Biology subjects

Sun, N.

Publications and source records attributed to Sun, N..

72 records · Page 4Linked to original sources

bioRxiv2020

Magnetic Temporal Interference For Noninvasive, High-resolution, and Localized Deep Brain Stimulation: Concept Validation

Non-invasive deep brain stimulation has been a major challenge in the field of neuroscience and brain stimulation in the past three decades. Current brain stimulation technologies suffer from such hurdles as the inability to do deep brain stimulation, poor spatial resolution, and invasiveness. Transcranial magnetic stimulation (TMS) technique, for instance, cannot target brain regions deeper than [~]2cm and has a poor spatial resolution, impacting a large area of the peripheral region and leading to various side effects. Implantable electrodes, even though effective for deep brain stimulation, are invasive and carry various drawbacks related to the surgery and site infection. In this paper, we propose a new concept that relies on temporal interference of two high- frequency magnetic fields generated by two electromagnetic coils. The neural system does not respond to each of these high-frequency magnetic fields alone because of the intrinsic low-pass filtering properties of the neural membrane. The peripheral areas of the brain are impacted only by the high-frequency magnetic fields that cannot stimulate the nerves, while the deep brain area where the two fields interfere experiences a magnetic field that contains a low-frequency envelope and therefore the nerves can be stimulated. This technique can noninvasively focus a magnetic or electric beam at any depth inside the brain with a high resolution, without impacting the peripheral regions.

bioengineering↗

bioRxiv2020

Berberine reverses multidrug resistance in Candida albicans by hijacking the drug efflux pump Mdr1p

Clinical use of antimicrobials faces great challenges from the emergence of multidrug resistant (MDR) pathogens. The overexpression of drug efflux pumps is one of the major contributors to MDR. It is considered as a promising approach to overcome MDR by reversing the function of drug efflux pumps. In the life-threatening fungal pathogen Candida albicans, the major facilitator superfamily (MFS) transporter Mdr1p can excrete many structurally unrelated antifungals, leading to multidrug resistance. Here we report a counterintuitive case of reversing multidrug resistance in C. albicans by using a natural product berberine to hijack the overexpressed Mdr1p for its own importation. Moreover, we illustrate that the imported berberine accumulates in mitochondria, and compromises the mitochondrial function by impairing mitochondrial membrane potential and mitochondrial Complex I. It results in the selective elimination of Mdr1p overexpressed C. albicans cells. Furthermore, we show that berberine treatment can prolong the mean survival time (MST) of mice with a blood-borne dissemination of Mdr1p overexpressed multidrug resistant candidiasis. This study provided a potential direction of novel anti-MDR drug discovery by screening for multidrug efflux pump converters.

microbiology↗

bioRxiv2020

Ultra-compact Dual-band Smart NEMS Magnetoelectric Antennas for Simultaneous Wireless Energy Harvesting and Magnetic Field Sensing

Ultra-compact wireless implantable medical devices (IMDs) are in great demand for healthcare applications, in particular for neural recording and stimulation. Current implantable technologies based on miniaturized micro-coils suffer from low wireless power transfer efficiency (PTE) and are not always compliant with the specific absorption rate imposed by the Federal Communications Commission, particularly for deep brain implantation where field attenuation and tissue loss are significant. Moreover, current implantable devices are reliant on recordings of voltage or current. This has two major weaknesses: 1) the necessary direct contact between electrode and tissue degrades over time due to electrochemical fouling and tissue reactions, and 2) the necessity for differential recordings across space. Here, we report, for the first time, an ultra-compact dual-band smart nanoelectromechanical systems magnetoelectric (ME) antenna with a size of 250×174 µm2 that can efficiently perform wireless energy harvesting and sense ultra-small magnetic fields such as those arising from neural activities. The proposed smart ME antenna has a wireless PTE 1∼2 orders of magnitude higher than any other reported miniaturized micro-coil, allowing the wireless IMDs to be compliant with the specific absorption rate (SAR) limit and to operate under safe exposure of radio frequency energy. Furthermore, the magnetic sensing capability of the proposed smart ME antenna, with a limit of detection of 300∼500pT at > 200Hz, should allow the IMDs to record neural magnetic fields from the brain without requiring differential recording.Competing Interest StatementThe authors have declared no competing interest.View Full Text

bioengineering↗

bioRxiv2020

Conserved Roles for Receptor Tyrosine Kinase Extracellular Regions in Regulating Receptor and Pathway Activity

