Huanan Seafood Market Research Articles

MiRNAs: Key Molecules in the Immunopathogenesis of Betacoronaviruses

A series of patients hospitalized with acute respiratory disease was reported in Wuhan, Hubei Province, China, in December 2019. Many patients have had direct or indirect links with the Huanan Seafood Wholesale Market, Wuhan. This is the prologue to the ongoing pandemic of Coronavirus Disease 2019 (COVID-19) that has affected more than 150 countries and over 250,000 people worldwide, killing thousands of people. The pandemic has once again drawn public attention to the coronaviruses that developed epidemics in China (2002) and Saudi Arabia (2012). Given the structural and phylogenetic similarity of the 2019 novel coronavirus (2019-nCoV) with the severe acute respiratory syndrome coronavirus (SARS-CoV) and the Middle East respiratory syndrome coronavirus (MERS-CoV), the results of recent studies have been combined with new findings to complete one of the strangest pneumonia puzzles in the human history. Coronaviruses establish extremely complex interactions with the immune system, especially in order to evade immune responses. Undoubtedly, increasing our knowledge of the immunopathogenesis of diseases caused by these viruses will eventually lead to more effective treatment and diagnosis. Non-coding RNAs (ncRNAs) are among the leading immune response regulators. MicroRNAs (miRNAs) play an important role in the expression and regulation of both innate and adaptive immune responses and in many immune disorders from autoimmunity to cancer and allergies. Our understanding of the functions of human and viral miRNAs in the pathogenesis of many viruses has increased in recent years. Accordingly, the present review article aims to review studies evaluating the role of miRNAs in the pathogenesis of other Betacoronaviruses. The results of these studies, given the similarity of viruses within the family Coronaviridae, could be helpful for future research on SARS-CoV-2.

Phylogenetic Analysis and Mutation of Sars-Cov-2 in Bats in Karst Malang City, Indonesia

Introduction: A group of people in China were hospitalized with an initial diagnosis of pneumonia of unknown cause. The patients were linked to a wholesale wet seafood and animal market in Wuhan, Hubei Province, China. The disease has spread to other provinces in China, Thailand, Japan, and South Korea in less than a month. SARS-CoV-2 was found to originate from bats. Therefore, this research aims to analyze SARS-CoV-2 mutation in bats in Malang Karst, Indonesia. Methods: Other bat body parts used as research samples include the brain, liver, kidneys, intestines, pancreas, fetus, blood, lungs, and ectoparasites. The samples were taken separately and placed in a container containing 10% PBF. For further analysis, we used RNA Extraction, Real-Time PCR, Sequencing, and CoV Gisaid mutation analysis software to analyze the sequencing data. Then, EMBL software will be used to analyze the phylogenetically. Results and Discussion: There was 1 sample that showed a positive result for Covid-19, namely the intestine of the Cynoptera brachyotis species. There were differences between SARS-CoV-2 in bats in Malang Karst in Indonesia compared to SARS-CoV from 2000 to 2019. The spike protein's receptor binding domain (RBD) is the most variable part of the coronavirus genome. Conclusion: From the research results, one positive sample was obtained using Real-Time PCR, and based on mutation analysis, mutations were found in SARS-CoV-2 against the SARS-CoV virus from 2000-2019. Further research is needed, especially regarding SARS-CoV-2 as a vaccine.

