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Biology subjects

Yang, Y.

Publications and source records attributed to Yang, Y..

At least 55 records · Page 3Linked to original sources

Hygrochastic Seedpods: Engineering Microclimates for Forest Restoration

Forest restoration at scale depends on sowing seeds directly onto the land, yet seedling establishment is often poor and inconsistent. Seed enhancement technologies, such as priming, coating, and pelleting, improve germination under water, temperature, and salinity stress by supplying polymers, nutrients, or microorganisms at the seed surface. Being mainly conformal films, they act continuously once wetted and cannot gate when a seed is exposed to the soil. They also enclose no air volume, so the microenvironment they create is inseparable from the surrounding soil and has been inferred from plant performance rather than measured directly. Whether an engineered carrier can instead set both the state and the duration of the post-dispersal microenvironment, and how such an effect can be directly quantified, remains unexplored. Here we show that hygrochastic seedpods hold seeds in a timed, directly measurable microclimate and accelerate seedling emergence. The pods are programmable, responsive conical shells enclosing an air cavity around the seed. Two design solutions were investigated in parallel: wooden seedpods that crack open upon hydration, and poly(vinyl alcohol)/boric acid seedpods that gradually disintegrate after sustained wetting. In both, wax coatings act as a programmable diffusion-limited timer that sets activation from hours to days. The pod cavity permits direct sensing and monitoring, which no coating geometries allow. As directly measured during the initial phase after deployment, seedpod interiors ran 2 - 3 C warmer and drier than the surrounding soil, and these differences persisted after opening. Across indoor and field trials in several tree species, pods accelerated early seedling emergence without penalizing subsequent growth. These results identify artificial hygrochastic seedpods as a transient ecological mediator that regulates both the timing of seed exposure and the microclimate around the seed, offering a strategy for improving forest restoration under variable environmental conditions.

bioengineering↗

Distinct RNA-RNA spatial interaction sub-networks of transcription factors in hepatic cells

We applied the latest RIC-seq technology to study the RNA-RNA interactions in human liver HepG2 cells. Integrating ChIP-seq data with the RIC-seq data, we clas-sified vari ous transcription factors (TFs) into two distinct clusters based on the in-teraction enrichment scores of the uaRNA (RNA transcribed in promoter regions) and eRNA (RNA tran scribed in enhancer regions) potentially transcribed by the TF binding sites. We went on to compare the genomic features and clinical significance across different clusters, by further integrating Hi-C, ATAC-seq, and clinical data from liver cancer patients. Our results showed that Cluster 1 exhibited low spatial interaction (RIC-seq derived RNA-RNA interactions between regulatory RNA ele-ments) and high tissue specificity (high proportion of binding sites covered by shared peaks between two different cell lines for each histone modification marker), showed higher associations with the B compartments and nucleoli, contained less densely clustered TF binding sites, and is more correlated with clinical outcomes. In contrast, Cluster 2 has higher spatial interaction, is more likely to be found in the A compartments and nuclear speckles, contained more densely clustered TF binding sites, and is more prone to form loops. These findings suggested that these transcrip-tion factors might play critical roles in regulating gene expression and serve as po-tential biomarkers and therapeutic targets with significant implications for cancer prognosis and treatment. In summary, groups of TFs could occur as distinct sub-networks based on spatial proximity of non-coding RNAs transcribed by the TF binding sites. These sub-networks appear to be related to regulatory differences for the TF groups and may partially explain the chromosome compartments/domains.

genomics↗

Brain organoid computing for robotic decision-making

Biomimicry has inspired the evolution of robotics toward greater autonomy, adaptability, and symbiosis with humans and dynamic environments. However, current robotic systems still face major challenges in recapitulating the high-efficiency decision-making capabilities of the human brain under complex and dynamic conditions. Here, we present Brainobot, a biohybrid robotic system that establishes a brain organoid controller as a high-level robotic decision-making layer for closed-loop embodiment. By leveraging brain organoid reservoir computing, Brainobot interacts with dynamic environments by receiving and processing sensory inputs and generating motor actions. As a proof-of-concept demonstration, Brainobot is implemented in a humanoid robotic system to perform real-world tasks, including object grasping and laser chasing. Interestingly, Brainobot exhibits unique features, including cross-task adaptivity, high computing efficiency, and low energy consumption. Thus, our approach may provide insights for advancing robotic embodiment and understanding biological decision-making.

