Biology subjects

Liu, M.

Publications and source records attributed to Liu, M..

At least 73 records · Page 4Linked to original sources

bioRxiv2026

ATAD2 BRD mediates liquid-liquid phase separation of ATAD2 to promote histone acetylation

ATAD2 possesses a C-terminal bromodomain (BRD) that plays a critical role in recognizing and binding to acetylated lysine residues. However, because the native intracellular structure of ATAD2 remains poorly defined, the mechanisms by which the ATAD2 BRD recruits acetylated histones and the regulatory pathways involved are not yet understood. In this study, we report that the ATAD2 BRD mediates the formation of liquid-liquid phase separation (LLPS) of ATAD2 in cells. This phase separation promotes the process of histone H4 acetylation, leading to the up-regulation of C-MYC, CCND3, and ATF2 gene expression and the facilitation of chromatin remodeling. Our findings elucidate a vital function of ATAD2, wherein BRD-mediated LLPS drives histone acetylation to promote cellular chromatin remodeling.

molecular biology↗

bioRxiv2026

Fluorescence anisotropy structured illumination microscopy for quantitative super-resolved mapping of cell microenvironment and cytoskeletal dynamics

The crowded intracellular milieu shapes organelle architecture and dynamics, yet nanoscale heterogeneity in its physicochemical properties remains difficult to visualize with conventional fluorescence anisotropy (FA) imaging. Here, we develop fluorescence anisotropy structured illumination microscopy (FA-SIM), which employs orthogonal-polarization structured illumination with dual-angle detection to achieve [~]100-nm resolution and quantitative FA retrieval with 0.56% relative error, representing over 20-fold higher accuracy than conventional FA imaging. With low phototoxicity, FA-SIM enables dual-color, hour-long quantitative super-resolution imaging in cells. Using viscosity standards, defined nanoparticles and small-molecule drug binding assays, we validate FA-SIM as a quantitative reporter of rotational mobility and molecular interactions. In cells, FA-SIM resolves nanoscale crowding heterogeneity, correlates anisotropy landscapes with condensate dynamics, and uncovers a radial crowding gradient across the microtubule network and mitotic spindle. Long-term dual-color imaging further resolves coordinated actin-microtubule remodeling and associated microenvironmental changes. By enabling quantitative, super-resolved mapping of intracellular physical properties in living systems, FA-SIM provides a powerful platform for investigating the physical regulation of cellular organization and dynamics in health and disease.

cell biology↗

bioRxiv2026

Functional Type I and Type II interferon crosstalk restricts progenitor exhausted CD8 T cells through spatial exclusion and checkpoint enforcement

Type I interferon (IFN-I) and interferon-{gamma} (IFN{gamma}) are central regulators of antiviral immunity, yet how they cooperatively govern CD8 T cell fate during chronic infection remains unresolved. Here, we uncover a previously unrecognized, spatially encoded interferon circuit that actively constrains progenitor exhausted CD8 T cells (Tpex) during chronic LCMV infection. Persistent IFN-I signaling indirectly restricts Tpex expansion by enforcing their sequestration within PDL1-rich B cell niches of lymphoid tissue and by suppressing T cell-derived IFN{gamma}. Blockade of IFN-I signaling enables Tpex migration into T cell zones of splenic follicles driving IFN{gamma} production, which in turn sustains PDL1 expression on myeloid cells to re-impose local inhibitory pressure. Combined IFN-I and IFN{gamma} blockade disrupts this feedback, promoting coordinated niche redistribution of Tpex and checkpoint remodeling that drives robust Tpex expansion. Single-cell transcriptomics reveal that this layered IFN-I-IFN{gamma} interplay establishes a regulatory balance that constrains Tpex proliferation while preserving effector-like transcriptional programs in their progeny effector CD8 T cells, ultimately preventing premature terminal differentiation. Thus, interferons orchestrate the coordinated T cell-myeloid regulatory circuit that integrates tissue organization, cytokine feedback, and checkpoint control to regulate CD8 T cell exhaustion during chronic infection.

