Biology subjects

Li, B.

Publications and source records attributed to Li, B..

At least 397 records · Page 22Linked to original sources

bioRxiv2022

A large-scale brain network of species-specific dynamic human body perception

This ultrahigh field 7T fMRI study addressed the question of whether there exists a core network of brain areas at the service of different aspects of body perception. Participants viewed naturalistic videos of monkey and human faces, bodies, and objects along with mosaic-scrambled videos for control of low-level features. ICA-based network analysis was conducted to find body and species modulations at both the voxel and the network levels. Among the body areas, the highest species selectivity was found in the middle frontal gyrus and amygdala. Two large-scale networks were highly selective to bodies, dominated by the lateral occipital cortex and right superior temporal sulcus (STS) respectively. The right STS network showed high species selectivity, and its significant human body-induced node connectivity was focused around the extrastriate body area (EBA), STS, temporoparietal junction (TPJ), premotor cortex, and inferior frontal gyrus (IFG). The human body-specific network discovered here may serve as a brain-wide internal model of the human body serving as an entry point for a variety of processes relying on body descriptions as part of their more specific categorization, action, or expression recognition functions.

neuroscience↗

bioRxiv2022

Integrated single-cell sequencing analysis reveals peripheral immune landscape across the human lifespan

Systematic understanding of immune dynamics across the entire human lifespan at single-cell resolution is currently lacking. Here, we performed single-cell RNA sequencing (scRNA-seq) and single-cell T cell receptor (TCR)/B cell receptor (BCR) sequencing (scTCR/BCR-seq) on over 380,000 peripheral blood mononuclear cells collected from 45 healthy participants aged 0 to over 90 years. We revealed that the functions of T cell subsets were most susceptible to senescence among all PBMCs, featured by increased NF-{kappa}B signaling and IFN-{gamma} responses pathways, while reduced telomere maintenance and energy metabolism. We subsequently explored the rewiring of cell-cell interactions among different immune cells across the lifespan and revealed the major alteration of immune checkpoints in T cells within the cellular interaction networks. By combined analysis of scRNA-seq and scTCR-seq, we revealed that 1) GNLY+ CD8 Effector T cells exhibited a high clonal expansion with distinct functional signatures in children and the elderly; 2) Naive CD4+ T and naive CD8+ T cells displayed different aging patterns in both transcriptomes and immune repertoires; and 3) CD8+ MAIT cells showed a higher cell abundance and clonal diversity in adolescents. Furthermore, we identified a unique cytotoxic B cell subset enriched in children by scRNA-seq and scBCR-seq analysis and experimental validations. In summary, our work provided valuable insights and rich resources for understanding the development and aging of the human immune system across the lifespan.

immunology↗

bioRxiv2022

MB-SupCon: Microbiome-based predictive models via Supervised Contrastive Learning

Human microbiome consists of trillions of microorganisms. Microbiota can modulate the host physiology through molecule and metabolite interactions. Integrating microbiome and metabolomics data have the potential to predict different diseases more accurately. Yet, most datasets only measure microbiome data but without paired metabolome data. Here, we propose a novel integrative modeling framework, Microbiome-based Supervised Contrastive Learning Framework (MB-SupCon). MB-SupCon integrates microbiome and metabolome data to generate microbiome embeddings, which can be used to improve the prediction accuracy in datasets that only measure microbiome data. As a proof of concept, we applied MB-SupCon on 720 samples with paired 16S microbiome data and metabolomics data from patients with type 2 diabetes. MB-SupCon outperformed existing prediction methods and achieves high average prediction accuracies for insulin resistance status (84.62%), sex (78.98%), and race (80.04%). Moreover, the microbiome embeddings form separable clusters for different covariate groups in the lower-dimensional space, which enhances data visualization. We also applied MB-SupCon on a large inflammatory bowel disease study and observed similar advantages. Thus, MB-SupCon could be broadly applicable to improve microbiome prediction models in multi-omics disease studies.

