Biology subjects

Ma, T.

Publications and source records attributed to Ma, T..

At least 73 records · Page 4Linked to original sources

bioRxiv2022

Perceptography: unveiling visual perceptual hallucinations induced by optogenetic stimulation of the inferior temporal cortex.

Neurons in the inferotemporal (IT) cortex respond selectively to complex visual features, implying their role in object perception. However, perception is subjective and cannot be read out from neural responses; thus, bridging the causal gap between neural activity and perception demands independent characterization of perception. Historically though, the complexity of the perceptual alterations induced by artificial stimulation of IT cortex has rendered them impossible to quantify. Here we addressed this old problem by combining machine learning with high-throughput behavioral optogenetics in macaque monkeys. In closed-loop experiments, we generated complex and highly specific images that the animal could not discriminate from the state of being cortically stimulated. These images, named "perceptograms" for the first time, reveal and depict the contents of the complex hallucinatory percepts induced by local neural perturbation in IT cortex. Furthermore, we found that the nature and magnitude of these hallucinations highly depend on concurrent visual input, stimulation location, and intensity. Objective characterization of stimulation-induced perceptual events opens the door to developing a mechanistic theory of visual perception. Further, it enables us to make better visual prosthetic devices and gain a greater understanding of visual hallucinations in mental disorders. One-Sentence SummaryCombining state-of-the-art AI with high-throughput closed-loop brain stimulation experiments, for the first time, we took "pictures" of the complex and subjective visual hallucinations induced by local stimulation in the inferior temporal cortex, a cortical area associated with object recognition.

neuroscience↗

bioRxiv2022

A vast space of compact strategies for highly efficient decisions

When foraging in dynamic and uncertain environments, animals can benefit from basing their decisions on smart inferences about hidden properties of the world. Typical theoretical approaches to understand the strategies that animals use in such settings combine Bayesian inference and value iteration to derive optimal behavioral policies that maximize total reward given changing beliefs about the environment. However, specifying these beliefs requires infinite numerical precision; with limited resources, this problem can no longer be separated into optimizing inference and optimizing action selections. To understand the space of behavioral policies in this constrained setting, we enumerate and evaluate all possible behavioral programs that can be constructed from just a handful of states. We show that only a small fraction of the top-performing programs can be constructed by approximating Bayesian inference; the remaining programs are structurally or even functionally distinct from Bayesian. To assess structural and functional relationships among all programs, we developed novel tree embedding algorithms; these embeddings, which are capable of extracting different relational structures within the program space, reveal that nearly all good programs are closely connected through single algorithmic "mutations". We demonstrate how one can use such relational structures to efficiently search for good solutions via an evolutionary algorithm. Moreover, these embeddings reveal that the diversity of non-Bayesian behaviors originates from a handful of key mutations that broaden the functional repertoire within the space of good programs. The fact that this diversity of behaviors does not significantly compromise performance suggests a novel approach for studying how these strategies generalize across tasks.

animal behavior and cognition↗

bioRxiv2022

The Hypoxia-regulated Ectonucleotidase CD73 is a Host Determinant of HIV Latency

Deciphering the mechanisms underlying viral persistence is critical to achieving a cure for HIV infection. We implemented a systems approach to discover molecular signatures of HIV latently-infected CD4+ T cells, identifying the immunosuppressive, adenosine-producing ectonucleotidase CD73 as a key surface marker of latent cells. Hypoxic conditioning, reflecting the lymphoid tissue microenvironment, increased the frequency of CD73+ CD4+ T cells and promoted HIV latency. Transcriptomic profiles of CD73+ CD4+ T cells favored viral quiescence, immune evasion, and cell survival. CD73+ CD4+ T cells were capable of harboring a functional HIV reservoir and reinitiating productive infection ex vivo. CD73 or adenosine receptor blockade facilitated latent HIV reactivation in vitro, mechanistically linking adenosine signaling to viral quiescence. Finally, tissue imaging of lymph nodes from HIV-infected individuals on antiretroviral therapy revealed spatial association between CD73 expression and HIV persistence in vivo. Our findings warrant development of HIV cure strategies targeting the hypoxia-CD73-adenosine axis.

