Characterization of alternative mRNA splicing in cultured cell populations representing progressive stages of human fetal kidney development.

Nephrons are the functional units of the kidney. During kidney development, cells from the cap mesenchyme-a transient kidney-specific progenitor state-undergo a mesenchymal to epithelial transition (MET) and subsequently differentiate into the various epithelial cell types that create the tubular structures of the nephron. Faults in this transition can lead to a pediatric malignancy of the kidney called Wilms' tumor that mimics normal kidney development. While human kidney development has been characterized at the gene expression level, a comprehensive characterization of alternative splicing is lacking. Therefore, in this study, we performed RNA sequencing on cell populations representing early, intermediate, and late developmental stages of the human fetal kidney, as well as three blastemal-predominant Wilms' tumor patient-derived xenografts. Using this newly generated RNAseq data, we identified a set of transcripts that are alternatively spliced between the different developmental stages. Moreover, we found that cells from the earliest developmental stage have a mesenchymal splice-isoform profile that is similar to that of blastemal-predominant Wilms' tumor xenografts. RNA binding motif enrichment analysis suggests that the mRNA binding proteins ESRP1, ESRP2, RBFOX2, and QKI regulate alternative mRNA splicing during human kidney development. These findings illuminate new molecular mechanisms involved in human kidney development and pediatric kidney cancer.

Applications of Community Detection Algorithms to Large Biological Datasets.

Recent advances in data acquiring technologies in biology have led to major challenges in mining relevant information from large datasets. For example, single-cell RNA sequencing technologies are producing expression and sequence information from tens of thousands of cells in every single experiment. A common task in analyzing biological data is to cluster samples or features (e.g., genes) into groups sharing common characteristics. This is an NP-hard problem for which numerous heuristic algorithms have been developed. However, in many cases, the clusters created by these algorithms do not reflect biological reality. To overcome this, a Networks Based Clustering (NBC) approach was recently proposed, by which the samples or genes in the dataset are first mapped to a network and then community detection (CD) algorithms are used to identify clusters of nodes.Here, we created an open and flexible python-based toolkit for NBC that enables easy and accessible network construction and community detection. We then tested the applicability of NBC for identifying clusters of cells or genes from previously published large-scale single-cell and bulk RNA-seq datasets.We show that NBC can be used to accurately and efficiently analyze large-scale datasets of RNA sequencing experiments.

Human kidney clonal proliferation disclose lineage-restricted precursor characteristics.

In-vivo single cell clonal analysis in the adult mouse kidney has previously shown lineage-restricted clonal proliferation within varying nephron segments as a mechanism responsible for cell replacement and local regeneration. To analyze ex-vivo clonal growth, we now preformed limiting dilution to generate genuine clonal cultures from one single human renal epithelial cell, which can give rise to up to 3.4 * 106 cells, and analyzed their characteristics using transcriptomics. A comparison between clonal cultures revealed restriction to either proximal or distal kidney sub-lineages with distinct cellular and molecular characteristics; rapidly amplifying de-differentiated clones and a stably proliferating cuboidal epithelial-appearing clones, respectively. Furthermore, each showed distinct molecular features including cell-cycle, epithelial-mesenchymal transition, oxidative phosphorylation, BMP signaling pathway and cell surface markers. In addition, analysis of clonal versus bulk cultures show early clones to be more quiescent, with elevated expression of renal developmental genes and overall reduction in renal identity markers, but with an overlapping expression of nephron segment identifiers and multiple identity. Thus, ex-vivo clonal growth mimics the in-vivo situation displaying lineage-restricted precursor characteristics of mature renal cells. These data suggest that for reconstruction of varying renal lineages with human adult kidney based organoid technology and kidney regeneration ex-vivo, use of multiple heterogeneous precursors is warranted.

Ex Vivo Expanded 3D Human Kidney Spheres Engraft Long Term and Repair Chronic Renal Injury in Mice.

