Biology subjects

Wang, C.

Publications and source records attributed to Wang, C..

At least 847 records · Page 47Linked to original sources

bioRxiv2021

Comparative phylogenomic analysis reveals evolutionary genomic changes and novel toxin families in endophytic Liberibacter pathogens

Liberibacter pathogens are the causative agents of several severe crop diseases worldwide, including citrus Huanglongbing and potato Zebra Chip. These bacteria are endophytic and non-culturable, which makes experimental approaches challenging and highlights the need for bioinformatic analysis in advancing our understanding about Liberibacter pathogenesis. Here, we performed an in-depth comparative phylogenomic analysis of the Liberibacter pathogens and their free-living, nonpathogenic, ancestral species, aiming to identify the major genomic changes and determinants associated with their evolutionary transitions in living habitats and pathogenicity. We found that prophage loci represent the most variable regions among Liberibacter genomes. Using gene neighborhood analysis and phylogenetic classification, we systematically recovered, annotated, and classified all prophage loci into four types, including one previously unrecognized group. We showed that these prophages originated through independent gene transfers at different evolutionary stages of Liberibacter and only the SC-type prophage was associated with the emergence of the pathogens. Using ortholog clustering, we vigorously identified two additional sets of genomic genes, which were either lost or gained in the ancestor of the pathogens. Consistent with the habitat change, the lost genes were enriched for biosynthesis of cellular building blocks. Importantly, among the gained genes, we uncovered several previously unrecognized toxins, including a novel class of polymorphic toxins, a YdjM phospholipase toxin, and a secreted EEP protein. Our results substantially extend the knowledge on the evolutionary events and potential determinants leading to the emergence of endophytic, pathogenic Liberibacter species and will facilitate the design of functional experiments and the development of new detection and blockage methods of these pathogens. ImportanceLiberibacter pathogens are associated with several severe crop diseases, including citrus Huanglongbing, the most destructive disease to the citrus industry. Currently, no effective cure or treatments are available, and no resistant citrus variety has been found. The fact that these obligate endophytic pathogens are not culturable has made it extremely challenging to experimentally uncover from the whole genome the genes/proteins important to Liberibacter pathogenesis. Further, earlier bioinformatics studies failed to identify the key genomic determinants, such as toxins and effector proteins, that underlie the pathogenicity of the bacteria. In this study, an in-depth comparative genomic analysis of Liberibacter pathogens together with their ancestral non-pathogenic species identified the prophage loci and several novel toxins that are evolutionarily associated with the emergence of the pathogens. These results shed new lights on the disease mechanism of Liberibacter pathogens and will facilitate the development of new detection and blockage methods targeting the toxins.

microbiology↗

bioRxiv2021

Genome of the giant panda roundworm illuminates its host shift and parasitic adaptation

Baylisascaris schroederi, a bamboo-feeding giant panda (Ailuropoda melanoleuca)-specific roundworm (ascaridoid) parasite, is the causative agent of baylisascariasis, which represents a leading reason for the mortality of wild giant panda populations and therefore poses a significant threat to giant panda conservation. Here we present a 293-Mb chromosome-level genome assembly of B. schroederi to inform its biology, including host adaptations. Comparative genomics revealed an evolutionary trajectory accompanied by host-shift events in ascaridoid parasite lineages after host separations, suggesting their potential transmissions and fast adaptations to hosts. Genomic and anatomical lines of evidence, including expansion and positive selection of genes related to cuticle and basal metabolisms, indicates that B. schroederi undergoes specific adaptations to survive in the sharp-edged bamboo enriched gut of giant panda by structurally increasing its cuticle thickness and efficiently utilizing host nutrients during gut parasitism. Also, we characterized the secretome and predicted potential drug and vaccine targets for new interventions. Overall, this genome resource provides new insights into the host adaptation of B. schroederi to giant panda as well as the host-shift events in ascaridoid parasite lineages. These findings also add to our knowledge on the unique biology of the giant panda roundworm and aid the development of much-needed novel strategies for the control of baylisascariasis and thus the protection of giant panda populations.

genomics↗

bioRxiv2021

Deep Learning-based Subcellular Phenotyping of Protrusion Dynamics Reveals Fine Differential Drug Responses at Subcellular and Single-Cell Levels

