Characterisation of the RNA Virome of Nine Ochlerotatus Species in Finland.

RNA viromes of nine commonly encountered Ochlerotatus mosquito species collected around Finland in 2015 and 2017 were studied using next-generation sequencing. Mosquito homogenates were sequenced from 91 pools comprising 16-60 morphologically identified adult females of Oc. cantans, Oc. caspius, Oc. communis, Oc. diantaeus, Oc. excrucians, Oc. hexodontus, Oc. intrudens, Oc. pullatus and Oc. punctor/punctodes. In total 514 viral Reverse dependent RNA polymerase (RdRp) sequences of 159 virus species were recovered, belonging to 25 families or equivalent rank, as follows: Aliusviridae, Aspiviridae, Botybirnavirus, Chrysoviridae, Chuviridae, Endornaviridae, Flaviviridae, Iflaviridae, Negevirus, Partitiviridae, Permutotetraviridae, Phasmaviridae, Phenuiviridae, Picornaviridae, Qinviridae, Quenyavirus, Rhabdoviridae, Sedoreoviridae, Solemoviridae, Spinareoviridae, Togaviridae, Totiviridae, Virgaviridae, Xinmoviridae and Yueviridae. Of these, 147 are tentatively novel viruses. One sequence of Sindbis virus, which causes Pogosta disease in humans, was detected from Oc. communis from Pohjois-Karjala. This study greatly increases the number of mosquito-associated viruses known from Finland and presents the northern-most mosquito-associated viruses in Europe to date.

ClusTRace, a bioinformatic pipeline for analyzing clusters in virus phylogenies.

BACKGROUND: SARS-CoV-2 is the highly transmissible etiologic agent of coronavirus disease 2019 (COVID-19) and has become a global scientific and public health challenge since December 2019. Several new variants of SARS-CoV-2 have emerged globally raising concern about prevention and treatment of COVID-19. Early detection and in-depth analysis of the emerging variants allowing pre-emptive alert and mitigation efforts are thus of paramount importance. RESULTS: Here we present ClusTRace, a novel bioinformatic pipeline for a fast and scalable analysis of sequence clusters or clades in large viral phylogenies. ClusTRace offers several high-level functionalities including lineage assignment, outlier filtering, aligning, phylogenetic tree reconstruction, cluster extraction, variant calling, visualization and reporting. ClusTRace was developed as an aid for COVID-19 transmission chain tracing in Finland with the main emphasis on fast screening of phylogenies for markers of super-spreading events and other features of concern, such as high rates of cluster growth and/or accumulation of novel mutations. CONCLUSIONS: ClusTRace provides an effective interface that can significantly cut down learning and operating costs related to complex bioinformatic analysis of large viral sequence sets and phylogenies. All code is freely available from https://bitbucket.org/plyusnin/clustrace/.

The phylodynamics of SARS-CoV-2 during 2020 in Finland.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused millions of infections and fatalities globally since its emergence in late 2019. The virus was first detected in Finland in January 2020, after which it rapidly spread among the populace in spring. However, compared to other European nations, Finland has had a low incidence of SARS-CoV-2. To gain insight into the origins and turnover of SARS-CoV-2 lineages circulating in Finland in 2020, we investigated the phylogeographic and -dynamic history of the virus. Methods: The origins of SARS-CoV-2 introductions were inferred via Travel-aware Bayesian time-measured phylogeographic analyses. Sequences for the analyses included virus genomes belonging to the B.1 lineage and with the D614G mutation from countries of likely origin, which were determined utilizing Google mobility data. We collected all available sequences from spring and fall peaks to study lineage dynamics. Results: We observed rapid turnover among Finnish lineages during this period. Clade 20C became the most prevalent among sequenced cases and was replaced by other strains in fall 2020. Bayesian phylogeographic reconstructions suggested 42 independent introductions into Finland during spring 2020, mainly from Italy, Austria, and Spain. Conclusions: A single introduction from Spain might have seeded one-third of cases in Finland during spring in 2020. The investigations of the original introductions of SARS-CoV-2 to Finland during the early stages of the pandemic and of the subsequent lineage dynamics could be utilized to assess the role of transboundary movements and the effects of early intervention and public health measures.

Viral RNA Metagenomics of Hyalomma Ticks Collected from Dromedary Camels in Makkah Province, Saudi Arabia.

Arthropod-borne infections are a medical and economic threat to humans and livestock. Over the last three decades, several unprecedented viral outbreaks have been recorded in the Western part of the Arabian Peninsula. However, little is known about the circulation and diversity of arthropod-borne viruses in this region. To prepare for new outbreaks of vector-borne diseases, it is important to detect which viruses circulate in each vector population. In this study, we used a metagenomics approach to characterize the RNA virome of ticks infesting dromedary camels (Camelus dromedaries) in Makkah province, Saudi Arabia. Two hundred ticks of species Hyalomma dromedarii (n = 196) and Hyalomma impeltatum (n = 4) were collected from the Alkhurma district in Jeddah and Al-Taif city. Virome analysis showed the presence of several tick-specific viruses and tick-borne viruses associated with severe illness in humans. Some were identified for the first time in the Arabian Peninsula. The human disease-associated viruses detected included Crimean Congo Hemorrhagic fever virus and Tamdy virus (family Nairoviridae), Guertu virus (family Phenuiviridae), and a novel coltivirus that shares similarities with Tarumizu virus, Tai forest reovirus and Kundal virus (family Reoviridae). Furthermore, Alkhurma hemorrhagic virus (Flaviviridae) was detected in two tick pools by specific qPCR. In addition, tick-specific viruses in families Phenuiviridae (phleboviruses), Iflaviridae, Chuviridae, Totiviridae and Flaviviridae (Pestivirus) were detected. The presence of human pathogenetic viruses warrants further efforts in tick surveillance, xenosurveillence, vector control, and sero-epidemiological investigations in human and animal populations to predict, contain and mitigate future outbreaks in the region.

