Multivariate analyses of codon usage of SARS-CoV-2 and other betacoronaviruses

Predicting viral host codon fitness and path shifting through tree-based learning on codon usage biases and genomic characteristics

Viral codon fitness (VCF) of the host and the VCF shifting has seldom been studied under quantitative measurements, although they could be concepts vital to understand pathogen epidemiology. This study demonstrates that the relative synonymous codon usage (RSCU) of virus genomes together with other genomic properties are predictive of virus host codon fitness through tree-based machine learning. Statistical analysis on the RSCU data matrix also revealed that the wobble position of the virus codons is critically important for the host codon fitness distinction. As the trained models can well characterise the host codon fitness of the viruses, the frequency and other details stored at the leaf nodes of these models can be reliably translated into human virus codon fitness score (HVCF score) as a readout of codon fitness of any virus infecting human. Specifically, we evaluated and compared HVCF of virus genome sequences from human sources and others and evaluated HVCF of SARS-CoV-2 genome sequences from NCBI virus database, where we found no obvious shifting trend in host codon fitness towards human-non-infectious. We also developed a bioinformatics tool to simulate codon-based virus fitness shifting using codon compositions of the viruses, and we found that Tylonycteris bat coronavirus HKU4 related viruses may have close relationship with SARS-CoV-2 in terms of human codon fitness. The finding of abundant synonymous mutations in the predicted codon fitness shifting path also provides new insights for evolution research and virus monitoring in environmental surveillance.

Increased preference for lysine over arginine in spike proteins of SARS-CoV-2 BA.2.86 variant and its daughter lineages

The COVID-19 pandemic offered an unprecedented glimpse into the evolution of its causative virus, SARS-CoV-2. It has been estimated that since its outbreak in late 2019, the virus has explored all possible alternatives in terms of missense mutations for all sites of its polypeptide chain. Spike protein of the virus exhibits the largest sequence variation in particular, with many individual mutations impacting target recognition, cellular entry, and endosomal escape of the virus. Moreover, recent studies unveiled a significant increase in the total charge on the spike protein during the evolution of the virus in the initial period of the pandemic. While this trend has recently come to a halt, we perform a sequence-based analysis of the spike protein of 2665 SARS-CoV-2 variants which shows that mutations in ionizable amino acids continue to occur with the newly emerging variants, with notable differences between lineages from different clades. What is more, we show that within mutations of amino acids which can acquire positive charge, the spike protein of SARS-CoV-2 exhibits a prominent preference for lysine residues over arginine residues. This lysine-to-arginine ratio increased at several points during spike protein evolution, most recently with BA.2.86 and its sublineages, including the recently dominant JN.1, KP.3, and XEC variants. The increased ratio is a consequence of mutations in different structural regions of the spike protein and is now among the highest among viral species in the Coronaviridae family. The impact of high lysine-to-arginine ratio in the spike proteins of BA.2.86 and its daughter lineages on viral fitness remains unclear; we discuss several potential mechanisms that could play a role and that can serve as a starting point for further studies.

Cellular and Molecular Mechanisms of Pathogenic and Protective Immune Responses to SARS-CoV-2 and Implications of COVID-19 Vaccines

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has devastated the world with coronavirus disease 2019 (COVID-19), which has imparted a toll of at least 631 million reported cases with 6.57 million reported deaths. In order to handle this pandemic, vaccines against SARS-CoV-2 have been developed and billions of doses of various vaccines have been administered. In the meantime, several antiviral drugs and other treatment modalities have been developed to treat COVID-19 patients. At the end of the day, it seems that anti-SARS-CoV-2 vaccines and newly developed antiviral drugs may be improved based on various new developments. COVID-19 represents a virus-induced, immune-mediated pathological process. The severity of the disease is related to the nature and properties of the host immune responses. In addition, host immunity plays a dominant role in regulating the extent of COVID-19. The present reality regarding the role of anti-SARS-CoV-2 vaccines, persistence of SARS-CoV-2 infection even three years after the initiation of the pandemic, and divergent faces of COVID-19 have initiated several queries among huge populations, policy makers, general physicians, and scientific communities. The present review aims to provide some information regarding the molecular and cellular mechanisms underlying SARS-CoV-2 infection.

