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Tong J, Ji B, Gao YH, Lin H, Ping F, Chen F, Liu XB. Sirt6 regulates autophagy in AGE-treated endothelial cells via KLF4. Nutr Metab Cardiovasc Dis 2022; 32:755-764. [PMID: 35123854 DOI: 10.1016/j.numecd.2021.12.020] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 12/13/2021] [Accepted: 12/20/2021] [Indexed: 02/07/2023]
Abstract
BACKGROUND AND AIMS High glucose and its byproducts are important factors causing dysfunction of endothelial cells. Autophagy is critical for endothelial cellular homeostasis. However, the specific molecular mechanism of how autophagy is regulated in endothelial cells under high-glucose condition remains unknown. We aim to explore the role Sirt6 plays in regulating autophagy in AGE-treated endothelial cells and how this function is exerted via KLF4. METHODS AND RESULTS Our results indicate that autophagy level increased in AGE-treated endothelial cells alongside with higher Sirt6 and KLF4 expression level. What's more, knock-in of Sirt6 by adenovirus led to augmented autophagy level while knockdown of Sirt6 led to the opposite. We also verified that Sirt6 affected KLF4 expression positively but KLF4 didn't influence Sirt6 expression level while knocking out of KLF4 impaired Sirt6-enhanced autophagy. Finally we found that STZ-induced diabetic mice showed more autophagosomes in endothelium and Sirt6 knockdown by adeno-associated virus reduced the number of autophagosomes. Knockdown of Sirt6 also caused impaired endothelium integrity but echocardiography indicated there were no significant functional differences. CONCLUSION Our research reveals more about how Sirt6 regulates autophagy in endothelial cells under high-glucose simulated condition and provides further insight into the relationships between Sirt6 and KLF4.
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Affiliation(s)
- Jing Tong
- Department of Cardiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Bing Ji
- Department of Cardiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Yan-Hua Gao
- Department of Cardiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Hao Lin
- Department of Cardiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Fan Ping
- Department of Cardiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Fei Chen
- Department of Cardiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China.
| | - Xue-Bo Liu
- Department of Cardiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China.
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Using semantics to scale up evidence-based chemical risk-assessments. PLoS One 2021; 16:e0260712. [PMID: 34910747 PMCID: PMC8673667 DOI: 10.1371/journal.pone.0260712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Accepted: 11/15/2021] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND The manual processes used for risk assessments are not scaling to the amount of data available. Although automated approaches appear promising, they must be transparent in a public policy setting. OBJECTIVE Our goal is to create an automated approach that moves beyond retrieval to the extraction step of the information synthesis process, where evidence is characterized as supporting, refuting, or neutral with respect to a given outcome. METHODS We combine knowledge resources and natural language processing to resolve coordinated ellipses and thus avoid surface level differences between concepts in an ontology and outcomes in an abstract. As with a systematic review, the search criterion, and inclusion and exclusion criterion are explicit. RESULTS The system scales to 482K abstracts on 27 chemicals. Results for three endpoints that are critical for cancer risk assessments show that refuting evidence (where the outcome decreased) was higher for cell proliferation (45.9%), and general cell changes (37.7%) than for cell death (25.0%). Moreover, cell death was the only end point where supporting claims were the majority (61.3%). If the number of abstracts that measure an outcome was used as a proxy for association there would be a stronger association with cell proliferation than cell death (20/27 chemicals). However, if the amount of supporting evidence was used (where the outcome increased) the conclusion would change for 21/27 chemicals (20 from proliferation to death and 1 from death to proliferation). CONCLUSIONS We provide decision makers with a visual representation of supporting, neutral, and refuting evidence whilst maintaining the reproducibility and transparency needed for public policy. Our findings show that results from the retrieval step where the number of abstracts that measure an outcome are reported can be misleading if not accompanied with results from the extraction step where the directionality of the outcome is established.
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Touré V, Flobak Å, Niarakis A, Vercruysse S, Kuiper M. The status of causality in biological databases: data resources and data retrieval possibilities to support logical modeling. Brief Bioinform 2021; 22:bbaa390. [PMID: 33378765 PMCID: PMC8294520 DOI: 10.1093/bib/bbaa390] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Revised: 11/26/2020] [Accepted: 11/27/2020] [Indexed: 12/16/2022] Open
Abstract
Causal molecular interactions represent key building blocks used in computational modeling, where they facilitate the assembly of regulatory networks. Logical regulatory networks can be used to predict biological and cellular behaviors by system perturbations and in silico simulations. Today, broad sets of causal interactions are available in a variety of biological knowledge resources. However, different visions, based on distinct biological interests, have led to the development of multiple ways to describe and annotate causal molecular interactions. It can therefore be challenging to efficiently explore various resources of causal interaction and maintain an overview of recorded contextual information that ensures valid use of the data. This review lists the different types of public resources with causal interactions, the different views on biological processes that they represent, the various data formats they use for data representation and storage, and the data exchange and conversion procedures that are available to extract and download these interactions. This may further raise awareness among the targeted audience, i.e. logical modelers and other scientists interested in molecular causal interactions, but also database managers and curators, about the abundance and variety of causal molecular interaction data, and the variety of tools and approaches to convert them into one interoperable resource.
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Affiliation(s)
- Vasundra Touré
- Department of Biology of the Norwegian University of Science and Technology
| | | | - Anna Niarakis
- Department of Biology, Univ Evry, University of Paris-Saclay, affiliated with the laboratory GenHotel in Genopole campus, and a delegate at the Lifeware Group, INRIA Saclay
| | - Steven Vercruysse
- Researcher in computer science and computational biology and focuses on building a bridge between human and computer understanding
| | - Martin Kuiper
- systems biology at the Department of Biology of the Norwegian University of Science and Technology
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Talikka M, Belcastro V, Boué S, Marescotti D, Hoeng J, Peitsch MC. Applying Systems Toxicology Methods to Drug Safety. SYSTEMS MEDICINE 2021. [DOI: 10.1016/b978-0-12-801238-3.11522-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
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5
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Madan S, Szostak J, Komandur Elayavilli R, Tsai RTH, Ali M, Qian L, Rastegar-Mojarad M, Hoeng J, Fluck J. The extraction of complex relationships and their conversion to biological expression language (BEL) overview of the BioCreative VI (2017) BEL track. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2020; 2019:5585579. [PMID: 31603193 PMCID: PMC6787548 DOI: 10.1093/database/baz084] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/27/2018] [Revised: 05/22/2019] [Accepted: 05/31/2019] [Indexed: 01/12/2023]
Abstract
Knowledge of the molecular interactions of biological and chemical entities and their involvement in biological processes or clinical phenotypes is important for data interpretation. Unfortunately, this knowledge is mostly embedded in the literature in such a way that it is unavailable for automated data analysis procedures. Biological expression language (BEL) is a syntax representation allowing for the structured representation of a broad range of biological relationships. It is used in various situations to extract such knowledge and transform it into BEL networks. To support the tedious and time-intensive extraction work of curators with automated methods, we developed the BEL track within the framework of BioCreative Challenges. Within the BEL track, we provide training data and an evaluation environment to encourage the text mining community to tackle the automatic extraction of complex BEL relationships. In 2017 BioCreative VI, the 2015 BEL track was repeated with new test data. Although only minor improvements in text snippet retrieval for given statements were achieved during this second BEL task iteration, a significant increase of BEL statement extraction performance from provided sentences could be seen. The best performing system reached a 32% F-score for the extraction of complete BEL statements and with the given named entities this increased to 49%. This time, besides rule-based systems, new methods involving hierarchical sequence labeling and neural networks were applied for BEL statement extraction.
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Affiliation(s)
- Sumit Madan
- Fraunhofer Institute for Algorithms and Scientific Computing, Schloss Birlinghoven, 53754 Sankt Augustin, Germany
| | - Justyna Szostak
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchatel, Switzerland
| | | | - Richard Tzong-Han Tsai
- Department of Computer Science and Information Engineering, National Central University, Taiwan, R.O.C., Taiwan 320
| | - Mehdi Ali
- Friedrich Wilhelm University of Bonn, 53012 Bonn, Germany
| | - Longhua Qian
- NLP Lab, School of Computer Science and Technology, Soochow University, Suzhou, 215006 Suzhou, China
| | - Majid Rastegar-Mojarad
- Department of Health Sciences Research, Mayo Clinic, 200 First St. SW, Rochester, MN 55905, USA
| | - Julia Hoeng
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchatel, Switzerland
| | - Juliane Fluck
- Fraunhofer Institute for Algorithms and Scientific Computing, Schloss Birlinghoven, 53754 Sankt Augustin, Germany
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Martin F, Gubian S, Talikka M, Hoeng J, Peitsch MC. NPA: an R package for computing network perturbation amplitudes using gene expression data and two-layer networks. BMC Bioinformatics 2019; 20:451. [PMID: 31481014 PMCID: PMC6724309 DOI: 10.1186/s12859-019-3016-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2018] [Accepted: 07/31/2019] [Indexed: 02/06/2023] Open
Abstract
Background High-throughput gene expression technologies provide complex datasets reflecting mechanisms perturbed in an experiment, typically in a treatment versus control design. Analysis of these information-rich data can be guided based on a priori knowledge, such as networks of related proteins or genes. Assessing the response of a specific mechanism and investigating its biological basis is extremely important in systems toxicology; as compounds or treatment need to be assessed with respect to a predefined set of key mechanisms that could lead to toxicity. Two-layer networks are suitable for this task, and a robust computational methodology specifically addressing those needs was previously published. The NPA package (https://github.com/philipmorrisintl/NPA) implements the algorithm, and a data package of eight two-layer networks representing key mechanisms, such as xenobiotic metabolism, apoptosis, or epithelial immune innate activation, is provided. Results Gene expression data from an animal study are analyzed using the package and its network models. The functionalities are implemented using R6 classes, making the use of the package seamless and intuitive. The various network responses are analyzed using the leading node analysis, and an overall perturbation, called the Biological Impact Factor, is computed. Conclusions The NPA package implements the published network perturbation amplitude methodology and provides a set of two-layer networks encoded in the Biological Expression Language.
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Affiliation(s)
- Florian Martin
- PMI R&D, Philip Morris Products S.A, Quai Jeanrenaud 5, CH-2000, Neuchâtel, Switzerland.
| | - Sylvain Gubian
- PMI R&D, Philip Morris Products S.A, Quai Jeanrenaud 5, CH-2000, Neuchâtel, Switzerland
| | - Marja Talikka
- PMI R&D, Philip Morris Products S.A, Quai Jeanrenaud 5, CH-2000, Neuchâtel, Switzerland
| | - Julia Hoeng
- PMI R&D, Philip Morris Products S.A, Quai Jeanrenaud 5, CH-2000, Neuchâtel, Switzerland
| | - Manuel C Peitsch
- PMI R&D, Philip Morris Products S.A, Quai Jeanrenaud 5, CH-2000, Neuchâtel, Switzerland
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7
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Yepiskoposyan H, Talikka M, Vavassori S, Martin F, Sewer A, Gubian S, Luettich K, Peitsch MC, Hoeng J. Construction of a Suite of Computable Biological Network Models Focused on Mucociliary Clearance in the Respiratory Tract. Front Genet 2019; 10:87. [PMID: 30828347 PMCID: PMC6384416 DOI: 10.3389/fgene.2019.00087] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2018] [Accepted: 01/29/2019] [Indexed: 11/13/2022] Open
Abstract
Mucociliary clearance (MCC), considered as a collaboration of mucus secreted from goblet cells, the airway surface liquid layer, and the beating of cilia of ciliated cells, is the airways’ defense system against airborne contaminants. Because the process is well described at the molecular level, we gathered the available information into a suite of comprehensive causal biological network (CBN) models. The suite consists of three independent models that represent (1) cilium assembly, (2) ciliary beating, and (3) goblet cell hyperplasia/metaplasia and that were built in the Biological Expression Language, which is both human-readable and computable. The network analysis of highly connected nodes and pathways demonstrated that the relevant biology was captured in the MCC models. We also show the scoring of transcriptomic data onto these network models and demonstrate that the models capture the perturbation in each dataset accurately. This work is a continuation of our approach to use computational biological network models and mathematical algorithms that allow for the interpretation of high-throughput molecular datasets in the context of known biology. The MCC network model suite can be a valuable tool in personalized medicine to further understand heterogeneity and individual drug responses in complex respiratory diseases.
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Affiliation(s)
| | - Marja Talikka
- PMI R&D, Philip Morris Products S.A., Neuchâtel, Switzerland
| | | | - Florian Martin
- PMI R&D, Philip Morris Products S.A., Neuchâtel, Switzerland
| | - Alain Sewer
- PMI R&D, Philip Morris Products S.A., Neuchâtel, Switzerland
| | - Sylvain Gubian
- PMI R&D, Philip Morris Products S.A., Neuchâtel, Switzerland
| | - Karsta Luettich
- PMI R&D, Philip Morris Products S.A., Neuchâtel, Switzerland
| | | | - Julia Hoeng
- PMI R&D, Philip Morris Products S.A., Neuchâtel, Switzerland
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8
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Liu S, Cheng W, Qian L, Zhou G. Combining relation extraction with function detection for BEL statement extraction. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2019; 2019:5277249. [PMID: 30624649 PMCID: PMC6323300 DOI: 10.1093/database/bay133] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/01/2018] [Accepted: 11/26/2018] [Indexed: 11/29/2022]
Abstract
The BioCreative-V community proposed a challenging task of automatic extraction of causal relation network in Biological Expression Language (BEL) from the biomedical literature. Previous studies on this task largely used models induced from other related tasks and then transformed intermediate structures to BEL statements, which left the given training corpus unexplored. To make full use of the BEL training corpus, in this work, we propose a deep learning-based approach to extract BEL statements. Specifically, we decompose the problem into two subtasks: entity relation extraction and entity function detection. First, two attention-based bidirectional long short-term memory networks models are used to extract entity relation and entity function, respectively. Then entity relation and their functions are combined into a BEL statement. In order to boost the overall performance, a strategy of threshold filtering is applied to improve the precision of identified entity functions. We evaluate our approach on the BioCreative-V Track 4 corpus with or without gold entities. The experimental results show that our method achieves the state-of-the-art performance with an overall F1-measure of 46.9% in stage 2 and 21.3% in stage 1, respectively.
