Key Mutations Research Articles

Differential Impact of Spike Protein Mutations on SARS-CoV-2 Infectivity and Immune Evasion: Insights from Delta and Kappa Variants.

SARS-CoV-2 continues to pose a global health challenge due to its high transmissibility and mutability, with new variants emerging that potentially undermine vaccination and therapeutic efforts. Mutations in the spike protein, particularly in the receptor-binding domain (RBD), significantly influence viral transmissibility and immune escape. However, the complex interplay of these mutations and their combined effects on viral fitness remain to be analyzed. In this study, we investigated the functional impact of key mutations found in the Delta and Kappa variants of SARS CoV-2. Using pseudovirus assays, we demonstrated that the T478K and L452R mutations characteristic of the Delta variant primarily enhance viral infectivity, with minimal effect on antibody-mediated neutralization. Conversely, the E484Q mutation of the Kappa variant, alone or in combination with L452R, significantly improved evasion of antibody-mediated neutralization but appeared to compromise viral fitness and infectivity. Notably, contrary to previous reports, we found that the P681R mutation contributed neither to increased infectivity nor immune evasion at least in the assay system employed in this study. Our findings suggest that the Delta variant's global dominance over the Kappa variant may be attributed to its superior infectivity and transmissibility rather than enhanced immune evasion capabilities. These results provide valuable insights into the functional consequences of spike protein mutations and may aid in predicting the emergence and spread of future SARS-CoV-2 variants. Such understanding is crucial for enhancing public health preparedness and informing the development of next-generation vaccines and therapeutics.

Characterization of novel small molecule inhibitors of estrogen receptor-activation function 2 (ER-AF2).

Up to 40% of patients with estrogen receptor (ER)-positive breast cancer will develop resistance against the majority of current ER-directed therapies. Resistance can arise through various mechanisms such as increased expression levels of coregulators, and key mutations acquired in the receptor's ligand binding domain rendering it constitutively active. To overcome these resistance mechanisms, we explored targeting the ER Activation Function 2 (AF2) site, which is essential for coactivator binding and activation. Using artificial intelligence and the deep docking methodology, we virtually screened > 1billion small molecules and identified 290 potential AF2 binders that were then characterized and validated through an iterative screening pipeline of cell-based and cell-free assays. We ranked the compounds based on their ability to reduce the transcriptional activity of the estrogen receptor and the viability of ER-positive breast cancer cells. We identified a lead compound, VPC-260724, which inhibits ER activity at low micromolar range. We confirmed its direct binding to the ER-AF2 site through a PGC1α peptide displacement experiment. Using proximity ligation assays, we showed that VPC-260724 disrupts the interaction between ER-AF2 and the coactivator SRC-3 and reduces the expression of ER target genes in various breast cancer models including the tamoxifen resistant cell line TamR3. In conclusion, we developed a novel ER-AF2 binder, VPC-260724, which shows antiproliferative activity in ER-positive breast cancer models. The use of an ER-AF2 inhibitor in combination with current treatments may provide a novel complementary therapeutic approach to target treatment resistance in ER-positive breast cancer.

A four-hit mechanism is sufficient for meningioma development.

