Spectral flow cytometry: Fundamentals and future impact.

Spectral flow cytometry has emerged as a significant player in the cytometry marketplace, with the potential for rapid growth. Despite a slow start, the technology has made significant strides in advancing various areas of single-cell analysis utilized by the scientific community. The integration of spectral cytometry into clinical laboratories and diagnostic processes is currently underway and is expected to garner a significant level of widespread acceptance in the near future. However, incorporating a new methodological approach into existing research programs can lead to misunderstandings or even misuse. This chapter offers an introductory yet comprehensive explanation of the scientific principles that form the foundation of spectral cytometry. Specifically, it delves into the unmixing processes that are utilized for data analysis. This overview is designed for those who are new to the field and seeking an informative guide to this exciting emerging technology.

A Portable Spark-Induced Breakdown Spectroscopic (SIBS) Instrument and its Analytical Performance.

A compact spark-induced plasma spectroscopic device was developed to detect elements used in a variety of applications. The system consists of a spark generator connected to tungsten electrodes, a custom-built delay generator, and two spectrometers that together cover the ultraviolet visible (UV-Vis) range (214-631 nm). The system was evaluated by qualitatively and quantitatively sampling copper standards. Prominent spectral peaks were identified using the NIST database for atomic emissions. The effectiveness of the proposed system was also tested with a lanthanide sample (gadolinium) and provided qualitative identification of the characteristic peaks. A semi-quantitative measurement for silicon and gold was performed using variable amounts of each particulate. Silica microbeads in solution were applied to paper wafers, while gold nanoparticles were sputter-coated onto silicon wafers. Results showed a positive correlation between the intensity of the signal and the concentration of each type of particulate. The variation of signal intensity was investigated to determine the repeatability, and the coefficient of variation was lowered from 60% to 25% after averaging measurements of multiple ablations per observation.

On-the-fly decoding luminescence lifetimes in the microsecond region for lanthanide-encoded suspension arrays.

Significant multiplexing capacity of optical time-domain coding has been recently demonstrated by tuning luminescence lifetimes of the upconversion nanoparticles called 'τ-Dots'. It provides a large dynamic range of lifetimes from microseconds to milliseconds, which allows creating large libraries of nanotags/microcarriers. However, a robust approach is required to rapidly and accurately measure the luminescence lifetimes from the relatively slow-decaying signals. Here we show a fast algorithm suitable for the microsecond region with precision closely approaching the theoretical limit and compatible with the rapid scanning cytometry technique. We exploit this approach to further extend optical time-domain multiplexing to the downconversion luminescence, using luminescence microspheres wherein lifetimes are tuned through luminescence resonance energy transfer. We demonstrate real-time discrimination of these microspheres in the rapid scanning cytometry, and apply them to the multiplexed probing of pathogen DNA strands. Our results indicate that tunable luminescence lifetimes have considerable potential in high-throughput analytical sciences.

Hyperspectral cytometry.

Hyperspectral cytometry is an emerging technology for single-cell analysis that combines ultrafast optical spectroscopy and flow cytometry. Spectral cytometry systems utilize diffraction gratings or prism-based monochromators to disperse fluorescence signals from multiple labels (organic dyes, nanoparticles, or fluorescent proteins) present in each analyzed bioparticle onto linear detector arrays such as multianode photomultipliers or charge-coupled device sensors. The resultant data, consisting of a series of characterizing every analyzed cell, are not compensated by employing the traditional cytometry approach, but rather are spectrally unmixed utilizing algorithms such as constrained Poisson regression or non-negative matrix factorization. Although implementations of spectral cytometry were envisioned as early as the 1980s, only recently has the development of highly sensitive photomultiplier tube arrays led to design and construction of functional prototypes and subsequently to introduction of commercially available systems. This chapter summarizes the historical efforts and work in the field of spectral cytometry performed at Purdue University Cytometry Laboratories and describes the technology developed by Sony Corporation that resulted in release of the first commercial spectral cytometry system-the Sony SP6800. A brief introduction to spectral data analysis is also provided, with emphasis on the differences between traditional polychromatic and spectral cytometry approaches.

