Papers - Tomita, Masaru

Genomic heterogeneity in a natural archaeal population suggests a model of tRNA gene disruption

Sugahara J, Fujishima K, Nunoura T, Takaki Y, Takami H, Takai K, Tomita M, Kanai A.

PLoS ONE (PLoS ONE)  7 ( 3 ) 1-8 2012.03

Research paper (scientific journal), Joint Work

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Understanding the mechanistic basis of the disruption of tRNA genes, as manifested in the intron-containing and split tRNAs found in Archaea, will provide considerable insight into the evolution of the tRNA molecule. However, the evolutionary processes underlying these disruptions have not yet been identified. Previously, a composite genome of the deep-branching archaeon Caldiarchaeum subterraneum was reconstructed from a community genomic library prepared from a C. subterraneum-dominated microbial mat. Here, exploration of tRNA genes from the library reveals that there are at least three types of heterogeneity at the tRNA Thr(GGU) gene locus in the Caldiarchaeum population. All three involve intronic gain and splitting of the tRNA gene. Of two fosmid clones found that encode tRNA Thr(GGU), one (tRNA Thr-I) contains a single intron, whereas another (tRNA Thr-II) contains two introns. Notably, in the clone possessing tRNA Thr-II, a 5′ fragment of the tRNA Thr-I (tRNA Thr-F) gene was observed 1.8-kb upstream of tRNA Thr-II. The composite genome contains both tRNA Thr-II and tRNA Thr-F, although the loci are >500 kb apart. Given that the 1.8-kb sequence flanked by tRNA Thr-F and tRNA Thr-II is predicted to encode a DNA recombinase and occurs in six regions of the composite genome, it may be a transposable element. Furthermore, its dinucleotide composition is most similar to that of the pNOB8-type plasmid, which is known to integrate into archaeal tRNA genes. Based on these results, we propose that the gain of the tRNA intron and the scattering of the tRNA fragment occurred within a short time frame via the integration and recombination of a mobile genetic element. © 2012 Sugahara et al.

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Bioinformatics Tools for Mass Spectroscopy-Based Metabolomic Data Processing and Analysis

Sugimoto, Masahiro; Kawakami, Masato; Robert, Martin; Soga, Tomoyoshi; Tomita, Masaru

Current Bioinformatics (Current Bioinformatics)  7 ( 1 ) 96-108 - 108 2012.03

Research paper (scientific journal), Joint Work,  ISSN  15748936

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Biological systems are increasingly being studied in a holistic manner, using omics approaches, to provide quantitative and qualitative descriptions of the diverse collection of cellular components. Among the omics approaches, metabolomics, which deals with the quantitative global profiling of small molecules or metabolites, is being used extensively to explore the dynamic response of living systems, such as organelles, cells, tissues, organs and whole organisms, under diverse physiological and pathological conditions. This technology is now used routinely in a number of applications, including basic and clinical research, agriculture, microbiology, food science, nutrition, pharmaceutical research, environmental science and the development of biofuels. Of the multiple analytical platforms available to perform such analyses, nuclear magnetic resonance and mass spectrometry have come to dominate, owing to the high resolution and large datasets that can be generated with these techniques. The large multidimensional datasets that result from such studies must be processed and analyzed to render this data meaningful. Thus, bioinformatics tools are essential for the efficient processing of huge datasets, the characterization of the detected signals, and to align multiple datasets and their features. This paper provides a state-of-the-art overview of the data processing tools available, and reviews a collection of recent reports on the topic. Data conversion, pre-processing, alignment, normalization and statistical analysis are introduced, with their advantages and disadvantages, and comparisons are made to guide the reader. © 2012 Bentham Science Publishers.

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Measures of Compositional Strand Bias Related to Replication Machinery and its Applications

Arakawa K., Tomita M.

