Biopolymer and water dynamics in microbial biofilm extracellular polymeric substance

Nuclear magnetic resonance (NMR) is a noninvasive and nondestructive tool able to access several observable quantities in biofilms such as chemical composition, diffusion, and macroscale structure and transport. Pulsed gradient spin echo (PGSE) NMR techniques were used to measure spectrally resolved biomacromolecular diffusion in biofilm biomass, extending previous research on spectrally resolved diffusion in biofilms. The dominant free water signal was nulled using an inversion recovery modification of the traditional PGSE technique in which the signal from free water is minimized in order to view the spectra of components such as the rotationally mobile carbohydrates, DNA, and proteins. Diffusion data for the major constituents obtained from each of these spectral peaks demonstrate that the biomass of the biofilm contains both a fast and slow diffusion component. The dependence of diffusion on antimicrobial and environmental challenges suggests the polymer molecular dynamics measured by NMR are a sensitive indicator of biofilm function.     

Assessment of near-infrared spectral information for rapid monitoring of bioprocess quality.

Access to real-time process information is desirable for consistent and efficient operation of bioprocesses. Near-infrared spectroscopy (NIRS) is known to have potential for providing real-time information on the quantitative levels of important bioprocess variables. However, given the fact that a typical NIR spectrum encompasses information regarding almost all the constituents of the sample matrix, there are few case studies that have investigated the spectral details for applications in bioprocess quality assessment or qualitative bioprocess monitoring. Such information would be invaluable in providing operator-level assistance on the progress of a bioprocess in industrial-scale productions. We investigated this aspect and report the results of our investigation. Near-infrared spectral information derived from scanning unprocessed culture fluid (broth) samples from a complex antibiotic production process was assessed for a data set that incorporated bioprocess variations. Principal component analysis was applied to the spectral data and the loadings and scores of the principal components studied. Changes in the spectral information that corresponded to variations in the bioprocess could be deciphered. Despite the complexity of the matrix, near-infrared spectra of the culture broth are shown to have valuable information that can be deconvoluted with the help of factor analysis techniques such as principal component analysis (PCA). Although complex to interpret, the loadings and score plots are shown to offer potential in process diagnosis that could be of value in the rapid assessment of process quality, and in data assessment prior to quantitative model development.     

Spectral mapping tools from the earth sciences applied to spectral microscopy data.

BACKGROUND: Spectral imaging, originating from the field of earth remote sensing, is a powerful tool that is being increasingly used in a wide variety of applications for material identification. Several workers have used techniques like linear spectral unmixing (LSU) to discriminate materials in images derived from spectral microscopy. However, many spectral analysis algorithms rely on assumptions that are often violated in microscopy applications. This study explores algorithms originally developed as improvements on early earth imaging techniques that can be easily translated for use with spectral microscopy. METHODS: To best demonstrate the application of earth remote sensing spectral analysis tools to spectral microscopy data, earth imaging software was used to analyze data acquired with a Leica confocal microscope with mechanical spectral scanning. For this study, spectral training signatures (often referred to as endmembers) were selected with the ENVI (ITT Visual Information Solutions, Boulder, CO) "spectral hourglass" processing flow, a series of tools that use the spectrally over-determined nature of hyperspectral data to find the most spectrally pure (or spectrally unique) pixels within the data set. This set of endmember signatures was then used in the full range of mapping algorithms available in ENVI to determine locations, and in some cases subpixel abundances of endmembers. RESULTS: Mapping and abundance images showed a broad agreement between the spectral analysis algorithms, supported through visual assessment of output classification images and through statistical analysis of the distribution of pixels within each endmember class. CONCLUSIONS: The powerful spectral analysis algorithms available in COTS software, the result of decades of research in earth imaging, are easily translated to new sources of spectral data. Although the scale between earth imagery and spectral microscopy is radically different, the problem is the same: mapping material locations and abundances based on unique spectral signatures.     

