# Galectin-3 modulates epithelial cell adaptation to stress at the ER-mitochondria interface

Lucie Coppin, Arnaud Jannin, Emilie Ait Yahya, Caroline Thuillier, Céline Villenet, Meryem Tardivel, Antonino Bongiovanni, Cécile Gaston, Simon de Beco, Nicolas Barois, et al.

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## To cite this version:

Lucie Coppin, Arnaud Jannin, Emilie Ait Yahya, Caroline Thuillier, Céline Villenet, et al. Galectin-3 modulates epithelial cell adaptation to stress at the ER-mitochondria interface. Cell Death and Disease, 2020, 11 (5), pp.360. 10.1038/s41419-020-2556-3. hal-03060582

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# Galectin-3 modulates epithelial cell adaptation to stress at the ER-mitochondria interface

Lucie Coppin<fnref n="1" />, Arnaud Jannin<fnref n="1" />, Emilie Ait Yahya<fnref n="2" />, Caroline Thuillier³, Céline Villenet⁴, Meryem Tardivel⁵,
Antonino Bongiovanni⁵, Cécile Gaston⁶, Simon de Beco⁶, Nicolas Barois⁷, Isabelle van Seuningen<fnref n="1" />,
Emmanuelle Durand⁸, Amélie Bonnefond⁸, Jean-Claude Vienne<fnref n="2" />, Joseph Vamecq<fnref n="2" />, Martin Figeac⁴, Audrey Vincent<fnref n="1" />,
Delphine Delacour⁶, Nicole Porchet<fnref n="1" /> and Pascal Pigny<fnref n="1" />

## Abstract

Cellular stress response contributes to epithelial defense in adaptation to environment changes. Galectins play a pivotal role in the regulation of this response in malignant cells. However, precise underlying mechanisms are largely unknown. Here we demonstrate that Galectin-3, a pro and anti-apoptotic lectin, is required for setting up a correct cellular response to stress by orchestrating several effects. First, Galectin-3 constitutes a key post-transcriptional regulator of stress-related mRNA regulons coordinating the cell metabolism, the mTORC1 complex or the unfolded protein response (UPR). Moreover, we demonstrated the presence of Galectin-3 with mitochondria-associated membranes (MAM), and its interaction with proteins located at the ER or mitochondrial membranes. There Galectin-3 prevents the activation and recruitment at the mitochondria of the regulator of mitochondria fission DRP-1. Accordingly, loss of Galectin-3 impairs mitochondrial morphology, with more fragmented and round mitochondria, and dynamics both in normal and cancer epithelial cells in basal conditions. Importantly, Galectin-3 deficient cells also display changes of the activity of the mitochondrial respiratory chain complexes, of the mTORC1/S6RP/4EBP1 translation pathway and reactive oxygen species levels. Regarding the ER, Galectin-3 did not modify the activities of the 3 branches of the UPR in basal conditions. However, Galectin-3 favours an adaptive UPR following ER stress induction by Thapsigargin treatment. Altogether, at the ER-mitochondria interface, Galectin-3 coordinates the functioning of the ER and mitochondria, preserves the integrity of mitochondrial network and modulates the ER stress response.

## Introduction

Eukaryotic cells are partitioned into discrete organelles endowed with specific functions. For example, protein synthesis, folding, secretion and degradation take place at the endoplasmic reticulum (ER), whereas cellular

bioenergetics occurs at the mitochondria. Cell homeostasis depends on the ability of these distinct organelles to communicate and to exchange cargos. Among them, the ER appears especially important since it can develop close contacts with most organelles, notably the mitochondria<fnref n="1" />. Interestingly, the ER-mitochondria interactions which are commonly referred to as mitochondria-associated membranes (MAM) regulate important cellular processes such as mitochondrial biogenesis and metabolism, calcium signalling or lipid biosynthesis<fnref n="2" />,³. When the protein synthetic load overcomes the ER folding capacities, a state called ER stress occurs. To restore ER homeostasis, a network of transduction pathways named unfolded protein response (UPR) is activated⁴.

Correspondence: Pascal Pigny (pascal.pigny@inserm.fr)

<figure><img src="image_3.png" /></figure>

<footnote n="1">¹University of Lille, CNRS, Inserm, CHU Lille, UMR9020 – UMR-S 1277 - Canther – Cancer Heterogeneity, Plasticity and Resistance to Therapies, F-59000 Lille, France</footnote>

<footnote n="2">²CHU Lille, Institut de Biochimie & Biologie Moléculaire, Centre de Biologie et Pathologie, F-59000 Lille, France</footnote>

<footnote>Full list of author information is available at the end of the article
These authors contributed equally: Audrey Vincent, Delphine Delacour, Nicole Porchet</footnote>

<footnote>Edited by C. Munoz-Pinedo</footnote>
Collectively, these pathways act to reduce protein synthesis and to increase ER folding and ER-associated degradation (ERAD) capacities. However, when this adaptive response fails the UPR evolves towards apoptosis.

Galectin-3 is a β-galactoside-binding lectin, encoded by *LGALS3* gene in humans, which contains a C-terminal carbohydrate recognition domain (CRD) responsible for interactions with glycolipids or glycoproteins and a low complexity domain which allows interactions with the CRD and other partners⁵,⁶. Moreover, despite the absence of a canonical RNA-binding domain, Galectin-3 is a non-classic RNA-binding protein (RBP) able to stabilise mucin *MUC4* mRNAs in cancer cells⁷. Galectin-3 is highly expressed by epithelial cells and plays important roles in the organisation of renal and intestinal cells. Although Galectin-3-KO mice are viable in controlled conditions, loss of Galectin-3 leads to morphological abnormalities of the epithelial cells as well as perturbation of the biosynthetic pathway⁸⁻¹⁰. Galectin-3 is a soluble protein which is synthesised on free ribosomes and thus bypasses the classical ER-Golgi pathway for its secretion in the extracellular medium. Indeed, premature binding of Galectin-3 with its ligands which are major components of the ER lumen would cause aggregation and perturb the secretory pathway¹¹,¹². While being synthesised in the cytosol, Galectin-3 associates with various organelles, such as carrier vesicles or endosomes¹³. At the mitochondria level, Galectin-3 prevents the cytochrome-c release and ensures mitochondrial integrity¹⁴,¹⁵. However, it is currently unknown whether these mitochondrial effects depend on Galectin-3 ability to modulate mitochondria-ER interactions in epithelial cells.

In the present study we first aimed to obtain a global view of the post-transcriptional regulatory action of Galectin-3 in epithelial cells. To this end, we combined whole transcriptome stability analysis with mRNA and protein quantification. We showed that Galectin-3 regulates the stability of subsets of mRNAs which share similar functions notably cell metabolism, cell death and stress response pathways. By coupling imaging and biochemical approaches, we showed that Galectin-3 localises at the ER-mitochondria interface where it preserves the integrity of the mitochondrial network and modulates the cellular bioenergetics and the UPR.

