Skip Navigation


Bioinformatics Advance Access originally published online on January 19, 2007
Bioinformatics 2007 23(5):648-650; doi:10.1093/bioinformatics/btl684
This Article
Right arrow Abstract Freely available
Right arrow FREE Full Text (Print PDF) Freely available
Right arrow All Versions of this Article:
23/5/648    most recent
btl684v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (1)
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Huber, H. J.
Right arrow Articles by Prehn, J. H. M.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Huber, H. J.
Right arrow Articles by Prehn, J. H. M.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

APOPTO-CELL—a simulation tool and interactive database for analyzing cellular susceptibility to apoptosis

Heinrich J. Huber 1,2,3,{dagger}, Markus Rehm 1,2,*,{dagger}, Martin Plchut 3, Heiko Düssmann 2 and Jochen H. M. Prehn 1,2

1Systems Biology Group, RCSI Research Institute, 2Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, Dublin 2, Ireland and 3Siemens Medical Division, Siemens Ireland, Dublin 2, Ireland

*To whom correspondence should be addressed.


   ABSTRACT
TOP
 ABSTRACT
1 INTRODUCTION
 2 Implementation
 3 User Interface
 ACKNOWLEDGEMENTS
 REFERENCES
 

We have developed a web service that provides a comprehensive analysis of the susceptibility of cells to undergo apoptosis in response to an activation of the mitochondrial apoptotic pathway. Based on ordinary differential equations, (pre-determined) protein concentrations and release kinetics of mitochondrial pro-apoptotic factors, a network of 52 reactions and 19 reaction partners can be employed as a tool to display temporal protein profiles, to identify key regulatory proteins and to determine critical threshold concentrations required for the execution of apoptosis in HeLa cancer cells or other cell types. The web service also provides an interactive database function for the deposition of cell-type-specific quantitative data. In addition, the web service provides an output that can be compared directly to experimental results obtained from real-time single-cell experiments, making this a widely applicable systems biology tool for apoptosis and cancer researchers.

Availability: http://systemsbiology.rcsi.ie/apopto-cell.html

Contact: mrehm{at}rcsi.ie

Supplementary information: Supplementary data are available at Bioinformatics online.


   1 INTRODUCTION
TOP
 ABSTRACT
 1 INTRODUCTION
2 Implementation
 3 User Interface
 ACKNOWLEDGEMENTS
 REFERENCES
 
Apoptosis is an evolutionary conserved, genetically defined form of cell death necessary for maintaining tissue homeostasis and removing malignant cells. Enhanced or repressed apoptosis contributes to cancer, developmental defects, autoimmune diseases and neurological disorders.

In most cellular systems, apoptotic cell death is activated through the mitochondrial pathway. The release of cytochrome-c (cyt-c) and Smac from the mitochondria into the cytosol triggers a complex network of interactions and feedbacks that ultimately result in the activation of caspase-3 and -7. These effector caspases are responsible for most morphological and biochemical changes characterizing this type of active cell death. A detailed biological description of the signaling network including full references is provided in the online introductory section of the APOPTO-CELL tool.

To understand the signaling processes in real time, we and others recently developed live cell imaging techniques that monitor the initiation of the mitochondrial apoptosis pathway (cyt-c and Smac release as the biological input) as well as the resulting effector caspase activity (substrate cleavage by caspase-3 or -7 as the biological output), using fluorescent probes (Goldstein et al., 2000; Tyas et al., 2000; Rehm et al., 2002, 2003). Due to the complexity of the processes initiated, the molecular dynamics and relative contribution of individual proteins to the activation or inhibition of effector caspases remained largely unknown in these analyses. Understanding these molecular control mechanisms is only possible at the systems level. We have therefore developed a MATLAB (The Mathworks, UK)-based mathematical model of the mitochondrial apoptosis pathway (Rehm et al., 2006) which enabled us to quantitatively understand apoptotic signaling dynamics in HeLa cells.

