Ecogenomics and metabolic potential of the South Atlantic Ocean microbiome

The unique combination of depth, salinity, and water masses make the South Atlantic Ocean an ecosystem of special relevance within the global ocean. Yet, the microbiome of this ecosystem has received less attention than other regions of the global Ocean. This has hampered our understanding of the diversity and metabolic potential of the microorganisms that dwell in this habitat. To fill this knowledge gap, we analyzed a collection of 31 metagenomes from the Atlantic Ocean that spanned the epipelagic, mesopelagic and bathypelagic zones (surface to 4000 m). Read-centric and gene-centric analysis revealed the unique taxonomic and functional composition of metagenomes from each depth zone, which was driven by differences in physical and chemical parameters. In parallel, a total of 40 metagenome-assembled genomes were obtained, which recovered one third of the total community. Phylogenomic reconstruction revealed that many of these genomes are derived from poorly characterized taxa of Bacteria and Archaea. Genomes derived from heterotrophic bacteria of the aphotic zone displayed a large apparatus of genes suited for the utilization of recalcitrant organic compounds such as cellulose, chitin and alkanes. In addition, we found genomic evidence suggesting that mixotrophic bacteria from the bathypelagic zone could perform carbon fixation through the Calvin-Benson-Bassham cycle, fueled by sulfur oxidation. Finally, we found that the viral communities shifted throughout the water column regarding their targeted hosts and virus-to-microbe ratio, in response to shifts in the composition and functioning their microbial counterparts. Our findings shed light on the microbial and viral drivers of important biogeochemical processes that take place in the South Atlantic Ocean.

New viral biogeochemical roles revealed through metagenomic analysis of Lake Baikal

BACKGROUND

Lake Baikal is the largest body of liquid freshwater on Earth. Previous studies have described the microbial composition of this habitat, but the viral communities from this ecosystem have not been characterized in detail.

RESULTS

Here, we describe the viral diversity of this habitat across depth and seasonal gradients. We discovered 19,475 bona fide viral sequences, which are derived from viruses predicted to infect abundant and ecologically important taxa that reside in Lake Baikal, such as Nitrospirota, Methylophilaceae, and Crenarchaeota. Diversity analysis revealed significant changes in viral community composition between epipelagic and bathypelagic zones. Analysis of the gene content of individual viral populations allowed us to describe one of the first bacteriophages that infect Nitrospirota, and their extensive repertoire of auxiliary metabolic genes that might enhance carbon fixation through the reductive TCA cycle. We also described bacteriophages of methylotrophic bacteria with the potential to enhance methanol oxidation and the S-adenosyl-L-methionine cycle.

CONCLUSIONS

These findings unraveled new ways by which viruses influence the carbon cycle in freshwater ecosystems, namely, by using auxiliary metabolic genes that act upon metabolisms of dark carbon fixation and methylotrophy. Therefore, our results shed light on the processes through which viruses can impact biogeochemical cycles of major ecological relevance. Video Abstract.

Charting the diversity of uncultured viruses of Archaea and Bacteria

BACKGROUND

Viruses of Archaea and Bacteria are among the most abundant and diverse biological entities on Earth. Unraveling their biodiversity has been challenging due to methodological limitations. Recent advances in culture-independent techniques, such as metagenomics, shed light on the unknown viral diversity, revealing thousands of new viral nucleotide sequences at an unprecedented scale. However, these novel sequences have not been properly classified and the evolutionary associations between them were not resolved.

RESULTS

Here, we performed phylogenomic analysis of nearly 200,000 viral nucleotide sequences to establish GL-UVAB: Genomic Lineages of Uncultured Viruses of Archaea and Bacteria. The pan-genome content of the identified lineages shed light on some of their infection strategies, potential to modulate host physiology, and mechanisms to escape host resistance systems. Furthermore, using GL-UVAB as a reference database for annotating metagenomes revealed elusive habitat distribution patterns of viral lineages and environmental drivers of community composition.

CONCLUSIONS

These findings provide insights about the genomic diversity and ecology of viruses of prokaryotes. The source code used in these analyses is freely available at https://sourceforge.net/projects/gluvab/.

Charting the diversity of uncultured viruses of Archaea and Bacteria

Background

Viruses of Archaea and Bacteria are among the most abundant and diverse biological entities on Earth. Unraveling their biodiversity has been challenging due to methodological limitations. Recent advances in culture-independent techniques, such as metagenomics, shed light on the unknown viral diversity, revealing thousands of new viral nucleotide sequences at an unprecedented scale. However, these novel sequences have not been properly classified and the evolutionary associations between them were not resolved.

Results

Here, we performed phylogenomic analysis of nearly 200,000 viral nucleotide sequences to establish GL-UVAB: Genomic Lineages of Uncultured Viruses of Archaea and Bacteria. The pan-genome content of the identified lineages shed light on some of their infection strategies, potential to modulate host physiology, and mechanisms to escape host resistance systems. Furthermore, using GL-UVAB as a reference database for annotating metagenomes revealed elusive habitat distribution patterns of viral lineages and environmental drivers of community composition.

Conclusions

These findings provide insights about the genomic diversity and ecology of viruses of prokaryotes. The source code used in these analyses is freely available at https://sourceforge.net/projects/gluvab/.

Modelling the influence of environmental parameters over marine planktonic microbial communities using artificial neural networks

Guanabara Bay is a tropical estuarine ecosystem that receives massive anthropogenic impacts from the metropolitan region of Rio de Janeiro. This ecosystem suffers from an ongoing eutrophication process that has been shown to promote the emergence of potentially pathogenic bacteria, giving rise to public health concerns. Although previous studies have investigated how environmental parameters influence the microbial community of Guanabara Bay, they often have been limited to small spatial and temporal gradients and have not been integrated into predictive mathematical models. Our objective was to fill this knowledge gap by building models that could predict how temperature, salinity, phosphorus, nitrogen and transparency work together to regulate the abundance of bacteria, chlorophyll and Vibrio (a potential human pathogen) in Guanabara Bay. To that end, we built artificial neural networks to model the associations between these variables. These networks were carefully validated to ensure that they could provide accurate predictions without biases or overfitting. The estimated models displayed high predictive capacity (Pearson correlation coefficients ≥0.67 and root mean square error ≤ 0.55). Our findings showed that temperature and salinity were often the most important factors regulating the abundance of bacteria, chlorophyll and Vibrio (absolute importance ≥5) and that each of these has a unique level of dependence on nitrogen and phosphorus for their growth. These models allowed us to estimate the Guanabara Bay microbiome's response to changes in environmental conditions, which allowed us to propose strategies for the management and remediation of Guanabara Bay.

Proposal of fifteen new species of Parasynechococcus based on genomic, physiological and ecological features

Members of the recently proposed genus Parasynechococcus (Cyanobacteria) are extremely abundant throughout the global ocean and contribute significantly to global primary productivity. However, the taxonomy of these organisms remains poorly characterized. The aim of this study was to propose a new taxonomic framework for Parasynechococcus based on a genomic taxonomy approach that incorporates genomic, physiological and ecological data. Through in silico DNA-DNA hybridization, average amino acid identity, dinucleotide signatures and phylogenetic reconstruction, a total of 15 species of Parasynechococcus could be delineated. Each species was then described on the basis of their gene content, light and nutrient utilization strategies, geographical distribution patterns throughout the oceans and response to environmental parameters.