Biology subjects

Liu, T.

Publications and source records attributed to Liu, T..

At least 217 records · Page 12Linked to original sources

bioRxiv2024

Dissecting reprogramming heterogeneity at single-cell resolution using scTF-seq

Reprogramming approaches often produce heterogeneous cell fates and the mechanisms behind this heterogeneity are not well-understood. To address this gap, we developed scTF-seq, a technique inducing single-cell barcoded and doxycycline-inducible TF overexpression while quantifying TF dose-dependent transcriptomic changes. Applied to mouse embryonic multipotent stromal cells (MSCs), scTF-seq produced a gain-of-function atlas for 384 murine TFs. This atlas offers a valuable resource for gene regulation and reprogramming research, identifying key TFs governing MSC lineage differentiation, cell cycle control, and their interplay. Leveraging the single-cell resolution, we dissected reprogramming heterogeneity along dose and pseudotime. We thereby revealed TF dose-dependent and stochastic cell fate branching, unveiling gene expression signatures that enhance our understanding and prediction of reprogramming efficiency. scTF-seq also allowed us to classify TFs into four sensitivity classes based on dose response and determining features. Finally, in combinatorial scTF-seq, we observed that the same TF can exhibit both synergistic and antagonistic effects on another TF depending on its dose. In summary, scTF-seq provides a powerful tool for gaining mechanistic insights into how TFs determine cell states, while offering novel perspectives for cellular engineering strategies.

cell biology↗

bioRxiv2024

Temporal variability in host availability alters the outcome of competition between two parasitoid species

O_LIVariability in the availability of resources through time is a common attribute in trophic interactions, but its effects on the fitness of different consumer species and on interspecific competition between them are not clearly understood. C_LIO_LITo investigate this, we allowed two parasitoid species, Trichopria drosophilae and Pachycrepoideus vindemiae, to exploit Drosophila host pupae under three temporal variability treatments, either on their own or simultaneously. C_LIO_LIWhen tested individually (in the absence of interspecific competition), both parasitoid species had lower fitness when hosts were exposed for a short duration at high density than when exposed for a long duration at low density. When both parasitoid species exploited hosts simultaneously, interspecific competition significantly decreased the number of offspring for both parasitoid species. The outcome of this interspecific competition depended on host temporal variability, with T. drosophilae or P. vindemiae dominating in short and long host exposure treatments, respectively. C_LIO_LIThese results can be explained by the combination of host availability and egg load of female adult parasitoids. When abundant hosts are provided for a short period, the ample mature eggs of the proovigenic T. drosophilae enable them to exploit hosts more efficiently than P. vindemiae, which is synovigenic. However, P. vindemiae is an intrinsically superior competitor and dominates when multiparasitism occurs. Multiparasitism is more frequent when hosts are at low levels relative to the egg load of the parasitoids. C_LIO_LIOur results clearly demonstrate that resource temporal availability can alter the outcome of competition between consumers with different reproductive traits. C_LI

ecology↗

bioRxiv2024

A fast and sensitive size-exclusion chromatography method for plasma extracellular vesicle proteomic analysis

Extracellular vesicles (EVs) carry diverse biomolecules derived from their parental cells, making their components excellent biomarker candidates. However, purifying EVs is a major hurdle in biomarker discovery since current methods require large amounts of samples, are time-consuming and typically have poor reproducibility. Here we describe a simple, fast, and sensitive EV fractionation method using size exclusion chromatography (SEC) on a fast protein liquid chromatography (FPLC) system. Our method uses a Superose 6 Increase 5/150, which has a bed volume of 2.9 mL. The FPLC system and small column size enable reproducible separation of only 50 {micro}L of human plasma in 15 minutes. To demonstrate the utility of our method, we used longitudinal samples from a group of individuals that underwent intense exercise. A total of 838 proteins were identified, of which, 261 were previously characterized as EV proteins, including classical markers, such as cluster of differentiation (CD)9 and CD81. Quantitative analysis showed low technical variability with correlation coefficients greater than 0.9 between replicates. The analysis captured differences in relevant EV-proteins involved in response to physical activity. Our method enables fast and sensitive fractionation of plasma EVs with low variability, which will facilitate biomarker studies in large clinical cohorts.

