 ), ρ is the density of air (~ 1.2 kg m −3 ), U is the wing tip velocity and S f is the area of the flapping wing 48 . For the centimeter-scale wingspans considered here, S f ~ 10 −4 m 2 . At the minimum, to hover, the F l must overcome the weight, which for the structures considered here is ~ 10 −4 N. The frequency of actuation needed to hover is typically in the > 10 2 Hz regime. The frequencies at which photo-responsive materials actuate by bending/flapping are at least an order of magnitude slower. Given this infeasibility, an intriguing possibility is demonstrated in this study, where photo-response is used to direct the dynamics of a passive flyer. In this case, the role of light is not to generate lift but to modulate the flight control surfaces via photomechanical morphing. The first-order kinetics of photoisomerization is associated with the saturation of photostrains with prolonged illumination with UV (trans-cis) or their erasure with visible light (cis-trans) in the azo-LCN. The kinetics of the progressive photostrain generation are intensity-dependent, as shown in Fig. 2c, i . The photoresponse in the material systems explored here is robust (Supplementary Fig. 12 ). Supplementary Fig. 24 shows the deformation of the azo-LCN strip upon UV and blue light irradiation, where during the relaxation, bending occurs at about 100° per second. These time scales are within that needed for modulating the responses during the gliding of the microfilters. To further enhance gliding performance, such as reducing terminal velocity, future research may consider employing lightweight materials, e.g. porous LCN 49 , for constructing both actuators and passive elements. The ability to optimize the response profiles by modulating the balance between drag and the influence of gravity on the payload offers a platform to broadly tune the trade-space of photo-tunable aerodynamics. Recently, many passive flying robots with different design configurations have emerged. Supplementary Table 2 summarizes the key factors in recent publications 27 , 28 , 31 , 33 . Research foci vary across disciplines: Advances in microrobotics drive integrated systems for wireless control, sensing, and communication. However, advances in responsive materials offer multimodal actuation profiles using unconventional stimuli such as light. The ability to photo adapt the aerodynamics of microfibers presents a convergence, where the photo strains are sufficient to induce a significant change in aerodynamic properties without constituting a burden in the payload or onboard power. In conclusion, we have developed an artificial maple samara by assembling a wing-shaped light-responsive film and an additive construct for optimization of mass distribution. This structure exhibits similar airborne autorotating behavior as the natural maple samara. Through external light excitation of ultraviolet and visible, the aerodynamic structure can be reversibly altered via photochemical deformation in LCN-based soft actuator. Placing the artificial seed in a vertical wind tunnel enables observation of reversible changes in altitude and spinning rate controlled by light. We demonstrate that the light can be used to modulate the dispersion of the passive fliers in both indoor and real-world environments. The utilization of photo-responsive materials is also shown to unlock a design space where the fliers can be miniaturized across length scales that span an order of magnitude. Thus, enabling a platform where flight dynamics can be contactlessly tuned. These results present a motif for reimagining how swarms of passive fliers can be controlled by using light."
} | 2,847 |
38915324 | PMC11194708 | pmc | 9,730 | {
"abstract": "The enzymatic decarboxylation of α,β-unsaturated acids using the ferulic acid decarboxylase (Fdc1) enzyme and prenylated flavin mononucleotide (prFMN) cofactor is a potential, environmentally friendly reaction for the biosynthesis of styrene and its derivatives. However, experiments showed that the enzyme activity of Fdc1 depends on the ring structure of prFMN, namely, the iminium and ketimine forms, and the loss of enzyme activity results from prFMN im → prFMN ket photoisomerization. To obtain insight into this photochemical process and to improve the enzyme efficiency of Fdc1, two proposed photoisomerization mechanisms with different proton sources for the acid–base reaction were studied herein using theoretical methods. The potential energy surfaces calculated using the density functional theory method with the Becke, 3-parameter, and Lee–Yang–Parr hybrid functionals and DZP basis set (DFT/B3LYP/DZP) and TD-DFT/B3LYP/DZP methods confirmed that the light-dependent reaction occurs in the rate-determining proton transfer process and that the mechanism involving intermolecular proton transfer between prFMN im and Glu282 (external base) is energetically more favorable than that involving intramolecular proton transfer in prFMN im (internal base). The thermodynamic results obtained from the transition state theory method suggested that the exothermic relaxation energy in the photo-to-thermal process can promote the spontaneous formation of a high-energy-barrier transition state, and an effective enzymatic decarboxylation could be achieved by slowing down the formation of the undesirable thermodynamically favorable product (prFMN ket ). Because the rate constant for formation of the high-energy-barrier transition state varies exponentially over the temperature range of 273–298 K, and experimental results have shown that incubating Fdc1 on ice results in a complete loss of enzyme activity, it is recommended to perform the decarboxylation reaction at 285 K to strike a balance between minimizing enzyme stability loss at 273 K and mitigating the effects of UV irradiation. The computational strategy and fundamental insights obtained in this study could serve as guidelines for future theoretical and experimental investigations on the same and similar photochemical systems.",
"conclusion": "Conclusions The enzymatic decarboxylation of α,β-unsaturated acids using the Fdc1 enzyme and prFMN cofactor is a potential, environmentally friendly reaction for the biosynthesis of styrene and its derivatives. However, an experiment indicated that the enzyme activity of Fdc1 depends on the ring structure of prFMN, namely, the iminium and ketimine forms, and the loss of the enzyme activity results from the prFMN im → prFMN ket photoisomerization with the light-dependent reaction suggested to occur in the cyclization process. Herein, to obtain insight into the prFMN im → prFMN ket photoisomerization process and to improve the enzyme efficiency of Fdc1, two proposed photoisomerization mechanisms with different proton sources for the acid–base reaction were studied using theoretical methods. This mechanistic study focused on the photoisomerization pathways in the S 1 and S 0 states and on the kinetics and thermodynamics of the photo-to-thermal process in the active site of Fdc1. Analysis of the equilibrium structures of the model active site clusters revealed that because the active site volumes (residue-to-residue distances) obtained from the DFT/B3LYP/DZP geometry optimization were not significantly different, the model active site clusters without the Fdc1 backbone were proved to be reasonable and can be used in the study of the enzymatic decarboxylation process. The PESs calculated from the DFT/B3LYP/DZP and TD-DFT/B3LYP/DZP methods suggested that the light-dependent reaction occurs in the rate-determining proton transfer process (acid–base reaction), and the mechanism involving intermolecular proton transfer between prFMN im and Glu282 (external base) is energetically more favorable than that involving intramolecular proton transfer in prFMN im (internal base). The light-dependent reaction was confirmed by the calculated UV-visible spectra to be a high-energy-barrier proton transfer process, for which the S 0 → S 1 photoexcited precursor is St0 (prFMN im in the active site cluster). The thermodynamic results obtained from the TST method suggested that the exothermic relaxation energy in the photo-to-thermal process in the Type (3) mechanism can promote the spontaneous formation of the high-energy-barrier transition state. Based on the analysis of the theoretical and experimental data, effective enzymatic decarboxylation of the α,β-unsaturated acids using Fdc1 could be achieved by slowing down the formation of the undesirable thermodynamically favorable product (prFMN ket ). Because the kinetic results suggested that the rate constant of formation of the high-energy-barrier transition state varies exponentially over the temperature range of 273–298 K, and because the experiment showed that incubating Fdc1 on ice could result in complete loss of enzyme stability, it is recommended to perform the decarboxylation reaction at T = 285 K. This temperature allows for kinetically controlled styrene production in the presence of UV radiation, thus addressing the balance between enzyme stability loss at 273 K and under UV radiation. The computational strategy and fundamental insights obtained in this study could serve as guidelines for future theoretical and experimental investigations on the same and similar photochemical systems.",
"introduction": "Introduction The enzymatic decarboxylation of α,β-unsaturated acids using the ferulic acid decarboxylase (Fdc1) enzyme is envisioned as a potential environmentally friendly process for synthesizing styrene and its derivatives from natural resources. 1–3 This enzymatic reaction can be effectively accomplished through 1,3-dipolar cycloaddition between substrates and enzyme cofactors, 4 among which the prenylated flavin mononucleotide (prFMN) has been proven to be effective for the biosynthesis of styrene. 1,3–5,7 Payne et al. 4 proposed a mechanism for the enzymatic decarboxylation of α,β-unsaturated acids using the prFMN cofactor. The mechanism comprising four consecutive elementary reactions has been widely accepted and further studied using various theoretical and experimental methods. They are 1,3-dipolar cycloaddition, Grob-type decarboxylation, protonation, and retro 1,3-dipolarcycloaddition, 4 among which the enzyme-catalyzed 1,3-dipolar cycloaddition of prFMN was suggested by a mechanism-based inhibitor experiment to play the most important role. 2 Ferguson et al. 1 studied the enzyme efficiency of Fdc1 in styrene production from cinnamic acid by monitoring substrate consumption using spectroscopic and kinetic isotope effect methods, from which the cycloelimination was suggested to represent the rate-determining step. In ref. 1 , two forms of prFMN with different ring structures were considered, namely, the iminium and ketimine forms, abbreviated prFMN im and prFMN ket , respectively. The experimental results indicated that with prFMN im , the decarboxylation reaction proceeded via 1,3-dipolar cycloaddition, whereas the reaction with prFMN ket occurred via Michael addition, and the enzyme activity was confirmed to be higher using prFMN im . To study the effect of the prFMN im and prFMN ket cofactors on the enzyme activity, the enzymatic decarboxylation using Fdc1 to generate styrene from cinnamic acid was further studied. 5 High-resolution crystal structures and mass spectrometric and kinetic experiments revealed that the prFMN im → prFMN ket isomerization could occur through an irreversible photochemical reaction, which is independent of the Glu277–Arg173–Glu282 residue network. This photoisomerization reaction was suggested to be the key factor for the loss of Fdc1 enzyme activity. Two photoisomerization mechanisms with different proton sources for the acid–base reaction are proposed in Fig. 1 . 5 Type (1) mechanism involves four consecutive elementary reactions and begins with the intramolecular proton transfer in prFMN im , whereas for Type (2) mechanism, the intermolecular proton transfer between prFMN im and Glu282 represents the initial process with only three consecutive elementary reactions. Although the elementary reactions in Type (1) and (2) mechanisms were not known in detail, the light-dependent reaction was anticipated to be in the cyclization process, in which the exposure to UV light at λ abs = 365 nm for 5 min led to a complete loss of enzyme activity and change in the absorption spectrum. 5 This light-dependent reaction is similar to maleimide [5 + 2] photocycloaddition reported in ref. 6 . Fig. 1 The proposed prFMN im → prFMN ket photoisomerization mechanisms obtained based on high-resolution crystal structures, mass spectrometric and kinetic experiments. 5 All the symbols are explained in the text. Type (1) = mechanism involving intramolecular proton transfer in the H-bond in prFMN im with four consecutive elementary reactions; Type (2) = mechanism involving intermolecular proton transfer in the H-bond between prFMN im and Glu282 with three consecutive elementary reactions. Int = internal base; Ext = external base. In our previous study, 7 the elementary reactions proposed in ref. 4 were examined in low and high local dielectric environments ( ε = 1 and 78) using the density functional theory (DFT) method with the Becke, 3-parameter, and Lee–Yang–Parr hybrid functionals and DZP basis set (DFT/B3LYP/DZP) and the transition state theory (TST) method. The active site models included the α-methylcinnamate (Cin) substrate, prFMN im cofactor, and all relevant Fdc1 residues. The results confirmed that the Fdc1 backbone does not play an important role in the decarboxylation reaction and that indirect cycloelimination in a low local dielectric environment is the rate-determining step. Literature review showed that in the past decade (2014–2024), there were 44 published research articles reporting the design and/or improvement of enzymatic decarboxylation in organic syntheses, among which 30 studies focused on the decarboxylation of α,β-unsaturated acids, and 14 studies used the Fdc1 enzyme in the biosynthesis of styrene and its derivatives. Literature review also revealed that only 5 studies investigated the photoisomerization of the enzyme cofactors under UV exposure, among which only one experimental study 5 examined in detail the loss of the enzyme activity through the prFMN im → prFMN ket photoisomerization. Because there is no theoretical study on this photoisomerization reaction, to bridge the gap between the experimental and theoretical knowledge, Type (1) and Type (2) mechanisms were studied in detail using the DFT/B3LYP/DZP, TD-DFT/B3LYP/DZP, and TST methods. To obtain insight into the prFMN im → prFMN ket photoisomerization, this mechanistic study focused on the molecular processes (scenarios) in the lowest singlet excited (S 1 ) state and on the kinetics and thermodynamics of nonradiative reaction pathways. The theoretical investigation began with calculations of the equilibrium structures and spectroscopic properties of the selected active site models, from which the potential energy surfaces (PESs) for prFMN im → prFMN ket were optimized in the S 1 and S 0 states. The kinetic and thermodynamic properties of the PESs were computed using the TST method. To suppress/delay the prFMN im → prFMN ket photoisomerization process, appropriate thermodynamic conditions were suggested in order to improve the enzymatic decarboxylation of α,β-unsaturated acids using Fdc1.",
"discussion": "Results and discussion Equilibrium structures of the active site clusters The DFT/B3LYP/DZP results show that starting from the seven hypothesized active site clusters shown in Fig. 1 , the optimized structures are slightly changed (Table S2a † ), except for St2 Int and St2 Ext . For St2 Int , DFT/B3LYP/DZP geometry optimization yielded the precursor St0 (prFMN im in the active site cluster), whereas starting from St2 Ext resulted in the product St4 (prFMN ket in the active site cluster). These results suggest that only five active site clusters are stationary points (intermediates/products) on the S 0 PESs, and St2 Int and St2 Ext could only be the transition structures on the reaction pathways. Analysis of the equilibrium structures of the five active site clusters revealed that in the S 0 state, the residue-to-residue (R-to-R) distances in Fig. 2b are not significantly different, characterized by standard deviations less than ±0.15 Å (Table S2b † ); the average R-to-R distances were calculated using the distances between the carbon atoms of the CH 3 groups that substituted the carbon atom of the Fdc1 backbone. For example, , and . Because our previous study 7 also revealed that the residue-to-residue distances (active site volume) do not change significantly during the enzymatic reaction, the lock-and-key model could explain the substrate specificity of the Fdc1 enzyme, and the catalytic efficiency of this enzymatic decarboxylation reaction is partly connected to the efficiency of the proton exchange between the substrate and Glu282, which is a part of the conserved Glu277–Arg173–Glu282 residue network. These results further suggested that the model active site clusters without the Fdc1 backbone are reasonable and can be used for further studies. DFT/B3LYP/DZP geometry optimization further suggested that St4 possesses the lowest total energy in the S 0 state, and St0 is 24 kJ mol −1 less stable. The TD-DFT/B3LYP/DZP method showed that the S 0 → S 1 energies of prFMN im and prFMN ket are Δ E Ex = 3.15 and 2.25 eV ( λ S 0 →S 1 = 394 and 551 nm), respectively. Comparison of Δ E Ex in Tables S1 and S2a † indicated that Δ E Ex of St0 is red-shifted from that of prFMN im ; Δ E Ex of St0 is 0.55 eV (∼83 nm red-shifted) lower than that of prFMN im , whereas Δ E Ex of St4 and that of prFMN ket are almost the same. The red-shift is hypothesized to result from strong H-bond interaction between prFMN im and residues in the S 1 state; based on TD-DFT calculations on the camphorsulfonic acid doped polyaniline, 25 the electronic spectral red- and blue-shifts could be induced by the excited state H-bond dynamics, for which strong H-bond interaction in the excited states leads to an increase in the oscillator strength and red-shift. Analysis of the HOMOs and LUMOs in Fig. 5a suggested that while the electron density distributions for prFMN ket in the S 0 and S 1 states are not substantially different, those for prFMN im are significantly different, especially for the HOMOs, which are characterized by a lower π-character in the phenyl ring. The H-bond formation between the cofactor and residues results in nearly the same electron density distributions in the S 0 and S 1 states for St0 and St4 ( Fig. 5b ); in the S 0 state, electron density distributions for St0 and St4 are extensive in the Glu277–Arg173–Glu282 network, whereas in the S 1 state, the electron densities at the cofactor are the highest, resulting in an increase in the π-character at the cofactors. This could explain why Δ E Ex for St0 and St4 are not significantly different (Table S2a † ), Δ E Ex = 2.60 and 2.69 eV, respectively. Fig. 5 The HOMOs and LUMOs of the prFMN im and prFMN ket cofactors (a), and model active site clusters (b), obtained from DFT/B3LYP/DZP geometry optimizations. Remarks should be made on the HOMOs of the Glu277–Arg173–Glu282 network in Fig. 5b . The extensive charge (electron density) distributions in the S 0 state within the Glu277–Arg173–Glu282 network reflect the predominant electrostatic interactions in the COO − ⋯Gdm + ⋯COO − salt-bridge; Gdm + stabilizes the two carboxylate anions. Because similar COO − ⋯Gdm + ⋯COO − salt-bridges were found in many protein structures, and theoretical studies have shown that the Gdm + ⋯COO − attractive interaction affects the ligand recognition and binding, as well as enzyme folding and activity, the COO − ⋯Gdm + ⋯COO − salt-bridge with specific electrostatic interaction could be synthesized and applied, for example, in drug design; Gdm + derivatives have already been used to treat various deceases related to muscle weakness, cancer and diabetes. 26 Potential energy surfaces for prFMN im → prFMN ket photoisomerization The structures and energies of the active site clusters on the S 0 and S 1 PESs obtained from the DFT/B3LYP/DZP and TD-DFT/B3LYP/DZP reaction path optimization (Fig. S1–S6 † ) are analyzed in detail. To study the possibility of St2 Int and St2 Ext being the S 0 → S 1 photoexcited precursors in the [5 + 2] photocycloaddition, as proposed in ref. 6 , the PESs for St0 → St1 Int → St2 Int and St0 → St1 Ext → St2 Ext in the S 0 state were primarily calculated; the intra- and intermolecular proton transfers and covalent bond dissociation occurring in the S 0 state serve as prerequisites for the light-dependent cycloaddition in Type (1) and Type (2) mechanisms, 5 respectively. The results showed that both St0 → St1 Int → St2 Int and St0 → St1 Ext → St2 Ext involve extraordinarily high energy barriers in the S 0 state, especially for the covalent bond dissociation, Δ E ‡ = 456.4 and 435.9 kJ mol −1 (Fig. S1b and S2b, † respectively). Based on these findings and the observations that St2 Int and St2 Ext are not stationary points with S 0 → S 1 energies significantly different from the experimental radiation wavelength ( λ abs = 365 nm/Δ E Ex = 3.40 eV), 5 these two active site clusters were ruled out from further study; TD-DFT/B3LYP/DZP single point calculations suggested that for St2 Int and St2 Ext , Δ E Ex = 2.96 and 1.88 eV, respectively (Table S2a † ). Similarly, because the intra- and intermolecular proton transfers (St0 → St1 Int and St0 → St1 Ext ) possess high energy barriers in the S 0 state, Δ E ‡ = 262.6 (Fig. S1a † ) and 125.7 kJ mol −1 (Fig. S2a † ), respectively, it is unlikely that St1 Int and St1 Ext serve as the photoexcited precursors for S 0 → S 1 . To study the possibility of St0 being the S 0 → S 1 photoexcited precursor, UV-visible absorption spectra were calculated at 277 and 300 K using 500 Wigner sampled initial conditions. The results in Fig. 6 show two outstanding peaks, e.g. , at 300 K, λ abs = 384 and 474 nm. Because the structured peak at λ abs = 384 nm is close to the radiation wavelength used in an experiment, 5 St0 was chosen as the S 0 → S 1 photoexcited precursor for Type (1) and Type (2) mechanisms. Fig. 6 The UV-visible spectra of the model active site cluster St0 (prFMN im in the residue network) obtained based on 500 Wigner sample structures at 277 and 300 K. The PESs obtained from reaction path optimization show that the S 0 → S 1 vertically excited structure barrierlessly relaxes to the structure at the S 0 /S 1 intersection (St0 * → St0 *,§ in Fig. S3a † ). The S 0 PES (Fig. S4 † ) illustrates that after the S 1 → S 0 nonradiative relaxation, the intramolecular proton transfer (St0 § → St0-[1] Int → St1 Int ) in the Type (1) mechanism possesses a rather high energy barrier, Δ E ‡ = 209.5 kJ mol −1 , whereas Δ E ‡ = 86.9 kJ mol −1 is for the intermolecular proton transfer (St0 § → St0-[1] Ext → St1 Ext ) in the Type (2) mechanism (Fig. S5a † ). Hence, one can conclude that the external base pathway is energetically more favorable than the internal one, and only the Type (2) mechanism is further discussed in detail. To test the hypothesis that the red-shift in Δ E Ex for St0 compared to that of prFMN im results from strong H-bond interaction between the prFMN im cofactor and residues in the S 1 state, the variation of the N Gln190 –H⋯O prFMN,− H-bond distance in the S 1 state was analyzed as an example. The results revealed that on the S 1 PES (Fig. S3a † ), while the R N Gln190 –H⋯O prFMN,− H-bond distance decreases, the R N Gln190 –H distance increases (Fig. S3b † ), reflecting an increase in the N Gln190 –H⋯O prFMN,− H-bond strength (red-shift) in the S 1 state towards the S 0 /S 1 intersection. Because St2 Ext had already been excluded from the photoisomerization pathway, an attempt was made to bypass this active site cluster. The results showed that after the S 1 → S 0 nonradiative relaxation at the S 0 /S 1 intersection (Fig. S3a † ) and intermolecular proton transfer from prFMN im to Glu282 (Fig. S5a † ), the S 0 PES shows a low energy barrier for St1 Ext → St3 Ext , Δ E ‡ = 11.2 kJ mol −1 (Fig. S5b † ), represented by concerted N prFMN 5 –C prFMN 5a and covalent bond dissociation and formation in Fig. 7a , respectively. This concerted process can be collectively regarded as “ring expansion.” To complete the formation of the St4 product (prFMN ket in the active site cluster), the S 0 PES for the reverse protonation from Glu282 to prFMN im (St3 Ext → St4) has Δ E ‡ = 63.9 kJ mol −1 (Fig. S5c † ). The potential energy profile, which bypasses St2 Ext , is regarded as the Type (3) mechanism shown in Fig. 7b . Fig. 7 (a) and (b) Type (3) mechanism and potential energy profiles involving the S 0 → S 1 excitation of St0, intermolecular proton transfer in H-bond between prFMN im and Glu282, ring expansion and reverse protonation, respectively. (c) The H-bond distances ( and R O Glu282 –H⋯O prFMN ) and local valence charge densities on the high-energy barrier intermolecular proton transfer process (St0-[1] Ext → St0-[1] Ext,‡ → St1 Ext ). (d) and (e) Type (4) mechanism and potential energy profiles involving the S 0 → S 1 excitation of St0 and concerted intramolecular proton transfer in prFMN im and ring expansion. The characteristic structures are shown in detail in Table S2. † (…) S 0 → S 1 = S 0 → S 1 vertical excitation energy; (…) Rel and (…) ‡ = relative and transition energies on the PES; (…) S 1/ S 0 = difference between the total energies in the S 0 and S 1 states at the S 0 /S 1 intersection. The analysis of the H-bond distances, local valence charge densities and energetics in the high-energy barrier intermolecular proton transfer process (St0-[1] Ext → St0-[1] Ext,‡ → St1 Ext ) in Fig. 7c reveals that although the H-bond in St0-[1] Ext is longer than the O Glu282 –H⋯O prFMN H-bond in St1 Ext ( R O Glu282 –H⋯O prFMN = 1.52 Å), due to the strong electrostatic interaction between Glu282 and prFMN im , St0-[1] Ext is more stable than St1 Ext . It also appears that proton transfer to one of the COO − groups in the COO − ⋯Gdm + ⋯COO − salt bridge leads to a strong decrease in the electrostatic interaction between Glu282 and prFMN im , recognized from a reduction of the local valence charge density at the COOH group of St1 Ext , and the high-energy barrier in St0-[1] Ext → St0-[1] Ext,‡ → St1 Ext could be attributed the covalent bond breaking. Because the Type (1) mechanism 5 has been established in this work to be energetically not favorable, to search for an alternative internal base pathway, the S 0 PES directly connecting structure St0 § at the S 0 /S 1 intersection and St4 (St0 § → St4) was optimized. It appeared that St0 § → St0-[1] direct → St0-[1] direct,‡ → St4 (Fig. S6 † ) can occur without proton exchange between the prFMN im cofactor and the Glu282 residue. This internal base pathway (Type (4) mechanism shown in Fig. 7d ) involves concerted intramolecular proton transfer, N prFMN 5 –C 5a prFMN and covalent bond dissociation and formation, respectively, with Δ E ‡ = 31.7 kJ mol −1 ( Fig. 7e ). Thermodynamics of the elementary reactions To study the kinetic and thermodynamic properties of the two energetically favorable pathways, the characteristic active site clusters in Type (3) and Type (4) mechanisms shown in Fig. 7 were used in TST calculations, and the results are summarized in Tables S3–S5. † The results discussed are included in Tables 1 and 2 . Analysis based on the photo-to-thermal pathway in Fig. 4 , (I) * → (II) *,§ /(II) § → (III), revealed that for the Type (3) mechanism at T = 298 K, although the entropy for the formation of St0-[1] Ext,‡ is negative (Δ S ° ,(I)*→(IV)‡ = −7.4 × 10 −2 kJ mol −1 ), the high exothermic relaxation energy for St0 * → St0 § → St0-[1] Ext (Δ H ° ,(I)*→(III) = −178.4 kJ mol −1 in Table 1a ) allows the spontaneous formation of this high energy-barrier transition state with Δ G ° ,(I)*→(IV)‡ = −77.7 kJ mol −1 . Thermodynamics of the elementary reactions for the external base prFMN im → prFMN ket photoisomerization (Type (3) mechanism), obtained from the DFT/B3LYP/DZP, TD-DFT/B3LYP/DZP and TST methods. Δ G ° and Δ H ° = Gibbs free energy and enthalpy in kJ mol −1 ; Δ S ° = entropy in kJ mol −1 K −1 ; Δ G ° ,Tot = total reaction Gibbs free energy for prFMN im → prFMN ket and; Δ S ° ,Rx = reaction entropy of all the elementary processes; T = temperature in K \n \n Based on the same approach, the total Gibbs free energy and reaction entropy for the prFMN im → prFMN ket photoisomerization via the Type (3) mechanism were computed to be ΔG° ,Tot = −226.3 kJ mol −1 and ΔS° ,Rx = −7.5 × 10 −2 kJ mol −1 K −1 at 298 K ( Table 1c ). For the Type (4) mechanism, Δ H ° ,(I)*→(III) = −221.1, Δ G ° ,Tot = −226.3 kJ mol −1 , and Δ S ° ,Rx = −7.4 × 10 −2 kJ mol −1 K −1 , with the spontaneous formation of St0-[1] direct,‡ , Δ G ° ,(I)*→(IV)‡ = −131.6 kJ mol −1 ( Table 2 ). Therefore, based on the values of Δ G ° ,(I)*→(IV)‡ of the rate-determining step, the Type (4) mechanism is thermodynamically more favorable than the Type (3) mechanism. Because Δ G ° ,Tot and Δ S ° ,Rx of Type (3) and Type (4) mechanisms are the same ( Tables 1 and 2 , respectively), the hypothesized photo-to-thermal pathway in Fig. 4 is validated and the applicability of the TST method is confirmed. Thermodynamics of the elementary reactions for the internal base prFMN im → prFMN ket photoisomerization (Type (4) mechanism), obtained from the DFT/B3LYP/DZP, TD-DFT/B3LYP/DZP and TST methods. Δ G ° and Δ H ° = Gibbs free energy and enthalpy in kJ mol −1 ; Δ S ° = entropy in kJ mol −1 K −1 ; Δ G ° ,Tot = total reaction Gibbs free energy for prFMN im → prFMN ket and; Δ S ° ,Rx = reaction entropy of all the elementary processes; T = temperature in K \n \n Kinetics of elementary reactions To correlate the theoretical results with the experimental data 5 and to explore the possibility of improving the enzyme efficiency of Fdc1, the rate constants ( k Q-vib ) for Type (3) and Type (4) mechanisms (Tables S3 and S4, † respectively) were analyzed and discussed in detail. The experimental rate constants revealed that the enzyme activity of Fdc1 purified in the dark was slightly higher than that under visible light, k cat = 9.3 ± 0.1 and 7.6 ± 0.2 s −1 , respectively, and when Fdc1 was prepared in the dark, the enzyme activity remained constant for many hours. However, direct exposure of the Fdc1 enzyme incubated in the dark with UV radiation at λ = 365 nm for ∼5 min led to a complete loss of enzyme activity and a change in the UV-visible spectra. The experimental results also showed that after purification, Fdc1 incubated on ice resulted in a loss of enzyme stability with a half-life τ 1/2 loss, T ≈ 30 min. Based on the assumption that the loss of enzyme activity at 273 K follows the first-order kinetics, k loss, T = 0.693/ τ 1/2 loss, T = 3.85 × 10 −4 s −1 . In addition, assuming that the photochemical experiment 5 was conducted at room temperature, the complete loss of enzyme activity due to UV radiation is approximated to be τ loss,UV = 300 s, with the rate constant k loss,UV = 1/ τ loss,UV = 3.33 × 10 −3 s −1 at 298 K. The value of k loss,UV is compatible with the rate-determining step in the Type (3) mechanism; for the intermolecular proton transfer from prFMN im to Glu282, k f Q-vib = 3.53 × 10 −3 s −1 at 298 K (Table S3 † ). Although the internal base pathway in Type (4) mechanism is energetically and thermodynamically more favorable than Type (3) mechanism, the concerted rate-determining process is too fast compared with the experimental rate constant, k f Q-vib = 3.26 × 10 0 s −1 compared with k loss,UV = 3.33 × 10 −3 s −1 at 298 K. Therefore, Type (3) mechanism, which requires an external base, is likely to represent the prFMN im → prFMN ket photoisomerization mechanism. Balance between the loss of enzyme stability and the efficiency by UV radiation Based on the above discussion on the theoretical and experimental data, 5 to reduce the prFMN im → prFMN ket photoisomerization rate without substantial loss of the Fdc1 stability, an appropriate enzymatic decarboxylation temperature should be chosen; an effective enzymatic decarboxylation using Fdc1 could be achieved by slowing down the photo-to-thermal process (formation of the high-energy barrier transition state) in Type (3) mechanism, compared with the enzymatic decarboxylation rate. To recommend the appropriate temperature, at which the styrene production is kinetically controlled in the presence of UV radiation, the plot of the half-life for the formation of the high-energy barrier transition state ( τ 1/2 Q-vib ) versus T and the Arrhenius plot for this photo-to-thermal pathway were constructed over the studied temperature range and are shown in Fig. 8 . Fig. 8a shows that τ 1/2 Q-vib varies exponentially over the temperature range of 273–298 K. Thus, to balance between the loss of the enzyme stability at 273 K and that under UV irradiation, the appropriate temperature should be in this temperature range, τ 1/2 loss, T = 1800 ( T = 273 K) and τ 1/2 loss,UV = 208 s ( T = 298 K). Fig. 8 (a) and (b) Correlations between τ 1/2 Q-vib and T , and ln k f Q-vib and 1/ T for the rate determining step (St0-[1] Ext → St0-[1] Ext,‡ in Fig. 7(b) in Type (3) mechanism obtained from the TST method, compared with experiment. 5 τ 1/2 loss, T and k loss, T = half-life and first-order rate constant for the loss of enzyme stability at 273 K; 5 τ 1/2 loss,UV and k loss,UV = half-life and first-order rate constant for the loss of enzyme activity due to UV radiation at 365 nm; 5 τ 1/2 Q-vib and k f Q-vib = half-life and first-order rate constant for the rate-determining intermolecular proton transfer (St0-[1] Ext → St0-[1] Ext,‡ ) in Fig. 7(b) . As a rule of thumb, the rate of chemical reaction doubles if the temperature increases by 10 K. Therefore, the experimental rate constants to produce styrene in this temperature range are k cat = 3.00 and 7.60 s −1 , and the rate constants for the intermolecular proton transfer (rate determining step for prFMN im → prFMN ket ) are k f Q-vib = 1.98 × 10 −4 s −1 (273 K) and 3.53 × 10 −3 s −1 (298 K). The Arrhenius plot in Fig. 8b reveals that in this temperature range, k loss, T = 3.85 × 10 −4 s −1 ( T = 273 K) and k loss,UV = 3.33 × 10 −3 s −1 ( T = 298 K), and the optimal temperature should be at T = 285 K with k f Q-vib = 8.16 × 10 −4 s −1 for the photo-to-thermal pathway. Therefore, the enzyme activity of Fdc1 purified under visible light at 285 K is approximated to be k cat ≈ 3.8 s −1 . This experimental rate constant is ∼4600 times larger than the rate-determining step for prFMN im → prFMN ket at the same temperature, and styrene production becomes kinetically controlled in the presence of UV radiation at this temperature."
