RNA expression analysis using a 30 base pair resolution Escherichia coli genome array

Genomic SELEX Screening of Regulatory Targets of Transcription Factors

The genome of Escherichia coli K-12 is transcribed by a single species of RNA polymerase. The selectivity of transcriptional targets is determined via interaction with one of seven species of the sigma subunit and a total of approximately 300 species of transcription factor (TFs). For comprehensive identification of the regulatory targets of these two groups of regulatory proteins on the genome, we developed an in vitro approach, "Genomic SELEX" (gSELEX) screening. Here we describe a detailed protocol of the gSELEX screening system, which uses purified regulatory proteins and fragments of genomic DNA from E. coli. Moreover, we describe methods and examples of results using cell-free synthetic proteins.

Silencing Transcription from an Influenza Reverse Genetics Plasmid in E. coli Enhances Gene Stability

Reverse genetics (RG) systems have been instrumental for determining the molecular aspects of viral replication, pathogenesis, and for the development of therapeutics. Here, we demonstrate that genes encoding the influenza surface antigens hemagglutinin and neuraminidase have varying stability when cloned into a common RG plasmid and transformed into Escherichia coli. Using GFP as a reporter, we demonstrate that E. coli expresses the target genes in the RG plasmid at low levels. Incorporating lac operators or a transcriptional terminator into the plasmid reduced expression and stabilized the viral genes to varying degrees. Sandwiching the viral gene between two lac operators provided the largest contribution to stability and we confirmed the stabilization is Lac repressor-dependent and crucial for subsequent plasmid propagations in E. coli. Viruses rescued from the lac operator-stabilized plasmid displayed similar kinetics and titers to the original plasmid in two different viral backbones. Together, these results indicate that silencing transcription from the plasmid in E. coli helps to maintain the correct influenza gene sequence and that the lac operator addition does not impair virus production. It is envisaged that sandwiching DNA segments between lac operators can be used for reducing DNA segment instability in any plasmid that is propagated in E. coli which express the Lac repressor.

Integrated Analysis of miRNA-mRNA Expression in Mink Lung Epithelial Cells Infected With Canine Distemper Virus

Canine distemper (CD) caused by canine distemper virus (CDV) is one of the major infectious diseases in minks, bringing serious economic losses to the mink breeding industry. By an integrated analysis of microRNA (miRNA)-messenger RNA (mRNA), the present study analyzed the changes in the mink transcriptome upon CDV infection in mink lung epithelial cells (Mv. l. Lu cells) for the first time. A total of 4,734 differentially expressed mRNAs (2,691 upregulated and 2,043 downregulated) with |log2(FoldChange) |>1 and P-adj<0.05 and 181 differentially expressed miRNAs (152 upregulated and 29 downregulated) with |log2(FoldChange) |>2 and P-adj<0.05 were identified. Gene Ontology (GO) enrichment indicated that differentially expressed genes (DEGs) were associated with various biological processes and molecular function, such as response to stimulus, cell communication, signaling, cytokine activity, transmembrane signaling receptor activity and signaling receptor activity. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the combination of miRNA and mRNA was done for immune and inflammatory responses, such as Janus kinase (JAK)-signal transducer and activator (STAT) signaling pathway and nuclear factor (NF)-kappa B signaling pathway. The enrichment analysis of target mRNA of differentially expressed miRNA revealed that mir-140-5p and mir-378-12 targeted corresponding genes to regulate NF-kappa B signaling pathway. JAK-STAT signaling pathway could be modulated by mir-425-2, mir-139-4, mir-140-6, mir-145-3, mir-140-5p and mir-204-2. This study compared the influence of miRNA-mRNA expression in Mv. l. Lu cells before and after CDV infection by integrated analysis of miRNA-mRNA and analyzed the complex network interaction between virus and host cells. The results can help understand the molecular mechanism of the natural immune response induced by CDV infection in host cells.

Hierarchy of transcription factor network in Escherichia coli K-12: H-NS-mediated silencing and Anti-silencing by global regulators

Transcriptional regulation for genome expression determines growth and adaptation of single-cell bacteria that are directly exposed to environment. The transcriptional apparatus in Escherichia coli K-12 is composed of RNA polymerase core enzyme and two groups of its regulatory proteins, seven species of promoter-recognition subunit sigma and about 300 species of transcription factors. The identification of regulatory targets for all these regulatory proteins is critical toward understanding the genome regulation as a whole. For this purpose, we performed a systematic search in vitro of the whole set of binding sites for each factor by gSELEX system. This review summarizes the accumulated knowledge of regulatory targets for more than 150 TFs from E. coli K-12. Overall TFs could be classified into four families: nucleoid-associated bifunctional TFs; global regulators; local regulators; and single-target regulators, in which the regulatory functions remain uncharacterized for the nucleoid-associated TFs. Here we overview the regulatory targets of two nucleoid-associated TFs, H-NS and its paralog StpA, both together playing the silencing role of a set of non-essential genes. Participation of LeuO and other global regulators have been indicated for the anti-silencing. Finally, we propose the hierarchy of TF network as a key framework of the bacterial genome regulation.

Tombusvirus p19 Captures RNase III-Cleaved Double-Stranded RNAs Formed by Overlapping Sense and Antisense Transcripts in Escherichia coli

Antisense transcription is widespread in bacteria. By base pairing with overlapping sense RNAs, antisense RNAs (asRNA) can form double-stranded RNAs (dsRNA), which are cleaved by RNase III, a dsRNA endoribonuclease. The ectopic expression of plant Tombusvirus p19 in Escherichia coli stabilizes ∼21-nucleotide (nt) dsRNA RNase III decay intermediates, which enabled us to characterize otherwise highly unstable asRNA by deep sequencing of p19-captured dsRNA. RNase III-produced small dsRNA were formed at most bacterial genes in the bacterial genome and in a plasmid.

Antisense transcription is widespread in bacteria. By base pairing with overlapping sense RNAs, antisense RNAs (asRNA) can form double-stranded RNAs (dsRNA), which are cleaved by RNase III, a dsRNA endoribonuclease. The ectopic expression of plant Tombusvirus p19 in Escherichia coli stabilizes ∼21-nucleotide (nt) dsRNA RNase III decay intermediates, which enabled us to characterize otherwise highly unstable asRNA by deep sequencing of p19-captured dsRNA. RNase III-produced small dsRNA were formed at most bacterial genes in the bacterial genome and in a plasmid. We classified the types of asRNA in genomic clusters producing the most abundant p19-captured dsRNA and confirmed RNase III regulation of asRNA and sense RNA decay at three type I toxin-antitoxin loci and at a coding gene, rsd. Furthermore, we provide potential evidence for the RNase III-dependent regulation of CspD protein by asRNA. The analysis of p19-captured dsRNA revealed an RNase III sequence preference for AU-rich sequences 3 nucleotides on either side of the cleavage sites and for GC-rich sequences in the 2-nt overhangs. Unexpectedly, GC-rich sequences were enriched in the middle section of p19-captured dsRNA, suggesting some unexpected sequence bias in p19 protein binding. Nonetheless, the ectopic expression of p19 is a sensitive method for identifying antisense transcripts and RNase III cleavage sites in dsRNA formed by overlapping sense and antisense transcripts in bacteria.