Maximizing plant species inventory efficiency by means of remotely sensed spectral distances

Aim Inventorying plant species in an area based on randomly placed quadrats can be quite inefficient. The aim of this paper is to test whether plant species richness can be inventoried more efficiently by means of a spectrally‐based ordering of sites to be sampled. Location The study area was a complex wetland ecosystem, the Lake Montepulciano Nature Reserve, central Italy. This is one of the most important wetland areas of central Italy because of the diverse plant communities and the seasonal avifauna. Methods Field sampling, based on a random stratified sampling design, was performed in June 2002. Plant species composition was recorded within sampling units of 100 m² (plots) and 1 ha (macroplots). A QuickBird multispectral image of the same date was acquired and corrected both geometrically and radiometrically. Species accumulation curves based on spectral information were obtained by ordering sites to be sampled according to a maximum spectral distance criterion (i.e. by ordering sampling units based on the maximum distances among them in a four‐dimensional spectral space derived from the remotely sensed data). Different distance measures based on mean and maximum spectral distances among sampling units were tested. The performance of the species accumulation curve derived by the spectrally‐based ordering of sampling units was tested against a rarefaction curve obtained from the mean of 10,000 accumulation curves based on randomly ordered sampling units. Results The spectrally‐derived curve based on the maximum spectral distance among sampling units showed the most rapid accumulation of species, well above the rarefaction curve, at both the plot and the macroplot scales. Other ordering criteria of sampling units captured less richness over most of the species accumulation curves at both the spatial scales. The accumulation curves based on other measurements of distance were much closer to the random curve and did not show differences with respect to the species rarefaction curve based on random ordering of sampling units. Main conclusions The present investigation demonstrated that spectral‐based ordering of sites to be sampled can lead to the maximization of the efficiency of plant species inventories, an activity usually driven by the ‘botanist's internal algorithm’ (intuition), without any formalized rule to drive field sampling. The proposed approach can reduce costs of plant species inventorying through a more efficient allotment of time and sampling.     

In vivo Quantification of G Protein Coupled Receptor Interactions using Spectrally Resolved Two-photon Microscopy

The study of protein interactions in living cells is an important area of research because the information accumulated both benefits industrial applications as well as increases basic fundamental biological knowledge. Förster (Fluorescence) Resonance Energy Transfer (FRET) between a donor molecule in an electronically excited state and a nearby acceptor molecule has been frequently utilized for studies of protein-protein interactions in living cells. The proteins of interest are tagged with two different types of fluorescent probes and expressed in biological cells. The fluorescent probes are then excited, typically using laser light, and the spectral properties of the fluorescence emission emanating from the fluorescent probes is collected and analyzed. Information regarding the degree of the protein interactions is embedded in the spectral emission data. Typically, the cell must be scanned a number of times in order to accumulate enough spectral information to accurately quantify the extent of the protein interactions for each region of interest within the cell. However, the molecular composition of these regions may change during the course of the acquisition process, limiting the spatial determination of the quantitative values of the apparent FRET efficiencies to an average over entire cells. By means of a spectrally resolved two-photon microscope, we are able to obtain a full set of spectrally resolved images after only one complete excitation scan of the sample of interest. From this pixel-level spectral data, a map of FRET efficiencies throughout the cell is calculated. By applying a simple theory of FRET in oligomeric complexes to the experimentally obtained distribution of FRET efficiencies throughout the cell, a single spectrally resolved scan reveals stoichiometric and structural information about the oligomer complex under study. Here we describe the procedure of preparing biological cells (the yeast Saccharomyces cerevisiae) expressing membrane receptors (sterile 2 α-factor receptors) tagged with two different types of fluorescent probes. Furthermore, we illustrate critical factors involved in collecting fluorescence data using the spectrally resolved two-photon microscopy imaging system. The use of this protocol may be extended to study any type of protein which can be expressed in a living cell with a fluorescent marker attached to it.Download video file.^{(90M, mov)}     

Presence and significance of minor antenna components in the energy transfer sequence of the green photosynthetic bacterium Chloroflexus aurantiacus

Antenna components in the energy transfer processes of a green photosynthetic bacterium Chloroflexus aurantiacus were spectrally investigated by time-resolved fluorescence spectroscopy at −196°C on intact cells. Besides major antenna components so far reported, three minor components were resolved; those were Bchl c located at 785 nm, the baseplate Bchl a at 819 nm and Bchl a in the B808-866 complex at 910 nm. The last component was assigned to a longer wavelength antenna closely associated with a reaction center. An additional Bchl c fluorescence component was kinetically suggested to be present, which can be an energy donor to a major Bchl c. Presence of these minor components was signified in terms of (1) increase in the spectral overlap integral and (2) adjustment of the direction of dipole moments in the energy transfer sequence of intact cells.     

