<?xml version="1.0" encoding="UTF-8"?>
<metabolite>
  <version>1.0</version>
  <creation_date>2016-09-30 22:20:01 UTC</creation_date>
  <update_date>2020-06-04 20:50:59 UTC</update_date>
  <accession>BMDB0000134</accession>
  <secondary_accessions>
    <accession>BMDB00134</accession>
  </secondary_accessions>
  <name>Fumaric acid</name>
  <description>Fumaric acid, also known as fumarate or E297, belongs to the class of organic compounds known as dicarboxylic acids and derivatives. These are organic compounds containing exactly two carboxylic acid groups. Fumaric acid exists as a solid, possibly soluble (in water), and a weakly acidic compound (based on its pKa) molecule. Fumaric acid exists in all living species, ranging from bacteria to humans. Fumaric acid is a potentially toxic compound.</description>
  <synonyms>
    <synonym>(2E)-2-Butenedioic acid</synonym>
    <synonym>(e)-2-Butenedioic acid</synonym>
    <synonym>e297</synonym>
    <synonym>Fumarsaeure</synonym>
    <synonym>trans-1,2-Ethylenedicarboxylic acid</synonym>
    <synonym>trans-But-2-enedioic acid</synonym>
    <synonym>trans-Butenedioic acid</synonym>
    <synonym>(2E)-2-Butenedioate</synonym>
    <synonym>(e)-2-Butenedioate</synonym>
    <synonym>trans-1,2-Ethylenedicarboxylate</synonym>
    <synonym>trans-But-2-enedioate</synonym>
    <synonym>trans-Butenedioate</synonym>
    <synonym>Fumarate</synonym>
    <synonym>(2E)-But-2-enedioate</synonym>
    <synonym>(2E)-But-2-enedioic acid</synonym>
    <synonym>2-(e)-Butenedioate</synonym>
    <synonym>2-(e)-Butenedioic acid</synonym>
    <synonym>Allomaleate</synonym>
    <synonym>Allomaleic acid</synonym>
    <synonym>Boletate</synonym>
    <synonym>Boletic acid</synonym>
    <synonym>FC 33</synonym>
    <synonym>Lichenate</synonym>
    <synonym>Lichenic acid</synonym>
    <synonym>trans-2-Butenedioate</synonym>
    <synonym>trans-2-Butenedioic acid</synonym>
    <synonym>Furamag</synonym>
    <synonym>Mafusol</synonym>
    <synonym>Fumaric acid</synonym>
  </synonyms>
  <chemical_formula>C4H4O4</chemical_formula>
  <average_molecular_weight>116.0722</average_molecular_weight>
  <monisotopic_moleculate_weight>116.010958616</monisotopic_moleculate_weight>
  <iupac_name>(2E)-but-2-enedioic acid</iupac_name>
  <traditional_iupac>fumaric acid</traditional_iupac>
  <cas_registry_number>110-17-8</cas_registry_number>
  <smiles>OC(=O)\C=C\C(O)=O</smiles>
  <inchi>InChI=1S/C4H4O4/c5-3(6)1-2-4(7)8/h1-2H,(H,5,6)(H,7,8)/b2-1+</inchi>
  <inchikey>VZCYOOQTPOCHFL-OWOJBTEDSA-N</inchikey>
  <taxonomy>
    <description> belongs to the class of organic compounds known as dicarboxylic acids and derivatives. These are organic compounds containing exactly two carboxylic acid groups.</description>
    <kingdom>Organic compounds</kingdom>
    <super_class>Organic acids and derivatives</super_class>
    <class>Carboxylic acids and derivatives</class>
    <sub_class>Dicarboxylic acids and derivatives</sub_class>
    <direct_parent>Dicarboxylic acids and derivatives</direct_parent>
    <alternative_parents>
      <alternative_parent>Carbonyl compounds</alternative_parent>
      <alternative_parent>Carboxylic acids</alternative_parent>
      <alternative_parent>Hydrocarbon derivatives</alternative_parent>
      <alternative_parent>Organic oxides</alternative_parent>
      <alternative_parent>Unsaturated fatty acids</alternative_parent>
    </alternative_parents>
    <substituents>
      <substituent>Aliphatic acyclic compound</substituent>
      <substituent>Carbonyl group</substituent>
      <substituent>Carboxylic acid</substituent>
      <substituent>Dicarboxylic acid or derivatives</substituent>
      <substituent>Fatty acid</substituent>
      <substituent>Fatty acyl</substituent>
      <substituent>Hydrocarbon derivative</substituent>
      <substituent>Organic oxide</substituent>
      <substituent>Organic oxygen compound</substituent>
      <substituent>Organooxygen compound</substituent>
      <substituent>Unsaturated fatty acid</substituent>
    </substituents>
    <molecular_framework>Aliphatic acyclic compounds</molecular_framework>
    <external_descriptors>
      <external_descriptor>butenedioic acid</external_descriptor>
    </external_descriptors>
  </taxonomy>
  <experimental_properties>
    <state>Solid</state>
    <property>
      <kind>melting_point</kind>
      <value>549 °C</value>
      <source/>
    </property>
    <property>
      <kind>water_solubility</kind>
      <value>7.0 mg/mL</value>
      <source/>
    </property>
    <property>
      <kind>logp</kind>
      <value>0.46</value>
      <source>HANSCH,C ET AL. (1995)</source>
    </property>
  </experimental_properties>
  <predicted_properties>
    <property>
      <kind>logp</kind>
      <value>0.21</value>
      <source>ALOGPS</source>
    </property>
    <property>
      <kind>logs</kind>
      <value>-0.68</value>
      <source>ALOGPS</source>
    </property>
    <property>
      <kind>logp</kind>
      <value>-0.041</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>pka_strongest_acidic</kind>
      <value>3.55</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>iupac</kind>
      <value>(2E)-but-2-enedioic acid</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>average_mass</kind>
      <value>116.0722</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>mono_mass</kind>
      <value>116.010958616</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>smiles</kind>
      <value>OC(=O)\C=C\C(O)=O</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>formula</kind>
      <value>C4H4O4</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>inchi</kind>
      <value>InChI=1S/C4H4O4/c5-3(6)1-2-4(7)8/h1-2H,(H,5,6)(H,7,8)/b2-1+</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>inchikey</kind>
      <value>VZCYOOQTPOCHFL-OWOJBTEDSA-N</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>polar_surface_area</kind>
      <value>74.6</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>refractivity</kind>
      <value>24.61</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>polarizability</kind>
      <value>9.35</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>rotatable_bond_count</kind>
      <value>2</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>acceptor_count</kind>
      <value>4</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>donor_count</kind>
      <value>2</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>physiological_charge</kind>
      <value>-2</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>formal_charge</kind>
