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Real-time tracking of ER turnover during ERLAD by a rhenium complex via lifetime imaging.

ABSTRACT: Endoplasmic reticulum (ER) degradation by autophagy (ER-phagy) is a recently revealed selective autophagy pathway that plays important roles in organelle turnover and protein degradation, but the biological functions of ER-phagy are largely unknown. Here, we present an ER-targeting Re(I) tricarbonyl complex (Re-ERLAD) that can accumulate in the ER, induce ER-to-lysosome-associated degradation (ERLAD) upon visible light irradiation, and label ER buds and track their morphological alterations during ER-phagy. The emission of Re-ERLAD is sensitive to viscosity, which is a key parameter reflecting the amount of unfolded protein in the ER. Quantitative detection using two-photon fluorescence lifetime imaging microscopy shows that ER viscosity initially increases and then decreases during ERLAD, which reveals that ERLAD is a pathway for alleviating ER stress caused by unfolded proteins. In conclusion, our work presents the first specific photoinducer and tracker of ERLAD, which can be used in studying the regulatory mechanism and function of this process.

SUBMITTER: Hao L

PROVIDER: S-EPMC9362766 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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Real-time tracking of ER turnover during ERLAD by a rhenium complex via lifetime imaging.

Hao Liang L Ling Yu-Yi YY Huang Zhi-Xin ZX Pan Zheng-Yin ZY Tan Cai-Ping CP Mao Zong-Wan ZW

National science review 20211028 7

Endoplasmic reticulum (ER) degradation by autophagy (ER-phagy) is a recently revealed selective autophagy pathway that plays important roles in organelle turnover and protein degradation, but the biological functions of ER-phagy are largely unknown. Here, we present an ER-targeting Re(I) tricarbonyl complex (Re-ERLAD) that can accumulate in the ER, induce ER-to-lysosome-associated degradation (ERLAD) upon visible light irradiation, and label ER buds and track their morphological alterations duri ...[more]

PMID: 35958681

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Project description:Lung cancer is the most common cause of cancer-related deaths worldwide. Early detection improves outcomes, however, existing sampling techniques are associated with suboptimal diagnostic yield and procedure-related complications. Autofluorescence-based fluorescence-lifetime imaging microscopy (FLIM), a technique which measures endogenous fluorophore decay rates, may aid identification of optimal biopsy sites in suspected lung cancer. Our fibre-based fluorescence-lifetime imaging system, utilising 488 nm excitation, which is deliverable via existing diagnostic platforms, enables real-time visualisation and lifetime analysis of distal alveolar lung structure. We evaluated the diagnostic accuracy of the fibre-based fluorescence-lifetime imaging system to detect changes in fluorescence lifetime in freshly resected ex vivo lung cancer and adjacent healthy tissue as a first step towards future translation. The study compares paired non-small cell lung cancer (NSCLC) and non-cancerous tissues with gold standard diagnostic pathology to assess the performance of the technique. Paired NSCLC and non-cancerous lung tissues were obtained from thoracic resection patients (N=21). A clinically compatible 488 nm fluorescence-lifetime endomicroscopy platform was used to acquire simultaneous fluorescence intensity and lifetime images. Fluorescence lifetimes were calculated using a computationally-lightweight, rapid lifetime determination method. Fluorescence lifetime was significantly reduced in ex vivo lung cancer, compared with non-cancerous lung tissue [mean ± standard deviation (SD), 1.79±0.40 vs. 2.15±0.26 ns, P<0.0001], and fluorescence intensity images demonstrated distortion of alveolar elastin autofluorescence structure. Fibre-based fluorescence-lifetime imaging demonstrated good performance characteristics for distinguishing lung cancer, from adjacent non-cancerous tissue, with 81.0% sensitivity and 71.4% specificity. Our novel fibre-based fluorescence-lifetime imaging system, which enables label-free imaging and quantitative lifetime analysis, discriminates ex vivo lung cancer from adjacent healthy tissue. This minimally invasive technique has potential to be translated as a real-time biopsy guidance tool, capable of optimising diagnostic accuracy in lung cancer.

Dataset Information

Real-time tracking of ER turnover during ERLAD by a rhenium complex via lifetime imaging.

Publications

Real-time tracking of ER turnover during ERLAD by a rhenium complex via lifetime imaging.

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