Summary of Study ST002535

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 PR001631. The data can be accessed directly via it's Project DOI: 10.21228/M8W43G 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 IDST002535
Study TitleRelationships between the gut microbiome and cognitive impairment in residents of long-term aged care.
Study SummaryAgeing-associated cognitive decline affects more than half of those in long-term residential aged care. Emerging evidence suggests that gut microbiome-host interactions influence the effects of modifiable risk factors. We investigated the relationship between gut microbiome characteristics and severity of cognitive impairment (CI) in 159 residents of long-term aged care. Severe CI was associated with a significantly increased abundance of proinflammatory bacterial species, including Methanobrevibacter smithii and Alistipes finegoldii, and decreased relative abundance of beneficial bacterial clades. Severe CI was associated with increased microbial capacity for methanogenesis, and reduced capacity for synthesis of short-chain fatty acids, neurotransmitters glutamate and gamma-aminobutyric acid, and amino acids required for neuro-protective lysosomal activity. These relationships were independent of age, sex, antibiotic exposure, and diet. Our findings implicate multiple gut microbiome-brain pathways in ageing-associated cognitive decline, including inflammation, neurotransmission, and autophagy, and highlight the potential to predict and prevent cognitive decline through microbiome-targeted strategies.
Institute
South Australian Health and Medical Research Institute
Last NameShoubridge
First NameAndrew
AddressNorth Terrace, Adelaide, South Australia, 5000, Australia
Emailandrew.shoubridge@sahmri.com
Phone+61405041977
Submit Date2023-03-26
Raw Data AvailableYes
Raw Data File Type(s)mzML
Analysis Type DetailLC-MS
Release Date2023-04-04
Release Version1
Andrew Shoubridge Andrew Shoubridge
https://dx.doi.org/10.21228/M8W43G
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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Project:

Project ID:PR001631
Project DOI:doi: 10.21228/M8W43G
Project Title:Metabolomic Profiling of Human Faecal Samples
Project Summary:Targeted analysis of SCFAs and polar metabolites in samples from human faeces.
Institute:South Australian Health and Medical Research Institute
Department:Lifelong Health
Laboratory:Microbiome and Host Health Programme
Last Name:Shoubridge
First Name:Andrew
Address:North Terrace, Adelaide, South Australia, 5000, Australia
Email:andrew.shoubridge@sahmri.com
Phone:+61405041977

Subject:

Subject ID:SU002635
Subject Type:Human
Subject Species:Homo sapiens
Taxonomy ID:9606
Gender:Male and female

Factors:

Subject type: Human; Subject species: Homo sapiens (Factor headings shown in green)

mb_sample_id local_sample_id CI_group
SA254947PBQC_001-
SA254948PBQC_007-
SA254949PBQC_008-
SA254950PBQC_005-
SA254951PBQC_003-
SA254952AS_36-
SA254953PBQC_002-
SA254954PBQC_009-
SA254955PBQC_004-
SA254956PBQC_006-
SA254957R_Blank_01-
SA254958R_Blank_02-
SA254959AS_052
SA254960AS_282
SA254961AS_332
SA254962AS_342
SA254963AS_032
SA254964AS_352
SA254965AS_262
SA254966AS_062
SA254967AS_202
SA254968AS_082
SA254969AS_132
SA254970AS_212
SA254971AS_323
SA254972AS_173
SA254973AS_163
SA254974AS_313
SA254975AS_193
SA254976AS_123
SA254977AS_233
SA254978AS_103
SA254979AS_273
SA254980AS_223
SA254981AS_043
SA254982AS_244
SA254983AS_114
SA254984AS_094
SA254985AS_074
SA254986AS_024
SA254987AS_144
SA254988AS_154
SA254989AS_294
SA254990AS_254
SA254991AS_014
SA254992AS_184
SA254993AS_304
Showing results 1 to 47 of 47

Collection:

Collection ID:CO002628
Collection Summary:Stool was collected and stored using Norgen Stool Nucleic Acid Collection and Preservation Tubes (Norgen Biotek, ON, Canada).
Sample Type:Feces
Storage Conditions:-80℃

Treatment:

Treatment ID:TR002647
Treatment Summary:Stool samples containing buffer were vortexed vigorously and 1 ml was transferred to a clean 2 ml tube. Samples were centrifuged for 20 min at 13,000 xg at 4°C and the supernatant was transferred to a clean 2 ml screw-cap tube for storage.

