Expertise

La plateforme de génomique fonctionnelle de Nice Sophia Antipolis existe depuis 1999. Initialement orientée vers la conception, la fabrication et l'analyse de puces à ADN, elle a contribué à ouvrir cette nouvelle technologie à une large communauté, mettant à cette occasion en place un système d'information performant (Mediante), capable de gérer de grandes masses de données, et fonctionnant en production depuis plus de 10 ans.

Tout en fournissant encore aujourd'hui un service d'analyse de puces à ADN s'appuyant sur la technologie développée par Agilent, son activité s'est principalement réorientée vers des services de séquencage à haut-débit (Illumina NextSeq500), offrant dans ce contexte de nombreux types d'analyses des acides nucléiques, et une capacité pour analyser de grandes collections d'échantillons, y compris au niveau de la cellule unique. L'activité de routine concerne des applications comme le RNA-seq, le smallRNA-seq, le CHiP-seq, le CLIP-seq, le reséquencage, mais des projets spécifiques peuvent aussi etre mis en place dans des domaines moins standards, comme le séquencage de novo de génomes, ou certains protocoles particuliers : riboSeq, capSeq,... La plateforme se compose de 4 ingénieurs wet lab et de 4 bio-informaticiens.

Equipements

1. Pré-séquencage : Nanodrop, Bioanalyzer, Qubit, CovarisS2, Ion Chef, NeoPrep, Blue pippin
2. Analyse Single Cell : 10x Genomics Chromium, Fluidigm C1, Fluidigm Biomark
3. Séquencage : NextSeq500 Illumina, MinION et PromethION Oxford Nanopore Technology, Chromium 10X Genomics
4. Puces à ADN : High-Resolution Microarray Scanner Agilent, Station Affymetrix

Les résultats sont stockés automatiquement sur le portail d'informations de la plateforme Mediante. Cela concerne notamment les fichiers .BAM d'alignement, les fichiers .BW de couverture et l'ensemble des fichiers de l'analyse secondaire et des analyses statistiques conduites en partenariat avec le collaborateur. Sur demande l'ensemble des données brutes sont également mises à disposition et une aide est fournit pour la soumission des données vers la base de données publiques GEO (Gene Expression Omnibus).

Related publications

Single-cell CRISPR-based transcriptome screens are potent genetic tools for concomitantly assessing the expression profiles of cells targeted by a set of guides RNA (gRNA), and inferring target gene functions from the observed perturbations. However, due to various limitations, this approach lacks sensitivity in detecting weak perturbations and is essentially reliable when studying master regulators such as transcription factors. To overcome the challenge of detecting subtle gRNA induced transcriptomic perturbations and classifying the most responsive cells, we developed a new supervised autoencoder neural network method. Our Sparse supervised autoencoder (SSAE) neural network provides selection of both relevant features (genes) and actual perturbed cells. We applied this method on an in-house single-cell CRISPR-interference-based (CRISPRi) transcriptome screening (CROP-Seq) focusing on a subset of long non-coding RNAs (lncRNAs) regulated by hypoxia, a condition that promote tumor aggressiveness and drug resistance, in the context of lung adenocarcinoma (LUAD). The CROP-seq library of validated gRNA against a subset of lncRNAs and, as positive controls, HIF1A and HIF2A, the 2 main transcription factors of the hypoxic response, was transduced in A549 LUAD cells cultured in normoxia or exposed to hypoxic conditions during 3, 6 or 24 h. We first validated the SSAE approach on HIF1A and HIF2 by confirming the specific effect of their knock-down during the temporal switch of the hypoxic response. Next, the SSAE method was able to detect stable short hypoxia-dependent transcriptomic signatures induced by the knock-down of some lncRNAs candidates, outperforming previously published machine learning approaches. This proof of concept demonstrates the relevance of the SSAE approach for deciphering weak perturbations in single-cell transcriptomic data readout as part of CRISPR-based screening.