Susceptibility to mice and potential evolutionary characteristics of porcine deltacoronavirus

Porcine deltacoronavirus (PDCoV) is a novel coronavirus that causes diarrhea in suckling piglets and has the potential for cross-species transmission, posing a threat to animal and human health. However, the susceptibility profile of different species of mice to PDCoV infection and its evolutionary characteristics are still unclear. In the current study, we found that BALB/c and Kunming mice are susceptible to PDCoV. Our results showed that there were obvious lesions in intestinal and lung tissues from the infected mice. PDCoV RNAs were detected in the lung, kidney, and intestinal tissues from the infected mice of both strains, and there existed wider tissue tropism in the PDCoV-infected BALB/c mice. The RNA and protein levels of aminopeptidase N from mice were relatively high in the kidney and intestinal tissues and obviously increased after PDCoV infection. The viral-specific IgG and neutralizing antibodies against PDCoV were detected in the serum of infected mice. An interesting finding was that two key amino acid mutations, D138H and Q641K, in the S protein were identified in the PDCoV-infected mice. The essential roles of these two mutations for PDCoV-adaptive evolution were confirmed by cryo-electron microscope structure model analysis. The evolutionary characteristics of PDCoV among Deltacoronaviruses (δ-CoVs) were further analyzed. δ-CoVs from multiple mammals are closely related based on the phylogenetic analysis. The codon usage analysis demonstrated that similar codon usage patterns were used by most of the mammalian δ-CoVs at the global codon, synonymous codon, and amino acid usage levels. These results may provide more insights into the evolution, host ranges, and cross-species potential of PDCoV.

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.

Establishment of Genome Based Criteria for Classification of the Family Desulfovibrionaceae and Proposal of Two Novel Genera, Alkalidesulfovibrio gen. nov. and Salidesulfovibrio gen. nov

Bacteria in the Desulfovibrionaceae family, which contribute to S element turnover as sulfate-reducing bacteria (SRB) and disproportionation of partially oxidized sulfoxy anions, have been extensively investigated since the importance of the sulfur cycle emerged. Novel species belonging to this taxon are frequently reported, because they exist in various environments and are easy to culture using established methods. Due to the rapid expansion of the taxon, correction and reclassification have been conducted. The development of high-throughput sequencing facilitated rapid expansion of genome sequence database. Genome-based criteria, based on these databases, proved to be potential classification standard by overcoming the limitations of 16S rRNA-based phylogeny. Although standards methods for taxogenomics are being established, the addition of a novel genus requires extensive calculations with taxa, including many species, such as Desulfovibrionaceae. Thus, the genome-based criteria for classification of Desulfovibrionaceae were established and validated in this study. The average amino-acid identity (AAI) cut-off value, 63.43 ± 0.01, was calculated to be an appropriate criterion for genus delineation of the family Desulfovibrionaceae. By applying the AAI cut-off value, 88 genomes of the Desulfovibrionaceae were divided into 27 genera, which follows the core gene phylogeny results. In this process, two novel genera (Alkalidesulfovibrio and Salidesulfovibrio) and one former invalid genus (“Psychrodesulfovibrio”) were officially proposed. Further, by applying the 95–96% average nucleotide identity (ANI) standard and the 70% digital DNA–DNA hybridization standard values for species delineation of strains that were classified as the same species, five strains have the potential to be newly classified. After verifying that the classification was appropriately performed through relative synonymous codon usage analysis, common characteristics were listed by group. In addition, by detecting metal resistance related genes via in silico analysis, it was confirmed that most strains display metal tolerance.

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.

