Biology subjects

Bauer, M.

Publications and source records attributed to Bauer, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Transcriptome-wide Differential Expression and Splicing in Inflammatory Bowel Disease Patients

The inflammatory bowel diseases (IBD), comprising mainly Crohn's disease (CD) and ulcerative colitis (UC), are characterized by chronic intestinal inflammation driven in part by complex genetic and gene regulatory mechanisms. Although transcriptomic studies have defined broad expression changes in IBD, the contribution of alternative splicing to disease-associated molecular variation remains less clear. We therefore integrated differential expression (DE) and differential splicing (DS) analyses in macroscopically uninvolved colonic mucosal biopsies from patients with either CD or UC along with non-IBD controls to define gene expression and intron-usage changes across disease subtypes. We identified 491 DS and 316 DE genes in CD vs. non-IBD, and 1,298 DS and 1,107 DE genes in UC vs. non-IBD. DS and DE genes were nearly mutually exclusive, with no overlapping genes in CD and 16 in UC. Consistent with this result, pathway analysis showed that differentially expressed and differentially spliced genes were associated with related but distinct biological programs. DE genes were involved in chromatin organization, transcriptional regulation, and metabolic pathways for glycans and drugs, whereas DS genes were enriched for splicing, cellular signaling, and lipid metabolism. We found substantial similarity in enriched pathways across CD and UC with some notable exceptions, including increased enrichment of DS and DE genes involved in extracellular vesicles and exosomes in CD and enrichment of DS genes in ER-to-Golgi trafficking and stress granules in UC. Direct comparisons of CD and UC patients additionally show differential splicing usage in genes involved in cell adhesion pathways. These findings identify alternative splicing as a major contributor to transcriptomic changes in IBD that is largely distinct from changes in expression level and provide a broader view of molecular contributors to IBD.

genomics↗

bioRxiv2026

Targeting poorly differentiated thyroid cancer with bispecific antibodies and CAR T cells from the human anti-TSHR autoantibody repertoire

Background: Poorly differentiated thyroid carcinoma (PDTC) has no effective systemic treatment option once radioactive iodine and tyrosine kinase inhibitors fail. The thyroid-stimulating hormone receptor (TSHR) is highly tissue-restricted and the anti-TSHR autoantibody repertoire of thyroid autoimmunity offers sequence-defined, fully human binders. We asked whether this repertoire can be converted into an off-the-shelf T cell-redirecting therapy for PDTC. Methods: TSHR expression was profiled on a 151-case thyroid cancer tissue microarray (TMA), 50 healthy controls and on fresh tumor material. Eight anti-TSHR clones, four of human autoimmune origin (M22, K1-18, K1-70, 5C9) and four murine (IRI-SAb2, IRI-SAb3, 9D33, 1H7), were reformatted as CD3-engaging bispecific antibodies (bsAbs; anti-TSHR Fab x anti-CD3 scFv) and, for leading clones, as chimeric antigen receptor (CAR) T cells. Activity was compared in vitro, across graded and mixed antigen densities and in a CAL-62-Luc-TSHR xenograft model, using healthy-donor (HD) or thyroid cancer-patient T cells. Results: TSHR was retained on a substantial fraction of PDTC, including metastatic lesions. Both formats mediated potent, antigen-selective killing and the leading bsAbs suppressed xenograft growth in vivo. For CAR T cells, scFv heavy/light-chain orientation was decisive. Anti-TSHR bsAbs cleared mixed cultures far beyond the antigen-positive fraction matching mosunetuzumab and indicating a modality-intrinsic bystander effect. Patient-derived T cells obtained on or after oncological treatment retained full effector function. Conclusions: The anti-TSHR autoantibody repertoire provides a promising source of binders for off-the-shelf bispecific antibodies targeting TSHR-positive thyroid cancer, while CAR T cells offer an autologous alternative.