bioengineering↗

Transdermal diagnosis and therapy using an integrated acoustofluidic patch

Transdermal biosensing and drug delivery provide convenient, pain-free, and user-friendly solutions for personalized therapy. However, challenges remain in detecting and treating acute diseases, primarily due to current limitations in effective detection of transdermal biomarkers and administration of therapeutics to an individual within a short time window in a real-world environment. Here, we integrate a compact acoustofluidic patch for transdermal sampling, sensing, and delivery in a rapid and automated manner. By leveraging acoustic streaming and 3D-printed microfluidic designs, acoustofluidic sampler and injector modules are assembled for penetration of the skin stratum corneum, precise sampling of skin interstitial fluids, and controlled percutaneous release of therapeutics, respectively. By incorporating an electrochemical sensing module, the integrated patch can be further developed to achieve in situ and rapid detection of transdermal biomarkers and automated transdermal delivery of therapeutics via closed-loop control. As a proof-of-concept application, we demonstrate our approach can detect and reverse life-threatening acute allergic reactions in a mouse model of anaphylaxis by rapid sampling and sensing transdermal histamine followed by automated transdermal delivery of epinephrine. The innovative acoustofluidic patch may enable a new kind of transdermal devices for personalized therapy of various acute diseases.

bioengineering↗

A quantum state of mitochondria in the living cell

The high energy-efficiency of life is hard to understand only with classical physics. Many efforts have been made to study its mechanism based on quantum mechanics; the progress is nevertheless slow due to lack of experimental evidence with living cells. Here, combining experiments on cells, tissues and mitochondria with a theoretical model, we demonstrate a quantum state of mitochondria, which can be employed to modulate ATP production in living cells. We found an anomalous 71.0-THz oscillation mode only in living cells and tissues, which is highly determined by intact structure of mitochondria, and cannot be assigned to any specific molecules. Based on experimental data, a quantum model of light-matter coupling was introduced to trace the origin of this mode. Our calculations suggest a quantum superposition state of functional mitochondrion that forms by the coupling of light and lipid CH2 bonds in functional cristae, and induces a splitting of the intrinsic CH2 vibration mode of 87 THz to two levels at 71 THz and 103 THz, respectively. The former can be observed only in living cells and tissues; whereas the latter falls in the range (90-110 THz) of biomolecular and water vibrations, thus indistinguishable. Additional experiments revealed this mitochondrial quantum state able to serve as an efficient channel to modulate ATP production. Our findings provide a quantum mechanics view for understanding living cells, and it will be interesting to further explore whether such quantum state could act as a channel for energy metabolism, and even information transmission in life.

biophysics↗

Deep reinforcement learning-driven discovery of a MsbA-targeted small-molecule antibiotic for the treatment of Acinetobacter baumannii infection

Antibiotics with new mechanisms are highly pursued to address the threat of infections caused by drug-resistant Gram-negative bacteria. Targeting MsbA, a key protein of the lipopolysaccharide biosynthesis pathway, represents a promising strategy to discover new classes of antibiotics. However, currently available MsbA-targeted molecules either lack sufficient potency or have unfavorable properties, necessitating expansion of chemical space. In this study, we chose the most promising cerastecin Cpd 4 as the template, and used two Artificial Intelligence (AI)-based tools, i.e. Link-INVENT and AutoMolDesigner for molecular design, performed chemical derivatization and antibacterial activity evaluation, which led to the discovery of Y-11 (MIC for A. baumannii: 0.5 g/mL). Encouragingly, Y-11 showed equivalent potency to Cpd4 for carbapenem-resistant A. baumannii, and less cytotoxicity and hemolysis as well as lower spontaneous resistance frequency. In vivo efficacy study demonstrated that Y-11 could effectively reduce bacterial loads in the mice infected by A. baumannii. The following mechanism study including molecular dynamics simulation, biochemical assay, and transmission electron microscope (TEM) analysis suggested that Y-11 inhibited the transport of lipooligosaccharide and impaired the formation of outer membrane, probably by competitively binding to the substrate binding site of MsbA and modulating ATPase activity. Taken together, we have discovered a MsbA-targeted small molecule Y-11 via AI-driven drug design, which provides a foundation for future antibiotic development.

