Representational difference analysis of cDNA for the detection of differential gene expression in bacteria: development using a model of iron-regulated gene expression in Neisseria meningitidis

Next-generation sequencing of representational difference analysis products for identification of genes involved in diosgenin biosynthesis in fenugreek (Trigonella foenum-graecum)

Representational difference analysis of cDNA was performed and differential products were sequenced and annotated. Candidate genes involved in biosynthesis of diosgenin in fenugreek were identified. Detailed mechanism of diosgenin synthesis was proposed. Fenugreek (Trigonella foenum-graecum L.) is a valuable medicinal and crop plant. It belongs to Fabaceae family and has a unique potential to synthesize valuable steroidal saponins, e.g., diosgenin. Elicitation (methyl jasmonate) and precursor feeding (cholesterol and squalene) were used to enhance the content of sterols and steroidal sapogenins in in vitro grown plants for representational difference analysis of cDNA (cDNA-RDA). To identify candidate genes involved in diosgenin biosynthesis, differential, factor-specific libraries were subject to the next-generation sequencing. Approximately 9.9 million reads were obtained, trimmed, and assembled into 31,491 unigenes with an average length of 291 bp. Then, functional annotation and gene ontogeny enrichment analysis was performed by aligning all-unigenes with public databases. Within the transcripts related to sterol and steroidal saponin biosynthesis, we discovered novel candidate genes of diosgenin biosynthesis and validated their expression using quantitative RT-PCR analysis. Based on these findings, we supported the idea that diosgenin is biosynthesized from cycloartenol via cholesterol. This is the first report on the next-generation sequencing of cDNA-RDA products. Analysis of the transcriptomes enriched in low copy sequences contributed substantially to our understanding of the biochemical pathways of steroid synthesis in fenugreek.

Medical bioremediation of age-related diseases

Catabolic insufficiency in humans leads to the gradual accumulation of a number of pathogenic compounds associated with age-related diseases, including atherosclerosis, Alzheimer's disease, and macular degeneration. Removal of these compounds is a widely researched therapeutic option, but the use of antibodies and endogenous human enzymes has failed to produce effective treatments, and may pose risks to cellular homeostasis. Another alternative is "medical bioremediation," the use of microbial enzymes to augment missing catabolic functions. The microbial genetic diversity in most natural environments provides a resource that can be mined for enzymes capable of degrading just about any energy-rich organic compound. This review discusses targets for biodegradation, the identification of candidate microbial enzymes, and enzyme-delivery methods.

Prokaryotic suppression subtractive hybridization PCR cDNA subtraction, a targeted method to identify differentially expressed genes

Molecular biology tools can be used to monitor and optimize biological treatment systems, but the application of nucleic acid-based tools has been hindered by the lack of available sequences for environmentally relevant biodegradation genes. The objective of our work was to extend an existing molecular method for eukaryotes to prokaryotes, allowing us to rapidly identify differentially expressed genes for subsequent sequencing. Suppression subtractive hybridization (SSH) PCR cDNA subtraction is a technique that can be used to identify genes that are expressed under specific conditions (e.g., growth on a given pollutant). While excellent methods for eukaryotic SSH PCR cDNA subtraction are available, to our knowledge, no methods previously existed for prokaryotes. This work describes our methodology for prokaryotic SSH PCR cDNA subtraction, which we validated using a model system: Pseudomonas putida mt-2 degrading toluene. cDNA from P. putida mt-2 grown on toluene (model pollutant) or acetate (control substrate) was subjected to our prokaryotic SSH PCR cDNA subtraction protocol to generate subtraction clone libraries. Over 90% of the sequenced clones contained gene fragments encoding toluene-related enzymes, and 20 distinct toluene-related genes from three key operons were sequenced. Based on these results, prokaryotic SSH PCR cDNA subtraction shows promise as a targeted method for gene identification.

