High-Throughput Raman Spectroscopy by Horizontally Shifted Collection Fibers.

Optical fiber probe-based Raman spectroscopy systems are widely used for in situ measurements ranging from material characterization to biomedical applications. However, small Raman cross sections necessitate the use of high-power lasers or long exposure times that limit Raman's larger application to multiple research fields. This limitation can be overcome by collecting more Raman photons through additional collection fibers with taller detectors. This system configuration requires replacement of the detector and modification of the spectrograph to incorporate larger optical components, making it a costly and cumbersome option. In probe-based Raman systems, a typical detector image shows stacked collection fibers on the vertical axis and Raman spectra on the horizontal axis. While the vertical pixels are fully packed with multiple collection fibers, horizontal pixels have broad silent regions due to the narrow bandwidth of Raman peaks, potentially wasting valuable detector pixels. Here, we propose a new approach utilizing horizontally shifted collection fibers rather than vertically stacked ones. We designed and fabricated a novel collection fiber bundle that has horizontally shifted optical fibers in two vertical lines at the spectrograph entrance. This custom-made fiber bundle was incorporated into the imaging spectrograph to provide multiple horizontally shifted spectra on the detector. Through deconvolution, the original spectra can be recovered with an improved detection limit from greater photon collection. We demonstrate an enhanced limit of detection on various bioanalytes, such as glucose, urea, and lactate. Further, we applied the probe to measure tissue Raman spectra and successfully decomposed them into basis spectra, demonstrating the potential application of high-throughput in vivo tissue diagnosis. Our approach provides a simple, cost-effective, and universal method to increase the throughput without modifying existing Raman spectrometers.

Episymbiotic Saccharibacteria induce intracellular lipid droplet production in their host bacteria.

Saccharibacteria (formerly TM7) are a group of widespread and genetically diverse ultrasmall bacteria with highly reduced genomes that belong to Candidate Phyla Radiation, a large monophyletic lineage with poorly understood biology. Nanosynbacter lyticus type strain TM7x is the first Saccharibacteria member isolated from the human oral microbiome. With restrained metabolic capacities, TM7x lives on the surface of, and forms an obligate episymbiotic relationship with its bacterial host, Schaalia odontolytica strain XH001. The symbiosis allows TM7x to propagate but presents a burden to host bacteria by inducing stress response. Here, we employed super-resolution fluorescence imaging to investigate the physical association between TM7x and XH001. We showed that the binding with TM7x led to a substantial alteration in the membrane fluidity of XH001. We also revealed the formation of intracellular lipid droplets in XH001 when forming episymbiosis with TM7x, a feature that has not been reported in oral bacteria. The TM7x-induced lipid droplets accumulation in XH001 was confirmed by label-free Raman spectroscopy, which also unveiled additional phenotypical features when XH001 cells are physically associated with TM7x. Further exploration through culturing XH001 under various stress conditions showed that lipid droplets accumulation was a general response to stress. A survival assay demonstrated that the presence of lipid droplets plays a protective role in XH001, enhancing its survival under adverse conditions. In conclusion, our study sheds new light on the intricate interaction between Saccharibacteria and their host bacteria, highlighting the potential benefit conferred by TM7x to its host and further emphasizing the context-dependent nature of symbiotic relationships.

Label-free morpho-molecular phenotyping of living cancer cells by combined Raman spectroscopy and phase tomography.

Accurate, rapid and non-invasive cancer cell phenotyping is a pressing concern across the life sciences, as standard immuno-chemical imaging and omics require extended sample manipulation. Here we combine Raman micro-spectroscopy and phase tomography to achieve label-free morpho-molecular profiling of human colon cancer cells, following the adenoma, carcinoma, and metastasis disease progression, in living and unperturbed conditions. We describe how to decode and interpret quantitative chemical and co-registered morphological cell traits from Raman fingerprint spectra and refractive index tomograms. Our multimodal imaging strategy rapidly distinguishes cancer phenotypes, limiting observations to a low number of pristine cells in culture. This synergistic dataset allows us to study independent or correlated information in spectral and tomographic maps, and how it benefits cell type inference. This method is a valuable asset in biomedical research, particularly when biological material is in short supply, and it holds the potential for non-invasive monitoring of cancer progression in living organisms.

Prediction of single-cell RNA expression profiles in live cells by Raman microscopy with Raman2RNA.

