DynaMut: predicting the impact of mutations on protein conformation, flexibility and stability

The stem region of group A transferase is crucial for its specificity, and its alteration promotes heterologous Forssman synthase activity

Some stem region mutants of human blood group A transferase (hAT) possess Forssman synthase (FS) activity, but very little is known about the mechanisms responsible for this enzymatic crosstalk. We performed confocal microscopy and image analysis to determine whether different intra-Golgi localization was accountable for this acquired activity. We also performed structural modeling and mutational and normal mode analyses. We introduced new mutations in the stem region and tested its FS and AT activities. No differences in subcellular localization were found between hAT and FS-positive mutants. AlphaFold models of hAT and mFS (mouse Forssman synthase) showed that the hAT stem region has a tether-like stem region, while in mFS, it encircles its catalytic domain. In silico analysis of FS-positive mutants indicated that stem region mutations induced structural changes, decreasing interatomic interactions and mobility of hAT that correlated with FS activity. Several additional mutations introduced in that region also bestowed FS activity without altering the AT activity: hAT 37-55 aa substitution by mFS 34-52, 37-55 aa deletion, and missense mutations: S46P, Q278Y, and Q286M. Stem region structure, mobility, and interactions are crucial for hAT specificity. Moreover, stem region mutations can lead to heterologous Forssman activity without changes in the catalytic machinery.

Spike protein mutations and structural insights of pangolin lineage B.1.1.25 with implications for viral pathogenicity and ACE2 binding affinity

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the causative agent of COVID -19, is constantly evolving, requiring continuous genomic surveillance. In this study, we used whole-genome sequencing to investigate the genetic epidemiology of SARS-CoV-2 in Bangladesh, with particular emphasis on identifying dominant variants and associated mutations. We used high-throughput next-generation sequencing (NGS) to obtain DNA sequences from COVID-19 patient samples and compared these sequences to the Wuhan SARS-CoV-2 reference genome using the Global Initiative for Sharing All Influenza Data (GISAID). Our phylogenetic and mutational analyzes revealed that the majority (88%) of the samples belonged to the pangolin lineage B.1.1.25, whereas the remaining 11% were assigned to the parental lineage B.1.1. Two main mutations, D614G and P681R, were identified in the spike protein sequences of the samples. The D614G mutation, which is the most common, decreases S1 domain flexibility, whereas the P681R mutation may increase the severity of viral infections by increasing the binding affinity between the spike protein and the ACE2 receptor. We employed molecular modeling techniques, including protein modeling, molecular docking, and quantum mechanics/molecular mechanics (QM/MM) geometry optimization, to build and validate three-dimensional models of the S_D614G-ACE2 and S_P681R-ACE2 complexes from the predominant strains. The description of the binding mode and intermolecular contacts of the referenced systems suggests that the P681R mutation may be associated with increased viral pathogenicity in Bangladeshi patients due to enhanced electrostatic interactions between the mutant spike protein and the human ACE2 receptor, underscoring the importance of continuous genomic surveillance in the fight against COVID -19. Finally, the binding profile of the S_D614G-ACE2 and S_P681R-ACE2 complexes offer valuable insights to deeply understand the binding site characteristics that could help to develop antiviral therapeutics that inhibit protein-protein interactions between SARS-CoV-2 spike protein and human ACE2 receptor.

Characterizing interactions in E-cadherin assemblages

Cadherin intermolecular interactions are critical for cell-cell adhesion and play essential roles in tissue formation and the maintenance of tissue structures. In this study, we focus on E-cadherin, a classical cadherin that connects epithelial cells, to understand how they interact in cis and trans conformations when attached to the same cell or opposing cells. We employ coevolutionary sequence analysis and molecular dynamics simulations to confirm previously known interaction sites as well as to identify new interaction sites. The sequence coevolutionary results yield a surprising result indicating that there are no strongly favored intermolecular interaction sites, which is unusual and suggests that many interaction sites may be possible, with none being strongly preferred over others. By using molecular dynamics, we test the persistence of these interactions and how they facilitate adhesion. We build several types of cadherin assemblages, with different numbers and combinations of cis and trans interfaces to understand how these conformations act to facilitate adhesion. Our results suggest that, in addition to the established interaction sites on the EC1 and EC2 domains, an additional plausible cis interface at the EC3-EC5 domain exists. Furthermore, we identify specific mutations at cis/trans binding sites that impair adhesion within E-cadherin assemblages.

Large-scale pathogenicity prediction analysis of cancer-associated kinase mutations reveals variability in sensitivity and specificity of computational methods

BACKGROUND

Mutations in kinases are the most frequent genetic alterations in cancer; however, experimental evidence establishing their cancerous nature is available only for a small fraction of these mutants.

AIMS

Predicition analysis of kinome mutations is the primary aim of this study. Further objective is to compare the performance of various softwares in pathogenicity prediction of kinase mutations.

MATERIALS AND METHODS

We employed a set of computational tools to predict the pathogenicity of over forty-two thousand mutations and deposited the kinase-wise data in Mendeley database (Estimated Pathogenicity of Kinase Mutants [EPKiMu]).

RESULTS

Mutations are more likely to be drivers when being present in the kinase domain (vs. non-kinase domain) and belonging to hotspot residues (vs. non-hotspot residues). We identified that, while predictive tools have low specificity in general, PolyPhen-2 had the best accuracy. Further efforts to combine all four tools by consensus, voting, or other simple methods did not significantly improve accuracy.

DISCUSSION

The study provides a large dataset of kinase mutations along with their predicted pathogenicity that can be used as a training set for future studies. Furthermore, a comparative sensitivity and selectivity of commonly used computational tools is presented.

CONCLUSION

Primary-structure-based in silico tools identified more cancerous/deleterious mutations in the kinase domains and at the hot spot residues while having higher sensitivity than specificity in detecting deleterious mutations.

POU6F2 mutation in humans with pubertal failure alters GnRH transcript expression

Idiopathic hypogonadotropic hypogonadism (IHH) is characterized by the absence of pubertal development and subsequent impaired fertility often due to gonadotropin-releasing hormone (GnRH) deficits. Exome sequencing of two independent cohorts of IHH patients identified 12 rare missense variants in POU6F2 in 15 patients. POU6F2 encodes two distinct isoforms. In the adult mouse, expression of both isoform1 and isoform2 was detected in the brain, pituitary, and gonads. However, only isoform1 was detected in mouse primary GnRH cells and three immortalized GnRH cell lines, two mouse and one human. To date, the function of isoform2 has been verified as a transcription factor, while the function of isoform1 has been unknown. In the present report, bioinformatics and cell assays on a human-derived GnRH cell line reveal a novel function for isoform1, demonstrating it can act as a transcriptional regulator, decreasing GNRH1 expression. In addition, the impact of the two most prevalent POU6F2 variants, identified in five IHH patients, that were located at/or close to the DNA-binding domain was examined. Notably, one of these mutations prevented the repression of GnRH transcripts by isoform1. Normally, GnRH transcription increases as GnRH cells mature as they near migrate into the brain. Augmentation earlier during development can disrupt normal GnRH cell migration, consistent with some POU6F2 variants contributing to the IHH pathogenesis.

A novel report of Cys1298Gly mutation in exon 24 of NOTCH3 gene in a Chinese family with CADASIL

OBJECTIVES

Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL) is the most common monogenic hereditary small cerebral vessel disease, which is caused by mutation of the neurogenic locus notch homolog protein 3 gene (NOTCH3). The exon 24 encodes EGF-like repeats, variants on this exon are rare. Here, we report a novel heterozygous variant c.3892 T >G (p. Cys1298Gly) on exon 24 of NOTCH3 gene in a 57-year-old Chinese woman.

MATERIALS AND METHODS

We present a patient with clinical manifestations, laboratory examination and imaging reveal suspicion of CADASIL. The family and genetic test and pathological examination were performed.

RESULTS

Magnetic resonance imaging revealed diffuse leukoencephalopathy with hyperintense signals in the bilateral temporal poles, periventricular white matter, centrum semiovale, basal ganglia, frontal and parietal cortex and subcortical areas bilaterally. Molecular Genetic testing identified a heterozygous variant c.3892 T >G (p. Cys1298Gly) on exon 24 of NOTCH3 gene. Her brother and his son were confirmed as subclinical carriers of the variant. The skin biopsy was negative, but the pathologic role of this mutation is predicted by using the DynaMut database and results showed the stability of the NOTCH gene is decreased.

CONCLUSIONS

To the best of our knowledge, this is the second case of exon 24 mutations reported from China and the variant of c.3892 T >G (p. Cys1298Gly) on exon 24 of NOTCH3 has not been reported so far. Our report broadens the mutation spectrum of the NOTCH3 gene in CADASIL.

