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.

Personalized Mapping of Drug Metabolism by the Human Gut Microbiome.

The human gut microbiome harbors hundreds of bacterial species with diverse biochemical capabilities. Dozens of drugs have been shown to be metabolized by single isolates from the gut microbiome, but the extent of this phenomenon is rarely explored in the context of microbial communities. Here, we develop a quantitative experimental framework for mapping the ability of the human gut microbiome to metabolize small molecule drugs: Microbiome-Derived Metabolism (MDM)-Screen. Included are a batch culturing system for sustained growth of subject-specific gut microbial communities, an ex vivo drug metabolism screen, and targeted and untargeted functional metagenomic screens to identify microbiome-encoded genes responsible for specific metabolic events. Our framework identifies novel drug-microbiome interactions that vary between individuals and demonstrates how the gut microbiome might be used in drug development and personalized medicine.

Learning beyond-pairwise interactions enables the bottom-up prediction of microbial community structure.

Understanding the assembly of multispecies microbial communities represents a significant challenge in ecology and has wide applications in agriculture, wastewater treatment, and human healthcare domains. Traditionally, studies on the microbial community assembly focused on analyzing pairwise relationships among species; however, neglecting higher-order interactions, i.e., the change of pairwise relationships in the community context, may lead to substantial deviation from reality. Herein, we have proposed a simple framework that incorporates higher-order interactions into a bottom-up prediction of the microbial community assembly and examined its accuracy using a seven-member synthetic bacterial community on a host plant, duckweed. Although the synthetic community exhibited emergent properties that cannot be predicted from pairwise coculturing results, our results demonstrated that incorporating information from three-member combinations allows the acceptable prediction of the community structure and actual interaction forces within it. This reflects that the occurrence of higher-order effects follows consistent patterns, which can be predicted even from trio combinations, the smallest unit of higher-order interactions. These results highlight the possibility of predicting, explaining, and understanding the microbial community structure from the bottom-up by learning interspecies interactions from simple beyond-pairwise combinations.

Microbiome Metabolome Integration Platform (MMIP): a web-based platform for microbiome and metabolome data integration and feature identification.

A microbial community maintains its ecological dynamics via metabolite crosstalk. Hence, knowledge of the metabolome, alongside its populace, would help us understand the functionality of a community and also predict how it will change in atypical conditions. Methods that employ low-cost metagenomic sequencing data can predict the metabolic potential of a community, that is, its ability to produce or utilize specific metabolites. These, in turn, can potentially serve as markers of biochemical pathways that are associated with different communities. We developed MMIP (Microbiome Metabolome Integration Platform), a web-based analytical and predictive tool that can be used to compare the taxonomic content, diversity variation and the metabolic potential between two sets of microbial communities from targeted amplicon sequencing data. MMIP is capable of highlighting statistically significant taxonomic, enzymatic and metabolic attributes as well as learning-based features associated with one group in comparison with another. Furthermore, MMIP can predict linkages among species or groups of microbes in the community, specific enzyme profiles, compounds or metabolites associated with such a group of organisms. With MMIP, we aim to provide a user-friendly, online web server for performing key microbiome-associated analyses of targeted amplicon sequencing data, predicting metabolite signature, and using learning-based linkage analysis, without the need for initial metabolomic analysis, and thereby helping in hypothesis generation.

The current status and trends of DNA extraction.

DNA extraction, playing an irreplaceable role in molecular biology as it is an essential step prior to various downstream biological analyses. Thus, the accuracy and reliability of downstream research outcomes depend largely on upstream DNA extraction methodology. However, with the advancement of downstream DNA detection techniques, the development of corresponding DNA extraction methods is lagging behind. The most innovative DNA extraction techniques are silica- or magnetic-based. Recent studies have demonstrated that plant fiber-based adsorbents (PF-BAs) have stronger DNA capturing ability than classic materials. Moreover, magnetic ionic liquid (MIL)-based DNA extraction has gathered attention lately, and extrachromosomal circular DNA (eccDNA), cell-free DNA (cfDNA), and microbial community DNA are current research hotspots. These require specific extraction methods, along with constant improvements in the way they are used. This review discusses the significance as well as the direction of innovation of DNA extraction methods to try to provide valuable references including current status and trends for DNA extraction.

