peerj_json_files/PeerJ_Json_14.json

{
    "v1_col_introduction": "introduction  : Methane is recognized as one of the most powerful greenhouse gases, with annual\nemissions of approximately 600 Tg (King, 1992; Hanson & Hanson, 1996; Etiope & Klusman, 2002; Keppler et al., 2006). Its atmospheric concentration has been steadily increasing over the past 300 years, mostly due to anthropogenic activities (Singh et al., 2010). Until recently, two major modes have been recognized by which methane is removed from the environment: aerobic oxidation conducted by a specialized group of bacteria, known as methanotrophs (Hanson & Hanson, 1996; Chistoserdova & Lidstrom 2013), and anaerobic oxidation linked to sulfate reduction, conducted by a specialized group of archaea, known as anaerobic methanotrophs or ANME (Valentine, 2002; Knittel & Boetius, 2009). The former process is important for methane consumption in freshwater sediments and soils, whereas the latter is thought to be the major process in anoxic marine environments. More recently, however, evidence has been accumulating that other metabolic modes for methane consumption must exist, linked to alternative electron donors, such as nitrate/nitrite-dependent anaerobic/microaerobic bacterial methane oxidation in freshwater environments (Wu et al., 2011) and metal-dependent methane oxidation by archaea in marine environments (Beal et al., 2009). These new findings point toward novel biogeochemical processes that need elucidation in order to be placed into the context of the global carbon cycle. However, the relative environmental significance of these processes, the identity of the microbes involved, and the details of their metabolism remain poorly characterized. On the other hand, the clear separation between the aerobic and the anaerobic modes of metabolism may represent an artifact originating from experimental data predating environmental microbiology approaches, including culture-independent approaches. This notion is nicely illustrated by anaerobic nitrite-dependent methane oxidation in members of the NC10 phylum occurring by aerobic methane oxidation. This metabolic mode involves canonical methane monooxygenase, the classic sets of methanol and formaldehyde oxidation enzymes, and a strict reliance on the presence of oxygen that, in 2 2\n24\n25\n26\n27\n28\n29\n30\n31\n32\n33\n34\n35\n36\n37\n38\n39\n40\n41\n42\n43\n44\n45\n46\n47\n48\n49\nPre Prin ts Pre Prin ts\nthis case, is produced intracellularly (Wu et al., 2011). At the same time data are available suggesting that at least some of the classic aerobic methanotroph and methylotroph species may be able to thrive in microaerobic environments and potentially utilize alternative electron acceptors, such as nitrate, for methylotrophic metabolism (Costa et al., 2000; Modin, Fukushi, Yamamoto, 2007; Kalyuzhnaya et al., 2009; Stein & Klotz, 2011).\nWe have previously characterized communities involved in methylotrophy in Lake\nWashington, Seattle, USA, using both culture-reliant and culture-independent approaches, focusing on organisms active in aerobic conditions. These studies identified a diverse functional community and highlighted the potential importance of the Methylococcaceae and the Methylophilaceae species as members of this community (Nercessian et al., 2005; Kalyuzhnaya et al., 2008; Chistoserdova, 2011a). Metagenome-based metabolic reconstruction of these species has indicated that at least some of them are capable of denitrification, suggesting that they may be adaptable to an anaerobic/microaerobic life style (Kalyuzhnaya et al., 2008, Kalyuzhnaya et al., 2009). In this study, we have expanded the previous efforts of characterizing functional methylotroph communities by addressing the nature of the communities involved in methane metabolism in both aerobic and microaerobic conditions. In addition, we have addressed the potential role of nitrate in these communities in an attempt to further link carbon and nitrogen cycles in terrestrial environments.",
    "v1_text": "materials and methods : Experimental setup, sample collection and stable isotope probing. The schematic of the experiments conducted is depicted in Figure 1. Sediment samples were collected on March 3, 2009, from a 63 m deep station in Lake Washington, Seattle, Washington (47.038075\u2019 N, 122.015993\u2019 W) using a box core that allowed collection of undisturbed sediment. Samples were transported to the laboratory on ice and immediately used to set up microcosms. In order to assess populations active in methane oxidation under different oxygen tensions and to test for 3 3 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 Pre Prin ts Pre Prin ts their potential dependence on the presence of nitrate we set up microcosm incubations as follows. One microcosm was incubated in an atmosphere of 50% 13C-labeled methane (99 atom % 13C, Sigma-Aldrich) and 50% ambient air, to assess the populations active in aerobic methane oxidation (the +O2-NO3- condition); the second microcosm was incubated in an atmosphere of 50% 13C-methane and 50% ambient air, in the presence of 10 mM KNO3, to assess the populations active in aerobic methane oxidation positively responding to the presence of nitrate (the +O2+NO3- condition); the third microcosm was incubated in an atmosphere of 50% 13C-methane and 50% N2, to assess the populations active in microaerobic methane oxidation (the -O2-NO3- condition); the fourth microcosm was incubated in an atmosphere of 50% 13C-methane and 50% N2, in the presence of 10 mM KNO3, to assess the populations active in microaerobic methane oxidation positively responding to the presence of nitrate (the -O2+NO3- condition). Each microcosm contained 50 ml of the top layer (1 cm) of the sediment and 50 ml of Lake Washington water filtered through 0.22 \u03bcm filters (Millipore). Samples were placed into 250 ml glass vials (6 vials per experiment, the contents of which were mixed before DNA extraction) and these were sealed with rubber stoppers. The duration of the incubation time for each microcosm was determined empirically by observing the formation of a heavy, 13C-enriched DNA fraction. It took 10 days for heavy DNA band to appear in the +O2+NO3- microcosm, compared to 15 days for the +O2-NO3- microcosm, suggesting that the methane-consuming community was stimulated by nitrate. It took much longer for heavy DNA band to appear in the microaerobic microcosms (20 and 30 days, respectively, for nitrate-amended and nitrate-free conditions; Figure 1). These data suggest that nitrate also had a positive effect on methane consumption by the microbial community in microaerobic conditions. Community DNA was extracted as described previously (Beck at al., 2011) with one modification as follows: DNA samples were subjected to an additional round of purification using UltraClean\u00ae Mega Soil DNA Isolation Kit (MOBIO). The heavy (13C-enriched) fractions of DNA 4 4 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 Pre Prin ts Pre Prin ts were separated from the light (12C) fractions by CsCl-ethidium bromide density gradient ultracentrifugation, visualized under UV (Figure 1), and collected and purified following standard procedures as previously described (Neufeld et al., 2007). DNA from an untreated sediment sample was extracted using the same protocol. This sample was not subjected to density gradient centrifugation. DNA sequencing and assembly. Five shotgun libraries were constructed, one from each microcosm. The libraries were sequenced using the 454 sequencing technology at the Joint Genome Institute (JGI) Production Genomics Facility. A total of 5,241,266 reads comprising 1.67 gigabases (Gb) of sequence were generated. These were assembled using the Newbler assembler. Assembly statistics are shown in Table 1. Pyrotag sequencing. We used 454 pyrotag sequencing of the V8 hypervariable region of the 16S rRNA gene to determine the compositions of microbial communities in the four 13C-enriched metagenomes using a computational pipeline PyroTagger, as previously described (Kunin & Hugenholtz, 2010), and we compared these to the community composition in the original (unamended) lake sediment sample. The number of total pyrotag sequences generated per microcosm is shown in Table 1. The PyroTagger assignments were used to calculate the Shannon-Weaver diversity index and the expected number of unique species rarefied to a constant value across all samples (Table 1). Metagenome analysis. The draft quality assemblies were processed using the IMG/M pipeline (Markowitz et al., 2012) and the outputs of these automated analyses were manually verified and used for metagenome profiling. Single gene taxonomy. To classify the 16S rRNA gene sequences in the metagenomes, the 5 5 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 Pre Prin ts Pre Prin ts 16S genes identified by JGI pipeline were aligned against the Ribosomal Database Project (RDP) version 10, release 26. The top scoring alignment for each sequence was used to assign taxonomy, based on the annotations in the RDP. Genes were classified to the family level. To detect pmoB and mmoX genes, respective peptides representing Methylococcaceae and Methylocystaceae were obtained from public databases and used as queries in pBLAST analyses against each dataset, and all matches were recorded. These queries pick each other and also the NC10 sequences. All matches were compared with sequences in public databases using pBLAST. Genus level assignments were made using an 80% identity cutoff level, and family level assignments were made at 70% identity cutoff, based on prior knowledge on gene diversity within each family (Chistoserdova & Lidstrom, 2013). To detect fae genes, respective peptides representing Methylococcaceae, Methylocystaceae, and Methylophilaceae were obtained from public databases and used as queries in pBLAST analyses against each dataset, and all matches were recorded. These queries pick each other, other proteobacterial sequences as well as NC10, planctomycete and unclassified sequences. Genus and family level assignments were done as above. For the nitrogen metabolism genes, sequences were selected by their annotation and aligned against the NCBI's nonredundant database (nt). The top scoring hit for each sequence was saved. The NCBI taxon ID was extracted and the NCBI taxonomy database queried to collect the 'scientific name' of each hit. The count of hits for each 'scientific name' were reported. The following annotation search terms were used: 'itrate reductase' for NO3- reductase, 'itrite reductase' for NO2- reductase, 'itric[-]oxide reductase' for NO reductase, \u2018itrous[-]oxide reductase for N2O reductase, and 'itrogenase' for nitrogenase. The first letter was omitted to avoid conflicts with upper and lower case letters and in the case of NO and N2O reductases, both annotations (with and without '-') were accepted. To classify mxaF and xoxF genes belonging to specific methylotroph families, high stringency pBLAST analyses were applied using 90% identity level cutoff at the protein level and 6 6 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 Pre Prin ts Pre Prin ts employing publically available sequences of the respective enzymes representing the respective taxonomic groups. results : Pyrotag profiling of community DNA shows enrichment for Methylococcaceae and Methylophilaceae sequences in aerobic microcosms As expected from prior analyses (Kalyuzhnaya et al., 2008), the community in the unamended sample revealed high complexity, being represented by a total of 1,486 sequence clusters (97% sequence identity; Kunin & Hugenholtz, 2010). The community was dominated by Proteobacteria (33.3%), of which phylotypes of the Methylococcaceae family that represents one class (called type I) of methane oxidizing bacteria were most prominently present (10% of all sequences). The second most dominant group was represented by chloroplast sequences (21.9%). Other prominently present phyla were Bacteroidetes (10.5%), Acidobacteria (7.2%) and Chloroflexi (4.0%; Figure 2A). The phylogenetic complexity of the 13C-enriched metagenomes representing three of the enrichment conditions (the +O2-NO3- condition, the +O2+NO3- condition, and the -O2-NO3- condition) was significantly reduced compared to the non-enriched community (313, 709 and 561 sequence clusters, respectively), and different shifts in phyla distribution occurred in these communities. The proportion of proteobacterial sequences increased in the aerobic communities (to 49.7% and to 82.0%, respectively, in +O2-NO3- and in +O2+NO3- conditions; Figure 2A). In both cases phylotypes classified as the Methylococcaceae and the Methylophilaceae were most prominently present (10.9% and 14.9% of all sequences in the +O2-NO3- condition and 56.5% and 10.5% of all sequences in the +O2+NO3- condition, respectively; Figure 2B). The proportion of Proteobacteria decreased (to 13.2%) in the -O2-NO3- condition, the dominant phylotypes being the chloroplast and the Bacteroidetes phylotypes (34.0% and 9.5% of total sequences, respectively), while the Methylococcaceae and the Methylophilaceae phylotypes constituted only a minor fraction of all 7 7 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 Pre Prin ts Pre Prin ts sequences (0.03% and 0.9%, respectively). The proportion of proteobacterial phylotypes and the overall make up of the community of the -O2+NO3- condition, at the phylum level, resembled that of the non-enriched community (Figure 2B). However, the Methylococcaceae phylotypes were less represented (4.0% of total sequences) while other proteobacterial phylotypes (such as Burkholderiales) were more represented than in the non-enriched community. Phylotypes representing other bona fide methylotroph taxa, including members of the Methylocystaceae and Bejerinckiaceae that represent the second class (called type II) of methane oxidizers and members of the recently described NC10 phylum implicated in anaerobic methane oxidation linked to denitrification (Wu et al., 2012) were detected in all five pyrotag libraries. However, their proportions were very small, not exceeding 0.5% of the total community in each case. Genome recruitment further highlights the dominant presence of Methylococcaceae and Methylophilaceae species in aerobic microcosms A total of 1,362,213,455 base pairs (1.36 Gb) of assembled sequence were generated. Genes were called using the standard JGI IMG/M pipeline (Markowitz et al., 2012), and each gene was taxonomically classified by using its best BLAST hit in the current genomic database employed by the IMG/M interface (3811 bacterial genomes, 163 archaeal genomes, 177 eukaryotic genomes and 2803 viral genomes; sequencing and assembly statistics are shown in Table 1). For taxonomic assignments, we considered separately all protein coding genes and genes classified at the 60% and the 90% cutoff levels (protein level classification). While few genes were classified at the 90% cutoff level (2.44 to 17.56% of the total, dependent on the microcosm) these provide very robust proxies for the organisms represented in the metagenomes, especially given the fact that genomes of key model methylotrophs were parts of the database used for comparisons, including genomes originating from Lake Washington (Lapidus et al., 2011, Kittichotirat et al., 2011 and unpublished). Thus we mostly relied on the 90% cutoff classification for the confident sequence assignments, while realizing that