Temperature and CO2 interactively drive shifts in the compositional and functional structure of peatland protist communities

Microbes affect the global carbon cycle that influences climate change and are in turn influenced by environmental change. Here, we use data from a long-term whole-ecosystem warming experiment at a boreal peatland to answer how temperature and CO2 jointly influence communities of abundant, diverse, yet poorly understood, non-fungi microbial Eukaryotes (protists). These microbes influence ecosystem function directly through photosynthesis and respiration, and indirectly, through predation on decomposers (bacteria and fungi). Using a combination of high-throughput fluid imaging and 18S amplicon sequencing, we report large climate-induced, community-wide shifts in the community functional composition of these microbes (size, shape, and metabolism) that could alter overall function in peatlands. Importantly, we demonstrate a taxonomic convergence but a functional divergence in response to warming and elevated CO2 with most environmental responses being contingent on organismal size: warming effects on functional composition are reversed by elevated CO2 and amplified in larger microbes but not smaller ones. These findings show how the interactive effects of warming and rising CO2 levels could alter the structure and function of peatland microbial food webs-a fragile ecosystem that stores upwards of 25% of all terrestrial carbon and is increasingly threatened by human exploitation.

Recovery of 197 eukaryotic bins reveals major challenges for eukaryote genome reconstruction from terrestrial metagenomes

As most eukaryotic genomes are yet to be sequenced, the mechanisms underlying their contribution to different ecosystem processes remain untapped. Although approaches to recovering Prokaryotic genomes have become common in genome biology, few studies have tackled the recovery of eukaryotic genomes from metagenomes. This study assessed the reconstruction of microbial eukaryotic genomes using 6000 metagenomes from terrestrial and some transition environments using the EukRep pipeline. Only 215 metagenomic libraries yielded eukaryotic bins. From a total of 447 eukaryotic bins recovered 197 were classified at the phylum level. Streptophytes and fungi were the most represented clades with 83 and 73 bins, respectively. More than 78% of the obtained eukaryotic bins were recovered from samples whose biomes were classified as host-associated, aquatic, and anthropogenic terrestrial. However, only 93 bins were taxonomically assigned at the genus level and 17 bins at the species level. Completeness and contamination estimates were obtained for a total of 193 bins and consisted of 44.64% (σ = 27.41%) and 3.97% (σ = 6.53%), respectively. Micromonas commoda was the most frequent taxon found while Saccharomyces cerevisiae presented the highest completeness, probably because more reference genomes are available. Current measures of completeness are based on the presence of single-copy genes. However, mapping of the contigs from the recovered eukaryotic bins to the chromosomes of the reference genomes showed many gaps, suggesting that completeness measures should also include chromosome coverage. Recovering eukaryotic genomes will benefit significantly from long-read sequencing, development of tools for dealing with repeat-rich genomes, and improved reference genomes databases.

Distinct response patterns of plants and soil microorganisms to agronomic practices and seasonal variation in a floodplain ecosystem

Introduction

Climate change and anthropogenic activities are the greatest threats to floodplain ecosystems. A growing body of literature shows that floodplain ecosystems have experienced increased chemical fertilizer and pesticide loads, which will disturb the above and belowground ecosystems. However, we lack knowledge regarding the effects of such human activities on the vegetation and soil microbiomes in these ecosystems.

Methods

In the present study, plant functional traits and Illumina Mi-Seq sequencing were to assess the impact of nitrogen fertilizer and glyphosate addition on the structure and function of the vegetation and soil microbiomes (bacteria, fungi, and protists) in a floodplain ecosystem, and to assess the influence of seasonal variation.

Results

We identified distinct response mechanisms of plant and microbial communities to the addition of nitrogen fertilizer and glyphosate, and seasonal variation. Nitrogen fertilizer and glyphosate significantly affected plant diversity, aboveground and underground biomass, and C and N content and significantly changed the leaf area and plant stature of dominant plants. However, the addition of nitrogen fertilizer and glyphosate did not significantly affect the diversity and structure of bacterial, fungal, and protist communities. The application of nitrogen fertilizer could improve the negative effects of glyphosate on the functional traits of plant communities. The seasonal variation of floodplain has significantly changed the soil's physical, chemical, and biological properties. Our results showed that compared with that in summer, the soil ecosystem multifunctionality of the floodplain ecosystem in autumn was significantly lower. Seasonal variation had a significant effect on plant diversity and functional traits. Moreover, seasonal variation significantly affected the community compositions, diversity, and structure of bacteria, fungi, and protists. Seasonal variation had a stronger impact on fungal community assembly than on that of bacteria and protists. In summer, the assembly of the fungal community was dominated by a deterministic process, while in autumn, it is dominated by a stochastic process. In addition, the negative association among bacteria, fungi, and protists has been strengthened in autumn and formed a more robust network to cope with external changes.

