A reconfigurable real-time compressive-sampling camera for biological applications

Many applications in biology, such as long-term functional imaging of neural and cardiac systems, require continuous high-speed imaging. This is typically not possible, however, using commercially available systems. The frame rate and the recording time of high-speed cameras are limited by the digitization rate and the capacity of on-camera memory. Further restrictions are often imposed by the limited bandwidth of the data link to the host computer. Even if the system bandwidth is not a limiting factor, continuous high-speed acquisition results in very large volumes of data that are difficult to handle, particularly when real-time analysis is required. In response to this issue many cameras allow a predetermined, rectangular region of interest (ROI) to be sampled, however this approach lacks flexibility and is blind to the image region outside of the ROI. We have addressed this problem by building a camera system using a randomly-addressable CMOS sensor. The camera has a low bandwidth, but is able to capture continuous high-speed images of an arbitrarily defined ROI, using most of the available bandwidth, while simultaneously acquiring low-speed, full frame images using the remaining bandwidth. In addition, the camera is able to use the full-frame information to recalculate the positions of targets and update the high-speed ROIs without interrupting acquisition. In this way the camera is capable of imaging moving targets at high-speed while simultaneously imaging the whole frame at a lower speed. We have used this camera system to monitor the heartbeat and blood cell flow of a water flea (Daphnia) at frame rates in excess of 1500 fps.     

Generalizing HMMs to Continuous Time for Fast Kinetics: Hidden Markov Jump Processes

The hidden Markov model (HMM) is a framework for time series analysis widely applied to single-molecule experiments. Although initially developed for applications outside the natural sciences, the HMM has traditionally been used to interpret signals generated by physical systems, such as single molecules, evolving in a discrete state space observed at discrete time levels dictated by the data acquisition rate. Within the HMM framework, transitions between states are modeled as occurring at the end of each data acquisition period and are described using transition probabilities. Yet, whereas measurements are often performed at discrete time levels in the natural sciences, physical systems evolve in continuous time according to transition rates. It then follows that the modeling assumptions underlying the HMM are justified if the transition rates of a physical process from state to state are small as compared to the data acquisition rate. In other words, HMMs apply to slow kinetics. The problem is, because the transition rates are unknown in principle, it is unclear, a priori, whether the HMM applies to a particular system. For this reason, we must generalize HMMs for physical systems, such as single molecules, because these switch between discrete states in “continuous time”. We do so by exploiting recent mathematical tools developed in the context of inferring Markov jump processes and propose the hidden Markov jump process. We explicitly show in what limit the hidden Markov jump process reduces to the HMM. Resolving the discrete time discrepancy of the HMM has clear implications: we no longer need to assume that processes, such as molecular events, must occur on timescales slower than data acquisition and can learn transition rates even if these are on the same timescale or otherwise exceed data acquisition rates.     

An improved ultrafast 2D NMR experiment: Towards atom-resolved real-time studies of protein kinetics at multi-Hz rates

Multidimensional NMR spectroscopy is a well-established technique for the characterization of structure and fast-time-scale dynamics of highly populated ground states of biological macromolecules. The investigation of short-lived excited states that are important for molecular folding, misfolding and function, however, remains a challenge for modern biomolecular NMR techniques. Off-equilibrium real-time kinetic NMR methods allow direct observation of conformational or chemical changes by following peak positions and intensities in a series of spectra recorded during a kinetic event. Because standard multidimensional NMR methods required to yield sufficient atom-resolution are intrinsically time-consuming, many interesting phenomena are excluded from real-time NMR analysis. Recently, spatially encoded ultrafast 2D NMR techniques have been proposed that allow one to acquire a 2D NMR experiment within a single transient. In addition, when combined with the SOFAST technique, such ultrafast experiments can be repeated at high rates. One of the problems detected for such ultrafast protein NMR experiments is related to the heteronuclear decoupling during detection with interferences between the pulses and the oscillatory magnetic field gradients arising in this scheme. Here we present a method for improved ultrafast data acquisition yielding higher signal to noise and sharper lines in single-scan 2D NMR spectra. In combination with a fast-mixing device, the recording of ¹H–¹⁵N correlation spectra with repetition rates of up to a few Hertz becomes feasible, enabling real-time studies of protein kinetics occurring on time scales down to a few seconds.     

