Mutations In Sequence Research Articles

VILOCA: sequencing quality-aware viral haplotype reconstruction and mutation calling for short-read and long-read data.

RNA viruses exist as large heterogeneous populations within their host. The structure and diversity of virus populations affects disease progression and treatment outcomes. Next-generation sequencing allows detailed viral population analysis, but inferring diversity from error-prone reads is challenging. Here, we present VILOCA (VIral LOcal haplotype reconstruction and mutation CAlling for short and long read data), a method for mutation calling and reconstruction of local haplotypes from short- and long-read viral sequencing data. Local haplotypes refer to genomic regions that have approximately the length of the input reads. VILOCA recovers local haplotypes by using a Dirichlet process mixture model to cluster reads around their unobserved haplotypes and leveraging quality scores of the sequencing reads. We assessed the performance of VILOCA in terms of mutation calling and haplotype reconstruction accuracy on simulated and experimental Illumina, PacBio and Oxford Nanopore data. On simulated and experimental Illumina data, VILOCA performed better or similar to existing methods. On the simulated long-read data, VILOCA is able to recover on average [Formula: see text] of the ground truth mutations with perfect precision compared to only [Formula: see text] recall and [Formula: see text] precision of the second-best method. In summary, VILOCA provides significantly improved accuracy in mutation and haplotype calling, especially for long-read sequencing data, and therefore facilitates the comprehensive characterization of heterogeneous within-host viral populations.

The impact of DNA point mutations and epigenetic modifications on the nucleosome wrapping energy

Nucleosome positioning and mobility, which plays an important role in gene expression and regulation, is in turn modulated by DNA sequence and its underlying mechanical properties. The free energy, required to deform a 147 bp linear DNA fragment into a nucleosomal configuration, is a way to quantify DNA mechanical propensity for nucleosome formation. This work explores how such energy, referred to as the nucleosome wrapping energy, is altered by DNA sequence mutations and epigenetic modifications. The nucleosome wrapping energy is computed using a newly developed computational method based on minimising the cgNA+ coarse-grain model energy with elastic constraints on phosphate positions. We find that the effect of sequence mutations and epigenetic modifications is highly dependent on the positions along the sequence of the modified bases. Most point mutations as well as cytosine methylation and hydroxymethylation, depending on their positions, can lead both to an increase and decrease in the nucleosome wrapping energy. We use the data of mutation-caused energy changes to identify sequence patterns in specific positions, leading to the smallest and highest wrapping energy values. Furthermore, we construct sequences corresponding to extremely low and high nucleosome wrapping energies, compared to energy distribution for human genome sequences. We believe that our findings are helpful for better understanding the role of DNA sequence and its epigenetic modifications in nucleosome positioning. Furthermore, our constructed minimum energy sequence could be used as a candidate for producing stable synthetic nucleosomes.

Genetic Diversity and Drug Resistance Mutations in HIV-1 pol Gene Sequences in the Philippines: A Retrospective Genomic Analysis

The Philippines has experienced a significant increase in HIV-1 infections in recent years, with a growing epidemic driven by the CRF01_AE strain. Understanding the genetic diversity of HIV-1 in the Philippines is crucial for the development of effective treatment strategies and the prevention of drug resistance. This study analyzed comprehensive data on common resistance mutation patterns from 2009 to 2017, revealing an increasing trend of mutations observed in NRTI and NNRTI resistance among the predominant CRF01_AE strains. The most common NRTI mutations observed were M184V, K65R, and S68G, whereas the most common NNRTI mutations were K103N, Y181C, and G190A. The study also found a high prevalence of M184V minority variants (0.5-20%) in treatment-naive patients, which could increase the risk of virological failure in 3TC-containing regimens. The findings of this study highlight the importance of comprehensive drug resistance surveillance and access to resistance testing to guide optimal first-line antiretroviral treatment selection and to manage the growing HIV-1 epidemic in the Philippines. The development of effective strategies to prevent and manage drug resistance is crucial to ensuring the long-term success of HIV treatment programs in the country.

