# Controlling lipid droplet dynamics via tether condensates

Chems Amari, Damien Simon, Emma Pasquier, Theodore Bellon, Marie-Aude Plamont, Sylvie Souquere, Gérard Pierron, Juliette Salvaing, Abdou Rachid Thiam, Zoher Gueroui

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Chems Amari, Damien Simon, Emma Pasquier, Theodore Bellon, Marie-Aude Plamont, et al. Controlling lipid droplet dynamics via tether condensates. Nature Chemical Biology, 2025, 21, pp.1589-1598. 10.1038/s41589-025-01915-2. hal-04786501

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Controlling lipid droplet dynamics via tether condensates

Chems Amari¹,², Damien Simon¹, ⁵, Emma Pasquier¹, Theodore Bellon¹, Marie-Aude
Plamont¹, Sylvie Souquere³, Gérard Pierron⁴, Juliette Salvaing², Abdou Rachid Thiam⁵,*,
Zoher Gueroui¹,*

¹ CPCV, Department of Chemistry, ENS, PSL University, Sorbonne Université, CNRS. Paris.
France

² LPCV, Université Grenoble-Alpes, CEA, CNRS, INRAE, Grenoble, France

³AMMICA UMS-3655, Institut Gustave Roussy, Université Paris-Saclay, Villejuif, France.

⁴ CNRS UMR-9196, Institut Gustave Roussy, Villejuif, France.

⁵ Department of Physics, ENS, PSL University, Sorbonne Université, CNRS. Université Paris Cité, Paris, France

* Corresponding authors

Corresponding authors

thiam@phys.ens.fr

zoher.gueroui@ens.psl.eu
**Abstract**

Lipid droplets (LDs) are dynamic cellular organelles that regulate lipid metabolism and various cellular processes. Their functionality relies on a dynamic proteome and precise spatiotemporal interactions with other organelles, making LD biology highly complex. Tools that enable the sequestration and release of LDs within their intracellular environment could synchronize their behavior, providing deeper insights into their functions. To address this need, we developed ControLD (Controlled Trapping of Lipid Droplets), a novel method for manipulating LD dynamics. This approach utilizes engineered condensates to reversibly sequester LDs, temporarily halting their activity. Upon release, the LDs resume their normal functions. ControLD effectively disrupts LD remobilization during metabolic demands and prevents the formation of LD-mitochondria contact sites, which are re-established upon condensate dissociation. ControLD represents a powerful tool for advancing the study of LD biology and opens avenues for investigating and manipulating other cellular organelles.
**Introduction**

Lipid droplets (LDs) are unique organelles at the nexus of cellular lipid metabolism. They consist of a neutral lipid core (mainly triacylglycerol, TG, and cholesterol ester) covered by a lipid monolayer embedded with proteins¹. They play significant roles in diverse biological functions, primarily to balance cellular energy fluxes: storing excess energy and delivering lipids during scar cities for making membranes or generating ATP²,³. In humans, dysregulation of LD formation and dynamics is related to several metabolic diseases linked to obesity, such as type II diabetes, liver or cardiac diseases, or lipodystrophies and neuronal disorders²,⁴. LDs interact with nearly all other cell organelles to perform their biological processes, e.g., the endoplasmic reticulum (ER), mitochondria, autophagosomes, lysosomes, or peroxisomes, for anabolic or catabolic processes⁵,⁶. For instance, during metabolic shifts towards energy expenditure, LDs recruit at their surface enzymes such as lipases, e.g., ATGL and HSL, for lipid breakdown and use microtubules to associate with mitochondria, to which they deliver the fatty acid products for β-oxidation⁷. This exemplifies the importance of LD communication with organelles to fulfill cellular needs ⁸,⁹.

LD dynamics and functions are partially regulated by proteins recruited to the LD surface¹⁰,¹¹. Most of these proteins come either from the cytosol, often associating with LDs by amphipathic helices, or from the ER membrane, associating with LDs with monotopic domains¹⁰,¹¹. How LDs form and how proteins control their dynamics and function have been studied from cell biology, *in vitro* reconstitution experiments, or biochemically perspectives ¹²,¹³ ¹⁴, identifying key steps leading to LD nucleation, growth, and maturation¹⁵ ¹⁶⁻¹⁹. Yet, how LD biogenesis and functions are spatiotemporally controlled to coordinate response to metabolic fluctuations remains poorly understood²⁰.

Developing methodologies to probe and perturb LDs directly in cells could be instrumental in answering these questions²¹. To achieve this goal, we devised a strategy to create intracellular compartments programmed to selectively confine LDs, capitalizing on our ability to create biomolecular assemblies. This approach could enable the physical sequestration of selected intracellular structures, potentially allowing for modifying their biological functions. Our method, termed ControLD (Controlled Trapping of LDs), focuses on targeting and confining LDs in cells in a controllable and reversible manner. ControLD employs engineered condensates as artificial compartments designed to target specifically LDs to reorganize and sequester them in cells.

ControLD is based on the design of a chimeric protein scaffold, composed of a part that is prone to phase-separate in cells and a second one, composed of an LD targeting protein, e.g., here, validated for Perilipin2 (Plin2). When produced in cells, our scaffolds eventually condensed at the surface of LDs to form micrometric condensates entrapping all LDs. These LD-containing condensates displayed the hallmarks of phase-separated condensates, including localized nucleation, growth, and coalescence of the condensed phases. Furthermore, we could trigger the release of LDs within a minute-time scale, by dissociating the condensates. LD-condensates robustly formed with 3 different LD-associated proteins, Plin1, Plin 2, Plin3, indicating that the LD-anchoring proteins could be used for a broad range of protein-LD affinities. LDs entrapped within condensates had their activity temporarily paused, which resumed upon release from confinement. This reversible process disrupted LD remobilization
during metabolic demands and prevented LD-mitochondria contact sites, which re-established
after the LDs were released.

