News Item
Multidisciplinary Sciences
Ewen Callaway
Summary: Microbial molecules from soil, seawater, and human bodies are among the least understood substances on Earth.
Article
Oncology
Richard J. Sove, Babita K. Verma, Hanwen Wang, Won Jin Ho, Mark Yarchoan, Aleksander S. Popel
Summary: This study uses quantitative systems pharmacology (QSP) framework to conduct a virtual clinical trial for nivolumab and ipilimumab in HCC patients. The model incorporates detailed biological mechanisms of immune cell-cancer cell interactions and generates virtual patients for the trial. The predictions of the model are consistent with clinically observed outcomes, demonstrating the potential of QSP models in patient selection and trial design.
JOURNAL FOR IMMUNOTHERAPY OF CANCER
(2022)
Article
Biochemical Research Methods
Andrea Laguillo-Gomez, Enrique Calvo, Noa Martin-Cofreces, Marta Lozano-Prieto, Francisco Sanchez-Madrid, Jesus Vazquez
Summary: Open-search methods with prior knowledge improve identification performance of protein post-translational modifications by minimizing experimental errors and precursor mass assignation. The introduction of a novel approach enables the study of a wider variety of PTMs, including unknown or unexpected modifications.
JOURNAL OF PROTEOMICS
(2023)
Article
Biochemistry & Molecular Biology
Yosui Nojima, Masahiko Aoki, Suyong Re, Hidekazu Hirano, Yuichi Abe, Ryohei Narumi, Satoshi Muraoka, Hirokazu Shoji, Kazufumi Honda, Takeshi Tomonaga, Kenji Mizuguchi, Narikazu Boku, Jun Adachi
Summary: This study investigated the anti-tumor efficacy of apatinib against gastric cancer cell lines and found that it differed among different cell lines. The study also revealed that apatinib acts as a multi-kinase inhibitor, predominantly targeting c-Kit. These findings contribute to a deeper understanding of the mechanism of action of apatinib in gastric cancer cells.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2023)
Article
Geriatrics & Gerontology
Daigo Okada
Summary: This study identified 17 age-related proteins produced by a single tissue and a single cell type through integrative data mining, which may be valuable for understanding age-related changes in the plasma proteome and inter-tissue networks.
News Item
Multidisciplinary Sciences
Ewen Callaway
Summary: Advancements in artificial intelligence enable researchers to create original molecules within seconds instead of months.
Review
Biochemical Research Methods
Timothy D. Veenstra
Summary: Biological research has shifted from focusing on single molecules to analyzing thousands simultaneously, giving rise to various omics fields. These omics fields are laying the groundwork for the development of systems biology, which aims to understand complex interactions within biological systems.
Article
Biochemistry & Molecular Biology
Alberto Cristiani, Arghya Dutta, Sergio Alejandro Poveda-Cuevas, Andreas Kern, Ramachandra M. M. Bhaskara
Summary: Selective autophagy receptors (SARs) play a crucial role in maintaining cellular homeostasis and recycling of organelles. However, the extent of selective autophagy pathways and the associated cargo components in different cellular contexts are not fully understood. In this study, we integrated autophagosome content profiling data with various datasets using predictive and modeling approaches to identify a global set of potential SARs and their associated cargo components. We classified these SARs based on their subcellular compartments and predicted their mode of action. Our findings provide unprecedented details on the autophagic state of HeLa cells and expand the repertoire of SARs, motivating further experiments to investigate the role of these novel factors in selective autophagy.
JOURNAL OF CELLULAR BIOCHEMISTRY
(2023)
Article
Oncology
Hanwen Wang, Huilin Ma, Richard J. Sove, Leisha A. Emens, Aleksander S. Popel
Summary: This study introduces a modular quantitative systems pharmacology (QSP) platform for predicting immunotherapy efficacy and identifying predictive biomarkers. Virtual clinical trials were conducted using a virtual patient cohort generated by the model, with retrospective analysis and model validation based on clinical trial data.
JOURNAL FOR IMMUNOTHERAPY OF CANCER
(2021)
Review
Biochemical Research Methods
Mohammad Reza Karimi, Amir Hossein Karimi, Shamsozoha Abolmaali, Mehdi Sadeghi, Ulf Schmitz
Summary: Holistic perspectives are crucial in understanding the complexity of tumors and current single-layer analysis has limitations. Integrative multilayer approaches are emerging as effective tools in achieving systemic views on cancer biology.
