Key Mutations Research Articles

Long-term monitoring of SARS-CoV-2 variants in wastewater using a coordinated workflow of droplet digital PCR and nanopore sequencing

Quantitative polymerase chain reaction (PCR) and genome sequencing are important methods for wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The reverse transcription-droplet digital PCR (RT-ddPCR) is a highly sensitive method for quantifying SARS-CoV-2 RNA in wastewater samples to track the trends of viral activity levels but cannot identify new variants. It also takes time to develop new PCR-based assays targeting variants of interest. Whole genome sequencing (WGS) can be used to monitor known and new SARS-CoV-2 variants, but it is generally not quantitative. Several short-read sequencing techniques can be expensive and might experience delayed turnaround times when outsourced due to inadequate in-house resources. Recently, a portable nanopore sequencing system offers an affordable and real-time method for sequencing SARS-CoV-2 variants in wastewater. This technology has the potential to enable swift response to disease outbreaks without relying on clinical sequencing results. In addressing concerns related to rapid turnaround time and accurate variant analysis, both RT-ddPCR and nanopore sequencing methods were employed to monitor the emergence of SARS-CoV-2 variants in wastewater. This surveillance was conducted at 23 sewer maintenance hole sites and five wastewater treatment plants in Michigan from 2020 to 2022. In 2020, the wastewater samples were dominated by the parental variants (20A, 20C and 20 G), followed by 20I (Alpha, B.1.1.7) in early 2021 and the Delta variant of concern (VOC) in late 2021. For the year 2022, Omicron variants dominated. Nanopore sequencing has the potential to validate suspected variant cases that were initially undetermined by RT-ddPCR assays. The concordance rate between nanopore sequencing and RT-ddPCR assays in identifying SARS-CoV-2 variants to the clade-level was 76.9%. Notably, instances of disagreement between the two methods were most prominent in the identification of the parental and Omicron variants. We also showed that sequencing wastewater samples with SARS-CoV-2 N gene concentrations of >104 GC/100 ml as measured by RT-ddPCR improve genome recovery and coverage depth using MinION device. RT-ddPCR was better at detecting key spike protein mutations A67V, del69–70, K417N, L452R, N501Y, N679K, and R408S (p-value <0.05) as compared to nanopore sequencing. It is suggested that RT-ddPCR and nanopore sequencing should be coordinated in wastewater surveillance where RT-ddPCR can be used as a preliminary quantification method and nanopore sequencing as the confirmatory method for the detection of variants or identification of new variants. The RT-ddPCR and nanopore sequencing methods reported here can be adopted as a reliable in-house analysis of SARS-CoV-2 in wastewater for rapid community level surveillance and public health response.

Engineering of glycoside hydrolase family 7 cellobiohydrolases directed by natural diversity screening

Protein engineering and screening of processive fungal cellobiohydrolases (CBHs) remain challenging due to limited expression hosts, synergy-dependency, and recalcitrant substrates. In particular, GH7 CBHs are a family critically important for the bioeconomy as well as a methodology for improving these and other difficult to engineer enzymes. Here, we target the discovery of highly active natural GH7 CBHs and engineering of variants with improved activity. Using experimentally assayed activities of genome mined CBHs, we applied sequence and structural alignments to top performers to identify key point mutations linked to improved activity. From ∼1500 known GH7 sequences, an evolutionarily diverse subset of 57 GH7 CBH genes was expressed in Trichoderma reesei and screened using a multiplexed activity screening assay. Ten catalytically enhanced natural variants were identified, produced, purified, and tested for efficacy using industrially-relevant conditions and substrates. Three key amino acids in CBHs with performance comparable or superior to Penicillium funiculosum Cel7A were identified and combinatorically engineered into P. funiculosum cel7a, expressed in T. reesei, and assayed on lignocellulosic biomass. The top performer generated using this combined approach of natural diversity genome mining, experimental assays, and computational modeling produced a 41% increase in conversion extent over native P. funiculosum Cel7A, a 55% increase over the current industrial standard T. reesei Cel7A, and 10% improvement over Aspergillus oryzae Cel7C, the best natural GH7 CBH previously identified in our laboratory.

