#METABOLOMICS WORKBENCH crr4tz_20221110_085440 DATATRACK_ID:3562 STUDY_ID:ST002345 ANALYSIS_ID:AN003829 VERSION 1 CREATED_ON 12-15-2022 #PROJECT PR:PROJECT_TITLE Stress-Induced Mucosal Layer Disruption Drives Gut Dysbiosis and Depressive-like PR:PROJECT_TITLE Behaviors PR:PROJECT_SUMMARY Depression is a common mental health condition with a large social and economic PR:PROJECT_SUMMARY impact. While depression etiology is multifactorial, chronic stress is a PR:PROJECT_SUMMARY well-accepted contributor to disease onset. In addition, depression is PR:PROJECT_SUMMARY associated with altered gut microbial signatures that can be replicated in PR:PROJECT_SUMMARY animal models. While targeted restoration of the microbiome has been shown to PR:PROJECT_SUMMARY reduce depressive-like behaviors in mice, the complexity and diversity of the PR:PROJECT_SUMMARY human microbiome has complicated therapeutic intervention in patients. To PR:PROJECT_SUMMARY circumvent these limitations, there is a critical need for identifying pathways PR:PROJECT_SUMMARY responsible for microbiome dysbiosis. Here, for the first time, we identify the PR:PROJECT_SUMMARY changes in host physiology that induce microbiome dysbiosis. Specifically, we PR:PROJECT_SUMMARY show that a component of mucosal layer, the transmembrane protein mucin 13, can PR:PROJECT_SUMMARY regulate microbiome composition. Using a model of chronic stress to induce PR:PROJECT_SUMMARY behavioral and microbial changes in mice, we show a significant reduction in PR:PROJECT_SUMMARY mucin 13 expression across the intestines that occurs independently of the PR:PROJECT_SUMMARY microbiome. Furthermore, deleting Muc13 leads to gut dysbiosis, and baseline PR:PROJECT_SUMMARY behavioral changes normally observed after stress exposure. Together, these PR:PROJECT_SUMMARY results validate the hypothesis that mucosal layer disruption is an initiating PR:PROJECT_SUMMARY event in stress-induced dysbiosis and offer mucin 13 as a potential new PR:PROJECT_SUMMARY therapeutic target for microbiome dysbiosis in stress-induced depression. For PR:PROJECT_SUMMARY the first time, our data provide an upstream and conserved target for treating PR:PROJECT_SUMMARY microbiome dysbiosis, a result with sweeping implications for diseases PR:PROJECT_SUMMARY presenting with microbial alterations. PR:INSTITUTE University of Virginia PR:DEPARTMENT Neuroscience PR:LABORATORY Gaultier Lab PR:LAST_NAME Rivet-Noor PR:FIRST_NAME Courtney PR:ADDRESS 409 Lane Road, Charlottsville, Virginia, 22903, USA PR:EMAIL crr4tz@virginia.edu PR:PHONE 434-243-1903 PR:FUNDING_SOURCE NIH PR:DOI http://dx.doi.org/10.21228/M85717 #STUDY ST:STUDY_TITLE Stress-Induced Mucosal Layer Disruption Drives Gut Dysbiosis and Depressive-like ST:STUDY_TITLE Behaviors ST:STUDY_SUMMARY Depression is a common mental health condition with a large social and economic ST:STUDY_SUMMARY impact. While depression etiology is multifactorial, chronic stress is a ST:STUDY_SUMMARY well-accepted contributor to disease onset. In addition, depression is ST:STUDY_SUMMARY