Automated quantification of budding Saccharomyces cerevisiae using a novel image cytometry method.

The measurements of concentration, viability, and budding percentages of Saccharomyces cerevisiae are performed on a routine basis in the brewing and biofuel industries. Generation of these parameters is of great importance in a manufacturing setting, where they can aid in the estimation of product quality, quantity, and fermentation time of the manufacturing process. Specifically, budding percentages can be used to estimate the reproduction rate of yeast populations, which directly correlates with metabolism of polysaccharides and bioethanol production, and can be monitored to maximize production of bioethanol during fermentation. The traditional method involves manual counting using a hemacytometer, but this is time-consuming and prone to human error. In this study, we developed a novel automated method for the quantification of yeast budding percentages using Cellometer image cytometry. The automated method utilizes a dual-fluorescent nucleic acid dye to specifically stain live cells for imaging analysis of unique morphological characteristics of budding yeast. In addition, cell cycle analysis is performed as an alternative method for budding analysis. We were able to show comparable yeast budding percentages between manual and automated counting, as well as cell cycle analysis. The automated image cytometry method is used to analyze and characterize corn mash samples directly from fermenters during standard fermentation. Since concentration, viability, and budding percentages can be obtained simultaneously, the automated method can be integrated into the fermentation quality assurance protocol, which may improve the quality and efficiency of beer and bioethanol production processes.

Novel image cytometric method for detection of physiological and metabolic changes in Saccharomyces cerevisiae.

The studying and monitoring of physiological and metabolic changes in Saccharomyces cerevisiae (S. cerevisiae) has been a key research area for the brewing, baking, and biofuels industries, which rely on these economically important yeasts to produce their products. Specifically for breweries, physiological and metabolic parameters such as viability, vitality, glycogen, neutral lipid, and trehalose content can be measured to better understand the status of S. cerevisiae during fermentation. Traditionally, these physiological and metabolic changes can be qualitatively observed using fluorescence microscopy or flow cytometry for quantitative fluorescence analysis of fluorescently labeled cellular components associated with each parameter. However, both methods pose known challenges to the end-users. Specifically, conventional fluorescent microscopes lack automation and fluorescence analysis capabilities to quantitatively analyze large numbers of cells. Although flow cytometry is suitable for quantitative analysis of tens of thousands of fluorescently labeled cells, the instruments require a considerable amount of maintenance, highly trained technicians, and the system is relatively expensive to both purchase and maintain. In this work, we demonstrate the first use of Cellometer Vision for the kinetic detection and analysis of vitality, glycogen, neutral lipid, and trehalose content of S. cerevisiae. This method provides an important research tool for large and small breweries to study and monitor these physiological behaviors during production, which can improve fermentation conditions to produce consistent and higher-quality products.

A novel method for kinetic measurements of rare cell proliferation using Cellometer image-based cytometry.

Cell proliferation is an important assay for pharmaceutical and biomedical research to test the effects of a variety of treatments on cultured primary cells or cell lines. For immunological studies, the ability to perform rapid cell proliferation analysis allows the identification of potential biological reagents for inducing or inhibiting immune cell proliferation. Current cell proliferation analysis methods employ flow cytometry for fluorescence detection of CFSE-labeled cells. However, conventional flow cytometers require a considerable amount of cells per sample, which becomes an issue for kinetic measurements with rare cell population due to the lack of samples for flow cytometric analyses at multiple time points during proliferation period. Here we report the development of a novel cell proliferation kinetic detection method for low cell concentration samples using the new Cellometer Vision system. Since the Cellometer system requires only 20 µl of sample, cell proliferation can be measured at multiple time points over the entire culturing period, whereas typically, flow cytometry is only performed at the end of the proliferation period. To validate the detection method, B1 and B2 B cells were treated with a B cell mitogen for 6 days, and proliferation was measured using Cellometer on day 1, 3, 5, and 6. To demonstrate the capability of the system, B1 B cells were treated with a panel of TLR agonists (Pam3Cys, PolyIC, CLO97, and CpG) for 7 days, and proliferation was measured on day 2, 4, 6, and 7. Cellometer image-based cytometry (IBC) was able to obtain proliferation results on each day with the last time point comparable to flow cytometry. This novel method allows for kinetic measurements of the rare cell samples such as B1 B cell, which has the potential to revolutionize kinetic analysis of cell proliferation.

Direct concentration and viability measurement of yeast in corn mash using a novel imaging cytometry method.

