The unusual mode of action of the polyketide glycoside antibiotic cervimycin C.

Cervimycins A-D are bis-glycosylated polyketide antibiotics produced by Streptomyces tendae HKI 0179 with bactericidal activity against Gram-positive bacteria. In this study, cervimycin C (CmC) treatment caused a spaghetti-like phenotype in Bacillus subtilis 168, with elongated curved cells, which stayed joined after cell division, and exhibited a chromosome segregation defect, resulting in ghost cells without DNA. Electron microscopy of CmC-treated Staphylococcus aureus (3 × MIC) revealed swollen cells, misshapen septa, cell wall thickening, and a rough cell wall surface. Incorporation tests in B. subtilis indicated an effect on DNA biosynthesis at high cervimycin concentrations. Indeed, artificial downregulation of the DNA gyrase subunit B gene (gyrB) increased the activity of cervimycin in agar diffusion tests, and, in high concentrations (starting at 62.5 × MIC), the antibiotic inhibited S. aureus DNA gyrase supercoiling activity in vitro. To obtain a more global view on the mode of action of CmC, transcriptomics and proteomics of cervimycin treated versus untreated S. aureus cells were performed. Interestingly, 3 × MIC of cervimycin did not induce characteristic responses, which would indicate disturbance of the DNA gyrase activity in vivo. Instead, cervimycin induced the expression of the CtsR/HrcA heat shock operon and the expression of autolysins, exhibiting similarity to the ribosome-targeting antibiotic gentamicin. In summary, we identified the DNA gyrase as a target, but at low concentrations, electron microscopy and omics data revealed a more complex mode of action of cervimycin, which comprised induction of the heat shock response, indicating protein stress in the cell.IMPORTANCEAntibiotic resistance of Gram-positive bacteria is an emerging problem in modern medicine, and new antibiotics with novel modes of action are urgently needed. Secondary metabolites from Streptomyces species are an important source of antibiotics, like the cervimycin complex produced by Streptomyces tendae HKI 0179. The phenotypic response of Bacillus subtilis and Staphylococcus aureus toward cervimycin C indicated a chromosome segregation and septum formation defect. This effect was at first attributed to an interaction between cervimycin C and the DNA gyrase. However, omics data of cervimycin treated versus untreated S. aureus cells indicated a different mode of action, because the stress response did not include the SOS response but resembled the response toward antibiotics that induce mistranslation or premature chain termination and cause protein stress. In summary, these results point toward a possibly novel mechanism that generates protein stress in the cells and subsequently leads to defects in cell and chromosome segregation.

Fosfomycin Uptake in Escherichia coli Is Mediated by the Outer-Membrane Porins OmpF, OmpC, and LamB.

The antibiotic fosfomycin (FOS) is widely recognized for the treatment of lower urinary tract infections with Escherichia coli and has lately gained importance as a therapeutic option to combat multidrug-resistant bacteria. However, resistance to FOS frequently develops through mutations reducing its uptake. Although the inner-membrane transport of FOS has been extensively studied in E. coli, its outer-membrane (OM) transport remains insufficiently understood. While evaluating minimal inhibitory concentrations in OM porin-deficient mutants, we observed that the E. coli ΔompFΔompC strain is four times more resistant to FOS than the wild type and the respective single mutants. Continuous monitoring of FOS-induced lysis of porin-deficient strains additionally highlighted the importance of LamB. The relevance of OmpF, OmpC, and LamB to FOS uptake was confirmed by electrophysiological and transcriptional analysis. Our study gives for the first time in-depth insight into the transport of FOS through the OM in E. coli.

An antibiotic from an uncultured bacterium binds to an immutable target.

