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.
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.
Study ID | ST003527 |
Study Title | Combining antibiotics alters the longitudinal maturation of gut microbiota and its short chain fatty acid metabolites in extremely and very preterm infants |
Study Summary | Antibiotics 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 Name | Kyeong-Seog |
First Name | Kim |
Address | Jongno-Gu, South Korea |
92kkim@gmail.com | |
Phone | +8227408905 |
Submit Date | 2024-09-23 |
Raw Data Available | Yes |
Raw Data File Type(s) | d, wiff |
Analysis Type Detail | GC/LC-MS |
Release Date | 2024-10-22 |
Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Project:
Project ID: | PR002170 |
Project DOI: | doi: 10.21228/M84C19 |
Project Title: | Combining antibiotics alters the longitudinal maturation of gut microbiota and its short chain fatty acid metabolites in extremely and very preterm infants |
Project Type: | Targeted metabolomics |
Project Summary: | Antibiotics 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 Name: | Kyeong-Seog |
First Name: | Kim |
Address: | Jongno-Gu, South Korea |
Email: | 92kkim@gmail.com |
Phone: | +8227408905 |
Subject:
Subject ID: | SU003656 |
Subject Type: | Human |
Subject Species: | Homo sapiens |
Taxonomy ID: | 9606 |
Species Group: | Mammals |
Factors:
Subject type: Human; Subject species: Homo sapiens (Factor headings shown in green)
mb_sample_id | local_sample_id | Sample source | Group | Antibiotics |
---|---|---|---|---|
SA387219 | NEC03_D1 | Feces | 1day | No |
SA387220 | PRE02_D1 | Feces | 1day | No |
SA387221 | PRE03_D1 | Feces | 1day | No |
SA387222 | PRE31_D1 | Feces | 1day | No |
SA387223 | PRE26_D1 | Feces | 1day | No |
SA387224 | PRE44_D1 | Feces | 1day | Yes |
SA387225 | PRE39_D1 | Feces | 1day | Yes |
SA387226 | PRE38_D1 | Feces | 1day | Yes |
SA387227 | PRE32_D1 | Feces | 1day | Yes |
SA387228 | PRE21_D1 | Feces | 1day | Yes |
SA387229 | PRE24_D1 | Feces | 1day | Yes |
SA387230 | PRE27_D1 | Feces | 1day | Yes |
SA387231 | NEC04_D1 | Feces | 1day | Yes |
SA387232 | NEC01_D1 | Feces | 1day | Yes |
SA387233 | PRE13_D1 | Feces | 1day | Yes |
SA387234 | PRE29_D1 | Feces | 1day | Yes |
SA387235 | PRE09_D1 | Feces | 1day | Yes |
SA387236 | PRE10_D1 | Feces | 1day | Yes |
SA387237 | PRE29_D28 | Feces | 28day | No |
SA387238 | PRE39_D28 | Feces | 28day | No |
SA387239 | PRE24_D28 | Feces | 28day | No |
SA387240 | PRE30_D28 | Feces | 28day | No |
SA387241 | PRE03_D28 | Feces | 28day | No |
SA387242 | PRE02_D28 | Feces | 28day | No |
SA387243 | PRE44_D28 | Feces | 28day | Yes |
SA387244 | PRE38_D28 | Feces | 28day | Yes |
SA387245 | NEC03_D28 | Feces | 28day | Yes |
SA387246 | PRE32_D28 | Feces | 28day | Yes |
SA387247 | PRE09_D28 | Feces | 28day | Yes |
SA387248 | PRE05_D28 | Feces | 28day | Yes |
SA387249 | PRE26_D28 | Feces | 28day | Yes |
SA387250 | NEC01_D28 | Feces | 28day | Yes |
SA387251 | NEC05_D28 | Feces | 28day | Yes |
SA387252 | PRE21_D28 | Feces | 28day | Yes |
SA387253 | NEC06_D28 | Feces | 28day | Yes |
SA387254 | PRE27_D28 | Feces | 28day | Yes |
SA387255 | PRE13_D56 | Feces | 56day | No |
SA387256 | PRE38_D56 | Feces | 56day | No |
SA387257 | PRE05_D56 | Feces | 56day | Yes |
SA387258 | PRE27_D56 | Feces | 56day | Yes |
SA387259 | NEC03_D56 | Feces | 56day | Yes |
SA387260 | PRE31_D56 | Feces | 56day | Yes |
SA387261 | PRE32_D56 | Feces | 56day | Yes |
SA387262 | NEC05_D56 | Feces | 56day | Yes |
SA387263 | PRE39_D56 | Feces | 56day | Yes |
SA387264 | PRE44_D56 | Feces | 56day | Yes |
SA387265 | PRE26_D56 | Feces | 56day | Yes |
Showing results 1 to 47 of 47 |
Collection:
Collection ID: | CO003649 |
Collection Summary: | All samples were obtained from infants who were born and admitted to the NICU at Samsung Medical Center in Seoul, after taking informed consent from parents. The institutional review board of Samsung Medical Center approved the collection of samples and clinical data (approval number 2021-02-038). The study was conducted in accordance with the principles outlined in the Declaration of Helsinki. A total of 47 stool samples from the patient cohort were collected on days 1, 28, and 56 after birth with a minimum of one sample per subject (Day in Study Design). |
