#METABOLOMICS WORKBENCH salvarez_20241022_084017 DATATRACK_ID:5302 STUDY_ID:ST003530 ANALYSIS_ID:AN005798 PROJECT_ID:PR002172 VERSION 1 CREATED_ON October 24, 2024, 9:48 am #PROJECT PR:PROJECT_TITLE Microbiome and metabolome association network analysis identifies PR:PROJECT_TITLE Clostridium_sensu_stricto_1 and Paraprevotella as putative keystone genera in PR:PROJECT_TITLE the gut of common marmosets PR:PROJECT_SUMMARY The common marmoset (Callithrix jacchus), a nonhuman primate species, is a model PR:PROJECT_SUMMARY organism that has garnered interest in recent years for its potential PR:PROJECT_SUMMARY translational value in a variety of research settings including the field of PR:PROJECT_SUMMARY microbiomics. While the composition of the marmoset’s gut microbiome has been PR:PROJECT_SUMMARY described in captivity, little is known about how gut microbiota interact with PR:PROJECT_SUMMARY each other over time and how they relate to metabolite productions. To help PR:PROJECT_SUMMARY answer this, we characterized interactions in the gut microbiome of the common PR:PROJECT_SUMMARY marmoset by calculating the Spearman correlation coefficient between 16S PR:PROJECT_SUMMARY rDNA-derived relative genera abundance data and targeted metabolomics data PR:PROJECT_SUMMARY collected longitudinally from 10 marmosets (6 males and 4 females). Association PR:PROJECT_SUMMARY network graphs were used to visualize significant correlations and identify PR:PROJECT_SUMMARY genera and metabolites that exhibit a high degree of associations, marking them PR:PROJECT_SUMMARY as more influential within the microbiome. Clostridium_sensu_stricto_1, among PR:PROJECT_SUMMARY the highest-degree genera for bacterial and metabololomic associations, also had PR:PROJECT_SUMMARY a high relative betweenness centrality and negatively associated with PR:PROJECT_SUMMARY high-degree Paraprevotella, indicating that it potentially plays a gatekeeping PR:PROJECT_SUMMARY role within the bacteria-bacteria interaction and communication network. PR:PROJECT_SUMMARY Corresponding metabolites with more numerous bacterial associations, including PR:PROJECT_SUMMARY bile acids and taurine, are known regulators of bacterial growth that provide a PR:PROJECT_SUMMARY potential mechanism through which Clostridium_sensu_stricto_1 and others exert PR:PROJECT_SUMMARY their influence. To further characterize microbiome interactions, we performed PR:PROJECT_SUMMARY hierarchical clustering on significant within-dataset associations and developed PR:PROJECT_SUMMARY a new “Keystone Candidate Score” metric that identified PR:PROJECT_SUMMARY Clostridium_sensu_stricto_1 and Paraprevotella as the most influential bacteria PR:PROJECT_SUMMARY (so-called candidate keystone genera) in the marmoset gut microbiome. PR:INSTITUTE University of Nebraska-Lincoln PR:LAST_NAME Alvarez PR:FIRST_NAME Sophie PR:ADDRESS 1901 Vine St PR:EMAIL salvarez@unl.edu PR:PHONE 4024724575 #STUDY ST:STUDY_TITLE Microbiome and metabolome association network analysis identifies ST:STUDY_TITLE Clostridium_sensu_stricto_1 and Paraprevotella as putative keystone genera in ST:STUDY_TITLE the gut of common marmosets ST:STUDY_SUMMARY The common marmoset (Callithrix jacchus), a nonhuman primate species, is a model ST:STUDY_SUMMARY organism that has garnered interest in recent years for its potential ST:STUDY_SUMMARY translational value in a variety of research settings including the field of ST:STUDY_SUMMARY microbiomics. While the composition of the marmoset’s gut microbiome has been ST:STUDY_SUMMARY described in captivity, little is known about how gut microbiota interact with ST:STUDY_SUMMARY each other over time and how they relate to metabolite productions. To help ST:STUDY_SUMMARY answer this, we characterized interactions in the gut microbiome of the common ST:STUDY_SUMMARY marmoset by calculating the Spearman correlation coefficient between 16S ST:STUDY_SUMMARY rDNA-derived relative genera abundance data and targeted metabolomics data ST:STUDY_SUMMARY collected longitudinally from 10 marmosets (6 males and 4 females). Association ST:STUDY_SUMMARY network graphs were used to visualize significant correlations and