Community-Level Metabolic Shifts Following Land Use Change in the Amazon Rainforest Identified by a Supervised Machine Leaning Approach.

ABSTRACT: The Amazon rainforest has been subjected to high rates of deforestation, mostly for pasturelands, over the last few decades. This change in plant cover is known to alter the soil microbiome and the functions it mediates, but the genomic changes underlying this response are still unresolved. In this study, we used a combination of deep shotgun metagenomics complemented by a supervised machine learning approach to compare the metabolic strategies of tropical soil microbial communities in pristine forests and long-term established pastures in the Amazon. Machine learning-derived metagenome analysis indicated that microbial community structures (bacteria, archaea and viruses) and the composition of protein-coding genes were distinct in each plant cover type environment. Forest and pasture soil

SUBMITTER: Khan MAW 

PROVIDER: S-EPMC12018533 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature