Do DNA microarrays have their future behind them?

Performance evaluation of multiplex PCR including Aspergillus-not so simple!

Multiplex PCRs have been designed for including species other than Aspergillus fumigatus for the diagnosis of invasive aspergillosis, such as microarrays, liquid-phase array, and electrospray-ionization mass spectrometry (PCR/ESI MS). These methods are based on the selection of multiple primers to amplify different species with the specificity checked by hybridization to a probe or by base composition of the amplicon for the PCR/ESI MS. When testing complex samples such as respiratory specimens, some clinically relevant species can be missed. Indeed, it is impossible to design primers able to amplify all the known fungal species with the same efficiency. Therefore, the best amplified species may not be the most clinically relevant. Multiplex assays have also been proposed to detect A. fumigatus DNA and azole resistance. Since the gene responsible for azole resistance is single copy and the gene used for detection is multicopy, only the high fungal loads can be evaluated. Thus, although interesting for investigating mycobiome, the multiplex assays should be used with cautious for the diagnosis of IA or the detection of resistance. For the diagnosis of invasive aspergillosis, validated quantitative PCRs specifically targeting A. fumigatus or a limited set of species to increase sensitivity is a safer option.

MicroRNA heterogeneity in endometrial cancer cell lines revealed by deep sequencing

The aim of the present study was to obtain comprehensive microRNA (miRNA) profiles of type I [Ishikawa (ISK)] and type II (HEC-1B) human endometrial adenocarcinoma cell lines, utilizing the latest high-throughput sequencing techniques. RNA was extracted from ISK and HEC-1B cell lines. Sequencing results were obtained from a next-generation sequencing platform. Using the miRBase database and a series of software pipelines, miRNA expression was analyzed in the ISK and HEC-1B cell lines. It was revealed that the type and quantity of miRNAs in the two cell types varied significantly; 34 miRNAs were upregulated and 105 miRNAs were downregulated in HEC-1B cells compared with those of ISK cells. Furthermore, it was observed that the expression pattern of the miRNA (miR)-17-92 cluster differed between the two cell types, and the expression levels of the miR-200 family in ISK cells were markedly increased compared with those of HEC-1B cells. The present study therefore identified potential novel biomarkers, which may be useful in the differentiation between type I and type II endometrial cancer, and also revealed miRNA alterations that may be associated with endometrial cancer and its underlying pathogenic mechanisms.

Whole-genome gene expression profiling revealed genes and pathways potentially involved in regulating interactions of soybean with cyst nematode (Heterodera glycines Ichinohe)

BACKGROUND

Soybean cyst nematode (SCN, Heterodera glycines Ichinohe) is the most devastating pathogen of soybean. Many gene expression profiling studies have been conducted to investigate the responses of soybean to the infection by this pathogen using primarily the first-generation soybean genome array that covered approximately 37,500 soybean transcripts. However, no study has been reported yet using the second-generation Affymetrix soybean whole-genome transcript array (Soybean WT array) that represents approximately 66,000 predicted soybean transcripts.

RESULTS

In the present work, the gene expression profiles of two soybean plant introductions (PIs) PI 437654 and PI 567516C (both resistant to multiple SCN HG Types) and cultivar Magellan (susceptible to SCN) were compared in the presence or absence of the SCN inoculum at 3 and 8 days post-inoculation using the Soybean WT array. Data analysis revealed that the two resistant soybean lines showed distinctive gene expression profiles from each other and from Magellan not only in response to the SCN inoculation, but also in the absence of SCN. Overall, 1,413 genes and many pathways were revealed to be differentially regulated. Among them, 297 genes were constitutively regulated in the two resistant lines (compared with Magellan) and 1,146 genes were responsive to the SCN inoculation in the three lines, with 30 genes regulated both constitutively and by SCN. In addition to the findings similar to those in the published work, many genes involved in ethylene, protein degradation, and phenylpropanoid pathways were also revealed differentially regulated in the present study. GC-rich elements (e.g., GCATGC) were found over-represented in the promoter regions of certain groups of genes. These have not been observed before, and could be new defense-responsive regulatory elements.

