Parent grain reconstruction from partially or fully transformed microstructures in MTEX

A versatile generic framework for parent grain reconstruction from fully or partially transformed child microstructures has been integrated into the open-source crystallographic toolbox MTEX. The framework extends traditional parent grain reconstruction, phase transformation and variant analysis to all parent–child crystal symmetry combinations. The inherent versatility of the universally applicable parent grain reconstruction methods and the ability to conduct in-depth variant analysis are showcased via example workflows that can be programmatically modified by users to suit their specific applications. This is highlighted by three applications, namely α′-to-γ reconstruction in a lath martensitic steel, α-to-β reconstruction in a Ti alloy, and a two-step reconstruction from α′ to ɛ to γ in a twinning and transformation-induced plasticity steel. Advanced orientation relationship discovery and analysis options, including variant analysis, are demonstrated via the add-on function library ORTools.

A short plus long-amplicon based sequencing approach improves genomic coverage and variant detection in the SARS-CoV-2 genome

High viral transmission in the COVID-19 pandemic has enabled SARS‐CoV‐2 to acquire new mutations that may impact genome sequencing methods. The ARTIC.v3 primer pool that amplifies short amplicons in a multiplex-PCR reaction is one of the most widely used methods for sequencing the SARS-CoV-2 genome. We observed that some genomic intervals are poorly captured with ARTIC primers. To improve the genomic coverage and variant detection across these intervals, we designed long amplicon primers and evaluated the performance of a short (ARTIC) plus long amplicon (MRL) sequencing approach. Sequencing assays were optimized on VR-1986D-ATCC RNA followed by sequencing of nasopharyngeal swab specimens from fifteen COVID-19 positive patients. ARTIC data covered 94.47% of the virus genome fraction in the positive control and patient samples. Variant analysis in the ARTIC data detected 217 mutations, including 209 single nucleotide variants (SNVs) and eight insertions & deletions. On the other hand, long-amplicon data detected 156 mutations, of which 80% were concordant with ARTIC data. Combined analysis of ARTIC + MRL data improved the genomic coverage to 97.03% and identified 214 high confidence mutations. The combined final set of 214 mutations included 203 SNVs, 8 deletions and 3 insertions. Analysis showed 26 SARS-CoV-2 lineage defining mutations including 4 known variants of concern K417N, E484K, N501Y, P618H in spike gene. Hybrid analysis identified 7 nonsynonymous and 5 synonymous mutations across the genome that were either ambiguous or not called in ARTIC data. For example, G172V mutation in the ORF3a protein and A2A mutation in Membrane protein were missed by the ARTIC assay. Thus, we show that while the short amplicon (ARTIC) assay provides good genomic coverage with high throughput, complementation of poorly captured intervals with long amplicon data can significantly improve SARS-CoV-2 genomic coverage and variant detection.

Variant analysis of SARS-CoV-2 strains with phylogenetic analysis and the Coronavirus Antiviral and Resistance Database

Aims: This study determined SARS-CoV-2 variations by phylogenetic and virtual phenotyping analyses. Materials & methods: Strains isolated from 143 COVID-19 cases in Turkey in April 2021 were assessed. Illumina NexteraXT library preparation kits were processed for next-generation ]sequencing. Phylogenetic (neighbor-joining method) and virtual phenotyping analyses (Coronavirus Antiviral and Resistance Database [CoV-RDB] by Stanford University) were used for variant analysis. Results: B.1.1.7–1/2 (n = 103, 72%), B.1.351 (n = 5, 3%) and B.1.525 (n = 1, 1%) were identified among 109 SARS-CoV-2 variations by phylogenetic analysis and B.1.1.7 (n = 95, 66%), B.1.351 (n = 5, 4%), B.1.617 (n = 4, 3%), B.1.525 (n = 2, 1.4%), B.1.526-1 (n = 1, 0.6%) and missense mutations (n = 15, 10%) were reported by CoV-RDB. The two methods were 85% compatible and B.1.1.7 (alpha) was the most frequent SARS-CoV-2 variation in Turkey in April 2021. Conclusion: The Stanford CoV-RDB analysis method appears useful for SARS-CoV-2 lineage surveillance.