microbiology↗

bioRxiv2022

Decoding functional cell-cell communication events by multi-view graph learning on spatial transcriptomics

Cell-cell communication events (CEs) are mediated by multiple ligand-receptor pairs. Usually only a particular subset of CEs directly works for a specific downstream response in a particular microenvironment. We name them as functional communication events (FCEs) of the target responses. Decoding the FCE-target gene relations is important for understanding the machanisms of many biological processes, but has been intractable due to the mixing of multiple factors and the lack of direct observations. We developed a method HoloNet for decoding FCEs using spatial transcriptomic data by integrating ligand-receptor pairs, cell-type spatial distribution and downstream gene expression into a deep learning model. We modeled CEs as a multiview network, developed an attention-based graph learning method to train the model for generating target gene expression with the CE networks, and decoded the FCEs for specific downstream genes by interpreting the trained model. We applied HoloNet on three Visium datasets of breast cancer or liver cancer. It revealed the communication landscapes in tumor microenvironments, and uncovered how various ligand-receptor signals and cell types affect specific biological processes. We also validated the stability of HoloNet in a Slideseq-v2 dataset. The experiments showed that HoloNet is a powerful tool on spatial transcriptomic data to help revealing specific cell-cell communications in a microenvironment that shape cellular phenotypes.

bioinformatics↗

bioRxiv2022

Alterations in protein kinase networks in astrocytes and neurons derived from patients with familial Alzheimers Disease

Neurons and astrocytes derived from Alzheimers Disease (AD) patient induced pluripotent stem cells are an evolving technology used to study the pathogenesis and etiology of AD. As the utility of mouse models of AD are increasingly coming into questions, using iPSC technology may offer an opportunity to study this disease with human substrates. Herein, we using a hypothesis generating platform, the PamGene12 Kinome Array, to identify core protein kinases in neurons and astrocytes derived from familial AD patient iPSCs. We identified five core protein kinases in these cells and examined the pathways in which they are enriched. Importantly, we complement our findings using an in-silico approach with postmortem AD brain datasets. While these protein kinases have been conceptualized in the context of traditional AD pathology, they have not been explored in the context of aberrant signaling in the pathophysiology of the disease.

neuroscience↗

bioRxiv2022

A novel cuproptosis-related long non-coding RNAs model that effectively predicts prognosis in hepatocellular carcinoma

BackgroundCuproptosis has recently been considered a novel form of programmed cell death. To date, factors crucial to the regulation of this process remain unelucidated. Here, we aimed to identify long-chain non-coding RNAs (lncRNAs) associated with cuproptosis in order to predict the prognosis of patients with hepatocellular carcinoma (HCC). MethodsUsing RNA sequence data from The Cancer Genome Atlas Live Hepatocellular Carcinoma (TCGA-LIHC), a co-expression network of cuproptosis-related mRNAs and lncRNAs was constructed. For HCC prognosis, we developed a cuproptosis-related lncRNA signature (CupRLSig) using univariate Cox, lasso, and multivariate Cox regression analyses. Kaplan-Meier analysis was used to compare overall survival among high- and low-risk groups stratified by median CupRLSig score. Furthermore, comparisons of functional annotation, immune infiltration, somatic mutation, TMB (tumor mutation burden), and pharmacologic options were made between high- and low-risk groups. ResultsOur prognostic risk model was constructed using the cuproptosis-related PICSAR, FOXD2-AS1, and AP001065.1 lncRNAs. The CupRLSig high-risk group was associated with poor overall survival (hazard ratio = 1.162, 95% CI = 1.063- 1.270; p < 0.001). Model accuracy was further supported by receiver operating characteristic and principal component analysis as well as internal validation cohorts. A prognostic nomogram developed considering CupRLSig data and a number of clinical characteristics were found to exhibit adequate performance in survival risk stratification. Mutation analysis revealed that high-risk combinations with high TMB carried worse prognoses. Finally, differences in immune checkpoint expression and responses to chemotherapy as well as in targeted therapy among CupRLSig stratified high- and low-risk groups were explored. ConclusionsThe lncRNA signature constructed in this study is valuable in prognostic estimation in the setting of HCC.

bioinformatics↗

bioRxiv2022

Autophagy Increases Occludin Levels to Enhance Intestinal Paracellular Tight Junction Barrier.

