In situ and ex situ surface‐enhanced Raman spectroscopy (SERS) analysis of cell mitochondria

Abstract

As the "powerhouse" of cells, mitochondrion is the main site of cellular aerobic respiration and plays a vital role in performing many important cellular functions. The consequence of mitochondrial dysfunction could lead to a wide range of disorders and diseases. Traditional mitochondria‐related cytobiology methods always require the isolation of organelles for biological components, followed by structural analysis and quantitative analysis. In this study, we tried to assess the feasibility and reliability of the isolation‐based method and the in situ approach from the spectral fingerprint characters. Surface‐enhanced Raman scattering spectroscopy (SERS) was employed to investigate the molecular information of mitochondria from cancer cells (HepG2 and MCF‐7 cells) in situ with the assistant of mitochondrion‐targeting nanoprobes, which was compared with the isolation‐based ex situ method. The results display two methods, which show high consistency in the spectral profiles of mitochondrion, proving the feasibility of both in bioanalysis. Abundant molecular information such as protein and DNA is disclosed, and protein is one of the main components. From spectral comparison between two cancer cells, differences in protein content are observed. We believe that this comparative study will provide a valuable and recommended reference for the selection of analytical methods for different study purposes.

Assisted laser impedance spectroscopy to probe breast cancer cells

“…Hence, the relative lipid/carbohydrate level is a factor related to σ (ω, ω ′ ) over the capacitive and resistive behaviour of the cell membrane. Therefore, based on the published Raman spectra for BT-474, MCF-7 and lymphocytes [55][56][57], the approximate lipid-to-carbohydrate ratios were extracted, as summarized in table 1. The overall capacitance, C p , is proportional to the lipid-to-carbohydrate integrated Raman vibrational ratios.…”

Decoding Optical Data with Machine Learning

“…[ 101 ] Future in vivo studies are expected to require highly efficient data processing and analysis, which can be provided by ML algorithms. [ 102 ] To further enhance the efficiency and robustness, automation of data collection and filtering for large‐sample‐set biological studies will be highly desired. [ 103 ]…”

Recent progress of surface-enhanced Raman spectroscopy for subcellular compartment analysis

“…They found that the AuNPs did not cause significant damage to mitochondria 100 . Besides, Xu's group investigated the molecular information of mitochondria from cancer cells in situ with the assistant of mitochondrion-targeting nanoprobes, compared with the isolation-based ex situ method 120 . In the following study, Xu et al investigated the dynamic molecular changes of the extracted living mitochondria upon phototherapy by SERS, to elucidate the underlying molecular mechanisms associated with cell death induced by subcellular dysfunction.…”