Construction of a Genetic Information Database for Analysis of Oncolytic Viruses

Myeongji Cho,Hyeon Seok Son,Hayeon Kim 한국인터넷방송통신학회 2020 Journal of Advanced Smart Convergence Vol.9 No.1

Oncolytic viruses are characterized by their ability to selectively kill cancer cells, and thus they have potential for application as novel anticancer agents. Despite an increase in the number of studies on methodologies involving oncolytic viruses, bioinformatic studies generating useful data are lacking. We constructed a database for oncolytic virus research (the oncolytic virus database, OVDB) by integrating scattered genetic information on oncolytic viruses and proposed a systematic means of using the biological data in the database. Our database provides data on 14 oncolytic viral strains and other types of viruses for comparative analysis. We constructed the OVDB using the basic local alignment search tool, and therefore can provides genetic information on highly homologous oncolytic viruses. This study contributes to facilitate systematic bioinformatics research, providing valuable data for development of oncolytic virus-based anticancer therapies.

Construction of a Genetic Information Database for Analysis of Oncolytic Viruses

Cho, Myeongji,Son, Hyeon Seok,Kim, Hayeon The Institute of Internet 2020 International journal of advanced smart convergenc Vol.9 No.1

Oncolytic viruses are characterized by their ability to selectively kill cancer cells, and thus they have potential for application as novel anticancer agents. Despite an increase in the number of studies on methodologies involving oncolytic viruses, bioinformatic studies generating useful data are lacking. We constructed a database for oncolytic virus research (the oncolytic virus database, OVDB) by integrating scattered genetic information on oncolytic viruses and proposed a systematic means of using the biological data in the database. Our database provides data on 14 oncolytic viral strains and other types of viruses for comparative analysis. We constructed the OVDB using the basic local alignment search tool, and therefore can provides genetic information on highly homologous oncolytic viruses. This study contributes to facilitate systematic bioinformatics research, providing valuable data for development of oncolytic virus-based anticancer therapies.

Analysis of evolutionary and genetic patterns in structural genes of primate lentiviruses

Cho Myeongji,Min Xianglan,Son Hyeon S. 한국유전학회 2022 Genes & Genomics Vol.44 No.7

Background: Primate lentiviruses (HIV1, HIV2, and Simian immunodeficiency virus [SIV]) cause immune deficiency, encephalitis, and infectious anemia in mammals such as cattle, cat, goat, sheep, horse, and puma. Objective: This study was designed and conducted with the main purpose of confirming the overall codon usage pattern of primate lentiviruses and exploring the evolutionary and genetic characteristics commonly or specifically expressed in HIV1, HIV2, and SIV. Methods: The gag, pol, and env gene sequences of HIV1, HIV2, and SIV were analyzed to determine their evolutionary relationships, nucleotide compositions, codon usage patterns, neutrality, selection pressure (influence of mutational pressure and natural selection), and viral adaptation to human codon usage. Results: A strong 'A' bias was confirmed in all three structural genes, consistent with previous findings regarding HIV. Notably, the ENC-GC3s plot and neutral evolution analysis showed that all primate lentiviruses were more affected by selection pressure than by mutation caused by the GC composition of the gene, consistent with prior reports regarding HIV1. The overall codon usage bias of pol was highest among the structural genes, while the codon usage bias of env was lowest. The virus groups showing high codon bias in all three genes were HIV1 and SIVcolobus. The codon adaptation index (CAI) and similarity D(A, B) values indicated that although there was a high degree of similarity to human codon usage in all three structural genes of HIV, this similarity was not caused by translation pressure. In addition, compared with HIV1, the codon usage of HIV2 is more similar to the human codon usage, but the overall codon usage bias is lower. Conclusion: The origin viruses of HIV (SIVcpz_gor and SIVsmm) exhibit greater similarity to human codon usage in the gag gene, confirming their robust adaptability to human codon usage. Therefore, HIV1 and HIV2 may have evolved to avoid human codon usage by selection pressure in the gag gene after interspecies transmission from SIV hosts to humans. By overcoming safety and stability issues, information from codon usage analysis will be useful for attenuated HIV1 vaccine development. A recoded HIV1 variant can be used as a vaccine vector or in immunotherapy to induce specific innate immune responses. Further research regarding HIV1 dinucleotide usage and codon pair usage will facilitate new approaches to the treatment of AIDS.

Analysis of protein determinants of host‐specific infection properties of polyomaviruses using machine learning

Myeongji Cho,Hayeon Kim,손현석 한국유전학회 2021 Genes & Genomics Vol.43 No.4

Background The large tumor antigen (LT-Ag) and major capsid protein VP1 are known to play important roles in determining the host-specifc infection properties of polyomaviruses (PyVs). Objective The objective of this study was to investigate the physicochemical properties of amino acids of LT-Ag and VP1 that have important efects on host specifcity, as well as classifcation techniques used to predict PyV hosts. Methods We collected and used reference sequences of 86 viral species for analysis. Based on the clustering pattern of the reconstructed phylogenetic tree, the dataset was divided into three groups: mammalian, avian, and fsh. We then used random forest (RF), naïve Bayes (NB), and k-nearest neighbors (kNN) algorithms for host classifcation. Results Among the three algorithms, classifcation accuracy using kNN was highest in both LT-Ag (ACC=98.83) and VP1 (ACC=96.51). The amino acid physicochemical property most strongly correlated with host classifcation was charge, followed by solvent accessibility, polarity, and hydrophobicity in LT-Ag. However, in VP1, amino acid composition showed the highest correlation with host classifcation, followed by charge, normalized van der Waals volume, and solvent accessibility. Conclusions The results of the present study suggest the possibility of determining or predicting the host range and infection properties of PyVs at the molecular level by identifying the host species of active and emerging PyVs that exhibit diferent infection properties among diverse host species. Structural and biochemical diferences of LT-Ag and VP1 proteins in host species that refect these amino acid properties can be considered primary factors that determine the host specifcity of PyV.