A framework for intelligent data acquisition and real-time database searching for shotgun proteomics

In the analysis of complex peptide mixtures by MS-based proteomics, many more peptides elute at any given time than can be identified and quantified by the mass spectrometer. This makes it desirable to optimally allocate peptide sequencing and narrow mass range quantification events. In computer science, intelligent agents are frequently used to make autonomous decisions in complex environments. Here we develop and describe a framework for intelligent data acquisition and real-time database searching and showcase selected examples. The intelligent agent is implemented in the MaxQuant computational proteomics environment, termed MaxQuant Real-Time. It analyzes data as it is acquired on the mass spectrometer, constructs isotope patterns and SILAC pair information as well as controls MS and tandem MS events based on real-time and prior MS data or external knowledge. Re-implementing a top10 method in the intelligent agent yields similar performance to the data dependent methods running on the mass spectrometer itself. We demonstrate the capabilities of MaxQuant Real-Time by creating a real-time search engine capable of identifying peptides "on-the-fly" within 30 ms, well within the time constraints of a shotgun fragmentation "topN" method. The agent can focus sequencing events onto peptides of specific interest, such as those originating from a specific gene ontology (GO) term, or peptides that are likely modified versions of already identified peptides. Finally, we demonstrate enhanced quantification of SILAC pairs whose ratios were poorly defined in survey spectra. MaxQuant Real-Time is flexible and can be applied to a large number of scenarios that would benefit from intelligent, directed data acquisition. Our framework should be especially useful for new instrument types, such as the quadrupole-Orbitrap, that are currently becoming available.     

Real-time impedance analysis of host cell response to meningococcal infection

Measuring cell proliferation and cell death during bacterial infection involves performing end-point assays that represent the response at a single time point. A new technology from Roche Applied Science and ACEA Biosciences allows continuous monitoring of cells in real-time using specialized cell culture microplates containing micro-electrodes. The xCELLigence system enables continuous measurement and quantification of cell adhesion, proliferation, spreading, cell death and detachment, thus creating a picture of cell function during bacterial infection. Furthermore, lag and log phases can be determined to estimate optimal times to infect cells.In this study we used this system to provide valuable insights into cell function in response to several virulence factors of the meningitis causing pathogen Neisseria meningitidis, including the lipopolysaccharide (LPS), the polysaccharide capsule and the outer membrane protein Opc. We observed that prolonged time of infection with pathogenic Neisseria strains led to morphological changes including cell rounding and loss of cell-cell contact, thus resulting in changed electrical impedance as monitored in real-time. Furthermore, cell function in response to 14 strains of apathogenic Neisseria spp. (N. lactamica and N. mucosa) was analyzed. In contrast, infection with apathogenic N. lactamica isolates did not change electrical impedance monitored for 48 h. Together our data show that this system can be used as a rapid monitoring tool for cellular function in response to bacterial infection and combines high data acquisition rates with ease of handling.     

Enhanced production of L-(+)-lactic acid in chemostat by Lactobacillus casei DSM 20011 using ion-exchange resins and cross-flow filtration in a fully automated pilot plant controlled via NIR

Due to the lack of suitable in-process sensors, on-line monitoring of fermentation processes is restricted almost exclusively to the measurement of physical parameters only indirectly related to key process variables, i.e., substrate, product, and biomass concentration. This obstacle can be overcome by near infrared (NIR) spectroscopy, which allows not only real-time process monitoring, but also automated process control, provided that NIR-generated information is fed to a suitable computerized bioreactor control system. Once the relevant calibrations have been obtained, substrate, biomass and product concentration can be evaluated on-line and used by the bioreactor control system to manage the fermentation. In this work, an NIR-based control system allowed the full automation of a small-scale pilot plant for lactic acid production and provided an excellent tool for process optimization. The growth-inhibiting effect of lactic acid present in the culture broth is enhanced when the growth-limiting substrate, glucose, is also present at relatively high concentrations. Both combined factors can result in a severe reduction of the performance of the lactate production process. A dedicated software enabling on-line NIR data acquisition and reduction, and automated process management through feed addition, culture removal and/or product recovery by microfiltration was developed in order to allow the implementation of continuous fermentation processes with recycling of culture medium and cell recycling. Both operation modes were tested at different dilution rates and the respective cultivation parameters observed were compared with those obtained in a conventional continuous fermentation. Steady states were obtained in both modes with high performance on lactate production. The highest lactate volumetric productivity, 138 g L(-1) h(-1), was obtained in continuous fermentation with cell recycling.     

