<?xml version="1.0" encoding="UTF-8"?>
<metabolite>
  <version>1.0</version>
  <creation_date>2016-09-30 22:19:12 UTC</creation_date>
  <update_date>2020-06-04 22:20:22 UTC</update_date>
  <accession>BMDB0000064</accession>
  <secondary_accessions>
    <accession>BMDB00064</accession>
  </secondary_accessions>
  <name>Creatine</name>
  <description>Creatine, also known as cosmocair C 100 or krebiozon, belongs to the class of organic compounds known as alpha amino acids and derivatives. These are amino acids in which the amino group is attached to the carbon atom immediately adjacent to the carboxylate group (alpha carbon), or a derivative thereof. Creatine is a drug which is used for nutritional supplementation, also for treating dietary shortage or imbalance. Creatine exists as a solid, possibly soluble (in water), and a very strong basic compound (based on its pKa) molecule. Creatine exists in all living organisms, ranging from bacteria to humans. Creatine is a potentially toxic compound.</description>
  <synonyms>
    <synonym>((Amino(imino)methyl)(methyl)amino)acetic acid</synonym>
    <synonym>(alpha-Methylguanido)acetic acid</synonym>
    <synonym>(N-Methylcarbamimidamido)acetic acid</synonym>
    <synonym>alpha-Methylguanidino acetic acid</synonym>
    <synonym>Creatin</synonym>
    <synonym>Kreatin</synonym>
    <synonym>Methylglycocyamine</synonym>
    <synonym>N-(Aminoiminomethyl)-N-methylglycine</synonym>
    <synonym>N-[(e)-AMINO(imino)methyl]-N-methylglycine</synonym>
    <synonym>N-Amidinosarcosine</synonym>
    <synonym>N-Carbamimidoyl-N-methylglycine</synonym>
    <synonym>N-Methyl-N-guanylglycine</synonym>
    <synonym>((Amino(imino)methyl)(methyl)amino)acetate</synonym>
    <synonym>(a-Methylguanido)acetate</synonym>
    <synonym>(a-Methylguanido)acetic acid</synonym>
    <synonym>(alpha-Methylguanido)acetate</synonym>
    <synonym>(Α-methylguanido)acetate</synonym>
    <synonym>(Α-methylguanido)acetic acid</synonym>
    <synonym>(N-Methylcarbamimidamido)acetate</synonym>
    <synonym>a-Methylguanidino acetate</synonym>
    <synonym>a-Methylguanidino acetic acid</synonym>
    <synonym>alpha-Methylguanidino acetate</synonym>
    <synonym>Α-methylguanidino acetate</synonym>
    <synonym>Α-methylguanidino acetic acid</synonym>
    <synonym>Cosmocair C 100</synonym>
    <synonym>Creatine hydrate</synonym>
    <synonym>Krebiozon</synonym>
    <synonym>Methylguanidoacetate</synonym>
    <synonym>Methylguanidoacetic acid</synonym>
    <synonym>N-(Aminoiminomethyl)-N-methyl-glycine</synonym>
    <synonym>Phosphagen</synonym>
    <synonym>[[Amino(imino)methyl](methyl)amino]acetate</synonym>
    <synonym>[[Amino(imino)methyl](methyl)amino]acetic acid</synonym>
  </synonyms>
  <chemical_formula>C4H9N3O2</chemical_formula>
  <average_molecular_weight>131.1332</average_molecular_weight>
  <monisotopic_moleculate_weight>131.069476547</monisotopic_moleculate_weight>
  <iupac_name>2-(N-methylcarbamimidamido)acetic acid</iupac_name>
  <traditional_iupac>creatine</traditional_iupac>
  <cas_registry_number>57-00-1</cas_registry_number>
  <smiles>CN(CC(O)=O)C(N)=N</smiles>
  <inchi>InChI=1S/C4H9N3O2/c1-7(4(5)6)2-3(8)9/h2H2,1H3,(H3,5,6)(H,8,9)</inchi>
  <inchikey>CVSVTCORWBXHQV-UHFFFAOYSA-N</inchikey>
  <taxonomy>
    <description> belongs to the class of organic compounds known as alpha amino acids and derivatives. These are amino acids in which the amino group is attached to the carbon atom immediately adjacent to the carboxylate group (alpha carbon), or a derivative thereof.</description>
    <kingdom>Organic compounds</kingdom>
    <super_class>Organic acids and derivatives</super_class>
    <class>Carboxylic acids and derivatives</class>
    <sub_class>Amino acids, peptides, and analogues</sub_class>
    <direct_parent>Alpha amino acids and derivatives</direct_parent>
    <alternative_parents>
      <alternative_parent>Carbonyl compounds</alternative_parent>
      <alternative_parent>Carboximidamides</alternative_parent>
      <alternative_parent>Carboxylic acids</alternative_parent>
      <alternative_parent>Guanidines</alternative_parent>
      <alternative_parent>Hydrocarbon derivatives</alternative_parent>
      <alternative_parent>Imines</alternative_parent>
      <alternative_parent>Monocarboxylic acids and derivatives</alternative_parent>
      <alternative_parent>Organic oxides</alternative_parent>
      <alternative_parent>Organopnictogen compounds</alternative_parent>
    </alternative_parents>
    <substituents>
      <substituent>Aliphatic acyclic compound</substituent>
      <substituent>Alpha-amino acid or derivatives</substituent>
      <substituent>Carbonyl group</substituent>
      <substituent>Carboximidamide</substituent>
      <substituent>Carboxylic acid</substituent>
      <substituent>Guanidine</substituent>
      <substituent>Hydrocarbon derivative</substituent>
      <substituent>Imine</substituent>