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Affiliation(s)
- Suwen Liu
- School of Computer Science and Technology, Soochow University, Suzhou, China
| | - Wei Cheng
- School of Computer Science and Technology, Soochow University, Suzhou, China
| | - Longhua Qian
- School of Computer Science and Technology, Soochow University, Suzhou, China
| | - Guodong Zhou
- School of Computer Science and Technology, Soochow University, Suzhou, China
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9
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Titz B, Kogel U, Martin F, Schlage WK, Xiang Y, Nury C, Dijon S, Baumer K, Peric D, Bornand D, Dulize R, Phillips B, Leroy P, Vuillaume G, Lebrun S, Elamin A, Guedj E, Trivedi K, Ivanov NV, Vanscheeuwijck P, Peitsch MC, Hoeng J. A 90-day OECD TG 413 rat inhalation study with systems toxicology endpoints demonstrates reduced exposure effects of the aerosol from the carbon heated tobacco product version 1.2 (CHTP1.2) compared with cigarette smoke. II. Systems toxicology assessment. Food Chem Toxicol 2018; 115:284-301. [PMID: 29545142 DOI: 10.1016/j.fct.2018.02.058] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2017] [Accepted: 02/27/2018] [Indexed: 12/11/2022]
Abstract
Modified risk tobacco products (MRTPs) have the potential to reduce smoking-related health risks. The Carbon Heated Tobacco Product 1.2 (CHTP1.2) is a potential MRTP that uses a pressed carbon heat source to generate an aerosol by heating tobacco. Here, we report the results from the systems toxicology arm of a 90-day rat inhalation study (OECD test guideline 413) to assess the effects of CHTP1.2 aerosol compared with cigarette smoke (CS). Transcriptomics, proteomics, and lipidomics analyses complemented the standard endpoints. In the respiratory nasal epithelium, CS induced an adaptive tissue and inflammatory response, which was much weaker after CHTP1.2 aerosol exposure, mostly limited to the highest CHTP1.2 concentration (at twice the 3R4F CS concentration: 50 vs. 23 μg nicotine/L), in female rats. In the lungs, the effects of CS exposure included inflammatory and cellular stress responses, which were absent or much lower after CHTP1.2 aerosol exposure. Outside of the respiratory tract, CS and CHTP1.2 aerosol induced effects that were previously associated with exposure to any nicotine-containing aerosol, e.g., lower lipid concentrations in serum. Overall, this systems toxicology analysis complements and confirms the results from classical toxicological endpoints and further suggests potentially reduced respiratory health risks of CHTP1.2.
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Affiliation(s)
- Bjoern Titz
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000, Neuchatel, Switzerland(2)
| | - Ulrike Kogel
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000, Neuchatel, Switzerland(2)
| | - Florian Martin
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000, Neuchatel, Switzerland(2)
| | - Walter K Schlage
- Biology Consultant, Max-Baermann-Str. 21, 51429, Bergisch Gladbach, Germany
| | - Yang Xiang
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000, Neuchatel, Switzerland(2)
| | - Catherine Nury
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000, Neuchatel, Switzerland(2)
| | - Sophie Dijon
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000, Neuchatel, Switzerland(2)
| | - Karine Baumer
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000, Neuchatel, Switzerland(2)
| | - Dariusz Peric
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000, Neuchatel, Switzerland(2)
| | - David Bornand
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000, Neuchatel, Switzerland(2)
| | - Remi Dulize
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000, Neuchatel, Switzerland(2)
| | - Blaine Phillips
- PMI R&D, Philip Morris International Research Laboratories Pte. Ltd., Science Park II, Singapore(2)
| | - Patrice Leroy
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000, Neuchatel, Switzerland(2)
| | - Gregory Vuillaume
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000, Neuchatel, Switzerland(2)
| | - Stefan Lebrun
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000, Neuchatel, Switzerland(2)
| | - Ashraf Elamin
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000, Neuchatel, Switzerland(2)
| | - Emmanuel Guedj
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000, Neuchatel, Switzerland(2)
| | - Keyur Trivedi
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000, Neuchatel, Switzerland(2)
| | - Nikolai V Ivanov
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000, Neuchatel, Switzerland(2)
| | - Patrick Vanscheeuwijck
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000, Neuchatel, Switzerland(2)
| | - Manuel C Peitsch
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000, Neuchatel, Switzerland(2)
| | - Julia Hoeng
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000, Neuchatel, Switzerland(2).
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10
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Iskandar AR, Titz B, Sewer A, Leroy P, Schneider T, Zanetti F, Mathis C, Elamin A, Frentzel S, Schlage WK, Martin F, Ivanov NV, Peitsch MC, Hoeng J. Systems toxicology meta-analysis of in vitro assessment studies: biological impact of a candidate modified-risk tobacco product aerosol compared with cigarette smoke on human organotypic cultures of the aerodigestive tract. Toxicol Res (Camb) 2017; 6:631-653. [PMID: 30090531 PMCID: PMC6062142 DOI: 10.1039/c7tx00047b] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2017] [Accepted: 05/26/2017] [Indexed: 12/22/2022] Open
Abstract
Systems biology combines comprehensive molecular analyses with quantitative modeling to understand the characteristics of a biological system as a whole. Leveraging a similar approach, systems toxicology aims to decipher complex biological responses following exposures. This work reports a systems toxicology meta-analysis in the context of in vitro assessment of a candidate modified-risk tobacco product (MRTP) using three human organotypic cultures of the aerodigestive tract (buccal, bronchial, and nasal epithelia). Complementing a series of functional measures, a causal network enrichment analysis of transcriptomic data was used to compare quantitatively the biological impact of aerosol from the Tobacco Heating System (THS) 2.2, a candidate MRTP, with 3R4F cigarette smoke (CS) at similar nicotine concentrations. Lower toxicity was observed in all cultures following exposure to THS2.2 aerosol compared with 3R4F CS. Because of their morphological differences, a smaller exposure impact was observed in the buccal (stratified epithelium) compared with the bronchial and nasal (pseudostratified epithelium). However, the causal network enrichment approach supported a similar mechanistic impact of CS across the three cultures, including the impact on xenobiotic, oxidative stress, and inflammatory responses. At comparable nicotine concentrations, THS2.2 aerosol elicited reduced and more transient effects on these processes. To demonstrate the benefits of additional data modalities, we employed a newly established targeted mass-spectrometry marker panel to further confirm the reduced cellular stress responses elicited by THS2.2 aerosol compared with 3R4F CS in the nasal culture. Overall, this work demonstrates the applicability and robustness of the systems toxicology approach for in vitro inhalation toxicity assessment.
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Affiliation(s)
- A R Iskandar
- PMI R&D , Philip Morris Products S.A. (part of the Philip Morris International group of companies) , Quai Jeanrenaud 5 , CH-2000 Neuchâtel , Switzerland . ; ; Tel: +41 (58)242 2214
| | - B Titz
- PMI R&D , Philip Morris Products S.A. (part of the Philip Morris International group of companies) , Quai Jeanrenaud 5 , CH-2000 Neuchâtel , Switzerland . ; ; Tel: +41 (58)242 2214
| | - A Sewer
- PMI R&D , Philip Morris Products S.A. (part of the Philip Morris International group of companies) , Quai Jeanrenaud 5 , CH-2000 Neuchâtel , Switzerland . ; ; Tel: +41 (58)242 2214
| | - P Leroy
- PMI R&D , Philip Morris Products S.A. (part of the Philip Morris International group of companies) , Quai Jeanrenaud 5 , CH-2000 Neuchâtel , Switzerland . ; ; Tel: +41 (58)242 2214
| | - T Schneider
- PMI R&D , Philip Morris Products S.A. (part of the Philip Morris International group of companies) , Quai Jeanrenaud 5 , CH-2000 Neuchâtel , Switzerland . ; ; Tel: +41 (58)242 2214
| | - F Zanetti
- PMI R&D , Philip Morris Products S.A. (part of the Philip Morris International group of companies) , Quai Jeanrenaud 5 , CH-2000 Neuchâtel , Switzerland . ; ; Tel: +41 (58)242 2214
| | - C Mathis
- PMI R&D , Philip Morris Products S.A. (part of the Philip Morris International group of companies) , Quai Jeanrenaud 5 , CH-2000 Neuchâtel , Switzerland . ; ; Tel: +41 (58)242 2214
| | - A Elamin
- PMI R&D , Philip Morris Products S.A. (part of the Philip Morris International group of companies) , Quai Jeanrenaud 5 , CH-2000 Neuchâtel , Switzerland . ; ; Tel: +41 (58)242 2214
| | - S Frentzel
- PMI R&D , Philip Morris Products S.A. (part of the Philip Morris International group of companies) , Quai Jeanrenaud 5 , CH-2000 Neuchâtel , Switzerland . ; ; Tel: +41 (58)242 2214
| | - W K Schlage
- Biology consultant , Max-Baermann-Str. 21 , 51429 Bergisch Gladbach , Germany
| | - F Martin
- PMI R&D , Philip Morris Products S.A. (part of the Philip Morris International group of companies) , Quai Jeanrenaud 5 , CH-2000 Neuchâtel , Switzerland . ; ; Tel: +41 (58)242 2214
| | - N V Ivanov
- PMI R&D , Philip Morris Products S.A. (part of the Philip Morris International group of companies) , Quai Jeanrenaud 5 , CH-2000 Neuchâtel , Switzerland . ; ; Tel: +41 (58)242 2214
| | - M C Peitsch
- PMI R&D , Philip Morris Products S.A. (part of the Philip Morris International group of companies) , Quai Jeanrenaud 5 , CH-2000 Neuchâtel , Switzerland . ; ; Tel: +41 (58)242 2214
| | - J Hoeng
- PMI R&D , Philip Morris Products S.A. (part of the Philip Morris International group of companies) , Quai Jeanrenaud 5 , CH-2000 Neuchâtel , Switzerland . ; ; Tel: +41 (58)242 2214
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11
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Talikka M, Martin F, Sewer A, Vuillaume G, Leroy P, Luettich K, Chaudhary N, Peck MJ, Peitsch MC, Hoeng J. Mechanistic Evaluation of the Impact of Smoking and Chronic Obstructive Pulmonary Disease on the Nasal Epithelium. CLINICAL MEDICINE INSIGHTS-CIRCULATORY RESPIRATORY AND PULMONARY MEDICINE 2017; 11:1179548417710928. [PMID: 28620266 PMCID: PMC5466113 DOI: 10.1177/1179548417710928] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2016] [Accepted: 04/04/2017] [Indexed: 12/27/2022]
Abstract
Chronic obstructive pulmonary disease (COPD) is one of the major causes of chronic morbidity and mortality worldwide. The development of markers of COPD onset is hampered by the lack of accessibility to the primary target tissue, and there is a need to consider other sample sources as surrogates for biomarker research. Airborne toxicants pass through the nasal epithelium before reaching the lower airways, and the similarity with bronchial histology makes it an attractive surrogate for lower airways. In this work, we describe the transcriptomics findings from the nasal epithelia of subjects enrolled in a clinical study focusing on the identification of COPD biomarkers. Transcriptomic data were analyzed using the biological network approach that enabled us to pinpoint the biological processes affected in the upper respiratory tract in response to smoking and mild-to-moderate COPD. Our results indicated that nasal and lower airway immune responses were considerably different in COPD subjects and caution should be exercised when using upper airway samples as a surrogate for the lower airway. Nevertheless, the network approach described here could present a sensitive means of identifying smokers at risk of developing COPD.
