New insight into the role of MMP14 in metabolic balance

Membrane-anchored matrix metalloproteinase 14 (MMP14) is involved broadly in organ development through both its proteolytic and signal-transducing functions. Knockout of Mmp14 (KO) in mice results in a dramatic reduction of body size and wasting followed by premature death, the mechanism of which is poorly understood. Since the mammary gland develops after birth and is thus dependent for its functional progression on systemic and local cues, we chose it as an organ model for understanding why KO mice fail to thrive. A global analysis of the mammary glands' proteome in the wild type (WT) and KO mice provided insight into an unexpected role of MMP14 in maintaining metabolism and homeostasis. We performed mass spectrometry and quantitative proteomics to determine the protein signatures of mammary glands from 7 to 11 days old WT and KO mice and found that KO rudiments had a significantly higher level of rate-limiting enzymes involved in catabolic pathways. Glycogen and lipid levels in KO rudiments were reduced, and the circulating levels of triglycerides and glucose were lower. Analysis of the ultrastructure of mammary glands imaged by electron microscopy revealed a significant increase in autophagy signatures in KO mice. Finally, Mmp14 silenced mammary epithelial cells displayed enhanced autophagy. Applied to a systemic level, these findings indicate that MMP14 is a crucial regulator of tissue homeostasis. If operative on a systemic level, these findings could explain how Mmp14KO litter fail to thrive due to disorder in metabolism.

Network analysis of breast cancer progression and reversal using a tree-evolving network algorithm

The HMT3522 progression series of human breast cells have been used to discover how tissue architecture, microenvironment and signaling molecules affect breast cell growth and behaviors. However, much remains to be elucidated about malignant and phenotypic reversion behaviors of the HMT3522-T4-2 cells of this series. We employed a "pan-cell-state" strategy, and analyzed jointly microarray profiles obtained from different state-specific cell populations from this progression and reversion model of the breast cells using a tree-lineage multi-network inference algorithm, Treegl. We found that different breast cell states contain distinct gene networks. The network specific to non-malignant HMT3522-S1 cells is dominated by genes involved in normal processes, whereas the T4-2-specific network is enriched with cancer-related genes. The networks specific to various conditions of the reverted T4-2 cells are enriched with pathways suggestive of compensatory effects, consistent with clinical data showing patient resistance to anticancer drugs. We validated the findings using an external dataset, and showed that aberrant expression values of certain hubs in the identified networks are associated with poor clinical outcomes. Thus, analysis of various reversion conditions (including non-reverted) of HMT3522 cells using Treegl can be a good model system to study drug effects on breast cancer.

Phenotypic transition maps of 3D breast acini obtained by imaging-guided agent-based modeling

We introduce an agent-based model of epithelial cell morphogenesis to explore the complex interplay between apoptosis, proliferation, and polarization. By varying the activity levels of these mechanisms we derived phenotypic transition maps of normal and aberrant morphogenesis. These maps identify homeostatic ranges and morphologic stability conditions. The agent-based model was parameterized and validated using novel high-content image analysis of mammary acini morphogenesis in vitro with focus on time-dependent cell densities, proliferation and death rates, as well as acini morphologies. Model simulations reveal apoptosis being necessary and sufficient for initiating lumen formation, but cell polarization being the pivotal mechanism for maintaining physiological epithelium morphology and acini sphericity. Furthermore, simulations highlight that acinus growth arrest in normal acini can be achieved by controlling the fraction of proliferating cells. Interestingly, our simulations reveal a synergism between polarization and apoptosis in enhancing growth arrest. After validating the model with experimental data from a normal human breast line (MCF10A), the system was challenged to predict the growth of MCF10A where AKT-1 was overexpressed, leading to reduced apoptosis. As previously reported, this led to non growth-arrested acini, with very large sizes and partially filled lumen. However, surprisingly, image analysis revealed a much lower nuclear density than observed for normal acini. The growth kinetics indicates that these acini grew faster than the cells comprising it. The in silico model could not replicate this behavior, contradicting the classic paradigm that ductal carcinoma in situ is only the result of high proliferation and low apoptosis. Our simulations suggest that overexpression of AKT-1 must also perturb cell-cell and cell-ECM communication, reminding us that extracellular context can dictate cellular behavior.

