GenoBase: comprehensive resource database of Escherichia coli K-12.

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.

Toward Network Biology in E. coli Cell.

E. coli has been a critically important model research organism for more than 50 years, particularly in molecular biology. In 1997, the E. coli draft genome sequence was published. Post-genomic techniques and resources were then developed that allowed E. coli to become a model organism for systems biology. Progress made since publication of the E. coli genome sequence will be summarized.

Colony-live--a high-throughput method for measuring microbial colony growth kinetics--reveals diverse growth effects of gene knockouts in Escherichia coli.

BACKGROUND: Precise quantitative growth measurements and detection of small growth changes in high-throughput manner is essential for fundamental studies of bacterial cell. However, an inherent tradeoff for measurement quality in high-throughput methods sacrifices some measurement quality. A key challenge has been how to enhance measurement quality without sacrificing throughput. RESULTS: We developed a new high-throughput measurement system, termed Colony-live. Here we show that Colony-live provides accurate measurement of three growth values (lag time of growth (LTG), maximum growth rate (MGR), and saturation point growth (SPG)) by visualizing colony growth over time. By using a new normalization method for colony growth, Colony-live gives more precise and accurate growth values than the conventional method. We demonstrated the utility of Colony-live by measuring growth values for the entire Keio collection of Escherichia coli single-gene knockout mutants. By using Colony-live, we were able to identify subtle growth defects of single-gene knockout mutants that were undetectable by the conventional method quantified by fixed time-point camera imaging. Further, Colony-live can reveal genes that influence the length of the lag-phase and the saturation point of growth. CONCLUSIONS: Measurement quality is critical to achieving the resolution required to identify unique phenotypes among a diverse range of phenotypes. Sharing high-quality genome-wide datasets should benefit many researchers who are interested in specific gene functions or the architecture of cellular systems. Our Colony-live system provides a new powerful tool to accelerate accumulation of knowledge of microbial growth phenotypes.

GlgS, described previously as a glycogen synthesis control protein, negatively regulates motility and biofilm formation in Escherichia coli.

Escherichia coli glycogen metabolism involves the regulation of glgBXCAP operon expression and allosteric control of the GlgC [ADPG (ADP-glucose) pyrophosphorylase]-mediated catalysis of ATP and G1P (glucose-1-phosphate) to ADPG linked to glycogen biosynthesis. E. coli glycogen metabolism is also affected by glgS. Though the precise function of the protein it encodes is unknown, its deficiency causes both reduced glycogen content and enhanced levels of the GlgC-negative allosteric regulator AMP. The transcriptomic analyses carried out in the present study revealed that, compared with their isogenic BW25113 wild-type strain, glgS-null (ΔglgS) mutants have increased expression of the operons involved in the synthesis of type 1 fimbriae adhesins, flagella and nucleotides. In agreement, ΔglgS cells were hyperflagellated and hyperfimbriated, and displayed elevated swarming motility; these phenotypes all reverted to the wild-type by ectopic glgS expression. Also, ΔglgS cells accumulated high colanic acid content and displayed increased ability to form biofilms on polystyrene surfaces. F-driven conjugation based on large-scale interaction studies of glgS with all the non-essential genes of E. coli showed that deletion of purine biosynthesis genes complement the glycogen-deficient, high motility and high biofilm content phenotypes of ΔglgS cells. Overall the results of the present study indicate that glycogen deficiency in ΔglgS cells can be ascribed to high flagellar propulsion and high exopolysaccharide and purine nucleotides biosynthetic activities competing with GlgC for the same ATP and G1P pools. Supporting this proposal, glycogen-less ΔglgC cells displayed an elevated swarming motility, and accumulated high levels of colanic acid and biofilm. Furthermore, glgC overexpression reverted the glycogen-deficient, high swarming motility, high colanic acid and high biofilm content phenotypes of ΔglgS cells to the wild-type. As on the basis of the present study GlgS has emerged as a major determinant of E. coli surface composition and because its effect on glycogen metabolism appears to be only indirect, we propose to rename it as ScoR (surface composition regulator).