      <value>0</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>number_of_rings</kind>
      <value>0</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>bioavailability</kind>
      <value>1</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>rule_of_five</kind>
      <value>Yes</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>ghose_filter</kind>
      <value>Yes</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>veber_rule</kind>
      <value>Yes</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>mddr_like_rule</kind>
      <value>Yes</value>
      <source>ChemAxon</source>
    </property>
  </predicted_properties>
  <pathways>
    <pathway>
      <name>Arginine and Proline Metabolism</name>
      <smpdb_id>SMP0087178</smpdb_id>
      <kegg_map_id/>
    </pathway>
    <pathway>
      <name>Aspartate Metabolism</name>
      <smpdb_id>SMP0087165</smpdb_id>
      <kegg_map_id/>
    </pathway>
    <pathway>
      <name>Citric Acid Cycle</name>
      <smpdb_id>SMP0087163</smpdb_id>
      <kegg_map_id/>
    </pathway>
    <pathway>
      <name>Mitochondrial Electron Transport Chain</name>
      <smpdb_id>SMP0087261</smpdb_id>
      <kegg_map_id/>
    </pathway>
    <pathway>
      <name>Phenylalanine and Tyrosine Metabolism</name>
      <smpdb_id>SMP0087218</smpdb_id>
      <kegg_map_id/>
    </pathway>
    <pathway>
      <name>Purine Metabolism</name>
      <smpdb_id>SMP0087239</smpdb_id>
      <kegg_map_id/>
    </pathway>
    <pathway>
      <name>Tyrosine Metabolism</name>
      <smpdb_id>SMP0087235</smpdb_id>
      <kegg_map_id/>
    </pathway>
    <pathway>
      <name>Urea Cycle</name>
      <smpdb_id>SMP0087224</smpdb_id>
      <kegg_map_id/>
    </pathway>
    <pathway>
      <name>Warburg Effect</name>
      <smpdb_id>SMP0087270</smpdb_id>
      <kegg_map_id/>
    </pathway>
  </pathways>
  <spectra>
    <spectrum>
      <type>Specdb::MsIr</type>
      <spectrum_id>210</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsIr</type>
      <spectrum_id>211</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsIr</type>
      <spectrum_id>212</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrTwoD</type>
      <spectrum_id>966</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrTwoD</type>
      <spectrum_id>1162</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>360</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>361</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>362</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>363</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>364</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>1063</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>2816</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>27694</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>30157</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>30188</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>30290</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>30291</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>30542</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>30868</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>31017</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>31937</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>37314</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>137191</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>144925</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>1051304</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>1051305</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>1051307</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::EiMs</type>
      <spectrum_id>232</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>206</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>207</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>208</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>3041</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>178911</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>178912</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>178913</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>181236</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>181237</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>181238</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2238392</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2239169</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2244560</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2245542</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2246647</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2247651</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2248738</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2249627</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2250808</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2251612</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2256268</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2265303</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2265304</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2265305</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>3076341</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>1104</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>1163</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>2142</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>2830</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>4764</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>4765</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142470</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142471</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142472</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142473</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142474</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142475</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142476</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142477</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142478</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142479</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142480</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142481</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142482</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142483</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142484</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142485</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142486</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142487</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142488</spectrum_id>