How many Mutations are needed to Evolve the Chemical Makeup of a Synthetic Cell?

The chemical evolution of a synthetic cell endowed with a synthetic amino acid as building block, analog to tryptophan, required the emergence of key mutations in genes involved in, inter alia, the general stress response, amino acid metabolism, stringent response, and chemotaxis. Understanding adaptation mechanisms to non-canonical biomass components will inform strategies for engineering synthetic metabolic pathways and cells.

A framework for automated scalable designation of viral pathogen lineages from genomic data.

Pathogen lineage nomenclature systems are a key component of effective communication and collaboration for researchers and public health workers. Since February 2021, the Pango dynamic lineage nomenclature for SARS-CoV-2 has been sustained by crowdsourced lineage proposals as new isolates were sequenced. This approach is vulnerable to time-critical delays as well as regional and personal bias. Here we developed a simple heuristic approach for dividing phylogenetic trees into lineages, including the prioritization of key mutations or genes. Our implementation is efficient on extremely large phylogenetic trees consisting of millions of sequences and produces similar results to existing manually curated lineage designations when applied to SARS-CoV-2 and other viruses including chikungunya virus, Venezuelan equine encephalitis virus complex and Zika virus. This method offers a simple, automated and consistent approach to pathogen nomenclature that can assist researchers in developing and maintaining phylogeny-based classifications in the face of ever-increasing genomic datasets.

Cell fate regulation governed by p53: Friends or reversible foes in cancer therapy.

Cancer is a leading cause of death worldwide. Targeted therapies aimed at key oncogenic driver mutations in combination with chemotherapy and radiotherapy as well as immunotherapy have benefited cancer patients considerably. Tumor protein p53 (TP53), a crucial tumor suppressor gene encoding p53, regulates numerous downstream genes and cellular phenotypes in response to various stressors. The affected genes are involved in diverse processes, including cell cycle arrest, DNA repair, cellular senescence, metabolic homeostasis, apoptosis, and autophagy. However, accumulating recent studies have continued to reveal novel and unexpected functions of p53 in governing the fate of tumors, for example, functions in ferroptosis, immunity, the tumor microenvironment and microbiome metabolism. Among the possibilities, the evolutionary plasticity of p53 is the most controversial, partially due to the dizzying array of biological functions that have been attributed to different regulatory mechanisms of p53 signaling. Nearly 40 years after its discovery, this key tumor suppressor remains somewhat enigmatic. The intricate and diverse functions of p53 in regulating cell fate during cancer treatment are only the tip of the iceberg with respect to its equally complicated structural biology, which has been painstakingly revealed. Additionally, TP53 mutation is one of the most significant genetic alterations in cancer, contributing to rapid cancer cell growth and tumor progression. Here, we summarized recent advances that implicate altered p53 in modulating the response to various cancer therapies, including chemotherapy, radiotherapy, and immunotherapy. Furthermore, we also discussed potential strategies for targeting p53 as a therapeutic option for cancer.

Novel insights on genetics and epigenetics as clinical targets for paediatric astrocytoma.

Paediatric and adult astrocytomas are notably different, where clinical treatments used for adults are not as effective on children with the same form of cancer and these treatments lead to adverse long-term health concerns. Integrative omics-based studies have shown the pathology and fundamental molecular characteristics differ significantly and cannot be extrapolated from the more widely studied adult disease. Recent clinical advances in our understanding of paediatric astrocytomas, with the aid of next-generation sequencing and epigenome-wide profiling, have led to the identification of key canonical mutations that vary based on the tumour location and age of onset. These driver mutations, in particular the identification of the recurrent histone H3 mutations in high-grade tumours, have confirmed the important role epigenetic dysregulations play in cancer progression. This review summarises the current updates of the classification, epidemiology, pathogenesis and clinical management of paediatric astrocytoma based on their grades and the ongoing clinical trials. It also provides novel insights on genetic and epigenetic alterations as diagnostic biomarkers, highlighting the potential of targeting these pathways as therapeutics for this devastating childhood cancer.

