Systematic Discovery and Analysis of Small Proteins and Small ORFs in Mycobacteria

分枝杆菌中小蛋白和小 ORF 的系统发现和分析

• 批准号: 10452528
• 负责人: KEITH M DERBYSHIRE
• 金额: $ 54.7万
• 依托单位: WADSWORTH CENTER
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10452528
• 关键词: 5' Untranslated Regions; Algorithms; Amino Acids; Archaea; Architecture; Bacteria; Biochemical; Bioinformatics; Biology; Birth; Cell Extracts; Codon Nucleotides; Collaborations; Coupling; Cryoelectron Microscopy; Cysteine; Data; Data Set; Detection; Eukaryota; Fruit; Gene Proteins; Genes; Genome; Genomics; Genus Mycobacterium; Goals; Infection; Instruction; Knowledge; Laboratories; Life; Mass Spectrum Analysis; Medical; Messenger RNA; Methods; Molecular Biology; Molecular Genetics; Mutation; Open Reading Frames; Operon; Organism; Pathogenesis; Pathogenicity; Peptides; Preparation; Prevalence; Prokaryotic Cells; Property; Proteins; Proteomics; Regulation; Research Personnel; Ribosomal Proteins; Ribosomes; Role; Selection Bias; Signal Transduction; Structure; Testing; Training; Translating; Translations; Work; attenuation; comparative; experimental study; genetic approach; genome annotation; genome-wide; improved; insight; member; mutant; mycobacterial; novel; protein function; response; ribosome profiling; whole genome

The last few decades have seen the birth and maturation of the field of Molecular Biology. Initially, mutant genes were focal points of genome exploration. Now, entire genomes are routinely sequenced, and the resident genes are automatically identified by annotation algorithms. Alternatively, proteomic approaches prepare proteolytic peptides of whole-cell extracts for analysis by mass spectrometry. Each of these approaches are strongly biased for large genes: large genes are frequent targets for mutation, long-open- reading frames are easily discerned in genomic sequence, and large proteins generate many peptides for mass spectrometry identification. This unintended bias has also created a large gap in our understanding of molecular biology. Recent work in eukaryotes and prokaryotes alike have uncovered multitudes of small genes or their encoded proteins. The numbers of small proteins (considered as 50 aa or less) rival that of traditionally large proteins, yet only a handful have been ascribed a function. The goal of this proposal is to propel this nascent field forward by facilitating both small protein discovery and functional characterization. Our preliminary data identify specific examples that clearly define cis- and trans-classes of function for short- open-reading frames and small proteins. These early leads will be pursued to fruition, providing the framework for the expanded rigorous study needed in any new field. We will test an additional subset of small proteins for function, which we anticipate will reveal functions for each member of this training set, while also establishing general principles for short-open-reading frames and small proteins. We will develop and apply our small protein approaches in mycobacteria. Mycobacteria offer many advantages for small protein study. Foremost is that they express >1000 small proteins in standard conditions. An extensive toolkit for modifying, culturing, and analyzing mycobacteria makes them very tractable. A GC-rich genome provides codon bias selection as one criterion to identify functional small proteins. Moreover, our findings of small gene/protein function in standard laboratory conditions may directly provide insights into the biology and pathogenesis of infection. This proposal integrates the complementary expertise of investigators whose ongoing collaboration has already provided the requisite groundwork leading to this proposal. Through the proposed Aims, we will identify new functional roles of encoded mycobacterial small proteins and develop an optimized, small-proteomics pipeline for efficient application to other bacteria, archaea, and eukaryotes.

过去几十年见证了分子生物学领域的诞生和成熟。最初，突变体 基因是基因组探索的焦点。现在，整个基因组都被常规测序，并且 常驻基因由注释算法自动识别。或者，蛋白质组学方法 制备全细胞提取物的蛋白水解肽，用于质谱分析。这些中的每一个 方法对大基因有很大的偏见：大基因是突变的常见目标，长期开放- 基因组序列中的阅读框很容易辨别，大蛋白质会产生许多肽 用于质谱鉴定。这种无意识的偏见也造成了我们之间的巨大差距。 了解分子生物学。 最近对真核生物和原核生物的研究发现了许多小基因或其 编码的蛋白质。小蛋白质（被认为是 50 个氨基酸或更少）的数量可与传统蛋白质的数量相媲美 大蛋白质，但只有少数被赋予了功能。该提案的目标是推动 通过促进小蛋白质的发现和功能表征，这一新兴领域向前发展。我们的 初步数据确定了明确定义顺式和反式功能的具体例子 开放阅读框和小蛋白质。这些早期的线索将得到实现，提供 任何新领域所需的扩展严格研究的框架。我们将测试一个额外的子集 用于功能的小蛋白质，我们预计它将揭示该训练集中每个成员的功能， 同时还建立了短开放阅读框和小蛋白质的一般原则。 我们将在分枝杆菌中开发和应用我们的小蛋白质方法。分枝杆菌提供许多 小蛋白质研究的优势。最重要的是它们在标准中表达 >1000 个小蛋白 状况。用于修改、培养和分析分枝杆菌的广泛工具包使它们非常有用 易于处理。富含 GC 的基因组提供密码子偏倚选择作为识别功能性小分子的标准之一 蛋白质。此外，我们在标准实验室条件下对小基因/蛋白质功能的发现可能 直接提供对感染的生物学和发病机制的见解。该提案整合了 调查人员的互补专业知识，他们的持续合作已经提供了必要的 导致该提案的基础工作。通过拟议的目标，我们将确定新的职能角色 编码分枝杆菌小蛋白质并开发优化的小蛋白质组学管道，以实现高效 适用于其他细菌、古细菌和真核生物。