Recovery of Deleted Deep Sequencing Data Sheds More Light on the Early Wuhan SARS-CoV-2 Epidemic

What we can and cannot learn from SARS-CoV-2 and animals in metagenomic samples from the Huanan market

While the exact context of the emergence of SARS-CoV-2 remains uncertain, data accumulated since 2020 have provided an increasingly more precise picture of Wuhan's Huanan Seafood Wholesale Market, to which the earliest clusters of human cases of Covid-19 were linked. After the market closed on January 1st 2020, teams from the Chinese Center for Disease Control and Prevention collected environmental samples, and sequenced them. Metagenomic sequencing data from these samples were shared in early 2023. These data confirmed that non-human animals susceptible to SARS-CoV-2 were present in the market before it closed, but also that these animals were located in the side of the market with most human cases, and in a corner with comparatively more SARS-CoV-2-positive environmental samples. The environmental samples were however collected after abundant human-to-human transmission had taken place in the market, precluding any identification of a non-human animal host. Jesse Bloom recently investigated associations between SARS-CoV-2 and non-human animals, concluding that the data failed to indicate whether non-human animals were infected by SARS-CoV-2, despite this being an already acknowledged limitation of the data. Here I explain why a correlation analysis could not confidently conclude which hosts(s) may have shed SARS-CoV-2 in the market, and I rebut the suggestion that such analyses had been encouraged. I show that Bloom's investigation ignores the temporal and spatial structure of the data, which led to incorrect interpretations. Finally, I show that criteria put forward by Bloom to identify the host(s) that shed environmental SARS-CoV-2 would also exclude humans. Progress on the topic of SARS-CoV-2's origin requires a clear distinction between scientific studies and news articles (mis)interpreting them.

The Question of the Origins of COVID-19 and the Ends of Science

Intense public interest in scientific claims about COVID-19, concerning its origins, modes of spread, evolution, and preventive and therapeutic strategies, has focused attention on the values to which scientists are assumed to be committed and the relationship between science and other public discourses. A much discussed claim, which has stimulated several inquiries and generated far-reaching political and economic consequences, has been that SARS-CoV-2 was deliberately engineered at the Wuhan Institute of Virology and then, either inadvertently or otherwise, released to the public by a laboratory worker. This has been pursued despite a clear refutation, through comprehensive genomic analysis, of the hypothesis that the virus was deliberately engineered and the failure of detailed investigations to identify any evidence in support of a laboratory leak. At the same time a substantial, established body of knowledge about the many factors underlying the emergence of novel zoonotic diseases has been largely ignored-including climate change and other mechanisms of environmental destruction, tourism, patterns of trade, and cultural influences. The existence and conduct of these debates have raised questions about the vulnerability of science to manipulation for political purposes. Scientific discourses are vulnerable because: (i) claims can be made with no more than probabilistic force; (ii) alleged "facts" are always subject to interpretation, which depends on social, ethical, and epistemological assumptions; and (iii) science and scientists are not inherently committed to any single set of values and historically have served diverse, and sometimes perverse, social and political interests. In the face of this complexity, the COVID-19 experience highlights the need for processes of ethical scrutiny of the scientific enterprise and its strategic deployment. To ensure reliability of truth claims and protection from corrupting influences robust ethical discourses are required that are independent of, and at times even contrary to, those of science itself.

Genetic tracing of market wildlife and viruses at the epicenter of the COVID-19 pandemic

Zoonotic spillovers of viruses have occurred through the animal trade worldwide. The start of the COVID-19 pandemic was traced epidemiologically to the Huanan Wholesale Seafood Market, the site with the most reported wildlife vendors in the city of Wuhan, China. Here, we analyze publicly available qPCR and sequencing data from environmental samples collected in the Huanan market in early 2020. We demonstrate that the SARS-CoV-2 genetic diversity linked to this market is consistent with market emergence, and find increased SARS-CoV-2 positivity near and within a particular wildlife stall. We identify wildlife DNA in all SARS-CoV-2 positive samples from this stall. This includes species such as civets, bamboo rats, porcupines, hedgehogs, and one species, raccoon dogs, known to be capable of SARS-CoV-2 transmission. We also detect other animal viruses that infect raccoon dogs, civets, and bamboo rats. Combining metagenomic and phylogenetic approaches, we recover genotypes of market animals and compare them to those from other markets. This analysis provides the genetic basis for a short list of potential intermediate hosts of SARS-CoV-2 to prioritize for retrospective serological testing and viral sampling.

