Shigehiko Kanaya

Global landscape of protein complexes in the yeast Saccharomyces cerevisiae

Identification of protein–protein interactions often provides insight into protein function, and many cellular processes are performed by stable protein complexes. We used tandem affinity purification to process 4,562 different tagged proteins of the yeast Saccharomyces cerevisiae. Each preparation was analysed by both matrix-assisted laser desorption/ionization–time of flight mass spectrometry and liquid chromatography tandem mass spectrometry to increase coverage and accuracy. Machine learning was used to integrate the mass spectrometry scores and assign probabilities to the protein–protein interactions. Among 4,087 different proteins identified with high confidence by mass spectrometry from 2,357 successful purifications, our core data set (median precision of 0.69) comprises 7,123 protein–protein interactions involving 2,708 proteins. A Markov clustering algorithm organized these interactions into 547 protein complexes averaging 4.9 subunits per complex, about half of them absent from the MIPS database, as well as 429 additional interactions between pairs of complexes. The data (all of which are available online) will help future studies on individual proteins as well as functional genomics and systems biology.

MassBank: a public repository for sharing mass spectral data for life sciences.

MassBank is the first public repository of mass spectra of small chemical compounds for life sciences (<3000 Da). The database contains 605 electron-ionization mass spectrometry (EI-MS), 137 fast atom bombardment MS and 9276 electrospray ionization (ESI)-MS(n) data of 2337 authentic compounds of metabolites, 11 545 EI-MS and 834 other-MS data of 10,286 volatile natural and synthetic compounds, and 3045 ESI-MS(2) data of 679 synthetic drugs contributed by 16 research groups (January 2010). ESI-MS(2) data were analyzed under nonstandardized, independent experimental conditions. MassBank is a distributed database. Each research group provides data from its own MassBank data servers distributed on the Internet. MassBank users can access either all of the MassBank data or a subset of the data by specifying one or more experimental conditions. In a spectral search to retrieve mass spectra similar to a query mass spectrum, the similarity score is calculated by a weighted cosine correlation in which weighting exponents on peak intensity and the mass-to-charge ratio are optimized to the ESI-MS(2) data. MassBank also provides a merged spectrum for each compound prepared by merging the analyzed ESI-MS(2) data on an identical compound under different collision-induced dissociation conditions. Data merging has significantly improved the precision of the identification of a chemical compound by 21-23% at a similarity score of 0.6. Thus, MassBank is useful for the identification of chemical compounds and the publication of experimental data.

Sequence-specific error profile of Illumina sequencers

We identified the sequence-specific starting positions of consecutive miscalls in the mapping of reads obtained from the Illumina Genome Analyser (GA). Detailed analysis of the miscall pattern indicated that the underlying mechanism involves sequence-specific interference of the base elongation process during sequencing. The two major sequence patterns that trigger this sequence-specific error (SSE) are: (i) inverted repeats and (ii) GGC sequences. We speculate that these sequences favor dephasing by inhibiting single-base elongation, by: (i) folding single-stranded DNA and (ii) altering enzyme preference. This phenomenon is a major cause of sequence coverage variability and of the unfavorable bias observed for population-targeted methods such as RNA-seq and ChIP-seq. Moreover, SSE is a potential cause of false single-nucleotide polymorphism (SNP) calls and also significantly hinders de novo assembly. This article highlights the importance of recognizing SSE and its underlying mechanisms in the hope of enhancing the potential usefulness of the Illumina sequencers.

Development and implementation of an algorithm for detection of protein complexes in large interaction networks.

BackgroundAfter complete sequencing of a number of genomes the focus has now turned to proteomics. Advanced proteomics technologies such as two-hybrid assay, mass spectrometry etc. are producing huge data sets of protein-protein interactions which can be portrayed as networks, and one of the burning issues is to find protein complexes in such networks. The enormous size of protein-protein interaction (PPI) networks warrants development of efficient computational methods for extraction of significant complexes.ResultsThis paper presents an algorithm for detection of protein complexes in large interaction networks. In a PPI network, a node represents a protein and an edge represents an interaction. The input to the algorithm is the associated matrix of an interaction network and the outputs are protein complexes. The complexes are determined by way of finding clusters, i. e. the densely connected regions in the network. We also show and analyze some protein complexes generated by the proposed algorithm from typical PPI networks of Escherichia coli and Saccharomyces cerevisiae. A comparison between a PPI and a random network is also performed in the context of the proposed algorithm.ConclusionThe proposed algorithm makes it possible to detect clusters of proteins in PPI networks which mostly represent molecular biological functional units. Therefore, protein complexes determined solely based on interaction data can help us to predict the functions of proteins, and they are also useful to understand and explain certain biological processes.