An in situ-Synthesized Gene Chip for the Detection of Food-Borne Pathogens on Fresh-Cut Cantaloupe and Lettuce

Fresh foods are vulnerable to foodborne pathogens which cause foodborne illness and endanger people's life and safety. The rapid detection of foodborne pathogens is crucial for food safety surveillance. An in situ-synthesized gene chip for the detection of foodborne pathogens on fresh-cut fruits and vegetables was developed. The target genes were identified and screened by comparing the specific sequences of Salmonella Typhimurium, Vibrio parahemolyticus, Staphylococcus aureus, Listeria monocytogenes, and Escherichia coli O157:H7 from the National Center for Biotechnology Information database. Tiling array probes were designed to target selected genes in an optimized hybridization system. A total of 141 specific probes were selected from 3,227 hybridization probes, comprising 26 L. monocytogenes, 24 S. aureus, 25 E. coli O157:H7, 20 Salmonella Typhimurium, and 46 V. parahemolyticus probes that are unique to this study. The optimized assay had strong amplification signals and high accuracy. The detection limit for the five target pathogens on fresh-cut cantaloupe and lettuce was approximately 3 log cfu/g without culturing and with a detection time of 24 h. The detection technology established in this study can rapidly detect and monitor the foodborne pathogens on fresh-cut fruits and vegetables throughout the logistical distribution chain, i.e., processing, cleaning, fresh-cutting, packaging, storage, transport, and sale, and represents a valuable technology that support the safety of fresh agricultural products.

Gene Expression of Haloferax volcanii on Intermediate and Abundant Sources of Fixed Nitrogen

Haloferax volcanii, a well-developed model archaeon for genomic, transcriptomic, and proteomic analyses, can grow on a defined medium of abundant and intermediate levels of fixed nitrogen. Here we report a global profiling of gene expression of H. volcanii grown on ammonium as an abundant source of fixed nitrogen compared to l-alanine, the latter of which exemplifies an intermediate source of nitrogen that can be obtained from dead cells in natural habitats. By comparing the two growth conditions, 30 genes were found to be differentially expressed, including 16 genes associated with amino acid metabolism and transport. The gene expression profiles contributed to mapping ammonium and l-alanine usage with respect to transporters and metabolic pathways. In addition, conserved DNA motifs were identified in the putative promoter regions and transcription factors were found to be in synteny with the differentially expressed genes, leading us to propose regulons of transcriptionally co-regulated operons. This study provides insight to how H. volcanii responds to and utilizes intermediate vs. abundant sources of fixed nitrogen for growth, with implications for conserved functions in related halophilic archaea.

Computational Assessment of Bacterial Protein Structures Indicates a Selection Against Aggregation

The aggregation of proteins compromises cell fitness, either because it titrates functional proteins into non-productive inclusions or because it results in the formation of toxic assemblies. Accordingly, computational proteome-wide analyses suggest that prevention of aggregation upon misfolding plays a key role in sequence evolution. Most proteins spend their lifetimes in a folded state; therefore, it is conceivable that, in addition to sequences, protein structures would have also evolved to minimize the risk of aggregation in their natural environments. By exploiting the AGGRESCAN3D structure-based approach to predict the aggregation propensity of >600 Escherichia coli proteins, we show that the structural aggregation propensity of globular proteins is connected with their abundance, length, essentiality, subcellular location and quaternary structure. These data suggest that the avoidance of protein aggregation has contributed to shape the structural properties of proteins in bacterial cells.

The Virulence Effect of CpxRA in Citrobacter rodentium Is Independent of the Auxiliary Proteins NlpE and CpxP

Citrobacter rodentium is a murine pathogen used to model the intestinal infection caused by Enteropathogenic and Enterohemorrhagic Escherichia coli (EPEC and EHEC), two diarrheal pathogens responsible for morbidity and mortality in developing and developed countries, respectively. During infection, these bacteria must sense and adapt to the gut environment of the host. In order to adapt to changing environmental cues and modulate expression of specific genes, bacteria can use two-component signal transduction systems (TCS). We have shown that the deletion of the Cpx TCS in C. rodentium leads to a marked attenuation in virulence in C3H/HeJ mice. In E. coli, the Cpx TCS is reportedly activated in response to signals from the outer-membrane lipoprotein NlpE. We therefore investigated the role of NlpE in C. rodentium virulence. We also assessed the role of the reported negative regulator of CpxRA, CpxP. We found that as opposed to the ΔcpxRA strain, neither the ΔnlpE, ΔcpxP nor the ΔnlpEΔcpxP strains were significantly attenuated, and had similar in vivo localization to wild-type C. rodentium. The in vitro adherence of the Cpx auxiliary protein mutants, ΔnlpE, ΔcpxP, ΔnlpEΔcpxP, was comparable to wild-type C. rodentium, whereas the ΔcpxRA strain showed significantly decreased adherence. To further elucidate the mechanisms behind the contrasting virulence phenotypes, we performed microarrays in order to define the regulon of the Cpx TCS. We detected 393 genes differentially regulated in the ΔcpxRA strain. The gene expression profile of the ΔnlpE strain is strikingly different than the profile of ΔcpxRA with regards to the genes activated by CpxRA. Further, there is no clear inverse correlation in the expression pattern of the ΔcpxP strain in comparison to ΔcpxRA. Taken together, these data suggest that in these conditions, CpxRA activates gene expression in a largely NlpE- and CpxP-independent manner. Compared to wildtype, 161 genes were downregulated in the ΔcpxRA strain, while being upregulated or unchanged in the Cpx auxiliary protein deletion strains. This group of genes, which we hypothesize may contribute to the loss of virulence of ΔcpxRA, includes T6SS components, ompF, the regulator for colanic acid synthesis, and several genes involved in maltose metabolism.

