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New drugs targeting the electron transport chain (ETC) seem to be a promising advance in leprosy treatment. In this study, we evaluated the bactericidal activity of telacebec (TCB), a phase 2 drug candidate for tuberculosis, alongside known ETC-targeting antibiotics, bedaquiline (BDQ) and clofazimine (CFZ), as monotherapy or in combination. We used the reference leprosy proportional bactericidal mouse footpad model. Four hundred and ten mice were inoculated in the footpads with 5x104 to 5x100 bacilli of M. leprae strain THAI53 for the untreated control group and groups treated with drug-monotherapies, and with 5x104 to 5x101 for groups treated with drug-combinations. Mice were randomly allocated into the following groups: 2 control groups (untreated or standard multi drug therapy (MDT), rifampin, dapsone and clofazimine with dosing equipotent to human dosing) and 7 test groups (TCB 10mg/kg, bedaquiline 25mg/kg (BDQ), clofazimine 20mg/kg (CFZ), CFZ + BDQ, TCB + BDQ, TCB + CFZ, TCB + CFZ + BDQ). Mice in the test groups received either one month treatment (MDT) or a single dose of the drugs (TCB, RIF, BDQ, CFZ). Twelve months later, mice were sacrificed to enumerate M. leprae bacilli in the footpad. All the footpads became negative in the MDT, TCB and combination groups except in the TCB + CFZ group where 2 mice remained positive in the 5x104 inoculum. We demonstrated that monotherapy of TCB exhibited bactericidal activity against M. leprae comparable to that of MDT and that all combination therapies were as effective as MDT, except the combination TCB + CFZ, possibly due to an antagonism between these two drugs.

Bedaquiline (BDQ), by targeting the electron transport chain and having a long half-life, is a good candidate to simplify leprosy treatment. Our objectives were to (i) determine the minimal effective dose (MED) of BDQ administered orally, (ii) evaluate the benefit of combining two inhibitors of the respiratory chain, BDQ administered orally and clofazimine (CFZ)) and (iii) evaluate the benefit of an intramuscular injectable long-acting formulation of BDQ (intramuscular BDQ, BDQ-LA IM), in a murine model of leprosy. To determine the MED of BDQ administered orally and the benefit of adding CFZ, 100 four-week-old female nude mice were inoculated in the footpads with 5x103 bacilli of M. leprae strain THAI53. Mice were randomly allocated into: 1 untreated group, 5 groups treated with BDQ administered orally (0.10 to 25 mg/kg), 3 groups treated with CFZ 20 mg/kg alone or combined with BDQ administered orally 0.10 or 0.33 mg/kg, and 1 group treated with rifampicin (RIF) 10 mg/kg. Mice were treated 5 days a week during 24 weeks. To evaluate the benefit of the BDQ-LA IM, 340 four-week-old female swiss mice were inoculated in the footpads with 5x103 to 5x101 bacilli (or 5x100 for the untreated control group) of M. leprae strain THAI53. Mice were randomly allocated into the following 11 groups treated with a single dose (SD) or 3 doses (3D) 24h after the inoculation: 1 untreated group, 2 treated with RIF 10 mg/kg SD or 3D, 8 treated with BDQ administered orally or BDQ-LA IM 2 or 20 mg/kg, SD or 3D. Twelve months later, mice were sacrificed and M. leprae bacilli enumerated in the footpad. All the footpads became negative with BDQ at 3.3 mg/kg. The MED of BDQ administered orally against M. leprae in this model is therefore 3.3 mg/kg. The combination of CFZ and BDQ 10-fold lower than this MED did not significantly increase the bactericidal activity of CFZ. The BDQ-LA IM displayed similar or lower bactericidal activity than the BDQ administered orally. We demonstrated that the MED of BDQ administered orally against M. leprae was 3.3 mg/kg in mice and BDQ did not add significantly to the efficacy of CFZ at the doses tested. BDQ-LA IM was similar or less active than BDQ administered orally at equivalent dosing and frequency but should be tested at higher dosing in order to reach equivalent exposure in further experiments.