Unheeded SARS-CoV-2 proteins? A deep look into negative-sense RNA

SARS-CoV-2 is a novel positive-sense single-stranded RNA virus from the Coronaviridae family (genus Betacoronavirus), which has been established as causing the COVID-19 pandemic. The genome of SARS-CoV-2 is one of the largest among known RNA viruses, comprising of at least 26 known protein-coding loci. Studies thus far have outlined the coding capacity of the positive-sense strand of the SARS-CoV-2 genome, which can be used directly for protein translation. However, it has been recently shown that transcribed negative-sense viral RNA intermediates that arise during viral genome replication from positive-sense viruses can also code for proteins. No studies have yet explored the potential for negative-sense SARS-CoV-2 RNA intermediates to contain protein-coding loci. Thus, using sequence and structure-based bioinformatics methodologies, we have investigated the presence and validity of putative negative-sense ORFs (nsORFs) in the SARS-CoV-2 genome. Nine nsORFs were discovered to contain strong eukaryotic translation initiation signals and high codon adaptability scores, and several of the nsORFs were predicted to interact with RNA-binding proteins. Evolutionary conservation analyses indicated that some of the nsORFs are deeply conserved among related coronaviruses. Three-dimensional protein modeling revealed the presence of higher order folding among all putative SARS-CoV-2 nsORFs, and subsequent structural mimicry analyses suggest similarity of the nsORFs to DNA/RNA-binding proteins and proteins involved in immune signaling pathways. Altogether, these results suggest the potential existence of still undescribed SARS-CoV-2 proteins, which may play an important role in the viral lifecycle and COVID-19 pathogenesis.

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.

Of vascular defense, hemostasis, cancer, and platelet biology: an evolutionary perspective

We have established considerable expertise in studying the role of platelets in cancer biology. From this expertise, we were keen to recognize the numerous venous-, arterial-, microvascular-, and macrovascular thrombotic events and immunologic disorders are caused by severe, acute-respiratory-syndrome coronavirus 2 (SARS-CoV-2) infections. With this offering, we explore the evolutionary connections that place platelets at the center of hemostasis, immunity, and adaptive phylogeny. Coevolutionary changes have also occurred in vertebrate viruses and their vertebrate hosts that reflect their respective evolutionary interactions. As mammals adapted from aquatic to terrestrial life and the heavy blood loss associated with placentalization-based live birth, platelets evolved phylogenetically from thrombocytes toward higher megakaryocyte-blebbing-based production rates and the lack of nuclei. With no nuclei and robust RNA synthesis, this adaptation may have influenced viral replication to become less efficient after virus particles are engulfed. Human platelets express numerous receptors that bind viral particles, which developed from archetypal origins to initiate aggregation and exocytic-release of thrombo-, immuno-, angiogenic-, growth-, and repair-stimulatory granule contents. Whether by direct, evolutionary, selective pressure, or not, these responses may help to contain virus spread, attract immune cells for eradication, and stimulate angiogenesis, growth, and wound repair after viral damage. Because mammalian and marsupial platelets became smaller and more plate-like their biophysical properties improved in function, which facilitated distribution near vessel walls in fluid-shear fields. This adaptation increased the probability that platelets could then interact with and engulf shedding virus particles. Platelets also generate circulating microvesicles that increase membrane surface-area encounters and mark viral targets. In order to match virus-production rates, billions of platelets are generated and turned over per day to continually provide active defenses and adaptation to suppress the spectrum of evolving threats like SARS-CoV-2.

Pathogenesis of COVID-19 described through the lens of an undersulfated and degraded epithelial and endothelial glycocalyx

The glycocalyx surrounds every eukaryotic cell and is a complex mesh of proteins and carbohydrates. It consists of proteoglycans with glycosaminoglycan side chains, which are highly sulfated under normal physiological conditions. The degree of sulfation and the position of the sulfate groups mainly determine biological function. The intact highly sulfated glycocalyx of the epithelium may repel severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) through electrostatic forces. However, if the glycocalyx is undersulfated and 3-O-sulfotransferase 3B (3OST-3B) is overexpressed, as is the case during chronic inflammatory conditions, SARS-CoV-2 entry may be facilitated by the glycocalyx. The degree of sulfation and position of the sulfate groups will also affect functions such as immune modulation, the inflammatory response, vascular permeability and tone, coagulation, mediation of sheer stress, and protection against oxidative stress. The rate-limiting factor to sulfation is the availability of inorganic sulfate. Various genetic and epigenetic factors will affect sulfur metabolism and inorganic sulfate availability, such as various dietary factors, and exposure to drugs, environmental toxins, and biotoxins, which will deplete inorganic sulfate. The role that undersulfation plays in the various comorbid conditions that predispose to coronavirus disease 2019 (COVID-19), is also considered. The undersulfated glycocalyx may not only increase susceptibility to SARS-CoV-2 infection, but would also result in a hyperinflammatory response, vascular permeability, and shedding of the glycocalyx components, giving rise to a procoagulant and antifibrinolytic state and eventual multiple organ failure. These symptoms relate to a diagnosis of systemic septic shock seen in almost all COVID-19 deaths. The focus of prevention and treatment protocols proposed is the preservation of epithelial and endothelial glycocalyx integrity.

