耐药结核分枝杆菌的适应性代价与补偿性进化

结核病耐药率的攀升是目前全球结核病防控面临的重大挑战。结核分枝杆菌主要通过其基因组中耐药相关基因发生点突变而获得耐药性。由于耐药相关基因通常具有重要的生理功能,其突变往往会导致结核分枝杆菌自身适应性下降,即产生“适应性代价”。然而,耐药结核分枝杆菌可通过进一步积累其他特定突变来回复其适应性,这种能使其适应性上升的突变称为“补偿性突变”。耐药结核分枝杆菌的补偿性进化被认为是耐药结核病广泛传播与流行的生物学基础。近年来,在结核病分子流行病学和基础研究领域,针对耐药结核分枝杆菌的补偿性进化开展了大量研究。本文从结核分枝杆菌的耐药分子机制、耐药突变的适应性代价与补偿性进化,以及补偿性进化如何影响耐药结核病传播等方面,综述耐药结核分枝杆菌补偿性进化的研究进展。     

耐药结核分枝杆菌潜伏-复发感染动物模型的研究进展

潜伏结核感染(latent tuberculosis infection,LTBI)复发是新发结核病的主要来源,其中耐药结核病所占比例较大,使耐药LTBI复发的防控成为结核病研究的重点。耐药结核分枝杆菌潜伏-复发感染动物模型是开展耐药结核病防控相关机制研究、抗耐药结核分枝杆菌药物和疫苗研究的基础。目前耐药结核分枝杆菌感染动物模型缺乏,而已有的结核分枝杆菌标准株H37Rv潜伏-复发感染模型存在缺陷,如小鼠模型的潜伏期荷菌量偏高、复发期变异大,而猴模型的潜伏期和复发期不可预测。模型的可控性差使其应用困难,且缺乏可用的免疫学评价指标,导致远期复发无法预测。因此,基于现有H37Rv潜伏-复发感染动物模型的制备方法,展望耐药结核分枝杆菌潜伏-复发感染动物模型可能存在的缺陷,通过选用新的抑菌剂和诱导剂,制备有稳定潜伏期、潜伏时长适中、复发起点和复发水平变异小的动物模型,是未来耐药结核分枝杆菌潜伏-复发感染动物模型研究的方向。     

结核分枝杆菌耐药性的分子生物学研究进展

结核病一直是世界性问题,我国其发病情况尤为严重,是亚洲的第二大结核病发病国家。结核病治疗方面常使用抗生素作为首选药物,随着抗菌药的滥用,结核杆菌对多种抗菌药产生耐药性,结核病耐药患者增多,治疗难度增加。因此,结核杆菌耐药分子机制的研究更加重要,新型抗结核药物研制更加迫切。结核分枝杆菌的基因突变是引起耐药的主要分子学依据,因此基于结核分枝杆菌耐药性相关基因的深入探索,对于预防结核病的传播及治疗皆具有深远影响。本文从分子生物学角度分析了近年来结核分枝杆菌耐药性产生的原因及相关研究进展。     

生长环境对结核分枝杆菌胁迫作用的研究进展

高传染性结核病是由结核分枝杆菌引起的慢性消耗性疾病,病死率较高,备受全球关注。结核分枝杆菌是一种胞内寄生菌,通过呼吸道感染宿主,感染期间寄居肺部形成肉芽肿。肉芽肿或者免疫系统施加的环境压力,比如低pH、缺乏营养(缺铁)、缺氧等使结核分枝杆菌进入休眠状态,从而影响结核分枝杆菌的正常生长和抗生素的疗效。结核病治疗周期长,易产生耐药性,因此迫切需要研发新的药物以提升治疗效果。本文通过3个主要具有胁迫作用的生长环境因素综述了近年来发现的结核分枝杆菌相关调控因子和药物新靶点,为疫苗研究及新药物设计提供理论基础和研究依据。     

结核分枝杆菌耐药性的分子机理研究进展

结核分枝杆菌内,抗结核药物的作用靶编码基因已在细菌染色体上定位,使人们能在分子水平上研究耐药结核分枝杆菌,并对其耐药机理有了深刻了解,本文就结核分枝杆菌对几种主要抗结核药物耐药性的分子机理相关的基因等方面的研究作一综述。     

