Experimental Evidence that Stochasticity Contributes to Bacterial Composition and Functioning in a Decomposer Community

Rainfall-induced changes in aquatic microbial communities and stability of dissolved organic matter: Insight from a Fen river analysis

Microbial communities are pivotal in aquatic ecosystems, as they affect water quality, energy dynamics, nutrient cycling, and hydrological stability. This study explored the effects of rainfall on hydrological and photosynthetic parameters, microbial composition, and functional gene profiles in the Fen River. Our results demonstrated that rainfall-induced decreases in stream temperature, dissolved oxygen, pH, total phosphorus, chemical oxygen demand, and dissolved organic carbon concentrations. In contrast, rainfall increased total dissolved solids, salinity, and ammonia-nitrogen concentrations. A detailed microbial community structure analysis revealed that Cyanobacteria was the dominant microbial taxon in the Fen River, accounting for approximately 75% and 25% of the microalgal and bacterial communities, respectively. The abundance of Chlorophyta and Bacillariophyta increased by 47.66% and 29.92%, respectively, whereas the relative abundance of Bacteroidetes decreased by 37.55% under rainfall conditions. Stochastic processes predominantly affected the assembly of the bacterial community on rainy days. Functional gene analysis revealed variations in bacterial functions between sunny (Sun) and rainy (Rain) conditions, particularly in genes associated with the carbon cycle. The 3-oxoacyl-[acyl-carrier-protein] reductase gene was more abundant in the Fen River bacterial community. Particular genes involved in metabolism and environmental information processing, including the acetyl-CoA C-acetyltransferase (atoB), enoyl-CoA hydratase (paaF), and branched-chain amino acid transport system gene (livK), which are integral to environmental information processing, were more abundant in Sun than the Rain conditions. In contrast, the phosphate transport system gene, the galactose metabolic gene, and the pyruvate metabolic gene were more abundant in Rain. The excitation-emission matrix analysis with parallel factor analysis identified four fluorescence components (C1-C4) in the river, which were predominantly protein- (C1) and humic-like (C2-C4) substances. Rainfall affected organic matter production and transport, leading to changes in the degradation and stability of dissolved organic matter. Overall, this study offers insight into how rainfall affects aquatic ecosystems.

High immigration rates critical for establishing emigration-driven diversity in microbial communities

Unraveling the mechanisms governing the diversity of ecological communities is a central goal in ecology. Although microbial dispersal constitutes an important ecological process, the effect of dispersal on microbial diversity is poorly understood. Here, we sought to fill this gap by combining a generalized Lotka-Volterra model with experimental investigations. Our model showed that emigration increases the diversity of the community when the immigration rate crosses a defined threshold, which we identified as Ineutral. We also found that at high immigration rates, emigration weakens the relative abundance of fast-growing species and thus enhances the mass effect and increases the diversity. We experimentally confirmed this finding using co-cultures of 20 bacterial strains isolated from the soil. Our model further showed that Ineutral decreases with the increase of species pool size, growth rate, and interspecies interaction. Our work deepens the understanding of the effects of dispersal on the diversity of natural communities.

Investigating eco-evolutionary processes of microbial community assembly in the wild using a model leaf litter system

Microbial communities are not the easiest to manipulate experimentally in natural ecosystems. However, leaf litter-topmost layer of surface soil-is uniquely suitable to investigate the complexities of community assembly. Here, we reflect on over a decade of collaborative work to address this topic using leaf litter as a model system in Southern California ecosystems. By leveraging a number of methodological advantages of the system, we have worked to demonstrate how four processes-selection, dispersal, drift, and diversification-contribute to bacterial and fungal community assembly and ultimately impact community functioning. Although many dimensions remain to be investigated, our initial results demonstrate that both ecological and evolutionary processes occur simultaneously to influence microbial community assembly. We propose that the development of additional and experimentally tractable microbial systems will be enormously valuable to test the role of eco-evolutionary processes in natural settings and their implications in the face of rapid global change.

