Global epistasis and the emergence of function in microbial consortia.

The many functions of microbial communities emerge from a complex web of interactions between organisms and their environment. This poses a significant obstacle to engineering microbial consortia, hindering our ability to harness the potential of microorganisms for biotechnological applications. In this study, we demonstrate that the collective effect of ecological interactions between microbes in a community can be captured by simple statistical models that predict how adding a new species to a community will affect its function. These predictive models mirror the patterns of global epistasis reported in genetics, and they can be quantitatively interpreted in terms of pairwise interactions between community members. Our results illuminate an unexplored path to quantitatively predicting the function of microbial consortia from their composition, paving the way to optimizing desirable community properties and bringing the tasks of predicting biological function at the genetic, organismal, and ecological scales under the same quantitative formalism.

Genomic structure predicts metabolite dynamics in microbial communities.

The metabolic activities of microbial communities play a defining role in the evolution and persistence of life on Earth, driving redox reactions that give rise to global biogeochemical cycles. Community metabolism emerges from a hierarchy of processes, including gene expression, ecological interactions, and environmental factors. In wild communities, gene content is correlated with environmental context, but predicting metabolite dynamics from genomes remains elusive. Here, we show, for the process of denitrification, that metabolite dynamics of a community are predictable from the genes each member of the community possesses. A simple linear regression reveals a sparse and generalizable mapping from gene content to metabolite dynamics for genomically diverse bacteria. A consumer-resource model correctly predicts community metabolite dynamics from single-strain phenotypes. Our results demonstrate that the conserved impacts of metabolic genes can predict community metabolite dynamics, enabling the prediction of metabolite dynamics from metagenomes, designing denitrifying communities, and discovering how genome evolution impacts metabolism.

Microbial Interkingdom Interactions in Roots Promote Arabidopsis Survival.

Roots of healthy plants are inhabited by soil-derived bacteria, fungi, and oomycetes that have evolved independently in distinct kingdoms of life. How these microorganisms interact and to what extent those interactions affect plant health are poorly understood. We examined root-associated microbial communities from three Arabidopsis thaliana populations and detected mostly negative correlations between bacteria and filamentous microbial eukaryotes. We established microbial culture collections for reconstitution experiments using germ-free A. thaliana. In plants inoculated with mono- or multi-kingdom synthetic microbial consortia, we observed a profound impact of the bacterial root microbiota on fungal and oomycetal community structure and diversity. We demonstrate that the bacterial microbiota is essential for plant survival and protection against root-derived filamentous eukaryotes. Deconvolution of 2,862 binary bacterial-fungal interactions ex situ, combined with community perturbation experiments in planta, indicate that biocontrol activity of bacterial root commensals is a redundant trait that maintains microbial interkingdom balance for plant health.

Culturing Human Gut Microbiomes in the Laboratory.

The human gut microbiota is a complex community of prokaryotic and eukaryotic microbes and viral particles that is increasingly associated with many aspects of host physiology and health. However, the classical microbiology approach of axenic culture cannot provide a complete picture of the complex interactions between microbes and their hosts in vivo. As such, recently there has been much interest in the culture of gut microbial ecosystems in the laboratory as a strategy to better understand their compositions and functions. In this review, we discuss the model platforms and methods available in the contemporary microbiology laboratory to study human gut microbiomes, as well as current knowledge surrounding the isolation of human gut microbes for the potential construction of defined communities for use in model systems.

Community interactions drive the evolution of antibiotic tolerance in bacteria.

