Use and abuse of correlation analyses in microbial ecology

Disentangling the seasonal co-occurrence patterns and ecological stochasticity of planktonic and benthic bacterial communities within multiple lakes

Both the planktonic bacterial community (PBC) and benthic bacterial community (BBC) are important for biogeochemical processes in freshwater lakes. Despite their ecological significance, little is known about their seasonal co-occurrence patterns and the ecological processes that drive them. In this study, we aimed to investigate the ecological associations among bacterial taxa and assembly processes of PBC and BBC in different seasons. We used 16S rRNA gene high-throughput sequencing of a total of 150 water and sediment samples collected from multiple lakes distributed in an urban region of China during winter and summer. Our results revealed that PBC showed stronger seasonal variations in co-occurrence patterns than BBC, suggesting that BBC had greater temporal stability than PBC. Winter PBC network was characterized by higher connectivity and complexity, and thereby the formation of a highly stable community structure; whereas lower connectivity arising from the presence of fewer predicted keystone taxa (hubs and connectors in a network) was destabilizing to summer PBC network. In addition, the phylum Firmicutes identified as a putative keystone taxon of PBC in both seasons played a non-negligible role in maintaining network structure which may result from strong functional associations with other bacterioplankton. Temperature and pH were the best explanatory factors predicting the seasonal co-occurrence patterns of PBC and BBC, respectively. Normalized stochasticity ratio based on null-model analysis indicated that deterministic processes overwhelmed stochastic processes in governing the assembly of PBC and BBC in both seasons. However, we observed a greater influence of ecological stochasticity on BBC assembly than PBC assembly in both seasons. Taken together, these findings provide insights into understanding the impacts of habitat heterogeneity and seasonal variability on microbial assemblage patterns in lake ecosystems.

Soil Fungal Community Composition, Not Assembly Process, Was Altered by Nitrogen Addition and Precipitation Changes at an Alpine Steppe

Global climate change and nitrogen deposition have been having broad impacts on microorganisms. On the Qinghai-Tibetan Plateau (QTP), the responses of soil microbial community assemblage and diversity to nitrogen deposition and changes in precipitation are poorly understood, especially in the alpine steppe. In this study, we conducted a field manipulative experiment of nitrogen deposition and precipitation amount in an alpine steppe on the northeastern QTP and investigated the responses of community composition, diversity, and community assemblage of soil fungi. Soil fungal community compositions were significantly altered under nitrogen addition, precipitation change, and their interaction, and positively related with soil moisture, soil pH, and plant species richness. However, they were negatively related to soil mineralizable N and soil available P content. Operational taxonomic units (OTU) richness and Chao 1 index decreased under nitrogen addition combined with precipitation reduction treatment, whereas the Shannon–Wiener index declined only under precipitation increment treatment. Convergent fungal community assembly processes were not acutely altered by both nitrogen addition and precipitation changes, indicating that environmental filtering was a dominant ecological process controlling fungal community assemblage. By elucidating the above questions, the study enhanced our ability to predict the responses of soil fungal communities to nitrogen deposition and precipitation changes at alpine steppes on the QTP in the future.

Higher-Order Interactions Dampen Pairwise Competition in the Zebrafish Gut Microbiome

