Community proteogenomics reveals the systemic impact of phosphorus availability on microbial functions in tropical soil.

Phosphorus is a scarce nutrient in many tropical ecosystems, yet how soil microbial communities cope with growth-limiting phosphorus deficiency at the gene and protein levels remains unknown. Here, we report a metagenomic and metaproteomic comparison of microbial communities in phosphorus-deficient and phosphorus-rich soils in a 17-year fertilization experiment in a tropical forest. The large-scale proteogenomics analyses provided extensive coverage of many microbial functions and taxa in the complex soil communities. A greater than fourfold increase in the gene abundance of 3-phytase was the strongest response of soil communities to phosphorus deficiency. Phytase catalyses the release of phosphate from phytate, the most recalcitrant phosphorus-containing compound in soil organic matter. Genes and proteins for the degradation of phosphorus-containing nucleic acids and phospholipids, as well as the decomposition of labile carbon and nitrogen, were also enhanced in the phosphorus-deficient soils. In contrast, microbial communities in the phosphorus-rich soils showed increased gene abundances for the degradation of recalcitrant aromatic compounds, transformation of nitrogenous compounds and assimilation of sulfur. Overall, these results demonstrate the adaptive allocation of genes and proteins in soil microbial communities in response to shifting nutrient constraints

Genome-Resolved Proteomic Stable Isotope Probing of Soil Microbial Communities Using 13CO2 and 13C-Methanol.

Stable isotope probing (SIP) enables tracking the nutrient flows from isotopically labeled substrates to specific microorganisms in microbial communities. In proteomic SIP, labeled proteins synthesized by the microbial consumers of labeled substrates are identified with a shotgun proteomics approach. Here, proteomic SIP was combined with targeted metagenomic binning to reconstruct metagenome-assembled genomes (MAGs) of the microorganisms producing labeled proteins. This approach was used to track carbon flows from 13CO2 to the rhizosphere communities of Zea mays, Triticum aestivum, and Arabidopsis thaliana. Rhizosphere microorganisms that assimilated plant-derived 13C were capable of metabolic and signaling interactions with their plant hosts, as shown by their MAGs containing genes for phytohormone modulation, quorum sensing, and transport and metabolism of nutrients typical of those found in root exudates. XoxF-type methanol dehydrogenases were among the most abundant proteins identified in the rhizosphere metaproteomes. 13C-methanol proteomic SIP was used to test the hypothesis that XoxF was used to metabolize and assimilate methanol in the rhizosphere. We detected 7 13C-labeled XoxF proteins and identified methylotrophic pathways in the MAGs of 8 13C-labeled microorganisms, which supported the hypothesis. These two studies demonstrated the capability of proteomic SIP for functional characterization of active microorganisms in complex microbial communities

Deep learning for peptide identification from metaproteomics datasets

This article explores a proposed deep-learning-based algorithm called DeepFilter for improving peptide identifications from a collection of tandem mass spectra. The authors find that DeepFilter is believed to generalize properly to new, previously unseen peptide-spectrum-matches and can be readily applied in peptide identification from metaproteomics data

Alterations of oral microbiota and impact on the gut microbiome in type 1 diabetes mellitus revealed by integrated multi-omic analyses

BACKGROUND: Alterations to the gut microbiome have been linked to multiple chronic diseases. However, the drivers of such changes remain largely unknown. The oral cavity acts as a major route of exposure to exogenous factors including pathogens, and processes therein may affect the communities in the subsequent compartments of the gastrointestinal tract. Here, we perform strain-resolved, integrated meta-genomic, transcriptomic, and proteomic analyses of paired saliva and stool samples collected from 35 individuals from eight families with multiple cases of type 1 diabetes mellitus (T1DM). RESULTS: We identified distinct oral microbiota mostly reflecting competition between streptococcal species. More specifically, we found a decreased abundance of the commensal Streptococcus salivarius in the oral cavity of T1DM individuals, which is linked to its apparent competition with the pathobiont Streptococcus mutans. The decrease in S. salivarius in the oral cavity was also associated with its decrease in the gut as well as higher abundances in facultative anaerobes including Enterobacteria. In addition, we found evidence of gut inflammation in T1DM as reflected in the expression profiles of the Enterobacteria as well as in the human gut proteome. Finally, we were able to follow transmitted strain-variants from the oral cavity to the gut at the individual omic levels, highlighting not only the transfer, but also the activity of the transmitted taxa along the gastrointestinal tract. CONCLUSIONS: Alterations of the oral microbiome in the context of T1DM impact the microbial communities in the lower gut, in particular through the reduction of "mouth-to-gut" transfer of Streptococcus salivarius. Our results indicate that the observed oral-cavity-driven gut microbiome changes may contribute towards the inflammatory processes involved in T1DM. Through the integration of multi-omic analyses, we resolve strain-variant "mouth-to-gut" transfer in a disease context

