Biology subjects

Onuchic, J. N.

Publications and source records attributed to Onuchic, J. N..

44 records · Page 3Linked to original sources

bioRxiv2018

Walking along chromosomes with super-resolution imaging, contact maps, and integrative modeling

Chromosome structure is thought to be crucial for proper functioning of the nucleus. Here, we present a method for visualizing chromosomal DNA at super-resolution and then integrating Hi-C data to produce three-dimensional models of chromosome organization. We begin by applying Oligopaint probes and the single-molecule localization microscopy methods of OligoSTORM and OligoDNA-PAINT to image 8 megabases of human chromosome 19, discovering that chromosomal regions contributing to compartments can form distinct structures. Intriguingly, our data also suggest that homologous maternal and paternal regions may be differentially organized. Finally, we integrate imaging data with Hi-C and restraint-based modeling using a method called integrative modeling of genomic regions (IMGR) to increase the genomic resolution of our traces to 10 kb.\n\nOne Sentence SummarySuper-resolution genome tracing, contact maps, and integrative modeling enable 10 kb resolution glimpses of chromosome folding.

genetics↗

bioRxiv2018

A mechanism-based computational model to capture the interconnections among epithelial-mesenchymal transition, cancer stem cells and Notch-Jagged signaling

Epithelial-mesenchymal transition (EMT) and cancer stem cell formation (CSCs) are two fundamental and well-studied processes contributing to cancer metastasis and tumor relapse. Cells can undergo a partial EMT to attain a hybrid epithelial/mesenchymal (E/M) phenotype or a complete EMT to attain a mesenchymal one. Similarly, cells can reversibly gain or lose stemness. This plasticity in cell states is modulated by signaling pathways such as Notch. However, the interconnections among the cell states enabled by EMT, CSCs and Notch signaling remain elusive. Here, we devise a computational model to investigate the coupling among the core decision-making circuits for EMT, CSCs and the Notch pathway. Our model predicts that hybrid E/M cells are most likely to associate with stemness traits and exhibit enhanced Notch-Jagged signaling - a pathway that is implicated in therapeutic resistance. Further, we show that the position of the stemness window on the EMT axis is varied by altering the coupling strength between EMT and CSC circuits, and/or modulating Notch signaling. Finally, we analyze the gene expression profile of CSCs from several cancer types and observe a heterogeneous distribution along the EMT axis, suggesting that different subsets of CSCs may exist with varying phenotypes along the epithelial-mesenchymal plasticity axis. Our computational model offers insights into the complex EMT-stemness interplay and provides a platform to investigate the effects of therapeutic perturbations such as treatment with metformin, a common anti-diabetic drug that has been associated with decreased cancer incidence and increased lifespan of patients. Our mechanism-based model helps explain how metformin can both inhibit EMT and blunt the aggressive potential of CSCs simultaneously, by driving the cells out of a hybrid E/M stem-like state with enhanced Notch-Jagged signaling.

cancer biology↗

bioRxiv2018

PAGE4 and Conformational Switching: Insights from Molecular Dynamics Simulations and Implications for Prostate Cancer

Prostate-Associated Gene 4 (PAGE4) is a disordered protein implicated in the progression of prostate cancer. PAGE4 can be phosphorylated at two residue sites by Homeodomain-Interacting Protein Kinase 1 (HIPK1) to facilitate its binding to the Activator Protein-1 (AP-1) transcription factor. In contrast, a further hyperphosphorylation of PAGE4 by CDC-Like Kinase 2 (CLK2) reduces its binding affinity to AP-1, thus affecting the androgen receptor (AR) activity. Both SAXS and smFRET experiments have shown a structural expansion of PAGE4 upon hyperphosphorylation and a significant increase in size at its N-terminal half than that at its C-terminus. To understand the molecular mechanism underlying this structural transition, we performed a series of constant temperature molecular dynamics simulations using Atomistic AWSEM -- a multi-scale molecular model combining detailed atomistic and coarse-grained simulation approaches. Our simulations show that electrostatic interaction drives a transient formation of an N-terminal loop, which causes the change in size for different phosphorylated forms of PAGE4. Phosphorylation also changes the preference of secondary structure formation of PAGE4, which signifies a transition between states that display different degree of disorder. Finally, we construct a mechanism-based mathematical model that allows us to capture the interactions of different forms of PAGE4 with AP-1 and AR, a key therapeutic target in prostate cancer. Our model predicts intracellular oscillatory dynamics of HIPK1-PAGE4, CLK2-PAGE4 and AR activity, indicating phenotypic heterogeneity in an isogenic cell population. Thus, conformational switching among different forms of PAGE4 may potentially affect the efficiency of therapeutic targeting of AR.