The microbial communities resident in animal intestines are composed of multiple species that together play important roles in host development, health, and disease. Due to the complexity of these communities and the difficulty of characterizing them in situ, the determinants of microbial composition remain largely unknown. Further, it is unclear for many multispecies consortia whether their species-level makeup can be predicted based on an understanding of pairwise species interactions or whether higher-order interactions are needed to explain emergent compositions. To address this, we examine commensal intestinal microbes in larval zebrafish, initially raised germfree, to allow the introduction of controlled combinations of bacterial species. Using a dissection and plating assay, we demonstrate the construction of communities of one to five bacterial species and show that the outcomes from the two-species competitions fail to predict species abundances in more complex communities. With multiple species present, interbacterial interactions become weaker, suggesting that higher-order interactions in the vertebrate gut stabilize complex communities.IMPORTANCE Understanding the rules governing the composition of the diverse microbial communities that reside in the vertebrate gut environment will enhance our ability to manipulate such communities for therapeutic ends. Synthetic microbial communities, assembled from specific combinations of microbial species in germfree animals, allow investigation of the fundamental question of whether multispecies community composition can be predicted solely based on the combined effects of interactions between pairs of species. If so, such predictability would enable the construction of communities with desired species from the bottom up. If not, the apparent higher-order interactions imply that emergent community-level characteristics are crucial. Our findings using up to five coexisting native bacterial species in larval zebrafish, a model vertebrate, provide experimental evidence for higher-order interactions and, moreover, show that these interactions promote the coexistence of microbial species in the gut.

Regularized S-Map Reveals Varying Bacterial Interactions

There is a growing awareness that bacterial interactions follow a highly nonlinear pattern in reality. However, it is challenging to track the varying bacterial interactions using pairwise correlation analysis, which fails to explore their potential effects on the behavior of microbes. Here, we utilized a regularized sequential locally weighted global linear map (S-map) to capture the varying interspecific interactions from the time series data of a bacterial community under exposure to nitrite. Our results show that bacterial interactions are highly variable and that asymmetric interactions dominate the interaction pattern in a community. Furthermore, we propose a Jacobian coefficient-based statistical method to predict the harmony level of a bacterial community at each successive ecosystem state. The results show that the bacterial community exhibits a higher harmony level in nitrite-treated samples than in the control group. We show that the community harmony level is positively associated with the specific endogenous respiration rates and biofilm formation of the culture. In addition, the community tends to process lower diversity and structural stability under zero- and high-nitrite stresses. We demonstrate that the harmony level, rather than structural stability, is a useful index for unveiling the underlying mechanism of bacterial performance. Overall, the regularized S-map can help us to understand bacterial interactions in ecosystems more accurately than previous approaches.IMPORTANCE It has long been acknowledged that bacterial interactions play important roles in community structure and function. Revealing the interaction variability can allow an understanding of how bacteria respond to perturbation and why bacterial community performance changes. Such information should improve our skills in engineering bacterial communities (e.g., in a wastewater treatment plant) and achieve better removal performance and lower energy consumption.

Fungal Endophyte Communities of Crucifer Crops Are Seasonally Dynamic and Structured by Plant Identity, Plant Tissue and Environmental Factors

Endophytic fungi are important in diverse plant functions but knowledge of the factors that shape assemblages of these symbionts is lacking. Here, using a culture-dependent approach, we report 4,178 endophytic fungal isolates representing 16 orders isolated from stems, roots and leaves of three cruciferous plant species, Chinese cabbage (Brassica rapa L.), radish (Raphanus sativus L.) and white cabbage (B. olerocea L.), collected from 21 focal fields with different landscape contexts and pesticide uses during four seasons (summer, autumn, winter and spring). The colonization rate of fungi was found to be most strongly affected by season, plant identity and plant tissue. The colonization was highest during autumn, followed by summer, spring and lowest during winter. The colonization was highest in B. olerocea (53.2%), followed by B. rapa (42.6%), and lowest in R. sativus (35.0%). The colonization was highest in stems (51.9%) in all plant types, followed by leaves (42.4%) and roots (37.5%). Hypocreales was the dominant order (33.3% of all the isolates), followed by Glomerellales (26.5%), Eurotiales (12.1%), Pleosporales (9.8%) and Capnodiales (6.0%). Fungal endophyte abundance (number of isolates) followed the same pattern as colonization rate, while species richness varied with season and host plant tissue. Ordination analyses showed that the abundance and richness of Hypocreales, Eurotiales and Sordariales were associated with plant roots, while Capnodiales, Pleosporales and Trichosphaeriales were associated with spring. Other environmental factors, elevation, and the proportions of grassland, forest, orchard and waterbodies in the surrounding landscape also exerted effects within some categories of other main effects or for certain fungal taxa. Our results indicate that while fungal endophyte communities of crucifer crops vary strongly with the season, they are also strongly structured by plant identity and plant tissue, to a lesser extent by pesticide use and only weakly by landscape composition. The understanding of the ecological roles of fungal endophytes could contribute to habitat management and consequently improve crop pest management.