Effects of a key acidic residue mutation on an AbpSH3 domain binding pathway

Effects of a key acidic residue mutation on an AbpSH3 domain binding pathway

The distribution of mutations across tumor size in ccRCC and their prognostic importance in small masses.

479 Background: Substantial efforts have been made to delineate mutational pathways to progression in ccRCC and the prognostic importance of key mutations, yet the distribution of these mutations across tumor size remains unknown. We hypothesized that VHL and PBRM, as more truncal mutations, would be roughly equally prevalent across tumor sizes, while mutations associated with aggressive disease - SETD2, BAP1, and CDKN2a copy-number loss - would be predominantly observed in larger tumors. We further hypothesized that SETD2, BAP1, and CDKN2a copy-number loss mutations, when present in smaller (≤7 cm) ccRCC tumors, would portend worse prognosis. Methods: We assessed a combined cohort of 333 ccRCC tumors from TCGA-KIRC and TRACERx Renal for the distribution of mutations across tumor size. Logistic regression was used to model the presence of each mutation against tumor size. We assessed a subset of 194 tumors ≤7cm for associations of key mutations with clinical outcomes while controlling for size. In small masses, logistic regression was used to model the presence of metastatic disease and invasive disease, and Cox proportional hazards was used to model overall survival, against SETD2, BAP1, CDKN2a copy-number loss, and tumor size. Results: On logistic regression an increase in one centimeter of tumor size was associated with SETD2, BAP1, and CDKN2a loss at odds ratios of 1.16, 1.11, 1.19 (p&lt;0.05); whereas no significant association was observed between tumor size and both VHL and PBRM1 (p=0.18, p=0.65). Among 194 tumors ≤7 cm, SETD2 and CDKN2a loss were associated with metastatic disease at odds ratios of 3.86 and 3.84 (p&lt;0.05); CDKN2a loss was associated with worse overall survival at hazard ratio 2.19 (p&lt;0.05), all while controlling for tumor size. Conclusions: SETD2 mutations, BAP1 mutations, and CDKN2a copy-number loss are rare in small ccRCC and are increasingly common in larger tumors, whereas VHL and PBRM1 are fairly evenly distributed across tumor sizes. In tumors≤7 cm, SETD2 mutation and CDKN2a loss were associated with metastatic disease and CDKN2a loss was associated with worse overall survival. SETD2 mutations and CDKN2a loss may help risk stratify ccRCC in biopsied and resected tumors. [Table: see text]

Simultaneous utilization of glucose and xylose by metabolically engineered Pseudomonas putida for the production of 3-hydroxypropionic acid

Pseudomonas putida,a robust candidate for lignocellulosicbiomass-based biorefineries, encounters challenges in metabolizing xylose. In this study, Weimberg pathway was introduced intoP. putidaEM42 under a xylose-inducible promoter, resulting in slow cell growth (0.05 h−1) on xylose.Through adaptive laboratory evolution, an evolved strain exhibited highly enhanced growth on xylose (0.36 h−1), comparable to that on glucose (0.39 h−1). Whole genome sequencing identified four mutations, with two key mutations located inPP3380andPP2219. Reverse-engineered strain 8EM42_Xyl, harboring these two mutations, showed enhanced growth on xylose but co-utilizing glucose and xylose at a rate of 0.3 g/L/h. Furthermore, 8EM42_Xyl was employed for 3-hydroxypropionic acid (3HP) production from glucose and xylose by expressing malonyl-CoA reductase and acetyl-CoA carboxylase, yielding 29 g/L in fed-batch fermentation. Moreover, the engineered strain exhibited promising performance in 3HP production from empty palm fruit bunch hydrolysate, demonstrating its potential as a promising cell factory forbiorefineries.