## Results

**Gal-3 regulates the half-life of subsets of mRNAs with shared functions**

We first aimed to obtain a global view of the action of Galectin-3 as a post-transcriptional regulator in epithelial cells. For that purpose, we used two models deriving from the human pancreatic cancer cell line T3M-4, control Sc cells expressing high levels of Galectin-3 and a representative mutant clone (Sh1 called Sh cells thereafter)

where Galectin-3 expression was stably knocked-down by *shRNA* (Fig. S1). Using actinomycin D and RNA-Seq, we performed a whole-transcriptome stability analysis. We built the decay curve for 9444 transcripts in both models using the most appropriate kinetic model. In all, 3356 transcripts with a decay curve characterised by a r² ≥ 0.9 were selected for further analysis. Rapidly decaying mRNAs (t₁/₂ < 3.0 h) were excluded as the experimental time-points did not allow reliable calculation of their half-lives. Therefore, the total number of RNAs analysable was 2275 (Fig. 1a). A total of 440 mRNAs showed a ≥2-fold difference in their half-life between Sc and Sh cells (Table S1). The vast majority (385 mRNAs) were stabilised by Galectin-3 whereas only 55 mRNAs were destabilised by Galectin-3 (Fig. 1a, b and Table S1). To further identify the biological processes and the organelles involved, the set of mRNAs whose stability was modified by Galectin-3 (n = 440) was submitted to an analysis by the Gene Set Enrichment Analysis (GSEA) tool (Fig. 1c, d). Focusing on cellular component, the mitochondria and the ER were significantly enriched in proteins whose mRNAs are post-transcriptionally regulated by Galectin-3 (Fig. 1c, Table S2). Using Hallmark as a reference collection, 13 biological pathways were significantly enriched in our data set, several previously unrelated to Galectin-3 such as metabolic pathways (i.e. glycolysis, fatty acid metabolism) and the UPR (Fig. 1d and Table S2). Regarding UPR, twelve mRNAs stabilised by Gal-3 were classified in this category by GSEA (in black). Twelve additional mRNAs (in blue) were assigned to UPR based on the Gene Ontology (GO) annotation of the gene product as determined with AmiGO (Fig. 1d). To check whether changes of the mRNA half-life influence mRNA levels, we evaluated by qPCR the steady state mRNA levels of 7 mRNA from the UPR category (Fig. 1d, underlined) and stabilised by Galectin-3. All but one mRNA showed a significant reduction of expression in Sh cells by comparison with Sc cells (Fig. 1e). Moreover, we studied protein expression of four mRNA stabilised by Galectin-3, namely PARN, XPOT, USP14 and SEL1L in basal state. Our results showed that the protein levels of USP14 and SEL1L, both involved in ERAD, were significantly higher in Sh cells whereas a similar trend existed for PARN and XPOT (Fig. 1f). Thus Galectin-3, as a non-conventional RBP, modulates selectively the half-life, levels and translation of mRNAs whose encoded proteins share similar biological functions (RNA regulons).

## Localisation of Galectin-3 at the ER-mitochondria interface

Since Galectin-3 post-transcriptionally regulates several genes involved in mitochondria and/or ER functioning, we next wondered whether Galectin-3 could localise at the ER-mitochondria interface. Using high-resolution fluorescence microscopy, KDEL as a proxy of the ER
<figure><img src="image_4.png" /><figcaption>**Fig. 1** (See legend on next page.)</figcaption></figure>
(see figure on previous page)

**Fig. 1** Galectin-3 regulates the half-life of more than 400 mRNAs which shared similar functions. **a** Total number of mRNA studied by whole transcriptome stability analysis in pancreatic Sh and control Sc cells (see text for details). **b** Example of one Galectin-3 stabilised (ATF6) and one Galectin-3 destabilised mRNA (EIF2AK1). **c, d** Significantly enriched organelles (c) or biological pathways (d) to which belong the mRNA stabilised or destabilised by Galectin-3 (n = 440) as determined by enrichment analysis performed with the GSEA tool (the number of mRNAs in the experimental dataset which overlaps with the reference datasets is shown under brackets; horizontal bar indicates the p value of the Fisher's exact test (–log10). Examples of mRNA species stabilised/destabilised by Galectin-3 belonging to three different pathways are shown in the table (mRNA species in black were assigned to the biological category by the GSEA analysis whereas those in blue were manually assigned based on AmiGO-derived annotation; in bold dark are shown mRNAs which were assigned to mitochondria as cellular component by GSEA; underlined are shown mRNAs which were studied in e). **e** Expression levels of selected mRNA species stabilised by Galectin-3 and belonging to the UPR pathway were determined by qRT-PCR in Sh and control Sc cells at baseline (n = 3 independent experiments). **f** Expression levels of four selected proteins and actin determined by western blotting (n = 3 independent experiments). Fold change was analysed by densitometry. Expression level was arbitrarily set at 100% for Sc cells. Data are mean ± SEM; \*p < 0.05, \*\*p < 0.01, \*\*\*p < 0.001 and NS not significant.

network and Mitotracker to stain the mitochondria (Fig. 2a), we showed that, although the ER and mitochondria display by themselves 12% of contacts, ~13% of the ER-mitochondria interfaces associate with Galectin-3 in pancreatic Sc cells (Fig. 2b). Conversely, 4% of total Galectin-3 associates with this area (as expected for a highly expressed lectin which associates with diverse subcellular compartments¹³,¹⁶). In addition, live microscopy using Mitotracker and Gal-3 dsRed construct validated the dynamic association between Galectin-3 and the mitochondria over time (Movie S1). Immunogold staining of human intestinal Caco2 cells coupled with transmission electron microscopy (TEM) revealed that Galectin-3 does associate with the ER complex. However, this association is transient, and specifically occurs at contact sites between the ER and the mitochondria (Fig. 2c, yellow circles and arrows). Finally, we performed density gradient centrifugations to collect subcellular fractions enriched in mitochondria, MAMs and ER, according to a reference method. We confirmed that a pool of intracellular Galectin-3 is present in MAM-enriched fraction in both Caco2 and pancreatic Sc cells (Fig. 2d). The presence of Galectin-3 in the ER fraction could be explained by its possible contamination by lysosomes. Interestingly, among the interacting partners of Galectin-3 identified in Caco-2 cells by immunoprecipitation (IP) coupled with mass spectrometry analysis, seven (≈4% of the whole) are exclusively located at the ER membrane such as TBL2, a regulator of ER stress response, and 13 in the mitochondria such ATP5J (Table S3 and Fig. S2). To conclude, by combining several approaches we show that Galectin-3 is found at MAMs thus suggesting a dedicated function of Galectin-3 at that level.

## Impact of Galectin-3 on mitochondria morphology, dynamics and bioenergetics

The ER-mitochondria interface constitutes a key hub for the ER stress response and mitochondria bioenergetics¹⁷,¹⁸. We then hypothesised that Galectin-3 may be instrumental there for cell adaptation to stress and/or

mitochondrial homeostasis. First, we studied the impact of Galectin-3 on the morphology and behaviour of mitochondria. Ultrastructural analyses performed in WT and *Lgals3*⁻/⁻ mouse enterocytes (Fig. 2e) showed that loss of Galectin-3 provokes the formation of enlarged and swollen mitochondria whereas in wild-type cells mitochondria display the classical “stick shape”. As expected, image analysis confirmed an increased maximum diameter in Galectin-3 deficient versus control mouse enterocytes (Fig. 2f). Similarly, ultrastructural analysis of the mitochondrial network in Sh cells revealed irregular mitochondrial shape in comparison with controls Sc cells (Fig. 2g). In addition, numerous degradative compartments appear in close proximity of mitochondria in Sh cells. We concluded that Galectin-3 is required for maintenance of typical mitochondrial morphology in epithelial cells. Second, we analysed the architecture of the mitochondrial network (Fig. 3a). In dense cultures, analysis of the images with the MiNA toolset¹⁹ enabled to calculate the values of mitochondrial network 2D parameters. The mitochondrial footprint (Fig. 3a, b), the number of branches per network and the summed branch length (Fig S3a) were significantly decreased in Sh cells versus control Sc cells. These results show that, in the absence of Galectin-3, the mitochondrial network exhibits a less tubular shape but instead mitochondrial fragmentation (Fig. 3a, d, e). Alterations of the basal ER stress level in Sh cells could be responsible for this phenotype. Along this line, we induced acute ER stress response by treating Sc and Sh cells with 250 nM Thapsigargin alone, or in combination with either GSK2606414, a potent and selective inhibitor of PERK, or ISRIB, a PERK-independent stabiliser of eIF2α dephosphorylation. Thapsigargin in Sc cells induced a significant decrease of mitochondrial footprint (Fig. 3b), of the number of branches per network and of the summed branch length (Fig. S3), leading to mitochondrial characteristics very similar to those of Sh cells. As expected, combined treatment with GSK2606414 or ISRIB partially reversed mitochondrial morphology in Sc cells. On the contrary, in
<figure><img src="image_5.png" /></figure>

the absence of Galectin-3, treatment with Thapsigargin
very negligibly altered the mitochondrial footprint and
branching. Moreover, combination with GSK2606414 or
ISRIB had no significant effect compared to Thapsigargin
treatment alone, and did not revert mitochondrial mor-
phology, indicating that mitochondrial fragmentation in