Alterations of oral microbiota and impact on the gut microbiome in type 1 diabetes mellitus revealed by integrated multi-omic analyses

Background: Alterations to the gut microbiome have been linked to multiple chronic diseases. However, the drivers of such changes remain largely unknown. The oral cavity acts as a major route of exposure to exogenous factors including pathogens, and processes therein may affect the communities in the subsequent compartments of the gastrointestinal tract. Here, we perform strain‑resolved, integrated meta‑genomic, transcriptomic, and proteomic analyses of paired saliva and stool samples collected from 35 individuals from eight families with multiple cases of type 1 diabetes mellitus (T1DM). Results: We identified distinct oral microbiota mostly reflecting competition between streptococcal species. More specifically, we found a decreased abundance of the commensal Streptococcus salivarius in the oral cavity of T1DM individuals, which is linked to its apparent competition with the pathobiont Streptococcus mutans. The decrease in S. salivarius in the oral cavity was also associated with its decrease in the gut as well as higher abundances in facultative anaerobes including Enterobacteria. In addition, we found evidence of gut inflammation in T1DM as reflected in the expression profiles of the Enterobacteria as well as in the human gut proteome. Finally, we were able to follow transmitted strain‑variants from the oral cavity to the gut at the individual omic levels, highlighting not only the transfer, but also the activity of the transmitted taxa along the gastrointestinal tract. Conclusions: Alterations of the oral microbiome in the context of T1DM impact the microbial communities in the lower gut, in particular through the reduction of “mouth‑to‑gut” transfer of Streptococcus salivarius. Our results indicate that the observed oral‑cavity‑driven gut microbiome changes may contribute towards the inflammatory processes involved in T1DM. Through the integration of multi‑omic analyses, we resolve strain‑variant “mouth‑to‑gut” transfer in a disease context

Implementación de una plataforma digital para el registro, procesamiento y categorización de datos relacionados a los perfiles de los sujetos de prueba, para estudios de metagenómica intestinal humana

La metagenómica es la ciencia que emplea el análisis genético directo de una población de microorganismos contenidos en una muestra ambiental, mediante la extracción directa y clonación de ADN (Thomas, Gilbert & Meyer, 2012; Singh, et. al., 2009). Uno de los focos de la metagenómica es el microbioma intestinal humano, debido a que desempeña un papel clave en la salud (Davenport et. al., 2017; Sekirov, 2010). En los estudios de metagenómica intestinal, se realiza un muestreo de las heces de los sujetos de prueba (Aagaard et. al., 2013), se secuencian los microorganismos que se encuentran en esta, se procesa esta información mediante herramientas bioinformáticas y finalmente los investigadores analizan los resultados obtenidos (Lloyd-Price et. al., 2016). Previamente al proceso de muestreo, se requiere recopilar los metadatos de la muestra (Kunin et. al., 2008), los cuales son datos de los sujetos de prueba que influyen en su microbioma intestinal. Actualmente, estos metadatos se recopilan y procesan de una forma manual, a modo de formulario físico, se almacenan de forma incompleta y no estandarizada, y requieren mucho tiempo para ser procesados y categorizados. Es por ello que, en el presente trabajo de fin de carrera, se busca proponer una herramienta digital que permita la recopilación, procesamiento y categorización de los datos de los sujetos de prueba. Estos datos, los cuales son de distintos tipos, serán recopilados de una manera uniforme en una base de datos, de tal manera que se preserven en el tiempo y los investigadores puedan reutilizar esta información en futuros estudios, sin tener que recurrir a volver a realizar el costoso proceso de secuenciación. Con el fin de resolver este problema, se diseñó una base de datos que almacene los datos de los sujetos de prueba, de una manera estandarizada. Utilizando las entidades y las relaciones identificadas en la revisión de la literatura, se pudo plantear un diseño de base de datos que permita la recopilación de los datos de los participantes. En ese mismo sentido, usando la base de datos planteada, se implementó una plataforma digital que permite gestionar estudios de metagenómica y recopilar los datos de sus participantes. De esta manera, se pueden almacenar los metadatos de las muestras a secuenciar de una manera digital, permitiendo a los investigadores revisar estos datos en un futuro. Finalmente, se identificó las funcionalidades necesarias para el procesamiento de los datos de los sujetos de prueba. Estas funcionalidades fueron implementadas en la plataforma digital, para poder permitir a los investigadores analizar estos datos de una manera rápida y sencilla