Widespread Antisense Transcription in Prokaryotes

Although bacterial genomes are usually densely protein-coding, genome-wide mapping approaches of transcriptional start sites revealed that a significant fraction of the identified promoters drive the transcription of noncoding RNAs. These can be trans -acting RNAs, mainly originating from intergenic regions and, in many studied examples, possessing regulatory functions. However, a significant fraction of these noncoding RNAs consist of natural antisense transcripts (asRNAs), which overlap other transcriptional units. Naturally occurring asRNAs were first observed to play a role in bacterial plasmid replication and in bacteriophage λ more than 30 years ago. Today’s view is that asRNAs abound in all three domains of life. There are several examples of asRNAs in bacteria with clearly defined functions. Nevertheless, many asRNAs appear to result from pervasive initiation of transcription, and some data point toward global functions of such widespread transcriptional activity, explaining why the search for a specific regulatory role is sometimes futile. In this review, we give an overview about the occurrence of antisense transcription in bacteria, highlight particular examples of functionally characterized asRNAs, and discuss recent evidence pointing at global relevance in RNA processing and transcription-coupled DNA repair.

Bacterial regulatory RNAs: complexity, function, and putative drug targeting

Over the past decade, RNA-deep sequencing has uncovered copious non-protein coding RNAs (npcRNAs) in bacteria. Many of them are key players in the regulation of gene expression, taking part in various regulatory circuits, such as metabolic responses to different environmental stresses, virulence, antibiotic resistance, and host-pathogen interactions. This has contributed to the high adaptability of bacteria to changing or even hostile environments. Their mechanisms include the regulation of transcriptional termination, modulation of translation, and alteration of messenger RNA (mRNA) stability, as well as protein sequestration. Here, the mechanisms of gene expression by regulatory bacterial npcRNAs are comprehensively reviewed and supplemented with well-characterized examples. This class of molecules and their mechanisms of action might be useful targets for the development of novel antibiotics.

Antisense transcription in Pseudomonas aeruginosa

A large number of antisense transcripts have been detected in diverse microbial genomes and considerable effort has been devoted to elucidating the functional role of antisense transcription. In this study, we reanalysed extensive RNA sequencing data from the opportunistic pathogen Pseudomonas aeruginosa and found that the majority of genes have a propensity for antisense transcription. Although antisense transcripts were found in more than 80 % of the genes of the P. aeruginosa genome, the majority of sequencing reads were mapping sense and only a minority (<2 %) were mapping antisense to genes. Similarly to the sense expression levels, the antisense expression levels varied under different environmental conditions, with the sense and antisense expression levels often being inversely regulated and modulated by the activity of alternative sigma factors. Environment-modulated antisense transcription showed a bias towards being antisense to genes within regions of genomic plasticity and to those encoding small regulatory RNAs. In the future, the validation and functional characterization of antisense transcripts, and novel transcripts that are antisense to small regulatory RNAs in particular, have the potential to contribute to our understanding of the various levels of transcriptional regulation and its dynamics in the bacterial pathogen P. aeruginosa.

Bacterial RNA Biology on a Genome Scale

Bacteria are an exceedingly diverse group of organisms whose molecular exploration is experiencing a renaissance. While the classical view of bacterial gene expression was relatively simple, the emerging view is more complex, encompassing extensive post-transcriptional control involving riboswitches, RNA thermometers, and regulatory small RNAs (sRNAs) associated with the RNA-binding proteins CsrA, Hfq, and ProQ, as well as CRISPR/Cas systems that are programmed by RNAs. Moreover, increasing interest in members of the human microbiota and environmental microbial communities has highlighted the importance of understudied bacterial species with largely unknown transcriptome structures and RNA-based control mechanisms. Collectively, this creates a need for global RNA biology approaches that can rapidly and comprehensively analyze the RNA composition of a bacterium of interest. We review such approaches with a focus on RNA-seq as a versatile tool to investigate the different layers of gene expression in which RNA is made, processed, regulated, modified, translated, and turned over.

Genomic SELEX Screening of Regulatory Targets of Escherichia coli Transcription Factors

The genome of Escherichia coli K-12 is transcribed by a single species of RNA polymerase. The selectivity of its transcriptional targets is modulated via two-steps of protein-protein interaction: at the first step, seven species of the sigma subunit are involved, at the second step, a total of approximately 300 species of transcription factor (TFs). For the identification of the regulatory targets of these two groups of regulatory proteins, we developed two in vitro approaches, "Genomic SELEX" (currently designated as gSELEX) and "PS (promoter-specific)-TF" screenings. Here, we describe a detailed protocol of the genomic SELEX screening system which uses purified regulatory proteins and fragments of genomic DNA from E. coli.

Deep sequencing approaches for the analysis of prokaryotic transcriptional boundaries and dynamics

The identification of the protein-coding regions of a genome is straightforward due to the universality of start and stop codons. However, the boundaries of the transcribed regions, conditional operon structures, non-coding RNAs and the dynamics of transcription, such as pausing of elongation, are non-trivial to identify, even in the comparatively simple genomes of prokaryotes. Traditional methods for the study of these areas, such as tiling arrays, are noisy, labour-intensive and lack the resolution required for densely-packed bacterial genomes. Recently, deep sequencing has become increasingly popular for the study of the transcriptome due to its lower costs, higher accuracy and single nucleotide resolution. These methods have revolutionised our understanding of prokaryotic transcriptional dynamics. Here, we review the deep sequencing and data analysis techniques that are available for the study of transcription in prokaryotes, and discuss the bioinformatic considerations of these analyses.

Changes in Gene Transcription Induced by Hydrogen Peroxide Treatment of Verotoxin-Producing Escherichia coli O157:H7 and Non-O157 Serotypes on Romaine Lettuce

Disease outbreaks of verotoxin-producing Escherichia coli (VTEC) O157:H7 and non-O157 serotypes associated with leafy green vegetables are becoming a growing concern. A better understanding of the behavior of VTEC, particularly non-O157 serotypes, on lettuce under stress conditions is necessary for designing more effective control strategies. Hydrogen peroxide (H₂O₂) can be used as a sanitizer to reduce the microbial load in leafy green vegetables, particularly in fresh produce destined for the organic market. In this study, we tested the hypothesis that H₂O₂ treatment of contaminated lettuce affects in the same manner transcription of stress-associated and virulence genes in VTEC strains representing O157 and non-O157 serotypes. Six VTEC isolates representing serotypes O26:H11, O103:H2, O104:H4, O111:NM, O145:NM, and O157:H7 were included in this study. The results indicate that 50 mM H₂O₂ caused a population reduction of 2.4-2.8 log₁₀ (compared to non-treated control samples) in all six VTEC strains present on romaine lettuce. Following the treatment, the transcription of genes related to oxidative stress (oxyR and sodA), general stress (uspA and rpoS), starvation (phoA), acid stress (gadA, gadB, and gadW), and virulence (stx1A, stx2A, and fliC) were dramatically downregulated in all six VTEC serotypes (P ≤ 0.05) compared to not treated control samples. Therefore, VTEC O157:H7 and non-O157 serotypes on lettuce showed similar survival rates and gene transcription profiles in response to 50 mM H₂O₂ treatment. Thus, the results derived from this study provide a basic understanding of the influence of H₂O₂ treatment on the survival and virulence of VTEC O157:H7 and non-O157 serotypes on lettuce.