Background The use of multiplex PCR to shorten time to identification of pathogens and their resistance mechanisms for patients with ventilator-associated pneumonia (VAP) is attractive, but poorly studied. The multiplex PCR–based Unyvero pneumonia cartridge assay can directly identify 20 bacteria and one fungus, amongst the most frequently causing VAP, and 19 of their resistance markers in clinical specimens (bronchoalveolar lavage or tracheal aspirate), with a turnaround time of 4–5 h. We performed this study to evaluate the concordance between the multiplex PCR–based Unyvero pneumonia cartridge assay and conventional microbiological techniques to identify pathogens and their resistance mechanisms in patients with VAP. Methods All patients suspected of having VAP (January 2016 to January 2019), who underwent fiberoptic bronchoscopy with bronchoalveolar lavage fluid (BALF) and whose BALF microscopy examination revealed intracellular bacteria, were included. BALF conventional cultures (gold standard), antimicrobial susceptibility testing and processing for the Unyvero pneumonia cartridge were done. Culture and Unyvero results were compared. Results Compared to cultures of the 93 samples processed for both techniques, Unyvero correctly identified pathogens in 68 (73%) proven VAP episodes, was discordant for 25 (27%), detected no pathogen in 11 and overdetected a not otherwise found pathogen in six. For the eight remaining discordant results, the pathogen responsible for VAP was not included in the Unyvero cartridge panel or it grew at a non-significant level in culture. Amongst the 31 (33%) resistance mechanism discordances observed, 22 were resistance detection failures and 24 concerned Pseudomonas aeruginosa . Conclusions Compared to conventional microbiological cultures, the Unyvero pneumonia cartridge had poor diagnostic performance: it correctly identified pathogens and their resistance mechanisms in 73% and 67% of VAP cases, respectively. The lack of performance on the resistance mechanism was more pronounced when the pathogen detected was a Pseudomonas aeruginosa .

High-dose isoniazid is recommended to treat multidrug-resistant tuberculosis (MDR TB). Among 958 MDR TB isolates identified in France during 2008-2022, 93.1% exhibited high-level isoniazid resistance, and molecular testing showed limited diagnostic accuracy in predicting resistance. Clinicians should reconsider using high-dose isoniazid in MDR TB treatment because of suboptimal effect and toxicity concerns.

We report the emergence of an atpE mutation in a clinical Mycobacterium tuberculosis strain. Genotypic and phenotypic bedaquiline susceptibility testing displayed variable results over time and ultimately were not predictive of treatment outcome. This observation highlights the limits of current genotypic and phenotypic methods for detection of bedaquiline resistance.

The GeneLEAD VIII (Diagenode, Belgium) is a new, fully automated, sample-to-result precision instrument for the extraction of DNA and PCR detection of Mycobacterium tuberculosis complex (MTBC) directly from clinical samples. The Deeplex Myc-TB ® assay (Genoscreen, France) is a diagnostic kit based on the deep sequencing of a 24-plexed amplicon mix allowing simultaneously the detection of resistance to 13 antituberculous (antiTB) drugs and the determination of spoligotype. We evaluated the performance of a strategy combining the both mentioned tools to detect directly from clinical samples, in 8 days, MTBC and its resistance to 13 antiTB drugs, and identify potential transmission of strains from patient-to-patient. Using this approach, we screened 112 clinical samples (65 smear-negative) and 94 MTBC cultured strains. The sensitivity and the specificity of the GeneLEAD/Deeplex Myc-TB approach for MTBC detection were 79.3% and 100%, respectively. One hundred forty successful Deeplex Myc-TB results were obtained for 46 clinical samples and 94 strains, a total of 85.4% of which had a Deeplex Myc-TB susceptibility and resistance prediction consistent with phenotypic drug susceptibility testing (DST). Importantly, the Deeplex Myc-TB assay was able to detect 100% of the multidrug-resistant (MDR) MTBC tested. The lowest concordance rates were for pyrazinamide, ethambutol, streptomycin, and ethionamide (84.5%, 81.5%, 73%, and 55%, respectively) for which the determination of susceptibility or resistance is generally difficult with current tools. One of the main difficulties of Deeplex Myc-TB is to interpret the non-synonymous uncharacterized variants that can represent up to 30% of the detected single nucleotide variants. We observed a good level of concordance between Deeplex Myc-TB-spoligotyping and MIRU-VNTR despite a lower discriminatory power for spoligotyping. The median time to obtain complete results from clinical samples was 8 days (IQR 7–13) provided a high-throughput NGS sequencing platform was available. Our results highlight that the GeneLEAD/Deeplex Myc-TB approach could be a breakthrough in rapid diagnosis of MDR TB in routine practice.