Data acquisition and control of a continuous fermentation unit

Summary Data acquisition and computer control ofZymomonas mobilis fermentation for ethanol production has been studied. An HP 200 series microcomputer system was used in conjunction with an HP 3497A data acquisition unit. On-line ethanol, glucose and cell mass were measured for use as possible control variables. Dilution rate was used as the manipulative variable. A versatile, user-friendly data acquisition program was written to gather, control and analyze data from the continuous fermentation. The program allows user-given control and calibration algorithms so that sophisticated control policies, e.g., self-tuning regulator (STR) and instrumentation, can be implemented with relative ease.     

Surgical Technique for the Implantation of Tissue Engineered Vascular Grafts and Subsequent In Vivo Monitoring

The development of Tissue Engineered Vessels (TEVs) is advanced by the ability to routinely and effectively implant TEVs (4-5 mm in diameter) into a large animal model. A step by-step protocol for inter-positional placement of the TEV and real-time digital assessment of the TEV and native carotid arteries is described here. In vivo monitoring is made possible by the implantation of flow probes, catheters and ultrasonic crystals (capable of recording dynamic diameter changes of implanted TEVs and native carotid arteries) at the time of surgery. Once implanted, researchers can calculate arterial blood flow patterns, invasive blood pressure and artery diameter yielding parameters such as pulse wave velocity, augmentation index, pulse pressures and compliance. Data acquisition is accomplished using a single computer program for analysis throughout the duration of the experiment. Such invaluable data provides insight into TEV matrix remodeling, its resemblance to native/sham controls and overall TEV performance in vivo.     

Synchronous fluorescence spectroscopy as a novel tool to enable PAT applications in bioprocesses

In this work, synchronous fluorescence spectroscopy (SFS) is evaluated as a new tool for real-time bioprocess monitoring of animal cell cultures. This technique presents several advantages over the traditional two-dimensional (2D) fluorometry since it provides data on various fluorescent compounds in a single spectrum, showing improved peak resolution and recording speed. Bioreactor cultures of three monoclonal antibody-producing CHO cell lines were followed in situ by both 2D and synchronous fluorometry techniques. The time profiles of the main spectral features in each data type present some differences, but principal component analysis indicated both as containing enough information to distinguish the cultures. Partial least squares regression models were then independently developed for viable cell density and antibody levels on the basis of the different fluorescence signals recorded, hiding half of the dataset for subsequent validation purposes. Regardless of the signal used, model predictions fit very well the off-line measurements; still, the synchronous spectra collected at a wavelength difference of 20 nm allowed comparable and superior performances for cell density and antibody titer, respectively, with validation accuracies higher than 91%. Therefore, SFS compares favorably with the traditional 2D approach, becoming an improved, faster option for real-time monitoring of cells and product titer over culture time. The readiness in data acquisition facilitates the design of process control strategies meeting the requirements of a PAT application.     

A low-cost microcomputer-based data acquisition and analysis system for an electron spin resonance spectrometer: data handling of dilute spin labeled nucleic acids

This article describes the construction of an inexpensive and reliable data acquisition system for a Varian E-line Century Series ESR spectrometer utilizing an Apple II Plus microcomputer. All necessary hardware is readily available and used without modification. A BASIC program for routine collection, display, plotting and disk storage of experimental data has been written and subsequently compiled into machine code for high speed operation. The interface offers distinct advantages in spectral resolution as well as instrument control. An example of signal enhancement via computer controlled time averaging is presented for a spin labeled DNA experiment. The technique has recently been applied to studies of relative binding affinities of gene-32 protein for various spin-labeled polynucleotides.     