Live cell imaging provides unparallel insights into dynamic cellular processes across spatiotemporal scales. Despite its potential, the inherent spatiotemporal heterogeneity within live cell imaging data often obscures critical mechanical details underlying cellular dynamics. Uncovering fine-grained phenotypes of live cell dynamics is pivotal for precise understandings of the heterogeneity of physiological and pathological processes. However, this endeavor introduces formidable technical challenges to unsupervised machine learning, demanding the extraction of features that can faithfully preserve heterogeneity, effectively discriminate between different molecularly perturbed states, and provide interpretability. While deep learning shows promise in extracting useful features from large datasets, it often falls short in producing such high-fidelity features, especially in unsupervised learning settings. To tackle these challenges, we present DeepHACX (Deep phenotyping of Heterogeneous Activities of Cellular dynamics with eXplanations), a self-training deep learning framework designed for fine-grained and interpretable phenotyping. This framework seamlessly integrates an unsupervised teacher model with interpretable features to facilitate feature learning in a student deep neural network (DNN). Significantly, it incorporates an autoencoder-based regularizer, termed SENSER (SENSitivity-enhancing autoEncoding Regularizer), designed to prompt the student DNN to maximize the heterogeneity associated with molecular perturbations. This approach enables the acquisition of features that not only discriminate between different molecularly perturbed states but also faithfully preserve the heterogeneity linked to these perturbations. In our study, DeepHACX successfully delineated fine-grained phenotypes within the heterogeneous protrusion dynamics of migrating epithelial cells, uncovering specific responses to pharmacological perturbations. Remarkably, DeepHACX adeptly captured a minimal number of highly interpretable features uniquely linked to these fine-grained phenotypes, each corresponding to specific temporal intervals crucial for their manifestation. This unique capability positions DeepHACX as a valuable tool for investigating diverse cellular dynamics and comprehensively studying their heterogeneity.

bioinformatics↗

bioRxiv2021

Neuronal mitochondria transport Pink1 mRNA via Synaptojanin 2 to support local mitophagy

PTEN-induced kinase 1 (PINK1) is a very short-lived protein that is required for the removal of damaged mitochondria through Parkin translocation and mitophagy. Because the short half-life of PINK1 limits its ability to be trafficked into neurites, local translation is required for this mitophagy pathway to be active far from the soma. The Pink1 transcript is associated with and cotransported with neuronal mitochondria. In concert with translation, the mitochondrial outer membrane protein Synaptojanin 2 binding protein (SYNJ2BP) and Synaptojanin 2 (SYNJ2) are required for tethering Pink1 mRNA to mitochondria via an RNA-binding domain in SYNJ2. This neuron-specific adaptation for local translation of PINK1 provides distal mitochondria with a continuous supply of PINK1 for activation of mitophagy.

neuroscience↗

bioRxiv2021

Early cross-coronavirus reactive signatures of protective humoral immunity against COVID-19

The introduction of vaccines has inspired new hope in the battle against SARS-CoV-2. However, the emergence of viral variants, in the absence of potent antivirals, has left the world struggling with the uncertain nature of this disease. Antibodies currently represent the strongest correlate of immunity against COVID-19, thus we profiled the earliest humoral signatures in a large cohort of severe and asymptomatic COVID-19 individuals. While a SARS-CoV-2-specific immune response evolved rapidly in survivors of COVID-19, non-survivors exhibited blunted and delayed humoral immune evolution, particularly with respect to S2-specific antibody evolution. Given the conservation of S2 across {beta}-coronaviruses, we found the early development of SARS-CoV-2-specific immunity occurred in tandem with pre-existing common {beta}-coronavirus OC43 humoral immunity in survivors, which was selectively also expanded in individuals that develop paucisymptomatic infection. These data point to the importance of cross-coronavirus immunity as a correlate of protection against COVID-19.

immunology↗

bioRxiv2021

Rapid Electronic Diagnostics of Ebola Virus with Synthetic Nanobody-Conjugated Gold Nanoparticles