} | 7,916 |
39450140 | null | s2 | 9,731 | {
"abstract": "The brain, which uses redundancy and continuous learning to overcome the unreliability of its components, provides a promising path to building computing systems that are robust to the unreliability of their constituent nanodevices. In this work, we illustrate this path by a computing system based on population coding with magnetic tunnel junctions that implement both neurons and synaptic weights. We show that equipping such a system with continuous learning enables it to recover from the loss of neurons and makes it possible to use unreliable synaptic weights ("
} | 142 |
22403036 | PMC3324691 | pmc | 9,732 | {
"abstract": "Excitation–emission fluorescence matrices of phytoplankton communities were simulated from laboratory-grown algae and cyanobacteria cultures, to define the optical configurations of theoretical fluorometers that either minimize or maximize the representation of these phytoplankton groups in community variable fluorescence measurements. Excitation sources that match the photosystem II (PSII) action spectrum of cyanobacteria do not necessarily lead to equal representation of cyanobacteria in community fluorescence. In communities with an equal share of algae and cyanobacteria, inducible PSII fluorescence in algae can be retrieved from community fluorescence under blue excitation (450–470 nm) with high accuracy ( R \n 2 = 1.00). The highest correlation between community and cyanobacterial variable fluorescence is obtained under orange-red excitation in the 590–650 nm range ( R \n 2 = 0.54). Gaussian band decomposition reveals that in the presence of cyanobacteria, the emission detection slit must be narrow (up to 10 nm) and centred on PSII chlorophyll- a emission (~683 nm) to avoid severe dampening of the signal by weakly variable phycobilisomal fluorescence and non-variable photosystem I fluorescence. When these optimizations of the optical configuration of the fluorometer are followed, both cyanobacterial and algal cultures in nutrient replete exponential growth exhibit values of the maximum quantum yield of charge separation in PSII in the range of 0.65–0.7.",
"introduction": "Introduction Differences in pigmentation are used to discriminate taxonomic phytoplankton groups in applications ranging from microscopy to remote sensing of water colour. The highest level of pigment discrimination between phytoplankton groups is found between prokaryotic cyanobacteria and the vast majority of algal taxa. Chlorophylls and carotenoids are dominant in algae, while phycobilipigments (phycoerythrin, phycoerythrocyanin, phycocyanin and allophycocyanin) are the main light harvesting pigments in cyanobacteria (prochlorophytes excepted) and red algae. Phycobilipigments extend the absorption of light to the green-orange part of the visible spectrum that is left unused by the algal groups. This spectral domain overlaps with the deepest penetration of solar irradiance in inland and coastal waters where turbidity and/or the concentration of coloured dissolved organic matter is high, yielding an advantage in light-harvesting at depth to phycobilin-containing species (Pick 1991; Stomp et al . \n 2007 ). Owing to the differences in pigmentation between the major phytoplankton groups, absorption and fluorescence techniques can be used to interpret biomass at the community and sub-community level (Yentsch and Yentsch 1979 ; Kolbowski and Schreiber 1995 ; Beutler et al . \n 2002 ; Millie et al . \n 2002 ; Beutler et al . \n 2003 ; Seppälä and Olli 2008 ). In vivo chlorophyll a (Chl a ) fluorescence is a widely used proxy of phytoplankton biomass, a non-intrusive measurement that can be carried out with high spatial resolution (Lorenzen 1966 ; Kiefer 1973 ) under the assumption that the Chl a fluorescence yield is constant. When excited with blue light, Chl a fluorescence per unit concentration in cyanobacteria tends, however, to be up to an order of magnitude lower than in algae, which results in erroneous biomass estimates unless corrected for (Vincent 1983 ; Seppälä et al . \n 2007 ). The distribution of Chl a between photosystems I and II (PSI, PSII) is fundamentally different in these phytoplankton groups (Johnsen and Sakshaug 1996 , 2007 ), and requires consideration in all aspects of phytoplankton community fluorescence measurements. Variable fluorescence methods relate the rise of fluorescence that occurs with ‘closure’ of PSII centres under saturating illumination to energy flow in PSII (Kautsky and Hirsch 1931 ; Genty et al. 1989 ). Closed reaction centres cannot use the energy absorbed in the photosystem antennae for photochemistry and emit at least part of the excess energy as fluorescence (e.g. Gilmore and Govindjee 1999 ). Saturating light conditions can be induced by generating intense light pulses, such as used in pulse-amplitude modulation (PAM), pump-and-probe and fast-repetition rate fluorescence (FRRF) techniques. These methods are designed to measure both the minimum ( F \n 0 , before closure of the reaction centres and after dark-adapting the sample) and maximum inducible ( F \n m , reaction centres closed) level of fluorescence. The variable (inducible) part of fluorescence is expressed as F \n v = F \n m – F \n 0 , and when normalized to F \n m ( F \n v / F \n m ) presents a measure of the maximum quantum yield of charge separation at PSII. Under ambient light conditions, the operational quantum yield of PSII ( F \n v ′/ F \n m ′) is obtained instead. Both parameters are useful as they respond to nutrient limitation, excess light or transiently when growth conditions change. A combination of dark- and light adapted measurements can be used to determine the electron transport rate under known irradiance(s), which can in turn be used to model primary production (Kolber and Falkowski 1993 ). The current work focuses on the experimental manipulation and spectral measurement of dark-adapted F \n v / F \n m . The use of this parameter in higher level applications is discussed at length in recent reviews of literature on the subject (Suggett et al. 2004 , Huot and Babin 2010 ). Advances in light-emitting diode (LED) manufacturing have led to the availability of narrow-band, high-power excitation light sources of high efficiency and stability. Their rapid flash capability and high output makes them the light source of choice for FRRF protocols and for PAM applications that require a small footprint. In FRRF, microsecond flashlets provide a saturating flash train within a single turnover period of PSII (<100–150 μs). PAM-type fluorometers have been developed with a combination of light sources of different colours for some time. FRRF instruments were until very recently limited to the use of LEDs of one colour in order to produce sufficiently bright flashlets. Blue light sources have been chosen to provide overlap with the absorption by Chl a and accessory photosynthetic pigments in algae, but do not overlap with cyanobacterial phycobilipigment absorption (Johnsen and Sakshaug 2007 ). Recent studies have shown that blue-light equipped FRRF instruments are relatively insensitive to the presence of cyanobacteria, if these do not possess short-wavelength forms of phycoerythrin (Raateoja et al. 2004 ; Suggett et al. 2004 ). While F \n v / F \n m can be recorded from cyanobacteria using blue excitation as long as the light source can saturate PSII, the intensity of the fluorescence is relatively low compared to algae. Variable fluorescence of cyanobacteria can alternatively be assessed from orange or red excitation sources that excite the phycobilipigments in cyanobacteria (Schubert et al. 1989 ). Now that LEDs are available at the brightness required by FRRF instruments, this concept stands to be adapted to the FRRF range of instrumentation. Studies on the optimization of the variable fluorescence measurement towards unbiased representation of the phytoplankton community, are therefore overdue. In this study, we address the representation of cyanobacteria and algae in community (variable) fluorescence measurements with special emphasis on narrow-band excitation sources. Our focus is on cyanobacteria with a pigment profile that results in low fluorescence under blue light. Most coastal and freshwater cyanobacteria belong to this group, whereas common clear-water species that produce phycourobilin-rich forms of phycoerythrin have stronger fluorescence with blue excitation. We analyse fluorescence excitation–emission matrices of cultures that are subjected to various treatments of light and nutrient availability. These fluorescence matrices are used to simulate variable fluorescence of mixed algal and cyanobacterial communities from which statistical analyses of the relation between community and subcommunity variable fluorescence follows. We describe the optimal optical configuration (excitation–emission waveband pairs) to obtain F \n v / F \n m values that represent a community cross section regardless of the share of cyanobacteria in the community. The excitation–emission waveband pairs that result in the best correspondence of community F \n v / F \n m measurements with either the cyanobacterial or the algal subpopulation are also determined. In previous studies, healthy cyanobacteria have reported maximum F \n v / F \n m in the order of 0.3–0.5 and seldom >0.6 (Raateoja et al. 2004 ; Suggett et al. 2009 ). This is markedly lower than reported for algae (0.65) and higher plants (near 0.8). Low F \n v / F \n m in healthy cells can be a measurement artefact when the light source does not provide sufficient intensity to saturate PSII (Raateoja et al. 2004 ). The solution is then to be found in the use of excitation wavebands that better match the photosynthetic action spectrum of the sample. It has also been suggested that phycobilipigment fluorescence can elevate F \n 0 in the PSII Chl a fluorescence band, and thus reduce observed F \n v / F \n m (Campbell et al. 1996 , 1998 ). Interestingly, this latter effect prevails under excitation with blue light, which incites only weak fluorescence from phycobilisome (PBS) pigments. To resolve this issue, we use Gaussian band decomposition of fluorescence emission spectra to determine the extent to which PSII F \n 0 and F \n m are offset by phycobilipigment fluorescence. We then show how the excitation and emission slits of the fluorometer can be optimized to exclude fluorescence from phycobilisomal and PSI pigments, yielding cyanobacterial F \n v / F \n m values in the same range as observed in algae.",
"discussion": "Discussion Cyanobacteria species that are considered harmful due to the production of toxins, odorous compounds, surface scums, or benthic mats, are widespread in coastal and inland water bodies, particularly in eutrophic systems (e.g. Hallegraeff 1993 ; Anderson et al . \n 2002 ). Blooms of these species negatively impact ecosystem value. Monitoring the presence and activity of cyanobacteria is therefore a pressing matter in environmental policy. The distinct absorption and fluorescence properties of cyanobacteria caused by the prominent role of phycobilipigments in photosynthetic light harvesting are already used to complement traditional observation methods (e.g. microscope counts) in environmental monitoring (Lee et al. 1994; Izydorczyk et al. 2005; Seppälä et al. 2007 ). Variable fluorescence measurements are increasingly included in these monitoring efforts, to reveal spatiotemporal trends in photosynthetic capacity or even photosynthetic activity of the phytoplankton. FRRF instruments equipped with a series of excitation sources are increasingly becoming available, and can be used to determine both the quantum yield of photochemistry and the functional absorption cross-section of PSII at e.g. blue, green and orange or red wavelengths. With these instruments it is possible to better assess the role of phytoplankton that efficiently harvest green and orange light in aquatic photosynthesis in environments where terrigenous organic matter skews the available radiation towards the green part of the light spectrum. Such knowledge may be used to determine ecophysiological constraints of coastal and freshwater phytoplankton, but in a wider sense also help to better represent the role of light uptake in ecosystem models that focus on the environments most exposed to, and most important to, human activities. This progress in FRRF design is made possible through more efficient light sources and detectors that have become available in recent years. It is therefore timely to conceive what properties the optimal instrument for these environments should possess and what pitfalls might be avoided. Some properties of cyanobacterial fluorescence emission must be taken into account when deciding upon the optimal detection waveband of the fluorometer, and before interpreting fluorescence induction results obtained with different fluorometer configuration. The major light harvesting pigments for photosynthesis in cyanobacteria are organized in the PBS which holds a group of highly fluorescent phycobilipigments. As long as these pigments are organized in the PBS, energy from phycoerythrin and phycocyanin will be transferred towards the core of the PBS where allophycocyanin subsequently fluoresces in the 650–670 nm range. It therefore stands to reason that this spectral domain should be avoided in fluorescence induction measurements where Chl a fluorescence is used as a proxy of energy flowing through PSII. Long wavelength (>690 nm) fluorescence from PSI is also relatively strong in cyanobacteria. Regardless of the excitation band that is used we therefore find that narrow (10-nm) wavebands centred at the PSII Chl a emission band (680–690 nm) yield best results (Fig. 11 ). The efficiency of energy transfer from the PBS to reaction centres is considered very high (Sidler 1994 for a review), but not all harvested energy is transferred to the PSII core. Our results show PBS fluorescence in the order of 22% of F \n o in the Chl a emission band. This emission is absent in algae (with exceptions) and theoretically leads to a lowered reading of F \n v / F \n m in cyanobacteria and in communities with a high cyanobacterial biomass (Campbell et al. 1996 , 1998 ). We find, however, that a variable component to PBS fluorescence can alleviate the theoretical dampening of F \n v / F \n m considerably (Fig. 10 ). Indeed, the peak of F \n v / F \n m in the excitation–emission spectrum is found in the order of 0.65–0.75, for several cyanobacteria species (Fig. 3 ), despite an average dampening by 6.2% of F \n v / F \n m due to the overlapping fluorescence of PBS pigments and Chl a . Such high F \n v / F \n m values for cyanobacteria have been reported in very few other studies (Raateoja et al. 2004 ; Suggett et al. 2009 ), which used FRRF. Variable fluorescence from PBS is surprising; it has been assumed that these pigments do not exhibit variable fluorescence at all. These findings that are reflected in some recent studies using different fluorescence induction techniques (Küpper et al . \n 2009 ; Kana et al. 2009 ) challenge the idea of a constant, highly efficient resonance transfer from PBS pigments to the reaction centres. Our fluorescence data provide insufficient means to explore the relation between the rise of PBS fluorescence and closing of PSII reaction centres, or to see how illumination or nutrient conditions might influence PBS F \n v / F \n m . Nevertheless, it is notable that F \n v / F \n m from the PBS at 650 nm showed a fair correlation with cyanobacterial PSII Chl a \n F \n v / F \n m (Fig. 8 c). In a pilot experiment that is not presented here, we exposed N. spumigena with saturating light flashes (590 nm) and observed induction of PBS fluorescence (650 nm), suggesting that the present result is neither merely an artefact of DCMU treatment nor to prolonged exposure to light in our spectrofluorometer. If the mechanism behind phycobilisomal variable fluorescence can be explained in terms of PSII kinetics, this may open up the way to study the physiology of cyanobacteria in natural communities. The possibility of variable fluorescence from phycobilipigments in cryptophytes and rhodophytes should in such studies be taken into account. The excitation spectrum of fluorescence in PSII is primarily dependent on the photosynthetic pigment composition, which distinguishes the major phytoplankton groups and, with exceptions, clearly separates cyanobacteria from algae (Fig. 2 ). Blue-green illumination (<550 nm) excites stronger fluorescence in algal cultures than in cyanobacteria (Yentsch and Yentsch 1979 ; Vincent 1983 ; Schubert et al. 1989 ). Longer wavelength illumination favours cyanobacterial fluorescence but algal fluorescence remains significant. If the emission band is located at its optimum of 680–690 nm, as we recommend, the maximum excitation wavelength is practically limited to approximately 650 nm to prevent stray light from the excitation source reaching the detector. There is thus a relatively large section of the photosynthetically active spectrum where algal fluorescence dominates. A ‘white’ illumination source (Fig. 12 a), for example, leads to a bias against cyanobacterial representation in community fluorescence. In contrast, a ‘broad-green’ light source (Fig. 12 b) that excites predominantly accessory photosynthetic pigments yields near-equal representation of algal and cyanobacterial F \n v / F \n m . Our results show a relatively low correlation coefficient ( R \n 2 = 0.33) of the community F \n v / F \n m with either group in the community, when we simulate the broad-green light source. Of course, many of the randomly mixed communities combine cultures exposed to widely different growth conditions and with very different F \n v / F \n m at a specific excitation-waveband pair, so that the community signal could never represent both subcommunities equally in these cases. The approach of simulating community fluorescence is, therefore, not to be used to interpret fluorometer performance beyond describing how well each group is represented in the community signal. In theory, the broad-green illumination band should predominantly excite accessory photosynthetic pigments, so that those phytoplankton groups that respond positively to the environmental conditions by producing accessory pigments, will dominate the result. This idea warrants further study, particularly in natural environments where such information may be desirable. For multi-channel configurations, two narrow excitation bands located in the blue and orange-to-red constitute the minimum required combination to resolve some degree of subcommunity variable fluorescence information. Algal variable fluorescence is obtained with high accuracy from the blue channel. The extent to which orange excitation subsequently yields a different F \n v / F \n m will give some indication of the variable fluorescence of cyanobacteria in the community. This result is not unambiguous, because equal F \n v / F \n m from both blue and orange-excited fluorescence can be interpreted as equal F \n v / F \n m in algae and cyanobacteria but also as the absence of fluorescence from cyanobacteria. To differentiate the two cases, the ratio of F \n 0 intensities of blue versus orange excitation can be used to reveal whether cyanobacteria form a significant part of the community, because the presence of PBS pigment will certainly lead to a markedly higher orange-excited F \n 0 (results not shown). Of course, this suggested approach is similar to previous attempts to separate phytoplankton groups based on fluorescence excitation spectra (Millie et al . \n 2002 ; Beutler et al . \n 2002 ; Beutler et al . \n 2004 ; Parésys et al . \n 2005 ; Gaevsky et al . \n 2005 ; Seppälä and Olli 2008 ). The small number of algal and cyanobacterial species used in our experiments, despite being grown in conditions to allow for a wide range in F \n v / F \n m , limits the applicability of our results. Fluorescence emission profiles of the major algae groups are relatively similar because the main source of fluorescence is always Chl a located in PSII. The excitation spectrum, on the other hand, is dependent on the accessory photosynthetic pigments present. The choice of a single chlorophyte and diatom, representing red absorption by Chlorophylls b and c , is therefore still a realistic representation of many natural communities where algae and cyanobacteria co-exist. It does, however, not cover natural communities extensively. We may consider the case of phycobilin-producing rhodophytes and cryptophytes, as well as cryptophyte-ingesting ciliates (Gustafson et al . \n 2000 ) in further studies. The fluorescence excitation–emission matrices of rhodophytes are similar to those of the cyanobacteria used here, although planktonic rhodophytes are generally few in environments where cyanobacteria are abundant. We hypothesize that the solutions for instrument design proposed here apply to these algae in the same manner as for the cyanobacteria described here. In contrast, the presence of phycoerythrin in cryptophytes and some dinoflagellates leads to a broader excitation domain in the algal groups. The presence of these ‘special’ algal groups in a natural sample will hamper efforts to decompose multi-channel fluorescence measurements into the contributions by individual groups (but see Seppälä and Olli 2008 ), even though it should not markedly change our definition of optimal excitation–emission bands to yield results that are most representative of the whole phytoplankton community. The PBS pigments produced by strains in this study absorb yellow-to-red light as is common to freshwater and coastal species. The presence of oceanic species with forms of phycoerythrin absorbing down to 495 nm (Lantoine and Neveux 1997 ; Subramaniam et al. 1999 ; Neveux et al. 2006 ) would reduce the specificity of the blue-excited fluorescence signals to the algal part of the community, but we remain confident that the inclusion of an orange-to-red excitation band markedly increases sensitivity to the cyanobacteria present. Even with short-wavelength sensitive forms of phycoerythrin present, it is likely that the cyanobacteria will not be equally represented when using a narrow blue light source, which warrants further study. To our knowledge, the present work constitutes the first effort to relate phytoplankton community variable fluorescence to the contributions from algal and cyanobacterial subpopulations over a wide domain of the spectral excitation–emission matrix. In order to collect this information with a standard, mid-range spectrofluorometer, some allowances have had to be made. We may question whether our analysis, based on dark adapted cells, manipulated in their growth environment to yield a range of F \n v / F \n m , are representative of results that would be obtained when using actinic light to manipulate F \n v ′/ F \n m ′. We do believe that transient physiological change ( i.e. state transitions) observed under (increasing) illumination can contribute to changes in the observed cyanobacterial influence on community variable fluorescence. At the same time, we assume that these changes are not likely to be of such magnitude that they would change our definition of the optimal fluorometer configuration. It would be most useful to see repeat experiments that focus on measuring F \n v ′/ F \n m ′ under varying actinic light intensities. A quantum-corrected FRRF or PAM instrument operating with multiple excitation bands would be an excellent platform for such investigations, simultaneously eliminating the need to use DCMU to induce F \n m . In conclusion, we observe that microscope-based active fluorescence measurements, flow-cytometry, remote laser stimulated fluorescence and FRRF are examples of emerging methods in oceanography where phytoplankton fluorescence can shed more light on community composition and photosynthetic capacity at the subcommunity level. We foresee that the use of variable fluorescence techniques will gain increasing importance in environmental monitoring as a complementary method to carbon fixation measurements. It is therefore of prime importance to develop instruments and data interpretation techniques that are not biased against any of the major phytoplankton groups, particularly in environments where the physical environment is heterogeneous in time or space, and come to favour one functional group over another. The results presented in this paper will hopefully lead to a standardized and better understood variable fluorescence meter that will support studies of photosynthesis in optically complex environments."
} | 6,036 |
34207673 | PMC8226481 | pmc | 9,733 | {
"abstract": "The root endophyte community of the grass species Elymus repens was investigated using both a culture-dependent approach and a direct amplicon sequencing method across five sites and from individual plants. There was much heterogeneity across the five sites and among individual plants. Focusing on one site, 349 OTUs were identified by direct amplicon sequencing but only 66 OTUs were cultured. The two approaches shared ten OTUs and the majority of cultured endophytes do not overlap with the amplicon dataset. Media influenced the cultured species richness and without the inclusion of 2% MEA and full-strength MEA, approximately half of the unique OTUs would not have been isolated using only PDA. Combining both culture-dependent and -independent methods for the most accurate determination of root fungal species richness is therefore recommended. High inter-plant variation in fungal species richness was demonstrated, which highlights the need to rethink the scale at which we describe endophyte communities.",
"conclusion": "5. Conclusions This study illustrates many of the issues at the core of endophyte discovery and community description. PDA medium recorded the highest species richness but also excluded many rare species. Only a fraction of those endophytes that could potentially be isolated were cultured and did not represent the most widespread species. Furthermore, large variation in the fungal species richness estimates highlights the high heterogeneity at both plant and site level. Despite the attention received, the field is still some way off in developing a satisfactory methodology with the desired outcomes. Our results indicate that a combination of culture-dependent and -independent methods is the best approach for estimating the root fungal species richness.",
"introduction": "1. Introduction Plants are surrounded by microorganisms living on seeds, roots, leaves and flowers [ 1 , 2 , 3 ]. Microorganisms found within asymptomatic plants, which are classified as endophytes [ 4 , 5 ], have gained a lot of attention from ecologists, agronomists and pharmacists. Endophytes have been shown to be able to shape the plant community [ 6 ] and their associated food webs [ 7 ]. Furthermore, some species of endophytes have been shown to provide plants with benefits such as drought tolerance [ 8 ], heat tolerance [ 9 ], salt stress tolerance [ 10 ], improved mineral nutrition [ 11 ], as well as protection against diseases [ 12 , 13 ] and pests [ 14 ]. In addition, useful secondary metabolites have been isolated from endophytes such as sphaeropsidin A, sphaeropsidin D and acetylsphaeropsidin A, which have shown anti-cancer properties [ 15 ]. Studies can deploy culture-dependent and/or direct sequencing methods to describe endophyte communities of plants. When studies use the culture-dependent method, the surface-sterilised tissue is placed on an agar-based medium and, once the endophyte grows out, they can be maintained in pure culture followed by identification on the basis of morphology as well as using DNA sequencing. Another possibility is to identify endophytes directly from the plant material using DNA sequencing. In this case, DNA is extracted from the surface-sterilised plant tissue and a set of primers are used in PCR to obtain sequences of interest. The obtained sequences are then compared to sequences with ‘known identity’, often but not always, using a public database [ 16 ]. It is generally accepted that not all fungi will grow on all artificial media [ 17 ] and studies have shown that different media can influence the number of isolated endophytes as well as the species richness [ 18 , 19 , 20 ]. In investigations of non-clavicipitaceous fungal endophytes of grasses, most often only one type of media is used [ 21 , 22 , 23 ] and when multiple types are used, the effect is not discussed [ 24 , 25 ]. In this study, the variation in species richness isolated on the three most commonly used media of non-clavicipitaceous fungal endophytes of grasses, PDA, MEA and 2% MEA, were investigated and compared. Furthermore, it is standard practice to pool samples independent of whether the endophyte study is based on direct sequencing or culturing without taking into account inter-plant variation [ 26 , 27 ]. To address this, we investigated the variation at site level as well as at individual plant level in the wild and serious grass weed species Elymus repens and discuss whether it is reasonable to pool samples. In addition, comparisons are made between the communities estimated by direct sequencing and culturing. The results help to optimise the discovery efficiency of endophytes and better understand the factors influencing their diversity.",
"discussion": "4. Discussion 4.1. Endophyte Community Described by Direct Amplicon Sequencing Organisms belonging to three kingdoms including Chromista, Fungi and Rhizaria were identified as root endophytes of Elymus repens by direct amplicon sequencing of roots. Plant associated organisms are found within the Chromista including plant pathogens belonging to the Oomycetes such as Phytophthora sp. causing as examples potato late blight [ 43 ] and collar rot of Kauri, Agathis australis [ 44 ]. The kingdom Rhizaria belongs to the paraphyletic protists [ 45 ] and was represented by an OTU within the phylum Cercozoa that was identified from two individual plants of E. repens . There are several root endophytic and plant pathogenic Cercozoa [ 46 ] including, as examples, Plasmodiophora brassicae causing clubroot in crucifers and Spongospora subterranea causing potato powdery scab disease [ 47 ]. There was a large degree of variation in the OTU richness identified from each root system from the five sites. Across all sites, each plant had an average of 151 OTUs determined by direct amplicon sequencing and an average of 8 isolates were cultured from each plant from a total pool of 715 different OTUs determined by direct amplicon sequencing. The fungal OTUs identified by direct amplicon sequencing from E. repens belonged to 31 taxonomic classes ( Table 1 ) from a total of 56 fungal classes recognised in the UNITE database ( https://unite.ut.ee/ , accessed on 1 February 2019 [ 36 ]). 4.2. Comparison Between the Cultured and Directly Sequenced Community of Site III The endophyte community identified by direct amplicon sequencing was much more species rich than the cultured community. A total of 349 OTUs, belonging to 21 classes and six divisions, were identified from site III using amplicon sequencing ( Table 1 and Figure 1 ). In comparison, only 27 OTUs, from four classes belonging to one division, was identified using cultures ( Table 3 ). Using direct amplicon sequencing, it also became clear that all plants hosted endophytes which were not evident or detectable from the culturing technique alone. It was hypothesised that the most widespread fungal species would also be the ones that were predominantly cultured. A total of 48 OTUs were identified across all plants of site III using amplicon sequencing and, interestingly, only four of these OTUs/species names were shared with the cultured community. The overlapping species included Ophiosphaerella sp. and Periconia sp. (Dothideomycetes), Glarea sp. (Leotiomycetes) and Gaeummanomyces graminis (Sordariomycetes). Ophiosphaerella sp. and Periconia sp. were among some of the species cultured relatively frequently. However, Glarea sp. and Gaeummanomyces graminis were only isolated once. An additional six species identifications were shared between the two types of methods and included Dothideomycetes sp. 2 and 3 (OTU3 and OTU4—most likely Pleosporales sp., Supplementary Table S3 ), Chaetosphaeriaceae sp. (OTU19), Diaporthe sp. (OTU20), Lasiosphaeriaceae sp. (OTU23), Sordariomycetes sp. 1 (OTU24—most likely Falciphora sp.) and Xylariaceae sp. (OTU27). The endophyte that was cultured from all roots ( Leptodontidium sp.; OTU17) is surprisingly not on the list of endophytes found in all plants from site III identified by direct amplicon sequencing. The identification of OTU17 was not straightforward ( Supplementary Table S3 ) and if this OTU had been identified as Helotiales sp. then there would have been a match to the 48 OTUs that were present in all ten plants of site III. Several culturable fungi were found in the amplicon sequencing dataset with examples such as Alternaria spp., Aspergillus spp., Trichoderma spp. and Verticillium spp. which were not cultured. This suggests that the cultured endophyte community is a fraction of what could potentially be cultured. In addition, most of the widespread fungi from direct amplicon sequencing were not recovered. Jayawardena et al. [ 48 ] suggest that the fast growing fraction is cultured and that these fungi might not represent the most widespread in the community. Some endophytes could be antagonistic to others on isolation media and some could be more sensitive to the surface sterilisation procedure than others. A limited number of studies have compared the fungal community estimated by direct sequencing with the community estimated by culturing methods in grasses. Yuan et al. [ 49 ] found that the cultured community on MEA had a few taxa overlapping with the directly sequenced community from wild rice, Oryza granulata . However, Tejesvi et al. [ 25 ] did not find any similarities between the cultured community on MEA and PDA, and the directly sequenced community of fungal root endophytes of the wavy hair grass, Deschampsia flexuosa . Our study of root endophytes of E. repens shows that the cultured endophytes are both a subset of the total community explored with direct amplicon sequencing and that most of the cultured endophyte set do not overlap with the amplicon dataset. The non-existing overlap for the majority of OTUs could reflect errors in the identification process. However, high percent identity scores were used and the same database (UNITE) as well as barcoding region (ITS) were employed. It is possible that the lack of overlap in the two communities is due to the use of different forward primers. For direct amplicon sequencing, fITS7 was used, whereas ITS1 was used for the cultured communities. fITS7 is more specific to fungi and was used in the amplicon sequencing to reduce the co-amplification of plant DNA; in the cultured fungal sequencing this was not an issue. In both the studies by Tejesvi et al. [ 25 ] and Yuan et al. [ 49 ] different primer pairs were employed for culture-dependent and -independent identification and the studies came to very different conclusions, no overlap and some taxa overlapping, respectively. Dissanayake et al. [ 50 ] also used different primer pairs and found 53% species composition overlap when they studied the endophyte communities of stems of grapevine, Vitis vinifera . They identified their cultured community using nine different barcoding regions and perhaps emphasis should be put on good identification of the cultured community. Studies will often explain that they assigned a name to their OTU based on the percent similarity obtained from the top hit of a database. Thus, another possibility for the difference in community overlap is the choice of percent similarity used when assigning names to OTUs. Tejesvi et al. [ 25 ] used 95% homology and had no overlap, Dissanayake et al. [ 50 ] used 90% for genera and 97% and above for species with 53% overlap and Yuan et al. [ 49 ] used 99% or above and found little overlap. Based on this, to get good correlation between cultured community and directly sequenced community using a middle ground might be necessary. Nilsson et al. [ 51 ] showed that the intraspecific ITS variability is dependent on species so there is no common yardstick for the variation expected in a fungal genus, family or any higher taxon. There is no one universally applicable percentage cut off value. However, 3% has become widely used [ 52 ]. Gazis et al. [ 53 ] and Luo et al. [ 22 ] compared diversity determined by 1% and 3% clustering criteria. Luo et al. [ 22 ] examined the root endophyte community from rosette grass, Dichanthelium acuminatum ; switchgrass, Panicum virgatum ; and pitch pine, Pinus rigida and found that the two cut off values resulted in similar community structure estimations. In contrast, Gazis et al. [ 53 ] studied three species complexes within the Sordariomycetes and found that increasing the percent similarity cut off value increased the number of OTUs. The intraspecific variation within the ITS region from fungi within the INSD database was examined by Nilsson et al. [ 51 ] and they found species with very low intraspecific variation 0.2% ( Aspergillus fumigatus and Candida albicans ) and species with very high variation 24.2% ( Xylaria hypoxylon ). The big difference in intraspecific variation between species might explain why Gazis et al. [ 53 ] and Luo et al. [ 22 ] had conflicting results. Across all the examined species, Nilsson et al. [ 51 ], found that the majority of species had intraspecific variability of 0–1%, and thus a 1% cut off value was adopted in this study. It is also possible that the time lapse between querying UNITE about individual sequences made a difference to identification. However, only approximately three months passed between identifying the cultures and the sequenced community. It is therefore most probable that the pattern is real. 4.3. The Influence of Media on OTU Richness This is the first evaluation of how the most commonly used media for isolation of endophytes of grasses can influence the isolation success. The majority of OTUs were discovered on PDA (18 OTUs) followed by MEA (10) and 2% MEA (9). The overall difference in these three media is the sugar source and the strength. PDA is composed of the monosaccharide dextrose and potato extract while MEA has dextrin, the disaccharide maltose and vegetable peptone [ 54 ]. A few studies of endophytes of grasses have isolated endophytes on several media but they do not discuss their influence on endophyte diversity [ 24 , 25 , 55 , 56 ]. Verma et al. [ 18 ] isolated endophytes from the neem tree on four different media and found that the maximum number of endophytes was recovered from PDA. The only known previously successful biocontrol agent, Epicoccum ssp. (OTU9 and OTU10) was only isolated on PDA. Gaeumannomyces graminis (OTU22), a known pathogen of barley and wheat [ 57 ], was only isolated on PDA. In contrast, Ophiosphaerella spp. (OTU11, OTU12 and OTU3) was isolated on all three media and has also been reported as a pathogen of a range of grasses. Known pathogens are often found as endophytes within non-symptomatic plants [ 58 , 59 , 60 ], which highlights the knowledge gap of the functional roles of endophytes and the abiotic as well as biotic cues that might change those roles."
} | 3,714 |
19519767 | null | s2 | 9,734 | {
"abstract": "Myxococcus xanthus is a common soil bacterium with an intricate multicellular lifestyle that continues to challenge the way in which we conceptualize the capabilities of prokaryotic organisms. Myxococcus xanthus is the preferred laboratory representative from the Myxobacteria, a family of organisms distinguished by their ability to form highly structured biofilms that include tentacle-like packs of surface-gliding cell groups, synchronized rippling waves of oscillating cells and massive spore-filled aggregates that protrude upwards from the substratum to form fruiting bodies. But most of the Myxobacteria are also predators that thrive on the degradation of macromolecules released through the lysis of other microbial cells. The aim of this review is to examine our understanding of the predatory life cycle of M. xanthus. We will examine the multicellular structures formed during contact with prey, and the molecular mechanisms utilized by M. xanthus to detect and destroy prey cells. We will also examine our understanding of microbial predator-prey relationships and the prospects for how bacterial predation mechanisms can be exploited to generate new antimicrobial technologies."
} | 298 |
35684284 | PMC9182583 | pmc | 9,736 | {
"abstract": "Despite the widespread occurrence of fungal endophytes (FE) in plants inhabiting arid ecosystems, the environmental and soil factors that modulate changes in FE diversity and community composition along an aridity gradient have been little explored. We studied three locations along the coast of the Atacama Desert in Chile, in which the plant Aristolochia chilensis naturally grows, and that differ in their aridity gradient from hyper-arid to semi-arid. We evaluated if root-associated FE diversity (frequency, richness and diversity indexes) and community composition vary as a function of aridity. Additionally, we assessed whether edaphic factors co-varying with aridity (soil water potential, soil moisture, pH and nutrients) may structure FE communities. We expected that FE diversity would gradually increase towards the aridity gradient declines, and that those locations that had the most contrasting environments would show more dissimilar FE communities. We found that richness indexes were inversely related to aridity, although this pattern was only partially observed for FE frequency and diversity. FE community composition was dissimilar among contrasting locations, and soil water availability significantly influenced FE community composition across the gradient. The results indicate that FE diversity and community composition associated with A. chilensis relate to differences in the aridity level across the gradient. Overall, our findings reveal the importance of climate-related factors in shaping changes in diversity, structure and distribution of FE in desert ecosystems.",
"introduction": "1. Introduction All terrestrial plants in natural ecosystems are considered to harbor fungal endophytes (FE) in their tissues. In most plant species, except for some grasses, FE are horizontally transmitted through spores, having the capacity to colonize a wide range of hosts [ 1 ]. Horizontally transmitted FE are abundant and highly diverse in plants [ 2 , 3 , 4 , 5 ] and may benefit their hosts by improving growth and resistance to diverse biotic and abiotic factors [ 1 ]. FE diversity is strongly influenced by numerous host-related and environmental factors, such as host genotype, host structural and chemical traits, precipitation, temperature and soil chemistry [ 6 , 7 , 8 ]. FE abundance and diversity usually vary across the latitude and an annual rainfall gradient, decreasing from the tropics to boreal and arctic regions [ 9 , 10 ]. In the tropics and semi-arid regions, FE diversity is higher during the wet seasons in comparison to dry seasons [ 11 , 12 , 13 ]. Thus, annual precipitation appears to be a crucial factor for determining FE diversity and community composition in different ecosystems [ 6 , 14 , 15 , 16 ]. For example, for the tropical tree Metrosideros polymorpha (Myrtaceae) in Hawaii, rainfall was one of the key factors structuring foliar FE communities across the landscape [ 6 ]. Moreover, Giauque and Hawkes [ 17 ] reported that past and present precipitation levels were the most important predictor factors of FE communities in savanna grasslands across a steep precipitation gradient. Few studies have characterized FE diversity and communities in desert environments [ 18 , 19 ]; particularly, how they vary as a function of precipitation. Understanding variations in FE diversity and composition in desert environments is relevant to predicting shifts in the distribution range of FE in contrasting arid environments under climate change. Deserts are characterized by extreme environmental conditions, where water deficit is one of the major limiting factors constraining species distribution and diversity [ 20 ]. Soil microbial diversity (bacteria and fungi), in general, declines towards the aridity gradient increases [ 21 ]. Some edaphic factors such as soil water availability, pH and nutrients may change in response to the long-term effects of the climate resulting from aridity gradients [ 22 ]. Importantly, they also seem to be relevant in influencing FE diversity in deserts [ 19 ]. For example, a study in the Sonora Desert on foliar FE diversity showed that endophytic fungi were isolated approximately 11- to 40-fold less frequently than that expected by the latitude of the study sites [ 19 ], suggesting that edaphic factors related to arid environments restrict endophyte distribution. Whereas edaphic factors appear to highly influence variations in soil microbial composition [ 23 ], the importance of these factors shaping FE communities at a large scale is not fully understood [ 24 ]. In contrast with the numerous studies on foliar FE communities in contrasting environmental and/or geographic sites, studies on the changes in diversity and community composition of root FE along an aridity gradient are still limited [ 25 ]. Here, we worked in three locations along the coast of the Atacama Desert in Chile, in which the perennial herb Aristolochia chilensis naturally grows, and that differ in their aridity gradient from hyper-arid to semi-arid ( Figure 1 ). Using a culture-dependent method, we characterized the diversity and community composition of FE associated with the roots of A. chilensis , growing naturally across the aridity gradient. The aims of the study were to: (1) evaluate how root FE diversity varies along the aridity gradient; (2) determine the degree of structural similarity in root FE communities across locations; and (3) reveal if edaphic factors co-varying with aridity (soil moisture, soil water potential, pH and nutrients) drive the structure of root FE communities. Since FE distribution is restricted by precipitation, it is expected that root FE diversity is lower in the more arid location and that it gradually increases towards the aridity gradient declines. We also predicted that locations that have the most contrasting environments (hyper-arid vs. semi-arid) would show a more different root FE community composition. A manipulative field experiment was additionally performed to assess potential variation in root FE abundance as a function of water availability.",
"discussion": "3. Discussion This study provides evidence that variations in root FE diversity and community composition associated with the endemic species A. chilensis relate to differences in the aridity level along the gradient. Our results showed that: (1) Both FE frequency and diversity were considerably lower in the more arid location (Huasco) than in the wettest locations (Totoralillo and Quilimarí); (2) FE richness indexes gradually increase towards the aridity gradient declines; and (3) FE communities were dissimilar across the aridity gradient, and soil water availability was a key factor in structuring FE community composition. Additionally, the abundance distribution of certain dominant FE taxa changed across the gradient, suggesting the importance of some fungal genera in structuring FE communities. Our proposed pattern, that root FE diversity gradually decreases when the aridity index increases (H < T < Q) was partially reached. The richness indexes fulfilled the expected pattern; Chao and Bootstrap indexes were observed that significantly decreased as the aridity increased. Contrary, FE frequency and the Shannon diversity did not wholly follow this pattern. As expected, both were significantly lower in the hyper-arid location of Huasco; nevertheless, both showed their highest values in the arid location of Totoralillo. Interestingly, Totoralillo showed the highest soil water availability, even when it did not experience the highest level of precipitation and the lowest aridity index. The latter is likely associated with microclimate conditions, highlighting the importance of integrating both local and regional environmental factors in studying FE community composition. Our results concur with previous studies, which showed that marked aridity gradients or distinct aridity conditions modulate rhizosphere and endosphere fungal diversity and community composition [ 25 , 30 , 31 ]. For example, there is evidence that foliar FE richness in the annual plant Brachypodium sp. was greater in wetter sites (over 1000 mm of annual precipitation) than in the drier sites along an aridity gradient (less than 500 mm of annual precipitation) [ 25 ]. By contrast, for the cactus Opuntia ficus-indica , it was shown that alpha fungal diversity in the rhizosphere and endosphere did not change along a bioclimatic gradient from 1200 to 200 mm of annual precipitation [ 31 ]. However, the aridity gradient significantly contributed to differences in fungal species composition (beta diversity) [ 31 ]. We found that the locations of A. chilensis , which had the most contrasting environments, showed dissimilar root FE communities. Whereas the more arid locations along the gradient (Huasco and Totoralillo) showed similar FE communities, both showed dissimilar FE communities to the wettest location (Quilimarí). Thus, aridity appears to play a key role in driving FE species turnover. Consistently, our data revealed a significant variation in FE community composition as a function of soil water potential and soil moisture. These results agree with previous observations by Herrera, et al. [ 32 ], who showed that the abundance of root endophytic fungi associated with the grass Bouteloua gracilis considerably increased under irrigation. Soil moisture is likely one of the major factors determining soil microbial communities [ 33 ], suggesting that soil moisture pulse events stimulate the activity of soil microbes [ 34 , 35 ]. Moreover, the results of our field experiment (in the Northern location along the gradient) supports these findings, showing that a greater soil water availability was associated with a higher frequency of root FE. Even though pH and nutrients are likely associated with inter-site variation in soil archaeal and bacterial communities [ 36 , 37 ], here we found that neither pH nor nutrients shaped root FE communities. Our study identified FE taxa that are specific for each location. Whereas Fusarium and Trichoderma seem to be generalist endophytes, i.e., with the ability to colonize locations with contrasting conditions of aridity, Penicillium and Clonostachys were observed to be habitat-specific FE taxa. Penicillium was dominant in the more arid locations (30 and 100 mm of annual precipitation, respectively), while the opposite pattern occurred for Clonostachys , which was almost absent in the more arid locations, but was dominant in the wettest location (over 250 mm of annual precipitation). Thus, our data suggest that extreme aridity selects for specific FE taxa, which likely contribute to variations in FE community composition across the gradient. Some of these taxa such as Fusarium , Penicillium and Trichoderma have previously been reported as common endophytes in plants inhabiting arid and semi-arid ecosystems [ 18 , 19 , 38 ]. The genus Penicillium , for example, has been found to be a dominant FE in below-ground tissues of other plant species native to the Atacama Desert in Chile, including Chenopodium quinoa and Prosopis chilensis [ 39 , 40 ]. FE isolated from the Atacama Desert seem to be a promising strategy to alleviate abiotic stress in host plants [ 39 , 40 , 41 ]. Therefore, this study contributes to the identification of new FE strains with potential benefits for plants to survive and tolerate stressful conditions in deserts. Understanding how arid-adapted FE taxa relate to the ability of A. chilensis to tolerate extreme arid conditions in the Atacama Desert is key to predicting the ecological significance of root FE in deserts. Further research in this context should consider testing potential differences in host stress tolerance depending on the symbiotic interaction with different aridity-adapted FE strains. Desert environments, despite the hostile conditions (low water availability and poor nutrient conditions), appear to harbor rich rhizosphere and endosphere fungal communities [ 30 , 42 ]. Our findings showed that environmental precipitation and soil water availability are relevant factors contributing to FE diversity and community composition in A. chilensis , revealing the importance of climate-related factors in shaping FE structure and distribution in desert ecosystems. Although this research covered only a few plant individuals in each location, our data supported our main prediction, that FE diversity and community composition vary as a function of aridity. Studies on changes in community composition of root FE along an aridity gradient are still limited [ 25 ]. Thus, our study provides new evidence in the topic and highlights the importance of considering environmental gradients as an appropriate approach to understand changes in the diversity, and the structure of FE communities. Large-scale studies across climate gradients, to investigate species adaptations to environmental pressures, are becoming common [ 43 , 44 ], and seem to be a promising alternative for climate change research. Understanding how FE community composition varies as a function of precipitation in deserts is critical to comprehending the whole ecosystem function in the face of climate change. The latter is particularly important for the Atacama Desert, the driest temperate desert on Earth [ 45 ], where the current decrease in precipitation and increase in temperature are the major threats of species distribution and overall diversity."
} | 3,367 |
20482743 | null | s2 | 9,737 | {
"abstract": "Spore-forming, Gram-positive sulfate-reducing bacteria (SRB) represent a group of SRB that dominates the deep subsurface as well as niches in which resistance to oxygen and dessication is an advantage. Desulfotomaculum reducens strain MI-1 is one of the few cultured representatives of that group with a complete genome sequence available. The metabolic versatility of this organism is reflected in the presence of genes encoding for the oxidation of various electron donors, including three- and four-carbon fatty acids and alcohols. Synteny in genes involved in sulfate reduction across all four sequenced Gram-positive SRB suggests a distinct sulfate-reduction mechanism for this group of bacteria. Based on the genomic information obtained for sulfate reduction in D. reducens, the transfer of electrons to the sulfite and APS reductases is proposed to take place via the quinone pool and heterodisulfide reductases respectively. In addition, both H(2) -evolving and H(2) -consuming cytoplasmic hydrogenases were identified in the genome, pointing to potential cytoplasmic H(2) cycling in the bacterium. The mechanism of metal reduction remains unknown."