A continuously changing selective context on microbial communities associated with fish, from egg to fork

Fast increase of fish aquaculture production to meet consumer demands is accompanied by important ecological concerns such as disease outbreaks. Meanwhile, food waste is an important concern with fish products since they are highly perishable. Recent aquaculture and fish product microbiology, and more recently, microbiota research, paved the way to a highly integrated approach to understand complex relationships between host fish, product and their associated microbial communities at health/disease and preservation/spoilage frontiers. Microbial manipulation strategies are increasingly validated as promising tools either to replace or to complement traditional veterinary and preservation methods. In this review, we consider evolutionary forces driving fish microbiota assembly, in particular the changes in the selective context along the production chain. We summarize the current knowledge concerning factors governing assembly and dynamics of fish hosts and food microbial communities. Then, we discuss the current microbial community manipulation strategies from an evolutionary standpoint to provide a perspective on the potential for risks, conflict and opportunities. Finally, we conclude that to harness evolutionary forces in the development of sustainable microbiota manipulation applications in the fish industry, an integrated knowledge of the controlling abiotic and especially biotic factors is required.

BALOs Improved Gut Microbiota Health in Postlarval Shrimp (Litopenaeus vannamei) After Being Subjected to Salinity Reduction Treatment

White shrimp, Litopenaeus vannamei, is a widely farmed species. In China, shrimp postlarvae (PL) are frequently subjected to salinity reduction treatment to meet end growers' needs. However, although this treatment effectively reduces vibrio counts, its impact on gut microbiota health is still unknown. In this study, we applied a euryhaline strain of BALOs, BDN-1F2 (BD), and Bacillus subtilis (SD) to the rearing of second-generation shrimp PL after salinity reduction treatment so as to determine if they could impact PL gut microbiota by using high-throughput sequencing analysis. Results show that PL gut microbiota, both compositionally and functionally, have been badly wrecked after salinity reduction treatment with the generally recognized as opportunistic pathogens Gammaproteobacteria being the only dominant class at day 1 of test, viz., 99.43, 85.61, and 83.28% in BD, SD, and control (CD) groups, respectively. At day 7, Gammaproteobacteria was still the only dominant class in the SD and CD groups with relative abundance of 99.77 and 99.87% correspondingly, whereas in the BD group, its value dropped to 8.44%. Regarding biodiversity parameter the Shannon index, over the 7-day test period, while the SD group was unchanged (0.98-0.93), the CD group dropped to 0.94 from 2.94, and the BD group was raised to 7.14 from 0.93. Functionally, compared to control, the SD group displayed similar strength of various predicted community functions, but the BD group had hugely enhanced its various capabilities (p < 0.05). These results demonstrated that the addition of BDN-1F2 had exceedingly improved PL gut microbiota health by raising its biodiversities and strengthening its functionalities. On reviewing data derived from this as well as relevant studies, a Shannon index cutoff value was tentatively suggested so as to differentiate microbiota-healthy PL7-15 from the unhealthy ones. Furthermore, a conceptual mechanism of BALOs in the rectification/improvement of the microbial community health has also been proposed.

A Primer for Microbiome Time-Series Analysis

Time-series can provide critical insights into the structure and function of microbial communities. The analysis of temporal data warrants statistical considerations, distinct from comparative microbiome studies, to address ecological questions. This primer identifies unique challenges and approaches for analyzing microbiome time-series. In doing so, we focus on (1) identifying compositionally similar samples, (2) inferring putative interactions among populations, and (3) detecting periodic signals. We connect theory, code and data via a series of hands-on modules with a motivating biological question centered on marine microbial ecology. The topics of the modules include characterizing shifts in community structure and activity, identifying expression levels with a diel periodic signal, and identifying putative interactions within a complex community. Modules are presented as self-contained, open-access, interactive tutorials in R and Matlab. Throughout, we highlight statistical considerations for dealing with autocorrelated and compositional data, with an eye to improving the robustness of inferences from microbiome time-series. In doing so, we hope that this primer helps to broaden the use of time-series analytic methods within the microbial ecology research community.

