C18ORF32 modulates lipid droplet secretion via secretory autophagy and restrains hepatic steatosis in vivo

Abhishek Kumar; Shailesh Kumar Gupta; Yogendra Pratap Mathuria; Debasish Kumar Ghosh

doi:10.1186/s12964-025-02581-6

. 2025 Dec 5;24:17. doi: 10.1186/s12964-025-02581-6

C18ORF32 modulates lipid droplet secretion via secretory autophagy and restrains hepatic steatosis in vivo

Abhishek Kumar ^1,^#, Shailesh Kumar Gupta ^2,^#, Yogendra Pratap Mathuria ², Debasish Kumar Ghosh ^1,^✉

PMCID: PMC12797721 PMID: 41351175

Abstract

Background

Lipid droplets (LDs) are essential for maintaining cellular homeostasis by storing excess lipids, but regulation of their cellular level is crucial to prevent lipotoxicity under normal conditions.

Methods and results

In this study, we identified C18ORF32 as a key player in lipid droplet secretion through secretory autophagy pathway. In a high-throughput imaging-based organellar screening, we found that C18ORF32 primarily localizes in autophagosomes and in the endoplasmic reticulum. C18ORF32 interacts with lipid droplets via its N-terminal helix: an amphiphilic region binds to the monolayer membrane leaflet of the LD, while a hydrophobic segment embeds in the droplet’s core, ensuring stable anchoring. Mutations of the clustered aromatic amino acids of the N-terminal amphiphilic region disrupt the proper folding and LD binding of C18ORF32. Additionally, C18ORF32 associates with secretory autophagosomes by binding to C-terminal coiled-coil region of SEC22B through its unstructured C-terminal region. Knockdown of C18ORF32 impairs LD secretion, leading to increased intracellular LD accumulation and reduced extracellular release of triacylglycerols, suggesting C18ORF32’s critical role in secretory LD turnover. In vivo knockdown of C18ORF32 caused NASH-like increased hepatic lipid retention and decreased circulating free fatty acids, indicating impaired lipid droplet export via secretory autophagy.

Conclusions

Our data suggest that C18ORF32 promotes the fusion of lipid droplet membranes with secretory autophagosomes, facilitating the release of LDs to extracellular space, thereby mitigating lipotoxicity under physiological conditions. These findings reveal a novel mechanism by which cells regulate lipid droplet homeostasis through secretory autophagy, with C18ORF32 acting as a critical mediator in lipid droplet trafficking and secretion.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12964-025-02581-6.

Keywords: C18ORF32, Lipid droplets, Lipid trafficking, Secretory autophagy, Clustered aromatic amino acids, Hepatic steatosis

Introduction

Cellular lipid droplets (LDs), also referred to as lipid globules, are dynamic organelles that store neutral lipids in eukaryotic cells [1]. These droplets serve as reservoirs of energy-rich lipids, particularly triacylglycerols (TAGs) and sterol esters, which are sequestered within a hydrophobic core [2]. This core is surrounded by a phospholipid monolayer, embedded with specific proteins that regulate lipid metabolism, trafficking, and storage [3]. The formation, maintenance, and regulation of lipid droplets are essential for maintaining cellular lipid homeostasis, energy balance, and membrane biogenesis [1–3].

Lipid droplets originate from the endoplasmic reticulum (ER) with the accumulation of neutral lipids between the two leaflets of the ER membrane [4]. As the concentration of TAGs or sterol esters increases, the lipids form ovoid-shaped structures that gradually bud off from the ER to form a lipid droplet [5]. This process is regulated by several proteins, including seipin [6], a membrane scaffold protein that facilitates the budding of LDs from the ER, and fat storage-inducing transmembrane and peripheral proteins (FIT2 and PLIN3) [7, 8], which promote the formation of lipid droplets by controlling lipid droplet size and maturation. In addition, diacylglycerol acyltransferase (DGAT) enzymes catalyze the final step of triacylglycerol synthesis [9], providing the necessary lipids for droplet formation. Once formed, lipid droplets play a critical role in cellular lipid homeostasis by storing excess lipids and preventing their toxic accumulation in the cytoplasm. However, when lipid droplets become too large or too numerous, they can cause lipotoxicity [10]. Lipotoxicity can lead to cellular dysfunction, particularly in tissues like the liver, brain, and heart, contributing to metabolic disorders such as non-alcoholic fatty liver disease, insulin resistance, neurodegeneration, and cardiovascular diseases [11]. To prevent lipotoxicity, cells utilize several degradation pathways to regulate lipid droplet turnover, including lipolysis and lipophagy [12, 13]. Lipolysis involves the breakdown of lipids by cytosolic lipases, such as adipose triglyceride lipase (ATGL) and hormone-sensitive lipase (HSL), and other modulatory proteins such as CGI-58 and G0S2 [14]. Lipophagy, a specialized form of autophagy, involves the engulfment of lipid droplets by autophagosomes, which fuse with lysosomes to degrade the lipid content [15]. Regulatory proteins like RAB7, RAB10, PLIN1, PLIN2, SQSTM1, OPTN and conserved autophagy machinery proteins are critical in lipophagy, mediating the interaction between autophagosomes and lipid droplets [16].

In addition to degradation, it is interesting to hypothesize that lipid droplets can also be secreted from the cell to supply lipids to distant tissues, particularly in physiological conditions where energy or lipid exchange is required. The secretion of lipid droplets may occur through specialized processes, such as secretory autophagy, where lipid droplets could be delivered to secretory autophagosomes and released to the extracellular space. Identification of secretory pathway can represent a novel mechanism for cell-to-extracellular medium lipid transfer, which could play a critical role in maintaining lipid homeostasis across tissues.

A recently discovered neurodevelopmental disorder is characterized by loss-of-function of C18ORF32 [17]. Because C18ORF32 is hypothesized to bind to lipids [18] and dysregulated lipid metabolism is increasingly recognized as a contributor to neurodevelopmental disorders [19], investigating the role of C18ORF32 is crucial for understanding its function in cell physiology, particularly regarding lipid storage and mobilization homeostasis and endomembrane trafficking. Human C18ORF32 is a small, 76-amino-acid protein that associates with cellular lipid droplets [18], putatively during lipid storage and metabolism. Its bipartite structure, consisting of an N-terminal helical region and a C-terminal unstructured region, suggests a functional flexibility that may allow it to interact with lipids and diverse protein partners. Importantly, C18ORF32 has been shown to bind to a variety of proteins involved in crucial cellular processes, including cell surface receptors [20], ion channels [21], and autophagy-associated proteins [22], hinting at a broader role in regulating intracellular trafficking and signaling. Understanding how C18ORF32 influences lipid droplets and interacts with autophagy-related proteins may uncover new insights into the regulation of energy metabolism and the development of therapeutic approaches for disorders.

This study explores the role of C18ORF32 in lipid droplet (LD) homeostasis and secretory autophagy. We find that C18ORF32 localizes to the lipid droplets and autophagosomes, interacting with LDs through its N-terminal amphiphilic helix and with SEC22B via its C-terminal region. Loss of C18ORF32 leads to intracellular accumulation of LDs and reduced secretion of lipids, highlighting its importance in lipid turnover. The protein helps loading LDs into secretory autophagosomes for extracellular release. Thus, disruptions in C18ORF32 function contribute to hepatic steatosis, potentially due to impaired lipid secretion.

Results

C18ORF32 localizes to Endoplasmic reticulum and autophagosome

Our study investigated the subcellular localization of C18ORF32 to understand its potential role in cellular processes, focusing on its association with various organelles. Using immunofluorescence-based imaging screening, we analyzed the colocalization of C18ORF32 with a number of organelle-specific protein markers. One of the most striking findings was the high colocalization of C18ORF32 with LC3B-positive puncta (Fig. 1A and B), indicating a strong presence of C18ORF32 on autophagosomes, suggesting that C18ORF32 might play a significant role in autophagic processes.

In addition to its association with autophagosomes, C18ORF32 exhibited colocalization at the endoplasmic reticulum (ER) (Fig. 1A and B), albeit to a lesser extent than at autophagosomes. This suggested that C18ORF32 could be co-translationally localized to the ER and might accumulate at specific ER sites that gave rise to specialized structures such as phagophore membranes and lipid droplets. These observations were consistent with the idea that C18ORF32 might participate in lipid droplet metabolism or in the autophagy, where the ER was known to contribute to the biogenesis of lipid droplets and autophagosomes. However, despite its presence at the ER, C18ORF32 showed no significant colocalization with the ER-Golgi intermediate compartment (ERGIC) or the Golgi complex (Fig. 1A and B). This finding suggested that C18ORF32 did not utilize the ER exit sites for transport through the secretory pathway, which aligned with the absence of a signal peptide in C18ORF32’s sequence.

Interestingly, while C18ORF32 was strongly associated with autophagosomes, it did not show significant colocalization with lysosomes (Fig. 1A and B). This suggested that C18ORF32-positive autophagosomes might not undergo maturation into autolysosomes. Instead, the C18ORF32-positive autophagosomes could be involved in an alternative autophagy pathway, such as secretory autophagy. Furthermore, C18ORF32 exhibited very low colocalization with early endosomes (RAB5-positive), late endosomes (RAB7-positive), fast recycling endosomes (RAB4-positive), and multivesicular bodies (RAB27A-positive) (Fig. 1A and B). This indicated that C18ORF32 is not involved in the endosomal trafficking system, nor does it participate in the endocytosis pathway. The lack of colocalization with endosomes suggested that C18ORF32’s role is more specialized and does not extend to general vesicle transport or recycling processes within the cell. Taken together, these results suggested that C18ORF32 primarily localized at the ER and autophagosomes, with a possible role in specialized autophagy pathways and lipid droplet homeostasis, while being largely excluded from the classical endomembrane trafficking routes such as endocytosis and secretion through the Golgi.

Although C18ORF32 was present on both autophagosomes and the ER, its genetic knockdown did not disrupt the structural integrity of the ER (no observed fragmentation of ER network), nor did it significantly alter the number of autophagosomes within cells (Fig. 1C and D). These findings suggested that while C18ORF32 localized to these organelles, it was not essential for maintaining ER membrane structure or for regulating the initiation and maturation of autophagosomes. Gene ontology analysis of the biological processes associated with C18ORF32-interacting proteins revealed enrichment in pathways related to autophagosome maturation, autophagosome assembly, and cellular stress response (Fig. 1E). This indicated that C18ORF32 might have functional roles related to autophagy but not in the direct assembly or maturation of autophagosomes. Instead, it is likely involved in more specialized processes, such as the regulation of lipid droplet biogenesis at the ER and the regulation of lipid droplet-associated autophagy.