结核分枝杆菌持续感染相关基因及其调控网络分析

结核分枝杆菌是结核病的致病菌, 也是迄今最成功的人类致病菌之一. 结核分枝杆菌能逃避宿主免疫攻击, 在人体内持续感染或呈休眠状态. 当人体免疫功能低下时, 持续感染或休眠的致病菌可能被重新激活. 结核分枝杆菌的持续感染是制约结核病控制计划成功的主要障碍之一. 揭示结核分枝杆菌持续感染的分子机制、寻找其中薄弱环节、发现适当的药物靶标并开发全新药物及免疫干预措施, 被认为是遏制结核病蔓延的关键. 结核分枝杆菌持续感染和再激活是众多基因协同的系统适应过程. 本文在全面分析全球结核分枝杆菌持续感染相关基因研究文献的基础上, 通过文本挖掘, 综合本实验室前期研究结果, 提出了结核分枝杆菌持续感染相关基因的调控网络, 为揭示结核分枝杆菌持续感染的机制, 筛选控制结核病的新靶标和免疫干预节点提供研究基础.     

结核分枝杆菌感染实验模型

结核分枝杆菌是引起人结核病的主要病原,全世界约有1/3人口感染结核分枝杆菌。尽管该病原可感染并引起许多动物疾病,但人类是其中心宿主。为研究结核分枝杆菌的致病机理及宿主对本病原的保护性和免疫病理学反应,选择合适的动物模型非常必要。本文阐述了结核病研究中常用的实验模型及各种模型的优缺点。实验模型的合理应用将促进我们对结核病的认识,从中获取的资料将有助于我们发现更好的预防和治疗方案。     

二代测序技术在结核分枝杆菌研究中的应用进展

结核病是由结核分枝杆菌引起的全球第二大传染病。二代测序技术为从基因组水平研究结核分枝杆菌提供了重要的研究方法。本文从结核病流行病学、结核分枝杆菌耐药和进化及相关生物信息学等方面,介绍二代测序技术在结核分枝杆菌研究中的应用进展。     

结核分枝杆菌耐氟喹诺酮类药物的分子机制研究进展

结核病是由结核分枝杆菌(Mycobacterium tuberculosis)通过空气传播引起人类感染的慢性传染病,耐药结核分枝杆菌的流行是目前结核病防治的世界难题。氟喹诺酮类药物是人工合成药物,应用于耐药结核的临床治疗中,在治疗中起着核心的作用。但近年来,氟喹诺酮类药物的抗性菌株不断出现,愈发增加了结核病治疗的困难与治疗失败风险。在临床中氟喹诺酮药物的靶点比较清楚,是结核分枝杆菌的DNA旋转酶。目前发现结核分枝杆菌耐氟喹诺酮类药物的机制主要包括药物靶点DNA旋转酶的关键氨基酸改变、药物外排泵系统、细菌细胞壁厚度的增加以及喹诺酮抗性蛋白MfpA介导的DNA旋转酶活性调控。其中在氟喹诺酮靶标DNA旋转酶功能活性改变的耐药机制方面,编码DNA旋转酶基因突变一直是研究的热点,但近年来发现DNA旋转酶的调控蛋白MfpA以及DNA旋转酶的修饰在细菌耐药性中起着重要的作用,相关机制还亟待发现。本文综述了当前结核分枝杆菌耐氟喹诺酮类药物的作用机制,旨在为研发精准诊断技术和药物发掘提供科学理论基础和参考。     

蛋白质组学在结核分枝杆菌研究中的应用

蛋白质组学是在基因组学基础上发展起来的新兴学科, 其基本技术包括样品制备、蛋白质分离和蛋白质鉴定分析, 其中的核心技术是双向凝胶电泳技术(2-Dimensional Electrophoresis, 2-DE)和质谱技术(Mass Spectrometry, MS)。近年来, 蛋白质组学技术已应用于结核分枝杆菌的研究领域。应用蛋白质组学技术分离、鉴定、检测结核分枝杆菌致病株的全菌蛋白及分泌蛋白, 分析其蛋白组成, 可深入解析结核分枝杆菌的致病机理和耐药机制。通过对结核分枝杆菌致病株抗原的分析, 为研制预防结核病的新型疫苗拓展了空间。通过对结核分枝杆菌临床分离株的蛋白组成分析还发现了一些有意义的结核病早期诊断标志物。蛋白质组学技术还应用于寻找新的药物靶标, 在研制和筛选新的抗结核药物等方面展示了一些有价值的研究成果, 为更好地开展结核病的预防、早期诊断及治疗打下了基础。     