Profiling of koumiss microbiota and organic acids and their effects on koumiss taste

BACKGROUND

Koumiss is a naturally fermented mare's milk. Over recent decades, numerous studies have revealed the diversity of lactic acid bacteria in koumiss. However, there is limited information available regarding its secondary major component yeast profile.

RESULTS

A total of 119 bacterial and 36 yeast species were identified among the 14 koumiss samples. The dominant bacterial species in koumiss were Lactobacillus helveticus, Lactobacillus kefiranofaciens, Lactococcus lactis, Lactococcus raffinolactis, and Citrobacter freundii. The main yeast species were Dekkera anomala, Kazachstania unispora, Meyerozyma caribbica, Pichia sp.BZ159, Kluyveromyces marxianus, and uncultured Guehomyces. The bacterial and yeast Shannon diversity of the Xilinhaote-urban group were higher than those of the Xilingol-rural group. The most dominant organic acids were lactic, acetic, tartaric, and malic acids. Lactic acid bacteria species were mostly responsible for the accumulation of those organic acids, although Kazachstania unispora, Dekkera anomala, and Meyerozyma caribbica may also have contributed. Redundancy analysis suggested that both bacteria and yeast respond to koumiss flavor, such as Lactobacillus helveticus and Dekkera anomala are associated with sourness, astringency, bitterness, and aftertaste, whereas Lactococcus lactis and Kazachstania unispora are associated with umami.

CONCLUSIONS

Our results suggest that differences were observed in koumiss microbiota of Xilinhaote-urban and Xilingol-rural samples. The biodiversity of the former was higher than the latter group. Positive or negative correlations between bacteria and yeast species and taste also were found.

Soil bacterial diversity correlates with precipitation and soil pH in long-term maize cropping systems

Unraveling the key drivers of bacterial community assembly in agricultural soils is pivotal for soil nutrient management and crop productivity. Presently, the drivers of microbial community structure remain unexplored in maize cropping systems under complex and variable environmental scenarios across large spatial scales. In this study, we conducted high-throughput 16S rRNA gene sequencing and network analysis to identify the major environmental factors driving bacterial community diversity and co-occurrence patterns in 21 maize field soils across China. The results show that mean annual precipitation and soil pH are the major environmental factors that shape soil bacterial communities in maize soils. The similarities of bacterial communities significantly decreased with increasing geographic distance between different sites. The differences in spatial turnover rates across bacterial phyla indicate the distinct dispersal capabilities of bacterial groups, and some abundant phyla exhibited high dispersal capabilities. Aeromicrobium, Friedmanniella, Saccharothrix, Lamia, Rhodococcus, Skermanella, and Pedobacter were identified as keystone taxa. Based on the node-level and network-level topological features, members of the core microbiome were more frequently found in the center of the ecosystem network compared with other taxa. This study highlights the major environmental factors driving bacterial community assembly in agro-ecosystems and the central ecological role of the core microbiome in maintaining the web of complex bacterial interactions.

Bacterial and Eukaryotic Small-Subunit Amplicon Data Do Not Provide a Quantitative Picture of Microbial Communities, but They Are Reliable in the Context of Ecological Interpretations

High-throughput sequencing (HTS) of amplified fragments of rRNA genes provides unprecedented insight into the diversity of prokaryotic and eukaryotic microorganisms. Unfortunately, HTS data are prone to quantitative biases, which may lead to an erroneous picture of microbial community composition and thwart efforts to advance its understanding. These concerns motivated us to investigate how accurately HTS data characterize the variability of microbial communities, the relative abundances of specific phylotypes, and their relationships with environmental factors in comparison to an established microscopy-based method. We compared results obtained by HTS and catalyzed reporter deposition-fluorescence in situ hybridization (CARD-FISH) from three independent aquatic time series for both prokaryotic and eukaryotic microorganisms (almost 900 data points, the largest obtained with both methods so far). HTS and CARD-FISH data disagree with regard to relative abundances of bacterial and eukaryotic phylotypes but identify similar environmental drivers shaping bacterial and eukaryotic communities.

