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Metagenomic surveys have revealed that natural microbial communities are predominantly composed of sequence-discrete, species-like populations but the genetic and/or ecological processes that maintain such populations remain speculative, limiting our understanding of population speciation and adaptation to perturbations. To address this knowledge gap, we sequenced 112 Salinibacter ruber isolates and 12 companion metagenomes from four adjacent saltern ponds in Mallorca, Spain that were experimentally manipulated to dramatically alter salinity and light intensity, the two major drivers of this ecosystem. Our analyses showed that the pangenome of the local Sal. ruber population is open and similar in size (~15,000 genes) to that of randomly sampled Escherichia coli genomes. While most of the accessory (noncore) genes were isolate-specific and showed low in situ abundances based on the metagenomes compared to the core genes, indicating that they were functionally unimportant and/or transient, 3.5% of them became abundant when salinity (but not light) conditions changed and encoded for functions related to osmoregulation. Nonetheless, the ecological advantage of these genes, while significant, was apparently not strong enough to purge diversity within the population. Collectively, our results provide an explanation for how this immense intrapopulation gene diversity is maintained, which has implications for the prokaryotic species concept.

 

ABSTRACT The use of enterococci as a fecal indicator bacterial group for public health risk assessment has been brought into question by recent studies showing that “naturalized” populations of Enterococcus faecalis exist in the extraenteric environment. The extent to which these naturalized E. faecalis organisms can confound water quality monitoring is unclear. To determine if strains isolated from different habitats display different survival strategies and responses, we compared the decay patterns of three E. faecalis isolates from the natural environment (environmental strains) against three human gut isolates (enteric strains) in laboratory mesocosms that simulate an oligotrophic, aerobic freshwater environment. Our results showed similar overall decay rates between enteric and environmental isolates based on viable plate and quantitative PCR (qPCR) counts. However, the enteric isolates exhibited a spike in copy number ratios of 16S rRNA gene transcripts to 16S rRNA gene DNA copies (rRNA:rDNA ratios) between days 1 and 3 of the mesocosm incubations that was not observed in environmental isolates, which could indicate a different stress response. Nevertheless, there was no strong evidence of differential gene expression between environmental and enteric isolates related to habitat adaptation in the accompanying mesocosm metatranscriptomes. Overall, our results provide novel information on how rRNA levels may vary over different growth conditions (e.g., standard lab versus oligotrophic) for this important indicator bacteria. We also observed some evidence for habitat adaptation in E. faecalis ; however, this adaptation may not be substantial or consistent enough for integration in water quality monitoring. IMPORTANCE Enterococci are commonly used worldwide to monitor environmental fecal contamination and public health risk for waterborne diseases. However, closely related enterococci strains adapted to living in the extraenteric environment may represent a lower public health risk and confound water quality estimates. We developed an rRNA:rDNA viability assay for E. faecalis (a predominant species within this fecal group) and tested it against both enteric and environmental isolates in freshwater mesocosms to assess whether this approach can serve as a more sensitive water quality monitoring tool. We were unable to reliably distinguish the different isolate types using this assay under the conditions tested; thus, environmental strains should continue to be counted during routine water monitoring. However, this assay could be useful for distinguishing more recent (i.e., higher-risk) fecal pollution because rRNA levels significantly decreased after 1 week in all isolates. 

ABSTRACT The recovery of metagenome-assembled genomes (MAGs) from metagenomic data has recently become a common task for microbial studies. The strengths and limitations of the underlying bioinformatics algorithms are well appreciated by now based on performance tests with mock data sets of known composition. However, these mock data sets do not capture the complexity and diversity often observed within natural populations, since their construction typically relies on only a single genome of a given organism. Further, it remains unclear if MAGs can recover population-variable genes (those shared by >10% but <90% of the members of the population) as efficiently as core genes (those shared by >90% of the members). To address these issues, we compared the gene variabilities of pathogenic Escherichia coli isolates from eight diarrheal samples, for which the isolate was the causative agent, against their corresponding MAGs recovered from the companion metagenomic data set. Our analysis revealed that MAGs with completeness estimates near 95% captured only 77% of the population core genes and 50% of the variable genes, on average. Further, about 5% of the genes of these MAGs were conservatively identified as missing in the isolate and were of different (non- Enterobacteriaceae ) taxonomic origin, suggesting errors at the genome-binning step, even though contamination estimates based on commonly used pipelines were only 1.5%. Therefore, the quality of MAGs may often be worse than estimated, and we offer examples of how to recognize and improve such MAGs to sufficient quality by (for instance) employing only contigs longer than 1,000 bp for binning. IMPORTANCE Metagenome assembly and the recovery of metagenome-assembled genomes (MAGs) have recently become common tasks for microbiome studies across environmental and clinical settings. However, the extent to which MAGs can capture the genes of the population they represent remains speculative. Current approaches to evaluating MAG quality are limited to the recovery and copy number of universal housekeeping genes, which represent a small fraction of the total genome, leaving the majority of the genome essentially inaccessible. If MAG quality in reality is lower than these approaches would estimate, this could have dramatic consequences for all downstream analyses and interpretations. In this study, we evaluated this issue using an approach that employed comparisons of the gene contents of MAGs to the gene contents of isolate genomes derived from the same sample. Further, our samples originated from a diarrhea case-control study, and thus, our results are relevant for recovering the virulence factors of pathogens from metagenomic data sets. 