these 8 8 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 Pre Prin ts Pre Prin ts provide the lowest estimate for the presence of a specific phylum. At the 60% cutoff level, between 28.9% and 42.5% of the total genes could be classified, allowing for encompassing species not represented in the databases by very closely related models. In either case, most of the genes in each metagenome were taxonomically classified as proteobacterial, with the absolute majority matching to beta- and gammaproteobacteria (up to 45.4% and up to 50.1% of genes at 90% cutoff level, respectively). The next most abundant group were alphaproteobacteria (up to 12.4% of genes at 90% cutoff level), excepting the -O2-NO2metagenome, in which, along with gamma- and betaproteobacteria, Bacteroidetes and deltaproteobacteria sequences were prominent. Remarkably, most of the gammaproteobacterial sequences (up to 84.2/98.4% at the 60/90% cutoff levels, dependent on the microcosm) were classified as belonging to the Methylococcaceae family. Among betaproteobacterial sequences, the largest proportion of sequences in the aerobic microcosms (up to 53.6/88.4%) were classified as belonging to the Methylophilaceae family, while in the microaerobic microcosms betaproteobacterial sequences were distributed among a number of dominant families, which included Methylophilaceae, Comamonadaceae, Rhodocyclaceae and Burkholderiaceae. Among the alphaproteobacterial sequences, those classified as belonging to the Methylocystaceae family only constituted the highest proportion (48.6/81.3%) in the +O2-NO3- microcosm, but they were also abundant in the +O2+NO3- microcosm (13.0/30.1% of total alphaproteobacterial sequences). In the remaining datasets, few alphaproteobacterial sequences were classified as Methylocystaceae, with Bradyrhizobiaceae sequences being most abundant. Similarly to the results of pyrotag analysis, sequences of other bona fide methylotrophs (such as Methylobacteriaceae, Bejerinckiaceae, Xanthobacteriaceae, Hyphomicrobiaceae) were identified in each metagenome. However, the proportions of the genes assigned to each of these families were low, suggesting that these species were minor members of the functional communities investigated. Sequences assigned to each of the major methylotroph families, Methylococcaceae, 9 9 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 Pre Prin ts Pre Prin ts Methylophilaceae and Methylocystaceae, were further classified at the genus level, by matching each gene classified to the family level to the available genomic scaffolds representing each family, at 60 and 90% cutoff values. In these analyses, the Methylococcaceae family was represented by a total of six genomes, of Methylobacter tundripaludum (Svenning et al., 2011), Methylomonas sp. (unpublished), Methylomicrobium album (unpublished), Methylocaldum szegediense (unpublished), Methylococcus capsulatus (Ward et al., 2004) and Crenothrix polyspora (unpublished). In the case of the latter, we find the claimed affiliation of this strain within a proposed new family of Crenothrichaceae (Soecker et al., 2006) invalid, based on high sequence similarity with the members of Methylococcaceae (at least 95% at 16S rRNA gene level; Iguchi, Yurimoto & Sakai, 2011), and thus we consider this organism as part of this family. However, the matters are complicated further by the fact that the sequence of the yet uncultivated C. polyspora originated from a highly enriched but not axenic culture that may contain other representatives of Methylococcaceae. Of the six genomes, only one represented an organism originating from Lake Washington, the Methylomonas sp. strain (unpublished data). The Methylocystaceae family was represented by only two genomes, of Methylosinus trichosporium (Stein et al., 2010) and Methylocystis sp. (Stein et al., 2011), none originating from Lake Washington. The Methylophilaceae family was represented by eight genomes, of Methylotenera mobilis, Methylotenera versatilis, Methylovorus glucosotrophus (Lapidus et al., 2011), Methylophilus sp., unclassified Methylophilaceae (unpublished), Methylobacillus flagellatus (Chistoserdova et al., 2007), and unclassified Methylophilaceae strains HTCC8121 (Giovannoni et al., 2008) and KB13 (unpublished). Of these, the first five strains originated from Lake Washington (Kalyuzhnaya et al., 2006; Kalyuzhnaya et al., 2012 and unpublished) and the latter two were marine Methylophilaceae with unusually small genomes (Giovannoni et al., 2008). All the genomes mentioned here as \u2018unpublished\u2019 have been sequenced by the JGI and are publically available through the IMG/M interface (http://img.jgi.doe.gov). From matching to this limited number of genomic scaffolds, the Methylobacter species appeared to be the 10 10 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 Pre Prin ts Pre Prin ts dominant type among the Methylococcaceae representatives, the Methylocystis types appeared to dominate over the Methylosinus types, and Methylotenera species appeared to be dominant among the Methylophilaceae. However, specific dynamics could be observed at the genus level in response to different stimuli (Table 2). The proportion of the Methylomonas and Methylomicrobium types increased in response to the addition of methane, especially pronounced in the +O2+NO3- condition, while the proportion of the \u2018Crenothrix\u2019 types decreased compared to unamended sediment. The Methylobacter types were most dominant in the -O2 +NO3- condition. Dynamics were also clearly seen among the Methylocystaceae, with the proportion of Methylosinus sequences upshifting in response to methane in aerobic conditions and downshifting in response to nitrate, with respect to Methylocystis sequences. The relative proportion of Methylotenera sequences among the Methylophilaceae populations upshifted significantly in response to nitrate in aerobic conditions. We were also able to distinguish between two different species within Methylotenera, M. mobilis vs. M. versatilis, based on their significant divergence at the genomic level (Lapidus et al., 2011). While the proportion of M. versatilis-like sequences increased in the +O2+NO3- condition, their proportion decreased in the -O2+NO3- condition, being replaced by the M. mobilis-like sequences. Dynamics could also be seen among sequences classified as other Methylophilaceae. Unsurprisingly, virtually no sequences were matched to the scaffolds representing marine Methylophilaceae. Taxonomic profiling demonstrated a good correlation between the populations of the Methylococcaceae and the Methylophilaceae in both aerobic conditions (Figures 2, 3). Both were more abundant in the +O2+NO3- microcosm and somewhat less abundant in the +O2-NO3microcosm, suggesting that both preferred higher nitrate concentrations for C1 metabolism. The low oxygen tension conditions selected against all methylotroph species. However, the Methylococcaceae still represented the majority of gammaproteobacterial sequences at the 90% cutoff level (Figure 2D). Overall, taxonomic profiling of metagenomes correlated well with pyrotag-based profiling both suggesting that Methylococcaceae and Methylophilaceae efficiently 11 11 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 Pre Prin ts Pre Prin ts consumed the 13C label from methane in aerobic conditions while the label distributed more evenly among multiple phyla in microaerobic conditions. Results of ordination analysis of dissimilarity of the five communities are shown in Supplemental Figure 1. Single gene-based taxonomic profiling supports data from whole-metagenome profiling 16S rRNA gene profiling in each microcosm was carried out (Tables 1, 3; Supplemental Table 1). For the metagenomes with significant sequence sampling (Table 1), the distribution of 16S rRNA genes among major phyla matched well those determined by the pyrotag sequencing approach, with some differences such as the reduced proportion of chloroplast sequences (data not shown), which is likely due to the low diversity of chloroplast sequences. Analysis of 16S rRNA gene sequences revealed that only in the aerobic microcosms did methylotroph sequences make up a significant fraction of total 16S rRNA gene sequences (26.3 to 31.8%, respectively, in the +O2-NO3- and the +O2+NO3- conditions; Table 1). In the microaerobic conditions and in the unamended sample, the methylotroph 16S rRNA gene fraction made up approximately 4% of the total 16S rRNA sequences. The methylotroph sequences represented three major families, Methylococcaceae, Methylocystaceae and Methylophilaceae. Within each family, a variety of phylotypes were detected suggesting complex community composition within each class. While the Methylococcaceae sequences were most numerous in each microcosm (50 to 100% of the methylotroph 16S rRNA sequences), including the unamended sample, shifts in phylotype composition occurred in response to different incubation conditions. The +O2+NO3microcosm was characterized by relatively low diversity of Methylococcaceae, with sequences closely related to those of the characterized Methylobacter species being most numerous (Table 3 and Supplemental Table 1). The diversity of Methylophilaceae and Methylocystaceae was also low in this microcosm. Community diversity in the +O2-NO3- microcosm was somewhat higher, and most of the Methylococcaceae sequences were novel sequences that could not be affiliated with any described Methylococcaceae. The Methylophilaceae sequences were also most 12 12 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 Pre Prin ts Pre Prin ts diverse in this microcosm, including unclassified Methylophilaceae. In the -O2-NO3- microcosm, only two methylotroph sequences were detected, both Methylococcaceae, while both Methylococcaceae and Methylophilaceae were detected in the -O2+NO3- microcosm. The diversity of methane oxidizing bacteria was further assessed by profiling genes encoding subunits of both particulate (pmo) and soluble (mmo) methane monooxygenase enzymes. Profiling of the pmoB genes (the largest and the less conserved of the pmo genes) revealed significant diversity at the genus level suggesting the presence of at least five identifiable genera within Methylococaceae and two genera within Methylocystaceae (Table 4), with an exception of the -O2-NO3- microcosm in which no pmoB genes were detected. The Methylocystaceae sequences were only detected in the aerobic microcosms, in agreement with the 16S rRNA gene profiling data. Once again, shifts in relative presence of different phyla were noted suggesting community dynamics in response to variable oxygen tensions and nitrate presence. The lowest phylotype diversity was observed for the -O2+NO3- condition, where only two methanotroph phylotypes were detected, Methylobacter and Methylovulum. In the aerobic microcosms, along with identifiable phylotypes, novel phylotypes of Methylococaceae were present, making up a significant proportion of the population. In the -O2+NO3- microcosm as well as in the unamended sample, pmo sequences were also identified belonging to the NC10 phylum, but in each case these constituted a minor proportion of the population. Very few mmo genes were detected in the metagenomes (Supplemental Table 2), suggesting that most of the active methane oxidizers were devoid of soluble methane monooxygenase. Genes encoding formaldehyde activating enzymes (fae) were profiled to evaluate the communities possessing formaldehyde oxidation potential. As expected, the diversity of fae genes/proteins extended beyond the bona fide methylotroph species (Table 5) and included Planctomycetes, Archaea, Burkholderiales as well as unclassified bacteria whose ability to oxidize or assimilate C1 compounds is unknown. The highest diversity of Fae was observed in the unamended sample and in the +O2-NO3- microcosm. In the latter, however, the 13 13 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 Pre Prin ts Pre Prin ts non-methylotroph sequences made up a very minor proportion of total sequences while in the former they made up 30.3% of total sequences. In the enriched microcosms, with the exception of the -O2+NO3- condition, the majority of sequences were classified as belonging to Methylococcaceae and Methylophilaceae. The Methylocystaceae sequences were only prominently present in the +O2-NO3- microcosms. Only in the -O2+NO3- microcosm, the bona fide methylotroph fae genes constituted a relatively minor fraction of the total, with the dominant type being the planctomycete type. While Planctomycetes typically encode Fae and other functions of the tetrahydromethanopterin-linked formaldehyde oxidation pathway, methylotrophy has not been demonstrated in these species, and their genomes lack recognizable genes for methane oxidation or methanol oxidation functions (Chistoserdova, 2011b). The Methylococcaceae were most prominently represented by the Methylobacter and Methylomonas-like sequences, while within Methylophilaceae, the Methylotenera sequences were most prominent. Overall, the community structure predictions as deduced from Fae analysis agreed with other analyses (16S rRNA gene, pmoB and mmoX genes and other methylotrophy genes, not shown). Methanol is the primary product of methane oxidation, and thus methanol dehydrogenase is an essential enzyme in the methane oxidation pathway (Anthony, 1982). In methanotrophs, this reaction is carried out by an enzyme encoded by mxaFI genes (Chistoserdova & Lidstrom, 2013). mxaFI genes are also essential in methanol oxidation by other groups of methylotrophs (Chistoserdova & Lidstrom, 2013). However, recently methylotrophs capable of methanol oxidation were described not possessing mxaFI genes, and in these, either mdh2 or xoxF genes have been implicated in this function (Chistoserdova & Lidstrom, 2013). Previous metagenomic analysis of Lake Washington populations suggested that the abundant Methylophilaceae phylotypes lacked mxaFI genes but possessed multiple copies of xoxF (Kalyuzhnaya et al., 2008). Genomes of both alpha- and gammaproteobacterial methanotrophs are also known to encode xoxF genes (Chistoserdova, 2011b). The 14 14 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 Pre Prin ts Pre Prin ts metagenomes generated in this study were specifically analyzed for the presence of mxaF and xoxF genes that classed in the families of Methylococcaceae, Methylocystaceae and Methylophilaceae, using high stringency BLAST searches (Supplemental Table 3). In each category, both types of genes were detected. As previously observed (Kalyuzhnaya et al., 2008), the Methylophilaceae populations appeared to be dominated by the types lacking mxaF. The Methyococcaceae xoxF genes also appeared to be more abundant compared to the mxaF genes with the exception of the +O2-NO3- microcosm. This may suggest either that some of the Methylococcaceae lack mxaF genes or that some of them contain multiple copies of xoxF genes. The diversity of genes for denitrification and relative abundance of genes belonging to key methylotroph groups (the Methylococcaceae, the Methylophilaceae and the Methylocystaceae) was evaluated by taxonomic profiling of the genes identified by the IMG/M platform as nitrate reductase, nitrite reductase, nitric oxide reductase or nitrous oxide reductase genes. For comparison, diversity and relative abundance of methylotroph nitrogenase genes were evaluated, revealing a significant phylogenetic complexity of the communities with a potential for denitrification (Table 6 and Supplemental Tables 4 - 8). We found that in the aerobic microcosms, the nitrogenase, nitrate reductase and nitrite reductase genes taxonomically ascribed to Methylococcaceae and primarily to the genus Methylobacter, were most abundant (Figure 4), suggesting that Methylobacter was the major species capable of both nitrogen fixation and denitrification in these conditions, as well as in the native sediment. Methylophilaceae-affiliated nitrate- and nitrite reductases represented another dominant class in the aerobic microcosms (Figure 4). The most abundant nitric oxide reductase type in these microcosms was classified as Methylophilaceae and most prominently Methylotenera, suggesting that most of Methylotenera species encode this step of the pathway while some of the Methylococcaceae represented in the metagenomes lack the respective gene. The phylotypes classified as Methylobacter were notably under-represented in this category 15 15 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 Pre Prin ts Pre Prin ts (Supplemental Table 6). No nitrous-oxide reductase genes were detected affiliated with either Methylococcaceae or Methylophilaceae suggesting that the denitrification pathway may be incomplete in these species. However, a number of sequences were classed with Methylocystaceae in the +O2-NO3- microcosm (Figure 4). Analysis of the nitrogenase genes demonstrated that Methylococcaceae and most prominently Methylobacter species were the major type possessing the potential for nitrogen fixation (up to 80% of total sequences), with a prominent presence of Methylocystaceae in the +O2-NO3- microcosm (Figure 4, Supplemental Table 8). The remaining sequences of the denitrification and nitrogen fixation genes were distributed evenly among a variety of phyla, and no other dominant groups or groups specifically responding to nitrate were detected (Supplemental Tables 4 - 8). figure legends : Figure 1. Schematic of experimental setup shows workflow, duration of each enrichment and actual DNA samples separated into heavy and light fractions. 