Biology subjects

Toju, H.

Publications and source records attributed to Toju, H..

At least 19 recordsLinked to original sources

bioRxiv2026

Global distributions and plant associations of the ecologically diverse ascomycete order Helotiales

Background Fungi in plant root systems are key to understanding the dynamics and functioning of terrestrial ecosystems. Whereas our knowledge of below-ground plant-fungus symbioses has derived mainly from studies of mycorrhizal and pathogenic fungi, recent studies have uncovered an unexpected diversity of ecological niches occupied by root-associated fungi. The fungal order Helotiales is conspicuous in this respect because this predominantly root-associated taxon encompasses a broad ecological spectrum, ranging from saprotrophic and pathogenic fungi to endophytic and mycorrhizal fungi with plant growth-promoting functions. In this study, we integrated a worldwide dataset of 1,996 Helotiales Species Hypotheses (i.e., species-level taxa tentatively defined based on DNA sequences) detected in roots of 362 plant genera representing 117 families and 47 orders, and systematically quantified the specificity of Helotiales-plant associations. Results The analysis of 37,688 unique occurrence records of Helotiales fungi across 1,940 global sampling locations revealed highly structured associations between Helotiales genera and plant lineages, exemplified by the strong specificity of Hyaloscypha, Oidiodendron, and Phialocephala for Pinales and that of Glutinomyces for Fagales, even after statistically controlling background biogeographic patterns. At the Species-Hypothesis-level analysis, major clades within the Helotiales phylogeny consistently exhibited high specificity for Pinaceae, whereas highly specific associations with other ectomycorrhizal, arbuscular mycorrhizal, and nonmycorrhizal plants were restricted to small terminal clades of the fungal phylogeny. Conclusions The integration of ecological specificity and phylogenetic analyses suggests the possibility that Helotiales fungi established close associations with Pinaceae early in their evolutionary history and subsequently underwent host shifts to diverse angiosperm lineages. Given the emerging evidence that Helotiales fungi play pivotal ecological and physiological roles in plant root systems, these statistical insights into Helotiales-plant associations provide a fundamental basis for understanding the evolutionary history and functioning of terrestrial ecosystems.

microbiology↗

bioRxiv2026

Environmental filtering and host identity collectively shape root-associated microbiomes of Ericaceae and ectomycorrhizal plants in fumarole fields

Background Symbiosis with microbes is a key strategy that has enabled plants to colonize extreme environments. Since the benefits conferred by root-associated microbes depend on both environmental conditions and host-microbe combinations, plant adaptation to harsh environments is closely linked to the assembly of root microbial communities. Understanding how environmental and host filtering jointly shape these communities is therefore fundamental to elucidating the mechanisms underlying plant adaptation to extreme environments. Results In this study, we investigated the differentiation of root-associated prokaryotic and fungal communities and individual operational taxonomic units (OTUs) across two contrasting habitats surrounding fumaroles, solfatara-field and forest-edge habitats, and six dominant Ericaceae and ectomycorrhizal plant taxa. Prokaryotic and fungal OTUs rarely exhibited strong preferences for both habitat and host identity. Instead, many of prokaryotic and fungal OTUs specialized to one of these niches, collectively generating root microbial communities differentiated by both factors. Nonetheless, striking specializations in habitat and host niches were observed in the fungal family Hyaloscyphaceae (Helotiales). To gain insight into the evolutionary basis of microbial specialization, we examined phylogenetic signals in preference phenotypes. The resulting weak phylogenetic signals in these preference phenotypes further suggest that this fungal clade has undergone substantial ecological divergence. Conclusion Overall, our findings indicate that root-associated microbial communities in extreme environments are assembled through the accumulation of microbial taxa specialized to either habitat or host, and that strong ecological specialization in fungi can arise with little phylogenetic constraint.

microbiology↗

bioRxiv2026

ELAplus: Fast and accurate analysis platform for energy landscape analysis facilitated by fine-tuning optimization algorithm.