      <substituent>Monocarboxylic acid or derivatives</substituent>
      <substituent>Organic nitrogen compound</substituent>
      <substituent>Organic oxide</substituent>
      <substituent>Organic oxygen compound</substituent>
      <substituent>Organonitrogen compound</substituent>
      <substituent>Organooxygen compound</substituent>
      <substituent>Organopnictogen compound</substituent>
    </substituents>
    <molecular_framework>Aliphatic acyclic compounds</molecular_framework>
    <external_descriptors>
      <external_descriptor>glycine derivative</external_descriptor>
      <external_descriptor>guanidines</external_descriptor>
    </external_descriptors>
  </taxonomy>
  <experimental_properties>
    <state>Solid</state>
    <property>
      <kind>melting_point</kind>
      <value>303 °C</value>
      <source/>
    </property>
    <property>
      <kind>water_solubility</kind>
      <value>13.3 mg/mL at 18 °C</value>
      <source/>
    </property>
  </experimental_properties>
  <predicted_properties>
    <property>
      <kind>logp</kind>
      <value>-1.59</value>
      <source>ALOGPS</source>
    </property>
    <property>
      <kind>logs</kind>
      <value>-1.50</value>
      <source>ALOGPS</source>
    </property>
    <property>
      <kind>logp</kind>
      <value>-2.9</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>pka_strongest_acidic</kind>
      <value>3.5</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>pka_strongest_basic</kind>
      <value>12.43</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>iupac</kind>
      <value>2-(N-methylcarbamimidamido)acetic acid</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>average_mass</kind>
      <value>131.1332</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>mono_mass</kind>
      <value>131.069476547</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>smiles</kind>
      <value>CN(CC(O)=O)C(N)=N</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>formula</kind>
      <value>C4H9N3O2</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>inchi</kind>
      <value>InChI=1S/C4H9N3O2/c1-7(4(5)6)2-3(8)9/h2H2,1H3,(H3,5,6)(H,8,9)</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>inchikey</kind>
      <value>CVSVTCORWBXHQV-UHFFFAOYSA-N</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>polar_surface_area</kind>
      <value>90.41</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>refractivity</kind>
      <value>42.01</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>polarizability</kind>
      <value>12.17</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>rotatable_bond_count</kind>
      <value>2</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>acceptor_count</kind>
      <value>5</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>donor_count</kind>
      <value>3</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>physiological_charge</kind>
      <value>0</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>Glycine and Serine Metabolism</name>
      <smpdb_id>SMP0087245</smpdb_id>
      <kegg_map_id/>
    </pathway>
  </pathways>
  <spectra>
    <spectrum>
      <type>Specdb::EiMs</type>
      <spectrum_id>1033</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>23236</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>31772</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>31773</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>37276</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>99530</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>99531</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>136709</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>144443</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>1049519</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>1049521</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>1049523</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>1049525</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>1049526</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsIr</type>
      <spectrum_id>138</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsIr</type>
      <spectrum_id>139</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsIr</type>
      <spectrum_id>140</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrTwoD</type>
      <spectrum_id>948</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrTwoD</type>