Codon usage, phylogeny and binding energy estimation predict the evolution of SARS-CoV-2

In the frames of a One Health strategy, i.e. a strategy should be able to predict susceptibility to infection in both humans and animals, developing a SARS-CoV-2 mutation tracking system is a goal. We observed that the phylogenetic proximity of vertebrate ACE2 receptors does not affect the binding energy for the viral spike protein. However, all viral variants seem to bind ACE2 better in many animals than in humans. Moreover, two observations highlight that the evolution of the virus started at the beginning of 2020 and culminated with the appearance of the variants. First, codon usage analysis shows that the B.1.1.7 (alpha), B.1.351 (beta) and B.1.617.2 (delta) variants, similar in the use of codons, are also similar to a virus sampled in January 2020. Second, the host-specific D614G mutation becomes prevalent starting from March 2020. Overall, we show that SARS-CoV-2 undergoes a process of molecular evolution that begins with the optimization of codons followed by the functional optimization of the spike protein.

Causes and Consequences of Purifying Selection on SARS-CoV-2

Owing to a lag between a deleterious mutation's appearance and its selective removal, gold-standard methods for mutation rate estimation assume no meaningful loss of mutations between parents and offspring. Indeed, from analysis of closely related lineages, in SARS-CoV-2, the Ka/Ks ratio was previously estimated as 1.008, suggesting no within-host selection. By contrast, we find a higher number of observed SNPs at 4-fold degenerate sites than elsewhere and, allowing for the virus's complex mutational and compositional biases, estimate that the mutation rate is at least 49-67% higher than would be estimated based on the rate of appearance of variants in sampled genomes. Given the high Ka/Ks one might assume that the majority of such intrahost selection is the purging of nonsense mutations. However, we estimate that selection against nonsense mutations accounts for only ∼10% of all the "missing" mutations. Instead, classical protein-level selective filters (against chemically disparate amino acids and those predicted to disrupt protein functionality) account for many missing mutations. It is less obvious why for an intracellular parasite, amino acid cost parameters, notably amino acid decay rate, is also significant. Perhaps most surprisingly, we also find evidence for real-time selection against synonymous mutations that move codon usage away from that of humans. We conclude that there is common intrahost selection on SARS-CoV-2 that acts on nonsense, missense, and possibly synonymous mutations. This has implications for methods of mutation rate estimation, for determining times to common ancestry and the potential for intrahost evolution including vaccine escape.

Variability in Codon Usage in Coronaviruses Is Mainly Driven by Mutational Bias and Selective Constraints on CpG Dinucleotide

The Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the third human-emerged virus of the 21st century from the Coronaviridae family, causing the ongoing coronavirus disease 2019 (COVID-19) pandemic. Due to the high zoonotic potential of coronaviruses, it is critical to unravel their evolutionary history of host species breadth, host-switch potential, adaptation and emergence, to identify viruses posing a pandemic risk in humans. We present here a comprehensive analysis of the composition and codon usage bias of the 82 Orthocoronavirinae members, infecting 47 different avian and mammalian hosts. Our results clearly establish that synonymous codon usage varies widely among viruses, is only weakly dependent on their primary host, and is dominated by mutational bias towards AU-enrichment and by CpG avoidance. Indeed, variation in GC3 explains around 34%, while variation in CpG frequency explains around 14% of total variation in codon usage bias. Further insight on the mutational equilibrium within Orthocoronavirinae revealed that most coronavirus genomes are close to their neutral equilibrium, the exception being the three recently infecting human coronaviruses, which lie further away from the mutational equilibrium than their endemic human coronavirus counterparts. Finally, our results suggest that, while replicating in humans, SARS-CoV-2 is slowly becoming AU-richer, likely until attaining a new mutational equilibrium.