Meningiomas are central nervous system tumors whose incidence increases with age. Benign meningioma pathogenesis involves germline or somatic mutation of target genes, such as NF2, leading to clonal expansion. We used an established cancer epidemiology model to investigate the number of rate-limiting steps sufficient for benign meningioma development. Incidence data was obtained from the Surveillance, Epidemiology and End Results Program (SEER) for nonmalignant meningioma from 2004 to 2020. Age-adjusted incidence rates per 100,000 person-years were divided into 5-year bands. This was repeated for vestibular schwannomas as a negative control. The Armitage-Doll methodology was applied. Mathematical solutions correcting for volatile tumor microenvironments were applied to fit higher-order models using polynomial regression when appropriate. A 75:25 training:test split was utilized for validation. 222,509 cases of benign meningiomas were identified. We noted strong linear relationships between log-transformed incidence and age across the cohort and multiple subpopulations: male, white, black, Hispanic, Asian/Pacific Islander, and American Indian subpopulations all demonstrated R2 = 0.99. Slopes were between 3.1 and 3.4, suggesting a four-step process for benign meningioma development. Female patients exhibited nonlinear deviations, but the corrected model demonstrated R2 = 0.99 with a four-hit pathway. This model performed robustly on test data with R2 = 0.99. Vestibular schwannomas demonstrated a slope of 2.1 with R2 = 0.99, suggesting a separate three-step process. Four mutations are uniquely required for the development of benign meningiomas. Correcting for volatile tumor microenvironments reliably accounted for nonlinear deviations in behavior. Further studies are warranted to elucidate genomic findings suggestive of key mutations in this pathway.

Rapid and supersensitive allele detection of Plasmodium falciparum chloroquine resistance via a Pyrococcus furiosus argonaute-triggered dual-signal biosensing platform

BackgroundMalaria remains a serious public health problem worldwide, particularly in Africa. Resistance to antimalarial drugs is an essential issue for malaria control and elimination. Currently, polymerase chain reaction (PCR) combined with Sanger sequencing is regarded as the gold standard for mutation detection. However, this method fails to meet the requirements of point-of-care testing (POCT) because of its time-consuming, expensive instruments and professional dependence. To support this strategy, we developed a novel diagnostic platform that combines recombinase polymerase amplification (RPA) with the Pyrococcus furiosus argonaute (PfAgo) protein and was designed to detect gene mutations related to antimalarial drug resistance. The Pfcrt haplotypes CVMNK and CVIET of chloroquine resistance (CQR) were used as examples and were assessed in this study.MethodsBy meticulously designing strategies, RPA primers, guide DNAs, and probes were screened, the reaction was optimized, and the resulting parameters were employed to ascertain the genotype of Pfcrt. The recombinant plasmids pUC57/Pfcrt-CVIET and pUC57/Pfcrt-CVMNK were constructed and diluted for sensitivity detection. The pUC57/Pfcrt-CVIET plasmid mixture was added to the pUC57/Pfcrt-CVMNK plasmid mixture in different additions to configure several specific proportions of mixed plasmid mixtures. The RPA-PfAgo platform was used, and the mixed plasmid was detected simultaneously via nest-PCR (nPCR) and Sanger sequencing. The platform was then evaluated on 85 clinical samples and compared with Sanger sequencing.ResultsThe entire process achieves the key mutation Pfcrt-CVMNK/CVIET genotype identification of CQR within 90 min. The platform achieved 1.8 × 104 copies/μL sensitivity and could detect as little as 3% CVIET in mixed plasmids, which is a higher sensitivity than that of Sanger sequencing (5%). Notably, the platform shows 100% concordance with the gold standard method when 85 clinical samples are tested. The sensitivity and specificity were 100% for the 85 clinical samples.ConclusionsThis study established an RPA-PfAgo platform for genotyping the key mutation Pfcrt-CVMNK/CVIET of CQR. This method can rapidly produce reliable results and avoid the disadvantages of nPCR with sequencing. This approach has the characteristics of a short operation time, low device dependence, and a good match to the POCT strategy, suggesting that the platform can be easily applied locally or on site.Graphical abstract

Divergent lineage trajectories and genetic landscapes in human gastric intestinal metaplasia organoids associated with early neoplastic progression

BackgroundGastric intestinal metaplasia (IM) is a precancerous stage spanning a morphological spectrum that is poorly represented by human cell line models.ObjectiveWe aim to establish and characterise human IM cell models...

Rational design of uncleaved prefusion-closed trimer vaccines for human respiratory syncytial virus and metapneumovirus.

