Sustainable Food Waste Management in Anaerobic Digesters: Prediction of the Organic Load Impact by Metagenome-Scale Metabolic Modeling

Autores
Orellana, Esteban; Zampieri, Guido; De Bernardini, Nicola; Guerrero, Leandro Demián; Erijman, Leonardo; Campanaro, Stefano; Treu, Laura
Año de publicación
2025
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The increasing urbanization has led to rising waste and energy demands, necessitating innovative solutions. A sustainable food waste management approach involves anaerobic codigestion with sewage sludge, enhancing biogas production while managing waste. Although this technology has been successfully tested, the biological mechanisms determining its efficiency are still poorly understood. This study leverages genome-scale metabolic modeling of 138 metagenome-assembled genomes to explore species interactions in lab-scale anaerobic reactors fed with sewage sludge to increasing proportions of food waste. The models showed positive correlations with experimental biogas production (CH4: r = 0.54, CO2: r = 0.66), validating their reliability. The dominant methanogen, Methanothrix sp., adapted its metabolism based on feedstock, affecting methane yields, which ranged from 2.5 to 3 mmol/g of volatile solids·h with sewage sludge to 10–14 mmol/g of VS·h with high food waste. The integration of extracellular enzymes into the models highlighted the role in methane production of pectin degradation, protein hydrolysis, and lipid metabolism, mediated by Proteiniphilum sp., Kiritimatiellae sp., and Olb16 sp. The study identified 475 mutualistic interactions involving amino acid, hydrogen, acetate, and phosphate exchange and 44 competitive interactions in hydrolytic and fermentative processes. These insights can help optimize anaerobic digestion and sustainable waste management in urban settings.
Fil: Orellana, Esteban. Universita Di Padova. Dipartimento Di Biología; Italia. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; Argentina
Fil: Zampieri, Guido. Universita Di Padova. Dipartimento Di Biología; Italia
Fil: De Bernardini, Nicola. Universita Di Padova. Dipartimento Di Biología; Italia
Fil: Guerrero, Leandro Demián. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; Argentina
Fil: Erijman, Leonardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; Argentina
Fil: Campanaro, Stefano. Universita Di Padova. Dipartimento Di Biología; Italia
Fil: Treu, Laura. Universita Di Padova. Dipartimento Di Biología; Italia
Materia
metabolic modeling
metagenomics
anaerobic codigestion
flux balance analysis
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/275429
Acceder
id CONICETDig_c59f5b67ce802a3e2302096c3e5ab272
oai_identifier_str oai:ri.conicet.gov.ar:11336/275429
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Sustainable Food Waste Management in Anaerobic Digesters: Prediction of the Organic Load Impact by Metagenome-Scale Metabolic ModelingOrellana, EstebanZampieri, GuidoDe Bernardini, NicolaGuerrero, Leandro DemiánErijman, LeonardoCampanaro, StefanoTreu, Laurametabolic modelingmetagenomicsanaerobic codigestionflux balance analysishttps://purl.org/becyt/ford/2.8https://purl.org/becyt/ford/2The increasing urbanization has led to rising waste and energy demands, necessitating innovative solutions. A sustainable food waste management approach involves anaerobic codigestion with sewage sludge, enhancing biogas production while managing waste. Although this technology has been successfully tested, the biological mechanisms determining its efficiency are still poorly understood. This study leverages genome-scale metabolic modeling of 138 metagenome-assembled genomes to explore species interactions in lab-scale anaerobic reactors fed with sewage sludge to increasing proportions of food waste. The models showed positive correlations with experimental biogas production (CH4: r = 0.54, CO2: r = 0.66), validating their reliability. The dominant methanogen, Methanothrix sp., adapted its metabolism based on feedstock, affecting methane yields, which ranged from 2.5 to 3 mmol/g of volatile solids·h with sewage sludge to 10–14 mmol/g of VS·h with high food waste. The integration of extracellular enzymes into the models highlighted the role in methane production of pectin degradation, protein hydrolysis, and lipid metabolism, mediated by Proteiniphilum sp., Kiritimatiellae sp., and Olb16 sp. The study identified 475 mutualistic interactions involving amino acid, hydrogen, acetate, and phosphate exchange and 44 competitive interactions in hydrolytic and fermentative processes. These insights can help optimize anaerobic digestion and sustainable waste management in urban settings.Fil: Orellana, Esteban. Universita Di Padova. Dipartimento Di Biología; Italia. