Tigecycline challenge triggers sRNA production in Salmonella enterica serovar Typhimurium

Background: Bacteria employ complex transcriptional networks involving multiple genes in response to stress, which is not limited to gene and protein networks but now includes small RNAs (sRNAs). These regulatory RNA molecules are increasingly shown to be able to initiate regulatory cascades and modulate the expression of multiple genes that are involved in or required for survival under environmental challenge. Despite mounting evidence for the importance of sRNAs in stress response, their role upon antibiotic exposure remains unknown. In this study, we sought to determine firstly, whether differential expression of sRNAs occurs upon antibiotic exposure and secondly, whether these sRNAs could be attributed to microbial tolerance to antibiotics.

Results: A small scale sRNA cloning strategy of Salmonella enterica serovar Typhimurium SL1344 challenged with half the minimal inhibitory concentration of tigecycline identified four sRNAs (sYJ5, sYJ20, sYJ75 and sYJ118) which were reproducibly upregulated in the presence of either tigecycline or tetracycline. The coding sequences of the four sRNAs were found to be conserved across a number of species. Genome analysis found that sYJ5 and sYJ118 mapped between the 16S and 23S rRNA encoding genes. sYJ20 (also known as SroA) is encoded upstream of the tbpAyabKyabJ operon and is classed as a riboswitch, whilst its role in antibiotic stress-response appears independent of its riboswitch function. sYJ75 is encoded between genes that are involved in enterobactin transport and metabolism. Additionally we find that the genetic deletion of sYJ20 rendered a reduced viability phenotype in the presence of tigecycline, which was recovered when complemented. The upregulation of some of these sRNAs were also observed when S. Typhimurium was challenged by ampicillin (sYJ5, 75 and 118); or when Klebsiella pneumoniae was challenged by tigecycline (sYJ20 and 118).

Conclusions: Small RNAs are overexpressed as a result of antibiotic exposure in S. Typhimurium where the same molecules are upregulated in a related species or after exposure to different antibiotics. sYJ20, a riboswitch, appears to possess a trans-regulatory sRNA role in antibiotic tolerance. These findings imply that the sRNA mediated response is a component of the bacterial response to antibiotic challenge.

Local network-based measures to assess the inferability of different regulatory networks

The purpose of this study is to compare the inferability of various synthetic as well as real biological regulatory networks. In order to assess differences we apply local network-based measures. That means, instead of applying global measures, we investigate and assess an inference algorithm locally, on the level of individual edges and subnetworks. We demonstrate the behaviour of our local network-based measures with respect to different regulatory networks by conducting large-scale simulations. As inference algorithm we use exemplarily ARACNE. The results from our exploratory analysis allow us not only to gain new insights into the strength and weakness of an inference algorithm with respect to characteristics of different regulatory networks, but also to obtain information that could be used to design novel problem-specific statistical estimators.

Inferring the conservative causal core of gene regulatory networks

Background
Inferring gene regulatory networks from large-scale expression data is an important problem that received much attention in recent years. These networks have the potential to gain insights into causal molecular interactions of biological processes. Hence, from a methodological point of view, reliable estimation methods based on observational data are needed to approach this problem practically.

Results
In this paper, we introduce a novel gene regulatory network inference (GRNI) algorithm, called C3NET. We compare C3NET with four well known methods, ARACNE, CLR, MRNET and RN, conducting in-depth numerical ensemble simulations and demonstrate also for biological expression data from E. coli that C3NET performs consistently better than the best known GRNI methods in the literature. In addition, it has also a low computational complexity. Since C3NET is based on estimates of mutual information values in conjunction with a maximization step, our numerical investigations demonstrate that our inference algorithm exploits causal structural information in the data efficiently.

Conclusions
For systems biology to succeed in the long run, it is of crucial importance to establish methods that extract large-scale gene networks from high-throughput data that reflect the underlying causal interactions among genes or gene products. Our method can contribute to this endeavor by demonstrating that an inference algorithm with a neat design permits not only a more intuitive and possibly biological interpretation of its working mechanism but can also result in superior results.