immunology↗

bioRxiv2026

MAP: A Knowledge-driven Framework for Predicting Single-cell Responses for Unprofiled Drugs

Predicting how cells respond to chemical perturbations is one of the goals for building virtual cells, yet experimentally profiled compounds cover only a small fraction of this space. Existing models struggle to generalize to unprofiled compounds, as they typically treat drugs as isolated identifiers without encoding their mechanistic relationships. We present MAP, a framework that integrates structured biological knowledge into cellular perturbation modeling and supports zero-shot prediction for small molecules with scarce or absent perturbation profiles. Specifically: (i) we construct MAP-KG, a large-scale knowledge graph tailored for cellular perturbation modeling that unifies 14 public resources, spanning 187k drugs, 23k genes, and 694k mechanistic relationships; (ii) we propose a knowledge-driven pre-training strategy that aligns molecular structures, protein sequence features, and textual mechanistic descriptions into a unified embedding space via contrastive learning, producing mechanism-aware and transferable gene and compound embeddings. The resulting knowledge-informed gene and drug representations are then coupled with a pretrained single-cell foundation model to condition perturbation response prediction; (iii) we evaluate MAP under two zero-shot generalization regimes: unseen cell type-drug combinations and the stricter setting of unprofiled drugs, where it improves top-50 DEG Pearson delta correlation by up to +13.3% and +12.2%, respectively, over the strongest baselines across three benchmarks. We further perform pathway-level functional analysis via GSEA for in-silico screening, where MAP predicts coherent, mechanism-consistent programs on unprofiled candidate drugs, and prioritizes 4 of 5 approved anti-cancer drugs in A-549 (non-small cell lung cancer).

bioinformatics↗

bioRxiv2026

Graph-based RNA structural representation reveals determinants of subcellular localization

RNA subcellular localization is a key determinant of RNA function and regulation, yet existing computational approaches rely primarily on sequence or simplified structural descriptors, limiting their scalability to long transcripts, their ability to model inter-label dependencies, and their applicability across RNA types. Here, we present GRASP, a unified graph neural network framework for predicting RNA subcellular localization using a heterogeneous graph representation that is RNA substructure-aware. GRASP presents each RNA as a multi-scale graph comprising nucleotide nodes and secondary-structure-derived substructure nodes, connected by relational edges, enabling joint modeling of base-level interactions and regional structural context. The model further incorporates multi-label dependency learning to capture co-localization patterns across cellular compartments within a unified framework. Across multiple benchmark datasets and RNA types, GRASP consistently outperforms state-of-the-art sequence-based and structure-informed methods, achieving substantial improvements in accuracy, F1 score, and AUC while maintaining strong scalability to long transcripts. In addition, the graph-based representation provides biologically interpretable insights into structural determinants of RNA localization. The source code and data are available at https://github.com/ABILiLab/GRASP, and the web server is accessible at http://grasp.biotools.bio.

bioinformatics↗

bioRxiv2026

Spatial multi-omics identify an immunosuppressive lipid-laden macrophage niche in primary CNS lymphoma

