Pub Date : 2026-01-01DOI: 10.1016/j.jgar.2025.12.001
Sudha Chandrashekar , Shambhavi Nimisha Prasad , Ramesh Masthi N R , Sheilja Walia , Anushree Trikha , Rajeev Sadanandan
Background
Antimicrobial resistance (AMR) poses a formidable threat to public health in India, requiring a multidimensional response that bridges policy, innovation and intersectoral collaborations. The rapid emergence and spread of multidrug-resistant pathogens driven by the misuse of antimicrobials in human health, animal health, agriculture and environmental settings has rendered many existing therapies obsolete, leaving the population vulnerable to untreatable infections.
Objectives
To examine the multifactorial drivers of AMR in India, review current national and state-level policies and explore the potential role of artificial intelligence (AI) in AMR surveillance, prevention and control.
Methods
This review synthesises evidence from published literature, reports and policy documents. It analyses AMR determinants across human, animal and environmental sectors, evaluates policy frameworks such as India’s National Action Plan and State Action Plans to combat AMR.
Results
Key AMR drivers include antibiotic misuse, inadequate regulation, over-the-counter availability, pharmaceutical and hospital wastewater contamination and gaps in infection prevention. India has come up with national and six state level action plans for AMR containment. The measures include stewardship programs, laboratory network strengthening, spreading awareness and intersectoral coordination. The role of AI in strengthening AMR surveillance and clinical decision-making by integrating complex, high-dimensional data for predictive modelling has been explored.
Conclusion
While India has made significant policy and surveillance advances, enforcement gaps, limited awareness and fragmented data hinder progress. Strengthening governance, expanding One Health surveillance, integrating AI and embedding AMR strategies into universal health coverage are critical to mitigating AMR’s health and economic burden.
{"title":"Antimicrobial resistance in India: Integrating the response into health systems for universal health coverage","authors":"Sudha Chandrashekar , Shambhavi Nimisha Prasad , Ramesh Masthi N R , Sheilja Walia , Anushree Trikha , Rajeev Sadanandan","doi":"10.1016/j.jgar.2025.12.001","DOIUrl":"10.1016/j.jgar.2025.12.001","url":null,"abstract":"<div><h3>Background</h3><div>Antimicrobial resistance (AMR) poses a formidable threat to public health in India, requiring a multidimensional response that bridges policy, innovation and intersectoral collaborations. The rapid emergence and spread of multidrug-resistant pathogens driven by the misuse of antimicrobials in human health, animal health, agriculture and environmental settings has rendered many existing therapies obsolete, leaving the population vulnerable to untreatable infections.</div></div><div><h3>Objectives</h3><div>To examine the multifactorial drivers of AMR in India, review current national and state-level policies and explore the potential role of artificial intelligence (AI) in AMR surveillance, prevention and control.</div></div><div><h3>Methods</h3><div>This review synthesises evidence from published literature, reports and policy documents. It analyses AMR determinants across human, animal and environmental sectors, evaluates policy frameworks such as India’s National Action Plan and State Action Plans to combat AMR.</div></div><div><h3>Results</h3><div>Key AMR drivers include antibiotic misuse, inadequate regulation, over-the-counter availability, pharmaceutical and hospital wastewater contamination and gaps in infection prevention. India has come up with national and six state level action plans for AMR containment. The measures include stewardship programs, laboratory network strengthening, spreading awareness and intersectoral coordination. The role of AI in strengthening AMR surveillance and clinical decision-making by integrating complex, high-dimensional data for predictive modelling has been explored.</div></div><div><h3>Conclusion</h3><div>While India has made significant policy and surveillance advances, enforcement gaps, limited awareness and fragmented data hinder progress. Strengthening governance, expanding One Health surveillance, integrating AI and embedding AMR strategies into universal health coverage are critical to mitigating AMR’s health and economic burden.</div></div>","PeriodicalId":15936,"journal":{"name":"Journal of global antimicrobial resistance","volume":"46 ","pages":"Pages 195-202"},"PeriodicalIF":3.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145827902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.jgar.2025.12.005
Tuelo Mogashoa , Justice T. Ngom , Johannes Loubser , Kedumetse Seru , Tuduetso Molefi , One Stephen , Rosemary M. Musonda , Simani Gaseitsiwe , Robin M. Warren , Anzaan Dippenaar , Elizabeth M. Streicher , Sikhulile Moyo
Background
Undetected rifampicin resistance is a threat to global tuberculosis (TB) control efforts by delaying effective treatment. In different studies, non-canonical rpoB mutations outside the rifampicin resistance-determining region have been reported at varying prevalences by country. Here, we report cases of rifampicin resistance in Botswana that were missed by the routine molecular diagnostic assays.
Methods
Individuals were tested under routine programme conditions, in accordance with national guidelines, at four designated drug-resistant TB clinics from 2017 to 2022. Initial testing at the facilities included GeneXpert MTB/RIF ultra and later phenotypic drug susceptibility testing (pDST), as well as the Hain MTBDRsl line probe assay, at the National Tuberculosis Reference Laboratory. A total of nine isolates were subsequently sequenced on the Illumina NextSeq 2000 instrument.
Results
At the point of care, routine molecular tests classified all nine individuals as susceptible to rifampicin. Subsequent culture and phenotypic drug susceptibility testing confirmed rifampicin resistance. Whole-genome sequencing identified non-canonical rpoB mutations outside the rifampicin resistance-determining region I49F and V170F, which are associated with low-level rifampicin resistance. Of the nine isolates sequenced, 4 (44%) harboured the rpoB V170F mutation, while 5 (56%) harboured the rpoB I491F mutation.
