Engineering Papers⌕ Search

DOE OSTI · 2434264

How Does Escherichia coli Allocate Proteome?

Abstract

Microorganisms are shown to actively partition their intracellular resources, such as pro- teins, for growth optimization. Recent experiments have begun to reveal molecular com- ponents unpinning the partition; however, it remains unclear quantitatively how individual parts orchestrate to yield precise resource allocation that is both robust and dynamic. Here we developed a coarse-grained mathematical framework that centers on guanosine pentaphosphate (ppGpp)-mediated regulation, and used it to systematically uncover the design principles of proteome allocation in Escherichia coli. Our results showed that cellular ability of resource partition lies in an ultrasensitive, negative feedback control- ling topology with the ultrasensitivity arising from zero-order amino acid kinetics and the negative feedback from ppGpp-controlled ribosome synthesis. In addition, together with the time-scale separation between slow ribosome kinetics and fast turnovers of ppGpp and amino acids, the network topology confers the organism an optimization mechanism which mimics sliding mode control, a nonlinear optimization strategy that is widely used in man-made systems. We further showed that such a controlling mechanism is robust against parameter variations and molecular fluctuations, and is also efficient for biomass production over time. Furthermore, this work elucidates the fundamental controlling mechanism of E. coli proteome allocation, thereby providing insights into quantitative microbial physiology as well as the design of synthetic gene networks.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Liao, Chen, Priyanka, Priyanka, Lai, Yi-Hui, Rao, Christopher V., Lu, Ting. 2024-08-09. How Does Escherichia coli Allocate Proteome?. https://doi.org/10.1021/acssynbio.3c00537

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

Soil metagenomics umbrella narrative

Implementing accessible, authentic research experiences in introductory courses is challenging, particularly at institutions serving diverse student populations. To address this gap, we developed and deployed a Course-based Undergraduate Research Experience (CURE) focused on plant-microbe interactions in General Biology II at Northeastern Illinois University (NEIU), a minority-serving institution with a diverse student body. Students grew sugar beets (Beta vulgaris), extracted DNA from the rhizoplane, and used the Department of Energy Systems Biology Knowledgebase (KBase) for bioinformatic analysis to compare microbial relative abundance in fertilized versus unfertilized soil. Over five semesters, the CURE engaged 103 students and leveraged the intuitive KBase platform to make complex sequencing data accessible. Pre/post-course survey data revealed significant increases in student self-assessed research skills, including the ability to explain results and determine the types of data to collect. Furthermore, students reported significant gains in confidence related to experimental design and hypothesis development, alongside a strong increase in familiarity with KBase. Informal faculty feedback indicated high student engagement and appreciation for the real-world connections (e.g. food systems, agriculture, and health). This scalable, low-cost model effectively integrates data science tools into the foundational curriculum, demonstrating a potent strategy for boosting research skills and broadening participation in authentic scientific inquiry among diverse undergraduate students.

59 BASIC BIOLOGICAL SCIENCES↗

Genome-resolved insights into microbial diversity and elemental cycling in Winogradsky columns

We retained 18 MAGs with ≥50% completion and <10% contamination (i.e., at least medium quality). Of these, 10 had >90% completion and <5% contamination; however, only one (Paceibacteria Bin.003_MG) can be described as high-quality, as the others lacked a full suite of 5S, 16S, and 23S rRNA genes. To maximize the diversity of our recovered MAGs, we also retained one MAG (Chromatiaceae Bin.008_AM) with >40% (but less than 50%) completion and <5% contamination, as well as one (Rhodopseudomonas Bin.015_MK) with >90% completion and <20% (but>10%) contamination. Interestingly, significant chimerism was not detected in this MAG (40) , suggesting that the elevated contamination (20%) may instead reflect two closely related strains collapsing into a single bin. Consistent with this, contig coverage was bimodal, with roughly 17% of the assembly at ~115x and the remaining 83% at ~282x, while GC content remained uniform across both groups (~64%), arguing against contamination from a taxonomically distinct source.

59 BASIC BIOLOGICAL SCIENCES↗