Phenotypic Susceptibility Research Articles

Susceptibility Screening of HIV-1 Viruses to Broadly Neutralizing Antibodies, Teropavimab and Zinlirvimab, in People with HIV-1 Suppressed by Antiretroviral Therapy

Background: HIV envelope (env) diversity may result in resistance to broadly neutralizing antibodies (bNAbs). Assessment of genotypic or phenotypic susceptibility to antiretroviral treatment is often performed in people with HIV-1 (PWH) and used for clinical trial screening for HIV-1 bNAb susceptibility. Optimal bNAb susceptibility screening methods are not yet clear. Methods: Phenotypic and genotypic analyses were conducted on 124 screening samples from a Phase 1b study of bNAbs teropavimab (3BNC117-LS) and zinlirvimab (10-1074-LS) administered with lenacapavir in virally suppressed PWH. Phenotypic analysis was conducted on integrated HIV-1 provirus and stimulated outgrowth virus, with susceptibility to bNAbs defined as 90% inhibitory concentration ≤2 μg/mL. The proviral DNA HIV env gene was genotyped using deep sequencing, and bNAb susceptibility predicted using published env amino acid signatures. Results: Proviral phenotypic results were reported for 109 of 124 samples; 75% (82/109) were susceptible to teropavimab, 65% (71/109) to zinlirvimab, and 50% (55/109) to both bNAbs. Phenotypic susceptibility of outgrowth viruses was available for 39 samples; 56% (22/39) were susceptible to teropavimab, and 64% (25/39) to zinlirvimab. Phenotypic susceptibilities correlated between these methods: teropavimab r = 0.82 (P<0.0001); zinlirvimab r = 0.77 (P<0.0001). Sixty-seven samples had genotypic and phenotypic data. Proviral genotypic signatures predicted proviral phenotypic susceptibility with high positive predictive value (68–86% teropavimab; 63–90% zinlirvimab). Conclusions: bNAb susceptibility was correlated among all three in-vitro assays used to determine teropavimab and zinlirvimab susceptibility in virally suppressed PWH. These findings may help refine PWH selection criteria for eligibility for future studies.

A comparative study of a rapid phenotypic antimicrobial susceptibility testing system directly from positive blood cultures to the disk diffusion and VITEK 2 methods

BackgroundSepsis is a life-threatening condition that impacts 49 million people annually and causes 11 million deaths worldwide. Surviving bloodstream infections (BSIs) depends on the rapid administration of effective antimicrobial treatment, underscoring a need for rapid antimicrobial susceptibility testing (AST). AimTo evaluate the performance of Quantamatrix's dRAST v2.5 system (Seoul, South Korea) for AST directly from positive blood cultures as compared to the Disk-Diffusion (DD) and VITEK 2 methods. MethodsThe study included 191 positive blood cultures from clinical samples and spiked blood culture bottles. Following Gram staining and species-level identification, AST was performed by VITEK 2 and standard DD methods using CLSI (2021) interpretation. ResultsdRAST demonstrated very good AST performance for a Gram-negative isolate, and good performance for Gram-positive isolates, meeting CLSI criteria for the acceptance of a new method. Antimicrobials that were not considered verified compared to VITEK 2 and DD were cefazolin, ceftazidime, meropenem, and trimethoprim/sulfamethoxazole for Gram-negatives and clindamycin, erythromycin, penicillin, and oxacillin for Gram-positives. dRAST ESBL detection results were strongly correlated with the ESBL phenotypes obtained with other methods. Additional resistance mechanisms were in concordance with traditional tests. ConclusionsdRAST demonstrated good AST performance, meeting CLSI criteria for most relevant antibiotics. dRAST was associated with a significant reduction in time-to-results, labor, and the subjectivity of result analyses, making it a valuable addition to efforts supporting the treatment of patients with bacteremia.AST (antimicrobial susceptibility test), blood culture, dRAST, rapid methods, sepsis, turnaround time (TAT).

