Computational Sequence Design Techniques for DNA Microarray Technologies.

Tulpan, D., Ghiggi, A., Montemanni, R. (2011). Computational Sequence Design Techniques for DNA Microarray Technologies. IGI Global, book chapter (accepted).

In systems biology and biomedical research, microarray technology is a method of choice that enables the complete quantitative and qualitative ascertainment of gene expression patterns for whole genomes. The selection of high quality oligonucleotide sequences that behave consistently across multiple experiments is a key step in the design, fabrication and experimental performance of DNA microarrays. The aim of this chapter is to outline recent algorithmic developments in microarray probe design, evaluate existing probe sequences used in commercial arrays, and suggest methodologies that have the potential to improve on existing design techniques.

qRT-PCR for validating microbial microarray data.

Tulpan, D., Davey, M., LaFlamme, M. (2011). qRT-PCR for validating microbial microarray data. Horizon Press, chapter 10, book: Quantitative Real-time PCR in Applied Microbiology.

The ability of DNA microarray technology to identify and quantify microbial entities and genes of interest in various environments, such as soil, water, air, compost, and blood, propelled biological, environmental and clinical research into the post-genomic era. Nevertheless, as it is valid for any new technology, errors may occur at different stages along the experimental process. Three sources of errors associated with DNA microarray utilization have been identified by Taniguchi et al. (2001), namely: (i) the microarray fabrication, (ii) the microarray experiment, and (iii) the interpretation of results (data analysis). Validation strategies are typically required to alleviate and eventually repair the undesired errors that may arise in a microarray experiment. One of the validation techniques widely accepted and used worldwide is the quantitative Reverse Transcriptase Polymerase Chain Reaction (RT-qPCR). This chapter will provide succinct introductions to microarray technologies applied to microbial research and fundamental notions regarding RT-qPCR and its use to validate microarray results. A discussion including advantages and disadvantages of microbial microarray validation using RT-qPCR will be presented and current and future trends and research directions will be summarized towards the end of the chapter.

MetaboHunter: an automatic approach for identification of metabolites from 1H-NMR spectra of complex mixtures.

Tulpan, D., Leger, S., Belliveau, L., Culf, A., Cuperlovic-Culf, M. (2011). MetaboHunter: an automatic approach for identification of metabolites from 1H-NMR spectra of complex mixtures. BMC Bioinformatics, 12:400.

Background:
One-dimensional 1H-NMR spectroscopy is widely used for high-throughput characterization of metabolites in complex biological mixtures. However, the accurate identification of individual compounds is still a challenging task, particularly in spectral regions with higher peak densities. The need for automatic tools to facilitate and further improve the accuracy of such tasks, while using increasingly larger reference spectral libraries becomes a priority of current metabolomics research.

Results:
We introduce a web server application, called MetaboHunter, which can be used for automatic assignment of 1H-NMR spectra of metabolites. MetaboHunter provides methods for automatic metabolite identification based on spectra or peak lists with three different search methods and with possibility for peak drift in a user defined spectral range. The assignment is performed using as reference libraries manually curated data from two major publicly available databases of NMR metabolite standard measurements (HMDB and MMCD). Tests using a variety of synthetic and experimental spectra of single and multi metabolite mixtures show that MetaboHunter is able to identify, in average, more than 80% of detectable metabolites from spectra of synthetic mixtures and more than 50% from spectra corresponding to experimental mixtures. This work also suggests that better scoring functions improve by more than 30% the performance of MetaboHunter’s metabolite identification methods.

Conclusions:
MetaboHunter is a freely accessible, easy to use and user friendly 1H-NMR-based web server application that provides efficient data input and pre-processing, flexible parameter settings, fast and automatic metabolite fingerprinting and results visualization via intuitive plotting and compound peak hit maps. Compared to other published and freely accessible metabolomics tools, MetaboHunter implements three efficient methods to search for metabolites in manually curated data from two reference libraries.

Availability: http://www.nrcbioinformatics.ca/metabohunter/

1H NMR metabolomics combined with gene expression analysis for the determination of major metabolic differences between subtypes of breast cell lines

Cuperlovic-Culf, M., Chute, I.C., Culf, A.S., Touaibia, M., Ghosh, A., Griffiths, S., Tulpan, D., Léger, S., Belkaid, A., Surette, M.E., Ouellette, R.J. (2011). 1H NMR metabolomics combined with gene expression analysis for the determination of major metabolic differences between subtypes of breast cell lines. Chemical Science, 2, 2263-2270.