The tRNA thiolation pathway modulates the intracellular redox state in Escherichia coli.

We have performed a screening of hydroxyurea (HU)-sensitive mutants using a single-gene-deletion mutant collection in Escherichia coli K-12. HU inhibits ribonucleotide reductase (RNR), an enzyme that catalyzes the formation of deoxyribonucleotides. Unexpectedly, seven of the mutants lacked genes that are required for the incorporation of sulfur into a specific tRNA modification base, 5-methylaminomethyl-2-thiouridine (mnm(5)s(2)U), via persulfide relay. We found that the expression of RNR in the mutants was reduced to about one-third both in the absence and presence of HU, while sufficient deoxynucleoside triphosphate (dNTP) was maintained in the mutants in the absence of HU but a shortage occurred in the presence of HU. Trans-supply of an RNR R2 subunit rescued the HU sensitivity of these mutants. The mutants showed high intracellular ATP/ADP ratios, and overexpression of Hda, which catalyzes the conversion of DnaA-ATP to DnaA-ADP, rescued the HU sensitivity of the mutants, suggesting that DnaA-ATP represses RNR expression. The high intracellular ATP/ADP ratios were due to high respiration activity in the mutants. Our data suggested that intracellular redox was inclined toward the reduced state in these mutants, which may explain a change in RNR activity by reduction of the catalytically formed disulfide bond and high respiration activity by the NADH reducing potential. The relation between persulfide relay and intracellular redox is discussed.

Proposal of De Novo Antigen Test for COVID-19: Ultrasensitive Detection of Spike Proteins of SARS-CoV-2.

Polymerase chain reaction (PCR)-based antigen tests are technically difficult, time-consuming, and expensive, and may produce false negative results requiring follow-up confirmation with computed tomography. The global coronavirus disease 2019 (COVID-19) pandemic has increased the demand for accurate, easy-to-use, rapid, and cost-effective antigen tests for clinical application. We propose a de novo antigen test for diagnosing COVID-19 using the combination of sandwich enzyme-linked immunosorbent assay and thio-nicotinamide adenine dinucleotide (thio-NAD) cycling. Our test takes advantage of the spike proteins specific to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. The limit of detection of our test was 2.3 × 10-18 moles/assay. If the virus has ~25 spike proteins on its surface, our method should detect on the order of 10-20 moles of virus/assay, corresponding to ~104 copies of the virus RNA/assay. The detection sensitivity approaches that of PCR-based assays because the average virus RNA load used for PCR-based assays is ~105 copies per oro- or naso-pharyngeal swab specimen. To our knowledge, this is the first ultrasensitive antigen test for SARS-CoV-2 spike proteins that can be performed with an easy-to-use microplate reader. Sufficient sensitivity can be achieved within 10 min of thio-NAD cycling. Our antigen test allows for rapid, cost-effective, specific, ultrasensitive, and simultaneous multiple measurements of SARS-CoV-2, and has broad application for the diagnosis for COVID-19.

A novel, rapid (within hours) culture-free diagnostic method for detecting live Mycobacterium tuberculosis with high sensitivity.