32 32 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 Pre Prin ts Pre Prin ts Figure 2. Taxonomic profiling of microcosms based on pyrotag analysis (A and B) and metagenome data analysis (C and D) shows high abundance of Methylococcaceae and Methylophilaceae in aerobic conditions. A. Distribution of pyrotag sequences among major phyla. Other, phyla making up less than 1% of total. B. Proportions of Methylococcaceae and Methylophilaceae sequences in pyrotag libraries. C. Distribution of sequences in metagenomes taxonomically classified at 90% identity level. D. Proportions of Methylococcaceae, Methylophilaceae and Methylocystaceae of total sequences taxonomically profiled at 90% identity level. Figure 3. Abundances of the Methylococcaceae and the Methylophilaceae sequences as per cent of total taxonomically classified sequences show good correlation. Figure 4. Relative abundance of nitrate metabolism genes ascribed to Methylococcaceae (blue), Methylophilaceae (red) and Methylocystaceae (green). Other (purple) represents a variety of phylotypes, including methylotrophs of other families, present at low abundances. See Supplemental Tables 4-8 for statistics. 33 33 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 Pre Prin ts Pre Prin ts Pre Prin ts Pre Prin ts Pre Prin ts Pre Prin ts Pre Prin ts Pre Prin ts Pre Prin ts Pre Prin ts Pre Prin ts Pre Prin ts acknowledgements : This research was supported by the National Science Foundation (grants MCB-0604269 and MCB-0950183) and the Department of Energy (grant DE-SC0005154). This work was facilitated through the use of advanced computational, storage, and networking infrastructure provided by the Hyak supercomputer system, supported in part by the University of Washington eScience Institute. The work conducted by the U.S. Department of Energy Joint Genome Institute was supported by the Office of Science of the U.S. Department of Energy under contract no. DE-AC02-05CH11231. 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Biochemical Society Transactions 39: 243-248. 27 27 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 Pre Prin ts Pre Prin ts Table 1. Sequencing, assembly, metagenome and pyrotag statistics Unamended +O2-NO3- +O2+NO3- -O2-NO3- -O2+NO3Number of raw metagenome reads (median read length) 1,644,561 (415) 1,601,297 (469) 342,227 (435) 206,554 (332) 1,446,627 (457) Size (base pairs) 559,537,102 308,706,277 80,246,742 59,711,589 354,011,745 DNA scaffolds 1,515,849 835,955 193,120 194,103 925,371 Number of contigs in the assembly 9,658 19,257 8,470 573 4,087 Number of bp in assembled contigs 7,058,808 12,145,462 7,540,157 326,365 2,187,627 N50 contig length, bp 985 803 1,459 935 802 Mean coverage of assembled contigs 3.9 3.4 5.7 5.1 3.8 Genes 1,554,721 821,124 216,380 160,657 948,029 Proteins 1,547,567 817,673 215,668 159,899 943,870 RNA genes 7,154 3,451 712 758 4,159 16S rRNA genes 488 211 22 59 273 16S rRNA genes curated (methylotroph genes) 458 (19) 186 (49) 22 (7) 50 (2) 261 (11) Raw pyrotag sequences (median read length) 21,348 (471) 6,457 (403) 27,720 (479) 16,364 (367) 27,714 (475) Pyrotag gene clusters 1,486 313 709 561 1,386 Pyrotag diversity index (Shannon\u2013Weaver ) 4.10 3.84 2.40 3.94 4.01 COG clusters 4,494 4,246 3,639 3,652 4,313 Pfam clusters 5,788 5,199 3,822 3,861 5,157 pmoB genes 31 106 30 0 9 fae genes 62 157 38 3 13 Nitrate reductase 902 634 224 44 523 28 28 697 Pre Prin ts Pre Prin ts genes Genome Unamended +O2-NO3- +O2+NO3- -O2-NO3- -O2+NO3Methylococcacea e Methylobacter 47.7/ 60.6 50.9/ 64.0 47.2/ 64.8 35.0/58.1 36.4/ 74.3 Crenothrix 30.0/ 30.1 19.4/17.5 12.7/ 5.2 38.5/31.0 36.2/ 19.0 Methylomonas 10.8/ 4.3 14.6/ 10.2 20.2/ 19.8 10.9/6.2 10.4/ 3.4 Methylomicrobium 7.4/ 3.8 11.4/ 7.5 17.6/ 10.1 9.1/4.0 8.0/ 2.9 Methylocaldum 2.3/ <1 2.3/ <1 1.5/ 1.2 3.9/<1 5.6/ <1 Methylococcus 1.5/ <1 1.4/ <1 <1/ <1 2.7/<1 3.4/ <1 Methylocystaceae Methylocystis 67.0/ 89.6 65.2/ 63.3 90.2/ 95.8 71.4/88.9 74.4/ 90.2 Methylosinus 33.0/ 10.4 34.8/ 36.7 9.8/ 4.2 28.6/11.1 25.6/ 9.8 Methylophilaceae Methylotenera versatilis 41.7/ 56.3 41.1/ 65.9 41.2/ 64.4 32.6/52.0 25.8/ 48.3 Methylotenera mobilis 21.5/ 24.8 21.1/ 17.7 41.5/ 28.2 21.6/25.0 26.3/ 35.4 Methylovorus 16.2/ 5.1 16.3/ 4.8 5.4/ <1 17.8/9.7 19.4/ 3.3 Methylobacillus 9.7/ 3.2 8.5/ 2.4 2.1/ <1 12.7/4.6 13.7/ 2.9 Methylophilus 3.4/ 2.3 2.9/ 1.8 2.4/ <1 6.3/2.6 4.9/ 2.0 Unclassified Methylophilaceae 7.0/ 7.9 9.7/ 7.3 7.3/ 5.1 8.5/6.1 8.7/ 7.8 Marine Methylophilaceae <1/ <1 <1/ <1 <1/ <1 <1/0 1.2/ <1 698 699 700 701 Pre Prin ts Pre Prin ts Methylosarcina 11.0 9.0 Methylomicrobium 50 Methylosoma 8.0 Unclassified Methylococcaceae 26.0 26.0 discussion : The metagenomic approaches, including \u2018functional metagenomics\u2019 allow glimpses into the content of natural microbial communities, including uncultivated species, along with understanding their most prominent activities in global elemental cycles (Chistoserdova, 2010; Morales & Holben, 2011). We have previously employed a \u2018high-resolution\u2019 metagenomics approach to communities inhabiting freshwater sediment using stable isotope probing (SIP), in order to specifically target populations involved in utilization of single carbon compounds with a few notable outcomes (Kalyuzhnaya et al., 2008). In this previous work we uncovered a dominant presence of Methylobacter species as part of the bacterial community actively consuming methane in this environment, in contrast to the results from cultivated methanotroph species (Auman et al., 2000). We also discovered a prominent presence of novel Methylophilaceae species that were classed into a separate, novel genus, Methylotenera (Kalyuzhnaya et al., 2006). These species appeared to be active in consuming a variety of C1 substrates, most notably methylamine, methanol and methane (Kalyuzhnaya et al., 2008). As we were able to cultivate Methylotenera species at the same time (Kalyuzhnaya et al., 2006; 16 16 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 Pre Prin ts Pre Prin ts 2012), another contradiction arose: as expected for members of the Methylophilaceae (Anthony 1982), these species contained no genes that would encode methane oxidation functions. No genes for a typical (MxaFI) methanol dehydrogenase were present in these organisms (Lapidus et al., 2011). How then could they successfully compete for carbon from either methane or methanol with other species that possess the traditional enzymes for such types of metabolism? One other notable discovery was the persistent presence of genes for the denitrification pathway in Methylotenera species, suggesting a potential connection between methylotrophy and denitrification and a potential for electron acceptor alternatives to oxygen (Kalyuzhnaya et al., 2008). However, in the laboratory the cultivated Methylotenera species revealed very low potential for methanol metabolism (Kalyuzhnaya et al., 2006; 2012). However, further experiments with in situ populations using labeled methanol, varying tensions of oxygen and varying presence of nitrate have confirmed that the Methylophilaceae, and most prominently the Methylotenera species, must be the major methanol utilizers in Lake Washington (Kalyuzhnaya et al., 2009). XoxF, a homolog of the traditional methanol dehydrogenase (large subunit) was proposed as a gene involved in methanol oxidation (Beck et al., 2011), supported by high expression of these genes in in situ conditions (Kalyuzhnaya et al., 2010). In this work, we pursued three major objectives: determining what, if any, guilds beyond Methylococcaceae and Methylocystaceae were involved in methane oxidation in freshwater lakes, whether Methylophilaceae were involved in this process, and if the presence of nitrate had an effect on methane-oxidizing communities. We demonstrate that the known methanotroph guilds, Methylococcaceae and Methylocystaceae appear to be the major responders to the methane stimulus in aerobic microcosm incubations. More specifically, the Methylococcaceae and species belonging to or related to the genus Methylobacter are both the dominant species in the natural environment as well as the dominant responders to methane and to nitrate in aerobic conditions. While sequences of the recently described methanotroph guild NC10 that carries out methane oxidation anaerobically and links it to nitrite or nitrate (Wu et al., 2012) were 17 17 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 Pre Prin ts Pre Prin ts detected in all samples, these were minor members of the community, and no response to methane or nitrate was observed. Even though the abundance of Methylococcaceae sequences in microaerobic microcosms was much lower compared to both aerobic microcosms and to the unamended sample, they significantly outnumbered the NC10 sequences. No other phylum revealed a pattern suggesting involvement in methane oxidation, and no novel methane monooxygenase genes were detected, suggesting that in both aerobic and microaerobic conditions methane was metabolized by the methanotrophs traditionally called \u2018aerobic methane oxidizers\u2019 (Chistoserdova & Lidstrom, 2013). Methanotrophs of the family Methylococcaceae revealed a pronounced positive response to the addition of nitrate in aerobic conditions. However, these organisms do not appear to encode a complete respiratory denitrification pathway and likely use nitrate and nitrite reductases for assimilating nitrogen. Most if not all of these organisms also encode nitrogenases. The Methylocystaceae that constitute a smaller population in Lake Washington sediment also positively responded to methane but not to nitrate, in aerobic conditions, but they were almost undetectable in microaerobic conditions. The only non-methanotroph guild that responded to methane and nitrate stimuli was the Methylophilaceae, of which Methylotenera species were the most prominent in the datasets analyzed. Moreover, the response pattern of the Methylophilaceae correlated well with the pattern of the Methylococcaceae in aerobic conditions, suggesting a potential cooperation between the two groups at ambient oxygen tension. On the contrary, at low oxygen tension, and especially in the presence of nitrate, high community diversity, including the diversity of the denitrification genes, was observed, suggesting cross-feeding from labeled metabolites originating from the methanotrophs, even though the latter were present at a low population level. The nature of the cooperation between the Methylococcaceae and the Methylophilaceae is not obvious. It could be suggested that the methane oxidizers release methanol as a result of high activity of methane monooxygenase, and that the Methylophilaceae consume this 18 18 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 Pre Prin ts Pre Prin ts methanol, quickly incorporating it into their biomass. However, the dominant population of the Methylophilaceae enriched in the methane-fed microcosms appears to be most closely related to Methylotenera versatilis, cultivated representatives of which grow poorly if at all on methanol and lack bona fide (MxaFI) methanol dehydrogenase (Kalyuzhnaya et al., 2012). On another hand, multiple guilds that are known to be robust methanol oxidizers, such as Methylobacteriaceae, Hyphomicrobiaceae, Xanthobacteriaceae, as well as methanol-oxidizing Methylophilaceae (Methylovorus, Methylophilus) are minor members of the enriched communities. The Methylophilaceae could be involved in detoxification of nitrogen species to some of which, most notably ammonia, Methylococcaceae are known to be sensitive (Nyerges & Stein, 2009). However, in this case it is difficult to explain why Methylophilaceae are more successful than other species active in nitrogen metabolism. The same argument would be appropriate if a non-specific cross-feeding (for example on metabolites resulting from lysis of the Methylococcaceae) is suggested. The analyses presented here suggest that methanotrophs known as \u2018aerobic\u2019 methanotrophs appear to be responsible for metabolizing methane in both aerobic and microaerobic conditions, even though they appear not to be as efficient at low oxygen tension as they are at high oxygen tension. The Methylophilaceae appear to be involved in methane oxidation in the aerobic conditions but not in microaerobic conditions, suggesting that the methanotrophs, dependent on the specific environmental circumstances, may engage in different types of partnerships, involving either a very specialized guild such as methylotrophs of the family Methylophilavceae or a diverse group of heterotrophs with versatile metabolic repertoires. a metagenomic insight into freshwater methane-utilizing communities and evidence for : cooperation between the Methylococcaceae and the Methylophilaceae David A.C. Beck, Department of Chemical Engineering and eScience Institute, University of Washington, Seattle, WA, USA Marina G. Kalyuzhnaya, Department of Microbiology, University of Washington, Seattle, WA, USA Stephanie Malfatti, Lawrence Livermore National Laboratory, Livermore, CA, USA and DOE Joint Genome Institute, Walnut Creek, CA, USA Susannah G. Tringe, DOE Joint Genome Institute, Walnut Creek, CA, USA Tijana Glavina del Rio, DOE Joint Genome Institute, Walnut Creek, CA, USA Natalia Ivanova, DOE Joint Genome Institute, Walnut Creek, CA, USA Mary E. Lidstrom, Departments of Chemical Engineering and Microbiology, University of