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Accurate drug susceptibility testing (DST) is crucial for designing effective regimens for multidrug-resistant (MDR) and pre-extensively drug-resistant tuberculosis (pre-XDR TB). Sensititre MYCOTB enables simultaneous determination of minimum inhibitory concentrations (MICs) for multiple drugs, but its diagnostic performance varies across studies. This meta-analysis evaluated the diagnostic performance of Sensititre MYCOTB for key MDR and pre-XDR TB drugs. The protocol was registered in PROSPERO (CRD420251230599). PubMed, Cochrane, Google Scholar, Scopus, ONOS, Web of Science, ScienceDirect, and registries were systematically searched for studies published between 2010 and 2025. Studies comparing the Sensititre MYCOTB with reference DST for Mycobacterium tuberculosis complex (MTBC) were included. Bias assessment and pooled diagnostic accuracy estimates were generated. Fourteen studies, including 1,728 isolates, were analyzed. Rifampicin and isoniazid demonstrated high sensitivity (0.976 [95% CI: 0.94-0.99] and 0.977 [95% CI: 0.95-0.99]) and specificity (0.958 [95% CI: 0.84-0.98] and 0.957 [95% CI: 0.83-0.99], respectively) with low heterogeneity. Amikacin, kanamycin, and ofloxacin demonstrate good diagnostic accuracy, with high specificity (>0.98 [95% CI]). Moderate diagnostic accuracy was observed for ethambutol, streptomycin, ethionamide, and rifabutin. Cycloserine, moxifloxacin, and para-aminosalicylic acid showed inconsistent performance despite excellent specificity (>0.97 [95% CI]). Sensitivity analysis partially improved pooled sensitivity for moxifloxacin 0.801 (95% CI: 0.585-0.924) and para-aminosalicylic acid 0.76 (95% CI: 0.518-0.894), whereas cycloserine remained at 0.436 (95% CI: 0.190-0.725), although heterogeneity persisted. Sensititre MYCOTB DST demonstrates high diagnostic accuracy for MDR-TB and pre-XDR-TB drugs, while caution is required with cycloserine, moxifloxacin, and para-aminosalicylic acid. These findings support the integration of MIC-based testing into clinical decision-making.
The rapid emergence of resistance to novel tuberculosis drugs, such as bedaquiline, is a key threat to the long-term effectiveness of novel regimens. Given that the introduction of these agents has enabled the introduction of an all-oral regimen for rifampicin-resistant and multidrug-resistant tuberculosis, the rise of resistance underscores the urgent need to safeguard their efficacy and responsible use. A major barrier is the delay in developing reliable tools to detect resistance to novel compounds, which limits clinical decision-making and surveillance efforts. Herein, we outline a framework for integrating the development of drug susceptibility testing alongside tuberculosis drug development, including early stage resistance profiling and defining appropriate epidemiological cutoff values. We highlight key gaps, including the need for structured partnerships between drug developers, diagnostic manufacturers, regulators, research institutions, funders, and policy makers. We propose a roadmap to accelerate drug susceptibility testing and development of new tuberculosis regimens, ensuring that resistance detection maintains pace with the introduction of novel drugs. Establishing collaborative platforms for data sharing, genomic analysis, and diagnostic innovation will help ensure that resistance detection evolves in step with drug development, thereby preserving novel treatments and improving global tuberculosis care.
BACKGROUND: Glioblastoma (GBM) remains a devastating cancer with limited treatment options, largely due to its heterogeneity. While supramaximal resection has recently provided survival benefits, therapeutic profiling of different tumor compartments, particularly its infiltrative edge remains largely unexplored. METHODS: Here, we leveraged magnetic resonance imaging (MRI)-guided multi-sampling, collecting 2 cores and 2 margins per case, to query GBM heterogeneity. Whole-exome and RNA-seq with drug testing in two patient-derived 3D models were used to reveal similarities and differences in genomic and transcriptomic makeups, cellular compositions, and drug responses across cores and margins. Bioinformatics interrogations further identified response biomarkers. RESULTS: Mutation analysis showed that oncogenes exhibited a higher degree of spatial heterogeneity than tumor suppressor genes, regardless of MRI status. While the mesenchymal transcriptional subtype with extracellular matrix remodeling, stress response, and immune programs were preferentially enriched in enhancing cores, proneural tumors with neurological processes favored non-enhancing margins. Using a 15-drug GBM-targeted panel, ERK (ulixertinib) and PI3K pathway (paxalisib, CC-115) inhibitors showed preferential efficacy in enhancing cores and non-enhancing margins, respectively. The anti-apoptosis, pan-Bcl2 agent navitoclax and the epigenetic drug trotabresib represented the most effective, tumor-wide monotherapies. Importantly, drug combinations generally outperformed single agents across all regions. CONCLUSIONS: This work demonstrates the regional heterogeneity of therapeutic vulnerabilities in GBM ex vivo, showing various drugs with tumor-wide or MRI-enhancement informed activity. These findings offer preclinical bases of numerous monotherapies and drug combinations for future clinical trial design.
