Bioinformatic Analysis of the Perilymph Proteome to Generate a Human Protein Atlas

Abstract

The high complexity of the cellular architecture of the human inner ear and the inaccessibility for tissue biopsy hampers cellular and molecular analysis of inner ear disease. Sampling and analysis of perilymph may present an opportunity for improved diagnostics and understanding of human inner ear pathology. Analysis of the perilymph proteome from patients undergoing cochlear implantation was carried out revealing a multitude of proteins and patterns of protein composition that may enable characterisation of patients into subgroups. Based on existing data and databases, single proteins that are not present in the blood circulation were related to cells within the cochlea to allow prediction of which cells contribute to the individual perilymph proteome of the patients. Based on the results, we propose a human atlas of the cochlea. Finally, druggable targets within the perilymph proteome were identified. Understanding and modulating the human perilymph proteome will enable novel avenues to improve diagnosis and treatment of inner ear diseases.

Keywords: bioinformatics; cochlea; hearing loss; hereditary inner ear disease; perilymph; proteome.

FIGURE 1

(A) Principle component analysis of proteins. Six individuals marked with triangles are grouped by the levels of protein expression (principle components) using Qlucore Omics Explorer. (B) Heatmap. This heatmap shows how the protein expression pattern of the six individuals identified in A differs from the other patients. White lines indicate the six grouped individuals. Red colour indication increased expression and blue colour reduced expression levels.

FIGURE 2

Druggability status of the 203 tissue-specific proteins. Based on Pharos, targets are divided into four categories. Of all tissue specific proteins, 5% were identified as targets for clinically approved drugs. For 15% of the proteins, active ligands (Tchem) were identified. Seventy six percent of perilymph proteins have an identifiable gene ontology and can be functionally classified but do not have available inhibitors (Tbio). Finally, a small percentage of identified proteins are unclassified (Tdark).

FIGURE 3

Functional distribution of the 203 proteins classified as tissue-specific after comparison with blood and CSF samples taken from four patients. The most common functional groups among the proteins were “enzyme modulator,” “nucleic acid binding,” “transferase,” “cytoskeletal protein” and “protease.”

FIGURE 4

A human cochlear atlas of proteins. Schematic drawing of the human organ of Corti, lateral wall and spiral ganglion showing the complex cellular architecture of the cochlea. Individual proteins were classified into functional groups and assigned to their putative cell source.