Quantitative Proteome Analysis of Atg5 -Deficient Mouse Embryonic Fibroblasts Reveals the Range of the Autophagy-Modulated Basal Cellular Proteome
Authors: Sudhanshu Vrati
Shinjini Bhatnagar
Kiran Bala Sharma
Amit Kumar Yadav
Manish Sharma
Manjula Kalia
Suruchi Aggarwal
Journal: mSystems (2019)
Discipline: MICROBIOLOGY
Keywords: Atg5; IL-6; JAK-STAT; TLR2; TMT mass spectrometry
Affiliations: Translational Health Science and Technology Institute, NCR Biotech Science Cluster, Faridabad, Haryana, India., Translational Health Science and Technology Institute, NCR Biotech Science Cluster, Faridabad, Haryana, India  ., Regional Centre for Biotechnology, NCR Biotech Science Cluster, Faridabad, Haryana, India.

Abstract:  Basal autophagy is crucial for maintenance of cellular homeostasis. ATG5 is an essential protein for autophagosome formation, and its depletion has been extensively used as a tool to disrupt autophagy. Here, we characterize the impact of Atg5 deficiency on the cellular proteome of mouse embryonic fibroblasts (MEFs). Using a tandem mass tagging (TMT)-based quantitative proteomics analysis, we observe that 14% of identified proteins show dysregulated levels in atg5-/- MEFs. These proteins were distributed across diverse biological processes, such as cell adhesion, development, differentiation, transport, metabolism, and immune responses. Several of the upregulated proteins were receptors involved in transforming growth factor β (TGF-β) signaling, JAK-STAT signaling, junction adhesion, and interferon/cytokine-receptor interactions and were validated as autophagy substrates. Nearly equal numbers of proteins, including several lysosomal proteins and enzymes, were downregulated, suggesting a complex role of autophagy/ATG5 in regulating their levels. The atg5-/- MEFs had lower levels of key immune sensors and effectors, including Toll-like receptor 2 (TLR2), interferon regulatory factor 3 (IRF3), IRF7, MLKL, and STAT1/3/5/6, which were restored by reexpression of ATG5. While these cells could efficiently mount a type I interferon response to the double-stranded RNA (dsRNA) mimic poly(I·C), they were compromised in their inflammatory response to the bacterial pathogen-associated molecular patterns (PAMPs) lipopolysaccharide (LPS) and Pam3CSK4. Transcriptional activation and secretion of interleukin-6 (IL-6) in these cells could be recovered by ATG5 expression, supporting the role of autophagy in the TLR2-induced inflammatory response. This study provides a key resource for understanding the effect of autophagy/ATG5 deficiency on the fibroblast proteome.IMPORTANCE Autophagy performs housekeeping functions for cells and maintains a functional mode by degrading damaged proteins and organelles and providing energy under starvation conditions. The process is tightly regulated by the evolutionarily conserved Atg genes, of which Atg5 is one such crucial mediator. Here, we have done a comprehensive quantitative proteome analysis of mouse embryonic fibroblasts that lack a functional autophagy pathway (Atg5 knockout). We observe that 14% of the identified cellular proteome is remodeled, and several proteins distributed across diverse cellular processes with functions in signaling, cell adhesion, development, and immunity show either higher or lower levels under autophagy-deficient conditions. These cells have lower levels of crucial immune proteins that are required to mount a protective inflammatory response. This study will serve as a valuable resource to determine the role of autophagy in modulating specific protein levels in cells. 

Retracted: No

PubPeer comments:
 ![file] It appears that STAT2 bands originated from same blot with different exposures. , 
 ![file] Why STAT1 band pattern is different in different blots? In some blots, it is showing two bands and in some blots it is showing single band. , 
 ![file] Why there is two actin loading controls? , 
 ![file] In both the graphs, the unit is same, i.e. pg ml. The first graph shows less than two-fold difference between wt and atg5 kncok out, got p-value less than 0.01. On the contrary, the second graph which has nearly tenfold difference between wt and atg5 knock out, got p-value less than 0.05. I am concerned about the statistical integrity of the data analysis. , 
 1. The STAT2 blots are same, and represent the same experimental condition. 2. STAT1 displays two isoforms of sizes 91kDa and 84 kDa. The two isoforms do not always resolve on a higher percentage gel. 3. The IRF7 blot was from an independent experiment and hence has a different actin control. 4. As stated in the figure legends, the statistical analysis in Fig 7 has been done using t-test, while that in Fig 9 has been done using ANOVA followed by Dunnettu2019s post hoc comparison test. , 
 Dear authors, Thanks for your quick reply. After reading your comments, I got few more doubts in the experimental design and data analysis. I am really sorry to say that your answers were not convincing to me. Lets discuss them one by one. 1. The STAT2 blots are same, and represent the same experimental condition. The authors have said that STAT2 blots are same and represent the same experimental condition for FIG 6A and FIG 7A. Does it mean, in FIG 6A, STAT2 blot represents the mock transfected cells (transfection reagent for 6 hours)? Does it applicable to only STAT2 blots or for all the blots in FIG 6A? Does it mean, FIG 6A, all the western blots represent the mock transfected cells (transfection reagent for 6 hours)? 2. STAT1 displays two isoforms of sizes 91kDa and 84 kDa. The two isoforms do not always resolve on a higher percentage gel. STAT5 also displays two isoforms and similar size, like STAT1. All the western blot images (FIG 6A, C and E) of STAT5 shows similar band pattern (two bands). But STAT1, which has similar isoform and size like STAT5, was not resolved into two bands. 3. The IRF7 blot was from an independent experiment and hence has a different actin control. If IRF7 was from different experiment, in FIG 8B which represents the bar graph for normalized protein expression (LPS control), why IRF7 was included in the same bar graph? IRF7 should have been represented in a separate bar graph. Does it mean densitometry and normalization of western blots from two different experiments were combined into a single bar graph? , 
 ![file] 4. As stated in the figure legends, the statistical analysis in Fig 7 has been done using t-test, while that in Fig 9 has been done using ANOVA followed by Dunnettu2019s post hoc comparison test. Irrespective of the statistical test used, the greater the difference between two observed values, the less likely it is that the difference is due to simple random chance, and this is reflected by a lower p-value. Lets take another example, which has same statistical test (ANOVA followed by Dunnettu2019s post hoc comparison). In Fig 8D, the first two bars represent nearly two-fold change got lesser p-value and Fig 9E, the first two bars represent nearly ten-fold change got higher p-value. ,