Respiratory syncytial virus (RSV) and human metapneumovirus (hMPV) cause human respiratory diseases and are major targets for vaccine development. In this study, we design uncleaved prefusion-closed (UFC) trimers for the fusion protein (F) of both viruses by examining mutations critical to F metastability. For RSV, we assess four previous prefusion F designs, including the first and second generations of DS-Cav1, SC-TM, and 847A. We then identify key mutations that can maintain prefusion F in a native-like, closed trimeric form (up to 76%) without introducing any interprotomer disulfide bond. For hMPV, we develop a stable UFC trimer with a truncated F2-F1 linkage and an interprotomer disulfide bond. Dozens of UFC constructs are characterized by negative-stain electron microscopy (nsEM), x-ray crystallography (11 RSV-F structures and one hMPV-F structure), and antigenic profiling. Using an optimized RSV-F UFC trimer as bait, we identify three potent RSV neutralizing antibodies (NAbs) from a phage-displayed human antibody library, with a public NAb lineage targeting sites Ø and V and two cross-pneumovirus NAbs recognizing site III. In mouse immunization, rationally designed RSV-F and hMPV-F UFC trimers induce robust antibody responses with high neutralizing titers. Our study provides a foundation for future prefusion F-based RSV and hMPV vaccine development.

Abstract A022: Novel technology affords real-time PCR the sensitivity required for minimal residual disease monitoring

Abstract Monitoring minimal residual disease (MRD) provides invaluable information for disease progression and therapeutic decision making. However, there are many challenges to reliably detect key mutations or biomarkers, such as the accessibility, turnaround time, and sensitivity of current methods. High sensitivity is crucial due to the limited DNA available in certain sample types such as liquid biopsy. Next generation sequencing (NGS) is capable of highly sensitive detection but is dependent on high sample input and read depth, which is not always feasible due to the variable nature of circulating tumor DNA (ctDNA) in blood or plasma. In addition, NGS is not an economical nor rapid option for recurrent longitudinal monitoring. Digital PCR (dPCR) offers the sensitivity required for MRD monitoring but has yet to be widely adopted for this application. While real-time and qPCR are commonly used in oncology research, RT-PCR does not have the sensitivity required for early detection of key MRD mutations. Here, we present novel patent-pending technology that enhances the sensitivity of RT-PCR, allowing this common platform to be used to reliably detect low abundant mutations. We performed comparisons between GT Molecular’s patent-pending technology paired with RT-PCR and commercially available research use only dPCR and NGS assays to assess the sensitivity this new technology provides for RT-PCR. Cell-free DNA (cfDNA) was extracted from real patient or contrived plasma samples using the QIAamp Circulating Nucleic Acid Kit and analyzed using RT-PCR and dPCR assays targeting KRAS or ESR1 mutations. Samples with KRAS or ESR1 mutations were tested at variant allele frequencies (VAFs) varying between 1%-0.01% to evaluate the ability of GT Molecular’s new technology to detect low abundant mutations using RT-PCR. KRAS and ESR1 mutations were reliably detected with RT-PCR at VAFs as low as 0.01%, demonstrating sensitivity comparable to dPCR. Samples demonstrating positivity for KRAS or ESR1 mutations via dPCR were also positive via RT-PCR. With this patent-pending technology, RT-PCR is now capable of achieving the sensitivity required for MRD monitoring, providing critical information from liquid biopsy samples at a fraction of the cost. Citation Format: Mary Stischer, Nick Allen, Stephanie Barbari, Sarah Kane. Novel technology affords real-time PCR the sensitivity required for minimal residual disease monitoring [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A022.

