Evolutionary and codon usage preference insights into spike glycoprotein of SARS-CoV-2

Codon usage bias of secretory protein in Fusarium oxysporum f. sp. cubense tropical race 4

Banana Fusarium oxysporum f. sp. cubense tropical race 4 (Foc-TR4) is a highly destructive pathogen that infects nearly all major banana cultivars and has a tendency to spread further. Secreted proteins play a crucial role in the process of Fusarium wilt infection in bananas. In this study, we analyzed the codon usage bias (CUB) of the Foc-TR4 classical secretory protein genome for the first time and observed a strong bias toward codons ending with C. We found that 572 out of the 14,543 amino acid sequences in the Foc-TR4 genome exhibited characteristics of classical secretory proteins. The CUB was largely influenced by selection optimization pressure, as indicated by the ENC value and neutral plot analysis. Among the identified codons, such as UCC and CCC, 11 were found to be optimal for Foc-TR4 gene expression. Codons with higher GC content and a C base in the third position showed greater selectivity. The CUB in the secretory proteins encoded by Foc-TR4 provides insights into their evolutionary patterns, contributing to the development and screening of novel and effective antifungal drugs.

Identification of putative antiviral bioactive compounds derived from family Asteraceae: An in silico approach

This computational study investigates 21 bioactive compounds from the Asteraceae family as potential inhibitors targeting the Spike protein (S protein) of SARS-CoV-2. Employing in silico methods and simulations, particularly CDOCKER and MM-GBSA, the study identifies two standout compounds, pterodontic acid and cichoric acid, demonstrating robust binding affinities (-46.1973 and -39.4265 kcal/mol) against the S protein. Comparative analysis with Favipiravir underscores their potential as promising inhibitors. Remarkably, these bioactives exhibit favorable ADMET properties, suggesting safety and efficacy. Molecular dynamics simulations validate their stability and interactions, signifying their potential as effective SARS-CoV-2 inhibitors.

Comprehensive Genomics Investigation of Neboviruses Reveals Distinct Codon Usage Patterns and Host Specificity

Neboviruses (NeVs) from the Caliciviridae family have been linked to enteric diseases in bovines and have been detected worldwide. As viruses rely entirely on the cellular machinery of the host for replication, their ability to thrive in a specific host is greatly impacted by the specific codon usage preferences. Here, we systematically analyzed the codon usage bias in NeVs to explore the genetic and evolutionary patterns. Relative Synonymous Codon Usage and Effective Number of Codon analyses indicated a marginally lower codon usage bias in NeVs, predominantly influenced by the nucleotide compositional constraints. Nonetheless, NeVs showed a higher codon usage bias for codons containing G/C at the third codon position. The neutrality plot analysis revealed natural selection as the primary factor that shaped the codon usage bias in both the VP1 (82%) and VP2 (57%) genes of NeVs. Furthermore, the NeVs showed a highly comparable codon usage pattern to bovines, as reflected through Codon Adaptation Index and Relative Codon Deoptimization Index analyses. Notably, yak NeVs showed considerably different nucleotide compositional constraints and mutational pressure compared to bovine NeVs, which appear to be predominantly host-driven. This study sheds light on the genetic mechanism driving NeVs' adaptability, evolution, and fitness to their host species.

Mutation and codon bias analysis of the spike protein of Omicron, the recent variant of SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant is a heavily mutated virus and designated as a variant of concern. To investigate the codon usage pattern of this new variant, we performed mutation and codon bias analysis for Omicron as well as for its sub-lineages BA.1 and BA.2 and compared them with the original SARS-CoV-2 and the Delta variant sequences obtained in this study. Our results indicate that the sub-lineage BA.1 and BA.2 have up to 23 sites of difference on the spike protein, which have minimal impact on function. The Omicron variant and its sub-lineages have similar codon usage patterns and A/U ending codons appear to be preferred over G/C ending codons. The Omicron has a lower degree of codon usage bias in spite of evidence that natural selection, mutation pressure and dinucleotide abundance shape the codon usage bias of Omicron, with natural selection being more significant on BA.2 than the other sub-lineages of Omicron. The codon usage pattern of Omicron variant that we explored provides valid information for a clearer understanding of Omicron and its sub-lineages, which could find application in vaccine development and optimization.

