Aare Abroi

Background: The COVID-19 pandemic was characterised by rapid waves of disease, carried by the emergence of new and more infectious SARS-CoV-2 virus variants. How the pandemic unfolded in various locations during its first two years has yet to be sufficiently covered. To this end, here we are looking at the circulating SARS-CoV-2 variants, their diversity, and hospitalisation rates in Estonia in the period from March 2000 to March 2022. Methods: We sequenced a total of 27,550 SARS-CoV-2 samples in Estonia between March 2020 and March 2022. High-quality sequences were genotyped and assigned to Nextstrain clades and Pango lineages. We used regression analysis to determine the dynamics of lineage diversity and the probability of clade-specific hospitalisation stratified by age and sex. Results: We successfully sequenced a total of 25,375 SARS-CoV-2 genomes (or 92%), identifying 19 Nextstrain clades and 199 Pango lineages. In 2020 the most prevalent clades were 20B and 20A. The various subsequent waves of infection were driven by 20I (Alpha), 21J (Delta) and Omicron clades 21K and 21L. Lineage diversity via the Shannon index was at its highest during the Delta wave. About 3% of sequenced SARS-CoV-2 samples came from hospitalised individuals. Hospitalisation increased markedly with age in the over-forties, and was negligible in the under-forties. Vaccination decreased the odds of hospitalisation in over-forties. The effect of vaccination on hospitalisation rates was strongly dependent upon age but was clade-independent. People who were infected with Omicron clades had a lower hospitalisation likelihood in age groups of forty and over than was the case with pre-Omicron clades regardless of vaccination status. Conclusions: COVID-19 disease waves in Estonia were driven by the Alpha, Delta, and Omicron clades. Omicron clades were associated with a substantially lower hospitalisation probability than pre-Omicron clades. The protective effect of vaccination in reducing hospitalisation likelihood was independent of the involved clade.

Cell-penetrating peptides (CPPs) are highly promising transfection agents that can deliver various compounds into living cells, including nucleic acids (NAs). Positively charged CPPs can form non-covalent complexes with negatively charged NAs, enabling simple and time-efficient nanoparticle preparation. However, as CPPs have substantially different chemical and physical properties, their complexation with the cargo and characteristics of the resulting nanoparticles largely depends on the properties of the surrounding environment, i.e., solution. Here, we show that the solvent used for the initial dissolving of a CPP determines the properties of the resulting CPP particles formed in an aqueous solution, including the activity and toxicity of the CPP–NA complexes. Using different biophysical methods such as dynamic light scattering (DLS), atomic force microscopy (AFM), transmission and scanning electron microscopy (TEM and SEM), we show that PepFect14 (PF14), a cationic amphipathic CPP, forms spherical particles of uniform size when dissolved in organic solvents, such as ethanol and DMSO. Water-dissolved PF14, however, tends to form micelles and non-uniform aggregates. When dissolved in organic solvents, PF14 retains its α-helical conformation and biological activity in cell culture conditions without any increase in cytotoxicity. Altogether, our results indicate that by using a solvent that matches the chemical nature of the CPP, the properties of the peptide–cargo particles can be tuned in the desired way. This can be of critical importance for in vivo applications, where CPP particles that are too large, non-uniform, or prone to aggregation may induce severe consequences.