Analysing the robustness of cellular rhythms

Autonomous oscillations at the cellular level are important for various timing and signalling functions. The rhythms depend on environmental influences in a specific manner. In particular, the period of some rhythms has been shown to be very robust to certain environmental factors whereas other rhythms show a high sensitivity towards these factors. It is discussed that the robustness of the systems towards environmental changes results from underlying design principles. However, a comparison of robustness properties of different rhythms is lacking. Here we analyse the sensitivity of the oscillatory period with respect to parameter variations in models describing oscillations in calcium signalling, glycolysis and the circadian system. By comparing models for the same and different rhythms it is shown that the sensitivity depends on the oscillatory mechanism rather than the details of the model description. In particular, we find models of calcium oscillations to be very sensitive, those for glycolytic oscillations intermediately sensitive and models for circadian rhythms very robust. The results are discussed with respect to the temperature dependency of the rhythms. The question of what impact design principles have on the robustness of an oscillator, is addressed more explicitly by a direct comparison of systems with positive and negative feedback regulation for various reaction chain lengths. We find that the systems with negative feedback are more robust than corresponding systems with positive feedback. An increase in the length of the reaction chain under regulation leads to a decrease in sensitivity.

Entrainment in a model of the mammalian circadian oscillator

To adapt the timing of processes regulated by the circadian clock to seasonally varying photoperiods, the phase relation between the circadian clock and dusk or dawn ("phase of entrainment") must be tightly adjusted. The authors use a mathematical model of the molecular mammalian circadian oscillator to investigate the influence of the free-running period (tau) and the shape of the PRC on the phase of entrainment. They find that a phase-dependent sensitivity ("gating") of light-induced period gene transcription enables a constant phase relation to dusk or dawn under different photoperiods. Depending on the freerunning period tau and on the shaping of the PRC by gating, the model circadian oscillator tracks either light onset or light offset under different photoperiods. The study indicates that the phase of entrainment of oscillating cells can be systematically controlled by regulating both gating and the free-running period tau.

Modeling feedback loops of the Mammalian circadian oscillator

The suprachiasmatic nucleus governs daily variations of physiology and behavior in mammals. Within single neurons, interlocked transcriptional/translational feedback loops generate circadian rhythms on the molecular level. We present a mathematical model that reflects the essential features of the mammalian circadian oscillator to characterize the differential roles of negative and positive feedback loops. The oscillations that are obtained have a 24-h period and are robust toward parameter variations even when the positive feedback is replaced by a constantly expressed activator. This demonstrates the crucial role of the negative feedback for rhythm generation. Moreover, it explains the rhythmic phenotype of Rev-erbalpha-/- mutant mice, where a positive feedback is missing. The interplay of negative and positive feedback reveals a complex dynamics. In particular, the model explains the unexpected rescue of circadian oscillations in Per2Brdm1/Cry2-/- double-mutant mice (Per2Brdm1 single-mutant mice are arrhythmic). Here, a decrease of positive feedback strength associated with mutating the Per2 gene is compensated by the Cry2-/- mutation that simultaneously decreases the negative feedback strength. Finally, this model leads us to a testable prediction of a molecular and behavioral phenotype: circadian oscillations should be rescued when arrhythmic Per2Brdm1 mutant mice are crossed with Rev- erbalpha -/- mutant mice.

A model of the mammalian circadian oscillator including the REV-ERBalpha module

Many cellular and physiological processes have been shown to display a rhythm of about 24 hours. This so-called circadian rhythm is based on a system of interlocked negative and positive molecular feedback loops. Here we extend a previous model of the circadian oscillator by including REV-ERBalpha as an additional component. This new model will allow us to investigate the function of an additional negative feedback loop via REV-ERBalpha. We obtain circadian oscillations with the correct period and phase relations between clock components. Parameter variations that correspond to clock-gene mutations reproduce experimental results: With parameter variations mimicking the Bmal1(-/-) and the Per2(Brdm1) mutation the oscillations cease to exist. In contrast, the system shows sustained oscillations if we use a parameter set that reflects the Rev-erbalpha mutation. The model also accounts for the differential effect of the Cry1(-/-) and Cry2(-/-) mutations on the circadian period. The simulations of the extended model indicate that the original model is robust with respect to the incorporation of the additional component. Depending on the kinetics of the Per2/Cry transcriptional activation by BMAL1, an increasing BMAL1 expression leads to either an increase or decrease of the clock period. This indicates that overexpression experiments could help to characterize the impact of BMAL1 on Per2/Cry transcription.