1. Large-scale community-composition datasets, especially from microbiome studies, increasingly provide opportunities to identify major community compositional types (e.g., enterotypes in human microbiomes) and potential transitions depending on environmental factors. Energy landscape analysis based on maximum entropy models has emerged as a promising framework for characterizing such multi-stability in ecological communities. However, its application to diverse, high-dimensional compositional datasets remains limited by computational inefficiency, insufficient evaluation of predictability, and lack of systematic assessment of uncertainty. 2. Here, we present a computationally tractable inference framework for energy landscape analysis of multispecies communities, implemented in the R package ELAplus. We introduce a framework combining cross-validation-based selection of optimization settings, enabling accurate and computationally efficient model fitting across a wide range of simulated community datasets. In addition, we incorporate a bootstrap-based approach to quantify the reliability of inferred stable states, providing a systematic measure of uncertainty in landscape structures. 3. Simulation analyses demonstrate improved predictive performance and robustness compared to existing implementations. Applications to empirical datasets further illustrate how the framework can reveal stable states, basins of attraction, and potential tipping points under varying environmental conditions. The package also provides visualization tools, including disconnectivity graphs and energy surface plots, to facilitate intuitive interpretation of complex ecological landscapes. 4. Our framework enables robust and computationally efficient inference of ecological stability from compositional and environmental data, expanding the applicability of energy landscape approaches in diverse natural communities.

ecology↗

bioRxiv2026

Response diversity can stabilize or destabilize community dynamics depending on the number of insensitive species

Investigating the factors that stabilize biological communities is a central topic in ecology. Response diversity, defined as variation in species responses to environmental change, has been proposed as a key mechanism underlying the biodiversity-ecosystem functional stability (BEFS) relationship, whereby greater species diversity enhances ecological stability. Previous studies have shown that response diversity promotes ecological stability by generating asynchronous population fluctuations and the resulting compensatory dynamics. Although several metrics have been proposed to quantify response diversity, they do not explicitly consider the presence of insensitive species whose performance is unaffected by current environmental conditions. To examine how insensitive species influence response diversity, species persistence, and ecological stability, we conducted numerical simulations of a generalized Lotka-Volterra model under environmental forcing. We first confirmed that increasing variation among sensitive species increased the response diversity index and stabilized community dynamics. We then examined a scenario in which response diversity depended solely on the proportion of sensitive and insensitive species, assuming that all sensitive species responded identically to environmental change. Under this assumption, the response diversity index was maximized when sensitive and insensitive species occurred in equal proportions, whereas increasing the number of sensitive species monotonically destabilized community dynamics. Consequently, the relationship between response diversity and community stability depended on how response diversity was generated, such that higher response diversity could even be associated with lower community stability. These findings demonstrate that overlooking environmentally insensitive species can obscure the mechanisms linking response diversity and ecological stability. More broadly, our results reveal that response diversity comprises at least two distinct biological components--species sensitivity and response variation among sensitive species--that can have contrasting consequences for community stability. We therefore highlight the need to quantify sensitive species empirically and to develop response diversity metrics that distinguish these components. Author SummaryUnderstanding why some communities remain stable despite environmental change is a longstanding goal in ecology. Response diversity, which refers to differences in how species respond to environmental change, has been proposed as a key mechanism explaining why greater biodiversity (species richness) can promote ecological stability. Because species respond differently to changing environments, declines in some species can be compensated by increases in others, helping to stabilize community dynamics. However, previous studies have rarely considered species that are insensitive to current environmental changes. Using a mathematical model, we show that response diversity can arise from two distinct biological components--the number of sensitive species and variation in their responses--and that these components can have contrasting effects on ecological stability. When response diversity reflects variation among sensitive species, greater response diversity stabilizes community dynamics, as expected. In contrast, when response diversity changes only because of the proportions of sensitive and insensitive species, higher response diversity can be associated with lower community stability. Our findings highlight the importance of quantifying the number of sensitive species and developing response diversity metrics that distinguish species sensitivity from variation in responses among sensitive species.

ecology↗

bioRxiv2026

Complexity-multistability relationships: How does species diversity shape the number of alternative stable states?