identify ST:STUDY_SUMMARY genera and metabolites that exhibit a high degree of associations, marking them ST:STUDY_SUMMARY as more influential within the microbiome. Clostridium_sensu_stricto_1, among ST:STUDY_SUMMARY the highest-degree genera for bacterial and metabololomic associations, also had ST:STUDY_SUMMARY a high relative betweenness centrality and negatively associated with ST:STUDY_SUMMARY high-degree Paraprevotella, indicating that it potentially plays a gatekeeping ST:STUDY_SUMMARY role within the bacteria-bacteria interaction and communication network. ST:STUDY_SUMMARY Corresponding metabolites with more numerous bacterial associations, including ST:STUDY_SUMMARY bile acids and taurine, are known regulators of bacterial growth that provide a ST:STUDY_SUMMARY potential mechanism through which Clostridium_sensu_stricto_1 and others exert ST:STUDY_SUMMARY their influence. To further characterize microbiome interactions, we performed ST:STUDY_SUMMARY hierarchical clustering on significant within-dataset associations and developed ST:STUDY_SUMMARY a new “Keystone Candidate Score” metric that identified ST:STUDY_SUMMARY Clostridium_sensu_stricto_1 and Paraprevotella as the most influential bacteria ST:STUDY_SUMMARY (so-called candidate keystone genera) in the marmoset gut microbiome. ST:INSTITUTE University of Nebraska-Lincoln ST:LAST_NAME Alvarez ST:FIRST_NAME Sophie ST:ADDRESS 2020 ryons st ST:EMAIL salvarez@unl.edu ST:PHONE 4024724575 #SUBJECT SU:SUBJECT_TYPE Mammal SU:SUBJECT_SPECIES Callithrix jacchus SU:TAXONOMY_ID 9483 #SUBJECT_SAMPLE_FACTORS: SUBJECT(optional)[tab]SAMPLE[tab]FACTORS(NAME:VALUE pairs separated by |)[tab]Raw file names and additional sample data SUBJECT_SAMPLE_FACTORS Dexter 643 Sample source:feces | Treatment:Pre RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_643.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-643.mzML SUBJECT_SAMPLE_FACTORS Dexter 671 Sample source:feces | Treatment:Stress RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_671.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-671.mzML SUBJECT_SAMPLE_FACTORS Dexter 745 Sample source:feces | Treatment:Post RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_745.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-745.mzML SUBJECT_SAMPLE_FACTORS Dexter 915 Sample source:feces | Treatment:Control RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_915.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-915.mzML SUBJECT_SAMPLE_FACTORS Hamlet 680 Sample source:feces | Treatment:Control RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_680.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-680.mzML SUBJECT_SAMPLE_FACTORS Hamlet 940 Sample source:feces | Treatment:Pre RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_940.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-940.mzML SUBJECT_SAMPLE_FACTORS Hamlet 1028 Sample source:feces | Treatment:Stress RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_1028.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-1028.mzML SUBJECT_SAMPLE_FACTORS Hamlet 1075 Sample source:feces | Treatment:Post RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_1075.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-1075.mzML SUBJECT_SAMPLE_FACTORS Indiana 1124 Sample source:feces | Treatment:Pre RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_1124.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-1124.mzML SUBJECT_SAMPLE_FACTORS Indiana 1161 Sample source:feces | Treatment:Stress RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_1161.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-1161.mzML SUBJECT_SAMPLE_FACTORS Indiana 1192 Sample source:feces | Treatment:Post RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_1192.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-1192.mzML SUBJECT_SAMPLE_FACTORS Indiana 1223 Sample source:feces | Treatment:Control RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_1223.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-1223.mzML SUBJECT_SAMPLE_FACTORS Izla 641 Sample source:feces | Treatment:Pre RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_641.