Video-rate Raman-based metabolic imaging by Airy light-sheet illumination and photon-sparse detection.

Despite its massive potential, Raman imaging represents just a modest fraction of all research and clinical microscopy to date. This is due to the ultralow Raman scattering cross-sections of most biomolecules that impose low-light or photon-sparse conditions. Bioimaging under such conditions is suboptimal, as it either results in ultralow frame rates or requires increased levels of irradiance. Here, we overcome this tradeoff by introducing Raman imaging that operates at both video rates and 1,000-fold lower irradiance than state-of-the-art methods. To accomplish this, we deployed a judicially designed Airy light-sheet microscope to efficiently image large specimen regions. Further, we implemented subphoton per pixel image acquisition and reconstruction to confront issues arising from photon sparsity at just millisecond integrations. We demonstrate the versatility of our approach by imaging a variety of samples, including the three-dimensional (3D) metabolic activity of single microbial cells and the underlying cell-to-cell variability. To image such small-scale targets, we again harnessed photon sparsity to increase magnification without a field-of-view penalty, thus, overcoming another key limitation in modern light-sheet microscopy.

Correction: Microbial phenotypic heterogeneity in response to a metabolic toxin: Continuous, dynamically shifting distribution of formaldehyde tolerance in Methylobacterium extorquens populations.

[This corrects the article DOI: 10.1371/journal.pgen.1008458.].

Microbial phenotypic heterogeneity in response to a metabolic toxin: Continuous, dynamically shifting distribution of formaldehyde tolerance in Methylobacterium extorquens populations.

While microbiologists often make the simplifying assumption that genotype determines phenotype in a given environment, it is becoming increasingly apparent that phenotypic heterogeneity (in which one genotype generates multiple phenotypes simultaneously even in a uniform environment) is common in many microbial populations. The importance of phenotypic heterogeneity has been demonstrated in a number of model systems involving binary phenotypic states (e.g., growth/non-growth); however, less is known about systems involving phenotype distributions that are continuous across an environmental gradient, and how those distributions change when the environment changes. Here, we describe a novel instance of phenotypic diversity in tolerance to a metabolic toxin within wild-type populations of Methylobacterium extorquens, a ubiquitous phyllosphere methylotroph capable of growing on the methanol periodically released from plant leaves. The first intermediate in methanol metabolism is formaldehyde, a potent cellular toxin that is lethal in high concentrations. We have found that at moderate concentrations, formaldehyde tolerance in M. extorquens is heterogeneous, with a cell's minimum tolerance level ranging between 0 mM and 8 mM. Tolerant cells have a distinct gene expression profile from non-tolerant cells. This form of heterogeneity is continuous in terms of threshold (the formaldehyde concentration where growth ceases), yet binary in outcome (at a given formaldehyde concentration, cells either grow normally or die, with no intermediate phenotype), and it is not associated with any detectable genetic mutations. Moreover, tolerance distributions within the population are dynamic, changing over time in response to growth conditions. We characterized this phenomenon using bulk liquid culture experiments, colony growth tracking, flow cytometry, single-cell time-lapse microscopy, transcriptomics, and genome resequencing. Finally, we used mathematical modeling to better understand the processes by which cells change phenotype, and found evidence for both stochastic, bidirectional phenotypic diversification and responsive, directed phenotypic shifts, depending on the growth substrate and the presence of toxin.

An unexpected phase transformation of ceria nanoparticles in aqueous media.

Cerium oxide Nanoparticles (CNPs) are of significant interest to the scientific community due to their wide spread applications in a variety of fields. It is proposed that size dependent variations in the extent of Ce3+ and Ce4+ oxidation states of cerium in CNPs determines the performance of CNPs in application environments. To obtain greater molecular and structural understanding of chemical state transformations previously reported for ceria ≈ 3 nm nanoparticles (CNPs) in response to changing ambient conditions, microXRD and Raman measurements were carried out for various solution conditions. The particles were observed to undergo a reversible transformation from a defective ceria structure to a non-ceria amorphous oxy-hydroxide/peroxide phase in response to the addition of 30% hydrogen peroxide. For CNPs made up of ~8 nm crystallites, a partial transformation was observed and no transformation was observed for CNPs made up of ~ 40 nm crystallites. This observation of differences in size dependent transition behavior may help explain the benefits of using smaller CNPs in applications requiring regenerative behavior.

