Alain Trubuil

Proteomic Signature of Lactococcus lactis NCDO763 Cultivated in Milk

ABSTRACT We have compared the proteomic profiles of L. lactis subsp. cremoris NCDO763 growing in the synthetic medium M17Lac, skim milk microfiltrate (SMM), and skim milk. SMM was used as a simple model medium to reproduce the initial phase of growth of L. lactis in milk. To widen the analysis of the cytoplasmic proteome, we used two different gel systems (pH ranges of 4 to 7 and 4.5 to 5.5), and the proteins associated with the cell envelopes were also studied by two-dimensional electrophoresis. In the course of the study, we analyzed about 800 spots and identified 330 proteins by mass spectrometry. We observed that the levels of more than 50 and 30 proteins were significantly increased upon growth in SMM and milk, respectively. The large redeployment of protein synthesis was essentially associated with an activation of pathways involved in the metabolism of nitrogenous compounds: peptidolytic and peptide transport systems, amino acid biosynthesis and interconversion, and de novo biosynthesis of purines. We also showed that enzymes involved in reactions feeding the purine biosynthetic pathway in one-carbon units and amino acids have an increased level in SMM and milk. The analysis of the proteomic data suggested that the glutamine synthetase (GS) would play a pivotal role in the adaptation to SMM and milk. The analysis of glnA expression during growth in milk and the construction of a glnA-defective mutant confirmed that GS is an essential enzyme for the development of L. lactis in dairy media. This analysis thus provides a proteomic signature of L. lactis, a model lactic acid bacterium, growing in its technological environment.

Human intestinal circadian clock : Expression of clock genes in colonocytes lining the crypt

Biological clock components have been detected in many epithelial tissues of the digestive tract of mammals (oral mucosa, pancreas, and liver), suggesting the existence of peripheral circadian clocks that may be entrainable by food. Our aim was to investigate the expression of main peripheral clock genes in colonocytes of healthy humans and in human colon carcinoma cell lines. The presence of clock components was investigated in single intact colonic crypts isolated by chelation from the biopsies of 25 patients (free of any sign of colonic lesions) undergoing routine colonoscopy and in cell lines of human colon carcinoma (Caco2 and HT29 clone 19A). Per‐1, per‐2, and clock mRNA were detected by real‐time RT‐PCR. The three‐dimensional distributions of PER‐1, PER‐2, CLOCK, and BMAL1 proteins were recorded along colonic crypts by immunofluorescent confocal imaging. We demonstrate the presence of per‐1, per‐2, and clock mRNA in samples prepared from colonic crypts of 5 patients and in all cell lines. We also demonstrate the presence of two circadian clock proteins, PER‐1 and CLOCK, in human colonocytes on crypts isolated from 20 patients (15 patients for PER‐1 and 6 for CLOCK) and in colon carcinoma cells. Establishing the presence of clock proteins in human colonic crypts is the first step toward the study of the regulation of the intestinal circadian clock by nutrients and feeding rhythms.

Specialization of Oleosins in Oil Body Dynamics during Seed Development in Arabidopsis Seeds

Oil body dynamics reveal new roles for oleosins during seed development. Oil bodies (OBs) are seed-specific lipid storage organelles that allow the accumulation of neutral lipids that sustain plantlet development after the onset of germination. OBs are covered with specific proteins embedded in a single layer of phospholipids. Using fluorescent dyes and confocal microscopy, we monitored the dynamics of OBs in living Arabidopsis (Arabidopsis thaliana) embryos at different stages of development. Analyses were carried out with different genotypes: the wild type and three mutants affected in the accumulation of various oleosins (OLE1, OLE2, and OLE4), three major OB proteins. Image acquisition was followed by a detailed statistical analysis of OB size and distribution during seed development in the four dimensions (x, y, z, and t). Our results indicate that OB size increases sharply during seed maturation, in part by OB fusion, and then decreases until the end of the maturation process. In single, double, and triple mutant backgrounds, the size and spatial distribution of OBs are modified, affecting in turn the total lipid content, which suggests that the oleosins studied have specific functions in the dynamics of lipid accumulation.

Bacillus subtilis serine/threonine protein kinase YabT is involved in spore development via phosphorylation of a bacterial recombinase.