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-641.mzML SUBJECT_SAMPLE_FACTORS Izla 676 Sample source:feces | Treatment:Stress RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_676.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-676.mzML SUBJECT_SAMPLE_FACTORS Izla 711 Sample source:feces | Treatment:Post RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_711.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-711.mzML SUBJECT_SAMPLE_FACTORS Izla 920 Sample source:feces | Treatment:Control RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_920.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-920.mzML SUBJECT_SAMPLE_FACTORS Joans 677 Sample source:feces | Treatment:Pre RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_677.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-677.mzML SUBJECT_SAMPLE_FACTORS Joans 748 Sample source:feces | Treatment:Stress RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_748.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-748.mzML SUBJECT_SAMPLE_FACTORS Joans 794 Sample source:feces | Treatment:Post RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_794.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-794.mzML SUBJECT_SAMPLE_FACTORS Joans 958 Sample source:feces | Treatment:Control RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_958.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-958.mzML SUBJECT_SAMPLE_FACTORS Leia 843 Sample source:feces | Treatment:Control RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_843.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-843.mzML SUBJECT_SAMPLE_FACTORS Leia 1087 Sample source:feces | Treatment:Pre RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_1087.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-1087.mzML SUBJECT_SAMPLE_FACTORS Leia 1160 Sample source:feces | Treatment:Stress RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_1160.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-1160.mzML SUBJECT_SAMPLE_FACTORS Leia 1189 Sample source:feces | Treatment:Post RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_1189.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-1189.mzML SUBJECT_SAMPLE_FACTORS Nikko 751 Sample source:feces | Treatment:Pre RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_751.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-751.mzML SUBJECT_SAMPLE_FACTORS Nikko 829 Sample source:feces | Treatment:Stress RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_829.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-829.mzML SUBJECT_SAMPLE_FACTORS Nikko 877 Sample source:feces | Treatment:Post RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_877.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-877.mzML SUBJECT_SAMPLE_FACTORS Nikko 1024 Sample source:feces | Treatment:Control RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_1024.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-1024.mzML SUBJECT_SAMPLE_FACTORS Quinoa 764 Sample source:feces | Treatment:Pre RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_764.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-764.mzML SUBJECT_SAMPLE_FACTORS Quinoa 816 Sample source:feces | Treatment:Stress RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_816.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-816.mzML SUBJECT_SAMPLE_FACTORS Quinoa 875 Sample source:feces | Treatment:Post RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_875.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-875.mzML SUBJECT_SAMPLE_FACTORS Quinoa 1022 Sample source:feces | Treatment:Control RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_1022.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-1022.mzML SUBJECT_SAMPLE_FACTORS Tank 640 Sample source:feces | Treatment:Pre RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_640.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-640.mzML SUBJECT_SAMPLE_FACTORS Tank 667 Sample source:feces | Treatment:Stress RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_667.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-667.mzML SUBJECT_SAMPLE_FACTORS Tank 716 Sample source:feces | Treatment:Post RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_716.