Currently, the SARS-CoV-2 immunity landscape is diverse, with various degrees of natural, vaccine-induced and hybrid immunity. Understanding how protection from natural and hybrid immunities compares with that from vaccine-induced immunity and understanding changes in protection against different SARS-CoV-2 variants are emergent research needs. We evaluated the real-world effectiveness of natural immunity in comparison to that of no SARS-CoV-2-specific immunity, vaccine-induced immunity and hybrid immunity against SARS-CoV-2 infection and hospitalization and evaluate epidemics stemming from Delta and Omicron variants. Methods: Individual-level linked data on SARS-CoV-2, vaccination, and health care utilization in Estonia from national health system testing for the period of February 2020 to June 2022 were used. Three cohorts were nested in these data by pairwise matching of birth year and sex to include individuals with natural immunity only and those with no immunity (Cohort 1; n=92917); those with hybrid and natural immunity (Cohort 2; n=46813); and those with vaccine-induced immunity only and natural immunity (Cohort 3; n=252414). The outcomes were laboratory-confirmed SARS-CoV-2 infection and COVID-19 hospitalization. We used adjusted Cox proportional hazards regression for modelling. Findings: In Cohort 1, in comparison to those with no immunity, those with natural immunity were at lower risk for infection during the Delta period (adjusted [aHR] 0·17, 95% CI 0·15, 0·18) and higher risk (aHR 1·24, 95% CI 1·18, 1·32) during the Omicron period. Natural immunity conferred substantial protection against COVID-19 hospitalization (Delta period aHR 0·05 (95% CI 0·03, 0·11); Omicron period aHR 0·10 (95% CI 0·04, 0·26).In Cohort 2, in comparison to natural immunity, hybrid immunity offered strong protection during the Delta period (aHR 0·61 (95% CI 0·46, 0·80)) but not the Omicron period (aHR 1·05 (95% CI 0·93,1·19)). COVID-19 hospitalization was extremely rare among individuals with hybrid immunity.In Cohort 3, individuals with vaccine-induced immunity were at higher risk than those with natural immunity for both COVID-19 infection ((Delta aHR 4·90 (95% CI 4·48, 5·36); Omicron 1·13 (95% CI 1·06, 1·21)) and hospitalization during the Delta period (aHR 7·19 (95% CI 4·02, 12·84)). Interpretation: Our findings suggest that risk of infection (and of developing severe disease) is driven by personal history of immunity-conferring events and the variant of SARS-CoV-2 virus causing infection. Hybrid immunity seems to confer the greatest protection against SARS-CoV-2 infection and severe disease as viral variants change. This finding highlights the need for continuous vaccination programmes. Funding Information: Research was carried out with the support of the European Regional Development Fund (RITA 1/02-120), Estonian Research Council (grants PRG1197, PRG198) and European Social Fund via IT Academy program. Declaration of Interests: All authors declare no competing interests. Ethics Approval Statement: The study was approved by the Research Ethics Committee of the University of Tartu.

Cell-penetrating peptides (CPPs) are promising tools for the transfection of various substances, including nucleic acids, into cells. The aim of the current work was to search for novel safe and effective approaches for enhancing transfection efficiency of nanoparticles formed from CPP and splice-correcting oligonucleotide (SCO) without increasing the concentration of peptide. We analyzed the effect of inclusion of calcium and magnesium ions into nanoparticles on CPP-mediated transfection in cell culture. We also studied the mechanism of such transfection as well as its efficiency, applicability in case of different cell lines, nucleic acid types and peptides, and possible limitations. We discovered a strong positive effect of these ions on transfection efficiency of SCO, that translated to enhanced synthesis of functional reporter protein. We observed significant changes in intracellular distribution and trafficking of nanoparticles formed by the addition of the ions, without increasing cytotoxicity. We propose a novel strategy for preparing CPP-oligonucleotide nanoparticles with enhanced efficiency and, thus, higher therapeutic potential. Our discovery may be translated to primary cell cultures and, possibly, in vivo studies, with the aim of increasing CPP-mediated transfection efficiency and the likelihood of using CPPs in clinics.

Methylation is an essential epigenetic modification mainly catalysed by S-Adenosyl methionine-dependent methyltransferases (MTases). Several MTases require a cofactor for their metabolic stability and enzymatic activity. TRMT112 is a small evolutionary conserved protein that acts as a co-factor and activator for different MTases involved in rRNA, tRNA and protein methylation. Using a SILAC screen, we pulled down seven methyltransferases—N6AMT1, WBSCR22, METTL5, ALKBH8, THUMPD2, THUMPD3 and TRMT11—as interaction partners of TRMT112. We showed that TRMT112 stabilises all seven MTases in cells. TRMT112 and MTases exhibit a strong mutual feedback loop when expressed together in cells. TRMT112 interacts with its partners in a similar way; however, single amino acid mutations on the surface of TRMT112 reveal several differences as well. In summary, mammalian TRMT112 can be considered as a central “hub” protein that regulates the activity of at least seven methyltransferases.

