AbstractSummary. PepMapViz is a versatile R package that provides flexible peptide mapping and visualization capabilities. PepMapViz can import peptide dat

Two-dimensional tandem mass spectrometry (2D MS/MS) provides in-depth biopolymer structural information previously not directly accessible with traditional one-dimensional MS/MS workflows, and in sign...

De novo peptide sequencing enables peptide identification from fragmentation spectra without relying on sequence databases. However, incomplete spectra create ambiguity, making unambiguous identificat...

Post-translational modifications (PTMs) play a central role in cellular regulation and are implicated in numerous diseases. Database searching remains the standard for identifying modified peptides fr...

npj Biofilms and Microbiomes - Peptide abundance correlations in metaproteomics enhance taxonomic and functional analysis of the human gut microbiome

FragPipe is recognized as one of the fastest computational platforms in proteomics, making it a practical solution for the rapid quality control of high-throughput sample analyses. Starting with version 23.0, FragPipe introduced the “Generate Summary Report” feature, offering .pdf reports with essential quality control metrics to address the challenge of intuitively assessing large-scale proteomics data. While traditional spreadsheet formats (e.g., tsv files) are accessible, the complexity of the data often limits user-friendly interpretation. To further enhance accessibility, PSManalyst, a Shiny-based R application, was developed to process FragPipe output files (psm.tsv, protein.tsv, and combined_protein.tsv) and provide interactive, code-free data visualization. Users can filter peptide-spectrum matches (PSMs) by quality scores, visualize protease cleavage fingerprints as heatmaps and SeqLogos, and access a range of quality control metrics and representations such as peptide length distributions, ion densities, mass errors, and wordclouds for overrepresented peptides. The tool facilitates seamless switching between PSM and protein data visualization, offering insights into protein abundance discrepancies, samplewise similarity metrics, protein coverage, and contaminants evaluation. PSManalyst leverages several R libraries (lsa, vegan, ggfortify, ggseqlogo, wordcloud2, tidyverse, ggpointdensity, and plotly) and runs on Windows, MacOS, and Linux, requiring only a local R setup and an IDE. The app is available at (https://github.com/41ison/PSManalyst.

Mass spectrometry-based metaproteomics allows for the identification and quantification of thousands of proteins from clinical and environmental samples and is rapidly gaining importance in microbiome...

Background Individual meat consumption in Germany has fallen slightly in recent years, but still exceeds the recommended quantities. High meat consumption has negative impacts both on human health and...

The ability to sequence proteins without reliance on a genomic template defines a critical frontier in modern proteomics. This approach, known as de novo protein sequencing, is essential for applicati...

Proteomics is going viral as a new diagnostic method for untargeted virus identification from patient samples. vPro-MS can be used to simultaneously identify human-pathogenic viruses and analyze the h...

Protein-based therapeutics, such as antibodies and nanobodies, are not encoded in reference genomes, challenging their accurate characterization via standard proteomics. Current methods rely on indire...

Abstract. Metaproteomics is an increasingly popular methodology that provides information regarding the metabolic functions of specific microbial taxa and has potential for contributing to ocean ecolo...

Alternative splicing-mediated protein N-terminal sequence variation is closely associated with diseases, but its identification by mass spectrometry faces technical bottlenecks. Traditional proteogeno...

AlphaFold - A practical guide

A LaTeX template for a basic DFG (Deutsche Forschungsgemeinschaft, German Research Foundation) grant proposal. - hoelzer/dfg

Antibodies are proteins produced by the immune system in response to antigens. Determining the sequence of purified unknown antibodies remains difficult due to factors like incomplete sequence coverage, ambiguous isobaric residues (I/L), and unstable assembly processes. To overcome these issues, we developed the Homo-Tag-Assembler, a software tool using a homology tag fuzzy string matching algorithm. By analyzing amino acid distributions from many similar antibody variable region sequences, we created a probability table specific to these regions. This helped evaluate peptide similarity during de novo sequencing, distinguish peptides from light and heavy chains, and differentiate leucine from isoleucine. Testing with the Herceptin antibody showed full-length sequence coverage with accuracy of 99.1% for the light chain and 100% for the heavy chain variable regions. This method uses conserved regional features and homology based information to enable accurate full-length antibody sequence reconstruction.