The emergence of antibiotic tolerance (prolonged survival against exposure) in natural bacterial populations is a major concern. Since it has been studied primarily in isogenic populations, we do not yet understand how ecological interactions in a diverse community impact the evolution of tolerance. To address this, we studied the evolutionary dynamics of a synthetic bacterial community composed of two interacting strains. In this community, an antibiotic-resistant strain protected the other, susceptible strain by degrading the antibiotic ampicillin in the medium. Surprisingly, we found that in the presence of antibiotics, the susceptible strain evolved tolerance. Tolerance was typified by an increase in survival as well as an accompanying decrease in the growth rate, highlighting a trade-off between the two. A simple mathematical model explained that the observed decrease in the death rate, even when coupled with a decreased growth rate, is beneficial in a community with weak protective interactions. In the presence of strong interactions, the model predicted that the trade-off would instead be detrimental, and tolerance would not emerge, which we experimentally verified. By whole genome sequencing the evolved tolerant isolates, we identified two genetic hot spots which accumulated mutations in parallel lines, suggesting their association with tolerance. Our work highlights that ecological interactions can promote antibiotic tolerance in bacterial communities, which has remained understudied.

Environmental fluctuations explain the universal decay of species-abundance correlations with phylogenetic distance.

Multiple ecological forces act together to shape the composition of microbial communities. Phyloecology approaches-which combine phylogenetic relationships between species with community ecology-have the potential to disentangle such forces but are often hard to connect with quantitative predictions from theoretical models. On the other hand, macroecology, which focuses on statistical patterns of abundance and diversity, provides natural connections with theoretical models but often neglects interspecific correlations and interactions. Here, we propose a unified framework combining both such approaches to analyze microbial communities. In particular, by using both cross-sectional and longitudinal metagenomic data for species abundances, we reveal the existence of an empirical macroecological law establishing that correlations in species-abundance fluctuations across communities decay from positive to null values as a function of phylogenetic dissimilarity in a consistent manner across ecologically distinct microbiomes. We formulate three variants of a mechanistic model-each relying on alternative ecological forces-that lead to radically different predictions. From these analyses, we conclude that the empirically observed macroecological pattern can be quantitatively explained as a result of shared population-independent fluctuating resources, i.e., environmental filtering and not as a consequence of, e.g., species competition. Finally, we show that the macroecological law is also valid for temporal data of a single community and that the properties of delayed temporal correlations can be reproduced as well by the model with environmental filtering.

Minorities drive growth resumption in cross-feeding microbial communities.

Microbial communities are fundamental to life on Earth. Different strains within these communities are often connected by a highly connected metabolic network, where the growth of one strain depends on the metabolic activities of other community members. While distributed metabolic functions allow microbes to reduce costs and optimize metabolic pathways, they make them metabolically dependent. Here, we hypothesize that such dependencies can be detrimental in situations where the external conditions change rapidly, as they often do in natural environments. After a shift in external conditions, microbes need to remodel their metabolism, but they can only resume growth once partners on which they depend have also adapted to the new conditions. It is currently not well understood how microbial communities resolve this dilemma and how metabolic interactions are reestablished after an environmental shift. To address this question, we investigated the dynamical responses to environmental perturbation by microbial consortia with distributed anabolic functions. By measuring the regrowth times at the single-cell level in spatially structured communities, we found that metabolic dependencies lead to a growth delay after an environmental shift. However, a minority of cells-those in the immediate neighborhood of their metabolic partners-can regrow quickly and come to numerically dominate the community after the shift. The spatial arrangement of a microbial community is thus a key factor in determining the communities' ability to maintain metabolic interactions and growth in fluctuating conditions. Our results suggest that environmental fluctuations can limit the emergence of metabolic dependencies between microorganisms.

Tracing human life trajectory using gut microbial communities by context-aware deep learning.