Background and AimFunctional loss of paracellular tight junction (TJ) barrier of the gut epithelium and mutations in autophagy genes are factors potentiating inflammatory bowel disease (IBD). Previously we showed the role of autophagy in enhancing the TJ barrier via claudin-2 degradation, however, its role in the regulation of the barrier-forming protein occludin remains unknown. Here, we investigate the role of autophagy in the regulation of occludin and its role in inflammation-mediated TJ barrier loss. MethodsPharmacological and genetic tools were used to study the effect of autophagy on occludin levels and localization, and the role of the MAPK pathway. ResultsAutophagy induction using pharmacological activators and nutrient starvation increased total occludin levels in different epithelial cells. Starvation enriched membrane occludin levels and reduced paracellular inulin flux in Caco-2 cells. Starvation-induced TJ barrier enhancement was contingent on the presence of occludin as OCLN-/- nullified its TJ barrier enhancing effect. Autophagy inhibited the constitutive degradation of occludin and protected against inflammation-induced TJ barrier loss. Starvation-induced TJ barrier enhancement was prevented by inhibition of autophagy. Autophagy enhanced the phosphorylation of ERK-1/2. Inhibition of these kinases in Caco-2 cells and human intestinal mucosa inhibited the protective effects of autophagy. In-vivo, autophagy induction by rapamycin increased occludin levels in mouse intestines and protected against LPS and TNF--induced TJ barrier loss. Additionally, acute Atg7 knockout in adult mice decreased intestinal occludin levels, increasing baseline colonic TJ-permeability and exacerbating the effect of DSS-induced colitis. ConclusionOur data suggest a novel role of autophagy in promoting the intestinal TJ barrier by increasing occludin levels in an ERK1/2 MAPK-dependent mechanism. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=151 SRC="FIGDIR/small/487876v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@1e08d0dorg.highwire.dtl.DTLVardef@14c65f5org.highwire.dtl.DTLVardef@b9e393org.highwire.dtl.DTLVardef@bcd65_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2022

CyTOF-Lec: Single-cell glycomics analysis reveals glycan features defining cells differentially susceptible to HIV

High-parameter single-cell phenotyping has enabled in-depth classification and interrogation of immune cells, but to date has not allowed for glycan characterization. Here, we develop CyTOF-Lec as an approach to simultaneously characterize many protein and glycan features of human immune cells at the single-cell level. We implemented CyTOF-Lec to compare glycan features between different immune subsets from blood and multiple tissue compartments, and to characterize HIV-infected cell cultures. Using bioinformatics approaches to distinguish preferential infection of cellular subsets from viral-induced remodeling, we demonstrate that HIV upregulates the levels of cell surface fucose and sialic acid in a cell- intrinsic manner, and that memory CD4+ T cells co-expressing high levels of fucose and sialic acid are highly susceptible to HIV infection. Sialic acid levels were found to distinguish memory CD4+ T cell subsets expressing different amounts of viral entry receptors, pro-survival factors, homing receptors, and activation markers, and to play a direct role in memory CD4+ T cells susceptibility to HIV infection. The ability of sialic acid to distinguish memory CD4+ T cells with different susceptibilities to HIV infection was experimentally validated through sorting experiments. Together, these results suggest that HIV remodels not only cellular proteins but also glycans, and that glycan expression can differentiate memory CD4+ T cells with vastly different susceptibility to HIV infection.

immunology↗

bioRxiv2022

High-dimension to high-dimension screening for detecting genome-wide epigenetic regulators of gene expression

