Molecular Microbiology, Institute of Food Research, Norwich Research Park, Norwich NR4 7UA, UK1
Author for correspondence: J. C. D. Hinton. Tel: +44 1603 255352. Fax: +44 1603 255076. e-mail: jay.hinton{at}bbsrc.ac.uk
Keywords: DNA microarray, gene expression profiling, microbial genomotyping
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Background |
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Assessment of transcription at the genomic scale has been achieved with DNA microarrays, which are glass slides containing an ordered mosaic of the entire genome as a collection of either oligonucleotides (oligonucleotide microarrays) or PCR products representing individual genes (commonly referred as cDNA microarrays).
The development of microarrays has been fuelled by the application of robotic technology to routine molecular biology, rather than by any fundamental breakthrough. The classical Southern and Northern blotting approaches for the detection of specific DNA and mRNA species (Southern, 1975 ; Alwine et al., 1977
, 1979
) provided the technological basis for microarray hybridization with fluorescently labelled cDNA. The idea of depositing multiple DNA spots representing different genes onto a solid surface is also nothing new, having been used by Blattners group to investigate Escherichia coli gene expression on membranes (macroarrays) as long ago as 1993 (Chuang et al., 1993
). Commercially available macroarrays have continued to produce useful data, and should be considered before recourse to microarrays (Tao et al., 1999
). The recent application of robotics to achieve high spotting densities of DNA on glass slides was innovative and facilitates the construction of microarrays containing up to 50000 genes on a single microscope slide (DeRisi et al., 1996
; Shalon et al., 1996
). This allows a single hybridization to be performed against multiple replicates of a single bacterial genome, or against copies of several unrelated genomes on a single glass slide. The development that has facilitated the reproducible comparison of gene expression between two samples, and hence between experiments, is dual fluorescent labelling (Schena et al., 1995
). Simultaneous hybridization of two cDNA populations labelled with the fluorescent dyes Cy3 and Cy5 allows accurate assessment of relative levels of gene expression, which is unaffected by hybridization variability or the differences between individual microarrays which can complicate macroarray experiments.
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Microarrays as a research tool |
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The explosive growth in the numbers of reviews discussing microarray technology has now been followed by many papers describing results obtained from gene expression microarray profiling (Fig. 1). Genomic and post-genomic approaches are likely to revolutionize our ability to understand how micro-organisms act, both in the laboratory and in the real world. But what effect has this new approach had on molecular microbiologists in general, and what difference is it likely to make in the future?
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Microbial gene expression profiling |
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One of the most impressive examples of the use of microarrays for bacterial research has been provided by recent work on Caulobacter crescentus (Laub et al., 2000 ). The definition of the cell cycle of C. crescentus by microarray analysis revealed that 572 of 2966 genes (19·3%) were cell-cycle-dependent. Not only were a number of classes of cell-cycle-induced genes identified, but also the proportion dependent upon the global cell cycle regulator CtrA was recognized for the first time. This study led to recognition of the role of 11 novel sensor kinases and 5 new sigma factors. The identification of cascades of gene expression during the Caulobacter cell cycle is an important landmark for bacterial research. We look forward to similar studies describing gene expression cascades during sporulation of Bacillus subtilis, and during E. coli cell division.
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Definition of entire regulons |
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Analysis of gene expression in vivo |
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Mammalian gene microarrays have recently been used to study hostpathogen interactions from the viewpoint of the host, by identifying gene expression patterns induced by the presence of a pathogen (Manger & Relman, 2000 ). Several in vitro studies have explored the effects of infection on the mRNA expression profile of human cells (Table 1
). The effects of Listeria monocytogenes (Cohen et al., 2000b
), Salmonella enterica (Eckmann et al., 2000
) and Salmonella typhimurium (Rosenberger et al., 2000
) have recently been reviewed by Cummings & Relman (2000)
. Briefly, these studies reveal a specific host response, which is modulated by different host factors (Rosenberger et al., 2000
). Other groups are using a more complex approach by comparison of the human cellular transcriptional signatures of pathogenic strains carrying well-defined mutations to get a more detailed view of the mechanisms underlying pathogen clearance (Manger & Relman, 2000
).
