Genomic characterization of ESBL-producing Escherichia coli isolates from patients in an orthopaedic ward in Mwanza, Tanzania

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Orthopaedic wards may facilitate persistence and transmission due to prolonged hospitalization, frequent antimicrobial exposure, and increased patient vulnerability. This study investigated the genomic characteristics of ESBL-producing E. coli recovered from hospitalized patients in an orthopaedic ward in Mwanza, Tanzania. Methods We performed whole-genome sequencing and comparative genomic analysis of ESBL-confirmed E. coli isolates obtained from stool or rectal swabs of hospitalized patients. Sequence reads were quality controlled and assembled using standard pipelines. Core genome single nucleotide polymorphism (SNP) alignments were generated using Snippy, and recombination was identified and masked using Gubbins prior to phylogenetic reconstruction. Sequence types (STs), AMR determinants, plasmid replicons, and virulence-associated genes were identified using established bioinformatics tools and databases. Results Phylogenetic analysis revealed a polyclonal population structure comprising multiple distinct lineages rather than a single outbreak clone. Several isolates formed tight phylogenetic clusters within the ward, consistent with local circulation of closely related strains. The population included internationally recognized sequence types, including ST131, ST1193, ST69, ST617, and ST38. ESBL production was predominantly associated with bla CTX-M-15, detected in most isolates, alongside additional resistance determinants to aminoglycosides, quinolones, sulfonamides, trimethoprim, and tetracyclines. IncF-family plasmid replicons predominated, with additional IncY plasmids identified. Virulence-associated genes, including fdeC and ybtP/ybtQ, were widely distributed. Conclusions ESBL-producing E. coli in this orthopaedic ward represent a genomically diverse, multidrug-resistant population dominated by bla CTX-M-15-positive lineages. The coexistence of multiple lineages alongside closely related clusters suggests ongoing circulation of high-risk clones. These findings highlight colonized patients as reservoirs of AMR and underscore the need to integrate genomic surveillance into infection prevention and control strategies in resource-constrained healthcare settings. " } { "@context": "http://schema.org", "@type": "BreadcrumbList", "itemListElement": [ { "@type": "ListItem", "position": "1", "item": { "@id": "https://f1000research.com/", "name": "Home" } }, { "@type": "ListItem", "position": "2", "item": { "@id": "https://f1000research.com/browse/articles", "name": "Browse" } }, { "@type": "ListItem", "position": "3", "item": { "@id": "https://f1000research.com/articles/15-670/v1", "name": "Genomic characterization of ESBL-producing Escherichia coli isolates..." } } ] } Home Browse Genomic characterization of ESBL-producing Escherichia coli isolates... ALL Metrics - Views Downloads Get PDF Get XML Cite How to cite this article Mboowa G, Kidenya BR, Sserwadda I et al. Genomic characterization of ESBL-producing Escherichia coli isolates from patients in an orthopaedic ward in Mwanza, Tanzania [version 1; peer review: 1 approved with reservations] . F1000Research 2026, 15 :670 ( https://doi.org/10.12688/f1000research.180294.1 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Close Copy Citation Details Export Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente EXPORT Select a format first Track Share ▬ ✚ Research Article Genomic characterization of ESBL-producing Escherichia coli isolates from patients in an orthopaedic ward in Mwanza, Tanzania [version 1; peer review: 1 approved with reservations] Gerald Mboowa https://orcid.org/0000-0001-8445-9414 1 , Benson R Kidenya 2 , Ivan Sserwadda https://orcid.org/0000-0001-7785-7297 1 , Stephen Kanyerezi https://orcid.org/0000-0002-2439-939X 1 , Jeremiah Seni 2 Gerald Mboowa https://orcid.org/0000-0001-8445-9414 1 , Benson R Kidenya 2 , [...] Ivan Sserwadda https://orcid.org/0000-0001-7785-7297 1 , Stephen Kanyerezi https://orcid.org/0000-0002-2439-939X 1 , Jeremiah Seni 2 PUBLISHED 05 May 2026 Author details Author details 1 Department of Immunology and Molecular Biology, College of Health Sciences, School of Biomedical Sciences, Makerere University, Kampala, P.O. Box 7072, Uganda 2 Weill Bugando School of Medicine, Catholic University of Health and Allied Sciences, Mwanza, P.O. Box 1464, Tanzania Gerald Mboowa Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Software, Supervision, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Benson R Kidenya Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Software, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing Ivan Sserwadda Roles: Data Curation, Formal Analysis, Investigation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Stephen Kanyerezi Roles: Data Curation, Formal Analysis, Investigation, Methodology, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Jeremiah Seni Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Software, Supervision, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing OPEN PEER REVIEW DETAILS REVIEWER STATUS This article is included in the Pathogens gateway. This article is included in the Genomics and Genetics gateway. Abstract Background Extended-spectrum β-lactamase (ESBL)-producing Escherichia coli are a major contributor to antimicrobial resistance (AMR) in healthcare settings, yet their genomic diversity and population structure remain poorly characterized in low-resource settings. Orthopaedic wards may facilitate persistence and transmission due to prolonged hospitalization, frequent antimicrobial exposure, and increased patient vulnerability. This study investigated the genomic characteristics of ESBL-producing E. coli recovered from hospitalized patients in an orthopaedic ward in Mwanza, Tanzania. Methods We performed whole-genome sequencing and comparative genomic analysis of ESBL-confirmed E. coli isolates obtained from stool or rectal swabs of hospitalized patients. Sequence reads were quality controlled and assembled using standard pipelines. Core genome single nucleotide polymorphism (SNP) alignments were generated using Snippy, and recombination was identified and masked using Gubbins prior to phylogenetic reconstruction. Sequence types (STs), AMR determinants, plasmid replicons, and virulence-associated genes were identified using established bioinformatics tools and databases. Results Phylogenetic analysis revealed a polyclonal population structure comprising multiple distinct lineages rather than a single outbreak clone. Several isolates formed tight phylogenetic clusters within the ward, consistent with local circulation of closely related strains. The population included internationally recognized sequence types, including ST131, ST1193, ST69, ST617, and ST38. ESBL production was predominantly associated with bla CTX-M-15 , detected in most isolates, alongside additional resistance determinants to aminoglycosides, quinolones, sulfonamides, trimethoprim, and tetracyclines. IncF-family plasmid replicons predominated, with additional IncY plasmids identified. Virulence-associated genes, including fdeC and ybtP/ybtQ , were widely distributed. Conclusions ESBL-producing E. coli in this orthopaedic ward represent a genomically diverse, multidrug-resistant population dominated by bla CTX-M-15 -positive lineages. The coexistence of multiple lineages alongside closely related clusters suggests ongoing circulation of high-risk clones. These findings highlight colonized patients as reservoirs of AMR and underscore the need to integrate genomic surveillance into infection prevention and control strategies in resource-constrained healthcare settings. READ ALL READ LESS Keywords Escherichia coli,ESBL (extended-spectrum β-lactamase), antimicrobial resistance, hospital environment, whole-genome sequencing Corresponding Author(s) Gerald Mboowa ( [email protected] ) Benson R Kidenya ( [email protected] ) Close Corresponding authors: Gerald Mboowa, Benson R Kidenya Competing interests: No competing interests were disclosed. Grant information: This study was part of the research project titled “Understanding transmission dynamics and acquisition of antimicrobial resistance at referral hospitals and community settings in East Africa,” supported through the Grand Challenges Africa programme (grant numbers GCA/AMR/rnd2/058/002 and GCA/AMR/rnd2/058-01 .Research reported in this publication was also supported by the Fogarty International Center of the National Institutes of Health under Award Numbers U2RTW012116 and D43TW013056 The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Copyright: © 2026 Mboowa G et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite: Mboowa G, Kidenya BR, Sserwadda I et al. Genomic characterization of ESBL-producing Escherichia coli isolates from patients in an orthopaedic ward in Mwanza, Tanzania [version 1; peer review: 1 approved with reservations] . F1000Research 2026, 15 :670 ( https://doi.org/10.12688/f1000research.180294.1 ) First published: 05 May 2026, 15 :670 ( https://doi.org/10.12688/f1000research.180294.1 ) Latest published: 05 May 2026, 15 :670 ( https://doi.org/10.12688/f1000research.180294.1 ) Introduction Antimicrobial resistance (AMR) among Gram-negative bacteria represents a major global public health threat, with extended-spectrum β -lactamase (ESBL)-producing Escherichia coli emerging as one of the most clinically significant pathogens in both community and healthcare settings. 