} | 289 |
37566739 | PMC10445776 | pmc | 9,738 | {
"abstract": "Abstract Standing genetic variation is a major driver of fitness and resilience and therefore of fundamental importance for threatened species such as stony corals. We analyzed RNA-seq data generated from 132 Montipora capitata and 119 Pocillopora acuta coral colonies collected from Kāneʻohe Bay, Oʻahu, Hawaiʻi. Our goals were to determine the extent of colony genetic variation and to study reproductive strategies in these two sympatric species. Surprisingly, we found that 63% of the P. acuta colonies were triploid, with putative independent origins of the different triploid clades. These corals have spread primarily via asexual reproduction and are descended from a small number of genotypes, whose diploid ancestor invaded the bay. In contrast, all M. capitata colonies are diploid and outbreeding, with almost all colonies genetically distinct. Only two cases of asexual reproduction, likely via fragmentation, were identified in this species. We report two distinct strategies in sympatric coral species that inhabit the largest sheltered body of water in the main Hawaiian Islands. These data highlight divergence in reproductive behavior and genome biology, both of which contribute to coral resilience and persistence.",
"introduction": "Introduction Given ongoing climate change, it is critical to understand how rapidly changing ocean conditions impact coral population biology and resilience and how the innate adaptability of coral populations may contribute to their persistence ( Cant et al. 2021 ; Fischer et al. 2021 ). For coral reef ecosystems, which depend on the nutritional symbiosis between scleractinian coral hosts and their single celled dinoflagellate (algal) endosymbionts in the family Symbiodiniaceae ( LaJeunesse et al. 2018 ), thermal stress may lead to dysbiosis and mortality. This phenomenon is known as coral “bleaching,” whereby symbiotic cells and pigments are expelled or lost from the host tissue, leaving the bright white color of the underlying coral animal body and skeleton ( van Oppen and Lough 2009 ). Bleaching is the primary cause of mass coral mortality ( Hughes et al. 2017 ). Coral reefs are also threatened by ocean acidification resulting from the increased amount of CO 2 in the atmosphere that dissolves in the surface ocean, changing carbonate chemistry and lowering the pH ( Hoegh-Guldberg et al. 2007 ). Understanding the mechanisms that underlie coral response to long-term environmental stress is, however, challenging, given the genetically diverse collection of organisms (cnidarian animal host, algal symbionts, prokaryotic microbiome, fungi and other eukaryotes, and viruses) that comprise the holobiont and contribute to its health and resilience ( Veron 2000 ). Furthermore, corals are impacted by persistent abiotic stresses (e.g., diurnal and seasonal light and temperature variation) and a plethora of interacting taxa (e.g., algae, fish, and viruses) that are of nonholobiont provenance, making these complex models for field studies. We previously generated high-quality genome assemblies from two Hawaiian coral species ( Stephens et al. 2022 ). The first is at chromosome-level from the rice coral, Montipora capitata , and comprises 14 large scaffolds that likely represent the 14 chromosomes predicted in other Montipora species ( Kenyon 1997 ). The second is from the cauliflower coral, Pocillopora acuta , and is the first polyploid (i.e., triploid) genome assembly generated from Scleractinia. Whereas the mechanisms that give rise to polyploidy in corals, and its effects on organismal fitness, are unknown, it can result from genome duplication within a species (autopolyploidy) or from hybridization of two different species (allopolyploidy). This process often precipitates drastic changes in cell organization and genome structure and can alter gene expression, genome stability, cell physiology, and the cell cycle ( Wertheim et al. 2013 ). In some animals, triploidy may be beneficial with respect to improved growth and pathogen resistance ( Kang and Rosenwaks 2008 ). This observation increases interest in corals with respect to how changes in their genomic configuration may contribute to the evolution of stress resistant genotypes. To advance understanding of ploidy variation in corals and differences in reproductive strategies of sympatric species, we generated and analyzed RNA-seq data from fragments (i.e., nubbins) of M. capitata and P. acuta colonies collected from across six reefs in Kāneʻohe Bay, a 45 km² sheltered water body in Oʻahu, Hawaiʻi. Analysis of single-nucleotide polymorphisms (SNPs) in each coral sample was used to investigate genetic diversity, ploidy, and reproductive strategy in these two sympatric species.",
"discussion": "Discussion In this study, we generated RNA-seq data from colonies of P. acuta and M. capitata collected from six reefs distributed across Kāneʻohe Bay, Oʻahu, Hawaiʻi. We report significant differences in ploidy and reproductive strategies between the two sympatric species, with P. acuta derived from a mix of diploid and triploid clonal lineages and M. capitata being a highly heterozygous, panmictic outbreeder. The Adaptive Advantage of Triploidy in Corals Is Currently Not Known The role of triploidy (or any form of polyploidy) in corals is not well understood. Although triploids are rare in wild populations, they occur frequently in commercially farmed plants and animals, such as oysters and some banana cultivars, often conferring beneficial commercial traits such as improved growth, pathogen resistance, and through infertility, protection of superior, adapted genotypes ( Kang et al. 2013 ). Triploids may also enhance the rate of autotetraploid formation ( Husband 2004 ). Triploids occur in the coral Acropora palmata and may be a path to generating different ploidy levels in different members of this genus ( Kenyon 1997 ; Baums et al. 2005 ). Our results show that triploidy is common in Kāneʻohe Bay P. acuta ( supplementary fig. S1 and supplementary table S3, Supplementary Material online) and has a higher abundance (63% at the sites sampled) than diploids (only 37%). This stands in clear contrast to M. capitata , which is completely (barring a single, possibly, chimeric sample) diploid. All methods for assessing sample relatedness (i.e., shared SNPs, relatedness metrics, PCA, and admixture analysis) predict that diploid samples are different from triploids, that is, there is clear separation between these groups ( figs. 2 , 3 , 4 , and 5 ). The only exception is a single diploid sample (Pacuta_HTHC_TP5_1415) that has higher similarity to triploid than diploid samples (although not high enough to be considered part of the closely related triploid Group 1). This individual could be an example of reversion (i.e., from triploid to a diploid) or be the extant member of the progenitor lineage of triploid Group 1. Our results suggest that the diploid P. acuta are both sexual outbreeders and generate asexual brooded larvae, as previously described ( Richmond and Jokiel 1984 ; Yeoh and Dai 2010 ; Combosch and Vollmer 2013 ; Gorospe and Karl 2013 ; Schmidt-Roach et al. 2014 ; Nakajima et al. 2018 ). Triploidy may have arisen from self-fertilization of a P. acuta egg, followed by fertilization by a foreign sperm, or one of the two gametes was diploid and provided two closely related sets of alleles. Alternatively, failure of the ovum to extrude the second polar body after fertilization could lead to triploidy. These are the most common mechanisms for generating triploid plants and animals ( Rosenbusch 2008 ; Carson et al. 2018 ). The evolution of triploid genotypes in P. acuta may be explained by adaptation to local conditions in Kāne‘ohe Bay, possibly allowing them to outcompete ancestral diploid genotypes. It is plausible that SNP allele frequency distributions, which are the basis of our estimation of ploidy, are explained by chimeric P. acuta colonies. Evidence exists for chimerism in corals through fusion of two or more genetically distinct individuals ( Willis et al. 2006 ; Rinkevich et al. 2016 ; Oury et al. 2020 ) as well as mosaicism via somatic cell mutations ( Willis et al. 2006 ; Schweinsberg et al. 2015 ). Nonetheless, the two-peaked SNP distributions of P. acuta are difficult to explain under chimerism because the fused colonies would have to comprise roughly equal amounts of one haploid and one diploid individual to generate this result, which is unlikely to have occurred in so many closely related colonies from across the bay. If cells from one of the fused colonies were present at a much higher frequency than the other (which is more likely than them having equal proportions), then we would see an increase in the frequency of SNP alleles with support toward the ends of the distribution (as observed for the one, putative chimeric M. capitata sample). In addition, k -mer analysis of the reference triploid genome of P. acuta from Kāne‘ohe Bay ( Stephens et al. 2022 ) provides results that are consistent with our current findings. Given these results, we hypothesize that the most likely scenario to explain our data is triploidy in many P. acuta individuals, rather than fused/mixed diploids. Differences in Reproductive Strategies of Sympatric Coral Species Our results also suggest that P. acuta in Kāne‘ohe Bay almost exclusively undergoes asexual reproduction, with only a few genets giving rise to colonies in the bay. This “genotypes everywhere” result has previously been found for Kāneʻohe Bay Pocillopora damicornis populations ( Gorospe and Karl 2013 ). Using microsatellite data, these authors studied a single reef and found that >70% of the colonies comprised seven genotypes with high clonal propagation. Neighboring reefs however conformed to a genetic panmixia model with no interreef genetic structure. Our results support this model, showing the existence of at least eight groups of P. acuta samples (with each group representing a genet that has given rise to multiple independent colonies [ramets]) with broad distribution across Kāneʻohe Bay. The presence of a limited number of genets in the bay, and the absence of isolation by distance, even when individual reefs show genetic structure is puzzling. This result may be explained by microhabitat variability that selects for particular genotypes that occupy specific niches in each reef ( Gorospe and Karl 2011 ). These locally adapted genotypes disperse via asexual reproduction given that no major barriers exist for larval dispersal in Kāneʻohe Bay. This result might also be explained by a genetic bottleneck. A recent natural event, such as severe bleaching that caused mass coral mortality (e.g., the 2014–2015 Kāneʻohe Bay bleaching event ( Bahr, Jokiel, Toonen 2015 )), may have removed much of the P. acuta from this region. The subsequent repopulation of Kāneʻohe Bay by surviving corals, or recolonization from different regions, coupled with asexual reproduction, would result in the observed, low genetic diversity. In addition, this would also explain why all the P. acuta samples analyzed in this study, even those not in the same clonal group, have relatively high relatedness. The majority of samples (even between diploids and triploids) has relatedness values around 0.25 (i.e., the relatedness expected between parent and offspring or full sibling; fig. 3 ; supplementary fig. S3 and supplementary table S6, Supplementary Material online). In contrast, most relatedness values of M. capitata samples were close to zero, that is, unrelated individuals ( fig. 7 ; supplementary fig. S6 and supplementary table S8, Supplementary Material online). This result for M. capitata has been previously reported ( Concepcion et al. 2014 ; Caruso et al. 2021 ). A recent survey of nearly 600 colonies of this species in Kāneʻohe Bay found very few clonal individuals and no evidence of isolation by distance ( Caruso et al. 2021 ). Colonies that were potentially derived from the same genet were almost exclusively found at the same collection site, consistent with our observations. Study Limitations Our study makes extensive use of RNA-seq data that was originally generated as part of a mesocosm experiment not relevant to the results of this research. Whereas RNA-seq data are not commonly used in population genetics, in this case, we believe that they provide valuable insights into coral biology that can inform follow-up DNA-based sequencing projects. We acknowledge however that ploidy is more challenging to interpret using RNA-seq data. We have previous described, using DNA sequencing data, a triploid P. acuta genet from Kāneʻohe Bay ( Stephens et al. 2022 ), which was included in this study and was identified using RNA-seq data as a triploid. To the best of our knowledge, all bioinformatic approaches for ploidy determination (such as nQuire and visualization of allele frequencies, which were used by this study) are designed for use with DNA, not RNA data. Thus, we cannot fully discount allele-specific expression (ASE) as an alternative explanation for the patterns that we observe. However, we believe it is unlikely that ASE has affected our results, for the following four reasons: 1) we have clear DNA evidence for triploidy from one of the samples ( Stephens et al. 2022 ). 2) If ASE is affecting our results, it would have to be strongly affecting some groups of samples and not others (i.e., ASE is only occurring in putative triploid and not diploid lineages and not in the triploid with DNA evidence). 3) ASE typically occurs at different rates across the genome, that is, ASE produces an uneven distribution of expression ratios. Our results suggest that all loci are being affected at the same rate, which would support variation in chromosome copy number and not locus-specific allelic expression modification. And 4), coral genomes have relatively low rates of methylation ( Trigg et al. 2022 ), with 11.4% of CpG sites in the M. capitata genome being methylated, with this value being 2.9% in P. acuta . Given that methylation would be the most obvious mechanism for ASE, the low methylation rate in P. acuta makes ASE a less likely explanation for the ploidy results. Regarding the analysis of samples with mixed ploidy, few of the available population genetic techniques accept nondiploid data and, none that we are aware of, accept data with mixed ploidies. As a result, all samples were treated as diploid, which may adversely affect results from the putative triploid samples because it would bias our analysis to just biallelic sites. However, given that we expect most variant sites in the genome to be biallelic (because multiple mutations occurring at a single site to create a multiallelic site are less likely than a single mutation to create a biallelic site), we believe that our approach is valid given the current techniques and data available. Furthermore, given that a variety of data analysis tools were used, and all led to the same conclusions, we believe our results are robust. These insights should prove valuable for designing DNA-based studies that focus on generating additional population genetic data not only from Kāneʻohe Bay but also from other locations in the Hawaiian Islands. There is currently very little data available for P. acuta , preventing us from comparing our results with other populations or studies done in this region. Final Remarks The data presented in this study underline how selection may be acting in a divergent manner to forge ecologically successful lineages. We find that two sympatric species, living in a sheltered Hawaiian bay, follow disparate strategies that enable their persistence in an environment that is strongly impacted by human activity, including warming events, freshwater incursion, and dredging ( Bahr, Jokiel, Toonen 2015 ). Montipora capitata relies on strict outbreeding to generate high standing genetic variation, likely as a “defense” against changing local environments. In contrast, P. acuta appears to undergo periodic polyploidization events, perhaps triggered by local stress, that putatively generate fitter, clonal groups that allow persistence (or reestablishment after stressful events) of populations in Kāneʻohe Bay. The next steps in this research are to expand our understanding of how these patterns relate to organismal fitness by studying the response of Hawaiian corals with divergent genotypes to the same regime of environmental stress."
} | 4,137 |
30911144 | PMC6443080 | pmc | 9,740 | {
"abstract": "Plant range expansion is occurring at a rapid pace, largely in response to human-induced climate warming. While the movement of plants along latitudinal and altitudinal gradients is well documented, effects on the belowground microbial communities remains largely unknown. Further, in range expansion not all plant species are equal: in a new range the relatedness between range-expanding plant species and native flora can influence plant-microbe interactions. Here we used a latitudinal gradient across Europe to examine bacterial and fungal communities in the rhizosphere and surrounding soils of range-expanding plant species. We selected range expanders with and without congeneric natives in the new range, and as a control, the congeneric natives, totaling 382 plant individuals collected across Europe. In general, a plant’s status as range expander was a weak predictor of bacterial and fungal community composition. However, microbial communities of range-expanding plant species became more similar to each other farther from their original range. Range expanders unrelated to the native community also experienced a decrease in the ratio of plant pathogens to symbionts, giving weak support to the enemy release hypothesis. Even at a continental scale the effects of plant range expansion on the belowground microbiome are detectable, though changes to specific taxa remain difficult to decipher.",
"discussion": "Results & Discussion Overall, rhizosphere and bulk soil communities were significantly different from each other, both in community overlap as visualized by a PCA ( p < 0.001 for both bacteria and fungi; Figure 2A and 2B ), and in taxa overlap ( Figure 2C and 2D ). We found 47,704 bacterial phylotypes and 9,374 fungal phylotypes in soils, and 33,939 bacterial phylotypes and 6,438 fungal phylotypes in the rhizosphere. Further, there was low community overlap among plant individuals in both soil (averaging 4,092 (8%) unique bacterial taxa and 523 (5.5%) unique fungal phylotypes per sample) and the rhizosphere (averaging 1,932 (5.6%) unique bacterial phylotypes and 257 (4%) unique fungal phylotypes per sample). High microbiome diversity among 11 plant species is not a surprise, especially because the selected plants represent a range of phylogenetically and ecologically distinct species 36 , 46 , 47 . Across the gradient, plant species was the strongest predictor of bacterial and fungal community composition in both soil and rhizosphere environments, explaining 7 to 14% of the variation ( Figure 3 ; Supplementary Table 2 ), and plant genus a proxy of phylogenetic relatedness ( Supplementary Figure 1 ) provided no additional prediction power. Conversely, the effects of plant grouping (unrelated range-expander, related range-expander and native) and latitude had a much smaller effect on microbial composition and explained a maximum of 2% of the variation in all cases. In general, soil abiotic factors also had a minor influence on variation, accounting for less than 1% of the variation for all factors (e.g. pH, N, C), except for soil bacterial communities where pH explained approximately 5% of the variation. The relatively minor effect of soil abiotics on microbial communities - compared to previous studies 25 - can be explained by the small variation in soil factors across the gradient and between plants ( Supplementary Figure 2 ), as was the goal of choosing plant species growing on the same parent soil material. In comparison, other studies have been more focused on elucidating patterns in microbial community composition relative to changes in abiotic factors 26 , 28 , 48 . Thus, the differences observed here are more likely due to plant species effects sensu 47 , such as plant ecology, relatedness with native flora, and life history traits 45 , 49 , 50 . In support of our hypothesis, we found that range-expanders farther from their original range had more similar microbial communities to other plant individuals. Put another way, the variation in community composition decreased among individuals in the new range. Further, there were negative correlations between “range” (country samples were collected from) and community dissimilarity for all plant groups ( Figure 4 and Supplementary Table 3 ); latitude and distance, gave equivalent results. This pattern was significant for bacterial communities in the soil and rhizosphere of all plant types (rho varied between -0.08 and -0.32 and p < 0.05 for all). However, for fungal communities, correlations were only observed in soils (rho varied from -0.10 to -0.13, p < 0.05 for all) and not in the rhizosphere. The negative correlation between range and community dissimilarity was strongest in unrelated range-expander species ( Supplementary Table 3 ). We also found a significant difference in the degree of microbial community similarity by plant group yet there was an interaction of country in two scenarios (p< 0.0001 in all cases) ( Supplementary Table 4 ). This suggests that controls on native and range-expanding plant microbiome community composition differs across the gradient. For instance, native plants microbiomes (and to a lesser extent related range-expanders) may be more influenced by a long-term co-evolutionary history that would be consistent across this latitudinal gradient 51 , 52 , while unrelated range expander microbiome patterns might be more determined by more recent spatial effects and the native (neighbor) plant community 53 . Because we used a survey to explore changes to the belowground microbiome across a natural range expansion transect, we were unable to test for co-evolutionary history between microbes and plants. Still, our results suggest that future studies should be designed with this process in mind, particularly to identify the role of the microbial community for plant adaptions during climate change 39 , 54 . While community structure became more similar across the gradient, changes in bacterial richness and fungal richness was much more variable ( Figure 5 ; Supplementary Table 5 ). Under unrelated range-expanders, fungal alpha diversity in the rhizosphere of significantly increased with distance from the original range (rho = 0.36 p <0.001 in the rhizosphere, p>0.05 in soil). However, related range-expanders showed no relationship between fungal diversity and distance from original range (p > 0.05 for both soil and rhizosphere) in comparison to native plants which where fungal alpha diversity increased with latitude in both the rhizosphere (rho = 0.20, p < 0.05 ) and in the bulk soil (rho = 0.23 p < 0.05 ). The mechanisms behind increased fungal diversity in the rhizosphere of unrelated range-expanders remains in question. It could be that if range-expanding plants do not need to invest in belowground defense 55 , 56 the rhizosphere becomes accessible for a larger proportion of microbes, though this varies by plant species 57 . Alternatively, it has been proposed that exotics and range-expanders promote high microbial diversity as part of a defense mechanism 53 , 57 . The later proposition, that range-expanding plants enrich their rhizosphere, is congruent with our findings that community composition becomes more similar among individuals in the northern part of the range ( Figure 4 ), and that unrelated range-expanders had higher fungal and bacterial diversity in their rhizosphere and lower diversity in the associated soils (p < 0.0001 in all cases) ( Supplementary Table 6 ). Overall, the inconsistency between the responses of the two expanders suggests that related and unrelated range-expanders have different controls on microbial diversity. Further, the variability in alpha diversity patterns indicates that alpha diversity and community similarity are affected by different mechanisms. It has been proposed that in novel ecosystems plant success or failure is based on reduced exposure to soil-borne pathogens combined with continued association with symbionts 58 , 59 . We applied this concept here and used FunGuild 60 to test how the abundance of potential fungal functional groups change as range-expanding plants move farther from their original range. Specifically, we examined potential plant pathogens and arbuscular mycorrhizal fungi (AMF), as these are the relevant mutualistic symbionts for most of our plant species, except for the crucifers. However, we could detect no significant change in the relative abundance in either of these groups under range expanding plant species ( Supplementary Figure 3 ). Though there was a significant positive correlation in the ratio of plant pathogens to symbionts across the transect (rho = 0.31 p< 0.001 ) ( Supplementary Table 7 ). On the other hand, under native plants the relative abundance of plant pathogens increased in both the soil and rhizosphere from south to north (rho = 0.23 for both). Contrary to previous studies, these results do not directly verify that range-expanders lose their specialist microbes 58 or are released from specialist enemies 61 . Instead, the results suggest that compared to natives, range expanders are exposed to fewer potential pathogens and symbionts in the new range, which has been predicted for range-expanding plant species 62 and demonstrated for introduced exotics in their new range 63 , 64 . At the same time, recent studies of plant succession 65 , 66 clearly demonstrate that plant success and nutrient cycling is tied to the microbial communities. Yet it remains unclear if the mechanisms underlying plant range-expansion are the same as those observed elsewhere. Still, these results are not without caveats. The first being that the molecular methods used are not infallible- the DNA community analysis does not assess the active microbial community nor the true functional capabilities. Thus, potential functional groupings and relative abundances of taxa cannot indicate the expected pathogenicity of these fungi in the host plant’s rhizospheres. Equally important is that for all plant groups the relative abundance of these functional groupings make up approximately 5% of the fungal community. Meaning, any changes in composition or diversity may overinflate or obscure true changes in these low abundance groups 67 and specific primers or culture work is necessary to explore functional changes more thoroughly. Our study exemplifies that high-throughput sequence data can be used to assess large-scale patterns in plant-soil associations, but future functional analyses (e.g. metagenomics and metatranscriptomics approaches) and experimental studies must be designed to take the low abundance of pathogen sequences into account. Our study contributes initial steps of identifying the patterns of changes in the plant microbiome during plant range expansion. While, microbial community and diversity dynamics change across a range expansion gradient, clarifying the mechanisms behind the observed changes would require further experimental study. In the present study, we attempted to link the concepts from plant ecology to the microbiome by assuming that plant establishment outside the native range will result in altered exposure for soil microbes. Our results suggest that while terms like ‘exotic’, ‘range-expander’ and ‘native’ are helpful descriptors in plant ecology, it should not be assumed that these labels are equally relevant to describe the belowground microbial community of such plant species. Future research will require consideration of the ecological roles of both plants and microbes 26 , 36 but currently, the ecological roles on many microbial taxa still remain unknown. At the same time, we think that this large-scale biogeographical studies of plant-soil-microbe associations of native, related and unrelated range expanders along a latitudinal gradient is an essential step to understand how climate warming-induced range-expanding plant species may assemble a new microbiome in their novel range. This approach may also stand as a model for processes that take place belowground upon the introduction of exotic plant species in a new continent. Subsequent experimental work is needed in order to understand functional consequences for invasiveness and naturalization. Almost 4% of extant global vascular flora have established outside their native range 68 , and climate change induced range expansion is not expected to slow down 69 . Though soil microbes exert strong selective pressures on plant species and communities 70 , 71 our understanding of microbial community dynamics during range expansion remains limited. Range expansion offers an opportunity to explore how global change may alter the relationship between plants and their microbiome, but also how the belowground microbiome changes across large geographic scales. Understanding the effect of range expansion on the belowground plant microbiome can provide baseline knowledge for predicting ecological consequences of current rapid climate warming, and it may also be used to enhance understanding of community responses to invasion scenarios for introduced exotic species."
} | 3,277 |
36983464 | PMC10058380 | pmc | 9,741 | {
"abstract": "Crop pathogenic fungi may originate from reservoir pools including wild vegetation surrounding fields, and it is thus important to characterize any potential source of pathogens. We therefore investigated natural vegetation’s potential for hosting a widespread pathogenic group, Colletotrichum gloeosporioides species complex. We stratified sampling in different forest environments and natural vegetation strata to determine whether the fungi were found preferentially in specific niches and areas. We found that the fungi complex was fairly broadly distributed in the wild flora, with high prevalence in every study environment and stratum. Some significant variation in prevalence nevertheless occurred and was possibly associated with fungal growth conditions (more humid areas had greater prevalence levels while drier places had slightly lower presence). Results also highlighted potential differences in disease effects of strains between strata components of study flora, suggesting that while natural vegetation is a highly probable source of inoculums for local crops nearby, differences in aggressiveness between vegetation strata might also lead to differential impact on cultivated crops.",
"conclusion": "5. Conclusions In summary, we described a broad presence of species from C. gloeosporioides complex in natural vegetation, and high prevalence was a feature of every niche and vegetation strata investigated. There were some effects attributable to local conditions, especially those associated with humidity and dryness, known to positively and negatively impact fungal growth, respectively. More humid environments might indeed be more prone to hosting important and diverse populations of the pathogen. We also note that prevalence was greater in natural vegetation than cultivated settings and the local flora and environment might well be considered important sources of diverse inocula for crops. Filtering effects of strain pools are nevertheless at play and may have quite different impacts on disease development depending on their origin, especially regarding strata. These filter effects are an important component in the study of epidemics and should be the focus of further research.",
"introduction": "1. Introduction Plant diseases are a serious factor in limiting crop production, and pathogens may attack cultivated plants at all stages of their life cycle [ 1 ], from germination to senescence, including post-harvest storage of foods [ 2 ]. Diseases take advantage of genetically homogenous fields at large scales, seed chain contaminations [ 3 ], and are explosive when favourable weather conditions for epidemics are met [ 4 ]. Nevertheless, many diseases are constrained by specificity in host range and specialisation due to their co-evolutionary nature [ 5 ], so that control can be somewhat efficient with proper regional monitoring effort, varietal turn-over [ 6 ] or multiline varietal strategies, and appropriately managed biocides [ 7 ]. On the other hand, disease control will be much harder for diseases resulting from more generalist pathogens—especially fungi, with epidemic bursts sometimes more difficult to anticipate [ 8 ]. While epidemic bursts are the result of favourable circumstances such as genetic homogeneity of cultivated varieties at broad scale [ 9 ] and weather conditions conducive to both explosive multiplication and dispersal (either passively from winds and rains [ 10 ] or more actively via vectors), inoculum sources play a major role in disease initiation, especially in proximity of fields [ 11 , 12 , 13 ]. As such, origin of inocula is a major focus of research in plant pathology [ 14 ], along with monitoring disease risk and spread over regions [ 15 ]. Specialist pathogens will have a narrower range of favourable circumstances for epidemics [ 16 ], possibly correlating more strongly to agronomic practices [ 17 , 18 ] and flow in the production chain (including storage and seeds distribution, see [ 2 ]) and are thus more amenable to control. On the other hand, generalist pathogens will have a broader spectrum of favourable circumstances, including ecological interactions resulting in disease initiation [ 19 ]. For generalist fungi, a specific issue is that of host plants allowing pathogens to survive intercrop season and initiate new epidemics [ 11 ], and sometimes proximal field vegetation is directly an inoculums source [ 12 , 13 ]. Therefore, deciphering host range and natural ecology of fungi is especially relevant to understanding plant disease risk [ 19 , 20 , 21 ], especially Colletotrichum species in their natural environment [ 22 ]. In this study, we investigated the potential role of natural flora in hosting potentially pathogenic species from the C.gloeosporioides complex. The fungal complex is indeed responsible for initiating anthracnose disease on water yams ( Dioscorea alata ) [ 21 ] in the Caribbean [ 17 , 23 ], despite breeding efforts against the disease [ 24 ] and a diverse pool of progenitors [ 25 ]. Anthracnose disease at epidemic stages often results in widely necrotic plants unable to sustain photosynthesis anymore and sometimes leads to complete crop wipeout and dramatic harvest losses [ 26 ]. Yet, little is known about inoculum sources. Seed tubers were once hypothesized as a plausible origin [ 27 ], since the fungus produces skin disease on tubers [ 28 , 29 ] and might start disease in young plants. The species complex is known to infect numerous plant hosts [ 30 , 31 , 32 ], even in natural settings, though despite a potentially widespread range it is also known to behave nearly symbiotically at times [ 33 ], sometimes even turning saprophytic [ 34 , 35 ]. Reasons why strains become harmful to crops are not yet fully understood, though the nature of species complex might play a role [ 36 ]. Recent studies have shown that weed species host C. gloeosporioides and may behave as inoculums’ relay during intercropping [ 11 ]), as well as field hedges [ 12 , 13 ]. In light of these results, we investigated the prevalence of the fungi in natural vegetation, as several studies have documented broad prevalence range in the wild [ 37 ] and local abundance in the study region [ 13 ], a situation often encountered with fungi in general [ 38 ]. We decided to closely focus on vegetation strata along an elevation gradient in a natural secondary growth forest in order to test whether host skill differed not among species but among ecological niches and vegetation strata, thus adding to current knowledge of Colleotrichum presence in woody vegetation [ 22 ]. We thus asked the following questions: What is the prevalence of the pathogen in natural vegetation? Does it vary across strata (canopy, understory, and floor)? Is it sensitive to elevation or changes in relative humidity or wind levels?",
"discussion": "4. Discussion C. gloeosporioides complex is considered an ubiquitous worldwide species and our results confirmed a widespread presence of these crop pathogen fungi in natural forest vegetation, generally at fairly high prevalence (average: 0.71; range 0.33–1.00), independent of environmental niche or vegetation strata, to the exception of places where conditions for growth were impacted (e.g., more humid riparian forest plots had greater prevalence, drier hill plots had slightly lower prevalence, and altitude generally decreased presence of the fungi). Patterns of correlations between prevalence in the different conditions (diseased or healthy leaves) and vegetation strata indicated differential influence on infection dynamics: healthy canopy prevalence was closely associated with diseased canopy prevalence, possibly suggesting a first filtering effect in canopy within a diverse pool from spore rain, and increased prevalence led to increased disease levels. However, if higher disease levels in canopy were expectedly associated with higher disease levels in floor strata, they were also strikingly correlated to healthy prevalence in understory. This result suggested that strains differentially affect plant species within different strata. We will discuss these findings within the guiding principle of potential impact on cultivated fields and crops. Colletotrichum is a generalist fungus, historically thought of as involving specialist relationships with very narrow host range (i.e., following single interactions pairs—a pathogenic species associated to a plant species), sometimes inducing taxonomic confusions [ 31 ], then transiently interpreted via the length of morphospecies complexes [ 40 ], but today interpreted as having broad host species range within species complexes [ 30 ]. Indeed, we describe here a fairly wide array of host species coexisting locally and most probably with an important share of strains. Prevalence was high in our population sample (a known feature of the complex [ 37 ]), and this was true within every forest niche and vegetation stratum. It was indeed even higher in natural vegetation than it was in weeds communities found in fields from very close (1 km) to regional distance (within 20 km) [ 11 ]. Perhaps most importantly, among the 71 plant species hosting Colletotrichum fungi (listed above), at least 27 are commonly found here and there in field edges or even within fields (e.g., Bidens alba , Calopogonium mucunoïdes , Centella asiatica , Centrosoma pubescens , Clidemia hirta , Commelina difusa , Cyathea sp., Desmodium axilare , Desmodium barbatum , Desmodium incanum , Desmodium sp., Desmodium trifolium , Elephantopus mollis , Heliconia sp., Hyptis atrorubens , Hyptis sp., Inga ingoïdes , Ipomea setifera , Ipomea tilliacea , Miconia mirabilis , Mimosa pigra , Mitracarpus hirtus , Stachytarpheta jamaicensis , Solanum torvum , Spathoglottis plicata , Stachytarpheta jamaicensis , Syzygium jambos , and Wedelia trilobata ), and some of them are already known hosts to C. gloeosporioides complex [ 11 ]. Amazingly, there seems to be a continuum in prevalence from broadly inoculated natural vegetation to cultivated areas where fungi presence is much scarcer (weed communities around fields and monocultural crop themselves, even susceptible species), suggesting Colletotrichum might best be seen as conquering agricultural land, and possibly in that process producing disease in crops. This idea might also explain why the fungi occur as such extremes as peaceful leaf commensal [ 33 , 37 ] or as strongly pathogenic and driving anthracnose disease in crops [ 44 ]. A consequence of this is that some local farmers shifted species cultivation in order to reduce disease impact on yams [ 18 ]. Despite high prevalence in general, our results also highlighted that some conditions might be limiting or on the contrary conducive to propagation. Indeed, riparian forest had higher rates of fungus presence, especially for understory and floor strata ( Table 1 ), and this might reflect more humid conditions favourable to fungus growth. On the other hand, top hill forest plots were places of lower prevalence ( Figure 3 ), and altitude was consistently associated with a weaker presence of Colletotrichum ( Figure 4 ). Of course, these are areas associated with drier atmospheric conditions, though these are also more exposed to winds, which is an important factor in spore dispersal and thus arrival of the fungi as well. The evidence would thus point to local conditions for installment and growth being more restrictive in explaining fungus prevalence than long distance dispersal (but see [ 45 ]). The pattern of lower prevalence at forest edges with greater variance (thus making edge statistically no different than deep forest) seems to corroborate this observation further. In addition, the pattern of increasing prevalence between canopy and understory or floor obviously reinforces the idea that local inoculation is rather passive through rains once Colletotrichum species successfully installs in canopy and that more humid conditions such as those expected below a canopy will increase odds for the fungus to inoculate other plant species, a situation similarly documented in field crops [ 46 ]. Local conditions will thus allow for higher presence of Colletotrichum if they are favourable to fungal growth compared to other locations undergoing a more important spore rain but drier and harsher growth conditions. Local inoculation dynamics are thus dependent on growth conditions, but our results suggested that other processes were at play, and that strata may respond differently, especially regarding disease status (prevalence from diseased leaves vs. from healthy leaves). Indeed, prevalence estimates were sometimes correlated in unexpected ways: for example, diseased canopy prevalence was strongly correlated to diseased floor prevalence but also very strongly to healthy understory prevalence. These correlations demonstrate that strains producing disease in canopy may well also be aggressive in lower strata too (e.g., floor species), but apparently do not necessarily translate into disease for understory species. It is unclear why such a pattern emerged, though possible hypotheses might focus either on species effect or possible specific ecophysiological features in the different strata (e.g., cuticle thickness and composition). If such effects were replicated, it would be of interest to investigate whether strain aggressiveness differential impacts risk of disease such as anthracnose when strains escape natural vegetation and disperse into cultivated areas (see discussion in [ 11 ]). This would explain why so many Colleotrichum strains seldom produce disease in crops known to be sensitive, while difficult-to-predict epidemics can suddenly put specific crops at risk when aggressive strains land in the right place. Natural vegetation is thus an important reservoir of potentially pathogenic strains of species from Colletotrichum gloeosporioides complex, given the broad host range exhibited. On the other hand, these results are most plausibly true for the other Colletotrichum complexes [ 47 , 48 ], and possibly other fungi with broad host range and affinity to crops. Understanding fungal dynamics and how they translate into increasing disease risk for crops is a pressing issue in the wake of agriculture transition toward reduced use of synthetic inputs, as fungi propagate near and within fields [ 11 , 12 , 13 ]. Disease control might nevertheless benefit from an extended microbiome approach in agriculture, for which pathogen displacement may be reached under field ecological conditions, provided microbial community functioning is better described [ 49 ]. Indeed, interactions between fungi are known to lead to competition and negative interactions, including for Colletotrichum complexes where apparent antinomy within weeds between members of C. acutatum complex and C. gloeosporioides [ 11 ] impacted anthracnose development and reduced disease symptoms in yams [ 50 ]. Another approach relying on endosymbiotic relationships may also provide opportunities for disease control [ 51 ]."
} | 3,771 |
30027053 | PMC6051221 | pmc | 9,742 | {
"abstract": "Abstract Soft actuators have demonstrated potential in a range of applications, including soft robotics, artificial muscles, and biomimetic devices. However, the majority of current soft actuators suffer from the lack of real‐time sensory feedback, prohibiting their effective sensing and multitask function. Here, a promising strategy is reported to design bilayer electrothermal actuators capable of simultaneous actuation and sensation (i.e., self‐sensing actuators), merely through two input electric terminals. Decoupled electrothermal stimulation and strain sensation is achieved by the optimal combination of graphite microparticles and carbon nanotubes (CNTs) in the form of hybrid films. By finely tuning the charge transport properties of hybrid films, the signal‐to‐noise ratio (SNR) of self‐sensing actuators is remarkably enhanced to over 66. As a result, self‐sensing actuators can actively track their displacement and distinguish the touch of soft and hard objects."
