Evolution of increased positive charge on the SARS-CoV-2 spike protein may be adaptation to human transmission

Large-Scale FMO-MP2 Calculations of the Spike Protein Droplet Model

The spike protein of SARS-CoV-2 is a challenging target for theoretical approaches. Here we report a benchmark calculation of the spike protein droplet model by the fragment molecular orbital (FMO) at the second-order Møller-Plesset perturbation (MP2) level on the supercomputer Fugaku. One hundred structure samples from molecular dynamics (MD) simulations were used for both the closed and open forms of this protein (PDB IDs 6XLU and 6XM0 respectively). The number of total fragments is about 20,000, and the job time per structure was about 2 h on 8 racks of Fugaku.

Sulfated Cellulose Nanofiber Hydrogel with Mucus-Like Activities for Virus Inhibition

Mucus is the first defense barrier against viruses in the human immune system. Inspired by the mucus structure, we designed a highly sulfated hydrogel to bind viruses and prevent infection of the underlying cells. The hydrogel was formed by gelation of sulfated cellulose nanofiber (SCNF) with Ca2+. SCNF exhibited a mucin-like nanofiber structure with high numbers of sulfated groups. Based on the electrostatic interactions with a virus, SCNF could efficiently inhibit herpes simplex virus-1 (HSV-1) infection with a half-maximal inhibitory concentration (IC50) of 0.43 μg/mL, which is comparable to that of heparin (IC50 = 0.30 μg/mL). Benefiting from the multiporous structure and sulfate groups, the Ca2+-SCNF hydrogel could efficiently trap HSV-1 and inhibit the virus from attacking the underlying cells in a transwell model. Furthermore, SCNF also inhibited SARS-CoV-2 infection in a similar experimental setting. By integrating the advantages of high and broad-spectrum virus inhibitory activity as well as low toxicity, it is believed that the Ca2+-SCNF hydrogel can promote the development of highly biocompatible and efficient antiviral material with "binding and inhibition" capability and other diverse strategies.

Core and accessory genomic traits of Vibrio cholerae O1 drive lineage transmission and disease severity

In Bangladesh, Vibrio cholerae lineages are undergoing genomic evolution, with increased virulence and spreading ability. However, our understanding of the genomic determinants influencing lineage transmission and disease severity remains incomplete. Here, we developed a computational framework using machine-learning, genome scale metabolic modelling (GSSM) and 3D structural analysis, to identify V. cholerae genomic traits linked to lineage transmission and disease severity. We analysed in-patients isolates from six Bangladeshi regions (2015-2021), and uncovered accessory genes and core SNPs unique to the most recent dominant lineage, with virulence, motility and bacteriophage resistance functions. We also found a strong correlation between V. cholerae genomic traits and disease severity, with some traits overlapping those driving lineage transmission. GSMM and 3D structure analysis unveiled a complex interplay between transcription regulation, protein interaction and stability, and metabolic networks, associated to lifestyle adaptation, intestinal colonization, acid tolerance and symptom severity. Our findings support advancing therapeutics and targeted interventions to mitigate cholera spread.

Semi-Covariance Coefficient Analysis of Spike Proteins from SARS-CoV-2 and Its Variants Omicron, BA.5, EG.5, and JN.1 for Viral Infectivity, Virulence and Immune Escape

Semi-covariance has attracted significant attention in recent years and is increasingly employed to elucidate statistical phenomena exhibiting fluctuations, such as the similarity or difference in charge patterns of spike proteins among coronaviruses. In this study, by examining values above and below the average/mean based on the positive and negative charge patterns of amino acid residues in the spike proteins of SARS-CoV-2 and its current circulating variants, the proposed methods offer profound insights into the nonlinear evolving trends in those viral spike proteins. Our study indicates that the charge span value can predict the infectivity of the virus and the charge density can estimate the virulence of the virus, and both predicated infectivity and virulence appear to be associated with the capability of viral immune escape. This semi-covariance coefficient analysis may be used not only to predict the infectivity, virulence and capability of immune escape for coronaviruses but also to analyze the functionality of other viral proteins. This study improves our understanding of the trend of viral evolution in terms of viral infectivity, virulence or the capability of immune escape, which remains further validated by more future studies and statistical data.

Plastisphere-hosted viruses: A review of interactions, behavior, and effects

Microbial communities, including bacteria, diatoms, and fungi, colonize plastic surfaces, forming biofilms known as the "plastisphere." Recent research has revealed that plastispheres also host a wide range of viruses, sparking interest in microbial ecology and virology. This shared habitat allows viruses to replicate, interact, infect, and spread, potentially impacting the environment and human health. Consequently, viruses attached to microplastics are now recognized to have broad effects on cellular and immune responses. However, the ecology and implications of viruses hosted in plastisphere habitats remain poorly understood, highlighting their fundamental importance as a subject of study. This review explores various pathways for virus attachment to plastispheres, factors influencing these interactions, their impacts within plastisphere and host-associated environments, and associated issues. It also summarizes current research and identifies knowledge gaps. We anticipate that this paper will help improve our predictive understanding of plastisphere viruses in natural settings and emphasizes the need for more research in real-world environments to advance the field.

