Loss of inter-cellular cooperation by complete epithelial-mesenchymal transition supports favorable outcomes in basal breast cancer patients.

According to the sequential metastasis model, aggressive mesenchymal (M) metastasis-initiating cells (MICs) are generated by an epithelial-mesenchymal transition (EMT) which eventually is reversed by a mesenchymal-epithelial transition (MET) and outgrowth of life-threatening epithelial (E) macrometastases. Paradoxically, in breast cancer M signatures are linked with more favorable outcomes than E signatures, and M cells are often dispensable for metastasis in mouse models. Here we present evidence at the cellular and patient level for the cooperation metastasis model, according to which E cells are MICs, while M cells merely support E cell persistence through cooperation. We tracked the fates of co-cultured E and M clones and of fluorescent CDH1-promoter-driven cell lines reporting the E state derived from basal breast cancer HMLER cells. Cells were placed in suspension state and allowed to reattach and select an EMT cell fate. Flow cytometry, single cell and bulk gene expression analyses revealed that only pre-existing E cells generated E cells, mixed E/M populations, or stem-like hybrid E/M cells after suspension and that complete EMT manifest in M clones and CDH1-negative reporter cells resulted in loss of cell plasticity, suggesting full transdifferentiation. Mechanistically, E-M coculture experiments supported the persistence of pre-existing E cells where M cells inhibited EMT of E cells in a mutual cooperation via direct cell-cell contact. Consistently, M signatures were associated with more favorable patient outcomes compared to E signatures in breast cancer, specifically in basal breast cancer patients. These findings suggest a potential benefit of complete EMT for basal breast cancer patients.

Analysis of mitochondrial metabolism in situ: Combining stable isotope labeling with selective permeabilization.

To date, it is well-established that mitochondrial dysfunction does not only play a vital role in cancer but also in other pathological conditions such as neurodegenerative diseases and inflammation. An important tool for the analysis of cellular metabolism is the application of stable isotope labeled substrates, which allow for the tracing of atoms throughout metabolic networks. While such analyses yield very detailed information about intracellular fluxes, the determination of compartment specific fluxes is far more challenging. Most approaches for the deconvolution of compartmented metabolism use computational models whereas experimental methods are rare. Here, we developed an experimental setup based on selective permeabilization of the cytosolic membrane that allows for the administration of stable isotope labeled substrates directly to mitochondria. We demonstrate how this approach can be used to infer metabolic changes in mitochondria induced by either chemical or genetic perturbations and give an outlook on its potential applications.

Relative stability of network states in Boolean network models of gene regulation in development.

Progress in cell type reprogramming has revived the interest in Waddington's concept of the epigenetic landscape. Recently researchers developed the quasi-potential theory to represent the Waddington's landscape. The Quasi-potential U(x), derived from interactions in the gene regulatory network (GRN) of a cell, quantifies the relative stability of network states, which determine the effort required for state transitions in a multi-stable dynamical system. However, quasi-potential landscapes, originally developed for continuous systems, are not suitable for discrete-valued networks which are important tools to study complex systems. In this paper, we provide a framework to quantify the landscape for discrete Boolean networks (BNs). We apply our framework to study pancreas cell differentiation where an ensemble of BN models is considered based on the structure of a minimal GRN for pancreas development. We impose biologically motivated structural constraints (corresponding to specific type of Boolean functions) and dynamical constraints (corresponding to stable attractor states) to limit the space of BN models for pancreas development. In addition, we enforce a novel functional constraint corresponding to the relative ordering of attractor states in BN models to restrict the space of BN models to the biological relevant class. We find that BNs with canalyzing/sign-compatible Boolean functions best capture the dynamics of pancreas cell differentiation. This framework can also determine the genes' influence on cell state transitions, and thus can facilitate the rational design of cell reprogramming protocols.

Pro-inflammatory Macrophages Sustain Pyruvate Oxidation through Pyruvate Dehydrogenase for the Synthesis of Itaconate and to Enable Cytokine Expression.

Upon stimulation with Th1 cytokines or bacterial lipopolysaccharides, resting macrophages shift their phenotype toward a pro-inflammatory state as part of the innate immune response. LPS-activated macrophages undergo profound metabolic changes to adapt to these new physiological requirements. One key step to mediate this metabolic adaptation is the stabilization of HIF1α, which leads to increased glycolysis and lactate release, as well as decreased oxygen consumption. HIF1 abundance can result in the induction of the gene encoding pyruvate dehydrogenase kinase 1 (PDK1), which inhibits pyruvate dehydrogenase (PDH) via phosphorylation. Therefore, it has been speculated that pyruvate oxidation through PDH is decreased in pro-inflammatory macrophages. However, to answer this open question, an in-depth analysis of this metabolic branching point was so far lacking. In this work, we applied stable isotope-assisted metabolomics techniques and demonstrate that pyruvate oxidation is maintained in mature pro-inflammatory macrophages. Glucose-derived pyruvate is oxidized via PDH to generate citrate in the mitochondria. Citrate is used for the synthesis of the antimicrobial metabolite itaconate and for lipogenesis. An increased demand for these metabolites decreases citrate oxidation through the tricarboxylic acid cycle, whereas increased glutamine uptake serves to replenish the TCA cycle. Furthermore, we found that the PDH flux is maintained by unchanged PDK1 abundance, despite the presence of HIF1. By pharmacological intervention, we demonstrate that the PDH flux is an important node for M(LPS) macrophage activation. Therefore, PDH represents a metabolic intervention point that might become a research target for translational medicine to treat chronic inflammatory diseases.

FR-like EBNA1 binding repeats in the human genome.

Epstein-Barr virus (EBV) is widely spread in the human population. EBV nuclear antigen 1 (EBNA1) is a transcription factor that activates viral genes and is necessary for viral replication and partitioning, which binds the EBV genome cooperatively. We identify similar EBNA1 repeat binding sites in the human genome using a nearest-neighbor positional weight matrix. Previously experimentally verified EBNA1 sites in the human genome are successfully recovered by our approach. Most importantly, 40 novel regions are identified in the human genome, constituted of tandemly repeated binding sites for EBNA1. Genes located in the vicinity of these regions are presented as possible targets for EBNA1-mediated regulation. Among these, four are discussed in more detail: IQCB1, IMPG1, IRF2BP2 and TPO. Incorporating the cooperative actions of EBNA1 is essential when identifying regulatory regions in the human genome and we believe the findings presented here are highly valuable for the understanding of EBV-induced phenotypic changes.

Transcription factor concentrations versus binding site affinities in the yeast S. cerevisiae.

Transcription regulation is largely governed by the profile and the dynamics of transcription factors' binding to DNA. Stochastic effects are intrinsic to this dynamics, and the binding to functional sites must be controlled with a certain specificity for living organisms to be able to elicit specific cellular responses. Specificity stems here from the interplay between binding affinity and cellular abundance of transcription factor proteins, and the binding of such proteins to DNA is thus controlled by their chemical potential. We combine large-scale protein abundance data in the budding yeast with binding affinities for all transcription factors with known DNA binding site sequences to assess the behavior of their chemical potentials in an exponential growth phase. A sizable fraction of transcription factors is apparently bound non-specifically to DNA, and the observed abundances are marginally sufficient to ensure high occupations of the functional sites. We argue that a biological cause of this feature is related to its noise-filtering consequences: abundances below physiological levels do not yield significant binding of functional targets and mis-expressions of regulated genes may thus be tamed.