Development of a novel automated ion channel recording method using "inside-out" whole-cell membranes

Efforts to develop novel methods for recording from ion channels have been receiving increased attention in recent years. In this study, the authors report a unique "inside-out" whole-cell configuration of patch-clamp recording that has been developed. This method entails adding cells into a standard patch pipette and, with positive pressure, obtaining a gigaseal recording from a cell at the inside tip of the electrode. In this configuration, the cell may be moved through the air, first rupturing part of the cellular membrane and enabling bath access to the intracellular side of the membrane, and then into a series of wells containing differing solutions, enabling robotic control of all the steps in an experiment. The robotic system developed here fully automates the electrophysiological experiments, including gigaseal formation, obtaining whole-cell configuration, data acquisition, and drug application. Proof-of-principle experiments consisting of application of intracellularly acting potassium channel blockers to K+ channel cell lines resulted in a very rapid block, as well as block reversal, of the current. This technique allows compound application directly to the intracellular side of ion channels and enables the dissociation of compound in activities due to cellular barrier limitations. This technique should allow for parallel implementation of recording pipettes and the future development of larger array-based screening methods.     

神经电生理信号多道同步采集和分析系统

单细胞多点同步记录技术在国内外已经被广泛应用,但在国内仍缺乏与国产或日产细胞电生理记录仪器相匹配的多通道同步生物电信号采集与分析系统。本文介绍了新近研制的可进行双通道甚至晚多通道细胞电生理信号采集的神经细胞电生理信号采集与分析系统,及其关键技术及实现方法和应用实例。     

Two-parameter data acquisition system for rapid slit-scan analysis of mammalian chromosomes

A data acquisition system is described for recording two independent signals simultaneously from a laser-based flow cytometer for rapid slit-scan chromosome analysis. High-aperture microscope optics allow recording of fluorescence distributions along the longest axis of metaphase chromosomes with a spatial resolution better than 1 micron. Fluorescence and small angle forward light scatter as well as dual-wavelength fluorescence signals from Indian muntjac chromosomes stained with propidium iodide (PI) or acridine orange (AO) have been recorded simultaneously. While maintaining the multi-user operation of the computer, photomultiplier signals are digitized at a rate of 400 signals per second, stored temporarily in high-speed cache memories, and transferred subsequently to a minicomputer for further storage. Extensive software packages for data acquisition, analysis, and display of the results are described. Data acquisition is generally done in list mode, allowing complete reconstruction of individual signals (profiles) at any time. The distribution of stained constituents along the chromosomes can be displayed. Furthermore, histograms of various parameters of the input signals may be generated.     

Application of green analytical chemistry to a green chemistry process: Magnetic resonance and Raman spectroscopic process monitoring of continuous ethanolic fermentation

Compact ¹H NMR and Raman spectrometers were used for real-time process monitoring of alcoholic fermentation in a continuous flow reactor. Yeast cells catalyzing the sucrose conversion were immobilized in alginate beads floating in the reactor. The spectrometers proved to be robust and could be easily attached to the reaction apparatus. As environmentally friendly analysis methods, ¹H NMR and Raman spectroscopy were selected to match the resource- and energy-saving process. Analyses took only a few seconds to minutes compared to chromatographic procedures and were, therefore, suitable for real-time control realized as a feedback loop. Both compact spectrometers were successfully implemented online. Raman spectroscopy allowed for faster spectral acquisition and higher quantitative precision, NMR yielded more resolved signals thus higher specificity. By using the software Matlab for automated data loading and processing, relevant parameters such as the ethanol, glycerol, and sugar content could be easily obtained. The subsequent multivariate data analysis using partial linear least-squares regression type 2 enabled the quantitative monitoring of all reactants within a single model in real time.     

Optical Data Compression in Time Stretch Imaging

Time stretch imaging offers real-time image acquisition at millions of frames per second and subnanosecond shutter speed, and has enabled detection of rare cancer cells in blood with record throughput and specificity. An unintended consequence of high throughput image acquisition is the massive amount of digital data generated by the instrument. Here we report the first experimental demonstration of real-time optical image compression applied to time stretch imaging. By exploiting the sparsity of the image, we reduce the number of samples and the amount of data generated by the time stretch camera in our proof-of-concept experiments by about three times. Optical data compression addresses the big data predicament in such systems.     

Design and demonstration of an automated cell-based biosensor.