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Affiliation(s)
- Marja Talikka
- Philip Morris Products SA and Research & Development (R&D), Philip Morris International, Neuchâtel, Switzerland
| | - Florian Martin
- Philip Morris Products SA and Research & Development (R&D), Philip Morris International, Neuchâtel, Switzerland
| | - Alain Sewer
- Philip Morris Products SA and Research & Development (R&D), Philip Morris International, Neuchâtel, Switzerland
| | - Grégory Vuillaume
- Philip Morris Products SA and Research & Development (R&D), Philip Morris International, Neuchâtel, Switzerland
| | - Patrice Leroy
- Philip Morris Products SA and Research & Development (R&D), Philip Morris International, Neuchâtel, Switzerland
| | - Karsta Luettich
- Philip Morris Products SA and Research & Development (R&D), Philip Morris International, Neuchâtel, Switzerland
| | - Nveed Chaudhary
- Philip Morris Products SA and Research & Development (R&D), Philip Morris International, Neuchâtel, Switzerland
| | - Michael J Peck
- Philip Morris Products SA and Research & Development (R&D), Philip Morris International, Neuchâtel, Switzerland
| | - Manuel C Peitsch
- Philip Morris Products SA and Research & Development (R&D), Philip Morris International, Neuchâtel, Switzerland
| | - Julia Hoeng
- Philip Morris Products SA and Research & Development (R&D), Philip Morris International, Neuchâtel, Switzerland
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12
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Gonzalez-Suarez I, Marescotti D, Martin F, Scotti E, Guedj E, Acali S, Dulize R, Baumer K, Peric D, Frentzel S, Ivanov NV, Hoeng J, Peitsch MC. In Vitro Systems Toxicology Assessment of Nonflavored e-Cigarette Liquids in Primary Lung Epithelial Cells. ACTA ACUST UNITED AC 2017. [DOI: 10.1089/aivt.2016.0040] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Affiliation(s)
- Ignacio Gonzalez-Suarez
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland (part of Philip Morris International group of companies)
| | - Diego Marescotti
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland (part of Philip Morris International group of companies)
| | - Florian Martin
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland (part of Philip Morris International group of companies)
| | - Elena Scotti
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland (part of Philip Morris International group of companies)
| | - Emmanuel Guedj
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland (part of Philip Morris International group of companies)
| | - Stefano Acali
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland (part of Philip Morris International group of companies)
| | - Remi Dulize
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland (part of Philip Morris International group of companies)
| | - Karine Baumer
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland (part of Philip Morris International group of companies)
| | - Dariusz Peric
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland (part of Philip Morris International group of companies)
| | - Stefan Frentzel
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland (part of Philip Morris International group of companies)
| | - Nikolai V. Ivanov
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland (part of Philip Morris International group of companies)
| | - Julia Hoeng
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland (part of Philip Morris International group of companies)
| | - Manuel C. Peitsch
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland (part of Philip Morris International group of companies)
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13
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Szostak J, Martin F, Talikka M, Peitsch MC, Hoeng J. Semi-Automated Curation Allows Causal Network Model Building for the Quantification of Age-Dependent Plaque Progression in ApoE -/- Mouse. GENE REGULATION AND SYSTEMS BIOLOGY 2016; 10:95-103. [PMID: 27840576 PMCID: PMC5100841 DOI: 10.4137/grsb.s40031] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/26/2016] [Revised: 08/31/2016] [Accepted: 08/31/2016] [Indexed: 11/05/2022]
Abstract
The cellular and molecular mechanisms behind the process of atherosclerotic plaque destabilization are complex, and molecular data from aortic plaques are difficult to interpret. Biological network models may overcome these difficulties and precisely quantify the molecular mechanisms impacted during disease progression. The atherosclerosis plaque destabilization biological network model was constructed with the semiautomated curation pipeline, BELIEF. Cellular and molecular mechanisms promoting plaque destabilization or rupture were captured in the network model. Public transcriptomic data sets were used to demonstrate the specificity of the network model and to capture the different mechanisms that were impacted in ApoE-/- mouse aorta at 6 and 32 weeks. We concluded that network models combined with the network perturbation amplitude algorithm provide a sensitive, quantitative method to follow disease progression at the molecular level. This approach can be used to investigate and quantify molecular mechanisms during plaque progression.
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Affiliation(s)
- Justyna Szostak
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Florian Martin
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Marja Talikka
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Manuel C Peitsch
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Julia Hoeng
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
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14
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Wong ET, Kogel U, Veljkovic E, Martin F, Xiang Y, Boue S, Vuillaume G, Leroy P, Guedj E, Rodrigo G, Ivanov NV, Hoeng J, Peitsch MC, Vanscheeuwijck P. Evaluation of the Tobacco Heating System 2.2. Part 4: 90-day OECD 413 rat inhalation study with systems toxicology endpoints demonstrates reduced exposure effects compared with cigarette smoke. Regul Toxicol Pharmacol 2016; 81 Suppl 2:S59-S81. [DOI: 10.1016/j.yrtph.2016.10.015] [Citation(s) in RCA: 50] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2016] [Revised: 10/04/2016] [Accepted: 10/24/2016] [Indexed: 10/20/2022]
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15
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Evaluation of the Tobacco Heating System 2.2. Part 7: Systems toxicological assessment of a mentholated version revealed reduced cellular and molecular exposure effects compared with mentholated and non-mentholated cigarette smoke. Regul Toxicol Pharmacol 2016; 81 Suppl 2:S123-S138. [DOI: 10.1016/j.yrtph.2016.11.001] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2016] [Revised: 10/31/2016] [Accepted: 11/01/2016] [Indexed: 12/29/2022]
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16
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Namasivayam AA, Morales AF, Lacave ÁMF, Tallam A, Simovic B, Alfaro DG, Bobbili DR, Martin F, Androsova G, Shvydchenko I, Park J, Calvo JV, Hoeng J, Peitsch MC, Racero MGV, Biryukov M, Talikka M, Pérez MB, Rohatgi N, Díaz-Díaz N, Mandarapu R, Ruiz RA, Davidyan S, Narayanasamy S, Boué S, Guryanova S, Arbas SM, Menon S, Xiang Y. Community-Reviewed Biological Network Models for Toxicology and Drug Discovery Applications. GENE REGULATION AND SYSTEMS BIOLOGY 2016; 10:51-66. [PMID: 27429547 PMCID: PMC4944831 DOI: 10.4137/grsb.s39076] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/04/2016] [Revised: 03/31/2016] [Accepted: 04/12/2016] [Indexed: 12/13/2022]
Abstract
Biological network models offer a framework for understanding disease by describing the relationships between the mechanisms involved in the regulation of biological processes. Crowdsourcing can efficiently gather feedback from a wide audience with varying expertise. In the Network Verification Challenge, scientists verified and enhanced a set of 46 biological networks relevant to lung and chronic obstructive pulmonary disease. The networks were built using Biological Expression Language and contain detailed information for each node and edge, including supporting evidence from the literature. Network scoring of public transcriptomics data inferred perturbation of a subset of mechanisms and networks that matched the measured outcomes. These results, based on a computable network approach, can be used to identify novel mechanisms activated in disease, quantitatively compare different treatments and time points, and allow for assessment of data with low signal. These networks are periodically verified by the crowd to maintain an up-to-date suite of networks for toxicology and drug discovery applications.
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Affiliation(s)
| | - Aishwarya Alex Namasivayam
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Campus Belval, Esch-sur-Alzette, Luxembourg
| | | | | | - Aravind Tallam
- TWINCORE, Zentrum für Experimentelle und Klinische Infektionsforschung, Hannover, Germany
| | | | | | - Dheeraj Reddy Bobbili
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Campus Belval, Esch-sur-Alzette, Luxembourg
| | - Florian Martin
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud, Neuchâtel, Switzerland (part of Philip Morris International group of companies)
| | - Ganna Androsova
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Campus Belval, Esch-sur-Alzette, Luxembourg
| | - Irina Shvydchenko
- Kuban State University of Physical Education, Sport and Tourism, Krasnodar, Russia
| | | | - Jorge Val Calvo
- Center for Molecular Biology, “Severo Ochoa” – Spanish National Research Council, Madrid, Spain
| | - Julia Hoeng
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud, Neuchâtel, Switzerland (part of Philip Morris International group of companies)
| | - Manuel C. Peitsch
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud, Neuchâtel, Switzerland (part of Philip Morris International group of companies)
| | | | - Maria Biryukov
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Campus Belval, Esch-sur-Alzette, Luxembourg
| | - Marja Talikka
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud, Neuchâtel, Switzerland (part of Philip Morris International group of companies)
| | | | - Neha Rohatgi
- Center for Systems Biology, University of Iceland, Reykjavik, Iceland
| | | | - Rajesh Mandarapu
- Prakhya Research Laboratories, Lakshminagar, Selaiyur, Chennai, Tamil Nadu, India
| | | | - Sergey Davidyan
- Institute of Biochemical Physics Russian Academy of Sciences, Moscow, Russia
| | - Shaman Narayanasamy
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Campus Belval, Esch-sur-Alzette, Luxembourg
| | - Stéphanie Boué
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud, Neuchâtel, Switzerland (part of Philip Morris International group of companies)
| | - Svetlana Guryanova
- Institute of Bioorganic Chemistry Russian Academy of Sciences, Moscow, Russia
| | - Susana Martínez Arbas
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Campus Belval, Esch-sur-Alzette, Luxembourg
| | - Swapna Menon
- AnalyzeDat Consulting Services, Edapally Byepass Junction, Kochi, Kerala, India
| | - Yang Xiang
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud, Neuchâtel, Switzerland (part of Philip Morris International group of companies)
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17
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Rinaldi F, Ellendorff TR, Madan S, Clematide S, van der Lek A, Mevissen T, Fluck J. BioCreative V track 4: a shared task for the extraction of causal network information using the Biological Expression Language. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2016; 2016:baw067. [PMID: 27402677 PMCID: PMC4940434 DOI: 10.1093/database/baw067] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/24/2015] [Accepted: 04/11/2016] [Indexed: 12/27/2022]
Abstract
Automatic extraction of biological network information is one of the most desired and most complex tasks in biological and medical text mining. Track 4 at BioCreative V attempts to approach this complexity using fragments of large-scale manually curated biological networks, represented in Biological Expression Language (BEL), as training and test data. BEL is an advanced knowledge representation format which has been designed to be both human readable and machine processable. The specific goal of track 4 was to evaluate text mining systems capable of automatically constructing BEL statements from given evidence text, and of retrieving evidence text for given BEL statements. Given the complexity of the task, we designed an evaluation methodology which gives credit to partially correct statements. We identified various levels of information expressed by BEL statements, such as entities, functions, relations, and introduced an evaluation framework which rewards systems capable of delivering useful BEL fragments at each of these levels. The aim of this evaluation method is to help identify the characteristics of the systems which, if combined, would be most useful for achieving the overall goal of automatically constructing causal biological networks from text.
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Affiliation(s)
- Fabio Rinaldi
- Institute of Computational Linguistics, University of Zurich, Zurich, Switzerland
| | | | - Sumit Madan
- Fraunhofer Institute for Algorithms and Scientific Computing, Schloss Birlinghoven, Sankt Augustin, Germany
| | - Simon Clematide
- Institute of Computational Linguistics, University of Zurich, Zurich, Switzerland
| | - Adrian van der Lek
- Institute of Computational Linguistics, University of Zurich, Zurich, Switzerland
| | - Theo Mevissen
- Fraunhofer Institute for Algorithms and Scientific Computing, Schloss Birlinghoven, Sankt Augustin, Germany
| | - Juliane Fluck
- Fraunhofer Institute for Algorithms and Scientific Computing, Schloss Birlinghoven, Sankt Augustin, Germany
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18
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Goljanek-Whysall K, Iwanejko LA, Vasilaki A, Pekovic-Vaughan V, McDonagh B. Ageing in relation to skeletal muscle dysfunction: redox homoeostasis to regulation of gene expression. Mamm Genome 2016; 27:341-57. [PMID: 27215643 PMCID: PMC4935741 DOI: 10.1007/s00335-016-9643-x] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2016] [Accepted: 05/05/2016] [Indexed: 12/17/2022]
Abstract
Ageing is associated with a progressive loss of skeletal muscle mass, quality and function—sarcopenia, associated with reduced independence and quality of life in older generations. A better understanding of the mechanisms, both genetic and epigenetic, underlying this process would help develop therapeutic interventions to prevent, slow down or reverse muscle wasting associated with ageing. Currently, exercise is the only known effective intervention to delay the progression of sarcopenia. The cellular responses that occur in muscle fibres following exercise provide valuable clues to the molecular mechanisms regulating muscle homoeostasis and potentially the progression of sarcopenia. Redox signalling, as a result of endogenous generation of ROS/RNS in response to muscle contractions, has been identified as a crucial regulator for the adaptive responses to exercise, highlighting the redox environment as a potentially core therapeutic approach to maintain muscle homoeostasis during ageing. Further novel and attractive candidates include the manipulation of microRNA expression. MicroRNAs are potent gene regulators involved in the control of healthy and disease-associated biological processes and their therapeutic potential has been researched in the context of various disorders, including ageing-associated muscle wasting. Finally, we discuss the impact of the circadian clock on the regulation of gene expression in skeletal muscle and whether disruption of the peripheral muscle clock affects sarcopenia and altered responses to exercise. Interventions that include modifying altered redox signalling with age and incorporating genetic mechanisms such as circadian- and microRNA-based gene regulation, may offer potential effective treatments against age-associated sarcopenia.
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Affiliation(s)
- Katarzyna Goljanek-Whysall
- MRC-Arthritis Research UK Centre for Integrated research into Musculoskeletal Ageing (CIMA), Department of Musculoskeletal Biology, Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool, L7 8XL, UK.
| | - Lesley A Iwanejko
- MRC-Arthritis Research UK Centre for Integrated research into Musculoskeletal Ageing (CIMA), Department of Musculoskeletal Biology, Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool, L7 8XL, UK
| | - Aphrodite Vasilaki
- MRC-Arthritis Research UK Centre for Integrated research into Musculoskeletal Ageing (CIMA), Department of Musculoskeletal Biology, Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool, L7 8XL, UK
| | - Vanja Pekovic-Vaughan
- MRC-Arthritis Research UK Centre for Integrated research into Musculoskeletal Ageing (CIMA), Department of Musculoskeletal Biology, Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool, L7 8XL, UK
| | - Brian McDonagh
- MRC-Arthritis Research UK Centre for Integrated research into Musculoskeletal Ageing (CIMA), Department of Musculoskeletal Biology, Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool, L7 8XL, UK.