Current Genomics (Current Genomics)  13 ( 1 ) 4 - 15 2012.03

ISSN  13892029

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The compositional asymmetry of complementary bases in nucleotide sequences implies the existence of a mutational or selectional bias in the two strands of the DNA duplex, which is commonly shaped by strand-specific mechanisms in transcription or replication. Such strand bias in genomes, frequently visualized by GC skew graphs, is used for the computational prediction of transcription start sites and replication origins, as well as for comparative evolutionary genomics studies. The use of measures of compositional strand bias in order to quantify the degree of strand asymmetry is crucial, as it is the basis for determining the applicability of compositional analysis and comparing the strength of the mutational bias in different biological machineries in various species. Here, we review the measures of strand bias that have been proposed to date, including the ΔGC skew, the B 1 index, the predictability score of linear discriminant analysis for gene orientation, the signal-to-noise ratio of the oligonucleotide bias, and the GC skew index. These measures have been predominantly designed for and applied to the analysis of replication-related mutational processes in prokaryotes, but we also give research examples in eukaryotes. ©2012 Bentham Science Publishers.

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Metatranscriptomic Analysis of Microbes in an Oceanfront Deep-Subsurface Hot Spring Reveals Novel Small RNAs and Type-Specific tRNA Degradation

Murakami S., Fujishima K., Tomita M., Kanai A.

Applied and Environmental Microbiology (Applied and Environmental Microbiology)  78 ( 4 ) 1015-1022 - 1022 2012.02

Research paper (scientific journal), Joint Work,  ISSN  00992240

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Studies of small noncoding RNAs (sRNAs) have been conducted predominantly using culturable organisms, and the acquisition of further information about sRNAs from global environments containing uncultured organisms now is very important. In this study, hot spring water (57°C, pH 8.1) was collected directly from the underground environment at depths of 250 to 1,000min Yunohama, Japan, and small RNA sequences obtained from the environment were analyzed. A phylogenetic analysis of both archaeal and bacterial 16S rRNA gene sequences was conducted, and the results suggested the presence of unique species in the environment, corresponding to the Archaeal Richmond Mine Acidophilic Nanoorganisms (ARMAN) group and three new Betaproteobacteria. A metatranscriptomic analysis identified 64,194 (20,057 nonredundant) cDNA sequences. Of these cDNAs, 90% were either tRNAs, tRNA fragments, rRNAs, or rRNA fragments, whereas 2,181 reads (10%) were classified as previously uncharacterized putative candidate sRNAs. Among these, 15 were particularly abundant, 14 of which showed no sequence similarity to any known noncoding RNA, and at least six of which form very stable RNA secondary structures. The analysis of a large number of tRNA fragments suggested that unique relationships exist between the anticodons of the tRNAs and the sites of tRNA degradation. Previous bacterial tRNA degradation studies have been limited to specific organisms, such as Escherichia coli and Streptomyces coelicolor, and the current results suggest that specific tRNA decay occurs more frequently than previously expected. © 2012, American Society for Microbiology.

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MMMDB: Mouse multiple tissue metabolome database

Sugimoto M., Ikeda S., Niigata K., Tomita M., Sato H., Soga T.

Nucleic Acids Research (Nucleic Acids Research)  40 ( D1 ) D809 - 14 2012.01

ISSN  03051048

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The Mouse Multiple Tissue Metabolome Database (MMMDB) provides comprehensive and quantitative metabolomic information for multiple tissues from single mice. Manually curated databases that integrate literature-based individual metabolite information have been available so far. However, data sets on the absolute concentration of a single metabolite integrated from multiple resources are often difficult to be used when different metabolomic studies are compared because the relative balance of the multiple metabolite concentrations in the metabolic pathways as a snapshot of a dynamic system is more important than the absolute concentration of a single metabolite. We developed MMMDB by performing non-targeted analyses of cerebra, cerebella, thymus, spleen, lung, liver, kidney, heart, pancreas, testis and plasma using capillary electrophoresis time-of-flight mass spectrometry and detected 428 non-redundant features from which 219 metabolites were successfully identified. Quantified concentrations of the individual metabolites and the corresponding processed raw data; for example, the electropherograms and mass spectra with their annotations, such as isotope and fragment information, are stored in the database. MMMDB is designed to normalize users' data, which can be submitted online and used to visualize overlaid electropherograms. Thus, MMMDB allows newly measured data to be compared with the other data in the database. MMMDB is available at: http:// mmmdb.iab.keio.ac.jp. © The Author(s) 2011.

