High-throughput fluorescence microscopy for systems biology

In this post-genomic era, we need to define gene function on a genome-wide scale for model organisms and humans. The fundamental unit of biological processes is the cell. Among the most powerful tools to assay such processes in the physiological context of intact living cells are fluorescence microscopy and related imaging techniques. To enable these techniques to be applied to functional genomics experiments, fluorescence microscopy is making the transition to a quantitative and high-throughput technology.     

Computer aided fluorescence imaging of photosynthetic systems

A fluorescence video imaging system utilizing relatively inexpensive commercial components is described. The instrument utilizes a black and white CCD video camera detector, a commercial video imaging board and a IBM-AT compatible computer. The color output of the imaging board greatly aids in the users ability to visually discriminate areas of interest in the video field. Software development that enables the user to capture kinetic traces in real time from the video images is also described. The system is used to monitor fluorescence from photosynthetic systems. The usefulness of the system in screening for photosynthetic mutants is also demonstrated. The cost of the system can be kept below $12,000.Abbreviations CCD charge-coupled device - DCMU diuron, 3-[3,4-Dichlorophenyl]1,1-dimethylurea - AGC automatic gain control - LUT look-up table - AOI area of interest - CPU central processing unit - RAM random access memory - ADC analog-to-digital converter - FVIPS fluorescence video image processing software - I/O input/output - F₀ dark-level fluorescence - OIDPSMT characteristic transient components, where O is dark level, I is intermediary peak, D is dip, P is peak of fast transient, S is quasi-steady state level, M is second maximum, T is terminal level     

Single-cell systems biology by super-resolution imaging and combinatorial labeling

Fluorescence microscopy is a powerful quantitative tool for exploring regulatory networks in single cells. However, the number of molecular species that can be measured simultaneously is limited by the spectral overlap between fluorophores. Here we demonstrate a simple but general strategy to drastically increase the capacity for multiplex detection of molecules in single cells by using optical super-resolution microscopy (SRM) and combinatorial labeling. As a proof of principle, we labeled mRNAs with unique combinations of fluorophores using fluorescence in situ hybridization (FISH), and resolved the sequences and combinations of fluorophores with SRM. We measured mRNA levels of 32 genes simultaneously in single Saccharomyces cerevisiae cells. These experiments demonstrate that combinatorial labeling and super-resolution imaging of single cells is a natural approach to bring systems biology into single cells.     

Wide-field photon counting fluorescence lifetime imaging microscopy: application to photosynthesizing systems

Fluorescence lifetime imaging microscopy (FLIM) is a technique that visualizes the excited state kinetics of fluorescence molecules with the spatial resolution of a fluorescence microscope. We present a scanningless implementation of FLIM based on a time- and space-correlated single photon counting (TSCSPC) method employing a position-sensitive quadrant anode detector and wide-field illumination. The standard time-correlated photon counting approach leads to picosecond temporal resolution, making it possible to resolve complex fluorescence decays. This allows parallel acquisition of time-resolved images of biological samples under minimally invasive low-excitation conditions (<10mW/cm²). In this way unwanted photochemical reactions induced by high excitation intensities and distorting the decay kinetics are avoided. Comparably low excitation intensities are practically impossible to achieve with a conventional laser scanning microscope, where focusing of the excitation beam into a tight spot is required. Therefore, wide-field FLIM permits to study Photosystem II (PS II) in a way so far not possible with a laser scanning microscope. The potential of the wide-field TSCSPC method is demonstrated by presenting FLIM measurements of the fluorescence dynamics of photosynthetic systems in living cells of the chlorophyll d-containing cyanobacterium Acaryochloris marina.     

Standards for systems biology

High-throughput technologies are generating large amounts of complex data that have to be stored in databases, communicated to various data analysis tools and interpreted by scientists. Data representation and communication standards are needed to implement these steps efficiently. Here we give a classification of various standards related to systems biology and discuss various aspects of standardization in life sciences in general. Why are some standards more successful than others, what are the prerequisites for a standard to succeed and what are the possible pitfalls?     

