ALISSA: an automated live-cell imaging system for signal transduction analyses

Probe photobleaching and a specimen’s sensitivity to phototoxicity severely limit the number of possible excitation cycles in time-lapse fluorescent microscopy experiments. Consequently, when a study of cellular processes requires measurements over hours or days, temporal resolution is limited, and spontaneous or rapid events may be missed, thus limiting conclusions about transduction events. We have developed ALISSA, a design framework and reference implementation for an automated live-cell imaging system for signal transduction analysis. It allows an adaptation of image modalities and laser resources tailored to the biological process, and thereby extends temporal resolution from minutes to seconds. The system employs online image analysis to detect cellular events that are then used to exercise microscope control. It consists of a reusable image analysis software for cell segmentation, tracking, and time series extraction, and a measurement-specific process control software that can be easily adapted to various biological settings. We have applied the ALISSA framework to the analysis of apoptosis as a demonstration case for slow onset and rapid execution signaling. The demonstration provides a clear proof-of-concept for ALISSA, and offers guidelines for its application in a broad spectrum of signal transduction studies

Mathematical modelling of the mitochondrial apoptosis pathway

Mitochondria are pivotal for cellular bioenergetics, but are also a core component of the cell death machinery. Hypothesis-driven research approaches have greatly advanced our understanding of the role of mitochondria in cell death and cell survival, but traditionally focus on a single gene or specific signalling pathway at a time. Predictions originating from these approaches become limited when signalling pathways show increased complexity and invariably include redundancies, feedback loops, anisotropies or compartmentalisation. By introducing methods from theoretical chemistry, control theory, and biophysics, computational models have provided new quantitative insights into cell decision processes and have led to an increased understanding of the key regulatory principles of apoptosis. In this review, we describe the currently applied modelling approaches, discuss the suitability of different modelling techniques, and evaluate their contribution to the understanding of the mitochondrial apoptosis pathway. This article is part of a Special Issue entitled Mitochondria: the deadly organelle.status: publishe

Supplementary Material For: ALISSA: an automated live-cell imaging system for signal transduction analyses

Abstract included in text

ALISSA: an automated live-cell imaging system for signal transduction analyses

Probe photobleaching and a specimen’s sensitivity to phototoxicity severely limit the number of possible excitation cycles in time-lapse fluorescent microscopy experiments. Consequently, when a study of cellular processes requires measurements over hours or days, temporal resolution is limited, and spontaneous or rapid events may be missed, thus limiting conclusions about transduction events. We have developed ALISSA, a design framework and reference implementation for an automated live-cell imaging system for signal transduction analysis. It allows an adaptation of image modalities and laser resources tailored to the biological process, and thereby extends temporal resolution from minutes to seconds. The system employs online image analysis to detect cellular events that are then used to exercise microscope control. It consists of a reusable image analysis software for cell segmentation, tracking, and time series extraction, and a measurement-specific process control software that can be easily adapted to various biological settings. We have applied the ALISSA framework to the analysis of apoptosis as a demonstration case for slow onset and rapid execution signaling. The demonstration provides a clear proof-of-concept for ALISSA, and offers guidelines for its application in a broad spectrum of signal transduction studies

Supplementary Material For: ALISSA: an automated live-cell imaging system for signal transduction analyses

Abstract included in text

ALISSA: an automated live-cell imaging system for signal transduction analyses

Probe photobleaching and a specimen’s sensitivity to phototoxicity severely limit the number of possible excitation cycles in time-lapse fluorescent microscopy experiments. Consequently, when a study of cellular processes requires measurements over hours or days, temporal resolution is limited, and spontaneous or rapid events may be missed, thus limiting conclusions about transduction events. We have developed ALISSA, a design framework and reference implementation for an automated live-cell imaging system for signal transduction analysis. It allows an adaptation of image modalities and laser resources tailored to the biological process, and thereby extends temporal resolution from minutes to seconds. The system employs online image analysis to detect cellular events that are then used to exercise microscope control. It consists of a reusable image analysis software for cell segmentation, tracking, and time series extraction, and a measurement-specific process control software that can be easily adapted to various biological settings. We have applied the ALISSA framework to the analysis of apoptosis as a demonstration case for slow onset and rapid execution signaling. The demonstration provides a clear proof-of-concept for ALISSA, and offers guidelines for its application in a broad spectrum of signal transduction studies

Supplementary Material For: ALISSA: an automated live-cell imaging system for signal transduction analyses

Abstract included in text