Sh cells is independent of UPR. Hence, the loss of
Galectin-3 silencing may provoke a perturbation of the
mitochondrial dynamics, most probably in relation with
fission/fusion events. Therefore, we analysed the beha-
viour of DRP-1 which is the central modulator of mito-
chondrial fission²⁰. Phosphorylation of Drp-1 at Ser637
<figure><img src="image_6.png" /></figure>
(see figure on previous page)

**Fig. 3** Analysis of the mitochondrial network in pancreatic Sc and Sh cells. **a** Representative images of MitoTracker staining in control Sc (top panel) and Sh (bottom panel). Cells are shown as well as the processed and skeletonised masks from which are extracted mitochondrial characteristics measurement. **b** Total surface of mitochondrial network (footprint, calculated from each measured skeletonised feature in the cell) measured using the MiNA toolset from ImageJ. The macrotool was run in at least three cells isolated from acquired images from three separate experiments. ***p < 0.001 by Mann-Whitney test. GSK GSK2606414, Tg Thapsigargin. **c** Mitochondrial (mito.) extracts were analysed for the expression level of "inactive" phospho Ser637 Drp-1 by western blotting (n = 3). HSP60 was used as a loading marker. The fold change in phospho Drp1 levels was analysed by densitometry. **d, e** Representative images of control Sc (d) and Sh cells (e) immunostained for the mitochondrial marker Tom20 (green) and for "active" phospho Ser616 Drp1 (upper panels, red) or "inactive" phospho Ser637 Drp-1 (lower panels, red) and counterstained with DAPI (blue). White rectangles indicate the location of the corresponding higher magnification (right image of each panel). Scale bars correspond to 20 µm.

prevents its translocation from the cytosol to the mito-
chondria and its fission activity. By contrast, pSer616 Drp-
1 stimulates mitochondrial fission<sup>21</sup>. Here we observed by
immunofluorescence that pSer637 Drp-1 expression was
higher in Sc than Sh cells, a trend further confirmed by
western blotting analysis of mitochondrial extracts (Fig.
3d, e). By contrast, pSer616 Drp-1 was highly expressed in
Sh cells and frequently co-localised with Tom20, a
mitochondrial marker. Total Drp-1 level was also sig-
nificantly increased in Sh cells (Fig. S3b). Altogether, these
data testify a mitochondrial pro-fission phenotype in the
absence of Galectin-3. Moreover, to test mitochondrial
plasticity, we performed live cell imaging and mitochon-
drial motility was assessed by particle-tracking analysis of
Mitotracker-labelled mitochondria in Sc (Movie S2) and
Sh cells (Movie S3). Whatever the parameter used (i.e.
speed or distance), the motility of mitochondria was sig-
nificantly decreased in absence of Galectin-3 (Fig. 4a, b).
Altogether, these results reveal that Galectin-3 influences
the mitochondrial dynamics/homeostasis by inhibiting
the fission process and promoting the motility instead.

To determine whether morphological abnormalities may
impinge on mitochondrial activity, the cell respiration was
studied by oxygraphy using O2k (OROBOROS instru-
ments). Results showed that the activities of mitochondrial
Complex I (NADH dehydrogenase) and Complex IV
(cytochrome C oxydase) were significantly higher in Sh
versus control pancreatic Sc cells (Fig. 5a). The activities of
Complex II and III did not differ between Sh and control Sc
cells. The electron transfer system (ETS) measured after
addition of FCCP, an uncoupling agent, was significantly
higher in Sh than control Sc cells (Fig. 5a). By contrast no
significant difference was observed for Complex V nor ETS
measured in coupled conditions (C ETS). In intestinal cells,
no significant differences in the activities of Complexes I–V
and ETS were observed between H3 and NT control cells,
probably because of the high SD values. However, despite
the versatility of Caco2 cells, Galectin-3 depleted cells
presented a reproducible and significant increase in C ETS
when compared to control cells (p = 0.0169).

Since oxidative phosphorylation (OXPHOS) is the
main contributor to ATP cellular production and occurs
downstream of the glycolysis, we hypothesised that this

<figure><img src="image_7.png" /></figure>

**Fig. 4** Analysis of mitochondria dynamics. **a** Time-lapse images of control Sc and Sh cells where mitochondria were labelled with Mitotracker. The open source imaging software Icy was used to detect (sensitivity: 100; 3 pixels) and track (estimated parameters) more than a hundred spots per image, each representative of isolated mitochondria. Coloured trackers are superimposed on the time-lapse images to illustrate the dynamics of each mitochondria during a 2-min time frame. **b** Speed of mitochondria was calculated for each track according to the total distance travelled by a detected spot and the duration of the frame (n = 3 independent experiments). Data are shown as individual values (black dots) and median (horizontal line). ***p < 0.001, Mann-Whitney test.
<figure><img src="image_8.png" /></figure>

inhibitory effect of Galectin-3 may induce a cellular
metabolic stress. We therefore measured extracellular
lactate levels as a proxy of the glycolytic activity. Lactate
levels were higher in Sc versus Sh pancreatic cells (Fig.
5b, *p* < 0.05), whereas no difference occurred between
Galectin-3-silenced Caco2 cells and parental cells.
However, the ADP/ATP ratio, which is inversely related
to the cell energy status, was not significantly lower in
Sh than control Sc cells. Thus, in the presence of
Galectin-3 the mitochondrial OXPHOS is less efficient
but no metabolic stress is observed. Leakage of electrons
from the mitochondrial electron transport chain results
in the generation of reactive oxygen species (ROS)
mainly at the level of complexes I and III<sup>22</sup>. By flow
cytometric analysis of MitoSOX® Red-stained popula-
tions, we herein showed that the number of cells with
positive mitochondria was not different between Sc and

Sh cells (Figs. 5c and S4). However, there was a higher
percentage of high ROS cells in Sh than in control Sc
cells (44% vs 16.5%, *p* < 0.0001) in agreement with a
higher OXPHOS activity in the mitochondria of
Galectin-3 silenced cells.

To explain these differences in mitochondria dynamics
and bioenergetics, we wondered whether Galectin-3
might affect the expression of components of the
respiratory chain post-transcriptionally. In this respect,
we identified two species of interest among the mRNAs
destabilised by Galectin-3 (Table S1). First, *PDSS2* which
encodes DLP1, a protein involved in the biosynthesis of
coenzyme Q which promotes electron transfer between
complexes II and III<sup>23</sup>, and *GUF1* alias *EF4* which encodes
a protein of the mitochondrial inner membrane important
for complex IV organisation and activity<sup>24</sup>. By western
blotting (Fig. S5), we showed that Galectin-3 did not
influence the expression of DLP1 or GUF1. The same was observed for ISCU, a scaffold protein involved in the assembly of Fe–S cluster found in complexes I, II and III. However, among the interacting partners of Galectin-3 identified by co-immunoprecipitation we did find ICSU, and also other members of mitochondrial complexes such as UQCRC2 (Complex III) or the F0 complex of ATP Synthase (Table S3).

