Biology subjects

Jiang, J.

Publications and source records attributed to Jiang, J..

At least 91 records · Page 5Linked to original sources

bioRxiv2025

Designing signaling environments to modulate neural progenitor cell differentiation with regulatory network models

During development, combinatorial signals modulate progenitor differentiation to build populations of diverse cell types. Classical deterministic fate-control circuits focus on stable commitment but do not explain how a diverse cell population is generated and tuned by signals. Here, using single-cell RNA-seq profiling of neural progenitor cells (NPCs) upon combinatorial signal inputs, we identify a candidate circuit-level mechanism for controlling cell type compositions through a noise-gated toggle switch. With 40 signaling conditions, we show that combinatorial signal inputs modulate the neuronal-glial population proportions following a simple log-linear model. Regulatory network models built by D-SPIN quantitatively capture cell state distribution shifts induced by signal combinations, and indicate a circuit model for the probabilistic fate specification by a toggle switch with controlled transcriptional heterogeneity. Noise levels drive the system from highly plastic to committed states, allowing the relative level of signal inputs to shift population structures. The model further predicts an early bipotent state expressing lineage-specifying factors of both fates, which we verify in our single-cell profiling experiment and a mouse embryonic visual cortex development dataset. Our work identifies a design principle of noise-driven additive regulation in the logarithmic cell-fate probability space, providing a new strategy for population-level stem cell control.

systems biology↗

bioRxiv2025

A mobile circular DNA element drives memory-related processes in mice

Extrachromosomal circular DNAs (ecDNAs) are double stranded, closed loop DNA molecules that act independently of the genome. Here we report the discovery of a brain-enriched ecDNA, ecCldn34d, that regulates the transcriptional state of plasticity-related genes and is temporally associated with the stability of fear memories. ecDNA therefore represents a novel class of mobile DNA elements that are involved in experience-dependent neuroadaptation.

neuroscience↗

bioRxiv2025

Local translation of circular RNAs is required for synaptic activity and memory

Circular RNAs (circRNAs) are enriched in synapses and implicated in cognitive processes, and recent studies have shown that circRNAs can encode micropeptides, which suggests that there may be novel synaptic proteoforms in the brain that await discovery. Here we report widespread learning-induced local circRNA translation in the prefrontal cortex of male C57BL/6 mice. More than 1500 synapse-enriched circRNAs contain active IRES elements, with 842 interacting with the ribosome and 241 exhibiting direct evidence of activity-induced translation. We discovered a synapse-enriched micropeptide (P1) that is derived from a single exon circRNA, the mRNA host of which encodes an enzyme associated with protein repair. Although P1 is only a third of the size of the full-length protein, it is locally expressed, enzymatically active, and interacts with plasticity-related proteins, including CaMKII. In addition to direct effects on synaptic activity, targeted P1 knockdown impairs whereas its overexpression enhances fear extinction memory. These findings shed new light on the dark proteome in the brain and reveal local circRNA translation as a novel mechanism of plasticity and memory.

neuroscience↗

bioRxiv2025

Hypercholesterolaemia promotes epigenetic memory in hematopoietic stem cells that persists after lipid lowering and causes systemic immunometabolic dysfunction mediated by macrophage metabolic reprogramming