Stabilizing microbial communities by looped mass transfer.

Building and changing a microbiome at will and maintaining it over hundreds of generations has so far proven challenging. Despite best efforts, complex microbiomes appear to be susceptible to large stochastic fluctuations. Current capabilities to assemble and control stable complex microbiomes are limited. Here, we propose a looped mass transfer design that stabilizes microbiomes over long periods of time. Five local microbiomes were continuously grown in parallel for over 114 generations and connected by a loop to a regional pool. Mass transfer rates were altered and microbiome dynamics were monitored using quantitative high-throughput flow cytometry and taxonomic sequencing of whole communities and sorted subcommunities. Increased mass transfer rates reduced local and temporal variation in microbiome assembly, did not affect functions, and overcame stochasticity, with all microbiomes exhibiting high constancy and increasing resistance. Mass transfer synchronized the structures of the five local microbiomes and nestedness of certain cell types was eminent. Mass transfer increased cell number and thus decreased net growth rates µ'. Subsets of cells that did not show net growth µ'SCx were rescued by the regional pool R and thus remained part of the microbiome. The loop in mass transfer ensured the survival of cells that would otherwise go extinct, even if they did not grow in all local microbiomes or grew more slowly than the actual dilution rate D would allow. The rescue effect, known from metacommunity theory, was the main stabilizing mechanism leading to synchrony and survival of subcommunities, despite differences in cell physiological properties, including growth rates.

Geological activity shapes the microbiome in deep-subsurface aquifers by advection.

Subsurface environments host diverse microorganisms in fluid-filled fractures; however, little is known about how geological and hydrological processes shape the subterranean biosphere. Here, we sampled three flowing boreholes weekly for 10 mo in a 1478-m-deep fractured rock aquifer to study the role of fracture activity (defined as seismically or aseismically induced fracture aperture change) and advection on fluid-associated microbial community composition. We found that despite a largely stable deep-subsurface fluid microbiome, drastic community-level shifts occurred after events signifying physical changes in the permeable fracture network. The community-level shifts include the emergence of microbial families from undetected to over 50% relative abundance, as well as the replacement of the community in one borehole by the earlier community from a different borehole. Null-model analysis indicates that the observed spatial and temporal community turnover was primarily driven by stochastic processes (as opposed to deterministic processes). We, therefore, conclude that the observed community-level shifts resulted from the physical transport of distinct microbial communities from other fracture(s) that outpaced environmental selection. Given that geological activity is a major cause of fracture activity and that geological activity is ubiquitous across space and time on Earth, our findings suggest that advection induced by geological activity is a general mechanism shaping the microbial biogeography and diversity in deep-subsurface habitats across the globe.

Analysis of endophytic bacterial diversity in seeds of different genotypes of cotton and the suppression of Verticillium wilt pathogen infection by a synthetic microbial community.

BACKGROUND: In agricultural production, fungal diseases significantly impact the yield and quality of cotton (Gossypium spp.) with Verticillium wilt posing a particularly severe threat. RESULTS: This study is focused on investigating the effectiveness of endophytic microbial communities present in the seeds of disease-resistant cotton genotypes in the control of cotton Verticillium wilt. The technique of 16S ribosomal RNA (16S rRNA) amplicon sequencing identified a significant enrichment of the Bacillus genus in the resistant genotype Xinluzao 78, which differed from the endophytic bacterial community structure in the susceptible genotype Xinluzao 63. Specific enriched strains were isolated and screened from the seeds of Xinluzao 78 to further explore the biological functions of seed endophytes. A synthetic microbial community (SynCom) was constructed using the broken-rod model, and seeds of the susceptible genotype Xinluzao 63 in this community that had been soaked with the SynCom were found to significantly control the occurrence of Verticillium wilt and regulate the growth of cotton plants. Antibiotic screening techniques were used to preliminarily identify the colonization of strains in the community. These techniques revealed that the strains can colonize plant tissues and occupy ecological niches in cotton tissues through a priority effect, which prevents infection by pathogens. CONCLUSION: This study highlights the key role of seed endophytes in driving plant disease defense and provides a theoretical basis for the future application of SynComs in agriculture.