Primary central nervous system lymphoma (PCNSL) is histologically a subtype of diffuse large B-cell lymphoma (DLBCL), sharing genetic and transcriptomic similarity, but with distinct clinical features, particularly its confinement to the CNS and higher relapse risk. The microenvironmental basis for its divergence from systemic DLBCL remains unclear. Using spatial transcriptomic approaches (Xenium/GeoMx digital spatial profiling) in a comparative study of PCNSL (n=17) and DLBCL (n=76), we found that PCNSL, unlike systemic DLBCL, is dominated by an immunosuppressive macrophage compartment enriched for cholesterol-metabolism programs. In independent cohorts of PCNSL profiled by single-cell RNA sequencing, we validated the presence of a recurrent population of lipid-laden macrophages (LLMs): TREM2/GPNMB-expressing, lipid-remodeled cells transcriptionally distinct from resident microglia and consistent with an infiltrating monocyte origin, not previously characterized in CNS lymphoma. LLMs formed immunosuppressive niches with regulatory T cells, and using Cellscape hyperplex proteomic imaging we demonstrate that LLM-Treg spatial interactions are associated with chemotherapy response. To test whether LLMs are lymphoma-driven and functionally important, we developed an immunocompetent syngeneic PCNSL mouse model, driven by Myd88L252P and Cd79b mutations with Bcl2 overexpression. Monocyte-derived macrophages in lymphoma-bearing brain regions acquired an LLM-like state, not seen in lymphoma-free brain regions or in splenic tumors driven by the same oncogenic lesions. TREM2-SYK signaling sustained this state, and SYK inhibition reversed its tumor-supportive activity ex vivo. These findings identify the LLM program as a targetable immunosuppressive myeloid state in CNS lymphoma.

cancer biology↗

bioRxiv2026

Differential analysis of image-based chromatin tracing data with Dory

Spatial organization of the genome plays a vital role in defining cell identity and regulating gene expression. The three-dimensional (3D) genome structure can be measured by sequencing-based techniques such as Hi-C usually on the cell population level or by imaging-based techniques such as chromatin tracing at the single-cell level. Chromatin tracing is a multiplexed DNA fluorescence in situ hybridization (FISH)-based method that can directly map the 3D positions of genomic loci along individual chromosomes at single-molecule resolution. However, few computational tools are available for statistical differential analysis of chromatin tracing data, which are inherently high-dimensional, highly variable and contain many missing values. Here, we present Dory, a statistical method for identifying differential spatial patterns between two groups of chromatin traces. Dory quantifies pairwise spatial distances among genomic regions in a chromatin trace and applies multi-level statistical tests to detect significant structural differences between the two groups of traces. It produces a differential score matrix highlighting region pairs with significant distance difference. Applying Dory to multiple chromatin tracing datasets, we found that the detected chromatin structural changes were associated with alterations in A/B compartments and promoter-enhancer interactions correlated with differential gene expression. Dory is a robust and user-friendly computational tool for quantitative analysis of imaging-based 3D genome data that enables systematic exploration of chromatin architecture and its roles in gene regulation.

bioinformatics↗

bioRxiv2026

Deep models of protein evolution in time generate realistic evolutionary trajectories and functional proteins

Models of protein evolution are foundational to biology, underpinning essential techniques such as phylogenetic tree inference, ancestral sequence reconstruction, multiple sequence alignment, variant effect prediction, and protein design. Historically, for computational tractability, these models have relied on the simplifying - but biologically unrealistic - assumption that sites in a given protein evolve independently of each other. A crucial test of any evolutionary model is its ability to simulate realistic evolutionary trajectories, but the independent-sites assumption leads to simulations that poorly reflect the complexity of natural protein evolution. Here we introduce PEINT (Protein Evolution IN Time), a flexible and generalizable deep learning framework for modeling how the entire protein sequence evolves over time while incorporating complex interactions between sites. This framework enables learning realistic patterns of constrained evolutionary transitions directly from millions of protein sequences spanning diverse fold families. Furthermore, unlike classical models that require pre-aligned sequences, PEINT learns indel dynamics directly from raw, unaligned sequences, thereby eliminating potential biases from alignment errors that can lead to incorrect inference of evolutionary patterns. By capturing higher-order epistatic interactions and modeling insertion-deletion processes that classical models typically ignore, PEINT accurately reproduces key signatures of natural evolution, including conservation patterns and family-specific dynamics. When simulating evolution along phylogenetic trees, PEINT generates highly novel sequences that preserve protein function, which we validate through experimental characterization of simulated carbonic anhydrase variants that retain enzymatic activity. PEINT thus enables realistic simulation of protein evolution that explores new sequence space while respecting structural and functional constraints. This evolution-informed generative modeling framework offers a powerful new tool for advancing both phylogenetic inference and protein engineering.