Ecologists have long investigated how community complexity affects ecological stability, yet how community complexity influences multistability, defined as the presence of alternative stable states, remains poorly understood. We developed a novel framework integrating stochastic community assembly with stability landscape analysis to quantify multistability from species interaction matrices. Using this framework, we systematically explored how species interaction properties shape the relationship between species diversity (species pool size) and the number of alternative stable states. Mean interaction strength was the primary determinant: competitive interactions amplified the positive relationship between species diversity and the number of alternative stable states. In competitive communities, a greater number of alternative stable states was associated with lower community uncertainty, a measure of the long-term unpredictability of community assembly dynamics. These results highlight the importance of characterizing the entire stability landscape. Our framework provides a general approach for understanding and quantifying multistability in complex ecological communities.

ecology↗

bioRxiv2025

High density invasion by the shrub Ardisia crenata in Florida, USA is associated with altered soil chemical properties and microbial communities

Invasive plants can reshape soil ecosystems by altering chemical conditions and microbial communities. However, field evidence for how these effects scale with invader density, and whether responses are nonlinear, remains limited. We examined whether local stem density of the invasive shrub Ardisia crenata is associated with shifts in soil chemistry and soil microbiomes. The local density of A. crenata, which reproduces clonally with apomictic seeds, forms a gradient from high density to low density across invaded stands. Our results show strong differences in soil ecosystems with invasion, including consistently lower soil moisture, pH, organic matter, total carbon, total nitrogen, and electrical conductivity. These changes were accompanied by shifts in the community composition of soil prokaryotes and fungi, such as increased abundances of Acidothermus and Saitozyma with higher density of A. crenata. While the exact mechanisms causing these changes could not be established, increases of more labile above- and below-ground litter, as well as A. crenata specific secondary metabolites, were possible causal factors. We conclude that strong changes in soil ecosystems can be caused by invasive plants in a mesic forest understory, especially when they occur at high densities. Hence, to maintain healthy soil ecosystems, it is recommendable to control aggressive invasive plants such as A. crenata before they reach high densities.

ecology↗

bioRxiv2025

Stochastic Forces in Microbial Community Assembly: Founding Community Size Governs Divergent Ecological Trajectories

Biological community dynamics are organized by the interplay of deterministic and stochastic processes. While species responses to biotic and abiotic environments determine the attractors of community compositions, stochastic processes, especially those in early stages of community assembly, can drastically influence the direction of temporal ecological dynamics. Nonetheless, establishing quantitative insights into the roles of stochastic processes has remained a major challenge. By developing a multi-replicated experimental system for tracking community assembly, we quantitatively evaluated the extent to which stochasticity could cause the divergence of community dynamics. We constructed soil- and freshwater-derived experimental microbial assemblages (microbiomes) with varying foundation community size, thereby controlling variation in initial community compositions among replicate communities (i.e., initial stochasticity). An analysis of > 3,000 community samples across four time points then indicated that higher levels of initial stochasticity could result in greater divergence of population- and community-level consequences. From the quantitative perspective, conspicuous differentiation into alternative trajectories of community assembly occurred when the absolute number of founding prokaryotic cells was less than the order of 104. Furthermore, the replicate microbiomes differed in dominant Pseudomonas species, suggesting divergence into alternative transient/stable states through competitive exclusion between species occupying similar niches. Overall, our experiment showed that quantitative differences in stochasticity could result in qualitative differences in the fate of ecological communities. Further quantitative insights into stochasticity in community assembly will reorganize our views on biological invasions, agroecosystem microbiome management, and therapeutics of human-associated microbiomes.