Successful control of emerging infectious diseases requires accelerated development of fast, affordable, and accessible assays to be widely implemented at a high frequency. Here we present a generalizable assay platform, nanobody-functionalized nanoparticles for rapid, electronic detection (Nano2RED), demonstrated in the detection of Ebola and COVID-19 antigens. To efficiently generate high-quality affinity reagents, synthetic nanobody co-binders and mono-binders with high affinity, specificity, and stability were selected by phage display screening of a vastly diverse, rationally randomized combinatorial library, bacterially expressed and site-specifically conjugated to gold nanoparticles (AuNPs) as multivalent in-solution sensors. Without requiring fluorescent labelling, washing, or enzymatic amplification, these AuNPs reliably transduce antigen binding signals upon mixing into physical AuNP aggregation and sedimentation processes, displaying antigen-dependent optical extinction readily detectable by spectrometry or simple electronic circuitry. With nanobodies against an Ebola virus secreted glycoprotein (sGP) and a SARS-CoV-2 spike protein receptor binding domain (RBD) as targets, Nano2RED showed a high sensitivity (limit of detection of [~]10 pg/mL for sGP and [~]40 pg/mL for RBD in diluted human serum), a high specificity, and a large dynamic range ([~]7 logs). Unlike conventional assays where slow mass transport for surface binding limits the assay time, Nano2RED features fast antigen diffusion at micrometer scale, and can be accelerated to deliver results within a few minutes. The rapid detection, low material cost (estimated < $0.01 per test), inexpensive and portable readout system (< $5 and < 100 cm3), and digital data output, make Nano2RED particularly suitable for screening of patient samples with simplified operation and accelerated data transmission. Our method is widely applicable for prototyping diagnostic assays for other antigens from new emerging viruses.

bioengineering↗

bioRxiv2021

Coil-to-Helix Transition at the Nup358-BicD2 Interface for Dynein Recruitment and Activation

Nup358, a nuclear pore protein, facilitates a nuclear positioning pathway that is essential for many biological processes, including neuromuscular and brain development. Nup358 binds and activates the auto-inhibited dynein adaptor Bicaudal D2 (BicD2), which in turn recruits and activates the dynein machinery to position the nucleus. However, the molecular details of the Nup358/BicD2 interaction remain poorly understood. Here, we show that a minimal Nup358 domain activates dynein/dynactin/BicD2 for processive motility on microtubules. Using nuclear magnetic resonance (NMR) titration and chemical exchange saturation transfer (CEST), a Nup358 helix encompassing residues 2162-2184 was identified, which transitioned from random coil to an -helix upon BicD2-binding and formed the core of the Nup358-BicD2 interface. Mutations in this region of Nup358 decreased the Nup358/BicD2 interaction, resulting in decreased dynein recruitment and impaired motility. BicD2 thus recognizes the cargo adaptor Nup358 though a "cargo recognition -helix", a structural feature that may stabilize BicD2 in its activated state and promote processive dynein motility.

biophysics↗

bioRxiv2021

Mechanistic Insights of High Temperature-Interfered Meiosis in Autotetraploid Arabidopsis thaliana

Environmental temperature has a huge impact on multiple meiosis processes in flowering plants. Polyploid plants derived from whole genome duplication are believed to have an enhanced abiotic stress tolerance. In this study, the impact of high temperatures on male meiosis in autotetraploid Arabidopsis thaliana was investigated. We found that autotetraploid Columbia (Col-0) plants generate a subpopulation of aberrant meiotic products under normal temperature, which is significantly increased under heat stress. Cytological studies revealed that, as the case in diploid Arabidopsis thaliana, assembly of microtubular cytoskeleton network, pairing and segregation of homologous chromosomes, and meiotic recombination in autotetraploid Arabidopsis are compromised under the high temperatures. Immunostaining of {ramshorn}H2A.X and recombinase DMC1 suggested that heat stress inhibits formation of DNA double-strand breaks; additionally, it specifically destabilizes ASY1 and ASY4, but not SYN1 on chromosomes. The loading defects of ASY1 and ASY4 overlap in the syn1 mutant, which supports that the building of lateral element of synaptonemal complex occurs downstream of a SYN1-ASY4-ASY3 stepwise assembly of axis. Remarkably, heat-induced abnormalities of ASY1 and ASY4 co-localize on chromosomes of both diploid and autotetraploid Arabidopsis, suggesting that high temperatures interfere with ASY1-associated SC via an impacted stability of chromosome axis. Furthermore, ZYP1-dependent transverse filament of SC is disrupted by heat stress. Taken together, these findings suggest that polyploidization negatively contributes to instability of chromosome axis and meiotic recombination in Arabidopsis thaliana under heat stress.