Effects of a co-bacterial agent on the growth, disease control, and quality of ginseng based on rhizosphere microbial diversity.

BACKGROUND: The ginseng endophyte Paenibacillus polymyxa Pp-7250 (Pp-7250) has multifaceted roles such as preventing ginseng diseases, promoting growth, increasing ginsenoside accumulation, and degrading pesticide residues, however, these effects still have room for improvements. Composite fungicides are an effective means to improve the biocontrol effect of fungicides, but the effect of Pp-7250 in combination with its symbiotic bacteria on ginseng needs to be further investigated, and its mechanism of action has not been elucidated. In this study, a series of experiments was conducted to elucidate the effect of Paenibacillus polymyxa and Bacillus cereus co-bacterial agent on the yield and quality of understory ginseng, and to investigate their mechanism of action. RESULTS: The results indicated that P. polymyxa and B. cereus co-bacterial agent (PB) treatment improved ginseng yield, ginsenoside accumulation, disease prevention, and pesticide degradation. The mechanism is that PB treatment increased the abundance of beneficial microorganisms, including Rhodanobacter, Pseudolabrys, Gemmatimonas, Bacillus, Paenibacillus, Cortinarius, Russula, Paecilomyces, and Trechispora, and decreased the abundance of pathogenic microorganisms, including Ellin6067, Acidibacter, Fusarium, Tetracladium, Alternaria, and Ilyonectria in ginseng rhizosphere soil. PB co-bacterial agents enhanced the function of microbial metabolic pathways, biosynthesis of secondary metabolites, biosynthesis of antibiotics, biosynthesis of amino acids, carbon fixation pathways in prokaryotes, DNA replication, and terpenoid backbone biosynthesis, and decreased the function of microbial plant pathogens and animal pathogens. CONCLUSION: The combination of P. polymyxa and B. cereus may be a potential biocontrol agent to promote the resistance of ginseng to disease and improve the yield, quality, and pesticide degradation.

EXPERT: transfer learning-enabled context-aware microbial community classification.

Microbial community classification enables identification of putative type and source of the microbial community, thus facilitating a better understanding of how the taxonomic and functional structure were developed and maintained. However, previous classification models required a trade-off between speed and accuracy, and faced difficulties to be customized for a variety of contexts, especially less studied contexts. Here, we introduced EXPERT based on transfer learning that enabled the classification model to be adaptable in multiple contexts, with both high efficiency and accuracy. More importantly, we demonstrated that transfer learning can facilitate microbial community classification in diverse contexts, such as classification of microbial communities for multiple diseases with limited number of samples, as well as prediction of the changes in gut microbiome across successive stages of colorectal cancer. Broadly, EXPERT enables accurate and context-aware customized microbial community classification, and potentiates novel microbial knowledge discovery.

Revealing the dynamics and mechanisms of bacterial interactions in cheese production with metabolic modelling.

Cheese taste and flavour properties result from complex metabolic processes occurring in microbial communities. A deeper understanding of such mechanisms makes it possible to improve both industrial production processes and end-product quality through the design of microbial consortia. In this work, we caracterise the metabolism of a three-species community consisting of Lactococcus lactis, Lactobacillus plantarum and Propionibacterium freudenreichii during a seven-week cheese production process. Using genome-scale metabolic models and omics data integration, we modeled and calibrated individual dynamics using monoculture experiments, and coupled these models to capture the metabolism of the community. This model accurately predicts the dynamics of the community, enlightening the contribution of each microbial species to organoleptic compound production. Further metabolic exploration revealed additional possible interactions between the bacterial species. This work provides a methodological framework for the prediction of community-wide metabolism and highlights the added value of dynamic metabolic modeling for the comprehension of fermented food processes.