BRIEFINGS IN BIOINFORMATICS
(2022)
Review
Cardiac & Cardiovascular Systems
Dara Vakili, Dina Radenkovic, Shreya Chawla, Deepak L. Bhatt
Summary: The multifactorial nature of cardiology makes separating noisy signals from real markers or drivers of disease challenging, while the pan-omics approach provides deeper insights into underlying biological mechanisms. Larger database sample sizes and longer follow-up are often better suited for pan-omic analyses in dealing with large biological variability.
FRONTIERS IN CARDIOVASCULAR MEDICINE
(2021)
News Item
Multidisciplinary Sciences
Ewen Callaway
Summary: Analysis of protein shapes reveals unexpected forms and connections.
Editorial Material
Multidisciplinary Sciences
Jeffrey A. Farrell
Summary: CellOracle, a computational tool, can predict the interaction of gene networks in programming cell identity during embryonic development. This tool will contribute to a better understanding of the regulation of development.
Review
Biochemical Research Methods
Peter D. Karp, Peter E. Midford, Richard Billington, Anamika Kothari, Markus Krummenacker, Mario Latendresse, Wai Kit Ong, Pallavi Subhraveti, Ron Caspi, Carol Fulcher, Ingrid M. Keseler, Suzanne M. Paley
Summary: The development of Pathway Tools software enables researchers to construct biological knowledge resources more efficiently, develop metabolic flux models, and interpret high-throughput data using pathway information.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Immunology
Mohamed Helmy, Kumar Selvarajoo
Summary: The majority of human genome consists of non-coding genes, with about half made up of transposable elements, including endogenous retroviruses. While generally harmless, endogenous retroviruses have been linked to inflammatory diseases and cancer, posing a challenge in elucidating the mechanistic understanding between them.
FRONTIERS IN IMMUNOLOGY
(2021)
Article
Biochemical Research Methods
Pieter Verschaffelt, James Collier, Alexander Botzki, Lennart Martens, Peter Dawyndt, Bart Mesuere
Summary: The Unipept Visualizations library is a JavaScript package that generates interactive visualizations of both hierarchical and non-hierarchical quantitative data, with support for different visualizations and utilizing the D3.js library.
Article
Biochemical Research Methods
Kay Schallert, Pieter Verschaffelt, Bart Mesuere, Dirk Benndorf, Lennart Martens, Tim Van den Bossche
Summary: In metaproteomics, the protein inference problem is more challenging than in single-species proteomics. To address this issue, we developed a tool called Pout2Prot, which converts Percolator output files into protein group output files that can be used with Prophane.
JOURNAL OF PROTEOME RESEARCH
(2022)
Article
Biochemistry & Molecular Biology
Mihaly Varadi, Stephen Anyango, David Armstrong, John Berrisford, Preeti Choudhary, Mandar Deshpande, Nurul Nadzirin, Sreenath S. Nair, Lukas Pravda, Ahsan Tanweer, Bissan Al-Lazikani, Claudia Andreini, Geoffrey J. Barton, David Bednar, Karel Berka, Tom Blundell, Kelly P. Brock, Jose Maria Carazo, Jiri Damborsky, Alessia David, Sucharita Dey, Roland Dunbrack, Juan Fernandez Recio, Franca Fraternali, Toby Gibson, Manuela Helmer-Citterich, David Hoksza, Thomas Hopf, David Jakubec, Natarajan Kannan, Radoslav Krivak, Manjeet Kumar, Emmanuel D. Levy, Nir London, Jose Ramon Macias, Madhusudhan M. Srivatsan, Debora S. Marks, Lennart Martens, Stuart A. McGowan, Jake E. McGreig, Vivek Modi, R. Gonzalo Parra, Gerardo Pepe, Damiano Piovesan, Jaime Prilusky, Valeria Putignano, Leandro G. Radusky, Pathmanaban Ramasamy, Atilio O. Rausch, Nathalie Reuter, Luis A. Rodriguez, Nathan J. Rollins, Antonio Rosato, Luis Serrano, Gulzar Singh, Petr Skoda, Carlos Oscar S. Sorzano, Jan Stourac, Joanna Sulkowska, Radka Svobodova, Natalia Tichshenko, Silvio C. E. Tosatto, Wim Vranken, Mark N. Wass, Dandan Xue, Daniel Zaidman, Janet Thornton, Michael Sternberg, Christine Orengo, Sameer Velankar
Summary: PDBe-KB is an open collaboration platform that aims to integrate functional and biophysical annotations from world-leading specialist data resources, serving the Protein Data Bank. By developing standardized data exchange formats and integrating functional annotations from partner resources, PDBe-KB aims to place macromolecular structure data in a biological context and provide valuable biological insights.