Washington, Seattle, WA, USA Ludmila Chistoserdova, Department of Chemical Engineering, University of Washington, Seattle, WA, USA Corresponding author: Ludmila Chistoserdova, Benjamin Hall IRB Room 454, 616 NE Northlake Place, Seattle WA 98105, phone 2066161913, e-mail milachis@uw.edu 1 1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Pre Prin ts Pre Prin ts conclusions : The well-characterized \u2018aerobic\u2019 methanotrophs and most prominently the Methylobacter species are responsible for metabolism of methane in Lake Washington sediment in both aerobic and microaerobic conditions. In aerobic conditions, some type of a cooperative behavior 19 19 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 Pre Prin ts Pre Prin ts between the Methylococcaceae, and most prominently the Methylobacter species is suggested by our data with the Methylophilaceae species, among which the Methylotenera species are most prominent. The nature of this type of cooperation remains unknown and requires a separate investigation. Both functional groups respond positively to the addition of nitrate. However, their ability to carry out classic respiratory denitrification is unlikely, as is a direct metabolic linkage between methane oxidation and denitrification. It is more likely that nitrate stimulates the methylotroph communities as a nutrient. methylocystaceae : Methylocystis 4.0 Methylosinus 4.0 29.0 Methylophilaceae Methylotenera 12.0 14.0 9.0 Methylovorus 11.0 10.0 9.0 Methylobacillus 5.0 2.0 9.0 Methylophilus 4.0 Unclassified Methylophylaceae 5.0 16.0 18.0 Table 4. PmoB* diversity. Sum in each column equals 100%. Genus/Family Unamended +O2-NO3- +O2+NO3- -O2-NO3- -O2+NO3Methylobacter 32.0 11.5 33.0 45.0 Methylovulum 19.0 19.0 7.0 45.0 Methylomonas 10.0 5.5 23.0 Methylomicrobium 7.0 1.0 10.0 Methylocaldum 1.0 Unclassified Methylococcaceae 29.0 37.5 20.0 Methylocystis 14.0 7.0 Methylosinus 5.5 Unclassified Methylocystaceae 4.0 NC10 3.0 1.0 10.0 *PmoB is the alpha subunit of the particulate methane monooxygenase 30 30 702 703 704 705 706 707 708 709 Pre Prin ts Pre Prin ts Table 5. Fae* diversity. Sum in each column equals 100%. Taxon Unamended +O2-NO3- +O2+NO3- -O2-NO3- -O2+NO3Methylococcacea e Methylobacter 27.0 10.8 21.0 100 7.7 Methylomicrobium 1.6 2.0 Methylomonas 8.0 11.0 16.0 7.7 Unclassified Methylococcaceae 6.4 9.5 Methylocystis 6.3 Methylosinus 1.6 9.5 5.0 Unclassified Methylocystaceae 2.0 methylophilaceae : Methylotenera versatilis 4.8 23.0 34.0 Methylotenera mobilis 1.6 10.8 13.0 15.4 Methylovorus 11.3 9.0 8.0 7.7 Methylobacillus 0.8 0.7 Unclassified Methylophilaceae 6.5 1.3 other : Burkholderiales 8.0 0.7 15.4 Unclassified Proteobacteria 3.2 1.3 Unclassified 1.6 3.0 Planctomycetes 6.4 0.7 30.7 NC10 1.6 LW phylum 1.6 0.7 7.7 Archaea 8.0 0.7 7.7 *Fae is formaldehyde activating enzyme 31 31 710 711 712 713 714 715 716 717 Pre Prin ts Pre Prin ts Table 6. Relative abundance and diversity of nitrate metabolism genes. Phylotypes are defined as unique taxon IDs assigned by BLAST to nr. Microcosm/ protein Total phylotypes Unamended +O2-NO3- +O2+NO3- -O2-NO3- -O2+NO3- Nitrate reductase 239 975a (0.37%) b 162 c 697 (0.44%) 116 259 (0.57%) 59 51 (0.24%) 33 541 (0.29%) 135 Nitrite reductase 207 454 (0.17%) 128 448 (0.28%) 94 167 (0.37%) 45 29 (0.13%) 24 225 (0.12%) 98 Nitric oxide reductase 118 200 (0.08%) 59 235 (0.15%) 49 135 (0.30%) 31 19 (0.09%) 18 121 (0.07%) 57 Nitrous oxide reductase 52 102 (0.04%) 32 75 (0.05%) 28 12 (0.026%) 6 15 (0.07%) 8 83 (0.05%) 25 Nitrogenase 66 172 (0.07%) 39 353 (0.22%) 30 123 (0.27%) 17 6 (0.03%) 4 45 (0.02%) 19 a Total number of genes annotated; b percent of total annotated enzymes; c number of phylotypes",
    "v2_text": "materials and methods 69 : Sample collection and stable isotope probing. Sediment samples were collected on March 70 3, 2009, from a 63 m deep station in Lake Washington, Seattle, Washington (47.038075\u2019 N, 71 122.015993\u2019 W) using a box core that allowed collection of undisturbed sediment. Samples 72 were transported to the laboratory on ice and immediately used to set up microcosms. Each 73 microcosm contained 50 ml of the top layer (1 cm) of the sediment and 50 ml of Lake 74 Washington water filtered through 0.22 \u00b5m filters (Millipore). Some of the samples (see below) 75 Pre Prin ts Pre Prin ts were supplemented with 10 mM KNO3. Samples were placed into 250 ml glass vials (6 vials per 76 experiment) and these were sealed with rubber stoppers. To mimic aerobic conditions, natural 77 atmosphere was maintained in those flasks. To mimic microarobic conditions, flasks were 78 flushed with nitrogen for 15-20 min. 50 ml of 13CH4 (99 atom % 13C, Sigma-Aldrich) was injected 79 into the headspace of each vial using a syringe, and vials were incubated at 100C for 10 80 (+O2+NO3- condition), 15 (+O2-NO3- condition), 20 (-O2+NO3- condition) or 30 days (-O2-NO3- 81 condition). The different incubation times were determined empirically by observing the 82 formation of a heavy, 13C-enriched DNA fraction. DNA was extracted as described previously 83 (Beck at al., 2011) with one modification as follows: DNA samples were subjected to an 84 additional round of purification using UltraClean\u00ae Mega Soil DNA Isolation Kit (MOBIO). The 85 heavy (13C-) and light (12C-) fractions of DNA preparations were separated by CsCl-ethidium 86 bromide density gradient ultracentrifugation, visualized under UV, and collected and purified 87 following standard procedures as previously described (Neufeld et al., 2007). DNA from an 88 untreated sediment sample was extracted using the same protocol. This sample was not 89 subjected to density gradient centrifugation. 90 91 DNA sequencing and assembly. Five shotgun libraries were constructed, one from each 92 microcosm. The libraries were sequenced using the 454 sequencing technology at the Joint 93 Genome Institute (JGI) Production Genomics Facility. A total of 5,241,266 reads comprising 94 1.67 gigabases (Gb) of sequence were generated. These were assembled using the Newbler 95 assembler. Assembly statistics are shown in Table 1. 96 97 Pyrotag sequencing. Pyrotag sequencing and data analysis were carried out at the JGI as 98 previously described (Kunin & Hugenholtz, 2010). 99 100 Metagenome analysis. The draft quality assemblies were processed using the IMG/M pipeline 101 Pre Prin ts Pre Prin ts (Markowitz et al., 2012) and the outputs of these automated analyses were manually verified 102 and used for metagenome profiling. 103 104 Single gene profiling. To classify the 16S rRNA gene sequences in the metagenomes, the 105 16S genes annotated as such by JGI pipeline were aligned against the Ribosomal Database 106 Project (RDP) version 10, release 26. The top scoring alignment for each sequence was used to 107 assign taxonomiy, based on the annotations in the RDP. Genes were classified to the family 108 level. 109 To detect pmoB and mmoX genes, respective peptides representing Methylococcaceae 110 and Methylocystaceae were obtained from public databases and used as queries in pBLAST 111 analyses against each dataset, and all matches were recorded. These queries pick each other 112 and also the NC10 sequences. All matches were profiled by matching to sequences in public 113 databases using pBLAST. Genus level assignments were made using an 80% identity cutoff 114 level, based on known diversity within each family, and family level assignments were made at 115 70% identity cutoff. 116 To detect fae genes, respective peptides representing Methylococcaceae, 117 Methylocystaceae, and Methylophilaceae were obtained from public databases and used as 118 queries in pBLAST analyses against each dataset, and all matches were recorded. These 119 queries pick each other, other proteobacterial sequences as well as NC10, planctomycete and 120 unclassified sequences. Genus and family level assignments were done as above. 121 For the nitrogen metabolism genes, sequences were selected by their annotation and 122 aligned against the NCBI's nonredundant database (nt). The top scoring hit for each sequence 123 was saved. The NCBI taxon ID was extracted and the NCBI taxonomy database queried to 124 collect the 'scientific name' of each hit. The count of hits for each 'scientific name' were reported. 125 The following annotation search terms were used: 1. 'itrate reductase' for NO3- reductase, 2. 126 'itrite reductase' for NO2 reductase, 3. 'itric[ -]oxide reductase' for NO reductase, and 4. 127 Pre Prin ts Pre Prin ts 'itrogenase' for nitrogenase. The first letter was omitted to avoid conflicts with upper and lower 128 case letters and in the case of NO reductase, both annotations with a '-' and ' ' separating the 129 nitric and oxide were accepted. 130 To classify mxaF and xoxF genes belonging to specific methylotroph families, high 131 stringency BLASTp analyses were applied using 90% identity level cutoff at the protein level 132 and employing publically available sequences of the respective enzymes representing the 133 respective phylogenetic groups. 134 135 Results 136 Experimental setup and duration of microcosm incubations 137 In order to assess populations active in methane oxidation under different oxygen tensions 138 and to test for their potential dependence on the presence of nitrate we set up microcosm 139 incubations as follows. One microcosm was incubated in an atmosphere of 50% 13C-labeled 140 methane and 50% ambient air, to assess the populations active in aerobic methane oxidation 141 (the +O2-NO3- condition); the second microcosm was incubated in an atmosphere of 50% 13C-142 methane and 50% ambient air, in the presence of 10 mM KNO3, to assess the populations 143 active in aerobic methane oxidation positively responding to the presence of nitrate (the 144 +O2+NO3- condition); the third microcosm was incubated in an atmosphere of 50% 13C-methane 145 and 50% N2, to assess the populations active in anaerobic/microaerobic methane oxidation (the 146 -O2-NO3- condition); the fourth microcosm was incubated in an atmosphere of 50% 13C-methane 147 and 50% N2, in the presence of 10 mM KNO3, to assess the populations active in 148 anaerobic/microaerobic methane oxidation positively responding to the presence of nitrate (the -149 O2+NO3- condition). 13C-labeled DNA was then separated from the unlabeled DNA by isopycnic 150 centrifugation and subjected to sequencing (see Materials and Methods). It took 10 days for 151 heavy DNA band to appear in the +O2+NO3- microcosm, compared to 15 days for the +O2+NO3- 152 microcosm, suggesting that the methane-consuming community was stimulated by nitrate. It 153 Pre Prin ts Pre Prin ts took much longer for heavy DNA band to appear in the microaerobic microcosms (20 and 30 154 days, respectively, for nitrate-amended and nitrate-free conditions). These data suggest that 155 nitrate also had a positive effect on methane consumption by the microbial community. 156 157 Pyrotag profiling of community DNA 158 We used 454 pyrotag sequencing of the V8 hypervariable region of the 16S rRNA gene to 159 determine the compositions of microbial communities in the four 13C-enriched metagenomes, 160 and we compared these to the community composition in the original (unamended) lake 161 sediment sample. As expected, the non-enriched community revealed the most complexity, 162 being represented by a total of 1,486 sequence clusters (97% sequence identity; Kunin and 163 Hugenholtz, 2010). The community was dominated by Proteobacteria (33.3%), of which 164 phylotypes of the Methylococcaceae family that represents one class (called type I) of methane 165 oxidizing bacteria were most prominently present (10% of all sequences). The second most 166 dominant group was represented by chloroplast sequences (21.9%). Other prominently present 167 phyla were Bacteroidetes (10.5%), Acidobacteria (7.2%) and Chloroflexi (4.0%; Figure 1). The 168 phylogenetic complexity of the 13C-enriched metagenomes representing three of the enrichment 169 conditions (the +O2-NO3- condition, the +O2+NO3- condition, and the -O2-NO3- condition) was 170 significantly reduced compared to the non-enriched community (313, 709 and 561 sequence 171 clusters, respectively), and different shifts in phyla distribution occurred in these communities. 172 The proportion of proteobacterial sequences increased in the aerobic communities (to 49.7% 173 and to 82.0%, respectively, in +O2-NO3- and in +O2+NO3- conditions; Figure 1A). In both cases 174 phylotypes classified as the Methylococcaceae and the Methylophilaceae were most 175 prominently present (10.9% and 14.9% of all sequences in the +O2-NO3- condition and 56.5% 176 and 10.5% of all sequences in the +O2+NO3- condition, respectively; Figure 1B). The proportion 177 of Proteobacteria decreased (to 13.2%) in the -O2-NO3- condition, the dominant phylotypes 178 being the chloroplast and the Bacteroidetes phylotypes (34.0% and 9.5% of total sequences, 179 Pre Prin ts Pre Prin ts respectively), while the Methylococcaceae and the Methylophilaceae phylotypes constituted 180 only a minor fraction of all sequences (0.03% and 0.9%, respectively). The proportion of 181 proteobacterial phylotypes and the overall make up of the community of the -O2+NO3- condition, 182 at the phylum level, resembled that of the non-enriched community (Figure 1B). However, the 183 Methylococcaceae phylotypes were less represented (4.0% of total sequences) while other 184 proteobacterial phylotypes (such as Burkholderiales) were more represented than in the non-185 enriched community. Phylotypes representing other bona fide methylotroph taxa, including 186 members of the Methylocystaceae and Bejerinckiaceae that represent the second class (called 187 type II) of methane oxidizers and members of the recently described NC10 phylum implicated in 188 anaerobic methane oxidation linked to denitrification (Wu et al., 2012) were detected in all five 189 pyrotag libraries. However, their proportions were very small, not exceeding 0.5% of the total 190 community in each case. 191 192 Metagenome analysis 193 Phylogenetic profiling 194 A total of 1,362,213,455 base pairs (1.36 Gb) of assembled sequence were generated. Genes 195 were called using the standard JGI IMG/M pipeline (Markowitz et al., 2012), and each gene was 196 taxonomically classified by using its best BLAST hit in the current genomic database employed 197 by the IMG/M interface (4418 bacterial genomes and 176 archaeal genomes (sequencing and 198 assembly statistics are shown in Table 1). For phylogenetic profiling, we considered separately 199 all protein coding genes and genes classified at the 60% and the 90% cutoff levels (protein level 200 classification). While few genes were classified at the 90% cutoff (2.44 to 17.56% of the total, 201 dependent on the microcosm) these provide very robust proxies for the organisms represented 202 in the metagenomes, especially given the fact that genomes of key model methylotrophs were 203 parts of the database used for comparisons, including genomes originating from Lake 204 Washington (Lapidus et al., 2011, Kittichotirat et al., 2011 and unpublished). Thus we mostly 205 Pre Prin ts Pre Prin ts relied on the 90% cutoff classification for the confident sequence assignments, while realizing 206 that these provide the lowest estimate for the presence of a specific phylum. At the 60% cutoff 207 level, between 28.9% and 42.5% of the total genes could be classified, allowing for 208 encompassing species not represented in the databases by very closely related models. In 209 either case, most of the genes in each metagenome were taxonomically classified as 210 proteobacterial, with the absolute majority being matched to beta- and gammaproteobacteria 211 (up to 45.4% and up to 50.1% of genes at 90% cutoff level, respectively), the next abundant 212 group being alphaproteobacteria (up to 12.4% of genes at 90% cutoff level). The only exception 213 was the -O2-NO2- metagenome, in which, along with gamma- and betaproteobacteria, 214 Bacteroidetes and deltaproteobacteria sequences were prominent. Remarkably, most of the 215 gammaproteobacterial sequences (up to 84.2/98.4% at the 60/90% cutoff levels, dependent on 216 the microcosm) were classified as belonging to the Methylococcaceae family. Among 217 betaproteobacterial sequences, the largest proportion of sequences in the aerobic microcosms 218 (up to 53.6/88.4%) were classified as belonging to the Methylophilaceae family, while in the 219 microaerobic microcosms betaproteobacterial sequences were distributed between a number of 220 dominant families, which included Methylophilaceae, Comamonadaceae, Rhodocyclaceae and 221 Burkholderiaceae. Among the alphaproteobacterial sequences, those classified as belonging to 222 the Methylocystaceae family only constituted the highest proportion (48.6/81.3%) in the +O2-223 NO3- microcosm, but they were also abundant in the +O2+NO3- microcosm (13.0/30.1% of total 224 alphaproteobacterial sequences). In the remaining datasets, few alphaproteobacterial 225 sequences were classified as Methylocystaceae, with Bradyrhizobiaceae sequences being most 226 abundant. Similarly to the results of pyrotag analysis, sequences of other bona fide 227 methylotrophs (such as Methylobacteriaceae, Bejerinckiaceae, Xanthobacteriaceae, 228 Hyphomicrobiaceae) were identified in each metagenome. However, the proportions of the 229 genes assigned to each of these families were low, suggesting that these species were minor 230 members of the functional communities investigated. 