Antimicrobial resistance is a leading mortality factor worldwide. Here, we report the discovery of clovibactin, an antibiotic isolated from uncultured soil bacteria. Clovibactin efficiently kills drug-resistant Gram-positive bacterial pathogens without detectable resistance. Using biochemical assays, solid-state nuclear magnetic resonance, and atomic force microscopy, we dissect its mode of action. Clovibactin blocks cell wall synthesis by targeting pyrophosphate of multiple essential peptidoglycan precursors (C55PP, lipid II, and lipid IIIWTA). Clovibactin uses an unusual hydrophobic interface to tightly wrap around pyrophosphate but bypasses the variable structural elements of precursors, accounting for the lack of resistance. Selective and efficient target binding is achieved by the sequestration of precursors into supramolecular fibrils that only form on bacterial membranes that contain lipid-anchored pyrophosphate groups. This potent antibiotic holds the promise of enabling the design of improved therapeutics that kill bacterial pathogens without resistance development.

OmicsTIDE: interactive exploration of trends in multi-omics data.

Motivation: The increasing amount of data produced by omics technologies has enabled researchers to study phenomena across multiple omics layers. Besides data-driven analysis strategies, interactive visualization tools have been developed for a more transparent analysis. However, most state-of-the-art tools do not reconstruct the impact of a single omics layer on the integration result. Results: We developed a data classification scheme focusing on different aspects of multi-omics datasets for a systemic understanding. Based on this classification, we developed the Omics Trend-comparing Interactive Data Explorer (OmicsTIDE), an interactive visualization tool for the comparison of gene-based quantitative omics data. The tool consists of a computational part that clusters omics datasets to determine trends and an interactive visualization. The trends are visualized as profile plots and are connected by a Sankey diagram that allows for an interactive pairwise trend comparison to discover concordant and discordant trends. Moreover, large-scale omics datasets are broken down into small subsets that can be analyzed functionally using Gene Ontology enrichment within few analysis steps. We demonstrate the interactive analysis using OmicsTIDE with two case studies focusing on different experimental designs. Availability and implementation: OmicsTIDE is a web tool available via http://omicstide-tuevis.cs.uni-tuebingen.de/. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

Horizontal Transfer of Bacteriocin Biosynthesis Genes Requires Metabolic Adaptation To Improve Compound Production and Cellular Fitness.

Biosynthetic gene clusters (BGCs) encoding the production of bacteriocins are widespread among bacterial isolates and are important genetic determinants of competitive fitness within a given habitat. Staphylococci produce a tremendous diversity of compounds, and the corresponding BGCs are frequently associated with mobile genetic elements, suggesting gain and loss of biosynthetic capacity. Pharmaceutical biology has shown that compound production in heterologous hosts is often challenging, and many BGC recipients initially produce small amounts of compound or show reduced growth rates. To assess whether transfer of BGCs between closely related Staphylococcus aureus strains can be instantly effective or requires elaborate metabolic adaptation, we investigated the intraspecies transfer of a BGC encoding the ribosomally synthesized and posttranslationally modified peptide (RiPP) micrococcin P1 (MP1). We found that acquisition of the BGC by S. aureus RN4220 enabled immediate MP1 production but also imposed a metabolic burden, which was relieved after prolonged cultivation by adaptive mutation. We used a multiomics approach to study this phenomenon and found adaptive evolution to select for strains with increased activity of the tricarboxylic acid cycle (TCA), which enhanced metabolic fitness and levels of compound production. Metabolome analysis revealed increases of central metabolites, including citrate and α-ketoglutarate in the adapted strain, suggesting metabolic adaptation to overcome the BGC-associated growth defects. Our results indicate that BGC acquisition requires genetic and metabolic predispositions, allowing the integration of bacteriocin production into the cellular metabolism. Inappropriate metabolic characteristics of recipients can entail physiological burdens, negatively impacting the competitive fitness of recipients within natural bacterial communities. IMPORTANCE Human microbiomes are critically associated with human health and disease. Importantly, pathogenic bacteria can hide in human-associated communities and can cause disease when the composition of the community becomes unbalanced. Bacteriocin-producing commensals are able to displace pathogens from microbial communities, suggesting that their targeted introduction into human microbiomes might prevent pathogen colonization and infection. However, to develop probiotic approaches, strains are needed that produce high levels of bioactive compounds and retain cellular fitness within mixed bacterial communities. Our work offers insights into the metabolic burdens associated with the production of the bacteriocin micrococcin P1 and highlights evolutionary strategies that increase cellular fitness in the context of production. Metabolic adaptations are most likely broadly relevant for bacteriocin producers and need to be considered for the future development of effective microbiome editing strategies.