MOLECULAR SURVEILLANCE OF GONOCOCCAL CIPROFLOXACIN SUSCEPTIBILITY/RESISTANCE IN BULGARIA, 2022-2023

Background: The emergence and spread of antimicrobial resistance in Neisseria gonorrhoeae is a significant public health issue, with Euro-GASP conducting surveillance across the EU-EEA. The advent of molecular diagnostics for N. gonorrhoeae may possibly limit the surveillance data because it is dependent on gonococcal culture for phenotypic susceptibility testing. Ideally, molecular diagnostics should combine identification and resistance detection but the complexity of gonococcal molecular genetics of resistance is a major barrier for test development. Currently, resistance prediction in N. gonorrhoeae is accurate only for fluoroquinolones and there are commercial kits available on the market that allow antimicrobial resistance surveillance and individualized treatment. The study examined Bulgaria's gonococcal fluoroquinolone resistance rate for 2022-2023 by molecular methods and compared it with previous years and EU-EEA trends. Methods: The commercial ResistancePlus® GC assay was used to predict ciprofloxacin susceptibility/resistance in 66 Neisseria gonorrhoeae-positive DNA samples from patients, diagnosed in 2022-2023. Results: The identified fluoroquinolone resistance rate in 2022-2023 was 68.2%. The majority of the cases were males in the age group 20-29 (50.8%), the most common mode of transmission was MSM (77%) and 17% of the cases with known HIV status were positive. Conclusion: This study found a higher than before fluoroquinolone resistance rate (68.2%) in Bulgaria, following the trend in Europe. In the EU-EEA, ciprofloxacin resistance increased to 65.9% in 2022. Molecular testing for predicting susceptibility/resistance is suitable for effective antimicrobial resistance surveillance and individualized treatment decisions.

Analysis of Plant and Fungal Transcripts from Resistant and Susceptible Phenotypes of Leptospermum scoparium Challenged by Austropuccinia psidii.

Austropuccinia psidii is the causal pathogen of myrtle rust disease of Myrtaceae. To gain understanding of the initial infection process, gene expression in germinating A. psidii urediniospores and in Leptospermum scoparium-inoculated leaves were investigated via analyses of RNA sequencing samples taken 24 and 48 h postinoculation (hpi). Principal component analyses of transformed transcript count data revealed differential gene expression between the uninoculated L. scoparium control plants that correlated with the three plant leaf resistance phenotypes (immunity, hypersensitive response, and susceptibility). Gene expression in the immune resistant plants did not significantly change in response to fungal inoculation, whereas susceptible plants showed differential expression of genes in response to fungal challenge. A putative disease resistance gene, jg24539.t1, was identified in the L. scoparium hypersensitive response phenotype family. Expression of this gene may be associated with the phenotype and could be important for further understanding the plant hypersensitive response to A. psidii challenge. Differential expression of pathogen genes was found between samples taken 24 and 48 hpi, but there were no significant differences in pathogen gene expression that were associated with the three different plant leaf resistance phenotypes. There was a significant decrease in the abundance of fungal transcripts encoding three putative effectors and a putative carbohydrate-active enzyme between 24 and 48 hpi, suggesting that the encoded proteins are important during the initial phase of infection. These transcripts, or their translated proteins, may be potential targets to impede the early phases of fungal infection by this wide-host-range obligate biotrophic basidiomycete.

A Genome-Focused Investigation Reveals the Emergence of a Mycobacterium tuberculosis Strain Related to Multidrug-Resistant Tuberculosis in the Amazon Region of Brazil.