## Gal-3 selectively controls mRNA translation through mTORC1

Since mTORC1 is a global sensor of the cell nutrient status we wondered whether Galectin-3 expression may influence mTORC1 activity due to its negative impact on OXPHOS. Addition of fetal calf serum (FCS), an activator of mTORC1, in serum-starved cells failed to induce S6RP and 4EBP1 phosphorylation in control cells by contrast with Sh cells (Fig. 6a). In agreement, a trend towards higher levels of phosphorylated mTOR at Ser2448 was observed in Sh cells vs control cells but the phospho-mTOR/mTOR ratio was not different between Sh and Sc, probably because a decrease of total mTOR occurred in Sc cells (Figs. 6a and S6). No difference was observed for the AMPK pathway between Sc and Sh cells, in accordance with the absence of metabolic stress reported earlier (Fig. 5b). Thus the presence of Galectin-3 decreases S6RP and 4EBP1 activity in part by reducing mTORC1 activation. Since phosphorylation of both S6RP and 4EBP favours mRNA translation initiation, Galectin-3 inhibitory effect may induce a blockage of mRNA translation in pancreatic cancer cells in usual culture conditions (with FCS). To validate this point, we prepared protein extracts and total RNA simultaneously and measured the protein levels by western blot and mRNA levels by qPCR of four genes representative of the mTORC1 and fatty acid metabolism GO categories whose mRNAs are stabilised by Galectin-3. Whereas *GBE1* and *SLC2A3* mRNA levels were higher in Sc cells than in Sh cells, the corresponding protein levels were unchanged or decreased in Sc versus Sh cells, respectively (Fig. 6b). Similarly, ACOT2 protein levels were decreased in Sc mitochondrial extracts whereas its mRNA levels were similar between Sc and Sh cells. Thus, the differential expression of transcript and protein observed for *GBE1*, *ACOT2* and *SLC2A3* but also for USP14 and XPOT (Fig. 1f) suggests that, in presence of Galectin-3, the translation of a fraction of these 5 mRNAs is blocked (Fig. 6c). A second category of mRNAs is represented by *ETFDH* whose mRNA and protein levels were unaffected by Galectin-3 expression (Fig. 6). In conclusion, Galectin-3 appears to reprogram selectively the translatome of pancreatic cancer cells in basal conditions through the control of S6RP and 4EBP1 activity.

## Gal-3 promotes an early transactivation of ATF6- and Xbp-1s target genes following ER stress induction

In mammalian cells, three canonical ER resident transmembrane proteins (IRE1, PERK and ATF6) act as ER stress sensors and activate three pathways (Fig. 7a). mRNA expression levels of 84 key UPR genes were then monitored by PCR arrays, at baseline (T0) and 1, 4 and 16 h following ER stress induction by treatment with 250 nM Thapsigargin. Levels of 31 mRNAs showed significant variations, among which 26 were significantly increased at early phases of cell response to Thapsigargin treatment whereas 5 were diminished in control Sc cells versus Sh cells respectively (Fig. 7b). Most of these mRNA inductions in Sc cells occurred at steady state (38.5%) or after 1 h of Thapsigargin treatment (61.5%). Based on promoter structure analysis²⁵, the 31 mRNAs which showed differential expression between Sc and Sh cells were classified according to the specific contribution of ATF4, ATF6(N) and Xbp-1s transcription factors for their expression (Fig. 7b). Interestingly, seven mRNAs correspond to ATF6(N)-target genes, three mRNAs to Xbp-1s-target genes, three mRNAs to ATF6(N) and Xbp1-s target genes, whereas only one mRNA corresponds to ATF4-target genes. Next we decided to study the impact of Galectin-3 on the three UPR branches at the protein level. As soon as 1 h of Thapsigargin treatment, the ratio cleaved ATF6/full length AT6 protein was significantly increased in control Sc cells, demonstrating an engagement of the ATF6 arm (Fig. 7c). Hence, we asked whether this could translate into early transactivation of specific ATF6 targets. Indeed, we observed that 1 h after Thapsigargin treatment *ATF6B* and *MBTPS1* mRNA levels (Figs. 7c and S7) were significantly increased in Sc versus Sh cells. Regarding the IRE1 branch (Fig. 7d), Xbp-1s protein expression was increased in control Sc cells as early as 1 h after Thapsigargin addition (*p* < 0.05 versus baseline) whereas in Sh cells activation was delayed. Maximal induction of Xbp-1s occurred at 4 h time course in both cell lines (Figs. 7d and S7). Accordingly, some XBP-1s-dependent targets such as *ERP44*, *EDEM1* (Fig. 7d) or *HERPUD1* (Fig. S7) were also significantly up-regulated in control Sc cells 1 h after Thapsigargin treatment. Finally, concerning the PERK arm (Fig. 7e), phosphorylation of eif2α was delayed in control Sc cells as was ATF4 protein expression. In fact, ATF4 protein levels were significantly higher as early as 1 h after Thapsigargin addition only in Sh cells (*p* < 0.05 versus baseline, Fig. S5). Since *ATF4* mRNA levels did not vary significantly during Thapsigargin treatment, ATF4 protein expression results from a phospho-eif2α-dependent translation reprogramming. Taken together, these data show that Galectin-3 favours an early activation of the ATF6 and IRE/Xbp1s arms of the UPR resulting in an increase of the ER protein folding (*ERP44*, *CALR*) as well as ERAD pathway (*HERPUD1*)
A

<figure><img src="image_9.png" /></figure>

pS6R/S6R (n=2)

<figure><img src="image_10.png" /></figure>

p4EBP1/4EBP1(n=2)

<figure><img src="image_11.png" /></figure>

pAMPK/AMPK (n=2)

<figure><img src="image_12.png" /></figure>

phospho mTORC1 (n=3)

<figure><img src="image_13.png" /></figure>

B

mRNA levels quantification (n=3)

<figure><img src="image_14.png" /></figure>

C

<figure><img src="image_15.png" /><figcaption>**Fig. 6** (See legend on next page.)</figcaption></figure>
(see figure on previous page)

**Fig. 6** Impact of Galectin-3 on mRNA translation in pancreatic cancer cells. **a** Influence of the addition of fetal calf serum (FCS) in serum-starved control Sc cells and galectin-3 deficient Sh cells on the mTORC1 and AMPK pathways. Protein lysates were analysed for indicated proteins by western blotting. Fold change in protein levels was analysed by densitometry and Student's t test. For phospho mTOR, levels are expressed relative to those in Sh cells without FCS which were set at 100%. **b** ETFDH, GBE1, ACOT2 and SLC2A3 mRNA and protein levels were evaluated simultaneously by Q-PCR (n = 3) or western blotting (n ≥ 2) in control Sc or galectin-3 deficient Sh cells. Fold changes are shown on corresponding graphs. **c** Schematics showing classification of mRNAs according to the influence of Galectin-3 on mRNA and protein expression: blocked in mRNA translation (red dots) and unaffected (black dot).

capacities. Moreover, Galectin-3 also delays ATF4 expression during an experimental ER stress. Finally, we studied the influence of Galectin-3 on cell viability during a prolonged Thapsigargin treatment (>16 h). By live and dead assay, we demonstrated that the mortality of control Sc cells was significantly higher than those of Sh cells at 24 and 48 h of the treatment (Fig. 7f).