In patients with atherosclerotic cardiovascular disease (ASCVD) lowering LDL cholesterol (LDL-C) reduces the risk of adverse cardiovascular events. However, these patients remain at continued risk of adverse cardiovascular events despite achieving optimal LDL-C lowering. We hypothesised that this residual risk is mediated by epigenetic programming of haematopoietic stem cells (HSC) which persists after cholesterol levels are lowered and results in sustained effects on innate immune cell metabolism, that is not resolved by cholesterol lowering. We found that exposure to high cholesterol (HC) in vivo induced long-term metabolic changes in macrophages differentiated ex vivo from bone marrow, leading to a pro-inflammatory profile; these changes persisted in vivo despite cholesterol lowering. HSC from HC mice had altered chromatin accessibility that persisted after cholesterol lowering and was also present in bone marrow monocytes and tissue resident macrophages. HC provoked RUNX1-dependent downregulation of stearoyl-CoA desaturase (SCD) which reduced mono-unsaturated fatty acid (MUFA) availability for OxPhos in murine and human monocytes and macrophages. Supplementation with MUFA restored OxPhos capacity and promoted a shift towards a less pro-inflammatory macrophage phenotype in HC-trained BMDM. Bone marrow chimera and lineage tracking studies revealed that prior exposure of HSC to HC conferred adverse systemic metabolic effects on normocholesterolemic mice, with increased adipose tissue mass and increased migration of macrophages derived from HC-exposed HSC into adipose tissue, resulting in increased adipose tissue inflammation and systemic glucose intolerance. These findings indicate that HC results in long-lasting immuno-epigenetic memory in HSC which is refractory to lipid lowering, and provide strong evidence that exposure to HC can have prolonged consequences that require new therapeutic approaches, beyond cholesterol lowering.

immunology↗

bioRxiv2025

Evolutionary remodeling of non-canonical ORF translation in mammals

Non-canonical open reading frames (ncORFs) are pervasive within transcripts annotated as "non-coding" or "untranslated regions" of mRNAs, yet their landscape under normal physiological conditions remains to be fully resolved, particularly outside humans. Here we applied a stringent and standardized pipeline to hundreds of high-quality ribosome profiling libraries from normal mammalian tissues and cell types, identifying 11,623 human and 16,485 mouse ncORFs. Evolutionary analyses revealed that thousands of ncORFs are subject to coding constraint and exhibit lineage-specific conservation, underscoring their functional potential. Ancient ncORFs are preferentially highly translated, broadly expressed, and enriched for lineage-specific conservation. Co-expression patterns further indicate that many ncORFs, especially ancient ones, are cotranslated with canonical coding sequences, consistent with functions mediated through protein-protein interactions. Together, these findings establish a comprehensive atlas of mammalian ncORFs and provide fundamental insights into their evolutionary dynamics and functional integration within the proteome.

genomics↗

bioRxiv2025

Fluorescent protein-based ticker tapes for multiplexed recordings of transcriptional histories in single cells in culture and in vivo

Recording and imaging of promoter activities in real time is critical for deciphering cellular states and dynamic signaling crosstalk, but technologies capable of simultaneously capturing multiple transient events in living cells are lacking. Here, we custom-design fluorescent protein-based ticker tapes (FPTT) for multiplexed and longitudinal recording of physiological activities in single cells. FPTT integrates multi-spectral monomeric fluorescent proteins with self-assembling protein fibers, enabling massively parallel analysis of signaling dynamics under varying cellular conditions. Using FPTT, we were able to log dose-dependent and reversible transcriptional histories of endogenous cFos signaling in primary hippocampus neurons at a 3-hour temporal resolution via biological timestamps and an extended recording time of over 8 days. Furthermore, we expanded the imaging toolset by engineering genetically encoded FPTT variants for human NF{kappa}B, JAK/STAT3, mTOR, NFAT and cAMP signaling, allowing for the quantification of potential crosstalk between cFos and NF{kappa}B pathways in neurons, multiplexed recording of STAT3- and cAMP-specific promoters during drug-induced liver injury in mice, as well as simultaneous analysis of up to four major signaling pathways involved in experimental T-cell activation. This platform advances single-cell analysis by providing a versatile tool to investigate transcriptional histories and signaling interplay across diverse biological contexts, with broad applications in developmental biology and disease modeling.

synthetic biology↗

bioRxiv2025

Biodegradation of the endocrine-disrupting compound bisphenol F by Sphingobium yanoikuyae DN12

