The research, led by Junrui Luo and Zhiqiang Liu at Henan Polytechnic University in Jiaozuo, China, focused on TRIM37, a member of the tripartite motif family of E3 ubiquitin ligases. These enzymes act as molecular quality-control agents, attaching small ubiquitin protein tags to specific target molecules, which then marks those targets for destruction or alters their behavior. TRIM37 had already been implicated in cancer development and in maintaining the health of centrioles, the barrel-shaped structures from which cilia are built. But its precise role in the assembly of primary cilia, a process biologists call ciliogenesis, had remained murky until now.

To probe that role, the team worked with two widely used laboratory cell lines: human retinal pigment epithelial cells, known as RPE1 cells, which are a standard model for studying cilia, and HK2 cells, a human kidney cell line. Both of these cell types normally grow prominent primary cilia when they exit the active cell cycle and settle into a quiescent state. When the researchers used RNA interference to knock down TRIM37 expression, they observed a striking effect: the fraction of cells that managed to grow cilia dropped significantly, and the cilia that did form were noticeably shorter than normal. Importantly, the team verified that this defect was not simply a side effect of altered cell cycle progression, ruling out one obvious alternative explanation.

A key clue to the mechanism came from the location of the protein itself. Using fluorescence microscopy, the researchers found that TRIM37 accumulates at the basal body, the modified centriole that anchors the cilium to the cell and serves as the gateway through which building blocks are ferried into the growing organelle. This strategic positioning suggested that TRIM37 might be doing more than just housekeeping at the cilium’s foundation. It hinted that the protein could be actively managing the local environment needed for ciliary assembly, possibly by coordinating the delivery or removal of materials at the base of the structure.

That suspicion led the investigators to autophagy, the cell’s internal recycling program. During autophagy, the cell engulfs damaged proteins and organelles in double-membraned vesicles called autophagosomes, which then fuse with lysosomes, the acidic compartments where the cargo is broken down and its components are returned for reuse. Autophagy has a complicated, two-sided relationship with cilia: at moderate levels it can help clear inhibitors of ciliary assembly, but excessive or insufficient autophagic activity can disrupt cilium formation. The researchers discovered that when TRIM37 was depleted, cells accumulated LC3-II, a lipidated form of a protein that decorates autophagosomal membranes, along with p62, also known as SQSTM1, a cargo receptor that shuttles tagged material into autophagosomes. At the same time, levels of Beclin1 and WIPI2, two proteins essential for launching the autophagy program, declined, indicating that the initiation of autophagy itself was being suppressed.

To determine whether the accumulated autophagic machinery was actually working, the team deployed bafilomycin A1, a toxin that blocks the final step of autophagy by preventing the acidification of lysosomes and the fusion of autophagosomes with them. By comparing autophagic flux, the complete throughput of the recycling pipeline, in the presence and absence of this blocker, the researchers confirmed that TRIM37-deficient cells suffered from genuine flux impairment. An independent immunofluorescence assay measuring the colocalization of LC3 with LAMP2, a lysosomal membrane protein, painted the same picture: autophagosome formation was reduced, and the fusion of autophagosomes with lysosomes was defective. In other words, losing TRIM37 did not merely slow the recycling line at one checkpoint; it jammed the entire conveyor belt.

The next question was whether TRIM37’s enzymatic activity, its ability to transfer ubiquitin tags, was required for these effects. The researchers performed functional complementation experiments, re-introducing TRIM37 variants into depleted cells and testing whether the protein could rescue normal cilium growth and autophagic balance. The results were unambiguous: only a version of TRIM37 with intact E3 ubiquitin ligase activity could restore normal ciliogenesis and autophagic homeostasis. A catalytically dead variant could not. This finding elevated TRIM37 from a passive structural component to an active enzymatic regulator whose chemical function is the linchpin of the whole process.

Having established that TRIM37’s ligase activity was essential, the team searched for the critical substrate and found it in p62, the very cargo receptor that had piled up in TRIM37-depleted cells. The experiments showed that TRIM37 directly mediates the ubiquitination of SQSTM1/p62, promoting its turnover and thereby keeping autophagic activity within the proper range. When TRIM37 is absent, p62 accumulates unchecked, and the resulting imbalance disrupts both the initiation of autophagy and the maturation of autophagosomes, which in turn sabotages the carefully choreographed process of cilium construction.

The most convincing demonstration of this regulatory axis came from a double-knockdown experiment. When the researchers simultaneously depleted both TRIM37 and SQSTM1/p62, the ciliogenesis defects and autophagic abnormalities caused by losing TRIM37 alone were substantially alleviated. This genetic epistasis experiment, a classic strategy for ordering genes into a pathway, showed that p62 acts downstream of TRIM37 and that removing the problematic accumulation of p62 can compensate for the loss of its regulator. Together, the findings define a novel TRIM37–SQSTM1/p62–autophagy signaling axis that modulates mammalian ciliogenesis, adding a new branch to the molecular regulatory network that biologists have been mapping for decades.

The implications of this work extend beyond basic cell biology. TRIM37 is already known as the gene mutated in mulibrey nanism, a rare inherited growth disorder, and its involvement in centriole maintenance and tumorigenesis has made it a subject of intense interest. By connecting this ubiquitin ligase to the autophagy machinery and to ciliary assembly, the study offers a mechanistic framework that could eventually inform research into ciliopathies, kidney disease, and cancers in which autophagy and ciliary signaling go awry. It also underscores a growing theme in modern cell biology: organelle construction is not an isolated program but an integrated process that depends on the cell’s recycling systems running at exactly the right tempo. As researchers continue to untangle the connections between ubiquitination, autophagy, and cilia, the TRIM37–p62 axis identified here provides a clear example of how a single enzymatic regulator can coordinate two fundamental cellular systems to build one of the cell’s most important sensory structures.

Subject of Research: Regulation of primary ciliogenesis by the E3 ubiquitin ligase TRIM37 through p62 ubiquitination and autophagy control

Article Title: Ciliogenesis is regulated by TRIM37 through ubiquitinating p62 and controlling the autophagy pathway

Article References: Luo, J., Zhang, X., Zhao, C., Zhang, Y., Chen, W., Wang, Z., Li, S., & Liu, Z. (2026). Ciliogenesis is regulated by TRIM37 through ubiquitinating p62 and controlling the autophagy pathway. Cellular and Molecular Life Sciences. https://doi.org/10.1007/s00018-026-06454-0

Image Credits: AI Generated

DOI: 10.1007/s00018-026-06454-0

Keywords: TRIM37, ciliogenesis, primary cilia, autophagy, p62, SQSTM1, ubiquitination, E3 ubiquitin ligase, basal body, autophagic flux, ciliopathies, cell biology

Peptidoglycan is the great success story of bacterial evolution. This mesh-like polymer of sugars and amino acids encases nearly every bacterial cell, protecting it from osmotic pressure and serving as the target of some of our most important antibiotics, from penicillin to vancomycin. Archaea, by contrast, were long thought to have abandoned peptidoglycan entirely, wrapping themselves in proteinaceous S-layers or pseudomembranes instead. Yet decades ago, researchers working on methanogenic archaea described a peptidoglycan-like polymer, dubbed pseudomurein, in a major clade of methane producers. Despite its early discovery, this archaeal peptidoglycan remained poorly characterized, largely because scientists lacked the dedicated analytical tools that transformed bacterial peptidoglycan research. Without enzymes capable of specifically degrading the polymer, its fine structure remained locked away.

The breakthrough came from an approach that mirrors the history of bacterial cell wall biology. In bacteria, enzymes called muramidases, which cleave the sugar backbone of peptidoglycan, proved indispensable for teasing apart wall architecture. The Pasteur-led team reasoned that archaea themselves, or the viruses that infect them, might harbor analogous hydrolases. Using a combination of bioinformatic screening and zymography, a technique that detects lytic activity directly in protein gels, the researchers identified eleven candidate hydrolases from M. smithii. Among these, one protein stood out: ArmA, a large multi-domain enzyme that proved to be the first glycosyl hydrolase specific for archaeal peptidoglycan.