A previous study in Pará, Northern Brazil, described a strain of Mycobacterium tuberculosis with a unique genotype (SIT2517/T1) associated with multidrug-resistant tuberculosis (MDR-TB). To improve our understanding of MDR-TB transmission dynamics of these strains within this region, we performed phenotypic and genotypic drug susceptibility testing (pDST/gDST), 24-loci mycobacterial interspersed repetitive units (MIRU-VNTR) genotyping, whole-genome sequencing (WGS) and geo-epidemiology analysis. Of the 28 SIT2517/T1 isolates, 19 (67.9%) could be genotyped by 24-loci MIRU-VNTR and 15 by WGS. All belonged to sublineage 4.1.1.3, distinct from other representative Lineage 4 isolates identified in Brazil. The MDR phenotype determined by pDST was confirmed by gDST, the latter also demonstrating the presence of additional mutations conferring pre-extensively drug-resistance (pre-XDR). Discrepancies between gDST and pDST were observed for pyrazinamide and fluoroquinolones. Thirteen out of 15 isolates analyzed by WGS were clustered when applying a 12 single nucleotide polymorphisms (SNPs) cutoff. The SIT2517/T1 isolates were distributed across the metropolitan regions of Belém and Collares municipalities, showing no geographic clustering. WGS-transmission network analysis revealed a high likelihood of direct transmission and the formation of two closely linked transmission chains. This study highlights the need to implement TB genomic surveillance in the Brazilian Amazon region.

Evaluating the efficacy of whole genome sequencing in predicting susceptibility profiles for first-line antituberculosis drugs

ObjectivesThis study aimed to examine the efficacy of whole genome sequencing (WGS) in accurately predicting susceptibility profiles, potentially eliminating the need for conventional phenotypic drug susceptibility testing (pDST) for first-line antituberculosis drugs in routine tuberculosis diagnosis. MethodsOver the period of 2017 to 2020, 1114 Mycobacterium tuberculosis complex isolates were collected with drug susceptibility testing conducted using the MGIT960 system and WGS performed for predicting drug resistance profiles. In addition, we implemented a new algorithm with an updated WGS workflow, omitting pan-susceptible strains from pDST. ResultsResults showed that out of 1075 analysed isolates, WGS-based genotypic sensitivity predictions for isoniazid, rifampicin, ethambutol, and pyrazinamide were 100% (95% CI, 99.6–100%), 100% (95% CI, 99.62–100%), 99.8% (95% CI, 99.26–99.94%), and 100% (95% CI, 99.63–100%), respectively. In contrast, the WGS-based genotypic resistance prediction, was 98.85% (95% CI, 93.77–99.79%) for isoniazid, 94.74% (95% CI, 82.71–98.54%) for rifampicin, 86.96% (95% CI, 67.87–95.46%) for ethambutol, and 75.7% (95% CI, 59.9–86.63%) for pyrazinamide. Moreover, WGS enabled the implementation of a new testing algorithm that made it unnecessary to perform pDST in 954 of all 1075 samples (88.7%) and in 890 of 901 pan-susceptible samples (98.8%). DiscussionIntegrating WGS into tuberculosis management offers significant potential to replace phenotypic drug susceptibility testing, especially for problematic drugs like pyrazinamide and ethambutol, potentially improving treatment outcomes.

Second-line drug-resistant TB and associated risk factors in Karakalpakstan, Uzbekistan

<sec><title>BACKGROUND</title>Drug-resistant TB (DR-TB) remains a major public health threat. In 2022, Uzbekistan reported 2,117 cases of DR-TB, with 69% tested for fluoroquinolone resistance. Limited information is available on the prevalence of resistance to bedaquiline, linezolid, and fluoroquinolone, which are key components of the all-oral treatment regimen for rifampicin-resistant TB in Uzbekistan.</sec><sec><title>METHODS</title>A retrospective study was conducted using extensive programmatic data from 2019 to 2023 in Uzbekistan. We assessed second-line drug-resistant TB (SLDR-TB) rates using phenotypic drug susceptibility testing (pDST). Demographic and clinical characteristics associated with SLDR-TB were analysed using multivariable logistic regression models based on the Allen-Cady approach.</sec><sec><title>RESULTS</title>In total, 2,405 patients with TB who had undergone pDST were included (median age 40 years, 47% female). The overall SLDR-TB resistance rate was 24% (95% CI 22–26). Prevalence of resistance to bedaquiline, linezolid, moxifloxacin, levofloxacin, and amikacin were respectively 3.1%, 0.8%, 15%, 13%, and 12%. Risk factors for SLDR-TB were resistance to rifampicin and/or isoniazid, exposure to clofazimine, retreatment status, contact with drug-susceptible TB case or DR-TB case, and diabetes.</sec><sec><title>CONCLUSIONS</title>The high prevalence of SLDR-TB is of major concern, emphasising the need for baseline pDST in RR-TB treatment. Identified risk factors can aid early detection of at-risk individuals and inform clinical practice.</sec>

