Quantitative views of cellular functions requires precise measures of rates of biomolecule production, especially proteins—the direct effectors of biological processes. Here we present a genome-wide approach, based on ribosome profiling, for measuring absolute protein synthesis rates. The resultant E. coli dataset transforms our understanding of the extent to which protein synthesis is precisely controlled to optimize function and efficiency. Members of multi-protein complexes are made in precise proportion to their stoichiometry, whereas components of functional modules are produced differentially according to their hierarchical role. Estimates of absolute protein abundance also reveal principles used to optimize design. These include how the level of different types of transcription factors is optimized for rapid response, and how a metabolic pathway (methionine biosynthesis) balances production cost with activity requirements. Our studies reveal how general principles, important both for understanding natural systems and for synthesizing new ones, emerge from quantitative analyses of protein synthesis.

How bacteria grow and divide while retaining a defined shape is a fundamental question in microbiology, but technological advances are now driving a new understanding of how the shape-maintaining bacterial peptidoglycan sacculus grows. In this Review, we highlight the relationship between peptidoglycan synthesis complexes and cytoskeletal elements, as well as recent evidence that peptidoglycan growth is regulated from outside the sacculus in Gram-negative bacteria. We also discuss how growth of the sacculus is sensitive to mechanical force and nutritional status, and describe the roles of peptidoglycan hydrolases in generating cell shape and of D-amino acids in sacculus remodelling.

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Summary The explosion of sequence information in bacteria makes developing high-throughput, cost-effective approaches to matching genes with phenotypes imperative. Using E. coli as proof of principle, we show that combining large-scale chemical genomics with quantitative fitness measurements provides a high-quality data set rich in discovery. Probing growth profiles of a mutant library in hundreds of conditions in parallel yielded > 10,000 phenotypes that allowed us to study gene essentiality, discover leads for gene function and drug action, and understand higher-order organization of the bacterial chromosome. We highlight new information derived from the study, including insights into a gene involved in multiple antibiotic resistance and the synergy between a broadly used combinatory antibiotic therapy, trimethoprim and sulfonamides. This data set, publicly available at http://ecoliwiki.net/tools/chemgen/, is a valuable resource for both the microbiological and bioinformatic communities, as it provides high-confidence associations between hundreds of annotated and uncharacterized genes as well as inferences about the mode of action of several poorly understood drugs.

Promoter recognition in eubacteria is carried out by the initiation factor sigma, which binds RNA polymerase and initiates transcription. Cells have one housekeeping factor and a variable number of alternative sigma factors that possess different promoter-recognition properties. The cell can choose from its repertoire of sigmas to alter its transcriptional program in response to stress. Recent structural information illuminates the process of initiation and also shows that the two key sigma domains are structurally conserved, even among diverse family members. We use the sigma repertoire of Escherichia coli, Bacillus subtilis, Streptomyces coelicolor, and cyanobacteria to illustrate the different strategies utilized to organize transcriptional space using multiple sigma factors.

SUMMARY Functional genomics efforts face tradeoffs between number of perturbations examined and complexity of phenotypes measured. We bridge this gap with Perturb-seq, which combines droplet-based single-cell RNA-seq with a strategy for barcoding CRISPR-mediated perturbations, allowing many perturbations to be profiled in pooled format. We applied Perturb-seq to dissect the mammalian unfolded protein response (UPR) using single and combinatorial CRISPR perturbations. Two genome-scale CRISPR interference (CRISPRi) screens identified genes whose repression perturbs ER homeostasis. Subjecting ~100 hits to Perturb-seq enabled high-precision functional clustering of genes. Single-cell analyses decoupled the three UPR branches, revealed bifurcated UPR branch activation among cells subject to the same perturbation, and uncovered differential activation of the branches across hits, including an isolated feedback loop between the translocon and IRE1α. These studies provide insight into how the three sensors of ER homeostasis monitor distinct types of stress and highlight the ability of Perturb-seq to dissect complex cellular responses.

Bacteria often cope with environmental stress by inducing alternative sigma (σ) factors, which direct RNA polymerase to specific promoters, thereby inducing a set of genes called a regulon to combat the stress. To understand the conserved and organism-specific functions of each σ, it is necessary to be able to predict their promoters, so that their regulons can be followed across species. However, the variability of promoter sequences and motif spacing makes their prediction difficult. We developed and validated an accurate promoter prediction model for Escherichia coli σE, which enabled us to predict a total of 89 unique σE-controlled transcription units in E. coli K-12 and eight related genomes. σE controls the envelope stress response in E. coli K-12. The portion of the regulon conserved across genomes is functionally coherent, ensuring the synthesis, assembly, and homeostasis of lipopolysaccharide and outer membrane porins, the key constituents of the outer membrane of Gram-negative bacteria. The larger variable portion is predicted to perform pathogenesis-associated functions, suggesting that σE provides organism-specific functions necessary for optimal host interaction. The success of our promoter prediction model for σE suggests that it will be applicable for the prediction of promoter elements for many alternative σ factors.

Summary Essential gene functions underpin the core reactions required for cell viability, but their contributions and relationships are poorly studied in vivo. Using CRISPR interference, we created knockdowns of every essential gene in Bacillus subtilis and probed their phenotypes. Our high-confidence essential gene network, established using chemical genomics, showed extensive interconnections among distantly related processes and identified modes of action for uncharacterized antibiotics. Importantly, mild knockdown of essential gene functions significantly reduced stationary phase survival without affecting maximal growth rate, suggesting that essential protein levels are set to maximize outgrowth from stationary phase. Finally, high-throughput microscopy indicated that cell morphology is relatively insensitive to mild knockdown but profoundly affected by depletion of gene function, revealing intimate connections between cell growth and shape. Our results provide a framework for systematic investigation of essential gene functions in vivo that is broadly applicable to diverse microorganisms and amenable to comparative analysis.