Review of methods to probe single cell metabolism and bioenergetics.

Single cell investigations have enabled unexpected discoveries, such as the existence of biological noise and phenotypic switching in infection, metabolism and treatment. Herein, we review methods that enable such single cell investigations specific to metabolism and bioenergetics. Firstly, we discuss how to isolate and immobilize individuals from a cell suspension, including both permanent and reversible approaches. We also highlight specific advances in microbiology for its implications in metabolic engineering. Methods for probing single cell physiology and metabolism are subsequently reviewed. The primary focus therein is on dynamic and high-content profiling strategies based on label-free and fluorescence microspectroscopy and microscopy. Non-dynamic approaches, such as mass spectrometry and nuclear magnetic resonance, are also briefly discussed.

Quantitative phase imaging by gradient retardance optical microscopy.

Quantitative phase imaging (QPI) has become a vital tool in bioimaging, offering precise measurements of wavefront distortion and, thus, of key cellular metabolism metrics, such as dry mass and density. However, only a few QPI applications have been demonstrated in optically thick specimens, where scattering increases background and reduces contrast. Building upon the concept of structured illumination interferometry, we introduce Gradient Retardance Optical Microscopy (GROM) for QPI of both thin and thick samples. GROM transforms any standard Differential Interference Contrast (DIC) microscope into a QPI platform by incorporating a liquid crystal retarder into the illumination path, enabling independent phase-shifting of the DIC microscope's sheared beams. GROM greatly simplifies related configurations, reduces costs, and eradicates energy losses in parallel imaging modalities, such as fluorescence. We successfully tested GROM on a diverse range of specimens, from microbes and red blood cells to optically thick (~ 300 µm) plant roots without fixation or clearing.

Scattered-light-sheet microscopy with sub-cellular resolving power.

Since its first demonstration over 100 years ago, scattering-based light-sheet microscopy has recently re-emerged as a key modality in label-free tissue imaging and cellular morphometry; however, scattering-based light-sheet imaging with subcellular resolution remains an unmet target. This is because related approaches inevitably superimpose speckle or granular intensity modulation on to the native subcellular features. Here, we addressed this challenge by deploying a time-averaged pseudo-thermalized light-sheet illumination. While this approach increased the lateral dimensions of the illumination sheet, we achieved subcellular resolving power after image deconvolution. We validated this approach by imaging cytosolic carbon depots in yeast and bacteria with increased specificity, no staining, and ultralow irradiance levels. Overall, we expect this scattering-based light-sheet microscopy approach will advance single, live cell imaging by conferring low-irradiance and label-free operation towards eradicating phototoxicity.

Density fluctuations, homeostasis, and reproduction effects in bacteria.

Single-cells grow by increasing their biomass and size. Here, we report that while mass and size accumulation rates of single Escherichia coli cells are exponential, their density and, thus, the levels of macromolecular crowding fluctuate during growth. As such, the average rates of mass and size accumulation of a single cell are generally not the same, but rather cells differentiate into increasing one rate with respect to the other. This differentiation yields a density homeostasis mechanism that we support mathematically. Further, we observe that density fluctuations can affect the reproduction rates of single cells, suggesting a link between the levels of macromolecular crowding with metabolism and overall population fitness. We detail our experimental approach and the "invisible" microfluidic arrays that enabled increased precision and throughput. Infections and natural communities start from a few cells, thus, emphasizing the significance of density-fluctuations when taking non-genetic variability into consideration.

Silicon oxide deposition for enhanced optical switching in polydimethylsiloxane-liquid crystal hybrids.

We report an optical switch based on a diffraction grating by combining PDMS microstructures with a photo-responsive Nematic Liquid Crystal (NLC). The grating was realized via replica molding and was subsequently coated with a thin SiO layer. SiO induced a full planar alignment of the liquid crystal. The induced parallel alignment of the LC reduces the response time of the structure by approximately an order of magnitude compared to the same structures without SiO. We explored the effect of the pump intensity on the transmission properties and time response of the switch and identified a strong dependence on the probe polarization, due to the full planar alignment in this structure. The aforementioned inclusion of the SiO layer enables enhanced performance of optical devices based on the fusion of nematogens with soft and flexible substrates.

