Probability of change in life: Amino acid changes in single nucleotide substitutions

Control of cell proliferation by memories of mitosis

Mitotic duration is tightly constrained, and extended mitosis is characteristic of problematic cells prone to chromosome missegregation and genomic instability. We show here that mitotic extension leads to the formation of p53-binding protein 1 (53BP1)-ubiquitin-specific protease 28 (USP28)-p53 protein complexes that are transmitted to, and stably retained by, daughter cells. Complexes assembled through a Polo-like kinase 1-dependent mechanism during extended mitosis and elicited a p53 response in G1 that prevented the proliferation of the progeny of cells that experienced an approximately threefold extended mitosis or successive less extended mitoses. The ability to monitor mitotic extension was lost in p53-mutant cancers and some p53-wild-type (p53-WT) cancers, consistent with classification of TP53BP1 and USP28 as tumor suppressors. Cancers retaining the ability to monitor mitotic extension exhibited sensitivity to antimitotic agents.

Improving the filtering of false positive single nucleotide variations by combining genomic features with quality metrics

MOTIVATION

Technical errors in sequencing or bioinformatics steps and difficulties in alignment at some genomic sites result in false positive (FP) variants. Filtering based on quality metrics is a common method for detecting FP variants, but setting thresholds to reduce FP rates may reduce the number of true positive variants by overlooking the more complex relationships between features. The goal of this study is to develop a machine learning-based model for identifying FPs that integrates quality metrics with genomic features and with the feature interpretability property to provide insights into model results.

RESULTS

We propose a random forest-based model that utilizes genomic features to improve identification of FPs. Further examination of the features shows that the newly introduced features have an important impact on the prediction of variants misclassified by VEF, GATK-CNN, and GARFIELD, recently introduced FP detection systems. We applied cost-sensitive training to avoid errors in misclassification of true variants and developed a model that provides a robust mechanism against misclassification of true variants while increasing the prediction rate of FP variants. This model can be easily re-trained when factors such as experimental protocols might alter the FP distribution. In addition, it has an interpretability mechanism that allows users to understand the impact of features on the model's predictions.

AVAILABILITY AND IMPLEMENTATION

The software implementation can be found at https://github.com/ideateknoloji/FPDetect.

Evolution of increased positive charge on the SARS-CoV-2 spike protein may be adaptation to human transmission

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to evolve and infect individuals. The exterior surface of the SARS-CoV-2 virion is dominated by the spike protein, and the current work examined spike protein biochemical features that have changed during the 3 years in which SARS-CoV-2 has infected humans. Our analysis identified a striking change in spike protein charge, from -8.3 in the original Lineage A and B viruses to -1.26 in most of the current Omicron viruses. We conclude that in addition to immune selection pressure, the evolution of SARS-CoV-2 has also altered viral spike protein biochemical properties, which may influence virion survival and promote transmission. Future vaccine and therapeutic development should also exploit and target these biochemical properties.

Impact of the Types and Relative Quantities of IGHV Gene Mutations in Predicting Prognosis of Patients With Chronic Lymphocytic Leukemia

Patients with CLL with mutated IGHV genes (M-CLL) have better outcomes than patients with unmutated IGHVs (U-CLL). Since U-CLL usually express immunoglobulins (IGs) that are more autoreactive and more effectively transduce signals to leukemic B cells, B-cell receptor (BCR) signaling is likely at the heart of the worse outcomes of CLL cases without/few IGHV mutations. A corollary of this conclusion is that M-CLL follow less aggressive clinical courses because somatic IGHV mutations have altered BCR structures and no longer bind stimulatory (auto)antigens and so cannot deliver trophic signals to leukemic B cells. However, the latter assumption has not been confirmed in a large patient cohort. We tried to address the latter by measuring the relative numbers of replacement (R) mutations that lead to non-conservative amino acid changes (Rnc) to the combined numbers of conservative (Rc) and silent (S) amino acid R mutations that likely do not or cannot change amino acids, "(S+Rc) to Rnc IGHV mutation ratio". When comparing time-to-first-treatment (TTFT) of patients with (S+Rc)/Rnc ≤ 1 and >1, TTFTs were similar, even after matching groups for equal numbers of samples and identical numbers of mutations per sample. Thus, BCR structural change might not be the main reason for better outcomes for M-CLL. Since the total number of IGHV mutations associated better with longer TTFT, better clinical courses appear due to the biologic state of a B cell having undergone many stimulatory events leading to IGHV mutations. Analyses of larger patient cohorts will be needed to definitively answer this question.

Sagacious epitope selection for vaccines, and both antibody-based therapeutics and diagnostics: tips from virology and oncology

The target of an antibody plays a significant role in the success of antibody-based therapeutics and diagnostics, and vaccine development. This importance is focused on the target binding site—epitope, where epitope selection as a part of design thinking beyond traditional antigen selection using whole cell or whole protein immunization can positively impact success. With purified recombinant protein production and peptide synthesis to display limited/selected epitopes, intrinsic factors that can affect the functioning of resulting antibodies can be more easily selected for. Many of these factors stem from the location of the epitope that can impact accessibility of the antibody to the epitope at a cellular or molecular level, direct inhibition of target antigen activity, conservation of function despite escape mutations, and even non-competitive inhibition sites. By incorporating novel computational methods for predicting antigen changes to model-informed drug discovery and development, superior vaccines and antibody-based therapeutics or diagnostics can be easily designed to mitigate failures. With detailed examples, this review highlights the new opportunities, factors and methods of predicting antigenic changes for consideration in sagacious epitope selection.

