Neotropical bats as bioindicators for emerging zoonoses in Central America: A case study identifying <i>Trypanosoma cruzi</i> in bats from Belize using metagenomic next-generation sequencing
Bibliographic record
Abstract
Abstract Emerging zoonoses remain a global public health concern. Surveillance of infectious and vector-borne diseases is vital for predicting and mitigating detrimental effects of zoonotic spillover events. Beyond assessing what microorganisms are circulating in specific environments, it is important to understand how potential reservoir hosts, especially animals such as bats, participate in pathogen transmission. Bats can host and potentially spread infections caused by bacteria, viruses, fungi, and protozoa. However, bats can also act as bioindicators that test positive for pathogenic microorganisms without necessarily contributing to the pathogen replication cycle. Metagenomic next-generation sequencing (mNGS) provides an efficient means to broadly screen for pathogens, although microorganism selectivity can sometimes be lower than targeted approaches. Pairing mNGS results with higher-sensitivity tests such as quantitative PCR (qPCR) can validate results and together these tools provide a relatively fast and reliable method for conducting surveillance. To test this approach, we surveyed the types of microorganisms circulating in Belize by collecting 263 blood samples from 20 different bat species captured in the Orange Walk District in 2019, 2022, and 2023. We used mNGS to initially characterize the microbial communities and qPCR to confirm presence and intensity of human pathogens of interest. We detected 1,430 different microorganisms with some relevance to human or animal health, including the protozoan Trypanosoma cruzi which was detected in the phyllostomid bats Desmodus rotundus and Artibeus jamaicensis . qPCR confirmed the presence and intensity of Trypanosoma cruzi in mNGS-positive bat samples. We documented the types of pathogenic microorganisms circulating throughout the bat community in northern Belize to demonstrate the capacity for bats to serve as bioindicators. Author Summary Tracking the spread of new and emerging zoonotic diseases is a major component of global health research. Pathogen surveillance is a vital part of predicting and reducing the consequences of disease outbreaks. Bats are a diverse group of mammals that can host and potentially transmit many pathogens that pose potential risks to human and environmental health. Our study surveyed blood samples (n=263) from 20 bat species collected from the Orange Walk District of Belize in 2019, 2022, and 2023. Metagenomic next-generation sequencing identified 1,430 different microorganisms that are considered potentially relevant to human or animal health. Among the microorganisms detected was Trypanosoma cruzi ( T. cruzi ), the protozoan causative agent of Chagas disease. T. cruzi was of particular interest due to its presence throughout the Americas and relevance to public health. We surveyed the types of microorganisms circulating throughout bat populations in northern Belize to demonstrate the ability of bats to act as bioindicators.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".