Metabolomic profiling of forages to identify anti-methanogenic compounds targeting enteric methane for sustainable livestock systems

Objective. Ruminant methane (CH₄) emissions are a major contributor to global greenhouse gas levels, highlighting the urgent need for sustainable mitigation strategies. This study, conducted as part of the Anti-Methanogenic Feedstock for Livestock Systems in the Global South project led by CIAT, aim...

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Autores principales: Clavijo-Buriticá, Diana Carolina, Vélez, Gabriel, Chaura, Juliana, Riccio, Camila, Lara, Gustavo, Villegas, Julián, Marin Gomez, Alejandra, Makkar, Harinder, Arango, Jacobo, Jaramillo-Botero, Andrés
Formato: Póster
Lenguaje:Inglés
Publicado: 2025
Materias:
Acceso en línea:https://hdl.handle.net/10568/177290
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author Clavijo-Buriticá, Diana Carolina
Vélez, Gabriel
Chaura, Juliana
Riccio, Camila
Lara, Gustavo
Villegas, Julián
Marin Gomez, Alejandra
Makkar, Harinder
Arango, Jacobo
Jaramillo-Botero, Andrés
author_browse Arango, Jacobo
Chaura, Juliana
Clavijo-Buriticá, Diana Carolina
Jaramillo-Botero, Andrés
Lara, Gustavo
Makkar, Harinder
Marin Gomez, Alejandra
Riccio, Camila
Villegas, Julián
Vélez, Gabriel
author_facet Clavijo-Buriticá, Diana Carolina
Vélez, Gabriel
Chaura, Juliana
Riccio, Camila
Lara, Gustavo
Villegas, Julián
Marin Gomez, Alejandra
Makkar, Harinder
Arango, Jacobo
Jaramillo-Botero, Andrés
author_sort Clavijo-Buriticá, Diana Carolina
collection Repository of Agricultural Research Outputs (CGSpace)
description Objective. Ruminant methane (CH₄) emissions are a major contributor to global greenhouse gas levels, highlighting the urgent need for sustainable mitigation strategies. This study, conducted as part of the Anti-Methanogenic Feedstock for Livestock Systems in the Global South project led by CIAT, aims to identify anti-methanogenic compounds (AMCs) in forages using an integrative metabolomics approach combined with in vitro CH₄ production assays. Identifying AMCs in livestock feed can support CH₄ mitigation—through selection or genetic optimization—while maintaining animal productivity. Methods. We employ advanced normalized untargeted metabolomics, specifically LC/MS-based techniques (liquid chromatography coupled with mass spectrometry), in conjunction with in vitro emissions data, to identify molecular targets with methane-reducing potential. To pinpoint relevant AMCs, we apply statistical analyses, unsupervised classification, and differential analysis of metabolomic profiles from contrasting high- and low-CH₄-producing samples. This enables the identification of under- or over-expressed metabolites (by mass) associated with methanogenic activity. A critical step in this process is the structural and functional annotation of individual compounds, inferred from LC/MS mass spectra. However, only a small fraction (~5–6%) of the compounds in these forage samples have been structurally resolved and annotated in public databases. To address this bottleneck, we have developed a machine-learning-based pipeline to predict, validate, and identify previously uncharacterized metabolites. This involves: predicting potential molecular structures that match the experimental mass spectra using a trained neural network; generating in silico single-electron impact MS for each predicted structure; and comparing the predicted spectra with the experimental data using dot-product similarity scoring to confirm the best structural matches. We are currently testing and refining this tool to improve the fraction of fully resolved compounds in our forage metabolite database. Progress in the development and application of this pipeline will be reported during this session. Results. Preliminary results from the analysis of three forage species—Leucaena diversifolia, Cratylia argentea, and Urochloa humidicola—revealed different flavonoids and saponins previously reported in the literature as AMCs. Notably, Leucaena diversifolia exhibited high flavonoid levels, which correlated with reduced in vitro CH₄ production, positioning it as a promising candidate for further study. Additionally, across these three species, we found that lyophilization significantly enhances the preservation of volatile and thermolabile metabolites compared to heat-drying, as evidenced by higher peak intensities in the mass spectra (p < 0.05). To broaden the search space across plant families, species, phenotypes, and potential AMCs, we have obtained LC/MS data from 26 samples representing 13 forage species, collected from three CGIAR centers: ICARDA, ILRI, and CIAT. Within the species Trifolium, Leucaena, Erythrina, Panicum, Stylosanthes, Lathyrus, Vicia, Desmodium, Chloris, Cenchrus, Flemingia, Cajanus, and Hedysarum, we selected sample pairs with contrasting CH₄ production profiles. In this talk, we will present a list of metabolites identified in these forages, associated with either positive or negative methanogenic activity. Implications. We expect this comprehensive approach will guide the development of forage-based feeding strategies and gene-edited forage varieties, ultimately contributing to sustainable livestock systems and addressing the dual challenges of climate change and food security in the Global South and beyond.