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19
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Rastegar-Mojarad M, Komandur Elayavilli R, Liu H. BELTracker: evidence sentence retrieval for BEL statements. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2016; 2016:baw079. [PMID: 27173525 PMCID: PMC4865361 DOI: 10.1093/database/baw079] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/04/2015] [Accepted: 04/22/2016] [Indexed: 01/09/2023]
Abstract
Biological expression language (BEL) is one of the main formal representation models of biological networks. The primary source of information for curating biological networks in BEL representation has been literature. It remains a challenge to identify relevant articles and the corresponding evidence statements for curating and validating BEL statements. In this paper, we describe BELTracker, a tool used to retrieve and rank evidence sentences from PubMed abstracts and full-text articles for a given BEL statement (per the 2015 task requirements of BioCreative V BEL Task). The system is comprised of three main components, (i) translation of a given BEL statement to an information retrieval (IR) query, (ii) retrieval of relevant PubMed citations and (iii) finding and ranking the evidence sentences in those citations. BELTracker uses a combination of multiple approaches based on traditional IR, machine learning, and heuristics to accomplish the task. The system identified and ranked at least one fully relevant evidence sentence in the top 10 retrieved sentences for 72 out of 97 BEL statements in the test set. BELTracker achieved a precision of 0.392, 0.532 and 0.615 when evaluated with three criteria, namely full, relaxed and context criteria, respectively, by the task organizers. Our team at Mayo Clinic was the only participant in this task. BELTracker is available as a RESTful API and is available for public use. Database URL:http://www.openbionlp.org:8080/BelTracker/finder/Given_BEL_Statement
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Affiliation(s)
- Majid Rastegar-Mojarad
- Department of Health Sciences Research, Mayo Clinic, USA University of Wisconsin-Milwaukee, Milwaukee, WI, USA
| | | | - Hongfang Liu
- Department of Health Sciences Research, Mayo Clinic, USA
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20
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Sun W, Bao J, Lin W, Gao H, Zhao W, Zhang Q, Leung CH, Ma DL, Lu J, Chen X. 2-Methoxy-6-acetyl-7-methyljuglone (MAM), a natural naphthoquinone, induces NO-dependent apoptosis and necroptosis by H2O2-dependent JNK activation in cancer cells. Free Radic Biol Med 2016; 92:61-77. [PMID: 26802903 DOI: 10.1016/j.freeradbiomed.2016.01.014] [Citation(s) in RCA: 57] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2015] [Revised: 01/01/2016] [Accepted: 01/19/2016] [Indexed: 12/12/2022]
Abstract
Redox signaling plays a fundamental role in maintaining cell physiological activities. A deregulation of this balance through oxidative stress or nitrosative stress has been implicated in cancer. Here, we reported that 2-methoxy-6-acetyl-7-methyl juglone (MAM), a natural naphthoquinone isolated from Polygonum cuspidatum Sieb. et Zucc, caused hydrogen peroxide (H2O2) dependent activation of JNK and induced the expression of inducible nitric oxide synthase (iNOS), thereby leading to nitric oxide (NO) generation in multiple cancer cells. Nitrosative stress induced necroptosis in A549 lung cancer cells, but resulted in caspase-dependent intrinsic apoptosis in B16-F10 melanoma and MCF7 breast cancer cells. In addition, a decrease in GSH/GSSG levels accompanied with increased ROS production was observed. Reversal of ROS generation and cell death in GSH pretreated cells indicated the involvement of GSH depletion in MAM mediated cytotoxicity. In summary, a natural product MAM induced NO-dependent multiple forms of cell death in cancer cells mediated by H2O2-dependent JNK activation in cancer cells. GSH depletion might play an initial role in MAM-induced cytotoxicity.
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Affiliation(s)
- Wen Sun
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao, China
| | - Jiaolin Bao
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao, China
| | - Wei Lin
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao, China
| | - Hongwei Gao
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao, China
| | - Wenwen Zhao
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao, China
| | - Qingwen Zhang
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao, China
| | - Chung-Hang Leung
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao, China
| | - Dik-Lung Ma
- Department of Chemistry, Hong Kong Baptist University, Kowloon Tong, Hong Kong
| | - Jinjian Lu
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao, China
| | - Xiuping Chen
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao, China.
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21
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Gonzalez-Suarez I, Martin F, Marescotti D, Guedj E, Acali S, Johne S, Dulize R, Baumer K, Peric D, Goedertier D, Frentzel S, Ivanov NV, Mathis C, Hoeng J, Peitsch MC. In Vitro Systems Toxicology Assessment of a Candidate Modified Risk Tobacco Product Shows Reduced Toxicity Compared to That of a Conventional Cigarette. Chem Res Toxicol 2015; 29:3-18. [DOI: 10.1021/acs.chemrestox.5b00321] [Citation(s) in RCA: 48] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Ignacio Gonzalez-Suarez
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Florian Martin
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Diego Marescotti
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Emmanuel Guedj
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Stefano Acali
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Stephanie Johne
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Remi Dulize
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Karine Baumer
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Dariusz Peric
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Didier Goedertier
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Stefan Frentzel
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Nikolai V. Ivanov
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Carole Mathis
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Julia Hoeng
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Manuel C. Peitsch
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
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22
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Kogel U, Gonzalez Suarez I, Xiang Y, Dossin E, Guy PA, Mathis C, Marescotti D, Goedertier D, Martin F, Peitsch MC, Hoeng J. Biological impact of cigarette smoke compared to an aerosol produced from a prototypic modified risk tobacco product on normal human bronchial epithelial cells. Toxicol In Vitro 2015; 29:2102-15. [PMID: 26277032 DOI: 10.1016/j.tiv.2015.08.004] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2015] [Revised: 07/10/2015] [Accepted: 08/10/2015] [Indexed: 01/09/2023]
Abstract
Cigarette smoking causes serious and fatal diseases. The best way for smokers to avoid health risks is to quit smoking. Using modified risk tobacco products (MRTPs) may be an alternative to reduce the harm caused for those who are unwilling to quit smoking, but little is known about the toxic effects of MRTPs, nor were the molecular mechanisms of toxicity investigated in detail. The toxicity of an MRTP and the potential molecular mechanisms involved were investigated in high-content screening tests and whole genome transcriptomics analyses using human bronchial epithelial cells. The prototypic (p)MRTP that was tested had less impact than reference cigarette 3R4F on the cellular oxidative stress response and cell death pathways. Higher pMRTP aerosol extract concentrations had impact on pathways associated with the detoxification of xenobiotics and the reduction of oxidative damage. A pMRTP aerosol concentration up to 18 times higher than the 3R4F caused similar perturbation effects in biological networks and led to the perturbation of networks related to cell stress, and proliferation biology. These results may further facilitate the development of a systems toxicology-based impact assessment for use in future risk assessments in line with the 21st century toxicology paradigm, as shown here for an MRTP.
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Affiliation(s)
- U Kogel
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.
| | - I Gonzalez Suarez
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.
| | - Y Xiang
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.
| | - E Dossin
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.
| | - P A Guy
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.
| | - C Mathis
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.
| | - D Marescotti
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.
| | - D Goedertier
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.
| | - F Martin
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.
| | - M C Peitsch
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.
| | - J Hoeng
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.
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23
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Iskandar AR, Xiang Y, Frentzel S, Talikka M, Leroy P, Kuehn D, Guedj E, Martin F, Mathis C, Ivanov NV, Peitsch MC, Hoeng J. Impact Assessment of Cigarette Smoke Exposure on Organotypic Bronchial Epithelial Tissue Cultures: A Comparison of Mono-Culture and Coculture Model Containing Fibroblasts. Toxicol Sci 2015; 147:207-21. [PMID: 26085348 PMCID: PMC4549394 DOI: 10.1093/toxsci/kfv122] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
Organotypic 3D cultures of epithelial cells are grown at the air-liquid interface (ALI) and resemble the in vivo counterparts. Although the complexity of in vivo cellular responses could be better manifested in coculture models in which additional cell types such as fibroblasts were incorporated, the presence of another cell type could mask the response of the other. This study reports the impact of whole cigarette smoke (CS) exposure on organotypic mono- and coculture models to evaluate the relevancy of organotypic models for toxicological assessment of aerosols. Two organotypic bronchial models were directly exposed to low and high concentrations of CS of the reference research cigarette 3R4F: monoculture of bronchial epithelial cells without fibroblasts (BR) and coculture with fibroblasts (BRF) models. Adenylate kinase (AK)-based cytotoxicity, cytochrome P450 (CYP) 1A1/1B1 activity, tissue histology, and concentrations of secreted mediators into the basolateral media, as well as transcriptomes were evaluated following the CS exposure. The results demonstrated similar impact of CS on the AK-based cytotoxicity, CYP1A1/1B1 activity, and tissue histology in both models. However, a greater number of secreted mediators was identified in the basolateral media of the monoculture than in the coculture models. Furthermore, annotation analysis and network-based systems biology analysis of the transcriptomic profiles indicated a more prominent cellular stress and tissue damage following CS in the monoculture epithelium model without fibroblasts. Finally, our results indicated that an in vivo smoking-induced xenobiotic metabolism response of bronchial epithelial cells was better reflected from the in vitro CS-exposed coculture model.
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Affiliation(s)
| | - Yang Xiang
- Philip Morris International R&D, 2000 Neuchâtel, Switzerland
| | - Stefan Frentzel
- Philip Morris International R&D, 2000 Neuchâtel, Switzerland
| | - Marja Talikka
- Philip Morris International R&D, 2000 Neuchâtel, Switzerland
| | - Patrice Leroy
- Philip Morris International R&D, 2000 Neuchâtel, Switzerland
| | - Diana Kuehn
- Philip Morris International R&D, 2000 Neuchâtel, Switzerland
| | - Emmanuel Guedj
- Philip Morris International R&D, 2000 Neuchâtel, Switzerland
| | - Florian Martin
- Philip Morris International R&D, 2000 Neuchâtel, Switzerland
| | - Carole Mathis
- Philip Morris International R&D, 2000 Neuchâtel, Switzerland
| | | | | | - Julia Hoeng
- Philip Morris International R&D, 2000 Neuchâtel, Switzerland
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24
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Phillips B, Esposito M, Verbeeck J, Boué S, Iskandar A, Vuillaume G, Leroy P, Krishnan S, Kogel U, Utan A, Schlage WK, Bera M, Veljkovic E, Hoeng J, Peitsch MC, Vanscheeuwijck P. Toxicity of aerosols of nicotine and pyruvic acid (separate and combined) in Sprague-Dawley rats in a 28-day OECD 412 inhalation study and assessment of systems toxicology. Inhal Toxicol 2015; 27:405-31. [PMID: 26295358 DOI: 10.3109/08958378.2015.1046000] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Toxicity of nebulized nicotine (Nic) and nicotine/pyruvic acid mixtures (Nic/Pyr) was characterized in a 28-day Organization for Economic Co-operation and Development 412 inhalation study with additional transcriptomic and lipidomic analyses. Sprague-Dawley rats were nose-only exposed, 6 h/day, 5 days/week to filtered air, saline, nicotine (50 µg/l), sodium pyruvate (NaPyr, 33.9 µg/l) or equimolar Nic/Pyr mixtures (18, 25 and 50 µg nicotine/l). Saline and NaPyr caused no health effects, but rats exposed to nicotine-containing aerosols had decreased body weight gains and concentration-dependent increases in liver weight. Blood neutrophil counts were increased and lymphocyte counts decreased in rats exposed to nicotine; activities of alkaline phosphatase and alanine aminotransferase were increased, and levels of cholesterol and glucose decreased. The only histopathologic finding in non-respiratory tract organs was increased liver vacuolation and glycogen content. Respiratory tract findings upon nicotine exposure (but also some phosphate-buffered saline aerosol effects) were observed only in the larynx and were limited to adaptive changes. Gene expression changes in the lung and liver were very weak. Nic and Nic/Pyr caused few significant changes (including Cyp1a1 gene upregulation). Changes were predominantly related to energy metabolism and fatty acid metabolism but did not indicate an obvious toxicity-related response. Nicotine exposure lowered plasma lipids, including cholesteryl ester (CE) and free cholesterol and, in the liver, phospholipids and sphingolipids. Nic, NaPyr and Nic/Pyr decreased hepatic triacylglycerol and CE. In the lung, Nic and Nic/Pyr increased CE levels. These data suggest that only minor biologic effects related to inhalation of Nic or Nic/Pyr aerosols were observed in this 28-day study.
