Simultaneous genotyping and species identification using hybridization pattern recognition analysis of generic Mycobacterium DNA arrays

High-density oligonucleotide arrays can be used to rapidly examine large amounts of DNA sequence in a high throughput manner. An array designed to determine the specific nucleotide sequence of 705 bp of the rpoB gene of Mycobacterium tuberculosis accurately detected rifampin resistance associated with mutations of 44 clinical isolates of M. tuberculosis. The nucleotide sequence diversity in 121 Mycobacterial isolates (comprised of 10 species) was examined by both conventional dideoxynucleotide sequencing of the rpoB and 165 genes and by analysis of the rpoB oligonucleotide array hybridization patterns. Species identification for each of the isolates was similar irrespective of whether 16S sequence, rpoB sequence, or the pattern of rpoB hybridization was used. However, for several species, the number of alleles in the 16S and rpoB gene sequences provided discordant estimates of the genetic diversity within a species. In addition to confirming the array's intended utility for sequencing the region of M. tuberculosis that confers rifampin resistance, this work demonstrates that this array can identify the species of nontuberculous Mycobacteria. This demonstrates the general point that DNA microarrays that sequence important genomic regions (such as drug resistance or pathogenicity islands) can simultaneously identify species and provide some insight into the organism's population structure

Analysis of oligonucleotide array experiments with repeated measures using mixed models

BACKGROUND: Two or more factor mixed factorial experiments are becoming increasingly common in microarray data analysis. In this case study, the two factors are presence (Patients with Alzheimer's disease) or absence (Control) of the disease, and brain regions including olfactory bulb (OB) or cerebellum (CER). In the design considered in this manuscript, OB and CER are repeated measurements from the same subject and, hence, are correlated. It is critical to identify sources of variability in the analysis of oligonucleotide array experiments with repeated measures and correlations among data points have to be considered. In addition, multiple testing problems are more complicated in experiments with multi-level treatments or treatment combinations. RESULTS: In this study we adopted a linear mixed model to analyze oligonucleotide array experiments with repeated measures. We first construct a generalized F test to select differentially expressed genes. The Benjamini and Hochberg (BH) procedure of controlling false discovery rate (FDR) at 5% was applied to the P values of the generalized F test. For those genes with significant generalized F test, we then categorize them based on whether the interaction terms were significant or not at the α-level (α(new )= 0.0033) determined by the FDR procedure. Since simple effects may be examined for the genes with significant interaction effect, we adopt the protected Fisher's least significant difference test (LSD) procedure at the level of α(new )to control the family-wise error rate (FWER) for each gene examined. CONCLUSIONS: A linear mixed model is appropriate for analysis of oligonucleotide array experiments with repeated measures. We constructed a generalized F test to select differentially expressed genes, and then applied a specific sequence of tests to identify factorial effects. This sequence of tests applied was designed to control for gene based FWER

A comparative analysis of existing oligonucleotides selection algorithms for microarray technology

In system biology, DNA microarray technology is an indispensable tool for the biological analysis involved at the level of the whole genome. Among the sophisticated analytical problems in microarray technology at the front and back ends, respectively, are the selection of optimal DNA oligonucleotides (henceforth oligos) and computational analysis of the genes expression data. A computational comparative analysis of the methods used to select oligos is important since the design and quality of the microarray probes are of critical importance for the hybridization experiments as well as subsequent analysis of the data. In an attempt to enhance efficient and effective design at the front end, a computational comparative analysis was performed on oligos selection tools using the barley ESTs, as well as the Saccharomyces cerevisiae, Encephalitozoon cuniculi and human genomes. The analysis also shows that a large number of the existing tools are difficult to install and configure. For cross hybridization test, most rely on BLAST and therefore design ill specific oligonucleotides. Furthermore, most are non-intuitive to use and lack important oligo design and software features

Physico-chemical foundations underpinning microarray and next-generation sequencing experiments

Hybridization of nucleic acids on solid surfaces is a key process involved in high-throughput technologies such as microarrays and, in some cases, next-generation sequencing (NGS). A physical understanding of the hybridization process helps to determine the accuracy of these technologies. The goal of a widespread research program is to develop reliable transformations between the raw signals reported by the technologies and individual molecular concentrations from an ensemble of nucleic acids. This research has inputs from many areas, from bioinformatics and biostatistics, to theoretical and experimental biochemistry and biophysics, to computer simulations. A group of leading researchers met in Ploen Germany in 2011 to discuss present knowledge and limitations of our physico-chemical understanding of high-throughput nucleic acid technologies. This meeting inspired us to write this summary, which provides an overview of the state-of-the-art approaches based on physico-chemical foundation to modeling of the nucleic acids hybridization process on solid surfaces. In addition, practical application of current knowledge is emphasized

Systems Biology and the Development of Vaccines and Drugs for Malaria Treatments

The sequencing race has ended and the functional race has already begun. Microarray technology enables simultaneous gene expression analysis of thousands of genes, enabling a snapshot of an organisms’ transcriptome at an unprecedented resolution. The close correlation between gene transcription and function, allow the inference of biological processes from the assessed transcriptome profile. Among the sophisticated analytical problems in microarray technology at the front and back ends respectively, are the selection of optimal DNA oligos and computational analysis of the genes expression. In this review paper, we analyse important methods in use today in customized oligos design. In the course of executing this, we discovered that the oligos designer algorithm hanged on gene PFA0135w of chromosome 1, while designing oligos for the gene sequences of Plasmodium falciparum. We do not know the reason for this yet, as the algorithm runs on other sequences like the yeast (Saccharomyces cervisiae) and Neurospora crassa. We conclude the paper highlighting the procedures encompassing the back end phase and discuss their application to the development of vaccines and drugs for malaria treatment. Note that, malaria is the cause of significant global morbidity and mortality with 300-500 million cases annually. Our aims are not ends, but a means to achieve the following: Iterate the need for experimental biologists to (i) know how to design their customized oligos and (ii) have some idea about gene expression analysis and the need for cooperation between experimental biologists and their counterpart, the computational biologists. These will help experimental biologists to coordinate very well the front and the back ends of the system biology analysis of the whole genome effectively

