Biology subjects

Zheng, A.

Publications and source records attributed to Zheng, A..

47 records · Page 3Linked to original sources

bioRxiv2021

Using synthetic MR images for field map-less distortion correction

Functional MRI (fMRI) data acquired using echo-planar imaging (EPI) are highly distorted by magnetic field inhomogeneities. Distortion combined with underlying differences in image contrast between EPI and T1-weighted and T2-weighted (T1w/T2w) structural images makes the alignment of functional and anatomical images a challenge. Typically, separately acquired field map data are used to correct fMRI distortions and a flexible cost function insensitive to cross-modal differences in image contrast and intensity is used for aligning fMRI and anatomical images. The quality of alignment achieved with this approach can vary greatly and depends on the quality of field map data. In addition, many publicly available datasets lack field map data entirely. To address this issue, we developed Synth, a software package for distortion correction and cross-modal image registration that does not require separately acquired field map data. Synth combines information from T1w and T2w anatomical images to construct an idealized undistorted synthetic image that has similar contrast properties to fMRI data. The undistorted synthetic image then serves as an effective reference for individual-specific nonlinear unwarping to correct fMRI distortions. We demonstrate, in both pediatric (ABCD: Adolescent Brain Cognitive Development) and adult (MSC: Midnight Scan Club) data that Synth performs comparably well to other leading distortion correction approaches that utilize field map data, and often outperforms them. Field map-less distortion correction with Synth allows accurate and precise registration of fMRI data with missing or corrupted field map information.

neuroscience↗

bioRxiv2021

Precision Diffusion Imaging

Diffusion tensor imaging (DTI) aims to non-invasively characterize the anatomy and integrity of the brains white matter fibers. To establish individual-specific precision approaches for DTI, we defined its reliability and accuracy as a function of data quantity and analysis method, using both simulations and highly sampled individual-specific data (927-1442 diffusion weighted images [DWIs] per individual). DTI methods that allow for crossing fibers (BedpostX [BPX], Q-Ball Imaging [QBI]) estimated excess fibers when insufficient data was present and when the data did not match the model priors. To reduce such overfitting, we developed a novel crossing-fiber diffusion imaging method, Bayesian Multi-tensor Model-selection (BaMM), that is designed for high-quality repeated sampling data sets. BaMM was robust to overfitting, showing high reliability and the relatively best crossing-fiber accuracy with increasing amounts of diffusion data. Thus, the choice of diffusion imaging analysis method is important for the success of individual-specific diffusion imaging. Importantly, for potential clinical applications of individual-specific precision DTI, such as deep brain stimulation (DBS), other forms of neuromodulation or neurosurgical planning, the data quantities required to achieve DTI reliability are lower than for functional MRI measures.

neuroscience↗

bioRxiv2020

HDLs extract lipophilic drugs from cells

High-density lipoproteins (HDLs) prevent cell death induced by a variety of cytotoxic drugs. The underlying mechanisms are however still poorly understood. Here we present evidence that HDLs efficiently protect cells against thapsigargin (a SERCA inhibitor) by extracting the drug from cells. Drug efflux could also be triggered to some extent by low-density lipoproteins (LDLs) and serum, which contains lipoproteins. HDLs did not reverse the non-lethal mild endoplasmic reticulum (ER) stress response induced by low thapsigargin concentrations or by SERCA knock-down but HDLs inhibited the toxic SERCA-independent effects mediated by high thapsigargin concentrations. HDLs were also found to extract other lipophilic compounds, such as the anti-diabetic drug glibenclamide. In contrast, hydrophilic substances (doxorubicin hydrochloride, rhodamine 123) were not extracted from cells by HDLs. This work shows that HDLs utilize their capacity of loading themselves with lipophilic compounds, akin to their ability to extract cellular cholesterol, to reduce the cell content of hydrophobic drugs. Silencing of the P-glycoprotein/ABCB1 transporter reduced the capacity of cells to load thapsigargin on HDLs. This work suggests that HDL-mediated cell efflux of toxic lipophilic xenobiotic is beneficial but also that HDL-mediated efflux can be detrimental to the therapeutic benefit of lipophilic drugs such as glibenclamide. Lipoprotein-mediated drug efflux should therefore be considered when evaluating drug efficacy.