Aicardi Syndrome Is a Genetically Heterogeneous Disorder

Aicardi Syndrome (AIC) is a rare neurodevelopmental disorder recognized by the classical triad of agenesis of the corpus callosum, chorioretinal lacunae and infantile epileptic spasms syndrome. The diagnostic criteria of AIC were revised in 2005 to include additional phenotypes that are frequently observed in this patient group. AIC has been traditionally considered as X-linked and male lethal because it almost exclusively affects females. Despite numerous genetic and genomic investigations on AIC, a unifying X-linked cause has not been identified. Here, we performed exome and genome sequencing of 10 females with AIC or suspected AIC based on current criteria. We identified a unique de novo variant, each in different genes: KMT2B, SLF1, SMARCB1, SZT2 and WNT8B, in five of these females. Notably, genomic analyses of coding and non-coding single nucleotide variants, short tandem repeats and structural variation highlighted a distinct lack of X-linked candidate genes. We assessed the likely pathogenicity of our candidate autosomal variants using the TOPflash assay for WNT8B and morpholino knockdown in zebrafish (Danio rerio) embryos for other candidates. We show expression of Wnt8b and Slf1 are restricted to clinically relevant cortical tissues during mouse development. Our findings suggest that AIC is genetically heterogeneous with implicated genes converging on molecular pathways central to cortical development.

Novel pathogenic NPR2 variants in short stature patients and the therapeutic response to rhGH

OBJECTIVE

Heterozygous loss-of-function variants in the NPR2 gene cause short stature with nonspecific skeletal abnormalities and account for about 2 ~ 6% of idiopathic short stature. This study aimed to analyze and identify pathogenic variants in the NPR2 gene and explore the therapeutic response to recombinant growth hormone (rhGH).

METHODS

NPR2 was sequenced in three Chinese Han patients with short stature via exome sequencing. In vitro functional experiments, homology modeling and molecular docking analysis of variants were performed to examine putative protein changes and the pathogenicity of the variants.

RESULT

Three patients received rhGH therapy for two years, and two NPR2 heterozygous variants were identified in three unrelated cases: c.1579 C > T,p.Leu527Phe in patient 1 and c.2842dupC,p.His948Profs*5 in patient 2. Subsequently, a small gene model was constructed, and transcriptional analysis of the synonymous variant (c.2643G > A) was performed in patient 3, which revealed the deletion of exon 17 and the premature formation of a stop codon (p.His840Gln*). Functional studies showed that both NPR2 variants, His948Profs*5 and His840Gln*, failed to produce cGMP in the homozygous state. Furthermore, the Leu527Phe variant of NPR2 was almost unresponsive to the stimulatory effect of ATP on CNP-dependent guanylyl cyclase activity. This loss of response to ATP has not been previously reported. The average age of patients at the start of treatment was 6.5 ± 1.8 years old, and their height increased by 1.59 ± 0.1 standard deviation score after 2 years of treatment.

CONCLUSION

In this report, two novel variants in NPR2 gene were described. Our findings broaden the genotypic spectrum of NPR2 variants in individuals with short stature and provid insights into the efficacy of rhGH in these patients.

The novel compound heterozygous variants identified in a Chinese family with glucose phosphate isomerase deficiency and pathogenicity analysis

BACKGROUND AND AIMS

Glucose phosphate isomerase (GPI) deficiency is an extremely rare autosomal recessive disorder caused by mutations in the GPI gene. In this research, the proband displaying typical manifestations of haemolytic anaemia and his family members were recruited to analyse the pathogenicity of the detected variants.

METHODS

Peripheral blood samples were collected from the family members and genomic DNA was extracted and targeted for capture and sequencing. The effect of the candidate pathogenic variants on splicing was further investigated using the minigene splicing system. The computer simulation was also used for further analysis of the detected data.

RESULTS

The proband carried the compound heterozygous variants c.633 + 3 A > G and c.295G > T in the GPI gene, which have never been reported before. In the genealogy, co-segregation of the mutant genotype with the phenotype was established. The minigene study showed that intronic mutations resulted in abnormal pre-mRNA splicing. Specifically, the two aberrant transcripts: r.546_633del and r.633 + 1_633 + 2insGT were transcribed by the minigene plasmid expressing the c.633 + 3 A > G variant. The missense mutation c.295G > T in exon 3 resulted in altering glycine at codon 87 to cysteine which was predicted to be pathogenic in an in silico analysis. Deeper analyses revealed that the Gly87Cys missense mutation led to steric hindrance. Compared to the wild-type, the mutation G87C led to a significant increase in intermolecular forces.

CONCLUSION

Overall, the novel compound heterozygous variants in the GPI gene contributed to the etiology of the disease. Genetic testing can assist in the diagnosis. The novel gene variants identified in the present study has further expanded the mutational spectrum of GPI deficiency, which can better guide family counselling.

SARS-CoV-2 vaccine breakthrough infections (VBI) by Omicron variant (B.1.1.529) and consequences in structural and functional impact

This study investigated the efficacy of existing vaccines against hospitalization and infection due to the Omicron variant of COVID-19, particularly for those who received two doses of Moderna or Pfizer vaccines and one dose of Johnson & Johnson vaccine or who were vaccinated more than five months before. A total of 36 variants in Omicron's spike protein, targeted by all three vaccinations, have made antibodies less effective at neutralizing the virus. The genotyping of the SARS-CoV-2 viral sequence revealed clinically significant variants such as E484K in three genetic mutations (T95I, D614G, and del142-144). A woman showed two of these mutations, indicating a potential risk of infection after successful immunization, as recently reported by Hacisuleyman (2021). We examine the effects of mutations on domains (NID, RBM, and SD2) found at the interfaces of the spike domains Omicron B.1.1529, Delta/B.1.1529, Alpha/B.1.1.7, VUM B.1.526, B.1.575.2, and B.1.1214 (formerly VOI Iota). We tested the affinity of Omicron for ACE2 and found that the wild- and mutant-spike proteins were using atomistic molecular dynamics simulations. According to the binding free energies calculated during mutagenesis, the ACE2 bound Omicron spikes more strongly than the wild strain SARS-CoV-2. T95I, D614G, and E484K are three substitutions that significantly contribute to RBD, corresponding to ACE2 binding energies and a doubling of the electrostatic potential of Omicron spike proteins. The Omicron appears to bind to ACE2 with greater affinity, increasing its infectivity and transmissibility. The spike virus was designed to strengthen antibody immune evasion through binding while boosting receptor binding by enhancing IgG and IgM antibodies that stimulate human β-cell, as opposed to the wild strain, which has more vital stimulation of both antibodies.

Understanding structure-guided variant effect predictions using 3D convolutional neural networks

Predicting pathogenicity of missense variants in molecular diagnostics remains a challenge despite the available wealth of data, such as evolutionary information, and the wealth of tools to integrate that data. We describe DeepRank-Mut, a configurable framework designed to extract and learn from physicochemically relevant features of amino acids surrounding missense variants in 3D space. For each variant, various atomic and residue-level features are extracted from its structural environment, including sequence conservation scores of the surrounding amino acids, and stored in multi-channel 3D voxel grids which are then used to train a 3D convolutional neural network (3D-CNN). The resultant model gives a probabilistic estimate of whether a given input variant is disease-causing or benign. We find that the performance of our 3D-CNN model, on independent test datasets, is comparable to other widely used resources which also combine sequence and structural features. Based on the 10-fold cross-validation experiments, we achieve an average accuracy of 0.77 on the independent test datasets. We discuss the contribution of the variant neighborhood in the model's predictive power, in addition to the impact of individual features on the model's performance. Two key features: evolutionary information of residues in the variant neighborhood and their solvent accessibilities were observed to influence the predictions. We also highlight how predictions are impacted by the underlying disease mechanisms of missense mutations and offer insights into understanding these to improve pathogenicity predictions. Our study presents aspects to take into consideration when adopting deep learning approaches for protein structure-guided pathogenicity predictions.

From genotype to phenotype: computational approaches for inferring microbial traits relevant to the food industry

When selecting microbial strains for the production of fermented foods, various microbial phenotypes need to be taken into account to achieve target product characteristics, such as biosafety, flavor, texture, and health-promoting effects. Through continuous advances in sequencing technologies, microbial whole-genome sequences of increasing quality can now be obtained both cheaper and faster, which increases the relevance of genome-based characterization of microbial phenotypes. Prediction of microbial phenotypes from genome sequences makes it possible to quickly screen large strain collections in silico to identify candidates with desirable traits. Several microbial phenotypes relevant to the production of fermented foods can be predicted using knowledge-based approaches, leveraging our existing understanding of the genetic and molecular mechanisms underlying those phenotypes. In the absence of this knowledge, data-driven approaches can be applied to estimate genotype-phenotype relationships based on large experimental datasets. Here, we review computational methods that implement knowledge- and data-driven approaches for phenotype prediction, as well as methods that combine elements from both approaches. Furthermore, we provide examples of how these methods have been applied in industrial biotechnology, with special focus on the fermented food industry.