The study of the airway epithelium in vitro is routinely performed using air-liquid culture (ALI) models from nasal or bronchial basal cells. These 3D experimental models allow to follow the regeneration steps of fully differentiated mucociliary epithelium and to study gene function by performing gene invalidation. Recent progress made with CRISPR-based techniques has overcome the experimental difficulty of this approach, by a direct transfection of ribonucleoprotein complexes combining a mix of synthetic small guide RNAs (sgRNAs) and recombinant Cas9. The approach shows more than 95% efficiency and does not require any selection step. A limitation of this approach is that it generates cell populations that contain heterogeneous deletions, which makes the evaluation of invalidation efficiency difficult. We have successfully used Flongle sequencing (Nanopore) to quantify the number of distinct deletions. We describe the use of CRISPR-Cas9 RNP in combination with single-cell RNA sequencing to functionally characterize the impact of gene invalidation in ALI cultures. The complex ecosystem of the airway epithelium, composed of many cell types, makes single-cell approaches particularly relevant to study cell type, or cell state-specific events. This protocol describes the invalidation of FOXJ1 in ALI cultures through the following steps: (1) Establishment of basal cell cultures from nasal turbinates, (2) CRISPR-Cas9 RNP invalidation of FOXJ1, (3) Quantification of FOXJ1 invalidation efficiency by Nanopore sequencing, (4) Dissociation of ALI cultures and single-cell RNAseq, (5) Analysis of single-cell RNAseq data from FOXJ1-invalidated cells.We confirm here that FOXJ1 invalidation impairs the final differentiation step of multiciliated cells and provides a framework to explore other gene functions.

Cholesterol efflux pathways could be exploited in tumor biology to unravel cancer vulnerabilities. A mouse model of lung-tumor-bearing KRASG12D mutation with specific disruption of cholesterol efflux pathways in epithelial progenitor cells promoted tumor growth. Defective cholesterol efflux in epithelial progenitor cells governed their transcriptional landscape to support their expansion and create a pro-tolerogenic tumor microenvironment (TME). Overexpression of the apolipoprotein A-I, to raise HDL levels, protected these mice from tumor development and dire pathologic consequences. Mechanistically, HDL blunted a positive feedback loop between growth factor signaling pathways and cholesterol efflux pathways that cancer cells hijack to expand. Cholesterol removal therapy with cyclodextrin reduced tumor burden in progressing tumor by suppressing the proliferation and expansion of epithelial progenitor cells of tumor origin. Local and systemic perturbations of cholesterol efflux pathways were confirmed in human lung adenocarcinoma (LUAD). Our results position cholesterol removal therapy as a putative metabolic target in lung cancer progenitor cells.

The MIR449 genomic locus encompasses several regulators of multiciliated cell (MCC) formation (multiciliogenesis). The miR-449 homologs miR-34b/c represent additional regulators of multiciliogenesis that are transcribed from another locus. Here, we characterized the expression of BTG4, LAYN, and HOATZ, located in the MIR34B/C locus using single-cell RNA-seq and super-resolution microscopy from human, mouse, or pig multiciliogenesis models. BTG4, LAYN, and HOATZ transcripts were expressed in both precursors and mature MCCs. The Layilin/LAYN protein was absent from primary cilia, but it was expressed in apical membrane regions or throughout motile cilia. LAYN silencing altered apical actin cap formation and multiciliogenesis. HOATZ protein was detected in primary cilia or throughout motile cilia. Altogether, our data suggest that the MIR34B/C locus may gather potential actors of multiciliogenesis.

In situ capturing technologies add tissue context to gene expression data, with the potential of providing a greater understanding of complex biological systems. However, splicing variants and full-length sequence heterogeneity cannot be characterized at spatial resolution with current transcriptome profiling methods. To that end, we introduce spatial isoform transcriptomics (SiT), an explorative method for characterizing spatial isoform variation and sequence heterogeneity using long-read sequencing. We show in mouse brain how SiT can be used to profile isoform expression and sequence heterogeneity in different areas of the tissue. SiT reveals regional isoform switching of Plp1 gene between different layers of the olfactory bulb, and the use of external single-cell data allows the nomination of cell types expressing each isoform. Furthermore, SiT identifies differential isoform usage for several major genes implicated in brain function (Snap25, Bin1, Gnas) that are independently validated by in situ sequencing. SiT also provides for the first time an in-depth A-to-I RNA editing map of the adult mouse brain. Data exploration can be performed through an online resource (https://www.isomics.eu), where isoform expression and RNA editing can be visualized in a spatial context.