## Results

### An engineered condensate designed to bind to lipid droplets

To promote the interactions between LDs and engineered condensates, we developed a protein scaffold with two specific properties: the ability to undergo phase separation in the cytoplasm and the capability to interact with the surface of LDs (Fig. 1a). We selected a protein scaffold (hereafter called 5Fm) consisting of five consecutive repeats of FKBP12-F36M, a protein domain able to form weak and specific homodimers. Due to its self-interacting multivalency, this scaffold undergoes a concentration-dependent phase separation, forming liquid-like condensates in cells. Furthermore, the condensates that can be reversibly dissociated by the small molecule FK506<sup>22,23</sup>. As the LD protein targeting component, we opted for Perilipin2 (Plin2), a member of the perilipin family known to target LD surface in most human cells<sup>24,25</sup>. As anticipated, the expression of 5Fm scaffolds lacking the LD surface protein (Plin2) for 24 hours in HeLa cells resulted in micrometric mCherry condensates scattered throughout the cytoplasm (Fig. 1b). These condensates did not interact with emGFP-Plin2 coated LDs and stained with LipidTOX, indicating the absence of non-specific interactions between Plin2-coated LDs and the 5Fm-based condensates (Fig. 1b). In contrast, when 5Fm-emGFP-Plin2 was co-expressed with mCherry-5Fm for 24 hours in cells, it led to the formation of large structures comprising LDs embedded within condensates (Fig. 1c-d). Typically, we observed approximately 2 to 6 large compartments per cell with a diameter of about 2-6 µm, encompassing tens of LDs (Fig. 1e). Nearly all LDs present in the HeLa cells were consistently trapped within the condensates (Fig. 1e). On closer examination, we observed that the 3D condensed phase typically separates individual LDs from each other (Extended Fig. 1a-b). A second pattern of LD organization was observed when the stoichiometry of co-transfected emGFP-5Fm-Plin2/5Fm plasmids was increased from 1:20 to 1:4, i.e., an increase in the levels of emGFP-5Fm-Plin2 quantity. Under these conditions, LDs were predominantly densely packed in a beads-on-a-string arrangement (Fig. 1g). While 5Fm-emGFP-Plin2 scaffolds were homogeneously localized around LDs, the mCherry-5Fm signal was enriched at the contacts between adjacent LDs, potentially forming optically unresolved condensates (Extended Fig. 1c-e).

Overall, our data demonstrate that bioengineered condensates designed to target the LD surface can trap and confine LDs.

### LD surface triggers localized condensate formation

Next, we conducted live imaging to determine the timing and location of condensate formation within the intracellular space. At early stages of protein expression, the 5Fm-emGFP-Plin2 signal localized at the surface of LDs, suggesting a 2D anchoring mechanism (Fig. 2a, S. Mov1). Subsequently, the mCherry-5Fm signal was recruited to the LD surface through Fm intermolecular interactions (Fig. 2a, S. Mov1). The condensates eventually
nucleated on the LD surface for both 5Fm-emGFP-Plin2 and mCherry-5Fm scaffolds, indicating that LD surfaces played a role in seeding their nucleation. These LD-nucleated condensates tended to coalesce into larger structures (Fig. 2b), as commonly observed with classical liquid condensates. The typical time scale for the relaxation towards spherical bodies was approximately 30 minutes for a 5 µm-sized LD-condensate. Furthermore, we noted that LDs, initially in contact, moved apart during condensate growth (Fig. 2a, S. Mov1). Fluorescence recovery after photobleaching (FRAP) revealed distinct dynamic properties of Plin2 within condensates depending on their localization. Specifically, approximately 60 % of Plin2 within 3D condensate phase exhibited dynamic reorganization, occurring on a timescale of about one minute, while most Plin2 proteins were static when they were located at the LD surface (Fig. 2c).

Simultaneously with the initiation of LD-condensate formation, we observed a strong slow-down of the increase of the cytosolic fluorescence intensity, regarding both emGFP-5Fm-Plin2 and mCherry-5Fm. In contrast, the total cytoplasmic fluorescence intensity (cytosolic + condensates) kept increasing at a regular rate (Fig. 2d left, S2). This suggests that the nucleation of LD-condensates occurs when a critical concentration of freely diffusing scaffolds is reached, driven by both homotypic and heterotypic interactions, with heterotypic interactions making a smaller but still significant contribution in determining the condensate location, i.e., around LDs. Overall, these results imply a sequential process in which the initial formation of a 2D scaffold layer takes place on the LD surface (as depicted in Fig. 2a), followed by the localized nucleation, growth, and coarsening of condensates, ultimately leading to the entrapment of LDs.

We next assessed whether the condensates could be disassembled by treating cells with FK506 (2.5 µM). This competitive binder disrupts Fm-Fm interactions (Fig. 3a). Upon addition of FK506, we observed the rapid dissociation of the condensates, followed by the release of LDs, allowing them to move freely within the cytosol (Fig. 3b, S.Mov. 2). This demonstrates the potential for targeted manipulation, entrapment, and synchronous release of LDs, thereby expanding the range of possibilities for druggable applications.

## The Plin binding affinity to LDs impacts LD-condensates

Plin2 belongs to the perilipin family of LD-associated proteins, known for their role in stabilizing LDs and regulating their surface accessibility²⁶. To investigate the possibility of entrapping LDs using engineered condensates targeting alternative LD surface proteins, we focused on Plin 1 and Plin 3, which interact with stronger and weaker affinities, respectively, than Plin 2 to the LD surface (Extended Fig. 3a-b)²⁷,²⁸. When co-expressing 5Fm-emGFP-Plin1 with mCherry-5Fm, we observed LD-condensates that exhibited a similar pattern to those observed for Plin2-LD-condensates (Fig. 4a). Specifically, LDs were embedded within condensates composed of 5Fm-emGFP-Plin1 and mCherry-5Fm. Plin3-condensates were equally observed but only when we used a larger concentration of 5Fm-emGFP-Plin3 scaffolds (Fig. 4b). Together, these findings indicate the robust formation of LD-condensates with different LD-associated proteins characterized by distinct protein-LD affinities.
## LD surface binding competition affects condensate formation

