Integration of the Microbiome, Metabolome and Transcriptome Reveals <i>Escherichia coli</i> F17 Susceptibility of Sheep
<i>Escherichia coli</i> (<i>E. coli</i>) F17 is one of the most common pathogens causing diarrhea in farm livestock. In the previous study, we accessed the transcriptomic and microbiomic profile of <i>E. coli</i> F17-antagonism (AN) and -sensitive (SE) lambs; howe...
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| Format: | Article |
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MDPI AG
2023-03-01
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| Series: | Animals |
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| Online Access: | https://www.mdpi.com/2076-2615/13/6/1050 |
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| author | Weihao Chen Xiaoyang Lv Xiukai Cao Zehu Yuan Shanhe Wang Tesfaye Getachew Joram M. Mwacharo Aynalem Haile Kai Quan Yutao Li Wei Sun |
| author_facet | Weihao Chen Xiaoyang Lv Xiukai Cao Zehu Yuan Shanhe Wang Tesfaye Getachew Joram M. Mwacharo Aynalem Haile Kai Quan Yutao Li Wei Sun |
| author_sort | Weihao Chen |
| collection | DOAJ |
| description | <i>Escherichia coli</i> (<i>E. coli</i>) F17 is one of the most common pathogens causing diarrhea in farm livestock. In the previous study, we accessed the transcriptomic and microbiomic profile of <i>E. coli</i> F17-antagonism (AN) and -sensitive (SE) lambs; however, the biological mechanism underlying <i>E. coli</i> F17 infection has not been fully elucidated. Therefore, the present study first analyzed the metabolite data obtained with UHPLC-MS/MS. A total of 1957 metabolites were profiled in the present study, and 11 differential metabolites were identified between <i>E. coli</i> F17 AN and SE lambs (i.e., FAHFAs and propionylcarnitine). Functional enrichment analyses showed that most of the identified metabolites were related to the lipid metabolism. Then, we presented a machine-learning approach (Random Forest) to integrate the microbiome, metabolome and transcriptome data, which identified subsets of potential biomarkers for <i>E. coli</i> F17 infection (i.e., GlcADG 18:0-18:2, ethylmalonic acid and <i>FBLIM1</i>); furthermore, the PCCs were calculated and the interaction network was constructed to gain insight into the crosstalk between the genes, metabolites and bacteria in <i>E. coli</i> F17 AN/SE lambs. By combing classic statistical approaches and a machine-learning approach, our results revealed subsets of metabolites, genes and bacteria that could be potentially developed as candidate biomarkers for <i>E. coli</i> F17 infection in lambs. |
| first_indexed | 2024-03-11T07:01:21Z |
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| institution | Directory Open Access Journal |
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| language | English |
| last_indexed | 2024-03-11T07:01:21Z |
| publishDate | 2023-03-01 |
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| record_format | Article |
| series | Animals |
| spelling | doaj.art-456aaff07ef147a89a6303e262e427762023-11-17T09:11:40ZengMDPI AGAnimals2076-26152023-03-01136105010.3390/ani13061050Integration of the Microbiome, Metabolome and Transcriptome Reveals <i>Escherichia coli</i> F17 Susceptibility of SheepWeihao Chen0Xiaoyang Lv1Xiukai Cao2Zehu Yuan3Shanhe Wang4Tesfaye Getachew5Joram M. Mwacharo6Aynalem Haile7Kai Quan8Yutao Li9Wei Sun10College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, ChinaJoint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou 225009, ChinaJoint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou 225009, ChinaJoint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou 225009, ChinaCollege of Animal Science and Technology, Yangzhou University, Yangzhou 225009, ChinaInternational Centre for Agricultural Research in the Dry Areas, Addis Ababa 999047, EthiopiaInternational Centre for Agricultural Research in the Dry Areas, Addis Ababa 999047, EthiopiaInternational Centre for Agricultural Research in the Dry Areas, Addis Ababa 999047, EthiopiaCollege of Animal Science and Technology, Henan University of Animal Husbandry and Economics, Zhengzhou 450046, ChinaCSIRO Agriculture and Food, 306 Carmody Rd, St Lucia, QLD 4067, AustraliaCollege of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China<i>Escherichia coli</i> (<i>E. coli</i>) F17 is one of the most common pathogens causing diarrhea in farm livestock. In the previous study, we accessed the transcriptomic and microbiomic profile of <i>E. coli</i> F17-antagonism (AN) and -sensitive (SE) lambs; however, the biological mechanism underlying <i>E. coli</i> F17 infection has not been fully elucidated. Therefore, the present study first analyzed the metabolite data obtained with UHPLC-MS/MS. A total of 1957 metabolites were profiled in the present study, and 11 differential metabolites were identified between <i>E. coli</i> F17 AN and SE lambs (i.e., FAHFAs and propionylcarnitine). Functional enrichment analyses showed that most of the identified metabolites were related to the lipid metabolism. Then, we presented a machine-learning approach (Random Forest) to integrate the microbiome, metabolome and transcriptome data, which identified subsets of potential biomarkers for <i>E. coli</i> F17 infection (i.e., GlcADG 18:0-18:2, ethylmalonic acid and <i>FBLIM1</i>); furthermore, the PCCs were calculated and the interaction network was constructed to gain insight into the crosstalk between the genes, metabolites and bacteria in <i>E. coli</i> F17 AN/SE lambs. By combing classic statistical approaches and a machine-learning approach, our results revealed subsets of metabolites, genes and bacteria that could be potentially developed as candidate biomarkers for <i>E. coli</i> F17 infection in lambs.https://www.mdpi.com/2076-2615/13/6/1050<i>Escherichia coli</i> F17lambmetabolometranscriptomemicrobiomeomics integration |
| spellingShingle | Weihao Chen Xiaoyang Lv Xiukai Cao Zehu Yuan Shanhe Wang Tesfaye Getachew Joram M. Mwacharo Aynalem Haile Kai Quan Yutao Li Wei Sun Integration of the Microbiome, Metabolome and Transcriptome Reveals <i>Escherichia coli</i> F17 Susceptibility of Sheep Animals <i>Escherichia coli</i> F17 lamb metabolome transcriptome microbiome omics integration |
| title | Integration of the Microbiome, Metabolome and Transcriptome Reveals <i>Escherichia coli</i> F17 Susceptibility of Sheep |
| title_full | Integration of the Microbiome, Metabolome and Transcriptome Reveals <i>Escherichia coli</i> F17 Susceptibility of Sheep |
| title_fullStr | Integration of the Microbiome, Metabolome and Transcriptome Reveals <i>Escherichia coli</i> F17 Susceptibility of Sheep |
| title_full_unstemmed | Integration of the Microbiome, Metabolome and Transcriptome Reveals <i>Escherichia coli</i> F17 Susceptibility of Sheep |
| title_short | Integration of the Microbiome, Metabolome and Transcriptome Reveals <i>Escherichia coli</i> F17 Susceptibility of Sheep |
| title_sort | integration of the microbiome metabolome and transcriptome reveals i escherichia coli i f17 susceptibility of sheep |
| topic | <i>Escherichia coli</i> F17 lamb metabolome transcriptome microbiome omics integration |
| url | https://www.mdpi.com/2076-2615/13/6/1050 |
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