Understanding how penicillin resistance develops in Streptococcus pneumoniae clinical populations
Understanding how penicillin resistance develops in Streptococcus pneumoniae clinical populations
批准号:
2902003
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --
中文摘要
研究背景肺炎链球菌是一种成功的人类病原体,也是世界范围内引起肺炎和死亡的主要原因。青霉素(和类似药物)通常用于治疗这些感染;然而,全球出现越来越多的抗生素耐药菌株,威胁患者。为了改善疾病管理,我们必须了解肺炎链球菌细胞如何应对青霉素压力,以及这种选择如何塑造细菌种群。芬顿实验室最近的工作揭示了称为pde 1的基因的功能缺失突变导致肺炎链球菌临床种群的青霉素耐药性。Pde 1是第二信使细菌应激反应的一部分,为了研究其功能,我们进行了全基因组分析(Tn-seq),确定了依赖于Pde 1的青霉素抗性所需的四个基因。我们假设这些蛋白质形成一个复合体,将第二信使信号传导与细胞壁生物学和青霉素药物靶点联系起来。目的1)表征肺炎链球菌中Pde 1依赖性青霉素耐药性所需基因的功能2)测量每个位点对临床菌株青霉素耐药性的影响3)建立一个将这些基因的遗传变异与临床人群的青霉素耐药性联系起来的分子模型。明确和及时地需要开发新的肺炎链球菌感染控制方案。这个项目建立在我们实验室最近的发现之上,即pde 1依赖的青霉素耐药性是通向青霉素耐药性的重要“门户”,并将发展对这种生物学如何工作的分子理解。这个项目结合了多个实验室的专业知识和互补经验:分子遗传学,细菌细胞信号传导和进化生物学。这种强大的合作将产生肺炎链球菌生物学的基本理解,利用这对改善治疗和监测的方法。研究方法我们的工作已经确定了所需的基因PDE 1依赖的青霉素耐药肺炎链球菌。我们假设两个参与细胞壁应激,而两个参与糖-磷酸代谢。为了实现我们的目标,EST 1将涉及纯化每种蛋白质,并使用第二信使信号核苷酸和细胞壁底物进行蛋白质结合测定。结构建模表明,已识别的蛋白质形成跨膜复合物,我们将使用分裂荧光素酶测定和活细胞共定位显微镜对其进行测试,使用AlphaFold对推定的复合物进行建模。将使用我们的临床分离物收集来测试这些基因对整个物种的青霉素耐药性的影响。将使用我们的比较基因组学方法来研究青霉素耐药菌株中四个基因的遗传变异。综合起来,这些数据将产生一个模型,说明青霉素耐药性如何在肺炎链球菌临床人群中出现。
英文摘要
Project BackgroundStreptococcus pneumoniae is a successful human pathogen and a leading cause of pneumonia and death in the world. Penicillins (and similar drugs) are commonly used to treat these infections; however a growing number of antibiotic resistant strains are emerging globally which threaten patients. To improve disease management, we must understand how S.pneumoniae cells deal with penicillin stress and how this selection shapes bacterial populations.Recent work in the Fenton lab has revealed loss-of-function mutations in the gene called pde1 leads to penicillin resistance in S.pneumoniae clinical populations. Pde1 is part of the second messenger bacterial stress response and to study its function we carried out whole-genome profiling (Tn-seq), identifying four genes required for pde1-dependent penicillin resistance. We hypothesise these proteins form a complex, linking second messenger signalling with cell wall biology and penicillin drug targets.Objectives1) Characterise the functions of genes required for Pde1-dependent penicillin resistance in S.pneumoniae 2) Measure the effect each locus has on penicillin resistance across clinical strains 3) Develop a molecular model linking genetic variation in these genes to penicillin resistance in clinical populations.TimelinessSet against the backdrop of increasing antimicrobial resistance there is a clear and timely need to develop new control regimes for S.pneumoniae infections. This project builds on our labs recent findings that pde1-dependent penicillin resistance is an important 'gateway' towards penicillin resistance and will develop a molecular understanding for how this biology works.This project combines the expertise of multiple labs with complementary experience in: molecular genetics, bacterial cell signalling and evolutionary biology. This formidable collaboration will generate fundamental understanding of S.pneumoniae biology, using this towards improving treatment and surveillance approaches.Research ApproachOur work has identified genes required for pde1-dependant penicillin resistance in S.pneumoniae. We hypothesise two are involved in cell wall stress, whilst two are involved in sugar-phosphate metabolism. To meet our objectives, Objective1 will involve purifying each protein and carrying out protein binding assays using second messenger signalling-nucleotides and cell wall substrates. Structural modelling suggests identified proteins form a membrane-spanning complex and we will test this using split-luciferase assays and live-cell co-localisation microscopy, modelling the putative complex using AlphaFold. Objective2, will use our clinical isolate collection to test the impact these genes have on penicillin resistance across the species. Objective3, will use our comparative genomics methods to study genetic variation within the four genes across penicillin resistant isolates. Combined, this data will generate a model for how penicillin resistance emerges in S.pneumoniae clinical populations.
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