Genomic Analysis of the Suspicious SARS-CoV-2 Sequences in the Public Sequencing Database

SARS-CoV-2 has infected more than 600 million people. However, the origin of the virus is still unclear; knowing where the virus came from could help us prevent future zoonotic epidemics. Sequencing data, particularly metagenomic data, can profile the genomes of all species in the sample, including those not recognized at the time, thus allowing for the identification of the progenitor of SARS-CoV-2 in samples collected before the pandemic. We analyzed the data from 5,196 SARS-CoV-2-positive sequencing runs in the NCBI's SRA database with collection dates prior to 2020 or unknown. We found that the mutation patterns obtained from these suspicious SARS-CoV-2 reads did not match the genome characteristics of an unknown progenitor of the virus, suggesting that they may derive from circulating SARS-CoV-2 variants or other coronaviruses. Despite a negative result for tracking the progenitor of SARS-CoV-2, the methods developed in the study could assist in pinpointing the origin of various pathogens in the future. IMPORTANCE Sequences that are homologous to the SARS-CoV-2 genome were found in numerous sequencing runs that were not associated with the SARS-CoV-2 studies in the public database. It is unclear whether they are derived from the possible progenitor of SARS-CoV-2 or contamination of more recent SARS-CoV-2 variants circulated in the population due to the lack of information on the collection, library preparation, and sequencing processes. We have developed a computational framework to infer the evolutionary relationship between sequences based on the comparison of mutations, which enabled us to rule out the possibility that these suspicious sequences originate from unknown progenitors of SARS-CoV-2.

Coordinated evolution at amino acid sites of SARS-CoV-2 spike

SARS-CoV-2 has adapted in a stepwise manner, with multiple beneficial mutations accumulating in a rapid succession at origins of VOCs, and the reasons for this are unclear. Here, we searched for coordinated evolution of amino acid sites in the spike protein of SARS-CoV-2. Specifically, we searched for concordantly evolving site pairs (CSPs) for which changes at one site were rapidly followed by changes at the other site in the same lineage. We detected 46 sites which formed 45 CSP. Sites in CSP were closer to each other in the protein structure than random pairs, indicating that concordant evolution has a functional basis. Notably, site pairs carrying lineage defining mutations of the four VOCs that circulated before May 2021 are enriched in CSPs. For the Alpha VOC, the enrichment is detected even if Alpha sequences are removed from analysis, indicating that VOC origin could have been facilitated by positive epistasis. Additionally, we detected nine discordantly evolving pairs of sites where mutations at one site unexpectedly rarely occurred on the background of a specific allele at another site, for example on the background of wild-type D at site 614 (four pairs) or derived Y at site 501 (three pairs). Our findings hint that positive epistasis between accumulating mutations could have delayed the assembly of advantageous combinations of mutations comprising at least some of the VOCs.

Evolutionary Challenges to Humanity Caused by Uncontrolled Carbon Emissions: The Stockholm Paradigm

This review paper discusses the Stockholm Paradigm (SP) as a theoretical framework and practical computational instrument for studying and assessing the risk of emerging infectious diseases (EIDs) as a result of climate change. The SP resolves the long-standing parasite paradox and explains how carbon emissions in the atmosphere increase parasites' generalization and intensify host switches from animals to humans. The SP argues that the growing rate of novel EID occurrence caused by mutated zoonotic pathogens is related to the following factors brought together as a unified issue of humanity: (a) carbon emissions and consequent climate change; (b) resettlement/migration of people with hyper-urbanization; (c) overpopulation; and (d) human-induced distortion of the biosphere. The SP demonstrates that, in an evolutionary way, humans now play a role migratory birds once played in spreading parasite pathogens between the three Earth megabiotopes (northern coniferous forest belt; tropical/equatorial rainforest areas; and hot/cold deserts), i.e., the role of "super-spreaders" of parasitic viruses, bacteria, fungi and protozoa. This makes humans extremely vulnerable to the EID threat. The SP sees the +1.0-+1.2 °C limit as the optimal target for the slow, yet feasible curbing of the EID hazard to public health (150-200 years). Reaching merely the +2.0 °C level will obviously be an EID catastrophe, as it may cause two or three pandemics each year. We think it useful and advisable to include the SP-based research in the scientific repository of the Intergovernmental Panel on Climate Change, since EID appearance and spread are indirect but extremely dangerous consequences of climate change.