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Time-structure of the yeast metabolism in vivo

Sasidharan K., Tomita M., Aon M., Lloyd D., Murray D.B.

Advances in Experimental Medicine and Biology  2012

ISSN  00652598

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Peptide Identification by Searching Large-Scale Tandem Mass Spectra against Large Databases: Bioinformatics Methods in Proteogenomics

Helmy, M, Tomita M, Ishihama Y

Genes, Genome and Genomics 6   76-85 2012

Research paper (scientific journal), Joint Work, Accepted

Profiling of the charged metabolites of traditional herbal medicines using capillary electrophoresis time-of-flight mass spectrometry

Iino¸ K., Sugimoto¸ M., Soga¸ T. and Tomita, M.

Metabolomics 8 ( 1 ) 99-108 - 108 2012

Research paper (scientific journal), Joint Work,  ISSN  15733882

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The quantification of a small number of bioactive components in herbal medicines is often inadequate when attempting to elucidate a medicine's biological effects. Despite rapid advances in analytical technologies, obtaining comprehensive metabolomic profiles of herbal medicines remains difficult, due to the complexity of natural product mixtures. Toki-Shakuyaku-San is a Chinese medicine used widely to treat gynecological and obstetric disorders, such as infertility, dysmenorrhea, toxemia during pregnancy and neural dysfunction. It consists of Angelica acutiloba Radix (Toki), Cnidium officinale Rhizoma (Senkyu), Paeonia lactiflora Radix (Shakuyaku), Atractylodes lancea Rhizoma (Sojutsu), Alisma orientale Rhizoma (Takusha) and Poria cocos Hoelen (Bukuryo). To elucidate the composition of these herbal medicines individually, we conducted non-targeted profiling analyses of extracts of these herbs using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS), which allows the simultaneous quantification of hundreds of charged metabolites. In total, 737 ± 183. 1 (average ± SD) metabolite-derived features were observed, and of these, 119 metabolites were identified. Score plots of principal component analysis (PCA) showed a clear cluster including Shakuyaku, Bukuryo, and Sojutsu, while the other three herbs were distributed over PCA spaces. Loading plots revealed that amino acids and shikimate-derived alkaloids were the predominant metabolite constituents. Hierarchical clustering analysis revealed that few clusters overlapped in the herbal medicines tested. This report is the first demonstration of the characterization of a herbal medicine using large-scale metabolomic analysis, which is complementary to traditional quality control methods. © 2011 Springer Science+Business Media, LLC.

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Validation of Bacterial Replication Termination Models Using Simulation of Genomic Mutations

Kono, N., Arakawa, K.,and Tomita, M.

PLoS ONE (PLoS ONE)  7 ( 4 ) e34526 2012

Research paper (scientific journal), Joint Work, Accepted

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In bacterial circular chromosomes and most plasmids, the replication is known to be terminated when either of the following occurs: the forks progressing in opposite directions meet at the distal end of the chromosome or the replication forks become trapped by Tus proteins bound to Ter sites. Most bacterial genomes have various polarities in their genomic structures. The most notable feature is polar genomic compositional asymmetry of the bases G and C in the leading and lagging strands, called GC skew. This asymmetry is caused by replication-associated mutation bias, and this "footprint" of the replication machinery suggests that, in contrast to the two known mechanisms, replication termination occurs near the chromosome dimer resolution site dif. To understand this difference between the known replication machinery and genomic compositional bias, we undertook a simulation study of genomic mutations, and we report here how different replication termination models contribute to the generation of replication-related genomic compositional asymmetry. Contrary to naive expectations, our results show that a single finite termination site at dif or at the GC skew shift point is not sufficient to reconstruct the genomic compositional bias as observed in published sequences. The results also show that the known replication mechanisms are sufficient to explain the position of the GC skew shift point. © 2012 Kono et al.

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Nematode-specific tRNAs that decode an alternative genetic code for leucine

Hamashima, K., Fujishima, K., Masuda, T., Sugahara, J., Tomita, M. and Kanai, A.

