Massively parallel in vivo Perturb-seq reveals cell-type-specific transcriptional networks in cortical development.

Leveraging AAVs' versatile tropism and labeling capacity, we expanded the scale of in vivo CRISPR screening with single-cell transcriptomic phenotyping across embryonic to adult brains and peripheral nervous systems. Through extensive tests of 86 vectors across AAV serotypes combined with a transposon system, we substantially amplified labeling efficacy and accelerated in vivo gene delivery from weeks to days. Our proof-of-principle in utero screen identified the pleiotropic effects of Foxg1, highlighting its tight regulation of distinct networks essential for cell fate specification of Layer 6 corticothalamic neurons. Notably, our platform can label >6% of cerebral cells, surpassing the current state-of-the-art efficacy at <0.1% by lentivirus, to achieve analysis of over 30,000 cells in one experiment and enable massively parallel in vivo Perturb-seq. Compatible with various phenotypic measurements (single-cell or spatial multi-omics), it presents a flexible approach to interrogate gene function across cell types in vivo, translating gene variants to their causal function.

Exploiting Sound for Emerging Applications of Extracellular Vesicles.

Extracellular vesicles are nano- to microscale, membrane-bound particles released by cells into extracellular space, and act as carriers of biomarkers and therapeutics, holding promising potential in translational medicine. However, the challenges remain in handling and detecting extracellular vesicles for disease diagnosis as well as exploring their therapeutic capability for disease treatment. Here, we review the recent engineering and technology advances by leveraging the power of sound waves to address the challenges in diagnostic and therapeutic applications of extracellular vesicles and biomimetic nanovesicles. We first introduce the fundamental principles of sound waves for understanding different acoustic-assisted extracellular vesicle technologies. We discuss the acoustic-assisted diagnostic methods including the purification, manipulation, biosensing, and bioimaging of extracellular vesicles. Then, we summarize the recent advances in acoustically enhanced therapeutics using extracellular vesicles and biomimetic nanovesicles. Finally, we provide perspectives into current challenges and future clinical applications of the promising extracellular vesicles and biomimetic nanovesicles powered by sound.

Functional sensory circuits built from neurons of two species.

A central question for regenerative neuroscience is whether synthetic neural circuits, such as those built from two species, can function in an intact brain. Here, we apply blastocyst complementation to selectively build and test interspecies neural circuits. Despite approximately 10-20 million years of evolution, and prominent species differences in brain size, rat pluripotent stem cells injected into mouse blastocysts develop and persist throughout the mouse brain. Unexpectedly, the mouse niche reprograms the birth dates of rat neurons in the cortex and hippocampus, supporting rat-mouse synaptic activity. When mouse olfactory neurons are genetically silenced or killed, rat neurons restore information flow to odor processing circuits. Moreover, they rescue the primal behavior of food seeking, although less well than mouse neurons. By revealing that a mouse can sense the world using neurons from another species, we establish neural blastocyst complementation as a powerful tool to identify conserved mechanisms of brain development, plasticity, and repair.

Fine-tuning TrailMap: The utility of transfer learning to improve the performance of deep learning in axon segmentation of light-sheet microscopy images.

Light-sheet microscopy has made possible the 3D imaging of both fixed and live biological tissue, with samples as large as the entire mouse brain. However, segmentation and quantification of that data remains a time-consuming manual undertaking. Machine learning methods promise the possibility of automating this process. This study seeks to advance the performance of prior models through optimizing transfer learning. We fine-tuned the existing TrailMap model using expert-labeled data from noradrenergic axonal structures in the mouse brain. By changing the cross-entropy weights and using augmentation, we demonstrate a generally improved adjusted F1-score over using the originally trained TrailMap model within our test datasets.

Engineering Heterogeneous Tumor Models for Biomedical Applications.