Sputnik Light booster after Sputnik V vaccination induces robust neutralizing antibody response to B.1.1.529 (Omicron) SARS-CoV-2 variant

COVID-19 vaccination campaign has been launched around the world. More than 8 billion vaccines doses have been administered, according to the WHO. Published studies shows that vaccination reduces the number of COVID-19 cases and dramatically reduces COVID-19-associated hospitalizations and deaths worldwide. In turn, the emergence of SARS-CoV-2 variants of concern (VOC) with mutations in the receptor-binding domain (RBD) of S glycoprotein poses risks of diminishing the effectiveness of the vaccination campaign. In November 2021, the first information appeared about a new variant of the SARS-CoV-2 virus, which was named Omicron. The Omicron variant is of concern because it contains a large number of mutations, especially in the S glycoprotein (16 mutation in RBD), which could be associated with resistance to neutralizing antibodies (NtAB) and significantly reduce the effectiveness of COVID-19 vaccines. Neutralizing antibodies are one of the important parameters characterizing the protective properties of a vaccine. We conducted a study of neutralizing antibodies in the blood serum of people vaccinated with Sputnik V, as well as those revaccinated with Sputnik Light after Sputnik V. Results showed that a decrease in the level of neutralizing antibodies was observed against SARS-CoV-2 Omicron (B.1.1.529) variant in comparison to B.1.1.1 variant. Analysis of the sera of individuals vaccinated with Sputnik V 6-12 months ago showed that there was a decrease in the level of neutralizing antibodies by 11.76 folds. While no direct comparison with other vaccines declines has been done in this study, we note their reported decline in antibody neutralization at a much more significant level of 40-84 times. At the same time, the analysis of sera of individuals who were vaccinated with Sputnik V, and then revaccinated Sputnik Light, showed that 2-3 months after revaccination the decrease in the level of neutralizing antibodies against the Omicron variant was 7.13 folds. Despite the decrease in NtAb, we showed that all revaccinated individuals had NtAb to Omicron variant. Moreover, the NtAb level to Omicron variant in revaccinated sera are slightly higher than NtAb to B.1.1.1 in vaccinated sera.

dfgcompare: a library to support process variant analysis through Markov models

Background Data-driven process analysis is an important area that relies on software support. Process variant analysis is a sort of analysis technique in which analysts compare executed process variants, a.k.a. process cohorts. This comparison can help to identify insights for improving processes. There are a few software supports to enable process cohort comparison based on the frequencies of process activities and performance metrics. These metrics are effective in cohort analysis, but they cannot support cohort comparison based on the probability of transitions among states, which is an important enabler for cohort analysis in healthcare. Results This paper defines an approach to compare process cohorts using Markov models. The approach is formalized, and it is implemented as an open-source python library, named dfgcompare. This library can be used by other researchers to compare process cohorts. The implementation is also used to compare caregivers’ behavior when prescribing drugs in the Stockholm Region. The result shows that the approach enables the comparison of process cohorts in practice. Conclusions We conclude that dfgcompare supports identifying differences among process cohorts.

Identification of disease-linked hyperactivating mutations in UBE3A through large-scale functional variant analysis

The mechanisms that underlie the extensive phenotypic diversity in genetic disorders are poorly understood. Here, we develop a large-scale assay to characterize the functional valence (gain or loss-of-function) of missense variants identified in UBE3A, the gene whose loss-of-function causes the neurodevelopmental disorder Angelman syndrome. We identify numerous gain-of-function variants including a hyperactivating Q588E mutation that strikingly increases UBE3A activity above wild-type UBE3A levels. Mice carrying the Q588E mutation exhibit aberrant early-life motor and communication deficits, and individuals possessing hyperactivating UBE3A variants exhibit affected phenotypes that are distinguishable from Angelman syndrome. Additional structure-function analysis reveals that Q588 forms a regulatory site in UBE3A that is conserved among HECT domain ubiquitin ligases and perturbed in various neurodevelopmental disorders. Together, our study indicates that excessive UBE3A activity increases the risk for neurodevelopmental pathology and suggests that functional variant analysis can help delineate mechanistic subtypes in monogenic disorders.