Insung Ahn

Genomic Analysis of Influenza A Viruses, including Avian Flu (H5N1) Strains

This study was designed to conduct genomic analysis in two steps, such as the overall relative synonymous codon usage (RSCU) analysis of the five virus species in the orthomyxoviridae family, and more intensive pattern analysis of the four subtypes of influenza A virus (H1N1, H2N2, H3N2, and H5N1) which were isolated from human population. All the subtypes were categorized by their isolated regions, including Asia, Europe, and Africa, and most of the synonymous codon usage patterns were analyzed by correspondence analysis (CA). As a result, influenza A virus showed the lowest synonymous codon usage bias among the virus species of the orthomyxoviridae family, and influenza B and influenza C virus were followed, while suggesting that influenza A virus might have an advantage in transmitting across the species barrier due to their low codon usage bias. The ENC values of the host-specific HA and NA genes represented their different HA and NA types very well, and this reveals that each influenza A virus subtype uses different codon usage patterns as well as the amino acid compositions. In NP, PA and PB2 genes, most of the virus subtypes showed similar RSCU patterns except for H5N1 and H3N2 (A/HK/1774/1999) subtypes which were suspected to be transmitted across the species barrier, from avian and porcine species to human beings, respectively. This distinguishable synonymous codon usage patterns in non-human origin viruses might be useful in determining the origin of influenza A viruses in genomic levels as well as the serological tests. In this study, all the process, including extracting sequences from GenBank flat file and calculating codon usage values, was conducted by Java codes, and these bioinformatics-related methods may be useful in predicting the evolutionary patterns of pandemic viruses.

Evolutionary analysis of human-origin influenza A virus (H3N2) genes associated with the codon usage patterns since 1993

This study investigated genetic variations in eight major genes (hemagglutinin, HA; neuraminidase, NA; matrix protein, MP; non-structural protein, NS; nucleoprotein, NP; polymerase, PA; PA basic protein 1, PB1; and PA basic protein 2, PB2) of the influenza A virus subtype H3N2 (A/H3N2) to determine the evolutionary pattern in codon bias. A total of 6,881 sequences isolated between 1993 and 2010 were used. The relative synonymous codon usage (RSCU) and G+C% content at the three codon positions were analyzed by calculating the codon substitution patterns were analyzed by calculating the percentage of synonymously substituted codons (SSCs) and that of codons substituted to the same codon within each synonymous codon group (EMC) between 1993 and subsequent years. In the multivariate analysis of RSCU, we observed directional changes in HA, NA, PB1, and PB2, and these changes were significantly correlated with the variation in the G+C contents at the first (GC1st) and second (GC2nd) codon positions over time. These directional changes in HA and NA appear to affect their antigenic characteristics by altering their SSCs gradually, and NP, PA, PB1, and PB2 genes also continuously changed their substitution patterns by accumulating the decrements of EMC values over a long term. Our findings suggest that, in human populations, A/H3N2 viruses have gradually changed their SSCs in two external genes, HA and NA, and that these accumulated alteration patterns may result in the antigenic changes over time. Moreover, A/H3N2 viruses also appear to change synonymous codon usage patterns in NP, PA, PB1, and PB2 genes by accumulating decrements in EMCs within synonymous codon groups over time.

Epidemiological comparisons of codon usage patterns among HIV-1 isolates from Asia, Europe, Africa and the Americas.

To investigate the genomic properties of HIV-1, we collected 3,081 sequences from the HIV Sequence Database. The sequences were categorized according to sampling region, country, year, subtype, gene name, and sequence and were saved in a database constructed for this study. The relative synonymous codon usage (RSCU) values of matrix, capsid, and gp120 and gp41 genes were calculated using correspondence analysis. The synonymous codon usage patterns based on the geographical regions of African countries showed broad distributions; when all the other regions, including Asia, Europe, and the Americas, were taken into account, the Asian countries tended to be divided into two groups. The sequences were clustered into nine non-CRF subtypes. Among these, subtype C showed the most distinct codon usage pattern. To determine why the codon usage patterns in Asian countries were divided into two groups for four target genes, the sequences of the isolates from the Asian countries were analyzed. As a result, the synonymous codon usage patterns among Asian countries were divided into two groups, the southern Asian countries and the other Asian countries, with subtype 01_AE being the most dominant subtype in southern Asia. In summary, the synonymous codon usage patterns among the individual HIV-1 subtypes reflect genetic variations, and this bioinformatics technique may be useful in conjunction with phylogenetic methods for predicting the evolutionary patterns of pandemic viruses.

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.

Research Article: Computational model for analyzing the evolutionary patterns of the neuraminidase gene of influenza A/H1N1

In this study, we performed computer simulations to evaluate the changes of selection potentials of codons in influenza A/H1N1 from 1999 to 2009. We artificially generated the sequences by using the transition matrices of positively selected codons over time, and their similarities against the database of influenzavirus A genus were determined by BLAST search. This is the first approach to predict the evolutionary direction of influenza A virus (H1N1) by simulating the codon substitutions over time. We observed that the BLAST results showed the high similarities with pandemic influenza A/H1N1 in 2009, suggesting that the classical human-origin influenza A/H1N1 isolated before 2009 might contain some selection potentials of swine-origin viruses. Computer simulations using the time series codon substitution patterns resulted dramatic changes of BLAST results in influenza A/H1N1, providing a possibility of developing a method for predicting the viral evolution in silico.