Responses of bacterial and three sub-microeukaryote communities in the water of white shrimp Penaeus vannamei aquaculture ponds in two polyculture models

Polyculture operations in freshwater aquaculture ponds can disrupt microbial communities. High-throughput sequencing was used to assess the impact of polyculture operations on bacterial and three sub-microeukaryote communities (fungi, zooplankton, and eukaryotic phytoplankton) in Penaeus vannamei aquaculture ponds containing oriental river prawns and giant freshwater prawns, respectively. The results showed that the bacterial community was less sensitive than the microeukaryote communities to both the polyculture activity and environmental variations. The polyculture of giant freshwater prawns rather than oriental river prawns was the primary factor affecting the beta diversity of the three sub-microeukaryote communities. This may be due to the larger biomass of the polyculture varieties of giant freshwater prawns compared with oriental river prawns. The polyculture activity of giant freshwater prawns with a higher density and that of oriental river prawns with a lower density increased the stochasticity of the community assembly of the three sub-microeukaryote communities. It also affected the topological properties of the microbial communities, including greater correlations between ecosystem elements, and reducing the correlations among zooplanktons. The eukaryotic phytoplankton was the only microbial community that could also be explained by nutrient variation (mainly the total nitrogen). This highlights the potential role of the eukaryotic phytoplankton as a suitable indicator of the effects of nutrient input into ecosystems.

Variation in Sphingomonas traits across habitats and phylogenetic clades

Whether microbes show habitat preferences is a fundamental question in microbial ecology. If different microbial lineages have distinct traits, those lineages may occur more frequently in habitats where their traits are advantageous. Sphingomonas is an ideal bacterial clade in which to investigate how habitat preference relates to traits because these bacteria inhabit diverse environments and hosts. Here we downloaded 440 publicly available Sphingomonas genomes, assigned them to habitats based on isolation source, and examined their phylogenetic relationships. We sought to address whether: (1) there is a relationship between Sphingomonas habitat and phylogeny, and (2) whether there is a phylogenetic correlation between key, genome-based traits and habitat preference. We hypothesized that Sphingomonas strains from similar habitats would cluster together in phylogenetic clades, and key traits that improve fitness in specific environments should correlate with habitat. Genome-based traits were categorized into the Y-A-S trait-based framework for high growth yield, resource acquisition, and stress tolerance. We selected 252 high quality genomes and constructed a phylogenetic tree with 12 well-defined clades based on an alignment of 404 core genes. Sphingomonas strains from the same habitat clustered together within the same clades, and strains within clades shared similar clusters of accessory genes. Additionally, key genome-based trait frequencies varied across habitats. We conclude that Sphingomonas gene content reflects habitat preference. This knowledge of how environment and host relate to phylogeny may also help with future functional predictions about Sphingomonas and facilitate applications in bioremediation.

Using Plate-Wash PCR and High-Throughput Sequencing to Measure Cultivated Diversity for Natural Product Discovery Efforts

Molecular techniques continue to reveal a growing disparity between the immense diversity of microbial life and the small proportion that is in pure culture. The disparity, originally dubbed “the great plate count anomaly” by Staley and Konopka, has become even more vexing given our increased understanding of the importance of microbiomes to a host and the role of microorganisms in the vital biogeochemical functions of our biosphere. Searching for novel antimicrobial drug targets often focuses on screening a broad diversity of microorganisms. If diverse microorganisms are to be screened, they need to be cultivated. Recent innovative research has used molecular techniques to assess the efficacy of cultivation efforts, providing invaluable feedback to cultivation strategies for isolating targeted and/or novel microorganisms. Here, we aimed to determine the efficiency of cultivating representative microorganisms from a non-human, mammalian microbiome, identify those microorganisms, and determine the bioactivity of isolates. Sequence-based data indicated that around 57% of the ASVs detected in the original inoculum were cultivated in our experiments, but nearly 53% of the total ASVs that were present in our cultivation experiments were not detected in the original inoculum. In light of our controls, our data suggests that when molecular tools were used to characterize our cultivation efforts, they provided a more complete and more complex, understanding of which organisms were present compared to what was eventually detected during cultivation. Lastly, about 3% of the isolates collected from our cultivation experiments showed inhibitory bioactivity against an already multidrug-resistant pathogen panel, further highlighting the importance of informing and directing future cultivation efforts with molecular tools.