The role of differentially expressed genes and immune cell infiltration in the progression of nonalcoholic steatohepatitis (NASH) to hepatocellular carcinoma (HCC): a new exploration based on bioinformatics analysis

Nonalcoholic fatty liver disease (NAFLD) is a spectrum of chronic liver disease characterized. The condition ranges from isolated excessive hepatocyte triglyceride accumulation and steatosis (nonalcoholic fatty liver (NAFL), to hepatic triglyceride accumulation plus inflammation and hepatocyte injury (nonalcoholic steatohepatitis (NASH)) and finally to hepatic fibrosis and cirrhosis and/or hepatocellular carcinoma (HCC). However, the mechanism driving this process is not yet clear. Obtain sample microarray from the GEO database. Extract 6 healthy liver samples, 74 nonalcoholic hepatitis samples, 8 liver cirrhosis samples, and 53 liver cancer samples from the GSE164760 dataset. We used the GEO2R tool for differentially expressed genes (DEGs) analysis of disease progression (nonalcoholic hepatitis healthy group, cirrhosis nonalcoholic hepatitis group, and liver cancer cirrhosis group) and necroptosis gene set. Gene set variation analysis (GSVA) is used to evaluate the association between biological pathways and gene features. The STRING database and Cytoscape software were used to establish and visualize protein-protein interaction (PPI) networks and identify the key functional modules of DEGs, drawn factor-target genes regulatory network. Gene Ontology (GO) and KEGG pathway enrichment analyses of DEGs were also performed. Additionally, immune infiltration patterns were analyzed using the cibersort, and the correlation between immune cell-type abundance and DEGs expression was investigated. We further screened and obtained a total of 152 intersecting DEGs from three groups. 23 key genes were obtained through the MCODE plugin. Transcription factors regulating common differentially expressed genes were obtained in the hTFtarget database, and a TF target network diagram was drawn. There are 118 nodes, 251 edges, and 4 clusters in the PPI network. The key genes of the four modules include METAP2, RPL14, SERBP1, EEF2; HR4A1; CANX; ARID1A, UBE2K. METAP2, RPL14, SERBP1 and EEF2 was identified as the key hub genes. CREB1 was identified as the hub TF interacting with those gens by taking the intersection of potential TFs. The types of key gene changes were genetic mutations. It can be seen that the incidence of key gene mutations is 1.7% in EEF2, 0.8% in METAP2, and 0.3% in RPL14, respectively. Finally, We found that the most significant expression differences of the immune infiltrating cells among the three groups, were Tregs and M2, M0 type macrophages. We identified four hub genes METAP2, RPL14, SERBP1 and EEF2 being the most closely with the process from NASH to cirrhosis to HCC. It is beneficial to examine and understand the interaction between hub DEGs and potential regulatory molecules in the process. This knowledge may provide a novel theoretical foundation for the development of diagnostic biomarkers and gene-related therapy targets in the process.

Differential laboratory passaging of SARS-CoV-2 viral stocks impacts the in vitro assessment of neutralizing antibodies.

Viral populations in natural infections can have a high degree of sequence diversity, which can directly impact immune escape. However, antibody potency is often tested in vitro with a relatively clonal viral populations, such as laboratory virus or pseudotyped virus stocks, which may not accurately represent the genetic diversity of circulating viral genotypes. This can affect the validity of viral phenotype assays, such as antibody neutralization assays. To address this issue, we tested whether recombinant virus carrying SARS-CoV-2 spike (VSV-SARS-CoV-2-S) stocks could be made more genetically diverse by passage, and if a stock passaged under selective pressure was more capable of escaping monoclonal antibody (mAb) neutralization than unpassaged stock or than viral stock passaged without selective pressures. We passaged VSV-SARS-CoV-2-S four times concurrently in three cell lines and then six times with or without polyclonal antiserum selection pressure. All three of the monoclonal antibodies tested neutralized the viral population present in the unpassaged stock. The viral inoculum derived from serial passage without antiserum selection pressure was neutralized by two of the three mAbs. However, the viral inoculum derived from serial passage under antiserum selection pressure escaped neutralization by all three mAbs. Deep sequencing revealed the rapid acquisition of multiple mutations associated with antibody escape in the VSV-SARS-CoV-2-S that had been passaged in the presence of antiserum, including key mutations present in currently circulating Omicron subvariants. These data indicate that viral stock that was generated under polyclonal antiserum selection pressure better reflects the natural environment of the circulating virus and may yield more biologically relevant outcomes in phenotypic assays. Thus, mAb assessment assays that utilize a more genetically diverse, biologically relevant, virus stock may yield data that are relevant for prediction of mAb efficacy and for enhancing biosurveillance.

