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Context: Inferring gene regulatory networks (GRN) from high-throughput gene expression data is a challenging task for which different strategies have been developed. Nevertheless, no ever-winning method exists, and each method has its advantages, intrinsic biases, and application domains. Thus, in order to analyze a dataset, users should be able to test different techniques and choose the most appropriate one. This step can be particularly difficult and time consuming, since most methods' implementations are made available independently, possibly in different programming languages. The implementation of an open-source library containing different inference methods within a common framework is expected to be a valuable toolkit for the systems biology community. Results: In this work, we introduce GReNaDIne (Gene Regulatory Network Data-driven Inference), a Python package that implements 18 machine learning data-driven gene regulatory network inference methods. It also includes eight generalist preprocessing techniques, suitable for both RNA-seq and microarray dataset analysis, as well as four normalization techniques dedicated to RNA-seq. In addition, this package implements the possibility to combine the results of different inference tools to form robust and efficient ensembles. This package has been successfully assessed under the DREAM5 challenge benchmark dataset. The open-source GReNaDIne Python package is made freely available in a dedicated GitLab repository, as well as in the official third-party software repository PyPI Python Package Index. The latest documentation on the GReNaDIne library is also available at Read the Docs, an open-source software documentation hosting platform. Contribution: The GReNaDIne tool represents a technological contribution to the field of systems biology. This package can be used to infer gene regulatory networks from high-throughput gene expression data using different algorithms within the same framework. In order to analyze their datasets, users can apply a battery of preprocessing and postprocessing tools and choose the most adapted inference method from the GReNaDIne library and even combine the output of different methods to obtain more robust results. The results format provided by GReNaDIne is compatible with well-known complementary refinement tools such as PYSCENIC. [ABSTRACT FROM AUTHOR]

Inferring Gene Regulatory Networks from high-throughput gene expression data is a challenging problem, addressed by the systems biology community. Most approaches that aim at unraveling the gene regulation mechanisms in a data-driven way, analyze gene expression datasets to score potential regulatory links between transcription factors and target genes. So far, three major families of approaches have been proposed to score regulatory links. These methods rely respectively on correlation measures, mutual information metrics, and regression algorithms. In this paper we present a new family of data-driven inference methods. This new family, inspired by the regression-based paradigm, relies on the use of classification algorithms. This paper assesses and advocates for the use of this paradigm as a new promising approach to infer gene regulatory networks. Indeed, the development and assessment of five new inference methods based on well-known classification algorithms shows that the classification-based inference family exhibits good results when compared to well-established paradigms. [ABSTRACT FROM AUTHOR]

Background: Nutritional symbioses play a central role in insects' adaptation to specialized diets and in their evolutionary success. The obligatory symbiosis between the pea aphid, Acyrthosiphon pisum, and the bacterium, Buchnera aphidicola, is no exception as it enables this important agricultural pest insect to develop on a diet exclusively based on plant phloem sap. The symbiotic bacteria provide the host with essential amino acids lacking in its diet but necessary for the rapid embryonic growth seen in the parthenogenetic viviparous reproduction of aphids. The aphid furnishes, in exchange, non-essential amino acids and other important metabolites. Understanding the regulations acting on this integrated metabolic system during the development of this insect is essential in elucidating aphid biology. Results: We used a microarray-based approach to analyse gene expression in the late embryonic and the early larval stages of the pea aphid, characterizing, for the first time, the transcriptional profiles in these developmental phases. Our analyses allowed us to identify key genes in the phenylalanine, tyrosine and dopamine pathways and we identified ACYPI004243, one of the four genes encoding for the aspartate transaminase (E.C. 2.6.1.1), as specifically regulated during development. Indeed, the tyrosine biosynthetic pathway is crucial for the symbiotic metabolism as it is shared between the two partners, all the precursors being produced by B. aphidicola. Our microarray data are supported by HPLC amino acid analyses demonstrating an accumulation of tyrosine at the same developmental stages, with an up-regulation of the tyrosine biosynthetic genes. Tyrosine is also essential for the synthesis of cuticular proteins and it is an important precursor for cuticle maturation: together with the up-regulation of tyrosine biosynthesis, we observed an up-regulation of cuticular genes expression. We were also able to identify some amino acid transporter genes which are essential for the switch over to the late embryonic stages in pea aphid development. Conclusions: Our data show that, in the development of A. pisum, a specific host gene set regulates the biosynthetic pathways of amino acids, demonstrating how the regulation of gene expression enables an insect to control the production of metabolites crucial for its own development and symbiotic metabolism. [ABSTRACT FROM AUTHOR]