C18ORF32 is present on secretory autophagosomes to modulates secretory autophagy

Our study aimed to further investigate the role of C18ORF32 in autophagy. Initial observations confirmed that while C18ORF32 was present on autophagosomes, it was absent from lysosomes. This led us to hypothesize that C18ORF32 might localize specifically to secretory autophagosomes. Genetic knockdown of C18ORF32 revealed no significant change in the number of WIPI2-positive phagophores or LC3B-positive autophagosomes (Fig. 2A and B), suggesting that C18ORF32 did not play a role in the initiation or formation of autophagosomes. Dynamic imaging revealed that C18ORF32-positive granules undergo fusion with LC3B-positive autophagosomes (Fig. 2C). However, when STX4, a protein involved in the fusion of secretory autophagosomes to the plasma membrane [23], was knocked down, there was a significant increase in the number of C18ORF32-positive autophagosomes, while C18ORF32-negative autophagosomes remained unchanged (Fig. 2D and E). This indicated that inhibition of secretory autophagy led to the accumulation of C18ORF32-positive autophagosomes, implying that C18ORF32 was specifically associated with secretory autophagosomes. In contrast, knockdown of STX17, a protein that mediates autophagosome-lysosome fusion [24], did not significantly alter the number of C18ORF32-positive autophagosomes, though C18ORF32-negative autophagosomes increased in number (Fig. 2D and E). This further supported the notion that C18ORF32 was exclusive to secretory autophagosomes and did not participate in the autophagosome-lysosome fusion process. High colocalization of C18ORF32 with secretory autophagosome markers ACBP and SEC22B confirmed its presence on secretory autophagosomes (Fig. 2F and G), strengthening the idea that C18ORF32 played a key role in this specialized form of autophagy.

We also observed that knockdown of C18ORF32 significantly reduced the release of ACBP into the extracellular medium (Fig. 2H and I), suggesting that C18ORF32 was critical for the proper function of secretory autophagy. ACBP is known to be secreted through unconventional autophagy pathways, and the reduced extracellular release of ACBP in C18ORF32-deficient cells indicates that C18ORF32 was involved in the trafficking or loading of secretory cargo onto secretory autophagosomes.

The C-terminal unstructured region of C18ORF32 interacts with the C-terminal coiled-coil region of SEC22B of secretory autophagosome

Next, we sought to elucidate the mechanisms by which C18ORF32 localized to secretory autophagosomes. To this end, we created different deletion mutants of C18ORF32 to identify the specific region responsible for its autophagosome localization. We constructed C18ORF32-(1–38), containing the N-terminal 38 residues, and C18ORF32-(39–76), containing the C-terminal 38 residues of C18ORF32 (Fig. 3A). Immunofluorescence assays revealed that the full-length C18ORF32 and C18ORF32-(39–76) showed significant colocalization with LC3B-positive autophagosomes (Fig. 3B and C), indicating that the C-terminal region of the protein was crucial for its autophagosomal localization. In contrast, C18ORF32-(1–38) did not exhibit any notable colocalization with autophagosomes (Fig. 3B and C), suggesting that the N-terminal region was not involved in autophagosome targeting.

Fig. 3 — The C-terminal unstructured region of C18ORF32 is essential for its colocalization with LC3B and SEC22B, and mediates its interaction with the secretory autophagy pathway. A Schematic representation of full-length and deletion constructs of C18ORF32 tagged with C-terminal FLAG. The full-length C18ORF32 (residues 1–76) contains an N-terminal helical region (residues 1–35) and a predicted C-terminal intrinsically disordered region (residues 39–76). The deletion mutants include C18ORF32-(1–38), C18ORF32-(39–76), highlighting different structural segments used in functional assays. B Representative immunofluorescence images of SH-SY5Y cells transfected with FLAG-tagged full-length or mutant C18ORF32 constructs, immunostained for FLAG and LC3B. Nuclei were stained with DAPI (blue). Enlarged images represent zoomed-in views of the boxed regions. Scale bar: 5 μm. C Quantification of colocalization (Pearson’s correlation coefficient) between C18ORF32 constructs and LC3B or SEC22B in SH-SY5Y cells. Data represent means ± SEM, n = 100 cells; **P < 0.01. D Nondenaturing co-immunoprecipitation assay demonstrating interaction between endogenous C18ORF32 and SEC22B. SH-SY5Y cell lysates were immunoprecipitated with anti-SEC22B antibody, and immunoblots were probed for C18ORF32 and SEC22B. E Structural model depicting the interaction between C18ORF32 and SEC22B. F Quantitative binding analysis of C18ORF32 and its deletion constructs to SEC22B, as determined by MST. G Representative immunofluorescence images of SH-SY5Y cells expressing C-terminal FLAG-tagged full-length or mutant C18ORF32 constructs, co-stained with SEC22B. Scale bar: 5 μm. H Representative immunofluorescence images of SH-SY5Y cells transfected with *control siRNA* or *SEC22B-siRNA*, and stained for endogenous C18ORF32 and LC3B. Scale bar: 5 μm. All experiments were performed in biological triplicates

Given that C18ORF32 localized exclusively to secretory autophagosomes, we hypothesized that its deposition might be mediated by specific interactions with proteins unique to this pathway. We found that C18ORF32 co-immunopurified with SEC22B (Fig. 3D), a secretory autophagosome-specific protein [23], suggesting a direct or indirect interaction. Molecular docking simulations of C18ORF32 with SEC22B revealed that the C-terminal unstructured region of C18ORF32 interacted with a part of the C-terminal coiled-coil region of SEC22B (Fig. 3E), primarily through hydrophobic and polar interactions. To confirm this interaction, we performed direct protein-protein binding assays using recombinant C18ORF32, C18ORF32-(1,–38), C18ORF32-(39–76), and SEC22B. The results showed that full-length C18ORF32 and C18ORF32-(39–76) exhibited high-affinity binding to SEC22B, while C18ORF32-(1–38) showed no interaction (Fig. 3F). These findings strongly suggested that the unstructured C-terminal region of C18ORF32 was responsible for C18ORF32’s binding to SEC22B. Interestingly, our binding affinity data showed that the C-terminal region of C18ORF32 bound to SEC22B with higher affinity than the full-length protein, suggesting that the N-terminal region might exert a steric hindrance on this interaction. Furthermore, colocalization assays confirmed these results, as both full-length C18ORF32 and C18ORF32-(39–76) showed high colocalization with SEC22B, whereas C18ORF32-(1–38) did not (Fig. 3C and G).

To further validate the role of SEC22B in mediating the localization of C18ORF32 to secretory autophagosomes, we performed genetic knockdown of SEC22B. This led to a significant reduction in the colocalization of C18ORF32 with LC3B-positive autophagosomes (Fig. 3C and H), confirming that SEC22B was essential for the recruitment of C18ORF32 to secretory autophagosomes. These collective findings indicated that the C-terminal unstructured region of C18ORF32 mediated its interaction with SEC22B, which in turn facilitated the deposition of C18ORF32 onto secretory autophagosomes. Our data suggested that C18ORF32 might function similarly to a SNARE-like protein, facilitating the fusion of C18ORF32-associated cargo, possibly membrane monolayer-enclosed lipid droplets, with the secretory autophagosome. This positioned C18ORF32 as a critical mediator in secretory autophagy, specifically in the transfer of lipid droplets and their cargo to the extracellular space through secretory autophagosomes.

The N-terminal helical region of C18ORF32 facilitates its localization to the lipid droplets

We endeavoured to uncover the mechanism by which C18ORF32 bound to lipid droplets, given the initial findings showing its role in lipid droplet-associated secretory autophagy. A predictive algorithm suggested that the N-terminal helical region of C18ORF32 had a high propensity to function as a membrane-binding region (Fig. 4A). To experimentally validate this, we performed immunofluorescence-based colocalization assays using full-length C18ORF32 and its deletion mutants - C18ORF32-(1–38) and C18ORF32-(39–76) (Fig. 4B). The results revealed high colocalization of full-length C18ORF32 and the C-terminal deletion mutant C18ORF32-(1–38) with Nile red-stained cellular lipid droplets, while C18ORF32-(39–76) did not colocalize with lipid droplets (Fig. 4C and D). This indicated that the N-terminal region of C18ORF32 was critical for its localization to lipid droplets.

Fig. 4 — The N-terminal helix of C18ORF32 mediates its binding with lipid droplets. A Membrane-binding prediction of C18ORF32 sequence shows high membrane-binding probability within the N-terminal residues (amino acids 5–35). B Schematic representation of full-length and deletion constructs of C18ORF32 used to dissect membrane-binding domains. The predicted helical domain (residues 4–35) and disordered C-terminal domain (residues 39–76) are indicated. Mutants include C18ORF32-(1–38), C18ORF32-(39–76), and C18ORF32-(Δ8–15), which lacks the predicted membrane-binding region. C Representative immunofluorescence images of SH-SY5Y cells expressing C-terminal FLAG-tagged full-length or mutant C18ORF32 constructs. Cells were co-stained with Nile Red and FLAG. Nuclei stained with DAPI (blue). Scale bar: 5 μm. D Quantitative analysis of colocalization using Pearson’s correlation coefficient between C18ORF32 constructs and lipid droplets (Nile Red), LC3B, and SEC22B. C18ORF32-(Δ8–15) and siRNA knockdown of *C18ORF32* significantly reduce colocalization with lipid compartments and LC3B-positive autophagosomes. n = 100 cells per group; **P < 0.01. E Structural model of the N-terminal helix of C18ORF32 embedded within the mono-membrane layer-enclosed lipid droplets. A surface representation of the amphipathic helix shows distinct hydrophobic (yellow) and polar (cyan) surfaces. Insets highlight specific residues contributing to hydrophobic insertion and membrane binding. F Representative immunofluorescence images of SH-SY5Y cells transfected with deletion constructs of C18ORF32, C18ORF32-(Δ7–16), C18ORF32-(Δ28–37), and C18ORF32-(1–38), and stained with Nile Red. Scale bar: 5 μm. G Nile Red staining in SH-SY5Y cells transfected with *control* or *C18ORF32-siRNA*. Immunostaining for LC3B and SEC22B was performed to assess autophagosome and secretory vesicle identity. Scale bar: 5 μm. All experiments were performed in triplicate with biological replicates

Further analysis of the N-terminal 38 residues of C18ORF32, which formed a helical region, identified two distinct regions: a hydrophobic patch spanning residues 7–15 and an amphiphilic region spanning residues 18–37. To assess the functional relevance of these regions, we generated additional deletion mutants: C18ORF32-(Δ7–15) and C18ORF32-(Δ18–37). Both deletion mutants completely lost their ability to colocalize with Nile red-positive lipid droplets, demonstrating that both the hydrophobic and amphiphilic regions of the N-terminal helix were essential for lipid droplet binding (Fig. 4E). The hydrophobic segment (residues 7–15) likely inserted into the lipid droplet’s core, interacting with the hydrophobic acyl chains of triacylglycerols, while the amphiphilic region (residues 18–37) might interact with the monolayer membrane that encloses the lipid droplet (Fig. 4F). This dual-region binding mechanism explained how C18ORF32 localized to lipid droplets in cells.

In addition to revealing the lipid droplet binding mechanism, we investigated the functional role of C18ORF32 in lipid droplet-autophagosome interaction. Genetic knockdown of C18ORF32 significantly reduced the colocalization of lipid droplets with LC3B-positive autophagosomes, particularly with SEC22B-positive secretory autophagosomes (Fig. 4D and G). This suggested that C18ORF32 played a critical role in the delivery of lipid droplets to autophagosomes, specifically secretory autophagosomes involved in secretory autophagy. C18ORF32’s N-terminal helical region enables it to bind lipid droplets, while its interaction with SEC22B facilitates the fusion of lipid droplet monolayers with the autophagosome membrane. Thus, C18ORF32 not only localized to lipid droplets but also played a crucial role in lipid droplet trafficking, acting as a SNARE-like protein that promoted the fusion of lipid droplets with autophagosomes, particularly in the context of secretory autophagy.

