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PubMed2026

Detection of antibiotic heteroresistance in clinical microbiology: current and emerging methodologies.

BACKGROUND: Antibiotic heteroresistance (HR) is characterised by the coexistence of susceptible and resistant subpopulations within an apparently isogenic bacterial isolate. Because routine antimicrobial susceptibility testing (AST) primarily assesses the dominant population, HR may escape detection, potentially leading to discrepancies between laboratory susceptibility categorisation and the underlying bacterial population structure. OBJECTIVES: To provide a critical and practice-oriented evaluation of current and emerging methodologies for HR detection and to discuss their strengths, limitations, and potential for clinical implementation. SOURCES: Narrative review based on PubMed searches, complemented by screening of key reference lists and relevant EUCAST and CLSI documents. Peer-reviewed literature was prioritised. CONTENT: Phenotypic approaches, particularly population analysis profiling, remain the reference method for HR definition, but their labour-intensive workflows, long turnaround times, and limited standardisation restrict routine implementation. Alternative strategies, including modified AST assays, metabolic assays, and single-cell platforms, offer gains in speed or throughput but require broader validation. Molecular approaches such as quantitative PCR, droplet digital PCR, targeted deep sequencing, and whole-genome sequencing improve detection of minority resistance determinants. Emerging computational frameworks, including machine learning models integrating phenotypic and genomic data, represent a promising frontier for scalable HR prediction. IMPLICATIONS: Available evidence supports the clinical relevance of HR, although its association with adverse outcomes varies across bacterial species and antibiotic classes. Harmonised methodologies and clinically validated interpretive criteria are needed to support integration of HR assessment into routine diagnostics. Prospective multicentre studies and further standardisation, including engagement with EUCAST and CLSI, will be important to advance clinical implementation.

Antimicrobial resistance↗
PubMed2026

Clinical and Microbiological Characteristics of Invasive Group A Streptococcus Infection: Four Case Series of Re-Emerging Pathogens.

INTRODUCTION: Group A Streptococcus (GAS), particularly the M1UK lineage, has re-emerged as a major global public health concern following the COVID-19 pandemic, with a rise in invasive GAS (iGAS) and streptococcal toxic shock syndrome (STSS). Although STSS is under national surveillance in Japan, comprehensive molecular monitoring of iGAS infections remains limited, and the clinical characteristics of M1UK-associated iGAS have not been fully elucidated. METHODS: We retrospectively reviewed four consecutive iGAS cases requiring intensive care between March and May 2024. Detailed clinical, microbiological, and genomic investigations were performed to characterize the causative strains and their associated virulence profiles. RESULTS: All patients required respiratory and/or circulatory support with surgical debridement. Three cases involved necrotizing fasciitis, and one involved intra-abdominal infection secondary to ovarian tumor rupture. All four patients received penicillin G and clindamycin as definitive antimicrobial therapy, with two developing severe drug-related adverse events. Genotypic analysis identified three isolates as emm1 strains, including two M1UK lineage strains. The two M1UK isolates commonly harbored multiple superantigen genes. All isolates remained susceptible to β-lactam, clindamycin, and macrolide antibiotics. CONCLUSION: This case series documents the identification of the M1UK lineage among critically ill patients with iGAS infections in Japan. Our findings support the need for continued molecular surveillance while reinforcing the importance of prompt surgical source control and appropriate antimicrobial therapy in the management of severe iGAS.

Group A Streptococcus↗
PubMed2025

Clinical and Microbiological Insights into Caseous Lymphadenitis in Sheep and Goats in Khorasan Razavi, Iran.

