Parameterizing cell-to-cell regulatory heterogeneities via stochastic transcriptional profiles

Bajikar SS, Fuchs C, Roller A, Theis FJ, Janes KA. Parameterizing cell-to-cell regulatory heterogeneities via stochastic transcriptional profiles. Proceedings of the National Academy of Sciences. 2014;111(5):E626-E635.Regulated changes in gene expression underlie many biological processes, but globally profiling cell-to-cell variations in transcriptional regulation is problematic when measuring single cells. Transcriptome-wide identification of regulatory heterogeneities can be robustly achieved by randomly collecting small numbers of cells followed by statistical analysis. However, this stochastic-profiling approach blurs out the expression states of the individual cells in each pooled sample. Here, we show that the underlying distribution of single-cell regulatory states can be deconvolved from stochastic-profiling data through maximum-likelihood inference. Guided by the mechanisms of transcriptional regulation, we formulated plausible mixture models for cell-to-cell regulatory heterogeneity and maximized the resulting likelihood functions to infer model parameters. Inferences were validated both computationally and experimentally for different mixture models, which included regulatory states for multicellular function that were occupied by as few as 1 in 40 cells of the population. Importantly, when the method was extended to programs of heterogeneously coexpressed transcripts, we found that population-level inferences were much more accurate with pooled samples than with one-cell samples when the extent of sampling was limited. Our deconvolution method provides a means to quantify the heterogeneous regulation of molecular states efficiently and gain a deeper understanding of the heterogeneous execution of cell decisions

Automated brightfield morphometry of 3D organoid populations by OrganoSeg

Spheroid and organoid cultures are powerful in vitro models for biology, but size and shape diversity within the culture is largely ignored. To streamline morphometric profiling, we developed OrganoSeg, an open-source software that integrates segmentation, filtering, and analysis for archived brightfield images of 3D culture. OrganoSeg is more accurate and flexible than existing platforms, and we illustrate its potential by stratifying 5167 breast-cancer spheroid and 5743 colon and colorectal-cancer organoid morphologies. Organoid transcripts grouped by morphometric signature heterogeneity were enriched for biological processes not prominent in the original RNA sequencing data. OrganoSeg enables complete, objective quantification of brightfield phenotypes, which may give insight into the molecular and multicellular mechanisms of organoid regulation

Tumor-Suppressor Inactivation of GDF11 Occurs by Precursor Sequestration in Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is an aggressive and heterogeneous carcinoma in which various tumor-suppressor genes are lost by mutation, deletion, or silencing. Here we report a tumor-suppressive mode of action for growth-differentiation factor 11 (GDF11) and an unusual mechanism of its inactivation in TNBC. GDF11 promotes an epithelial, anti-invasive phenotype in 3D triple-negative cultures and intraductal xenografts by sustaining expression of E-cadherin and inhibitor of differentiation 2 (ID2). Surprisingly, clinical TNBCs retain the GDF11 locus and expression of the protein itself. GDF11 bioactivity is instead lost because of deficiencies in its convertase, proprotein convertase subtilisin/kexin type 5 (PCSK5), causing inactive GDF11 precursor to accumulate intracellularly. PCSK5 reconstitution mobilizes the latent TNBC reservoir of GDF11 in vitro and suppresses triple-negative mammary cancer metastasis to the lung of syngeneic hosts. Intracellular GDF11 retention adds to the concept of tumor-suppressor inactivation and reveals a cell-biological vulnerability for TNBCs lacking therapeutically actionable mutations

Heterozygous loss-of-function variants significantly expand the phenotypes associated with loss of GDF11.

PurposeGrowth differentiation factor 11 (GDF11) is a key signaling protein required for proper development of many organ systems. Only one prior study has associated an inherited GDF11 variant with a dominant human disease in a family with variable craniofacial and vertebral abnormalities. Here, we expand the phenotypic spectrum associated with GDF11 variants and document the nature of the variants.MethodsWe present a cohort of six probands with de novo and inherited nonsense/frameshift (4/6 patients) and missense (2/6) variants in GDF11. We generated gdf11 mutant zebrafish to model loss of gdf11 phenotypes and used an overexpression screen in Drosophila to test variant functionality.ResultsPatients with variants in GDF11 presented with craniofacial (5/6), vertebral (5/6), neurological (6/6), visual (4/6), cardiac (3/6), auditory (3/6), and connective tissue abnormalities (3/6). gdf11 mutant zebrafish show craniofacial abnormalities and body segmentation defects that match some patient phenotypes. Expression of the patients' variants in the fly showed that one nonsense variant in GDF11 is a severe loss-of-function (LOF) allele whereas the missense variants in our cohort are partial LOF variants.ConclusionGDF11 is needed for human development, particularly neuronal development, and LOF GDF11 alleles can affect the development of numerous organs and tissues

Heterozygous loss-of-function variants significantly expand the phenotypes associated with loss of GDF11

Growth differentiation factor 11 (GDF11) is a key signaling protein required for proper development of many organ systems. Only one prior study has associated an inherited GDF11 variant with a dominant human disease in a family with variable craniofacial and vertebral abnormalities. Here, we expand the phenotypic spectrum associated with GDF11 variants and document the nature of the variants.We present a cohort of six probands with de novo and inherited nonsense/frameshift (4/6 patients) and missense (2/6) variants in GDF11. We generated gdf11 mutant zebrafish to model loss of gdf11 phenotypes and used an overexpression screen in Drosophila to test variant functionality.Patients with variants in GDF11 presented with craniofacial (5/6), vertebral (5/6), neurological (6/6), visual (4/6), cardiac (3/6), auditory (3/6), and connective tissue abnormalities (3/6). gdf11 mutant zebrafish show craniofacial abnormalities and body segmentation defects that match some patient phenotypes. Expression of the patients’ variants in the fly showed that one nonsense variant in GDF11 is a severe loss-of-function (LOF) allele whereas the missense variants in our cohort are partial LOF variants.GDF11 is needed for human development, particularly neuronal development, and LOF GDF11 alleles can affect the development of numerous organs and tissues