biochemistry↗

bioRxiv2024

Innate Immune Activation and Mitochondrial ROS Invoke Persistent Cardiac Conduction System Dysfunction after COVID-19

BackgroundCardiac risk rises during acute SARS-CoV-2 infection and in long COVID syndrome in humans, but the mechanisms behind COVID-19-linked arrhythmias are unknown. This study explores the acute and long term effects of SARS-CoV-2 on the cardiac conduction system (CCS) in a hamster model of COVID-19. MethodsRadiotelemetry in conscious animals was used to non-invasively record electrocardiograms and subpleural pressures after intranasal SARS-CoV-2 infection. Cardiac cytokines, interferon-stimulated gene expression, and macrophage infiltration of the CCS, were assessed at 4 days and 4 weeks post-infection. A double-stranded RNA mimetic, polyinosinic:polycytidylic acid (PIC), was used in vivo and in vitro to activate viral pattern recognition receptors in the absence of SARS-CoV-2 infection. ResultsCOVID-19 induced pronounced tachypnea and severe cardiac conduction system (CCS) dysfunction, spanning from bradycardia to persistent atrioventricular block, although no viral protein expression was detected in the heart. Arrhythmias developed rapidly, partially reversed, and then redeveloped after the pulmonary infection was resolved, indicating persistent CCS injury. Increased cardiac cytokines, interferon-stimulated gene expression, and macrophage remodeling in the CCS accompanied the electrophysiological abnormalities. Interestingly, the arrhythmia phenotype was reproduced by cardiac injection of PIC in the absence of virus, indicating that innate immune activation was sufficient to drive the response. PIC also strongly induced cytokine secretion and robust interferon signaling in hearts, human iPSC-derived cardiomyocytes (hiPSC-CMs), and engineered heart tissues, accompanied by alterations in electrical and Ca2+ handling properties. Importantly, the pulmonary and cardiac effects of COVID-19 were blunted by in vivo inhibition of JAK/STAT signaling or by a mitochondrially-targeted antioxidant. ConclusionsThe findings indicate that long term dysfunction and immune cell remodeling of the CCS is induced by COVID-19, arising indirectly from oxidative stress and excessive activation of cardiac innate immune responses during infection, with implications for long COVID Syndrome.

pathology↗

bioRxiv2023

Effect of eye globe and optic nerve morphologies on gaze-induced optic nerve head deformations

PurposeTo investigate the effect of globe and optic nerve (ON) morphologies and tissue stiffnesses on gaze-induced optic nerve head deformations using parametric finite element modeling and a Design of Experiment (DOE) approach. MethodsA custom software was developed to generate finite element models of the eye using 10 morphological parameters: dural radius, scleral, choroidal, retinal, pial, peripapillary border tissue thicknesses, prelaminar tissue depth, lamina cribrosa (LC) depth, ON radius, and ON tortuosity. A 10-factor 2-level full-factorial analysis (1,024 models) was used to predict the effects of each morphological factor and their interactions on LC strains induced by 13{degrees} adduction. Subsequently, a further DOE analysis (1,024 models) was conducted to study the effects and potential interactions between the top 5 morphological parameters identified from the initial DOE study and 5 critical tissue stiffnesses. ResultsIn the DOE analysis of 10 morphological parameters, the five most significant factors were ON tortuosity, dural radius, ON radius, scleral thickness and LC depth. Further DOE analysis incorporating biomechanical parameters highlighted the importance of dural and LC stiffness. A larger dural radius and stiffer dura increased LC strains but the other main factors had the opposite effects. Notably, a significant interaction was found between dural radius and dural stiffness. ConclusionsThis study highlights the significant impact of morphological factors on LC deformations during eye movements, with key morphological effects being more pronounced than tissue stiffnesses.

bioengineering↗

bioRxiv2023

Integrated Transcriptomic and Metabolomic Profiling of Sheep Ovarian Tissues Confer their association in Fecundity associated Pathways