Bisphenol F (BPF) is an emerging environmental pollutant widely present in surface water and wastewater systems. Microbial activity is crucial in driving its degradation, offering a potential avenue for mitigating its environmental impact. Although the degradation pathway for BPF has been identified in various bacteria, the biodegradation mechanisms remain unclear. In this study, we isolated a highly efficient BPF-degrading strain of Sphingobium yanoikuyae DN12, which could utilize BPF as the sole carbon source and energy source for growth, from a river sediment in Anhui Province China. Through Ultra performance liquid chromatography high-resolution mass spectrometry (UPLC-HRMS) analysis, we found that oxidation and hydrolysis are key steps for BPF biodegradation. Utilizing whole-genome sequencing, comparative transcriptomics analysis and biochemical identification, a gene cluster bpf was identified to be involved in BPF degradation. BpfAB is a two-component oxidoreductase responsible for converting BPF to 4,4-dihydroxybenzophenone (DHBP). BpfC is a Baeyer-Villiger monooxygenase (BVMO) responsible for converting DHBP to 4-hydroxyphenyl-4-hydroxybenzoate (HPHB). Isotope tracing demonstrated that the oxygen atom incorporated by BpfAB originates from water, whereas that incorporated by BpfC derives from molecular oxygen (O2). BpfD is an /{beta} hydrolase responsible for converting HPHB to 4-hydroxybenzoate (4HB) and 1,4-hydroquinone (HQ). Analysis of the taxonomic and habitat of 325 prokaryotic genomes revealed that BpfA-like homologs are predominantly found in the phylum Pseudomonadota, primarily inhabiting soil and aquatic environments. This study enhances our understanding of the biodegradation mechanism of BPF, and provides guidance for the effective remediation of BPF-contaminated environments. IMPORTANCEBPF is a widely used alternative to bisphenol A and poses a growing threat to ecosystems and human health due to its environmental persistence and endocrine-disrupting effects. Although microbial degradation pathways for BPF have been reported, the key enzymes involved and their catalytic mechanisms remain unclear. This work reports the isolation of a Sphingobium strain capable of mineralizing BPF and the genetic basis for the catabolic pathway. Three enzymes--a two-component oxidoreductase, a Baeyer-Villiger monooxygenase, and an /{beta} hydrolase--were biochemically characterized and shown to catalyze the three critical steps in BPF degradation. These findings provide insights into the biochemical processes involved in the microbial degradation of BPF.

microbiology↗

bioRxiv2025

Nutrient-Sensing Nuclear Receptor PPARα Controls Liver Proteostasis

Peroxisome proliferator-activated receptor alpha (PPAR) is a nuclear receptor that orchestrates metabolic adaptation to fasting by regulating hepatic lipid and glucose metabolism. While these functions are well established, its role in protein homeostasis, another energy-intensive process, has remained unclear. Here, we performed multi-omics analyses in wild-type and PPAR knockout mice treated with the PPAR agonist fenofibrate to define its broader role in proteostasis. Interestingly, chronic PPAR activation suppressed hepatic secretory pathways, reducing secretome gene expression and circulating serum proteins, and downregulated genes involved in endoplasmic reticulum (ER) translocation, glycosylation, folding, and trafficking. Concurrently, PPAR activation enhanced proteasome activity, which was associated with selective induction of proteasome 26S subunit non-ATPase (PSMD) family members. In addition, hepatic protein synthesis was strongly attenuated. This was associated with an increase in the inhibitory phosphorylation of the eukaryotic translation initiation factor 2 (eIF2), that in turn was linked to disrupted iron homeostasis. Together, these findings identify PPAR as a regulator of proteostasis, suppressing protein synthesis and secretion while promoting protein degradation pathways. Beyond its canonical role in lipid and glucose metabolism, we conclude that PPAR exerts an additional energy-conserving function by coordinating proteostasis, expanding our understanding of its systemic metabolic role.

physiology↗

bioRxiv2025

An integrated multi-tissue atlas of epigenomic landscapes and regulatory elements in the bovine genome