Influence of the experimental design of gene expression studies on the inference of gene regulatory networks: environmental factors

The inference of gene regulatory networks gained within recent years a considerable interest in the biology and biomedical community. The purpose of this paper is to investigate the influence that environmental conditions can exhibit on the inference performance of network inference algorithms. Specifically, we study five network inference methods, Aracne, BC3NET, CLR, C3NET and MRNET, and compare the results for three different conditions: (I) observational gene expression data: normal environmental condition, (II) interventional gene expression data: growth in rich media, (III) interventional gene expression data: normal environmental condition interrupted by a positive spike-in stimulation. Overall, we find that different statistical inference methods lead to comparable, but condition-specific results. Further, our results suggest that non-steady-state data enhance the inferability of regulatory networks.

Urothelial cancer gene regulatory networks inferred from large-scale RNAseq, Bead and Oligo gene expression data

BACKGROUND: Urothelial pathogenesis is a complex process driven by an underlying network of interconnected genes. The identification of novel genomic target regions and gene targets that drive urothelial carcinogenesis is crucial in order to improve our current limited understanding of urothelial cancer (UC) on the molecular level. The inference of genome-wide gene regulatory networks (GRN) from large-scale gene expression data provides a promising approach for a detailed investigation of the underlying network structure associated to urothelial carcinogenesis.

METHODS: In our study we inferred and compared three GRNs by the application of the BC3Net inference algorithm to large-scale transitional cell carcinoma gene expression data sets from Illumina RNAseq (179 samples), Illumina Bead arrays (165 samples) and Affymetrix Oligo microarrays (188 samples). We investigated the structural and functional properties of GRNs for the identification of molecular targets associated to urothelial cancer.

RESULTS: We found that the urothelial cancer (UC) GRNs show a significant enrichment of subnetworks that are associated with known cancer hallmarks including cell cycle, immune response, signaling, differentiation and translation. Interestingly, the most prominent subnetworks of co-located genes were found on chromosome regions 5q31.3 (RNAseq), 8q24.3 (Oligo) and 1q23.3 (Bead), which all represent known genomic regions frequently deregulated or aberated in urothelial cancer and other cancer types. Furthermore, the identified hub genes of the individual GRNs, e.g., HID1/DMC1 (tumor development), RNF17/TDRD4 (cancer antigen) and CYP4A11 (angiogenesis/ metastasis) are known cancer associated markers. The GRNs were highly dataset specific on the interaction level between individual genes, but showed large similarities on the biological function level represented by subnetworks. Remarkably, the RNAseq UC GRN showed twice the proportion of significant functional subnetworks. Based on our analysis of inferential and experimental networks the Bead UC GRN showed the lowest performance compared to the RNAseq and Oligo UC GRNs.

CONCLUSION: To our knowledge, this is the first study investigating genome-scale UC GRNs. RNAseq based gene expression data is the data platform of choice for a GRN inference. Our study offers new avenues for the identification of novel putative diagnostic targets for subsequent studies in bladder tumors.

New perspectives on neoplasia and the RNA world

Key tenets of modern biology are the central place of protein in cell regulation and the flow of genetic information from DNA to RNA to protein. However, it is becoming increasingly apparent that genomes are much more complex than hitherto thought with remarkably complex regulatory systems. The notion that the fraction of the genome involved in coding protein is all that matters is increasingly being questioned as the roles of non-coding RNA (ncRNA) in cellular systems becomes recognised. The RNA world, including microRNA (miRNA), small inhibitory RNA (siRNA) and other RNA species, are now recognised as being crucial for the regulation of chromatin structure, gene expression, mRNA processing and splicing, mRNA stability and translational control. Furthermore such ncRNA systems may be perturbed in disease states and most notably in neoplasia, including in haematological malignancies. Here the burgeoning evidence for a role of miRNA in neoplasia is reviewed and the importance of understanding the RNA world emphasised. Copyright (c) 2005 John Wiley & Sons, Ltd.

Overexpression of the rhamnose catabolism regulatory protein, RhaR: a novel mechanism for metronidazole resistance in Bacteroides thetaiotaomicron

