Peer review process
Not revised: This Reviewed Preprint includes the authors’ original preprint (without revision), an eLife assessment, and public reviews.
Read more about eLife’s peer review process.Editors
- Reviewing EditorTom RutkowskiUniversity of Iowa, Iowa City, United States of America
- Senior EditorDavid RonUniversity of Cambridge, Cambridge, United Kingdom
Joint Public Review:
Summary
Non-alcoholic fatty liver disease (NAFLD) is a widespread metabolic disease associated with obesity. Endoplasmic reticulum and calcium dysregulation are hallmarks of NAFLD. Here, the authors explore whether the secreted liver protein transthyretin (TTR), which has been previously shown to modulate calcium signaling in the context of insulin resistance, could also impact NAFLD. The study is motivated by a small cohort of NASH patients who show elevated TTR levels. The authors then overexpress TTR in two mouse obesogenic models, which leads to elevated liver lipid deposition. In contrast, liver-specific TTR knockdown improves some liver lipid levels, reduces inflammation markers, and improves glucose tolerance, overall improving the NAFLD markers. These phenotypic findings are overall convincing and largely consistent in two different diet models.
Because of TTR's connection to calcium regulation, the authors then assess whether the knockdown affects ER stress and impacts SERCA2 expression. However, the direct mechanistic evidence supporting the central claim that TTR physically interacts with and inhibits the SERCA2 calcium pump is preliminary and requires further validation. Whether the broader effects on lipid accumulation, inflammation markers, and glucose tolerance are mechanistically connected remains to be determined.
Strengths
The premise of the study is built on prior work from the authors identifying a link between increased transthyretin secretion and the development of insulin resistance, a related obesity condition. The in vivo studies are comprehensive, using human NASH samples, two distinct diet-induced mouse models (HFD and GAN), and in vitro hepatocyte models. The phenotypic data showing that TTR knockdown alleviates steatosis, inflammation, and insulin resistance are robust and convincing across these systems.
Weaknesses
The mechanistic studies in Figures 6-9 are incomplete. There are several issues encompassing experimental design, rigor, and interpretation that, if properly addressed, would make the study much stronger.
(1) Exogenous TTR that is endocytosed by cells is unlikely to ever find itself inside the lumen of the ER. Conversely, endogenous TTR that is produced in cells and that has not yet been secreted is almost certain to have an ER lumenal localization (as in Figures 7B and 9A, and where an apparent colocalization with SERCA is likely to be incidental). In a model where TTR, acting as a hepatokine, has inhibitory effects on SERCA, these would almost certainly be realized from the cytosolic side of the ER membrane-a region inaccessible to lumenal endogenous TTR. It is possible that the overexpression and knockdown of endogenous TTR have the effects seen due to its secretion and uptake (that is, cell-non-autonomous effects), but this possibility was not directly tested through Transwell or similar assays. Given the identity of TTR as a secretory pathway client protein, the only localization data for TTR that are unexpected are those suggesting an ER localization of exogenously added TTR (Figure 7A), but this localization seems to involve only a minor population of TTR, is hindered by a technical issue with cell permeabilization (see below), and lacks orthogonal approaches to convincingly demonstrate meaningful localization of exogenous TTR at the ER membrane.
(2) The experimental logic in Figure 8 is problematic. The authors use Thapsigargin (Tg), a potent and specific SERCA inhibitor, to probe SERCA function. However, since both Tg and TTR are proposed to inhibit SERCA2, the design lacks a critical control to demonstrate that TTR's effects are indeed mediated through SERCA2. SERCA2 activity should, in principle, be fully and irreversibly inhibited by Tg treatment, especially using such a high concentration (5 µM). If TTR's effect on calcium flux is exclusively through SERCA2, then SERCA2 impairment by TTR should have no additional effect in the presence of Tg, as Tg would already be maximally inhibiting the pump. The current data (Figures 8G-H) showing an effect of TTR-KD even with Tg present is difficult to interpret and may suggest off-target or compensatory mechanisms.
(3) The coIP data in Figure 9 need to be better controlled, including by overexpression of FLAG- and MYC-tagged irrelevant proteins, ideally also localized to the ER. The coIP of overexpressed TTR with endogenous SERCA in Figure 9D, in addition to requiring a more rigorous control, is itself of relatively low quality, with the appearance of a possible gel/blotting artifact.
(4) The ER stress markers in Figure 6 are not convincing. Molecular weight markers and positive controls (for example, livers from animals injected with tunicamycin) are missing. In addition, the species of ATF6 that is purportedly being detected (cleaved or full-length) is not indicated, and this protein is also notoriously difficult to detect with convincing specificity in mouse tissues. As well, CHOP protein is usually not detectable in control normal diet mouse livers, raising questions of whether the band identified as CHOP is, in fact, CHOP. These issues, along with the observation that ER stress-regulated RNAs are not altered (Figure S5), raise the question of whether ER stress is involved at all. Likewise, the quantification of SERCA2 levels from Figure 6 requires more rigor. For all blots, it isn't clear that analyzing only 3 or 4 of the animals provides adequate and unbiased power to detect differences; in addition, in Figure 6C, at least the SERCA2 exposure (assuming SERCA2 is being specifically detected; see above) is well beyond the linear range of quantification.
In addition, the following important issues were raised:
(5) n=4 for overexpression might not provide adequate statistical power.
(6) The error for human NASH samples and controls in Figure 1A is surprisingly small. Larger gene expression data sets from NASH cohorts exist and should be used to test the finding in a larger population.
(7) For experiments involving two independent variables (e.g., diet and TTR manipulation, as in Figures 2, 3, 4, 5), a Two-way ANOVA must be used instead of One-way ANOVA or t-tests. Also, the ND-TTR-KD group is missing - these data are an essential control to show the specificity of the knockdown and its effects in a non-diseased state.
(8) Figure 7A: The co-localization signal between TTR-Alexa488 and the ER marker is not strong or convincing, which could be due to the inappropriate immunofluorescence protocol used, of permeabilization prior to fixation. The standard and recommended order is fixation first (to preserve cellular architecture), followed by permeabilization.