} | 245 |
34257910 | PMC8258234 | pmc | 9,745 | {
"abstract": "Abstract The high number and diversity of microbial strains circulating in host populations have motivated extensive research on the mechanisms that maintain biodiversity. However, much of this work focuses on strain‐specific and cross‐immunity interactions. Another less explored mode of pairwise interaction is via altered susceptibilities to co‐colonization in hosts already colonized by one strain. Diversity in such interaction coefficients enables strains to create dynamically their niches for growth and persistence, and “engineer” their common environment. How such a network of interactions with others mediates collective coexistence remains puzzling analytically and computationally difficult to simulate. Furthermore, the gradients modulating stability‐complexity regimes in such multi‐player endemic systems remain poorly understood. In a recent study (Madec & Gjini, Bulletin of Mathematical Biology , 82), we obtained an analytic representation for N ‐type coexistence in an SIS epidemiological model with co‐colonization. We mapped multi‐strain dynamics to a replicator equation using timescale separation. Here, we examine what drives coexistence regimes in such co‐colonization system. We find the ratio of single to co‐colonization, µ , critically determines the type of equilibrium and number of coexisting strains, and encodes a trade‐off between overall transmission intensity R \n 0 and mean interaction coefficient in strain space, k . Preserving a given coexistence regime, under fixed trait variation, requires balancing between higher mean competition in favorable environments, and higher cooperation in harsher environments, and is consistent with the stress gradient hypothesis. Multi‐strain coexistence tends to steady‐state attractors for small µ , whereas as µ increases, dynamics tend to more complex attractors. Following strain frequencies, evolutionary dynamics in the system also display contrasting patterns with µ , interpolating between multi‐stable and fluctuating selection for cooperation and mean invasion fitness, in the two extremes. This co‐colonization framework could be applied more generally, to study invariant principles in collective coexistence, and to quantify how critical shifts in community dynamics get potentiated by mean‐field and environmental gradients.",
"introduction": "1 INTRODUCTION Rich ecosystems comprise many species interacting together in a myriad of ways and on multiple temporal and spatial scales. Understanding the scope and consequences of such interactions has been the focus of countless theoretical ecology studies, starting with the seminal work by Lotka ( 1926 ) and Volterra ( 1926 ) on mathematical models of the population dynamics of interacting species. This model has been later extended and sophisticated by many other theoretical studies (May 1972 ; Pascual et al., 2006 ), and is currently extensively used to characterize interaction networks in empirical microbiome communities (Bucci et al., 2016 ; Stein et al., 2013 ). Theoretically, a crucial question has been to study stability and coexistence patterns in such Lotka–Volterra multi‐species communities, analyzing both structured ecological networks and random networks (Serván et al., 2018 ; Song & Saavedra, 2018 ). Modeling efforts seek to understand organizing principles for species composition, including the balance between competition and cooperation (Mougi & Kondoh, 2012 ). Overall, analysis of such models with arbitrarily high dimensionality has been and continues to remain difficult. In particular, beyond the complexity‐stability debate which represents a major force in ecology (Landi et al., 2018 ; May 1972 ; McCann, 2000 ), many studies are increasingly addressing the problem of deriving collective dynamics from pairwise outcomes between species, which constitutes another major challenge, both at an analytical (Levine et al., 2017 ; Momeni et al., 2017 ) and empirical (Friedman et al., 2017 ) level. The challenge of high‐dimensionality in ecological microbial networks parallels a similar challenge in the epidemiology of polymorphic pathogen systems, where understanding the mechanisms and forces that maintain diversity among interacting strains, is also an area of active research (Cobey & Lipsitch, 2012 ; Gupta & Anderson, 1999 ; Lipsitch et al., 2009 ; Wearing & Rohani, 2006 ). While it is well recognized that population patterns of infection are to a large extent determined by susceptibility to infection, most multi‐strain SIR models, inspired from influenza, dengue, and malaria parasites, have focused on cross‐immunity between strains as driver of population structure (Gog & Grenfell, 2002 ; Gomes et al., 2002 ; Gupta et al., 1998 ; Lin et al., 1999 ). Yet, other factors, besides persistent host immunity, may make strains compete or cooperate with each other, and it remains unclear which environmental variables also contribute to their epidemiologic fitness. Here, we bridge between multi‐species ecology and multi‐strain epidemiology, revisiting coexistence and diversity in a new context. We explore another mode of strain interactions, namely altered susceptibilities to coinfection, whereby N strains compete in SIS endemic scenarios of no persistent immunity and no virulence. Coinfection models with up to two strains have described vulnerability to coinfection with a single parameter (Alizon et al., 2013 ; Davies et al., 2019 ; Gaivão et al., 2017 ; van Baalen & Sabelis, 1995 ), two coefficients (Lipsitch, 1997 ) or four coefficients (Gjini et al., 2016 ) depending on model structure and aims, but very few analytical investigations have been done for a larger number of interacting strains (Adler & Brunet, 1991 ), recognizing the difficulties of including within‐and between‐strain details for such coefficients (Mosquera & Adler, 1998 ). Moreover, analytic solutions for strain frequency dynamics in coinfection models remain rare, due to nonlinearities even for N = 2. In a recent co‐colonization (coinfection) SIS model framework, with N ‐strains, we have simplified the complex ecology embedded in N \n 2 epidemiological variables (Madec & Gjini, 2020 ). Using timescale separation, we obtained a model reduction from the matrix of pairwise coinfection vulnerabilities between strains. This coincides with a special replicator equation (Cressman & Tao, 2014 ; Hofbauer & Sigmund, 2003 ) by which we can predict explicitly multi‐strain frequency evolution. This N ‐dimensional model reduction makes the entire epidemiology more accessible to analysis, and relates emergent collective dynamics to the ensemble of pairwise competitive outcomes, not only qualitatively but moreover in an explicit quantitative manner. In the present article, we harness the simplicity of this co‐colonization model framework (Madec & Gjini, 2020 ) to investigate coexistence, stability, and evolution of such multi‐strain systems with variable co‐colonization susceptibility coefficients among strains. We start by studying the behavior of the system for different global variables such as total transmission intensity R \n 0 and mean interaction coefficient in the pool of available strains k . We then study coexistence through random co‐colonization interactions, where the matrix coefficients are drawn from fixed distributions, and can range from competitive to cooperative links. We ask what is the number of strains that can coexist when starting from a pool of N strains, and in which diversity–stability configuration. We uncover rich transient and asymptotic behavior of such systems, where steady states, limit cycles, multi‐stability, and chaotic attractors are possible. We find that the ratio of single‐ to co‐colonization is a critical factor in collective dynamics, by modulating the asymmetry in pairwise invasion fitness between types, and consequently, the dynamic complexity of the system as a whole. This ratio is key to observe the emergent context dependence of strain interactions (Bascompte, 2019 ; Coyte & Rakoff‐Nahoum, 2019 ) in our model. We argue that the analytically explicit form of this ratio in our formalism enables direct connection with the stress gradient hypothesis (SGH) in ecology (Bertness & Callaway, 1994 ; Callaway & Walker, 1997 ). This hypothesis postulates that as stress increases, the importance of positive facilitative effects increases in a community, whereas in benign environmental conditions, competitive effects are higher; a finding that emerges also from our results. In support of complex higher‐order dynamics emergent from simple pairwise interactions, with critical links between mean and variance, we uncover the exact formulation for why the sum as a collective is much more than its parts. Our results invite a deeper understanding of the biology of endemic multi‐strain systems and point to key global modulators of collective polymorphic coexistence in nature.",
"discussion": "4 DISCUSSION A central question in microbial ecology is whether community members compete or cooperate with one another, and how such interactions mediate community stability, resilience and function. In our model, we study an epidemiological multi‐strain system, where members interact with each other via altered susceptibilities to co‐colonization, which broadly include both competition and facilitation. By clearly delineating the role of mean interaction coefficient, basic reproduction number R 0 , and biases in pairwise coefficients relative to the mean, we obtain a model reduction for strain frequency evolution for any N . The questions we addressed within such a system are similar to a long‐standing ecological quest on multispecies dynamics (Bunin, 2017 ; May, 1972 ; Pascual et al., 2006 ; Serván et al., 2018 ; Song & Saavedra, 2018 ): what governs coexistence regimes, diversity and stability in such systems? Although we do not specify the molecular mechanisms that can mediate positive or negative interactions between strains in co‐colonization (Dawid et al., 2007 ; Leggett et al., 2014 ; Lysenko et al., 2010 ; Riley & Gordon, 1999 ; Shen et al., 2019 ), this renders the system generic and broadly applicable. We can quantitatively predict very important features of system behavior with a simple mathematical framework derived under quasi‐neutrality and strain similarity assumptions (Madec & Gjini, 2020 ). This model reduction captures selective dynamics between strains over long time, and coincides with an instance of the replicator equation from evolutionary game theory (Hofbauer & Sigmund, 2003 ; Nowak & Sigmund, 2004 ). Studying this equation and its biological consequences in detail, here we find that in our system, there is a critical ratio that tunes complexity and dynamic regimes in such multi‐strain contagion context: namely the ratio of single to co‐colonization. This ratio, μ , is given by the inverse of the product of the basic reproduction number and mean vulnerability to co‐colonization μ = 1 / ( ( R 0 ‐ 1 ) k ) . We show that it amplifies the importance of asymmetry in interaction between strains, lending theoretical support to the principle of context‐dependence (Coyte & Rakoff‐Nahoum, 2019 ) of relative fitnesses in a coupled microbial community. As strain relative abundances fluctuate, the resource and fitness landscape change dramatically and feed back on the system. This dynamic interdependence is on one hand, the source of complexity, but also a key driver of evolving mean fitness between extant strains. A global, symmetric and temporally varying, environmental feedback on all strains emerges naturally in co‐colonization dynamics ( Q in Equation 4 ), describing mean invasibility and following the evolution of diversity. Mean invasion fitness will tend to increase when more strains are stably maintained over time, and it will tend to zero in the extreme cases of competitive exclusion. Depending on parameter values, there is a gradient for number of resources in the system. Strains compete more strongly for susceptible hosts (one limiting resource) in the extreme of co‐colonization ( μ → 0 ), whereas they compete for (at most) N singly colonized hosts, open to co‐colonization ( N resources) in the opposite extreme of single colonization dominance ( μ → ∞ ). We find that for small values of the ratio between single and co‐colonization μ , which means high transmission intensity or high cooperation among strains on average, the system dynamics is characterized by multi‐stability, where typically nonoverlapping strain subsets can coexist, depending on initial conditions, a result that resonates with earlier multi‐strain SIRS models with cross‐immunity (Gupta & Anderson, 1999 ). In our model, we find a similar principle applies, despite the interactions between strains being mediated via altered susceptibilities to co‐colonization, without persistent immune memory. While in the present setup this gradient emerges naturally from the intrinsic structure of infection‐mediated interactions among all strains, similar gradients have been found also in ecological communities studied with generalized Lotka–Volterra models, when the correlation between i ‐ j and j ‐ i interactions was explicitly varied (Bunin, 2017 ). Our study brings together several themes of interest across many multi‐type systems shaped by interactions and higher‐order feedbacks between their members. Many fields including ecology, geophysics, and economics are calling attention on critical transitions, which occur when natural systems drastically shift from one state to another (Scheffer et al., 2012 ). Critical transitions in the epidemiology of infectious diseases are of relevance to the emergence of new pathogens and escape from control, such as vaccines. The critical transitions analyzed in this paper relate global and mean‐field environmental variables to the manifestation of competitive hierarchies between multiple strains interacting in co‐colonization. We have made explicit how a gradient emerges from the epidemiological ratio of single to co‐colonization, and how it tunes effectively the diversity, stability and complexity of the coexistence between strains. Such gradient can mediate critical transitions in collective dynamics, when the normalized interaction coefficients between members are held fixed. These transitions may underlie and potentially enhance (or counteract) efforts to control and eliminate multi‐type infectious pathogens, as via vaccines or drugs, or in the face of climate change. Other studies have shown that concurrent multiple infection in malaria creates tipping points that give rise to hysteresis in responses to control or seasonal variation in vector abundance (Alonso et al., 2019 ). Our work supports a similar perspective, but more generally relevant to interacting systems with multiple strains, and coexistence regimes, rather than prevalence tipping points. Mean facilitation and competition among strains, affecting μ , appear as two sides along a continuum for the system, which particular strain compositions or environmental drivers (seasonality, general host immunity, population turnover) may tip towards one or the other extreme. We find that when μ tends to favor co‐colonization, for example in the limit of more facilitation between strains on average, the system tends to multi‐stability and stable coexistence of a few strains in simple dynamics. In contrast, when μ tends to favor single colonization, for example in the limit of more competition between strains on average, the system tends to more complexity and unstable equilibria (Figure 5 ), but coexistence of more strains becomes possible (Figure S1 ). Although at first sight this may seem to suggest, somewhat contrary to previous expectation from lower‐dimensional models (Chen et al., 2017 ; Hébert‐Dufresne & Althouse, 2015 ), that average cooperation in co‐colonization is stabilizing and average competition is destabilizing, our result should be related to the fact that k in our model is not a measure of cooperation in the classical sense, whereby cooperation is exclusively defined as a between‐strain phenomenon. In our model k includes self and nonself‐interaction, and is critical to the global resource dynamics shaped dynamically by N strains. Our study has also several limitations. Although we explored the qualitative aspects of the dynamics, including the complexity and stability of steady states, their dimensionality and associated entropy, we did not study which strains ultimately coexist. This question relates to optimal strategies among N players in a game theoretic context. How the interaction traits of each member determine its persistence or exclusion from the system, and what is the role of N , requires further investigation and algorithmic optimization (Bárány et al., 2007 ). We also did not develop all the links with the Lotka–Volterra modeling literature in microbial ecology, although special cases of our model are similar to particular cases of GLV dynamics. The metaphor of co‐colonization, as adopted here, could be applied to more general cases of ecological dynamics between microbial species or ecotypes. We did not study alternative distributions of rescaled interaction strengths A , only focusing on a symmetric distribution around 0. It would be interesting in the future to test our findings against nonrandom topologies, and empirical interaction networks, as studied for example by Grilli, Adorisio, et al. ( 2017 ). In the limit μ → ∞ the patterns analyzed here still hold independently of the distribution governing A ij , but in the limit μ → 0 , the distribution of A matters, and different distributions may lead to slightly different numerical predictions. Finally, this model makes several predictions which can be tested empirically. First, the invariant principles in the slow time scale (Box 1 ) suggest that dominance patterns in single and co‐colonization of particular strains should be the same. The other finding that stable (multi‐stable) coexistence between types through co‐colonization is more likely when mean interactions tend towards cooperation, and that a single stable coexistence between types becomes more probable at intermediate values of μ , and ultimately only unstable coexistence is possible for large values of μ could be tested in endemic multi‐type microbial ecosystems. For example, empirical data in polymorphic Streptococcus pneumoniae bacteria, have been consistent with estimates of about 90% mutual inhibition between co‐colonizing serotypes (Gjini et al., 2016 ; Lipsitch et al., 2012 ), and R 0 values around 2. This implies that for this system, μ ≈ 10 , and multi‐stability is highly unlikely but a single stable equilibrium point is almost as likely as complex unstable coexistence. This may reconcile the secular trends observed in some settings consistently over many years (Ekdahl et al., 1998 ; Feikin & Klugman, 2002 ; Fenoll et al., 1998 ). Such secular trends can interfere with vaccine introductions and need to be accounted for when estimating impact (Moore, 2009 ; Moore & Whitney, 2008 ). Our model makes explicit predictions about the timescale and qualitative aspects of such secular trends (Box 2 , Figure S4 ), under the plausible assumption that they are driven by co‐colonization interactions. The requirement of being simultaneously stable and feasible tends to push coexistence regimes toward intermediate entropy, independently of precise strain composition. The consistency of the optimal evenness (Shannon entropy) configuration for a given number of strains has been observed empirically for pneumococcus serotypes across geographical settings, before and after vaccination (Hanage et al., 2010 ). Our model, offers a new perspective on such observations, thanks to co‐colonization interactions between serotypes. As this optimal rank‐order abundance distribution depends on the context μ , model expectations for such dependence could be tested with multi‐site data from different endemicity levels. We postulate that the stress gradient hypothesis (SGH) (Bertness & Callaway, 1994 ; Callaway & Walker, 1997 ; Chamberlain et al., 2014 ) could help interpret the critical role of multiple infection in shaping epidemiological multi‐strain systems. Our link suggests that to preserve a certain “optimal” single‐to co‐colonization ratio (optimal complexity/coexistence balance), independently of community size N , facilitation in co‐colonization between microbial strains should be more common in settings with low prevalence, a prediction to be tested in the future. It becomes intriguing to verify, beyond pneumococcus, to what extent this model and its insights (Box 3 ) can be used as an analytic backbone to interpret multi‐strain dynamics in other systems of relevance for public health, for example influenza (Yang et al., 2019 ), dengue (Mier‐y Teran‐Romero et al., 2013 ), malaria (Alonso et al., 2019 ; Gupta & Maiden, 2001 ) or human papilloma viruses (Murall et al., 2014 ). Disentangling multi‐strain interactions and their role in community function at the epidemiological level remains challenging, but can be made more accessible analytically using frameworks such as the one proposed here. With the simplicity and deep insights afforded by this model, we can address better the role of mean fitness of the microbial system as a whole, trait variance, and the role of environmental gradients for stabilizing versus equalizing forces in biodiversity."
} | 5,409 |
37229213 | PMC10205512 | pmc | 9,747 | {
"abstract": "Soft robots have received a lot of attention because of their great human-robot interaction and environmental adaptability. Most soft robots are currently limited in their applications due to wired drives. Photoresponsive soft robotics is one of the most effective ways to promote wireless soft drives. Among the many soft robotics materials, photoresponsive hydrogels have received a lot of attention due to their good biocompatibility, ductility, and excellent photoresponse properties. This paper visualizes and analyzes the research hotspots in the field of hydrogels using the literature analysis tool Citespace, demonstrating that photoresponsive hydrogel technology is currently a key research direction. Therefore, this paper summarizes the current state of research on photoresponsive hydrogels in terms of photochemical and photothermal response mechanisms. The progress of the application of photoresponsive hydrogels in soft robots is highlighted based on bilayer, gradient, orientation, and patterned structures. Finally, the main factors influencing its application at this stage are discussed, including the development directions and insights. Advancement in photoresponsive hydrogel technology is crucial for its application in the field of soft robotics. The advantages and disadvantages of different preparation methods and structures should be considered in different application scenarios to select the best design scheme.",
"conclusion": "6 Conclusion This article reviews photoresponsive hydrogels for soft robots. Based on the response principle, they are divided into three categories: photoisomerization, photo(de)crosslinking, and photothermal hydrogels. Their application in soft robots is discussed based on bilayer structures, gradient structures, oriented structures, and patterned structures. Such as soft grippers, crawling robots, walking robots, jumping robots, swimming robots, and bionic robots. In order to achieve the best design solution in various application scenarios, soft robots based on photoresponsive hydrogels need to consider the advantages and disadvantages of various preparation methods and structures. Finally, this paper discusses the issues affecting the application of photoresponsive hydrogels in the field of soft robotics, along with the analysis in terms of material property improvement, manufacturing and assembly technology advancement, light source technology development, and environmental optimization. These issues will be addressed in the future through multidisciplinary research to advance and develop photoresponsive hydrogel technology.",
"introduction": "1 Introduction Traditional robots have been applied in medical, scientific, industrial, and military fields and have helped people live more productive lives. The majority of these robots are made up of rigid motion sub-connections made of rigid materials that can only work in structured environments and have poor flexibility, adaptability, and safety. In addition, soft robots have far more freedom and can operate in unstructured environments. Therefore, they can solve problems in a much safer manner [ 25 ]. Smart responsive materials are becoming increasingly popular as soft robotics advances. Smart materials have a wide range of applications in soft robotics [ 4 , 5 ] due to their bio-affinity, light weight [ 1 ], and flexible deformation [ 2 , 3 ]. Smart-responsive hydrogels are three-dimensional polymer networks that are physically or chemically cross-linked and have excellent biocompatibility, ductility, permeability, degradability, and stimulus adaptability [ 6 , 7 ]. To respond to a variety of external stimuli, smart responsive hydrogels interact with the polymer network and the external environment. Therefore, its use as an ideal material for soft robots can provide them with additional capabilities due to the material's unique properties. When stimulated by temperature, pH, an electric or magnetic field, light, enzymes, or ion concentration, smart responsive hydrogels change their own physical or chemical properties. They have promising applications in sensors [ 8 ], tissue engineering scaffolds [ 9 ], microfluidic valves [ 10 ], bionic devices [ [11] , [12] , [13] ], medical carriers [ [14] , [15] , [16] ], and soft robotics [ 17 ] due to their tunable chemical structure and physical properties and rich stimulation sources. Photoresponsive hydrogels provide intelligent responsiveness through light stimulation without direct physical contact with external factors. The light allows for remote manipulation of the robot without the use of any additional reagents. Processes triggered by light can also be paused and resumed. Furthermore, the light parameters (intensity, wavelength, and light duration) can be adjusted to precisely control the degree of light response. Photoresponsive hydrogels, with proper design, can acquire photodeformation and perform a variety of complex movements such as stretching, bending, crawling, and rotating. Lee [ 18 ], Liu [ 19 ], and others have recently reviewed hydrogel soft robots and various hydrogel applications. However, a comprehensive overview of photoresponsive hydrogel soft robots is still lacking. This paper reviews current research on various response mechanisms, structural forms, and applications of photoresponsive hydrogels in soft robots. The second section of this paper utilizes Citespace to analyze current literature in order to identify hot areas and the main directions of current hydrogel research. Section 3 examines the properties of the various response mechanisms, including photoisomerization, photo(de)crosslinking, and photothermal types. Section 4 reviews application advancements in soft robots based on bilayer, gradient, oriented, and patterned structures. Section 5 discusses the main issues affecting the application of photoresponsive hydrogels, solutions to these problems, and future directions. Section 6 provides a summary of the topics covered.",
"discussion": "5 Discussion and outlook 5.1 Discussion Photoresponsive hydrogel, a new type of intelligent material, has a promising application in soft robotics. To improve the photoresponsive hydrogel material stability, strength, and response speed, improvements in the material's structure and preparation process are required. As illustrated in Fig. 8 , the self-healing properties of mechanical strength, responsiveness, structure, and shape will be discussed separately. Fig. 8 Discussion and future outlook. Fig. 8 5.1.1 Self healing Robots are vulnerable to external damage or their own material properties in extreme environments, which can reduce their efficiency. Self-healing capabilities can increase the life and robustness of robots. Photostimulation is non-polluting, controllable, and remotely operable, making it safer and more convenient for soft robot repair. Photoresponsive hydrogels can modulate the binding affinity of the hydrogel to β-CD by photoisomerizing the azobenzene fraction, enabling modification of the crosslink density of the hydrogel. It also self-heals wounds via dynamic host-guest interactions [ [93] , [94] , [95] , [96] , [97] , [98] ] and hydrophobic interactions [ 99 ]. Reversible complexation of borate esters can also be used to make self-healing hydrogels. Photoresponsive hydrogels based on azobenzene host guest interaction repair can be activated by ultraviolet light and deactivated by visible light [ 100 ]. Furthermore, self-healing properties can be obtained by reforming dynamic chemical bonds at damaged sites via hydrogen bonding/metal-ligands [ 101 , 102 ] or by reconstructing networks via hydrogel covalent bonds [ 103 , 104 ]. Table 4 summarizes the properties of photoresponsive hydrogels based on self-healing. Table 4 The properties of photoresponsive hydrogels based on self-healing. Table 4 Publication Input Time Self-healing rate Method Xiong et al.(2018)[ 96 ] Vis440nm 2 h 77% Host-guest interactions Zhang et al.(2020)[ 101 ] – 20s 96% Metal–ligand/Hydrogen bonds Cheng et al.(2019)[ 103 ] NIR980nm 60s – Covalent bond reconstruction network Yang et al.(2017)[ 100 ] UV365 nm/vis 450 nm – 90%(vis) Host-guest interactions Yang et al.(2019)[ 93 ] Dark 24 h 100% Host-guest interactions Yu et al.(2018)[ 104 ] UV＜384 nm NO UV 350min/UV180min 50%/95% Covalent bond reconstruction network Wang et al.(2019)[ 102 ] UV – – Hydrogen bonds Zhang et al.(2020)[ 99 ] NIR3min(60 °C) – 60% Hydrophobic interac-tions Kim et al.(2020)[ 97 ] UV365nm/Vis430nm 12 h 81.59% Host-guest interactions Zheng et al.(2017)[ 98 ] UV365nm/Vis430nm 20min 89.80% Host-guest interactions 5.1.2 Mechanical strength As the demand for robots grows, the limitations imposed by the mechanical strength deficiencies of conventional hydrogels become more apparent. Soft robots poor mechanical properties make it difficult to accurately manufacture complex structures and make them prone to functional failures when working in unstructured environments. Some existing approaches to improving the mechanical properties of hydrogel soft robots include dual network structures, host-guest recognition, material enhancement methods, and 3/4D printing preparation techniques. The covalent bonds of conventional covalently bonded double network hydrogels cannot be reformed when subjected to large mechanical deformations, resulting in irreversible and permanent material damage. Finally, the overall mechanical properties of the hydrogel deteriorate. As a result, hybridised or physical DN [ 105 , 106 ] hydrogels with high mechanical properties can be employed to create hydrogel networks. Furthermore, topologically structured hydrogels [ 107 ] improve the microstructural regularity of the hydrogel by modulating the “8″-shaped cross-linked ring structure, thereby improving reversibility and mechanical strength. Physical interactions based on supramolecular linkages, such as ionic bonds, hydrogen bonds [ 108 , 109 ], crystallisation, and hydrophobic interactions [ 110 ], are reversible in contrast to covalent bonds. Furthermore, host-guest recognition can improve the hydrogel's mechanical strength alongside its self-healing performance. The type, concentration, and surface properties of nanofillers may be applied to tune hydrogel properties [ 111 ]. As physical crosslinkers and fillers, nanoparticles can relax applied stresses and delay the fracture of the hydrogel [ 112 ]. GO can also be added to increase crosslinking density by forming H-bonds with the hydrogel backbone, thereby increasing the elastic modulus of the hydrogel [ 113 , 114 ]. Similar to GO, CNT/CNC/NFC [ 72 ] can be added to the hydrogel matrix to increase stiffness while preserving biocompatibility [ 115 , 116 ]. In addition, clay and noble metal nanoparticles (e.g., Au, Ag), which are naturally mechanically robust nanofillers, can significantly enhance the mechanical properties of hydrogel matrices [ 46 , 117 ]. 4D printing technology is derived from 3D printing with the addition of a “temporal” dimension, enabling printed material structures to respond to external physical field stimuli. By combining specific composite materials, 3D models of target structures [ 58 ] (e.g., dual-network hydrogels) can be rapidly fabricated into solids using 3D/4D printing techniques [ 119 , 120 , 135 ]. 5.1.3 Response speed Fast drive strategys, such as fast starts, jumps, must generate high intensity in a short amount of time. Soft robots based on photoresponsive hydrogels can increase their response speed by altering the ratio of light conversion efficiency to actual mechanical energy transfer efficiency. The expansion and contraction of hydrogels are primarily caused by a network of polymers absorbing and releasing water molecules. Currently, hydrogel network structures (e.g., porous hydrogels, comb-like hydrogels [ 60 ], and microsphere composite hydrogels [ 61 ]) can be modified to allow water molecules to pass easily into and out of the gel network, to reduce diffusion resistance, or to improve response rate by decreasing the hydrogel feature size. However, the field still faces significant obstacles, such as material and structural design optimization. 5.1.4 Structure shape Chemical and physical structures, such as cross-link density, pore size, and pore channels, comprise the structure of hydrogels. These structural parameters will directly influence the mechanical properties, water absorption performance, mechanical stability, etc. of hydrogels. For instance, hydrogels with a high crosslink density have greater strength and stiffness and can withstand large tensile or compressive forces, whereas hydrogels with a low crosslink density are softer and can be utilised in bionic robots. Various preparation techniques can yield hydrogels with distinct structures and forms, such as fibrous, spherical, and sheet-like. These various hydrogel shapes can be used to create soft robots with various forms and functions. Fiberous hydrogels are able to design robotic gloves or skin, while spherical hydrogels may be employed to build miniature pumps and sensors. To achieve the optimal structure and shape for a particular application scenario, the optimal preparation method (free radical polymerization, ionic gelation, physical cross-linking, etc.) is chosen. Using different crosslinking agents, crosslinking times and temperatures, etc., it is possible to produce hydrogels with varying crosslinking densities, resulting in hydrogels with distinct mechanical properties and shapes. By analysing the applicability and performance of the structure and form of hydrogels, it can improve the motility of soft robots and develop new applications. 5.2 Future outlook The study of photoresponsive hydrogels has made significant strides in recent years, and future research will focus on diversification, intelligence, and autonomy. This paper provides an outlook on preparation strategy, action diversity, environmental adaptability, and self-drive. 5.2.1 Preparation strategy and action diversity of hydrogel soft robot Most hydrogel soft robots are currently difficult to control multiple movements at once, have complex preparation processes, and have long stimulus response times. In order to improve the efficacy of hydrogel soft robots for rapid and precise action deformation, preparative strategies are investigated. Combining multifunctional materials with hydrogels to design photoresponsive hydrogel soft robots that can operate in harsh environments. For instance, hydrogels can be combined with functions such as fluorescence or shape memory to create new soft robots with collaborative vision detection capabilities. Additionally, 3D/4D printing technologies can be utilised to obtain anisotropic structures of hydrogels in order to customise the hydrogel's shape and internal structure. Smart materials can also be combined with printing technologies to improve assembly efficiency and precision. In the meantime, novel assembly technologies, including micro and nanotechnologies [ 136 ] and self-assembly technologies, are being researched and developed to achieve more efficient and accurate assembly. 5.2.2 Environmental adaptability of hydrogel soft robot Environmental factors restrict the application of the vast majority of photoresponsive hydrogels to the laboratory setting (light intensity, air, etc.). In order to investigate photoresponsive hydrogels that can operate in air, it is important to tackle obstacles such as their unstable operation in the open air, dehydration, and the difficulty of maintaining mechanical deformation. To prevent water diffusion, it is currently possible to add moisturising and elastic coatings, including wetting agents, but the results are not very satisfactory. In order to obtain photoresponsive hydrogels that perform well and can operate in air, new strategies are required. Additionally, the design of photoresponsive hydrogel skin based on ionic skin enables improved access to external information. This can help improve soft robots environmental adaptability and autonomous driving strategies. The majority of photoresponsive hydrogels' stimulation sources are NIR and UV, and UV has been extensively studied as a stimulation source. Existing NIR [ 137 ] excitation technologies are inefficient and difficult to precisely control despite their advantages in tissue penetration and photodamage. Multiple wavelengths (or natural light) trigger an intelligent synergistic response that still needs to be investigated. 5.2.3 Self driving strategy of hydrogel soft robot Systematization enables the components of a hydrogel soft robot to cooperate with one another, to execute various commands well without additional intervention, and to be lightweight, flexible, compact, and agile; programmability enables it to have capabilities such as programming and machine learning. Therefore, the study of self-driven strategies requires systematization and programming. There are two ways to study self-driving soft robots: semi-autonomous (requiring external control) and fully autonomous. The semi-autonomous type requires human intervention to replenish energy and provide subsequent instructions. In comparison, the fully autonomous type is more appealing. A soft robot can make autonomous decisions based on its task or external feedback, interacting with its surroundings to decide where to go or whether to avoid the light. Autonomous control requires both internal and external perception as well as the ability to obtain energy from the outside world in order to make optimal decisions. Future development of photoresponsive hydrogel soft robots will aim to achieve stable autonomous sensing, decision making, and movement with minimal human intervention. This serves as a foundation for future research into clustered photoresponsive hydrogel soft robots. The robots are able to communicate, share information, and collaborate to perform tasks more efficiently.\n\n5.1 Discussion Photoresponsive hydrogel, a new type of intelligent material, has a promising application in soft robotics. To improve the photoresponsive hydrogel material stability, strength, and response speed, improvements in the material's structure and preparation process are required. As illustrated in Fig. 8 , the self-healing properties of mechanical strength, responsiveness, structure, and shape will be discussed separately. Fig. 8 Discussion and future outlook. Fig. 8 5.1.1 Self healing Robots are vulnerable to external damage or their own material properties in extreme environments, which can reduce their efficiency. Self-healing capabilities can increase the life and robustness of robots. Photostimulation is non-polluting, controllable, and remotely operable, making it safer and more convenient for soft robot repair. Photoresponsive hydrogels can modulate the binding affinity of the hydrogel to β-CD by photoisomerizing the azobenzene fraction, enabling modification of the crosslink density of the hydrogel. It also self-heals wounds via dynamic host-guest interactions [ [93] , [94] , [95] , [96] , [97] , [98] ] and hydrophobic interactions [ 99 ]. Reversible complexation of borate esters can also be used to make self-healing hydrogels. Photoresponsive hydrogels based on azobenzene host guest interaction repair can be activated by ultraviolet light and deactivated by visible light [ 100 ]. Furthermore, self-healing properties can be obtained by reforming dynamic chemical bonds at damaged sites via hydrogen bonding/metal-ligands [ 101 , 102 ] or by reconstructing networks via hydrogel covalent bonds [ 103 , 104 ]. Table 4 summarizes the properties of photoresponsive hydrogels based on self-healing. Table 4 The properties of photoresponsive hydrogels based on self-healing. Table 4 Publication Input Time Self-healing rate Method Xiong et al.(2018)[ 96 ] Vis440nm 2 h 77% Host-guest interactions Zhang et al.(2020)[ 101 ] – 20s 96% Metal–ligand/Hydrogen bonds Cheng et al.(2019)[ 103 ] NIR980nm 60s – Covalent bond reconstruction network Yang et al.(2017)[ 100 ] UV365 nm/vis 450 nm – 90%(vis) Host-guest interactions Yang et al.(2019)[ 93 ] Dark 24 h 100% Host-guest interactions Yu et al.(2018)[ 104 ] UV＜384 nm NO UV 350min/UV180min 50%/95% Covalent bond reconstruction network Wang et al.(2019)[ 102 ] UV – – Hydrogen bonds Zhang et al.(2020)[ 99 ] NIR3min(60 °C) – 60% Hydrophobic interac-tions Kim et al.(2020)[ 97 ] UV365nm/Vis430nm 12 h 81.59% Host-guest interactions Zheng et al.(2017)[ 98 ] UV365nm/Vis430nm 20min 89.80% Host-guest interactions 5.1.2 Mechanical strength As the demand for robots grows, the limitations imposed by the mechanical strength deficiencies of conventional hydrogels become more apparent. Soft robots poor mechanical properties make it difficult to accurately manufacture complex structures and make them prone to functional failures when working in unstructured environments. Some existing approaches to improving the mechanical properties of hydrogel soft robots include dual network structures, host-guest recognition, material enhancement methods, and 3/4D printing preparation techniques. The covalent bonds of conventional covalently bonded double network hydrogels cannot be reformed when subjected to large mechanical deformations, resulting in irreversible and permanent material damage. Finally, the overall mechanical properties of the hydrogel deteriorate. As a result, hybridised or physical DN [ 105 , 106 ] hydrogels with high mechanical properties can be employed to create hydrogel networks. Furthermore, topologically structured hydrogels [ 107 ] improve the microstructural regularity of the hydrogel by modulating the “8″-shaped cross-linked ring structure, thereby improving reversibility and mechanical strength. Physical interactions based on supramolecular linkages, such as ionic bonds, hydrogen bonds [ 108 , 109 ], crystallisation, and hydrophobic interactions [ 110 ], are reversible in contrast to covalent bonds. Furthermore, host-guest recognition can improve the hydrogel's mechanical strength alongside its self-healing performance. The type, concentration, and surface properties of nanofillers may be applied to tune hydrogel properties [ 111 ]. As physical crosslinkers and fillers, nanoparticles can relax applied stresses and delay the fracture of the hydrogel [ 112 ]. GO can also be added to increase crosslinking density by forming H-bonds with the hydrogel backbone, thereby increasing the elastic modulus of the hydrogel [ 113 , 114 ]. Similar to GO, CNT/CNC/NFC [ 72 ] can be added to the hydrogel matrix to increase stiffness while preserving biocompatibility [ 115 , 116 ]. In addition, clay and noble metal nanoparticles (e.g., Au, Ag), which are naturally mechanically robust nanofillers, can significantly enhance the mechanical properties of hydrogel matrices [ 46 , 117 ]. 4D printing technology is derived from 3D printing with the addition of a “temporal” dimension, enabling printed material structures to respond to external physical field stimuli. By combining specific composite materials, 3D models of target structures [ 58 ] (e.g., dual-network hydrogels) can be rapidly fabricated into solids using 3D/4D printing techniques [ 119 , 120 , 135 ]. 5.1.3 Response speed Fast drive strategys, such as fast starts, jumps, must generate high intensity in a short amount of time. Soft robots based on photoresponsive hydrogels can increase their response speed by altering the ratio of light conversion efficiency to actual mechanical energy transfer efficiency. The expansion and contraction of hydrogels are primarily caused by a network of polymers absorbing and releasing water molecules. Currently, hydrogel network structures (e.g., porous hydrogels, comb-like hydrogels [ 60 ], and microsphere composite hydrogels [ 61 ]) can be modified to allow water molecules to pass easily into and out of the gel network, to reduce diffusion resistance, or to improve response rate by decreasing the hydrogel feature size. However, the field still faces significant obstacles, such as material and structural design optimization. 5.1.4 Structure shape Chemical and physical structures, such as cross-link density, pore size, and pore channels, comprise the structure of hydrogels. These structural parameters will directly influence the mechanical properties, water absorption performance, mechanical stability, etc. of hydrogels. For instance, hydrogels with a high crosslink density have greater strength and stiffness and can withstand large tensile or compressive forces, whereas hydrogels with a low crosslink density are softer and can be utilised in bionic robots. Various preparation techniques can yield hydrogels with distinct structures and forms, such as fibrous, spherical, and sheet-like. These various hydrogel shapes can be used to create soft robots with various forms and functions. Fiberous hydrogels are able to design robotic gloves or skin, while spherical hydrogels may be employed to build miniature pumps and sensors. To achieve the optimal structure and shape for a particular application scenario, the optimal preparation method (free radical polymerization, ionic gelation, physical cross-linking, etc.) is chosen. Using different crosslinking agents, crosslinking times and temperatures, etc., it is possible to produce hydrogels with varying crosslinking densities, resulting in hydrogels with distinct mechanical properties and shapes. By analysing the applicability and performance of the structure and form of hydrogels, it can improve the motility of soft robots and develop new applications."
} | 6,400 |
34516870 | PMC8442876 | pmc | 9,750 | {
"abstract": "Living plants are turned into light-storing and emitting photonic devices by infiltrating them with phosphorescent nanoparticles.",
"introduction": "INTRODUCTION There has been substantial interest in using living plants to create functional devices that replace those fabricated from plastic and circuit boards, and are ultimately disposed of as waste ( 1 – 10 ). Examples of these devices include the use of plant leaves as sensors for the detection of plant mechanical wounding ( 11 ), development of biocompatible plant-based electronic semiconductors and electrochromic pixels ( 4 ), and plant adenosine triphosphate (ATP)–powered genetically encoded autoluminescent light sources ( 6 – 8 ) as sustainable alternatives. The plant leaf itself, in particular, has specific optical properties that enable its functions of photosynthesis and reflectance ( 12 ). However, to date, there has not been a study on how to change these properties in plants to achieve additional functions, such as phosphorescence, in pursuit of these larger sustainability goals. The hypothesis addressed in this work is whether the plant spongy mesophyll itself can provide a photonic substrate to enhance or augment plant-based photonics and light emission specifically. This is a scientific question because the biocompatibility, particle adhesion, and mesophyll hydraulic function upon nanoparticle (NP) deposition are not known. In this work, we investigate how NPs can be infiltrated into the leaf mesophyll ( Fig. 1A ) to change its ability to absorb, store, and re-emit incident light. The resulting photonic capacitance will help to introduce functional optics into living plants with the particular localization in the plant mesophyll area, fully biocompatible and functional. Fig. 1. SA NP infiltrated in living plants. ( A ) (Left) Schematic image of the mesophyll region of a plant leaf. The image shows cuticle, upper epidermis, mesophyll region, lower epidermis, vessel, palisade cells, spongy cells, guard cells, and stomata. (Right) Schematic image of the modified leaf with the SA NPs. ( B ) Light emission (after charging for 10 s with 400 mW/cm 2 400-nm light source) infused in 3-week-old watercress leaf with solution of 650 ± 290 nm SA NP (25 mg/ml). The image was captured on camera set on 30-s exposure time. ( C ) Cryo-SEM image of nonmodified freeze-fractured watercress leaf. Scale bar, 10 μm. ( D and E ) Original and false-colored cryo-SEM images of freeze-fractured modified watercress leaf with solution of 650 ± 290 nm SA NPs (25 mg/ml). Scale bar, 2 μm. ( F ) Cryo-SEM images of freeze-fractured partially infused watercress leaf [the direction of the fracture is shown with the red line in (B)] having both nonmodified (left side) and modified (right side) with 650 ± 290–nm SA NP regions. Orange box shows the zoom region for the next images. Scale bar, 10 μm. ( G and H ) Original and false-colored zoom of the cryo-SEM images of SA-modified region in watercress leaf with solution of 650 ± 290 nm SA NP. Scale bar, 2 μm. Photo credit: Pavlo Gordiichuk, Massachusetts Institute of Technology. There have been significant advances toward the conversion of living plants into functional devices; however, photonic modifications have not been studied to date, particularly with NP approaches ( 9 ). For example, Giacomo et al. ( 3 ) applied plant cells and carbon nanotube composites to develop state-of-the-art electronic temperature sensors. We previously used a DNA-wrapped carbon nanotube to transform living spinach plants into ground-water monitoring sensors and described methods for the modification of plant optical properties ( 2 ). Stavrinidou et al. ( 4 ) synthesized conducting organic polymers inside plants, with the potential for creating electrical conductors in living plants. As a distinct objective, we used NP techniques to transform living watercress plants into chemiluminescent lamps that emit light at an average intensity of 10 10 photons/s ( 5 ). However, these past techniques do not address or change the optical properties of the leaf itself. Others have genetically modified plants to emit light using bioluminescence genes ( 8 ), the six genes of the lux operon ( 7 ), or the firefly enzyme Luciferase ( 6 ). However, no work to date has focused on manipulating the optical properties of the leaves themselves, and their control in terms of absorption, light storage, and re-emission. This is despite the obvious benefits of such control to the overall aim of creating living plant light sources and optical sensors. In addition to studies that functionalize plants, researchers have also explored the interface of materials with living plants, however, not the underlying spongy mesophyll, for other applications. Nassar et al. ( 13 ) applied wearable electronic circuits to plant leaves to monitor microclimate and growth conditions. Similarly, Zhao et al. ( 14 ) developed stretchable sensors for long-term studies on plant leaves. Tang et al. ( 15 ) developed a chitosan-based ink for plant growth monitoring with the flexible sensor. We applied microfluidic-printed stomata sensors allowing the continual monitoring of drought conditions in plants ( 16 ). Last, Damak et al. ( 17 ) developed a strategy for enhancing water deposition on plant leaves via an in situ precipitation strategy that used charged polymers sprayed from two nozzles. While these external devices are useful, the application of nanomaterials inside plant leaves confers several alternate advantages. These nanomaterials can serve the role of a real-time reporter, monitoring analytes taken up by roots ( 2 ) [such as nitric oxide ( 9 )], probing the innate plant signaling pathways in response to external stresses ( 11 ), or serving as an organelle-specific nanocarrier for genetic engineering in plants ( 18 – 20 ). The passive transport of NPs into plant protoplasts can be controlled by tuning their size and charge, established by a theoretical model called lipid exchange envelope penetration developed by our group (LEEP) ( 21 ). Despite this progress in understanding NP transport and localization in plant cells, there has not been a study addressing how NPs can interact with the mesophyll of the plant to modify its optical properties. In contrast to previous reports leading to the development of light-emitting plants via nanobionics ( 5 ) and genetic modification strategies ( 6 – 8 ), we aim for decoration of plant mesophyll surfaces with photoactive materials having photoemission properties upon multiple excitations without the application of chemical reactions or infusions. In this work, we show that several plants such as tobacco ( Nicotiana tabacum ), basil ( Ocimum basilicum ), daisy ( Bellis perennis ), watercress ( Nasturtium officinale ), and elephant ear ( Colocasia ) can be converted into a plant-based photonic device by stomata infusion using an optimal size of 650 ± 290 nm strontium aluminate (SA) NPs. We show that using SA particles with weak interparticle potentials, homogeneous and high-density coverage of the mesophyll can be obtained in vivo. We demonstrate that there is a characteristic difference in performance between NPs infused in different plant types, an indication that the mesophyll surface area plays a crucial role in the morphology and resulting photo-optical properties. We examine the biocompatibility in the form of chlorophyll concentrations [soil plant analysis development (SPAD)] across watercress plants and measure phosphorescent decay times as a function of particle properties. Our work establishes the fabrication and characterization methods required to transform living plants into functioning photonic substrates with useful phosphorescent capacitance, creating opportunities for plant-based optical reflectance, signaling, and light emission.",
"discussion": "DISCUSSION We compared the measured light intensity produced of our plants with the chemiluminescent light of other light-emitting plant systems ( Fig. 7B ) ( 6 – 8 ). I max is the maximum observed photon intensity at the start of the measurement. Here, we define illumination lifetime as the time when the intensity falls to 90% of I max [see ( 10 )]. The phosphorescence in this work can exceed the emission intensities of plants that generate their own emission studied in the literature. That means that the photonic capacitance demonstrated in this work could potentially augment the light generated in these other studies by, for example, being charged from or re-emitting in parallel with chemiluminescent or genetic engineering emission strategies. For this, the absorption cross section of the SA should be optimized to receive bioluminescence from the plant. This has the benefit of increasing the total amount of potential radiant light energy available for emission from the plant (i.e., augmentation with stored solar energy). In addition, the function of phosphorescent NPs as light capacitors can also smooth and regulate chemiluminescent emission to produce more even illumination [see, for example, figure 2A in ( 5 )]. In addition, our experiments showed close to 60% SA NP recovery from the infused tobacco plants as a forcible strategy for e-waste utilization (Materials and Methods and fig. S22). As a final proof-of-concept experiment, mSA NPs were infiltrated into 50-cm-tall seedling of a “Thailand Giant” Elephant Ear ( Colocasia ) tree. We applied mSA particles to a 30-cm-long leaf with the same infusion method as with previous plants. However, the large size of the leaf required many more point-by-point infiltrations to cover the entire area ( Fig. 7C ). After 10 s of charging with 400-nm blue LED (400 mW/cm 2 UV-blue), the portrait pictures were made on Pixel 3a camera after the immediate movement of the excitation source. Because the elephant ear leaf was subjected to serial infusion, the close images recorded similarly enable illustrating of phosphor NP deposition along either side of the mid-vein along the secondary veins as shown in Fig. 7E . The recorded images showed efficient lateral spreading of the NPs along the leaf, even between veins, and demonstrated the potential scalability of our methods to large, potentially meter-sized plants. In conclusion, we investigated the mesophyll region of living plants as a biocompatible substrate for the photonic display of thin nanophosphor films, with the ultimate goal of creating living plant optical devices. We find that size-sorted, silica-coated SA NPs can be successfully infused into the mesophyll through the stomata pores of tobacco ( N. tabacum ), basil ( O. basilicum ), daisy ( B. perennis ), watercress ( N. officinale ), and Colocasia (also called Thailand Giant Elephant Ear) plants. Our work demonstrates that infused SA NPs remain in the spongy mesophyll area of plant leaves without entering into the plant cells themselves. Unexpectedly, maximum phosphorescent emission intensities per plant approach 4.8 × 10 13 photons/s, which is sufficient to advance plant-based emission strategies. Biocompatibility is examined by long-term chlorophyll concentrations measured across 180 watercress plants over a period of 9 days after infiltration. We mapped the trade-off between phosphorescent decay time and particle size for Si/SiO 2 -coated species, balancing infusion efficiency with desired optical properties for the first time. Our work demonstrates long-term robustness by examining a cohort of 160 plants, which were subjected to alternating cycles of charging and emission for 16 hours a day for approximately 2 weeks without observable impact to plant physiology. Hence, our work advances the fabrication and characterization required to transform living plants into functioning photonic substrates. Therefore, this enables opportunities for plant-based optical reflectance, signaling, and the augmentation of plant-based light emission."