The gut microbial communities are highly plastic throughout life, and the human gut microbial communities show spatial-temporal dynamic patterns at different life stages. However, the underlying association between gut microbial communities and time-related factors remains unclear. The lack of context-awareness, insufficient data, and the existence of batch effect are the three major issues, making the life trajection of the host based on gut microbial communities problematic. Here, we used a novel computational approach (microDELTA, microbial-based deep life trajectory) to track longitudinal human gut microbial communities' alterations, which employs transfer learning for context-aware mining of gut microbial community dynamics at different life stages. Using an infant cohort, we demonstrated that microDELTA outperformed Neural Network for accurately predicting the age of infant with different delivery mode, especially for newborn infants of vaginal delivery with the area under the receiver operating characteristic curve of microDELTA and Neural Network at 0.811 and 0.436, respectively. In this context, we have discovered the influence of delivery mode on infant gut microbial communities. Along the human lifespan, we also applied microDELTA to a Chinese traveler cohort, a Hadza hunter-gatherer cohort and an elderly cohort. Results revealed the association between long-term dietary shifts during travel and adult gut microbial communities, the seasonal cycling of gut microbial communities for the Hadza hunter-gatherers, and the distinctive microbial pattern of elderly gut microbial communities. In summary, microDELTA can largely solve the issues in tracing the life trajectory of the human microbial communities and generate accurate and flexible models for a broad spectrum of microbial-based longitudinal researches.

Evolution and stability of complex microbial communities driven by trade-offs.

Microbial communities are ubiquitous in nature and play an important role in ecology and human health. Cross-feeding is thought to be core to microbial communities, though it remains unclear precisely why it emerges. Why have multi-species microbial communities evolved in many contexts and what protects microbial consortia from invasion? Here, we review recent insights into the emergence and stability of coexistence in microbial communities. A particular focus is the long-term evolutionary stability of coexistence, as observed for microbial communities that spontaneously evolved in the E. coli long-term evolution experiment (LTEE). We analyze these findings in the context of recent work on trade-offs between competing microbial objectives, which can constitute a mechanistic basis for the emergence of coexistence. Coexisting communities, rather than monocultures of the 'fittest' single strain, can form stable endpoints of evolutionary trajectories. Hence, the emergence of coexistence might be an obligatory outcome in the evolution of microbial communities. This implies that rather than embodying fragile metastable configurations, some microbial communities can constitute formidable ecosystems that are difficult to disrupt.

Fast growth can counteract antibiotic susceptibility in shaping microbial community resilience to antibiotics.

Microbial communities often face external perturbations that can induce lasting changes in their composition and functions. Our understanding of how multispecies communities respond to perturbations such as antibiotics is limited, with susceptibility assays performed on individual, isolated species our primary guide in predicting community transitions. Here, we studied how bacterial growth dynamics can overcome differences in antibiotic susceptibility in determining community resilience: the recovery of the original community state following antibiotic exposure. We used an experimental community containing Corynebacterium ammoniagenes and Lactobacillus plantarum that displays two alternative stable states as a result of mutual inhibition. Although C. ammoniagenes was more susceptible to chloramphenicol in monocultures, we found that chloramphenicol exposure nonetheless led to a transition from the L. plantarum-dominated to the C. ammoniagenes-dominated community state. Combining theory and experiments, we demonstrated that growth rate differences between the two species made the L. plantarum-dominated community less resilient to several antibiotics with different mechanisms of action. Taking advantage of an observed cooperativity­a dependence on population abundance­in the growth of C. ammoniagenes, we next analyzed in silico scenarios that could compromise the high resilience of the C. ammoniagenes-dominated state. The model predicted that lowering the dispersal rate, through interacting with the growth at low population densities, could make the C. ammoniagenes state fragile against virtually any kind of antibiotic, a prediction that we confirmed experimentally. Our results highlight that species susceptibility to antibiotics is often uninformative of community resilience, as growth dynamics in the wake of antibiotic exposure can play a dominant role.

Flux sampling in genome-scale metabolic modeling of microbial communities.

BACKGROUND: Microbial communities play a crucial role in ecosystem function through metabolic interactions. Genome-scale modeling is a promising method to understand these interactions and identify strategies to optimize the community. Flux balance analysis (FBA) is most often used to predict the flux through all reactions in a genome-scale model; however, the fluxes predicted by FBA depend on a user-defined cellular objective. Flux sampling is an alternative to FBA, as it provides the range of fluxes possible within a microbial community. Furthermore, flux sampling can capture additional heterogeneity across a population, especially when cells exhibit sub-maximal growth rates. RESULTS: In this study, we simulate the metabolism of microbial communities and compare the metabolic characteristics found with FBA and flux sampling. With sampling, we find significant differences in the predicted metabolism, including an increase in cooperative interactions and pathway-specific changes in predicted flux. CONCLUSIONS: Our results suggest the importance of sampling-based approaches to evaluate metabolic interactions. Furthermore, we emphasize the utility of flux sampling in quantitatively studying interactions between cells and organisms.