Soil microbiome predictability increases with spatial and taxonomic scale

Soil microorganisms shape ecosystem function, yet it remains an open question whether we can predict the composition of the soil microbiome in places before observing it. Furthermore, it is unclear whether the predictability of microbial life exhibits taxonomic- and spatial-scale dependence, as it does for macrobiological communities. Here, we leverage multiple large-scale soil microbiome surveys to develop predictive models of bacterial and fungal community composition in soil, then test these models against independent soil microbial community surveys from across the continental United States. We find remarkable scale dependence in community predictability. The predictability of bacterial and fungal communities increases with the spatial scale of observation, and fungal predictability increases with taxonomic scale. These patterns suggest that there is an increasing importance of deterministic versus stochastic processes with scale, consistent with findings in plant and animal communities, suggesting a general scaling relationship across biology. Biogeochemical functional groups and high-level taxonomic groups of microorganisms were equally predictable, indicating that traits and taxonomy are both powerful lenses for understanding soil communities. By focusing on out-of-sample prediction, these findings suggest an emerging generality in our understanding of the soil microbiome, and that this understanding is fundamentally scale dependent.

Adaptive differentiation and rapid evolution of a soil bacterium along a climate gradient

Increasing evidence suggests that evolutionary processes frequently shape ecological patterns; however, most microbiome studies thus far have focused on only the ecological responses of these communities. By using parallel field experiments and focusing in on a model soil bacterium, we showed that bacterial “species” are differentially adapted to local climates, leading to changes in their composition. Furthermore, we detected strain-level evolution, providing direct evidence that both ecological and evolutionary processes operate on annual timescales. The consideration of eco-evolutionary dynamics may therefore be important to understand the response of soil microbiomes to future environmental change.

Microbial community responses to environmental change are largely associated with ecological processes; however, the potential for microbes to rapidly evolve and adapt remains relatively unexplored in natural environments. To assess how ecological and evolutionary processes simultaneously alter the genetic diversity of a microbiome, we conducted two concurrent experiments in the leaf litter layer of soil over 18 mo across a climate gradient in Southern California. In the first experiment, we reciprocally transplanted microbial communities from five sites to test whether ecological shifts in ecotypes of the abundant bacterium, Curtobacterium, corresponded to past adaptive differentiation. In the transplanted communities, ecotypes converged toward that of the native communities growing on a common litter substrate. Moreover, these shifts were correlated with community-weighted mean trait values of the Curtobacterium ecotypes, indicating that some of the trait variation among ecotypes could be explained by local adaptation to climate conditions. In the second experiment, we transplanted an isogenic Curtobacterium strain and tracked genomic mutations associated with the sites across the same climate gradient. Using a combination of genomic and metagenomic approaches, we identified a variety of nonrandom, parallel mutations associated with transplantation, including mutations in genes related to nutrient acquisition, stress response, and exopolysaccharide production. Together, the field experiments demonstrate how both demographic shifts of previously adapted ecotypes and contemporary evolution can alter the diversity of a soil microbiome on the same timescale.

Considerations for mosquito microbiome research from the Mosquito Microbiome Consortium

In the past decade, there has been increasing interest in mosquito microbiome research, leading to large amounts of data on different mosquito species, with various underlying physiological characteristics, and from diverse geographical locations. However, guidelines and standardized methods for conducting mosquito microbiome research are lacking. To streamline methods in mosquito microbiome research and optimize data quality, reproducibility, and comparability, as well as facilitate data curation in a centralized location, we are establishing the Mosquito Microbiome Consortium, a collaborative initiative for the advancement of mosquito microbiome research. Our overall goal is to collectively work on unraveling the role of the mosquito microbiome in mosquito biology, while critically evaluating its potential for mosquito-borne disease control. This perspective serves to introduce the consortium and invite broader participation. It highlights the issues we view as most pressing to the community and proposes guidelines for conducting mosquito microbiome research. We focus on four broad areas in this piece: (1) sampling/experimental design for field, semi-field, or laboratory studies; (2) metadata collection; (3) sample processing, sequencing, and use of appropriate controls; and (4) data handling and analysis. We finally summarize current challenges and highlight future directions in mosquito microbiome research. We hope that this piece will spark discussions around this area of disease vector biology, as well as encourage careful considerations in the design and implementation of mosquito microbiome research. Video Abstract.