First insight into the whole genome sequence variations in clarithromycin resistant Helicobacter pylori clinical isolates in Russia

Clarithromycin (CLR) is currently a key antibiotic for Helicobacter pylori infection treatment, however, the data on CLR resistance patterns in Russia are missing. Here, we applied WGS-based approach to H. pylori clinical isolates from Russia to comprehensively investigate sequence variation, identify putative markers of CLR resistance and correlate them with phenotypic susceptibility testing. The phenotypic susceptibility of 44 H. pylori isolates (2014–2022) to CLR was determined by disc diffusion method: 23 isolates were CLR-resistant and 21-CLR-susceptible. All isolates were subjected to WGS and submitted to GenBank. Based on complete sequence analysis, we showed that among all sequence variants, the combination of mutations A2146G/A2147G in the 23S rRNA gene is the most reliable for prediction of phenotypic susceptibility. For the first time, the average number of mutations in 106 virulence-associated genes between resistant and susceptible groups were compared. Moreover, this study presents the first WGS insight into genetic diversity of H. pylori in Russia with a particular focus on the molecular basis of drug resistance: the novel mutations were described as potential markers for the resistance development. Of these, the most prominent was a frameshift deletion (252:CGGGT) in HP0820 coding region, which is a good candidate for further investigation.

Evaluation of Antimicrobial Resistance Patterns of Pseudomonas aeruginosa Strains Isolated among COVID-19 Patients in Brazil Typed by Fourier-Transform Infrared Spectroscopy.

This study aimed to characterize Pseudomonas aeruginosa strains isolated from hospitalized patients during the COVID-19 pandemic. This was achieved using phenotypic and molecular techniques, including their antimicrobial resistance profile and biofilm formation. Eighteen strains were isolated from a hospital in Rio de Janeiro, Brazil, and identified by VITEK®2, MALDI-TOF/MS (VITEK MS® and MALDI Biotyper®), and 16S rRNA sequencing. Fourier-transform infrared (FTIR) spectroscopy, antimicrobial susceptibility testing, and biofilm formation and disinfectant tolerance tests were applied to evaluate the virulence characteristics of the strains. VITEK®2 (≥99%), VITEK MS® (≥82.7%), and MALDI Biotyper® (score ≥ 2.01) accurately identified the P. aeruginosa strains, but 16S rRNA sequencing did not differentiate the species P. aeruginosa from P. paraeruginosa. FTIR typing identified three different clusters, but no correlation between the phenotypical or antimicrobial susceptibility testing patterns was found. Most strains exhibited resistance to various antimicrobials. The exceptions were sensitivity to amikacin and norfloxacin, and consequently, these could be considered potential treatment options. Most strains (n = 15, 83.3%) produced biofilms on polystyrene. Sodium hypochlorite treatment (0.5%/15 min) was shown to be the most effective disinfectant for biofilm elimination. P. aeruginosa biofilm formation and tolerance to disinfectants demonstrate the need for effective cleaning protocols to eliminate contamination by this organism in the hospital environment and medical equipment.

A subanalysis of Clostridium perfringens bloodstream infections from a 5-year retrospective nationwide survey (ITANAEROBY)

Clostridium perfingens bloodstream infections (BSIs) can be associated with high mortality rates. We performed a subanalysis of all C. perfringens BSIs enrolled during a multicentric retrospective observational study (ITANAEROBY). Data were collected from January 2016 to December 2020. C. perfringens BSIs were 134 (134/1960, 6.8 %). The highest resistance rate was observed for clindamycin (26/120, 21.6 %), penicillin (11/71, 15.4 %) and metronidazole (14/131, 10.7 %). In conclusion, C. perfringens reduced susceptibility phenotype to first-line therapy.

Rapid Phenotypic and Genotypic Antimicrobial Susceptibility Testing Approaches for Use in the Clinical Laboratory.

