Adaptation of a microbial consortium to pelagic Sargassum modifies its taxonomic and functional profile that improves biomethane potential.
Enrique Salgado-HernándezÁngel Isauro Ortiz-CeballosAlejandro Alvarado-LassmanSergio Martínez-HernándezAna Elena Dorantes-AcostaErik Samuel Rosas-MendozaPublished in: Environmental science and pollution research international (2024)
In recent years, pelagic Sargassum has invaded the Caribbean coasts, and anaerobic digestion has been proposed as a sustainable management option. However, the complex composition of these macroalgae acts as a barrier to microbial degradation, thereby limiting methane production. Microbial adaptation is a promising strategy to improve substrate utilization and stress tolerance. This study aimed to investigate the adaptation of a microbial consortium to enhance methane production from the pelagic Sargassum. Microbial adaptation was performed in a fed-batch mode for 100 days by progressive feeding of Sargassum. The evolution of the microbial community was analyzed by high-throughput sequencing of 16S rRNA amplicons. Additionally, 16S rRNA data were used to predict functional profiles using the iVikodak platform. The results showed that, after adaptation, the consortium was dominated by the bacterial phyla Bacteroidota, Firmicutes, and Atribacterota, as well as methanogens of the families Methanotrichaceae and Methanoregulaceae. The abundance of predicted genes related to different metabolic functions was affected during the adaptation stage when Sargassum concentration was increased. At the end of the adaptation stage, the abundance of the predicted genes increased again. The adapted microbial consortium demonstrated a 60% increase in both biomethane potential and biodegradability index. This work offers valuable insights into the development of treatment technologies and the effective management of pelagic Sargassum in coastal regions, emphasizing the importance of microbial adaptation in this context.
Keyphrases
- microbial community
- anaerobic digestion
- antibiotic resistance genes
- genome wide
- multiple sclerosis
- sewage sludge
- human health
- machine learning
- dna methylation
- municipal solid waste
- electronic health record
- high throughput sequencing
- gene expression
- carbon dioxide
- wastewater treatment
- genome wide identification
- smoking cessation
- single cell
- water quality