Label-free functional analysis of root-associated microbes with dynamic quantitative oblique back-illumination microscopy.

The increasing global demand for food, coupled with concerns about the environmental impact of synthetic fertilizers, underscores the urgency of developing sustainable agricultural practices. Nitrogen-fixing bacteria, known as diazotrophs, offer a potential solution by converting atmospheric nitrogen into bioavailable forms, reducing the reliance on synthetic fertilizers. However, a deeper understanding of their interactions with plants and other microbes is needed. In this study, we introduce a recently developed label-free 3D quantitative phase imaging technology called dynamic quantitative oblique back-illumination microscopy (DqOBM) to assess the functional dynamic activity of diazotrophs in vitro and in situ. Our experiments involved three different diazotrophs (Sinorhizobium meliloti, Azotobacter vinelandii, and Rahnella aquatilis) cultured on media with amendments of carbon and nitrogen sources. Over 5 days, we observed increased dynamics in nutrient-amended media. These results suggest that the observed bacterial dynamics correlate with their metabolic activity. Furthermore, we applied qOBM to visualize microbial dynamics within the root cap and elongation zone of Arabidopsis thaliana primary roots. This allowed us to identify distinct areas of microbial infiltration in plant roots without the need for fluorescent markers. Our findings demonstrate that DqOBM can effectively characterize microbial dynamics and provide insights into plant-microbe interactions in situ, offering a valuable tool for advancing our understanding of sustainable agriculture.

Hybrid Lipid Nanocapsules: A Robust Platform for mRNA Delivery.

The success of the mRNA vaccine against COVID-19 has garnered significant interest in the development of mRNA therapeutics against other diseases, but there remains a strong need for a stable and versatile delivery platform for these therapeutics. In this study, we report on a family of robust hybrid lipid nanocapsules (hLNCs) for the delivery of mRNA. The hLNCs are composed of kolliphore HS15, labrafac lipophile WL1349, 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE), and a conjugate of oleic acid (OA) and polyethylenimines of varying size (PEI─0.8, 1.8, and 25 kDa). They are prepared by a solvent-free, temperature-phase inversion method, yielding an average size of ∼40 nm and a particle distribution index (PDI) < 0.2. We demonstrate that the PDI remains <0.2 over a wide pH range and in a wide range of medium. We further show that the PDI and the functionality of mRNA condensed on the particles are robust to drying in a sugar glass and subsequent rehydration. Finally, we demonstrate that mRNA-loaded hLNCs yield reasonable transfection in vitro and in vivo settings.

Label-Free Functional Analysis of Root-Associated Microbes with Dynamic Quantitative Oblique Back-illumination Microscopy.

The increasing global demand for food, coupled with concerns about the environmental impact of synthetic fertilizers, underscores the urgency of developing sustainable agricultural practices. Nitrogen-fixing bacteria, known as diazotrophs, offer a potential solution by converting atmospheric nitrogen into bioavailable forms, reducing the reliance on synthetic fertilizers. However, a deeper understanding of their interactions with plants and other microbes is needed. In this study, we introduce a recently developed label-free 3D quantitative phase imaging technology called dynamic quantitative oblique back-illumination microscopy (DqOBM) to assess the dynamic activity of diazotrophs in vitro and in situ. Our experiments involved three different diazotrophs (Sinorhizobium meliloti, Azotobacter vinelandii, and Rahnella aquatilis) cultured on media with amendments of carbon and nitrogen sources. Over five days, we observed increased dynamic activity in nutrient-amended media. These results suggest that the observed bacterial dynamics correlate with their metabolic activity. Furthermore, we applied qOBM to visualize bacterial activity within the root cap and elongation zone of Arabidopsis thaliana primary roots. This allowed us to identify distinct areas of microbial infiltration in plant roots without the need for fluorescent markers. Our findings demonstrate that DqOBM can effectively characterize microbial activity and provide insights into plant-microbe interactions in situ, offering a valuable tool for advancing our understanding of sustainable agriculture.

Toward Gene-Correlated Spatially Resolved Metabolomics with Fingerprint Coherent Raman Imaging.

