Biology subjects

Ji, N.

Publications and source records attributed to Ji, N..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Identification of Intrinsic Features for Cortical Separability of Human and Mouse Neurons

This work introduces a novel framework for holistic comparative analysis of cortical regions in mouse and human brains at single-neuron resolution, with a primary focus on the morphological and molecular characteristics of neurons. To do so, we generated one of the largest dendritic reconstruction datasets of cortical neurons to date, comprising 2,363 human neurons and 16,011 mouse neurons from the frontal, parietal, and temporal lobes, followed by establishing a rigorous procedure to identify anatomically and functionally corresponding brain regions with minimal variability in brain mapping. Additionally, we leveraged single nucleus/cell transcriptomic data from independent groups to validate the molecular correspondence of the brain regions identified in this study. The significance of these anatomically, functionally, and molecularly corresponding mouse-human region pairs is highlighted by examining the intrinsic features of their respective cortical regions. Our findings reveal that human neuron branching patterns differ dramatically from those in mouse brains, particularly in terms of dendritic branching frequency and normalized dendritic branching intervals. This difference is pronounced in the frontal and temporal lobes, underscoring the distinct neuronal architectures between the two species. At the single-neuron level, we found that neurons from the human frontal and parietal lobes are six times more separable than those from the same regions in mouse brains. This heightened separability is also observed between the frontal and temporal lobes, as well as between the parietal and temporal lobes in humans. We thoroughly explored the entire morphological feature space, along with its characteristic subspaces, and consistently found this distinct separability. Remarkably, this neuronal separability can be partially recapitulated when examining the global functional states of these brain lobes--using newly acquired Electroencephalography (EEG) and Magnetoencephalography (MEG) signals as physiological measures--as well as their global metabolic states, molecular profiles, and cortical geometry. These findings suggest that our comparative analysis of single-neuron intrinsic features could serve as a valuable foundation for future comprehensive studies of cross-species brain structures and functions.

neuroscience↗

bioRxiv2024

Improving positively tuned voltage indicators for brightness and kinetics

Existing positively tuned ASAP-family voltage indicators such as ASAP4e exhibit superior photostability compared to the negatively tuned ASAP3 and ASAP5, but signal-to-noise ratios for spike detection remained similar to ASAP3. To improve spike detection by positively tuned ASAP indicators, we performed multiple rounds of structure-guided saturation mutagenesis of an ASAP4e predecessor while screening directly for faster responses. One variant, ASAP6c, demonstrated [~]100% increases in fluorescence in response to single action potentials in both one-photon and two-photon imaging in vivo, achieving a 3-fold improvement in signal-to-noise ratios over ASAP4e.

neuroscience↗

bioRxiv2024

Adaptive optical third-harmonic generation microscopy for in vivo imaging of tissues

Third-harmonic generation microscopy is a powerful label-free nonlinear imaging technique, providing essential information about structural characteristics of cells and tissues without requiring external labelling agents. In this work, we integrated a recently developed compact adaptive optics module into a third-harmonic generation microscope, to measure and correct for optical aberrations in complex tissues. Taking advantage of the high sensitivity of the third-harmonic generation process to material interfaces and thin membranes, along with the 1,300-nm excitation wavelength used here, our adaptive optical third-harmonic generation microscope enabled high-resolution in vivo imaging within highly scattering biological model systems. Examples include imaging of myelinated axons and vascular structures within the mouse spinal cord and deep cortical layers of the mouse brain, along with imaging of key anatomical features in the roots of the model plant Brachypodium distachyon. In all instances, aberration correction led to significant enhancements in image quality.

biophysics↗

bioRxiv2024

Label-free structural imaging of plant roots and microbes using third- harmonic generation microscopy

Root biology is pivotal in addressing global challenges including sustainable agriculture and climate change. However, roots have been relatively understudied among plant organs, partly due to the difficulties in imaging root structures in their natural environment. Here we used microfabricated ecosystems (EcoFABs) to establish growing environments with optical access and employed nonlinear multimodal microscopy of third-harmonic generation (THG) and three-photon fluorescence (3PF) to achieve label-free, in situ imaging of live roots and microbes at high spatiotemporal resolution. THG enabled us to observe key plant root structures including the vasculature, Casparian strips, dividing meristematic cells, and root cap cells, as well as subcellular features including nuclear envelopes, nucleoli, starch granules, and putative stress granules. THG from the cell walls of bacteria and fungi also provides label-free contrast for visualizing these microbes in the root rhizosphere. With simultaneously recorded 3PF fluorescence signal, we demonstrated our ability to investigate root-microbe interactions by achieving single-bacterium tracking and subcellular imaging of fungal spores and hyphae in the rhizosphere.