A simple phylogenetic approach to analyze hypermutated HIV proviruses reveals insights into their dynamics and persistence during antiretroviral therapy

Abstract Hypermutated proviruses, which arise in a single HIV replication cycle when host antiviral APOBEC3 proteins introduce extensive G-to-A mutations throughout the viral genome, persist in all people living with HIV receiving antiretroviral therapy (ART). But, hypermutated sequences are routinely excluded from phylogenetic trees because their extensive mutations complicate phylogenetic inference, and as a result we know relatively little about their within-host evolutionary origins and dynamics. Using >1400 longitudinal single-genome-amplified HIV env-gp120 sequences isolated from six women over a median 18 years of follow-up − including plasma HIV RNA sequences collected over a median 9 years between seroconversion and ART initiation, and >500 proviruses isolated over a median 9 years on ART − we evaluated three approaches for masking hypermutation in nucleotide alignments. Our goals were to 1) reconstruct phylogenies that can be used for molecular dating and 2) phylogenetically infer the integration dates of hypermutated proviruses persisting during ART. Two of the approaches (stripping all positions containing putative APOBEC3 mutations from the alignment, or replacing individual putative APOBEC3 mutations in hypermutated sequences with the ambiguous base R) consistently normalized tree topologies, eliminated erroneous clustering of hypermutated proviruses, and brought env-intact and hypermutated proviruses into comparable ranges with respect to multiple tree-based metrics. Importantly, these corrected trees produced integration date estimates for env-intact proviruses that were highly concordant with those from benchmark trees that excluded hypermutated sequences, supporting the use of these corrected trees for molecular dating. Subsequent molecular dating of hypermutated proviruses revealed that these sequences spanned a wide age range, with the oldest ones dating to shortly after infection. This indicates that hypermutated proviruses, like other provirus types, begin to be seeded into the proviral pool immediately following infection, and can persist for decades. In two of the six participants, hypermutated proviruses differed from env-intact ones in terms of their age distributions, suggesting that different provirus types decay at heterogeneous rates in some hosts. These simple approaches to reconstruct hypermutated provirus’ evolutionary histories reveal insights into their in vivo origins and longevity, towards a more comprehensive understanding of HIV persistence during ART.

Gene Therapy in Cardiovascular Disease: Recent Advances and Future Directions in Science: A Science Advisory From the American Heart Association.

Cardiovascular disease remains the foremost cause of morbidity and mortality globally, affecting millions of individuals. Recent discoveries illuminate the substantial role of genetics in cardiovascular disease pathogenesis, encompassing both monogenic and polygenic mechanisms and identifying tangible targets for gene therapies. Innovative strategies have emerged to rectify pathogenic variants that cause monogenic disorders such as hypertrophic, dilated, and arrhythmogenic cardiomyopathies and hypercholesterolemia. These include delivery of exogenous genes to supplement insufficient protein levels caused by pathogenic variants or genome editing to correct, delete, or modify mutant sequences to restore protein function. However, effective delivery of gene therapy to specified cells presents formidable challenges. Viral vectors, notably adeno-associated viruses and nonviral vectors such as lipid and engineered nanoparticles, offer distinct advantages and limitations. Additional risks and obstacles remain, including treatment durability, tissue-specific targeting, vector-associated adverse events, and off-target effects. Addressing these challenges is an ongoing imperative; several clinical gene therapy trials are underway, and many more first-in-human studies are anticipated. This science advisory reviews core concepts of gene therapy, key obstacles, patient risks, and ongoing research endeavors to enable clinicians to understand the complex landscape of this emerging therapy and its remarkable therapeutic potential to benefit cardiovascular disease.

Genomic profiling of circulating tumor DNA for childhood cancers.

