Summary of Study ST001382

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 PR000946. The data can be accessed directly via it's Project DOI: 10.21228/M8DM63 This work is supported by NIH grant, U2C- DK119886.

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Study IDST001382
Study TitleDistinct metabolic states of a cell guide alternate fates of mutational buffering through altered proteostasis
Study SummaryChanges in metabolism can alter the cellular milieu; can this also change intracellular proteostasis? Since proteostasis can modulate mutational buffering, if change in metabolism has the ability to change proteostasis, arguably, it should also alter mutational buffering. Building on this, we find that altered cellular metabolic states in E. coli buffer distinct mutations. Buffered-mutants had folding problems in vivo and were differently chaperoned in different metabolic states. Notably, this assistance was dependent upon the metabolites and not on the increase in canonical chaperone machineries. Additionally, we were able to reconstitute the folding assistance afforded by metabolites in vitro and propose that changes in metabolite concentrations have the potential to alter proteostasis. Collectively, we unravel that the metabolite pools are bona fide members of proteostasis and aid in mutational buffering. Given the plasticity in cellular metabolism, we posit that metabolic alterations may play an important role in the positive or negative regulation of proteostasis.
Institute
CSIR-National Chemical Laboratory
Last NameShanmugam
First NameDhanasekaran
AddressDr. Homi Bhabha Road, Pune, maharashtra, 411008, India
Emaild.shanmugam@ncl.res.in
Phone2025902719
Submit Date2020-05-14
Raw Data AvailableYes
Raw Data File Type(s)mzXML
Analysis Type DetailLC-MS
Release Date2020-06-01
Release Version1
Dhanasekaran Shanmugam Dhanasekaran Shanmugam
https://dx.doi.org/10.21228/M8DM63
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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Project:

Project ID:PR000946
Project DOI:doi: 10.21228/M8DM63
Project Title:Distinct metabolic states of a cell guide alternate fates of mutational buffering through altered proteostasis.
Project Summary:Changes in metabolism can alter the cellular milieu; can this also change intracellular proteostasis? Since proteostasis can modulate mutational buffering, if change in metabolism has the ability to change proteostasis, arguably, it should also alter mutational buffering. Building on this, we find that altered cellular metabolic states in E. coli buffer distinct mutations. Buffered-mutants had folding problems in vivo and were differently chaperoned in different metabolic states. Notably, this assistance was dependent upon the metabolites and not on the increase in canonical chaperone machineries. Additionally, we were able to reconstitute the folding assistance afforded by metabolites in vitro and propose that changes in metabolite concentrations have the potential to alter proteostasis. Collectively, we unravel that the metabolite pools are bona fide members of proteostasis and aid in mutational buffering. Given the plasticity in cellular metabolism, we posit that metabolic alterations may play an important role in the positive or negative regulation of proteostasis.
Institute:CSIR-National Chemical Laboratory
Department:Biochemical Sciences Division
Last Name:Shanmugam
First Name:Dhanasekaran
Address:Dr. Homi Bhabha Road, Pune, maharashtra, 411008, India
Email:d.shanmugam@ncl.res.in
Phone:2025902719

Subject:

Subject ID:SU001456
Subject Type:Bacteria
Subject Species:Escherichia coli
Taxonomy ID:562

Factors:

Subject type: Bacteria; Subject species: Escherichia coli (Factor headings shown in green)

mb_sample_id local_sample_id Grown in presence of NaCl (mM)
SA100956WG350-5-
SA100957WG350-1-
SA100958WG350-3-
SA100959WG350-4-
SA100960WG350-2-
SA100961CSH4-5-
SA100962CSH4-4-
SA100963CSH4-2-
SA100964CSH4-1-
SA100965CSH4-3-
SA100966WG350_Salt-5350
SA100967WG350_Salt-1350
SA100968WG350_Salt-4350
SA100969WG350_Salt-3350
SA100970WG350_Salt-2350
SA100971CSH4_Salt-4350
SA100972CSH4_Salt-1350
SA100973CSH4_Salt-5350
SA100974CSH4_Salt-2350
SA100975CSH4_Salt-3350
SA100976Blank-2N/A
SA100977Blank-1N/A
SA100978Blank-3N/A
Showing results 1 to 23 of 23

Collection:

Collection ID:CO001451
Collection Summary:3ml of LB was inoculated with 0.1% inoculum from overnight grown culture and grown till OD600~0.8 at 37°C, 200 rpm. Cells equivalent to 0.1 OD were harvested at 14000 rpm, 1 min, 4°C.
Sample Type:Bacterial cells

Treatment:

Treatment ID:TR001471
Treatment Summary:CSH4 and WG350 strains were transformed with the mutant GFP clones and subjected to osmotic stress with 350mM NaCl. The pool of mutants buffered under osmotic stress in WG350 was sorted and single clones of GFP were picked from here and checked for their fluorescence in presence and absence of osmotic stress.

