Biology subjects

Qiao, L.

Publications and source records attributed to Qiao, L..

At least 55 records · Page 3Linked to original sources

bioRxiv2022

STOmics-GenX: CRISPR based approach to improve cell identity specific gene detection from spatially resolved transcriptomics

The spatial organisation of cells defines the biological functions of tissue ecosystems from development to disease. Recently, an array of technologies have been developed to query gene expression in a spatial context. These include techniques such as employing barcoded oligonucleotides, single-molecule fluorescence in situ hybridization (smFISH), and DNA nanoball (DNB)-patterned arrays. However, resolution and efficiency vary across platforms and technologies. To obtain spatially relevant biological information from spatially resolved transcriptomics, we combined the Stereo-seq workflow with CRISPRclean technology to develop the STOmics-GenX pipeline. STOmics-GenX not only allowed us to reduce genomic, mitochondrial, and ribosomal reads, but also lead to a [~]2.1-fold increase in the number of detected genes when compared to conventional Stereo-seq (STOmics). Additionally, the STOmics-GenX pipeline resulted in an improved detection of cell type specific genes, thereby improving cellular annotations. Most importantly, STOmics-GenX allowed for enhanced detection of clinically relevant biomarkers such as Alpha-fetoprotein (AFP), enabling the identification of two spatially distinct subsets of hepatocytes in hepatocellular carcinoma tissue. Thereby, combining CRISPRclean technology with STOmics not only allowed improved gene detection but also paved the way for spatial precision oncology by improved detection of clinically relevant biomarkers.

molecular biology↗

bioRxiv2022

The Effect of Node Features on GCN-based Brain Network Classification: An Empirical Study

Brain functional network (BFN) analysis has become a popular technique for identifying neurological/mental diseases. Due to the fact that BFN is a graph, graph convolutional network (GCN) can be naturally used in the classification of BFN. Different from traditional methods that directly use the adjacency matrices of BFNs to train a classifier, GCN requires an additional input -- node features. To our best knowledge, however, there is no systematic study to analyze their influence on the performance of GCN-based brain disorder classification. Therefore, in this per, we conduct an empirical study on various node feature measures, including 1) original fMRI signals, 2) one-hot encoding, 3) node statistics, 4) node correlation, and 5) their combination. Experimental results on two benchmark databases show that different node feature inputs to GCN significantly affect the brain disease classification performance, and node correlation usually contributes higher accuracy compared to original signals and manually extracted statistical features.

neuroscience↗

bioRxiv2022

Design principles of dose-response alignment in coupled GTPase switches

"Dose-response alignment" (DoRA), where the downstream response of cellular signaling path-ways closely matches the fraction of activated receptor, can improve the fidelity of dose information transmission. It is believed that a key component for DoRA is negative feedback and thus a natural question that arises is whether there exist design principles for signaling motifs within such negative feedback loops, which may enable these motifs to attain near-perfect DoRA. Here, we investigated several model formulations of an experimentally validated circuit that couples two molecular switches--mGTPase (monomeric GTPase) and tGTPase (heterotrimeric GTPases) -- with negative feedback loops. We find that, in the absence of feedback, the low and intermediate mGTPase activation levels benefit DoRA in the mass action and Hill-function models, respectively. In other cases, where the mass action model with a high mGTPase activation level or the Hill-function model with a non-intermediate mGTPase activation level, the DoRA can be improved by adding negative feedback loops. Furthermore, we found that DoRA in a longer cascade (i.e., tGTPase) can be obtained using Hill-function kinetics under certain conditions. In summary, we show how ranges of activity of mGTPase, reaction kinetics, the negative feedback, and the cascade length affect DoRA. This work provides a framework for improving the DoRA performance in signaling motifs with negative feedback loops. Significance StatementDose-response alignment helps cells faithfully transmit dose information; how this alignment is achieved in motifs with negative feedback is unclear. Through rigorous studies interrogating a naturally occurring motif comprised of two species of GTPases coupled by negative feedback loops, this work reveals the versatile roles of negative feedback loops and GTPase regulators on DoRA. We find that the negative feedback can enhance DoRA only with specific kinetic forms and with certain ranges of GTPases activation levels. This knowledge advances our understanding of the role of negative feedback on DoRA and sheds light on the importance of dynamic range of signaling processes as an essential determinant of how cells transfer information about stimuli. Findings can help design signaling circuits with better DoRA behavior, and ultimately augment cell signaling studies.