NUCLEIC ACIDS RESEARCH
(2022)
Article
Biochemical Research Methods
Genet Abay Shiferaw, Ralf Gabriels, Robbin Bouwmeester, Tim Van den Bossche, Elien Vandermarliere, Lennart Martens, Pieter-Jan Volders
Summary: Maintaining high sensitivity while limiting false positives in peptide identification from mass spectrometry data is a key challenge. This study investigates the effects of integrating the machine learning-based postprocessor Percolator into the spectral library searching tool COSS.
JOURNAL OF PROTEOME RESEARCH
(2022)
Article
Multidisciplinary Sciences
Bart Van Puyvelde, Simon Daled, Sander Willems, Ralf Gabriels, Anne Gonzalez de Peredo, Karima Chaoui, Emmanuelle Mouton-Barbosa, David Bouyssie, Kurt Boonen, Christopher J. Hughes, Lee A. Gethings, Yasset Perez-Riverol, Nic Bloomfield, Stephen Tate, Odile Schiltz, Lennart Martens, Dieter Deforce, Maarten Dhaenens
Summary: In the past decade, there has been a revolution in liquid chromatography-mass spectrometry (LC-MS) based proteomics with the introduction of novel instruments and data acquisition methodologies. However, the lack of a benchmark experimental design hampers the development of algorithms to mine publicly available proteomics datasets. To address this, we present a comprehensive dataset acquired using different instrument platforms and data acquisition methods, allowing for algorithm development and performance assessment.
Article
Biochemical Research Methods
Pathmanaban Ramasamy, Elien Vandermarliere, Wim F. Vranken, Lennart Martens
Summary: Protein phosphorylation, the most common reversible post-translational modification of proteins, plays a key role in cellular processes. Using large-scale phospho-proteomics data, we analyze and characterize proteome-wide protein phosphorylation sites (P sites). Differentiating correctly observed P sites from false-positive sites, we explore the context of these P sites in terms of protein structure, solvent accessibility, structural transitions, disorder, and biophysical properties. We also investigate the relative prevalence of disease-linked mutations on and around P sites and assess the structural dynamics of P sites in their phosphorylated and unphosphorylated states. Reprocessing available proteomics experiments enables a more reliable understanding of proteome-wide P sites. Adding the structural context of proteins around P sites uncovers possible conformational switches upon phosphorylation, and by examining different biophysical contexts, we reveal the differential preference in protein dynamics at phosphorylated sites compared to nonphosphorylated counterparts.
JOURNAL OF PROTEOME RESEARCH
(2022)
Article
Biochemical Research Methods
Arthur Declercq, Robbin Bouwmeester, Aurelie Hirschler, Christine Carapito, Sven Degroeve, Lennart Martens, Ralf Gabriels
Summary: Immunopeptidomics aims to identify MHC-presented peptides on cells for anti-cancer vaccine development. However, existing data analysis pipelines have difficulty identifying nontryptic peptides. In this study, a retrained (MSPIP)-P-2 model improved predictions for both immuno-peptides and tryptic peptides. The integration of the new models with DeepLC and Percolator in MS(2)Rescore increased spectrum identification rate and unique identified peptides compared to standard Percolator rescoring, and outperformed current immunopeptide-specific identification approaches.
MOLECULAR & CELLULAR PROTEOMICS
(2022)
Article
Multidisciplinary Sciences
Rupert L. Mayer, Rein Verbeke, Caroline Asselman, Ilke Aernout, Adillah Gul, Denzel Eggermont, Katie Boucher, Fabien Thery, Teresa M. Maia, Hans Demol, Ralf Gabriels, Lennart Martens, Christophe Becavin, Stefaan C. De Smedt, Bart Vandekerckhove, Ine Lentacker, Francis Impens
Summary: The authors used immunopeptidomics to identify bacterial peptides presented on infected cells and identified antigens that provided protection in mice when used as mRNA vaccine.
