Lost in diversity Mommer, Liesje; Cotton, T. E. Anne; Raaijmakers, Jos M. ...
The New phytologist,
April 2018, Letnik:
218, Številka:
2
Journal Article
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There is consensus that plant species richness enhances plant productivity within natural grasslands, but the underlying drivers remain debated. Recently, differential accumulation of soil-borne ...fungal pathogens across the plant diversity gradient has been proposed as a cause of this pattern. However, the below-ground environment has generally been treated as a ‘black box’ in biodiversity experiments, leaving these fungi unidentified.
Using next generation sequencing and pathogenicity assays, we analysed the community composition of root-associated fungi from a biodiversity experiment to examine if evidence exists for host specificity and negative density dependence in the interplay between soil-borne fungi, plant diversity and productivity.
Plant species were colonised by distinct (pathogenic) fungal communities and isolated fungal species showed negative, species-specific effects on plant growth. Moreover, 57% of the pathogenic fungal operational taxonomic units (OTUs) recorded in plant monocultures were not detected in eight plant species plots, suggesting a loss of pathogenic OTUs with plant diversity.
Our work provides strong evidence for host specificity and negative density-dependent effects of root-associated fungi on plant species in grasslands. Our work substantiates the hypothesis that fungal root pathogens are an important driver of biodiversity-ecosystem functioning relationships.
Most attempts to identify the processes that structure natural communities have focused on conspicuous macroorganisms whereas the processes responsible for structuring microbial communities remain ...relatively unknown. Two main theories explaining these processes have emerged; niche theory, which highlights the importance of deterministic processes, and neutral theory, which focuses on stochastic processes. We examined whether neutral or niche-based mechanisms best explain the composition and structure of communities of a functionally important soil microbe, the arbuscular mycorrhizal (AM) fungi. Using molecular techniques, we surveyed AM fungi from 425 individual plants of 28 plant species along a soil pH gradient. There was evidence that both niche and neutral processes structured this community. Species abundances fitted the zero-sum multinomial distribution and there was evidence of dispersal limitation, both indicators of neutral processes. However, we found stronger support that niche differentiation based on abiotic soil factors, primarily pH, was structuring the AM fungal community. Host plant species affected AM fungal community composition negligibly compared to soil pH. We conclude that although niche partitioning was the primary mechanism regulating the composition and diversity of natural AM fungal communities, these communities are also influenced by stochastic-neutral processes. This study represents one of the most comprehensive investigations of community-level processes acting on soil microbes; revealing a community that although influenced by stochastic processes, still responded in a predictable manner to a major abiotic niche axis, soil pH. The strong response to environmental factors of this community highlights the susceptibility of soil microbes to environmental change.
Tropical forests have long fascinated ecologists, inspiring a plethora of research into the mechanisms regulating their immense biodiversity, which originally captured the interests of early natural ...historians and explorers, and that still persists to this day. A new focus of this research emerged in the early 2000s highlighting the potential role of neutral (stochastic) processes in regulating the composition and diversity of tropical forest communities, and thus the maintenance of a large portion of global biodiversity (Hubbell, ). This strictly contrasted the long‐held belief that communities assembled via the sorting of species (and their abundances) via a deterministic response to local abiotic and biotic environmental conditions, reflecting the niche of each species (Leibold & McPeek, ). Yet, it is unlikely that the assembly of any community is solely governed by either stochastic or deterministic processes, but instead a combination of both. However, whether deterministic processes via niche‐based environmental sorting of species, or stochastic processes reflecting pattens of dispersal limitation, neutral effects and ecological drift dominate is often unclear. This prompts questions as to whether the relative influence of one process over another is dependent on the scale (spatial or temporal) or context of the study, or specific traits of the taxa under investigation (e.g., body size). In a From the Cover paper in this issue of Molecular Ecology, Zinger et al. () tackle all these issues and show, among other things, that for soil microbes and mesofauna from tropical forests, the relative contribution of stochastic and deterministic processes in assembling their communities is strongly dependent on the body size or the studied taxa.
