Quantitative proteomics for the analysis of spatio-temporal protein dynamics during autophagy

Zimmermann, Andrea C.; Zarei, Mostafa; Eiselein, Sven; Dengjel, Jörn

doi:10.4161/auto.6.8.12786

Cited by 29 publications

(30 citation statements)

References 105 publications

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“…In the data used for network interface, each phosphosites x i has 5 time points of fold changes data with the experimental conditions of after starvation and rampacyin treatments, which can be represented as [x i (t 11 ), x i (t 12 ), x i (t 13 ), x i (t 14 ), x i (t 15 ), x i (t 21 ), x i (t 22 ), x i (t 23 ), x i (t 24 ), x i (t 25 )]. We calculated the time-lagged correlation coefficients based on the Pearson correlation coefficients between two phosphosites x i and x j with one time-interval lag:…”

Section: Calculation Of the Time-lagged Correlation Coefficients And mentioning

confidence: 99%

“…where X = [x i (t 11 ), x i (t 12 ), x i (t 13 ), x i (t 14 ), x i (t 21 ), x i (t 22 ), x i (t 23 ), x i (t 24 )] and Y = [x j (t 12 ), x j (t 13 ), x j (t 14 ), x j (t 15 ), x j (t 22 ), x j (t 23 ), x j (t 24 ), x j (t 25 )].…”

Section: Calculation Of the Time-lagged Correlation Coefficients And mentioning

confidence: 99%

“…To study cellular processes underlying autophagy, methodologies utilizing mass spectrometry (MS)-based proteomics have proven very powerful, 14 e.g., for establishing the protein composition of autophagosomes, 15 addressing protein degradation dynamics, 16,17 and studying protein-interaction networks. 18 In the past decade numerous technological advances have made quantitative phosphoproteomics the method of choice for studying protein phosphorylation in an unbiased manner.…”

Section: Introductionmentioning

confidence: 99%

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Characterization of early autophagy signaling by quantitative phosphoproteomics

et al. 2013

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Section: Calculation Of the Time-lagged Correlation Coefficients And mentioning

confidence: 99%

Section: Calculation Of the Time-lagged Correlation Coefficients And mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Characterization of early autophagy signaling by quantitative phosphoproteomics

et al. 2013

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“…Cell membrane permeabilization with digitonin and extraction of the nonmembrane-bound form of LC3 allows combined 480 Autophagy Volume 8 Issue 4…”

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confidence: 99%

“…These assays may be applied to autophagy-related questions enabling researchers to investigate differential effects in global protein or even organelle degradation studies. 480,481 SILAC (stable isotope labeling with amino acids in cell culture) can also provide comparative information between different treatment conditions, or between a wild type and mutant.…”

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confidence: 99%

Guidelines for the use and interpretation of assays for monitoring autophagy

Klionsky¹,

Abdalla²,

Abeliovich³

et al. 2012

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In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

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An Endoplasmic Reticulum (ER)‐Targeting DNA Nanodevice for Autophagy‐Dependent Degradation of Proteins in Membrane‐Bound Organelles

et al. 2022

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Targeted protein degradation via proteasomal and lysosomal pathways is a promising therapeutic approach, and proteins in cytoplasm or on the cell membrane can be easily contacted and have become the major targets. However, degradation of disease-related proteins that exist in membrane-bound organelles (MBO) such as the endoplasmic reticulum (ER) remains unsolved due to the membrane limits. Here we describe a DNA nanodevice that shows ER targeting capacity and undergoes new intracellular degradation via the autophagy-dependent pathway. Then the DNA nanostructure functionalized with specific ligands is used to selectively catch ER-localized proteins and then transport them to the lysosome for degradation. Through this technique, the degradation of both exogenous ERresident protein (ER-eGFP) and endogenous overexpressed molecular chaperone (glucose-regulated protein 78) in cancer cells has been successfully executed with high efficiency.

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Quantitative proteomics for the analysis of spatio-temporal protein dynamics during autophagy

Cited by 29 publications

References 105 publications

Characterization of early autophagy signaling by quantitative phosphoproteomics

Characterization of early autophagy signaling by quantitative phosphoproteomics

Guidelines for the use and interpretation of assays for monitoring autophagy

An Endoplasmic Reticulum (ER)‐Targeting DNA Nanodevice for Autophagy‐Dependent Degradation of Proteins in Membrane‐Bound Organelles

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