systems biology↗

bioRxiv2022

The right inferior frontal gyrus as pivotal node and effective regulator of the basal ganglia-thalamocortical response inhibition circuit in humans

The involvement of specific basal ganglia-thalamocortical circuits in response inhibition has been extensively mapped in the last few decades. However, the pivotal brain nodes and directed casual regulation within this inhibitory circuit in humans remains controversial. Here, we capitalize on recent progress in robust and biologically plausible directed causal modelling (DCM-PEB) and a large fMRI response inhibition dataset (n=218) to determine key nodes, their causal regulation and modulation via biological variables (sex) and inhibitory performance in the inhibitory control circuit encompassing the right inferior frontal gyrus (rIFG), caudate nucleus (rCau), globus pallidum (rGP) and thalamus (rThal).The entire neural circuit exhibited high intrinsic connectivity and an increasing rIFG inflow and its causal regulation over the rCau and rThal during response inhibition. In addition, sex and behavioral performance influenced the architecture of the regulatory circuits such that women displayed increased rThal self-inhibition and decreased rThal to GP modulation, while better inhibitory performance was associated with stronger rThal to rIFG communication. Furthermore, control analyses did not reveal a similar key communication in a left lateralized model. Together these findings indicate a pivotal role of the rIFG as input and causal regulator of subcortical response inhibition nodes.

neuroscience↗

bioRxiv2022

Bone marrow haematopoietic stem cells influence liver homeostatic networks and cancer development after dietary intervention

A holistic understanding of anti-tumor immunity requires examination of systemic immunity beyond the tumor microenvironment. This link between systemic and tumor immune activity is underexplored. We demonstrate that a stronger Type I interferon response in human liver tumors predicts better survival and correlates with the immune response in the adjacent non-tumor liver. Further, in patients with liver cancer, clonal hematopoiesis (CH) (a marker of systemic immune activation) is associated with a trend towards improved survival. In a mouse model of liver cancer, basal liver immune responses correlate with the degree of bone marrow hematopoietic stem and progenitor cell responses. A higher systemic and liver immune response, marked by innate myeloid cell infiltration reduces tumor burden, while sub-optimal systemic and liver immunity corresponded with a higher tumor burden. Our findings indicate that the state of bone marrow hematopoiesis impacts liver tumor outcomes, offering both therapeutic and prognostic opportunities.

systems biology↗

bioRxiv2021

Network design principle for robust oscillatory behaviors with respect to biological noise

Oscillatory behaviors, which are ubiquitous in transcriptional regulatory networks, are often subject to inevitable biological noise. Thus a natural question is how transcriptional regulatory networks can robustly achieve accurate oscillation in the presence of biological noise. Here, we search all two- and three-node transcriptional regulatory network topologies for those robustly capable of accurate oscillation against the parameter variability (extrinsic noise) or stochasticity of chemical reactions (intrinsic noise). We find that, no matter what source of the noise is applied, the topologies containing the repressilator with positive auto-regulation show higher robustness of accurate oscillation than those containing the activator-inhibitor oscillator, and additional positive auto-regulation enhances the robustness against noise. Nevertheless, the attenuation of different sources of noise is governed by distinct mechanisms: the parameter variability is buffered by the long period, while the stochasticity of chemical reactions is filtered by the high amplitude. Furthermore, we analyze the noise of a synthetic human nuclear factor {kappa}B (NF-{kappa}B) signaling network by varying three different topologies, and verify that the addition of a repressilator to the activator-inhibitor oscillator, which leads to the emergence of high-robustness motif--the repressilator with positive auto-regulation, improves the oscillation accuracy in comparison to the topology with only an activator-inhibitor oscillator. These design principles may be applicable to other oscillatory circuits.

systems biology↗

bioRxiv2021

Identification and Characterization of Stem Cells in Mammalian Esophageal Stratified Squamous Epithelia