Tumor tissue engineering holds great promise for replicating the physiological and behavioral characteristics of tumors in vitro. Advances in this field have led to new opportunities for studying the tumor microenvironment and exploring potential anti-cancer therapeutics. However, the main obstacle to the widespread adoption of tumor models is the poor understanding and insufficient reconstruction of tumor heterogeneity. In this review, the current progress of engineering heterogeneous tumor models is discussed. First, the major components of tumor heterogeneity are summarized, which encompasses various signaling pathways, cell proliferations, and spatial configurations. Then, contemporary approaches are elucidated in tumor engineering that are guided by fundamental principles of tumor biology, and the potential of a bottom-up approach in tumor engineering is highlighted. Additionally, the characterization approaches and biomedical applications of tumor models are discussed, emphasizing the significant role of engineered tumor models in scientific research and clinical trials. Lastly, the challenges of heterogeneous tumor models in promoting oncology research and tumor therapy are described and key directions for future research are provided.

Fine-tuning TrailMap: The utility of transfer learning to improve the performance of deep learning in axon segmentation of light-sheet microscopy images.

Light-sheet microscopy has made possible the 3D imaging of both fixed and live biological tissue, with samples as large as the entire mouse brain. However, segmentation and quantification of that data remains a time-consuming manual undertaking. Machine learning methods promise the possibility of automating this process. This study seeks to advance the performance of prior models through optimizing transfer learning. We fine-tuned the existing TrailMap model using expert-labeled data from noradrenergic axonal structures in the mouse brain. By fine-tuning the final two layers of the neural network at a lower learning rate of the TrailMap model, we demonstrate an improved recall and an occasionally improved adjusted F1-score within our test dataset over using the originally trained TrailMap model.

A suite of engineered mice for interrogating psychedelic drug actions.

Psychedelic drugs like lysergic acid diethylamide (LSD) and psilocybin have emerged as potentially transformative therapeutics for many neuropsychiatric diseases, including depression, anxiety, post-traumatic stress disorder, migraine, and cluster headaches. LSD and psilocybin exert their psychedelic effects via activation of the 5-hydroxytryptamine 2A receptor (HTR2A). Here we provide a suite of engineered mice useful for clarifying the role of HTR2A and HTR2A-expressing neurons in psychedelic drug actions. We first generated Htr2a-EGFP-CT-IRES-CreERT2 mice (CT:C-terminus) to independently identify both HTR2A-EGFP-CT receptors and HTR2A-containing cells thereby providing a detailed anatomical map of HTR2A and identifying cell types that express HTR2A. We also generated a humanized Htr2a mouse line and an additional constitutive Htr2A-Cre mouse line. Psychedelics induced a variety of known behavioral changes in our mice validating their utility for behavioral studies. Finally, electrophysiology studies revealed that extracellular 5-HT elicited a HTR2A-mediated robust increase in firing of genetically-identified pyramidal neurons--consistent with a plasma membrane localization and mode of action. These mouse lines represent invaluable tools for elucidating the molecular, cellular, pharmacological, physiological, behavioral, and other actions of psychedelic drugs in vivo.

Cortical Brain Injury Causes Retrograde Degeneration of Afferent Basal Forebrain Cholinergic Neurons via the p75NTR.

Traumatic brain injury (TBI) elicits neuronal loss at the site of injury and progressive neuronal loss in the penumbra. However, the consequences of TBI on afferent neurons projecting to the injured tissue from distal locations is unknown. Basal forebrain cholinergic neurons (BFCNs) extend long projections to multiple brain regions including the cortex, regulate many cognitive functions, and are compromised in numerous neurodegenerative disorders. To determine the consequence of cortical injury on these afferent neurons, we used the fluid percussion injury model of traumatic brain injury and assessed the effects on BFCN survival and axon integrity in male and female mice. Survival or death of BF neurons can be regulated by neurotrophins or proneurotrophins, respectively. The injury elicited an induction of proNGF and proBDNF in the cortex and a loss of BFCNs ipsilateral to the injury compared with sham uninjured mice. The p75NTR knock-out mice did not show loss of BFCN neurons, indicating a retrograde degenerative effect of the cortical injury on the afferent BFCNs mediated through p75NTR. In contrast, locus ceruleus neurons, which also project throughout the cortex, were unaffected by the injury, suggesting specificity in retrograde degeneration after cortical TBI. Proneurotrophins (proNTs) provided directly to basal forebrain axons in microfluidic cultures triggered retrograde axonal degeneration and cell death, which did not occur in the absence of p75NTR. This study shows that after traumatic brain injury, proNTs induced in the injured cortex promote BFCN axonal degeneration and retrograde neuron loss through p75NTR.