BIOM-07. SURVIVAL-ASSOCIATED GENETIC VARIATIONS IN TAIWANESE GLIOBLASTOMA MULTIFORME PATIENTS - A RETROSPECTIVE NGS STUDY

Abstract This retrospective study, conducted at Taichung Veterans General Hospital in Taiwan, employed Next-Generation Sequencing (NGS) technology to analyze genetic variations associated with survival in patients with glioblastoma multiforme (GBM). The study encompassed 30 newly diagnosed GBM patients, divided into two groups based on survival duration: long-term (over two years) and short-term (under two years). The findings are outlined below: Key Mutations: Significant mutations included CHEK2, IDH1, and TP53, along with variations in the TERT promoter and TP53 RNA splicing sites. Correlation Between Mutations and Survival: Contrary to Western data, TP53 mutations were more prevalent in the long-term survival group, suggesting that regional genetic differences may influence GBM prognosis. Therapeutic Effectiveness: The application of bevacizumab was significantly associated with improved survival rates, indicating its potential efficacy in treatment. The study highlights the critical role of personalized medicine in the treatment of GBM in Taiwan and points to the necessity of further research into the genetic characteristics and treatment responses of GBM patients in Taiwan and potentially other non-Western regions. These insights underline the importance of continuing to explore effective personalized treatment strategies and enhancing our understanding of genetic determinants in diverse populations. Moreover, the prevalence of certain mutations in Taiwanese patients, which differ from those commonly observed in Western populations, prompts a reevaluation of global treatment frameworks and suggests the potential for region-specific therapeutic protocols. The implication of these findings extends beyond immediate clinical applications, providing a foundation for future clinical trials and research into genetic markers that could dictate treatment choices. In conclusion, this study not only underscores the importance of individualized treatment plans based on genetic profiling but also highlights the variations in genetic mutations across different populations, which could have profound implications for the management of GBM worldwide. Further investigation into these disparities and their implications on treatment efficacy is essential for advancing GBM treatment and improving patient outcomes globally.

PATH-62. CORRELATES OF NEURAL SIGNALING ELUCIDATE SURVIVAL BENEFIT IN GLIOMAS

Abstract Recent literature has highlighted neural signaling markers (SM) as drivers for synaptogenesis, invasion, and proliferation in gliomas. Further work on elucidating key mutations can provide improved prognostication and potential treatment targets. Our objective is to identify correlates of neural signaling in relation to glioma histopathology and patient outcomes. We used a combination of bulk RNA sequencing (RNA-seq) and a DNA gene panel (DPG) by Tempus next-generation sequencing. Differential gene expression (DGE) was performed using DESeq2 after subsetting genes for neural SM. Dimensionality reduction was applied through t-SNE projections. Variant calls were analyzed using EnsemblVEP and maftools. Survival analysis was determined through log-rank tests. All analyses were conducted with R. 176 and 184 patient samples were analyzed for RNA-seq and DPG, respectively. t-SNE of DGE highlights two distinct functional clusters with no correlation to WHO classification status (Chi-squared p = 0.39) The median survival for the big cluster was observed at 957 days, while no median survival was reached even after 4,420 days of follow-up in the small cluster (p = 0.01). This contrast remains consistent when examining subsets of gliomas with unmethylated MGMT promoter (p = 0.02) and glioblastomas (p = 0.02), but not others such as IDH mutation status and low-grade gliomas (p > 0.1). Genes upregulated in the small cluster had equal representation of synaptic and paracrine SM (45% and 55%), while the big cluster had a greater representation of paracrine SM (69% and 31%). DPG of low-grade gliomas highlighted 3 somatic signaling mutations (FGFR1, PTPRD, and SLIT2) that are more prevalent in the big cluster. Functional classification based on neural signaling markers can elucidate a novel set of biomarkers that may impact survival in glioma patients. Further studies are required to validate such findings and develop therapeutic targets.

From precursor to cancer: decoding the intrinsic and extrinsic pathways of pancreatic intraepithelial neoplasia progression.