    </spectrum>
  </spectra>
  <normal_concentrations>
    <concentration>
      <biospecimen>Blood</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <references>
        <reference>
          <reference_text>Jiyuan Li, Everestus C. Akanno, Tiago Valente, Mohammed Abo-Ismail, Brian Karisa, Zhiquan Wang, Graham S. Plastow.  Genomic heritability and genome-wide association studies of plasma metabolites in crossbred beef cattle. (in preparation)</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Blood</biospecimen>
      <concentration_value>1.2 +/- 0.2</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By NMR</comment>
      <references>
        <reference>
          <reference_text>Aidin Foroutan, Carolyn Fitzsimmons, Rupasri Mandal, Hamed Piri‐Moghadam, Jiamin Zheng, AnChi Guo, Carin Li, Le Luo Guan and David S. Wishart. The Bovine Metabolome. Metabolites 2020, 10, 233; doi:10.3390/metabo10060233</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Colostrum</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Detected by NMR</comment>
      <references>
        <reference>
          <reference_text>Zanardi E, Caligiani A, Palla L, Mariani M, Ghidini S, Di Ciccio PA, Palla G, Ianieri A: Metabolic profiling by (1)H NMR of ground beef irradiated at different irradiation doses. Meat Sci. 2015 May;103:83-9. doi: 10.1016/j.meatsci.2015.01.005. Epub 2015 Jan 15.</reference_text>
          <pubmed_id>25637742</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Liver</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>8 multiparous Chinese Holstein dairy cows fed in the Hangzhou Hangjiang Dairy Farm based on the milk production under corn stover based diets. Detection used gas chromatography time-of-flight/mass spectrometry (GC-TOF/MS) platform.</comment>
      <references>
        <reference>
          <reference_text>Sun HZ, Zhou M, Wang O, Chen Y, Liu JX, Guan LL: Multi-omics reveals functional genomic and metabolic mechanisms of milk production and quality in dairy cows. Bioinformatics. 2020 Apr 15;36(8):2530-2537. doi: 10.1093/bioinformatics/btz951.</reference_text>
          <pubmed_id>31873721</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Liver</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>8 multiparous Chinese Holstein dairy cows fed in the Hangzhou Hangjiang Dairy Farm based on the milk production under alfalfa hay based diets. Detection used gas chromatography time-of-flight/mass spectrometry (GC-TOF/MS) platform.</comment>
      <references>
        <reference>
          <reference_text>Sun HZ, Zhou M, Wang O, Chen Y, Liu JX, Guan LL: Multi-omics reveals functional genomic and metabolic mechanisms of milk production and quality in dairy cows. Bioinformatics. 2020 Apr 15;36(8):2530-2537. doi: 10.1093/bioinformatics/btz951.</reference_text>
          <pubmed_id>31873721</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Liver</biospecimen>
      <concentration_value>299 +/- 55</concentration_value>
      <concentration_units>nmol/g of tissue</concentration_units>
      <comment>By NMR</comment>
      <references>
        <reference>
          <reference_text>Aidin Foroutan, Carolyn Fitzsimmons, Rupasri Mandal, Hamed Piri‐Moghadam, Jiamin Zheng, AnChi Guo, Carin Li, Le Luo Guan and David S. Wishart. The Bovine Metabolome. Metabolites 2020, 10, 233; doi:10.3390/metabo10060233</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Liver</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Metabolomics analysis was performed using GC-MS/LC-MS in multiparous Holstein dairy cows</comment>
      <references>
        <reference>
          <reference_text>Shahzad K, Lopreiato V, Liang Y, Trevisi E, Osorio JS, Xu C, Loor JJ: Hepatic metabolomics and transcriptomics to study susceptibility to ketosis in response to prepartal nutritional management. J Anim Sci Biotechnol. 2019 Dec 18;10:96. doi: 10.1186/s40104-019-0404-z. eCollection 2019.</reference_text>
          <pubmed_id>31867104</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Longissimus Thoracis Muscle</biospecimen>
      <concentration_value>141 +/- 64</concentration_value>
      <concentration_units>nmol/g of tissue</concentration_units>
      <comment>By NMR</comment>
      <references>
        <reference>
          <reference_text>Aidin Foroutan, Carolyn Fitzsimmons, Rupasri Mandal, Hamed Piri‐Moghadam, Jiamin Zheng, AnChi Guo, Carin Li, Le Luo Guan and David S. Wishart. The Bovine Metabolome. Metabolites 2020, 10, 233; doi:10.3390/metabo10060233</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Mammary Gland</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>8 multiparous Chinese Holstein dairy cows fed in the Hangzhou Hangjiang Dairy Farm based on the milk production under corn stover based diets. Detection used gas chromatography time-of-flight/mass spectrometry (GC-TOF/MS) platform.</comment>
      <references>
        <reference>
          <reference_text>Sun HZ, Zhou M, Wang O, Chen Y, Liu JX, Guan LL: Multi-omics reveals functional genomic and metabolic mechanisms of milk production and quality in dairy cows. Bioinformatics. 2020 Apr 15;36(8):2530-2537. doi: 10.1093/bioinformatics/btz951.</reference_text>
          <pubmed_id>31873721</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Mammary Gland</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>8 multiparous Chinese Holstein dairy cows fed in the Hangzhou Hangjiang Dairy Farm based on the milk production under alfalfa hay based diets. Detection used gas chromatography time-of-flight/mass spectrometry (GC-TOF/MS) platform.</comment>
      <references>
        <reference>
          <reference_text>Sun HZ, Zhou M, Wang O, Chen Y, Liu JX, Guan LL: Multi-omics reveals functional genomic and metabolic mechanisms of milk production and quality in dairy cows. Bioinformatics. 2020 Apr 15;36(8):2530-2537. doi: 10.1093/bioinformatics/btz951.</reference_text>
          <pubmed_id>31873721</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>11.63 +/- 3.65</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Raw milk metabolite measured during mid-lactation from cows fed diets consisting of total mixed ration (TMR), by 1H-NMR</comment>
      <references>
        <reference>
          <reference_text>O'Callaghan TF, Vazquez-Fresno R, Serra-Cayuela A, Dong E, Mandal R, Hennessy D, McAuliffe S, Dillon P, Wishart DS, Stanton C, Ross RP: Pasture Feeding Changes the Bovine Rumen and Milk Metabolome. Metabolites. 2018 Apr 6;8(2). pii: metabo8020027. doi: 10.3390/metabo8020027.</reference_text>