The utility of circulating tumor DNA (ctDNA) analysis has not been well-established for disease detection and monitoring of childhood cancers, especially leukemias. We developed PeCan-Seq, a deep sequencing method targeting diverse somatic genomic variants in cell-free samples in childhood cancer. Plasma samples were collected at diagnosis from 233 children with hematologic, solid and brain tumors. All children with hematologic malignancy (n = 177) had detectable ctDNA at diagnosis. The median ctDNA fraction was 0.77, and 97% of 789 expected tumor variants were identified, including sequence mutations, copy number variations, and structural variations responsible for oncogenic fusions. In contrast, ctDNA was detected in 19 of 38 solid tumor patients and 1 of 18 brain tumor patients. Somatic variants from ctDNA were correlated with minimal residual disease levels as determined by flow cytometry in serial plasma samples from patients with B-cell acute lymphoblastic leukemia (B-ALL). We showcase multi-tumor detection by ctDNA analysis for a patient with concurrent B-ALL and neuroblastoma. In conclusion, PeCan-seq sensitively identified heterogeneous ctDNA alterations from 1 mL plasma for childhood hematologic malignancies and a subset of solid tumors. PeCan-seq provides a robust, non-invasive approach to augment comprehensive genomic profiling at diagnosis and mutation-specific detection during disease monitoring.

Epigenetic Regulation of Anthocyanin Biosynthesis in Betula pendula 'Purple Rain'.

Betula pendula 'Purple Rain' is characterized by its purple leaves and has ornamental applications. A green mutant line NL, which was mutated by line NZ of B. pendula 'Purple Rain' during tissue culture, shows green leaves instead of the typical purple color of B. pendula 'Purple Rain'. This study quantified the leaf color traits of NL and a normal B. pendula 'Purple Rain' line NZ, and uncovered differentially expressed genes involved in flavonoid biosynthesis pathway genes in NL through RNA-Seq analysis. Compared to NZ, reduced levels of six anthocyanins contained in NL were revealed via flavonoids-targeted metabolomics. Sequence mutations in transcription factors that could explain NL's phenotype failed to be screened via whole-genome resequencing, suggesting an epigenetic basis for this variant. Therefore, a key gene, BpMYB113, was identified in NL via the combined analysis of small RNA sequencing, whole-genome methylation sequencing, and transcriptomics. In NL, this gene features a hyper CHH context methylation site and a lower transcription level compared to NZ, disrupting the expression of downstream genes in the phenylalanine metabolism pathway, and thereby reducing flavonoid biosynthesis. Our study elucidates an epigenetic mechanism underlying color variation in variegated trees, providing pivotal insights for the breeding and propagation of colored-leaf tree species.

Respiratory virus infections and adenovirus characteristics during acute exacerbation of chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is a common respiratory disease globally, characterized by obstructive ventilatory disorder under pulmonary function tests. Recent years have witnessed a yearly increase in the prevalence of COPD. To investigate the impact of respiratory virus infections on patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD), and to perform sequencing typing and mutation analysis of viruses with high detection rate. A total of 1523 inpatients with AECOPD admitted to our hospital from April 1,2020 to March 30,2022 were collected and divided into two groups: the infected group (n= 532) and the non-infected group (n= 991). The related indexes between the two groups were collected and compared (including clinical characteristics and laboratory tests that blood cell count, PCT, CRP, adenovirus, respiratory syncytial virus, rhinovirus, influenza A virus, influenza B virus, etc.). In the infected group, the proportion of patients with palpitations (49.44% VS 8.07%, P< 0.001), lipid metabolism abnormalities (18.42% VS 39.96%, P< 0.001), heart failure (39.85% VS 29.87%, P< 0.001), disease duration (17.48 ± 7.47 VS 12.45 ± 11.43 d, P< 0.001), and poor prognosis (69.55% VS 17.15%, P< 0.001) were higher than those in the non-infected group; Adenovirus (ADV) accounted for 75.94% (404/532) of all infected viruses. 31 virus strains could be categorized into 16 ADV-C1, one ADV-C5, two ADV-B3, three ADV-B7, two ADV-D17, two ADV-D19, and five ADV-D27, which were similar to the serotypes reported in severe pneumonia. Furthermore, three strains of C1 adenovirus were found to be highly homologous to the original strain AF534906 by sequencing, and the phylogenetic trees of the three main structural genes were all on the same branch as the original strain. Base mutations and amino acid variants were found in each structural gene segment. In clinical data, it's found that patients with mutations are worse than those without mutations. Respiratory viruses are common in patients with poor prognosis of AECOPD, especially adenovirus, respiratory syncytial virus. Respiratory virus infections will lead to the deterioration of patients with AECOPD, accompanied by longer treatment cycles and poor prognosis.

