Genomic adaptations in information processing underpin trophic strategy in a whole-ecosystem nutrient enrichment experiment

The effects of food provisioning on the gut microbiota community and antibiotic resistance genes of Yunnan snub-nosed monkey

Yunnan snub-nosed monkeys (Rhinopithecus bieti) are the highest elevation lived non-human primate, and their survival has been threatened for decades. To promote their population growth, a reserve provides a typical monkey population with supplemental food. However, the influences of this food provisioning on their gut microbiota and antibiotic resistance genes (ARGs) were unknown. Therefore, we investigated the gut microbiota and ARGs of the food-provisioned monkey population compared with another wild foraging population. We found that food provisioning significantly increased the gut microbiota diversity and changed the community composition, particularly increased both the Firmicutes abundance and Firmicutes/Bacteroidetes ratio. Meanwhile, the food provisioning decreased the complex and stable gut microbiota network. KEGG functions were also influenced by food provisioning, with wild foraging monkeys showing higher functions of metabolism and genetic information processing, especially the carbohydrate metabolism, while food-provisioned monkeys exhibited increased environmental information processing, cellular processes, and organismal systems, including valine, leucine, and isoleucine degradation. In addition, food provisioning increased the abundance of ARGs in the gut microbiota, with most increasing the abundance of bacA gene and changing the correlations between specific ARGs and bacterial phyla in each population. Our study highlights that even food provisioning could promote wildlife nutrient intake, and it is necessary to pay attention to the increased ARGs and potential effects on gut microbiota stability and functions for this human conservation measure.

r/K selection of GC content in prokaryotes

The guanine/cytosine (GC) content of prokaryotic genomes is species-specific, taking values from 16% to 77%. This diversity of selection for GC content remains contentious. We analyse the correlations between GC content and a range of phenotypic and genotypic data in thousands of prokaryotes. GC content integrates well with these traits into r/K selection theory when phenotypic plasticity is considered. High GC-content prokaryotes are r-strategists with cheaper descendants thanks to a lower average amino acid metabolic cost, colonize unstable environments thanks to flagella and a bacillus form and are generalists in terms of resource opportunism and their defence mechanisms. Low GC content prokaryotes are K-strategists specialized for stable environments that maintain homeostasis via a high-cost outer cell membrane and endospore formation as a response to nutrient deprivation, and attain a higher nutrient-to-biomass yield. The lower proteome cost of high GC content prokaryotes is driven by the association between GC-rich codons and cheaper amino acids in the genetic code, while the correlation between GC content and genome size may be partly due to functional diversity driven by r/K selection. In all, molecular diversity in the GC content of prokaryotes may be a consequence of ecological r/K selection.

Ecology theory disentangles microbial dichotomies

Microbes are often discussed in terms of dichotomies such as copiotrophic/oligotrophic and fast/slow-growing microbes, defined using the characterisation of microbial growth in isolated cultures. The dichotomies are usually qualitative and/or study-specific, sometimes precluding clear-cut results interpretation. We can unravel microbial dichotomies as life history strategies by combining ecology theory with Monod curves, a laboratory mathematical tool of bacterial physiology that relates the specific growth rate of a microbe with the concentration of a limiting nutrient. Fitting of Monod curves provides quantities that directly correspond to key parameters in ecological theories addressing species coexistence and diversity, such as r/K selection theory, resource competition and community structure theory and the CSR triangle of life strategies. The resulting model allows us to reconcile the copiotrophic/oligotrophic and fast/slow-growing dichotomies as different subsamples of a life history strategy triangle that also includes r/K strategists. We also used the number of known carbon sources together with community structure theory to partially explain the diversity of heterotrophic microbes observed in metagenomics experiments. In sum, we propose a theoretical framework for the study of natural microbial communities that unifies several existing proposals. Its application would require the integration of metagenomics, metametabolomics, Monod curves and carbon source data.

Eukaryotic genomes from a global metagenomic data set illuminate trophic modes and biogeography of ocean plankton