bioinformatics↗

bioRxiv2022

Membrane curvature governs the distribution of Piezo1 in cellulo

Piezo1 is a bona fide mechanosensitive ion channel ubiquitously expressed in mammalian cells. The distribution of Piezo1 within a cell is essential for various biological processes including cytokinesis, cell migration, and wound healing. However, the underlying principles that guide the subcellular distribution of Piezo1 remain largely unexplored. Here, we demonstrate that membrane curvature serves as a key regulator of the spatial distribution of Piezo1 in the plasma membrane of living cells. Piezo1 depletes from highly curved membrane protrusions such as filopodia and enriches to nanoscale membrane invaginations. Quantification of the curvaturedependent sorting of Piezo1 directly reveals the in situ nano-geometry of the Piezo1-membrane complex. Piezo1 density on filopodia increases upon activation, independent of Ca2+, suggesting flattening of the channel upon opening. Consequently, the expression of Piezo1 inhibits filopodia formation, an effect that diminishes with channel activation.

biophysics↗

bioRxiv2022

Synaptic homeostasis transiently leverages Hebbian mechanisms for a multiphasic response to inactivity

Neurons use various forms of negative feedback to maintain their synaptic strengths within an operationally useful range. While this homeostatic plasticity is thought to distinctly counteract the destabilizing positive feedback of Hebbian plasticity, there is considerable overlap in the molecular components mediating both forms of plasticity. The varying kinetics of these components spurs additional inquiry into the dynamics of synaptic homeostasis. We discovered that upscaling of synaptic weights in response to prolonged inactivity is nonmonotonic. Surprisingly, this seemingly oscillatory adaptation involved transient appropriation of molecular effectors associated with Hebbian plasticity, namely CaMKII, L-type Ca2+ channels, and Ca2+-permeable AMPARs, and homeostatic elements such as calcineurin. We created a dynamic model that shows how traditionally "Hebbian" and "homeostatic" mechanisms can cooperate to autoregulate postsynaptic Ca2+ levels. We propose that this combination of mechanisms allows excitatory synapses to adapt to prolonged activity changes and safeguard the capability to undergo future strengthening on demand.

neuroscience↗

bioRxiv2022

T cell receptor convergence is an indicator of antigen-specific T cell response in cancer immunotherapies

T cells are potent at eliminating pathogens and playing a crucial role in the adaptive immune response. T cell receptor (TCR) convergence describes T cells that share identical TCRs with the same amino acid sequences but have different DNA sequences due to codon degeneracy. We conducted a systematic investigation of TCR convergence using single-cell immune profiling and bulk TCR{beta}-sequence (TCR-seq) data obtained from both mouse and human samples, and uncovered a strong link between antigen-specificity and convergence. This association was stronger than T cell expansion, a putative indicator of antigen-specific T cells. By using flow sorted tetramer+ single T cell data, we discovered that convergent T cells were enriched for a neoantigen-specific CD8+ effector phenotype in the tumor microenvironment. Moreover, TCR convergence demonstrated better prediction accuracy for immunotherapy response than the existing TCR repertoire indexes. In conclusion, convergent T cells are likely to be antigen-specific and might be a novel prognostic biomarker for anti-cancer immunotherapy.

bioinformatics↗

bioRxiv2022

Endothelial TET2 Regulates Cardiac Remodeling by Modifying Endothelial-to-Mesenchymal Transition

DNA methylation modification has been proved to play an important role in heart diseases. In this study, the role of Ten-Eleven Translocation-2 (TET2), which is a key demethylation enzyme, is investigated in cardiac remodeling. TET2 is abundant in endothelial cells but decreased in hypertrophic hearts. TET2 knockdown in endothelial cells triggers endothelial-to-mesenchymal transition (EndMT), while overexpression of TET2 inhibits the EndMT. In vivo, Cdh5-CreERT2/TET2flox/flox; Rosa26-mTmG+/- mice are developed and undergo transverse aortic constriction (TAC) subsequently to induce pathological cardiac hypertrophy model. Hearts of Cdh5-CreERT2/TET2flox/flox mice show more severe hypertrophy and fibrosis than controls in the TAC model. Furthermore, EGLN3 is identified to participate in EndMT as the downstream target of TET2 by using RNA sequencing and whole-genome bisulfite sequencing (WGBS). Finally, vitamin C, which can mimic TET2 restoration, is found to partially improve cardiac function and inhibit myocardial fibrosis. These insights into how TET2 alleviates cardiac fibrosis may open new avenues for treating cardiac remodeling in the future.