evolutionary biology↗

bioRxiv2026

Ecological interactions mediate evolutionary responses to temperature in microbial communities

Microbial populations play a pivotal role in ecosystem-level responses to rising temperatures and both their ecology and evolution can be directly influenced by warming. However, predicting microbial evolution and its ecological consequences is challenging because different genotypes within a population might respond uniquely to shifts in the abiotic and biotic environment. To understand how, we quantified evolutionary and ecological responses across temperatures in a protist of wide geographic distribution in the presence and absence of other microbial species with whom they interact (i.e., heterospecifics). In the absence of heterospecifics, we found that intraspecific interactions and warming selected in favor of a particular genotype, reducing genotypic diversity. In the presence of heterospecifics, 1) genetic diversity was further reduced under warming, resulting in temperature-dependent selection; but, 2) the magnitude of this change depended on the sign (+, 0, -) of the net ecological effect on the focal species by the heterospecifics, and this effect was itself temperature-dependent. Together, our results demonstrate that both intra- and interspecific interactions can mediate how temperature shapes microbial population rapid evolutionary responses, underscoring the importance of the ecological context in predicting evolutionary outcomes under climate change.

ecology↗

bioRxiv2026

SMECT: a framework for benchmarking post-GWAS methods for spatial mapping of cells associated with human complex traits

Spatially resolving the cellular basis of complex human traits is essential for elucidating disease mechanisms, yet the comparative performance of computational methods for this task has not been systematically evaluated. Here, we present SMECT (Spatial Mapping Evaluation of Complex Traits), the first comprehensive framework for systematically evaluating methods that integrate genetic data with spatial transcriptomics. SMECT combines a biologically realistic simulation engine, a curated resource of 21 diverse real-world datasets, and a multi-faceted assessment toolkit. Using this framework, we benchmarked three state-of-the-art methods--DESE, S-LDSC, and scDRS--across 19 complex traits. Our analysis reveals a fundamental trade-off between detection sensitivity and biological specificity. We demonstrate that while S-LDSC identifies extensive spatial signals, it suffers from inflated non-specific significant associations. Conversely, scDRS is highly specific but conservative, performing well only in tissues with strong biological signals while missing subtle associations in sparser datasets. DESE overcomes these limitations, consistently achieving high power and robust specificity across both simulated and real-world scenarios. SMECT provides critical guidelines for method selection and serves as a foundational resource for developing robust spatial analyses of human complex traits. The framework is publicly available at https://github.com/pmglab/smect.

bioinformatics↗

bioRxiv2026

TDP-43 pathology is linked to motor neuron loss but is independent of stress granules in vivo

Nuclear depletion and cytoplasmic aggregation of TDP-43 define a pathological signature across amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), Alzheimers disease, and limbic-predominant age-related TDP-43 encephalopathy (LATE). Stress granule persistence and chronic activation of the integrated stress response (ISR) have been proposed to trigger this pathology, yet clinical trials targeting these pathways have failed despite robust target engagement suggesting that the prevailing model may be incomplete. Here, we use a physiologically relevant recurrent hyperthermia paradigm to directly test the relationship between stress granules and TDP-43 pathology in vivo. We find that RNA-binding proteins typically associated with stress granules persist as dynamic, phase-separated cytoplasmic assemblies in spinal motor neurons of both wild-type and mutant TDP-43 mice. These structures resolve spontaneously and are spatially distinct from TDP-43 puncta. Strikingly, in mutant TDP-43 mice with a compromised acute stress granule response, stress exposure provokes TDP-43 nuclear export and cytoplasmic deposition, culminating in selective loss of spinal -motor neurons after recurrent stress. Our results reveal that TDP-43 nuclear clearance and cytoplasmic aggregation can occur independently of stress granules in vivo, overturning a central assumption of TDP-43 pathogenesis. This paradigm shift reframes the mechanistic link between cellular stress and TDP-43 pathology, providing a new perspective for therapeutic strategies related to ISR modulation.