The clustered aromatic residues in the amphiphilic region of N-terminal helix of C18ORF32 are crucial for its structural stability and binding to lipid droplets

Our further investigation into the mechanisms by which C18ORF32 bound to lipid droplets revealed critical insights into the role of its N-terminal helical region. Having identified the N-terminal helical region of C18ORF32 as essential for the protein’s lipid droplet binding, we aimed to pinpoint specific amino acid residues responsible for its structural stability and interaction with the lipid droplet-surrounding membrane monolayer. A notable feature of the amphiphilic region of N-terminal helix was a cluster of aromatic amino acids (Y16, F19, Y23, and Y25) (Fig. 5A). Aromatic residues were known to play important roles in protein stability by facilitating proper folding and maintaining structural integrity [25]. To assess their importance in C18ORF32’s stability and lipid droplet binding, we generated a mutant of C18ORF32 [C18ORF32-(Y16A, F19A, Y23A, Y25A)] in which these residues were substituted with alanine (Fig. 5B).

Fig. 5 — A cluster of aromatic amino acids in the N-terminal helix of C18ORF32 stabilizes the protein structure and mediates its lipid-binding. A Structural model highlighting the N-terminal helix of C18ORF32 and the cluster of aromatic residues (Y16, F19, Y23, Y25). Enlarged surface and cartoon representations show the spatial orientation of these residues that form a putative aromatic patch. B Schematic representation of wild-type C18ORF32 and the alanine-substituted mutant C18ORF32-(Y16A, F19A, Y23A, Y25A). C Isothermal titration calorimetry (ITC) analysis showing the binding affinity of wild-type C18ORF32 and its mutant (Y16A, F19A, Y23A, Y25A) to choline. The wild-type protein exhibits high-affinity binding (K_d = 67.8 nM), whereas the mutant shows a drastically reduced binding affinity (K_d = 556.8 µM). D Up: far-UV circular dichroism (CD) spectra of wild-type and mutant C18ORF32 proteins. Bottom: secondary structure components of wild-type and mutant C18ORF32 derived from the CD spectra. E Representative immunofluorescence images of SH-SY5Y cells transfected with FLAG-tagged wild-type or mutant C18ORF32. Nuclei were stained with DAPI (blue). Enlarged panels show zoomed-in views of the boxed regions. Scale bar: 5 μm. Bottom: High-resolution three-dimensional representative immunofluorescence images showing colocalization of C18ORF32 with Nile red-positive lipid droplets, whereas C18ORF32-(Y16A, F19A, Y23A, Y25A) fail to colocalize on lipid droplets. F Quantification of Pearson’s correlation coefficient for colocalization between C18ORF32 and Nile Red in wild-type and mutant expressing cells. n = 100; **P < 0.01. All experiments were conducted in biological and technical triplicates

Next, we examined the ability of wild-type C18ORF32 and C18ORF32-(Y16A, F19A, Y23A, Y25A) to interact with the phospholipid head groups, particularly choline, which is commonly found in the membrane monolayer surrounding lipid droplets. While wild-type C18ORF32 displayed high-affinity binding to choline (Fig. 5C), the mutant protein lacking the aromatic cluster showed no such interaction (Fig. 5C). This suggested that the aromatic side chains of Y16, F19, Y23, and Y25 played a critical role in binding to the lipid monolayer, potentially through π-cation interactions with the choline group. Additionally, the hydroxyl groups of the tyrosine residues may have facilitated hydrogen bonding, while the aromatic rings of the tyrosine and phenylalanine residues likely participated in hydrophobic interactions with other phospholipid head groups, such as ethanolamine and serine.

Structural analysis using circular dichroism (CD) spectroscopy further confirmed the role of these aromatic residues in maintaining the structural stability of C18ORF32. The CD spectrum of wild-type C18ORF32 showed characteristics of both helical and disordered secondary structures (Fig. 5D), indicative of its functional folded state. In contrast, the mutant C18ORF32-(Y16A, F19A, Y23A, Y25A) exhibited a CD spectrum typical of an unstructured protein (Fig. 5D), indicating that the loss of these aromatic residues led to a failure in proper folding (or helix-to-disorder transition) of the N-terminal region of C18ORF32.

The wild-type C18ORF32 colocalized strongly with Nile red-stained lipid droplets (Fig. 5E and F). In contrast, the C18ORF32-(Y16A, F19A, Y23A, Y25A) protein did not localize to lipid droplets and instead displayed a diffuse cytosolic distribution (Fig. 5E and F), further emphasizing the importance of the aromatic residues for targeting C18ORF32 to lipid droplets.

Taken together, our results demonstrated that the aromatic amino acids Y16, F19, Y23, and Y25 were essential for maintaining the N-terminal helical structure of C18ORF32. These residues contributed to both the structural stability of the helix and its interaction with lipid droplet-enclosing membrane monolayers, thereby ensuring proper localization and function of C18ORF32 on lipid droplets.

C18ORF32 mediates the release of lipid droplets to extracellular space by secretory autophagy

To investigate the role of C18ORF32 in lipid droplet secretion, we conducted a series of experiments that explored how genetic knockdown of C18ORF32 affected lipid droplet accumulation and secretion in cells. First, we observed that genetic knockdown of C18ORF32 significantly increased the number of lipid droplets within the cells compared to control cells (Fig. 6A and B), suggesting that C18ORF32 was involved in the regulation of lipid droplet turnover. Additionally, the extracellular medium of C18ORF32 knockdown cells showed reduced levels of triacylglycerols (Fig. 6C), indicating that C18ORF32 played a crucial role in the secretion of lipid droplet components into the extracellular space.

Further quantification of fatty acid composition in the extracellular medium revealed a significant reduction in long-chain fatty acids in C18ORF32-siRNA treated cells compared to control cells (Fig. 6D). This reduction underscores the importance of C18ORF32 in facilitating the secretion of triacylglycerols and its components such as fatty acids from intracellular lipid droplets into the extracellular environment. These findings were corroborated by experiments in which individual knockdowns of other proteins involved in secretory autophagy, such as LC3B, SEC22B, and STX4, led to similar results. The knockdown of these proteins increased the number of intracellular lipid droplets and decreased extracellular triacylglycerol levels (Fig. 6E and F), further suggesting that C18ORF32 functions within the same pathway as these autophagy-related proteins.

Interestingly, while knockdown of STX17 also increased intracellular lipid droplets (Fig. 6E and F), the extracellular content of triacylglycerols remained unchanged compared to control cells. This observation suggested that STX17 is not directly involved in the secretory autophagy pathway. The increases in the STX17 knocked down cells could be due to reduced lipophagy, resulting from inhibition of fusion of lipid droplet-containing autophagosomes with lysosomes. The increase in lipid droplets in STX17 knockdown cells was lower than in cells knocked down for LC3B, SEC22B, STX4, or C18ORF32, further supporting the idea that STX17 operated in a different autophagic pathway, likely related to lysosome-mediated degradation, rather than secretion.

These results highlighted the modulatory role of C18ORF32 in lipid droplet secretion through secretory autophagy. C18ORF32 appeared to function alongside LC3B, SEC22B, and STX4 in facilitating the export of lipid droplets from cells. Specifically, C18ORF32 bound to SEC22B on the surface of secretory autophagosomes, allowing the fusion of the C18ORF32-bound lipid droplet membrane monolayer with the autophagosome membrane. This interaction was critical for incorporating lipid droplets as cargo into secretory autophagosomes, which were then secreted into the extracellular space through a process involving STX4, and possibly STX3, at the plasma membrane.

Loss of expression and function of C18ORF32 leads to NASH-like hepatic lipid accumulation in vivo

To determine whether dysregulation of C18ORF32 perturbs lipid homeostasis in vivo, mice were administered UPF0729-targeting siRNA (UPF0729 is the homolog of C18ORF32 in mus musculus) repeatedly over a 15-day regimen and compared with control-siRNA-treated animals (Fig. 7A). The treatment was well tolerated with no mortality observed in either group over the experimental period (Fig. 7B). At day 15, analysis of liver and serum from all five mice of each group revealed robust knockdown of UPF0729 - both transcript and protein levels in liver tissue were markedly reduced in UPF0729-siRNA-treated animals relative to controls, confirming effective suppression of gene expression in vivo (Fig. 7C).

Fig. 7 — In vivo knockdown of *UPF0729* induces hepatic steatosis-like phenotype and systemic lipid alterations in mice. A Schematic representation of the experimental strategy: mice were injected at regular intervals with either *control-siRNA* or *UPF0729-siRNA* for 15 days. B Kaplan-Meier survival curves showing 100% survival of both *control-siRNA* and *UPF0729-siRNA* treated mice. C Validation of *UPF0729* knockdown at day 15 showing significantly reduced transcript levels (qRT-PCR) and protein expression (ELISA) in *UPF0729-siRNA* treated mice compared to control; **P < 0.01. Values of male and female mice are represented with red and blue, respectively. D Physiological parameters at day 15: *UPF0729* knockdown significantly increased average body weight and liver coefficient [**P < 0.01], while food and water intake remained unchanged. Values of male and female mice are represented with red and blue, respectively. E Representative H&E-stained sections of liver tissue of male and female mice. *Control-siRNA* treated mice displayed normal hepatic architecture with well-preserved hepatocyte plate distribution, intact portal triads, and minimal apoptosis. In contrast, *UPF0729-siRNA* treated mice exhibited severe disruption of hepatocyte plates, nuclear atypia, vacuolated areas indicative of steatosis, and increased apoptotic cells. F Serum analysis of free fatty acids (C2 to C18) showing significantly reduced levels across multiple acyl chain lengths in *UPF0729-siRNA* treated mice compared to controls; **P < 0.01. G Triglyceride levels in serum and liver tissue of *control-siRNA* and *UPF0729-siRNA*-treated mice; **P < 0.01. Values of male and female mice are represented with red and blue, respectively

Physiological measures showed that UPF0729-depleted mice exhibited a significant increase in average body weight and in liver coefficient (liver mass normalized to body weight) compared with control animals (Fig. 7D), while daily food and water intake were not significantly different between groups (Fig. 7D). Thus, the observed hepatic enlargement was not attributable to altered food or water intake. Histopathological analysis of liver sections revealed clear morphological abnormalities in UPF0729-deficient mice - normal hepatic architecture present in control livers (Fig. 7E) was replaced by disruption of the hepatocyte plate arrangement, prominent cytoplasmic vacuolation consistent with steatosis, nuclear atypia, and increased apoptotic cells in UPF0729-siRNA-treated livers (Fig. 7D). These changes are indicative of lipid overload and hepatocellular injury.

Biochemical profiling of circulating free fatty acids showed a significant reduction in serum free fatty acid levels across a range of acyl chain lengths (C2 to C18) in UPF0729-siRNA-treated mice compared with controls (Fig. 7F). Moreover, the levels of triglycerides were significantly reduced in serum and significantly increased in liver tissues of UPF0729-siRNA-treated mice compared to control-siRNA-treated mice (Fig. 7G). Concomitant hepatic enlargement and steatotic histology together with reduced circulating free fatty acids point to impaired export or secretion of lipid droplets from the liver following loss of UPF0729 expression and function.