biophysics↗

bioRxiv2017

RACIPE: A computational tool for Modeling Gene Regulatory Circuits using Randomization

MotivationOne of the major challenges in traditional mathematical modeling of gene regulatory circuits is the insufficient knowledge of kinetic parameters. These parameters are often inferred from existing experimental data and/or educated guesses, which can be time-consuming and error-prone, especially for large networks.\n\nResultsWe present a computational tool based on our newly developed method named random circuit perturbation (RACIPE), to explore the robust dynamical features of gene regulatory circuits without the requirement of detailed kinetic parameters. RACIPE generates an ensemble of circuit models with distinct random parameters and uniquely identifies robust dynamical properties by statistical analysis. Here, we discuss software implementation and illustrate the usage of RACIPE on coupled toggle-switch circuits and a published circuit of B-lymphopoiesis. We expect RACIPE to contribute to a more comprehensive and unbiased understanding of gene regulatory mechanisms.\n\nAvailabilityRACIPE is a free open source software distributed under (Apache 2.0) license and can be downloaded from GitHub (https://github.com/simonhb1990/RACIPE-1.0).\n\nContactMingyang.Lu@jax.org, Herbert.Levine@rice.edu or jonuchic@rice.edu

systems biology↗

bioRxiv2017

Numb prevents a complete EMT by modulating Notch signalling

Epithelial-Mesenchymal Transition (EMT) plays key roles during embryonic development, wound healing, and cancer metastasis. Cells in a partial EMT or hybrid epithelial/mesenchymal (E/M) phenotype tend to exhibit collective cell migration, forming clusters of circulating tumour cells - the primary drivers of metastasis. Activation of cell-cell signalling pathways such as Notch fosters a partial or complete EMT, yet the mechanisms enabling cluster formation remain poorly understood. Using an integrated computational-experimental approach, we examine the role of Numb - an inhibitor of Notch intercellular signalling - in mediating EMT and clusters formation of hybrid E/M cells. Knockdown of Numb in stable hybrid E/M cells H1975 results in a full EMT, thereby showing that Numb acts as a brake for a full EMT. Consistent with this observation, we show via a mathematical model that Numb inhibits a full EMT by stabilizing a hybrid E/M phenotype. Thus, Numb can behave as a phenotypic stability factor by modulating Notch-driven EMT. By generalizing the mathematical model to a multi-cell level, Numb is predicted to alter the balance of hybrid E/M versus mesenchymal cells in clusters, potentially resulting in a higher tumour-initiation ability. Finally, Numb correlates with a poor survival in multiple independent lung and ovarian cancer datasets, hence confirming its relationship with increased cancer aggressiveness.\n\nMajor Findings: we adopt an integrative computational-experimental approach to identify that Numb, an inhibitor of Notch signalling, can stabilize a hybrid epithelial/mesenchymal (E/M) phenotype. We show that knockdown of Numb in H1975 cells that display a stable hybrid E/M state is sufficient to destabilize a hybrid E/M state and push them to a full EMT phenotype. Next, we develop a mechanism-based mathematical model that recapitulates this ability of Numb in maintaining a hybrid E/M state, and predicts that Numb can alter the relative frequency of hybrid E/M and mesenchymal cells at a tissue level or in clusters of circulating tumor cells (CTCs) - the primary drivers of metastasis. Finally, we show that across cancer types, Numb correlates with worse patient survival, thus reinforcing the emerging notion that a hybrid E/M, but not necessarily a completely mesenchymal, phenotype associates with elevated tumour progression.

cancer biology↗

bioRxiv2017

De Novo Prediction of Human Chromosome Structures: Epigenetic Marking Patterns Encode Genome Architecture