Quantitative effects of carbohydrates and aromatic amino acids on Clostridium botulinum toxin gene expression using a rapid competitive RT/PCR assay

A rapid competitive RT/PCR assay was developed to determine the effects of nutrients on Clostridium botulinum type E toxin gene expression. The type E strain (EVH) was grown in a nutrient-rich broth containing 1% glucose (base medium). Toxin gene expression was quantified at both mid and late exponential phases of growth. It was found that toxin encoding mRNA levels were highly growth phase dependent with elevated levels found in late exponential phase compared to mid exponential phase. Changing the carbohydrate source had a smaller effect on toxin encoding mRNA levels but as earlier results have suggested, toxin encoding mRNA levels show a strong correlation with type E growth rate. The results have important implications for the food industry whereby risk of type E botulism could be correlated to the nutrient composition of the contaminated food or assessed from C. botulinum growth rates in challenged foodstuffs.

Metagenomic gene discovery: past, present and future

It is now widely accepted that the application of standard microbiological methods for the recovery of microorganisms from the environment has had limited success in providing access to the true extent of microbial biodiversity. It follows that much of the extant microbial genetic diversity (collectively termed the metagenome) remains unexploited, an issue of considerable relevance to a wider understanding of microbial communities and of considerable importance to the biotechnology industry. The recent development of technologies designed to access this wealth of genetic information through environmental nucleic acid extraction has provided a means of avoiding the limitations of culture-dependent genetic exploitation.

Representational difference analysis: critical appraisal and method development for the identification of unique DNA sequences from prokaryotes

Representational difference analysis (RDA) has great potential for preferential amplification of unique but uncharacterised DNA sequences present in one source such as a whole genome, but absent from a related genome or other complex population of sequences. While a few examples of its successful exploitation have been published, the method has not been well dissected and robust, detailed published protocols are lacking. Here we examine the method in detail, suggest improvements and provide a protocol that has yielded key unique sequences from a pathogenic bacterial genome.

Identification of a differentially expressed oligopeptide binding protein (OppA2) in Streptococcus uberis by representational difference analysis of cDNA

Streptococcus uberis is an increasingly significant cause of intramammary infection in the dairy cow, presently responsible for approximately 33% of all cases of bovine mastitis in the United Kingdom. Following experimentally induced infection of the lactating mammary gland, S. uberis is found predominantly in the luminal areas of secretory alveoli and ductular tissue, indicating that much of the bacterial growth occurs in residual and newly synthesized milk. With the objective of identifying potential virulence determinants in a clinical isolate of S. uberis, we have used representational difference analysis of cDNA to identify genes that show modified expression in milk. We have identified a number of differentially expressed genes that may contribute to the overall pathogenicity of the organism. Of these, a transcript encoding a putative oligopeptide binding protein (OppA) was further characterized. We have found that S. uberis possesses two oppA-like open reading frames, oppA1 and oppA2, which are up-regulated to different degrees following growth in milk. Mutants lacking either oppA1 or oppA2 are viable and have an increased resistance to the toxic peptide derivative aminopterin; however, only mutants lacking oppA1 display a lower rate of growth in milk. In addition, expression of the oppA genes appears to be coordinated by different mechanisms. We conclude that the oppA genes encode oligopeptide binding proteins, possibly displaying different specificities, required for the efficient growth of S. uberis in milk.

Screening and expression of associated genes in gastric dysplasia

AIM: To explore molecular mechanism of gastric carcinogenesis, we screened associated genes of gastric dysplasia and further investigated their expression in gastric carcinomas with different stages.

METHODS: Relatively pure dysplasia and normal tissue were procured by manual microdissection, amplified by cDNA-PCR, and then used to carry out forward(dysplasia as tester, normal tissue as driver) and reverse(normal tissue as tester, dysplasia as driver) SSH. Subtracted cDNA fragments were cloned into vector, screened, sequenced, and made homologous analysis. The expression of differentially expressed fragments was detected and verified by Dot hybridization and reverse transcription-PCR.

RESULTS: Two subtracted cDNA libraries were constructed. Twenty-one of 26 sequenced clones were verified to be expressed differentially. It was noted that differentiall expressions of 4 genes(P125, cytochrome c oxidase subunit I, meprin A, acidic calponin)were detected simultaneously in dysplasia, early cancer and advanced cancer.