Receptor Tyrosine Kinases (RTKs) comprise a diverse group of cell-surface receptors that mediate key signaling events during animal development and are frequently activated in cancer. Ligand-induced dimerization is the canonical mechanism by which RTKs are thought to be activated. We show here that deletion of the extracellular regions of 10 RTKs representing 7 RTK classes or their substitution with the dimeric immunoglobulin Fc region results in constitutive receptor phosphorylation but fails to result in phosphorylation of downstream signaling effectors Erk or Akt. Conversely, substitution of RTK extracellular regions with the extracellular region of the Epidermal Growth Factor Receptor (EGFR) results in increases in Erk and/or Akt phosphorylation in response to EGF. These results indicate that the activation signal generated by the EGFR extracellular region is capable of activating at least 7 different RTK classes. Failure of phosphorylated Fc-RTK chimeras to stimulate phosphorylation of downstream effectors indicates that either dimerization and receptor phosphorylation per se are insufficient to activate signaling or constitutive dimerization leads to pathway inhibition.

molecular biology↗

bioRxiv2020

B1 and B2 B cells are characterized by distinct CpG modification states at DNMT3A-maintained enhancers

We show that DNA methylation is a layered process in B lymphocytes. An underlying foundational methylome is stably established during B lineage commitment and overlaid with a DNMT3A-maintained dynamic methylome which is sculpted in distinct ways in B1 and B2 B cells during B cell development. An engineered loss of DNMT3A after commitment to the B lineage unmasks a foundational methylome that is shared in both B1 and B2 sub-lineages. The dynamic methylome is comprised of novel enhancers whose methylation state is maintained by DNMT3A but can be modulated in strikingly different ways in B1 and B2 B cells. During B1 B cell development, the dynamic methylome undergoes a prominent programmed demethylation event that is not observed during B2 B cell development. The methylation pattern of the dynamic methylome is determined by the coincident recruitment of DNMT3A and TET enzymes and it regulates the developmental expression of B1 and B2 lineage-specific genes.

immunology↗

bioRxiv2020

Measuring genetic variation in the multi-ethnic Million Veteran Program (MVP)

The Million Veteran Program (MVP), initiated by the Department of Veterans Affairs (VA), aims to collect consented biosamples from at least one million Veterans. Presently, blood samples have been collected from over 800,000 enrolled participants. The size and diversity of the MVP cohort, as well as the availability of extensive VA electronic health records make it a promising resource for precision medicine. MVP is conducting array-based genotyping to provide genome-wide scan of the entire cohort, in parallel with whole genome sequencing, methylation, and other omics assays. Here, we present the design and performance of MVP 1.0 custom Axiom(R) array, which was designed and developed as a single assay to be used across the multi-ethnic MVP cohort. A unified genetic quality control analysis was developed and conducted on an initial tranche of 485,856 individuals leading to a high-quality dataset of 459,777 unique individuals. 668,418 genetic markers passed quality control and showed high quality genotypes not only on common variants but also on rare variants. We confirmed the substantial ancestral diversity of MVP with nearly 30% non-European individuals, surpassing other large biobanks. We also demonstrated the quality of the MVP dataset by replicating established genetic associations with height in European Americans and African Americans ancestries. This current data set has been made available to approved MVP researchers for genome-wide association studies and other downstream analyses. Further data releases will be available for analysis as recruitment at the VA continues and the cohort expands both in size and diversity.

genetics↗

bioRxiv2019

Reconciling Dimensional and Categorical Models of Autism Heterogeneity: a Brain Connectomics & Behavioral Study