High-throughput sequencing (HTS) of gene amplicons is a preferred method of assessing microbial community composition, because it rapidly provides information from a large number of samples at high taxonomic resolution and low costs. However, mock community studies show that HTS data poorly reflect the actual relative abundances of individual phylotypes, casting doubt on the reliability of subsequent statistical analysis and data interpretation. We investigated how accurately HTS data reflect the variability of bacterial and eukaryotic community composition and their relationship with environmental factors in natural samples. For this, we compared results of HTS from three independent aquatic time series (n = 883) with those from an established, quantitative microscopic method (catalyzed reporter deposition-fluorescence in situ hybridization [CARD-FISH]). Relative abundances obtained by CARD-FISH and HTS disagreed for most bacterial and eukaryotic phylotypes. Nevertheless, the two methods identified the same environmental drivers to shape bacterial and eukaryotic communities. Our results show that amplicon data do provide reliable information for their ecological interpretations. Yet, when studying specific phylogenetic groups, it is advisable to combine HTS with quantification using microscopy and/or the addition of internal standards.

IMPORTANCE High-throughput sequencing (HTS) of amplified fragments of rRNA genes provides unprecedented insight into the diversity of prokaryotic and eukaryotic microorganisms. Unfortunately, HTS data are prone to quantitative biases, which may lead to an erroneous picture of microbial community composition and thwart efforts to advance its understanding. These concerns motivated us to investigate how accurately HTS data characterize the variability of microbial communities, the relative abundances of specific phylotypes, and their relationships with environmental factors in comparison to an established microscopy-based method. We compared results obtained by HTS and catalyzed reporter deposition-fluorescence in situ hybridization (CARD-FISH) from three independent aquatic time series for both prokaryotic and eukaryotic microorganisms (almost 900 data points, the largest obtained with both methods so far). HTS and CARD-FISH data disagree with regard to relative abundances of bacterial and eukaryotic phylotypes but identify similar environmental drivers shaping bacterial and eukaryotic communities.

Analysis of leaf microbiome composition of near-isogenic maize lines differing in broad-spectrum disease resistance

Plant genotype strongly affects disease resistance, and also influences the composition of the leaf microbiome. However, these processes have not been studied and linked in the microevolutionary context of breeding for improved disease resistance. We hypothesised that broad-spectrum disease resistance alleles also affect colonisation by nonpathogenic symbionts. Quantitative trait loci (QTL) conferring resistance to multiple fungal pathogens were introgressed into a disease-susceptible maize inbred line. Bacterial and fungal leaf microbiomes of the resulting near-isogenic lines were compared with the microbiome of the disease-susceptible parent line at two time points in multiple fields. Introgression of QTL from disease-resistant lines strongly shifted the relative abundance of diverse fungal and bacterial taxa in both 3-wk-old and 7-wk-old plants. Nevertheless, the effects on overall community structure and diversity were minor and varied among fields and years. Contrary to our expectations, host genotype effects were not any stronger in fields with high disease pressure than in uninfected fields, and microbiome succession over time was similar in heavily infected and uninfected plants. These results show that introgressed QTL can greatly improve broad-spectrum disease resistance while having only limited and inconsistent pleiotropic effects on the leaf microbiome in maize.

