Fabien Pierrat

Pancreatic ductal adenocarcinoma (PDAC) is expected to be the second cause of cancer death by 2022. For nearly 80% of patients, diagnosis occurs at an advanced, nonsurgical stage, making such patients incurable. Gemcitabine is still an important component in PDAC treatment and is most often used as a backbone to test new targeted therapies and there is, to date, no routine biomarker to predict its efficacy. Samples from a phase III randomized trial were used to develop through a large approach based on blood-based liquid biopsy, transcriptome profiling, and machine learning, a nine gene predictive signature for gemcitabine sensitivity. Patients with a positive test (41.6%) had a significantly longer progression free survival (PFS) (3.8 months vs. 1.9 months p = 0.03) and a longer overall survival (OS) (14.5 months vs. 5.1, p < 0.0001). In multivariate analyses, this signature was independently associated with PFS (HR = 0.5 (0.28–0.9) p = 0.025) and OS (HR = 0.39 (0.21–0.7) p = 0.002).

Biofloc technology (BFT), a rearing method with little or no water exchange, is gaining popularity in aquaculture. In the water column, such systems develop conglomerates of microbes, algae and protozoa, together with detritus and dead organic particles. The intensive microbial community presents in these systems can be used as a pond water quality treatment system, and the microbial protein can serve as a feed additive. The current problem with BFT is the difficulty of controlling its bacterial community composition for both optimal water quality and optimal shrimp health. The main objective of the present study was to investigate microbial diversity of samples obtained from different culture environments (Biofloc technology and clear seawater) as well as from the intestines of shrimp reared in both environments through high-throughput sequencing technology. Analyses of the bacterial community identified in water from BFT and “clear seawater” (CW) systems (control) containing the shrimp Litopenaeus stylirostris revealed large differences in the frequency distribution of operational taxonomic units (OTUs). Four out of the five most dominant bacterial communities were different in both culture methods. Bacteria found in great abundance in BFT have two principal characteristics: the need for an organic substrate or nitrogen sources to grow and the capacity to attach to surfaces and co-aggregate. A correlation was found between bacteria groups and physicochemical and biological parameters measured in rearing tanks. Moreover, rearing-water bacterial communities influenced the microbiota of shrimp. Indeed, the biofloc environment modified the shrimp intestine microbiota, as the low level (27 %) of similarity between intestinal bacterial communities from the two treatments. This study provides the first information describing the complex biofloc microbial community, which can help to understand the environment-microbiota-host relationship in this rearing system.

Trisomy 21 (T21), or Down syndrome (DS), is the most frequent and recognizable cause of intellectual disabilities. The level of disability, as evaluated by the intelligence quotient (IQ) test, varies considerably between patients independent of other factors. To determine the genetic or molecular basis of this difference, a high throughput transcriptomic analysis was performed on twenty T21 patients with high and low IQ, and 10 healthy controls using Digital Gene Expression. More than 90 millions of tags were sequenced in the three libraries. A total of 80 genes of potential interest were selected for the qPCR experiment validation, and three housekeeping genes were used for normalizing purposes. HLA DQA1 and HLA DRB1 were significantly downregulated among the patients with a low IQ, the values found in the healthy controls being intermediate between those noted in the IQ+ and IQ- T21 patients. Interestingly, the intergenic region between these genes contains a binding sequence for the CCCTC-binding factor, or CTCF, and cohesin (a multisubunit complex), both of which are essential for expression of HLA DQA1 and HLA DRB1 and numerous other genes. Our results might lead to the discovery of genes, or genetic markers, that are directly involved in several phenotypes of DS and, eventually, to the identification of potential targets for therapeutic interventions.

Since the development of methods for homologous gene recombination, mouse models have played a central role in research in renal pathophysiology. However, many published and unpublished results show that mice with genetic changes mimicking human pathogenic mutations do not display the human phenotype. These functional differences may stem from differences in gene expression between mouse and human kidneys. However, large scale comparison of gene expression networks revealed conservation of gene expression among a large panel of human and mouse tissues including kidneys. Because renal functions result from the spatial integration of elementary processes originating in the glomerulus and the successive segments constituting the nephron, we hypothesized that differences in gene expression profiles along the human and mouse nephron might account for different behaviors. Analysis of SAGE libraries generated from the glomerulus and seven anatomically defined nephron segments from human and mouse kidneys allowed us to identify 4644 pairs of gene orthologs expressed in either one or both species. Quantitative analysis shows that many transcripts are present at different levels in the two species. It also shows poor conservation of gene expression profiles, with less than 10% of the 4644 gene orthologs displaying a higher conservation of expression profiles than the neutral expectation (p<0.05). Accordingly, hierarchical clustering reveals a higher degree of conservation of gene expression patterns between functionally unrelated kidney structures within a given species than between cognate structures from the two species. Similar findings were obtained for sub-groups of genes with either kidney-specific or housekeeping functions. Conservation of gene expression at the scale of the whole organ and divergence at the level of its constituting sub-structures likely account for the fact that although kidneys assume the same global function in the two species, many mouse “models” of human pathologies do not display the expected phenotype.

