Trichinosis Imitating an Inflammatory Systematic Disease.

Trichinellosis (trichinosis) is a parasitic infection caused by nematodes of the genus Trichinella. Pigs are the most common source of human infection. We describe a case of a 47-year-old woman presented with a wide range of intermittent symptoms including prolonged fever, dry cough, diarrhea, rash, myalgias and arthralgias. The patient was attended by physicians with various medical specialties such as dermatologists, rheumatologists and allergiologists, but they did not establish a certain diagnosis because of the gradual onset of symptoms, raising the suspicion of a systematic disease. After extensive work up, the diagnosis of trichinosis was established with femoral muscle biopsy compatible with inflammatory myopathy of parasitic etiology with trichinosis to be the predominant diagnosis. Despite the significant delay of diagnosis for almost three months, patient was treated successfully with no further complications. Trichinellosis is a food-borne treatable infection. Preventive measures include community education especially in zones where parasite prevalence is increased, improvement of farming and cooking techniques.

Synthesis cost-optimal targeted mutant protein libraries.

Protein variant libraries produced by site-directed mutagenesis are a useful tool utilized by protein engineers to explore variants with potentially improved properties, such as activity and stability. These libraries are commonly built by selecting residue positions and alternative beneficial mutations for each position. All possible combinations are then constructed and screened, by incorporating degenerate codons at mutation sites. These degenerate codons often encode additional unwanted amino acids or even STOP codons. Our study aims to take advantage of annealing based recombination of oligonucleotides during synthesis and utilize multiple degenerate codons per mutation site to produce targeted protein libraries devoid of unwanted variants. Toward this goal we created an algorithm to calculate the minimum number of degenerate codons necessary to specify any given amino acid set, and a dynamic programming method that uses this algorithm to optimally partition a DNA target sequence with degeneracies into overlapping oligonucleotides, such that the total cost of synthesis of the target mutant protein library is minimized. Computational experiments show that, for a modest increase in DNA synthesis costs, beneficial variant yields in produced mutant libraries are increased by orders of magnitude, an effect particularly pronounced in large combinatorial libraries.

Improved algorithms for approximate string matching (extended abstract).

BACKGROUND: The problem of approximate string matching is important in many different areas such as computational biology, text processing and pattern recognition. A great effort has been made to design efficient algorithms addressing several variants of the problem, including comparison of two strings, approximate pattern identification in a string or calculation of the longest common subsequence that two strings share. RESULTS: We designed an output sensitive algorithm solving the edit distance problem between two strings of lengths n and m respectively in time O((s - |n - m|).min(m, n, s) + m + n) and linear space, where s is the edit distance between the two strings. This worst-case time bound sets the quadratic factor of the algorithm independent of the longest string length and improves existing theoretical bounds for this problem. The implementation of our algorithm also excels in practice, especially in cases where the two strings compared differ significantly in length. CONCLUSION: We have provided the design, analysis and implementation of a new algorithm for calculating the edit distance of two strings with both theoretical and practical implications. Source code of our algorithm is available online.

Codon Context Optimization in Synthetic Gene Design.

Advances in de novo synthesis of DNA and computational gene design methods make possible the customization of genes by direct manipulation of features such as codon bias and mRNA secondary structure. Codon context is another feature significantly affecting mRNA translational efficiency, but existing methods and tools for evaluating and designing novel optimized protein coding sequences utilize untested heuristics and do not provide quantifiable guarantees on design quality. In this study we examine statistical properties of codon context measures in an effort to better understand the phenomenon. We analyze the computational complexity of codon context optimization and design exact and efficient heuristic gene recoding algorithms under reasonable constraint models. We also present a web-based tool for evaluating codon context bias in the appropriate context.