Discussion

Our data showed that Galectin-3 behaves as a selective post-transcriptional regulator which coordinates the expression of 13 RNA regulons which merge subsets of functionally related mRNAs²⁶. Some RNA regulons con- trol a biological function previously linked to Galectin-3, such as cell death/apoptosis²⁷ or protein secretion²⁸, which strengthens the validity of our experimental approach. Interestingly, other RNA regulons such as fatty acid metabolism, cholesterol homeostasis or UPR were previously rarely or never related to Galectin-3. We thus focused our work on Galectin-3's control of the mito- chondrial bioenergetics and the ER stress response in epithelial cancer cells.

Regarding the mitochondrial function, our data
demonstrated a more efficient OXPHOS in the absence
of Galectin-3, and especially a higher activity of complex
I (NADH oxidase) and complex IV (cytochrome C oxi-
dase) in pancreatic cancer cells. The activity of complex
V (ATP synthase) was increased in the absence of
Galectin-3 but not significantly. How does Galectin-3
affect the activity of the mitochondrial OXPHOS com-
plexes? Despite its ability to inhibit the mTORC1/S6RP-
4EBP1-dependent translation, we did not highlight any
impact of Galectin-3 on the protein levels of key reg-
ulator of OXPHOS such as DLP1²³, GUF1/EF-4²⁴ or
ISCU, a scaffold protein important for the assembly of
Fe-S clusters found in Complexes I, II and III²⁹. Pre-
vious¹⁵ and our immunoprecipitation data demonstrated
however that Galectin-3 interacts with the F1¹⁵ and
F0 subunits of ATP synthase located in the mitochondria
inner membrane and also ICSU, thus suggesting that
Galectin-3 may prevent the assembly of mitochondrial
complexes and finally decreases OXPHOS. An alter-
native hypothesis consists in considering that Galectin-
3's impact on OXPHOS is linked to its regulator role on

the ER-mitochondria communication. Indeed, in normal
and cancer epithelial cells deriving from the digestive
tract, Galectin-3 is localised at the interface between ER
and outer mitochondrial membrane. Moreover we con-
firmed by subcellular fractionation experiment the pre-
sence of Galectin-3 within MAMs, in agreement with
previous proteomic studies conducted on human fibro-
blasts³⁰ or on mouse brain³¹. This is probably not ran-
dom since MAMs are enriched in proteins involved in
mitochondrial function or Ca²⁺ trafficking such as the
calcium channels InsP3Rs at the ER membrane or
VDAC1 on the mitochondria outer membrane³¹,³².
Therefore, the inhibitory effect of Galectin-3 on
OXPHOS may result from its ability to perturb calcium
exchanges at MAMs which are crucial for mitochondrial
bioenergetics³²,³³.

Regarding mitochondrial morphology, we observed pro-
found alterations of the mitchondrial network and
dynamics in absence of Galectin-3 with more fragmented
and round mitochondria. Different mechanisms may par-
ticipate in these changes. First, Galectin-3 localised at
MAM, may prevent the wrapping of the ER around
mitochondria which occurs during the first step of mito-
chondrial fission<sup>2,34</sup>. Accordingly, the “pro-fission”
phospho-Ser616 Drp1 was increased and recruited to the
mitochondria in absence of Galectin-3. Second, the
alterations of the mitochondrial network observed in Sh
cells are reproduced by Thapsigargin treatment of Sc cells.
Thapsigargin, a SERCA inhibitor, is known to induce
mitochondrial fragmentation by increasing mitochondrial
Ca<sup>2+</sup> <sup>35</sup>. By constrat, PERK silencing normalises mito-
chondrial Ca<sup>2+</sup> level and rescues mitochondrial morphol-
ogy<sup>36</sup>. Thus, we proposed that Galectin-3 controls the Ca<sup>2+</sup>
exchanges at MAMs between the ER and mitochondria<sup>37</sup>
and prevents mitochondrial Ca<sup>2+</sup> overload in cancer cells.
This point will require additional investigations.

Considering the ER per se, no significant differences in
the activity of the three arms of the UPR, notably the
PERK /ATF4 branch involved in the control of mito-
chondrial respiration³⁸ occurred between Sc and Sh cells
in basal conditions. Therefore, an involvement of the ER
in the effects of Galectin-3 on mTORC1 or OXPHOS can
be excluded. However, after induction of an acute ER
stress, Galectin-3 favours an early activation of the
<figure><img src="image_16.png" /></figure>
(see figure on previous page)

**Fig. 7 Impact of Galectin-3 on the ER stress response.** a Schematics showing the three branches activated by the accumulation of misfolded proteins in the ER lumen. b Expression levels of 84 genes related to the UPR pathway were analysed by real-time qPCR in control Sc and Sh cells at baseline and 1 h, 4 h and 16 h after addition of Thapsigargin (250 nm) (n = 2 independent experiments). Genes whose mRNA levels were significantly different between control Sc and Sh cells are presented in the graph and classified into four subgroups according to their dependence towards ATF6α (in red), XBP-1s (in purple), ATF6α and or XBP-1s (in orange), ATF4 or XBP-1s (pink), ATF4 (green), ATF6α or ATF4 or XBP1s (light blue). This classification relies on the analysis of promoter cis element structures (ERSE and UPRE) of the UPR-related genes performed elsewhere by Montibeller et al., using JASPAR, REACTOME, and TRUSST databases. Expression level is shown as the Sc cells mRNA levels/Sh cells mRNA levels ratio. The length of the graph bar is related to the level of statistical significance of variation. c ATF6 pathway activation: Variation of full length and cleaved ATF6 proteins (upper panel) during Thapsigargin treatment studied by western blotting (n = 2 independent experiments). Fold change in protein levels was analysed by densitometry (medium panel). Expression level was arbitrarily set at 100% for Sc cells. Data are shown as mean ± SEM and were compared by Student's *t* test. Variation of the mRNA levels of *MBTPS1*, an ATF6-N target gene, was followed by real-time qPCR both at baseline and during Tg treatment (n = 2, lower panel). d. IRE/Xbp-1s activation: variation of XBP-1s protein levels (upper part) by western blotting (n = 3) and variation of the mRNA levels of *EDEM1* and *ERP44* (two XBP1s targets, lower part) was followed by real-time qPCR both at baseline and during Tg treatment (n = 2). e PERK activation: variation of phospho-eIF2α, ATF4 and CHOP proteins levels (upper part) by western blotting (n = 2). f Cell mortality during a long term Thapsigargin treatment was assessed by cell cytometry with the Live and Dead Assay. Data are shown as mean ± SEM of two independent experiments and were compared by Student's *t* test (*p* < 0.05; **p** < 0.01; ***p** < 0.001; ns non significant).

IRE/Xbp-1s and ATF-6 branches of the UPR and delays those of the PERK/ATF4 pathway resulting in an adaptative response. However, when the stress became chronic (>16 h), Galectin-3 triggers cell death, which corresponds to the proper UPR response occurring when the adaptative phase fails.

To summarise, we show that the localisation of Galectin-3 at MAM is accompanied by novel functions for this lectin. At the ER, Galectin-3 promotes an earlier activation of two branches of the UPR which result in an adaptative response to ER stress. Simultaneously, Galectin-3 preserves the mitochondrial network and dynamics independently of the UPR and regulates cell bioenergetics (Fig. 8). Therefore, Galectin-3 appears to act as a coordinator of the ER and mitochondria functioning.