plant biology↗

bioRxiv2023

Distinct mechanisms drive plant-nitrifier interactions in topsoil and subsoil

Plants can influence soil microbes through resource acquisition and interference competition, with consequences for ecosystem function such as nitrification. However, how plants alter soil conditions to influence nitrifiers and nitrification rates remains poorly understood, especially in the subsoil. Here, coupling the 15N isotopic pool dilution technique, high throughput sequencing and in situ soil O2 monitoring, we investigated how a deep-rooted perennial grass, miscanthus, versus an adjacent shallow-rooted turfgrass reference shapes nitrifier assembly and function along 1 meter soil profiles. In topsoil, the suppression of ammonia (NH3) oxidizing archaea (AOA) and gross nitrification rates in miscanthus relative to the reference likely resulted from nitrifiers being outcompeted by plant roots and heterotrophic bacteria for ammonium (NH4+). The stronger tripartite competition under miscanthus may have been caused in part by the lower soil organic matter (SOM) content, which supported lower gross nitrogen (N) mineralization, the major soil process that produces NH4+. In contrast, below 10 cm soil depth, significantly greater gross nitrification rates were observed in miscanthus compared to the reference. This was likely driven by the significantly lower oxygen (O2) in miscanthus than reference subsoil, which selected against aerobic heterotrophic bacteria but in favor of AOA. Overall, we found that plants can regulate AOA community structure and function through different mechanisms in topsoil and subsoil, with suppression of nitrification in topsoil and enhancement of nitrification in subsoil.

ecology↗

bioRxiv2023

maskNMF: A denoise-sparsen-detect approach for extracting neural signals from dense imaging data

A number of calcium imaging methods have been developed to monitor the activity of large populations of neurons. One particularly promising approach, Bessel imaging, captures neural activity from a volume by projecting within the imaged volume onto a single imaging plane, therefore effectively mixing signals and increasing the number of neurons imaged per pixel. These signals must then be computationally demixed to recover the desired neural activity. Unfortunately, currently-available demixing methods can perform poorly in the regime of high imaging density (i.e., many neurons per pixel). In this work we introduce a new pipeline (maskNMF) for demixing dense calcium imaging data. The main idea is to first denoise and temporally sparsen the observed video; this enhances signal strength and reduces spatial overlap significantly. Next we detect neurons in the sparsened video using a neural network trained on a library of neural shapes. These shapes are derived from segmented electron microscopy images input into a Bessel imaging model; therefore no manual selection of "good" neural shapes from the functional data is required here. After cells are detected, we use a constrained non-negative matrix factorization approach to demix the activity, using the detected cells shapes to initialize the factorization. We test the resulting pipeline on both simulated and real datasets and find that it is able to achieve accurate demixing on denser data than was previously feasible, therefore enabling faithful imaging of larger neural populations. The method also provides good results on more "standard" two-photon imaging data. Finally, because much of the pipeline operates on a significantly compressed version of the raw data and is highly parallelizable, the algorithm is fast, processing large datasets faster than real time.

neuroscience↗

bioRxiv2023

Incorporating physics to overcome data scarcity in predictive modeling of protein function: a case study of BK channels

Machine learning has played transformative roles in numerous chemical and biophysical problems such as protein folding where large amount of data exists. Nonetheless, many important problems remain challenging for data-driven machine learning approaches due to the limitation of data scarcity. One approach to overcome data scarcity is to incorporate physical principles such as through molecular modeling and simulation. Here, we focus on the big potassium (BK) channels that play important roles in cardiovascular and neural systems. Many mutants of BK channel are associated with various neurological and cardiovascular diseases, but the molecular effects are unknown. The voltage gating properties of BK channels have been characterized for 473 site-specific mutations experimentally over the last three decades; yet, these functional data by themselves remain far too sparse to derive a predictive model of BK channel voltage gating. Using physics-based modeling, we quantify the energetic effects of all single mutations on both open and closed states of the channel. Together with dynamic properties derived from atomistic simulations, these physical descriptors allow the training of random forest models that could reproduce unseen experimentally measured shifts in gating voltage, {Delta}V1/2, with a RMSE [~] 32 mV and correlation coefficient of R [~] 0.7. Importantly, the model appears capable of uncovering nontrivial physical principles underlying the gating of the channel, including a central role of hydrophobic gating. The model was further evaluated using four novel mutations of L235 and V236 on the S5 helix, mutations of which are predicted to have opposing effects on V1/2 and suggest a key role of S5 in mediating voltage sensor-pore coupling. The measured {Delta}V1/2 agree quantitatively with prediction for all four mutations, with a high correlation of R = 0.92 and RMSE = 18 mV. Therefore, the model can capture nontrivial voltage gating properties in regions where few mutations are known. The success of predictive modeling of BK voltage gating demonstrates the potential of combining physics and statistical learning for overcoming data scarcity in nontrivial protein function prediction. Author SummaryDeep machine learning has brought many exciting breakthroughs in chemistry, physics and biology. These models require large amount of training data and struggle when the data is scarce. The latter is true for predictive modeling of the function of complex proteins such as ion channels, where only hundreds of mutational data may be available. Using the big potassium (BK) channel as a biologically important model system, we demonstrate that a reliable predictive model of its voltage gating property could be derived from only 473 mutational data by incorporating physics-derived features, which include dynamic properties from molecular dynamics simulations and energetic quantities from Rosetta mutation calculations. We show that the final random forest model captures key trends and hotspots in mutational effects of BK voltage gating, such as the important role of pore hydrophobicity. A particularly curious prediction is that mutations of two adjacent residues on the S5 helix would always have opposite effects on the gating voltage, which was confirmed by experimental characterization of four novel mutations. The current work demonstrates the importance and effectiveness of incorporating physics in predictive modeling of protein function with scarce data.