Molecular evidence for SARS-CoV-2 in samples collected from patients with morbilliform eruptions since late 2019 in Lombardy, northern Italy

As a reference laboratory for measles and rubella surveillance in Lombardy, we evaluated the association between SARS-CoV-2 infection and measles-like syndromes, providing preliminary evidence for undetected early circulation of SARS-CoV-2. Overall, 435 samples from 156 cases were investigated. RNA from oropharyngeal swabs (N = 148) and urine (N = 141) was screened with four hemi-nested PCRs and molecular evidence for SARS-CoV-2 infection was found in 13 subjects. Two of the positive patients were from the pandemic period (2/12, 16.7%, March 2020-March 2021) and 11 were from the pre-pandemic period (11/44, 25%, August 2019-February 2020). Sera (N = 146) were tested for anti-SARS-CoV-2 IgG, IgM, and IgA antibodies. Five of the RNA-positive individuals also had detectable anti-SARS-CoV-2 antibodies. No strong evidence of infection was found in samples collected between August 2018 and July 2019 from 100 patients. The earliest sample with evidence of SARS-CoV-2 RNA was from September 12, 2019, and the positive patient was also positive for anti-SARS-CoV-2 antibodies (IgG and IgM). Mutations typical of B.1 strains previously reported to have emerged in January 2020 (C3037T, C14408T, and A23403G), were identified in samples collected as early as October 2019 in Lombardy. One of these mutations (C14408T) was also identified among sequences downloaded from public databases that were obtained by others from samples collected in Brazil in November 2019. We conclude that a SARS-CoV-2 progenitor capable of producing a measles-like syndrome may have emerged in late June-late July 2019 and that viruses with mutations characterizing B.1 strain may have been spreading globally before the first Wuhan outbreak. Our findings should be complemented by high-throughput sequencing to obtain additional sequence information. We highlight the importance of retrospective surveillance studies in understanding the early dynamics of COVID-19 spread and we encourage other groups to perform retrospective investigations to seek confirmatory proofs of early SARS-CoV-2 circulation.

Tracing the origin of Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2): A systematic review and narrative synthesis

The aim of the study was to trace and understand the origin of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) through various available literatures and accessible databases. Although the world enters the third year of the coronavirus disease 2019 pandemic, health and socioeconomic impacts continue to mount, the origin and mechanisms of spill-over of the SARS-CoV-2 into humans remain elusive. Therefore, a systematic review of the literature was performed that showcased the integrated information obtained through manual searches, digital databases (PubMed, CINAHL, and MEDLINE) searches, and searches from legitimate publications (1966-2022), followed by meta-analysis. Our systematic analysis data proposed three postulated hypotheses concerning the origin of the SARS-CoV-2, which include zoonotic origin (Z), laboratory origin (L), and obscure origin (O). Despite the fact that the zoonotic origin for SARS-CoV-2 has not been conclusively identified to date, our data suggest a zoonotic origin, in contrast to some alternative concepts, including the probability of a laboratory incident or leak. Our data exhibit that zoonotic origin (Z) has higher evidence-based support as compared to laboratory origin (L). Importantly, based on all the studies included, we generated the forest plot with 95% confidence intervals (CIs) of the risk ratio estimates. Our meta-analysis further supports the zoonotic origin of SARS/SARS-CoV-2 in the included studies.

The molecular epidemiology of multiple zoonotic origins of SARS-CoV-2

Understanding the circumstances that lead to pandemics is important for their prevention. We analyzed the genomic diversity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) early in the coronavirus disease 2019 (COVID-19) pandemic. We show that SARS-CoV-2 genomic diversity before February 2020 likely comprised only two distinct viral lineages, denoted "A" and "B." Phylodynamic rooting methods, coupled with epidemic simulations, reveal that these lineages were the result of at least two separate cross-species transmission events into humans. The first zoonotic transmission likely involved lineage B viruses around 18 November 2019 (23 October to 8 December), and the separate introduction of lineage A likely occurred within weeks of this event. These findings indicate that it is unlikely that SARS-CoV-2 circulated widely in humans before November 2019 and define the narrow window between when SARS-CoV-2 first jumped into humans and when the first cases of COVID-19 were reported. As with other coronaviruses, SARS-CoV-2 emergence likely resulted from multiple zoonotic events.

TopHap: rapid inference of key phylogenetic structures from common haplotypes in large genome collections with limited diversity

MOTIVATION

Building reliable phylogenies from very large collections of sequences with a limited number of phylogenetically informative sites is challenging because sequencing errors and recurrent/backward mutations interfere with the phylogenetic signal, confounding true evolutionary relationships. Massive global efforts of sequencing genomes and reconstructing the phylogeny of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains exemplify these difficulties since there are only hundreds of phylogenetically informative sites but millions of genomes. For such datasets, we set out to develop a method for building the phylogenetic tree of genomic haplotypes consisting of positions harboring common variants to improve the signal-to-noise ratio for more accurate and fast phylogenetic inference of resolvable phylogenetic features.

