In Situ Non-Destructive Temporal Measurements of the Rhizosphere Microbiome ‘Hot-Spots’ Using Metaproteomics

Rhizosphere arguably embodies the most diverse microbial ecosystem on the planet, yet it is largely a functional ‘black box’ of belowground plant-microbiome interactions. The rhizosphere is the primary site of entry for subsurface injection of fixed carbon (C) into soil with impacts on local to global scale C biogeochemistry and ultimately Earth’s climate. While spatial organization of rhizosphere is central to its function, small scale and steep microbial and geochemical gradients within this dynamic region make it easily disrupted by sampling. The significant challenge presented by sampling blocks elucidation of discreet functions, drivers, and interactions within rhizosphere ecosystems. Here, we describe a non-destructive sampling method linked to metaproteomic analysis in order to measure temporal shifts in the microbial composition and function of rhizosphere. A robust, non-destructive method of sampling microbial hotspots within rhizosphere provides an unperturbed window into the elusive functional interactome of this system over time and space.

Macrofungi Cultivation in Shady Forest Areas Significantly Increases Microbiome Diversity, Abundance and Functional Capacity in Soil Furrows

Cultivating macrofungi is an important management measure to develop economy in shady forest areas; however, its effect on soil ecology, especially microbial abundance and structure, remains insufficiently studied. Herein, in a subtropical forestland, soil chemical and enzyme analyses, metagenomic sequencing and quantitative real-time PCR were employed to evaluate the impact of Stropharia rugosoannulata cultivation on soil microbiomes in three niches: soil below fungal beds, soil from furrows, and control forest soil with no influence from mushroom cultivation. Nutrients were accumulated in the soil below fungal beds with a significant increase (p < 0.05) in SOC, total C, total N, available P, and the activities of glucosidase and cellobiosidase. Non-metric multidimensional scaling and PERMANOVA results indicated that the structure of the microbiomes had been significantly (p < 0.05) shaped among the different niches. Soil furrows were microbial hotspots characterized by the higher microbial diversity and richness. Moreover, the increased microbiome abundance (assessed through qPCR) and the high number of significant stimulated functional types (based on MetaCyc genome database) indicated an enhanced functional capacity in furrows. Together, these results provide a comprehensive understanding of the microbial assemblies and the differently influenced soil properties in mushroom cultivation areas.

Microbial Genome-Resolved Metaproteomic Analyses Frame Intertwined Carbon and Nitrogen Cycles in River Hyporheic Sediments

Background:Rivers serve as a nexus for nutrient transfer between terrestrial and marine ecosystems and as such, have a significant impact on global carbon and nitrogen cycles. In river ecosystems, the sediments found within the hyporheic zone are microbial hotspots that can account for a significant portion of ecosystem respiration and have profound impacts on system biogeochemistry. Despite this, studies using genome-resolved analyses linking microbial and viral communities to nitrogen and carbon biogeochemistry are limited.Results:Here, we characterized the microbial and viral communities of Columbia River hyporheic zone sediments to reveal the metabolisms that actively cycle carbon and nitrogen. Using genome-resolved metagenomics, we created the Hyporheic Uncultured Microbial and Viral (HUM-V) database, containing a dereplicated database of 55 microbial Metagenome-Assembled Genomes (MAGs), representing 12 distinct phyla. We also sampled 111 viral Metagenome Assembled Genomes (vMAGs) from 26 distinct and novel genera. The HUM-V recruited metaproteomes from these same samples, providing the first inventory of microbial gene expression in hyporheic zone sediments. Combining this data with metabolite data, we generated a conceptual model where heterotrophic and autotrophic metabolisms co-occur to drive an integrated carbon and nitrogen cycle, revealing microbial sources and sinks for carbon dioxide and ammonium in these sediments. We uncovered the metabolic handoffs underpinning these processes including mutualistic nitrification by Thermoproteota (formerly Thaumarchaeota) and Nitrospirota, as well as identified possible cooperative and cheating behavior impacting nitrogen mineralization. Finally, by linking vMAGs to microbial genome hosts, we reveal possible viral controls on microbial nitrification and organic carbon degradation.Conclusions:Our multi-omics analyses provide new mechanistic insight into coupled carbon-nitrogen cycling in the hyporheic zone. This is a key step in developing predictive hydrobiogeochemical models that account for microbial cross-feeding and viral influences over potential and expressed microbial metabolisms. Furthermore, the publicly available HUM-V genome resource can be queried and expanded by researchers working in other ecosystems to assess the transferability of our results to other parts of the globe.

