The attachment of enteropathogenic Escherichia coli (EPEC) to intestinal epithelial cells is facilitated by several adhesins; however, the individual host-cell receptors for pili-mediated adherence have not been fully characterized. In this study, we evaluated the hypothesis that the E. coli common pilus (ECP) tip adhesin protein EcpD mediates attachment of EPEC to several extracellular matrix (ECM) glycoproteins (fibronectin, laminin, collagens I and IV, and mucin). We found that the ΔecpA mutant, which lacks production of the EcpA filament but retains EcpD on the surface, adhered to these glycoproteins below the wild-type levels, while the ΔecpD mutant, which does not display EcpA or EcpD, bound significantly less to these host glycoproteins. In agreement, a purified recombinant EcpD subunit bound significantly more than EcpA to laminin, fibronectin, collagens I and IV, and mucin in a dose-dependent manner. These are compelling data that strongly suggest that ECP-producing EPEC may bind to host ECM glycoproteins and mucins through the tip adhesin protein EcpD. This study highlights the versatility of EPEC to bind to different host proteins and suggests that the interaction of ECP with the host’s ECM glycoproteins may facilitate colonization of the intestinal mucosal epithelium.

Many cancer cell lines are aneuploid and heterogeneous, with multiple karyotypes co-existing within the same cell line. Karyotype heterogeneity has been shown to manifest phenotypically, thus affecting how cells respond to drugs or to minor differences in culture media. Knowing how to interpret karyotype heterogeneity phenotypically would give insights into cellular phenotypes before they unfold temporally. Here, we re-analyzed single cell RNA (scRNA) and scDNA sequencing data from eight stomach cancer cell lines by placing gene expression programs into a phenotypic context. Using live cell imaging, we quantified differences in the growth rate and contact inhibition between the eight cell lines and used these differences to prioritize the transcriptomic biomarkers of the growth rate and carrying capacity. Using these biomarkers, we found significant differences in the predicted growth rate or carrying capacity between multiple karyotypes detected within the same cell line. We used these predictions to simulate how the clonal composition of a cell line would change depending on density conditions during in-vitro experiments. Once validated, these models can aid in the design of experiments that steer evolution with density-dependent selection.