Cervimycin-Resistant Staphylococcus aureus Strains Display Vancomycin-Intermediate Resistant Phenotypes.

Resistance to antibiotics is an increasing problem and necessitates novel antibacterial therapies. The polyketide antibiotics cervimycin A to D are natural products of Streptomyces tendae HKI 0179 with promising activity against multidrug-resistant staphylococci and vancomycin-resistant enterococci. To initiate mode of action studies, we selected cervimycin C- and D-resistant (CmR) Staphylococcus aureus strains. Genome sequencing of CmR mutants revealed amino acid exchanges in the essential histidine kinase WalK, the Clp protease proteolytic subunit ClpP or the Clp ATPase ClpC, and the heat shock protein DnaK. Interestingly, all characterized CmR mutants harbored a combination of mutations in walK and clpP or clpC. In vitro and in vivo analyses showed that the mutations in the Clp proteins abolished ClpP or ClpC activity, and the deletion of clpP rendered S. aureus but not all Bacillus subtilis strains cervimycin-resistant. The essential gene walK was the second mutational hotspot in the CmR S. aureus strains, which decreased WalK activity in vitro and generated a vancomycin-intermediate resistant phenotype, with a thickened cell wall, a lower growth rate, and reduced cell lysis. Transcriptomic and proteomic analyses revealed massive alterations in the CmR strains compared to the parent strain S. aureus SG511, with major shifts in the heat shock regulon, the metal ion homeostasis, and the carbohydrate metabolism. Taken together, mutations in the heat shock genes clpP, clpC, and dnaK, and the walK kinase gene in CmR mutants induced a vancomycin-intermediate resistant phenotype in S. aureus, suggesting cell wall metabolism or the Clp protease system as primary target of cervimycin. IMPORTANCE Staphylococcus aureus is a frequent cause of infections in both the community and hospital setting. Resistance development of S. aureus to various antibiotics is a severe problem for the treatment of this pathogen worldwide. New powerful antimicrobial agents against Gram-positives are needed, since antibiotics like vancomycin fail to cure vancomycin-intermediate resistant S. aureus (VISA) and vancomycin-resistant enterococci (VRE) infections. One candidate substance with promising activity against these organisms is cervimycin, which is an antibiotic complex with a yet unknown mode of action. In our study, we provide first insights into the mode of action of cervimycins. By characterizing cervimycin-resistant S. aureus strains, we revealed the Clp system and the essential kinase WalK as mutational hotspots for cervimycin resistance in S. aureus. It further emerged that cervimycin-resistant S. aureus strains show a VISA phenotype, indicating a role of cervimycin in perturbing the bacterial cell envelope.

Secondary Metabolite Transcriptomic Pipeline (SeMa-Trap), an expression-based exploration tool for increased secondary metabolite production in bacteria.

For decades, natural products have been used as a primary resource in drug discovery pipelines to find new antibiotics, which are mainly produced as secondary metabolites by bacteria. The biosynthesis of these compounds is encoded in co-localized genes termed biosynthetic gene clusters (BGCs). However, BGCs are often not expressed under laboratory conditions. Several genetic manipulation strategies have been developed in order to activate or overexpress silent BGCs. Significant increases in production levels of secondary metabolites were indeed achieved by modifying the expression of genes encoding regulators and transporters, as well as genes involved in resistance or precursor biosynthesis. However, the abundance of genes encoding such functions within bacterial genomes requires prioritization of the most promising ones for genetic manipulation strategies. Here, we introduce the 'Secondary Metabolite Transcriptomic Pipeline' (SeMa-Trap), a user-friendly web-server, available at https://sema-trap.ziemertlab.com. SeMa-Trap facilitates RNA-Seq based transcriptome analyses, finds co-expression patterns between certain genes and BGCs of interest, and helps optimize the design of comparative transcriptomic analyses. Finally, SeMa-Trap provides interactive result pages for each BGC, allowing the easy exploration and comparison of expression patterns. In summary, SeMa-Trap allows a straightforward prioritization of genes that could be targeted via genetic engineering approaches to (over)express BGCs of interest.