cancer biology↗

bioRxiv2026

Design of synthetic activators for programmable gene expression

Transcription factors control gene expression by recruiting transcriptional coactivators through intrinsically disordered transcriptional activation domains (TADs), whose weak and promiscuous interactions make it difficult to establish quantitative relationships between coactivator recruitment and transcriptional output, and to precisely modulate gene expression. To overcome this limitation, we set out to design coactivator-recruiting proteins using AlphaFold3-predicted TAD-coactivator interactions as a guide. We developed a high-throughput functional screening platform in mammalian cells and identified over 300 well folded nanomolar affinity binders to the transcription coactivators Mediator (multiple subunits), BRD4, NCOA, and p300; targeted interface mutations enabled systematic tuning of their binding affinities. Using a panel of p300 binders spanning nanomolar to micromolar affinities, we found an ultrasensitive relationship between coactivator-binding affinity and transcriptional output, with a sharp transcriptional activation threshold at ~500 nM. Incorporating p300 binder designs into CRISPRa yielded compact synthetic effectors that drove stronger activation than VPR across multiple genomic loci with minimal detectable cytotoxicity. Combining p300- and Mediator-specific binders further enhanced transcription, revealing functional synergy between these coactivators. Together, our work establishes a quantitative framework linking coactivator-binding affinity to transcriptional output and provides compact synthetic effectors for programmable gene activation.

synthetic biology↗

bioRxiv2026

Empirical Geometry-Guided Modeling Enables Robust, High-Throughput Collagen Structure Prediction

Protein structure prediction is increasingly dominated by large learned generative models, yet for proteins governed by strong structural constraints, much of the relevant conformational space may be captured by substantially more compact representations. Collagen provides a compelling test case: its repeating Gly-X-Y sequence, restricted backbone conformations, and conserved triple-helical topology define a highly constrained structural manifold. Here, we develop a Collagen-specific Deterministic Structure Modeler (CDSM), extending the empirical geometric parameterization of THeBuScr into a robust, all-atom structure-prediction pipeline, and benchmark it against AlphaFold 3, Boltz-2, Chai-1, and Protenix-v1 on 80 experimentally resolved collagen triple-helical structures. CDSM increases coverage of this benchmark from 8.8% for native THeBuScr to 93.8%. Across the 75 structures successfully predicted by all methods, CDSM closely reproduces experimental backbone and global geometry, with fewer large-error predictions, while the learned models achieve modestly higher local and side-chain accuracy. When evaluated only on structures deposited after each learned model's training-data cutoff, CDSM becomes more competitive, with aggregate win rates increasing from 29% to 55% for TM-score and from 40% to 65% for backbone RMSD, while CDSM performance remains comparatively stable across the same subsets. CDSM generates structures in 2.4 s on a single CPU core at approximately $3 x 10^-5 per structure, making it 400 to 790x cheaper than the learned methods even when each is run on its lowest-cost compatible GPU. These results demonstrate how identifying and explicitly encoding relevant geometric constraints can dramatically compress a structure-prediction problem, retaining much of the accuracy at orders-of-magnitude lower computational cost. More broadly, CDSM illustrates the potential for compact, executable scientific representations that complement large learned models, and motivates future AI-driven searches over algorithms, representations, and empirical parameterizations to discover and continually refine such models for other structural protein domains.