RESULTS

We present the TopHap approach that determines spatiotemporally common haplotypes of common variants and builds their phylogeny at a fraction of the computational time of traditional methods. We develop a bootstrap strategy that resamples genomes spatiotemporally to assess topological robustness. The application of TopHap to build a phylogeny of 68 057 SARS-CoV-2 genomes (68KG) from the first year of the pandemic produced an evolutionary tree of major SARS-CoV-2 haplotypes. This phylogeny is concordant with the mutation tree inferred using the co-occurrence pattern of mutations and recovers key phylogenetic relationships from more traditional analyses. We also evaluated alternative roots of the SARS-CoV-2 phylogeny and found that the earliest sampled genomes in 2019 likely evolved by four mutations of the most recent common ancestor of all SARS-CoV-2 genomes. An application of TopHap to more than 1 million SARS-CoV-2 genomes reconstructed the most comprehensive evolutionary relationships of major variants, which confirmed the 68KG phylogeny and provided evolutionary origins of major and recent variants of concern.

AVAILABILITY AND IMPLEMENTATION

TopHap is available at https://github.com/SayakaMiura/TopHap.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Waiting for the truth: is reluctance in accepting an early origin hypothesis for SARS-CoV-2 delaying our understanding of viral emergence?

Two years after the start of the COVID-19 pandemic, key questions about the emergence of its aetiological agent (SARS-CoV-2) remain a matter of considerable debate. Identifying when SARS-CoV-2 began spreading among people is one of those questions. Although the current canonically accepted timeline hypothesises viral emergence in Wuhan, China, in November or December 2019, a growing body of diverse studies provides evidence that the virus may have been spreading worldwide weeks, or even months, prior to that time. However, the hypothesis of earlier SARS-CoV-2 circulation is often dismissed with prejudicial scepticism and experimental studies pointing to early origins are frequently and speculatively attributed to false-positive tests. In this paper, we critically review current evidence that SARS-CoV-2 had been circulating prior to December of 2019, and emphasise how, despite some scientific limitations, this hypothesis should no longer be ignored and considered sufficient to warrant further larger-scale studies to determine its veracity.

Preprint servers and patent prior art: Preprints can jeopardize the patentability of an invention: Preprints can jeopardize the patentability of an invention

Posting papers on preprint servers creates patent 'prior art' and is likely to affect the patentability of any underlying invention.

TopHap: Rapid inference of key phylogenetic structures from common haplotypes in large genome collections with limited diversity

MOTIVATION

Building reliable phylogenies from very large collections of sequences with a limited number of phylogenetically informative sites is challenging because sequencing errors and recurrent/backward mutations interfere with the phylogenetic signal, confounding true evolutionary relationships. Massive global efforts of sequencing genomes and reconstructing the phylogeny of SARS-CoV-2 strains exemplify these difficulties since there are only hundreds of phylogenetically informative sites and millions of genomes. For such datasets, we set out to develop a method for building the phylogenetic tree of genomic haplotypes consisting of positions harboring common variants to improve the signal-to-noise ratio for more accurate phylogenetic inference of resolvable phylogenetic features.

RESULTS

We present the TopHap approach that determines spatiotemporally common haplotypes of common variants and builds their phylogeny at a fraction of the computational time of traditional methods. To assess topological robustness, we develop a bootstrap resampling strategy that resamples genomes spatiotemporally. The application of TopHap to build a phylogeny of 68,057 genomes (68KG) produced an evolutionary tree of major SARS-CoV-2 haplotypes. This phylogeny is concordant with the mutation tree inferred using the co-occurrence pattern of mutations and recovers key phylogenetic relationships from more traditional analyses. We also evaluated alternative roots of the SARS-CoV-2 phylogeny and found that the earliest sampled genomes in 2019 likely evolved by four mutations of the most recent common ancestor of all SARS-CoV-2 genomes. An application of TopHap to more than 1 million genomes reconstructed the most comprehensive evolutionary relationships of major variants, which confirmed the 68KG phylogeny and provided evolutionary origins of major variants of concern.

AVAILABILITY

TopHap is available on the web at https://github.com/SayakaMiura/TopHap .

CONTACT

s.kumar@temple.edu.