This review explores the progression of pancreatic intraepithelial neoplasia (PanIN) to pancreatic ductal adenocarcinoma through a dual lens of intrinsic molecular alterations and extrinsic microenvironmental influences. PanIN development begins with Kirsten rat sarcoma viral oncogene (KRAS) mutations driving PanIN initiation. Key additional mutations in cyclin-dependent kinase inhibitor 2A (CDKN2A), tumor protein p53 (TP53), and mothers against decapentaplegic homolog 4 (SMAD4) disrupt cell cycle control and genomic stability, crucial for PanIN progression from low-grade to high-grade dysplasia. Additional molecular alterations in neoplastic cells, including epigenetic modifications and chromosomal alterations, can further contribute to neoplastic progression. In parallel with these alterations in neoplastic cells, the microenvironment, including fibroblast activation, extracellular matrix remodeling, and immune modulation, plays a pivotal role in PanIN initiation and progression. Crosstalk between neoplastic and stromal cells influences nutrient support and immune evasion, contributing to tumor development, growth, and survival. This review underscores the intricate interplay between cell-intrinsic molecular drivers and cell-extrinsic microenvironmental factors, shaping PanIN predisposition, initiation, and progression. Future research aims to unravel these interactions to develop targeted therapeutic strategies and early detection techniques, aiming to alleviate the severe impact of pancreatic cancer by addressing both genetic predispositions and environmental influences.

TERT Gene Mutation in Gliomas Cross-Linked With (NTRK, PDL1, ALK, IDH, P53, EGFR, HER2): A Integrative Review TERT Gene Mutation in Gliomas.

Recent advancements in glioma treatment are largely driven by the identification of genetic alterations, which enhance diagnostic precision and prognostic assessments, and unveil potential therapeutic targets. TERT promoter mutations, in particular, are associated with a poorer prognosis and aggressive clinical behavior. This study explores the genetic interplay between TERT and other genes (ntrk, pdl1, alk, idh, p53, egfr, her2) in brain tumors through an integrative literature review. This method synthesizes evidence from selected articles spanning 2014 to 2023. The review identified 65 articles based on defined inclusion criteria, out of which 14 were analyzed in depth. Findings reveal that TERT, TP53, and IDH1 are the most frequently mutated genes in gliomas. The prognosis of glioma patients can be refined through the combined analysis of IDH and TERT mutations. Additionally, PD-L1 expression levels are associated with prognosis and may influence treatment responses, particularly, in immunotherapy. The study underscores the importance of molecular diagnostics, such as Next-Generation Sequencing (NGS), in detecting key genetic mutations. These advancements have paved the way for new therapeutic strategies and better patient outcomes. The findings highlight the crucial role of genetic markers in glioma treatment and prognosis, advocating for continued research to enhance clinical applications and patient care. The use of NGS is indispensable in identifying biomarkers associated with mutations in the TERT gene.

Unraveling the molecular mechanism of FgGcn5 inhibition by phenazine-1-carboxamide: combined in silico and in vitro studies.

Fusarium head blight (FHB), mainly caused by Fusarium graminearum (F. graminearum), remains a devastating disease worldwide. The histone acetyltransferase Gcn5 plays a crucial role in epigenetic regulation. Aberrant Gcn5 acetylation activity can result in serious impacts such as impaired growth and development in organisms. The secondary metabolite phenazine-1-carboxamide (PCN) inhibits F. graminearum by blocking the acetylation process of Gcn5 (FgGcn5), and is currently used to control FHB. However, the molecular basis of acetylation inhibition by PCN remains to be further explored. Our molecular dynamics simulations revealed that PCN binds to the cleft in FgGcn5 where histone H3 is bound, with key amino acid residues including Leu96 (L96), Arg121 (R121), Phe133 (F133), Tyr169 (Y169), and Tyr201 (Y201), preventing FgGcn5 from binding to histone H3 and affecting histone H3 from being acetylated. Experimental validation of key amino acid mutations further confirmed the impact of these mutations on the interaction of FgGcn5 with PCN and histone H3 peptide. In summary, our study sheds light on the mechanism by which PCN inhibits the acetylation function of FgGcn5, providing a foundation for the development of drugs or fungicides targeting histone acetyltransferases. © 2024 Society of Chemical Industry.