bioinformatics↗

bioRxiv2026

Sepsis Subtypes in Blood and Liver Define Precision Strategy for CXCR2 Blockade

Sepsis is classified into distinct transcriptomic endotypes. Yet specific cellular drivers for those subtypes remain ambiguous. Although dysregulated CXCL8-CXCR1/2 signaling and neutrophil hyperactivation are implicated in severe endotypes, the therapeutic window and organ-specific consequences of CXCR2 antagonism remain unclear. To determine whether murine transcriptomic subtypes (MTSs) recapitulate human consensus transcriptomic subtypes (CTSs) and evaluate how subtype state dictates the efficacy and trade-offs of Danirixin in polymicrobial sepsis. We reanalyzed septic patients whole-blood CITE-seq data to characterize CXCL8- CXCR2 signaling. Using a severity-stratified murine polymicrobial model, we evaluated Danirixins efficacy. Endpoints included 7-day survival, cytokine profiling, and hepatic histology. Early (24-h) multi-compartment assessments of bacterial burden, NETosis, immune infiltration, and paired blood-liver bulk RNA sequencing informed MTS classification and mechanistic insights. Human CTS1 exhibited neutrophil and progenitor expansion, elevated CXCL8/CD11b expression, and reduced CXCR2, defining a hyperactivated, dysregulated myeloid state. Applying CTS-derived gene signatures to murine tissues identified three MTSs correlating with pathogen load and interleukin-6. Human CTS1 dysregulation was mirrored in murine MTS3. Crucially, Danirixin improved 7-day survival in MTS3 sepsis. Conversely, in MTS1, Danirixin attenuated systemic NETosis and hepatic injury but exacerbated bacterial dissemination, without improving survival. Murine transcriptomic subtypes translationally model human sepsis subtypes. In severely dysregulated host-response states (MTS3/CTS1), CXCR2 antagonism effectively mitigates maladaptive, neutrophil-driven immunopathology. However, in less severe subtypes, it compromises early bacterial containment. These findings therefore support for endotype-guided precision targeting of CXCR2 in sepsis. One Sentence SummaryTargeting CXCR2 improves sepsis survival only in a specific molecular subtype, showing that host traits dictate therapeutic outcomes.

systems biology↗

bioRxiv2026

Epigenetic and brain age across development: Performance and associations in the MIND consortium

Understanding how biological age measures perform across development lays the groundwork for investigations into lifespan trajectories of healthy aging. We provide the most comprehensive assessment of epigenetic and brain age models across development (birth to 24 years; [≤]20,917 observations across 15 cohorts), evaluating how these models associate with chronological age and with each other, and how these associations change across development. Chronological age-prediction accuracy of epigenetic and brain age models was modest and varied substantially. Accuracy improved with age and stabilized by middle childhood. Few brain and fewer epigenetic clocks performed stably and well across all developmental stages. Performance was better when age range and tissue corresponded between training and testing data. Associations between epigenetic-brain age residuals were small, and changed little across development, tissues or clock generation. Given this developmentally dynamic system of epigenetic-brain age performances and associations, we give key recommendations to improve developmental research in this field.

neuroscience↗

bioRxiv2026

Dorsomedial Striatum Calcium Permeable AMPA Receptors in the Development of Aversion-Resistant Alcohol Drinking

RationaleAlcohol use disorder is defined by drinking alcohol despite knowledge of negative consequences, often referred to as aversion-resistant drinking (ARD). The dorsomedial (DMS) and dorsolateral striatum (DLS) are necessary for goal-directed and habitual action selection, respectively. Leading hypotheses posit that once drug use becomes compulsive, DMS dependence degrades while DLS dependence increases. This shift may be mediated by changes in synaptic weights from glutamatergic inputs. ObjectivesUsing a combination of western-blot, micro-injections, and ex-vivo electrophysiology, we investigated the role of -Amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors AMPAR, which drive glutamatergic transmission, during quinine-adulterated alcohol (QuA) drinking in the DMS and DLS across the development of ARD. ResultsWe found that AMPAR subunit composition and function change in the DMS across the development of ARD whereby, calcium permeable (CP) - AMPARs drive behavior. Western blots revealed a negative relationship between DMS GluA1 and QuA drinking in aversion-sensitive mice and positive relationships between DMS or DLS GluA1/A2 ratios and QuA drinking in ARD mice. DMS CP-AMPAR antagonism caused an increase in QuA drinking suggesting that CP-AMPARs in the DMS prevent ARD. Ex-vivo electrophysiology of DMS spiny projection neurons (SPNs) revealed that ARD mice had a greater rectification index than aversion-sensitive mice indicating that SPNs in the DMS express more CP-AMPARs following the development of ARD. ConclusionsThese data provide evidence that repeated alcohol binges alter DMS CP-AMPAR activity, where initial DMS activity acts to prevent ARD but after repeated binges that result in ARD, DMS SPNs recruit CP-AMPARs.