However, to fully exploit the versatility and flexibility of the model and its application to other cellular systems access to quantitative experimental data is needed. Currently, this represents an important and major challenge in systems biology as often such basic data are available in many experimental laboratories, yet remain unpublished. To overcome these limitations and to stimulate collaboration between apoptosis researchers, systems biologists and translational clinician scientists, appropriate interaction platforms are urgently required. We therefore developed a novel user-friendly web-based tool that allows a prediction of cellular susceptibility to apoptosis for any desired cell type based on cell-type-specific data, including the identification of key regulatory proteins and the calculation of temporal protein profiles. We have also implemented an interactive database that permits users to store and share quantitative data defining the molecular composition of their cells of choice.


   2 Implementation
TOP
 ABSTRACT
 1 INTRODUCTION
 2 Implementation
3 User Interface
 ACKNOWLEDGEMENTS
 REFERENCES
 
2.1 Modeling approach
The modeling is based on a biochemical reactions network published previously (Rehm et al., 2006) and described in the introductory section of the web service. The model is initiated by input functions that remodel cyt-c-induced apoptosome formation and Smac release. All reactions are based on the law of mass action. Moreover, proteasomal degradation and protein production rates were implemented. This network led to a set of 52 ordinary differential equations with 19 reaction partners. Substrate cleavage by effector caspases was implemented as a model output. Importantly, both apoptosis initiation and substrate cleavage can be measured experimentally in single living cells using established fluorescent probes (Goldstein et al., 2000; Rehm et al., 2002, 2003; Tyas et al., 2000). This allows a direct comparison of the computational predictions with experimental results.

2.2 Systems architecture
The web server is implemented as a client-server-based architecture using the MATLAB web server tool to provide the CGI interface and to format input data to the MATLAB interpreter language. The MATLAB web server itself acts as a client to an Apache web server (The Apache Foundation, http://www.apache.org) that maintains the communication with the browser. The database is implemented as a flat file with a PERL interface for data storage and retrieval.


   3 User Interface
TOP
 ABSTRACT
 1 INTRODUCTION
 2 Implementation
 3 User Interface
ACKNOWLEDGEMENTS
 REFERENCES
 
At http://systemsbiology.rcsi.ie/apopto-cell.html the service can be accessed by any internet browser supporting HTML 4.0 such as Mozilla Firefox or Microsoft Internet Explorer as of version 3.0. Figure 1 shows an overview of the web service.


Figure 1
View larger version (38K):
[in this window]
[in a new window]
[Download PowerPoint slide]
  		Fig. 1. Screen shot of the APOPTO-CELL graphical user interface. Cell-type-specific data can be selected in the left frame and inserted into the calculation forms. A general introduction and all options described in Sections 3.2 and 3.3 can be individually accessed in the header.

 
3.1 Default settings
As the default cell system, intracellular protein concentrations and kinetic parameters are adjusted to values measured or estimated for human HeLa cells (Rehm et al., 2006). All default parameters can be adjusted either manually or selected from a database to resemble other cellular systems.

3.2 Interactive cell database
In the left frame, quantitative data for various cell types can be selected. Upon selecting the cell type, associated data for each parameter can be chosen from a drop-down menu. Following the data selection, additional information on how the parameters were determined and, if available, publication references are displayed. Clicking the ‘Fill Form’ button transfers the selected data into the calculation forms (see Section 3.3). Unselected or undetermined parameters are substituted by default values for HeLa cells in the calculation forms but can be manually adjusted as well if desired.

Importantly, users can upload additional quantitative data into the database. A data submission form is loaded upon clicking the ‘Submit Cell Data’ button in the main header. Data for new or already existing cell systems may be entered. Contact details and information on the experimental approach to determine the values need to be included. A publication reference, if available, may be uploaded as well.

The data submission deliberately allows the submission of single parameters, as the majority of experimental projects focus on only one or two targets per study. Furthermore the database is capable of storing and displaying multiple entries for one and the same parameter. With a growing number of entries the database thus will reflect the variability of diverse experimental quantifications. The database will greatly enhance the biological significance of the analyses offered here and also can supplement other systemic approaches focusing on this pathway or its components (Eissing et al., 2004; Fussenegger et al., 2000; Stucki and Simon, 2005).