Enhancing single molecule imaging in optofluidics and microfluidics.

Microfluidics and optofluidics have revolutionized high-throughput analysis and chemical synthesis over the past decade. Single molecule imaging has witnessed similar growth, due to its capacity to reveal heterogeneities at high spatial and temporal resolutions. However, both resolution types are dependent on the signal to noise ratio (SNR) of the image. In this paper, we review how the SNR can be enhanced in optofluidics and microfluidics. Starting with optofluidics, we outline integrated photonic structures that increase the signal emitted by single chromophores and minimize the excitation volume. Turning then to microfluidics, we review the compatible functionalization strategies that reduce noise stemming from non-specific interactions and architectures that minimize bleaching and blinking.

Microbial metabolic noise.

From the time a cell was first placed under the microscope, it became apparent that identifying two clonal cells that "look" identical is extremely challenging. Since then, cell-to-cell differences in shape, size, and protein content have been carefully examined, informing us of the ultimate limits that hinder two cells from occupying an identical phenotypic state. Here, we present recent experimental and computational evidence that similar limits emerge also in cellular metabolism. These limits pertain to stochastic metabolic dynamics and, thus, cell-to-cell metabolic variability, including the resulting adapting benefits. We review these phenomena with a focus on microbial metabolism and conclude with a brief outlook on the potential relationship between metabolic noise and adaptive evolution. This article is categorized under: Metabolic Diseases > Computational Models Metabolic Diseases > Biomedical Engineering.

Deep learning classification of lipid droplets in quantitative phase images.

We report the application of supervised machine learning to the automated classification of lipid droplets in label-free, quantitative-phase images. By comparing various machine learning methods commonly used in biomedical imaging and remote sensing, we found convolutional neural networks to outperform others, both quantitatively and qualitatively. We describe our imaging approach, all implemented machine learning methods, and their performance with respect to computational efficiency, required training resources, and relative method performance measured across multiple metrics. Overall, our results indicate that quantitative-phase imaging coupled to machine learning enables accurate lipid droplet classification in single living cells. As such, the present paradigm presents an excellent alternative of the more common fluorescent and Raman imaging modalities by enabling label-free, ultra-low phototoxicity, and deeper insight into the thermodynamics of metabolism of single cells.

Microfluidic assays for DNA manipulation based on a block copolymer immobilization strategy.

Methods to manipulate and visualize isolated DNA and oligonucleotide strands are important for investigation of their biophysics as well as their interactions with proteins. Herein, we report such a method by combining a block copolymer surface functionalization strategy with microfluidics. The copolymer poly(l-lysine-graft-polyethylene glycol) (PLL-g-PEG) coated one surface of the microfluidic channels, rendering it passive to adsorption and thus minimizing any noise arising from nontargeted adsorbed molecules. Single lambda-phage DNA molecules were immobilized and were extended by molecular combing. Their extension did not exceed their contour length, which we attribute to the low surface tension of the coated surface. To demonstrate further the applicability of our method, the anchored DNA was extended by hydrodynamic flow. We propose this method for exploring DNA-protein interactions due to the copolymer's enhanced capacity for single-molecule detection, stability under wet or dry conditions, hydrophilicity, full compatibility with microfluidics and simplicity being a one-step process.

Exploiting Bioprocessing Fluctuations to Elicit the Mechanistics of De Novo Lipogenesis in Yarrowia lipolytica.

Despite substantial achievements in elucidating the metabolic pathways of lipogenesis, a mechanistic representation of lipid accumulation and degradation has not been fully attained to-date. Recent evidence suggests that lipid accumulation can occur through increases of either the cytosolic copy-number of lipid droplets (LDs), or the LDs size. However, the prevailing phenotype, or how such mechanisms pertain to lipid degradation remain poorly understood. To address this shortcoming, we employed the-recently discovered-innate bioprocessing fluctuations in Yarrowia lipolytica, and performed single-cell fluctuation analysis using optical microscopy and microfluidics that generate a quasi-time invariant microenvironment. We report that lipid accumulation at early stationary phase in rich medium is substantially more likely to occur through variations in the LDs copy-number, rather than the LDs size. Critically, these mechanistics are also preserved during lipid degradation, as well as upon exposure to a protein translation inhibitor. The latter condition additionally induced a lipid accumulation phase, accompanied by the downregulation of lipid catabolism. Our results enable an in-depth mechanistic understanding of lipid biogenesis, and expand longitudinal single-cell fluctuation analyses from gene regulation to metabolism.