BACKGROUND: Nucleic acid amplification tests (NAATs) are widely used to diagnose tuberculosis (TB), but cannot discriminate live bacilli from dead bacilli. Live bacilli can be isolated by culture methods, but this is time-consuming. We developed a de novo TB diagnostic method that detects only live bacilli with high sensitivity within hours. METHODS: A prospective study was performed in Taiwan from 2017 to 2018. Sputum was collected consecutively from 1102 patients with suspected TB infection. The sputum was pretreated and heated at 46°C for 1 h to induce the secretion of MPT64 protein from live Mycobacterium tuberculosis. MPT64 was detected with our ultrasensitive enzyme-linked immunosorbent assay (ELISA) coupled with thionicotinamide-adenine dinucleotide (thio-NAD) cycling. We compared our data with those obtained using a culture test (MGIT), a smear test (Kinyoun staining), and a NAAT (Xpert). FINDINGS: The limit of detection for MPT64 in our culture-free ultrasensitive ELISA was 2.0 × 10-19 moles/assay. When the criterion for a positive response was set as an absorbance value ≥17 mAbs, this value corresponded to ca. 330 CFU/mL in the culture method - almost the same high-detection sensitivity as the culture method. To confirm that MPT64 is secreted from only live bacilli, M. bovis BCG was killed using 8 µg/mL rifampicin and then heated. Following this procedure, our method detected no MPT64. Our rapid ultra-sensitive ELISA-based method required only 5 h to complete. Comparing the results of our method with those of culture tests for 944 specimens revealed a sensitivity of 86.9% (93/107, 95% CI: 79.0-92.7%) and a specificity of 92.0% (770/837, 95% CI: 89.9-93.7%). The performance data were not significantly different (McNemar's test, P = 0.887) from those of the Xpert tests. In addition, at a ≥1+ titer in the smear test, the positive predictive value of our culture-free ultrasensitive ELISA tests was in a good agreement with that of the culture tests. Furthermore, our culture-free ultrasensitive ELISA test had better validity for drug effectiveness examination than Xpert tests because our test detected only live bacilli. INTERPRETATION: Our culture-free ultrasensitive ELISA method detects only live TB bacilli with high sensitivity within hours, allowing for rapid diagnosis of TB and monitoring drug efficacy. FUNDING: Matching Planner Program from JST (VP29117939087), the A-STEP Program from JST (AS3015096U), Waseda University grants for Specific Research Projects (2017A-015 and 2019C-123), the Precise Measurement Technology Promotion Foundation to E.I.

Ultrasensitive enzyme-linked immunosorbent assay for the detection of MPT64 secretory antigen to evaluate Mycobacterium tuberculosis viability in sputum.

OBJECTIVES: This study examined Mycobacterium tuberculosis (MTB)-secreted MPT64 as a surrogate of bacterial viability for the diagnosis of active pulmonary TB (PTB) and for follow-up treatment. METHODS: In this proof-of-concept prospective study, 50 PTB patients in the Tokyo metropolitan region, between 2017 and 2018, were consecutively included and 30 healthy individuals were also included. Each PTB patient submitted sputum on days 0, 14 and 28 for diagnosis and follow-up, and each healthy individual submitted one sputum sample. The following were performed: smear microscopy, Xpert MTB/RIF, MGIT and solid culture, and MPT64 detection on the sputum samples. Ultrasensitive ELISA (usELISA) was used to detect MPT64. The receiver operating characteristic analyses for diagnosis and follow-up revealed the optimal cut-off value of MPT64 absorbance for detecting culture positivity at multiple intervals. RESULTS: The sensitivity of MPT64 for diagnosing PTB was 88.0% (95% CI 75.7-95.5) and the specificity was 96.7% (95% CI 82.8-99.9). The specificity of MPT64 for predicting negative culture results on day 14 was 89.5% (95% CI 66.9-98.7). The sensitivity of MPT64 for predicting positive culture results on day 28 was 81.0% (95% CI 58.1-94.6). CONCLUSIONS: This study revealed that MPT64 is useful for diagnosing active PTB in patients and predicting treatment efficacy at follow-up.

Identification of essential genes and synthetic lethal gene combinations in Escherichia coli K-12.

Here we describe the systematic identification of single genes and gene pairs, whose knockout causes lethality in Escherichia coli K-12. During construction of precise single-gene knockout library of E. coli K-12, we identified 328 essential gene candidates for growth in complex (LB) medium. Upon establishment of the Keio single-gene deletion library, we undertook the development of the ASKA single-gene deletion library carrying a different antibiotic resistance. In addition, we developed tools for identification of synthetic lethal gene combinations by systematic construction of double-gene knockout mutants. We introduce these methods herein.