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spelling CGSpace1772902025-11-05T11:31:40Z Metabolomic profiling of forages to identify anti-methanogenic compounds targeting enteric methane for sustainable livestock systems Clavijo-Buriticá, Diana Carolina Vélez, Gabriel Chaura, Juliana Riccio, Camila Lara, Gustavo Villegas, Julián Marin Gomez, Alejandra Makkar, Harinder Arango, Jacobo Jaramillo-Botero, Andrés emission reduction reducción de emisiones metabolomics genetic markers methane emission forage species especie forrajera emisión de metano in vitro selection metaboloma selección in vitro Objective. Ruminant methane (CH₄) emissions are a major contributor to global greenhouse gas levels, highlighting the urgent need for sustainable mitigation strategies. This study, conducted as part of the Anti-Methanogenic Feedstock for Livestock Systems in the Global South project led by CIAT, aims to identify anti-methanogenic compounds (AMCs) in forages using an integrative metabolomics approach combined with in vitro CH₄ production assays. Identifying AMCs in livestock feed can support CH₄ mitigation—through selection or genetic optimization—while maintaining animal productivity. Methods. We employ advanced normalized untargeted metabolomics, specifically LC/MS-based techniques (liquid chromatography coupled with mass spectrometry), in conjunction with in vitro emissions data, to identify molecular targets with methane-reducing potential. To pinpoint relevant AMCs, we apply statistical analyses, unsupervised classification, and differential analysis of metabolomic profiles from contrasting high- and low-CH₄-producing samples. This enables the identification of under- or over-expressed metabolites (by mass) associated with methanogenic activity. A critical step in this process is the structural and functional annotation of individual compounds, inferred from LC/MS mass spectra. However, only a small fraction (~5–6%) of the compounds in these forage samples have been structurally resolved and annotated in public databases. To address this bottleneck, we have developed a machine-learning-based pipeline to predict, validate, and identify previously uncharacterized metabolites. This involves: predicting potential molecular structures that match the experimental mass spectra using a trained neural network; generating in silico single-electron impact MS for each predicted structure; and comparing the predicted spectra with the experimental data using dot-product similarity scoring to confirm the best structural matches. We are currently testing and refining this tool to improve the fraction of fully resolved compounds in our forage metabolite database. Progress in the development and application of this pipeline will be reported during this session. Results. Preliminary results from the analysis of three forage species—Leucaena diversifolia, Cratylia argentea, and Urochloa humidicola—revealed different flavonoids and saponins previously reported in the literature as AMCs. Notably, Leucaena diversifolia exhibited high flavonoid levels, which correlated with reduced in vitro CH₄ production, positioning it as a promising candidate for further study. Additionally, across these three species, we found that lyophilization significantly enhances the preservation of volatile and thermolabile metabolites compared to heat-drying, as evidenced by higher peak intensities in the mass spectra (p < 0.05). To broaden the search space across plant families, species, phenotypes, and potential AMCs, we have obtained LC/MS data from 26 samples representing 13 forage species, collected from three CGIAR centers: ICARDA, ILRI, and CIAT. Within the species Trifolium, Leucaena, Erythrina, Panicum, Stylosanthes, Lathyrus, Vicia, Desmodium, Chloris, Cenchrus, Flemingia, Cajanus, and Hedysarum, we selected sample pairs with contrasting CH₄ production profiles. In this talk, we will present a list of metabolites identified in these forages, associated with either positive or negative methanogenic activity. Implications. We expect this comprehensive approach will guide the development of forage-based feeding strategies and gene-edited forage varieties, ultimately contributing to sustainable livestock systems and addressing the dual challenges of climate change and food security in the Global South and beyond. 2025-10-06 2025-10-23T13:11:00Z 2025-10-23T13:11:00Z Poster https://hdl.handle.net/10568/177290 en Open Access application/pdf Clavijo-Buriticá, D.C.; Vélez, G.; Chaura, J.; Riccio, C.; Lara, G.; Villegas, J.; Marin Gomez, A.; Makkar, H.; Arango, J.; Jaramillo-Botero, A. (2025) Metabolomic profiling of forages to identify anti-methanogenic compounds targeting enteric methane for sustainable livestock systems. Presented at the 9th International Greenhouse Gas and Animal Agriculture Conference (GGAA2025) on 5-9 October 2025 in Nairobi (Kenya). 1 p.
spellingShingle emission reduction
reducción de emisiones
metabolomics
genetic markers
methane emission
forage species
especie forrajera
emisión de metano
in vitro selection
metaboloma
selección in vitro
Clavijo-Buriticá, Diana Carolina
Vélez, Gabriel
Chaura, Juliana
Riccio, Camila
Lara, Gustavo
Villegas, Julián
Marin Gomez, Alejandra
Makkar, Harinder
Arango, Jacobo
Jaramillo-Botero, Andrés
Metabolomic profiling of forages to identify anti-methanogenic compounds targeting enteric methane for sustainable livestock systems
title Metabolomic profiling of forages to identify anti-methanogenic compounds targeting enteric methane for sustainable livestock systems
title_full Metabolomic profiling of forages to identify anti-methanogenic compounds targeting enteric methane for sustainable livestock systems
title_fullStr Metabolomic profiling of forages to identify anti-methanogenic compounds targeting enteric methane for sustainable livestock systems
title_full_unstemmed Metabolomic profiling of forages to identify anti-methanogenic compounds targeting enteric methane for sustainable livestock systems
title_short Metabolomic profiling of forages to identify anti-methanogenic compounds targeting enteric methane for sustainable livestock systems
title_sort metabolomic profiling of forages to identify anti methanogenic compounds targeting enteric methane for sustainable livestock systems
topic emission reduction
reducción de emisiones
metabolomics
genetic markers
methane emission
forage species
especie forrajera
emisión de metano
in vitro selection
metaboloma
selección in vitro
url https://hdl.handle.net/10568/177290
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