Difference in microbial community structure along a gradient of crater altitude: insights from the Nushan volcano.

The variation in the soil microbial community along the altitude gradient has been widely documented. However, the structure and function of the microbial communities distributed along the altitude gradient in the crater still need to be determined. We gathered soil specimens from different elevations within the Nushan volcano crater to bridge this knowledge gap. We investigated the microbial communities of bacteria and fungi in the soil. It is noteworthy that the microbial alpha diversity peaks in the middle of the crater. However, network analysis shows that bacterial (nodes 760 vs 613 vs 601) and fungal (nodes 328 vs 224 vs 400) communities are most stable at the bottom and top of the crater, respectively. Furthermore, the soil microbial network exhibited a decline, followed by an increase across varying altitudes. The core microorganisms displayed the highest correlation with pH and alkaline phosphatase (AP, as determined through redundancy analysis (RDA) and Mantel tests for correlation analysis. The fungal community has a higher number of core microorganisms, while the bacterial core microorganisms demonstrate greater susceptibility to environmental factors. In conclusion, we utilized Illumina sequencing techniques to assess the disparities in the structure and function of bacteria and fungi in the soil.IMPORTANCEThese findings serve as a foundation for future investigations on microbial communities present in volcanic soil.

Successional changes in bacterial phyllosphere communities are plant-host species dependent.

Phyllosphere microbial communities are increasingly experiencing intense pulse disturbance events such as drought. It is currently unknown how phyllosphere communities respond to such disturbances and if they are able to recover. We explored the stability of phyllosphere communities over time, in response to drought stress, and under recovery from drought on temperate forage grasses. Compositional or functional changes were observed during the disturbance period and whether communities returned to non-stressed levels following recovery. Here, we found that phyllosphere community composition shifts as a result of simulated drought but does not fully recover after irrigation is resumed and that the degree of community response to drought is host species dependent. However, while community composition had changed, we found a high level of functional stability (resistance) over time and in the water deficit treatment. Ecological modeling enabled us to understand community assembly processes over a growing season and to determine if they were disrupted during a disturbance event. Phyllosphere community succession was characterized by a strong level of ecological drift, but drought disturbance resulted in variable selection, or, in other words, communities were diverging due to differences in selective pressures. This successional divergence of communities with drought was unique for each host species. Understanding phyllosphere responses to environmental stresses is important as climate change-induced stresses are expected to reduce crop productivity and phyllosphere functioning. IMPORTANCE: Leaf surface microbiomes have the potential to influence agricultural and ecosystem productivity. We assessed their stability by determining composition, functional resistance, and resilience. Resistance is the degree to which communities remain unchanged as a result of disturbance, and resilience is the ability of a community to recover to pre-disturbance conditions. By understanding the mechanisms of community assembly and how they relate to the resistance and resilience of microbial communities under common environmental stresses such as drought, we can better understand how communities will adapt to a changing environment and how we can promote healthy agricultural microbiomes. In this study, phyllosphere compositional stability was highly related to plant host species phylogeny and, to a lesser extent, known stress tolerances. Phyllosphere community assembly and stability are a result of complex interactions of ecological processes that are differentially imposed by host species.

Activated sludge microbial community assembly: the role of influent microbial community immigration.

Wastewater treatment plants (WWTPs) are host to diverse microbial communities and receive a constant influx of microbes from influent wastewater. However, the impact of immigrants on the structure and activities of the activated sludge (AS) microbial community remains unclear. To gain insight on this phenomenon known as perpetual community coalescence, the current study utilized controlled manipulative experiments that decoupled the influent wastewater composition from the microbial populations to reveal the fundamental mechanisms involved in immigration between sewers and AS-WWTP. The immigration dynamics of heterotrophs were analyzed by harvesting wastewater biomass solids from three different sewer systems and adding to synthetic wastewater. Immigrating influent populations were observed to contribute up to 14% of the sequencing reads in the AS. By modeling the net growth rate of taxa, it was revealed that immigrants primarily exhibited low or negative net growth rates. By developing a protocol to reproducibly grow AS-WWTP communities in the lab, we have laid down the foundational principles for the testing of operational factors creating community variations with low noise and appropriate replication. Understanding the processes that drive microbial community diversity and assembly is a key question in microbial ecology. In the future, this knowledge can be used to manipulate the structure of microbial communities and improve system performance in WWTPs.IMPORTANCEIn biological wastewater treatment processes, the microbial community composition is essential in the performance and stability of the system. This study developed a reproducible protocol to investigate the impact of influent immigration (or perpetual coalescence of the sewer and activated sludge communities) with appropriate reproducibility and controls, allowing intrinsic definitions of core and immigrant populations to be established. The method developed herein will allow sequential manipulative experiments to be performed to test specific hypothesis and optimize wastewater treatment processes to meet new treatment goals.