associated with altered gut microbial signatures that can be replicated in ST:STUDY_SUMMARY animal models. While targeted restoration of the microbiome has been shown to ST:STUDY_SUMMARY reduce depressive-like behaviors in mice, the complexity and diversity of the ST:STUDY_SUMMARY human microbiome has complicated therapeutic intervention in patients. To ST:STUDY_SUMMARY circumvent these limitations, there is a critical need for identifying pathways ST:STUDY_SUMMARY responsible for microbiome dysbiosis. Here, for the first time, we identify the ST:STUDY_SUMMARY changes in host physiology that induce microbiome dysbiosis. Specifically, we ST:STUDY_SUMMARY show that a component of mucosal layer, the transmembrane protein mucin 13, can ST:STUDY_SUMMARY regulate microbiome composition. Using a model of chronic stress to induce ST:STUDY_SUMMARY behavioral and microbial changes in mice, we show a significant reduction in ST:STUDY_SUMMARY mucin 13 expression across the intestines that occurs independently of the ST:STUDY_SUMMARY microbiome. Furthermore, deleting Muc13 leads to gut dysbiosis, and baseline ST:STUDY_SUMMARY behavioral changes normally observed after stress exposure. Together, these ST:STUDY_SUMMARY results validate the hypothesis that mucosal layer disruption is an initiating ST:STUDY_SUMMARY event in stress-induced dysbiosis and offer mucin 13 as a potential new ST:STUDY_SUMMARY therapeutic target for microbiome dysbiosis in stress-induced depression. For ST:STUDY_SUMMARY the first time, our data provide an upstream and conserved target for treating ST:STUDY_SUMMARY microbiome dysbiosis, a result with sweeping implications for diseases ST:STUDY_SUMMARY presenting with microbial alterations. ST:INSTITUTE University of Virginia ST:LAST_NAME Rivet-Noor ST:FIRST_NAME Courtney ST:ADDRESS 409 Lane Road, Charlottsville, Virginia, 22903, USA ST:EMAIL crr4tz@virginia.edu ST:PHONE 434-243-1903 ST:SUBMIT_DATE 2022-11-10 #SUBJECT SU:SUBJECT_TYPE Mammal SU:SUBJECT_SPECIES Mus musculus SU:TAXONOMY_ID 10090 SU:AGE_OR_AGE_RANGE 12-24 weeks SU:GENDER Male SU:ANIMAL_ANIMAL_SUPPLIER Jackson SU:ANIMAL_LIGHT_CYCLE 12L/12D #SUBJECT_SAMPLE_FACTORS: SUBJECT(optional)[tab]SAMPLE[tab]FACTORS(NAME:VALUE pairs separated by |)[tab]Additional sample data SUBJECT_SAMPLE_FACTORS - blank1 Group:CTL RAW_FILE_NAME=x06242021x_PRM_blank1 SUBJECT_SAMPLE_FACTORS - blank2 Group:CTL RAW_FILE_NAME=x06242021x_PRM_blank2 SUBJECT_SAMPLE_FACTORS - blank3 Group:CTL RAW_FILE_NAME=x06242021x_PRM_blank3 SUBJECT_SAMPLE_FACTORS - blank4 Group:CTL RAW_FILE_NAME=x06242021x_PRM_blank4 SUBJECT_SAMPLE_FACTORS - Cal1_A Group:CTL RAW_FILE_NAME=x06242021x_PRM_Cal1_A SUBJECT_SAMPLE_FACTORS - Cal1_B Group:CTL RAW_FILE_NAME=x06242021x_PRM_Cal1_B SUBJECT_SAMPLE_FACTORS - Cal2_A Group:CTL RAW_FILE_NAME=x06242021x_PRM_Cal2_A SUBJECT_SAMPLE_FACTORS - Cal2_B Group:CTL RAW_FILE_NAME=x06242021x_PRM_Cal2_B SUBJECT_SAMPLE_FACTORS - Cal3_A Group:CTL RAW_FILE_NAME=x06242021x_PRM_Cal3_A SUBJECT_SAMPLE_FACTORS - Cal3_B Group:CTL RAW_FILE_NAME=x06242021x_PRM_Cal3_B