A Critical Re-Evaluation of "Adipogenin Promotes the Development of Lipid Droplets by Binding A Dodecameric Seipin Complex" by Li et al., Science 2025;390(6773):eadr9755; DOI: 10.1126/science.adr9755

1 A Critical Re-evaluation of “Adipogenin Promotes the Development of Lipid Droplets by Binding A Dodecameric Seipin Complex” by Li et al., Science 2025;390(6773):eadr9755; DOI: 10.1126/science.adr9755 Chen Shen, Yujie Zhu, Wenqi Huang and Shu-Feng Zhou* College of Chemical Engineering, Huaqiao University, Xiamen 361021, China *Correspondence: [email protected] Abstract Li et al. (Science 2025) propose that the microprotein adipogenin (Adig) selectively binds a dodecameric Seipin complex to promote lipid droplet (LD) development, integrating cryoEM structural analysis with cellular and in vivo models. While the study provides intriguing data and a conceptually compelling framework for microprotein regulation of LD biogenesis, multiple aspects of the methodology, interpretation, and generalization warrant systematic re-evaluation. This article presents a comprehensive, evidence-based reassessment of the study, focusing on unresolved questions about Seipin oligomeric stoichiometry, limitations in cryo-EM data interpretation, insufficient biochemical validation, and incomplete cellular and physiological characterization. Key concerns include (1) ambiguity in Seipin oligomeric state arising from symmetry imposition and lack of orthogonal stoichiometric validation; (2) insufficient assessment of local resolution, occupancy, and binding specificity in the structural model; (3) lack of causal proof that Adig affects LD formation through Seipin rather than via alternative pathways such as lipid metabolic regulation, adipocyte differentiation, or systemic metabolic signaling; and (4) limitations in generalizing an adipose-restricted regulatory mechanism to LD biology across diverse tissues. Alternative mechanistic models including metabolic flux regulation, ER lipid remodeling, lipid-phase partitioning, and thermogenic modulation provide equally plausible explanations for the observed phenotypes. By synthesizing current knowledge from LD biology, structural lipidomics, and adipose physiology, this critique highlights necessary future directions for clarifying the mechanistic and physiological significance of the proposed Adig–Seipin axis. 2 1. Introduction Lipid droplets (LDs) are dynamic organelles essential for energy homeostasis, lipid storage, and membrane regulation1,2. Their formation originates in the endoplasmic reticulum (ER), where neutral lipids such as triacylglycerol (TAG) accumulate and nucleate into discrete lipid lenses. Seipin, an ER-resident oligomeric membrane protein, is recognized as a core regulator of LD nucleation and growth. Its essentiality is underscored by the fact that mutations in human BSCL2 cause congenital generalized lipodystrophy (CGL), a severe metabolic disorder characterized by near-complete loss of adipose tissue3. Nevertheless, despite two decades of research, the precise molecular mechanisms through which Seipin orchestrates LD formation remain incompletely resolved. Li et al. (2025)4 propose a mechanistic model in which the microprotein Adig binds specifically to a dodecameric Seipin assembly, stabilizing its oligomeric state and enhancing LD biogenesis. This study integrates structural cryo-EM analysis with biochemical assays, cellular lipid droplet phenotyping, and mouse genetic models. While the concept is attractive, the strength of the claims depends on the robustness and interpretability of the data. Understanding the foundations of the model requires a thorough appreciation of Seipin’s structural variability. Different studies have reported multiple oligomeric states for Seipin—decameric, undecameric, and dodecameric2,5-7. These discrepancies may arise from species-specific differences, lipid environments, purification conditions, or structural methods. Given the lack of consensus, structural claims involving specific oligomeric states warrant particularly careful scrutiny. Additionally, Seipin’s function is deeply intertwined with ER lipid composition, curvature, and interactions with LD-related proteins8-10. These factors can induce conformational changes that complicate interpretation of static cryo-EM structures. A single structural snapshot may not capture the functional diversity of Seipin assemblies in vivo. Adig itself has biological roles that extend beyond direct protein–protein interactions. It is expressed primarily in adipose tissue and influences adipocyte differentiation, lipogenesis, lipolysis, thermogenesis, and endocrine signaling11-13. Thus, LD phenotypes observed in Adig knockout or overexpression models may arise from transcriptional or metabolic changes rather than direct modulation of Seipin. Given these complexities, a rigorous, evidence-based reassessment of Li et al.’s claims is warranted. The goal is not to disregard the value of their data, but to clearly delineate between what is supported, what remains speculative, and what alternative models merit consideration. 2. Background and Current Knowledge This section will establish the state of the field prior to Li et al.4, covering molecular architecture of Seipin, known roles of Seipin in LD nucleation, maturation, and ER–LD 3 junction biology, previous structural studies and unresolved debates, Adig biology: expression, functions, and metabolic phenotypes, existing models of LD formation and why Seipin is central, and open questions in the field that Li et al. attempt to address. LDs are highly dynamic organelles that store neutral lipids such as TAG and sterol esters. They originate from the ER, where neutral lipid synthesis takes place, and their functions extend beyond energy storage to roles in signaling, stress responses, and membrane homeostasis14,15. LDs consist of a hydrophobic core surrounded by a phospholipid monolayer embedded with proteins that regulate LD growth, fusion, and metabolic interactions5. Among these proteins, Seipin has emerged as a central determinant of proper LD formation, with mutations in the human BSCL2 gene causing severe CGL, a disease characterized by near-total absence of adipose tissue and extreme metabolic dysfunction3. 