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-716.mzML SUBJECT_SAMPLE_FACTORS Tank 970 Sample source:feces | Treatment:Control RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_970.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-970.mzML SUBJECT_SAMPLE_FACTORS Yoshi 790 Sample source:feces | Treatment:Control RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_790.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-790.mzML SUBJECT_SAMPLE_FACTORS Yoshi 1026 Sample source:feces | Treatment:Pre RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_1026.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-1026.mzML SUBJECT_SAMPLE_FACTORS Yoshi 1097 Sample source:feces | Treatment:Stress RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_1097.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-1097.mzML SUBJECT_SAMPLE_FACTORS Yoshi 1140 Sample source:feces | Treatment:Post RAW_FILE_NAME(Raw file name CDF)=20210623_SIM_SCFA_SH_1140.CDF; RAW_FILE_NAME(Raw file name mzML)=SH_samples_1ul_BA_20210215-1140.mzML #COLLECTION CO:COLLECTION_SUMMARY Fecal samples were collected from captive marmosets approximately 2 days before CO:COLLECTION_SUMMARY the isolation challenge (Pre-Stress or Pre), 2 days into the challenge (Stress), CO:COLLECTION_SUMMARY 2 days after the end of the challenge (Post-Stress or Post), and 1 month CO:COLLECTION_SUMMARY afterward (Control). A total of 40 fecal samples collected (4 time CO:COLLECTION_SUMMARY points/marmoset × 10 marmosets) were used for metabolomics analysis. Collected CO:COLLECTION_SUMMARY fecal samples were aliquoted and frozen before being stored at -80°C. CO:SAMPLE_TYPE Feces #TREATMENT TR:TREATMENT_SUMMARY The antibiotic regimen (vancomycin = 30 mg/kg, enrofloxacin = 10 mg/kg and TR:TREATMENT_SUMMARY neomycin = 20 mg/kg) was administered orally using marshmallows and marshmallow TR:TREATMENT_SUMMARY fluff once daily for 28 days. Fecal samples were collected from captive TR:TREATMENT_SUMMARY marmosets approximately 2 days before the isolation challenge (Pre-Stress or TR:TREATMENT_SUMMARY Pre), 2 days into the challenge (Stress), 2 days after the end of the challenge TR:TREATMENT_SUMMARY (Post-Stress or Post), and 1 month afterward (Control). #SAMPLEPREP SP:SAMPLEPREP_SUMMARY For SCFAs, an aliquot of 50 mg of fecal sample was extracted using 0.5% SP:SAMPLEPREP_SUMMARY phosphoric acid spiked with 83.7 µg of D3-acetate as the internal standard. The SP:SAMPLEPREP_SUMMARY samples were disrupted and homogenized by adding 2 stainless steel beads (SSB SP:SAMPLEPREP_SUMMARY 32) using the TissueLyserII at 20 Hz for 2 min. The samples were additionally SP:SAMPLEPREP_SUMMARY sonicated for 5 min. After centrifugation at 16,000 g for 10 min, the SP:SAMPLEPREP_SUMMARY supernatants were transferred to a new tube. Butanol was added to the SP:SAMPLEPREP_SUMMARY supernatant, and samples were extracted one more time using the TissueLyserII at SP:SAMPLEPREP_SUMMARY 2 Hz for 2 min. The samples were centrifuged at 16,000 g for 10 min and the SP:SAMPLEPREP_SUMMARY upper phase was transferred to a new tube. For Bile Acids, an aliquot of 50 mg SP:SAMPLEPREP_SUMMARY of fecal samples was extracted by adding 2 stainless steel beads (SSB 32) and SP:SAMPLEPREP_SUMMARY chilled methanol:acetonitrile (1:1) solution using the TissueLyserII at 20 Hz SP:SAMPLEPREP_SUMMARY for 3 min. The internal standard used is a mixture of several isotope labelled SP:SAMPLEPREP_SUMMARY bile acids (D4-taurochenodeoxycholic acid; D4-taurocholic acid; D4-glycocholic SP:SAMPLEPREP_SUMMARY acid; D4-glycochenodeoxycholic acid; D4-chenodeoxycholic acid; D4-deoxycholic SP:SAMPLEPREP_SUMMARY acid). Samples were centrifuged at 4°C at 16,000 g for 10 min, and supernatants SP:SAMPLEPREP_SUMMARY were transferred to new tubes. Samples were extracted the same way a second time SP:SAMPLEPREP_SUMMARY with supernatants combined to the first one and then dried down using a SAVANT SP:SAMPLEPREP_SUMMARY speed-vac. Pellets were resuspended using 30% methanol and transferred to HPLC SP:SAMPLEPREP_SUMMARY vials. #CHROMATOGRAPHY CH:CHROMATOGRAPHY_SUMMARY for SCFAs CH:CHROMATOGRAPHY_TYPE GC