plant biology↗

bioRxiv2021

Circadian Control of Heparan Sulfate Levels Times Phagocytosis of Amyloid Beta Aggregates

Alzheimers Disease (AD) is a neuroinflammatory disease characterized partly by the inability to clear, and subsequent build-up, of amyloid-beta (A{beta}). A{beta} clearance is regulated by several pathways and has a circadian component. However, the mechanism underlying the circadian clearance of A{beta} has not been defined. Myeloid-based phagocytosis, a key mechanism in the metabolism of A{beta}, is circadianly-regulated, presenting a potential mechanism for the circadian clearance of A{beta}. In this work, we revealed that the phagocytosis of A{beta}42 undergoes a daily oscillation that is dependent on the circadian clock. We found the circadian timing of global heparan sulfate proteoglycan (HSPG) biosynthesis was the molecular timer for the clock-controlled phagocytosis of A{beta} and that both HSPG binding and A{beta}42 aggregation were essential for this oscillation. These data highlight that circadian regulation in immune cells may play a role in the intricate relationship between the circadian clock and AD. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/442651v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@bca9b3org.highwire.dtl.DTLVardef@29575corg.highwire.dtl.DTLVardef@2673c5org.highwire.dtl.DTLVardef@7a8daa_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2021

MRI-derived brain age as a biomarker of ageing in rats: validation using a healthy lifestyle intervention

MRI data can be used as input to machine learning models to accurately predict brain age in healthy human subjects. A large difference between predicted and chronological brain age (the so-called BrainAGE score) has been associated with disease and neurodegeneration, indicating the potential utility of neuroimaging-based ageing biomarkers. So far, most brain age prediction studies have been carried out on humans. However, it is important for such a biomarker to be validated on laboratory animals too, in order to better account for specific environmental or genetic factors within a more controlled laboratory framework. In this work, we developed a new algorithm for rat brain age prediction based on the combination of Gaussian process regression and a logistic regression classifier. The algorithm was trained on a cohort of 31 normal rats. High prediction accuracy was achieved using leave-one-out cross-validation (mean absolute error = 4.87 weeks, correlation between predicted and chronological age r = 0.92), supporting the validity and potential of the method. Furthermore, the trained model was tested on two independent groups of 24 rats each: a new normal control group and a "healthy lifestyle" group that underwent long-term environmental enrichment and dietary restriction (EEDR) between 3 and 17 months of age. After fitting a linear mixed-effects model, the BrainAGE values were found to increase more slowly with chronological age in the EEDR group than in the controls (slope = 0.52 vs. 0.61; p = 0.015 for the interaction term). When survival analysis was performed with a Cox regression model, the BrainAGE score at 5 months of age had a significant prediction power (p = 0.03). Our results demonstrate that BrainAGE, as computed by the proposed approach, is significantly modulated by EEDR intervention, hence it is a sensitive marker of biological ageing. These findings also support the potential of lifestyle-related prevention approaches to slow down the brain ageing process. Moreover, the results of the survival analysis further demonstrate that BrainAGE is indeed a predictor of ageing outcome.

neuroscience↗

bioRxiv2021

Genomic analysis reveals the influence of climate change and currents on adaptation in an estuarine species

Understanding the roles of genetic divergence and phenotypic plasticity in adaptation is central to evolutionary biology and important for assessing adaptive potential of species under climate change. Analysis of a chromosome-level assembly and resequencing of individuals across wide latitude distribution in the estuarine oyster (Crassostrea ariakensis) revealed unexpectedly low genomic diversity and population structures shaped by historical glaciation, geological events and oceanographic forces. Strong selection signals were detected in genes responding to temperature and salinity stress, especially of the expanded solute carrier families, highlighting the significance of gene expansion in environmental adaptation. Genes exhibiting high plasticity showed strong selection in upstream regulatory regions that modulate transcription, indicating selection favoring plasticity. Our findings suggest that genomic variation and population structure in marine bivalves are heavily influenced by climate history and physical forces, and gene expansion and selection may enhance phenotypic plasticity that is critical for the adaptation to rapidly changing environments.

evolutionary biology↗

bioRxiv2021

Homo-harringtonine (HHT) - A highly effective drug against coronaviruses and the potential for large-scale clinical applications

