The containment of outbreaks of emerging infectious diseases rely on early and reliable detection of the etiological agents. However, current diagnostic technologies are only able to detect viral infections just prior to symptom onset. This technological limitation increases the likelihood that diseases with protracted asymptomatic incubation periods (e.g. Ebola), will spread globally undetected and rapidly via air travel. Thus, the development of novel technologies that can identify infections early during the asymptomatic phase is critical, and will revolutionise the way we contain epidemics.
We hypothesize that early during an infection, as part of the innate immune response, the host will express a unique set of biomolecules which can be exploited as early biomarkers for detecting the infection. Next generation sequencing now make the sensitive detection of whole transcriptome of small RNAs possible, and recent work in oncology have shown that microRNAs are promising cancer biomarkers. We postulate that the host microRNA profile of mammals changes early during an infection, and that these differential expression patterns may serve as an early prognosticator for disease.
Thirty-two ferrets were infected with either influenza (H1N1) or Hendra virus, and their health metrics (e.g. weight, temperature) were measured up to 7 days post-inoculation. At 0, 1, 2, 3, 5, 7 days post-inoculation, viral loads in tissues were ascertained, and small RNAs in the sera were purified and whole microRNA expression were determined using RNA-Seq analysis. A similar study was also carried out for Hendra virus in six horses.
Our results demonstrate in two animal infection models that the expressions of a subset of microRNAs in host sera alter significantly after an acute virus infection. Interestingly, these infection-associated microRNA profiles appear prior to symptom onset. This suggests that host microRNAs from biofluids can be useful as an early biomarker for acute viral infections during the asymptomatic period.