Clostridioides difficile (CD) infections are defined by toxins A (TcdA) and B (TcdB) along with the binary toxin (CDT). The emergence of the ‘hypervirulent’ (Hv) strain PR 027, along with PR 176 and 181, two decades ago, reshaped CD infection epidemiology in Europe. This study assessed MALDI‐TOF mass spectrometry (MALDI‐TOF MS) combined with machine learning (ML) and Deep Learning (DL) to identify toxigenic strains (producing TcdA, TcdB with or without CDT) and Hv strains. In total, 201 CD strains were analysed, comprising 151 toxigenic (24 ToxA+B+CDT+, 22 ToxA+B+CDT+ Hv+ and 105 ToxA+B+CDT−) and 50 non‐toxigenic (ToxA−B−) strains. The DL‐based classifier exhibited a 0.95 negative predictive value for excluding ToxA−B− strains, showcasing accuracy in identifying this strain category. Sensitivity in correctly identifying ToxA+B+CDT− strains ranged from 0.68 to 0.91. Additionally, all classifiers consistently demonstrated high specificity (>0.96) in detecting ToxA+B+CDT+ strains. The classifiers' performances for Hv strain detection were linked to high specificity (≥0.96). This study highlights MALDI‐TOF MS enhanced by ML techniques as a rapid and cost‐effective tool for identifying CD strain virulence factors. Our results brought a proof‐of‐concept concerning the ability of MALDI‐TOF MS coupled with ML techniques to detect virulence factor and potentially improve the outbreak's management. This study assessed the use of MALDI‐TOF Mass Spectrometry combined with Machine Learning including Deep Learning techniques to identify toxigenic and hypervirulent strains of Clostridioides difficile. The method demonstrated high accuracy, particularly in excluding non‐toxigenic strains with a negative predictive value of 0.95 and consistently high specificity (>0.96) for detecting binary producing strains. The findings suggest that MALDI‐TOF MS enhanced by ML techniques is a rapid, cost‐effective tool for detecting virulence factors in CD strains, potentially improving outbreak management.

Background Amikacin infusion requires targeting a peak serum concentration (C max ) 8–10 times the minimal inhibitory concentration, corresponding to a C max of 60–80 mg/L for the least susceptible bacteria to theoretically prevent therapeutic failure. Because drug pharmacokinetics on extracorporeal membrane oxygenation (ECMO) are challenging, we undertook this study to assess the frequency of insufficient amikacin C max in critically ill patients on ECMO and to identify relative risk factors. Methods This was a prospective, observational, monocentric study in a university hospital. Patients on ECMO who received an amikacin loading dose for suspected Gram-negative infections were included. The amikacin loading dose of 25 mg/kg total body weight was administered intravenously and C max was measured 30 min after the end of the infusion. Independent predicators of C max  < 60 mg/L after the first amikacin infusion were identified with mixed-model multivariable analyses. Various dosing simulations were performed to assess the probability of reaching 60 mg/L < C max < 80 mg/L. Results A total of 106 patients on venoarterial ECMO (VA-ECMO) (68%) or venovenous-ECMO (32%) were included. At inclusion, their median (1st; 3rd quartile) Sequential Organ-Failure Assessment score was 15 (12; 18) and 54 patients (51%) were on renal replacement therapy. Overall ICU mortality was 54%. C max was < 60 mg/L in 41 patients (39%). Independent risk factors for amikacin under-dosing were body mass index (BMI) < 22 kg/m 2 and a positive 24-h fluid balance. Using dosing simulation, increasing the amikacin dosing regimen to 30 mg/kg and 35 mg/kg of body weight when the 24-h fluid balance is positive and the BMI is ≥ 22 kg/m 2 or < 22 kg/m 2 (Table 3), respectively, would have potentially led to the therapeutic target being reached in 42% of patients while reducing under-dosing to 23% of patients. Conclusions ECMO-treated patients were under-dosed for amikacin in one third of cases. Increasing the dose to 35 mg/kg of body weight in low-BMI patients and those with positive 24-h fluid balance on ECMO to reach adequate targeted concentrations should be investigated.