Conclusions
These results highlight a diagnostic gap within the current algorithms and show the value of sequencing-based approaches for accurately detecting drug resistance. Incorporating sequencing into routine clinical practice could help guide the selection of TB treatment and improve treatment outcomes in patients who do not respond to first-line therapy.
{"title":"Undetected rifampicin-resistant tuberculosis associated with rpoB I491F and V170F mutations in Botswana: Diagnostic implications","authors":"Tuelo Mogashoa , Justice T. Ngom , Johannes Loubser , Kedumetse Seru , Tuduetso Molefi , One Stephen , Rosemary M. Musonda , Simani Gaseitsiwe , Robin M. Warren , Anzaan Dippenaar , Elizabeth M. Streicher , Sikhulile Moyo","doi":"10.1016/j.jgar.2025.12.005","DOIUrl":"10.1016/j.jgar.2025.12.005","url":null,"abstract":"<div><h3>Background</h3><div>Undetected rifampicin resistance is a threat to global tuberculosis (TB) control efforts by delaying effective treatment. In different studies, non-canonical <em>rpoB</em> mutations outside the rifampicin resistance-determining region have been reported at varying prevalences by country. Here, we report cases of rifampicin resistance in Botswana that were missed by the routine molecular diagnostic assays.</div></div><div><h3>Methods</h3><div>Individuals were tested under routine programme conditions, in accordance with national guidelines, at four designated drug-resistant TB clinics from 2017 to 2022. Initial testing at the facilities included GeneXpert MTB/RIF ultra and later phenotypic drug susceptibility testing (pDST), as well as the Hain MTBDR<em>sl</em> line probe assay, at the National Tuberculosis Reference Laboratory. A total of nine isolates were subsequently sequenced on the Illumina NextSeq 2000 instrument.</div></div><div><h3>Results</h3><div>At the point of care, routine molecular tests classified all nine individuals as susceptible to rifampicin. Subsequent culture and phenotypic drug susceptibility testing confirmed rifampicin resistance. Whole-genome sequencing identified non-canonical <em>rpoB</em> mutations outside the rifampicin resistance-determining region I49F and V170F, which are associated with low-level rifampicin resistance. Of the nine isolates sequenced, 4 (44%) harboured the <em>rpoB</em> V170F mutation, while 5 (56%) harboured the <em>rpoB</em> I491F mutation.</div></div><div><h3>Conclusions</h3><div>These results highlight a diagnostic gap within the current algorithms and show the value of sequencing-based approaches for accurately detecting drug resistance. Incorporating sequencing into routine clinical practice could help guide the selection of TB treatment and improve treatment outcomes in patients who do not respond to first-line therapy.</div></div>","PeriodicalId":15936,"journal":{"name":"Journal of global antimicrobial resistance","volume":"46 ","pages":"Pages 171-174"},"PeriodicalIF":3.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145756899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The use of antibiotics may facilitate the colonisation of antimicrobial-resistant organisms and genes within the host microbiome. However, studies on the effects of antibiotics on microbiomes and resistomes in clinical settings are limited.
Aim
The aim of this study was to determine the effects of antibiotic prophylaxis during colorectal cancer surgery on the oral and gut microbiomes and resistomes of patients.
Methods
We conducted a single-centre prospective observational cohort study on patients who underwent colorectal cancer surgery with antibiotic prophylaxis. DNA was extracted from oral and stool samples 1 day prior to the procedure and on postoperative days 1, 7, and 28. Subsequently, metagenomic sequencing was performed.
Findings
Among the eight patients with colorectal cancer, α-diversity in the oral and stool samples significantly decreased from baseline to each of the three post-administration time points. The abundance of anaerobic genera significantly decreased from baseline to Day 7. In the stool samples, Enterococcus, Limosilactobacillus, and Lacticaseibacillus abundances were markedly increased. Total antibiotic resistance gene (ARG) abundance significantly increased from the baseline to Day 7 in both oral and stool samples. The impact of the increase observed on Day 7 decreased but still persisted until Day 28 for diversity and total abundance of ARGs.
Conclusions
Oral and gut microbiomes and resistomes exhibited marked alterations that gradually reversed over time. Changes in the microbiome were associated with the spectrum of antibiotics used.