Genomic alteration in sporadic adolescent and young adult-onset colorectal adenocarcinoma.

154 Background: Colorectal cancer (CRC) incidence is increasing in adults younger than 50 years. This study evaluated genomic alteration in adolescent and young adult (AYA)-onset sporadic CRC patients who aged between 15 and 39 years. Methods: DNA from 90 archived formalin-fixed, paraffin-embedded (FFPE) tissue samples that histologically confirmed adenocarcinoma with proficient mismatch repair tumors at Siriraj Hospital (Bangkok, Thailand) were extracted. Patients who clinically suspected familial adenomatous polyposis were excluded. Gene mutational analysis was performed by next-generation sequencing (NGS) using an Oncomine Comprehensive Assay Plus kit (Thermo Fisher Scientific, Inc., Waltham, MA, USA) and compared with previous reported molecular data in adult-onset CRC from our group. Results: The top 5 mutations frequency observed were TP53, KRAS, FBXW7, PIK3CA, and SMAD4 mutations which were comparable to what reported in adult-onset CRC. However, FBXW7, PIK3CA, NOTCH1, FGFR3, ERBB2, and PTEN were reported more frequent in AYA group. No difference in number of KRAS, NRAS, and BRAF mutations among 2 groups. Table below shows key cancer genes mutation frequencies. Conclusions: This study is the comprehensive report hotspot mutations using NGS in sporadic AYA-onset sporadic CRC patients. The most commonly identified gene mutation frequencies among AYA-onset were similar to those reported in adult-onset, except for FBXW7, PIK3CA, NOTCH1, FGFR3, ERBB2, and PTEN mutations that had a slightly higher frequency. Further studies on larger sample set for genetic and epigenetic landscape are required. [Table: see text]

Trade-offs between receptor modification and fitness drive host-bacteriophage co-evolution leading to phage extinction or co-existence.

Parasite-host co-evolution results in population extinction or co-existence, yet the factors driving these distinct outcomes remain elusive. In this study, Salmonella strains were individually co-evolved with the lytic phage SF1 for 30days, resulting in phage extinction or co-existence. We conducted a systematic investigation into the phenotypic and genetic dynamics of evolved host cells and phages to elucidate the evolutionary mechanisms. Throughout co-evolution, host cells displayed diverse phage resistance patterns: sensitivity, partial resistance, and complete resistance, to wild-type phage. Moreover, phage resistance strength showed a robust linear correlation with phage adsorption, suggesting that surface modification-mediated phage attachment predominates as the resistance mechanism in evolved bacterial populations. Additionally, bacterial isolates eliminating phages exhibited higher mutation rates and lower fitness costs in developing resistance compared to those leading to co-existence. Phage resistance genes were classified into two categories: key mutations, characterized by nonsense/frameshift mutations in rfaH-regulated rfb genes, leading to the removal of the receptor O-antigen; and secondary mutations, which involve less critical modifications, such as fimbrial synthesis and tRNA modification. The accumulation of secondary mutations resulted in partial and complete resistance, which could be overcome by evolved phages, whereas key mutations conferred undefeatable complete resistance by deleting receptors. In conclusion, higher key mutation frequencies with lower fitness costs promised strong resistance and eventual phage extinction, whereas deficiencies in fitness cost, mutation rate, and key mutation led to co-existence. Our findings reveal the distinct population dynamics and evolutionary trade-offs of phage resistance during co-evolution, thereby deepening our understanding of microbial interactions.

Analytical and Clinical Validation of a Highly Sensitive NGS-Based ctDNA Assay with Real-World Concordance in Non-Small Cell Lung Cancer.