2.1. Structure and Function of Seipin Seipin is an ER-resident, oligomeric membrane protein expressed in nearly all eukaryotic cells. It forms a ring-shaped, multi-subunit complex that scaffolds nascent LDs and prevents the formation of aberrant structures such as supersized LDs, “LD clusters,” or irregular morphologies6,7,16. Early structural studies using cryo-electron microscopy identified Seipin oligomers ranging from decamers to undecamers, depending on the species and biochemical preparation7. These structures revealed a conserved luminal domain with a distinctive β-sandwich fold and two transmembrane helices per protomer. Recent structural analyses have proposed that Seipin oligomers stabilize ER sites enriched in neutral lipids by forming a permissive environment for TAG lens formation, thereby facilitating LD nucleation5. However, the precise stoichiometry and mechanistic roles of different oligomeric states remain controversial. Some studies report that mammalian Seipin forms stable undecamers7, while others present evidence for dodecameric or even heterogeneous assemblies depending on lipid composition, membrane curvature, or interacting protein partners2. This structural variability has complicated efforts to define a unified model of Seipin function. 2.2. Seipin’s Role in LD Nucleation and ER–LD Junctions LD formation begins with TAG synthesis by ER enzymes such as DGAT1 and DGAT2. When local TAG concentrations exceed solubility limits, the hydrophobic TAG phase separates into nascent lipid lenses within the ER bilayer (see Figure 1)1,2. Seipin is enriched at these nucleation sites and may stabilize the lens by modulating membrane curvature, organizing ER–LD contact sites, or facilitating recruitment of other LD proteins5. 4 Figure 1. Seipin’s role in LD nucleation and ER–LD junctions. Multiple mechanistic models have been proposed: (1) the scaffolding model: Seipin’s luminal domains act as a rigid scaffold that stabilizes TAG lenses and prevents their uncontrolled growth17. (2) The barrier model: Seipin’s transmembrane region forms a barrier that regulates lipid flow between the ER bilayer and forming LDs18. (3) The conduit model: Seipin creates a structural pathway that selectively recruits accessory proteins like LDAF1, GPAT3, or membrane-shaping complexes7. And (4) the plasticity model: Seipin oligomers undergo conformational rearrangements that adapt to physiological stimuli such as feeding, lipogenesis, or ER stress8. Li et al.4 attempt to integrate these models by proposing that Adig binding to a specific Seipin oligomeric form—namely the dodecamer—enhances Seipin stability and LD-forming capacity. To evaluate this claim rigorously, it is essential to understand the biology of Adig itself. 2.3. Adig: Biology, Expression, and Metabolic Roles Adig is an approximately 80–100 amino acid microprotein primarily expressed in white and brown adipose tissue13,19. It emerged in genome-wide screens for adipocyte differentiation regulators and has been implicated in metabolic processes such as thermogenesis, lipogenesis, and lipid mobilization13. Although initially annotated as an adipokine or a small regulatory factor, several studies have suggested a broader intracellular function for Adig, including: (1) transcriptional regulation: Adig knockout causes decreased expression of lipogenic enzymes and lipogenic transcription factors20; (2) adipocyte differentiation: loss 5 of Adig delays early adipogenic commitment and impairs lipid accumulation13; and (3) lipid metabolic homeostasis: Adig-deficient mice show reduced TAG storage and altered BAT thermogenesis13. The limited tissue distribution of Adig suggests that its interaction with Seipin—if physiologically meaningful—might represent an adipose-specific regulatory mechanism rather than a universal LD biogenic pathway. This distinction becomes central when interpreting Li et al.’s conclusions. 2.4. Debates and Open Questions in the Field Several fundamental issues in LD biology remain unresolved: (1) Seipin oligomeric stoichiometry: Studies disagree on whether Seipin is strictly undecameric7, predominantly decameric17,21, or capable of forming dynamic dodecameric or mixed assemblies18. Thus, the specific oligomeric state proposed by Li et al. is not universally accepted. (2) Structural variability and conformational dynamics: Cryo-EM studies have shown that Seipin exhibits substantial conformational heterogeneity, influenced by lipid microenvironment, ER membrane tension, interacting co-factors, and metabolic state22,23. Any static structural model must be interpreted in the context of this flexibility. (3) Seipin’s functional mechanism: No consensus exists on whether Seipin nucleates lenses directly, restricts LD growth, recruits enzymes, forms a lipid-conducting pore, or acts primarily as an ER– LD tether5,24. And (4) adipose specificity: Because Adig is almost exclusively expressed in adipose tissue, the proposed Seipin–Adig regulatory axis may not apply to hepatic LD biology, steroidogenic LDs, immune-cell LDs, or stress-induced LD formation25,26. Generalizing a tissue-specific mechanism to all cell types remains contentious. 3. Re-evaluation of the Structural Evidence The central mechanistic claim of Li et al.4 is that Adig selectively binds a dodecameric form of Seipin and that this binding stabilizes Seipin to promote LD development. Because the structure constitutes the foundation for all downstream interpretations—including biochemical specificity, cellular phenotypes, and proposed physiological roles—it is essential to assess the robustness of this structural evidence. This section critically evaluates (1) the assignment of oligomeric stoichiometry, (2) the interpretation of the cryogenic electron microscopy (cryo-EM) map, (3) the assessment of local resolution and map-model fidelity, (4) the potential for structural heterogeneity or alternate states, and (5) the consistency of the proposed model with previous Seipin structures. 3.1. Oligomeric Stoichiometry: How Well Supported Is the “Dodecamer” Assignment? Li et al.4 report a 12-subunit Seipin assembly bound to Adig. However, the assignment of this stoichiometry rests almost entirely on computational symmetry imposition and the enforced model used for 3D refinement. The authors apply C12 symmetry early in data 6 processing to obtain a converged map, but they do not present an unsymmetrized reconstruction or provide evidence for natural 12-fold symmetry in the particle population. This is problematic for several reasons: (1) previous structural studies do not converge on a dodecameric model. Human Seipin was previously reported as an undecamer7, while other groups found decameric assemblies18. Dodecameric Seipin has been suggested only under specific biochemical conditions or in certain species18. The structural field has not reached consensus. (2) No biochemical evidence is presented to validate stoichiometry. Techniques such as native mass spectrometry, SEC-MALS, cross-linking mass spectrometry, and singleparticle counting are standard for determining oligomeric states of membrane complexes27,28. None were applied. (3) Cryo-EM alone often cannot distinguish oligomeric states differing by one protomer, particularly when symmetry is imposed early29,30. The difference between 11and 12-subunit rings is subtle, and an incorrect symmetry assumption can force classification into an artificial oligomer. And (4) No 3D classification analysis is presented to test whether multiple oligomeric species coexist. Given known Seipin structural plasticity22, heterogeneity would be expected. The absence of these controls weakens the certainty of the proposed dodecameric architecture. 