Shenzhen Center for Chronic Disease Control, Shenzhen, China.
Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Sciences, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity and Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Microbiol Spectr. 2022 Jun 29;10(3):e0271421. doi: 10.1128/spectrum.02714-21. Epub 2022 Jun 6.
Defining the precise relationship between resistance mutations and quantitative phenotypic drug susceptibility testing will increase the value of whole-genome sequencing (WGS) for predicting tuberculosis drug resistance. However, a large number of WGS data sets currently lack corresponding quantitative phenotypic data-the MICs. Using MYCOTBI plates, we determined the MICs to nine antituberculosis drugs for 154 clinical multidrug-resistant tuberculosis isolates from the Shenzhen Center for Chronic Disease Control in Shenzhen, China. Comparing MICs with predicted drug-resistance profiles inferred by WGS showed that WGS could predict the levels of resistance to isoniazid, rifampicin, streptomycin, fluoroquinolones, and aminoglycosides. We also found some mutations that may not be associated with drug resistance, such as EmbB D328G, mutations in the gene, and C-12T in the promoter. However, some strains carrying the same mutations showed different levels of resistance to the corresponding drugs. The MICs of different strains with the RpsL K88R, C-15T mutations and some with mutations in and , had MICs to the corresponding drugs that varied by 8-fold or more. This variation is unexplained but could be influenced by the bacterial genetic background. Additionally, we found that 32.3% of rifampicin-resistant isolates were rifabutin-susceptible, particularly those with mutations H445D, H445L, H445S, D435V, D435F, L452P, S441Q, and S441V. Studying the influence of bacterial genetic background on the MIC and the relationship between rifampicin-resistant mutations and rifabutin resistance levels should improve the ability of WGS to guide the selection of medical treatment regimens. Whole-genome sequencing (WGS) has excellent potential in drug-resistance prediction. The MICs are essential indications of adding a particular antituberculosis drug dosage or changing the entire treatment regimen. However, the relationship between many known drug-resistant mutations and MICs is unclear, especially for rarer ones. The results showed that WGS could predict resistance levels to isoniazid, rifampicin, streptomycin, fluoroquinolones, and aminoglycosides. However, some mutations may not be associated with drug resistance, and some others may confer various MICs to strains carrying them. Also, 32.3% of rifampicin (RIF)-resistant strains were classified as sensitive to rifabutin (RFB), and some mutations in the gene may be associated with this phenotype. Our data on the MIC distribution of strains with some rarer mutations add to the accumulated data on the resistance level associated with such mutations to help guide further research and draw meaningful conclusions.
定义耐药突变与定量表型药敏试验之间的精确关系将提高全基因组测序（WGS）预测结核病药物耐药性的价值。然而，目前大量的 WGS 数据集缺乏相应的定量表型数据（MICs）。我们使用 MYCOTBI 平板，测定了来自中国深圳慢性病预防控制中心的 154 例临床耐多药结核分离株对 9 种抗结核药物的 MIC。将 MIC 与 WGS 推断的预测耐药谱进行比较表明，WGS 能够预测异烟肼、利福平、链霉素、氟喹诺酮类和氨基糖苷类的耐药水平。我们还发现了一些可能与耐药性无关的突变，如 EmbB D328G、 基因中的突变和 启动子中的 C-12T。然而，一些携带相同突变的菌株对相应药物的耐药水平不同。RpsL K88R、 C-15T 突变以及一些 和 基因中的突变的不同菌株的 MIC 对相应药物的 MIC 差异可达 8 倍或更高。这种差异无法解释，但可能受细菌遗传背景的影响。此外，我们发现 32.3%的利福平耐药分离株对利福布丁敏感，特别是那些携带 基因 H445D、H445L、H445S、D435V、D435F、L452P、S441Q 和 S441V 突变的分离株。研究细菌遗传背景对 MIC 的影响以及利福平耐药突变与利福布丁耐药水平的关系，应能提高 WGS 指导治疗方案选择的能力。全基因组测序（WGS）在耐药性预测方面具有巨大潜力。MIC 是添加特定抗结核药物剂量或改变整个治疗方案的重要指标。然而，许多已知耐药突变与 MIC 之间的关系尚不清楚，特别是对于罕见的突变。结果表明，WGS 能够预测异烟肼、利福平、链霉素、氟喹诺酮类和氨基糖苷类的耐药水平。然而，一些突变可能与耐药性无关，而另一些突变可能使携带它们的菌株具有不同的 MIC。此外，32.3%的利福平（RIF）耐药株对利福布丁（RFB）敏感， 基因中的某些突变可能与这种表型有关。我们关于一些罕见突变菌株 MIC 分布的数据增加了与这些突变相关的耐药水平的累积数据，有助于指导进一步的研究并得出有意义的结论。