Metagenomics is a powerful method for interpreting the ecological roles and physiological capabilities of mixed microbial communities. Yet, many tools for processing metagenomic data are neither designed to consider eukaryotes nor are they built for an increasing amount of sequence data. EukHeist is an automated pipeline to retrieve eukaryotic and prokaryotic metagenome-assembled genomes (MAGs) from large-scale metagenomic sequence data sets. We developed the EukHeist workflow to specifically process large amounts of both metagenomic and/or metatranscriptomic sequence data in an automated and reproducible fashion. Here, we applied EukHeist to the large-size fraction data (0.8-2,000 µm) from Tara Oceans to recover both eukaryotic and prokaryotic MAGs, which we refer to as TOPAZ (Tara Oceans Particle-Associated MAGs). The TOPAZ MAGs consisted of >900 environmentally relevant eukaryotic MAGs and >4,000 bacterial and archaeal MAGs. The bacterial and archaeal TOPAZ MAGs expand upon the phylogenetic diversity of likely particle- and host-associated taxa. We use these MAGs to demonstrate an approach to infer the putative trophic mode of the recovered eukaryotic MAGs. We also identify ecological cohorts of co-occurring MAGs, which are driven by specific environmental factors and putative host-microbe associations. These data together add to a number of growing resources of environmentally relevant eukaryotic genomic information. Complementary and expanded databases of MAGs, such as those provided through scalable pipelines like EukHeist, stand to advance our understanding of eukaryotic diversity through increased coverage of genomic representatives across the tree of life.IMPORTANCESingle-celled eukaryotes play ecologically significant roles in the marine environment, yet fundamental questions about their biodiversity, ecological function, and interactions remain. Environmental sequencing enables researchers to document naturally occurring protistan communities, without culturing bias, yet metagenomic and metatranscriptomic sequencing approaches cannot separate individual species from communities. To more completely capture the genomic content of mixed protistan populations, we can create bins of sequences that represent the same organism (metagenome-assembled genomes [MAGs]). We developed the EukHeist pipeline, which automates the binning of population-level eukaryotic and prokaryotic genomes from metagenomic reads. We show exciting insight into what protistan communities are present and their trophic roles in the ocean. Scalable computational tools, like EukHeist, may accelerate the identification of meaningful genetic signatures from large data sets and complement researchers' efforts to leverage MAG databases for addressing ecological questions, resolving evolutionary relationships, and discovering potentially novel biodiversity.

The evolving copiotrophic/oligotrophic dichotomy: From Winogradsky to physiology and genomics

Nearly 100 years ago, Winogradsky published a classic communication in which he described two groups of microbes, zymogenic and autochthonous. When organic matter penetrates the soil, zymogenic microbes quickly multiply and degrade it, then giving way to the slow combustion of autochthonous microbes. Although the text was originally written in French, it is often cited by English-speaking authors. We undertook a complete translation of the 1924 publication, which we provide as Supporting information. Here, we introduce the translation and describe how the zymogenic/autochthonous dichotomy shaped research questions in the study of microbial diversity and physiology. We also identify in the literature three additional and closely related dichotomies, which we propose to call exclusive copiotrophs/oligotrophs, coexisting copiotrophs/oligotrophs and fast-growing/slow-growing microbes. While Winogradsky focussed on a successional view of microbial populations over time, the current discussion is focussed on the differences in the specific growth rate of microbes as a function of the concentration of a given limiting substrate. In the future, it will be relevant to keep in mind both nutrient-focussed and time-focussed microbial dichotomies and to design experiments with both isolated laboratory cultures and multi-species communities in the spirit of Winogradsky's direct method.

Microbial and Viral Genome and Proteome Nitrogen Demand Varies across Multiple Spatial Scales within a Marine Oxygen Minimum Zone

Nutrient availability can significantly influence microbial genomic and proteomic streamlining, for example, by selecting for lower nitrogen to carbon ratios. Oligotrophic open ocean microbes have streamlined genomic nitrogen requirements relative to those of their counterparts in nutrient-rich coastal waters. However, steep gradients in nutrient availability occur at meter-level, and even micron-level, spatial scales. It is unclear whether such gradients also structure genomic and proteomic stoichiometry. Focusing on the eastern tropical North Pacific oxygen minimum zone (OMZ), we use comparative metagenomics to examine how nitrogen availability shapes microbial and viral genome properties along the vertical gradient across the OMZ and between two size fractions, distinguishing free-living microbes versus particle-associated microbes. We find a substantial increase in the nitrogen content of encoded proteins in particle-associated over free-living bacteria and archaea across nitrogen availability regimes over depth. Within each size fraction, we find that bacterial and viral genomic nitrogen tends to increase with increasing nitrate concentrations with depth. In contrast to cellular genes, the nitrogen content of virus proteins does not differ between size fractions. We identified arginine as a key amino acid in the modulation of the C:N ratios of core genes for bacteria, archaea, and viruses. Functional analysis reveals that particle-associated bacterial metagenomes are enriched for genes that are involved in arginine metabolism and organic nitrogen compound catabolism. Our results are consistent with nitrogen streamlining in both cellular and viral genomes on spatial scales of meters to microns. These effects are similar in magnitude to those previously reported across scales of thousands of kilometers. IMPORTANCE The genomes of marine microbes can be shaped by nutrient cycles, with ocean-scale gradients in nitrogen availability being known to influence microbial amino acid usage. It is unclear, however, how genomic properties are shaped by nutrient changes over much smaller spatial scales, for example, along the vertical transition into oxygen minimum zones (OMZs) or from the exterior to the interior of detrital particles. Here, we measure protein nitrogen usage by marine bacteria, archaea, and viruses by using metagenomes from the nitracline of the eastern tropical North Pacific OMZ, including both particle-associated and nonassociated biomass. Our results show higher genomic and proteomic nitrogen content in particle-associated microbes and at depths with higher nitrogen availability for cellular and viral genomes. This discovery suggests that stoichiometry influences microbial and viral evolution across multiple scales, including the micrometer to millimeter scale associated with particle-associated versus free-living lifestyles.