MotivationThe advancement of high-throughput technology characterizes a wide range of epigenetic modifications across the genome involved in disease pathogenesis via regulating gene expression. The high-dimensionality of both epigenetic and gene expression data make it challenging to identify the important epigenetic regulators of genes. Conducting univariate test for each epigenetic-gene pair is subject to serious multiple comparison burden, and direct application of regularization methods to select epigenetic-gene pairs is computationally infeasible. Applying fast screening to reduce dimension first before regularization is more efficient and stable than applying regularization methods alone. ResultsWe propose a novel screening method based on robust partial correlation to detect epigenetic regulators of gene expression over the whole genome, a problem that includes both high-dimensional predictors and high-dimensional responses. Compared to existing screening methods, our method is conceptually innovative that it reduces the dimension of both predictor and response, and screens at both node (epigenetic features or genes) and edge (epigenetic-gene pairs) levels. We develop data-driven procedures to determine the conditional sets and the optimal screening threshold, and implement a fast iterative algorithm. Simulations and two applications to long non-coding RNA and DNA methylation regulation in Kidney cancer and Glioblastoma Multiforme illustrate the validity and advantage of our method. AvailabilityThe R package, related source codes and real data sets used in this paper are provided at https://github.com/kehongjie/rPCor.

bioinformatics↗

bioRxiv2021

CAMO: A molecular congruence analysis framework for evaluating model organisms

CAMO provides a rigorous and user-friendly solution for quantification and mechanistic exploration of omics congruence in model organisms and humans. It performs threshold-free differential analysis, quantitative concordance/discordance scoring, pathway-centric investigation, and topological subnetwork detection. Instead of dichotomous claims of "poorly" or "greatly" mimicking humans, CAMO facilitates discovery and visualization of specific molecular mechanisms that are best or least mimicked, providing foundations for hypothesis generation and subsequent translational investigations.

genomics↗

bioRxiv2021

A multivariate to multivariate approach for voxel-wise genome-wide association analysis

The joint analysis of imaging-genetics data facilitates the systematic investigation of genetic effects on brain structures and functions with spatial specificity. We focus on voxel-wise genome-wide association analysis, which may involve trillions of single nucleotide polymorphism (SNP)-voxel pairs. We attempt to identify underlying organized association patterns of SNP-voxel pairs and understand the polygenic and pleiotropic networks on brain imaging traits. We propose a bi-clique graph structure (i.e., a set of SNPs highly correlated with a cluster of voxels) for the systematic association pattern. Next, we develop computational strategies to detect latent SNP-voxel bi-cliques and inference model for statistical testing. We further provide theoretical results to guarantee the accuracy of our computational algorithms and statistical inference. We validate our method by extensive simulation studies, and then apply it to the whole genome genetic and voxel-level white matter integrity data collected from 1052 participants of the human connectome project (HCP). The results demonstrate multiple genetic loci influencing white matter integrity measures on splenium and genu of the corpus callosum.

neuroscience↗

bioRxiv2021

Chronic alcohol drinking persistently suppresses thalamostriatal excitation of cholinergic neurons to impair cognitive flexibility

Exposure to addictive substances impairs flexible decision-making. Cognitive flexibility is mediated by striatal cholinergic interneurons (CINs). However, how chronic alcohol drinking alters cognitive flexibility through CINs remains unclear. Here, we report that chronic alcohol consumption and withdrawal impaired reversal of instrumental learning. Chronic alcohol consumption and withdrawal also caused a long-lasting (21 d) reduction of excitatory thalamic inputs onto CINs and reduced pause response of CINs in the dorsomedial striatum (DMS). CINs are known to inhibit glutamatergic transmission in dopamine D1 receptor-expressing medium spiny neurons (D1-MSNs) but facilitate this transmission in D2-MSNs, which may contribute to flexible behavior. We discovered that chronic alcohol drinking impaired CIN-mediated inhibition in D1-MSNs and facilitation in D2-MSNs. Importantly, in vivo optogenetic induction of long-term potentiation of thalamostriatal transmission in DMS CINs rescued alcohol-induced reversal learning deficits. These results demonstrate that chronic alcohol drinking reduces thalamic excitation of DMS CINs, compromising their regulation of glutamatergic transmission in MSNs, which may contribute to alcohol-induced impairment of cognitive flexibility. These findings provide a neural mechanism underlying inflexible drinking in alcohol use disorder.

