Dataset Information

Mini-Complexome Profiling, an FDR-controlled workflow for global targeted Detection of protein complexes (Hek293 data)

ABSTRACT: Co-fractionation mass spectrometry experiments (CF-MS) using native-like protein separations such as Blue Native electrophoresis (BNE) or size exclusion chromatography (SEC) enable a global characterization of protein networks, and a better understanding of cellular functions. They do, however, pose significant requirements on sample amounts, on wet lab and on instrument time, which frequently renders statistically useful replication or comparative experiments between multiple biological states non-feasible. Here we present a fast workflow called mini-Complexome Profiling (mCP) for global targeted detection of annotated protein-protein complexes. It comprises mild extraction of complexes, fractionation by BNE and analysis by data independent acquisition mass spectrometry (DIA-MS). Of note, BNE fractionation into 35 fractions is achieved using commercial mini-gels, with minimal requirements on sample amounts. Complexes are detected using a novel, bespoke R package with a controlled false discovery rate (FDR) approach. The tool is available to the community on a Github repository (https://github.com/hugoagno3/mCP ). We first benchmarked our workflow using Hek293 cell lysates as a well established cell line model. We then challenged mCP by investigating changes in the complexome of mouse cardiomyocytes isolated from different heart cavities of single mice. In these challenging and limited samples we detected 48 annotated protein complexes per compartment on average and were able to perform differential inter-cavity comparisons from single animals. These reduced sample and instrument time requirements suggest the suitability of our workflow for complexome screening in sparse samples, e.g. in human patient biopsies.

INSTRUMENT(S): timsTOF Pro 2

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Kidney Cell

SUBMITTER: Christof Lenz

LAB HEAD: Christof Lenz

PROVIDER: PXD049340 | Pride | 2024-07-25

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	20220117_UP_Reference_HOMSA_79038_Entries.fasta	Fasta
	DIANN_Search_Hek293_P1.zip.zip	Other
	DIANN_Search_Hek293_P2.zip.zip	Other
	H_Amedei_021122_P31_HEK293_P1_1_A_01_GA1_1_6389.d.zip	Other
	H_Amedei_021122_P31_HEK293_P1_1_A_02_GA2_1_6390.d.zip	Other

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Project description:Background: Phospholamban (PLN) is a tail-anchored sarco-endoplasmic reticulum (SER) membrane protein that regulates cardiac contraction/relaxation by reversibly inhibiting the SERCA2a Ca2+ 36 -reuptake pump. The R14Δ-PLN mutation causes severe cardiomyopathy that is resistant to conventional treatment. Multi-protein complexes and higher-order supercomplexes, such as intercalated disk components and SER Ca+2 -cycling domains, underlie many critical cardiac functions, a subset of which may be disrupted by R14∆-PLN. Complexome profiling (CP) is a systems biology approach to characterize high molecular weight (MW) assemblies in biological samples. Most current CP data analysis strategies rely on external protein42 complex databases that are predominantly curated from immortalized or cancerous cell lines; thus, assemblies unique to specialized cell types such as cardiomyocytes, as well as higher-order supercomplexes that may have fluid stoichiometry/composition are significantly underrepresented. The requirement for computer programming expertise also presents a barrier to generalized adoption. Methods: We developed and applied a novel CP workflow to identify protein-complexes/supercomplexes disrupted in presymptomatic 28wk-old R14Δ/+ knockin mice hearts. Cardiac tissues were homogenized under non-denaturing conditions, fractionated by size-exclusion chromatography (SEC) and subjected to quantitative data-independent acquisition mass spectrometry (DIA-MS)-based proteomics analysis. As expected, traditional database-dependent analysis offered only limited insights due to underrepresentation of cardiac-specific assemblies and higher-order supercomplexes. We thus developed a novel data analysis strategy (PERCOM) that does not rely upon external protein-complex databases and can, furthermore, be implemented on widely available spreadsheet software. Results: SEC-DIA-MS coupled with PERCOM analysis identified 296 proteins with disrupted MW-distribution profiles. Hits were significantly enriched for mitochondrial and intercalated disk (ICD) components. Mitochondrial alterations were confirmed at the level of global protein expression and metabolic function. Disruption of mitochondrial and ICD supercomplexes was confirmed in mice as young as 9wks of age. Conclusion: We present a novel CP workflow that is highly suited to the analysis of very high MW protein-complexes and supercomplexes in specialized tissue types. It includes a data analysis strategy that removes a computer programming resource barrier to general application. Our findings are among the first to show altered mitochondrial function as a hallmark of early-stage R14Δ-PLN, and identify disruption of the intercalated disk as a novel potential disease pathway. These molecular-level alterations target key machinery underlying cardiac energy generation and electromechanical connectivity, and may significantly contribute to the R14∆-PLN pathogenesis.

Dataset Information

Mini-Complexome Profiling, an FDR-controlled workflow for global targeted Detection of protein complexes (Hek293 data)

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