      <spectrum_id>1122</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>1064</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142010</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142011</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142012</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142013</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142014</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142015</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142016</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142017</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142018</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142019</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142020</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142021</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142022</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142023</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142024</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142025</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142026</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142027</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142028</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>142029</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>105</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>106</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>107</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2716</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2717</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2718</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2719</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2720</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2721</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2722</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2723</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2724</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2725</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2726</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2727</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2728</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2729</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2730</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2731</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2732</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2733</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2734</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2735</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2736</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2737</spectrum_id>
    </spectrum>
  </spectra>
  <normal_concentrations>
    <concentration>
      <biospecimen>Adipose 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>Bladder</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>Blood</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Detected by NMR in lactating Holstein cows.</comment>
      <references>
        <reference>
          <reference_text>Tian H, Wang W, Zheng N, Cheng J, Li S, Zhang Y, Wang J: Identification of diagnostic biomarkers and metabolic pathway shifts of heat-stressed lactating dairy cows. J Proteomics. 2015 Jul 1;125:17-28. doi: 10.1016/j.jprot.2015.04.014. Epub 2015 Apr 22.</reference_text>
          <pubmed_id>25913299</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Blood</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Detected by NMR in multiparous-early lactation Holstein cows.</comment>
      <references>
        <reference>
          <reference_text>Sun LW, Zhang HY, Wu L, Shu S, Xia C, Xu C, Zheng JS: (1)H-Nuclear magnetic resonance-based plasma metabolic profiling of dairy cows with clinical and subclinical ketosis. J Dairy Sci. 2014 Mar;97(3):1552-62. doi: 10.3168/jds.2013-6757. Epub 2014 Jan 17.</reference_text>
          <pubmed_id>24440255</pubmed_id>
        </reference>
      </references>
    </concentration>
    <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>189.883-542.197</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Detected by procedure of Folin and Wu (1919)</comment>
      <references>
        <reference>
          <reference_text>Arthur K. Anderson, Howard E. Gayley, Avery D. Pratt. Studies on the Chemical Composition of Bovine Blood. J. Dairy Science (1930) 13(4):336-348   doi: 10.3168/jds.S0022-0302(30)93530-8</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Blood</biospecimen>
      <concentration_value>196 +/- 28</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By LC-MS/MS &amp; 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>Blood</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Detected by NMR</comment>
      <references>
        <reference>
          <reference_text>De Buck J, Shaykhutdinov R, Barkema HW, Vogel HJ: Metabolomic profiling in cattle experimentally infected with Mycobacterium avium subsp. paratuberculosis. PLoS One. 2014 Nov 5;9(11):e111872. doi: 10.1371/journal.pone.0111872. eCollection 2014.</reference_text>
