Article
Biochemical Research Methods
Marc Isaksson, Christofer Karlsson, Thomas Laurell, Agnete Kirkeby, Moritz Heusel
Summary: Data-independent acquisition-mass spectrometry (DIA-MS) is the method of choice for deep, consistent, and accurate single-shot profiling in bottom-up proteomics. Library-free approaches based on in silico prediction promise deep DIA-MS profiling with reduced experimental effort and cost, but coverage and sensitivity in such analyses are limited.
JOURNAL OF PROTEOME RESEARCH
(2022)
Article
Biochemistry & Molecular Biology
Douglas Ricardo Souza Junior, Amanda Ribeiro Martins Silva, Graziella Eliza Ronsein
Summary: The introduction of mass spectrometry-based proteomics has greatly impacted the study of high-density lipoprotein (HDL) by identifying and characterizing HDL-associated proteins involved in various pathologies. However, obtaining reliable and reproducible data for HDL proteomics remains a challenge. In this study, a pipeline was developed to standardize quantification of HDL proteome. Data-independent acquisition (DIA) was used, and the performance of four freely available software was compared for data analysis. Precision, linearity, and detection limits were evaluated using E. coli background and synthetic peptides. The results showed that precision is crucial for confidently quantifying HDL proteins.
JOURNAL OF LIPID RESEARCH
(2023)
Article
Chemistry, Analytical
Eva Borras, Olga Pastor, Eduard Sabido
Summary: The use of linear ion traps mass analyzers in data-independent acquisition methods can boost peptide and protein identifications in low-input proteomes.
ANALYTICAL CHEMISTRY
(2021)
Review
Spectroscopy
Reta Birhanu Kitata, Jhih-Ci Yang, Yu-Ju Chen
Summary: Data-independent acquisition mass spectrometry (DIA-MS) is a highly reproducible proteome profiling method that generates permanent digital maps for retrospective analysis. Recent advancements have improved the sensitivity and coverage of DIA-MS. This review discusses the evolution of DIA-MS techniques, recent applications, and challenges.
MASS SPECTROMETRY REVIEWS
(2023)
Article
Biochemical Research Methods
Leon Bichmann, Shubham Gupta, George Rosenberger, Leon Kuchenbecker, Timo Sachsenberg, Phil Ewels, Oliver Alka, Julianus Pfeuffer, Oliver Kohlbacher, Hannes Rost
Summary: DIA is a leading analysis method in biomedical mass spectrometry with advantages such as reproducibility and sensitivity, but its data analysis complexity requires expert knowledge. DIAproteomics is a multifunctional, automated pipeline that allows easy processing of DIA datasets.
JOURNAL OF PROTEOME RESEARCH
(2021)
Article
Biology
Matthias Fahrner, Melanie Christine Foll, Bjorn Andreas Gruning, Matthias Bernt, Hannes Rost, Oliver Schilling
Summary: The integration of an open-source DIA analysis suite in the web-based and user-friendly Galaxy framework, along with comprehensive training materials, enables a wide community of researchers to perform reproducible and transparent DIA data analysis.
Article
Biochemical Research Methods
Zainab Noor, Selvam Paramasivan, Priya Ghodasara, Saul Chemonges, Rajesh Gupta, Steven Kopp, Paul C. Mills, Shoba Ranganathan, Nana Satake, Pawel Sadowski
Summary: Blood plasma is a rich source of proteins for biomarker studies, and mass spectrometry can quantitate hundreds of proteins in non-depleted plasma; current limitations in using SWATH for non-laboratory animals include lack of comprehensively annotated genomes. A study established plasma peptide spectral repositories for sheep and cattle, enabling quantification of over 200 proteins.
JOURNAL OF PROTEOMICS
(2022)
Article
Biochemical Research Methods
Lindsay K. Pino, Josue Baeza, Richard Lauman, Birgit Schilling, Benjamin A. Garcia
Summary: The study presents a workflow combining SILAC and DIA-MS using free software, showing that DIA achieves similar peptide detection numbers as DDA but with improved quantitative accuracy and precision for SILAC by an order of magnitude. Application of SILAC-DIA-MS to determine protein turnover rates reveals more sensitive protein turnover models and identifies known proteins degraded by the ubiquitinproteasome pathway, as well as proteins with slower turnover rates implicated in invasive breast cancer. The improved quantification from DIA is expected to make SILAC-based experiments like protein turnover more sensitive.