BackgroundHeterogeneity in autism spectrum disorder (ASD) has hindered the development of biomarkers, thus motivating subtyping efforts. Most subtyping studies divide ASD individuals into non-overlapping (categorical) subgroups. However, continuous inter-individual variation in ASD suggests the need for a dimensional approach.\n\nMethodsA Bayesian model was employed to decompose resting-state functional connectivity (RSFC) of ASD individuals into multiple abnormal RSFC patterns, i.e., categorical subtypes henceforth referred to as \"factors\". Importantly, the model allowed each individual to express one or more factors to varying degrees (dimensional subtyping). The model was applied to 306 ASD individuals (age 5.2-57 years) from two multisite repositories. Posthoc analyses associated factors with symptoms and demographics.\n\nResultsAnalyses yielded three factors with dissociable whole-brain hypo/hyper RSFC patterns. Most participants expressed multiple (categorical) factors, suggestive of a mosaic of subtypes within individuals. All factors shared abnormal RSFC involving the default network, but the directionality (hypo/hyper RSFC) differed across factors. Factor 1 was associated with core ASD symptoms, while factor 2 was associated with comorbid symptoms. Older males preferentially expressed factor 3. Factors were robust across multiple control analyses and not associated with IQ, nor head motion.\n\nConclusionsThere exist at least three ASD factors with dissociable patterns of whole-brain RSFC, behaviors and demographics. Heterogeneous default network hypo/hyper RSFC across the factors might explain previously reported inconsistencies. The factors differentiated between core ASD and comorbid symptoms - a less appreciated domain of heterogeneity in ASD. These factors are co-expressed in ASD individuals with different degrees, thus reconciling categorical and dimensional perspectives of ASD heterogeneity.

neuroscience↗

bioRxiv2019

Data-driven detection of latent atrophy factors related to phenotypical variants of posterior cortical atrophy

Posterior cortical atrophy is a clinical-radiological syndrome characterized by visual processing deficits and atrophy in posterior parts of the brain, most often caused by Alzheimers disease pathology. Recent consensus criteria describe four distinct phenotypical variants of posterior cortical atrophy defined by clinical and radiological features; i) object perception/occipitotemporal (ventral), ii) space perception/temporoparietal (dorsal), iii) non-visual/dominant parietal and iv) primary visual (caudal). We employed a data-driven approach to identify atrophy factors related to these proposed variants in a multi-center cohort of 119 individuals with posterior cortical atrophy (age: 64 SD 7, 38% male, MMSE: 21 SD 5, 71% amyloid-{beta} positive, 29% amyloid-{beta} status unknown). A Bayesian modelling framework based on latent Dirichlet allocation was used to compute four latent atrophy factors in accordance with the four proposed variants. The model uses standardized gray matter density images as input (adjusted for age, sex, intracranial volume, field strength and whole-brain gray matter volume) and provides voxelwise probabilistic maps for all atrophy factors, allowing every individual to express each factor to a degree without a priori classification. The model revealed four distinct yet partially overlapping atrophy factors; right-dorsal, right-ventral, left-ventral, and limbic. Individual participant profiles revealed that the vast majority of participants expressed multiple factors, rather than predominantly expressing a single factor. To assess the relationship between atrophy factors and cognition, neuropsychological test scores covering four posterior cortical atrophy-specific cognitive domains were assessed (object perception, space perception, non-visual parietal functions and primary visual processing) and we used general linear models to examine the association between atrophy factor expression and cognition. We found that object perception and primary visual processing were associated with atrophy that predominantly reflects the right-ventral factor. Furthermore, space perception was associated with atrophy that predominantly represents the right-ventral and right-dorsal factors. Similar to the atrophy factors, most participants had mixed clinical profiles with impairments across multiple domains. However, when selecting four participants with an isolated impairment, we observed atrophy patterns and factor expressions that were largely in accordance with the hypothesized variants. Taken together, our results indicate that variants of posterior cortical atrophy exist but these constitute phenotypical extremes and most individuals fall along a broad clinical-radiological spectrum, indicating that classification into four mutually exclusive variants is unlikely to be clinically useful.

neuroscience↗

bioRxiv2019

Somatosensory-Motor Dysconnectivity Spans Multiple Transdiagnostic Dimensions of Psychopathology

