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. We analysed the evolutionary relationships, nucleotide compositions, codon usage patterns, selection pressures (mutational pressure and natural selection) and viral adaptation to host codon usage based on the coding sequences (CDS) of key functional genes of ASFV. AT bias was detected in the six genes analysed, irrespective of clade. The AT bias of genes (A224L, A179L, EP153R) encoding proteins involved in interaction with host cells after infection was high; among them, the AT bias of EP153R was the greatest at 78.3%. A large number of overrepresented codons were identified in EP153R, whereas there were no overrepresented codons with a relative synonymous codon usage (RSCU) value of ≥3 in B646L. In most genes, the pattern of selection pressure was similar for each clade, but in EP153R, diverse patterns of selection pressure were captured within the same clade and genotype. As a result of evaluating host adaptation based on the codon adaptation index (CAI), for B646L, E183L, CP204L and A179L, the codon usage patterns in all sequences were more similar to tick than domestic pig or wild boar. However, EP153R showed the lowest average CAI value of 0.52 when selecting tick as a reference set. The genes analysed in this study showed different magnitudes of selection pressure at the clade and genotype levels, which is likely to be related to the function of the encoded proteins and may determine key evolutionary traits of viruses, such as the level of genetic variation and host range. The diversity of codon adaptations at the genetic level in ASFV may account for differences in translational selection in ASFV hosts and provides insight into viral host adaptation and co-evolution.

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. Therefore, before constructing a phylogenetic tree, it is necessary to assess the causes of systematic bias to improve the accuracy of phylogenetic estimates. We performed analyses of three datasets (Terebelliformia, Daphniid, and Glires clades) using bioinformatics software to assess systematic error and improve phylogenetic tree accuracy. Then, we proposed a combination of systematic biases capable of discerning the most suitable gene markers within a series of taxa and generating conflicting phylogenetic topologies. Our findings will help improve the reliability of phylogenetic software to estimate phylogenies more accurately by exploiting systematic bias.

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. 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.

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. Based on the clustering pattern of the reconstructed phylogenetic tree, the dataset was divided into three groups: mammalian, avian, and fish. We then used random forest (RF), naïve Bayes (NB), and k-nearest neighbors (kNN) algorithms for host classification. RESULTS: Among the three algorithms, classification 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 classification was charge, followed by solvent accessibility, polarity, and hydrophobicity in LT-Ag. However, in VP1, amino acid composition showed the highest correlation with host classification, 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 different infection properties among diverse host species. Structural and biochemical differences of LT-Ag and VP1 proteins in host species that reflect these amino acid properties can be considered primary factors that determine the host specificity of PyV.

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. Among the four segments of RVFV, the nucleotide composition, overall GC content and the difference of GC composition in the third position of the codons (%GC3) between groups were the largest in the S (NP) segment, showing that more diverse codons were used than in other segments. Furthermore, the results of CAI analysis of the S (NP) segment showed that viruses isolated from regions where no previous infections had been reported had the highest values, indicating greater adaptability to human hosts compared with other viruses. This result suggests that mutations in the S (NP) segment co-evolve with the infected hosts and may lead to expansion of the geographic range. The distinctive codon usage patterns observed in specific genomic regions of a group with similar infection properties may be related to the increasing likelihood of RVFV infections in new areas.

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. Parity rule 2 (PR2) and neutrality analysis were applied to evaluate the effects of mutation and selection pressure on codon usage bias. To investigate evolutionary relationships among PyVs, we carried out a phylogenetic analysis, and a correspondence analysis of relative synonymous codon usage (RSCU) values was performed. RESULTS: Nucleotide composition analysis using LT-Ag gene sequences showed that the GC and GC3 values of avian PyVs were higher than those of mammalian PyVs. The effective number of codon (ENC) analysis showed host-specific ENC distribution characteristics in both the LT-Ag gene and the coding sequences of its domain regions. In the avian and fish PyVs, the codon diversity was significant, whereas the mammalian PyVs tended to exhibit conservative and host-specific evolution of codon usage bias. The results of our PR2 and neutrality analysis revealed mutation bias or highly variable GC contents by showing a narrow GC12 distribution and wide GC3 distribution in all sequences. Furthermore, the calculated RSCU values revealed differences in the codon usage preference of the LT-AG gene according to the host group. A similar tendency was observed in the two functional domains used in the analysis. CONCLUSIONS: Our study showed that specific domains or sequence motifs of various PyV LT-Ags have evolved so that each virus protein interacts with host cell targets. They have also adapted to thrive in specific host species and cell types. Functional domains of LT-Ag, which are known to interact with host proteins involved in cell proliferation and gene expression regulation, may provide important information, as they are significantly related to the host specificity of PyVs.

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. Evolutionary divergence matrices and a sequence similarity scoring program were used to determine the distance and similarity of receptor sequences. The discriminant analysis was validated with cross-validation methods. The results showed that the primary structure of the receptor protein influences host susceptibility to cross-species viral infections. Pair-wise distance, relative distance, and sequence similarity showed the best accuracy in identifying the susceptible group. Based on the results of the discriminant analysis, we constructed ViCIPR (http://lcbb3.snu.ac.kr/ViCIPR/home.jsp), a server-based tool to enable users to easily extract the cross-species infection propensities of specific viruses using a simple two-step procedure. Our sequence-based approach suggests that it may be possible to identify virus transmission between hosts without requiring complex structural analysis. Due to a lack of available data, this method is limited to viruses whose receptor use has been determined. However, the significant accuracy of predictive variables that positively and negatively influence virus transmission suggests that this approach could be improved with further analysis of receptor sequences.

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. Other experiments included predicting the effects of antibiotics when added to two different groups, one group of nonresistant bacteria and another group of both resistant and nonresistant bacteria. Carbapenem class antibiotics such as Imipenem were used for the simulation. The simulation results showed that the biological principles of bacteria and their antibiotic resistance mechanisms were correctly designed and implemented. Using the computational approaches developed in this study, we hope to provide researchers with a more effective method for finding new ways to fight antibiotic resistance.

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. RESULTS: Of the 34 NNIDs, malaria showed the most significant correlation with temperature (r=0.949, p<0.01) and concentration of nitrogen dioxide (r=-0.884, p<0.01). We also found a strong correlation between the incidence of NNIDs and the number of hospital beds in 25 districts in Seoul (r=0.606, p<0.01). In particular, Geumcheon-gu was found to have the lowest incidence rate of NNIDs and the highest number of hospital beds per patient. CONCLUSIONS: In this study, we conducted a correlational analysis of public data from Korean government portals that can be used as parameters to forecast the spread of outbreaks.