Ecological dependencies and the illusion of cooperation in microbial communities.

Ecological dependencies - where organisms rely on other organisms for survival - are a ubiquitous feature of life on earth. Multicellular hosts rely on symbionts to provide essential vitamins and amino acids. Legume plants similarly rely on nitrogen-fixing rhizobia to convert atmospheric nitrogen to ammonia. In some cases, dependencies can arise via loss-of-function mutations that allow one partner to benefit from the actions of another. It is common in microbiology to label ecological dependencies between species as cooperation - making it necessary to invoke cooperation-specific frameworks to explain the phenomenon. However, in many cases, such traits are not (at least initially) cooperative, because they are not selected for because of the benefits they confer on a partner species. In contrast, dependencies in microbial communities may originate from fitness benefits gained from genomic-streamlining (i.e. Black Queen Dynamics). Here, we outline how the Black Queen Hypothesis predicts the formation of metabolic dependencies via loss-of-function mutations in microbial communities, without needing to invoke any cooperation-specific explanations. Furthermore we outline how the Black Queen Hypothesis can act as a blueprint for true cooperation as well as discuss key outstanding questions in the field. The nature of interactions in microbial communities can predict the ability of natural communities to withstand and recover from disturbances. Hence, it is vital to gain a deeper understanding of the factors driving these dynamic interactions over evolutionary time.

Microbial biofilms on macroalgae harbour diverse integron gene cassettes.

Integrons are genetic platforms that capture, rearrange and express mobile modules called gene cassettes. The best characterized gene cassettes encode antibiotic resistance, but the function of most integron gene cassettes remains unknown. Functional predictions suggest that many gene cassettes could encode proteins that facilitate interactions with other cells and with the extracellular environment. Because cell interactions are essential for biofilm stability, we sequenced gene cassettes from biofilms growing on the surface of the marine macroalgae Ulva australis and Sargassum linearifolium. Algal samples were obtained from coastal rock platforms around Sydney, Australia, using seawater as a control. We demonstrated that integrons in microbial biofilms did not sample genes randomly from the surrounding seawater, but harboured specific functions that potentially provided an adaptive advantage to both the bacterial cells in biofilm communities and their macroalgal host. Further, integron gene cassettes had a well-defined spatial distribution, suggesting that each bacterial biofilm acquired these genetic elements via sampling from a large but localized pool of gene cassettes. These findings suggest two forms of filtering: a selective acquisition of different integron-containing bacterial species into the distinct biofilms on Ulva and Sargassum surfaces, and a selective retention of unique populations of gene cassettes at each sampling location.

OsCIPK2 mediated rice root microorganisms and metabolites to improve plant nitrogen uptake.