Inside the cell nucleus, genomes fold into organized structures that are characteristic of cell type. Here, we show that this chromatin architecture can be predicted de novo using epigenetic data derived from ChIP-Seq. We exploit the idea that chromosomes encode a one-dimensional sequence of chromatin structural types. Interactions between these chromatin types determine the three-dimensional (3D) structural ensemble of chromosomes through a process similar to phase separation. First, a recurrent neural network is used to infer the relation between the epigenetic marks present at a locus, as assayed by ChIP-Seq, and the genomic compartment in which those loci reside, as measured by DNA-DNA proximity ligation (Hi-C). Next, types inferred from this neural network are used as an input to an energy landscape model for chromatin organization (MiChroM) in order to generate an ensemble of 3D chromosome conformations. After training the model, dubbed MEGABASE (Maximum Entropy Genomic Annotation from Biomarkers Associated to Structural Ensembles), on odd numbered chromosomes, we predict the chromatin type sequences and the subsequent 3D conformational ensembles for the even chromosomes. We validate these structural ensembles by using ChIP-Seq tracks alone to predict Hi-C maps as well as distances measured using 3D FISH experiments. Both sets of experiments support the hypothesis of phase separation being the driving process behind compartmentalization. These findings strongly suggest that epigenetic marking patterns encode sufficient information to determine the global architecture of chromosomes and that de novo structure prediction for whole genomes may be increasingly possible.

biophysics↗

bioRxiv2017

Guiding the design of bacterial signaling interactions using a coevolutionary landscape

The selection of amino acid identities that encode new interactions between two-component signaling (TCS) proteins remains a significant challenge. Recent work constructed a co-evolutionary landscape that can be used to select mutations to maintain signal transfer interactions between partner TCS proteins without introducing signal transfer between non-partners (crosstalk). A bigger challenge is to introduce mutations between non-natural partner TCS proteins using the landscape to enhance, suppress, or have a neutral effect on their basal signal transfer rates. This study focuses on the selection of mutations to a response regulator (RR) from Bacilus subtilis and its effect on phosphotransfer with a histidine kinase (HK) from Escherichia Coli. Twelve single-point mutations of the RR protein are selected from the landscape and experimentally expressed to directly test the theoretical predictions on the effect of signal transfer. Differential Scanning Calorimetry is used to monitor any protein stability effects caused by the mutations, which could be detrimental to proper protein function. Of these proteins, seven mutants successfully perturb phosphoryl transfer activity in the computationally predicted manner between the TCS proteins. Furthermore, brute-force exhaustive mutagenesis approaches indicate that only 1% of mutations result in enhanced activity. In comparison, of the six mutations predicted to enhance phosphotransfer, two mutations exhibit a significant enhancement while two mutations are comparable to the wild-type. Thus co-evolutionary landscape theory offers significant improvement over traditional large-scale mutational studies in the efficiency of selecting mutations for protein engineering and design.

bioinformatics↗

bioRxiv2017

Distinguishing Mechanisms Underlying EMT Tristability

BackgroundThe Epithelial-Mesenchymal Transition (EMT) endows epithelial-looking cells with enhanced migratory ability during embryonic development and tissue repair. EMT can also be co-opted by cancer cells to acquire metastatic potential and drug-resistance. Recent research has argued that epithelial (E) cells can undergo either a partial EMT to attain a hybrid epithelial/mesenchymal (E/M) phenotype that typically displays collective migration, or a complete EMT to adopt a mesenchymal (M) phenotype that shows individual migration. The core EMT regulatory network - miR-34/SNAIL/miR-200/ZEB1 - has been identified by various studies, but how this network regulates the transitions among the E, E/M, and M phenotypes remains controversial. Two major mathematical models - ternary chimera switch (TCS) and cascading bistable switches (CBS) - that both focus on the miR-34/SNAIL/miR-200/ZEB1 network, have been proposed to elucidate the EMT dynamics, but a detailed analysis of how well either or both of these two models can capture recent experimental observations about EMT dynamics remains to be done.\n\nResultsHere, via an integrated experimental and theoretical approach, we first show that both these two models can be used to understand the two-step transition of EMT - E[->]E/M[->]M, the different responses of SNAIL and ZEB1 to exogenous TGF-{beta} and the irreversibility of complete EMT. Next, we present new experimental results that tend to discriminate between these two models. We show that ZEB1 is present at intermediate levels in the hybrid E/M H1975 cells, and that in HMLE cells, overexpression of SNAIL is not sufficient to initiate EMT in the absence of ZEB1 and FOXC2.\n\nConclusionsThese experimental results argue in favor of the TCS model proposing that miR-200/ZEB1 behaves as a three-way decision-making switch enabling transitions among the E, hybrid E/M and M phenotypes.

cancer biology↗