Defensin-based therapeutic peptide design in attenuating V30M TTR-induced Familial Amyloid Polyneuropathy

In the present study, we aimed to formulate an effective therapeutic candidate against V30M mutant transthyretin (TTR) protein to hinder its pathogenic misfolding. Nicotiana alata Defensin 1 (NaD1) Antimicrobial Peptide (AMP) was availed due to its tendency to aggregate, which may compete for aggregation-prone regions of pathogenic TTR protein. Based on NaD1's potential to bind to V30M TTR, we proposed NaD1-derived tetra peptides: CKTE and SKIL to be initial therapeutic candidates. Based on their association with mutant TTR protein, CKTE tetra peptide showed considerable interaction and curative potential as compared to SKIL tetra peptide. Further analyses from discrete molecular dynamics simulation corroborate CKTE tetra peptide's effectiveness as a 'beta-sheet breaker' against V30M TTR. Various post-simulation trajectory analyses suggested that CKTE tetra peptide alters the structural dynamics of pathogenic V30M TTR protein, thereby potentially attenuating its beta-sheets and impeding its aggregation. Normal mode analysis simulation corroborated that V30M TTR conformation is altered upon its interaction with CKTE peptide. Moreover, simulated thermal denaturation findings suggested that CKTE-V30M TTR complex is more susceptible to simulated denaturation, relative to pathogenic V30M TTR; further substantiating CKTE peptide's potential to alter V30M TTR's pathogenic conformation. Moreover, the residual frustration analysis augmented CKTE tetra peptide's proclivity in reorienting the conformation of V30M TTR. Therefore, we predicted that the tetra peptide, CKTE could be a promising therapeutic candidate in mitigating the amyloidogenic detrimental effects of V30M TTR-mediated familial amyloid polyneuropathy (FAP).

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03646-4.

SLC5A1 Variants in Turkish Patients with Congenital Glucose-Galactose Malabsorption

Congenital glucose-galactose malabsorption is a rare autosomal recessive disorder caused by mutations in SLC5A1 encoding the apical sodium/glucose cotransporter SGLT1. We present clinical and molecular data from eleven affected individuals with congenital glucose-galactose malabsorption from four unrelated, consanguineous Turkish families. Early recognition and timely management by eliminating glucose and galactose from the diet are fundamental for affected individuals to survive and develop normally. We identified novel SLC5A1 missense variants, p.Gly43Arg and p.Ala92Val, which were linked to disease in two families. Stable expression in CaCo-2 cells showed that the p.Ala92Val variant did not reach the plasma membrane, but was retained in the endoplasmic reticulum. The p.Gly43Arg variant, however, displayed processing and plasma membrane localization comparable to wild-type SGLT1. Glycine-43 displays nearly invariant conservation in the relevant structural family of cotransporters and exchangers, and localizes to SGLT1 transmembrane domain TM0. p.Gly43Arg represents the first disease-associated variant in TM0; however, the role of TM0 in the SGLT1 function has not been established. In summary, we are expanding the mutational spectrum of this rare disorder.

SARS-CoV-2: analysis of the effects of mutations in non-structural proteins

A worldwide pandemic that started in China in late 2019 was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a single-stranded RNA virus belonging to the family Coronaviridae. Due to its structural variability and mutability, this virus continues to evolve and pose a major health threat around the world. Its characteristics, such as transmissibility, antigenicity, and resistance to drugs and vaccines, are continually altered through mutations. Examining mutational hotspots and their structural repercussions can thus aid in the development of more-effective vaccinations and treatment plans. In this study, we used full genome sequences of SARS-CoV-2 variants to predict structural changes in viral proteins. These sequences were obtained from the Global Initiative on Sharing Avian Influenza Data (GISAID), and a set of significant mutations were identified in each of the non-structural proteins (NSP1-16) and structural proteins, including the envelope, nucleocapsid, membrane, and spike proteins. The mutations were characterized as stabilizing or destabilizing based on their effect on protein dynamics and stability, and their impact on structure and function was evaluated. Among all of the proteins, NSP6 stands out as especially variable. The results of this study augment our understanding of how mutational events influence virus pathogenicity and evolution.

Identifying the Molecular Drivers of Pathogenic Aldehyde Dehydrogenase Missense Mutations in Cancer and Non-Cancer Diseases

Human aldehyde dehydrogenases (ALDHs) comprising 19 isoenzymes play a vital role on both endogenous and exogenous aldehyde metabolism. This NAD(P)-dependent catalytic process relies on the intact structural and functional activity of the cofactor binding, substrate interaction, and the oligomerization of ALDHs. Disruptions on the activity of ALDHs, however, could result in the accumulation of cytotoxic aldehydes, which have been linked with a wide range of diseases, including both cancers as well as neurological and developmental disorders. In our previous works, we have successfully characterised the structure-function relationships of the missense variants of other proteins. We, therefore, applied a similar analysis pipeline to identify potential molecular drivers of pathogenic ALDH missense mutations. Variants data were first carefully curated and labelled as cancer-risk, non-cancer diseases, and benign. We then leveraged various computational biophysical methods to describe the changes caused by missense mutations, informing a bias of detrimental mutations with destabilising effects. Cooperating with these insights, several machine learning approaches were further utilised to investigate the combination of features, revealing the necessity of the conservation of ALDHs. Our work aims to provide important biological perspectives on pathogenic consequences of missense mutations of ALDHs, which could be invaluable resources in the development of cancer treatment.

SARS CoV-2 spike protein variants exploit DC-SIGN/DC-SIGNR receptor for evolution and severity: an in-silico insight

The Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is related with the COVID-19 pandemic. Recent spike protein variations have had an effect on the transmission of the virus. In addition to ACE-2, spike proteins can employ DC-SIGN and its analogous receptor, DC-SIGNR, for host evasion. Spike variations in the DC-SIGN interaction region and role of DC-SIGN in immune evasion have not been well defined. To understand the spike protein variations and their binding mode, phylogenetic analysis of the complete GISAID (Global Initiative for Sharing Avian Influenza Data) data of the SARS-CoV-2 spike protein was considered. In addition, an in silico knockout network evaluation of the SARS-CoV-2 single-cell transcriptome was conducted to determine the key role of DC-SIGN/R in immunological dysregulation. Within the DC-SIGN-interacting region of the SARS-CoV spike protein, the spike protein of SARS-CoV-2 displayed remarkable similarity to the SARS-CoV spike protein. Surprisingly, the phylogenetic analysis revealed that the SARS-CoV-2's spike exhibited significantly diverse variants in the DC-SIGN interaction domain, which altered the frequency of these variants. The variation within the DC-SIGN-interacting domain of spike proteins affected the binding of a limited number of variants with DC-SIGN and DC-SIGNR and affected their evolution. MMGBSA binding free energies evaluation differed for variants from those of the wild type, suggesting the influence of substitution mutations on the interaction pattern. In silico knockout network analysis of the single-cell transcriptome of Bronchoalveolar Lavage and peripheral blood mononuclear cells revealed that SARS-CoV-2 altered DC-SIGN/R signaling. Early surveillance of diverse SARS-CoV-2 strains could preclude a worsening of the pandemic and facilitate the development of an optimum vaccine against variations. The spike Receptor Binding Domain genetic variants are thought to boost SARS CoV-2 immune evasion, resulting in its higher longevity.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13337-023-00820-3.

Rare variant contribution to cholestatic liver disease in a South Asian population in the United Kingdom

This study assessed the contribution of five genes previously known to be involved in cholestatic liver disease in British Bangladeshi and Pakistani people. Five genes (ABCB4, ABCB11, ATP8B1, NR1H4, TJP2) were interrogated by exome sequencing data of 5236 volunteers. Included were non-synonymous or loss of function (LoF) variants with a minor allele frequency < 5%. Variants were filtered, and annotated to perform rare variant burden analysis, protein structure, and modelling analysis in-silico. Out of 314 non-synonymous variants, 180 fulfilled the inclusion criteria and were mostly heterozygous unless specified. 90 were novel and of those variants, 22 were considered likely pathogenic and 9 pathogenic. We identified variants in volunteers with gallstone disease (n = 31), intrahepatic cholestasis of pregnancy (ICP, n = 16), cholangiocarcinoma and cirrhosis (n = 2). Fourteen novel LoF variants were identified: 7 frameshift, 5 introduction of premature stop codon and 2 splice acceptor variants. The rare variant burden was significantly increased in ABCB11. Protein modelling demonstrated variants that appeared to likely cause significant structural alterations. This study highlights the significant genetic burden contributing to cholestatic liver disease. Novel likely pathogenic and pathogenic variants were identified addressing the underrepresentation of diverse ancestry groups in genomic research.

Case report: A rare variant m.4135T>C in the MT-ND1 gene leads to Leber hereditary optic neuropathy and altered respiratory chain supercomplexes

Leber hereditary optic neuropathy is a primary mitochondrial disease characterized by acute visual loss due to the degeneration of retinal ganglion cells. In this study, we describe a patient carrying a rare missense heteroplasmic variant in MT-ND1, NC_012920.1:m.4135T>C (p.Tyr277His) manifesting with a typical bilateral painless decrease of the visual function, triggered by physical exercise or higher ambient temperature. Functional studies in muscle and fibroblasts show that amino acid substitution Tyr277 with His leads to only a negligibly decreased level of respiratory chain complex I (CI), but the formation of supercomplexes and the activity of the enzyme are disturbed noticeably. Our data indicate that although CI is successfully assembled in the patient's mitochondria, its function is hampered by the m.4135T>C variant, probably by stabilizing CI in its inactive form. We conclude that the m.4135T>C variant together with a combination of external factors is necessary to manifest the phenotype.