PIPE-chipSAD: A Pipeline for the Analysis of High Density Arrays of Bacterial Transcriptomes

PIPE-chipSAD is a pipeline for bacterial transcriptome studies based on high-density microarray experiments. The main algorithm chipSAD, integrates the analysis of the hybridization signal with the genomic position of probes and identifies portions of the genome transcribing for mRNAs. The pipeline includes a procedure, align-chipSAD, to build a multiple alignment of transcripts originating in the same locus in multiple experiments and provides a method to compare mRNA expression across different conditions. Finally, the pipeline includes anno-chipSAD a method to annotate the detected transcripts in comparison to the genome annotation. Overall, our pipeline allows transcriptional profile analysis of both coding and non-coding portions of the chromosome in a single framework. Importantly, due to its versatile characteristics, it will be of wide applicability to analyse, not only microarray signals, but also data from other high throughput technologies such as RNA-sequencing. The current PIPE-chipSAD implementation is written in Python programming language and is freely available at https://github.com/silviamicroarray/chipSAD.

The unexpected complexity of bacterial genomes

Gene organization and control are described by models conceived in the 1960s. These models explain basic gene regulatory mechanisms and underpin current genome annotation. However, such models struggle to explain recent genome-scale observations. For example, accounts of RNA synthesis initiating within genes, widespread antisense transcription and non-canonical DNA binding by gene regulatory proteins are difficult to reconcile with traditional thinking. As a result, unexpected observations have often been dismissed and downstream consequences ignored. In this paper I will argue that, to fully understand the biology of bacterial chromosomes, we must embrace their hidden layers of complexity.

Replication fork progression is paused in two large chromosomal zones flanking the DNA replication origin in Escherichia coli

Although the speed of nascent DNA synthesis at individual replication forks is relatively uniform in bacterial cells, the dynamics of replication fork progression on the chromosome are hampered by a variety of natural impediments. Genome replication dynamics can be directly measured from an exponentially growing cell population by sequencing newly synthesized DNA strands that were specifically pulse-labeled with the thymidine analogue 5-bromo-2'-deoxyuridine (BrdU). However, a short pulse labeling with BrdU is impracticable for bacteria because of poor incorporation of BrdU into the cells, and thus, the genomewide dynamics of bacterial DNA replication remain undetermined. Using a new thymidine-requiring Escherichia coli strain, eCOMB, and high-throughput sequencing, we succeeded in determining the genomewide replication profile in bacterial cells. We also found that fork progression is paused in two ~200-kb chromosomal zones that flank the replication origin in the growing cells. This origin-proximal obstruction to fork progression was overcome by an increased thymidine concentration in the culture medium and enhanced by inhibition of transcription. These indicate that DNA replication near the origin is sensitive to the impediments to fork progression, namely a scarcity of the DNA precursor deoxythymidine triphosphate and probable conflicts between replication and transcription machineries.

Precise Identification of Genome-Wide Transcription Start Sites in Bacteria by 5'-Rapid Amplification of cDNA Ends (5'-RACE)

Transcription start sites are commonly used to locate promoter elements in bacterial genomes. TSS were previously studied one gene at a time, often through 5'-rapid amplification of cDNA ends (5'-RACE). This technique has now been adapted for high-throughput sequencing and can be used to precisely identify TSS in a genome-wide fashion for practically any bacterium, which greatly contributes to our understanding of gene regulatory networks in microorganisms.

An automated approach for global identification of sRNA-encoding regions in RNA-Seq data from Mycobacterium tuberculosis

Deep-sequencing of bacterial transcriptomes using RNA-Seq technology has made it possible to identify small non-coding RNAs, RNA molecules which regulate gene expression in response to changing environments, on a genome-wide scale in an ever-increasing range of prokaryotes. However, a simple and reliable automated method for identifying sRNA candidates in these large datasets is lacking. Here, after generating a transcriptome from an exponential phase culture of Mycobacterium tuberculosis H37Rv, we developed and validated an automated method for the genome-wide identification of sRNA candidate-containing regions within RNA-Seq datasets based on the analysis of the characteristics of reads coverage maps. We identified 192 novel candidate sRNA-encoding regions in intergenic regions and 664 RNA transcripts transcribed from regions antisense (as) to open reading frames (ORF), which bear the characteristics of asRNAs, and validated 28 of these novel sRNA-encoding regions by northern blotting. Our work has not only provided a simple automated method for genome-wide identification of candidate sRNA-encoding regions in RNA-Seq data, but has also uncovered many novel candidate sRNA-encoding regions in M. tuberculosis, reinforcing the view that the control of gene expression in bacteria is more complex than previously anticipated.

Antisense transcription as a tool to tune gene expression

A surprise that has emerged from transcriptomics is the prevalence of genomic antisense transcription, which occurs counter to gene orientation. While frequent, the roles of antisense transcription in regulation are poorly understood. We built a synthetic system in Escherichia coli to study how antisense transcription can change the expression of a gene and tune the response characteristics of a regulatory circuit. We developed a new genetic part that consists of a unidirectional terminator followed by a constitutive antisense promoter and demonstrate that this part represses gene expression proportionally to the antisense promoter strength. Chip‐based oligo synthesis was applied to build a large library of 5,668 terminator–promoter combinations that was used to control the expression of three repressors (PhlF, SrpR, and TarA) in a simple genetic circuit (NOT gate). Using the library, we demonstrate that antisense promoters can be used to tune the threshold of a regulatory circuit without impacting other properties of its response function. Finally, we determined the relative contributions of antisense RNA and transcriptional interference to repressing gene expression and introduce a biophysical model to capture the impact of RNA polymerase collisions on gene repression. This work quantifies the role of antisense transcription in regulatory networks and introduces a new mode to control gene expression that has been previously overlooked in genetic engineering.

