Ongoing improvements in instrumentation, fractionation techniques, and enrichment procedures have dramatically increased the coverage of the proteome achievable via LC-MS/MS-based methodologies, opening the call for approaches to quantitatively assess differences at a proteome-wide scale. Stable isotope labeling by amino acids in cell culture (SILAC) has emerged as a powerful and versatile approach for proteome-wide quantitation by mass spectrometry. SILAC utilizes the cells' own metabolism to incorporate isotopically labeled amino acids into its proteome which can be mixed with the proteome of unlabeled cells and differences in protein expression can easily be read out by comparing the abundance of the labeled versus unlabeled proteins. SILAC has been applied to numerous different cell lines and the technique has been adapted for a wide range of experimental procedures. In this chapter we provide detailed procedure for performing SILAC-based experiment for proteome-wide quantitation, including a protocol for optimizing SILAC labeling. We also provide an update on the most recent developments of this technique.
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Am J Hum Genet
January 2025
Division of Biostatistics and Health Data Science, University of Minnesota, Minneapolis, MN, USA. Electronic address:
Alzheimer disease (AD) is a complex and progressive neurodegenerative disorder that accounts for the majority of individuals with dementia. Here, we aim to identify causal plasma proteins for AD, shedding light on the etiology of AD. We utilized the latest large-scale plasma proteomic data from the UK Biobank Pharma Proteomics Project (UKB-PPP) and AD genome-wide association study (GWAS) summary data from the International Genomics of Alzheimer's Project (IGAP).
View Article and Find Full Text PDFNat Hum Behav
January 2025
Department of Psychosomatics and Psychiatry, Zhongda Hospital, School of Medicine, Jiangsu Provincial Key Laboratory of Brain Science and Medicine, Advanced Institute for Life and Health, Southeast University, Nanjing, China.
Genome-wide association studies (GWASs) have reported multiple risk loci for schizophrenia (SCZ). However, the majority of the associations were from populations of European ancestry. Here we conducted a large-scale GWAS in Eastern Asian populations (29,519 cases and 44,392 controls) and identified ten Eastern Asian-specific risk loci, two of which have not been previously reported.
View Article and Find Full Text PDFInt J Womens Health
December 2024
Department of Gynecologic Oncology, Obstetrics and Gynecology Hospital, Fudan University, Shanghai, 200011, People's Republic of China.
Background: Epithelial ovarian cancer (EOC) remains an unmet medical challenge due to its insidious onset, atypical symptoms, and increasing resistance to conventional chemotherapeutic agents. It is imperative to explore novel biomarkers and generate innovative target drugs.
Methods: To identify potential proteins with causal association to EOC subtypes, we conducted a Mendelian Randomization (MR) analysis using 15,419 protein quantitative trait loci (pQTLs) associated with 2015 proteins.
Front Microbiol
December 2024
Department of Biochemistry and Microbiology, University of Victoria, Victoria, BC, Canada.
Introduction: Strains of the syphilis spirochete, ssp. , group into one of two deep-branching clades: the Nichols clade or the globally dominant Street Strain 14 (SS14) clade. To date, in-depth proteome-wide analyses have focused on Nichols clade strains.
View Article and Find Full Text PDFCommun Biol
December 2024
Department of Computational Diagnostic Radiology and Preventive Medicine, The University of Tokyo Hospital, Tokyo, Japan.
Skin cancer is one of the most common cancers worldwide. Some risk factors including sun exposure and MC1R variants are recognized; however, the identification of additional genetic factors is essential for the development of novel therapeutic strategies. Here, we conducted a proteome-wide Mendelian randomization (MR) using plasma protein quantitative trait loci (pQTLs) from a published study and the UK Biobank genome-wide association study (GWAS) of skin cancers.
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