Tumor organoids improve mutation detection of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) presents challenges in detecting somatic mutations due to its complex cellular composition. This study investigated the utility of patient-derived organoids (PDOs) to overcome these obstacles and enhance somatic mutation identification. Surgically resected PDAC tumors and their paired PDOs from 21 patients were examined. Whole-exome sequencing (WES) of tumor tissue, organoids, and peripheral blood mononuclear cells was performed to identify somatic mutations. Our findings demonstrate that PDOs retained about 80% of the somatic mutations from the original tumors, showing high concordance in mutation types. PDOs exhibited increased tumor purity and uncovered key driver mutations, aiding in identifying clinically relevant genomic alterations. Moreover, eight cycles of FOLFIRINOX treatment did not significantly alter the mutational landscape at the DNA level, indicating the stability of the mutational profile after therapeutic pressure in patients. In conclusion, PDOs are potentially important tools for exploring the somatic mutational landscape of PDAC. While they can reveal mutations that may be challenging to detect through traditional biopsy sequencing due to the inherently low tumor purity of PDAC, it is important to note that PDOs may not always fully recapitulate all mutations found in primary tumors. Despite this limitation, PDOs can still offer critical insights into the genomic complexities of PDAC, which is crucial for the development of personalized vaccines and therapies for this disease.

Addressing the antibody germline bias and its effect on language models for improved antibody design.

The versatile binding properties of antibodies have made them an extremely important class of biotherapeutics. However, therapeutic antibody development is a complex, expensive, and time-consuming task, with the final antibody needing to not only have strong and specific binding but also be minimally impacted by developability issues. The success of transformer-based language models in protein sequence space and the availability of vast amounts of antibody sequences, has led to the development of many antibody-specific language models to help guide antibody design. Antibody diversity primarily arises from V(D)J recombination, mutations within the CDRs, and/or from a few nongermline mutations outside the CDRs. Consequently, a significant portion of the variable domain of all natural antibody sequences remains germline. This affects the pre-training of antibody-specific language models, where this facet of the sequence data introduces a prevailing bias toward germline residues. This poses a challenge, as mutations away from the germline are often vital for generating specific and potent binding to a target, meaning that language models need be able to suggest key mutations away from germline. In this study, we explore the implications of the germline bias, examining its impact on both general-protein and antibody-specific language models. We develop and train a series of new antibody-specific language models optimized for predicting nongermline residues. We then compare our final model, AbLang-2, with current models and show how it suggests a diverse set of valid mutations with high cumulative probability. AbLang-2 is trained on both unpaired and paired data, and is freely available at https://github.com/oxpig/AbLang2.git.

Real-time and programmable transcriptome sequencing with PROFIT-seq.

The high diversity and complexity of the eukaryotic transcriptome make it difficult to effectively detect specific transcripts of interest. Current targeted RNA sequencing methods often require complex pre-sequencing enrichment steps, which can compromise the comprehensive characterization of the entire transcriptome. Here we describe programmable full-length isoform transcriptome sequencing (PROFIT-seq), a method that enriches target transcripts while maintaining unbiased quantification of the whole transcriptome. PROFIT-seq employs combinatorial reverse transcription to capture polyadenylated, non-polyadenylated and circular RNAs, coupled with a programmable control system that selectively enriches target transcripts during sequencing. This approach achieves over 3-fold increase in effective data yield and reduces the time required for detecting specific pathogens or key mutations by 75%. We applied PROFIT-seq to study colorectal polyp development, revealing the intricate relationship between host immune responses and bacterial infection. PROFIT-seq offers a powerful tool for accurate and efficient sequencing of target transcripts while preserving overall transcriptome quantification, with broad applications in clinical diagnostics and targeted enrichment scenarios.

