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Vector-Borne Diseases Driven by Climate Change?

Global Health Surveillance Human Health

Team Conducts Sequencing in the Field for Real-Time Results

The health of the global population is at risk due to vector-borne diseases. Studies provide evidence that climate change has contributed to the expanded range of ticks and mosquitoes, with these disease vectors potentially increasing their range by hundreds of miles over many generations. As they spread, they expand the geographical distribution of the new and emerging vector-borne diseases they carry with them. This increased range makes vector-borne diseases like Dengue fever, Zika virus, Rocky Mountain spotted fever, tularemia, and others an emerging threat to the health of human and wildlife populations. 

Off the coast of Georgia, St. Catherine’s Island is in an ideal sentinel location to monitor for ticks and mosquitoes as they expand their range and associated vector-borne diseases further north. The location is also unique because there is a population of free-ranging ring-tailed lemurs living on the island. Introduced in 1985 as part of a captive breeding program by what is today the Wildlife Conservation Society, the animals now roam freely. These non-human primates in the system can serve as a model of the human anatomy and sylvatic cycle (the transmission of virus between tick and mosquito species found in the area and non-human primates), approximating what could happen across the zoonotic barrier between these same disease vectors and humans. 

Our colleague Dr. Joseph A. Russell, Ph.D. – an expert in biosurveillance – was interested in better understanding this sylvatic cycle and the variety of tick- and mosquito-borne pathogens that may exist in this environment. Working with a team of entomologists and a veterinarian this past summer, the group spent time on the island in search of:  

  • Tick-borne pathogens: Babesia spp. (Babesiosis), Rickettsia spp. (Rocky Mountain spotted fever), Ehrlichia spp. (Erlichiosis), Fransicella tularensis (tularemia), and Borrelia spp. (Lyme disease)
  • Mosquito-borne pathogens: Powassan Virus, St. Louis Encephalitis Virus, and West Nile Virus 

In their work to collect ticks and mosquitoes, the team sampled from three different sites across the island. The only tick species found was Amblyomma americanum, better known as the Lone Star tick. They are known to be the main human-biting ticks in southeastern and southcentral regions of the U.S. Five different species of mosquitoes were found, while serum samples were also taken from lemurs on the island. 

Sequencing the Samples

Following sample collection, the team conducted sequencing on the tick samples with field-forward protocols. Because researchers in field environments can be impacted by the elements and natural threats – in this case wild alligators and rattlesnakes – the team wanted to move quickly and get real-time results within 90 minutes.  

Because some of the viruses they were looking for have RNA genomes (rather than DNA), they used what is known as a ‘metatranscriptome’ approach – extracting the RNA directly from the sample, converting it to DNA, and sequencing the resultant genomic material. This allowed the team to discover any pathogen that may be in the sample within one test, rather than targeting specific pathogens with multiple pre-designed assays. 

In the field, the team used nanopore sequencing technology. The portable sequencing unit has a flow cell with tiny holes in it that are called “nanopores.” On top of each pore are small protein motors that catch the DNA molecules as they flow over the pores and pull them through. An electrical potential is active across the array, so as the DNA is pulled through, it disrupts the signal in known and predictable ways. Based on that disruption, the sequence of nucleotides can be calculated to determine what organisms are in the sample. 

To further speed the process, the team utilized what is known as “adaptive sampling.” They supplied the device’s software with a list of reference genomes for specific pathogens they were looking to find. As the device starts sequencing, if it doesn’t promptly recognize one of these targeted pathogens in a few dozen base pairs, it will reverse the current of the electrical signal, releasing the undesirable sequence and leaving the pore open for potential capture of a molecule-of-interest. Doing so increased the probability of promptly finding targeted genomes because this process ‘enriches’ the targets above the complex and higher-abundance signal of the insect vector’s genomic material. The team also ran an unenriched sequencing run to see if the results differed. 

A computer program then taxonomically classified the sequence reads, allowing researchers to observe the members of the microbial community (the “microbiome”) of the ticks. Using adaptive sampling resulted in modest increases in target pathogen signal when compared with un-enriched samples. However, this may have been because of the limited duration of sequencing the team assessed in order to evaluate fieldable protocols. Another similar study of tick surveillance in Wisconsin using adaptive sampling resulted in a 2-3-fold increase in target pathogens found – this previous study sequenced for 24 hours compared with our team’s 90 minutes.

In the samples, the team found expected pathogens. Specifically, they found Babesia microti (Babesiosis), which was somewhat curious because deer ticks are the only known vectors for that pathogen. This prompted the team to wonder if that was evidence of an expanded vector range of the Babesia species, which doesn’t traditionally inhabit that area, or whether one of the sample ticks had recently fed on something that had come into contact with B. microti

Next Steps

The team will next conduct deep-sequencing characterization of more than 30 diverse mosquito pools found and more than 20 tick pools (all Amblyoma Americanum – Lone Star tick), as well as the 15 lemur serum samples. 

Going forward, the team hopes to conduct deeper sequencing on the remaining samples to fully characterize the arthropod-borne microbiomes of Saint Catherine’s Island. They will establish baseline tick and mosquito counts and associated microbiome datasets, paired with shotgun sequencing datasets for the lemur serum samples, to build baseline information on the island’s sylvatic cycles. They also plan to establish an on-going sentinel research program on the island, setting a critical baseline for climate change-induced vector and pathogen migrations. 


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