结核分枝杆菌外排泵研究进展

结核病是由结核分枝杆菌(Mycobacterium tuberculosis,Mtb)引起的一种传染病。随着多药耐药和广泛耐药结核分枝杆菌的出现,结核病的治疗变得更为艰难。近年来研究发现,结核分枝杆菌存在外排泵是其耐药的原因之一,现已发现结核分枝杆菌的主要易化子超家族(major facilitator superfamily,MFS)、三磷酸腺苷(adenosine-triphosphate,ATP)结合盒超家族(ATP-Binding Cassette,ABC)、耐受小节分裂区家族(resistance-nodulation-division,RND)和小耐多药性家族(small multidrug resistance,SMR)外排泵。但是人们对结核分枝杆菌外排泵介导的耐药现象认识不足,仍缺乏从新药发现角度研发外排泵抑制剂的研究。本文拟对结核分枝杆菌的ABC、MFS、RND和SMR外排泵的结构和功能,以及结核分枝杆菌外排泵抑制剂的研究进展进行综述。     

Proteome microarray technology and application: higher,wider, and deeper

ABSTRACT

Introduction: Protein microarray is a powerful tool for both biological study and clinical research. The most useful features of protein microarrays are their miniaturized size (low reagent and sample consumption), high sensitivity and their capability for parallel/high-throughput analysis. The major focus of this review is functional proteome microarray.

Areas covered: For proteome microarray, this review will discuss some recently constructed proteome microarrays and new concepts that have been used for constructing proteome microarrays and data interpretation in past few years, such as PAGES, M-NAPPA strategy, VirD technology, and the first protein microarray database. this review will summarize recent proteomic scale applications and address the limitations and future directions of proteome microarray technology.

Expert opinion: Proteome microarray is a powerful tool for basic biological and clinical research. It is expected to see improvements in the currently used proteome microarrays and the construction of more proteome microarrays for other species by using traditional strategies or novel concepts. It is anticipated that the maximum number of features on a single microarray and the number of possible applications will be increased, and the information that can be obtained from proteome microarray experiments will more in-depth in the future.     

Epitope-driven TB vaccine development: a streamlined approach using immuno-informatics, ELISpot assays, and HLA transgenic mice

New vaccine candidates that might better control the worldwide prevalence of Mycobacterium tuberculosis (Mtb) have yet to be described. Strong CD4+ T cell-mediated immune response (CMI) is correlated with protection from the development of TB disease; however, the selection of suitable vaccine antigens has been thwarted by the size and complexity of the (Mtb) proteome, and by the relative difficulty of delivering these antigens in the right immunological context. One possible solution is to develop immunotherapeutic vaccines for TB that are based on T cell epitopes representing multiple antigens. This text illustrates the stepwise development of epitope-driven vaccines from in silico epitope mapping to testing the vaccine in a live Mtb challenge model. First, we used the whole genome Mtb microarray to identify bacterial proteins expressed under the conditions thought to model Mtb survival and replication in human macrophages. Eighteen of these proteins were also found by Behr et al. to be absent from at least one strain of BCG; the sequences of these eighteen proteins were then screened for T-cell epitopes using the immuno-informatics algorithm, EpiMatrix. Of the seventeen representative epitopes evaluated in ELISpot assays, all seventeen were confirmed to elicit interferon (IFN)-gamma secretion by PBMC from Mtb-exposed subjects. A parallel live Mtb challenge study in mice showed prototype epitope-based TB vaccines to be robustly immunogenic but not as effective as BCG. These experiments illustrate the use of immuno-informatics tools for vaccine development and describe a pathway for the development of a more effective, epitope-driven, immunotherapeutic vaccine for TB.     

Functional protein microarray: an ideal platform for investigating protein binding property

Functional protein microarray is an important tool for high-throughput and large-scale systems biology studies.Besides the progresses that have been made for protein microarray fabrication,significant ...     

High-throughput proteomics using antibody microarrays

Antibody-based microarrays are a novel technology that hold great promise in proteomics. Microarrays can be printed with thousands of recombinant antibodies carrying the desired specificities, the biologic sample (e.g., an entire proteome) and any specifically bound analytes detected. The microarray patterns that are generated can then be converted into proteomic maps, or molecular fingerprints, revealing the composition of the proteome. Using this tool, global proteome analysis and protein expression profiling will thus provide new opportunities for biomarker discovery, drug target identification and disease diagnostics, as well as providing insights into disease biology. Intense work is currently underway to develop this novel technology platform into the high-throughput proteomic tool required by the research community.     