Since LD proteome is regulated by protein binding competitions occurring at the LD monolayer surface²⁹, we probed the impact of protein competition on condensate formation. Knowing that Plin1 exhibits a stronger affinity with LDs than Plin2²⁷,²⁸, we assessed the effect of such competition on LD-condensate formation by co-transfecting Plin2 condensate scaffolds (5Fm-mCherry-Plin2 and 5Fm) with emGFP-Plin1. Whereas emGFP-Plin1 strongly labeled LD surface as expected, Plin2-condensates were devoid of LDs (Fig. 4d). This behavior was also observed when co-transfecting Plin3 condensate scaffolds with mCherry-Plin2, for which we found that mCherry-Plin2 were labeling all LDs and Plin3-condensates formed without trapping any LDs (Fig. 4e). The saturation of the LD surface with a higher-affinity protein could prevent the targeting of LD-functionalized LLPS scaffolds and consequently the entrapping of LDs. Therefore, the over-expression of Plin1 of stronger affinity, which binds preferentially to the LD surface, resulted in the formation of condensates of Plin3 condensates of weaker affinities devoid of LDs.

Next, we assessed the impact of the condensates' properties depending on the Plin type. First, we noticed differences in the proteins' enrichment at the LD surface and within the condensates. We observed a 10-fold difference in the intensity ratio of Plin proteins at the LD surface compared to within the condensates between Plin1 and Plin3 (Fig. 4c). Interestingly, this result aligns with the previously reported 10-fold difference in LD affinity between for Plin1 and Plin3³². The intensity ratio for Plin2 showed an intermediate distribution, consistent with its intermediate affinity for the LD surface. This trend was further confirmed using FRAP, with Plin1 exhibiting weak and slow fluorescence recovery, consistent with its strong binding to the LD surface (Extended Fig. 4a). In contrast, Plin3 recovered approximately 80% of its fluorescence within 20 seconds, reflecting its strong enrichment in the condensed phase and low affinity for the LD surface (Extended Fig. 4b). Plin2 showed an intermediate behavior, with roughly 50% fluorescence recovering within one to two minutes (Fig. 2c).

## Condensates halt lipid fluxes across LDs

Condensates physically isolated LDs, prompting us to investigate whether this isolation could block or modulate LD functions. To assess this, we examined the ability of sequestered LDs to store and exchange lipids by tracking lipid flux into LDs. This was achieved by visualizing the localization of the fluorescently labelled fatty acid BODIPY-C12 supplied with oleate. Without LD-confinement in condensates, all LDs were BODIPY-positive, following the fatty acid supply, indicating their ability to store newly synthesized lipids (Extended Fig. 5a). In contrast, when we added the fatty acids to the cells for a limited time before the condensate formation (during 4 hours post-transfection), the formed condensates contained two distinct but coexisting populations of LDs (Fig. 5a). BODIPY-labeled LD population was primarily located at the condensate center, and an unstained LD population was positioned at the condensate periphery (Fig. 5a, 5c). This suggests that LDs that incorporated BODIPY-C12 fatty acids are trapped within the condensates and that their fatty acid content is no longer available for exchanges. By contrast, LDs at the periphery were probably newly synthetized LDs produced when BODIPY-C12 was no longer available. We interpreted this phenotype as an LD age marking phenotype whereby the BODIPY-C12-positive LDs were made first and trapped before the second wave of unstained LDs were made. In agreement with this
interpretation, when we supplemented the BODIPY-C12 after condensate formation, the newly
formed BODIPY-C12 LDs were primarily found at the periphery of the condensates (Fig. 5b,
5c, and S5b). This data suggests that the centrally located LDs originated from pre-existing
LDs, while the peripheral LDs formed de novo after condensate formation (Fig. 5d).

The spatial separation of lipid droplets (LDs) within condensates remained stable over
several hours, likely due to the viscosity of the condensates, which restricts LD diffusion and
interactions. The absence of labeled fatty acid transfer to unlabeled LDs indicates that
condensates act as physical barriers, limiting lipid exchange. In contrast, when LDs were
released by dissociating the condensates with FK506, all LDs became BODIPY-positive after
24 hours (Extended Fig. 5c). Together, these data provide evidence of our ability to temporarily
pause and resume LD dynamics through condensate dissolution.

LD confinement shields LDs during energy remobilization

Our data suggest that LDs embedded within condensates are physically isolated from
the rest of the cell, disrupting their life cycle and dynamics, and potentially jeopardizing their
capacity to supply fatty acids and be an energy source during nutrient fluctuations. To
investigate this possibility, we studied the consumption of LDs, confined or not within Plin2-
LD condensates, during cell starvation. The induction of starvation was achieved by switching
the cell culture medium to a nutrient-low culture Earle's Balanced Salt Solution medium
(EBSS). As expected, we observed that unconfined LDs, detected using LipidTOX, were
entirely consumed when cells were placed in the nutrient-deprived media for 24 hours, in
contrast to cells placed in complete medium, as shown by Plin2-coated signals (Fig. 5e). Most
interestingly, we observed a large number of LDs within condensates in the starved cells,
indicating that they were protected from consumption by the confinement (Fig. 5f). To analyze
the effect further, we quantified the total number of LDs in cells in an unconfined or confined
situation, i.e., either expressing non-functionalized condensates or LD-condensates, both with
and without starvation induction (Fig. 5 e-f). Following starvation, we found a 7-fold decrease
in the mean of LD numbers in cells when LDs were unconfined. In comparison, this decrease
was only about 1.2 folds for the cells containing LD-condensates. Plin1- and Plin3-LDs
condensates were also found to protect LDs from consumption during starvation (Extended
Fig. 5d). Altogether, this reveals that condensates protect LDs from being consumed during
cell starvation, most probably due to a restriction of LD surface accessibility.