          <pubmed_id>29642378</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>2 - 81</concentration_value>
      <concentration_units>uM</concentration_units>
      <references>
        <reference>
          <reference_text>Klein MS, Almstetter MF, Schlamberger G, Nurnberger N, Dettmer K, Oefner PJ, Meyer HH, Wiedemann S, Gronwald W: Nuclear magnetic resonance and mass spectrometry-based milk metabolomics in dairy cows during early and late lactation. J Dairy Sci. 2010 Apr;93(4):1539-50. doi: 10.3168/jds.2009-2563.</reference_text>
          <pubmed_id>20338431</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>7 - 23</concentration_value>
      <concentration_units>uM</concentration_units>
      <references>
        <reference>
          <reference_text>Klein MS, Buttchereit N, Miemczyk SP, Immervoll AK, Louis C, Wiedemann S, Junge W, Thaller G, Oefner PJ, Gronwald W: NMR metabolomic analysis of dairy cows reveals milk glycerophosphocholine to phosphocholine ratio as prognostic biomarker for risk of ketosis. J Proteome Res. 2012 Feb 3;11(2):1373-81. doi: 10.1021/pr201017n. Epub 2011 Dec 9.</reference_text>
          <pubmed_id>22098372</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>10 - 23</concentration_value>
      <concentration_units>uM</concentration_units>
      <references>
        <reference>
          <reference_text>Klein MS, Buttchereit N, Miemczyk SP, Immervoll AK, Louis C, Wiedemann S, Junge W, Thaller G, Oefner PJ, Gronwald W: NMR metabolomic analysis of dairy cows reveals milk glycerophosphocholine to phosphocholine ratio as prognostic biomarker for risk of ketosis. J Proteome Res. 2012 Feb 3;11(2):1373-81. doi: 10.1021/pr201017n. Epub 2011 Dec 9.</reference_text>
          <pubmed_id>22098372</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Commercial, conventional whole milk</comment>
      <references>
        <reference>
          <reference_text>Kurt J. Boudonck, Matthew W. Mitchell, Jacob Wulff, John A. Ryals. Characterization of the biochemical variability of bovine milk using metabolomics. Metabolomics (2009) 5:375-386   doi: 10.1007/s11306-009-0160-8</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>13 +/- 1</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>1% milk by NMR</comment>
      <references>
        <reference>
          <reference_text>Foroutan A, Guo AC, Vazquez-Fresno R, Lipfert M, Zhang L, Zheng J, Badran H, Budinski Z, Mandal R, Ametaj BN, Wishart DS: Chemical Composition of Commercial Cow's Milk. J Agric Food Chem. 2019 Apr 17. doi: 10.1021/acs.jafc.9b00204.</reference_text>
          <pubmed_id>30994344</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Detected but not quantified in conventional whole milk</comment>
      <references>
        <reference>
          <reference_text>Kurt J. Boudonck, Matthew W. Mitchell, Jacob Wulff and John A. Ryals. Characterization of the biochemical variability of bovine milk using metabolomics. Metabolomics (2009) 5:375?386</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>13 +/- 1</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>2% milk by NMR</comment>
      <references>
        <reference>
          <reference_text>Foroutan A, Guo AC, Vazquez-Fresno R, Lipfert M, Zhang L, Zheng J, Badran H, Budinski Z, Mandal R, Ametaj BN, Wishart DS: Chemical Composition of Commercial Cow's Milk. J Agric Food Chem. 2019 Apr 17. doi: 10.1021/acs.jafc.9b00204.</reference_text>
          <pubmed_id>30994344</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>13 +/- 1</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>3.25% milk by NMR</comment>
      <references>
        <reference>
          <reference_text>Foroutan A, Guo AC, Vazquez-Fresno R, Lipfert M, Zhang L, Zheng J, Badran H, Budinski Z, Mandal R, Ametaj BN, Wishart DS: Chemical Composition of Commercial Cow's Milk. J Agric Food Chem. 2019 Apr 17. doi: 10.1021/acs.jafc.9b00204.</reference_text>
          <pubmed_id>30994344</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>14 +/- 1</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Skim milk by NMR</comment>
      <references>
        <reference>
          <reference_text>Foroutan A, Guo AC, Vazquez-Fresno R, Lipfert M, Zhang L, Zheng J, Badran H, Budinski Z, Mandal R, Ametaj BN, Wishart DS: Chemical Composition of Commercial Cow's Milk. J Agric Food Chem. 2019 Apr 17. doi: 10.1021/acs.jafc.9b00204.</reference_text>
          <pubmed_id>30994344</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>11.20 +/- 4.36</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Raw milk metabolite measured during mid-lactation from cows fed diets consisting of perennial ryegrass (GRS), by 1H-NMR</comment>
      <references>
        <reference>
          <reference_text>O'Callaghan TF, Vazquez-Fresno R, Serra-Cayuela A, Dong E, Mandal R, Hennessy D, McAuliffe S, Dillon P, Wishart DS, Stanton C, Ross RP: Pasture Feeding Changes the Bovine Rumen and Milk Metabolome. Metabolites. 2018 Apr 6;8(2). pii: metabo8020027. doi: 10.3390/metabo8020027.</reference_text>
          <pubmed_id>29642378</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>12.54 +/- 2.98</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Raw milk metabolite measured during mid-lactation from cows fed diets consisting of perennial ryegrass and white clover (CLV), by 1H-NMR</comment>
      <references>
        <reference>
          <reference_text>O'Callaghan TF, Vazquez-Fresno R, Serra-Cayuela A, Dong E, Mandal R, Hennessy D, McAuliffe S, Dillon P, Wishart DS, Stanton C, Ross RP: Pasture Feeding Changes the Bovine Rumen and Milk Metabolome. Metabolites. 2018 Apr 6;8(2). pii: metabo8020027. doi: 10.3390/metabo8020027.</reference_text>
          <pubmed_id>29642378</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Samples collected from 54 Holstein cows</comment>
      <references>
        <reference>
          <reference_text>Maher AD, Hayes B, Cocks B, Marett L, Wales WJ, Rochfort SJ: Latent biochemical relationships in the blood-milk metabolic axis of dairy cows revealed by statistical integration of 1H NMR spectroscopic data. J Proteome Res. 2013 Mar 1;12(3):1428-35. doi: 10.1021/pr301056q. Epub 2013 Feb 21.</reference_text>
          <pubmed_id>23394630</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Milk samples collected from 456 Danish Holstein cows </comment>
      <references>
        <reference>
