Testing Fundamental Tradeoffs between Power and Efficiency in the Translational Machinery of Bacteria

蛋白质合成的机制在所有形式的生命中都是相似的，然而，尽管最近在了解核糖体的结构和翻译所涉及的事件序列方面取得了进展，但人们对生物体之间翻译机制的产生或性能的差异知之甚少。在NSF的支持下，启动了一个研究项目，以记录和解释不同数量的核糖体RNA编码基因在进化上不同的细菌中令人费解的出现。这项研究的结果表明，拥有多个rRNA基因拷贝的细菌在资源可获得性波动时更具竞争力，因为它们能够快速合成核糖体，而那些拥有较少rRNA基因的细菌可能在持续的低营养条件下更有效地生长。研究还表明，每个核糖体的平均蛋白质合成速率与菌株在适应间歇性快速生长和适应缓慢资源有限生长之间的位置有关。这些结果构成了将细菌生理学与生物生态学和进化联系起来的概念模型的基础。该模型的重点是蛋白质合成，这是细菌中最大的代谢费用，并包括翻译速度和资源利用效率之间的拟议折衷。该模型挑战了广泛持有的观点，即细菌中的蛋白质合成机制在性能上几乎没有变化，并为我们理解核糖体的结构和功能带来了生态学的最新进展。拟议的研究的总体目标是测试这一概念模型的各个方面，从而促进我们对细菌生理学、生态学和进化的基本特性之间的相互作用的理解，并帮助研究生发展在微生物生理学和生态学中发现所需的实践和概念技能。这些目标将通过解决以下具体目标来实现：1)确定细菌翻译机制是否在功率和效率之间存在权衡，以及这种权衡对种群增长率和产量的潜在影响；2)增加我们对维持不同数量rRNA操纵子的细菌的生理和生态后果的理解；3)增加我们对翻译机制和密码子偏向之间相互作用的理解，并探索利用这些信息推进未培养细菌基因组分析的可能性；4)培养研究生和本科生在设计实验和解释结果时的创造性和批判性思维的能力，特别是当他们应用于开发对细菌纯培养研究产生的想法的现场测试时。PI将通过组合方法来解决前三个具体目标，包括：已被选为代表定位为快速或有效生长的微生物的细菌的生长研究；对翻译机器的速度和处理能力的直接测量；确定一个基因组标记(rRNA操纵子拷贝数)和不同细菌生活史背后的生理机制将把细菌能量学和生态学联系起来，并为细菌在特定环境中如何反应的预测和可测试模型提供基础。这些信息将提供对自然和管理微生物系统中存在的微生物的竞争成功的洞察，包括生物反应器、废水处理厂和农业土壤。

The machinery of protein synthesis is similar in all forms of life, and yet despite recent progress in understanding the structure of ribosomes and the sequence of events involved in translation, little is known about differences in the production or performance of the translational machinery between organisms. With support from the NSF, a research project was initiated to document and explain the puzzling occurrence of different numbers of ribosomal RNA-encoding genes in evolutionarily diverse bacteria. Results from this research suggest that bacteria possessing multiple copies of the rRNA genes are more competitive when resource availability fluctuates, due to their ability to synthesize ribosomes rapidly, while those possessing few rRNA genes may be more efficient at growth under constant, low-nutrient conditions. It was also revealed that the average rate of protein synthesis per ribosome correlated with the position of a strain along a spectrum between adaptation for episodic, fast growth and adaptation for slow, resource-limited growth. These results form the basis for a conceptual model that links bacterial physiology with organismal ecology and evolution. The model focuses on protein synthesis, the single largest metabolic expense in bacteria, and includes a proposed tradeoff between translational speed and resource utilization efficiency. The model challenges the widely held notion that the protein synthesis machinery in bacteria operates with little variation in performance, and brings an ecological perspective to the recent and spectacular advances in our understanding of the structure and function of ribosomes.The overall goals of the proposed research are to test aspects of this conceptual model and thereby advance our understanding of the interplay between fundamental properties of bacterial physiology, ecology and evolution, and to help graduate students develop the practical and conceptual skills necessary to make discoveries in microbial physiology and ecology. These goals will be met by addressing the following specific aims:1) Determine if there is a tradeoff between power and efficiency in the translational machinery of bacteria, and the potential impact of such a tradeoff on population growth rate and yield;2) Increase our understanding of the physiological and ecological consequences to bacteria maintaining different numbers of rRNA operons;3) Increase our understanding of the interplay between the translation machinery and codon bias, and explore the possibility of using this information to advance the analysis of genomes from uncultivated bacteria; and4) Develop the capacity for graduate and undergraduate students to think creatively and critically in the design of experiments and interpretation of results, especially as they apply to developing field tests of ideas resulting from research on pure cultures of bacteria.The PI will address the first three specific aims by a combination of approaches, including: growth studies of bacteria that have been selected to represent microbes positioned for rapid or efficient growth; direct measurements of the rate and processivity of the translational machinery; and examination of the structure of microbial communities in nature.Identifying a genomic marker (rRNA operon copy number) and the physiological mechanisms that underlie different bacterial life histories would link bacterial energetics and ecology, and provide the basis for predictive and testable models of how bacteria respond in specific environments. This information would provide insight into the competitive success of microbes present in natural and managed microbial systems, including bioreactors, waste water treatment plants, and agricultural soils.