CONCLUSIONS

Different soybean lines showed different gene expression profiles in the presence and absence of the SCN inoculum. Both inducible and constitutive gene expression may contribute to resistance to multiple SCN HG Types in the resistant soybean PI lines. Ethylene, protein degradation, and phenylpropanoid pathways, as well as many other pathways reported previously, may play important roles in mediating the soybean-SCN interactions. The revealed genes, pathways, and promoter elements can be further explored to regulate or engineer soybean for resistance to SCN.

High-Throughput Sequencing, a VersatileWeapon to Support Genome-Based Diagnosis in Infectious Diseases: Applications to Clinical Bacteriology

The recent progresses of high-throughput sequencing (HTS) technologies enable easy and cost-reduced access to whole genome sequencing (WGS) or re-sequencing. HTS associated with adapted, automatic and fast bioinformatics solutions for sequencing applications promises an accurate and timely identification and characterization of pathogenic agents. Many studies have demonstrated that data obtained from HTS analysis have allowed genome-based diagnosis, which has been consistent with phenotypic observations. These proofs of concept are probably the first steps toward the future of clinical microbiology. From concept to routine use, many parameters need to be considered to promote HTS as a powerful tool to help physicians and clinicians in microbiological investigations. This review highlights the milestones to be completed toward this purpose.

MRE11A and SKP2 genes are associated with the increased cytotoxicity induced by the synergistic effects of cisplatin and gemcitabine in bladder cancer cells

The combination of gemcitabine and cisplatin has been shown previously to elicit a synergistic therapeutic effect on bladder cancer cell lines and result in reduced cell survival. However, the precise mechanism by which cells die has not been elucidated. Cell cycle-related genes are the predominant targets of chemotherapeutic protocols. Therefore, molecular biomarkers that are predictive of therapeutic outcomes associated with tumor sensitivity might be important for optimal treatment protocol selection. The aim of this study was to investigate the changes in gene expression in cell cycle-related genes that were induced by cisplatin, gemcitabine or a combined treatment using both agents in a low-grade urinary bladder transitional carcinoma cell line (RT4). The following three treatment protocols were used: 1.0 μM cisplatin, 1.56 μM gemcitabine and a combination of 1.0 μM cisplatin and 1.56 μM gemcitabine. Cytometry and morphology analysis (by phase-contrast photomicrography) were performed in addition to pathway-specific gene expression analysis using quantitative RT-PCR gene arrays. The following results were observed after 1.0 μM cisplatin treatment: (1) a decrease in cell number, (2) an increased percentage of scattered cells and (3) downregulated expression of genes related to cell cycle arrest, G1/S-to-mitotic cell cycle transition, DNA repair, apoptosis, transcription and mitosis. Treatment with 1.56 μM gemcitabine, or with both drugs simultaneously, induced the following effects: (1) a decrease in cell number, (2) an increased percentage of scattered and elongated cells, (3) the modulation of genes that are predominantly involved in DNA repair and (4) a significant upregulation of genes related to cell cycle arrest. Reduced cell density was observed after the combined treatment compared to the two other single-agent protocols. The downregulation of MRE11A and SKP2 was observed only in cells subjected to the combined treatment. In conclusion, cisplatin, gemcitabine and the combination of both drugs elicited distinct toxicogenomic effects in the RT4 bladder transitional carcinoma cell line, although disruptions in the expression of cell cycle control-related genes and other pathways responsible for cell survival were observed for all of the protocols. MRE11A and SKP2 downregulation appeared to be responsible for the synergistic therapeutic effects elicited by cisplatin and gemcitabine.