231 Pre Prin ts Pre Prin ts Sequences assigned to each of the major methylotroph families, Methylococcaceae, 232 Methylophilaceae and Methylocystaceae, were further categorized at the genus level, by 233 matching each gene categorized to the family level to the available genomic scaffolds 234 representing each family, at 60 and 90% cutoff values. In these analyses, the 235 Methylococcaceae family was represented by a total of six genomes, of Methylobacter 236 tundripaludum (Svenning et al., 2011), Methylomonas sp. (unpublished), Methylomicrobium 237 album (unpublished), Methylocaldum szegediense (unpublished), Methylococcus capsulatus 238 (Ward et al., 2004) and Crenothrix polyspora (unpublished). In the case of the latter, we find the 239 claimed affiliation of this strain within a proposed new family of Chrenothrochaceae (Soecker et 240 al., 2006) invalid, based on high sequence similarity with the members of Methylococcaceae 241 (Iguchi, Yurimoto & Sakai, 2011), and thus we consider this organism as part of this family. Of 242 the six genomes, only one represented an organism originating from Lake Washington, the 243 Methylomonas sp. strain (unpublished data). The Methylocystaceae family was represented by 244 only two genomes, of Methylosinus trichosporium (Stein et al., 2010) and Methylocystis sp. 245 (Stein et al., 2011), none originating from Lake Washington. The Methylophilaceae family was 246 represented by eight genomes, of Methylotenera mobilis, Methylotenera versatilis, Methylovorus 247 glucosotrophus (Lapidus et al., 2011), Methylophilus sp., unclassified Methylophilaceae 248 (unpublished), Methylobacillus flagellatus (Chistoserdova et al., 2007), and of unclassified 249 Methylophilaceae strains HTCC8121 (Giovannoni et al., 2008) and KB13 (unpublished). Of 250 these, the first five strains originated from Lake Washington (Kalyuzhnaya et al., 2006; 251 Kalyuzhnaya et al., 2012 and unpublished) and the latter two were marine Methylophilaceae 252 with unusually small genomes (Giovannoni et al., 2008). All the genomes mentioned here as 253 \u2018unpublished\u2019 have been sequenced by the JGI and are publically available through the IMG/M 254 interface (http://img.jgi.doe.gov). From matching to this limited number of genomic scaffolds, the 255 Methylobacter species appeared to be the dominant type among the Methylococcaceae 256 representatives, the Methylocystis types appeared to dominate over the Methylosinus types, 257 Pre Prin ts Pre Prin ts and Methylotenera species appeared to be dominant among the Methylophilaceae. However, 258 specific dynamics could be observed at the genus level in response to different stimuli (Table 2). 259 The proportion of the Methylomonas and Methylomicrobium types increased in response to the 260 addition of methane, especially pronounced in the +O2+NO3- condition, while the proportion of 261 the \u2018Crenothrix\u2019 types decreased compared to unamended sediment. The Methylobacter types 262 were most dominant in the -O2 +NO3- condition. Dynamics were also clearly seen among the 263 Methylocystaceae, with the proportion of Methylosinus sequences upshifting in response to 264 methane in aerobic conditions and downshifting in response to nitrate, with respect to 265 Methylocystis sequences. The relative proportion of Methylotenera sequences among the 266 Methylophilaceae populations upshifted significantly in response to nitrate in aerobic conditions. 267 We were also able to distinguish between two different species within Methylotenera, M. mobilis 268 vs. M. versatilis, based on their significant divergence at the genomic level (Lapidus et al., 269 2011). While the proportion of M. versatilis-like sequences increased in the +O2+NO3- condition, 270 their proportion decreased in the -O2+NO3- condition, being replaced by the M. mobilis-like 271 sequences. Dynamics could also be seen among sequences classified as other 272 Methylophilaceae. Unsurprisingly, virtually no sequences were matched to the scaffolds 273 representing marine Methylophilaceae. 274 Phylogenetic profiling demonstrated a good correlation between the populations of the 275 Methylococcaceae and the Methylophilaceae in both aerobic conditions (Figures 1, 2), Both 276 were more abundant in the +O2+NO3- microcosm and somewhat less abundant in the +O2-NO3- 277 microcosm, suggesting that both preferred higher nitrate concentrations for C1 metabolism. The 278 low oxygen tension conditions selected against all methylotroph species. However, the 279 Methylococcaceae still represented the majority of gammaproteobacterial sequences at the 280 90% cutoff level (Figure 1D). Overall, phylogenetic profiling of metagenomes correlated well 281 with pyrotag-based profiling. 282 283 Pre Prin ts Pre Prin ts Single gene-based phylogenetic profiling 284 16S rRNA genes 285 16S rRNA gene profiling in each microcosm was carried out (Tables 1, 3). For the 286 metagenomes with significant sequence sampling, the distribution of 16S rRNA genes among 287 major phyla matched well those determined by the pyrotag sequencing approach, with some 288 differences such as the reduced proportion of chloroplast sequences (Supplemental Figure 1), 289 which is likely due to the low diversity of chloroplast sequences. Analysis of 16S rRNA gene 290 sequences revealed that only in the aerobic microcosms did methylotroph sequences make up 291 a significant fraction of total 16S rRNA gene sequences (26.3 to 31.8%, respectively, in the +O2-292 NO3- and the +O2+NO3- conditions; Table 1). In the microaerobic conditions and in the 293 unamended sample, the methylotroph 16S rRNA gene fraction made up approximately 4% of 294 the total 16S rRNA sequences. The methylotroph sequences represented three major families, 295 Methylococcaceae, Methylocystaceae and Methylophilaceae. Within each family, a variety of 296 phylotypes were detected suggesting complex community composition within each class. While 297 the Methylococcaceae sequences were most numerous in each microcosm, including the 298 unamended sample, shifts in phylotype composition occurred in response to different incubation 299 conditions. The +O2+NO3- microcosm was characterized by relatively low diversity of 300 Methylococcaceae, with sequences closely related to those of the characterized Methylobacter 301 species being most numerous. The diversity of Methylophilaceae and Methylocystaceae was 302 also low in this microcosm. Community diversity in the +O2-NO3- microcosm was somewhat 303 higher, and most of the Methylococcaceae sequences were novel sequences that could not be 304 affiliated with any described Methylococcaceae. The Methylophilaceae sequences were also 305 most diverse in this microcosm, including unclassified Methylophilaceae. In the -O2-NO3- 306 microcosm, only two methylotroph sequences were detected, both Methylococcaceae, while 307 both Methylococcaceae and Methylophilaceae were detected in the -O2+NO3- microcosm. 308 309 Pre Prin ts Pre Prin ts Methane monooxygenase genes 310 The diversity of methane oxidizing bacteria was further assessed by profiling genes 311 encoding subunits of both particulate (pmo) and soluble (mmo) methane monooxygenase 312 enzymes. Profiling of the pmoB genes (the largest and the less conserved of the pmo genes) 313 revealed significant diversity at the genus level suggesting the presence of at least five 314 identifiable genera within Methylococaceae and two genera within Methylocystaceae (Table 4), 315 with an exception of the -O2-NO3- microcosm in which no pmoB genes were detected. The 316 Methylocystaceae sequences were only detected in the aerobic microcosms, in agreement with 317 the 16S rRNA gene profiling data. Once again, shifts in relative presence of different phyla were 318 noted suggesting community dynamics in response to variable oxygen tensions and nitrate 319 presence. The lowest phylotype diversity was observed for the -O2+NO3- condition, where only 320 two methanotroph phylotypes were detected, Methylobacter and Methylovulum. In the aerobic 321 microcosms, along with identifiable phylotypes, novel phylotypes of Methylococaceae were 322 present, making up a significant proportion of the population. In the -O2+NO3- microcosm as well 323 as in the unamended sample, pmo sequences were also identified belonging to the NC10 324 phylum, but in each case these constituted a minor proportion of the population. Very few mmo 325 genes were detected in the metagenomes (Supplemental Table 2), suggesting that most of the 326 active methane oxidizers were devoid of soluble methane monooxygenase. 327 328 Fae gene diversity 329 Genes encoding formaldehyde activating enzymes (fae) were profiled to evaluate the 330 communities possessing formaldehyde oxidation potential. As expected, the diversity of fae 331 genes/proteins extended beyond the bona fide methylotroph species (Table 5) and included 332 Planctomycetes, Archaea, Burkholderiales as well as unclassified bacteria whose ability to 333 oxidize or assimilate C1 compounds is unknown. The highest diversity of Fae was observed in 334 the unamended sample and in the +O2-NO3- microcosm. In the latter, however, the non-335 Pre Prin ts Pre Prin ts methylotroph sequences made up a very minor proportion of total sequences while in the former 336 they made up 30.3% of total sequences. In the enriched microcosms, with the exception of the 337 -O2+NO3- condition, the majority of sequences were classified as belonging to 338 Methylococcaceae and Methylophilaceae. The Methylocystaceae sequences were only 339 prominently present in the +O2-NO3- microcosms. Only in the -O2+NO3- microcosm, the bona 340 fide methylotroph fae genes constituted a relatively minor fraction of the total, with the dominant 341 type being the planctomycete type. While Planctomycetes typically encode Fae and other 342 functions of the tetrahydromethanopterin-linked formaldehyde oxidation pathway, methylotrophy 343 has not been demonstrated in these species, and their genomes lack recognizable genes for 344 methane oxidation or methanol oxidation functions (Chistoserdova, 2011). The 345 Methylococcaceae were most prominently represented by the Methylobacter and 346 Methylomonas-like sequences, while within Methylophilaceae the Methylotenera sequences 347 were most prominent. Overall, the community structure predictions as deduced from Fae 348 analysis agreed with other analyses (16S rRNA gene, pmoB and mmoX genes and other 349 methylotrophy genes, not shown). 350 351 mxaF and xoxF genes 352 Methanol is the primary product of methane oxidation, and thus methanol 353 dehydrogenase is an essential enzyme in the methane oxidation pathway (Anthony, 1982). In 354 methanotrophs, this reaction is carried out by an enzyme encoded by mxaFI genes 355 (Chistoserdova & Lidstrom, 2013). mxaFI genes are also essential in methanol oxidation by 356 other groups of methylotrophs (Chistoserdova & Lidstrom, 2013). However, recently 357 methylotrophs capable of methanol oxidation were described not possessing mxaFI genes, and 358 in these, either mdh2 or xoxF genes have been implicated in this function (Chistoserdova & 359 Lidstrom, 2013). Previous metagenomic analysis of Lake Washington populations suggested 360 that the abundant Methylophilaceae phylotypes lacked mxaFI genes but possessed multiple 361 Pre Prin ts Pre Prin ts copies of xoxF (Kalyuzhnaya et al., 2008). Genomes of both alpha- and gammaproteobacterial 362 methanotrophs are also known to encode xoxF genes (Chistoserdova, 2011b). The 363 metagenomes generated in this study were specifically analyzed for the presence of mxaF and 364 xoxF genes that classed in the families of Methylococcaceae, Methylocystaceae and 365 Methylophilaceae, using high stringency BLAST searches (Supplemental Table 3). In each 366 category, both types of genes were detected. As previously observed (Kalyuzhnaya et al., 367 2008), the Methylophilaceae populations appeared to be dominated by the types lacking mxaF. 368 The Methyococcaceae xoxF genes appeared to also be more abundant compared to the mxaF 369 genes with the exception of the +O2-NO3- microcosm. This may suggest either that some of the 370 Methylococcaceae lack mxaF genes or that some of them contain multiple copies of xoxF 371 genes. 372 373 Diversity and abundance of nitrate metabolism genes 374 The diversity of genes for denitrification and relative abundance of genes belonging to 375 key methylotroph groups (the Methylococcaceae, the Methylophilaceae and the 376 Methylocystaceae) was evaluated by phylogenetic profiling of the genes annotated by the 377 IMG/M platform as nitrate reductase, nitrite reductase, nitric oxide reductase or nitrous oxide 378 reductase genes. For comparison, diversity and relative abundance of methylotroph nitrogenase 379 genes were evaluated, revealing a significant phylogenetic complexity of the communities with a 380 potential for denitrification (Table 6 and Supplementary Tables 4 - 8). We found that in the 381 aerobic microcosms, the nitrogenase, nitrate reductase and nitrite reductase genes 382 phylogenetically ascribed to Methylococcaceae and primarily to the genus Methylobacter, were 383 most abundant (Figure 3), suggesting that Methylobacter was the major species capable of both 384 nitrogen fixation and denitrification in these conditions, as well as in the native sediment. 