INTRODUCTION: Caseous lymphadenitis (CLA), a chronic bacterial disease caused by Corynebacterium pseudotuberculosis, significantly impacts small-ruminant health and productivity worldwide, causing economic losses through reduced wool and milk yields, reproductive issues, and carcass condemnation. Despite its importance, CLA prevalence and microbial dynamics remain under explored in Iran, where small ruminants are vital to rural economies. This study assessed the prevalence, clinical manifestations, and bacteriological profile of CLA in Khorasan Razavi Province, northeast Iran, to inform regional control strategies and address potential zoonotic risks. MATERIALS & METHODS: We examined 15 flocks totaling 4,733 animals (4,640 sheep, 93 goats) through clinical inspections and microbiological analysis of pus samples from affected lymph nodes. RESULTS: The results revealed a lymphadenitis prevalence of 11.59% (95% CI, 10.58%, 12.66%), with 8.62% of sheep (400/4640) and 8.60% of goats (8/93) affected, varying across flocks from 0% to 28.57%. Submandibular lymph nodes were most commonly affected (51.35%), followed by retropharyngeal (18.02%) and parotid (15.32%) nodes, with peak incidence in the 2-3-year age group (38.24%), likely linked to shearing practices. Bacteriological analysis of 102 pus samples identified C. pseudotuberculosis in 19.6% (20/102) of cases, characterized by small, dry, white colonies with β-hemolysis on Columbia blood agar. A diverse microbial profile included Actinobacillus spp. (7.8%), Trueperella pyogenes (3.9%), and novel isolates like Acinetobacter spp. and Yersinia spp. (1.0% each), with 43.14% of samples sterile, suggesting chronicity or sampling challenges. CONCLUSION: These findings indicate CLA etiology is complex, extending beyond a single pathogen and influenced by local husbandry practices. The study underscores CLA's economic burden and zoonotic potential, given rare but documented human cases. Integrated control measures-enhanced molecular diagnostics, recombinant phospholipase D (PLD) vaccine trials, and improved biosecurity-are urgently needed. Future research should prioritize genomic strain typing and environmental reservoir analysis to refine CLA management in Northeast Iran, offering insights applicable to similar agroecosystems globally.

Animals↗
PubMed2026

Conference report: the third Bacterial Genome Sequencing Pan-European Network conference.

The third Bacterial Genome Sequencing Pan-European Network conference, held in Engelberg, Switzerland (12-15 January 2026), brought together experts from six European countries to discuss the implementation of bacterial genome sequencing in clinical microbiology and public health. Key themes included regulatory frameworks (In Vitro Diagnostic Regulation, General Data Protection Regulation), standardization, quality control, data sharing, economic evaluation, and the integration of artificial intelligence and long-read sequencing into diagnostic workflows. Across presentations, panel discussions, and workshops, participants emphasized that successful implementation of genome sequencing requires more than technical capacity: it depends on robust validation, sustainable funding, interoperable data standards, ethical governance, and interdisciplinary collaboration. The meeting highlighted that sequencing should remain question-driven and clinically meaningful, balancing cost, turnaround time, and public health impact. Overall, the conference reinforced the need for coordinated European efforts to advance responsible, standardized, and sustainable genomic surveillance and diagnostics.

bacterial genome sequencing↗
PubMed2026

Rapid diagnosis of common, undetected, and uncultivable bloodstream infections from positive blood cultures using Oxford Nanopore sequencing: a metagenomic pipeline analysis.

BACKGROUND: Metagenomic sequencing can potentially transform clinical microbiology by enabling rapid pathogen identification and antimicrobial resistance (AMR) prediction in critically ill patients with bloodstream infections. However, the clinical use of metagenomic sequencing has been constrained by its speed, accuracy, and technical feasibility. Our aim was to develop and evaluate a direct-from-positive blood culture workflow using Oxford Nanopore sequencing that overcomes these limitations and delivers rapid, accurate results. METHODS: In this metagenomic pipeline analysis, 211 positive (130 aerobic and 81 anaerobic) and 62 negative (30 aerobic and 32 anaerobic) randomly selected blood cultures were processed from Oxford University Hospitals for comparing species identification, AMR detection, and time-to-result against standard culture-based diagnostics performed by the hospital's routine microbiology laboratory. Species prediction was performed using Kraken2 with a comprehensive standard database, applying heuristic and random forest classification models. Additionally, we benchmarked AMR classification tools and databases, including ResFinder, CARD, and NCBI AMRFinderPlus. FINDINGS: Across all samples, our method achieved 97% sensitivity and 94% specificity for species identification compared with that of routine culture and matrix-assisted laser desorption ionisation time-of-flight-based diagnostics; both sensitivity and specificity increased to 100% after adjudication of plausible additional infections. We detected 19 additional infections (13 polymicrobial, five previously unidentifiable, and one in a culture-negative sample) and delivered species identification results within 3 h 20 min (IQR 3 h 7 min-3 h 27 min), approximately 10 h earlier than routine diagnostic methods. For the ten most common clinically relevant pathogens, our method yielded AMR results 20 h earlier than current antimicrobial susceptibility testing, with an overall sensitivity of 88% and specificity of 93%. Performance varied by species. For Staphylococcus aureus, the AMR prediction sensitivity was 100% and specificity was 99%, and for Escherichia coli, the prediction sensitivity was 91% and specificity was 94%. INTERPRETATION: These findings show that metagenomic sequencing has the potential to rapidly and comprehensively detect pathogens and AMR in bloodstream infections. Integration into clinical practice could help to close diagnostic gaps, reduce empirical antibiotic use, and enable rapid targeted treatment. Nonetheless, improvements in AMR prediction for some species and drugs, along with further multisite validation, are required before clinical implementation. FUNDING: National Institute for Health Research (NIHR) Oxford Biomedical Research Centre.

