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1.  Comparative genomic analyses of Streptococcus mutans provide insights into chromosomal shuffling and species-specific content 
BMC Genomics  2009;10:358.
Streptococcus mutans is the major pathogen of dental caries, and it occasionally causes infective endocarditis. While the pathogenicity of this species is distinct from other human pathogenic streptococci, the species-specific evolution of the genus Streptococcus and its genomic diversity are poorly understood.
We have sequenced the complete genome of S. mutans serotype c strain NN2025, and compared it with the genome of UA159. The NN2025 genome is composed of 2,013,587 bp, and the two strains show highly conserved core-genome. However, comparison of the two S. mutans strains showed a large genomic inversion across the replication axis producing an X-shaped symmetrical DNA dot plot. This phenomenon was also observed between other streptococcal species, indicating that streptococcal genetic rearrangements across the replication axis play an important role in Streptococcus genetic shuffling. We further confirmed the genomic diversity among 95 clinical isolates using long-PCR analysis. Genomic diversity in S. mutans appears to occur frequently between insertion sequence (IS) elements and transposons, and these diversity regions consist of restriction/modification systems, antimicrobial peptide synthesis systems, and transporters. S. mutans may preferentially reject the phage infection by clustered regularly interspaced short palindromic repeats (CRISPRs). In particular, the CRISPR-2 region, which is highly divergent between strains, in NN2025 has long repeated spacer sequences corresponding to the streptococcal phage genome.
These observations suggest that S. mutans strains evolve through chromosomal shuffling and that phage infection is not needed for gene acquisition. In contrast, S. pyogenes tolerates phage infection for acquisition of virulence determinants for niche adaptation.
PMCID: PMC2907686  PMID: 19656368
2.  Pseudocounts for transcription factor binding sites 
Nucleic Acids Research  2008;37(3):939-944.
To represent the sequence specificity of transcription factors, the position weight matrix (PWM) is widely used. In most cases, each element is defined as a log likelihood ratio of a base appearing at a certain position, which is estimated from a finite number of known binding sites. To avoid bias due to this small sample size, a certain numeric value, called a pseudocount, is usually allocated for each position, and its fraction according to the background base composition is added to each element. So far, there has been no consensus on the optimal pseudocount value. In this study, we simulated the sampling process by artificially generating binding sites based on observed nucleotide frequencies in a public PWM database, and then the generated matrix with an added pseudocount value was compared to the original frequency matrix using various measures. Although the results were somewhat different between measures, in many cases, we could find an optimal pseudocount value for each matrix. These optimal values are independent of the sample size and are clearly correlated with the entropy of the original matrices, meaning that larger pseudocount vales are preferable for less conserved binding sites. As a simple representative, we suggest the value of 0.8 for practical uses.
PMCID: PMC2647310  PMID: 19106141

Results 1-2 (2)