Nucleic Acids Research (Nucleic Acids Research)  40 ( 8 ) 3653-3662 - 3662 2012

Research paper (scientific journal), Joint Work, Accepted,  ISSN  03051048

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Class II transfer RNAs (tRNAs), including tRNALeu and tRNA Ser, have an additional stem and loop structure, the long variable arm (V-arm). Here, we describe Class II tRNAs with a unique anticodon corresponding to neither leucine nor serine. Because these tRNAs are specifically conserved among the nematodes, we have called them 'nematode-specific V-arm-containing tRNAs' (nev-tRNAs). The expression of nev-tRNA genes in Caenorhabditis elegans was confirmed experimentally. A comparative sequence analysis suggested that the nev-tRNAs derived phylogenetically from tRNALeu. In vitro aminoacylation assays showed that nev-tRNAGly and nev-tRNAIle are only charged with leucine, which is inconsistent with their anticodons. Furthermore, the deletion and mutation of crucial determinants for leucylation in nev-tRNA led to a marked loss of activity. An in vitro translation analysis showed that nev-tRNA Gly decodes GGG as leucine instead of the universal glycine code, indicating that nev-tRNAs can be incorporated into ribosomes and participate in protein biosynthesis. Our findings provide the first example of unexpected tRNAs that do not consistently obey the general translation rules for higher eukaryotes. © 2011 The Author(s).

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The role of Staphylococcal enterotoxin in atopic keratoconjunctivitis and corneal ulceration

Fujishima, H., Okada, N., Dogru., M., Baba, F., Tomita, M., Abe, J., Matsumoto, K. and Saito, H.

Allergy 67 ( 6 ) 799-803 - 803 2012

Research paper (scientific journal), Joint Work, Accepted,  ISSN  01054538

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Background Patients with atopic eczema frequently experience colonization with Staphylococcus aureus that is directly correlated with the eczema severity. We hypothesized that S. aureus-secreted enterotoxins (SE) are involved in the pathophysiology of atopic keratoconjunctivitis (AKC). Methods A total of 45 subjects (18 with AKC, nine vernal keratoconjunctivitis (VKC), eight seasonal allergic conjunctivitis (SAC), and ten healthy volunteers) were enrolled. Slit lamp examinations, including fluorescein staining, were performed. Scraped samples were collected from the upper tarsal conjunctiva, lower conjunctival sacs, and the skin around the eyelid margins. Superantigen (SAg) genes were detected using polymerase chain reaction (PCR). Results Among 45 cases, S. aureus was detected significantly more in AKC patients than VKC patients (P = 0.026), SAC patients (P = 0.0003), and healthy volunteers (P = 0.0001). SAg genes were detected in 11 patients. SEB (2/11), SEG (8/11), and SEI (8/11) were detected, but no other SE. There was a significant difference in SE detection between AKC and SAC patients (P = 0.03). In severe types of ocular allergic disease such as AKC and VKC (N = 27), SE was detected in six of ten patients with corneal ulcers and two of 17 patients without corneal ulcers. SE was detected in significantly more patients with corneal ulcers (P = 0.025). Conclusions In patients with AKC, S. aureus and SE were detected more frequently compared with other patients and healthy volunteers, especially in association with corneal ulceration suggesting a role of SE. So far, it is unknown whether SE leads to tissue damage of the cornea by initiating an immune response or has direct toxic effects. © 2012 John Wiley & Sons A/S.

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Systems Biology, Metabolomics, and Cancer Metabolism

Tomita, M.,Kami, K.

Science 336   990-991 2012

Research paper (scientific journal), Joint Work, Accepted

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The third plasmid pVV8 from Thermus thermophilus HB8: isolation, characterization, and sequence determination

Ohtani., N., Tomita, M. and Itaya, M.