The Evolution of Severe Acute Respiratory Syndrome Coronavirus-2 during Pandemic and Adaptation to the Host

Severe Acute Respiratory Syndrome Coronavirus-2 is a zoonotic virus with a possible origin in bats and potential transmission to humans through an intermediate host. When zoonotic viruses jump to a new host, they undergo both mutational and natural selective pressures that result in non-synonymous and synonymous adaptive changes, necessary for efficient replication and rapid spread of diseases in new host species. The nucleotide composition and codon usage pattern of SARS-CoV-2 indicate the presence of a highly conserved, gene-specific codon usage bias. The codon usage pattern of SARS-CoV-2 is mostly antagonistic to human and bat codon usage. SARS-CoV-2 codon usage bias is mainly shaped by the natural selection, while mutational pressure plays a minor role. The time-series analysis of SARS-CoV-2 genome indicates that the virus is slowly evolving. Virus isolates from later stages of the outbreak have more biased codon usage and nucleotide composition than virus isolates from early stages of the outbreak.

Genome-Wide Analysis of Codon Usage Patterns of SARS-CoV-2 Virus Reveals Global Heterogeneity of COVID-19

The ongoing outbreak of coronavirus disease COVID-19 is significantly implicated by global heterogeneity in the genome organization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The causative agents of global heterogeneity in the whole genome of SARS-CoV-2 are not well characterized due to the lack of comparative study of a large enough sample size from around the globe to reduce the standard deviation to the acceptable margin of error. To better understand the SARS-CoV-2 genome architecture, we have performed a comprehensive analysis of codon usage bias of sixty (60) strains to get a snapshot of its global heterogeneity. Our study shows a relatively low codon usage bias in the SARS-CoV-2 viral genome globally, with nearly all the over-preferred codons' A.U. ended. We concluded that the SARS-CoV-2 genome is primarily shaped by mutation pressure; however, marginal selection pressure cannot be overlooked. Within the A/U rich virus genomes of SARS-CoV-2, the standard deviation in G.C. (42.91% ± 5.84%) and the GC3 value (30.14% ± 6.93%) points towards global heterogeneity of the virus. Several SARS-CoV-2 viral strains were originated from different viral lineages at the exact geographic location also supports this fact. Taking all together, these findings suggest that the general root ancestry of the global genomes are different with different genome's level adaptation to host. This research may provide new insights into the codon patterns, host adaptation, and global heterogeneity of SARS-CoV-2.

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.

Predicting the animal hosts of coronaviruses from compositional biases of spike protein and whole genome sequences through machine learning

The COVID-19 pandemic has demonstrated the serious potential for novel zoonotic coronaviruses to emerge and cause major outbreaks. The immediate animal origin of the causative virus, SARS-CoV-2, remains unknown, a notoriously challenging task for emerging disease investigations. Coevolution with hosts leads to specific evolutionary signatures within viral genomes that can inform likely animal origins. We obtained a set of 650 spike protein and 511 whole genome nucleotide sequences from 222 and 185 viruses belonging to the family Coronaviridae, respectively. We then trained random forest models independently on genome composition biases of spike protein and whole genome sequences, including dinucleotide and codon usage biases in order to predict animal host (of nine possible categories, including human). In hold-one-out cross-validation, predictive accuracy on unseen coronaviruses consistently reached ~73%, indicating evolutionary signal in spike proteins to be just as informative as whole genome sequences. However, different composition biases were informative in each case. Applying optimised random forest models to classify human sequences of MERS-CoV and SARS-CoV revealed evolutionary signatures consistent with their recognised intermediate hosts (camelids, carnivores), while human sequences of SARS-CoV-2 were predicted as having bat hosts (suborder Yinpterochiroptera), supporting bats as the suspected origins of the current pandemic. In addition to phylogeny, variation in genome composition can act as an informative approach to predict emerging virus traits as soon as sequences are available. More widely, this work demonstrates the potential in combining genetic resources with machine learning algorithms to address long-standing challenges in emerging infectious diseases.