Prevalence of COVID-19 among high school teachers in Erbil city

Background and objective: An outbreak of pneumonia of unknown origin was reported in Wuhan, Hubei Province, China, in December 2019. Cases of epidemic pneumonia have been linked to the Huanan Seafood Market; thus, it has been dubbed the severe acute respiratory syndrome coronavirus (SARS-CoV-2). The global spread of thousands of deaths from the coronavirus disease (COVID-19) has led the WHO to declare a pandemic on March 12, 2020. This study aimed to find out the prevalence of COVID-19 disease and vaccination coverage among public preparatory school teachers in Erbil. Methods: A cross-sectional study was conducted among the target group of 772 teachers in 76 public preparatory schools. The study population was 3157 teachers, 1263 male and 1894 female, in Erbil city, from September 1, 2021, to March 30, 2022. A questionnaire was used to collect data through face-to-face interviews using a simple random sampling method. Results: The study sample ages ranged from 26 to 62 years; the mean age, ±standard deviation, was 40.53 ± 9.75. The prevalence rate of COVID-19 was 63.1%. Of the study samples, 58.5% received information about COVID-19 disease from social media and 23.8% from satellite channels. 68.9% of the study samples received the COVID-19 vaccine, and the majority preferred the Pfizer vaccine. Conclusion: The majority of the study samples were infected with COVID-19 disease; many of the study samples received the COVID-19 vaccine; misconceptions need further correction; an increase in updating information regarding mode of transmission; an explanation of COVID-19 disease preventive measures; raising awareness of COVID-19 vaccination; more interesting health campaigns; and using mass media and community programs to change health behavior and reduce future health consequences of COVID-19 disease.

The Emergence and Evolution of SARS-CoV-2.

The origin of SARS-CoV-2 has evoked heated debate and strong accusations, yet seemingly little resolution. I review the scientific evidence on the origin of SARS-CoV-2 and its subsequent spread through the human population. The available data clearly point to a natural zoonotic emergence within, or closely linked to, the Huanan Seafood Wholesale Market in Wuhan. There is no direct evidence linking the emergence of SARS-CoV-2 to laboratory work conducted at the Wuhan Institute of Virology. The subsequent global spread of SARS-CoV-2 was characterized by a gradual adaptation to humans, with dual increases in transmissibility and virulence until the emergence of the Omicron variant. Of note has been the frequent transmission of SARS-CoV-2 from humans to other animals, marking it as a strongly host generalist virus. Unless lessons from the origin of SARS-CoV-2 are learned, it is inevitable that more zoonotic events leading to more epidemics and pandemics will plague human populations.

Proximity ascertainment bias in early COVID case locations

Abstract A comparison of the distances to the Huanan Seafood Market of early COVID cases with known links to the market versus cases without known links shows results apparently incompatible with a location model lacking proximity ascertainment bias. The sign of the difference instead agrees with a model in which such ascertainment bias is large. In the presence of such bias inferences based on the clustering of case locations become unreliable.

Erratum for the Research Article "The Huanan Seafood Wholesale Market in Wuhan was the early epicenter of the COVID-19 pandemic" by M. Worobey et al.

Erratum for the Research Article "The Huanan Seafood Wholesale Market in Wuhan was the early epicenter of the COVID-19 pandemic" by M. Worobey et al.

Ontology-based taxonomical analysis of experimentally verified natural and laboratory human coronavirus hosts and its implication for COVID-19 virus origination and transmission.

To fully understand COVID-19, it is critical to study all possible hosts of SARS-CoV-2 (the pathogen of COVID-19). In this work, we collected, annotated, and performed ontology-based taxonomical analysis of all the reported and verified hosts for all human coronaviruses including SARS-CoV, MERS-CoV, SARS-CoV-2, HCoV-229E, HCoV-NL63, HCoV-OC43, and HCoV-HKU1. A total of 37 natural hosts and 19 laboratory animal hosts of human coronaviruses were identified based on experimental evidence. Our analysis found that all the verified susceptible natural and laboratory animals belong to therian mammals. Specifically, these 37 natural therian hosts include one wildlife marsupial mammal (i.e., Virginia opossum) and 36 Eutheria mammals (a.k.a. placental mammals). The 19 laboratory animal hosts are also classified as therian mammals. The mouse models with genetically modified human ACE2 or DPP4 were more susceptible to virulent human coronaviruses with clear symptoms, suggesting the critical role of ACE2 and DPP4 to coronavirus virulence. Coronaviruses became more virulent and adaptive in the mouse hosts after a series of viral passages in the mice, providing clue to the possible coronavirus origination. The Huanan Seafood Wholesale Market animals identified early in the COVID-19 outbreak were also systematically analyzed as possible COVID-19 hosts. To support knowledge standardization and query, the annotated host knowledge was modeled and represented in the Coronavirus Infectious Disease Ontology (CIDO). Based on our and others' findings, we further propose a MOVIE model (i.e., Multiple-Organism viral Variations and Immune Evasion) to address how viral variations in therian animal hosts and the host immune evasion might have led to dynamic COVID-19 pandemic outcomes.