Deciphering the regulatory syntax of the genome is essential to understand the genetic and molecular architecture of complex traits, as most trait-associated variants lie in non-coding regions. Yet, functional annotation of the bovine genome remains limited, hindering our ability to unravel the mechanisms underpinning complex traits of economic and ecological importance in cattle. Here, we present a comprehensive epigenetic atlas comprising 1,138 genome-wide epigenetic profiles, including chromatin accessibility, six histone modifications, CCCTC-binding factor (CTCF) transcription factor binding, DNA methylation, chromatin conformation, and transcriptomes across 53 adult tissues, five fetal tissues, and seven primary cell types. This atlas-level data enables us to annotate around 45% of the genome as putative regulatory elements exhibiting tissue- or cell-specific regulatory activity. Leveraging sequence-to-function deep learning models, we discovered 301 sequence motifs and predicted the functional impact of genetic variants through in silico mutagenesis, thereby facilitating the decoding of the regulatory syntax of the cattle genome and fine-mapping of GWAS loci for 22 complex traits. Cross-species analysis further revealed evolutionarily conserved features of regulatory architecture and provided evolutionary insights into complex traits and diseases in humans. Together, this atlas offers a foundational resource for advancing cattle functional genomics, sustainable breeding, and studies of regulatory evolution.

genomics↗

bioRxiv2025

A Practical Preprocessing Pipeline for Concurrent TMS-iEEG: Critical Steps and Methodological Considerations

Transcranial magnetic stimulation combined with intracranial EEG (TMS-iEEG) has emerged as a powerful approach for probing the causal organization and dynamics of the human brain. Despite its promise, the presence of TMS-induced artifacts poses significant challenges for accurately characterizing and interpreting evoked neural responses. In this study, we present a practical preprocessing pipeline for single pulse TMS-iEEG data, incorporating key steps of re-referencing, filtering, artifact interpolation, and detrending. Using both real and simulated data, we systematically evaluated the effects of each step and compared alternative methodological choices. Our results demonstrate that this pipeline effectively attenuated various types of artifacts and noise, yielding cleaner signals for the subsequent analysis of intracranial TMS-evoked potentials (iTEPs). Moreover, we showed that methodological choices can substantially influence iTEPs outcomes. In particular, referencing methods might strongly affect iTEP morphology and amplitude, underscoring the importance of tailoring the referencing strategy to specific signal characteristics and research objectives. For filtering, we recommend a segment-based strategy, i.e., applying filters to data segments excluding the artifact window, to minimize distortion from abrupt TMS-related transients. Overall, this work represents an important step toward establishing a general preprocessing framework for TMS-iEEG data. We hope it encourages broader adoption and methodological development in concurrent TMS-iEEG research, ultimately advancing our understanding of brain organization and TMS mechanisms. HighlightsO_LIWe presented a practical preprocessing pipeline for single pulse TMS-iEEG data, incorporating key steps of re-referencing, filtering, artifact interpolation, and detrending. C_LIO_LIThe pipeline effectively attenuates multiple types of artifacts and noise, enabling accurate characterization of evoked neural responses. C_LIO_LIMethodological alternatives for each preprocessing step were evaluated using real and/or simulated datasets. C_LIO_LIRe-referencing substantially affects the morphology and amplitude of intracranial TMS-evoked potentials and requires careful consideration. C_LIO_LIA segment-based filtering strategy is recommended to better minimize distortion from TMS-related artifacts. C_LI

neuroscience↗

bioRxiv2025

Comparative analysis reveals distinct actin-based motility mechanisms in divergent Rickettsia species