bioinformatics↗

bioRxiv2023

Tumor-specific neutrophils originating from meninges promote glioblastoma

Glioma is one of the most aggressive human cancers with limited therapeutic options. Though research has extensively examined immune components in those malignant tumors, the pathophysiological mechanism establishing their immunosuppressive microenvironment remains incompletely characterized. In this study, we report for the first time the unique presence of tumor-specific neutrophils (TSNs) in human glioblastoma (GBM) tumors. This newly defined neutrophil subtype exhibits the high expression of several immunosuppressive genes (e.g., CD274 and IDO1) and is strongly correlated with glioma grades and poor prognosis of patients. TSNs with comparable gene signatures are similarly present in the tumors but not bone marrow or spleen of mouse glioma models. Blockage of TSN recruitment by either Cxcl1-knockout in glioma cells or Cxcr2-deletion in host mice significantly enhances antitumor immunity and inhibits tumor progression. Surprisingly, we further identify the meninges as the key extratumoral source of generating TSNs in both human GBM patients and mouse glioma models. These results have elucidated a novel mechanism of neutrophils designating the tumor immune microenvironment and the essential link of meningeal immunity to glioma.

cancer biology↗

bioRxiv2023

Multi-omics and Pharmacological Characterization of Patient-derived Glioma Cell Lines

Glioblastoma (GBM) is the most common brain tumor and is currently incurable. Primary GBM cultures are widely used tools for screening potentially therapeutic drugs; however, there is a lack of genomic and pharmacological characterization of these primary GBM cultures. Here, we collected 52 patient-derived glioma cell (PDGC) lines and characterized them through whole- genome sequencing (WGS), RNA-seq, and drug response screening. We identified three molecular subtypes among PDGCs: mesenchymal (MES), proneural (PN), and oxidative phosphorylation (OXPHOS). Upon profiling the responses of PDGCs to 214 drugs, we found that the PN subtype PDGCs were sensitive to tyrosine kinase inhibitors, whereas the OXPHOS subtype PDGCs were sensitive to histone deacetylase inhibitors, oxidative phosphorylation inhibitors, and HMG-CoA reductase inhibitors. PN and OXPHOS subtype PDGCs stably formed tumors in vivo upon intracranial transplantation into immunodeficient mice, while most MES subtype PDGCs were incapable of tumorigenesis in vivo. In addition, profiling and follow-up investigations showed that the serum-free culture system used for PDGCs enriched and propagated rare MYC/MYCN- amplified glioma cells. Our study provides a resource for understanding primary glioma cell cultures and aiding clinical translation. SignificanceOur study provides a resource for patient-derived glioma cell lines (PDGCs) on transcriptome, genome, drug response, and tumorigenic abilities. PDGCs are categorized into PN, MES, and OXPHOS subtypes, with MES-subtype PDGCs incapable of tumorigenesis in vivo. Notably, the serum-free culture system for PDGCs enriches glioma cells with MYC/MYCN amplification.

cancer biology↗

bioRxiv2023

Adaptive optical two-photon fluorescence microscopy probes cellular organization of ocular lenses in vivo

