Chemical biology-whole genome engineering datasets predict new antibacterial combinations

Trimethoprim and sulfamethoxazole are used commonly together as cotrimoxazole for the treatment of urinary tract and other infections. The evolution of resistance to these and other antibacterials threatens therapeutic options for clinicians. We generated and analysed a chemical-biology-whole-genome data set to predict new targets for antibacterial combinations with trimethoprim and sulfamethoxazole. For this we used a large transposon mutant library in Escherichia coli BW25113 where an outward-transcribing inducible promoter was engineered into one end of the transposon. This approach allows regulated expression of adjacent genes in addition to gene inactivation at transposon insertion sites, a methodology that has been called TraDIS-Xpress. These chemical genomic data sets identified mechanisms for both reduced and increased susceptibility to trimethoprim and sulfamethoxazole. The data identified that over-expression of FolA reduced trimethoprim susceptibility, a known mechanism for reduced susceptibility. In addition, transposon insertions into the genes tdk, deoR, ybbC, hha, ldcA, wbbK and waaS increased susceptibility to trimethoprim and likewise for rsmH, fadR, ddlB, nlpI and prc with sulfamethoxazole, while insertions in ispD, uspC, minC, minD, yebK, truD and umpG increased susceptibility to both these antibiotics. Two of these genes’ products, Tdk and IspD, are inhibited by AZT and fosmidomycin respectively, antibiotics that are known to synergise with trimethoprim. Thus, the data identified two known targets and several new target candidates for the development of co-drugs that synergise with trimethoprim, sulfamethoxazole or cotrimoxazole. We demonstrate that the TraDIS-Xpress technology can be used to generate information-rich chemical-genomic data sets that can be used for antibacterial development.

In silico drug repositioning based on the integration of chemical, genomic and pharmacological spaces

Background Drug repositioning refers to the identification of new indications for existing drugs. Drug-based inference methods for drug repositioning apply some unique features of drugs for new indication prediction. Complementary information is provided by these different features. It is therefore necessary to integrate these features for more accurate in silico drug repositioning. Results In this study, we collect 3 different types of drug features (i.e., chemical, genomic and pharmacological spaces) from public databases. Similarities between drugs are separately calculated based on each of the features. We further develop a fusion method to combine the 3 similarity measurements. We test the inference abilities of the 4 similarity datasets in drug repositioning under the guilt-by-association principle. Leave-one-out cross-validations show the integrated similarity measurement IntegratedSim receives the best prediction performance, with the highest AUC value of 0.8451 and the highest AUPR value of 0.2201. Case studies demonstrate IntegratedSim produces the largest numbers of confirmed predictions in most cases. Moreover, we compare our integration method with 3 other similarity-fusion methods using the datasets in our study. Cross-validation results suggest our method improves the prediction accuracy in terms of AUC and AUPR values. Conclusions Our study suggests that the 3 drug features used in our manuscript are valuable information for drug repositioning. The comparative results indicate that integration of the 3 drug features would improve drug-disease association prediction. Our study provides a strategy for the fusion of different drug features for in silico drug repositioning.

Autophagy and Apoptosis Specific Knowledgebases-guided Systems Pharmacology Drug Research

Background: Autophagy and apoptosis are the basic physiological processes in cells that clean up aged and mutant cellular components or even the entire cells. Both autophagy and apoptosis are disrupted in most major diseases such as cancer and neurological disorders. Recently, increasing attention has been paid to understand the crosstalk between autophagy and apoptosis due to their tightly synergetic or opposite functions in several pathological processes. Objective: This study aims to assist autophagy and apoptosis-related drug research, clarify the intense and complicated connections between two processes, and provide a guide for novel drug development. Methods: We established two chemical-genomic databases which are specifically designed for autophagy and apoptosis, including autophagy- and apoptosis-related proteins, pathways and compounds. We then performed network analysis on the apoptosis- and autophagy-related proteins and investigated the full protein-protein interaction (PPI) network of these two closely connected processes for the first time. Results: The overlapping targets we discovered show a more intense connection with each other than other targets in the full network, indicating a better efficacy potential for drug modulation. We also found that Death-associated protein kinase 1 (DAPK1) is a critical point linking autophagy- and apoptosis-related pathways beyond the overlapping part, and this finding may reveal some delicate signaling mechanism of the process. Finally, we demonstrated how to utilize our integrated computational chemogenomics tools on in silico target identification for small molecules capable of modulating autophagy- and apoptosis-related pathways. Conclusion: The knowledge-bases for apoptosis and autophagy and the integrated tools will accelerate our work in autophagy and apoptosis-related research and can be useful sources for information searching, target prediction, and new chemical discovery.