Repair-supportive mesenchymal cells (RSMCs) have been recently reported in the context of naphthalene (NA)-induced airway injury and regeneration. These cells transiently express smooth muscle actin (Acta2) and are enriched with platelet-derived growth factor receptor alpha (Pdgfra) and fibroblast growth factor 10 (Fgf10) expression. Genetic deletion of Ctnnb1 (gene coding for beta catenin) or Fgf10 in these cells using the Acta2-Cre-ERT2 driver line after injury (defined as NA-Tam condition; Tam refers to tamoxifen) led to impaired repair of the airway epithelium. In this study, we demonstrate that RSMCs are mostly captured using the Acta2-Cre-ERT2 driver when labeling occurs after (NA-Tam condition) rather than before injury (Tam-NA condition), and that their expansion occurs mostly between days 3 and 7 following NA treatment. Previous studies have shown that lineage-traced peribronchial GLI1+ cells are transiently amplified after NA injury. Here, we report that Gli1 expression is enriched in RSMCs. Using lineage tracing with Gli1Cre-ERT2 mice combined with genetic inactivation of Fgf10, we show that GLI1+ cells with Fgf10 deletion fail to amplify around the injured airways, thus resulting in impaired airway epithelial repair. Interestingly, Fgf10 expression is not upregulated in GLI1+ cells following NA treatment, suggesting that epithelial repair is mostly due to the increased number of Fgf10-expressing GLI1+ cells. Co-culture of SCGB1A1+ cells with GLI1+ cells isolated from non-injured or injured lungs showed that GLI1+ cells from these two conditions are similarly capable of supporting bronchiolar organoid (or bronchiolosphere) formation. Single-cell RNA sequencing on sorted lineage-labeled cells showed that the RSMC signature resembles that of alveolar fibroblasts. Altogether, our study provides strong evidence for the involvement of mesenchymal progenitors in airway epithelial regeneration and highlights the critical role played by Fgf10-expressing GLI1+ cells in this context.

Cell response variability is a starting point in cancer drug resistance that has been difficult to analyze because the tolerant cell states are short lived. Here, we present fate-seq, an approach to isolate single cells in their transient states of drug sensitivity or tolerance before profiling. The drug response is predicted in live cells, which are laser-captured by microdissection before any drug-induced change can alter their states. This framework enables the identification of the cell-state signatures causing differential cell decisions upon treatment. For complete details on the use and execution of this protocol, please refer to Meyer et al. (2020).

Despite the development of new therapeutic strategies, cancer remains one of the leading causes of mortality worldwide. One of the current major challenges is the resistance of cancers to chemotherapy treatments inducing metastases and relapse of the tumor. The Hedgehog receptor Patched (Ptch1) is overexpressed in many types of cancers. We showed that Ptch1 contributes to the efflux of doxorubicin and plays an important role in the resistance to chemotherapy in adrenocortical carcinoma (ACC), a rare cancer which presents strong resistance to the standard of care chemotherapy treatment. In the present study, we isolated and characterized a subpopulation of the ACC cell line H295R in which Ptch1 is overexpressed and more present at the cell surface. This cell subpopulation is more resistant to doxorubicin, grows as spheroids, and has a greater capability of clonogenicity, migration, and invasion than the parental cells. Xenograft experiments performed in mice and in ovo showed that this cell subpopulation is more tumorigenic and metastatic than the parental cells. These results suggest that this cell subpopulation has cancer stem-like or persistent cell properties which were strengthened by RNA-seq. If present in tumors from ACC patients, these cells could be responsible for therapy resistance, relapse, and metastases.

Monocytes are part of the mononuclear phagocytic system. Monocytes play a central role during inflammatory conditions and a better understanding of their dynamics might open therapeutic opportunities. In the present study, we focused on the characterization and impact of monocytes on brown adipose tissue (BAT) functions during tissue remodeling. Single-cell RNA sequencing analysis of BAT immune cells uncovered a large diversity in monocyte and macrophage populations. Fate-mapping experiments demonstrated that the BAT macrophage pool requires constant replenishment from monocytes. Using a genetic model of BAT expansion, we found that brown fat monocyte numbers were selectively increased in this scenario. This observation was confirmed using a CCR2-binding radiotracer and positron emission tomography. Importantly, in line with their tissue recruitment, blood monocyte counts were decreased while bone marrow hematopoiesis was not affected. Monocyte depletion prevented brown adipose tissue expansion and altered its architecture. Podoplanin engagement is strictly required for BAT expansion. Together, these data redefine the diversity of immune cells in the BAT and emphasize the role of monocyte recruitment for tissue remodeling.