The mammalian ocular lens is an avascular multicellular organ that grows continuously throughout life. Traditionally, its cellular organization is investigated using dissected lenses, which eliminates in vivo environmental and structural support. Here, we demonstrated that two-photon fluorescence microscopy (2PFM) can visualize lens cells in vivo. To maintain subcellular resolution at depth, we employed adaptive optics (AO) to correct aberrations due to ocular and lens tissues, which led to substantial signal and resolution improvements. Imaging lens cells up to 980 m deep, we observed novel cellular organizations including suture-associated voids, enlarged vacuoles, and large cavities, contrary to the conventional view of a highly ordered organization. We tracked these features longitudinally over weeks and observed the incorporation of new cells during growth. Taken together, non-invasive longitudinal in vivo imaging of lens morphology using AO 2PFM will allow us to directly observe the development or alterations of lens cellular organization in living animals.

bioengineering↗

bioRxiv2022

Retinal microvascular and neuronal pathologies probed in vivo by adaptive optical two-photon fluorescence microscopy

The retina, behind the transparent optics of the eye, is the only neural tissue whose physiology and pathology can be non-invasively probed by optical microscopy. The aberrations intrinsic to the mouse eye, however, prevent high-resolution investigation of retinal structure and function in vivo. Optimizing the design of a two-photon fluorescence microscope (2PFM) and sample preparation procedure, we found that adaptive optics (AO), by measuring and correcting ocular aberrations, is essential for resolving synapses and achieving three-dimensional cellular resolution in the mouse retina in vivo. Applying AO-2PFM to longitudinal retinal imaging in transgenic models of retinal pathology, we characterized microvascular lesions and observed microglial migration in a proliferative vascular retinopathy model, and found Lidocaine to effectively suppress retinal ganglion cell hyperactivity in a retinal degeneration model. Tracking structural and functional changes at high resolution longitudinally, AO-2PFM enables microscopic investigations of retinal pathology and pharmacology for disease diagnosis and treatment in vivo.

neuroscience↗

bioRxiv2022

Whole Human-Brain Mapping of Single Cortical Neurons for Profiling Morphological Diversity and Stereotypy

Quantification of individual cells morphology and their distribution at the whole brain scale is essential to understand the structure and diversity of cell types. Despite recent technological advances, especially single cell labeling and whole brain imaging, for many prevailing animal models, it is exceedingly challenging to reuse similar technologies to study human brains. Here we propose Adaptive Cell Tomography (ACTomography), a low-cost, high-throughput, high-efficacy tomography approach, based on adaptive targeting of individual cells suitable for human-brain scale modeling of single neurons to characterize their 3-D structures, statistical distributions, and extensible for other cellular features. Specifically, we established a platform to inject dyes into cortical neurons in surgical tissues of 18 patients with brain tumors or other conditions and 1 donated fresh postmortem brain. We collected 3-D images of 1746 cortical neurons, of which 852 neurons were subsequentially reconstructed to quantify their local dendritic morphology, and mapped to standard atlases both computationally and semantically. In our data, human neurons are more diverse across brain regions than by subject age or gender. The strong stereotypy within cohorts of brain regions allows generating a statistical tensor-field of neuron morphology to characterize 3-D anatomical modularity of a human brain.

neuroscience↗

bioRxiv2022

Bessel-droplet foci enable high-resolution and high-contrast volumetric imaging of synapses and circulation in the brain in vivo

Bessel beam has long been utilized in physics for its ability to maintain lateral confinement during propagation. When used for two-photon fluorescence microscopy, Bessel foci have enabled high-speed volumetric imaging of the brain. At high numeric aperture (NA), however, the substantial energy in the side rings of Bessel foci reduces image contrast. Therefore, a compromise between resolution and contrast has to be made, limiting Bessel foci in microscopy to low NA. Here, we describe a method of generating axially extended Bessel-droplet foci with much suppressed side rings. Shaping the excitation wavefront with novel phase patterns, we generated Bessel-droplet foci of variable NAs at high power throughput and scanned them interferometrically along the axial direction for continuous volume imaging. More resistant to optical aberrations than Bessel foci, Bessel-droplet foci enabled high-resolution and high-contrast volumetric imaging of synaptic anatomy and function as well as lymphatic circulation in the mouse brain in vivo.

bioengineering↗

bioRxiv2021

A positively Tuned Voltage Indicator Reveals Electrical Correlates of Calcium Activity in the Brain