Reversible disruption of LD-mitochondria contact sites

LD-mitochondria contact sites are hubs of cellular lipid metabolism, prompting us to
investigate how ControLD can modulate these interactions. We used the human hepatocyte-
derived HuH7 cell model, which is suitable for studying inter-organelle communication. We
first confirmed that LD-condensates form in HuH7 cells, exhibiting the same canonical
morphologies observed in HeLa cells, thereby demonstrating the robustness of ControLD
(Extended Fig. 6). Mitochondria, stained with MitoTracker DeepRed, and LDs were imaged in
cells expressing both unfunctionalized and Plin-functionalized condensates. To analyze their
proximity, we employed an automated image analysis pipeline based on organelle
segmentation to quantify co-localization from spinning-disk microscopy acquisitions;
moreover, we used electron microscopy to visualize contact sites.
Without LD confinement, co-localization between mitochondria and Plin1-coated LDs was more frequent compared to Plin2-LDs (Fig. 6a and 6g). Ultrastructural characterization using electron microscopy revealed that Plin1-coated LDs were indeed often in close contact with mitochondria, while non-interacting with non-functionalized condensates (Fig. 6b). Strikingly, upon Plin1-LD confinement, we observed that mitochondrial structures were largely excluded from LDs (Fig. 6c-d) and spinning-disk microscopy analysis revealed that LD-mitochondria co-localization decreased approximately threefold (Fig. 6g). Electron microscopy further confirmed the exclusion of mitochondria from Plin1-LD condensates, with the majority of entrapped LDs showing no contact with mitochondria (Fig. 6d). These findings suggest that condensates effectively prevented the formation of LD-mitochondria contact sites. Similar disruptions were observed with Plin2-LD condensates, although to a lesser extent (Fig. 6e, f, g).

To determine whether the disrupted contacts could re-form, we monitored LD-mitochondria co-localization after dissociating the condensates. Remarkably, the co-localization percentage was restored, demonstrating the dynamic reassembly of LD-mitochondria contact sites (Fig. 6g).

Next, we examined changes in LD-mitochondria contacts during nutrient deprivation, when fatty acids are transferred from LDs to mitochondria for β-oxidation. We found that Plin1-mediated LD confinement prevented the formation of LD-mitochondria contact sites (Fig. 6h), similar to what was observed in complete media. These findings indicate that condensates effectively shield LDs from mitochondria even during acute starvation, as confirmed by electron microscopy (Extended Fig. 7). Similarly, LD-mitochondria contact sites were inhibited by Plin2 condensates (Fig. 6h). Finally, we observed the re-establishment of LD-mitochondria contacts upon the release of LDs from condensates under nutrient-deprived conditions (Fig. 6h).

These findings collectively suggest that tethering condensates effectively prevent LD-mitochondria interactions, and that these contacts can re-form upon condensate dissociation, highlighting the dynamic and plasticity of these interactions.

## Discussion

We developed ControLD, a versatile method to trap and confine LDs within engineered condensates. To demonstrate its effectiveness, ControLD was tested using Perilipin-functionalized phase-separating scaffolds. These scaffolds specifically target the surface of LDs, nucleating a condensed protein meshwork that effectively isolates LDs from the surrounding intracellular environment. Importantly, the trapping of LDs is reversible, as they can be synchronously released within a minute by triggering the disassembly of the condensates. Remarkably, ControLD enables temporary arrest of LD dynamics and restoration of their activity upon release. We demonstrated that physically isolating LDs from the cytosol protects them from consumption during metabolic demands. Additionally, condensate formation significantly reduces LD-mitochondria contacts across the 3 assessed Perilipin types, with Plin1-based condensates having the greatest impact, probably due to the implication of Plin1 safeguarding the surface of LDs and controlling metabolic process. Notably, LD-mitochondria contact sites reform upon condensate disassembly, highlighting the dynamic and
reversible nature of this approach. Thus, our tool provides temporal control over LD dynamics, offering a powerful approach to studying LD biology.

The life cycle and dynamics of LDs are central to the metabolic roles they play, and such processes are tightly linked to specific biochemical mechanisms occurring at LDs' surface and LD-organelle contact sites. How does entrapping LDs within condensates result in arresting such LD dynamics? We could envision distinct but not exclusive mechanisms. Firstly, condensates may act as a diffusion barrier, preventing enzymes such as lipases from targeting the LD surface. Secondly, the condensate physical barrier could limit the initiation of the degradation machinery of LDs, e.g. mediated by lipophagy³⁰. Thirdly, contact sites between LDs and other organelles could be strongly perturbed, leading to altered communication between organelles. This perturbation of LD dynamics is, indeed, in agreement with the loss of LD-mitochondria contacts upon condensate entrapping (Fig. 6).

All these mechanisms could play collectively, enabling ControLD to manipulate LD metabolism and interactions with organelles reversibly.

Beyond its technical characteristics, ControLD opens up avenues for exploring the significance of condensates in regulating LD biology. While mounting evidence shows an interplay between membrane-bound organelles, e.g., ER, Golgi, plasma membrane, mitochondria, and condensates, no conclusive evidence exists that LDs might interact with condensates. Only Cidec, mediating LD-LD material transfer, has been recently suggested to undergo 2D phase separation, leading to the formation of a 2D plate between LDs³¹. Yet, a description of the interplay between LD dynamics and protein phase separation could provide a fresh perspective on regulatory mechanisms to tune the LD life cycle. Our characterization offers a novel framework describing the interplay between LD dynamics and protein phase separation.

In our study, we found that the nucleation of condensates occurred on LDs by a step-wise formation process with the recruitment of LLPS scaffolds at the LD surface, followed by their localized condensation (Fig. 2, S. Mov1). LD surface provides numerous anchoring sites for disordered motifs such as amphipathic helices³². Therefore, LDs may favorably recruit LLPS scaffolds and restrict their mobility on 2D compared to free diffusing in the cytosol. This restriction in scaffold diffusion could reduce the concentration threshold for condensation, as proposed for the regulation of phase-separated condensates by membranes³³. As LD phospholipid monolayers show more packing voids than bilayer membranes³⁴, it is perfectly plausible that the LD surface facilitates more LLPS nucleation events.

