Jihoon Han

Programmable RNA sensors enable sequence-specific detection of RNA inputs for diagnostics, genetic circuit control, and multiplexed molecular readouts. Although readily programmable, their performance varies substantially with the target site selected within a transcript, making target-site selection a major challenge. Here, we report DeSTAR (Detectron Sensor TARget-site ranker), a machine-learning-assisted target-site ranking model for programmable RNA sensors. To train this model, we generated transcript-wide, single-nucleotide-resolution tiling sensor libraries across six diverse RNA targets, enabling generalization to be tested across transcripts rather than within a single RNA. In leave-one-transcript-out evaluation, DeSTAR's top-ranked sites were enriched for high-performing sensors in held-out transcripts, driven predominantly by interpretable sequence grammar in the sensor stem rather than transcript-specific patterns. Prospectively, on an unseen SARS-CoV-2 transcript, the model's top-ranked sites yielded working sensors roughly five-fold more often than random selection. These results support DeSTAR as a generalizable strategy for target-site selection in RNA sensors across transcripts.

Programmable RNA sensors such as toehold switches are used to detect specific RNA sequences. However, their reliance on protein-based or RNA-based outputs limits their use in multiplexed and sequencing-based applications. Here we introduce Detectrons, modular biosensors that couple programmable toehold switches with retron-mediated reverse transcription to transduce RNA inputs into unique DNA barcodes, converting dynamic RNA signals into durable DNA records within living cells. The framework enables alternative modes of transcript-based sensing with applications including viral infection detection. Through the construction of a synthetic toehold retron library and application of machine learning, we uncover key design principles that improve signal strength and specificity. We apply Detectrons to the multiplexed live-cell detection of specific phage infections, enabling transcript-triggered barcode synthesis and quantitative host susceptibility profiling in pooled bacterial populations. Detectrons provide a scalable and generalizable strategy for phage screening and for recording transcriptional events in complex bacterial communities.

Here, we introduce Detectrons, modular biosensors that couples programmable toehold switches with retron-mediated reverse transcription to transduce RNA inputs into unique DNA barcodes. The ability to convert dynamic RNA signals into durable DNA records within living cells unlocks powerful new modes of transcript-based sensing with applications including viral infection detection. Through the construction of a synthetic toehold-retron library and application of machine learning, we uncovered key design principles that improve signal strength and specificity. We applied Detectrons to the multiplexed live-cell detection of specific phage infections, enabling transcript-triggered barcode synthesis and quantitative host susceptibility profiling in pooled bacterial populations. Detectrons are the first RNA-to-DNA transduction system, directly linking transient RNA detection to stable, sequence-encoded DNA outputs. This platform provides a scalable and generalizable strategy for phage screening and for recording transcriptional events in complex bacterial communities.

The application of extracellular vesicles (EVs) as vehicles for anti‐Parkinson's agents represents a significant advance, yet their clinical translation is hampered by challenges in efficient brain delivery and complex blood‐brain barrier (BBB) targeting strategies. In this study, we engineered dopamine onto the surface of adipose‐derived stem cell EVs (Dopa‐EVs) utilizing a facile, two‐step cross‐linking approach. This engineering enhanced neuronal uptake of the EVs in primary neurons and neuroblastoma cells, a process shown to be competitively inhibited by dopamine pretreatment and dopamine receptor antibodies. Notably, Dopa‐EVs demonstrated increased brain accumulation in mouse Parkinson's disease (PD) models. Therapeutically, Dopa‐EVs administration led to the rescue of dopaminergic neuronal loss and amelioration of behavioural deficits in both 6‐hydroxydopamine (6‐OHDA) and α‐Syn PFF‐induced PD models. Furthermore, we observed that Dopa‐EVs stimulated autophagy evidenced by the upregulation of Beclin‐1 and LC3‐II. These findings collectively indicate that surface modification of EVs with dopamine presents a potent strategy for targeting dopaminergic neurons in the brain. The remarkable therapeutic potential of Dopa‐EVs, demonstrated in PD models, positions them as a highly promising candidate for PD treatment, offering a significant advance over current therapeutic modalities.