neuroscience↗

bioRxiv2026

Transient protein phosphorylation promotes disease tolerance to sepsis

One of the enduring paradoxes of sepsis is that organs fail despite little evidence of irreversible tissue injury. Emerging evidence suggests that this state reflects a regulated metabolic shutdown within host tissues, yet whether such hypometabolism contributes to pathology or promotes survival remains unclear. This phenomenon resembles torpor, a physiological state of profound hypometabolism induced by environmental stress and mediated through reversible protein phosphorylation. Septic hypometabolism is identified here as a conserved tissue-specific metabolic adaptation which is characterized by transient activation of Glycogen Synthase Kinase (GSK)3{beta}. This activation reduced disease severity of bacterial sepsis without affecting the hosts pathogen burden, indicating that GSK3{beta} activity promotes disease tolerance to infection. Consistent with these findings, plasma signatures associated with GSK3{beta} inhibition correlated with worse clinical outcomes in patients with sepsis. Together, these results define septic hypometabolism as a torpor-like response and identify reversible phosphorylation as a key mechanism governing host adaptation to severe bacterial infection.

immunology↗

bioRxiv2026

Viral rewiring of APC/C-CDC20 drives Aurora B hyperubiquitination, mitotic regression and polyploidy

Cytokinesis requires elaborate processes in the midbody, including the timely inactivation of Aurora B kinase (AurB) and membrane fission to separate the daughter cells. Here, we show that human adenovirus (AdV) perturbs midbody function, prevents daughter separation and induces cytoplasmic regression of both cancer cells and primary diploid human airway basal cells resulting in polyploidy. Infected cells undergo cleavage furrow regression after midbody formation driven by the viral protein E4orf4 independently of E4orf4 interaction with protein phosphatase 2A. The co-activator of the anaphase-promoting complex/cyclosome (APC/C), CDC20 is upregulated in AdV infection and required for regression. E4orf4 directly interacts with CDC20 and redirects the E3-ubiquitin ligase APC/C-CDC20 towards AurB, promoting hyperubiquitination and premature extraction of AurB from the midbody. Loss of midbody-associated AurB coincides with midbody collapse and furrow regression. Our findings reveal a previously unrecognized APC/C-CDC20-dependent pathway controlling late cytokinesis through AurB extraction from the midbody.

cell biology↗

bioRxiv2026

Proteostasis sustains T cell differentiation potential and tumor-infiltrating lymphocyte function

Tumor-infiltrating lymphocytes (TIL) often fail to restrain tumor growth due to progressive differentiation to an exhausted state. In healthy tissues, tissue-resident memory T cells (TRM) maintain protection for years, and patient tumors that contain TIL with TRM features are associated with better prognosis. Proteomic and transcriptomic profiling of T cell populations identified proteostasis as a significant factor distinguishing TRM and progenitor-exhausted TIL from terminally-exhausted TIL, including loss of E3 ubiquitin ligases NEURL3, RNF149, and WSB1, with accumulation of unfolded proteins in spite of functional proteasome activity. Enforced expression of these ligases by TIL preserved stem-like TCF1+ populations and improved anti-tumor function, whereas their knockout impaired TIL and altered T cell differentiation in acute infection. Sustained ligase expression rescued accumulation of unfolded proteins in TIL and improved immunotherapy outcome in preclinical models, highlighting the critical role of proteostasis in TIL function and identifying new avenues for advancing cancer immunotherapy.

immunology↗

bioRxiv2025

A STAT5B-driven mouse model of hepatosplenic γδ T-cell lymphoma reveals therapeutic efficacy of JAK inhibition