Humans↗
PubMed2026

[Microbiological Characterization of Exacerbations in Severe Asthma and Their Impact on Therapeutic Decision-Making].

INTRODUCTION: Severe asthma (SA) exacerbations impose a substantial healthcare burden. Microbiological characterization using molecular techniques may improve pathogen identification and contribute to a more individualized therapeutic approach. OBJECTIVE: To characterize the microbiological profile of exacerbations in patients with severe asthma and to analyze the prescription patterns for antibiotics (ATB) and systemic corticosteroids (SC). METHODS: This retrospective observational study was conducted in a Severe Asthma Unit. A total of 103 exacerbations were investigated using conventional microbiological methods and multiplex polymerase chain reaction (FilmArray™) performed on respiratory samples. Bacterial findings were classified according to operational criteria compatible with infection or colonization based on genomic load and culture results. Associations between clinical, microbiological, and therapeutic variables were explored using univariate analyses. RESULTS: Microbiological detection was achieved in 78.6% of exacerbations. Viruses were identified in 59.2% of episodes, with rhinovirus representing the predominant pathogen (62.3% of viral detections). Bacteria were identified in 53.4% of exacerbations (H. influenzae 36,6%), frequently in association with viral coinfection. Bronchiectasis was associated with a higher probability of bacterial detection (OR 2.50; p = 0.031). ATB and SC were prescribed in 61.2% and 44.6% of exacerbations, respectively, with frequent use of combination therapy. No significant differences in overall microbiological detection rates were observed according to biologic therapy status. Considerable microbiological variability was observed across recurrent exacerbations in the same patient. CONCLUSIONS: Microbiological findings were common during severe asthma exacerbations, with respiratory viruses, particularly rhinovirus, being the most frequently identified pathogens. Bronchiectasis was associated with higher rates of bacterial detection and ATB use. The marked variability observed between episodes supports the potential value of individualized microbiological assessment during exacerbations and warrants prospective studies aimed at optimizing therapeutic decision-making.

Biologic therapies.↗
PubMed2026

Machine learning to differentiate colonization from infection in multidrug-resistant Gram-negative bacteria: implications for further research.

PURPOSE OF REVIEW: Machine learning has emerged as a promising tool to support antimicrobial decision-making in infectious diseases. In colonized patients, distinguishing multidrug-resistant Gram-negative bacteria (MDR-GNB) colonization from true infection remains a major clinical challenge, as both delayed appropriate therapy in severe infections and unnecessary broad-spectrum antimicrobial use may adversely affect patient outcomes and antimicrobial stewardship. This review discusses the current evidence on machine learning models for predicting or detecting MDR-GNB infection in colonized patients, highlights key methodological limitations of the available literature, and outlines future research priorities. RECENT FINDINGS: Current evidence specifically evaluating machine learning models beyond logistic regression in MDR-GNB-colonized patients remains limited. Overall, while machine learning may achieve encouraging discriminatory performance, important methodological limitations persist. Most notably, predictive models are frequently developed in heterogeneous populations that do not reflect the clinically relevant populations of colonized patients in which treatment decisions are made. Furthermore, improvements in predictive performance remain modest, possibly reflecting limited sample sizes and data granularity rather than insufficient algorithmic complexity. In our opinion, future advances could require multicenter datasets enriched with longitudinal clinical, microbiological, and genomic information, together with automated feature extraction from electronic health records. SUMMARY: The main challenge for machine learning in predicting MDR-GNB infection in colonized patients may lie not in developing increasingly sophisticated algorithms, but in generating clinically representative datasets and adopting rigorous methodological standards for model development, validation, calibration, and implementation. Future research should prioritize clinically meaningful target populations and demonstrate improvements in patient outcomes and antimicrobial stewardship beyond conventional measures of predictive performance.

antimicrobial resistance↗
PubMed2026

Evaluation of carbapenem inactivation method-based phenotypic assays for the detection of GES-type carbapenemases in Enterobacterales, Pseudomonas aeruginosa, and Acinetobacter baumannii.