Computational Insight into Intraspecies Distinctions in Pseudoalteromonas distincta: Carotenoid-like Synthesis Traits and Genomic Heterogeneity

Advances in the computational annotation of genomes and the predictive potential of current metabolic models, based on more than thousands of experimental phenotypes, allow them to be applied to identify the diversity of metabolic pathways at the level of ecophysiology differentiation within taxa and to predict phenotypes, secondary metabolites, host-associated interactions, survivability, and biochemical productivity under proposed environmental conditions. The significantly distinctive phenotypes of members of the marine bacterial species Pseudoalteromonas distincta and an inability to use common molecular markers make their identification within the genus Pseudoalteromonas and prediction of their biotechnology potential impossible without genome-scale analysis and metabolic reconstruction. A new strain, KMM 6257, of a carotenoid-like phenotype, isolated from a deep-habituating starfish, emended the description of P. distincta, particularly in the temperature growth range from 4 to 37 °C. The taxonomic status of all available closely related species was elucidated by phylogenomics. P. distincta possesses putative methylerythritol phosphate pathway II and 4,4'-diapolycopenedioate biosynthesis, related to C30 carotenoids, and their functional analogues, aryl polyene biosynthetic gene clusters (BGC). However, the yellow-orange pigmentation phenotypes in some strains coincide with the presence of a hybrid BGC encoding for aryl polyene esterified with resorcinol. The alginate degradation and glycosylated immunosuppressant production, similar to brasilicardin, streptorubin, and nucleocidines, are the common predicted features. Starch, agar, carrageenan, xylose, lignin-derived compound degradation, polysaccharide, folate, and cobalamin biosynthesis are all strain-specific.

Mixotrophy broadens the ecological niche range of the iron oxidizer Sideroxydans sp. CL21 isolated from an iron-rich peatland

Sideroxydans sp. CL21 is a microaerobic, acid-tolerant Fe(II)-oxidizer, isolated from the Schlöppnerbrunnen fen. Since the genome size of Sideroxydans sp. CL21 is 21% larger than that of the neutrophilic Sideroxydans lithotrophicus ES-1, we hypothesized that strain CL21 contains additional metabolic traits to thrive in the fen. The common genomic content of both strains contains homologs of the putative Fe(II) oxidation genes, mtoAB and cyc2. A large part of the accessory genome in strain CL21 contains genes linked to utilization of alternative electron donors, including NiFe uptake hydrogenases, and genes encoding lactate uptake and utilization proteins, motility and biofilm formation, transposable elements, and pH homeostasis mechanisms. Next, we incubated the strain in different combinations of electron donors and characterized the fen microbial communities. Sideroxydans spp. comprised 3.33% and 3.94% of the total relative abundance in the peatland soil and peatland water, respectively. Incubation results indicate Sideroxydans sp. CL21 uses H2 and thiosulfate, while lactate only enhances growth when combined with Fe, H2, or thiosulfate. Rates of H2 utilization were highest in combination with other substrates. Thus, Sideroxydans sp. CL21 is a mixotroph, growing best by simultaneously using substrate combinations, which helps to thrive in dynamic and complex habitats.