Toxicogenomic activity of gemcitabine in two TP53-mutated bladder cancer cell lines: special focus on cell cycle-related genes

Because of its lower toxicity and good tolerability and response, gemcitabine has been described as one of the most highly promising drugs for urinary bladder cancer therapy. Its phosphorylated active-dFdCTP metabolite can incorporate into DNA, causing replication blockage. Additionally, it is known that mutations in the TP53 gene are related to the high recurrence rate of these neoplasias. Based on these premises, we investigated the effects of gemcitabine on the expression of the cell cycle-related genes in two different TP53-mutated bladder transitional carcinoma cell lines-5637 (from a moderate-grade tumor with a TP53 allele carrying two mutations) and T24 (from an invasive tumor with a TP53 allele encoding an in-frame deletion). Cell viability and morphology analyses (phase-contrast photomicrographs), Nuclear Division Index and pathway-specific quantitative RT-PCR gene arrays were performed. Treatment with gemcitabine led to the following results: (1) a significant decrease of viable T24 cells after treatment at the highest concentration (3.12 μM) tested; (2) scattered, elongated and vacuolated 5637 and T24 cells; (3) a cytostatic effect in both cell lines; and (4) significant upregulation of the BRCA1, CCNE1, CDK2, CDK6, CDKN1A, CDKN2B, E2F4, GADD45A, MAD2L2, CCNH, SERTAD1, CDC1, and CHEK1 genes. Gemcitabine had distinct toxicogenomic effects in the bladder transitional carcinoma cell lines with two different TP53 mutations. However, independent of the type of mutation and tumor grade, gemcitabine induced cell cycle arrest; upregulation of DNA repair-related genes, G1/S transition, apoptosis and activation of transcription factors, mainly by upregulation of the CCNE1, CDKN1A and GADD45A genes.

A platform for combined DNA and protein microarrays based on total internal reflection fluorescence

We have developed a novel microarray technology based on total internal reflection fluorescence (TIRF) in combination with DNA and protein bioassays immobilized at the TIRF surface. Unlike conventional microarrays that exhibit reduced signal-to-background ratio, require several stages of incubation, rinsing and stringency control, and measure only end-point results, our TIRF microarray technology provides several orders of magnitude better signal-to-background ratio, performs analysis rapidly in one step, and measures the entire course of association and dissociation kinetics between target DNA and protein molecules and the bioassays. In many practical cases detection of only DNA or protein markers alone does not provide the necessary accuracy for diagnosing a disease or detecting a pathogen. Here we describe TIRF microarrays that detect DNA and protein markers simultaneously, which reduces the probabilities of false responses. Supersensitive and multiplexed TIRF DNA and protein microarray technology may provide a platform for accurate diagnosis or enhanced research studies. Our TIRF microarray system can be mounted on upright or inverted microscopes or interfaced directly with CCD cameras equipped with a single objective, facilitating the development of portable devices. As proof-of-concept we applied TIRF microarrays for detecting molecular markers from Bacillus anthracis, the pathogen responsible for anthrax.

Using genome-wide expression profiling to define gene networks relevant to the study of complex traits: from RNA integrity to network topology

Postgenomic studies of the function of genes and their role in disease have now become an area of intense study since efforts to define the raw sequence material of the genome have largely been completed. The use of whole-genome approaches such as microarray expression profiling and, more recently, RNA-sequence analysis of transcript abundance has allowed an unprecedented look at the workings of the genome. However, the accurate derivation of such high-throughput data and their analysis in terms of biological function has been critical to truly leveraging the postgenomic revolution. This chapter will describe an approach that focuses on the use of gene networks to both organize and interpret genomic expression data. Such networks, derived from statistical analysis of large genomic datasets and the application of multiple bioinformatics data resources, potentially allow the identification of key control elements for networks associated with human disease, and thus may lead to derivation of novel therapeutic approaches. However, as discussed in this chapter, the leveraging of such networks cannot occur without a thorough understanding of the technical and statistical factors influencing the derivation of genomic expression data. Thus, while the catch phrase may be "it's the network … stupid," the understanding of factors extending from RNA isolation to genomic profiling technique, multivariate statistics, and bioinformatics are all critical to defining fully useful gene networks for study of complex biology.