ecology↗

bioRxiv2024

Mycorrhizal and endophytic fungi structure contrasting but interdependent assembly processes in forest below-ground symbiosis

Interactions between plants and diverse root-associated fungi are essential drivers of forest ecosystem dynamics. The nature of the symbiosis in root systems is potentially dependent on multiple ecological factors/processes such as host/symbiont specificity, background soil microbiome structure, inter-root sharing/dispersal of symbionts, and fungus-fungus interactions within fine roots. Nonetheless, it has remained a major challenge to reveal the mechanisms by which those multiple factors/processes determine the assembly of mycorrhizal and endophytic fungal communities. Based on a framework of joint species distribution modeling, we here examined how root-associated fungal community structure was collectively formed through filtering by host plants, associations with background soil fungi, spatial autocorrelation, and symbiont-symbiont interactions. In our analysis targeting 1,615 root-tip samples collected in a cool-temperate forest dominated by ectomycorrhizal plants, statistical models including all the four ecological factors/processes best explained the fine-scale community structure of root-associated fungi. Meanwhile, among partial models including subsets of those ecological factors/processes, those including background soil microbiome structure and within-root fungus-fungus interactions showed the highest performance. When fine-root distributions of respective fugal species/taxa were examined, ectomycorrhizal fungi tended to show stronger associations with background soil community structure and stronger spatially-autocorrelated patterns than other fungal guilds. In contrast, the distributions of root-endophytic fungi were inferred to depend greatly on fungus-fungus interactions. A network statistical analysis further suggested that some endophytic fungi, such as those belonging to the ascomycete genera Phialocephala and Leptodontidium, were involved in webs of positive and negative interactions with other root-associated fungi. These results suggest that basic assembly rules can differ between mycorrhizal and endophytic fungi, both of which are major components of forest ecosystems. Consequently, knowledge of how multiple ecological factors/processes differentially drive the assembly of multiple fungal functional guilds is indispensable for comprehensively understanding the mechanisms by which terrestrial ecosystem dynamics are organized by plant-fungal symbiosis.

ecology↗

bioRxiv2023

Soil Prokaryotic and Fungal Biome Structures Associated with Crop Disease Status across the Japan Archipelago

Archaea, bacteria, and fungi in the soil are increasingly recognized as determinants of agricultural productivity and sustainability. A crucial step for exploring soil microbiomes with high ecosystem functions is to perform statistical analyses on potential relationship between microbiome structure and functions based on comparisons of hundreds or thousands of environmental samples collected across broad geographic ranges. In this study, we integrated agricultural field metadata with microbial community analyses by targeting > 2,000 soil samples collected along a latitudinal gradient from cool-temperate to subtropical regions in Japan (26.1- 42.8 {degrees}N). The data involving 632 archaeal, 26,868 bacterial, and 4,889 fungal operational taxonomic units detected across the fields of 19 crop plant species allowed us to conduct statistical analyses (permutational analyses of variance, generalized linear mixed models, and randomization analyses) on relationship among edaphic factors, microbiome compositions, and crop disease prevalence. We then examined whether the diverse microbes form species sets varying in potential ecological impacts on crop plants. A network analysis suggested that the observed prokaryotes and fungi were actually classified into several species sets (network modules), which differed substantially in associations with crop disease prevalence. Within the network of microbe-to-microbe coexistence, ecologically diverse microbes, such as an ammonium-oxidizing archaeum, an antibiotics-producing bacterium, and a potentially mycoparasitic fungus, were inferred to play key roles in shifts between crop-disease-promotive and crop-disease-suppressive states of soil microbiomes. The birds-eye view of soil microbiome structure will provide a basis for designing and managing agroecosystems with high disease-suppressive functions. IMPORTANCEUnderstanding how microbiome structure and functions are organized in soil ecosystems is one of the major challenges in both basic ecology and applied microbiology. Given the ongoing worldwide degradation of agroecosystems, building frameworks for exploring structural diversity and functional profiles of soil microbiomes is an essential task. Our study provides an overview of cropland microbiome states in light of potential crop-disease-suppressive functions. The large dataset allowed us to explore highly functional species sets that may be stably managed in agroecosystems. Furthermore, an analysis of network architecture highlighted species that are potentially used to cause shifts from disease-prevalent states of agroecosystems to disease-suppressive states. By extending the approach of comparative analyses towards broader geographic ranges and diverse agricultural practices, agroecosystem with maximized biological functions will be further explored.

