Summary of Study ST002747

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001710. The data can be accessed directly via it's Project DOI: 10.21228/M8P43M This work is supported by NIH grant, U2C- DK119886.

See: https://www.metabolomicsworkbench.org/about/howtocite.php

This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.

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Study IDST002747
Study TitleEvolutionary genomics identifies host-directed therapeutics to treat intracellular bacterial infections
Study SummaryObligate intracellular bacteria from the Rickettsiaceae family have shed essential biosynthetic pathways during their evolution towards host dependency. By systematically comparing this cytosolic family of bacteria to the related vacuolar Anaplasmataceae family using a novel computational pipeline called PoMeLo, we identified 20 metabolic pathways that may have been lost since the divergence of Anaplasmataceae and Rickettsiaceae, corresponding to the latter’s change to a cytosolic niche. We hypothesized that drug inhibition of these host metabolic pathways would reduce the levels of metabolic products available to the bacteria, thereby inhibiting bacterial growth. We tested 22 commercially available inhibitors for 14 of the identified pathways and found that 59% of the inhibitors reduced bacterial growth at concentrations that did not contribute to host cell cytotoxicity. Of these, 5 inhibitors with an IC50 under 5 µM were tested to determine whether their mode of inhibition was bactericidal or bacteriostatic. Both mycophenolate mofetil, an inhibitor of inosine-5'-monophosphate dehydrogenase in the purine biosynthesis pathway, and roseoflavin, an analog of riboflavin, displayed bactericidal activity. We then took an unbiased metabolomics approach to Rickettsia-infected cells to determine whether there was any overlap between our predicted host pathways and depletion of metabolite levels in infected cells, as measured by mass spectrometry. Our results show that 13 pathways were identified as metabolic gaps in both our computational predictions and our metabolomics analysis. These in vitro validation studies support the feasibility of a novel evolutionary genomics-guided approach for antibiotic drug development against obligate pathogens.
Institute
CZ Biohub
Last NameDeFelice
First NameBrian
Address1291 Welch Rd., Rm. G0821 (SIM1), Stanford CA, California, 94305, USA
Emailbcdefelice@ucdavis.edu
Phone5303564485
Submit Date2023-06-23
Raw Data AvailableYes
Raw Data File Type(s)mzML, raw(Thermo)
Analysis Type DetailLC-MS
Release Date2023-07-07
Release Version1
Brian DeFelice Brian DeFelice
https://dx.doi.org/10.21228/M8P43M
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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Sample Preparation:

Sampleprep ID:SP002860
Sampleprep Summary:A549 cells were seeded into 10 x 6-well tissue culture treated plates the day before infection. On the day of infection, cells were either infected with an MOI of 0.05 in 1 mL of DMEM (5 replicates) or mock-infected with DMEM only (5 replicates). Plates were centrifuged at 300 × g for 5 minutes and placed in a 33°C in 5% CO2 for 4 days. After 4 days, cells from each well of a 6-well plate were washed with 2 mL of 1x PBS, scraped, and collected into an 1.5 mL centrifuge tube. Samples were washed twice with 500 µl of 1x PBS before resuspending in 225 µl ice-cold methanol with 1.5% iSTD-SPLASH and freezing on dry ice. Samples were processed within 48 h. Sample preparation and analysis have been detailed previously (DOI: dx.doi.org/10.17504/protocols.io.e6nvwj86dlmk/v1 (Private link for reviewers: https://www.protocols.io/private/8962C900975C11ED8E800A58A9FEAC02 to be removed before publication.) Analysis of metabolomics data was performed on MetaboAnalyst 5.0 and GraphPad Prism (Version 9.5.1 (528); Chong et al., 2018).
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