1 , 2 ESBL enzymes, particularly those of the CTX-M family, confer resistance to third-generation cephalosporins and are frequently co-associated with resistance to other antimicrobial classes, resulting in multidrug-resistant (MDR) phenotypes that complicate treatment and increase morbidity and mortality. 3 – 5 Among these, bla CTX-M-15 has become the dominant ESBL gene globally and is widely disseminated across diverse E. coli lineages and geographic regions. 6 , 7 In sub-Saharan Africa, the burden of ESBL-producing Enterobacteriaceae is increasing, driven by limited diagnostic capacity, high antimicrobial usage, and constrained infection prevention and control (IPC) infrastructure. 8 – 10 E. coli is a major contributor to this burden, not only as a cause of invasive infections but also as a colonizer of the gastrointestinal tract, where it serves as a reservoir for AMR genes. 11 , 12 Colonization is particularly important in hospitalized patients, as it can precede infection and facilitate onward transmission within healthcare settings. 12 – 20 However, genomic data describing the population structure, resistance determinants, and transmission dynamics of ESBL-producing E. coli in African hospital environments remain limited. Orthopaedic wards represent a high-risk setting for the persistence and dissemination of MDR organisms. 21 – 24 Patients in these settings often experience prolonged hospital stays, repeated exposure to antibiotics, and increased vulnerability due to underlying trauma or surgical interventions. 25 These factors create conditions that may facilitate the maintenance and spread of resistant bacterial populations within the patient cohort. Understanding the diversity and relatedness of colonizing strains in such settings is therefore essential for informing infection prevention and antimicrobial stewardship strategies. Whole-genome sequencing (WGS) has transformed the study of bacterial epidemiology by enabling high-resolution characterization of population structure, resistance mechanisms, and clonal relationships. 26 Genomic approaches allow discrimination between clonal expansion and polyclonal populations, identification of high-risk sequence types such as ST131 and ST1193, and detection of mobile genetic elements, including plasmids that mediate the spread of AMR genes. 27 – 29 Despite these advances, relatively few studies have applied WGS to investigate ESBL-producing E. coli colonization in hospitalized patient populations in sub-Saharan Africa. Data from Tanzanian healthcare settings are particularly scarce, especially with respect to genomic characterization of ESBL-producing E. coli in high-risk hospital wards. In this study, we performed a genomic epidemiological analysis of ESBL-confirmed E. coli isolates recovered from stool or rectal swabs of patients admitted to an orthopaedic ward in a tertiary hospital in Mwanza, Tanzania. By integrating WGS with detailed clinical metadata, we aimed to (i) characterize the population structure and sequence types of ESBL-producing E. coli , (ii) define their AMR, plasmid, and virulence-associated profiles, and (iii) assess patterns of genomic relatedness consistent with the circulation of multidrug-resistant lineages within the patient population. Methods Study setting and design This study was nested within a larger longitudinal investigation conducted over a 4-month period, from 3 January 2020 to 30 May 2020, assessing gastrointestinal colonization with ESBL-producing Enterobacteriaceae among orthopaedic patients admitted to a tertiary hospital in Mwanza, Tanzania. 30 The parent study included broader sampling activities within the ward. For this study, we analyzed ESBL-confirmed E. coli isolates recovered from stool or rectal swabs collected from patients admitted to the orthopaedic ward. By integrating whole-genome sequencing data with available clinical and ward-level metadata, the study aimed to investigate the population structure of ESBL-producing E. coli , define their AMR and associated genomic features, and assess patterns of clustering consistent with the circulation of multidrug-resistant lineages within the orthopaedic ward. Bacterial isolation and ESBL confirmation Clinical stool and rectal swab samples were processed using standard microbiological procedures at the Department of Microbiology and Immunology, Weill Bugando School of Medicine, Catholic University of Health and Allied Sciences, Mwanza, Tanzania. Samples were inoculated onto MacConkey agar (Oxoid, UK) and CHROMagar™ ESBL (CHROMagar, France), a selective medium containing cephalosporins for the isolation of ESBL-producing Gram-negative bacteria. Plates were incubated aerobically at 35–37 °C for 18–24 hours. Colonies with morphology consistent with E. coli were selected and subcultured to obtain pure isolates. ESBL production was then confirmed phenotypically using the combination disk method, comparing inhibition zones for cefotaxime and ceftazidime, alone and in combination with clavulanic acid, in accordance with CLSI recommendations for phenotypic ESBL confirmation. 31 Only isolates confirmed as ESBL-producing E. coli were included in downstream genomic analyses. DNA extraction, library preparation, and sequencing Pure E. coli isolates were shipped to the Genomics Laboratory, Department of Immunology and Molecular Biology, College of Health Sciences, Makerere University, Kampala, Uganda, where genomic DNA was extracted using standardized protocols. DNA concentration was measured using the Qubit dsDNA High Sensitivity Assay (Thermo Fisher Scientific, USA), and DNA purity was assessed using a NanoDrop spectrophotometer (Thermo Fisher Scientific, USA) by evaluating A260/280 and A260/230 ratios. DNA integrity was further assessed by 1.0% agarose gel electrophoresis. Whole-genome sequencing was performed at the Earlham Institute (Norwich, UK) using the Illumina NovaSeq 6000 platform. Sequencing libraries were prepared using the LITE (Low Input Transposase-Enabled) protocol, and sequencing was carried out using paired-end 150-bp chemistry (2 × 150 bp reads). Read processing and genome assembly Raw sequencing reads were subjected to quality control using FastQC (v0.12.1), 32 followed by adapter trimming and removal of low-quality bases using Trimmomatic (v0.40), 33 with default parameters. High-quality reads were retained for downstream analyses. De novo genome assemblies were generated using SKESA (Strategic K -mer Extension for Scrupulous Assemblies) assembler (v2.4.0), 34 with default settings and assembly quality was assessed using standard metrics, including genome size, contiguity, and N50 values, to ensure suitability for comparative genomic analysis. Genomic species confirmation Genomic species confirmation was performed using a multi-tool approach to ensure robust and accurate taxonomic classification. Draft genome assemblies were analyzed using GTDB-Tk (v2.6.0) 35 (Genome Taxonomy Database Toolkit), which assigns taxonomy based on genome-wide phylogenetic placement against the GTDB reference database. To complement this, GAMBIT v1.1.0 (Genomic Approximation Method for Bacterial Identification and Tracking) 36 was used to provide k -mer–based taxonomic classification, enabling rapid and high-resolution identification of bacterial genomes. In addition, Basic Local Alignment Search Tool for nucleotides (BLASTn) searches were performed against the NCBI nucleotide database to confirm species identity based on sequence similarity to well-characterized reference genomes. Blast analyses were conducted using the Docker image gmboowa/blast-analysis:1.9.4. Concordance across these three independent approaches (GTDB-Tk, GAMBIT, and BLAST) was used to validate species assignments, ensuring all isolates were accurately classified as E. coli prior to downstream comparative genomic analyses. Genome characterization and typing Sequence types (STs) were assigned from draft genome assemblies using the MLST module in rMAP-2.0, implemented with the mlst tool (Torsten Seemann; Docker image staphb/mlst:2.19.0). This approach scans assembled contigs against PubMLST-curated schemes to determine the sequence type and allele profile for each isolate, enabling classification into globally recognized E. coli lineages. 