The rapid rise in increasingly resistant bacteria has become a major threat to public health. Antimicrobial susceptibility testing (AST) is crucial in guiding appropriate therapeutic decisions and infection prevention practices for patient care. However, conventional culture-based AST methods are time-consuming and labor-intensive. Therefore, rapid AST approaches exist to address the delayed gap in time to actionable results. There are two main types of rapid AST technologies- phenotypic and genotypic approaches. In this review, we provide a summary of all commercially available rapid AST platforms for use in clinical microbiology laboratories. We describe the technologies utilized, performance characteristics, acceptable specimen types, types of resistance detected, turnaround times, limitations, and clinical outcomes driven by these rapid tests. We also discuss crucial factors to consider for the implementation of rapid AST technologies in a clinical laboratory and what the future of rapid AST holds.

Characterization of methicillin resistant Staphylococcus Aureus in municipal wastewater in Finland

Wastewater-based surveillance (WBS) of multidrug-resistant bacteria could complement clinical data, serving as a population-level early warning tool. This study evaluated WBS as a pandemic preparedness tool, by selectively isolating and culturing methicillin-resistant Staphylococcus aureus (MRSA) with CHROMagar MRSA. Some 24-h composite wastewater samples (n = 80) were collected from ten treatment plants across Finland between February 2021 and January 2022. MRSA prevalence in wastewater samples was 27.5% (n = 22/80), showing seasonal and temporal variations. Phenotypic antimicrobial susceptibility testing (AST) with microdilution showed that over 80% of isolates were drug-resistant to clindamycin, sulfamethoxazole/trimethoprim, tetracycline, fusidic acid, and erythromycin. Four isolates (18.2%) were vancomycin-resistant. WGS revealed that 31.8% (n = 7) of the isolates belonged to the ST8-t008 and ST6-t304 spa types, respectively. In addition, two spa types (t011 and t034) belong to the CC398 complex. The mecA gene was found in all isolates (n = 22) and three tetracycline resistance determinants (tet38, tetK, and tetM) were detected with tet38 being the most abundant (81.8%, n = 18/22). Three isolates harboured the plasmid-mediated sat4 gene that confers resistance to Streptothricin. In addition, resistance determinants to macrolide antibiotics (mph (C)/msr (A) and fosfomycin (fosB) were detected in the seven isolates that belonged to spa type t008. All isolates except one harboured the SCCmec_type_IVa(2B). Six ST8 isolates harboured the LukS/F-PV genes encoding the Panton–Valentine leukocidin (PVL) and were also positive for the Arginine Catabolic Mobile Element (ACME), suggesting they belong to the USA300 clone. The Inc18 plasmid was the most abundant as it was detected in 72.7% (n = 16/22) of the isolates. Other plasmid replicons detected were the rep_trans and repA_N which were detected in 45.4% (n = 10/22) and 40.9% (n = 9/22) of the isolates respectively. Ten isolates harboured at least three plasmid replicons and no plasmid replicons were detected in four isolates (ST6/t304). The cgMLST revealed that some isolates aggregated into two genomically indistinguishable clusters: ST6/t304 belonging to cluster type CT12405 (≤20 allelic differences) and ST8/t008 belonging to cluster type CT1925 (<8 allelic differences). Overall, we found a high genotypic concordance with the national clinical bacterial resistance data. Our study demonstrates the sensitivity of culture-based wastewater surveillance for MRSA using clinical media following pre-enrichment, reliably predicting pathogen occurrence at the population level.

HIV-1 Integrase T218I/S Polymorphisms Do Not Reduce HIV-1 Integrase Inhibitors' Phenotypic Susceptibility.