High-resolution analysis of the m-xylene/toluene biodegradation subtranscriptome of Pseudomonas putida mt-2

Pseudomonas putida mt-2 metabolizes m-xylene and other aromatic compounds through the enzymes encoded by the xyl operons of the TOL plasmid pWW0 along with other chromosomally encoded activities. Tiling arrays of densely overlapping oligonucleotides were designed to cover every gene involved in this process, allowing dissection of operon structures and exposing the interplay of plasmid and chromosomal functions. All xyl sequences were transcribed in response to aromatic substrates and the 3'-termini of both upper and lower mRNA operons extended beyond their coding regions, i.e. the 3'-end of the lower operon mRNA penetrated into the convergent xylS regulatory gene. Furthermore, xylR mRNA for the master m-xylene responsive regulator of the system was decreased by aromatic substrates, while the cognate upper operon mRNA was evenly stable throughout its full length. RNA sequencing confirmed these data at a single nucleotide level and refined the formerly misannotated xylL sequence. The chromosomal ortho route for degradation of benzoate (the ben, cat clusters and some pca genes) was activated by this aromatic, but not by the TOL substrates, toluene or m-xylene. We advocate this scenario as a testbed of natural retroactivity between a pre-existing metabolic network and a new biochemical pathway implanted through gene transfer.

quantro: a data-driven approach to guide the choice of an appropriate normalization method

Normalization is an essential step in the analysis of high-throughput data. Multi-sample global normalization methods, such as quantile normalization, have been successfully used to remove technical variation. However, these methods rely on the assumption that observed global changes across samples are due to unwanted technical variability. Applying global normalization methods has the potential to remove biologically driven variation. Currently, it is up to the subject matter experts to determine if the stated assumptions are appropriate. Here, we propose a data-driven alternative. We demonstrate the utility of our method (quantro) through examples and simulations. A software implementation is available from http://www.bioconductor.org/packages/release/bioc/html/quantro.html.

A dual reporter system for detecting RNA interactions in bacterial cells

Detecting RNA-partner interactions in cells is often difficult due to a lack of suitable tools. Here we describe a dual reporter system capable of detecting intracellular interactions in which one of the partners is an RNA. The system utilizes two fluorescent proteins with similar maturation rates but distinct spectral properties, specifically cyan fluorescent protein (CFP) and yellow fluorescent protein (YFP). By placing the CFP gene upstream and the YFP gene downstream of an RNA gene of interest, the production of YFP becomes sensitive to RNA-partner interaction, whereas the synthesis of CFP is not disturbed. Therefore, the RNA-partner interaction can be simply measured by the change in the ratio of fluorescence of YFP over CFP. The utility of our approach is demonstrated through verification of three known RNA-partner interactions in the model bacterium Escherichia coli. Our two-reporter strategy should be broadly useful to the study of RNA-targeted interactions in bacteria.

Where to begin? Mapping transcription start sites genome-wide in Escherichia coli

Recent genome-wide studies of bacterial transcription have revealed large numbers of promoters located inside genes. In this issue of the Journal of Bacteriology, Thomason and colleagues (J. Bacteriol. 197:18-28, 2015, doi:10.1128/JB.02096-14) map transcription start sites in Escherichia coli on an unprecedented scale. This work provides important insights into the regulation of transcripts that initiate inside genes and sources of variability between studies aimed at identifying these RNAs.

Gene finding in metatranscriptomic sequences

BACKGROUND

Metatranscriptomic sequencing is a highly sensitive bioassay of functional activity in a microbial community, providing complementary information to the metagenomic sequencing of the community. The acquisition of the metatranscriptomic sequences will enable us to refine the annotations of the metagenomes, and to study the gene activities and their regulation in complex microbial communities and their dynamics.

RESULTS

In this paper, we present TransGeneScan, a software tool for finding genes in assembled transcripts from metatranscriptomic sequences. By incorporating several features of metatranscriptomic sequencing, including strand-specificity, short intergenic regions, and putative antisense transcripts into a Hidden Markov Model, TranGeneScan can predict a sense transcript containing one or multiple genes (in an operon) or an antisense transcript.

CONCLUSION

We tested TransGeneScan on a mock metatranscriptomic data set containing three known bacterial genomes. The results showed that TranGeneScan performs better than metagenomic gene finders (MetaGeneMark and FragGeneScan) on predicting protein coding genes in assembled transcripts, and achieves comparable or even higher accuracy than gene finders for microbial genomes (Glimmer and GeneMark). These results imply, with the assistance of metatranscriptomic sequencing, we can obtain a broad and precise picture about the genes (and their functions) in a microbial community.

AVAILABILITY

TransGeneScan is available as open-source software on SourceForge at https://sourceforge.net/projects/transgenescan/.

Unprecedented high-resolution view of bacterial operon architecture revealed by RNA sequencing

We analyzed the transcriptome of Escherichia coli K-12 by strand-specific RNA sequencing at single-nucleotide resolution during steady-state (logarithmic-phase) growth and upon entry into stationary phase in glucose minimal medium. To generate high-resolution transcriptome maps, we developed an organizational schema which showed that in practice only three features are required to define operon architecture: the promoter, terminator, and deep RNA sequence read coverage. We precisely annotated 2,122 promoters and 1,774 terminators, defining 1,510 operons with an average of 1.98 genes per operon. Our analyses revealed an unprecedented view of E. coli operon architecture. A large proportion (36%) of operons are complex with internal promoters or terminators that generate multiple transcription units. For 43% of operons, we observed differential expression of polycistronic genes, despite being in the same operons, indicating that E. coli operon architecture allows fine-tuning of gene expression. We found that 276 of 370 convergent operons terminate inefficiently, generating complementary 3′ transcript ends which overlap on average by 286 nucleotides, and 136 of 388 divergent operons have promoters arranged such that their 5′ ends overlap on average by 168 nucleotides. We found 89 antisense transcripts of 397-nucleotide average length, 7 unannotated transcripts within intergenic regions, and 18 sense transcripts that completely overlap operons on the opposite strand. Of 519 overlapping transcripts, 75% correspond to sequences that are highly conserved in E. coli (>50 genomes). Our data extend recent studies showing unexpected transcriptome complexity in several bacteria and suggest that antisense RNA regulation is widespread.

We precisely mapped the 5′ and 3′ ends of RNA transcripts across the E. coli K-12 genome by using a single-nucleotide analytical approach. Our resulting high-resolution transcriptome maps show that ca. one-third of E. coli operons are complex, with internal promoters and terminators generating multiple transcription units and allowing differential gene expression within these operons. We discovered extensive antisense transcription that results from more than 500 operons, which fully overlap or extensively overlap adjacent divergent or convergent operons. The genomic regions corresponding to these antisense transcripts are highly conserved in E. coli (including Shigella species), although it remains to be proven whether or not they are functional. Our observations of features unearthed by single-nucleotide transcriptome mapping suggest that deeper layers of transcriptional regulation in bacteria are likely to be revealed in the future.

