Microarrays as a functional approach to the transcriptome

Knowing a cell’s transcriptome is a fundamental requisite in order to analyze its response to the environment. Microarrays have supposed a revolution on this field as they are able to yield an overview of gene expression at any environmental condition on a genome-wide scale. This technique consists in the hybridisation of a nucleic acid sample, previously marked, with a probe (which might be made up of cDNA, oligonucleotides or PCR products) anchored to a solid surface (made of glass, plastic, silicon...) giving as a result a dot grid which reveals, after image analysis, which genes are being expressed. Nevertheless, this only can be achieved if information on the species genome has been generated. Different kinds of expression microarrays exist attending to the probe’s nature and the method used in its synthesis. In this poster two of these will be treated: Spotted Microarrays, for which the probe is synthesised prior to its fixation to the array and allow the analysis of two targets simultaneously. They can be easily customized, but lack high reproducibility and sensitivity. Oligonucleotide Microarrays, which are characterized by the direct printing of the probe on the array. In this case the probes consist on, invariably, oligonucleotides that are complementary to a small fraction of the gene it is representing at the microarray. Their application is somewhat restricted. This fact, however, makes them more reproducible. Currently, the approach towards the transcriptome studies from the Next Generation Sequencing technologies offers a large volume of information in a short amount of time needing less previous information on the target organism than that needed by microarrays, but their expensive price limits their use. The versatility of the latter, together with their reduced costs in comparison to other techniques, makes them an interesting resource in applications that may need less complexity.

OC-OT-LIBS: A novel approach to the chemical characterization of single particles

Spectral identification of individual micro- and nano-sized particles by the sequential intervention of optical catapulting, optical trapping and laser-induced breakdown spectroscopy is presented [1]. The three techniques are used for different purposes. Optical catapulting (OC) serves to put the particulate material under inspection in aerosol form [2-4]. Optical trapping (OT) permits the isolation and manipulation of individual particles from the aerosol, which are subsequently analyzed by laser-induced breakdown spectroscopy (LIBS). Once catapulted, the dynamics of particle trapping depends on the laser beam characteristics (power and intensity gradient) and on the particle properties (size, mass and shape). Particles are stably trapped in air at atmospheric pressure and can be conveniently manipulated for a precise positioning for LIBS analysis. The spectra acquired from the individually trapped particles permit a straightforward identification of the inspected material. The current work focuses on the development of a procedure for simultaneously acquiring dual information about the particle under study via LIBS and time-resolved plasma images by taking advantage of the aforementioned features of the OC-OT-LIBS instrument to align the multiple lines in a simple yet highly accurate way. The plasma imaging does not only further reinforce the spectral data, but also allows a better comprehension of the chemical and physical processes involved during laser-particle interaction. Also, a thorough determination of the optimal excitation conditions generating the most information out of each laser event was run along the determination of parameters such as the width of the optical trap, its stability as a function of the laser power and the laser wavelength. The extreme sensibility of the presented OC-OT-LIBS technology allows a detection power of attograms for single/individual particle analysis.

Integer Linear Programming for Sequence Problems: A general approach to reduce the problem size

Sequence problems belong to the most challenging interdisciplinary topics of the actuality. They are ubiquitous in science and daily life and occur, for example, in form of DNA sequences encoding all information of an organism, as a text (natural or formal) or in form of a computer program. Therefore, sequence problems occur in many variations in computational biology (drug development), coding theory, data compression, quantitative and computational linguistics (e.g. machine translation). In recent years appeared some proposals to formulate sequence problems like the closest string problem (CSP) and the farthest string problem (FSP) as an Integer Linear Programming Problem (ILPP). In the present talk we present a general novel approach to reduce the size of the ILPP by grouping isomorphous columns of the string matrix together. The approach is of practical use, since the solution of sequence problems is very time consuming, in particular when the sequences are long.