Structural Dynamics Predominantly Determine the Adaptability of Proteins to Amino Acid Deletions

The insertion or deletion (indel) of amino acids has a variety of effects on protein function, ranging from disease-forming changes to gaining new functions. Despite their importance, indels have not been systematically characterized towards protein engineering or modification goals. In the present work, we focus on deletions composed of multiple contiguous amino acids (mAA-dels) and their effects on the protein (mutant) folding ability. Our analysis reveals that the mutant retains the native fold when the mAA-del obeys well-defined structural dynamics properties: localization in intrinsically flexible regions, showing low resistance to mechanical stress, and separation from allosteric signaling paths. Motivated by the possibility of distinguishing the features that underlie the adaptability of proteins to mAA-dels, and by the rapid evaluation of these features using elastic network models, we developed a positive-unlabeled learning-based classifier that can be adopted for protein design purposes. Trained on a consolidated set of features, including those reflecting the intrinsic dynamics of the regions where the mAA-dels occur, the new classifier yields a high recall of 84.3% for identifying mAA-dels that are stably tolerated by the protein. The comparative examination of the relative contribution of different features to the prediction reveals the dominant role of structural dynamics in enabling the adaptation of the mutant to mAA-del without disrupting the native fold.

Crucial neuroprotective roles of the metabolite BH4 in dopaminergic neurons

Dopa-responsive dystonia (DRD) and Parkinson's disease (PD) are movement disorders caused by the dysfunction of nigrostriatal dopaminergic neurons. Identifying druggable pathways and biomarkers for guiding therapies is crucial due to the debilitating nature of these disorders. Recent genetic studies have identified variants of GTP cyclohydrolase-1 (GCH1), the rate-limiting enzyme in tetrahydrobiopterin (BH4) synthesis, as causative for these movement disorders. Here, we show that genetic and pharmacological inhibition of BH4 synthesis in mice and human midbrain-like organoids accurately recapitulates motor, behavioral and biochemical characteristics of these human diseases, with severity of the phenotype correlating with extent of BH4 deficiency. We also show that BH4 deficiency increases sensitivities to several PD-related stressors in mice and PD human cells, resulting in worse behavioral and physiological outcomes. Conversely, genetic and pharmacological augmentation of BH4 protects mice from genetically- and chemically induced PD-related stressors. Importantly, increasing BH4 levels also protects primary cells from PD-affected individuals and human midbrain-like organoids (hMLOs) from these stressors. Mechanistically, BH4 not only serves as an essential cofactor for dopamine synthesis, but also independently regulates tyrosine hydroxylase levels, protects against ferroptosis, scavenges mitochondrial ROS, maintains neuronal excitability and promotes mitochondrial ATP production, thereby enhancing mitochondrial fitness and cellular respiration in multiple preclinical PD animal models, human dopaminergic midbrain-like organoids and primary cells from PD-affected individuals. Our findings pinpoint the BH4 pathway as a key metabolic program at the intersection of multiple protective mechanisms for the health and function of midbrain dopaminergic neurons, identifying it as a potential therapeutic target for PD.

CTCF variant begets to short stature by down-regulation of IGF1

Pathogenic variants in the transcription factor CCCTC-binding factor (CTCF) are associated with mental retardation, autosomal dominant 21 (MRD21, MIM#615502). Current studies supported the strong relationship between CTCF variants and growth, yet the mechanism of CTCF mutation leading to short stature is not known. Clinical information, treatment regimens, and follow-up outcomes of a patient with MRD21 were collected. The possible pathogenic mechanisms of CTCF variants leading to short stature were investigated using immortalized lymphocyte cell lines (LCLs), HEK-293T, and immortalized normal human liver cell lines (LO2). This patient received long-term treatment with recombinant human growth hormone (rhGH) which resulted in an increased height of 1.0 SDS. She had low serum insulin-like growth factor 1 (IGF1) before the treatment and the IGF1 level was not significantly increased during the treatment (-1.38 ± 0.61 SDS). The finding suggested that the CTCF R567W variant could have impaired IGF1 production pathway. We further demonstrated that the mutant CTCF had a reduced ability to bind to the promoter region of IGF1, consequently significantly reducing the transcriptional activation and expression of IGF1. Our novel results demonstrated a direct positive regulation of CTCF on the transcription of the IGF1 promoter. The impaired IGF1 expression due to CTCF mutation may explain the substandard effect of rhGH treatment on MRD21 patients. This study provided novel insights into the molecular basis of CTCF-associated disorder.

Accelerating therapeutic protein design with computational approaches toward the clinical stage

Therapeutic protein, represented by antibodies, is of increasing interest in human medicine. However, clinical translation of therapeutic protein is still largely hindered by different aspects of developability, including affinity and selectivity, stability and aggregation prevention, solubility and viscosity reduction, and deimmunization. Conventional optimization of the developability with widely used methods, like display technologies and library screening approaches, is a time and cost-intensive endeavor, and the efficiency in finding suitable solutions is still not enough to meet clinical needs. In recent years, the accelerated advancement of computational methodologies has ushered in a transformative era in the field of therapeutic protein design. Owing to their remarkable capabilities in feature extraction and modeling, the integration of cutting-edge computational strategies with conventional techniques presents a promising avenue to accelerate the progression of therapeutic protein design and optimization toward clinical implementation. Here, we compared the differences between therapeutic protein and small molecules in developability and provided an overview of the computational approaches applicable to the design or optimization of therapeutic protein in several developability issues.

Identification of mutations that causes glucose-6-phosphate transporter defect in tunisian patients with glycogenosis type 1b

BACKGROUND

Glycogen storage disease type 1b (GSD1b) is an autosomal recessive lysosomal storage disease caused by defective glucose-6-phosphate transporter encoded by SLC37A4 leading to the accumulation of glycogen in various tissues. The high rate of consanguineous marriages in Tunisian population provides an ideal environment to facilitate the identification of homozygous pathogenic mutations. We aimed to determine the clinical and genetic profiles of patients with GSD1b to evaluate SLC37A4 mutations spectrum in Tunisian patients.

METHODS

All exons and flanking intron regions of SLC37A4 gene were screened by direct sequencing to identify mutations and polymorphisms in three unrelated families with GSD1b. Bioinformatics tools were then used to predict the impacts of identified mutations on the structure and function of protein in order to propose a function-structure relationship of the G6PT1 protein.

RESULTS

Three patients (MT, MB and SI) in Families I, II and III who had the severe phenotype were homoallelic for the two identified mutations: p.R300H (famillies I, II) and p.W393X (Family III), respectively. One of the alterations was a missense mutation p.R300H of exon 6 in SLC37A4 gene. The analysis of the protein structure flexibility upon p.R300H mutation using DynaMut tool and CABS-flex 2.0 server showed that the reported mutation increase the molecule flexibility of in the cytosol region and would probably lead to significant conformational changes.

CONCLUSION

This is the first Tunisian report of SLC37A4 mutations identified in Tunisia causing the glycogenosis type Ib disease. Bioinformatics analysis allowed us to establish an approximate structure-function relationship for the G6PT1 protein, thereby providing better genotype/phenotype correlation knowledge.

Identifying Novel Risk Conferring Genes Involved in Glycosylation Processes with Familial Schizophrenia in an Indian Cohort: Prediction of ADAMTS9 gene Variant for Structural Stability

Schizophrenia is a complex neuropsychiatric disorder and heritability is as high as 80% making it the most heritable mental disorder. Although GWAS has identified numerous variants, the pathophysiology is still elusive. Here, an attempt was made to identify genetic risk factors in familial cases of schizophrenia that are associated with a common causative pathway. To achieve this objective, exome sequencing was done in 4 familial cases and identified six unique coding variants in five genes. Among these genes, PIGQ gene has two pathogenic variants, one nonsense and in-frame deletion. One missense variant in GALNT16 and one in GALNT5 have variable damaging score, however, the other variants, in ADAMTS9 and in LTBP4 have the highest damaging score. Further analysis showed that the variant of LTBP4 was not present in the functional domain. The other missense variant in the ADAMTS9 gene was found to be significant and was present in the thrombospondin repeat motif, one of the important motifs. Detailed molecular dynamics simulation study on this variant showed a damaging effect on structural stability. Since, all these genes culminated into the glycosylation process, it was evident that an aberrant glycosylation process may be one of the risk factors. Although, extracellular matrix formation through glycosylation have been shown to be associated, the involvement of ADAMTS9 and PIGQ gene mediated glycosylation has not been reported. In this paper, a novel link between ADAMTS9 and PIGQ gene with schizophrenia have been reported. Therefore, this novel observation has contributed immensely to the existing knowledge on risk factor of Schizophrenia.