Statistics did not prove that the Huanan Seafood Wholesale Market was the early epicentre of the COVID-19 pandemic

Abstract In a recent prominent study, Worobey et al. (2022. The Huanan Seafood Wholesale Market in Wuhan was the early epicenter of the COVID-19 pandemic. Science, 377(6609), 951–959) purported to demonstrate statistically that the Huanan Seafood Wholesale Market was the epicentre of the early COVID-19 epidemic. We show that this statistical conclusion is invalid on two grounds: (a) The assumption that a centroid of early case locations or another simply constructed point is the origin of an epidemic is unproved. (b) A Monte Carlo test used to conclude that no other location than the seafood market can be the origin is flawed. Hence, the question of the origin of the pandemic has not been answered by their statistical analysis.

Review on Canine Coronavirus Disease; Its Clinical Management and Zoonotic Spillover

Coronaviruses are a diverse group of viruses infecting many different animals, and they can cause mild to severe respiratory infections in humans, as with the recently emerged spillover caused by COVID-19 (SARS-CoV2), which broke out in China’s Wuhan seafood market. Human coronaviruses (HCoVs) often have animal origins. Canine coronavirus is a highly contagious viral disease which is a member of the broader coronavirus family with known pathogens in dogs. Both enteric and respiratory coronaviruses are the two common types of canine coronaviruses, and it often causes mild or hard-to-spot illness; however, it can be fatal under certain conditions, particularly in young puppies. Antibiotics are ineffective against coronavirus infection in dogs, but may be useful in controlling secondary bacterial infections and a dehydrated case requires adequate fluid therapy to maintain the fluid and electrolyte imbalances. Canine coronavirus is spread through contact with fecal material from infected dogs, so isolating infected dogs from healthy ones can help reduce disease distribution. The virus is susceptible to the household disinfectants, so cleaning virus contaminated areas and bedding enable to limit the spread of disease. Therefore, this literature review is designed to highlight about the canine coronavirus and its relation with other group of viruses including their public health importance.

Importance of quantifying the number of viral reads in metagenomic sequencing of environmental samples from the Huanan Seafood Market.

In March 2023, the Chinese CDC publicly released raw metagenomic sequencing data for environmental samples collected in early 2020 from the Huanan Seafood Market. Prior to that data release, some scientists had suggested that these samples could be informative for establishing if animals such as raccoon dogs had been infected with severe acute respiratory syndrome virus 2 (SARS-CoV-2). However, no one had analyzed how much SARS-CoV-2 was actually present in the metagenomic sequencing data. After the raw data became available, I fully analyzed the abundance of both viral and animal genetic material in the samples. That analysis, which was published in Virus Evolution, found that the SARS-CoV-2 content of most samples was very low and that the abundance of SARS-CoV-2 was most strongly associated with animals such as largemouth bass that are not plausible candidates for having been infected. Based on these results, I concluded that the metagenomic content of the samples was not informative for determining if any non-human animals in the market had been infected with SARS-CoV-2. One of the authors of an earlier study of these samples, Florence Débarre, recently submitted a response to my paper. Here, I reply in turn to explain why it is important to quantify the abundance of viral material before drawing conclusions from metagenomic sequencing. I also report new analyses of other animal coronaviruses in the samples and show that material from some other animal coronaviruses is much more abundant than SARS-CoV-2 in samples collected on the date when most wildlife stall sampling was performed. I further show that material from some of these animal coronaviruses is associated with the animals they probably infect but that no such association exists for SARS-CoV-2. Overall, these new analyses further emphasize the importance of quantifying the actual amount of viral material in metagenomic samples and underscore why the environmental samples from the Huanan Seafood Market are not informative for determining if any non-human animals were infected with SARS-CoV-2.

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.