COVID-19: A challenge for electrochemical biosensors

Coronavirus disease (COVID-19) caused by SARS-CoV-2 has spread since the end of 2019 and has resulted in a pandemic with unprecedented socioeconomic consequences. This situation has created enormous demand for the improvement of current diagnostic methods and the development of new diagnostic methods for fast, low-cost and user-friendly confirmation of SARS-CoV-2 infection. This critical review focuses on viral electrochemical biosensors that are promising for the development of rapid medical COVID-19 diagnostic tools. The molecular biological properties of SARS-CoV-2 as well as currently known biochemical attributes of infection necessary for biosensor development are outlined. The advantages and drawbacks of conventional diagnostic methods, such as quantitative reverse-transcription polymerase chain reaction (qRT-PCR), are critically discussed. Electrochemical biosensors focusing on viral nucleic acid and whole viral particle detection are highlighted and discussed in detail. Finally, future perspectives on viral electrochemical biosensor development are briefly mentioned.

Global Geographic and Temporal Analysis of SARS-CoV-2 Haplotypes Normalized by COVID-19 Cases During the Pandemic

Since the identification of SARS-CoV-2, a large number of genomes have been sequenced with unprecedented speed around the world. This marks a unique opportunity to analyze virus spreading and evolution in a worldwide context. Currently, there is not a useful haplotype description to help to track important and globally scattered mutations. Also, differences in the number of sequenced genomes between countries and/or months make it difficult to identify the emergence of haplotypes in regions where few genomes are sequenced but a large number of cases are reported. We propose an approach based on the normalization by COVID-19 cases of relative frequencies of mutations using all the available data to identify major haplotypes. Furthermore, we can use a similar normalization approach to tracking the temporal and geographic distribution of haplotypes in the world. Using 171,461 genomes, we identify five major haplotypes or operational taxonomic units (OTUs) based on nine high-frequency mutations. OTU_3 characterized by mutations R203K and G204R is currently the most frequent haplotype circulating in four of the six continents analyzed (South America, North America, Europe, Asia, Africa, and Oceania). On the other hand, during almost all months analyzed, OTU_5 characterized by the mutation T85I in nsp2 is the most frequent in North America. Recently (since September), OTU_2 has been established as the most frequent in Europe. OTU_1, the ancestor haplotype, is near to extinction showed by its low number of isolations since May. Also, we analyzed whether age, gender, or patient status is more related to a specific OTU. We did not find OTU's preference for any age group, gender, or patient status. Finally, we discuss structural and functional hypotheses in the most frequently identified mutations, none of those mutations show a clear effect on the transmissibility or pathogenicity.

Tracing the origins of SARS-COV-2 in coronavirus phylogenies: a review

SARS-CoV-2 is a new human coronavirus (CoV), which emerged in China in late 2019 and is responsible for the global COVID-19 pandemic that caused more than 97 million infections and 2 million deaths in 12 months. Understanding the origin of this virus is an important issue, and it is necessary to determine the mechanisms of viral dissemination in order to contain future epidemics. Based on phylogenetic inferences, sequence analysis and structure-function relationships of coronavirus proteins, informed by the knowledge currently available on the virus, we discuss the different scenarios on the origin-natural or synthetic-of the virus. The data currently available are not sufficient to firmly assert whether SARS-CoV2 results from a zoonotic emergence or from an accidental escape of a laboratory strain. This question needs to be solved because it has important consequences on the risk/benefit balance of our interactions with ecosystems, on intensive breeding of wild and domestic animals, on some laboratory practices and on scientific policy and biosafety regulations. Regardless of COVID-19 origin, studying the evolution of the molecular mechanisms involved in the emergence of pandemic viruses is essential to develop therapeutic and vaccine strategies and to prevent future zoonoses. This article is a translation and update of a French article published in Médecine/Sciences, August/September 2020 (10.1051/medsci/2020123).

Supplementary Information

The online version of this article (10.1007/s10311-020-01151-1) contains supplementary material, which is available to authorized users.