Quality assurance of RNA expression profiling in clinical laboratories

RNA expression profiles are increasingly used to diagnose and classify disease, based on expression patterns of as many as several thousand RNAs. To ensure quality of expression profiling services in clinical settings, a standard operating procedure incorporates multiple quality indicators and controls, beginning with preanalytic specimen preparation and proceeding thorough analysis, interpretation, and reporting. Before testing, histopathological examination of each cellular specimen, along with optional cell enrichment procedures, ensures adequacy of the input tissue. Other tactics include endogenous controls to evaluate adequacy of RNA and exogenous or spiked controls to evaluate run- and patient-specific performance of the test system, respectively. Unique aspects of quality assurance for array-based tests include controls for the pertinent outcome signatures that often supersede controls for each individual analyte, built-in redundancy for critical analytes or biochemical pathways, and software-supported scrutiny of abundant data by a laboratory physician who interprets the findings in a manner facilitating appropriate medical intervention. Access to high-quality reagents, instruments, and software from commercial sources promotes standardization and adoption in clinical settings, once an assay is vetted in validation studies as being analytically sound and clinically useful. Careful attention to the well-honed principles of laboratory medicine, along with guidance from government and professional groups on strategies to preserve RNA and manage large data sets, promotes clinical-grade assay performance.

Microbial Diagnostic Microarrays for the Detection and Typing of Food- and Water-Borne (Bacterial) Pathogens

Reliable and sensitive pathogen detection in clinical and environmental (including food and water) samples is of greatest importance for public health. Standard microbiological methods have several limitations and improved alternatives are needed. Most important requirements for reliable analysis include: (i) specificity; (ii) sensitivity; (iii) multiplexing potential; (iv) robustness; (v) speed; (vi) automation potential; and (vii) low cost. Microarray technology can, through its very nature, fulfill many of these requirements directly and the remaining challenges have been tackled. In this review, we attempt to compare performance characteristics of the microbial diagnostic microarrays developed for the detection and typing of food and water pathogens, and discuss limitations, points still to be addressed and issues specific for the analysis of food, water and environmental samples.

Clinical implementation of RNA signatures for pharmacogenomic decision-making

RNA profiling is increasingly used to predict drug response, dose, or toxicity based on analysis of drug pharmacokinetic or pharmacodynamic pathways. Before implementing multiplexed RNA arrays in clinical practice, validation studies are carried out to demonstrate sufficient evidence of analytic and clinical performance, and to establish an assay protocol with quality assurance measures. Pathologists assure quality by selecting input tissue and by interpreting results in the context of the input tissue as well as the technologies that were used and the clinical setting in which the test was ordered. A strength of RNA profiling is the array-based measurement of tens to thousands of RNAs at once, including redundant tests for critical analytes or pathways to promote confidence in test results. Instrument and reagent manufacturers are crucial for supplying reliable components of the test system. Strategies for quality assurance include careful attention to RNA preservation and quality checks at pertinent steps in the assay protocol, beginning with specimen collection and proceeding through the various phases of transport, processing, storage, analysis, interpretation, and reporting. Specimen quality is checked by probing housekeeping transcripts, while spiked and exogenous controls serve as a check on analytic performance of the test system. Software is required to manipulate abundant array data and present it for interpretation by a laboratory physician who reports results in a manner facilitating therapeutic decision-making. Maintenance of the assay requires periodic documentation of personnel competency and laboratory proficiency. These strategies are shepherding genomic arrays into clinical settings to provide added value to patients and to the larger health care system.

