Systemic effects of missense mutations on SARS-CoV-2 spike glycoprotein stability and receptor-binding affinity.

The spike (S) glycoprotein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the binding to the permissive cells. The receptor-binding domain (RBD) of SARS-CoV-2 S protein directly interacts with the human angiotensin-converting enzyme 2 (ACE2) on the host cell membrane. In this study, we used computational saturation mutagenesis approaches, including structure-based energy calculations and sequence-based pathogenicity predictions, to quantify the systemic effects of missense mutations on SARS-CoV-2 S protein structure and function. A total of 18 354 mutations in S protein were analyzed, and we discovered that most of these mutations could destabilize the entire S protein and its RBD. Specifically, residues G431 and S514 in SARS-CoV-2 RBD are important for S protein stability. We analyzed 384 experimentally verified S missense variations and revealed that the dominant pandemic form, D614G, can stabilize the entire S protein. Moreover, many mutations in N-linked glycosylation sites can increase the stability of the S protein. In addition, we investigated 3705 mutations in SARS-CoV-2 RBD and 11 324 mutations in human ACE2 and found that SARS-CoV-2 neighbor residues G496 and F497 and ACE2 residues D355 and Y41 are critical for the RBD-ACE2 interaction. The findings comprehensively provide potential target sites in the development of drugs and vaccines against COVID-19.

A phenome-wide investigation of risk factors for severe COVID-19.

With the continued spread of COVID-19 globally, it is crucial to identify the potential risk or protective factors associated with COVID-19. Here, we performed genetic correlation analysis and Mendelian randomization analysis to examine genetic relationships between COVID-19 hospitalization and 405 health conditions and lifestyle factors in 456 422 participants from the UK Biobank. The genetic correlation analysis revealed 134 positive and 65 negative correlations, including those with intakes of a variety of dietary components. The MR analysis indicates that a set of body fat-related traits, maternal smoking around birth, basal metabolic rate, lymphocyte count, peripheral enthesopathies and allied syndromes, blood clots in the leg, and arthropathy are causal risk factors for severe COVID-19, while higher education attainment, physical activity, asthma, and never smoking status protect against the illness. Our findings have implications for risk stratification in patients with COVID-19 and the prevention of its severe outcomes.

Shared genetics and causal associations between COVID-19 and multiple sclerosis.

Neuroinflammation caused by COVID-19 negatively impacts brain metabolism and function, while pre-existing brain pathology may contribute to individuals' vulnerability to the adverse consequences of COVID-19. We used summary statistics from genome-wide association studies (GWAS) to perform Mendelian randomization (MR) analyses, thus assessing potential associations between multiple sclerosis (MS) and two COVID-19 outcomes (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2] infection and COVID-19 hospitalization). Genome-wide risk genes were compared between the GWAS datasets on hospitalized COVID-19 and MS. Literature-based analysis was conducted to construct molecular pathways connecting MS and COVID-19. We found that genetic liability to MS confers a causal effect on hospitalized COVID-19 (odd ratio [OR]: 1.09, 95% confidence interval: 1.03-1.16) but not on SARS-CoV-2 infection (1.03, 1.00-1.05). Genetic liability to hospitalized COVID-19 confers a causal effect on MS (1.15, 1.02-1.30). Hospitalized COVID-19 and MS share five risk genes within two loci, including TNFAIP8, HSD17B4, CDC37, PDE4A, and KEAP1. Pathway analysis identified a panel of immunity-related genes that may mediate the links between MS and COVID-19. Our study suggests that MS was associated with a 9% increased risk for COVID-19 hospitalization, while hospitalized COVID-19 was associated with a 15% increased risk for MS. Immunity-related pathways may underlie the link between MS on COVID-19.

Correction to: Multiple selective sweeps of ancient polymorphisms in and around LTα located in the MHC class III region on chromosome 6.