neuroscience↗

bioRxiv2026

Lacticaseibacillus rhamnosus GR-1 attenuates Escherichia coli-induced endometritis in mice, accompanied by modulation of uterine microbiota and metabolite profiles

ObjectiveEndometritis in dairy cows is a highly prevalent infectious disease in cattle farming, which can cause persistent inflammatory responses in the uterus. This study aimed to evaluate the therapeutic efficacy of Lacticaseibacillus rhamnosus (L. rhamnosus) GR-1 against Escherichia coli (E. coli)-induced endometritis in mice and investigate its regulatory effects on uterine microbiota and metabolites. MethodsA total of 36 female BALB/c mice aged 7-8 weeks were randomly divided into 4 groups: CONT group, ECOL group (1.0x108 CFU/mL E. coli), AMP group (0.1 mg/kg ampicillin), and GR-1 group (1.0x109 CFU/mL L. rhamnosus GR-1). Uterine morphological characteristics were observed, and the expression of uterine inflammatory cytokines, oxidative apoptosis-related genes and proteins, as well as related reproductive indices were detected. 16S rRNA sequencing and metabolomic sequencing were performed to evaluate the profiles of uterine microbiota and metabolites. ResultsL. rhamnosus GR-1 effectively alleviated E. coli-induced uterine edema and inflammatory infiltration, and modulated the levels of inflammatory factors (MPO, IL-6, IL-1{beta}, TNF-, IL-10 and MDA) in the uterus. Meanwhile, this strain elevated the levels of antioxidant factors (GSH-Px and SOD), inhibited the expression of the oxidative apoptosis-related factors Keap1, Bax and caspase-3, and upregulated that of Nrf2, HO-1, NQO1 and Bcl-2. Furthermore, treatment with L. rhamnosus GR-1 increased the abundance of beneficial uterine microbiota, promoted the accumulation of L-isoleucyl-L-proline and N-acetylcysteine, and ameliorated the pregnancy status of mice. ConclusionL. rhamnosus GR-1 enhanced uterine anti-inflammatory and antioxidant stress capacity to alleviate E. coli-induced endometritis in mice. It modulated uterine microbiota and metabolites, and also improved the reproductive capacity of mice. Thus it may provide a potential antibiotic alternative for the treatment of dairy cow endometritis.

microbiology↗

bioRxiv2026

Efficient replication of influenza D virus in the human airway underscores zoonotic potential

Influenza D virus (IDV), primarily found in livestock species, has demonstrated cross-species transmission potential, yet its threat to humans remains poorly understood. Here, we curated a panel of IDV isolates collected during field surveillance from 2011 to 2020 from swine and cattle to assess their ability to infect human airway cells as a proxy for zoonotic threat assessment. Using lung epithelial cell lines, primary well-differentiated airway epithelial cultures, and precision-cut lung slices, we demonstrated that IDV efficiently propagates in cells and tissues from the human respiratory tract, reaching titers comparable to human influenza A virus (IAV). Infection kinetics in primary porcine airway cultures and respiratory tissues mirrored those from human, suggesting similar infectivity across species. To define host responses to IDV infection, we evaluated innate immune sensing and downstream interferon signaling in human respiratory cells. IDV infection resulted in markedly reduced activation of interferon regulatory factor (IRF) signaling and diminished induction of interferon lambda 1 and interferon-stimulated genes compared to IAV, indicating inefficient activation of innate immune sensing pathways. However, IDV replication was potently restricted in interferon-pretreated cells, demonstrating sensitivity to interferon-mediated antiviral effector mechanisms once an antiviral state was established. Together, these findings show that IDV can efficiently infect the human airway while limiting innate immune sensing, a feature that may facilitate zoonotic spillover. Our study highlights the need for enhanced surveillance of IDV at the animal-human interface and provides a foundation for further investigation into its biology and potential for causing human infection and disease. SIGNIFICANCE STATEMENTInfluenza D virus (IDV) is a poorly understood virus type in the Orthomyxoviridae family. Although initially considered incapable of infecting humans, high seropositivity rates among cattle and swine workers suggest that zoonotic infections may already be occurring. However, the extent of human compatibility--and the potential for spillover--remains poorly understood. Our study demonstrates that IDV replicates efficiently in multiple human respiratory models while largely evading innate immune defenses, raising concern that only minimal evolutionary changes may be required for sustained human transmission. These findings underscore the need for further investigation into IDV biology and zoonotic risk. Such studies are critical for identifying viruses with the potential to adapt to humans before they become public health threats.