Co-occurrence patterns of bacteria within microbiome of Moscow subway

Microbial ecosystems of the built environments have become key mediators of health as people worldwide tend to spend large amount of time indoors. Underexposure to microbes at an early age is linked to increased risks of allergic and autoimmune diseases. Transportation systems are of particular interest, as they are globally the largest space for interactions between city-dwellers. Here we performed the first pilot study of the Moscow subway microbiome by analyzing swabs collected from 5 types of surfaces at 4 stations using high-throughput 16S rRNA gene sequencing. The study was conducted as a part of The Metagenomics and Metadesign of the Subways and Urban Biomes (MetaSUB) project. The most abundant microbial taxa comprising the subway microbiome originated from soil and human skin. Microbiome diversity was positively correlated with passenger traffic. No substantial evidence of major human pathogens presence was found. Co-occurrence analysis revealed clusters of microbial genera including combinations of microbes likely originating from different niches. The clusters as well as the most abundant microbes were similar to ones obtained for the published data on New-York City subway microbiome. Our results suggest that people are the main source and driving force of diversity in subway-associated microbiome. The data form a basis for a wider survey of Moscow subway microbiome to explore its longitudinal dynamics by analyzing an extended set of sample types and stations. Complementation of methods with viability testing, "shotgun" metagenomics, sequencing of bacterial isolates and culturomics will provide insights for public health, biosafety, microbial ecology and urban design.

Progressive Microbial Community Networks with Incremental Organic Loading Rates Underlie Higher Anaerobic Digestion Performance

Although biotic interactions among members of microbial communities have been conceived to be crucial for community assembly, it remains unclear how changes in environmental conditions affect microbial interaction and consequently system performance. Here, we adopted a random matrix theory-based network analysis to explore microbial interactions in triplicate anaerobic digestion (AD) systems, which is widely applied for organic pollutant treatments. The digesters were operated with incremental organic loading rates (OLRs) from 1.0 g volatile solids (VS)/liter/day to 1.3 g VS/liter/day and then to 1.5 g VS/liter/day, which increased VS removal and methane production proportionally. Higher resource availability led to networks with higher connectivity and shorter harmonic geodesic distance, suggestive of more intense microbial interactions and quicker responses to environmental changes. Strikingly, a number of topological properties of microbial network showed significant (P < 0.05) correlation with AD performance (i.e., methane production, biogas production, and VS removal). When controlling for environmental parameters (e.g., total ammonia, pH, and the VS load), node connectivity, especially that of the methanogenic archaeal network, still correlated with AD performance. Last, we identified the Methanothermus, Methanobacterium, Chlorobium, and Haloarcula taxa and an unclassified Thaumarchaeota taxon as keystone nodes of the network.IMPORTANCE AD is a biological process widely used for effective waste treatment throughout the world. Biotic interactions among microbes are critical to the assembly and functioning of the microbial community, but the response of microbial interactions to environmental changes and their influence on AD performance are still poorly understood. Using well-replicated time series data of 16S rRNA gene amplicons and functional gene arrays, we constructed random matrix theory-based association networks to characterize potential microbial interactions with incremental OLRs. We demonstrated striking linkage between network topological features of methanogenic archaea and AD functioning independent of environmental parameters. As the intricate balance of multiple microbial functional groups is responsible for methane production, our results suggest that microbial interaction may be an important, previously unrecognized mechanism in determining AD performance.

Availability of Zinc Impacts Interactions between Streptococcus sanguinis and Pseudomonas aeruginosa in Coculture