385 Methylophilaceae-affiliated nitrate- and nitrite reductases represented another dominant class in 386 the aerobic microcosms (Figure 3). The most abundant nitric oxide reductase type in these 387 Pre Prin ts Pre Prin ts microcosms was classified as Methylophilaceae and most prominently Methylotenera, 388 suggesting that most of Methylotenera species encode this step of the pathway while some of 389 the Methylococcaceae represented in the metagenomes lack the respective gene. The 390 phylotypes classified as Methylobacter were notably under-represented in this category 391 (Supplemental Table 6). No nitrous-oxide reductase genes were detected affiliated with either 392 Methylococcaceae or Methylophilaceae suggesting that the denitrification pathway may be 393 incomplete in these species. However, a number of sequences were classed with 394 Methylocystaceae in the +O2-NO3- microcosm (Figure 3). Analysis of the nitrogenase genes 395 demonstrated that Methylococcaceae and most prominently Methylobacter species were the 396 major type possessing the potential for nitrogen fixation (up to 80% of total sequences), with a 397 prominent presence of Methylocystaceae in the +O2-NO3- microcosm (Figure 3, Supplemental 398 Table 8). The remaining sequences of the denitrification and nitrogen fixation genes were 399 distributed evenly among a variety of phyla, and no other dominant groups or groups specifically 400 responding to nitrate were detected (Supplemental Tables 4 -8). 401 402 Discussion 403 The metagenomic approaches, including \u2018functional metagenomics\u2019 allow glimpses into 404 the content of natural microbial communities, including uncultivated species, along with 405 understanding their most prominent activities in global elemental cycles (Chistoserdova, 2010; 406 Morales & Holben, 2011). We have previously employed a \u2018high-resolution\u2019 metagenomics 407 approach to communities inhabiting freshwater sediment using stable isotope probing (SIP), in 408 order to specifically target populations involved in utilization of single carbon compounds with a 409 few notable outcomes (Kalyuzhnaya et al., 2008). In this previous work we uncovered a 410 dominant presence of Methylobacter species as part of the bacterial community actively 411 consuming methane in this environment, in contrast to the results from cultivated methanotroph 412 species (Auman et al., 2000). We also discovered a prominent presence of novel 413 Pre Prin ts Pre Prin ts Methylophilaceae species that were classed into a separate, novel genus, Methylotenera 414 (Kalyuzhnaya et al., 2006). These species appeared to be active in consuming a variety of C1 415 substrates, most notably methylamine, methanol and methane (Kalyuzhnaya et al., 2008). As 416 we were able to cultivate Methylotenera species at the same time (Kalyuzhnaya et al., 2006; 417 2012), another contradiction arose: as expected for members of the Methylophilaceae (Anthony 418 1982), these species contained no genes that would encode methane oxidation. No genes for a 419 typical (MxaFI) methanol dehydrogenase were present in these organisms (Lapidus et al., 420 2011). How then could they successfully compete for carbon from either methane or methanol 421 with other species that possess the traditional enzymes for such types of metabolism? One 422 other notable discovery was the persistent presence of genes for the denitrification pathway in 423 Methylotenera species, suggesting a potential connection between methylotrophy and 424 denitrification and a potential for electron acceptor alternatives to oxygen (Kalyuzhnaya et al., 425 2008). However, in the laboratory the cultivated Methylotenera species revealed very low 426 potential for methanol metabolism (Kalyuzhnaya et al., 2006; 2012). However, further 427 experiments with in situ populations using labeled methanol, varying tensions of oxygen and 428 varying presence of nitrate have confirmed that the Methylophilaceae, and most prominently the 429 Methylotenera species, must be the major methanol utilizers in Lake Washington (Kalyuzhnaya 430 et al., 2009). XoxF, a homolog of the traditional methanol dehydrogenase (large subunit) was 431 proposed as a gene involved in methanol oxidation (Beck et al., 2011), supported by high 432 expression of these genes in in situ conditions (Kalyuzhnaya et al., 2010). 433 In this work, we pursued three major objectives: determining what, if any, guilds beyond 434 Methylococcaceae and Methylocystaceae were involved in methane oxidation in freshwater 435 lakes, whether Methylophilaceae were involved in this process, and if the presence of nitrate 436 had an effect on methane-oxidizing communities. We demonstrate that the known 437 methanotroph guilds, Methylococcaceae and Methylocystaceae appear to be the major 438 responders to the methane stimulus in aerobic microcosm incubations. More specifically, the 439 Pre Prin ts Pre Prin ts Methylococcaceae and species belonging to or related to the genus Methylobacter are both the 440 dominant species in the natural environment as well as the dominant responders to methane 441 and to nitrate in aerobic conditions. While sequences of the recently described methanotroph 442 guild NC10 that carries out methane oxidation anaerobically and links it to nitrite or nitrate (Wu 443 et al., 2012) were detected in all samples, these were minor members of the community, and no 444 response to methane or nitrate was observed. Even though the abundance of 445 Methylococcaceae sequences in microaerobic microcosms was much lower compared to both 446 aerobic microcosms and to the unamended sample, they significantly outnumbered the NC10 447 sequences. No other phylum revealed a pattern suggesting involvement in methane oxidation, 448 and no novel methane monooxygenase genes were detected, suggesting that in both aerobic 449 and microaerobic conditions methane was metabolized by the methanotrophs traditionally called 450 \u2018aerobic methane oxidizers\u2019 (Chistoserdova & Lidstrom, 2013). Methanotrophs of the family 451 Methylococcaceae revealed a pronounced positive response to the addition of nitrate in aerobic 452 conditions. However, these organisms do not appear to encode a complete respiratory 453 denitrification pathway and likely use nitrate and nitrite reductases for assimilating nitrogen. 454 Most if not all of these organisms also encode nitrogenases. The Methylocystaceae that 455 constitute a smaller population in Lake Washington sediment also positively responded to 456 methane but not to nitrate, in aerobic conditions, but they were almost undetectable in 457 microaerobic conditions. The only non-methanotroph guild that responded to methane and 458 nitrate stimuli was the Methylophilaceae, of which Methylotenera species were the most 459 prominent in the datasets analyzed. Moreover, the response pattern of the Methylophilaceae 460 correlated well with the pattern of the Methylococcaceae in aerobic conditions, suggesting a 461 potential cooperation between the two groups at ambient oxygen tension. On the contrary, at 462 low oxygen tension, and especially in the presence of nitrate, high community diversity, 463 including the diversity of the denitrification genes, was observed, suggested cross-feeding from 464 Pre Prin ts Pre Prin ts labeled metabolites originating from the methanotrophs, even though the latter were present at 465 a low population level. 466 The nature of the cooperation between the Methylococcaceae and the Methylophilaceae 467 is not obvious. It could be suggested that the methane oxidizers release methanol as a result of 468 high activity of methane monooxygenase, and that the Methylophilaceae consume this 469 methanol, quickly incorporating it into their biomass. However, the dominant population of the 470 Methylophilaceae enriched in the methane-fed microcosms appears to be most closely related 471 to Methylotenera versatilis, cultivated representatives of which grow poorly if at all on methanol 472 and lack bona fide (MxaFI) methanol dehydrogenase (Kalyuzhnaya et al., 2012). On another 473 hand, multiple guilds that are known to be robust methanol oxidizers, such as 474 Methylobacteriaceae, Hyphomicrobiaceae, Xanthobacteriaceae, as well as methanol-oxidizing 475 Methylophilaceae (Methylovorus, Methylophilus) are minor members of the enriched 476 communities. The Methylophilaceae could be involved in detoxification of nitrogen species to 477 some of which, most notably ammonia, Methylococcaceae are known to be sensitive (Nyerges 478 & Stein, 2009). However, in this case it is difficult to explain why Methylophilaceae are more 479 successful than other species active in nitrogen metabolism. The same argument would be 480 appropriate if a non-specific cross-feeding (for example on metabolites resulting from lysis of the 481 Methylococcaceae) is suggested. The analyses presented here suggest that methanotrophs 482 known as \u2018aerobic\u2019 methanotrophs appear to be responsible for metabolizing methane in both 483 aerobic and microaerobic conditions, even though they appear not to be as efficient at low 484 oxygen tension as they are at high oxygen tension. The Methylophilaceae appear to be involved 485 in methane oxidation in the aerobic conditions but not in microaerobic conditions, suggesting 486 that the methanotrophs, dependent on the specific environmental circumstances, may engage 487 in different types of partnerships, involving either a very specialized guild such as methylotrophs 488 of the family Methylophilavceae or a diverse group of heterotrophs with versatile metabolic 489 repertoires. 490 Pre Prin ts Pre Prin ts Conclusions 491 The well-characterized \u2018aerobic\u2019 methanotrophs and most prominently the Methylobacter 492 species are responsible for metabolism of methane in Lake Washington sediment in both 493 aerobic and microaerobic conditions. In aerobic conditions, some type of a cooperative behavior 494 is suggested with the Methylophilaceae species among which the Methylotenera species are 495 most prominent. The nature of this type of cooperation remains unknown and requires a 496 separate investigation. Both functional groups respond positively to the addition of nitrate. 497 However, their ability to carry out classic respiratory denitrification is unlikely, as is a direct 498 metabolic linkage between methane oxidation and denitrification. Thus the nature of the positive 499 effect of nitrate on methane-oxidizing communities is also a topic for future investigation. 500 501 502 503 504 Acknowledgements 505 This research was supported by the National Science Foundation (grants MCB-0604269 and 506 MCB-0950183) and the Department of Energy (grant DE-SC0005154). This work was facilitated 507 through the use of advanced computational, storage, and networking infrastructure provided by 508 the Hyak supercomputer system, supported in part by the University of Washington eScience 509 Institute. The work conducted by the U.S. Department of Energy Joint Genome Institute was 510 supported by the Office of Science of the U.S. Department of Energy under contract no. 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Biochemical Society Transactions 39: 243-248. 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 Pre Prin ts Pre Prin ts Table 1. Sequencing, assembly and metagenome statistics 698 Unamended +O2-NO3- +O2+NO3- -O2-NO3- -O2+NO3- Size (base pairs) 559,537,102 308,706,277 80,246,742 59,711,589 354,011,745 DNA scaffolds 1,515,849 835,955 193,120 194,103 925,371 Number of contigs in the assembly 9,658 19,257 8,470 573 4,087 Number of bp in assembled contigs 7,058,808 12,145,462 7,540,157 326,365 2,187,627 N50 contig length, bp 985 803 1,459 935 802 Mean coverage of assembled contigs 3.9 3.4 5.7 5.1 3.8 Genes 1,554,721 821,124 216,380 160,657 948,029 Proteins 1,547,567 817,673 215,668 159,899 943,870 RNA genes 7,154 3,451 712 758 4,159 16S rRNA genes 488 211 22 59 273 16S rRNA genes curated (methylotroph genes) 458 (19) 186 (49) 22 (7) 50 (2) 261 (11) Pyrotag gene clusters 1,486 313 709 561 1,386 Pre Prin ts Pre Prin ts COG clusters 4,494 4,246 3,639 3,652 4,313 Pfam clusters 5,788 5,199 3,822 3,861 5,157 pmoB genes 31 106 30 0 9 mmoX genes 1 18 3 0 0 Fae proteins 62 157 38 3 13 Nitrate reductase genes 902 634 224 44 523 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 Pre Prin ts Pre Prin ts Table 2. Relative distribution of genes classified at 60%/90% cutoff among different genera. 717 Sum of genes assigned to each family at each cutoff level equals 100%. 718 Genome Unamended +O2-NO3- +O2+NO3- -O2-NO3- -O2+NO3Methylococcaceae Methylobacter 47.7/ 60.6 50.9/ 64.0 47.2/ 64.8 35.0/58.1 36.4/ 74.3 Crenothrix 30.0/ 30.1 19.4/17.5 12.7/ 5.2 38.5/31.0 36.2/ 19.0 Methylomonas 10.8/ 4.3 14.6/ 10.2 20.2/ 19.8 10.9/6.2 10.4/ 3.4 Methylomicrobium 7.4/ 3.8 11.4/ 7.5 17.6/ 10.1 9.1/4.0 8.0/ 2.9 Methylocaldum 2.3/ <1 2.3/ <1 1.5/ 1.2 3.9/<1 5.6/ <1 Methylococcus 1.5/ <1 1.4/ <1 <1/ <1 2.7/<1 3.4/ <1 Methylocystaceae Methylocystis 67.0/ 89.6 65.2/ 63.3 90.2/ 95.8 71.4/88.9 74.4/ 90.2 Methylosinus 33.0/ 10.4 34.8/ 36.7 9.8/ 4.2 28.6/11.1 25.6/ 9.8 Methylophilaceae Methylotenera versatilis 41.7/ 56.3 41.1/ 65.9 41.2/ 64.4 32.6/52.0 25.8/ 48.3 Methylotenera mobilis 21.5/ 24.8 21.1/ 17.7 41.5/ 28.2 21.6/25.0 26.3/ 35.4 Methylovorus 16.2/ 5.1 16.3/ 4.8 5.4/ <1 17.8/9.7 19.4/ 3.3 Methylobacillus 9.7/ 3.2 8.5/ 2.4 2.1/ <1 12.7/4.6 13.7/ 2.9 Methylophilus 3.4/ 2.3 2.9/ 1.8 2.4/ <1 6.3/2.6 4.9/ 2.0 Unclassified Methylophilaceae 7.0/ 7.9 9.7/ 7.3 7.3/ 5.1 8.5/6.1 8.7/ 7.8 Marine Methylophilaceae <1/ <1 <1/ <1 <1/ <1 <1/0 1.2/ <1 Pre Prin ts Pre Prin ts Table 3. Distribution of 16S rRNA gene sequences among different genera (% of total 719 methylotroph sequences distributed among the three families). 720 Family/Genus Unamended +O2-NO3- +O2+NO3- -O2-NO3- -O2+NO3Methylococcaceae Methylobacter (\u226597%) 21.0 12.0 43.0 28.0 Methylobacter (95%) 21.0 2.0 14.0 50 18.0 Methylosarcina 11.0 9.0 Methylomicrobium 50 Methylosoma 8.0 Unclassified Methylococcaceae 26.0 26.0 Methylocystaceae Methylocystis 4.0 Methylosinus 4.0 29.0 Methylophilaceae Methylotenera 12.0 14.0 9.0 Methylovorus 11.0 10.0 9.0 Methylobacillus 5.0 2.0 9.0 Methylophilus 4.0 Unclassified Methylophylaceae 5.0 16.0 18.0 721 722 Pre Prin ts Pre Prin ts Table 4. PmoB diversity. Sum in each column equals 100%. 723 Genus/Family Unamended +O2-NO3- +O2+NO3- -O2-NO3- -O2+NO3Methylobacter 32.0 11.5 33.0 45.0 Methylovulum 19.0 19.0 7.0 45.0 Methylomonas 10.0 5.5 23.0 Methylomicrobium 7.0 1.0 10.0 Methylocaldum 1.0 Unclassified Methylococcaceae 29.0 37.5 20.0 Methylocystis 14.0 7.0 Methylosinus 5.5 Unclassified Methylocystaceae 4.0 NC10 3.0 1.0 10.0 724 725 726 727 728 729 730 731 732 733 734 Pre Prin ts Pre Prin ts Table 5. Fae diversity. Sum in each column equals 100%. 