COVID-19’s Social and Economic Impact on Health Care Professionals in India

Novel Corona Virus or COVID 19 is from the family Coronaviridae, known to mankind since 1962 when it was first isolated from a patient of a respiratory illness. These are pleomorphic viruses containing varying size peplomers (80- 160nM). They have very high rates of mutation due to constantly developing transcription errors & RNA dependent RNA polymerase (RdRP) jumps. These viruses are zoonotic pathogens affecting mostly animals including cattle, dogs, cats & bats. However these animal viruses can spread to humans causing pandemics like SARS & COVID19. They can cause wide range of infections from asymptomatic stage to cases requiring management at intensive care units. The first notable disease caused by Coronaviridae viruses was severe acute respiratory syndrome (SARS) in China in 2002- 2003. After a decade there was an outbreak in Middle East countries causing thousands of deaths and causative CoV was named as Middle East Respiratory Syndrome Coronavirus (MERS-CoV). The present corona virus pandemic, which erupted in Dec 2019 from Wuhan sea food market and was later labelled as 2019 novel corona virus (nCOVID 19) by world health organisation, is posing as a major healthcare challenge across the globe. It is rapidly spreading across the globe taking millions of lives and causing chaos. It has severely jeopardized the world economy causing global recession.

Association between SARS-CoV-2 andmetagenomic content ofsamples from the Huanan Seafood Market.

The role of the Huanan Seafood Market in the early severe acute respiratory syndrome virus 2 (SARS-CoV-2) outbreak remains unclear. Recently, the Chinese Centers for Disease Control (CDC) released data from deep sequencing of environmental samples collected from the market after it was closed on 1 January 2020. Prior to this release, Crits-Christoph etal. analyzed data from a subset of the samples. Both that study and the Chinese CDC study concurred that the samples contained genetic material from a variety of species, including some like raccoon dogs that are susceptible to SARS-CoV-2. However, neither study systematically analyzed the relationship between the amount of genetic material from SARS-CoV-2 and different animal species. Here I implement a fully reproducible computational pipeline that jointly analyzes the number of reads mapping to SARS-CoV-2 and the mitochondrial genomes of chordate species across the full set of samples. I validate the presence of genetic material from numerous species and calculate mammalian mitochondrial compositions similar to those reported by Crits-Christoph etal. However, the SARS-CoV-2 content of the environmental samples is generally very low: only 21 of 176 samples contain more than ten SARS-CoV-2 reads, despite most samples being sequenced to depths exceeding 108 total reads. None of the samples with double-digit numbers of SARS-CoV-2 reads have a substantial fraction of their mitochondrial material from any non-human susceptible species. Only one of the fourteen samples with at least a fifth of the chordate mitochondrial material from raccoon dogs contains any SARS-CoV-2 reads, and that sample only has 1 of ~200,000,000 reads mapping to SARS-CoV-2. Instead, SARS-CoV-2 reads are most correlated with reads mapping to various fish, such as catfish and largemouth bass. These results suggest that while metagenomic analysis of the environmental samples is useful for identifying animals or animal products sold at the market, co-mingling of animal and viral genetic material is unlikely to reliably indicate whether any animals were infected by SARS-CoV-2.

Analysis of SARS-CoV-2 Population Genetics from Samples Associated with Huanan Market and Early Cases Identifies Substitutions Associated with Future Variants of Concern.

SARS-CoV-2 began spreading through human-to-human transmission first within China and then worldwide, with increasing sequence diversity associated with time and the further spread of the virus. The spillover events in the Huanan market were associated with two lineages of SARS-CoV-2 (lineages A and B). Infecting virus populations and those in infected individuals consist of a dominant genomic sequence and minor genomic variants; these latter populations can indicate sites on the genome that may be subject to mutational changes-either neutral or advantageous sites and those that act as a reservoir for future dominant variants-when placed under selection pressure. The earliest deposited sequences with human infections associated with the Huanan market shared very close homology with each other and were all lineage B. However, there were minor genomic variants present in each sample that encompassed synonymous and non-synonymous changes. Fusion sequences characteristic of defective RNA were identified that could potentially link transmission chains between individuals. Although all the individuals appeared to have lineage B as the dominant sequence, nucleotides associated with lineage A could be found at very low frequencies. Several substitutions (but not deletions) associated with much later variants of concern (VoCs) were already present as minor genomic variants. This suggests that low-frequency substitutions at the start of a pandemic could be a reservoir of future dominant variants and/or provide information on potential sites within the genome associated with future plasticity.