BackgroundLow fertility is considered the major constraint in sheep rearing industry depending on several factors like, estrus cycle, ovulation rate and litter size but fecundity of ewe plays a key role in sheep reproduction, influenced by several intrinsic and extrinsic factors. However, genetic improvements of traits associated with reproduction through conventional breeding is a very complex and slow process. In current study, we went through a comprehensive integration of high throughput transcriptomic and metabolomics approaches to understand the role of key regulatory genes and metabolites in fecundity of two different and widely raised sheep breeds (Small Tail Han & Dolang) in different regions of China. ResultUPLC/MS/MS system based metabolomic profiling of ovarian tissue from both breeds results into the identification of 1,423 metabolites, including 542 DEMs (379 upregulated and 163 downregulated). Integration of metabolomics and transcriptomics data identified 48 pathways contributed by 37 genes and 85 metabolites through regulatory network analysis. Functional enrichment analysis showed significantly enriched pathways associated with fecundity including Riboflavin metabolism, xenobiotics, bile acid biosynthesis, and Drug metabolism, which produces hormones for regulation of ovarian function, ovulation, and establishment of pregnancy. Further, analyzed two restrictive constrained plots analyzed via multivariate statistical analysis. In one plot complement component C3 associated with Leukotriene D4, and Uridine 5-diphosphate involved in the processes of Neuroactive legend receptor interaction pathway and in second plot IFNGR1 associated with Progesterone, Fumaric acid, and Cortisone involved in the processes of cancer pathway and any disruptions in hormonal balance may induce cancer, which can affect fertility, menstrual cycles, and overall reproductive health. ConclusionExpression profiling, functional enrichments, co-expression network analysis and integrated transcriptomemetabolome data showed gene-metabolite association in energy metabolism, Inflammation, and drug metabolism, all of which play a role in ovarian physiology and ovarian metabolic disorders. Identification and validation of genes, metabolites, and gene-metabolite interactions will help to elucidate the regulatory mechanisms and pathways underlying sheep fecundity and could be leveraged to improve reproductive traits. Graphical Abstract: Scheme of Study O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=190 SRC="FIGDIR/small/572136v1_ufig1.gif" ALT="Figure 1"> View larger version (119K): org.highwire.dtl.DTLVardef@12a42b7org.highwire.dtl.DTLVardef@182169forg.highwire.dtl.DTLVardef@19b2ed4org.highwire.dtl.DTLVardef@11f9eab_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2023

Single cell sequencing as a general variant interpretation assay

The human genome contains [~]70 million possible protein-altering variants, the vast majority of which are of uncertain clinical significance. Closing this gap is essential for accurate diagnosis of disease-causing variants and understanding their mechanisms of action. Towards this goal, we developed a pooled perturbation approach combining saturation mutagenesis with single cell RNA sequencing to map the effects of every single nucleotide variant in a gene. We sequenced [~]440,000 cells expressing variants in CDKN2A (p16INK4a), TP53, and SOD1, observing almost all possible protein-coding variants, with a mean of 61 cells per variant. Using single cell gene expression signatures, we show that each gene may contain multiple types of pathogenic variants that affect distinct downstream pathways. We demonstrate that single cell expression signatures outperform existing bulk experimental assays and computational models for predicting pathogenicity, and summarize both the utility and potential limitations of single cell sequencing as a general variant interpretation assay.

genomics↗

bioRxiv2023

scELMo: Embeddings from Language Models are Good Learners for Single-cell Data Analysis

Various Foundation Models (FMs) have been built based on the pre-training and fine-tuning framework to analyze single-cell data with different degrees of success. In this manuscript, we propose a method named scELMo (Single-cell Embedding from Language Models), to analyze single-cell data that utilizes Large Language Models (LLMs) as a generator for both the description of metadata information and the embeddings for such descriptions. We combine the embeddings from LLMs with the raw data under the zero-shot learning framework to further extend its function by using the fine-tuning framework to handle different tasks. We demonstrate that scELMo is capable of cell clustering, batch effect correction, and cell-type annotation without training a new model. Moreover, the fine-tuning framework of scELMo can help with more challenging tasks including in-silico treatment analysis or modeling perturbation. scELMo has a lighter structure and lower requirements for resources. Our method also outperforms recent large-scale FMs (such as scGPT [1], Geneformer [2]) and other LLM-based single-cell data analysis pipelines (such as GenePT [3] and GPTCelltype [4]) based on our evaluations, suggesting a promising path for developing domain-specific FMs.

