Novel Applications of Immuno-bioinformatics in Vaccine and Bio-product Developments at Research Institutes.

There are many challenges in the field of public health sciences. Rational decisions are required in order to treat different diseases, gain knowledge and wealth regarding research, and produce biological or synthetic products. Various advances in the basic laboratory science, computer science, and the engineering of biological production processes can help solve the occurring problems. Bioinformatics is defined as a field of science combined of biology, mathematics, physics, chemistry, and computer sciences. Recently, bioinformatics has been extensively used in the designing of the epitope, vaccines, antibodies, adjuvants, diagnostic kits, and therapeutic purposes (e.g., proteins, peptides, or small molecules). Moreover, bioinformatics includes chemoinformatics that has been employed to produce various biological or chemical products to target and combat pathogens. Bioinformatics is involved in other areas of data analysis and prediction, such as structural biology, system biology, phylogeny, population genetics, and next-generation data sequencing. To the best of our knowledge, no published study coherently described the benefits of bioinformatics fields applied for medication development or diagnostic aims in bio-productive and pharmaceutical/vaccine companies. Therefore, in the current review, we attempted to present the available bioinformatics resources, practical experiences, and other findings in the mentioned field along with providing a harmonized and applied model(s). The key points presented in the current review may help to elevate production and reduce the costs for the development of novel vaccines, medicines, and antibodies. In addition, these methods can facilitate the identification of organisms and may guarantee the quality of biological products.

Determination of CD Markers Profile of the Cell Line Infected by S15 Vaccine Strain of Theileria annulata Schizont Using RT-PCR Analysis.

The aim of this study was to identify the cell surface cluster of differentiation (CD) markers of the cell lines infected by Theileria annulata schizont. The CD molecules are very useful for the characterization of cells and different subpopulations of leukocytes. They are usually recognized by specific antibodies using flow cytometry and immunohistochemistry. In the current study, we applied reverse transcriptase-polymerase chain reaction (RT-PCR) to define the profile of cell surface markers in a cell line infected by an attenuated S15 vaccine strain of T. annulata schizont and a new laboratory-established cell line infected by a non-attenuated form. In order to determine the specific markers that can be used for excluding the non-attenuated cell lines, the characterization of the surface proteins profile of the S15 vaccine cell line is important. The RT-PCR was carried out by specifically designed primers using a panel of seven bovine CD markers, as well as beta-actin as an internal control house-keeping gene. We showed that both of the examined cell lines had a consistent expression of CD4, CD5, CD11a, CD14, CD43, and CD45 markers. However, the specific finding in this study was the expression of B-cell markers CD79a and CD5 by the newly-transformed cell line. On the other hand, CD5 as a marker for B-cell subset was expressed by S15 vaccine strain. In conclusion, we consider CD79a surface protein as a new marker for the cell lines infected by non-attenuated T. annulata schizont, while the cell lines infected by the vaccine strain do not express this marker. In addition, the identification of CD marker expression based on the RT-PCR assay might be a suitable and appropriate alternative technique for flow cytometry.

Numerical solution of DGLAP equations using Laguerre polynomials expansion and Monte Carlo method.

We investigate the numerical solutions of the DGLAP evolution equations at the LO and NLO approximations, using the Laguerre polynomials expansion. The theoretical framework is based on Furmanski et al.'s articles. What makes the content of this paper different from other works, is that all calculations in the whole stages to extract the evolved parton distributions, are done numerically. The employed techniques to do the numerical solutions, based on Monte Carlo method, has this feature that all the results are obtained in a proper wall clock time by computer. The algorithms are implemented in FORTRAN and the employed coding ideas can be used in other numerical computations as well. Our results for the evolved parton densities are in good agreement with some phenomenological models. They also indicate better behavior with respect to the results of similar numerical calculations.

Microbial contamination of cell cultures: a 2 years study.

Cell line contamination is a major drawback of main cell banks of the world and it has cost of losing important biological products or valuable research. The causative agents are different chemicals, invertebrates, bacteria, fungi, parasites, viral species and even other cell lines. In this retrospective study, cell lines from various species such as human, fish, insect, animals either offered or accessed through usual official accession in CGBRI were studied during 2 years (2002-2004) to detect their microbial contaminations and the causative organisms. Samples were taken for sterility test upon cell lines receipt and upon each cell line sub-culture. Samples were examined for bacterial (including mycoplasmas) and fungal contamination using conventional microbiological techniques. The study excluded parasites, viruses and other contaminating agents. This study revealed 39% of specimens were contaminated. The major contaminating agents were mycoplasmas (19%) followed by mixed infection (8%), fungi (8%) and bacteria (4%). Among various bacterial species (except mycoplasmas) Bacillus sp., Enterococcus sp. and Staphylococcus sp. are main bacterial agents and among various fungi Aspergillus sp. followed by Penicillium sp., Sepedonium sp. and Botrytis sp. were main fungal causative agents of CGBRI cell line contamination. Our study also delineates each cell line contamination rate and its causative agents. This is the first report of cell culture contamination from cell banks of Middle-East countries like Iran.