# Materials and methods

## Cell culture

Caco2BBE cells were routinely grown in DMEM 4.5 g/l glucose, 20% foetal bovine serum, 10% penicillin-streptomycin (Gibco, Thermo Fischer Scientific, Waltham, MA). The culture medium was renewed every day. Galectin-3 reduction was carried out by lentiviral delivery of shRNA constructs directed against human *LGALS3* (*shGalectin-3*: TRCN0000029305 5'-CCGGCCCACGCT TCAATGAGAACAACTCG-AGTTCTCATTGAAGCG TGGGTTTTT_3') designed and cloned into the lentiviral pLKO.1 puromycin resistant vector MISSION shRNA lentiviral Transduction particle (Sigma Aldrich). Clone generation was performed in DMEM supplemented with 20% FBS, 10% penicillin/streptomycin and 2 µg/ml puromycin (Invivogen, San Diego, CA) and selected clones were routinely maintained in 1 µg/ml puromycin. Control Caco2 clones (*shNT*) were generated using pLKO.1-puro non-target shRNA control transduction particles SHC016V (5'-CCGGGCGCGATAGCGCTAATAATTT CTCGAGAAATTAT-TAGCGCTATCGCGCTTTTTT-3').

Efficiency and specificity of Galectin-3 reduction was assessed by Western blot (Fig. S1). Control Sc cells and Galectin-3 knock-down cells (Sh1, Sh2 and Sh3) were obtained by stable transfection of human pancreatic cancer cells T3M-4 with pSuper.Retro.puro vectors, as previously described³⁹. The Sh1 cells were used throughout the study (and called Sh thereafter) since they exhibited a high silencing of *LGALS3* (Fig. S1). Sc and Sh cells were routinely grown in RPMI 1640 medium supplemented with 15% of FCS, 2 mM L Glutamine, 1% penicillin-streptomycin and 200 ng/ml puromycin (Gibco). The cells were authenticated by ATCC using STR profiling. For ER stress experiments, cells were treated with 250 nM of Thapsigargin alone, or combined with 250 nM or IRSIB or 250 bM of GSK2606414 for 4 h. concentrations of inhibitors were determined by evaluation their impact of Thapsigargin-induced phosphorylation of eIF2α (not shown). DMSO was used as a control.

## Mice

Wt and Gal-3 null mutant (*Lgals3<sup>-/-</sup>*) mice of the 129/Sv background¹⁰ were housed in EOPS (environment without specific pathogenic organisms) environment and handled in accordance with the French regulation for animal care. Experimental protocol was approved by the ethical committee of the Paris Diderot University (approval #A75-13-17).

## qPCR

Total RNA was extracted using "Nucleospin RNA II" from Macherey Nagel. RNA concentration and purity were determined with Nanodrop. Quantification of Gal-3 targeted mRNAs was carried out by qRT-PCR (relative quantification, Taqman technology) using the 2⁻⁵ΔΔCt method and *GAPDH* as an internal standard. Each sample was run in triplicate. Primers are available in Table S4.
<figure><img src="image_17.png" /><figcaption>**Fig. 8** Schematics recapitulating the different impacts of Galectin 3 expression on mitochondria and ER functioning. At the ER-mitochondria interface, Galectin-3 (i) prevents excessive mitochondrial fission and preserves the shape and dynamics of the mitochondrial network; (ii) modulates OXPHOS activity; (iii) reprograms selectively the mRNA translation via a partial inhibition of the mTORC1 pathway; (iv) favours an adaptive UPR following ER stress induction.</figcaption></figure>

UPR gene analysis was performed with RT2 Profiler PCR Array System (Qiagen, Courtaboeuf, France) which contained 84 genes for the UPR pathway (Cat.# PAHS-089Z). To this purpose cells were treated with thapsigargin (250 nM, Sigma Aldrich, Lyon, France) for 1 h, 4 h and 16 h or with DMSO as control. RNAs were collected and extracted as previously described⁷. Reverse Transcription was carried out with the RT2 First Strand Kit (Qiagen) following the manufacturer's instructions. Quantitative Real-Time PCR was performed on QuantStudio 7 Flex Real-Time PCR System (Life technologies). Standard 2⁻⁰·ΔΔCt method was used for determining changes in gene expression according to genes used as references in the kit. Jaspar reactome is an open-access database for eukaryotic transcription factor binding profiles experimentally defined⁴¹.

## Western blot

Western blot were performed as previously described⁷,³⁹. Membranes were incubated overnight at 4°C with specific antibodies as detailed in (Table S4). The membranes were then incubated with peroxydase-conjugated secondary antibodies (Sigma-Aldrich) and revelation was performed with LAS 4000 (Fujifilm) using the West Pico chemoluminescent substrate (Perbio, Villebon/Yvette, France). Mitochondria extracts were prepared using the Mitochondria Isolation Kit (from Pierce, ThermoFisher, France) according to the manufacturer's instructions.

## OXPHOS

Respirometry experiments were performed at 37 °C in the two glass chambers of an OROBOROS Oxygraph under normoxic conditions. DatLab software (OROBOROS INSTRUMENTS, Innsbruck, Austria) was used for real-time data acquisition and analysis. Experiments were carried out according to a previously published protocol⁴² with some modifications. In brief, cells were seeded onto T75 culture flasks and culture for 7 days to reach ~80% confluence. Cells were trypsinized, washed with PBS and resuspended in mitochondrial respiration medium (MiR05: 110 mM sucrose, 60 mM K⁺-lactobio-nate, 0.5 mM EGTA, 3 mM MgCl₂, 20 mM taurine, 10 mM KH₂PO₄, 20 mM HEPES, 1 g/L BSA fatty acid free and adjusted to pH 7.1 with KOH at 37 °C) to obtain a concentration of 3.0 × 10⁶ cells per mL. Subsequently, basal OXPHOS was measured after adding glutamate (10 mM), pyruvate (10 mM), malate (10 mM) and succinate (10 mM). Complexes I to IV were studied together in three different series whereas complex V was studied isolated in three different series. Uncoupling was performed by stepwise titration of carbonyl cyanide p-trifluoromethoxy phenyl hydrazone (FCCP 1 µM 0.5 µl/0.5 µl steps), followed by CII inhibition (thenoyltrifluoroacetone (TTFA, 50 µM) and then CI inhibition (rotenone, 2.5 µM). CIII was inhibited after addition of sn-glycerol-3-phosphate (10 mM) by antimycin A (2.5 µM) to correct for residual oxygen consumption, followed by N'-N'-tetramethyl-p-phenylenediamine (TMPD, 300 µM)
adding and cyanide potassium (KCN, 2 mM) to
inhibit CIV.

For the study of Complex V, the substrates were introduced at the same concentration as previously. Cell permeabilization was then carried out directly in the chamber by digitonin (8.1 mM, 1 µl/million of cells). Then ADP (2.5 mM) was added to exhibit phosphorylation, followed by CV inhibition (oligomycin, 2.5 µM), uncoupling by FCCP (1 µM 0.5 µl/0.5 µl steps), inhibition by KCN (2 mM) and antimycin A (2,5 µM) to correct for residual consumption. Respiratory flow, Oxygen Consumption Rate (OCR), is expressed as pmol O₂·s⁻¹·10⁻⁶ cells.

