Gaëlle Lelandais

Comparative transcriptomics of drought responses in Populus: a meta-analysis of genome-wide expression profiling in mature leaves and root apices across two genotypes

BackgroundComparative genomics has emerged as a promising means of unravelling the molecular networks underlying complex traits such as drought tolerance. Here we assess the genotype-dependent component of the drought-induced transcriptome response in two poplar genotypes differing in drought tolerance. Drought-induced responses were analysed in leaves and root apices and were compared with available transcriptome data from other Populus species.ResultsUsing a multi-species designed microarray, a genomic DNA-based selection of probesets provided an unambiguous between-genotype comparison. Analyses of functional group enrichment enabled the extraction of processes physiologically relevant to drought response. The drought-driven changes in gene expression occurring in root apices were consistent across treatments and genotypes. For mature leaves, the transcriptome response varied weakly but in accordance with the duration of water deficit. A differential clustering algorithm revealed similar and divergent gene co-expression patterns among the two genotypes. Since moderate stress levels induced similar physiological responses in both genotypes, the genotype-dependent transcriptional responses could be considered as intrinsic divergences in genome functioning. Our meta-analysis detected several candidate genes and processes that are differentially regulated in root and leaf, potentially under developmental control, and preferentially involved in early and long-term responses to drought.ConclusionsIn poplar, the well-known drought-induced activation of sensing and signalling cascades was specific to the early response in leaves but was found to be general in root apices. Comparing our results to what is known in arabidopsis, we found that transcriptional remodelling included signalling and a response to energy deficit in roots in parallel with transcriptional indices of hampered assimilation in leaves, particularly in the drought-sensitive poplar genotype.

Statistical inference of the time-varying structure of gene-regulation networks

BackgroundBiological networks are highly dynamic in response to environmental and physiological cues. This variability is in contrast to conventional analyses of biological networks, which have overwhelmingly employed static graph models which stay constant over time to describe biological systems and their underlying molecular interactions.MethodsTo overcome these limitations, we propose here a new statistical modelling framework, the ARTIVA formalism (Auto Regressive TIme VArying models), and an associated inferential procedure that allows us to learn temporally varying gene-regulation networks from biological time-course expression data. ARTIVA simultaneously infers the topology of a regulatory network and how it changes over time. It allows us to recover the chronology of regulatory associations for individual genes involved in a specific biological process (development, stress response, etc.).ResultsWe demonstrate that the ARTIVA approach generates detailed insights into the function and dynamics of complex biological systems and exploits efficiently time-course data in systems biology. In particular, two biological scenarios are analyzed: the developmental stages of Drosophila melanogaster and the response of Saccharomyces cerevisiae to benomyl poisoning.ConclusionsARTIVA does recover essential temporal dependencies in biological systems from transcriptional data, and provide a natural starting point to learn and investigate their dynamics in greater detail.

Transcriptomic Analyses during the Transition from Biomass Production to Lipid Accumulation in the Oleaginous Yeast Yarrowia lipolytica

We previously developed a fermentation protocol for lipid accumulation in the oleaginous yeast Y. lipolytica. This process was used to perform transcriptomic time-course analyses to explore gene expression in Y. lipolytica during the transition from biomass production to lipid accumulation. In this experiment, a biomass concentration of 54.6 gCDW/l, with 0.18 g/gCDW lipid was obtained in ca. 32 h, with low citric acid production. A transcriptomic profiling was performed on 11 samples throughout the fermentation. Through statistical analyses, 569 genes were highlighted as differentially expressed at one point during the time course of the experiment. These genes were classified into 9 clusters, according to their expression profiles. The combination of macroscopic and transcriptomic profiles highlighted 4 major steps in the culture: (i) a growth phase, (ii) a transition phase, (iii) an early lipid accumulation phase, characterized by an increase in nitrogen metabolism, together with strong repression of protein production and activity; (iv) a late lipid accumulation phase, characterized by the rerouting of carbon fluxes within cells. This study explores the potential of Y. lipolytica as an alternative oil producer, by identifying, at the transcriptomic level, the genes potentially involved in the metabolism of oleaginous species.