Our observations of condensate nucleation triggered at the LD surface are also consistent with *in vitro* experiments using the histidine-modified FUS low complexity domain interacting with NTA(Ni)-phospholipids³⁵. In our system, the mechanism of recruitment of LLPS scaffolds to the LD surface is mediated by Plin proteins, which are LD-specific proteins. Other biomolecules than LD surface proteins are likely to bind to their surface, including RNA or RNA Binding Proteins ³⁶, which could act as putative linkers with endogenous condensates. Our data suggest that the surface of LD could drive the nucleation of condensates, which implies a general mechanism of regulation of phase separation that is based both on the biophysical and biochemical properties of lipid droplet/condensate interactions.

The affinity between Plin and LD surface controls several features of Plin-condensate organization and biophysical properties. For instance, Plin1-condensates were less dynamic
than other Plin-condensates (Extended Fig. 4). Furthermore, the weaker affinity of Plin3 could
drive the peripheral localization of LDs to the condensate interface rather than in condensates,
as LD surface localization was more frequent for Plin3 than other Plins. Physical considerations
may also explain how LD organizations targeted with Plin-functionalized scaffolds could be
remodeled through two main different patterns, either entrapped within large condensates or
arranged into a string-like pattern (Fig. 1f-g). Two patterns depended on 5Fm-emGFP-Plin2
expressed in cells, with a lower quantity of 5Fm-emGFP-Plin2 favoring large 3D condensates.
Our time-lapse imaging suggests that LDs-on-a-string arrangements formed through the
irreversible adhesion between close LDs (Fig. 1g). In these conditions, large condensates on
LD surface failed to grow. Since the co-condensation of mCherry-5Fm with 5Fm-emGFP-
Plin2 at the LD surface is energetically more favorable than forming 3D condensates, this
prevents independent nucleation elsewhere in the cell. These patterns were mainly observed
when a larger amount of 5Fm-emGFP-Plin2 was transfected compared to the quantity used for
forming LD-condensates (five-fold increase). This indicates that competition between adhesion
strength, dependent on the 5Fm-emGFP-Plin2 surface density, and 3D phase separation
dictates the balance between LDs-on-a-string arrangements and LD-condensates. This
mechanism could potentially elucidate why, under physiological conditions, LDs often cluster
resembling a grape-like structure, potentially facilitated by proteins prone to forming
condensates, similar to Cidec³¹. When metabolic demands arise, these adhesion interactions
may be disrupted by removing such proteins, allowing for LDs to disperse and fulfill their
metabolic functions.

Several applications can be envisioned using ControLD as a tool to synchronize LD
availability, enabling detailed investigations of specific molecular processes controlling LD
dynamics. ControLD also facilitates the disruption and restoration of LD contact sites, making
it a versatile method for studying these dynamic interactions. Its adaptability further supports
its use in exploring other LD surface proteins in physiological contexts, such as in adipocyte
cells. Given the increasing evidence of the pivotal roles of LD metabolism and contact sites in
health and disease⁵, understanding how LDs entrapped within condensates influence the
progression of pathogen-infected or cancer cells represents an exciting direction for future
research. Furthermore, we anticipate that the extension of the ControLD concept to control
other cellular organelles will significantly broaden its potential applications.

## Acknowledgments and Funding

We thank Mohyeddine Omrane for the help along the project. CA was supported by a PhD
fellowship from ENS. D.S was supported by the Labex IPGG (ANR-10-IDEX-0001-02). This
work was supported by the centre national de la recherche scientifique, Ecole Normale
Superieure, and ANR (ANR-22-CE44-0036) to A-R.T, J.S and Z.G, and the foundation
ARC(ARCPJA2023080007011) to Z.G.

## Author Contributions

C.A, A-R.T and Z.G conceived and analyzed the experiments. Z.G supervised the work. C.A, D.S, E.P, T.B carried out and analyzed the experiments. J.S and M-A.P contributed to the design of the experiments. S.S. and G.P. performed and analyzed TEM experiments. All
authors analyzed the data and commented on the manuscript. C.A., A-R.T and Z.G wrote the manuscript.

**Competing Interests**

The authors declare that they have no competing interests.
## Figure Legends

### Figure 1. Controlled trapping of Lipid Droplets (ControLD) using bioengineered condensates programmed to interact with LDs

(a) Schematic of the LD-targeting protein scaffold enabling phase-separation. The scaffold is made of a repetition of homodimerization domains, and a LD-binding protein used for LD surface recognition (Fm = FKBP12-F36M, Plin2 = perilipin 2). Left: HeLa cell expressing mCherry-5Fm condensates. Right: Hela cell expressing Plin2 localized at LD surface. (b) Confocal imaging of mCherry-5Fm condensates and Plin2-coated LDs in HeLa cells. (c) Confocal imaging of HeLa cells expressing Plin2-functionalized LLPS scaffolds. (d) Cells expressing Plin2-functionalized 5Fm scaffolds. The experiments in (b-d) were repeated independently three times with similar results. (e) From left to right: distribution of the number of condensates per cell; size distribution of the condensates (Feret's diameter); distribution of the number of LDs per condensate; percentage of total LDs trapped within condensates per cell (n = 60 cells, two independent experiments). For all panels, cells were fixed 24 h after transfection, and LDs were revealed using LipidTOX. Scale bars are 10 µm for full cell images and 1 µm for zooms.

### Figure 2. Dynamics of formation of LD-condensates

(a) Time-lapse confocal imaging of the formation of LD-condensates in HeLa cells. Cells were transfected 6 hours before the start of the time-lapse. (b) Time-lapse confocal imaging showing the coalescence of two LD-condensates in HeLa cells. (c) Left panel: Fluorescence recovery after photobleaching performed on 5Fm-emGFP-Plin2 within the 3D condensate phase (red curve, 13 cells) and at the LD surface (green curve, 8 cells). Control experiments were performed on unconfined Plin2-labelled LDs (grey curve, 13 cells). Solid line: mean value, colored area: 95% confidence interval. Right panel: Two representative FRAP experiments associated with the kymograph of intensity recovery extracted on the region of interest (dash circle). (d) Left: plot of the temporal evolution of the GFP mean fluorescence intensities during the formation of LD-condensates in a HeLa cell, looking at the entire cell area ("whole cell") and at areas without LD-condensates ("dilute phase"). Right: evolution of solubilized 5Fm-emGFP-Plin2 fluorescence compared to total fluorescence, before and after condensates nucleation. The experiments in (d) were repeated independently two times with similar results. For all panels, scale bars are 10 µm for full cell images and 1 µm for zooms.

