Molecular Structure and Interactions of Lipids in the Outer Membrane of Living Cells Based on Surface-Enhanced Raman Scattering and Liposome Models

A Single-Cell Metabolic Profiling Characterizes Human Aging via SlipChip-SERS

Metabolic dysregulation is a key driver of cellular senescence, contributing to the progression of systemic aging. The heterogeneity of senescent cells and their metabolic shifts are complex and unexplored. A microfluidic SlipChip integrated with surface-enhanced Raman spectroscopy (SERS), termed SlipChip-SERS, is developed for single-cell metabolism analysis. This SlipChip-SERS enables compartmentalization of single cells, parallel delivery of saponin and nanoparticles to release intracellular metabolites and to realize SERS detection with simple slipping operations. Analysis of different cancer cell lines using SlipChip-SERS demonstrated its capability for sensitive and multiplexed metabolic profiling of individual cells. When applied to human primary fibroblasts of different ages, it identified 12 differential metabolites, with spermine validated as a potent inducer of cellular senescence. Prolonged exposure to spermine can induce a classic senescence phenotype, such as increased senescence-associated β-glactosidase activity, elevated expression of senescence-related genes and reduced LMNB1 levels. Additionally, the senescence-inducing capacity of spermine in HUVECs and WRL-68 cells is confirmed, and exogenous spermine treatment increased the accumulation and release of H2O2. Overall, a novel SlipChip-SERS system is developed for single-cell metabolic analysis, revealing spermine as a potential inducer of senescence across multiple cell types, which may offer new strategies for addressing ageing and ageing-related diseases.

SERS microscopy as a tool for comprehensive biochemical characterization in complex samples

Surface enhanced Raman scattering (SERS) spectra of biomaterials such as cells or tissues can be used to obtain biochemical information from nanoscopic volumes in these heterogeneous samples. This tutorial review discusses the factors that determine the outcome of a SERS experiment in complex bioorganic samples. They are related to the SERS process itself, the possibility to selectively probe certain regions or constituents of a sample, and the retrieval of the vibrational information in order to identify molecules and their interaction. After introducing basic aspects of SERS experiments in the context of biocompatible environments, spectroscopy in typical microscopic settings is exemplified, including the possibilities to combine SERS with other linear and non-linear microscopic tools, and to exploit approaches that improve lateral and temporal resolution. In particular the great variation of data in a SERS experiment calls for robust data analysis tools. Approaches will be introduced that have been originally developed in the field of bioinformatics for the application to omics data and that show specific potential in the analysis of SERS data. They include the use of simulated data and machine learning tools that can yield chemical information beyond achieving spectral classification.

Photo-induced Oriented Crystallization of Intracellular Nanocrystals Based on Phase Separation for Diagnostic Bioimaging and Analysis

Biomineral crystals form complex nonequilibrium structures based on the multistep nucleation theory, via transient amorphous precursors. However, the intricate nature of the biological system results in the inconsistent frequency of nucleation and crystallization, which making it problematic to obtain homogeneous nanocrystals, limits their application in biomedicine. Here, it is reported that homogeneous nanocrystals of photoinduced oriented crystallization with protein coronas are based on intracellular liquid-liquid phase separation for in situ analysis and mapping of surface-enhanced Raman spectroscopy (SERS). Near-infrared light promotes the formation of intracellular dense phases, accelerates the nucleation of gold atoms at secondary structure sites of proteins, and promotes the growth of crystals. Homogeneous gold nanocrystals with stable SERS signals can be used to analysis different cell cycles and acquire in situ molecular information of metastatic tumor cells. Of note are tag molecule is embedded in protein coronas of gold nanocrystals to enable the mapping of patient tumor tissue samples and the portable recognition of tumor cells. Thus, this study proposes a new strategy for biomineralization of intracellular homogeneous gold nanocrystals and its potential application.

Label-Free Multiplex Profiling of Exosomal Proteins with a Deep Learning-Driven 3D Surround-Enhancing SERS Platform for Early Cancer Diagnosis

Identification of protein profiling on plasma exosomes by SERS can be a promising strategy for early cancer diagnosis. However, it is still challenging to detect multiple exosomal proteins simultaneously by SERS since the Raman signals of exosomes detected by conventional colloidal nanocrystals or two-dimensional SERS substrates are incomplete and complex. Herein, we develop a novel three-dimensional (3D) surround-enhancing SERS platform, named 3D se-SERS, for the multiplex detection of exosomal proteins. In this 3D se-SERS, proteins and exosomes are covered with "hotspots" generated by the gold nanoparticles, which surround the analytes densely and three-dimensionally, providing sensitive and comprehensive SERS signals. Combining this 3D se-SERS with a deep learning model, we successfully quantitatively profiled seven proteins including CD63, CD81, CD9, CD151, CD171, TSPAN8, and PD-L1 on the surface of plasma exosomes from patients, which can predict the occurrence and advancement of lung cancer. This 3D se-SERS integrating deep learning technique benefits from high sensitivity and significant multiplexing ability for comprehensive analysis of proteins and exosomes, demonstrating the potential of deep learning-driven 3D se-SERS technology for plasma exosome-based early cancer diagnosis.

