Wide-field probing of silica laser-induced damage precursors by photoluminescence photochemical quenching.

We describe a wide-field approach to probe transient changes in photoluminescence (PL) of defects on silica surfaces. This technique allows simultaneous capture of spatially resolved PL with spontaneous quenching behavior. We attribute the quenching of PL intensity to photochemical reactions of surface defects and/or subsurface fractures with ambient molecules. Such quenching curves can be accurately reproduced by our theoretical model using two quenchable defect populations with different reaction rates. The fitting parameters of our model are spatially correlated to fractures in silica where point defects and mechanical stresses are known to be present, potentially indicating regions prone to laser-induced damage growth. We believe that our approach allows rapid spatial resolved identification of damage prone morphology, providing a new pathway to fast, non-destructive predictions of laser-induced damage growth.

Tailored approach to study Legionella infection using a lattice light sheet microscope (LLSM).

Legionella is a genus of ubiquitous environmental pathogens found in freshwater systems, moist soil, and composted materials. More than four decades of Legionella research has provided important insights into Legionella pathogenesis. Although standard commercial microscopes have led to significant advances in understanding Legionella pathogenesis, great potential exists in the deployment of more advanced imaging techniques to provide additional insights. The lattice light sheet microscope (LLSM) is a recently developed microscope for 4D live cell imaging with high resolution and minimum photo-damage. We built a LLSM with an improved version for the optical layout with two path-stretching mirror sets and a novel reconfigurable galvanometer scanner (RGS) module to improve the reproducibility and reliability of the alignment and maintenance of the LLSM. We commissioned this LLSM to study Legionella pneumophila infection with a tailored workflow designed over instrumentation, experiments, and data processing methods. Our results indicate that Legionella pneumophila infection is correlated with a series of morphological signatures such as smoothness, migration pattern and polarity both statistically and dynamically. Our work demonstrates the benefits of using LLSM for studying long-term questions in bacterial infection. Our free-for-use modifications and workflow designs on the use of LLSM system contributes to the adoption and promotion of the state-of-the-art LLSM technology for both academic and commercial applications.

Biophysical Characterization of Membrane Proteins Embedded in Nanodiscs Using Fluorescence Correlation Spectroscopy.

Proteins embedded in biological membranes perform essential functions in all organisms, serving as receptors, transporters, channels, cell adhesion molecules, and other supporting cellular roles. These membrane proteins comprise ~30% of all human proteins and are the targets of ~60% of FDA-approved drugs, yet their extensive characterization using established biochemical and biophysical methods has continued to be elusive due to challenges associated with the purification of these insoluble proteins. In response, the development of nanodisc techniques, such as nanolipoprotein particles (NLPs) and styrene maleic acid polymers (SMALPs), allowed membrane proteins to be expressed and isolated in solution as part of lipid bilayer rafts with defined, consistent nanometer sizes and compositions, thus enabling solution-based measurements. Fluorescence correlation spectroscopy (FCS) is a relatively simple yet powerful optical microscopy-based technique that yields quantitative biophysical information, such as diffusion kinetics and concentrations, about individual or interacting species in solution. Here, we first summarize current nanodisc techniques and FCS fundamentals. We then provide a focused review of studies that employed FCS in combination with nanodisc technology to investigate a handful of membrane proteins, including bacteriorhodopsin, bacterial division protein ZipA, bacterial membrane insertases SecYEG and YidC, Yersinia pestis type III secretion protein YopB, yeast cell wall stress sensor Wsc1, epidermal growth factor receptor (EGFR), ABC transporters, and several G protein-coupled receptors (GPCRs).

Wavefront shaping with a Hadamard basis for scattering soil imaging.