Collectively, these in vivo data demonstrate that loss of UPF0729 (C18ORF32) promotes hepatic lipid retention, hepatocellular pathology consistent with steatosis, and a reduction in circulating free fatty acids, supporting a model in which UPF0729 (C18ORF32) contributes to lipid droplet clearance from tissues, likely via secretory autophagy, and thus acts to prevent hepatic lipid accumulation. These findings establish a physiological role for C18ORF32 in controlling tissue lipid burden and anti-lipogenic factor and indicate that its dysfunction can produce NASH-like features in mice.

Discussion

C18ORF32 was observed to localize to both the endoplasmic reticulum (ER) and lipid droplets (LDs), suggesting a dynamic role in lipid metabolism and autophagy. The ER plays a pivotal role in lipid droplet biogenesis, as it provides the phospholipid monolayer that envelops the lipid core. C18ORF32’s localization to the ER indicates that it might be initially recruited to ER subdomains, particularly at lipid droplet biogenesis sites of ER, which are known to form nascent lipid droplets. The interaction of C18ORF32 with lipid droplets likely occurs when lipid droplets bud off from the ER, facilitating its transition from the ER membrane to the surface of lipid droplets. Imaging assays showed significant colocalization with lipid droplets, with C18ORF32 binding driven by its N-terminal amphipathic helix, which interacted with the lipid monolayer. In general, C18ORF32 putatively associates with specific ER sites that are involved in lipid droplet biogenesis, playing a role in lipid homeostasis.

C18ORF32 is conserved in higher eukaryotes and plays an essential role in lipid droplet homeostasis, particularly through its involvement in secretory autophagy. By associating with lipid droplets and secretory autophagosomes, C18ORF32 helps regulate the secretion of lipid droplet contents into the extracellular environment, a process that that might be critical for maintaining cellular lipid balance. The release of lipid droplets via secretory autophagy may complement traditional pathways of lipid turnover, such as lipolysis and lipophagy, by providing an alternative route for lipid droplet clearance. This pathway could be particularly important under physiological conditions where lipid storage needs to be rapidly adjusted in response to metabolic demands.

The bipartite nature of the N-terminal helix of C18ORF32 is crucial for its function. C18ORF32 associates with the monolayer membrane enclosing lipid droplets through its N-terminal amphipathic helix. The hydrophobic region of C18ORF32 (residues 7–15) is thought to insert into the hydrophobic core of the lipid droplet, while the amphiphilic region (residues 18–37) interacts with the phospholipid monolayer that surrounds the droplet. This interaction is strengthened by a cluster of aromatic residues (Y16, F19, Y23, and Y25) within the amphiphilic helix, which provide structural stability to the protein and bind to the polar head groups of the monolayer, likely through π-cation and hydrogen bonding interactions. These interactions allow C18ORF32 to anchor itself to the lipid droplet surface, allowing it to function in lipid droplet homeostasis, and facilitate lipid droplet trafficking and turnover in autophagic processes, particularly secretory autophagy.

C18ORF32 selectively localizes to secretory autophagosomes rather than those destined to fuse with lysosomes. This specificity suggests that C18ORF32 is involved in a unique autophagic pathway, secretory autophagy, where autophagosomes do not fuse with lysosomes but instead release their contents extracellularly. One of the key proteins involved in secretory autophagy is SEC22B [23], a SNARE protein that mediates the fusion of autophagosomes with the plasma membrane. C18ORF32 interacts with SEC22B through its C-terminal unstructured region, which facilitates its recruitment to secretory autophagosomes. Knockdown of SEC22B disrupts C18ORF32’s localization to secretory autophagosomes, underscoring the importance of SEC22B in this process. In contrast, C18ORF32 does not localize to autophagosomes involved in the autophagosome-lysosome fusion pathway, likely because SEC22B is not involved in lysosomal fusion, as that role is mediated mostly by proteins like STX17.

C18ORF32 binds to SEC22B via its C-terminal unstructured region, which interacts with the C-terminal coiled-coil region of SEC22B. This interaction is critical for the localization of C18ORF32 to secretory autophagosomes, and molecular docking simulations have shown that this binding is stabilized by both hydrophobic and polar interactions. The role of SEC22B in mediating autophagosome-plasma membrane fusion positions C18ORF32 as a regulator of this process, potentially acting in a SNARE-like manner to facilitate the fusion of lipid droplet-containing secretory autophagosomes with the plasma membrane. This interaction is critical for the secretion of lipid droplets through the secretory autophagy pathway.

Lipid droplet secretion via secretory autophagy could be essential for maintaining lipid homeostasis under both physiological and diseased conditions. In normal physiology, the release of lipid droplets through this pathway may serve several functions, including the removal of excess lipids, the provision of lipids to neighboring cells, or the modulation of signaling pathways that are influenced by extracellular lipid levels. In disease contexts, such as metabolic disorders or neurodegenerative diseases, the regulation of lipid droplet secretion could become dysregulated, leading to lipid accumulation or depletion. Therefore, lipid droplet secretion through secretory autophagy serves as an alternative to traditional lipid degradation pathways such as lipolysis and lipophagy. By facilitating the extracellular release of lipid droplets, secretory autophagy can alleviate intracellular lipid accumulation when lysosomal degradation is insufficient or impaired. C18ORF32 plays a key role in this process by ensuring the proper trafficking of lipid droplets to secretory autophagosomes and facilitating their fusion with the plasma membrane. This process is particularly important in maintaining lipid balance in cells that rely on lipolysis and lipophagy for energy production and lipid turnover.

The in vivo knockdown experiments provide compelling evidence that C18ORF32 is required for physiological lipid export and for preventing hepatic lipid overload. UPF0729 knockdown in mice elicited an increase in body weight and liver coefficient accompanied by striking steatotic histopathology - disrupted hepatocyte plates, prominent vacuolation, nuclear atypia and elevated apoptosis - consistent with hepatocellular injury. Concomitantly, circulating free fatty acids were markedly reduced, indicating that the phenotype reflects impaired export of lipid droplet–derived material rather than increased intake. Thus, UPF0729 (C18ORF32) functions in vivo as an anti-lipogenic factor that facilitates clearance of intracellular lipid droplets via secretory autophagosomes; its loss promotes hepatic lipid retention and a NASH-like state and perturbs systemic lipid homeostasis. These results underscore the physiological relevance of the C18ORF32-secretory autophagy axis for organ and organismal lipid balance.

Mutations in C18ORF32 that affect its expression and function can also lead to deregulated lipid droplet secretion, particularly in neurons, where lipid homeostasis is critical for proper cellular function. Neurons have a high demand for lipid metabolism [26], as lipids are essential components of membranes and are involved in signaling pathways. Dysregulation of lipid droplet secretion due to mutations in C18ORF32 can lead to lipid accumulation or depletion, potentially contributing to neurodevelopmental disorders characterized by hypotonia and contractures. The high expression of C18ORF32 in brain cells suggests that it plays a significant role in maintaining lipid homeostasis in neurons, and its dysfunction could contribute to the pathophysiology of these disorders.

In conclusion, C18ORF32 plays a pivotal role in lipid droplet homeostasis and secretory autophagy, facilitating the trafficking and secretion of lipid droplets through its interactions with SEC22B and its ability to bind to lipid droplet monolayers via its N-terminal amphipathic helix (Fig. 8). Its selective localization to secretory autophagosomes highlights its specialized function in a non-canonical autophagy pathway that complements traditional lipid turnover mechanisms such as lipolysis and lipophagy. Deregulation of C18ORF32’s function, particularly in neurons, may lead to neurodevelopmental disorders, underscoring the importance of this protein in maintaining cellular lipid balance under both physiological and pathological conditions.

Fig. 8 — Model depicting the role of C18ORF32 in secretory autophagy-mediated lipid droplet clearance. C18ORF32 localizes to the surface of lipid droplets (LDs) via its N-terminal amphipathic helix, which contains both hydrophobic and amphiphilic regions. Its intrinsically disordered C-terminal region interacts with the coiled-coil region of SEC22B, localized on secretory autophagosomes (sAVs). This interaction facilitates the docking and fusion of lipid droplets with secretory autophagosomes. C18ORF32 mediates the recruitment and delivery of LDs into sAVs as cargo, which are subsequently secreted via the secretory autophagy pathway

Methods and materials

Gene cloning

Total RNA was isolated from SH-SY5Y cells using total RNA purification system reagent (12183018 A, Invitrogen) and reverse transcribed into cDNA using the Superscript III First-Strand Synthesis System (18080051, Invitrogen). The C18ORF32 coding region was amplified by RT-PCR with gene-specific primers (Eurofins Genomics), incorporating an in-frame FLAG nucleotide sequence in the reverse primer for expression in mammalian systems. The amplified ORF of C18ORF32 and its deletion or point mutants were cloned into pcDNA3.1+ (for mammalian expression) and pET21b+ (for bacterial expression) vectors. PCR products and vectors were restriction digested with specific restriction enzymes (New England Biolabs [NEB]) for pcDNA3.1 + and pET21b+, then ligated using the T4 DNA Ligase System (M0202S, NEB) and transformed into competent DH5α Escherichia coli cells. Transformed cells were plated on LB agar containing ampicillin. Positive colonies were screened by colony PCR (RR350A/B, Takara Bio), and plasmids were extracted and sequenced to confirm the correct insert sequence. The overall procedure of gene cloning for mCherry-LC3B and SEC22B was similar to our earlier studies [27, 28]. Deletion and point mutants were generated by site-directed mutagenesis using PCR and nested PCR methods as described in our earlier studies [29, 30], with all clones confirmed by restriction digestion and sequencing.

Recombinant protein production and purification

Recombinant proteins were produced and purified from bacterial expression system as described in our earlier studies [31, 32]. In general, the pET21b vectors containing C18ORF32 and its mutant C18ORF32-(Y16A, F19A, Y23A, Y25A) were individually transformed into competent BL21(DE3) strain of Escherichia coli for recombinant protein expression. Transformed cells were grown in primary culture overnight, and the following day, a secondary culture was initiated by inoculating fresh LB medium with 1% of the primary culture. When the OD₆₀₀ reached 0.6–0.8, protein expression was induced with 1 mM IPTG (I6758, Sigma Aldrich), and cultures were incubated at 37 °C for 12 h at 190 rpm. Cells were harvested by centrifugation at 5000 rpm for 10 min. The cell pellets were resuspended in lysis buffer (20 mM NaH₂PO₄, 300 mM NaCl, 10 mM Imidazole, 1 mM PMSF (36978, Thermo Fischer Scientific); pH: 8.0) and lysed on ice for 30 min with intermittent vortexing. The lysate was cleared by centrifugation at 14,000 rpm for 40 min at 4 °C. The supernatant containing soluble proteins was passed through a pre-equilibrated Nickel-NTA (R90110, Thermo Fischer Scientific) column to capture the 6xHis-tagged recombinant proteins. The column was washed with wash buffer (20 mM NaH₂PO₄, 300 mM NaCl, 40 mM Imidazole; pH: 8.0) to remove non-specifically bound proteins. The recombinant proteins were eluted with elution buffer (20 mM NaH₂PO₄, 300 mM NaCl, 300 mM Imidazole; pH: 8.0). The eluted proteins were concentrated and dialyzed in 3 kDa cut-off centricon tubes (UFC700308, Merck) with appropriate dialysis buffer based on the downstream assay requirements. Protein purity was assessed by 12% SDS-PAGE, and proteins with > 95% purity were used for further experiments.