We foresee a new global-scale, ecological approach to biomonitoring emerging within the next decade that can detect ecosystem change accurately, cheaply, and generically. Next-generation sequencing ...of DNA sampled from the Earth’s environments would provide data for the relative abundance of operational taxonomic units or ecological functions. Machine-learning methods would then be used to reconstruct the ecological networks of interactions implicit in the raw NGS data. Ultimately, we envision the development of autonomous samplers that would sample nucleic acids and upload NGS sequence data to the cloud for network reconstruction. Large numbers of these samplers, in a global array, would allow sensitive automated biomonitoring of the Earth’s major ecosystems at high spatial and temporal resolution, revolutionising our understanding of ecosystem change.
Next-generation sequencing (NGS) can used to sample nucleic acids in the environment for the presence of species and ecological functions.
Machine-learning software can search for ‘the ghosts of interactions past’ in the raw NGS data to reconstruct the networks of ecological interactions.
NGS data and machine-learning in the cloud could be combined in the next generation of global biomonitoring. Autonomous NGS samplers would sequence and upload data for ecological network reconstruction, to detect ecosystem change accurately, cheaply and generically.
Reconstruction of highly replicated networks of ecological interaction, using this next generation of biomonitoring, would provide general ecological information for ecosystem comparison and a revolution in the breadth of our understanding of the ecology of ecosystem change.
Understanding the dynamics of rhizosphere microbial communities is essential for predicting future ecosystem function, yet most research focuses on either spatial or temporal processes, ignoring ...combined spatio-temporal effects. Using pyrosequencing, we examined the spatio-temporal dynamics of a functionally important community of rhizosphere microbes, the arbuscular mycorrhizal (AM) fungi. We sampled AM fungi from plant roots growing in a temperate grassland in a spatially explicit manner throughout a year. Ordination analysis of the AM fungal assemblages revealed significant temporal changes in composition and structure. Alpha and beta diversity tended to be negatively correlated with the climate variables temperature and sunshine hours. Higher alpha diversity during colder periods probably reflects more even competitive interactions among AM fungal species under limited carbon availability, a conclusion supported by analysis of beta diversity which highlights how resource limitation may change localized spatial dynamics. Results reveal distinct AM fungal assemblages in winter and summer at this grassland site. A seasonally changing supply of host-plant carbon, reflecting changes in temperature and sunshine hours, may be the driving force in regulating the temporal dynamics of AM fungal communities. Climate change effects on seasonal temperatures may therefore substantially alter future AM fungal community dynamics and ecosystem functioning.
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•Microalgae-microbial consortia (ACs) can be isolated from various organic wastes.•Chlorella and Tetradesmus are the most isolated algae from organic wastes.•Chemical-biological ...parameters affected ACs composition.•Cow slurry provides more chance for isolating Chlorella and Tetradesmus.
Pure microalgae cultivation in organic wastes may be hampered by their low adaptation to extreme growth conditions and by the risk of microbial contamination. This work aimed to isolate self-adapted microalgae-microbial consortia able to survive in organic wastes characterized by extreme conditions, to be then proposed for technological application in removing carbon and nutrients from wastes’ streams. To do so, sixteen organic wastes with different origins and consistency were sampled. Twelve microbial consortia were isolated from wastes and their eukaryotic and prokaryotic compositions were analyzed by next generation sequencing. Eight eukaryotic communities were dominated by Chlorophyta, led by Chlorella, able to survive in different wastes regardless of chemical-biological properties. Tetradesmus, the second most represented genus, grew preferentially in substrates with less stressing chemical-physical parameters. Chlorella and Tetradesmus were mostly isolated from cow slurry and derived wastes which proved to be the best local residual organic source.
