Metaproteomic Analysis of Biogas Plants: A Complete Workflow from Lab to Bioinformatics.

Metaproteomics represents a promising and fast method to analyze the taxonomic and functional composition of biogas plant microbiomes. However, metaproteomics sample preparation and bioinformatics analysis is still challenging due to the sample complexity and contaminants. In this chapter, a tailored workflow including sampling, phenol extraction in a ball mill, amido black protein quantification, FASP digestion, LC-MS/MS measurement as well as bioinformatics and biostatistical data evaluation are here described for the metaproteomics advancements applied to biogas plant samples.

Breakdown of hardly degradable carbohydrates (lignocellulose) in a two-stage anaerobic digestion plant is favored in the main fermenter.

The yield and productivity of biogas plants depend on the degradation performance of their microbiomes. The spatial separation of the anaerobic digestion (AD) process into a separate hydrolysis and a main fermenter should improve cultivation conditions of the microorganisms involved in the degradation of complex substrates like lignocellulosic biomass (LCB) and, thus, the performance of anaerobic digesters. However, relatively little is known about such two-stage processes.

The importance of graph databases and graph learning for clinical applications.

The increasing amount and complexity of clinical data require an appropriate way of storing and analyzing those data. Traditional approaches use a tabular structure (relational databases) for storing data and thereby complicate storing and retrieving interlinked data from the clinical domain. Graph databases provide a great solution for this by storing data in a graph as nodes (vertices) that are connected by edges (links).

Advances in the clinical use of metaproteomics.

Introduction: Investigating the taxonomic and functional composition of human microbiomes can aid in the understanding of disease etiologies, diagnosis, and therapy monitoring for several diseases, including inflammatory bowel disease or obesity. One method for microbiome monitoring is metaproteomics, which assesses human and microbial proteins and thus enables the study of host-microbiome interactions. This advantage led to increased interest in metaproteome analyses and significant developments to introduce this method into a clinical context.

Discovering Biomarkers for Non-Alcoholic Steatohepatitis Patients with and without Hepatocellular Carcinoma Using Fecal Metaproteomics.

High-calorie diets lead to hepatic steatosis and to the development of non-alcoholic fatty liver disease (NAFLD), which can evolve over many years into the inflammatory form of non-alcoholic steatohepatitis (NASH), posing a risk for the development of hepatocellular carcinoma (HCC). Due to diet and liver alteration, the axis between liver and gut is disturbed, resulting in gut microbiome alterations. Consequently, detecting these gut microbiome alterations represents a promising strategy for early NASH and HCC detection.

: An Efficient Tool to Create Protein (Sub)groups from Percolator Output Files.

In metaproteomics, the study of the collective proteome of microbial communities, the protein inference problem is more challenging than in single-species proteomics. Indeed, a peptide sequence can be present not only in multiple proteins or protein isoforms of the same species, but also in homologous proteins from closely related species. To assign the taxonomy and functions of the microbial species, specialized tools have been developed, such as Prophane.

MPA_Pathway_Tool: User-Friendly, Automatic Assignment of Microbial Community Data on Metabolic Pathways.

Taxonomic and functional characterization of microbial communities from diverse environments such as the human gut or biogas plants by multi-omics methods plays an ever more important role. Researchers assign all identified genes, transcripts, or proteins to biological pathways to better understand the function of single species and microbial communities. However, due to the versality of microbial metabolism and a still-increasing number of newly biological pathways, linkage to standard pathway maps such as the KEGG central carbon metabolism is often problematic.

Fecal Metaproteomics Reveals Reduced Gut Inflammation and Changed Microbial Metabolism Following Lifestyle-Induced Weight Loss.

Gut microbiota-mediated inflammation promotes obesity-associated low-grade inflammation, which represents a hallmark of metabolic syndrome. To investigate if lifestyle-induced weight loss (WL) may modulate the gut microbiome composition and its interaction with the host on a functional level, we analyzed the fecal metaproteome of 33 individuals with metabolic syndrome in a longitudinal study before and after lifestyle-induced WL in a well-defined cohort. The 6-month WL intervention resulted in reduced BMI (-13.

The structure and function of soil archaea across biomes.

We lack a predictive understanding of the environmental drivers determining the structure and function of archaeal communities as well as the proteome associated with these important soil organisms. Here, we characterized the structure (by 16S rRNA gene sequencing) and function (by metaproteomics) of archaea from 32 soil samples across terrestrial ecosystems with contrasting climate and vegetation types. Our multi-"omics" approach unveiled that genes from Nitrosophaerales and Thermoplasmata dominated soils collected from four continents, and that archaea comprise 2.

A complete and flexible workflow for metaproteomics data analysis based on MetaProteomeAnalyzer and Prophane.

Metaproteomics, the study of the collective protein composition of multi-organism systems, provides deep insights into the biodiversity of microbial communities and the complex functional interplay between microbes and their hosts or environment. Thus, metaproteomics has become an indispensable tool in various fields such as microbiology and related medical applications. The computational challenges in the analysis of corresponding datasets differ from those of pure-culture proteomics, e.

Impact of feeding and stirring regimes on the internal stratification of microbial communities in the fermenter of anaerobic digestion plants.

In anaerobic digestion plants (ADs), homogenization of the feed, fermenter content and microbial communities is crucial for efficient and robust biogas production. However, mixing also requires a significant amount of energy. For an 850 m agricultural AD equipped with eight sampling ports, we investigated whether different feeding and stirring regimes enable a sufficient homogenization of the microbial community using metaproteomics and terminal restriction fragment length polymorphism (TRFLP) analysis.

Connecting MetaProteomeAnalyzer and PeptideShaker to Unipept for Seamless End-to-End Metaproteomics Data Analysis.

Although metaproteomics, the study of the collective proteome of microbial communities, has become increasingly powerful and popular over the past few years, the field has lagged behind on the availability of user-friendly, end-to-end pipelines for data analysis. We therefore describe the connection from two commonly used metaproteomics data processing tools in the field, MetaProteomeAnalyzer and PeptideShaker, to Unipept for downstream analysis. Through these connections, direct end-to-end pipelines are built from database searching to taxonomic and functional annotation.

A Robust and Universal Metaproteomics Workflow for Research Studies and Routine Diagnostics Within 24 h Using Phenol Extraction, FASP Digest, and the MetaProteomeAnalyzer.

The investigation of microbial proteins by mass spectrometry (metaproteomics) is a key technology for simultaneously assessing the taxonomic composition and the functionality of microbial communities in medical, environmental, and biotechnological applications. We present an improved metaproteomics workflow using an updated sample preparation and a new version of the MetaProteomeAnalyzer software for data analysis. High resolution by multidimensional separation (GeLC, MudPIT) was sacrificed to aim at fast analysis of a broad range of different samples in less than 24 h.

SDS-PAGE fractionation to increase metaproteomic insight into the taxonomic and functional composition of microbial communities for biogas plant samples.

Metaproteomics represent an important tool for the taxonomic and functional investigation of microbial communities in humans, environment, and technical applications. Due to the high complexity of the microbial communities, protein, and peptide fractionation is applied to improve the characterization of taxonomic and functional composition of microbial communities. In order to target scientific questions regarding taxonomic and functional composition adequately, a tradeoff between the number of fractions analyzed and the required depth of information has to be found.

Challenges and perspectives of metaproteomic data analysis.

In nature microorganisms live in complex microbial communities. Comprehensive taxonomic and functional knowledge about microbial communities supports medical and technical application such as fecal diagnostics as well as operation of biogas plants or waste water treatment plants. Furthermore, microbial communities are crucial for the global carbon and nitrogen cycle in soil and in the ocean.