Mycobacterium abscessus (MABS) displays differential subspecies susceptibility to macrolides. Thus, identifying MABS's subspecies (M. abscessus, M. bolletii and M. massiliense) is a clinical necessity for guiding treatment decisions. We aimed to assess the potential of Machine Learning (ML)‐based classifiers coupled to Matrix‐Assisted Laser Desorption/Ionization Time‐of‐Flight (MALDI‐TOF) MS to identify MABS subspecies. Two spectral databases were created by using 40 confirmed MABS strains. Spectra were obtained by using MALDI‐TOF MS from strains cultivated on solid (Columbia Blood Agar, CBA) or liquid (MGIT®) media for 1 to 13 days. Each database was divided into a dataset for ML‐based pipeline development and a dataset to assess the performance. An in‐house programme was developed to identify discriminant peaks specific to each subspecies. The peak‐based approach successfully distinguished M. massiliense from the other subspecies for strains grown on CBA. The ML approach achieved 100% accuracy for subspecies identification on CBA, falling to 77.5% on MGIT®. This study validates the usefulness of ML, in particular the Random Forest algorithm, to discriminate MABS subspecies by MALDI‐TOF MS. However, identification in MGIT®, a medium largely used in mycobacteriology laboratories, is not yet reliable and should be a development priority. Machine Learning (ML) enhances Mycobacterium abscessus (MABS) subspecies identification using Matrix‐Assisted Laser Desorption/Ionization Time‐of‐Flight (MALDI‐TOF) Mass Spectrometry (MS). The ML method demonstrated 100% accuracy in identifying subspecies on the Columbia Blood Agar (CBA) solid medium, with a reduction to 77.5% on the MGIT® liquid medium.

The treatment of Buruli ulcer (BU) that is caused by Mycobacterium ulcerans, is currently based on a daily administration of rifampin and streptomycin (RIF-STR). A fully oral intermittent regimen would greatly simplify its treatment on the field. The objective of this study was to assess the bactericidal and sterilizing activities of intermittent oral regimens in a murine model of established M. ulcerans infection. Regimens combining rifapentine (RFP 20 mg/kg) with either moxifloxacin (MXF 200 mg/kg), clarithromycin (CLR 100 mg/kg) or bedaquiline (BDQ 25 mg/kg) were administrated twice (2/7) or three (only for RFP-CLR 3/7) times weekly during 8 weeks. The bactericidal but also the sterilizing activities of these four intermittent oral regimens were at least as good as those obtained with control weekdays regimens, i.e. RFP-CLR 5/7 or RIF-STR 5/7. A single mouse from the RFP-MFX 2/7 group had culture-positive relapse at the end of the 28 weeks following treatment completion among the 157 mice treated with one of the four intermittent regimens (40 RFP-CLR 2/7, 39 RFP-CLR 3/7, 39 RFP-MXF 2/7, 39 RFP-BDQ 2/7). These results open the door for a fully intermittent oral drug regimen for BU treatment avoiding intramuscular injections and facilitating supervision by health care workers.