{"title":"Impact of antimicrobial prophylaxis in colorectal cancer surgery on the gut and oral microbiome and resistome: A prospective observational cohort study","authors":"Hiroki Kitagawa , Toshiki Kajihara , Koji Yahara , Norikazu Kitamura , Norifumi Shigemoto , Hirofumi Doi , Kensuke Shimbara , Kosuke Yoshimura , Ikki Nakashima , Shinnosuke Uegami , Yusuke Watadani , Miki Kawada-Matsuo , Hitoshi Komatsuzawa , Hiroki Ohge , Motoyuki Sugai","doi":"10.1016/j.jgar.2025.12.014","DOIUrl":"10.1016/j.jgar.2025.12.014","url":null,"abstract":"<div><h3>Background</h3><div>The use of antibiotics may facilitate the colonisation of antimicrobial-resistant organisms and genes within the host microbiome. However<strong>,</strong> studies on the effects of antibiotics on microbiomes and resistomes in clinical settings are limited.</div></div><div><h3>Aim</h3><div>The aim of this study was to determine the effects of antibiotic prophylaxis during colorectal cancer surgery on the oral and gut microbiomes and resistomes of patients.</div></div><div><h3>Methods</h3><div>We conducted a single-centre prospective observational cohort study on patients who underwent colorectal cancer surgery with antibiotic prophylaxis. DNA was extracted from oral and stool samples 1 day prior to the procedure and on postoperative days 1, 7, and 28. Subsequently, metagenomic sequencing was performed.</div></div><div><h3>Findings</h3><div>Among the eight patients with colorectal cancer, α-diversity in the oral and stool samples significantly decreased from baseline to each of the three post-administration time points. The abundance of anaerobic genera significantly decreased from baseline to Day 7. In the stool samples, <em>Enterococcus, Limosilactobacillus</em>, and <em>Lacticaseibacillus</em> abundances were markedly increased. Total antibiotic resistance gene (ARG) abundance significantly increased from the baseline to Day 7 in both oral and stool samples. The impact of the increase observed on Day 7 decreased but still persisted until Day 28 for diversity and total abundance of ARGs.</div></div><div><h3>Conclusions</h3><div>Oral and gut microbiomes and resistomes exhibited marked alterations that gradually reversed over time. Changes in the microbiome were associated with the spectrum of antibiotics used.</div></div>","PeriodicalId":15936,"journal":{"name":"Journal of global antimicrobial resistance","volume":"46 ","pages":"Pages 227-234"},"PeriodicalIF":3.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145846392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.jgar.2025.12.011
Melina Rapoport , Nahir Gattoni , Celeste Lucero , Juan Manuel de Mendieta
Objective
This study describes the phenotypic, molecular, and genomic characterisation of emerging blaNDM-1-producing Pseudomonas aeruginosa in Argentina, mainly driven by ST308 and ST274 clones.
Methods
Nineteen clinical isolates submitted to the National and Regional Reference Laboratory on Antimicrobial Resistance between 2018 and 2024 from nine hospitals were analysed. Antimicrobial susceptibility and carbapenemase activity were evaluated. In-house PCR assays were used to detect relevant resistance determinants. Genetic relatedness was assessed by SpeI-PFGE, and whole-genome sequencing was performed on nine isolates using Illumina and Oxford Nanopore technologies.
Results
All isolates were resistant to all β-lactams tested, except two, M28149 and M28715, that remained susceptible to aztreonam. All carried blaNDM-1. PFGE identified six pulsotypes, with 13 isolates in one dominant type. Whole-genome sequencing revealed six ST308, two ST274, and one ST3243; five ST308 isolates also harboured the rmtD 16S methylase gene. Phylogenetic analysis of ST308 isolates showed they formed a distinct cluster compared with those from other countries.
Conclusions
The emergence of blaNDM-1-producing P. aeruginosa associated with ST308 and ST274 clones represents a public health concern, particularly given the scarcity of effective treatment options for severe infections caused by these high-risk clones.
{"title":"Dissemination of NDM-1-producing Pseudomonas aeruginosa ST308 and ST274 high-risk clones in Argentina","authors":"Melina Rapoport , Nahir Gattoni , Celeste Lucero , Juan Manuel de Mendieta","doi":"10.1016/j.jgar.2025.12.011","DOIUrl":"10.1016/j.jgar.2025.12.011","url":null,"abstract":"<div><h3>Objective</h3><div>This study describes the phenotypic, molecular, and genomic characterisation of emerging <em>bla</em><sub>NDM-1</sub>-producing <em>Pseudomonas aeruginosa</em> in Argentina, mainly driven by ST308 and ST274 clones.</div></div><div><h3>Methods</h3><div>Nineteen clinical isolates submitted to the National and Regional Reference Laboratory on Antimicrobial Resistance between 2018 and 2024 from nine hospitals were analysed. Antimicrobial susceptibility and carbapenemase activity were evaluated. In-house PCR assays were used to detect relevant resistance determinants. Genetic relatedness was assessed by SpeI-PFGE, and whole-genome sequencing was performed on nine isolates using Illumina and Oxford Nanopore technologies.</div></div><div><h3>Results</h3><div>All isolates were resistant to all β-lactams tested, except two, M28149 and M28715, that remained susceptible to aztreonam. All carried <em>bla</em><sub>NDM-1</sub>. PFGE identified six pulsotypes, with 13 isolates in one dominant type. Whole-genome sequencing revealed six ST308, two ST274, and one ST3243; five ST308 isolates also harboured the <em>rmtD</em> 16S methylase gene. Phylogenetic analysis of ST308 isolates showed they formed a distinct cluster compared with those from other countries.</div></div><div><h3>Conclusions</h3><div>The emergence of <em>bla</em><sub>NDM-1</sub>-producing <em>P. aeruginosa</em> associated with ST308 and ST274 clones represents a public health concern, particularly given the scarcity of effective treatment options for severe infections caused by these high-risk clones.</div></div>","PeriodicalId":15936,"journal":{"name":"Journal of global antimicrobial resistance","volume":"46 ","pages":"Pages 187-194"},"PeriodicalIF":3.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145781085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.jgar.2025.12.009
Jee Hong KIM , Hyunkeun KIM , Kwan Soo KO
Objective
DNA methylation, catalysed by DNA methyltransferases (MTases), plays a crucial role in bacterial physiology. In this study, we investigated the effects of the DNA MTases, DNA adenine methyltransferase (Dam) and DNA cytosine methyltransferase (Dcm), on bacterial fitness and mutation rates in Escherichia coli.
Methods
We constructed an E. coli K-12 MG1655 strain lacking both the dam and dcm genes (ΔdamΔdcm). The bacterial fitness was assessed using growth curves and competition assays. Antibiotic susceptibility and persister cell formation were also evaluated. Additionally, the spontaneous mutation rates and mutation types in response to rifampicin and colistin were analysed.