Analysis of genetic characteristics associated with reduced bedaquiline susceptibility in multidrug-resistant Mycobacterium tuberculosis

Bedaquiline (BDQ) has shown efficacy in shortening treatment duration and enhancing treatment success rates for multidrug-resistant tuberculosis (MDR-TB), thereby prompting widespread adoption. However, resistance to BDQ has emerged. This study aimed to identify genetic characteristics associated with decreased susceptibility to BDQ, using a public database to aid in the detection of resistant strains. Seventy-one BDQ-resistant and 929 BDQ-susceptible isolates from the open-source CRyPTIC database were selected for analysis. Variant calling was conducted via the clockwork pipeline. Univariate logistic regression was performed for each gene mutation, followed by LASSO regression for further variant selection. Ultimately, a multiple linear regression model was developed using log2-transformed Minimum Inhibitory Concentration values as the dependent variable, with variant selection refined through stepwise regression based on the Akaike Information Criterion. Ten gene mutations were significantly associated with reduced BDQ susceptibility, including two key gene mutations: Rv0678_141_ins_1 and Rv1979c_D249E, with effect estimates of 1.76 (95 % CI: 0.67–2.84) and 1.69 (95 % CI: 0.22–3.17), respectively. Other implicated genes included Rv2699c_-84_del_1, hsaB_I179T, mmpL9_T241A, pncA_C14R, Rv0373c_G621S, Rv0893c_L27F, Rv1770_A4D, and Rv3428c_S327C. This study identified ten gene mutations linked to decreased susceptibility to BDQ, providing a reference for developing a comprehensive catalog of BDQ-resistant genes.

Biologically-informed killer cell immunoglobulin-like receptor gene annotation tool.

Natural killer (NK) cells are essential components of the innate immune system, with their activity significantly regulated by Killer cell Immunoglobulin-like Receptors (KIRs). The diversity and structural complexity of KIR genes present significant challenges for accurate genotyping, essential for understanding NK cell functions and their implications in health and disease. Traditional genotyping methods struggle with the variable nature of KIR genes, leading to inaccuracies that can impede immunogenetic research. These challenges extend to high-quality phased assemblies, which have been recently popularized by the Human Pangenome Consortium. This article introduces BAKIR (Biologically informed Annotator for KIR locus), a tailored computational tool designed to overcome the challenges of KIR genotyping and annotation on high-quality, phased genome assemblies. BAKIR aims to enhance the accuracy of KIR gene annotations by structuring its annotation pipeline around identifying key functional mutations, thereby improving the identification and subsequent relevance of gene and allele calls. It uses a multi-stage mapping, alignment, and variant calling process to ensure high-precision gene and allele identification, while also maintaining high recall for sequences that are significantly mutated or truncated relative to the known allele database. BAKIR has been evaluated on a subset of the HPRC assemblies, where BAKIR was able to improve many of the associated annotations and call novel variants. BAKIR is freely available on GitHub, offering ease of access and use through multiple installation methods, including pip, conda, and singularity container, and is equipped with a user-friendly command-line interface, thereby promoting its adoption in the scientific community. BAKIR is available at github.com/algo-cancer/bakir.

Grain Lysine enrichment and improved stress tolerance in rice through protein engineering.

Amino acids are a major source of nourishment for people living in regions where rice is a staple food. However, rice grain is deficient in essential amino acids, such as lysine. The activity of dihydrodipicolinate synthase (DHDPS) enzyme is crucial for lysine production in higher plants, but it is highly regulated through a feedback inhibition by its end product lysine, leading to its limited activity in the grain and resulting in low lysine accumulation. We identified lysine binding sites in the DHDPS enzyme and introduced key mutations to make it lysine feedback insensitive. Using in vivo analysis and functional complementation assays, we confirmed that protein engineering of the DHDPS renders it insensitive to lysine. Expression of mutated DHDPS resulted in 29 % higher lysine and 15 % higher protein accumulation in rice grains than the wild type. Importantly, the lysine content in transgenic grains was maintained in cooked rice. Further, the transgenic plants exhibited enhanced stress tolerance along with better antioxidant levels, improved photosynthesis, and higher grain yield compared to wild type plants. We have shown for the first time in rice that protein engineering of DHDPS can lead to accumulation of lysine in grains and impart abiotic stress tolerance. This approach could improve health in regions with nutrient deficiencies and environmental stressors that challenge food production and human health.