Virulence evolution of the human pathogen Neisseria meningitidis by recombination in the core and accessory genome

Background

Neisseria meningitidis is a naturally transformable, facultative pathogen colonizing the human nasopharynx. Here, we analyze on a genome-wide level the impact of recombination on gene-complement diversity and virulence evolution in N. meningitidis. We combined comparative genome hybridization using microarrays (mCGH) and multilocus sequence typing (MLST) of 29 meningococcal isolates with computational comparison of a subset of seven meningococcal genome sequences.

Principal Findings

We found that lateral gene transfer of minimal mobile elements as well as prophages are major forces shaping meningococcal population structure. Extensive gene content comparison revealed novel associations of virulence with genetic elements besides the recently discovered meningococcal disease associated (MDA) island. In particular, we identified an association of virulence with a recently described canonical genomic island termed IHT-E and a differential distribution of genes encoding RTX toxin- and two-partner secretion systems among hyperinvasive and non-hyperinvasive lineages. By computationally screening also the core genome for signs of recombination, we provided evidence that about 40% of the meningococcal core genes are affected by recombination primarily within metabolic genes as well as genes involved in DNA replication and repair. By comparison with the results of previous mCGH studies, our data indicated that genetic structuring as revealed by mCGH is stable over time and highly similar for isolates from different geographic origins.

Conclusions

Recombination comprising lateral transfer of entire genes as well as homologous intragenic recombination has a profound impact on meningococcal population structure and genome composition. Our data support the hypothesis that meningococcal virulence is polygenic in nature and that differences in metabolism might contribute to virulence.

Expression of genes related to apoptosis, cell cycle and signaling pathways are independent of TP53 status in urinary bladder cancer cells

Urinary bladder cancer is the fourth most common malignancy in the Western world. Transitional cell carcinoma (TCC) is the most common subtype, accounting for about 90% of all bladder cancers. The TP53 gene plays an essential role in the regulation of the cell cycle and apoptosis and therefore contributes to cellular transformation and malignancy; however, little is known about the differential gene expression patterns in human tumors that present with the wild-type or mutated TP53 gene. Therefore, because gene profiling can provide new insights into the molecular biology of bladder cancer, the present study aimed to compare the molecular profiles of bladder cancer cell lines with different TP53 alleles, including the wild type (RT4) and two mutants (5637, with mutations in codons 280 and 72; and T24, a TP53 allele encoding an in-frame deletion of tyrosine 126). Unsupervised hierarchical clustering and gene networks were constructed based on data generated by cDNA microarrays using mRNA from the three cell lines. Differentially expressed genes related to the cell cycle, cell division, cell death, and cell proliferation were observed in the three cell lines. However, the cDNA microarray data did not cluster cell lines based on their TP53 allele. The gene profiles of the RT4 cells were more similar to those of T24 than to those of the 5637 cells. While the deregulation of both the cell cycle and the apoptotic pathways was particularly related to TCC, these alterations were not associated with the TP53 status.

Evaluation of one- and two-color gene expression arrays for microbial comparative genome hybridization analyses in routine applications

DNA microarray technology has already revolutionized basic research in infectious diseases, and whole-genome sequencing efforts have allowed for the fabrication of tailor-made spotted microarrays for an increasing number of bacterial pathogens. However, the application of microarrays in diagnostic microbiology is currently hampered by the high costs associated with microarray experiments and the specialized equipment needed. Here, we show that a thorough bioinformatic postprocessing of the microarray design to reduce the amount of unspecific noise also allows the reliable use of spotted gene expression microarrays for gene content analyses. We further demonstrate that the use of only single-color labeling to halve the costs for dye-labeled nucleotides results in only a moderate decrease in overall specificity and sensitivity. Therefore, gene expression microarrays using only single-color labeling can also reliably be used for gene content analyses, thus reducing the costs for potential routine applications such as genome-based pathogen detection or strain typing.

Transcriptome analysis of porcine PBMCs after in vitro stimulation by LPS or PMA/ionomycin using an expression array targeting the pig immune response

Background

Designing sustainable animal production systems that better balance productivity and resistance to disease is a major concern. In order to address questions related to immunity and resistance to disease in pig, it is necessary to increase knowledge on its immune system and to produce efficient tools dedicated to this species.