Neuronal spiking activity is routinely recorded using genetically encoded calcium indicators (GECIs), but calcium imaging is limited in temporal resolution and does not report subthreshold voltage changes. Genetically encoded voltage indicators (GEVIs) offer better temporal resolution and subthreshold sensitivity, but spike detection with fast GEVIs has required specialized imaging equipment. Here, we report the ASAP4 subfamily of genetically encoded voltage indicators (GEVIs) that brighten in response to membrane depolarization, inverting the fluorescence-voltage relationship of previous ASAP GEVIs. Two variants, ASAP4b and ASAP4e, feature 128% and 178% fluorescence increases over 100-mV of depolarization, respectively, facilitating spike detection in single trials in vivo with standard 1 and 2-photon imaging systems. Simultaneous voltage and calcium imaging confirms improved temporal resolution and spike discernment by ASAP4 GEVIs. Thus, positively tuned ASAP4 voltage indicators enable recording of neuronal spiking activity using similar equipment as calcium imaging, while providing higher temporal resolution. One Sentence SummaryUpward ASAPs increase detection capability of GEVIs in vivo.

neuroscience↗

bioRxiv2020

An adaptive optics module for deep tissue multiphoton imaging in vivo

Understanding complex biological systems requires visualizing structures and processes deep within living organisms. We developed a compact adaptive optics module and incorporated it into two- and three-photon fluorescence microscopes, to measure and correct tissue-induced aberrations. We resolved synaptic structures in deep cortical and subcortical areas of the mouse brain, and demonstrated high-resolution imaging of neuronal structures and somatosensory-evoked calcium responses in the mouse spinal cord at unprecedented depths in vivo.

bioengineering↗

bioRxiv2020

A neural circuit for flexible control of persistent behavioral states

To adapt to their environments, animals must generate behaviors that are closely aligned to a rapidly changing sensory world. However, behavioral states such as foraging or courtship typically persist over long time scales to ensure proper execution. It remains unclear how neural circuits generate persistent behavioral states while maintaining the flexibility to select among alternative states when the sensory context changes. Here, we elucidate the functional architecture of a neural circuit controlling the choice between roaming and dwelling states, which underlie exploration and exploitation during foraging in C. elegans. By imaging ensemble-level neural activity in freely-moving animals, we identify stable, circuit-wide activity patterns corresponding to each behavioral state. Combining circuit-wide imaging with genetic analysis, we find that mutual inhibition between two antagonistic neuromodulatory systems underlies the persistence and mutual exclusivity of the opposing network states. Through machine learning analysis and circuit perturbations, we identify a sensory processing neuron that can transmit information about food odors to both the roaming and dwelling circuits and bias the animal towards different states in different sensory contexts, giving rise to context-appropriate state transitions. Our findings reveal a potentially general circuit architecture that enables flexible, sensory-driven control of persistent behavioral states.

neuroscience↗

bioRxiv2019

Corollary Discharge Promotes a Sustained Motor State in a Neural Circuit for Navigation

Animals exhibit behavioral and neural responses that persist on longer time scales than transient or fluctuating stimulus inputs. Here, we report that C. elegans uses feedback from the motor circuit to a sensory processing interneuron to sustain its motor state during thermotactic navigation. By imaging circuit activity in behaving animals, we show that a principal postsynaptic partner of the AFD thermosensory neuron, the AIY interneuron, encodes both temperature and motor state information. By optogenetic and genetic manipulation of this circuit, we demonstrate that the motor state representation in AIY is a corollary discharge signal. RIM, an interneuron that is connected with premotor interneurons, is required for this corollary discharge. Ablation of RIM eliminates the motor representation in AIY, allows thermosensory representations to reach downstream premotor interneurons, and reduces the animals ability to sustain forward movements during thermotaxis. We propose that feedback from the motor circuit to the sensory processing circuit underlies a positive feedback mechanism to generate persistent neural activity and sustained behavioral patterns in a sensorimotor transformation.

neuroscience↗

bioRxiv2019

A distinct population of L6 neurons in mouse V1 mediate cross-callosal communication

Through the corpus callosum, interhemispheric communication is mediated by callosal projection (CP) neurons. Using retrograde labeling, we identified a population of layer 6 (L6) excitatory neurons as the main conveyer of transcallosal information in the monocular zone of the mouse primary visual cortex (V1). Distinct from L6 corticothalamic (CT) population, V1 L6 CP neurons contribute to an extensive reciprocal network across multiple sensory cortices over two hemispheres. Receiving both local and long-range cortical inputs, they encode orientation, direction, and receptive field information, while are also highly spontaneous active. The spontaneous activity of L6 CP neurons exhibits complex relationships with brain states and stimulus presentation, distinct from the spontaneous activity patterns of the CT population. The anatomical and functional properties of these L6 CP neurons enable them to broadcast visual and nonvisual information across two hemispheres, and thus play a major role in regulating and coordinating brain-wide activity events.

neuroscience↗