neuroscience↗

bioRxiv2021

A new Mendelian Randomization method to estimate causal effects of multivariable brain imaging exposures

The advent of simultaneously collected imaging-genetics data in large study cohorts provides an unprecedented opportunity to assess the causal effect of brain imaging traits on externally measured experimental results (e.g., cognitive tests) by treating genetic variants as instrumental variables. However, classic Mendelian Randomization methods are limited when handling high-throughput imaging traits as exposures to identify causal effects. We propose a new Mendelian Randomization framework to jointly select instrumental variables and imaging exposures, and then estimate the causal effect of multivariable imaging data on the outcome. We validate the proposed method with extensive data analyses and compare it with existing methods. We further apply our method to evaluate the causal effect of white matter microstructure integrity on cognitive function. The findings suggest that our method achieved better performance regarding sensitivity, bias, and false discovery rate compared to individually assessing the causal effect of a single exposure and jointly assessing the causal effect of multiple exposures without dimension reduction. Our application results indicated that WM measures across different tracts have a joint causal effect that significantly impacts the cognitive function among the participants from the UK Biobank.

bioinformatics↗

bioRxiv2021

Characterization of early Alzheimer's-like pathological alterations in non-human primates with aging: a pilot study

Sporadic or late onset Alzheimers disease (LOAD) is a multifactorial neurodegenerative disease with aging the most known risk factor. Non-human primates (NHPs) may serve as an excellent model to study LOAD because of their close similarity to humans in many aspects including neuroanatomy and neurodevelopment. Recent studies reveal AD-like pathology in old NHPs. In this pilot study, we took advantage of brain samples from 6 Cynomolgus macaques that were divided into two groups: middle aged (average age 14.81 years) and older (average age 19.33 years). We found multiple AD-like pathological alteration in the prefrontal cortex (but not in the hippocampus) of the older NHPs including tau hyperphosphorylation, increased activity of AMP-activated protein kinase (AMPK), decreased expression of protein phosphatase 2A (PP2A), impairments in mitochondrial morphology and postsynaptic densities (PSDs) formation. These findings may provide insights into the factors contributing to the development of LOAD, particularly during the early stage transitioning from middle to old age. Future endeavors are warranted to elucidate mechanisms underlying the regional (and perhaps cellular) vulnerability with aging and the functional correlation of such pathological changes in NHPs.

molecular biology↗

bioRxiv2021

A pair of transporters controls mitochondrial Zn2+ levels to maintain mitochondrial homeostasis

Zn2+ is required for the activity of many mitochondrial proteins, which regulate mitochondrial dynamics, apoptosis and mitophagy. However, it is not understood how the proper mitochondrial Zn2+ level is achieved to maintain mitochondrial homeostasis. Using Caenorhabditis elegans, we reveal here that a pair of mitochondrion-localized transporters controls the mitochondrial level of Zn2+. We demonstrate that SLC-30A9/ZnT9 is a mitochondrial Zn2+ exporter. Loss of SLC-30A9 leads to mitochondrial Zn2+ accumulation, which damages mitochondria, impairs animal development and shortens the life span. We further identify SLC-25A25/SCaMC-2 as an important regulator of mitochondrial Zn2+ import. Loss of SLC-25A25 suppresses the abnormal mitochondrial Zn2+ accumulation and defective mitochondrial structure and functions caused by loss of SLC-30A9. Moreover, we reveal that the endoplasmic reticulum contains the Zn2+ pool from which mitochondrial Zn2+ is imported. These findings establish the molecular basis for controlling the correct mitochondrial Zn2+ levels for normal mitochondrial structure and functions. SummaryZn2+ is a trace ion essential for the function of many mitochondrial proteins. It is not known how mitochondrial Zn2+ levels are regulated. Ma at al. identify transporters that mediate mitochondrial Zn2+ export and import to maintain mitochondrial homeostasis.

