Tracing active members in microbial communities by BONCAT and click chemistry-based enrichment of newly synthesized proteins.

A comprehensive understanding of microbial community dynamics is fundamental to the advancement of environmental microbiology, human health, and biotechnology. Metaproteomics, defined as the analysis of all proteins present within a microbial community, provides insights into these complex systems. Microbial adaptation and activity depend to an important extent on newly synthesized proteins (nP), however, the distinction between nP and bulk proteins is challenging.

Proteomic Characterization of 1000 Human and Murine Neutrophils Freshly Isolated From Blood and Sites of Sterile Inflammation.

Neutrophils are indispensable for defense against pathogens. Injured tissue-infiltrated neutrophils can establish a niche of chronic inflammation and promote degeneration. Studies investigated transcriptome of single-infiltrated neutrophils which could misinterpret molecular states of these post mitotic cells.

Detection, isolation and characterization of phage-host complexes using BONCAT and click chemistry.

Introduction: Phages are viruses that infect prokaryotes and can shape microbial communities by lysis, thus offering applications in various fields. However, challenges exist in sampling, isolation and accurate prediction of the host specificity of phages as well as in the identification of newly replicated virions in response to environmental challenges.

Methods: A new workflow using biorthogonal non-canonical amino acid tagging (BONCAT) and click chemistry (CC) allowed the combined analysis of phages and their hosts, the identification of newly replicated virions, and the specific tagging of phages with biotin for affinity chromatography.

Microbiome modeling: a beginner's guide.

Microbiomes, comprised of diverse microbial species and viruses, play pivotal roles in human health, environmental processes, and biotechnological applications and interact with each other, their environment, and hosts via ecological interactions. Our understanding of microbiomes is still limited and hampered by their complexity. A concept improving this understanding is systems biology, which focuses on the holistic description of biological systems utilizing experimental and computational methods.

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.

Improved biological methanation using tubular foam-bed reactor.

Background: Power-to-gas is the pivotal link between electricity and gas infrastructure, enabling the broader integration of renewable energy. Yet, enhancements are necessary for its full potential. In the biomethanation process, transferring H into the liquid phase is a rate-limiting step.

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.

Uncovering Microbiome Adaptations in a Full-Scale Biogas Plant: Insights from MAG-Centric Metagenomics and Metaproteomics.

The current focus on renewable energy in global policy highlights the importance of methane production from biomass through anaerobic digestion (AD). To improve biomass digestion while ensuring overall process stability, microbiome-based management strategies become more important. In this study, metagenomes and metaproteomes were used for metagenomically assembled genome (MAG)-centric analyses to investigate a full-scale biogas plant consisting of three differentially operated digesters.

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.

Decision tree learning in Neo4j on homogeneous and unconnected graph nodes from biological and clinical datasets.

Background: Graph databases enable efficient storage of heterogeneous, highly-interlinked data, such as clinical data. Subsequently, researchers can extract relevant features from these datasets and apply machine learning for diagnosis, biomarker discovery, or understanding pathogenesis.

Methods: To facilitate machine learning and save time for extracting data from the graph database, we developed and optimized Decision Tree Plug-in (DTP) containing 24 procedures to generate and evaluate decision trees directly in the graph database Neo4j on homogeneous and unconnected nodes.

Adaptation of a microbial community to demand-oriented biological methanation.

Background: Biological conversion of the surplus of renewable electricity and carbon dioxide (CO) from biogas plants to biomethane (CH) could support energy storage and strengthen the power grid. Biological methanation (BM) is linked closely to the activity of biogas-producing Bacteria and methanogenic Archaea. During reactor operations, the microbiome is often subject to various changes, e.

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.

Lignocellulose Fermentation Products Generated by Giant Panda Gut Microbiomes Depend Ultimately on pH Rather than Portion of Bamboo: A Preliminary Study.

Giant pandas feed almost exclusively on bamboo but miss lignocellulose-degrading genes. Their gut microbiome may contribute to their nutrition; however, the limited access to pandas makes experimentation difficult. In vitro incubation of dung samples is used to infer gut microbiome activity.

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.

Triangulation of microbial fingerprinting in anaerobic digestion reveals consistent fingerprinting profiles.

The anaerobic digestion microbiome has been puzzling us since the dawn of molecular methods for mixed microbial community analysis. Monitoring of the anaerobic digestion microbiome can either take place via a non-targeted holistic evaluation of the microbial community through fingerprinting or by targeted monitoring of selected taxa. Here, we compared four different microbial community fingerprinting methods, i.

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 Role of ING2-E5A in Mesophilic Biogas Reactor Systems as Deduced from Multiomics Analyses.

Members of the genera and were speculated to represent indicators reflecting process instability within anaerobic digestion (AD) microbiomes. Therefore, ING2-E5A was isolated from a biogas reactor sample and sequenced on the PacBio and Illumina MiSeq sequencers. Phylogenetic classification positioned the strain ING2-E5A in close proximity to and species (family Dysgonomonadaceae).

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.

Substrate-Dependent Fermentation of Bamboo in Giant Panda Gut Microbiomes: Leaf Primarily to Ethanol and Pith to Lactate.

The giant panda is known worldwide for having successfully moved to a diet almost exclusively based on bamboo. Provided that no lignocellulose-degrading enzyme was detected in panda's genome, bamboo digestion is believed to depend on its gut microbiome. However, pandas retain the digestive system of a carnivore, with retention times of maximum 12 h.

The performance of practitioners conducting facial comparisons on images of children across age.

Determining the identity of children is critical to aid in the fight against child exploitation, as well as for passport control and visa issuance purposes. Facial image comparison is one method that may be used to determine identity. Due to the substantial amount of facial growth that occurs in childhood, it is critical to understand facial image comparison performance across both chronological age (the age of the child), and age variation (the age difference between images).

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.

Metaproteome analysis reveals that syntrophy, competition, and phage-host interaction shape microbial communities in biogas plants.

Background: In biogas plants, complex microbial communities produce methane and carbon dioxide by anaerobic digestion of biomass. For the characterization of the microbial functional networks, samples of 11 reactors were analyzed using a high-resolution metaproteomics pipeline.

Results: Examined methanogenesis archaeal communities were either mixotrophic or strictly hydrogenotrophic in syntrophy with bacterial acetate oxidizers.

Metaproteomics of fecal samples of Crohn's disease and Ulcerative Colitis.

Crohn's Disease (CD) and Ulcerative Colitis (UC) are chronic inflammatory bowel diseases (IBD) of the gastrointestinal tract. This study used non-invasive LC-MS/MS to find disease specific microbial and human proteins which might be used later for an easier diagnosis. Therefore, 17 healthy controls, 11 CD patients and 14 UC patients but also 13 Irritable Bowel Disease (IBS) patients, 8 Colon Adenoma (CA) patients, and 8 Gastric Carcinoma (GCA) patients were investigated.