ATP and lactate assays

ATP levels in cells were determined by using the ADP/
ATP ratio assay kit (Sigma-Aldrich, MAK135) according
to the manufacturer's protocol. Briefly, Sc and Sh cells
were seeded (5000/well) in a 96-well, flat-bottom, white
plate with clear bottoms (Greiner Cellstar®) and grown in
medium described above for 48 h. Luminescence was read
in a Mithras LB 940 luminometer. All analyses were
performed in triplicate. Cells were seeded onto T25 cul-
ture flasks and culture for 5 days to reach ~80% con-
fluence. Then 0.5 ml of medium was removed from each
culture and deproteinated by adding 0.5 ml of perchloric
acid at 8% v/v, vortexing for 30 s, then placing the mixture
in 4 °C for 5 min, and centrifugating at 4500×g for 10 min.
Accumulation of lactate in the culture medium was
determined using lactate assay kit (Lactate Gen.2 Roche).
To determine lactic acid, 500 µl of the deproteinated
supernate was added to a reaction mixture containing B
reagent (Hydrogen donor: 1,75 mmol/L, ascorbate oxi-
dase: 501 µkat/L) and C reagent (4-Aminoantipyrine:
5 mmol/L, lactate oxidase: 251µkat/L, peroxidase:
401 µkat/L). Formation of lactate was measured by a
Konelab 60 analyzer. Samples were analysed in quad-
ruplicate (Sc/Sh) and triplicate (NT/H3).

Reactive oxygen species

To assess Reactive Oxygen Species (ROS) levels, the
MitoSox Red reagent was used ((Molecular Probes,
Thermo, Illkirch, France). It is selectively captured by
mitochondria, and oxidised by superoxyde anion before
exhibiting a red fluorescence. Cell viability was assessed
using Sytox Blue reageant (Molecular Probes) which
labels cells exhibiting a loss of membrane integrity. Three
independent experiments run in triplicate were per-
formed. Each experiment includes a negative control
(unlabelled cells) and a positive control where cells were
cultured in presence of 100 microM menadione, an
inducer of oxidative stress, during 90 min before sample
preparation. Sample Preparation: After trypsinization,
cells (300,000) were incubated with MitoSox Red reagent

(2.5 microM, 30 min, 37 °C) in cytometry-specific tubes.
Cells were then pelleted by centrifugation (1500 rpm,
5 min), the supernatant was discarded and the cells
washed once in PBS buffer. Then, cells were labelled by
Sytox blue(5 microg/ml) during 10 min at RT in a dark
room. Reaction was stopped by placing the tubes in ice
before being analysed by Cell cytometer on a Becton
Dickinson LSRFortessa X-20 using Kaluza software
(Beckman coulter, Villepinte, France).

Live cell imaging

Sc and Sh cells were grown in µ-slide 8-well dishes (Ibidi) for 24 h before transfection with Gal-3 dsRed construct (king gift of Pr R. Jacob, Marburg<sup>43</sup>) as previously described<sup>44</sup> and adapted to 8-well µ-slides. After 48 h, cells were rinsed with 1X HBSS buffer and then incubated for 30 min at 37 °C in 1X HBSS buffer containing 250 nM MitoTracker™ Green FM (Invitrogen™, Thermo, Illkirch, France). Cells were maintained at 37 °C and 5% CO2 during real-time acquisitions. Ten-minute time-lapse acquisitions were performed using an inverted Yokogawa Spinning Disk confocal microscope with a 100× oil-immersion lens (NA 1.4 with an optical resolution of 164 nm, Zeiss). Images were acquired and processed with ZEN software for further analyses with the open source image processing software Icy. All setups, using similar illumination and recording conditions (detector frequency, gain and laser intensity), were applied to Sc and Sh cell lines.

Immunofluorescence and SIM microscopy

Cells were seeded at 20,000 cells per 8-well Lab-Tek
chamber slides (Nunc) and culture for 72 h. Cells were
then stained using 250 nM Mitotracker Green FM for
30 min at 37 °C. Cells were rinsed in 1X warm PBS with
MgCl2 and CaCl2 and were fixed in 2% paraformaldehyde
in 1X PBS pH 7.4 for 10 min. After permeabilization and
saturation for 20 min respectively with 0.025% saponin
and 0.025% saponin and 1% BSA in 1X PBS, anti-Galec-
tin-3, anti-pSer637-Drp-1 or anti-pSer616Drp-1 anti-
bodies was added at a 1:50 (Galectin-3) or 1:100 final
dilution in 0.025% saponin, 1%BSA, 1X PBS overnight at
4°C. Alexa488-anti-rabbit antibodies (Invitrogen) were
then used as a secondary antibody. Imaging was performed
on a Zeiss LSM 710 confocal microscope (Jena, Germany)
with a ×63 oil-immersion lens (NA 1.4 with an
optical resolution of 164 nm).

3D-Structured Illumination Microscopy (SIM) was
performed on a Zeiss Elyra Microscope coupled to an
optovar 1.6, ×63 objective and a camera EM CCD Andor
SIM. During z-astack acquisitions, 5 rotations were
applied. Deconvoluted structured illumination images
were generated by Zen software, and images were merged
in Image). Triple colocalization was analysed using a
Matlab-based custom program. Briefly, fluorescence was first segmented in each channel using local thresholding (Phansalkar method<sup>45</sup>), and a local 2-D median filter with user-defined neighbourhood size was applied to remove noise. Colocalization was then measured using the Manders split coefficients M1 and M2<sup>46</sup>

as such:
$$M1 = \frac{\sum S1_{i, coloc}}{\sum S1_i} \text{ and } 2 = \frac{\sum S2_{j, coloc}}{\sum S2_j}, \text{ where } S1_{i, coloc} = S1_i \text{ if } S1_i > 0 \text{ and } S2_i > 0, \text{ and } S2_{j, coloc} = S2_j \text{ if } S2_j > 0 \text{ and } S1_j > 0.$$

The Matlab Code or the standalone user interface can be shared upon request.

## Electronic microscopy

1 mm sections of wt or *Lgals3*<sup>-/-</sup> mouse jejunum were fixed in 2.5% glutaraldehyde (Electron Microscopy Sciences (EMS), Hatfield, PA, USA) in 0.1 M cacodylate buffer (pH 7.4) (Sigma-Aldrich) for 2 h at 4 °C and then in 1% osmic acid (EMS) in 0.1 M cacodylate buffer for 1 h. Standard procedures for dehydration and embedding in Epon-Araldite (EMS) were used. Ultrathin sections were stained with uranyl acetate and lead citrate (Sigma-Aldrich) solutions before examination using a Tecnai T12 microscope (FEI, Eindhoven, Netherlands). Cells were fixed with 1 % glutaraldehyde in 0.1 M sodium cacodylate pH 7.2 overnight at 4 °C. They were post-fixed with 1% osmium tetroxide reduced with 1.5% potassium hexacyanoferrate (III) for 1.5 hours then with 1 % uranyl acetate for 45 min, both in distilled water at room temperature in the dark. After washing, tissues were dehydrated in graded ethanol solutions, infiltrated with epoxy resin and cured at 60 °C for 24 h. Sections of 70–80 nm thickness on formvar-coated grids were observed with a Tecnai T12 microscope (FEI, Eindhoven, Netherlands).

For the analysis of Galectin-3 distribution at the ultrastructural level, immunogold pre-embedding was performed. Human enterocytes Caco2 cells were fixed 3 h in 3% PFA, 0.04% glutaraldehyde, 0.04 M cacodylate buffer, pH7.4 and then permeabilized in 0.025% saponin solution. After 30 min incubation in solution A (i.e. 0.1% Tween20, 1% serum albumin, 0.45% gelatin and 0.4% glycin), the primary antibody rat monoclonal anti-Galectin-3 was incubated overnight at 4 °C at dilution 1/300 in solution A. Rat monoclonal antibody directed Galectin-3 was a gift of Hakon Leffler (Lund University, Sweden). After washes in 0.1% Tween20, PBS, the secondary antibody, 10 nm immunogold-conjugated goat anti-rat (British Biocell International) diluted 1/300 in solution A, was incubated 1 h. After washes in 0.1% Tween20, PBS, post-fixation was performed with 1 h incubation in 1.2% glutaraldhehyde, 0.1 M cacodylate pH7.4 and 5% sucrose. After washes in 50 mM glycin, PBS, then in 1% serum albumin, PBS, and then filtered H2O, signal enhancement was performed with the Gold Enhance EM Plus kit (Nanoprobes, NY).