} | 2,974 |
35541775 | PMC9075744 | pmc | 9,751 | {
"abstract": "Thanks to the advent of the random laser, new light applications have opened up, ranging from biophotonic to security devices. Here, by using the well-known but unexplored light-harvesting bio-pigment of butterfly pea ( Clitoria ternatea , CT) flower extract, generation of continuous-wave (CW) random lasing at ∼660 nm has been demonstrated. Furthermore, a wavelength tunability of ∼30 nm in the lasing emission was obtained by utilizing the resonance energy transfer (RET) mechanism in a gain medium with a binary mixture of CT extract and a commercially available methylene blue (MB) dye as the gain medium. In the CT extract–dye mixture, the bio-pigments are acting as donors and the MB dye molecules are acting as acceptors. Amplification in intensity of the lasing emission of this binary system has further been achieved in the presence of optimized concentrations of metal (Ag)–semiconductor (ZnO) scattering nanoparticles. Interestingly, the lasing threshold has been reduced from 128 to 25 W cm −2 , with a narrowed emission peak just after loading of the Ag nanoplasmon in the ZnO-doped binary gain medium. Thanks to the strong localized electric field in the metal nanoplasmon, and the multiple scattering effects of ZnO, the lasing threshold was reduced by approximately four times compared to that of the gain medium without the use of scatterers. Thus, we believe that our findings on wavelength-tunable, non-toxic, biocompatible random lasing will open up new applications, including the design of low-cost biophotonic devices.",
"conclusion": "3. Conclusions In conclusion, here we have reported biocompatible CW RL generation, from the natural light-harvesting bio-antenna of butterfly pea flower extract. The positive influence of metal–semiconductor NPs on the bio-pigment leads to enhanced lasing emission at ∼660 nm. In addition, RET-based tunable NIR random lasing is demonstrated at ∼692 nm by using the natural dye, i.e. CT extract, and the common, commercially available MB dye. It has been shown that significant reduction in lasing threshold, band narrowing, wavelength tunability in RL emission of over 30 nm from 660 to 692 nm and generation of lasing mode are possible by addition of Ag NPs into the ZnO-doped CT–MB binary system, which is due to the enhancement in the local electric field in triangular-shaped Ag NPs. The biocompatible random laser developed here could provide a new tool for imaging in biological tissues. In addition, we believe that our findings offer a cost-effective approach for optimizing a tunable multi-colour plasmonic RL, avoiding the need to resort to specially engineered, expensive and toxic dyes.",
"introduction": "1. Introduction The laser, almost 60 years after its invention, has become a key light source in modern imaging systems. However, a conventional laser has a high degree of spatial coherence, which produces unwanted coherent imaging artefacts, such as the formation of speckles. Therefore, researchers are now putting enormous effort into devising an unconventional laser system, called a random laser (RL), which is free from such drawbacks. 1–3 Demonstrations of random lasing have been reported with both pulsed and continuous-wave (CW) pumping. 4–12 Generally, long-wavelength or near-infrared (NIR) (>650 nm) fluorescent dyes have high penetration properties in tissue. 13–15 Therefore, they can be fruitfully used for biomedical and biophotonic applications, such as in surgical therapy treatments, cancer diagnostics, etc. 13–16 However, these dyes have some drawbacks, including poor photostability, low absorption at specific pump wavelength, non-biodegradability, toxicity, and also expense. 1,13–16 Therefore, they are not appropriate in biomedical and biophotonics applications. Recently, environmentally friendly, non-toxic, optically active bioorganic dyes extracted from natural resources, such as carotene, porphyrins, chlorophylls, etc. , have become the obvious choice as the gain medium in RL generation. Use of these dyes has many advantages; 8,10,17,18 for example, they (1) are biodegradable and biocompatible, (2) have efficient light-harvesting capabilities in the long-wavelength region, and (3) have higher molar extinction coefficients to enable efficient light harvesting. Additionally, these bio-pigments are available in large quantity, and can be safely extracted from fruits, flowers and leaves. 8–10,17–20 Here, we have selected a biocompatible natural organic dye, namely extract of butterfly pea ( Clitoria ternatea , CT), a medicinal plant, which is used extensively as a natural colouring agent around the world. 17 This flower extract has already been used as a substitute for commercial toxic blue dye in different medical and food packaging sectors. 18,19 The blue colour of the extract in neutral aqueous solution indicates the presence of different flavonoid and anthocyanin content, as reported by others. 18,19 Such optically active biodegradable organic dyes provide a unique possibility for RL generation in combination with metal/semiconductor nanoparticles (NPs) as the scattering particles. 4–6,21–23 Traditionally, it has been reported that, RL generation is dependent on multiple scattering of light in a random gain medium. The presence of the strong electric field of metal NPs may enhance these scattering properties, and may also modify the transition rates of nearby dye molecules. 4–6 Random lasing has been obtained in several materials, such as metal/semiconductor NPs, human tissue, liquid crystals, fluorescent polymers, commercial dyes, etc. 4–7,21–23 At present, there is a huge demand for multi-coloured random laser sources in the medical and optoelectronics sectors. The resonance energy transfer (RET) process is another strategy to achieve tunable emission, with improved emission intensity from a gain media. 24–27 The minimum requirement for the occurrence of energy transfer in the RET process is the availability of good overlap between the emission band of the donor and the absorption band of the acceptor. 4 One example, is a mixture system with more than one dye, in which one (donor) dye efficiently absorbs the pump radiation, and then the excitation energy is non-radiatively transferred to the second (acceptor) dye. 6,24–27 Here, we demonstrate RET-assisted CW RL generation using a bioorganic pigment as the gain medium, which is biodegradable and cheap. Also, we have improved the lasing efficiency and achieved tunable emissions by employing a RET process in which CT dye molecules transfer energy to methylene blue (MB) dye. The mechanism of the energy transfer has also been studied by analyzing the optical properties of the mixtures of donor and acceptor after encapsulation in a polymer film. A significant reduction in lasing threshold, from 128 to 25 W cm −2 , has been demonstrated, with systematic increase in the number and concentration of scatterers (ZnO and Ag NPs). Thorough analysis of the RL emission allowed us to infer the role of the energy transfer process and the presence of semiconductor and plasmonic NPs in enhancing the lasing emission. The unprecedented demonstration of RET-assisted tunable random lasing in this work indicates that natural pigments can be effectively utilized to develop cost-effective random lasers using easy processing steps.",
"discussion": "2. Results and discussion The UV-visible absorption spectrum of the bio-pigment was measured and is shown in Fig. 1a . The presence of Q-bands at ∼533 nm, ∼573 nm, and ∼618 nm are clearly seen in Fig. 1a . We also studied the photoluminescence (PL) emission spectrum of the extracted pigment ( Fig. 1a ), which was found to be consistent with the visible PL emission peak at ∼660 nm corresponding to the S 1 → S 0 transition. Digital photographs of the butterfly pea and the extraction of pigments in water are also shown in Fig. 1a (right inset). To determine the presence of different functional groups in the organic pigments, Fourier-transform infrared spectroscopy (FTIR) data were collected and are shown in Fig. 1b . From Fig. 1b it can be seen that several functional groups, such as –CH, –C \n \n\n<svg xmlns=\"http://www.w3.org/2000/svg\" version=\"1.0\" width=\"13.200000pt\" height=\"16.000000pt\" viewBox=\"0 0 13.200000 16.000000\" preserveAspectRatio=\"xMidYMid meet\"><metadata>\nCreated by potrace 1.16, written by Peter Selinger 2001-2019\n</metadata><g transform=\"translate(1.000000,15.000000) scale(0.017500,-0.017500)\" fill=\"currentColor\" stroke=\"none\"><path d=\"M0 440 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z M0 280 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z\"/></g></svg>\n\n O, –OH, are present in the bio-pigment. The presence of hydroxyl groups ( Fig. 1b ) helps the anthocyanins to absorb light in the visible region. 18 The existence of a strong absorption band at ∼632 nm and a good PL emission peak at ∼660 nm facilitated the use of this bio-pigment as a gain medium in the RL experiment, as shown later. The PL emission of the pigment in the solution phase was measured at different input pump intensities (IP) of a He–Ne laser with λ pump = 632.8 nm, as shown schematically in Fig. 1c . The results obtained are shown in Fig. 1d and e . Although amplified spontaneous emission (ASE) was observed, narrowing of the spectral profile, as well as a distinct threshold, was not observed, even after increasing the pump intensity. Fig. 1 (a) UV-visible absorption and PL emission spectra of natural CT dye extract. Right inset (upper panel) shows digital photographs of the flower and its extraction in water (lower panel). (b) FTIR spectrum of CT. (c) A schematic illustration of CW excitation and PL emission of the bio-pigment in solution phase. (d) Emission spectra of the CT dye extract without scatterers at different IP intensities. (e) Emission intensity from CT excited by 632.8 nm under different IP without scatterers. (f) The normalized absorption spectra (1 and 2) and the PL emission spectra (3 and 4) of CT and MB dye in water. (g) A schematic illustration of the RET process in the metal–semiconductor-based dual-colour random laser under CW pumping. Therefore, to overcome such drawbacks, i.e. low laser emission at NIR region as well as tunability in lasing emission, the RET process has been employed as an important strategy. It was found that there is good overlap between the emission band of CT (solid red line) and the absorption band of MB (solid black line) ( Fig. 1f ), confirming the possibility of efficient energy transfer (ET) from the donor (CT) to the acceptor (MB) dye. The calculated value of the overlap integral is J ( λ ) = 2.94 × 10 15 nm 4 M −1 cm −1 using eqn (1) , 6 1 where F D ( λ ) is the total normalized PL intensity (area under the curve) of pigments in the wavelength range λ + Δ λ and ε ( λ ) is the molar extinction coefficient of the MB dye at λ . The origin of the emission tunability and details of the tuning mechanism for the lasing emission using the RET process are illustrated schematically in Fig. 1g . The input energy of the pump light (632.8 nm) is mostly absorbed by CT molecules. The excited CT molecules partially transfer their energy to the MB molecules, leading to the dual-colour emission at ∼660 nm (near red) and ∼692 nm (deep red), respectively. It was found that the output emission intensity from the donor increased rapidly once the pump intensity exceeded the lasing threshold energy, while some residual acceptor emission was also found to increase slowly. As the acceptor/donor (A/D) ratio increased further, the lasing threshold of the acceptor showed a stable output from the donor/acceptor mixture system. Furthermore, after addition of semiconductor and metal NPs as scatterers in the random system, multiple scattering significantly disturbed the random system and decreased the lasing threshold, by dynamically changing the strong local electromagnetic field. 4,5 Thus, the RET process greatly influences the multi-colour RL under single excitation conditions. In addition, we have measured stability of the MB dye with laser exposure time (Fig. S1 † ) and it was clearly seen that there is almost no change in emission intensity after laser irradiation for a duration up to 15 min (for details see ESI † ), and only a 10% reduction in intensity after 45 min. \n Fig. 2a represents the PL emission spectra of the RET-based binary system with different volume ratios of the acceptor and donor. Two clear emission bands (red and cyan arrow) for the CT and MB dyes, centred at ∼660 nm and ∼692 nm, are observed under 632.8 nm excitation. The A/D ratio was changed in order to control the RET efficiency ( Fig. 2b ). A coefficient known as the energy transfer coefficient ( η ET ) 27 was calculated using eqn (2) , to describe the ET processes physically in the semiconductor–metal-based binary random lasing system. The expression for η ET is given as, 2 η ET = I A /( I A + I D ), where I A is the integrated emission intensity of MB dye at ∼692 nm and I D is the integrated emission intensity of CT at ∼660 nm. It was found that, as we increased the A/D ratio from 0 to 7.33, the intensity of the emission band corresponding to CT quenches, while the intensity of the emission corresponding to the MB dye increases gradually under excitation at 632 nm (Fig. S2 † ). The evolution of η ET with A/D ratio is demonstrated in Fig. 2b . As the A/D ratio increases from 0.85 to 19.0, the RET coefficient is also found to increase and reaches saturation at A/D = 7.33 ( Fig. 2b ). 25 Fig. 2 (a) Normalized PL emission spectra of CT and MB dye with different A/D ratios. (b) Effective RET efficiency as a function of A/D ratio in the binary system. The PL emission spectra of the bio-pigment in the presence of scatterers with appropriate concentrations are shown in Fig. 3 . The microstructural properties of rod-like ZnO and triangular Ag NPs are shown in the typical SEM and TEM images in Fig. 3a and b . The absorption spectra of ZnO and Ag NPs can also be seen to have a spectral overlap with the emission spectra of the bio-pigment, as shown in Fig. 3c . The presence of a broad absorption peak at ∼600 nm is due to the in-plane dipole resonance in the triangular Ag NPs. 8 The large scattering property of ZnO NPs, which is due to the contrast in refractive index in the gain medium, provides multiple scattering leading to the observation of ASE. 27–29 The results are shown in Fig. 3d and indicate that the amplification is not sufficient to achieve proper lasing emission at low pumping energy using only ZnO NPs. Therefore, to achieve further increase in the output intensity of the solution, metal NPs were used as an additional scatterer to provide strong, multiple scattering through enhancement of the electromagnetic field ( Fig. 3e ). The changes in emission intensity with a fixed concentration ratio of ZnO and triangular-shaped Ag NPs are shown in Fig. 3e and it can be seen that effective light amplification takes place and some lasing peaks have appeared on top of the emission band (inset in Fig. 3e ). The dependence of the integrated normalized emission intensity of the pigments on input pump intensity, in the presence of scatterers, is shown in Fig. 3f . From Fig. 3f , a lasing threshold ( CW I th ) of 128 W cm −2 was obtained after addition of an optimized concentration of ZnO ( n ZnO = 7 × 10 12 ml −1 ) and Ag NPs ( C Ag = 12 × 10 15 ml −1 ) in the random system. Fig. 3 (a) SEM image of ZnO NPs. (b) TEM image of triangular Ag NPs. (c) Normalized absorption spectra of ZnO and Ag NPs with absorption-emission spectra of the CT dye. Emission spectra of CT dye extract in the presence of (d) ZnO only and (e) ZnO–Ag NP scatterers at different input intensities. The inset shows an enlarged section of the emission pattern, where we can easily observe generation of the RL mode. (f) Emission intensity from CT–ZnO (left) and CT–ZnO–Ag (right) solution excited by 632.8 nm under different input intensities. It can be seen from the plot ( Fig. 3f , left) that within the pump energy used there is only one kink when ZnO NPs are used as the scatterer in the CT dye. However, two kinks are clearly visible ( Fig. 3f , right) in the presence of the binary scatterer, i.e. ZnO and Ag NPs in the CT dye, 3 indicating the transition from spontaneous emission (SE) to amplified spontaneous emission (ASE) and to lasing. Therefore, from the results shown in Fig. 3f (right), it can be concluded that, even with the low pump energy used, lasing is observed in the CT dye by using the binary scatterer, since the metal NPs have caused further enhancement of the electromagnetic field of the pump light by surface plasmon resonance processes. To demonstrate RL generation in the near-IR region, with significant improvement in the lasing emission of the gain medium, the dye mixture was encapsulated in a homogeneously dispersed aqueous solution of a polymer matrix, as shown in Fig. 4a (details of the procedure are in given in the Experimental section). Fig. 4b shows the emission spectra of samples with optimized scatterer concentrations at two input pump intensities of 10 W cm −2 and 135 W cm −2 . Depending on the different A/D ratios with energy transfer efficiency, different scenarios have been observed. At low A/D concentration ratio (A/D = 0.85), the emission peak intensity of the CT dye at ∼660 nm is found to be stronger than that of the emission peak intensity of the MB dye at ∼692 nm. As the value of IP increases, from 10 to 135 W cm −2 , a large number of lasing peaks appear on top of the emission band at ∼660 nm, which is clear from Fig. 4b , and those peaks fluctuate randomly. 6,30–32 On the other hand, a relatively low, intense, broad emission band for the MB dye is observed at ∼692 nm. Upon further increase in the A/D ratio (from 1.5 to 7.33), more energy is non-radiatively transferred to the acceptor, which prevents lasing of the donor and helps spectral narrowing of the acceptor ( Fig. 4b ). 33 Therefore, it can be concluded that the emission intensity ratios are greatly influenced by the variation in A/D ratio in such random binary systems. Additionally, for a fixed A/D ratio, the appearance of a number of sharp peaks increased with increasing IP value, indicating the occurrence of RL at high values of input energy. It can be seen from Fig. 4b that there are some random spikes appearing that cover the wavelength range beyond 700 nm, and at around 750 nm when the pump intensity is at its highest. From static PL emission measurements of the MB dye only, it was found that some shoulder peaks appear at ∼750 nm; so, the peaks at ∼750 nm in Fig. 4b might have appeared due to emission from the MB dye. However, further studies are required to find the exact origin of peaks other than those appearing at ∼660 nm and ∼692 nm. Continuing our study of the switching of emission with A/D ratio, the change in CIE colour chromaticity with increasing A/D has also been calculated, as shown in Fig. 4c . In the CIE 1931 colour diagram, the circles describe the calculated colour chromaticity of the binary mixture at different A/D ratios ( Fig. 4c ). It was observed that, with increasing A/D ratio, the chromaticity values of the multi-colour RL varied from (0.69, 0.29) to (0.54, 0.21) under the same pumping energy of 135 W cm −2 . The results shown in Fig. 4d were obtained by multi-peak fitting of the corresponding emission spectra. In Fig. 4d , the transition from SE to ASE and then to random lasing emission in the binary system can be seen. However, the position of the random lasing emission is solely dependent on the A/D ratio. At low A/D ratio (0.85), the binary system shows random lasing emission at ∼660 nm, corresponding to the CT dye with two clear kinks, whereas, at this ratio, the emission from the MB dye at ∼692 nm is of a spontaneous type ( Fig. 4d ). On the other hand, at high A/D ratio (4.50), the binary system exhibits random lasing emission at ∼692 nm due to energy transfer from the CT dye to the MB dye. To study the changes in RL emission intensity, if any, with respect to the number of measurements, the lasing emission spectra in the gain media with optimized A/D ratios of 0.85 and 4.50 were collected up to 95 times at a fixed pump laser excitation intensity of 135 W cm −2 . The corresponding results for the two narrow spikes obtained at ∼660 nm and ∼692 nm with an A/D ratio of 0.85 and 4.50, respectively, are shown in Fig. 4e . It can be seen that the fluctuations in peak intensity from their average values at ∼660 nm and 692 nm are very small. However, it was found that the RL peak at 660 nm was the most intense for an A/D ratio of 0.85, whereas the peak appearing at 692 nm was the most intense for an A/D ratio of 4.50. So, this indicates that the peak intensity at ∼692 nm can be enhanced with increasing A/D ratio. Thus, switching of the lasing emission can be achieved by varying the mixing ratio of the donor and acceptor dyes. Fig. 4 (a) Representation of the preparation process for the polymer films. The resulting composite film is then pumped using a CW He–Ne laser ( λ pump = 632.8 nm) and the emission from the film is collected and sent to a spectrometer with a detector for analysis. (b) Normalized emission spectra from random systems with different A/D ratio of (i) 0.85, (ii) 1.50, (iii) 4.50, (iv) 7.33, are excited by 632.8 nm under low and high IP energy. The concentration of the ZnO and Ag NP suspensions are 7 × 10 12 ml −1 and 12 × 10 15 ml −1 , respectively. (c) Switching of colour chromaticity of the emission spectra with different A/D ratio, extracted from the spectra in Fig. 2a . (d) Variation of lasing intensity with different IP at the two peaks of CT (∼660 nm) and MB (∼692 nm) at A/D ratios of 0.85 (upper panel) and 4.50 (lower panel), and observation of their threshold behaviour. (e) The variation in emission intensity of the observed narrow spikes (at ∼660 nm and 692 nm) with the number of measurements carried out in a sample with optimized A/D ratios and for a fixed excitation energy of 135 W cm −2 . In order to study the dependency on the direction of the lasing emission from the polymer film, lasing was measured at different emission angles. Fig. 5a shows a schematic of the position of the detector for collecting the emission spectra at different angles ( θ = 0 to 180°) with respect to the incident CW excitation. Fig. 5b shows the polar graph of the integrated emission intensity versus the detection angles ( θ ) of the lasing emission and it can be seen that the emission intensity depends strongly on the angle. It was observed that the lasing emission intensity is highest at θ ≅ 60°. Therefore, subsequently, the RL emission data have only been collected at an angle of 60°. Fig. 5 (a) Schematic representation showing the detection of lasing emission at different angles. (b) Polar graph of integrated emission intensity at different detection angles. In an optical gain medium, disordered structure can offer random lasing via multiple scattering in the medium by changing the scattering length, and this conclusion has been supported by measurement of the mean free path of the binary system. The minimum mean free path ( l min ) of the photons in the polymer film was calculated using eqn (3) , 30 3 where, n and d are the refractive index and thickness, respectively, of the CT–MB–ZnO composite polymer film, and the value of l min was found to be ∼0.28 mm. As reported previously, random lasing is also observed in a weakly scattering regime ( kl min ≫ 1). 34,35 Therefore, our system has acted as an extremely weak scattering medium ( l min ∼ 0.28 mm), which does not help to achieve band narrowing or distinguish threshold behaviour as expected. Therefore, we introduced a plasmonic enhancer ( i.e. triangular Ag NPs) into the random system, which can greatly enhance the local electrical field. 5,6,35 In order to investigate the significance of Ag NPs on the random system, different concentrations of ZnO and Ag NPs were carefully mixed in the polymer matrix with different donor–acceptor ratios. Fig. 6a and b shows the RL emission spectra of the polymer films obtained under different input intensity in the absence and presence of Ag NPs, but for the same number density of ZnO NPs. To determine the dependence of the scatterer concentration on CW I th , the number density of the ZnO NPs ( n ZnO ) was varied from 2 × 10 12 to 20 × 10 12 ml −1 , as shown in Fig. 6a and S3. † It was observed that, with the increase in the number density of ZnO NPs from 2 × 10 12 to 20 × 10 12 ml −1 , CW I th was reduced significantly, from 107 W cm −2 to 43 W cm −2 , as shown in Table 1 and Fig. S3. † The dependence of the input pump energy on the integrated emission intensity in the CT–MB–ZnO system (with n ZnO = 20 × 10 12 ml −1 ), as depicted in the inset in Fig. 6a , shows a typical ASE nature, with a threshold value of 43 W cm −2 . In the case of CW operation, CW I th was not as distinct as it is often observed to be during pulsed mode operation, since under CW conditions spontaneous emission may significantly influence the threshold. 36 Fig. 6 The emission spectra of CT–MB medium in the presence of the ZnO scatterer ( n ZnO = 7 × 10 12 ) at different IP energies (a) without Ag NPs and (b) with Ag NPs ( n ZnO = 20 × 10 12 and C Ag = 36 × 10 15 ml −1 ), respectively. The inset shows the threshold behaviour of the random system for RL generation in the MB dye. (c) Normalized emission spectra of polymer films containing a mixture of CT and MB dye with ZnO ( n ZnO = 20 × 10 12 ml −1 ) and Ag NPs ( C Ag = 36 × 10 15 ml −1 ) under low (red line) and high (black line) IP energy. (d) RL generation in polymer film with three different A/D ratios and in the presence of ZnO ( n ZnO = 20 × 10 12 ml −1 ) and Ag NPs ( C Ag = 12 × 10 15 ml −1 ) under an IP energy of 68 W cm −2 . Experimentally obtained values of lasing threshold of the binary mixture CT–MB and ZnO (×10 12 ml −1 ) CT–MB–ZnO ( n ZnO = 20 × 10 12 ml −1 ) and Ag NP (×10 15 ml −1 ) Concentrations 2 7 13 20 12 24 36 \n CW I th (W cm −2 ) 107 83 60 43 35 33 25 However, with the addition of Ag NPs, CW I th is reduced significantly, as shown in Fig. 6b . It can be clearly seen that the emission spectra of the polymer film with Ag NPs has multiple peaks, as shown in Fig. 6b , with the central lasing peak at ∼692.4 nm narrowed down compared with that without Ag NPs ( Fig. 6a ) for the same pumping energy. The lasing threshold value of the random system has decreased by up to four orders of magnitude due to the presence of Ag NPs (Fig. S3 † and Table 1 ). This result indicates the occurrence of random lasing in the presence of Ag NPs, and the lasing modes are generated due to multiple scattering of trapped photons and enhancement of the local field inside the gain medium. 5,6,24–26 The narrowed, sharp emission occurring at ∼692.4 nm ( Fig. 6c ) in CT–MB–ZnO–Ag was obtained after the input energy exceeded the threshold value. When the input pump intensity exceeds the threshold, the bandwidth of the central peak becomes narrowed, which signifies the occurrence of random lasing. Furthermore, with increasing the number density of ZnO and Ag NPs, the value of the bandwidth is reduced significantly due to enriched multiple scattering. The normalized output characteristics of the binary random lasing system, shown in Fig. 6d , have been significantly affected due to the change in the mixing ratio of the donor and the acceptor. The central wavelength peaks of the emission have shifted positions, indicating that the ET between CT and MB dyes caused switching of the lasing emission by ∼30 nm. The output emission spectra of the binary system were found to be tunable by adjusting the addition of different concentrations of Ag NPs, as shown in Fig. 7a . The normalized emission spectra, as shown in Fig. 7b , clearly show reduction of the lasing threshold from 107 to 25 W cm −2 , and the threshold value decreased by ∼76% after addition of Ag NPs in the presence of ZnO NPs ( n ZnO = 20 × 10 12 ml −1 ) in the binary system. Fig. 7 (a) Scatterer-dependent ASE/lasing spectra of the films; average results in the formation of sharp narrow peaks. (b) The comparison between the effects of injection of Ag NPs on the value of threshold. (c) Q -factor as a function of different A/D ratio at the same scatterer concentration. (d) Q -factor as a function of concentration of Ag NPs at ∼692.4 nm. The maximum value of the electric field is located on the surface edges of the Ag NPs. 7,8,28 Therefore, we believe that this experiment clearly demonstrates that it is possible to achieve low threshold and efficient random lasing by engineering the plasmonic NPs in organic semiconductor thin films. The quality factor ( Q -factor) is another important parameter and has been calculated using eqn (4) , 4 Q = λ 0 /Δ λ , where λ 0 is the central peak wavelength and Δ λ is the mode bandwidth. The value of the Q -factor was calculated by fitting the central mode of the emission spectra. In addition, the Q -factor is inversely proportional to the energy loss rate of a mode and is a signature of the lasing threshold for a random system. 37 Fig. 7c shows that, as the A/D ratio changed, the value of the Q -factor changed from 627 to 1024. Fig. 7d shows the variation in Q -factor as a function of Ag NP concentration, and it was found that Q = 1081 is the best value for the highest concentration of Ag NPs. This indicates that the presence of both ZnO and Ag NPs has significantly improved the laser efficiency."
} | 7,440 |
35527853 | PMC9069711 | pmc | 9,752 | {
"abstract": "Memristors, which feature small sizes, fast speeds, low power, CMOS compatibility and nonvolatile modulation of device resistance, are promising candidates for next-generation data storage and in-memory computing paradigms. Compared to the binary logics enabled by memristor devices, ternary logics with larger information-carrying capacity can provide higher computation efficiency with simple operation schemes, reduced circuit complexity and smaller chip areas. In this study, we report the fabrication of memristor devices based on nano-columnar crystalline ZnO thin films; they show symmetric and reliable multi-level resistive switching characteristics over three hundred cycles, which benefits the implementation of univariate ternary logic operations. Experimental results demonstrate that a three-valued logic complete set can be realized by the univariate operations of the present ZnO memristor device, and a ternary multiplier unit circuit is designed for potential applications. The present methodology can be beneficial for constructing future high-performance computation architectures.",
"conclusion": "4. Conclusion We produced a bipolar three-state memristor device with columnar nanocrystalline zinc oxide as the switching layer to obtain symmetric resistive switching characteristics and proposed a simple approach to implement ternary logics. Through univariate operation in no more than three steps of initializing and writing(s), literal AND and OR operations can be achieved with a single device to form a functional complete three-valued logic set. Based on this, four memristors were used to design a three-value multiplier unit. In addition to the in-memory computing capabilities, the higher order computation scheme with the present ternary routes may further enhance the efficiency of in-memory computing with reduced wire connections and lower chip areas. By including materials with high dielectric constants or optimizing the thickness and microstructure of the switching matrix, the device current can be further lowered to enhance the energy efficiency of in-memory computing with resistive switching memristors.",
"introduction": "1. Introduction The foreseeable end of Moore's law in the near future and the von Neumann communication bottleneck impose urgent demands on the launching of next-generation electronic devices and new computation paradigms that can enhance the running efficiency of modern computer systems. 1 Resistive switching memristors, with their fast operation speed, low-power potential, excellent scalability and integrativity, and capability of executing memory and logic operations through reversible modulation of device resistance under an electric field, 2–4 are considered as promising candidates for in-memory computing techniques when performing data-intensive tasks in the big data and artificial intelligence era. 5–7 After the first demonstration of memristive logics through Materials Implication (IMP) by the HP Laboratory in 2010, 3 numerous efforts have been devoted towards developing methods and circuits for the implementation of basic NAND, NOR and INV gates worldwide. 8–11 Kvatinsky, Lu and Choi proposed the concept of Memristor-Aided Logic (MAGIC) to implement all 16 Boolean logic operations, 12–14 whereas Waser adopted the sequential logic idea, in which the same target could be achieved with a single memristor device in no more than 3 steps. 15 Recently, You, Li and Gao have further extended sequential logics to non-symmetric, complementary and unipolar devices, 16–18 again suggesting that memristors offer a alternative yet simple strategy for in-memory computing applications. Compared with traditional binary systems, multi-value digital circuits not only may increase the information processing capability of the computing systems significantly, but may also help obtain simple architectures with better anti-interference ability. 19 Many practical events exhibit ternary characteristics, such as the operating state of an automobile (forward, reverse, stop) and the three primary colors of pixels in display panels, wherein the use of a three-value logic unit to control the input and output signals may enhance the performance of the system. This is especially true when millions of pixels are integrated in a large-area display panel because the total number of the driving device units involved will be reduced significantly. Generally, implementing ternary logic through a memristor not only requires the device to demonstrate reliable three-level resistive switching behavior between the high resistance state (HRS), intermediate state (MRS) and low resistance state (LRS) but also show equal amplitudes of the set and reset voltages during the HRS/MRS and MRS/LRS transitions. However, due to the uncontrolled migration of the ionic species inside the oxide switching matrix and the consequent random evolution of the conductive filaments, memristor devices usually show fluctuation in their programming voltages and device resistances. Due to this concern, efforts should be devoted to optimizing the chemical compositions and microstructures of the resistive switching materials and devices. Considering that zinc oxide nanofilms usually grow into columnar nanocrystals, pseudo-straight conductive filaments may be formed along the vertically aligned grain boundaries. The elimination of branch-structured conductive filament formation and suppression of their stochastic evolution can result in more controllable and stable switching performance of the device. In this letter, columnar nanocrystalline structured zinc oxide thin films and memristor devices exhibiting symmetric and reliable three-state resistive switching characteristics are used to implement univariate ternary logic operations for the first time. Taking the literal logics of F 2 , F 6 and F 18 as an example, all 27 possible single-variable ternary operations can be realized with a single device in no more than three steps. Together with AND and OR operations, a functional complete set of ternary logics has been established to construct a three-value multiplier. Beyond the advantages of in situ calculation and data storage towards in-memory computing applications, the selection of the ternary literal logics F 2 , F 6 and F 18 also allows a simpler function expression and circuit architecture, with smaller numbers of required memristor devices for the construction of multiplier units.",
"discussion": "3. Results and discussion Symmetric three-level resistive switching characteristics with comparable set/reset voltages and similar device resistances in both positive and negative polarities are essential prerequisites for the physical implementation of univariate ternary logic operation in memristors. However, based on the well-developed filamentary conduction theory, conductive filaments (CFs) with dendritic structures and uncontrolled numbers are usually formed in resistive switching devices through random mobile ion migration and solid-state redox reactions along the grain boundaries of polycrystalline oxide films. 20,21 The stochastic evolution of these CFs during subsequent annihilation and regeneration will lead to severe fluctuations of the programming voltages and device resistances, as well as deterioration of the device retention and endurance characteristics; 22 this hinders the direct application of memristors. In order to avoid reliability and stability issues, straight or pseudo-straight filaments that can suppress the random disconnection and reconnection of the branched CFs occurring at different spots during consecutive operations are greatly desired. Achieving these targets may require optimization of the compositions of the resistive switching materials, microstructures and AND/OR operating schemes of the devices. 23–25 Regarding these concerns, zinc oxide (ZnO) is considered to be a promising candidate for memristors due to its simple stoichiometry, facile fabrication, and good compatibility with the CMOS platform, as well as its tunable resistive switching characteristics via doping and microstructure manipulation. 26–32 In particular, its columnar crystalline structure with vertical grain boundaries along the direction of growth may provide a cut-through pathway for oxygen anion or oxygen vacancy migration 33–36 and facilitate the formation of pseudo-straight conductive filaments across the switching layer ( Fig. 1a–c ). The orderly packed ZnO columnar grains with nearly perfect crystalline microstructures around the as-formed CFs would further limit the radial in-diffusion of the mobile oxygen species from the surrounding matrix to neutralize the metallic Zn or ZnO 1− x suboxide-based filaments. As such, more stable and reliable resistive switching performance can be expected for multivalue in-memory computing applications. 24,37 Fig. 1 (a) Schematic of the formation of pseudo-straight conductive filaments in Pt/ZnO/Pt resistive switching memristor devices with vertical grain boundaries. (b) XRD patterns of the Pt-coated substrate (blue) and the ZnO nanofilm grown on it (red). (c) TEM image, (d) HRTEM image and (e) zoom-in view of the lattice fringes and fast Fourier transformed images of the as-fabricated Pt/ZnO/Pt device showing columnar ZnO nanocrystals. Based on this idea, we fabricated a Pt/ZnO/Pt structured device on a commercially available SiO 2 /Si substrate by magnetron sputtering as described above in the Experimental Methods section. The X-ray diffractive pattern and TEM images indicate that the ZnO nanofilm is (002)-textured and grew into straight columnar microcrystals ( Fig. 1b and c ). The thicknesses of the as-prepared ZnO nanofilms are ≈30 nm. As marked by the white dashed line in the HRTEM image in Fig. 1d , the vertical grain boundaries propagating along the out-of-plane direction can be clearly identified from the surrounding oxide columnar crystals. On one side of the boundary (region a), the ZnO nanocrystal shows a uniform lattice fringe of (002) planes with a d -spacing of 0.260 nm (upper panels of Fig. 1e ), indicating that the particular column has a majority phase of hexagonal wurtzite structure. The corresponding fast Fourier transformed micrograph also verifies this claim. On the other side (region b), although the lattice fringe shows a smaller d -space of 0.247 nm, which indicates observation of the (101) crystal planes (lower panel of Fig. 1e ), the fast Fourier transformed micrograph reveals that the crystalline structure of this nano-column is identical to that of region a except for the different grain orientation. Therefore, it can be confirmed that with the present sputtering setups, zinc oxide nanofilms with a hexagonal wurtzite column structure that favors the formation of pseudo-straight conductive filaments can be obtained as expected. The current–voltage ( I – V ) curve of the Pt/ZnO/Pt device is shown in Fig. 2a . Three resistive states that are stable and accessible can be obtained by controlling the limiting current during the set process and the cut-off voltage during the reset process. During the set process, the device can be switched from a high resistance state (HRS, 2.5 kΩ to 5.0 kΩ) to a middle resistance state (MRS, 200 Ω to 600 Ω) by sweeping the voltage (applied to TE) from 0 V to 0.8 V with a limiting current of 1 mA (blue curve, sweep 1). Although the device current is limited by the compliance preset, continuous migration of the oxygen species can lead to overgrowth of the conductive filaments, and the device resistance is smaller than the nominal value determined by the I – V curve. 38 As such, in sweep 2, the device current (pink curve) departs significantly from the previous level and transits from MRS to a low resistance state (LRS, 30 Ω to 80 Ω) at ∼0.5 V with an increased compliance current of 10 mA. Upon reversing the voltage polarity in the subsequent reset process, sweeping from 0 V to −0.8 V and −1.6 V can reprogram the device resistance state back to the MRS and HRS, respectively (sweeps 3 and 4). It is noteworthy that the present Pt/ZnO/Pt device shows gradual rather than abrupt transitions during the reset processes, which benefits the selection of proper programming voltages to maintain the operation symmetry for logic algorithms. Herein, 0.7 V ( V th1 ), 1.4 V ( V th2 ), −0.7 V (− V th1 ) and −1.4 V (− V th2 ) were employed as the threshold voltages for the device to switch between HRS, MRS, and LRS in subsequent experiments. The switching ratios of both the HRS/MRS and MRS/LRS transitions are close to 10, which provides a good distinction window for the subsequent logic output identification. As shown in Fig. 2b , three-state switching can also be achieved with pulse mode operation, where the black, dashed and red lines represent the input voltage pulses, immediate responding currents and device currents read at 0.2 V, respectively. All these states can be repeatedly programmed and accessed ( Fig. 2c ) and can be maintained for at least 10 4 seconds at room temperature ( Fig. 2d ). The cycle-to-cycle and device-to-device variations of all the programming voltages and HRS/MRS/LRS resistances are less than 7%, which indicates the potential capability of the present device for practical applications. In this work, the pulse voltages applied to either T1 or T2 serve as the univariate input signals, while the value of V T1 − V T2 determines the change of the device resistance in the logic operation. We define V 0 = 0 V, V 1 = 0.8 V, and V 2 = 1.6 V as logic inputs “0”, “1”, and “2” and the high, intermediate and low resistances as the logic outputs “0”, “1”, and “2”, respectively. The output logic (final resistance) state of the memristor is stored directly in the same device and can be read out by an additional independent read step with a small voltage pulse of 0.2 V. Fig. 2 (a) DC current–voltage characteristics and (b) pulse mode response of the Pt/ZnO/Pt memristor showing three-state switching behavior. (c) and (d) show the room-temperature endurance and retention performance of the device, respectively. Generally, univariate ternary logic consists of 27 functions ( f ( x ) ∈ {0, 1, 2}) and can be classified into several groups. 39 Based on the above definitions, all 27 of these operations can be achieved in no more than 3 sequential steps of initializing and writing(s) with a single memristor (Tables S1 and S2 † ). In practical applications, we only need to select a combination of functions that can form a complete set of three-valued univariate functions ( e.g. { f 2, f 6, f 18}, { f 21, f 9, f 18} and { f 21, f 2, f 8}). With the aid of AND and OR operations, certain groups of the univariate functions can be used to form a three-valued functional complete set. When implementing the same function, there are certain differences in the arithmetic complexity of different univariate function combinations. Due to the simple function expression and circuit architecture for the three-valued multiplier, we demonstrate the implementation of literal logics of F 2 , F 6 and F 18 as an example. As shown in the truth table of Fig. 3a , upon fixing the initial logic state of the device and one of the terminal voltage inputs, one more step of univariate writing to the other terminal can implement literal logic operations. Herein, the variable q takes the values “0”, “1” or “2”; V base is defined as 0.2 V, and V th2 is defined as 1.4 V. Fig. 3 (a) Truth table and (b–d) experimental demonstration of the F 2 , F 18 and F 6 literal operations, showing the equivalent voltages and resistances of the memristor. As a proof-of-concept, we show the experimental implementation of the literal logic in Fig. 3b–d . For logic F 2 , the ZnO memristor is initially programmed to logic “0” with a resistance of 2.5 kΩ to 5.0 kΩ, and the T2 terminal is fixed as V base ( Fig. 3b ). When voltage pulses with amplitudes of 0 V (logic “0”), 0.8 V (logic “1”) and 1.6 V (logic “1”) are applied to the T1 terminal, respectively, the final resistances of the device are recorded as 3.5 kΩ (logic output “0”), 3.6 kΩ (logic output “0”) and 48 Ω (logic output “2”). Consistent with the results summarized in the truth table, logic function F 2 is thus achieved with a two-step operation (initial = “0”, T1 = q , T2 = V base ). Logic F 18 can be realized similarly by fixing the initial logic state of the memristor as “0” and the T1 terminal as V th2 and applying writing voltage variables q to T2. To achieve logic F 6 , one more writing step is necessary: the memristor is first initialized to logic “2”; then, T2 is fixed as V th2 while T1 is written with the voltage variable q ; finally, T1 is fixed as V base , and T2 is written with the voltage variable q . As such, F 6 is implemented through a three-step operation. To form the functional complete logic set, we demonstrate the truth table and operation method of the AND and OR operations in Fig. 4 . In the AND operation, after the device is initialized to logic “0”, input p is first written at T1 while T2 is grounded; then, input q is written into T1, and T2 is fixed at V 2 ( Fig. 4a ). The actual equivalent voltages ( V T1 − V T2 ) applied to the memristor and the corresponding resistance states during the p / q input process are sequentially shown in Fig. 4c , confirming the realization of the AND operation in the present ternary scheme. Similarly, Fig. 4b provides the truth table and operation method for OR operation, and Fig. 4d shows the actual equivalent voltages applied to the memristor and the changes in device resistance during execution. Fig. 4 (a and b) Truth table and (c and d) experimental demonstration of the AND and OR operations showing the equivalent voltages and resistances of the memristor. Based on the functional complete logic set of the literal logics of F 2 , F 6 and F 18 and the AND and OR operators, a simple three-valued multiplier circuit was designed with four ZnO-based memristors ( Fig. 5a ). Herein, the memristors M 1 , M 2 , and M 3 are responsible for multiplication, while M 4 is responsible for the bit-carry operation. The multiplicand and multiplier are defined as logic inputs A and B , respectively. Note that the logic state of the HRS/LRS device will not change even when continuous negative/positive voltages are applied to the ZnO memristor. We used this characteristic to stop M 2 and M 3 from working when the multiplicand input A = 0; thus, only M 1 was functional. Similarly, when the A inputs are “1” and “2”, the working devices are M 2 and M 3 , respectively. In other words, the M i ( i = 1, 2, 3) device is responsible for the multiplication of the multiplicand A = “ i − 1”. The ternary multiplier produces a carry output only when both the multiplicand A and the multiplier B are equal to 2; therefore, it is only necessary to store the carry output value with the M 4 device in the M 3 branch. Because the carry signal in the multi-valued logic is a binary signal, e.g. the product output at C is a binary digit, the carry operation is only performed when the output of M 4 is logic “2”. Otherwise, it is not carried. After the calculation is completed, the current value read by the small voltage can be used as the output result. The truth table and operation method of the full multiplier (FM) are shown in Fig. 5b . Due to the two-step implementation of the univariate function, bimodal pulse input is used during the operation. Fig. 5c shows the experimental FM operation, wherein the red and blue lines represent the operating pulse voltage and current response on the memristor. The four blue current curves are the current responses of M 1 to M 4 . The gray area ( M 1 to M 3 ) represents the multiplier result value output, and the yellow area ( M 4 ) is the carry output. Fig. 5 (a) Circuit structure diagram of the three-valued multiplier unit based on ZnO memristors. (b) The truth table, operation method and (c) experimental demonstration of the full multiplier operation."