Raman spectroscopy has long been known to provide sufficient information to discriminate distinct cell phenotypes. Underlying this discriminating capability is that Raman spectra provide an overall readout of the metabolic profiles that change with transcriptomic activity. Robustly associating Raman spectral changes with the regulation of specific signaling pathways may be possible, but the spectral signals of interest may be weak and vary somewhat among individuals. Establishing a Raman-to-transcriptome mapping will thus require tightly controlled and easily manipulated biological systems and high-throughput spectral acquisition. We attempt to meet these requirements using broadband coherent anti-Stokes Raman scattering (BCARS) microscopy to spatio-spectrally map the C. elegans hermaphrodite gonad in vivo at subcellular resolution. The C. elegans hermaphrodite gonad is an ideal model system with a sequential, continuous process of highly regulated spatiotemporal cellular events. We demonstrate that the BCARS spatio-spectral signatures correlate with gene expression profiles in the gonad, evincing that BCARS has potential as a spatially resolved omics surrogate.

Identifying lipid particle sub-types in live Caenorhabditis elegans with two-photon fluorescence lifetime imaging.

Fat metabolism is an important modifier of aging and longevity in Caenorhabditis elegans. Given the anatomy and hermaphroditic nature of C. elegans, a major challenge is to distinguish fats that serve the energetic needs of the parent from those that are allocated to the progeny. Broadband coherent anti-Stokes Raman scattering (BCARS) microscopy has revealed that the composition and dynamics of lipid particles are heterogeneous both within and between different tissues of this organism. Using BCARS, we have previously succeeded in distinguishing lipid-rich particles that serve as energetic reservoirs of the parent from those that are destined for the progeny. While BCARS microscopy produces high-resolution images with very high information content, it is not yet a widely available platform. Here we report a new approach combining the lipophilic vital dye Nile Red and two-photon fluorescence lifetime imaging microscopy (2p-FLIM) for the in vivo discrimination of lipid particle sub-types. While it is widely accepted that Nile Red staining yields unreliable results for detecting lipid structures in live C. elegans due to strong interference of autofluorescence and non-specific staining signals, our results show that simple FLIM phasor analysis can effectively separate those signals and is capable of differentiating the non-polar lipid-dominant (lipid-storage), polar lipid-dominant (yolk lipoprotein) particles, and the intermediates that have been observed using BCARS microscopy. An advantage of this approach is that images can be acquired using common, commercially available 2p-FLIM systems within about 10% of the time required to generate a BCARS image. Our work provides a novel, broadly accessible approach for analyzing lipid-containing structures in a complex, live whole organism context.

Excitations follow (or lead?) density scaling in propylene carbonate.

Structural excitations that enable interbasin (IB) barrier crossings on a potential energy landscape are thought to play a facilitating role in the relaxation of liquids. Here, we show that the population of these excitations exhibits the same density scaling observed for α relaxation in propylene carbonate, even though they are heavily influenced by intramolecular modes. We also find that IB crossing modes exhibit a Grüneisen parameter (γG) that is approximately equivalent to the density scaling parameter γTS. These observations suggest that the well-documented relationship between γG and γTS may be a direct result of the pressure dependence of the frequency of unstable (relaxation) modes associated with IB motion.

Discriminating cell line specific features of antibiotic-resistant strains of Escherichia coli from Raman spectra via machine learning analysis.

While Raman spectroscopy can provide label-free discrimination between highly similar biological species, the discrimination is often marginal, and optimal use of spectral information is imperative. Here, we compare two machine learning models, an artificial neural network and a support vector machine, for discriminating between Raman spectra of 11 bacterial mutants of Escherichia coli MDS42. While we find that both models discriminate the 11 bacterial strains with similarly high accuracy, sensitivity and specificity, it is clear that the models form different class boundaries. By extracting strain-specific (and function-specific) spectral features utilized by the models, we find that both models utilize a small subset of high intensity peaks while separate subsets of lower intensity peaks are utilized by only one method or the other. This analysis highlights the need for methods to use the complete spectral information more effectively, beginning with a better understanding of the distinct information gained from each model.

Witnessing the survival of time-energy entanglement through biological tissue and scattering media.

We demonstrate the preservation of the time-energy entanglement of near-IR photons through thick biological media (≤1.55 mm) and tissue (≤ 235 µm) at room temperature. Using a Franson-type interferometer, we demonstrate interferometric contrast of over 0.9 in skim milk, 2% milk, and chicken tissue. This work supports the many proposed opportunities for nonclassical light in biological imaging and analyses from sub-shot noise measurements to entanglement-enhanced fluorescence imaging, clearly indicating that the entanglement characteristics of photons can be maintained even after propagation through thick, turbid biological samples.

Low-aberration high-speed-compatible optical delay line.