Hepatosplenic T-cell lymphoma (HSTCL) is a rare and aggressive neoplasm associated with poor responses to standard chemotherapy regimens and low survival rates. No targeted therapies are available for HSTCL, and preclinical models to test new treatment options have not been established. The JAK-STAT signaling cascade is a key dysregulated pathway in HSTCL, and STAT5BN642His the most frequent somatic mutation in the disease. Here, we report on newly established clonal, murine {gamma}{delta} T-cell lymphoma cell lines initiated and driven by oncogenic STAT5BN642H, which recapitulate key immunophenotypic features, gene expression profiles and typically low cytolytic activity of patient-derived human HSTCL cells. CRISPR-Cas9 mediated knockout demonstrated growth dependence on STAT5BN642H. Murine C15 cells were allo-engrafted intravenously into both immunodeficient and immunocompetent mice to model an aggressive HSTCL-like disease at high penetrance, with recipient mice displaying hepatosplenomegaly and destructive {gamma}{delta} T cell organ infiltration, including bone marrow and blood involvement. We identified the potential of JAK inhibition as a targeted treatment strategy for HSTCL, and found the clinically approved JAK inhibitor upadacitinib to display selective anti-tumor efficacy against STAT5B-mutated HSTCL cell lines in vitro, in vivo, and in primary HSTCL patient samples. Overall, we describe the first robust STAT5B-driven preclinical model resembling features of HSTCL in an immune competent setting. This tool is expected to accelerate the study of HSTCL disease mechanisms and the testing of novel therapies. Our data further present the JAK inhibitor upadacitinib as a promising targeted treatment option for STAT5B-mutated HSTCL.

cancer biology↗

bioRxiv2025

Estrogen Signaling During Abrupt Involution Leads to Long-Term Metabolic Dysfunction Similar to Estrogen Receptor Negative Breast Cancer

Epidemiological data links lack of breastfeeding with increased risk of breast cancer. Breast tissue undergoes remodeling to pre-pregnancy state after birth through involution. Long-term breastfeeding leads to gradual involution (GI). Lack of breastfeeding leads to abrupt involution (AI). While estrogen impacts repopulation of adipocytes, AI causes several precancerous changes in the mouse mammary gland. The impact of AI on adipocyte repopulation and metabolism is yet to be elucidated. ObjectivesTo investigate effects of AI on mammary gland metabolism and its potential link to breast cancer. MethodsAt partum (day 0), FVB/n dams were randomized to AI or GI and standardized to 6 pups. AI mice had pups removed on day 7 postpartum to mimic short-term breastfeeding. GI mice had 3 pups each were removed on day 28 and 31 postpartum to mimic gradual weaning. Mammary glands were harvested on day 28, 56, and 120 postpartum. Subset of AI mice had long-term sustained release tamoxifen placed subscapular on day 8 postpartum. Metabolic changes were assessed using: 1) transcriptional; 2) functional; 3) oxidative stress; and 4) metabolites analysis. ResultsDay 28 GI glands sustains/continues milk synthesis pathways impacting metabolic comparison with day28 AI glands. Day 28 AI when compared to day 56 GI showed upregulation of estrogen signaling, neutrophil degranulation, glucose metabolism, RNA synthesis, and down regulation of adipogenesis and glycolysis. At day 120, AI glands had downregulation of oxidative phosphorylation and upregulation of mitochondria dysfunction similar to pregnancy associated estrogen receptor negative breast cancer. Tamoxifen treatment of AI dams showed metabolic pathways and estrogen signaling similar to that of GI glands on day 28. ConclusionEarly metabolic phenotypes in AI and GI glands may be caused by differences in adipocyte repopulation related to estrogen signaling. Long-term metabolic effects of AI lead to similar metabolic effects found in breast cancer.