Sunflower Trypsin Monocyclic Inhibitor Selected for the Main Protease of SARS-CoV-2 by Phage Display.

Main protease (Mpro), also known as 3-chymotrypsin-like protease (3CLpro), is a nonstructural protein (NSP5) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) responsible for the cleavage of virus polyproteins during viral replication at 11 sites, which generates 12 functional proteins. Mpro is a cysteine protease that presents specificity for the amino acid residue glutamine (Gln) at the P1 position of the substrate. Due to its essential role in processing the viral polyprotein for viral particle formation (assembly), Mpro inhibition has become an important tool to control coronavirus disease 2019 (COVID-19), since Mpro inhibitors act as antivirals. In this work, we proposed to identify specific inhibitors of the Mpro of SARS-CoV-2 using a monocyclic peptide (sunflower trypsin inhibitor (SFTI)) phage display library. Initially, we expressed, purified and activated recombinant Mpro. The screening of the mutant SFTI phage display library using recombinant Mpro as a receptor resulted in the five most frequent SFTI mutant sequences. Synthetized mutant SFTIs did not inhibit Mpro protease using the fluorogenic substrate. However, the mutant SFTI 4 efficiently decreased the cleavage of recombinant human prothrombin as a substrate by Mpro, as confirmed by sodium dodecyl sulfate (SDS)-polyacrylamide gel electrophoresis (PAGE). Additionally, SFTI 4 presented a dissociation constant (KD) of 21.66 ± 6.66 µM for Mpro by surface plasmon resonance. Finally, 0.1 µM SFTI 4 reduced VERO cell infection by SARS-CoV-2 wt after 24 and 48 h. In conclusion, we successfully screened a monocyclic peptide library using phage display for the Mpro of SARS-CoV-2, suggesting that this methodology can be useful in identifying new inhibitors of viral enzymes.

Critical Assessment of Protein Engineering (CAPE): A Student Challenge on the Cloud.

The success of AlphaFold in protein structure prediction highlights the power of data-driven approaches in scientific research. However, developing machine learning models to design and engineer proteins with desirable functions is hampered by limited access to high-quality data sets and experimental feedback. The Critical Assessment of Protein Engineering (CAPE) challenge addresses these issues through a student-focused competition, utilizing cloud computing and biofoundries to lower barriers to entry. CAPE serves as an open platform for community learning, where mutant data sets and design algorithms from past contestants help improve overall performance in subsequent rounds. Through two competition rounds, student participants collectively designed >1500 new mutant sequences, with the best-performing variants exhibiting catalytic activity up to 5-fold higher than the wild-type parent. We envision CAPE as a collaborative platform to engage young researchers and promote computational protein engineering.

The effects of Remdesivir’s functional groups on its antiviral potency and resistance against the SARS-CoV-2 polymerase

Remdesivir (RDV, Veklury®) is the first FDA-approved antiviral treatment for COVID-19. It is a nucleotide analogue (NA) carrying a 1'-cyano (1'-CN) group on the ribose and a pseudo-adenine nucleobase whose contributions to the mode of action (MoA) are not clear. Here, we dissect these independent contributions by employing RDV-TP analogues. We show that while the 1'-CN group is directly responsible for transient stalling of the SARS-CoV-2 replication/transcription complex (RTC), the nucleobase plays a role in the strength of this stalling. Conversely, RNA extension assays show that the 1'-CN group plays a role in fidelity and that RDV-TP can be incorporated as a GTP analogue, albeit with lower efficiency. However, a mutagenic effect by the viral polymerase is not ascertained by deep sequencing of viral RNA from cells treated with RDV. We observe that once added to the 3' end of RNA, RDV-MP is sensitive to excision and its 1'-CN group does not impact its nsp14-mediated removal. A >14-fold RDV-resistant SARS-CoV-2 isolate can be selected carrying two mutations in the nsp12 sequence, S759A and A777S. They confer both RDV-TP discrimination over ATP by nsp12 and stalling during RNA synthesis, leaving more time for excision-repair and potentially dampening RDV efficiency. We conclude that RDV presents a multi-faced MoA. It slows down or stalls overall RNA synthesis but is efficiently repaired from the primer strand, whereas once in the template, read-through inhibition adds to this effect. Its efficient incorporation may corrupt proviral RNA, likely disturbing downstream functions in the virus life cycle.

