PHYLOGENOMIC AND MOLECULAR SIGNATURE-BASED APPROACHES FOR RESOLVING THE EVOLUTIONARY RELATIONSHIPS AMONG PSEUDOMONAS SPECIES

Abstract

The genus Pseudomonas includes genetically diverse groups of species that do not share a common evolutionary history. My research focused on analyzing the genome sequences of different Pseudomonas species to robustly elucidate their evolutionary relationships using multiple independent approaches, which include: (i) Construction of phylogenetic trees based on several large data sets of conserved proteins, and 16S rRNA gene sequences (ii) Determination of pairwise genomic similarities based on AAI and POCP matrices, (iii) Identification of molecular markers such as Conserved Signature Indels (CSIs) and Conserved Signature Proteins (CSPs), specific for different Pseudomonas species clades supported by other methods. Our Phylogenomic analyses revealed three major lineages/groups within Pseudomonas: Aeruginosa, Fluorescens, and Pertucinogena. While the Aeruginosa and Fluorescens lineages include multiple distinct clades, no molecular or biochemical traits were previously known to differentiate them. Our analyses identified >160 CSIs specific to these clades/groups, providing molecular means for their reliable demarcation. Based on phylogenomic evidence, AAI and POCP values, and clade-specific CSIs, we proposed restricting the genus Pseudomonas only to the Aeruginosa clade of species. Prior to this, based on our analyses, we reclassified the Pertucinogena lineage of species as a novel genus, Halopseudomonas, and reclassified several misclassified species into their related genera. Further analyses led to the reclassification of the Aeruginosa lineage of species into 12 novel and emended genera. Ongoing studies on the Fluorescens lineage, comprising 13 clades, have identified CSIs for several of them. Additionally, our studies led to the discovery of a novel species, Pseudomonas paraeruginosa. The resulting CSI-based phylogenetic framework offers a stable, predictive system for classifying new or uncharacterized Pseudomonas species. Using the predictive ability of CSIs, we predicted assigning ~300 uncharacterized strains into 14 Pseudomonadaceae genera. Besides systematic studies, these conserved markers hold promise for diagnostic applications and deeper insights into microbial evolution and function.