After publication of our article [1] we were notified that a few duplicate sentences were included on Figure 3 and Figure 4 legends.

Multiple selective sweeps of ancient polymorphisms in and around LTα located in the MHC class III region on chromosome 6.

BACKGROUND: Lymphotoxin-α (LTα), located in the Major Histocompatibility Complex (MHC) class III region on chromosome 6, encodes a cytotoxic protein that mediates a variety of antiviral responses among other biological functions. Furthermore, several genotypes at this gene have been implicated in the onset of a number of complex diseases, including myocardial infarction, autoimmunity, and various types of cancer. However, little is known about levels of nucleotide variation and linkage disequilibrium (LD) in and near LTα, which could also influence phenotypic variance. To address this gap in knowledge, we examined sequence variation across ~ 10 kilobases (kbs), encompassing LTα and the upstream region, in 2039 individuals from the 1000 Genomes Project originating from 21 global populations. RESULTS: Here, we observed striking patterns of diversity, including an excess of intermediate-frequency alleles, the maintenance of multiple common haplotypes and a deep coalescence time for variation (dating > 1.0 million years ago), in global populations. While these results are generally consistent with a model of balancing selection, we also uncovered a signature of positive selection in the form of long-range LD on chromosomes with derived alleles primarily in Eurasian populations. To reconcile these findings, which appear to support different models of selection, we argue that selective sweeps (particularly, soft sweeps) of multiple derived alleles in and/or near LTα occurred in non-Africans after their ancestors left Africa. Furthermore, these targets of selection were predicted to alter transcription factor binding site affinity and protein stability, suggesting they play a role in gene function. Additionally, our data also showed that a subset of these functional adaptive variants are present in archaic hominin genomes. CONCLUSIONS: Overall, this study identified candidate functional alleles in a biologically-relevant genomic region, and offers new insights into the evolutionary origins of these loci in modern human populations.

Disrupted-in-Schizophrenia-1 (DISC1) protein disturbs neural function in multiple disease-risk pathways.

Although the genetic contribution is under debate, biological studies in multiple mouse models have suggested that the Disrupted-in-Schizophrenia-1 (DISC1) protein may contribute to susceptibility to psychiatric disorders. In the present study, we took the advantages of the Drosophila model to dissect the molecular pathways that can be affected by DISC1 in the context of pathology-related phenotypes. We found that three pathways that include the homologs of Drosophila Dys, Trio, and Shot were downregulated by introducing a C-terminal truncated mutant DISC1. Consistently, these three molecules were downregulated in the induced pluripotent stem cell-derived forebrain neurons from the subjects carrying a frameshift deletion in DISC1 C-terminus. Importantly, the three pathways were underscored in the pathophysiology of psychiatric disorders in bioinformatics analysis. Taken together, our findings are in line with the polygenic theory of psychiatric disorders.

NGS for Sequence Variants.

Recent technological advances in next-generation sequencing (NGS) provide unprecedented power to sequence personal genomes, characterize genomic landscapes, and detect a large number of sequence variants. The discovery of disease-causing variants in patients' genomes has dramatically changed our perspective on precision medicine. This chapter provides an overview of sequence variant detection and analysis in NGS study. We outline the general methods for identifying different types of sequence variants from NGS data. We summarize the common approaches for analyzing and visualizing casual variants associated with complex diseases on precision medicine informatics.

Impact of Missense Mutations on Spike Protein Stability and Binding Affinity in the Omicron Variant.