Hypermut 3: Identifying specific mutational patterns in a defined nucleotide context that allows multistate characters.

The detection of APOBEC3F- and APOBEC3G-induced mutations in virus sequences is useful for identifying hypermutated sequences. These sequences are not representative of viral evolution and can therefore alter the results of downstream sequence analyses if included. We previously published the software Hypermut, which detects hypermutation events in sequences relative to a reference. Two versions of this method are available as a webtool. Neither of these methods consider multistate characters or gaps in the sequence alignment. Here, we present an updated, user-friendly web and command-line version of Hypermut with functionality to handle multistate characters and gaps in the sequence alignment. This tool allows for straightforward integration of hypermutation detection into sequence analysis pipelines. As with the previous tool, while the main purpose is to identify G to A hypermutation events, any mutational pattern and context can be specified. Hypermut 3 is written in Python 3. It is available as a command-line tool at https://github.com/MolEvolEpid/hypermut3 and as a webtool at https://www.hiv.lanl.gov/content/sequence/HYPERMUT/hypermutv3.html . tkl@lanl.gov or seq-info@lanl.gov.

Engineering quantitative stomatal trait variation and local adaptation potential by cis-regulatory editing.

Cis-regulatory element editing can generate quantitative trait variation that mitigates extreme phenotypes and harmful pleiotropy associated with coding sequence mutations. Here, we applied a multiplexed CRISPR/Cas9 approach, informed by bioinformatic datasets, to generate genotypic variation in the promoter of OsSTOMAGEN, a positive regulator of rice stomatal density. Engineered genotypic variation corresponded to broad and continuous variation in stomatal density, ranging from 70% to 120% of wild-type stomatal density. This panel of stomatal variants was leveraged in physiological assays to establish discrete relationships between stomatal morphological variation and stomatal conductance, carbon assimilation and intrinsic water use efficiency in steady-state and fluctuating light conditions. Additionally, promoter alleles were subjected to vegetative drought regimes to assay the effects of the edited alleles on developmental response to drought. Notably, the capacity for drought-responsive stomatal density reprogramming in stomagen and two cis-regulatory edited alleles was reduced. Collectively our data demonstrate that cis-regulatory element editing can generate near-isogenic trait variation that can be leveraged for establishing relationships between anatomy and physiology, providing a basis for optimizing traits across diverse environments.

RNA elements required for the high efficiency of West Nile Virus-induced ribosomal frameshifting.

West Nile Virus (WNV), a member of the Flaviviridae family, requires programmed -1 ribosomal frameshifting (PRF) for translation of the viral genome. The efficiency of WNV frameshifting is among the highest observed to date. Despite structural similarities to frameshifting sites in other viruses, it remains unclear why WNV exhibits such a high frameshifting efficiency. Here we employed dual-luciferase reporter assays in multiple human cell lines to probe the RNA requirements for highly efficient frameshifting by the WNV genome. We find that both the sequence and structure of a predicted RNA pseudoknot downstream of the slippery sequence-the codons in the genome on which frameshifting occurs-are required for efficient frameshifting. We also show that multiple proposed RNA secondary structures downstream of the slippery sequence are inconsistent with efficient frameshifting. We mapped the most favorable distance between the slippery site and the pseudoknot essential for optimal frameshifting, and found the base of the pseudoknot structure likely is unfolded prior to frameshifting. Finally, we find that many mutations in the WNV slippery sequence allow efficient frameshifting, but often result in aberrant shifting into other reading frames. Mutations in the slippery sequence also support a model in which frameshifting occurs concurrent with or after translocation of the mRNA and tRNA on the ribosome. These results provide a comprehensive analysis of the molecular determinants of WNV-programmed ribosomal frameshifting and provide a foundation for the development of new antiviral strategies targeting viral gene expression.