735 Taxon Unamended +O2-NO3- +O2+NO3- -O2-NO3- -O2+NO3Methylococcaceae Methylobacter 27.0 10.8 21.0 100 7.7 Methylomicrobium 1.6 2.0 Methylomonas 8.0 11.0 16.0 7.7 Unclassified Methylococcaceae 6.4 9.5 Methylocystaceae Methylocystis 6.3 Methylosinus 1.6 9.5 5.0 Unclassified Methylocystaceae 2.0 Methylophilaceae Methylotenera versatilis 4.8 23.0 34.0 Methylotenera mobilis 1.6 10.8 13.0 15.4 Methylovorus 11.3 9.0 8.0 7.7 Methylobacillus 0.8 0.7 Unclassified Methylophilaceae 6.5 1.3 Other Burkholderiales 8.0 0.7 15.4 Unclassified 3.2 1.3 Pre Prin ts Pre Prin ts Proteobacteria Unclassified 1.6 3.0 Planctomycetes 6.4 0.7 30.7 NC10 1.6 LW phylum 1.6 0.7 7.7 Archaea 8.0 0.7 7.7 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 Pre Prin ts Pre Prin ts Table 6. Relative abundance and diversity of nitrate metabolism genes. Phylotypes are defined 754 as unique taxon IDs assigned by BLAST to nr. 755 Microcosm/ protein Total phylotypes Unamended +O2-NO3- +O2+NO3- -O2-NO3- -O2+NO3- Nitrate reductase 239 975a (0.37%) b 162 c 697 (0.44%) 116 259 (0.57%) 59 51 (0.24%) 33 541 (0.29%) 135 Nitrite reductase 207 454 (0.17%) 128 448 (0.28%) 94 167 (0.37%) 45 29 (0.13%) 24 225 (0.12%) 98 Nitric oxide reductase 118 200 (0.08%) 59 235 (0.15%) 49 135 (0.30%) 31 19 (0.09%) 18 121 (0.07%) 57 Nitrous oxide reductase 52 102 (0.04%) 32 75 (0.05%) 28 12 (0.026%) 6 15 (0.07%) 8 83 (0.05%) 25 Nitrogenase 66 172 (0.07%) 39 353 (0.22%) 30 123 (0.27%) 17 6 (0.03%) 4 45 (0.02%) 19 756 a Total number of genes annotated; b percent of total annotated enzymes; c number of 757 phylotypes 758 759 760 761 Pre Prin ts Pre Prin ts 762 Figure 1. Phylogenetic profiling of microcosms based on pyrotag analysis (A and B) and 763 metagenome data analysis (C and D). A. Distribution of pyrotag sequences among major phyla. 764 Clock-wise starting with blue: Proteobacteria, Bacteroidetes, Chloroplast, Acidobacteria, 765 Chloroflexi, Actinobacteria, Planctomycetes, Gemmatimonadetes, Firmicutes, Chlorobi, 766 Nitrospirae, Verrucomicrobia, Other (phyla making up to less than 1% of total). B. Proportions of 767 Methylococcaceae (blue) and Methylophilaceae (red) sequences in pyrotag libraries; other 768 sequences are in green. C. Distribution of sequences in metagenomes phylogenetically 769 classified at 90% identity level: blue, gammaproteobacteria, red, betaproteobacteria, green, 770 alphaproteobacteria, purple, all others. D. Proportions of Methylococcaceae (blue), 771 Methylophilaceae (red) and Methylocystaceae (green) of total sequences phylogenetically 772 profiled at 90% identity level. 773 !\" #\" $%&'(%)\" $%&$(%)\" \" \" '%&'(%)\" \" \" \" '%&$(%)\" \" \" *+,-.+/./\" 0\" 1\" Pre Prin ts Pre Prin ts 774 Figure 2. Abundance of the Methylococcaceae (blue) and the Methylophilaceae (pink) 775 sequences as determined by BLAST-based phylogenetic profiling, expressed as percent of total 776 sequences annotated at the 60% (light color) and the 90% (dark color) cutoff. 777 778 779 780 !\" #!\" $!\" %!\" &!\" '!!\" '#!\" '$!\" '%!\" ()*+,)-,-\" ./#01/2\" \" \" ./#.1/2\" \" 0/#.1/2\" \" 0/#01/2\" \" \" Pre Prin ts Pre Prin ts 781 Figure 3. Relative abundance of nitrate metabolism genes ascribed to Methylococcaceae (blue), 782 Methylophilaceae (red) and Methylocystaceae (green). Other (purple) represents a variety of 783 phylotypes, including methylotrophs of other families, present at low abundances. See 784 Supplemental Tables 4-8 for statistics. 1 to 5, 6 to 10, 11 to 15, 16 to 20 and 21 to 25 represent, 785 respectively, the unamended sample and the +O2-NO3-, +O2+NO3-, -O2-NO3-, and -O2+NO3- 786 conditions. 787 788 789 790 791 792 793 794 795 !\"#$ %&'()*+,&$ !\"-$ %&'()*+,&$ !-\"$ %&'()*+,&$ !\"$ %&'()*+,&$ !.*%/0&1+,&$ 23$ 423$ -23$ #23$ 523$ 623$ 723$ 823$ 923$ :23$ 4223$ 4$ -$ #$ 5$ 6$ 7$ 8$ 9$ :$ 42$ 44$ 4-$ 4#$ 45$ 46$ 47$ 48$ 49$ 4:$ -2$ -4$ --$ -#$ -5$ -6$Pre Prin ts Pre Prin ts Supplemental Table 2. Relative abundance of mmoX genes. Actual numbers of genes are 796 shown. 797 Taxon Unamended +O2-NO3- +O2+NO3- -O2-NO3- -O2+NO3Methylococcaceae 0 5 3 0 0 Methylocystaceae 1 13 0 0 0 798 Supplemental Table 3. Relative abundance of mxaF/xoxF genes representing 799 Methylococcaceae, Methylophilaceae and Methylocystaceae. Actual numbers of genes are 800 shown. 801 Enzyme/microcosm Unamended +O2-NO3- +O2+NO3- -O2-NO3- O2+NO3Methylococcaceae MxaF 2 12 9 0 3 Methylococcaceae XoxF 27 41 17 4 6 Methylophilaceae MxaF 0 2 0 0 0 Methylophilaceae XoxF 19 92 37 0 4 Methylocystaceae MxaF 0 16 0 0 0 Methylocystaceae XoxF 0 15 0 0 0 802 803 804 Pre Prin ts Pre Prin ts 805 806 Supplemental Figure 1. Comparison of phylogenetic profiling at major phylum level using the 807 pyrotag sequencing approach (A, C) versus analysis of 16S rRNA genes in metagenomes (B, 808 D). A, B, unamended sediment; C, D, the -O2+NO3- condition. 809 810 !\" #\" $\"%\" Pre Prin ts Pre Prin ts",
    "url": "https://peerj.com/articles/32/reviews/",
    "review_1": "Simon Silver \u00b7 Jan 15, 2013 \u00b7 Academic Editor\nACCEPT\nThank you for your submission to PeerJ. I am writing to inform you that your manuscript, \"Associations between the human intestinal microbiota, Lactobacillus rhamnosus GG and serum lipids indicated by integrated analysis of high-throughput profiling data\" (#2012:11:101:1:0:REVIEW), has been accepted for publication.\n\nOur production staff will be in touch with you shortly with any publication-related queries, to clarify any details required to move the manuscript forward, and to set a publication date.\n\nCongratulations and thank you for your submission.\n\nSimon Silver\nAcademic Editor for PeerJ",
    "review_2": "Simon Silver \u00b7 Jan 6, 2013 \u00b7 Academic Editor\nMINOR REVISIONS\n5 January 2013\n\nDear Dr. de Vos,\n\nFirstly, the good news is that the two outside expert reviewers of your manuscript both agree this is \u201cgood stuff\u201d and subsequent to revision should be published in our new journal PeerJ. Their detailed (and supportive and incisive) comments are below.\n\nNext my apologies that it has taken as long as it has: PeerJ intends to be timely and quick, as well as thorough and supportive of authors\u2019 goals. Here it has taken longer than we wish, for a variety of reasons high amongst which were the holidays and people being unavailable.\n\nAs you said on submission, this report furthers that in two reports form your groups, Kekkonen RA, Sysi-Aho M, Seppanen-Laakso T, Julkunen I, Vapaatalo H, Oresic M, Korpela R. 2008a. Effect of probiotic Lactobacillus rhamnosus GG intervention on global serum lipidomic profiles in healthy adults. World J Gastroenterol. 14(20):3188-3194. and Kekkonen RA, Lummela N, Karjalainen H, Latvala S, Tynkkynen S, Jarvenpaa S, Kautiainen H, Julkunen I, Vapaatalo H, Korpela R. 2008b. Probiotic intervention has strain-specific anti-inflammatory effects in healthy adults. World J Gastroenterol. 14(13): 2029-2036, both of which I printed and read in addition to the 39 pp manuscript (9ncluding abstract, figures and tables) itself.\n\nPlease revise the manuscript \u2013 quite minor \u2013 taking in to account the comments of the two outside reviewers plus myself (who cannot resist making suggestions, if I am reading). You as authors might have two goals: (1) firstly to get this on record as normal EU process in a form that no one is ever expected to read but you can cite as being on record. Or (2) as experienced scientists you may wish to communicate to your colleagues interested in the topic just what they should be thinking and taking in to regard. Unless the manuscript is seriously revised (and of course with 8 authors and the EU practices, none of these has really thought this through adequately), I promise you this will fit into the first class and be ignored except by the authors. Of course, a modern editor is not usually so blunt \u2013 she or he merely shuffles papers or files. However, I hope to help PeerJ set a high standard, as I have in previous efforts with a hand-full of other journals. Therefore a 3rd set of comments are attached, dealing primarily with the figures and tables (of course, the data) and to a much less extent the writing.\n\nGood luck in your effort. It would be wonderful if all authors were required to be involved and learn and work together. It is our hope that after taking longer than wished-for in the initial review, the revised manuscript should be accepted for publications within a day or two of posting.\n\nYours sincerely,\n\n\nSimon Silver\nAcademic Editor, simon@uic.edu\n\nSuggestions from the Editor:\n\n1) Minor, but remove \u201clipidome\u201d and \u201clipidomic\u201d et alia. and other novel \u201comics\u201d terms. A meta-genomics PhD student here suggested that the journal should charge 700\u20ac for every \u201come\u201d or \u201comics\u201d beyond the most-used 3-5. There are actually hundreds now and I recall when a new genomics centre was being started when I was at the University of Cape Town, in order to gain support for the Centre, it started with \u201cnose-omics\u201d for a mouse researcher in the Zoology Department) and \u201croot-omics\u201d for someone interested in gene expression in flooded maize fields. It is bad enough that we are probably stuck with metabolomics, but we do not need vitaminomics, sugaromics, aminoacidomics, et alia as well as lipomics. You have \u201cmixOmics\u201d from previous papers.\n\nThere are 3 Figures and 2 Tables, each of which could communicate its meaning much easier than now:\n\nFig. 1 legend of course has a trivial capitalizing error that none of the 8 authors considers one\u2019s responsibility. There are three times for sampling and that information absolutely must be in the legend, as well as a simple statement of what \u201csignal\u201d is intended \u2013 as by telegraph? The sentence in the legend on \u201csignificance\u201d should be moved from there to the text itself and the \u201cbar\u201d should be defined as for example +/- SD (N-x). The significant increase was only for the 2nd time data and not for the 1st or 3rd (earlier and later) time points, or else this reader does not understand the figure. Is the editor wrong or the authors just not careful?\n\n2) For Figure 2, \u201ccorrelation heatmap\u201d is neither science nor English. It does not made clearer by the first hit in google.com \u201cSignificance level added to matrix correlation heatmap using ggplot2 \u201c. How does \u201cq\u201d less than 5% differ from the most usually used \u201cp\u201d less than 5% standard for weakly significant and for example on line 154, p. 7? And of course when the authors say in the legend of Figure 2 that \u201cabbreviations of lipid names, see the Methods section\u201d, that is false, as line 141 on p. 7 says to look at the authors\u2019 2008 paper for this list. Again, either the editor is making a major mistake or the 8 authors have failed to read their own manuscript. That long long list needs to be added to the Fig. 2 legend if any reader is expected to gain any understanding from it.\n\n3) For Fig. 3, \u201cet rel\u201d again is horrible narrow jargon and google.com shows it is used by microbiologists and USA government legal courts in different meanings. Which is intended here? Say it in words. Better of course is to use precise words and not confusing jargon. \u201cCross plots\u201d is again jargon rather than language. And any author with a sense of statistical meaning would be impressed with the \u201cscatter\u201d of data in Fig. 3A and B, and so \u201chighly correlated\u201d is a poor choice of words. There is a significant correlation and you can calculate an R value for this, but mostly there is wide scatter of the data. Of course we do not know what TG54:5 means. [TG is measured in our doctors\u2019 offices.] Much the same is for Fig. 4 with a lot of scatter more than a \u201cpositive association\u201d being most visible and we do not know what ChoE920:5) is, although LDL is familiar.\n4) The problems continue with the Tables. \u201cPearson correlation\u201d is unfamiliar to most journal readers, most microbiologists and most \u201comics\u201d researchers. It is in fact a measure of the scatter r that we are not given for Figs. 3 and 4. For Table 1, please say what those times are, 1 hour, 1 week or 1 month? \u201cBetween subjects can be said once; it is not said 3x? And the4 correlations all look quite tight with small scatter.\n\n4) Table 2 is again a Table that cannot be read by intended readers and has the sole purpose of allowing the authors to get something that can not be understood on record. Are these )probably) Pearson correlations again? -- we are not told. The values are a bit lower than in Table 1, and some correlations are negative. Bacteriodes would be \u201cgenus level\u201d and not two separate subgroups listed with species \u201cet rel\u201d, which is not defined. Please try again.\n\nOf course, we all wish the authors would do their jobs carefully, so that outside peer reviewers can deal more with larger issues (a they have here with enthusiasm) and editors can not try to substitute for statisticians et rel. Good luck.",
    "review_3": "Shira Doron \u00b7 Jan 2, 2013\nBasic reporting\nThis is a well written study by experienced investigators in the field demonstrating several findings:\nFirst, the absence of an impact of LGG administration on the fecal microbiota, as measured by HITChip and quantitative PCR, with the exception of the Lactobacillus quantities.\nSecond, the absence of an impact of LGG on serum lipid profiles.\nThird, the correlation between certain bacterial phylotypes and lipid classes.\nThe negative findings support those of previously published studies and the positive findings are hypothesis generating and should lead to further research.\nExperimental design\nHere I have only one suggestion, and that is to clarify whether subjects were instructed not to consume store-bought probiotics during the study period, whether subjects were questioned on compliance with the intervention and with abstinence from store-bought probiotics, and to clarify not just the average excretion of LGG in the placebo group, but the range, so that the reader can ascertain whether the treatment and placebo groups were indeed distinct in their exposure to probiotics.\nValidity of the findings\nBecause most of the latest studies in this field are using pyrosequencing technology, some discussion of how these results might be expected to differ or be the same if that technology had been used of HITChip instead would be very helpful.\nCite this review as\nDoron S (2013) Peer Review #1 of \"Associations between the human intestinal microbiota, Lactobacillus rhamnosus GG and serum lipids indicated by integrated analysis of high-throughput profiling data (v0.1)\". PeerJ https://doi.org/10.7287/peerj.32v0.1/reviews/1",
    "review_4": "Reviewer 2 \u00b7 Dec 19, 2012\nBasic reporting\nThe authors present a two compelling study that demonstrates, firstly, that there was no impact of a probiotic containing \u201cL. rhamnosus GG\u201d on the diversity and composition of the native gut community or the blood chemistry of 11 individuals versus 14 individuals given a placebo; secondly, the authors go onto to explore potential correlations between the microbial taxa detected in the study and blood serum lipids. Overall the manuscript is well written and presents an interesting study. It fulfills all the requirements of the journal.\nExperimental design\nI have one small criticism. The correlations in the second part of the paper, while based on 22 observations, are still only correlations between 2 time points. I know very well that you can generate such correlations and they do indeed turn out to be meaningful. However, in this current manuscript, as the authors themselves say, these correlations are deemed to be hypothesis generating. With this in mind, the authors need to statement to the methods (statistics section) and a paragraph to the discussion, which explicitly deals with the limitations of the experimental design for exploring such correlations. Even with the statistical tests applied, the correlation across 2 time points could be indicative of many other variables \u2013 the authors go so far as to suggest diet \u2013 but this is the tip of the iceberg. To get proper statistical power you would need to explore a more resolved longitudinal analysis. The authors absolutely need to expand on the limitations of their study. Especially, also toning down the rhetoric in the abstract, the final sentence of which is simply untrue \u201cOur results suggest that several members of the Firmicutes,\nActinobacteria and Proteobacteria are involved in the metabolism of dietary and endogenous lipids\u201d\nValidity of the findings\nSee experimental design, the findings are valid if you accept that the experimental design is a little bit strained.\nAdditional comments\nMinor comment.\n\nLn 35 \u2013 \u2018affecting\u2019 not \u2018affect\u2019.\nCite this review as\nAnonymous Reviewer (2013) Peer Review #2 of \"Associations between the human intestinal microbiota, Lactobacillus rhamnosus GG and serum lipids indicated by integrated analysis of high-throughput profiling data (v0.1)\". PeerJ https://doi.org/10.7287/peerj.32v0.1/reviews/2",