An In Silico Functional Analysis of Non-Synonymous Single-Nucleotide Polymorphisms of Bovine CMAH Gene and Potential Implication in Pathogenesis

The sugar molecule N-glycolylneuraminic acid (Neu5Gc) is one of the most common sialic acids discovered in mammals. Cytidine monophospho-N-acetylneuraminic acid hydroxylase (CMAH) catalyses the conversion of N-acetylneuraminic acid (Neu5Ac) to Neu5Gc, and it is encoded by the CMAH gene. On the one hand, food metabolic incorporation of Neu5Gc has been linked to specific human diseases. On the other hand, Neu5Gc has been shown to be highly preferred by some pathogens linked to certain bovine diseases. We used various computational techniques to perform an in silico functional analysis of five non-synonymous single-nucleotide polymorphisms (nsSNPs) of the bovine CMAH (bCMAH) gene identified from the 1000 Bull Genomes sequence data. The c.1271C>T (P424L) nsSNP was predicted to be pathogenic based on the consensus result from different computational tools. The nsSNP was also predicted to be critical based on sequence conservation, stability, and post-translational modification site analysis. According to the molecular dynamic simulation and stability analysis, all variations promoted stability of the bCMAH protein, but mutation A210S significantly promoted CMAH stability. In conclusion, c.1271C>T (P424L) is expected to be the most harmful nsSNP among the five detected nsSNPs based on the overall studies. This research could pave the way for more research associating pathogenic nsSNPs in the bCMAH gene with diseases.

Mutant p53 activates hnRNPA2B1-AGAP1-mediated exosome formation to promote esophageal squamous cell carcinoma progression

p53 mutations predispose cancer cell development, promote their survival and metastasis, and lead to ineffective therapeutic responses and unfavorable prognosis. No drug that abrogates the oncogenic functions of mutant p53 has been approved for cancer treatment. Here, we performed whole-genome sequencing of 663 esophageal squamous cell carcinoma (ESCC) tumor tissues and paired normal tissues. The results indicated that ESCC samples from our cohort had a more dispersed distribution of TP53 mutants and a higher proportion of nonsense mutants than European and American ESCC samples in the International Agency for Research on Cancer (IARC) database. The most frequent p53 mutations disrupt the inhibition of proliferation, migration, and invasion mediated by wild-type p53 in ESCC. Furthermore, p53 mutations alter its protein nucleoplasmic localization and protein stability. The p53 mutation G245S (p53-G245S) interacts with heterogeneous nuclear ribonucleoprotein A2B1 (hnRNPA2B1) to increase protein translation of phosphatidylinositol-dependent Arf GAP (AGAP1) by promoting AGAP1 mRNA stability. AGAP1 promotes cancer cell proliferation and metastasis by enhancing exosome formation. Furthermore, we explored the combination of the HSP90 inhibitor HSP90i and the AGAP1 inhibitor QS11 could inhibit ESCC cell proliferation and metastasis. Thus, the p53-G245S/hnRNPA2B1/AGAP1 axis promotes ESCC progression by enhancing exosome formation, and the combination of an HSP90 inhibitor and an AGAP1 inhibitor may serve as a potential therapeutic strategy.

A biallelic variant in POLR2C is associated with congenital hearing loss and male infertility: Case report

BACKGROUND

DNA-directed RNA polymerase II subunit 3 (RPB3) is the third largest subunit of RNA polymerase II and is encoded by the POLR2C (OMIM:180663). A large Iranian family with congenital hearing loss and infertility is described here with genetic and clinical characterizations of five male patients.

METHODS

After doing clinical examinations, the proband was subjected to karyotyping and GJB2/6 sequencing to rule out the most evident chromosomal and gene abnormalities for male infertility and hearing loss, respectively. A custom-designed next-generation sequencing panel was also used to detect mutations in deafness-related genes. Finally, to reveal the underlying molecular cause(s) justifying hearing loss and male infertility, five male patients and 2 healthy male controls within the family were subjected to paired-end whole-exome sequencing (WES). Linkage analysis was also performed based on the data.

RESULTS

All male patients showed prelingual sensorineural hearing loss and also decreased sperm motility. Linkage analysis determined 16q21 as the most susceptible locus in which a missense variant in exon 7 of POLR2C-NM_032940.3:c.545T>C;p.(Val182Ala)-was identified as a 'likely pathogenic' variant co-segregated with phenotypes.

CONCLUSIONS

Using segregation and in silico analyses, for the first time, we suggested that the NM_032940.3:c.545T>C; p.(Val182Ala) in POLR2C is associated with hearing loss and male infertility.

Common and Rare Variants in TMEM175 Gene Concur to the Pathogenesis of Parkinson's Disease in Italian Patients

Parkinson's disease (PD) represents the most common neurodegenerative movement disorder. We recently identified 16 novel genes associated with PD. In this study, we focused the attention on the common and rare variants identified in the lysosomal K⁺ channel TMEM175. The study includes a detailed clinical and genetic analysis of 400 cases and 300 controls. Molecular studies were performed on patient-derived fibroblasts. The functional properties of the mutant channels were assessed by patch-clamp technique and co-immunoprecipitation. We have found that TMEM175 was highly expressed in dopaminergic neurons of the substantia nigra pars compacta and in microglia of the cerebral cortex of the human brain. Four common variants were associated with PD, including two novel variants rs2290402 (c.-10C > T) and rs80114247 (c.T1022C, p.M341T), located in the Kozak consensus sequence and TM3II domain, respectively. We also disclosed 13 novel highly penetrant detrimental mutations in the TMEM175 gene associated with PD. At least nine of these mutations (p.R35C, p. R183X, p.A270T, p.P308L, p.S348L, p. L405V, p.R414W, p.P427fs, p.R481W) may be sufficient to cause the disease, and the presence of mutations of other genes correlated with an earlier disease onset. In vitro functional analysis of the ion channel encoded by the mutated TMEM175 gene revealed a loss of the K⁺ conductance and a reduced channel affinity for Akt. Moreover, we observed an impaired autophagic/lysosomal proteolytic flux and an increase expression of unfolded protein response markers in patient-derived fibroblasts. These data suggest that mutations in TMEM175 gene may contribute to the pathophysiology of PD.

Recent advances in simultaneous thermostability-activity improvement of industrial enzymes through structure modification

Engineered thermostable microbial enzymes are widely employed to catalyze chemical reactions in numerous industrial sectors. Although high thermostability is a prerequisite of industrial applications, enzyme activity is usually sacrificed during thermostability improvement. Therefore, it is vital to select the common and compatible strategies between thermostability and activity improvement to reduce mutants̕ libraries and screening time. Three functional protein engineering approaches, including directed evolution, rational design, and semi-rational design, are employed to manipulate protein structure on a genetic basis. From a structural standpoint, integrative strategies such as increasing substrate affinity; introducing electrostatic interaction; removing steric hindrance; increasing flexibility of the active site; N- and C-terminal engineering; and increasing intramolecular and intermolecular hydrophobic interactions are well-known to improve simultaneous activity and thermostability. The current review aims to analyze relevant strategies to improve thermostability and activity simultaneously to circumvent the thermostability and activity trade-off of industrial enzymes.

Super High-Throughput Screening of Enzyme Variants by Spectral Graph Convolutional Neural Networks

Finding new enzyme variants with the desired substrate scope requires screening through a large number of potential variants. In a typical in silico enzyme engineering workflow, it is possible to scan a few thousands of variants, and gather several candidates for further screening or experimental verification. In this work, we show that a Graph Convolutional Neural Network (GCN) can be trained to predict the binding energy of combinatorial libraries of enzyme complexes using only sequence information. The GCN model uses a stack of message-passing and graph pooling layers to extract information from the protein input graph and yield a prediction. The GCN model is agnostic to the identity of the ligand, which is kept constant within the mutant libraries. Using a miniscule subset of the total combinatorial space (20⁴-20⁸ mutants) as training data, the proposed GCN model achieves a high accuracy in predicting the binding energy of unseen variants. The network's accuracy was further improved by injecting feature embeddings obtained from a language module pretrained on 10 million protein sequences. Since no structural information is needed to evaluate new variants, the deep learning algorithm is capable of scoring an enzyme variant in under 1 ms, allowing the search of billions of candidates on a single GPU.

Conformational dynamics of A30G α-synuclein that causes familial Parkinson disease

The first gene shown to be responsible for autosomal-dominant Parkinson's disease (PD) is the SNCA gene, which encodes for alpha synuclein (α-Syn). Recently, a novel heterozygous A30G mutation of the SNCA gene associated with familial PD has been reported. However, little research has been done on how the A30G mutation affects the structure of α-Syn. So, using atomistic molecular dynamics (MD) simulation, we demonstrate here the key structural characteristics of A30G α-Syn in the free monomer form and membrane associated state. From the MD trajectory analysis, the structure of A30G α-Syn was noticed to exhibit rapid conformational change, increase in backbone flexibility near the site of mutation and decrease in α-helical propensity. The typical torsion angles in residues (Val26 and Glu28) near the mutation site were observed to deviate significantly in A30G α-Syn. In the case of membrane bound A30G α-Syn, the regions that were submerged in the lipid bilayer (N-helix (3-37) and turn region (38-44)) found to contain higher helical content than the elevated region above the lipid surface. The bending angle in the helix-N and helix-C regions were noticed to be relatively higher in the free form of A30G α-Syn (38.50) than in the membrane bound form (370). The A30G mutation in α-Syn was predicted to have an impact on the stability and function of the protein based on ΔΔG values obtained from the online servers. Our results demonstrate that the A30G mutation in α-Syn altered the protein's α-helical structure and slightly altered the membrane binding.Communicated by Ramaswamy H. Sarma.