We describe a simple approach to dispersion-free optical delay line design that provides very low aberration over an extended delay range. In this approach, we minimize aberrations by directing non-axial beam displacements along a line of symmetry built into the apparatus. We show improved performance and significant reduction of wavefront aberrations by comparing simulation and experimental results with a similar delay line that lacks this line of symmetry. The new design facilitates transform-limited recovery of spectral resolution in Fourier transform coherent anti-Stokes Raman scattering, and accordingly, we demonstrate 3.5cm-1 spectral resolution with a 10 ps delay scan range.

Spectroscopic coherent Raman imaging of Caenorhabditis elegans reveals lipid particle diversity.

Caenorhabditis elegans serves as a model for understanding adiposity and its connections to aging. Current methodologies do not distinguish between fats serving the energy needs of the parent, akin to mammalian adiposity, from those that are distributed to the progeny, making it difficult to accurately interpret the physiological implications of fat content changes induced by external perturbations. Using spectroscopic coherent Raman imaging, we determine the protein content, chemical profiles and dynamics of lipid particles in live animals. We find fat particles in the adult intestine to be diverse, with most destined for the developing progeny. In contrast, the skin-like epidermis contains fats that are the least heterogeneous, the least dynamic and have high triglyceride content. These attributes are most consistent with stored somatic energy reservoirs. These results challenge the prevailing practice of assessing C. elegans adiposity by measurements that are dominated by the intestinal fat content.

The polarizability response of a glass-forming liquid reveals intrabasin motion and interbasin transitions on a potential energy landscape.

Potential energy landscape (PEL) concepts have been useful in conceptualizing the effects of intermolecular interactions on dynamic and thermodynamic properties of liquids and glasses. "Basins", or regions of reduced potential energy associated with locally preferred molecular packing are important PEL features. The molecular configurations at the bottom of these basins are referred to as inherent structures (ISs). Experimental methods for directly characterizing PEL features such as these are rare, largely relegating PEL concepts to theory and simulation studies, and impeding their exploration in real systems. Recently, we showed that quasielastic neutron scattering (QENS) data from propylene carbonate (PC) exhibit signatures of picosecond timescale motion that are consistent with intrabasin motion and interbasin transitions [Cicerone et al., J. Chem. Phys., 2017, 146, 054502]. Here we present optically-heterodyne-detected optical Kerr effect (OHD-OKE) spectroscopy studies on PC. The data exhibit signatures of motion within and transitions between basins that agree quantitatively with and extend the QENS results. We show that the librational component of the OKE response corresponds to intrabasin dynamics, and the enigmatic intermediate OKE response corresponds to interbasin transition events. The OKE data extend the measurement range of these parameters and reveal their utility in characterizing PEL features of real systems.

Histological coherent Raman imaging: a prognostic review.

Histopathology plays a central role in diagnosis of many diseases including solid cancers. Efforts are underway to transform this subjective art to an objective and quantitative science. Coherent Raman imaging (CRI), a label-free imaging modality with sub-cellular spatial resolution and molecule-specific contrast possesses characteristics which could support the qualitative-to-quantitative transition of histopathology. In this work we briefly survey major themes related to modernization of histopathology, review applications of CRI to histopathology and, finally, discuss potential roles for CRI in the transformation of histopathology that is already underway.

Enhanced Stabilization in Dried Silk Fibroin Matrices.

Preliminary studies have shown that silk fibroin can protect biomacromolecules from thermal degradation, but a deeper understanding of underlying mechanisms needed to fully leverage the stabilizing potential of this matrix has not been realized. In this study, we investigate stabilization of plasma C-reactive protein (CRP), a diagnostic indicator of infection or inflammation, to gain insight into stabilizing mechanisms of silk. We observed that the addition of antiplasticizing excipients that suppress ß-relaxation amplitudes in silk matrices resulted in enhanced stability of plasma CRP. These observations are consistent with those made in sugar-glass-based protein-stabilizing matrices and suggest fundamental insight into mechanisms as well as practical strategies to employ with silk protein matrices for enhanced stabilization utility.

Metabasin transitions are Johari-Goldstein relaxation events.

We show that by representing quasi-elastic and inelastic neutron scattering from propylene carbonate (PC) with an explicitly heterogeneous model, we recover signatures of two distinct localized modes in addition to diffusive motion. The intermediate scattering function provides access to the time-dependence of these two localized dynamic processes, and they appear to correspond to transitions between inherent states and between metabasins on a potential energy landscape. By fitting the full q-dependence of inelastic scattering, we confirm that the Johari-Goldstein (ßJG) relaxation in PC is indistinguishable from metabasin transitions.

Accurate and interpretable classification of microspectroscopy pixels using artificial neural networks.