Trait-trait relationships and tradeoffs vary with genome size in prokaryotes

We report genomic traits that have been associated with the life history of prokaryotes and highlight conflicting findings concerning earlier observed trait correlations and tradeoffs. In order to address possible explanations for these contradictions we examined trait–trait variations of 11 genomic traits from ~18,000 sequenced genomes. The studied trait–trait variations suggested: (i) the predominance of two resistance and resilience-related orthogonal axes and (ii) at least in free living species with large effective population sizes whose evolution is little affected by genetic drift an overlap between a resilience axis and an oligotrophic-copiotrophic axis. These findings imply that resistance associated traits of prokaryotes are globally decoupled from resilience related traits and in the case of free-living communities also from traits associated with resource availability. However, further inspection of pairwise scatterplots showed that resistance and resilience traits tended to be positively related for genomes up to roughly five million base pairs and negatively for larger genomes. Genome size distributions differ across habitats and our findings therefore point to habitat dependent tradeoffs between resistance and resilience. This in turn may preclude a globally consistent assignment of prokaryote genomic traits to the competitor - stress-tolerator - ruderal (CSR) schema that sorts species depending on their location along disturbance and productivity gradients into three ecological strategies and may serve as an explanation for conflicting findings from earlier studies. All reviewed genomic traits featured significant phylogenetic signals and we propose that our trait table can be applied to extrapolate genomic traits from taxonomic marker genes. This will enable to empirically evaluate the assembly of these genomic traits in prokaryotic communities from different habitats and under different productivity and disturbance scenarios as predicted via the resistance-resilience framework formulated here.

Genome-resolved analyses show an extensive diversification in key aerobic hydrocarbon-degrading enzymes across bacteria and archaea

Background

Hydrocarbons (HCs) are organic compounds composed solely of carbon and hydrogen that are mainly accumulated in oil reservoirs. As the introduction of all classes of hydrocarbons including crude oil and oil products into the environment has increased significantly, oil pollution has become a global ecological problem. However, our perception of pathways for biotic degradation of major HCs and key enzymes in these bioconversion processes has mainly been based on cultured microbes and is biased by uneven taxonomic representation. Here we used Annotree to provide a gene-centric view of the aerobic degradation ability of aliphatic and aromatic HCs in 23,446 genomes from 123 bacterial and 14 archaeal phyla. 

Results

Apart from the widespread genetic potential for HC degradation in Proteobacteria, Actinobacteriota, Bacteroidota, and Firmicutes, genomes from an additional 18 bacterial and 3 archaeal phyla also hosted key HC degrading enzymes. Among these, such degradation potential has not been previously reported for representatives in the phyla UBA8248, Tectomicrobia, SAR324, and Eremiobacterota. Genomes containing whole pathways for complete degradation of HCs were only detected in Proteobacteria and Actinobacteriota. Except for several members of Crenarchaeota, Halobacterota, and Nanoarchaeota that have tmoA, ladA, and alkB/M key genes, respectively, representatives of archaeal genomes made a small contribution to HC degradation. None of the screened archaeal genomes coded for complete HC degradation pathways studied here; however, they contribute significantly to peripheral routes of HC degradation with bacteria.

Conclusion

Phylogeny reconstruction showed that the reservoir of key aerobic hydrocarbon-degrading enzymes in Bacteria and Archaea undergoes extensive diversification via gene duplication and horizontal gene transfer. This diversification could potentially enable microbes to rapidly adapt to novel and manufactured HCs that reach the environment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08906-w.

Translation Comes First: Ancient and Convergent Selection of Codon Usage Bias Across Prokaryotic Genomes

Codon usage is the outcome of different evolutionary processes and can inform us about the conditions in which organisms live and evolve. Here, we present R_ENC', which is an improvement to the original S index developed by dos Reis et al. (2004). Our index is less sensitive to G+C content, which greatly affects synonymous codon usage in prokaryotes, making it better suited to detect selection acting on codon usage. We used R_ENC' to estimate the extent of selected codon usage bias in 1800 genomes representing 26 prokaryotic phyla. We found that Gammaproteobacteria, Betaproteobacteria, Actinobacteria, and Firmicutes are the phyla/subphyla showing more genomes with selected codon usage bias. In particular, we found that several lineages within Gammaproteobacteria and Firmicutes show a similar set of functional terms enriched in genes under selected codon usage bias, indicating convergent evolution. We also show that selected codon usage bias tends to evolve in genes coding for the translation machinery before other functional GO terms. Finally, we discuss the possibility to use R_ENC' to predict whether lineages evolved in copiotrophic or oligotrophic environments.