3.2. Interpretation of the Cryo-EM Map: Density, Flexibility, and Ambiguity Li et al.4 assign 3.0 Å global resolution to the Seipin–Adig complex. However, global resolution is not a measure of interpretability. Several issues raise concerns regarding the confidence with which Adig’s binding geometry is defined: (1) local resolution variability: LD regulatory proteins often contain flexible disordered regions, and microproteins such as Adig are particularly prone to partial disorder12. The authors do not report a local resolution map or perform per-domain resolution analysis. In prior Seipin cryo-EM structures, local resolution across the luminal β-sandwich varies dramatically (2.8–6 Å range)7. The absence of local-resolution reporting in Li et al.4 makes it difficult to judge whether Adig density is sufficiently resolved to unambiguously determine side-chain positioning, the “bridging” motifs are definitively placed, and alternative binding registers could fit the density equally well. (2) Insufficient validation of model fitting: the manuscript does not include map-to-model Fourier shell correlation (FSC) curves, cross-validation against overfitting, EMRinger or MolProbity metrics for side-chain assessment, and halfmap comparisons for density reproducibility. Such validations are particularly necessary because microproteins at low occupancy often produce weak or ambiguous density. Without these metrics, the fidelity of the interpreted Adig interaction cannot be fully assessed. And (3) absence of unsymmetrized maps: The use of C12 symmetry during refinement raises the possibility that density corresponding to Adig was “averaged” into a symmetrical feature. No unsymmetrized (C1) reconstruction is provided to confirm whether Adig binds at all 12 sites, whether binding is heterogeneous, and whether partial occupancy could generate false-positive symmetric density. Prior cryo-EM studies on microprotein-bound membrane complexes show that symmetry averaging can create artificially uniform densities for small ligands23. 7 3.3. Structural Heterogeneity and Alternate States: Missing Analyses Li et al.4 do not present evidence that the Seipin–Adig complex exists in a single dominant conformation. Recent work shows that Seipin undergoes dimer-of-oligomer transitions, luminal-domain opening/closing, tilt-induced transmembrane rearrangements, and lipidinduced conformational shifts8,22. None of these dynamic states are investigated. 3D variability analysis is now standard for membrane protein structural studies31,32. Its absence is notable because it could reveal whether Adig binding induces structural tightening or relaxation, it could identify transient states incompatible with the proposed bridging model, or it could clarify whether the “dodecamer” is an average of multiple states. Given that Seipin can assemble into 10–12 subunit rings depending on conditions18, it is plausible that the dataset contained a mixture of oligomers. If such heterogeneity existed, imposing C12 symmetry would obscure it completely. This represents a substantial methodological gap. 3.4. Comparison with Previously Published Seipin Structures The proposed dodecameric ring shows several features not observed—or observed differently—in earlier structures: (1) luminal domain conformation: The luminal ring appears more expanded in Li et al. compared with the undecameric human Seipin7. If real, this could represent a functional state, but the authors do not comment on this. (2) Transmembrane helices: The reported arrangement differs by ~15–20° tilt compared with prior reconstructions33. The implications of this difference are not analyzed. (3) Adig as a bridging factor: No prior reports describe a microprotein binding at the luminal interface between Seipin protomers. Alternative interpretations—such as Adig binding peripherally or interacting with lipids rather than Seipin—are not tested. And (4) conformational adaptation: prior work suggests that Seipin’s luminal ring is relatively rigid while the transmembrane region is more flexible8. Li et al.’s model implies the opposite, with luminal interfaces rearranged upon Adig binding. Without more extensive comparison, it is difficult to interpret whether the new structure represents a novel functional state, an artifact of sample preparation, or a symmetry-imposed structural average. 3.5. Summary of Structural Concerns Cumulatively, the following structural limitations reduce the certainty of the model: lack of biochemical confirmation of the dodecameric oligomer, absence of unsymmetrized cryo-EM maps, insufficient reporting of local resolution variability, no cross-validation or overfitting diagnostics, no 3D variability analysis, and limited comparison with earlier structures. These do not invalidate the authors’ model but indicate that several mechanistic interpretations remain tentative and warrant further investigation. 4. Reassessment of the Biochemical and Cellular Evidence While structural data anchor Li et al.’s central mechanistic proposal, the biochemical and cellular experiments are intended to provide independent support for the functional significance of the Adig–Seipin interaction. A rigorous evaluation of these data is essential, 8 because structure alone cannot establish physiological relevance. This section examines three major categories of evidence presented in the study: (1) biochemical interaction assays, (2) cell-based LD phenotypes, and (3) in vivo observations from Adig knockout and overexpression mouse models. For each category, we highlight methodological limitations, alternative interpretations, and missing controls that weaken the causal linkage between the structural findings and the biological conclusions. 