          <reference_text>Buitenhuis AJ, Sundekilde UK, Poulsen NA, Bertram HC, Larsen LB, Sorensen P: Estimation of genetic parameters and detection of quantitative trait loci for metabolites in Danish Holstein milk. J Dairy Sci. 2013 May;96(5):3285-95. doi: 10.3168/jds.2012-5914. Epub 2013 Mar 15.</reference_text>
          <pubmed_id>23497994</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Milk samples from Danish Holstein-Friesian (n = 456) and Jersey cows (n = 436)</comment>
      <references>
        <reference>
          <reference_text>Sundekilde UK, Poulsen NA, Larsen LB, Bertram HC: Nuclear magnetic resonance metabonomics reveals strong association between milk metabolites and somatic cell count in bovine milk. J Dairy Sci. 2013 Jan;96(1):290-9. doi: 10.3168/jds.2012-5819. Epub 2012 Nov 22.</reference_text>
          <pubmed_id>23182357</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Whole milk  from markets</comment>
      <references>
        <reference>
          <reference_text>Scano P, Murgia A, Pirisi FM, Caboni P: A gas chromatography-mass spectrometry-based metabolomic approach for the characterization of goat milk compared with cow milk. J Dairy Sci. 2014 Oct;97(10):6057-66. doi: 10.3168/jds.2014-8247. Epub 2014 Aug 6.</reference_text>
          <pubmed_id>25108860</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>407 Milk samples from Swedish Red cows</comment>
      <references>
        <reference>
          <reference_text>Sundekilde UK, Gustavsson F, Poulsen NA, Glantz M, Paulsson M, Larsen LB, Bertram HC: Association between the bovine milk metabolome and rennet-induced coagulation properties of milk. J Dairy Sci. 2014 Oct;97(10):6076-84. doi: 10.3168/jds.2014-8304. Epub 2014 Jul 30.</reference_text>
          <pubmed_id>25087032</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Muscle</biospecimen>
      <concentration_value>36-208</concentration_value>
      <concentration_units>nmol/g of tissue</concentration_units>
      <comment>By CE-TOFMS</comment>
      <references>
        <reference>
          <reference_text>Muroya S, Oe M, Ojima K, Watanabe A: Metabolomic approach to key metabolites characterizing postmortem aged loin muscle of Japanese Black (Wagyu) cattle. Asian-Australas J Anim Sci. 2019 Aug;32(8):1172-1185. doi: 10.5713/ajas.18.0648.  Epub 2019 Jan 4.</reference_text>
          <pubmed_id>30744349</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Muscle</biospecimen>
      <concentration_value>107.37 +/- 14.42</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Detected by NMR in US commercial beef sirloin</comment>
      <references>
        <reference>
          <reference_text>Jung Y, Lee J, Kwon J, Lee KS, Ryu DH, Hwang GS: Discrimination of the geographical origin of beef by (1)H NMR-based metabolomics. J Agric Food Chem. 2010 Oct 13;58(19):10458-66. doi: 10.1021/jf102194t.</reference_text>
          <pubmed_id>20831251</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Muscle</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Detected by NMR</comment>
      <references>
        <reference>
          <reference_text>Zanardi E, Caligiani A, Palla L, Mariani M, Ghidini S, Di Ciccio PA, Palla G, Ianieri A: Metabolic profiling by (1)H NMR of ground beef irradiated at different irradiation doses. Meat Sci. 2015 May;103:83-9. doi: 10.1016/j.meatsci.2015.01.005. Epub 2015 Jan 15.</reference_text>
          <pubmed_id>25637742</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Muscle</biospecimen>
      <concentration_value>123.02 +/- 19.31</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Detected by NMR in Australian commercial beef sirloin.</comment>
      <references>
        <reference>
          <reference_text>Jung Y, Lee J, Kwon J, Lee KS, Ryu DH, Hwang GS: Discrimination of the geographical origin of beef by (1)H NMR-based metabolomics. J Agric Food Chem. 2010 Oct 13;58(19):10458-66. doi: 10.1021/jf102194t.</reference_text>
          <pubmed_id>20831251</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Muscle</biospecimen>
      <concentration_value>160.89 +/- 17.1</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Detected by NMR in New Zealand commercial beef sirloin.</comment>
      <references>
        <reference>
          <reference_text>Jung Y, Lee J, Kwon J, Lee KS, Ryu DH, Hwang GS: Discrimination of the geographical origin of beef by (1)H NMR-based metabolomics. J Agric Food Chem. 2010 Oct 13;58(19):10458-66. doi: 10.1021/jf102194t.</reference_text>
          <pubmed_id>20831251</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Muscle</biospecimen>
      <concentration_value>73-178</concentration_value>
      <concentration_units>nmol/g of tissue</concentration_units>
      <comment>By NMR</comment>
      <references>
        <reference>
          <reference_text>Jung Y, Lee J, Kwon J, Lee KS, Ryu DH, Hwang GS: Discrimination of the geographical origin of beef by (1)H NMR-based metabolomics. J Agric Food Chem. 2010 Oct 13;58(19):10458-66. doi: 10.1021/jf102194t.</reference_text>
          <pubmed_id>20831251</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Muscle</biospecimen>
      <concentration_value>140</concentration_value>
      <concentration_units>nmol/g of tissue</concentration_units>
      <comment>By NMR</comment>
      <references>
        <reference>
          <reference_text>Kim YH, Kemp R, Samuelsson LM: Effects of dry-aging on meat quality attributes and metabolite profiles of beef loins. Meat Sci. 2016 Jan;111:168-76. doi: 10.1016/j.meatsci.2015.09.008. Epub 2015 Sep  26.</reference_text>
          <pubmed_id>26437054</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Muscle</biospecimen>
      <concentration_value>84.76 +/- 11.89</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Detected by NMR in Korean commercial beef sirloin.</comment>
      <references>
        <reference>
          <reference_text>Jung Y, Lee J, Kwon J, Lee KS, Ryu DH, Hwang GS: Discrimination of the geographical origin of beef by (1)H NMR-based metabolomics. J Agric Food Chem. 2010 Oct 13;58(19):10458-66. doi: 10.1021/jf102194t.</reference_text>
          <pubmed_id>20831251</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Muscle</biospecimen>
      <concentration_value>37-49</concentration_value>
      <concentration_units>nmol/g of tissue</concentration_units>
      <comment>By NMR</comment>
      <references>
        <reference>
          <reference_text>Kodani Y, Miyakawa T, Komatsu T, Tanokura M: NMR-based metabolomics for simultaneously evaluating multiple determinants of primary beef quality in Japanese Black cattle. Sci Rep. 2017 May 2;7(1):1297. doi: 10.1038/s41598-017-01272-8.</reference_text>