microbiology↗

bioRxiv2023

Deterministic and stochastic processes generating alternative states of microbiomes

The structure of microbial communities is often classified into discrete or semi-discrete compositions of taxa as represented by "enterotypes" of human gut microbiomes. Elucidating mechanisms that generate such "alternative states" of microbiome compositions has been one of the major challenges in ecology and microbiology. In a time-series analysis of experimental microbiomes, we here show that both deterministic and stochastic ecological processes drive divergence of alternative microbiome states. We introduced species-rich soil-derived microbiomes into eight types of culture media with 48 replicates, monitoring shifts in community compositions at six time points (8 media x 48 replicates x 6 time points = 2,304 community samples). We then confirmed that microbial community structure diverged into a few discrete states in each of the eight medium conditions as predicted in the presence of both deterministic and stochastic community processes. In other words, microbiome structure was differentiated into a small number of reproducible compositions under the same environment. This fact indicates not only the presence of selective forces leading to specific equilibria of community-scale resource use but also the influence of demographic drift (fluctuations) across basins of such equilibria. A reference-genome analysis further suggested that the observed alternative states differed in ecosystem-level functions. These findings will help us examine how microbiome structure and functions can be controlled by changing the "stability landscapes" of ecological community compositions.

ecology↗

bioRxiv2023

Facilitative interaction networks in experimental microbial community dynamics

Understanding potential roles of facilitative interactions between species is one of the major challenges in ecology and microbiology. However, we still have limited knowledge of entangled webs of facilitative interactions in ecosystems. By compiling whole-genome shotgun metagenomic data of an experimental microbial community, we tested the hypothesis that architecture of facilitative interaction networks could change through time. A metabolic modeling approach for estimating dependence between microbial genomes (species) allowed us to infer the network structure of potential facilitative interactions at 13 time points through the 110-day monitoring of experimental microbiomes. We then found that positive feedback loops, which were theoretically predicted to promote cascade breakdown of ecological communities, existed within the inferred networks of metabolic interactions prior to the drastic community-compositional shift observed in the microbiome time-series. We further applied "directed-graph" analyses to pinpoint potential keystone species located at the "upper stream" positions of such feedback loops. These analyses on facilitative interactions will help us understand key mechanisms causing catastrophic shifts in microbial community structure.

ecology↗

bioRxiv2023

Metagenomic analysis of ecological niche overlap and community collapse in microbiome dynamics

Species utilizing the same resources often fail to coexist for extended periods of time. Such competitive exclusion mechanisms potentially underly microbiome dynamics, causing breakdowns of communities composed of species with similar genetic backgrounds of resource utilization. Although genes responsible for competitive exclusion among a small number of species have been investigated in pioneering studies, it remains a major challenge to integrate genomics and ecology for understanding stable coexistence in species-rich communities. Here, we show that community-scale analyses of functional gene redundancy can provide a useful platform for interpreting and predicting collapse of bacterial communities. Through 110-day time-series of experimental microbiome dynamics, we analyzed the metagenome-assembled genomes of co-occurring bacterial species. We then inferred ecological niche space based on the multivariate analysis of the genome compositions. The analysis allowed us to evaluate potential shifts in the level of niche overlap between species through time. We hypothesized that community-scale pressure of competitive exclusion could be evaluated by quantifying overlap of genetically determined resource-use profiles (metabolic pathway profiles) among coexisting species. We found that the degree of community compositional changes observed in the experimental microbiome was explained by the magnitude of gene-repertoire overlaps among bacterial species. The metagenome-based analysis of genetic potential for competitive exclusion will help us forecast major events in microbiome dynamics such as sudden community collapse (i.e., dysbiosis).