Extremophiles (Extremophiles)  16 ( 2 ) 237-44 - 244 2012

Research paper (scientific journal), Joint Work,  ISSN  14310651

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The extremely thermophilic bacterium Thermus thermophilus is a model organism for structural biology and systems biology, and the so-called "Structural and Functional Whole-Cell Project for T. thermophilus HB8" is in progress. The released genomic sequence of the strain HB8 is composed of chromosome, pTT27 megaplasmid, and pTT8 plasmid. In this paper, however, a third plasmid was demonstrated and its sequence was determined. Although this plasmid pVV8 had been reported before, limited information and an unfortunate dropout in the substrain, whose genomic sequence was determined, would have prevented the plasmid from coming to public attention. The intrinsic circular plasmid, which was estimated to be six to ten copies in a cell, is 81151 bp and its G + C content is 68%. Among the identified 91 ORFs, a single gene has been experimentally analyzed before and is known as xylose isomerase. The phnCDEGHIJKLMX operon related to phosphonate metabolism, alkaline phosphatase, putative transcriptional regulators, several sets of toxin-antitoxin system, and transposase-like ORFs are also encoded on the pVV8 plasmid. Although association with cell aggregation was the one phenotypic characteristic of the plasmid that had been reported, it was never confirmed. Comparison of T. thermophilus HB8 strains suggests that the pVV8 is nonessential for growth. © 2011 Springer.

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Prediction of axillary lymph node metastasis in primary breast cancer patients using a decision tree-based model

Takada, M., Sugimoto, M., Naito, Y., Moon, H., G., Han, W., Noh, D., Y., Kondo, M., Kuroi, K., Sasano, H., Inamoto, T., Tomita, M., and Toi, M.

BMC Medical Informatics and Decision Making (BMC Medical Informatics and Decision Making)  12 ( 1 ) 54 2012

Research paper (scientific journal), Joint Work, Accepted

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Background: The aim of this study was to develop a new data-mining model to predict axillary lymph node (AxLN) metastasis in primary breast cancer. To achieve this, we used a decision tree-based prediction method-The alternating decision tree (ADTree). Methods: Clinical datasets for primary breast cancer patients who underwent sentinel lymph node biopsy or AxLN dissection without prior treatment were collected from three institutes (institute A, n = 148; institute B, n = 143; institute C, n = 174) and were used for variable selection, model training and external validation, respectively. The models were evaluated using area under the receiver operating characteristics (ROC) curve analysis to discriminate node-positive patients from node-negative patients. Results: The ADTree model selected 15 of 24 clinicopathological variables in the variable selection dataset. The resulting area under the ROC curve values were 0.770 [95% confidence interval (CI), 0.689-0.850] for the model training dataset and 0.772 (95% CI: 0.689-0.856) for the validation dataset, demonstrating high accuracy and generalization ability of the model. The bootstrap value of the validation dataset was 0.768 (95% CI: 0.763-0.774). Conclusions: Our prediction model showed high accuracy for predicting nodal metastasis in patients with breast cancer using commonly recorded clinical variables. Therefore, our model might help oncologists in the decision-making process for primary breast cancer patients before starting treatment. © 2012 Takada et al.; licensee BioMed Central Ltd.

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Rapid DNA, RNA and protein extraction protocols optimized for slow continuously growing yeast cultures

Sasidharan, K., Amariei, C., Tomita, M., and Murray, D, B.

Yeast (Yeast)  29 ( 8 ) 311-22 - 322 2012

Research paper (scientific journal), Joint Work, Accepted,  ISSN  0749503X

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Conventional extraction protocols for yeast have been developed for relatively rapid-growing low cell density cultures of laboratory strains and often do not have the integrity for frequent sampling of cultures. Therefore, these protocols are usually inefficient for cultures under slow growth conditions or of non-laboratory strains. We have developed a combined mechanical and chemical disruption procedure using vigorous bead-beating that can consistently disrupt yeast cells (> 95%), irrespective of cell cycle and metabolic state. Using this disruption technique coupled with quenching, we have developed DNA, RNA and protein extraction protocols that are optimized for a large number of samples from slow-growing high-density industrial yeast cultures. Additionally, sample volume, the use of expensive reagents/enzymes, handling times and incubations were minimized. We have tested the reproducibility of our methods using triplicate/time-series extractions and compared these with commonly used protocols or commercially available kits. Moreover, we utilized a simple flow-cytometric approach to estimate the mitochondrial DNA copy number. Based on the results, our methods have shown higher reproducibility, yield and quality. © 2012 John Wiley & Sons, Ltd.

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Predictions of the pathological response to neoadjuvant chemotherapy in patients with primary breast cancer using a data mining technique

Takada, M., Sugimoto, M., Ohno, S., Kuroi, K., N. Sato , H., Bando, H., Masuda, N., Iwata, H., Kondo, M., Sasano, H., Chow, L., W., C., Inamoto , T., Naito, Y., Tomita, M. and Toi, M.