} | 5,037 |
33657378 | PMC8121099 | pmc | 9,753 | {
"abstract": "SUMMARY Harnessing the microbiota for beneficial outcomes is limited by our poor understanding of the constituent bacteria, as the functions of most of their genes are unknown. Here, we measure the growth of a barcoded transposon mutant library of the gut commensal Bacteroides thetaiotaomicron on 48 carbon sources, in the presence of 56 stress-inducing compounds, and during mono-colonization of gnotobiotic mice. We identify 516 genes with a specific phenotype under only one or a few conditions, enabling informed predictions of gene function. For example, we identify a glycoside hydrolase important for growth on type I rhamnogalacturonan, a DUF4861 protein for glycosaminoglycan utilization, a 3-keto-glucoside hydrolase for disaccharide utilization, and a tripartite multidrug resistance system specifically for bile salt tolerance. Furthermore, we show that B. thetaiotaomicron uses alternative enzymes for synthesizing nitrogen-containing metabolic precursors based on ammonium availability and that these enzymes are used differentially in vivo in a diet-dependent manner.",
"introduction": "INTRODUCTION The human gut microbiota plays important roles in health and disease ( Cho and Blaser, 2012 ; Zitvogel et al., 2017 ). It is anticipated that the human gut microbiota can be manipulated to treat a number of diseases ( Guinane and Cotter, 2013 ). However, these efforts will be limited without a greater understanding of the functional potential of the bacteria that comprise the human microbiota. A primary bottleneck is that approximately half of protein-coding genes do not yet have a known molecular function ( Heintz-Buschart and Wilmes, 2018 ). One of the most well-studied and prevalent members of the human gut microbiota is the anaerobe Bacteroides thetaiotaomicron VPI-5482 ( Wexler and Goodman, 2017 ). Pioneering work revealed the broad range of complex polysaccharides and simple carbohydrates that B. thetaiotaomicron can degrade and ferment in the gut ( Kotarski and Salyers, 1984 ; Salyers and O’Brien, 1980 ; Salyers et al., 1977 ). Genome analysis found that many carbon degradation systems are encoded within polysaccharide utilization loci (PULs) ( Xu et al., 2003 ), which typically contain a cluster of genes involved in the regulation, transport, and catabolism of polysaccharides ( Bjursell et al., 2006 ). The most well-studied PUL in B. thetaiotaomicron is the starch utilization system (Sus), encoded by susRABCDEFG ( Martens et al., 2009 ). SusR is the sensor/regulator, SusCDEF are membrane proteins responsible for starch binding and transport, and SusABG are hydrolytic enzymes. With the minimal requirement of a susCD gene pair, computational analyses have identified >80 predicted PULs in the B. thetaiotaomicron genome ( Martens et al., 2008 ) but the majority are experimentally uncharacterized. Although traditional single-gene genetics and enzymology are useful for elucidating protein function, such approaches are often time-consuming and laborious. Thus, large-scale functional-genetic methods are attractive for the characterization of genes of unknown function ( Gray et al., 2015 ). Methods based on transposon-site sequencing (TnSeq) are useful for assaying the importance of many genes in parallel under multiple conditions ( van Opijnen and Camilli, 2013 ). For example, transposon insertion sequencing (INSeq) applied to B. thetaiotaomicron revealed genes required for colonizing mice ( Goodman et al., 2009 ). Subsequent application of INSeq to multiple Bacteroides species identified species-specific genes important in vivo ( Wu et al., 2015 ). The development of large, multi-condition gene-phenotype datasets has proven useful for inferring gene function in a broad range of organisms ( Deutschbauer et al., 2011 ; Hillenmeyer et al., 2010 ; Nichols et al., 2011 ), although this approach has not been applied to gut commensals. Using a barcoded variant of TnSeq (RB-TnSeq) ( Wetmore et al., 2015 ), we performed hundreds of in vitro genome-wide fitness assays in B. thetaiotaomicron , including in the presence of simple sugars, complex polysaccharides, and antibiotics. We further profiled fitness during mono-colonization of germ-free mice. This rich dataset provides experimental evidence for many predicted gene functions in B. thetaiotaomicron and links genes that previously lacked informative annotations to specific processes including polysaccharide degradation, disaccharide catabolism, and bile salt tolerance. Our data also revealed that alternative enzymes are used to synthesize nitrogen-containing precursor metabolites in response to diet-dependent availability of ammonium in the gut.",
"discussion": "DISCUSSION A small fraction of the gene content of the human microbiome has been experimentally characterized, and there are large knowledge gaps in our molecular understanding of these health-relevant bacteria. To address this knowledge gap, we performed hundreds of genome-wide fitness experiments in B. thetaiotaomicron and used the data to reannotate the functions of 40 proteins ( Table S5 ). Nineteen of these proteins were annotated as “hypothetical protein” in RefSeq (as of April 2019), and many of the other proteins had vague annotations such as “MFS transporter.” These reannotations are also available in the Fitness Browser ( Price et al., 2018 ) and PaperBLAST ( Price and Arkin, 2017 ). Our large dataset contains phenotypes for hundreds of additional genes and should be a valuable resource for gene function inference and hypothesis generation. To facilitate these future studies, the B. thetaiotaomicron fitness data are publicly available for comparative analyses in the Fitness Browser at https://fit.genomics.lbl.gov . Much of the research to date on B. thetaiotaomicron has focused on polysaccharide degradation by PULs. Although our analysis was able to link 20 PULs to carbon sources, these findings represent <25% of the predicted PULs in the genome. Why so few? First, B. thetaiotaomicron may contain two or more PULs that act on the same substrate, and this redundancy would mask the impact of any single-gene mutation. Second, the PUL component(s) may perform its activity extracellularly, such that other mutants in the pooled library can complement any growth deficiency in trans . In addition to assaying mutants individually, approaches for performing genome-wide fitness assays within droplets hold the potential for eliminating complementation by other mutants ( Thibault et al., 2019 ). Third, some PULs may not be expressed under our growth conditions or are involved in the breakdown of polysaccharides that we did not profile. For example, transcriptional profiling connected some PULs with N-linked glycans ( Briliūtė et al., 2019 ; Cao et al., 2014 ). Some of these substrates may be activated only within the host; interestingly, we identified a phenotype for components of PUL27 within mice but not in any in vitro assays. Fourth, some PULs may have evolved to consume simpler sugars and oligosaccharides. For example, we identified a PUL (BT3567–BT3569) that was important only for fitness on the disaccharide laminaribiose, suggesting that chemical-genetic profiling with additional simple carbon sources may reveal functions for some PULs. Lastly, the definition of a PUL is very minimal and only requires a SusCD gene pair. Some of these minimal PULs may have other cellular roles. For instance, we showed that a two-gene PUL (BT1439–BT1440) confers susceptibility to vancomycin in BHIS ( Figure 6D ). We showed that growth on trehalose and other disaccharides required a 3-keto-disaccharide hydrolase (BT2157). This enzyme has a predicted signal peptide ( Almagro Armenteros et al., 2019 ), implying that these disaccharides are oxidized in the periplasm. However, B. thetaiotaomicron does not encode the periplasmic 3-ketoglycoside dehydrogenases LacABC or ThuAB ( Ampomah et al., 2013 ; Arellano et al., 2010 ; Miyazaki et al., 2018 ). Moreover, B. thetaiotaomicron has a limited electron transport chain that ends at menaquinol:fumarate oxidoreductase ( Fischbach and Sonnenburg, 2011 ), yielding succinate as the reduced end product, which probably precludes the operation of cytochrome c -dependent dehydrogenases such as LacABC or ThuAB. Instead, oxidation to a 3-keto-disaccharide is probably performed by BT2158, which was important for growth on trehalose and several other disaccharides but not for growth on 3-keto-trehalose ( Figure 4A ). BT2158 has a putative Tat export signal ( Almagro Armenteros et al., 2019 ) and is distantly related (Pfam: PF01408) to periplasmic glucose-fructose oxidoreductase (Gfo). Gfo has a tightly bound NADP cofactor that is exported together with the folded protein by the Tat system ( Halbig et al., 1999 ), and it oxidizes glucose to gluconolactone while reducing fructose to sorbitol ( Kingston et al., 1996 ). Hence, we propose that BT2158 uses a tightly bound NAD(P) cofactor to oxidize disaccharides to 3-keto-disaccharides while reducing another as yet unidentified sugar. Integrating data from gnotobiotic mouse models and our chemical-genetic screen, we presented evidence that B. thetaiotaomicron remodels its biosynthetic pathways to directly incorporate ammonium into nitrogen-rich compounds when ammonium is plentiful and uses alternative nitrogen sources when ammonium is scarce. Furthermore, we showed that this capacity is likely an adaptation to diet-dependent ammonium fluctuations in the colon. Interestingly, the genes encoding the ammonium-independent enzymes are all located in the high-affinity ammonium (HAA) locus. Expression of genes in the HAA locus is induced under low-ammonium conditions (Iakiviak, 2017), providing a simple regulatory mechanism for the transition between ammonium-dependent and -independent pathways. We found that the HAA locus carries the genes for a canonical glutamine-dependent carbamoyl phosphate synthetase (CPS). Meanwhile, an orphan CPS synthetase subunit (CarB2) is critical for growth in high-ammonium environments. The lack of support for any glutaminase partner for CarB2 in our dataset suggests that CarB2 functions as an ammonium-dependent CPS ( Figure 7D ). Prokaryotic ammonium-dependent CPSs have been described previously, but these proteins are restricted to Archaea ( Legrain et al., 1995 ; Popa et al., 2012 ), leading to a long-standing hypothesis that eubacteria only encode glutamine-dependent CPSs. Further experimental confirmation that CarB2 is an ammonium-dependent CPS will be an important future step in filling this knowledge gap. Our approach can be applied generally to uncover gene functions in the human microbiome. In particular, barcoding of mutant libraries enables a rapid assessment of gene importance across many conditions at low cost ( Price et al., 2018 ). Nevertheless, challenges still need to be overcome, including the accelerated development of genetic tools for non-model species in the human microbiota ( Liu and Deutschbauer, 2018 ; Peters et al., 2019 ) and of scalable phenotypic assays that more accurately reflect the natural ecology of these species. In addition, conservation of a phenotype in multiple species is a powerful indicator of gene function ( Price et al., 2018 ), and the generation of similar gene-phenotype maps in related bacteria will expand the scope of our analysis."
} | 2,846 |
27435659 | PMC4951719 | pmc | 9,755 | {
"abstract": "The global decline of reef-building corals is understood to be due to a combination of local and global stressors. However, many reef scientists assume that local factors predominate and that isolated reefs, far from human activities, are generally healthier and more resilient. Here we show that coral reef degradation is not correlated with human population density. This suggests that local factors such as fishing and pollution are having minimal effects or that their impacts are masked by global drivers such as ocean warming. Our results also suggest that the effects of local and global stressors are antagonistic, rather than synergistic as widely assumed. These findings indicate that local management alone cannot restore coral populations or increase the resilience of reefs to large-scale impacts. They also highlight the truly global reach of anthropogenic warming and the immediate need for drastic and sustained cuts in carbon emissions.",
"discussion": "Results and Discussion Our results suggest that coral reef degradation is not correlated with human population density ( Table 1 , Fig. 2 ) and thus any impacts of local stressors were undetectable at a geographic scale. Most reefs are in close proximity to high human population densities, are exposed to numerous potential local stressors, and are directly exploited by people 33 . Thus, the absence of a signal of local impacts could be due either to their weak effects sizes or to an antagonistic interaction with global stressors. Although human population density was statistically significant in both global models ( Table 1 ), it explained <1% of the among-reef variance in coral and macroalgal cover. This is not surprising, since our very large sample size enabled us to detect statistically significant but weak and ecologically meaningless relationships. This lack of a relationship was consistent within every region and subregion for which we had sufficient data (Tables S1 and S2, Figs. S2 and S3). There is broad agreement that coral reefs in most regions continue to lose coral and generally degrade 4 5 . Yet there is ongoing debate about the proximate and ultimate causes of coral loss, particularly about the relative role of local and global factors 11 . There is a growing hope among coral reef scientists that local impacts are the dominant drivers of reef degradation and that these factors can be managed 41 . If true proximate threats could then be mitigated on site by local communities 40 . It is also assumed that local and global impacts are at least additive and likely synergistic 40 42 . This supposition underlies the widespread argument that human-dominated reefs can be made more resilient to global stressors (particularly warming) via local conservation and management 40 42 . Our results do not support either assumption. This is the first global test of the hypothesis that isolated reefs are less degraded and have higher coral cover and less macroalgae cover. Most past tests of this hypothesis have relied on very small samples (i.e., <5), often based on non-random site selection. For example, Sandin et al . 36 compared coral cover (and other community attributes) of coral reefs adjacent to four of the Northern Line Islands in the central Pacific that differed greatly in human population density (range 0–109 people/km of reef). They quantified earlier observations that coral cover was substantially greater adjacent to the two atoll islands with the fewest people (e.g., Kingman and Palmyra). However, our results indicate such patterns are not general: although some isolated reefs have exceptionally high coral cover, most do not ( Fig. 3 ). In fact very isolated reefs with no human inhabitants within 50 km display a large range in coral cover and macroalgae cover, with a typical mean and distribution ( Fig. 3 and S4). Our results are concordant with Smith et al . 37 which tested the generality of the findings of Sandin et al . 36 by surveying reefs surrounding 56 central Pacific islands. Their results indicated that coral and macroalgal cover were unrelated to the presence/absence of human inhabitants 37 . Ocean warming is the most likely explanation for coral loss on isolated reefs. Anthropogenic warming due to greenhouse gas emissions causes coral mortality and population declines via coral bleaching and infectious diseases 21 23 43 . Warming and subsequent mass bleaching and coral mortality have been documented at countless isolated reefs, far from any local human influence in remote locations including Kirabati, Phoenix Islands, the Bahamas, the Chagos Archipelago, the outer Great Barrier Reef, and the northwest Hawaiian Islands 11 24 44 45 . A striking example is the mass-bleaching of hundreds of kilometers of the northern and central Great Barrier Reef– one of the world’s most isolated and well-protected reefs – earlier this year. Likewise, regional disease outbreaks, a primary cause of coral losses in regions including the Caribbean, have been linked to ocean warming 21 43 . Many scientists have noted the lack of any obvious association of coral disease outbreaks and mass bleaching episodes with proximity to people and urban centers 11 46 . Many coral reef scientists assume that observed increases in macroalgae, though less common and far less severe than previously assumed 1 12 , are due to local impacts including generalized reduction of grazing pressure caused by the loss of key herbivores through disease and overfishing and by localized nutrient pollution 9 10 12 . This expectation is based on: 1) the observation that reefs with a greater abundance and diversity of herbivores tend to have less macroalgae 32 , and 2) the results of numerous small-scale experiments that increase nutrient concentration or exclude fishes generally find strong top-down and bottom-up control of macroalgae 47 48 . However, our results surprisingly indicate that macroalgal cover is not correlated with local human population density ( Table 1 , Fig. 2 ). Across 56 islands in the central Pacific, Smith et al . 37 also found that macroalgal cover was unrelated to human presence and that reefs adjacent to densely populated islands such as Oahu, Hawaii had less macroalgae than many remote reefs far from human activities. The causes of this unexpected global pattern are unclear. Perhaps increases in macroalgae are also caused by the global stressors 11 that reduce coral populations and thus indirectly increase resource availability for benthic seaweeds and other organisms such as sponges and soft corals 2 49 . In this scenario, when and where herbivory is high relative to open space and benthic primary production, then macroalgal cover is low. Whereas when and where herbivory is low relative to open space, then macroalgal cover is high unless storms or other factors such as temperature extremes remove the seaweeds. This hypothesis is concordant with our results and the common observation that macroalgae often rapidly occupy available space directly following coral loss. If true, this finding has important management implications: fishing bans and reductions in coastal pollution, though desirable 11 , might not meaningfully reduce macroalgal abundance or restore corals if the ultimate drivers are larger-scale and beyond the control of local managers 50 . To be effective such local mitigation would need to be paired with reduction of the global stressors that have apparently enabled macroalgae to increase on some reefs. Alternatively, it is possible that predators, which are more abundant on isolated reefs 3 31 32 , suppress herbivores, either via direct consumption or behavioral modification that reduces foraging time, indirectly facilitating macroalgae 51 . Our results also suggest that the effects of global and local stressors may be antagonistic and not additive or synergistic as widely assumed 40 42 . If the interaction were additive or multiplicative, coral populations exposed to both impact categories (i.e., those with high human population densities and ocean warming) would have lower coral cover. Antagonism, rather than synergism, could be due to co-tolerance of species to local and global stressors. If true, local stressors would reduce the abundance of species sensitive to global stressors, making locally disturbed communities less sensitive to large-scale factors like ocean warming 52 . This interpretation is consistent with numerous local, regional, and global studies indicating that local protection (e.g., the implementation of marine reserves), does not measurably lessen the impacts of ocean warming on coral populations 25 44 50 53 54 . In conclusion, our findings contradict several widespread assumptions about the relative and interactive effects of local and global stressors causing coral losses around the world. We found that coral and macroalgal cover were not correlated with isolation from local anthropogenic stressors. Remote locations such as isolated reefs are often mythologized as pristine and barely impacted windows into the pre-human state of ecosystems 29 . In terms of fishes and other wildlife they can be, as reef fish biomass is clearly negatively correlated with human population density 3 31 32 . But given the global reach of many other aspects of the human footprint 55 , perhaps it should not be surprising that coral losses on remote reefs match those on disturbed reefs adjacent to densely populated islands. The results of this and numerous other studies indicate that local management is unlikely to meaningfully increase the “resilience” of coral populations to warming, bleaching, disease, acidification, and other global stressors 25 44 50 54 . In fact, due to the apparent antagonistic relationship between local and global stressors, locally impacted reefs might be less sensitive to global stressors than isolated reefs 52 . Thus removing local stressors could counterintuitively increase sensitivity to warming of other large-scale disturbances 52 . Although our analysis did not detect a synergistic effect of localized human impacts, we believe there is adequate evidence in many locations to justify continued mitigation of small-scale stressors like overfishing and pollution. Given the continued global loss of reef-building corals and the results of this and other analyses indicating the primacy of large-scale stressors like warming 25 56 57 , the immediate, drastic reduction of greenhouse gas emissions is essential to restoring the health and functioning of coral reefs."
} | 2,633 |
22913372 | PMC3542253 | pmc | 9,756 | {
"abstract": "Background Pseudomonas putida KT2440 is able to synthesize large amounts of medium-chain-length polyhydroxyalkanoates (mcl-PHAs). To reduce the substrate cost, which represents nearly 50% of the total PHA production cost, xylose, a hemicellulose derivate, was tested as the growth carbon source in an engineered P. putida KT2440 strain. Results The genes encoding xylose isomerase (XylA) and xylulokinase (XylB) from Escherichia coli W3110 were introduced into P. putida KT2440. The recombinant KT2440 exhibited a XylA activity of 1.47 U and a XylB activity of 0.97 U when grown on a defined medium supplemented with xylose. The cells reached a maximum specific growth rate of 0.24 h -1 and a final cell dry weight (CDW) of 2.5 g L -1 with a maximal yield of 0.5 g CDW g -1 xylose. Since no mcl-PHA was accumulated from xylose, mcl-PHA production can be controlled by the addition of fatty acids leading to tailor-made PHA compositions. Sequential feeding strategy was applied using xylose as the growth substrate and octanoic acid as the precursor for mcl-PHA production. In this way, up to 20% w w -1 of mcl-PHA was obtained. A yield of 0.37 g mcl-PHA per g octanoic acid was achieved under the employed conditions. Conclusions Sequential feeding of relatively cheap carbohydrates and expensive fatty acids is a practical way to achieve more cost-effective mcl-PHA production. This study is the first reported attempt to produce mcl-PHA by using xylose as the growth substrate. Further process optimizations to achieve higher cell density and higher productivity of mcl-PHA should be investigated. These scientific exercises will undoubtedly contribute to the economic feasibility of mcl-PHA production from renewable feedstock.",
"conclusion": "Conclusion Introduction of xylAB from E. coli into P. putida KT2440 was sufficient to allow the recombinant to efficiently utilize xylose as the sole carbon source. Experiments performed in bioreactors showed that XylA and XylB were active in P. putida KT2440. The recombinant did not produce mcl-PHA from xylose, thus enabled production of a tailor-made mcl-PHA of up to 20% (w w -1 ) by sequential-feeding of xylose and octanoate. A maximal yield of 0.37 g mcl-PHA g -1 octanoic acid was obtained with PHA containing mainly 3-hydroxyoctanoate monomers (87% w w -1 ). Sequential feeding of relatively cheap carbohydrates and expensive fatty acids is a practical way to achieve more cost-effective mcl-PHA production. Optimization of initiation, rate and duration of feeding should be performed to achieve a higher yield and higher productivity of mcl-PHA. Furthermore, an optimized growth conditions will undoubtedly contribute to the economic feasibility of mcl-PHA production from renewable feedstock.",
"introduction": "Introduction of pSLM1 into P. putida KT2440 The obtained plasmid pSLM1 was introduced into P. putida KT2440 by triparental mating\n[ 40 ]. E. coli HB101 (RK600)\n[ 38 ] was used as the helper strain. E. coli JM109 (pSLM1) was the donor strain and P. putida KT2440 was the acceptor strain. The P. putida KT2440 recombinants were selected on E2 medium (see below) containing 0.2% citrate and 25 μg mL -1 kanamycin. In analogy, the empty vector pVLT33 was also introduced into P. putida KT2440 as a control.",
"discussion": "Discussion Growth of KT2440 on xylose A recombinant P. putida KT2440 strain was constructed that could efficiently utilize xylose. The introduction of xylose isomerase (XylA) and xylulokinase (XylB) was essential and sufficient for the utilization of xylose and a growth rate of 0.24 h -1 was routinely obtained. Previously, it has been reported that a so called “laboratory evolution” was necessary to improve the growth rate of P. putida S12 ( xylAB ) on xylose from 0.01 h -1 to 0.35 h -1 and to obtain a yield of 0.52 g CDW per g xylose\n[ 23 ]. The laboratory evolution is an adoption process by growing the cells consecutively in a fresh medium containing the unfavorable carbon source. The “laboratory evolution” was not needed for the KT2440 recombinant to grow on xylose. This difference could be attributed to the different physiological background/metabolic fluxes of KT2440 and S12. It has been reported that in P. putida a complete pentose phosphate pathway is present\n[ 23 , 27 ] (Figure\n 4 ) as well as the key enzymes for mcl-PHA accumulation\n[ 28 ]. Our study demonstrated that the enzymes responsible for converting xylose to the entry intermediate xylulose-5-phosphate of PP pathway are missing in P. putida . By introducing the relevant enzymes XylA and XylB, P. putida KT2440 was able to utilize xylose. Figure 4 Hypothetical pathway for mcl-PHA accumulation from xylose in P. putida . Enhanced arrows: steps absent in wild-type P. putida strains; XylA: xylose isomerase; XylB: xylulokinase; PhaG: 3- hydroxyacyl-ACP:CoA transferase; PhaC: PHA polymerase. In addition, the recombinant P. putida KT2440 appeared to have an efficient xylose uptake system. Similarly, P. putida S12 carrying D-xylonate dehydratase has been reported to grow on xylose without expressing any xylose transporter\n[ 29 ]. Since pentose and hexose transporters have been shown to be promiscuous\n[ 30 ], it is possible that xylose uptake can be accomplished by glucose uptake systems in strain KT2440 ( xylAB ). Many bacteria also possess non-specific transporters. Indeed, many sugars are transported into E. coli by phosphoenolpyruvate-dependent phosphotransferase systems (PTS) like glucose, mannose, fructose, and N-acetylglucosamine\n[ 31 ]. In this study, no specific xylose transporters such as XylE or XylFGH were needed for growth of KT2440 ( xylAB ) on xylose. Thus, it is also possible that xylose entered the cell through the PTS system present in P. putida in a similar way as reported for fructose\n[ 32 ]. Xylose, after uptake into the cell, is isomerized by xylose isomerase to xylulose, which is then converted by xylulokinase to xylulose 5-phosphate. This phosphorylated derivate is then catabolized by the pentose phosphate pathway. In comparison to growth on glucose, the growth of P. putida KT2440 ( xylAB ) on xylose exhibited a similar specific growth rate of 0.24 h -1 (Figure 1). This demonstrated that the uptake and the catabolic rate of xylose by the recombinant P. putida KT2440 (pSLM1) is in the same range as that of glucose. PHA production by sequential feeding The biosynthesis of mcl-PHA is mainly studied for fluorescent pseudomonads, e.g. P. putida KT2440. Strain KT2440 is characterized by a wide metabolic and physiologic versatility and is able to accumulate mcl-PHA from glucose\n[ 33 ]. In this study, we demonstrated that mcl-PHA biosynthesis on xylose does not occur when xylA and xylB are expressed even under nitrogen limitation, perhaps because the expression of xylAB channels the metabolic flux to central metabolism such as TCA cycle for cell maintenance or/and to production of side products like acetate, rather than to PHA synthesis (Figure\n 4 ). Up to now, there has been no report on mcl-PHA production by using xylose as the growth substrate. Substrate cost make up a large proportion of the total production cost of PHA. Fatty acids are generally much more expensive than lignocellulose hydrolysates (such as xylose) and often toxic to the cells at relatively low concentrations and, for some of them, do not support fast growth rates. Xylose is in a similar price range like cane molasses and half the price of glucose\n[ 34 ], consequently, sequential-feeding strategies are a valid option to reduce the production cost\n[ 35 , 36 ]. Sequential-feeding consists of using on one hand cheap carbohydrates for achieving a large biomass and on the other hand fatty acids as mcl-PHA precursors to produce tailor-made mcl-PHAs. In this study, xylose was used for cell growth in the first step, and then octanoate was supplied to synthesize mcl-PHA in the second step under nitrogen limitation. This sequential feeding process allowed a tailor-made mcl-PHA accumulation of up to 20% (w w -1 ) under not-yet-optimized conditions. When 1.44 g L -1 octanoate was employed alone for growth and PHA production (Table\n 2 , entry C), lower PHA content (about 21% w w -1 ) was obtained than that from using both xylose and 1.44 g L -1 octanoate (Table\n 2 , entry G, about 28.7% w w -1 ), even though the growth rate and the final cell density reached in entry C were higher than those in entry G. These results suggest that xylose is not a substrate as good as octanoate for growth of KT2440, however, it can facilitate the PHA production by being a substrate for growth and allowing only octanoate to be converted to PHA. In this study, P. putida KT2440 (pSLM1) showed a biomass yield from xylose at 0.50 g g -1 , which is similar to what has been previously reported 0.52 g g -1 for P. putida S12 ( xylAB )\n[ 23 ]. Previously, Kim and co-workers used a sequential feeding strategy to maximize the PHA production in P. putida using glucose as growth substrate and then octanoic acid for PHA accumulation\n[ 37 ]. A yield of 0.4 g mcl-PHA g -1 octanoic acid was reached\n[ 37 ], similar to the yield of 0.37 g mcl-PHA g -1 octanoic acid obtained in this study by sequential feeding of xylose and octanoic acid. However, it has also been reported that the yield of mcl-PHAs from fatty acids such as nonanoic acid could achieve 0.66 to 0.69 g −1 mcl-PHA g nonanoic acid by co-feeding glucose\n[ 36 ]. Therefore, further optimization of the sequential-feeding process is needed to increase the yield of tailor-made mcl-PHAs."
} | 2,391 |
31177633 | null | s2 | 9,757 | {
"abstract": "The 3-(3-hydroxyalkanoyloxy)alkanoate (HAA) synthase RhlA is an essential enzyme involved in the biosynthesis of HAAs in Pseudomonas and Burkholderia species. RhlA modulates the aliphatic chain length in rhamnolipids, conferring distinct physicochemical properties to these biosurfactants exhibiting promising industrial and pharmaceutical value. A detailed molecular understanding of substrate specificity and catalytic performance in RhlA could offer protein engineering tools to develop designer variants involved in the synthesis of novel rhamnolipid mixtures for tailored eco-friendly products. However, current directed evolution progress remains limited due to the absence of high-throughput screening methodologies and lack of an experimentally resolved RhlA structure. In the present work, we used comparative modeling and chimeric-based approaches to perform a comprehensive semi-rational mutagenesis of RhlA from Pseudomonas aeruginosa. Our extensive RhlA mutational variants and chimeric hybrids between the Pseudomonas and Burkholderia homologs illustrate selective modulation of rhamnolipid alkyl chain length in both Pseudomonas aeruginosa and Burkholderia glumae. Our results also demonstrate the implication of a putative cap-domain motif that covers the catalytic site of the enzyme and provides substrate specificity to RhlA. This semi-rational mutant-based survey reveals promising 'hot-spots' for the modulation of RL congener patterns and potential control of enzyme activity, in addition to uncovering residue positions that modulate substrate selectivity between the Pseudomonas and Burkholderia functional homologs. DATABASE: Model data are available in the PMDB database under the accession number PM0081867."
} | 433 |
22207869 | PMC3246358 | pmc | 9,758 | {
"abstract": "Microbial heterotrophic activity was investigated in oxic sub-seafloor sediments at North Pond, a sediment pond situated at 23°N on the western flank of the Mid-Atlantic Ridge. The North Pond sediments underlie the oligotrophic North Atlantic Gyre at 4580-m water depth and cover a 7–8 million-year-old basaltic crust aquifer through which seawater flows. Discrete samples for experimentation were obtained from up to ~9 m-long gravity cores taken at 14 stations in the North Pond area. Potential respiration rates were determined in sediment slurries incubated under aerobic conditions with 14 C-acetate. Microbial heterotrophic activity, as defined by oxidation of acetate to CO 2 (with O 2 as electron acceptor), was detected in all 14 stations and all depths sampled. Potential respiration rates were generally low (<0.2 nmol of respired acetate cm −3 d −1 ) in the sediment, but indicate that microbial heterotrophic activity occurs in deep-sea, oxic, sub-seafloor sediments. Furthermore, discernable differences in activity existed between sites and within given depth profiles. At seven stations, activity was increased by several orders of magnitude at depth (up to ~12 nmol of acetate respired cm −3 d −1 ). We attempted to correlate the measures of activity with high-resolution color and element stratigraphy. Increased activities at certain depths may be correlated to variations in the sediment geology, i.e., to the presence of dark clay-rich layers, of sandy layers, or within clay-rich horizons presumably overlying basalts. This would suggest that the distribution of microbial heterotrophic activity in deeply buried sediments may be linked to specific lithologies. Nevertheless, high-resolution microbial examination at the level currently enjoyed by sedimentologists will be required to fully explore this link.",
"introduction": "Introduction The mineralization of organic matter in marine sediments is governed by microbial metabolism. In the deep subsurface (>1.5 mbsf) of marine sediments, sulfate reduction, methanogenesis, and fermentation are considered to be the main metabolic activities responsible for the degradation of organic matter to small organic acids and CO 2 (e.g., Parkes et al., 2000 ; D’hondt et al., 2002 ). However, since most sub-seafloor sediments considered in previous studies underlie productive coastal or upwelling areas, the microbial processes reflect the consequences of a high organic carbon flux to the seafloor, in which oxygen is rapidly depleted (D’hondt et al., 2009 ). Oligotrophic regions occur in the subtropical ocean gyres that represent a major part of the world’s ocean where the organic matter flux to the sediments is low, leading to deep oxygen penetration depths of tens of centimeters or more (Murray and Grundmanis, 1980 ). At the extreme, penetration depths of dissolved oxygen in the South Pacific Gyre sediments reached up to 9 m (D’hondt et al., 2009 ; Fischer et al., 2009 ). Deep penetration of oxygen in sediments of the Atlantic Ocean to ~9 meters have also been shown in sediments contained in ponded basins on the flanks of the North Mid-Atlantic Ridge (MAR), in the so-named North Pond (Cruise report MSM 11/1). North Pond is an isolated region of ponded sediment situated at ~100 km west of the rift valley of the MAR and~110 km south of the Kane fracture zone (22°46′N and 46°06′W; e.g., Hussong et al., 1979 ; Purdy et al., 1979 ). It is a large pond (~13 km N–S and ~7 km E–W) and lies below a low-productivity 4580-m water column. The sediment at North Pond can reach up to 300 m thickness and overlies a young basaltic active crust (7–8 Ma) through which vigorous lateral flow of cold seawater has been proposed to take place (Langseth et al., 1984 ). We investigated microbial heterotrophic activity in sediment cores recovered at North Pond. Studies of microbial life in deep-oxic sediments are rare (D’hondt et al., 2009 ), and no measurements of experimentally determined, potential respiration rates have been reported yet in sub-seafloor sediment in which oxygen is penetrating several meters deep. We used 14 C-acetate in the deep-oxic sediments from North Pond for this purpose as acetate has been proven to be well-suited to estimate potential respiration and uptake rates of organic molecules in subsurface environments (e.g., Wirsen and Jannasch, 1974 ; Phelps et al., 1989 ; Fredrickson et al., 1997 ). In the case of anoxic sediments the changes in pore water chemistry usually help to target the zones where specific types of microbial activity can be expected (i.e., sulfate–methane transition zones). At North Pond, the sampled sediments were oxic throughout, thus the sampling strategy was different. To gain an overview of the potential respiration rates, which were expected to be low and decreasing with depth at all stations, we sampled the oxic sediment with a regular spacing along the length of gravity cores obtained from North Pond. Occasionally, distinct layers, such as sandy, clay-rich, dark layers, were also sampled. The goal of the microbial heterotrophic activity measurements was to compare potential respiration rates at different stations over a small area and investigate correlations between activity profiles and geological features. We present profiles of potential microbial heterotrophic activity in deep-sea, deep-oxic sub-seafloor sediments, and examine these rates in conjunction with respect to variations in sediment lithology.",
"discussion": "Discussion North Pond sediments are oligotrophic, nonetheless, our experiments indicate that microbial heterotrophic communities continue to be active in these deeply buried sediments. The communities react immediately to the supply of acetate as substrate, as no lag phase was observed before the oxidation of acetate to carbon dioxide. In our experiments, we added labeled acetate to concentrations of 20 μmol l −1 . Growth of a specific aerobic acetotrophic (acetate-oxidizing) community can be excluded with a reasonable probability. More likely, heterotrophic communities are present and potentially active at all depths of the sediments sampled. Moreover, the range of potential activities is highly variable on both depth and lateral scales. Such heterogeneity in potential activity rates over a small area is remarkable in such an oligotrophic environment, where one would expect low activity rates throughout the cores without much variation. Conversely, nitrate and oxygen fluxes at the surface sediment – water interface appear to be similar across all sites (Cruise report MSM 11/1). Some of this variability in potential activity may be linked to the location and water depth of the sites sampled. In three cores, the activity maxima occurred near the surface, where organic matter is younger and expectedly more accessible toward microbial degradation. The location in the pond might thus influence the magnitude of the increase in activity. For example, the three stations with greater near-surface acetate turnover rates follow a crest directed toward the center of the pond. GeoB13511 is at the bottom of the slope at 4445 m water depth; GeoB13510 is a bit further north on the slope at 4448 m water depth and GeoB13512 is northern at 4200 m water depth at the top of the edge. However, these three stations were the only ones where potential activity was greatest near the surface observed in the upper core; otherwise, peaks in potential acetate turnover could be observed at various depths. While microbial cell counts and activities tend to decrease with increasing depth in the deep anaerobic sub-seafloor (Parkes et al., 1994 , 2000 ), occurrences of enhanced activity in deep anoxic sub-seafloor layers have been attributed to geochemical reaction zones, e.g., at sulfate–methane transition zones; at fluid or gas-venting sites; or due to thermally driven alteration of organic matter to form acetate or methane (Cragg et al., 1992 , 1995 ; Wellsbury et al., 1997 ; Parkes et al., 2005 ). Remarkable case of increases in sub-seafloor microbial population abundances and activities have also been observed in gas hydrate associated sediments (Cragg et al., 1995 , 1996 ; Wellsbury et al., 2000 ). On the other hand, down-core variability in microbial populations and enhanced microbial activities may be more closely related to changes in the lithology. At an open-ocean site of the Equatorial Pacific (site 1226, ODP Leg 201), prokaryotic activity was stimulated within Miocene age diatomaceous-rich layers (Parkes et al., 2005 ). At this same site, fluctuations in microbial populations have been related to depositional cycles of high organic carbon content linked to Milankovitch cycles (Aiello and Bekins, 2010 ). The stimulation of microbial activity at interfaces has also been studied in subsurface consolidated sedimentary structures. For example, increased microbial activity was observed in permeable sandstone layers adjacent to low-permeability organic-rich shales (Fredrickson et al., 1997 ; Krumholz et al., 1997 ) and was fueled by excess organic acids produced in the shales which diffused into the adjacent sandstone sediments (McMahon and Chapelle, 1991 ; McMahon et al., 1992 ; Fredrickson et al., 1997 ; Krumholz et al., 1997 ; Fry et al., 2009 ). The North Pond sedimentary ecosystem is, at first glance, different from the systems described above. Specifically geochemical measurements indicate the presence of only one electron acceptor, i.e., oxygen (Cruise report MSM 11/1). In such an oligotrophic environment one would assume low rates of activity that decrease with increasing depth. Nevertheless, lithologic variability on a centimeter- to decimeter-scale can be seen throughout all of the examined cores (e.g., color scan figures in Figures 2 – 7 ). A link between sediment lithology and potential activity might therefore dictate the variability in the observed rates of potential activity. We can associate the peaks in potential acetate turnover with three different types of lithology, but no one single lithological type appears to dominate. (1) In cores GeoB13507 and GeoB13508 increased microbial heterotrophic activity can be observed near sandy layers, which are characterized by a high L* value, a high Ca content and a high Ca/Al ratio. Due to a different permeability, sand layers may be a source of dissolved organic matter that diffuses into the adjacent clay layers, for example as described by Fredrickson et al. ( 1997 ) and Krumholz et al. ( 1997 ). (2) Other carbonate-rich layers also seem to influence microbial heterotrophic activity in several of the sites cores. In GeoB13506, 13513, 13502, 13514, and 13504, increases in activity are also related to relatively high L* value, Ca content and Ca/Al ratio. At GeoB 13504 the presence of clay indicates the proximity to the basaltic basement. Based on increases with depth of dissolved oxygen (Cruise report MSM 11/1), it is inferred that the basalt is in near proximity at GeoB13514, GeoB 13504, and GeoB13502. Even without the presence of clay at GeoB 13514 and GeoB 13502, it is probable that the basal part of the retrieved sediment section represents the transition to the clay overlying the basaltic basement. (3) Finally there are occurrences of increased activity in cores 13502 and 13507 at dark layers, presumably containing more clay than the surrounding nannofossil ooze. The experiments show that heterotrophic microbial communities are active in deeply buried sediments, even in oligotrophic, low-organic carbon flux conditions. Most of the highest rates could be partially correlated with the presence of basalt nearby or directly associated with the presence of sandy layers. This suggests that microbial populations are stimulated near/at geological layers where lateral transport of fluids can occur and potential substrates can be provided to the microbes residing in the sediments. Nevertheless, we also detected potential rates of acetate turnover in other distinctly different lithological layers. Thus, while we can not link increased microbial heterotrophic activity to a single, distinct lithological type, this study highlights the importance of a sampling strategy following the basic characteristics of the sediment, such as the color or the light reflectance, in the absence of strong pore water chemical gradients. A high-resolution study of the interfaces foraminifer sand/nannofossil ooze and basalt/clay would be of great interest. In the case of deep-oxic sediments, in which exposure to the atmosphere is not as critical, the sampling procedure could be dictated by non-destructive core analysis such as those employed in this study."