What ArmA revealed when set loose on purified M. smithii cell walls was genuinely unexpected. The prevailing model, built on chemical analyses from the late 1970s and early 1980s, held that the glycan backbone of pseudomurein consisted of alternating N-acetylglucosamine and N-acetyltalosaminuronic acid residues. The new work shows that the reality is different. The glycan backbone comprises N-acetylglucosamine or N-acetylgalactosamine linked to a previously undescribed sugar, which the team has named N-acetylarmosamine. Even more strikingly, the glycan strands do not run with a uniform linkage pattern. Instead, they alternate between beta(1,4) and beta(1,3) glycosidic linkages, an arrangement that distinguishes archaeal peptidoglycan sharply from its bacterial counterpart, in which the backbone is stitched together exclusively with beta(1,4) bonds.

The peptide stems that cross-link the glycan strands also attach in an unusual way. In bacterial peptidoglycan, stem peptides are typically joined to the sugar backbone through standard amide bonds on the carboxyl groups of the constituent sugars. In the archaeal polymer, the researchers found that the stem peptide is attached by means of an amide bond to the succinyl group of N-acetylarmosamine, an architectural detail that had escaped earlier characterization. Mass spectrometry and nuclear magnetic resonance spectroscopy, applied to fragments released by enzymatic digestion, provided the structural evidence needed to establish these features with confidence, and the analysis was extended across diverse methanogens to confirm that the architecture is broadly conserved.

ArmA itself turned out to be a remarkably versatile molecular machine. The enzyme displays dual enzymatic activity, cleaving both the glycosidic linkages of the sugar backbone and the peptide crosslinks that hold the wall mesh together. This two-in-one capability makes it a uniquely powerful analytical reagent, comparable in impact to the muramidases that revolutionized the study of bacterial walls. Phylogenetic analyses added an evolutionary dimension to the story: ArmA homologues are restricted to archaea that actually possess peptidoglycan walls, suggesting that the enzyme co-evolved with the polymer it degrades. The team confirmed hydrolase activity across a range of methanogenic species, establishing ArmA and its relatives as a general toolkit for interrogating methanogen cell walls.

Perhaps the most biologically satisfying finding concerns what ArmA actually does inside the cell. Using antibodies raised against the protein, the researchers tracked ArmA’s localization through the M. smithii cell cycle with super-resolution microscopy. The enzyme forms a discontinuous ring-like structure precisely at the division plane, and as cytokinesis progresses, new rings appear in the prospective daughter cells at the sites where the next round of division will occur. This pattern strongly suggested a role in splitting the wall during cell division, and genetic experiments confirmed it. Deleting the armA gene in the thermophilic methanogen Methanothermobacter thermautotrophicus produced cells that failed to complete cytokinesis properly, forming elongated filaments. ArmA, in other words, is required to cleave archaeal peptidoglycan at the site of cell division, playing a role analogous to the autolysins that bacteria deploy to separate their daughter cells.

The implications of the work extend well beyond structural biology. Methanogens are ecologically and biotechnologically significant organisms: they dominate the archaeal component of the human gut microbiome, contribute substantially to methane emissions from livestock, and are increasingly explored as platforms for biotechnology. Because archaeal peptidoglycan is essential to the organisms that build it and is structurally distinct from bacterial peptidoglycan, the pathway and its enzymes represent an attractive target for targeted intervention. The authors note that a patent application covering the use of ArmA to regulate methanogen populations in industrial, agricultural and medical settings has been filed by Institut Pasteur, underscoring the applied potential of the discovery. Selectively disrupting the walls of gut methanogens, for instance, could offer new strategies for modulating the archaeome in contexts ranging from digestive health to methane mitigation in ruminants.

Scientifically, the study marks a turning point in how the field approaches archaeal cell biology. For decades, archaeal peptidoglycan was a curiosity, described in classic biochemical studies but largely inaccessible to modern genetic and cell biological analysis. ArmA changes that calculus entirely. Just as muramidases enabled the dissection of bacterial wall architecture, muropeptide profiling and hydrolase genetics in bacteria, this archaeal enzyme opens the door to biochemical and genetic interrogation of methanogen cell-wall biology with the same rigor. The work also carries evolutionary weight: peptidoglycan is often invoked in debates about the deep ancestry of the two prokaryotic domains, and a precise, experimentally grounded picture of the archaeal polymer will inform models of how cell-wall biochemistry evolved and diversified across the tree of life.

What began as a search for a molecular tool ended as a revision of a textbook paradigm. A 50-year-old model of archaeal peptidoglycan structure has given way to a new one, built on an alternating-linkage glycan backbone, an unprecedented sugar called N-acetylarmosamine, and a stem-peptide attachment chemistry unique to the archaeal domain. And the enzyme that made the discovery possible turns out to be no mere laboratory reagent but a bona fide division machine, choreographed to the cell cycle and essential for the propagation of some of the most consequential microbes on Earth. For a polymer that spent half a century in the shadows, archaeal peptidoglycan has suddenly become one of the most exciting molecules in microbiology.

Subject of Research: Structure and cell division role of archaeal peptidoglycan in methanogenic archaea

Article Title: A methanogen hydrolase reveals the structure of archaeal peptidoglycan

Article References: Smith, R., Pende, N., Rifflet, A., Taib, N., Witwinowski, J., Martin-Gallausiaux, C., Cornilleau, C., Garcia, P. S., Villa, R., Douché, T., Matondo, M., Majrouh, M., Reichelt, R., Grohmann, D., Tripp, P., Albers, S.-V., Borrel, G., Rittmann, S. K.-M. R., Sartori-Rupp, A., … Gribaldo, S. (2026). A methanogen hydrolase reveals the structure of archaeal peptidoglycan. Nature. https://doi.org/10.1038/s41586-026-11028-y

Image Credits: AI Generated

DOI: 10.1038/s41586-026-11028-y

Keywords: archaea, peptidoglycan, methanogens, cell wall, ArmA hydrolase, Methanobrevibacter smithii, pseudomurein, N-acetylarmosamine, cytokinesis, glycosyl hydrolase, human gut microbiome, cell biology

The core problem SIMworks addresses is deceptively simple to state and notoriously hard to solve. SIM works by illuminating a specimen with patterned light, typically a fine grid of stripes, and computationally extracting high-frequency information that the objective lens alone cannot capture. Because the final image is assembled by an algorithm rather than recorded directly, the technique is exquisitely sensitive to imperfections in the raw data. Misaligned illumination patterns, photobleaching during acquisition, spherical aberrations introduced by the sample itself, and noise amplification during reconstruction can all conspire to produce images that look plausible but contain artifacts, sometimes even fabricating structures that do not exist in the specimen. For a field increasingly reliant on quantitative measurements of nanoscale biology, such artifacts are not merely cosmetic; they can distort conclusions about protein clustering, chromatin organization, or organelle interactions.

SIMworks tackles this challenge by unifying four previously established tools into a single, coherent platform. The suite builds on SIMcheck, a widely used toolbox for assessing raw and reconstructed SIM data quality; Chromagnon, a program for correcting chromatic shifts between color channels; ChaiN, which addresses channel registration and related corrections; and SIMinspector, a tool for examining reconstruction quality. Rather than forcing users to juggle separate programs with incompatible interfaces and workflows, SIMworks wraps these capabilities into a modular architecture that runs within Fiji, the open-source image analysis environment built on ImageJ. Because Fiji is already a fixture in most biology laboratories, the barrier to adoption is dramatically lower than it would be for a standalone package requiring unfamiliar installation procedures or proprietary licenses.

The workflow that the protocol describes is organized around a logical progression from raw data to quantitative results. It begins with calibration and quality checks on the raw, unreconstructed images, verifying that the illumination pattern was properly modulated, that signal-to-noise ratios are adequate, and that the acquisition parameters fall within acceptable ranges. Only after the raw data pass these checks does the user proceed to reconstruction and a second round of quality assessment on the processed images. This two-stage gating is crucial: artifacts introduced during acquisition can be caught before they are amplified by reconstruction, while reconstruction-specific problems, such as residual ringing or noise-driven pseudo-structures, can be identified in the output. The protocol provides detailed guidance on interpreting each quality metric, helping users decide whether their data are suitable for processing and how to optimize parameters for the best possible results.

One of the most technically interesting aspects of SIMworks is its handling of augmentation and artifact correction. The suite includes tools for Fourier bandpass filtering, which suppresses high-frequency noise that would otherwise manifest as a characteristic hammerstroke pattern in the final image. The protocol’s extended data illustrate this vividly: in DAPI-stained chromatin imaged by three-dimensional SIM, appropriate bandpass filtering transforms a noisy frequency profile into a near-linear response that kinks cleanly into the noise floor, corresponding to an effective spatial resolution of around 108 nanometers on the tested instrument. The authors also demonstrate masking based on the modulation contrast-to-noise ratio, a metric that helps distinguish genuine spot-like signals from noise-driven pseudo-structures. Crucially, they show that the optimal threshold depends on raw data quality, with lower-quality datasets requiring more conservative settings to avoid eroding real features.