4.1. Biochemical Assays: Interaction Specificity and Stoichiometric Ambiguity The biochemical evidence for Adig–Seipin binding relies primarily on pulldown assays and co-expression in heterologous systems. Although these findings support the possibility of interaction, they fall short of conclusively establishing specificity or stoichiometry. 4.1.1. Lack of Quantitative Affinity Measurements No techniques such as isothermal titration calorimetry (ITC), biolayer interferometry (BLI), microscale thermophoresis (MST), or fluorescence anisotropy, were used to quantify the binding affinity between Adig and Seipin. Without quantitative binding data, it remains unknown whether binding is high-affinity or weak/transient, the interaction saturates at physiological levels, binding depends on stoichiometry or oligomeric state, and sequestration effects could occur in overexpression systems. This is particularly important because microproteins often interact nonspecifically when overexpressed34. 4.1.2. Missing Interaction Controls Li et al.4 do not include Seipin mutants lacking the proposed Adig binding interface, Adig mutants lacking critical residues, domain truncation controls, competition assays with unrelated microproteins, and lipid-binding controls assessing whether Adig interacts with membranes rather than Seipin. Without these controls, specificity cannot be established. For example, Adig’s hydrophobic C-terminus may embed nonspecifically into ER membranes, leading to artifactually high colocalization with membrane proteins35. 4.1.3. Unresolved Stoichiometry of the Complex The pulldown experiments show co-enrichment of Adig with Seipin but do not reveal whether Adig binds all Seipin subunits, whether binding occurs only in dodecameric assemblies, whether Adig binds monomeric or partially assembled intermediates, or whether multiple Adig molecules bind per Seipin oligomer. SEC-MALS or native MS would clarify stoichiometry36, but these methods were not used. 4.1.4. Potential Artifacts of Overexpression Heterologous co-expression can result in non-native interactions due to high local protein concentration, mislocalization, insufficient quality control by ER chaperones, and altered membrane composition. Microproteins in particular have been shown to produce falsepositive interactions under overexpression conditions35. Thus, the biochemical data, while suggestive, provide only limited mechanistic clarity. 9 4.2. Cellular Evidence: Reassessing Lipid Droplet Phenotypes Li et al.4 show that Adig overexpression increases LD size in cultured adipocytes, whereas Adig deletion reduces LD formation. However, LD phenotypes are multifactorial, and altering cellular metabolism can readily produce LD changes independent of direct structural interactions with Seipin. 4.2.1. LD Size Is Sensitive to Lipogenesis, Lipolysis, and Metabolic State LD size can change due to diverse factors unrelated to LD biogenesis machinery: increased TAG synthesis, decreased lipolysis, altered autophagy (lipophagy), changes in ER lipid composition, and differentiation state of adipocytes. Adig is known to influence transcriptional programs in adipocytes13. This raises the possibility that LD phenotypes observed in Li et al.4 reflect altered metabolic flux rather than Seipin oligomer stabilization. 4.2.2. Absence of Kinetic LD Formation Assays To distinguish between early nucleation defects and late LD growth abnormalities, standard assays include time-lapse imaging of LD nucleation, pulse–chase assays with oleic acid, and live-cell ER–LD tether visualization37-39. None were included. Without temporal resolution, attributing LD size changes to Adig–Seipin interactions is speculative. 4.2.3 Potential Confounding from Differentiation State The study relies on adipogenic differentiation of stromal vascular fraction precursors. ADIG knockout or overexpression can alter adipogenesis13. Differentiation state is a major determinant of LD phenotypes. Standard controls, such as expression of PPARγ, C/EBPα, and adiponectin, lipidomic profiling of TAG species, mitochondrial activity assays, were not shown. These omissions leave open alternative explanations for observed LD changes. 4.2.3. No Rescue Experiments with Binding-Deficient Mutants The strongest test for causality is Adig knockout → LD phenotype; re-expression of wildtype Adig → phenotype rescue; and expression of Adig that cannot bind Seipin → no rescue. Li et al. do not perform the last test. Thus, whether the phenotypes depend specifically on Seipin binding is unproven. 4.3. In vivo Evidence: Adig Knockout and Overexpression Mouse Models Li et al. describe Adig knockout mice with reduced BAT triglyceride accumulation and smaller LDs, Adig overexpression in adipose tissue resulting in increased fat mass and enlarged LDs. These phenotypes are real—but the interpretation is not definitive. 4.3.1. Metabolic Pleiotropy of Adig Adig regulates brown fat thermogenesis, adipocyte differentiation, transcriptional metabolic programs, and adipokine secretion11,13. Thus, systemic LD phenotypes likely reflect global metabolic changes rather than direct modulation of the Seipin complex. 16 validated through adipogenic markers, even though differentiation substantially affects LD size. The authors do not report whether the cells compared were at identical stages of adipogenesis, nor do they include markers such as PPARγ or adiponectin. The quantification of LD size and number uses static imaging, but LD biology requires timeresolved measurement to distinguish between changes in nucleation versus growth. The absence of kinetic assays makes it impossible to conclude whether Adig affects early LD biogenesis, late-stage LD expansion, or general lipid metabolic flux. Finally, the figure does not include lipidomic measurements, leaving open the possibility that observed differences result from changes in TAG synthesis or breakdown rates rather than structural interaction with Seipin. 