High-throughput proteomics using antibody microarrays

Antibody-based microarrays are a novel technology that hold great promise in proteomics. Microarrays can be printed with thousands of recombinant antibodies carrying the desired specificities, the biologic sample (e.g., an entire proteome) and any specifically bound analytes detected. The microarray patterns that are generated can then be converted into proteomic maps, or molecular fingerprints, revealing the composition of the proteome. Using this tool, global proteome analysis and protein expression profiling will thus provide new opportunities for biomarker discovery, drug target identification and disease diagnostics, as well as providing insights into disease biology. Intense work is currently underway to develop this novel technology platform into the high-throughput proteomic tool required by the research community.     

Genetics-directed drug discovery for combating Mycobacterium tuberculosis infection

Mycobacterium tuberculosis (Mtb), the pathogen of tuberculosis (TB), is one of the most infectious bacteria in the world. The traditional strategy to combat TB involves targeting the pathogen directly; however, the rapid evolution of drug resistance lessens the efficiency of this anti-TB method. Therefore, in recent years, some researchers have turned to an alternative anti-TB strategy, which hinders Mtb infection through targeting host genes. In this work, using a theoretical genetic analysis, we identified 170 Mtb infection-associated genes from human genetic variations related to Mtb infection. Then, the agents targeting these genes were identified to have high potential as anti-TB drugs. In particular, the agents that can target multiple Mtb infection-associated genes are more druggable than the single-target counterparts. These potential anti-TB agents were further screened by gene expression data derived from connectivity map. As a result, some agents were revealed to have high interest for experimental evaluation. This study not only has important implications for anti-TB drug discovery, but also provides inspirations for streamlining the pipeline of modern drug discovery.     

Uncovering potential Drug Targets for Tuberculosis using Protein Networks

The emergence of HIV-TB co-infection and multi-drug resistant strains of Mycobacterium tuberculosis (Mtb) drive the need for new therapeutics against the infectious disease tuberculosis. Among the reported putative TB targets in the literature, the identification and characterization of the most probable therapeutic targets that influence the complex infectious disease, primarily through interactions with other influenced proteins, remains a statistical and computational challenge in proteomic epidemiology. Protein interaction network analysis provides an effective way to understand the relationships between protein products of genes by interconnecting networks of essential genes and its protein-protein interactions for 5 broad functional categories in Mtb. We also investigated the substructure of the protein interaction network and focused on highly connected nodes known as cliques by giving weight to the edges using data mining algorithms. Cliques containing Sulphate assimilation and Shikimate pathway enzymes appeared continuously inspite of increasing constraints applied by the K-Core algorithm during Network Decomposition. The potential target narrowed down through Systems approaches was Prephanate Dehydratase present in the Shikimate pathway this gives an insight to develop novel potential inhibitors through Structure Based Drug Design with natural compounds.     

Bedaquiline: Fallible Hope Against Drug Resistant Tuberculosis

Tuberculosis (TB) is a deadly bacterial infectious disease caused by intra-cellular pathogen Mycobacterium tuberculosis (Mtb). There were an estimated 1.4 million TB deaths in 2015 and an additional 0.4 million deaths resulting from TB among individuals with HIV. Drug-discovery for its cure is very slow in comparison with the causative organism’s fast pace of mutations conferring drug resistance. Moreover, the field of drug-discovery of anti-TB drugs is constantly being challenged by the drug resistant strains of Mtb. Several molecules/inhibitors are being tested across the pharmaceutical industry and research centres for their suitability as drug candidate. It takes immense effort, high costs and a whole lot of screening to bring a single molecule to the clinics for patient cure. In last 60 years, hundreds of molecules have been patented for their probable use to develop drug for treatment of TB. However, only one drug has been successfully approved that is bedaquiline (1-(6-bromo-2 -methoxy-quinolin-3-yl)-4-dimethylamino-2-naphtalen-1-yl-1-phenyl-butan-2-ol). This is a brief review about bedaquiline (BDQ), the only drug in last 45 years approved for curing drug-resistant pulmonary TB, its development, action mechanism and development of resistance against it.     

Current perspectives in cancer proteomics

Proteome technology has been used widely in cancer research and is a useful tool for the identification of new cancer markers and treatment-related changes in cancer. This article details the use of proteome technology in cancer research, and laboratory-based and clinical cancer research studies are described. New developments in proteome technology that enable higher sample-throughput are evaluated and methods for enhancing conventional proteome analysis (based on two-dimensional electrophoresis) discussed. The need to couple laboratory-based proteomics research with clinically relevant models of the disease is also considered, as this remains the next main challenge of cancer-related proteome research.