The recently Food and Drug Administration (FDA)-approved cabotegravir (CAB) has demonstrated efficacy as an antiretroviral agent for HIV treatment and prevention, becoming an important tool to stop the epidemic in the United States of America (USA). However, the effectiveness of CAB can be compromised by the presence of specific integrase natural polymorphisms, including T97A, L74M, M50I, S119P, and E157Q, particularly when coupled with the primary drug-resistance mutations G140S and Q148H. CAB's recent approval as a pre-exposure prophylaxis (PrEP) may increase the number of individuals taking CAB, which, at the same time, could increase the number of epidemiological implications. In this context, where resistance mutations, natural polymorphisms, and the lack of drug-susceptibility studies prevail, it becomes imperative to comprehensively investigate concerns related to the use of CAB. We used molecular and cell-based assays to assess the impact of T218I and T218S in the context of major resistance mutations G140S/Q148H on infectivity, integration, and resistance to CAB. Our findings revealed that T218I and T218S, either individually or in combination with G140S/Q148H, did not significantly affect infectivity, integration, or resistance to CAB. Notably, these polymorphisms also exhibited neutrality concerning other widely used integrase inhibitors, namely raltegravir, elvitegravir, and dolutegravir. Thus, our study suggests that the T218I and T218S natural polymorphisms are unlikely to undermine the effectiveness of CAB as a treatment and PrEP strategy.

MiR-155 enhances apoptosis of macrophage through suppressing PI3K-AKT activation in Pseudomonas aeruginosa keratitis

Keratitis induced by Pseudomonas aeruginosa (P. aeruginosa) is an acute and serious corneal inflammation. As a family of gene regulators, miRNAs play a crucial role in modulating host response after microbial invasion. However, their functions in P. aeruginosa keratitis remain largely unclear. In the present study, we demonstrated that miR-155 expression was significantly increased in macrophages and corneal tissue after P. aeruginosa infection. In vivo studies demonstrated that mice with miR-155 knockdown displayed more resistance to P. aeruginosa keratitis, with a lower bacterial burden. In addition, in vitro and in vivo studies indicated that miR-155 enhanced apoptosis of macrophages after P. aeruginosa infection, and resulted in a susceptible phenotype of P. aeruginosa keratitis. Moreover, miR-155 induced apoptosis through reducing activation of PI3K-Akt signaling pathway. Our data provided evidence of miR-155 mediated apoptosis of macrophage in P. aeruginosa keratitis, which may be an underlying target for the therapy of P. aeruginosa keratitis and other infectious diseases.

Performance evaluation of the Xpert MTB/XDR test for the detection of drug resistance to Mycobacterium tuberculosis among people diagnosed with tuberculosis in South Africa.

Drug-resistant tuberculosis (TB) poses a significant public health concern in South Africa due to its complexity in diagnosis, treatment, and management. This study assessed the diagnostic performance of the Xpert MTB/XDR test for detecting drug resistance in patients with TB by using archived sputum sediments. This study analyzed 322 samples collected from patients diagnosed with TB between 2016 and 2019 across South Africa, previously characterized by phenotypic and genotypic methods. The Xpert MTB/XDR test was evaluated for its ability to detect resistance to isoniazid (INH), ethionamide (ETH), fluoroquinolones (FLQ), and second-line injectable drugs (SLIDs) compared with phenotypic drug susceptibility testing (pDST) and whole-genome sequencing (WGS). Culture, Xpert MTB/RIF Ultra, and Xpert MTB/RIF (G4) tests were performed to determine sensitivity and agreement with this test for TB detection. The sensitivities using a composite reference standard, pDST, and sequencing were >90% for INH, FLQ, amikacin (AMK), kanamycin (KAN), and capreomycin (CAP) resistance, meeting the WHO target product profile criteria for this class. A lower sensitivity of 65.9% (95% CI: 57.1-73.6) for ETH resistance was observed. The Xpert MTB/XDR showed a sensitivity of 98.3% (95% CI: 96.1-99.3) and specificity of 100% (95% CI: 86.7-100) compared with culture, a positive percent agreement (PPA) of 98.8% (95% CI: 93.7-99.8) and negative percent agreement (NPA) of 100.0% (95% CI: 78.5-100.0) compared with G4, and a PPA of 99.5% (95% CI: 97.3-99.9) and NPA of 100.0% (95% CI: 78.5-100.0) compared with Xpert MTB/RIF Ultra for detecting Mycobacterium tuberculosis. The test offers a promising solution for the rapid detection of drug-resistant TB and could significantly enhance control efforts in this setting.