A Visualization Tool for Calculating the Genetic Substitution Patterns Between Two Different Groups

We developed simulation tool for influenza virus variation (SimFluVar), an analytics software for calculating genomic variation among members of the influenza virus group. This study is related to computational evolutionary biology and evolutionary bioinformatics. SimFluVar is an analytical tool that can be used to calculate codon substitution patterns of viral genes. Designed to compare a large number of nucleotide sequences, SimFluVar provides precise patterns of codon variations between two viral groups, especially for the influenza virus. SimFluVar also provides useful functions, such as editing and visualization of the result matrix. This new tool can be used to analyze codon variation patterns over time as well as to analyze the genomic differences between viruses obtained from different geographical locations. SimFluVar is developed in C++, and Java RCP is used as a distribution package. SimFluVar, including the associated documentation, manuals, and examples, is publicly available at http://lcbb.snu.ac.kr/simfluvar.

Discriminant analysis of prion sequences for prediction of susceptibility

Prion diseases, including ovine scrapie, bovine spongiform encephalopathy (BSE), human kuru and Creutzfeldt–Jakob disease (CJD), originate from a conformational change of the normal cellular prion protein (PrPC) into abnormal protease-resistant prion protein (PrPSc). There is concern regarding these prion diseases because of the possibility of their zoonotic infections across species. Mutations and polymorphisms of prion sequences may influence prion-disease susceptibility through the modified expression and conformation of proteins. Rapid determination of susceptibility based on prion-sequence polymorphism information without complex structural and molecular biological analyses may be possible. Information regarding the effects of mutations and polymorphisms on prion-disease susceptibility was collected based on previous studies to classify the susceptibilities of sequences, whereas the BLOSUM62 scoring matrix and the position-specific scoring matrix were utilised to determine the distance of target sequences. The k-nearest neighbour analysis was validated with cross-validation methods. The results indicated that the number of polymorphisms did not influence prion-disease susceptibility, and three and four k-objects showed the best accuracy in identifying the susceptible group. Although sequences with negative polymorphisms showed relatively high accuracy for determination, polymorphisms may still not be an appropriate factor for estimating variation in susceptibility. Discriminant analysis of prion sequences with scoring matrices was attempted as a possible means of determining susceptibility to prion diseases. Further research is required to improve the utility of this method.

Comparative study of codon substitution patterns in foot-and-mouth disease virus (serotype O)

We compared genetic variations in the VP1 gene of foot-and-mouth disease viruses (FMDVs) isolated since 2000 from various region of the world. We analyzed relative synonymous codon usage (RSCU) and phylogenetic relationship between geographical regions, and calculated the genetic substitution patterns between Korean isolate and those from other countries. We calculated the ratios of synonymously substituted codons (SSC) to all observed substitutions and developed a new analytical parameter, EMC (the ratio of exact matching codons within each synonymous substitution group) to investigate more detailed substitution patterns within each synonymous codon group. We observed that FMDVs showed distinct RSCU patterns according to phylogenetic relationships in the same serotype (serotype O). Moreover, while the SSC and EMC values of FMDVs decreased according to phylogenetic distance, G + C composition at the third codon position was strictly conserved. Although there was little variation among the SSC values of 18 amino acids, more dynamic differences were observed in EMC values. The EMC values of 4- and 6-fold degenerate amino acids showed significantly lower values while most 2-fold degenerate amino acids showed no significant difference. Our findings suggest that different EMC patterns among the 18 amino acids might be an important factor in determining the direction of evolution in FMDV.

Comparative study of synonymous codon usage variations between the nucleocapsid and spike genes of coronavirus, and C-type lectin domain genes of human and mouse

Coronaviruses (CoVs) are single-stranded RNA viruses which contain the largest RNA genomes, and severe acute respiratory syndrome coronavirus (SARS-CoV), a newly found group 2 CoV, emerged as infectious disease with high mortality rate. In this study, we compared the synonymous codon usage patterns between the nucleocapsid and spike genes of CoVs, and C-type lectin domain (CTLD) genes of human and mouse on the codon basis. Findings indicate that the nucleocapsid genes of CoVs were affected from the synonymous codon usage bias than spike genes, and the CTLDs of human and mouse partially overlapped with the nucleocapsid genes of CoVs. In addition, we observed that CTLDs which showed the similar relative synonymous codon usage (RSCU) patterns with CoVs were commonly derived from the human chromosome 12, and mouse chromosome 6 and 12, suggesting that there might be a specific genomic region or chromosomes which show a more similar synonymous codon usage pattern with viral genes. Our findings contribute to developing the codon-optimization method in DNA vaccines, and further study is needed to determine a specific correlation between the codon usage patterns and the chromosomal locations in higher organisms.

SimFlu: A simulation tool for predicting the variation pattern of influenza A virus

Since the first pandemic outbreak of avian influenza A virus (H5N1 subtype) in 1997, the National Center for Biotechnology Information (NCBI) has provided a large number of influenza virus sequences with well-organized annotations. Using the time-series sequences of influenza A viruses, we developed a simulation tool for influenza virus, named SimFlu, to predict possible future variants of influenza viruses. SimFlu can create variants from a seed nucleotide sequence of influenza A virus using the codon variation parameters included in the SimFlu package. The SimFlu library provides pre-calculated codon variation parameters for the H1N1, H3N2, and H5N1 subtypes of influenza A virus isolated from 2000 to 2011, allowing the users to simulate their own nucleotide sequences by selecting their preferred parameter options. SimFlu supports three operating systems - Windows, Linux, and Mac OS X. SimFlu is publicly available at http://lcbb.snu.ac.kr/simflu.