UNLABELLED: Detection of GES-type carbapenemases remains challenging because of their low prevalence and frequently weak hydrolytic activity against carbapenems. Carbapenem inactivation method (CIM)-based assays are widely used as phenotypic screening tools for carbapenemase detection; however, their performance in large collections of GES producers has not been systematically evaluated. We assessed the performance of CIM, modified CIM (mCIM), and CIM-Tris in a diverse collection of GES-producing clinical isolates, including 110 Enterobacterales and 108 Pseudomonas aeruginosa, recovered from Spanish hospitals (2010-2024), and 10 Acinetobacter baumannii isolates, mostly obtained from a hospital in Egypt. Whole-genome sequencing was carried out for species confirmation and resistome analysis. Meropenem MICs were determined by broth microdilution. Overall, 92.1% of isolates were GES-carbapenemase producers (CP), whereas 7.9% expressed GES-type extended-spectrum β-lactamases (ESBLs). In Enterobacterales (predominantly carrying blaGES-6), mCIM improved sensitivity compared with CIM (63.6% vs 40.0%), although many isolates remained undetected due to low meropenem MICs (MIC50, 0.5 µg/mL). In CP-P. aeruginosa (mainly blaGES-5), CIM, mCIM, and CIM-Tris showed sensitivities of 89.1%, 94.6%, and 100%, respectively; however, CIM-Tris yielded false-positive results in 50% of non-CP isolates (mostly blaGES-1 producers). Meropenem MICs in P. aeruginosa were higher (MIC50, >32 µg/mL). In A. baumannii, CIM-Tris improved sensitivity compared with CIM (100% vs 25.0%). These findings indicate that CIM-based methods can detect GES-type carbapenemases, but performance varies according to bacterial species and GES variant, and reduced specificity may occur in isolates producing GES-type ESBLs. Complementary molecular testing may therefore be necessary to ensure accurate detection of GES-type carbapenemases in routine clinical laboratories. IMPORTANCE: GES-type carbapenemases represent an important but underrecognized diagnostic challenge due to their low global prevalence, heterogeneous hydrolytic activity, and the limited performance data available for routine phenotypic detection methods. Although CIM-based assays are widely implemented in clinical microbiology laboratories for carbapenemase screening, their performance against GES-producing organisms has not been comprehensively evaluated across different bacterial genera and GES variants. In this study, we evaluated the performance of CIM, modified CIM (mCIM), and CIM-Tris in a large multicenter collection of well-characterized GES-producing clinical isolates, including Enterobacterales, Pseudomonas aeruginosa, and Acinetobacter baumannii. Our findings demonstrate substantial variability in assay performance according to bacterial species and GES variant. Notably, mCIM improved sensitivity among Enterobacterales with low meropenem MICs, whereas CIM-Tris achieved excellent sensitivity in P. aeruginosa and A. baumannii but at the expense of reduced specificity in isolates producing GES-type ESBLs. To the best of our knowledge, this is the first study directly comparing multiple CIM-based approaches in such a large and taxonomically diverse collection of GES-producing isolates.

beta-Lactamases↗
PubMed2026

Update on novel, validly published, and included bacterial taxa derived from human clinical specimens and taxonomic revisions published in 2025.

This review summarizes novel taxon designations ascribed to prokaryotes derived from human primary clinical material during calendar year 2025, as well as proposed revisions to existing taxonomy. Major activity took place in the Streptococcus genus, as more than one dozen novel species were validly and effectively published, with two of these later classified as synonyms of Streptococcus thalassemiae. Moreover, whole genome sequencing and phylogenetic investigation of Streptococcus mitis group organisms resulted in a proposal to designate five species-level Streptococcus spp. taxa as Streptococcus mitis and an additional taxon as Streptococcus oralis subsp. dentisani. More than one dozen taxa were newly included in order Enterobacterales in 2025. Select novel taxa within genera Providencia and Enterobacter commonly possessed genotypes that conferred resistance to carbapenem and/or higher-generation cephem agents. Stenotrophomonas muris sp. nov. and Terrisporobacter muris sp. nov., initially characterized in gnotobiotic murine systems within the past 4 years, had clinical significance in human infection that was demonstrated in primary literature. The vast majority of the more than 70 novel obligate anaerobic taxa were derived from microbiome studies and had little ascribed clinical significance. Four novel obligate anaerobic Gram-negative taxa were shown to be of greater abundance in persons with Parkinson's disease than in those without. Updates to taxa previously published in the Journal of Clinical Microbiology compendia reveal that several could serve as reservoirs for multiple antimicrobial resistance determinants. One example is the non-glucose fermentative Gram-negative bacillus Pseudomonas juntendi.

human clinical specimens↗
PubMed2026

Dual β-lactam therapy against high-risk Pseudomonas aeruginosa isolates: a dynamic in-vitro infection model study integrating population genomics with quantitative systems pharmacology modelling and simulations.