Crop roots are colonized by large numbers of microorganisms, collectively known as the root-microbiome, which modulate plant growth, development and contribute to elemental nutrient uptake. In conditions of nitrogen limitation, the over-expressed Calcineurin B-like interacting protein kinase 2 (OsCIPK2) gene with root-specific promoter (RC) has been shown to enhance growth and nitrogen uptake in rice. Analysis of root-associated bacteria through high-throughput sequencing revealed that OsCIPK2 has a significant impact on the diversity of the root microbial community under low nitrogen stress. The quantification of nifH gene expression demonstrated a significant enhancement in nitrogen-fixing capabilities in the roots of RC transgenetic rice. Synthetic microbial communities (SynCom) consisting of six nitrogen-fixing bacterial strains were observed to be enriched in the roots of RC, leading to a substantial improvement in rice growth and nitrogen uptake in nitrogen-deficient soils. Forty and twenty-three metabolites exhibiting differential abundance were identified in the roots and rhizosphere soils of RC transgenic rice compared to wild-type (WT) rice. These findings suggest that OSCIPK2 plays a role in restructuring the microbial community in the roots through the regulation of metabolite synthesis and secretion. Further experiments involving the exogenous addition of citric acid revealed that an optimal concentration of this compound facilitated the growth of nitrogen-fixing bacteria and substantially augmented their population in the soil, highlighting the importance of citric acid in promoting nitrogen fixation under conditions of low nitrogen availability. These findings suggest that OsCIPK2 plays a role in enhancing nitrogen uptake by rice plants from the soil by influencing the assembly of root microbial communities, thereby offering valuable insights for enhancing nitrogen utilization in rice cultivation.

Diversity in the utilization of different molecular classes of dissolved organic matter by heterotrophic marine bacteria.

Heterotrophic marine bacteria utilize and recycle dissolved organic matter (DOM), impacting biogeochemical cycles. It is currently unclear to what extent distinct DOM components can be used by different heterotrophic clades. Here, we ask how a natural microbial community from the Eastern Mediterranean Sea (EMS) responds to different molecular classes of DOM (peptides, amino acids, amino sugars, disaccharides, monosaccharides, and organic acids) comprising much of the biomass of living organisms. Bulk bacterial activity increased after 24 h for all treatments relative to the control, while glucose and ATP uptake decreased or remained unchanged. Moreover, while the per-cell uptake rate of glucose and ATP decreased, that of Leucin significantly increased for amino acids, reflecting their importance as common metabolic currencies in the marine environment. Pseudoalteromonadaceae dominated the peptides treatment, while different Vibrionaceae strains became dominant in response to amino acids and amino sugars. Marinomonadaceae grew well on organic acids, and Alteromonadaseae on disaccharides. A comparison with a recent laboratory-based study reveals similar peptide preferences for Pseudoalteromonadaceae, while Alteromonadaceae, for example, grew well in the lab on many substrates but dominated in seawater samples only when disaccharides were added. We further demonstrate a potential correlation between the genetic capacity for degrading amino sugars and the dominance of specific clades in these treatments. These results highlight the diversity in DOM utilization among heterotrophic bacteria and complexities in the response of natural communities. IMPORTANCE: A major goal of microbial ecology is to predict the dynamics of natural communities based on the identity of the organisms, their physiological traits, and their genomes. Our results show that several clades of heterotrophic bacteria each grow in response to one or more specific classes of organic matter. For some clades, but not others, growth in a complex community is similar to that of isolated strains in laboratory monoculture. Additionally, by measuring how the entire community responds to various classes of organic matter, we show that these results are ecologically relevant, and propose that some of these resources are utilized through common uptake pathways. Tracing the path between different resources to the specific microbes that utilize them, and identifying commonalities and differences between different natural communities and between them and lab cultures, is an important step toward understanding microbial community dynamics and predicting how communities will respond to perturbations.

Arthropod prey type drives decomposition rates and microbial community processes.