Unravelling metabolic cross-feeding in a yeast-bacteria community using 13 C-based proteomics.

Cross-feeding is fundamental to the diversity and function of microbial communities. However, identification of cross-fed metabolites is often challenging due to the universality of metabolic and biosynthetic intermediates. Here, we use 13 C isotope tracing in peptides to elucidate cross-fed metabolites in co-cultures of Saccharomyces cerevisiae and Lactococcus lactis. The community was grown on lactose as the main carbon source with either glucose or galactose fraction of the molecule labelled with 13 C. Data analysis allowing for the possible mass-shifts yielded hundreds of peptides for which we could assign both species identity and labelling degree. The labelling pattern showed that the yeast utilized galactose and, to a lesser extent, lactic acid shared by L. lactis as carbon sources. While the yeast provided essential amino acids to the bacterium as expected, the data also uncovered a complex pattern of amino acid exchange. The identity of the cross-fed metabolites was further supported by metabolite labelling in the co-culture supernatant, and by diminished fitness of a galactose-negative yeast mutant in the community. Together, our results demonstrate the utility of 13 C-based proteomics for uncovering microbial interactions.

Microbial and transcriptional response of Acropora valida and Turbinaria peltata to Vibrio coralliilyticus challenge: insights into corals disease resistance.

BACKGROUND: Coral diseases are significant drivers of global coral reef degradation, with pathogens dominated by Vibrio coralliilyticus playing a prominent role in the development of coral diseases. Coral phenotype, symbiotic microbial communities, and host transcriptional regulation have been well-established as factors involved in determining coral disease resistance, but the underlying mechanisms remain incompletely understood. METHODS: This study employs high-throughput sequencing to analyse the symbiotic microbial and transcriptional response of the hosts in order to evaluate the disease resistance of Acropora valida and Turbinaria peltata exposed to Vibrio coralliilyticus. RESULTS: A. valida exhibited pronounced bleaching and tissue loss within 7 h of pathogen infection, whereas T. peltata showed no signs of disease throughout the experiment. Microbial diversity analyses revealed that T. peltata had a more flexible microbial community and a higher relative abundance of potential beneficial bacteria compared to A. valida. Although Vibrio inoculation resulted in a more significant decrease in the Symbiodiniaceae density of A. valida compared to that of T. peltata, it did not lead to recombination of the coral host and Symbiodiniaceae in either coral species. RNA-seq analysis revealed that the interspecific differences in the transcriptional regulation of hosts after Vibrio inoculation. Differentially expressed genes in A. valida were mainly enriched in the pathways associated with energy supply and immune response, such as G protein-coupled receptor signaling, toll-like receptor signaling, regulation of TOR signaling, while these genes in T. peltata were mainly involved in the pathway related to immune homeostasis and ion transport, such as JAK-STAT signaling pathway and regulation of ion transport. CONCLUSIONS: Pathogenic challenges elicit different microbial and transcriptional shifts across coral species. This study offers novel insights into molecular mechanisms of coral resistance to disease.

High-throughput sequencing reveals differences in microbial community structure and diversity in the conjunctival tissue of healthy and type 2 diabetic mice.

