Abstract
The pelagic environment represents a mosaic of biogeographical domains shaped by regional oceanographic processes. Here, a coastal-to-open ocean microbiome investigation was conducted from 64 water samples of the Santos Basin (SB), located in the subtropical South Atlantic Ocean. We combined shotgun metagenomics with a hybrid machine learning workflow to investigate the taxonomic diversity, community structure, and ecosystem functions of pelagic microbiomes. The workflow integrated self-organizing maps (unsupervised) for pattern discovery and Random Forest (supervised) for predictive modeling. Unsupervised machine learning revealed a clear spatial and vertical (light-driven) distribution, with indicator taxa reflecting biogeochemical patterns consistent with global surveys. Supervised learning identified phosphate, salinity, and nitrate, influenced by local upwelling and La Plata River plume, as the primary environmental drivers of microbial community structure. In terms of functionality, the SB microbiome displayed depth- and region-specific patterns: photoautotrophs and nitrogen fixers dominated photic waters (with differences between coastal and oceanic stations), whereas chemolithoautotrophs and mixotrophs prevailed in the aphotic zone. Notably, nitrification signatures were more frequent in northern mesopelagic communities, while sulfur-oxidation pathways were enriched toward the south. Genes for CO bio-oxidation and dimethylsulfoniopropionate (DMSP) degradation were present across all depths. Furthermore, potential non-cyanobacterial diazotrophs were detected in the deep waters, underscoring previous underappreciated to nitrogen cycling. Our findings indicated that the Santos Basin hosts a functionally diverse microbiome including putative novel lineages. The taxonomic and functional patterns observed in the SB might provide insights into potential ecological responses to shifts in nutrient dynamics and physical processes. This investigation provides an ecogenomic baseline for understanding the microbial ecosystem services in subtropical oceans and reveals the potential of machine learning to uncover ecological patterns in underexplored marine regions.
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Data availability
The sequencing reads dataset generated and analyzed during the current study are available in the National Centre for Biotechnology Information (NCBI) repositor under the BioProject PRJNA1191028. The genomic dataset generated during and analyzed during the current study are available in the Figshare repositor under https://doi.org/10.6084/m9.figshare.30043690. The iMESc and iMESc Savepoints used for the machine learning analyses are available at Github via https://github.com/DaniloCVieira/imesc_savepoints/tree/2c5a4441ad447c71cc8f5d3e11811fb5a76a3427/Bergo_2025/Microbial-signatures-define-the-ecosystem-functions-of-the-pelagic-microbiome-in-a-basin-scale-Southwest-Atlantic-Ocean
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Acknowledgements
We are grateful to PETROBRAS for the PCR-BS project planning and management. We would like to thank Daniel Moreira for coordinating the PCR-BS project and Dr. Frederico Pereira Brandini for coordinating the “Pelagic realm project”. We would like to thank members of the LECOM team for their scientific support on board. We are deeply grateful for the invaluable guidance and support provided by Rosa Carvalho Gamba, your legacy wisdom continues to inspire us even in her absence. A special thanks to the following PCR-BS project’s researchers and their institutions: UFRJ, UFF, PUC-Rio, UERJ, FIRJAN/SENAI, SALT, INPE, USP, UNIFESP, UFPR, UNESP, IP-SP, FURG and Socioambiental. To the University of São Paulo Foundation (FUSP) for financial administrative management. We also thank the RV Ocean Stalwart and RV Seward Johnson crew, and OceanPact for the scientific expeditions. We thank Barbara Resende Silva for providing valuable support in designing the conceptual diagram. We thank Alexandra Lehmkuhl Gerber and Ana Paula C. Guimarães from UGCDFA/LNCC for sequencing the samples. We acknowledge the anonymous reviewers’ valuable comments that helped to improve this manuscript.
Funding
This study was funded by Petróleo Brasileiro S.A. (PETROBRAS), through the RD&I investments clauses of Brazilian National Agency of Petroleum, Natural Gas, and Biofuels (ANP), under grant numbers 5850.0109317.18.9 and 21167–2, respectively. The project “Caracterização química e biológica do sistema pelágico da Bacia de Santos/PCR-BS” is a national collaboration between PETROBRAS and Universidade de São Paulo. NMB and LNL was financed by a Pos Postdoctoral ‘s fellowship from the PETROBRAS. ATRV is supported by FAPERJ (E-26/201.046/2022) and CNPq (307145/2021–2).
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N.M.B., V.H.P., D.L.M. and C.R.J. conceived and designed the study. J.C.F.M., A.M.A., A.M.E., R.G.R., D.C.D.C., F.S.P. and W.S.G.B. was responsible for onboard sampling and extracting DNA from water samples. M.G.C and F.P.B. was responsible for onboard sampling and generating environmental dataset. A.T.R.V. was responsible for generating the sequencing dataset. N.M.B., L.N.L., F.V.P., R.G.M.L., D.C.V. and F.M. carried out the bioinformatics and statistical analysis. N.M.B., R.G.R., and F.V.P., performed analysis of genomic data. D.C.V. and N.M.B. performed oceanographic analyses; N.M.B., F.V.P., D.C.V. and F.M. prepared the figures and tables and wrote the first draft of the manuscript. A.G.B. and G.F. provided helpful discussions and technical help. All authors discussed the results, commented, and reviewed the manuscript.
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Bergo, N.M., Peres, F.V., Vieira, D.C. et al. Microbial signatures define the ecosystem functions of the pelagic microbiome in a basin-scale, Southwest Atlantic Ocean. Sci Rep (2026). https://doi.org/10.1038/s41598-026-37419-9
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DOI: https://doi.org/10.1038/s41598-026-37419-9