Tracking the evolution of the SARS-CoV-2 Delta variant of concern: analysis of genetic diversity and selection across the whole viral genome

Background

Since 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has diversified extensively, producing five highly virulent lineages designated as variants of concern (VOCs). The Delta VOC emerged in India with increased transmission, immune evasion, and mortality, causing a massive global case surge in 2021. This study aims to understand how the Delta VOC evolved by characterizing mutation patterns in the viral population before and after its emergence. Furthermore, we aim to identify the influence of positive and negative selection on VOC evolution and understand the prevalence of different mutation types in the viral genome.

Methods

Three groups of whole viral genomes were retrieved from GISAID, sourced from India, with collection periods as follows: Group A-during the initial appearance of SARS-CoV-2; Group B-just before the emergence of the Delta variant; Group C-after the establishment of the Delta variant in India. Mutations in >1% of each group were identified with BioEdit to reveal differences in mutation quantity and type. Sites under positive or negative selection were identified with FUBAR. The results were compared to determine how mutations correspond with selective pressures and how viral mutation profiles changed to reflect genetic diversity before and after VOC emergence.

Results

The number of mutations increased progressively in Groups A-C, with Group C reporting a 2.2- and 1.9-fold increase from Groups A and B, respectively. Among all the observed mutations, Group C had the highest percentage of deletions (22.7%; vs. 4.2% and 2.6% in Groups A and B, respectively), and most mutations altered the final amino acid code, such as non-synonymous substitutions and deletions. Conversely, Group B had the most synonymous substitutions that are effectively silent. The number of sites experiencing positive selection increased in Groups A-C, but Group B had 2.4- and 2.6 times more sites under negative selection compared to Groups A and C, respectively.

Conclusion

Our findings demonstrated that viral genetic diversity continuously increased during and after the emergence of the Delta VOC. Despite this, Group B reports heightened negative selection, which potentially preserves important gene regions during evolution. Group C contains an unprecedented quantity of mutations and positively selected sites, providing strong evidence of active viral adaptation in the population.

Insights into the Evolution and Host Adaptation of the Monkeypox Virus from a Codon Usage Perspective: Focus on the Ongoing 2022 Outbreak

The exceptionally widespread outbreak of human monkeypox, an emerging zoonosis caused by the monkeypox virus (MPXV), with more than 69,000 confirmed cases in 100 non-endemic countries since 2022, is a major public health concern. Codon usage patterns reflect genetic variation and adaptation to new hosts and ecological niches. However, detailed analyses of codon usage bias in MPXV based on large-scale genomic data, especially for strains responsible for the 2022 outbreak, are lacking. In this study, we analyzed codon usage in MPXV and its relationship with host adaptation. We confirmed the ongoing outbreak of MPXVs belonging to the West Africa (WA) lineage by principal component analysis based on their codon usage patterns. The 2022 outbreak strains had a relatively low codon usage bias. Codon usage of MPXVs was shaped by mutation and natural selection; however, different from past strains, codon usage in the 2022 outbreak strains was predominantly determined by mutation pressure. Additionally, as revealed by the codon adaptation index (CAI), relative codon deoptimization index (RCDI), and similarity index (SiD) analyses, the codon usage patterns of MPXVs were also affected by their hosts. In particular, the 2022 outbreak strains showed slightly but significantly greater adaptation to many primates, including humans, and were subjected to stronger selection pressure induced by hosts. Our results suggest that MPXVs contributing to the 2022 outbreak have unique evolutionary features, emphasizing the importance of sustained monitoring of their transmission and evolution.

Clinical characteristics of the host DNA-removed metagenomic next-generation sequencing technology for detecting SARS-CoV-2, revealing host local immune signaling and assisting genomic epidemiology

BACKGROUND

Metagenomic next-generation sequencing (mNGS) technology has been central in detecting infectious diseases and helping to simultaneously reveal the complex interplay between invaders and their hosts immune response characteristics. However, it needs to be rigorously assessed for clinical utility. The present study is the first to evaluate the clinical characteristics of the host DNA-removed mNGS technology for detecting SARS-CoV-2, revealing host local immune signaling and assisting genomic epidemiology.

METHODS

46 swab specimens collected from COVID-19 patients were assayed by two approved commercial RT-qPCR kits and mNGS. The evolutionary tree of SARS-CoV-2 was plotted using FigTree directly from one sample. The workflow of removing the host and retaining the host was compared to investigate the influence of host DNA removal on the performances of mNGS. Functional enrichment analysis of DEGs and xCell score were used to explore the characteristics of host local immune signaling.

