Department of Physics, U.C. San Diego, La Jolla, CA, USA.
Bavarian Center for Biomolecular Mass Spectrometry, Technical University of Munich, Freising, Germany.
Nat Microbiol. 2023 Feb;8(2):347-359. doi: 10.1038/s41564-022-01310-w. Epub 2023 Feb 3.
Bacterial fitness depends on adaptability to changing environments. In rich growth medium, which is replete with amino acids, Escherichia coli primarily expresses protein synthesis machineries, which comprise ~40% of cellular proteins and are required for rapid growth. Upon transition to minimal medium, which lacks amino acids, biosynthetic enzymes are synthesized, eventually reaching ~15% of cellular proteins when growth fully resumes. We applied quantitative proteomics to analyse the timing of enzyme expression during such transitions, and established a simple positive relation between the onset time of enzyme synthesis and the fractional enzyme 'reserve' maintained by E. coli while growing in rich media. We devised and validated a coarse-grained kinetic model that quantitatively captures the enzyme recovery kinetics in different pathways, solely on the basis of proteomes immediately preceding the transition and well after its completion. Our model enables us to infer regulatory strategies underlying the 'as-needed' gene expression programme adopted by E. coli.
细菌的适应性取决于其对环境变化的适应能力。在富含氨基酸的丰富生长培养基中,大肠杆菌主要表达蛋白质合成机器,这些机器约占细胞蛋白质的 40%,是快速生长所必需的。当过渡到缺乏氨基酸的基本培养基时,合成生物合成酶,当生长完全恢复时,最终达到细胞蛋白质的约 15%。我们应用定量蛋白质组学来分析这种转变过程中酶表达的时间,并且在大肠杆菌在丰富的培养基中生长时,建立了一个简单的正相关关系,即酶合成的起始时间与大肠杆菌维持的酶“储备”分数之间的关系。我们设计并验证了一个粗粒度的动力学模型,该模型仅基于转变之前和完成之后的蛋白质组,就可以定量捕获不同途径中的酶恢复动力学。我们的模型使我们能够推断出大肠杆菌采用的“按需”基因表达程序背后的调控策略。