Extensive impact of non-antibiotic drugs on human gut bacteria.

A few commonly used non-antibiotic drugs have recently been associated with changes in gut microbiome composition, but the extent of this phenomenon is unknown. Here, we screened more than 1,000 marketed drugs against 40 representative gut bacterial strains, and found that 24% of the drugs with human targets, including members of all therapeutic classes, inhibited the growth of at least one strain in vitro. Particular classes, such as the chemically diverse antipsychotics, were overrepresented in this group. The effects of human-targeted drugs on gut bacteria are reflected on their antibiotic-like side effects in humans and are concordant with existing human cohort studies. Susceptibility to antibiotics and human-targeted drugs correlates across bacterial species, suggesting common resistance mechanisms, which we verified for some drugs. The potential risk of non-antibiotics promoting antibiotic resistance warrants further exploration. Our results provide a resource for future research on drug-microbiome interactions, opening new paths for side effect control and drug repurposing, and broadening our view of antibiotic resistance.

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.

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.

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).

Glycogen is the primary source of glucose during the lag phase of E. coli proliferation.

In the studies of Escherichia coli (E. coli), metabolomics analyses have mainly been performed using steady state culture. However, to analyze the dynamic changes in cellular metabolism, we performed a profiling of concentration of metabolites by using batch culture. As a first step, we focused on glucose uptake and the behavior of the first metabolite, G6P (glucose-6-phosphate). A computational formula was derived to express the glucose uptake rate by a single cell from two kinds of experimental data, extracellular glucose concentration and cell growth, being simulated by Cell Illustrator. In addition, average concentration of G6P has been measured by CE-MS. The existence of another carbon source was suggested from the computational result. After careful comparison between cell growth, G6P concentration, and the computationally obtained curve of glucose uptake rate, we predicted the consumption of glycogen in lag phase and its accumulation as an energy source in an E. coli cell for the next proliferation. We confirmed our prediction experimentally. This behavior indicates the importance of glycogen participation in the lag phase for the growth of E. coli. This article is part of a Special Issue entitled: Computational Methods for Protein Interaction and Structural Prediction.

1H-Imidazo[4,5-c]quinoline derivatives as novel potent TNF-alpha suppressors: synthesis and structure-activity relationship of 1-, 2-and 4-substituted 1H-imidazo[4,5-c]quinolines or 1H-imidazo[4,5-c]pyridines.

Structural modification of imiquimod (1), which is known as an interferon-alpha (IFN-alpha) inducer, for the aim of finding a novel and small-molecule tumor necrosis factor-alpha (TNF-alpha) suppressor and structure-activity relationship (SAR) are described. Structural modification of a imiquimod analogue, 4-amino-1-[2-(1-benzyl-4-piperidyl)ethyl-1H-imidazo[4,5-c]quinoline (2), which had moderate TNF-alpha suppressing activity without IFN-alpha inducing activity, led to a finding of 4-chloro-2-phenyl-1-[2-(4-piperidyl)ethyl]-1H-imidazo[4,5-c]quinoline (10) with potent TNF-alpha suppressing activity. The relation between conformational direction of 2-(4-piperidyl)ethyl group at position 1 and TNF-alpha suppressing activity is also demonstrated by NMR.