Article
Biochemical Research Methods
Fernando Pozo, Jose Manuel Rodriguez, Laura Martinez Gomez, Jesus Vazquez, Michael L. Tress
Summary: Selecting the splice variant that best represents a coding gene is crucial for experimental analyses and mapping clinically relevant variants. This study compares different methods and finds that APPRIS principal isoforms and MANE Select transcripts are the best choices for selecting the main splice variant.
Article
Biochemical Research Methods
Mark Ivanov, Elizaveta M. Solovyeva, Julia A. Bubis, Mikhail Gorshkov
Summary: Protein inference is a crucial step in proteome characterization using a bottom-up approach, and this study proposes a method using peptide feature information from precursor mass spectra to assist in distinguishing homologous proteins more accurately and efficiently.
JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY
(2021)
Article
Cardiac & Cardiovascular Systems
Yu Han, Silas D. Wood, Julianna M. Wright, Vishantie Dostal, Edward Lau, Maggie P. Y. Lam
Summary: Alternative splicing is common in the heart and plays a role in cardiovascular diseases, but detecting non-canonical isoforms at the protein level is challenging. This study used a computational-assisted targeted proteomics workflow to detect protein alternative isoforms in the human heart, combining deep RNA-seq and mass spectrometry data to identify candidate translated isoform peptides. By applying machine learning and designing specific PRM assays, they successfully detected non-canonical isoform peptides in a human heart lysate, showing promise for validating non-canonical protein identification and discovering functionally relevant isoforms in the heart.
JOURNAL OF MOLECULAR AND CELLULAR CARDIOLOGY
(2021)
Article
Biochemistry & Molecular Biology
Matteo Mori, Zhongge Zhang, Amir Banaei-Esfahani, Jean-Benoit Lalanne, Hiroyuki Okano, Ben C. Collins, Alexander Schmidt, Olga T. Schubert, Deok-Sun Lee, Gene-Wei Li, Ruedi Aebersold, Terence Hwa, Christina Ludwig
Summary: Accurate quantification of over 2,000 proteins in Escherichia coli under > 60 growth conditions using a new mass spectrometry workflow led to novel biological findings, providing valuable resources for systems biology and future multi-omics studies.
MOLECULAR SYSTEMS BIOLOGY
(2021)
Article
Biotechnology & Applied Microbiology
Pavel Sinitcyn, Alicia L. Richards, Robert J. Weatheritt, Dain R. Brademan, Harald Marx, Evgenia Shishkova, Jesse G. Meyer, Alexander S. Hebert, Michael S. Westphall, Benjamin J. Blencowe, Juergen Cox, Joshua J. Coon
Summary: Deep proteome sequencing provides an 80% coverage of the human proteome. Shotgun proteomics experiments detect about 10,000 human proteins from a single sample, but fail to distinguish protein variants and isoforms. Our study using various methods identifies a million unique peptides and provides evidence for the translation of nonsynonymous variants.
NATURE BIOTECHNOLOGY
(2023)
Article
Biochemical Research Methods
Ryan M. Riley, Sandra E. Spencer Miko, Ryan D. Morin, Gregg B. Morin, Gian Luca Negri
Summary: PeptideRanger is a tool that efficiently detects and quantifies low abundance proteins by identifying peptides with suitable physiochemical properties for mass spectrometry analysis. It is a flexible and extensively annotated R package that can be customized to prioritize and filter peptides based on selected properties.
JOURNAL OF PROTEOME RESEARCH
(2023)
Article
Biochemical Research Methods
Ryan M. Riley, Sandra E. Spencer Miko, Ryan D. Morin, Gregg B. Morin, Gian Luca Negri
Summary: Targeted and semitargeted mass spectrometry-based approaches are reliable methods to consistently detect and quantify low abundance proteins of clinical significance. However, their development is time-consuming and often requires costly libraries of synthetic peptides. To address this, we developed PeptideRanger, an R package that identifies peptides from proteins of interest with physiochemical properties suitable for mass spectrometry analysis.
