Christian Conrad

Automatic identification and clustering of chromosome phenotypes in a genome wide RNAi screen by time-lapse imaging

High-throughput time-lapse microscopy is an excellent way of studying gene function by collecting time-resolved image data of the cellular responses to gene perturbations. With the increase in both data amount and complexity, computational methods capable of dealing with large image data sets are required. While image processing methods have been successfully applied to endpoint assays in the past, the analysis of complex time-resolved read-outs was so far still too immature to be applied on a large-scale. Here, we present a complete computational processing pipeline for such screens. By automatic image processing and machine learning, a quantitative description of phenotypic dynamics is obtained from the raw bitmaps. In order to visualize the resulting phenotypes in their temporal context, we introduce Event Order Maps allowing a concise representation of the major tendencies of causes and consequences of phenotypic classes. In order to cluster the phenotypic kinetics, we propose a novel technique based on trajectory representation of multidimensional time series. We demonstrate the use of these methods applying them on a genome wide RNAi screen by time-lapse microscopy.

High-Content siRNA Screen Reveals Global ENaC Regulators and Potential Cystic Fibrosis Therapy Targets

Dysfunction of ENaC, the epithelial sodium channel that regulates salt and water reabsorption in epithelia, causes several human diseases, including cystic fibrosis (CF). To develop a global understanding of molecular regulators of ENaC traffic/function and to identify of candidate CF drug targets, we performed a large-scale screen combining high-content live-cell microscopy and siRNAs in human airway epithelial cells. Screening over 6,000 genes identified over 1,500 candidates, evenly divided between channel inhibitors and activators. Genes in the phosphatidylinositol pathway were enriched on the primary candidate list, and these, along with other ENaC activators, were examined further with secondary siRNA validation. Subsequent detailed investigation revealed ciliary neurotrophic factor receptor (CNTFR) as an ENaC modulator and showed that inhibition of (diacylglycerol kinase, iota) DGKι, a protein involved in PiP2 metabolism, downgrades ENaC activity, leading to normalization of both Na+ and fluid absorption in CF airways to non-CF levels in primary human lung cells from CF patients.

Automatic quantification of microtubule dynamics enables RNAi-screening of new mitotic spindle regulators.

The genetic integrity of every organism depends on the faithful partitioning of its genome between two daughter cells in mitosis. In all eukaryotes, chromosome segregation requires the assembly of the mitotic spindle, a bipolar array of dynamic microtubules. Perturbations in microtubule dynamics affect spindle assembly and maintenance and ultimately result in aberrant cell divisions. To identify new regulators of microtubule dynamics within the hundreds of mitotic hits, reported in RNAi screens performed in C. elegans, Drosophila and mammalian tissue culture cells [Sonnichsen et al., 2005; Goshima et al., 2007; Neumann et al., 2010], we established a fast and quantitative assay to measure microtubule dynamics in living cells. Here we present a fully automated workflow from RNAi transfection, via image acquisition and data processing, to the quantitative characterization of microtubule behaviour. Candidate genes are knocked down by solid‐phase reverse transfection with siRNA oligos in HeLa cells stably expressing EB3‐EGFP, a microtubule plus end marker. Mitotic cells are selected using an automatic classifier [Conrad et al., 2011] and imaged on a spinning disk confocal microscope at high temporal and spatial resolution. The time‐lapse movies are analysed using a multiple particle tracking software, developed in‐house, that automatically detects microtubule plus ends, tracks microtubule growth events over consecutive frames and calculates growth speeds, lengths and lifetimes of the tracked microtubules. The entire assay provides a powerful tool to analyse the effect of essential mitotic genes on microtubule dynamics in living cells and to dissect their contribution in spindle assembly and maintenance.

Convergent origination of a Drosophila-like dosage compensation mechanism in a reptile lineage

Sex chromosomes differentiated from different ancestral autosomes in various vertebrate lineages. Here, we trace the functional evolution of the XY Chromosomes of the green anole lizard (Anolis carolinensis), on the basis of extensive high-throughput genome, transcriptome and histone modification sequencing data and revisit dosage compensation evolution in representative mammals and birds with substantial new expression data. Our analyses show that Anolis sex chromosomes represent an ancient XY system that originated at least ≈160 million years ago in the ancestor of Iguania lizards, shortly after the separation from the snake lineage. The age of this system approximately coincides with the ages of the avian and two mammalian sex chromosomes systems. To compensate for the almost complete Y Chromosome degeneration, X-linked genes have become twofold up-regulated, restoring ancestral expression levels. The highly efficient dosage compensation mechanism of Anolis represents the only vertebrate case identified so far to fully support Ohnos original dosage compensation hypothesis. Further analyses reveal that X up-regulation occurs only in males and is mediated by a male-specific chromatin machinery that leads to global hyperacetylation of histone H4 at lysine 16 specifically on the X Chromosome. The green anole dosage compensation mechanism is highly reminiscent of that of the fruit fly, Drosophila melanogaster Altogether, our work unveils the convergent emergence of a Drosophila-like dosage compensation mechanism in an ancient reptilian sex chromosome system and highlights that the evolutionary pressures imposed by sex chromosome dosage reductions in different amniotes were resolved in fundamentally different ways.

Functional Genomics Assays to Study CFTR Traffic and ENaC Function

As several genomes have been sequenced, post-genomic approaches like transcriptomics and proteomics, identifying gene products differentially expressed in association with a given pathology, have held promise both of understanding the pathways associated with the respective disease and as a fast track to therapy. Notwithstanding, these approaches cannot distinguish genes and proteins with mere secondary pathological association from those primarily involved in the basic defect(s). New global strategies and tools identifying gene products responsible for the basic cellular defect(s) in CF pathophysiology currently being performed are presented here. These include high-content screens to determine proteins affecting function and trafficking of CFTR and ENaC.

pheno-seq - linking 3D phenotypes of clonal tumor spheroids to gene expression

3D-culture systems have advanced cancer modeling by reflecting physiological characteristics of in-vivo tissues, but our understanding of functional intratumor heterogeneity including visual phenotypes and underlying gene expression is still limited. Transcriptional heterogeneity can be dissected by single-cell RNA-sequencing, but these technologies suffer from low RNA-input and fail to directly correlate gene expression with contextual cellular phenotypes. Here we present ‘pheno-seq’ for integrated high-throughput imaging and transcriptomic profiling of clonal tumor spheroids derived from 3D models of breast and colorectal cancer. Specifically, we identify characteristic expression signatures that are associated with heterogeneous invasive and proliferative behavior including a rare cell subtype. Furthermore, we identify functionally relevant transcriptional regulators missed by single-cell RNA-seq, link visual phenotypes defined by heterogenous expression to inhibitor response and infer single-cell regulatory states by deconvolution. We anticipate that directly linking molecular features with patho-phenotypes of cancer cells will improve the understanding of intratumor heterogeneity and consequently prove to be useful for translational research.