BACKGROUND: Basic research on castration-resistant prostate cancer (CRPC) is limited by the lack of clinically relevant models. This study aimed to establish patient-derived xenografts (PDX) and PDX-derived organoids from clinical CRPC specimens to develop a bidirectional experimental platform for in vivo xenografts and ex vivo organoids. METHODS: We established a new PDX library (KUCaP PDX series) using CRPC clinical specimens and derived prostate cancer organoids. Comprehensive biological characterization of clinical specimens, PDXs, PDX-derived organoids, and organoid-derived xenografts (ODXs) was performed to confirm the preservation of the original tumor features. Using our PDX library, we conducted genetic engineering and drug testing to explore novel therapeutic approaches. RESULTS: PDX-derived organoids were successfully established from all eight KUCaP PDX lines (100%). Four of the eight lines (50%) were maintained during the long-term culture experiments for over ten passages. Key features observed in the original clinical specimens, including genetic alterations and castration responsiveness, were maintained across the PDX, PDX-derived organoid, and ODX models. RNA sequencing revealed that transcriptomic profiles were consistently maintained across clinical specimens, PDXs, PDX-derived organoids, and ODXs. One PDX and organoid (KUCaP19) which exhibited a high homologous recombination deficiency (HRD) score, without any pathogenic homologous recombination repair (HRR) gene alterations, showed sensitivity to a poly ADP-ribose polymerase (PARP) inhibitor. In contrast, KUCaP12, which had no HRR alterations and a low HRD score, did not respond to PARP inhibition. CONCLUSIONS: We developed the KUCaP library as a novel experimental platform for CRPC research by integrating clinical specimens with PDX, organoid, and ODX models along with their genomic and transcriptomic data. These models largely retained the genetic profiles and responses to castration observed in the original tumors. The bidirectional use of personalized PDX and organoids will facilitate the elucidation of the molecular mechanisms of CRPC.
BACKGROUND: Gastric cancer (GC) exhibits marked inter-patient heterogeneity, limiting empirical chemotherapy efficacy. Patient-derived xenograft (PDX) models preserve the molecular features of parental tumors and can serve as pharmacodynamic surrogates, but conventional subcutaneous PDX suffers from low engraftment rates. This study evaluated an optimized intramuscular PDX platform for individualized drug testing in GC and applied whole exome sequencing (WES) for biomarker identification (Clinical trial registry: ChiCTR-OOC-17012731). MATERIALS AND METHODS: Ninety-eight treatment-naive GC patients were enrolled between April 2018 and December 2020. Fresh tumor tissues were engrafted into NCG mice by intramuscular transplantation. Drug efficacy was evaluated using tumor cell necrosis rate and Ki-67 expression. WES was performed on 32 engrafted tumorgrafts to characterize driver mutations in fast- and slow-growing subgroups. RESULTS: An engraftment rate of 71.7% (43/60) was achieved, substantially exceeding rates reported in prior studies. Clinical characteristics were independent of engraftment success and outgrowth time (all p > 0.05). Fast- and slow-growing tumorgrafts diverged in frequently altered genes: KMT2C, APOB, CDK12 and MSH2 predominated in fast-growing grafts, whereas TP53, CHD3 and TET2 were enriched in slow-growing grafts. Slow-growing tumorgrafts correlated with longer progression-free survival (p = 0.02). PDX-guided treatment was associated with improved prognosis. CONCLUSIONS: Intramuscular transplantation into NCG mice yields high engraftment rates for GC PDX. PDX-guided chemotherapy selection is associated with favorable outcomes. Driver mutation divergence between fast- and slow-growing tumorgrafts provides candidate prognostic biomarkers.