JOURNAL OF PROTEOME RESEARCH
(2023)
Article
Biochemical Research Methods
Laurent Gatto, Ruedi Aebersold, Juergen Cox, Vadim Demichev, Jason Derks, Edward Emmott, Alexander M. Franks, Alexander R. Ivanov, Ryan T. Kelly, Luke Khoury, Andrew Leduc, Michael J. MacCoss, Peter Nemes, David H. Perlman, Aleksandra A. Petelski, Christopher M. Rose, Erwin M. Schoof, Jennifer Van Eyk, Christophe Vanderaa, John R. R. Yates III, Nikolai Slavov
Summary: Analyzing proteins from single cells by tandem mass spectrometry (MS) has the potential to accurately quantify thousands of proteins across thousands of single cells. However, various factors affecting experimental design, sample preparation, data acquisition and analysis may undermine the accuracy and reproducibility of the results. Best practices, quality controls, and data-reporting recommendations are proposed to enhance the reliability of quantitative workflows for single-cell proteomics.
Article
Biochemical Research Methods
Devon Kohler, Mateusz Staniak, Tsung-Heng Tsai, Ting Huang, Nicholas Shulman, Oliver M. Bernhardt, Brendan X. MacLean, Alexey I. Nesvizhskii, Lukas Reiter, Eduard Sabido, Meena Choi, Olga Vitek
Summary: The MSstats R-Bioconductor family of packages, particularly the new version MSstats v4.0, is widely used for statistical analyses of quantitative proteomic experiments. It provides improved usability, versatility, and accuracy of statistical methodology, as well as better memory use and computation speed. Empirical comparisons have demonstrated the stronger performance and better usability of MSstats v4.0 compared to existing methods.
JOURNAL OF PROTEOME RESEARCH
(2023)
Article
Biochemistry & Molecular Biology
Nicolai Bjodstrup Palstrom, Aleksandra M. Rojek, Hanne E. H. Moller, Charlotte Toftmann Hansen, Rune Matthiesen, Lars Melholt Rasmussen, Niels Abildgaard, Hans Christian Beck
Summary: Amyloidosis is a rare disease caused by the misfolding and aggregation of proteins, and accurate identification of the specific proteins is crucial for treatment choice. Mass spectrometry-based proteomics has become the preferred method for identifying the amyloidogenic protein. However, manual interpretation of the data by an expert can introduce bias. To address this, a statistical model-assisted method was developed to identify amyloid-containing biopsies and classify amyloidosis subtypes. This method successfully identified novel amyloid-associated proteins and demonstrated the unbiased and reliable classification of amyloid deposits and subtype using mass spectrometry-based data.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Chemistry, Multidisciplinary
Pin-Lian Jiang, Cong Wang, Anne Diehl, Rosa Viner, Chris Etienne, Premchendar Nandhikonda, Leigh Foster, Ryan D. Bomgarden, Fan Liu
Summary: Cross-linking mass spectrometry (XL-MS) is a useful method for studying protein structures and interactions. However, its application in vivo is limited. To address this limitation, researchers have developed a new cross-linker called tBu-PhoX and established a tBu-PhoX-based XL-MS approach. This approach allows for the identification of a large number of cross-links in intact human cells with reduced analysis time.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
(2022)
Article
Food Science & Technology
Yanchao Wang, Yaoguang Chang, Hu Hou, Jingfeng Wang, Changhu Xue
Summary: This review discusses the latest developments in proteomics technologies for solving problems in blue foods, such as traceability, quality, safety, and nutrition evaluation. It highlights the successful applications of proteomics strategies in addressing these critical issues and identifies the challenges and future development trends in the field.
TRENDS IN FOOD SCIENCE & TECHNOLOGY
(2023)
Article
Chemistry, Multidisciplinary
Florian Leonardus Rudolfus Lucas, Kumar Sarthak, Erica Mariska Lenting, David Coltan, Nieck Jordy van der Heide, Roderick Corstiaan Abraham Versloot, Aleksei Aksimentiev, Giovanni Maglia
Summary: This study enhanced the capture frequency and discrimination of peptides by introducing aromatic amino acids into nanopores. Molecular dynamics simulations identified the sensing region and microscopic mechanisms of nanopores, as well as the effects of pore modification on peptide discrimination in FraC.