1H NMR analysis was performed on metabolic extracts from a selection of six breast cell lines, including normal-immortalized, invasive ductal carcinomas and adenocarcinomas. Metabolites with significant concentration differences between normal and cancerous cells as well as ER+ and ER− (estrogen receptor) cells were determined and their relation to the differentially expressed genes was explored. Major differences have been shown for many amino acids and this was linked to expression level changes of related genes. Observed changes in choline concentration were connected to expression level changes of the SCL44A1 transporter gene.

Recent Patents and Challenges on DNA Microarray Probe Design Technologies

D. Tulpan, Recent Patents and Challenges on DNA Microarray Probe Design Technologies, Recent Patents on DNA & Gene Sequences, Bentham Science Publishers, Feb 2011, http://www.benthamscience.com/dnag/E-Pub-Ahead-of-Schedule.htm#3

Free energy estimation of short DNA duplex hybridizations

D. Tulpan, M. Andronescu, S. Leger, BMC Bioinformatics, 11(1):105, 2010.

The microarray manual curation tool (MMCT): A web server for microarray probe evaluations

D. Tulpan, L. Belliveau, S. Leger, Bioinformation, 4(8):344-346, 2010.

Non-intrusive Patient Monitoring of Alzheimer's Disease Subjects Using Wireless Sensor Networks

M. Avvenuti, C. Baker, J. Light, D. Tulpan, A. Vecchio, Prceedings of the 2009 World Congress on Privacy, Security, Trust and the Management of e-Business, 2009.

InnateDB: facilitating systems-level analyses of the mammalian innate immune response

D.J. Lynn, G.L. Winsor, C. Chan, N. Richard, M.R. Laird, A. Barsky, J.L. Gardy, F.M. Roche, T.H.W. Chan, N. Shah, R. Lo, M. Naseer, J. Que,M. Yau,M. Acab, D. Tulpan, M.D. Whiteside, A. Chikatamarla, B. Mah, T. Munzner, K. Hokamp, R.E.W. Hancock, F.S.L. Brinkman, Molecular Systems Biology 4:218, 2008.

Thermodynamically based DNA strand design

D. Tulpan, M. Andronescu, M. Shortreed, S. Chang, A. Condon, H. Hoos, L. Smith, Nucleic Acids Research, Vol. 33, No. 15, pp. 4951-4964, 2005.

A Thermodynamic Approach to Designing Structure-Free Combinatorial DNA Word Sets

M. Shortreed, S. Chang, D. Phillips, M. Campion, D. Tulpan, M. Andronescu, A. Condon, H. Hoos, L. Smith, Nucleic Acids Research, Vol. 33, No. 15, pp. 4965-4977, 2005.

Hybrid Randomized Neighborhoods Improve Stochastic Local Search for DNA Code Design

D. Tulpan, H. Hoos, Lecture Notes in Computer Science, 2671, Springer-Verlag, pp. 418-433, 2003.

Stochastic Local Search Algorithms for DNA Word Design

D. Tulpan, H. Hoos, A. Condon, Lecture Notes in Computer Science, 2568, Springer-Verlag, pp. 229-241, 2002.

Effective heuristic methods for DNA strand design

Ph.D. Thesis

Sets of DNA strands that satisfy combinatorial and thermodynamic properties play
an important role in various approaches to biomolecular computations, nano structure
design, molecular tagging, and DNA microarrays. The problem of designing
such sets of DNA strands appears to be computationally hard.
This thesis introduces new algorithms for design of DNA strand sets that satisfy
any of several combinatorial and thermodynamic constraints, which aim to maximize
desired hybridization between strands and their complements, while minimizing
undesired cross-hybridizations. To heuristically search for good strand sets
for bio-computing applications, our algorithms use a conflict-driven stochastic local
search approach, which is known to be effective in solving comparable search
problems.
We describe new and improved thermodynamic measures of the quality of
strand sets. With respect to these measures of quality, our algorithms consistently
find, within reasonable time, sets that are significantly better than previously published
sets in the literature. We also present a detailed analysis and selection of
heuristics for improving the quality of DNA strand selection criteria with direct
applications in microarray probe design.