Summary of Study ST003527

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 PR002170. The data can be accessed directly via it's Project DOI: 10.21228/M84C19 This work is supported by NIH grant, U2C- DK119886.

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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 IDST003527
Study TitleCombining antibiotics alters the longitudinal maturation of gut microbiota and its short chain fatty acid metabolites in extremely and very preterm infants
Study SummaryAntibiotics are routinely prescribed to extremely and very premature infants as a pre-emptive and prophylactic treatment to reduce the risk of acute neonatal illness (i.e. necrotizing enterocolitis, NEC) associated with morbidity. To investigate the effects of antibiotic types, combinations, and duration on the preterm gut microbiome and metabolome, we analyzed the microbiome compositions of 123 stool samples collected at 3 timepoints (postnatal day 1, 28 and 56) from extremely- and very-low-birthweight infants treated with 14 different antibiotics spanning across 5 classes. Targeted metabolomics were performed on 47 samples available, allowing us to quantify 649 metabolites including amino acids, bile acids, fatty acids, and lipids. As a result, we found that antibiotics exerted the most profound disruptive impact on the gut microbiota, while antibiotics and breastfeeding highly influence the gut metabolome. Short chain fatty acids were reduced in both antibiotic-treated and NEC group. Finally, we revealed that cephalosporins negatively impact conjugated bile acids due to a positive correlation with bile salt hydrolase-producing Staphylococcus.
Institute
Seoul National University
Last NameKyeong-Seog
First NameKim
AddressJongno-Gu, South Korea
Email92kkim@gmail.com
Phone+8227408905
Submit Date2024-09-23
Raw Data AvailableYes
Raw Data File Type(s)d, wiff
Analysis Type DetailGC-MS/LC-MS
Release Date2024-10-22
Release Version1
Kim Kyeong-Seog Kim Kyeong-Seog
https://dx.doi.org/10.21228/M84C19
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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Combined analysis:

Analysis ID AN005792 AN005793 AN005794
Analysis type MS MS MS
Chromatography type GC Reversed phase None (Direct infusion)
Chromatography system Agilent 7890B Waters Acquity Waters Acquity
Column Agilent DB-FFAP (30m × 0.25mm, 0.25um) Biocrates MxP Quant 500 (XL) PN 21117 NA (FIA mode)
MS Type EI ESI ESI
MS instrument type Triple quadrupole Triple quadrupole Triple quadrupole
MS instrument name Agilent 7000B ABI Sciex Triple Quad 5500+ ABI Sciex Triple Quad 5500+
Ion Mode POSITIVE UNSPECIFIED UNSPECIFIED
Units uM uM uM

MS:

MS ID:MS005512
Analysis ID:AN005792
Instrument Name:Agilent 7000B
Instrument Type:Triple quadrupole
MS Type:EI
MS Comments:Selected Ion Monitoring (SIM) was applied to measure the short-chain fatty acid levels. The m/z values at 60 (acetic acid, butyric acid, valeric acid, and isovaleric acid), 63 (acetic acid-d4 which used as internal standard), 73 (isobutyric acid), and 74 (propionic acid) was applied.
Ion Mode:POSITIVE
  
MS ID:MS005513
Analysis ID:AN005793
Instrument Name:ABI Sciex Triple Quad 5500+
Instrument Type:Triple quadrupole
MS Type:ESI
MS Comments:Samples were analyzed with four methods employing LC separation or flow injection analysis (FIA). LC1 used ionization in positive mode and scheduled MRM detection (125 transitions). LC2 used ionization in negative mode and scheduled MRM detection (69 transitions). Both FIA methods used ionization in positive mode and MRM detection (165 and 382 transitions). Data were analyzed employing the Biocrates MetIDQ software.
Ion Mode:UNSPECIFIED
  
MS ID:MS005514
Analysis ID:AN005794
Instrument Name:ABI Sciex Triple Quad 5500+
Instrument Type:Triple quadrupole
MS Type:ESI
MS Comments:Samples were analyzed with four methods employing LC separation or flow injection analysis (FIA). LC1 used ionization in positive mode and scheduled MRM detection (125 transitions). LC2 used ionization in negative mode and scheduled MRM detection (69 transitions). Both FIA methods used ionization in positive mode and MRM detection (165 and 382 transitions). Data were analyzed employing the Biocrates MetIDQ software.
Ion Mode:UNSPECIFIED
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