In our research, we use metabarcoding and metagenomics to better understand tropical wildlife, combining cutting-edge molecular tools with field-based conservation. These approaches allow us to monitor biodiversity and wildlife health in a non-invasive, high-throughput manner—essential for working in complex and sensitive tropical ecosystems. By harnessing both Illumina and Oxford Nanopore Technologies (ONT) platforms, we work with environmental DNA (eDNA) and host-derived samples (such as blood, feces, and oral swabs) to explore species diversity, community structure, and emerging conservation challenges across a wide range of taxa.
Metabarcoding for Biodiversity Discovery
We routinely apply metabarcoding—amplifying genetic markers like 12S, 16S, and COI—to identify species within environmental or biological samples. This technique is especially powerful in tropical regions, where traditional biodiversity surveys are logistically difficult and often miss cryptic or rare species. Our team uses eDNA from water, soil, or feces collected in the field to detect amphibians, fish, bats, primates, and more, revealing hidden diversity in Amazonian rivers, rainforests, and mangroves.
To do this, we employ both:
Our Nanopore-based workflows are tailored to tropical field conditions and include custom bioinformatics pipelines to improve taxonomic resolution and correct for inherent sequencing errors, enabling fine-scale resolution of species and haplotypes in complex samples.
Metagenomics for Captive Wildlife Health
Beyond wild ecosystems, we also apply metagenomic approaches to support captive animal health in rescue centers and zoos. We assess:
From Genes to Conservation Action
Our work also contributes to conservation genetics and taxonomy:
By combining lab-based genetics with fieldwork, our research connects biodiversity science to real-world conservation—helping design protected areas, guide wildlife management, and train local teams in DNA-based methods.
Metabarcoding for Biodiversity Discovery
We routinely apply metabarcoding—amplifying genetic markers like 12S, 16S, and COI—to identify species within environmental or biological samples. This technique is especially powerful in tropical regions, where traditional biodiversity surveys are logistically difficult and often miss cryptic or rare species. Our team uses eDNA from water, soil, or feces collected in the field to detect amphibians, fish, bats, primates, and more, revealing hidden diversity in Amazonian rivers, rainforests, and mangroves.
To do this, we employ both:
- Illumina sequencing (e.g., MiSeq, NextSeq), ideal for short-read, high-accuracy profiling of entire biological communities
- Nanopore sequencing, which allows us to work directly in the field, sequencing longer reads in real time, and offering flexible deployment for rapid biodiversity assessments—even in remote locations.
Our Nanopore-based workflows are tailored to tropical field conditions and include custom bioinformatics pipelines to improve taxonomic resolution and correct for inherent sequencing errors, enabling fine-scale resolution of species and haplotypes in complex samples.
Metagenomics for Captive Wildlife Health
Beyond wild ecosystems, we also apply metagenomic approaches to support captive animal health in rescue centers and zoos. We assess:
- Microbiome diversity and health status
- Pathogen presence, including zoonotic threats
- Diet composition and nutritional monitoring
From Genes to Conservation Action
Our work also contributes to conservation genetics and taxonomy:
- Delineate species boundaries in taxa with high cryptic diversity
- Identify undescribed species, especially in under-sampled regions of the Amazon and Neotropics
- Monitor ecological change, by comparing biodiversity profiles in degraded versus intact habitats, including forests impacted by fire, mining, or agriculture.
By combining lab-based genetics with fieldwork, our research connects biodiversity science to real-world conservation—helping design protected areas, guide wildlife management, and train local teams in DNA-based methods.