Somatic stem cells are essential for maintenance of cell proliferation-differentiation homeostasis in organs. Despite the importance, how the esophageal epithelium that executes its self-renewal and maintenance remains elusive. In this study, using 5-bromo-2-deoxyuridine (BrdU) label-chase in rat and rat esophageal keratinocyte cell line-derived organoids together with genome-wide DNA methylation profiling and single-cell RNA sequencing (scRNA-seq), we identify slow cycling/quiescent stem cell population that contain high levels of hemidesmosome (HD)s and low levels of Wnt signaling localized spatially and randomly at the basal layer of the esophageal epithelium. Pseudo-time cell trajectory from scRNA-seq indicates that cell fates begin from quiescent basal cells (the stem cells) of the basal layer that produce proliferating and/or differentiating cells in the basal layer, which, in turn, progress into differentiating cells in the suprabasal layer, ultimately transforming into differentiated keratinocytes in the differentiated layer. Perturbations of HD component expressions and/or Wnt signaling reduce stem cell in the basal layer of esophageal keratinocyte organoids, resulting in alterations of organoid formation rate, size, morphogenesis and proliferation-differentiation homeostasis. Furthermore, we show that not only high levels of HDs and low levels of Wnt signaling but also an interplay between HD and Wnt signaling defined stem cells of the basal layer in the esophageal squamous epithelium. Hence, HDs and Wnt signaling are the critical determinants for defining stem cells of the basal layer required for proliferation-differentiation homeostasis and maintenance in the mammalian esophageal squamous epithelium.

cell biology↗

bioRxiv2021

GproDIA enables data-independent acquisition glycoproteomics with comprehensive statistical control

Large-scale profiling of intact glycopeptides is critical but challenging in glycoproteomics. Data independent acquisition (DIA) is an emerging technology with deep proteome coverage and accurate quantitative capability in proteomics studies, but is still in the early stage of development in the field of glycoproteomics. We propose GproDIA, a framework for the proteome-wide characterization of intact glycopeptides from DIA data with comprehensive statistical control by a 2-dimentional false discovery rate approach and a glycoform inference algorithm, enabling accurate identification of intact glycopeptides using wide isolation windows. We further adapt a semi-empirical spectrum prediction strategy to expand the coverage of spectral libraries of glycopeptides. We benchmark our method for N-glycopeptide profiling on DIA data of yeast and human serum samples, demonstrating that DIA with GproDIA outperforms the data dependent acquisition (DDA) based methods for glycoproteomics in terms of capacity and data completeness of identification, as well as accuracy and precision of quantification. We expect that this work can provide a powerful tool for glycoproteomic studies.

bioinformatics↗

bioRxiv2021

Closed-Loop Control between Two GTPase Switches makes the Secretory Functions of the Golgi Responsive to Growth Factors

Cancers represent complex autonomous systems, displaying self-sufficiency in growth signaling. Autonomous growth is fueled by a cancer cells ability to secrete-and-sense growth factors: a poorly understood phenomenon. Using an integrated systems and experimental approach, here we dissect the impact of a feedback-coupled GTPase circuit within the secretory pathway that imparts secretion-coupled autonomy. The circuit is assembled when the Ras-superfamily monomeric GTPase Arf1, and the heterotrimeric GTPase Gi{beta}{gamma} and their corresponding GAPs and GEFs are coupled by GIV/Girdin, a protein that is known to fuel aggressive traits in diverse cancers. One forward and two key negative feedback loops within the circuit create closed-loop control (CLC), allow the two GTPases to coregulate each other, and convert the expected switch-like behavior of Arf1-dependent secretion into an unexpected dose response alignment behavior of sensing and secretion. Such behavior translates into cell survival that is self-sustained by stimulus-proportionate secretion. Proteomic studies and protein-protein interaction network analyses pinpoint growth factors (e.g., the epidermal growth factor; EGF) as a key stimuli for such self-sustenance. Findings highlight how enhanced coupling of two biological switches in cancer cells is critical for multiscale feedback control to achieve secretion-coupled autonomy of growth factors. SYNOPSIS IMAGE O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY STANDFIRST TEXTThis work defines the inner workings of a Golgi-localized molecular circuitry comprised of coupled GTPases, which empowers cells to achieve self-sufficiency in growth factor signaling by creating a secrete-and-sense autocrine loop. HIGHLIGHTS/MAIN FINDINGSO_LIModeling and experimental approaches were used to dissect a coupled GTPase circuit. C_LIO_LICoupling enables closed loop feedback and mutual control of GTPases. C_LIO_LICoupling generates dose response alignment behavior of sensing and secretion of growth factors. C_LIO_LICoupling is critical for multiscale feedback control to achieve secretion-coupled autonomy. C_LI

systems biology↗

bioRxiv2021

Modeling of histone modifications reveals formation mechanism and function of bivalent chromatin