A General Approach to Modeling Covid-19

The present work shows that it is possible to analytically solve a general model to explain the transmission dynamics of SARS-CoV-2. First, the within-host model is described, and later a between-host model, where the coupling between them is the viral load of SARS-CoV-2. The within-host model describes the equations involved in the life cycle of SARS-CoV-2, and also the immune response; while that the between-Host model analyzes the dynamics of virus spread from the original source of contagion associated with bats, subsequently transmitted to a host, and then reaching the reservoir (Huanan Seafood Wholesale Market in Wuhan ), until finally infecting the human population.

Effects of social factors on the COVID-19 cases and its evolution in Hubei, China.

In order to study the impact of social factors on the evolution of the epidemic, this paper takes the COVID-19 in Hubei Province of China as an example to study the impact of social factors such as the permanent population, universities, hospitals, the distance between Wuhan seafood market and 17 cities in Hubei Province, and the distribution of medical supplies on the COVID-19. This is of great significance for helping to develop effective prevention and control measures and response strategies, ensuring public health and social stability. Time series regression analysis is used to study the impact of various factors on the epidemic situation, multidimensional scale analysis is used to assess the differences among provinces, and Almon polynomial is used to study the lag effect of the impact. We found that these cities can be divided into three groups based on the number of confirmed cases and the time course data of the cases. The results verify that these factors have a great impact on the evolution of the COVID-19. With the increase in the number of universities, the number of confirmed cases and new cases has significantly increased. With the increase in population density, the number of new cases has significantly increased. In addition, the farther away from the Wuhan seafood market, the fewer confirmed cases. It is worth noting that the insufficient increase in medical supplies in some cities still leads to a significant increase in new cases. This impact is regional, and their lag periods are also different. Through the comparison with Guangdong Province, it is concluded that social factors will affect COVID-19. Overall, promoting the construction of medical schools and ensuring the reasonable distribution of medical supplies is crucial as it can effectively assist decision-making.

TACKLING POST COVID-19 PANDEMIC CHALLENGES THROUGH HOME ECONOMICS EDUCATION FOR FAMILY SUSTAINABILITY

Coronavirus disease (COVID-19) is an infectiousdisease caused by a newly discovered coronavirus.The origin of the coronavirus is said to have beentraced to the Wuhan seafood market in Wuhan,China in late 2019 (Centre for Disease Control andPrevention, 2020). The outbreak was declared aPublic Health Emergency of International Concernon 30 January 2020 and on 11th of February 2020,the World Health Organization (WHO) announcedCOVID-19 as the name of this new disease.On March 11 2020, the World HealthOrganization (WHO) (2020) officially declared aglobal pandemic. Since then, the Covid-19pandemic has had a dramatic effect, not least ofwhich is the clear demonstration of the fragility ofhuman life, with more than 170 million infectionsand 3.5 million deaths in just over a year(Worldometer, 2021) and with no end in sight. Theadvent of this global pandemic is not withoutprecedent, with many pandemics changing thecourse of human history over centuries, includingleprosy; the Black Death, plagues, cholera, measles,the Russian, Spanish and Asian flus, HIV/AIDS and,in the 21st century, SARS (History.com, 2020). Oneof the key strategies for reducing the spread of thevirus has been to maintain a safe distance from others to avoid transmission, and to that end, since the pandemic was declared, most people around the world have been directed to isolate at home for aperiod, alongside employing personal protectivebehaviours such as wearing masks, washing handsfrequently, and avoiding crowds for the individualand family safety.