bioinformatics↗

bioRxiv2023

Adaptive Regularized Tri-Factor Non-Negative Matrix Factorization for Cell Type Deconvolution

Accurate deconvolution of cell types from bulk gene expression is crucial for understanding cellular compositions and uncovering cell-type specific differential expression and physiological states of diseased tissues. Existing deconvolution methods have limitations, such as requiring complete cellular gene expression signatures or neglecting partial biological information. Moreover, these methods often overlook varying cell-type mRNA amounts, leading to biased proportion estimates. Additionally, they do not effectively utilize valuable reference information from external studies, such as means and ranges of population cell-type proportions. To address these challenges, we introduce an Adaptive Regularized Tri-factor non-negative matrix factorization approach for deconvolution (ARTdeConv). We rigorously establish the numerical convergence of our algorithm. Through benchmark simulations, we demonstrate the superior performance of ARTdeConv compared to state-of-the-art semi-reference-based and reference-free methods. In a real-world application, our method accurately estimates cell proportions, as evidenced by the nearly perfect Pearsons correlation between ARTdeConv estimates and flow cytometry measurements in a dataset from a trivalent influenza vaccine study. Moreover, our analysis of ARTdeConv estimates in COVID-19 patients reveals patterns consistent with important immunological phenomena observed in other studies. The proposed method, ARTdeConv, is implemented as an R package and can be accessed on GitHub for researchers and practitioners.

bioinformatics↗

bioRxiv2023

Wearable Disposable Electrotherapy

We design and validate a novel electrotherapy platform without electronic components, using printed abundant, environmentally benign materials. Whereas existing electrotherapy devices use an independent power source and electronics to generate and control stimulation currents, our design eliminates the need for these components. Device production relies only on scalable additive manufacturing and common materials, minimizing cost and environmental impact. The disposable single-use platform (as discreet as adhesive bandages) is activated simply by placement on the body. A prescribed electrotherapy discharge is regulated by a flexible 3D electrochemical architecture tailored to each application by a novel operational theory. The single-dose usability of this platform is a categorical shift from existing approaches with durable equipment that require programming and assembly to disposable electrodes for each use. Our Wearable Disposable Electrotherapy technology can be distributed like pharmacotherapy, with indications spanning neuromodulation of brain disorders, wound healing, transcutaneous drug delivery, bioelectronic medicine, and aesthetics.

bioengineering↗

bioRxiv2023

A mitochondria-regulated p53-CCF circuit integrates genome integrity with inflammation

Genomic instability and inflammation are distinct hallmarks of aging, but the connection between them is poorly understood. Understanding their interrelationship will help unravel new mechanisms and therapeutic targets of aging and age-associated diseases. Here we report a novel mechanism directly linking genomic instability and inflammation in senescent cells through a mitochondria-regulated molecular circuit driven by p53 and cytoplasmic chromatin fragments (CCF). We show, through activation or inactivation of p53 by genetic and pharmacologic approaches, that p53 suppresses CCF accumulation and the downstream inflammatory senescence-associated secretory phenotype (SASP), without affecting cell cycle arrest. p53 activation suppressed CCF formation by promoting DNA repair, and this is reflected in maintenance of genomic integrity, particularly in subtelomeric regions, as shown by single cell genome resequencing. Activation of p53 in aged mice by pharmacological inhibition of MDM2 reversed signatures of aging, including age- and senescence-associated transcriptomic signatures of inflammation and age-associated accumulation of monocytes and macrophages in liver. Remarkably, mitochondria in senescent cells suppressed p53 activity by promoting CCF formation and thereby restricting ATM-dependent nuclear DNA damage signaling. These data provide evidence for a mitochondria-regulated p53 signaling circuit in senescent cells that controls DNA repair, genome integrity, and senescence- and age-associated inflammation. This pathway is immunomodulatory in mice and a potential target for healthy aging interventions by small molecules already shown to activate p53.

cell biology↗

bioRxiv2023

Utility of T1 mapping and T2 mapping for non-invasive assessment of liver fibrosis: preclinical results