SUBJECT_SAMPLE_FACTORS - Cal4_A Group:CTL RAW_FILE_NAME=x06242021x_PRM_Cal4_A SUBJECT_SAMPLE_FACTORS - Cal4_B Group:CTL RAW_FILE_NAME=x06242021x_PRM_Cal4_B SUBJECT_SAMPLE_FACTORS - Cal5_A Group:CTL RAW_FILE_NAME=x06242021x_PRM_Cal5_A SUBJECT_SAMPLE_FACTORS - Cal5_B Group:CTL RAW_FILE_NAME=x06242021x_PRM_Cal5_B SUBJECT_SAMPLE_FACTORS - Naive_226 Group:Naïve RAW_FILE_NAME=x06242021x_PRM_Naive_226 SUBJECT_SAMPLE_FACTORS - Naive_227 Group:Naïve RAW_FILE_NAME=x06242021x_PRM_Naive_227 SUBJECT_SAMPLE_FACTORS - Naive_229 Group:Naïve RAW_FILE_NAME=x06242021x_PRM_Naive_229 SUBJECT_SAMPLE_FACTORS - Naive_230 Group:Naïve RAW_FILE_NAME=x06242021x_PRM_Naive_230 SUBJECT_SAMPLE_FACTORS - Naive_231 Group:Naïve RAW_FILE_NAME=x06242021x_PRM_Naive_231 SUBJECT_SAMPLE_FACTORS - Naive_237 Group:Naïve RAW_FILE_NAME=x06242021x_PRM_Naive_237 SUBJECT_SAMPLE_FACTORS - Naive_238 Group:Naïve RAW_FILE_NAME=x06242021x_PRM_Naive_238 SUBJECT_SAMPLE_FACTORS - Naive_239 Group:Naïve RAW_FILE_NAME=x06242021x_PRM_Naive_239 SUBJECT_SAMPLE_FACTORS - Naive_247 Group:Naïve RAW_FILE_NAME=x06242021x_PRM_Naive_247 SUBJECT_SAMPLE_FACTORS - Naive_248 Group:Naïve RAW_FILE_NAME=x06242021x_PRM_Naive_248 SUBJECT_SAMPLE_FACTORS - Naive_249 Group:Naïve RAW_FILE_NAME=x06242021x_PRM_Naive_249 SUBJECT_SAMPLE_FACTORS - Stress_232 Group:Stress RAW_FILE_NAME=x06242021x_PRM_Stress_232 SUBJECT_SAMPLE_FACTORS - Stress_233 Group:Stress RAW_FILE_NAME=x06242021x_PRM_Stress_233 SUBJECT_SAMPLE_FACTORS - Stress_234 Group:Stress RAW_FILE_NAME=x06242021x_PRM_Stress_234 SUBJECT_SAMPLE_FACTORS - Stress_235 Group:Stress RAW_FILE_NAME=x06242021x_PRM_Stress_235 SUBJECT_SAMPLE_FACTORS - Stress_236 Group:Stress RAW_FILE_NAME=x06242021x_PRM_Stress_236 SUBJECT_SAMPLE_FACTORS - Stress_240 Group:Stress RAW_FILE_NAME=x06242021x_PRM_Stress_240 SUBJECT_SAMPLE_FACTORS - Stress_241 Group:Stress RAW_FILE_NAME=x06242021x_PRM_Stress_241 SUBJECT_SAMPLE_FACTORS - Stress_242 Group:Stress RAW_FILE_NAME=x06242021x_PRM_Stress_242 SUBJECT_SAMPLE_FACTORS - Stress_243 Group:Stress RAW_FILE_NAME=x06242021x_PRM_Stress_243 SUBJECT_SAMPLE_FACTORS - Stress_244 Group:Stress RAW_FILE_NAME=x06242021x_PRM_Stress_244 SUBJECT_SAMPLE_FACTORS - Stress_245 Group:Stress RAW_FILE_NAME=x06242021x_PRM_Stress_245 SUBJECT_SAMPLE_FACTORS - Stress_246 Group:Stress RAW_FILE_NAME=x06242021x_PRM_Stress_246 #COLLECTION CO:COLLECTION_SUMMARY Whole blood was extracted from animals at the time of euthanization from the CO:COLLECTION_SUMMARY heart chamber. Blood was collected into blood collection tubes (Fisher CO:COLLECTION_SUMMARY Scientific; #02-675-185) and spun for 10 min at 11,000g. Serum was collected and CO:COLLECTION_SUMMARY frozen in liquid nitrogen. 