NATURE COMMUNICATIONS
(2022)
Article
Biochemical Research Methods
Elke Debrie, Milan Malfait, Ralf Gabriels, Arthur Declerq, Adriaan Sticker, Lennart Martens, Lieven Clement
Summary: Reliable peptide identification is crucial in MS-based proteomics, and the TDA method is widely used for estimating the FDR. However, the assumptions of TDA are often not verified in practice, which can result in poor FDR control and negatively impact downstream data analysis. To address this issue, the TargetDecoy package is introduced, providing necessary functionality to assess the quality and assumptions of TDA for a given set of PSMs.
JOURNAL OF PROTEOME RESEARCH
(2023)
Article
Biochemical Research Methods
Ralf Gabriels, Arthur Declercq, Robbin Bouwmeester, Sven Degroeve, Lennart Martens
Summary: There are various output file formats from proteomics search engines, but the lack of standardized formats makes it difficult to process peptide-spectrum matches (PSMs) and PSM files downstream. This article presents psm_utils, a Python package that can handle various PSM file formats and provides a unified and user-friendly interface. It includes a Python API, a command line interface, and a web application for interconverting PSM files and retrieving basic PSM statistics.
JOURNAL OF PROTEOME RESEARCH
(2023)
Article
Biochemical Research Methods
Benjamin A. Neely, Viktoria Dorfer, Lennart Martens, Isabell Bludau, Robbin Bouwmeester, Sven Degroeve, Eric W. Deutsch, Siegfried Gessulat, Lukas Kaell, Pawel Palczynski, Samuel H. Payne, Tobias Greisager Rehfeldt, Tobias Schmidt, Veit Schwaemmle, Julian Uszkoreit, Juan Antonio Vizcaino, Mathias Wilhelm, Magnus Palmblad
Summary: In recent years, machine learning has made significant progress in modeling mass spectrometry data for proteomics analysis. A workshop was conducted to evaluate and explore machine learning applications in multidimensional mass spectrometry-based proteomics analysis. The workshop helped identify knowledge gaps, define needs, and discuss the possibilities, challenges, and future opportunities. The summary of the discussions conveys excitement about the potential of machine learning in proteomics and aims to inspire future research.
JOURNAL OF PROTEOME RESEARCH
(2023)
Article
Biochemical Research Methods
Tine Claeys, Maxime Menu, Robbin Bouwmeester, Kris Gevaert, Lennart Martens
Summary: Using data from 183 public human data sets, a machine learning model was trained to identify tissue and cell-type specific protein patterns. The model achieved high accuracy in predicting tissues (98%) and cell types (99%) based on protein abundance. The results provide valuable insights into tissue-specific proteins and can be applied to various downstream applications.
JOURNAL OF PROTEOME RESEARCH
(2023)
Article
Biochemical Research Methods
Pieter Verschaffelt, Alessandro Tanca, Marcello Abbondio, Tim van den Bossche, Tibo Vande Moortele, Peter Dawyndt, Lennart Martens, Bart Mesuere
Summary: Unipept Desktop 2.0 is the latest version of the Unipept Desktop tool, which now supports the analysis of metaproteogenomics datasets. It allows for the automatic construction of targeted protein reference databases for improved taxonomic and functional resolution. By limiting the proteins in the database, (meta)proteogenomic analyses can also be performed with better control and privacy. A case study using human gut metaproteome dataset and matched 16S rRNA gene sequencing data is presented as a proof of concept.
JOURNAL OF PROTEOME RESEARCH
(2023)
Article
Multidisciplinary Sciences
Tine Claeys, Tim van den Bossche, Yasset Perez-Riverol, Kris Gevaert, Juan Antonio Vizcaino, Lennart Martens
Summary: Public proteomics data often lack essential metadata, but lesSDRF provides a tool to simplify the process of metadata annotation and ensure that the data has lasting impact beyond its initial publication.
NATURE COMMUNICATIONS
(2023)
Article
Biochemical Research Methods
Ralf Gabriels, Arthur Declercq, Robbin Bouwmeester, Sven Degroeve, Lennart Martens
Summary: This study introduces a Python package called psm_utils, which can read and write various proteomics search engine output file formats and handle peptide-spectrum matches (PSMs) and PSM lists in a unified data structure. The package includes a Python API and command line interface, as well as a user-friendly web application for converting PSM files and retrieving basic PSM statistics.
JOURNAL OF PROTEOME RESEARCH
(2023)