37 Read mapping and variant calling Quality-controlled reads were mapped to the clinical E. coli reference genome GCF_000285655.3_EC958.v1 using the Snippy pipeline (v4.6.0), 38 which integrates BWA-MEM for read alignment and bcftools for variant calling. This clinically relevant reference was selected to improve mapping accuracy and reduce reference bias in the analysis of hospital-associated isolates. Core genome single nucleotide polymorphisms (SNPs) were identified across all isolates, and a multiple sequence alignment of core SNPs was generated for downstream phylogenetic analysis. Recombination filtering and phylogenetic reconstruction To account for homologous recombination, SNP alignments were processed using Gubbins v3.4.1 (Genealogies Unbiased By recomBinations In Nucleotide Sequences), 39 which identifies and masks regions of elevated SNP density consistent with recombination. The resulting recombination-filtered alignment represents clonal variation across the dataset. Maximum-likelihood phylogenetic trees were inferred using IQ-TREE v3.1.1, 40 based on the recombination-filtered core genome SNP alignment. Branch support was assessed using standard bootstrap approaches. Pairwise SNP distances between isolates were calculated using snp-dists, providing a quantitative measure of genomic relatedness. The final phylogenetic tree was visualized in iTOL v7.0 (Interactive Tree of Life), 41 where isolate metadata were incorporated to annotate the tree and facilitate interpretation of clustering patterns, epidemiological relationships, and potential transmission events. Transmission network analysis To investigate potential transmission events among ESBL-producing E. coli isolates, pairwise SNP distances were calculated from the recombination-filtered core genome alignment generated using Snippy and processed with Gubbins. SNP distances were computed using snp-dists, providing a matrix of pairwise genomic distances among the 39 clinical isolates and the included reference genome. A transmission-linked network was constructed using a predefined SNP threshold of ≤5 SNPs, consistent with thresholds commonly applied to infer recent transmission or shared-source acquisition in bacterial genomic epidemiology. Isolates and the reference genome were represented as nodes, and edges were drawn between nodes with pairwise SNP distances at or below this threshold. Edge labels indicate the number of SNP differences between connected nodes. The network was generated using Python (version 3.14) with the NetworkX library for graph construction and Matplotlib for visualization. A force-directed layout algorithm (spring layout) was applied to position nodes based on their connectivity, enabling clear visualization of clusters of closely related isolates and facilitating identification of putative transmission events within the orthopaedic ward. Antimicrobial resistance, plasmid, and virulence analysis Antimicrobial resistance genes were identified using the ResFinder v4.5.0 database, 42 enabling classification of resistance determinants into antimicrobial classes. MDR was defined as the presence of resistance determinants spanning three or more antimicrobial classes. 43 Plasmid replicons were identified within rMAP-2.0 using PlasmidFinder 44 to screen assembled genomes for known plasmids, while virulence-associated genes were detected using ABRicate, 45 implemented through the Docker image staphb/abricate:1.0.0 against curated E. coli virulence factor databases. These analyses were executed through the containerized rMAP-2.0 workflow, ensuring reproducibility, portability, and consistent processing across all samples. 37 Data integration and comparative analysis Genomic data were integrated with available epidemiological and clinical metadata, including non-identifiable clinical and epidemiological metadata. This enabled an integrated analysis of population structure, antimicrobial resistance burden, plasmid content, and virulence-associated profiles. Phylogenetic clustering was interpreted in the context of ward-level and patient-level metadata to assess patterns consistent with the circulation and local persistence of closely related multidrug-resistant lineages within the orthopaedic ward. Results Sample characteristics A total of 45 ESBL-producing clinical E. coli isolates were initially collected from patient-derived stool and rectal swab samples obtained from individuals admitted to the orthopaedic ward. Of these, 39 isolates passed quality control and were included in the whole-genome sequencing and downstream analyses ( Table 1 ). Core genome phylogenetic analysis revealed multiple distinct clusters, indicating genomic diversity among isolates circulating within the ward. Several isolates formed tight phylogenetic clusters, suggestive of potential shared sources or localized transmission events, while others appeared more genetically distinct. Notably, isolate A55728 formed a long independent branch, indicating substantial divergence from other isolates. The distribution of isolates across phylogenetic clusters, together with metadata on sample source and collection site, provided a framework for investigating potential transmission dynamics between patients and the hospital environment. Detailed isolate-level characteristics are presented in Extended data 1 (Table S1) . Table 1. Summary of sample characteristics of 39 ESBL-producing E. coli isolates. Characteristic Value Total isolates 39 Source Patient and environment Median age (years) 30.5 years Sex distribution 21 female (53.8%), 18 male (46.2%) Common fracture types Closed (66.7%), Open (23.1%) Most common fracture sites Femur (38.5%), Tibia (10.3%) Median genome size (Mb) ~5.1 Median contigs 90 (range: 50–3339) Median GC (%) ~50.6 MDR isolates 39/39 (100%) Dominant sequence types (MLST) ST131, ST1193, ST69 Number of phylogenetic clusters 8 clusters + 1 outlier Genomic features Whole-genome sequencing of 39 ESBL-producing E. coli isolates generated high-quality draft assemblies suitable for downstream comparative genomic analysis. Species identity was genomically confirmed using a combination of GTDB-Tk, GAMBIT, Extended data 1 (Table S1) and BLAST-based approaches ( https://gmboowa.github.io/rMAP-2.0/reports/esbl_ecoli.html#blast ), ensuring accurate taxonomic assignment and minimizing misclassification within the E. coli species complex. The assemblies had a median genome size of approximately 5.1 Mb, consistent with typical E. coli genomes. Assembly fragmentation varied across isolates, with a median of 90 contigs (range: 50–3339), indicating overall good assembly quality, although a small number of genomes were highly fragmented. The GC content was highly conserved across isolates, with a median of approximately 50.6%, reflecting the expected genomic composition of E. coli. Sequence typing revealed a genetically diverse population comprising several globally recognized high-risk and community-associated lineages, including ST131, ST1193, ST69, ST617, and ST38, alongside additional less frequent sequence types. This diversity indicates the co-circulation of internationally disseminated high-risk clones and locally established lineages within the orthopaedic ward population. Core genome SNP analysis using Snippy identified substantial genomic diversity across the isolates. The reference-based alignment revealed a wide range of variant sites, highlighting the presence of both closely related and highly divergent isolates within the same clinical setting. The distribution of SNPs per isolate demonstrated marked heterogeneity, with some isolates showing minimal divergence consistent with recent transmission or shared ancestry, while others exhibited extensive polymorphism, reflecting the presence of multiple independent lineages. Antimicrobial resistance, plasmids, and virulence determinants All 39 isolates were classified as MDR, carrying resistance determinants to three or more antimicrobial classes. ESBL production was predominantly associated with bla CTX-M-15 , which was detected in most isolates and is consistent with its recognized role as a globally disseminated ESBL determinant. Beyond β -lactam resistance, the isolates harbored genes associated with resistance to several additional antimicrobial classes, including aminoglycosides, fluoroquinolones, sulfonamides, trimethoprim, and tetracyclines. This broad resistome highlights the accumulation of multiple resistance determinants within individual isolates and reflects the complex AMR burden present in the orthopaedic ward setting. Plasmid analysis showed a predominance of IncF-family replicons, which are frequently implicated in the dissemination of ESBL genes in E. coli. Additional plasmid types, including IncY, were also identified in a subset of isolates, indicating the involvement of diverse mobile genetic elements in the acquisition and spread of resistance determinants. Virulence-associated genes were also widely distributed across the isolate collection, including factors linked to adhesion, iron acquisition, and extraintestinal survival, such as fdeC and ybtP/ybtQ. The co-occurrence of antimicrobial resistance and virulence-associated determinants underscores the clinical relevance of these isolates and raises concern about the circulation of lineages with both enhanced pathogenic potential and limited treatment options. Pairwise SNP distances and transmission inference Pairwise SNP distances were calculated from the recombination-filtered core genome alignment to assess genomic relatedness among E. coli clinical isolates. SNP distances ranged widely across the dataset, from 0 to 20,176 SNPs, with a mean distance of approximately 2,506 SNPs, indicating substantial genetic diversity within the orthopaedic ward population. Despite this overall diversity, a subset of isolates exhibited very low SNP distances (0–5 SNPs), consistent with recent transmission events or a shared source within the hospital environment. 