End-stage renal disease is a worldwide epidemic requiring renal replacement therapy. Harvesting tissue from failing kidneys and autotransplantation of tissue progenitors could theoretically delay the need for dialysis. Here we use healthy and end-stage human adult kidneys to robustly expand proliferative kidney epithelial cells and establish 3D kidney epithelial cultures termed "nephrospheres." Formation of nephrospheres reestablishes renal identity and function in primary cultures. Transplantation into NOD/SCID mice shows that nephrospheres restore self-organogenetic properties lost in monolayer cultures, allowing long-term engraftment as tubular structures, potentially adding nephron segments and demonstrating self-organization as critical to survival. Furthermore, long-term tubular engraftment of nephrospheres is functionally beneficial in murine models of chronic kidney disease. Remarkably, nephrospheres inhibit pro-fibrotic collagen production in cultured fibroblasts via paracrine modulation, while transplanted nephrospheres induce transcriptional signatures of proliferation and release from quiescence, suggesting re-activation of endogenous repair. These data support the use of human nephrospheres for renal cell therapy.

A cluster robustness score for identifying cell subpopulations in single cell gene expression datasets from heterogeneous tissues and tumors.

MOTIVATION: A major aim of single cell biology is to identify important cell types such as stem cells in heterogeneous tissues and tumors. This is typically done by isolating hundreds of individual cells and measuring expression levels of multiple genes simultaneously from each cell. Then, clustering algorithms are used to group together similar single-cell expression profiles into clusters, each representing a distinct cell type. However, many of these clusters result from overfitting, meaning that rather than representing biologically meaningful cell types, they describe the intrinsic 'noise' in gene expression levels due to limitations in experimental precision or the intrinsic randomness of biochemical cellular processes. Consequentially, these non-meaningful clusters are most sensitive to noise: a slight shift in gene expression levels due to a repeated measurement will rearrange the grouping of data points such that these clusters break up. RESULTS: To identify the biologically meaningful clusters we propose a 'cluster robustness score': We add increasing amounts of noise (zero mean and increasing variance) and check which clusters are most robust in the sense that they do not mix with their neighbors up to high levels of noise. We show that biologically meaningful cell clusters that were manually identified in previously published single cell expression datasets have high robustness scores. These scores are higher than what would be expected in corresponding randomized homogeneous datasets having the same expression level statistics. We believe that this scoring system provides a more automated way to identify cell types in heterogeneous tissues and tumors. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

In Vivo Expansion of Cancer Stemness Affords Novel Cancer Stem Cell Targets: Malignant Rhabdoid Tumor as an Example.

Cancer stem cell (CSC) identification relies on transplantation assays of cell subpopulations sorted from fresh tumor samples. Here, we attempt to bypass limitations of abundant tumor source and predetermined immune selection by in vivo propagating patient-derived xenografts (PDX) from human malignant rhabdoid tumor (MRT), a rare and lethal pediatric neoplasm, to an advanced state in which most cells behave as CSCs. Stemness is then probed by comparative transcriptomics of serial PDXs generating a gene signature of epithelial to mesenchymal transition, invasion/motility, metastasis, and self-renewal, pinpointing putative MRT CSC markers. The relevance of these putative CSC molecules is analyzed by sorting tumorigenic fractions from early-passaged PDX according to one such molecule, deciphering expression in archived primary tumors, and testing the effects of CSC molecule inhibition on MRT growth. Using this platform, we identify ALDH1 and lysyl oxidase (LOX) as relevant targets and provide a larger framework for target and drug discovery in rare pediatric cancers.

Geometry of Gene Expression Space of Wilms' Tumors From Human Patients.