The global effort to combat the COVID-19 pandemic faces ongoing uncertainty with the emergence of Variants of Concern featuring numerous mutations on the Spike (S) protein. In particular, the Omicron Variant is distinguished by 32 mutations, including 10 within its receptor-binding domain (RBD). These mutations significantly impact viral infectivity and the efficacy of vaccines and antibodies currently in use for therapeutic purposes. In our study, we employed structure-based computational saturation mutagenesis approaches to predict the effects of Omicron missense mutations on RBD stability and binding affinity, comparing them to the original Wuhan-Hu-1 strain. Our results predict that mutations such as G431W and P507W induce the most substantial destabilizations in the Wuhan-Hu-1-S/Omicron-S RBD. Notably, we postulate that mutations in the Omicron-S exhibit a higher percentage of enhancing binding affinity compared to Wuhan-S. We found that the mutations at residue positions G447, Y449, F456, F486, and S496 led to significant changes in binding affinity. In summary, our findings may shed light on the widespread prevalence of Omicron mutations in human populations. The Omicron mutations that potentially enhance their affinity for human receptors may facilitate increased viral binding and internalization in infected cells, thereby enhancing infectivity. This informs the development of new neutralizing antibodies capable of targeting Omicron's immune-evading mutations, potentially aiding in the ongoing battle against the COVID-19 pandemic.

A Computational Approach: The Functional Effects of Thyroid Peroxidase Variants in Thyroid Cancer and Genetic Disorders.

PURPOSE: Thyroid peroxidase (TPO) is essential for the synthesis of thyroid hormones. However, specific mutations render TPO antigenic and prone to autoimmune attacks leading to thyroid cancer, TPO deficiency, and congenital hypothyroidism (CH). Despite technological advancement, most experimental procedures cannot quickly identify the genetic causes of CH nor detect thyroid cancer in the early stages. METHODS: We performed saturated computational mutagenesis to calculate the folding energy changes (∆∆G) caused by missense mutations and analyzed the mutations involved in post-translational modifications (PTMs). RESULTS: Our results showed that the functional important missense mutations occurred in the heme peroxidase domain. Through computational saturation mutagenesis, we identified the TPO mutations in G393 and G348 affecting protein stability and PTMs. Our folding energy calculations revealed that seven of nine somatic thyroid cancer mutations destabilized TPO. CONCLUSION: These findings highlight the impact of these specific mutations on TPO stability, linking them to thyroid cancer and other genetic thyroid-related disorders. Our results show that computational mutagenesis of proteins provides a quick insight into rare mutations causing Mendelian disorders and cancers in humans.

Rational design of a novel propeptide for improving active production of Streptomyces griseus trypsin in Pichia pastoris.

Applying in silico simulations and in vitro experiments, the amino acid proline was proved to have a profound influence on Streptomyces griseus trypsinogen, and the hydrogen bond between H(57) and D(102) was found to be crucial for trypsin activity. By introducing an artificial propeptide, IVEF, the titer of trypsin was increased 6.71-fold.

Recombinant immunotoxin induces tumor intrinsic STING signaling against head and neck squamous cell carcinoma.

The innate immune stimulator of interferon genes (STING) pathway is known to activate type I interferons (IFN-I) and participate in generating antitumor immunity. We previously produced hDT806, a recombinant diphtheria immunotoxin, and demonstrated its efficacy against head and neck squamous cell carcinoma (HNSCC). However, it's unknown whether the tumor-intrinsic STING plays a role in the anti-HNSCC effects of hDT806. In this study, we investigated the innate immune modulation of hDT806 on HNSCC. hDT806 significantly upregulated the level of STING and the ratio of p-TBK1/TBK1 in the HNSCC cells. Moreover, intratumoral hDT806 treatment increased the expression of STING-IFN-I signaling proteins including IFNA1, IFNB, CXCL10 and MX1, a marker of IFN-I receptor activity, in the HNSCC xenografts. Overexpression of STING mimicked the hDT806-induced upregulation of the STING-IFN-I signaling and induced apoptosis in the HNSCC cells. In the mouse xenograft models of HNSCC with STING overexpression, we observed a significant suppression of tumor growth and reduced tumor weight with increased apoptosis compared to their control xenograft counterparts without STING overexpression. Collectively, our data revealed that hDT806 may act as a stimulator of tumor-intrinsic STING-IFN-I signaling to inhibit tumor growth in HNSCC.