46 In contrast, the majority of isolate pairs showed large SNP distances (>1000 SNPs), suggesting the presence of genetically unrelated strains and multiple independent introductions into the hospital ward. Identification of genetically indistinguishable isolates (0 SNP cluster) A cluster of isolates with zero SNP differences was identified, comprising isolates A55724, A55793, and A55798. These isolates were genetically indistinguishable at the core genome level ( Table 2 ), strongly indicating a recent transmission event or a common source. Such zero-distance clustering provides high-confidence evidence of direct or near-direct transmission within the clinical setting. Table 2. Pairwise SNP distances among isolates with zero SNP differences (Cluster 1). This table shows isolate pairs with 0 SNP differences based on core genome SNP analysis, indicating genetically indistinguishable genomes. These isolates (A55724, A55793, A55798) likely represent a recent transmission cluster or a shared source within the orthopaedic ward. Cluster 1 (0 SNP differences — identical genomes). Isolate 1 Isolate 2 SNP Distance A55724 A55793 0 A55724 A55798 0 A55793 A55798 0 Detection of closely related transmission clusters (≤3 SNPs) A second cluster of closely related isolates was identified, with pairwise SNP distances ranging from 0 to 3 SNPs. This cluster included isolates A55769, A55939, A55941, and A55966 ( Table 3 ). The low level of genomic variation within this group is consistent with a recent transmission chain or ongoing circulation of a closely related lineage within the ward. Table 3. Pairwise SNP distances among closely related isolates (Cluster 2). This table presents isolate pairs with 0–3 SNP differences, indicating highly related genomes. The isolates (A55769, A55939, A55941, A55966) form a closely related cluster consistent with recent transmission or an ongoing transmission chain within the ward. Isolate 1 Isolate 2 SNP distance A55769 A55939 1 A55769 A55941 1 A55769 A55966 3 A55939 A55941 0 A55939 A55966 2 A55941 A55966 2 Interpretation of transmission dynamics Together, these findings indicate a mixed epidemiological scenario within the orthopaedic ward. The presence of both genetically indistinguishable isolates and closely related clusters supports the occurrence of localized transmission events, while the broader distribution of high SNP distances across the dataset reflects a diverse background population structure, likely driven by multiple introductions of unrelated E. coli lineages into the hospital environment. These results demonstrate the coexistence of recent transmission clusters and genetically diverse strains, underscoring the importance of integrating genomic data with epidemiological context to better understand transmission pathways and inform infection prevention strategies. Two distinct transmission clusters were identified based on pairwise SNP distances of ≤5 SNPs. The first cluster, comprising isolates A55724, A55793, and A55798, showed 0 SNP differences, indicating genetically indistinguishable isolates and providing strong evidence of recent transmission or a common source. The second cluster, comprising A55769, A55939, A55941, and A55966, showed pairwise SNP distances ranging from 0 to 3 SNPs, consistent with a very closely related group and suggestive of an ongoing transmission chain within the ward. Shared variant analysis Analysis of shared SNPs identified groups of isolates with common variant profiles, further supporting the phylogenetic structure observed in the core genome SNP analysis. Isolates that were closely related in the phylogeny shared a higher proportion of SNPs, forming distinct genomic clusters consistent with possible transmission chains or recent common ancestry. In contrast, isolates with few or no shared variants were more genetically distant, supporting the presence of multiple unrelated lineages within the study population. Phylogenetic relationships Core genome phylogenetic analysis based on the recombination-filtered SNP alignment demonstrated a clearly polyclonal population structure among the 39 ESBL-producing E. coli isolates ( Figure 2 ). The isolates were distributed across multiple distinct lineages, with eight phylogenetic clusters identified alongside one genetically distinct outlier, rather than forming a single outbreak clone. This overall structure indicates substantial genomic diversity within the orthopaedic ward population. Despite this broad diversity, several isolates formed tight phylogenetic clusters characterized by short branch lengths, consistent with the low pairwise SNP distances observed and suggestive of recent transmission or shared-source exposure within the ward ( Figure 2 ). In contrast, a subset of isolates displayed long branches, indicating marked genetic divergence and supporting the presence of unrelated strains likely introduced independently into the hospital setting. Notably, isolate A55728 formed a long independent branch and remained clearly separated from the main clusters, consistent with the high SNP distances observed and arguing against its involvement in recent local transmission events. Taken together, the recombination-filtered phylogeny, pairwise SNP distance analysis, and shared variant patterns support a mixed epidemiological scenario in which localized transmission occurs within a background of multiple independent introductions. The coexistence of closely related isolate clusters and more widely separated lineages suggests that ESBL-producing E. coli in this orthopaedic ward are shaped by both local clonal expansion and the repeated introduction of diverse MDR strains. High-risk sequence types, including ST131 and ST1193, were represented across this population, further underscoring their contribution to the dissemination of ESBL-producing E. coli in this setting. Comparative analysis Comparative genomic analysis revealed both heterogeneity and shared features across the ESBL-producing E. coli population. Although the isolates were distributed across multiple sequence types and phylogenetic clusters, many shared a common repertoire of antimicrobial resistance determinants, most notably bla CTX-M-15 , indicating the widespread distribution of key ESBL-associated resistance genes across genetically distinct lineages. Comparison of plasmid content further showed that diverse sequence types frequently carried similar IncF-family replicons, supporting a common role for these plasmids in the dissemination of resistance determinants. At the same time, variation in accessory resistance and virulence-associated genes across isolates highlighted the presence of lineage-specific genomic features superimposed on a shared multidrug-resistant background. Taken together, these findings suggest that the ESBL-producing E. coli population in the orthopaedic ward is shaped by both the persistence of successful lineages and the circulation of shared mobile genetic elements, resulting in isolates that are phylogenetically diverse but convergent in their resistance profiles. Discussion This study provides a genomic snapshot of ESBL-producing E. coli colonizing patients admitted to an orthopaedic ward in Mwanza, Tanzania, and demonstrates that this patient population harbors a diverse but highly resistant set of lineages. Rather than identifying a single dominant outbreak clone, our data revealed a polyclonal population structure composed of multiple globally recognized and locally circulating sequence types, including ST131, ST1193, ST69, ST617, and ST38. At the same time, the identification of closely related isolate clusters with pairwise distances of 0–3 SNPs indicates that, within this broader diversity, recent transmission or shared-source exposure likely occurred within the ward. Taken together, these findings suggest that ESBL-producing E. coli in this setting are maintained through a combination of repeated introduction of diverse strains and localized circulation of specific lineages. 16 , 18 The predominance of bla CTX-M-15 across the isolate collection is notable and consistent with its recognized role as the most widely disseminated ESBL determinant in E. coli. 5 , 6 In this study, bla CTX-M-15 was distributed across multiple phylogenetically distinct backgrounds, indicating that the burden of ESBL production in the ward is not restricted to a single lineage. This pattern supports the view that successful resistance genes can become embedded in diverse strain backgrounds, thereby amplifying their epidemiological and clinical impact. 3 The fact that all sequenced isolates were multidrug resistant, with resistance determinants spanning β -lactams, aminoglycosides, fluoroquinolones, sulfonamides, trimethoprim, and tetracyclines, further emphasizes the limited therapeutic options associated with these colonizing strains and reinforces the clinical importance of gastrointestinal carriage as a reservoir of difficult-to-treat organisms. 