microbiology↗

bioRxiv2022

Dynamics of interaction networks and species' contributions to community-scale flexibility

Architecture of species interaction networks is a key factor determining stability of ecological communities. However, the fact that ecological network architecture can change through time is often overlooked in discussions on community-level processes despite its theoretical importance. By compiling a time-series community dataset involving 50 spider species and 974 Hexapoda prey species/strains, we quantified the extent to which architecture of predator-prey interaction networks can shift across time points. We then developed a framework for finding species that could promote flexibility of interaction network architecture. Those "network coordinator" species are expected to promote persistence of species-rich ecological communities by buffering perturbations to communities. Although spiders are often considered as generalist predators, contributions to network flexibility varied greatly among species. We also found that detritivorous prey species can be cores of interaction rewiring, dynamically interlinking below-ground and above-ground community dynamics. Analyses of network coordinators will add a new dimension to our understanding of species coexistence mechanisms and provide platforms for systematically prioritizing species in terms of their potential contributions in ecosystem conservation and restoration. Significance StatementLike networks of human relations, webs of interactions between species are dynamically restructured through time. By compiling time-series time-series dataset including > 1,000 species/strains, we quantified the magnitude of ecological network dynamics in the wild. The analytical framework developed in this study highlighted "network coordinator" species, which are keys to conserve and restore endangered ecosystems.

ecology↗

bioRxiv2022

Dynamics of species-rich predator-prey networks and seasonal alternations of keystone species

In nature, entangled webs of predator-prey interactions constitute the backbones of ecosystems. Uncovering the network architecture of such trophic interactions has been recognized as the essential step for exploring species with great impacts on ecosystem-level phenomena and functions. However, it has remained a major challenge to reveal how species-rich networks of predator-prey interactions are continually reshaped though time in the wild. We here show that dynamics of species-rich predator-prey interactions can be characterized by remarkable network structural changes and alternations of potential keystone species. Based on high-throughput detection of prey DNA from 1,556 spider individuals collected in a grassland ecosystem, we reconstructed dynamics of interaction networks involving, in total, 50 spider species and 974 prey species/strains through eight months. The networks were compartmentalized into modules (groups) of closely interacting predators and prey in some but not all months. As the modules differed in detritus/grazing food chain properties, complex fission-fusion dynamics of below-ground and above-ground energy channels was reconstructed across the seasons. The substantial shifts of network structure entailed alternations of spider species located at the core positions within the entangled webs of interactions. These results indicate that knowledge of dynamically shifting food webs is essential for understanding the temporally-varying roles of keystone species that interlink multiple energy channels.

ecology↗

bioRxiv2022

Core species and interactions prominent in fish-associated microbiome dynamics

In aquatic ecosystems, the health of fish depends greatly on the dynamics of microbial community structure in the background environment. Nonetheless, finding microbes with profound impacts on fishs performance out of thousands of candidate species remains a major challenge. We here show that time-series analyses of microbial population dynamics illuminate core components and structure of fish-associated microbiomes. By targeting eel aquaculture microbiomes as model systems, we reconstructed the population dynamics of 9,605 bacterial and 303 archaeal species/strains across 128 days. Due to the remarkable increase/decrease of constituent microbial populations, the taxonomic compositions of microbiomes changed drastically through time. We then found that some specific microbial taxa showed positive relationship with eels activity level even after excluding cofounding effects of environmental parameters (pH and dissolved oxygen level) on population dynamics. In particular, a vitamin B12-producing bacteria, Cetobacterium somerae, consistently showed strong positive associations with eels activity level across the replicate time-series of the five aquaculture tanks. Network theoretical and metabolic modeling analyses further suggested that the highlighted bacterium formed compartments of close microbe-to-microbe interactions with some other bacterial taxa, forming potential core microbiomes with positive impacts on eels. Overall, these results suggest that integration of microbiology, ecological theory, and network science allows us to explore core species and interactions embedded within complex dynamics of fish-associated microbiomes.