ObjectiveTo explore the potential of T1 and T2 mappings in assessing liver fibrosis (LF) and investigate the relationships between MRI and liver fibrogenesis markers. Materials and methods A total of 39 male C57BL/6 mice were divided into the control group (n = 9) and the model group (n = 10 per subgroup) with carbon tetrachloride (CCl4) administration for 2, 4, and 6 weeks. The METAVIR system (F0-4) was performed to stage fibrosis. MRI T1 and T2 mappings were performed and T1, and T2 values were calculated. One-way analysis of variance (ANOVA), Spearmans rank correlation analysis, and receiver operating characteristic (ROC) curves were performed. ResultsT1 and T2 values increased with progressing severity of fibrosis induction (P < 0.01). T1 and T2 were significantly correlated with LF stages ({rho} = 0.854, 0.697, P < 0.001). The area under the curves (AUCs) range of T1 and T2 for predicting [≥]F1, [≥]F2, [≥]F3, and F4 were 0.842-0.994 and 0.808-0.883, respectively. T1 and T2 showed moderate to strong correlations with collagen-associated protein and inflammatory factors. DiscussionT1 and T2 mappings can evaluate and differentiate LF stages in the CCl4-induced model. T1 is better correlated with collagen deposition and inflammation of LF than T2.

bioengineering↗

bioRxiv2023

Resting state global brain activity induces bias in fMRI motion estimates

Head motion is a significant source of artifacts in resting-state fMRI (rsfMRI) studies and has been shown to affect resting-state functional connectivity (rsFC) measurements. In many rsfMRI studies, motion parameters estimated from volume registration are used to characterize head motion and to mitigate motion artifacts in rsfMRI data. While prior task-based fMRI studies have shown that task-evoked brain activations may induce temporally correlated bias in the motion estimates, resulting in artificial activations after registration, relatively little is known about neural-related bias in rsfMRI motion parameters. In this study, we demonstrate that neural-related bias exists in rsfMRI motion estimates and characterize the potential effects of the bias on rsFC estimates. Using a public multi-echo rsfMRI dataset, we use the differences between motion estimates from the first echo and second echo data as a measure of neural-induced bias. We show that the resting-state global activity of the brain, as characterized with the global signal (GS), induces bias in the motion estimates in the y- and z-translational axes. Furthermore, we demonstrate that the GS-related bias reflects superior-inferior and anterior-posterior asymmetries in the GS beta coefficient map. Finally, we demonstrate that regression with biased motion estimates can negatively bias rsFC estimates and also reduce rsFC differences between young and old subjects.

neuroscience↗

bioRxiv2023

Evaluation of chromosome structure modelling tools in bacteria

The three-dimensional (3D) structure of bacterial chromosomes is crucial for understanding chromosome function. With the growing availability of high-throughput chromosome conformation capture (3C/Hi-C) data, the 3D structure reconstruction algorithms have become powerful tools to study bacterial chromosome structure and function. It is highly desired to have a recommendation on the chromosome structure reconstruction tools to facilitate the prokaryotic 3D genomics. In this work, we review existing chromosome 3D structure reconstruction algorithms and classify them based on their underlying computational models into two categories: constraint-based modeling and thermodynamics-based modeling. We briefly compare these algorithms utilizing 3C/Hi-C datasets and fluorescence microscopy data obtained from Escherichia coli and Caulobacter crescentus, as well as simulating datasets. We discuss current challenges in the 3D reconstruction algorithms for bacterial chromosomes, primarily focusing on software usability. Finally, we briefly prospect future research directions for bacterial chromosome structure reconstruction algorithms.

bioinformatics↗

bioRxiv2023

Microglia facilitate and stabilize the response to general anesthesia

General anesthesia leads to a loss of consciousness and an unarousable state in patients. Although general anesthetics are widely used in clinical practice, their underlying mechanisms remain elusive. The potential involvement of nonneuronal cells is unknown. Microglia are important immune cells in the central nervous system (CNS) that play critical roles in CNS function and dysfunction. We unintentionally observed delayed anesthesia induction and early anesthesia emergence in microglia-depleted mice. We found that microglial depletion differentially regulates neuronal activities by suppressing the neuronal network of anesthesia-activated brain regions and activating emergence-activated brain regions. Thus, microglia facilitate and stabilize the anesthesia status. This influence is not mediated by dendritic spine plasticity. Instead, it relies on the activation of microglial P2Y12 and subsequent calcium influx, which facilitates the general anesthesia response. Together, we elucidate the regulatory role of microglia in general anesthesia, extending our knowledge of how nonneuronal cells modulate neuronal activities.