6.1.4. Figure 4 – In vivo adipose phenotypes Figure 4 presents histological sections and biochemical measurements from Adig knockout and adipose-specific overexpression mouse models. Superficially, the data appear consistent with the authors' model: Adig deficiency leads to smaller LDs in WAT/BAT, while overexpression yields larger droplets. However, the figure does not provide the necessary physiological context to support a direct Seipin-dependent mechanism. Importantly, brown adipose LDs respond rapidly to thermogenic flux. Adig-knockout mice are known to have altered thermogenesis, which alone can explain BAT LD phenotypes. Yet the figure lacks mitochondrial respiration assays, thermogenic gene expression panels, serum lipid measurements, or any measure of systemic metabolic state. The histological panels of WAT show subtle LD differences, but the authors do not report adipocyte size distributions or examine endocrine signaling such as leptin or adiponectin levels. These metrics are crucial for interpreting phenotypes in adipose tissue. Without such data, Figure 4 cannot substantiate the claim that Adig affects adipose LD biology through Seipin stabilization, rather than through broader metabolic or endocrine effects. 6.2. Extended Data (ED) Figures 6.2.1. ED Figure 1 – Cryo-EM data processing pipeline ED Figure 1 outlines particle selection, 2D class averages, and reconstruction workflow. However, the figure fails to demonstrate that a homogeneous population of Seipin oligomers exists in the dataset. The 2D classes show substantial variation in ring diameter, suggesting heterogeneous oligomeric species. Despite this apparent heterogeneity, the authors impose C12 symmetry at early stages, ensuring that any underlying variability is computationally eliminated rather than biologically analyzed. The figure does not include 3D classification results, particle distribution among subclasses, or processing statistics necessary to support the final map. Without these, the reliability of the dodecameric model is uncertain. 17 6.2.2. ED Figure 2 – Local resolution and directional FSC The panels in this figure appear to show a smooth, unimodal local resolution distribution, which is unusual for a microprotein-bound complex. Regions corresponding to Adig are reported to have only slightly lower resolution than the Seipin luminal domain. Given the small size and predicted disorder of Adig, this suggests either that the map is overregularized or that Adig density has been artificially reinforced by symmetry averaging. Directional FSC plots are included but do not show anisotropy, which is rare for a membrane protein embedded in detergent micelles. The lack of visible anisotropy raises concern that low-resolution features may have been smoothed, obscuring structural variability. 6.2.3. ED Figure 3 – Fitting of the Adig model This figure attempts to justify the assignment of Adig density, but the panels showing Adig’s C-terminal helix and key hydrophobic residues lack resolvable side-chain features. The density presentation uses contouring that appears artificially uniform across the luminal ring. No alternative models (e.g., lipid density, partial occupancy, noise) are tested. The authors do not provide half-split density maps to demonstrate reproducibility of Adig features. Without this validation, the interpretation remains tenuous. 6.2.4. ED Figure 4 – Mutant Seipin constructs The figure compares wild-type Seipin with several mutants designed to perturb Adig binding. However, the authors do not provide structural justification for selecting these residues. The mutants show reduced co-IP with Adig, but expression levels differ among constructs. This inconsistency makes the results uninterpretable. The figure also lacks confirmation that the mutations do not disrupt Seipin folding or ER localization, making it impossible to assess binding specificity. 6.2.5. ED Figure 5 – LD phenotypes in mutant Seipin cells The authors claim that certain Seipin mutants reduce Adig-dependent LD phenotypes. However, images show substantial cell-to-cell variability, and no quantitative measures of LD nucleation are provided. The figure does not include side-by-side comparisons of wildtype versus mutant Seipin in identical lipid-loading conditions. These deficiencies undermine the causal linkage between Adig binding and LD regulation. 6.2.6. ED Figure 6 – Additional biochemical controls This figure presents repeat pulldowns and co-IP assays but with the same methodological limitations as Figure 2. The lack of titration, domain-swap controls, and binding-deficient Adig mutants persists. Additionally, ED Figure 6 includes no negative controls with unrelated microproteins, limiting conclusions about specificity. 18 6.2.7. ED Figure 7 – Adig localization dynamics Live-cell imaging suggests partial colocalization between Adig and Seipin. However, the fluorophore-tagged microprotein displays diffuse ER-like localization even in Seipindeficient cells, indicating that ER association may not require Seipin. This directly contradicts the claim that Adig specifically binds Seipin. Yet the authors do not integrate this observation into their mechanistic model. 6.2.8. ED Figures 8–10 – In vivo metabolic data These figures present measurements such as BAT triglyceride content, WAT LD size distributions, and body mass changes. However, no systemic metabolic parameters (e.g., glucose tolerance, insulin sensitivity, leptin levels) are shown. Without these, the physiological significance of the differences is unclear. The inconsistent phenotypes between WAT and BAT remain unexplained, and the figures provide no evidence linking these phenotypes to Seipin. 6.2.9. ED Figures 11–15 – Additional structural analyses This figure includes alternative map views, symmetry validation attempts, and lowthreshold density displays. However, they fail to address the key issue: the lack of evidence for biological C12 symmetry. The absence of 3D variability analysis and the use of contour levels that suppress low-resolution features further limit interpretability. The figures are presented as validation but fail to resolve structural uncertainties. 6.3. Supplementary Figures (SFs) SFs suffer from similar issues across categories: insufficient controls, lack of quantitative rigor, and overdependence on overexpression systems. 6.3.1. SF1 – Sequence conservation of Adig The sequence alignment shows moderate conservation across mammals but does not highlight residues implicated in Seipin binding. No mutational analysis is provided to test structure-function hypotheses suggested by the figure. 6.3.2. SFs 2–5 – Additional LD imaging These figures contain additional microscopy images but do not contribute mechanistic clarity. The absence of lipidomics, differentiation markers, and metabolic profiling prevents interpretation. Many images appear to show heterogeneous LD size distributions inconsistent with the authors’ simplified model. 6.3.3. SFs 6–8 – Seipin localization patterns These figures include Seipin-GFP localization across cell types. However, Seipin is ubiquitously ER-resident, and the panels provide no evidence for Adig-dependence. The absence of direct colocalization with endogenous Adig weakens the figure’s relevance. 