ArrayOme: a program for estimating the sizes of microarray-visualized bacterial genomes

ArrayOme is a new program that calculates the size of genomes represented by microarray-based probes and facilitates recognition of key bacterial strains carrying large numbers of novel genes. Protein-coding sequences (CDS) that are contiguous on annotated reference templates and classified as ‘Present’ in the test strain by hybridization to microarrays are merged into ICs (ICs). These ICs are then extended to account for flanking intergenic sequences. Finally, the lengths of all extended ICs are summated to yield the ‘microarray-visualized genome (MVG)’ size. We tested and validated ArrayOme using both experimental and in silico-generated genomic hybridization data. MVG sizing of five sequenced Escherichia coli and Shigella strains resulted in an accuracy of 97–99%, as compared to true genome sizes, when the comprehensive ShE.coli meta-array gene sequences (6239 CDS) were used for in silico hybridization analysis. However, the E.coli CFT073 genome size was underestimated by 14% as this meta-array lacked probes for many CFT073 CDS. ArrayOme permits rapid recognition of discordances between PFGE-measured genome and MVG sizes, thereby enabling high-throughput identification of strains rich in novel genes. Gene discovery studies focused on these strains will greatly facilitate characterization of the global gene pool accessible to individual bacterial species

Deep Sequencing Analysis of Small Noncoding RNA and mRNA Targets of the Global Post-Transcriptional Regulator, Hfq

Recent advances in high-throughput pyrosequencing (HTPS) technology now allow a thorough analysis of RNA bound to cellular proteins, and, therefore, of post-transcriptional regulons. We used HTPS to discover the Salmonella RNAs that are targeted by the common bacterial Sm-like protein, Hfq. Initial transcriptomic analysis revealed that Hfq controls the expression of almost a fifth of all Salmonella genes, including several horizontally acquired pathogenicity islands (SPI-1, -2, -4, -5), two sigma factor regulons, and the flagellar gene cascade. Subsequent HTPS analysis of 350,000 cDNAs, derived from RNA co-immunoprecipitation (coIP) with epitope-tagged Hfq or control coIP, identified 727 mRNAs that are Hfq-bound in vivo. The cDNA analysis discovered new, small noncoding RNAs (sRNAs) and more than doubled the number of sRNAs known to be expressed in Salmonella to 64; about half of these are associated with Hfq. Our analysis explained aspects of the pleiotropic effects of Hfq loss-of-function. Specifically, we found that the mRNAs of hilD (master regulator of the SPI-1 invasion genes) and flhDC (flagellar master regulator) were bound by Hfq. We predicted that defective SPI-1 secretion and flagellar phenotypes of the hfq mutant would be rescued by overexpression of HilD and FlhDC, and we proved this to be correct. The combination of epitope-tagging and HTPS of immunoprecipitated RNA detected the expression of many intergenic chromosomal regions of Salmonella. Our approach overcomes the limited availability of high-density microarrays that have impeded expression-based sRNA discovery in microorganisms. We present a generic strategy that is ideal for the systems-level analysis of the post-transcriptional regulons of RNA-binding proteins and for sRNA discovery in a wide range of bacteria

The transcriptional programme of Salmonella enterica serovar Typhimurium reveals a key role for tryptophan metabolism in biofilms