Many Rickettsia species undergo actin-based motility to promote cell-cell spread during infection. Rickettsial genomes encode two motility effectors, RickA and Sca2. In the spotted fever group species R. parkeri, RickA acts early in infection by activating the host Arp2/3 complex; Sca2 acts later by mimicking the structure and function of eukaryotic formins. The function of RickA and Sca2 orthologs in the distantly related species R. bellii was unclear. We report that the R. bellii Sca2 ortholog, Sca2/6, nucleates and elongates actin with a flexible structure and an unusual actin monomer-binding motif in a mechanism distinct from formins or other microbial actin nucleators. R. bellii motility occurs only later in infection and is solely correlated with Sca2/6 localization. Compared with R. parkeri, R. bellii motility is slow and meandering, and generates distinctly organized actin tails, reflecting differences in Sca2 ortholog mechanism and localization. The evolutionary flexibility in the mechanism and regulation of rickettsial actin-based motility suggests similar adaptability for other microbes.

cell biology↗

bioRxiv2025

Adaptive behavior is guided by integrated representations of controlled and non-controlled information

Understanding how task knowledge is encoded neurally is crucial for uncovering the mechanisms underlying adaptive behavior. Here, we test the theory that all task information is integrated into a conjunctive task representation by investigating whether this representation simultaneously includes two types of associations that can guide behavior: stimulus-response (non-controlled) associations and stimulus-control (controlled) associations that inform how task focus should be adjusted to achieve goal-directed behavior. We extended the classic item-specific proportion congruency paradigm to dissociate the electroencephalographic (EEG) representations of controlled and non-controlled associations. Behavioral data replicated previous findings of association-driven adaptive behaviors. Decoding analyses of EEG data further showed that associations of controlled and non-controlled information were represented concurrently and differentially. Brain-behavioral analyses also showed that the strength of both associations was associated with faster responses. These findings provide initial evidence supporting the idea that controlled and non-controlled associations are governed by an integrated task representation to guide adaptive behaviors simultaneously.

neuroscience↗

bioRxiv2025

RESM: Capturing sequence and structure encoding of RNAs by mapped transfer learning from ESM (evolutionary scale modeling) protein language model

RNA sequences exhibit lower evolutionary conservation than proteins due to their informationally constrained four-letter alphabet, compared to the 20-letter code of proteins. More limited information makes unsupervised learning of structural and functional evolutionary patterns more challenging from single RNA sequences. We overcame this limitation by mapping RNA sequences to pseudo-protein sequences to allow effective transfer training from a protein language model (protein Evolution-Scale Model 2, protESM-2). The resulting RNA ESM (RESM) outperforms 12 existing RNA language models in zero-shot prediction, not only in sequence classification but also in RNA secondary structure and RNA-RNA interaction prediction. Further supervised fine-tuning demonstrates RESMs generalizability and superior performance over the existing models compared across multiple downstream tasks, including mRNA ribosome loading efficiency and gene expression prediction, despite RESM being trained exclusively on noncoding RNAs. Moreover, RESM can generalize to unseen sequences beyond its 1,024-nucleotide training limit, achieving 81.3% improvement over state-of-the-art methods in supervised secondary structure prediction for RNAs up to 4,000 nucleotides, limited only by the available GPU memory, while providing >1000-fold speedup compared to MSA-based approaches. RESM provides a robust foundation for deciphering RNA sequence-structure-function relationships, with broad implications for RNA biology.

bioinformatics↗

bioRxiv2025

gCoSRNA: Generalizable Coaxial-Stacking Prediction for RNA Junctions Using Secondary Structure

Coaxial stacking between adjacent stems is a key tertiary interaction that defines the spatial organization of RNA junctions, which are core structural motifs in folded RNAs. Accurate prediction of coaxial stacking is critical for RNA 3D structure modeling, yet existing computational tools remain limited, especially for junctions with variable numbers of branches or complex topologies. Here, we present gCoSRNA, a generalizable computational framework for predicting coaxial stacking configurations using RNA sequence and secondary structure as input. Instead of developing separate models for each junction type, gCoSRNA decomposes multi-way junctions into all possible adjacent stem pairs, termed pseudo two-way junctions, and uses a unified random forest classifier to evaluate stacking probabilities. Global stacking configurations are inferred by integrating these pairwise predictions, eliminating the need for explicit junction-type classification. Benchmarking on two independent test sets, including CASP15/16 and RNA-Puzzles targets, shows that gCoSRNA achieves consistently high accuracy (mean [~]0.87) across junctions with two to seven branches, outperforming existing junction-specific methods. These results highlight the models ability to capture higher-order structural features and its potential utility in RNA tertiary structure prediction pipelines. The source code is freely available at https://github.com/RNA-folding-lab/gCoSRNA.

