The evolutionary and genetic patterns of African swine fever virus.

African swine fever (ASF) is a serious animal disease, and has spread to Africa, Europe and Asia, causing massive economic losses. African swine fever virus (ASFV) is transmitted from a reservoir host (warthog) to domestic pigs via a sylvatic cycle (transmission between warthogs and soft ticks) and a domestic cycle (transmission between domestic pigs) and survives by expressing a variety of genes related to virus-host interactions. We evaluated differences in codon usage patterns among ASFV genotypes and clades and explored the common and specific evolutionary and genetic characteristics of ASFV sequences.

Utilization of systematic error-assessment software to improve phylogenetic accuracy.

Unlike classical systems based on the use of morphological data, modern phylogenetic analyses use genetic information to construct phylogenetic trees. Ongoing research in the field of phylogenetics is evaluating the accuracy of phylogenetic estimation results and the reliability of phylogenetic trees to explain evolutionary relationships. Recently, the probability of stochastic errors in large-scale phylogenetic datasets has decreased, while the probability of systematic errors has increased.

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

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.

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

Background: The large tumor antigen (LT-Ag) and major capsid protein VP1 are known to play important roles in determining the host-specific 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 effects on host specificity, as well as classification techniques used to predict PyV hosts.

Methods: We collected and used reference sequences of 86 viral species for analysis.

Comparative analysis of codon usage patterns in Rift Valley fever virus.

Rift Valley fever virus (RVFV) is a vector-borne pathogen and is the most widely known virus in the genus Phlebovirus. Since it was first reported, RVFV has spread to western Africa, Egypt and Madagascar from its traditional endemic region, and infections continue to occur in new areas. In this study, we analyzed genomic patterns according to the infection properties of RVFV.

Codon usage patterns of LT-Ag genes in polyomaviruses from different host species.

Background: Polyomaviruses (PyVs) have a wide range of hosts, from humans to fish, and their effects on hosts vary. The differences in the infection characteristics of PyV with respect to the host are assumed to be influenced by the biochemical function of the LT-Ag protein, which is related to the cytopathic effect and tumorigenesis mechanism via interaction with the host protein.

Methods: We carried out a comparative analysis of codon usage patterns of large T-antigens (LT-Ags) of PyVs isolated from various host species and their functional domains and sequence motifs.

Prediction of cross-species infection propensities of viruses with receptor similarity.

Studies of host factors that affect susceptibility to viral infections have led to the possibility of determining the risk of emerging infections in potential host organisms. In this study, we constructed a computational framework to estimate the probability of virus transmission between potential hosts based on the hypothesis that the major barrier to virus infection is differences in cell-receptor sequences among species. Information regarding host susceptibility to virus infection was collected to classify the cross-species infection propensity between hosts.

Simulation Model of Bacterial Resistance to Antibiotics Using Individual-Based Modeling.

We designed and implemented simulation models of bacterial growth and antibiotic resistance to determine the appropriate antibiotics to use against antibiotic-resistant bacteria. Simulation models were designed using individual-based modeling, and a simulation tool, ARSim, was developed to conduct experiments using the models. Simulations of bacterial growth were conducted by virtually growing Klebsiella pneumoniae bacteria in a virtual environment with predefined parameters.

Correlations Between the Incidence of National Notifiable Infectious Diseases and Public Open Data, Including Meteorological Factors and Medical Facility Resources.

Objectives: This study was performed to investigate the relationship between the incidence of national notifiable infectious diseases (NNIDs) and meteorological factors, air pollution levels, and hospital resources in Korea.

Methods: We collected and stored 660,000 pieces of publicly available data associated with infectious diseases from public data portals and the Diseases Web Statistics System of Korea. We analyzed correlations between the monthly incidence of these diseases and monthly average temperatures and monthly average relative humidity, as well as vaccination rates, number of hospitals, and number of hospital beds by district in Seoul.