          <pubmed_id>25372282</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Brain</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>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>Epidermis</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>Fibroblasts</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>Heart</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>Intestine</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>Kidney</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>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>1321 +/- 464</concentration_value>
      <concentration_units>nmol/g of tissue</concentration_units>
      <comment>By LC-MS/MS &amp; 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>4672 +/- 438</concentration_value>
      <concentration_units>nmol/g of tissue</concentration_units>
      <comment>By LC-MS/MS &amp; 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>491 +/- 40</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>537 +/- 30</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>534 +/- 16</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>510 +/- 42</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>432.95 +/- 84.67</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>427.70 +/- 115.63</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>Milk samples collected from 16 multiparous Holstein cows </comment>
      <references>
        <reference>
          <reference_text>Sun HZ, Wang DM, Wang B, Wang JK, Liu HY, Guan le L, Liu JX: Metabolomics of four biofluids from dairy cows: potential biomarkers for milk production and quality. J Proteome Res. 2015 Feb 6;14(2):1287-98. doi: 10.1021/pr501305g. Epub 2015 Jan 28.</reference_text>
          <pubmed_id>25599412</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>436.42 +/- 79.99</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>Muscle</biospecimen>
      <concentration_value>10147.92 +/- 171.42</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/>
      <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>6100 +/- 2670</concentration_value>
      <concentration_units>nmol/g of tissue</concentration_units>
      <comment>Detected by NMR in beef muscle (longissimus dorsi) matured for 14 days.</comment>
      <references>
        <reference>
          <reference_text>S. F. Graham, T. Kennedy, O. Chevallier, A. Gordon, L. Farmer, C. Elliott, B. Moss. The application of NMR to study changes in polar metabolite concentrations in beef longissimus dorsi stored for different periods post mortem. Metabolomics (2010) 6:395-404   doi: 10.1007/s11306-010-0206-y</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Muscle</biospecimen>
      <concentration_value>91980 +/- 5880</concentration_value>
      <concentration_units>nmol/g of tissue</concentration_units>
      <comment>Detected by NMR in beef muscle (longissimus dorsi) matured for 21 days.</comment>
      <references>
        <reference>
          <reference_text>S. F. Graham, T. Kennedy, O. Chevallier, A. Gordon, L. Farmer, C. Elliott, B. Moss. The application of NMR to study changes in polar metabolite concentrations in beef longissimus dorsi stored for different periods post mortem. Metabolomics (2010) 6:395-404   doi: 10.1007/s11306-010-0206-y</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Muscle</biospecimen>
      <concentration_value>86620 +/- 4690</concentration_value>
      <concentration_units>nmol/g of tissue</concentration_units>
      <comment>Detected by NMR in beef muscle (longissimus dorsi) matured for 3 days.</comment>
      <references>
        <reference>
          <reference_text>S. F. Graham, T. Kennedy, O. Chevallier, A. Gordon, L. Farmer, C. Elliott, B. Moss. The application of NMR to study changes in polar metabolite concentrations in beef longissimus dorsi stored for different periods post mortem. Metabolomics (2010) 6:395-404   doi: 10.1007/s11306-010-0206-y</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Muscle</biospecimen>
      <concentration_value>83850 +/- 4340</concentration_value>
      <concentration_units>nmol/g of tissue</concentration_units>
      <comment>Detected by NMR in beef muscle (longissimus dorsi) matured for 7 days.</comment>
      <references>
        <reference>
          <reference_text>S. F. Graham, T. Kennedy, O. Chevallier, A. Gordon, L. Farmer, C. Elliott, B. Moss. The application of NMR to study changes in polar metabolite concentrations in beef longissimus dorsi stored for different periods post mortem. Metabolomics (2010) 6:395-404   doi: 10.1007/s11306-010-0206-y</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Muscle</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Detected by NMR in beef muscle (longissimus dorsi).</comment>
      <references>
        <reference>
          <reference_text>S. F. Graham, T. Kennedy, O. Chevallier, A. Gordon, L. Farmer, C. Elliott, B. Moss. The application of NMR to study changes in polar metabolite concentrations in beef longissimus dorsi stored for different periods post mortem. Metabolomics (2010) 6:395-404   doi: 10.1007/s11306-010-0206-y</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Muscle</biospecimen>