BACKGROUND: Pseudomonas aeruginosa has an extraordinary capacity for resistance emergence during treatment, even with newer antipseudomonals. There is a gap in understanding how resistance mechanisms affect the time-course of bacterial response to these newer agents. Traditional approaches for predicting pathogen response to an antibiotic do not apply to combination therapy. We aimed to develop a modelling framework to predict treatment response based on resistome information, using isolates of the worldwide-disseminated high-risk clone sequence type (ST) 235 and β-lactam antibiotics as the example. METHODS: In this hollow-fibre in-vitro infection study, we used three extensively drug-resistant ST235 clinical isolates from the national collection of the Clinical Microbiology Department of the Hospital Son Espases (Palma de Mallorca, Spain) that were hospital-acquired, were isolated following routine microbiological procedures from different patients between 2017 and 2022, were susceptible to ceftolozane-tazobactam, and had different levels of meropenem resistance. The selected isolates (ST235-05, ST235-09, and ST235-10) showed classical β-lactam resistance mechanisms pre-treatment. The isolates were investigated in 240-h dynamic hollow-fibre in-vitro infection models (HFIMs). The studies exposed the isolates to pharmacokinetic profiles of ceftolozane-tazobactam (simulating 1 g of ceftolozane and 0·5 g of tazobactam as a 3-h infusion every 8 h) and meropenem (simulating 6 g per day continuous infusion) as observed in hospitalised patients, as monotherapy and in combination. Treatment response was assessed through the quantification of the time-courses of viable total and resistant bacteria. Whole-genome sequencing identified the mechanisms of emerging resistance. A quantitative systems pharmacology (QSP) approach was used to model total and resistant bacterial counts and corresponding pharmacokinetic data from the HFIM. Monte Carlo simulations were used to predict treatment responses in 1000 virtual infected patients treated with ceftolozane-tazobactam and meropenem as monotherapies or in combination over 10 days. FINDINGS: In the HFIMs, each antibiotic alone amplified resistance by approximately 48 h for all isolates; that is, monotherapies resulted in a higher concentration of resistant bacteria compared with the control treatment at the respective time, except ceftolozane-tazobactam against ST235-10. Combination of ceftolozane-tazobactam and meropenem was synergistic (bacterial counts ≥2 log10 colony forming units [CFU] per mL lower than the best performing monotherapy and initial inoculum) against all isolates and suppressed resistance. Against ST235-10, ceftolozane-tazobactam monotherapy reduced counts to less than 1 log10 CFU per mL from 192 h onwards, whereas the combination reached less than 1 log10 CFU per mL by 24 h. Across strains, population genomics confirmed monotherapy failures were associated with emerging resistance mechanisms (ceftolozane-tazobactam: ampC Ω-loop mutations; meropenem: ftsl mutation). The developed QSP model incorporated baseline resistance mechanisms and those emerging in resistant mutant subpopulations. The model explained and predicted the monotherapy failures involving amplification of these subpopulations, and synergistic killing and resistance suppression by the combination. Simulations using the model predicted bacterial regrowth above the initial inoculum for more than 90% of patients after 0 to approximately 3 days for meropenem monotherapy across all strains and for ceftolozane-tazobactam monotherapy against ST235-05 and ST235-09. For ceftolozane-tazobactam monotherapy against ST235-10, regrowth was predicted for approximately 30% of patients. In contrast, the simulations predicted sustained bacterial killing of at least 2 log10 CFU per mL compared with the initial inoculum by the combination for more than 89% of patients across all strains. INTERPRETATION: To our knowledge, this model is the first to characterise and predict the time-course of responses of clinical isolates to antibiotics only by the resistance mechanisms present and their complex interplay, representing a step towards pathogen-specific, personalised medicine. FUNDING: Australian National Health and Medical Research Council.

Pseudomonas aeruginosa↗
PubMed2026

Global reach and sustained engagement of a structured digital education program in medical mycology: an observational analysis of the 2025 ESCMID-EFISG webinar series.