Surveillance of SARS-CoV-2 at the Huanan Seafood Market.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019, emerged in December 2019. Its origins remain uncertain. It has been reported that a number of the earlyhuman cases of coronavirus disease 2019 had a history of contact with the Huanan Seafood Market. Here we present the results of surveillance for SARS-CoV-2 within the market. From 1 January 2020, after closure of the market, 923 samples were collected from the environment. From 18 January, 457 samples were collected from 18 species of animal, comprising unsold contents of refrigerators and freezers, swabs from stray animals and the contents of a fish tank. Using quantitative real-time polymerase chain reaction (RT-qPCR) and high-throughput sequencing (Bowtie2 analysis), SARS-CoV-2 was detected in 74 (70 RT-qPCR and 4 Bowtie2) environmental samples, but none of the animal samples. Three live viruses were successfully isolated. The viruses from the market shared a nucleotide identity of 99.99% to 100% with the human isolate HCoV-19/Wuhan/IVDC-HB-01/2019. SARS-CoV-2 lineage A (8782T and 28144C) was found in an environmental sample. RNA-sequencing analysis of SARS-CoV-2-positive and SARS-CoV-2-negative environmental samples showed an abundance of different vertebrate genera at the market. In summary, this study provides information about the distribution and prevalence of SARS-CoV-2 in the Huanan Seafood Market during the early stages of the outbreak of coronavirus disease 2019.

Immune evasion of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2); molecular approaches.

In December 2019, a new betacoronavirus, known as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), caused an outbreak at the Wuhan seafood market in China. The disease was further named coronavirus disease 2019 (COVID-19). In March 2020, the World Health Organization (WHO) announced the disease to be a pandemic, as more cases were reported globally. SARS-CoV-2, like many other viruses, employs diverse strategies to elude the host immune response and/or counter immune responses. The infection outcome mainly depends on interactions between the virus and the host immune system. Inhibiting IFN production, blocking IFN signaling, enhancing IFN resistance, and hijacking the host's translation machinery to expedite the production of viral proteins are among the main immune evasion mechanisms of SARS-CoV-2. SARS-CoV-2 also downregulates the expression of MHC-I on infected cells, which is an additional immune-evasion mechanism of this virus. Moreover, antigenic modifications to the spike (S) protein, such as deletions, insertions, and also substitutions are essential for resistance to SARS-CoV-2 neutralizing antibodies. This review assesses the interaction between SARS-CoV-2 and host immune response and cellular and molecular approaches used by SARS-CoV-2 for immune evasion. Understanding the mechanisms of SARS-CoV-2 immune evasion is essential since it can improve the development of novel antiviral treatment options as well as vaccination methods.

Unwarranted Exclusion of Intermediate Lineage A-B SARS-CoV-2 Genomes Is Inconsistent with the Two-Spillover Hypothesis of the Origin of COVID-19

Pekar et al. (2022) propose that SARS-CoV-2 was a zoonotic spillover that first infected humans in the Huanan Seafood Market in Wuhan, China. They propose that there were two separate spillovers of the closely related lineages A and lineage B in a short period of time. The two lineages are differentiated by two SNVs; hence, a single-SNV A-B intermediate must have occurred in an unsampled animal host if the two-spillover hypothesis is correct. Consequently, confirmation of the existence of an intermediate A-B genome from humans would falsify their hypothesis of two spillovers. Pekar et al. identified and excluded 20 A-B intermediate genomes from their analysis. A variety of exclusion criteria were applied, including low read depth and the assertion of repeated erroneous base calls at lineage-defining positions 8782 and 28144. However, data from GISAID show that most of the genomes were sequenced to high average sequencing depth, appearing inconsistent with these criteria. The decision to exclude the majority of genomes was based on personal communications, with raw data unavailable for inspection. Multiple errors, biases, and inconsistencies were observed in the exclusion process. For example, 12 intermediate genomes from one study were excluded; however, 54 other genomes from the same study were included, indicating selection bias. Puzzlingly, two intermediate genomes from Beijing were discarded despite an average sequencing depth of 2175X; however, four genomes from the same sequencing study were included in the analysis. Lastly, we discuss 14 additional possible intermediate genomes not discussed by Pekar et al. and note that genome sequence filtration is inappropriate when considering the presence or absence of a specific SNV pair in an outbreak. Consequently, we find that the exclusion of many of the intermediate genomes is unfounded, leaving the conclusion of two natural zoonoses unsupported.