Breast Cancer Research and Treatment 134 ( 2 ) 661-70 - 670 2012

Research paper (scientific journal), Joint Work, Accepted,  ISSN  01676806

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Nomogram, a standard technique that utilizes multiple characteristics to predict efficacy of treatment and likelihood of a specific status of an individual patient, has been used for prediction of response to neoadjuvant chemotherapy (NAC) in breast cancer patients. The aim of this study was to develop a novel computational technique to predict the pathological complete response (pCR) to NAC in primary breast cancer patients. A mathematical model using alternating decision trees, an epigone of decision tree, was developed using 28 clinicopathological variables that were retrospectively collected from patients treated with NAC (n = 150), and validated using an independent dataset from a randomized controlled trial (n = 173). The model selected 15 variables to predict the pCR with yielding area under the receiver operating characteristics curve (AUC) values of 0.766 [95 % confidence interval (≥I)], 0.671-0.861, P value< 0.0001) in cross-validation using training dataset and 0.787 (95 % CI 0.716-0.858, P value < 0.0001) in the validation dataset. Among three subtypes of breast cancer, the luminal subgroup showed the best discrimination (AUC = 0.779, 95 % CI 0.641-0.917, P value = 0.0059). The developed model (AUC = 0.805, 95 % CI 0.716-0.894, P value\0.0001) outperformed multivariate logistic regression (AUC = 0.754, 95 % CI 0.651-0.858, P value = 0.00019) of validation datasets without missing values (n = 127). Several analyses, e.g. bootstrap analysis, revealed that the developed model was insensitive to missing values and also tolerant to distribution bias among the datasets. Our model based on clinicopathological variables showed high predictive ability for pCR. This model might improve the prediction of the response to NAC in primary breast cancer patients. © Springer Science+Business Media, LLC. 2012.

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Non-targeted metabolite profiling in activated macrophage secretion

Sugimoto, M., Sakagami, H., Yokote, Y., Onuma, H., Kaneko, M., Mori, M., Sakaguchi, Y., Soga, T. and Tomita, M.

Metabolomics 8 ( 4 ) 624–633 - 633 2012

Research paper (scientific journal), Joint Work, Accepted,  ISSN  15733882

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Periodontal diseases are inflammatory infectious diseases that affect the periodontal tissue. Macrophages play a central role in inflammatory conditions, leading to the destruction of tissues. Identifying the signaling molecules secreted by macrophages would be valuable to the study of these diseases. Here, we present non-targeted analysis using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS) for the profiling of extracellular metabolites released during macrophage activation. Lipopolysaccharide (LPS)-induced activation of a mouse macrophage-like cell line RAW264. 7 was used as a model system. Cells were treated without (control) or with LPS for 22 h and, after washing, were incubated for 1 h in phosphate-buffered saline. The accumulation of metabolites in the culture supernatant was monitored. LPS treatment significantly enhanced the accumulation of prostaglandins, tumor necrosis factor-α, nitric oxide and citrulline in the culture medium. RAW264. 7 cells produced 46 metabolites and 66% of these showed significant changes (P < 0.05) following cell activation. In particular, the production of leucine, hypoxanthine, choline, putrecine, N 8-acetylspermidine, succinate, itaconate, and 4-methyl-2-oxopentanoate was significantly increased by cell activation (P < 0.001). Significantly elevated production of lactate and glycine was also observed. Here, we present the first catalog of the up and down-regulation of the various metabolites secreted by macrophages following inflammatory activation. © 2011 Springer Science+Business Media, LLC.

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Mass spectrum sequential subtraction speeds up searching large peptide MS/MS spectra datasets against large nucleotide databases for proteogenomics

Helmy, M., Sugiyama, N., Tomita, M. and Ishihama, Y.