Worldwide awareness of fossil-fuel depletion and global warming has been increasing over the last 30 years. Numerous countries, including the USA and Brazil, have introduced large-scale industrial fermentation facilities for bioethanol, biobutanol, or biodiesel production. Most of these biofuel facilities perform fermentation using standard baker's yeasts that ferment sugar present in corn mash, sugar cane, or other glucose media. In research and development in the biofuel industry, selection of yeast strains (for higher ethanol tolerance) and fermentation conditions (yeast concentration, temperature, pH, nutrients, etc.) can be studied to optimize fermentation performance. Yeast viability measurement is needed to identify higher ethanol-tolerant yeast strains, which may prolong the fermentation cycle and increase biofuel output. In addition, yeast concentration may be optimized to improve fermentation performance. Therefore, it is important to develop a simple method for concentration and viability measurement of fermenting yeast. In this work, we demonstrate an imaging cytometry method for concentration and viability measurements of yeast in corn mash directly from operating fermenters. It employs an automated cell counter, a dilution buffer, and staining solution from Nexcelom Bioscience to perform enumeration. The proposed method enables specific fluorescence detection of viable and nonviable yeasts, which can generate precise results for concentration and viability of yeast in corn mash. This method can provide an essential tool for research and development in the biofuel industry and may be incorporated into manufacturing to monitor yeast concentration and viability efficiently during the fermentation process.

A comparison of muscle thin filament models obtained from electron microscopy reconstructions and low-angle X-ray fibre diagrams from non-overlap muscle.

The regulation of striated muscle contraction involves changes in the interactions of troponin and tropomyosin with actin thin filaments. In resting muscle, myosin-binding sites on actin are thought to be blocked by the coiled-coil protein tropomyosin. During muscle activation, Ca2+ binding to troponin alters the tropomyosin position on actin, resulting in cyclic actin-myosin interactions that accompany muscle contraction. Evidence for this steric regulation by troponin-tropomyosin comes from X-ray data [Haselgrove, J.C., 1972. X-ray evidence for a conformational change in the actin-containing filaments of verterbrate striated muscle. Cold Spring Habor Symp. Quant. Biol. 37, 341-352; Huxley, H.E., 1972. Structural changes in actin and myosin-containing filaments during contraction. Cold Spring Habor Symp. Quant. Biol. 37, 361-376; Parry, D.A., Squire, J.M., 1973. Structural role of tropomyosin in muscle regulation: analysis of the X-ray diffraction patterns from relaxed and contracting muscles. J. Mol. Biol. 75, 33-55] and electron microscope (EM) data [Spudich, J.A., Huxley, H.E., Finch, J., 1972. Regulation of skeletal muscle contraction. II. Structural studies of the interaction of the tropomyosin-troponin complex with actin. J. Mol. Biol. 72, 619-632; O'Brien, E.J., Gillis, J.M., Couch, J., 1975. Symmetry and molecular arrangement in paracrystals of reconstituted muscle thin filaments. J. Mol. Biol. 99, 461-475; Lehman, W., Craig, R., Vibert, P., 1994. Ca2+-induced tropomyosin movement in Limulus thin filaments revealed by three-dimensional reconstruction. Nature 368, 65-67] each with its own particular strengths and limitations. Here we bring together some of the latest information from EM analysis of single thin filaments from Pirani et al. [Pirani, A., Xu, C., Hatch, V., Craig, R., Tobacman, L.S., Lehman, W. (2005). Single particle analysis of relaxed and activated muscle thin filaments. J. Mol. Biol. 346, 761-772], with synchrotron X-ray data from non-overlapped muscle fibres to refine the models of the striated muscle thin filament. This was done by incorporating current atomic-resolution structures of actin, tropomyosin, troponin and myosin subfragment-1. Fitting these atomic coordinates to EM reconstructions, we present atomic models of the thin filament that are entirely consistent with a steric regulatory mechanism. Furthermore, fitting the atomic models against diffraction data from skinned muscle fibres, stretched to non-overlap to preclude crossbridge binding, produced very similar results, including a large Ca2+-induced shift in tropomyosin azimuthal location but little change in the actin structure or apparent alteration in troponin position.

An atomic model of the thin filament in the relaxed and Ca2+-activated states.