Wilms' tumor is a pediatric malignancy that is thought to originate from faulty kidney development during the embryonic stage. However, there is a large variation between tumors from different patients in both histology and gene expression that is not well characterized. Here we use a meta-analysis of published microarray datasets to show that Favorable Histology Wilms' Tumors (FHWT's) fill a triangle-shaped continuum in gene expression space of which the vertices represent three idealized "archetypes". We show that these archetypes have predominantly renal blastemal, stromal, and epithelial characteristics and that they correlate well with the three major lineages of the developing embryonic kidney. Moreover, we show that advanced stage tumors shift towards the renal blastemal archetype. These results illustrate the potential of this methodology for characterizing the cellular composition of Wilms' tumors and for assessing disease progression.

A brief review of single-cell transcriptomic technologies.

In recent years, there has been an effort to develop new technologies for measuring gene expression and sequence information from thousands of individual cells. Large data sets that were obtained using these 'single cell' technologies have allowed scientists to address fundamental questions in biomedicine ranging from stems cells and development to cancer and immunology. Here, we provide a brief review of recent developments in single-cell technology. Our intention is to provide a quick background for newcomers to the field as well as a deeper description of some of the leading technologies to date.

Visualizing nuclear RNAi activity in single living human cells.

Nuclear RNA interference (RNAi) is mediated by the canonical RNAi machinery and can lead to transcriptional silencing, transcriptional activation, or modulation of alternative splicing patterns. These effects transpire through changes in histone and DNA modifications via RNAi-mediated recruitment of chromatin-modifying enzymes. To prove that nuclear RNAi occurs and modulates transcription in human cells, we used live-cell imaging to detect and track nuclear RNAi transcriptional repression in single living human cells. While employing reporter genes constructed with inducible promoters and cognate-inducible short hairpin RNA (shRNA) targeted against the reporter coding region, we have characterized the dynamics of the nuclear RNAi process in living human cells. We show that the silencing effect is mediated through the nascent mRNA, followed by activity of histone methylating enzymes, but not through DNA methylation.

Mutations in S-adenosylhomocysteine hydrolase (AHCY) affect its nucleocytoplasmic distribution and capability to interact with S-adenosylhomocysteine hydrolase-like 1 protein.

S-adenosylhomocysteine hydrolase (AHCY) is thought to be located at the sites of ongoing AdoMet-dependent methylation, presumably in the cell nucleus. Endogenous AHCY is located both in cytoplasm and the nucleus. Little is known regarding mechanisms that drive its subcellular distribution, and even less is known on how mutations causing AHCY deficiency affect its intracellular dynamics. Using fluorescence microscopy and GFP-tagged AHCY constructs we show significant differences in the intensity ratio between nuclei and cytoplasm for mutant proteins when compared with wild type AHCY. Interestingly, nuclear export of AHCY is not affected by leptomycin B. Systematic deletions showed that AHCY has two regions, located at both sides of the protein, that contribute to its nuclear localization, implying the interaction with various proteins. In order to evaluate protein interactions in vivo we engaged in bimolecular fluorescence complementation (BiFC) based studies. We investigated previously assumed interaction with AHCY-like-1 protein (AHCYL1), a paralog of AHCY. Indeed, significant interaction between both proteins exists. Additionally, silencing AHCYL1 leads to moderate inhibition of nuclear export of endogenous AHCY.

Evidence of In Vitro Preservation of Human Nephrogenesis at the Single-Cell Level.

During nephrogenesis, stem/progenitor cells differentiate and give rise to early nephron structures that segment to proximal and distal nephron cell types. Previously, we prospectively isolated progenitors from human fetal kidney (hFK) utilizing a combination of surface markers. However, upon culture nephron progenitors differentiated and could not be robustly maintained in vitro. Here, by culturing hFK in a modified medium used for in vitro growth of mouse nephron progenitors, and by dissection of NCAM+/CD133- progenitor cells according to EpCAM expression (NCAM+/CD133-/EpCAM-, NCAM+/CD133-/EpCAMdim, NCAM+/CD133-/EpCAMbright), we show at single-cell resolution a preservation of uninduced and induced cap mesenchyme as well as a transitioning mesenchymal-epithelial state. Concomitantly, differentiating and differentiated epithelial lineages are also maintained. In vitro expansion of discrete stages of early human nephrogenesis in nephron stem cell cultures may be used for drug screening on a full repertoire of developing kidney cells and for prospective isolation of mesenchymal or epithelial renal lineages for regenerative medicine.