CH:INSTRUMENT_NAME Agilent 7890B CH:COLUMN_NAME Agilent VF-WAXms (30m x 0.25mm, 0.25um) CH:SOLVENT_A none CH:SOLVENT_B none CH:FLOW_GRADIENT none CH:FLOW_RATE 1.2 mL/min CH:COLUMN_TEMPERATURE 70 #ANALYSIS AN:ANALYSIS_TYPE MS #MS MS:INSTRUMENT_NAME Agilent 5977A MS:INSTRUMENT_TYPE Single quadrupole MS:MS_TYPE EI MS:ION_MODE POSITIVE MS:MS_COMMENTS The acquisition was set up as a SIM (Single Ion Monitoring) scan method using MS:MS_COMMENTS selected ions to analyze the detectable SCFAs (D3-acetate, 46-63 ions; acetate, MS:MS_COMMENTS 43-60 ions; propionate, 45-74 ions; butyric acid, 60-73 ions; isovaleric acid, MS:MS_COMMENTS 60-74 ions; valeric acid, 60-73 ions). The data was acquired at a scan speed of MS:MS_COMMENTS 3.125 u/s with a dwell time of 30 ms for each ion selected. The generated data MS:MS_COMMENTS was analyzed with Agilent Mass Hunter Quantitative Analysis. For quantification, MS:MS_COMMENTS an external standard curve was prepared using a series of standard samples MS:MS_COMMENTS containing different concentrations of SCFAs and fixed concentration of the MS:MS_COMMENTS internal standard. #MS_METABOLITE_DATA MS_METABOLITE_DATA:UNITS concentration in mg/g wet feces MS_METABOLITE_DATA_START Samples 640 641 643 677 671 676 677 680 711 716 745 748 751 764 790 794 816 829 843 875 877 915 920 940 958 970 1022 1024 1026 1028 1075 1087 1097 1124 1140 1160 1161 1189 1192 1223 Factors Sample source:feces | Treatment:Pre Sample source:feces | Treatment:Pre Sample source:feces | Treatment:Pre Sample source:feces | Treatment:Pre Sample source:feces | Treatment:Stress Sample source:feces | Treatment:Stress Sample source:feces | Treatment:Pre Sample source:feces | Treatment:Control Sample source:feces | Treatment:Post Sample source:feces | Treatment:Post Sample source:feces | Treatment:Post Sample source:feces | Treatment:Stress Sample source:feces | Treatment:Pre Sample source:feces | Treatment:Pre Sample source:feces | Treatment:Control Sample source:feces | Treatment:Post Sample source:feces | Treatment:Stress Sample source:feces | Treatment:Stress Sample source:feces | Treatment:Control Sample source:feces | Treatment:Post Sample source:feces | Treatment:Post Sample source:feces | Treatment:Control Sample source:feces | Treatment:Control Sample source:feces | Treatment:Pre Sample source:feces | Treatment:Control Sample source:feces | Treatment:Control Sample source:feces | Treatment:Control Sample source:feces | Treatment:Control Sample source:feces | Treatment:Pre Sample source:feces | Treatment:Stress Sample source:feces | Treatment:Post Sample source:feces | Treatment:Pre Sample source:feces | Treatment:Stress Sample source:feces | Treatment:Pre Sample source:feces | Treatment:Post Sample source:feces | Treatment:Stress Sample source:feces | Treatment:Stress Sample source:feces | Treatment:Post Sample source:feces | Treatment:Post Sample source:feces | Treatment:Control Acetic acid 2.47 3.04 6.59 2.94 3.13 2.35 4.17 3.30 3.69 2.89 4.11 2.89 3.00 3.99 2.41 3.25 3.60 3.03 3.99 2.37 3.23 2.40 3.25 2.30 3.01 2.71 3.73 4.09 2.65 2.72 2.37 1.91 3.56 2.54 3.04 2.83 3.27 1.53 2.66 2.76 Propionic acid 1.77 1.73 5.93 1.36 1.72 1.10 1.40 1.85 1.71 1.37 3.60 1.64 1.42 1.55 1.72 1.72 2.45 1.96 2.21 1.66 1.32 2.95 0.57 0.84 1.75 1.31 3.24 2.50 1.14 0.72 1.05 1.74 1.33 1.09 1.67 1.84 1.48 1.17 1.43 1.10 Butyric acid 1.71 1.68 2.46 0.65 0.97 0.27 0.49 1.19 1.60 0.98 1.45 0.98 1.00 0.46 1.24 1.10 0.85 0.86 1.10 0.72 0.69 0.81 0.74 0.40 0.79 0.58 0.64 2.24 0.54 0.64 0.48 0.45 1.59 0.82 1.05 0.88 1.25 0.38 1.03 1.19 Isovaleric acid 0.77 0.27 0.33 0.11 0.06 ND 0.07 0.14 ND 0.05 0.05 0.10 0.03 ND 0.08 0.02 0.02 0.06 ND 0.18 ND 0.15 ND 0.03 0.04 0.06 ND 0.08 0.04 ND 0.03 0.07 0.07 0.05 0.15 0.11 0.09 0.13 0.10 0.07 Valeric acid 1.75 1.50 1.83 0.11 0.20 0.06 0.10 0.10 ND 0.11 0.24 0.13 0.18 ND 0.15 0.07 ND 0.15 0.05 0.29 0.14 0.42 ND 0.05 0.06 0.08 ND 0.09 0.05 ND 0.05 0.10 0.05 0.18 0.17 0.30 0.31 0.21 0.35 0.26 MS_METABOLITE_DATA_END #METABOLITES METABOLITES_START metabolite_name SIM Pubchem ID Acetic acid 43-60 176 Propionic acid 45-74 1032 Butyric acid 60-73 264 Isovaleric acid 60-74 10430 Valeric acid 60-73 7991 METABOLITES_END #END