Bivalent chromatin is characterized by occupation of both activating histone modifications and repressive histone modifications. While bivalent chromatin is known to link with many biological processes, the mechanisms responsible for its multiple functions remain unclear. Here, we develop a mathematical model that involves antagonistic histone modifications H3K4me3 and H3K27me3 to capture the key features of bivalent chromatin. Three necessary conditions for the emergence of bivalent chromatin are identified, including advantageous methylating activity over demethylating activity, frequent noise conversions of modifications, and sufficient nonlinearity. The first condition is further confirmed by analyzing the experimental data from a recent study. Investigation of the composition of bivalent chromatin reveals that bivalent nucleosomes carrying both H3K4me3 and H3K27me3 account for no more than half of nucleosomes at the bivalent chromatin domain. We identify that bivalent chromatin not only allows transitions to multiple states but also serves as a stepping stone to facilitate a step-wise transition between repressive chromatin state and activating chromatin state, and thus elucidate crucial roles of bivalent chromatin in mediating phenotypical plasticity during cell fate determination.

systems biology↗

bioRxiv2021

Spray-induced gene silencing for disease control is dependent on the efficiency of pathogen RNA uptake

Recent discoveries show that fungi can take up environmental RNA, which can then silence fungal genes through environmental RNA interference. This discovery prompted the development of Spray-Induced Gene Silencing (SIGS) for plant disease management. In this study, we aimed to determine the efficacy of SIGS across a variety of eukaryotic microbes. We first examined the efficiency of RNA uptake in multiple pathogenic and non-pathogenic fungi, and an oomycete pathogen. We observed efficient double-stranded RNA (dsRNA) uptake in the fungal plant pathogens Botrytis cinerea, Sclerotinia sclerotiorum, Rhizoctonia solani, Aspergillus niger, and Verticillium dahliae, but no uptake in Colletotrichum gloeosporioides, and weak uptake in a beneficial fungus, Trichoderma virens. For the oomycete plant pathogen, Phytophthora infestans, RNA uptake was limited, and varied across different cell types and developmental stages. Topical application of dsRNA targeting virulence-related genes in the pathogens with high RNA uptake efficiency significantly inhibited plant disease symptoms, whereas the application of dsRNA in pathogens with low RNA uptake efficiency did not suppress infection. Our results have revealed that dsRNA uptake efficiencies vary across eukaryotic microbe species and cell types. The success of SIGS for plant disease management can largely be determined by the pathogen RNA uptake efficiency.

microbiology↗

bioRxiv2021

Randomized controlled studies comparing traditional lectures versus online modules

We assessed the efficacy of traditional lectures versus online modules with respect to student learning in an undergraduate introductory biochemistry course in two successive years. In the first year, students had the options of attending live lectures by the course instructor and viewing online modules pre-recorded by the instructor, with the lectures and modules covering identical content; in addition, all students had a mandatory weekly application session. Utilizing pre-course and post-course tests as an instrument with which to measure learning during the course, we observed significantly increased learning (0.7 standard deviations) with attendance of traditional lectures and decreased learning with use of online modules, even after adjustment for grade point average. In the second year, the course had the same curriculum, but students were randomized to either live lectures or online modules for the first half of the course, crossing over to the other modality during the second half. With randomization, no difference in learning was observed between the two groups. Furthermore, we found that students self-reported greater engagement when viewing online modules than when attending lectures in person. These findings suggest some aspects of the lecture experience can be shifted to online modules in STEM courses without impacts on student learning so as to use classroom time more fully for application-based active learning interventions.

scientific communication and education↗

bioRxiv2019

Arabidopsis CPR5 regulates ethylene signaling via interacting with ETR1 N-terminus and controlling mRNAs nucleocytoplasmic transport