ABSTRACT The phylogenetic and functional diversities of microbial communities in tropical rainforests and how these differ from those of temperate communities remain poorly described but are directly related to the increased fluxes of greenhouse gases such as nitrous oxide (N 2 O) from the tropics. Toward closing these knowledge gaps, we analyzed replicated shotgun metagenomes representing distinct life zones and an elevation gradient from four locations in the Luquillo Experimental Forest (LEF), Puerto Rico. These soils had a distinct microbial community composition and lower species diversity compared to those of temperate grasslands or agricultural soils. In contrast to the overall distinct community composition, the relative abundances and nucleotide sequences of N 2 O reductases ( nosZ ) were highly similar between tropical forest and temperate soils. However, respiratory NO reductase ( norB ) was 2-fold more abundant in the tropical soils, which might be relatable to their greater N 2 O emissions. Nitrogen fixation ( nifH ) also showed higher relative abundance in rainforest than in temperate soils, i.e., 20% versus 0.1 to 0.3% of bacterial genomes in each soil type harbored the gene, respectively. Finally, unlike temperate soils, LEF soils showed little stratification with depth in the first 0 to 30 cm, with ∼45% of community composition differences explained solely by location. Collectively, these results advance our understanding of spatial diversity and metabolic repertoire of tropical rainforest soil communities and should facilitate future ecological studies of these ecosystems. IMPORTANCE Tropical rainforests are the largest terrestrial sinks of atmospheric CO 2 and the largest natural source of N 2 O emissions, two greenhouse gases that are critical for the climate. The microbial communities of rainforest soils that directly or indirectly, through affecting plant growth, contribute to these fluxes remain poorly described by cultured-independent methods. To close this knowledge gap, the present study applied shotgun metagenomics to samples selected from three distinct life zones within the Puerto Rico rainforest. The results advance our understanding of microbial community diversity in rainforest soils and should facilitate future studies of natural or manipulated perturbations of these critical ecosystems. 

ABSTRACT Little is known about the public health risks associated with natural creek sediments that are affected by runoff and fecal pollution from agricultural and livestock practices. For instance, the persistence of foodborne pathogens such as Shiga toxin-producing Escherichia coli (STEC) originating from these practices remains poorly quantified. Towards closing these knowledge gaps, the water-sediment interface of two creeks in the Salinas River Valley of California was sampled over a 9-month period using metagenomics and traditional culture-based tests for STEC. Our results revealed that these sediment communities are extremely diverse and have functional and taxonomic diversity comparable to that observed in soils. With our sequencing effort (∼4 Gbp per library), we were unable to detect any pathogenic E. coli in the metagenomes of 11 samples that had tested positive using culture-based methods, apparently due to relatively low abundance. Furthermore, there were no significant differences in the abundance of human- or cow-specific gut microbiome sequences in the downstream impacted sites compared to that in upstream more pristine (control) sites, indicating natural dilution of anthropogenic inputs. Notably, the high number of metagenomic reads carrying antibiotic resistance genes (ARGs) found in all samples was significantly higher than ARG reads in other available freshwater and soil metagenomes, suggesting that these communities may be natural reservoirs of ARGs. The work presented here should serve as a guide for sampling volumes, amount of sequencing to apply, and what bioinformatics analyses to perform when using metagenomics for public health risk studies of environmental samples such as sediments. IMPORTANCE Current agricultural and livestock practices contribute to fecal contamination in the environment and the spread of food- and waterborne disease and antibiotic resistance genes (ARGs). Traditionally, the level of pollution and risk to public health are assessed by culture-based tests for the intestinal bacterium Escherichia coli . However, the accuracy of these traditional methods (e.g., low accuracy in quantification, and false-positive signal when PCR based) and their suitability for sediments remain unclear. We collected sediments for a time series metagenomics study from one of the most highly productive agricultural regions in the United States in order to assess how agricultural runoff affects the native microbial communities and if the presence of Shiga toxin-producing Escherichia coli (STEC) in sediment samples can be detected directly by sequencing. Our study provided important information on the potential for using metagenomics as a tool for assessment of public health risk in natural environments. 

Northern-latitude tundra soils harbor substantial carbon (C) stocks that are highly susceptible to microbial degradation with rising global temperatures. Understanding the magnitude and direction (e.g., C release or sequestration) of the microbial responses to warming is necessary to accurately model climate change. In this study, Alaskan tundra soils were subjected to experimental in situ warming by ∼1.1 °C above ambient temperature, and the microbial communities were evaluated using metagenomics after 4.5 years, at 2 depths: 15 to 25 cm (active layer at outset of the experiment) and 45 to 55 cm (transition zone at the permafrost/active layer boundary at the outset of the experiment). In contrast to small or insignificant shifts after 1.5 years of warming, 4.5 years of warming resulted in significant changes to the abundances of functional traits and the corresponding taxa relative to control plots (no warming), and microbial shifts differed qualitatively between the two soil depths. At 15 to 25 cm, increased abundances of carbohydrate utilization genes were observed that correlated with (increased) measured ecosystem carbon respiration. At the 45- to 55-cm layer, increased methanogenesis potential was observed, which corresponded with a 3-fold increase in abundance of a single archaeal clade of the Methanosarcinales order, increased annual thaw duration (45.3 vs. 79.3 days), and increased CH 4 emissions. Collectively, these data demonstrate that the microbial responses to warming in tundra soil are rapid and markedly different between the 2 critical soil layers evaluated, and identify potential biomarkers for the corresponding microbial processes that could be important in modeling.