Genome-scale identification and characterization of moonlighting proteins.

BACKGROUND: Moonlighting proteins perform two or more cellular functions, which are selected based on various contexts including the cell type they are expressed, their oligomerization status, and the binding of different ligands at different sites. To understand overall landscape of their functional diversity, it is important to establish methods that can identify moonlighting proteins in a systematic fashion. Here, we have developed a computational framework to find moonlighting proteins on a genome scale and identified multiple proteomic characteristics of these proteins. RESULTS: First, we analyzed Gene Ontology (GO) annotations of known moonlighting proteins. We found that the GO annotations of moonlighting proteins can be clustered into multiple groups reflecting their diverse functions. Then, by considering the observed GO term separations, we identified 33 novel moonlighting proteins in Escherichia coli and confirmed them by literature review. Next, we analyzed moonlighting proteins in terms of protein-protein interaction, gene expression, phylogenetic profile, and genetic interaction networks. We found that moonlighting proteins physically interact with a higher number of distinct functional classes of proteins than non-moonlighting ones and also found that most of the physically interacting partners of moonlighting proteins share the latter's primary functions. Interestingly, we also found that moonlighting proteins tend to interact with other moonlighting proteins. In terms of gene expression and phylogenetically related proteins, a weak trend was observed that moonlighting proteins interact with more functionally diverse proteins. Structural characteristics of moonlighting proteins, i.e. intrinsic disordered regions and ligand binding sites were also investigated. CONCLUSION: Additional functions of moonlighting proteins are difficult to identify by experiments and these proteins also pose a significant challenge for computational function annotation. Our method enables identification of novel moonlighting proteins from current functional annotations in public databases. Moreover, we showed that potential moonlighting proteins without sufficient functional annotations can be identified by analyzing available omics-scale data. Our findings open up new possibilities for investigating the multi-functional nature of proteins at the systems level and for exploring the complex functional interplay of proteins in a cell. REVIEWERS: This article was reviewed by Michael Galperin, Eugine Koonin, and Nick Grishin.

Development of a system for discovery of genetic interactions for essential genes in Escherichia coli K-12.

Genetic interaction networks are especially useful for functional assignment of genes and gaining new insights into the systems-level organization of the cell. While studying interactions of nonessential genes can be relatively straight-forward via use of deletion mutants, different approaches must be used to reveal interactions of essential genes due to their indispensability. One method shown to be useful for revealing interactions of essential genes requires tagging the query protein. However, this approach can be complicated by mutational effects of potential hypomorphic alleles. Here, we describe a pilot study for a new scheme of systematically studying the interactions of essential genes. Our method uses a low-copy, F-based, complementing plasmid, pFE604T, from which the essential gene is conditionally expressed. The essential gene is expressed at lower levels, producing a moderate growth defect in a query host. Secondary mutations are introduced into the query host by conjugation and the resultant exconjugants are scored for growth by imaging them over time. We report results from studying five essential query genes: dnaN, ftsW, trmD, yrfF and yjgP, showing (on average) interactions with nearly 80 nonessential genes. This system should prove useful for genome-wide analyses of other essential genes in E. coli K-12.

High-throughput, quantitative analyses of genetic interactions in E. coli.

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 Saccharomyces cerevisiae have dramatically accelerated the acquisition of genetic interaction information and the biological inferences that follow. Here we describe a method based on F factor-driven conjugation, which allows for high-throughput generation of double mutants in Escherichia 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 previously unidentified negative (synthetic sickness or lethality) and positive (suppressive or epistatic) relationships. Finally, we describe a complementary strategy for genome-wide suppressor-mutant identification. Together, these methods permit rapid, large-scale genetic interaction studies in E. coli.