Signaling pathways as linear transmitters

One challenge in biology is to make sense of the complexity of biological networks. A good system to approach this is signaling pathways, whose well-characterized molecular details allow us to relate the internal processes of each pathway to their input-output behavior. In this study, we analyzed mathematical models of three metazoan signaling pathways: the canonical Wnt, MAPK/ERK, and Tgfβ pathways. We find an unexpected convergence: the three pathways behave in some physiological contexts as linear signal transmitters. Testing the results experimentally, we present direct measurements of linear input-output behavior in the Wnt and ERK pathways. Analytics from each model further reveal that linearity arises through different means in each pathway, which we tested experimentally in the Wnt and ERK pathways. Linearity is a desired property in engineering where it facilitates fidelity and superposition in signal transmission. Our findings illustrate how cells tune different complex networks to converge on the same behavior

Signaling pathways as linear transmitters

One challenge in biology is to make sense of the complexity of biological networks. A good system to approach this is signaling pathways, whose well-characterized molecular details allow us to relate the internal processes of each pathway to their input-output behavior. In this study, we analyzed mathematical models of three metazoan signaling pathways: the canonical Wnt, MAPK/ERK, and Tgfβ pathways. We find an unexpected convergence: the three pathways behave in some physiological contexts as linear signal transmitters. Testing the results experimentally, we present direct measurements of linear input-output behavior in the Wnt and ERK pathways. Analytics from each model further reveal that linearity arises through different means in each pathway, which we tested experimentally in the Wnt and ERK pathways. Linearity is a desired property in engineering where it facilitates fidelity and superposition in signal transmission. Our findings illustrate how cells tune different complex networks to converge on the same behavior

Linearity in Cell Signaling Pathways

Accurate cellular communication is of paramount importance for the development, growth, and maintenance of multi-cellular organisms. Communication between cells is carried out by a highly conserved set of signaling pathways, whose dysregulation can lead to many diseases. The molecular details of these signaling pathways are now well-characterized, allowing researchers to investigate the emergent properties that arise from the complex signaling networks. These properties often arise from counter-intuitive or paradoxical mechanisms, meaning that systems-level analysis is necessary. Importantly, mathematical models have been constructed for many pathways that capture measured reaction rates and protein levels. These mathematical models successfully recapitulate dynamic responses of each pathway. Here, I investigated the input-output response of the Wnt, MAPK/ERK, and Tgfβ pathways using analytical and numerical treatment of mathematical models. Using this approach, I found that the distinct architectures of the three signaling pathways lead to a convergent behavior, linear input-output response. Specifically, mathematical analysis reveals that a futile cycle in the Wnt pathway, a kinase cascade coupled to feedback in the ERK pathway, and nucleocytoplasmic shuttling in the Tgfβ pathways all yield linear signal transmission. I then verified this finding experimentally in the Wnt and ERK pathways. For the Wnt pathway, direct measurements of the input-output response reveal that β-catenin is linear with respect to Wnt co-receptor LRP5/6 activity up until receptor saturation. For the ERK pathway, direct measurements indicate a linear relationship between phosphorylated ERK1/2 and the concentration of EGF ligand, up until saturation of ERK1/2. Finally, mathematical modeling reveals that linear response in the Wnt pathway, in conjunction with a recently identified cis-regulatory motif, is sufficient to explain gene expression buffering to perturbations. Therefore, this thesis demonstrates how linearity emerges across three dissimilar architectures, and introduces a novel benefit for linear signal transmission in biology.</p

Sensing relative signal in the Tgf-β/Smad pathway

How signaling pathways function reliably despite cellular variation remains a question in many systems. In the transforming growth factor-β (Tgf-β) pathway, exposure to ligand stimulates nuclear localization of Smad proteins, which then regulate target gene expression. Examining Smad3 dynamics in live reporter cells, we found evidence for fold-change detection. Although the level of nuclear Smad3 varied across cells, the fold change in the level of nuclear Smad3 was a more precise outcome of ligand stimulation. The precision of the fold-change response was observed throughout the signaling duration and across Tgf-β doses, and significantly increased the information transduction capacity of the pathway. Using single-molecule FISH, we further observed that expression of Smad3 target genes (ctgf, snai1, and wnt9a) correlated more strongly with the fold change, rather than the level, of nuclear Smad3. These findings suggest that some target genes sense Smad3 level relative to background, as a strategy for coping with cellular noise

Asymmetric Damage Segregation Constitutes an Emergent Population-Level Stress Response

Asymmetric damage segregation (ADS) is a mechanism for increasing population fitness through non-random, asymmetric partitioning of damaged macromolecules at cell division. ADS has been reported across multiple organisms, though the measured effects on fitness of individuals are often small. Here, we introduce a cell-lineage-based framework that quantifies the population-wide effects of ADS and then verify our results experimentally in E. coli under heat and antibiotic stress. Using an experimentally validated mathematical model, we find that the beneficial effect of ADS increases with stress. In effect, low-damage subpopulations divide faster and amplify within the population acting like a positive feedback loop whose strength scales with stress. Analysis of protein aggregates shows that the degree of asymmetric inheritance is damage dependent in single cells. Together our results indicate that, despite small effects in single cell, ADS exerts a strong beneficial effect on the population level and arises from the redistribution of damage within a population, through both single-cell and population-level feedback

Abstracts from the NIHR INVOLVE Conference 2017

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Genetic subtyping and phenotypic characterization of the immune microenvironment and MYC/BCL2 double expression reveal heterogeneity in diffuse large B-cell lymphoma

Purpose: Diffuse large B-cell lymphoma (DLBCL) is molecularly and clinically heterogeneous, and can be subtyped according to genetic alterations, B cell-of-origin or microenvironmental signatures using high-throughput genomic data at the DNA or RNA level. Although high-throughput proteomic profiling has not been available for DLBCL subtyping, MYC/BCL2 protein double-expression (DE) is an established prognostic biomarker in DLBCL. The purpose of this study is to reveal the relative prognostic roles of DLBCL genetic, phenotypic, and microenvironmental biomarkers. Experimental design: We performed targeted next-generation sequencing, immunohistochemistry for MYC, BCL2, and FN1, and fluorescent multiplex immunohistochemistry for microenvironmental markers in a large cohort of DLBCL. We performed correlative and prognostic analyses within and across DLBCL genetic subtypes and MYC/BCL2 double-expressors. Results: We found that MYC/BCL2 double-high-expression (DhE) had significant adverse prognostic impact within the EZB genetic subtype and LymphGen-unclassified DLBCL cases but not within MCD and ST2 genetic subtypes. Conversely, KMT2D mutations significantly stratified DhE but not non-DhE DLBCL. T-cell infiltration showed favorable prognostic effects within BN2, MCD, and DhE but unfavorable within ST2 and LymphGen-unclassified cases. FN1 and PD-1-high expression had significant adverse prognostic effects within multiple DLBCL genetic/phenotypic subgroups. The prognostic effects of DhE and immune biomarkers within DLBCL genetic subtypes were independent although DhE and high Ki-67 were significantly associated with lower T-cell infiltration in LymphGen-unclassified cases. Conclusions: Together, these results demonstrated independent and additive prognostic effects of phenotypic MYC/BCL2 and microenvironment biomarkers and genetic subtyping in DLBCL prognostication, important for improving DLBCL classification and identifying prognostic determinants and therapeutic targets