OBJECTIVES: Evaluate the 2025 European Society of Clinical Microbiology and Infectious Diseases-European Fungal Infection Study Group webinar series to assess digital education as a scalable, equitable model for global professional development in medical mycology. METHODS: This observational study analyzed Zoom metadata across 17 webinars (January-December 2025). Metrics included registration, unique viewers, peak concurrent views, attendance rate, and duration. RESULTS: The series recorded 4631 registrations and 1372 unique participants. Median live attendance was 199 (interquartile range [IQR] 138-269), with a 39.3% attendance rate (IQR 33.7-47.5%) and peak concurrent viewership of 165 (IQR 106-229). Median session duration was 108 minutes. Webinars engaged a median of 60 countries (range 26-89) simultaneously, spanning 128 countries globally. Faculty comprised 67 unique experts from 23 countries with balanced gender representation (52.8% men, 47.2% women), of whom 16.4% (n = 11/67) were affiliated with institutions in low- and middle-income countries. CONCLUSION: Structured digital programs achieve wide global reach and sustained engagement. Strong participation in long-form sessions supports implementing Continuing Medical Education accreditation and unrestricted on-demand access to enhance global health equity.

Antimicrobial resistance↗
PubMed2025

Global spread of Streptococcus pyogenes A genomics-supported narrative review.

Group A Streptococcus (GAS) has recently reemerged as a leading cause of both mild and severe invasive infections worldwide, with recent upsurges in invasive disease among children and adults. Notwithstanding a partial synchronicity with the COVID-19 pandemic, this rapid global dissemination of more virulent GAS lineages has been promptly detected, as well as the molecular shifts underlying the observed changes in clinical patterns. Whole-genome sequencing (WGS)-based genomic epidemiology allowed us to gain relevant insights into this upsurge as it was happening. This review integrates the canonical research publication-based approach with genomic data and metadata and identifies a subset of genomic clusters playing a major role in invasive GAS (iGAS) infections worldwide, which were named as Global Pathogenic Lineages (GPLs). The four GPLs broadly coincide with five sequence types (STs): GPL1 with ST28, GPL2 with ST15 and ST315, GPL3 with ST52, and GPL4 with ST39. While non-GPLs clusters maintain a baseline reservoir of antimicrobial-resistance and virulence genes, GPLs show varying but noteworthy resistance profiles and are frequent causes of iGAS. The integration of WGS into routine diagnostics procedures is a forthcoming improvement, aimed not only at informing tailored therapy and implementing infection control strategies, but also to perform continuous surveillance. Ongoing WGS in clinical microbiology, as a matter of fact, will provide unparalleled insights into lineage emergence, transmission dynamics, and the geographic clustering of virulence and resistance determinants.

Streptococcus pyogenes↗
PubMed2026

DNA sequencing for microbial surveillance in cystic fibrosis airways: advances, challenges, and clinical translation.

SUMMARYDNA sequencing has revolutionized microbial surveillance in cystic fibrosis (CF), transforming pathogen identification from culture-dependent to total microbial community identification using molecular-based approaches. Techniques such as 16S rRNA gene sequencing have uncovered the complexity of the CF airway microbiome, while shotgun metagenomics, metatranscriptomics, and viromics now provide strain-level, functional, and viral insights beyond bacterial identification. Despite these advances, key technical and logistical challenges remain, including the processing of high-viscosity sputum samples, overwhelming host DNA contamination, managing large data sets, and the integration of complex bioinformatic outputs into clinical workflows. Emerging innovations such as host DNA depletion protocols, targeted enrichment panels, and adaptive sampling on Oxford Nanopore platforms are helping to overcome these barriers, improving microbial recovery and sequencing efficiency. As cystic fibrosis transmembrane conductance regulator (CFTR) modulator therapies are changing the lives of people with cystic fibrosis (pwCF), sequencing offers an unprecedented opportunity to track potential microbial adaptation in response. This review investigates current advances, limitations, and translational opportunities in DNA sequencing for CF airway microbiome surveillance, highlighting how these technologies can help reshape research and clinical microbiology in the post-modulator era.

Cystic Fibrosis↗
PubMed2026

The catheterized urinary tract selects for MRR1-mediated efflux and fluconazole resistance in Candida albicans biofilms.