The Influence of Microbial Communities on Spatiotemporal Elemental Cycling in Coastal Margins Revealed by Community- and Population-level Genomics and Proteomics

Biotic and abiotic processes at continent-ocean interfaces cycle a disproportionate mass of carbon and nutrients relative to their global surface area, and microbial activity is a principal determinant of organic and inorganic matter flux in these transition zones. Most studies using modern high-throughput ‘omics techniques to link microorganisms with costal biogeochemical cycles have focused on large riverine-estuarine continuums, yet there is emerging evidence that smaller, more numerous rivers and estuaries are also key contributors to regional element fluxes, especially in temperate ecosystems. In this work, I characterized microbe-mediated carbon and nutrient flux through an estuary in the highly-productive Oregon coastal margin. To achieve this aim, I used multiple ‘omics techniques to characterize the functional and taxonomic composition, diversity, and activity of estuarine and coastal microorganisms at the community and population levels and across ecologically- relevant spatial scales. Chapter 2 presents the first spatially-resolved effort to measure microbial metabolic capacity for altering carbon and nitrogen flowing from the Yaquina River to the coastal ocean. Overall, we concluded that the microbial activity in Yaquina Bay is (1) a net source of carbon dioxide to the atmosphere via a biased capacity for respiratory processes and (spatially-constrained) carbon monoxide oxidation, and (2) a net sink of inorganic nitrogen via imbalanced assimilation and mineralization potentials. Population-level life strategies of microbial groups were also important for carbon and nitrogen cycling, with high and low molecular weight organic matter specialization divided between two dominant lineages within this system. These results represent a significant step toward constraining the flow of carbon and nitrogen through estuaries and provide future avenues of research for linking microbial populations with the specific pools of bioavailable resources. Chapter 3 describes the first investigation of microbial community composition across a winter freshwater plume on the Oregon coast. Using population distributions across space from the coastline to the continental shelf, we identified many coastal populations that may be directly involved in the turnover of plume-derived particulate organic carbon and inorganic nutrients. When these data were considered with the observations that (1) community respiration rate peaked at the plume particle maximum and (2) high concentrations of resources were ejected to the coastal ocean in plume water, we concluded that winter river plumes supplement food webs during the cold and wet season of low primary productivity on the central Oregon coast. Chapter 4 characterizes the metabolic roles of microorganisms in transforming organic matter in the Oregon coastal margin. In this project, we performed proteomic stable isotope probing (SIP) on native Yaquina Bay microbial communities using 13Carbon-labeled substrates that simulate naturally-occurring organic matter inputs from active phytoplankton into the heterotrophic food web. SIP patterns and estimated growth rates showed that these resources were partitioned among distinct bacterial taxa and assimilated by populations in taxon-specific patterns. Highly enriched community metaproteomes indicated that substrate addition primarily elicited the de novo synthesis of growth, transcription, and translation functions. Altogether, results from these experiments suggested that rapid (< 18 hours) assimilation into the biomass of many estuarine populations is a major fate of complex dissolved organic matter in Yaquina Bay, thereby making this resource available to different components of the food web in this system. A major outcome of my dissertation is the generation and interpretation of multiple datasets that help advance our understanding of microbe-mediated carbon and nutrient cycling within the Oregon coastal margin. This work is a significant contribution to the scientific community, particularly to biological oceanographers, ecosystem modelers, and microbial ecologists, by providing a prototype investigation of a small estuarine ecosystem and adjacent coastal ocean through microbiological, biogeochemical, and spatial ecology lenses, which can be extended to similar systems to constrain the role of microbes in altering carbon and nutrient flow from the land to the seas