Comparative analysis of missing value imputation methods to improve clustering and interpretation of microarray experiments

BackgroundMicroarray technologies produced large amount of data. In a previous study, we have shown the interest of k-Nearest Neighbour approach for restoring the missing gene expression values, and its positive impact of the gene clustering by hierarchical algorithm. Since, numerous replacement methods have been proposed to impute missing values (MVs) for microarray data. In this study, we have evaluated twelve different usable methods, and their influence on the quality of gene clustering. Interestingly we have used several datasets, both kinetic and non kinetic experiments from yeast and human.ResultsWe underline the excellent efficiency of approaches proposed and implemented by Bo and co-workers and especially one based on expected maximization (EM_array). These improvements have been observed also on the imputation of extreme values, the most difficult predictable values. We showed that the imputed MVs have still important effects on the stability of the gene clusters. The improvement on the clustering obtained by hierarchical clustering remains limited and, not sufficient to restore completely the correct gene associations. However, a common tendency can be found between the quality of the imputation method and the gene cluster stability. Even if the comparison between clustering algorithms is a complex task, we observed that k-means approach is more efficient to conserve gene associations.ConclusionsMore than 6.000.000 independent simulations have assessed the quality of 12 imputation methods on five very different biological datasets. Important improvements have so been done since our last study. The EM_array approach constitutes one efficient method for restoring the missing expression gene values, with a lower estimation error level. Nonetheless, the presence of MVs even at a low rate is a major factor of gene cluster instability. Our study highlights the need for a systematic assessment of imputation methods and so of dedicated benchmarks. A noticeable point is the specific influence of some biological dataset.

Structure and properties of transcriptional networks driving selenite stress response in yeasts.

BackgroundStress responses provide valuable models for deciphering the transcriptional networks controlling the adaptation of the cell to its environment. We analyzed the transcriptome response of yeast to toxic concentrations of selenite. We used gene network mapping tools to identify functional pathways and transcription factors involved in this response. We then used chromatin immunoprecipitation and knock-out experiments to investigate the role of some of these regulators and the regulatory connections between them.ResultsSelenite rapidly activates a battery of transcriptional circuits, including iron deprivation, oxidative stress and protein degradation responses. The mRNA levels of several transcriptional regulators are themselves regulated. We demonstrate the existence of a positive transcriptional loop connecting the regulator of proteasome expression, Rpn4p, to the pleiotropic drug response factor, Pdr1p. We also provide evidence for the involvement of this regulatory module in the oxidative stress response controlled by the Yap1p transcription factor and its conservation in the pathogenic yeast C. glabrata. In addition, we show that the drug resistance regulator gene YRR1 and the iron homeostasis regulator gene AFT2 are both directly regulated by Yap1p.ConclusionThis work depicted a highly interconnected and complex transcriptional network involved in the adaptation of yeast genome expression to the presence of selenite in its chemical environment. It revealed the transcriptional regulation of PDR1 by Rpn4p, proposed a new role for the pleiotropic drug resistance network in stress response and demonstrated a direct regulatory connection between oxidative stress response and iron homeostasis.

Genome adaptation to chemical stress: clues from comparative transcriptomics in Saccharomyces cerevisiae and Candida glabrata

BackgroundRecent technical and methodological advances have placed microbial models at the forefront of evolutionary and environmental genomics. To better understand the logic of genetic network evolution, we combined comparative transcriptomics, a differential clustering algorithm and promoter analyses in a study of the evolution of transcriptional networks responding to an antifungal agent in two yeast species: the free-living model organism Saccharomyces cerevisiae and the human pathogen Candida glabrata.ResultsWe found that although the gene expression patterns characterizing the response to drugs were remarkably conserved between the two species, part of the underlying regulatory networks differed. In particular, the roles of the oxidative stress response transcription factors ScYap1p (in S. cerevisiae) and Cgap1p (in C. glabrata) had diverged. The sets of genes whose benomyl response depends on these factors are significantly different. Also, the DNA motifs targeted by ScYap1p and Cgap1p are differently represented in the promoters of these genes, suggesting that the DNA binding properties of the two proteins are slightly different. Experimental assays of ScYap1p and Cgap1p activities in vivo were in accordance with this last observation.ConclusionsBased on these results and recently published data, we suggest that the robustness of environmental stress responses among related species contrasts with the rapid evolution of regulatory sequences, and depends on both the coevolution of transcription factor binding properties and the versatility of regulatory associations within transcriptional networks.