genetics↗

bioRxiv2022

Redefining and subtyping of major depression based on brain functional connectivity signatures with high generalization: an ensemble hybrid framework

Current clinical diagnosis of major depression is solely based on subjective symptoms and signs rather than the underlying biological mechanisms, which has hindered the improvement in treatment effectiveness and outcomes. Redefining and subtyping major depressive disorder (MDD) based on neural circuits has been an emerging consensus. Here, we proposed a novel ensemble hybrid deep-learning framework based on graph neural network for redefining and subtyping of MDD with the brains "fingerprinting", i.e. nuanced functional connectivity profiles. A graph neural network (GNN) based supervised model was first employed to discriminate MDD patients from healthy controls. The graph embedding features obtained from the supervised classifier was then employed for subtyping of MDD with an unsupervised clustering by fast search and find of density peaks (CFDP) approach. The generalization accuracy and reproducibility of the proposed framework were further validated with one of the largest resting-state fMRI data set for MDD which included 2428 participants recruited from 25 independent sites. Our classifier showed a high generalization of 75% for leave-one-site-out cross validation. In addition, we obtained three biologically homogenous MDD subtypes characterized by impairments in subcortical-limbic, DMN-FPN, VN-SMN circuits, respectively. Notably, we demonstrated that subtyping of MDD according to graph embedding features showed high robustness and reproducibility across different sites. The proposed framework is not only essential for redefining and subtyping of MDD, but also paves the way towards precision medicine of mental disorders.

neuroscience↗

bioRxiv2022

A common mechanism of temperature-sensing in thermoTRP channels

Detecting temperature is crucial for the survival of living organisms. Though the thermo transient receptor potential (thermoTRP) channels, such as TRPV1 or TRPM8, have been identified as prototypic heat or cold sensors, respectively, how they detect temperature remains elusive. Here we first identified groups of clustered residues in these channels that undergo burial/exposure conformational rearrangements during temperature activation by analyzing available protein structures or hydroxyl radical footprinting-mass spectroscopy (HRF-MS). By systematically perturbing water-protein interactions at these residues, we found that the temperature sensitivity in these channels were modulated in accordance with the sidechain hydrophobicity. The changes in energy associated with changes in water-protein interactions were sufficient for thermo activation. Therefore, our study has established that the water-protein interactions as a common mechanism underlying temperature sensing in TRPM8 and TRPV1.

biophysics↗

bioRxiv2022

Differential regulation of mRNA stability modulates transcriptional memory and facilitates environmental adaptation

Transcriptional memory, by which cells respond faster to repeated stimuli, is key for cellular adaptation and organism survival. Factors related to chromatin organization and activation of transcription have been shown to play a role in the faster response of those cells previously exposed to a stimulus (primed). However, the contribution of post-transcriptional regulation is not yet explored. Here, combining flow cytometry and high throughput sequencing, we perform a genome-wide screen to identify novel factors modulating transcriptional memory in S. cerevisiae in response to galactose nutrition sources. In addition to the well-known chromatin factors modulating transcriptional memory, we find that depletion of the nuclear RNA exosome increases GAL1 expression in primed cells. We perform a genome-wide characterisation of this process and show that changes in nuclear surveillance factor association can enhance both gene induction and repression in primed cells. Finally, we show that in addition to nuclear mRNA degradation, differences in cytoplasmic mRNA decay also modulate transcriptional memory and contribute to faster gene expression remodelling in primed cells. Our results demonstrate that mRNA post-transcriptional regulation, and not only transcription regulation, should be considered when investigating gene expression memory.

genomics↗

bioRxiv2022

Leishmania allelic selection during experimental sand fly infection correlates with mutational signatures of oxidative DNA damage