Beyond quality control, SIMworks extends into quantitative analysis, which is where the software’s ambitions become most apparent. The suite includes segmentation and classification modules capable of identifying spot-like signals, such as DNA replication foci or cohesin complexes, as well as more complex structures like Golgi apparatus, peroxisomes, lysosomes and mitochondria. Once objects are segmented, the software can quantify their spatial relationships, measuring distances and co-localization in ways that support rigorous statistical comparison across conditions. The protocol even demonstrates compatibility with images from other modalities, including Zeiss Airyscan confocal data, suggesting that the segmentation and quantification tools have value beyond SIM proper. This breadth positions SIMworks not just as a SIM utility but as a general framework for quantitative analysis of high-resolution fluorescence data.

Reproducibility and interoperability were clearly central design considerations. The authors emphasize that SIMworks is compatible with both custom-built and commercial SIM systems and supports advanced SIM modalities, not just the classical two-dimensional implementations. All code is distributed through Fiji’s update sites, ensuring that users receive updates through the same mechanism they already use for other plugins, and the peer-reviewed code is archived on Zenodo with a persistent digital object identifier. A freely available test dataset, including raw images, reconstructed images and alignment files, accompanies the project on GitHub, allowing newcomers to practice the full workflow before committing their own precious samples. The authors report that the complete workflow, from raw data to quantitative output, can be completed in approximately half a day, depending on dataset size and complexity.

The timing of this release is significant. The past few years have seen an explosion of SIM variants, including lattice SIM for large fields of view, Hessian SIM for fast live imaging, point-spread-function-engineered SIM for high fidelity, and deep-learning approaches that promise instant denoising and super-resolution. Each advance brings new capabilities but also new reconstruction algorithms, new parameter choices and new opportunities for artifacts to creep in. At the same time, institutional imaging facilities are making SIM available to researchers with no optical engineering background, meaning that the people operating the microscopes often cannot diagnose technical problems on their own. A unified, well-documented quality control pipeline arrives at precisely the moment the community needs one, providing a common language for discussing data quality across instruments and laboratories.

The biological payoff is already evident in the authors’ own research programs. The Ochs laboratory in Copenhagen, which studies genome integrity and chromatin organization, has used SIM to reveal how sister chromatid cohesion is mediated by individual cohesin complexes and how chromatin topology safeguards the genome. The Schermelleh group in Oxford has long contributed to the development and dissemination of three-dimensional SIM methods for imaging the nuclear periphery. Tools like SIMworks are what allow such discoveries to be made reliably and, just as importantly, to be reproduced by other groups. When a claimed nanoscale arrangement of chromatin or a measured distance between protein clusters can be traced through a documented, artifact-checked pipeline, the entire field gains confidence in the underlying biology.

For laboratories considering adopting SIM, or struggling to make sense of data they already have, the message from this protocol is encouraging. The technical barriers that once made SIM the province of specialist facilities are being dismantled not by making the physics simpler, but by making the software smarter and the best practices explicit. SIMworks does not eliminate the need for careful sample preparation, appropriate fluorophore choice, or thoughtful experimental design; no software can rescue poorly acquired data. What it does provide is a safety net, catching problems before they contaminate the scientific record and lowering the expertise threshold for rigorous quantitative imaging. As super-resolution microscopy continues its march from specialist tool to standard laboratory technique, platforms like this one will determine whether the resulting data can be trusted, compared and built upon. In that sense, SIMworks may prove as important for what it prevents, namely artifact-driven false discoveries, as for what it enables.

Subject of Research: Quality-controlled quantitative structured illumination microscopy software

Article Title: SIMworks—an integrated software suite for quality-controlled augmented quantitative structured illumination microscopy

Article References: Pytowski, L., Jandi, W., Henggeler, A., Cho, W., Schermelleh, L., & Ochs, F. (2026). SIMworks—an integrated software suite for quality-controlled augmented quantitative structured illumination microscopy. Nature Protocols. https://doi.org/10.1038/s41596-026-01444-9

Image Credits: AI Generated

DOI: 10.1038/s41596-026-01444-9

Keywords: structured illumination microscopy, super-resolution microscopy, SIMworks, Fiji, image quality control, artifact correction, image segmentation, quantitative imaging, chromatin imaging, Nature Protocols, open-source software, cell biology

BCR-ABL1 is the fusion protein born from the Philadelphia chromosome, the hallmark genetic abnormality of chronic myeloid leukemia and a subset of B-cell acute lymphoblastic leukemia. First described in landmark reviews by Goldman and Melo, the fusion fuses the BCR gene on chromosome 22 with the ABL1 tyrosine kinase gene on chromosome 9, producing a constitutively active kinase that drives uncontrolled proliferation and survival of white blood cells. Tyrosine kinase inhibitors were designed to slip into the ATP-binding pocket of ABL1 and freeze the enzyme in an inactive state. In structural studies of the kinase domain, including work by Cowan-Jacob and colleagues, imatinib and related compounds achieve exactly that. And yet, in patients, the kinetics of treatment response are markedly slower than direct enzyme inhibition would predict, an effect sometimes described as target sluggishness.

The new research reframes this sluggishness as an emergent property of how BCR-ABL1 organizes itself inside the cell. Rather than floating freely through the cytoplasm as isolated molecules, the team found that BCR-ABL1 molecules condense into dense, membraneless assemblies reminiscent of liquid droplets. These condensates form through multivalent, weak interactions among intrinsically disordered regions of the protein, the same class of physical chemistry that governs the formation of cellular structures such as nucleoli, stress granules and P bodies. The study connects this condensate behavior directly to therapeutic response: when BCR-ABL1 resides within these droplets, the local molecular environment becomes a physical barricade that slows the entry and action of tyrosine kinase inhibitors.

The concept of phase separation has transformed cell biology over the past decade. In a widely cited 2018 paper in Cell, Qamar and colleagues demonstrated that low-complexity protein domains can undergo liquid-liquid phase separation, creating compartments whose material properties dictate how molecules exchange with the surrounding cytoplasm. The new study applies this framework to cancer signaling for the first time in the context of targeted therapy. The authors showed that disrupting the conditions that promote condensate formation made BCR-ABL1 more accessible to drugs, while conditions that stabilized the droplets exaggerated the sluggish response. The droplet, in effect, functions as a microscopic shelter: drug molecules can reach the droplet surface, but penetrating the dense interior to reach every kinase molecule takes far longer than engaging freely diffusing protein.

Technically, the researchers combined protein biochemistry with cellular assays and clinical material. They purified BCR-ABL1 protein and observed its condensation behavior in solution, finding that the protein spontaneously demixes from the aqueous phase to form spherical droplets that fuse with one another and exchange internal contents, hallmarks of a liquid state. In cells, they visualized BCR-ABL1 condensates and correlated their abundance with the speed and completeness of kinase inhibition after tyrosine kinase inhibitor treatment. Crucially, the team collected bone marrow and blood samples from patients with BCR-ABL1-positive leukemia through collaborations with clinicians at Zhejiang Cancer Hospital and the First Hospital of China Medical University, allowing them to test whether condensate behavior in patient-derived cells tracked with treatment response.

The clinical implications of this reframing are substantial. Resistance to tyrosine kinase inhibitors has traditionally been attributed to kinase domain mutations, most famously the T315I substitution that abolishes imatinib binding, or to the persistence of leukemic stem cells that are intrinsically insensitive to the drugs. Studies such as those by Braun and colleagues and by Schneider and colleagues in Nature Cancer have catalogued the biology of these persistent cells, which survive initial therapy and fuel relapse. The phase separation model adds an entirely orthogonal mechanism: a cell can carry a completely drug-sensitive kinase and still mount a delayed response simply because its target protein is packaged inside droplets that physically exclude or retard drug penetration. This innate, non-genetic sluggishness could explain why a measurable fraction of cells in every treated patient survives the earliest hours and days of therapy without carrying any resistance mutation at all.