Partitioning plant spectral diversity into alpha and beta components

Plant spectral diversity – how plants differentially interact with solar radiation – is an integrator of plant chemical, structural, and taxonomic diversity that can be remotely sensed. We propose to measure spectral diversity as spectral variance, which allows the partitioning of the spectral diversity of a region, called spectral gamma (γ) diversity, into additive alpha (α; within communities) and beta (β; among communities) components. Our method calculates the contributions of individual bands or spectral features to spectral γ‐, β‐, and α‐diversity, as well as the contributions of individual plant communities to spectral diversity. We present two case studies illustrating how our approach can identify 'hotspots’ of spectral α‐diversity within a region, and discover spectrally unique areas that contribute strongly to β‐diversity. Partitioning spectral diversity and mapping its spatial components has many applications for conservation since high local diversity and distinctiveness in composition are two key criteria used to determine the ecological value of ecosystems.     

Excitation dynamics and heterogeneity of energy equilibration in the core antenna of photosystem I from the cyanobacterium Synechocystis sp. PCC 6803

Energy equilibration in the photosystem I core antenna from the cyanobacterium Synechocystis sp. PCC 6803 was studied using femtosecond transient absorption spectroscopy at 298 K. The photosystem I core particles were excited at 660, 693, and 710 nm with 150 fs spectrally narrow laser pulses (fwhm = 5 nm). Global analysis revealed three kinetic processes in the core antenna with lifetimes of 250-500 fs, 1.5-2.5 ps, and 20-30 ps. The first two components represent strongly excitation wavelength-dependent energy equilibration processes while the 20-30 ps phase reflects the trapping of energy by the reaction center. Excitation into the blue and red edge of the absorption band induces downhill and uphill energy flows, respectively, between different chlorophyll a spectral forms of the core. Excitation at 660 nm induces a 500 fs downhill equilibration process within the bulk of antenna while the selective excitation of long-wavelength-absorbing chlorophylls at 710 nm results in a 380 fs uphill energy transfer to the chlorophylls absorbing around 695-700 nm, presumably reaction center pigments. The 1.5-2.5 ps phases of downhill and uphill energy transfer are largely equivalent but opposite in direction, indicating energy equilibration between bulk antenna chlorophylls at 685 nm and spectral forms absorbing below 700 nm. Transient absorption spectra with excitation at 693 nm exhibit spectral evolution within approximately 2 ps of uphill energy transfer to major spectral forms at 680 nm and downhill energy transfer to red pigments at 705 nm. The 20-30 ps trapping component and P(700) photooxidation spectra derived from data on the 100 ps scale are largely excitation wavelength independent. An additional decay component of red pigments at 710 nm can be induced either by selective excitation of red pigments or by decreasing the temperature to 264 K. This component may represent one of the phases of energy transfer from inhomogeneously broadened red pigments to P(700). The data are discussed based on the available structural model of the photosystem I reaction center and its core antenna.     

A Ca2+-insensitive form of fura-2 associated with polymorphonuclear leukocytes. Assessment and accurate Ca2+ measurement

The new, fluorescent Ca2+ indicator, fura-2, promises to expand our understanding of the role of subcellular changes in Ca2+ underlying cell function. During an investigation of the role of Ca2+ in the polarization response of human polymorphonuclear leukocytes to formyl-methionyl-leucyl-phenylalanine, we found that fura-2 trapped by cells incubated with the acetoxy-methyl ester of fura-2, F2-AM, yielded measurements of Ca2+ that were depressed at rest and during the response to formyl-methionyl-leucyl-phenylalanine. Fura-2, trapped by the cells, exhibited a spectrum in the presence of saturating Ca2+ that differed from that of fura-2 free acid. We have shown that the cellular fluorescence can be spectrally decomposed into two components: one with Ca2+ sensitivity identical to fully deesterified fura-2, and another which is Ca2+-insensitive. The Ca2+-insensitive component appears to be more fluorescent than F2-AM as well as spectrally different from F2-AM. The insensitive form probably results from incomplete deesterification of F2-AM by the cells. In order to accurately measure Ca2+ in polymorphonuclear leukocytes, it is imperative to check for the presence of Ca2+-insensitive fluorescence. The contribution of Ca2+-insensitive fura-2 fluorescence can be assessed routinely from spectral data obtained by calibration of intracellular fura-2 with known [Ca2+] using ionomycin. The end-of-experiment calibration step not only ensures accurate [Ca2+] measurements in polymorphonuclear leukocytes and in other cell types that display Ca2+-insensitive, contaminating fluorescence but also yields the spectral characteristics of the insensitive species.     

