In 2019, the whole world came together to confront a life-threatening virus named SARS-CoV-2, causing COVID-19 illness. The virus infected the human host by attaching to the ACE2 and CD147 receptors in some human cells, resulting in cytokine storm and death. The new variants of the virus that caused concern are Alpha, Beta, Gamma, Delta, and Epsilon, according to the WHO label. However, Pango lineages designated them as B.1.1.7, B.1.351, P.1, B.1.617.2, and B.1.429. Variants may be progressively formed in one chronic COVID-19 patient and transmitted to others. They show some differences in cellular and molecular mechanisms. Mutations in the receptor-binding domain (RBD) and N-terminal domain (NTD) lead to alterations in the host's physiological responses. They show significantly higher transmissibility rates and viral load while evading neutralizing antibodies at different rates. These effects are through mutations, deletion, and conformational alterations in the virus, resulting in the enhanced affinity of RBD to PD of ACE2 protein, virus entry, and spike conformational change. In the clinical laboratory, new variants may diagnose from other variants using specific primers for RBD or NTD. There are some controversial findings regarding the efficacy of the developed vaccines against the new variants. This research aimed to discuss the cellular and molecular mechanisms beyond COVID-19 pathogenesis, focusing on the new variants. We glanced at why the mutations and the ability to transmit the virus increase and how likely the available vaccines will be effective against these variants.

Background and objectives: To understand how organisms evolve, it is fundamental to study how mutations emerge and establish. Here, we estimated the rate of mutation accumulation of SARS-CoV-2 in vitro and investigated the repeatability of its evolution when facing a new cell type but no immune or drug pressures. Methodology: We performed experimental evolution with two strains of SARS-CoV-2, one carrying the originally described spike protein (CoV-2-D) and another carrying the D614G mutation that has spread worldwide (CoV-2-G). After 15 passages in Vero cells and whole genome sequencing, we characterized the spectrum and rate of the emerging mutations and looked for evidences of selection across the genomes of both strains. Results: From the frequencies of the mutations accumulated, and excluding the genes with signals of selection, we estimate a spontaneous mutation rate of 1.3 × 10−6 ± 0.2 × 10−6 per-base per-infection cycle (mean across both lineages of SARS-CoV-2 ± 2SEM). We further show that mutation accumulation is larger in the CoV-2-D lineage and heterogeneous along the genome, consistent with the action of positive selection on the spike protein, which accumulated five times more mutations than the corresponding genomic average. We also observe the emergence of mutators in the CoV-2-G background, likely linked to mutations in the RNA-dependent RNA polymerase and/or in the error-correcting exonuclease protein. Conclusions and implications: These results provide valuable information on how spontaneous mutations emerge in SARS-CoV-2 and on how selection can shape its genome toward adaptation to new environments. Lay Summary: Each time a virus replicates inside a cell, errors (mutations) occur. Here, via laboratory propagation in cells originally isolated from the kidney epithelium of African green monkeys, we estimated the rate at which the SARS-CoV-2 virus mutates—an important parameter for understanding how it can evolve within and across humans. We also confirm the potential of its Spike protein to adapt to a new environment and report the emergence of mutators—viral populations where mutations occur at a significantly faster rate.

Tracking the within-patient evolution of SARS-CoV-2 is key to understanding how this pandemic virus shapes its genome toward immune evasion and survival. In the present study, by monitoring a long-term COVID-19 immunocompromised patient, we observed the concurrent emergence of mutations potentially associated with immune evasion and/or enhanced transmission, mostly targeting the SARS-CoV-2 key host-interacting protein and antigen.

Field epidemiology and viral sequencing provide a comprehensive characterization of transmission chains and allow a better identification of superspreading events. However, very few examples have been presented to date during the COVID-19 pandemic. We studied the first COVID-19 cluster detected in Portugal (59 individuals involved amongst extended family and work environments), following the return of four related individuals from work trips to Italy. The first patient to introduce the virus would be misidentified following the traditional field inquiry alone, as shown by the viral sequencing in isolates from 23 individuals. The results also pointed out family, and not work environment, as the primary mode of transmission.

