Biology subjects

Li, S. H.-J.

Publications and source records attributed to Li, S. H.-J..

6 recordsLinked to original sources

bioRxiv2022

Global Protein-Turnover Quantification in Escherichia coli Reveals Cytoplasmic Recycling under Nitrogen-Limitation

Protein turnover is critical for proteostasis, but turnover quantification is challenging, and even in well-studied E. coli, proteome-wide measurements remain scarce. Here, we quantify the degradation rates of [~]3.2k E. coli proteins under 12 conditions by combining heavy isotope labeling with complement reporter ion quantification and find that cytoplasmic proteins are recycled when nitrogen is limited. We use knockout experiments to assign substrates to the known cytoplasmic ATP-dependent proteases. Surprisingly, none of these proteases are responsible for the observed cytoplasmic protein degradation in nitrogen limitation, suggesting that a major proteolysis pathway in E. coli remains to be discovered. Lastly, we show that protein degradation rates are generally independent of cell division rates. Thus, we introduce broadly applicable technology for protein turnover measurements and provide a rich resource for protein half-lives and protease substrates in E. coli, complementary to genomics data, that will allow researchers to decipher the control of proteostasis.

systems biology↗

bioRxiv2022

Global and gene-specific translational regulation in Escherichia coli across different conditions

How well mRNA transcript levels represent protein abundances has been a controversial issue. Particularly across different environments, correlations between mRNA and protein exhibit remarkable variability from gene to gene. Translational regulation is likely to be one of the key factors contributing to mismatches between mRNA level and protein abundance in bacteria. Here, we quantified genome-wide transcriptome and relative translation efficiency (RTE) under 12 different conditions in Escherichia coli. By quantifying the mRNA-RTE correlation both across genes and across conditions, we uncovered a diversity of gene-specific translational regulations, cooperating with transcriptional regulations, in response to carbon (C), nitrogen (N), and phosphate (P) limitations. Intriguingly, we found that many genes regulating translation are themselves subject to translational regulation, suggesting possible feedbacks. Furthermore, a random forest model suggests that codon usage partially predicts a genes cross-condition variability in translation efficiency; such cross-condition variability tends to be an inherent quality of a gene, independent of the specific nutrient limitations. These findings broaden the understanding of translational regulation under different environments, and provide novel strategies for the control of translation in synthetic biology.

genomics↗

bioRxiv2020

A dual-mechanism antibiotic targets Gram-negative bacteria and avoids drug resistance

The rise of antibiotic resistance and declining discovery of new antibiotics have created a global health crisis. Of particular concern, no new antibiotic classes have been approved for treating Gram-negative pathogens in decades. Here, we characterize a compound, SCH-79797, that kills both Gram-negative and Gram-positive bacteria through a unique dual-targeting mechanism of action (MoA) with undetectably low resistance frequencies. In an animal host model, SCH-79797 reduces pathogenesis of Acinetobacter baumannii, a drug-resistant Gram-negative pathogen. To characterize the MoA of SCH-79797 we combined quantitative imaging, proteomic, genetic, metabolomic, and cell-based assays. This pipeline shows that SCH-79797 has two independent cellular targets, folate metabolism and bacterial membrane integrity, and outperforms combination treatments with other antifolates and membrane disruptors in killing MRSA persisters. Thus, SCH-79797 represents a promising lead antibiotic and suggests that combining multiple MoAs onto a single chemical scaffold may be an underappreciated approach to target challenging bacterial pathogens.

microbiology↗

bioRxiv2019

Modeling microbial diversity with metabolic trade-offs

Microbes face intense competition in the natural world, and so need to wisely allocate their resources to multiple functions, in particular to metabolism. Understanding competition among metabolic strategies that are subject to trade-offs is therefore crucial for deeper insight into the competition, cooperation, and community assembly of microorganisms. In this work, we evaluate competing metabolic strategies within an ecological context by considering not only how the environment influences cell growth, but also how microbes shape their chemical environment. Utilizing chemostat-based resource-competition models, we exhibit a set of intuitive and general procedures for assessing metabolic strategies. Using this framework, we are able to relate and unify multiple metabolic models, and to demonstrate how the fitness landscape of strategies becomes intrinsically dynamic due to species-environment feedback. Such dynamic fitness landscapes produce rich behaviors, and prove to be crucial for ecological and evolutionary stable coexistence in all the models we examined.

systems biology↗

bioRxiv2018

E. coli translation strategies differ across nutrient conditions

For cells to grow faster they must increase their protein production rate. Microorganisms have traditionally been thought to accomplish this increase by producing more ribosomes to enhance protein synthesis capacity, leading to the linear relationship between ribosome level and growth rate observed under most growth conditions previously examined. Past studies have suggested that this linear relationship represents an optimal resource allocation strategy for each growth rate, independent of any specific nutrient state. Here we investigate protein production strategies in continuous cultures limited for carbon, nitrogen, and phosphate, which differentially impact substrate supply for protein versus nucleic acid metabolism. Unexpectedly, we find that at slow growth rates, E. coli achieves the same protein production rate using three different strategies under the three different nutrient limitations. Upon phosphate (P) limitation, translation is slow due to a particularly low abundance of ribosomes, which are RNA-rich and thus particularly costly for phosphorous-limited cells. In nitrogen (N) limitation, translation is slowed by limited glutamine and stalling at glutamine codons, resulting is slow elongation. In carbon (C) limitation, translation is slowed by accumulation of inactive ribosomes not bound to mRNA. These extra ribosomes enable rapid growth acceleration upon nutrient upshift. Thus, bacteria tune ribosome usage across different limiting nutrients to enable balanced nutrient-limited growth while also preparing for future nutrient upshifts.

microbiology↗

bioRxiv2017

Metabolic Interactions Between Dynamic Bacterial Subpopulations

Within multi-species microbial communities, individual species are known to occupy distinct metabolic niches. By contrast, it has remained largely unclear whether and how metabolic specialization occurs within clonal bacterial populations. The possibility of such metabolic specialization in clonal populations raises several questions: Does specialization occur, and if it does, which metabolic processes are involved? How is specialization coordinated? How rapidly do cells switch between states? And finally, what functions might metabolic specialization provide? One potential function of metabolic specialization could be to manage overflow metabolites such as acetate, which presents a toxic challenge due to low pH, and protective pH-neutral overflow metabolites. Here we show that exponentially dividing Bacillus subtilis cultures divide into distinct interacting metabolic subpopulations including one population that produces acetate, and another population that differentially expresses metabolic genes for the production of acetoin, a pH-neutral storage molecule. These subpopulations grew at distinct rates, and cells switched dynamically between states, with acetate influencing the relative sizes of the different subpopulations. These results show that clonal populations can use metabolic specialization to control the environment through a process of dynamic, environmentally-sensitive state-switching.

microbiology↗