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Affiliation(s)
- Blaine Phillips
- a Philip Morris International Research Laboratories Pte Ltd , Science Park II , Singapore and
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25
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Boué S, Talikka M, Westra JW, Hayes W, Di Fabio A, Park J, Schlage WK, Sewer A, Fields B, Ansari S, Martin F, Veljkovic E, Kenney R, Peitsch MC, Hoeng J. Causal biological network database: a comprehensive platform of causal biological network models focused on the pulmonary and vascular systems. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2015; 2015:bav030. [PMID: 25887162 PMCID: PMC4401337 DOI: 10.1093/database/bav030] [Citation(s) in RCA: 82] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2014] [Accepted: 03/09/2015] [Indexed: 01/28/2023]
Abstract
With the wealth of publications and data available, powerful and transparent computational approaches are required to represent measured data and scientific knowledge in a computable and searchable format. We developed a set of biological network models, scripted in the Biological Expression Language, that reflect causal signaling pathways across a wide range of biological processes, including cell fate, cell stress, cell proliferation, inflammation, tissue repair and angiogenesis in the pulmonary and cardiovascular context. This comprehensive collection of networks is now freely available to the scientific community in a centralized web-based repository, the Causal Biological Network database, which is composed of over 120 manually curated and well annotated biological network models and can be accessed at http://causalbionet.com. The website accesses a MongoDB, which stores all versions of the networks as JSON objects and allows users to search for genes, proteins, biological processes, small molecules and keywords in the network descriptions to retrieve biological networks of interest. The content of the networks can be visualized and browsed. Nodes and edges can be filtered and all supporting evidence for the edges can be browsed and is linked to the original articles in PubMed. Moreover, networks may be downloaded for further visualization and evaluation. Database URL:http://causalbionet.com
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Affiliation(s)
- Stéphanie Boué
- Philip Morris International R&D, Philip Morris Products S.A. Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland, Selventa, One Alewife Center, Cambridge, MA 02140, USA and Applied Dynamic Solutions, LLC, 220 Davidson Avenue, Suite 100, Somerset, NJ 08873, USA
| | - Marja Talikka
- Philip Morris International R&D, Philip Morris Products S.A. Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland, Selventa, One Alewife Center, Cambridge, MA 02140, USA and Applied Dynamic Solutions, LLC, 220 Davidson Avenue, Suite 100, Somerset, NJ 08873, USA
| | - Jurjen Willem Westra
- Philip Morris International R&D, Philip Morris Products S.A. Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland, Selventa, One Alewife Center, Cambridge, MA 02140, USA and Applied Dynamic Solutions, LLC, 220 Davidson Avenue, Suite 100, Somerset, NJ 08873, USA
| | - William Hayes
- Philip Morris International R&D, Philip Morris Products S.A. Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland, Selventa, One Alewife Center, Cambridge, MA 02140, USA and Applied Dynamic Solutions, LLC, 220 Davidson Avenue, Suite 100, Somerset, NJ 08873, USA
| | - Anselmo Di Fabio
- Philip Morris International R&D, Philip Morris Products S.A. Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland, Selventa, One Alewife Center, Cambridge, MA 02140, USA and Applied Dynamic Solutions, LLC, 220 Davidson Avenue, Suite 100, Somerset, NJ 08873, USA
| | - Jennifer Park
- Philip Morris International R&D, Philip Morris Products S.A. Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland, Selventa, One Alewife Center, Cambridge, MA 02140, USA and Applied Dynamic Solutions, LLC, 220 Davidson Avenue, Suite 100, Somerset, NJ 08873, USA
| | - Walter K Schlage
- Philip Morris International R&D, Philip Morris Products S.A. Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland, Selventa, One Alewife Center, Cambridge, MA 02140, USA and Applied Dynamic Solutions, LLC, 220 Davidson Avenue, Suite 100, Somerset, NJ 08873, USA
| | - Alain Sewer
- Philip Morris International R&D, Philip Morris Products S.A. Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland, Selventa, One Alewife Center, Cambridge, MA 02140, USA and Applied Dynamic Solutions, LLC, 220 Davidson Avenue, Suite 100, Somerset, NJ 08873, USA
| | - Brett Fields
- Philip Morris International R&D, Philip Morris Products S.A. Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland, Selventa, One Alewife Center, Cambridge, MA 02140, USA and Applied Dynamic Solutions, LLC, 220 Davidson Avenue, Suite 100, Somerset, NJ 08873, USA
| | - Sam Ansari
- Philip Morris International R&D, Philip Morris Products S.A. Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland, Selventa, One Alewife Center, Cambridge, MA 02140, USA and Applied Dynamic Solutions, LLC, 220 Davidson Avenue, Suite 100, Somerset, NJ 08873, USA
| | - Florian Martin
- Philip Morris International R&D, Philip Morris Products S.A. Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland, Selventa, One Alewife Center, Cambridge, MA 02140, USA and Applied Dynamic Solutions, LLC, 220 Davidson Avenue, Suite 100, Somerset, NJ 08873, USA
| | - Emilija Veljkovic
- Philip Morris International R&D, Philip Morris Products S.A. Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland, Selventa, One Alewife Center, Cambridge, MA 02140, USA and Applied Dynamic Solutions, LLC, 220 Davidson Avenue, Suite 100, Somerset, NJ 08873, USA
| | - Renee Kenney
- Philip Morris International R&D, Philip Morris Products S.A. Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland, Selventa, One Alewife Center, Cambridge, MA 02140, USA and Applied Dynamic Solutions, LLC, 220 Davidson Avenue, Suite 100, Somerset, NJ 08873, USA
| | - Manuel C Peitsch
- Philip Morris International R&D, Philip Morris Products S.A. Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland, Selventa, One Alewife Center, Cambridge, MA 02140, USA and Applied Dynamic Solutions, LLC, 220 Davidson Avenue, Suite 100, Somerset, NJ 08873, USA
| | - Julia Hoeng
- Philip Morris International R&D, Philip Morris Products S.A. Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland, Selventa, One Alewife Center, Cambridge, MA 02140, USA and Applied Dynamic Solutions, LLC, 220 Davidson Avenue, Suite 100, Somerset, NJ 08873, USA
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26
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Boue S, Fields B, Hoeng J, Park J, Peitsch MC, Schlage WK, Talikka M, Binenbaum I, Bondarenko V, Bulgakov OV, Cherkasova V, Diaz-Diaz N, Fedorova L, Guryanova S, Guzova J, Igorevna Koroleva G, Kozhemyakina E, Kumar R, Lavid N, Lu Q, Menon S, Ouliel Y, Peterson SC, Prokhorov A, Sanders E, Schrier S, Schwaitzer Neta G, Shvydchenko I, Tallam A, Villa-Fombuena G, Wu J, Yudkevich I, Zelikman M. Enhancement of COPD biological networks using a web-based collaboration interface. F1000Res 2015; 4:32. [PMID: 25767696 PMCID: PMC4350443 DOI: 10.12688/f1000research.5984.2] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/14/2015] [Indexed: 01/06/2023] Open
Abstract
The construction and application of biological network models is an approach that offers a holistic way to understand biological processes involved in disease. Chronic obstructive pulmonary disease (COPD) is a progressive inflammatory disease of the airways for which therapeutic options currently are limited after diagnosis, even in its earliest stage. COPD network models are important tools to better understand the biological components and processes underlying initial disease development. With the increasing amounts of literature that are now available, crowdsourcing approaches offer new forms of collaboration for researchers to review biological findings, which can be applied to the construction and verification of complex biological networks. We report the construction of 50 biological network models relevant to lung biology and early COPD using an integrative systems biology and collaborative crowd-verification approach. By combining traditional literature curation with a data-driven approach that predicts molecular activities from transcriptomics data, we constructed an initial COPD network model set based on a previously published non-diseased lung-relevant model set. The crowd was given the opportunity to enhance and refine the networks on a website ( https://bionet.sbvimprover.com/) and to add mechanistic detail, as well as critically review existing evidence and evidence added by other users, so as to enhance the accuracy of the biological representation of the processes captured in the networks. Finally, scientists and experts in the field discussed and refined the networks during an in-person jamboree meeting. Here, we describe examples of the changes made to three of these networks: Neutrophil Signaling, Macrophage Signaling, and Th1-Th2 Signaling. We describe an innovative approach to biological network construction that combines literature and data mining and a crowdsourcing approach to generate a comprehensive set of COPD-relevant models that can be used to help understand the mechanisms related to lung pathobiology. Registered users of the website can freely browse and download the networks.
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Affiliation(s)
- The sbv IMPROVER project team (in alphabetical order)
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
- Selventa, One Alewife Center, Cambridge, MA, 02140, USA
- Systems Bioengineering Group - National Technical University of Athens, Ethniko Metsovio Politechnio, , 28is Oktovriou 42, Athina, 106 82, Greece
- Touro University Nevada, 874 American Pacific Drive, Henderson, NV, 89052, USA
- University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA, 15260, USA
- Intelligent Data Analysis Group (DATAi), School of Engineering, Pablo de Olavide University, Ctra. de Utrera, km. 1 41013, Sevilla, Spain
- University of Toledo, 2801 W Bancroft St, Toledo, OH, 43606, USA
- Shemyakin & Ovchinnikov Institute of Bioorganic Chemistry, 16/10, Miklukho-Maklay str., Moscow, 117997, Russian Federation
- Private, Washington DC, USA
- USAMRIID, Attn: MCMR-UIZ-R, 1425 Porter Street, Frederick, MD, 21702-5011, USA
- Private, Boston, MA, USA
- Institute of Microbial Technology, Chandigarh, 160036, India
- Technion - Israel Institute of Technology, Technion City, Haifa, 3200003, Israel
- Louisville University, 301 E. Muhammad Ali Blvd, Louisville, KY, 40202, USA
- AnalyzeDat Consulting Services, Ernakulam, India
- Northeastern University, 360 Huntington Ave, Boston, MA, 02115, USA
- Edward Sanders Scientific Consulting, Rue du Clos 33, 2034 Peseux, Switzerland
- Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA, 02139, USA
- Kuban State University of Physical Education, Sport and Tourism, 161, Budennogo Str., Krasnodar City, 350015, Russian Federation
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 7, avenue des Hauts-Fourneaux, 4362 Esch sur Alzette, Luxembourg
- Pablo de Olavide University, Ctra. de Utrera, km. 1 41013, Sevilla, Spain
- Cal Biopharma, 710 Somerset Ln, Foster Cit, CA, 94404-3728, USA
- University of Manchester, Oxford Rd, Manchester, M13 9PL, UK
- University of Washington, 1959 NE Pacific Street, HSB T-466, Seattle, WA, USA
| | - Stephanie Boue
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Brett Fields
- Selventa, One Alewife Center, Cambridge, MA, 02140, USA
| | - Julia Hoeng
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Jennifer Park
- Selventa, One Alewife Center, Cambridge, MA, 02140, USA
| | - Manuel C. Peitsch
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Walter K. Schlage
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Marja Talikka
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - The Challenge Best Performers (in alphabetical order)
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
- Selventa, One Alewife Center, Cambridge, MA, 02140, USA
- Systems Bioengineering Group - National Technical University of Athens, Ethniko Metsovio Politechnio, , 28is Oktovriou 42, Athina, 106 82, Greece
- Touro University Nevada, 874 American Pacific Drive, Henderson, NV, 89052, USA
- University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA, 15260, USA
- Intelligent Data Analysis Group (DATAi), School of Engineering, Pablo de Olavide University, Ctra. de Utrera, km. 1 41013, Sevilla, Spain
- University of Toledo, 2801 W Bancroft St, Toledo, OH, 43606, USA
- Shemyakin & Ovchinnikov Institute of Bioorganic Chemistry, 16/10, Miklukho-Maklay str., Moscow, 117997, Russian Federation
- Private, Washington DC, USA
- USAMRIID, Attn: MCMR-UIZ-R, 1425 Porter Street, Frederick, MD, 21702-5011, USA
- Private, Boston, MA, USA
- Institute of Microbial Technology, Chandigarh, 160036, India
- Technion - Israel Institute of Technology, Technion City, Haifa, 3200003, Israel
- Louisville University, 301 E. Muhammad Ali Blvd, Louisville, KY, 40202, USA
- AnalyzeDat Consulting Services, Ernakulam, India
- Northeastern University, 360 Huntington Ave, Boston, MA, 02115, USA
- Edward Sanders Scientific Consulting, Rue du Clos 33, 2034 Peseux, Switzerland
- Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA, 02139, USA
- Kuban State University of Physical Education, Sport and Tourism, 161, Budennogo Str., Krasnodar City, 350015, Russian Federation
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 7, avenue des Hauts-Fourneaux, 4362 Esch sur Alzette, Luxembourg
- Pablo de Olavide University, Ctra. de Utrera, km. 1 41013, Sevilla, Spain
- Cal Biopharma, 710 Somerset Ln, Foster Cit, CA, 94404-3728, USA
- University of Manchester, Oxford Rd, Manchester, M13 9PL, UK
- University of Washington, 1959 NE Pacific Street, HSB T-466, Seattle, WA, USA
| | - Ilona Binenbaum
- Systems Bioengineering Group - National Technical University of Athens, Ethniko Metsovio Politechnio, , 28is Oktovriou 42, Athina, 106 82, Greece
| | - Vladimir Bondarenko
- Touro University Nevada, 874 American Pacific Drive, Henderson, NV, 89052, USA
| | - Oleg V. Bulgakov
- University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA, 15260, USA
| | | | - Norberto Diaz-Diaz
- Intelligent Data Analysis Group (DATAi), School of Engineering, Pablo de Olavide University, Ctra. de Utrera, km. 1 41013, Sevilla, Spain
| | - Larisa Fedorova
- University of Toledo, 2801 W Bancroft St, Toledo, OH, 43606, USA
| | - Svetlana Guryanova
- Shemyakin & Ovchinnikov Institute of Bioorganic Chemistry, 16/10, Miklukho-Maklay str., Moscow, 117997, Russian Federation
| | | | | | | | - Rahul Kumar
- Institute of Microbial Technology, Chandigarh, 160036, India
| | - Noa Lavid
- Technion - Israel Institute of Technology, Technion City, Haifa, 3200003, Israel
| | - Qingxian Lu
- Louisville University, 301 E. Muhammad Ali Blvd, Louisville, KY, 40202, USA
| | - Swapna Menon
- AnalyzeDat Consulting Services, Ernakulam, India
| | - Yael Ouliel
- Technion - Israel Institute of Technology, Technion City, Haifa, 3200003, Israel
| | | | - Alexander Prokhorov
- Shemyakin & Ovchinnikov Institute of Bioorganic Chemistry, 16/10, Miklukho-Maklay str., Moscow, 117997, Russian Federation
| | - Edward Sanders
- Edward Sanders Scientific Consulting, Rue du Clos 33, 2034 Peseux, Switzerland
| | - Sarah Schrier
- Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA, 02139, USA
| | | | - Irina Shvydchenko
- Kuban State University of Physical Education, Sport and Tourism, 161, Budennogo Str., Krasnodar City, 350015, Russian Federation
| | - Aravind Tallam
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 7, avenue des Hauts-Fourneaux, 4362 Esch sur Alzette, Luxembourg
| | | | - John Wu
- Cal Biopharma, 710 Somerset Ln, Foster Cit, CA, 94404-3728, USA
| | - Ilya Yudkevich
- University of Manchester, Oxford Rd, Manchester, M13 9PL, UK
| | - Mariya Zelikman
- University of Washington, 1959 NE Pacific Street, HSB T-466, Seattle, WA, USA
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27
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Boue S, Fields B, Hoeng J, Park J, Peitsch MC, Schlage WK, Talikka M, Binenbaum I, Bondarenko V, Bulgakov OV, Cherkasova V, Diaz-Diaz N, Fedorova L, Guryanova S, Guzova J, Igorevna Koroleva G, Kozhemyakina E, Kumar R, Lavid N, Lu Q, Menon S, Ouliel Y, Peterson SC, Prokhorov A, Sanders E, Schrier S, Schwaitzer Neta G, Shvydchenko I, Tallam A, Villa-Fombuena G, Wu J, Yudkevich I, Zelikman M. Enhancement of COPD biological networks using a web-based collaboration interface. F1000Res 2015; 4:32. [PMID: 25767696 PMCID: PMC4350443 DOI: 10.12688/f1000research.5984.1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/12/2015] [Indexed: 11/20/2022] Open
Abstract
The construction and application of biological network models is an approach that offers a holistic way to understand biological processes involved in disease. Chronic obstructive pulmonary disease (COPD) is a progressive inflammatory disease of the airways for which therapeutic options currently are limited after diagnosis, even in its earliest stage. COPD network models are important tools to better understand the biological components and processes underlying initial disease development. With the increasing amounts of literature that are now available, crowdsourcing approaches offer new forms of collaboration for researchers to review biological findings, which can be applied to the construction and verification of complex biological networks. We report the construction of 50 biological network models relevant to lung biology and early COPD using an integrative systems biology and collaborative crowd-verification approach. By combining traditional literature curation with a data-driven approach that predicts molecular activities from transcriptomics data, we constructed an initial COPD network model set based on a previously published non-diseased lung-relevant model set. The crowd was given the opportunity to enhance and refine the networks on a website ( https://bionet.sbvimprover.com/) and to add mechanistic detail, as well as critically review existing evidence and evidence added by other users, so as to enhance the accuracy of the biological representation of the processes captured in the networks. Finally, scientists and experts in the field discussed and refined the networks during an in-person jamboree meeting. Here, we describe examples of the changes made to three of these networks: Neutrophil Signaling, Macrophage Signaling, and Th1-Th2 Signaling. We describe an innovative approach to biological network construction that combines literature and data mining and a crowdsourcing approach to generate a comprehensive set of COPD-relevant models that can be used to help understand the mechanisms related to lung pathobiology. Registered users of the website can freely browse and download the networks.