          <pubmed_id>28465593</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Placenta</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <references>
        <reference>
          <reference_text>Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vazquez-Fresno R, Sajed T, Johnson D, Li C, Karu N, Sayeeda Z, Lo E, Assempour N, Berjanskii M, Singhal S, Arndt D, Liang Y, Badran H, Grant J, Serra-Cayuela A, Liu Y, Mandal R, Neveu V, Pon A, Knox C, Wilson M, Manach C, Scalbert A: HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 2018 Jan 4;46(D1):D608-D617. doi: 10.1093/nar/gkx1089.</reference_text>
          <pubmed_id>29140435</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Prostate Tissue</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <references>
        <reference>
          <reference_text>Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vazquez-Fresno R, Sajed T, Johnson D, Li C, Karu N, Sayeeda Z, Lo E, Assempour N, Berjanskii M, Singhal S, Arndt D, Liang Y, Badran H, Grant J, Serra-Cayuela A, Liu Y, Mandal R, Neveu V, Pon A, Knox C, Wilson M, Manach C, Scalbert A: HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 2018 Jan 4;46(D1):D608-D617. doi: 10.1093/nar/gkx1089.</reference_text>
          <pubmed_id>29140435</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>19-315</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By NMR</comment>
      <references>
        <reference>
          <reference_text>Lee HJ, Jung JY, Oh YK, Lee SS, Madsen EL, Jeon CO: Comparative survey of rumen microbial communities and metabolites across one caprine and three bovine groups, using bar-coded pyrosequencing and (1)H nuclear magnetic resonance spectroscopy. Appl Environ Microbiol. 2012 Sep;78(17):5983-93. doi: 10.1128/AEM.00104-12. Epub  2012 Jun 15.</reference_text>
          <pubmed_id>22706048</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>5.82</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By NMR. Primiparous Holstein cows fed barley grains (15% of diet dry matter)</comment>
      <references>
        <reference>
          <reference_text>Burim NA, Qendrim Z, Fozia S, Psychogios N, Michael JL, Dunn SM, Jianguo X, Wishart DS. Metabolomics reveals unhealthy alterations in rumen metabolism with increased proportion of cereal grain in the diet of dairy cows. Metabolomics. 2010;6(4):583-594   doi: 10.1007/s11306-010-0227-6</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>1.42</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By NMR. Primiparous Holstein cows fed barley grains (30% of diet dry matter)</comment>
      <references>
        <reference>
          <reference_text>Burim NA, Qendrim Z, Fozia S, Psychogios N, Michael JL, Dunn SM, Jianguo X, Wishart DS. Metabolomics reveals unhealthy alterations in rumen metabolism with increased proportion of cereal grain in the diet of dairy cows. Metabolomics. 2010;6(4):583-594   doi: 10.1007/s11306-010-0227-6</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>6.44</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By NMR. Primiparous Holstein cows fed barley grains (45% of diet dry matter)</comment>
      <references>
        <reference>
          <reference_text>Burim NA, Qendrim Z, Fozia S, Psychogios N, Michael JL, Dunn SM, Jianguo X, Wishart DS. Metabolomics reveals unhealthy alterations in rumen metabolism with increased proportion of cereal grain in the diet of dairy cows. Metabolomics. 2010;6(4):583-594   doi: 10.1007/s11306-010-0227-6</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>1.64</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By NMR. Primiparous Holstein cows, no barley grains in diet.</comment>
      <references>
        <reference>
          <reference_text>Burim NA, Qendrim Z, Fozia S, Psychogios N, Michael JL, Dunn SM, Jianguo X, Wishart DS. Metabolomics reveals unhealthy alterations in rumen metabolism with increased proportion of cereal grain in the diet of dairy cows. Metabolomics. 2010;6(4):583-594   doi: 10.1007/s11306-010-0227-6</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Detected by NMR in bovines in growth and fattening stages.</comment>
      <references>
        <reference>
          <reference_text>Lee HJ, Jung JY, Oh YK, Lee SS, Madsen EL, Jeon CO: Comparative survey of rumen microbial communities and metabolites across one caprine and three bovine groups, using bar-coded pyrosequencing and (1)H nuclear magnetic resonance spectroscopy. Appl Environ Microbiol. 2012 Sep;78(17):5983-93. doi: 10.1128/AEM.00104-12. Epub  2012 Jun 15.</reference_text>
          <pubmed_id>22706048</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Detected by NMR in bovines in growth and fattening stages.</comment>
      <references>
        <reference>
          <reference_text>Lee HJ, Jung JY, Oh YK, Lee SS, Madsen EL, Jeon CO: Comparative survey of rumen microbial communities and metabolites across one caprine and three bovine groups, using bar-coded pyrosequencing and (1)H nuclear magnetic resonance spectroscopy. Appl Environ Microbiol. 2012 Sep;78(17):5983-93. doi: 10.1128/AEM.00104-12. Epub  2012 Jun 15.</reference_text>
          <pubmed_id>22706048</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Detected by NMR in bovines in growth and fattening stages.</comment>
      <references>
        <reference>
          <reference_text>Lee HJ, Jung JY, Oh YK, Lee SS, Madsen EL, Jeon CO: Comparative survey of rumen microbial communities and metabolites across one caprine and three bovine groups, using bar-coded pyrosequencing and (1)H nuclear magnetic resonance spectroscopy. Appl Environ Microbiol. 2012 Sep;78(17):5983-93. doi: 10.1128/AEM.00104-12. Epub  2012 Jun 15.</reference_text>
          <pubmed_id>22706048</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>18 +/- 7</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By NMR</comment>
      <references>
        <reference>
          <reference_text>Aidin Foroutan, Carolyn Fitzsimmons, Rupasri Mandal, Hamed Piri‐Moghadam, Jiamin Zheng, AnChi Guo, Carin Li, Le Luo Guan and David S. Wishart. The Bovine Metabolome. Metabolites 2020, 10, 233; doi:10.3390/metabo10060233</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>8.75 +/- 3.84</concentration_value>
      <concentration_units>uM</concentration_units>
      <references>
        <reference>
          <reference_text>Fozia Saleem, Souhaila Bouatra, An Chi Guo, Nikolaos Psychogios, Rupasri Mandal, Suzanna M. Dunn, Burim N. Ametaj, David S. Wishart. The Bovine Ruminal Fluid Metabolome. Metabolomics (2013) 9:360–378.</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>11.2</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By NMR. Daily cows fed barley grains (15% of diet dry matter) (n=8)</comment>