11 , 12 The plasmid findings provide an important mechanistic explanation for this convergence in resistance profiles across otherwise unrelated lineages. The predominance of IncF-family replicons, together with the detection of additional plasmid types such as IncY, suggests that mobile genetic elements play a major role in shaping the ward resistome. IncF plasmids are particularly important in E. coli because of their well-established association with ESBL dissemination and persistence in clinically successful clones. 28 In our dataset, the recurrence of similar plasmid backgrounds across multiple sequence types supports the likelihood that plasmid-mediated horizontal gene transfer contributes substantially to the spread of resistance determinants in this setting. Thus, the resistance burden observed here appears to reflect not only the persistence of successful lineages, but also the circulation of shared mobile elements capable of moving across strain backgrounds. Beyond resistance, the widespread detection of virulence-associated loci, including genes linked to adhesion, iron acquisition, and extraintestinal survival such as fdeC and ybtP/ybtQ , underscores the clinical relevance of these colonizing isolates. The co-occurrence of antimicrobial resistance and virulence-associated determinants raises concern that the orthopaedic ward patient population may be colonized by strains with both enhanced pathogenic potential and reduced susceptibility to commonly used antibiotics. This is especially important in orthopaedic settings, where prolonged hospitalization, surgical interventions, trauma-related wounds, and repeated antimicrobial exposure may increase opportunities for colonization, persistence, and progression to infection. 11 , 12 From an infection prevention perspective, colonized patients should therefore be viewed not simply as passive carriers, but as potential reservoirs of clinically important multidrug-resistant organisms. 21 – 24 The pairwise SNP analysis adds an important epidemiological dimension to these genomic findings. Although the overall SNP distance distribution was wide, indicating substantial diversity, two distinct low-SNP clusters were identified. One cluster comprised isolates that were genomically indistinguishable at the core genome level, while the second comprised isolates differing by only 0–3 SNPs. These patterns are consistent with recent transmission or shared-source acquisition within the ward. 46 Importantly, however, these clusters were observed against a backdrop of many genetically unrelated isolates, indicating that ward-level transmission is only part of the overall picture. This mixed scenario suggests that ESBL-producing E. coli in the orthopaedic ward likely arise through both ongoing circulation of closely related strains and repeated introduction of unrelated lineages from colonized patients entering the hospital. Such a pattern is epidemiologically plausible in a setting where patient turnover, referral pathways, and prior healthcare exposure may continually seed new resistant strains into the ward environment ( Figure 1 ). Figure 1. Transmission-linked network of ESBL-producing E. coli isolates (≤5 SNPs). Nodes represent individual isolates, and edges represent pairwise SNP distances of ≤5 SNPs derived from recombination-filtered core genome analysis. Edge labels indicate the number of SNP differences between connected isolates. Two transmission clusters were identified. The first cluster comprised isolates A55939, A55769, A55966, and A55941, with pairwise SNP distances ranging from 0 to 3 SNPs, consistent with recent transmission or a shared source. The second cluster comprised isolates A55724, A55793, and A55798, which were genetically indistinguishable at the core genome level (0 SNP differences). Most isolates were not connected within the ≤5 SNP threshold, indicating substantial genetic diversity and suggesting multiple independent introductions into the orthopaedic ward. Figure 2. Core genome phylogenetic relationships and antimicrobial resistance profiles of ESBL-producing E. coli isolates. Core genome SNP-based phylogenetic tree of 39 ESBL-producing E. coli isolates recovered from stool or rectal swabs of patients admitted to an orthopaedic ward in Mwanza, Tanzania. The tree was constructed from a recombination-filtered core genome alignment generated using Snippy, with recombination regions identified and masked using Gubbins, and maximum-likelihood inference performed using IQ-TREE. Isolates are grouped into eight phylogenetic clusters (Clusters 1–8) and one genetically distinct outlier, indicated by colored symbols at the tips. Several clusters comprise closely related isolates with short branch lengths, consistent with low pairwise SNP distances and potential recent transmission events, while others show greater divergence, reflecting multiple independent lineages circulating within the ward. The recombination-filtered phylogeny and shared variant analysis support this interpretation. Several isolates formed tight clusters with short branches and shared variant profiles, consistent with recent common ancestry and possible recent transmission. In contrast, isolates such as A55728 showed marked divergence from the main clusters, reflecting distant ancestry and arguing against participation in recent local transmission events. These observations highlight the value of combining phylogenetic structure, SNP distances, and shared variant patterns when interpreting transmission dynamics. In a setting such as this, reliance on one metric alone could oversimplify the epidemiology; instead, the data support a model in which both clonal spread and genomic convergence through shared resistance elements are occurring simultaneously. 16 , 18 , 26 From a clinical and public health perspective, these findings have several implications. These findings highlight the importance of colonized patients as reservoirs of multidrug-resistant organisms with potential implications for infection prevention and antimicrobial stewardship. First, they reinforce the importance of gastrointestinal colonization surveillance in hospitalized patients, particularly in high-risk wards such as orthopaedics, where colonized patients may serve as reservoirs for onward transmission and possibly subsequent infection. 11 , 14 Second, they support the need for strengthened infection prevention and control measures aimed not only at preventing environmental contamination and patient-to-patient spread, but also at recognizing the role of patient importation of resistant strains. 25 Third, they highlight the utility of genomic surveillance for distinguishing between true clonal spread and broader background diversity, thereby informing targeted interventions. In resource-constrained settings, this kind of genomic information may be especially valuable for prioritizing IPC strategies and antimicrobial stewardship around the organisms and lineages most likely to circulate and persist. 26 This study has limitations that should be acknowledged. First, only 39 isolates passed sequencing quality control and were included in the genomic analyses, which limits the breadth of inference. Second, the study focused on patient-derived stool and rectal swab isolates and did not include contemporaneous sequencing of environmental or healthcare worker isolates, limiting our ability to reconstruct precise transmission pathways. Third, the analysis was conducted within a single orthopaedic ward at one tertiary hospital, and the findings may therefore not be fully generalizable to other wards, hospitals, or regions. Fourth, although plasmid replicons and resistance genes were identified, the use of short-read sequencing limits full resolution of plasmid architecture and the exact genomic context of some resistance determinants. Finally, while low SNP thresholds provide evidence consistent with recent transmission, genomic similarity alone cannot establish the direction or exact route of transmission in the absence of denser epidemiological linkage data. These limitations mean that our findings should be interpreted as evidence of likely circulation patterns rather than definitive proof of specific transmission events. Despite these limitations, this study provides important genomic evidence that ESBL-producing E. coli colonizing orthopaedic patients in Mwanza comprise a multidrug-resistant, genomically diverse, yet epidemiologically connected population. The co-circulation of high-risk international clones, widespread bla CTX-M-15 , common IncF-family plasmids, and low-SNP transmission clusters suggests that the orthopaedic ward functions as both a point of convergence for imported resistant strains and a setting that may permit local persistence and spread. These findings underscore the need to integrate genomic surveillance into infection prevention and antimicrobial resistance monitoring frameworks in sub-Saharan African hospitals, particularly in wards where prolonged stays and antibiotic exposure may amplify the risks of colonization and onward transmission. 