New evidence suggests that Chikungunya virus arrived in Brazil at least one year earlier than it was detected by public health surveillance systems. Scientists at the Center for Infection and Immunity (CII) at the Columbia Mailman School of Public Health and Fundação Oswaldo Cruz published their findings in the journal Scientific Reports.
Blood samples collected at the Institute Nacional de Infectologia in Rio de Janeiro between March 2016 and June 2017 were analyzed using a genetic test, the QuantiTect/QuantiNova Prove RT-PCR Kit. The test identified 40 samples positive for Chikungunya virus and negative for Dengue virus and Zika virus. Researchers then retested these samples using the CII-ArboViroPlex, a multiplex test developed by CII that can simultaneously scan for the presence of Zika virus, all serotypes of dengue virus, chikungunya virus, and West Nile virus. The CII test confirmed the earlier testing, but performed with greater sensitivity, suggesting it could identify the virus when other tests could not.
Fourteen of these samples representing dates across the fifteen-month collection period were further analyzed using VirCapSeq-VERT, a method developed at CII for viral diagnosis, surveillance, and discovery. VirCapSeq-VERT enabled recovery of near-complete viral genomic sequences and identification of the viruses as representatives of the East-Central-South-African genotype of chikungunya virus.
An analysis of the fourteen genomic sequences showed a strong correlation between genetic divergence and the date at which the sample was taken. This allowed the researchers to identify a “molecular clock” based on the pace of mutations between samples. The timing suggested the virus could have circulated as early as 2012 and was likely imported from Central Africa. Chikungunya virus was first reported by public health surveillance systems in 2014.
“With heightened concerns around Zika, more Brazilians were tested for the infection,” says Nischay Mishra, PhD, the study’s leader at CII. “At the same time, many of those tested were actually infected with dengue or chikungunya, which present with similar symptoms.”
“This study demonstrates the value of sensitive diagnostic technologies that can differentiate between these infectious diseases and provide insights into the origins of the chikungunya outbreak in Brazil,” says first author Thiago Moreno L. Souza, a professor of biochemistry at Fundação Oswaldo Cruz in Rio de Janeiro, Brazil.
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Additional authors include Yasmine Rangel Vieira, Edson Delatorre, Giselle Barbosa-Lima, Raul Leal Faria Luiz, Alexandre Vizzoni, Komal Jain, Milene Mesquita, Nishit Bhuva, Jan F. Gogarten, James Ng, Riddhi Thakkar, Andrea Surrage Calheiros, Ana Paula Teixeira Monteiro, Patrícia T. Bozza, Fernando A. Bozza, Diogo A. Tschoeke, Luciana Leomil, Marcos Cesar Lima de Mendonça, Cintia Damasceno dos Santos Rodrigues, Maria C. Torres, Ana Maria Bispo de Filippis, Rita Maria Ribeiro Nogueira, Fabiano L. Thompson, Cristina Lemos, Betina Durovni, José Cerbino-Neto, and Carlos M. Morel.
This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES); National Council for Scientific and Technological Development (CNPq); Ministry of Science, Technology, Information and Communications; Research Foundation of the State of Rio de Janeiro and Oswaldo Cruz Foundation; the National Institutes of Health (AI109761), the German Federal Ministry of Education and Research, and the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme.
About VirCapSeq-VERT
VirCapSeq-VERT, a streamlined version of unbiased sequencing, references a library of sequences selected from among approximately 2 million genetic pieces, representing all viral taxa known to infect vertebrates. These genetic pieces are used to constitute a probe, which is introduced alongside material taken from the sample being tested. A magnetic process “pulls out” segments from the sample that match the probe; these segments are then analyzed using high-throughput sequencing. A 2015 study reported that the method resulted in 100 to 10,000-fold increases in viral matches compared with conventional high-throughput tests. The test has been used in studies of type 1 diabetes in Australia, respiratory disease in Uganda, and unexplained illness in Tanzania.
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