Dataset Information

Sample multiplexing-based targeted pathway proteomics with real-time analytics reveals the impact of genetic variation on protein expression

ABSTRACT: Targeted proteomics plays a specialized role in hypothesis-driven research where the expression of cohorts of dozens of proteins related by function, disease, co-expression, localization, or class are measured after perturbing a pathway. Moreover, a major advance in proteomics is the ability to combine many samples (up to 16) for simultaneous quantification using tandem mass tag (TMT) reagents. Here we present a pathway-centric approach for targeting protein lists selected from up to 10,000 expressed proteins to directly measure their abundances, exploiting sample multiplexing to increase throughput. The strategy, termed GoDig, requires only a single-shot LC-MS analysis, ~1 µg combined peptide material, and real-time analytics to trigger simultaneous quantification of up to 16 samples for hundreds of analytes. We applied GoDig to investigate the impact of genetic variation on protein expression in mice fed a Western-style diet high in fat and sucrose. For selected sets of proteins of interest (e.g., kinases, lipid metabolism- and lipid droplet-associated proteins), protein abundances from mouse livers from 480 fully genotyped Diversity Outbred mice were profiled. The results revealed previously unknown protein quantitative trait loci (QTL) and established potential linkages between specific proteins and lipid homeostasis. In all, GoDig provides an integrated solution for next-generation targeted pathway proteomics.

INSTRUMENT(S): Orbitrap Eclipse

ORGANISM(S): Mus Musculus (mouse)

TISSUE(S): Hepatocyte

SUBMITTER: Qing Yu

LAB HEAD: Steven Gygi

PROVIDER: PXD033679 | Pride | 2023-03-11

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	536514_ec04104_qy_aml12_gm4951_KD60h_OA30h_Rep1_B5.mzIdentML	Mzid
	536515_ec04103_qy_aml12_gm4951_KD60h_OA30h_Rep1_B3.mzIdentML	Mzid
	536516_ec04102_qy_aml12_gm4951_KD60h_OA30h_Rep1_B1.mzIdentML	Mzid
	536517_ec04101_qy_aml12_gm4951_KD60h_OA30h_Rep1_A11.mzIdentML	Mzid
	536518_ec04100_qy_aml12_gm4951_KD60h_OA30h_Rep1_A9.mzIdentML	Mzid

Items per page:

1 - 5 of 73

Publications

Sample multiplexing-based targeted pathway proteomics with real-time analytics reveals the impact of genetic variation on protein expression.

Yu Qing Q Liu Xinyue X Keller Mark P MP Navarrete-Perea Jose J Zhang Tian T Fu Sipei S Vaites Laura P LP Shuken Steven R SR Schmid Ernst E Keele Gregory R GR Li Jiaming J Huttlin Edward L EL Rashan Edrees H EH Simcox Judith J Churchill Gary A GA Schweppe Devin K DK Attie Alan D AD Paulo Joao A JA Gygi Steven P SP

Nature communications 20230202 1

Targeted proteomics enables hypothesis-driven research by measuring the cellular expression of protein cohorts related by function, disease, or class after perturbation. Here, we present a pathway-centric approach and an assay builder resource for targeting entire pathways of up to 200 proteins selected from >10,000 expressed proteins to directly measure their abundances, exploiting sample multiplexing to increase throughput by 16-fold. The strategy, termed GoDig, requires only a single-shot LC- ...[more]

PMID: 36732331

Similar Datasets

Project description:Genome-wide expression and methylation profiling identifies novel targets with aberrant hypermethylation and reduced expression in low-risk myelodysplastic syndromes (MDSs). Gene expression profiling signatures may be used to classify the subtypes of Myelodysplastic syndrome (MDS) patients. However, there are few reports on the global methylation status in MDS. The integration of genome-wide epigenetic regulatory marks with gene expression levels would provide additional information regarding the biological differences between MDS and healthy controls. Gene expression and methylation status were measured using high-density microarrays. A total of 552 differentially methylated CpG loci were identified as being present in low-risk MDS; hypermethylated genes were more frequent than hypomethylated genes. In addition, mRNA expression profiling identified 1005 genes that significantly differed between low-risk MDS and the control group. Integrative analysis of the epigenetic and expression profiles revealed that 66.7% of the hypermethylated genes were underexpressed in low-risk MDS cases. Gene network analysis revealed molecular mechanisms associated with the low-risk MDS group, including altered apoptosis pathways. The two key apoptotic genes BCL2 and ETS1 were identified as silenced genes. In addition, the immune response and micro RNA biogenesis were affected by the hypermethylation and underexpression of IL27RA and DICER1. Our integrative analysis revealed that aberrant epigenetic regulation is a hallmark of low-risk MDS patients and could have a central role in these diseases. Low-risk MDS patients and age-matched controls without haematological malignancies were included in the study. Mononuclear cells were isolated from bone marrow samples of low-risk MDS patients and controls by density gradient (Ficoll). A cohort of 18 patients with low-risk MDS and seven controls were included in a simultaneous integrative study of methylation (using Methylated CpG Island Amplification and Microarrays, MCAM) and expression (using Affymetrix microarrays HG-U133 Plus 2), while the whole series was used as a control group of expression data.

Project description:The liver is a major site for synthesis, storage and redistribution of carbohydrates, proteins and lipids. In addition, it is well-known that maternal obesity (MO) increases risk of offspring cardiovascular disease (CVD), diabetes and obesity. However, the mechanisms by which the MO intrauterine environment predisposes offspring to CVD and metabolic dysregulation are unknown. The goal of this study was to assess the impact of MO on primate fetal liver and identify underlying molecular mechanisms by which MO increases disease risk. The goal of this study was to identify candidate molecular mechanisms underlying MO in the near-term NHP fetal liver. This is the first study of NHP fetal MO livers using unbiased transcriptome analysis to quantify hepatic gene expression, identify dysregulated signaling pathways and potential miRNAs regulating the disrupted metabolic processes. Unbiased gene (arrays) and microRNA (miRNA; small RNA-Seq) abundances were quantified in near-term (0.9 Gestation (0.9G)) baboon fetal livers (control (CON) = 6; MO = 5) and subjected to pathway and network analyses (GeneSifter, Ingenuity® Pathway Analysis (IPA)) to identify a coordinated molecular response to MO. Lipid and glycogen content (CON = 16; MO = 16) were quantified by Computer Assisted Stereology Toolbox (CAST) in 0.9G livers.Pairwise comparisons showed 933 differentially expressed genes between CON and MO livers: 350 genes were upregulated and 583 were downregulated. Pathway analysis revealed upregulation of Wnt/β-catenin signaling and downregulation of tricarboxylic acid (TCA) cycle, proteasome, oxidative phosphorylation and glycolysis pathways in MO fetal livers compared with CON. Inversely expressed miRNAs that target genes in these pathways provide additional support for the importance of these pathways in fetal liver metabolic regulation. Consistent with the observed pathway changes in MO, we found hepatic lipid content was threefold greater in MO than CON fetal livers (p=0.02). Molecular genetic analyses of CON and MO fetal baboon livers revealed dysregulation of Wnt/β-catenin signaling, TCA cycle, proteasome, oxidative phosphorylation and glycolysis pathways in MO livers, all of which are central to fatty acid metabolism and lipid storage. The marked lipid accumulation in MO fetal livers supports our hypothesis that dysregulation of these pathways detrimentally impacts lipid management. Furthermore, our findings demonstrate the detrimental impact of MO on fetal liver development and suggest impaired hepatic function prior to birth.