Intratumor heterogeneity has been recognized in numerous cancers as a major source of metastatic dissemination. In uveal melanomas, the existence and identity of specific subpopulations, their biological function and their contribution to metastasis remain unknown. Here, in multiscale analyses using single-cell RNA sequencing of six different primary uveal melanomas, we uncover an intratumoral heterogeneity at the genomic and transcriptomic level. We identify distinct transcriptional cell states and diverse tumor-associated populations in a subset of the samples. We also decipher a gene regulatory network underlying an invasive and poor prognosis state driven in part by the transcription factor HES6. HES6 heterogenous expression has been validated by RNAscope assays within primary human uveal melanomas, which further unveils the existence of these cells conveying a dismal prognosis in tumors diagnosed with a favorable outcome using bulk analyses. Depletion of HES6 impairs proliferation, migration and metastatic dissemination in vitro and in vivo using the chick chorioallantoic membrane assay, demonstrating the essential role of HES6 in uveal melanomas. Thus, single-cell analysis offers an unprecedented view of primary uveal melanoma heterogeneity, identifies bona fide biomarkers for metastatic cells in the primary tumor, and reveals targetable modules driving growth and metastasis formation. Significantly, our findings demonstrate that HES6 is a valid target to stop uveal melanoma progression.

To gain better insight into the dynamic interaction between cells and their environment, we developed the agonist-induced functional analysis and cell sorting (aiFACS) technique, which allows the simultaneous recording and sorting of cells in real-time according to their immediate and individual response to a stimulus. By modulating the aiFACS selection parameters, testing different developmental times, using various stimuli, and multiplying the analysis of readouts, it is possible to analyze cell populations of any normal or pathological tissue. The association of aiFACS with single-cell transcriptomics allows the construction of functional tissue cartography based on specific pharmacological responses of cells. As a proof of concept, we used aiFACS on the dissociated mouse brain, a highly heterogeneous tissue, enriching it in interneurons by stimulation with KCl or with AMPA, an agonist of the glutamate receptors, followed by sorting based on calcium levels. After AMPA stimulus, single-cell transcriptomics of these aiFACS-selected interneurons resulted in a nine-cluster classification. Furthermore, we used aiFACS on interneurons derived from the brain of the Fmr1-KO mouse, a rodent model of fragile X syndrome. We showed that these interneurons manifest a generalized defective response to AMPA compared with wild-type cells, affecting all the analyzed cell clusters at one specific postnatal developmental time.

Non-genetic heterogeneity observed in clonal cell populations is an immediate cause of drug resistance that remains challenging to profile because of its transient nature. Here, we coupled three single-cell technologies to link the predicted drug response of a cell to its own genome-wide transcriptomic profile. As a proof of principle, we analyzed the response to tumor-necrosis-factor-related apoptosis-inducing ligand (TRAIL) in HeLa cells to demonstrate that cell dynamics can discriminate the transient transcriptional states at the origin of cell decisions such as sensitivity and resistance. Our same-cell approach, named fate-seq, can reveal the molecular factors regulating the efficacy of a drug in clonal cells, providing therapeutic targets of non-genetic drug resistance otherwise confounded in gene expression noise. A record of this paper's transparent peer review process is included in the Supplemental Information.

Mammary carcinoma, including triple-negative breast carcinomas (TNBC) are tumor-types for which human and canine pathologies are closely related at the molecular level. The efficacy of an oncolytic vaccinia virus (VV) was compared in low-passage primary carcinoma cells from TNBC versus non-TNBC. Non-TNBC cells were 28 fold more sensitive to VV than TNBC cells in which VV replication is impaired. Single-cell RNA-seq performed on two different TNBC cell samples, infected or not with VV, highlighted three distinct populations: naïve cells, bystander cells, defined as cells exposed to the virus but not infected and infected cells. The transcriptomes of these three populations showed striking variations in the modulation of pathways regulated by cytokines and growth factors. We hypothesized that the pool of genes expressed in the bystander populations was enriched in antiviral genes. Bioinformatic analysis suggested that the reduced activity of the virus was associated with a higher mesenchymal status of the cells. In addition, we demonstrated experimentally that high expression of one gene, DDIT4, is detrimental to VV production. Considering that DDIT4 is associated with a poor prognosis in various cancers including TNBC, our data highlight DDIT4 as a candidate resistance marker for oncolytic poxvirus therapy. This information could be used to design new generations of oncolytic poxviruses. Beyond the field of gene therapy, this study demonstrates that single-cell transcriptomics can be used to identify cellular factors influencing viral replication.