Article
Multidisciplinary Sciences
Shadi Ferdosi, Behzad Tangeysh, Tristan R. Brown, Patrick A. Everley, Michael Figa, Matthew McLean, Eltaher M. Elgierari, Xiaoyan Zhao, Veder J. Garcia, Tianyu Wang, Matthew E. K. Chang, Kateryna Riedesel, Jessica Chu, Max Mahoney, Hongwei Xia, Evan S. O'Brien, Craig Stolarczyk, Damian Harris, Theodore L. Platt, Philip Ma, Martin Goldberg, Robert Langer, Mark R. Flory, Ryan Benz, Wei Tao, Juan Cruz Cuevas, Serafim Batzoglou, John E. Blume, Asim Siddiqui, Daniel Hornburg, Omid C. Farokhzad
Summary: Exploring plasma proteins on a large scale is challenging, but a multi-nanoparticle workflow proves superior to conventional methods in terms of depth and precision. The physicochemical properties and surface functionalization of nanoparticles are found to affect their selectivity for specific proteins, presenting new possibilities for designing multi-nanoparticle panels in complex biological sample analysis.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Biochemical Research Methods
Mark Ivanov, Julia A. Bubis, Vladimir Gorshkov, Daniil A. Abdrakhimov, Frank Kjeldsen, Mikhail Gorshkov
Summary: The study introduced a new fast proteomic method, DirectMS1, which, combined with machine-learning algorithm and other tools, successfully identified a large number of proteins efficiently in a short period of time.
JOURNAL OF PROTEOME RESEARCH
(2021)
Review
Biochemical Research Methods
Di Xiao, Carissa Chen, Pengyi Yang
Summary: This article reviews computational methods, tools, and systems approaches that have been developed for phosphoproteomics data analysis, categorizing them into data processing, functional analysis, phosphoproteome annotation, and integration with other omics. The article highlights potential research directions that could contribute significantly to this fast-growing field.
Article
Biochemical Research Methods
Heather C. Murray, Kasey Miller, Joshua S. Brzozowski, Richard G. S. Kahl, Nathan D. Smith, Sean J. Humphrey, Matthew D. Dun, Nicole M. Verrills
Summary: Acute myeloid leukemia (AML) is a highly aggressive form of leukemia with a poor prognosis. Mutations in kinases, such as FLT3 and KIT, are common in AML patients and are associated with treatment resistance. This study identified DNA-PK as a potential therapeutic target in AML and demonstrated that DNA-PK inhibition sensitizes AML cells with FLT3 and KIT mutations to standard treatments. The findings suggest that targeting DNA-PK could improve the outcomes of AML patients with these mutations.
MOLECULAR & CELLULAR PROTEOMICS
(2023)
Editorial Material
Multidisciplinary Sciences
Sean J. Humphrey, Elise J. Needham
Summary: A computational resource can identify candidate protein targets for a major class of kinase enzymes in humans, which is important for understanding the role of cell signaling in health and disease.
Article
Biochemical Research Methods
Jie Hao, Jiawei Zou, Jiaqiang Zhang, Ke Chen, Duojiao Wu, Wei Cao, Guoguo Shang, Jean Y. H. Yang, KongFatt Wong-Lin, Hourong Sun, Zhen Zhang, Xiangdong Wang, Wantao Chen, Xin Zou
Summary: Cell-state transition analysis using single-cell RNA-sequencing can reveal additional information in time-resolved biological phenomena. However, current methods are limited to short-term evolution of cell states based on gene expression derivative. This study presents scSTAR, a method that overcomes this limitation by constructing a paired-cell projection between different biological conditions with arbitrary time spans, leading to more accurate predictions and new discoveries in aging and cancer research.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Biochemical Research Methods
Yue Cao, Shila Ghazanfar, Pengyi Yang, Jean Yang
Summary: The advancement of scRNA-seq technology has led to its increasing use in large-scale patient cohort studies. This study evaluates the impact of analytical choices on patient outcome prediction using scRNA-seq COVID-19 datasets. The study examines the difference between single-view and multi-view feature spaces, surveys multiple learning platforms, and compares integration approaches. The results highlight the power of ensemble learning, consistency among different learning methods, and the importance of dataset normalization.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Biology
Xiaohang Fu, Ellis Patrick, Jean Y. H. Yang, David Dagan Feng, Jinman Kim
Summary: The spatial architecture and phenotypic heterogeneity of tumor cells are associated with cancer prognosis and outcomes. Imaging mass cytometry captures high-dimensional maps of disease-relevant biomarkers at single-cell resolution, which can inform patient-specific prognosis. However, existing methods for survival prediction do not utilize spatial phenotype information at the single-cell level, and there is a lack of end-to-end methods that integrate imaging data with clinical information for improved accuracy. We propose a deep multimodal graph-based network that considers spatial phenotype information and clinical variables to enhance survival prediction, and demonstrate its effectiveness in breast cancer datasets.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Biochemical Research Methods
Ellis Patrick, Nicolas P. Canete, Sourish S. Iyengar, Andrew N. Harman, Greg T. Sutherland, Pengyi Yang
Summary: Highly multiplexed in situ imaging cytometry assays enable simultaneous study of spatial organization of multiple cell types. We propose a statistical method that clusters local indicators of spatial association to quantify complex multi-cellular relationships. Our approach successfully identifies distinct tissue architectures in datasets from state-of-the-art high-parameter assays, demonstrating its value in summarizing information-rich data generated from these technologies.