Results
The MTase-deficient mutant ΔdamΔdcm exhibited significantly reduced growth rates and competitiveness compared to the wild-type (WT) strain. However, no significant differences in antibiotic resistance or persister cell formation rates were observed between the mutant and WT strains. Mutation frequencies in ΔdamΔdcm were significantly higher than in the WT when exposed to both rifampicin and colistin. Furthermore, a higher ratio of transition mutations in the rpoB and pmrAB genes was observed in rifampicin-resistant and colistin-resistant colonies derived from ΔdamΔdcm, respectively. DNA methylation influences bacterial growth and competitiveness, and the absence of MTases leads to increased spontaneous mutation rates under antibiotic pressure.
Conclusions
These findings suggest that DNA methylation plays a critical role in maintaining genomic stability and contributing to the development of antibiotic resistance.
{"title":"Impact of DNA methyltransferases on bacterial fitness and genome stability in Escherichia coli","authors":"Jee Hong KIM , Hyunkeun KIM , Kwan Soo KO","doi":"10.1016/j.jgar.2025.12.009","DOIUrl":"10.1016/j.jgar.2025.12.009","url":null,"abstract":"<div><h3>Objective</h3><div>DNA methylation, catalysed by DNA methyltransferases (MTases), plays a crucial role in bacterial physiology. In this study, we investigated the effects of the DNA MTases, DNA adenine methyltransferase (Dam) and DNA cytosine methyltransferase (Dcm), on bacterial fitness and mutation rates in <em>Escherichia coli.</em></div></div><div><h3>Methods</h3><div>We constructed an <em>E. coli</em> K-12 MG1655 strain lacking both the <em>dam</em> and <em>dcm</em> genes (Δ<em>dam</em>Δ<em>dcm</em>). The bacterial fitness was assessed using growth curves and competition assays. Antibiotic susceptibility and persister cell formation were also evaluated. Additionally, the spontaneous mutation rates and mutation types in response to rifampicin and colistin were analysed.</div></div><div><h3>Results</h3><div>The MTase-deficient mutant Δ<em>dam</em>Δ<em>dcm</em> exhibited significantly reduced growth rates and competitiveness compared to the wild-type (WT) strain. However, no significant differences in antibiotic resistance or persister cell formation rates were observed between the mutant and WT strains. Mutation frequencies in Δ<em>dam</em>Δ<em>dcm</em> were significantly higher than in the WT when exposed to both rifampicin and colistin. Furthermore, a higher ratio of transition mutations in the <em>rpoB</em> and <em>pmrAB</em> genes was observed in rifampicin-resistant and colistin-resistant colonies derived from Δ<em>dam</em>Δ<em>dcm</em>, respectively. DNA methylation influences bacterial growth and competitiveness, and the absence of MTases leads to increased spontaneous mutation rates under antibiotic pressure.</div></div><div><h3>Conclusions</h3><div>These findings suggest that DNA methylation plays a critical role in maintaining genomic stability and contributing to the development of antibiotic resistance.</div></div>","PeriodicalId":15936,"journal":{"name":"Journal of global antimicrobial resistance","volume":"46 ","pages":"Pages 203-208"},"PeriodicalIF":3.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145781070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.jgar.2025.12.004
Muhammad Sharjeel , Memoona Irshad , Azka Rizvi , Altaf Ahmed , Muhammad Jan Leghari
Objective
Rapid identification of lower respiratory tract infection pathogens is critical for initiating early antimicrobial therapy. This study aimed at evaluating the role of multiplex polymerase chain reaction (mPCR) in detecting respiratory pathogens and antimicrobial resistance at a transplant centre.
Methods
The study was a single-centre, retrospective analysis, completed at a tertiary care transplant centre. Data were included from 242 patients admitted with lower respiratory tract infection during a 24-month period. Respiratory specimens were analysed through BioFire PCR. Blood mPCR specimens were excluded (n = 44). Multiplex PCR results were compared with the gold standard of culture and sensitivity testing.
Results
A total of 198 patients were included in the study. The majority had a history of chronic hepatic or renal impairment (n = 95; 48%) or liver/kidney transplantation (n = 57; 28.8%). Chest imaging (n = 162) predominantly revealed pleural effusions (35.2%) and parenchymal infiltrates (28.4%). Most common sample types included sputum (n = 101; 51.0%) and tracheal aspirates (n = 93; 47.0%). Standard culture detected the following pathogens: 290 typical bacteria, 2 atypical organisms, and 95 viral detections. Klebsiella pneumoniae (32.3%) and Escherichia coli (28.8%) were most frequently identified. In n = 102 patients with corresponding culture results, mPCR had sensitivity of 76% and specificity of 59%, with 66.7% concordance between methods. Multiplex PCR and culture identified multiple bacterial species in 38 (37.3%) and 17 (16.7%) cases, respectively. Antimicrobial resistance gene analysis revealed high prevalence of CTX-M (30%), NDM (28%), and OXA-48-like (22%) mutations.
Conclusions
Multiplex PCR pneumonia panel demonstrated high sensitivity in detecting respiratory pathogens but had limitations in its specificity when compared to culture methods.
