A stochastic model dissects cell states in biological transition processes

Scientific Reports (Impact Factor: 5.58). 01/2014; 4:3692. DOI: 10.1038/srep03692
Source: PubMed


Many biological processes, including differentiation, reprogramming, and disease transformations, involve transitions of cells through distinct states. Direct, unbiased investigation of cell states and their transitions is challenging due to several factors, including limitations of single-cell assays. Here we present a stochastic model of cellular transitions that allows underlying single-cell information, including cell-state-specific parameters and rates governing transitions between states, to be estimated from genome-wide, population-averaged time-course data. The key novelty of our approach lies in specifying latent stochastic models at the single-cell level, and then aggregating these models to give a likelihood that links parameters at the single-cell level to observables at the population level. We apply our approach in the context of reprogramming to pluripotency. This yields new insights, including profiles of two intermediate cell states, that are supported by independent single-cell studies. Our model provides a general conceptual framework for the study of cell transitions, including epigenetic transformations.

Download full-text


Available from: Krishanu Saha, Jan 20, 2014
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Estrogen responsive breast cancer cell lines have been extensively studied to characterize transcriptional patterns in hormone-responsive tumors. Nevertheless, due to current technological limitations, genome-wide studies have typically been limited to population averaged data. Here we obtain, for the first time, a characterization at the single-cell level of the states and expression signatures of a hormone-starved MCF-7 cell system responding to estrogen. To do so, we employ a recently proposed model that allows for dissecting single-cell states from time-course microarray data. We show that within 32 hours following stimulation, MCF-7 cells traverse, most likely, six states, with a faster early response followed by a progressive deceleration. We also derive the genome-wide transcriptional profiles of such single-cell states and their functional characterization. Our results support a scenario where estrogen promotes cell cycle progression by controlling multiple, sequential regulatory steps, whose single-cell events are here identified.
    Full-text · Article · Feb 2014 · PLoS ONE
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Forced expression of transcription factors epigenetically reprograms somatic cells harvested from routine skin biopsies into induced pluripotent stem cells (iPSCs). Human iPSCs are key resources for drug discovery, regenerative medicine and tissue engineering. Here we developed a materials approach to explore how culture substrates could impact factor-mediated reprogramming of human fibroblasts. A materials library consisting of nanofibrous substrates with randomly oriented and aligned structures was prepared by electrospinning four polymers [polylactic acid (PLA), polycaprolactone (PCL), thermoplastic polyurethane (TPU) and polypropylene carbonate (PPC)] into nanofiber orientations. Adsorbing protein to each substrate permitted robust attachment of fibroblasts to all substrates. Fibroblasts on aligned substrates had elongated nuclei, but after reprogramming factor expression, nuclei became more circular. Reprogramming factors could override the nuclear shape constraints imposed by nanofibrous substrates, and the majority of substrates supported full reprogramming. Early culture on PCL and TPU substrates promoted reprogramming, and TGF-β repressed substrate effects. Partial least squares modeling of the biochemical and biophysical cues within our reprogramming system identified TGF-β and polymer identity as important cues governing cellular reprogramming responses. We believe that our approach of using a nanofibrous materials library can be used to dissect molecular mechanisms of reprogramming and generate novel substrates that enhance epigenetic reprogramming.
    Full-text · Article · Sep 2014 · Cellular and Molecular Bioengineering
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The acquisition of and departure from stemness in cancer tissues might not only be hardwired by genetic controllers, but also by the pivotal regulatory role of the cellular metabotype, which may act as a "starter dough" for cancer stemness traits. We have coined the term metabostemness to refer to the metabolic parameters causally controlling or functionally substituting the epitranscriptional orchestration of the genetic reprograming that redirects normal and tumor cells toward less-differentiated cancer stem cell (CSC) cellular states. Certain metabotypic alterations might operate as pivotal molecular events rendering a cell of origin susceptible to epigenetic rewiring required for the acquisition of aberrant stemness and, concurrently, of refractoriness to differentiation. The metabostemness attribute can remove, diminish, or modify the nature of molecular barriers present in Waddington's epigenetic landscapes, thus allowing differentiated cells to more easily (re)-enter into CSC cellular macrostates. Activation of the metabostemness trait can poise cells with chromatin states competent for rapid dedifferentiation while concomitantly setting the idoneous metabolic stage for later reprograming stimuli to finish the journey from non-cancerous into tumor-initiating cells. Because only a few permitted metabotypes will be compatible with the operational properties owned by CSC cellular states, the metabostemness property provides a new framework through which to pharmacologically resolve the apparently impossible problem of discovering drugs aimed to target the molecular biology of the cancer stemness itself. The metabostemness cancer hallmark generates a shifting oncology theory that should guide a new era of metabolo-epigenetic cancer precision medicine.
    Full-text · Article · Sep 2014 · Frontiers in Oncology
Show more