Since the identification of SARS-CoV-2 in December 2019 a large number of SARS-CoV-2 genomes has been sequenced with unprecedented speed around the world and deposited in several databases. This marks a unique opportunity to study how a virus spread and evolve in a worldwide context. However, currently there is not a useful haplotype classification system to help tracking the virus evolution. Here we identified eleven mutations with 10 % or more frequency in a data set of 7848 genomes. Using these mutations, we identified 6 SARS-CoV-2 haplotypes or OTUs (Operational Taxonomic Unit) that correlate well with a phylogenomic tree. After that, we analyzed the geographical and temporal distribution of these OTUs, as well as their correlation with patient status. Our geographical analysis showed different OTUs prevalence between continents and the temporal distribution analysis revealed an evolution-like pattern in SARS-CoV-2. Finally, we observed a homogenous distribution of OTUs in mild and severe patients and a great prevalence of OTU 2 in asymptomatic patients. However, genomes in the asymptomatic category, comes from isolates on three consecutive days in February (15 to 17), weakening this observation and highlighting the need to increase genomic analyzes in asymptomatic and severe patients. Our classification system is phylogenetically consistent and allows us to easily track geographic and temporal distribution of important mutations around the world. In the next months, it could be updated using similar steps that we used here.

Since the identification of SARS-CoV-2, a large number of genomes have been sequenced with unprecedented speed around the world. This marks a unique opportunity to analyze virus spreading and evolution in a worldwide context. Currently, there is not a useful haplotype description to help to track important and globally scattered mutations. Also, differences in the number of sequenced genomes between countries and/or months make it difficult to identify the emergence of haplotypes in regions where few genomes are sequenced but a large number of cases are reported. We propose an approach based on the normalization by COVID-19 cases of relative frequencies of mutations using all the available data to identify major haplotypes. Furthermore, we can use a similar normalization approach to tracking the temporal and geographic distribution of haplotypes in the world. Using 171,461 genomes, we identify five major haplotypes or operational taxonomic units (OTUs) based on nine high-frequency mutations. OTU_3 characterized by mutations R203K and G204R is currently the most frequent haplotype circulating in four of the six continents analyzed (South America, North America, Europe, Asia, Africa, and Oceania). On the other hand, during almost all months analyzed, OTU_5 characterized by the mutation T85I in nsp2 is the most frequent in North America. Recently (since September), OTU_2 has been established as the most frequent in Europe. OTU_1, the ancestor haplotype, is near to extinction showed by its low number of isolations since May. Also, we analyzed whether age, gender, or patient status is more related to a specific OTU. We did not find OTU’s preference for any age group, gender, or patient status. Finally, we discuss structural and functional hypotheses in the most frequently identified mutations, none of those mutations show a clear effect on the transmissibility or pathogenicity.

Coronavirus disease 2019 (COVID-19) is a contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This disease has spread globally, causing more than 161.5 million cases and 3.3 million deaths to date. Surveillance and monitoring of new mutations in the virus’ genome are crucial to our understanding of the adaptation of SARS-CoV-2. Moreover, how the temporal dynamics of these mutations is influenced by control measures and non-pharmaceutical interventions (NPIs) is poorly understood. Using 1,058,020 SARS-CoV-2 from sequenced COVID-19 cases from 98 countries (totaling 714 country-month combinations), we perform a normalization by COVID-19 cases to calculate the relative frequency of SARS-CoV-2 mutations and explore their dynamics over time. We found 115 mutations estimated to be present in more than 3% of global COVID-19 cases and determined three types of mutation dynamics: high-frequency, medium-frequency, and low-frequency. Classification of mutations based on temporal dynamics enable us to examine viral adaptation and evaluate the effects of implemented control measures in virus evolution during the pandemic. We showed that medium-frequency mutations are characterized by high prevalence in specific regions and/or in constant competition with other mutations in several regions. Finally, taking N501Y mutation as representative of high-frequency mutations, we showed that level of control measure stringency negatively correlates with the effective reproduction number of SARS-CoV-2 with high-frequency or not-high-frequency and both follows similar trends in different levels of stringency.

Despite being of environmental concern around the world due to its toxicity, cyanide continues to be used in many important industrial processes. Thus, searching for cyanide bioremediation methods is a matter of societal concern and must be present on the political agenda of all governments.