Disentangling the lifestyle of bacterial communities in tropical soda lakes

Microbial lifestyles may reveal niche-specific signatures and can contribute to detecting the effects of abiotic fluctuations on biogeochemical cycles. Microorganisms make a tradeoff between optimizing nutrient uptake, improving biomass yield, and overcoming environmental changes according to environmental hostility. Soda lakes are natural environments rich in carbonate and bicarbonate water, resulting in elevated pH and salinities that frequently approach saturation. We hypothesized that during the dry period (elevated pH and salinity), microorganisms try to overcome this harshness by allocating energy to the cellular maintenance process. As these environmental conditions improve during the wet period, microorganisms will begin to invest in nutrient uptake. To test this hypothesis, we evaluated four soda lakes in two different seasons by applying metagenomics combined with flow cytometry (estimate heterotrophic bacterial biomass). The natural occurrence of cyanobacterial blooms in some lakes is the main driver of carbon. These primary producers provide organic carbon that supports heterotrophic bacterial growth and, consequently, a high biomass yield. Under harsh conditions (dry season), cyanobacteria invest in nutrient uptake mechanisms, whereas heterotrophic bacteria allocate energy to survive at the expense of biomass yield. Lakes without cyanobacteria blooms invest in nutrient uptake independent of environmental hostility. This study clarifies the microbial tradeoffs in hostile environments and the impact of this choice on carbon and energy flux in tropical alkaline lakes.

Estimating maximal microbial growth rates from cultures, metagenomes, and single cells via codon usage patterns

Despite the wide perception that microbes have rapid growth rates, many environments like seawater and soil are often dominated by microorganisms that can only grow very slowly. Our knowledge about growth is necessarily biased toward easily culturable organisms, which tend to be those that grow fast, because microbial growth rates have traditionally been measured using laboratory growth experiments. However, how are potential growth rates distributed in nature? Using genomic data, we predicted the growth rates of over 200,000 organisms, including many as yet uncultivated species. These data reveal how current culture collections are strongly biased toward fast-growing organisms. Finally, we noticed a bimodal distribution of maximal growth rates, suggesting a natural division of microbial growth strategies into two classes.

Maximal growth rate is a basic parameter of microbial lifestyle that varies over several orders of magnitude, with doubling times ranging from a matter of minutes to multiple days. Growth rates are typically measured using laboratory culture experiments. Yet, we lack sufficient understanding of the physiology of most microbes to design appropriate culture conditions for them, severely limiting our ability to assess the global diversity of microbial growth rates. Genomic estimators of maximal growth rate provide a practical solution to survey the distribution of microbial growth potential, regardless of cultivation status. We developed an improved maximal growth rate estimator and predicted maximal growth rates from over 200,000 genomes, metagenome-assembled genomes, and single-cell amplified genomes to survey growth potential across the range of prokaryotic diversity; extensions allow estimates from 16S rRNA sequences alone as well as weighted community estimates from metagenomes. We compared the growth rates of cultivated and uncultivated organisms to illustrate how culture collections are strongly biased toward organisms capable of rapid growth. Finally, we found that organisms naturally group into two growth classes and observed a bias in growth predictions for extremely slow-growing organisms. These observations ultimately led us to suggest evolutionary definitions of oligotrophy and copiotrophy based on the selective regime an organism occupies. We found that these growth classes are associated with distinct selective regimes and genomic functional potentials.

Signatures of optimal codon usage in metabolic genes inform budding yeast ecology

Reverse ecology is the inference of ecological information from patterns of genomic variation. One rich, heretofore underutilized, source of ecologically relevant genomic information is codon optimality or adaptation. Bias toward codons that match the tRNA pool is robustly associated with high gene expression in diverse organisms, suggesting that codon optimization could be used in a reverse ecology framework to identify highly expressed, ecologically relevant genes. To test this hypothesis, we examined the relationship between optimal codon usage in the classic galactose metabolism (GAL) pathway and known ecological niches for 329 species of budding yeasts, a diverse subphylum of fungi. We find that optimal codon usage in the GAL pathway is positively correlated with quantitative growth on galactose, suggesting that GAL codon optimization reflects increased capacity to grow on galactose. Optimal codon usage in the GAL pathway is also positively correlated with human-associated ecological niches in yeasts of the CUG-Ser1 clade and with dairy-associated ecological niches in the family Saccharomycetaceae. For example, optimal codon usage of GAL genes is greater than 85% of all genes in the genome of the major human pathogen Candida albicans (CUG-Ser1 clade) and greater than 75% of genes in the genome of the dairy yeast Kluyveromyces lactis (family Saccharomycetaceae). We further find a correlation between optimization in the GALactose pathway genes and several genes associated with nutrient sensing and metabolism. This work suggests that codon optimization harbors information about the metabolic ecology of microbial eukaryotes. This information may be particularly useful for studying fungal dark matter-species that have yet to be cultured in the lab or have only been identified by genomic material.