biochemistry↗

Markov models of SHAPE data improve secondary structure prediction

RNA structure is a key determinant of RNA function and regulation. The coupling of chemical probing technologies, such as SHAPE, with deep sequencing has enabled large-scale experimental characterization of RNA structures in complex samples and under diverse conditions. Furthermore, probing data are often used to guide thermodynamics-based secondary structure prediction algorithms and have been shown to improve their accuracy. However, current algorithms treat these single-nucleotide measurements as statistically independent signals, inherently overlooking short-range dependencies in the data. Here, we show that discretized SHAPE data display context dependence within loop regions and within stem regions and we use Markov models to formally capture such dependencies. We then leverage Markov modeling in the classification of small structure motifs from their discretized SHAPE data signatures and subsequently integrate the classifying feature into the dynamic programming recursions that underlie computational RNA folding. Compared to state-of-the-art SHAPE-guided structure prediction methods, our Markov-informed framework improves prediction performance. Furthermore, we identify SHAPE signatures characteristic of highly stable hairpins, such as GAAA, GCAA, and UUCG tetraloops, and integrate these insights into the folding recursions to further improve predictions. Overall, the proposed framework provides a foundation for context-aware statistical modeling of SHAPE data, particularly in loop regions, where signal characterization has proven challenging due to high variance. This work further demonstrates that finer modeling of SHAPE data has the potential to push the limits of data-guided secondary structure prediction.

bioinformatics↗

Melittin-induced membrane disruption in hepatocellular carcinoma involves mtROS/GSDME-mediated pyroptosis

Although melittin is classically regarded as a membrane-lytic peptide, it remains unclear whether its membrane-disruptive effects in tumour cells result exclusively from direct peptide-lipid interactions or are partly generated by pyroptosis. Here, we show that melittin markedly suppresses the viability and clonogenic growth of human Huh7 and murine Hepa1-6 HCC cells and rapidly induces characteristic features of pyroptosis, including cell swelling, balloon-like membrane protrusions, plasma-membrane permeabilization and lactate dehydrogenase release. In Hepa1-6 cells, melittin induced prominent GSDME cleavage and accumulation of its pore-forming N-terminal fragment, whereas GSDMD activation was not detected. Quantitative proteomics and ultrastructural analyses further revealed pronounced mitochondrial perturbation after melittin treatment, accompanied by loss of mitochondrial membrane potential and increased mitochondrial reactive oxygen species (mtROS). Importantly, scavenging mitochondrial oxidants with Mito-TEMPO markedly reduced mtROS accumulation, attenuated pyroptotic membrane damage and partially restored cell viability. Collectively, our findings provide, to our knowledge, the first evidence that melittin induces pyroptotic cell death in HCC cells through a mechanism involving mitochondrial oxidative stress and GSDME processing. These results extend the conventional view of melittin as a direct membrane-lytic peptide and uncover an mtROS/GSDME-associated pyroptotic mechanism underlying its antitumour activity in HCC.

cancer biology↗

Information processing-like phenotype of human brain organoids

Human brain organoids recapitulate key physiological features and functions of the human brain and hold remarkable potential for studying neurological diseases. Despite clinical evidence suggesting that neurodegenerative diseases impair the information-processing ability of the human brain, the capacity of brain organoids for information processing and its relationship to neural network function remain largely unexplored. Here, we test and quantify information-processing-like properties of human cortical organoids using a task-based functional phenotyping framework (Brainopheno). We demonstrate the pattern-processing-like phenotype of cortical organoids through the representation and classification of evoked neural activities in response to distinct spatial input stimulation patterns via a microelectrode array (MEA) system. Moreover, this functional phenotype emerges with network maturation and is disrupted by pharmacological perturbations, linking classification performance to the functional integrity of organoid neural networks (ONNs). Importantly, this functional phenotype also reveals functional deficits in ONNs altered by a familial Alzheimer's disease (AD)-associated gene mutation (APP) and by monocytes from patients with sporadic AD. This work may establish a new quantifiable functional phenotype of neural organoids and provide a framework to bridge molecular and cellular profiles with neural circuit function for basic neurology, disease phenotyping, and therapeutic development.

bioengineering↗

A patient-centric therapeutic paradigm uncouples prostate cancer suppression from systemic metabolic collapse