Despite of massive emergence of molecular targeting drugs, the mainstay of advanced gastric cancer (GC) therapy is DNA-damaging drugs. Using a reverse-phase protein array-based proteogenomic analysis of a panel of 8 GC cell lines, we identified genetic alterations and signaling pathways, potentially associated with resistance to DNA-damaging drugs, including 5-fluorouracil (5FU), cisplatin, and etoposide. Resistance to cisplatin and etoposide, but not 5FU, was negatively associated with global copy number loss, vimentin expression, and caspase activity, which are considered hallmarks of previously established EMT subtype. The segregation of 19,392 protein expression time courses by sensitive and resistant cell lines for the drugs tested revealed that 5FU-resistant cell lines had lower changes in global protein dynamics, suggesting their robust protein level regulation, than their sensitive counterparts, whereas the cell lines that are resistant to other drugs showed increased protein dynamics in response to each drug. Despite faint global protein dynamics, 5FU-resistant cell lines showed increased signal transducer and activator of transcription 1 phosphorylation and PD-L1 expression in response to 5FU. In publicly available cohort data, expression of signal transducer and activator of transcription 1 and NFκB target genes induced by proinflammatory cytokines was associated with prolonged survival in GC. In our validation cohort, total lymphocyte count, rather than PD-L1 positivity, predicted a better relapse-free survival rate in GC patients with 5FU-based adjuvant chemotherapy than those with surgery alone. Moreover, total lymphocyte count+ patients who had no survival benefit from adjuvant chemotherapy were discriminated by expression of IκBα, a potent negative regulator of NFκB. Collectively, our results suggest that 5FU resistance observed in cell lines may be overcome by host immunity or by combination therapy with immune checkpoint blockade.
BACKGROUND: Ovarian cancer (OC) is frequently diagnosed at an advanced stage, where tumor heterogeneity and rapid development of chemoresistance contribute to a poor prognosis. The lack of reliable predictive biomarkers further hinders the development of effective treatment strategies. Patient-derived organoids (PDOs) have recently emerged as promising preclinical models with the potential to predict therapeutic responses. METHODS: OC PDOs were generated from ascites samples representing diverse histological subtypes. Histological and genomic fidelity to parental tumors was confirmed through histopathological analysis and whole-exome sequencing. Drug sensitivity to cisplatin and poly (ADP-ribose) polymerase (PARP) inhibitors was evaluated and correlated with 1-year clinical outcomes. We also investigated the therapeutic efficacy of oncolytic herpes simplex virus 2 (OH2) both as a single agent and in combination with cisplatin. The expression of cancer stem cell (CSC) markers CD44 and ALDH1A1 under treatment conditions was analyzed using immunohistochemistry and flow cytometry. RESULTS: PDOs were successfully established with an 86.2% success rate. These PDOs faithfully recapitulated the histopathological and genomic features of their corresponding tumors, maintaining intratumoral heterogeneity, and were amenable to xenotransplantation. Drug sensitivity assays demonstrated that PDOs accurately predicted patient-specific responses to cisplatin and PARP inhibitors. OH2 exhibited direct cytotoxicity in both cisplatin-sensitive and cisplatin-resistant PDOs, reducing cell viability by 20-60%. Notably, the combination treatment with OH2 and cisplatin enhanced antitumor efficacy, resulting in a significant reduction of the CD44+CSC subpopulation. CONCLUSIONS: Ascites-derived OC PDOs represent a robust platform for individualized drug testing. The combination of OH2 and cisplatin offers a novel and effective strategy for circumventing chemoresistance in OC.
As arthropod-borne viruses continue to threaten populations globally, there is a pressing need for experimental systems that enable rapid antiviral discovery. Reverse-genetics platforms producing recombinant reporter orthoflaviviruses have been developed to address this gap. Here, we present two new recombinant tick-borne encephalitis viruses (TBEVrec) generated on a European-subtype Haselmühl Tiho1 isolate backbone. A reporter gene, either eGFP or Nluc, was inserted in the capsid-coding region of the genome downstream of the capsid RNA regulatory signal and separated from the complete viral polyprotein by a 2A self-cleaving peptide. TBEVrec was better rescued using the circular polymerase extension reaction (CPER) than with the infectious subgenomic amplicon (ISA) method. TBEVrec replicated efficiently in relevant human cell lines, with comparable replication to wild-type TBEV in a neuronal cell line and moderately reduced titers and RNA levels in immune-derived cell lines. Using either eGFP or Nluc, we illustrate how TBEVrec enabled high-content RNAi screening, highlighting Nucleolin and PRKD1 as potential TBEV host factors, and drug testing on a benchtop plate reader. Nanopore sequencing of the eGFP insert revealed that the reporter is excised without affecting flanking regions. Comparative analysis of eGFP and Nluc further shows that this instability is time- and cell type-dependent, and that Nluc is comparatively more stable. From these observations, we outline safeguards and design principles that are broadly applicable both to the rescue of existing constructs and to the design of future recombinant reporter virus platforms.