Genes to Cells (Genes to Cells)  17 ( 8 ) 633-44 - 644 2012

Research paper (scientific journal), Joint Work, Accepted,  ISSN  13569597

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We have developed a novel bioinformatics method called mass spectrum sequential subtraction (MSSS) to search large peptide spectra datasets produced by liquid chromatography/mass spectrometry (LC-MS/MS) against protein and large-sized nucleotide sequence databases. The main principle in MSSS is to search the peptide spectra set against the protein database, followed by removal of the spectra corresponding to the identified peptides to create a smaller set of the remaining peptide spectra for searching against the nucleotide sequences database. Therefore, we reduce the number of spectra to be searched to limit the peptide search space. Comparing MSSS and conventional search approach using a dataset of 27 LC-MS/MS runs of rice culture cells indicated that MSSS reduced the search queries to 50% and the search time to 75% on average. In addition, MSSS had no effect on the identification false-positive rate (FPR) or the novel peptide sequences identification ability. We used MSSS to analyze another dataset of 34 LC-MS/MS runs, resulting in identifying additional 74 novel peptides. Proteogenomic analysis with these additional peptides yielded 47 new genomic features in 24 rice genes plus 24 intergenic peptides. These results show that the utility of MSSS in searching large databases with large MS/MS datasets for proteogenomics. © 2012 The Authors Journal compilation © 2012 by the Molecular Biology Society of Japan/Blackwell Publishing Ltd.

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Investigation of stochasticity in TRAIL signaling cancer model

Piras, V., Hayashi, K., Tomita, M. and Selvarajoo, K.

IEEE/ICME Com. Med. Eng.    609-614. - 614 2012

Research paper (scientific journal), Joint Work, Accepted

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In cancer, apoptosis or programmed cell death has been demonstrated through the tumor necrosis factor related apoptosis-inducing ligand (TRAIL) signal transduction. As a result, TRAIL-based therapies have been widely investigated to fight cancers. However, several malignant cancer types still remain resistant to TRAIL. Recently, we developed a dynamic computational model to investigate the resistance mechanisms in TRAIL-stimulated human fibrosarcoma (HT1080) cells. The macroscopic average-cell response model, based on the law of mass action and signaling flux conservation, successfully simulates the semi-quantitative temporal profiles of cell survival (I?B, JNK, p38) and apoptotic (caspase-8 and -3) molecules in wildtype and several mutants (FADD, RIP1 and TRAF2 knockdowns or KD). However, cancer populations are known to be highly heterogeneous, and various studies have demonstrated the importance of stochasticity and variability for phenotypic diversity between identical cells. Here, we extend our original model to investigate the effect of such fluctuations on TRAIL signaling response by adopting probabilities of signaling reactions through the Gillespie algorithm. Notably, when we stimulated the model 1000 times to indicate the variability of 1000 single cell responses in all 4 experimental conditions with different levels of stochasticity, we notice that TRAF2 KD produced the most variable signaling response. This variance subsequently affected the level of cellular apoptosis analysed through the cell-survival metric (CSM). Our work highlights the necessity to understand variable responses of cell signaling reactions to different levels of stochasticity. Thus, prior to the actual development of potential drug targets for killing cancer cells, the effect of stochastic variance could be investigated through dynamic models. © 2012 IEEE.

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A Yeast Metabolite Extraction Protocol Optimised for Time-Series Analyses

Sasidharan, K., Soga, T., Tomita, M. and Murray, D., B.

PLoS ONE (PLoS ONE)  7 ( 8 ) e44283 2012

Research paper (scientific journal), Joint Work, Accepted

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There is an increasing call for the absolute quantification of time-resolved metabolite data. However, a number of technical issues exist, such as metabolites being modified/degraded either chemically or enzymatically during the extraction process. Additionally, capillary electrophoresis mass spectrometry (CE-MS) is incompatible with high salt concentrations often used in extraction protocols. In microbial systems, metabolite yield is influenced by the extraction protocol used and the cell disruption rate. Here we present a method that rapidly quenches metabolism using dry-ice ethanol bath and methanol N-ethylmaleimide solution (thus stabilising thiols), disrupts cells efficiently using bead-beating and avoids artefacts created by live-cell pelleting. Rapid sample processing minimised metabolite leaching. Cell weight, number and size distribution was used to calculate metabolites to an attomol/cell level. We apply this method to samples obtained from the respiratory oscillation that occurs when yeast are grown continuously. © 2012 Sasidharan et al.

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