} | 3,169 |
22541437 | null | s2 | 9,761 | {
"abstract": "Biofilms are structured communities of bacteria that are held together by an extracellular matrix consisting of protein and exopolysaccharide. Biofilms often have a limited lifespan, disassembling as nutrients become exhausted and waste products accumulate. D-amino acids were previously identified as a self-produced factor that mediates biofilm disassembly by causing the release of the protein component of the matrix in Bacillus subtilis. Here we report that B. subtilis produces an additional biofilm-disassembly factor, norspermidine. Dynamic light scattering and scanning electron microscopy experiments indicated that norspermidine interacts directly and specifically with exopolysaccharide. D-amino acids and norspermidine acted together to break down existing biofilms and mutants blocked in the production of both factors formed long-lived biofilms. Norspermidine, but not closely related polyamines, prevented biofilm formation by B. subtilis, Escherichia coli, and Staphylococcus aureus."
} | 250 |
28667104 | PMC5561297 | pmc | 9,763 | {
"abstract": "ABSTRACT During the 1960s, small quantities of radioactive materials were codisposed with chemical waste at the Little Forest Legacy Site (Sydney, Australia) in 3-meter-deep, unlined trenches. Chemical and microbial analyses, including functional and taxonomic information derived from shotgun metagenomics, were collected across a 6-week period immediately after a prolonged rainfall event to assess the impact of changing water levels upon the microbial ecology and contaminant mobility. Collectively, results demonstrated that oxygen-laden rainwater rapidly altered the redox balance in the trench water, strongly impacting microbial functioning as well as the radiochemistry. Two contaminants of concern, plutonium and americium, were shown to transition from solid-iron-associated species immediately after the initial rainwater pulse to progressively more soluble moieties as reducing conditions were enhanced. Functional metagenomics revealed the potentially important role that the taxonomically diverse microbial community played in this transition. In particular, aerobes dominated in the first day, followed by an increase of facultative anaerobes/denitrifiers at day 4. Toward the mid-end of the sampling period, the functional and taxonomic profiles depicted an anaerobic community distinguished by a higher representation of dissimilatory sulfate reduction and methanogenesis pathways. Our results have important implications to similar near-surface environmental systems in which redox cycling occurs. IMPORTANCE The role of chemical and microbiological factors in mediating the biogeochemistry of groundwaters from trenches used to dispose of radioactive materials during the 1960s is examined in this study. Specifically, chemical and microbial analyses, including functional and taxonomic information derived from shotgun metagenomics, were collected across a 6-week period immediately after a prolonged rainfall event to assess how changing water levels influence microbial ecology and contaminant mobility. Results demonstrate that oxygen-laden rainwater rapidly altered the redox balance in the trench water, strongly impacting microbial functioning as well as the radiochemistry. Two contaminants of concern, plutonium and americium, were shown to transition from solid-iron-associated species immediately after the initial rainwater pulse to progressively more soluble moieties as reducing conditions were enhanced. Functional metagenomics revealed the important role that the taxonomically diverse microbial community played in this transition. Our results have important implications to similar near-surface environmental systems in which redox cycling occurs.",
"conclusion": "Conclusions. The inability to comprehensively access and sample within legacy radioactive waste environments hampers our ability to comprehend cooccurring elemental cycling and microbial metabolism, potentially curtailing our ability to effectively manage and remediate such sites. The trench-sampling point at LFLS is therefore a particularly useful resource for such research. In this study, our coupled use of metagenomics and chemical analyses has provided a previously unattainable level of understanding for the LFLS trench water, highlighting the responsiveness of the microbial community to external changes and dynamic nature of the resulting chemistry. The combined results show that the trench waters contain a taxonomically diverse microbial community, which has likely evolved in response to variations in energy sources supplied by frequent redox fluctuations. When combined with the complex nature of the waste form, a myriad of microenvironments have developed within the trenches, allowing for simultaneous O, N, Fe, S, and C elemental cycling, as shown by cooccurring metabolic reactions in the aggregate water samples. Consequently, it can be inferred that Pu and Am are subject to persistent reducing conditions (as evident from active iron oxide dissolution, sulfate reduction, and methanogenesis) when the water level is low between rainfall events. These reductive processes maintain Pu and Am solubility, despite the occasional onset of oxidizing conditions associated with rainfall events. Ultimately however, the high concentrations of Fe present and the tendency of Fe(II) to be relatively rapidly oxidized to strongly sorbing Fe(III) (oxy)hydroxide solids on exposure to oxic conditions result in limited transport of Pu and Am. Although the findings described above are intrinsically linked to the specific site under investigation, they provide important generic insights into the dynamic biogeochemical behavior of iron-rich, redox-cycling environments. Of particular interest is the rapid response of the microbial community to dynamic redox conditions and the potential impact upon persistent contaminant solubility and enhanced mobility.",
"introduction": "INTRODUCTION The rapid expansion of an emerging nuclear industry immediately following World War II resulted in substantial volumes of low-level radioactive waste (LLRW) being generated from nuclear fuel cycle, weapons production, medical radioisotope, and radiochemical research activities. Although there was no consensus at this time, low-level waste (and in some cases more-active material) was commonly disposed of by burial in shallow trenches, as evidenced in the United States at Maxey Flats ( 1 ), Oak Ridge ( 2 ), and Hanford ( 3 , 4 ), in Canada at Chalk River ( 5 ), in the United Kingdom at Harwell ( 6 ) and at an LLRW disposal site ( 7 ), in Lithuania at Maišiagala ( 8 ), and more recently in Ukraine at Chernobyl ( 9 ), to name but a few. This was also the case for Australia's only nuclear (research) reactor at Lucas Heights. Known as the Little Forest Legacy Site (LFLS), radioactive materials, including minor amounts of 239+240 Pu and 241 Am were placed in narrow (0.6-m), 3-m-deep, unlined trenches from 1960 to 1968 ( 10 – 12 ). Large volumes of contaminated nonradioactive materials and equipment were also disposed of in these trenches ( 10 ). The LFLS trenches were excavated within undisturbed geological matrices of red-brown and gray clay (primarily kaolinite and illite/smectite) derived from the underlying weathered shale, interspersed with minor phases of hematite and goethite ( 11 , 13 ). The site was chosen in part due to the low hydraulic conductivities of these materials (∼9 to 66 mm/day) in order to isolate the LLRW from waters associated with the local hydrology cycle ( 10 – 12 ). However, an unintended consequence of this (also experienced at other disposal sites) has been that periodic intense rainfall and prolonged dry conditions can facilitate complete saturation and desaturation of the more-permeable waste material via surface infiltration and evapo(transpi)ration/leakage mechanisms, respectively. Elaborating further, this frequently results in infiltrating water filling up the more-porous trenches to the surface (akin to a “bathtub”), which has been shown to be a primary mechanism for the dispersion of contaminants 239+240 Pu and 241 Am ( 10 ). Furthermore, this has allowed for redox cycling to occur unabated in the LLRW trenches since their construction, potentially promoting redox-tolerant plasticity in the microbial communities present ( 14 ). With actinide mobility, in many instances, strongly dependent on their oxidation state ( 15 ), microbial communities can potentially play decisive roles in determining the fate and mobility of such elements in the environment. In general, microbial communities can influence actinide chemistry by partaking in redox ( 16 – 18 ), dissolution ( 19 , 20 ), precipitation ( 21 , 22 ), sorption ( 23 ), and/or methylation ( 24 ) reactions, which may either enhance or retard contaminant mobility. Despite this, much of the scientific research to date has focused on isolated individual species (such as those of Geobacter , Shewanella , and Clostridium spp.) and their impact on actinide, particularly uranium, behavior. The challenge remains as to how best to identify the role of microorganisms and their functioning within the wider microbial community which may be undergoing external, environmental changes ( 25 ). Furthermore, subsurface environments such as aquifers and shallow groundwaters, aside from being poorly studied, have been shown to be havens for microbial novelty not dominated by the well-characterized organisms listed above ( 26 ). Culture-independent techniques, such as metagenomics, in which genomic sequences capture the aggregate microbial ecology of a sample ( 27 , 28 ) have the potential to enhance our understanding of these complex biogeochemical systems. The question remains at LFLS, and in similar contaminated redox-cycling environments, as to what function microbial communities may be performing in the direct or indirect mobilization and/or retention of legacy radionuclides. As the establishment of causality between the legacy contaminants and microbial communities cannot be achieved in such a noninvasive environmental study, the aim of this research was to understand the role that periodic inundation from a large rainfall event, and presumably oxygen penetration, had on the concomitant changes to chemistry-radiochemistry and microbial communities in an LLRW trench environment. The two contaminants of major concern, Pu and Am, were the focus of this research, with shotgun metagenomics used to examine the microbial systems function and taxonomy.",
"discussion": "RESULTS AND DISCUSSION Water level changes and chemical analyses. The initial 220-mm rainfall event resulted in trenches filling to capacity and discharging from the surface or porous near-surface (0- to 0.2-m) in the “bathtub” mechanism described by Payne et al. ( 10 ) (see Fig. S1 in the supplemental material). Despite the subsequent 47-day sampling period receiving a further 72 mm of rainfall, which periodically increased trench water levels, an overall decline in trench water levels was observed across the sampling period (Fig. S1). Across the sampling period and as the water level declined, the pH was observed to increase from 6.30 to 6.60, whereas the E h values decreased from 247 to 147 mV ( Fig. 1 ). Of the cations and anions analyzed ( Fig. 2 ), iron displayed one of the greatest variations in concentration, increasing from 0.42 mM at day 0 to 1.00 mM by day 47. The elevated concentrations of iron are unsurprising, given that the LLRW at LFLS was disposed of in part within ∼760 steel drums ( 29 ) and buried within a highly weathered shale geological matrix ( 11 ). The continuous presence of Fe(II), even at day 0, confers reducing conditions in excess of E h values recorded, casting uncertainty over the absolute values supplied by the E h probe. The increase in Fe(II) concentrations with time was likely due to Fe(III) oxyhydroxide reduction, an observation supported by the concurrent liberation of Si and P, two elements that are typically coassociated with Fe(III)-oxyhydroxide at LFLS ( 30 ). The constant concentrations of expected conservative elements Cl − and K suggest that the drop in the trench water level was due to subsurface outflow rather than evaporative processes across the course of sampling. Other important elemental transitions included a 10-fold decrease in dissolved sulfur concentrations (presumed to be sulfate), from an initial concentration of 62.4 to 6.2 μM at day 47 ( Fig. 2 ). Nitrate concentrations doubled between days 0 and 6 (from 0.24 to 0.55 μM), after which they decreased to below detection limits at days 21 and 47 ( Fig. 2 ). FIG 1 pH and E h (standard hydrogen electrode corrected) measurements from the trench water across the sampling period. FIG 2 Temporal changes to element/ion concentrations in the trench water. Bars show the individual concentrations of each element/ion over the five sampling days 0, 4, 6, 21, and 47. The total (unfiltered) 241 Am activity increased from 15.7 to 27.8 Bq/liter (1.8-fold increase), while the soluble (filtered) fraction increased 3.4 times (7.2 to 24.7 Bq/liter) between days 0 and 47 ( Fig. 3 ). Although the activity of the total 239+240 Pu showed a proportionally smaller increase than 241 Am across the sampling period, from 30.4 to 45.6 Bq/liter (1.5 times), the soluble fraction increased from 0.21 at day 0 and reached a maximum of 0.80 (35.1 Bq/liter) by day 21. Despite the low-flow sampling conditions, the majority of 241 Am and 239+240 Pu in the trench water was solid associated at day 0. This implies that the solid-associated actinides are relatively stable or easily (re)mobilized and also that during the rapid influx of rainwater, when the trenches are filling up (and potentially overspilling), colloidal transport is likely to be the major form of contaminant movement at this site. Previous redox state measurements at LFLS found that Pu was present in the Pu(IV) (64.5%) and colloidal/Pu(III) (35.5%) states while Am was present exclusively as Am(III) ( 31 ). The vast quantities of Fe(II) as well as the results of ancillary measurements (dissolved oxygen [DO], oxidation/reduction potential [ORP]) would suggest that Pu(IV) and Am(III) were again the dominant oxidation states of the trench water contaminants. The results of all water quality parameters measured are provided in Table 1 . FIG 3 Activity of filtered and unfiltered radionuclides measured in the trench water. Filtered fractions (<0.45 μm, solid fill) are equivalent to soluble and smaller colloidal particles. Unfiltered fractions (full bar) are considered total (soluble plus all suspended solids) concentrations. Error bars show the standard deviations of triplicate measurements. TABLE 1 Geochemical parameters measured in the trench water Parameter Value at sampling day (date) a Maximum background concn b 0 (23 April) 4 (27 April) 6 (29 April) 21 (14 May) 47 (9 June) Field parameters pH 6.3 6.22 6.35 6.5 6.6 NA E h (mV) c 247 177 192 117 147 NA DO (mg/liter) 0.5 0.6 0.6 0.6 0.5 NA TDS h (g/liter) 0.115 0.12 0.118 0.156 0.185 NA Temp (°C) 20.9 19.5 19.8 18.2 19.2 NA Water level (m) d −0.89 −1.26 −1.36 −1.55 −1.64 NA Radiochemistry (activity in Bq/liter) e 241 Am (UF) f 15.68 ± 0.38 22.85 ± 0.58 22.09 ± 0.55 25.4 ± 0.64 27.8 ± 1.49 NA 241 Am (F) g 7.17 ± 0.19 11.24 ± 0.48 12.15 ± 0.22 21.56 ± 0.59 24.71 ± 1.3 NA 239+240 Pu (UF) f 30.44 ± 0.9 40.53 ± 1.22 41.71 ± 1.29 43.66 ± 1.27 45.6 ± 2.43 NA 239+240 Pu (F) g 6.46 ± 0.21 16.28 ± 0.51 17.73 ± 0.56 35.11 ± 0.99 26.93 ± 2.36 NA Chemistry DOC (mg/liter) 4.07 4.15 5.30 5.91 6.77 0.04 Fe(II) (mM) 0.34 0.39 0.45 0.75 0.92 <0.01 Fe (mM) 0.42 0.45 0.46 0.80 0.99 <0.01 Na (mM) 0.73 0.70 0.70 0.79 0.85 <0.01 SiO 2 (mM) 0.36 0.37 0.37 0.44 0.52 <0.01 Cl − (mM) 0.51 0.51 0.51 0.54 0.54 0.01 Mg (mM) 0.08 0.08 0.08 0.11 0.12 <0.01 Ca (μM) 33.43 30.69 34.18 41.42 50.40 0.25 K (μM) 31.71 32.48 32.74 31.97 32.23 0.31 Mn (μM) 1.80 1.86 1.64 2.00 2.55 <0.02 P (μM) 4.20 4.20 5.17 7.10 9.69 <1.6 S (μM) 62.36 62.36 59.25 28.06 6.24 <3.11 F − (μM) 2.63 2.11 2.11 3.16 4.21 <0.53 Br − (μM) 2.63 2.50 2.50 3.25 4.01 <0.13 I − (μM) 4.96 4.81 5.12 7.88 11.03 <0.22 NO 3 − (μM) 0.24 0.24 0.55 0.00 0.00 <0.01 a Day count from the first day with no precipitation after the rainfall event. All dates are for the year 2015. b Highest concentrations measured on multiple blanks ( n > 5) processed in parallel with trench samples. NA, not applicable. c Corrected values against standard hydrogen electrode. d Depth below ground surface. e Plus or minus 1 standard deviation. f Filtered through 0.45-μm filter (soluble/colloidal). g Unfiltered (total). h TDS, total dissolved solids. Community composition. Community profiles showed that Bacteria dominated over Archaea in the trench water across the entire sampling period. A total of 70 phyla of the 85 included in the GreenGenes database were detected at some point, and 11 phyla with values of >1% of the total community were detected at all times. Eukarya were found in low (∼1% to ∼2%), nearly constant abundance throughout the samples. Similarly, eukaryotic-specific family groups determined by MetaCyc reactions (RXNs) were all below our threshold significance level. As such, they are not considered in further detail or for the taxon abundance numbers throughout this paper. Archaea oscillated between 2.6 and 10.6% of the classified reads with minimum and maximum at days 4 and 47, respectively. Micrarchaeota and Parvarchaeota (superphylum DPANN) were the most abundant phyla at all times with a combined 45.5 to 55.9% of Archaea , while remaining sequences were shared in variable proportions between the superphylum TACK and Euryarchaeota ( Fig. 4 ). Although the fraction of TACK decreased over time from 24.8% at day 0 to 12.4% at day 47, Euryarchaeota reached a maximum at day 47, contributing 37.2% of all Archaea . These changes were derived mainly from variations in the SAGMA-X family ( Thaumarchaeota ), related to the ammonia-oxidizing archaeon “ Candidatus Nitrosotalea” ( 32 , 33 ), and in Bathyarchaeota (Miscellaneous Crenarchaeotal Group [MCG]), which includes the only potential noneuryarchaeal methanogens ( 33 , 34 ) and/or one of the few acetogenic Archaea ( 35 ). The increase in total abundance of Archaea over time was related to changes in ANME-2d Methanoregulaceae and Methanosaetaceae families, implicated in methane metabolism ( 36 – 38 ), as well as the Micrarchaeota and Parvarchaeota phyla. FIG 4 Taxon relative abundances over time. Only taxa with an average relative abundance of >5% of the total sequences in at least a single sampling day are shown. Taxa with <5% of all sequences are grouped under “other.” Phyla with <5% of relative abundance at all times are grouped under “other phyla,” except Archaea . Only 8 bacterial phyla grouped more than 5% of the total bacterial reads at any one sampling point, and among them, only Chloroflexi , OD1 ( Parcubacteria ), OP11 ( Microgenomates ), OP3 ( Omnitrophica ), and Proteobacteria were within the 10 most abundant bacterial phyla at all times ( Fig. 4 ). The principal changes observed over time refer to Proteobacteria , TM7 ( Saccharibacteria ), OP3, Acidobacteria , and OD1. While the proportion of TM7 and Acidobacteria decreased from day 0, both OP3 and OD1 reached their maximum by day 47 (18.9% and 14.7%). The Proteobacteria , often the most abundant phylum, showed a conspicuous increase, mainly due to Betaproteobacteria , comprising 48.7% of all classified reads at day 4. The order Burkholderiales was identified as being primarily responsible for this change (42.6% of total), especially the genus Ralstonia (20.3%) within Oxalobacteraceae (34.0%). These bacteria were also responsible for the altered functional profile observed at day 4. Several studies focusing on the microbiology of groundwater or subsurface ecosystems have demonstrated the existence of organisms able to pass through standard 0.22-μm filters ( 39 – 41 ). Despite this, a substantial portion of the Little Forest trench water community corresponded to taxa known to be able to pass through 0.22-μm filters, i.e., OD1, OP11, and DPANN. We suggest that this could be derived from the fast precipitation of iron in our extracted trench waters, effectively entrapping cells, or that they were attached to colloidal particles or to other cells. Still, it is possible that the numbers for these “ultrasmall” taxa could be underestimated in our results. A complete taxonomic profile of all sample replicates at each individual time point is provided in the supplemental material. An important aside to be noted with these data is the inherent reproducibility between sample triplicates. This finding provides a level of reassurance with regard to the aggregate nature of these water samples, often neglected in similar studies. Carbon cycling. Initial time points were characterized by a significantly ( P ≤ 0.05) higher relative abundance of RXNs using molecular dioxygen as the substrate, such as cytochrome c oxidase (CYTOCHROME-C-OXIDASE-RXN, EC 1.9.3.1 [ Fig. 5A ]) (MetaCyc RXN notations are shown here in all-uppercase format to provide an exact match with the MetaCyc database), quinol-cytochrome c reductase (1.10.2.2-RXN), and several mono- and dioxygenases. This was combined with a significantly ( P ≤ 0.05) lower relative abundance of methanogenesis-related RXNs, nitrogenase (ferredoxin, NITROGENASE-RXN), rubisco (RIBULOSE-BISPHOSPHATE-CARBOXYLASE-RXN), or heterolactic fermentation (PHOSPHOKETOLASE-RXN). The catalase (CATAL-RXN, EC 1.11.1.6/21 [see “Reactive oxygen species detoxification” in the supplemental material]) gene's relative abundance was highest at day 4 along with those of several ABC transporters and phosphotransferases, e.g., d -ribopyranose, d -xylose, spermidine, or l -arginine, as well as assimilatory sulfur and nitrogen pathway RXNs (refer to the supplemental material for details). The higher relative abundances of all these genes at day 4 suggest a metabolism more dependent on oxygen, i.e., aerobic, or at least microaerophilic (see “Nitrogen cycling” below). It also confers a higher dependence on available organic carbon ( viz ., heterotrophy) or on the presence of decaying complex organic matter ( 42 ). These interpretations are collectively supported by the geochemical measurements, including the higher E h values, decreasing concentrations of sulfur, and absence of nitrate, along with lower iron concentrations across the first sampling points. FIG 5 Changes in the relative abundances of selected RXNs over time. (A) Cytochrome c oxidase; (B) cellulase; (C) malate synthase; (D) 5-methyltetrahydrosarcinapterin:corrinoid/iron-sulfur protein co-methyltransferase (CH3-HSPT:Fe-S protein Co-MT); (E) sulfite reductase; (F) superoxide dismutase. Regarding the source of the organic fraction, the results suggest that soil particles and associated organochemicals were mobilized from material above the trenches via advective transport mechanisms during and immediately after rainfall. This was evidenced by the increased proportion of soil-associated Actinobacteria at day 0, which diminished to 0.71% by day 4 ( Fig. 4 ). Furthermore, the presence of genes encoding enzymes representing chitin degradation, such as chitobiase (RXN-12625, EC 3.2.1.52), diminished progressively until day 47, indicating a potential one-off provision of chitin, matching the leaching hypothesis (see Fig. S2 in the supplemental material). In addition, numerous facultative and strict anaerobes can degrade chitin and/or chitobiose ( 43 – 45 ), which lessens the likelihood of the alternative hypothesis that chitin depletion could be derived from the intrinsic lack of chitobiase in anaerobes. The other primary biopolymer found in soil is cellulose ( 46 ). The relative abundance of cellulase (RXN-2043, EC 3.2.1.4) showed no significant differences between days 0, 21, and 47 ( P = 0.172), suggesting a consistent supply of cellulose ( Fig. 5B ). The exception, noted at day 4, can be explained by the proliferation of Burkholderiales . The constant abundance of cellulose is unsurprising given the historical records, which indicate that a range of organic (particularly cellulose-based) compounds were codisposed of in the LFLS trenches ( 11 ). This hypothesis accords with previous stable isotope measurements, which identified the degradation of legacy organic matter as being responsible for enriched δ 13 C (inorganic) values measured near the trench ( 11 ). Lignin is present to a lesser or greater extent in all plant biomass. From the list of enzymes in the literature capable of degrading lignin ( 47 , 48 ), only below-threshold levels of certain genes were detected: versatile peroxidase (RXN0-267, EC 1.11.1.16), dye peroxidase (RXN-11813, EC 1.11.1.19), and laccase (LACCASE-RXN, EC 1.10.3.2). The overall lack of genes for proteins capable of lignin degradation strengthens the hypothesis that trench waste material is the source of cellulosic material rather than being derived from the degradation of plant material from the topsoil. The two fundamental genes representing the glyoxylate pathway, isocitrate lyase (ISOCIT-CLEAV-RXN, EC 4.1.3.1) (see Fig. S3 in the supplemental material) and malate synthase (MALSYN-RXN, EC 4.1.3.2) ( Fig. 5C ) showed between 3 and 4 times higher relative abundance on days 0 and 4 than on day 47. This pathway facilitates the use of short-chain carbon compounds (C 2 or C 3 ) for anabolic purposes, compounds especially generated during anaerobic processes. Although the glyoxylate pathway genes have been previously detected in organisms living in anaerobic environments ( 49 ), they were absent from strict anaerobic organisms based on the results from EggNOG ( 50 ), KEGG ( 51 ), and UniProtKB ( 52 ) databases (as of 24 May 2017). This finding supports the hypothesis that trench waters became anoxic as the water level declined, promoting conditions that favor the development of strict anaerobes. Furthermore, the aerobic community that developed immediately after the rainfall event likely utilized (and benefited from) the short-chain carbon compounds generated by preceding anaerobic conditions. Both acetoclastic and hydrogenotrophic methanogenesis pathways were evident from the functional profile analysis. Similar maximum relative abundances, about 1.4 × 10 −4 , of 5-methyltetrahydrosarcinapterin:corrinoid/iron-sulfur protein co-methyltransferase (RXN-12908, EC 2.1.1.245) ( Fig. 5D ) and coenzyme F 420 -dependent hydrogenase (COENZYME-F420-HYDROGENASE-RXN, EC 1.12.98.1) (see Fig. S4 in the supplemental material), which are specific RXNs for the methanogenesis from acetate and H 2 and CO 2 , were observed at day 47. The presence of methanogenesis-specific RXNs is supported by previous isotopic measurements, showing δ 2 H enrichment, relative to δ 18 O, in the vicinity of the trenches ( 11 ). Concurrently, the taxonomy revealed the presence of the ANME-2d division contributing up to 13.8% of all Archaea at day 47 (1.5% of the community). The ANME-2d division was initially linked to the anaerobic oxidation of methane using NO 3 − ( 36 ) or even NO 2 − ( 53 ), constituting one of the primary methane sinks under anaerobic conditions. However, recent research has shown that some of the members of this taxon are able to utilize Fe(III) in place of NO 2 − or NO 3 − ( 38 , 54 , 55 ). This provides a more reasonable explanation given the limited nitrate present and abundance of iron during the later sampling days. Sulfur cycling. The relative abundance of sulfite cytochrome c reductase (SULFITE-DEHYDROGENASE-RXN, EC 1.8.2.1) (see Fig. S5 in the supplemental material), involved in the assimilatory reduction of sulfate, peaked at day 4, with ∼10 times higher relative abundance than on day 0. At the same time, dissimilatory sulfate reduction RXNs, e.g., dissimilatory sulfite reductase (HYDROGENSULFITE-REDUCTASE-RXN, EC 1.8.99.3), followed the opposite trend, with a maximum at day 47 ( Fig. 5E ). The combined relative abundance of all the putative sulfate-reducing bacterium (SRB) taxa detected (mainly Syntrophobacterales , Thermodesulfovibrionaceae , and Desulfobacterales ) also increased over time, from 2.3% of the total prokaryotes at day 0 to 4.9% at day 47. Dissimilatory sulfate reduction is one of the major redox processes in both natural ( 56 ) and artificial ( 57 ) anaerobic environments. The 10-fold reduction in the sulfur concentration is thought to result from the loss of dissolved sulfate via reduction to sulfide and subsequent precipitation of insoluble heavy metal sulfides, particularly FeS. This interpretation is supported by the lack of measurable sulfides in the trench water (see “Chemical analyses of trench waters” below), along with previous reports showing sulfate reduction based on isotopic fractionation and severe (10- to 100-fold) depletion in sulfate concentrations in trench waters relative to surrounding wells ( 11 ). The potential contribution of sulfate- and nitrite-dependent anaerobic methane oxidation (S-DAMO and N-DAMO, respectively) was discounted due to the near-complete absence of ANME taxa ( Archaea ) aside from ANME-2d, and NC10 ( Bacteria ) (see “Carbon cycling” above) ( 38 , 53 , 58 , 59 ). Nitrogen cycling. The (inorganic) nitrogen cycle was represented mostly by RXNs related to denitrification and assimilatory nitrogen reactions, primarily dissimilatory nitrate reductase (RXN-16471, EC 1.7.5.1) (see Fig. S6 for a complete profile of the N-associated RXNs), although nitrogen fixation (NITROGENASE-RXN, EC 1.18.6.1) was the predominant N-associated RXN. All other prominent N-associated RXNs peaked at day 4 with the exception of hydroxylamine reductase (HYDROXYLAMINE-REDUCTASE-RXN, EC 1.7.99.1) and ammonia oxygenase (AMONITRO-RXN, EC 1.14.99.39). The increase in nitrate concentrations observed between days 4 and 6 (0.236 and 0.552 μM, respectively) might be derived from the oxidation of NO by nitric oxide dioxygenase (R621-RXN, EC 1.14.12.17). This surge in the relative abundance of nitrogen metabolism RXNs (at day 4) coincided with an increased dominance of Betaproteobacteria , mostly Burkholderiales . Betaproteobacteria have been linked to denitrification processes in a uranium-polluted aquifer in Rifle, CO, USA ( 60 ), and they may play a similar ecological role at LFLS. However, the increase in nitrate concentrations could equally be indicative of NO or NO 2 − oxidation, originally produced by the aerobic oxidation of ammonium by the Thaumarchaeota ( 61 , 62 ). The inorganic nitrogen cycling results provide important information regarding the transition from aerobic to anaerobic conditions as the water level declines. The competing requirements of nitrate respiration, which necessitates oxygen-limiting conditions at a minimum ( 63 ), and NO dioxygenase, needing molecular oxygen, collectively suggest that at day 4 the trench waters were no longer aerobic but more likely microaerophilic/hypoxic. However, many facultative anaerobes are capable of using nitrate as an alternate electron acceptor when oxygen is not available. As such, the high relative abundance of nitrate reducing enzyme genes at day 4 ( viz ., dissimilatory nitrate reductases) could be a confounding effect associated with the increased abundance of Burkholderiales . This was confirmed by searching the denitrifying pathway in KEGG (map00910) (as of 8 July 2016) ( 51 ). Iron cycling. Temporal increases in Fe(II) concentrations, such as those experienced in the later anoxic periods of the sampling, may be associated with the use of Fe(III) during anaerobic respiration, previously attributed to decaheme c -type cytochromes from the OmcA/MtrC family present in iron-reducing bacteria (FeRB) such as Shewanella spp. and Geobacter spp. ( 64 ). However, their representation in the trench water metagenome data was scarce (relative abundance, ≤10 −6 ). It is known that for respiration to occur, FeRB often require direct physical contact with Fe(III) solids ( 65 ). As only aqueous/suspended-phase sampling was permissible at LFLS, it is possible that the underrepresentation of an FeRB community was due to our sampling regime in which the solid phase was largely excluded. The genes associated with RXNs specific to the Fe(II) oxidation pathway (via rusticyanin, PWY-6692), i.e., ubiquinone-cytochrome- bc1 reductase (EC 1.10.2.2, RXN-15829) and aa3 -type cytochrome oxidase (EC 1.9.3.1, RXN-15830), were present, despite no iron-rusticyanin reductase (EC 1.16.9.1, RXN-12075), cyc2 , being found under the established threshold (maximum value, ∼3 × 10 −6 ) ( 66 ). The presence of both cytochromes may be explained by the fact that HUMAnN2 could not distinguish between the “generic” quinol-cytochrome c reductase (RXN-15816, EC 1.10.2.2) and cytochrome c oxidase (CYTOCHROME-C-OXIDASE-RXN), particularly when analyzing short reads. The presence of 1.9% of Gallionellaceae (over the total community composition) at day 0 and that of 2.9% of Crenothrix , a non-iron-oxidizing bacterium (non-FeOB) usually associated with Fe-mineralizing biofilms ( 67 ), suggests the existence of transient microaerophilic iron-oxidizing activity in the trench water despite the extremely low relative abundance of cyc2 . Waste disposal records from LFLS indicate that numerous steel drums (∼760) were codisposed of in the trenches ( 29 ). Based on the active sulfate respiration observed in the trench waters, we would expect that iron/steel materials may have suffered microbially induced corrosion (MIC) ( 68 ), potentially contributing to the elevated Fe(II) concentrations. However, the main iron MIC product is likely FeS ( 68 ), which can be utilized by Gallionella ferruginea ( Gallionellaceae ), an FeOB ( 69 ). Furthermore, this process would also provide an explanation for a persistent source of Fe(III) (oxy)hydroxides and their ongoing interaction with the S cycle. Previous research on soils experiencing fluctuating redox conditions and active iron cycling has shown that they frequently lack “typical” Fe(III)-respiring bacteria ( 70 ), because these organisms are outcompeted by sulfate respiration ( 71 ). Despite Fe(III) being a more thermodynamically favorable electron acceptor, it is commonly acknowledged that sulfate respiration often outcompetes Fe(III) respiration in both high- and low-sulfate environments ( 71 , 72 ). High levels of sulfate reduction in low-sulfate environments, akin to the LFLS trenches, has been previously observed to occur in the presence of crystalline Fe(III) oxyhydroxides that partially reoxidize sulfide generated by SRB to elemental sulfur ( 72 ). This mechanism provides a plausible explanation for our observations at LFLS. The large concentration of dissolved Fe(II) in the trench waters would likely contribute to the Fe(II)-catalyzed transformation of amorphous ferrihydrite to more crystalline, thermodynamically favorable forms ( 73 , 74 ), although this would be limited to some extent by the large concentrations of dissolved organic matter and silica ( 75 ). Furthermore, the abiotic reduction of crystalline Fe(III) oxyhydroxides would severely limit the energy acquisition by FeRB, and therefore, the FeRB would only outcompete SRB when sulfate and other reducible sulfur compounds were totally consumed. Alternatively, fermentative bacteria coupling the oxidation of a range of organic compounds to the reduction of ferric iron ( 76 – 78 ) may play an integral role in maintaining the elevated Fe(II) concentrations observed within the trenches. One example is the organism Propionibacterium freudenreichii , which has previously been observed to reduce Fe(III) by using humic substances as an electron mediator ( 79 ). In this regard, both heterolactic and propionic acid fermentation pathways showed high relative abundances based on phosphoketolase (PHOSPHOKETOLASE-RXN, EC 4.1.2.9) and methylmalonyl-coenzyme A (methylmalonyl-CoA) decarboxylase (RXN0-310, EC 4.1.1.41), respectively (see Fig. S7 in the supplemental material). Their decrease in relative abundance (at day 4) could be explained by the lack of fermentative pathways present in the genomes associated with the population shift, i.e., increase in Burkholderiales . This was confirmed by searching (as of 8 June 2016) methylmalonyl-CoA decarboxylase and phosphoketolase in the KEGG maps (map00640 and map00030, respectively). Synthesis of trench processes and radiochemical mobilization implications. The biogeochemistry of this dynamic system is conceptually described by the elemental cycling schematic shown in Fig. 6 . Immediately following the rainfall event, the E h reached its most-oxidizing value (247 mV) with the microbial community characterized by higher relative abundances of pathways related to aerobic (or at least microaerophilic) heterotrophic metabolism and one capable of chitin degradation. Although conditions were not strongly oxidizing, this pulse of oxic water would be sufficient to induce the abiotic oxidation of part of the large store of dissolved Fe(II), likely forming a combination of the reactive Fe(III) oxyhydroxides ferrihydrite and silica-ferrihydrite, along with the more-crystalline oxyhydroxide lepidocrocite, as has previously been observed in these trench waters ( 30 ). As both Am(III) and Pu(III)/(IV) are known to strongly sorb to sediments and iron oxides ( 15 ), it is of little surprise to observe the greatest proportions of (suspended) solid-associated actinides at this time point (day 0) ( Fig. 3 ). Note that even though most Am (54.3%) and particularly Pu (78.8%) were associated with a solid fraction of >0.45 μm, they were still extracted from the trench under our low-flow sampling method. This finding implies that colloid-associated Pu, and to a lesser extent Am, remains mobile within the trench waters, congruent with observations from other legacy radioactive waste sites ( 80 ). Interestingly though, the Pu migration distance away from source at LFLS in groundwater has been shown to be much smaller (∼1 order of magnitude less) than in other legacy locations such as the Nevada Test Site ( 81 ), Rocky Flats ( 82 ), and Mayak ( 83 ). We attribute this to a low-permeability soil matrix, inhibiting downward migration to the connected/permanent water table, coupled with the biogeochemical conditions within the trenches themselves. The high concentrations of Fe(II), circumneutral pH, and proliferation of aerobic heterotrophs drive the rapid formation of large quantities of Fe(III) oxides. The quantity of Fe(III) oxides that form upon oxic rainwater intrusion is evidently sufficient to contain the bulk of contaminants within the trenches during “bathtub” overflow events. The rate of Fe(II) oxidation is likely to be crucial for the ongoing attenuation of Pu and Am at LFLS ( 30 ). FIG 6 Hypothetical global scheme of the processes at LFLS. Orange details on barrels reading Fe(III) represent solid Fe(III) minerals, mainly (oxy)hydroxides. Colors of arrows represent the time at which each process takes place: red, aerobic/after rain; brown, microaerophilic; blue, anaerobic/dry phase; black arrows indicate processes that seem to be independent from the sampling time. Dashed arrows indicate transport. Abbreviations: C org , organic carbon; MIC, microbially induced corrosion; CH 3 -HSPT:Fe-S protein Co -MT, 5-methyltetrahydrosarcinapterin:corrinoid/iron-sulfur protein co-methyltransferase. By day 4, as water levels rapidly decrease, an increase of Burkholderiales ( Betaproteobacteria ) generates a functional profile disturbance, and while the aerobic profile is maintained, it is also the time point at which nitrogen cycling (e.g., nitrate respiration) becomes most active ( Fig. 6 , green circle number 2). Therefore, day 4 represents a potential transition away from oxic conditions derived from rain infiltration, though this sequence of events is somewhat confounded by the microbial growth lag phase associated with aerobic respirators. Over the following weeks (days 21 and 47), the microbial community transitions to a functional profile dominated by carbon fixation, methanogenesis, and sulfate respiration pathways ( Fig. 6 , green circles 3, 8, 9, and 12). The increase in anaerobicity correlated with increasing concentrations of soluble Fe and soluble radionuclides and a depletion of sulfate and nitrate. In the case of Am, although the total activity increased gradually as the water level in the trench declined, the soluble fraction increased by a greater proportion ( Fig. 3 ). This indicates that either a desorption or a dissolution process occurred. The concomitant increases in the soluble Am fraction and Fe(II) concentrations point toward reductive dissolution of Fe(III) oxyhydroxides as a major driver behind Am solubilization. The Pu behavior in the trenches presents a more-complex temporal dynamic due, in part, to its more-varied redox chemistry. As conditions become more reducing over time, one would expect to observe soluble Pu activities increase, both through the dissolution of Fe(III) oxides and, to a lesser extent, from Pu(IV) to Pu(III) reduction. In an interesting point of difference from Am, our results show that Pu proportionally remained in the particle-associated fraction for a substantially longer period, even as the dissolved Am(III) activity and Fe(II) concentration increased. The reason for the differing solution/solid-phase partitioning observed for Pu and Am is not clear based on the evidence at hand. The inability to sample solid materials from within the trenches has limited more-conclusive understanding. However, we suggest that the differing Am and Pu associations are likely due to different redox states, based on the previous measurements at LFLS, which showed a dominant Pu oxidation state of +4 ( 31 ). Electrostatically, Pu(IV), as the neutral hydrolyzed cation Pu(OH) 4 (aq) or as an intrinsic colloid, is more likely sorbed or incorporated into positively charged pseudocolloids such as Fe(III) oxides than Am 3+ . This is supported by research showing the highly reversible nature of Am(III) sorption onto poor crystalline iron colloids ( 84 ) and association with carbonate- and exchangeable sites on clays ( 85 ). Conclusions. The inability to comprehensively access and sample within legacy radioactive waste environments hampers our ability to comprehend cooccurring elemental cycling and microbial metabolism, potentially curtailing our ability to effectively manage and remediate such sites. The trench-sampling point at LFLS is therefore a particularly useful resource for such research. In this study, our coupled use of metagenomics and chemical analyses has provided a previously unattainable level of understanding for the LFLS trench water, highlighting the responsiveness of the microbial community to external changes and dynamic nature of the resulting chemistry. The combined results show that the trench waters contain a taxonomically diverse microbial community, which has likely evolved in response to variations in energy sources supplied by frequent redox fluctuations. When combined with the complex nature of the waste form, a myriad of microenvironments have developed within the trenches, allowing for simultaneous O, N, Fe, S, and C elemental cycling, as shown by cooccurring metabolic reactions in the aggregate water samples. Consequently, it can be inferred that Pu and Am are subject to persistent reducing conditions (as evident from active iron oxide dissolution, sulfate reduction, and methanogenesis) when the water level is low between rainfall events. These reductive processes maintain Pu and Am solubility, despite the occasional onset of oxidizing conditions associated with rainfall events. Ultimately however, the high concentrations of Fe present and the tendency of Fe(II) to be relatively rapidly oxidized to strongly sorbing Fe(III) (oxy)hydroxide solids on exposure to oxic conditions result in limited transport of Pu and Am. Although the findings described above are intrinsically linked to the specific site under investigation, they provide important generic insights into the dynamic biogeochemical behavior of iron-rich, redox-cycling environments. Of particular interest is the rapid response of the microbial community to dynamic redox conditions and the potential impact upon persistent contaminant solubility and enhanced mobility."