Circular dichroism spectroscopy

Circular dichroism (CD) spectroscopy was performed to analyze the secondary structure of C18ORF32 and its mutant, C18ORF32-(Y16A, F19A, Y23A, Y25A), similar to our previous study [32]. Proteins were prepared in CD spectroscopy buffer containing 10 mM NaH₂PO₄ and 50 mM NaF (pH 8.0). Spectroscopic measurements were carried out using a JASCO J-810 spectropolarimeter equipped with a Peltier temperature controller to maintain a temperature of 25 °C. A quartz cuvette with a 10 mm path length was used, and CD spectra were recorded over the wavelength range of 190 nm to 260 nm (far-UV wavelength). The data were averaged from multiple scans and baseline corrected by subtracting the buffer spectrum. Deconvolution of the CD spectra was performed using the Convex Constraint Algorithm (CCA) to estimate the protein’s secondary structure content. The K2D3 algorithm was used to analyze the secondary structure from the CD spectra, providing estimates of alpha-helices, beta-sheets, and random coil proportions.

Isothermal Titration calorimetry for protein-ligand interaction analysis

Isothermal titration calorimetry (ITC) was used to assess the binding interaction between C18ORF32 and its mutant C18ORF32-(Y16A, F19A, Y23A, Y25A) with choline. Both proteins (20 µM) and choline (200 µM) were prepared in phosphate-buffered saline (PBS, pH 7.4). The thermal titrations were carried out at 25 °C using a MicroCal iTC200 instrument (GE Healthcare), equipped with a MicroCal Thermovac temperature-control thermostat system. A total of 20 injections were performed, with a reference power of 10 µcal/s and an initial delay of 60 s. The syringe contained 200 µM choline, and the sample cell contained 20 µM protein. The first injection volume was 2 µL, followed by 19 injections of 4 µL each, with a syringe stirring speed of 300 rpm. The data were analyzed assuming a 1:1 binding stoichiometry using the instrument’s integrated analysis software to determine binding affinity (K_d), enthalpy, and stoichiometry of the protein-ligand interaction [33].

Microscale thermophoresis analysis of protein-peptide interaction

Microscale thermophoresis (MST) was used to analyze the interaction between SEC22B and C18ORF32, as well as its truncated forms, C18ORF32-(1–38) and C18ORF32-(39–76). The overall method followed the procedure described in our earlier study [34]. SEC22B was labelled using the Monolith NT Protein labeling kit RED (NanoTemper Technologies) according to the manufacturer’s protocol. The labeling reaction was performed in MST buffer consisting of 50 mM Tris-Cl (pH 7.2), 150 mM NaCl, and 10 mM MgCl₂. A final concentration of 20 nM labelled SEC22B was titrated with C18ORF32, C18ORF32-(1–38), and C18ORF32-(39–76) at concentrations ranging from 1.25 nM to 10,000 nM. MST measurements were performed in standard capillaries (NanoTemper Technologies) using the Monolith NT.115 system (NanoTemper Technologies) with 50% LED power and 20% IR-570 laser power (laser settings: 30 s on/5 s off). Fluorescence values were normalized, and the dissociation constant (K_d) values were calculated using GraphPad Prism software.

Cell culture and transfections

SH-SY5Y cells were obtained from the American Type Culture Collection (CRL-2266, ATCC) and were characterized based on their typical phenotypic features. The cells were cultured in advanced MEM medium containing glucose, non-essential amino acids, and sodium pyruvate (12492013, Gibco), and supplemented with 10% fetal bovine serum (A5669701, Gibco), 2 mM L-glutamine (35050061, Gibco), and 1X penicillin/streptomycin (15140122, Gibco). Cells were maintained in a humidified incubator at 37 °C with 5% CO₂. Mycoplasma contamination was regularly monitored using commercial detection kit (M7006, Thermo Fischer Scientific).

DNA transfections were performed using Lipofectamine 2000 (11668019, Invitrogen) and Opti-MEM (31985070, Gibco) medium according to the manufacturer’s instructions, while siRNA (Table 1) transfections were carried out using the Lipofectamine 3000 transfection reagent system (L3000001, Invitrogen) following the manufacturer’s protocol.

Table 1.

SiRNA

Target gene siRNA	Supplier	Identifier
C18ORF32-siRNA (human)	Sigma Aldrich	EHU160121
LC3B-siRNA	Sigma Aldrich	EHU002651
SEC22B-siRNA	Sigma Aldrich	EHNC-027001
STX4-siRNA	Sigma Aldrich	EHU033151
STX17-siRNA	Sigma Aldrich	EHU018011
Control-siRNA	Sigma Aldrich	SIC001
UPF0729-siRNA (mouse)	Custom made (Eurofin Genomics)

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Immunocytochemistry and microscopy

For immunocytochemistry, cells were grown on sterile glass coverslips under optimal growth conditions. DNA transfections were performed in various combinations and conditions as described in the results. After 24 h of transfection, cells were washed twice with PBS and fixed with 4% paraformaldehyde (J61899AK, Thermo Fischer Scientific) for 20 min at room temperature, followed by two PBS washes. The cells were then permeabilized with 0.2% Triton X-100 (A16046, Thermo Fischer Scientific) for 10 min at room temperature and washed twice with PBS. To block non-specific binding, the cells were incubated with 1% BSA (PI37525, Thermo Fischer Scientific) for 15 min at room temperature, followed by two PBS washes. For immunostaining, cells were incubated with primary antibodies (Table 2) (diluted 1:200 to 1:500, depending on the antibody) for 4 h at room temperature on a rocker. After incubation, cells were washed three times with PBS and blocked again with 1% BSA for 15 min at room temperature, followed by two PBS washes. Secondary antibodies (Table 2) (diluted 1:500) were then applied for 2 h at room temperature on a rocker. Following incubation, cells were washed twice with PBS and once with double-distilled water. Coverslips were mounted on glass slides using anti-fade mounting medium with DAPI (P36962, Thermo Fischer Scientific) to counterstain nuclei.

Table 2.

Antibodies

Target protein	Host organism for antibody production	Supplier	Identifier
Primary antibodies
ACBP	Mouse	Santa Cruz Biotechnology	sc-376,853
C18ORF32	Rabbit	Abcam	ab122677
CANX	Mouse	Thermo Fischer Scientific	MA3-027
ERGIC53	Mouse	Santa Cruz Biotechnology	sc-271,517
FLAG	Rabbit	Thermo Fischer Scientific	740,001
GOLGA1	Mouse	Thermo Fischer Scientific	14–9767-82
LAMP1	Mouse	Thermo Fischer Scientific	14–1079-80
LC3B	Mouse	Thermo Fischer Scientific	MA5-31541
RAB4	Mouse	NovoPro Biosciences	168,320
RAB5	Mouse	Thermo Fischer Scientific	14–9711-82
RAB7	Mouse	Cell Signaling Technology	95,746
RAB27A	Mouse	Thermo Fischer Scientific	MA1-172
SEC22B	Mouse	Santa Cruz Biotechnology	sc-101,267
WIPI2	Mouse	MyBioSource	MBS5310732
Secondary antibodies
Goat anti-Rabbit IgG (H + L) Secondary Antibody, HRP	Goat	Thermo Fischer Scientific	31,460
Goat anti-Mouse IgG (H + L) Secondary Antibody, HRP	Goat	Thermo Fischer Scientific	62–6520
Goat anti-Mouse IgG (H + L) Cross-Adsorbed Secondary Antibody, Alexa Fluor™ 488	Goat	Thermo Fischer Scientific	A-11,001
Goat anti-Mouse IgG (H + L) Cross-Adsorbed Secondary Antibody, Alexa Fluor™ 555	Goat	Thermo Fischer Scientific	A-21,422
Goat anti-Rabbit IgG (H + L) Cross-Adsorbed Secondary Antibody, Alexa Fluor™ 488	Goat	Thermo Fischer Scientific	A-11,008
Goat anti-Rabbit IgG (H + L) Cross-Adsorbed Secondary Antibody, Alexa Fluor™ 555	Goat	Thermo Fischer Scientific	A-21,428

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Nile red staining: Nile red staining was used to visualize lipid droplets in cells. Cells were fixed with 4% paraformaldehyde (PFA) for 15 min at room temperature, followed by two washes with PBS to remove residual PFA. A working solution of Nile Red (1 µg/mL) was freshly prepared by diluting a stock solution in PBS or 75% glycerol. The cells were then incubated with this Nile Red solution for 10 min at room temperature in the dark. After staining, the cells were washed twice with PBS. Images were acquired with appropriate filter sets for Nile Red.

ER morphology was assessed using cells CANX immunofluorescence. The degree of ER structural disruption was quantified as an ER fragmentation index using ImageJ software. Briefly, the ER area within each cell was segmented, and the number of discontinuous ER puncta was determined using the ‘Analyze Particles’ function. The ER fragmentation index was calculated as the ratio of fragmented ER puncta to total ER area per cell. Cells displaying a continuous reticular network were considered to have intact ER, whereas those exhibiting discontinuous or punctate structures were classified as fragmented. At least 50 cells per condition were analyzed across three independent experiments.

Fluorescence imaging, including the live-cell imaging, was performed using an LSM900 confocal laser scanning microscope (Zeiss) equipped with a Plan-Apochromat 63x/1.4 Oil DIC M27 (FWD = 0.19 mm) objective (Zeiss) as described earlier [35, 36]. Images were processed using Zen Lite software (Zeiss). Pearson’s correlation coefficient for protein-protein and protein-lipid colocalization was analyzed using the Coloc2 plugin in ImageJ. The number of LC3B, WIPI2 puncta, and Nile Red-positive lipid droplets were quantified using the Multi-point Tool in ImageJ.

Immunoprecipitation and Immunoblotting

Nondenaturing immunoprecipitation: For immunoprecipitation assays, protein lysates were prepared from cells under nondenaturing conditions. Cells were first harvested and lysed in ice-cold lysis buffer (50 mM Tris-HCl, pH 7.4, 150 mM NaCl, 1% Triton X-100, and a protease inhibitor cocktail). The lysate was clarified by centrifugation at 14,000 rpm for 15 min at 4 °C, and the supernatant was collected. A total of 2 mg of protein from the clarified lysate was used for each immunoprecipitation reaction. The protein concentration was determined by a BCA protein assay (23225, Thermo Fisher Scientific), and samples were normalized across all experimental conditions. Immunoprecipitations were carried out using anti-SEC22B antibody. The antibody was first crosslinked to magnetic beads using the Pierce Crosslink Magnetic IP/Co-IP Kit (Thermo Fisher Scientific, 88805) following the manufacturer’s protocol. Briefly, the SEC22B antibody was coupled to Protein A/G magnetic beads and then crosslinked using DSS (disuccinimidyl suberate) according to the kit’s specifications. The antibody-bead complexes were incubated with the lysate at 4 °C overnight with gentle rotation to allow optimal binding. After incubation, the beads were washed extensively with the provided wash buffer (50 mM Tris-HCl, 150 mM NaCl, 1% NP-40) to remove nonspecifically bound proteins. Immunoprecipitated protein complexes were eluted using elution buffer containing low pH (0.1 M glycine, pH 2.8) and neutralized with 1 M Tris-HCl, pH 8.0. Eluted proteins were subsequently analyzed by SDS-PAGE and immunoblotting to validate the presence of the target protein and its interaction partners.