The clinical benefits of cancer therapies are often compromised by the tolerable adverse effects that impair systemic organismal health and may evolve into latent life threats. Here, we identified profound abiraterone-induced but androgen-independent metabolic perturbations in prostate cancer patients and developed Lifehug-9892 to balance tumor therapy with systemic metabolic homeostasis. By integrating population cohorts with high-resolution metabolomics, we demonstrate that abiraterone induces profound systemic lipidomic dysregulation, characterized by the massive, pathological accumulation of desmosterol. Abiraterone inhibits but stabilizes DHCR24, leading to a metabolic trap in patients showing elevated levels of both desmosterol and cholesterol. Desmosterol accumulation is highly lipotoxic, potently triggering endothelial cell senescence and necrosis, macrophage foam cell formation, murine atherosclerosis, and hepatic senescence. To mechanistically uncouple and therapeutically rescue this systemic metabolic collapse, Lifehug-9892 was rationally designed to selectively retain on-target CYP17A1 inhibition while completely sparing DHCR24 function. Lifehug-9892 maintains potent tumor-suppressive activity while fully preserving the desmosterol-cholesterol metabolic axis and preventing systemic cardiovascular and hepatic damage. Our study uncovers a critical mechanistic link between drug-induced metabolic dysregulation and organismal health in cancer patients, providing a biochemical framework for developing patient-centric targeted therapies that preserve host homeostasis.

cancer biology↗

A multi-tissue epigenomic atlas links the sheep non-coding genome to domestication and complex traits

Non-coding regulatory variation drives complex traits, domestication, and evolutionary adaptation, yet the sheep genome lacks high-resolution functional annotation. Here we present SheepEpimap, a multi-tissue regulatory atlas harmonizing 516 CUT&Tag histone modifications, ATAC-seq, and RNA-seq datasets across 43 adult tissues in sheep. We annotated 2.93 million cis-regulatory elements, yielding 557,441 enhancer-gene pairs and 145,407 variants with allele-specific effects. By training a sequence-to-function deep-learning model, we decoded the base-pair syntax of chromatin accessibility, annotated transcription factor motif instances genome-wide, and constructed 12,210 tissue-specific gene regulatory networks (GRNs). Integrating this resource with multi-tissue expression quantitative trait loci, selection sweeps, and genome-wide association studies prioritized non-coding variants driving domestication and complex traits. Finally, cross-species analysis revealed that sequence-conserved, tissue-matched enhancers were significantly enriched in the heritability of complex traits and diseases in humans. In summary, SheepEpimap (https://genome.ucsc.edu/s/mengzhu/SheepEpimap) provides an open-access foundational ecosystem for sheep functional genomics, precision breeding, and comparative biology.

genetics↗

CellCage™ Technology Enables High-throughput Isolation of Defined Cell Combinations to Resolve the Determinants of CAR-T mediated Cytotoxicity

Understanding the cellular determinants of CAR-T cell-mediated cytotoxicity at the single-cell level remains a critical challenge in developing effective cellular immunotherapies. Conventional bulk co-culture assays provide only population-level measurements of cytotoxic activity and cannot resolve the functional heterogeneity of individual effector-target interactions. Here, we demonstrate the Cellanome platform, which enables the formation of CellCage Enclosures (CCEs) through spatially controlled photopolymerization, as a tool for high-resolution, high-throughput characterization of CAR-T cell-mediated cytotoxicity. By isolating defined effector-target combinations within individual CCEs and coupling encapsulation with longitudinal time-lapse imaging and automated image analysis, we resolve cytotoxic activity across thousands of individually tracked CCEs. Using anti-CD19 CAR-T effectors and NALM6-GFP targets, we show that individual CD8+ CAR-T effectors exhibit substantial functional heterogeneity, with serial killing capacity, effector-target contact dynamics, and intrinsic motility each independently correlating with cytotoxic potency. Cytotoxic efficacy scaled positively with effector number, and CD4+ T helper cells augmented CD8+-mediated killing in a dose-dependent manner, providing direct evidence for cooperative T cell behavior during tumor cell clearance. Extending the platform to a solid tumor model using AIC100 anti-ICAM-1 CAR-T cells and HeLa-GFP targets, we show that individual AIC100 effectors are insufficient to mediate effective killing, while multi-effector CCEs exhibit robust cytotoxicity scaling with effector abundance and CD4+:CD8+ composition. These data establish the Cellanome platform as a broadly applicable system for dissecting the determinants of CAR-T cell cytotoxicity at single-cell resolution, with direct translational relevance to the optimization of cellular immunotherapy.

immunology↗

Image-Derived 3D Blood-Brain Mechanics: Cerebral Haemodynamics, Brain Motion and In Vivo Benchmarking