ETR1 is the major ethylene receptor in Arabidopsis thaliana. Previous studies showed that RTE1 and CPR5 can bind to ETR1 and play regulatory roles in ethylene signaling. RTE1 has been suggested to promote ETR1 signal transduction by influencing the conformation of ETR1, but little is known about the mechanism of CPR5 on the regulation of ETR1 signaling. In this study, we showed that both CPR5 and RTE1 could interact with the N-terminal transmembrane domains of ETR1, and CPR5 needs at least three transmembrane domains of ETR1 while RTE1 needs only two for the binding. As CPR5 has also been shown to be localized in the nuclear membrane and might act as a nucleoporin, we analyzed the effects of CPR5 on the nucleocytoplasmic transport of ethylene-related mRNAs using poly(A)-mRNA in situ hybridization and real-time quantitative PCR (qPCR), and the results indicated that CPR5 could selectively regulate the nucleocytoplasmic transport of mRNAs in ethylene signaling pathway. In contrast, the nucleoporin mutants (nup160, nup96-1 and nup96-2) dramatically accumulated all the examined mRNAs in the nucleus. In conclusion, the present study provides evidence demonstrating that CPR5 regulates ethylene signaling through interacting with the ETR1 receptor and controlling the mRNAs nucleocytoplasmic transport in ethylene signaling pathway. Key messageThis study reveals that CPR5 is involved in the regulation of ethylene signaling via two different ways: interacting with the N-terminal domains of ERT1 and controlling the nucleocytoplasmic transport of mRNAs in ethylene signaling pathway.

plant biology↗

bioRxiv2019

Genome-wide Association study of facial morphology identifies novel genetic loci in Han Chinese

Human face is a heritable surface with many complex sensory organs. In recent years, many genetic loci associated with facial features have been reported in different populations, yet there is a lack for the Han Chinese population. We report a genome-wide association analysis of 3D normal human faces in 2659 Han Chinese with two groups of phenotypes, the partial and whole face phenotypes and the distance and angle phenotypes. We found significant signals in five genomic regions with traits related to nose or eyes, including rs970797 in 2q31.1 near HOXD1 and MTX2, rs16897517 in 8q22.2 at intron of VPS13B, rs9995821 in 4q31.3 near DCHS2 and SFRP2, rs12636297 in 3q23 near PISRT1, and rs12948076 in 17q24.3 near SOX9 and CASC17. We visualized changes in facial morphology by comparing the volume of local areas and observed that these nose-related loci were associated with different features of the nose, including nose prominence, nasion height, and nostril shape, suggesting that the nose underlies precise genetic regulation. These results provide a more comprehensive understanding of the relationship between genetic loci and human facial morphology.\n\nAuthor SummaryHuman face as a combination of delicate sensory organs has a strong genetic component, as evidenced by the identical appearance in twins and shared facial features in close relatives. Although facial genetics have been studied in different populations, our knowledge between genetic markers with facial features is still limited. In this paper, we found genetic variants associated with nose and eyes through a large-scale high-resolution 3D facial genetic study on the Han Chinese population. We observed that these nose-related loci were associated with different features of the nose, including nose prominence, nasion height, and nostril shape, which suggests the nose underlies precise genetic regulation. Intriguingly, we noted that genes (DCHS2 and SFRP2) related to one of these loci are differentially expressed in human and chimp cranial neural crest cells, which plays a crucial role in the early formation of facial morphology. The ongoing genetic studies of facial morphology will improve our understanding of human craniofacial development, and provide potential evolution evidence of human facial features.

genetics↗

bioRxiv2019

Towards a Better Estimation of Functional Brain Network for Mild Cognitive Impairment Identification: A Transfer Learning View

Mild cognitive impairment (MCI) is an intermediate stage of brain cognitive decline, associated with increasing risk of developing Alzheimers disease (AD). It is believed that early treatment of MCI could slow down the progression of AD, and functional brain network (FBN) could provide potential imaging biomarkers for MCI diagnosis and response to treatment. However, there are still some challenges to estimate a \"good\" FBN, particularly due to the poor quality and limited quantity of functional magnetic resonance imaging (fMRI) data from the target domain (i.e., MCI study). Inspired by the idea of transfer learning, we attempt to transfer information in high-quality data from source domain (e.g., human connectome project in this paper) into the target domain towards a better FBN estimation, and propose a novel method, namely NERTL (Network Estimation via Regularized Transfer Learning). Specifically, we first construct a high-quality network \"template\" based on the source data, and then use the template to guide or constrain the target of FBN estimation by a weighted l1-norm regularizer. Finally, we conduct experiments to identify subjects with MCI from normal controls (NCs) based on the estimated FBNs. Despite its simplicity, our proposed method is more effective than the baseline methods in modeling discriminative FBNs, as demonstrated by the superior MCI classification accuracy of 82.4% and the area under curve (AUC) of 0.910.

