Biology subjects

Tsiodras, S.

Publications and source records attributed to Tsiodras, S..

3 recordsLinked to original sources

bioRxiv2020

SARS-CoV-2 exhibits intra-host genomic plasticity and low-frequency polymorphic quasispecies

In December 2019, an outbreak of atypical pneumonia (Coronavirus disease 2019 - COVID-19) associated with a novel coronavirus (SARS-CoV-2) was reported in Wuhan city, Hubei province, China. The outbreak was traced to a seafood wholesale market and human to human transmission was confirmed. The rapid spread and the death toll of the new epidemic warrants immediate intervention. The intra-host genomic variability of SARS-CoV-2 plays a pivotal role in the development of effective antiviral agents and vaccines, but also in the design of accurate diagnostics. We analyzed NGS data derived from clinical samples of three Chinese patients infected with SARS-CoV-2, in order to identify small- and large-scale intra-host variations in the viral genome. We identified tens of low- or higher-frequency single nucleotide variations (SNVs) with variable density across the viral genome, affecting 7 out of 10 protein-coding viral genes. The majority of these SNVs corresponded to missense changes. The annotation of the identified SNVs but also of all currently circulating strain variations revealed colocalization of intra-host but also strain specific SNVs with primers and probes currently used in molecular diagnostics assays. Moreover, we de-novo assembled the viral genome, in order to isolate and validate intra-host structural variations and recombination breakpoints. The bioinformatics analysis disclosed genomic rearrangements over poly-A / poly-U regions located in ORF1ab and spike (S) gene, including a potential recombination hot-spot within S gene. Our results highlight the intra-host genomic diversity and plasticity of SARS-CoV-2, pointing out genomic regions that are prone to alterations. The isolated SNVs and genomic rearrangements, reflect the intra-patient capacity of the polymorphic quasispecies, which may arise rapidly during the outbreak, allowing immunological escape of the virus, offering resistance to anti-viral drugs and affecting the sensitivity of the molecular diagnostics assays.

genomics↗

bioRxiv2020

Full-genome evolutionary analysis of the novel corona virus (2019-nCoV) rejects the hypothesis of emergence as a result of a recent recombination event

BackgroundA novel coronavirus (2019-nCoV) associated with human to human transmission and severe human infection has been recently reported from the city of Wuhan in China. Our objectives were to characterize the genetic relationships of the 2019-nCoV and to search for putative recombination within the subgenus of sarbecovirus. MethodsPutative recombination was investigated by RDP4 and Simplot v3.5.1 and discordant phylogenetic clustering in individual genomic fragments was confirmed by phylogenetic analysis using maximum likelihood and Bayesian methods. ResultsOur analysis suggests that the 2019-nCoV although closely related to BatCoV RaTG13 sequence throughout the genome (sequence similarity 96.3%), shows discordant clustering with the Bat-SARS-like coronavirus sequences. Specifically, in the 5-part spanning the first 11,498 nucleotides and the last 3-part spanning 24,341-30,696 positions, 2019-nCoV and RaTG13 formed a single cluster with Bat-SARS-like coronavirus sequences, whereas in the middle region spanning the 3-end of ORF1a, the ORF1b and almost half of the spike regions, 2019-nCoV and RaTG13 grouped in a separate distant lineage within the sarbecovirus branch. ConclusionsThe levels of genetic similarity between the 2019-nCoV and RaTG13 suggest that the latter does not provide the exact variant that caused the outbreak in humans, but the hypothesis that 2019-nCoV has originated from bats is very likely. We show evidence that the novel coronavirus (2019-nCov) is not-mosaic consisting in almost half of its genome of a distinct lineage within the betacoronavirus. These genomic features and their potential association with virus characteristics and virulence in humans need further attention.

microbiology↗

bioRxiv2018

Mortality attributable to seasonal influenza in Greece, 2013-2017: variation by type and age, and a possible harvesting effect

BACKGROUNDEstimating the contribution of influenza to excess mortality in the population presents substantial methodological challenges. We combined environmental, epidemiological and laboratory surveillance data to estimate influenza-attributable mortality in Greece, over four seasons (2013-2014 to 2017-2018), specifically addressing the lag dimension and the confounding effect of temperature.\n\nMETHODSAssociations of influenza type-specific incidence proxies and of daily mean temperature with mortality were estimated with a distributed-lag non-linear model with 30 days of maximum lag, separately for each age group. Total and weekly deaths attributable to influenza and cold temperatures were calculated.\n\nRESULTSOverall influenza-attributable mortality was 23.6 deaths per 100,000 population (95%CI: 17.8, 29.2), and varied greatly between seasons, by influenza type and by age group, with the vast majority occurring in persons 65 years or older. Most deaths were attributable to A/H3N2, followed by type B influenza. During periods of A/H1N1 circulation, weekly attributable mortality to this subtype among older people increased rapidly in the first half, but then fell to zero and even negative, suggesting a mortality displacement (harvesting) effect. Mortality attributable to non-optimum temperatures was much higher than that attributable to influenza.\n\nCONCLUSIONSStudies of influenza-attributable mortality need to take distributed-lag effects into account, stratify by age group and adjust for circulating influenza types and daily mean temperatures, in order to produce reliable estimates. Our approach is useful and readily applicable in the context of influenza surveillance.

epidemiology↗