19 6.3.4. SFs 9–12 – Adig expression profiling The qPCR and RNA-seq data confirm adipose-enriched expression but do not support generalization of the Adig–Seipin axis to other tissues. The authors do not integrate this specificity into their mechanistic interpretation, contradicting their own data. 6.3.5. SFs 13–20 – Structural model elaborations These figures include speculative models, domain annotations, and hypothetical mechanism illustrations. However, none reconcile the discrepancies in stoichiometry, local resolution, or map-model fidelity. The figures tend to overinterpret ambiguous density. 6.4. Overall Assessment of Figures Across the main figures, Extended Data, and Supplementary Information, several persistent issues fundamentally weaken the evidentiary basis of the study. First, the structural analyses are overinterpreted: the cryo-EM density attributed to Adig is insufficiently validated, and the asserted dodecameric Seipin architecture is not convincingly demonstrated in the absence of symmetry-free reconstructions, local-resolution analysis, or orthogonal stoichiometric confirmation. Second, the biochemical assays exhibit substantial ambiguity. Nearly all interaction data rely on artificial overexpression systems, lack essential specificity and competition controls, and do not quantify binding affinity or stoichiometry, precluding any firm conclusion about a direct, physiologically relevant Adig– Seipin interaction. Third, the cellular lipid-droplet phenotypes are confounded by unaddressed variables. The experiments do not control for metabolic state, adipogenic differentiation, lipid-synthetic flux, or ER lipid composition, any of which could independently account for the observed LD changes. Fourth, the physiological evidence presented in mouse models lacks depth and breadth. Without systemic metabolic profiling—including thermogenic output, mitochondrial function, endocrine markers, and lipidomics—the in vivo LD phenotypes cannot be confidently attributed to Seipin modulation. Fifth, several figures across the dataset contradict or complicate the central mechanistic narrative, yet the manuscript does not address these internal inconsistencies or propose reconciliatory explanations. Taken together, the visual data provide suggestive but not definitive support for the proposed mechanism. The interpretation that Adig directly binds and stabilizes a dodecameric Seipin oligomer to drive lipid-droplet biogenesis exceeds what the presented evidence can substantiate. A more rigorous framework—incorporating symmetry-free structural validation, quantitative biophysical interaction measurements, differentiationmatched cellular analyses, and comprehensive metabolic phenotyping—is required before this model can be accepted as a reliable and generalizable explanation for Seipin-dependent LD formation. 7. Alternative Interpretations and Mechanistic Models This section proposes scientifically grounded alternative models that can explain the data presented by Li et al. without requiring the specific mechanistic conclusions they assert. 20 Each alternative model is supported by independent literature and reflects mainstream understanding of LD biogenesis, Seipin function, and adipocyte biology. Li et al. interpret their findings as evidence that Adig binds a dodecameric Seipin complex to stabilize its structure and thereby promote LD development. While this is one possible explanation, several alternative mechanistic models could also account for the same biochemical, cellular, and in vivo observations—often more parsimoniously and with stronger alignment to established LD biology. Alternative interpretations are essential, not only because the structural and functional evidence in Li et al. remains inconclusive, but also because LD biology is influenced by numerous overlapping pathways that extend well beyond Seipin itself. 7.1. Model A — Adig Modulates Lipid Metabolic Enzymes Upstream of Seipin Several studies have shown that Adig influences transcriptional networks regulating lipid synthesis enzymes such as ACC, DGAT1, DGAT2, and GPAT3/411,13,40. This raises the possibility that Adig affects LD development indirectly by regulating TAG synthesis rates rather than through direct structural modulation of Seipin. Predictions of this model include: increased TAG synthesis → enlarged LDs in Adigoverexpressing adipocytes; reduced TAG synthesis → smaller LDs in Adig-knockout adipocytes; and changes in LD morphology would be secondary consequences of altered lipid flux. Consistency with Li et al.’s observations include: Adig overexpression increases LD size, Adig knockout produces smaller droplets, and TAG levels in brown adipose tissue (BAT) decrease in Adig-KO mice. These findings are equally well—or better—explained by altered lipid metabolic flux rather than a structural Seipin mechanism. 7.2. Model B — Adig Affects Adipocyte Differentiation and ER Lipid Composition Adig plays a role in adipogenesis, with knockout resulting in delayed differentiation and reduced adipocyte maturation13. Early differentiation state strongly affects LD size, number, and composition43. Thus, LD phenotypes could arise from changes in adipocyte identity, not Seipin modulation. Predictions of this model include that Adig-KO cells differentiate more slowly → produce fewer and smaller LDs; Adig-overexpressing cells differentiate faster or more robustly → produce larger LDs; and changes in ER phospholipid composition may indirectly affect Seipin function5,24. Support from existing literature encompasses that ER lipid composition heavily influences LD budding geometry8, Seipin’s function is sensitive to membrane curvature and phospholipid balance, and even small differences in ER composition can dramatically alter LD size, independent of Seipin structure. Thus, Adig may influence LD biogenesis indirectly by altering the ER lipid environment, not by binding Seipin. 21 7.3. Model C — Adig Stabilizes LDs through Lipid-Phase Partitioning rather than Protein–Protein Interaction Microproteins often partition into lipid phases, stabilizing lipid structures without requiring direct protein–protein binding35. Given Adig’s hydrophobic C-terminal segment, it may preferentially insert into neutral-lipid interfaces or the ER monolayer surrounding forming LDs. In this model, Adig enriches at ER–LD junctions due to lipid affinity, apparent colocalization with Seipin could arise from shared microdomains, and LD stabilization occurs via lipid–protein interactions rather than Seipin binding. Evidence supporting this model include that multiple LD-associated proteins (CIDEC, GPAT4, FIT2) localize based on lipid affinity rather than protein interactions26, hydrophobic microproteins can selectively partition into TAG-rich microenvironments35, and that lipidsensing amphipathic helices can regulate LD morphology independently of Seipin. Thus, Adig’s structural role in LDs may not require direct Seipin interaction. 