neuroscience↗

bioRxiv2019

Folate deficiency facilitates coordination of KDM6A with p53 in response to DNA damage

Folate contributes to the accumulation of DNA strand breaks (DSBs) in the genome. Kdm6a plays a critical role in early embryogenesis but it is unknown whether Kdm6a is involved in the DNA damage response under folate deficiency. Here, we established a low folate environment for mouse embryonic cells using a folate antagonist (methotrexate, MTX). We found increased enrichment of DSBs in Kdm6a in MTX-treated cells, resulting in reduced Kdm6a expression. MTX treatment enriched KDM6A in the nonhomologous end-joining (NHEJ) repair pathway and controlled the expression of the Ku heterodimer (Ku70/80) and XRCC4. The activation of NHEJ repair pathway-associated genes under folate deficiency relied on the specific interaction between KDM6A and p53. p53 silencing increased Ku heterodimer expression. In addition, in a neural tube defect (NTD) mouse model and low folate neural tube defect human brain samples, KDM6A levels were also decreased and accompanied by over-expression of Ku80. Our findings highlight how alterations in folate levels affect KDM6A with respect to DNA breakage and DNA repair, offering a new insight into the molecular function of KDM6A.\n\nSummary statementOur study demonstrates for the first time that in mammals, Kdm6a and p53 have synergistic effects during DNA fragmentation repair.

bioinformatics↗

bioRxiv2017

Functional Brain Network Estimation with Time Series Self-scrubbing

Functional brain network (FBN) has been becoming an increasingly important measurement for exploring the cerebral working mechanism and mining informative biomarkers for assisting diagnosis of some neurodegenerative disorders. Despite its potential performance in discovering the valuable patterns hidden in the brains, the estimated FBNs are often heavily influenced by the quality of the observed data (e.g., BOLD signal series). In practice, a preprocessing pipeline is usually employed for improving the data quality prior to the FBN estimation; but, even so, some data points in the time series are still not clean enough, possibly including original artifacts (e.g., micro head motion), non-resting functional disturbing (e.g., mind-wandering), and new \"noises\" caused by the preprocessing pipeline per se. Therefore, not all data points in the time series can contribute to the subsequent FBN estimation. To address this issue, in this paper, we propose a novel FBN estimation method by introducing a latent variable as an indicator of the data quality, and develop an alternating optimization algorithm for scrubbing the data and estimating FBN simultaneously in a single framework. As a result, we can obtain more accurate FBNs with the self-scrubbing data. To illustrate the effectiveness of the proposed method, we conduct experiments on two publicly available datasets to identify mild cognitive impairment (MCI) patients from normal control (NC) subjects based on the estimated FBNs. Experimental results show that the proposed FBN modelling method can achieve higher classification accuracy, significantly outperforming the baseline methods.

neuroscience↗

bioRxiv2017

Genome-wide Variants of Eurasian Facial Shape Differentiation and a prospective model of DNA based Face Prediction

It is a long standing question as to which genes define the characteristic facial features among different ethnic groups. In this study, we use Uyghurs, an ancient admixed population to query the genetic bases why Europeans and Han Chinese look different. Facial traits were analyzed based on high-dense 3D facial images; numerous biometric spaces were examined for divergent facial features between European and Han Chinese, ranging from inter-landmark distances to dense shape geometrics. Genome-wide association analyses were conducted on a discovery panel of Uyghurs. Six significant loci were identified four of which, rs1868752, rs118078182, rs60159418 at or near UBASH3B, COL23A1, PCDH7 and rs17868256 were replicated in independent cohorts of Uyghurs or Southern Han Chinese. A prospective model was also developed to predict 3D faces based on top GWAS signals, and tested in hypothetic forensic scenarios.

genetics↗