The finding also resonates with earlier structural and biochemical work on the ABL1 kinase. Structures of ABL1 bound to imatinib, dasatinib and nilotinib published by Tokarski and colleagues revealed exactly how these compounds lock the kinase in its inactive conformation, and kinetic studies showed rapid association rates in purified systems. The paradox between fast in vitro inhibition and slow cellular response now finds a candidate resolution: the purified enzyme in a test tube has no condensate, no barrier and no sluggishness, while the same enzyme inside a leukemic cell is wrapped in a liquid compartment that throttles drug access. Zhao and colleagues’ early structural characterization of the BCR-ABL1 complex, and Smith and colleagues’ dissection of its signaling architecture, provided the molecular map; phase separation now supplies the cellular geography that shapes how drugs navigate that map.

From a therapeutic standpoint, the study suggests that modulating condensate properties could become a strategy to sensitize leukemic cells to existing drugs. If the physical barrier created by BCR-ABL1 condensates is a principal cause of sluggish drug response, then agents that dissolve or destabilize the droplets, or that alter the material properties of the condensate so that small molecules diffuse through it freely, could accelerate and deepen the effect of tyrosine kinase inhibitors. Conversely, the work raises a caution for drug development: potency measured against purified kinase may systematically overestimate how quickly a compound will work in a cell whose target is phase-separated. Screening platforms that incorporate condensate-relevant conditions could help identify compounds that retain efficacy against droplet-sequestered targets, particularly for B-cell acute lymphoblastic leukemia, where early response kinetics strongly influence long-term outcome, as population studies by Qin and colleagues and reports by Ravandi and Molica have documented.

The broader significance extends beyond a single kinase or a single disease. Cancer biologists have increasingly recognized that many oncogenic proteins contain the disordered, multivalent regions that drive phase separation, and that signaling complexes such as those assembled by fusion oncoproteins, including the EML4-ALK and NUP98 fusions studied by Dixon and colleagues in engineered systems, may exploit condensation to amplify and sustain their signals. The BCR-ABL1 study demonstrates that this same organizational principle can also serve as a defensive architecture against therapy. Pendergast and colleagues’ classic 1991 work showed that BCR sequences activate ABL1 tyrosine kinase; three decades later, the new findings suggest that those same BCR-derived regions may coil the fusion protein into droplets that protect the activated kinase from the drugs designed to silence it.

For patients with chronic myeloid leukemia, tyrosine kinase inhibitors have converted a uniformly fatal disease into a manageable chronic condition, and a minority of patients now attempt treatment-free remission under close monitoring. Yet discontinuation fails in a substantial fraction, and persistent cells endure for years. By exposing the physical mechanism behind innate sluggishness, this research opens a new front in the effort to eliminate residual disease: rather than only designing better inhibitors, oncologists may one day prescribe drugs that strip away the droplet shield itself. The image of a cancer protein hiding inside a liquid droplet is a vivid one, and it captures a larger truth about modern biology. Cancer is not only a disease of genes and pathways but of physical organization, and conquering it may require manipulating not just what proteins do, but where and how they gather inside the cell.

Subject of Research: Phase-separated BCR-ABL1 condensates that delay the response of leukemic cells to tyrosine kinase inhibitor therapy

Article Title: Phase separation drives the innate sluggishness of BCR-ABL1 in response to targeted therapy

Article References: Li, G., Wu, J., He, Z., Zhao, J., Chen, H., Zhou, J., Zhang, Q., Wang, Z., Li, Q., & Jiang, P. (2026). Phase separation drives the innate sluggishness of BCR-ABL1 in response to targeted therapy. Cell Research. https://doi.org/10.1038/s41422-026-01286-w

Image Credits: AI Generated

DOI: 10.1038/s41422-026-01286-w

Keywords: BCR-ABL1, phase separation, chronic myeloid leukemia, tyrosine kinase inhibitors, condensates, imatinib, targeted therapy, leukemia, drug resistance, liquid-liquid phase separation, oncology, cell biology

The finding adds a striking new dimension to a long-running discussion in cell biology about how organelle membranes are mended. Over the past decade, researchers have identified several repair pathways that respond to lysosomal damage, many of them involving the protein galectin-3, which binds exposed sugars on the inner surface of the ruptured lysosome, and the lipid PI4P, produced by phosphatidylinositol 4-kinases. ESCRT machinery, a membrane-scission apparatus best known for its roles in cytokinesis and viral budding, is then recruited to seal small holes in the lysosomal limit membrane. The new study demonstrates that this repair landscape is more complex than previously appreciated, because it also draws on lipid signaling that originates on the endoplasmic reticulum, an organelle physically distinct from the wounded lysosome.

The endoplasmic reticulum, or ER, is the cell’s largest membrane network, an interconnected system of tubules and sheets that reaches nearly every corner of the cytoplasm. It is the site where lipids are synthesized and where calcium is stored, and it maintains intimate contact sites with endosomes and lysosomes. Those contacts allow the exchange of lipids and ions and coordinate processes such as organelle fission and autophagy. The notion that the ER participates in lysosomal repair fits naturally into this picture of close cross-talk, but the new work identifies a specific molecular mechanism: a spatially defined pool of PI3P that appears on ER membranes in response to lysosomal injury.

Phosphatidylinositol phosphates, or phosphoinositides, are minor lipid components of cellular membranes that act as positional labels, telling proteins where in the cell they should act. Different phosphoinositides decorate different compartments: PI4P marks the Golgi apparatus and late endosomes, PI4,5P2 marks the plasma membrane, and PI3P is characteristic of early endosomes and, notably, of autophagic structures. The key enzyme that generates PI3P for autophagy is PIK3C3, also known as VPS34, a phosphatidylinositol 3-kinase that is activated during starvation to drive the growth of autophagosomes. Because DFCP1 was already known as an autophagy-associated protein that binds PI3P and decorates nascent autophagosome precursors, the authors’ discovery that it operates in lysosomal repair connects two processes, autophagy and membrane repair, that were largely studied in isolation.

Using cell biological and imaging approaches, Radulovic and colleagues observed that when lysosomes are damaged, PI3P accumulates on discrete ER microdomains rather than being distributed uniformly across the reticular network. These PI3P-positive ER zones then serve as docking platforms for DFCP1, whose recruitment depends on its PI3P-binding activity. In cells lacking PIK3C3, the ER pool of PI3P is not formed, DFCP1 fails to be recruited to damaged lysosomes, and the repair of lysosomal membranes is compromised. Conversely, manipulations that promote PI3P formation support DFCP1 recruitment and improve repair outcomes. The experiments trace a clear causal chain from lysosomal injury, through ER-localized lipid signaling, to the assembly of a repair-competent structure at the wounded organelle.

The functional consequences of this pathway are significant for the health of the cell. Unrepaired lysosomes lose their acidic lumen, release hydrolases into the cytosol, and can ultimately rupture, a process that triggers inflammatory signaling and, in severe cases, a form of programmed cell death called lysosomal cell death. By ensuring that damaged lysosomes are rapidly resealed, the PI3P-DFCP1 axis helps preserve organelle integrity and prevents the leakage of degradative enzymes. The study also places DFCP1 in a new functional context: rather than acting only as an autophagy marker, it emerges as an active participant in membrane homeostasis, an ATPase whose enzymatic activity and lipid binding are harnessed for the physical task of restoring membrane continuity.

The discovery also raises intriguing mechanistic questions that the field will now pursue. How is PIK3C3 activated on ER microdomains specifically after lysosomal damage, and what upstream signal conveys the news of a rupture from the lysosome to the ER? Existing repair pathways appear to be organized in parallel modules, with galectins, PI4P, and ESCRT acting at different stages of the response, and it will be important to determine how the ER-derived PI3P-DFCP1 pathway is integrated with them. One possibility is that DFCP1 facilitates the recruitment or function of ESCRT complexes; another is that it contributes lipid or membrane resources from ER-lysosome contact sites to the repair process. The physical proximity of the ER to endolysosomal organelles makes both scenarios plausible and testable.

Beyond its cell biological interest, the work has potential implications for human disease. Lysosomal dysfunction is a hallmark of numerous disorders, including lysosomal storage diseases, many common neurodegenerative conditions such as Parkinson’s and Alzheimer’s disease, and disorders of autophagy. Pathogenic agents, from silica crystals to cholesterol crystals to certain bacteria, damage lysosomes as part of their life cycle or disease mechanism. If the PI3P-DFCP1 repair pathway proves to be conserved and essential in human tissues, it may represent a point of vulnerability or a therapeutic target: boosting the pathway could strengthen cells against lysosomal stress, whereas pathogens or cancer cells might be sensitized to lysosome-directed therapies by disabling it.