Peroxisome proliferator-activated receptor gamma (PPARγ) is central to the initiation and propagation of human angiomyolipoma, suggesting its potential as a therapeutic target

Angiomyolipoma (AML), the most common benign renal tumor, can result in severe morbidity from hemorrhage and renal failure. While mTORC1 activation is involved in its growth, mTORC1 inhibitors fail to eradicate AML, highlighting the need for new therapies. Moreover, the identity of the AML cell of origin is obscure. AML research, however, is hampered by the lack of in vivo models. Here, we establish a human AML-xenograft (Xn) model in mice, recapitulating AML at the histological and molecular levels. Microarray analysis demonstrated tumor growth in vivo to involve robust PPARγ-pathway activation. Similarly, immunostaining revealed strong PPARγ expression in human AML specimens. Accordingly, we demonstrate that while PPARγ agonism accelerates AML growth, PPARγ antagonism is inhibitory, strongly suppressing AML proliferation and tumor-initiating capacity, via a TGFB-mediated inhibition of PDGFB and CTGF. Finally, we show striking similarity between AML cell lines and mesenchymal stem cells (MSCs) in terms of antigen and gene expression and differentiation potential. Altogether, we establish the first in vivo human AML model, which provides evidence that AML may originate in a PPARγ-activated renal MSC lineage that is skewed toward adipocytes and smooth muscle and away from osteoblasts, and uncover PPARγ as a regulator of AML growth, which could serve as an attractive therapeutic target.

CD-tagging-MS2: detecting allelic expression of endogenous mRNAs and their protein products in single cells.

Discriminating between the mRNA and protein outputs of each of the alleles of an endogenous gene in intact cells, is a difficult task. To examine endogenous transcripts originating from a specific allele, we applied Central Dogma tagging (CD-tagging), which is based on a tag insertion into an endogenous gene by creation of a new exon. Previously, CD-tagging was used to tag endogenous proteins. Here we developed a CD-tagging-MS2 approach in which two tags were inserted in tandem; a fluorescent protein tag in conjunction with the mRNA MS2 tag used for tagging mRNAs in cells. A cell clone library of CD-tagged-MS2 genes was generated, and protein and mRNA distributions were examined and characterized in single cells. Taking advantage of having one allele tagged, we demonstrate how the transcriptional activity of all alleles, tagged and untagged, can be identified using single molecule RNA fluorescence in situ hybridization (smFISH). Allele-specific mRNA expression and localization were quantified under normal and stress conditions. The latter generate cytoplasmic stress granules (SGs) that can store mRNAs, and the distribution of the mRNAs within and outside of the SGs was measured. Altogether, CD-tagging-MS2 is a robust and inexpensive approach for direct simultaneous detection of an endogenous mRNA and its translated protein product in the same cell.

Quantifying ß-catenin subcellular dynamics and cyclin D1 mRNA transcription during Wnt signaling in single living cells.

Signal propagation from the cell membrane to a promoter can induce gene expression. To examine signal transmission through sub-cellular compartments and its effect on transcription levels in individual cells within a population, we used the Wnt/ß-catenin signaling pathway as a model system. Wnt signaling orchestrates a response through nuclear accumulation of ß-catenin in the cell population. However, quantitative live-cell measurements in individual cells showed variability in nuclear ß-catenin accumulation, which could occur in two waves, followed by slow clearance. Nuclear accumulation dynamics were initially rapid, cell cycle independent and differed substantially from LiCl stimulation, presumed to mimic Wnt signaling. ß-catenin levels increased simultaneously at adherens junctions and the centrosome, and a membrane-centrosome transport system was revealed. Correlating ß-catenin nuclear dynamics to cyclin D1 transcriptional activation showed that the nuclear accumulation rate of change of the signaling factor, and not actual protein levels, correlated with the transcriptional output of the pathway.