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; ArgentinaFil: Zampieri, Guido. Universita Di Padova. Dipartimento Di Biología; ItaliaFil: De Bernardini, Nicola. Universita Di Padova. Dipartimento Di Biología; ItaliaFil: Guerrero, Leandro Demián. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; ArgentinaFil: Erijman, Leonardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; ArgentinaFil: Campanaro, Stefano. Universita Di Padova. Dipartimento Di Biología; ItaliaFil: Treu, Laura. Universita Di Padova. Dipartimento Di Biología; ItaliaAmerican Chemical Society2025-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/275429Orellana, Esteban; Zampieri, Guido; De Bernardini, Nicola; Guerrero, Leandro Demián; Erijman, Leonardo; et al.; Sustainable Food Waste Management in Anaerobic Digesters: Prediction of the Organic Load Impact by Metagenome-Scale Metabolic Modeling; American Chemical Society; Environmental Science & Technology; 59; 13; 3-2025; 6659-66720013-936XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://pubs.acs.org/doi/10.1021/acs.est.4c11180info:eu-repo/semantics/altIdentifier/doi/10.1021/acs.est.4c11180info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-12-03T08:51:27Zoai:ri.conicet.gov.ar:11336/275429instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-12-03 08:51:28.178CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Sustainable Food Waste Management in Anaerobic Digesters: Prediction of the Organic Load Impact by Metagenome-Scale Metabolic Modeling
title Sustainable Food Waste Management in Anaerobic Digesters: Prediction of the Organic Load Impact by Metagenome-Scale Metabolic Modeling
spellingShingle Sustainable Food Waste Management in Anaerobic Digesters: Prediction of the Organic Load Impact by Metagenome-Scale Metabolic Modeling
Orellana, Esteban
metabolic modeling
metagenomics
anaerobic codigestion
flux balance analysis
title_short Sustainable Food Waste Management in Anaerobic Digesters: Prediction of the Organic Load Impact by Metagenome-Scale Metabolic Modeling
title_full Sustainable Food Waste Management in Anaerobic Digesters: Prediction of the Organic Load Impact by Metagenome-Scale Metabolic Modeling
title_fullStr Sustainable Food Waste Management in Anaerobic Digesters: Prediction of the Organic Load Impact by Metagenome-Scale Metabolic Modeling
title_full_unstemmed Sustainable Food Waste Management in Anaerobic Digesters: Prediction of the Organic Load Impact by Metagenome-Scale Metabolic Modeling
title_sort Sustainable Food Waste Management in Anaerobic Digesters: Prediction of the Organic Load Impact by Metagenome-Scale Metabolic Modeling
dc.creator.none.fl_str_mv Orellana, Esteban
Zampieri, Guido
De Bernardini, Nicola
Guerrero, Leandro Demián
Erijman, Leonardo
Campanaro, Stefano
Treu, Laura
author Orellana, Esteban
author_facet Orellana, Esteban
Zampieri, Guido
De Bernardini, Nicola
Guerrero, Leandro Demián
Erijman, Leonardo
Campanaro, Stefano
Treu, Laura
author_role author
author2 Zampieri, Guido
De Bernardini, Nicola
Guerrero, Leandro Demián
Erijman, Leonardo
Campanaro, Stefano
Treu, Laura
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv metabolic modeling
metagenomics
anaerobic codigestion
flux balance analysis
topic metabolic modeling
metagenomics
anaerobic codigestion
flux balance analysis
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.8
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv The increasing urbanization has led to rising waste and energy demands, necessitating innovative solutions. A sustainable food waste management approach involves anaerobic codigestion with sewage sludge, enhancing biogas production while managing waste. Although this technology has been successfully tested, the biological mechanisms determining its efficiency are still poorly understood. This study leverages genome-scale metabolic modeling of 138 metagenome-assembled genomes to explore species interactions in lab-scale anaerobic reactors fed with sewage sludge to increasing proportions of food waste. The models showed positive correlations with experimental biogas production (CH4: r = 0.54, CO2: r = 0.66), validating their reliability. The dominant methanogen, Methanothrix sp., adapted its metabolism based on feedstock, affecting methane yields, which ranged from 2.5 to 3 mmol/g of volatile solids·h with sewage sludge to 10–14 mmol/g of VS·h with high food waste. The integration of extracellular enzymes into the models highlighted the role in methane production of pectin degradation, protein hydrolysis, and lipid metabolism, mediated by Proteiniphilum sp., Kiritimatiellae sp., and Olb16 sp. The study identified 475 mutualistic interactions involving amino acid, hydrogen, acetate, and phosphate exchange and 44 competitive interactions in hydrolytic and fermentative processes. These insights can help optimize anaerobic digestion and sustainable waste management in urban settings.