Sample Preparation:

Sampleprep ID:SP001464
Sampleprep Summary:Cell pellets were extracted with 200ul of chilled extraction solvent (80% MetOH in MS grade water containing 1ng/µl PIPES and U13C-U15N-glutamine as internal standard) was added to the pellet, mixed and incubated in ice for 5 minutes for quenching metabolism. This is followed by sonication in water bath for 15 min at 4°C with intermittent vortexing. Metabolites were collected in the supernatant by centrifugation at 14000 rpm for 5 min at 4°C. Previous step was repeated twice by adding 100µl 80% chilled solvent each time to increase metabolite yield and polled extracts were stored in -80°C refrigerator till further analysis.

Combined analysis:

Analysis ID AN002303
Analysis type MS
Chromatography type Reversed phase
Chromatography system Thermo Accela 1250
Column Thermo Accucore C18 (100 x 2.1mm,2.6um)
MS Type ESI
MS instrument type Orbitrap
MS instrument name Thermo Q Exactive Orbitrap
Ion Mode NEGATIVE
Units Peak Intensity

Chromatography:

Chromatography ID:CH001692
Chromatography Summary:The acetonitrile:water extracts from parasites were dried under nitrogen flow and resuspended in 200 µls of water:methanol (97:3) containing 10 mM tributylamine and 15 mM acetic acid. A Thermo Accucore C18 column with a bed volume of 150 mm x 2.1 mm and 2.6 µ particle size was used. A solvent system composed of water buffered with 0.1 % formic acid (buffer A) and acetonitrile (buffer B), was used on a 20 minute gradient run with a flow rate of 200 µl/min as follows- hold at 10% acetonitrile for 30 seconds and gradually ramp up to 15%, 20%, 50%, 60% and 90% acetonitrile by 3, 6, 10, 12, 13 minutes, hold at 90% acetonitrile till 15 minutes, ramp down to 10% acetonitrile by 15.5 minutes and hold till 20 minutes.
Instrument Name:Thermo Accela 1250
Column Name:Thermo Accucore C18 (100 x 2.1mm,2.6um)
Flow Gradient:hold at 10% acetonitrile for 30 seconds and gradually ramp up to 15%, 20%, 50%, 60% and 90% acetonitrile by 3, 6, 10, 12, 13 minutes, hold at 90% acetonitrile till 15 minutes, ramp down to 10% acetonitrile by 15.5 minutes and hold till 20 minutes.
Flow Rate:200 µl/min
Solvent A:100% water; 0.1 % formic acid
Solvent B:100% acetonitrile
Chromatography Type:Reversed phase

MS:

MS ID:MS002146
Analysis ID:AN002303
Instrument Name:Thermo Q Exactive Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:LC-MS analysis was done using a Exactive Orbitrap mass spectrometer, coupled to an Accela U-HPLC and HTC PAL autosampler. The mass spectrometer was run in negative mode, scanning a mass-charge ratio (m/z) range of 85-1000. The RAW file output from the mass spectrometer was converted from the profile mode into centroid mode using the ReAdW or Proteowizard program and further analyzed using the ElMAVEN program. Data from replicate samples for each time point was aligned within MAVEN and ion chromatograms were extracted for each compound to within a 10 PPM window of the expected m/z value. Peaks were detected from these ion chromatograms and their quality was ascertained using default settings available in MAVEN. Metabolites were identified by matching the retention times as well as the m/z values to >99% pure commercial standards for which in-house calibration was done. Grouped peaks from replicate samples for all time points were matched to the expected retention time of standards, and the peaks with a quality score of at least 0.5 were hand picked for metabolites of interest. Signals obtained from blank runs were used for noise correction and only peaks with a signal intensity of at least 1000 counts were considered.
Ion Mode:NEGATIVE
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