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Affiliation(s)
- The sbv IMPROVER project team (in alphabetical order)
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
- Selventa, One Alewife Center, Cambridge, MA, 02140, USA
- Systems Bioengineering Group - National Technical University of Athens, Ethniko Metsovio Politechnio, , 28is Oktovriou 42, Athina, 106 82, Greece
- Touro University Nevada, 874 American Pacific Drive, Henderson, NV, 89052, USA
- University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA, 15260, USA
- Intelligent Data Analysis Group (DATAi), School of Engineering, Pablo de Olavide University, Ctra. de Utrera, km. 1 41013, Sevilla, Spain
- University of Toledo, 2801 W Bancroft St, Toledo, OH, 43606, USA
- Shemyakin & Ovchinnikov Institute of Bioorganic Chemistry, 16/10, Miklukho-Maklay str., Moscow, 117997, Russian Federation
- Private, Washington DC, USA
- USAMRIID, Attn: MCMR-UIZ-R, 1425 Porter Street, Frederick, MD, 21702-5011, USA
- Private, Boston, MA, USA
- Institute of Microbial Technology, Chandigarh, 160036, India
- Technion - Israel Institute of Technology, Technion City, Haifa, 3200003, Israel
- Louisville University, 301 E. Muhammad Ali Blvd, Louisville, KY, 40202, USA
- AnalyzeDat Consulting Services, Ernakulam, India
- Northeastern University, 360 Huntington Ave, Boston, MA, 02115, USA
- Edward Sanders Scientific Consulting, Rue du Clos 33, 2034 Peseux, Switzerland
- Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA, 02139, USA
- Kuban State University of Physical Education, Sport and Tourism, 161, Budennogo Str., Krasnodar City, 350015, Russian Federation
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 7, avenue des Hauts-Fourneaux, 4362 Esch sur Alzette, Luxembourg
- Pablo de Olavide University, Ctra. de Utrera, km. 1 41013, Sevilla, Spain
- Cal Biopharma, 710 Somerset Ln, Foster Cit, CA, 94404-3728, USA
- University of Manchester, Oxford Rd, Manchester, M13 9PL, UK
- University of Washington, 1959 NE Pacific Street, HSB T-466, Seattle, WA, USA
| | - Stephanie Boue
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Brett Fields
- Selventa, One Alewife Center, Cambridge, MA, 02140, USA
| | - Julia Hoeng
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Jennifer Park
- Selventa, One Alewife Center, Cambridge, MA, 02140, USA
| | - Manuel C. Peitsch
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Walter K. Schlage
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Marja Talikka
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - The Challenge Best Performers (in alphabetical order)
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
- Selventa, One Alewife Center, Cambridge, MA, 02140, USA
- Systems Bioengineering Group - National Technical University of Athens, Ethniko Metsovio Politechnio, , 28is Oktovriou 42, Athina, 106 82, Greece
- Touro University Nevada, 874 American Pacific Drive, Henderson, NV, 89052, USA
- University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA, 15260, USA
- Intelligent Data Analysis Group (DATAi), School of Engineering, Pablo de Olavide University, Ctra. de Utrera, km. 1 41013, Sevilla, Spain
- University of Toledo, 2801 W Bancroft St, Toledo, OH, 43606, USA
- Shemyakin & Ovchinnikov Institute of Bioorganic Chemistry, 16/10, Miklukho-Maklay str., Moscow, 117997, Russian Federation
- Private, Washington DC, USA
- USAMRIID, Attn: MCMR-UIZ-R, 1425 Porter Street, Frederick, MD, 21702-5011, USA
- Private, Boston, MA, USA
- Institute of Microbial Technology, Chandigarh, 160036, India
- Technion - Israel Institute of Technology, Technion City, Haifa, 3200003, Israel
- Louisville University, 301 E. Muhammad Ali Blvd, Louisville, KY, 40202, USA
- AnalyzeDat Consulting Services, Ernakulam, India
- Northeastern University, 360 Huntington Ave, Boston, MA, 02115, USA
- Edward Sanders Scientific Consulting, Rue du Clos 33, 2034 Peseux, Switzerland
- Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA, 02139, USA
- Kuban State University of Physical Education, Sport and Tourism, 161, Budennogo Str., Krasnodar City, 350015, Russian Federation
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 7, avenue des Hauts-Fourneaux, 4362 Esch sur Alzette, Luxembourg
- Pablo de Olavide University, Ctra. de Utrera, km. 1 41013, Sevilla, Spain
- Cal Biopharma, 710 Somerset Ln, Foster Cit, CA, 94404-3728, USA
- University of Manchester, Oxford Rd, Manchester, M13 9PL, UK
- University of Washington, 1959 NE Pacific Street, HSB T-466, Seattle, WA, USA
| | - Ilona Binenbaum
- Systems Bioengineering Group - National Technical University of Athens, Ethniko Metsovio Politechnio, , 28is Oktovriou 42, Athina, 106 82, Greece
| | - Vladimir Bondarenko
- Touro University Nevada, 874 American Pacific Drive, Henderson, NV, 89052, USA
| | - Oleg V. Bulgakov
- University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA, 15260, USA
| | | | - Norberto Diaz-Diaz
- Intelligent Data Analysis Group (DATAi), School of Engineering, Pablo de Olavide University, Ctra. de Utrera, km. 1 41013, Sevilla, Spain
| | - Larisa Fedorova
- University of Toledo, 2801 W Bancroft St, Toledo, OH, 43606, USA
| | - Svetlana Guryanova
- Shemyakin & Ovchinnikov Institute of Bioorganic Chemistry, 16/10, Miklukho-Maklay str., Moscow, 117997, Russian Federation
| | | | | | | | - Rahul Kumar
- Institute of Microbial Technology, Chandigarh, 160036, India
| | - Noa Lavid
- Technion - Israel Institute of Technology, Technion City, Haifa, 3200003, Israel
| | - Qingxian Lu
- Louisville University, 301 E. Muhammad Ali Blvd, Louisville, KY, 40202, USA
| | - Swapna Menon
- AnalyzeDat Consulting Services, Ernakulam, India
| | - Yael Ouliel
- Technion - Israel Institute of Technology, Technion City, Haifa, 3200003, Israel
| | | | - Alexander Prokhorov
- Shemyakin & Ovchinnikov Institute of Bioorganic Chemistry, 16/10, Miklukho-Maklay str., Moscow, 117997, Russian Federation
| | - Edward Sanders
- Edward Sanders Scientific Consulting, Rue du Clos 33, 2034 Peseux, Switzerland
| | - Sarah Schrier
- Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA, 02139, USA
| | | | - Irina Shvydchenko
- Kuban State University of Physical Education, Sport and Tourism, 161, Budennogo Str., Krasnodar City, 350015, Russian Federation
| | - Aravind Tallam
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 7, avenue des Hauts-Fourneaux, 4362 Esch sur Alzette, Luxembourg
| | | | - John Wu
- Cal Biopharma, 710 Somerset Ln, Foster Cit, CA, 94404-3728, USA
| | - Ilya Yudkevich
- University of Manchester, Oxford Rd, Manchester, M13 9PL, UK
| | - Mariya Zelikman
- University of Washington, 1959 NE Pacific Street, HSB T-466, Seattle, WA, USA
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Talikka M, Boue S, Schlage WK. Causal Biological Network Database: A Comprehensive Platform of Causal Biological Network Models Focused on the Pulmonary and Vascular Systems. METHODS IN PHARMACOLOGY AND TOXICOLOGY 2015. [DOI: 10.1007/978-1-4939-2778-4_3] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
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Talikka M, Kostadinova R, Xiang Y, Mathis C, Sewer A, Majeed S, Kuehn D, Frentzel S, Merg C, Geertz M, Martin F, Ivanov NV, Peitsch MC, Hoeng J. The response of human nasal and bronchial organotypic tissue cultures to repeated whole cigarette smoke exposure. Int J Toxicol 2014; 33:506-17. [PMID: 25297719 DOI: 10.1177/1091581814551647] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Exposure to cigarette smoke (CS) is linked to the development of respiratory diseases, and there is a need to understand the mechanisms whereby CS causes damage. Although animal models have provided valuable insights into smoking-related respiratory tract damage, modern toxicity testing calls for reliable in vitro models as alternatives for animal experimentation. We report on a repeated whole mainstream CS exposure of nasal and bronchial organotypic tissue cultures that mimic the morphological, physiological, and molecular attributes of the human respiratory tract. Despite the similar cellular staining and cytokine secretion in both tissue types, the transcriptomic analyses in the context of biological network models identified similar and diverse biological processes that were impacted by CS-exposed nasal and bronchial cultures. Our results demonstrate that nasal and bronchial tissue cultures are appropriate in vitro models for the assessment of CS-induced adverse effects in the respiratory system and promising alternative to animal experimentation.