Human induced pluripotent stem cells (iPSCs) have emerged as a transformative platform for modeling inherited cardiac arrhythmia syndromes and uncovering human-specific disease mechanisms. However, the promise of iPSC-derived cardiomyocytes lies beyond the recapitulation of arrhythmogenic phenotypes and channelopathies. In this review, we explore recent works which have enabled mechanistic interrogation and therapeutic insight for inherited arrhythmia syndromes, beyond the capabilities of traditional animal models. Such studies have leveraged iPSCs to elucidate the role of splice variants, transcriptional regulation, and mitochondrial stress in arrhythmogenesis. Further, iPSC systems have proven important for reclassifying variants of uncertain significance and in modeling idiopathic arrhythmias where genotype-phenotype links are elusive. Advances in directed differentiation now permit chamber-specific cardiac cell generation, allowing for atrial and ventricular disease modeling and revealing critical cell-cell interactions. iPSCs also serve as high-fidelity precursor platforms for drug testing, offering predictive insight into mutation-specific responses to pharmacologic and genetic therapies. Though limitations in maturation and scalability persist, ongoing efforts for integration with tissue engineering, multi-cellular models, and computational frameworks are evolving to improve model reliability. iPSC-based systems now occupy a critical role in arrhythmia research, bridging basic discovery with translational applications, thereby contributing to personalizing care and advancing therapeutics in inherited and idiopathic arrhythmic syndromes.
Zoonoses pose substantial global health risks, highlighting the need to better understand animal-to-human transmission. Reptiles are increasingly recognized as hosts of diverse pathogens, including numerous viruses, yet the diversity and prevalence of reptile pathogens, as well as their potential risk to humans, remain poorly understood. Here, we establish and characterize airway organoids derived from Python regius, providing an in vitro model to study reptile airway infection. Through de novo assembly of a Python regius reference genome, we characterize airway organoids at single-cell resolution, which suggests the presence of diverse cell populations including ionocytes, ciliated, secretory, goblet, endocrine, tuft, and basal cells. The organoids support productive infection with Ball Python Nidovirus (BPNV) and mount a robust epithelial antiviral response through the induction of interferon-stimulated genes, cytokines, and genes involved in chemical defense. As a proof-of-concept, treating organoids with antiviral drugs during infection reduces BPNV levels, highlighting the model's utility for drug testing. By providing a reductionist system of the serpentes airway, these organoids constitute a physiologically relevant in vitro model to study reptile viruses and host-pathogen interactions in their native host.
Glioblastoma (GBM) is one of the most aggressive and lethal primary brain tumors in adults, characterized by dynamic clonal evolution and extensive genomic, cellular, spatial, and microenvironmental heterogeneity. Multi-omics studies have revealed that GBM follows complex evolutionary trajectories involving genetic, epigenetic, transcriptional, and immune-microenvironmental remodeling as tumors grow, adapt to the brain microenvironment, and acquire therapeutic resistance. Increasing evidence suggests that GBM may originate from aberrant neural stem or progenitor cells, including those residing in the subventricular zone, and that glioblastoma stem cells (GSCs) contribute to tumor propagation, heterogeneity, and recurrence. A key conceptual challenge is to reconcile hierarchical cancer stem cell models, in which GSCs are viewed as relatively stable tumor-propagating subpopulations, with dynamic state plasticity models, in which stem-like properties can be reversibly acquired or lost during transitions among proneural-like, mesenchymal-like, invasive, and therapy-tolerant states. Recent advances in single-cell profiling, spatial transcriptomics, lineage tracing, organoid culture, 3D bioprinting, genetically engineered models, and artificial intelligence (AI)-assisted computational modeling have substantially improved the ability to study these processes. However, no currently available model fully recapitulates human GBM heterogeneity, recurrence, treatment history, and tumor-microenvironment interactions. Therefore, model selection should be guided by clearly defined mechanistic questions rather than by reliance on any single platform. This review summarizes current advances in in vitro, ex vivo, in vivo, and computational models for studying GBM evolution and heterogeneity, and discusses how integrated model pipelines may improve preclinical drug testing, treatment-response prediction, and precision neuro-oncology.