Hamigeran G Does Not Affect Golgi Structure or Function in HEK293 Cells

The hamigerans are diterpenoid secondary metabolites isolated from the New Zealand marine sponge Hamigera tarangaensis. Of all the hamigerans that have been isolated and characterised at Victoria University of Wellington, hamigeran G showed the most potent anti-proliferative activity against a mammalian cancer cell line. We previously reported that it might be targeting the Golgi network of cells based on a chemical genomic screen on yeast (Saccharomyces cerevisiae). Here, we investigated the effects of hamigeran G on the Golgi network of mammalian cells and showed that it did not have a significant effect on Golgi apparatus morphology or Golgi network functions such as protein secretion and endocytosis. Results of this study, therefore, conclude that the Golgi network is unlikely to be the primary target of hamigeran G's anti-proliferative activity. Further work is needed to fully elucidate the mechanism of action and target(s) of hamigeran G.

Genomic Identification of the TOR Signaling Pathway as a Target of the Plant Alkaloid Antofine in the Phytopathogen Fusarium graminearum

ABSTRACT Antofine, a phenanthroindolizidine alkaloid, is a bioactive natural product isolated from milkweeds that exhibits numerous biological activities, including anticancer, antimicrobial, antiviral, and anti-inflammatory properties. However, the direct targets and mode of action of antofine have not been determined. In this report, we show that antofine displays antifungal properties against the phytopathogen Fusarium graminearum, the cause of Fusarium head blight disease (FHB). FHB does devastating damage to agriculture, causing billions of dollars in economic losses annually. We therefore sought to understand the mode of action of antofine in F. graminearum using insights from yeast chemical genomic screens. We used haploinsufficiency profiling (HIP) to identify putative targets of antofine in yeast and identified three candidate targets, two of which had homologs in F. graminearum. The Fusarium homologues of two targets, glutamate dehydrogenase (FgGDH) and resistance to rapamycin deletion 2 (FgRRD2), can bind antofine. Of the two genes, only the Fgrrd2 knockout displayed a loss of virulence in wheat, indicating that RRD2 is an antivirulence target of antofine in F. graminearum. Mechanistically, we demonstrate that antofine disrupts the interaction between FgRRD2 and FgTap42, which is part of the Tap42-phosphatase complex in the target of rapamycin (TOR) signaling pathway, a central regulator of cell growth in eukaryotes and a pathway of extensive study for controlling numerous pathologies. IMPORTANCE Fusarium head blight caused by the fungal pathogen Fusarium graminearum is a devastating disease of cereal crops worldwide, with limited effective chemical treatments available. Here we show that the natural alkaloid compound antofine can inhibit fusarium head blight in wheat. Using yeast genomic screening, we identified the TOR pathway component RRD2 as a target of antofine that is also required for F. graminearum pathogenicity.

Chemical genomic guided engineering of gamma-valerolactone tolerant yeast

BackgroundGamma valerolactone (GVL) is a promising technology for degradation of biomass for biofuel production; however, GVL has adverse toxicity effects on fermentative microbes. Using a combination of chemical genomics and chemical proteomics we sought to understand the mechanism toxicity and resistance to GVL with the goal of engineering a GVL-tolerant, xylose-fermenting yeast.ResultsChemical genomic profiling of GVL predicted that this chemical affects membranes and membrane-bound processes. We show that GVL causes rapid, dose-dependent cell permeability, and is synergistic with ethanol. Chemical genomic profiling of GVL revealed that deletion of the functionally related enzymes Pad1p and Fdc1p, which act together to decarboxylate phenolic acids to vinyl derivatives, increases yeast tolerance to GVL. Further, overexpression of Pad1p sensitizes cells to GVL toxicity. To improve GVL tolerance, we deleted PAD1 and FDC1 in a xylose-fermenting yeast strain. The modified strain exhibited increased anaerobic growth, sugar utilization, and ethanol production in synthetic hydrolysate with 1.5% GVL, and under other conditions. Chemical proteomic profiling of the engineered strain revealed that enzymes involved in ergosterol biosynthesis were more abundant in the presence of GVL compared to the background strain. The engineered GVL strain contained greater amounts of ergosterol than the background strain.ConclusionsWe found that GVL exerts toxicity to yeast by compromising cellular membranes, and that this toxicity is synergistic with ethanol. Deletion of PAD1 and FDC1 conferred GVL resistance to a xylose-fermenting yeast strain by increasing ergosterol content in cells. The GVL-tolerant strain fermented sugars in the presence of GVL levels that were inhibitory to the unmodified strain. This strain represents a xylose fermenting yeast specifically tailored to GVL produced hydrolysates