There have been needs to improve the sensitivity of liquid biopsy. This report aims to report the analytical and clinical validation of a next-generation sequencing (NGS)-based circulating tumor DNA (ctDNA) assay. Analytical validation was conducted in vitro by evaluating the limit of detection (LOD), precision, and specificity for various genomic aberrations. The real-world performance in non-small cell lung cancer (NSCLC) was assessed by comparing the results of AlphaLiquid100 to the tissue-based results. The LODs with 30 ng input DNA were 0.11%, 0.11%, 0.06%, 0.21%, and 2.13 copies for detecting single nucleotide variants, insertions, deletions, fusions, and copy number alterations (CNA), respectively. Quantitatively, single nucleotide variants/insertions and deletions, fusions, and CNAs showed a good correlation (R2=0.91, 0.40, and 0.65; y=0.95, 1.06, and 1.19) to the manufacturer's values, and per-base specificities for all types of variants were near 100%. In real-world NSCLC (n=122), key actionable mutations in NSCLC were detected in 60.7% (74/122) with the ctDNA assay. Comparative analysis against the NGS-based tissue results for all key mutations showed positive percent agreement (PPA) of 85.3%. For individual genes, the PPA was as high as 95.7% for epidermal growth factor receptor (EGFR) mutations and 83.3% for ALK translocations. AlphaLiquid100 detected drug-sensitive EGFR mutation at a variant allele frequency as low as 0.02% and also identified an EGFR mutation in a case where tissue sample missed. Blood samples collected post-targeted therapies revealed additional acquired mutations. The AlphaLiquid100 ctDNA assay demonstrates robust analytical validity, offering clinically important information for NSCLC patients.

Development of multiplex allele-specific RT-qPCR assays for differentiation of SARS-CoV-2 Omicron subvariants.

Quick differentiation of current circulating variants and the emerging recombinant variants of SARS-CoV-2 is essential to monitor their transmissions. However, the widely applied gene sequencing method is time-consuming and costly especially when facing recombinant variants, because a large part or whole genome sequencing is required. Allele-specific reverse transcriptase real time RT-PCR (RT-qPCR) represents a quick and cost-effective method for SNP (single nucleotide polymorphism) genotyping and has been successfully applied for SARS-CoV-2 variant screening. In the present study, we developed a panel of 5 multiplex allele-specific RT-qPCR assays targeting 20 key mutations for quick differentiation of the Omicron subvariants (BA.1 to BA.5 and their descendants) and the recombinant variants (XBB.1 and XBB.1.5). Two parallel multiplex RT-qPCR reactions were designed to separately target the prototype allele and the mutated allele of each mutation in the allele-specific RT-qPCR assay. Optimal annealing temperatures, primer and probe dosage, and time for annealing/extension for each reaction were determined by multi-factor and multi-level orthogonal test. The variation of Cp (crossing point) values (ΔCp) between the two multiplex RT-qPCR reactions was applied to determine if a mutation occurs or not. SARS-CoV-2 subvariants and related recombinant variants were differentiated by their unique mutation patterns. The developed multiplex allele-specific RT-qPCR assays exhibited excellent analytical sensitivities (with limits of detection (LoDs) of 1.47-18.52 copies per reaction), wide linear detection ranges (109-100 copies per reaction), good amplification efficiencies (88.25 to 110.68%), excellent reproducibility (coefficient of variations (CVs) < 5% in both intra-assay and inter-assay tests), and good clinical performances (99.5-100% consistencies with Sanger sequencing). The developed multiplex allele-specific RT-qPCR assays in the present study provide an alternative tool for quick differentiation of the SARS-CoV-2 Omicron subvariants and their recombinant variants. KEY POINTS: • A panel of five multiplex allele-specific RT-qPCR assays for quick differentiation of 11 SARS-CoV-2 Omicron subvariants (BA.1, BA.2, BA.4, BA.5, and their descendants) and 2 recombinant variants (XBB.1 and XBB.1.5). • The developed assays exhibited good analytical sensitivities and reproducibility, wide linear detection ranges, and good clinical performances, providing an alternative tool for quick differentiation of the SARS-CoV-2 Omicron subvariants and their recombinant variants.