<p>Abstract</p> <p>Background</p> <p>Biofilm formation enhances the capacity of pathogenic <it>Salmonella </it>bacteria to survive stresses that are commonly encountered within food processing and during host infection. The persistence of <it>Salmonella </it>within the food chain has become a major health concern, as biofilms can serve as a reservoir for the contamination of food products. While the molecular mechanisms required for the survival of bacteria on surfaces are not fully understood, transcriptional studies of other bacteria have demonstrated that biofilm growth triggers the expression of specific sets of genes, compared with planktonic cells. Until now, most gene expression studies of <it>Salmonella </it>have focused on the effect of infection-relevant stressors on virulence or the comparison of mutant and wild-type bacteria. However little is known about the physiological responses taking place inside a <it>Salmonella </it>biofilm.</p> <p>Results</p> <p>We have determined the transcriptomic and proteomic profiles of biofilms of <it>Salmonella enterica </it>serovar Typhimurium. We discovered that 124 detectable proteins were differentially expressed in the biofilm compared with planktonic cells, and that 10% of the <it>S</it>. Typhimurium genome (433 genes) showed a 2-fold or more change in the biofilm compared with planktonic cells. The genes that were significantly up-regulated implicated certain cellular processes in biofilm development including amino acid metabolism, cell motility, global regulation and tolerance to stress. We found that the most highly down-regulated genes in the biofilm were located on <it>Salmonella </it>Pathogenicity Island 2 (SPI2), and that a functional SPI2 secretion system regulator (<it>ssrA</it>) was required for <it>S</it>. Typhimurium biofilm formation. We identified STM0341 as a gene of unknown function that was needed for biofilm growth. Genes involved in tryptophan (<it>trp</it>) biosynthesis and transport were up-regulated in the biofilm. Deletion of <it>trpE </it>led to decreased bacterial attachment and this biofilm defect was restored by exogenous tryptophan or indole.</p> <p>Conclusions</p> <p>Biofilm growth of <it>S</it>. Typhimurium causes distinct changes in gene and protein expression. Our results show that aromatic amino acids make an important contribution to biofilm formation and reveal a link between SPI2 expression and surface-associated growth in <it>S</it>. Typhimurium.</p

A short-oligonucleotide microarray that allows improved detection of gastrointestinal tract microbial communities

<p>Abstract</p> <p>Background</p> <p>The human gastrointestinal (GI) tract contains a diverse collection of bacteria, most of which are unculturable by conventional microbiological methods. Increasingly molecular profiling techniques are being employed to examine this complex microbial community. The purpose of this study was to develop a microarray technique based on 16S ribosomal gene sequences for rapidly monitoring the microbial population of the GI tract.</p> <p>Results</p> <p>We have developed a culture-independent, semi-quantitative, rapid method for detection of gut bacterial populations based on 16S rDNA probes using a DNA microarray. We compared the performance of microarrays based on long (40- and 50-mer) and short (16–21-mer) oligonucleotides. Short oligonucleotides consistently gave higher specificity. Optimal DNA amplification and labelling, hybridisation and washing conditions were determined using a probe with an increasing number of nucleotide mismatches, identifying the minimum number of nucleotides needed to distinguish between perfect and mismatch probes. An independent PCR-based control was used to normalise different hybridisation results, and to make comparisons between different samples, greatly improving the detection of changes in the gut bacterial population. The sensitivity of the microarray was determined to be 8.8 × 10⁴bacterial cells g^-1faecal sample, which is more sensitive than a number of existing profiling methods. The short oligonucleotide microarray was used to compare the faecal flora from healthy individuals and a patient suffering from Ulcerative Colitis (UC) during the active and remission states. Differences were identified in the bacterial profiles between healthy individuals and a UC patient. These variations were verified by Denaturing Gradient Gel Electrophoresis (DGGE) and DNA sequencing.</p> <p>Conclusion</p> <p>In this study we demonstrate the design, testing and application of a highly sensitive, short oligonucleotide community microarray. Our approach allows the rapid discrimination of bacteria inhabiting the human GI tract, at taxonomic levels ranging from species to the superkingdom bacteria. The optimised protocol is available at: <url>http://www.ifr.ac.uk/safety/microarrays/#protocols</url>. It offers a high throughput method for studying the dynamics of the bacterial population over time and between individuals.</p

BABAR: an R package to simplify the normalisation of common reference design microarray-based transcriptomic datasets

