Biology subjects

Nemzer, L. R.

Publications and source records attributed to Nemzer, L. R..

4 recordsLinked to original sources

bioRxiv2023

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

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.

genomics↗

bioRxiv2023

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

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.

genomics↗

bioRxiv2021

Visualizing Amino Acid Substitutions in a Physicochemical Vector Space

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 non-arbitrary benefits of evolvability that may have shaped the development standard genetic code to increase the probability that adaptive point mutations will be generated. Illustrations of the usefulness of visualizing amino acid substitutions in a 3D physicochemical space are shown using recent datasets collected regarding the SARS-CoV-2 receptor binding domain. First, the substitutions most responsible for antibody escape are almost always inaccessible via single nucleotide mutation, and change multiple properties concurrently. Second, it is shown that assays of ACE2 binding by sarbecovirus variants, including the viruses responsible for SARS and COVID-19, are more easily understood when plotted with this method. 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.

bioinformatics↗

bioRxiv2021

Experimental evidence that metapopulation structure can accelerate adaptive evolution

Whether the spatial arrangement of a population influences adaptive evolution has puzzled evolutionary biologists. Theoretical models make contrasting predictions about the probability a beneficial mutation will become fixed in a population for certain topologies like stars, where leaf populations are connected through a hub. To date, these predictions have not been evaluated under realistic conditions. Here, we test the prediction that topology can change the fixation probability both in vitro and in silico by tracking the dynamics of a beneficial mutant under positive selection as it spreads through networks of different topologies. Our results provide empirical support that metapopulation topology can increase the likelihood that a beneficial mutation spreads, broadens the conditions under which this phenomenon is thought to occur, and points the way towards using network topology to amplify the effects of weakly favored mutations under directed evolution in industrial applications.

evolutionary biology↗