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Protein–protein interactions play key roles in protein function and the structural organization of a cell. A thorough description of these interactions should facilitate elucidation of cellular activities, targeted-drug design, and whole cell engineering. A large-scale comprehensive pull-down assay was performed using a His-tagged Escherichia coli ORF clone library. Of 4339 bait proteins tested, partners were found for 2667, including 779 of unknown function. Proteins copurifying with hexahistidine-tagged baits on a Ni²⁺-NTA column were identified by MALDI-TOF MS (matrix-assisted laser desorption ionization time of flight mass spectrometry). An extended analysis of these interacting networks by bioinformatics and experimentation should provide new insights and novel strategies for E. coli systems biology.

Persisters represent a small subpopulation of non- or slow-growing bacterial cells that are tolerant to killing by antibiotics. Despite their prominent role in the recalcitrance of chronic infections to antibiotic therapy, the mechanism of their formation has remained elusive. We show that sorted cells of Escherichia coli with low levels of energy-generating enzymes are better able to survive antibiotic killing. Using microfluidics time-lapse microscopy and a fluorescent reporter for in vivo ATP measurements, we find that a subpopulation of cells with a low level of ATP survives killing by ampicillin. We propose that these low ATP cells are formed stochastically as a result of fluctuations in the abundance of energy-generating components. These findings point to a general “low energy” mechanism of persister formation.

Tetracycline-inhibited ribosome profiling (TetRP) provides a powerful new experimental tool for comprehensive genome-wide identification of translation initiation sites in bacteria. We validated TetRP by confirming the translation start sites of protein-coding genes in accordance with the 2006 version of Escherichia coli K-12 annotation record (GenBank U00096.2) and found ∼150 new start sites within 60 nucleotides of the annotated site. This analysis revealed 72 per cent of the genes whose initiation site annotations were changed from the 2006 GenBank record to the newer 2014 annotation record (GenBank U00096.3), indicating a high sensitivity. Also, results from reporter fusion and proteomics of N-terminally enriched peptides showed high specificity of the TetRP results. In addition, we discovered over 300 translation start sites within non-coding, intergenic regions of the genome, using a threshold that retains ∼2,000 known coding genes. While some appear to correspond to pseudogenes, others may encode small peptides or have previously unforeseen roles. In summary, we showed that ribosome profiling upon translation inhibition by tetracycline offers a simple, reliable and comprehensive experimental tool for precise annotation of translation start sites of expressed genes in bacteria.

There is a significant difference between synonymous codon usage in many organisms, and it is known that codons used more frequently generally showed efficient decoding rate. At the gene level, however, there are conflicting reports on the existence of a correlation between codon adaptation and translation efficiency, even in the same organism. To resolve this issue, we cultured Escherichia coli under conditions designed to maintain constant levels of mRNA and protein and subjected the cells to ribosome profiling (RP) and mRNA-seq analyses. We showed that the RP results correlated more closely with protein levels generated under similar culture conditions than with the mRNA abundance from the mRNA-seq. Our result indicated that RP/mRNA ratio could be used as a measure of translation efficiency at gene level. On the other hand, the RP data showed that codon-specific ribosome density at the decoding site negatively correlated with codon usage, consistent with the hypothesis that preferred codons display lower ribosome densities due to their faster decoding rate. However, highly codon-adapted genes showed higher ribosome densities at the gene level, indicating that the efficiency of translation initiation, rather than higher elongation efficiency of preferred codons, exerted a greater effect on ribosome density and thus translation efficiency. These findings indicate that evolutionary pressure on highly expressed genes influenced both codon bias and translation initiation efficiency and therefore explains contradictory findings that codon usage bias correlates with translation efficiency of native genes, but not with the artificially created gene pool, which was not subjected to evolution pressure.

Comprehensive experimental resources, such as ORFeome clone libraries and deletion mutant collections, are fundamental tools for elucidation of gene function. Data sets by omics analysis using these resources provide key information for functional analysis, modeling and simulation both in individual and systematic approaches. With the long-term goal of complete understanding of a cell, we have over the past decade created a variety of clone and mutant sets for functional genomics studies of Escherichia coli K-12. We have made these experimental resources freely available to the academic community worldwide. Accordingly, these resources have now been used in numerous investigations of a multitude of cell processes. Quality control is extremely important for evaluating results generated by these resources. Because the annotation has been changed since 2005, which we originally used for the construction, we have updated these genomic resources accordingly. Here, we describe GenoBase (http://ecoli.naist.jp/GB/), which contains key information about comprehensive experimental resources of E. coli K-12, their quality control and several omics data sets generated using these resources.