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Genomotyping and microbial evolution |
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Industrial applications of microarrays |
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Microarray data analysis |
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A further step towards the prediction of gene function has been made by combining the high-throughput production of data provided by microarrays with a rigorous statistical analysis. Hughes et al. (2000a) have reported a large-scale approach that is intended to avoid problems of biological noise, and to build up a reference database or compendium of patterns of gene expression profiles corresponding to 300 different mutations and chemical treatments in Sacch. cerevisiae. Two-dimensional hierarchical clustering of the obtained expression profiles identified several large groups of coregulated genes. Mutations in genes having similar known functions gave rise to similar profiles, which clustered together, giving an experimental basis for gene function prediction. This tactic has allowed small but coordinated differential gene expression levels to be observed across many different conditions, and to be related to gene function.
In the excitement of pursuing gene expression profiling for entire organisms, we must not lose sight of the fact that mRNA is only one intermediate between DNA and protein. Post-transcriptional and post-translational controls also play a major role in modulating protein expression. Transcriptional analysis may generate hypotheses, but more traditional molecular biological and proteomic approaches are still required to test these hypotheses.
The utility of microarrays now extends to the study of translational initiation. Kuhn et al. (2001) analysed translational regulation of specific mRNAs in yeast. Polysomal fractionation was used in conjunction with microarrays to study changes in translational initiation during diauxic shift. Although overall mRNA translation decreased, the authors identified one group of mRNA species (representing 610 out of 6275 genes examined) whose level of translational initiation was less affected by the change in carbon source. This group corresponded to the genes upregulated on diauxic shift, emphasizing the importance to the cell of mechanisms that ensure the translation of newly expressed genes.
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Reliability of microarray data |
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We have described some of the technical problems commonly encountered with microarrays. It is important to remember that the use of microarrays for gene expression profiling is a recent development, and some aspects of the approach are not completely understood. Therefore, important results obtained with microarrays must be confirmed with other techniques, such as real-time quantitative PCR or Northern blotting, until microarray-based methodologies are completely validated.
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To build or to buy, that is the question |
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The scale of replication required to yield significant data could prove to be a significant barrier to the widespread application of microarray technology. And it is not yet possible for every medium-sized lab to design and print its own microarray slides. In-house microarray technology is still expensive (especially at the level of consumables) and labour-intensive. The equipment for making and analysing microarrays is readily available, at a price. But fierce competition is pushing some companies to release machines before they are completely optimized. We would argue that it is worthwhile to rely on the robust homemade Stanford technology, which is responsible for the majority of microarray publications to date (Thompson et al., 2001 ). The significant investment now being made in genomic and post-genomic centres throughout Europe should allow researchers at all levels to pursue functional genomic approaches, either independently or through collaboration, without needing to set-up in-house facilities. Clearly, financial constraints can be overcome: Oh & Liao (2000)
successfully used a small subarray of 111 E. coli genes involved in central metabolism to investigate metabolic flux.
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Caveat emptor! |
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The future |
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A significant area that needs to be investigated is the utility of microarrays for analysis of mixed bacterial communities. The application of gene expression profiling or genomotyping to obtain information about individual species within a natural community would prove invaluable for microbial ecology and for microbial systematics alike. Assuming that appropriate hybridization stringencies are employed, and given a sufficient microbial diversity within the population of interest, there is no theoretical reason for this approach to fail.
Microarrays can also be used to gain clues to gene function through looking at knockout mutants, particularly of predicted regulatory genes. This approach has already been successfully used by Winzeler et al. (1999b) to follow the growth of pools of 500 yeast knockout mutants under various environmental conditions. Each mutant was tagged with a unique oligonucleotide sequence (a molecular barcode) that was detected by hybridization to a custom-built microarray to determine growth conditions when certain mutants were unable to grow. This methodology combined with a massive parallel analysis of mapped mutants (Ross-Macdonald et al., 1999
; Spradling et al., 1999
) offers a rapid route to determining the function of the FUN genes found in every microbial genome (Hinton, 1997
).
The application of microbial gene expression profiling is only limited by our imagination! Bacteria have been used for decades as sensitive biosensors for mutagenicity (Maron & Ames, 1983 ), and this approach has recently been brought up to date. E. coli has been used to determine the effects of microwave radiation produced by mobile telephones. Macroarray analysis demonstrated that 13 genes were induced by a 2 h exposure to a commercial mobile telephone (A. Morby, personal communication). As we integrate the power of microarray analyses with our particular research interests, more creative applications are bound to arise.
We are moving from the period of genomics towards the post-genomic future and we are entering what is arguably the most exciting period in the history of microbiology. At last we have the potential to ask questions at a relevant scale, that of the whole genome and hence the whole organism. We are optimistic that swift progress will be made as we learn to implement microarray technology more effectively, and we look forward to the time when innovative ideas can be tested extremely quickly.
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