Direct quantification of ecological drift at the population level in synthetic bacterial communities

In community ecology, drift refers to random births and deaths in a population. In microbial ecology, drift is estimated indirectly via community snapshots but in this way, it is almost impossible to distinguish the effect of drift from the effect of other ecological processes. Controlled experiments where drift is quantified in isolation from other processes are still missing. Here we isolate and quantify drift in a series of controlled experiments on simplified and tractable bacterial communities. We detect drift arising randomly in the populations within the communities and resulting in a 1.4–2% increase in their growth rate variability on average. We further use our experimental findings to simulate complex microbial communities under various conditions of selection and dispersal. We find that the importance of drift increases under high selection and low dispersal, where it can lead to ~5% of species loss and to ~15% increase in β-diversity. The species extinct by drift are mainly rare, but they become increasingly less rare when selection increases, and dispersal decreases. Our results provide quantitative insights regarding the properties of drift in bacterial communities and suggest that it accounts for a consistent fraction of the observed stochasticity in natural surveys.

Stochastic Dispersal Rather Than Deterministic Selection Explains the Spatio-Temporal Distribution of Soil Bacteria in a Temperate Grassland

Spatial and temporal processes shaping microbial communities are inseparably linked but rarely studied together. By Illumina 16S rRNA sequencing, we monitored soil bacteria in 360 stations on a 100 square meter plot distributed across six intra-annual samplings in a rarely managed, temperate grassland. Using a multi-tiered approach, we tested the extent to which stochastic or deterministic processes influenced the composition of local communities. A combination of phylogenetic turnover analysis and null modeling demonstrated that either homogenization by unlimited stochastic dispersal or scenarios, in which neither stochastic processes nor deterministic forces dominated, explained local assembly processes. Thus, the majority of all sampled communities (82%) was rather homogeneous with no significant changes in abundance-weighted composition. However, we detected strong and uniform taxonomic shifts within just nine samples in early summer. Thus, community snapshots sampled from single points in time or space do not necessarily reflect a representative community state. The potential for change despite the overall homogeneity was further demonstrated when the focus shifted to the rare biosphere. Rare OTU turnover, rather than nestedness, characterized abundance-independent β-diversity. Accordingly, boosted generalized additive models encompassing spatial, temporal and environmental variables revealed strong and highly diverse effects of space on OTU abundance, even within the same genus. This pure spatial effect increased with decreasing OTU abundance and frequency, whereas soil moisture – the most important environmental variable – had an opposite effect by impacting abundant OTUs more than the rare ones. These results indicate that – despite considerable oscillation in space and time – the abundant and resident OTUs provide a community backbone that supports much higher β-diversity of a dynamic rare biosphere. Our findings reveal complex interactions among space, time, and environmental filters within bacterial communities in a long-established temperate grassland.

The Plant Microbiome: From Ecology to Reductionism and Beyond

Methodological advances over the past two decades have propelled plant microbiome research, allowing the field to comprehensively test ideas proposed over a century ago and generate many new hypotheses. Studying the distribution of microbial taxa and genes across plant habitats has revealed the importance of various ecological and evolutionary forces shaping plant microbiota. In particular, selection imposed by plant habitats strongly shapes the diversity and composition of microbiota and leads to microbial adaptation associated with navigating the plant immune system and utilizing plant-derived resources. Reductionist approaches have demonstrated that the interaction between plant immunity and the plant microbiome is, in fact, bidirectional and that plants, microbiota, and the environment shape a complex chemical dialogue that collectively orchestrates the plantmicrobiome. The next stage in plant microbiome research will require the integration of ecological and reductionist approaches to establish a general understanding of the assembly and function in both natural and managed environments.