Identification of a novel HKU4-related coronavirus in single-cell datasets and clade viral host analysis (preprint)

HKU4-related coronaviruses (CoVs) are merbecoviruses related to Middle Eastern Respiratory Syndrome coronavirus (MERS-CoV). In 2022 and 2023, two HKU4-related CoV strains were discovered in Manis javanica (Malayan pangolin) metagenomic datasets derived from organ samples: HKU4-P251T and MjHKU4r-CoV-1. Together with the Tylonycteris robustula bat CoV 162275, which was discovered in 2022, pangolin CoVs HKU4-P251T and MjHKU4r-CoV-1 form a novel phylogenetic clade distinct from all previously documented HKU4-related CoVs. In this study, we identified a novel HKU4-related CoV in a pangolin single-cell sequencing dataset generated by BGI-Shenzhen in Shenzhen, Guangdong, China in 2020. The CoV phylogenetically belongs to the same newly identified clade. The single cell datasets were reported as generated from organ samples of a single pangolin that died of natural causes. 98% of the HKU4-related CoV reads were found in only one of the seven single cell datasets -- a large intestine cell dataset, cells of which exhibit low expression of DPP4. Bacterial contamination was found to be moderately correlated with HKU4-related CoV presence. We further identified with high confidence that the RNA-Seq dataset supporting one of four near identical variants of MjHKU4r-CoV-1 is a Sus scrofa (wild pig) metagenomic dataset, with only a trace level of Manis javanica genomic content. The presence of HKU4-related CoV reads in the dataset are almost certainly laboratory research-related and not from a premortal pangolin or pig infection. Our findings raise concerns about the provenance of the novel HKU4-related CoV we identify here, MjHKU4r-CoV-1 and its four near-identical variants.

Discovery of a novel merbecovirus cDNA clone contaminating agricultural rice sequencing datasets from Wuhan, China (preprint)

HKU4-related coronaviruses are a group of betacoronaviruses belonging to the same merbecovirus subgenus as Middle Eastern Respiratory Syndrome coronavirus (MERS-CoV), which causes severe respiratory illness in humans with a mortality rate of over 30%. The high genetic similarity between HKU4-related coronaviruses and MERS-CoV makes them an attractive subject of research for modeling potential zoonotic spillover scenarios. In this study, we identify a novel coronavirus contaminating agricultural rice RNA sequencing datasets from Wuhan, China. The datasets were generated by the Huazhong Agricultural University in early 2020. We were able to assemble the complete viral genome sequence, which revealed that it is a novel HKU4-related merbecovirus. The assembled genome is 98.38% identical to the closest known full genome sequence, Tylonycteris pachypus bat isolate BtTp-GX2012. Using in silico modeling, we identified that the novel HKU4-related coronavirus spike protein likely binds to human dipeptidyl peptidase 4 (DPP4), the receptor used by MERS-CoV. We further identified that the novel HKU4-related coronavirus genome has been inserted into a bacterial artificial chromosome in a format consistent with previously published coronavirus infectious clones. Additionally, we have found a near complete read coverage of the spike gene of the MERS-CoV reference strain HCoV-EMC/2012, and identify the likely presence of a HKU4-related-MERS chimera in the datasets. Our findings contribute to the knowledge of HKU4-related coronaviruses and document the use of a previously unpublished HKU4 reverse genetics system in apparent MERS-CoV related gain-of-function research. Our study also emphasizes the importance of improved biosafety protocols in sequencing centers and coronavirus research facilities.

Visualizing Amino Acid Substitutions in a Physicochemical Vector Space (preprint)

A three-dimensional representation of the twenty proteinogenic amino acids in a physicochemical space is presented. Vectors corresponding to amino acid substitutions are classified based on whether they are accessible via a single-nucleotide mutation. It is shown that the standard genetic code establishes a "choice architecture" that permits nearly independent tuning of the properties related with size and those related with hydrophobicity. This work sheds light on the metarules of evolvability that may have shaped the standard genetic code to increase the probability that adaptive point mutations will be generated. An illustration of the usefulness of visualizing amino acid substitutions in a 3D physicochemical space is shown using data collected from the SARS-CoV-2 receptor binding domain. The substitutions most responsible for antibody escape are almost always inaccessible via single nucleotide mutation, and also change multiple properties concurrently. The results of this research can extend our understanding of certain hereditary disorders caused by point mutations, as well as guide the development of rational protein and vaccine design.