Trypanosomatid pathogens are transmitted by blood-feeding insects, causing devastating human infections. Survival of these parasites in their vertebrate and invertebrate hosts relies on their capacity to differentiate into distinct stages that are the result of a co-evolutionary process. These stages show in addition important phenotypic shifts that often impacts infection, affecting for example parasite pathogenicity, tissue tropism, or drug susceptibility. Despite their clinical relevance, the evolutionary mechanisms that allow for the selection of such adaptive phenotypes remain only poorly investigated. Here we use Leishmania donovani as a trypanosomatid model pathogen to shed first light on parasite evolutionary adaptation during experimental sand fly infection. Applying a comparative genomics approach on hamster- isolated amastigotes and derived promastigotes before (input) and after (output) infection of Phlebotomus orientalis revealed a strong bottleneck effect on the parasite population as judged by principal component and phylogenetic analyses of input and output parasite DNA sequences. Despite random genetic drift caused by the bottleneck effect, our analyses revealed various genomic signals that seem under positive selection given their convergence between independent biological replicates. While no significant fluctuations in gene copy number were revealed between input and output parasites, convergent selection was observed for karyotype, haplotype and allelic changes during sand fly infection. Our analyses further uncovered signature mutations of oxidative DNA damage in the output parasite genomes, suggesting that Leishmania suffers from oxidative stress inside the insect digestive tract. Our results propose a new model of Leishmania genomic adaptation during sand fly infection, where oxidative DNA damage and DNA repair processes drive haplotype and allelic selection. The experimental and computational framework presented here provides a useful blueprint to assess evolutionary adaptation of other eukaryotic pathogens inside their insect vectors, such as Plasmodium spp, Trypanosoma brucei and Trypanosoma cruzi.

evolutionary biology↗

bioRxiv2022

Separation of phosphatase and kinase activity within the Bub complex is required for proper mitosis

The Bub1 and BubR1 kinetochore proteins support proper chromosome segregation and mitotic checkpoint activity. Bub1 and BubR1 are paralogues with Bub1 being a kinase while BubR1 localizes the PP2A-B56 protein phosphatase to kinetochores in humans. Whether this separation of kinase and phosphatase activity is important is unclear as some organisms integrate both activities into one Bub protein. Here we engineer human Bub1 and BubR1 proteins integrating kinase and phosphatase activities into one protein and show that these do not support normal mitotic progression. A Bub1-PP2A-B56 complex can supports chromosome alignment but results in impairment of the checkpoint due to dephosphorylation of the Mad1 binding site in Bub1. Furthermore, a chimeric BubR1 protein containing the Bub1 kinase domain induces delocalized H2ApT120 phosphorylation resulting in reduction of centromeric hSgo2 and chromosome segregation errors. Collectively, these results argue that the separation of kinase and phosphatase activities within the Bub complex is required for balancing its functions in the checkpoint and chromosome alignment.

cell biology↗

bioRxiv2022

LTD-inducing low frequency stimulation enhances p-Tau181 and p-Tau217 in an age-dependent manner in live rats

The progressive cognitive decline in Alzheimers disease (AD) patients correlates with the extent of tau pathology, in particular tau hyperphosphorylation, which is strongly age-associated. Although elevation of phosphorylated tau (p-Tau) on residues Thr181 (p-Tau181), Thr217 (p-Tau217), and Thr231 (p-Tau231) in cerebrospinal fluid or blood are recently proposed to be particularly sensitive markers of early AD, the generation of p-Tau during brain activity is poorly understood. A major form of synaptic plasticity, long-term depression (LTD), has recently been linked to the enhancement of tau phosphorylation. Here we show that low frequency stimulation (LFS), used to induce LTD, enhances p-Tau181 and p-Tau217 in an age-dependent manner in the hippocampus of live rats. In contrast, phosphorylation at residues Thr231, Ser202/Thr205, and Ser396 is less sensitive to LFS. Pharmacological antagonism of either NMDA or metabotropic glutamate 5 (mGluR5) receptors inhibits the elevation of both p-Tau181 and p-Tau217. Targeting ageing with a small molecule cognitive enhancer ISRIB (trans-isomer) prevents the enhancement of p-Tau by LFS in aged rats. Together, our data provide an in vivo means to uncover brain plasticity-related cellular and molecular processes of tau phosphorylation in health and ageing conditions.