UNLABELLED: Ethiopia ranks 30th among the tuberculosis (TB) burden countries, with children representing a significant yet understudied population group. This study aims to investigate the genetic diversity and drug-resistant profile among Ethiopian children. We included children under 15 years of age diagnosed with culture-confirmed pulmonary TB/drug-resistant TB between January 2017 and June 2023. Phenotypic drug susceptibility testing and whole-genome sequencing were conducted for 85 Mycobacterium tuberculosis (MTB) isolates. Demographic data were combined with genomic information. Lineage 4 was the most dominant (77.6%), while lineage 2 was less common (1%). Within lineage 4, several sub-lineages were identified, with lineage 4.2.2.2 being notably the most predominant (48%). Most of these cases were from Oromia (58%), including the hotspot areas for lineage 4 that were identified at a 99% confidence level. Among 17 MDR/pre-XDR-TB isolates, lineages 3 and 4.2.2.2 were the dominantly observed lineages/sub-lineages, with proportions of 29% and 65%, respectively. Of the 85 cases, 30.5% were drug-resistant TB to at least one of the five first-line anti-TB drugs tested by phenotypic drug susceptibility testing. Of these 26 drug-resistant TB cases, 23 were concordant with whole-genome sequencing characterization. The most frequent resistance mutations to rifampicin were found in the rpoB gene, specifically p.Ser450Leu (88%), followed by isoniazid in the katG gene, p.Ser315Thr (86%). Multidrug-resistant TB was strongly associated with MTB lineages (P = 0.007). This study identified high genetic diversity of M. tuberculosis and related drug-resistance mutations, with a strong concordance between whole-genome sequencing-based predictions and phenotypic drug susceptibility testing. IMPORTANCE: Our findings revealed a high genetic diversity of Mycobacterium tuberculosis among Ethiopian children, with the most common lineage being lineage 4, specifically lineage 4.2.2.2, in which a higher frequency of multidrug-resistant tuberculosis (TB) was observed. Additionally, we identified regional hotspots, suggesting ongoing community transmission. Moreover, whole-genome sequencing demonstrated high concordance with phenotypic drug susceptibility testing and identified mutation genes associated with first- and second-line anti-TB drugs, highlighting its usefulness in providing comprehensive results for resistance detection in children. Thus, it is essential for integrating genomic surveillance into childhood TB and drug resistance control.
BACKGROUND: Childhood drug-resistant tuberculosis is often underdiagnosed and inadequately characterized due to the paucibacillary nature of the disease. This study aimed to assess resistance to first-line anti-tuberculosis drugs in children using phenotypic drug susceptibility testing and whole-genome sequencing. METHODS: A retrospective-prospective study was conducted on culture-confirmed childhood tuberculosis cases in Ethiopia (2017–2023). Phenotypic drug susceptibility testing was performed on 110 Mycobacterium tuberculosis complex isolates. Whole-genome sequencing was completed for 85 of these isolates, which were analyzed using the TB-Profiler and MTBSeq pipelines. We assessed the sensitivity, specificity, predictive values, and kappa agreement of whole-genome sequencing compared with phenotypic drug susceptibility testing. RESULTS: Phenotypic resistance to at least one first-line anti-TB drug was observed in 26/110 (23.6%) of the examined isolates, with isoniazid resistance being the most frequent, 23/110 (20.9%), followed by rifampicin resistance, 18/110 (16.4%). TB-Profiler showed almost perfect agreement with phenotypic drug susceptibility testing for rifampicin (sensitivity 94.4%, kappa = 0.96) and isoniazid (sensitivity 91.3%, kappa = 0.91), whereas MTBSeq showed slightly lower performance. Both pipelines demonstrated moderate to weak agreement with phenotypic drug susceptibility testing for detecting resistance to ethambutol, pyrazinamide, and streptomycin. The most frequently observed resistance mutations among phenotypically resistant isolates were rpoB (Ser450Leu), katG (S315Thr), embB (Met306Ile), and pncA (C-11 A > G) for rifampicin, isoniazid, ethambutol, and pyrazinamide, respectively. Discrepancies between genotypic and phenotypic drug susceptibility testing were observed across all first-line anti-TB drug-resistant isolates, particularly for ethambutol and pyrazinamide. CONCLUSION: We found a high prevalence of isoniazid resistance, along with rifampicin resistance, underscoring the need for early detection in vulnerable groups. Whole-genome sequencing showed good accuracy for these drugs, with TB-Profiler performing best. CLINICAL TRIAL NUMBER: Not applicable.
