CESIMAR - CENPAT   25625
CENTRO PARA EL ESTUDIO DE SISTEMAS MARINOS
Unidad Ejecutora - UE
capítulos de libros
Título:
Contribution of metagenomics to our understanding of microbial processes in Antarctic and sub-Antarctic coastal sediments
Autor/es:
ESPINOLA FERNANDO; GONZÁLEZ J A; JANSSON, JANET; LOZADA MARIANA; CALDEROLI PRISCILA ; LOPEZ, J. L; DIONISI HEBE; MUSUMECI MATIAS; MACCORMACK WP
Libro:
Microbial Ecology: Current advances from genomics, metagenomics and other omics
Editorial:
Caister Academic Press
Referencias:
Lugar: Haverhill; Año: 2019; p. 65 - 106
Resumen:
Despite recent advances in metagenomics, increasing our understanding of sediment microbial communities remains a challenge because of their remarkable diversity. In this chapter we describe various strategies for the analysis of metagenomes from complex microbial communities, using a sequence dataset of coastal sediments from Antarctic and sub-Antarctic sheltered environments as a case study. Microbial diversity and community structure were analysed by 16S rRNA gene amplicon sequencing, and shotgun sequencing was used to unveil key metabolic processes at multiple levels. The phylogenetic analysis of biomarker genes (nitrogen cycle, anaerobic hydrocarbon biodegradation) allowed us to shed light on the structure of environmentally relevant, yet low-abundance microbial populations. Gene content and shared synteny in brown algae polysaccharide utilization loci provided evidence on the evolution of a relevant process for coastal carbon cycling. The statistical analysis of putative microbial rhodopsin sequences showed two levels of phylogeographical segregation, providing evidence on the evolutionary origin of viral sequences. Finally, a workflow was designed for the rational selection of metagenomic sequences encoding enzymes with promising biotechnological features. Each of these analyses provided a glimpse into the biology, ecology and biotechnological potential of these microbial communities, overcoming limitations in coverage and assembly of metagenomes from high-complexity communities.