Full-Spectrum Neuronal Diversity and Stereotypy through Whole Brain Morphometry.

We conducted a large-scale study of whole-brain morphometry, analyzing 3.7 peta-voxels of mouse brain images at the single-cell resolution, producing one of the largest multi-morphometry databases of mammalian brains to date. We spatially registered 205 mouse brains and associated data from six Brain Initiative Cell Census Network (BICCN) data sources covering three major imaging modalities from five collaborative projects to the Allen Common Coordinate Framework (CCF) atlas, annotated 3D locations of cell bodies of 227,581 neurons, modeled 15,441 dendritic microenvironments, characterized the full morphology of 1,891 neurons along with their axonal motifs, and detected 2.58 million putative synaptic boutons. Our analysis covers six levels of information related to neuronal populations, dendritic microenvironments, single-cell full morphology, sub-neuronal dendritic and axonal arborization, axonal boutons, and structural motifs, along with a quantitative characterization of the diversity and stereotypy of patterns at each level. We identified 16 modules consisting of highly intercorrelated brain regions in 13 functional brain areas corresponding to 314 anatomical regions in CCF. Our analysis revealed the dendritic microenvironment as a powerful method for delineating brain regions of cell types and potential subtypes. We also found that full neuronal morphologies can be categorized into four distinct classes based on spatially tuned morphological features, with substantial cross-areal diversity in apical dendrites, basal dendrites, and axonal arbors, along with quantified stereotypy within cortical, thalamic and striatal regions. The lamination of somas was found to be more effective in differentiating neuron arbors within the cortex. Further analysis of diverging and converging projections of individual neurons in 25 regions throughout the brain reveals branching preferences in the brain-wide and local distributions of axonal boutons. Overall, our study provides a comprehensive description of key anatomical structures of neurons and their types, covering a wide range of scales and features, and contributes to our understanding of neuronal diversity and its function in the mammalian brain.

High-throughput confocal airy beam oblique light-sheet tomography of brain-wide imaging at single-cell resolution.

Brain research is an area of research characterized by its cutting-edge nature, with brain mapping constituting a crucial aspect of this field. As sequencing tools have played a crucial role in gene sequencing, brain mapping largely depends on automated, high-throughput and high-resolution imaging techniques. Over the years, the demand for high-throughput imaging has scaled exponentially with the rapid development of microscopic brain mapping. In this paper, we introduce the novel concept of confocal Airy beam into oblique light-sheet tomography named CAB-OLST. We demonstrate that this technique enables the high throughput of brain-wide imaging of long-distance axon projection for the entire mouse brain at a resolution of 0.26 µm × 0.26 µm × 1.06 µm in 58 hours. This technique represents an innovative contribution to the field of brain research by setting a new standard for high-throughput imaging techniques.

Brain Organoid Computing for Artificial Intelligence.

Brain-inspired hardware emulates the structure and working principles of a biological brain and may address the hardware bottleneck for fast-growing artificial intelligence (AI). Current brain-inspired silicon chips are promising but still limit their power to fully mimic brain function for AI computing. Here, we develop Brainoware , living AI hardware that harnesses the computation power of 3D biological neural networks in a brain organoid. Brain-like 3D in vitro cultures compute by receiving and sending information via a multielectrode array. Applying spatiotemporal electrical stimulation, this approach not only exhibits nonlinear dynamics and fading memory properties but also learns from training data. Further experiments demonstrate real-world applications in solving non-linear equations. This approach may provide new insights into AI hardware.

Acoustofluidic assembly of primary tumor-derived organotypic cell clusters for rapid evaluation of cancer immunotherapy.