Background: The development of DNA microarrays has facilitated the generation of hundreds of thousands of transcriptomic datasets. The use of a common reference microarray design allows existing transcriptomic data to be readily compared and re-analysed in the light of new data, and the combination of this design with large datasets is ideal for 'systems' level analyses. One issue is that these datasets are typically collected over many years and may be heterogeneous in nature, containing different microarray file formats and gene array layouts, dye-swaps, and showing varying scales of log(2)- ratios of expression between microarrays. Excellent software exists for the normalisation and analysis of microarray data but many data have yet to be analysed as existing methods struggle with heterogeneous datasets; options include normalising microarrays on an individual or experimental group basis. Our solution was to develop the Batch Anti-Banana Algorithm in R (BABAR) algorithm and software package which uses cyclic loess to normalise across the complete dataset. We have already used BABAR to analyse the function of Salmonella genes involved in the process of infection of mammalian cells. Results: The only input required by BABAR is unprocessed GenePix or BlueFuse microarray data files. BABAR provides a combination of 'within' and 'between' microarray normalisation steps and diagnostic boxplots. When applied to a real heterogeneous dataset, BABAR normalised the dataset to produce a comparable scaling between the microarrays, with the microarray data in excellent agreement with RT-PCR analysis. When applied to a real non-heterogeneous dataset and a simulated dataset, BABAR's performance in identifying differentially expressed genes showed some benefits over standard techniques. Conclusions: BABAR is an easy-to-use software tool, simplifying the simultaneous normalisation of heterogeneous two-colour common reference design cDNA microarray-based transcriptomic datasets. We show BABAR transforms real and simulated datasets to allow for the correct interpretation of these data, and is the ideal tool to facilitate the identification of differentially expressed genes or network inference analysis from transcriptomic datasets

A short noncoding viral DNA element showing characteristics of a replication origin confers Bacteriophage resistance to Streptococcus thermophiles.

A 302-bp noncoding DNA fragment from the DNA replication module of phage φSfi21 was shown to protect theStreptococcus thermophilusstrainSfi1 from infection by 17 of 25 phages. The phage-inhibitory DNA possesses two determinants, each of which individually mediated phage resistance. The phage-inhibitory activity was copy number dependent and operates by blocking the accumulation of phage DNA. Furthermore, when cloned on a plasmid, the φSfi21 DNA acts as an origin of replication driven by phage infection. Protein or proteins in the φSfi21-infected cells were shown to interact with this phage-inhibitory DNA fragment, forming a retarded protein–DNA complex in gel retardation assays. A model in which phage proteins interact with the inhibitory DNA such that they are no longer available for phage propagation can be used to explain the observed bacteriophage resistance. Genome analysis of φSfi19, a phage that is insensitive to the inhibitory activity of the φSfi21-derived DNA, led to the characterisation of a variant putative phage replication origin that differed in 14 of 302 nucleotides from that of φSfi21. The variant origin was cloned and exhibited an inhibitory activity toward phages that were insensitive to the φSfi21-derived DNA

Transcriptomic Analysis of Escherichia coli O157:H7 and K-12 Cultures Exposed to Inorganic and Organic Acids in Stationary Phase Reveals Acidulant- and Strain-Specific Acid Tolerance Responses ▿ †

The food-borne pathogen Escherichia coli O157:H7 is commonly exposed to organic acid in processed and preserved foods, allowing adaptation and the development of tolerance to pH levels otherwise lethal. Since little is known about the molecular basis of adaptation of E. coli to organic acids, we studied K-12 MG1655 and O157:H7 Sakai during exposure to acetic, lactic, and hydrochloric acid at pH 5.5. This is the first analysis of the pH-dependent transcriptomic response of stationary-phase E. coli. Thirty-four genes and three intergenic regions were upregulated by both strains during exposure to all acids. This universal acid response included genes involved in oxidative, envelope, and cold stress resistance and iron and manganese uptake, as well as 10 genes of unknown function. Acidulant- and strain-specific responses were also revealed. The acidulant-specific response reflects differences in the modes of microbial inactivation, even between weak organic acids. The two strains exhibited similar responses to lactic and hydrochloric acid, while the response to acetic acid was distinct. Acidulant-dependent differences between the strains involved induction of genes involved in the heat shock response, osmoregulation, inorganic ion and nucleotide transport and metabolism, translation, and energy production. E. coli O157:H7-specific acid-inducible genes were identified, suggesting that the enterohemorrhagic E. coli strain possesses additional molecular mechanisms contributing to acid resistance that are absent in K-12. While E. coli K-12 was most resistant to lactic and hydrochloric acid, O157:H7 may have a greater ability to survive in more complex acidic environments, such as those encountered in the host and during food processing