cell biology↗

bioRxiv2020

Parallel Hippocampal-Parietal Circuits for Self- and Goal-oriented Processing

The hippocampus is critically important for a diverse range of cognitive processes, such as episodic memory, prospective memory, affective processing, and spatial navigation. The human hippocampus has been thought of as being solely functionally connected to a set of neocortical regions known as the default mode network (DMN), which supports self-referential cognition. Using individual-specific precision functional mapping of resting state fMRI data, we found the anterior hippocampus (head and body) to be preferentially connected to the DMN as expected. The hippocampal tail, however, was strongly preferentially connected to the parietal memory network (PMN), which supports goal-oriented cognition and stimulus recognition. This resting state functional connectivity (RSFC) anterior-posterior dichotomy was well-matched by differences in task deactivations and anatomical segmentations of the hippocampus. Task deactivations were localized to the head and body of the hippocampus (DMN), relatively sparing the tail (PMN). Anterior and posterior hippocampal connectivity was network-specific even though the DMN and PMN are interdigitated in medial parietal cortex. The functional dichotomization of the hippocampus into anterior DMN-connected and posterior PMN-connected parcels suggests parallel, but distinct circuits between the hippocampus and medial parietal cortex for self vs. goal-oriented processing.

neuroscience↗

bioRxiv2020

Mechanisms underlying divergent responses of genetically distinct macrophages to IL-4

Mechanisms by which non-coding genetic variation influences gene expression remain only partially understood but are considered to be major determinants of phenotypic diversity and disease risk. Here, we evaluated effects of >50 million SNPs and InDels provided by five inbred strains of mice on the responses of macrophages to interleukin 4 (IL-4), a cytokine that plays pleiotropic roles in immunity and tissue homeostasis. Remarkably, of >600 genes induced >2-fold by IL-4 across the five strains, only 26 genes reached this threshold in all strains. By applying deep learning and motif mutation analyses to epigenetic data for macrophages from each strain, we identified the dominant combinations of lineage determining and signal-dependent transcription factors driving late enhancer activation. These studies further revealed mechanisms by which non-coding genetic variation influences absolute levels of enhancer activity and their dynamic responses to IL-4, thereby contributing to strain-differential patterns of gene expression and phenotypic diversity.

genomics↗

bioRxiv2020

Cingulo-Opercular Control Network Supports Disused Motor Circuits in Standby Mode

Whole-brain resting-state functional MRI (rs-fMRI) during two weeks of limb constraint revealed that disused motor regions became more strongly connected to the cingulo-opercular network (CON), an executive control network that includes regions of the dorsal anterior cingulate cortex (dACC) and insula (1). Disuse-driven increases in functional connectivity (FC) were specific to the CON and somatomotor networks and did not involve any other networks, such as the salience, frontoparietal, or default mode networks. Censoring and modeling analyses showed that FC increases during casting were mediated by large, spontaneous activity pulses that appeared in the disused motor regions and CON control regions. During limb constraint, disused motor circuits appear to enter a standby mode characterized by spontaneous activity pulses and strengthened connectivity to CON executive control regions. SignificanceMany studies have examined plasticity in the primary somatosensory and motor cortex during disuse, but little is known about how disuse impacts the brain outside of primary cortical areas. We leveraged the whole-brain coverage of resting-state functional MRI (rs-fMRI) to discover that disuse drives plasticity of distant executive control regions in the cingulo-opercular network (CON). Two complementary analyses, pulse censoring and pulse addition, demonstrated that increased functional connectivity between the CON and disused motor regions was driven by large, spontaneous pulses of activity in the CON and disused motor regions. These results point to a previously unknown role for the CON in supporting motor plasticity and reveal spontaneous activity pulses as a novel mechanism for reorganizing the brains functional connections.