Computational modeling to understand the interaction of TMPyP4 with a G-quadruplex

The potential of small molecules to bind to G-quadruplex-forming sequences in oncogene promoter regions, thereby regulating their structural equilibrium, has been explored as a promising strategy for cancer chemotherapy. The model drug 5,10,15,20-tetrakis-(N-methyl-4-pyridyl)porphine (TMPyP4) has been shown to have an affinity toward G-quadruplex DNA. However, the precise sites and modes of TMPyP4 binding to G-quadruplex DNA remain a subject of debate. In this study, we focus on identifying potential binding sites on a mutant c-MYC sequence known to fold into a single 1:2:1 loop isomer quadruplex. Our findings provide insights into the 4:1 stoichiometry reported for TMPyP4 binding to this G-quadruplex. Binding enthalpy and free energy calculations show that intercalation of a TMPyP4 molecule between the quadruplexes is thermodynamically favorable. Our calculations suggest that two of the binding sites are located at the top and bottom of the quadruplex, respectively, while the remaining two are likely intercalations.

Reconstructing signaling history of single cells with imaging-based molecular recording.

The intensity and duration of biological signals encode information that allows a few pathways to regulate a wide array of cellular behaviors. Despite the central importance of signaling in biomedical research, our ability to quantify it in individual cells over time remains limited. Here, we introduce INSCRIBE, an approach for reconstructing signaling history in single cells using endpoint fluorescence images. By regulating a CRISPR base editor, INSCRIBE generates mutations in genomic target sequences, at a rate proportional to signaling activity. The number of edits is then recovered through a novel ratiometric readout strategy, from images of two fluorescence channels. We engineered human cell lines for recording WNT and BMP pathway activity, and demonstrated that INSCRIBE faithfully recovers both the intensity and duration of signaling. Further, we used INSCRIBE to study the variability of cellular response to WNT and BMP stimulation, and test whether the magnitude of response is a stable, heritable trait. We found a persistent memory in the BMP pathway. Progeny of cells with higher BMP response levels are likely to respond more strongly to a second BMP stimulation, up to 3 weeks later. Together, our results establish a scalable platform for genetic recording and in situ readout of signaling history in single cells, advancing quantitative analysis of cell-cell communication during development and disease.

Disruption of the signal recognition particle pathway leading to impaired growth, sugar metabolism and acid resistance of Lactococcus lactis

Lactococcus lactis is a well-known workhorse for dairy products, whose important industrial traits are tightly associated with numerous cytoplasmic membrane proteins. However, roles of the signal recognition particle (SRP) pathway responsible for membrane protein targeting have not been studied in L. lactis. In this work, the putative genes ffh and ftsY encoding SRP pathway components were identified in the genome of L. lactis NZ9000. Experimental evidence showed that sequence mutation in either the ffh or ftsY was not lethal, but prolonged the lag phase of the resultant mutants Δffh and ΔftsY by 2 h and lowered their biomass to 85.7 % of the wild type under static conditions, as well as deprived the mutants of improved growth capacity under aerobic respiration conditions. Besides, the speeds of glucose consumption and lactate production were significantly decreased in the mutants. Then, the impact of the SPR components on acid resistance was detected, showing that the ffh and ftsY were transcriptionally upregulated by 3.02 ± 1.21 and 8.66 ± 1.01-fold in the wild type during acid challenge at pH 3.0, and cell survival of the Δffh and ΔftsY decreased by10- and 100-fold compared with the wild type. To explore the possible mechanism about the SRP pathway involved in the above physiological traits, proteomics analysis was performed and revealed that disruption of the Ffh or FtsY led to decrease in ribosomal proteins, but increase in DnaK, GroEL and heat shock protein GrpE, indicating that the SRP pathway was closely linked to protein synthesis and folding in L. lactis. Decrease in the fructose-bisphosphate aldolase, respiratory complexes NADH dehydrogenase, as well as glutamate decarboxylase was also detected in the Δffh and ΔftsY, which is consistent with the phenomena of impaired sugar metabolism and acid resistance. Our results demonstrated the dispensable SRP pathway could contribute to the maintenance of metabolism homeostasis and acid resistance of L. lactis.

