Molecular and Phenotypic Characterization of Escherichia coli Associated with Granulomatous Colitis of Boxer Dogs.

Invasive Escherichia coli is causally associated with granulomatous colitis (GC) of Boxer dogs and French Bulldogs. The virulence determinants of GC E. coli are unclear. E. coli isolated from 16 GC (36 strains) and 17 healthy control (HC: 33 strains) dogs were diverse in phylogeny, genotype, and serotype and lacked diarrheagenic genes. Genes encoding type II (gsp), IV (traC), and VI (hcp) secretion systems, long polar fimbriae (lpfA154/141), and iron acquisition (fyuA, chuA) were frequent in GC and HC. E. coli from 14/15 GC and 10/11 HC invaded Caco-2 better than non-pathogenic E. coli strain DH5α, with invasion correlated with motility and presence of chuA and colV. E. coli from all GC and 10/11 HC survived better than DH5α in J774 macrophages, with adherent-invasive E. coli (AIEC) in 60% GC and 73% HC. AIEC replicated in monocyte derived macrophages from a GC Boxer with CD48/SLAM risk haplotype but not the HC. Fluroquinolone resistant E. coli were less motile and invasive than fluoroquinolone sensitive (p < 0.05), and only 1/8 resistant strains met criteria for AIEC. In conclusion GC E. coli are diverse, resemble extraintestinal pathogenic E. coli (ExPEC), including AIEC, and can replicate in GC-susceptible macrophages. They are likely resident pathosymbionts that can opportunistically persist within macrophages of a GC-susceptible dog.

Genome-wide cell-free DNA mutational integration enables ultra-sensitive cancer monitoring.

In many areas of oncology, we lack sensitive tools to track low-burden disease. Although cell-free DNA (cfDNA) shows promise in detecting cancer mutations, we found that the combination of low tumor fraction (TF) and limited number of DNA fragments restricts low-disease-burden monitoring through the prevailing deep targeted sequencing paradigm. We reasoned that breadth may supplant depth of sequencing to overcome the barrier of cfDNA abundance. Whole-genome sequencing (WGS) of cfDNA allowed ultra-sensitive detection, capitalizing on the cumulative signal of thousands of somatic mutations observed in solid malignancies, with TF detection sensitivity as low as 10-5. The WGS approach enabled dynamic tumor burden tracking and postoperative residual disease detection, associated with adverse outcome. Thus, we present an orthogonal framework for cfDNA cancer monitoring via genome-wide mutational integration, enabling ultra-sensitive detection, overcoming the limitation of cfDNA abundance and empowering treatment optimization in low-disease-burden oncology care.

DNA methylation disruption reshapes the hematopoietic differentiation landscape.

Mutations in genes involved in DNA methylation (DNAme; for example, TET2 and DNMT3A) are frequently observed in hematological malignancies1-3 and clonal hematopoiesis4,5. Applying single-cell sequencing to murine hematopoietic stem and progenitor cells, we observed that these mutations disrupt hematopoietic differentiation, causing opposite shifts in the frequencies of erythroid versus myelomonocytic progenitors following Tet2 or Dnmt3a loss. Notably, these shifts trace back to transcriptional priming skews in uncommitted hematopoietic stem cells. To reconcile genome-wide DNAme changes with specific erythroid versus myelomonocytic skews, we provide evidence in support of differential sensitivity of transcription factors due to biases in CpG enrichment in their binding motif. Single-cell transcriptomes with targeted genotyping showed similar skews in transcriptional priming of DNMT3A-mutated human clonal hematopoiesis bone marrow progenitors. These data show that DNAme shapes the topography of hematopoietic differentiation, and support a model in which genome-wide methylation changes are transduced to differentiation skews through biases in CpG enrichment of the transcription factor binding motif.

Somatic mutations and cell identity linked by Genotyping of Transcriptomes.

Defining the transcriptomic identity of malignant cells is challenging in the absence of surface markers that distinguish cancer clones from one another, or from admixed non-neoplastic cells. To address this challenge, here we developed Genotyping of Transcriptomes (GoT), a method to integrate genotyping with high-throughput droplet-based single-cell RNA sequencing. We apply GoT to profile 38,290 CD34+ cells from patients with CALR-mutated myeloproliferative neoplasms to study how somatic mutations corrupt the complex process of human haematopoiesis. High-resolution mapping of malignant versus normal haematopoietic progenitors revealed an increasing fitness advantage with myeloid differentiation of cells with mutated CALR. We identified the unfolded protein response as a predominant outcome of CALR mutations, with a considerable dependency on cell identity, as well as upregulation of the NF-κB pathway specifically in uncommitted stem cells. We further extended the GoT toolkit to genotype multiple targets and loci that are distant from transcript ends. Together, these findings reveal that the transcriptional output of somatic mutations in myeloproliferative neoplasms is dependent on the native cell identity.