Interaction Networks Are Driven by Community-Responsive Phenotypes in a Chitin-Degrading Consortium of Soil Microbes

Soil microorganisms provide key ecological functions that often rely on metabolic interactions between individual populations of the soil microbiome. To better understand these interactions and community processes, we used chitin, a major carbon and nitrogen source in soil, as a test substrate to investigate microbial interactions during its decomposition. Chitin was applied to a model soil consortium that we developed, “model soil consortium-2” (MSC-2), consisting of eight members of diverse phyla and including both chitin degraders and nondegraders. A multiomics approach revealed how MSC-2 community-level processes during chitin decomposition differ from monocultures of the constituent species. Emergent properties of both species and the community were found, including changes in the chitin degradation potential of Streptomyces species and organization of all species into distinct roles in the chitin degradation process. The members of MSC-2 were further evaluated via metatranscriptomics and community metabolomics. Intriguingly, the most abundant members of MSC-2 were not those that were able to metabolize chitin itself, but rather those that were able to take full advantage of interspecies interactions to grow on chitin decomposition products. Using a model soil consortium greatly increased our knowledge of how carbon is decomposed and metabolized in a community setting, showing that niche size, rather than species metabolic capacity, can drive success and that certain species become active carbon degraders only in the context of their surrounding community. These conclusions fill important knowledge gaps that are key to our understanding of community interactions that support carbon and nitrogen cycling in soi

Interaction Networks Are Driven by Community-Responsive Phenotypes in a Chitin-Degrading Consortium of Soil Microbes

Soil microorganisms provide key ecological functions that often rely on metabolic interactions between individual populations of the soil microbiome. To better understand these interactions and community processes, we used chitin, a major carbon and nitrogen source in soil, as a test substrate to investigate microbial interactions during its decomposition. Chitin was applied to a model soil consortium that we developed, “model soil consortium-2” (MSC-2), consisting of eight members of diverse phyla and including both chitin degraders and nondegraders. A multiomics approach revealed how MSC-2 community-level processes during chitin decomposition differ from monocultures of the constituent species. Emergent properties of both species and the community were found, including changes in the chitin degradation potential of Streptomyces species and organization of all species into distinct roles in the chitin degradation process. The members of MSC-2 were further evaluated via metatranscriptomics and community metabolomics. Intriguingly, the most abundant members of MSC-2 were not those that were able to metabolize chitin itself, but rather those that were able to take full advantage of interspecies interactions to grow on chitin decomposition products. Using a model soil consortium greatly increased our knowledge of how carbon is decomposed and metabolized in a community setting, showing that niche size, rather than species metabolic capacity, can drive success and that certain species become active carbon degraders only in the context of their surrounding community. These conclusions fill important knowledge gaps that are key to our understanding of community interactions that support carbon and nitrogen cycling in soil

New mass spectrometry technologies contributing towards comprehensive and high throughput omics analyses of single cells

Mass-spectrometry based omics technologies - namely proteomics, metabolomics and lipidomics - have enabled the molecular level systems biology investigation of organisms in unprecedented detail. There has been increasing interest for gaining a thorough, functional understanding of the biological consequences associated with cellular heterogeneity in a wide variety of research areas such as developmental biology, precision medicine, cancer research and microbiome science. Recent advances in mass spectrometry (MS) instrumentation and sample handling strategies are quickly making comprehensive omics analyses of single cells feasible, but key breakthroughs are still required to push through remaining bottlenecks. In this review, we discuss the challenges faced by single cell MS-based omics analyses and highlight recent technological advances that collectively can contribute to comprehensive and high throughput omics analyses in single cells. We provide a vision of the potential of integrating pioneering technologies such as Structures for Lossless Ion Manipulations (SLIM) for improved sensitivity and resolution, novel peptide identification tactics and standards free metabolomics approaches for future applications in single cell analysis

Fungal organic acid uptake of mineral-derived K is dependent on distance from carbon hotspot

