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The role of MIC shifts as early markers of treatment failure in tuberculosis

M Moreno-Molina(1) C Mariner-Llicer(1) B Saavedra(2,3) E Mambuque(2) N Gomes(2) M Torres-Puente(1) L Villamayor(4) P Cano-Jimenez(1) M G Lopez(1) A Garcia-Basteiro(2,3) I Comas(1,5)

1:Biomedicine Institute of Valencia IBV-CSIC; 2:Centro de Investigação em Saúde de Manhiça; 3:ISGlobal, Barcelona Centre for International Health Research, Hospital Clínic - Universitat de Barcelona; 4:FISABIO Public Health; 5:CIBER in Epidemiology and Public Health

Understanding the pathogen genetic basis of treatment failure beyond canonical resistance in tuberculosis (TB) can have a major impact on its global control. In this work we performed deep whole-genome sequencing in serial TB samples from 40 patients from Mozambique during their first month of treatment. Then, using the EUCAST protocol, we determined the minimum inhibitory concentration (MIC) of six antitubercular drugs -isoniazid, rifampicin, ethambutol, streptomycin, levofloxacin and amikacin- for the baseline and a follow-up sample of every patient. We sought to assess how antibiotic selective forces shape tuberculosis population dynamics and diversity during the first weeks of treatment, and evaluate the impact of mutations both inside and outside of the canonical resistance genes in the overall MICs.

Analyzing the population dynamics between both samples, we detected that 26 patients experienced a decreased capacity to eliminate TB diversity during this early stage of treatment, and we correlated this finding with longer periods of culture positivity. Concurrently, we identified 12 cases where the MIC shifted to higher drug concentrations during treatment, with 10/12 failing to reduce diversity or become culture-negative. Thanks to deep sequencing, we could observe transient non-canonical heteroresistance at low frequencies, providing candidates to explain some of these MIC shifts. We reason that subtle shifts in minimum inhibitory concentration during early treatment may serve as a clinical tool to predict a reduced capacity to eliminate bacterial diversity but will need further validation. This, in turn, could be an indicator of worse prognosis and eventual treatment failure.

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