# Tracking Down the Evolution of Microorganisms by Exhaustive Bottom-Up Analysis of Proteomes

## TL;DR

This study introduces a new method to analyze proteomes by examining k-mer frequencies, revealing strong correlations with evolutionary relationships among bacteria.

## Contribution

The study introduces a bottom-up proteomic analysis method using k-mer frequencies to trace microbial evolution.

## Key findings

- K-mer frequency vectors coevolve unambiguously with entire proteomes.
- Tripeptide frequency analysis can precisely position proteomes in k-mer space.
- K-mer-based comparisons correlate up to 99% with phylogenetic classifications.

## Abstract

Proteomes are typically analyzed at the level of individual proteins or protein families. In this study, we introduce a bottom-up approach that treats proteomes as holistic entities by examining the properties of k-mers within entire proteomes and protein groups. We performed a comprehensive analysis of short amino acid k-mer (k = 1, 2, 3) distributions across all proteins in a given proteome. Using 86 bacterial proteomes representing 18 clades, we evaluated whether k-mer frequencies characterize uniquely the analyzed organisms. Remarkably, in a post hoc analysis, we found that the k-mer frequency vector unambiguously coevolves with the entire proteome—a pattern not observed even within specific protein groups, such as conserved ribosomal proteins or more variable nucleotide-binding proteins. This finding holds regardless of the k-mer calculation parameters or the distance metrics employed. Our results show that even a simple analysis based on tripeptide frequencies can precisely position proteomes within the k-mer space. Moreover, relationships derived from k-mer comparisons highly correlate with evolutionary relationships derived from phylogenetic trees, reaching up to 99% match with reference classification of the proteomes within major bacterial clades. These findings establish k-mer-based proteomic analysis as an additional robust and powerful feature for characterizing evolutionary relationships, opening new pathways in phylogenetics and evolutionary genomics.