Cancer immunotherapy shows promising potential for treating breast cancer. While patients may have heterogeneous treatment responses for adjuvant therapy, it is challenging to predict an individual patient's response to cancer immunotherapy. Here, we report primary tumor-derived organotypic cell clusters (POCCs) for rapid and reliable evaluation of cancer immunotherapy. By using a label-free, contactless, and highly biocompatible acoustofluidic method, hundreds of cell clusters could be assembled from patient primary breast tumor dissociation within 2 min. Through the incorporation of time-lapse living cell imaging, the POCCs could faithfully recapitulate the cancer-immune interaction dynamics as well as their response to checkpoint inhibitors. Superior to current tumor organoids that usually take more than two weeks to develop, the POCCs can be established and used for evaluation of cancer immunotherapy within 12 h. The POCCs can preserve the cell components from the primary tumor due to the short culture time. Moreover, the POCCs can be assembled with uniform fabricate size and cell composition and served as an open platform for manipulating cell composition and ratio under controlled treatment conditions with a short turnaround time. Thus, we provide a new method to identify potentially immunogenic breast tumors and test immunotherapy, promoting personalized cancer therapy.

Acoustic metamaterials-driven transdermal drug delivery for rapid and on-demand management of acute disease.

Transdermal drug delivery provides convenient and pain-free self-administration for personalized therapy. However, challenges remain in treating acute diseases mainly due to their inability to timely administrate therapeutics and precisely regulate pharmacokinetics within a short time window. Here we report the development of active acoustic metamaterials-driven transdermal drug delivery for rapid and on-demand acute disease management. Through the integration of active acoustic metamaterials, a compact therapeutic patch is integrated for penetration of skin stratum corneum and active percutaneous transport of therapeutics with precise control of dose and rate over time. Moreover, the patch device quantitatively regulates the dosage and release kinetics of therapeutics and achieves better delivery performance in vivo than through subcutaneous injection. As a proof-of-concept application, we show our method can reverse life-threatening acute allergic reactions in a female mouse model of anaphylaxis via a multi-burst delivery of epinephrine, showing better efficacy than a fixed dosage injection of epinephrine, which is the current gold standard 'self-injectable epinephrine' strategy. This innovative method may provide a promising means to manage acute disease for personalized medicine.

Activation of MAP2K signaling by genetic engineering or HF-rTMS promotes corticospinal axon sprouting and functional regeneration.

Facilitating axon regeneration in the injured central nervous system remains a challenging task. RAF-MAP2K signaling plays a key role in axon elongation during nervous system development. Here, we show that conditional expression of a constitutively kinase-activated BRAF in mature corticospinal neurons elicited the expression of a set of transcription factors previously implicated in the regeneration of zebrafish retinal ganglion cell axons and promoted regeneration and sprouting of corticospinal tract (CST) axons after spinal cord injury in mice. Newly sprouting axon collaterals formed synaptic connections with spinal interneurons, resulting in improved recovery of motor function. Noninvasive suprathreshold high-frequency repetitive transcranial magnetic stimulation (HF-rTMS) activated the BRAF canonical downstream effectors MAP2K1/2 and modulated the expression of a set of regeneration-related transcription factors in a pattern consistent with that induced by BRAF activation. HF-rTMS enabled CST axon regeneration and sprouting, which was abolished in MAP2K1/2 conditional null mice. These data collectively demonstrate a central role of MAP2K signaling in augmenting the growth capacity of mature corticospinal neurons and suggest that HF-rTMS might have potential for treating spinal cord injury by modulating MAP2K signaling.

Engineering human spinal microphysiological systems to model opioid-induced tolerance.

pioids are commonly used for treating chronic pain. However, with continued use, they may induce tolerance and/or hyperalgesia, which limits therapeutic efficacy. The human mechanisms of opioid-induced tolerance and hyperalgesia are significantly understudied, in part, because current models cannot fully recapitulate human pathology. Here, we engineered novel human spinal microphysiological systems (MPSs) integrated with plug-and-play neural activity sensing for modeling human nociception and opioid-induced tolerance. Each spinal MPS consists of a flattened human spinal cord organoid derived from human stem cells and a 3D printed organoid holder device for plug-and-play neural activity measurement. We found that the flattened organoid design of MPSs not only reduces hypoxia and necrosis in the organoids, but also promotes their neuron maturation, neural activity, and functional development. We further demonstrated that prolonged opioid exposure resulted in neurochemical correlates of opioid tolerance and hyperalgesia, as measured by altered neural activity, and downregulation of µ-opioid receptor expression of human spinal MPSs. The MPSs are scalable, cost-effective, easy-to-use, and compatible with commonly-used well-plates, thus allowing plug-and-play measurements of neural activity. We believe the MPSs hold a promising translational potential for studying human pain etiology, screening new treatments, and validating novel therapeutics for human pain medicine.