BackgroundThere is considerable interest in a dimensional transdiagnostic approach to psychiatry. Most transdiagnostic studies have derived factors based only on clinical symptoms, which might miss possible links between psychopathology, cognitive processes and personality traits. Furthermore, many psychiatric studies focus on higher-order association brain networks, thus neglecting the potential influence of huge swaths of the brain.\n\nMethodsA multivariate data-driven approach (partial least squares; PLS) was utilized to identify latent components linking a large set of clinical, cognitive and personality measures to whole-brain resting-state functional connectivity (RSFC) patterns across 224 participants. The participants were either healthy (N=110) or diagnosed with bipolar disorder (N=40), attention-deficit/hyperactivity disorder (N=37), schizophrenia (N=29) or schizoaffective disorder (N=8). In contrast to traditional case-control analyses, the diagnostic categories were not utilized in the PLS analysis, but were helpful for interpreting the components.\n\nResultsOur analyses revealed three latent components corresponding to general psychopathology, cognitive dysfunction and impulsivity. Each component was associated with a unique whole-brain RSFC signature and shared across all participants. The components were robust across multiple control analyses and replicated using independent task functional magnetic resonance imaging data from the same participants. Strikingly, all three components featured connectivity alterations within the somatosensory-motor network, and its connectivity with subcortical structures and cortical executive networks.\n\nConclusionsWe identified three distinct dimensions with dissociable (but overlapping) whole-brain RSFC signatures across healthy individuals and individuals with psychiatric illness, providing potential intermediate phenotypes that span across diagnostic categories. Our results suggest expanding the focus of psychiatric neuroscience beyond higher-order brain networks.

neuroscience↗

bioRxiv2019

Validation of a CRISPR/cas9-based technology platform for examining specific immune gene functions in an experimental murine model of IBD

Inflammatory bowel diseases (IBD) are complex, multifactorial disorders characterized by chronic relapsing intestinal inflammation. Association studies have identified hundreds of genes that are linked to IBD and potentially regulate its pathology. The further dissection of the genetic network underlining IBD pathogenesis and pathophysiology is hindered by the limited capacity to investigate the role of each GWAS association through functional studies, including the generation of knockout animal models for each of the associated genes. The CRISPR/Cas9 system represents a cutting edge technology which has the potential to transform the field of IBD research by facilitating the introduction of genetic alterations in an efficient and effective manner. Using the CD40-mediated-colitis model, our results demonstrate the validity of a CRISPR/Cas9-based platform as a tool for the validation of target genes or interference strategies in experimental IBD. The utilization of this discovery strategy will allow for the timely in vivo validation of therapeutic targets as the rapidly emerge from current genetic and genomics efforts with human disease tissue. As such, the CRISPR/Cas9-based platform can significantly shorten the time span between target identification and generation of proof of principle experiments for drug discovery.

immunology↗

bioRxiv2019

VHL Synthetic Lethality Signatures Uncovered by Genotype-specific CRISPR-Cas9 Screens

BackgroundGenome-wide CRISPR-Cas9 essentiality screening represents a powerful approach to identify genetic vulnerabilities in cancer cells. Here, we applied this technology and designed a strategy to identify target genes that are synthetic lethal (SL) with von Hippel-Lindau (VHL) tumor suppressor gene. Inactivation of VHL has been frequently found in clear cell renal cell carcinoma (ccRCC). Its SL partners serve as potential drug targets for the development of targeted cancer therapies.\n\nResultsWe performed parallel genome-wide CRISPR screens in two pairs of isogenic ccRCC cell lines that differ only in the VHL status. Comparative analyses of screening results not only confirmed a well-known role for mTOR signaling in renal carcinoma, but also identified DNA damage response and selenocysteine biosynthesis pathways as major SL targets in VHL-inactivated cancer cells. Follow-up studies provided cellular and mechanistic insights into SL interactions of these pathway genes with the VHL gene.\n\nConclusionsUsing isogenic CRISPR screening approach, we uncovered novel biological processes that are SL with VHL, which can be exploited for drug development for ccRCC. Our CRISPR and RNA-seq datasets provide a rich resource for future investigation of the function of the VHL tumor suppressor protein. Our work demonstrates the efficiency of CRISPR-based synthetic lethality screening in human isogenic cell pairs. Similar strategies could be employed to unveil SL partners with other oncogenic drivers.