Social network analysis of cell networks improves deep learning for prediction of molecular pathways and key mutations in colorectal cancer

Colorectal cancer (CRC) is a primary global health concern, and identifying the molecular pathways, genetic subtypes, and mutations associated with CRC is crucial for precision medicine. However, traditional measurement techniques such as gene sequencing are costly and time-consuming, while most deep learning methods proposed for this task lack interpretability. This study offers a new approach to enhance the state-of-the-art deep learning methods for molecular pathways and key mutation prediction by incorporating cell network information. We build cell graphs with nuclei as nodes and nuclei connections as edges of the network and leverage Social Network Analysis (SNA) measures to extract abstract, perceivable, and interpretable features that explicitly describe the cell network characteristics in an image. Our approach does not rely on precise nuclei segmentation or feature extraction, is computationally efficient, and is easily scalable. In this study, we utilize the TCGA-CRC-DX dataset, comprising 499 patients and 502 diagnostic slides from primary colorectal tumours, sourced from 36 distinct medical centres in the United States. By incorporating the SNA features alongside deep features in two multiple instance learning frameworks, we demonstrate improved performance for chromosomal instability (CIN), hypermutated tumour (HM), TP53 gene, BRAF gene, and Microsatellite instability (MSI) status prediction tasks (2.4%–4% and 7–8.8% improvement in AUROC and AUPRC on average). Additionally, our method achieves outstanding performance on MSI prediction in an external PAIP dataset (99% AUROC and 98% AUPRC), demonstrating its generalizability. Our findings highlight the discrimination power of SNA features and how they can be beneficial to deep learning models’ performance and provide insights into the correlation of cell network profiles with molecular pathways and key mutations.

Mechanistic study of the transmission pattern of the SARS-CoV-2 omicron variant.

The omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) characterized by 30 mutations in its spike protein, has rapidly spread worldwide since November 2021, significantly exacerbating the ongoing COVID-19 pandemic. In order to investigate the relationship between these mutations and the variant's high transmissibility, we conducted a systematic analysis of the mutational effect on spike-angiotensin-converting enzyme-2 (ACE2) interactions and explored the structural/energy correlation of key mutations, utilizing a reliable coarse-grained model. Our study extended beyond the receptor-binding domain (RBD) of spike trimer through comprehensive modeling of the full-length spike trimer rather than just the RBD. Our free-energy calculation revealed that the enhanced binding affinity between the spike protein and the ACE2 receptor is correlated with the increased structural stability of the isolated spike protein, thus explaining the omicron variant's heightened transmissibility. The conclusion was supported by our experimental analyses involving the expression and purification of the full-length spike trimer. Furthermore, the energy decomposition analysis established those electrostatic interactions make major contributions to this effect. We categorized the mutations into four groups and established an analytical framework that can be employed in studying future mutations. Additionally, our calculations rationalized the reduced affinity of the omicron variant towards most available therapeutic neutralizing antibodies, when compared with the wild type. By providing concrete experimental data and offering a solid explanation, this study contributes to a better understanding of the relationship between theories and observations and lays the foundation for future investigations.

New findings on the genetic basis of feathered legs in chickens: association of CUBN gene mutations with feathered-leg phenotype.

Chickens are the most thoroughly domesticated vertebrate species, and after long-continued natural and artificial selection, they now show rich phenotypic diversity. In particular, feathered legs present in domestic chickens are a characteristic that is carefully selected by advanced breeders. Previous studies have identified the key mutations responsible for feathered legs on chromosomes 13 and 15; however, not all chickens can be easily distinguished based on these two markers. In this study, whole-genome resequencing of 29 Bamaxiaogu chickens (BXCs) yielded 12,201,978 valid single-nucleotide polymorphisms (SNPs) and 2,792,426 valid insertions and deletions (InDels). Population structure analysis based on SNPs revealed that the test samples came from the same natural population. Based on these findings, we used an SNP- and InDel-based genome-wide association study (GWAS) to investigate the genetic basis of feathered legs in chickens. GWAS results revealed that 2 SNPs located in the introns of cubilin (CUBN; SNP1, chr2:19885382T>A) and recombinant Ras suppressor protein 1 (RSU1) genes (SNP2, chr2:20002551G>A), as well as an InDel (InDel1, chr2:19884383TG>T) on CUBN, were all significantly associated with the presence of feathered legs. Diagnostic testing demonstrated that SNP1 effectively differentiated between chickens with feathered legs and those with clean legs (leg without feathers) within the BXC population and may thus be considered an effective marker of feathered legs in BXC. In contrast, other loci did not show the same discriminatory power. This study not only presents a new variant of feathered legs but also provides valuable novel insights into the underlying mechanisms of variation in the feathered-legs trait among chickens.