7.4. Model D — Adig Functions as A Metabolic Stress Modulator Adipose microproteins commonly act as stress responders, modulating proteostasis, mitochondrial function, or ER homeostasis35. If Adig modulates ER stress or UPR pathways, secondary effects on Seipin function would occur because Seipin is highly sensitive to ER homeostasis42. Predictions based on this model are: reduced ER stress → improved Seipin assembly and LD nucleation, elevated ER stress → impaired LD biogenesis, and Adig-KO phenotypes could arise from unmitigated ER stress. This model aligns with observations that Seipin misfolding induces severe ER stress phenotypes42, ER-stress modulators affect LD phenotypes independent of structural interactions9, and microproteins can modulate stress granules and ER proteostasis35. Thus, Adig may indirectly influence LDs via ER proteome homeostasis. 7.5. Model E — Adig Influences Seipin Indirectly by Altering ER–LD Tethering Proteins LD formation requires an ensemble of ER-localized tethering proteins including LDAF1, GPAT4, FIT2, Rab18, ORP family members, and SNX proteins25,26. Adig might regulate the recruitment or stability of these factors. Thus, Adig’s colocalization with Seipin could reflect proximity to ER–LD junctions enriched for LD tethers. Seipin structural changes observed by Li et al. might arise from altered accessory-protein occupancy, not direct binding. For example, LDAF1 directly binds Seipin and modulates LD budding7, FIT2 regulates ER neutral-lipid synthesis and LD budding geometry41, and GPAT4’s ER partitioning shifts during LD formation37-39. Thus, disruption of any of these pathways could produce LD phenotypes similar to those reported in Li et al.4 22 7.6. Model F — Seipin Oligomer Stabilization Does not Require Direct Adig Interaction Even if Seipin oligomerization is altered in Adig-deficient contexts, this does not prove direct binding. Changes could be mediated by (1) lipid composition shifts: ER cholesterol, lysophospholipids, or DAG levels can change Seipin oligomerization8; (2) altered membrane curvature: Adipocyte differentiation changes ER curvature, impacting Seipin assembly; (3) changes in TAG lens nucleation: if TAG levels drop, Seipin oligomerization can appear altered due to incomplete assembly. Thus, the structural findings in Li et al. may represent indirect consequences rather than evidence of direct molecular interaction. 7.7. Model G — Adig’s Effects Arise from Brown Adipose Thermogenic Regulation Adig deletion reduces thermogenic capacity and alters BAT function. BAT LDs respond rapidly to thermogenic state, shrinking during sympathetic activation and enlarging when thermogenesis is suppressed. Thus, smaller LDs in Adig-KO mice could reflect elevated BAT metabolic demand, while larger LDs in Adig-overexpressing adipose tissue could reflect suppressed thermogenesis. These systemic effects could fully explain Li et al.’s in vivo findings without invoking a direct Seipin mechanism. 7.8. Summary of Alternative Models Together, these models demonstrate that Li et al.’s interpretation is only one of many scientifically plausible explanations. A more conservative interpretation would acknowledge that Adig likely influences LD biology indirectly, Seipin binding is not definitively proven, multiple alternative pathways could better explain observed phenotypes, and tissue specificity limits general applicability. 8. Summary of Key flaws, Uncertain Claims and Recommended Correction Paths Table 1 provides an integrated, evidence-based evaluation of the structural, biochemical, cellular, and physiological limitations identified in the study “Adipogenin promotes the development of lipid droplets by binding a dodecameric seipin complex.” The first column summarizes key technical weaknesses in data acquisition, processing, and experimental design, including unvalidated Seipin stoichiometry, insufficient structural-resolution assessment, lack of binding specificity controls, and incomplete metabolic phenotyping. The second column outlines claims that are not fully supported by the presented data— such as the physiological predominance of the Seipin dodecamer, the specificity and stoichiometry of Adig binding, and the generalization of adipose-restricted mechanisms to other tissues. The third column proposes concrete corrective strategies and validation pathways, including symmetry-free cryo-EM reconstruction, biophysical quantification of Adig–Seipin affinity, use of binding-deficient mutant rescue assays, lipidomic and metabolic flux measurements, and tissue-specific validation across non-adipose LD-forming cell types. 23 Collectively, the table serves as a concise roadmap for resolving the mechanistic uncertainties and strengthening the interpretability and physiological relevance of the proposed Adig–Seipin regulatory axis. Table 1. Summary of Key Flaws, Uncertain Claims, and Recommended Correction Paths Category Key Flaws / Limitations Uncertain or Unsupported Claims Recommended Correction / Validation Path Structural Evidence • Cryo-EM map refined with enforced C12 symmetry; no C1 reconstruction shown. • No biochemical validation of Seipin stoichiometry (native MS, SEC-MALS). • Local resolution not reported; potential model overfitting unaddressed. • “Dodecameric Seipin is the physiological predominant form.” • “Adig binds with defined stoichiometry to each protomer.” • Generate symmetry-free (C1) reconstructions. • Perform 3D variability analysis. • Validate oligomeric states with native MS / SEC-MALS. • Provide FSC, EMRinger, MolProbity metrics. Density Interpretation • Adig density weak/ambiguous; map-to-model fit not validated. • No occupancy analysis; potential symmetry-averaging artifacts. • “Adig bridges Seipin subunits via defined binding interfaces.” • Provide half-map comparisons and local-resolution maps. • Test alternative docking models. • Determine occupancy via focused classification. Biochemical Evidence • No quantitative binding assays (ITC, BLI, MST). • Overexpression artifacts likely; no binding-deficient mutants used. • Lack of domain-swap or competition assays. • “Adig specifically and directly binds Seipin with functional specificity.” • Measure affinity and kinetics via ITC/BLI. • Use Adig and Seipin mutants to test specificity. • Perform competition experiments with unrelated microproteins. LD Phenotypes (Cellular) • No time-lapse LD nucleation assays. • Differentiation markers not controlled. • Metabolic flux changes not accounted for. • “LD size changes arise directly from altered Seipin oligomerization.” • Perform live-cell LD nucleation tracking. • Control for adipocyte differentiation state. • Conduct lipidomics (TAG/DAG species, phospholipids). In Vivo Physiology • No metabolic phenotyping (glucose tolerance, indirect • “Adig–Seipin axis regulates systemic adipose lipid storage.” • Evaluate systemic metabolic metrics. 