Deciphering biomolecular complexities: the indispensable role of surface-enhanced Raman spectroscopy in modern bioanalytical research

Surface-enhanced Raman spectroscopy (SERS) has emerged as an indispensable analytical tool in biomolecular research, providing unmatched sensitivity critical for the elucidation of biomolecular structures. This review presents a thorough examination of SERS, outlining its fundamental principles, cataloging its varied applications within the biomolecular sphere, and contemplating its future developmental trajectories. We begin with a detailed analysis of SERS's mechanistic principles, emphasizing both the phenomena of surface enhancement and the complexities inherent in Raman scattering spectroscopy. Subsequently, we delve into the pivotal role of SERS in the structural analysis of diverse biomolecules, including proteins, nucleic acids, lipids, carbohydrates, and biochromes. The remarkable capabilities of SERS extend beyond mere detection, offering profound insights into biomolecular configurations and interactions, thereby enriching our comprehension of intricate biological processes. This review also sheds light on the application of SERS in real-time monitoring of various bio-relevant compounds, from enzymes and coenzymes to metal ion-chelate complexes and cellular organelles, thereby providing a holistic view and empowering researchers to unravel the complexities of biological systems. We also address the current challenges faced by SERS, such as enhancing sensitivity and resolution, developing stable and reproducible substrates, and conducting thorough analyses in complex biological matrices. Nonetheless, the continual advancements in nanotechnology and spectroscopy solidify the standing of SERS as a formidable force in biomolecular research. In conclusion, the versatility and robustness of SERS not only deepen our understanding of biomolecular intricacies but also pave the way for significant developments in medical research, therapeutic innovation, and diagnostic approaches.

The presence of uncoated gold nanoparticle aggregates may alter the phase of phosphatidylcholine lipid as evidenced by vibrational spectroscopies

Spherical structures built from uni- and multilamellar lipid bilayers (LUV and MLV) are nowadays considered not just as nanocarriers of various kinds of therapeutics, but also as the vehicles that, when coupled with gold (Au) nanoparticles (NPs), can also serve as a tool for imaging and discriminating healthy and diseased tissues. Since the presence of Au NPs or their aggregates may affect the properties of the drug delivery vehicle, we investigated how the shape and position of Au NP aggregates adsorbed on the surface of MLV affect the arrangement and conformation of lipid molecules. By preparing MLVs constituted from 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) in the presence of uncoated Au NP aggregates found i) both within liposome core and on the surface of the outer lipid bilayer, or ii) adsorbed on the outer lipid bilayer surface only, we demonstrated the maintenance of lipid bilayer integrity by microscopic techniques (cryo-TEM, and AFM). The employment of SERS and FTIR-ATR techniques enabled us not only to elucidate the lipid interaction pattern and their orientation in regards to Au NP aggregates but also unequivocally confirmed the impact of Au NP aggregates on the persistence/breaking of van der Waals interactions between hydrocarbon chains of DPPC.

In Situ Raman Study of Neurodegenerated Human Neuroblastoma Cells Exposed to Outer-Membrane Vesicles Isolated from Porphyromonas gingivalis

The aim of this study was to elucidate the chemistry of cellular degeneration in human neuroblastoma cells upon exposure to outer-membrane vesicles (OMVs) produced by Porphyromonas gingivalis (Pg) oral bacteria by monitoring their metabolomic evolution using in situ Raman spectroscopy. Pg-OMVs are a key factor in Alzheimer's disease (AD) pathogenesis, as they act as efficient vectors for the delivery of toxins promoting neuronal damage. However, the chemical mechanisms underlying the direct impact of Pg-OMVs on cell metabolites at the molecular scale still remain conspicuously unclear. A widely used in vitro model employing neuroblastoma SH-SY5Y cells (a sub-line of the SK-N-SH cell line) was spectroscopically analyzed in situ before and 6 h after Pg-OMV contamination. Concurrently, Raman characterizations were also performed on isolated Pg-OMVs, which included phosphorylated dihydroceramide (PDHC) lipids and lipopolysaccharide (LPS), the latter in turn being contaminated with a highly pathogenic class of cysteine proteases, a key factor in neuronal cell degradation. Raman characterizations located lipopolysaccharide fingerprints in the vesicle structure and unveiled so far unproved aspects of the chemistry behind protein degradation induced by Pg-OMV contamination of SH-SY5Y cells. The observed alterations of cells' Raman profiles were then discussed in view of key factors including the formation of amyloid β (Aβ) plaques and hyperphosphorylated Tau neurofibrillary tangles, and the formation of cholesterol agglomerates that exacerbate AD pathologies.