Molecular characterization of canine parvovirus type 2 (CPV2) reveals a high prevalence of the CPV2c genotype among dogs suffering from diarrhea

AbstractCanine parvovirus 2 (CPV-2) is a highly contagious virus in dogs that typically causes hemorrhagic enteritis and a high mortality rate in unvaccinated puppies. The genetic variability and antigenic diversity of CPV-2 hinder its effective prevention of infection by vaccination. To investigate the epidemiology and genetic characteristics of CPV-2 in China, rectal swabs from affected dogs were collected from different animal clinics in Kunshan from 2022 to 2023. Preliminary detection and capsid gene sequencing of CPV-2 were performed using previously described primers and protocols. The overall detection rate for CPV-2 was 16.5% (33/200). A significant association was found between the CPV-2-positivity and clinical signs, age, breed and vaccination status. Sequence analysis revealed the presence of CPV-2c genotypes in all positive samples, which were genetically similar to other Asian CPV-2c strains. Notably, four key mutations (A5G, F267Y, Y324I and Q370R) were detected in all isolates, and one novel mutation (I447M) was detected in three CPV-2 isolates. These mutations in the CPV-2 strains could impact vaccine efficacy and the effectiveness of the virus immune evasion. Surprisingly, no recombination events were observed between the identified CPV-2c strains and reference strains from China. Our data revealed that amino acid residues 324, 426 and 440 of VP2 may under strong selection pressure. This pattern of genetic variation in the CPV-2 lineage warrants continuous laboratory-based surveillance programs in other parts of China to better understand the pattern of seasonal distribution and association between emerging genotypes and the intensity of disease severity.

Recombination Events Among SARS-CoV-2 Omicron Subvariants: Impact on Spike Interaction With ACE2 Receptor and Neutralizing Antibodies.

The recombination plays a key role in promoting evolution of RNA viruses and emergence of potentially epidemic variants. Some studies investigated the recombination occurrence among SARS-CoV-2, without exploring its impact on virus-host interaction. In the aim to investigate the burden of recombination in terms of frequency and distribution, the occurrence of recombination was first explored in 44 230 Omicron sequences among BQ subvariants and the under investigation "ML" (Multiple Lineages) denoted sequences, using 3seq software. Second, the recombination impact on interaction between the Spike protein and ACE2 receptor as well as neutralizing antibodies (nAbs), was analyzed using docking tools. Recombination was detected in 56.91% and 82.20% of BQ and ML strains, respectively. It took place mainly in spike and ORF1a genes. For BQ recombinant strains, the docking analysis showed that the spike interacted strongly with ACE2 and weakly with nAbs. The mutations S373P, S375F and T376A constitute a residue network that enhances the RBD interaction with ACE2. Thirteen mutations in RBD (S373P, S375F, T376A, D405N, R408S, K417N, N440K, S477N, P494S, Q498R, N501Y, and Y505H) and NTD (Y240H) seem to be implicated in immune evasion of recombinants by altering spike interaction with nAbs. In conclusion, this "in silico" study demonstrated that the recombination mechanism is frequent among Omicron BQ and ML variants. It highlights new key mutations, that potentially implicated in enhancement of spike binding to ACE2 (F376A) and escape from nAbs (RBD: F376A, D405N, R408S, N440K, S477N, P494S, and Y505H; NTD: Y240H). Our findings present considerable insights for the elaboration of effective prophylaxis and therapeutic strategies against future SARS-CoV-2 waves.