cancer biology↗

bioRxiv2025

Mapping neural activity during naturalistic visual and memory search

In everyday life, individuals often search for one of several items stored in memory. This cognitive process, known as hybrid search, is critical for tasks like navigating using landmarks. While the behavioral aspects of hybrid search have been extensively studied, the underlying neural mechanisms remain less understood. In this study, we combined concurrent magnetoencephalography (MEG) and eye movement recordings to investigate the oscillatory and evoked neural dynamics supporting hybrid search in naturalistic settings. Twenty-one participants (12 males, 9 females) performed a free-viewing task involving visual search for targets embedded in memory (hybrid search) across naturalistic scenes. Time-Frequency analyses revealed specific neural signatures during memory encoding, retention, and visual search. During encoding and retention, posterior alpha-band power decreased with memory load, reflecting heightened perceptual and mnemonic demands. During visual search, frontoparietal beta-band activity scaled with memory load, suggesting increased cognitive control. By aligning MEG signals to eye movement events and applying source reconstruction, we identified an early visually evoked lambda response, localized to V1, followed by a distributed P3m component, with maximum activation in the right inferior parietal lobe, that discriminated target from distractor fixations. Together, these findings demonstrate how oscillatory and evoked responses dynamically support hybrid search in naturalistic settings, revealing how memory, attention, and visual processing interact during active vision. Significance statementUnderstanding how the brain supports everyday tasks, like searching for familiar objects, requires studying cognition under realistic conditions, yet most knowledge comes from highly controlled lab tasks with simple stimuli. Here, we combined MEG and eye-tracking to examine how the brain supports free-viewing hybrid search -looking for any of several remembered items-across natural scenes. We found memory load modulations in posterior alpha oscillations during encoding and retention, as well as in frontoparietal beta oscillations during search. By time-locking neural signals to eye movements, we identified a robust marker of target detection. These findings provide direct evidence of how attention, memory, and vision interact in realistic settings, helping bridge the gap between controlled experimental paradigms and real-world cognition.

neuroscience↗

bioRxiv2025

A bioenergetic basis for multiorgan dysfunction in sepsis

Sepsis is a life-threatening multiorgan dysfunction that develops from a maladaptive host response to infection1. With an estimated 49 million cases per year and [~]11 million related deaths2, sepsis is a global WHO health priority3. Failure to overcome sepsis morbidity and lethality4,5 calls for alternative therapeutic approaches6-8. Here we report that adipocyte lipolysis is vital to prevent the pathogenesis of sepsis in mice. This protective response is evolutionary conserved, producing a plasma lipidomic profile9,10 that reflects on the severity of clinical sepsis. Mechanistically, adipocyte lipolysis fuels energy metabolism to sustain adaptive thermoregulation to infection, via insulin production and insulin receptor (INSR) signaling in adipocytes. This metabolic-based defense strategy does not impact on bacterial burden, establishing disease tolerance to infection11-14. In conclusion, adipocyte lipolysis induces insulin to rewire energy metabolism and support organ function in response to infection.

pathology↗

bioRxiv2025

Atom level enzyme active site scaffolding using RFdiffusion2

De novo enzyme design starts from ideal active site descriptions consisting of constellations of catalytic residue functional groups around reaction transition state(s), and seeks to generate protein structures that can accurately hold the site in place. Highly active enzymes have been designed starting from such descriptions using the generative AI method RFdiffusion [1-3], but there are two current methodological limitations. First, the geometry of the active site can only be specified at the residue level, so for each catalytic residue functional group placed around the reaction transition state, the possible locations of the residue backbone must be enumerated by building side chain rotamers back from the functional group. Second, the location of the catalytic residues along the sequence must be specified in advance, which considerably limits the space of solutions which can be sampled. Here we describe a new deep generative method, Rosetta Fold diffusion 2 (RFdiffusion2), that solves both problems, enabling enzymes to be designed from sequence agnostic descriptions of functional group locations without inverse rotamer generation. We first evaluate RFdiffusion2 on an in silico enzyme design benchmark of 41 diverse active sites and find that it is able to successfully build proteins scaffolding all 41 sites, compared to 16/41 with prior state-of-the-art deep learning methods. Next, we design enzymes around three diverse catalytic sites and characterize the designs experimentally; in each case we identify active catalysts in testing less than 96 sequences. RFdiffusion2 demonstrates the potential of atomic resolution generative models for the design of de novo enzymes directly from their reaction mechanisms.

biochemistry↗

bioRxiv2025

De novo design of miniprotein agonists and antagonists targeting G protein-coupled receptors

