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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.

 

Recent advances in sequencing technology and bioinformatic pipelines have allowed unprecedented access to the genomes of yet‐uncultivated microorganisms from diverse environments. However, the catalogue of freshwater genomes remains limited, and most genome recovery attempts in freshwater ecosystems have only targeted specific taxa. Here, we present a genome recovery pipeline incorporating iterative subtractive binning, and apply it to a time series of 100 metagenomic datasets from seven connected lakes and estuaries along the Chattahoochee River (Southeastern USA). Our set of metagenome‐assembled genomes (MAGs) represents >400 yet‐unnamed genomospecies, substantially increasing the number of high‐quality MAGs from freshwater lakes. We propose names for two novel species: ‘CandidatusElulimicrobium humile’ (‘Ca. Elulimicrobiota’, ‘Patescibacteria’) and ‘CandidatusAquidulcis frankliniae’ (‘Chloroflexi’). Collectively, our MAGs represented about half of the total microbial community at any sampling point. To evaluate the prevalence of these genomospecies in the chronoseries, we introduce methodologies to estimate relative abundance and habitat preference that control for uneven genome quality and sample representation. We demonstrate high degrees of habitat‐specialization and endemicity for most genomospecies in the Chattahoochee lakes. Wider ecological ranges characterized smaller genomes with higher coding densities, indicating an overall advantage of smaller, more compact genomes for cosmopolitan distributions.

 

Bacteriophages encode host‐acquired functional genes known as auxiliary metabolic genes (AMGs). Photosynthesis AMGs are commonly found in marine cyanobacteria‐infectingMyoviridaeandPodoviridaecyanophages, but their ecology remains understudied in freshwater environments. To advance knowledge of this issue, we analysed viral metagenomes collected in the summertime for four years from five lakes and two estuarine locations interconnected by the Chattahoochee River, Southeast USA. Sequences representing ten different AMGs were recovered and found to be prevalent in all sites. Most freshwater AMGs were 10‐fold less abundant than estuarine and marine AMGs and were encoded by novelMyoviridaeandPodoviridaecyanophage genera. Notably, several of the corresponding viral genomes showed endemism to a specific province along the river. This translated intopsbAgene phylogenetic clustering patterns that matched a marine vs. freshwater origin indicating thatpsbAmay serve as a robust classification and source‐tracking biomarker. Genomes classified in a novel viral lineage represented by isolate S‐EIVl containedpsbA, which is unprecedented for this lineage. Collectively, our findings indicated that the acquisition of photosynthesis AMGs is a widespread strategy used by cyanophages in aquatic ecosystems, and further indicated the existence of viral provinces in which certain viral species and/or genotypes are locally abundant.

 

Abstract Background Microbes and their viruses are hidden engines driving Earth’s ecosystems from the oceans and soils to humans and bioreactors. Though gene marker approaches can now be complemented by genome-resolved studies of inter-(macrodiversity) and intra-(microdiversity) population variation, analytical tools to do so remain scattered or under-developed. Results Here, we introduce MetaPop, an open-source bioinformatic pipeline that provides a single interface to analyze and visualize microbial and viral community metagenomes at both the macro - and microdiversity levels. Macrodiversity estimates include population abundances and α- and β-diversity. Microdiversity calculations include identification of single nucleotide polymorphisms, novel codon-constrained linkage of SNPs, nucleotide diversity ( π and θ ), and selective pressures (pN/pS and Tajima’s D ) within and fixation indices ( F ST ) between populations. MetaPop will also identify genes with distinct codon usage. Following rigorous validation, we applied MetaPop to the gut viromes of autistic children that underwent fecal microbiota transfers and their neurotypical peers. The macrodiversity results confirmed our prior findings for viral populations (microbial shotgun metagenomes were not available) that diversity did not significantly differ between autistic and neurotypical children. However, by also quantifying microdiversity, MetaPop revealed lower average viral nucleotide diversity ( π ) in autistic children. Analysis of the percentage of genomes detected under positive selection was also lower among autistic children, suggesting that higher viral π in neurotypical children may be beneficial because it allows populations to better “bet hedge” in changing environments. Further, comparisons of microdiversity pre- and post-FMT in autistic children revealed that the delivery FMT method (oral versus rectal) may influence viral activity and engraftment of microdiverse viral populations, with children who received their FMT rectally having higher microdiversity post-FMT. Overall, these results show that analyses at the macro level alone can miss important biological differences. Conclusions These findings suggest that standardized population and genetic variation analyses will be invaluable for maximizing biological inference, and MetaPop provides a convenient tool package to explore the dual impact of macro - and microdiversity across microbial communities. 

ABSTRACT Identification of genes encoding β-lactamases (BLs) from short-read sequences remains challenging due to the high frequency of shared amino acid functional domains and motifs in proteins encoded by BL genes and related non-BL gene sequences. Divergent BL homologs can be frequently missed during similarity searches, which has important practical consequences for monitoring antibiotic resistance. To address this limitation, we built ROCker models that targeted broad classes (e.g., class A, B, C, and D) and individual families (e.g., TEM) of BLs and challenged them with mock 150-bp- and 250-bp-read data sets of known composition. ROCker identifies most-discriminant bit score thresholds in sliding windows along the sequence of the target protein sequence and hence can account for nondiscriminative domains shared by unrelated proteins. BL ROCker models showed a 0% false-positive rate (FPR), a 0% to 4% false-negative rate (FNR), and an up-to-50-fold-higher F1 score [2 × precision × recall/(precision + recall)] compared to alternative methods, such as similarity searches using BLASTx with various e-value thresholds and BL hidden Markov models, or tools like DeepARG, ShortBRED, and AMRFinder. The ROCker models and the underlying protein sequence reference data sets and phylogenetic trees for read placement are freely available through http://enve-omics.ce.gatech.edu/data/rocker-bla . Application of these BL ROCker models to metagenomics, metatranscriptomics, and high-throughput PCR gene amplicon data should facilitate the reliable detection and quantification of BL variants encoded by environmental or clinical isolates and microbiomes and more accurate assessment of the associated public health risk, compared to the current practice. IMPORTANCE Resistance genes encoding β-lactamases (BLs) confer resistance to the widely prescribed antibiotic class β-lactams. Therefore, it is important to assess the prevalence of BL genes in clinical or environmental samples for monitoring the spreading of these genes into pathogens and estimating public health risk. However, detecting BLs in short-read sequence data is technically challenging. Our ROCker model-based bioinformatics approach showcases the reliable detection and typing of BLs in complex data sets and thus contributes toward solving an important problem in antibiotic resistance surveillance. The ROCker models developed substantially expand the toolbox for monitoring antibiotic resistance in clinical or environmental settings. 

Mapping of short metagenomic (or metatranscriptomic) read data to reference isolate or single-cell genomes or metagenome-assembled genomes (MAGs) to assess microbial population relative abundance and/or structure represents an essential task of many studies across environmental and clinical settings. The filtering for the quality of the read match and assessment of read mapping results are frequently performed without visual aids or with the assistance of visualizations produced through ad-hoc, in-house approaches. Here, we introduce RecruitPlotEasy, a fully automated, user-friendly pipeline for these purposes that integrates statistical approaches to quantify intra-population sequence and gene-content diversity and identify co-occurring relative populations in the sample. Hence, RecruitPlotEasy should also greatly facilitate population genetics studies. RecruitPlotEasy is implemented in Python and R languages and is freely available open source software under the Artistic License 2.0 from https://github.com/KGerhardt/RecruitPlotEasy .