Responses of Pathogenic and Nonpathogenic Yeast Species to Steroids Reveal the Functioning and Evolution of Multidrug Resistance Transcriptional Networks

ABSTRACT Steroids are known to induce pleiotropic drug resistance states in hemiascomycetes, with tremendous potential consequences for human fungal infections. Our analysis of gene expression in Saccharomyces cerevisiae and Candida albicans cells subjected to three different concentrations of progesterone revealed that their pleiotropic drug resistance (PDR) networks were strikingly sensitive to steroids. In S. cerevisiae, 20 of the Pdr1p/Pdr3p target genes, including PDR3 itself, were rapidly induced by progesterone, which mimics the effects of PDR1 gain-of-function alleles. This unique property allowed us to decipher the respective roles of Pdr1p and Pdr3p in PDR induction and to define functional modules among their target genes. Although the expression profiles of the major PDR transporters encoding genes ScPDR5 and CaCDR1 were similar, the S. cerevisiae global PDR response to progesterone was only partly conserved in C. albicans. In particular, the role of Tac1p, the main C. albicans PDR regulator, in the progesterone response was apparently restricted to five genes. These results suggest that the C. albicans and S. cerevisiae PDR networks, although sharing a conserved core regarding the regulation of membrane properties, have different structures and properties. Additionally, our data indicate that other as yet undiscovered regulators may second Tac1p in the C. albicans drug response.

Posttranscriptional control of mitochondrial biogenesis: Spatio-temporal regulation of the protein import process

This review focuses on the posttranscriptional processes which govern mitochondrial biogenesis, with a special emphasis on the asymmetric localization–translation of nuclear‐encoded mRNAs as an important regulatory step of the protein import process. We review how spatio‐temporal mRNA regulons help to elicit timely, versatile, and coordinated intracellular processes to assemble mitochondrial structures. Our current knowledge on the mitochondrial import of respiratory chain assembly factors and the role of the ribonucleic acid (RNA) binding protein Puf3 are presented. A connection with the target of rapamycine signalling pathway may explain how respiratory chain assembly senses environmental conditions via the protein import machinery.

The metacaspase Mca1p has a dual role in farnesol-induced apoptosis in Candida albicans

Manipulating the apoptotic response of Candida albicans may help in the control of this opportunistic pathogen. The metacaspase Mca1p has been described as a key protease for apoptosis in C. albicans but little is known about its cleavage specificity and substrates. We therefore initiated a series of studies to describe its function. We used a strain disrupted for the MCA1 gene (mca1Δ/Δ) and compared its proteome to that of a wild-type isogenic strain, in the presence and absence of a known inducer of apoptosis, the quorum-sensing molecule farnesol. Label-free and TMT labeling quantitative proteomic analyses showed that both mca1 disruption and farnesol treatment significantly affected the proteome of the cells. The combination of both conditions led to an unexpected biological response: the strong overexpression of proteins implicated in the general stress. We studied sites cleaved by Mca1p using native peptidomic techniques, and a bottom-up approach involving GluC endoprotease: there appeared to be a “K/R” substrate specificity in P1 and a “D/E” specificity in P2. We also found 77 potential substrates of Mca1p, 13 of which validated using the most stringent filters, implicated in protein folding, protein aggregate resolubilization, glycolysis, and a number of mitochondrial functions. An immunoblot assay confirmed the cleavage of Ssb1p, a member of the HSP70 family of heat-shock proteins, in conditions where the metacaspase is activated. These various results indicate that Mca1p is involved in a limited and specific proteolysis program triggered by apoptosis. One of the main functions of Mca1p appears to be the degradation of several major heat-shock proteins, thereby contributing to weakening cellular defenses and amplifying the cell death process. Finally, Mca1p appears to contribute significantly to the control of mitochondria biogenesis and degradation. Consequently, Mca1p may be a link between the extrinsic and the intrinsic programmed cell death pathways in C. albicans.

RNA sequencing revealed novel actors of the acquisition of drug resistance in Candida albicans

BackgroundDrug susceptible clinical isolates of Candida albicans frequently become highly tolerant to drugs during chemotherapy, with dreadful consequences to patient health. We used RNA sequencing (RNA-seq) to analyze the transcriptomes of a CDR (Candida Drug Resistance) strain and its isogenic drug sensitive counterpart.ResultsRNA-seq unveiled differential expression of 228 genes including a) genes previously identified as involved in CDR, b) genes not previously associated to the CDR phenotype, and c) novel transcripts whose function as a gene is uncharacterized. In particular, we show for the first time that CDR acquisition is correlated with an overexpression of the transcription factor encoding gene CZF1. CZF1 null mutants were susceptible to many drugs, independently of known multidrug resistance mechanisms. We show that CZF1 acts as a repressor of β-glucan synthesis, thus negatively regulating cell wall integrity. Finally, our RNA-seq data allowed us to identify a new transcribed region, upstream of the TAC1 gene, which encodes the major CDR transcriptional regulator.ConclusionOur results open new perspectives of the role of Czf1 and of our understanding of the transcriptional and post-transcriptional mechanisms that lead to the acquisition of drug resistance in C. albicans, with potential for future improvements of therapeutic strategies.