Background: Buchnera aphidicola is an obligate symbiotic bacterium, associated with most of the aphididae, whose genome has drastically shrunk during intracellular evolution. Gene regulation in Buchnera has been a matter of controversy in recent years as the combination of genomic information with the experimental results has been contradictory, refuting or arguing in favour of a functional and responsive transcription regulation in Buchnera. The goal of this study was to describe the gene transcription regulation capabilities of Buchnera based on the inventory of cis- and trans-regulators encoded in the genomes of five strains from different aphids (Acyrthosiphon pisum, Schizaphis graminum, Baizongia pistacea, Cinara cedri and Cinara tujafilina), as well as on the characterisation of some intrinsic structural properties of the DNA molecule in these bacteria. Results: Interaction graph analysis shows that gene neighbourhoods are conserved between E. coli and Buchnera in structures called transcriptons, interactons and metabolons, indicating that selective pressures have acted on the evolution of transcriptional, protein-protein interaction and metabolic networks in Buchnera. The transcriptional regulatory network in Buchnera is composed of a few general DNA-topological regulators (Nucleoid Associated Proteins and topoisomerases), with the quasi-absence of any specific ones (except for multifunctional enzymes with a known gene expression regulatory role in Escherichia coli, such as AlaS, PepA and BolA, and the uncharacterized hypothetical regulators YchA and YrbA). The relative positioning of regulatory genes along the chromosome of Buchnera seems to have conserved its ancestral state, despite the genome erosion. Sigma-70 promoters with canonical thermodynamic sequence profiles were detected upstream of about 94% of the CDS of Buchnera in the different aphids. Based on Stress-Induced Duplex Destabilization (SIDD) measurements, unstable σ70 promoters were found specifically associated with the regulator and transporter genes. Conclusions: This genomic analysis provides supporting evidence of a selection of functional regulatory structures and it has enabled us to propose hypotheses concerning possible links between these regulatory elements and the DNA-topology (i.e., supercoiling, curvature, flexibility and base-pair stability) in the regulation of gene expression in the shrunken genome of Buchnera. [ABSTRACT FROM AUTHOR]

Background: Gene expression regulation is still poorly documented in bacteria with highly reduced genomes. Understanding the evolution and mechanisms underlying the regulation of gene transcription in Buchnera aphidicola, the primary endosymbiont of aphids, is expected both to enhance our understanding of this nutritionally based association and to provide an intriguing case-study of the evolution of gene expression regulation in a reduced bacterial genome. Results: A Bayesian predictor was defined to infer the B. aphidicola transcription units, which were further validated using transcriptomic data and RT-PCR experiments. The characteristics of B. aphidicola predicted transcription units (TUs) were analyzed in order to evaluate the impact of operon map organization on the regulation of gene transcription. On average, B. aphidicola TUs contain more genes than those of E. coli. The global layout of B. aphidicola operon map was mainly shaped by the big reduction and the rearrangements events, which occurred at the early stage of the symbiosis. Our analysis suggests that this operon map may evolve further only by small reorganizations around the frontiers of B. aphidicola TUs, through promoter and/or terminator sequence modifications and/or by pseudogenization events. We also found that the need for specific transcription regulation exerts some pressure on gene conservation, but not on gene assembling in the operon map in Buchnera. Our analysis of the TUs spacing pointed out that a selection pressure is maintained on the length of the intergenic regions between divergent adjacent gene pairs. Conclusions: B. aphidicola can seemingly only evolve towards a more polycistronic operon map. This implies that gene transcription regulation is probably subject to weak selection pressure in Buchnera conserving operons composed of genes with unrelated functions. [ABSTRACT FROM AUTHOR]

Parallel quantification of a large number of messenger RNA transcripts, using microarray technology, promises to provide unsuspected information about many cellular processes. Although experimental protocols on microarray applications are available, only limited methodological information on glass-slide manufacturing and signal interpretation has been published. The aim of this paper is to provide new insights into the practical aspects of the construction and hybridization of oligonucleotide-based microarrays. The intracellular symbiotic bacterium of aphids, Buchnera aphidicola, is used here as a model organism. The first part of the work is devoted to the optimization of procedures for printing slides, labeling of cDNA targets and hybridization. In the second part, based on a statistical analysis of the results, we discuss the influence of the probe attachment chemistry, of the labeling method, of the oligonucleotide position and of the concentration of a spotted oligonucleotide on signal intensity. The problem of signal specificity is also addressed, based on the calculation of the fluorescent ratio for each probe to its corresponding mismatch control probe. Lastly, the selection of internal spiked RNAs appropriate to our bacterial samples and useful for the data normalization step is presented. [Copyright &y& Elsevier]

Metal pollution is a major concern for aquatic environments. Widespread contamination by various trace metal ions has been described in freshwater streams as well as their subsequent bioaccumulation, potentially leading to toxicity and trophic transfer. Metallothioneins constitute an evolutionary conserved family of low molecular weight, cysteine-rich, metal-chelating proteins, whose known physiological functions are the maintenance of the homeostasis of essential metals, the detoxification of non-essential metals, and the protection against oxidative stress and free radicals. In this study, we identified two metallothionein-coding transcripts, mt1 and mt2 , in the transcriptome of the amphipod Gammarus fossarum , a sentinel species widely used to assess the quality of watersheds. For the first time, we investigated the organ-specific patterns of expression of these two mt transcripts at the individual level in the gills and the caeca of this small crustacean. In silico analysis and experimental exposures to environmentally relevant concentrations of cadmium, zinc and silver showed that G. fossarum mt1 induction is stronger after Cd exposure compared to the other tested metals. G. fossarum mt1 was more significantly induced in the caeca than in the gills of exposed organisms for any metal exposure, while G. fossarum mt2 was, at least at the individual level, more inducible in the gills than in the caeca of G. fossarum exposed to Cd and Zn. Our results provide new genetic resources that will help to improve the understanding of metal homeostasis in this sentinel species. [Display omitted] • Identification of two transcripts coding for two metallothioneins in the freshwater sentinel specie Gammarus fossarum. • Gene expression quantification of Gfoss mt1 and mt2 at the organ level in a small crustacean. • Identification of Gfoss mt1 as a cadmium responsive metallothionein. [ABSTRACT FROM AUTHOR]