Land use impact on carbon mineralization is mainly caused by variation of particulate organic matter content rather than of soil structure

Land use is known to exert a dominant impact on a range of essential soil functions like water retention, carbon sequestration, matter cycling and plant growth. At the same time, land use management is known to have a strong influence on soil structure, e.g. through bioturbation, tillage and compaction. However, it is often unclear whether differences in soil structure are the actual cause for differences in soil functions or just co-occurring. This impact of land use (conventional and organic farming, intensive and extensive meadow, extensive pasture) on the relationship between soil structure and short-term carbon mineralization was investigated at the Global Change Exploratory Facility, in Bad Lauchstädt, Germany. Intact topsoil cores (n = 75) were sampled from each land use type at the early growing season. Soil structure and microbial activity were measured using X-ray computed tomography and respirometry, respectively. Grasslands had a greater microbial activity than croplands, both in terms of basal respiration and rate of carbon mineralization during growth. This was caused by a larger amount of particulate organic matter (POM) in the topsoil of grasslands. The frequently postulated dependency of basal respiration on soil moisture was absent even though some cores were apparently water limited. This finding was related to microenvironments shaping microbial hotspots where the decomposition of plant residues was obviously decoupled from water limitation in bulk soil. Differences in microstructural properties between land uses were surprisingly small, mainly due huge variability induced by patterns of compacted clods and loose areas caused by tillage in cropland soils. The most striking difference was larger macropore diameters in grasslands soil due to the presence of large biopores that are periodically destroyed in croplands. Variability of basal respiration among all soil cores amounted to more than one order of magnitude (0.08–1.42 µg CO2-C h−1 g−1 soil) and was best described by POM mass (R2 = 0.53, p < 0.001). Predictive power was hardly improved by considering all bulk, microstructure and microbial properties jointly. The predictive power of image-derived microstructural properties was low, because aeration was not limiting carbon mineralization and was sustained by pores smaller than the image resolution limit (< 30 µm). The rate of glucose mineralization during growth was explained well by substrate-induced respiration (R2 = 0.84) prior to growth, which was in turn correlated with total microbial biomass, basal respiration and POM mass and again not affected by pore metrics. These findings stress that soil structure had little relevance in predicting carbon mineralization in well-aerated soil, as this predominantly took place in microbial hotspots around degrading POM that was detached from the pore structure and moisture of the bulk soil. Land use therefore affects carbon mineralization in well-aerated soil mainly by the amount and quality of labile carbon.

Microbial Hotspots in Lithic Microhabitats Inferred from DNA Fractionation and Metagenomics in the Atacama Desert

The existence of microbial activity hotspots in temperate regions of Earth is driven by soil heterogeneities, especially the temporal and spatial availability of nutrients. Here we investigate whether microbial activity hotspots also exist in lithic microhabitats in one of the most arid regions of the world, the Atacama Desert in Chile. While previous studies evaluated the total DNA fraction to elucidate the microbial communities, we here for the first time use a DNA separation approach on lithic microhabitats, together with metagenomics and other analysis methods (i.e., ATP, PLFA, and metabolite analysis) to specifically gain insights on the living and potentially active microbial community. Our results show that hypolith colonized rocks are microbial hotspots in the desert environment. In contrast, our data do not support such a conclusion for gypsum crust and salt rock environments, because only limited microbial activity could be observed. The hypolith community is dominated by phototrophs, mostly Cyanobacteria and Chloroflexi, at both study sites. The gypsum crusts are dominated by methylotrophs and heterotrophic phototrophs, mostly Chloroflexi, and the salt rocks (halite nodules) by phototrophic and halotolerant endoliths, mostly Cyanobacteria and Archaea. The major environmental constraints in the organic-poor arid and hyperarid Atacama Desert are water availability and UV irradiation, allowing phototrophs and other extremophiles to play a key role in desert ecology.