Biochemical Studies of Systemic Lupus Erythematosus-Associated Mutations in Nonreceptor Tyrosine Kinases Ack1 and Brk

Tyrosine kinases (TKs) play essential roles in signaling processes that regulate cell survival, migration, and proliferation. Dysregulation of tyrosine kinases underlies many disorders, including cancer, cardiovascular and developmental diseases, as well as pathologies of the immune system. Ack1 and Brk are nonreceptor tyrosine kinases (NRTKs) best known for their roles in cancer. Here, we have biochemically characterized novel Ack1 and Brk mutations identified in patients with systemic lupus erythematosus (SLE). These mutations are the first SLE-linked polymorphisms found among NRTKs. We show that two of the mutants are catalytically inactive, while the other three have reduced activity. To understand the structural changes associated with the loss-of-function phenotype, we solved the crystal structure of one of the Ack1 kinase mutants, K161Q. Furthermore, two of the mutated residues (Ack1 A156 and K161) critical for catalytic activity are highly conserved among other TKs, and their substitution in other members of the kinase family could have implications in cancer. In contrast to canonical gain-of-function mutations in TKs observed in many cancers, we report loss-of-function mutations in Ack1 and Brk, highlighting the complexity of TK involvement in human diseases.

Insights on the interaction of SARS-CoV-2 variant B.1.617.2 with antibody CR3022 and analysis of antibody resistance

BACKGROUND

The existence of mutated Delta (B.1.617.2) variants of SARS-CoV-2 causes rapid transmissibility, increase in virulence, and decrease in the effectiveness of public health. Majority of mutations are seen in the surface spike, and they are considered as antigenicity and immunogenicity of the virus. Hence, finding suitable cross antibody or natural antibody and understanding its biomolecular recognition for neutralizing surface spike are crucial for developing many clinically approved COVID-19 vaccines. Here, we aim to design SARS-CoV-2 variant and hence, to understand its mechanism, binding affinity and neutralization potential with several antibodies.

RESULTS

In this study, we modelled six feasible spike protein (S1) configurations for Delta SARS-CoV-2 (B.1.617.2) and identified the best structure to interact with human antibodies. Initially, the impact of mutations at the receptor-binding domain (RBD) of B.1.617.2 was tested, and it is found that all mutations increase the stability of proteins (ΔΔG) and decrease the entropies. An exceptional case is noted for the mutation of G614D variant for which the vibration entropy change is found to be within the range of 0.133-0.004 kcal/mol/K. Temperature-dependent free energy change values (ΔG) for wild type is found to be - 0.1 kcal/mol, whereas all other cases exhibit values within the range of - 5.1 to - 5.5 kcal/mol. Mutation on spike increases the interaction with the glycoprotein antibody CR3022 and the binding affinity (CLUSpro energy =  - 99.7 kcal/mol). The docked Delta variant with the following antibodies, etesevimab, bebtelovimab, BD-368-2, imdevimab, bamlanivimab, and casirivimab, exhibit a substantially decreased docking score (- 61.7 to - 112.0 kcal/mol) and the disappearance of several hydrogen bond interactions.

CONCLUSION

Characterization of antibody resistance for Delta variant with respect to the wild type gives understanding regarding why Delta variant endures the resistance boosted through several trademark vaccines. Several interactions with CR3022 have appeared compared to Wild for Delta variant, and hence, it is suggested that modification on the CR3022 antibody could further improve for the prevention of viral spread. Antibody resistance decreased significantly due to numerous hydrogen bond interactions which clearly indicate that these marketed/launched vaccines (etesevimab) will be effective for Delta variants.

Bioinformatics toolbox for exploring target mutation-induced drug resistance

Drug resistance is increasingly among the main issues affecting human health and threatening agriculture and food security. In particular, developing approaches to overcome target mutation-induced drug resistance has long been an essential part of biological research. During the past decade, many bioinformatics tools have been developed to explore this type of drug resistance, and they have become popular for elucidating drug resistance mechanisms in a low cost, fast and effective way. However, these resources are scattered and underutilized, and their strengths and limitations have not been systematically analyzed and compared. Here, we systematically surveyed 59 freely available bioinformatics tools for exploring target mutation-induced drug resistance. We analyzed and summarized these resources based on their functionality, data volume, data source, operating principle, performance, etc. And we concisely discussed the strengths, limitations and application examples of these tools. Specifically, we tested some predictive tools and offered some thoughts from the clinician's perspective. Hopefully, this work will provide a useful toolbox for researchers working in the biomedical, pesticide, bioinformatics and pharmaceutical engineering fields, and a good platform for non-specialists to quickly understand drug resistance prediction.

Production of neutralizing antibody fragment variants in the cytoplasm of E. coli for rapid screening: SARS-CoV-2 a case study

Global health challenges such as the coronavirus pandemic warrant the urgent need for a system that allows efficient production of diagnostic and therapeutic interventions. Antibody treatments against SARS-CoV-2 were developed with an unprecedented pace and this enormous progress was achieved mainly through recombinant protein production technologies combined with expeditious screening approaches. A heterologous protein production system that allows efficient soluble production of therapeutic antibody candidates against rapidly evolving variants of deadly pathogens is an important step in preparedness towards future pandemic challenges. Here, we report cost and time-effective soluble production of SARS-CoV-2 receptor binding domain (RBD) variants as well as an array of neutralizing antibody fragments (Fabs) based on Casirivimab and Imdevimab using the CyDisCo system in the cytoplasm of E. coli. We also report variants of the two Fabs with higher binding affinity against SARS-CoV-2 RBD and suggest this cytoplasmic production of disulfide containing antigens and antibodies can be broadly applied towards addressing future global public health threats.

Structure of Photosystem I Supercomplex Isolated from a Chlamydomonas reinhardtii Cytochrome b6f Temperature-Sensitive Mutant

The unicellular green alga, Chlamydomonas reinhardtii, has been widely used as a model system to study photosynthesis. Its possibility to generate and analyze specific mutants has made it an excellent tool for mechanistic and biogenesis studies. Using negative selection of ultraviolet (UV) irradiation–mutated cells, we isolated a mutant (TSP9) with a single amino acid mutation in the Rieske protein of the cytochrome b6f complex. The W143R mutation in the petC gene resulted in total loss of cytochrome b6f complex function at the non-permissive temperature of 37 °C and recovery at the permissive temperature of 25 °C. We then isolated photosystem I (PSI) and photosystem II (PSII) supercomplexes from cells grown at the non-permissive temperature and determined the PSI structure with high-resolution cryogenic electron microscopy. There were several structural alterations compared with the structures obtained from wild-type cells. Our structural data suggest that the mutant responded by excluding the Lhca2, Lhca9, PsaL, and PsaH subunits. This structural alteration prevents state two transition, where LHCII migrates from PSII to bind to the PSI complex. We propose this as a possible response mechanism triggered by the TSP9 phenotype at the non-permissive temperature.

High risk genetic variants of human insulin receptor substrate 1(IRS1) infer structural instability and functional interference

Insulin receptor substrate 1(IRS1) is a signaling adapter protein encoded by the IRS1 gene. This protein delivers signals from insulin and insulin-like growth factor-1(IGF-1) receptors to the phosphatidylinositol 3-kinases (P13K)/protein kinase B (Akt) and Extracellular signal-regulated kinases (Erk) - Mitogen-activated protein (MAP) kinase pathways, which regulate particular cellular processes. Mutations in this gene have been linked to type 2 diabetes mellitus, a heightened risk of insulin resistance, and an increased likelihood of developing a number of different malignancies. The structure and function of IRS1 could be severely compromised as a result of single nucleotide polymorphism (SNP) type genetic variants. In this study, we focused on identification of the most harmful non-synonymous SNPs (nsSNPs) of the IRS1 gene as well as prediction of their structural and functional consequences. Six different algorithms made the initial prediction that 59 of the 1142 IRS1 nsSNPs would have a negative impact on the protein structure. In-depth evaluations detected 26 nsSNPs located inside the functional domains of IRS1. Following that, 16 nsSNPs were identified as more harmful based on conservation profile, hydrophobic interaction, surface accessibility, homology modelling, and inter-atomic interactions. Following an in-depth analysis of protein stability, M249T (rs373826433), I223T (rs1939785175) and V204G (rs1574667052) were identified as three most deleterious SNPs and were subjected to molecular dynamics simulation for further insights. These findings will help us understand the implications for disease susceptibility, cancer progression, and the efficacy of therapeutic development against IRS1 gene mutants.Communicated by Ramaswamy H. Sarma.

An immunoinformatics approach to study the epitopes of SARS-CoV-2 helicase, Nsp13

Introduction and objective.