6 , 26 Conclusions This study demonstrates that ESBL-producing E. coli colonizing patients in an orthopaedic ward in Mwanza, Tanzania comprise a multidrug-resistant, genomically diverse population dominated by bla CTX-M-15 and carried across multiple globally recognized and locally circulating lineages. Despite this overall diversity, the identification of low-SNP transmission clusters indicates that recent transmission or shared-source exposure is occurring within the ward, highlighting the coexistence of multiple introductions and localized spread. The widespread presence of IncF-family plasmids and shared resistance determinants across phylogenetically distinct isolates suggests that horizontal gene transfer, alongside clonal expansion, plays a key role in shaping the resistance landscape. The concurrent detection of virulence-associated genes further underscores the clinical significance of these colonizing strains as potential sources of difficult-to-treat infections. Together, these findings emphasize the importance of gastrointestinal colonization as a reservoir for antimicrobial resistance in hospitalized patients and highlight the need for strengthened infection prevention and control measures, improved antimicrobial stewardship, and the integration of genomic surveillance into routine monitoring frameworks in resource-limited healthcare settings. Software availability The bioinformatics analyses in this study were conducted using the rMAP-2.0 (Rapid Microbial Analysis Pipeline). The pipeline is openly available and can be accessed via GitHub: • Repository: https://github.com/gmboowa/rMAP-2.0 • Version: v2.0 • License: MIT License A representative report including sample quality control (QC) metrics and downstream analysis outputs is available at: https://gmboowa.github.io/rMAP-2.0/reports/esbl_ecoli.html Ethics approval and consent to participate This study was conducted in accordance with the Declaration of Helsinki and relevant national regulations. It was approved by the Joint CUHAS/BMC Research and Ethics Committee (CREC/409/2019) and the National Health Research Ethics Review Committee of the National Institute for Medical Research (NIMR/HQ/R.8a/Vol. IX/3322) in Tanzania. Permission to conduct the study was obtained from the hospital administration, the Head of the Department of Orthopaedics, and ward supervisors/in-charge nurses prior to sample and data collection. Sampling did not involve collection of identifiable patient information. In the parent study, written informed consent (or assent for children) was obtained from all participants where clinical samples and data were collected. Patients with suspected surgical site infections received appropriate clinical management, including culture and antimicrobial susceptibility testing to guide therapy. Data availability All sequencing data generated in this study have been deposited in the National Center for Biotechnology Information under BioProject accession PRJNA1452460. Raw sequencing reads for all E. coli isolates are available in the Sequence Read Archive and are linked to this BioProject. The corresponding BioSample accession numbers are SAMN57232750–SAMN57232788, and these are also listed in the Extended data 1 (Table S1) associated with this study. Bioinformatics analyses were performed using reproducible workflows implemented in rMAP-2.0 (Rapid Microbial Analysis Pipeline). The scripts and workflow used for data processing and analysis are available at https://github.com/gmboowa/rMAP-2.0 . The following Extended dataset is provided: • Extended data 1 (Table S1) : Metadata for all isolates, including BioSample accessions, sample information, and associated genomic characteristics. This dataset is available on Figshare: https://doi.org/10.6084/m9.figshare.32016402 Internal isolate identifiers used in the manuscript are not included in the public dataset to ensure de-identification; corresponding SRA accession numbers are provided in Extended data Table S1. All data are openly available without restriction in accordance with F1000Research open data policies. Acknowledgements We sincerely thank the hospital infection prevention and control and laboratory teams in Tanzania for their support in coordinating sampling, culture, and isolate processing. References 1. Global action plan on antimicrobial resistance.[cited 2026 Apr 11]. Reference Source 2. Murray CJL, Ikuta KS, Sharara F, et al. : Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. Lancet. 2022 Feb 12; 399 (10325): 629–655. PubMed Abstract | Publisher Full Text | Free Full Text 3. Woerther PL, Burdet C, Chachaty E, et al. : Trends in human fecal carriage of extended-spectrum β-lactamases in the community: toward the globalization of CTX-M. Clin. Microbiol. Rev. 2013 Oct; 26 (4): 744–758. PubMed Abstract | Publisher Full Text | Free Full Text 4. Bush K, Bradford PA: β-Lactams and β-Lactamase Inhibitors: An Overview. Cold Spring Harb. Perspect. Med. 2016 Aug 1; 6 (8): a025247. PubMed Abstract | Publisher Full Text | Free Full Text 5. Paterson DL, Bonomo RA: Extended-spectrum beta-lactamases: a clinical update. Clin. Microbiol. Rev. 2005 Oct; 18 (4): 657–686. PubMed Abstract | Publisher Full Text | Free Full Text 6. Cantón R, González-Alba JM, Galán JC: CTX-M Enzymes: Origin and Diffusion. Front. Microbiol. 2012; 3 : 110. PubMed Abstract | Publisher Full Text | Free Full Text 7. Bevan ER, Jones AM, Hawkey PM: Global epidemiology of CTX-M β-lactamases: temporal and geographical shifts in genotype. J. Antimicrob. Chemother. 2017 Aug 1; 72 (8): 2145–2155. PubMed Abstract | Publisher Full Text 8. Tadesse BT, Ashley EA, Ongarello S, et al. : Antimicrobial resistance in Africa: a systematic review. BMC Infect. Dis. 2017 Sep 11; 17 (1): 616. PubMed Abstract | Publisher Full Text | Free Full Text 9. Totaro V, Guido G, Cotugno S, et al. : Antimicrobial Resistance in Sub-Saharan Africa: A Comprehensive Landscape Review. Am J Trop Med Hyg. 2025 Aug; 113 (2): 253–263. PubMed Abstract | Publisher Full Text | Free Full Text 10. Gulumbe BH, Haruna UA, Almazan J, et al. : Combating the menace of antimicrobial resistance in Africa: a review on stewardship, surveillance and diagnostic strategies. Biol Proced Online. 2022 Nov; 23 (24): 19. PubMed Abstract | Publisher Full Text | Free Full Text 11. Tawfick MM, Elshamy AA, Mohamed KT, et al. : Gut Commensal Escherichia coli, a High-Risk Reservoir of Transferable Plasmid-Mediated Antimicrobial Resistance Traits. Infect Drug Resist. 2022 Mar 16; 15 : 1077–1091. PubMed Abstract | Publisher Full Text | Free Full Text 12. Jia H, Lu S, Jia Y, et al. : Human intestinal colonization by Escherichia coli ST4014 co-harboring tet(X4) and blaNDM-1 gene: a potential reservoir for antimicrobial resistance dissemination. Microbiol. Spectrum. 2026; 14 (3): e03336–e03325. PubMed Abstract | Publisher Full Text | Free Full Text 13. Manning S, Lautenbach E, Tolomeo P, et al. : 344Risk Factors for Infection with Escherichia coli among Long-Term Care Facility Residents with Gastrointestinal Tract Colonization with Fluoroquinolone-Resistant E. coli. Open Forum Infect. Dis. 2014 Dec; 1 (Suppl 1): S137. Publisher Full Text | Free Full Text 14. Rodríguez I, Figueiredo AS, Sousa M, et al. : A 21-Year Survey of Escherichia coli from Bloodstream Infections (BSI) in a Tertiary Hospital Reveals How Community-Hospital Dynamics of B2 Phylogroup Clones Influence Local BSI Rates. mSphere. 2021; 6 (6): e00868–21. PubMed Abstract | Publisher Full Text | Free Full Text 15. Mangalea MR, Halpin AL, Haile M, et al. : Decolonization and Pathogen Reduction Approaches to Prevent Antimicrobial Resistance and Healthcare-Associated Infections. Emerg. Infect. Dis. 2024 Jun; 30 (6): 1069–1076. PubMed Abstract | Publisher Full Text | Free Full Text 16. Gladstone RA, McNally A, Pöntinen AK, et al. : Emergence and dissemination of antimicrobial resistance in Escherichia coli causing bloodstream infections in Norway in 2002–17: a nationwide, longitudinal, microbial population genomic study. The Lancet Microbe. 2021 Jul 1; 2 (7): e331–e341. PubMed Abstract | Publisher Full Text | Free Full Text 17. Johnson JR, Clabots C, Porter SB, et al. : Intestinal Persistence of Colonizing Escherichia coli Strains, Especially ST131-H30, in Relation to Bacterial and Host Factors. J. Infect. Dis. 2022 Jan 3; 225 (12): 2197–2207. PubMed Abstract | Publisher Full Text | Free Full Text 18. Pöntinen AK, Gladstone RA, Pesonen H, et al. : Modulation of multidrug-resistant clone success in Escherichia coli populations: a longitudinal, multi-country, genomic and antibiotic usage cohort study. The Lancet Microbe. 2024 Feb 1; 5 (2): e142–e150. PubMed Abstract | Publisher Full Text 19. Wende M, Osbelt L, Eisenhard L, et al. : Suppression of gut colonization by multidrug-resistant Escherichia coli clinical isolates through cooperative niche exclusion. Nat. Commun. 