Sample Preparation:

Sampleprep ID:SP002641
Sampleprep Summary:SCFA analysis was performed using an Agilent 6490 series triple quadrupole mass spectrometer (Agilent Technologies) with chromatographic separation on an Agilent 1200 series high-performance liquid chromatography system (HPLC) (Agilent Technologies). SCFAs were extracted by adding 360μL of 50% acetonitrile with 10μM 4-methylvaleric acid internal standard to 40μL of biological sample supernatant. Samples were then vortexed for 30 seconds, incubated at 10oC for 30 minutes at 950RPM, centrifuged at 14,000RPM for five minutes at 4oC, followed by supernatant collection. Derivatisation for SCFA analysis was performed by first adding 20μL of 20μM 13C6-nitrophenylhydrazine as internal standard to 40μL of the extracted supernatant, followed by 20μL each of 200mM nitrophenylhydrazine and 120mM 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide (EDC), incubated at 40oC for 30 minutes at 950RPM, quenched with 20μL of 200mM quinic acid, and incubated at 40oC for a further 30 minutes at 950RPM. Lastly, the samples were reconstituted with 1.9mL of 15% acetonitrile and 1μL was injected onto the column. Pooled biological quality controls (PBQCs) were created by pooling extracts (20μL) from individual biological samples and injected onto the column in five sample intervals. A reagent and procedural blank of the original sample preservation buffer was included for analysis to perform background correction. Polar metabolite analysis was performed using an Agilent 6545 series quadrupole time-of-flight mass spectrometer (Agilent Technologies) with chromatographic separation on an Agilent 1200 series HPLC system (Agilent Technologies). Metabolite extraction was performed by first adding a solvent mixture of acetonitrile, methanol and water to 20μL of biological sample, followed by vortexing, sonication and agitation. Samples were then centrifuged and supernatant collected and mixed with an internal standard mixture containing 13C5, 15N-valine, 13C6-leucine, and 13C6-sorbitol, and 14μL of sample was injected onto the column. Samples were injected in a randomised order and PBQCs were injected onto the column in five sample intervals. Data matrices were imported to the web-based platform MetaboAnalyst (v5.0) for quality control checks by multivariate statistics. SCFA data were normalised to internal standards, and polar metabolite data were log-transformed and median-normalised.

Combined analysis:

Analysis ID AN004170
Analysis type MS
Chromatography type HILIC
Chromatography system Agilent 1200
Column Merck SeQuant ZIC-HILIC (150 x 2.1mm,5um)
MS Type ESI
MS instrument type QTOF
MS instrument name Agilent 6545 QTOF
Ion Mode NEGATIVE
Units ng/ml

Chromatography:

Chromatography ID:CH003088
Instrument Name:Agilent 1200
Column Name:Merck SeQuant ZIC-HILIC (150 x 2.1mm,5um)
Column Temperature:40
Flow Gradient:time = 0 min, 90% B; t = 0.5 min, 90% B; t = 12 min, 40% B; t = 14 min, 40% B; t = 15 min, 5%; t = 18 min, 5% B; and t = 19 min, 90%.
Flow Rate:250 ul/min
Solvent A:100% water; 20 mM ammonium carbonate (pH 9.0)
Solvent B:100% acetonitrile
Chromatography Type:HILIC

MS:

MS ID:MS003917
Analysis ID:AN004170
Instrument Name:Agilent 6545 QTOF
Instrument Type:QTOF
MS Type:ESI
MS Comments:Negative mode LC-MS data were collected in centroid mode with a scan range of 50 to 1700 mass-to-charge ratio (m/z) and an acquisition rate of 1.2 spectra/s. Samples were analyzed in the same analytical batch and randomized with a quality control every five samples. Authentic standards were also run to generate the library for targeted analysis. Level 1 metabolite identification [according to the Metabolite Standard Initiative] was based on matching accurate mass, retention time, and tandem MS (MS/MS) spectra to the 550 authentic standards in the MA in-house library. Metabolite abundance based on area under the curve (AUC) was obtained using Agilent Masshunter Quantitative Analysis B 0.7.00. Statistical analysis was performed applying the web-based platform MetaboAnalyst applying no missing value imputation, normalization to median peak area, and no scaling or transformation. RAW_FILE_NAME=AS_01.mzML to AS_35.mzML refer to metabolite detection of short-chain fatty acids, and RAW_FILE_NAME=AS_001.mzML to AS_035.mzML refer the polar metabolites.
Ion Mode:NEGATIVE
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