Studies of codon usage and tRNA genes of 18 unicellular organisms and quantification of Bacillus subtilis tRNAs: gene expression level and species-specific diversity of codon usage based on multivariate analysis

We examined codon usage in Bacillus subtilis genes by multivariate analysis, quantified its cellular levels of individual tRNAs, and found a clear constraint of tRNA contents on synonymous codon choice. Individual tRNA levels were proportional to the copy number of the respective tRNA genes. This indicates that the tRNA gene copy number is an important factor to determine in cellular tRNA levels, which is common with Escherichia coli and yeast Saccharomyces cerevisiae. Codon usage in 18 unicellular organisms whose genomes have been sequenced completely was analyzed and compared with the composition of tRNA genes. The 18 organisms are as follows: yeast S. cerevisiae, Aquifex aeolicus, Archaeoglobus fulgidus, B. subtilis, Borrelia burgdorferi, Chlamydia trachomatis, E. coli, Haemophilus influenzae, Helicobacterpylori, Methanococcusjannaschii, Methanobacterium thermoautotrophicum, Mycobacterium tuberculosis, Mycoplasma genitalium, Mycoplasma pneumoniae, Pyrococcus horikoshii, Rickettsia prowazekii, Synechocystis sp., and Treponema pallidum. Codons preferred in highly expressed genes were related to the codons optimal for the translation process, which were predicted by the composition of isoaccepting tRNA genes. Genes with specific codon usage are discussed in connection with their evolutionary origins and functions. The origin and terminus of replication could be predicted on the basis of codon usage when the usage was analyzed relative to the transcription direction of individual genes.

Transcriptome analysis of all two-component regulatory system mutants of Escherichia coli K-12

We have systematically examined the mRNA profiles of 36 two‐component deletion mutants, which include all two‐component regulatory systems of Escherichia coli, under a single growth condition. DNA microarray results revealed that the mutants belong to one of three groups based on their gene expression profiles in Luria–Bertani broth under aerobic conditions: (i) those with no or little change; (ii) those with significant changes; and (iii) those with drastic changes. Under these conditions, the anaeroresponsive ArcB/ArcA system, the osmoresponsive EnvZ/OmpR system and the response regulator UvrY showed the most drastic changes. Cellular functions such as flagellar synthesis and expression of the RpoS regulon were affected by multiple two‐component systems. A high correlation coefficient of expression profile was found between several two‐component mutants. Together, these results support the view that a network of functional interactions, such as cross‐regulation, exists between different two‐component systems. The compiled data are avail‐able at our website (http:ecoli.aist‐nara.ac.jpxpanalysis 2components).

Codon usage and tRNA genes in eukaryotes: correlation of codon usage diversity with translation efficiency and with CG-dinucleotide usage as assessed by multivariate analysis.

Abstract. The species-specific diversity of codon usage in five eukaryotes (Schizosaccharomyces pombe, Caenorhabditis elegans, Drosophila melanogaster, Xenopus laevis, and Homo sapiens) was investigated with principal component analysis. Optimal codons for translation were predicted on the basis of tRNA-gene copy numbers. Highly expressed genes, such as those encoding ribosomal proteins and histones in S. pombe, C. elegans, and D. melanogaster, have biased patterns of codon usage which have been observed in a wide range of unicellular organisms. In S. pombe and C. elegans, codons contributing positively to the principal component with the largest variance (Z1-parameter) corresponded to the optimal codons which were predicted on the basis of tRNA gene numbers. In D. melanogaster, this correlation was less evident, and the codons contributing positively to the Z1-parameter corresponded primarily to codons with a C or G in the codon third position. In X. laevis and H. sapiens, codon usage in the genes encoding ribosomal proteins and histones was not significantly biased, suggesting that the primary factor influencing codon-usage diversity in these species is not translation efficiency. Codon-usage diversity in these species is known to reflect primarily isochore structures. In the present study, the second additional factor was explained by the level of use of codons containing CG-dinucleotides, and this is discussed with respect to transcription regulation via methylation of CG-dinucleotides, which is observed in mammalian genomes.