Objectives: The aim of the investigation was to use in vitro transposon mutagenesis to generate metronidazole resistance in the obligately anaerobic pathogenic bacterium Bacteroides thetaiotaomicron, and to identify the genes involved to enable investigation of potential mechanisms for the generation of metronidazole resistance.
Methods: The genes affected by the transposon insertion were identified by plasmid rescue and sequencing. Expression levels of the relevant genes were determined by semi-quantitative RNA hybridization and catabolic activity by lactate dehydrogenase/pyruvate oxidoreductase assays.
Results: A metronidazole-resistant mutant was isolated and the transposon insertion site was identified in an intergenic region between the rhaO and rhaR genes of the gene cluster involved in the uptake and catabolism of rhamnose. Metronidazole resistance was observed during growth in defined medium containing either rhamnose or glucose. The metronidazole-resistant mutant showed improved growth in the presence of rhamnose as compared with the wild-type parent. There was increased transcription of all genes of the rhamnose gene cluster in the presence of rhamnose and glucose, likely due to the transposon providing an additional promoter for the rhaR gene, encoding the positive transcriptional regulator of the rhamnose operon. The B. thetaiotaomicron metronidazole resistance phenotype was recreated by overexpressing the rhaR gene in the B. thetaiotaomicron wild-type parent. Both the metronidazole-resistant transposon mutant and RhaR overexpression strains displayed a phenotype of higher lactate dehydrogenase and lower pyruvate oxidoreductase activity in comparison with the parent strain during growth in rhamnose.
Conclusions: These data indicate that overexpression of the rhaR gene generates metronidazole resistance in B. thetaiotaomicron

The Yin and Yang of vitamin D receptor (VDR) signaling in neoplastic progression: Operational networks and tissue-specific growth control

Substantive evidence implicates vitamin D receptor (VDR) or its natural ligand 1a,25-(OH)2 D3 in modulation of tumor growth. However, both human and animal studies indicate tissue-specificity of effect. Epidemiological studies show both inverse and direct relationships between serum 25(OH)D levels and common solid cancers. VDR ablation affects carcinogen-induced tumorigenesis in a tissue-specific manner in model systems. Better understanding of the tissue-specificity of vitamin D-dependent molecular networks may provide insight into selective growth control by the seco-steroid, 1a,25-(OH)2 D3. This commentary considers complex factors that may influence the cell- or tissue-specificity of 1a,25-(OH)2 D3/VDR growth effects, including local synthesis, metabolism and transport of vitamin D and its metabolites, vitamin D receptor (VDR) expression and ligand-interactions, 1a,25-(OH)2 D3 genomic and non-genomic actions, Ca2+ flux, kinase activation, VDR interactions with activating and inhibitory vitamin D responsive elements (VDREs) within target gene promoters, VDR coregulator recruitment and differential effects on key downstream growth regulatory genes. We highlight some differences of VDR growth control relevant to colonic, esophageal, prostate, pancreatic and other cancers and assess the potential for development of selective prevention or treatment strategies.

IL-12R2 promotes the development of CD4+CD25+ regulatory T cells

We have previously shown that mice lacking the IL-12-specific receptor subunit ß2 (IL-12Rß2) develop more severe experimental autoimmune encephalomyelitis than wild-type (WT) mice. The mechanism underlying this phenomenon is not known; nor is it known whether deficiency of IL-12Rß2 impacts other autoimmune disorders similarly. In the present study we demonstrate that IL-12Rß2-/- mice develop earlier onset and more severe disease in the streptozotocin-induced model of diabetes, indicating predisposition of IL-12Rß2-deficient mice to autoimmune diseases. T cells from IL-12Rß2-/- mice exhibited significantly higher proliferative responses upon TCR stimulation. The numbers of naturally occurring CD25+CD4+ regulatory T cells (Tregs) in the thymus and spleen of IL-12Rß2-/- mice were comparable to those of WT mice. However, IL-12Rß2-/- mice exhibited a significantly reduced capacity to develop Tregs upon stimulation with TGF-ß, as shown by significantly lower numbers of CD25+CD4+ T cells that expressed Foxp3. Functionally, CD25+CD4+ Tregs derived from IL-12Rß2-/- mice were less efficient than those from WT mice in suppressing effector T cells. The role of IL-12Rß2 in the induction of Tregs was confirmed using small interfering RNA. These findings suggest that signaling via IL-12Rß2 regulates both the number and functional maturity of Treg cells, which indicates a novel mechanism underlying the regulation of autoimmune diseases by the IL-12 pathway. Copyright © 2008 by The American Association of Immunologists, Inc.

Information processing in the transcriptional regulatory network of yeast: Functional robustness

Background: Gene networks are considered to represent various aspects of molecular biological systems meaningfully because they naturally provide a systems perspective of molecular interactions. In this respect, the functional understanding of the transcriptional regulatory network is considered as key to elucidate the functional organization of an organism.