RESULTS

The detection rate of mNGS achieved 92.9% (26/28) for 28 samples with a Ct value ≤ 35 and 81.1% (30/37) for all 46 samples. The genome coverage of SARS-CoV-2 could reach up to 98.9% when the Ct value is about 20 in swab samples. Removing the host could enhance the sensitivity of mNGS for detecting SARS-CoV-2 from the swab sample but does not affect the species abundance of microbes RNA. Improving the sequencing depth did not show a positive effect on improving the detection sensitivity of SARS-CoV-2. Cell type enrichment scores found multiple immune cell types were differentially expressed between patients with high and low viral load.

CONCLUSIONS

The host DNA-removed mNGS has great potential utility and superior performance on comprehensive identification of SARS-CoV-2 and rapid traceability, revealing the microbiome's transcriptional profiles and host immune responses.

A novel structure-based approach for identification of vertebrate susceptibility to SARS-CoV-2: Implications for future surveillance programmes

Understanding the origin of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a highly debatable and unresolved issue for scientific communities all over the world. Understanding the mechanism of virus entry to the host cells is crucial to deciphering the susceptibility profiles of animal species to SARS-CoV-2. The interaction of SARS-CoV-2 ligands (receptor-binding domain on spike protein) with its host cell receptor, angiotensin-converting enzyme 2 (ACE2), is a critical determinant of host range and cross-species transmission. In this study, we developed and implemented a rigorous computational approach for predicting binding affinity between 299 ACE2 orthologs from diverse vertebrate species and the SARS-CoV-2 spike protein. The findings show that the SARS-CoV-2 spike protein can bind to a wide range of vertebrate species carrying evolutionary divergent ACE2, implying a broad host range at the virus entry level, which may contribute to cross-species transmission and further viral evolution. Furthermore, the current study facilitated the identification of genetic determinants that may differentiate susceptible from resistant host species based on the conservation of ACE2-spike protein interacting residues in vertebrate host species known to facilitate SARS-CoV-2 infection; however, these genetic determinants warrant in vivo experimental confirmation. The molecular interactions associated with varied binding affinity of distinct ACE2 isoforms in a specific bat species were identified using protein structure analysis, implying the existence of diversified bat species' susceptibility to SARS-CoV-2. The current study's findings highlight the importance of intensive surveillance programmes aimed at identifying susceptible hosts, especially those with the potential to transmit zoonotic pathogens, in order to prevent future outbreaks.

Natural selection plays a significant role in governing the codon usage bias in the novel SARS-CoV-2 variants of concern (VOC)

The ongoing prevailing COVID-19 pandemic caused by SARS-CoV-2 is becoming one of the major global health concerns worldwide. The SARS-CoV-2 genome encodes spike (S) glycoprotein that plays a very crucial role in viral entry into the host cell via binding of its receptor binding domain (RBD) to the host angiotensin converting enzyme 2 (ACE2) receptor. The continuously evolving SARS-CoV-2 genome results in more severe and transmissible variants characterized by the emergence of novel mutations called 'variants of concern' (VOC). The currently designated alpha, beta, gamma, delta and omicron VOC are the focus of this study due to their high transmissibility, increased virulence, and concerns for decreased effectiveness of the available vaccines. In VOC, the spike (S) gene and other non-structural protein mutations may affect the efficacies of the approved COVID-19 vaccines. To understand the diversity of SARS-CoV-2, several studies have been performed on a limited number of sequences. However, only a few studies have focused on codon usage bias (CUBs) pattern analysis of all the VOC strains. Therefore, to evaluate the evolutionary divergence of all VOC S-genes, we performed CUBs analysis on 300,354 sequences to understand the evolutionary relationship with its adaptation in different hosts, i.e., humans, bats, and pangolins. Base composition and RSCU analysis revealed the presence of 20 preferred AU-ended and 10 under-preferred GC-ended codons. In addition, CpG was found to be depleted, which may be attributable to the adaptive response by viruses to escape from the host defense process. Moreover, the ENC values revealed a higher bias in codon usage in the VOC S-gene. Further, the neutrality plot analysis demonstrated that S-genes analyzed in this study are under 83.93% influence of natural selection, suggesting its pivotal role in shaping the CUBs. The CUBs pattern of S-genes was found to be very similar among all the VOC strains. Interestingly, we observed that VOC strains followed a trend of antagonistic codon usage with respect to the human host. The identified CUBs divergence would help to understand the virus evolution and its host adaptation, thus help design novel vaccine strategies against the emerging VOC strains. To the best of our knowledge, this is the first report for identifying the evolution of CUBs pattern in all the currently identified VOC.