To gain molecular insight into kidney function, we performed a high-resolution quantitative analysis of gene expression in glomeruli and nine different nephron segments dissected from mouse kidney using Serial Analysis of Gene Expression (SAGE). We also developed dedicated bioinformatics tools and databases to annotate mRNA tags as transcripts. Over 800,000 mRNA SAGE tags were sequenced corresponding to >20,000 different mRNA tags present at least twice in at least one library. Hierarchical clustering analysis of tags demonstrated similarities between the three anatomical subsegments of the proximal tubule, between the cortical and medullary segments of the thick ascending limb of Henle's loop, and between the three segments constituting the aldosterone-sensitive distal nephron segments, whereas the glomerulus and distal convoluted tubule clusterized independently. We also identified highly specific mRNA markers of each subgroup of nephron segments and of most nephron segments. Tag annotation also identified numbers of putative antisense mRNAs. This database constitutes a reference resource in which the quantitative expression of a given gene can be compared with that of other genes in the same nephron segment, or between different segments of the nephron. To illustrate possible applications of this database, we performed a deeper analysis of the glomerulus transcriptome that unexpectedly revealed expression of several ion and water carriers; within the glomerulus, they were found to be preferentially expressed in the parietal sheet. It also revealed the major role of the zinc finger transcription factor Wt1 in the specificity of gene expression in the glomerulus. Finally, functional annotation of glomerulus-specific transcripts suggested a high proliferation activity of glomerular cells. Immunolabeling for PCNA confirmed a high percentage of proliferating cells in the glomerulus parietal sheet.

Background: The shell of the pearl-producing bivalvePinctada margaritiferais composed of an organic cell-free matrix that plays a key role in the dynamic process of biologically-controlled biomineralization. In order to increase genomic resources and identify shell matrix proteins implicated in biomineralization inP. margaritifera, high-throughput Expressed Sequence Tag (EST) pyrosequencing was undertaken on the calcifying mantle, combined with a proteomic analysis of the shell.Results: We report the functional analysis of 276 738 sequences, leading to the constitution of an unprecedented catalog of 82P. margaritiferabiomineralization-related mantle protein sequences. Components of the current "chitin-silk fibroin gel-acidic macromolecule" model of biomineralization processes were found, in particular a homolog of a biomineralization protein (Pif-177) recently discovered inP. fucata. Among these sequences, we could show the localization of two other biomineralization protein transcripts,pmarg-aspeinandpmarg-pearlin, in two distinct areas of the outer mantle epithelium, suggesting their implication in calcite and aragonite formation. Finally, by combining the EST approach with a proteomic mass spectrometry analysis of proteins isolated from theP. margaritiferashell organic matrix, we demonstrated the presence of 30 sequences containing almost all of the shell proteins that have been previously described from shell matrix protein analyses of thePinctadagenus. The integration of these two methods allowed the global composition of biomineralizing tissue and calcified structures to be examined in tandem for the first time.Conclusions: This EST study made on the calcifying tissue ofP. margaritiferais the first description of pyrosequencing on a pearl-producing bivalve species. Our results provide direct evidence that our EST data set covers most of the diversity of the matrix protein ofP. margaritiferashell, but also that the mantle transcripts encode proteins present inP. margaritiferashell, hence demonstrating their implication in shell formation. Combining transcriptomic and proteomic approaches is therefore a powerful way to identify proteins involved in biomineralization. Data generated in this study supply the most comprehensive list of biomineralization-related sequences presently available among protostomian species, and represent a major breakthrough in the field of molluskan biomineralization.

Analysis of several million expressed gene signatures (tags) revealed an increasing number of different sequences, largely exceeding that of annotated genes in mammalian genomes. Serial analysis of gene expression (SAGE) can reveal new Poly(A) RNAs transcribed from previously unrecognized chromosomal regions. However, conventional SAGE tags are too short to identify unambiguously unique sites in large genomes. Here, we design a novel strategy with tags anchored on two different restrictions sites of cDNAs. New transcripts are then tentatively defined by the two SAGE tags in tandem and by the spanning sequence read on the genome between these tagged sites. Having developed a new algorithm to locate these tag-delimited genomic sequences (TDGS), we first validated its capacity to recognize known genes and its ability to reveal new transcripts with two SAGE libraries built in parallel from a single RNA sample. Our algorithm proves fast enough to experiment this strategy at a large scale. We then collected and processed the complete sets of human SAGE tags to predict yet unknown transcripts. A cross-validation with tiling arrays data shows that 47% of these TDGS overlap transcriptional active regions. Our method provides a new and complementary approach for complex transcriptome annotation.

As a growing number of complementary transcripts, susceptible to exert various regulatory functions, are being found in eukaryotes, high throughput analytical methods are needed to investigate their expression in multiple biological samples. Serial Analysis of Gene Expression (SAGE), based on the enumeration of directionally reliable short cDNA sequences (tags), is capable of revealing antisense transcripts. We initially detected them by observing tags that mapped on to the reverse complement of known mRNAs. The presence of such tags in individual SAGE libraries suggested that SAGE datasets contain latent information on antisense transcripts. We raised a collection of virtual tags for mining these data. Tag pairs were assembled by searching for complementarities between 24-nt long sequences centered on the potential SAGE-anchoring sites of well-annotated human expressed sequences. An analysis of their presence in a large collection of published SAGE libraries revealed transcripts expressed at high levels from both strands of two adjacent, oppositely oriented, transcription units. In other cases, the respective transcripts of such cis-oriented genes displayed a mutually exclusive expression pattern or were co-expressed in a small number of libraries. Other tag pairs revealed overlapping transcripts of trans-encoded unique genes. Finally, we isolated a group of tags shared by multiple transcripts. Most of them mapped on to retroelements, essentially represented in humans by Alu sequences inserted in opposite orientations in the 3′UTR of otherwise different mRNAs. Registering these tags in separate files makes possible computational searches focused on unique sense–antisense pairs. The method developed in the present work shows that SAGE datasets constitute a major resource of rapidly investigating with high sensitivity the expression of antisense transcripts, so that a single tag may be detected in one library when screening a large number of biological samples.