Catheter-associated urinary tract infections (CAUTIs) are the most common nosocomial infection in developed countries, and Candida species are among the most frequently isolated organisms. Despite this, little is known about the biology, host-pathogen interactions, or outcomes of these infections, and this has led to uncertain guidelines for clinical management of Candida CAUTIs. Here, we develop the first physiologically relevant artificial urine medium (AUM) that supports fungal growth in a manner similar to, but more consistent than, human urine samples. We demonstrate that human catheter-associated (CA) clinical isolates of C. albicans exhibit environment-dependent fluconazole resistance: many isolates determined to be susceptible by standard CLSI testing in RPMI (MIC ≤ 2 µg/mL) were fully resistant (MIC ≥ 128 µg/mL) when grown in pooled human urine or AUM, complicating clinical management, which is based on catheter exchange and fluconazole treatment. Transcriptomic profiling of biofilms formed in AUM revealed a remarkably convergent upregulation of efflux and detoxification processes across clinical isolates with diverse biofilm phenotypes. Whole-genome sequencing of the CA isolates identified variant alleles of transcriptional regulators of drug efflux, including MRR1, that have been previously associated with antifungal resistance. A competition assay confirmed that Mrr1 provides a fitness advantage in urine and AUM in a urea-dependent manner. Thus, we show that the urinary environment promotes a unique biofilm differentiation program and selects for adaptations that increase drug resistance and would be predicted to render standard treatment regimens ineffective.IMPORTANCECatheter-associated urinary tract infections are the most common nosocomial infection in the United States, and Candida albicans is one of the most frequently isolated organisms from these infections. Despite this high prevalence, few molecular studies have examined C. albicans biology in the urinary environment, and recommendations for clinical management lack robust evidence. Here, we show that clinical catheter-associated isolates of C. albicans identified as susceptible to fluconazole by standard clinical microbiology testing were resistant when grown in human or artificial urine. We identified transcriptional responses intrinsic to the urinary environment that produce this environment-specific resistance phenotype. Biofilm growth in the urinary environment induces cellular processes for efflux and detoxification. These findings suggest that standard susceptibility testing may not predict fluconazole efficacy in the urinary tract and underscore the need for niche-informed approaches to antifungal management of these common infections.

Candida albicans↗
PubMed2025

Diversity of Salmonella enterica isolates from urban river and sewage water in Blantyre, Malawi.

BACKGROUND: Salmonella enterica encompasses over 2,600 serovars, including several commonly associated with severe infection in humans. Salmonella is a major cause of sepsis in Africa; however, diagnosis requires clinical microbiology facilities. Environmental surveillance has the potential to play a role in Salmonella surveillance. METHODS: We undertook water-based environmental surveillance in Blantyre, Malawi, from 2018-2020, taking samples from rivers (87.9%), a sewage plant (8.85%) and other water sources (3.24%), isolating and storing 1,042 non-typhoidal Salmonella (NTS) isolates in this period. Of these, 341 NTS isolates were whole genome sequenced, genome quality was checked, duplicate genomes from any given sample were removed and core genome phylogeny was reconstructed. AMRFinder, PathogenWatch and SISTR were used to further investigate serovar, sequence type and antimicrobial resistance determinants. RESULTS: After quality checks, and removal of duplicate genomes, 270 NTS genomes remained for further analysis. Multiple Salmonella serovars associated with human infection were detected, of which S. Typhimurium (55/270 isolates) was the most common, including 44 of Sequence Type (ST) 313, a serovar commonly associated with severe invasive disease (iNTS). Six lineage 2 ST313 genomes possessed AMR genes predicting multidrug resistance (MDR), while 29 lineage 3 isolates contained no AMR predictive genes. PCR based detection of staG has been proposed as a diagnostic marker of S. Typhi; however, all eight genomes that contained staG identified as Salmonella enterica serovar Orion, raising concerns about the specificity of this marker as a monoplex for environmental surveillance of S. Typhi. DISCUSSION: The study identified diverse Salmonella serovars in the environment, including those reported to cause invasive disease, emphasizing the complex but potentially valuable contribution of implementing environmental surveillance for Salmonella in high burden areas lacking diagnostic microbiology capacity.

Sewage↗
PubMed2026

Employing Metagenomics Capture targeted next-generation sequencing for the etiological diagnosis of bloodstream infections.