Colony-live--a high-throughput method for measuring microbial colony growth kinetics--reveals diverse growth effects of gene knockouts in Escherichia coli

Background

Precise quantitative growth measurements and detection of small growth changes in high-throughput manner is essential for fundamental studies of bacterial cell. However, an inherent tradeoff for measurement quality in high-throughput methods sacrifices some measurement quality. A key challenge has been how to enhance measurement quality without sacrificing throughput.

Results

We developed a new high-throughput measurement system, termed Colony-live. Here we show that Colony-live provides accurate measurement of three growth values (lag time of growth (LTG), maximum growth rate (MGR), and saturation point growth (SPG)) by visualizing colony growth over time. By using a new normalization method for colony growth, Colony-live gives more precise and accurate growth values than the conventional method. We demonstrated the utility of Colony-live by measuring growth values for the entire Keio collection of Escherichia coli single-gene knockout mutants. By using Colony-live, we were able to identify subtle growth defects of single-gene knockout mutants that were undetectable by the conventional method quantified by fixed time-point camera imaging. Further, Colony-live can reveal genes that influence the length of the lag-phase and the saturation point of growth.

Conclusions

Measurement quality is critical to achieving the resolution required to identify unique phenotypes among a diverse range of phenotypes. Sharing high-quality genome-wide datasets should benefit many researchers who are interested in specific gene functions or the architecture of cellular systems. Our Colony-live system provides a new powerful tool to accelerate accumulation of knowledge of microbial growth phenotypes.

Complex intra-operonic dynamics mediated by a small RNA in Streptomyces coelicolor

Streptomyces are predominantly soil-dwelling bacteria that are best known for their multicellular life cycle and their prodigious metabolic capabilities. They are also renowned for their regulatory capacity and flexibility, with each species encoding >60 sigma factors, a multitude of transcription factors, and an increasing number of small regulatory RNAs. Here, we describe our characterization of a conserved small RNA (sRNA), scr4677. In the model species Streptomyces coelicolor, this sRNA is located in the intergenic region separating SCO4677 (an anti-sigma factor-encoding gene) and SCO4676 (a putative regulatory protein-encoding gene), close to the SCO4676 translation start site in an antisense orientation. There appears to be considerable genetic interplay between these different gene products, with wild type expression of scr4677 requiring function of the anti-sigma factor SCO4677, and scr4677 in turn influencing the abundance of SCO4676-associated transcripts. The scr4677-mediated effects were independent of RNase III (a double stranded RNA-specific nuclease), with RNase III having an unexpectedly positive influence on the level of SCO4676-associated transcripts. We have shown that both SCO4676 and SCO4677 affect the production of the blue-pigmented antibiotic actinorhodin under specific growth conditions, and that this activity appears to be independent of scr4677.

Improved understanding of gene expression regulation using systems biology

This article reviews the current state of systems biology approaches, including the experimental tools used to generate 'omic' data and computational frameworks to interpret this data. Through illustrative examples, systems biology approaches to understand gene expression and gene expression regulation are discussed. Some of the challenges facing this field and the future opportunities in the systems biology era are highlighted.

High-density tiling microarray analysis of the full transcriptional activity of yeast

Understanding the relationship between DNA sequence variation and phenotypic variation in complex or quantitative traits is one of the major challenges in modern biology. We are witnessing a deluge of DNA sequence information and association studies of genetic polymorphisms with phenotypes of interest in families and populations. In addition, it has become clear that large portions of eukaryotic genomes beyond protein-coding genes are transcribed, generating numerous noncoding RNA (ncRNA) molecules whose functions remain mostly unknown.DNA oligonucleotide microarrays constitute a powerful technology for studying the expression of genes in different organisms. The Saccharomyces cerevisiae tiling array presents a significant advance over previous array-based platforms. It has a high density of overlapping probes that start on average every 8 bp along each strand of the genome, enabling precise definition of transcript structure. Furthermore, the array includes probes specific for the polymorphic positions of another, distantly related yeast strain, allowing accurate measurement of allele-specific expression in a hybrid of the two strains. This technology thus allows high-resolution, quantitative, strand- and allele-specific measurements of transcription from a full eukaryotic genome. In this chapter, we describe the methods for extracting RNA, synthesizing first-strand cDNA, fragmenting, and labeling of samples for hybridization to the tiling array. Combining genome-wide information on variation in DNA sequence with variation in transcript structure and levels promises to increase our understanding of the genotype-to-phenotype relationship.

Tiling array study of MNNG treated Escherichia coli reveals a widespread transcriptional response

The alkylating agent N-methyl-N'-nitro-N-nitrosoguanidine (MNNG) is known to trigger the adaptive response by inducing the ada-regulon – consisting of three DNA repair enzymes Ada, AlkB, AlkA and the enigmatic AidB. We have applied custom designed tiling arrays to study transcriptional changes in Escherichia coli following a MNNG challenge. Along with the expected upregulation of the adaptive response genes (ada, alkA and alkB), we identified a number of differentially expressed transcripts, both novel and annotated. This indicates a wider regulatory response than previously documented. There were 250 differentially-expressed and 2275 similarly-expressed unannotated transcripts. We found novel upregulation of several stress-induced transcripts, including the SOS inducible genes recN and tisAB, indicating a novel role for these genes in alkylation repair. Furthermore, the ada-regulon A and B boxes were found to be insufficient to explain the regulation of the adaptive response genes after MNNG exposure, suggesting that additional regulatory elements must be involved.

Synthetic biology of cyanobacteria: unique challenges and opportunities

Photosynthetic organisms, and especially cyanobacteria, hold great promise as sources of renewably-produced fuels, bulk and specialty chemicals, and nutritional products. Synthetic biology tools can help unlock cyanobacteria's potential for these functions, but unfortunately tool development for these organisms has lagged behind that for S. cerevisiae and E. coli. While these organisms may in many cases be more difficult to work with as “chassis” strains for synthetic biology than certain heterotrophs, the unique advantages of autotrophs in biotechnology applications as well as the scientific importance of improved understanding of photosynthesis warrant the development of these systems into something akin to a “green E. coli.” In this review, we highlight unique challenges and opportunities for development of synthetic biology approaches in cyanobacteria. We review classical and recently developed methods for constructing targeted mutants in various cyanobacterial strains, and offer perspective on what genetic tools might most greatly expand the ability to engineer new functions in such strains. Similarly, we review what genetic parts are most needed for the development of cyanobacterial synthetic biology. Finally, we highlight recent methods to construct genome-scale models of cyanobacterial metabolism and to use those models to measure properties of autotrophic metabolism. Throughout this paper, we discuss some of the unique challenges of a diurnal, autotrophic lifestyle along with how the development of synthetic biology and biotechnology in cyanobacteria must fit within those constraints.

