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.

SUMMARY As nascent polypeptides exit ribosomes, they are engaged by a series of processing, targeting and folding factors. Here we present a selective ribosome profiling strategy that enables global monitoring of when these factors engage polypeptides in the complex cellular environment. Studies of the Escherichia coli chaperone Trigger Factor (TF) reveal that, while TF can interact with many polypeptides, β-barrel outer membrane proteins are the most prominent substrates. Loss of TF leads to broad outer membrane defects and premature, cotranslational protein translocation. While in vitro studies suggested that TF is prebound to ribosomes waiting for polypeptides to emerge from the exit channel, we find that in vivo TF engages ribosomes only after ~100 amino acids are translated. Moreover, excess TF interferes with cotrantslational removal of the N-terminal formyl methionine. Our studies support a triaging model in which proper protein biogenesis relies on the fine-tuned, sequential engagement of processing, targeting ad folding factors.

SummaryGrowth of the meshlike peptidoglycan (PG) sacculus located between the bacterial inner and outer membranes (OM) is tightly regulated to ensure cellular integrity, maintain cell shape and orchestrate division. Cytoskeletal elements direct placement and activity of PG synthases from inside the cell but precise spatiotemporal control over this process is poorly understood. We demonstrate that PG synthases are also controlled from outside the sacculus. Two OM lipoproteins, LpoA and LpoB, are essential for the function respectively of PBP1A and PBP1B, the major E. coli bifunctional PG synthases. Each Lpo protein binds specifically to its cognate PBP and stimulates its transpeptidase activity, thereby facilitating attachment of new PG to the sacculus. LpoB shows partial septal localization and our data suggest that the LpoB-PBP1B complex contributes to OM constriction during cell division. LpoA/ LpoB and their PBP docking regions are restricted to γ-proteobacteria, providing models for niche-specific regulation of sacculus growth.

Large-scale genetic interaction studies provide the basis for defining gene function and pathway architecture. Recent advances in the ability to generate double mutants en masse in S. cerevisiae have dramatically accelerated the acquisition of genetic interaction information and the biological inferences that follow. Here, we describe a method based on F-driven conjugation, which allows for high-throughput generation of double mutants in E. coli. This method, termed Genetic Interaction ANalysis Technology for E. coli (GIANT-coli), permits us to systematically generate and array double mutant cells on solid media, in high-density arrays. We show that colony size provides a robust and quantitative output of cellular fitness and that GIANT-coli can recapitulate known synthetic interactions and identify new negative (synthetic sickness/lethality) and positive (suppressive/epistatic) relationships. Finally, we describe a complementary strategy for suppressor mutant identification on a genome-wide level. Together, these methods permit rapid, large-scale genetic interaction studies in E. coli.

Identifying all essential genomic components is critical for the assembly of minimal artificial life. In the genome-reduced bacterium Mycoplasma pneumoniae, we found that small ORFs (smORFs; < 100 residues), accounting for 10% of all ORFs, are the most frequently essential genomic components (53%), followed by conventional ORFs (49%). Essentiality of smORFs may be explained by their function as members of protein and/or DNA/RNA complexes. In larger proteins, essentiality applied to individual domains and not entire proteins, a notion we could confirm by expression of truncated domains. The fraction of essential non-coding RNAs (ncRNAs) non-overlapping with essential genes is 5% higher than of non-transcribed regions (0.9%), pointing to the important functions of the former. We found that the minimal essential genome is comprised of 33% (269,410 bp) of the M. pneumoniae genome. Our data highlight an unexpected hidden layer of smORFs with essential functions, as well as non-coding regions, thus changing the focus when aiming to define the minimal essential genome.