Mesoscale Polymer Dissolution Probed by Raman Spectroscopy and Molecular Simulations.

The diffusion of various solvents into a polystyrene (PS) matrix was probed experimentally by monitoring the temporal profiles of the Raman spectra and theoretically from molecular dynamics simulations. The simulation results assist in providing a fundamental, molecular-level connection between the mixing/dissolution processes and the difference, Δδ = δsolvent - δPS, in the values of the Hildebrand parameter (δ) between the two components of the binary systems: solvents having values of δ similar to those for PS (small Δδ) exhibit fast diffusion into the polymer matrix, whereas the diffusion slows down considerably when the δ's are different (large Δδ). To this end, the Hildebrand parameter was identified as a useful descriptor that governs the process of mixing in polymer-solvent binary systems. The experiments also provide insight into further refinements of the models specific to non-Fickian diffusion phenomena that need to be used in the simulations.

Elastomer based tunable optofluidic devices.

The synergetic integration of photonics and microfluidics has enabled a wide range of optofluidic devices that can be tuned based on various physical mechanisms. One such tuning mechanism can be realized based on the elasticity of polydimethylsiloxane (PDMS). The mechanical tuning of these optofluidic devices was achieved by modifying the geometry of the device upon applying internal or external forces. External or internal forces can deform the elastomeric components that in turn can alter the optical properties of the device or directly induce flow. In this review, we discuss recent progress in tunable optofluidic devices, where tunability is enabled by the elasticity of the construction material. Different subtypes of such tuning methods will be summarized, namely tuning based on bulk or membrane deformations, and pneumatic actuation.

Precision intracellular delivery based on optofluidic polymersome rupture.

We present an optical approach for intracellular delivery of molecules contained within oxidation-sensitive polymersomes. The photosensitizer ethyl eosin is associated with the polymersome membrane to oxidatively increase the hydrophilicity of the hydrophobic block under optical excitation. This optofluidic interaction induces rapid polymersome rupture and payload release via the reorganization of the aggregate structure into smaller diameter vesicles and micelles. When the particles are endocytosed by phagocytes, such as RAW macrophages and dendritic cells, the polymersomes' payload escapes the endosome and is released in the cell cytosol within a few seconds of illumination. The released payload is rapidly distributed throughout the cytosol within milliseconds. The presented optofluidic method enables fast delivery and distribution throughout the cytosol of individual cells, comparable to photochemical internalization, but a factor of 100 faster than similar carrier mediated delivery methods (e.g., liposomes, polymersomes, or nanoparticles). Due to the ability to simultaneously induce payload delivery and endosomal escape, this approach can find applications in detailed characterizations of intra- and intercellular processes. As an example in quantitative cell biology, a peptide antigen was delivered in dendritic cells and MHC I presentation kinetics were measured at the single cell and single complex level.

Electro-switchable polydimethylsiloxane-based optofluidics.

We report on the fabrication and characterization of a new generation of electro-switchable optofluidic devices based on flexible substrates, combined with the extraordinary properties of reconfigurable soft-materials. A conductive polydimethylsiloxane microstructure has been first sputtered with an Indium Tin Oxide (ITO) layer and then functionalized with an amorphous film of SiO(x). Then, the "layer" by "layer" microstructure has been infiltrated with an anisotropic and reconfigurable fluid (Nematic Liquid Crystal, NLC). The sample has been characterized in terms of morphological, optical and electro-optical properties: the soft-conductive microstructure exhibits a uniform and regular morphology, even after testing with mechanical stretching and deformations. Combination of the conductive ITO with the functionalization film (which has been employed for inducing in-plane alignment of NLC molecules) enables us to carry out a series of optical and electro-optical experiments; these confirm excellent properties in terms of a reconfigurable device and a diffractive element as well.