{"title":"Multiplex PCR pneumonia panel compared to standard culture of respiratory specimens: Retrospective results from a transplant centre","authors":"Muhammad Sharjeel , Memoona Irshad , Azka Rizvi , Altaf Ahmed , Muhammad Jan Leghari","doi":"10.1016/j.jgar.2025.12.004","DOIUrl":"10.1016/j.jgar.2025.12.004","url":null,"abstract":"<div><h3>Objective</h3><div>Rapid identification of lower respiratory tract infection pathogens is critical for initiating early antimicrobial therapy. This study aimed at evaluating the role of multiplex polymerase chain reaction (mPCR) in detecting respiratory pathogens and antimicrobial resistance at a transplant centre.</div></div><div><h3>Methods</h3><div>The study was a single-centre, retrospective analysis, completed at a tertiary care transplant centre. Data were included from 242 patients admitted with lower respiratory tract infection during a 24-month period. Respiratory specimens were analysed through BioFire PCR. Blood mPCR specimens were excluded (<em>n</em> = 44). Multiplex PCR results were compared with the gold standard of culture and sensitivity testing.</div></div><div><h3>Results</h3><div>A total of 198 patients were included in the study. The majority had a history of chronic hepatic or renal impairment (<em>n</em> = 95; 48%) or liver/kidney transplantation (<em>n</em> = 57; 28.8%). Chest imaging (<em>n</em> = 162) predominantly revealed pleural effusions (35.2%) and parenchymal infiltrates (28.4%). Most common sample types included sputum (<em>n</em> = 101; 51.0%) and tracheal aspirates (<em>n</em> = 93; 47.0%). Standard culture detected the following pathogens: 290 typical bacteria, 2 atypical organisms, and 95 viral detections. <em>Klebsiella pneumoniae</em> (32.3%) and <em>Escherichia coli</em> (28.8%) were most frequently identified. In <em>n</em> = 102 patients with corresponding culture results, mPCR had sensitivity of 76% and specificity of 59%, with 66.7% concordance between methods. Multiplex PCR and culture identified multiple bacterial species in 38 (37.3%) and 17 (16.7%) cases, respectively. Antimicrobial resistance gene analysis revealed high prevalence of CTX-M (30%), NDM (28%), and OXA-48-like (22%) mutations.</div></div><div><h3>Conclusions</h3><div>Multiplex PCR pneumonia panel demonstrated high sensitivity in detecting respiratory pathogens but had limitations in its specificity when compared to culture methods.</div></div>","PeriodicalId":15936,"journal":{"name":"Journal of global antimicrobial resistance","volume":"46 ","pages":"Pages 179-186"},"PeriodicalIF":3.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145723937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.jgar.2025.12.008
Samara Sant’Anna de Oliveira , Camille Alves Brito de Moura , Kaylanne Montenegro , Thereza Cristina da Costa Vianna , Ana Paula Alves do Nascimento , Gerson Gatto de Azeredo Coutinho , Hosana Dau Ferreira de Souza , Claudia Gladys Flores Sejas , Alexander Machado Cardoso , Kayo Bianco , Maysa Mandetta Clementino
Objective
Uropathogenic Escherichia coli (UPEC) poses a significant public health challenge due to increasing antimicrobial resistance (AMR) and severe infections. This study aimed to investigate the genetic heterogeneity and AMR mechanisms of a clinical UPEC strain associated with a fatal healthcare-associated infection.
Methods
Whole-genome sequencing (WGS) was performed on a multidrug-resistant (MDR) UPEC strain isolated from a pediatric patient by using an Illumina Miseq platform. The genome was assembled using Unicycler v0.4.8 and was annotated using the NCBI Prokaryotic Genome Annotation Pipeline (PGAP). Genomic analysis included characterisation of the resistome, virulome, and phylogenetic profile using various bioinformatics tools such as ResFinder v4.7.2, VFDB, and PubMLST.
Results
The isolate has a genome with a size of 4,681,240 bp, a GC content of 50.60% and harbour seven plasmids. Genomic analysis revealed multiple genetic determinants contributing to a multidrug-resistant profile, including efflux systems, enzymatic target alterations, and antibiotic transporter modifications. Adhesin genes (fimH, afaA-D, lpfA, fdeC, csgA), hemolysins (hlyE, hlyF), iron acquisition systems (iucC, iutA, sitA), and genes related to antimicrobial peptide degradation (ompT, traJ) and colicin production (cma, cvaC) were identified. Resistance to heavy metals (tellurium, copper/silver, arsenic) was also detected. These findings characterise the isolate as a highly virulent, multidrug-resistant, and environmentally resilient emerging UPEC clone.
Conclusions
This study highlights the convergence of virulence, AMR, and environmental adaptability in an ST131-H30 UPEC strain. The findings underscore the critical need for comprehensive genomic surveillance, infection control strategies to mitigate the public health impact of MDR E. coli.