bioinformatics↗

bioRxiv2025

Representation Transfer via Invariant Input-driven Neural Manifolds for Brain-inspired Computations

Domain adaptation is a core challenge for embodied AI deployed in unpredictable, noisy environments. Conventional deep models degrade under domain shifts and require costly retraining. Inspired by biological brains, we propose a modular framework where each module is a recurrent neural network pretrained via a simple, task-agnostic protocol to learn robust, transferable features. This shapes stable yet flexible representations as invariant input-driven continuous attractor manifolds embedded in high-dimensional latent space, supporting robust transfer and resilience to noise. At deployment, only a lightweight adapter needs training, enabling rapid few-shot adaptation. Evaluated on the DVS Gesture benchmark and a custom RGB rehabilitation dataset, our framework matches or surpasses leading C3D and ViViT models while using ten times fewer parameters and only one training epoch. By unifying biologically inspired attractor dynamics with cortical-like modular composition, our approach offers a practical path toward robust, continual adaptation for real-world embodied AI. TeaserInvariant input-driven attractors enable representation transfer and domain adaptation in brain-inspired AI.

neuroscience↗

bioRxiv2025

A guide to D-SPIN: constructing regulatory network models from single-cell RNA-seq perturbation data

D-SPIN (Dimension-scalable Single-cell Perturbation Integration Network) is a computational framework for constructing regulatory network models from large-scale single-cell perturbation data. D-SPIN models the transcriptional state of cells as a set of individual genes or gene programs that interact through a condition-dependent spin network model or Markov random field. A single unified network is learned across multiple conditions, where the perturbations modulate the activity of individual network nodes. The architecture allows information integration between different perturbation conditions and supports efficient inference algorithms that scale to thousands of genes, thousands of conditions, and millions of single cells. For interpretability, D-SPIN can also operate at the level of programs of co-expressing gene sets, which are extracted via unsupervised orthogonal non-negative matrix factorization (oNMF). Here we present the theory and detailed procedures for applying D-SPIN to build program-level or gene-level network models from single-cell data. With a public immune dictionary dataset, we illustrate multiple applications of D-SPIN, including identifying gene programs and network modules, classifying perturbation responses of cytokines, and nominating key regulators that mediate cytokine responses.

bioinformatics↗

bioRxiv2025

XoxF and the Calvin-Benson Cycle Mediate Lanthanide-Dependent Growth on Methanol in Bradyrhizobium and Sinorhizobium