Discussion

These results extended our understanding of the ecological patterns of soil microbiomes in floodplain ecosystems and provided support for enhancing the ecological barrier function and the service potential of floodplain ecosystems.

The neglected role of micronutrients in predicting soil microbial structure

Predicting the distribution patterns of soil microbial communities requires consideration of more environmental drivers. The effects of soil micronutrients on composition of microbial communities are largely unknown despite micronutrients closely relating to soil fertility and plant communities. Here we used data from 228 agricultural fields to identify the importance of micronutrients (iron, zinc, copper and manganese) in shaping structure of soil microbial communities (bacteria, fungi and protist) along latitudinal gradient over 3400 km, across diverse edaphic conditions and climatic gradients. We found that micronutrients explained more variations in the structure of microbial communities than macronutrients in maize soils. Moreover, micronutrients, particularly iron and copper, explained a unique percentage of the variation in structure of microbial communities in maize soils even after controlling for climate, soil physicochemical properties and macronutrients, but these effects were stronger for fungi and protist than for bacteria. The ability of micronutrients to predict the structure of soil microbial communities declined greatly in paddy soils. Machine learning approach showed that the addition of micronutrients substantially increased the predictive power by 9-17% in predicting the structure of soil microbial communities with up to 69-78% accuracy. These results highlighted the considerable contributions of soil micronutrients to microbial community structure, and advocated that soil micronutrients should be considered when predicting the structure of microbial communities in a changing world.

The community ecology perspective of omics data

The measurement of uncharacterized pools of biological molecules through techniques such as metabarcoding, metagenomics, metatranscriptomics, metabolomics, and metaproteomics produces large, multivariate datasets. Analyses of these datasets have successfully been borrowed from community ecology to characterize the molecular diversity of samples (ɑ-diversity) and to assess how these profiles change in response to experimental treatments or across gradients (β-diversity). However, sample preparation and data collection methods generate biases and noise which confound molecular diversity estimates and require special attention. Here, we examine how technical biases and noise that are introduced into multivariate molecular data affect the estimation of the components of diversity (i.e., total number of different molecular species, or entities; total number of molecules; and the abundance distribution of molecular entities). We then explore under which conditions these biases affect the measurement of ɑ- and β-diversity and highlight how novel methods commonly used in community ecology can be adopted to improve the interpretation and integration of multivariate molecular data. Video Abstract.

Functional microbial ecology in arctic soils: the need for a year-round perspective

The microbial ecology of arctic and sub-arctic soils is an important aspect of the global carbon cycle, due to the sensitivity of the large soil carbon stocks to ongoing climate warming. These regions are characterized by strong climatic seasonality, but the emphasis of most studies on the short vegetation growing season could potentially limit our ability to predict year-round ecosystem functions. We compiled a database of studies from arctic, subarctic, and boreal environments that include sampling of microbial community and functions outside the growing season. We found that for studies comparing across seasons, in most environments, microbial biomass and community composition vary intra-annually, with the spring thaw period often identified by researchers as the most dynamic time of year. This seasonality of microbial communities will have consequences for predictions of ecosystem function under climate change if it results in: seasonality in process kinetics of microbe-mediated functions; intra-annual variation in the importance of different (a)biotic drivers; and/or potential temporal asynchrony between climate change-related perturbations and their corresponding effects. Future research should focus on (i) sampling throughout the entire year; (ii) linking these multi-season measures of microbial community composition with corresponding functional or physiological measurements to elucidate the temporal dynamics of the links between them; and (iii) identifying dominant biotic and abiotic drivers of intra-annual variation in different ecological contexts.