### Figure 3. Drug-induced dissociation of LD-Condensates

(a) Schematic of FK506-induced dissolution of LD-Condensates. (b) Time-lapse epifluorescence imaging of the drug-induced dissolution of LD-trapping condensates in HeLa cells. Cells were transfected 24 hours before observation with 5Fm-emGFP-Plin2, mCherry-5Fm, and 5Fm (plasmid ratio 1:5:14). Dissolution is induced upon the addition of FK506 (2.5 µM) at the start of the time-lapse. The experiment was independently repeated three times with similar results. Scale bar, 10 µm for full cell, 1 µm for zooms µm. (c) Evolution of fluorescence in the dilute phase during the condensate dissolution of the cell shown in (b), for 5Fm-GFP-Plin2 and mCherry-5Fm. The grey area represents the timing of dissolution of condensates.

### Figure 4: Formation of LD-condensates using Plin 1 and Plin 3 and protein binding competition.

(a) Confocal imaging of LD-condensates in HeLa cells using Plin1 functionalized LLPS scaffolds. (b) Confocal imaging of LD-condensates in HeLa cells using Plin3 functionalized LLPS scaffolds. Cells were transfected with plasmids 5Fm-emGFP-Plin3, mCherry-5Fm, and 5Fm. (c) Quantification of the
intensity ratio at the LD surface and within the condensates for Plin1, Plin2 and Plin3 respectively (n=46, 73, 61 cells, two independent experiments). Centre lines represent medians, boxes show interquartile ranges (IQR) and whiskers represent 1.5*IQR. (d) Protein binding competition and condensate formation with cells co-transfected with emGFP-Plin1, 5Fm-mCherry-Plin2, 5Fm, showing no Plin2-coated LDs and no subsequent trapping. (e) Protein binding competition and condensate formation with cells co-transfected with mCherry-Plin2, 5Fm-emGFP-Plin3, 5Fm, showing no Plin3-coated LDs and no subsequent trapping. The experiments in (a-b, d-e) were repeated independently three times with similar results. For all panels, LDs were marked using LipidTOX. Scale bars are 10 µm for full cell images and 1 µm for zooms.

**Figure 5: LD-trapping condensates restrict trafficking between LDs and protect LDs during starvation**

(a) Schematic showing incorporation of fluorescent fatty acid analogs (BODIPY-C12) before condensate formation in HeLa cells expressing LD-condensates. HeLa cells were fixed 28 hours post-transfection and cultured in oleic acid-enriched medium. Bottom: imaging of LDs within Plin2-condensates. (b) Schematic showing incorporation of BODIPY-C12 after condensate formation. Bottom: Imaging of LDs within Plin2-condensates. Cells fixed 28 hours post-transfection. The experiments in (a-b) were repeated independently three times with similar results. (c) Quantification of radial distribution of BODIPY-labeled LDs within condensates. Solid line: mean value, colored area: 95% confidence interval. (d) Schematic illustrating condensate formation from pre-existing LDs, followed by peripheral incorporation of new lipids. (e, f) Starvation effect on unconfined and confined LDs. Left: Epifluorescence imaging of Plin2-coated LDs and 5Fm-mCherry condensates (e) and LDs confined in condensates (f) 48 hours post-transfection. Media changed 24 hours before fixation to complete or low-nutrient media (EBSS + 1% BSA). Right: Mean LD number per cell expressing $\ge 1$ condensate (5Fm or LD-Condensate), $\pm$starvation; unconfined LDs (p=8$\times$10$^{-15}$), confined LDs (p=4.3$\times$10$^{-3}$). For (e-f) box plots, centre lines represent medians, boxes show interquartile ranges (IQR) and whiskers represent 1.5*IQR. Scale bars: 10 µm (full cell), 1 µm (zooms).

**Figure 6: Reversible disruption of LD-mitochondria contacts**

(a) Spinning-disk imaging of Plin1-coated LDs in HuH7 expressing for 24 hours emGFP-Plin1, BFP-5Fm, and 5Fm with BODIPY-C12 red and MitoTracker Deep Red. (b) Ultrastructural characterization of non-functionalized condensate, LDs and mitochondria in HuH7 cells (C: condensate, M: mitochondria, Nu: nucleus). (c) Spinning-disk imaging of Plin1 LD-condensates in HuH7 expressing for 24 hours emGFP-5Fm-mCherry-Plin1, BFP-5Fm, and 5Fm with BODIPY-C12 and MitoTracker Deep Red. (d) TEM image of LDs-trapped into a large Plin1-condensate from which mitochondria are excluded. (e) Imaging of Plin2 LD-condensates in HuH7 expressing for 24 hours 5Fm-mCherry-Plin2, BFP-5Fm, and 5Fm with BODIPY-C12 and MitoTracker Deep Red. (f) TEM image of Plin2 condensates with entrapped LDs. The experiments in (a, c, e) and (b, d, f) were independently repeated three and two times, respectively, with similar results. (g) Quantification of LD-mitochondria colocalization in complete media conditions for HuH7 cells expressing LD-condensates (confined LDs) or Plin-coated LDs (unconfined LDs). Displayed p-values of 10$^{-12}$, 10$^{-9}$, 10$^{-16}$ and 10$^{-15}$. (h) Quantification of LD-mitochondria colocalization during starvation. Displayed p-values of 10$^{-13}$, 10$^{-11}$, 10$^{-8}$ and 10$^{-7}$. In (g-h), middle line represents medians, and error bars show interquartile ranges. For all panels, scale bars are 10 µm for full cell images, 5 µm for zooms and 1µm for TEM images.
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# METHODS

## Experimental model

Human epithelioid carcinoma HeLa cells (ATCC, ccl-2) were kept in Dulbecco's modified Eagle's medium (with 4.5 g/l D-glucose, HyClone) with 10% fetal bovine serum (Gibco) and 1% penicillin-streptomycin (Sigma, P4333), at 37°C in a 5% CO2-humidified atmosphere. Hepatocyte-derived carcinoma HuH7 cells (ATCC) were kept in minimum essential medium with 10% fetal bovine serum (Gibco), 1% penicillin-streptomycin (Sigma, P4333), 1% MEM non-essential amino acids (Gibco), and 1% sodium pyruvate (Gibco) at 37°C in a 5% CO2-humidified atmosphere. Tests for mycoplasma contamination were routinely carried out.