For researchers who have followed the lysosome repair field, the study is a reminder that organelle quality control is a whole-cell endeavor, coordinated among compartments that communicate through lipids, proteins, and physical contacts. The ER, often treated in textbooks as a passive factory for proteins and lipids, now appears to be an active sentinel that monitors and supports the integrity of its neighboring organelles. As imaging technologies and lipidomics methods continue to improve, more such inter-organellar rescue pathways are likely to come to light, and DFCP1-containing ER microdomains may prove to be just the first example of a membrane network acting as a first responder for the cell’s damaged endomembrane system.

Subject of Research: ER-localized PI3P signaling and DFCP1 recruitment in lysosomal membrane repair

Article Title: DFCP1-containing ER microdomains mediate lysosomal membrane repair

Article References: Radulovic, M., Pust, S., Kournoutis, A., Chen, D., Giner, M. I., Liang, Q., Phuyal, S., Böddeker, T. J., McCarron, K., Herrmann, E., Rose, K., Schultz, S. W., Brech, A., Hurley, J. H., Bussi, C., Bonet-Ponce, L., Gutierrez, M. G., Raiborg, C., & Stenmark, H. (2026). DFCP1-containing ER microdomains mediate lysosomal membrane repair. Nature Cell Biology. https://doi.org/10.1038/s41556-026-02062-z

Image Credits: AI Generated

DOI: 10.1038/s41556-026-02062-z

Keywords: lysosome, membrane repair, DFCP1, PI3P, PIK3C3, endoplasmic reticulum, autophagy, phosphoinositides, organelle crosstalk, cell biology, ESCRT, lysosomal damage

The core challenge that MemBrain v2 addresses begins with segmentation. A cryo-electron tomogram is essentially a three-dimensional reconstruction assembled from a tilt series of two-dimensional projection images of a vitrified sample. Within that volumetric data, membranes appear as weak, noisy, curving sheets only a few nanometers thick, often distorted by the so-called missing wedge artifact that arises from physical limits on how far the sample can be tilted in the microscope. Early approaches to membrane segmentation relied on hand-crafted filters, edge detectors, and painstaking manual contouring, a process that could consume days of an expert’s time for a single tomogram and that varied substantially from one analyst to another. Such variability made large-scale, quantitative comparisons across cells, conditions, or organisms extremely difficult, effectively capping the throughput of the field.

MemBrain v2 builds on the deep-learning foundations laid by its predecessor, which introduced convolutional neural network models trained to recognize membrane density patterns that human eyes and classical algorithms routinely miss. The new version extends this philosophy across the entire analysis pipeline. Rather than providing a single segmentation model that researchers must then stitch into their own homemade workflows, the software packages the full sequence of steps: preprocessing of raw tomograms, automated segmentation of membranes, extraction of continuous membrane meshes from the segmented volumes, localization of membrane proteins relative to those meshes, and quantitative spatial statistics describing how proteins and curvature features are organized across the membrane surface. The result is a pipeline in which a user can move from a reconstructed tomogram to publication-ready membrane measurements with minimal manual intervention.

Technically, the segmentation engine in MemBrain v2 employs neural networks trained on curated, manually annotated datasets of tomograms spanning diverse biological contexts, from isolated organelles to intact cells prepared by focused ion beam milling. The models operate on three-dimensional patches of the tomogram, predicting per-voxel probabilities that a given location belongs to a membrane. Crucially, the developers have placed strong emphasis on generalization: the goal is that a network trained on one set of samples and imaging conditions will still perform reliably on tomograms acquired on a different microscope, with a different detector, or from a different biological system. This kind of cross-dataset robustness has been a persistent pain point in cryo-ET machine learning, where models frequently overfit to the specific noise characteristics and contrast regimes of their training data. Performance across heterogeneous datasets was therefore treated as a first-class evaluation criterion rather than an afterthought.

Once membranes are segmented, the software converts the voxel-level predictions into geometrically clean surface meshes, a step that is far less trivial than it sounds. Segmentation outputs are typically noisy at the pixel scale, containing holes, spurious protrusions, and disconnected fragments that would corrupt any downstream measurement of surface area, curvature, or protein spacing. MemBrain v2 incorporates methods to extract smooth, watertight representations of membrane surfaces, preserving fine topological features such as tight junctions, cristae junctions, organelle contact sites, and highly curved tubular structures. This geometric fidelity matters because many of the most interesting biological questions in modern cell biology hinge precisely on such features: how the folded inner membrane of a mitochondrion organizes its respiratory machinery, how the endoplasmic reticulum generates curved hubs that recruit certain proteins, or how viral replication compartments remodel host membranes into convoluted replication factories.

Perhaps the most consequential addition in version 2 is the integration of membrane protein localization into the same workflow. Subtomogram averaging has long allowed structural biologists to determine high-resolution structures of abundant, repetitive complexes, but mapping the broader landscape of membrane-associated proteins in situ, including those that are sparse, irregularly arranged, or conformationally heterogeneous, remains a formidable task. MemBrain v2 provides tools to detect and classify particles in the vicinity of segmented membranes, project their positions onto the extracted meshes, and compute spatial statistics that characterize their distribution: clustering tendencies, exclusion patterns, correlations with local membrane curvature, and nearest-neighbor relationships. By unifying segmentation and particle analysis in one software environment, the tool removes the error-prone handoffs between disconnected programs that have historically plagued multi-step cryo-ET analyses.

The significance of this integration extends well beyond convenience. Spatial organization of proteins on membranes is now understood to be a central regulatory principle in cell biology. The clustering of receptors can amplify signaling; the sorting of complexes into curvature-sensing domains can drive vesicle budding; the exclusion of certain proteins from contact sites can maintain organelle identity. Quantifying these patterns rigorously requires exactly the kind of joint membrane-and-protein analysis that MemBrain v2 enables. Instead of qualitative statements that a protein appears enriched on curved regions, researchers can now report statistically grounded measurements of enrichment, complete with the geometric context of the underlying membrane. This shift from descriptive to quantitative in situ analysis aligns cryo-electron tomography with the standards of rigor that fields such as light-sheet microscopy and single-cell genomics achieved years ago.

Accessibility has been a guiding concern throughout the design. Cryo-ET is a technique that sits at the intersection of biology, physics, and computer science, and many research groups possess deep biological questions but limited computational infrastructure. Earlier generations of analysis tools often assumed considerable programming expertise, requiring users to assemble pipelines from research code written by other laboratories, with little documentation and no guarantee of stability between versions. MemBrain v2 counters this with user-friendly interfaces, containerized installation options, thorough documentation, and standardized output formats designed to interoperate with the broader ecosystem of tomography software, including visualization platforms and subtomogram averaging packages. The developers have also made the trained models and processing tools openly available, consistent with a broader movement in structural biology toward open, reproducible computational methods that any laboratory can adopt, inspect, and extend.

The timing of such a tool is not accidental. Cryo-electron tomography is undergoing explosive growth, propelled by advances in direct electron detectors, automated data collection, focused ion beam milling of lamellae, and reconstruction algorithms that dramatically improve resolution and contrast. Large-scale initiatives now aim to image thousands of cellular volumes, generating data at a rate that makes manual analysis categorically impossible. In this environment, automated, reliable, generalizable analysis pipelines are not merely convenient; they are the precondition for the field’s ambition to build a quantitative atlas of cellular architecture. Tools like MemBrain v2 represent the computational counterpart to the hardware revolution, ensuring that the flood of tomographic data can be converted into biological insight rather than accumulating as unprocessed archives.

For the practicing researcher, the practical implications are immediate. A laboratory studying mitochondrial remodeling during stress, for example, could apply the pipeline across dozens of tomograms of control and treated cells, obtain consistent membrane segmentations, quantify changes in cristae morphology, map the redistribution of respiratory chain complexes, and test whether protein reorganization tracks with local membrane curvature, all within a unified framework. A virology group could chart how viral proteins reshape intracellular membranes as replication compartments mature. A neurobiologist could examine the nanoscale organization of synaptic vesicle clusters and presynaptic membrane specializations. In each case, the same underlying machinery of segmentation, mesh extraction, particle localization, and spatial statistics does the heavy lifting, freeing scientists to focus on experimental design and biological interpretation rather than on debugging bespoke image-analysis scripts.