microbiology↗

bioRxiv2026

A remarkable case of conserved domain swapping in the COMMD family of proteins

The eukaryotic COMMD family of proteins are core subunits of the Commander protein complex, with a central role in endosomal membrane trafficking and signalling. Previous crystal and cryoEM structures show that COMMD and COMMD-like proteins form homo-oligomeric and hetero-decameric assemblies with a central ring structure formed by their small C-terminal COMM domains. Their -helical N-terminal (HN) domains decorate each side of these rings, and in the eukaryotic Commander complex engage the coiled-coil proteins CCDC22 and CCDC93. Here, we have determined new crystal structures of the isolated HN domains of human Commd4, Commd9 and Commd10, and find that all three proteins form domain swapped structures with a remarkably consistent topology. This occurs via a conformational change in a hinge-loop between helices 2 and 3, leading to exchange of helices 3 to 6 between protomers. The hinge-loops of Commd9 and Commd10 possess several serine and threonine residues that can be phosphorylated, and we find that specific phospho-mimicking mutations in Commd10 can promote or inhibit domain swapping. Whether the unique COMMD HN domains play any roles beyond assembly with CCDC proteins is unclear, but this work suggests a common conformational switch exists with a potential to regulate their function.

biochemistry↗

bioRxiv2026

A Most Powerful Test for Gene-Gene Interaction in the Presence of Main Effects

We consider the problem of optimal testing for genetic interaction between two variants, allowing for possible main effects. Finding a most powerful test is important because it ends a series of attempts in the literature to construct ever more powerful tests for interaction at the variant pair level. Testing under a logistic regression model is known to be underpowered, partly because patterns of enrichment in the genotypes themselves are lost when regarding genotypes solely as predictors. Instead, we use the retrospective likelihood approach, which makes use of all the data by treating genotypes as outcomes alongside affection status. Using a parsimonious parameterization of penetrance based on the risk ratio, which links directly to the population prevalence and avoids having to estimate an intercept term, we construct an approximate uniformly most powerful unbiased test for interaction. This test is based on optimal testing theory and accounts for nuisance main effects without requiring their explicit estimation. The test statistic can be easily modified for optimal testing under other modes of genetic interaction, such as recessive x recessive or dominant x dominant. We demonstrate significant power gains compared to the odds-ratio-based PLINK test, in simulation studies. Finally, we apply the test to scan for interactions in IBD cases and controls from the UK Biobank. The top SNP pairs show enrichment for a pathway related to existing therapies for IBD.

genetics↗

bioRxiv2026

Organoid-Based Transcriptomics Indicate IFIT-Associated Immune Modulation during Cryptotanshinone Treatment in Bladder Cancer