ABSTRACT Fungal mineral weathering regulates the bioavailability of inorganic nutrients from mineral surfaces to organic matter and increase the bioavailable fraction of nutrients. Such weathering strategies are classified as biomechanical or biochemical. In the case of fungal uptake of mineral nutrients through biochemical weathering, it is widely hypothesized that uptake of inorganic nutrients occurs through organic acid chelation, but such processes have not been directly visualized. This is in part due to challenges in probing the complex and heterogeneous soil environment. Here, using an epoxy-based, mineral-doped soil micromodel platform, which emulates soil mineralogy and porosity, we visualize the molecular mechanisms of mineral weathering. Mass spectrometry imaging revealed differences in the distribution of fungal exudates, citric acid, and tartaric acid on the soil micromodels in presence of minerals. Citric acid was detected closer to the nutrient-rich inoculation point, whereas tartaric acid was highly abundant away from inoculation point. This suggested that the organic acid exuded by the fungi depended on the proximity from the carbon-rich organic substrate at the point of inoculation. Using a combination of X-ray fluorescence and X-ray near edge structure analysis, we identified citric acid- and tartaric acid-bound K within fungal hyphae networks grown in the presence of minerals. Combined, our results provide direct evidence that fungi uptake and transport mineral derived nutrient organic acid chelation. The results of this study provided unprecedented visualization of fungal uptake and transport of K+, while resolving the indirect weathering mechanism of fungal K uptake from mineral interfaces. IMPORTANCE Fungal species are foundational members of soil ecosystems with vital contributions that support interspecies resource translocation. The minute details of these biogeochemical processes are poorly investigated. Here, we addressed this knowledge gap by probing fungal growth in a novel mineral-doped soil micromodel platform using spatially-resolved imaging methodologies. We found that fungi uptake K from K-rich minerals using organic acids exuded in a distance-dependent manner from a carbon-rich hotspot. While identification of specific mechanisms within soil remains challenging, our findings demonstrate the significance of reduced complexity platforms such as the mineral-doped micromodel in probing biogeochemical processes. These findings provide visualization into hyphal uptake and transport of mineral-derived nutrients in a resource-limited environment

Influence of soil depth, irrigation, and plant genotype on the soil microbiome, metaphenome, and carbon chemistry

ABSTRACT Climate change is causing an increase in drought in many soil ecosystems and a loss of soil organic carbon. Calcareous soils may partially mitigate these losses via carbon capture and storage. Here, we aimed to determine how irrigation-supplied soil moisture and perennial plants impact biotic and abiotic soil properties that underpin deep soil carbon chemistry in an unfertilized calcareous soil. Soil was sampled up to 1 m in depth from irrigated and planted field treatments and was analyzed using a suite of omics and chemical analyses. The soil microbial community composition was impacted more by irrigation and plant cover treatments than by soil depth. By contrast, metabolomes, lipidomes, and proteomes differed more with soil depth than treatments. Deep soil (>50 cm) had higher soil pH and calcium concentrations and higher levels of organic acids, bicarbonate, and triacylglycerides. By contrast, surface soil (0–5 cm) had higher concentrations of soil organic matter, organic carbon, oxidizable carbon, and total nitrogen. Surface soils also had higher amounts of sugars, sugar alcohols, phosphocholines, and proteins that reflect osmotic and oxidative stress responses. The lipidome was more responsive to perennial tall wheatgrass treatments compared to the metabolome or proteome, with a striking change in diacylglyceride composition. Permanganate oxidizable carbon was more consistently correlated to metabolites and proteins than soil organic and inorganic carbon and soil organic matter. This study reveals specific compounds that reflect differences in organic, inorganic, and oxidizable soil carbon fractions that are impacted by interactions between irrigation-supplied moisture and plant cover in calcareous soil profiles. IMPORTANCE Carbon is cycled through the air, plants, and belowground environment. Understanding soil carbon cycling in deep soil profiles will be important to mitigate climate change. Soil carbon cycling is impacted by water, plants, and soil microorganisms, in addition to soil mineralogy. Measuring biotic and abiotic soil properties provides a perspective of how soil microorganisms interact with the surrounding chemical environment. This study emphasizes the importance of considering biotic interactions with inorganic and oxidizable soil carbon in addition to total organic carbon in carbonate-containing soils for better informing soil carbon management decisions

Comparing Top-Down Proteoform Identification: Deconvolution, PrSM Overlap, and PTM Detection