Soil is a scattering medium that inhibits imaging of plant-microbial-mineral interactions that are essential to plant health and soil carbon sequestration. However, optical imaging in the complex medium of soil has been stymied by the seemingly intractable problems of scattering and contrast. Here, we develop a wavefront shaping method based on adaptive stochastic parallel gradient descent optimization with a Hadamard basis to focus light through soil mineral samples. Our approach allows a sparse representation of the wavefront with reduced dimensionality for the optimization. We further divide the used Hadamard basis set into subsets and optimize a certain subset at once. Simulation and experimental optimization results demonstrate our method has an approximately seven times higher convergence rate and overall better performance compared to that with optimizing all pixels at once. The proposed method can benefit other high-dimensional optimization problems in adaptive optics and wavefront shaping.

Label-Free Multiphoton Imaging of Microbes in Root, Mineral, and Soil Matrices with Time-Gated Coherent Raman and Fluorescence Lifetime Imaging.

Imaging biogeochemical interactions in complex microbial systems─such as those at the soil-root interface─is crucial to studies of climate, agriculture, and environmental health but complicated by the three-dimensional (3D) juxtaposition of materials with a wide range of optical properties. We developed a label-free multiphoton nonlinear imaging approach to provide contrast and chemical information for soil microorganisms in roots and minerals with epi-illumination by simultaneously imaging two-photon excitation fluorescence (TPEF), coherent anti-Stokes Raman scattering (CARS), second-harmonic generation (SHG), and sum-frequency mixing (SFM). We used fluorescence lifetime imaging (FLIM) and time gating to correct CARS for the autofluorescence background native to soil particles and fungal hyphae (TG-CARS) using time-correlated single-photon counting (TCSPC). We combined TPEF, TG-CARS, and FLIM to maximize image contrast for live fungi and bacteria in roots and soil matrices without fluorescence labeling. Using this instrument, we imaged symbiotic arbuscular mycorrhizal fungi (AMF) structures within unstained plant roots in 3D to 60 µm depth. High-quality imaging was possible at up to 30 µm depth in a clay particle matrix and at 15 µm in complex soil preparation. TG-CARS allowed us to identify previously unknown lipid droplets in the symbiotic fungus, Serendipita bescii. We also visualized unstained putative bacteria associated with the roots of Brachypodium distachyon in a soil microcosm. Our results show that this multimodal approach holds significant promise for rhizosphere and soil science research.

Determination of the Maturation Status of Dendritic Cells by Applying Pattern Recognition to High-Resolution Images.

The maturation or activation status of dendritic cells (DCs) directly correlates with their behavior and immunofunction. A common means to determine the maturity of dendritic cells is from high-resolution images acquired via scanning electron microscopy (SEM) or atomic force microscopy (AFM). While direct and visual, the determination has been made by directly looking at the images by researchers. This work reports a machine learning approach using pattern recognition in conjunction with cellular biophysical knowledge of dendritic cells to determine the maturation status of dendritic cells automatically. The determination from AFM images reaches 100% accuracy. The results from SEM images reaches 94.9%. The results demonstrate the accuracy of using machine learning for accelerating data analysis, extracting information, and drawing conclusions from high-resolution cellular images, paving the way for future applications requiring high-throughput and automation, such as cellular sorting and selection based on morphology, quantification of cellular structure, and DC-based immunotherapy.

Applying Pattern Recognition to High-Resolution Images to Determine Cellular Signaling Status.

Two frequently used tools to acquire high- resolution images of cells are scanning electron microscopy (SEM) and atomic force microscopy (AFM). The former provides a nanometer resolution view of cellular features rapidly and with high throughput, while the latter enables visualizing hydrated and living cells. In current practice, these images are viewed by eye to determine cellular status, e.g., activated versus resting. Automatic and quantitative data analysis is lacking. This paper develops an algorithm of pattern recognition that works very effectively for AFM and SEM images. Using rat basophilic leukemia cells, our approach creates a support vector machine to automatically classify resting and activated cells. Ten-fold cross-validation with cells that are known to be activated or resting gives a good estimate of the generalized classification results. The pattern recognition of AFM images achieves 100% accuracy, while SEM reaches 95.4% for our images as well as images published in prior literature. This outcome suggests that our methodology could become an important and frequently used tool for researchers utilizing AFM and SEM for structural characterization as well as determining cellular signaling status and function.