As with any computational method, caveats remain. Deep-learning segmentations are probabilistic and can fail in unexpected regimes, particularly with extreme imaging conditions, unusual staining or labeling approaches, or membrane-like features such as dense protein coats that mimic lipid bilayers. Responsible use therefore still entails expert validation, and the developers emphasize that the tool is intended to accelerate and standardize expert workflows rather than eliminate judgment from the loop. Nevertheless, by demonstrating robust performance across diverse datasets and by wrapping the entire analysis chain into a coherent, accessible package, MemBrain v2 marks a meaningful step toward making the quantitative analysis of cellular membranes as routine as the imaging itself. If the trajectory of cryo-electron tomography continues on its current course, tools of this kind will become the standard infrastructure on which the next decade of in situ structural biology is built, transforming noisy three-dimensional images into a rigorous, comparative anatomy of the cell’s molecular geography.

Subject of Research: A deep-learning software pipeline for membrane segmentation and membrane protein spatial analysis in cryo-electron tomography

Article Title: MemBrain v2: an end-to-end tool for the analysis of membranes in cryo-electron tomography

Article References: Lamm, L., Zufferey, S., Zhang, H., Righetto, R. D., Waltz, F., Wietrzynski, W., Yamauchi, K. A., Burt, A., Liu, Y., Martinez-Sanchez, A., Ziegler, S., Isensee, F., Schnabel, J. A., Engel, B. D., & Peng, T. (2026). MemBrain v2: an end-to-end tool for the analysis of membranes in cryo-electron tomography. Nature Methods. https://doi.org/10.1038/s41592-026-03178-8

Image Credits: AI Generated

DOI: 10.1038/s41592-026-03178-8

Keywords: cryo-electron tomography, MemBrain v2, membrane segmentation, deep learning, membrane proteins, spatial analysis, structural biology, cell biology, organelle architecture, image analysis, subtomogram averaging, Nature Methods

The central innovation behind SPIFFI lies in its use of polarimetry, the measurement and manipulation of the polarization state of light, as a vehicle for encoding information that would normally require repeated measurements to capture. In conventional fluorescence imaging, the polarization of emitted or illuminated light is often treated as a nuisance parameter to be minimized or ignored. SPIFFI instead treats polarization as a rich information channel. By carefully structuring the polarization of light interacting with the sample, and by decoding the resulting polarization-dependent patterns, the technique extracts sub-diffraction-scale spatial information from what would otherwise be a single, ordinary-looking frame of data.

To understand why this matters, it helps to recall how super-resolution microscopy typically works. Techniques such as structured illumination microscopy overlay known patterns onto the sample, and the interaction between the illumination pattern and fine sample structure shifts normally invisible high-frequency information into the observable range. Capturing that information, however, usually demands multiple raw images taken with the pattern shifted and reoriented, phase stepping through several positions before a reconstruction algorithm can assemble a super-resolved result. Each additional frame adds exposure time, phototoxicity, and sensitivity to sample motion. In a living cell that is crawling, dividing, or trafficking vesicles along microtubules, even a few tens of milliseconds between frames can smear fine structures into unrecognizable streaks.

SPIFFI’s single-shot design sidesteps this problem by ensuring that all the information needed for super-resolution reconstruction is packed into one exposure. Rather than stepping through illumination phases sequentially, the system encodes the necessary spatial and polarization diversity simultaneously, so that a single camera frame contains, in a multiplexed form, the data that earlier approaches gathered across multiple frames. Decoding software then computationally separates the multiplexed channels and reconstructs a super-resolved image, along with additional multidimensional information about the sample. The practical consequence is that researchers can follow fast biological processes with spatial resolution beyond the diffraction limit while acquiring images at video rates or faster, limited primarily by camera speed and signal brightness rather than by the imaging protocol itself.

The multidimensional character of the technique is one of its most striking features. Beyond simply sharpening the lateral position of fluorescent structures, SPIFFI’s polarimetric readout carries information about additional dimensions of the light field, which can be exploited to characterize properties of the sample or the fluorescent labels themselves. Fluorescent molecules do not emit light uniformly in all directions; their emission and excitation depend on the orientation of their dipoles, and the polarization of fluorescence therefore encodes molecular orientation information. In many biological contexts, from the tilt of transmembrane proteins to the architecture of cytoskeletal filaments, this orientation information is biologically meaningful. A technique that retrieves it simultaneously with super-resolved spatial position, in real time, opens the door to imaging modalities in which each frame conveys a richer picture of molecular-scale organization than a conventional intensity image ever could.

The implications for live-cell imaging are substantial. Dynamic processes that have been particularly challenging for super-resolution methods include the remodeling of the actin cortex during cell migration, the rapid exchange of proteins at synapses, membrane fusion and fission events, and the motion of molecular motors along cytoskeletal tracks. In each case, the structures involved are small enough to demand super-resolution, yet fast enough that sequential multi-frame acquisition would blur them. Single-shot acquisition removes the temporal bottleneck: because the entire measurement occurs within one exposure, there is no inter-frame delay during which the sample can move, and motion artifacts that plague phase-stepped approaches are eliminated by design rather than corrected after the fact.

Photodamage is a second front on which the single-shot approach promises advantages. Phototoxicity in live-cell fluorescence microscopy scales with the total light dose delivered to the sample, and multi-frame super-resolution techniques necessarily illuminate the specimen repeatedly. By compressing the acquisition into a single exposure, SPIFFI reduces the number of illumination cycles required per reconstructed image, which can lower the cumulative dose and help keep living specimens healthy over longer observation windows. For experiments in which cells must be followed through division, differentiation, or stress responses over many minutes or hours, reducing light exposure is often as important as improving resolution, and imaging frameworks that economize on dose while preserving detail address a genuine unmet need.

Real-time capability also changes the experimental workflow in a more subtle way. When reconstruction requires lengthy offline computation, microscopists typically acquire data first and analyze it later, discovering only after the experiment ends whether the labeling was adequate, the focus was stable, or the biology behaved as expected. An imaging mode that produces super-resolved results in real time allows researchers to adjust conditions on the fly: to re-focus, re-label, or re-design the experiment while the sample is still on the stage. In the longer term, real-time super-resolution also makes live feedback experiments feasible, in which perturbations such as optogenetic activation or drug addition are triggered based on features detected in the super-resolved image itself, closing the loop between observation and intervention at a spatial scale previously reserved for slower, fixed-cell methods.

The technical challenges that SPIFFI had to overcome are nontrivial and illuminate why such a capability has been slow to arrive. Encoding polarization diversity into an optical system while preserving diffraction-limited image quality requires precise wavefront and polarization control, typically with patterned retarders, spatial light modulators, or polarization-sensitive optics arranged so that different polarization channels are spatially multiplexed onto the detector without crosstalk that would corrupt the reconstruction. The decoding algorithms must unmix these channels robustly in the presence of shot noise, background autofluorescence, and the inevitable imperfections of real optical components. Achieving this in a form that runs fast enough for real-time display demands efficient computational implementations, often leveraging modern graphics hardware. That SPIFFI achieves all of this while remaining usable on biological samples reflects years of incremental progress across polarization imaging, computational microscopy, and fluorescent probe chemistry.

For the broader microscopy community, SPIFFI represents part of a larger convergence between optical engineering and computational reconstruction that has come to define the current era of microscopy. The classical divide between what the optics measure and what the software infers has blurred: polarization, phase, spectrum, and incidence angle have all been conscripted as carriers of encoded spatial information, with algorithms doing the work of translation. Within this landscape, the appeal of single-shot designs is a growing recognition that biology cannot be asked to hold still. The techniques that ultimately shape our understanding of living systems will be those that deliver their full power within the timescales on which life unfolds, and by bringing super-resolution and multidimensional contrast into a single real-time exposure, SPIFFI marks a meaningful step in that direction. If the approach proves widely adoptable on standard microscopes, it could bring real-time, multidimensional super-resolution imaging out of specialized laboratories and into everyday use across cell biology, neuroscience, and biophysics.