Simultaneous co-circulation of two genotypes of dengue virus serotype 3 causing a large outbreak in Sri Lanka in year 2023.

We observed a discrepancy between dengue NS1 antigen test and molecular diagnostics, with the emergence of (DENV) serotype 3 in Sri Lanka and sought to understand the cause for the rise in cases and high failure rates of molecular diagnostics. Whole genomic sequencing was carried out in 22 DENV-3 samples. Phylogenetic and molecular clock analysis were done for genotype assignment and to understand the rate of evolution. Mutation analysis was done to understand the reasons for PCR non-detection. We identified two DENV-3 genotypes (I and III) co-circulating. DENV-3 genotype III strains shared a common ancestor with a sequence from India collected in 2022, while DENV-3 genotype I, was found to share a common ancestor with DENV-3 sequences from China. DENV-3 genotype III was detected by the modified CDC DENV-3 primers whereas, genotype I evaded detection due to key mutations at forward and reverse primer binding sites. We identified point mutations, C744T and A756G of the forward primer binding sites and in position G795A of the reverse primer binding sites which were not identified in DENV-3 genotype III. Furthermore, our Sri Lankan DENV-3 strains demonstrated a high root to tip ratio, compared to the previous DENV-3 sequences, indicating a high mutation rate during the points of sampling (year 2017 to 2023). The co-circulation of multiple genotypes associated with an increase in cases highlights the importance of continuous surveillance of DENVs to identify mutations resulting in non-detection by diagnostics and differences in virulence.

Impact of Genetic Testing on the Diagnosis, Management, and Prognosis of Hypertrophic Cardiomyopathy: A Systematic Review.

Hypertrophic cardiomyopathy (HCM) is a hereditary cardiovascular condition marked by heart muscle thickening, fibrosis, and myocardial disorders. It is often inherited in an autosomal dominant pattern. Symptoms include dyspnea, fatigue, palpitations, dizziness, syncope, and an increased risk of sudden cardiac death (SCD). Genetic studies have identified many asymptomatic carriers, indicating a higher prevalence of HCM. Advances in genetic testing (GT) and novel therapies, such as cardiac myosin inhibitors, have significantly impacted the diagnosis and management of HCM. This integrative review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and aimed to synthesize information regarding the impact of GT on the diagnosis and management of HCM patients. An electronic search was conducted on May 17, 2024, across PubMed, Embase, Scopus, Web of Science, and Cochrane databases, covering January 2020 to May 2024. Inclusion criteria were studies involving adult HCM patients who underwent GT and follow-up. Exclusion criteria included non-human studies, pediatric cases, non-HCM-related GT, non-peer-reviewed articles, systematic reviews, conference abstracts, and editorials. From 1,155 articles identified, 42 met the inclusion criteria after applying filters and removing duplicates. GT identified pathogenic variants in a significant proportion of HCM patients, enhancing diagnostic accuracy and management. Key mutations were found in myosin binding protein C3 and myosin heavy chain 7 genes. GT facilitated personalized management strategies, including risk stratification for SCD and family screening. Patients with identified mutations often required closer monitoring and tailored treatments. GT has revolutionized the diagnosis and management of HCM. The integration of genetic data has improved risk stratification, facilitated early intervention, and enhanced patient outcomes. Despite these advances, challenges remain in identifying genetic variants in some patients, emphasizing the need for continuous improvement in genetic panels and diagnostic methods. This review highlights the significant role of GT in optimizing HCM care through precise risk assessment and tailored treatment strategies.