Airway infections associated with cystic fibrosis (CF) are polymicrobial. We reported previously that clinical isolates of Pseudomonas aeruginosa promote the growth of a variety of streptococcal species. To explore the mechanistic basis of this interaction, we performed a genetic screen to identify mutants of Streptococcus sanginuis SK36 whose growth was no longer enhanced by P. aeruginosa PAO1. Mutations in the zinc uptake systems of S. sanguinis SK36 reduced growth of these strains by 1 to 3 logs compared to that of wild-type S. sanguinis SK36 when grown in coculture with P. aeruginosa PAO1, and exogenous zinc (0.1 to 10 μM) rescued the coculture defect of zinc uptake mutants of S. sanguinis SK36. Zinc uptake mutants of S. sanguinis SK36 had no obvious growth defect in monoculture. Consistent with competition for zinc driving coculture dynamics, S. sanguinis SK36 grown in coculture with P. aeruginosa showed increased expression of zinc uptake genes compared to that of S. sanguinis grown alone. Strains of P. aeruginosa PAO1 defective in zinc transport also supported ∼2-fold more growth by S. sanguinis compared to that in coculture with wild-type P. aeruginosa PAO1. An analysis of 118 CF sputum samples revealed that total zinc levels varied from ∼5 to 145 μM. At relatively low zinc levels, Pseudomonas and Streptococcus spp. were found in approximately equal abundance; at higher zinc levels, we observed a decline in relative abundance of Streptococcus spp., perhaps as a result of increasing zinc toxicity. Together, our data indicate that the relative abundances of these microbes in the CF airway may be impacted by zinc levels.IMPORTANCE Polymicrobial infections in CF cases likely impact patient health, but the mechanism(s) underlying such interactions is poorly understood. Here, we show using an in vitro model system that interactions between Pseudomonas and Streptococcus are modulated by zinc availability, and clinical data are consistent with this model. Together with previous studies, our work supports a role for metal homeostasis as a key factor driving microbial interactions.

Metatranscriptomic reconstruction reveals RNA viruses with the potential to shape carbon cycling in soil

Viruses impact nearly all organisms on Earth, with ripples of influence in agriculture, health, and biogeochemical processes. However, very little is known about RNA viruses in an environmental context, and even less is known about their diversity and ecology in soil, 1 of the most complex microbial systems. Here, we assembled 48 individual metatranscriptomes from 4 habitats within a planted soil sampled over a 22-d time series: Rhizosphere alone, detritosphere alone, rhizosphere with added root detritus, and unamended soil (4 time points and 3 biological replicates). We resolved the RNA viral community, uncovering a high diversity of viral sequences. We also investigated possible host organisms by analyzing metatranscriptome marker genes. Based on viral phylogeny, much of the diversity was Narnaviridae that may parasitize fungi or Leviviridae, which may infect Proteobacteria. Both host and viral communities appear to be highly dynamic, and rapidly diverged depending on experimental conditions. The viral and host communities were structured based on the presence of root litter. Clear temporal dynamics by Leviviridae and their hosts indicated that viruses were replicating. With this time-resolved analysis, we show that RNA viruses are diverse, abundant, and active in soil. When viral infection causes host cell death, it may mobilize cell carbon in a process that may represent an overlooked component of soil carbon cycling.

Annual Protist Community Dynamics in a Freshwater Ecosystem Undergoing Contrasted Climatic Conditions: The Saint-Charles River (Canada)

Protists are key stone components of aquatic ecosystems, sustaining primary productivity and aquatic food webs. However, their diversity, ecology and structuring factors shaping their temporal distribution remain strongly misunderstood in freshwaters. Using high-throughput sequencing on water samples collected over 16 different months (including two summer and two winter periods), combined with geochemical measurements and climate monitoring, we comprehensively determined the pico- and nanoeukaryotic community composition and dynamics in a Canadian river undergoing prolonged ice-cover winters. Our analysis revealed a large protist diversity in this fluctuating ecosystem and clear seasonal patterns demonstrating a direct and/or indirect selective role of abiotic factors, such as water temperature or nitrogen concentrations, in structuring the eukaryotic microbial community. Nonetheless, our results also revealed that primary productivity, predatory as well as parasitism lifestyles, inferred from fine phylogenetic placements, remained potentially present over the annual cycle, despite the large seasonal fluctuations and the remodeling of the community composition under ice. In addition, potential interplays with the bacterial community composition were identified supporting a possible contribution of the bacterial community to the temporal dynamics of the protist community structure. Our results illustrate the complexity of the eukaryotic microbial community and provide a substantive and useful dataset to better understand the global freshwater ecosystem functioning.