Two-dimensional components and hidden dependencies provide insight into ion channel gating mechanisms

Correlations between the durations of adjacent open and shut intervals recorded from ion channels contain information about the underlying gating mechanism. This study presents an additional approach to extracting the correlation information. Detailed correlation information is obtained directly from single-channel data and quantified in a manner that can provide insight into the connections among the states underlying the gating. The information is obtained independently of any specific kinetic scheme, except for the general assumption of Markov gating. The durations of adjacent open and shut intervals are binned into two-dimensional (2-D) dwell-time distributions. The 2-D (joint) distributions are fitted with sums of 2-D exponential components to determine the number of 2-D components, their volumes, and their open and closed time constants. The dependency of each 2-D component is calculated by comparing its observed volume to the volume that would be expected if open and shut intervals paired independently. The estimated component dependencies are then used to suggest gating mechanisms and to provide a powerful means of examining whether proposed gating mechanisms have the correct connections among states. The sensitivity of the 2-D method can identify hidden components and dependencies that can go undetected by previous correlation methods.     

Simultaneous Multicolor Single-Molecule Tracking with Single-Laser Excitation via Spectral Imaging

Single-molecule tracking (SMT) offers rich information on the dynamics of underlying biological processes, but multicolor SMT has been challenging due to spectral cross talk and a need for multiple laser excitations. Here, we describe a single-molecule spectral imaging approach for live-cell tracking of multiple fluorescent species at once using a single-laser excitation. Fluorescence signals from all the molecules in the field of view are collected using a single objective and split between positional and spectral channels. Images of the same molecule in the two channels are then combined to determine both the location and the identity of the molecule. The single-objective configuration of our approach allows for flexible sample geometry and the use of a live-cell incubation chamber required for live-cell SMT. Despite a lower photon yield, we achieve excellent spatial (20–40 nm) and spectral (10–15 nm) resolutions comparable to those obtained with dual-objective, spectrally resolved Stochastic Optical Reconstruction Microscopy. Furthermore, motions of the fluorescent molecules did not cause loss of spectral resolution owing to the dual-channel spectral calibration. We demonstrate SMT in three (and potentially more) colors using spectrally proximal fluorophores and single-laser excitation, and show that trajectories of each species can be reliably extracted with minimal cross talk.     

Spectral unmixing of flavin autofluorescence components in cardiac myocytes

We applied linear unmixing approach to reveal individual components of intrinsic flavin fluorescence signal recorded in living cardiac cells by spectrally resolved confocal microscopy. Responses of whole-cell autofluorescence to modulators of cell metabolism and respiration were used as a tool of separation of its components; their spectral profiles, estimated by principal component analysis, correspond to free FAD and FAD bound to different enzymes of electron transport chain.     

Spectrally specific temporal analyses of spike-train responses to complex sounds: A unifying framework

Significant scientific and translational questions remain in auditory neuroscience surrounding the neural correlates of perception. Relating perceptual and neural data collected from humans can be useful; however, human-based neural data are typically limited to evoked far-field responses, which lack anatomical and physiological specificity. Laboratory-controlled preclinical animal models offer the advantage of comparing single-unit and evoked responses from the same animals. This ability provides opportunities to develop invaluable insight into proper interpretations of evoked responses, which benefits both basic-science studies of neural mechanisms and translational applications, e.g., diagnostic development. However, these comparisons have been limited by a disconnect between the types of spectrotemporal analyses used with single-unit spike trains and evoked responses, which results because these response types are fundamentally different (point-process versus continuous-valued signals) even though the responses themselves are related. Here, we describe a unifying framework to study temporal coding of complex sounds that allows spike-train and evoked-response data to be analyzed and compared using the same advanced signal-processing techniques. The framework uses a set of peristimulus-time histograms computed from single-unit spike trains in response to polarity-alternating stimuli to allow advanced spectral analyses of both slow (envelope) and rapid (temporal fine structure) response components. Demonstrated benefits include: (1) novel spectrally specific temporal-coding measures that are less confounded by distortions due to hair-cell transduction, synaptic rectification, and neural stochasticity compared to previous metrics, e.g., the correlogram peak-height, (2) spectrally specific analyses of spike-train modulation coding (magnitude and phase), which can be directly compared to modern perceptually based models of speech intelligibility (e.g., that depend on modulation filter banks), and (3) superior spectral resolution in analyzing the neural representation of nonstationary sounds, such as speech and music. This unifying framework significantly expands the potential of preclinical animal models to advance our understanding of the physiological correlates of perceptual deficits in real-world listening following sensorineural hearing loss.     