LOV-based reporters for fluorescence imaging

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Emerging technologies: systems biology

The field of systems biology is based on the paradigm that the whole is greater than the sum of the parts. Through a combination of high-throughput experiments analyzing "-omic" scale phenomenon and the development of new computational techniques and algorithms, it is now feasible to study biological systems in a way that was previously not possible. During the 232nd National Meeting of the American Chemical Society, a session devoted to the emerging technology of Systems Biology was held. A number of talks on a wide variety of subjects covering cell signaling, network regulation and analysis, novel experimental procedures, synthetic biology, and metabolic flux analysis were presented. All of these approaches shared the common theme of using a systems biology approach to aid in the understanding of fundamental biology, with an eye toward applications for the benefit of society.     

Advanced computing for systems biology

Systems biology is based on computational modelling and simulation of large networks of interacting components. Models may be intended to capture processes, mechanisms, components and interactions at different levels of fidelity. Input data are often large and geographically disperse, and may require the computation to be moved to the data, not vice versa. In addition, complex system-level problems require collaboration across institutions and disciplines. Grid computing can offer robust, scaleable solutions for distributed data, compute and expertise. We illustrate some of the range of computational and data requirements in systems biology with three case studies: one requiring large computation but small data (orthologue mapping in comparative genomics), a second involving complex terabyte data (the Visible Cell project) and a third that is both computationally and data-intensive (simulations at multiple temporal and spatial scales). Authentication, authorisation and audit systems are currently not well scalable and may present bottlenecks for distributed collaboration particularly where outcomes may be commercialised. Challenges remain in providing lightweight standards to facilitate the penetration of robust, scalable grid-type computing into diverse user communities to meet the evolving demands of systems biology.     

Interaction networks for systems biology

Cellular functions are almost always the result of the coordinated action of several proteins, interacting in protein complexes, pathways or networks. Progress made in devising suitable tools for analysis of protein-protein interactions, have recently made it possible to chart interaction networks on a large-scale. The aim of this review is to provide a short overview of the most promising contributions of interaction networks to human biology, structural biology and human genetics.     

Mining literature for systems biology

Currently, literature is integrated in systems biology studies in three ways. Hand-curated pathways have been sufficient for assembling models in numerous studies. Second, literature is frequently accessed in a derived form, such as the concepts represented by the Medical Subject Headings (MeSH) and Gene Ontologies (GO), or functional relationships captured in protein-protein interaction (PPI) databases; both of these are convenient, consistent reductions of more complex concepts expressed as free text in the literature. Moreover, their contents are easily integrated into computational processes required for dealing with large data sets. Last, mining text directly for specific types of information is on the rise as text analytics methods become more accurate and accessible. These uses of literature, specifically manual curation, derived concepts captured in ontologies and databases, and indirect and direct application of text mining, will be discussed as they pertain to systems biology.     

Pathway information for systems biology

Pathway information is vital for successful quantitative modeling of biological systems. The almost 170 online pathway databases vary widely in coverage and representation of biological processes, making their use extremely difficult. Future pathway information systems for querying, visualization and analysis must support standard exchange formats to successfully integrate data on a large scale. Such integrated systems will greatly facilitate the constructive cycle of computational model building and experimental verification that lies at the heart of systems biology.     

Reconfigurable modular automation systems for automotive power-train manufacture

This paper describes research towards the realization of reconfigurable modular automated machines and the associated engineering methods and tools necessary to support their lifecycle needs. UK-based research, in collaboration with the Ford Motor Company and several machine builders, has resulted in the development of full-scale prototype reconfigurable modular automation systems for both engine assembly and machining applications. The implementation of an assembly system is featured in this paper. An engineering environment and associated reconfigurable component-based control system architecture have been created aimed at supporting the lifecycle needs of a new generation of agile automated systems, i.e., providing reconfigurable, easily scalable automated machinery. This approach has the potential to fit within a wider collaborative automation strategy where manufacturing systems are implemented as a conglomerate of distributed, autonomous, and reusable units.