Genotoxic stress in constitutive trisomies induces autophagy and the innate immune response via the cGAS-STING pathway
Authors: Line L Andersen
Sahar Karbassi
Maria Krivega
Clara M Stiefel
Neysan Donnelly
Andreas Pichlmair
Narendra K Chunduri
Zuzana Storchová
Journal: Communications Biology (2021)
Discipline: BIOLOGY & BIOCHEMISTRY
Keywords: chromosome gain; human cell physiology; DNA replication pathway; autophagy; lysosomal degradation
Affiliations: Molecular Genetics, University of Kaiserslautern, Kaiserslautern, Germany., Institute of Virology, TU Munich, München, Germany., Max Planck Institute of Biochemistry, Martinsried, Germany., German Center for Infection Research (DZIF), Munich partner site, München, Germany., Molecular Genetics, University of Kaiserslautern, Kaiserslautern, Germany. .

Abstract:  Gain of even a single chromosome leads to changes in human cell physiology and uniform perturbations of specific cellular processes, including downregulation of DNA replication pathway, upregulation of autophagy and lysosomal degradation, and constitutive activation of the type I interferon response. Little is known about the molecular mechanisms underlying these changes. We show that the constitutive nuclear localization of TFEB, a transcription factor that activates the expression of autophagy and lysosomal genes, is characteristic of human trisomic cells. Constitutive nuclear localization of TFEB in trisomic cells is independent of mTORC1 signaling, but depends on the cGAS-STING activation. Trisomic cells accumulate cytoplasmic dsDNA, which activates the cGAS-STING signaling cascade, thereby triggering nuclear accumulation of the transcription factor IRF3 and, consequently, upregulation of interferon-stimulated genes. cGAS depletion interferes with TFEB-dependent upregulation of autophagy in model trisomic cells. Importantly, activation of both the innate immune response and autophagy occurs also in primary trisomic embryonic fibroblasts, independent of the identity of the additional chromosome. Our research identifies the cGAS-STING pathway as an upstream regulator responsible for activation of autophagy and inflammatory response in human cells with extra chromosomes, such as in Down syndrome or other aneuploidy-associated pathologies. 