In the search for treatment schemes of COVID-19, we start by examining the general weakness of coronaviruses and then identify approved drugs attacking that weakness. The approach, if successful, should identify drugs with a specific mechanism that is at least as effective as the best drugs proposed and are ready for clinical trials. All coronaviruses translate their non-structural proteins ([~]16) in concatenation, resulting in a very large super-protein. Homo-harringtonine (HHT), which has been approved for the treatment of leukemia, blocks protein elongation very effectively. Hence, HHT can repress the replication of many coronaviruses at the nano-molar concentration. In two mouse models, HHT clears SARS-CoV-2 in 3 days, especially by nasal dripping of 40 ug per day. We also use dogs to confirm the safety of HHT delivered by nebulization. The nebulization scheme could be ready for large-scale applications at the onset of the next epidemics. For the current COVID-19, a clinical trial has been approved by the Ditan hospital of Beijing but could not be implemented for want of patients. The protocol is available to qualified medical facilities.

microbiology↗

bioRxiv2021

Personalized genome assembly for accurate cancer somatic mutation discovery using cancer-normal paired reference samples

The use of personalized genome assembly as a reference for detecting the full spectrum of somatic events from cancers has long been advocated but never been systematically investigated. Here we address the critical need of assessing the accuracy of somatic mutation detection using personalized genome assembly versus the standard human reference assembly (i.e. GRCh38). We first obtained massive whole genome sequencing data using multiple sequencing technologies, and then performed de novo assembly of the first tumor-normal paired genomes, both nuclear and mitochondrial, derived from the same donor with triple negative breast cancer. Compared to standard human reference assembly, the haplotype phased chromosomal-scale personalized genome was best demonstrated with individual specific haplotypes for some complex regions and medical relevant genes. We then used this well-assembled personalized genome as a reference for read mapping and somatic variant discovery. We showed that the personalized genome assembly results in better alignments of sequencing reads and more accurate somatic mutation calls. Direct comparison of mitochondrial genomes led to discovery of unreported nonsynonymous somatic mutations. Our findings provided a unique resource and proved the necessity of personalized genome assembly as a reference in improving somatic mutation detection at personal genome level not only for breast cancer reference samples, but also potentially for other cancers.

bioinformatics↗

bioRxiv2021

Genome-wide CRISPR activation screen identifies novel receptors for SARS-CoV-2 entry

The ongoing pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been endangering worldwide public health and economy. SARS-CoV-2 infects a variety of tissues where the known receptor ACE2 is low or almost absent, suggesting the existence of alternative pathways for virus entry. Here, we performed a genome-wide barcoded-CRISPRa screen to identify novel host factors that enable SARS-CoV-2 infection. In addition to known host proteins, i.e. ACE2, TMPRSS2 and NRP1, we identified multiple host components, among which LDLRAD3, TMEM30A and CLEC4G were confirmed as functional receptors for SARS-CoV-2. All these membrane proteins bind directly to spikes N-terminal domain (NTD). Their essential and physiological roles have all been confirmed in either neuron or liver cells. In particular, LDLRAD3 and CLEC4G mediate SARS-CoV-2 entry and infection in a fashion independent of ACE2. The identification of the novel receptors and entry mechanisms could advance our understanding of the multiorgan tropism of SARS-CoV-2, and may shed light on the development of the therapeutic countermeasures against COVID-19.

microbiology↗

bioRxiv2021

A meta-analysis of Microarray Data is Effective for Identifying Gravity-Sensitive Genes

Gravity affects the function and maintenance of organs, such as bones, muscles, and the heart. Several studies have used DNA microarrays to identify genes with altered expressions in response to gravity. However, it is technically challenging to combine the results from various microarray datasets because of their different data structures. We hypothesized it is possible to identify common changes in gene expression from the DNA microarray datasets obtained under various conditions and methods. In this study, we grouped homologous genes to perform a meta-analysis of multiple vascular endothelial cell and skeletal muscle datasets. According to the t-distributed stochastic neighbor embedding (t-SNE) analysis, the changes in the gene expression pattern in vascular endothelial cells formed specific clusters. We also identified candidate genes in endothelial cells that responded to gravity. Further, we exposed human umbilical vein endothelial cells to simulated microgravity using a clinostat and measured the expression levels of the candidate genes. Gene expression analysis using qRT-PCR revealed that the expression level of the prostaglandin transporter gene SLCO2A1 decreased in response to microgravity, consistent with the meta-analysis of microarray datasets. Furthermore, the direction of gravity affected the expression level of SLCO2A1, buttressing the finding that its expression was affected by gravity. These results suggest that a meta-analysis of DNA microarray datasets may help identify new target genes previously overlooked in individual microarray analyses.