CRISPR use in diagnosis and therapy for COVID-19

Since the beginning of the COVID-19 pandemic, many diagnostic approaches (RT-qPCR, RAPID, LFA) have been adopted, with RT-qPCR being the most popular/gold standard. But, one of the major problems of COVID-19 diagnostics is the presentation of a wide range of symptoms which varies among different patients and needs early diagnosis for better management. Even though RT-qPCR is a precise molecular technique false negative results may be obtained. On the other hand, CRISPR-based SARS-CoV-2 detection approaches are cost and time efficient, highly sensitive and specific, and do not require sophisticated instruments. Moreover, they also show promise for increased scalability and diagnostic tests can be carried out at the point-of-care (POC). The CRISPR can be customized to the target of any genomic region of interest within the desired genome possessing a broad range of other applications and has been efficiently implemented for diagnosis of SARS-CoV-2. The CRISPR/Cas systems provide the specific gene targeting with immense potential to develop new generation diagnostics and therapeutics. Moreover, with the CRISPR/Cas based therapeutics, multiplexing is possible, where different sgRNAs or crRNAs can be guided to more than one target within the same gene thus decreasing the possibility of viral escape mutants. As an exceptionally efficient tool CRISPR/Cas13 and CARVER (Cas13-assisted restriction of viral expression and readout) systems can be implemented to target a broad range of ssRNA viruses that can be used for both, diagnosis and treatment for a variety of viral diseases including SARS-CoV-2. However, the efficacy and safety of the CRISPR-based therapeutics needs to be assessed in pre-clinical and clinical settings. Although the CRISPR biotechnologies are not very helpful to control the present pandemic of COVID-19 it is hopeful that the limitations of the CRISPR/Cas system can be overcome in the near future. The CRISPR based strategies may lead to a new era in the field of disease diagnosis and therapeutic development that would make us better prepared for future viral threats.

Statistical modeling of SARS-CoV-2 substitution processes: predicting the next variant

We build statistical models to describe the substitution process in the SARS-CoV-2 as a function of explanatory factors describing the sequence, its function, and more. These models serve two different purposes: first, to gain knowledge about the evolutionary biology of the virus; and second, to predict future mutations in the virus, in particular, non-synonymous amino acid substitutions creating new variants. We use tens of thousands of publicly available SARS-CoV-2 sequences and consider tens of thousands of candidate models. Through a careful validation process, we confirm that our chosen models are indeed able to predict new amino acid substitutions: candidates ranked high by our model are eight times more likely to occur than random amino acid changes. We also show that named variants were highly ranked by our models before their appearance, emphasizing the value of our models for identifying likely variants and potentially utilizing this knowledge in vaccine design and other aspects of the ongoing battle against COVID-19.

As the virus that causes COVID-19 continues to mutate and spread, new methods are needed to predict new potential variants. Here, the authors identify the best regression models for predicting likely mutation sites in the SARS-CoV-2 genome using a candidate set that considers sequence, gene location, and biological function.

SARS-CoV-2 host prediction based on virus-host genetic features

The genetic diversity of the Coronaviruses gives them different biological abilities, such as infect different cells and/or organisms, a wide spectrum of clinical manifestations, their different routes of dispersion, and viral transmission in a specific host. In recent decades, different Coronaviruses have emerged that are highly adapted for humans and causing serious diseases, leaving their host of unknown origin. The viral genome information is particularly important to enable the recognition of patterns linked to their biological characteristics, such as the specificity in the host-parasite relationship. Here, based on a previously computational tool, the Seq2Hosts, we developed a novel approach which uses new variables obtained from the frequency of spike-Coronaviruses codons, the Relative Synonymous Codon Usage (RSCU) to shed new light on the molecular mechanisms involved in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) host specificity. By using the RSCU obtained from nucleotide sequences before the SARS-CoV-2 pandemic, we assessed the possibility of know the hosts capable to be infected by these new emerging species, which was first identified infecting humans during 2019 in Wuhan, China. According to the model trained and validated using sequences available before the pandemic, bats are the most likely the natural host to the SARS-CoV-2 infection, as previously suggested in other studies that searched for the host viral origin.