Ribosomal computing: implementation of the computational method

BackgroundSeveral computational and mathematical models of protein synthesis have been explored to accomplish the quantitative analysis of protein synthesis components and polysome structure. The effect of gene sequence (coding and non-coding region) in protein synthesis, mutation in gene sequence, and functional model of ribosome needs to be explored to investigate the relationship among protein synthesis components further. Ribosomal computing is implemented by imitating the functional property of protein synthesis.ResultIn the proposed work, a general framework of ribosomal computing is demonstrated by developing a computational model to present the relationship between biological details of protein synthesis and computing principles. Here, mathematical abstractions are chosen carefully without probing into intricate chemical details of the micro-operations of protein synthesis for ease of understanding. This model demonstrates the cause and effect of ribosome stalling during protein synthesis and the relationship between functional protein and gene sequence. Moreover, it also reveals the computing nature of ribosome molecules and other protein synthesis components. The effect of gene mutation on protein synthesis is also explored in this model.ConclusionThe computational model for ribosomal computing is implemented in this work. The proposed model demonstrates the relationship among gene sequences and protein synthesis components. This model also helps to implement a simulation environment (a simulator) for generating protein chains from gene sequences and can spot the problem during protein synthesis. Thus, this simulator can identify a disease that can happen due to a protein synthesis problem and suggest precautions for it.

Large scale analysis of the SARS-CoV-2 main protease reveals marginal presence of nirmatrelvir-resistant SARS-CoV-2 Omicron mutants in Ontario, Canada, December 2021-September 2023.

In response to the COVID-19 pandemic, a new oral antiviral called nirmatrelvir-ritonavir (PaxlovidTM) was authorized for use in Canada in January 2022. In vitro studies have reported mutations in Mpro protein that may be associated with the development of nirmatrelvir resistance. To survey the prevalence, relevance and temporal patterns of Mpro mutations among SARS-CoV-2 Omicron lineages in Ontario, Canada. A total of 93,082 Mpro gene sequences from December 2021 to September 2023 were analyzed. Reported in vitro Mpro mutations were screened against our database using in-house data science pipelines to determine the nirmatrelvir resistance. Negative binomial regression was conducted to analyze the temporal trends in Mpro mutation counts over the study time period. A declining trend was observed in non-synonymous mutations of Mpro sequences, showing a 7.9% reduction (95% CI: 6.5%-‬9.4%; p<0.001) every 30 days. The P132H was the most prevalent mutation (higher than 95%) in all Omicron lineages. In vitro nirmatrelvir-resistant mutations were found in 3.12% (n=29/929) Omicron lineages with very low counts, ranging from one to 19. Only two mutations, A7T (n=19) and M82I (n=9), showed temporal presence among the BA.1.1 in 2022 and the BQ.1.2.3 in 2022, respectively. The observations suggest that, as of September 2023, no significant or widespread resistance to nirmatrelvir has developed among SARS-CoV-2 Omicron variants in Ontario. This study highlights the importance of creating automated monitoring systems to track the emergence of nirmatrelvir-resistant mutations within the SARS-CoV-2 virus, utilizing genomic data generated in real-time.

Beyond RNA-binding domains: determinants of protein-RNA binding.

RNA-binding proteins (RBPs) are composed of RNA-binding domains (RBDs) often linked via intrinsically disordered regions (IDRs). Structural and biochemical analyses have shown that disordered linkers contribute to RNA binding by orienting the adjacent RBDs and also characterized certain disordered repeats that directly contact the RNA. However, the relative contribution of IDRs and predicted RBDs to the in vivo binding pattern is poorly explored. Here, we upscaled the RNA-tagging method to map the transcriptome-wide binding of 16 RBPs in budding yeast. We then performed extensive sequence mutations to distinguish binding determinants within predicted RBDs and the surrounding IDRs in eight of these. The majority of the predicted RBDs tested were not individually essential for mRNA binding. However, multiple IDRs that lacked predicted RNA-binding potential appeared essential for binding affinity or specificity. Our results provide new insights into the function of poorly studied RBPs and emphasize the complex and distributed encoding of RBP-RNA interaction in vivo.