    "pdf_1": "https://peerj.com/articles/32v0.2/submission",
    "pdf_2": "https://peerj.com/articles/32v0.1/submission",
    "all_reviews": "Review 1: Simon Silver \u00b7 Jan 15, 2013 \u00b7 Academic Editor\nACCEPT\nThank you for your submission to PeerJ. I am writing to inform you that your manuscript, \"Associations between the human intestinal microbiota, Lactobacillus rhamnosus GG and serum lipids indicated by integrated analysis of high-throughput profiling data\" (#2012:11:101:1:0:REVIEW), has been accepted for publication.\n\nOur production staff will be in touch with you shortly with any publication-related queries, to clarify any details required to move the manuscript forward, and to set a publication date.\n\nCongratulations and thank you for your submission.\n\nSimon Silver\nAcademic Editor for PeerJ\nReview 2: Simon Silver \u00b7 Jan 6, 2013 \u00b7 Academic Editor\nMINOR REVISIONS\n5 January 2013\n\nDear Dr. de Vos,\n\nFirstly, the good news is that the two outside expert reviewers of your manuscript both agree this is \u201cgood stuff\u201d and subsequent to revision should be published in our new journal PeerJ. Their detailed (and supportive and incisive) comments are below.\n\nNext my apologies that it has taken as long as it has: PeerJ intends to be timely and quick, as well as thorough and supportive of authors\u2019 goals. Here it has taken longer than we wish, for a variety of reasons high amongst which were the holidays and people being unavailable.\n\nAs you said on submission, this report furthers that in two reports form your groups, Kekkonen RA, Sysi-Aho M, Seppanen-Laakso T, Julkunen I, Vapaatalo H, Oresic M, Korpela R. 2008a. Effect of probiotic Lactobacillus rhamnosus GG intervention on global serum lipidomic profiles in healthy adults. World J Gastroenterol. 14(20):3188-3194. and Kekkonen RA, Lummela N, Karjalainen H, Latvala S, Tynkkynen S, Jarvenpaa S, Kautiainen H, Julkunen I, Vapaatalo H, Korpela R. 2008b. Probiotic intervention has strain-specific anti-inflammatory effects in healthy adults. World J Gastroenterol. 14(13): 2029-2036, both of which I printed and read in addition to the 39 pp manuscript (9ncluding abstract, figures and tables) itself.\n\nPlease revise the manuscript \u2013 quite minor \u2013 taking in to account the comments of the two outside reviewers plus myself (who cannot resist making suggestions, if I am reading). You as authors might have two goals: (1) firstly to get this on record as normal EU process in a form that no one is ever expected to read but you can cite as being on record. Or (2) as experienced scientists you may wish to communicate to your colleagues interested in the topic just what they should be thinking and taking in to regard. Unless the manuscript is seriously revised (and of course with 8 authors and the EU practices, none of these has really thought this through adequately), I promise you this will fit into the first class and be ignored except by the authors. Of course, a modern editor is not usually so blunt \u2013 she or he merely shuffles papers or files. However, I hope to help PeerJ set a high standard, as I have in previous efforts with a hand-full of other journals. Therefore a 3rd set of comments are attached, dealing primarily with the figures and tables (of course, the data) and to a much less extent the writing.\n\nGood luck in your effort. It would be wonderful if all authors were required to be involved and learn and work together. It is our hope that after taking longer than wished-for in the initial review, the revised manuscript should be accepted for publications within a day or two of posting.\n\nYours sincerely,\n\n\nSimon Silver\nAcademic Editor, simon@uic.edu\n\nSuggestions from the Editor:\n\n1) Minor, but remove \u201clipidome\u201d and \u201clipidomic\u201d et alia. and other novel \u201comics\u201d terms. A meta-genomics PhD student here suggested that the journal should charge 700\u20ac for every \u201come\u201d or \u201comics\u201d beyond the most-used 3-5. There are actually hundreds now and I recall when a new genomics centre was being started when I was at the University of Cape Town, in order to gain support for the Centre, it started with \u201cnose-omics\u201d for a mouse researcher in the Zoology Department) and \u201croot-omics\u201d for someone interested in gene expression in flooded maize fields. It is bad enough that we are probably stuck with metabolomics, but we do not need vitaminomics, sugaromics, aminoacidomics, et alia as well as lipomics. You have \u201cmixOmics\u201d from previous papers.\n\nThere are 3 Figures and 2 Tables, each of which could communicate its meaning much easier than now:\n\nFig. 1 legend of course has a trivial capitalizing error that none of the 8 authors considers one\u2019s responsibility. There are three times for sampling and that information absolutely must be in the legend, as well as a simple statement of what \u201csignal\u201d is intended \u2013 as by telegraph? The sentence in the legend on \u201csignificance\u201d should be moved from there to the text itself and the \u201cbar\u201d should be defined as for example +/- SD (N-x). The significant increase was only for the 2nd time data and not for the 1st or 3rd (earlier and later) time points, or else this reader does not understand the figure. Is the editor wrong or the authors just not careful?\n\n2) For Figure 2, \u201ccorrelation heatmap\u201d is neither science nor English. It does not made clearer by the first hit in google.com \u201cSignificance level added to matrix correlation heatmap using ggplot2 \u201c. How does \u201cq\u201d less than 5% differ from the most usually used \u201cp\u201d less than 5% standard for weakly significant and for example on line 154, p. 7? And of course when the authors say in the legend of Figure 2 that \u201cabbreviations of lipid names, see the Methods section\u201d, that is false, as line 141 on p. 7 says to look at the authors\u2019 2008 paper for this list. Again, either the editor is making a major mistake or the 8 authors have failed to read their own manuscript. That long long list needs to be added to the Fig. 2 legend if any reader is expected to gain any understanding from it.\n\n3) For Fig. 3, \u201cet rel\u201d again is horrible narrow jargon and google.com shows it is used by microbiologists and USA government legal courts in different meanings. Which is intended here? Say it in words. Better of course is to use precise words and not confusing jargon. \u201cCross plots\u201d is again jargon rather than language. And any author with a sense of statistical meaning would be impressed with the \u201cscatter\u201d of data in Fig. 3A and B, and so \u201chighly correlated\u201d is a poor choice of words. There is a significant correlation and you can calculate an R value for this, but mostly there is wide scatter of the data. Of course we do not know what TG54:5 means. [TG is measured in our doctors\u2019 offices.] Much the same is for Fig. 4 with a lot of scatter more than a \u201cpositive association\u201d being most visible and we do not know what ChoE920:5) is, although LDL is familiar.\n4) The problems continue with the Tables. \u201cPearson correlation\u201d is unfamiliar to most journal readers, most microbiologists and most \u201comics\u201d researchers. It is in fact a measure of the scatter r that we are not given for Figs. 3 and 4. For Table 1, please say what those times are, 1 hour, 1 week or 1 month? \u201cBetween subjects can be said once; it is not said 3x? And the4 correlations all look quite tight with small scatter.\n\n4) Table 2 is again a Table that cannot be read by intended readers and has the sole purpose of allowing the authors to get something that can not be understood on record. Are these )probably) Pearson correlations again? -- we are not told. The values are a bit lower than in Table 1, and some correlations are negative. Bacteriodes would be \u201cgenus level\u201d and not two separate subgroups listed with species \u201cet rel\u201d, which is not defined. Please try again.\n\nOf course, we all wish the authors would do their jobs carefully, so that outside peer reviewers can deal more with larger issues (a they have here with enthusiasm) and editors can not try to substitute for statisticians et rel. Good luck.\nReview 3: Shira Doron \u00b7 Jan 2, 2013\nBasic reporting\nThis is a well written study by experienced investigators in the field demonstrating several findings:\nFirst, the absence of an impact of LGG administration on the fecal microbiota, as measured by HITChip and quantitative PCR, with the exception of the Lactobacillus quantities.\nSecond, the absence of an impact of LGG on serum lipid profiles.\nThird, the correlation between certain bacterial phylotypes and lipid classes.\nThe negative findings support those of previously published studies and the positive findings are hypothesis generating and should lead to further research.\nExperimental design\nHere I have only one suggestion, and that is to clarify whether subjects were instructed not to consume store-bought probiotics during the study period, whether subjects were questioned on compliance with the intervention and with abstinence from store-bought probiotics, and to clarify not just the average excretion of LGG in the placebo group, but the range, so that the reader can ascertain whether the treatment and placebo groups were indeed distinct in their exposure to probiotics.\nValidity of the findings\nBecause most of the latest studies in this field are using pyrosequencing technology, some discussion of how these results might be expected to differ or be the same if that technology had been used of HITChip instead would be very helpful.\nCite this review as\nDoron S (2013) Peer Review #1 of \"Associations between the human intestinal microbiota, Lactobacillus rhamnosus GG and serum lipids indicated by integrated analysis of high-throughput profiling data (v0.1)\". PeerJ https://doi.org/10.7287/peerj.32v0.1/reviews/1\nReview 4: Reviewer 2 \u00b7 Dec 19, 2012\nBasic reporting\nThe authors present a two compelling study that demonstrates, firstly, that there was no impact of a probiotic containing \u201cL. rhamnosus GG\u201d on the diversity and composition of the native gut community or the blood chemistry of 11 individuals versus 14 individuals given a placebo; secondly, the authors go onto to explore potential correlations between the microbial taxa detected in the study and blood serum lipids. Overall the manuscript is well written and presents an interesting study. It fulfills all the requirements of the journal.\nExperimental design\nI have one small criticism. The correlations in the second part of the paper, while based on 22 observations, are still only correlations between 2 time points. I know very well that you can generate such correlations and they do indeed turn out to be meaningful. However, in this current manuscript, as the authors themselves say, these correlations are deemed to be hypothesis generating. With this in mind, the authors need to statement to the methods (statistics section) and a paragraph to the discussion, which explicitly deals with the limitations of the experimental design for exploring such correlations. Even with the statistical tests applied, the correlation across 2 time points could be indicative of many other variables \u2013 the authors go so far as to suggest diet \u2013 but this is the tip of the iceberg. To get proper statistical power you would need to explore a more resolved longitudinal analysis. The authors absolutely need to expand on the limitations of their study. Especially, also toning down the rhetoric in the abstract, the final sentence of which is simply untrue \u201cOur results suggest that several members of the Firmicutes,\nActinobacteria and Proteobacteria are involved in the metabolism of dietary and endogenous lipids\u201d\nValidity of the findings\nSee experimental design, the findings are valid if you accept that the experimental design is a little bit strained.\nAdditional comments\nMinor comment.\n\nLn 35 \u2013 \u2018affecting\u2019 not \u2018affect\u2019.\nCite this review as\nAnonymous Reviewer (2013) Peer Review #2 of \"Associations between the human intestinal microbiota, Lactobacillus rhamnosus GG and serum lipids indicated by integrated analysis of high-throughput profiling data (v0.1)\". PeerJ https://doi.org/10.7287/peerj.32v0.1/reviews/2\nReview 5: nan\nReview 6: \n",
    "LLM_extracted_review": "[\"**Review 1:**\\n- Manuscript accepted for publication.\\n\\n**Review 2:**\\n- Two outside expert reviewers found the manuscript to be \u201cgood stuff\u201d and recommended publication after minor revisions.\\n- Apologies for the delay in the review process due to holidays and unavailability of reviewers.\\n- Suggestions for minor revisions include:\\n  1. Remove novel \u201comics\u201d terms to avoid confusion.\\n  2. Improve clarity of figures and tables, including correcting trivial errors and ensuring all necessary information is included in legends.\\n  3. Address jargon and ensure precise language is used in descriptions.\\n  4. Clarify statistical terms and ensure that tables are understandable to the intended audience.\\n- Emphasis on the need for authors to collaborate effectively to enhance the manuscript's quality.\\n\\n**Review 3:**\\n- The study is well-written and presents several findings, including:\\n  1. No impact of LGG administration on fecal microbiota, except for Lactobacillus quantities.\\n  2. No impact of LGG on serum lipid profiles.\\n  3. Correlation between certain bacterial phylotypes and lipid classes.\\n- Suggestion to clarify subjects' compliance with the intervention and the range of LGG excretion in the placebo group.\\n- Recommendation to discuss how results might differ if pyrosequencing technology had been used instead of HITChip.\\n\\n**Review 4:**\\n- The study demonstrates no impact of L. rhamnosus GG on gut community diversity or blood chemistry compared to placebo.\\n- The manuscript is well-written and fulfills journal requirements.\\n- Criticism regarding the correlations being based on only two time points, suggesting the need for a more resolved longitudinal analysis.\\n- Authors should explicitly discuss the limitations of their experimental design and tone down exaggerated claims in the abstract.\\n\\n**Review 5:**\\n- No content provided.\\n\\n**Review 6:**\\n- No content provided.\"]"
}