BACKGROUND: To investigate the differences in bacterial and fungal community structure and diversity in conjunctival tissue of healthy and diabetic mice. METHODS: RNA-seq assays and high-throughput sequencing of bacterial 16 S rDNA and fungal internal transcribed spacer (ITS) gene sequences were used to identify differentially expressed host genes and fungal composition profiles in conjunctival tissues of diabetic BKS-db/db mice and BKS (control) mice. Functional enrichment analysis of differentially expressed genes and the correlation between the relative abundance of bacterial and fungal taxa in the intestinal mucosa were also performed. RESULTS: Totally, 449 differential up-regulated genes and 1,006 down-regulated genes were identified in the conjunctival tissues of diabetic mice. The differentially expressed genes were mainly enriched in metabolism-related functions and pathways. A decrease in conjunctival bacterial species diversity and abundance in diabetic mice compared to control mice. In contrast, fungal species richness and diversity were not affected by diabetes. The microbial colonies were mainly associated with cellular process pathways regulating carbohydrate and lipid metabolism, as well as cell growth and death. Additionally, some interactions between bacteria and fungi at different taxonomic levels were also observed. CONCLUSION: The present study revealed significant differences in the abundance and composition of bacterial and fungal communities in the conjunctival tissue of diabetic mice compared to control mice. The study also highlighted interactions between bacteria and fungi at different taxonomic levels. These findings may have implications for the diagnosis and treatment of diabetes.

Drought resistance and resilience of rhizosphere communities in forest soils from the cellular to ecosystem scale - insights from 13C pulse labeling.

The link between above- and belowground communities is a key uncertainty in drought and rewetting effects on forest carbon (C) cycle. In young beech model ecosystems and mature naturally dry pine forest exposed to 15-yr-long irrigation, we performed 13C pulse labeling experiments, one during drought and one 2 wk after rewetting, tracing tree assimilates into rhizosphere communities. The 13C pulses applied in tree crowns reached soil microbial communities of the young and mature forests one and 4 d later, respectively. Drought decreased the transfer of labeled assimilates relative to the irrigation treatment. The 13C label in phospholipid fatty acids (PLFAs) indicated greater drought reduction of assimilate incorporation by fungi (-85%) than by gram-positive (-43%) and gram-negative bacteria (-58%). 13C label incorporation was more strongly reduced for PLFAs (cell membrane) than for microbial cytoplasm extracted by chloroform. This suggests that fresh rhizodeposits are predominantly used for osmoregulation or storage under drought, at the expense of new cell formation. Two weeks after rewetting, 13C enrichment in PLFAs was greater in previously dry than in continuously moist soils. Drought and rewetting effects were greater in beech systems than in pine forest. Belowground C allocation and rhizosphere communities are highly resilient to drought.

Is there a latitudinal diversity gradient for symbiotic microbes? A case study with sensitive partridge peas.

Mutualism is thought to be more prevalent in the tropics than temperate zones and may therefore play an important role in generating and maintaining high species richness found at lower latitudes. However, results on the impact of mutualism on latitudinal diversity gradients are mixed, and few empirical studies sample both temperate and tropical regions. We investigated whether a latitudinal diversity gradient exists in the symbiotic microbial community associated with the legume Chamaecrista nictitans. We sampled bacteria DNA from nodules and the surrounding soil of plant roots across a latitudinal gradient (38.64-8.68 °N). Using 16S rRNA sequence data, we identified many non-rhizobial species within C. nictitans nodules that cannot form nodules or fix nitrogen. Species richness increased towards lower latitudes in the non-rhizobial portion of the nodule community but not in the rhizobial community. The microbe community in the soil did not effectively predict the non-rhizobia community inside nodules, indicating that host selection is important for structuring non-rhizobia communities in nodules. We next factorially manipulated the presence of three non-rhizobia strains in greenhouse experiments and found that co-inoculations of non-rhizobia strains with rhizobia had a marginal effect on nodule number and no effect on plant growth. Our results suggest that these non-rhizobia bacteria are likely commensals-species that benefit from associating with a host but are neutral for host fitness. Overall, our study suggests that temperate C. nictitans plants are more selective in their associations with the non-rhizobia community, potentially due to differences in soil nitrogen across latitude.