## Plasmids

The plasmids used during this study are listed in the table S1. The pcDNA3.1-5Fm and pcDNA3.1-mCherry-5Fm plasmids were obtained as described in²³. The pcDNA3.1-emGFP-Plin2 plasmid was created by replacing the 5Fm coding sequence from the pcDNA3.1-emGFP-5Fm (between the Eco47III and XbaI restriction sites) with the mPlin2 coding sequence. The pcDNA3.1-5Fm-emGFP-Plin2 plasmid was created by inserting the mPlin2 coding sequence between the XbaI and AgeI restriction sites from the pcDNA3.1-5Fm-emGFP. The pcDNA3.1-5Fm-emGFP-Plin1 plasmid was created by replacing the Plin2 coding sequence from the pcDNA3.1-5Fm-emGFP-Plin2 (between the XbaI and AgeI restriction sites) with the mPlin1 coding sequence. The pcDNA3.1-5Fm-emGFP-Plin3 plasmid was created by replacing the mPlin2 coding sequence from the pcDNA3.1-5Fm-emGFP-Plin2 (between the XbaI and AgeI restriction sites) with the mPlin3 coding sequence. The pcDNA3.1-emGFP-Plin1 plasmid was created by replacing the mPlin2 coding sequence from the pcDNA3.1-emGFP-Plin2 (between the AfeI and XbaI restriction sites) with the mPlin1 coding sequence. The pcDNA3.1-5Fm-mCherry-Plin2 plasmid was created by replacing the emGFP coding sequence from the pcDNA3.1-5Fm-emGFP-Plin2 (between the SacII and XbaI restriction sites) with the mCherry coding sequence. The pcDNA3.1-mCherry-Plin2 plasmid was created by replacing the 5Fm coding sequence from the pcDNA3.1-mCherry-5Fm (between the Eco47III and XbaI restriction sites) with the Plin2 coding sequence. The pcDNA3.1-emGFP-Plin3 plasmid was created by replacing the 5Fm coding sequence from the pcDNA3.1-emGFP-5Fm (between the Eco47III and XbaI restriction sites) with the mPlin3 coding sequence.

## Transfection

For imaging after cell transfection and fixation, HeLa cells were cultured on 22x22 mm glass coverslips (VWR) in 6-well plates (Falcon, 3.5 × 10⁵ cells per well). For live imaging, HeLa cells were seeded on 35-mm dishes with a polymer coverslip bottom (Ibidi, 1.5 × 10⁵ cells per dish). In both cases, adhesion surfaces were treated with a solution of 0.002% poly-L-lysine (Sigma) for 30 min. Cells were transfected with Lipofectamine 2000 (Invitrogen) 24 hours after seeding. In every case, cells were incubated at 37°C under a 5% CO₂ atmosphere.

For fixed samples, a total quantity of 2 µg of DNA was used for every well. Unless stated otherwise, when Plin1- and Plin2-related proteins are transfected, 0.1 µg of plasmid was used. When plin3-related proteins was used, 0.5 µg of plasmid was used. When 5Fm-related proteins are transfected, 0.5 µg of mCherry-5Fm + 1.4 µg of 5Fm plasmids were used. For every
condition, when the total mass of coding DNA was lower than 2 µg, an empty pcDNA3.1 plasmid was added to reach 2 µg. For live imaging, a total quantity of 0,85 µg of DNA was used, and quantities described above were scaled accordingly.

### Fixation

To prepare fixed samples, cells were washed two times with PBS, and then incubated 20 min in a solution of 4% PFA (polyformaldehyde, Fisher Scientific) in PBS. Cells were washed again two times with PBS, and mounted on slides (VWR) using Vectashield mounting medium (Vector Laboratories, H-1200).

### Fluorescent staining

To stain LDs with a fluorescent reporter, a solution of LipidTOX HCS DeepRed (ThermoFisher H34477), diluted at 1:1000 in PBS was used. Fixed samples were exposed 30 min to this solution, then mounted on slides without washes. To reveal mitochondria, MitoTracker (FisherScientific 17531655) was used following the manufacturer's protocol.

### Fluorescent fatty acid assays

To feed cells with the fluorescent fatty acids BODIPY-C12 green (Fig. 5a-d), culture medium was supplemented with 200 µM of oleic acid (complexed with BSA, ratio 8:1) during the 28h following the transfection. During the 4h BODIPY-C12 pulse, culture medium was also supplemented with 2 µM of BODIPY-C12 green. To label cells with fluorescent BODIPY-C12 red (Fig. 6), the medium was solely supplemented with 2µM BODIPY-C12 red, without oleic acid supplementation.

### Live dissolution assay

To induce the live dissolution of condensates (Fig. 3, Supplementary Movie 2), 1 µL of FK506 (Sigma, F4679) at 2.5 mM in DMSO was added in the medium at the edge of the culture plate, after the start of live acquisition. No mixing was performed to allow the slow diffusion of FK506 in the medium, to reach a final concentration of 2.5 µM.

### Delipidation assays

To induce the delipidation of cells, HeLa cells were first seeded and transfected 24h later as previously described, on a 22x22 mm coverslip in a 6-well plate. After another 24h, cells were washed 2 times with pre-heated DPBS (Dulbecco Phosphate-Buffered Saline, Sigma) and placed in EBSS (Earle's Balanced Saline Solution, Fisher Scientific) containing 1% of BSA (Bovine Serum Albumin, Sigma) during 24h. Control cells were instead placed again in the same culture medium as the first steps during 24h. Cells were then fixed and observed as described above.