Vaccines are administered worldwide to control on-going coronavirus disease-19 (COVID-19) pandemic caused by SARS-CoV-2. Vaccine efficacy is largely contributed by the epitopes present on the viral proteins and their alteration might help emerging variants to escape host immune surveillance. Therefore, this study was designed to study SARS-CoV-2 Nsp13 protein, its epitopes and evolution.

Methods

Clustal Omega was used to identify mutations in Nsp13 protein. Secondary structure and disorder score was predicted by CFSSP and PONDR-VSL2 webservers. Protein stability was predicted by DynaMut webserver. B cell epitopes were predicted by IEDB DiscoTope 2.0 tools and their 3D structures were represented by discovery studio. Antigenicity and allergenicity of epitopes were predicted by Vaxijen2.0 and AllergenFPv.1.0. Physiochemical properties of epitopes were predicted by Toxinpred, HLP webserver tool.

Results

Our data revealed 182 mutations in Nsp13 among Indian SARS-CoV-2 isolates, which were characterised by secondary structure and per-residue disorderness, stability and dynamicity predictions. To correlate the functional impact of these mutations, we characterised the most prominent B cell and T cell epitopes contributed by Nsp13. Our data revealed twenty-one epitopes, which exhibited antigenicity, stability and interactions with MHC class-I and class-II molecules. Subsequently, the physiochemical properties of these epitopes were analysed. Furthermore, eighteen mutations reside in these Nsp13 epitopes.

Conclusions

We report appearance of eighteen mutations in the predicted twenty-one epitopes of Nsp13. Among these, at least seven epitopes closely matches with the functionally validated epitopes. Altogether, our study shows the pattern of evolution of Nsp13 epitopes and their probable implications.

Computational refinement identifies functional destructive single nucleotide polymorphisms associated with human retinoid X receptor gene

Alterations in the nuclear retinoid X receptor (RXRs) signalling have been implicated in neurodegenerative disorders such as Alzheimer's disease, Parkinson's disease, stroke, multiple sclerosis and glaucoma. Single nucleotide polymorphisms (SNPs) are the main cause underlying single nucleic acid variations which in turn determine heterogeneity within various populations. These genetic polymorphisms have been suggested to associate with various degenerative disorders in population-wide analysis. This bioinformatics study was designed to investigate, search, retrieve and identify deleterious SNPs which may affect the structure and function of various RXR isoforms through a computational and molecular modelling approach. Amongst the 1,813 retrieved SNPs several were found to be deleterious with rs140464195_G139R, rs368400425_R358W and rs368586400_L383F RXRα mutant variants being the most detrimental ones causing changes in the interatomic interactions and decreasing the flexibility of the mutant proteins. Molecular genetics analysis identified seven missense mutations in RXRα/β/γ isoforms. Two novel mutations SNP IDs (rs1588299621 and rs1057519958) were identified in RXRα isoform. We used several in silico prediction tools such as SIFT, PolyPhen, I-Mutant, Protein Variation Effect Analyzer (PROVEAN), PANTHER, SNP&Go, PhD-SNP and SNPeffect to predict pathogenicity and protein stability associated with RXR mutations. The structural assessment by DynaMut tool revealed that hydrogen bonds were affected along with hydrophobic and carbonyl interactions resulting in reduced flexibility at the mutated residue positions but ultimately stabilizing the molecule as a whole. Summarizing, analysis of the missense mutations in RXR isoforms showed a mix of conclusive and inconclusive genotype-phenotype correlations suggesting the use of sophisticated computational analysis tools for studying RXR variants.Communicated by Ramaswamy H. Sarma.

Compensatory mutations in the matrix protein of viral hemorrhagic septicemia virus (VHSV) genotype IVa in response to artificial mutation of two amino acids (D62A E181A)

The matrix (M) protein of rhabdoviruses locates between the inner line of the viral envelope and the nucleocapsids core and plays an important role in viral replication. In the present study, we aimed to rescue a mutant of VHSV genotype IVa that has artificial mutations in the M protein (M-D62A E181A). However, most rescued recombinant viruses unexpectedly showed non-targeted secondary mutations in the M protein. Therefore, this study was conducted to know whether the targeted artificial mutation can lead to specific non-targeted secondary mutations in the M protein and whether the secondary mutations are compensatory for the targeted artificial mutations. Experiments were conducted to rescue three kinds of M protein mutants (rVHSV-M-D62A, -E181A, and -D62A E181A), and rVHSV-M-E181A and rVHSV-M-D62A E181A without the secondary mutations were rescued only from IRF-9 gene-knockout EPC cells. Recombinant VHSVs having only targeted mutation(s) (rVHSV-M-D62A, -E181A, and -D62A E181A) showed slower CPE progression and retarded growth compared to rVHSV-wild. Although the sites of secondary mutations were changed in every transfection experiment to generate recombinant VHSVs, the positions of the secondary mutations were not random. Some amino acid residues in the M protein showed more frequent mutations than others, and the changed amino acid residues were always the same. EPC cells infected with rVHSV-M-D62A E181A showed significantly higher type I interferon response and NF-κB activity, and the inhibitory activity against type I interferon response and NF-κB activity in other recombinant VHSVs having secondary mutations in M gene were similar to those of rVHSV-wild. In conclusion, the present results showed that VHSV actively responded to the artificial mutation of M protein through the secondary mutations, and those secondary mutations occurred when the artificial mutations were deleterious to viral replication and protein stability. Furthermore, most secondary mutations in recombinant viruses compensated for the deleterious effect of the engineered mutations.

Identification and clinical characteristics of a novel missense ADGRG1 variant in bilateral Frontoparietal Polymicrogyria: The electroclinical change from infancy to adulthood after Callosotomy in three siblings

OBJECTIVE

Bilateral frontoparietal polymicrogyria (BFPP) is a rare genetic-related migration disorder. It has been attributed to loss-of-function of the ADGRG1 gene, which encodes an adhesion G protein-coupled receptor, ADGRG1/GPR56. We report the EEG findings of BFPP in three Asian patients, and confirmed that change in protein function was caused by the novel missense variant (p.Leu290Pro).

METHODS

We reviewed the medical records of three siblings with BFPP including one elder girl and two identical twin boys from birth to adulthood. The clinical symptoms, electroencephalography (EEG), brain MRI, whole-exome sequencing, treatment including medications, neuromodulation, and epilepsy surgery, and clinical outcomes were reviewed. The protein structure of a novel missense variant (p.Leu290Pro) was predicted by in silico studies, and molecular analysis was performed via typical flow cytometry and Western blotting.

RESULTS

The elder girl (Patient 1) was 22 years old and the twin boys (Patients 2 and 3) were 20 years old at the time of publication. All of them presented with typical clinical symptoms/signs and MRI findings of BFPP. Whole-exome sequencing followed by Sanger confirmation showed that all three patients had compound heterozygous variants in the ADGRG1 gene. The missense variant (p.Leu290Pro) was confirmed to be related to a reduction in cell surface GPR56 expression. High-amplitude rhythmic activity was noted in sleep EEG during infancy, which may have been due to excessive sleep spindle, and the rhythm disappeared when they were of pre-school age. Partial callosotomy provided short-term benefits in seizure control in Patients 1 and 2, and combined vagus nerve stimulation and partial callosotomy provided longer benefits in Patient 3.

SIGNIFICANCE

Sleep EEG findings of high-amplitude rhythmic activity in our BFPP cases were only noted during infancy and childhood. We also confirmed that the missense variant (p.Leu290Pro) led to loss of function due to a reduction in cell surface GPR56 expression.

Targeted next-generation sequencing identifies novel deleterious variants in ANK1 gene causing severe hereditary spherocytosis in Indian patients: expanding the molecular and clinical spectrum

Hereditary Spherocytosis (HS) is a common cause of hemolytic anemia varying from mild to severe hemolysis due to defects in red cell membrane protein genes, namely ANK1, SPTB, SPTA1, SLC4A1, and EPB42. These genes are considerably very large spaning 40-50 exons making gene-by-gene analysis costly and laborious by conventional methods. In this study, we explored 26 HS patients harboring 21 ANK1 variants identified by next-generation sequencing (NGS), characteristics and spectrum of the detected ANK1variants were analyzed in this study. Clinically, all the HS patients showed moderate to severe transfusion-dependent hemolytic anemia, some requiring splenectomy. We identified 13 novel and 8 reported variants, mainly 9 frameshifts, 2 missense, 6 nonsense, and 4 splice site ANK1 variants, using NGS technology. Frameshifts were remarkably the most common variant type seen in Indian HS patients with ANK1 gene defects. We have also explored expression levels of red cell membrane ankyrin protein by flow cytometry in 14 HS patients with ANK1 gene defects and a significant reduction in ankyrin protein expression has been found. This report mainly illustrates the molecular and phenotypic heterogeneity of ANK1 variants causing HS in Indian patients. Ankyrin-1 mutations are a significant cause of loss of function in dominant HS in the Indian population. Comprehensive genetic and phenotypic evaluation assists in implementing the knowledge of genetic patterns and spectrum of ANK1 gene variants, providing molecular support for HS diagnosis.