cancer biology↗

bioRxiv2019

Global Signal Regression Strengthens Association between Resting-State Functional Connectivity and Behavior

Global signal regression (GSR) is one of the most debated preprocessing strategies for resting-state functional MRI. GSR effectively removes global artifacts driven by motion and respiration, but also discards globally distributed neural information and introduces negative correlations between certain brain regions. The vast majority of previous studies have focused on the effectiveness of GSR in removing imaging artifacts, as well as its potential biases. Given the growing interest in functional connectivity fingerprinting, here we considered the utilitarian question of whether GSR strengthens or weakens associations between resting-state functional connectivity (RSFC) and multiple behavioral measures across cognition, personality and emotion. By applying the variance component model to the Brain Genomics Superstruct Project (GSP), we found that behavioral variance explained by whole-brain RSFC increased by an average of 47% across 23 behavioral measures after GSR. In the Human Connectome Project (HCP), we found that behavioral variance explained by whole-brain RSFC increased by an average of 40% across 58 behavioral measures, when GSR was applied after ICA-FIX de-noising. To ensure generalizability, we repeated our analyses using kernel regression. GSR improved behavioral prediction accuracies by an average of 64% and 12% in the GSP and HCP datasets respectively. Importantly, the results were consistent across methods. A behavioral measure with greater RSFC-explained variance (using the variance component model) also exhibited greater prediction accuracy (using kernel regression). A behavioral measure with greater improvement in behavioral variance explained after GSR (using the variance component model) also enjoyed greater improvement in prediction accuracy after GSR (using kernel regression). Furthermore, GSR appeared to benefit task performance measures more than self-reported measures. Since GSR was more effective at removing motion-related and respiratory-related artifacts, GSR-related increases in variance explained and prediction accuracies were unlikely the result of motion-related or respiratory-related artifacts. However, it is worth emphasizing that the current study focused on whole-brain RSFC, so it remains unclear whether GSR improves RSFC-behavioral associations for specific connections or networks. Overall, our results suggest that at least in the case for young healthy adults, GSR strengthens the associations between RSFC and most (although not all) behavioral measures. Code for the variance component model and ridge regression can be found here: https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/preprocessing/Li2019_GSR. HighlightsO_LIGlobal signal regression improves RSFC-behavior associations C_LIO_LIGlobal signal regression improves RSFC-based behavioral prediction accuracies C_LIO_LIImprovements replicated across two large-scale datasets and methods C_LIO_LITask-performance measures enjoyed greater improvements than self-reported ones C_LIO_LIGSR beneficial even after ICA-FIX C_LI

neuroscience↗

bioRxiv2018

Multi-modal Latent Factor Exploration of Atrophy, Cognitive and Tau Heterogeneity in Typical Late-Onset Alzheimer’s Disease