### Imaging

For overnight live imaging (Fig. 2, Supplementary Movie 1), cells were imaged on a Zeiss LSM 710 confocal microscope using an x63 oil-immersion objective (PlanApochromatic, numerical aperture (NA) 1.4), at 37°C under a 5% CO₂ atmosphere. The acquisition was started 6h hours after transfection for the formation of condensates. Microscope hardware and image
acquisition were controlled with LSM Software Zen 2012. For the dissolution assay, we used (Fig. 3, Supplementary Movie 2), cells were imaged on an Olympus IX81 microscope and 60X oil immersion objective (PlanApo, NA 1.42), equipped with a CMOS camera, Orca-Fusion (Hamamatsu, Corporation), and a LED system of illumination (Spectra X, Lumencor) at 37°C. The acquisition was started 24h hours after cell transfection. Microscope hardware and image acquisition were controlled using Micro-Manager. For Airyscan images, cells were imaged with Zeiss LSM 880 confocal microscope equipped with Airyscan detector using a 60× oil immersion objective (PlanApo, NA 1.42). Airyscan processing was performed automatically with Zeiss Zen software (v. 2.3).

## Fluorescence Recovery After Photobleaching

Fluorescence recovery after photobleaching (FRAP) experiments on LD-condensates in live HeLa cells were performed starting approximately 24 hours after transfection. Bleaching experiments were performed in a humidified chamber maintained at 37 C and 5% CO2, which was mounted on a Zeiss LSM 710 META laser scanning confocal microscope (using an 63x (NA 1.4) oil-immersion objective) and operated with the LSM Zen 2012 software. Each region of interest was scanned 5 times to establish the average level of initial fluorescence, then bleached using 25 iterations at 100% 488-nm laser intensity. Subsequently, the fluorescence recovery was monitored using one acquisition every 3 sec for at least 300 sec. FRAP data analysis and fitting of the recovery curves were performed with Python. Fluorescence of the bleached zone was normalized using the intensity of a non-bleached zone, as far as possible from the bleaching ROI. The presented FRAP curves were also normalized using the initial average fluorescence of the ROI before bleaching as the maximum value, and its fluorescence right after bleaching as the minimum value. Fitting was performed using a bi-exponential decay $f(t) = A \cdot \exp(-t/\tau)$ + $A \cdot \exp(-t/\tau_0)$, with $\tau_0$ constrained in [0 sec ; 1 sec] to reflect the freely diffusing species. To determine the spatio-temporal FRAP patterns, kymographs were generated by measuring fluorescence evolution as a function of time across a line of interest, using Fiji.

## Transmission electron microscopy (TEM)

Cells fixed in 2% glutaraldehyde in 0.1 M Sörensen phosphate buffer, were post-fixed with 2% osmium tetroxide and stained in bloc in 2% uranyl acetate in 30% methanol. Following dehydration through a graded ethanol series, cells were embedded in Epon™ 812. Ultrathin sections were stained with standard uranyl acetate and lead citrate and observed with a Tecnai 12 electron microscope (Thermo Fisher Scientific). Digital images were taken with a SIS MegaviewIII CCD camera.

## Data analysis

To measure mean fluorescence signals in cells (Fig. 2c, Extended Fig. 2), cells were systematically segmented using Cellpose³⁷,³⁸ using a pre-trained model which was fine-tuned on our data, across an overnight time-lapse movie. Fluorescence mean values were then computed using Python. To obtain the signal in the cytosol only, condensates were systematically thresholded using Otsu threshold³⁹ provided by the scikit-image Python package⁴⁰, and fluorescence mean values were computed on the remaining areas of the cell as
before. Segmentation of organelles on fluorescence images (Fig. 6) has been performed using Nellie ⁴¹, an automated organelle segmentation plugin for Napari (https://zenodo.org/records/8115575). Colocalization was then computed using Mander's coefficient m1, defined as the percentage of LDs pixels that were also located on mitochondria pixels. Plotted fluorescence profiles (Extended Fig. 1) were generated using Fiji ⁴². All plots were generated using the seaborn Python package ⁴³.

**Statistical analysis and reproducibility**

All statistical analyses were performed using Python and plotted using Seaborn. To measure the distribution of condensate features (Fig. 1e), 60 cells expressing condensates from two independent experiments were imaged through blind acquisition. Imaging and analysis were performed using a 3D stack with a z-step of 0.5 µm. Counting was done manually, and size measurement was performed using Fiji. To measure the ratio of intensities (Fig. 4c), respectively 11 (Plin1), 18 (Plin2) and 14 (Plin3) different images of LD-condensates were used. For each of them, a fluorescence profile has been measured in at least 4 different LD interfaces. obtaining a total of respectively 46, 73, 61 fluorescence profiles. Counting of LDs in cells during the starving experiments (Fig. 5e-f) was performed by blind 3D acquisitions of at least 35 cells expressing condensates for each condition, from two independent experiments, followed by manual counting of all LDs in the 3D stack using a z-step of 0.5µm. The number of cells for these plots were respectively 39 (unconfined LDs and complete medium), 45 (unconfined LDs and starving medium), 52 (confined LDs and complete medium), and 57 (confined LDs and starving medium), and cells from two independent experiments were observed though blind acquisition, by selecting every cell expressing a condensate. Cell numbers for Fig. 6g: n=68, 93, 25, 66, 77, 35 cells, respectively, from two independent experiments. Cell numbers for Fig. 6g: n=50, 82, 30, 52, 77, 21 cells, respectively, from two independent experiments. For all experiments displaying p-values, the p-value was calculated using a two-sided Wilcoxon-Mann-Whitney provided by the Scipy Python package ⁴⁴.

**Data availability:**

All data needed to interpret and analyze the research in the article are present in the paper and/or the Supplementary Materials.

**Methods-only references**

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