The paucity of diagnostic tests for isoniazid-resistant tuberculosis is concerning, given its status as the most common form of drug-resistant tuberculosis and a gateway to multidrug-resistant diseases. Molecular drug-susceptibility testing has improved access to timely diagnosis of rifampicin-resistant tuberculosis, but testing for isoniazid-resistant tuberculosis still remains rare. In this Review, we assessed the characteristics of molecular drug-susceptibility testing for detection of isoniazid-resistant tuberculosis, referencing the WHO target product profiles. 9243 citations were screened to select 238 studies published between 2000 and 2024. The diagnostics options have expanded rapidly since 2020, with 27 nucleic acid amplification tests, eight line probe assays, five DNA microarrays, two targeted next-generation sequencing platforms, and two whole-genome sequencing platforms. Most of the evaluated molecular drug-susceptibility tests met diagnostic performance targets but were often complex and costly. Although a few low-complexity nucleic acid amplification tests met key target product profile criteria, additional field validation and greater efforts are needed to ensure optimal feasibility and affordability for low-resource settings.
INTRODUCTION: Early and accurate diagnosis of drug-resistant tuberculosis (DR-TB) is essential for improving treatment outcomes. Phenotypic drug susceptibility testing (pDST) is comprehensive but slow, while rapid molecular assays provide resistance information for a limited number of drugs. Targeted next-generation sequencing (tNGS) offers the potential for broad and rapid resistance detection, but its integration into diagnostic algorithms has been hindered by uncertainty about its placement within existing workflows. METHODS: This study evaluated the extent to which two tNGS solutions-Deeplex Myc-TB (GenoScreen) and TB Drug Resistance Test (Oxford Nanopore Technologies, ONT)-provided interpretable drug resistance results that could inform regimen design, in comparison to other WHO-recommended molecular assays and pDST. Data were collected from three high-burden DR-TB settings under the Seq&Treat study. Sequencing success rates and drug resistance detection were analysed based on: (1) the initial Xpert MTB/RIF result (very low, low, medium, high), (2) resistance results for drugs in WHO-recommended regimens and (3) performance relative to other WHO-endorsed assays. The potential impact of different algorithms on the estimates was also considered. Key factors influencing successful tNGS adoption within diagnostic pathways were identified, leveraging insights from the Seq&Treat diagnostic accuracy study. RESULTS: Sequencing success rates were 88.5% (GenoScreen) and 93.1% (ONT) across 763 samples. While tNGS provided complete resistance data for 73%-86% of drugs in recommended regimens, pDST achieved 92%-93%. Both tNGS solutions matched or exceeded the sensitivity of WHO-recommended molecular assays. CONCLUSIONS: This study highlights the critical role of tNGS as a centralised tool for comprehensive drug resistance testing to inform DR-TB treatment decisions following initial screening assays. By complementing existing molecular tests with tNGS, diagnostic workflows can be optimised to ensure timely and comprehensive resistance detection. These findings support policy updates to integrate tNGS into global TB diagnostic algorithms. TRIAL REGISTRATION NUMBER: NCT04239326.