      <concentration_value>7262-10319</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>21000</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>7752.34 +/- 490.5</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>8768.14 +/- 196.21</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>8769.99 +/- 413.59</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>1040-1520</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>Muscle</biospecimen>
      <concentration_value>19488-27111</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>Neuron</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>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>Platelet</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>2-15</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By 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>Ruminal Fluid</biospecimen>
      <concentration_value>3 +/- 4</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By LC-MS/MS &amp; 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/>
      <concentration_units/>
      <comment>Detected by NMR in male Holstein cows.</comment>
      <references>
        <reference>
          <reference_text>Hanne Christine Bertram, Niels Bastian Kristensen, Mogens Vestergaard, SÃ¸ren Krogh Jensen, Jakob Sehested, Niels Christian Nielsen, Anders Malmendal. Metabolic characterization of rumen epithelial tissue from dairy calves fed different starter diets using 1H NMR spectroscopy. Livestock Science (2008) 120:127-134   doi: 10.1016/j.livsci.2008.05.001</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Semimembranosus Muscle</biospecimen>
      <concentration_value>4755 +/- 306</concentration_value>
      <concentration_units>nmol/g of tissue</concentration_units>
      <comment>By LC-MS/MS &amp; 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>Spleen</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>Testis</biospecimen>
      <concentration_value>7553 +/- 1850</concentration_value>
      <concentration_units>nmol/g of tissue</concentration_units>
      <comment>By LC-MS/MS &amp; 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>C00300</kegg_id>
  <drugbank_id>DB00148</drugbank_id>
  <chemspider_id>566</chemspider_id>
  <foodb_id>FDB005403</foodb_id>
  <pdbe_id/>
  <chebi_id>16919</chebi_id>
  <pubchem_compound_id>586</pubchem_compound_id>
  <knapsack_id/>
  <meta_cyc_id>CREATINE</meta_cyc_id>
  <wikipedia_id>Creatine</wikipedia_id>
  <phenol_explorer_compound_id/>
  <bigg_id>34543</bigg_id>
  <metlin_id>7</metlin_id>
  <synthesis_reference>Thalhammer, Franz; Gastner, Thomas.  Preparation of creatine, creatine monohydrate and guanidinoacetic acid.    Ger. Offen.  (2007),     5pp.</synthesis_reference>
  <general_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>
    <reference>
      <reference_text>Sun HZ, Wang DM, Wang B, Wang JK, Liu HY, Guan le L, Liu JX: Metabolomics of four biofluids from dairy cows: potential biomarkers for milk production and quality. J Proteome Res. 2015 Feb 6;14(2):1287-98. doi: 10.1021/pr501305g. Epub 2015 Jan 28.</reference_text>
      <pubmed_id>25599412</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>A. Foroutan et al. The Chemical Composition of Commercial Cow's Milk (in preparation)</reference_text>
    </reference>
  </general_references>
  <protein_associations>
    <protein>
      <protein_accession>BMDBP00255</protein_accession>
      <name>Creatine kinase S-type, mitochondrial</name>
      <uniprot_id>Q3ZBP1</uniprot_id>
      <gene_name>CKMT2</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP00256</protein_accession>
      <name>Creatine kinase B-type</name>
      <uniprot_id>Q5EA61</uniprot_id>
      <gene_name>CKB</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP00257</protein_accession>
      <name>Creatine kinase U-type, mitochondrial</name>
      <uniprot_id>Q9TTK8</uniprot_id>
      <gene_name>CKMT1</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP00258</protein_accession>
      <name>Creatine kinase M-type</name>
      <uniprot_id>Q9XSC6</uniprot_id>
      <gene_name>CKM</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP00412</protein_accession>
      <name>Guanidinoacetate N-methyltransferase</name>
      <uniprot_id>Q2TBQ3</uniprot_id>
      <gene_name>GAMT</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP01895</protein_accession>
      <name>DNA-binding protein inhibitor ID-3</name>
      <uniprot_id>Q5E981</uniprot_id>
      <gene_name>ID3</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP01896</protein_accession>
      <name>Sodium- and chloride-dependent creatine transporter 1</name>
      <uniprot_id>O18875</uniprot_id>
      <gene_name>SLC6A8</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
  </protein_associations>
</metabolite>