Contraction of striated muscles is regulated by tropomyosin strands that run continuously along actin-containing thin filaments. Tropomyosin blocks myosin-binding sites on actin in resting muscle and unblocks them during Ca2+-activation. This steric effect controls myosin-crossbridge cycling on actin that drives contraction. Troponin, bound to the thin filaments, couples Ca2+-concentration changes to the movement of tropomyosin. Ca2+-free troponin is thought to trap tropomyosin in the myosin-blocking position, while this constraint is released after Ca2+-binding. Although the location and movements of tropomyosin are well known, the structural organization of troponin on thin filaments is not. Its mechanism of action therefore remains uncertain. To determine the organization of troponin on the thin filament, we have constructed atomic models of low and high-Ca2+ states based on crystal structures of actin, tropomyosin and the "core domain" of troponin, and constrained by distances between filament components and by their location in electron microscopy (EM) reconstructions. Alternative models were also built where troponin was systematically repositioned or reoriented on actin. The accuracy of the different models was evaluated by determining how well they corresponded to EM images. While the initial low and high-Ca2+ models fitted the data precisely, the alternatives did not, suggesting that the starting models best represented the correct structures. Thin filament reconstructions were generated from the EM data using these starting models as references. In addition to showing the core domain of troponin, the reconstructions showed additional detail not present in the starting models. We attribute this to an extension of TnI linking the troponin core domain to actin at low (but not at high) Ca2+, thereby trapping tropomyosin in the OFF-state. The bulk of the core domain of troponin appears not to move significantly on actin, regardless of Ca2+ level. Our observations suggest a simple model for muscle regulation in which troponin affects the charge balance on actin and hence tropomyosin position.

Single particle analysis of relaxed and activated muscle thin filaments.

The movement of tropomyosin from actin's outer to its inner domain plays a key role in sterically regulating muscle contraction. This movement, from a low Ca2+ to a Ca2+-induced position has been directly demonstrated by electron microscopy and helical reconstruction. Solution studies, however, suggest that tropomyosin oscillates dynamically between these positions at all Ca2+ levels, and that it is the position of this equilibrium that is controlled by Ca2+. Helical reconstruction reveals only the average position of tropomyosin on the filament, and not information on the local dynamics of tropomyosin in any one Ca2+ state. We have therefore used single particle analysis to analyze short filament segments to reveal local variations in tropomyosin behavior. Segments of Ca2+-free and Ca2+ treated thin filaments were sorted by cross-correlation to low and high Ca2+ models of the thin filament. Most segments from each data set produced reconstructions matching those previously obtained by helical reconstruction, showing low and high Ca2+ tropomyosin positions for low and high Ca2+ filaments. However, approximately 20% of segments from Ca2+-free filaments fitted best to the high Ca2+ model, yielding a corresponding high Ca2+ reconstruction. Conversely, approximately 20% of segments from Ca2+-treated filaments fitted best to the low Ca2+ model and produced a low Ca2+ reconstruction. Hence, tropomyosin position on actin is not fixed in either Ca2+ state. These findings provide direct structural evidence for the equilibration of tropomyosin position in both high and low Ca2+ states, and for the concept that Ca2+ controls the position of this equilibrium. This flexibility in the localization of tropomyosin may provide a means of sterically regulating contraction at low energy cost.

In the absence of type III receptor, the transforming growth factor (TGF)-beta type II-B receptor requires the type I receptor to bind TGF-beta2.

Transforming growth factor beta (TGF-beta) ligands exert their biological effects through type II (TbetaRII) and type I receptors (TbetaRI). Unlike TGF-beta1 and -beta3, TGF-beta2 appears to require the co-receptor betaglycan (type III receptor, TbetaRIII) for high affinity binding and signaling. Recently, the TbetaRIII null mouse was generated and revealed significant non-overlapping phenotypes with the TGF-beta2 null mouse, implying the existence of TbetaRIII independent mechanisms for TGF-beta2 signaling. Because a variant of the type II receptor, the type II-B receptor (TbetaRII-B), has been suggested to mediate TGF-beta2 signaling in the absence of TbetaRIII, we directly tested the ability of TbetaRII-B to bind TGF-beta2. Here we show that the soluble extracellular domain of the type II-B receptor (sTbetaRII-B.Fc) bound TGF-beta1 and TGF-beta3 with high affinity (K(d) values = 31.7 +/- 22.8 and 74.6 +/- 15.8 pm, respectively), but TGF-beta2 binding was undetectable at corresponding doses. Similar results were obtained for the soluble type II receptor (sTbetaRII.Fc). However, sTbetaRII.Fc or sTbetaRII-B.Fc in combination with soluble type I receptor (sTbetaRI.Fc) formed a high affinity complex that bound TGF-beta2, and this complex inhibited TGF-beta2 in a biological inhibition assay. These results show that TGF-beta2 has the potential to signal in the absence of TbetaRIII when sufficient TGF-beta2, TbetaRI, and TbetaRII or TbetaRII-B are present. Our data also support a cooperative model for receptor-ligand interactions, as has been suggested by crystallization studies of TGF-beta receptors and ligands. Our cell-free binding assay system will allow for testing of models of receptor-ligand complexes prior to actual solution of crystal structures.