Induction and measurement of the early stage of a host-parasite interaction using a combined optical trapping and Raman microspectroscopy system

From Genotype to Phenotype: Raman Spectroscopy and Machine Learning for Label-Free Single-Cell Analysis

Raman spectroscopy has made significant progress in biosensing and clinical research. Here, we describe how surface-enhanced Raman spectroscopy (SERS) assisted with machine learning (ML) can expand its capabilities to enable interpretable insights into the transcriptome, proteome, and metabolome at the single-cell level. We first review how advances in nanophotonics-including plasmonics, metamaterials, and metasurfaces-enhance Raman scattering for rapid, strong label-free spectroscopy. We then discuss ML approaches for precise and interpretable spectral analysis, including neural networks, perturbation and gradient algorithms, and transfer learning. We provide illustrative examples of single-cell Raman phenotyping using nanophotonics and ML, including bacterial antibiotic susceptibility predictions, stem cell expression profiles, cancer diagnostics, and immunotherapy efficacy and toxicity predictions. Lastly, we discuss exciting prospects for the future of single-cell Raman spectroscopy, including Raman instrumentation, self-driving laboratories, Raman data banks, and machine learning for uncovering biological insights.

Vibrational spectroscopy for decoding cancer microbiota interactions: Current evidence and future perspective

The role of human microbiota in cancer initiation and progression is recognized in recent years. In order to investigate the interactions between cancer cells and microbes, a systematic analysis using various emerging techniques is required. Owing to the label-free, non-invasive and molecular fingerprinting characteristics, vibrational spectroscopy is uniquely suited to decode and understand the relationship and interactions between cancer and the microbiota at the molecular level. In this review, we first provide a quick overview of the fundamentals of vibrational spectroscopic techniques, namely Raman and infrared spectroscopy. Next, we discuss the emerging evidence underscoring utilities of these spectroscopic techniques to study cancer or microbes separately, and share our perspective on how vibrational spectroscopy can be employed at the intersection of the two fields. Finally, we envision the potential opportunities in exploiting vibrational spectroscopy not only in basic cancer-microbiome research but also in its clinical translation, and discuss the challenges in the bench to bedside translation.

Model systems for optical trapping: the physical basis and biological applications

The micromechanical methods, among which optical trapping and atomic force microscopy have a special place, are widespread currently in biology to study molecular interactions between different biological objects. Optical trapping is reported to be quite applicable to study the mechanical properties of surface structures onto bacterial (pili and flagella) and eukaryotic (filopodia) cells. The review briefly summarizes the physical basis of optical trapping, as well as the principles of calculating the van der Waals, electrostatic, and donor-acceptor forces when two microparticles or a microparticle and a flat surface are used. Three main types of model systems (abiotic, biotic, and mixed) used in trapping experiments are described, and the peculiarities of manipulation with living (bacteria, fungal spores, etc.) and non-spherical objects (e.g., rod-shaped bacteria) are summarized.

Sub-Surface Molecular Analysis and Imaging in Turbid Media Using Time-Gated Raman Spectral Multiplexing

Obtaining molecular information deeper within optically turbid samples is valuable in many applications. However, in many cases this is challenging, in particular when the sample elicits strong laser-induced fluorescence emission. Here, we investigated the use of time-gated and micro-spatially offset Raman spectroscopy (micro-SORS) based on spectral multiplexing detection to obtain sub-surface molecular analysis and imaging for both fluorescing and non-fluorescing samples. The multiplexed spectral detection achieved with a digital micromirror device (DMD) allowed fast acquisition of the time-gated signals to enable three-dimensional Raman mapping (raster scanning in the lateral x,y plane and using time-of-flight calibration for the axial z-direction). Sub-millimeter resolution molecular depth mapping was achieved with dwell times on the order of seconds per pixel. To suppress fluorescence backgrounds and enhance Raman bands, time-gated Raman spectroscopy was combined with micro-SORS to recover Raman signals of red pigments placed behind a layer of optically turbid material. Using a defocusing micro-SORS approach, both fluorescence and Raman signals from the surface layers were further suppressed, which enhanced the Raman signals from the deeper sublayers containing the pigment. These results demonstrate that time-gated Raman spectroscopy based on spectral multiplexed detection, and in combination with micro-SORS, is a powerful technique for sub-surface molecular analysis and imaging, which may find practical applications in medical imaging, cultural heritage, forensics, and industry.

The Role of Single-Cell Technology in the Study and Control of Infectious Diseases

The advent of single-cell research in the recent decade has allowed biological studies at an unprecedented resolution and scale. In particular, single-cell analysis techniques such as Next-Generation Sequencing (NGS) and Fluorescence-Activated Cell Sorting (FACS) have helped show substantial links between cellular heterogeneity and infectious disease progression. The extensive characterization of genomic and phenotypic biomarkers, in addition to host-pathogen interactions at the single-cell level, has resulted in the discovery of previously unknown infection mechanisms as well as potential treatment options. In this article, we review the various single-cell technologies and their applications in the ongoing fight against infectious diseases, as well as discuss the potential opportunities for future development.