      <references>
        <reference>
          <reference_text>Saleem F, Ametaj BN, Bouatra S, Mandal R, Zebeli Q, Dunn SM, Wishart DS: A metabolomics approach to uncover the effects of grain diets on rumen health in dairy cows. J Dairy Sci. 2012 Nov;95(11):6606-23. doi: 10.3168/jds.2012-5403. Epub 2012 Sep 7.</reference_text>
          <pubmed_id>22959937</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>11.2</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By NMR. Daily cows fed barley grains (15% of diet dry matter) (n=8)</comment>
      <references>
        <reference>
          <reference_text>Saleem F, Ametaj BN, Bouatra S, Mandal R, Zebeli Q, Dunn SM, Wishart DS: A metabolomics approach to uncover the effects of grain diets on rumen health in dairy cows. J Dairy Sci. 2012 Nov;95(11):6606-23. doi: 10.3168/jds.2012-5403. Epub 2012 Sep 7.</reference_text>
          <pubmed_id>22959937</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>7.5</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By NMR. Daily cows fed barley grains (30% of diet dry matter) (n=8)</comment>
      <references>
        <reference>
          <reference_text>Saleem F, Ametaj BN, Bouatra S, Mandal R, Zebeli Q, Dunn SM, Wishart DS: A metabolomics approach to uncover the effects of grain diets on rumen health in dairy cows. J Dairy Sci. 2012 Nov;95(11):6606-23. doi: 10.3168/jds.2012-5403. Epub 2012 Sep 7.</reference_text>
          <pubmed_id>22959937</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>7.5</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By NMR. Daily cows fed barley grains (30% of diet dry matter) (n=8)</comment>
      <references>
        <reference>
          <reference_text>Saleem F, Ametaj BN, Bouatra S, Mandal R, Zebeli Q, Dunn SM, Wishart DS: A metabolomics approach to uncover the effects of grain diets on rumen health in dairy cows. J Dairy Sci. 2012 Nov;95(11):6606-23. doi: 10.3168/jds.2012-5403. Epub 2012 Sep 7.</reference_text>
          <pubmed_id>22959937</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>11.7</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By NMR. Daily cows fed barley grains (45% of diet dry matter) (n=8)</comment>
      <references>
        <reference>
          <reference_text>Saleem F, Ametaj BN, Bouatra S, Mandal R, Zebeli Q, Dunn SM, Wishart DS: A metabolomics approach to uncover the effects of grain diets on rumen health in dairy cows. J Dairy Sci. 2012 Nov;95(11):6606-23. doi: 10.3168/jds.2012-5403. Epub 2012 Sep 7.</reference_text>
          <pubmed_id>22959937</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>11.7</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By NMR. Daily cows fed barley grains (45% of diet dry matter) (n=8)</comment>
      <references>
        <reference>
          <reference_text>Saleem F, Ametaj BN, Bouatra S, Mandal R, Zebeli Q, Dunn SM, Wishart DS: A metabolomics approach to uncover the effects of grain diets on rumen health in dairy cows. J Dairy Sci. 2012 Nov;95(11):6606-23. doi: 10.3168/jds.2012-5403. Epub 2012 Sep 7.</reference_text>
          <pubmed_id>22959937</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>8.8</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By NMR. No barley grains in diet (n=8)</comment>
      <references>
        <reference>
          <reference_text>Saleem F, Ametaj BN, Bouatra S, Mandal R, Zebeli Q, Dunn SM, Wishart DS: A metabolomics approach to uncover the effects of grain diets on rumen health in dairy cows. J Dairy Sci. 2012 Nov;95(11):6606-23. doi: 10.3168/jds.2012-5403. Epub 2012 Sep 7.</reference_text>
          <pubmed_id>22959937</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>8.8</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By NMR. No barley grains in diet (n=8)</comment>
      <references>
        <reference>
          <reference_text>Saleem F, Ametaj BN, Bouatra S, Mandal R, Zebeli Q, Dunn SM, Wishart DS: A metabolomics approach to uncover the effects of grain diets on rumen health in dairy cows. J Dairy Sci. 2012 Nov;95(11):6606-23. doi: 10.3168/jds.2012-5403. Epub 2012 Sep 7.</reference_text>
          <pubmed_id>22959937</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>11 +/- 4</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Samples have been collected from 8 healthy primiparous Holstein cow fed barley grains (15% of diet dry matter). </comment>
      <references>
        <reference>
          <reference_text>Fozia Saleem, Souhaila Bouatra, An Chi Guo, Nikolaos Psychogios, Rupasri Mandal, Suzanna M. Dunn, Burim N. Ametaj, David S. Wishart. The Bovine Ruminal Fluid Metabolome. Metabolomics (2013) 9:360–378.</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>8 +/- 2</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Samples have been collected from 8 healthy primiparous Holstein cow fed barley grains (30% of diet dry matter). </comment>
      <references>
        <reference>
          <reference_text>Fozia Saleem, Souhaila Bouatra, An Chi Guo, Nikolaos Psychogios, Rupasri Mandal, Suzanna M. Dunn, Burim N. Ametaj, David S. Wishart. The Bovine Ruminal Fluid Metabolome. Metabolomics (2013) 9:360–378.</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>12 +/- 4</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Samples have been collected from 8 healthy primiparous Holstein cow fed barley grains (45% of diet dry matter). </comment>
      <references>
        <reference>
          <reference_text>Fozia Saleem, Souhaila Bouatra, An Chi Guo, Nikolaos Psychogios, Rupasri Mandal, Suzanna M. Dunn, Burim N. Ametaj, David S. Wishart. The Bovine Ruminal Fluid Metabolome. Metabolomics (2013) 9:360–378.</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>9 +/- 4</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Samples have been collected from 8 healthy primiparous Holstein cow, no barley grains in diet.</comment>
      <references>
        <reference>
          <reference_text>Fozia Saleem, Souhaila Bouatra, An Chi Guo, Nikolaos Psychogios, Rupasri Mandal, Suzanna M. Dunn, Burim N. Ametaj, David S. Wishart. The Bovine Ruminal Fluid Metabolome. Metabolomics (2013) 9:360–378.</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Semen</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Analysis was performed using GC-MS in Holstein bulls (n = 16). Compound was identified by probable match parameters of the NIST Mass Spectral Search Program</comment>