GlgS, described previously as a glycogen synthesis control protein, negatively regulates motility and biofilm formation in Escherichia coli

Escherichia coli glycogen metabolism involves the regulation of glgBXCAP operon expression and allosteric control of the GlgC [ADPG (ADP-glucose) pyrophosphorylase]-mediated catalysis of ATP and G1P (glucose-1-phosphate) to ADPG linked to glycogen biosynthesis. E. coli glycogen metabolism is also affected by glgS. Though the precise function of the protein it encodes is unknown, its deficiency causes both reduced glycogen content and enhanced levels of the GlgC-negative allosteric regulator AMP. The transcriptomic analyses carried out in the present study revealed that, compared with their isogenic BW25113 wild-type strain, glgS-null (ΔglgS) mutants have increased expression of the operons involved in the synthesis of type 1 fimbriae adhesins, flagella and nucleotides. In agreement, ΔglgS cells were hyperflagellated and hyperfimbriated, and displayed elevated swarming motility; these phenotypes all reverted to the wild-type by ectopic glgS expression. Also, ΔglgS cells accumulated high colanic acid content and displayed increased ability to form biofilms on polystyrene surfaces. F-driven conjugation based on large-scale interaction studies of glgS with all the non-essential genes of E. coli showed that deletion of purine biosynthesis genes complement the glycogen-deficient, high motility and high biofilm content phenotypes of ΔglgS cells. Overall the results of the present study indicate that glycogen deficiency in ΔglgS cells can be ascribed to high flagellar propulsion and high exopolysaccharide and purine nucleotides biosynthetic activities competing with GlgC for the same ATP and G1P pools. Supporting this proposal, glycogen-less ΔglgC cells displayed an elevated swarming motility, and accumulated high levels of colanic acid and biofilm. Furthermore, glgC overexpression reverted the glycogen-deficient, high swarming motility, high colanic acid and high biofilm content phenotypes of ΔglgS cells to the wild-type. As on the basis of the present study GlgS has emerged as a major determinant of E. coli surface composition and because its effect on glycogen metabolism appears to be only indirect, we propose to rename it as ScoR (surface composition regulator).

Full design automation of multi-state RNA devices to program gene expression using energy-based optimization

Small RNAs (sRNAs) can operate as regulatory agents to control protein expression by interaction with the 5′ untranslated region of the mRNA. We have developed a physicochemical framework, relying on base pair interaction energies, to design multi-state sRNA devices by solving an optimization problem with an objective function accounting for the stability of the transition and final intermolecular states. Contrary to the analysis of the reaction kinetics of an ensemble of sRNAs, we solve the inverse problem of finding sequences satisfying targeted reactions. We show here that our objective function correlates well with measured riboregulatory activity of a set of mutants. This has enabled the application of the methodology for an extended design of RNA devices with specified behavior, assuming different molecular interaction models based on Watson-Crick interaction. We designed several YES, NOT, AND, and OR logic gates, including the design of combinatorial riboregulators. In sum, our de novo approach provides a new paradigm in synthetic biology to design molecular interaction mechanisms facilitating future high-throughput functional sRNA design.

Is our current knowledge of in vivo RNA-RNA interactions and thermodynamics enough to perform the unsupervised computational design of fully synthetic sequences encoding functional RNAs in living cells? Recent work gave a positive answer for the challenging problem of designing activating riboregulators. This was done by integrating theory and computation to develop a physicochemical framework for the design of regulatory RNA systems, using Watson-Crick interactions and optimization algorithms. Still, the objective function was not directly validated, preventing using with confidence the methodology for other systems. We here validate experimentally an objective function relying on free energies of RNA complex activation and formation, which allows extending the framework to produce logic devices that can be implemented to program gene expression. We demonstrate that it is possible to design increasingly sophisticated and modular functions, pointing our results out that energy-based optimization methods can perform the large combinatorial search required for RNA design.

Directional RNA-seq reveals highly complex condition-dependent transcriptomes in E. coli K12 through accurate full-length transcripts assembling

BACKGROUND

Although prokaryotic gene transcription has been studied over decades, many aspects of the process remain poorly understood. Particularly, recent studies have revealed that transcriptomes in many prokaryotes are far more complex than previously thought. Genes in an operon are often alternatively and dynamically transcribed under different conditions, and a large portion of genes and intergenic regions have antisense RNA (asRNA) and non-coding RNA (ncRNA) transcripts, respectively. Ironically, similar studies have not been conducted in the model bacterium E coli K12, thus it is unknown whether or not the bacterium possesses similar complex transcriptomes. Furthermore, although RNA-seq becomes the major method for analyzing the complexity of prokaryotic transcriptome, it is still a challenging task to accurately assemble full length transcripts using short RNA-seq reads.

RESULTS

To fill these gaps, we have profiled the transcriptomes of E. coli K12 under different culture conditions and growth phases using a highly specific directional RNA-seq technique that can capture various types of transcripts in the bacterial cells, combined with a highly accurate and robust algorithm and tool TruHMM (http://bioinfolab.uncc.edu/TruHmm_package/) for assembling full length transcripts. We found that 46.9 ~ 63.4% of expressed operons were utilized in their putative alternative forms, 72.23 ~ 89.54% genes had putative asRNA transcripts and 51.37 ~ 72.74% intergenic regions had putative ncRNA transcripts under different culture conditions and growth phases.

CONCLUSIONS

As has been demonstrated in many other prokaryotes, E. coli K12 also has a highly complex and dynamic transcriptomes under different culture conditions and growth phases. Such complex and dynamic transcriptomes might play important roles in the physiology of the bacterium. TruHMM is a highly accurate and robust algorithm for assembling full-length transcripts in prokaryotes using directional RNA-seq short reads.