Immunoblotting: For immunoblotting, cells were lysed in RIPA buffer [50 mM Tris-HCl (pH 7.4), 150 mM NaCl, 1% NP-40, 0.5% sodium deoxycholate, 0.1% SDS, 1 mM EDTA, and protease inhibitor cocktail] on ice for 30 min with repeated vortexing. The cell lysate was clarified by centrifugation at 14,000 rpm for 15 min at 4 °C, and the supernatant was collected. 60 µg of protein from the supernatant was resolved by 12% SDS-PAGE. Proteins were transferred from the gel to a PVDF membrane using transfer buffer [25 mM Tris, 192 mM glycine, 20% methanol, pH 8.3] at constant voltage. After transfer, the membrane was blocked for 1 h at room temperature with 5% skim milk prepared in TBS buffer [20 mM Tris-HCl, 150 mM NaCl, pH 7.4]. The membrane was then washed twice with TBST buffer [TBS with 0.1% Tween-20]. Primary antibodies [Table 2], diluted 1:1000 to 1:3000 in TBS, were applied, and the membrane was incubated overnight at 4 °C with gentle rocking. After incubation, the membrane was washed three times with TBST. Next, the membrane was incubated with secondary antibodies [Table 2] (diluted 1:1000 in TBS) for 2 h at room temperature. Following this, the membrane was washed twice with TBST and once with double-distilled water. Chemiluminescent signals were developed using SuperSignal West Femto Maximum Sensitivity Substrate (34094, Thermo Fisher Scientific), and the signals were detected using the ChemiDoc XRS + imaging system (Bio-Rad) [37, 38].

Gas chromatography-mass spectrometry (GC-MS)-based quantification of free fatty acids

For gas chromatography-mass spectrometry (GC-MS)-based quantification of free fatty acids (FFAs) in extracellular media, 100 µL of internal standard was added to 0.5 mL of extracellular medium. The sample was then mixed with an equal volume of methanol and acidified with HCl to a final concentration of 25 mM. The sample was prepared in a 16 mm x 125 mm glass tube, with three additional control samples containing only internal standard and dPBS. Next, 1 mL of iso-octane was added to the tube, and the sample was vortexed and centrifuged at 3000 g for 1 min to separate the layers. The top layer (containing the fatty acids) was transferred to a 10 mm x 75 mm glass tube. This extraction step was repeated to ensure maximum recovery of the fatty acids.

For free fatty acids, the top layer was dried under vacuum. 100 µL of internal standard was added to the methanol fraction, followed by 500 µL of 1 N KOH. The sample was vortexed and incubated for 1 h. After incubation, 500 µL of 1 N HCl was added, and the pH was checked to ensure it was below 5. Once the samples were dried under vacuum, derivatization was performed by adding 25 µL of 1% pentafluorobenzyl bromide in acetonitrile and 25 µL of 1% di-isopropylethylamine in acetonitrile. The tubes were capped, vortexed, and allowed to stand at room temperature for 20 min. The samples were then dried again under vacuum, and the derivatized products were dissolved in 50 µL of iso-octane. The samples were transferred to labeled vials with 250 µL glass inserts, capped, and placed in the GC-MS sample tray for analysis.

GC-MS analysis was performed using an Agilent 6890 N Gas Chromatograph equipped with a Zebron ZB-1 column (15 m x 0.25 mm ID x 0.10 mm film thickness) and Helium carrier gas at a flow rate of 0.9 mL/min. The injector temperature was set at 250 °C in pulsed split-less mode (25 psi pulse), and the sample transfer line was maintained at 280 °C. The GC temperature gradient started at 150 °C, ramping at 10 °C/min to 270 °C, followed by a faster ramp of 40 °C/min to 310 °C, with a one-minute hold.

The mass spectrometric analysis was performed using an Agilent 5975 Mass Selective Detector under negative ion chemical ionization (NICI) conditions with methane as the reagent gas (40% flow). The mass spectrometer was operated with a solvent delay of 1 min, a quad temperature of 150 °C, and a source temperature of 280 °C. Ion monitoring was conducted in Selected Ion Monitoring (SIM) mode with a dwell time of 10 ms per ion.

Enzyme linked immunosorbent assay for quantification of triacylglycerols

The triglyceride content in the extracellular medium was quantified using Triglyceride Assay Kit – Quantification kit (ab65336, Abcam) following the manufacturer’s protocol. ELISA kits for C18ORF32, STX4, and STX17 were as follows: Human C18orf32 ELISA Kit (E008883, Biobool), Human STX4 ELISA Kit (E037217, Biobool), and Human STX17 ELISA Kit (E037202, Biobool). All ELISA assays were done according to the manufacturer’s instructions.

Mice studies

A combination of 6 siRNAs targeting UPF0729 were designed to minimize off-target potential. Chemically synthesized siRNAs were further modified with 2′-O-methyl bases and phosphorothioate linkages to enhance stability in vivo, reduce immune stimulation, and minimize off-target effects. For functional screening, effectivity of siRNAs was evaluated in Hepa1-6 cells. For in vivo delivery, the selected siRNA was formulated into lipid nanoparticles (LNPs). The aqueous phase consisted of siRNA duplexes in citrate buffer, and the ethanol phase contained the lipid mixture composed of C12-200, 1,2-distearoyl-sn-glycero-3-phosphocholine (DSPC, Avanti Polar Lipids, 816-94-4), cholesterol (Sigma Aldrich, C8667), and C14-PEG2000 (Avanti Polar Lipids, 474922-82-2). The two phases were rapidly mixed to enable spontaneous self-assembly of LNPs encapsulating siRNA. Formulations were subsequently dialyzed overnight against PBS to remove ethanol and unincorporated lipids. The hydrodynamic size distribution and polydispersity index (PDI) of the LNPs were measured using dynamic light scattering, yielding an average particle diameter of 80–150 nm suitable for systemic injection.

For in vivo experiments, Swiss Webster mice (3 males and 2 females per group, 8 weeks old) were purchased from Charles River Laboratories. All procedures were carried out in accordance with ethical guidelines, and study protocols were approved by the Accelgen Bharat Bioinnovations. Mice were housed in a facility under a climate-controlled environment with a 12-h light/12-h dark cycle and were provided standard rodent chow and water ad libitum. Mice received LNP-formulated siRNA targeting UPF0729 or control-siRNA at a dose of 0.2 mg/kg body weight via tail vein injection. Injections were administered on day − 3, 5, 7, 9, 11, 13. Throughout the study, body weight, food intake, and water consumption were recorded at regular intervals. Blood samples were collected by submandibular bleeding for fatty acid analysis. At the endpoint (day 15), animals were euthanized by CO₂ overdose, and tissues (liver) were harvested for histological, biochemical, and molecular analyses.

For histological analysis, liver tissues were fixed in 4% buffered paraformaldehyde at 4 °C overnight and subsequently embedded in paraffin. Tissue blocks were sectioned into 5-µm-thick slices using a rotary microtome. Sections were mounted on glass slides and subjected to hematoxylin-eosin (H&E) staining following standard protocol. Hematoxylin and eosin staining and imaging of liver sections were done from all the male and female mice. Serum biochemical analyses were performed using samples from all the five mice. The Transcript and protein expression analysis were conducted using liver tissue lysates from all the animals. Analyses of triglycerides and free fatty acid levels were also done in all the five mice.

Bioinformatics analysis

Structures:Structures of C18ORF32 (AF-Q8TCD1-F1) and SEC22B (AF-O75396-F1) were curated from the AlphaFold database [39].

Gene ontology: C18ORF32-intercating proteins were curated from the BioGRID [40], IntAct [41], MINT [42], and STRING [43] databases. Gene ontology enrichment analysis of C18ORF32-intercating proteins was done in GENE ONTOLOGY webserver.

Molecular Docking: The docking simulation of C18ORF32 on SEC22B was done using the algorithms of ClusPro [44]. Docking of C18ORF32 on the membrane monolayer was done in Discovery Studio Biovia 2021.

Statistical analysis

The statistical significance of differences between group means was determined using either a two-tailed, homoscedastic Student’s t-test or a one-way analysis of variance (ANOVA) followed by post hoc testing for multiple group comparisons. The Student’s t-test was used for comparisons between two groups, while ANOVA was applied when more than two groups were analyzed. A p-value of < 0.05 was considered statistically significant. Data were analyzed using GraphPad Prism software, and all results are presented as mean ± standard error of the mean (SEM).

Supplementary Information

Supplementary Material 1^{(86.4KB, pdf)}

Acknowledgements

The authors gratefully acknowledge the DBT-IPLS (Department of Biotechnology-Interdisciplinary Program for Life Sciences) facility at the University of Calcutta for providing the microscopy and Isothermal Titration Calorimetry (ITC) facilities.

Authors’ contributions

AK: Methodology, investigation, formal analysis.SKG: Methodology, investigation, formal analysis.YPM: Formal analysis, validation.DKG: Methodology, resource acquisition, formal analysis, validation, data curation, project supervision, writing the original draft.

Funding

None received.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Abhishek Kumar and Shailesh Kumar Gupta contributed equally to this work.