25uL of plasma was extracted with 500uL of CO:COLLECTION_SUMMARY acetonitrile by vortexing and centrifugation at 10min at 14,000rpm. 450uL of CO:COLLECTION_SUMMARY supernatant was transferred to new tube and dried via SpeedVac. Dried samples CO:COLLECTION_SUMMARY were reconstituted with 25uL of 50% methanol and transferred to autosampler CO:COLLECTION_SUMMARY vials. Injection volume =10uL in PRM mode for detection and quantification of 10 CO:COLLECTION_SUMMARY different analytes. Metabolite mixture was analyzed on Thermo Orbitrap IDX MS CO:COLLECTION_SUMMARY system coupled to a Vanquish UPLC system. Samples were transported via the CO:COLLECTION_SUMMARY autosampler (10uL injection volume) onto a Waters BEH C18 column. Runtime was CO:COLLECTION_SUMMARY 15min in PRM mode. Buffer A: 0.1% formic acid in water. Buffer B: 0.1% formic CO:COLLECTION_SUMMARY acid in methanol. LC Gradient: 0min: 0% B, 8min: 50% B, 9 min: 98% B, 13min: 98% CO:COLLECTION_SUMMARY B. Recalibration of system up to 15 min at 0% B for next injection. CO:SAMPLE_TYPE Blood (serum) CO:COLLECTION_METHOD Cardiac Puncture CO:COLLECTION_LOCATION Heart CO:STORAGE_CONDITIONS Described in summary #TREATMENT TR:TREATMENT_SUMMARY Mice were subjected to 3weeks of unpredictable chronic mild restraint stress or TR:TREATMENT_SUMMARY kept in a naive setting #SAMPLEPREP SP:SAMPLEPREP_SUMMARY Whole blood was extracted from animals at the time of euthanization from the SP:SAMPLEPREP_SUMMARY heart chamber. Blood was collected into blood collection tubes (Fisher SP:SAMPLEPREP_SUMMARY Scientific; #02-675-185) and spun for 10 min at 11,000g. Serum was collected and SP:SAMPLEPREP_SUMMARY frozen in liquid nitrogen. 25uL of plasma was extracted with 500uL of SP:SAMPLEPREP_SUMMARY acetonitrile by vortexing and centrifugation at 10min at 14,000rpm. 450uL of SP:SAMPLEPREP_SUMMARY supernatant was transferred to new tube and dried via SpeedVac. Dried samples SP:SAMPLEPREP_SUMMARY were reconstituted with 25uL of 50% methanol and transferred to autosampler SP:SAMPLEPREP_SUMMARY vials. Injection volume =10uL in PRM mode for detection and quantification of 10 SP:SAMPLEPREP_SUMMARY different analytes. Metabolite mixture was analyzed on Thermo Orbitrap IDX MS SP:SAMPLEPREP_SUMMARY system coupled to a Vanquish UPLC system. Samples were transported via the SP:SAMPLEPREP_SUMMARY autosampler (10uL injection volume) onto a Waters BEH C18 column. Runtime was SP:SAMPLEPREP_SUMMARY 15min in PRM mode. Buffer A: 0.1% formic acid in water. Buffer B: 0.1% formic SP:SAMPLEPREP_SUMMARY acid in methanol. LC Gradient: 0min: 0% B, 8min: 50% B, 9 min: 98% B, 13min: 98% SP:SAMPLEPREP_SUMMARY B. Recalibration of system up to 15 min at 0% B for next injection. SP:PROCESSING_STORAGE_CONDITIONS Described in summary SP:EXTRACT_STORAGE Described in summary #CHROMATOGRAPHY CH:INSTRUMENT_NAME Thermo Vanquish CH:COLUMN_NAME Waters Acquity BEH C18 (100 x 2mm,1.7um) CH:FLOW_GRADIENT 0min: 0% B, 8min: 50% B, 9 min: 98% B, 13min: 98% B. Recalibration of system up CH:FLOW_GRADIENT to 15 min at 0% B for next injection. CH:SOLVENT_A 100% water; 0.1% formic acid CH:SOLVENT_B 100% methanol 0.1% formic acid CH:ANALYTICAL_TIME 15 min CH:CHROMATOGRAPHY_TYPE Reversed phase #ANALYSIS AN:ANALYSIS_TYPE MS #MS MS:INSTRUMENT_NAME Thermo Orbitrap ID-X tribrid MS:INSTRUMENT_TYPE Orbitrap MS:MS_TYPE Other MS:MS_COMMENTS Raw data files were brought into Skyline software. Targeted peak detection was MS:MS_COMMENTS