Experimental and computational applications of microarray technology for malaria eradication in Africa

Various mutation assisted drug resistance evolved in Plasmodium falciparum strains and insecticide resistance to female Anopheles mosquito account for major biomedical catastrophes standing against all efforts to eradicate malaria in Sub-Saharan Africa. Malaria is endemic in more than 100 countries and by far the most costly disease in terms of human health causing major losses among many African nations including Nigeria. The fight against malaria is failing and DNA microarray analysis need to keep up the pace in order to unravel the evolving parasite’s gene expression profile which is a pointer to monitoring the genes involved in malaria’s infective metabolic pathway. Huge data is generated and biologists have the challenge of extracting useful information from volumes of microarray data. Expression levels for tens of thousands of genes can be simultaneously measured in a single hybridization experiment and are collectively called a “gene expression profile”. Gene expression profiles can also be used in studying various state of malaria development in which expression profiles of different disease states at different time points are collected and compared to each other to establish a classifying scheme for purposes such as diagnosis and treatments with adequate drugs. This paper examines microarray technology and its application as supported by appropriate software tools from experimental set-up to the level of data analysis. An assessment of the level of microarray technology in Africa, its availability and techniques required for malaria eradication and effective healthcare in Nigeria and Africa in general were also underscored

Application of COMPOCHIP Microarray to Investigate the Bacterial Communities of Different Composts

A microarray spotted with 369 different 16S rRNA gene probes specific to microorganisms involved in the degradation process of organic waste during composting was developed. The microarray was tested with pure cultures, and of the 30,258 individual probe-target hybridization reactions performed, there were only 188 false positive (0.62%) and 22 false negative signals (0.07%). Labeled target DNA was prepared by polymerase chain reaction amplification of 16S rRNA genes using a Cy5-labeled universal bacterial forward primer and a universal reverse primer. The COMPOCHIP microarray was applied to three different compost types (green compost, manure mix compost, and anaerobic digestate compost) of different maturity (2, 8, and 16 weeks), and differences in the microorganisms in the three compost types and maturity stages were observed. Multivariate analysis showed that the bacterial composition of the three composts was different at the beginning of the composting process and became more similar upon maturation. Certain probes (targeting Sphingobacterium, Actinomyces, Xylella/Xanthomonas/ Stenotrophomonas, Microbacterium, Verrucomicrobia, Planctomycetes, Low G + C and Alphaproteobacteria) were more influential in discriminating between different composts. Results from denaturing gradient gel electrophoresis supported those of microarray analysis. This study showed that the COMPOCHIP array is a suitable tool to study bacterial communities in composts

Specific discrimination of three pathogenic salmonella enterica subsp enterica serotypes using CarB-based oligonuceotide microarray

It is important to rapidly and selectively detect and analyze pathogenic Salmonella enterica subsp. enterica in contaminated food to reduce the morbidity and mortality of Salmonella infection and to guarantee food safety. In the present work, we developed an oligonucleotide microarray containing duplicate specific capture probes based on the carB gene, which encodes the carbamoyl phosphate synthetase large subunit, as a competent biomarker evaluated by genetic analysis to selectively and efficiently detect and discriminate three S. enterica subsp. enterica serotypes: Choleraesuis, Enteritidis, and Typhimurium. Using the developed microarray system, three serotype targets were successfully analyzed in a range as low as 1.6 to 3.1 nM and were specifically discriminated from each other without nonspecific signals. In addition, the constructed microarray did not have cross-reactivity with other common pathogenic bacteria and even enabled the clear discrimination of the target Salmonella serotype from a bacterial mixture. Therefore, these results demonstrated that our novel carB-based oligonucleotide microarray can be used as an effective and specific detection system for S. enterica subsp. enterica serotypes.open117Nsciescopu

Molecular analysis of endocrine disruption in hornyhead turbot at wastewater outfalls in southern california using a second generation multi-species microarray.

Sentinel fish hornyhead turbot (Pleuronichthysverticalis) captured near wastewater outfalls are used for monitoring exposure to industrial and agricultural chemicals of ~ 20 million people living in coastal Southern California. Although analyses of hormones in blood and organ morphology and histology are useful for assessing contaminant exposure, there is a need for quantitative and sensitive molecular measurements, since contaminants of emerging concern are known to produce subtle effects. We developed a second generation multi-species microarray with expanded content and sensitivity to investigate endocrine disruption in turbot captured near wastewater outfalls in San Diego, Orange County and Los Angeles California. Analysis of expression of genes involved in hormone [e.g., estrogen, androgen, thyroid] responses and xenobiotic metabolism in turbot livers was correlated with a series of phenotypic end points. Molecular analyses of turbot livers uncovered altered expression of vitellogenin and zona pellucida protein, indicating exposure to one or more estrogenic chemicals, as well as, alterations in cytochrome P450 (CYP) 1A, CYP3A and glutathione S-transferase-α indicating induction of the detoxification response. Molecular responses indicative of exposure to endocrine disruptors were observed in field-caught hornyhead turbot captured in Southern California demonstrating the utility of molecular methods for monitoring environmental chemicals in wastewater outfalls. Moreover, this approach can be adapted to monitor other sites for contaminants of emerging concern in other fish species for which there are few available gene sequences