Stochastic processes regulate belowground community assembly in alpine grasslands on the Tibetan Plateau

Understanding biogeographical patterns and underlying processes of belowground community assembly is crucial for predicting soil functions and their responses to global environmental change. However, little is known about potential differences of belowground community assembly among bacteria, fungi, protists and soil animals, particularly for alpine ecosystems. Based on the combination of large-scale field sampling, high-throughput marker-gene sequencing and multiple statistical analyses, we explored patterns and drivers of belowground community assembly in alpine grasslands on the Tibetan Plateau. Our results revealed that the distance-decay rates varied among trophic levels, with organisms of higher trophic level having weaker distance-decay pattern. The spatial and environmental variables explained limited variations of belowground communities. By contrast, the stochastic processes, mainly consisting of dispersal limitation and drift, played a primary role in regulating belowground community assembly. Moreover, the relative importance of stochastic processes varied among trophic levels, with the role of dispersal limitation weakening whereas that of drift enhancing in the order of bacteria, fungi, protists and soil animals. These findings advance our understanding of patterns and mechanisms driving belowground community assembly in alpine ecosystems and provide a reference basis for predicting the dynamics of ecosystem functions under changing environment.

A walk on the dirt: soil microbial forensics from ecological theory to the crime lab

Forensics aims at using physical evidence to solve investigations with science-based principles, thus operating within a theoretical framework. This however is often rather weak, the exception being DNA-based human forensics that is well anchored in theory. Soil is a most commonly encountered, easily and unknowingly transferred evidence but it is seldom employed as soil analyses require extensive expertise. In contrast, comparative analyses of soil bacterial communities using nucleic acid technologies can efficiently and precisely locate the origin of forensic soil traces. However, this application is still in its infancy, and is very rarely used. We posit that understanding the theoretical bases and limitations of their uses is essential for soil microbial forensics to be judiciously implemented. Accordingly, we review the ecological theory and experimental evidence explaining differences between soil microbial communities, i.e. the generation of beta diversity, and propose to integrate a bottom-up approach of interactions at the microscale, reflecting historical contingencies with top-down mechanisms driven by the geographic template, providing a potential explanation as to why bacterial communities map according to soil types. Finally, we delimit the use of soil microbial forensics based on the present technologies and ecological knowledge, and propose possible venues to remove existing bottlenecks.

On the phenology of protists: recurrent patterns reveal seasonal variation of protistan (Rhizaria: Cercozoa and Endomyxa) communities in tree canopies

Tree canopies are colonized by billions of highly specialized microorganisms that are well adapted to the highly variable microclimatic conditions, caused by diurnal fluctuations and seasonal changes. In this study, we investigated seasonality patterns of protists in the tree canopies of a temperate floodplain forest via high-throughput sequencing with group-specific primers for the phyla Cercozoa and Endomyxa. We observed consistent seasonality, and identified divergent spring and autumn taxa. Tree crowns were characterized by a dominance of bacterivores and omnivores, while eukaryvores gained a distinctly larger share in litter and soil communities on the ground. In the canopy seasonality was largest among communities detected on the foliar surface: In spring, higher variance within alpha diversity of foliar samples indicated greater heterogeneity during initial colonization. However, communities underwent compositional changes during the aging of leaves in autumn, highly reflecting recurring phenological changes during protistan colonization. Surprisingly, endomyxan root pathogens appeared to be exceptionally abundant across tree canopies during autumn, demonstrating a potential role of the canopy surface as a physical filter for air-dispersed propagules. Overall, about 80% of detected OTUs could not be assigned to known species-representing dozens of microeukaryotic taxa whose canopy inhabitants are waiting to be discovered.

DNA Metabarcoding for the Characterization of Terrestrial Microbiota-Pitfalls and Solutions

Soil-borne microbes are major ecological players in terrestrial environments since they cycle organic matter, channel nutrients across trophic levels and influence plant growth and health. Therefore, the identification, taxonomic characterization and determination of the ecological role of members of soil microbial communities have become major topics of interest. The development and continuous improvement of high-throughput sequencing platforms have further stimulated the study of complex microbiota in soils and plants. The most frequently used approach to study microbiota composition, diversity and dynamics is polymerase chain reaction (PCR), amplifying specific taxonomically informative gene markers with the subsequent sequencing of the amplicons. This methodological approach is called DNA metabarcoding. Over the last decade, DNA metabarcoding has rapidly emerged as a powerful and cost-effective method for the description of microbiota in environmental samples. However, this approach involves several processing steps, each of which might introduce significant biases that can considerably compromise the reliability of the metabarcoding output. The aim of this review is to provide state-of-the-art background knowledge needed to make appropriate decisions at each step of a DNA metabarcoding workflow, highlighting crucial steps that, if considered, ensures an accurate and standardized characterization of microbiota in environmental studies.