Subject of Research: Single-shot polarimetric super-resolution fluorescence microscopy for live-cell imaging

Article Title: SPIFFI enables single-shot super-resolution and multidimensional imaging

Article References: Guo, W., Feletti, L., & Radenovic, A. (2026). SPIFFI enables single-shot super-resolution and multidimensional imaging. Nature Methods. https://doi.org/10.1038/s41592-026-03196-6

Image Credits: AI Generated

DOI: 10.1038/s41592-026-03196-6

Keywords: super-resolution microscopy, fluorescence imaging, polarimetry, live-cell imaging, structured illumination, single-shot imaging, real-time imaging, phototoxicity, computational microscopy, cell biology, SPIFFI, enables

G protein-coupled receptors, or GPCRs, form the largest receptor family in most animal genomes and are the targets of a substantial fraction of modern medicines. Classically, these proteins thread through the membrane seven times, forming a bundle that shifts shape when a hormone, neurotransmitter, or sensory molecule binds on the outside, thereby activating G proteins and other signaling partners on the inside. TM184C shares the hallmark seven-transmembrane architecture of this family, but the new work argues that its role is not the canonical one. Instead of simply relaying external signals, the protein appears to sit at the interface of membrane trafficking systems that determine what can pass between neighboring cells and what gets delivered to the lysosome for degradation. That dual assignment, intercellular exchange on one hand and autophagy on the other, points to a coordinating function at a junction where membrane biology has long been studied but poorly unified.

Intercellular exchange is a broad term covering several distinct mechanisms by which one cell transfers material to another. Cells can release small membrane-enclosed vesicles such as exosomes, form transient cytoplasmic bridges, or engage in contact-dependent transfer at specialized junctions. These processes matter in immunity, where antigen fragments are handed between immune cells; in development, where signaling molecules and even organelles can move between neighboring cells; and in disease, where tumor cells exploit exchange pathways to spread survival signals or drug resistance. The identification of TM184C as a regulator of such exchange suggests that at least part of this traffic is actively managed by a dedicated protein rather than arising purely from generic membrane dynamics. Understanding which exchange route TM184C controls, and how its GPCR-like fold supports that control, is now a central question raised by the study.

Autophagy, the second process attributed to TM184C, is the cell’s quality-control and recycling program. Through a sequence of carefully choreographed steps, the cell wraps damaged organelles, protein aggregates, and invading microbes in a double-membrane vesicle called an autophagosome, which then fuses with lysosomes where the contents are broken down into building blocks the cell can reuse. Autophagy is induced by starvation and stress, but a basal level runs continuously, clearing molecular wear and tear. Defects in the pathway are implicated in neurodegenerative disease, cancer, and metabolic disorders, which is why the machinery of autophagy has been mapped in extraordinary detail over the past three decades. That a GPCR-like protein would feed into this system is notable because autophagy regulation has traditionally been dominated by a different cast of characters: kinase cascades, ubiquitin-like conjugation systems, and adaptor proteins that recognize cargo.

The conceptual bridge between the two roles may lie in membrane handling. Both intercellular exchange and autophagy depend on the cell’s ability to remodel, tether, and fuse membranes with precision. Vesicles that leave one cell to enter another must bud, travel, and merge with target membranes; autophagosomes must nucleate from a specific membrane source, engulf cargo, and fuse with lysosomes. A protein with seven membrane-spanning segments has the structural means to sit within such membranes and influence their curvature, composition, or interactions with the trafficking machinery. The authors’ designation of TM184C as GPCR-like rather than simply a GPCR is therefore meaningful: it implies conservation of the fold, and possibly of some regulatory logic, without necessarily implying ligand binding and classical signal transduction. Evolutionary biologists have increasingly recognized that receptor-like folds are sometimes repurposed for transport, adhesion, or scaffolding roles, and TM184C may be a fresh example of that repurposing.

For researchers in membrane biology, the study offers a potential new handle on a long-standing puzzle: how cells coordinate what they send out with what they break down. If the same molecular apparatus governs both export routes and lysosomal delivery, then signals that alter TM184C function could simultaneously change how a cell communicates with its neighbors and how it recycles its own components. Such coupling would have wide implications. In the immune system, for instance, the presentation of antigens to other cells depends on both vesicular transfer and autophagic processing of intracellular proteins. In cancer, tumor cells often boost both exosome secretion and autophagy to survive hostile conditions, and a single regulator touching both pathways would be an attractive target for therapeutic intervention. The study’s framing of TM184C as a point of convergence makes these connections explicit even as many mechanistic details remain to be worked out.

The technical path to such a discovery typically involves a combination of genetic, cell biological, and structural approaches. Identifying a protein as a regulator of intercellular exchange generally requires assays that measure transfer of fluorescent or functional cargo between cells, coupled with perturbations, such as gene knockout or knockdown, that reveal what changes when the protein is absent. Assigning a role in autophagy demands complementary readouts: accumulation of autophagosome markers, flux assays that distinguish blocked degradation from increased autophagosome formation, and electron microscopy or biochemical fractionation to see where the protein acts in the pathway. Demonstrating GPCR-like character involves sequence and structural analysis confirming the seven-transmembrane arrangement and comparison with known receptor families. While the published report’s full experimental detail is not reproduced here, the combination of claims in the title indicates that the authors crossed these methodological thresholds, positioning TM184C within both the exchange and autophagy literatures simultaneously.

What makes the result likely to draw broad attention is the sheer prominence of both processes in current biology. Autophagy research has been recognized with a Nobel Prize, and extracellular vesicles have become one of the fastest-growing areas of biomedical science, driven by their roles in intercellular communication and their potential as drug delivery vehicles. A molecule that links these two fields creates an immediate agenda: structural biologists will want to see the protein’s architecture at atomic resolution; cell biologists will want to map its interaction partners and pinpoint which trafficking step it controls; physiologists will want to know in which tissues it matters most; and clinicians will ask whether its dysfunction contributes to diseases where exchange or recycling goes wrong. Each of these questions is standard follow-up for a new regulator, but few new regulators arrive with credentials in two such active areas at once.

There are also evolutionary implications worth noting. GPCR-like proteins that do not signal in the classical sense have been described before, including adhesion GPCRs with long N-terminal domains that function partly as structural tethers, and various orphan receptors whose ligands remain unknown. TM184C extends this spectrum by suggesting that the receptor fold can be recruited for intracellular membrane management, not just surface sensing. If homologs of TM184C exist across species, comparative studies could reveal when this exchange-and-autophagy function arose and how conserved it is, from single-celled organisms to complex animals. Conversely, if the protein is restricted to particular lineages, that distribution could explain why it escaped attention for so long and hint at specialized biological contexts, perhaps in tissues with high exchange demands, where its function is most critical.

As with any first report of a new regulator, caution is warranted until independent laboratories reproduce the findings and extend them. The field will want clarity on whether TM184C binds any ligand, whether it couples to G proteins at all, and exactly which step of autophagy it influences, from initiation to cargo recognition to lysosomal fusion. It will also matter whether the intercellular exchange phenotype reflects a direct role in vesicle formation or an indirect consequence of altered membrane homeostasis. Nevertheless, the study establishes a clear identity for TM184C and a defined set of processes to interrogate. In a research landscape where the boundaries between signaling, trafficking, and degradation are increasingly seen as porous, a GPCR-like protein that regulates both intercellular exchange and autophagy is a fitting emblem of that shift, and a reminder that some of the cell’s most important traffic controllers may have been hiding in plain sight within the receptor family’s structural vocabulary.

Subject of Research: TM184C, a GPCR-like regulator of intercellular exchange and autophagy

Article Title: TM184C is a GPCR-like regulator of intercellular exchange and autophagy

Article References: Lee, K. D., Taylor, S., Arcuri, J., Chandthakuri, S., Pujols, J., Colon, B., Wang, Q., Wu, C., Meng, Z., Thompson-Ceccato, S. J., Mitchell, J., Bayik, D., Carbone, A., Slepak, V., Slepak, T. I., Welford, S. M., Ivan, M. E., Wang, D., Goldberg, B. O., … Isom, D. G. (2026). TM184C is a GPCR-like regulator of intercellular exchange and autophagy. Nature. https://doi.org/10.1038/s41586-026-10993-8

Image Credits: AI Generated

DOI: 10.1038/s41586-026-10993-8

Keywords: TM184C, GPCR-like protein, autophagy, intercellular exchange, membrane trafficking, cell biology, exosomes, lysosomes, seven-transmembrane protein, cellular recycling, vesicle transfer, Nature

The article, led by Carsten Janke of Institut Curie and Université Paris-Saclay together with Anna Akhmanova of Utrecht University and an international consortium of sixteen colleagues from institutions spanning Europe and the United States, lays out a coordinated agenda for the microtubule field. Its authors span structural biology, biophysics, cell biology, neuroscience, parasitology and computational modelling, reflecting their central conviction that progress will come not from any single discipline but from a deliberate fusion of them. The paper is punctuated by the admission that some of the most basic questions remain unexplored, including how the properties and functions of microtubules are affected by the chemical marks known as tubulin post-translational modifications, by disease-related mutations in tubulin genes, or by variation in the microtubule lattice itself.