Expression and Association of the Yersinia pestis Translocon Proteins, YopB and YopD, Are Facilitated by Nanolipoprotein Particles.

Yersinia pestis enters host cells and evades host defenses, in part, through interactions between Yersinia pestis proteins and host membranes. One such interaction is through the type III secretion system, which uses a highly conserved and ordered complex for Yersinia pestis outer membrane effector protein translocation called the injectisome. The portion of the injectisome that interacts directly with host cell membranes is referred to as the translocon. The translocon is believed to form a pore allowing effector molecules to enter host cells. To facilitate mechanistic studies of the translocon, we have developed a cell-free approach for expressing translocon pore proteins as a complex supported in a bilayer membrane mimetic nano-scaffold known as a nanolipoprotein particle (NLP) Initial results show cell-free expression of Yersinia pestis outer membrane proteins YopB and YopD was enhanced in the presence of liposomes. However, these complexes tended to aggregate and precipitate. With the addition of co-expressed (NLP) forming components, the YopB and/or YopD complex was rendered soluble, increasing the yield of protein for biophysical studies. Biophysical methods such as Atomic Force Microscopy and Fluorescence Correlation Spectroscopy were used to confirm that the soluble YopB/D complex was associated with NLPs. An interaction between the YopB/D complex and NLP was validated by immunoprecipitation. The YopB/D translocon complex embedded in a NLP provides a platform for protein interaction studies between pathogen and host proteins. These studies will help elucidate the poorly understood mechanism which enables this pathogen to inject effector proteins into host cells, thus evading host defenses.

Protective spin-labeled fluorenes maintain amyloid beta peptide in small oligomers and limit transitions in secondary structure.

Alzheimer's disease is characterized by the presence of extracellular plaques comprised of amyloid beta (Aß) peptides. Soluble oligomers of the Aß peptide underlie a cascade of neuronal loss and dysfunction associated with Alzheimer's disease. Single particle analyses of Aß oligomers in solution by fluorescence correlation spectroscopy (FCS) were used to provide real-time descriptions of how spin-labeled fluorenes (SLFs; bi-functional small molecules that block the toxicity of Aß) prevent and disrupt oligomeric assemblies of Aß in solution. Furthermore, the circular dichroism (CD) spectrum of untreated Aß shows a continuous, progressive change over a 24-hour period, while the spectrum of Aß treated with SLF remains relatively constant following initial incubation. These findings suggest the conformation of Aß within the oligomer provides a complementary determinant of Aß toxicity in addition to oligomer growth and size. Although SLF does not produce a dominant state of secondary structure in Aß, it does induce a net reduction in beta secondary content compared to untreated samples of Aß. The FCS results, combined with electron paramagnetic resonance spectroscopy and CD spectroscopy, demonstrate SLFs can inhibit the growth of Aß oligomers and disrupt existing oligomers, while retaining Aß as a population of smaller, yet largely disordered oligomers.

Engineered Nanostructures of Haptens Lead to Unexpected Formation of Membrane Nanotubes Connecting Rat Basophilic Leukemia Cells.