JOURNAL OF PROTEOME RESEARCH
(2021)
Article
Biochemical Research Methods
Carolyn Allen, Rico Meinl, J. Sebastian Paez, Brian C. Searle, Seth Just, Lindsay K. Pino, William E. Fondrie
Summary: This study presents an open-source NextFlow pipeline, nf-encyclopedia, which connects three open-source tools (MSConvert, EncyclopeDIA, and MSstats) for analyzing DIA proteomics experiments with or without chromatogram libraries. The pipeline is reproducible and provides robust peptide and protein quantification. MSstats improves protein-level quantification performance over EncyclopeDIA alone.
JOURNAL OF PROTEOME RESEARCH
(2023)
Article
Biochemical Research Methods
Masaki Ishikawa, Ryo Konno, Daisuke Nakajima, Mari Gotoh, Keiko Fukasawa, Hironori Sato, Ren Nakamura, Osamu Ohara, Yusuke Kawashima
Summary: In this study, an ultrafast proteomic method was established using a 5-min gradient LC and quadrupole-Orbitrap MS. By optimizing parameters, the method achieved a high throughput and sensitivity for measuring a large number of samples. The method was demonstrated to be applicable for chemical responsivity screening.
JOURNAL OF PROTEOME RESEARCH
(2022)
Article
Biochemical Research Methods
Kyung-Cho Cho, Sungtaek Oh, Yuefan Wang, Liana S. Rosenthal, Chan Hyun Na, Hui Zhang
Summary: This study demonstrates that DIA-MS can successfully identify and quantify a large number of proteins in CSF and serum samples, with high sensitivity, linearity, and reproducibility. DIA-MS shows great potential as a targeted proteomic analysis tool for candidate proteins from biological fluids.
JOURNAL OF PROTEOME RESEARCH
(2021)
Article
Biochemical Research Methods
Debora A. . Lima, Rodrigo A. . Schuch, Jessica S. Salgueiro, Maria Carolina T. Pintao, Valdemir M. Carvalho
Summary: Combining Data-independent acquisition (DIA) with volumetric absorptive microsampling (VAMS) and automated proteomics sample processing can be used to assess clinical markers, but there are still issues with method imprecision in some biomarkers.
JOURNAL OF PROTEOME RESEARCH
(2022)
Article
Oncology
Yaoting Sun, Lu Li, Yan Zhou, Weigang Ge, He Wang, Runxin Wu, Wei Liu, Hao Chen, Qi Xiao, Xue Cai, Zhen Dong, Fangfei Zhang, Junhong Xiao, Guangzhi Wang, Yi He, Jinlong Gao, Oi Lian Kon, Narayanan Gopalakrishna Iyer, Haixia Guan, Xiaodong Teng, Yi Zhu, Yongfu Zhao, Tiannan Guo
Summary: Thyroid nodules are common in about 60% of the population. Differentiating between follicular adenoma (FA) and carcinoma (FTC) is a challenge in thyroid nodule diagnosis. This study presents a comprehensive thyroid spectral library and identifies nine proteins that could potentially distinguish FA and FTC.
MOLECULAR ONCOLOGY
(2022)
Article
Biochemical Research Methods
Yue Zhou, Zengqi Tan, Peng Xue, Yi Wang, Xiang Li, Feng Guan
Summary: A novel data-independent acquisition (DIA)/MS-based workflow was developed for high-throughput, in-depth, and estimated absolute quantification of plasma proteins. The approach demonstrated high quantification accuracy and was successfully applied to a myelodysplastic syndromes (MDS) disease cohort, discovering 95 differentially expressed proteins providing insights into MDS pathophysiology.
Article
Biochemistry & Molecular Biology
Franjo Martinkovic, Marin Popovic, Ozren Smolec, Vladimir Mrljak, Peter David Eckersall, Anita Horvatic
Summary: Comprehensive profiling of serum proteome using DIA-MS method was applied to analyze non-depleted serum samples of healthy and naturally Leishmania-infected dogs, resulting in the identification of 554 proteins, 140 of which showed significant differences in abundance. These proteins are involved in lipid metabolism, hematological abnormalities, immune response, and oxidative stress, providing valuable insights into the complex molecular basis of canine leishmaniosis. Our study demonstrates that DIA-MS is a preferred method for understanding pathophysiological processes in serum and biomarker development.