The R‐type pyocin of Pseudomonas aeruginosa is related to P2 phage, and the F‐type is related to lambda phage

Pseudomonas aeruginosa produces three types of bacteriocins: R‐, F‐ and S‐type pyocins. The S‐type pyocin is a colicin‐like protein, whereas the R‐type pyocin resembles a contractile but non‐flexible tail structure of bacteriophage, and the F‐type a flexible but non‐contractile one. As genetically related phages exist for each type, these pyocins have been thought to be variations of defective phage. In the present study, the nucleotide sequence of R2 pyocin genes, along with those for F2 pyocin, which are located downstream of the R2 gene cluster on the chromosome of P. aeruginosa PAO1, was analysed in order to elucidate the relationship between the pyocins and bacteriophages. The results clearly demonstrated that the R‐type pyocin is derived from a common ancestral origin with P2 phage and the F‐type from λ phage. This notion was supported by identification of a lysis gene cassette similar to those for bacteriophages. The gene organization of the R2 and F2 pyocin gene cluster, however, suggested that both pyocins are not simple defective phages, but are phage tails that have been evolutionarily specialized as bacteriocins. A systematic polymerase chain reaction (PCR) analysis of P. aeruginosa strains that produce various subtypes of R and F pyocins revealed that the genes for every subtype are located between trpE and trpG in the same or very similar gene organization as for R2 and F2 pyocins, but with alterations in genes that determine the receptor specificity.

The complete nucleotide sequence of φCTX, a cytotoxin‐converting phage of Pseudomonas aeruginosa: implications for phage evolution and horizontal gene transfer via bacteriophages

φCTX is a cytotoxin‐converting phage isolated from Pseudomonas aeruginosa. In this study, we determined the complete nucleotide sequence of the φCTX phage genome. The precise genome size was 35 538 bp with 21 base 5′‐extruding cohesive ends. Forty‐seven open reading frames (ORFs) were identified on the φCTX genome, including two previously identified genes, ctx and int. Among them, 15 gene products were identified in the phage particle by protein microsequencing. The most striking feature of the φCTX genome was an extensive homology with the coliphage P2 and P2‐related phages; more than half of the ORFs (25 ORFs) had marked homology to P2 genes with 28.9–65.8% identity. The gene arrangement on the genome was also highly conserved for the two phages, although the G+C content and codon usage of most φCTX genes were similar to those of the host P. aeruginosa chromosome. In addition, φCTX was found to share several common features with P2, including the morphology, non‐inducibility, use of lipopolysaccharide core oligosaccharide as receptor and Ca2+‐dependent receptor binding. These findings indicate that φCTX is a P2‐like phage well adapted to P. aeruginosa, and provide clear evidence of the intergeneric spread and evolution of bacteriophages. Furthermore, comparative analysis of genome structures of φCTX, P2 and other P2 relatives revealed the presence of several hot‐spots where foreign DNAs, including the cytotoxin gene, were inserted. They appear to be deeply concerned in the acquisition of various genes that are horizontally transferred by bacteriophage infection.

Enhanced Recombinant Protein Productivity by Genome Reduction in Bacillus subtilis

The emerging field of synthetic genomics is expected to facilitate the generation of microorganisms with the potential to achieve a sustainable society. One approach towards this goal is the reduction of microbial genomes by rationally designed deletions to create simplified cells with predictable behavior that act as a platform to build in various genetic systems for specific purposes. We report a novel Bacillus subtilis strain, MBG874, depleted of 874 kb (20%) of the genomic sequence. When compared with wild-type cells, the regulatory network of gene expression of the mutant strain is reorganized after entry into the transition state due to the synergistic effect of multiple deletions, and productivity of extracellular cellulase and protease from transformed plasmids harboring the corresponding genes is remarkably enhanced. To our knowledge, this is the first report demonstrating that genome reduction actually contributes to the creation of bacterial cells with a practical application in industry. Further systematic analysis of changes in the transcriptional regulatory network of MGB874 cells in relation to protein productivity should facilitate the generation of improved B. subtilis cells as hosts of industrial protein production.