Molecular transport enhancement in pure metallic carbon nanotube porins.

Nanofluidic channels impose extreme confinement on water and ions, giving rise to unusual transport phenomena strongly dependent on the interactions at the channel-wall interface. Yet how the electronic properties of the nanofluidic channels influence transport efficiency remains largely unexplored. Here we measure transport through the inner pores of sub-1 nm metallic and semiconducting carbon nanotube porins. We find that water and proton transport are enhanced in metallic nanotubes over semiconducting nanotubes, whereas ion transport is largely insensitive to the nanotube bandgap value. Molecular simulations using polarizable force fields highlight the contributions of the anisotropic polarizability tensor of the carbon nanotubes to the ion-nanotube interactions and the water friction coefficient. We also describe the origin of the proton transport enhancement in metallic nanotubes using deep neural network molecular dynamics simulations. These results emphasize the complex role of the electronic properties of nanofluidic channels in modulating transport under extreme nanoscale confinement.

Fluorescence lifetime measurements using photon pair correlations generated via spontaneous parametric down conversion (SPDC).

We have used photon pair correlations generated via spontaneous parametric downconversion (SPDC) to measure the fluorescence lifetime of the organic dye rhodamine 6 G, demonstrating that fluorescence lifetime measurements can be achieved using a continuous wave (CW) laser, without pulsed or modulated lasers. Our entangled photon method, quantum fluorescence lifetime (Q-FL) measurements, uses one photon to excite fluorescence and the resulting fluorescence photon is timed and referenced to the arrival time of the other entangled photon. Thus, we can exploit the short timescale of photon pair correlations to conduct experiments that are typically carried out with pulsed lasers and we show that the inherent timing of the photons is fast enough to resolve the nanosecond scale fluorescence lifetime of the sample. This measurement paves the way towards using the time correlations of entangled photons for fluorescence imaging; capitalizing on the presence of fast, sub-100 ps correlations that have not been demonstrated classically.

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.

FRET-based dynamic structural biology: Challenges, perspectives and an appeal for open-science practices.

Single-molecule FRET (smFRET) has become a mainstream technique for studying biomolecular structural dynamics. The rapid and wide adoption of smFRET experiments by an ever-increasing number of groups has generated significant progress in sample preparation, measurement procedures, data analysis, algorithms and documentation. Several labs that employ smFRET approaches have joined forces to inform the smFRET community about streamlining how to perform experiments and analyze results for obtaining quantitative information on biomolecular structure and dynamics. The recent efforts include blind tests to assess the accuracy and the precision of smFRET experiments among different labs using various procedures. These multi-lab studies have led to the development of smFRET procedures and documentation, which are important when submitting entries into the archiving system for integrative structure models, PDB-Dev. This position paper describes the current 'state of the art' from different perspectives, points to unresolved methodological issues for quantitative structural studies, provides a set of 'soft recommendations' about which an emerging consensus exists, and lists openly available resources for newcomers and seasoned practitioners. To make further progress, we strongly encourage 'open science' practices.

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.

Photon-HDF5: An Open File Format for Timestamp-Based Single-Molecule Fluorescence Experiments.

We introduce Photon-HDF5, an open and efficient file format to simplify exchange and long-term accessibility of data from single-molecule fluorescence experiments based on photon-counting detectors such as single-photon avalanche diode, photomultiplier tube, or arrays of such detectors. The format is based on HDF5, a widely used platform- and language-independent hierarchical file format for which user-friendly viewers are available. Photon-HDF5 can store raw photon data (timestamp, channel number, etc.) from any acquisition hardware, but also setup and sample description, information on provenance, authorship and other metadata, and is flexible enough to include any kind of custom data. The format specifications are hosted on a public website, which is open to contributions by the biophysics community. As an initial resource, the website provides code examples to read Photon-HDF5 files in several programming languages and a reference Python library (phconvert), to create new Photon-HDF5 files and convert several existing file formats into Photon-HDF5. To encourage adoption by the academic and commercial communities, all software is released under the MIT open source license.

Photon-HDF5: Open Data Format and Computational Tools for Timestamp-based Single-Molecule Experiments.

Archival of experimental data in public databases has increasingly become a requirement for most funding agencies and journals. These data-sharing policies have the potential to maximize data reuse, and to enable confirmatory as well as novel studies. However, the lack of standard data formats can severely hinder data reuse. In photon-counting-based single-molecule fluorescence experiments, data is stored in a variety of vendor-specific or even setup-specific (custom) file formats, making data interchange prohibitively laborious, unless the same hardware-software combination is used. Moreover, the number of available techniques and setup configurations make it difficult to find a common standard. To address this problem, we developed Photon-HDF5 (www.photon-hdf5.org), an open data format for timestamp-based single-molecule fluorescence experiments. Building on the solid foundation of HDF5, Photon-HDF5 provides a platform- and language-independent, easy-to-use file format that is self-describing and supports rich metadata. Photon-HDF5 supports different types of measurements by separating raw data (e.g. photon-timestamps, detectors, etc) from measurement metadata. This approach allows representing several measurement types and setup configurations within the same core structure and makes possible extending the format in backward-compatible way. Complementing the format specifications, we provide open source software to create and convert Photon-HDF5 files, together with code examples in multiple languages showing how to read Photon-HDF5 files. Photon-HDF5 allows sharing data in a format suitable for long term archival, avoiding the effort to document custom binary formats and increasing interoperability with different analysis software. We encourage participation of the single-molecule community to extend interoperability and to help defining future versions of Photon-HDF5.

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.