Differential expression of secretion machinery during bacterial growth: SecY and SecF decrease while SecA increases during transition from exponential phase to stationary phase

Transcription of many house-keeping genes, including secY and some other sec genes, decreases in the transition from the exponential phase to the stationary phase (feast to famine) in Bacillus subtilis. Unexpectedly and in contradiction to earlier reports, enhanced transcription was observed for another group of sec genes, including secA which codes for an essential ATPase for protein secretion. Consistent with the transcription data, the SecA protein of B. subtilis increases significantly in the stationary phase. Immunoblot analyses of Sec proteins during the transition in Escherichia coli also revealed the pronounced decreases of SecY and SecF and the increase of SecA, resulting in drastic increases of SecA/SecY and SecA/SecF ratios from exponential to stationary phases. The differential expression of Sec proteins in the stationary phase suggests the possibility of specific physiological functions.

Three-state mechanism couples ligand and temperature sensing in riboswitches

Riboswitches are cis-acting gene-regulatory RNA elements that can function at the level of transcription, translation and RNA cleavage. The commonly accepted molecular mechanism for riboswitch function proposes a ligand-dependent conformational switch between two mutually exclusive states. According to this mechanism, ligand binding to an aptamer domain induces an allosteric conformational switch of an expression platform, leading to activation or repression of ligand-related gene expression. However, many riboswitch properties cannot be explained by a pure two-state mechanism. Here we show that the regulation mechanism of the adenine-sensing riboswitch, encoded by the add gene on chromosome II of the human Gram-negative pathogenic bacterium Vibrio vulnificus, is notably different from a two-state switch mechanism in that it involves three distinct stable conformations. We characterized the temperature and Mg(2+) dependence of the population ratios of the three conformations and the kinetics of their interconversion at nucleotide resolution. The observed temperature dependence of a pre-equilibrium involving two structurally distinct ligand-free conformations of the add riboswitch conferred efficient regulation over a physiologically relevant temperature range. Such robust switching is a key requirement for gene regulation in bacteria that have to adapt to environments with varying temperatures. The translational adenine-sensing riboswitch represents the first example, to our knowledge, of a temperature-compensated regulatory RNA element.

Current challenges in bacterial transcriptomics

Over the past decade or so, dramatic developments in our ability to experimentally determine the content and function of genomes have taken place. In particular, next-generation sequencing technologies are now inspiring a new understanding of bacterial transcriptomes on a global scale. In bacterial cells, whole-transcriptome studies have not received attention, owing to the general view that bacterial genomes are simple. However, several recent RNA sequencing results are revealing unexpected levels of complexity in bacterial transcriptomes, indicating that the transcribed regions of genomes are much larger and complex than previously anticipated. In particular, these data show a wide array of small RNAs, antisense RNAs, and alternative transcripts. Here, we review how current transcriptomics are now revolutionizing our understanding of the complexity and regulation of bacterial transcriptomes.

Emerging tools for synthetic genome design

Synthetic biology is an emerging discipline for designing and synthesizing predictable, measurable, controllable, and transformable biological systems. These newly designed biological systems have great potential for the development of cheaper drugs, green fuels, biodegradable plastics, and targeted cancer therapies over the coming years. Fortunately, our ability to quickly and accurately engineer biological systems that behave predictably has been dramatically expanded by significant advances in DNA-sequencing, DNA-synthesis, and DNA-editing technologies. Here, we review emerging technologies and methodologies in the field of building designed biological systems, and we discuss their future perspectives.

Identification and characterization of a cis-encoded antisense RNA associated with the replication process of Salmonella enterica serovar Typhi

Antisense RNAs that originate from the complementary strand of protein coding genes are involved in the regulation of gene expression in all domains of life. In bacteria, some of these antisense RNAs are transcriptional noise whiles others play a vital role to adapt the cell to changing environmental conditions. By deep sequencing analysis of transcriptome of Salmonella enterica serovar Typhi, a partial RNA sequence encoded in-cis to the dnaA gene was revealed. Northern blot and RACE analysis confirmed the transcription of this antisense RNA which was expressed mostly in the stationary phase of the bacterial growth and also under iron limitation and osmotic stress. Pulse expression analysis showed that overexpression of the antisense RNA resulted in a significant increase in the mRNA levels of dnaA, which will ultimately enhance their translation. Our findings have revealed that antisense RNA of dnaA is indeed transcribed not merely as a by-product of the cell's transcription machinery but plays a vital role as far as stability of dnaA mRNA is concerned.

Next-generation annotation of prokaryotic genomes with EuGene-P: application to Sinorhizobium meliloti 2011

The availability of next-generation sequences of transcripts from prokaryotic organisms offers the opportunity to design a new generation of automated genome annotation tools not yet available for prokaryotes. In this work, we designed EuGene-P, the first integrative prokaryotic gene finder tool which combines a variety of high-throughput data, including oriented RNA-Seq data, directly into the prediction process. This enables the automated prediction of coding sequences (CDSs), untranslated regions, transcription start sites (TSSs) and non-coding RNA (ncRNA, sense and antisense) genes. EuGene-P was used to comprehensively and accurately annotate the genome of the nitrogen-fixing bacterium Sinorhizobium meliloti strain 2011, leading to the prediction of 6308 CDSs as well as 1876 ncRNAs. Among them, 1280 appeared as antisense to a CDS, which supports recent findings that antisense transcription activity is widespread in bacteria. Moreover, 4077 TSSs upstream of protein-coding or non-coding genes were precisely mapped providing valuable data for the study of promoter regions. By looking for RpoE2-binding sites upstream of annotated TSSs, we were able to extend the S. meliloti RpoE2 regulon by ∼3-fold. Altogether, these observations demonstrate the power of EuGene-P to produce a reliable and high-resolution automatic annotation of prokaryotic genomes.

Correction of spatial bias in oligonucleotide array data

Background. Oligonucleotide microarrays allow for high-throughput gene expression profiling assays. The technology relies on the fundamental assumption that observed hybridization signal intensities (HSIs) for each intended target, on average, correlate with their target's true concentration in the sample. However, systematic, nonbiological variation from several sources undermines this hypothesis. Background hybridization signal has been previously identified as one such important source, one manifestation of which appears in the form of spatial autocorrelation. Results. We propose an algorithm, pyn, for the elimination of spatial autocorrelation in HSIs, exploiting the duality of desirable mutual information shared by probes in a common probe set and undesirable mutual information shared by spatially proximate probes. We show that this correction procedure reduces spatial autocorrelation in HSIs; increases HSI reproducibility across replicate arrays; increases differentially expressed gene detection power; and performs better than previously published methods. Conclusions. The proposed algorithm increases both precision and accuracy, while requiring virtually no changes to users' current analysis pipelines: the correction consists merely of a transformation of raw HSIs (e.g., CEL files for Affymetrix arrays). A free, open-source implementation is provided as an R package, compatible with standard Bioconductor tools. The approach may also be tailored to other platform types and other sources of bias.