A recent finding reports that co-stimulation of the high-affinity immunoglobulin E (IgE) receptor (FcεRI) and the chemokine receptor 1 (CCR1) triggered formation of membrane nanotubes among bone-marrow-derived mast cells. The co-stimulation was attained using corresponding ligands: IgE binding antigen and macrophage inflammatory protein 1α (MIP1 α), respectively. However, this approach failed to trigger formation of nanotubes among rat basophilic leukemia (RBL) cells due to the lack of CCR1 on the cell surface (Int. Immunol. 2010, 22 (2), 113-128). RBL cells are frequently used as a model for mast cells and are best known for antibody-mediated activation via FcεRI. This work reports the successful formation of membrane nanotubes among RBLs using only one stimulus, a hapten of 2,4-dinitrophenyl (DNP) molecules, which are presented as nanostructures with our designed spatial arrangements. This observation underlines the significance of the local presentation of ligands in the context of impacting the cellular signaling cascades. In the case of RBL, certain DNP nanostructures suppress antigen-induced degranulation and facilitate the rearrangement of the cytoskeleton to form nanotubes. These results demonstrate an important scientific concept; engineered nanostructures enable cellular signaling cascades, where current technologies encounter great difficulties. More importantly, nanotechnology offers a new platform to selectively activate and/or inhibit desired cellular signaling cascades.

Gigashot optical degradation in silica optics at 351 nm.

As applications of lasers demand higher average powers, higher repetition rates, and longer operation times, optics will need to perform well under unprecedented conditions. We investigate the optical degradation of fused silica surfaces at 351 nm for up to 10(9) pulses with pulse fluences up to 12 J/cm(2). The central result is that the transmission loss from defect generation is a function of the pulse intensity, I(p), and total integrated fluence, φ(T), and is influenced by oxygen partial pressure. In 10(-6) Torr vacuum, at low I(p), a transmission loss is observed that increases monotonically as a function of number of pulses. As the pulse intensity increases above 13 MW/cm(2), the observed transmission losses decrease, and are not measureable for 130 MW/cm(2). A physical model which supports the experimental data is presented to describe the suppression of transmission loss at high pulse intensity. Similar phenomena are observed in anti-reflective sol-gel coated optics. Absorption, not scattering, is the primary mechanism leading to transmission loss. In 2.5 Torr air, no transmission loss was detected under any pulse intensity used. We find that the absorption layer that leads to transmission loss is less than 1 nm in thickness, and results from a laser-activated chemical process involving photo-reduction of silica within a few monolayers of the surface. The competition between photo-reduction and photo-oxidation explains the measured data: transmission loss is reduced when either the light intensity or the O(2) concentration is high. We expect processes similar to these to occur in other optical materials for high average power applications.

Fluorescence correlation spectroscopy at micromolar concentrations without optical nanoconfinement.

Fluorescence correlation spectroscopy (FCS) is an important technique for studying biochemical interactions dynamically that may be used in vitro and in cell-based studies. It is generally claimed that FCS may only be used at nM concentrations. We show that this general consensus is incorrect and that the limitation to nM concentrations is not fundamental but due to detector limits as well as laser fluctuations. With a high count rate detector system and applying laser fluctuation corrections, we demonstrate FCS measurements up to 38 µM with the same signal-to-noise as at lower concentrations. Optical nanoconfinement approaches previously used to increase the concentration range of FCS are not necessary, and further increases above 38 µM may be expected using detectors and detector arrays with higher saturation rates and better laser fluctuation corrections. This approach greatly widens the possibilities of dynamic measurements of biochemical interactions using FCS at physiological concentrations.

Quantifying interactions of a membrane protein embedded in a lipid nanodisc using fluorescence correlation spectroscopy.

Using fluorescence correlation spectroscopy, we measured a dissociation constant of 20 nM between EGFP-labeled LcrV from Yersinia pestis and its cognate membrane-bound protein YopB inserted into a lipid nanodisc. The combination of fluorescence correlation spectroscopy and nanodisc technologies provides a powerful approach to accurately measure binding constants of interactions between membrane bound and soluble proteins in solution. Straightforward sample preparation, acquisition, and analysis procedures make this combined technology attractive for accurately measuring binding kinetics for this important class of protein-protein interactions.

Advances in superresolution optical fluctuation imaging (SOFI).