Analysis of SARS-CoV-2 synonymous codon usage evolution throughout the COVID-19 pandemic

SARS-CoV-2, the seventh coronavirus known to infect humans, can cause severe life-threatening respiratory pathologies. To better understand SARS-CoV-2 evolution, genome-wide analyses have been made, including the general characterization of its codons usage profile. Here we present a bioinformatic analysis of the evolution of SARS-CoV-2 codon usage over time using complete genomes collected since December 2019. Our results show that SARS-CoV-2 codon usage pattern is antagonistic to, and it is getting farther away from that of the human host. Further, a selection of deoptimized codons over time, which was accompanied by a decrease in both the codon adaptation index and the effective number of codons, was observed. All together, these findings suggest that SARS-CoV-2 could be evolving, at least from the perspective of the synonymous codon usage, to become less pathogenic.

Mutation Profiles, Glycosylation Site Distribution and Codon Usage Bias of Human Papillomavirus Type 16

Human papillomavirus type 16 (HPV16) is the most prevalent HPV type causing cervical cancers. Herein, using 1597 full genomes, we systemically investigated the mutation profiles, surface protein glycosylation sites and the codon usage bias (CUB) of HPV16 from different lineages and sublineages. Multiple lineage- or sublineage-conserved mutation sites were identified. Glycosylation analysis showed that HPV16 lineage D contained the highest number of different glycosylation sites from lineage A in both L1 and L2 capsid proteins, which might lead to their antigenic distances between the two lineages. CUB analysis showed that the HPV16 open reading frames (ORFs) preferred codons ending with A/T. The CUB of HPV16 ORFs was mainly affected by natural selection except for E1, E5 and L2. HPV16 only shared some of the preferred codons with humans, which might help reduce competition in translational resources. These findings increase our understanding of the heterogeneity between HPV16 lineages and sublineages, and the adaptation mechanism of HPV in human cells. In summary, this study might facilitate HPV classification and improve vaccine development and application.

Base Composition and Host Adaptation of the SARS-CoV-2: Insight From the Codon Usage Perspective

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been spreading rapidly all over the world and has raised grave concern globally. The present research aims to conduct a robust base compositional analysis of SARS-CoV-2 to reveal adaptive intricacies to the human host. Multivariate statistical analysis revealed a complex interplay of various factors including compositional constraint, natural selection, length of viral coding sequences, hydropathicity, and aromaticity of the viral gene products that are operational to codon usage patterns, with compositional bias being the most crucial determinant. UpG and CpA dinucleotides were found to be highly preferred whereas, CpG dinucleotide was mostly avoided in SARS-CoV-2, a pattern consistent with the human host. Strict avoidance of the CpG dinucleotide might be attributed to a strategy for evading a human immune response. A lower degree of adaptation of SARS-CoV-2 to the human host, compared to Middle East respiratory syndrome (MERS) coronavirus and SARS-CoV, might be indicative of its milder clinical severity and progression contrasted to SARS and MERS. Similar patterns of enhanced adaptation between viral isolates from intermediate and human hosts, contrasted with those isolated from the natural bat reservoir, signifies an indispensable role of the intermediate host in transmission dynamics and spillover events of the virus to human populations. The information regarding avoided codon pairs in SARS-CoV-2, as conferred by the present analysis, promises to be useful for the design of vaccines employing codon pair deoptimization based synthetic attenuated virus engineering.

IHEC_RAAC: a online platform for identifying human enzyme classes via reduced amino acid cluster strategy

Enzymes have been proven to play considerable roles in disease diagnosis and biological functions. The feature extraction that truly reflects the intrinsic properties of protein is the most critical step for the automatic identification of enzymes. Although lots of feature extraction methods have been proposed, some challenges remain. In this study, we developed a predictor called IHEC_RAAC, which has the capability to identify whether a protein is a human enzyme and distinguish the function of the human enzyme. To improve the feature representation ability, protein sequences were encoded by a new feature-vector called 'reduced amino acid cluster'. We calculated 673 amino acid reduction alphabets to determine the optimal feature representative scheme. The tenfold cross-validation test showed that the accuracy of IHEC_RAAC to identify human enzymes was 74.66% and further discriminate the human enzyme classes with an accuracy of 54.78%, which was 2.06% and 8.68% higher than the state-of-the-art predictors, respectively. Additionally, the results from the independent dataset indicated that IHEC_RAAC can effectively predict human enzymes and human enzyme classes to further provide guidance for protein research. A user-friendly web server, IHEC_RAAC, is freely accessible at http://bioinfor.imu.edu.cn/ihecraac .