Predicting protein sumoylation sites from sequence features.

Protein sumoylation is a post-translational modification that plays an important role in a wide range of cellular processes. Small ubiquitin-related modifier (SUMO) can be covalently and reversibly conjugated to the sumoylation sites of target proteins, many of which are implicated in various human genetic disorders. The accurate prediction of protein sumoylation sites may help biomedical researchers to design their experiments and understand the molecular mechanism of protein sumoylation. In this study, a new machine learning approach has been developed for predicting sumoylation sites from protein sequence information. Random forests (RFs) and support vector machines (SVMs) were trained with the data collected from the literature. Domain-specific knowledge in terms of relevant biological features was used for input vector encoding. It was shown that RF classifier performance was affected by the sequence context of sumoylation sites, and 20 residues with the core motif ΨKXE in the middle appeared to provide enough context information for sumoylation site prediction. The RF classifiers were also found to outperform SVM models for predicting protein sumoylation sites from sequence features. The results suggest that the machine learning approach gives rise to more accurate prediction of protein sumoylation sites than the other existing methods. The accurate classifiers have been used to develop a new web server, called seeSUMO (http://bioinfo.ggc.org/seesumo/), for sequence-based prediction of protein sumoylation sites.

Impact of SARS-CoV-2 on Host Factors Involved in Mental Disorders.

COVID-19, caused by SARS-CoV-2, is a systemic illness due to its multiorgan effects in patients. The disease has a detrimental impact on respiratory and cardiovascular systems. One early symptom of infection is anosmia or lack of smell; this implicates the involvement of the olfactory bulb in COVID-19 disease and provides a route into the central nervous system. However, little is known about how SARS-CoV-2 affects neurological or psychological symptoms. SARS-CoV-2 exploits host receptors that converge on pathways that impact psychological symptoms. This systemic review discusses the ways involved by coronavirus infection and their impact on mental health disorders. We begin by briefly introducing the history of coronaviruses, followed by an overview of the essential proteins to viral entry. Then, we discuss the downstream effects of viral entry on host proteins. Finally, we review the literature on host factors that are known to play critical roles in neuropsychiatric symptoms and mental diseases and discuss how COVID-19 could impact mental health globally. Our review details the host factors and pathways involved in the cellular mechanisms, such as systemic inflammation, that play a significant role in the development of neuropsychological symptoms stemming from COVID-19 infection.

Computational Saturation Mutagenesis to Investigate the Effects of Neurexin-1 Mutations on AlphaFold Structure.

Neurexin-1 (NRXN1) is a membrane protein essential in synapse formation and cell signaling as a cell-adhesion molecule and cell-surface receptor. NRXN1 and its binding partner neuroligin have been associated with deficits in cognition. Recent genetics research has linked NRXN1 missense mutations to increased risk for brain disorders, including schizophrenia (SCZ) and autism spectrum disorder (ASD). Investigation of the structure-function relationship in NRXN1 has proven difficult due to a lack of the experimental full-length membrane protein structure. AlphaFold, a deep learning-based predictor, succeeds in high-quality protein structure prediction and offers a solution for membrane protein model construction. In the study, we applied a computational saturation mutagenesis method to analyze the systemic effects of missense mutations on protein functions in a human NRXN1 structure predicted from AlphaFold and an experimental Bos taurus structure. The folding energy changes were calculated to estimate the effects of the 29,540 mutations of AlphaFold model on protein stability. The comparative study on the experimental and computationally predicted structures shows that these energy changes are highly correlated, demonstrating the reliability of the AlphaFold structure for the downstream bioinformatics analysis. The energy calculation revealed that some target mutations associated with SCZ and ASD could make the protein unstable. The study can provide helpful information for characterizing the disease-causing mutations and elucidating the molecular mechanisms by which the variations cause SCZ and ASD. This methodology could provide the bioinformatics protocol to investigate the effects of target mutations on multiple AlphaFold structures.

