Literature DB >> 29248373

Resolving the Combinatorial Complexity of Smad Protein Complex Formation and Its Link to Gene Expression.

Philippe Lucarelli1, Marcel Schilling1, Clemens Kreutz2, Artyom Vlasov1, Martin E Boehm3, Nao Iwamoto1, Bernhard Steiert2, Susen Lattermann1, Marvin Wäsch1, Markus Stepath1, Matthias S Matter4, Mathias Heikenwälder5, Katrin Hoffmann6, Daniela Deharde7, Georg Damm8, Daniel Seehofer8, Maria Muciek9, Norbert Gretz9, Wolf D Lehmann10, Jens Timmer11, Ursula Klingmüller12.   

Abstract

Upon stimulation of cells with transforming growth factor β (TGF-β), Smad proteins form trimeric complexes and activate a broad spectrum of target genes. It remains unresolved which of the possible Smad complexes are formed in cellular contexts and how these contribute to gene expression. By combining quantitative mass spectrometry with a computational selection strategy, we predict and provide experimental evidence for the three most relevant Smad complexes in the mouse hepatoma cell line Hepa1-6. Utilizing dynamic pathway modeling, we specify the contribution of each Smad complex to the expression of representative Smad target genes, and show that these contributions are conserved in human hepatoma cell lines and primary hepatocytes. We predict, based on gene expression data of patient samples, increased amounts of Smad2/3/4 proteins and Smad2 phosphorylation as hallmarks of hepatocellular carcinoma and experimentally verify this prediction. Our findings demonstrate that modeling approaches can disentangle the complexity of transcription factor complex formation and its impact on gene expression.
Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  L1 regularization; Smad proteins and complexes; TGF-β signal transduction; dynamic pathway modeling; hepatocellular carcinoma; liver; mathematical modeling; quantitative mass spectrometry; regulation of gene expression; systems biology

Mesh:

Substances:

Year:  2017        PMID: 29248373     DOI: 10.1016/j.cels.2017.11.010

Source DB:  PubMed          Journal:  Cell Syst        ISSN: 2405-4712            Impact factor:   10.304


  21 in total

Review 1.  Specificity, versatility, and control of TGF-β family signaling.

Authors:  Rik Derynck; Erine H Budi
Journal:  Sci Signal       Date:  2019-02-26       Impact factor: 8.192

2.  The context-dependent, combinatorial logic of BMP signaling.

Authors:  Heidi E Klumpe; Matthew A Langley; James M Linton; Christina J Su; Yaron E Antebi; Michael B Elowitz
Journal:  Cell Syst       Date:  2022-04-13       Impact factor: 11.091

3.  Identification and Profiling of Environmental Chemicals That Inhibit the TGFβ/SMAD Signaling Pathway.

Authors:  Zhengxi Wei; Srilatha Sakamuru; Li Zhang; Jinghua Zhao; Ruili Huang; Nicole C Kleinstreuer; Yanling Chen; Yan Shu; Thomas B Knudsen; Menghang Xia
Journal:  Chem Res Toxicol       Date:  2019-11-11       Impact factor: 3.739

4.  Using Regularization to Infer Cell Line Specificity in Logical Network Models of Signaling Pathways.

Authors:  Sébastien De Landtsheer; Philippe Lucarelli; Thomas Sauter
Journal:  Front Physiol       Date:  2018-05-22       Impact factor: 4.566

5.  Perturbation biology links temporal protein changes to drug responses in a melanoma cell line.

Authors:  Elin Nyman; Richard R Stein; Xiaohong Jing; Weiqing Wang; Benjamin Marks; Ioannis K Zervantonakis; Anil Korkut; Nicholas P Gauthier; Chris Sander
Journal:  PLoS Comput Biol       Date:  2020-07-15       Impact factor: 4.475

6.  Loss-of-Function in SMAD4 Might Not Be Critical for Human Natural Killer Cell Responsiveness to TGF-β.

Authors:  Lachlan P Healy; Gustavo R Rossi; Jai Rautela; Charlotte A Slade; Nicholas D Huntington; Ingrid M Winship; Fernando Souza-Fonseca-Guimaraes
Journal:  Front Immunol       Date:  2019-05-01       Impact factor: 7.561

7.  Modeling cell line-specific recruitment of signaling proteins to the insulin-like growth factor 1 receptor.

Authors:  Keesha E Erickson; Oleksii S Rukhlenko; Md Shahinuzzaman; Kalina P Slavkova; Yen Ting Lin; Ryan Suderman; Edward C Stites; Marian Anghel; Richard G Posner; Dipak Barua; Boris N Kholodenko; William S Hlavacek
Journal:  PLoS Comput Biol       Date:  2019-01-17       Impact factor: 4.475

8.  Systemic network analysis identifies XIAP and IκBα as potential drug targets in TRAIL resistant BRAF mutated melanoma.

Authors:  Greta Del Mistro; Philippe Lucarelli; Ines Müller; Sébastien De Landtsheer; Anna Zinoveva; Meike Hutt; Martin Siegemund; Roland E Kontermann; Stefan Beissert; Thomas Sauter; Dagmar Kulms
Journal:  NPJ Syst Biol Appl       Date:  2018-11-05

9.  JNK regulates muscle remodeling via myostatin/SMAD inhibition.

Authors:  Sarah J Lessard; Tara L MacDonald; Prerana Pathak; Myoung Sook Han; Vernon G Coffey; Johann Edge; Donato A Rivas; Michael F Hirshman; Roger J Davis; Laurie J Goodyear
Journal:  Nat Commun       Date:  2018-08-02       Impact factor: 14.919

10.  The transcriptional regulator ZNF398 mediates pluripotency and epithelial character downstream of TGF-beta in human PSCs.

Authors:  Irene Zorzan; Marco Pellegrini; Mattia Arboit; Danny Incarnato; Mara Maldotti; Mattia Forcato; Guidantonio Malagoli Tagliazucchi; Elena Carbognin; Marco Montagner; Salvatore Oliviero; Graziano Martello
Journal:  Nat Commun       Date:  2020-05-12       Impact factor: 14.919

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