Cerebrovascular pulsatility drives measurable brain tissue deformation and has been associated with ageing and a range of neurological disorders. Yet how pulsatile haemodynamic forces are transmitted through deformable cerebral arteries into the surrounding brain remains poorly understood, particularly in anatomically realistic vascular geometries. Existing computational approaches have largely treated cerebral fluid and tissue mechanics separately or relied on idealised geometries, limiting our ability to determine how vascular anatomy simultaneously governs intraluminal haemodynamics and extravascular mechanical loading. Here, we develop an image-derived three-dimensional computational framework that jointly resolves pulsatile blood flow, arterial wall deformation and surrounding brain tissue motion in representative cerebral arteries. Four arterial segments, including the middle cerebral artery, middle cerebral artery bifurcation, basilar artery and internal carotid artery, are reconstructed from high-field (5 Tesla) magnetic resonance imaging data of a healthy subject. A finite-deformation fluid-structure interaction model is established by coupling non-Newtonian blood flow, hyperelastic arterial wall and hyper-viscoelastic brain tissue. The predicted tissue response is benchmarked against in vivo magnetic resonance elastography measurements of cardiac-induced volumetric strain over a cardiac cycle. Results reveal spatially localised arterial and tissue deformation whose magnitude and distribution are strongly governed by vascular geometry and wall thickness. Among the segments examined, the internal carotid artery exhibits the largest deformation response, while reduced wall thickness increases strain transmission into the surrounding tissue. Geometrically complex regions also exhibit greater spatial heterogeneity in near-wall haemodynamic metrics. These findings demonstrate that cerebral vascular anatomy simultaneously shapes intraluminal haemodynamics and extravascular mechanical loading. By integrating image-derived vascular anatomy, coupled blood-vessel-brain mechanics and in vivo benchmarking within a unified framework, this study provides a mechanically consistent reference for healthy cerebral pulsatility and establishes a foundation for quantifying how blood-vessel-brain interactions are altered under pathological conditions.

bioengineering↗

Melittin intervention induces lncRNA response, mitochondrial dysfunction, and cell proliferation in murine cervical cancer cells

Melittin exhibits antitumor activity in cervical cancer models, yet the long non-coding RNA (lncRNA) response and associated regulatory networks remain poorly understood. Here, strand-specific RNA-seq data from melittin-treated and untreated U14 murine cervical cancer cells were analyzed to characterize melittin-responsive lncRNAs and explore their potential functional associations. A total of 28,162 lncRNAs were identified, including 27,307 known and 855 novel transcripts. Differential expression analysis revealed 404 differentially expressed lncRNAs (DElncRNAs), comprising 191 upregulated and 213 downregulated lncRNAs, w most of which were predicted to localize to the cytoplasm or nucleus. Cis-target analysis identified 52 neighboring mRNAs as putative targets of 46 DElncRNAs. Functional enrichment highlighted mitochondrial electron transfer and redox-related processes, including the mitochondrial electron transfer flavoprotein complex, electron-transferring-flavoprotein dehydrogenase activity, ubiquinone binding, and quinone binding. In parallel, melittin induced mitochondrial membrane depolarization and increased intracellular reactive oxygen species accumulation in U14 cells. Co-expression analysis further identified 138 lncRNAs co-expressed with 161 mRNAs, which were enriched in chromatin remodeling, DNA replication, and DNA repair. EdU incorporation decreased with increasing melittin concentrations, indicating suppression of DNA synthesis and proliferative activity. RT-qPCR analysis confirmed the expression trends of selected DElncRNAs. Collectively, these findings demonstrate extensive remodeling of the lncRNA landscape in melittin-treated U14 cells and suggest that melittin-responsive lncRNA-mRNA networks are associated with mitochondrial redox disruption and impaired DNA synthesis. This study provides a transcriptomic framework for identifying candidate lncRNA-mRNA regulatory axes underlying the antitumor response to melittin.

cancer biology↗

Juvenile AAV-Mediated MEF2C Gene Replacement Ameliorates Selected Phenotypes in Mef2c-Haploinsufficient Mice