ecology↗

bioRxiv2022

Alternative stable states, nonlinear behavior, and predictability of microbiome dynamics

Microbiome dynamics are both crucial indicators and drivers of human health, agricultural output, and industrial bio-applications. However, predicting microbiome dynamics is notoriously difficult because communities often show abrupt structural changes, such as "dysbiosis" in human microbiomes. We here integrate theoretical and empirical bases for anticipating drastic shifts of microbial communities. We monitored 48 experimental microbiomes for 110 days and observed that various community-level events, including collapse and gradual compositional changes, occurred according to a defined set of environmental conditions. We then confirmed that the abrupt community changes observed through the time-series could be described as shifts between "alternative stable states" or dynamics around complex attractors. Furthermore, collapses of microbiome structure were successfully anticipated by means of the diagnostic threshold defined with the energy landscape analysis of statistical physics or that of a stability index of nonlinear mechanics. These results indicate that abrupt microbiome events in complex microbial communities can be forecasted by extending classic ecological concepts to the scale of species-rich microbial systems.

ecology↗

bioRxiv2022

Stable states and keystone species in soil microbiomes of agroecosystems

Theory predicts that biological communities can have multiple basins of attraction in terms of their species/taxonomic compositions. The presence of such basins of community structure has been examined in classic empirical studies on forest-savanna transitions and those on eutrophication in freshwater lakes. Nonetheless, it remains a major challenge to extend the investigations of multistability to species-rich microbial communities. By targeting soil microbiomes, we infer the stability landscapes of community structure based on the concepts of statistical physics. Our analysis on the compiled dataset involving 11 archaeal, 332 bacterial, and 240 fungal families detected from > 1,500 agroecosystem soil samples suggested that both prokaryotic and fungal community compositions could be classified into several basins of attraction. We also found that the basins differed greatly in their associations with crop disease prevalence in agroecosystems. A further analysis highlighted microbial taxa potentially playing key roles in transitions between basins with different ecosystem-scale functions. The statistical framework commonly applicable to diverse microbial and non-microbial communities will reorganize our understanding of relationship among community structure, stability, and functions.

microbiology↗

bioRxiv2022

Effects of source sample amount on biodiversity surveys of bacteria, fungi, and nematodes in soil ecosystems

Bacteria, fungi, and nematodes are major components of soil ecosystems, playing pivotal roles in belowground material cycles and biological community processes. A number of studies have recently uncovered the diversity and community structure of those organisms in various types of soil ecosystems based on DNA metabarcoding (amplicon sequencing). However, because each of the most previous studies examined only one or two of the three organismal groups, it remains an important challenge to reveal the entire picture of soil community structure. We herein examined how we could standardize DNA extraction protocols for simultaneous DNA metabarcoding of bacteria, fungi, and nematodes. Specifically, in an Illumina sequencing analysis of forest and farmland soil samples, we performed DNA extraction at five levels of soil-amount settings (0.5 g, 2 g, 5 g, 10 g, and 20 g). We then found that DNA extraction with the 0.5-g soil setting, which had been applied as default in many commercial DNA extraction kits, could lead to underestimation of -diversity in nematode community. The detected family-level diversity of nematodes, in particular, increased with increasing soil amounts in DNA extraction. Our analyses also indicated that dissimilarity ({beta}-diversity) of community structure among replicate samples were higher in fungi and nematodes than in bacteria, suggesting difference in basic levels of spatial heterogeneity among the three organismal groups. These findings provide platforms for optimizing DNA metabarcoding protocols commonly applicable to major groups of organisms in soil ecosystems.

ecology↗