Microbial communities perform various functions, many of which contribute to ecosystem-level nutrient cycling via decomposition. Factors influencing leaf detrital decomposition are well understood in terrestrial and aquatic ecosystems, but much less is known about arthropod detrital inputs. Here, we sought to infer how differences in arthropod detritus affect microbial-driven decomposition and community function in a carnivorous pitcher plant, Sarracenia purpurea. Using sterile mesh bags filled with different types of sterile arthropod prey, we assessed if prey type influenced the rate of decomposition in pitcher plants over 7 weeks. Additionally, we measured microbial community composition and function, including hydrolytic enzyme activity and carbon substrate use. When comparing decomposition rates, we found that ant and beetle prey with higher exoskeleton content lost less mass compared with fly prey. We observed the highest protease activity in the fly treatment, which had the lowest exoskeleton content. Additionally, we saw differences in the pH of the pitcher fluid, driven by the ant treatment which had the lowest pH. According to our results from 16S rRNA gene metabarcoding, prey treatments with the highest bacterial amplicon sequence variant (ASV) richness (ant and beetle) were associated with prey that lost a lower proportion of mass over the 7 weeks. Overall, arthropod detritus provides unique nutrient sources to decomposer communities, with different prey influencing microbial hydrolytic enzyme activity and composition. IMPORTANCE: Microbial communities play pivotal roles in nutrient cycling via decomposition and nutrient transformation; however, it is often unclear how different substrates influence microbial activity and community composition. Our study highlights how different types of insects influence decomposition and, in turn, microbial composition and function. We use the aquatic pools found in a carnivorous pitcher plant as small, discrete ecosystems that we can manipulate and study independently. We find that some insect prey (flies) breaks down faster than others (beetles or ants) likely because flies contain more things that are easy for microbes to eat and derive essential nutrients from. This is also reflected in higher enzyme activity in the microbes decomposing the flies. Our work bridges a knowledge gap about how different substrates affect microbial decomposition, contributing to the broader understanding of ecosystem function in a nutrient cycling context.

Evolutionary history influences the microbiomes of a female symbiotic reproductive organ in cephalopods.

Many female squids and cuttlefishes have a symbiotic reproductive organ called the accessory nidamental gland (ANG) that hosts a bacterial consortium involved with egg defense against pathogens and fouling organisms. While the ANG is found in multiple cephalopod families, little is known about the global microbial diversity of these ANG bacterial symbionts. We used 16S rRNA gene community analysis to characterize the ANG microbiome from different cephalopod species and assess the relationship between host and symbiont phylogenies. The ANG microbiome of 11 species of cephalopods from four families (superorder: Decapodiformes) that span seven geographic locations was characterized. Bacteria of class Alphaproteobacteria, Gammaproteobacteria, and Flavobacteriia were found in all species, yet analysis of amplicon sequence variants by multiple distance metrics revealed a significant difference between ANG microbiomes of cephalopod families (weighted/unweighted UniFrac, Bray-Curtis, P = 0.001). Despite being collected from widely disparate geographic locations, members of the family Sepiolidae (bobtail squid) shared many bacterial taxa including (~50%) Opitutae (Verrucomicrobia) and Ruegeria (Alphaproteobacteria) species. Furthermore, we tested for phylosymbiosis and found a positive correlation between host phylogenetic distance and bacterial community dissimilarity (Mantel test r = 0.7). These data suggest that closely related sepiolids select for distinct symbionts from similar bacterial taxa. Overall, the ANGs of different cephalopod species harbor distinct microbiomes and thus offer a diverse symbiont community to explore antimicrobial activity and other functional roles in host fitness.IMPORTANCEMany aquatic organisms recruit microbial symbionts from the environment that provide a variety of functions, including defense from pathogens. Some female cephalopods (squids, bobtail squids, and cuttlefish) have a reproductive organ called the accessory nidamental gland (ANG) that contains a bacterial consortium that protects eggs from pathogens. Despite the wide distribution of these cephalopods, whether they share similar microbiomes is unknown. Here, we studied the microbial diversity of the ANG in 11 species of cephalopods distributed over a broad geographic range and representing 15-120 million years of host divergence. The ANG microbiomes shared some bacterial taxa, but each cephalopod species had unique symbiotic members. Additionally, analysis of host-symbiont phylogenies suggests that the evolutionary histories of the partners have been important in shaping the ANG microbiome. This study advances our knowledge of cephalopod-bacteria relationships and provides a foundation to explore defensive symbionts in other systems.

Illegal dumping of oil and gas wastewater alters arid soil microbial communities.