Could artificial intelligence revolutionize the development of nanovectors for gene therapy and mRNA vaccines?

Gene therapy enables the introduction of nucleic acids like DNA and RNA into host cells, and is expected to revolutionize the treatment of a wide range of diseases. This growth has been further accelerated by the discovery of CRISPR/Cas technology, which allows accurate genomic editing in a broad range of cells and organisms in vitro and in vivo. Despite many advances in gene delivery and the development of various viral and non-viral gene delivery vectors, the lack of highly efficient non-viral systems with low cellular toxicity remains a challenge. The application of cutting-edge technologies such as artificial intelligence (AI) has great potential to find new paradigms to solve this issue. Herein, we review AI and its major subfields including machine learning (ML), neural networks (NNs), expert systems, deep learning (DL), computer vision and robotics. We discuss the potential of AI-based models and algorithms in the design of targeted gene delivery vehicles capable of crossing extracellular and intracellular barriers by viral mimicry strategies. We finally discuss the role of AI in improving the function of CRISPR/Cas systems, developing novel nanobots, and mRNA vaccine carriers.

Structure and Interaction of Ceramide-Containing Liposomes with Gold Nanoparticles as Characterized by SERS and Cryo-EM

Due to the great potential of surface-enhanced Raman scattering (SERS) as local vibrational probe of lipid-nanostructure interaction in lipid bilayers, it is important to characterize these interactions in detail. The interpretation of SERS data of lipids in living cells requires an understanding of how the molecules interact with gold nanostructures and how intermolecular interactions influence the proximity and contact between lipids and nanoparticles. Ceramide, a sphingolipid that acts as important structural component and regulator of biological function, therefore of interest to probing, lacks a phosphocholine head group that is common to many lipids used in liposome models. SERS spectra of liposomes of a mixture of ceramide, phosphatidic acid, and phosphatidylcholine, as well as of pure ceramide and of the phospholipid mixture are reported. Distinct groups of SERS spectra represent varied contributions of the choline, sphingosine, and phosphate head groups and the structures of the acyl chains. Spectral bands related to the state of order of the membrane and moreover to the amide function of the sphingosine head groups indicate that the gold nanoparticles interact with molecules involved in different intermolecular relations. While cryogenic electron microscopy shows the formation of bilayer liposomes in all preparations, pure ceramide was found to also form supramolecular, concentric stacked and densely packed lamellar, nonliposomal structures. That the formation of such supramolecular assemblies supports the intermolecular interactions of ceramide is indicated by the SERS data. The unique spectral features that are assigned to the ceramide-containing lipid model systems here enable an identification of these molecules in biological systems and allow us to obtain information on their structure and interaction by SERS.

Combined Second Harmonic Generation and Fluorescence Analyses of the Structures and Dynamics of Molecules on Lipids Using Dual-Probes: A Review

Revealing the structures and dynamic behaviors of molecules on lipids is crucial for understanding the mechanism behind the biophysical processes, such as the preparation and application of drug delivery vesicles. Second harmonic generation (SHG) has been developed as a powerful tool to investigate the molecules on various lipid membranes, benefiting from its natural property of interface selectivity, which comes from the principle of even order nonlinear optics. Fluorescence emission, which is in principle not interface selective but varies with the chemical environment where the chromophores locate, can reveal the dynamics of molecules on lipids. In this contribution, we review some examples, which are mainly from our recent works focusing on the application of combined spectroscopic methods, i.e., SHG and two-photon fluorescence (TPF), in studying the dynamic behaviors of several dyes or drugs on lipids and surfactants. This review demonstrates that molecules with both SHG and TPF efficiencies may be used as intrinsic dual-probes in plotting a clear physical picture of their own behaviors, as well as the dynamics of other molecules, on lipid membranes.

Surface enhanced Raman scattering for probing cellular biochemistry

Surface enhanced Raman scattering (SERS) from biomolecules in living cells enables the sensitive, but also very selective, probing of their biochemical composition. This minireview discusses the developments of SERS probing in cells over the past years from the proof-of-principle to observe a biochemical status to the characterization of molecule-nanostructure and molecule-molecule interactions and cellular processes that involve a wide variety of biomolecules and cellular compartments. Progress in applying SERS as a bioanalytical tool in living cells, to gain a better understanding of cellular physiology and to harness the selectivity of SERS, has been achieved by a combination of live cell SERS with several different approaches. They range from organelle targeting, spectroscopy of relevant molecular models, and the optimization of plasmonic nanostructures to the application of machine learning and help us to unify the information from defined biomolecules and from the cell as an extremely complex system.

Coexistence of lipid phases in multilayer phospholipid films probed by Raman mapping

Raman spectroscopy of stacked phospholipid bilayers reveals the chemical and conformational composition of coexisting domains.