Evolutionary design of multiple genes encoding the same protein.

MOTIVATION: Enhancing expression levels of a target protein is an important goal in synthetic biology. A widely used strategy is to integrate multiple copies of genes encoding a target protein into a host organism genome. Integrating highly similar sequences, however, can induce homologous recombination between them, resulting in the ultimate reduction of the number of integrated genes. RESULTS: We propose a method for designing multiple protein-coding sequences (i.e. CDSs) that are unlikely to induce homologous recombination, while encoding the same protein. The method, which is based on multi-objective genetic algorithm, is intended to design a set of CDSs whose nucleotide sequences are as different as possible and whose codon usage frequencies are as highly adapted as possible to the host organism. We show that our method not only successfully designs a set of intended CDSs, but also provides insight into the trade-off between nucleotide differences among gene copies and codon usage frequencies. AVAILABILITY AND IMPLEMENTATION: Our method, named Tandem Designer, is available as a web-based application at http://tandem.trahed.jp/tandem/ . CONTACT: : terai_goro@intec.co.jp or asai@k.u-tokyo.ac.jp. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

CDSfold: an algorithm for designing a protein-coding sequence with the most stable secondary structure.

MOTIVATION: An important problem in synthetic biology is to design a nucleotide sequence of an mRNA that confers a desirable expression level of a target protein. The secondary structure of protein-coding sequences (CDSs) is one potential factor that could have both positive and negative effects on protein production. To elucidate the role of secondary structure in CDSs, algorithms for manipulating secondary structure should be developed. RESULTS: We developed an algorithm for designing a CDS with the most stable secondary structure among all possible ones translated into the same protein, and implemented it as the program CDSfold. The algorithm runs the Zuker algorithm under the constraint of a given amino acid sequence. The time and space complexity is O(L(3)) and O(L(2)), respectively, where L is the length of the CDS to be designed. Although our algorithm is slower than the original Zuker algorithm, it could design a relatively long (2.7-kb) CDS in approximately 1 h. AVAILABILITY AND IMPLEMENTATION: The CDSfold program is freely available for non-commercial users as stand-alone and web-based software from http://cdsfold.trahed.jp/cdsfold/ CONTACTS: terai-goro@aist.go.jp or asai@k.u-tokyo.ac.jp SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A Proteomic Approach for the Diagnosis of 'Oketsu' (blood stasis), a Pathophysiologic Concept of Japanese Traditional (Kampo) Medicine.

'Oketsu' is a pathophysiologic concept in Japanese traditional (Kampo) medicine, primarily denoting blood stasis/stagnant syndrome. Here we have explored plasma protein biomarkers and/or diagnostic algorithms for 'Oketsu'. Sixteen rheumatoid arthritis (RA) patients were treated with keishibukuryogan (KBG), a representative Kampo medicine for improving 'Oketsu'. Plasma samples were diagnosed as either having an 'Oketsu' (n = 19) or 'non-Oketsu' (n = 29) state according to Terasawa's 'Oketsu' scoring system. Protein profiles were obtained by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) and hierarchical clustering and decision tree analyses were performed. KBG treatment for 4 or 12 weeks decreased the 'Oketsu' scores significantly. SELDI protein profiles gave 266 protein peaks, whose expression was significantly different between the 'Oketsu' and 'non-Oketsu' states. Hierarchical clustering gave three major clusters (I, II, III). The majority (68.4%) of 'Oketsu' samples were clustered into one cluster as the principal component of cluster I. The remaining 'Oketsu' profiles constituted a minor component of cluster II and were all derived from patients cured of the 'Oketsu' state at 12 weeks. Construction of the decision tree addressed the possibility of developing a diagnostic algorithm for 'Oketsu'. A reduction in measurement/pre-processing conditions (from 55 to 16) gave a similar outcome in the clustering and decision tree analyses. The present study suggests that the pathophysiologic concept of Kampo medicine 'Oketsu' has a physical basis in terms of the profile of blood proteins. It may be possible to establish a set of objective criteria for diagnosing 'Oketsu' using a combination of proteomic and bioinformatics-based classification methods.

Identification of a predictive biomarker for the beneficial effect of a Kampo (Japanese traditional) medicine keishibukuryogan in rheumatoid arthritis patients.

OBJECTIVES: Kampo (Japanese traditional herbal) medicines are now ethically used in Japan as pharmaceutical grade prescription drugs. However, there are distinct groups of responders and non-responders to Kampo medicines. We searched for biomarker candidates to discriminate responders from non-responders to keishibukuryogan (KBG); one of the most frequently used Kampo medicines. DESIGN AND METHODS: A combination of SELDI technology and a decision tree analysis with proprietary developed bioinformatics tools was applied to 41 (32 for tree construction and 9 for validation test) plasma samples obtained from rheumatoid arthritis (RA) patients. A candidate biomarker protein was identified using LC-MS/MS. RESULTS: The constructed tree with measurable reliability contained only a single peak which was identified as haptoglobin alpha 1 chain (Hpalpha1). CONCLUSION: Hpalpha1 is a biomarker candidate for discriminating responders from non-responders to KBG treatment for RA. The present results may open the way to the establishment of "evidence-based" complementary and alternative medicine.