ThreadStates: State-based Visual Analysis of Disease Progression.

A growing number of longitudinal cohort studies are generating data with extensive patient observations across multiple timepoints. Such data offers promising opportunities to better understand the progression of diseases. However, these observations are usually treated as general events in existing visual analysis tools. As a result, their capabilities in modeling disease progression are not fully utilized. To fill this gap, we designed and implemented ThreadStates, an interactive visual analytics tool for the exploration of longitudinal patient cohort data. The focus of ThreadStates is to identify the states of disease progression by learning from observation data in a human-in-the-loop manner. We propose a novel Glyph Matrix design and combine it with a scatter plot to enable seamless identification, observation, and refinement of states. The disease progression patterns are then revealed in terms of state transitions using Sankey-based visualizations. We employ sequence clustering techniques to find patient groups with distinctive progression patterns, and to reveal the association between disease progression and patient-level features. The design and development were driven by a requirement analysis and iteratively refined based on feedback from domain experts over the course of a 10-month design study. Case studies and expert interviews demonstrate that ThreadStates can successively summarize disease states, reveal disease progression, and compare patient groups.

Evidente-a visual analytics tool for data enrichment in SNP-based phylogenetic trees.

Motivation: A common practice in the analysis of pathogens and their strains is using single-nucleotide polymorphisms (SNPs) to reconstruct their evolutionary history. However, genome-wide SNP-based phylogenetic trees are rarely analyzed without any further information. Including the underlying SNP data together with further metadata on the respective samples in the exploration process can facilitate linking the genomic and phenotypic properties of the samples. Results: We introduce Efficient VIsual analytics tool for Data ENrichment in phylogenetic TreEs (Evidente), a web-application that provides an interactive visual analysis interface for the simultaneous interrogation of phylogenetic relationships, genome-wide SNP data and metadata for samples of an organism. Besides visualizing the phylogenetic tree, Evidente classifies SNPs as supporting or non-supporting of the tree structures and shows the distribution of both types of SNPs among samples and clades of interest. Furthermore, additional metadata can be included in the visualization. Lastly, Evidente includes an enrichment analysis to identify over-represented genomic features encoded by GO-terms within the clades of the tree. We demonstrate the usability of Evidente with the data of the pathogens Treponema pallidum and Mycobacterium leprae. Availability and implementation: Evidente is available at the TueVis visualization web server at https://evidente-tuevis.cs.uni-tuebingen.de/, it can also be run locally. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

OncoThreads: visualization of large-scale longitudinal cancer molecular data.

MOTIVATION: Molecular profiling of patient tumors and liquid biopsies over time with next-generation sequencing technologies and new immuno-profile assays are becoming part of standard research and clinical practice. With the wealth of new longitudinal data, there is a critical need for visualizations for cancer researchers to explore and interpret temporal patterns not just in a single patient but across cohorts. RESULTS: To address this need we developed OncoThreads, a tool for the visualization of longitudinal clinical and cancer genomics and other molecular data in patient cohorts. The tool visualizes patient cohorts as temporal heatmaps and Sankey diagrams that support the interactive exploration and ranking of a wide range of clinical and molecular features. This allows analysts to discover temporal patterns in longitudinal data, such as the impact of mutations on response to a treatment, for example, emergence of resistant clones. We demonstrate the functionality of OncoThreads using a cohort of 23 glioma patients sampled at 2-4 timepoints. AVAILABILITY AND IMPLEMENTATION: Freely available at http://oncothreads.gehlenborglab.org. Implemented in Java Script using the cBioPortal web API as a backend. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.