Retracted: No

PubPeer comments:
 There is splicing in Sup. Fig9b for total P70S6K which authors indicated, however there are no such splicings for phosphorylated form and for loading control. Based on their raw data it seems that LC3B WB and pP70S6K are from different gels and membranes. alpha-actinin WB is on different orientations in the Sup. Fig. and raw data. Which is correct? It seems that selection of lines was random. Could authors please clarify this.![file] ![file] , 
 WBs for IkBa and b-actin in raw data for Sup. Fig5c contain different number of lines and it seems they are from different gels. Could authors comment on these. ![file] , 
 The molecular weight of the analyzed proteins and the multiple analysis do not allow to perform all WB from the same gel. Thus, in this case the p-P70 and LC3 are from one gel and blot, which was 15% to allow for LC3 separation (the molecular weight of LC3 is small). P70 was taken from another blot than p-P70, because we did not develop p-P70 and P70 from the same blot. This is to avoid any possible bleed-through of a signal in case of insufficient stripping, as well as to avoid potentially reduced signal when reprobing the same membrane. Since p-ULK1 is of a high molecular weight, we used a gel with a different percentage (7.5 % or 10%), which was also used for alpha-actinin analysis. (Equal loading was always controlled by Ponceau staining and alpha-actinin for each immunoblotting). Importantly, all used samples were always the same on all gels for each biological replicate, and can therefore be presented together. All experiments were performed at least in three biological replicates. The same applies for IkBa and b-actin, which are of molecular weight 39 kDa and 43 kDa, i.e. too close to each other to enable cutting the membrane. Regarding the Sup. Fig. 9 - there was no random line selection. The Sup. Figure 9 is correct, but unfortunately there was a mistake in a raw data, where the alpha-actinin figure was inadvertently placed in an incorrect orientation. We thank PubPeer for noticing this small discrepancy. , 
 Dear Dr. Storchovu00e1, Thank you for your reply. However according to the Image integrity and standards: Loading controls (e.g. GAPDH, actin) must be run on the same blot. When sample processing controls are run on different gels, they must be identified as such in the figure legend. . And as you claim equal loading was controlled for each blot it is necessary to show proper one to each blot at least Ponceau. And there are also concerns regarding statistical analysis of data. All your data is more than two groups for each data set, but you use the t-test or the Mann-Whitney test even without any correction for multiple comparisons, instead of ANOVA. Which should be performed according to the Journal rules. Multiple comparisons: When making multiple statistical comparisons on a single data set, authors should explain how they adjusted the alpha level to avoid an inflated Type I error rate, or they should select statistical tests appropriate for multiple groups (such as ANOVA rather than a series of t-tests). . Could you please justify choice of tests? , 
 How can we be sure if there are no loading controls (ponceau) that an even amount of protein was loaded on each gel? In addition, there are statistical issues, and the authors used a t-test without any correction for multiple comparisons, but they compared in each experiment more than two groups. , 
 Pairwise u0441omparison of groups could give a p-value lower than 0.05 by chance without applying any correction for multiple comparisons. , 
 #6 We are fully aware of the problem with statistics. That s why we did in parallel also an analysis by ANOVA, as you can see in the supplementary data. , 
 From the supplementary file is unclear if the p-value was only derived from ANOVA or ANOVA followed by the post hoc test. If ANOVA is unsignificant there is no reason to run a post hoc test. Please find an attached example for figure 3 where p-values obtained from ANOVA and t-test are inconsistent. ![file] ![file] , 
 Yes, we are fully aware of that, and we also provided al these data. , 
 #8 A prerequiste of ANOVA is equal variances, because it and the post hoc tests use the pooled variance. If that condition is violated, the post hoc tests can give quite different (i.e. wrong) results from individual t-tests (even assuming similar corrections for multiple comparisons). , 
 Please find attached more results which significance is doubtable, as a more suitable test does not indicate significance. Moreover, in the methods section, the authors did not report which test was performed to analyze the normality of the data. In some cases, they used a nonparametric test and the test for checking if variances were equal. In addition, multiple t-tests violate rules of the journal 1) Multiple comparisons: When making multiple statistical comparisons on a single data set, authors should explain how they adjusted the alpha level to avoid an inflated Type I error rate, or they should select statistical tests appropriate for multiple groups (such as ANOVA rather than a series of t-tests. 2) Normal distribution: Many statistical tests require that the data be approximately normally distributed; when using these tests, authors should explain how they tested their data for normality. If the data do not meet the assumptions of the test, then a non-parametric alternative should be used instead.) ![file] ![file] ![file] , 
 Pleased find attached more results with doubtful significance, ![file] ![file] ![file] , 
 Some results were significant, and some not. We show in the plots T-test statistics, but because we are aware that it s not optimal (although broadly used in biology), we also provide the statistics from ANOVA. , 
 But conclusions were general for all aneuploids Fig4f  Importantly, this modest cGAS depletion diminished the expression of its targets IFIT1 or IFIT3 in constitutive trisomic tetrasomic cells, and in diploid cells treated with AraC. In contrast, the expression remained largely unchanged in diploid cells upon cGAS depletion. Fig6f  Reduced STING also caused a decrease in cytoplasmic LC3 and LAMP2 signal, but only in trisomic cells. Fig7g and i  By WB, we observed increased levels of STING, p-STING, and p-TBK1u2013S172, as well as increased STING clustering in the cytoplasm in trisomic cells (Fig. 7cu2013i). , 
 #13 I think there is some misunderstanding. Just ANOVA (SD equal between groups), Brown-Forsythe ANOVA, or Welch s ANOVA test (SD unequal between groups) is not an end-point. After such test dependent on its results should be run post hoc test. For instance, for ANOVA Tukey, Holm-Sidak for Welch s ANOVA Dunnetts test. But if ANOVA shows no changes (not significant), pairwise comparisons have no sense. T-test only allowed for the comparison of two groups in the same experiment. However, in almost each experiment, you have more than two groups; for multiple comparisons with t-test, it also needed correction, such as Bonferroni correction. More interestingly, when you analyzed data for qPCR, you used Welchs test (unequal SD, which I assume was) and t-test but chose to show results for t-test because they were significant in more comparisons. , 
 #13 Dear author, I like that you put the actual p values into the paper, much better than simply putting asterisks. Makes it easy for the reader to judge on the data. , 
 #16 Thank you so much. It nice to see that the work is appreciated. ,