Sample Type: | Feces |
Collection Method: | Using a sterile plastic spoon and adhering to aseptic protocols, approximately 1g of feces were collected |
Collection Location: | NICU at Samsung Medical Center in Seoul |
Collection Frequency: | NA |
Collection Duration: | approx. 3 years |
Volumeoramount Collected: | approx. 1g |
Storage Conditions: | -80℃ |
Collection Vials: | 2.0 mL cryovial |
Storage Vials: | 2.0 mL cryovial |
Collection Tube Temp: | -80C |
Additives: | NA |
Treatment:
Treatment ID: | TR003665 |
Treatment Summary: | 14 types of antibiotics were used for each preterm infant with the specific antibiotics varying based on the individual, namely gentamicin, cefazolin, vancomycin, meropenem, tazoferan, fluconazole, amphotericin, ampicillin, nafcillin, cefotaxime, teicoplanin, clarithromycin, cefepime, and amikacin. Of the 54 subjects, 38 received antibiotics treatment more than once (Antibiotics = Yes in Study Design). |
Sample Preparation:
Sampleprep ID: | SP003663 |
Sampleprep Summary: | For metabolome extraction from stool samples, 2-propanol was added at the 1 mg: 3 µL ratio. The mixture was vortexed vigorously until the stools are entirely homogenized, and then centrifuged to remove stool debris for 5 min at 18,341 × g and 4°C. Finally, the supernatant was collected for further analysis including targeted metabolomics using the MxP Quant 500 kit provided by Biocrates (Biocrates Life Science AG, Innsbruck, Austria), and for the analysis of SCFAs as described previously [10.3390/metabo12060525]. Briefly, for MxP Quant 500 kit assay, 10 µL of stool extract was used and the stool metabolome was derivatized with phenylisothiocyanate per manufacturer’s instruction. For the extraction of SCFAs, 10 µL of 10 µg/mL of acetic acid-d4, which was used for internal standard (IS) was added to the 30 µL of stool extract. Then, 0.1 mL of deionized water and 10 µL of 1.0 M hydrochloric acid was added to the sample, and further extracted SCFAs by adding 0.2 mL of methyl-tert butyl ether (MTBE). The MTBE phase was collected after vortex and centrifugation for gas chromatography–mass spectrometry (GC–MS) analysis. |
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 |
Chromatography:
Chromatography ID: | CH004397 |
Chromatography Summary: | Selected Ion Monitoring (SIM) was applied to measure the short-chain fatty acid in feces. The m/z values at 60 (acetic acid, butyric acid, and isovaleric acid), 73 (isobutyric acid), and 74 (propionic acid) was applied. |
Instrument Name: | Agilent 7890B |
Column Name: | Agilent DB-FFAP (30m × 0.25mm, 0.25um) |
Column Temperature: | an initial GC oven temperature was 40°C, held for 2 min, increased by 40°C/min to 200°C. The post-run time was 6 min at 240°C |
Flow Gradient: | NA |
Flow Rate: | NA |
Solvent A: | NA |
Solvent B: | NA |
Chromatography Type: | GC |
Chromatography ID: | CH004398 |
Instrument Name: | Waters Acquity |
Column Name: | Biocrates MxP Quant 500 (XL) PN 21117 |
Column Temperature: | 50 |
Flow Gradient: | Flow Gradient LC1: 0% B (0.25 min) -> 12% B (1.25 min) -> 17.5% B (1.2 min) -> 50% B (1.3 min) -> 100% B (0.5 min) -> stay at 100% B (0.5 min) -> 0% B (0.1 min) -> held at 0% B (0.7 min), total 5.8 min; Flow Gradient LC2: 0% B (0.25 min) -> 25% B (0.25 min) -> 50% B (1.5 min) -> 75% B (1.0 min) -> 100% B (0.5 min) -> stay at 100% B (1.5 min) -> 0% B (0.1 min) -> held at 0% B (0.7 min), total 5.8 min |
Flow Rate: | 0.8 mL/min, increased to 1.0 mL/min from minute 4.7 to 5.1 |
Solvent A: | 100% water; 0.2% formic acid |
Solvent B: | 95% acetonitrile/5% water; 0.2% formic acid |
Chromatography Type: | Reversed phase |
Chromatography ID: | CH004399 |
Instrument Name: | Waters Acquity |
Column Name: | NA (FIA mode) |
Column Temperature: | NA |
Flow Gradient: | 100% B, 0-3min |
Flow Rate: | 0.03mL/min (0-1.6min), 0.2mL/min (1.6-2.8min), Back to 0.03mL/min (2.8-3.0min) |
Solvent A: | 100% water; 0.2% formic acid |
Solvent B: | 95% acetonitrile/5% water; 0.2% formic acid |
Chromatography Type: | None (Direct infusion) |
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 |