References

1.Zadoorian A, Du X, Yang H. Lipid droplet biogenesis and functions in health and disease. Nat Rev Endocrinol. 2023;19:443–59. [DOI] [PMC free article] [PubMed] [Google Scholar]
2.Olzmann JA, Carvalho P. Dynamics and functions of lipid droplets. Nat Rev Mol Cell Biol. 2019;20:137–55. [DOI] [PMC free article] [PubMed] [Google Scholar]
3.Gao M, Huang X, Song BL, Yang H. The biogenesis of lipid droplets: lipids take center stage. Prog Lipid Res. 2019;75:100989. [DOI] [PubMed] [Google Scholar]
4.Kumari RM, Khatri A, Chaudhary R, Choudhary V. Concept of lipid droplet biogenesis. Eur J Cell Biol. 2023;102:151362. [DOI] [PMC free article] [PubMed] [Google Scholar]
5.Walther TC, Chung J, Farese RV Jr. Lipid droplet biogenesis. Annu Rev Cell Dev Biol. 2017;33:491–510. [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Salo VT, Belevich I, Li S, Karhinen L, Vihinen H, Vigouroux C, Magre J, Thiele C, Holtta-Vuori M, Jokitalo E, Ikonen E. Seipin regulates ER-lipid droplet contacts and cargo delivery. EMBO J. 2016;35:2699–716. [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Chen F, Yan B, Ren J, Lyu R, Wu Y, Guo Y, et al. FIT2 organizes lipid droplet biogenesis with ER tubule-forming proteins and septins. J Cell Biol. 2021. 10.1083/jcb.201907183. [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Khaddaj R, Stribny J, Cottier S, Schneiter R. Perilipin 3 promotes the formation of membrane domains enriched in diacylglycerol and lipid droplet biogenesis proteins. Front Cell Dev Biol. 2023;11:1116491. [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Xu N, Zhang SO, Cole RA, McKinney SA, Guo F, Haas JT, et al. The FATP1-DGAT2 complex facilitates lipid droplet expansion at the ER-lipid droplet interface. J Cell Biol. 2012;198:895–911. [DOI] [PMC free article] [PubMed] [Google Scholar]
10.Dalhaimer P. Lipid droplets in disease. Cells. 2019. 10.3390/cells8090974. [DOI] [PMC free article] [PubMed] [Google Scholar]
11.Onal G, Kutlu O, Gozuacik D, Dokmeci S Emre. Lipid droplets in health and disease. Lipids Health Dis. 2017;16:128. [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Grabner GF, Xie H, Schweiger M, Zechner R. Lipolysis: cellular mechanisms for lipid mobilization from fat stores. Nat Metab. 2021;3:1445–65. [DOI] [PubMed] [Google Scholar]
13.Zhang S, Peng X, Yang S, Li X, Huang M, Wei S, Liu J, He G, Zheng H, Yang L, Li H, Fan Q. The regulation, function, and role of lipophagy, a form of selective autophagy, in metabolic disorders. Cell Death Dis. 2022;13:132. [DOI] [PMC free article] [PubMed] [Google Scholar]
14.Lass A, Zimmermann R, Oberer M, Zechner R. Lipolysis - a highly regulated multi-enzyme complex mediates the catabolism of cellular fat stores. Prog Lipid Res. 2011;50:14–27. [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Shin DW. Lipophagy: molecular mechanisms and implications in metabolic disorders. Mol Cells. 2020;43:686–93. [DOI] [PMC free article] [PubMed] [Google Scholar]
16.Liu K, Czaja MJ. Regulation of lipid stores and metabolism by lipophagy. Cell Death Differ. 2013;20:3–11. [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Salian S, Guo XY, Murakami Y, Kinoshita T, Kaur P, Shukla A, Girisha KM, Fujita M, Campeau PM. C18orf32 loss-of-function is associated with a neurodevelopmental disorder with hypotonia and contractures. Hum Genet. 2022;141:1423–9. [DOI] [PubMed] [Google Scholar]
18.Bersuker K, Peterson CWH, To M, Sahl SJ, Savikhin V, Grossman EA, Nomura DK, Olzmann JA. A proximity labeling strategy provides insights into the composition and dynamics of lipid droplet proteomes. Dev Cell. 2018;44:97–e112117. [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Adibhatla RM, Hatcher JF. Altered lipid metabolism in brain injury and disorders. Subcell Biochem. 2008;49:241–68. [DOI] [PMC free article] [PubMed] [Google Scholar]
20.Huang X, Dai FF, Gaisano G, Giglou K, Han J, Zhang M, Kittanakom S, Wong V, Wei L, Showalter AD, Sloop KW, Stagljar I, Wheeler MB. The identification of novel proteins that interact with the GLP-1 receptor and restrain its activity. Mol Endocrinol. 2013;27:1550–63. [DOI] [PMC free article] [PubMed] [Google Scholar]
21.Sakai Y, Shaw CA, Dawson BC, Dugas DV, Al-Mohtaseb Z, Hill DE, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci Transl Med. 2011;3:86ra49. [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Behrends C, Sowa ME, Gygi SP, Harper JW. Network organization of the human autophagy system. Nature. 2010;466:68–76. [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Kimura T, Jia J, Kumar S, Choi SW, Gu Y, Mudd M, Dupont N, Jiang S, Peters R, Farzam F, Jain A, Lidke KA, Adams CM, Johansen T, Deretic V. Dedicated snares and specialized TRIM cargo receptors mediate secretory autophagy. EMBO J. 2017;36:42–60. [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Jian F, Wang S, Tian R, Wang Y, Li C, Li Y, Wang S, Fang C, Ma C, Rong Y. The STX17-SNAP47-VAMP7/VAMP8 complex is the default SNARE complex mediating autophagosome-lysosome fusion. Cell Res. 2024;34:151–68. [DOI] [PMC free article] [PubMed] [Google Scholar]
25.Hong H, Park S, Jimenez RH, Rinehart D, Tamm LK. Role of aromatic side chains in the folding and thermodynamic stability of integral membrane proteins. J Am Chem Soc. 2007;129:8320–7. [DOI] [PubMed] [Google Scholar]
26.Tracey TJ, Steyn FJ, Wolvetang EJ, Ngo ST. Neuronal lipid metabolism: multiple pathways driving functional outcomes in health and disease. Front Mol Neurosci. 2018;11:10. [DOI] [PMC free article] [PubMed] [Google Scholar]
27.Udupa P, Shrikondawar AN, Nayak SS, Shah H, Ranjan A, Girisha KM, et al. Deep intronic mutation in CRTAP results in unstable isoforms of the protein to induce type I collagen aggregation in a lethal type of osteogenesis imperfecta type VII. Biochim Biophys Acta Mol Basis Dis. 2023;1869:166741. [DOI] [PMC free article] [PubMed] [Google Scholar]
28.Ghosh DK, Udupa P, Shrikondawar AN, Bhavani GS, Shah H, Ranjan A, Girisha KM. Mutant MESD links cellular stress to type I collagen aggregation in osteogenesis imperfecta type XX. Matrix Biol. 2023;115:81–106. [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Ghosh DK, Roy A, Ranjan A. Aggregation-prone regions in HYPK help it to form sequestration complex for toxic protein aggregates. J Mol Biol. 2018;430(7):963–86. [DOI] [PubMed] [Google Scholar]
30.Kumar A, Gaurav V, Mathuria YP, Jain BP, Gupta SK, Ghosh DK. NOL10 variant disrupts ribosome biogenesis and underlies hippocampal sclerosis. J Hum Genet 2025 Oct 16. 10.1038/s10038-025-01418-x [DOI] [PubMed]
31.Ghosh DK, Roy A, Ranjan A. The ATPase VCP/p97 functions as a disaggregase against toxic Huntingtin-exon1 aggregates. FEBS Lett. 2018;592:2680–92. [DOI] [PubMed] [Google Scholar]
32.Ghosh DK, Roy A, Ranjan A. Disordered nanostructure in Huntingtin interacting protein K acts as a stabilizing switch to prevent protein aggregation. Biochemistry. 2018;57:2009–23. [DOI] [PubMed] [Google Scholar]
33.Udupa P, Kumar A, Parit R, Ghosh DK. Acyl-CoA binding protein regulates nutrient-dependent autophagy. Metabolism. 2023;145:155338. [DOI] [PubMed] [Google Scholar]
34.Saha S, Jain BP, Ghosh DK, Ranjan A. Conformational plasticity links structural instability of NAA10(F128I) and NAA10(F128L) mutants to their catalytic deregulation. Comput Struct Biotechnol J. 2024;23:4047–63. [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Saha S, Mandal A, Ranjan A, Ghosh DK. Membrane tension sensing formin-binding protein 1 is a neuronal nutrient stress-responsive Golgiphagy receptor. Metabolism. 2025;162:156040. [DOI] [PubMed]
36.Udupa P, Shrikondawar AN, Ranjan A, Ghosh DK. Assessing type I collagen expression and quality in cellular models of osteogenesis imperfecta. Clin Genet. 2024;105:329–34. [DOI] [PubMed] [Google Scholar]
37.Ghosh DK, Ranjan A. An IRES-dependent translation of HYPK mRNA generates a truncated isoform of the protein that lacks the nuclear localization and functional ability. RNA Biol. 2019;16:1604–21. [DOI] [PMC free article] [PubMed] [Google Scholar]
38.Ghosh DK, Pande S, Kumar J, Yesodharan D, Nampoothiri S, Radhakrishnan P, et al. The E262K mutation in Lamin A links nuclear proteostasis imbalance to laminopathy-associated premature aging. Aging Cell. 2022;21:e13688. [DOI] [PMC free article] [PubMed] [Google Scholar]
39.Varadi M, Bertoni D, Magana P, Paramval U, Pidruchna I, Radhakrishnan M, Tsenkov M, Nair S, Mirdita M, Yeo J, Kovalevskiy O, Tunyasuvunakool K, Laydon A, Zidek A, Tomlinson H, Hariharan D, Abrahamson J, Green T, Jumper J, Birney E, Steinegger M, Hassabis D, Velankar S. AlphaFold protein structure database in 2024: providing structure coverage for over 214 million protein sequences. Nucleic Acids Res. 2024;52:D368–75. [DOI] [PMC free article] [PubMed] [Google Scholar]
40.Oughtred R, Rust J, Chang C, Breitkreutz BJ, Stark C, Willems A, et al. The biogrid database: a comprehensive biomedical resource of curated protein, genetic, and chemical interactions. Protein Sci. 2021;30:187–200. [DOI] [PMC free article] [PubMed] [Google Scholar]
41.Del Toro N, Shrivastava A, Ragueneau E, Meldal B, Combe C, Barrera E, et al. The IntAct database: efficient access to fine-grained molecular interaction data. Nucleic Acids Res. 2022;50:D648–53. [DOI] [PMC free article] [PubMed] [Google Scholar]
42.Chatr-aryamontri A, Ceol A, Palazzi LM, Nardelli G, Schneider MV, Castagnoli L, Cesareni G. MINT: the molecular interaction database. Nucleic Acids Res. 2007;35:D572–574. [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Szklarczyk D, Kirsch R, Koutrouli M, Nastou K, Mehryary F, Hachilif R, et al. The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Res. 2023;51:D638–46. [DOI] [PMC free article] [PubMed] [Google Scholar]
44.Kozakov D, Hall DR, Xia B, Porter KA, Padhorny D, Yueh C, et al. The cluspro web server for protein-protein docking. Nat Protoc. 2017;12:255–78. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1^{(86.4KB, pdf)}

Data Availability Statement

No datasets were generated or analysed during the current study.