24 Category Key Flaws / Limitations Uncertain or Unsupported Claims Recommended Correction / Validation Path calorimetry, BAT thermogenesis). • Lack of tissue-specific analyses. • No Seipin-null or Adig-bindingmutant rescue experiments. • “Mechanism generalizes across tissues.” • Test Adig overexpression in Seipin-KO animals. • Include tissue-specific rescue and knock-in Adig mutants. Mechanistic Interpretation • Multiple alternative models not addressed (lipogenesis, ER lipid composition, thermogenesis, microprotein lipid partitioning). • No ruling out of indirect pathways. • “Adig exerts its function primarily through Seipin binding.” • Compare WT vs. bindingdeficient Adig mutants. • Evaluate ER lipidome, UPR, thermogenic pathways. • Determine if Seipinindependent phenotypes persist. Generalization & Scope • Adig expression is adiposespecific, but conclusions generalized to all LD biology. • “Mechanism applies broadly to LD formation across cell types.” • Test primary hepatocytes, macrophages, steroidogenic cells. • Quantify Adig mRNA/protein across tissues. 9. Synthesis and Future Directions The study by Li et al.4 proposes a structurally elegant and biologically compelling model in which Adig binds selectively to a dodecameric Seipin oligomer to stabilize its architecture and promote LD development. Yet, as the preceding sections have shown, multiple aspects of this conclusion remain insufficiently supported by available evidence. The limitations in structural validation, biochemical characterization, cellular phenotyping, and physiological interpretation collectively suggest that the mechanistic scope of the Adig–Seipin axis has been overstated relative to what the data can confidently support. This section synthesizes the key critiques and outlines experimentally actionable future directions for resolving the uncertainties. 9.1. Integrating Structural and Biochemical Uncertainties Li et al.4 place heavy emphasis on the structural model of Adig bound to a Seipin dodecamer. While the cryo-EM study provides valuable insights into potential conformations, several lines of evidence indicate that the model should be regarded as provisional rather than definitive: (1) stoichiometric ambiguity: Seipin’s oligomeric state varies across species and biochemical contexts7,18. Without native mass spectrometry or SEC-MALS validation, assigning a strict dodecameric architecture is premature; (2) symmetry imposition risks: early application of C12 symmetry may force the observed structure into a configuration that reflects computational assumptions more than biological reality; (3) unresolved 25 density for Adig: the flexible and microprotein-like nature of Adig suggests that regions attributed to Adig may not be sufficiently resolved or could reflect partially averaged density. These concerns do not negate the utility of the structure but suggest that its mechanistic interpretation must be cautious. 9.2. Reconciling Cell-Based Observations with Metabolic Context Li et al. interpret LD phenotypes in cell models as direct consequences of Seipin oligomer stabilization. Yet, alternative explanations—such as changes in lipogenesis, lipolysis, adipocyte differentiation, ER lipid composition, or thermogenic programming—are equally consistent with the observed phenotypes. Because Adig influences adipogenesis, any experimental system relying on adipocyte differentiation must include time-course differentiation markers, lipidomic analysis of TAG species, mitochondrial activity profiles, ER phospholipid composition assays. Without such controls, interpreting LD size changes as direct mechanistic outcomes is risky. A central mechanistic claim—that Adig stabilizes Seipin—cannot be supported without the use of Adig mutants deficient in Seipin binding and Seipin mutants lacking the putative Adigbinding groove. The absence of such mutants leaves the causal chain incomplete. 9.3. Re-evaluating in vivo Interpretation through Systemic Physiology LD phenotypes in mice integrate influences from mitochondrial thermogenesis, hormonal regulation, inflammatory signaling, systemic insulin sensitivity, feeding behavior, and sympathetic tone25,41. Li et al. attribute BAT and WAT LD changes to direct Seipin modulation without evaluating these systemic variables. To establish physiological relevance, the following analyses are needed: glucose and insulin tolerance tests, indirect calorimetry, mitochondrial respiration assays, cold-exposure challenges for BAT, endocrine profiling of adipokines, and detailed lipidomic profiling across tissues. These are standard metabolic-phenotyping assays for functional interpretation. Their absence substantially limits the strength of physiological claims. 9.4. Integrative Critique: Constraints on Mechanistic Generalization The preceding sections converge on several key conceptual conclusions. 9.4.1. The Seipin–Adig Axis Is Likely Adipose-Specific Given the highly restricted expression of Adig, the proposed mechanism cannot be generalized to LD formation in hepatocytes, macrophages, steroidogenic tissues, and immune cells. Li et al.’s generalization to “lipid storage broadly” overlooks decades of work showing tissue-specific LD regulation14,15,26,46. 9.4.2. The Mechanism May Be Indirect Rather than Structural Several alternative models (see Section 6) provide equally plausible explanations—often with stronger evidentiary support: transcriptional regulation of lipid metabolic enzymes, modulation of thermogenesis, ER lipid-composition shifts, and lipid-phase partitioning of 32 46 Klug, Y. A., Ferreira, J. V. & Carvalho, P. A unifying mechanism for seipinmediated lipid droplet formation. FEBS Lett 598, 1116-1126 (2024). https://doi.org/10.1002/1873-3468.14825