Dissecting Stages of Human Kidney Development and Tumorigenesis with Surface Markers Affords Simple Prospective Purification of Nephron Stem Cells.

When assembling a nephron during development a multipotent stem cell pool becomes restricted as differentiation ensues. A faulty differentiation arrest in this process leads to transformation and initiation of a Wilms' tumor. Mapping these transitions with respective surface markers affords accessibility to specific cell subpopulations. NCAM1 and CD133 have been previously suggested to mark human renal progenitor populations. Herein, using cell sorting, RNA sequencing, in vitro studies with serum-free media and in vivo xenotransplantation we demonstrate a sequential map that links human kidney development and tumorigenesis; In nephrogenesis, NCAM1(+)CD133(-) marks SIX2(+) multipotent renal stem cells transiting to NCAM1(+)CD133(+) differentiating segment-specific SIX2(-) epithelial progenitors and NCAM1(-)CD133(+) differentiated nephron cells. In tumorigenesis, NCAM1(+)CD133(-) marks SIX2(+) blastema that includes the ALDH1(+) WT cancer stem/initiating cells, while NCAM1(+)CD133(+) and NCAM1(-)CD133(+) specifying early and late epithelial differentiation, are severely restricted in tumor initiation capacity and tumor self-renewal. Thus, negative selection for CD133 is required for defining NCAM1(+) nephron stem cells in normal and malignant nephrogenesis.

Exploring chromatin organization mechanisms through its dynamic properties.

The organization of the genome in the nucleus is believed to be crucial for different cellular functions. It is known that chromosomes fold into distinct territories, but little is known about the mechanisms that maintain these territories. To explore these mechanisms, we used various live-cell imaging methods, including single particle tracking to characterize the diffusion properties of different genomic regions in live cells. Chromatin diffusion is found to be slow and anomalous; in vast contrast, depletion of lamin A protein significantly increases chromatin motion, and the diffusion pattern of chromatin transforms from slow anomalous to fast normal. More than this, depletion of lamin A protein also affects the dynamics of nuclear bodies. Our findings indicate that chromatin motion is mediated by lamin A and we suggest that constrained chromatin mobility allows to maintain chromosome territories. Thus, the discovery of this function of nucleoplasmic lamin A proteins sheds light on the maintenance mechanism of chromosome territories in the interphase nucleus, which ensures the proper function of the genome.

Cellular Levels of Signaling Factors Are Sensed by ß-actin Alleles to Modulate Transcriptional Pulse Intensity.

The transcriptional response of ß-actin to extra-cellular stimuli is a paradigm for transcription factor complex assembly and regulation. Serum induction leads to a precisely timed pulse of ß-actin transcription in the cell population. Actin protein is proposed to be involved in this response, but it is not known whether cellular actin levels affect nuclear ß-actin transcription. We perturbed the levels of key signaling factors and examined the effect on the induced transcriptional pulse by following endogenous ß-actin alleles in single living cells. Lowering serum response factor (SRF) protein levels leads to loss of pulse integrity, whereas reducing actin protein levels reveals positive feedback regulation, resulting in elevated gene activation and a prolonged transcriptional response. Thus, transcriptional pulse fidelity requires regulated amounts of signaling proteins, and perturbations in factor levels eliminate the physiological response, resulting in either tuning down or exaggeration of the transcriptional pulse.

Single cell transcriptomics: methods and applications.

Traditionally, gene expression measurements were performed on "bulk" samples containing populations of thousands of cells. Recent advances in genomic technology have made it possible to measure gene expression in hundreds of individual cells at a time. As a result, cellular properties that were previously masked in "bulk" measurements can now be observed directly. In this review, we will survey emerging technologies for single cell transcriptomics, and describe how they are used to study complex disease such as cancer, as well as other biological phenomena such as tissue regeneration, embryonic development, and immune response.