Uncovering the genomic potential of the Amazon River microbiome to degrade rainforest organic matter.

BACKGROUND: The Amazon River is one of the largest in the world and receives huge amounts of terrestrial organic matter (TeOM) from the surrounding rainforest. Despite this TeOM is typically recalcitrant (i.e. resistant to degradation), only a small fraction of it reaches the ocean, pointing to a substantial TeOM degradation by the river microbiome. Yet, microbial genes involved in TeOM degradation in the Amazon River were barely known. Here, we examined the Amazon River microbiome by analysing 106 metagenomes from 30 sampling points distributed along the river. RESULTS: We constructed the Amazon River basin Microbial non-redundant Gene Catalogue (AMnrGC) that includes ~ 3.7 million non-redundant genes, affiliating mostly to bacteria. We found that the Amazon River microbiome contains a substantial gene-novelty compared to other relevant known environments (rivers and rainforest soil). Genes encoding for proteins potentially involved in lignin degradation pathways were correlated to tripartite tricarboxylates transporters and hemicellulose degradation machinery, pointing to a possible priming effect. Based on this, we propose a model on how the degradation of recalcitrant TeOM could be modulated by labile compounds in the Amazon River waters. Our results also suggest changes of the microbial community and its genomic potential along the river course. CONCLUSIONS: Our work contributes to expand significantly our comprehension of the world's largest river microbiome and its potential metabolism related to TeOM degradation. Furthermore, the produced gene catalogue (AMnrGC) represents an important resource for future research in tropical rivers. Video abstract.

A novel ß-glucosidase isolated from the microbial metagenome of Lake Poraquê (Amazon, Brazil).

The Amazon region holds most of the biological richness of Brazil. Despite their ecological and biotechnological importance, studies related to microorganisms from this region are limited. Metagenomics leads to exciting discoveries, mainly regarding non-cultivable microorganisms. Herein, we report the discovery of a novel ß-glucosidase (glycoside hydrolase family 1) gene from a metagenome from Lake Poraquê in the Amazon region. The gene encodes a protein of 52.9 kDa, named AmBgl-LP, which was recombinantly expressed in Escherichia coli and biochemically and structurally characterized. Although AmBgl-LP hydrolyzed the synthetic substrate p-nitrophenyl-ß-d-glucopyranoside (pNPßG) and the natural substrate cellobiose, it showed higher specificity for pNPßG (kcat/Km = 6 s-1·mM-1) than cellobiose (kcat/Km = 0.6 s-1·mM-1). AmBgl-LP showed maximum activity at 40 °C and pH 6.0 when pNPßG was used as the substrate. Glucose is a competitive inhibitor of AmBgl-LP, presenting a Ki of 14 mM. X-ray crystallography and Small Angle X-ray Scattering were used to determine the AmBgl-LP three-dimensional structure and its oligomeric state. Interestingly, despite sharing similar active site architecture with other structurally characterized GH1 family members which are monomeric, AmBgl-LP forms stable dimers in solution. The identification of new GH1 members by metagenomics might extend our understanding of the molecular mechanisms and diversity of these enzymes, besides enabling us to survey their industrial applications.

Metagenome Sequencing of Prokaryotic Microbiota Collected from Rivers in the Upper Amazon Basin.

Tropical freshwater environments, like rivers, are important reservoirs of microbial life. This study employed metagenomic sequencing to survey prokaryotic microbiota in the Solimões, Purus, and Urucu Rivers of the Amazon Basin in Brazil. We report a rich and diverse microbial community.

Metagenomics Analysis of Microorganisms in Freshwater Lakes of the Amazon Basin.

The Amazon Basin is the largest hydrographic basin on the planet, and the dynamics of its aquatic microorganisms strongly impact global biogeochemical cycles. However, it remains poorly studied. This metagenome project was performed to obtain a snapshot of prokaryotic microbiota from four important lakes in the Amazon Basin.

MAPSAR Image Simulation Based on L-band Polarimetric Data from the SAR-R99B Airborne Sensor (SIVAM System).

This paper describes the methodology applied to generate simulated multipolarized L-band SAR images of the MAPSAR (Multi-Application Purpose SAR) satellite from the airborne SAR R99B sensor (SIVAM System). MAPSAR is a feasibility study conducted by INPE (National Institute for Space Research) and DLR (German Aerospace Center) targeting a satellite L-band SAR innovative mission for assessment, management and monitoring of natural resources. Examples of simulated products and their applications are briefly discussed.