2025 Jul 1; 16 (1): 5426. PubMed Abstract | Publisher Full Text | Free Full Text 20. Wolford H, McCarthy NL, Baggs J, et al. : Antimicrobial-Resistant Infections in Hospitalized Patients. JAMA Netw. Open. 2025 Mar 14; 8 (3): e2462059. Publisher Full Text 21. Liang M, Liu Q: Distribution and Risk Factors of Multidrug-Resistant Bacteria Infection in Orthopedic Patients. J Healthc Eng. 2022 Jan 27; 2022 : 2114661–2114665. PubMed Abstract | Publisher Full Text | Free Full Text 22. Yang Y, Ting TT, Lin J, et al. : The effect of a full-time infection control nursing service in the prevention of multidrug-resistant organism in the orthopedic ward. BMC Infect. Dis. 2022 Apr 7; 22 : 348. PubMed Abstract | Publisher Full Text | Free Full Text 23. Yang X, Guo R, Zhang B, et al. : Retrospective analysis of drug resistance characteristics and infection related risk factors of multidrug-resistant organisms (MDROs) isolated from the orthopedics department of a tertiary hospital. Sci. Rep. 2023 Feb 7; 13 (1): 2199. PubMed Abstract | Publisher Full Text | Free Full Text 24. Elifranji ZO, Haddad B, Salameh A, et al. : Microbiological Profile and Drug Resistance Analysis of Postoperative Infections following Orthopedic Surgery: A 5-Year Retrospective Review. Adv Orthop. 2022 Jul 4; 2022 : 7648014. PubMed Abstract | Publisher Full Text | Free Full Text 25. Otter JA, Yezli S, Salkeld JAG, et al. : Evidence that contaminated surfaces contribute to the transmission of hospital pathogens and an overview of strategies to address contaminated surfaces in hospital settings. Am. J. Infect. Control. 2013 May; 41 (5 Suppl): S6–S11. PubMed Abstract | Publisher Full Text 26. Gardy JL, Loman NJ: Towards a genomics-informed, real-time, global pathogen surveillance system. Nat. Rev. Genet. 2018; 19 (1): 9–20. PubMed Abstract | Publisher Full Text | Free Full Text 27. Johnson JR, Porter S, Thuras P, et al. : The Pandemic H30 Subclone of Sequence Type 131 (ST131) as the Leading Cause of Multidrug-Resistant Escherichia coli Infections in the United States (2011–2012). Open Forum Infect. Dis. 2017 May 2; 4 (2): ofx089. PubMed Abstract | Publisher Full Text | Free Full Text 28. Carattoli A: Plasmids and the spread of resistance. Int. J. Med. Microbiol. 2013 Aug; 303 (6–7): 298–304. PubMed Abstract | Publisher Full Text 29. Pitout JDD, DeVinney R: Escherichia coli ST131: a multidrug-resistant clone primed for global domination. F1000Res. 2017; 6 : F1000 Faculty Rev-195. PubMed Abstract | Publisher Full Text | Free Full Text 30. Seni J, Akaro IL, Mkinze B, et al. : Gastrointestinal Tract Colonization Rate of Extended-Spectrum Beta-Lactamase-Producing Gram-Negative Bacteria and Associated Factors Among Orthopaedic Patients in a Tertiary Hospital in Tanzania: Implications for Infection Prevention. Infect Drug Resist. 2021; 14 : 1733–1745. PubMed Abstract | Publisher Full Text | Free Full Text 31. Poulou A, Grivakou E, Vrioni G, et al. : Modified CLSI Extended-Spectrum β-Lactamase (ESBL) Confirmatory Test for Phenotypic Detection of ESBLs among Enterobacteriaceae Producing Various β-Lactamases. J. Clin. Microbiol. 2014 May; 52 (5): 1483–1489. PubMed Abstract | Publisher Full Text | Free Full Text 32. Babraham Bioinformatics - FastQC A Quality Control tool for High Throughput Sequence Data.[cited 2026 Apr 12]. Reference Source 33. Bolger AM, Lohse M, Usadel B: Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014 Aug 1; 30 (15): 2114–2120. PubMed Abstract | Publisher Full Text | Free Full Text 34. Souvorov A, Agarwala R, Lipman DJ: SKESA: strategic k-mer extension for scrupulous assemblies. Genome Biol. 2018 Oct 4; 19 : 153. PubMed Abstract | Publisher Full Text | Free Full Text 35. Chaumeil PA, Mussig AJ, Hugenholtz P, et al. : GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database. Bioinformatics. 2020 Mar 15; 36 (6): 1925–1927. PubMed Abstract | Publisher Full Text | Free Full Text 36. Lumpe J, Gumbleton L, Gorzalski A, et al. : GAMBIT (Genomic Approximation Method for Bacterial Identification and Tracking): A methodology to rapidly leverage whole genome sequencing of bacterial isolates for clinical identification. PLoS One. 2023; 18 (2): e0277575. PubMed Abstract | Publisher Full Text | Free Full Text 37. Mboowa G, Sserwadda I, Kanyerezi S: rMAP 2.0: a modular, reproducible, and scalable WDL–Cromwell–Docker workflow for genomic analysis of ESKAPEE pathogens. Bioinformatics Advances. 2026 Jan 1; 6 (1): vbag046. PubMed Abstract | Publisher Full Text | Free Full Text 38. Seemann T: tseemann/snippy [Perl].2026 [cited 2026 Apr 12]. Reference Source 39. Croucher NJ, Page AJ, Connor TR, et al. : Rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences using Gubbins. Nucleic Acids Res. 2015 Feb 18; 43 (3): e15. PubMed Abstract | Publisher Full Text | Free Full Text 40. Nguyen LT, Schmidt HA, von Haeseler A , et al. : IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies. Mol. Biol. Evol. 2015 Jan; 32 (1): 268–274. PubMed Abstract | Publisher Full Text | Free Full Text 41. Letunic I, Bork P: Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation. Nucleic Acids Res. 2021 Jul 2; 49 (W1): W293–W296. PubMed Abstract | Publisher Full Text | Free Full Text 42. Bortolaia V, Kaas RS, Ruppe E, et al. : ResFinder 4.0 for predictions of phenotypes from genotypes. J. Antimicrob. Chemother. 2020 Dec 1; 75 (12): 3491–3500. PubMed Abstract | Publisher Full Text | Free Full Text 43. Magiorakos AP, Srinivasan A, Carey RB, et al. : Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin. Microbiol. Infect. 2012 Mar 1; 18 (3): 268–281. PubMed Abstract | Publisher Full Text 44. Carattoli A, Zankari E, García-Fernández A, et al. : In Silico Detection and Typing of Plasmids using PlasmidFinder and Plasmid Multilocus Sequence Typing. Antimicrob. Agents Chemother. 2014 Jul; 58 (7): 3895–3903. PubMed Abstract | Publisher Full Text | Free Full Text 45. Seemann T: tseemann/abricate [Perl].2026 [cited 2026 Apr 12]. Reference Source 46. Jones G, Nodari CS, Fabre L, et al. : Lessons from 5 Years of Routine Whole-Genome Sequencing for Epidemiologic Surveillance of Shiga Toxin–Producing Escherichia coli, France, 2018–2022. Emerging Infectious Diseases journal - CDC. May 2025; 31, Supplement : 117–128. PubMed Abstract | Publisher Full Text | Free Full Text Comments on this article Comments (0) Version 1 VERSION 1 PUBLISHED 05 May 2026 ADD YOUR COMMENT Comment Author details Author details 1 Department of Immunology and Molecular Biology, College of Health Sciences, School of Biomedical Sciences, Makerere University, Kampala, P.O. Box 7072, Uganda 2 Weill Bugando School of Medicine, Catholic University of Health and Allied Sciences, Mwanza, P.O. Box 1464, Tanzania Gerald Mboowa Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Software, Supervision, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Benson R Kidenya Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Software, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing Ivan Sserwadda Roles: Data Curation, Formal Analysis, Investigation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Stephen Kanyerezi Roles: Data Curation, Formal Analysis, Investigation, Methodology, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Jeremiah Seni Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Software, Supervision, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Competing interests No competing interests were disclosed. Grant information This study was part of the research project titled “Understanding transmission dynamics and acquisition of antimicrobial resistance at referral hospitals and community settings in East Africa,” supported through the Grand Challenges Africa programme (grant numbers GCA/AMR/rnd2/058/002 and GCA/AMR/rnd2/058-01 .Research reported in this publication was also supported by the Fogarty International Center of the National Institutes of Health under Award Numbers U2RTW012116 and D43TW013056 The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Article Versions (1) version 1 Published: 05 May 2026, 15:670 https://doi.org/10.12688/f1000research.180294.1 Copyright © 2026 Mboowa G et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Download Export To Sciwheel Bibtex EndNote ProCite Ref. Manager (RIS) Sente metrics Views Downloads F1000Research - - PubMed Central info_outline Data from PMC are received and updated monthly. - - Citations open_in_new 0 open_in_new 0 open_in_new SEE MORE DETAILS CITE how to cite this article Mboowa G, Kidenya BR, Sserwadda I et al. Genomic characterization of ESBL-producing Escherichia coli isolates from patients in an orthopaedic ward in Mwanza, Tanzania [version 1; peer review: 1 approved with reservations] . F1000Research 2026, 15 :670 ( https://doi.org/10.12688/f1000research.180294.1 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS track receive updates on this article Track an article to receive email alerts on any updates to this article. TRACK THIS ARTICLE Share Open Peer Review Current Reviewer Status: ? Key to Reviewer Statuses VIEW HIDE Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Version 1 VERSION 1 PUBLISHED 05 May 2026 Views 0 Cite How to cite this report: Afolayan AO. Reviewer Report For: Genomic characterization of ESBL-producing Escherichia coli isolates from patients in an orthopaedic