Clinical characteristics of outpatients and inpatients with COVID-19 in Bushehr: a report from the south of Iran

Aim: To investigate clinical, laboratory and imaging features of COVID-19 patients in Bushehr, a southern province of Iran. Materials & methods: A total of 148 COVID-19 patients were enrolled. The patients were categorized into four groups including inpatients, outpatients, elderly and nonelderly. Clinical, laboratory and computed tomography characteristics were analyzed and compared. Results: Levels of erythrocyte sedimentation rate, CRP, lactate dehydrogenase and aspartate aminotransferas among inpatients were higher than outpatients. There were significant differences in the levels of creatinine and blood urine nitrogen between elderly and nonelderly patients. The incidence of ground-glass opacities in inpatients was significantly higher than in outpatients. Conclusion: COVID-19 is associated with more severe renal failure in elderly patients. Elderly patients with underlying conditions are at increased risk of severe progression of COVID-19.

Computational Analysis of SARS-CoV-2 and SARS-Like Coronavirus Diversity in Human, Bat and Pangolin Populations

In 2019, a novel coronavirus, SARS-CoV-2/nCoV-19, emerged in Wuhan, China, and has been responsible for the current COVID-19 pandemic. The evolutionary origins of the virus remain elusive and understanding its complex mutational signatures could guide vaccine design and development. As part of the international "CoronaHack" in April 2020, we employed a collection of contemporary methodologies to compare the genomic sequences of coronaviruses isolated from human (SARS-CoV-2; n = 163), bat (bat-CoV; n = 215) and pangolin (pangolin-CoV; n = 7) available in public repositories. We have also noted the pangolin-CoV isolate MP789 to bare stronger resemblance to SARS-CoV-2 than other pangolin-CoV. Following de novo gene annotation prediction, analyses of gene-gene similarity network, codon usage bias and variant discovery were undertaken. Strong host-associated divergences were noted in ORF3a, ORF6, ORF7a, ORF8 and S, and in codon usage bias profiles. Last, we have characterised several high impact variants (in-frame insertion/deletion or stop gain) in bat-CoV and pangolin-CoV populations, some of which are found in the same amino acid position and may be highlighting loci of potential functional relevance.

SARS-CoV-2 Is Restricted by Zinc Finger Antiviral Protein despite Preadaptation to the Low-CpG Environment in Humans

Recent evidence shows that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is sensitive to interferons (IFNs). However, the most effective types of IFNs and the underlying antiviral effectors remain to be defined. Here, we show that zinc finger antiviral protein (ZAP), which preferentially targets CpG dinucleotides in viral RNA sequences, restricts SARS-CoV-2. We further demonstrate that ZAP and its cofactors KHNYN and TRIM25 are expressed in human lung cells. Type I, II, and III IFNs all strongly inhibited SARS-CoV-2 and further induced ZAP expression. Comprehensive sequence analyses revealed that SARS-CoV-2 and its closest relatives from horseshoe bats showed the strongest CpG suppression among all known human and bat coronaviruses, respectively. Nevertheless, endogenous ZAP expression restricted SARS-CoV-2 replication in human lung cells, particularly upon treatment with IFN-α or IFN-γ. Both the long and the short isoforms of human ZAP reduced SARS-CoV-2 RNA expression levels, but the former did so with greater efficiency. Finally, we show that the ability to restrict SARS-CoV-2 is conserved in ZAP orthologues of the reservoir bat and potential intermediate pangolin hosts of human coronaviruses. Altogether, our results show that ZAP is an important effector of the innate response against SARS-CoV-2, although this pandemic pathogen emerged from zoonosis of a coronavirus that was preadapted to the low-CpG environment in humans.IMPORTANCE Although interferons inhibit SARS-CoV-2 and have been evaluated for treatment of coronavirus disease 2019 (COVID-19), the most effective types and antiviral effectors remain to be defined. Here, we show that IFN-γ is particularly potent in restricting SARS-CoV-2 and in inducing expression of the antiviral factor ZAP in human lung cells. Knockdown experiments revealed that endogenous ZAP significantly restricts SARS-CoV-2. We further show that CpG dinucleotides which are specifically targeted by ZAP are strongly suppressed in the SARS-CoV-2 genome and that the two closest horseshoe bat relatives of SARS-CoV-2 show the lowest genomic CpG content of all coronavirus sequences available from this reservoir host. Nonetheless, both the short and long isoforms of human ZAP reduced SARS-CoV-2 RNA levels, and this activity was conserved in horseshoe bat and pangolin ZAP orthologues. Our findings indicating that type II interferon is particularly efficient against SARS-CoV-2 and that ZAP restricts this pandemic viral pathogen might promote the development of effective immune therapies against COVID-19.