XML-based data model and architecture for a knowledge-based grid-enabled problem-solving environment for high-throughput biological imaging.

High-throughput biological imaging uses automated imaging devices to collect a large number of microscopic images for analysis of biological systems and validation of scientific hypotheses. Efficient manipulation of these datasets for knowledge discovery requires high-performance computational resources, efficient storage, and automated tools for extracting and sharing such knowledge among different research sites. Newly emerging grid technologies provide powerful means for exploiting the full potential of these imaging techniques. Efficient utilization of grid resources requires the development of knowledge-based tools and services that combine domain knowledge with analysis algorithms. In this paper, we first investigate how grid infrastructure can facilitate high-throughput biological imaging research, and present an architecture for providing knowledge-based grid services for this field. We identify two levels of knowledge-based services. The first level provides tools for extracting spatiotemporal knowledge from image sets and the second level provides high-level knowledge management and reasoning services. We then present cellular imaging markup language, an extensible markup language-based language for modeling of biological images and representation of spatiotemporal knowledge. This scheme can be used for spatiotemporal event composition, matching, and automated knowledge extraction and representation for large biological imaging datasets. We demonstrate the expressive power of this formalism by means of different examples and extensive experimental results.

Intracellularly grown gold nanoparticles as potential surface-enhanced Raman scattering probes.

Gold nanoparticles grown within the intracellular confines of living cells are introduced as potential surface-enhanced Raman scattering (SERS) substrates for confocal Raman spectrometry. Electron microscopy and a silver-enhanced reflectance laser scanning confocal microscopic approach were used to visualize the size, shape, and distribution of intracellularly grown gold nanoparticles (IGAuN) as small as 1 nm. Passive uptake as the conventional approach for delivering nanoparticles inside cells faces the insurmountable challenge of escaping the endosomal/lysosomal pathway. In contrast, IGAuN provides an unprecedented advantage of providing access to cytoplasm and nucleus.

Variation in genome size of argasid and ixodid ticks.

The suborder Ixodida includes many tick species of medical and veterinary importance, but little is known about the genomic characteristics of these ticks. We report the first study to determine genome size in two species of Argasidae (soft ticks) and seven species of Ixodidae (hard ticks) using flow cytometry analysis of fluorescent stained nuclei. Our results indicate a large haploid genome size (1C>1000 Mbp) for all Ixodida with a mean of 1281 Mbp (1.31+/-0.07 pg) for the Argasidae and 2671 Mbp (2.73+/-0.04 pg) for the Ixodidae. The haploid genome size of Ixodes scapularis was determined to be 2262 Mbp. We observed inter- and intra-familial variation in genome size as well as variation between strains of the same species. We explore the implications of these results for tick genome evolution and tick genomics research.

Detection of reactive oxygen species by flow cytometry after spinal cord injury.

The monitoring of reactive oxygen species (ROS) levels in injured nervous tissue is critical for both studying the mechanism of secondary damage and evaluating the effectiveness of antioxidants. Flow cytometry is an excellent method to detect ROS in cultured cells and naturally suspended individual cells. However, its use in nervous tissue is limited due to the difficulties in obtaining single cells in suspension. We have developed a new method which minimizes the error during conventional dissociation. Specifically, we introduced a fixation step (with formaldehyde) between the dye loading and dissociation. As a result, the post-injury ROS signals detected by flow cytometry increase significantly when using hydroethidine as superoxide indicator. The injury-induced elevation of ROS obtained from this new method was also in better agreement with the two other standard ROS detection methods, fluorescence microscopy and lipid peroxidation assay. Furthermore, more pronounced decrease of ROS was found in this improved method in response to treatment with a superoxide scavenger, manganese(III)tetrakis(4-benzoic acid)porphyrin. Based on these observations, we suggest that the data obtained from the cells by this new method are more accurate than those from the classic cell dissociation method that dissociates cells directly from fresh tissues.