Bladder cancer (BC), particularly muscle-invasive and metastatic disease, remains a major clinical challenge despite recent advances in immunotherapy. In this study, we aimed to identify a promising antitumor compound from five candidate small molecules and to explore its potential roles in BC progression. Through antiproliferative screening, cryptotanshinone (CTS) was identified as the promising candidate. Using both two-dimensional BC cell lines and three-dimensional bladder tumor organoid models, we comprehensively evaluated the effects of CTS on cell proliferation, migration, apoptosis, and organoid growth. To further explore the underlying mechanisms, transcriptomic sequencing based on bladder cancer organoid models, protein-protein interaction network analysis, and public databases (TCGA-BLCA, TIMER, and TISIDB) were integrated to examine immune-related pathways and potential molecular targets associated with CTS. GeneMANIA network prediction and molecular docking analyses were subsequently performed to investigate upstream regulatory networks and the potential interactions between CTS and key components of the cGAS-STING-IFN-I-JAK-STAT signaling pathway. Integrative analyses suggested that IFIT1, IFIT2, and IFIT3 may function as immune-associated genes potentially linked to BC progression, patient prognosis, immune cell infiltration, and PD-1/PD-L1 expression. Molecular docking results suggested that CTS may interact with core regulatory proteins within the cGAS-STING-IFN-I-JAK-STAT pathway, potentially influencing IFIT transcriptional regulation. Collectively, these findings indicate that CTS exhibits measurable antitumor and immunomodulatory effects, which may be associated with modulation of the cGAS-STING-IFN-I-JAK-STAT-IFIT signaling axis, supporting its potential as a small-molecule candidate for bladder cancer.

cancer biology↗

bioRxiv2026

ALK R1275Q mutation drives expansion of SCP-like cells during sympathoadrenal commitment and primes neuroblastoma initiation.

Neuroblastoma (NB) is a pediatric malignancy developing in the sympathoadrenal lineage of the neural crest, characterized by clinical heterogeneity ranging from spontaneous regression to poor outcomes. Activating mutations in the receptor tyrosine kinase anaplastic lymphoma kinase (ALK) are frequently observed in both sporadic and familial NB, yet the functional role of ALK in tumor initiation is not fully understood. Using a patient-derived human induced pluripotent stem cell (iPSC) model of sympathoadrenal development, we show that upon sympathoadrenal lineage commitment, ALK R1275Q, the most common hotspot mutation found in familial NB, sustain a proliferative, immature Schwann cell precursor (SCP)-like cell state with elevated ALK signaling and increased susceptibility to MYCN-driven transformation. While ALK-mutant cells alone did not form tumors in vivo, they cooperated with MYCN to accelerate tumor initiation, suggesting that ALK R1275Q creates a permissive but insufficient state for transformation. These findings define an ALK-driven cell progenitor-like state that facilitates the initiation of NB during embryonal development.

cancer biology↗

bioRxiv2026

Proteomic composition and mutual assembly of the C2a projection in vertebrate motile cilia

The central apparatus of motile cilia, consisting of central microtubules and various protein projections, is essential for dictating the ciliary movement. Although three proteins (FAP65, FAP147, and FAP70) have been localized to the C2a projection in Chlamydomonas reinhardtii, the full protein composition and functional roles of the vertebrate C2a remain inadequately defined. Here, we use three knockout mouse models corresponding to their respective homologs (Ccdc108, Mycbpap, and Cfap70) to systematically investigate their functions in vertebrates. Notably, all three knockout strains exhibit distinct phenotypes related to primary ciliary dyskinesia (PCD), including hydrocephalus and sinusitis. The ciliary incorporation of CCDC108, MYCBPAP, and CFAP70 is essential for one anothers stability, with the loss of any single component triggering C2a collapse, which destabilizes the central pair microtubules and ultimately alters the ciliary movement pattern. Furthermore, we significantly expand the vertebrate C2a proteome by identifying ARMC3 and MYCBP as additional C2a components. Collectively, our findings illuminate the proteomic composition and strict physiological requirements of the vertebrate C2a projection, providing new insights into the molecular pathogenesis of PCD. Impact StatementDeficiency in any of the interdependent C2a proteins (CCDC108, MYCBPAP, and CFAP70) collapses this central pair microtubule-associated projection, disrupting vertebrate ciliary movement and causing primary ciliary dyskinesia phenotypes in mice.

cell biology↗