HAVoC, a bioinformatic pipeline for reference-based consensus assembly and lineage assignment for SARS-CoV-2 sequences.

BACKGROUND: SARS-CoV-2 related research has increased in importance worldwide since December 2019. Several new variants of SARS-CoV-2 have emerged globally, of which the most notable and concerning currently are the UK variant B.1.1.7, the South African variant B1.351 and the Brazilian variant P.1. Detecting and monitoring novel variants is essential in SARS-CoV-2 surveillance. While there are several tools for assembling virus genomes and performing lineage analyses to investigate SARS-CoV-2, each is limited to performing singular or a few functions separately. RESULTS: Due to the lack of publicly available pipelines, which could perform fast reference-based assemblies on raw SARS-CoV-2 sequences in addition to identifying lineages to detect variants of concern, we have developed an open source bioinformatic pipeline called HAVoC (Helsinki university Analyzer for Variants of Concern). HAVoC can reference assemble raw sequence reads and assign the corresponding lineages to SARS-CoV-2 sequences. CONCLUSIONS: HAVoC is a pipeline utilizing several bioinformatic tools to perform multiple necessary analyses for investigating genetic variance among SARS-CoV-2 samples. The pipeline is particularly useful for those who need a more accessible and fast tool to detect and monitor the spread of SARS-CoV-2 variants of concern during local outbreaks. HAVoC is currently being used in Finland for monitoring the spread of SARS-CoV-2 variants. HAVoC user manual and source code are available at https://www.helsinki.fi/en/projects/havoc and https://bitbucket.org/auto_cov_pipeline/havoc , respectively.

An Unsupervised Algorithm for Host Identification in Flaviviruses.

Early characterization of emerging viruses is essential to control their spread, such as the Zika Virus outbreak in 2014. Among other non-viral factors, host information is essential for the surveillance and control of virus spread. Flaviviruses (genus Flavivirus), akin to other viruses, are modulated by high mutation rates and selective forces to adapt their codon usage to that of their hosts. However, a major challenge is the identification of potential hosts for novel viruses. Usually, potential hosts of emerging zoonotic viruses are identified after several confirmed cases. This is inefficient for deterring future outbreaks. In this paper, we introduce an algorithm to identify the host range of a virus from its raw genome sequences. The proposed strategy relies on comparing codon usage frequencies across viruses and hosts, by means of a normalized Codon Adaptation Index (CAI). We have tested our algorithm on 94 flaviviruses and 16 potential hosts. This novel method is able to distinguish between arthropod and vertebrate hosts for several flaviviruses with high values of accuracy (virus group 91.9% and host type 86.1%) and specificity (virus group 94.9% and host type 79.6%), in comparison to empirical observations. Overall, this algorithm may be useful as a complementary tool to current phylogenetic methods in monitoring current and future viral outbreaks by understanding host-virus relationships.

A novel negevirus isolated from Aedes vexans mosquitoes in Finland.

Negeviruses are insect-specific enveloped RNA viruses that have been detected in mosquitoes and sandflies from various geographical locations. Here, we describe a new negevirus from Northern Europe, isolated from pool of Aedes vexans mosquitoes collected in Finland, designated as Mekrijärvi negevirus (MEJNV). MEJNV had a typical negevirus genome organization, is 9,740 nucleotides in length, and has a GC content of 47.53%. The MEJNV genome contains three ORFs, each containing the following identified conserved domains: ORF1 (7,068 nt) encodes a viral methyltransferase, an FtsJ-like methyltransferase, a viral RNA helicase, and an RNA-dependent RNA polymerase, ORF2 (1,242 nt) encodes a putative virion glycoprotein, and ORF3 (660 nt) encodes a putative virion membrane protein. A distinctive feature relative to other currently known negeviruses is a 7-nucleotide-long overlap between ORF1 and ORF2. MEJNV shares the highest sequence identity with Ying Kou virus from China, with 67.71% nucleotide and 75.19% and 59.00% amino acid sequence identity in ORF 1 and ORF 2, respectively. ORF3 had the highest amino acid sequence similarity to Daeseongdong virus 1 and negevirus Nona 1, both with 77.61% identity, and to Ying Kou virus, with 71.22% identity. MEJNV is currently the northernmost negevirus described. Our report supports the view that negeviruses are a globally distributed, diverse group of viruses that can be found from mosquitoes in a wide range of terrestrial biomes from tropical to boreal forests.