Quasi-equilibrium state based quantification of biological macromolecules in single-molecule localization microscopy.
Xuecheng ChenYaqian LiXiaowei LiJielin SunDaniel M CzajkowskyZhifeng ShaoPublished in: Methods and applications in fluorescence (2023)
The stoichiometry of molecular components within supramolecular biological complexes is often an important property to understand their biological functioning, particularly within their native environment. While there are well established methods to determine stoichiometry in vitro, it is presently challenging to precisely quantify this property in vivo, especially with single molecule resolution that is needed for the characterization stoichiometry heterogeneity. Previous work has shown that optical microscopy can provide some information to this end, but it can be challenging to obtain highly precise measurements at higher densities of fluorophores. Here we provide a simple approach using already established procedures in single-molecule localization microscopy (SMLM) to enable precise quantification of stoichiometry within individual complexes regardless of the density of fluorophores. We show that by focusing on the number of fluorophore detections accumulated during the quasi equilibrium-state of this process, this method yields a 50-fold improvement in precision over values obtained from images with higher densities of active fluorophores. Further, we show that our method yields more correct estimates of stoichiometry with nuclear pore complexes and is easily adaptable to quantify the DNA content with nanodomains of chromatin within individual chromosomes inside cells. Thus, we envision that this straightforward method may become a common approach by which SMLM can be routinely employed for the accurate quantification of subunit stoichiometry within individual complexes within cells.
Keyphrases
- single molecule
- induced apoptosis
- atomic force microscopy
- living cells
- cell cycle arrest
- high resolution
- gene expression
- molecular dynamics
- cell death
- deep learning
- molecular dynamics simulations
- healthcare
- signaling pathway
- dna damage
- endoplasmic reticulum stress
- genome wide
- health information
- oxidative stress
- optical coherence tomography
- convolutional neural network
- pi k akt
- quantum dots
- fluorescent probe