} | 10,911 |
20385577 | PMC2860127 | pmc | 9,765 | {
"abstract": "Proteins are the most versatile among the various biological building blocks and a mature field of protein engineering has lead to many industrial and biomedical applications. But the strength of proteins—their versatility, dynamics and interactions—also complicates and hinders systems engineering. Therefore, the design of more sophisticated, multi-component protein systems appears to lag behind, in particular, when compared to the engineering of gene regulatory networks. Yet, synthetic biologists have started to tinker with the information flow through natural signaling networks or integrated protein switches. A successful strategy common to most of these experiments is their focus on modular interactions between protein domains or domains and peptide motifs. Such modular interaction swapping has rewired signaling in yeast, put mammalian cell morphology under the control of light, or increased the flux through a synthetic metabolic pathway. Based on this experience, we outline an engineering framework for the connection of reusable protein interaction devices into self-sufficient circuits. Such a framework should help to ‘refacture’ protein complexity into well-defined exchangeable devices for predictive engineering. We review the foundations and initial success stories of protein synthetic biology and discuss the challenges and promises on the way from protein- to protein systems design.",
"conclusion": "CONCLUSION Superficially, the field of synthetic biology is currently dominated by the manipulation of gene regulatory networks. However, speed, versatility and a large body of knowledge all point to proteins as an optimal substrate for biological systems engineering. In fact, a string of recent studies have illustrated this potential. Nevertheless, the bewildering complexity of proteins remains to be tamed by a robust engineering framework. Such a framework, based on natural modularity and specific interactions, appears now within reach and may allow the assembly of synthetic networks from reusable protein (and non-protein) devices. Just as in natural cells, protein interaction devices are poised to take center stage in future systems that integrate synthetic RNA and gene networks with non-natural chemistry and metabolic engineering.",
"introduction": "INTRODUCTION Dynamic networks of interacting proteins are the nuts, bolts, sensors and microprocessors of any cellular machinery. Networks of protein assemblies give cells their structure, provide energy, convert chemicals, sense, integrate and process information, and build or break down most other components of a cell. So when the (arguably) first generation of synthetic biologists set out to construct artificial feedback loops ( 1 , 2 ), oscillators ( 3 ) and toggle switches ( 4 ), why did they not tap into this rich repertoire of protein signaling? Why was the first synthetic oscillator constructed from an energy-hungry and slow network of mutually repressive transcription factors ( 3 ) —so slow, in fact, that a single period could span several cell divisions? Why, for example, was it not based on protein circuitry from neurons which fire with millisecond frequencies? For a long time now, a large community of researchers has been studying chemistry, structure and function of proteins as well as their complexes and interactions. This includes a growing body of experience in protein design and engineering with a multitude of biotechnological applications. Evidently, we should thus be ready to jump from the manipulation of individual proteins to the design of protein systems—larger assemblies or protein networks that combine different functions. Protein circuits that integrate sensing and information processing with biochemical effectors could have enormous impact on medicine, biotechnology and the way we study and understand life. Yet, protein engineering has so far been restricted to an only auxiliary role in the design of synthetic gene circuits ( 5–7 ). The design of evenly matched, self-contained protein systems appears still out of reach. What is holding us back? There are good reasons why the design of increasingly sophisticated gene networks was—and still is—more feasible than the development of protein circuits. The basic rules for the regulation of gene expression are rather well understood. Ideally, regulative sequences such as promoters, operators or ribosomal binding sites are more or less independent both from each other and from the protein coding region that they control. In engineering terms, they are (or can be made) ‘uncoupled’. The logic of gene circuits can therefore be stitched together from linear pieces of DNA. In contrast, the complexity and dynamics of proteins and protein networks still puzzles us. Large-scale screens continue to turn out long lists of potentially interacting proteins, often with little overlap between experiments ( 8 ). Furthermore, many reproducibly verified physical interactions may still turn out to be ‘noise’ without functional relevance ( 9 ). Our understanding of even the best studied signaling pathways is still far from complete. In fact, the very concept of cascading pathways may be misleading ( 10 ). Information is often processed through the cooperative re-arrangement and modification of pre-assembled protein complexes ( 10 ) and ‘cross-talk’ (at least in eukaryotes) is the rule not the exception. Adding to the puzzle is the complexity of individual proteins. The stability and kinetics of their interactions is governed by a complex interplay of atomic structure and dynamics spanning several scales of length and time ( 11 , 12 ) ( Figure 1 ).\n Figure 1. Already single proteins are complex dynamic systems but they are open to scrutiny by experimental and computational methods. Simplified structures of an enzyme (glycosyltransferase, left) and its inhibitor (right) are shown as ensembles of snapshots taken from molecular dynamics simulations. The specific complex of the two proteins is shown in the background together with alternative non-native orientations from a docking calculation. Binding is governed by diffusion but may also require the correct matching of quickly interchanging conformational states. The stability of the complex is then influenced by the redistribution of dynamics between different protein regions as well as the surrounding solvent [simulation and docking data taken from ( 11 )]. On the surface, all this complexity appears to leave no hope for the rational design of sophisticated protein circuitry, at least, not in the near future. Yet, here we show that efforts in this direction are well underway and progress is being made. Several recent studies have utilized the natural modularity of proteins and managed to rewire signaling networks by the clever exchange and transfer of individual protein domains. Many more have fused unrelated domains into synthetic protein switches. Missing, however, are conceptual frameworks ( 13 , 14 ) for the design of ‘plug-and-play’ protein devices—devices that would be mutually compatible and reusable for the construction of sophisticated multicomponent protein systems. We briefly review the foundational technologies that will help us to reach this next level of protein systems design. We will then document initial success stories in the rewiring of signaling networks and the construction of modular protein switches. Our second purpose is to outline an engineering framework for protein synthetic biology as it is emerging from these works. The framework is based on the modularity of specific interactions, and we discuss its possible applications and challenges."
} | 1,904 |
26478780 | PMC4594533 | pmc | 9,766 | {
"abstract": "What bees learn during pollen collection, and how they might discriminate between flowers on the basis of the quality of this reward, is not well understood. Recently we showed that bees learn to associate colors with differences in pollen rewards. Extending these findings, we present here additional evidence to suggest that the strength and time-course of memory formation may differ between pollen- and sucrose-rewarded bees. Color-naïve honeybees, trained with pollen or sucrose rewards to discriminate colored stimuli, were found to differ in their responses when recalling learnt information after reversal training. Such differences could affect the decision-making and foraging dynamics of individual bees when collecting different types of floral rewards."
} | 191 |
33630153 | null | s2 | 9,767 | {
"abstract": "Yeast whole cells have been widely used in modern biotechnology as biocatalysts to generate numerous compounds of industrial, chemical, and pharmaceutical importance. Since many of the biocatalysis-utilizing manufactures have become more concerned about environmental issues, seawater is now considered a sustainable alternative to freshwater for biocatalytic processes. This approach plausibly commenced new research initiatives into exploration of salt-tolerant yeast strains. Recently, there has also been a growing interest in possible applications of microbial biofilms in the field of biocatalysis. In these complex communities, cells demonstrate higher resistance to adverse environmental conditions due to their embedment in an extracellular matrix, in which physical, chemical, and physiological gradients exist. Considering these two topics, seawater and biofilms, in this work, we characterized biofilm formation in seawater-based growth media by several salt-tolerant yeast strains with previously demonstrated biocatalytic capacities. The tested strains formed both air-liquid-like biofilms and biofilms on silicone surfaces, with Debaryomyces fabryi, Schwanniomyces etchellsii, Schwanniomyces polymorphus, and Kluyveromyces marxianus showing the highest biofilm formation. The extracted biofilm extracellular matrices mostly consisted of carbohydrates and proteins. The latter group was primarily represented by enzymes involved in metabolic processes, particularly the biosynthetic ones, and in the response to stimuli. Specific features were also found in the carbohydrate composition of the extracellular matrix, which were dependent both on the yeast isolate and the nature of formed biofilms. Overall, our findings presented herein provide a unique data resource for further development and optimization of biocatalytic processes and applications employing seawater and halotolerant yeast biofilms.Key points• Ability for biofilm formation of some yeast-halotolerant strains in seawater medium• ECM composition dependent on strain and biofilm-forming surface• Metabolic enzymes in the ECM with potential applications for biocatalysis."
} | 538 |
39658562 | PMC11632070 | pmc | 9,770 | {
"abstract": "Cyanobacterial photosynthesis (to produce ATP and NADPH) might have played a pivotal role in the endosymbiotic evolution to chloroplast. However, rather than meeting the ATP requirements of the host cell, the modern-day land plant chloroplasts are suggested to utilize photosynthesized ATP predominantly for carbon assimilation. This is further highlighted by the fact that the plastidic ADP/ATP carrier translocases from land plants preferentially import ATP. Here, we investigate the preferences of plastidic ADP/ATP carrier translocases from key lineages of photosynthetic eukaryotes including red algae, glaucophytes, and land plants. Particularly, we observe that the cyanobacterial endosymbionts expressing plastidic ADP/ATP carrier translocases from red algae and glaucophyte are able to export ATP and support ATP dependent endosymbiosis, whereas those expressing ADP/ATP carrier translocases from land plants preferentially import ATP and are unable to support ATP dependent endosymbiosis. These data are consistent with a scenario where the ancestral plastids may have exported ATP to support the bioenergetic functions of the host cell.",
"introduction": "Introduction Chloroplasts evolved from cyanobacterial endosymbionts (symbionts within host cells) established within eukaryotic cells 1 – 5 . This key evolutionary event was foundational to the evolution of photosynthetic eukaryotic life forms, including plants. Modern-day chloroplasts perform various functions like carbon assimilation, sulfate assimilation, nitrate assimilation, amino acid biosynthesis, fatty acid biosynthesis amongst others 4 . However, it is unclear what the exact functions of the early cyanobacterial endosymbionts were. Indirect insights have been obtained from host and organelle genome sequencing, bioinformatics analysis, and investigations into chloroplast biochemistry. Particularly, these studies have helped to identify the features retained within the organelles, metabolic pathways that were redundant and lost from the organelle genome, and pathways and adaptation elements that were transferred from the endosymbiont genome to the host genome. Despite all these studies, the key drivers of the endosymbiotic evolution of chloroplast are still unclear 6 . It is widely suggested that in the case of chloroplast evolution, the cyanobacterial oxygenic photosynthesis to produce ATP and NADPH may have been one of the key drivers 6 – 8 . This is highlighted by the fact that ADP/ATP carrier translocases and transporters are widely conserved across organelles like mitochondria and chloroplasts, including organisms that are related to the endosymbiotic precursors of mitochondria and chloroplasts 9 , 10 . ADP/ATP carrier translocases localized on the membrane of organelles facilitate the exchange of ATP and ADP between the cytoplasm and the organelle; this feature is crucial for the organelle to perform key bioenergetic functions for the host cell. The preference for ATP export versus ATP import is suggested to vary from one organelle to other. Importantly, the preferences of ATP import versus export for mitochondrial versus plastidic ADP/ATP carrier translocases reflect the roles of the organelles 8 , 9 , 11 , 12 . Briefly, it is generally accepted that the key function of modern-day land plant chloroplasts is carbon assimilation. On the other hand, the mitochondria within the land plant cells provide ATP (generated from oxidative phosphorylation) to the host cell while the chloroplasts utilize photosynthesized ATP predominantly for carbon assimilation instead of supplying it to the host cell 13 . Therefore, unlike the mitochondrial ADP/ATP carrier translocases that preferentially export ATP, the ADP/ATP carrier translocases from the plastids of green land plants preferentially import ATP 9 , 12 . The major ATP burden of the land plant cells is supported by mitochondrial oxidative phosphorylation, and this is highlighted by the fact that mitochondrial ADP/ATP carrier translocases preferentially export ATP 13 . However, it is important to note that the chloroplasts still play an important role in cellular bioenergetics by contributing assimilated carbon sources. In contrast, the major function of the endosymbiont that was the key precursor of chloroplast is unclear; particularly it is unclear if the cyanobacterial endosymbionts also provided photosynthetically generated ATP in addition to assimilated carbon. We hypothesized that studying the preferences of plastidic ATP/ADP carrier proteins from various lineages of photosynthetic eukaryotes, i.e., red algae, glaucophytes, and land plants, could provide some insights into the evolution of chloroplast functions 14 . Red algae are typically aquatic photoautotrophs 15 , 16 . Red algae belong to Archaeplastida and form a clade with land plants and glaucophyte algae 17 . Further red algal plastids have compacted and gene-rich architectures that most closely resemble the plastid ancestors, lack of unique unknown ORFs, highly conserved gene order, and slower rate of plastid-to-nucleus gene transfer amongst others 17 , 18 . Glaucophytes plastids share several traits with free-living cyanobacteria like peptidoglycan wall between the organelle membranes 19 , similar composition of their photosynthetic apparatuses 20 . These molecular features are suggested to support the hypothesis that glaucophytes diverged earliest within Archaeplastida 21 , 22 . In this study, we bioinformatically identify putative ADP/ATP carrier translocases from red algae, glaucophytes and land plants. We then generate a series of cyanobacterial mutants that heterologously express these proteins for biochemical characterization using cyanobacterial cell-based assays (Fig. 1A ). Next, using synthetic directed endosymbiosis (where the yeast cells depend on cyanobacterial endosymbionts for ATP) 23 , 24 , we test whether the engineered cyanobacterial endosymbionts expressing these ADP/ATP carrier proteins are able to support the bioenergetic functions of the host yeast mutants that depend on these cyanobacterial endosymbionts for photosynthetically generated ATP (Fig. 1B ). Particularly, we observe that the cyanobacterial endosymbionts expressing the ADP/ATP carrier translocases from red algae and glaucophytes are able to support photosynthesis-driven ATP-dependent endosymbiosis, whereas those expressing ADP/ATP carrier translocases from land plant plastids are unable to support photosynthesis-driven ATP-dependent endosymbiosis. These studies suggest that the chloroplast functions may have evolved over the course of evolution. Our investigations also result in the identification of a series of cyanobacterial mutants as optimal photosynthetic endosymbionts within yeast cells. We anticipate that such artificial photosynthetic yeast/cyanobacteria chimeras could also have the potential to be further developed for sustainable synthetic biology applications (e.g., photosynthetic metabolic engineering, carbon dioxide sequestration) 25 . Fig. 1 An approach to study the properties of plastidic ADP/ATP carrier translocases. A \n In-silico analysis and bioinformatic identification of plastidic ADP/ATP carrier translocase proteins from key lineages of photosynthetic eukaryotes. B Engineering cyanobacteria, Synechococcus elongatus PCC7942 (Syn7942), for recombinant expression of bioinformatically identification of plastidic ADP/ATP carrier translocase proteins. C ATP-dependent directed endosymbiosis between yeast mutants and cyanobacterial mutants expressing plastidic ADP/ATP carrier translocases.",
"discussion": "Discussion Organelles like mitochondria and chloroplasts are one of the endpoints of endosymbiosis. It is generally accepted that chloroplasts evolved from cyanobacterial endosymbionts that were established within eukaryotic cells. The key metabolic drivers that led to the establishment of cyanobacterial endosymbionts are still unclear 6 . It is suggested that that bioenergetic factors (e.g., dependence of host cells on endosymbionts for ATP synthesis) may have been crucial for endosymbiosis and organelle evolution 6 , 7 . In case of mitochondria, the ATP synthesized by oxidative phosphorylation of ADP whereas in case of chloroplast the ATP is synthesized by photophosphorylation of ADP. Since the key role of mitochondria is fulfilling the ATP requirements of the cell, the mitochondria express ADP/ATP carrier translocases to preferentially exchange synthesized ATP with cytosolic ADP. While the present-day chloroplasts also possess ADP/ATP carrier translocases, they are generally suggested to have varied preferences for ATP import versus export as compared to the mitochondrial ADP/ATP carrier translocases. In case of the plant chloroplasts, ADP/ATP carrier translocase are suggested to be expressed and functional during different stages as the plant cell cycles between photosynthesis and dark cycle 28 , 39 . The ADP/ATP carrier translocase from Arabidopsis thaliana preferentially imports ATP and are suggested to be crucial to sustain the metabolic functions of the plant plastids 37 . Evolutionary studies suggest that the endosymbiotic cyanobacteria, a precursor of chloroplast, may have acquired ADP/ATP carrier translocases through horizontal gene transfer from parasitic strains belonging to Chlamydiales 8 , 13 . Based on these observations, we hypothesized that studying the preferences of ADP/ATP carrier translocases from key lineages of photosynthetic eukaryotes, i.e., red algae, glaucophytes and land plants, could provide insights into the role of bioenergetics in the context of chloroplast evolution. Using bioinformatics analysis, we first identified a few putative plastidic ADP/ATP carrier translocases from these lineages. Next, we determined the preferences of these plastidic ADP/ATP carrier translocases for ATP export versus import. Since properties of translocases are indicative of organelle function 8 , 9 , 11 , 12 , we believe that understanding these preferences could highlight the differences in organelle functions in photosynthetic eukaryotes. Using cyanobacterial cell-based translocase assays and ATP uptake assays we observed that representative plastidic ntt1 homologs from different lineages of photosynthetic eukaryotes had differing preferences for ATP export versus ATP import. Particularly, we observed that the cyanobacterial cells expressing plastidic ADP/ATP carrier translocases from red algal and glaucophytes exported ATP when challenged with extracellular ADP. On the other hand, the cyanobacterial cells expressing ADP/ATP carrier translocases from land plant plastids secreted very low levels of ATP when challenged with extracellular ADP and also imported higher levels of ATP. To determine the relevance of our observations to endosymbiosis and bioenergetics, we tested cyanobacterial mutant strains recombinantly expressing bioinformatically identified ADP/ATP carrier translocases as yeast endosymbionts. We observed that the cyanobacterial mutants expressing ADP/ATP carrier proteins that were competent to export ATP were able to establish ATP-dependent endosymbiosis with yeast mutants whereas the cyanobacterial mutants expressing ADP/ATP carrier proteins that imported ATP were unable to establish ATP-dependent endosymbiosis with yeast mutants. These artificially directed endosymbiosis approaches demonstrated the relevance of different preferences for ATP import vs export on endosymbiont function and stability of bioenergetically driven endosymbiosis. Our observations could potentially have implications on the evolution of photosynthetic eukaryotes. As mentioned earlier, red algal plastids have compacted and gene-rich architectures that most closely resemble the plastid ancestors, lack of unique unknown ORFs, highly conserved gene order, and slower rate of plastid-to-nucleus gene transfer amongst others 17 , 18 . Additionally, glaucophyte plastids have retained several molecular trait from their cyanobacterial ancestors (e.g., peptidoglycan wall between the organelle membranes 19 , similar composition of their photosynthetic apparatuses 20 ) making them an attractive target to investigate the evolution of primary plastids 21 , 22 . The plastidic ntt1 homologs from red algae and glaucophytes that we identified, showed properties that were distinct from the land plant plastidic ntt1 homologs. Based on these studies, one hypothetical scenario would be that the initial interaction between chloroplast and host cell was based on ATP production by the cyanobacterial endosymbiont. Over the course of evolution, the cyanobacterial endosymbionts may have transformed from ATP and assimilated carbon-providing endosymbionts into land plant chloroplasts that primarily provide assimilated carbon sources for other bioenergetically important processes like glycolysis. Further, as mitochondria continued to evolve into specialized organelles that were efficient in ATP synthesis, the chloroplasts in land green plants which grow in relatively abundant oxygen conditions, might have started to evolve into organelles whose primary function was to provide assimilated carbon sources (e.g., sugars) to the host cell rather than photosynthetically generated ATP. Another hypothetical scenario would be that the ATP secretion from these red algal and glaucophyte plastids was an adaptation feature in response to their ecology (e.g., underwater growth in limiting oxygen concentrations). These intriguing hypotheses could be further tested directly in relevant organisms. Further, these approaches can be used to study host/endosymbiont adaptation factors in ATP driven endosymbiosis, the fitness cost of endosymbiont, and host mediated control over endosymbiont numbers. Additionally, the synthetic cyanobacterial endosymbionts we generated in this study may also have implications for various sustainable synthetic biology applications (e.g., photosynthetic metabolic engineering 25 , carbon dioxide sequestration)."
} | 3,495 |
25383190 | null | s2 | 9,771 | {
"abstract": "Embiopterans produce silken galleries and sheets using exceptionally fine silk fibers in which they live and breed. In this study, we use electron microscopy (EM), Fourier-transform infrared (FT-IR) spectroscopy, wide angle X-ray diffraction (WAXD) and solid-state nuclear magnetic resonance (ssNMR) techniques to elucidate the molecular level protein structure of webspinner (embiid) silks. Silks from two species "
} | 103 |
38966238 | PMC11220791 | pmc | 9,775 | {
"abstract": "Fiber reinforced polymer composites (FRPs) are valuable\nconstruction\nmaterials owing to their strength, durability, and design flexibility;\nhowever, conventional FRPs utilize petroleum-based polymer matrices\nwith limited recyclability. Furthermore, fiber reinforcements are\nmade from nonrenewable feedstocks, through expensive and energy intensive\nprocesses, making recovery and reuse advantageous. Thus, FRPs that\nuse biobased and degradable or reprocessable matrices would enable\na more sustainable product, as both components can be recovered and\nreused. We previously developed a family of degradable and reprocessable\ncross-linked polyesters from bioderived cyclic esters ( l -lactide,\nδ-valerolactone, and ε-caprolactone) copolymerized with\na bis(1,3-dioxolan-4-one) cross-linker. We now incorporate these networks\ninto FRPs and demonstrate degradability of the matrix into tartaric\nacid and oligomers, enabling recovery and reuse of the fiber reinforcement.\nFurthermore, the effect of varying comonomer structure, catalyst,\nreinforcement type, and lay-up method on mechanical properties of\nthe resultant FRPs is explored. The FRPs produced have tensile strengths\nof up to 202 MPa and Young’s moduli up to 25 GPa, promising\nevidence that sustainable FRPs can rival the mechanical properties\nof conventional high performance FRPs.",
"conclusion": "Conclusions Cross-linked polyester composites from\nδ-valerolactone, l -lactide, and ε-caprolactone\nmonomers and a bis(1,3-dioxolan-4-one)\ncross-linker with glass and carbon fiber reinforcements are promising\nsustainable composites. Two setup procedures suitable for use with\nair-sensitive resins were developed, modifying VARI and hot press\ntechnologies. Optimization of composite composition allowed tuning\nof the mechanical properties. Variation of the monomer structure,\ncatalyst, and reinforcement changed strength and rigidity, with fully\nbiobased PLA composites proving to be the strongest. The ability to\nimprove the compatibility between matrix and reinforcement via functionalization\nof the glass fiber surface and the addition of classical recycling\nadditives was established. Finally, the recycling of these composites\nwas demonstrated through degradation of the matrix under accelerated\nbasic hydrolysis conditions, followed by recovery and reuse of the\nfiber reinforcement. These materials present an encouraging step in\nthe transition toward more sustainable FRPs.",
"introduction": "Introduction Thermoplastics and thermosets are lightweight,\ndurable, and nonconductive\nyet may lack sufficient strength, dimensional stability, or stiffness\nfor load bearing applications. 1 Additional\nstrength can be imparted through reinforcement with fiber fillers\nto create fiber reinforced polymer composites (FRPs) which have a\nsignificantly higher strength to weight ratio. 2 FRPs are incredibly versatile and can be used for a wide variety\nof applications, including aerospace and automotive components, boat\nhulls, sports equipment, and wind turbine blades. 3 Despite their utility, there are major drawbacks\nassociated with\nthe use of FRPs, primarily the use of nonrenewable materials in their\nsynthesis and the generation of vast quantities of nonrecyclable waste\nat end-of-life. 4 FRPs are generally made\nusing a cross-linked, thermosetting polymer matrix with elusive reprocessability,\nwhich precludes recycling and forces the majority of FRP waste to\nbe landfilled, buried, or incinerated. 5 , 6 A promising\nalternative to conventional thermosets as polymeric matrix materials,\nthat offer greater scope for reprocessing, are covalent adaptable\nnetworks (CANs). 7 , 8 These are thermosetting polymers\nthat contain dynamic covalent bonds, such as ester, imine, disulfide,\nhindered urea, acetal, carbamate, or Diels–Alder linkages.\nThese bonds undergo reversible exchange reactions when subjected to\ncertain external stimuli, such as heat, solvent, or UV light. 9 The mechanism of exchange can be associative\nor dissociative, with associative CANs often being referred to as\nvitrimers, a term coined by Leibler and collaborators. 10 − 15 Our group has developed a bifunctional 1,3-dioxolan-4-one\nmonomer,\nbis(1,3-dioxolan-4-one) (bisDOX), 16 synthesized\nfrom l -(+)-tartaric acid; a nonhazardous, inexpensive, naturally\noccurring starting material. 17 Through\ncopolymerization of cyclic ester monomers l -lactide, δ-valerolactone,\nand ε-caprolactone with bisDOX as a cross-linker, poly(lactic\nacid), polyvalerolactone, and polycaprolactone networks (PLA, PVL,\nand PCL, respectively) have been made. 16 These networks have high thermal stability and tunable mechanical\nproperties, depending on the comonomer structure. Reprocessability\nis enabled by transesterification reactions at elevated temperatures,\nfacilitated by the polymerization catalyst which remains embedded\nin the networks. Moreover, they are susceptible to degradation via\nbase-catalyzed hydrolysis, facilitating recovery of oligomers, monomers,\nand l -(+)-tartaric acid. These thermosets showed promise\nas renewable and degradable alternatives to petroleum-derived thermosets. This work focuses on the extension of these degradable polyester\nresins to support recyclable FRPs ( Figure 1 ). We present a novel vacuum-assisted resin\ninfusion process carried out under air-free conditions, explore the\nintersection between catalyst and monomer choice with layup procedure,\nand test the effects of fiber sizing, fiber reinforcement type (glass\nor carbon), and comonomer structure on composite performance. Finally,\nchemical recycling of the matrix and recovery and reuse of the fiber\nreinforcement are demonstrated. Figure 1 (A) Synthesis of degradable cross-linked\npolyester networks with\nδ-valerolactone (VL), l -lactide (LA), and ε-caprolactone\n(CL) monomers and bisDOX cross-linker and (B) development of fiber\nreinforced polymer composites.",
"discussion": "Results and Discussion The bifunctional cross-linker,\nbisDOX, can be copolymerized with\ncyclic ester monomers to afford cross-linked polymeric networks, using\nthe salen aluminum alkoxide catalyst, [salen]AlOBn. 16 This work extended to using these resins in all-polyester\nFRPs ( Figure 1 ). Composite\nnomenclature throughout the paper will reference the polyester being\ncross-linked (PLA, PCL, or PVL) followed by an indicator of the transesterification\ncatalyst used in network formation (e.g., PVL-Al for [salen]AlOBn\ncatalyzed synthesis), followed by the suffix -GF or -CF to indicate\nthe nature of the reinforcement (e.g., PVL-Al-GF refers to a glass-fiber\nreinforced PVL composite prepared with an aluminum catalyst). Importantly,\nthe Al-catalyzed reactions are air-sensitive, requiring methodological\nmodifications from classical lay-up processes. Hand Lay-Up Our first generation of GFRPs was prepared\nusing hand lay-up, the oldest and still most common lay-up technique. 2 It entails manually layering fibers into a mold,\nadding the matrix material, and then using a brush or roller to ensure\nuniform distribution of the resin and remove trapped air ( Figure 2 , top). Finally,\nthe composite is left to cure at a specific temperature, before it\nis removed from the mold. 18 This technique\nwas modified to make it compatible with our air-sensitive catalyst\nby carrying it out under an inert atmosphere. However, there were\nchallenges with this approach, which affected the integrity of the\ncomposites produced. Irregular resin distribution within and between\ncomposite samples stemmed from difficulties maintaining consistent\nresin thickness when pouring it over the fibers in a glovebag while\npoor fiber wetting left the composites with a distinct layer of resin\non top of the fiber mats, leaving large voids between layers which\nresulted in delamination ( Figure 2 B,C). Figure 2 (A) Hand lay-up method of composite production, (B) SEM\nmicrograph,\nand (C) photograph of PVL-Al-3GF composite made by hand lay-up. Inert VARI To improve fiber wetting in our composites,\nwe turned to vacuum assisted resin infusion (VARI) where driving the\nliquid resin through a dry reinforcement under vacuum can improve\nperformance ( Figure 3 ; see the Supporting Information for more\ndetails). 19 Typically, VARI is carried\nout on the benchtop; however, our air-sensitive catalyst had to be\nhandled under an inert atmosphere, which presented practical difficulties.\nRecreating the VARI setup inside a glovebox or glovebag was challenging.\nControlling the rate of resin flow through the VARI setup was difficult\nas manual dexterity was significantly reduced and efforts to increase\nthe viscosity of the resin mixture by preinitiating the polymerization\ngave negligible improvements. Hence, when developing the VARI technique,\nwe recognized the need to manufacture the composites outside of a\nglovebox without exposing the resin mixture to air. This was achieved\nthrough removing of the mixture from the glovebox in a gastight syringe\nand directly injecting it into the VARI setup ( Figure 3 , bottom). This modification proved highly\nsuccessful, facilitating greater control over resin flow through the\nsetup, improving fiber wetting and, consequently, performance ( Figure S1 ). Figure 3 (A) Vacuum-assisted resin infusion (VARI)\nmethod of composite production\nand (B) modified VARI setup. Optimization of Polyester Composites Initial system\noptimization was conducted with the δ-VL monomer. Variables\nfor optimization are discussed in this section, with characterization\nacross these optimizations discussed in the characterization section. GF Modification To improve the interfacial adhesion\nbetween the GFs and matrix, a surface treatment, or “size”,\nis often applied to GFs. This size is bifunctional; one part of its\nstructure interacts with the matrix and the other with the GF, so\nit acts as a coupling agent. The formation of stronger noncovalent,\nor preferably covalent, connectivity between the GFs and matrix enhances\nthe strength of interfacial bonding. This improves the efficiency\nof stress transfer between the matrix and GFs, thereby improving the\nmechanical properties of the FRP. 20 The\nmost common GF sizes are organosilanes bearing silanol groups, which\ncondense with hydroxyl groups on the surface of the GFs, and variable\ngroups that interact with the polymer matrix ( Figure 4 ). 21 , 22 We investigated sizing\nwith four silanes: γ-glycidoxypropyltrimethoxysilane (GPTMS),\nethyltriethoxysilane (ETES), γ-hydroxymethyltriethoxysilane\n(HMTES), and aminopropyltriethoxysilane (APTES). While GF modification\ndid not improve the mechanical properties of the composites in these\nPVL systems, this optimization will prove important in other systems\n( vide infra ). For PVL, Young’s modulus was\nunaffected, while strain at break (ε b ) and stress\nat break (σ b ) decreased ( Figure S2 ); the modification process involved soaking the fiber mats,\nwhich may have affected the integrity of the weave. Figure 4 Schematic depicting functionalization\nof glass fiber surface with\nan organosilane (left). Structure of glass fibers functionalized with\nγ-glycidoxypropyltrimethoxysilane (GPTMS), ethyltriethoxysilane\n(ETES), γ- hydroxymethyltriethoxysilane (HMTES), and aminopropyltriethoxysilane\n(APTES) (right). Matrix Modification For construction applications,\nepoxy composites are often preferred to polyester composites, due\nto their superior thermomechanical properties. 23 We hoped to increase the strength and toughness of our\npolyester systems and make them more competitive with epoxies, by\nexploiting our understanding of the chemical dynamics of transesterification.\nThese dynamics are exemplified during the mechanical recycling of\nPET. 24 , 25 The low T g of\nthe polyester networks, combined with the low E a for transesterification, enables vitrimeric exchanges to\noccur at ambient temperature, which could reduce the structural integrity\nof the resins. We postulated that by using epoxy-based chain extension\nchemistry, we could balance the dynamic network structure with that\nof a conventional thermoset. Thus, the commercial chain extender Joncryl\nADR-4400 was added to the matrix mixture to introduce a small number\nof nondynamic cross-links ( Scheme S1 ) in\naddition to the dynamic cross-links. However, when GF was added to\nmake a composite ( PVL-Al-J-GF ), the resin did not set.\nThe hydroxyl groups on the GF surface can open the epoxy ring in Joncryl,\npreventing reaction with the secondary hydroxyl groups in the ring-opened\nbisDOX and inhibiting the polyester network formation. To circumvent\nthis issue, GFs were functionalized with ETES (EtmGF) to mask the\nreactive hydroxy groups. Composites with EtmGF and Joncryl ( PVL-Al-J-EtmGF ) were prepared, resulting in materials with\nhad the highest Young’s modulus (1.43 GPa) of all of the GF-reinforced\nPVL composites made using hand lay-up ( Table S1 ), demonstrating the utility of Joncryl for improving the mechanical\nproperties of this system. Variation of Fiber Reinforcement Carbon fibers and\ntheir composites exhibit superior mechanical properties than their\nglass fiber counterparts, so they yield more robust construction materials.\nInitially, PVL-Al-3CF was made using the VARI methodology.\nIt was observed that CF mats absorbed more resin into their weave\nstructure than GF mats, so a larger quantity of resin was needed to\nadhere the mats together and avoid delamination, corroborated via\nSEM analysis (cf. Characterization ). Variation of Comonomer PCL is made from ε-caprolactone,\nwhich, like δ-valerolactone, is a liquid monomer, so the same\nVARI procedure was used for the setup of both PCL and PVL composites.\nIn contrast, PLA is made using a solid monomer, l -(+)-lactide,\nwhich precluded the use of VARI, as this technique is only suitable\nfor liquid resin mixtures under ambient conditions. Thus, alternative\nmethods have to be investigated. The most successful approach was\na compression molding procedure, which entailed mixing the resin components\nin the glovebox and spreading the mixture onto GF mats, which were\nthen sandwiched between two sheets of vacuum bagging. Once this setup\nwas sealed, it was transferred outside the glovebox to then be hot\npressed, before leaving to cure in the oven. Alternative Catalysis While the Al-salen system is\na proven catalyst for the ring-opening polymerization (ROP) of DOX\nmonomers, 26 the air-sensitive nature would\nmake scale-up challenging. Sn(oct) 2 is an effective catalyst\nfor the ring-opening polymerization (ROP) of our cyclic ester comonomers, 27 − 29 although it does not work as effectively on DOX systems. The resultant\ncross-linked networks ( PVL-Sn , PLA-Sn , and PCL-Sn ) showed lower gel contents than their salen-catalyzed\ncounterparts (84 and 75% for PCL-Sn and PVL-Sn cf. 92 and 79% for PCL-Al and PVL-Al ,\nrespectively), indicative of a lower cross-link density. This was\nreflected in the mechanical properties of the GF composites ( Table 1 ). In contrast, CF\ncomposites demonstrated better mechanical properties when Sn(oct) 2 was used as the ROP catalyst (cf. Characterization ), which will enable more facile scale up. Table 1 Mechanical Properties of PVL-Al , PCL-Al , PLA-Al , PVL-Sn ,\nand PLA-Sn Composites with Glass and Carbon Fiber Reinforcements,\nManufactured via VARI a sample σ b (MPa) a ε b (%) a E (GPa) a fiber content (%) b PVL-Al-3GF 81.9 ± 7.6 1.51 ± 0.14 14.4 ± 1.9 77.0 ± 0.4 PCL-Al-3GF 70.6 ± 0.4 0.809 ± 0.093 15.3 ± 0.9 70.7 ± 1.7 PLA-Al-3GF 112 ± 35 3.21 ± 0.19 13.7 ± 1.4 64.8 ± 1.3 PVL-Sn-3GF 41.1 ± 2.8 1.03 ± 0.05 7.42 ± 0.25 73.7 ± 0.4 PLA-Sn-3GF 196 ± 27 2.49 ± 0.32 16.0 ± 1.8 71.3 ± 2.0 PVL-Al-3CF 41.3 ± 10.0 0.474 ± 0.045 15.9 ± 2.1 65.3 ± 0.5 PLA-Al-3CF 202 ± 15 1.75 ± 0.21 24.5 ± 1.7 52.5 ± 1.3 PVL-Sn-3CF 41.1 ± 1.7 0.603 ± 0.039 19.9 ± 2.8 56.3 ± 0.9 PLA-Sn-3CF 63.2 ± 14.2 2.48 ± 1.20 17.7 ± 2.5 59.2 ± 2.4 a σ b (stress at\nbreak), ε b (strain at break), and E (Young’s modulus) data obtained from tensile testing measurements. b Fiber content obtained from\nTGA\nanalyses. Characterization The thermal properties of the composites\nwere examined via TGA and DSC ( Table S2, Figures S4–S15 ). TGA data showed that the GFRPs had fiber contents\nfrom 64.8% to 77.0%. This variation was attributed to differences\nin the amount of resin mixture remaining in the VARI setup. CFRPs\nhad lower fiber contents than GFRPs, with values between 52.5% and\n65.3%. This difference was due to the larger quantity of matrix mixture\nrequired to"
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