The pH Effects on SARS-CoV and SARS-CoV-2 Spike Proteins in the Process of Binding to hACE2.

COVID-19 has been threatening human health since the late 2019, and has a significant impact on human health and economy. Understanding SARS-CoV-2 and other coronaviruses is important to develop effective treatments for COVID-19 and other coronavirus-caused diseases. In this work, we applied multi-scale computational approaches to study the electrostatic features of spike (S) proteins for SARS-CoV and SARS-CoV-2. From our results, we found that SARS-CoV and SARS-CoV-2 have similar charge distributions and electrostatic features when binding with the human angiotensin-converting enzyme 2 (hACE2). Energy pH-dependence calculations revealed that the complex structures of hACE2 and the S proteins of SARS-CoV/SARS-CoV-2 are stable at pH values ranging from 7.5 to 9. Three independent 100 ns molecular dynamics (MD) simulations were performed using NAMD to investigate the hydrogen bonds between S proteins RBD and hACE2 RBD. From MD simulations, we found that SARS-CoV-2 forms 19 pairs (average of three simulations) of hydrogen bonds with high occupancy (>50%) to hACE2, compared to 16 pairs between SARS-CoV and hACE2. Additionally, SARS-CoV viruses prefer sticking to the same hydrogen bond pairs, while SARS-CoV-2 tends to have a larger range of selections on hydrogen bonds acceptors. We also labelled key residues involved in forming the top five hydrogen bonds that were found in all three independent 100 ns simulations. This identification is important to potential drug designs for COVID-19 treatments. Our work will shed the light on current and future coronavirus-caused diseases.

In-silico investigation of systematic missense mutations of middle east respiratory coronavirus spike protein.

Middle East Respiratory Syndrome Coronavirus (MERS-CoV) causes severe pneumonia-like symptoms and is still pose a significant threat to global public health. A key component in the virulence of MERS-CoV is the Spike (S) protein, which binds with the host membrane receptor dipeptidyl peptidase 4 (DPP4). The goal of the present investigation is to examine the effects of missense mutations in the MERS-CoV S protein on protein stability and binding affinity with DPP4 to provide insight that is useful in developing vaccines to prevent coronavirus infection. We utilized a saturation mutagenesis approach to simulate all possible mutations in the MERS-CoV full-length S, S Receptor Binding Domain (RBD) and DPP4. We found the mutations in MERS-CoV S protein residues, G552, C503, C526, N468, G570, S532, S451, S419, S465, and S435, affect protein stability. We identified key residues, G538, E513, V555, S557, L506, L507, R511, M452, D537, and S454 in the S protein RBD region are important in the binding of MERS-CoV S protein to the DPP4 receptor. We investigated the effects of MERS-CoV S protein viral mutations on protein stability and binding affinity. In addition, we studied all DPP4 mutations and found the functional substitution R336T weakens both DPP4 protein stability and S-DPP4 binding affinity. We compared the S protein structures of MERS-CoV, SARS-CoV, and SARS-CoV-2 viruses and identified the residues like C526, C383, and N468 located in equivalent positions of these viruses have effects on S protein structure. These findings provide further information on how mutations in coronavirus S proteins effect protein function.

Prediction of the Effects of Missense Mutations on Human Myeloperoxidase Protein Stability Using In Silico Saturation Mutagenesis.

