Whole-genome sequence analysis of Mycobacteria tuberculosis bacteria to identify the genetic determinants and mechanisms of anti-tuberculosis drug

阻力。结核病（TB）是一个重大的公共卫生问题。结核分枝杆菌菌株对用于治疗该疾病的药物具有耐药性的出现威胁着控制结核病的努力。对至少两种一线药物的耐药性被称为耐多药结核病（MDR-TB），而对用于治疗耐多药结核病的任何药物的额外耐药性被称为广泛耐药结核病。这些菌株的出现使临床药物选择复杂化，加上药物的毒副作用，导致预后差，依从性差，最终可能扩大耐药性。因此，早期发现耐药菌株至关重要。临床样本的敏感性测试传统上是通过表型方法进行的，这种方法成本高昂，而且可能需要数周时间，因为它们涉及培养和操作高度传染性的细菌。对于一些一线药物，也有基于分子的测试，但大多数灵敏度较低。耐药性几乎完全是由编码靶标或药物激活酶的基因的点突变和插入或缺失的积累而产生的。基因型-表型关联的研究使耐药标记突变文库的建立成为可能。因此，使用临床样本的全基因组序列分析与突变文库相结合，可以比表型方法更及时地为临床药物管理提供信息。然而，挑战之一是实施痰样本的直接分析，其中细菌培养之前的序列仍然是必要的。一种被称为选择性全基因组扩增（SWGA）的方法是一种潜在的解决方案，它可以通过使用不退火痰中非结核分枝杆菌元基因组的特定引物，从复杂样品中扩增结核分枝杆菌目标基因组。在此基础上，本项目的目标是：(i)通过应用基于回归2的模型，从全基因组序列数据中识别新的耐药突变和抗结核药物耐药机制；（ii）利用蛋白质结构模型描述突变对蛋白质稳定性和药物对接的影响；（iii）开发定量方法，根据全基因组序列数据快速预测耐药性。为了实现这些目标，将获得强大的生物信息学和大数据分析技能并将其应用于基因组学领域。将获得跨学科技能，包括结核分枝杆菌培养培训和SWGA方法的发展。最后，该项目的成果可能导致新的诊断工具，协助结核病的管理，并最终使公共卫生受益。圣乔治医院和大学的参与将协助在临床环境中推出任何测序或实验室开发的工具。

resistance.Tuberculosis disease (TB) is a major public health problem. The emergence of Mycobacteriumtuberculosis strains resistant to the drugs used to treat the disease threatens to derail efforts tocontrol TB. Resistance to at least two of the first line drugs is denoted as multidrug-resistanttuberculosis (MDR-TB), whilst additional resistance to any drug used to treat MDR-TB is known asextensively drug-resistant tuberculosis (XDR-TB). The appearance of these strains has complicatedclinical drug selection, which along with the considerable toxicity and side effects of the drugs resultin poor outcomes, less compliance and ultimately can amplify resistance. For this reason, earlydetection of resistant strains is crucial. Susceptibility tests of clinical samples have been traditionallycarried out by phenotypic methods, which are costly and can take weeks since they involve cultureand manipulation of highly infectious bacteria. For some first-line drugs there are also molecularbasedtests, but most have low sensitivity.Drug resistance is conferred almost exclusively by accumulation of point mutations and insertionsand deletions in genes encoding targets or drug-activating enzymes. The study of genotypephenotypeassociations has enabled the creation of a mutation library for drug resistance markers.Therefore, the use of whole-genome sequence analysis of clinical samples in combination with amutation library can inform clinical drug management, in a more timely fashion than phenotypicmethods. Nevertheless, one of the challenges is implement the direct analysis of sputum samples,for which culture of the bacteria prior to sequence is still necessary. A method known as selectivewhole-genome amplification (SWGA) is a potential solution, and enables the amplification of the M.tuberculosis target genome from a complex sample by using specific primers that do not anneal tonon- M. tuberculosis meta genomes in the sputum.On this basis, the aims of this project are: (i) to identify novel resistance mutations and mechanismsof anti-tuberculosis drug resistance from whole-genome sequence data by applying regression-2based models; (ii) to characterise the effects of mutations on protein stability and drug docking byusing protein structure models; (iii) to develop quantitative methods to rapidly predict drugresistance from whole genome sequence data. In order to accomplish these aims, strongbioinformatics and big data analysis skills will be gained and applied in the field of genomics.Interdisciplinary skills will be gained including training in culture of M. tuberculosis and developmentof the SWGA approach. Finally, the results of this project could lead to new diagnostic tools, assistwith the management of the TB, and eventually benefit public health. The participation of St.George's Hospital and University will assist with the roll-out in a clinical setting of any sequencingor laboratory-based tools developed..