cell biology↗

bioRxiv2021

Antagonists targeting eEF2 kinase rescue multiple aspects of pathophysiology in Alzheimer's disease model mice

It is imperative to develop novel therapeutic strategies for Alzheimers disease (AD) and related dementia syndromes based on solid mechanistic studies. Maintenance of memory and synaptic plasticity relies on de novo protein synthesis, which is partially regulated by phosphorylation of eukaryotic elongation factor 2 (eEF2) via its kinase eEF2K. Abnormally increased eEF2 phosphorylation and impaired mRNA translation have been linked to AD. We recently reported that prenatal genetic suppression of eEF2K is able to prevent aging-related cognitive deficits in AD model mice, suggesting the therapeutic potential of targeting eEF2K/eEF2 signaling in AD. Here, we tested two structurally distinct small-molecule eEF2K inhibitors in two different lines of AD model mice after onset of cognitive impairments. Our data revealed that treatment with eEF2K inhibitors improved AD-associated synaptic plasticity impairments and cognitive dysfunction, without altering brain amyloid {beta} (A{beta}) and tau pathology. Furthermore, eEF2K inhibition alleviated AD-associated defects in dendritic spine morphology, postsynaptic density formation, protein synthesis, and dendritic polyribosome assembly. Our results may offer critical therapeutic implications for AD, and the proof-of-principle study indicates translational implication of inhibiting eEF2K for AD and related dementia syndromes. One Sentence SummaryTreatment with eEF2K inhibitors and genetic eEF2K knockout improved cognitive deficits in Alzheimers disease model mice.

neuroscience↗

bioRxiv2021

Highly potent photoinactivation of bacteria using a water soluble, cell permeable, DNA-binding photosensitizer

Antimicrobial photodynamic therapy (APDT) employs a photosensitizer, light, and molecular oxygen to treat infectious diseases via oxidative damage, with a low likelihood for the development of resistance. For optimal APDT efficacy, photosensitizers with cationic charges that can permeate bacteria cells and bind intracellular targets are desired to not limit oxidative damage to the outer bacterial structure. Here we report the application of brominated DAPI (Br-DAPI), a water-soluble, DNA-binding photosensitizer for eradication of both gram-negative and gram-positive bacteria (as demonstrated on N99 E. coli and B. subtilis, respectively). We observe intracellular uptake of Br-DAPI, ROS-mediated bacterial cell death via 1- and 2-photon excitation, and selective photocytotoxicity of bacteria over mammalian cells. Photocytotoxicity of both N99 E. coli and B. subtilis occurred at sub-micromolar concentrations (IC50 = 0.2 M - 0.4 M) and low light doses (5-minute irradiation times, 4.5 J cm-2 dose) making it superior to commonly employed APDT phenothiazinium photosensitizers such as methylene blue. Given its high potency and 2-photon excitability, Br-DAPI is a promising novel photosensitizer for in vivo APDT applications.

biophysics↗

bioRxiv2021

Discovering single-cell eQTLs from scRNA-seq data only

eQTL studies are essential for understanding genomic regulation. Effects of genetic variations on gene regulation are cell-type-specific and cellular-context-related, so studying eQTLs at a single-cell level is crucial. The ideal solution is to use both mutation and expression data from the same cells. However, current technology of such paired data in single cells is still immature. We present a new method, eQTLsingle, to discover eQTLs only with single cell RNA-seq (scRNA-seq) data, without genomic data. It detects mutations from scRNA-seq data and models gene expression of different genotypes with the zero-inflated negative binomial (ZINB) model to find associations between genotypes and phenotypes at single-cell level. On a glioblastoma and gliomasphere scRNA-seq dataset, eQTLsingle discovered hundreds of cell-type-specific tumor-related eQTLs, most of which cannot be found in bulk eQTL studies. Detailed analyses on examples of the discovered eQTLs revealed important underlying regulatory mechanisms. eQTLsingle is a unique powerful tool for utilizing the huge scRNA-seq resources for single-cell eQTL studies, and it is available for free academic use at https://github.com/horsedayday/eQTLsingle.

bioinformatics↗