      <references>
        <reference>
          <reference_text>Velho ALC, Menezes E, Dinh T, Kaya A, Topper E, Moura AA, Memili E: Metabolomic markers of fertility in bull seminal plasma. PLoS One. 2018 Apr 10;13(4):e0195279. doi: 10.1371/journal.pone.0195279. eCollection 2018.</reference_text>
          <pubmed_id>29634739</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Semimembranosus Muscle</biospecimen>
      <concentration_value>220 +/- 76</concentration_value>
      <concentration_units>nmol/g of tissue</concentration_units>
      <comment>By NMR</comment>
      <references>
        <reference>
          <reference_text>Aidin Foroutan, Carolyn Fitzsimmons, Rupasri Mandal, Hamed Piri‐Moghadam, Jiamin Zheng, AnChi Guo, Carin Li, Le Luo Guan and David S. Wishart. The Bovine Metabolome. Metabolites 2020, 10, 233; doi:10.3390/metabo10060233</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Testis</biospecimen>
      <concentration_value>27 +/- 8</concentration_value>
      <concentration_units>nmol/g of tissue</concentration_units>
      <comment>By NMR</comment>
      <references>
        <reference>
          <reference_text>Aidin Foroutan, Carolyn Fitzsimmons, Rupasri Mandal, Hamed Piri‐Moghadam, Jiamin Zheng, AnChi Guo, Carin Li, Le Luo Guan and David S. Wishart. The Bovine Metabolome. Metabolites 2020, 10, 233; doi:10.3390/metabo10060233</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
  </normal_concentrations>
  <kegg_id>C00122</kegg_id>
  <drugbank_id>DB01677</drugbank_id>
  <foodb_id>FDB003291</foodb_id>
  <chemspider_id>10197150</chemspider_id>
  <pubchem_compound_id>444972</pubchem_compound_id>
  <pdbe_id/>
  <chebi_id>18012</chebi_id>
  <knapsack_id>C00001183</knapsack_id>
  <wikipedia_id>Fumaric_Acid</wikipedia_id>
  <meta_cyc_id>FUM</meta_cyc_id>
  <phenol_explorer_compound_id/>
  <bigg_id>33938</bigg_id>
  <metlin_id>3242</metlin_id>
  <synthesis_reference>Dong, Changsheng; Ma, Xinming.  Method for preparation of fumaric acid from the tail gas acid spray solution from oxidation of phthalic anhydride.    Faming Zhuanli Shenqing Gongkai Shuomingshu  (2007),  5pp.</synthesis_reference>
  <general_references>
    <reference>
      <reference_text>Klein MS, Almstetter MF, Schlamberger G, Nurnberger N, Dettmer K, Oefner PJ, Meyer HH, Wiedemann S, Gronwald W: Nuclear magnetic resonance and mass spectrometry-based milk metabolomics in dairy cows during early and late lactation. J Dairy Sci. 2010 Apr;93(4):1539-50. doi: 10.3168/jds.2009-2563.</reference_text>
      <pubmed_id>20338431</pubmed_id>
    </reference>
    <reference>
      <reference_text>Klein MS, Buttchereit N, Miemczyk SP, Immervoll AK, Louis C, Wiedemann S, Junge W, Thaller G, Oefner PJ, Gronwald W: NMR metabolomic analysis of dairy cows reveals milk glycerophosphocholine to phosphocholine ratio as prognostic biomarker for risk of ketosis. J Proteome Res. 2012 Feb 3;11(2):1373-81. doi: 10.1021/pr201017n. Epub 2011 Dec 9.</reference_text>
      <pubmed_id>22098372</pubmed_id>
    </reference>
    <reference>
      <reference_text>Sundekilde UK, Poulsen NA, Larsen LB, Bertram HC: Nuclear magnetic resonance metabonomics reveals strong association between milk metabolites and somatic cell count in bovine milk. J Dairy Sci. 2013 Jan;96(1):290-9. doi: 10.3168/jds.2012-5819. Epub 2012 Nov 22.</reference_text>
      <pubmed_id>23182357</pubmed_id>
    </reference>
    <reference>
      <reference_text>Sundekilde UK, Gustavsson F, Poulsen NA, Glantz M, Paulsson M, Larsen LB, Bertram HC: Association between the bovine milk metabolome and rennet-induced coagulation properties of milk. J Dairy Sci. 2014 Oct;97(10):6076-84. doi: 10.3168/jds.2014-8304. Epub 2014 Jul 30.</reference_text>
      <pubmed_id>25087032</pubmed_id>
    </reference>
    <reference>
      <reference_text>Buitenhuis AJ, Sundekilde UK, Poulsen NA, Bertram HC, Larsen LB, Sorensen P: Estimation of genetic parameters and detection of quantitative trait loci for metabolites in Danish Holstein milk. J Dairy Sci. 2013 May;96(5):3285-95. doi: 10.3168/jds.2012-5914. Epub 2013 Mar 15.</reference_text>
      <pubmed_id>23497994</pubmed_id>
    </reference>
    <reference>
      <reference_text>Scano P, Murgia A, Pirisi FM, Caboni P: A gas chromatography-mass spectrometry-based metabolomic approach for the characterization of goat milk compared with cow milk. J Dairy Sci. 2014 Oct;97(10):6057-66. doi: 10.3168/jds.2014-8247. Epub 2014 Aug 6.</reference_text>
      <pubmed_id>25108860</pubmed_id>
    </reference>
    <reference>
      <reference_text>Maher AD, Hayes B, Cocks B, Marett L, Wales WJ, Rochfort SJ: Latent biochemical relationships in the blood-milk metabolic axis of dairy cows revealed by statistical integration of 1H NMR spectroscopic data. J Proteome Res. 2013 Mar 1;12(3):1428-35. doi: 10.1021/pr301056q. Epub 2013 Feb 21.</reference_text>
      <pubmed_id>23394630</pubmed_id>
    </reference>
    <reference>
      <reference_text>O'Callaghan TF, Vazquez-Fresno R, Serra-Cayuela A, Dong E, Mandal R, Hennessy D, McAuliffe S, Dillon P, Wishart DS, Stanton C, Ross RP: Pasture Feeding Changes the Bovine Rumen and Milk Metabolome. Metabolites. 2018 Apr 6;8(2). pii: metabo8020027. doi: 10.3390/metabo8020027.</reference_text>
      <pubmed_id>29642378</pubmed_id>
    </reference>
    <reference>
      <reference_text>Kurt J. Boudonck, Matthew W. Mitchell, Jacob Wulff and John A. Ryals. Characterization of the biochemical variability of bovine milk using metabolomics. Metabolomics (2009) 5:375?386</reference_text>
    </reference>
    <reference>
      <reference_text>A. Foroutan et al. The Chemical Composition of Commercial Cow's Milk (in preparation)</reference_text>
    </reference>
  </general_references>
  <protein_associations>
    <protein>
      <protein_accession>BMDBP00238</protein_accession>
      <name>Argininosuccinate lyase</name>
      <uniprot_id>Q3SZJ0</uniprot_id>
      <gene_name>ASL</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP00427</protein_accession>
      <name>Fumarylacetoacetase</name>
      <uniprot_id>A5PKH3</uniprot_id>
      <gene_name>FAH</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP00935</protein_accession>
      <name>Adenylosuccinate lyase</name>
      <uniprot_id>A3KN12</uniprot_id>
      <gene_name>ADSL</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP02846</protein_accession>
      <name>Fumarate hydratase</name>
      <uniprot_id>Q148D3</uniprot_id>
      <gene_name>FH</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
  </protein_associations>
</metabolite>