Individuals with Alzheimers disease (AD) dementia exhibit significant heterogeneity across clinical symptoms, atrophy patterns, and spatial distribution of Tau deposition. Most previous studies of AD heterogeneity have focused on atypical clinical subtypes, defined subtypes with a single modality, or restricted their analyses to a priori brain regions and cognitive tests. Here, we considered a data-driven hierarchical Bayesian model to identify latent factors from atrophy patterns and cognitive deficits simultaneously, thus exploiting the rich dimensionality within each modality. Unlike most previous studies, our model allows each factor to be expressed to varying degrees within an individual, in order to reflect potential multiple co-existing pathologies.\n\nBy applying our model to ADNI-GO/2 AD dementia participants, we found three atrophy-cognitive factors. The first factor was associated with medial temporal lobe atrophy, episodic memory deficits and disorientation to time/place (\"MTL-Memory\"). The second factor was associated with lateral temporal atrophy and language deficits (\"Lateral Temporal-Language\"). The third factor was associated with atrophy in posterior bilateral cortex, and visuospatial executive function deficits (\"Posterior Cortical-Executive\"). While the MTL-Memory and Posterior Cortical-Executive factors were discussed in previous literature, the Lateral Temporal-Language factor is novel and emerged only by considering atrophy and cognition jointly. Several analyses were performed to ensure generalizability, replicability and stability of the estimated factors. First, the factors generalized to new participants within a 10-fold cross-validation of ADNI-GO/2 AD dementia participants. Second, the factors were replicated in an independent ADNI-1 AD dementia cohort. Third, factor loadings of ADNI-GO/2 AD dementia participants were longitudinally stable, suggesting that these factors capture heterogeneity across patients, rather than longitudinal disease progression. Fourth, the model outperformed canonical correlation analysis at capturing associations between atrophy patterns and cognitive deficits.\n\nTo explore the influence of the factors early in the disease process, factor loadings were estimated in ADNI-GO/2 mild cognitively impaired (MCI) participants. Although the associations between the atrophy patterns and cognitive profiles were weak in MCI compared to AD, we found that factor loadings were associated with inter-individual regional variation in Tau uptake. Taken together, these results suggest that distinct atrophy-cognitive patterns exist in typical Alzheimers disease, and are associated with distinct patterns of Tau depositions before clinical dementia emerges.\n\nHighlightsO_LIBayesian model reveals 3 atrophy-cognitive factors in typical AD from ADNI-GO/2\nC_LIO_LIReplicated in independent ADNI-1 cohort; longitudinally stable within individuals\nC_LIO_LITriple cognitive dissociations among atrophy patterns suggest subtypes, not stages\nC_LIO_LIOutperforms canonical correlation analysis\nC_LIO_LIFactor loadings associated with spatial patterns of Tau uptake in MCI\nC_LI

neuroscience↗

bioRxiv2018

The rat medial prefrontal cortex exhibits flexible neural activity states during the performance of an odor span task

Medial prefrontal cortex (mPFC) activity is fundamental for working memory (WM), attention, and behavioral inhibition; however, a comprehensive understanding of the neural computations underlying these processes is still forthcoming. Towards this goal, neural recordings were obtained from the mPFC of awake, behaving rats performing an odor span task of WM capacity. Neural populations were observed to encode distinct task epochs and the transitions between epochs were accompanied by abrupt shifts in neural activity patterns. Putative pyramidal neuron activity increased significantly earlier in the delay for sessions where rats achieved higher spans. Furthermore, increased putative interneuron activity was only observed at the termination of the delay thus indicating that local processing in inhibitory networks was a unique feature to initiate foraging. During foraging, changes in neural activity patterns associated with the approach to a novel odor, but not familiar odors, were robust. Collectively, these data suggest that distinct mPFC activity states underlie the delay, foraging, and reward epochs of the odor span task. Transitions between these states enable successful performance in dynamic environments placing strong demands on the substrates of working memory.

neuroscience↗

bioRxiv2018

Circadian gene Clock regulates mitochondrial morphology and functions by posttranscriptional way

Many daily activities are under the control of circadian clock, including nutrition metabolism and energy generation. Mitochondria, as the core factories of oxidizing substrates and producing ATP, undergo changes in quantity and morphology to adapt to the demand for energy. It has been demonstrated that mitochondrial gene expression, dynamics and functions are all affected by circadian clock. Here, we demonstrated that circadian gene Clock affects the number, architecture and function of mitochondria via posttranscriptional regulation of Drp1. Clock{Delta}19 leads to fragmented mitochondria accompanied with the loss of membrane potential, excessive ROS accumulation and decreased mitochondrial respiration and ATP generation. Clock{Delta}19 mice exhibit disordered lipid metabolism and evident nonalcoholic fatty liver disease (NAFLD), which are rescued by treatment with the mitochondrial fission inhibitor Mdivi-1. These results suggest a strong relationship between Clock, mitochondrial dynamics and metabolic diseases and provide a new perspective on disordered circadian clock and related diseases.

cell biology↗

bioRxiv2017

Controlling for Intra-Subject and Inter-Subject Variability in Individual-Specific Cortical Network Parcellations