BACKGROUND: Bloodstream infections (BSIs) represent a significant public health concern. Metagenomic Capture targeted next-generation sequencing technology, as a newly emerging method for pathogen detection, has been applied in the etiological diagnosis of various infectious diseases and demonstrates good diagnostic efficacy. However, there is relatively limited research on the diagnostic value of this technology for the etiological diagnosis of BSIs. METHODS: A comprehensive retrospective analysis was performed on patients suspected of having BSIs who were admitted to the Affiliated Guangdong Second Provincial General Hospital of Jinan University in 2024. These patients underwent both blood culture analysis and Metagenomic Capture targeted next-generation sequencing technology for diagnostic testing, and a detailed comparison of the results was conducted. RESULTS: It was found that the Metagenomic Capture-targeted next-generation sequencing method has a shorter time to result [1.33 (1.18 - 1.69) vs 2.73 (1.89 - 3.84) days, p&#xa0;<&#xa0;0.001], more pathogenic microbial species detected, higher positive detection rate and higher sensitivity than blood culture. CONCLUSIONS: Metagenomic Capture targeted next-generation sequencing technology is a promising tool for pathogen identification in BSIs, offering substantial methodological advantages in terms of turnaround time, detection breadth, and sensitivity. These diagnostic performance characteristics support its potential utility in clinical microbiology practice.

Humans↗
PubMed2026

Impact of Contact Lens Use on Clinical Profile and Outcomes of Fungal Keratitis: An 8-Year Retrospective Study.

PURPOSE: To compare clinical characteristics, microbiological profiles, treatment strategies, and outcomes between contact lens-associated (CL) and noncontact lens-associated (non-CL) fungal keratitis. DESIGN: Retrospective, comparative clinical cohort study. METHODS: A review of culture-proven fungal keratitis treated at a tertiary referral center between 2018 and 2025 was conducted. Cases were categorized as CL or non-CL-associated. Demographic, clinical, microbiological, treatment, and outcome data were analyzed and compared between groups. RESULTS: Thirty-seven eyes were included, comprising 16 CL and 21 non-CL cases. CL users presented earlier than non-CL patients (median 7 vs 14 days, P = .007) and had fewer associated ocular risk factors (31% vs 81%, P = .001). Baseline visual acuity and infiltrate size did not differ significantly between groups. Candida species were isolated in 21% cases, Fusarium in 16% and Aspergillus in 8%. Fusarium (19% vs 13%) and Candida (24% vs 19%) infections were slightly more frequent in non-CL cases. Overall, filamentous fungi were the predominant organism group. Topical voriconazole was the most frequently used antifungal agent (78%). All CL-associated cases resolved with medical therapy alone, with a median time to resolution of 38 days (IQR 22-58). In contrast, 76% of non-CL cases resolved medically (median 42 days, IQR 32-76), while 23% required therapeutic keratoplasty (P = .04). Final visual acuity was comparable between groups (logMAR 0.2 vs 0.5, P = .56). CONCLUSION: Contact lens-associated fungal keratitis is characterized by earlier presentation and fewer underlying ocular comorbidities, with favorable outcomes achieved through medical therapy alone. Despite similar microbiological profiles and treatment approaches, noncontact lens-associated fungal keratitis more frequently follows a complicated course requiring surgical intervention.

Humans↗
PubMed2026

Intra-amniotic infection: diagnosis, nomenclature, clinical significance, management, and microbiologic tools used for the diagnosis.

SUMMARYIntra-amniotic infection is the main cause of spontaneous preterm birth and adverse maternal-fetal outcomes; therefore, rapid, robust, and accurate diagnosis remains a clinical priority. Conventional microbiological techniques, especially culture-based methods, are limited by long turnaround times and the inability to detect fastidious or unculturable organisms. This review summarizes the diagnosis, nomenclature, clinical significance, management, and laboratory approaches for diagnosing intra-amniotic infection. Targeted nucleic acid amplification methods, including species-specific polymerase chain reaction and broad-range 16S rRNA gene sequencing, have improved the detection of bacterial DNA and enabled the identification of organisms that evade routine culture in intra-amniotic infection. More recently, whole-genome sequencing and metagenomic next-generation sequencing have provided culture-independent strategies for comprehensive pathogen profiling, allowing simultaneous detection of bacteria, viruses, and fungi, as well as characterization of antimicrobial resistance determinants and virulence-associated genes. However, challenges remain, particularly in low-biomass samples such as amniotic fluid, where contamination, host DNA background, and data interpretation can compromise specificity. This review critically evaluates the advantages and limitations of each molecular modality and discusses pre-analytical, analytical, and bioinformatic considerations essential for reliable implementation. Integration of molecular diagnostics into clinical workflows holds promise for improving etiological diagnosis and guiding targeted therapy in intra-amniotic infection, thereby improving maternal and fetal outcomes.

Humans↗