cell biology↗

bioRxiv2021

Bayesian metamodeling of complex biological systems across varying representations

Comprehensive modeling of a whole cell requires an integration of vast amounts of information on various aspects of the cell and its parts. To divide-and-conquer this task, we introduce Bayesian metamodeling, a general approach to modeling complex systems by integrating a collection of heterogeneous input models. Each input model can in principle be based on any type of data and can describe a different aspect of the modeled system using any mathematical representation, scale, and level of granularity. These input models are (i) converted to a standardized statistical representation relying on Probabilistic Graphical Models, (ii) coupled by modeling their mutual relations with the physical world, and (iii) finally harmonized with respect to each other. To illustrate Bayesian metamodeling, we provide a proof-of-principle metamodel of glucose-stimulated insulin secretion by human pancreatic {beta}-cells. The input models include a coarse-grained spatiotemporal simulation of insulin vesicle trafficking, docking, and exocytosis; a molecular network model of glucose-stimulated insulin secretion signaling; a network model of insulin metabolism; a structural model of glucagon-like peptide-1 receptor activation; a linear model of a pancreatic cell population; and ordinary differential equations for systemic postprandial insulin response. Metamodeling benefits from decentralized computing, while often producing a more accurate, precise, and complete model that contextualizes input models as well as resolves conflicting information. We anticipate Bayesian metamodeling will facilitate collaborative science by providing a framework for sharing expertise, resources, data, and models, as exemplified by the Pancreatic {beta}-Cell Consortium. Significance StatementCells are the basic units of life, yet their architecture and function remain to be fully characterized. This work describes Bayesian metamodeling, a modeling approach that divides-and-conquers a large problem of modeling numerous aspects of the cell into computing a number of smaller models of different types, followed by assembling these models into a complete map of the cell. Metamodeling enables a facile collaboration of multiple research groups and communities, thus maximizing the sharing of expertise, resources, data, and models. A proof-of-principle is provided by a model of glucose-stimulated insulin secretion produced by the Pancreatic {beta}-Cell Consortium.

cell biology↗

bioRxiv2021

Sex disparities in influenza: a multiscale network analysis

Sex differences in the pathogenesis of infectious diseases due to differential immune responses between females and males have been well documented for multiple pathogens. However, the molecular mechanism underlying the observed sex differences in influenza virus infection remains poorly understood. In this study, we used a network-based approach to characterize the blood transcriptome collected over the course of infection with influenza A virus from female and male ferrets to dissect sex-biased gene expression. We identified significant differences in the temporal dynamics and regulation of immune responses between females and males. Our results elucidate sex-differentiated pathways involved in the unfolded protein response (UPR), lipid metabolism, and inflammatory responses, including a female-biased IRE1/XBP1 activation and male-biased crosstalk between metabolic reprogramming and IL-1 and AP-1 pathways. Overall, our study provides molecular insights into sex differences in transcriptional regulation of immune responses and contributes to a better understanding of sex bias in influenza pathogenesis.

systems biology↗

bioRxiv2021

High resolution ultrasonic neural modulation observedvia in vivo two-photon calcium imaging

Neural modulation plays a major role in delineating the circuit mechanisms and serves as the cornerstone of neural interface technologies. Among the various modulation mechanisms, ultrasound enables noninvasive label-free deep access to mammalian brain tissue. To date, most if not all ultrasonic neural modulation implementations are based on [~]1 MHz carrier frequency. The long acoustic wavelength results in a spatially coarse modulation zone, often spanning over multiple function regions. The modulation of one brain region is inevitably linked with the modulation of its neighboring regions. To significantly increase the spatial resolution, we explored the application of high-frequency ultrasound. To investigate the neuronal response at cellular resolutions, we developed a dual-modality system combining in vivo two-photon calcium imaging and focused ultrasound modulation. The studies show that the [~]30 MHz ultrasound can suppress the neuronal activity in awake mice at 100-micron scale spatial resolutions, paving the way for high-resolution ultrasonic neural modulation.

bioengineering↗