Phylogroup Homeostasis of <i>Escherichia coli</i> in the Human Gut Reflects the Physiological State of the Host

The development of alignment-free approaches using short k-mers as barcodes has revo-lutionized taxonomic analysis, enabling bacterial identification at the phylogroup level even within natural communities. We applied this approach to characterize Escherichia coli intraspecific diversity in human gut microbiomes using publicly available datasets. By estimating the relative abundance of eight E. coli phylogroups defined by their 18-mer markers in 558 fecal samples, we employed correlation analysis and machine learning techniques to assess the discriminatory power of their patterns under different host phys-iological states. We compared E. coli phylogroup distribution between microbiomes of healthy individuals and patients with chronic colorectal disorders, tracked their dynamic alterations following prolonged antibiotic exposure with subsequent probiotic-assisted recovery, and evaluated changes induced by a physiologically beneficial dietary interven-tion for obesity. As a result, binary classification methods distinguished most compared datasets, while correlation analysis revealed shifts in phylogroups connectivity networks and their bimodal interactions with Prevotella, suggesting intra- and inerspecific epistatic relationships. Finally, a technique based on nonlinear dimensionality reduction visual-ized all distinct clusters of all sets, providing a chance to test the feasibility of using intra-specific phylotyping of E. coli for medical applications.