Myeloperoxidase (MPO) is a heme peroxidase with microbicidal properties. MPO plays a role in the host's innate immunity by producing reactive oxygen species inside the cell against foreign organisms. However, there is little functional evidence linking missense mutations to human diseases. We utilized in silico saturation mutagenesis to generate and analyze the effects of 10,811 potential missense mutations on MPO stability. Our results showed that ~71% of the potential missense mutations destabilize MPO, and ~8% stabilize the MPO protein. We showed that G402W, G402Y, G361W, G402F, and G655Y would have the highest destabilizing effect on MPO. Meanwhile, D264L, G501M, D264H, D264M, and G501L have the highest stabilization effect on the MPO protein. Our computational tool prediction showed the destabilizing effects in 13 out of 14 MPO missense mutations that cause diseases in humans. We also analyzed putative post-translational modification (PTM) sites on the MPO protein and mapped the PTM sites to disease-associated missense mutations for further analysis. Our analysis showed that R327H associated with frontotemporal dementia and R548W causing generalized pustular psoriasis are near these PTM sites. Our results will aid further research into MPO as a biomarker for human complex diseases and a candidate for drug target discovery.

Genetic variations affecting ACE2 protein stability in minority populations.

While worldwide efforts for improving COVID-19 vaccines are currently considered a top priority, the role of the genetic variants responsible for virus receptor protein stability is less studied. Angiotensin-converting enzyme-2 is the primary target of the SARS-CoV-1/SARS-CoV-2 spike (S) glycoprotein, enabling entry into the human body. Here, we applied computational saturation mutagenesis approaches to determine the folding energy caused by all possible mutations in ACE2 proteins within ACE2 - SARS-CoV-1-S/ACE2 - SARS-CoV-2-S complexes. We observed ACE2 mutations at residue D350 causing the most stabilizing effects on the protein. In addition, we identified ACE2 genetic variations in African Americans (rs73635825, rs766996587, and rs780574871), Latino Americans (rs924799658), and both groups (rs4646116 and rs138390800) affecting stability in the ACE2 - SARS-CoV-2-S complex. The findings in this study may aid in targeting the design of stable neutralizing peptides for treating minority patients.

A novel diG motif in ORF3a protein of SARS-Cov-2 for intracellular transport.

The ongoing SARS-CoV-2/COVID-19 pandemic caused a global public health crisis. Yet, everyone's response to SARS-CoV-2 infection varies, and different viral variants confer diverse pathogenicity. Thus, it is imperative to understand how viral determinants contribute to COVID-19. Viral ORF3a protein is one of those viral determinants, as its functions are linked to induction of cell and tissues damages, disease severity and cytokine storm that is a major cause of COVID-19-related death. ORF3a is a membrane-associated protein. Upon synthesis, it is transported from endoplasmic reticulum, Golgi apparatus to plasma membrane and subcellular endomembranes including endosomes and lysosomes. However, how ORF3a is transported intracellularly remains elusive. The goal of this study was to carry out a systematic mutagenesis study to determine the structural relationship of ORF3a protein with its subcellular locations. Single amino acid (aa) and deletion mutations were generated in the putative function-relevant motifs and other regions of interest. Immunofluorescence and ImageJ analyses were used to determine and quantitate subcellular locations of ORF3a mutants in comparison with wildtype ORF3a. The wildtype ORF3a localizes predominantly (Pearson's coefficients about 0.8) on the membranes of endosomes and lysosomes. Consistent with earlier findings, deletion of the YXXΦ motif, which is required for protein export, retained ORF3a in the Golgi apparatus. Interestingly, mutations in a double glycine (diG) region (aa 187-188) displayed a similar phenotype to the YXXΦ deletion, implicating a similar role of the diG motif in intracellular transport. Indeed, interrupting any one of the two glycine residues such as deletion of a single (dG188), both (dG187/dG188) or substitution (G188Y) of these residues led to ORF3a retention in the Golgi apparatus (Pearson's coefficients ≥0.8). Structural analyses further suggest that the diG motif supports a type-II ß-turn between the anti-parallel ß4 and ß5 sheets and connects to the YXXΦ motif via hydrogen bonds between two monomers. The diG- YXXΦ interaction forms a hand-in-hand configuration that could facilitate dimerization. Together, these observations suggest a functional role of the diG motif in intracellular transport of ORF3a.