Nodule-forming bacteria play crucial roles in plant health and nutrition by providing fixed nitrogen to leguminous plants. Despite the importance of this relationship, how nodule-forming bacteria are affected by plant exudates and soil minerals is not fully characterized. Here, the effects of plant-derived methanol and lanthanide metals on the growth of nitrogen-fixing Rhizobiales are examined. Prior work has demonstrated that select Bradyrhizobium strains can assimilate methanol only in the presence of lanthanide metals; however, the pathway enabling assimilation remains unknown. In this study, we characterize Bradyrhizobium diazoefficiens USDA 110, Bradyrhizobium sp. USDA 3456, and Sinorhizobium meliloti 2011 to determine the pathways involved in methanol metabolism in previously characterized strains, other clades of Bradyrhizobium, and the more distantly related Sinorhizobium. Based on genomic analyses, we hypothesized that methanol assimilation in these organisms occurs via the lanthanide-dependent methanol dehydrogenase XoxF, followed by oxidation of formaldehyde via the glutathione-linked oxidation pathway, subsequent oxidation of formate via formate dehydrogenases, and finally assimilation of CO2 via the Calvin-Benson-Bassham (CBB) cycle. Transcriptomics revealed upregulation of the aforementioned pathways in Bradyrhizobium sp. USDA 3456 during growth on methanol. Enzymatic assays demonstrated increased activity of the glutathione-linked oxidation pathway and formate dehydrogenases in all strains during growth on methanol compared to succinate. 13C-labeling studies confirmed the presence of CBB intermediates and label incorporation during growth on methanol. Our findings provide multiple lines of evidence supporting the proposed XoxF-CBB pathway and, combined with genomic analyses, suggest that this metabolism is widespread among Bradyrhizobium and Sinorhizobium species. ImportanceNitrogen-fixing soil bacteria such as Bradyrhizobium and Sinorhizobium promote plant growth while reducing dependence on artificial, energy-intensive fertilizers. Numerous studies have attempted to increase bacterial nitrogen fixation and colonization of plant tissues by identifying the micronutrients and plant exudates that promote successful symbiotic relationships. Among the compounds encountered by rhizobacteria, lanthanides have received little attention, despite reports that plant growth is affected by the presence of lanthanides. We characterized three agriculturally relevant Bradyrhizobium and Sinorhizobium strains, demonstrated that they gain the capacity to utilize methanol when lanthanides are present, and experimentally determined the pathway by which this metabolism occurs. This study provides a foundation for understanding the impacts of bacteria-mediated lanthanide metabolism on plant growth.

microbiology↗

bioRxiv2025

Development of PROTACs for targeted degradation of oncogenic TRK fusions

Chromosomal translocations leading to the fusion of tropomyosin receptor kinases (TRK) with diverse partner proteins have been identified as oncogenic drivers in many adult and pediatric cancers. While first-generation TRK kinase inhibitors, such as entrectinib and larotrectinib, have shown positive responses in TRK fusion-positive cancers, resistance mutations against these inhibitors in the kinase domain limit their efficacy. Second-generation inhibitors are in clinical evaluation, highlighting a need for novel therapeutic modalities to achieve durable suppression of the oncogenic activity of TRK fusions. Here, we developed heterobifunctional small molecule degraders (PROTACs) to achieve targeted degradation of TRK fusions. By conjugating entrectinib to thalidomide, we identified JWJ-01-378 as a potent and selective CRBN-recruiting degrader of the TPM3-TRKA fusion. JWJ-01-378 induced TPM3-TRKA degradation through the ubiquitin-proteasome system and proteomics analysis confirmed the acute selectivity of JWJ-01-378 for achieving TPM3-TRKA degradation with minimal off-target effects. While JWJ-01-378 was also able to degrade wild-type TRK, it was unable to degrade TRK inhibitor resistant mutants and ALK fusions. Importantly, TPM3-TRKA degradation by JWJ-01-378 suppressed downstream signaling and reduced cancer cell viability, with improved responses compared to heterobifunctional control compounds that cannot degrade TPM3-TRKA. Together, our study expands the toolbox of compounds for evaluating targeted degradation of TRK fusions in cancer. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC="FIGDIR/small/660465v1_ufig13.gif" ALT="Figure 13"> View larger version (19K): org.highwire.dtl.DTLVardef@6c78f7org.highwire.dtl.DTLVardef@179dcdeorg.highwire.dtl.DTLVardef@1939988org.highwire.dtl.DTLVardef@144c718_HPS_FORMAT_FIGEXP M_FIG C_FIG JWJ-01-378 recruits cereblon (CRBN) to induce potent and selective degradation of oncogenic TRK fusions, leading to a collapse in downstream signaling and loss of cancer cell viability. Graphical abstract was created using Biorender.com.

cancer biology↗