neuroscience↗

bioRxiv2020

Towards Reproducible Brain-Wide Association Studies

Magnetic resonance imaging (MRI) continues to drive many important neuroscientific advances. However, progress in uncovering reproducible associations between individual differences in brain structure/function and behavioral phenotypes (e.g., cognition, mental health) may have been undermined by typical neuroimaging sample sizes (median N=25)1,2. Leveraging the Adolescent Brain Cognitive Development (ABCD) Study3 (N=11,878), we estimated the effect sizes and reproducibility of these brain-wide associations studies (BWAS) as a function of sample size. The very largest, replicable brain-wide associations for univariate and multivariate methods were r=0.14 and r=0.34, respectively. In smaller samples, typical for brain-wide association studies (BWAS), irreproducible, inflated effect sizes were ubiquitous, no matter the method (univariate, multivariate). Until sample sizes started to approach consortium-levels, BWAS were underpowered and statistical errors assured. Multiple factors contribute to replication failures4-6; here, we show that the pairing of small brain-behavioral phenotype effect sizes with sampling variability is a key element in wide-spread BWAS replication failure. Brain-behavioral phenotype associations stabilize and become more reproducible with sample sizes of N{gap}2,000. While investigator-initiated brain-behavior research continues to generate hypotheses and propel innovation, large consortia are needed to usher in a new era of reproducible human brain-wide association studies.

neuroscience↗

bioRxiv2020

Deep neural networks identify context-specific determinants of transcription factor binding affinity

Transcription factors (TFs) bind DNA by recognizing highly specific DNA sequence motifs, typically of length 6-12bp. A TF motif can occur tens of thousands of times in the human genome, but only a small fraction of those sites are actually bound. Despite the availability of genome-wide TF binding maps for hundreds of TFs, predicting whether a given motif occurrence is bound and identifying the influential context features remain challenging. Here we present a machine learning framework leveraging existing convolutional neural network architectures and state of the art model interpretation techniques to identify, visualize, and interpret context features most important for determining binding activity for a particular TF. We apply our framework to predict binding at motifs for 38 TFs in a lymphoblastoid cell line and achieve superior classification performance compared to existing frameworks. We compute importance scores for context regions at single base pair resolution and uncover known and novel determinants of TF binding. Finally, we demonstrate that important context bases are under increased purifying selection compared to nearby bases and are enriched in disease-associated variants identified by genome-wide association studies.

genomics↗

bioRxiv2019

Dynamic Palmitoylation Events Following T-Cell Receptor Signaling

Palmitoylation is the reversible addition of palmitate to cysteine via a thioester linkage. Following stimulation of the T-cell receptor we find a number of proteins are newly palmitoylated, including those involved in vesicle-mediated transport and Ras signal transduction. Among these stimulation-dependent palmitoylation targets are the v-SNARE VAMP7, important for docking of vesicular LAT during TCR signaling, and the largely undescribed palmitoyl acyltransferase DHHC18 that is expressed in two isoforms in T cells. Using our newly developed On-Plate Palmitoylation Assay (OPPA), we show DHHC18 is capable of palmitoylating VAMP7 at Cys183. Cellular imaging shows that the palmitoylation-deficient protein fails to be retained at the Golgi.

biochemistry↗

bioRxiv2019

A flexible simulation toolkit for designing and evaluating ChIP-sequencing experiments

A major challenge in evaluating quantitative ChIP-seq analyses, such as peak calling and differential binding, is a lack of reliable ground truth data. We present Tulip, a toolkit for rapidly simulating ChIP-seq data using statistical models of the experimental steps. Tulip may be used for a range of applications, including power analysis for experimental design, benchmarking of analysis tools, and modeling effects of processes such as replication on ChIP-seq signals.

genomics↗

bioRxiv2017

Building a genome browser with GIVE

Growing popularity and diversity of genomic data demands portable and versatile genome browsers. Here, we present an open source programming library, called GIVE that facilitates creation of personalized genome browsers without requiring a system administrator. By inserting HTML tags, one can add to a personal webpage interactive visualization of multiple types of genomics data, including genome annotation, \"linear\" quantitative data (wiggle), and genome interaction data. GIVE includes a graphical interface called HUG (HTML Universal Generator) that automatically generates HTML code for displaying user chosen data, which can be copy-pasted into users personal website or saved and shared with collaborators. The simplicity of use was enabled by encapsulation of novel data communication and visualization technologies, including new data structures, a memory management method, and a double layer display method. GIVE is available at: http://www.givengine.org/.

bioinformatics↗