Results

A long-oligonucleotide-based chip referred to as SLA-RI/NRSP8-13K was produced by combining a generic set with a newly designed SLA-RI set that targets all annotated loci of the pig major histocompatibility complex (MHC) region (SLA complex) in both orientations as well as immunity genes outside the SLA complex.

The chip was used to study the immune response of pigs following stimulation of porcine peripheral blood mononuclear cells (PBMCs) with lipopolysaccharide (LPS) or a mixture of phorbol myristate acetate (PMA) and ionomycin for 24 hours. Transcriptome analysis revealed that ten times more genes were differentially expressed after PMA/ionomycin stimulation than after LPS stimulation. LPS stimulation induced a general inflammation response with over-expression of SAA1, pro-inflammatory chemokines IL8, CCL2, CXCL5, CXCL3, CXCL2 and CCL8 as well as genes related to oxidative processes (SOD2) and calcium pathways (S100A9 and S100A12). PMA/ionomycin stimulation induced a stronger up-regulation of T cell activation than of B cell activation with dominance toward a Th1 response, including IL2, CD69 and TNFRSF9 (tumor necrosis factor receptor superfamily, member 9) genes. In addition, a very intense repression of THBS1 (thrombospondin 1) was observed. Repression of MHC class I genes was observed after PMA/ionomycin stimulation despite an up-regulation of the gene cascade involved in peptide processing. Repression of MHC class II genes was observed after both stimulations. Our results provide preliminary data suggesting that antisense transcripts mapping to the SLA complex may have a role during immune response.

Conclusion

The SLA-RI/NRSP8-13K chip was found to accurately decipher two distinct immune response activations of PBMCs indicating that it constitutes a valuable tool to further study immunity and resistance to disease in pig. The transcriptome analysis revealed specific and common features of the immune responses depending on the stimulation agent that increase knowledge on pig immunity.

AGRONOMICS1: a new resource for Arabidopsis transcriptome profiling

Transcriptome profiling has become a routine tool in biology. For Arabidopsis (Arabidopsis thaliana), the Affymetrix ATH1 expression array is most commonly used, but it lacks about one-third of all annotated genes present in the reference strain. An alternative are tiling arrays, but previous designs have not allowed the simultaneous analysis of both strands on a single array. We introduce AGRONOMICS1, a new Affymetrix Arabidopsis microarray that contains the complete paths of both genome strands, with on average one 25mer probe per 35-bp genome sequence window. In addition, the new AGRONOMICS1 array contains all perfect match probes from the original ATH1 array, allowing for seamless integration of the very large existing ATH1 knowledge base. The AGRONOMICS1 array can be used for diverse functional genomics applications such as reliable expression profiling of more than 30,000 genes, detection of alternative splicing, and chromatin immunoprecipitation coupled to microarrays (ChIP-chip). Here, we describe the design of the array and compare its performance with that of the ATH1 array. We find results from both microarrays to be of similar quality, but AGRONOMICS1 arrays yield robust expression information for many more genes, as expected. Analysis of the ATH1 probes on AGRONOMICS1 arrays produces results that closely mirror those of ATH1 arrays. Finally, the AGRONOMICS1 array is shown to be useful for ChIP-chip experiments. We show that heterochromatic H3K9me2 is strongly confined to the gene body of target genes in euchromatic chromosome regions, suggesting that spreading of heterochromatin is limited outside of pericentromeric regions.