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Affiliation(s)
- Marja Talikka
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland
| | - Radina Kostadinova
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland
| | - Yang Xiang
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland
| | - Carole Mathis
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland
| | - Alain Sewer
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland
| | - Shoaib Majeed
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland
| | - Diana Kuehn
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland
| | - Stefan Frentzel
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland
| | - Celine Merg
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland
| | - Marcel Geertz
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland
| | - Florian Martin
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland
| | - Nikolai V Ivanov
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland
| | - Manuel C Peitsch
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland
| | - Julia Hoeng
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland
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Schlage WK, Iskandar AR, Kostadinova R, Xiang Y, Sewer A, Majeed S, Kuehn D, Frentzel S, Talikka M, Geertz M, Mathis C, Ivanov N, Hoeng J, Peitsch MC. In vitro systems toxicology approach to investigate the effects of repeated cigarette smoke exposure on human buccal and gingival organotypic epithelial tissue cultures. Toxicol Mech Methods 2014; 24:470-87. [PMID: 25046638 PMCID: PMC4219813 DOI: 10.3109/15376516.2014.943441] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2014] [Revised: 06/20/2014] [Accepted: 06/29/2014] [Indexed: 11/13/2022]
Abstract
Smoking has been associated with diseases of the lung, pulmonary airways and oral cavity. Cytologic, genomic and transcriptomic changes in oral mucosa correlate with oral pre-neoplasia, cancer and inflammation (e.g. periodontitis). Alteration of smoking-related gene expression changes in oral epithelial cells is similar to that in bronchial and nasal epithelial cells. Using a systems toxicology approach, we have previously assessed the impact of cigarette smoke (CS) seen as perturbations of biological processes in human nasal and bronchial organotypic epithelial culture models. Here, we report our further assessment using in vitro human oral organotypic epithelium models. We exposed the buccal and gingival organotypic epithelial tissue cultures to CS at the air-liquid interface. CS exposure was associated with increased secretion of inflammatory mediators, induction of cytochrome P450s activity and overall weak toxicity in both tissues. Using microarray technology, gene-set analysis and a novel computational modeling approach leveraging causal biological network models, we identified CS impact on xenobiotic metabolism-related pathways accompanied by a more subtle alteration in inflammatory processes. Gene-set analysis further indicated that the CS-induced pathways in the in vitro buccal tissue models resembled those in the in vivo buccal biopsies of smokers from a published dataset. These findings support the translatability of systems responses from in vitro to in vivo and demonstrate the applicability of oral organotypical tissue models for an impact assessment of CS on various tissues exposed during smoking, as well as for impact assessment of reduced-risk products.
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Affiliation(s)
- Walter K. Schlage
- Philip Morris International R&D, Philip Morris Products S.A.NeuchâtelSwitzerland
| | - Anita R. Iskandar
- Philip Morris International R&D, Philip Morris Products S.A.NeuchâtelSwitzerland
| | - Radina Kostadinova
- Philip Morris International R&D, Philip Morris Products S.A.NeuchâtelSwitzerland
| | - Yang Xiang
- Philip Morris International R&D, Philip Morris Products S.A.NeuchâtelSwitzerland
| | - Alain Sewer
- Philip Morris International R&D, Philip Morris Products S.A.NeuchâtelSwitzerland
| | - Shoaib Majeed
- Philip Morris International R&D, Philip Morris Products S.A.NeuchâtelSwitzerland
| | - Diana Kuehn
- Philip Morris International R&D, Philip Morris Products S.A.NeuchâtelSwitzerland
| | - Stefan Frentzel
- Philip Morris International R&D, Philip Morris Products S.A.NeuchâtelSwitzerland
| | - Marja Talikka
- Philip Morris International R&D, Philip Morris Products S.A.NeuchâtelSwitzerland
| | - Marcel Geertz
- Philip Morris International R&D, Philip Morris Products S.A.NeuchâtelSwitzerland
| | - Carole Mathis
- Philip Morris International R&D, Philip Morris Products S.A.NeuchâtelSwitzerland
| | - Nikolai Ivanov
- Philip Morris International R&D, Philip Morris Products S.A.NeuchâtelSwitzerland
| | - Julia Hoeng
- Philip Morris International R&D, Philip Morris Products S.A.NeuchâtelSwitzerland
| | - Manuel C. Peitsch
- Philip Morris International R&D, Philip Morris Products S.A.NeuchâtelSwitzerland
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Vasilyev DM, Thomson TM, Frushour BP, Martin F, Sewer A. An algorithm for score aggregation over causal biological networks based on random walk sampling. BMC Res Notes 2014; 7:516. [PMID: 25113603 PMCID: PMC4266947 DOI: 10.1186/1756-0500-7-516] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2014] [Accepted: 07/31/2014] [Indexed: 01/10/2023] Open
Abstract
Background We recently published in BMC Systems Biology an approach for calculating the perturbation amplitudes of causal network models by integrating gene differential expression data. This approach relies on the process of score aggregation, which combines the perturbations at the level of the individual network nodes into a global measure that quantifies the perturbation of the network as a whole. Such "bottom-up" aggregation relates the changes in molecular entities measured by omics technologies to systems-level phenotypes. However, the aggregation method we used is limited to a specific class of causal network models called "causally consistent", which is equivalent to the notion of balance of a signed graph used in graph theory. As a consequence of this limitation, our aggregation method cannot be used in the many relevant cases involving "causally inconsistent" network models such as those containing negative feedbacks. Findings In this note, we propose an algorithm called "sampling of spanning trees" (SST) that extends our published aggregation method to causally inconsistent network models by replacing the signed relationships between the network nodes by an appropriate continuous measure. The SST algorithm is based on spanning trees, which are a particular class of subgraphs used in graph theory, and on a sampling procedure leveraging the properties of specific random walks on the graph. This algorithm is applied to several cases of biological interest. Conclusions The SST algorithm provides a practical means of aggregating nodal values over causally inconsistent network models based on solid mathematical foundations. We showed its utility in systems biology, where the nodal values can be perturbation amplitudes of protein activities or gene differential expressions, while the networks can be models of cellular signaling or expression regulation. Since the SST algorithm is based on general graph-theoretical considerations, it is scalable to arbitrary graph sizes and can potentially be used for performing quantitative analyses in any context involving signed graphs. Electronic supplementary material The online version of this article (doi:10.1186/1756-0500-7-516) contains supplementary material, which is available to authorized users.
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Affiliation(s)
| | | | | | | | - Alain Sewer
- Philip Morris International R&D, Philip Morris Products S,A, Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.
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Titz B, Elamin A, Martin F, Schneider T, Dijon S, Ivanov NV, Hoeng J, Peitsch MC. Proteomics for systems toxicology. Comput Struct Biotechnol J 2014; 11:73-90. [PMID: 25379146 PMCID: PMC4212285 DOI: 10.1016/j.csbj.2014.08.004] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Current toxicology studies frequently lack measurements at molecular resolution to enable a more mechanism-based and predictive toxicological assessment. Recently, a systems toxicology assessment framework has been proposed, which combines conventional toxicological assessment strategies with system-wide measurement methods and computational analysis approaches from the field of systems biology. Proteomic measurements are an integral component of this integrative strategy because protein alterations closely mirror biological effects, such as biological stress responses or global tissue alterations. Here, we provide an overview of the technical foundations and highlight select applications of proteomics for systems toxicology studies. With a focus on mass spectrometry-based proteomics, we summarize the experimental methods for quantitative proteomics and describe the computational approaches used to derive biological/mechanistic insights from these datasets. To illustrate how proteomics has been successfully employed to address mechanistic questions in toxicology, we summarized several case studies. Overall, we provide the technical and conceptual foundation for the integration of proteomic measurements in a more comprehensive systems toxicology assessment framework. We conclude that, owing to the critical importance of protein-level measurements and recent technological advances, proteomics will be an integral part of integrative systems toxicology approaches in the future.
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Martin F, Sewer A, Talikka M, Xiang Y, Hoeng J, Peitsch MC. Quantification of biological network perturbations for mechanistic insight and diagnostics using two-layer causal models. BMC Bioinformatics 2014; 15:238. [PMID: 25015298 PMCID: PMC4227138 DOI: 10.1186/1471-2105-15-238] [Citation(s) in RCA: 92] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2014] [Accepted: 06/26/2014] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND High-throughput measurement technologies such as microarrays provide complex datasets reflecting mechanisms perturbed in an experiment, typically a treatment vs. control design. Analysis of these information rich data can be guided based on a priori knowledge, such as networks or set of related proteins or genes. Among those, cause-and-effect network models are becoming increasingly popular and more than eighty such models, describing processes involved in cell proliferation, cell fate, cell stress, and inflammation have already been published. A meaningful systems toxicology approach to study the response of a cell system, or organism, exposed to bio-active substances requires a quantitative measure of dose-response at network level, to go beyond the differential expression of single genes. RESULTS We developed a method that quantifies network response in an interpretable manner. It fully exploits the (signed graph) structure of cause-and-effect networks models to integrate and mine transcriptomics measurements. The presented approach also enables the extraction of network-based signatures for predicting a phenotype of interest. The obtained signatures are coherent with the underlying network perturbation and can lead to more robust predictions across independent studies. The value of the various components of our mathematically coherent approach is substantiated using several in vivo and in vitro transcriptomics datasets. As a proof-of-principle, our methodology was applied to unravel mechanisms related to the efficacy of a specific anti-inflammatory drug in patients suffering from ulcerative colitis. A plausible mechanistic explanation of the unequal efficacy of the drug is provided. Moreover, by utilizing the underlying mechanisms, an accurate and robust network-based diagnosis was built to predict the response to the treatment. CONCLUSION The presented framework efficiently integrates transcriptomics data and "cause and effect" network models to enable a mathematically coherent framework from quantitative impact assessment and data interpretation to patient stratification for diagnosis purposes.
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Affiliation(s)
- Florian Martin
- Philip Morris International, R&D, Biological Systems Research, Quai Jeanrenaud 5, 2000 Neuchatel, Switzerland.
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De León H, Boué S, Schlage WK, Boukharov N, Westra JW, Gebel S, VanHooser A, Talikka M, Fields RB, Veljkovic E, Peck MJ, Mathis C, Hoang V, Poussin C, Deehan R, Stolle K, Hoeng J, Peitsch MC. A vascular biology network model focused on inflammatory processes to investigate atherogenesis and plaque instability. J Transl Med 2014; 12:185. [PMID: 24965703 PMCID: PMC4227037 DOI: 10.1186/1479-5876-12-185] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2014] [Accepted: 06/09/2014] [Indexed: 12/20/2022] Open
Abstract
Background Numerous inflammation-related pathways have been shown to play important roles in atherogenesis. Rapid and efficient assessment of the relative influence of each of those pathways is a challenge in the era of “omics” data generation. The aim of the present work was to develop a network model of inflammation-related molecular pathways underlying vascular disease to assess the degree of translatability of preclinical molecular data to the human clinical setting. Methods We constructed and evaluated the Vascular Inflammatory Processes Network (V-IPN), a model representing a collection of vascular processes modulated by inflammatory stimuli that lead to the development of atherosclerosis. Results Utilizing the V-IPN as a platform for biological discovery, we have identified key vascular processes and mechanisms captured by gene expression profiling data from four independent datasets from human endothelial cells (ECs) and human and murine intact vessels. Primary ECs in culture from multiple donors revealed a richer mapping of mechanisms identified by the V-IPN compared to an immortalized EC line. Furthermore, an evaluation of gene expression datasets from aortas of old ApoE-/- mice (78 weeks) and human coronary arteries with advanced atherosclerotic lesions identified significant commonalities in the two species, as well as several mechanisms specific to human arteries that are consistent with the development of unstable atherosclerotic plaques. Conclusions We have generated a new biological network model of atherogenic processes that demonstrates the power of network analysis to advance integrative, systems biology-based knowledge of cross-species translatability, plaque development and potential mechanisms leading to plaque instability.
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Affiliation(s)
- Héctor De León
- Philip Morris International R&D, Philip Morris Products S,A,, Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.
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Kogel U, Schlage WK, Martin F, Xiang Y, Ansari S, Leroy P, Vanscheeuwijck P, Gebel S, Buettner A, Wyss C, Esposito M, Hoeng J, Peitsch MC. A 28-day rat inhalation study with an integrated molecular toxicology endpoint demonstrates reduced exposure effects for a prototypic modified risk tobacco product compared with conventional cigarettes. Food Chem Toxicol 2014; 68:204-17. [PMID: 24632068 DOI: 10.1016/j.fct.2014.02.034] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2013] [Revised: 02/21/2014] [Accepted: 02/24/2014] [Indexed: 11/26/2022]
Abstract
Towards a systems toxicology-based risk assessment, we investigated molecular perturbations accompanying histopathological changes in a 28-day rat inhalation study combining transcriptomics with classical histopathology. We demonstrated reduced biological activity of a prototypic modified risk tobacco product (pMRTP) compared with the reference research cigarette 3R4F. Rats were exposed to filtered air or to three concentrations of mainstream smoke (MS) from 3R4F, or to a high concentration of MS from a pMRTP. Histopathology revealed concentration-dependent changes in response to 3R4F that were irritative stress-related in nasal and bronchial epithelium, and inflammation-related in the lung parenchyma. For pMRTP, significant changes were seen in the nasal epithelium only. Transcriptomics data were obtained from nasal and bronchial epithelium and lung parenchyma. Concentration-dependent gene expression changes were observed following 3R4F exposure, with much smaller changes for pMRTP. A computational-modeling approach based on causal models of tissue-specific biological networks identified cell stress, inflammation, proliferation, and senescence as the most perturbed molecular mechanisms. These perturbations correlated with histopathological observations. Only weak perturbations were observed for pMRTP. In conclusion, a correlative evaluation of classical histopathology together with gene expression-based computational network models may facilitate a systems toxicology-based risk assessment, as shown for a pMRTP.
