Non-adaptive Evolution of Trimeric Autotransporters in Brucellaceae

Front Microbiol. 2020 Nov 12:11:560667. doi: 10.3389/fmicb.2020.560667. eCollection 2020.

Abstract

Brucella species are Gram-negative, facultative intracellular pathogens. They are the main cause of brucellosis, which has led to a global health burden. Adherence of the pathogen to the host cells is the first step in the infection process. The bacteria can adhere to various biotic and abiotic surfaces using their outer membrane proteins. Trimeric autotransporter adhesins (TAAs) are modular homotrimers of various length and domain complexity. They are a diverse, and widespread gene family constituting the type Vc secretion pathway. These adhesins have been established as virulence factors in Brucellaceae. To date, no comprehensive and exhaustive study has been performed on the trimeric autotransporter family in the genus. In the present study, various bioinformatics tools were used to provide a novel evolutionary insight into the sequence and structure of this protein family in Brucellaceae. To this end, a dataset of all trimeric autotransporters from the Brucella genomes was built. Analyses included but were not limited to sequence alignment, phylogenetic tree constructions, codon-based test for selection, clustering of the sequences, and structure (primary to quaternary) predictions. Batch analyzes of the dataset suggested the existence of a few structural domains within the whole population. BatA from the B. abortus 2308 genome was selected as a reference to describe the features of these structural domains. Furthermore, we examined the structural basis for the observed rigidity and resiliency of the protein structure through a molecular dynamics evaluation, which led us to deduce that the random drift results in the non-adaptive evolution of the trimeric autotransporter genes in the Brucella genus. Notably, the modifications have occurred across the genus without interference of gene transmission.

Keywords: BatA; Brucellaceae; TAA; adhesin; bioinformatics; in silico.