The Viromes of Mosquitoes from the Natural Landscapes of Western Siberia

The metagenomic analysis of mosquitoes allows for the genetic characterization of mosquito-associated viruses in different regions of the world. This study applied a metagenomic approach to identify novel viral sequences in seven species of mosquitoes collected from the Novosibirsk region of western Siberia. Using NGS sequencing, we identified 15 coding-complete viral polyproteins (genomes) and 15 viral-like partial sequences in mosquitoes. The complete sequences for novel viruses or the partial sequences of capsid proteins, hypothetical viral proteins, and RdRps were used to identify their taxonomy. The novel viral sequences were classified within the orders Tymovirales and Picornavirales and the families Partitiviridae, Totiviridae, Tombusviridae, Iflaviridae, Nodaviridae, Permutotetraviridae, and Solemoviridae, with several attributed to four unclassified RNA viruses. Interestingly, the novel putative viruses and viral sequences were mainly associated with the mosquito Coquillettidia richardii. This study aimed to increase our understanding of the viral diversity in mosquitoes found in the natural habitats of Siberia, which is characterized by very long, snowy, and cold winters.

Sensitivity and identifiability analysis of COVID-19 pandemic models

The paper presents the results of sensitivity-based identifiability analysis of the COVID-19 pandemic spread models in the Novosibirsk region using the systems of differential equations and mass balance law. The algorithm is built on the sensitivity matrix analysis using the methods of differential and linear algebra. It allows one to determine the parameters that are the least and most sensitive to data changes to build a regularization for solving an identification problem of the most accurate pandemic spread scenarios in the region. The performed analysis has demonstrated that the virus contagiousness is identifiable from the number of daily confirmed, critical and recovery cases. On the other hand, the predicted proportion of the admitted patients who require a ventilator and the mortality rate are determined much less consistently. It has been shown that building a more realistic forecast requires adding additional information about the process such as the number of daily hospital admissions. In our study, the problems of parameter identification using additional information about the number of daily confirmed, critical and mortality cases in the region were reduced to minimizing the corresponding misfit functions. The minimization problem was solved through the differential evolution method that is widely applied for stochastic global optimization. It has been demonstrated that a more general COVID-19 spread compartmental model consisting of seven ordinary differential equations describes the main trend of the spread and is sensitive to the peaks of confirmed cases but does not qualitatively describe small statistical datasets such as the number of daily critical cases or mortality that can lead to errors in forecasting. A more detailed agent-oriented model has been able to capture statistical data with additional noise to build scenarios of COVID-19 spread in the region.

Cases of Q fever detected in residents of the novosibirsk region hospitalized with suspection of infections transmitted by ticks

Coxiella burnetii is the causative agent of Q fever (coxiellosis), which, in addition to acute manifestations, often occurs in a latent form, is prone to chronic course and, in the absence of antibiotic therapy, has a high risk of disability or death. As a result of the presence of a wide range of clinical manifestations specific to other infectious diseases, the use of laboratory test methods (LTM) is required to make a diagnosis. The presence of Q fever anthropurgic foci in the Novosibirsk region was described in the 90s of the last century, but due attention to its laboratory diagnostics is not paid in this region. The aim of the study was to identify genetic and serological markers of the causative agent, C. burnetii, in patients of the Novosibirsk region who were admitted for treatment with fever with suspected tick-borne infections (TBIs). DNA marker of the causative agent of Q fever was detected in blood samples by real time PCR in 9 out of 325 patients. In three patients, the presence of C. burnetii DNA was confirmed by sequencing of the IS1111 and htpB gene fragments. In ELISA tests, antibodies against the causative agent of coxiellosis were detected in the blood sera of 4 patients with positive results of PCR analysis. Contact with tick was registered in 7 out of 9 patients who had C. burnetii DNA and lacked markers of other TBIs. Six people were infected in the Novosibirsk region, two suffered from tick's bite in Altai, and one case was from the Republic of Kyrgyzstan. Thus, a complex approach using both PCR analysis and ELISA provided the identification of markers of the Q fever causative agent in patients admitted with suspected TBIs, thereby differentiating it from other infections. Contact with ticks in most cases suggests that infection with C. burnetii had a transmissible pathway.