done based on the parent mass. Mass analyzer set to Orbitrap and resolution MS:MS_COMMENTS power set to 120,000 resolution. Then all raw files and unknown samples were MS:MS_COMMENTS imported to Skyline. Calibration curves were generated by Linear regression fit. MS:MS_COMMENTS Targeted precursor MZ and MZ of analytes was used to track and quantification of MS:MS_COMMENTS the metabolite. Peak areas for analytes in samples were used for quantification MS:MS_COMMENTS based in the generated calibration curves. MS:ION_MODE UNSPECIFIED #MS_METABOLITE_DATA MS_METABOLITE_DATA:UNITS ug/mL MS_METABOLITE_DATA_START Samples Naive_226 Naive_227 Naive_229 Naive_230 Naive_231 Naive_237 Naive_238 Naive_239 Naive_247 Naive_248 Naive_249 Stress_232 Stress_233 Stress_234 Stress_235 Stress_236 Stress_240 Stress_241 Stress_242 Stress_243 Stress_244 Stress_245 Stress_246 Factors Group:Naïve Group:Naïve Group:Naïve Group:Naïve Group:Naïve Group:Naïve Group:Naïve Group:Naïve Group:Naïve Group:Naïve Group:Naïve Group:Stress Group:Stress Group:Stress Group:Stress Group:Stress Group:Stress Group:Stress Group:Stress Group:Stress Group:Stress Group:Stress Group:Stress Aldosterone 0.0006 0.0009 0.0005 0.0012 0.0003 0.0006 0.0010 0.0029 0.0004 0.0021 0.0006 0.0004 0.0005 0.0019 0.0006 0.0024 0.0010 0.0008 0.0006 corticosterone 0.2340 0.1613 0.0866 0.2250 0.2597 0.0983 0.1150 0.0872 0.1040 0.1956 0.0175 0.1676 0.0940 0.1090 0.0855 0.1096 0.0465 0.0681 0.3389 0.0615 0.1631 0.1515 0.1038 cortisol 0.0005 0.0007 0.0006 0.0009 0.0028 0.0022 0.0009 0.0017 0.0039 0.0020 0.0044 0.0177 0.0094 0.0067 0.0119 0.0053 Dopamine 0.0001 0.0004 0.0004 0.0001 0.0004 0.0003 0.0002 0.0001 0.0001 0.0002 0.0003 0.0008 0.0002 0.0001 0.0001 Kynurenic acid 0.0300 0.0079 0.0345 0.0052 0.0051 0.0110 0.0298 0.0345 0.0030 0.0179 0.0068 0.0245 0.0382 0.0354 0.0179 0.0938 0.0187 0.0167 0.0747 0.0300 0.0111 0.0143 0.0099 kynurenine 0.0824 0.0646 0.0939 0.0898 0.0612 0.0759 0.0738 0.0942 0.0607 0.0793 0.0622 0.0645 0.0778 0.0898 0.0984 0.1841 0.0849 0.0935 0.1181 0.1102 0.0722 0.0742 0.0840 Norepinephrine 0.3074 serotonin 1.5176 1.7400 2.1098 1.6257 1.5459 1.6917 1.7629 2.1109 2.3721 2.4149 1.9543 1.3737 1.0737 1.0977 0.8581 1.7386 1.0889 1.2108 1.7373 1.2840 1.3241 1.4063 1.4263 Thyroxine 0.0027 0.0035 0.0022 0.0028 0.0020 0.0034 0.0022 0.0006 0.0044 0.0025 0.0024 0.0051 0.0026 0.0075 0.0017 0.0064 0.0022 0.0071 0.0040 0.0005 0.0023 0.0043 0.0052 Tryptophan 478.7400 412.7300 467.6400 591.5500 404.8800 443.6200 408.8100 483.1400 417.1900 423.2400 342.6400 517.7800 517.7200 511.8654 511.1200 689.6750 501.5900 580.2708 475.4900 543.0800 437.0700 477.3200 484.7900 MS_METABOLITE_DATA_END #METABOLITES METABOLITES_START metabolite_name pubchem_id inchi_key kegg_id other_id other_id_type ri ri_type moverz_quant Aldosterone 10.77 343.1886 corticosterone 11.05 329.2097 cortisol 10.94 327.1938 Dopamine 2.01 137.0592 Kynurenic acid 8.1 162.0545 kynurenine 4.69 94.0648 Norepinephrine 1.56 152.07 serotonin 4.08 160.0725 Thyroxine 10.93 731.6843 Tryptophan 6.43 188.07 METABOLITES_END #END