International audienceGenerating top-down tandem mass spectra (MS/MS) from complex mixtures of proteoforms benefits from improvements in fractionation, separation, fragmentation, and mass analysis. The algorithms to match MS/MS to sequences have undergone a parallel evolution, with both spectral alignment and match-counting approaches producing high-quality proteoform-spectrum matches (PrSMs). This study assesses state-of-the-art algorithms for top-down identification (ProSight PD, TopPIC, MSPathFinderT, and pTop) in their yield of PrSMs while controlling false discovery rate. We evaluated deconvolution engines (ThermoFisher Xtract, Bruker AutoMSn, Matrix Science Mascot Distiller, TopFD, and FLASHDeconv) in both ThermoFisher Orbitrap-class and Bruker maXis Q-TOF data (PXD033208) to produce consistent precursor charges and mass determinations. Finally, we sought post-translational modifications (PTMs) in proteoforms from bovine milk (PXD031744) and human ovarian tissue. Contemporary identification workflows produce excellent PrSM yields, although approximately half of all identified proteoforms from these four pipelines were specific to only one workflow. Deconvolution algorithms disagree on precursor masses and charges, contributing to identification variability. Detection of PTMs is inconsistent among algorithms. In bovine milk, 18% of PrSMs produced by pTop and TopMG were singly phosphorylated, but this percentage fell to 1% for one algorithm. Applying multiple search engines produces more comprehensive assessments of experiments. Top-down algorithms would benefit from greater interoperability

Standardized multi-omics of Earth’s microbiomes reveals microbial and metabolite diversity

Despite advances in sequencing, lack of standardization makes comparisons across studies challenging and hampers insights into the structure and function of microbial communities across multiple habitats on a planetary scale. Here we present a multi-omics analysis of a diverse set of 880 microbial community samples collected for the Earth Microbiome Project. We include amplicon (16S, 18S, ITS) and shotgun metagenomic sequence data, and untargeted metabolomics data (liquid chromatography-tandem mass spectrometry and gas chromatography mass spectrometry). We used standardized protocols and analytical methods to characterize microbial communities, focusing on relationships and co-occurrences of microbially related metabolites and microbial taxa across environments, thus allowing us to explore diversity at extraordinary scale. In addition to a reference database for metagenomic and metabolomic data, we provide a framework for incorporating additional studies, enabling the expansion of existing knowledge in the form of an evolving community resource. We demonstrate the utility of this database by testing the hypothesis that every microbe and metabolite is everywhere but the environment selects. Our results show that metabolite diversity exhibits turnover and nestedness related to both microbial communities and the environment, whereas the relative abundances of microbially related metabolites vary and co-occur with specific microbial consortia in a habitat-specific manner. We additionally show the power of certain chemistry, in particular terpenoids, in distinguishing Earth’s environments (for example, terrestrial plant surfaces and soils, freshwater and marine animal stool), as well as that of certain microbes including Conexibacter woesei (terrestrial soils), Haloquadratum walsbyi (marine deposits) and Pantoea dispersa (terrestrial plant detritus). This Resource provides insight into the taxa and metabolites within microbial communities from diverse habitats across Earth, informing both microbial and chemical ecology, and provides a foundation and methods for multi-omics microbiome studies of hosts and the environment

Standardized multi-omics of Earth's microbiomes reveals microbial and metabolite diversity

Despite advances in sequencing, lack of standardization makes comparisons across studies challenging and hampers insights into the structure and function of microbial communities across multiple habitats on a planetary scale. Here we present a multi-omics analysis of a diverse set of 880 microbial community samples collected for the Earth Microbiome Project. We include amplicon (16S, 18S, ITS) and shotgun metagenomic sequence data, and untargeted metabolomics data (liquid chromatography-tandem mass spectrometry and gas chromatography mass spectrometry). We used standardized protocols and analytical methods to characterize microbial communities, focusing on relationships and co-occurrences of microbially related metabolites and microbial taxa across environments, thus allowing us to explore diversity at extraordinary scale. In addition to a reference database for metagenomic and metabolomic data, we provide a framework for incorporating additional studies, enabling the expansion of existing knowledge in the form of an evolving community resource. We demonstrate the utility of this database by testing the hypothesis that every microbe and metabolite is everywhere but the environment selects. Our results show that metabolite diversity exhibits turnover and nestedness related to both microbial communities and the environment, whereas the relative abundances of microbially related metabolites vary and co-occur with specific microbial consortia in a habitat-specific manner. We additionally show the power of certain chemistry, in particular terpenoids, in distinguishing Earth’s environments (for example, terrestrial plant surfaces and soils, freshwater and marine animal stool), as well as that of certain microbes including Conexibacter woesei (terrestrial soils), Haloquadratum walsbyi (marine deposits) and Pantoea dispersa (terrestrial plant detritus). This Resource provides insight into the taxa and metabolites within microbial communities from diverse habitats across Earth, informing both microbial and chemical ecology, and provides a foundation and methods for multi-omics microbiome studies of hosts and the environment