Simultaneous determination of hemes a, b, and c from pyridine hemochrome spectra

Two procedures for analyzing overlapping optical spectra of mixtures of pyridine hemochromes are described, and extinction coefficients of pyridine hemochromes are provided for use with these methods. In the first procedure, absorbance is measured at a number of wavelengths equal to the number of components to be analyzed. This is the minimum amount of spectral data from which the concentration of each species can be calculated. In the second procedure, absorbance is measured at a number of wavelengths greater than the number of components to be analyzed. This redundancy of information makes it impossible to fit spectra which contain contributions from additional components, unless the spectra of the additional components are equal to linear combinations of the spectra of the species being analyzed. These two procedures are generally applicable to analyses of absolute or difference spectra of mixtures of components obeying Beer's law. The sensitivity to error in the absorbance measurements is only slightly greater than that for measuring a pure component at a single wavelength.     

Flower Colours through the Lens: Quantitative Measurement with Visible and Ultraviolet Digital Photography

Background

The study of the signal-receiver relationship between flowering plants and pollinators requires a capacity to accurately map both the spectral and spatial components of a signal in relation to the perceptual abilities of potential pollinators. Spectrophotometers can typically recover high resolution spectral data, but the spatial component is difficult to record simultaneously. A technique allowing for an accurate measurement of the spatial component in addition to the spectral factor of the signal is highly desirable.

Methodology/Principal findings

Consumer-level digital cameras potentially provide access to both colour and spatial information, but they are constrained by their non-linear response. We present a robust methodology for recovering linear values from two different camera models: one sensitive to ultraviolet (UV) radiation and another to visible wavelengths. We test responses by imaging eight different plant species varying in shape, size and in the amount of energy reflected across the UV and visible regions of the spectrum, and compare the recovery of spectral data to spectrophotometer measurements. There is often a good agreement of spectral data, although when the pattern on a flower surface is complex a spectrophotometer may underestimate the variability of the signal as would be viewed by an animal visual system.

Conclusion

Digital imaging presents a significant new opportunity to reliably map flower colours to understand the complexity of these signals as perceived by potential pollinators. Compared to spectrophotometer measurements, digital images can better represent the spatio-chromatic signal variability that would likely be perceived by the visual system of an animal, and should expand the possibilities for data collection in complex, natural conditions. However, and in spite of its advantages, the accuracy of the spectral information recovered from camera responses is subject to variations in the uncertainty levels, with larger uncertainties associated with low radiance levels.     

Bumblebees directly perceive variations in the spectral quality of illumination

Individual bumblebees were tested on a task of walking along a test tunnel to collect sucrose solution in an initial training illumination condition that simulated natural daylight, and in two spectrally different illumination conditions. Compared to the training condition the bees took a significantly longer time to complete the task in conditions that simulated either an ultraviolet negative illumination environment, or an illumination environment that represented blue skylight. In a control condition, bees did not derive this cue from spectral information reflected from the dark background material. This result shows that bees can directly perceive spectral changes in illumination conditions, even in the context of a task that does not require colour processing. This potentially enables the visual system of bees to have prior knowledge about the spectral quality of illumination conditions in which they may forage. The findings are discussed in relation to both theoretical models and empirical evidence of colour constancy, and it is concluded that bees can use multiple mechanisms to solve the dilemma posed by having to find colour targets in the spectrally different illumination conditions that exist for insects visiting flowers.     