Fil: Orellana, Esteban. Universita Di Padova. Dipartimento Di Biología; Italia. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; Argentina
Fil: Zampieri, Guido. Universita Di Padova. Dipartimento Di Biología; Italia
Fil: De Bernardini, Nicola. Universita Di Padova. Dipartimento Di Biología; Italia
Fil: Guerrero, Leandro Demián. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; Argentina
Fil: Erijman, Leonardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; Argentina
Fil: Campanaro, Stefano. Universita Di Padova. Dipartimento Di Biología; Italia
Fil: Treu, Laura. Universita Di Padova. Dipartimento Di Biología; Italia
description The increasing urbanization has led to rising waste and energy demands, necessitating innovative solutions. A sustainable food waste management approach involves anaerobic codigestion with sewage sludge, enhancing biogas production while managing waste. Although this technology has been successfully tested, the biological mechanisms determining its efficiency are still poorly understood. This study leverages genome-scale metabolic modeling of 138 metagenome-assembled genomes to explore species interactions in lab-scale anaerobic reactors fed with sewage sludge to increasing proportions of food waste. The models showed positive correlations with experimental biogas production (CH4: r = 0.54, CO2: r = 0.66), validating their reliability. The dominant methanogen, Methanothrix sp., adapted its metabolism based on feedstock, affecting methane yields, which ranged from 2.5 to 3 mmol/g of volatile solids·h with sewage sludge to 10–14 mmol/g of VS·h with high food waste. The integration of extracellular enzymes into the models highlighted the role in methane production of pectin degradation, protein hydrolysis, and lipid metabolism, mediated by Proteiniphilum sp., Kiritimatiellae sp., and Olb16 sp. The study identified 475 mutualistic interactions involving amino acid, hydrogen, acetate, and phosphate exchange and 44 competitive interactions in hydrolytic and fermentative processes. These insights can help optimize anaerobic digestion and sustainable waste management in urban settings.
publishDate 2025
dc.date.none.fl_str_mv 2025-03
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/275429
Orellana, Esteban; Zampieri, Guido; De Bernardini, Nicola; Guerrero, Leandro Demián; Erijman, Leonardo; et al.; Sustainable Food Waste Management in Anaerobic Digesters: Prediction of the Organic Load Impact by Metagenome-Scale Metabolic Modeling; American Chemical Society; Environmental Science & Technology; 59; 13; 3-2025; 6659-6672
0013-936X
CONICET Digital
CONICET
url http://hdl.handle.net/11336/275429
identifier_str_mv Orellana, Esteban; Zampieri, Guido; De Bernardini, Nicola; Guerrero, Leandro Demián; Erijman, Leonardo; et al.; Sustainable Food Waste Management in Anaerobic Digesters: Prediction of the Organic Load Impact by Metagenome-Scale Metabolic Modeling; American Chemical Society; Environmental Science & Technology; 59; 13; 3-2025; 6659-6672
0013-936X
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://pubs.acs.org/doi/10.1021/acs.est.4c11180
info:eu-repo/semantics/altIdentifier/doi/10.1021/acs.est.4c11180
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv American Chemical Society
publisher.none.fl_str_mv American Chemical Society
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1850504968567521280
score 13.275514

Publicaciones similares