We characterized YabT, a serine/threonine kinase of the Hanks family, from Bacillus subtilis. YabT is a putative transmembrane kinase that lacks the canonical extracellular signal receptor domain. We demonstrate that YabT possesses a DNA‐binding motif essential for its activation. In vivo YabT is expressed during sporulation and localizes to the asymmetric septum. Cells devoid of YabT sporulate more slowly and exhibit reduced resistance to DNA damage during sporulation. We established that YabT phosphorylates DNA‐recombinase RecA at the residue serine 2. A non‐phosphorylatable mutant of RecA exhibits the same phenotype as the ΔyabT mutant, and a phosphomimetic mutant of RecA complements ΔyabT, suggesting that YabT acts via RecA phosphorylation in vivo. During spore development, phosphorylation facilitates the formation of transient and mobile RecA foci that exhibit a scanning‐like movement associated to the nucleoid in the mother cell. In some cells these foci persist at the end of spore development. We show that persistent RecA foci, which presumably coincide with irreparable lesions, are mutually exclusive with the completion of spore morphogenesis. Our results highlight similarities between the bacterial serine/threonine kinase YabT and eukaryal kinases C‐Abl and Mec1, which are also activated by DNA, and phosphorylate proteins involved in DNA damage repair.

Role of bacterial peptidase F inferred by statistical analysis and further experimental validation

Despite the quantity of high‐throughput data available nowadays, the precise role of many proteins has not been elucidated. Available methods for classifying proteins and reconstructing metabolic networks are efficient for finding global categories, but do not answer the biologists specific and targeted questions. Following Yamanishi et al. [Yamanishi, Y, Vert, JP, Nakaya, A, and Kaneisha, M (2003). “Extraction of correlated clusters from multiple genomic data by generalized kernel canonical correlation analysis.” Bioinformatics 19, Suppl. 1, i323‐i330] we used a kernel canonical correlation analysis (KCCA) to predict the role of the bacterial peptidase PepF. We integrated five existing data types: protein metabolic networks, microarray data, phylogenetic profiles, distances between proteins and incomplete two‐dimensional‐gel data (for which we propose a completion strategy), available for Lactococcus lactis to determine relationships between proteins. The predicted relationships were then used to guide our laboratory work which proved most of the predictions correct. PepF had previously been characterized as a zinc dependent endopeptidase [Nardi, M, Renault, P, and Monnet, V (1997). “Duplication of the pepF gene and shuffling of DNA fragments on the lactose plasmid of Lactococcus lactis.” J. Bacteriol. 179, 4164–4171; Monnet, V, Nardi, M, Chopin, MC, and Gripon, JC (1994). “Biochemical and genetic characterization of PepF on oligoendopeptidase from Lactococcus lactis.” J. Bio. Chem. 269, 32070–32076]. Analyzing a PepF mutant, we confirmed its participation in protein secretion through a strong relationship between the signal peptidase I and PepF predicted by the KCCA. The global nature of our approach made it possible to discover pleiotropic roles of the protein which had remained unknown using classical approaches.

3-D aggregated object detection and labeling from multivariate confocal microscopy images: a model validation approach

One essential assumption used in object detection and labeling by imaging is that the photometric properties of the object are homogeneous. This homogeneousness requirement is often violated in microscopy imaging. Classical methods are usually of high computational cost and fail to give a stable solution. This paper presents a low computational complexity and robust method for three-dimensional (3-D) biological object detection and labeling. The developed approach is based on a statistical, nonparametric framework. Image is first divided into regular nonoverlapped regions and each region is evaluated according to a general photometric variability model. The regions not consistent with this model are considered as aberration in the data and excluded from the analysis procedure. Simultaneously, the interior parts of the object are detected, they correspond to regions where the supposed model is valid. In the second stage, the valid regions from a same object are merged together depending on a set of hypotheses. These hypotheses are generated by taking into account photometric and geometric properties of objects of interest and the merging is achieved according to an iterative algorithm. The approach has been applied in investigations of spatial distribution of nuclei within colonic glands of rats observed with the help of confocal fluorescence microscopy.