Validation of a phenotyping method to identify PRRSV-resilient sows and its impact on sow stayability.

Endemic and epidemic outbreaks of porcine reproductive and respiratory syndrome virus (PRRSV) are causing large economic losses in commercial pig production worldwide. Given the complexity of controlling this disease with vaccines or other biosecurity measures, the selection for pigs with a natural resilience to this infection has been proposed as an alternative approach. In this context, we previously reported a vaccine-based protocol to classify 6-week-old female piglets from one farm into resilient and susceptible phenotypes. Subsequent analysis showed that resilient sows had fewer lost piglets during a PRRSV epidemic. In the present study, we validated the results in four additional farms by showing a robust effect on the percentage of piglets lost (P<0.05). We were able to associate the resilient phenotype with a 2-4% reduction in piglet losses on sow farms in both endemic and endemic/epidemic situations. Also consistent with previous results, susceptible sows delivered on average, almost 0.5 more piglets born per parity (P<0.05). However, we show here that resilient sows have a longer stayability in the farm (+57 d; P<0.05) and +0.3 more successful parities (P<0.05), which balances the total number of piglets born and born alive in the full productive life of the sow between the two groups. Resilient sows thus contribute towards to a more sustainable production system, reducing sow replacement and piglet mortality. The validation of this protocol on four independent production farms paves the way for the study of the genetic variation underlying the resilient/susceptible classification, with a view to incorporating this information into selection programs in the future.

The Drug Susceptibility of Non-Tuberculous Mycobacteria (NTM) in a Referral Hospital in Rome from 2018 to 2023.

Background: The treatment of non-tuberculous mycobacterial (NTM) infections is challenging because of the difficulty in obtaining phenotypic (pDST) and/or molecular (mDST) drug susceptibility testing and the need of a multi-drug regimen. Objectives: The objective was to describe the in vitro susceptibility patterns of various NTM species through an analysis of susceptibility results obtained on isolates collected between 2018 and 2023. Methods: Species identification and mutations in rrs or rrl genes (mDST) were identified by a line probe assay, while the pDST was performed by broth microdilution and interpreted according to CLSI criteria. Results: We analysed 337 isolates of NTM belonging to 15 species/subspecies. The Mycobacterium avium complex (MAC) was the most common (62%); other species identified included M. gordonae (11%), M. kansasii (5%), the M. abscessus complex (8%), M. chelonae (6%), and M. fortuitum (2%). The results of pDST (claritromycin and amikacin) and mDST (rrl and rrs genes) on 66 NTM strains showed that while wild-type rrl and rrs occurred in 86.3% and 94% strains, respectively, the pDST showed 88% sensitivity for clarithromycin and 57.5% for amikacin. The main incongruity was observed for macrolides. Conclusions: Most NTM are likely to be susceptible to macrolides and aminoglycosides. The molecular identification of resistant genotypes is accurate and strongly recommended for optimal patient management.

Applying whole genome sequencing to predict phenotypic drug resistance in Mycobacterium tuberculosis: leveraging 20 years of nationwide data from Denmark.

Infection with Mycobacterium tuberculosis remains one of the biggest causes of death from a single microorganism worldwide, and the continuous emergence of drug resistance aggravates our ability to cure the disease. New improved resistance detection methods are needed to provide adequate treatment, such as whole genome sequencing (WGS), which has been used increasingly to identify resistance-conferring mutations over the last decade. The steadily increasing knowledge of resistance-conferring mutations increases our ability to predict resistance based on genomic data alone. This study evaluates the performance of WGS to predict M. tuberculosis complex resistance. It compares WGS predictions with the phenotypic (culture-based) drug susceptibility results based on 20 years of nationwide Danish data. Analyzing 6,230 WGS-sequenced samples, the sensitivities for isoniazid, rifampicin, ethambutol, and pyrazinamide were 82.5% [78.0%-86.5%, 95% confidence interval (CI)], 97.3% (90.6%-99.7%, 95% CI), 58.0% (43.2%-71.8%, 95% CI), and 60.5% (49.0%-71.2%, 95% CI), respectively, and specificities were 99.8% (99.7%-99.9%, 95% CI), 99.8% (99.7%-99.9%, 95% CI), 99.4% (99.2%-99.6%, 95% CI), and 99.9% (99.7%-99.9%, 95% CI), respectively. A broader range of both sensitivities and specificities was observed for second-line drugs. The results conform with previously reported values and indicate that WGS is reliable for routine resistance detection in resource-rich tuberculosis low-incidence and low-resistance settings such as Denmark.