[CR1] 1.Zadoorian A, Du X, Yang H. Lipid droplet biogenesis and functions in health and disease. Nat Rev Endocrinol. 2023;19:443–59. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR2] 2.Olzmann JA, Carvalho P. Dynamics and functions of lipid droplets. Nat Rev Mol Cell Biol. 2019;20:137–55. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR3] 3.Gao M, Huang X, Song BL, Yang H. The biogenesis of lipid droplets: lipids take center stage. Prog Lipid Res. 2019;75:100989. [DOI] [PubMed] [Google Scholar]

[CR4] 4.Kumari RM, Khatri A, Chaudhary R, Choudhary V. Concept of lipid droplet biogenesis. Eur J Cell Biol. 2023;102:151362. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR5] 5.Walther TC, Chung J, Farese RV Jr. Lipid droplet biogenesis. Annu Rev Cell Dev Biol. 2017;33:491–510. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR6] 6.Salo VT, Belevich I, Li S, Karhinen L, Vihinen H, Vigouroux C, Magre J, Thiele C, Holtta-Vuori M, Jokitalo E, Ikonen E. Seipin regulates ER-lipid droplet contacts and cargo delivery. EMBO J. 2016;35:2699–716. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR7] 7.Chen F, Yan B, Ren J, Lyu R, Wu Y, Guo Y, et al. FIT2 organizes lipid droplet biogenesis with ER tubule-forming proteins and septins. J Cell Biol. 2021. 10.1083/jcb.201907183. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR8] 8.Khaddaj R, Stribny J, Cottier S, Schneiter R. Perilipin 3 promotes the formation of membrane domains enriched in diacylglycerol and lipid droplet biogenesis proteins. Front Cell Dev Biol. 2023;11:1116491. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR9] 9.Xu N, Zhang SO, Cole RA, McKinney SA, Guo F, Haas JT, et al. The FATP1-DGAT2 complex facilitates lipid droplet expansion at the ER-lipid droplet interface. J Cell Biol. 2012;198:895–911. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR10] 10.Dalhaimer P. Lipid droplets in disease. Cells. 2019. 10.3390/cells8090974. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR11] 11.Onal G, Kutlu O, Gozuacik D, Dokmeci S Emre. Lipid droplets in health and disease. Lipids Health Dis. 2017;16:128. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR12] 12.Grabner GF, Xie H, Schweiger M, Zechner R. Lipolysis: cellular mechanisms for lipid mobilization from fat stores. Nat Metab. 2021;3:1445–65. [DOI] [PubMed] [Google Scholar]

[CR13] 13.Zhang S, Peng X, Yang S, Li X, Huang M, Wei S, Liu J, He G, Zheng H, Yang L, Li H, Fan Q. The regulation, function, and role of lipophagy, a form of selective autophagy, in metabolic disorders. Cell Death Dis. 2022;13:132. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR14] 14.Lass A, Zimmermann R, Oberer M, Zechner R. Lipolysis - a highly regulated multi-enzyme complex mediates the catabolism of cellular fat stores. Prog Lipid Res. 2011;50:14–27. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR15] 15.Shin DW. Lipophagy: molecular mechanisms and implications in metabolic disorders. Mol Cells. 2020;43:686–93. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR16] 16.Liu K, Czaja MJ. Regulation of lipid stores and metabolism by lipophagy. Cell Death Differ. 2013;20:3–11. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR17] 17.Salian S, Guo XY, Murakami Y, Kinoshita T, Kaur P, Shukla A, Girisha KM, Fujita M, Campeau PM. C18orf32 loss-of-function is associated with a neurodevelopmental disorder with hypotonia and contractures. Hum Genet. 2022;141:1423–9. [DOI] [PubMed] [Google Scholar]

[CR18] 18.Bersuker K, Peterson CWH, To M, Sahl SJ, Savikhin V, Grossman EA, Nomura DK, Olzmann JA. A proximity labeling strategy provides insights into the composition and dynamics of lipid droplet proteomes. Dev Cell. 2018;44:97–e112117. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR19] 19.Adibhatla RM, Hatcher JF. Altered lipid metabolism in brain injury and disorders. Subcell Biochem. 2008;49:241–68. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR20] 20.Huang X, Dai FF, Gaisano G, Giglou K, Han J, Zhang M, Kittanakom S, Wong V, Wei L, Showalter AD, Sloop KW, Stagljar I, Wheeler MB. The identification of novel proteins that interact with the GLP-1 receptor and restrain its activity. Mol Endocrinol. 2013;27:1550–63. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR21] 21.Sakai Y, Shaw CA, Dawson BC, Dugas DV, Al-Mohtaseb Z, Hill DE, et al. Protein interactome reveals converging molecular pathways among autism disorders. Sci Transl Med. 2011;3:86ra49. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR22] 22.Behrends C, Sowa ME, Gygi SP, Harper JW. Network organization of the human autophagy system. Nature. 2010;466:68–76. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR23] 23.Kimura T, Jia J, Kumar S, Choi SW, Gu Y, Mudd M, Dupont N, Jiang S, Peters R, Farzam F, Jain A, Lidke KA, Adams CM, Johansen T, Deretic V. Dedicated snares and specialized TRIM cargo receptors mediate secretory autophagy. EMBO J. 2017;36:42–60. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR24] 24.Jian F, Wang S, Tian R, Wang Y, Li C, Li Y, Wang S, Fang C, Ma C, Rong Y. The STX17-SNAP47-VAMP7/VAMP8 complex is the default SNARE complex mediating autophagosome-lysosome fusion. Cell Res. 2024;34:151–68. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR25] 25.Hong H, Park S, Jimenez RH, Rinehart D, Tamm LK. Role of aromatic side chains in the folding and thermodynamic stability of integral membrane proteins. J Am Chem Soc. 2007;129:8320–7. [DOI] [PubMed] [Google Scholar]

[CR26] 26.Tracey TJ, Steyn FJ, Wolvetang EJ, Ngo ST. Neuronal lipid metabolism: multiple pathways driving functional outcomes in health and disease. Front Mol Neurosci. 2018;11:10. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR27] 27.Udupa P, Shrikondawar AN, Nayak SS, Shah H, Ranjan A, Girisha KM, et al. Deep intronic mutation in CRTAP results in unstable isoforms of the protein to induce type I collagen aggregation in a lethal type of osteogenesis imperfecta type VII. Biochim Biophys Acta Mol Basis Dis. 2023;1869:166741. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR28] 28.Ghosh DK, Udupa P, Shrikondawar AN, Bhavani GS, Shah H, Ranjan A, Girisha KM. Mutant MESD links cellular stress to type I collagen aggregation in osteogenesis imperfecta type XX. Matrix Biol. 2023;115:81–106. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR29] 29.Ghosh DK, Roy A, Ranjan A. Aggregation-prone regions in HYPK help it to form sequestration complex for toxic protein aggregates. J Mol Biol. 2018;430(7):963–86. [DOI] [PubMed] [Google Scholar]

[CR30] 30.Kumar A, Gaurav V, Mathuria YP, Jain BP, Gupta SK, Ghosh DK. NOL10 variant disrupts ribosome biogenesis and underlies hippocampal sclerosis. J Hum Genet 2025 Oct 16. 10.1038/s10038-025-01418-x [DOI] [PubMed]

[CR31] 31.Ghosh DK, Roy A, Ranjan A. The ATPase VCP/p97 functions as a disaggregase against toxic Huntingtin-exon1 aggregates. FEBS Lett. 2018;592:2680–92. [DOI] [PubMed] [Google Scholar]

[CR32] 32.Ghosh DK, Roy A, Ranjan A. Disordered nanostructure in Huntingtin interacting protein K acts as a stabilizing switch to prevent protein aggregation. Biochemistry. 2018;57:2009–23. [DOI] [PubMed] [Google Scholar]

[CR33] 33.Udupa P, Kumar A, Parit R, Ghosh DK. Acyl-CoA binding protein regulates nutrient-dependent autophagy. Metabolism. 2023;145:155338. [DOI] [PubMed] [Google Scholar]

[CR34] 34.Saha S, Jain BP, Ghosh DK, Ranjan A. Conformational plasticity links structural instability of NAA10(F128I) and NAA10(F128L) mutants to their catalytic deregulation. Comput Struct Biotechnol J. 2024;23:4047–63. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR35] 35.Saha S, Mandal A, Ranjan A, Ghosh DK. Membrane tension sensing formin-binding protein 1 is a neuronal nutrient stress-responsive Golgiphagy receptor. Metabolism. 2025;162:156040. [DOI] [PubMed]

[CR36] 36.Udupa P, Shrikondawar AN, Ranjan A, Ghosh DK. Assessing type I collagen expression and quality in cellular models of osteogenesis imperfecta. Clin Genet. 2024;105:329–34. [DOI] [PubMed] [Google Scholar]

[CR37] 37.Ghosh DK, Ranjan A. An IRES-dependent translation of HYPK mRNA generates a truncated isoform of the protein that lacks the nuclear localization and functional ability. RNA Biol. 2019;16:1604–21. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR38] 38.Ghosh DK, Pande S, Kumar J, Yesodharan D, Nampoothiri S, Radhakrishnan P, et al. The E262K mutation in Lamin A links nuclear proteostasis imbalance to laminopathy-associated premature aging. Aging Cell. 2022;21:e13688. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR39] 39.Varadi M, Bertoni D, Magana P, Paramval U, Pidruchna I, Radhakrishnan M, Tsenkov M, Nair S, Mirdita M, Yeo J, Kovalevskiy O, Tunyasuvunakool K, Laydon A, Zidek A, Tomlinson H, Hariharan D, Abrahamson J, Green T, Jumper J, Birney E, Steinegger M, Hassabis D, Velankar S. AlphaFold protein structure database in 2024: providing structure coverage for over 214 million protein sequences. Nucleic Acids Res. 2024;52:D368–75. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR40] 40.Oughtred R, Rust J, Chang C, Breitkreutz BJ, Stark C, Willems A, et al. The biogrid database: a comprehensive biomedical resource of curated protein, genetic, and chemical interactions. Protein Sci. 2021;30:187–200. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR41] 41.Del Toro N, Shrivastava A, Ragueneau E, Meldal B, Combe C, Barrera E, et al. The IntAct database: efficient access to fine-grained molecular interaction data. Nucleic Acids Res. 2022;50:D648–53. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR42] 42.Chatr-aryamontri A, Ceol A, Palazzi LM, Nardelli G, Schneider MV, Castagnoli L, Cesareni G. MINT: the molecular interaction database. Nucleic Acids Res. 2007;35:D572–574. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR43] 43.Szklarczyk D, Kirsch R, Koutrouli M, Nastou K, Mehryary F, Hachilif R, et al. The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Res. 2023;51:D638–46. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR44] 44.Kozakov D, Hall DR, Xia B, Porter KA, Padhorny D, Yueh C, et al. The cluspro web server for protein-protein docking. Nat Protoc. 2017;12:255–78. [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

C18ORF32 modulates lipid droplet secretion via secretory autophagy and restrains hepatic steatosis in vivo

Abhishek Kumar

Shailesh Kumar Gupta

Yogendra Pratap Mathuria

Debasish Kumar Ghosh

Abstract

Background

Methods and results

Conclusions

Supplementary Information

Introduction

Results

C18ORF32 localizes to Endoplasmic reticulum and autophagosome

Fig. 1.

C18ORF32 is present on secretory autophagosomes to modulates secretory autophagy

Fig. 2.

The C-terminal unstructured region of C18ORF32 interacts with the C-terminal coiled-coil region of SEC22B of secretory autophagosome

Fig. 3.

The N-terminal helical region of C18ORF32 facilitates its localization to the lipid droplets

Fig. 4.

The clustered aromatic residues in the amphiphilic region of N-terminal helix of C18ORF32 are crucial for its structural stability and binding to lipid droplets

Fig. 5.

C18ORF32 mediates the release of lipid droplets to extracellular space by secretory autophagy

Fig. 6.

Loss of expression and function of C18ORF32 leads to NASH-like hepatic lipid accumulation in vivo

Fig. 7.

Discussion

Fig. 8.

Methods and materials

Gene cloning

Recombinant protein production and purification

Circular dichroism spectroscopy

Isothermal Titration calorimetry for protein-ligand interaction analysis

Microscale thermophoresis analysis of protein-peptide interaction

Cell culture and transfections

Table 1.

Immunocytochemistry and microscopy

Table 2.

Immunoprecipitation and Immunoblotting

Gas chromatography-mass spectrometry (GC-MS)-based quantification of free fatty acids

Enzyme linked immunosorbent assay for quantification of triacylglycerols

Mice studies

Bioinformatics analysis

Statistical analysis

Supplementary Information

Acknowledgements

Authors’ contributions

Funding

Data availability

Declarations

Competing interests

Footnotes

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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