calculateProportionOfMitochondrialProteins: Calculate contribution of mitochondrial proteins

In tnaake/apoptosisQuantification: Assessment of apoptosis and necroptosus unsing proteomics

Description

Apoptotic cells show an increase in the proportion of gene expression which originates from the mitochondria, which occurs after the opening of the MPT pore as apoptosis begins. This gradually results in a decrease in the total expression of chromosomal genes as the DNA is degraded. In late apoptosis, there is typically a drastically reduced total count of genes in a cell, with a large proportion of the gene expression stemming from mitochondria.

For transcriptomics, typically, at a threshold of where 10-20 transcripts are mitochondrial in origin, the total number of transcripts drops substantially (<20

The function calculateProportionOfMitochondrialProteins calculates proportions of the intensities of mitochondrial proteins (i.e. proteins that are encoded in the mitochondrial DNA) to all intensities. The function returns the proportions in percent.

Mitochondrial proteins are defined by the Human Protein Atlas (1139 proteins found by searching the Human Protein Atlas database for mitochondrial sublocalization). These proteins are matched against the proteins found in values. Currently, two types of ids are encoded: either rownames(values) have to be "Symbol" or "Ensembl" ids.

Usage

calculateProportionOfMitochondrialProteins(values, id = c("Symbol", "Ensembl"))

Arguments

values	matrix, data.frame, or tibble
id	character(1), either "Symbol" or "Ensembl"

Details

Protein intensities have to in untransformed format such that proportions can be calculated as are.

Protein ids are stored in rownames(values). In case of multiple assignments the ids are separeted by ";". In that case, a feature will be treated as of mitochondrial origin when there is at least one mitochondrial protein in the multiple assignment.

Value

numeric vector

References

The Human Protein Atlas (search: subcell_location:Mitochondria, https://www.proteinatlas.org/humanproteome/subcellular/mitochondria, accessed January 31, 2022).

Uhlen et al. (2015): Tissue-based map of the human proteome. Science, 347, 1260419. 10.1126/science.1260419

Thul et al. (2017): A subcellular map of the human proteome. Science, 356, eaal3321. 10.1126/science.aal3321

Examples

set.seed(2022) 
## fake measured protein intensities and create matrix that stores 
## intensities
prot_vals <- runif(1000, min = 10000, max = 1000000)
prot <- matrix(prot_vals, ncol = 10, nrow = 100)

## fake some protein names and sample names
rownames(prot) <- paste("prot", seq_len(nrow(prot)), sep = "_")
colnames(prot) <- paste("sample", seq_len(ncol(prot)), sep = "_")

## randomly assign 10 mitochondrial proteins to the matrix
inds_mito <- sample(seq_len(nrow(prot)), 10)
prot_mito <- c("MDH2", "OMA1", "NLN", "CS", "OPA1", "CSPG5", "SPATA9", 
    "POLG", "RAB38", "NSD3")
rownames(prot)[inds_mito] <- prot_mito

calculateProportionOfMitochondrialProteins(values = prot, id = "Symbol")

tnaake/apoptosisQuantification documentation built on Feb. 20, 2022, 5:37 p.m.