CD1d-restricted invariant Natural Killer T (iNKT) cells represent a unique class of T lymphocytes endowed with potent regulatory and effector immune functions. Although these functions are acquired during thymic ontogeny, the sequence of events that gives rise to discrete effector subsets remains unclear. Using an unbiased single-cell transcriptomic analysis combined with functional assays, we reveal an unappreciated diversity among thymic iNKT cells, especially among iNKT1 cells. Mathematical modeling and biological methods unravel a developmental map whereby iNKT2 cells constitute a transient branching point toward the generation of iNKT1 and iNKT17 cells, which reconciles the two previously proposed models. In addition, we identify the transcription co-factor Four-and-a-half LIM domains protein 2 (FHL2) as a critical cell-intrinsic regulator of iNKT1 specification. Thus, these data illustrate the changing transcriptional network that guides iNKT cell effector fate.

Droplet-based high throughput single cell sequencing techniques tremendously advanced our insight into cell-to-cell heterogeneity. However, those approaches only allow analysis of one extremity of the transcript after short read sequencing. In consequence, information on splicing and sequence heterogeneity is lost. To overcome this limitation, several approaches that use long-read sequencing were introduced recently. Yet, those techniques are limited by low sequencing depth and/or lacking or inaccurate assignment of unique molecular identifiers (UMIs), which are critical for elimination of PCR bias and artifacts. We introduce ScNaUmi-seq, an approach that combines the high throughput of Oxford Nanopore sequencing with an accurate cell barcode and UMI assignment strategy. UMI guided error correction allows to generate high accuracy full length sequence information with the 10x Genomics single cell isolation system at high sequencing depths. We analyzed transcript isoform diversity in embryonic mouse brain and show that ScNaUmi-seq allows defining splicing and SNVs (RNA editing) at a single cell level.

Rationale: The respiratory tract constitutes an elaborated line of defense that is based on a unique cellular ecosystem. Single-cell profiling methods enable the investigation of cell population distributions and transcriptional changes along the airways. Methods: We have explored the cellular heterogeneity of the human airway epithelium in 10 healthy living volunteers by single-cell RNA profiling. 77,969 cells were collected at 35 distinct locations, from the nose to the 12th division of the airway tree. Results: The resulting atlas is composed of a high percentage of epithelial cells (89.1%), but also immune (6.2%) and stromal (4.7%) cells with distinct cellular proportions in different regions of the airways. It reveals differential gene expression between identical cell types (suprabasal, secretory, and multiciliated cells) from the nose (MUC4, PI3, SIX3) and tracheobronchial (SCGB1A1, TFF3) airways. By contrast, cell-type specific gene expression is stable across all tracheobronchial samples. Our atlas improves the description of ionocytes, pulmonary neuro-endocrine (PNEC) and brush cells, and identifies a related population of NREP-positive cells. We also report the association of KRT13 with dividing cells that are reminiscent of previously described mouse "hillock" cells, and with squamous cells expressing SCEL, SPRR1A/B. Conclusions: Robust characterization of a single-cell cohort in healthy airways establishes a valuable resource for future investigations. The precise description of the continuum existing from the nasal epithelium to successive divisions of the airways and the stable gene expression profile of these regions better defines conditions under which relevant tracheobronchial proxies of human respiratory diseases can be developed.

The upper airway epithelium, mainly composed of multiciliated, goblet, club and basal cells, ensures proper mucociliary function and can regenerate upon aggressions. In chronic airway diseases, defective repair leads to tissue remodeling. Delineating key drivers of differentiation dynamics can help understand how normal or pathological regeneration occurs.Using single-cell transcriptomics and lineage inference, we have unraveled trajectories from basal to luminal cells, providing novel markers for specific populations. We report that: (1) a precursor subgroup of multiciliated cells that we have entitled deuterosomal cells, is defined by specific markers, such as DEUP1, FOXN4, YPEL1, HES6 and CDC20B; (2) goblet cells can be precursors of multiciliated cells, thus explaining the presence of hybrid cells that co-express markers of goblet and multiciliated cells; (3) a repertoire of molecules involved in the regeneration process, such as keratins or components of the Notch, Wnt or BMP/TGFβ pathways can be established. Confirmations of our results on fresh human and pig airway samples, and on mouse tracheal cells, extend and confirm our conclusions regarding the molecular and cellular choreography at work during mucociliary epithelial differentiation.