The Permian Basin, underlying southeast New Mexico and west Texas, is one of the most productive oil and gas (OG) provinces in the United States. Oil and gas production yields large volumes of wastewater with complex chemistries, and the environmental health risks posed by these OG wastewaters on sensitive desert ecosystems are poorly understood. Starting in November 2017, 39 illegal dumps, as defined by federal and state regulations, of OG wastewater were identified in southeastern New Mexico, releasing ~600,000 L of fluid onto dryland soils. To evaluate the impacts of these releases, we analyzed changes in soil geochemistry and microbial community composition by comparing soils from within OG wastewater dump-affected samples to unaffected zones. We observed significant changes in soil geochemistry for all dump-affected compared with control samples, reflecting the residual salts and hydrocarbons from the OG-wastewater release (e.g., enriched in sodium, chloride, and bromide). Microbial community structure significantly (P < 0.01) differed between dump and control zones, with soils from dump areas having significantly (P < 0.01) lower alpha diversity and differences in phylogenetic composition. Dump-affected soil samples showed an increase in halophilic and halotolerant taxa, including members of the Marinobacteraceae, Halomonadaceae, and Halobacteroidaceae, suggesting that the high salinity of the dumped OG wastewater was exerting a strong selective pressure on microbial community structure. Taxa with high similarity to known hydrocarbon-degrading organisms were also detected in the dump-affected soil samples. Overall, this study demonstrates the potential for OG wastewater exposure to change the geochemistry and microbial community dynamics of arid soils.IMPORTANCEThe long-term environmental health impacts resulting from releases of oil and gas (OG) wastewater, typically brines with varying compositions of ions, hydrocarbons, and other constituents, are understudied. This is especially true for sensitive desert ecosystems, where soil microbes are key primary producers and drivers of nutrient cycling. We found that releases of OG wastewater can lead to shifts in microbial community composition and function toward salt- and hydrocarbon-tolerant taxa that are not typically found in desert soils, thus altering the impacted dryland soil ecosystem. Loss of key microbial taxa, such as those that catalyze organic carbon cycling, increase arid soil fertility, promote plant health, and affect soil moisture retention, could result in cascading effects across the sensitive desert ecosystem. By characterizing environmental changes due to releases of OG wastewater to soils overlying the Permian Basin, we gain further insights into how OG wastewater may alter dryland soil microbial functions and ecosystems.

Soil microbial identity explains home-field advantage for litter decomposition.

Unraveling the mechanisms of home-field advantage (HFA) is essential to gain a complete understanding of litter decomposition processes. However, knowledge of the relationships between HFA effects and microbial communities is lacking. To examine HFA effects on litter decomposition, we identified the microbial communities and conducted a reciprocal transplant experiment, including all possible combinations of soil and litter, between sites at two elevations in cool-temperate forests. Soil origin, rather than HFA, was an important factor in controlling litter decomposition processes. Microbiome-wide association analyses identified litter fungi and bacteria specific to the source soil, which completely differed at a low taxonomic level between litter types. The relative abundance of these microbes specific to source soil was positively correlated with litter mass loss. The results indicated that the unique relationships between plant litter and soil microbes through plant-soil linkages drive litter decomposition processes. In the short term, soil disturbances resulting from land-use changes have the potential to disrupt the effect of soil origin and hinder the advancement of litter decomposition. These findings contribute to an understanding of HFA mechanisms and the impacts of land-use change on decomposition processes in forest ecosystems.

Molecular ecology of microbiomes in the wild: Common pitfalls, methodological advances and future directions.

The study of microbiomes across organisms and environments has become a prominent focus in molecular ecology. This perspective article explores common challenges, methodological advancements, and future directions in the field. Key research areas include understanding the drivers of microbiome community assembly, linking microbiome composition to host genetics, exploring microbial functions, transience and spatial partitioning, and disentangling non-bacterial components of the microbiome. Methodological advancements, such as quantifying absolute abundances, sequencing complete genomes, and utilizing novel statistical approaches, are also useful tools for understanding complex microbial diversity patterns. Our aims are to encourage robust practices in microbiome studies and inspire researchers to explore the next frontier of this rapidly changing field.