{"title":"Genomic insights into a multidrug-resistant uropathogenic Escherichia coli ST131-H30 strain associated with a fatal healthcare-associated infection","authors":"Samara Sant’Anna de Oliveira , Camille Alves Brito de Moura , Kaylanne Montenegro , Thereza Cristina da Costa Vianna , Ana Paula Alves do Nascimento , Gerson Gatto de Azeredo Coutinho , Hosana Dau Ferreira de Souza , Claudia Gladys Flores Sejas , Alexander Machado Cardoso , Kayo Bianco , Maysa Mandetta Clementino","doi":"10.1016/j.jgar.2025.12.008","DOIUrl":"10.1016/j.jgar.2025.12.008","url":null,"abstract":"<div><h3>Objective</h3><div>Uropathogenic Escherichia coli (UPEC) poses a significant public health challenge due to increasing antimicrobial resistance (AMR) and severe infections. This study aimed to investigate the genetic heterogeneity and AMR mechanisms of a clinical UPEC strain associated with a fatal healthcare-associated infection.</div></div><div><h3>Methods</h3><div>Whole-genome sequencing (WGS) was performed on a multidrug-resistant (MDR) UPEC strain isolated from a pediatric patient by using an Illumina Miseq platform. The genome was assembled using Unicycler v0.4.8 and was annotated using the NCBI Prokaryotic Genome Annotation Pipeline (PGAP). Genomic analysis included characterisation of the resistome, virulome, and phylogenetic profile using various bioinformatics tools such as ResFinder v4.7.2, VFDB, and PubMLST.</div></div><div><h3>Results</h3><div>The isolate has a genome with a size of 4,681,240 bp, a GC content of 50.60% and harbour seven plasmids. Genomic analysis revealed multiple genetic determinants contributing to a multidrug-resistant profile, including efflux systems, enzymatic target alterations, and antibiotic transporter modifications. Adhesin genes (fimH, afaA-D, lpfA, fdeC, csgA), hemolysins (hlyE, hlyF), iron acquisition systems (iucC, iutA, sitA), and genes related to antimicrobial peptide degradation (ompT, traJ) and colicin production (cma, cvaC) were identified. Resistance to heavy metals (tellurium, copper/silver, arsenic) was also detected. These findings characterise the isolate as a highly virulent, multidrug-resistant, and environmentally resilient emerging UPEC clone.</div></div><div><h3>Conclusions</h3><div>This study highlights the convergence of virulence, AMR, and environmental adaptability in an ST131-H30 UPEC strain. The findings underscore the critical need for comprehensive genomic surveillance, infection control strategies to mitigate the public health impact of MDR <em>E. coli.</em></div></div>","PeriodicalId":15936,"journal":{"name":"Journal of global antimicrobial resistance","volume":"46 ","pages":"Pages 175-178"},"PeriodicalIF":3.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145774901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Studies of carbapenem-resistant Pseudomonas aeruginosa (CRPA)-harbouring OXA-48-like carbapenemases are rare. The study aimed to report the emergence and characterization of a novel high-risk clone of CRPA-harbouring OXA-48-like from India.
Methods
Identification, AST, phenotypic detection of carbapenemases and WGS using Ion-Torrent-S5 platform were carried out. Analyses included ResFinder, VFDB, MLST, PAst, Phastest and CRISPR/Cas. SNP-based phylogenetic analysis with global OXA-48-like-harbouring CRPA genomes was carried out by CSI Phylogeny and iTOL for visualization.
Results
The clinical MDR strain of CRPA AMRIR00655 belonged to a novel sequence type ST5217 and serotype O11. Phenotypic tests followed by WGS revealed the presence of dual carbapenemases, OXA-181 (serine-carbapenemase) and VIM-2 (zinc-carbapenemase), both located on chromosome. blaOXA-181 resides between chromosomal genes encoding RodZ and PAP2 in P. aeruginosa, confirming chromosomal integration.4,261 bp of blaOXA-181-bearing contig-DNA showed 100% homology to K. pneumoniae plasmid pKP3-A. ISEcp1 was present on upstream and on downstream, △lysR, △ereA and repA genes were detected. blaVIM-2 was located within class 1 integron along with aacC6-II, dfrB5, aac(3)-Id, tniC in surrounding regions and 13,242 bp showing 100% identity to P. aeruginosa chromosome. Presence of other ARGs (blaPAO, blaOXA-488,aph(3′')-Ib, aph(6)-Id, crpP, catB7, fosA, sul2) and efflux-pump genes might explain its MDR phenotype. Virulence factors including T3SS (PscF, PopB, PopD, PcrV) and its effectors (ExoT, ExoU, ExoY) indicated the pathogenic potential of ST5217. Core genome analysis showed that ST5217 was closest with other high-risk clones ST1339 and ST773-harbouring blaOXA-48-like.
Conclusions
To the best of our knowledge, this is the first report of blaOXA-181-harbouring novel high-risk clone of CRPA ST5217/ExoU+/O11 in India which emphasises the spread of OXA-181 among bacteria other than Enterobacteriaceae-family and warrant close monitoring.