Characterization of codon usage pattern in SARS-CoV-2

The outbreak of coronavirus disease 2019 (COVID-19) due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has posed significant threats to international health. The genetic traits as well as evolutionary processes in this novel coronavirus are not fully characterized, and their roles in viral pathogenesis are yet largely unknown. To get a better picture of the codon architecture of this newly emerging coronavirus, in this study we perform bioinformatic analysis, based on publicly available nucleotide sequences of SARS-CoV-2 along with those of other members of human coronaviruses as well as non-human coronaviruses in different hosts, to take a snapshot of the genome-wide codon usage pattern of SARS-CoV-2 and uncover that all over-represented codons end with A/U and this newly emerging coronavirus has a relatively low codon usage bias, which is shaped by both mutation pressure and natural selection. Additionally, there is slight variation in the codon usage pattern among the SARS-CoV-2 isolates from different geo-locations. Furthermore, the overall codon usage pattern of SARS-CoV-2 is generally similar to that of its phylogenetic relatives among non-human betacoronaviruses such as RaTG13. Taken together, we comprehensively analyze the characteristics of codon usage pattern in SARS-CoV-2 via bioinformatic approaches. The information from this research may not only be helpful to get new insights into the evolution of SARS-CoV-2, but also have potential value for developing coronavirus vaccines.

An Extensive Meta-Metagenomic Search Identifies SARS-CoV-2-Homologous Sequences in Pangolin Lung Viromes

In numerous instances, tracking the biological significance of a nucleic acid sequence can be augmented through the identification of environmental niches in which the sequence of interest is present. Many metagenomic data sets are now available, with deep sequencing of samples from diverse biological niches. While any individual metagenomic data set can be readily queried using web-based tools, meta-searches through all such data sets are less accessible. In this brief communication, we demonstrate such a meta-metagenomic approach, examining close matches to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in all high-throughput sequencing data sets in the NCBI Sequence Read Archive accessible with the "virome" keyword. In addition to the homology to bat coronaviruses observed in descriptions of the SARS-CoV-2 sequence (F. Wu, S. Zhao, B. Yu, Y. M. Chen, et al., Nature 579:265-269, 2020, https://doi.org/10.1038/s41586-020-2008-3; P. Zhou, X. L. Yang, X. G. Wang, B. Hu, et al., Nature 579:270-273, 2020, https://doi.org/10.1038/s41586-020-2012-7), we note a strong homology to numerous sequence reads in metavirome data sets generated from the lungs of deceased pangolins reported by Liu et al. (P. Liu, W. Chen, and J. P. Chen, Viruses 11:979, 2019, https://doi.org/10.3390/v11110979). While analysis of these reads indicates the presence of a similar viral sequence in pangolin lung, the similarity is not sufficient to either confirm or rule out a role for pangolins as an intermediate host in the recent emergence of SARS-CoV-2. In addition to the implications for SARS-CoV-2 emergence, this study illustrates the utility and limitations of meta-metagenomic search tools in effective and rapid characterization of potentially significant nucleic acid sequences.IMPORTANCE Meta-metagenomic searches allow for high-speed, low-cost identification of potentially significant biological niches for sequences of interest.

The Rapid Assessment and Early Warning Models for COVID-19

Human beings have experienced a serious public health event as the new pneumonia (COVID-19), caused by the severe acute respiratory syndrome coronavirus has killed more than 3000 people in China, most of them elderly or people with underlying chronic diseases or immunosuppressed states. Rapid assessment and early warning are essential for outbreak analysis in response to serious public health events. This paper reviews the current model analysis methods and conclusions from both micro and macro perspectives. The establishment of a comprehensive assessment model, and the use of model analysis prediction, is very efficient for the early warning of infectious diseases. This would significantly improve global surveillance capacity, particularly in developing regions, and improve basic training in infectious diseases and molecular epidemiology.