MEF2C haploinsufficiency syndrome is a severe neurodevelopmental disorder for which no disease-directed treatment is available. We investigated whether neuron-directed adeno- associated virus (AAV) delivery of a functional MEF2C coding sequence during the juvenile period could modify disease-relevant phenotypes in mice heterozygous for a Mef2c exon 4 deletion. Transcript-level analysis identified a brain-enriched MEF2C isoform containing the 1 and {beta} regions (nMEF2C) and a skeletal-muscle-enriched isoform containing 2 but lacking {beta} (mMEF2C). Separate human-synapsin-driven AAV vectors encoding either isoform were administered at postnatal day 28. Control-treated Mef2c heterozygous mice retained baseline sociability but lacked social-novelty preference. Mice treated with either nMEF2C or mMEF2C displayed social-novelty preference and improved selected responses to a new social partner, whereas open-field effects were limited. nMEF2C replacement also corrected dark-phase wakefulness and non-rapid eye movement sleep abnormalities and modified selected state- dependent electroencephalographic ratios, without broadly changing absolute band amplitudes or social-contact electroencephalographic activity. Atlas-based whole-brain mapping revealed region-selective reductions in parvalbumin-immunoreactive profiles; direct statistical evidence of cellular rescue was confined to the secondary motor area after nMEF2C treatment. These findings show that selected MEF2C-dependent phenotypes remain modifiable during the juvenile period and support further optimization of MEF2C gene replacement with respect to isoform, dose, expression control, and cellular targeting.

neuroscience↗

Hybrid speciation and ghost ancestry shape the Anopheles gambiae species complex

Speciation within reticulate radiations can involve both lineage divergence and hybrid lineage formation, yet recurrent introgression obscures both histories. In the Anopheles gambiae complex, gene-family presence-absence data yielded a species tree favored over four sequence-derived alternatives by network-model comparison. D-BPP analyses recovered seven reticulation events, including multiple ghost-lineage contributions, and supported a ghost-mediated hybrid origin of A. merus. Simulations showed that sampled-parent hybrid origin generates temporal convergence between reticulation and lineage formation when analyzed under an ordinary introgression model; this signature supported hybrid speciation in A. gambiae. Loci with contrasting parental affinities contained olfactory and cuticular genes with potential roles in prezygotic isolation. Together, these results resolve species relationships and identify candidate genomic mechanisms through which hybridization may have contributed to reproductive isolation.

evolutionary biology↗

Long-read sequencing quantifies synthetic mRNA abundance, integrity and host response in vivo

Synthetic mRNA can be used to reprogram biological systems and is increasingly used in vaccines, gene therapies and other advanced therapeutics. However, measuring mRNA abundance, molecular integrity and biological effects in complex samples remains challenging. Existing assays typically quantify short transcript regions or infer delivery from lipid or protein readouts. Here we present a long-read nanopore sequencing method that directly quantifies synthetic mRNA in complex cell and tissue samples. The approach enables absolute quantification of full-length synthetic mRNA, maps degradation at nucleotide resolution and simultaneously profiles associated host transcriptional responses. Applied to lipid nanoparticle (LNP) delivered mRNA in mice, the method revealed tissue-specific delivery and degradation patterns and uncovered a critical disconnect between mRNA accumulation and protein expression across organs. This approach enables integrated measurement of mRNA fate, integrity and biological responses, and will enable mechanistic studies of RNA delivery, stability, translation and innate immune recognition.

pharmacology and toxicology↗

A targeted bispecific TGFBR2 antagonist antibody demonstrates cell selectivity and enhanced potency on human fibroblasts

Beyond its critical roles in development and tissue homeostasis, TGF{beta} signaling promotes key aspects of cancer progression and is a primary driver of fibrosis. Although blocking TGF{beta} signaling has great therapeutic potential for cancer and fibrotic diseases such as idiopathic pulmonary fibrosis (IPF), preclinical and clinical studies revealed that non-specific alteration of the pathway can have severe adverse consequences; therefore, inhibiting TGF{beta} signaling in a cell-type specific manner may avoid systemic toxic effects while preserving potential therapeutic effects. The parasitic helminth Heligmosomoides polygyrus has evolved cell-type-targeted modulators of TGF{beta} signaling. With insights from the development of other targeted signaling modulators and using the worm proteins as a guide, we sought to develop a human-fibroblast-targeted TGFBR2 antagonist. Here, we report mechanistic insights into the targeted worm TGFBR2 antagonist TGM6 and fusion proteins containing the TGM6 targeting domains. We created a bispecific antibody TGFBR2 antagonist that binds PDGFRA as a targeting receptor and demonstrates cell selectivity and enhanced potency in fibroblasts. Our findings suggest a viable path for developing targeted TGF{beta} signaling antagonists as therapeutics for cancer and tissue fibrosis.

cell biology↗