ward in Mwanza, Tanzania [version 1; peer review: 1 approved with reservations] . F1000Research 2026, 15 :670 ( https://doi.org/10.5256/f1000research.198895.r481994 ) The direct URL for this report is: https://f1000research.com/articles/15-670/v1#referee-response-481994 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 18 May 2026 Ayorinde O Afolayan , Leibniz Institute - German Collection of Microorganisms and Cell Cultures (DSMZ), Germany, Germany Approved with Reservations VIEWS 0 https://doi.org/10.5256/f1000research.198895.r481994 The study investigated the genomic characteristics of ESBL-carrying Escherichia coli recovered from patients admitted into the orthopaedic ward in Mwanza, Tanzania over a 3-month period. The identification of strains belonging to globally recognized sequence types highlights the international dissemination of ... Continue reading READ ALL The study investigated the genomic characteristics of ESBL-carrying Escherichia coli recovered from patients admitted into the orthopaedic ward in Mwanza, Tanzania over a 3-month period. The identification of strains belonging to globally recognized sequence types highlights the international dissemination of these pathogens and their associated antimicrobial resistance (AMR) genes and virulence genes. The observed transmission clusters suggests possible in-hospital (within-ward) spread among vulnerable patients. The study contributes valuable data to the limited scientific knowledge on the spread of ESBL gene-carrying E. coli strains in low- and middle-income countries, and points to the need for routine genomic surveillance in order to inform strategies and policies needed to reduce their spread. Methodology: It will be useful to know the phylogroup, serotype, and pathotype of the E. coli strains (including whether any pathogen carried virulence genes associated with more than one pathotype). Some of the embedded web-links are non-functional (e.g., https://gmboowa.github.io/rMAP-2.0/reports/assets/sections/A55724_blast.html, returned a 'Page not found' error message) Concordance (or level of agreement) between genotypic AMR prediction results and phenotypic antimicrobial susceptibility testing (AST) results should be reported. Authors should consider adding a table summarizing the SNP ranges and mean SNP distance per sequence type. Under the sub-heading 'Pairwise SNP distances and transmission inference', the authors mentioned that 'a subset of isolates exhibited very low SNP distances (0-5)...'. Authors should specify how many isolates exhibited very low SNP distances, and the sequence type to which they belong. Table 2: It is not clear whether some of the E. coli strains were recovered from the same patient or not. Figure 2: This figure would benefit from the inclusion of relevant epidemiological data alongside the phylogenetic tree. Midpoint-rooting the tree may also improve interpretation. The figure legends should not appear pixelated. Readers would also benefit from a careful examination of the figure associated with the transmission network analysis, as it provides important visual context for the inferred transmission clusters and relationships among the isolates. The study could be strengthened by placing the strains within the context of other E. coli genomes from Tanzania, the rest of Africa, and globally. This would help clarify whether the strains reflect single or multiple introductions into Tanzania, as well as potential regional or international dissemination patterns. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Not applicable Are all the source data underlying the results available to ensure full reproducibility? Partly Are the conclusions drawn adequately supported by the results? Yes Competing Interests: No competing interests were disclosed. Reviewer Expertise: Genomic surveillance of antimicrobial resistance I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Afolayan AO. Reviewer Report For: Genomic characterization of ESBL-producing Escherichia coli isolates from patients in an orthopaedic ward in Mwanza, Tanzania [version 1; peer review: 1 approved with reservations] . F1000Research 2026, 15 :670 ( https://doi.org/10.5256/f1000research.198895.r481994 ) The direct URL for this report is: https://f1000research.com/articles/15-670/v1#referee-response-481994 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Comments on this article Comments (0) Version 1 VERSION 1 PUBLISHED 05 May 2026 ADD YOUR COMMENT Comment keyboard_arrow_left keyboard_arrow_right Open Peer Review Reviewer Status info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Reviewer Reports Invited Reviewers 1 Version 1 05 May 26 read Ayorinde O Afolayan , Leibniz Institute - German Collection of Microorganisms and Cell Cultures (DSMZ), Germany, Germany Comments on this article All Comments (0) Add a comment Sign up for content alerts Sign Up You are now signed up to receive this alert Browse by related subjects keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2026 Afolayan A. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 18 May 2026 | for Version 1 Ayorinde O Afolayan , Leibniz Institute - German Collection of Microorganisms and Cell Cultures (DSMZ), Germany, Germany 0 Views copyright © 2026 Afolayan A. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions The study investigated the genomic characteristics of ESBL-carrying Escherichia coli recovered from patients admitted into the orthopaedic ward in Mwanza, Tanzania over a 3-month period. The identification of strains belonging to globally recognized sequence types highlights the international dissemination of these pathogens and their associated antimicrobial resistance (AMR) genes and virulence genes. The observed transmission clusters suggests possible in-hospital (within-ward) spread among vulnerable patients. The study contributes valuable data to the limited scientific knowledge on the spread of ESBL gene-carrying E. coli strains in low- and middle-income countries, and points to the need for routine genomic surveillance in order to inform strategies and policies needed to reduce their spread. Methodology: It will be useful to know the phylogroup, serotype, and pathotype of the E. coli strains (including whether any pathogen carried virulence genes associated with more than one pathotype). Some of the embedded web-links are non-functional (e.g., https://gmboowa.github.io/rMAP-2.0/reports/assets/sections/A55724_blast.html, returned a 'Page not found' error message) Concordance (or level of agreement) between genotypic AMR prediction results and phenotypic antimicrobial susceptibility testing (AST) results should be reported. Authors should consider adding a table summarizing the SNP ranges and mean SNP distance per sequence type. Under the sub-heading 'Pairwise SNP distances and transmission inference', the authors mentioned that 'a subset of isolates exhibited very low SNP distances (0-5)...'. Authors should specify how many isolates exhibited very low SNP distances, and the sequence type to which they belong. Table 2: It is not clear whether some of the E. coli strains were recovered from the same patient or not. Figure 2: This figure would benefit from the inclusion of relevant epidemiological data alongside the phylogenetic tree. Midpoint-rooting the tree may also improve interpretation. The figure legends should not appear pixelated. Readers would also benefit from a careful examination of the figure associated with the transmission network analysis, as it provides important visual context for the inferred transmission clusters and relationships among the isolates. The study could be strengthened by placing the strains within the context of other E. coli genomes from Tanzania, the rest of Africa, and globally. This would help clarify whether the strains reflect single or multiple introductions into Tanzania, as well as potential regional or international dissemination patterns. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Not applicable Are all the source data underlying the results available to ensure full reproducibility? Partly Are the conclusions drawn adequately supported by the results? Yes Competing Interests No competing interests were disclosed. Reviewer Expertise Genomic surveillance of antimicrobial resistance I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (0) Afolayan AO. Peer Review Report For: Genomic characterization of ESBL-producing Escherichia coli isolates from patients in an orthopaedic ward in Mwanza, Tanzania [version 1; peer review: 1 approved with reservations] . F1000Research 2026, 15 :670 ( https://doi.org/10.5256/f1000research.198895.r481994) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/15-670/v1#referee-response-481994 Alongside their report, reviewers assign a status to the article: Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions Adjust parameters to alter display View on desktop for interactive features Includes Interactive Elements View on desktop for interactive features Competing Interests Policy Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. 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