The soil microbiome — from metagenomics to metaphenomics

Jansson, Janet; Hofmockel, Kirsten

doi:10.1016/j.mib.2018.01.013

Cited by 348 publications

(278 citation statements)

References 45 publications

Supporting

Mentioning

254

Contrasting

Order By: Relevance

“…Thus far, the limited studies of soil viruses have identified few AMGs relative to studies of marine environments. This may be due to under-sampling, or difficulties in identifying AMGs; since AMGs are homologs of host genes, they can be mistaken for microbial contamination (103) and thus are more difficult to discern in bulk-soil metagenomes (whereas marine virology has been dominated by viromes); also, microbial gene function is more poorly understood in soils (104). Alternately, soil viruses could indeed encode fewer AMGs.…”

Section: Resultsmentioning

confidence: 99%

Soil viruses are underexplored players in ecosystem carbon processing

Trubl

Jang

Roux

et al. 2018

Preprint

View full text Add to dashboard Cite

SummaryRapidly thawing permafrost harbors ~30–50% of global soil carbon, and the fate of this carbon remains unknown. Microorganisms will play a central role in its fate, and their viruses could modulate that impact via induced mortality and metabolic controls. Because of the challenges of recovering viruses from soils, little is known about soil viruses or their role(s) in microbial biogeochemical cycling. Here, we describe 53 viral populations (vOTUs) recovered from seven quantitatively-derived (i.e. not multiple-displacement-amplified) viral-particle metagenomes (viromes) along a permafrost thaw gradient. Only 15% of these vOTUs had genetic similarity to publicly available viruses in the RefSeq database, and ~30% of the genes could be annotated, supporting the concept of soils as reservoirs of substantial undescribed viral genetic diversity. The vOTUs exhibited distinct ecology, with dramatically different distributions along the thaw gradient habitats, and a shift from soil-virus-like assemblages in the dry palsas to aquatic-virus-like in the inundated fen. Seventeen vOTUs were linked to microbial hosts (in silico), implicating viruses in infecting abundant microbial lineages from Acidobacteria, Verrucomicrobia, and Deltaproteoacteria, including those encoding key biogeochemical functions such as organic matter degradation. Thirty-one auxiliary metabolic genes (AMGs) were identified, and suggested viral-mediated modulation of central carbon metabolism, soil organic matter degradation, polysaccharide-binding, and regulation of sporulation. Together these findings suggest that these soil viruses have distinct ecology, impact host-mediated biogeochemistry, and likely impact ecosystem function in the rapidly changing Arctic.

show abstract

Section: Resultsmentioning

confidence: 99%

Soil viruses are underexplored players in ecosystem carbon processing

Trubl

Jang

Roux

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…Our simulation results suggest that metabolic activation/deactivation strategies of microbial functional groups may be a key control of C turnover in soil. These modelbased implications could be tested with targeted experiments that enable spatially resolved measurements of microbial community composition and C fluxes at the microhabitat scale by extending existing approaches (e.g., Poll et al, 2006) and using novel techniques such as flow cells (Krueger et al, 2018) in combination with functional multilayered omics approaches (Jansson and Hofmockel, 2018;Sergaki et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

Spatial Control of Carbon Dynamics in Soil by Microbial Decomposer Communities

Pagel

Kriesche

Uksa

et al. 2020

Front. Environ. Sci.

View full text Add to dashboard Cite

Trait-based models have improved the understanding and prediction of soil organic matter dynamics in terrestrial ecosystems. Microscopic observations and pore scale models are now increasingly used to quantify and elucidate the effects of soil heterogeneity on microbial processes. Combining both approaches provides a promising way to accurately capture spatial microbial-physicochemical interactions and to predict overall system behavior. The present study aims to quantify controls on carbon (C) turnover in soil due to the mm-scale spatial distribution of microbial decomposer communities in soil. A new spatially explicit trait-based model (SpatC) has been developed that captures the combined dynamics of microbes and soil organic matter (SOM) by taking into account microbial life-history traits and SOM accessibility. Samples of spatial distributions of microbes at µm-scale resolution were generated using a spatial statistical model based on Log Gaussian Cox Processes which was originally used to analyze distributions of bacterial cells in soil thin sections. These µm-scale distribution patterns were then aggregated to derive distributions of microorganisms at mm-scale. We performed Monte-Carlo simulations with microbial distributions that differ in mm-scale spatial heterogeneity and functional community composition (oligotrophs, copiotrophs, and copiotrophic cheaters). Our modeling approach revealed that the spatial distribution of soil microorganisms triggers spatiotemporal patterns of C utilization and microbial succession. Only strong spatial clustering of decomposer communities induces a diffusion limitation of the substrate supply on the microhabitat scale, which significantly reduces the total decomposition of C compounds and the overall microbial growth. However, decomposer communities act as functionally redundant microbial guilds with only slight changes in C utilization. The combined statistical and process-based modeling approach derives distribution patterns of microorganisms at the mm-scale from microbial biogeography at microhabitat scale (µm) and quantifies the emergent macroscopic (cm) microbial and C dynamics. Thus, it effectively links observable process dynamics to the spatial control by microbial communities. Our study highlights a powerful approach that can provide further insights into the biological control of soil organic matter turnover.

show abstract

“…Recent efforts are mapping the microbiome of Earth for different habitat types (see for instance the Earth Microbiome project 1 and the Global Ocean Microbiome project 2 ), however, the connection between environment and population microbiome is still lacking and difficult to predict. While it is true that consistent efforts have been devoted to the analysis of diseaseor symptom-specific alterations of the microbiome in relation to external environmental agents (Bucci et al, 2012;Davenport et al, 2017;Karkman et al, 2017;Mitmesser and Combs, 2017), a large gap exists in the analysis of how the spatiotemporal distribution of microbiota in the environment [e.g., soils (Jansson and Hofmockel, 2018), plants (Wackett, 2019), water (Lee et al, 2016), and natural hosts (Bahrndorff et al, 2016;Degli Esposti and Martinez Romero, 2017)] affects the microbiome in natural and human communities. Note that this ecological investigation, guided by theory, targeted monitoring and models (see section "Pattern-Oriented Models"), does not necessarily need to focus on health but on any spatio-temporal pattern manifesting ecological states of co-evolving microbiomes such as biodiversity patterns [see Parfrey and Knight (2012) and Ochman et al (Moeller et al, 2016b;Ochman, 2016)] and other socio-ecological ecosystem services.…”

Section: Human -Environment-microbiome Nexusmentioning

confidence: 99%