Zooming in: a single-cell perspective on nitrogen fixation in the rhizosphere of rice

&lt;p&gt;Our current understanding of microbial hotspots such as the rhizosphere mainly stems from observations through measurements at the macroscopic scale, integrating a multitude of microbial cells and taxa into a few measured variables. Consequently, we still lack an understanding of the individual participants that actively contribute to processes. Identifying microorganisms and relating their activity to these processes within the soil-plant interface on a microscopic scale represent a missing link in understanding nutrient flux in agriculturally important ecosystems such as rice cultivation.&lt;/p&gt;&lt;p&gt;I will present a novel workflow for single-cell isotope imaging in the rhizosphere that combines fluorescence &lt;em&gt;in situ&lt;/em&gt; hybridization, gold-targeted secondary electron microscopy, and nano-scale secondary ion mass spectrometry. Based on correlative microscopy and hotspot detection, this approach now allows to (i) identify single bacteria on root surfaces that actively incorporate stable isotopes, (ii) quantify their contribution to processes of interest within a given population, and (iii) potentially trace nutrient fluxes among plants and bacteria on a microscale.&lt;/p&gt;&lt;p&gt;Illuminating plant-microorganism interactions on a microscale provides the potential to evaluate the actual impact of bio-inoculants applied as fertilizers and to engineer plant-microorganism associations which may be essential to increase the production of major staple crops for a growing world population.&lt;/p&gt;

How 'hot' are the hotspots: Statistical approach to localize the high activity areas on soil images

&lt;p&gt;The recently raised topic of microbial hotspots in soil needs not only visualizations of their spatial distribution and biochemical analyses, but also statistical approaches to segregate these hotspots and separate them from the background. &amp;#160;We hypothesized that each type of hotspots (e.g. hotspots of root exudation, enzyme activities, root water uptake, pesticides accumulation in plant) is a result of processes driven by biotic or abiotic factors, and consequently corresponds to a statistical distribution follows of a composite functions (e.g. normal/Gaussian), which is significantly different from the background. Consequently, the elucidation of microbial hotspots should be based on statistical separation of the distributions or segregate of maximal values within one distribution. As examples, we collected 3 groups of published images: 1) &lt;sup&gt;14&lt;/sup&gt;C images on carbon input by roots into the rhizosphere, &lt;sup&gt;14&lt;/sup&gt;C localization in roots and glyphosate accumulation in the plant, 2) zymogram on leucine aminopeptidase, 3) neutron image on root water uptake. Each of the images was analyzed for statistical distribution of activity and its area. In the next step, respective distribution parameters (means and standard deviations) were calculated, the modeled distribution was fit, and the background was removed. For the parameters with one distribution, we identified hotspots as the areas outside of the &amp;#8220;Mean+2SD&amp;#8221; values (corresponding to the upper ~ 2.5% of activity being over 95.5 % of background values). Finally, images of solely hotspots locations were visualised. Comparison with previously used decisions of the hotspot intensity (i.e. Top-25% intensity) thresholding showed advantages of the &amp;#8220;Mean+2SD&amp;#8221; approach. The advantages (suitable for &amp;#8220;time-specific&amp;#8221; hotspots in temporal sequence of images, identification of hotspots with different level of activity, unification of thresholding approach for several imaging methods with different principles of activities distribution) and limitations (loss of hotspot areas at low quality images, several thresholding rounds for two or more distributions at on image) of the suggested approach and the potentials of its further development were discussed. We conclude that objective elucidation and separation of the hotspots is case specific and should be based on statistical tools of distribution analysis, which will also help to understand the processes responsible for the highest activities.&lt;/p&gt;