Cell-penetrating peptides (CPPs) are promising tools for transfection of various substances, including nucleic acids, into cells. The aim of current work was to search for novel safe and effective approaches for enhancing transfection efficiency of nanoparticles formed of CPP and splice-correcting oligonucleotide (SCO) without increasing the concentration of peptide. We analyzed an effect of inclusion of calcium and magnesium ions into nanoparticles on CPP-mediated transfection in cell culture. We also studied the mechanism of such transfection as well as its efficiency, applicability in case of different cell lines, nucleic acid types and peptides, and possible limitations. We discovered a strong positive effect of these ions on transfection efficiency of SCO, that translated to enhanced synthesis of functional reporter protein. We observed significant changes in intracellular distribution and trafficking of nanoparticles formed with addition of the ions, without increasing cytotoxicity. We propose a novel strategy of preparing CPP-oligonucleotide nanoparticles with enhanced efficiency and, thus, higher therapeutic potential. Our discovery may be translated to primary cell cultures and, possibly, in vivo studies, in the aim to increase CPP-mediated transfection efficiency and likelihood of using CPPs in clinics.

Methylation is a widespread modification occurring in DNA, RNA and proteins. The N6AMT1 (HEMK2) protein has DNA N6-methyladenine as well as the protein glutamine and histone lysine methyltransferase activities. The human genome encodes two different isoforms of N6AMT1, the major isoform and the alternatively spliced isoform, where the substrate binding motif is missing. Several RNA methyltransferases involved in ribosome biogenesis, tRNA methylation and translation interact with the common partner, the TRMT112 protein. In this study, we show that TRMT112 regulates the expression of N6AMT1 isoforms in mammalian cells. Both isoforms are equally expressed on mRNA level, but only isoform 1 is detected on the protein level in human cells. We show that the alternatively spliced isoform is not able to interact with TRMT112 and when translated, is rapidly degraded from the cells. This suggests that TRMT112 is involved in cellular quality control ensuring that N6AMT1 isoform with missing substrate binding domain is eliminated from the cells. The down-regulation of TRMT112 does not affect the N6AMT1 protein levels in cells, suggesting that the two proteins of TRMT112 network, WBSCR22 and N6AMT1, are differently regulated by their common cofactor.

The Third Annual Meeting of the European Virus Bioinformatics Center (EVBC) took place in Glasgow, United Kingdom, 28–29 March 2019. Virus bioinformatics has become central to virology research, and advances in bioinformatics have led to improved approaches to investigate viral infections and outbreaks, being successfully used to detect, control, and treat infections of humans and animals. This active field of research has attracted approximately 110 experts in virology and bioinformatics/computational biology from Europe and other parts of the world to attend the two-day meeting in Glasgow to increase scientific exchange between laboratory- and computer-based researchers. The meeting was held at the McIntyre Building of the University of Glasgow; a perfect location, as it was originally built to be a place for “rubbing your brains with those of other people”, as Rector Stanley Baldwin described it. The goal of the meeting was to provide a meaningful and interactive scientific environment to promote discussion and collaboration and to inspire and suggest new research directions and questions. The meeting featured eight invited and twelve contributed talks, on the four main topics: (1) systems virology, (2) virus-host interactions and the virome, (3) virus classification and evolution and (4) epidemiology, surveillance and evolution. Further, the meeting featured 34 oral poster presentations, all of which focused on specific areas of virus bioinformatics. This report summarizes the main research findings and highlights presented at the meeting.

It has been believed for a long time that the transfer and fixation of genetic material from RNA viruses to eukaryote genomes is very unlikely. However, during the last decade, there have been several cases in which “virus-to-host” gene transfer from various viral families into various eukaryotic phyla have been described. These transfers have been identified by sequence similarity, which may disappear very quickly, especially in the case of RNA viruses. However, compared to sequences, protein structure is known to be more conserved. Applying protein structure-guided protein domain-specific Hidden Markov Models, we detected homologues of the Virgaviridae capsid protein in Schizophora flies. Further data analysis supported “virus-to-host” transfer into Schizophora ancestors as a single transfer event. This transfer was not identifiable by BLAST or by other methods we applied. Our data show that structure-guided Hidden Markov Models should be used to detect ancestral virus-to-host transfers.