Metabarcoding of DNA extracted from environmental or bulk specimen samples is increasingly used to profile biota in basic and applied biodiversity research because of its targeted nature that allows ...sequencing of genetic markers from many samples in parallel. To achieve this, PCR amplification is carried out with primers designed to target a taxonomically informative marker within a taxonomic group, and sample‐specific nucleotide identifiers are added to the amplicons prior to sequencing. The latter enables assignment of the sequences back to the samples they originated from. Nucleotide identifiers can be added during the metabarcoding PCR and during “library preparation”, that is, when amplicons are prepared for sequencing. Different strategies to achieve this labelling exist. All have advantages, challenges and limitations, some of which can lead to misleading results, and in the worst case compromise the fidelity of the metabarcoding data. Given the range of questions addressed using metabarcoding, ensuring that data generation is robust and fit for the chosen purpose is critically important for practitioners seeking to employ metabarcoding for biodiversity assessments. Here, we present an overview of the three main workflows for sample‐specific labelling and library preparation in metabarcoding studies on Illumina sequencing platforms; one‐step PCR, two‐step PCR, and tagged PCR. Further, we distill the key considerations for researchers seeking to select an appropriate metabarcoding strategy for their specific study. Ultimately, by gaining insights into the consequences of different metabarcoding workflows, we hope to further consolidate the power of metabarcoding as a tool to assess biodiversity across a range of applications.
Bioaerosols (or biogenic aerosols) have largely been overlooked by molecular ecologists. However, this is rapidly changing as bioaerosols play key roles in public health, environmental chemistry and ...the dispersal ecology of microbes. Due to the low environmental concentrations of bioaerosols, collecting sufficient biomass for molecular methods is challenging. Currently, no standardized methods for bioaerosol collection for molecular ecology research exist. Each study requires a process of optimization, which greatly slows the advance of bioaerosol science. Here, we evaluated air filtration and liquid impingement for bioaerosol sampling across a range of environmental conditions. We also investigated the effect of sampling matrices, sample concentration strategies and sampling duration on DNA yield. Air filtration using polycarbonate filters gave the highest recovery, but due to the faster sampling rates possible with impingement, we recommend this method for fine ‐scale temporal/spatial ecological studies. To prevent bias for the recovery of Gram‐positive bacteria, we found that the matrix for impingement should be phosphate‐buffered saline. The optimal method for bioaerosol concentration from the liquid matrix was centrifugation. However, we also present a method using syringe filters for rapid in‐field recovery of bioaerosols from impingement samples, without compromising microbial diversity for high ‐throughput sequencing approaches. Finally, we provide a resource that enables molecular ecologists to select the most appropriate sampling strategy for their specific research question.
Aim
Ecological communities that exist closer together in space are generally more compositionally similar than those far apart, as defined by the distance–decay of similarity relationship. However, ...recent research has revealed substantial variability in the distance–decay relationships of microbial communities between studies of different taxonomic groups, ecosystems and spatial scales and between those using different molecular methodologies (e.g., high‐throughput sequencing versus molecular fingerprinting). Here, we test how these factors influence the strength of microbial distance–decay relationships, in order to draw generalizations about how microbial β‐diversity scales with space.
Location
Global.
Time period
Studies published between 2005 and 2019 (inclusive).
Major taxa studied
Bacteria, Archaea and microbial Eukarya.
Methods
We conducted a meta‐analysis of microbial distance–decay relationships, using the Mantel correlation coefficient as a measure of the strength of distance–decay relationships. Our final dataset consisted of 452 data points, varying in environmental/ecological context or methodological approaches, and we used linear models to test the effects of each variable.
Results
Both ecological and methodological factors had significant impacts on the strength of microbial distance–decay relationships. Specifically, the strength of these relationships varied between environments and habitats, with soils showing significantly weaker distance–decay relationships than other habitats, whereas increasing spatial extents had no effect. Methodological factors, such as sequencing depth, were positively related to the strength of distance–decay relationships, and choice of dissimilarity metric was also important, with phylogenetic metrics generally giving weaker distance–decay relationships than binary or abundance‐based indices.
Main conclusions
We conclude that widely studied microbial biogeographical patterns, such as the distance–decay relationship, vary by ecological context but are primarily distorted by methodological choices. Consequently, we suggest that by linking methodological approaches appropriately to the ecological context of a study, we can progress towards generalizable biogeographical relationships in microbial ecology.
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