Effective intracellular delivery of therapeutic proteins can potentially treat a wide array of diseases. However, efficient delivery of functional proteins across the cell membrane remains challenging. Exosomes are nanosized vesicles naturally secreted by various types of cells and may serve as promising nanocarriers for therapeutic biomolecules. Here, we engineered exosomes equipped with a photoinducible cargo protein release system, termed mMaple3-mediated protein loading into and release from exosome (MAPLEX), in which cargo proteins can be loaded into the exosomes by fusing them with photocleavable protein (mMaple3)–conjugated exosomal membrane markers and subsequently released from the exosomal membrane by inducing photocleavage with blue light illumination. Using this system, we first induced transcriptional regulation by delivering octamer-binding transcription factor 4 and SRY-box transcription factor 2 to fibroblasts in vitro. Second, we induced in vivo gene recombination in Cre reporter mice by delivering Cre recombinase. Last, we achieved targeted epigenome editing in the brains of 5xFAD and 3xTg-AD mice, two models of Alzheimer’s disease. Administration of MAPLEXs loaded with β-site amyloid precursor protein cleaving enzyme 1 ( Bace1 )–targeting single guide RNA–incorporated dCas9 ribonucleoprotein complexes, coupled with the catalytic domain of DNA methyltransferase 3A, resulted in successful methylation of the targeted CpG sites within the Bace1 promoter. This approach led to a significant reduction in Bace1 expression, improved recognition memory impairment, and reduced amyloid pathology in 5xFAD and 3xTg-AD mice. These results suggest that MAPLEX is an efficient intracellular protein delivery system that can deliver diverse therapeutic proteins for multiple diseases.

A bstract: Self-relevant concepts are major building blocks of spontaneous thought, and their dynamics in a natural stream of thought are likely to reveal one’s internal states important for mental health. Here we conducted an fMRI experiment ( n = 62) to examine brain representations and dynamics of self-generated concepts in the context of spontaneous thought using a newly developed free association-based thought sampling task. The dynamics of conceptual associations were predictive of individual differences in general negative affectivity, replicating across multiple datasets ( n = 196). Reflecting on self-generated concepts strongly engaged brain regions linked to autobiographical memory, conceptual processes, emotion, and autonomic regulation, including the medial prefrontal and medial temporal subcortical structures. Multivariate pattern-based predictive modeling revealed that the neural representations of valence became more person-specific as the level of perceived self-relevance increased. Overall, this study provides a hint of how self-generated concepts in spontaneous thought construct inner affective states and idiosyncrasies.

Osteoporosis is one of the most common skeletal disorders caused by the imbalance between bone formation and resorption, resulting in quantitative loss of bone tissue. Since stem cell‐derived extracellular vesicles (EVs) are growing attention as novel cell‐free therapeutics that have advantages over parental stem cells, the therapeutic effects of EVs from adipose tissue‐derived stem cells (ASC‐EVs) on osteoporosis pathogenesis were investigated. ASC‐EVs were isolated by a multi‐filtration system based on the tangential flow filtration (TFF) system and characterized using transmission electron microscopy, dynamic light scattering, zeta potential, flow cytometry, cytokine arrays, and enzyme‐linked immunosorbent assay. EVs are rich in growth factors and cytokines related to bone metabolism and mesenchymal stem cell (MSC) migration. In particular, osteoprotegerin (OPG), a natural inhibitor of receptor activator of nuclear factor‐κB ligand (RANKL), was highly enriched in ASC‐EVs. We found that the intravenous administration of ASC‐EVs attenuated bone loss in osteoporosis mice. Also, ASC‐EVs significantly inhibited osteoclast differentiation of macrophages and promoted the migration of bone marrow‐derived MSCs (BM‐MSCs). However, OPG‐depleted ASC‐EVs did not show anti‐osteoclastogenesis effects, demonstrating that OPG is critical for the therapeutic effects of ASC‐EVs. Additionally, small RNA sequencing data were analysed to identify miRNA candidates related to anti‐osteoporosis effects. miR‐21‐5p in ASC‐EVs inhibited osteoclast differentiation through Acvr2a down‐regulation. Also, let‐7b‐5p in ASC‐EVs significantly reduced the expression of genes related to osteoclastogenesis. Finally, ASC‐EVs reached the bone tissue after they were injected intravenously, and they remained longer. OPG, miR‐21‐5p, and let‐7b‐5p in ASC‐EVs inhibit osteoclast differentiation and reduce gene expression related to bone resorption, suggesting that ASC‐EVs are highly promising as cell‐free therapeutic agents for osteoporosis treatment.