Optimal Level Curves and Global Minimizers of Cost Functionals in Image Segmentation

We propose a variational framework for determining global minimizers of rough energy functionals used in image segmentation. Segmentation is achieved by minimizing an energy model, which is comprised of two parts: the first part is the interaction between the observed data and the model, the second is a regularity term. The optimal boundaries are the curves that globally minimize the energy functional. Our motivation comes from the observation that energy functionals are traditionally complex, for which it is usually difficult to precise global minimizers corresponding to “best” segmentations. Therefore, we focus on basic energy models, which global minimizers can be characterized. None of the proposed segmentation models captures all the important scene variables but may be useful to get an insight into objects, surfaces or parts of objects in the scene. In this paper, we prove that the set of curves that minimizes the cost functionals is a subset of level lines, i.e. the boundaries of level sets of the image. For the completeness of the paper, we present a fast algorithm for computing partitions with connected components. It leads to a sound initialization-free algorithm without any hidden parameter to be tuned. We illustrate the performance of our algorithm with several examples on both 2D biomedical and aerial images, and synthetic images.

Isophotes Selection and Reaction-Diffusion Model for Object Boundaries Estimation

This paper investigates generic region-based segmentation schemes using area-minimization constraint and background modeling, and develops a computationally efficient framework based on level lines selection coupled with biased anisotropic diffusion. A common approach to image segmentation is to construct a cost function whose minima yield the segmented image. This is generally achieved by competition of two terms in the cost function, one that punishes deviations from the original image and another that acts as a regularization term. We propose a variational framework for characterizing global minimizers of a particular segmentation energy that can generates irregular object boundaries in image segmentation. Our motivation comes from the observation that energy functionals are traditionally complex, for which it is usually difficult to precise global minimizers corresponding to “best” segmentations. In this paper, we prove that the set of curves that minimizes the basic energy model under concern is a subset of level lines or isophotes, i.e. the boundaries of image level sets. The connections of our approach with region-growing techniques, snakes and geodesic active contours are also discussed. Moreover, it is absolutely necessary to regularize isophotes delimiting object boundaries and to determine piecewise smooth or constant approximations of the image data inside the objects boundaries for vizualization and pattern recognition purposes. Thus, we have constructed a reaction-diffusion process based on the Perona-Malik anisotropic diffusion equation. In particular, a reaction term has been added to force the solution to remain close to the data inside object boundaries and to be constant in non-informative regions, that is the background region. In the overall approach, diffusion requires the design of the background and foreground regions obtained by segmentation, and segmentation of the adaptively smoothed image is performed after each iteration of the diffusion process. From an application point of view, the sound initialization-free algorithm is shown to perform well in a variety of imaging contexts with variable texture, noise and lighting conditions, including optical imaging, medical imaging and meteorological imaging. Depending on the context, it yields either a reliable segmentation or a good pre-segmentation that can be used as initialization for more sophisticated, application-dependent segmentation models.

PARIS: a proteomic analysis and resources indexation system

UNLABELLED We developed a system for managing data from two-dimensional electrophoresis-based proteomic experiments. Named PARIS, the system stores gel image and information about experiments and analysis procedures, allows the user to search and navigate in genomic and proteomic data, supports visual verification and validation of the analysis results, and provides tools for cross multi-experiment and multi-experimenter data validation and exploration. AVAILABILITY The software is freely available from http://www.inra.fr/bia/J/imaste/Projets/PARIS/index.html

Analysis of one-dimensional electrophoregrams

One-dimensional electrophoresis is widely used for the estimation of molecular weight, genotype determination, identification of varieties and DNA sequencing. Many tools have been developed in numerous laboratories in order to perform semi-automatic and sometimes automatic analysis of gels. A one-dimensional electrophoregram consists of lanes and bands; pertinent information is essentially one-dimensional and, for each lane, entirely contained in an optical density profile. Detection of lanes and bands, quantitative analysis and fragment size or molecular weight calculation are provided by some software packages. Here we present our approach to one-dimensional gel analysis using digitized images. We concentrate on the correction of global distortion that may result from inhomogeneous electric field through the gel and on the interpretation of gels in the specific case of genetic studies of families. The package contains most of the usual facilities found in other special-purpose software for one-dimensional gel analysis but particular attention is given here to distortions and interpretation.