Background and objectives: To understand how organisms evolve, it is fundamental to study how mutations emerge and establish. Here, we estimated the rate of mutation accumulation of SARS-CoV-2 in vitro and investigated the repeatability of its evolution when facing a new cell type but no immune or drug pressures.Methodology: We performed experimental evolution with two strains of SARS-CoV-2, one carrying the originally described spike protein (CoV-2-D) and another carrying the D614G mutation that has spread worldwide (CoV-2-G). After 15 passages in Vero cells and whole genome sequencing, we characterized the spectrum and rate of the emerging mutations and looked for evidences of selection across the genomes of both strains.Results: From the mutations accumulated, and excluding the genes with signals of selection, we estimate a spontaneous mutation rate of 1.25×10^-6 nt^-1 per infection cycle for both lineages of SARS-CoV-2. We further show that mutation accumulation is heterogeneous along the genome, with the spike gene accumulating mutations at rate five-fold higher than the genomic average. We also observe the emergence of mutators in the CoV-2-G background, likely linked to mutations in the RNA-dependent RNA polymerase and/or in the error-correcting exonuclease protein.Conclusions and implications: These results provide valuable information on how spontaneous mutations emerge in SARS-CoV-2 and on how selection can shape its genome towards adaptation to new environments.Lay summary: Mutation is the ultimate source of variation. We estimated how the SARS-COV-2 virus—cause of the COVID-19 pandemic—mutates. Upon infecting cells, its genome can change at a rate of 0.04 per replication. We also find that this rate can change and that its spike protein can adapt, even within few replications.

SARS-CoV-2 is thought to have originated in the human population from a zoonotic spillover event. Infection in humans results in a variety of outcomes ranging from asymptomatic cases to the disease COVID-19, which can have significant morbidity and mortality, with over two million confirmed deaths worldwide as of January 2021. Over a year into the pandemic, sequencing analysis has shown that variants of SARS-CoV-2 are being selected as the virus continues to circulate widely within the human population. The predominant drivers of genetic variation within SARS-CoV-2 are single nucleotide polymorphisms (SNPs) caused by polymerase error, potential host factor driven RNA modification, and insertion/deletions (indels) resulting from the discontinuous nature of viral RNA synthesis. While many mutations represent neutral ‘genetic drift’ or have quickly died out, a subset may be affecting viral traits such as transmissibility, pathogenicity, host range, and antigenicity of the virus. In this review, we summarise the current extent of genetic change in SARS-CoV-2, particularly recently emerging variants of concern, and consider the phenotypic consequences of this viral evolution that may impact the future trajectory of the pandemic.

Dissemination of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in healthcare institutions affects both patients and health-care workers (HCW), as well as the institutional capacity to provide essential health services. Here, we investigated an outbreak of SARS-CoV-2 in a “non-COVID-19” hospital ward unveiled by massive testing, which challenged the reconstruction of transmission chains. The contacts network during the 15-day period before the screening was investigated, and positive SARS-CoV-2 RNA samples were subjected to virus genome sequencing. Of the 245 tested individuals, 48 (21 patients and 27 HCWs) tested positive for SARS-CoV-2. HCWs were mostly asymptomatic, but the mortality among patients reached 57.1% (12/21). Phylogenetic reconstruction revealed that all cases were part of the same transmission chain. By combining contact tracing and genomic data, including analysis of emerging minor variants, we unveiled a scenario of silent SARS-CoV-2 dissemination, mostly driven by the close contact within the HCWs group and between HCWs and patients. This investigation triggered enhanced prevention and control measures, leading to more timely detection and containment of novel outbreaks. This study shows the benefit of combining genomic and epidemiological data for disclosing complex nosocomial outbreaks, and provides valuable data to prevent transmission of COVID-19 in healthcare facilities.

The global propagation of SARS‐CoV‐2 and the detection of a large number of variants, some of which have replaced the original clade to become dominant, underscores the fact that the virus is actively exploring its evolutionary space. The longer high levels of viral multiplication occur – permitted by high levels of transmission –, the more the virus can adapt to the human host and find ways tosuccess. The third wave of the COVID‐19 pandemic is starting in different parts of the world, emphasizing that transmission containment measures that are being imposed are not adequate. Part of the consideration in determining containment measures is the rationale that vaccination will soon stop transmission and allow a return to normality. However, vaccines themselves represent a selection pressure for evolution of vaccine‐resistant variants, so the coupling of a policy of permitting high levels of transmission/virus multiplication during vaccine roll‐out with the expectation that vaccines will deal with the pandemic, is unrealistic. In the absence of effective antivirals, it is not improbable that SARS‐CoV‐2 infection prophylaxis will involve an annual vaccination campaign against “dominant” viral variants, similar to influenza prophylaxis. Living with COVID‐19 will be an issue of SARS‐CoV‐2 variants and evolution. It is therefore crucial to understand how SARS‐CoV‐2 evolves and what constrains its evolution, in order to anticipate the variants that will emerge. Thus far, the focus has been on the receptor‐binding spike protein, but the virus is complex, encoding 26 proteins which interact with a large number of host factors, so the possibilities for evolution are manifold and not predictable a priori. However, if we are to mount the best defence against COVID‐19, we must mount it against the variants, and to do this, we must have knowledge about the evolutionary possibilities of the virus. In addition to the generic cellular interactions of the virus, there are extensive polymorphisms in humans (e.g. Lewis, HLA, etc.), some distributed within most or all populations, some restricted to specific ethnic populations, and these variations pose additional opportunities for/constraints on viral evolution. We now have the wherewithal – viral genome sequencing, protein structure determination/modelling, protein interaction analysis – to functionally characterise viral variants, but access to comprehensive genome data is extremely uneven. Yet, to develop an understanding of the impacts of such evolution on transmission and disease, we must link it to transmission (viral epidemiology) and disease data (patient clinical data), and the population granularities of these. In this editorial, we explore key facets of viral biology and the influence of relevant aspects of human polymorphisms, human behaviour, geography and climate and, based on this, derive a series of recommendations to monitor viral evolution and predict the types of variants that are likely to arise.