Article
Biochemical Research Methods
Soren Madsen, Marin E. Nelson, Vinita Deshpande, Sean J. Humphrey, Kristen C. Cooke, Anna Howell, Alexis Diaz-Vegas, James G. Burchfield, Jacqueline Stockli, David E. James
Summary: White adipose tissue consists of subcutaneous adipose tissue (SAT) and abdominal/visceral adipose tissue, which have different molecular underpinnings. Through proteomics profiling, it was found that SAT adipocytes are geared toward higher catabolic activity, while visceral adipocytes are more suited for lipid storage. A Western diet caused significant changes in adipocyte proteomes, particularly in visceral adipocytes, indicating mitochondrial stress and adipocyte de-differentiation. The comparison between adipocytes and 3T3-L1 proteomes revealed overlap, supporting the utility of the 3T3-L1 adipocyte model.
MOLECULAR & CELLULAR PROTEOMICS
(2023)
Article
Biochemistry & Molecular Biology
Chunlei Liu, Hao Huang, Pengyi Yang
Summary: Multimodal single-cell omics technologies allow for simultaneous profiling of multiple molecular programs in individual cells, providing a new level of resolution for studying biological systems. However, integrating and analyzing multimodal single-cell omics data presents challenges due to the lack of suitable methods. In this study, we propose Matilda, a multi-task learning method that can perform data simulation, dimension reduction, cell type classification, and feature selection in a unified framework. We compare Matilda with other state-of-the-art methods using datasets from popular multimodal single-cell omics technologies, and show its utility in addressing multiple key tasks in integrative analysis.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Multidisciplinary Sciences
Daniel J. Fazakerley, Julian van Gerwen, Kristen C. Cooke, Xiaowen Duan, Elise J. Needham, Alexis Diaz-Vegas, Soren Madsen, Dougall M. Norris, Amber S. Shun-Shion, James R. Krycer, James G. Burchfield, Pengyi Yang, Mark R. Wade, Joseph T. Brozinick, David E. James, Sean J. Humphrey
Summary: The failure of metabolic tissues to respond to insulin is an early marker of type 2 diabetes. Using global phosphoproteomics, the authors demonstrate that insulin resistance is caused by a significant rewiring of insulin signaling pathways, leading to dysregulated GSK3 activity. Dysregulation of protein phosphorylation plays a crucial role in adipocyte insulin response and insulin resistance. Through phosphoproteomics, the researchers reveal a marked rewiring of the insulin signaling network and identify common dysregulated phosphosites and subnetworks that contribute to insulin resistance, including non-canonical regulators MARK2/3 and GSK3. Inhibition of GSK3 partially reverses insulin resistance in cells and tissue explants.
NATURE COMMUNICATIONS
(2023)
Article
Biochemical Research Methods
Taiyun Kim, Hani Jieun Kim, Andrew J. Oldfield, Pengyi Yang
Summary: This article introduces a protocol for utilizing PAD2, an interactive web application, to investigate the colocalization of various transcription factors and chromatin-regulating proteins in mouse embryonic stem cells. The protocol includes steps for accessing and searching the PAD2 database, selecting and submitting genomic regions, and conducting protein colocalization analysis using heatmap and ranked correlation plot.
Review
Mathematical & Computational Biology
Daniel Kim, Andy Tran, Hani Jieun Kim, Yingxin Lin, Jean Yee Hwa Yang, Pengyi Yang
Summary: Inferring gene regulatory networks is crucial in biology, and recent advances in sequencing technology have led to the development of state-of-the-art methods that utilize single-cell multi-omic data for more comprehensive and precise network reconstruction.
NPJ SYSTEMS BIOLOGY AND APPLICATIONS
(2023)