CONCLUSION: Four new associated genes have been identified in dysplasia. Further studies are necessary to determine their roles in gastric carcinogenesis.

The use of animal models in expression pharmacogenomic analyses

Expression pharmacogenomics applies genome/proteome scale differential expression technologies to both in vivo and in vitro models of drug response to identify candidate markers correlative with and predictive of drug toxicity and efficacy. It is anticipated to streamline drug development by triaging towards lead compounds and clinical candidates that maximize efficacy while minimizing safety risks. As the majority of expression pharmacogenomics will be performed on preclinical therapeutic candidates, compatibility with favored preclinical animal model systems will be essential. This review will address expression pharmacogenomics in the context of those animal model systems commonly used for pharmacokinetic, pharmacodynamic and toxicologic analyses. Specific discussions will cover: (A) relative robustness of genomic and proteomic technology platforms used to generate drug response data in critical model systems; (B) animal handling, treatment and other experimental design optimizations; (C) data analysis strategies for extracting and validating candidate pharmacogenomic markers; and (D) overarching limitations in applying expression pharmacogenomics to animal model systems.

Detection of differential gene expression in biofilm-forming versus planktonic populations of Staphylococcus aureus using micro-representational-difference analysis

Microbial proliferation and biofilm formation on biologic or inert substrates are characteristics of invasive Staphylococcus aureus infections and is associated with phenotypic alterations such as reduced antimicrobial susceptibility. To identify genes which are typically expressed in biofilms, a micro-representational-difference analysis (micro-RDA) was adapted for gram-positive bacteria and used with cDNA derived from populations of S. aureus DSM 20231 growing in a biofilm or plankonically. In comparison to previously described cDNA RDA protocols, micro-RDA has the advantages that only minimal quantities of total RNA are needed and, most importantly, that total RNA can be used since the large amount of rRNA in total RNA does not interfere with the micro-RDA procedure. Using a series of spiked controls with various amounts of MS2 RNA in a background of total RNA from S. aureus, the equivalent of five copies of MS2 per cell were detectable after three rounds of subtractive enrichment. Five genes were identified as being differentially expressed in biofilm versus planktonic cultures. These genes revealed homology to a threonyl-tRNA synthetase, a phosphoglycerate mutase, a triosephosphate isomerase, an alcohol dehydrogenase I, and a ClpC ATPase. Differential levels of expression were subsequently confirmed by standard Northern blotting. In conclusion, micro-RDA is a sensitive and specific method to detect transcripts differentially expressed as a function of different S. aureus growth conditions.

Open systems: panoramic views of gene expression

Since their development in the early 1990s, differential gene expression (DGE) technologies have been applied to a multitude of biological challenges, both for the purpose of basic biological research and as a valuable tool for the discovery and development of pharmaceuticals. In this review we survey a class of DGE technologies collectively referred to as 'open' architecture systems. These technologies are distinct from the 'closed' DGE technologies (quantitative PCR, chip technologies), in that no pre-existing biological or sequence information is necessary and they are applicable to any species. Examples of open systems include GeneCalling, SAGE, TOGA, READS, and their progenitor DGE technologies, differential display and cDNA representational difference analysis. We review these technologies and summarize a specific application using GeneCalling for novel gene discovery. Additionally, the significance of data management and experimental design in this new age of expression analysis is discussed.

Current awareness

In order to keep subscribers up-to-date with the latest developments in their field, this current awareness service is provided by John Wiley & Sons and contains newly-published material on comparative and functional genomics. Each bibliography is divided into 16 sections. 1 Reviews & symposia; 2 General; 3 Large-scale sequencing and mapping; 4 Genome evolution; 5 Comparative genomics; 6 Gene families and regulons; 7 Pharmacogenomics; 8 Large-scale mutagenesis programmes; 9 Functional complementation; 10 Transcriptomics; 11 Proteomics; 12 Protein structural genomics; 13 Metabolomics; 14 Genomic approaches to development; 15 Technological advances; 16 Bioinformatics. Within each section, articles are listed in alphabetical order with respect to author. If, in the preceding period, no publications are located relevant to any one of these headings, that section will be omitted