Search bioRxiv⌕ Search

bioRxiv · 10.1101/2022.06.29.498070

Molecular characteristics of phages located in Carbapenemase-Producing Escherichia coli clinical isolates: New Phage-Like Plasmids

Abstract

Escherichia coli normally inhabits the gastrointestinal tract of humans and animals. Most E. coli bacteria do not cause problems, but the acquisition of different resistance and virulence genes encoded by mobile plasmids or phages by different bacterial isolates has been associated with the appearance of successful high-risk clones of multidrug-resistant (MDR) E. coli such as ST131 or ST405. In the present study, 50 temperate bacteriophages present in 21 clinical isolates of carbapenemase-producing E. coli of sequence types (STs) ST38, ST131, ST167, ST405 and ST410 were analysed. These phages were classified in the three families of the order Caudovirales: 24 within the family Siphoviridae, 23 in Myoviridae and 3 in Podoviridae. The size of the phages studied ranged from 11 to 95 Kb. Phylogenetic analysis of the terminase large subunit allowed us to classify these phages into different groups showing similarity with the phage sequences deposited in the Microbe Versus Phage (MVP) database and which belonged to clusters 229, 604, 2503 and 2725. On the other hand, bioinformatic study revealed that most of the identified proteins exerted a structural function (26.73%) but also functions involved in lysis/lysogeny (6.70%) or regulation (5.20%) among others. In addition, the ParA-ParB partitioning system and the type II toxin-antitoxin Phd-Doc system were also found in two of the phages studied, which could indicate the presence of plasmid-prophages. Host range testing revealed that two isolates were more susceptible to infection than the other isolates. IMPORTANCEEscherichia coli is one of the pathogens that causes most problems in human health, as it presents multiple resistances to different antibiotics. The study of bacteriophages located in different isolates of this species is important for the development of new anti-infective therapies. Currently, antibiotic resistance is a major problem, but more and more studies are pointing to experimental treatments with bacteriophages as a possible solution.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Diaz, M. L., Bleriot, I., Pacios, O., Fernandez-Garcia, L., Blasco, L., Ambroa, A., Ortiz-Cartagena, C., Woodford, N., Ellington, M. J., Tomas, M.. 2022-07-02. Molecular characteristics of phages located in Carbapenemase-Producing Escherichia coli clinical isolates: New Phage-Like Plasmids. https://doi.org/10.1101/2022.06.29.498070

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

CellChat Hotspot: A Targeted Approach to Cell Cell Communication Analysis With Spatial transcriptomics Validation.

Abstract. In recent years, single cell RNA sequencing (scRNA seq) has enabled the investigation of intercellular communication through Cell Cell Communication (CCC) tools such as CellChat. Despite their potential, these approaches remain challenging to interpret, particularly when global analyses generate complex interaction networks that may include biologically irrelevant signals. To address this limitation, we developed a framework termed CellChat Hotspot, designed to improve the biological interpretability of inferred communication networks. This approach integrates gene set enrichment analysis with a context driven filtering strategy, selecting both genes and cells based on their functional relevance prior to communication inference. Applied to stage II colon cancer data, CellChat Hotspot enabled the identification of condition-specific interaction patterns associated with recurrence. Non recurrent patients showed enrichment of immune related processes, whereas recurrent cases were characterized by pathways associated with invasion and metastasis. Notably, a loss of interaction in the HSPG pathway between CALB1+ and stromal cells was observed in recurrent patients, suggesting a potential disruption of cell matrix adhesion mechanisms. To verify the reliability of this finding, we applied the framework to spatial transcriptomics data, which confirmed the presence of the HSPG2 DAG1 interaction in non-recurrent tumors and its near absence in recurrent ones. Overall, this framework provides a biologically guided strategy for studying intercellular communication in complex systems such as the tumor microenvironment.

bioinformatics↗

SIFT: Syncmer-Informed Selection of Haplotypes for T2T Imputation

Genome patching improves the completeness of fragmented assemblies by filling unresolved gaps with sequences from reference genomes. Pangenome panels provide diverse candidate haplotypes for this task, but identifying suitable references efficiently becomes increasingly challenging as these panels grow. We present SIFT, a compressed indexing method for selecting reference haplotypes for genome patching with ImpuT2T. SIFT combines closed-syncmer parsing, phrase-level indexing, and pseudo-maximal exact match (pseudo-MEM) queries. Closed syncmers provide a context-independent parsing rule with bounded distances between consecutive selected positions, enabling consistent parsing of reference and query sequences. We demonstrate that two closed syncmers determine the distance at which they can occur consecutively in any string, so that equal substrings of two parses represent identical sequences and no gap sequence need be stored. SIFT indexes the reference parse and its reverse using run-length compressed suffix arrays and adapts the Boyer-Moore-Li search procedure to identify pseudo-MEMs between the reference parse and query parse. It then aggregates matching evidence to identify candidate reference haplotypes for downstream patching. This framework connects compressed sequence indexing with haplotype selection and provides a basis for querying large reference panels at the phrase level. SIFT is publicly available under the GNU license at https://github.com/EddieFerro/SIFT.

bioinformatics↗

Assessing the Capacity of Genomic Language Models to Generate Informative Embeddings of Viral Genome Fragments

Genomic language models (gLMs) trained on large volumes of nucleotide sequences are becoming an alternative to classical methods in metagenomic analysis, particularly for studying genomic "dark matter". In this work, we investigate the ability of four gLMs (DNABERT-2, DNABERT-S, ViraLM, and Evo2-7B) to generate taxonomically informative vector representations of short viral genome fragments. We constructed a balanced reference dataset of viruses based on the ICTV Virus Metadata Resource and compared the representations generated by gLMs with conventional k-mer profiles and MinHash sketches using clustering and neighborhood-based metrics (adjusted Rand index (ARI), precision@k, and CROSS precision@k). On the reference dataset, three of the four gLMs outperformed the 4-mer profile in terms of ARI and precision@5 under the same evaluation protocol. The best performance was generally achieved by intermediate model layers. Conventional k-mer profiles consistently outperformed MinHash sketches. We further evaluated the methods on two viral orders (egoviruses and mriyaviruses) absent from the reference dataset, with model layers and k-mer lengths selected exclusively on the reference dataset. DNABERT-S showed the most consistently strong performance across these two orders, ranking first on mriyaviruses and second on egoviruses, while k-mer profiles with Jensen-Shannon distance remained competitive. We also observed the consistency of representations between forward fragments and their reverse complements. Overall, the best-performing gLMs surpassed conventional baselines, although their advantage depended on the dataset and evaluation metric. The consistently strong performance of DNABERT-S suggests a potential benefit of contrastive fine-tuning and indicates that larger models are not necessarily more effective for generating taxonomically informative representations.

bioinformatics↗