Cells were then post-fixed with 1 h incubation in 2% osmium tetroxide, 2% potassium ferrocyanide, 0.1 M cacodylate pH7.4. Afterwards, standard procedures for dehydration and embedding in Epon-Araldite (EMS) were used. Ultrathin sections were stained with uranyl acetate and lead citrate (Sigma-Aldrich) solutions before examination using a Tecnai T12 microscope (FEI, Eindhoven, Netherlands).

## Whole transcriptome stability

Total RNA was extracted from Sh1 and Sc cells cultured in the presence of 8 µg/ml actinomycin D for 0, 3, 6, 9, 12, 24 and 30 h. A TruSeq Stranded mRNA Sample Preparation Kit (Illumina Inc., SanDiego, California) was used to construct cDNA libraries according to the manufacturer's instructions with a fragmentation time of 2 min at 94 °C. The individual libraries were multiplexed (2pools, 7 libraries/pool) and sequenced on HiSeq2500 Illumina sequencer using a High Output paired end 2×75 bp run (UMR CNRS 8199 platform, Lille). qPCR quantification and QuBit control of the pool was done before cBot clusterization. Minimal number of reads per sample was 114 × 10<sup>6</sup>. RNA-Seq reads were aligned to hg19 reference genome using Tophat v2.0.12<sup>47</sup>. Cufflinks v2.2.1 was used to assemble transcripts and derive as Fragments Per Kilobase of exon model per Million mapped reads (FPKM) values with the ucsc hg19 transcriptome as a reference<sup>48,49</sup>. Expression data among time points were normalised by the geometric mean of several stable transcripts: *RPLP0* (NM_001002), *PGK1* (NM_000291) and *TRAP1* (NM_016292) (Fig. S8). FPKM normalisation, decay model assessment and calculation of mRNA half-lives were conducted according to the protocol described in Imamachi et al.<sup>50</sup>. Statistical analyses throughout this study were performed with statistical program R<sup>51</sup>. To identify the Gene Ontology (GO) terms enriched in our mRNA data set we used the GSEA computational method<sup>50</sup> and two reference gene sets (Hallmark and GO cellular component) from the Molecular Signatures Data base (MSigDB)<sup>52</sup>. For the UPR category, GSEA analysis was also performed using AmiGO, an official web-based open-source tool for querying, browsing, and visualising the Gene Ontology and annotations as described by Monoz-Torres<sup>53,54</sup>. RNA Seq data have been deposited in the Sequence Read Archive of the NCBI (accession number: PRJNA552473).

## Immunoprecipitation and mass spectrometry analysis

The identification of the Galectin-3 binding proteins was performed as previously described<sup>10</sup>. Briefly, cell extracts were precleared by incubation with Protein-A Sepharose beads (Sigma-Aldrich), and then rat monoclonal anti-Galectin-3 antibody was applied. Immunoprecipitation of EpCAM and incubation of Protein-A
coated beads alone served as controls. Immunocomplexes
were recovered by addition of Protein-A/Sepharose beads
overnight at 4 °C, followed by three washes in PBS. To
identify the co-immunoprecipitated proteins, beads were
submitted to proteolytic digestion and the peptides were
analysed by mass spectrometry (ESI-LTQ-Orbitrap spec-
trometer) coupled with nanoLC chromatographic
separation system (Proxeon) in the IJM Proteomic facility
(Institut Jacques Monod, Paris, Fr).

MAM isolation

MAM were isolated from pancreatic Sc and Caco2 cells
as previously described⁵⁵. 30 µg of proteins of each frac-
tion were analysed by western blotting. SEL1L was used as
a marker of the ER, FAC4L as a marker of MAM and
Tom20 as a mitochondrial protein.

Cell viability

Cells were treated with 250 nM of thapsigargin or DMSO as a control for 24 or 48 h. Mortality and viability was assessed by flow cytometry using the Live and Dead assay (Thermofisher, USA) according to the manufacturer instructions.

Statistical analyses

For each kind of experiment (WB, qPCR and enzymatic
complex activities) n = 3 biological replicates were carried
unless otherwise mentioned in the text. All statistical
analyses were performed with the GraphPad Prism soft-
ware version 6.05. Data are expressed as mean ± SEM
unless otherwise mentioned. Data between 2 groups
were compared using Student's t-test with Welch cor-
rection. Multiple data sets were compared by one-way
ANOVA. Frequencies were compared using the Khi2 test.
Differences were considered significant if *p* values ≤0.05.
*p* < 0.05, **p** < 0.01, ***p** < 0.001 and NS is non significant.

Acknowledgements

We thank Drs O. Pluquet, F. Zerimech, J. Kluza for helpful discussions, Ms M-P. Ducourouble for laboratory management, Rémi Le Borgne (ImagoSeine) for cell monolayer sample preparation for TEM, Nathalie Jouy and Véronique Dhennin for facility access. High-resolution 3D-SIM was performed in the ImagoSeine microscopy facility (Institut Jacques Monod, IJM, Paris). Mass spectrometry analyses were carried out at the Proteomic facility of the IJM (Paris). This work was supported by academic fundings from Inserm, Université de Lille, CHU de Lille and by the Ligue Nationale contre le Cancer, comité de la Somme (grant to PP) and comité du Nord (grant to IVS); by grants from "Initiatives d'excellence" (Idex ANR-11-IDEX-0005-02) - Labex « Who Am I? » (ANR-11-LABX-0071) (to D.D.), the Groupama Foundation – Research Prize for Rare Diseases (to D.D.), the Human Frontier Science Program (RGP0038/2018), from Contrat de Plan Etat Région (CPER Cancer 2007-2013 (to I.v.S.)). The UMR CNRS 8199 platform, (Lille, France) which belongs to the 'Federation de Recherche' 3508 Labex EGID (European Genomics Institute for Diabetes; ANR-10-LABX-46) was supported by the ANR Equipex 2010 session (ANR-10-EQPX-07-01; 'LIGAN-PM').

Author details

**Conflict of interest**

The authors declare that they have no conflict of interest.

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**Supplementary Information** accompanies this paper at (https://doi.org/
10.1038/s41419-020-2556-3).

Received: 25 November 2019 Revised: 24 April 2020 Accepted: 24 April 2020

Published online: 12 May 2020

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<footnote n="1">¹University of Lille, CNRS, Inserm, CHU Lille, UMR9020 – UMR-S 1277 – Canther – Cancer Heterogeneity, Plasticity and Resistance to Therapies, F-59000 Lille,</footnote>

<footnote>France. ²CHU Lille, Institut de Biochimie & Biologie Moléculaire, Centre de Biologie et Pathologie, F-59000 Lille, France. ³CHU Lille, Institut de Génétique, Centre de Biologie et Pathologie, F-59000 Lille, France. ⁴University of Lille, CHU Lille, Plate-forme de génomique fonctionnelle, Centre de Biologie et Pathologie, F-59000 Lille, France. ⁵University of Lille, F-59000 Lille, France. ⁶Equipe Cell adhesion and mechanics, Institut Jacques Monod - UMR 7592 CNRS - Université Paris Diderot, F-75205 Paris Cedex 13, France. ⁷University of Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, U1019 - UMR 8204 - CIIL - Center for Infection and Immunity of Lille, F-59000 Lille, France. ⁸University of Lille, CNRS, CHU Lille, Institut Pasteur de Lille, UMR 8199, EGID, F-59000 Lille, France</footnote>
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