Resting-state functional magnetic resonance imaging (rs-fMRI) offers the opportunity to delineate individual-specific brain networks. A major question is whether individual-specific network topography (i.e., location and spatial arrangement) is behaviorally relevant. Here, we propose a multi-session hierarchical Bayesian model (MS-HBM) for estimating individual-specific cortical networks and investigate whether individual-specific network topography can predict human behavior. The multiple layers of the MS-HBM explicitly differentiate intra-subject (within-subject) from inter-subject (between-subject) network variability. By ignoring intra-subject variability, previous network mappings might confuse intra-subject variability for inter-subject differences. Compared with other approaches, MS-HBM parcellations generalized better to new rs-fMRI and task-fMRI data from the same subjects. More specifically, MS-HBM parcellations estimated from a single rs-fMRI session (10 minutes) showed comparable generalizability as parcellations estimated by two state-of-the-art methods using five sessions (50 minutes). We also showed that behavioral phenotypes across cognition, personality and emotion could be predicted by individual-specific network topography with modest accuracy, comparable to previous reports predicting phenotypes based on connectivity strength. Network topography estimated by MS-HBM was more effective for behavioral prediction than network size, as well as network topography estimated by other parcellation approaches. Thus, similar to connectivity strength, individual-specific network topography might also serve as a fingerprint of human behavior.

neuroscience↗

bioRxiv2017

Akt/PKB enhances non-canonical Wnt signals by compartmentalizing β-Catenin

Cellular proliferation is antagonistically regulated by canonical and non-canonical Wnt signals; their dysbalance triggers cancers. It is widely believed that the PI3-K[->] Akt pathway enhances canonical Wnt signals by affecting transcriptional activity and stability of {beta}-catenin. Here we demonstrate that the PI3-K[->]Akt pathway also enhances non-canonical Wnt signals by compartmentalizing {beta}-catenin. By phosphorylating the phosphoinositide(PI)-binding domain of a multimodular signal transducer, Daple, Akt abolishes Daples ability to bind PI3-P-enriched endosomes that engage dynein motor complex for long-distance trafficking of {beta}-catenin/E-cadherin complexes to pericentriolar recycling endosomes (PCREs). Phosphorylation compartmentalizes Daple/{beta}-catenin/E-cadherin complexes to cell-cell contact sites, enhances non-canonical Wnt signals, and thereby, suppresses colony growth. Dephosphorylation compartmentalizes {beta}-catenin on PCREs, a specialized compartment for prolonged unopposed canonical Wnt signaling, and enhances colony growth. Cancer-associated Daple mutants that are insensitive to Akt mimic a constitutively dephosphorylated state. This work not only identifies Daple as a platform for crosstalk between Akt and the non-canonical Wnt pathway, but also reveals the impact of such crosstalk during cancer initiation and progression.

cell biology↗

bioRxiv2017

Convergence of Wnt, Growth Factor and Trimeric G protein signals on Daple

Cellular proliferation, differentiation, and morphogenesis are shaped by multiple signaling cascades; their concurrent dysregulation plays an integral role in cancer progression and is a common feature of many malignancies. Three such cascades that contribute to the oncogenic potential are the Wnt/Frizzled(FZD), growth factor-receptor tyrosine kinases (RTKs), and G-proteins/GPCRs. Here we identify Daple, a modulator of trimeric G-proteins and a Dishevelled (Dvl)-binding protein as an unexpected point of convergence for all three cascades. Daple-dependent activation of Gi and enhancement of non-canonical Wnt signals is not just triggered by Wnt5a/FZD to suppress tumorigenesis, but also hijacked by growth factor-RTKs to stoke tumor progression. Phosphorylation of Daple by both RTKs and non-RTKs triggers Gi activation and potentiates non-canonical Wnt signals that trigger epithelial-mesenchymal transition. In patients with colorectal cancers, concurrent upregulation of Daple and the prototype RTK, EGFR, carried poor prognosis. Thus, this work defines a novel growth factor{leftrightarrow}G-protein{leftrightarrow}Wnt crosstalk paradigm in cancer biology.

cancer biology↗