This paper addresses the problem of classifying materials from microspectroscopy at a pixel level. The challenges lie in identifying discriminatory spectral features and obtaining accurate and interpretable models relating spectra and class labels. We approach the problem by designing a supervised classifier from a tandem of Artificial Neural Network (ANN) models that identify relevant features in raw spectra and achieve high classification accuracy. The tandem of ANN models is meshed with classification rule extraction methods to lower the model complexity and to achieve interpretability of the resulting model. The contribution of the work is in designing each ANN model based on the microspectroscopy hypothesis about a discriminatory feature of a certain target class being composed of a linear combination of spectra. The novelty lies in meshing ANN and decision rule models into a tandem configuration to achieve accurate and interpretable classification results. The proposed method was evaluated using a set of broadband coherent anti-Stokes Raman scattering (BCARS) microscopy cell images (600 000  pixel-level spectra) and a reference four-class rule-based model previously created by biochemical experts. The generated classification rule-based model was on average 85% accurate measured by the DICE pixel label similarity metric, and on average 96% similar to the reference rules measured by the vector cosine metric.

Molecular imaging with CARS micro-spectroscopy.

After more than a decade of instrument and method development, broadband coherent anti-Stokes Raman scattering (CARS) micro-spectroscopy is beginning to live up to its potential as a label-free imaging modality that can rapidly generate high resolution images with full vibrational spectra at each image pixel. Presently these instruments are able to obtain quantitative, spatially resolved information on lipids from the CH stretch region of the Raman spectrum, and some instrument designs facilitate acquisition of high quality fingerprint spectra, containing information on a host of molecular species including structural proteins, nucleotides, and metabolites. While most of the existing instruments are research projects themselves, it appears that the relevant technologies are maturing so that commercially available instruments may not be too far in the future, making this remarkable imaging modality widely available.

Addition of Monovalent Electrolytes to Improve Storage Stability of Freeze-Dried Protein Formulations.

This study investigates the effect of low levels of electrolytes on storage stability in freeze-dried sucrose-based protein formulations. Both bovine serum albumin and recombinant human serum albumin were freeze dried with sucrose and alkali halides (LiCl, NaCl, KCl, RbCl, and CsCl) at selected low levels. All formulations were stored at 50 °C and 65 °C up to 2 months and then assayed for protein aggregation. The data demonstrate that low levels of LiCl and NaCl enhance stability. No obvious correlations with either protein secondary structure or global dynamics (structural relaxation time) were found. However, good correlations were found between stability and both free-volume hole size via positron annihilation lifetime spectroscopy (PALS) and fast dynamics by neutron scattering. Volume changes on mixing and the partial molal volume of salt were also studied in an effort to detect decreases in free volume. These data did not support the hypothesis that reduction in free volume was the primary mechanism for salt-induced stabilization. Finally, a positive effect of postlyophilization annealing on stability was demonstrated. In summary, we find that small amounts of LiCl and NaCl significantly stabilize these proteins, which is a result at variance with conventional formulation wisdom.

Quantitative, Comparable Coherent Anti-Stokes Raman Scattering (CARS) Spectroscopy: Correcting Errors in Phase Retrieval.

Coherent anti-Stokes Raman scattering (CARS) microspectroscopy has demonstrated significant potential for biological and materials imaging. To date, however, the primary mechanism of disseminating CARS spectroscopic information is through pseudocolor imagery, which explicitly neglects a vast majority of the hyperspectral data. Furthermore, current paradigms in CARS spectral processing do not lend themselves to quantitative sample-to-sample comparability. The primary limitation stems from the need to accurately measure the so-called nonresonant background (NRB) that is used to extract the chemically-sensitive Raman information from the raw spectra. Measurement of the NRB on a pixel-by-pixel basis is a nontrivial task; thus, reference NRB from glass or water are typically utilized, resulting in error between the actual and estimated amplitude and phase. In this manuscript, we present a new methodology for extracting the Raman spectral features that significantly suppresses these errors through phase detrending and scaling. Classic methods of error-correction, such as baseline detrending, are demonstrated to be inaccurate and to simply mask the underlying errors. The theoretical justification is presented by re-developing the theory of phase retrieval via the Kramers-Kronig relation, and we demonstrate that these results are also applicable to maximum entropy method-based phase retrieval. This new error-correction approach is experimentally applied to glycerol spectra and tissue images, demonstrating marked consistency between spectra obtained using different NRB estimates, and between spectra obtained on different instruments. Additionally, in order to facilitate implementation of these approaches, we have made many of the tools described herein available free for download.