A global analysis of conservative and non-conservative mutations in SARS-CoV-2 detected in the first year of the COVID-19 world-wide diffusion

The ability of SARS-CoV-2 to rapidly mutate represents a remarkable complicancy. Quantitative evaluations of the effects that these mutations have on the virus structure/function is of great relevance and the availability of a large number of SARS-CoV-2 sequences since the early phases of the pandemic represents a unique opportunity to follow the adaptation of the virus to humans. Here, we evaluated the SARS-CoV-2 amino acid mutations and their progression by analyzing publicly available viral genomes at three stages of the pandemic (2020 March 15th and October 7th, 2021 February 7th). Mutations were classified in conservative and non-conservative based on the probability to be accepted during the evolution according to the Point Accepted Mutation substitution matrices and on the similarity of the encoding codons. We found that the most frequent substitutions are T > I, L > F, and A > V and we observe accumulation of hydrophobic residues. These findings are consistent among the three stages analyzed. We also found that non-conservative mutations are less frequent than conservative ones. This finding may be ascribed to a progressive adaptation of the virus to the host. In conclusion, the present study provides indications of the early evolution of the virus and tools for the global and genome-specific evaluation of the possible impact of mutations on the structure/function of SARS-CoV-2 variants.

Molecular Characteristics of Repotrectinib That Enable Potent Inhibition of TRK Fusion Proteins and Resistant Mutations

NTRK chromosomal rearrangements yield oncogenic TRK fusion proteins that are sensitive to TRK inhibitors (larotrectinib and entrectinib) but often mutate, limiting the durability of response for NTRK ⁺ patients. Next-generation inhibitors with compact macrocyclic structures (repotrectinib and selitrectinib) were designed to avoid resistance mutations. Head-to-head potency comparisons of TRK inhibitors and molecular characterization of binding interactions are incomplete, obscuring a detailed understanding of how molecular characteristics translate to potency. Larotrectinib, entrectinib, selitrectinib, and repotrectinib were characterized using cellular models of wild-type TRKA/B/C fusions and resistance mutant variants with a subset evaluated in xenograft tumor models. Crystal structures were determined for repotrectinib bound to TRKA (wild-type, solvent-front mutant). TKI-naïve and pretreated case studies are presented. Repotrectinib was the most potent inhibitor of wild-type TRKA/B/C fusions and was more potent than selitrectinib against all tested resistance mutations, underscoring the importance of distinct features of the macrocycle structures. Cocrystal structures of repotrectinib with wild-type TRKA and the TRKA^G595R SFM variant elucidated how differences in macrocyclic inhibitor structure, binding orientation, and conformational flexibility affect potency and mutant selectivity. The SFM crystal structure revealed an unexpected intramolecular arginine sidechain interaction. Repotrectinib caused tumor regression in LMNA-NTRK1 xenograft models harboring GKM, SFM, xDFG, and GKM + SFM compound mutations. Durable responses were observed in TKI-naïve and -pretreated patients with NTRK ⁺ cancers treated with repotrectinib (NCT03093116). This comprehensive analysis of first- and second-generation TRK inhibitors informs the clinical utility, structural determinants of inhibitor potency, and design of new generations of macrocyclic inhibitors.

Peering into Avian Influenza A(H5N8) for a Framework towards Pandemic Preparedness

2014 marked the first emergence of avian influenza A(H5N8) in Jeonbuk Province, South Korea, which then quickly spread worldwide. In the midst of the 2020-2021 H5N8 outbreak, it spread to domestic poultry and wild waterfowl shorebirds, leading to the first human infection in Astrakhan Oblast, Russia. Despite being clinically asymptomatic and without direct human-to-human transmission, the World Health Organization stressed the need for continued risk assessment given the nature of Influenza to reassort and generate novel strains. Given its promiscuity and easy cross to humans, the urgency to understand the mechanisms of possible species jumping to avert disastrous pandemics is increasing. Addressing the epidemiology of H5N8, its mechanisms of species jumping and its implications, mutational and reassortment libraries can potentially be built, allowing them to be tested on various models complemented with deep-sequencing and automation. With knowledge on mutational patterns, cellular pathways, drug resistance mechanisms and effects of host proteins, we can be better prepared against H5N8 and other influenza A viruses.

Spontaneous Mutations in HIV-1 Gag, Protease, RT p66 in the First Replication Cycle and How They Appear: Insights from an In Vitro Assay on Mutation Rates and Types

While drug resistant mutations in HIV-1 are largely credited to its error prone HIV-1 RT, the time point in the infection cycle that these mutations can arise and if they appear spontaneously without selection pressures both remained enigmatic. Many HIV-1 RT mutational in vitro studies utilized reporter genes (LacZ) as a template to investigate these questions, thereby not accounting for the possible contribution of viral codon usage. To address this gap, we investigated HIV-1 RT mutation rates and biases on its own Gag, protease, and RT p66 genes in an in vitro selection pressure free system. We found rare clinical mutations with a general avoidance of crucial functional sites in the background mutations rates for Gag, protease, and RT p66 at 4.71 × 10-5, 6.03 × 10-5, and 7.09 × 10-5 mutations/bp, respectively. Gag and p66 genes showed a large number of 'A to G' mutations. Comparisons with silently mutated p66 sequences showed an increase in mutation rates (1.88 × 10-4 mutations/bp) and that 'A to G' mutations occurred in regions reminiscent of ADAR neighbor sequence preferences. Mutational free energies of the 'A to G' mutations revealed an avoidance of destabilizing effects, with the natural p66 gene codon usage providing barriers to disruptive amino acid changes. Our study demonstrates the importance of studying mutation emergence in HIV genes in a RT-PCR in vitro selection pressure free system to understand how fast drug resistance can emerge, providing transferable applications to how new viral diseases and drug resistances can emerge.