{"title":"Genomic analysis of a novel high-risk ST5217/ExoU+/O11 clone of carbapenem-resistant OXA-181- and VIM-2-producing Pseudomonas aeruginosa in India","authors":"Subhasree Roy , Souvik Nandy , Daichi Morita , Ranjan Kumar Nandy , Balaji Veeraraghavan , Kamini Walia , Santasabuj Das , Sulagna Basu","doi":"10.1016/j.jgar.2025.12.002","DOIUrl":"10.1016/j.jgar.2025.12.002","url":null,"abstract":"<div><h3>Objectives</h3><div>Studies of carbapenem-resistant <em>Pseudomonas aeruginosa</em> (CRPA)-harbouring OXA-48-like carbapenemases are rare. The study aimed to report the emergence and characterization of a novel high-risk clone of CRPA-harbouring OXA-48-like from India.</div></div><div><h3>Methods</h3><div>Identification, AST, phenotypic detection of carbapenemases and WGS using Ion-Torrent-S5 platform were carried out. Analyses included ResFinder, VFDB, MLST, PAst, Phastest and CRISPR/Cas. SNP-based phylogenetic analysis with global OXA-48-like-harbouring CRPA genomes was carried out by CSI Phylogeny and iTOL for visualization.</div></div><div><h3>Results</h3><div>The clinical MDR strain of CRPA AMRIR00655 belonged to a novel sequence type ST5217 and serotype O11. Phenotypic tests followed by WGS revealed the presence of dual carbapenemases, OXA-181 (serine-carbapenemase) and VIM-2 (zinc-carbapenemase), both located on chromosome. <em>bla</em><sub>OXA-181</sub> resides between chromosomal genes encoding RodZ and PAP2 in <em>P. aeruginosa</em>, confirming chromosomal integration<em>.</em>4,261 bp of <em>bla</em><sub>OXA-181</sub>-bearing contig-DNA showed 100% homology to <em>K. pneumoniae</em> plasmid pKP3-A. IS<em>Ecp1</em> was present on upstream and on downstream, △<em>lysR,</em> △<em>ereA</em> and <em>repA</em> genes were detected. <em>bla</em><sub>VIM-2</sub> was located within class 1 integron along with <em>aacC6-II, dfrB5, aac(3)-Id, tniC</em> in surrounding regions and 13,242 bp showing 100% identity to <em>P. aeruginosa</em> chromosome. Presence of other ARGs (<em>bla</em><sub>PAO</sub>, <em>bla</em><sub>OXA-488,</sub> <em>aph(3′')-Ib, aph(6)-Id, crpP, catB7, fosA, sul2</em>) and efflux-pump genes might explain its MDR phenotype. Virulence factors including T3SS (PscF, PopB, PopD, PcrV) and its effectors (ExoT, ExoU, ExoY) indicated the pathogenic potential of ST5217. Core genome analysis showed that ST5217 was closest with other high-risk clones ST1339 and ST773-harbouring <em>bla</em><sub>OXA-48-like</sub>.</div></div><div><h3>Conclusions</h3><div>To the best of our knowledge, this is the first report of <em>bla</em><sub>OXA-181</sub>-harbouring novel high-risk clone of CRPA ST5217/ExoU+/O11 in India which emphasises the spread of OXA-181 among bacteria other than Enterobacteriaceae-family and warrant close monitoring.</div></div>","PeriodicalId":15936,"journal":{"name":"Journal of global antimicrobial resistance","volume":"46 ","pages":"Pages 158-161"},"PeriodicalIF":3.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145742985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tuberculosis (TB) remains a leading infectious cause of death, with drug-resistant TB threatening control gains worldwide Rapid, accurate prediction of resistance to first-line agents is essential to guide therapy.
The objective of this meta-analysis is to evaluate the diagnostic performance of machine learning (ML) algorithms trained on genomic data for predicting phenotypic resistance to the antitubercular drugs.
Methods
We searched 4 databases for original studies applying ML to whole-genome or targeted sequencing for resistance prediction against rifampicin (RIF), isoniazid (INH), ethambutol (EMB), streptomycin (STM), and other routinely tested drugs. Random-effects meta-analyses (REML) pooled sensitivity and specificity; Area Under Curve (AUC) was meta-analysed after logit transformation. Publication bias was examined via funnel plots plus Egger’s and Begg’s tests with trim-and-fill adjustment.
Results
Seven eligible studies were included. Pooled performance was strongest for RIF and INH (RIF: sensitivity 0.90, specificity 0.95; INH: sensitivity 0.88, specificity 0.93). EMB and STM showed lower sensitivities despite reasonable AUCs. Forest plots for AUC (including logit scale), sensitivity, and specificity demonstrated drug-wise variation. Across studies, specificity (mean ≈ 0.92) exceeded sensitivity (mean ≈ 0.75). Bias diagnostics revealed marked funnel plot asymmetry; trim-and-fill imputation added 22, 29, and 23 studies for AUC, sensitivity, and specificity, respectively, yielding adjusted pooled estimates of ∼0.89 (AUC), 0.70 (sensitivity), and 0.93 (specificity).
Conclusions
ML models trained on genomic data demonstrate high diagnostic accuracy and robust discriminative ability for predicting first-line drug resistance—particularly for RIF and INH—although sensitivity remains variable across drugs and model types. Standardized external validation and calibration are needed before broad clinical deployment.
{"title":"Integrative machine learning approaches with genomic data for predicting antitubercular drug resistance: A systematic review and meta-analysis","authors":"Rohan Shrivastava , Kashmi Sharma , Somesh Mishra , Poonam Parihar , Gobardhan Das , Khushhali Menaria Pandey , Anand Kumar Maurya , Vineet Kumar Sharma , Anamika Mishra , Sandeep Kushwaha , Rekha Khandia , Kuldeep Singh Yadav , Anvita Gupta Malhotra , Amit Agrawal , Jitendra Singh , Megha Katare Pandey","doi":"10.1016/j.jgar.2025.11.021","DOIUrl":"10.1016/j.jgar.2025.11.021","url":null,"abstract":"<div><h3>Objectives</h3><div>Tuberculosis (TB) remains a leading infectious cause of death, with drug-resistant TB threatening control gains worldwide Rapid, accurate prediction of resistance to first-line agents is essential to guide therapy.</div><div>The objective of this meta-analysis is to evaluate the diagnostic performance of machine learning (ML) algorithms trained on genomic data for predicting phenotypic resistance to the antitubercular drugs.</div></div><div><h3>Methods</h3><div>We searched 4 databases for original studies applying ML to whole-genome or targeted sequencing for resistance prediction against rifampicin (RIF), isoniazid (INH), ethambutol (EMB), streptomycin (STM), and other routinely tested drugs. Random-effects meta-analyses (REML) pooled sensitivity and specificity; Area Under Curve (AUC) was meta-analysed after logit transformation. Publication bias was examined via funnel plots plus Egger’s and Begg’s tests with trim-and-fill adjustment.</div></div><div><h3>Results</h3><div>Seven eligible studies were included. Pooled performance was strongest for RIF and INH (RIF: sensitivity 0.90, specificity 0.95; INH: sensitivity 0.88, specificity 0.93). EMB and STM showed lower sensitivities despite reasonable AUCs. Forest plots for AUC (including logit scale), sensitivity, and specificity demonstrated drug-wise variation. Across studies, specificity (mean ≈ 0.92) exceeded sensitivity (mean ≈ 0.75). Bias diagnostics revealed marked funnel plot asymmetry; trim-and-fill imputation added 22, 29, and 23 studies for AUC, sensitivity, and specificity, respectively, yielding adjusted pooled estimates of ∼0.89 (AUC), 0.70 (sensitivity), and 0.93 (specificity).</div></div><div><h3>Conclusions</h3><div>ML models trained on genomic data demonstrate high diagnostic accuracy and robust discriminative ability for predicting first-line drug resistance—particularly for RIF and INH—although sensitivity remains variable across drugs and model types. Standardized external validation and calibration are needed before broad clinical deployment.</div></div>","PeriodicalId":15936,"journal":{"name":"Journal of global antimicrobial resistance","volume":"46 ","pages":"Pages 148-157"},"PeriodicalIF":3.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145756841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Antimicrobial resistance (AMR) is a pressing global health challenge, particularly affecting low- and middle-income countries. This study aims to evaluate the spread of AMR both across time and across different regions of the world.