Cancer-selective Mechanisms of Oncolytic Viruses

Myeongji Cho,Hyeon S. Son 서울대학교 보건환경연구소 2015 보건학논집 Vol.52 No.1

Viruses that can be used for the treatment of cancer are referred to as oncolytic viruses. These viruses selectively infect cancer cells and induce cell death through a process of viral replication, proliferation, and budding. Diverse oncolytic viruses exist, and the genetic mechanisms of their cancer-selective killing strategies vary with the genetic diversity of each virus. Therefore, accurate information on viral genes and an understanding of cancer-selective killing mechanisms are required to study the treatment of cancer using oncolytic viruses. These require the storage and utilization of large amounts of data related to oncolytic viruses and cancer and studies based on enormous data sets using computer-based bioinformatics approaches. Such resources will aid in the development of novel cancer therapeutics using oncolytic viruses by providing the scientific basis for problem solving and decision making. In this study, we discuss the anti-cancer mechanisms of oncolytic viruses, classify them into four categories, and investigate the anti-cancer activities of different viruses. In addition, we evaluate the need for interdisciplinary research on oncolytic viruses by considering future research and therapy directions based on our understanding of molecular mechanisms, genetic mechanisms, and research achievements.

Analysis of Coronaviral Spike Proteins and Virus–host Interactions

Miran Kim,Myeongji Cho,Ji-Hae Lee,Hayeon Kim,Hyeon S. Son 서울대학교 보건환경연구소 2019 보건학논집 Vol.56 No.1

Objectives: Recent outbreaks caused by Middle East respiratory syndrome coronavirus (MERS-CoV), such as the May 2015 outbreak in Korea, highlight the urgency of studying new mutant viruses that may be introduced in the future and preparing effective countermeasures to prevent large-scale infections. Most coronaviruses that infect humans cause only mild respiratory infections, but research on coronaviruses has increased in the wake of large-scale epidemics of MERS and severe acute respiratory syndrome (SARS). Therefore, we conducted a comparative analysis of the major human coronaviruses using genetic information and performed a network analysis to investigate the interactions between viruses and host immune proteins. Methods: Phylogenetic and structural analyses were performed using the spike protein sequences of six coronaviruses (HCoV-OC43, HCoV-HKU1, MERS-CoV, SARS-CoV, HCoV-229E, and HCoV-NL63) causing diseases in humans. Network analysis was performed using Cytoscape 3.3.0 to analyze the interactions of viral proteins with host immune proteins. Results: The phylogenetic analysis showed that although HCoV-OC43 and MERS belong to different lineages (lineages A and C, respectively), the evolutionary distance between spike proteins in these two viruses is relatively close. The structural analysis confirmed that the structure of the spike protein of HCoVOC43 was similar to those of SARS-CoV and MERS-CoV, which are both highly transmissible. Finally, the network analysis confirmed interactions between the human IC1 protein, which is involved in the activation of the C1 complex, and non-structural proteins in SARS-CoV. Conclusion: The similarity of SARS-CoV and MERS-CoV with other coronaviruses suggests the need for continued study of mutations in coronaviral genomes. In particular, the IC1 protein, which interacts with nonstructural proteins in SARS-CoV, may have a major effect on the host immune response to viral infection because it has functions related to complement system activation. Studies of these viruses and host immune proteins will assist the development of vaccines and therapeutic agents against coronaviruses by enhancing our understanding of the detailed immune mechanisms against viral infections.

유전자 네트워크 분석을 통한 심근증 마커유전자 탐색 연구

서명석(Moungseock Seo),조명지(Myeongji Cho),손현석(Hyeonseok Son) 서울대학교 보건환경연구소 2018 보건학논집 Vol.55 No.1

Objectives: Cardiomyopathy is a heterogeneous disease with structural and functional abnormalities in the heart muscle, which is characterized by a prognosis of heart failure. Recently, several genes related to this have been found. In this study, we aimed to investigate marker genes that can predict the prognosis of heart failure in cardiomyopathies due to genetic factors through network analysis using microarray data. Methods: GSE1145 data of Gene Expression Omnibus was used as microarray data. 11 of normal, 12 of idiopathic dilated cardiomyopathy, 11 of ischemic cardiomyopathy and 5 of hypertrophic cardiomyopathy were used respectively. The gene network was constructed based on the expression correlation data corresponding to the heart-left ventricle mRNA type of the genotype-tissue expression v5 group, and the centrality analysis was performed using the R program. Results: In the case of heart failure due to cardiomyopathy, a total of 73 genes were specifically regulated. The network analysis of these genes showed high centrality of 10 genes including C1QTNF7, ECM2 and FAM188A. In the 2-mode network analysis between the above genes and the genes responsible for cardiomyopathy, 26 genes including ACTC1, ACTN2, BAG3 and DES showed a high centrality in DCM. In HCM, 10 genes including ACTC1 and ACTN2 showed a significant high centrality. Conclusion: Genes with high centrality in 1-mode network analysis are likely to play an important role in the development of cardiac failure as a prognosis for cardiomyopathy and may therefore be a target for research and treatment of heart failure. Genes with high centrality in the 2-mode network analysis may be used as markers to predict heart failure due to myocardial prognosis through routine diagnostic tests.