We review the concept of superresolution optical fluctuation imaging (SOFI), discuss its attributes and trade-offs (in comparison with other superresolution methods), and present superresolved images taken on samples stained with quantum dots, organic dyes, and plasmonic metal nanoparticles. We also discuss the prospects of SOFI for live cell superresolution imaging and for imaging with other (non-fluorescent) contrasts.

Binding of apolipoprotein E inhibits the oligomer growth of amyloid-ß peptide in solution as determined by fluorescence cross-correlation spectroscopy.

One of the primary neuropathological hallmarks of Alzheimer disease is the presence of extracellular amyloid plaques resulting from the aggregation of amyloid-ß (Aß) peptides. The intrinsic disorder of the Aß peptide drives self-association and progressive reordering of the conformation in solution, and this dynamic distribution of Aß complicates biophysical studies. This property poses a challenge for understanding the interaction of Aß with apolipoprotein E (apoE). ApoE plays a pivotal role in the aggregation and clearance of Aß peptides in the brain, and the ε4 allele of APOE is the most significant known genetic modulator of Alzheimer risk. Understanding the interaction between apoE and Aß will provide insight into the mechanism by which different apoE isoforms determine Alzheimer disease risk. Here we applied alternating laser excitation fluorescence cross-correlation spectroscopy to observe the single molecule interaction of Aß with apoE in the hydrated state. The diffusion time of freely diffusing Aß in the absence of apoE shows significant self-aggregation, whereas in the presence of apoE, binding of the protein results in a more stable complex. These results show that apoE slows down the oligomerization of Aß in solution and provide direct insight into the process by which apoE influences the deposition and clearance of Aß peptides in the brain. Furthermore, by developing an approach to remove signals arising from very large Aß aggregates, we show that real-time single particle observations provide access to information regarding the fraction of apoE bound and the stoichiometry of apoE and Aß in the complex.

Single-step nanoplasmonic VEGF165 aptasensor for early cancer diagnosis.

Early cancer diagnosis is very important for the prevention or mitigation of metastasis. However, effective and efficient methods are needed to improve the diagnosis and assessment of cancer. Here, we report a single-step detection method using a nanoplasmonic aptamer sensor (aptasensor), targeting a vascular endothelial growth factor-165 (VEGF(165)), a predominant biomarker of cancer angiogenesis. Our single-step detection is accomplished by (1) specific target recognition by an aptamer-target molecule interaction and (2) direct readouts of the target recognition. The readout is achieved by inactivation of surface plasmon enhancement of fluorescent probes preattached to the aptamers. Our aptasensor provides the appropriate sensitivity for clinical diagnostics with a wide range of linear detection from 25 pg/mL to 25 µg/mL (=from 1.25 pM to 1.25 µM), high specificity for VEGF(165) against PDGF-BB, osteopontin (OPN), VEGF(121), NaCl, and temporal/thermal/biological stability. In experiments with 100% serum and saliva from clinical samples, readouts of the aptasensor and an ELISA for VEGF(165) show good agreement within the limit of the ELISA kit. We envision that our developed aptasensor holds utilities for point-of-care cancer prognostics by incorporating simplicity in detection, low-cost for test, and required small sample volumes.

Extracting the distribution of laser damage precursors on fused silica surfaces for 351 nm, 3 ns laser pulses at high fluences (20-150 J/cm2).

Surface laser damage limits the lifetime of optics for systems guiding high fluence pulses, particularly damage in silica optics used for inertial confinement fusion-class lasers (nanosecond-scale high energy pulses at 355 nm/3.5 eV). The density of damage precursors at low fluence has been measured using large beams (1-3 cm); higher fluences cannot be measured easily since the high density of resulting damage initiation sites results in clustering. We developed automated experiments and analysis that allow us to damage test thousands of sites with small beams (10-30 µm), and automatically image the test sites to determine if laser damage occurred. We developed an analysis method that provides a rigorous connection between these small beam damage test results of damage probability versus laser pulse energy and the large beam damage results of damage precursor densities versus fluence. We find that for uncoated and coated fused silica samples, the distribution of precursors nearly flattens at very high fluences, up to 150 J/cm2, providing important constraints on the physical distribution and nature of these precursors.