3.3 Calculation modes
Links to three different program modes in the header lead to customized input forms for calculations in the main frame:

3.3.1 Temporal protein profiles
This option allows the visualization of the temporal profiles of all proteins and protein complexes involved in the apoptotic process, including intermediary and transient products that cannot be monitored experimentally. Furthermore, the cleavage profile of intracellular effector caspase substrates is displayed and can directly be compared to experimental data from single-cell analyses.

3.3.2 Sensitivity analysis
This option analyzes how the up- or down-regulation of key proteins or the kinetics of cyt-c-induced apoptosome formation or Smac release influence the time required to substrate cleavage. This mode enables the swift identification of key regulatory parameters.

3.3.3 1D/2D substrate cleavage profiles
In 1D analysis, temporal substrate cleavage profiles are predicted for a user-defined concentration range of one key protein. In 2D profiles, the model calculates the amount of cleaved substrate for concentration ranges of two key proteins. Both modes can be used to define threshold concentrations separating conditions that either block apoptosis or allow apoptosis to proceed.


   ACKNOWLEDGEMENTS
TOP
 ABSTRACT
 1 INTRODUCTION
 2 Implementation
 3 User Interface
 ACKNOWLEDGEMENTS
REFERENCES
 
This research was supported by grants from Science Foundation Ireland to JHMP (03/RP1/B344S) and MR (05/RFP/BIM0056), and by Siemens Research Ireland.

Conflict of Interest: none declared.


   FOOTNOTES
 
{dagger}The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors. Back

Associate Editor: Olga Troyanskaya

Received on December 13, 2006; revised on December 13, 2006; accepted on January 7, 2007

   REFERENCES
TOP
 ABSTRACT
 1 INTRODUCTION
 2 Implementation
 3 User Interface
 ACKNOWLEDGEMENTS
 REFERENCES
 

    Eissing T, et al. Bistability analyses of a caspase activation model for receptor-induced apoptosis. J. Biol. Chem., ( (2004) ) 279, : 36892–36897.[Abstract/Free Full Text].

    Fussenegger M, et al. A mathematical model of caspase function in apoptosis. Nat. Biotechnol., ( (2000) ) 18, : 768–774.[CrossRef][ISI][Medline].

    Goldstein JC, et al. The coordinate release of cytochrome c during apoptosis is rapid, complete and kinetically invariant. Nat. Cell. Biol., ( (2000) ) 2, : 156–162.[CrossRef][ISI][Medline].

    Rehm M, et al. Single-cell fluorescence resonance energy transfer analysis demonstrates that caspase activation during apoptosis is a rapid process. Role of caspase-3. J. Biol. Chem., ( (2002) ) 277, : 24506–24514.[Abstract/Free Full Text].

    Rehm M, et al. Real-time single cell analysis of Smac/DIABLO release during apoptosis. J. Cell Biol., ( (2003) ) 162, : 1031–1043.[Abstract/Free Full Text].

    Rehm M, et al. Systems analysis of effector caspase activation and its control by X-linked inhibitor of apoptosis protein. EMBO J., ( (2006) ) 25, : 4338–4349.[CrossRef][ISI][Medline].

    Stucki JW, Simon HU. Mathematical modeling of the regulation of caspase-3 activation and degradation. J. Theor. Biol., ( (2005) ) 234, : 123–131.[CrossRef][ISI][Medline].

    Tyas L, et al. Rapid caspase-3 activation during apoptosis revealed using fluorescence-resonance energy transfer. EMBO Rep., ( (2000) ) 1, : 266–270.[CrossRef][ISI][Medline].


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?



This Article
Right arrow Abstract Freely available
Right arrow FREE Full Text (Print PDF) Freely available
Right arrow All Versions of this Article:
23/5/648    most recent
btl684v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (1)
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Huber, H. J.
Right arrow Articles by Prehn, J. H. M.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Huber, H. J.
Right arrow Articles by Prehn, J. H. M.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?