Evaluation of WHO catalog of mutations and five WGS analysis tools for drug resistance prediction of Mycobacterium tuberculosis isolates from China.

The continuous advancement of molecular diagnostic techniques, particularly whole-genome sequencing (WGS), has greatly facilitated the early diagnosis of drug-resistant tuberculosis patients. Nonetheless, the interpretation of results from various types of mutations in drug-resistant-associated genes has become the primary challenge in the field of molecular drug-resistance diagnostics. In this study, our primary objective is to evaluate the diagnosis accuracy of the World Health Organization (WHO) catalog of mutations and five WGS analysis tools (PhyResSE, Mykrobe, TB Profiler, Gen-TB, and SAM-TB) in drug resistance to 10 anti-Mycobacterium tuberculosis (MTB) drugs. We utilized the data of WGS collected between 2014 and 2017 in Zhejiang Province, consisting of 110 MTB isolates as detailed in our previous study. Based on phenotypic drug susceptibility testing (DST) results using the proportion method on Löwenstein-Jensen medium with antibiotics, we evaluated the predictive accuracy of genotypic DST obtained by these tools. The results revealed that the WHO catalog of mutations and five WGS analysis tools exhibit robust predictive capabilities concerning resistance to isoniazid, rifampicin, ethambutol, streptomycin, amikacin, kanamycin, and capreomycin. Notably, Mykrobe, SAM-TB, and TB Profiler demonstrate the most accurate predictions for resistance to pyrazinamide, prothionamide, and para-aminosalicylic acid, respectively. These findings are poised to significantly guide and influence future clinical treatment strategies and resistance monitoring protocols.IMPORTANCEWhole-genome sequencing (WGS) has the potential for the early diagnosis of drug-resistant tuberculosis. However, the interpretation of mutations of drug-resistant-associated genes represents a significant challenge as the amount and complexity of WGS data. We evaluated the accuracy of the World Health Organization catalog of mutations and five WGS analysis tools in predicting drug resistance to first-line and second-line anti-TB drugs. Our results offer clinicians guidance on selecting appropriate WGS analysis tools for predicting resistance to specific anti-TB drugs.

Quantitative drug susceptibility testing for Mycobacterium tuberculosis using unassembled sequencing data and machine learning.

There remains a clinical need for better approaches to rapid drug susceptibility testing in view of the increasing burden of multidrug resistant tuberculosis. Binary susceptibility phenotypes only capture changes in minimum inhibitory concentration when these cross the critical concentration, even though other changes may be clinically relevant. We developed a machine learning system to predict minimum inhibitory concentration from unassembled whole-genome sequencing data for 13 anti-tuberculosis drugs. We trained, validated and tested the system on 10,859 isolates from the CRyPTIC dataset. Essential agreement rates (predicted MIC within one doubling dilution of observed MIC) were above 92% for first-line drugs, 91% for fluoroquinolones and aminoglycosides, and 90% for new and repurposed drugs, albeit with a significant drop in performance for the very few phenotypically resistant isolates in the latter group. To further validate the model in the absence of external MIC datasets, we predicted MIC and converted values to binary for an external set of 15,239 isolates with binary phenotypes, and compare their performance against a previously validated mutation catalogue, the expected performance of existing molecular assays, and World Health Organization Target Product Profiles. The sensitivity of the model on the external dataset was greater than 90% for all drugs except ethionamide, clofazimine and linezolid. Specificity was greater than 95% for all drugs except ethambutol, ethionamide, bedaquiline, delamanid and clofazimine. The proposed system can provide quantitative susceptibility phenotyping to help guide antimicrobial therapy, although further data collection and validation are required before machine learning can be used clinically for all drugs.