Noninvasive prenatal diagnosis targeting fetal nucleated red blood cells.

Noninvasive prenatal diagnosis (NIPD) aims to detect fetal-related genetic disorders before birth by detecting markers in the peripheral blood of pregnant women, holding the potential in reducing the risk of fetal birth defects. Fetal-nucleated red blood cells (fNRBCs) can be used as biomarkers for NIPD, given their remarkable nature of carrying the entire genetic information of the fetus. Here, we review recent advances in NIPD technologies based on the isolation and analysis of fNRBCs. Conventional cell separation methods rely primarily on physical properties and surface antigens of fNRBCs, such as density gradient centrifugation, fluorescence-activated cell sorting, and magnetic-activated cell sorting. Due to the limitations of sensitivity and purity in Conventional methods, separation techniques based on micro-/nanomaterials have been developed as novel methods for isolating and enriching fNRBCs. We also discuss emerging methods based on microfluidic chips and nanostructured substrates for static and dynamic isolation of fNRBCs. Additionally, we introduce the identification techniques of fNRBCs and address the potential clinical diagnostic values of fNRBCs. Finally, we highlight the challenges and the future directions of fNRBCs as treatment guidelines in NIPD.

Microfluidics guided by deep learning for cancer immunotherapy screening.

Immunocyte infiltration and cytotoxicity play critical roles in both inflammation and immunotherapy. However, current cancer immunotherapy screening methods overlook the capacity of the T cells to penetrate the tumor stroma, thereby significantly limiting the development of effective treatments for solid tumors. Here, we present an automated high-throughput microfluidic platform for simultaneous tracking of the dynamics of T cell infiltration and cytotoxicity within the 3D tumor cultures with a tunable stromal makeup. By recourse to a clinical tumor-infiltrating lymphocyte (TIL) score analyzer, which is based on a clinical data-driven deep learning method, our platform can evaluate the efficacy of each treatment based on the scoring of T cell infiltration patterns. By screening a drug library using this technology, we identified an epigenetic drug (lysine-specific histone demethylase 1 inhibitor, LSD1i) that effectively promoted T cell tumor infiltration and enhanced treatment efficacy in combination with an immune checkpoint inhibitor (anti-PD1) in vivo. We demonstrated an automated system and strategy for screening immunocyte-solid tumor interactions, enabling the discovery of immuno- and combination therapies.

Understanding Immune-Driven Brain Aging by Human Brain Organoid Microphysiological Analysis Platform.

The aging of the immune system drives systemic aging and the pathogenesis of age-related diseases. However, a significant knowledge gap remains in understanding immune-driven aging, especially in brain aging, due to the limited current in vitro models of neuroimmune interaction. Here, the authors report the development of a human brain organoid microphysiological analysis platform (MAP) to discover the dynamic process of immune-driven brain aging. The organoid MAP is created by 3D printing that confines organoid growth and facilitates cell and nutrition perfusion, promoting organoid maturation and their committment to forebrain identity. Dynamic rocking flow is incorporated into the platform that allows to perfuse primary monocytes from young (20 to 30-year-old) and aged (>60-year-old) donors and culture human cortical organoids to model neuroimmune interaction. The authors find that the aged monocytes increase infiltration and promote the expression of aging-related markers (e.g., higher expression of p16) within the human cortical organoids, indicating that aged monocytes may drive brain aging. The authors believe that the organoid MAP may provide promising solutions for basic research and translational applications in aging, neural immunological diseases, autoimmune disorders, and cancer.