G protein-coupled receptors (GPCRs) play key roles in physiology and are central targets for drug discovery and development, but the design of protein agonists and antagonists has been challenging as GPCRs are integral membrane proteins and conformationally dynamic. Here we describe computational de novo design methods and a high throughput "receptor diversion" microscopy-based screen for generating GPCR binding miniproteins with high affinity, potency and selectivity, and the use of these methods to generate agonists for MRGPRX1, NK1R and CCR5, as well as antagonists for CXCR4, CCR5, OXTR, GLP1R, GIPR, GCGR, PTH1R and CGRPR.. Cryo-electron microscopy data reveals atomic-level agreement between designed and experimentally determined structures for CGRPR- and CXCR4-bound antagonists and MRGPRX1-bound agonists. Our de novo design and screening approach opens new frontiers in GPCR drug discovery and development.

bioengineering↗

bioRxiv2025

LILRA5 functions to induce ROS production on innate immune cells

Activating immune receptors provide mechanisms for phagocytes to elicit important effector functions that promote the killing of microbes. Leukocyte immunoglobulin-like receptor A5 (LILRA5) an orphan immune receptor expressed by human phagocytes and co-localising with FcR{gamma}, remains poorly characterised. To address this, we developed a highly-specific anti-LILRA5 monoclonal antibody that has agonistic properties. Using a specific anti-LILRA5 antibody, we show LILRA5 expression on naive monocytes and neutrophils, and that ligation of LILRA5 stimulates ROS production. While increased LILRA5 transcript copy numbers have been associated with sepsis, we also observed increased levels in patients with systemic infection but without sepsis complications. Ex vivo bacterial infection of whole blood did not alter surface LILRA5 expression, but LPS stimulation changed expression levels. This indicates that surface LILRA5 expression is dynamic and likely regulated posttranscriptionally, changing responses to different stimuli or over time. Soluble (s)LILRA5 was enhanced in sera from sepsis patients and in supernatants of monocytes that were LPS-stimulated, indicative that shedding of LILRA5 from cell surfaces or that expression of sLILRA5 isoforms provides a mechanism to regulate surface LILRA5 expression levels. Finally, we show that altered surface LILRA5 expression influences LILRA5-induced ROS production capacity. We propose that LILRA5 is a dynamically regulated activating receptor expressed on phagocytes that can stimulate ROS production.

immunology↗

bioRxiv2025

Anti-resonance in developmental signaling regulates cell fate decisions

Cells process dynamic signaling inputs to regulate fate decisions during development. While oscillations or waves in key developmental pathways, such as Wnt, have been widely observed, the principles governing how cells decode these signals remain unclear. By leveraging optogenetic control of the Wnt signaling pathway in both HEK293T cells and H9 human embryonic stem cells, we systematically map the relationship between signal frequency and downstream pathway activation. We find that cells exhibit a minimal response to Wnt at certain frequencies, a behavior we term anti-resonance. We developed both detailed biochemical and simplified hidden variable models that explain how anti-resonance emerges from the interplay between fast and slow pathway dynamics. Remarkably, we find that frequency directly influences cell fate decisions involved in human gastrulation; signals delivered at anti-resonant frequencies result in dramatically reduced mesoderm differentiation. Our work reveals a previously unknown mechanism of how cells decode dynamic signals and how anti-resonance may filter against spurious activation. These findings establish new insights into how cells decode dynamic signals with implications for tissue engineering, regenerative medicine, and cancer biology. Significance StatementWnt signaling is responsible for driving stem cell differentiation. Our study explores a wide range of temporal patterns of Wnt activation using state-of-the-art optogenetics, advanced imaging and modeling. We identify anti-resonant frequencies that suppress mesoderm differentiation. We confirm this anti-resonant suppression for two human cell lines, HEK and embryonic stem cells, and expect that it also occurs in other pathways, as it arises from the interplay of different timescales along the pathway. Our work opens new avenues for systematically exploring signal spaces that natural systems can robustly respond to, and has broader implications for tissue engineering, regenerative medicine, and cancer biology.

cell biology↗