Target amplification for broad spectrum microbial diagnostics and detection

Microarrays are massively parallel detection platforms that were first used extensively for gene expression studies, but have also been successfully applied to microbial detection in a number of diverse fields requiring broad-range microbial identification. This technology has enabled researchers to gain an insight into the microbial diversity of environmental samples, facilitated discovery of a number of new pathogens and enabled studies of multipathogen infections. In contrast to gene expression studies, the concentrations of targets in analyzed samples for microbial detection are usually much lower, and require the use of nucleic acid amplification techniques. The rapid advancement of manufacturing technologies has increased the content of the microarrays; thus, the required amplification is a challenging problem. The constant parallel improvements in both microarray and sample amplification techniques in the near future may lead to a radical progression in medical diagnostics and systems for efficient detection of microorganisms in the environment.

Analyzing mRNA expression using single mRNA resolution fluorescent in situ hybridization

As the product of transcription and the blueprint for translation, mRNA is the main intermediate product of the gene expression pathway. The ability to accurately determine mRNA levels is, therefore, a major requirement when studying gene expression. mRNA is also a target of different regulatory steps, occurring in different subcellular compartments. To understand the different steps of gene expression regulation, it is therefore essential to analyze mRNA in the context of a single cell, maintaining spatial information. Here, we describe a stepwise protocol for fluorescent in situ hybridization (FISH) that allows detection of individual mRNAs in single yeast cells. This method allows quantitative analysis of mRNA expression in single cells, permitting "absolute" quantification by simply counting mRNAs. It further allows us to study many aspects of mRNA metabolism, from transcription to processing, localization, and mRNA degradation.

Dramatic increase in signal by integration of polymerase chain reaction and hybridization on surface of DNA microarray

The cumbersome process required for diagnosis by DNA microarray can be simplified by simple extraction of nucleic acid from cells and by integration of liquid-phase polymerase chain reaction (PCR) and hybridization on the surface of a microarray slide. An unexpected benefit was the large (five- to sixfold) increase in detection signal that also is translated into an increase in sensitivity and the confidence level of diagnosis. The large increase in the detection signal appears to be due to participation of PCR primers as well as to extension of the immobilized capture probes during the hybridization process. The reason for the large increase in signal is not clear in view of only one round of DNA synthesis during the hybridization step. The integrated process correctly identified various genotypes of human papillomavirus (HPV) in the infected clinical human cervical specimens with specificity and efficiency. The process described in this article saves labor, time, and cost and should be applicable for automation of diagnosis by DNA microarray.

Microarray comparative genomic hybridisation analysis incorporating genomic organisation, and application to enterobacterial plant pathogens

Microarray comparative genomic hybridisation (aCGH) provides an estimate of the relative abundance of genomic DNA (gDNA) taken from comparator and reference organisms by hybridisation to a microarray containing probes that represent sequences from the reference organism. The experimental method is used in a number of biological applications, including the detection of human chromosomal aberrations, and in comparative genomic analysis of bacterial strains, but optimisation of the analysis is desirable in each problem domain.We present a method for analysis of bacterial aCGH data that encodes spatial information from the reference genome in a hidden Markov model. This technique is the first such method to be validated in comparisons of sequenced bacteria that diverge at the strain and at the genus level: Pectobacterium atrosepticum SCRI1043 (Pba1043) and Dickeya dadantii 3937 (Dda3937); and Lactococcus lactis subsp. lactis IL1403 and L. lactis subsp. cremoris MG1363. In all cases our method is found to outperform common and widely used aCGH analysis methods that do not incorporate spatial information. This analysis is applied to comparisons between commercially important plant pathogenic soft-rotting enterobacteria (SRE) Pba1043, P. atrosepticum SCRI1039, P. carotovorum 193, and Dda3937.Our analysis indicates that it should not be assumed that hybridisation strength is a reliable proxy for sequence identity in aCGH experiments, and robustly extends the applicability of aCGH to bacterial comparisons at the genus level. Our results in the SRE further provide evidence for a dynamic, plastic 'accessory' genome, revealing major genomic islands encoding gene products that provide insight into, and may play a direct role in determining, variation amongst the SRE in terms of their environmental survival, host range and aetiology, such as phytotoxin synthesis, multidrug resistance, and nitrogen fixation.