Robust SERS enhancement factor statistics using rotational correlation spectroscopy.

We characterize the distribution of surface-enhanced Raman spectroscopy (SERS) enhancement factors observed in individual hot spots of single Ag "nanocapsules", encapsulated Ag nanoparticle dimers formed via controlled nanoparticle linking, polymer encapsulation, and small molecule infusion. The enhancement factors are calculated for over 1000 individual nanocapsules by comparing Raman scattering intensities of 4-mercaptobenzoic acid (MBA) measured from single SERS hot spots to intensities measured from high-concentration solutions of MBA. Correlation spectroscopy measurements of the rotational diffusion identify nanocapsules with signals dominated by single hot spots via their strong polarization response. Averaging over the entire surface of the nanocapsules, the distribution of enhancement factors is found to range from 10(6) to 10(8), with a mean of 6 × 10(6). Averaging only over nanoparticle junctions (where most SERS signals are expected) increases this average value to 10(8), with a range from 2 × 10(7) to 2 × 10(9). This significant statistical sampling shows that very high SERS enhancement factors can be obtained on a consistent basis using nanoparticle linking.

Four-color alternating-laser excitation single-molecule fluorescence spectroscopy for next-generation biodetection assays.

BACKGROUND: Single-molecule detection (SMD) technologies are well suited for clinical diagnostic applications by offering the prospect of minimizing precious patient sample requirements while maximizing clinical information content. Not yet available, however, is a universal SMD-based platform technology that permits multiplexed detection of both nucleic acid and protein targets and that is suitable for automation and integration into the clinical laboratory work flow. METHODS: We have used a sensitive, specific, quantitative, and cost-effective homogeneous SMD method that has high single-well multiplexing potential and uses alternating-laser excitation (ALEX) fluorescence-aided molecule sorting extended to 4 colors (4c-ALEX). Recognition molecules are tagged with different-color fluorescence dyes, and coincident confocal detection of ≥2 colors constitutes a positive target-detection event. The virtual exclusion of the majority of sources of background noise eliminates washing steps. Sorting molecules with multidimensional probe stoichiometries (S) and single-molecule fluorescence resonance energy transfer efficiencies (E) allows differentiation of numerous targets simultaneously. RESULTS: We show detection, differentiation, and quantification-in a single well-of (a) 25 different fluorescently labeled DNAs; (b) 8 bacterial genetic markers, including 3 antibiotic drug-resistance determinants found in 11 septicemia-causing Staphylococcus and Enterococcus strains; and (c) 6 tumor markers present in blood. CONCLUSIONS: The results demonstrate assay utility for clinical molecular diagnostic applications by means of multiplexed detection of nucleic acids and proteins and suggest potential uses for early diagnosis of cancer and infectious and other diseases, as well as for personalized medicine. Future integration of additional technology components to minimize preanalytical sample manipulation while maximizing throughput should allow development of a user-friendly ("sample in, answer out") point-of-care platform for next-generation medical diagnostic tests that offer considerable savings in costs and patient sample.

Stoichiometry of reconstituted high-density lipoproteins in the hydrated state determined by photon antibunching.

Apolipoprotein A-I plays a central role in the solution structure of high-density lipoproteins. Determining the stoichiometry of lipid-bound apo A-I in the hydrated state is therefore fundamental to understanding how high-density lipoproteins form and function. Here, we use the quantum optical phenomenon of photon antibunching to determine the number of apo A-I molecules bound to discoidal lipoproteins and compare this with values obtained by photon-counting histogram analysis. Both the photon antibunching and photon-counting analyses show that reconstituted high-density lipoprotein particles contain two apo A-I molecules, which is in agreement with the commonly accepted double-belt model.