Microtubules are hollow tubes assembled from αβ-tubulin dimers that stack into protofilaments, typically thirteen of which align laterally to form the wall of the polymer. What makes these structures extraordinary is their behaviour: individual microtubules stochastically switch between phases of growth and rapid shrinkage, a phenomenon called dynamic instability, which was first described by Tim Mitchison and Marc Kirschner in 1984. A stabilizing cap of GTP-bound tubulin at the growing plus end controls this behaviour, and its loss triggers catastrophic depolymerization. Beyond pure polymerization, microtubules can self-repair by incorporating new tubulin along damaged stretches of lattice, a property revealed in studies showing that lattice defects actually induce self-renewal and protect the polymers from destruction by molecular motors. These discoveries have transformed the view of microtubules from static beams into dynamic, self-healing machines.

The Roadmap emphasizes that microtubule function is not determined by the polymer alone but by a dense layer of regulation encoded on the tubulin subunit itself. Enzymes of the tubulin tyrosine ligase-like family decorate the unstructured carboxy-terminal tails of tubulin with modifications such as tyrosination, detyrosination, acetylation, glutamylation and glycylation, creating what has become known as the tubulin code. Recent structural work has shown, for example, that enzymes involved in polyglutamylation recognize microtubules through a quadrivalent mechanism that links microtubule geometry to the generation of localized modification patterns, and that protofilament-specific nanopatterns of these marks tune the mechanics of beating cilia. The Roadmap argues that understanding how this chemical language is written, read and erased across cellular contexts is one of the field’s most pressing challenges, particularly because disruptions in the code are now firmly linked to neurodegeneration, ciliopathies and other disorders.

Nowhere is the clinical relevance more evident than in the nervous system. Neurons depend on microtubule tracks for the long-range transport of organelles, messenger RNAs and signalling endosomes along axons and dendrites, a process powered by kinesin and dynein motor proteins. Mutations in tubulin genes such as TUBA1A cause lissencephaly, a severe developmental brain malformation, by perturbing neuronal migration, and variants in a growing list of tubulin genes underlie a spectrum of neurodevelopmental disorders collectively known as tubulinopathies. Defective axonal transport is a shared hallmark of motor neuron diseases, and recent work has shown that excessive polyglutamylation of tubulin in the brain is sufficient to drive neurodegeneration by disrupting transport, while restoring the balance of these modifications can rescue affected neurons. The Roadmap positions a systems-level understanding of these processes as essential for translating molecular insight into therapies.

The heart and the immune system tell equally compelling stories. In beating cardiomyocytes, detyrosinated microtubules act as load-bearing elements that buckle under contraction and stiffen the cell, and suppressing this modification improves cardiac function in models of heart failure. In immune cells, microtubule networks orchestrate cell shape, migration and the directed release of lytic granules by natural killer cells, while platelets, whose tubulin repertoire is dominated by the β1-tubulin isotype, rely on precisely regulated microtubule assembly during their biogenesis; mutations in the TUBB1 gene cause congenital macrothrombocytopenia and thyroid dysgenesis. The Roadmap argues that these tissue-specific roles cannot be understood piecemeal and demand approaches that bridge the molecular properties of tubulin to the physiology of whole organs.

Technological innovation sits at the centre of the proposed strategy. Cryo-electron microscopy and cryo-electron tomography now reveal microtubules and their associated proteins at near-atomic and in situ resolution, while expansion microscopy and ultrastructure expansion microscopy allow researchers to visualize centrioles, cilia and mitotic spindles in whole cells and tissues with nanometre precision. In vitro reconstitution, a tradition stretching back to the pioneering work of Tim Mitchison and Marc Kirschner and continued in landmark experiments showing that purified microtubules and motors can self-organize into asters and vortices, remains indispensable for dissecting minimal systems. These experimental approaches are increasingly paired with computational and physical models that simulate spindle assembly, microtubule network organization and chromosome movement, and the Roadmap calls for tighter coupling between modelling and experiment, including the development of virtual cells powered by artificial intelligence.

Recombinant tubulin technology is highlighted as a particularly transformative advance. For decades, biochemists were limited to native tubulin purified from brain tissue, a mixture of isotypes and modifications that obscured cause and effect. The ability to produce functional human tubulin dimers in defined isotypes, with controlled post-translational modifications, has now enabled researchers to show directly that different isotypes confer distinct dynamic properties, that detyrosination tunes microtubule stability through selective recruitment of associated factors, and that systematic mutagenesis can map the functional landscape of disease-linked variants. Combined with deep mutational scanning and artificial-intelligence-driven phenotyping, the authors argue, these tools will allow the effects of every clinically observed tubulin mutation to be predicted and tested, a goal that seemed out of reach only a few years ago.

The Roadmap also looks beyond animal cells, drawing attention to the diversity of microtubule arrays across eukaryotes, from the cortical arrays that guide plant cell morphogenesis to the subpellicular arrays of trypanosomes and the specialized mitotic machinery of parasites. Comparative studies of parasites such as Plasmodium have revealed that adaptations in tubulin sequence generate distinct microtubule architectures, mechanics and drug susceptibilities, opening avenues for species-selective therapeutics. The authors contend that this evolutionary breadth is not a curiosity but a resource: organisms that build microtubules with unusual lattices, modifications or assembly mechanisms offer natural experiments that can illuminate principles hidden in familiar model systems.

Ultimately, the Roadmap is an invitation to think bigger. Its authors conclude that the microtubule cytoskeleton will continue to inspire scientists for decades precisely because so many fundamental questions remain open: how microtubule arrays are organized and diversified in different cell types, how the tubulin code is orchestrated across space and time, how mechanical forces reshape and stabilize microtubule lattices in living cells, and how all of this integrates into the physiology of tissues and organisms in health, ageing and disease. By bridging the atomic structure of the tubulin dimer with the behaviour of mitotic spindles, migrating neurons and beating hearts, the field aims to transform its fragmented molecular knowledge into a coherent systems-level picture, one that could reshape how disorders ranging from neurodegeneration and cancer to ciliopathies and heart failure are understood and treated.

The historical depth of the field is worth appreciating. Microtubules were first visualized in the late nineteenth and early twentieth centuries, but their protein building block was only identified in the late 1960s, when colchicine-binding assays led to the isolation of what was soon named tubulin, and amino-acid analysis of sperm flagella confirmed it as the universal subunit of the polymer. The discovery of dynamic instability two decades later established that these polymers are fundamentally nonequilibrium structures, a insight that continues to shape how spindle assembly and chromosome movement are understood today.

Equally important is the cast of regulatory proteins that act on microtubules. Microtubule-associated proteins such as tau can condense on the lattice in regulated phases, altering how motors and severing enzymes engage the polymer, while enzymes that cut microtubules generate new seeds and reshape networks. Proteins like doublecortin, which is mutated in human brain malformations, illustrate how even lattice geometry itself can be read selectively, recognizing only specific protofilament numbers. These layered interactions, spanning motors, maps, severing enzymes and modifying enzymes, form the mechanistic vocabulary that any systems-level account of the cytoskeleton will ultimately need to integrate.

Subject of Research: Systems-level integration of microtubule cytoskeleton structure, regulation and function in physiology and disease

Article Title: Towards a systems-level view of the microtubule cytoskeleton and its functions in physiology and disease

Article References: Janke, C., Akhmanova, A., Bartolini, F., Bodakuntla, S., Del Bene, F., Hamel, V., Mitchison, T. J., Müller-Reichert, T., Nédélec, F., Nogales, E., Pigino, G., Roll-Mecak, A., Schiavo, G., Surrey, T., & Lansky, Z. (2026). Towards a systems-level view of the microtubule cytoskeleton and its functions in physiology and disease. Nature Reviews Molecular Cell Biology. https://doi.org/10.1038/s41580-026-01011-w

Image Credits: AI Generated

DOI: 10.1038/s41580-026-01011-w

Keywords: microtubules, tubulin code, post-translational modifications, dynamic instability, axonal transport, tubulinopathies, ciliopathies, neurodegeneration, mitotic spindle, cryo-electron tomography, in vitro reconstitution, systems biology