Peering into the Genetic Makeup of Natural Microbial Populations Using Metagenomics

Structure-informed microbial population genetics elucidate selective pressures that shape protein evolution

Comprehensive sampling of natural genetic diversity with metagenomics enables highly resolved insights into the interplay between ecology and evolution. However, resolving adaptive, neutral, or purifying processes of evolution from intrapopulation genomic variation remains a challenge, partly due to the sole reliance on gene sequences to interpret variants. Here, we describe an approach to analyze genetic variation in the context of predicted protein structures and apply it to a marine microbial population within the SAR11 subclade 1a.3.V, which dominates low-latitude surface oceans. Our analyses reveal a tight association between genetic variation and protein structure. In a central gene in nitrogen metabolism, we observe decreased occurrence of nonsynonymous variants from ligand-binding sites as a function of nitrate concentrations, revealing genetic targets of distinct evolutionary pressures maintained by nutrient availability. Our work yields insights into the governing principles of evolution and enables structure-aware investigations of microbial population genetics.

Alterations of oral microbiota and impact on the gut microbiome in type 1 diabetes mellitus revealed by integrated multi-omic analyses

BACKGROUND

Alterations to the gut microbiome have been linked to multiple chronic diseases. However, the drivers of such changes remain largely unknown. The oral cavity acts as a major route of exposure to exogenous factors including pathogens, and processes therein may affect the communities in the subsequent compartments of the gastrointestinal tract. Here, we perform strain-resolved, integrated meta-genomic, transcriptomic, and proteomic analyses of paired saliva and stool samples collected from 35 individuals from eight families with multiple cases of type 1 diabetes mellitus (T1DM).

RESULTS

We identified distinct oral microbiota mostly reflecting competition between streptococcal species. More specifically, we found a decreased abundance of the commensal Streptococcus salivarius in the oral cavity of T1DM individuals, which is linked to its apparent competition with the pathobiont Streptococcus mutans. The decrease in S. salivarius in the oral cavity was also associated with its decrease in the gut as well as higher abundances in facultative anaerobes including Enterobacteria. In addition, we found evidence of gut inflammation in T1DM as reflected in the expression profiles of the Enterobacteria as well as in the human gut proteome. Finally, we were able to follow transmitted strain-variants from the oral cavity to the gut at the individual omic levels, highlighting not only the transfer, but also the activity of the transmitted taxa along the gastrointestinal tract.

CONCLUSIONS

Alterations of the oral microbiome in the context of T1DM impact the microbial communities in the lower gut, in particular through the reduction of "mouth-to-gut" transfer of Streptococcus salivarius. Our results indicate that the observed oral-cavity-driven gut microbiome changes may contribute towards the inflammatory processes involved in T1DM. Through the integration of multi-omic analyses, we resolve strain-variant "mouth-to-gut" transfer in a disease context. Video Abstract.

To Dereplicate or Not To Dereplicate?

Metagenome-assembled genomes (MAGs) expand our understanding of microbial diversity, evolution, and ecology. Concerns have been raised on how sequencing, assembly, binning, and quality assessment tools may result in MAGs that do not reflect single populations in nature. Here, we reflect on another issue, i.e., how to handle highly similar MAGs assembled from independent data sets. Obtaining multiple genomic representatives for a species is highly valuable, as it allows for population genomic analyses; however, when retaining genomes of closely related populations, it complicates MAG quality assessment and abundance inferences.

Metagenome-assembled genomes (MAGs) expand our understanding of microbial diversity, evolution, and ecology. Concerns have been raised on how sequencing, assembly, binning, and quality assessment tools may result in MAGs that do not reflect single populations in nature. Here, we reflect on another issue, i.e., how to handle highly similar MAGs assembled from independent data sets. Obtaining multiple genomic representatives for a species is highly valuable, as it allows for population genomic analyses; however, when retaining genomes of closely related populations, it complicates MAG quality assessment and abundance inferences. We show that (i) published data sets contain a large fraction of MAGs sharing >99% average nucleotide identity, (ii) different software packages and parameters used to resolve this redundancy remove very different numbers of MAGs, and (iii) the removal of closely related genomes leads to losses of population-specific auxiliary genes. Finally, we highlight some approaches that can infer strain-specific dynamics across a sample series without dereplication.

Single-amino acid variants reveal evolutionary processes that shape the biogeography of a global SAR11 subclade

Members of the SAR11 order Pelagibacterales dominate the surface oceans. Their extensive diversity challenges emerging operational boundaries defined for microbial 'species' and complicates efforts of population genetics to study their evolution. Here, we employed single-amino acid variants (SAAVs) to investigate ecological and evolutionary forces that maintain the genomic heterogeneity within ubiquitous SAR11 populations we accessed through metagenomic read recruitment using a single isolate genome. Integrating amino acid and protein biochemistry with metagenomics revealed that systematic purifying selection against deleterious variants governs non-synonymous variation among very closely related populations of SAR11. SAAVs partitioned metagenomes into two main groups matching large-scale oceanic current temperatures, and six finer proteotypes that connect distant oceanic regions. These findings suggest that environmentally-mediated selection plays a critical role in the journey of cosmopolitan surface ocean microbial populations, and the idea 'everything is everywhere but the environment selects' has credence even at the finest resolutions.

Dairy soil bacterial responses to nitrogen application in simulated Italian ryegrass and white clover pasture

Through clearing and use of fertilizer and legumes, areas of southwestern Australia's unique coastal sand plains can support relatively low-cost dairies. However, the ancient, highly weathered nature of the soils in this region makes the dairies susceptible to a range of threats, including nutrient leaching and erosion. Despite this, Western Australian dairy cows typically produce up to 5,500 L of milk per head annually supported by inorganic nitrogen (N) fertilizer (commonly 50:50 urea and ammonium sulfate) at rates up to <320 kg of N/ha per year. Where hotspots exist (up to 2,000 kg of N/ha per year), total N exceeds pasture requirements. We investigated plant and soil bacteria responses to N fertilizer rates consistent with Australian legislated production practices on dairy farms for pure and mixed swards of white clover (Trifolium repens) and Italian ryegrass (Lolium multiflorum) in a long-term pasture experiment in controlled glasshouse conditions. Although the soil bacterial community structure at phylum level was similar for white clover and Italian ryegrass, relative abundances of specific subgroups of bacteria differed among plant species according to the N fertilizer regimen. Marked increases in relative abundance of some bacterial phyla and subphyla indicated potential inhibition of N cycling, especially for N hotspots in soil. Ammonium concentration in soil was less correlated with dominance of some N-cycling bacterial phyla than was nitrate concentration. Changes in bacterial community structure related to altered nutrient cycling highlight the potential for considering this area of research in policy assessment frameworks related to nutrient loads in dairy soils, especially for N.