Single-cell RNA sequencing and other profiling assays have helped interrogate cells at unprecedented resolution and scale, but are inherently destructive. Raman microscopy reports on the vibrational energy levels of proteins and metabolites in a label-free and nondestructive manner at subcellular spatial resolution, but it lacks genetic and molecular interpretability. Here we present Raman2RNA (R2R), a method to infer single-cell expression profiles in live cells through label-free hyperspectral Raman microscopy images and domain translation. We predict single-cell RNA sequencing profiles nondestructively from Raman images using either anchor-based integration with single molecule fluorescence in situ hybridization, or anchor-free generation with adversarial autoencoders. R2R outperformed inference from brightfield images (cosine similarities: R2R >0.85 and brightfield <0.15). In reprogramming of mouse fibroblasts into induced pluripotent stem cells, R2R inferred the expression profiles of various cell states. With live-cell tracking of mouse embryonic stem cell differentiation, R2R traced the early emergence of lineage divergence and differentiation trajectories, overcoming discontinuities in expression space. R2R lays a foundation for future exploration of live genomic dynamics.

Episymbiotic bacterium induces intracellular lipid droplet production in its host bacteria.

Saccharibacteria (formerly TM7) Nanosynbacter lyticus type strain TM7x exhibits a remarkably compact genome and an extraordinarily small cell size. This obligate epibiotic parasite forms a symbiotic relationship with its bacterial host, Schaalia odontolytica, strain XH001 (formerly Actinomyces odontolyticus strain XH001). Due to its limited genome size, TM7x possesses restrained metabolic capacities, predominantly living on the surface of its bacterial host to sustain this symbiotic lifestyle. To comprehend this intriguing, yet understudied interspecies interaction, a thorough understanding of the physical interaction between TM7x and XH001 is imperative. In this study, we employed super-resolution fluorescence imaging to investigate the physical association between TM7x and XH001. We found that the binding with TM7x led to a substantial alteration in the membrane fluidity of the host bacterium XH001. Unexpectedly, we revealed the formation of intracellular lipid droplets in XH001 when forming episymbiosis with TM7x, a feature not commonly observed in oral bacteria cells. The TM7x-induced LD accumulation in XH001 was further confirmed by label-free non-invasive Raman spectroscopy, which also unveiled additional phenotypical features when XH001 cells are physically associated with TM7x. Further exploration through culturing host bacterium XH001 alone under various stress conditions showed that LD accumulation was a general response to stress. Intriguingly, a survival assay demonstrated that the presence of LDs likely plays a protective role in XH001, enhancing its overall survival under adverse conditions. In conclusion, our study sheds new light on the intricate interaction between Saccharibacteria and its host bacterium, highlighting the potential benefit conferred by TM7x to its host, and further emphasizing the context-dependent nature of symbiotic relationships.

Optical Diffraction Tomography and Raman Confocal Microscopy for the Investigation of Vacuoles Associated with Cancer Senescent Engulfing Cells.

Wild-type p53 cancer therapy-induced senescent cells frequently engulf and degrade neighboring ones inside a massive vacuole in their cytoplasm. After clearance of the internalized cell, the vacuole persists, seemingly empty, for several hours. Despite large vacuoles being associated with cell death, this process is known to confer a survival advantage to cancer engulfing cells, leading to therapy resistance and tumor relapse. Previous attempts to resolve the vacuolar structure and visualize their content using dyes were unsatisfying for lack of known targets and ineffective dye penetration and/or retention. Here, we overcame this problem by applying optical diffraction tomography and Raman spectroscopy to MCF7 doxorubicin-induced engulfing cells. We demonstrated a real ability of cell tomography and Raman to phenotype complex microstructures, such as cell-in-cells and vacuoles, and detect chemical species in extremely low concentrations within live cells in a completely label-free fashion. We show that vacuoles had a density indistinguishable to the medium, but were not empty, instead contained diluted cell-derived macromolecules, and we could discern vacuoles from medium and cells using their Raman fingerprint. Our approach is useful for the noninvasive investigation of senescent engulfing (and other peculiar) cells in unperturbed conditions, crucial for a better understanding of complex biological processes.

Linear Regression Links Transcriptomic Data and Cellular Raman Spectra.

Raman microscopy is an imaging technique that has been applied to assess molecular compositions of living cells to characterize cell types and states. However, owing to the diverse molecular species in cells and challenges of assigning peaks to specific molecules, it has not been clear how to interpret cellular Raman spectra. Here, we provide firm evidence that cellular Raman spectra and transcriptomic profiles of Schizosaccharomyces pombe and Escherichia coli can be computationally connected and thus interpreted. We find that the dimensions of high-dimensional Raman spectra and transcriptomes measured by RNA sequencing can be reduced and connected linearly through a shared low-dimensional subspace. Accordingly, we were able to predict global gene expression profiles by applying the calculated transformation matrix to Raman spectra, and vice versa. Highly expressed non-coding RNAs contributed to the Raman-transcriptome linear correspondence more significantly than mRNAs in S. pombe. This demonstration of correspondence between cellular Raman spectra and transcriptomes is a promising step toward establishing spectroscopic live-cell omics studies.