This study aims to investigate the potential safety hazards and provide reference for improving the medical waste disposal procedure in SARS-CoV-2 testing laboratory. Our SARS-CoV-2 testing group detected the RNA residue on the surface of medical waste with Droplet Digital PCR, and held a meeting to discuss the risks in the laboratory medical waste disposal process. After effective autoclaving, SARS-CoV-2 contaminated on the surface of medical waste bags was killed, but the average concentration of viral RNA residues was still 0.85 copies/cm². It would not pose a health risk, but might contaminate the laboratory and affect the test results. When the sterilized medical waste bags were transferred directly by the operators without hand disinfection, re-contamination would happen, which might cause the virus to leak out of the laboratory. Furthermore, we found that sterilization effect monitoring and cooperation among operators were also very important. In summary, we investigated and analyzed the potential safety hazards during the medical waste disposal process in SARS-CoV-2 testing laboratory, and provided reasonable suggestions to ensure the safety of medical waste disposal.

Background Genomic surveillance of SARS-CoV-2 in Portugal was rapidly implemented by the National Institute of Health in the early stages of the COVID-19 epidemic, in collaboration with more than 50 laboratories distributed nationwide. This unprecedented collaborative effort culminated in the generation of 1275 SARS-CoV-2 genome sequences, which represent 15.5% of all confirmed cases in March 2020, making Portugal one of the countries generating the highest volumes of SARS-CoV-2 genomic data during early COVID-19 pandemic. Methods We reconstructed and characterized the spatio-temporal dynamics of SARS-CoV-2 introductions and early dissemination in Portugal using recent phylodynamic models that allow integration of individual-based travel history, in order to obtain a more realistic reconstruction of the viral dynamics. Results We detected at least 277 independent SARS-CoV-2 introductions, mostly from European countries (namely the United Kingdom, Spain, France, Italy and Switzerland), which was broadly consistent with the available travel history data, as well as with the countries with most frequent connectivity and/or with the highest number of Portuguese immigrants. Although most introductions were estimated to have occurred during the last week of February and the first week of March 2020, it is likely that SARS-CoV-2 was silently circulating in Portugal several weeks before the first confirmed local cases on March 2, 2020. Discussion and Conclusion While the implemented preventive and early control measures seem to have been successful in mitigating community transmission from most independent introductions, our results suggest that their earlier implementation could have largely minimized the number of introductions and subsequent virus expansion. Here we lay the foundation for genomic epidemiology of SARS-CoV-2 in Portugal, and highlight the need for systematic, continuous and geographically-representative genomic surveillance to guide national and international public health authorities toward the characterization and control of SARS-CoV-2 circulating diversity.

A few molecularly proven severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cases of symptomatic reinfection are currently known worldwide, with a resolved first infection followed by a second infection after a 48 to 142-day intervening period. We report a multiple-component study of a clinically severe and prolonged viral shedding coronavirus disease 2019 (COVID-19) case in a 17-year-old Portuguese female. She had two hospitalizations, a total of 19 RT-PCR tests, mostly positive, and criteria for releasing from home isolation at the end of 97 days. The viral genome was sequenced in seven serial samples and in the diagnostic sample from her infected mother. A human genome-wide array (>900 K) was screened on the seven samples, and in vitro culture was conducted on isolates from three late samples. The patient had co-infection by two SARS-CoV-2 lineages, which were affiliated in distinct clades and diverging by six variants. The 20A lineage was absolute at the diagnosis (shared with the patient’s mother), but nine days later, the 20B lineage had 3% frequency, and two months later, the 20B lineage had 100% frequency. The 900 K profiles confirmed the identity of the patient in the serial samples, and they allowed us to infer that she had polygenic risk scores for hospitalization and severe respiratory disease within the normal distributions for a Portuguese population cohort. The early-on dynamic co-infection may have contributed to the severity of COVID-19 in this otherwise healthy young patient, and to her prolonged SARS-CoV-2 shedding profile.