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Affiliation(s)
- Ulrike Kogel
- Philip Morris International R&D, Philip Morris Research Laboratories GmbH, Fuggerstrasse 3, 51149 Cologne, Germany; Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.
| | - Walter K Schlage
- Philip Morris International R&D, Philip Morris Research Laboratories GmbH, Fuggerstrasse 3, 51149 Cologne, Germany; Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.
| | - Florian Martin
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.
| | - Yang Xiang
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.
| | - Sam Ansari
- Philip Morris International R&D, Philip Morris Research Laboratories GmbH, Fuggerstrasse 3, 51149 Cologne, Germany; Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.
| | - Patrice Leroy
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.
| | - Patrick Vanscheeuwijck
- Philip Morris International R&D, Philip Morris Research Laboratories GmbH, Fuggerstrasse 3, 51149 Cologne, Germany; Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland; Philip Morris International R&D, Philip Morris Research Laboratories bvba, Grauwmeer 14, Researchpark Haasrode, 3001 Leuven, Belgium.
| | - Stephan Gebel
- Philip Morris International R&D, Philip Morris Research Laboratories GmbH, Fuggerstrasse 3, 51149 Cologne, Germany.
| | - Ansgar Buettner
- Philip Morris International R&D, Philip Morris Research Laboratories GmbH, Fuggerstrasse 3, 51149 Cologne, Germany.
| | - Christoph Wyss
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.
| | - Marco Esposito
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.
| | - Julia Hoeng
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.
| | - Manuel C Peitsch
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.
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Gonzalez-Suarez I, Sewer A, Walker P, Mathis C, Ellis S, Woodhouse H, Guedj E, Dulize R, Marescotti D, Acali S, Martin F, Ivanov NV, Hoeng J, Peitsch MC. Systems biology approach for evaluating the biological impact of environmental toxicants in vitro. Chem Res Toxicol 2014; 27:367-76. [PMID: 24428674 DOI: 10.1021/tx400405s] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Exposure to cigarette smoke is a leading cause of lung diseases including chronic obstructive pulmonary disease and cancer. Cigarette smoke is a complex aerosol containing over 6000 chemicals and thus it is difficult to determine individual contributions to overall toxicity as well as the molecular mechanisms by which smoke constituents exert their effects. We selected three well-known harmful and potentially harmful constituents (HPHCs) in tobacco smoke, acrolein, formaldehyde and catechol, and established a high-content screening method using normal human bronchial epithelial cells, which are the first bronchial cells in contact with cigarette smoke. The impact of each HPHC was investigated using 13 indicators of cellular toxicity complemented with a microarray-based whole-transcriptome analysis followed by a computational approach leveraging mechanistic network models to identify and quantify perturbed molecular pathways. HPHCs were evaluated over a wide range of concentrations and at different exposure time points (4, 8, and 24 h). By high-content screening, the toxic effects of the three HPHCs could be observed only at the highest doses. Whole-genome transcriptomics unraveled toxicity mechanisms at lower doses and earlier time points. The most prevalent toxicity mechanisms observed were DNA damage/growth arrest, oxidative stress, mitochondrial stress, and apoptosis/necrosis. A combination of multiple toxicological end points with a systems-based impact assessment allows for a more robust scientific basis for the toxicological assessment of HPHCs, allowing insight into time- and dose-dependent molecular perturbations of specific biological pathways. This approach allowed us to establish an in vitro systems toxicology platform that can be applied to a broader selection of HPHCs and their mixtures and can serve more generally as the basis for testing the impact of other environmental toxicants on normal bronchial epithelial cells.
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Affiliation(s)
- Ignacio Gonzalez-Suarez
- Philip Morris International R&D, Philip Morris Products S.A. , Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
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Sturla SJ, Boobis AR, FitzGerald RE, Hoeng J, Kavlock RJ, Schirmer K, Whelan M, Wilks MF, Peitsch MC. Systems toxicology: from basic research to risk assessment. Chem Res Toxicol 2014; 27:314-29. [PMID: 24446777 PMCID: PMC3964730 DOI: 10.1021/tx400410s] [Citation(s) in RCA: 211] [Impact Index Per Article: 21.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Systems Toxicology is the integration of classical toxicology with quantitative analysis of large networks of molecular and functional changes occurring across multiple levels of biological organization. Society demands increasingly close scrutiny of the potential health risks associated with exposure to chemicals present in our everyday life, leading to an increasing need for more predictive and accurate risk-assessment approaches. Developing such approaches requires a detailed mechanistic understanding of the ways in which xenobiotic substances perturb biological systems and lead to adverse outcomes. Thus, Systems Toxicology approaches offer modern strategies for gaining such mechanistic knowledge by combining advanced analytical and computational tools. Furthermore, Systems Toxicology is a means for the identification and application of biomarkers for improved safety assessments. In Systems Toxicology, quantitative systems-wide molecular changes in the context of an exposure are measured, and a causal chain of molecular events linking exposures with adverse outcomes (i.e., functional and apical end points) is deciphered. Mathematical models are then built to describe these processes in a quantitative manner. The integrated data analysis leads to the identification of how biological networks are perturbed by the exposure and enables the development of predictive mathematical models of toxicological processes. This perspective integrates current knowledge regarding bioanalytical approaches, computational analysis, and the potential for improved risk assessment.
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Affiliation(s)
- Shana J Sturla
- Department of Health Sciences and Technology, Institute of Food, Nutrition and Health, ETH Zürich , Schmelzbergstrasse 9, 8092 Zürich, Switzerland
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Handy DE, Loscalzo J, Leopold JA. Systems analysis of oxidant stress in the vasculature. IUBMB Life 2013; 65:911-20. [PMID: 24265198 DOI: 10.1002/iub.1221] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2013] [Accepted: 10/01/2013] [Indexed: 01/11/2023]
Abstract
Systems biology and network analysis are emerging as valuable tools for the discovery of novel relationships, the identification of key regulatory factors, and the prediction of phenotypic changes in complex biological systems. Redox homeostasis in the vasculature is maintained by an intricate balance between oxidant-generating and antioxidant systems. When these systems are perturbed, conditions are permissive for oxidant stress, which, in turn, promotes vascular dysfunction and structural remodeling. Owing to the number of elements involved in redox regulation and the different vascular pathophenotypes associated with oxidant stress, vascular oxidant stress represents an ideal system to study by network analysis. Networks offer a method to organize experimentally derived factors, including proteins, metabolites, and DNA, that are represented as nodes into an unbiased comprehensive platform for study. Through analysis of the network, it is possible to determine essential or regulatory nodes, identify previously unknown connections between nodes, and locate modules, which are groups of nodes located within the same neighborhood that function together and have implications for phenotype. Investigators have only recently begun to construct oxidant stress-related networks to examine vascular structure and function; however, these early studies have provided mechanistic insight to further our understanding of this complicated biological system.
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Affiliation(s)
- Diane E Handy
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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Ansari S, Binder J, Boue S, Di Fabio A, Hayes W, Hoeng J, Iskandar A, Kleiman R, Norel R, O'Neel B, Peitsch MC, Poussin C, Pratt D, Rhrissorrakrai K, Schlage WK, Stolovitzky G, Talikka M. On Crowd-verification of Biological Networks. Bioinform Biol Insights 2013; 7:307-25. [PMID: 24151423 PMCID: PMC3798292 DOI: 10.4137/bbi.s12932] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
Biological networks with a structured syntax are a powerful way of representing biological information generated from high density data; however, they can become unwieldy to manage as their size and complexity increase. This article presents a crowd-verification approach for the visualization and expansion of biological networks. Web-based graphical interfaces allow visualization of causal and correlative biological relationships represented using Biological Expression Language (BEL). Crowdsourcing principles enable participants to communally annotate these relationships based on literature evidences. Gamification principles are incorporated to further engage domain experts throughout biology to gather robust peer-reviewed information from which relationships can be identified and verified. The resulting network models will represent the current status of biological knowledge within the defined boundaries, here processes related to human lung disease. These models are amenable to computational analysis. For some period following conclusion of the challenge, the published models will remain available for continuous use and expansion by the scientific community.
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Systems approaches evaluating the perturbation of xenobiotic metabolism in response to cigarette smoke exposure in nasal and bronchial tissues. BIOMED RESEARCH INTERNATIONAL 2013; 2013:512086. [PMID: 24224167 PMCID: PMC3808713 DOI: 10.1155/2013/512086] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/17/2013] [Revised: 08/14/2013] [Accepted: 08/16/2013] [Indexed: 02/03/2023]
Abstract
Capturing the effects of exposure in a specific target organ is a major challenge in risk assessment. Exposure to cigarette smoke (CS) implicates the field of tissue injury in the lung as well as nasal and airway epithelia. Xenobiotic metabolism in particular becomes an attractive tool for chemical risk assessment because of its responsiveness against toxic compounds, including those present in CS. This study describes an efficient integration from transcriptomic data to quantitative measures, which reflect the responses against xenobiotics that are captured in a biological network model. We show here that our novel systems approach can quantify the perturbation in the network model of xenobiotic metabolism. We further show that this approach efficiently compares the perturbation upon CS exposure in bronchial and nasal epithelial cells in vivo samples obtained from smokers. Our observation suggests the xenobiotic responses in the bronchial and nasal epithelial cells of smokers were similar to those observed in their respective organotypic models exposed to CS. Furthermore, the results suggest that nasal tissue is a reliable surrogate to measure xenobiotic responses in bronchial tissue.
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Hoeng J, Talikka M, Martin F, Sewer A, Yang X, Iskandar A, Schlage WK, Peitsch MC. Case study: the role of mechanistic network models in systems toxicology. Drug Discov Today 2013; 19:183-92. [PMID: 23933191 DOI: 10.1016/j.drudis.2013.07.023] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2013] [Revised: 07/14/2013] [Accepted: 07/25/2013] [Indexed: 10/26/2022]
Abstract
Twenty first century systems toxicology approaches enable the discovery of biological pathways affected in response to active substances. Here, we briefly summarize current network approaches that facilitate the detailed mechanistic understanding of the impact of a given stimulus on a biological system. We also introduce our network-based method with two use cases and show how causal biological network models combined with computational methods provide quantitative mechanistic insights. Our approach provides a robust comparison of the transcriptional responses in different experimental systems and enables the identification of network-based biomarkers modulated in response to exposure. These advances can also be applied to pharmacology, where the understanding of disease mechanisms and adverse drug effects is imperative for the development of efficient and safe treatment options.
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Affiliation(s)
- Julia Hoeng
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Marja Talikka
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Florian Martin
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Alain Sewer
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Xiang Yang
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Anita Iskandar
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Walter K Schlage
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
| | - Manuel C Peitsch
- Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.
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42
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Thomson TM, Sewer A, Martin F, Belcastro V, Frushour BP, Gebel S, Park J, Schlage WK, Talikka M, Vasilyev DM, Westra JW, Hoeng J, Peitsch MC. Quantitative assessment of biological impact using transcriptomic data and mechanistic network models. Toxicol Appl Pharmacol 2013; 272:863-78. [PMID: 23933166 DOI: 10.1016/j.taap.2013.07.007] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2013] [Revised: 07/01/2013] [Accepted: 07/13/2013] [Indexed: 12/29/2022]
Abstract
Exposure to biologically active substances such as therapeutic drugs or environmental toxicants can impact biological systems at various levels, affecting individual molecules, signaling pathways, and overall cellular processes. The ability to derive mechanistic insights from the resulting system responses requires the integration of experimental measures with a priori knowledge about the system and the interacting molecules therein. We developed a novel systems biology-based methodology that leverages mechanistic network models and transcriptomic data to quantitatively assess the biological impact of exposures to active substances. Hierarchically organized network models were first constructed to provide a coherent framework for investigating the impact of exposures at the molecular, pathway and process levels. We then validated our methodology using novel and previously published experiments. For both in vitro systems with simple exposure and in vivo systems with complex exposures, our methodology was able to recapitulate known biological responses matching expected or measured phenotypes. In addition, the quantitative results were in agreement with experimental endpoint data for many of the mechanistic effects that were assessed, providing further objective confirmation of the approach. We conclude that our methodology evaluates the biological impact of exposures in an objective, systematic, and quantifiable manner, enabling the computation of a systems-wide and pan-mechanistic biological impact measure for a given active substance or mixture. Our results suggest that various fields of human disease research, from drug development to consumer product testing and environmental impact analysis, could benefit from using this methodology.
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Affiliation(s)
- Ty M Thomson
- Selventa, One Alewife Center, Cambridge, MA 02140, USA
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Belcastro V, Poussin C, Gebel S, Mathis C, Schlage WK, Lichtner RB, Quadt-Humme S, Wagner S, Hoeng J, Peitsch MC. Systematic verification of upstream regulators of a computable cellular proliferation network model on non-diseased lung cells using a dedicated dataset. Bioinform Biol Insights 2013; 7:217-30. [PMID: 23926424 PMCID: PMC3733638 DOI: 10.4137/bbi.s12167] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
We recently constructed a computable cell proliferation network (CPN) model focused on lung tissue to unravel complex biological processes and their exposure-related perturbations from molecular profiling data. The CPN consists of edges and nodes representing upstream controllers of gene expression largely generated from transcriptomics datasets using Reverse Causal Reasoning (RCR). Here, we report an approach to biologically verify the correctness of upstream controller nodes using a specifically designed, independent lung cell proliferation dataset. Normal human bronchial epithelial cells were arrested at G1/S with a cell cycle inhibitor. Gene expression changes and cell proliferation were captured at different time points after release from inhibition. Gene set enrichment analysis demonstrated cell cycle response specificity via an overrepresentation of proliferation related gene sets. Coverage analysis of RCR-derived hypotheses returned statistical significance for cell cycle response specificity across the whole model as well as for the Growth Factor and Cell Cycle sub-network models.
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Affiliation(s)
- Vincenzo Belcastro
- Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland
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