Genomics and structural insight into the masking of gentamicin-resistance in clinical Burkholderia pseudomallei strain VB29710 from India

The present study reported a rare gentamicin-susceptible β-lactamase (PenA, OXA-57) expressing clinical Burkholderia pseudomallei isolate VB29710 from India. Whole-genome sequencing and structural analyses revealed the insertion of R962 and L963 into AmrB, the transmembrane-protein of the AmrAB-OprA efflux-pump that affected aminoglycoside-efflux through local alterations in backbone conformation.

A novel variant in AFF3 underlying isolated syndactyly

Isolated syndactyly is a common limb malformation with limited known genetic etiology. We used exome sequencing to discover a novel heterozygous missense variant c.2915G > C: p.Arg972Pro in AFF3 on chromosome 2q11.2 in a family with isolated syndactyly in hands and feet. AFF3 belongs to a family of nuclear transcription activating factors and is involved in limb dorsoventral patterning. The variant Arg972Pro is located near the C terminus, a region that is yet to be associated with human disorders. Functional studies did not show a difference in the stability or subcellular localization of the mutant and wild type proteins. Instead, overexpression in zebrafish embryos suggests that Arg972Pro is a loss-of-function allele. These results suggest that variants in the C terminus of AFF3 may cause a phenotype distinct from previously characterized AFF3 variants.

Global landscape of SARS-CoV-2 mutations and conserved regions

BACKGROUND

At the end of December 2019, a novel strain of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) disease (COVID-19) has been identified in Wuhan, a central city in China, and then spread to every corner of the globe. As of October 8, 2022, the total number of COVID-19 cases had reached over 621 million worldwide, with more than 6.56 million confirmed deaths. Since SARS-CoV-2 genome sequences change due to mutation and recombination, it is pivotal to surveil emerging variants and monitor changes for improving pandemic management.

METHODS

10,287,271 SARS-CoV-2 genome sequence samples were downloaded in FASTA format from the GISAID databases from February 24, 2020, to April 2022. Python programming language (version 3.8.0) software was utilized to process FASTA files to identify variants and sequence conservation. The NCBI RefSeq SARS-CoV-2 genome (accession no. NC_045512.2) was considered as the reference sequence.

RESULTS

Six mutations had more than 50% frequency in global SARS-CoV-2. These mutations include the P323L (99.3%) in NSP12, D614G (97.6) in S, the T492I (70.4) in NSP4, R203M (62.8%) in N, T60A (61.4%) in Orf9b, and P1228L (50.0%) in NSP3. In the SARS-CoV-2 genome, no mutation was observed in more than 90% of nsp11, nsp7, nsp10, nsp9, nsp8, and nsp16 regions. On the other hand, N, nsp3, S, nsp4, nsp12, and M had the maximum rate of mutations. In the S protein, the highest mutation frequency was observed in aa 508-635(0.77%) and aa 381-508 (0.43%). The highest frequency of mutation was observed in aa 66-88 (2.19%), aa 7-14, and aa 164-246 (2.92%) in M, E, and N proteins, respectively.

CONCLUSION

Therefore, monitoring SARS-CoV-2 proteomic changes and detecting hot spots mutations and conserved regions could be applied to improve the SARS-CoV-2 diagnostic efficiency and design safe and effective vaccines against emerging variants.

Pan-cancer clinical impact of latent drivers from double mutations

Here, we discover potential 'latent driver' mutations in cancer genomes. Latent drivers have low frequencies and minor observable translational potential. As such, to date they have escaped identification. Their discovery is important, since when paired in cis, latent driver mutations can drive cancer. Our comprehensive statistical analysis of the pan-cancer mutation profiles of ~60,000 tumor sequences from the TCGA and AACR-GENIE cohorts identifies significantly co-occurring potential latent drivers. We observe 155 same gene double mutations of which 140 individual components are cataloged as latent drivers. Evaluation of cell lines and patient-derived xenograft response data to drug treatment indicate that in certain genes double mutations may have a prominent role in increasing oncogenic activity, hence obtaining a better drug response, as in PIK3CA. Taken together, our comprehensive analyses indicate that same-gene double mutations are exceedingly rare phenomena but are a signature for some cancer types, e.g., breast, and lung cancers. The relative rarity of doublets can be explained by the likelihood of strong signals resulting in oncogene-induced senescence, and by doublets consisting of non-identical single residue components populating the background mutational load, thus not identified.

A Key Role in Catalysis and Enzyme Thermostability of a Conserved Helix H5 Motif of Human Glutathione Transferase A1-1

Glutathione transferases (GSTs) are promiscuous enzymes whose main function is the detoxification of electrophilic compounds. These enzymes are characterized by structural modularity that underpins their exploitation as dynamic scaffolds for engineering enzyme variants, with customized catalytic and structural properties. In the present work, multiple sequence alignment of the alpha class GSTs allowed the identification of three conserved residues (E137, K141, and S142) at α-helix 5 (H5). A motif-directed redesign of the human glutathione transferase A1-1 (hGSTA1-1) was performed through site-directed mutagenesis at these sites, creating two single- and two double-point mutants (E137H, K141H, K141H/S142H, and E137H/K141H). The results showed that all the enzyme variants displayed enhanced catalytic activity compared to the wild-type enzyme hGSTA1-1, while the double mutant hGSTA1-K141H/S142H also showed improved thermal stability. X-ray crystallographic analysis revealed the molecular basis of the effects of double mutations on enzyme stability and catalysis. The biochemical and structural analysis presented here will contribute to a deeper understanding of the structure and function of alpha class GSTs.

Variant-specific deleterious mutations in the SARS-CoV-2 genome reveal immune responses and potentials for prophylactic vaccine development

Introduction: Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, has had a disastrous effect worldwide during the previous three years due to widespread infections with SARS-CoV-2 and its emerging variations. More than 674 million confirmed cases and over 6.7 million deaths have been attributed to successive waves of SARS-CoV-2 infections as of 29th January 2023. Similar to other RNA viruses, SARS-CoV-2 is more susceptible to genetic evolution and spontaneous mutations over time, resulting in the continual emergence of variants with distinct characteristics. Spontaneous mutations of SARS-CoV-2 variants increase its transmissibility, virulence, and disease severity and diminish the efficacy of therapeutics and vaccines, resulting in vaccine-breakthrough infections and re-infection, leading to high mortality and morbidity rates. Materials and methods: In this study, we evaluated 10,531 whole genome sequences of all reported variants globally through a computational approach to assess the spread and emergence of the mutations in the SARS-CoV-2 genome. The available data sources of NextCladeCLI 2.3.0 (https://clades.nextstrain.org/) and NextStrain (https://nextstrain.org/) were searched for tracking SARS-CoV-2 mutations, analysed using the PROVEAN, Polyphen-2, and Predict SNP mutational analysis tools and validated by Machine Learning models. Result: Compared to the Wuhan-Hu-1 reference strain NC 045512.2, genome-wide annotations showed 16,954 mutations in the SARS-CoV-2 genome. We determined that the Omicron variant had 6,307 mutations (retrieved sequence:1947), including 67.8% unique mutations, more than any other variant evaluated in this study. The spike protein of the Omicron variant harboured 876 mutations, including 443 deleterious mutations. Among these deleterious mutations, 187 were common and 256 were unique non-synonymous mutations. In contrast, after analysing 1,884 sequences of the Delta variant, we discovered 4,468 mutations, of which 66% were unique, and not previously reported in other variants. Mutations affecting spike proteins are mostly found in RBD regions for Omicron, whereas most of the Delta variant mutations drawn to focus on amino acid regions ranging from 911 to 924 in the context of epitope prediction (B cell & T cell) and mutational stability impact analysis protruding that Omicron is more transmissible. Discussion: The pathogenesis of the Omicron variant could be prevented if the deleterious and persistent unique immunosuppressive mutations can be targeted for vaccination or small-molecule inhibitor designing. Thus, our findings will help researchers monitor and track the continuously evolving nature of SARS-CoV-2 strains, the associated genetic variants, and their implications for developing effective control and prophylaxis strategies.

Structural prediction of chimeric immunogens to elicit targeted antibodies against betacoronaviruses

Betacoronaviruses pose an ongoing pandemic threat. Antigenic evolution of the SARS-CoV-2 virus has shown that much of the spontaneous antibody response is narrowly focused rather than broadly neutralizing against even SARS-CoV-2 variants, let alone future threats. One way to overcome this is by focusing the antibody response against better-conserved regions of the viral spike protein. Here, we present a design approach to predict stable chimeras between SARS-CoV-2 and other coronaviruses, creating synthetic spike proteins that display a desired conserved region and vary other regions. We leverage AlphaFold to predict chimeric structures and create a new metric for scoring chimera stability based on AlphaFold outputs. We evaluated 114 candidate spike chimeras using this approach. Top chimeras were further evaluated using molecular dynamics simulation as an intermediate validation technique, showing good stability compared to low-scoring controls. This demonstrates the feasibility of the underlying approach, which can be used to design custom immunogens to focus the immune response against a desired viral glycoprotein epitope.