An evolutionary theory on virus mutation in COVID-19

With the rapid evolution of SARS-CoV-2, the emergence of new strains is an intriguing question. This paper presents an evolutionary theory to analyze the mutations of the virus and identify the conditions that lead to the generation of new strains. We represent the virus variants using a 4-letter sequence based on amino acid mutations on the spike protein and employ an n-distance algorithm to derive a variant phylogenetic tree. We show that the theoretically-derived tree aligns with experimental data on virus evolution. Additionally, we propose an A-X model, utilizing the set of existing mutation sites (A) and a set of randomly generated sites (X), to calculate the emergence of new strains. Our findings demonstrate that a sufficient number of random iterations can predict the generation of new macro-lineages when the number of sites in X is large enough. These results provide a crucial theoretical basis for understanding the evolution of SARS-CoV-2.

Changes in total charge on spike protein of SARS-CoV-2 in emerging lineages

Motivation

Charged amino acid residues on the spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been shown to influence its binding to different cell surface receptors, its non-specific electrostatic interactions with the environment, and its structural stability and conformation. It is therefore important to obtain a good understanding of amino acid mutations that affect the total charge on the spike protein which have arisen across different SARS-CoV-2 lineages during the course of the virus' evolution.

Results

We analyse the change in the number of ionizable amino acids and the corresponding total charge on the spike proteins of almost 2200 SARS-CoV-2 lineages that have emerged over the span of the pandemic. Our results show that the previously observed trend toward an increase in the positive charge on the spike protein of SARS-CoV-2 variants of concern has essentially stopped with the emergence of the early omicron variants. Furthermore, recently emerged lineages show a greater diversity in terms of their composition of ionizable amino acids. We also demonstrate that the patterns of change in the number of ionizable amino acids on the spike protein are characteristic of related lineages within the broader clade division of the SARS-CoV-2 phylogenetic tree. Due to the ubiquity of electrostatic interactions in the biological environment, our findings are relevant for a broad range of studies dealing with the structural stability of SARS-CoV-2 and its interactions with the environment.

Availability and implementation

The data underlying the article are available in the Supplementary material.

Evolutionary changes in the number of dissociable amino acids on spike proteins and nucleoproteins of SARS-CoV-2 variants

The spike protein of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for target recognition, cellular entry, and endosomal escape of the virus. At the same time, it is the part of the virus that exhibits the greatest sequence variation across the many variants which have emerged during its evolution. Recent studies have indicated that with progressive lineage emergence, the positive charge on the spike protein has been increasing, with certain positively charged amino acids (AAs) improving the binding of the spike protein to cell receptors. We have performed a detailed analysis of dissociable AAs of more than 1400 different SARS-CoV-2 lineages, which confirms these observations while suggesting that this progression has reached a plateau with Omicron and its subvariants and that the positive charge is not increasing further. Analysis of the nucleocapsid protein shows no similar increase in positive charge with novel variants, which further indicates that positive charge of the spike protein is being evolutionarily selected for. Furthermore, comparison with the spike proteins of known coronaviruses shows that already the wild-type SARS-CoV-2 spike protein carries an unusually large amount of positively charged AAs when compared to most other betacoronaviruses. Our study sheds light on the evolutionary changes in the number of dissociable AAs on the spike protein of SARS-CoV-2, complementing existing studies and providing a stepping stone towards a better understanding of the relationship between the spike protein charge and viral infectivity and transmissibility.

SARS-CoV-2 evolved variants optimize binding to cellular glycocalyx

Viral variants of concern continue to arise for SARS-CoV-2, potentially impacting both methods for detection and mechanisms of action. Here, we investigate the effect of an evolving spike positive charge in SARS-CoV-2 variants and subsequent interactions with heparan sulfate and the angiotensin converting enzyme 2 (ACE2) in the glycocalyx. We show that the positively charged Omicron variant evolved enhanced binding rates to the negatively charged glycocalyx. Moreover, we discover that while the Omicron spike-ACE2 affinity is comparable to that of the Delta variant, the Omicron spike interactions with heparan sulfate are significantly enhanced, giving rise to a ternary complex of spike-heparan sulfate-ACE2 with a large proportion of double-bound and triple-bound ACE2. Our findings suggest that SARS-CoV-2 variants evolve to be more dependent on heparan sulfate in viral attachment and infection. This discovery enables us to engineer a second-generation lateral-flow test strip that harnesses both heparin and ACE2 to reliably detect all variants of concern, including Omicron.