Factor graph analysis of live cell-imaging data reveals mechanisms of cell fate decisions.

MOTIVATION: Cell fate decisions have a strong stochastic component. The identification of the underlying mechanisms therefore requires a rigorous statistical analysis of large ensembles of single cells that were tracked and phenotyped over time. RESULTS: We introduce a probabilistic framework for testing elementary hypotheses on dynamic cell behavior using time-lapse cell-imaging data. Factor graphs, probabilistic graphical models, are used to properly account for cell lineage and cell phenotype information. Our model is applied to time-lapse movies of murine granulocyte-macrophage progenitor (GMP) cells. It decides between competing hypotheses on the mechanisms of their differentiation. Our results theoretically substantiate previous experimental observations that lineage instruction, not selection is the cause for the differentiation of GMP cells into mature monocytes or neutrophil granulocytes. AVAILABILITY AND IMPLEMENTATION: The Matlab source code is available at http://treschgroup.de/Genealogies.html.

High definition plus colonoscopy combined with i-scan tone enhancement vs. high definition colonoscopy for colorectal neoplasia: A randomized trial.

BACKGROUND: High definition endoscopy is the accepted standard in colonoscopy. However, an important problem is missed polyps. AIMS: Our objective was to assess the additional adenoma detection rate between high definition colonoscopy with tone enhancement (digital chromoendoscopy) vs. white light high definition colonoscopy. METHODS: In this prospective randomized trial patients were included to undergo a tandem colonoscopy. The first exam was a white light colonoscopy with removal of all visualized polyps. The second examination was randomly assigned in a 1:1 ratio as either again white light colonoscopy (Group A) or colonoscopy with tone enhancement (Group B). Primary endpoint was the adenoma detection rate during the second withdrawal (sample size calculation - 40 per group). RESULTS: 67 lesions (Group A: n=34 vs. Group B: n=33) in 80 patients (mean age 61 years, male 64%) were identified on the first colonoscopy. The second colonoscopy detected 78 additional lesions: n=60 with tone enhancement vs. n=18 with white light endoscopy (p<0.001). Tone enhancement found more additional adenomas (A n=20 vs. B n=6, p=0.006) and identified significantly more missed adenomas per subject (0.5 vs. 0.15, p=0.006). CONCLUSIONS: High definition plus colonoscopy with tone enhancement detected more adenomas missed by white light colonoscopy.

MC EMiNEM maps the interaction landscape of the Mediator.

The Mediator is a highly conserved, large multiprotein complex that is involved essentially in the regulation of eukaryotic mRNA transcription. It acts as a general transcription factor by integrating regulatory signals from gene-specific activators or repressors to the RNA Polymerase II. The internal network of interactions between Mediator subunits that conveys these signals is largely unknown. Here, we introduce MC EMiNEM, a novel method for the retrieval of functional dependencies between proteins that have pleiotropic effects on mRNA transcription. MC EMiNEM is based on Nested Effects Models (NEMs), a class of probabilistic graphical models that extends the idea of hierarchical clustering. It combines mode-hopping Monte Carlo (MC) sampling with an Expectation-Maximization (EM) algorithm for NEMs to increase sensitivity compared to existing methods. A meta-analysis of four Mediator perturbation studies in Saccharomyces cerevisiae, three of which are unpublished, provides new insight into the Mediator signaling network. In addition to the known modular organization of the Mediator subunits, MC EMiNEM reveals a hierarchical ordering of its internal information flow, which is putatively transmitted through structural changes within the complex. We identify the N-terminus of Med7 as a peripheral entity, entailing only local structural changes upon perturbation, while the C-terminus of Med7 and Med19 appear to play a central role. MC EMiNEM associates Mediator subunits to most directly affected genes, which, in conjunction with gene set enrichment analysis, allows us to construct an interaction map of Mediator subunits and transcription factors.

Processive RNA decay by the exosome: merits of a quantitative Bayesian sampling approach.

RNA exosomes are large multi-subunit protein complexes involved in controlled and processive 3' to 5' RNA degradation. Exosomes form large molecular chambers and harbor multiple nuclease sites as well as RNA binding regions. This makes a quantitative kinetic analysis of RNA degradation with reliable parameter and error estimates challenging. For instance, recent quantitative biochemical assays revealed that degradation speed and efficiency depend on various factors, such as the type of RNA binding caps and the RNA length. We propose the combination of a differential equation model with bayesian Markov Chain Monte Carlo (MCMC) sampling for a more robust and reliable analysis of such complex kinetic systems. Using the exosome as a paradigm, it is shown that conventional "best fit" approaches to parameter estimation are outperformed by the MCMC method. The parameter distribution returned by MCMC sampling allows for a reliable and meaningful comparison of the data from different time series. In the case of the exosome, we find that the cap structures of the exosome have a direct effect on the recruitment and degradation of RNA, and that these effects are RNA length-dependent. The described approach can be widely applied to any processive reaction with a similar kinetics like the XRN1-dependent RNA degradation, RNA/DNA synthesis by polymerases, and protein synthesis by the ribosome.

Quantitative analysis of processive RNA degradation by the archaeal RNA exosome.

RNA exosomes are large multisubunit assemblies involved in controlled RNA processing. The archaeal exosome possesses a heterohexameric processing chamber with three RNase-PH-like active sites, capped by Rrp4- or Csl4-type subunits containing RNA-binding domains. RNA degradation by RNA exosomes has not been studied in a quantitative manner because of the complex kinetics involved, and exosome features contributing to efficient RNA degradation remain unclear. Here we derive a quantitative kinetic model for degradation of a model substrate by the archaeal exosome. Markov Chain Monte Carlo methods for parameter estimation allow for the comparison of reaction kinetics between different exosome variants and substrates. We show that long substrates are degraded in a processive and short RNA in a more distributive manner and that the cap proteins influence degradation speed. Our results, supported by small angle X-ray scattering, suggest that the Rrp4-type cap efficiently recruits RNA but prevents fast RNA degradation of longer RNAs by molecular friction, likely by RNA contacts to its unique KH-domain. We also show that formation of the RNase-PH like ring with entrapped RNA is not required for high catalytic efficiency, suggesting that the exosome chamber evolved for controlled processivity, rather than for catalytic chemistry in RNA decay.