A class of linear spectral models and analyses for the study of longitudinal data

Longitudinal data can always be represented by a time series with a deterministic trend and randomly correlated residuals, the latter of which do not usually form a stationary process. The class of linear spectral models is a basis for the exploratory analysis of these data. The theory and techniques of factor analysis provide a means by which one component of the residual series can be separated from an error series, and then partitioned into a sum of randomly scaled metameters that characterize the sample paths of the residuals. These metameters, together with linear modelling techniques, are then used to partition the nonrandom trend into a determined component, which is associated with the sample paths of the residuals, and an independent inherent component. Linear spectral models are assumption-free and represent both random and nonrandom trends with fewer terms than any other mixed-effects linear model. Data on body-weight growth of juvenile mice are used in this paper to illustrate the application of linear spectral models, through a relatively sophisticated exploratory analysis.     

The colour hexagon: a chromaticity diagram based on photoreceptor excitations as a generalized representation of colour opponency

Summary A chromaticity diagram which plots the 3 photoreceptor excitations of trichromatic colour vision systems at an angle of 120° is presented. It takes into acount the nonlinear transduction process in the receptors. The resulting diagram has the outline of an equilateral hexagon. It is demonstrated by geometrical means that excitation values for any type of spectrally opponent mechanism can be read from this diagram if the weighting factors of this mechanism add up to zero. Thus, it may also be regarded as a general representation of colour opponent relations, linking graphically the Young-Helmholtz theory of trichromacy and Hering's concept of opponent colours. It is shown on a geometrical. basis that chromaticity can be coded unequivocally by any two combined spectrally opponent mechanisms, the main difference between particular mechanisms being the extension and compression of certain spectral areas. This type of graphical representation can qualitatively explain the Bezold-Brücke phenomenon. Furthermore, colour hexagon distances may be taken as standardized perceptual colour distance values for trichromatic insects, as is demonstrated by comparison with behavioural colour discrimination data of 3 hymenopteran species.     

Blind Source Separation Techniques for the Decomposition of Multiply Labeled Fluorescence Images

Methods of blind source separation are used in many contexts to separate composite data sets according to their sources. Multiply labeled fluorescence microscopy images represent such sets, in which the sources are the individual labels. Their distributions are the quantities of interest and have to be extracted from the images. This is often challenging, since the recorded emission spectra of fluorescent dyes are environment- and instrument-specific. We have developed a nonnegative matrix factorization (NMF) algorithm to detect and separate spectrally distinct components of multiply labeled fluorescence images. It operates on spectrally resolved images and delivers both the emission spectra of the identified components and images of their abundance. We tested the proposed method using biological samples labeled with up to four spectrally overlapping fluorescent labels. In most cases, NMF accurately decomposed the images into contributions of individual dyes. However, the solutions are not unique when spectra overlap strongly or when images are diffuse in their structure. To arrive at satisfactory results in such cases, we extended NMF to incorporate preexisting qualitative knowledge about spectra and label distributions. We show how data acquired through excitations at two or three different wavelengths can be integrated and that multiple excitations greatly facilitate the decomposition. By allowing reliable decomposition in cases where the spectra of the individual labels are not known or are known only inaccurately, the proposed algorithms greatly extend the range of questions that can be addressed with quantitative microscopy.     

Spectrally silent transitions in the bacteriorhodopsin photocycle.

The photocycle kinetics of bacteriorhodopsin were analyzed from 0 to 40 degrees C at 101 wavelengths (330-730 nm). The data can be satisfactorily approximated by eight exponents. The slowest component (half-time 20 ms at 20 degrees C) belongs to the 13-cis cycle. The residual seven exponentials that are sufficient to describe the all-trans photocycle indicate that at least seven intermediates of the all-trans cycle must exist, although only five spectrally distinct species (K, L, M, N, and O) have been identified. These seven exponentials and their spectra at different temperatures provide the basis for the discussion of various kinetic schemes of the relaxation. The simplest model of irreversible sequential transitions includes after the first K--> L step the quasiequilibria of L<-->M, M<-->N, and N<-->O intermediates. These quasiequilibria are controlled by rate-limiting dynamics of the protein and/or proton transfer steps outside the chromophore region. Thus there exists an apparent kinetic paradox (i.e., why is the number of exponents of relaxation (at least seven) higher than the number of distinct spectral intermediates (only five)), which can be explained by assuming that some of the transitions correspond to changes in the quasiequilibria between spectrally distinct intermediates (i.e., are spectrally silent).