neuroscience↗

bioRxiv2023

From sensory to perceptual manifold: the twist of neural geometry

Classification constitutes a core cognitive challenge for both biological and artificial intelligence systems, with many tasks potentially reducible to classification problems. Here we investigated how the brain categorizes stimuli that are not linearly separable in the physical world by analyzing the geometry of neural manifolds in high-dimensional neural space, formed by macaques V2 neurons during a classification task on the orientations of motion-induced illusory contours. We identified two related but distinct neural manifolds in this high-dimensional neural space: the sensory and perceptual manifolds. The sensory manifold was embedded in a 3-D subspace defined by three stimulus features, where contour orientations remained linearly inseparable. However, through a series of geometric transformations equivalent to twist operations, this 3-D sensory manifold evolved into a 7-D perceptual manifold with four additional axes, enabling the linear separability of contour orientations. Both formal proof and computational modeling revealed that this dimension expansion was facilitated by nonlinear mixed selectivity neurons exhibiting heterogeneous response profiles. These findings provide insights into the mechanisms by which biological neural networks increase the dimensionality of representational spaces, illustrating how perception arises from sensation through the lens of neural geometry.

neuroscience↗

bioRxiv2023

Pan-genome of pear provides insights into the differentiation of fruit quality traits between Asian and European pears

The pear (Pyrus spp.) is a remarkable fruit, well known for its diverse flavors, textures, culinary versatility, and global horticultural importance. However, the genetic diversity responsible for its extensive phenotypic variations remains largely unexplored. Here, we de novo assembled and annotated the genomes of the maternal (PsbM) and paternal (PsbF) lines of the hybrid Yuluxiang pear and constructed the first pear pangenome of 1.15Gb by combining these two genomes with five previously published pear genomes. Using the constructed pangenome, we identified 21,224 gene PAVs and 1,158,812 SNPs in the non-reference genome that were absent in the PsbM reference genome. Compared with SNP markers, we found that PAV-based analysis provides additional insights into the pear population structure. In addition, we also revealed that some genes associated with pear fruit quality traits have differential occurrence frequencies and differential gene expression between Asian and European populations. Moreover, our analysis of the pear pangenome revealed a mutated SNP and an insertion in the promoter region of the gene PsbMGH3.1 potentially enhances sepal shedding in Xuehuali which is vital for pear quality. This research helps further capture the genetic diversity of pear populations and provides valuable genomic resources for accelerating pear breeding.

genomics↗

bioRxiv2023

Reconciling ASPP-p53 Binding Mode Discrepancies through an Ensemble Binding Framework that Bridges Crystallography and NMR Data

ASPP2 and iASPP bind to p53 through their conserved ANK-SH3 domains to respectively promote and inhibit p53-dependent cell apoptosis. While crystallography has indicated that these two proteins employ distinct surfaces of their ANK-SH3 domains to bind to p53, solution NMR data has suggested similar surfaces. In this study, we employed multi-scale molecular dynamics (MD) combined with free energy calculations to reconcile the discrepancy in the binding modes. We demonstrated that the binding mode based solely on a single crystal structure does not enable iASPPs RT loop to engage with p53s C-terminal linker--a verified interaction. Instead, an ensemble of simulated iASPP-p53 complexes facilitates this interaction. We showed that the ensemble-average inter-protein contacting residues and NMR-detected interfacial residues align well with ASPP proteins, and the ensemble-average binding free energies better match experimental Kd values compared to single crystallgarphy-determined binding mode. For iASPP, the sampled ensemble complexes can be grouped into two classes, resembling the binding modes determined by crystallography and solution NMR. We thus propose that crystal packing shifts the equilibrium of binding modes towards the crystallographydetermined one. Lastly, we show that the ensemble binding complexes are sensitive to p53s intrinsically disordered regions (IDRs), attesting to experimental observations that these IDRs contribute to biological functions. Our results provide a dynamic and ensemble perspective for scrutinizing these important cancer-related protein-protein interactions (PPIs).

biophysics↗