Methods
We analysed clinical isolates from 65 countries. A country-specific time-series forecasting (i.e. seasonal autoregressive integrated moving average (SARIMA), long short-term memory (LSTM), and seasonal autoregressive integrated moving average-LSTM hybrid models) were performed for Acinetobacter baumannii in Argentina (2004–2030) as a case study to demonstrate model applicability for national-level prediction. Moreover, interrupted time series regression was applied to predict antibiotic-resistance trends and assess the global impact of national action plans.
Results
Southeast Asia and Africa exhibited the highest AMR burdens, with Indonesia (0.65), Egypt (0.52), and Malawi (0.49) having the highest resistance scores. An income-based gradient was observed across key pathogens, third-generation cephalosporin and carbapenem-resistant Escherichia coli, Klebsiella pneumoniae, and A. baumannii were significantly more prevalent in low- and middle-income countries. Gender-wise analysis revealed significantly higher resistance rates in males across most antibiotics, especially levofloxacin. Age-stratified analyses revealed higher resistance in elderly populations, particularly to fluoroquinolones and β-lactams. Forecasting for A. baumannii in Argentina (2004–2030) indicated a continued upward resistance across β-lactam and fluoroquinolones, with LSTM achieving the lowest root mean square error across five antibiotics. The interrupted time series revealed a prenational action plan decline but no significant postimplementation change.
Conclusion
This study provides a comprehensive data-driven framework to monitor and forecast AMR, evaluate policy interventions, and, hence, suggest targeted interventions and strategies for each income group and region, moving beyond the one-size-fits-all approach.
{"title":"Global prediction of antimicrobial resistance trends using statistical and machine learning models: Evaluating national action plan policy impacts through interrupted time series analysis","authors":"Linta Khalid , Kashif Saleem , Saima Mushtaq , Iltaf Hussain , Zamir Hussain , Zainab Hussain , Rehan Zafar Paracha , Amjad Khan , Jie Chang , Yu Fang , Imran Sajid","doi":"10.1016/j.jgar.2025.11.022","DOIUrl":"10.1016/j.jgar.2025.11.022","url":null,"abstract":"<div><h3>Objective</h3><div>Antimicrobial resistance (AMR) is a pressing global health challenge, particularly affecting low- and middle-income countries. This study aims to evaluate the spread of AMR both across time and across different regions of the world.</div></div><div><h3>Methods</h3><div>We analysed clinical isolates from 65 countries. A country-specific time-series forecasting (i.e. seasonal autoregressive integrated moving average (SARIMA), long short-term memory (LSTM), and seasonal autoregressive integrated moving average-LSTM hybrid models) were performed for <em>Acinetobacter baumannii</em> in Argentina (2004–2030) as a case study to demonstrate model applicability for national-level prediction. Moreover, interrupted time series regression was applied to predict antibiotic-resistance trends and assess the global impact of national action plans.</div></div><div><h3>Results</h3><div>Southeast Asia and Africa exhibited the highest AMR burdens, with Indonesia (0.65), Egypt (0.52), and Malawi (0.49) having the highest resistance scores. An income-based gradient was observed across key pathogens, third-generation cephalosporin and carbapenem-resistant <em>Escherichia coli, Klebsiella pneumoniae</em>, and <em>A. baumannii</em> were significantly more prevalent in low- and middle-income countries. Gender-wise analysis revealed significantly higher resistance rates in males across most antibiotics, especially levofloxacin. Age-stratified analyses revealed higher resistance in elderly populations, particularly to fluoroquinolones and β-lactams. Forecasting for <em>A. baumannii</em> in Argentina (2004–2030) indicated a continued upward resistance across β-lactam and fluoroquinolones, with LSTM achieving the lowest root mean square error across five antibiotics. The interrupted time series revealed a prenational action plan decline but no significant postimplementation change.</div></div><div><h3>Conclusion</h3><div>This study provides a comprehensive data-driven framework to monitor and forecast AMR, evaluate policy interventions, and, hence, suggest targeted interventions and strategies for each income group and region, moving beyond the one-size-fits-all approach.</div></div>","PeriodicalId":15936,"journal":{"name":"Journal of global antimicrobial resistance","volume":"46 ","pages":"Pages 214-226"},"PeriodicalIF":3.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145800582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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