Cell-based biosensors have the capacity to respond to a wide range of analytes in a physiologically relevant manner and appear well-suited for toxicity monitoring of both known and unknown analytes. One means of acquiring cellular functional information for biosensor applications involves extracellular recording from excitable cells, which can generate noninvasive and long-term measurements. Previous work from our laboratory described a prototype portable system capable of high signal-to-noise extracellular recordings, in spite of deficiencies in thermal control, fluidics handling, and absence of data acquisition (DAQ) capability. The present work describes a cell-based biosensor system that incorporates low noise amplifier and filter boards, a two-stage thermal control system with integrated fluidics and a flexible graphical user interface for DAQ and control implemented on a personal computer. Wherever possible, commercial off-the-shelf components have been utilized for system design and fabrication. The system exhibits input-referred noise levels of 5-10 microV(RMS), such that extracellular potentials exceeding 50-60 microV can be readily resolved. In addition, the biosensor system is capable of automated temperature and fluidics control. Flow rates can range from 0-2.5 ml/min, while the cell recording chamber temperature is maintained within a range of 36-37 degrees C. To demonstrate the capability of this system to resolve small extracellular potentials, recordings from embryonic chick cardiac myocytes have been performed.     

Adaptive Imaging Cytometry to Estimate Parameters of Gene Networks Models in Systems and Synthetic Biology

The use of microfluidics in live cell imaging allows the acquisition of dense time-series from individual cells that can be perturbed through computer-controlled changes of growth medium. Systems and synthetic biologists frequently perform gene expression studies that require changes in growth conditions to characterize the stability of switches, the transfer function of a genetic device, or the oscillations of gene networks. It is rarely possible to know a priori at what times the various changes should be made, and the success of the experiment is unknown until all of the image processing is completed well after the completion of the experiment. This results in wasted time and resources, due to the need to repeat the experiment to fine-tune the imaging parameters. To overcome this limitation, we have developed an adaptive imaging platform called GenoSIGHT that processes images as they are recorded, and uses the resulting data to make real-time adjustments to experimental conditions. We have validated this closed-loop control of the experiment using galactose-inducible expression of the yellow fluorescent protein Venus in Saccharomyces cerevisiae. We show that adaptive imaging improves the reproducibility of gene expression data resulting in more accurate estimates of gene network parameters while increasing productivity ten-fold.     

Spatial pattern analysis in forest dynamics: deviation from power law and direction of regeneration waves

Grid-based models have been used to understand spatial heterogeneity of the vegetation height in forests and to analyze spatio-temporal dynamics of the forest regeneration process. In this report, we present two methods of identifying lattice models when spatio-temporal data are given. The first method detects directionality of regeneration waves based on the timing of local disturbance events. The second evaluates the forest pattern by recording the fraction of high and low vegetation areas at multiple spatial scales. We illustrate these methods by applying them to patterns generated using three simple stochastic lattice models: (1) two-state model, distinguishing sites with high and low vegetation, (2) three-state model, in which sites can be in an additional disturbed state, and (3) Shimagare model, which considers a continuous range of states. The combination of the two methods provides efficient means of distinguishing the models. The first method has a more direct ecological meaning, while the second is useful when forest data are limited in time.     

A simple method for high temporal resolution calcium imaging with dual excitation dyes.

Calcium-sensitive dual excitation dyes, such as fura-2, are now widely used to measure the free calcium concentration ([Ca2+]) in living cells. Preferentially, [Ca2+] is calculated in a ratiometric manner, but if calcium images need to be acquired at high temporal resolution, a potential drawback of ratiometry is that it requires equally fast switching of the excitation light between two wavelengths. To circumvent continuous excitation switching, some investigators have devised methods for calculating [Ca2+] from single-wavelength measurements combined with the acquisition of a single ratiometric pair of fluorescence images at the start of the recording. These methods, however, are based on the assumption that the concentration of the dye does not change during the experiment, a condition that is often not fulfilled. We describe here a method of single-wavelength calcium imaging, in which the dye concentration is estimated from ratiometric fluorescence image pairs acquired at regular intervals during the recording period, that furthermore includes a correction for the changing dye concentration in the calculation of [Ca2+].