UNLABELLED: Clostridioides difficile (C. difficile) is the primary pathogen responsible for nosocomial infectious diarrhea and pseudomembranous colitis. In China, metronidazole and vancomycin are the preferred treatments for C. difficile infection (CDI). This study aimed to investigate the evolution of vancomycin (VA) and metronidazole (MTZ) resistance, as well as the longitudinal changes in virulence over time, using next-generation sequencing, drug susceptibility tests, and analysis of resistance and virulence genes. Additionally, we monitored the emergence of the highly virulent C. difficile strain RT027 and the spread and potential outbreak of C. difficile in the hospital setting. A random stratified sampling method was used to select 114 fecal samples from inpatients at Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, between 2021 and 2024. Clinical data from the enrolled patients were also collected. We conducted antigen and toxin protein detection for C. difficile, strain isolation and identification, drug sensitivity tests, whole genome sequencing, and bioinformatics analysis. This included comparisons of drug resistance genes, detection of toxin genes, and the construction of phylogenetic trees based on pan-genome analysis to investigate the resistance and toxin gene variations in C. difficile. Among the 114 samples collected from Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, no vancomycin- or metronidazole-resistant strains were identified. However, the average minimum inhibitory concentration (MIC) of C. difficile to vancomycin increased annually (H = 33.208, P < 0.05). The average MIC of C. difficile to metronidazole was highest in 2022 but decreased in 2023 and 2024 (H = 41.990, P < 0.05). Notably, in 2024, one C. difficile strain exhibited an MIC for metronidazole at the resistance threshold (2.00 μg/mL). Further Spearman correlation analysis of the strain years with drug sensitivity results revealed a positive correlation between strain years and the MIC levels of vancomycin and metronidazole (r = 0.528, P < 0.05; r = 0.377, P < 0.05). The proportion of toxin-producing strains increased annually, with 100% of strains in 2024 producing toxins, representing the highest proportion compared to the previous three years (X² =11.75, P < 0.05). Both vancomycin and metronidazole remain effective for the treatment of CDI in clinical practice. However, the sensitivity of C. difficile to these two drugs is gradually decreasing, and the rate of toxin gene carriage is also rising in clinical cases. No hospital outbreaks of C. difficile infections were identified in this study. IMPORTANCE: Clostridioides difficile has developed resistance to multiple antibiotics, including cephalosporins, clindamycin, and fluoroquinolones. This has exacerbated the global antibiotic resistance crisis. In China, according to current treatment guidelines, vancomycin and metronidazole are the preferred first-line drugs for treating C. difficile infections. However, there are reports indicating the emergence of new resistance to both vancomycin and metronidazole. Although there is extensive research on the long-term antibiotic resistance of C. difficile abroad, research on the continuous monitoring of antibiotic resistance and potential outbreaks of C. difficile in China is relatively limited. To fill this gap, we studied positive C. difficile strains from a tertiary general hospital in China. Through Next-Generation Sequencing (NGS), drug sensitivity testing, and analysis of drug resistance and virulence genes, we revealed the evolution of C. difficile's resistance to vancomycin and metronidazole, as well as changes in virulence, and monitored the spread within the hospital and potential outbreaks of C. difficile.
BACKGROUND: The increasing prevalence of non-tuberculous mycobacteria pulmonary disease (NTM PD) is a burden to public health. Successful management of NTM PD critically depends on accurate species identification and reliable drug susceptibility testing to guide appropriate antibiotic therapy. Emerging molecular technologies offer rapid diagnostic solutions compared to conventional methods, but their performance varies. This study aims to provide a comprehensive evaluation of current molecular techniques for NTM identification and to present a global antibiotic resistance profile. METHODS: A systematic literature search was conducted in PubMed and Web of Science for studies published between 2005 and 2024. Studies applying molecular methods for NTM identification and resistance detection in humans were included. Data on study characteristics, diagnostic methods, sample types, sample sizes, identification sensitivity, and drug susceptibility results were extracted. Meta-analysis was performed using R with the meta4diag package. The quality of included studies was assessed using the QUADAS-2 tool. RESULTS: The analysis included 49 studies on NTM identification and 33 studies on antibiotic resistance. For species identification, all evaluated molecular technologies (MALDI-TOF MS, PCR-based methods, Sequencing, DNA chip, and DNA strip) demonstrated high pooled sensitivities (>0.92). Subgroup analysis revealed that sample type significantly affected performance for MALDI-TOF MS. Preliminary analysis of antibiotic resistance rates revealed varying patterns. For slowly growing mycobacteria, a significantly high Ethambutol resistance rate was observed in M. avium (69.20%). Among rapidly growing mycobacteria, resistance to Imipenem was notable (54.22%), and Clarithromycin resistance varied significantly within the Mycobacterium abscessus complex. CONCLUSION: Emerging molecular technologies have revolutionized the methodology for NTM identification with excellent performance. However, their performance can be influenced by sample type, particularly for MALDI-TOF MS. The alarming and heterogeneous antibiotic resistance patterns also highlight the critical need for rapid and accurate species identification and drug susceptibility testing to inform effective therapeutic strategies. Key messagesMolecular technologies demonstrate high accuracy for NTM identification.Antibiotic resistance is a serious concern with variations among NTM species and subspecies.Rapid and accurate species identification and drug susceptibility testing are crucial for guiding effective clinical management of NTM PD.