neuroscience↗

bioRxiv2022

Safety assessment of insecticidal proteins: A case study utilizing His-tagged protein to determine the safety of Mpp75Aa1.1, a new ETX_MTX2 protein that controls western corn rootworm

The recently discovered insecticidal protein Mpp75Aa1.1 from Brevibacillus laterosporus is one member of the ETX_MTX family of beta-pore forming proteins ({beta}-PFPs) expressed in genetically modified (GM) maize to control western corn rootworm (WCR; Diabrotica virgifera virgifera LeConte). In this paper, bioinformatic analysis establishes that although Mpp75Aa1.1 shares varying degrees of similarity to members of the ETX_MTX2 protein family, it is unlikely to contribute to any allergenic, toxic, or otherwise adverse biological effects. The safety of Mpp75Aa1.1 is further supported by a weight of evidence including evaluation of history of safe use (HOSU) of ETX_MTX2 proteins. Assessments using either purified Mpp75Aa1.1 protein or a poly-histidine-tagged (His-tagged) variant of the Mpp75Aa1.1 protein demonstrate that both forms of the protein are heat labile at temperatures at or above 55 {degrees}C, degraded by gastrointestinal proteases within 0.5 min, and have no adverse effects in acute mouse oral toxicity studies at a dose level of 1920 or 2120 mg/kg body weight. Results also indicate that the domain-based protein characterization should be considered as part of the weight of evidence for the safe consumption of food or feed. Furthermore, these results support the use of His-tagged proteins as suitable surrogates for assessing the safety of their non-tagged parent proteins.

pharmacology and toxicology↗

bioRxiv2022

Inter-brain coupling reflects disciplinary differences in real-world classroom learning

Classroom is the primary site for learning. One important feature of classroom learning is its organization into different disciplines. While disciplinary differences could substantially influence students learning processes, little is known about the neural mechanism underlying successful disciplinary learning. In the present study, wearable EEG devices were used to record a group of high school students during their classes of a soft (Chinese) and a hard (Math) discipline throughout one semester. The students with higher learning outcomes in Chinese were found to have better inter-brain neural couplings with their excellent peers, whereas the students with higher Math outcomes were found to have better couplings with the class average. Moreover, the inter-brain couplings showed distinct dominant frequencies for the two disciplines. Our results illustrate disciplinary differences in successful learning from an inter-brain perspective and suggest the neural activities of excellent peers and class average as exemplars for soft and hard disciplines. TeaserSuccessful classroom learning is associated with distinct inter-brain coupling patterns for soft and hard disciplines

neuroscience↗

bioRxiv2022

Establishing a reproducible approach for the controllable deposition and maintenance of plants cells with 3D bioprinting

Capturing cell-to-cell and cell-to-environment signals in a defined 3 dimensional (3D) microenvironment is key to study cellular functions, including cellular reprogramming towards tissue regeneration. A major challenge in current culturing methods is that these methods cannot accurately capture this multicellular 3D microenvironment. In this study, we established the framework of 3D bioprinting with plant cells to study cell viability, cell division, and cell identity. We established long-term cell viability for bioprinted Arabidopsis root cells and soybean meristematic cells. To analyze the large image datasets generated during these long-term viability studies, we developed an open source high-throughput image analysis pipeline. Furthermore, we showed the cell cycle re-entry of the isolated Arabidopsis and soybean cells leading to the formation of microcalli. Finally, we showed that the identity of isolated cells of Arabidopsis roots expressing endodermal markers maintained longer periods of time. The framework established in this study paves the way for a general use of 3D bioprinting for studying cellular reprogramming and cell cycle re-entry towards tissue regeneration.

plant biology↗

bioRxiv2022

Novel Murine models of Mania and Depression

Neuropathological mechanisms triggering manic syndrome or manic episodes in bipolar disorder remain poorly characterised, as the research progress is severely limited by the paucity of appropriate animal models. Here we developed a novel manic mice model by combining a series of chronic unpredictable rhythm disturbances (CURD), which include disruption of circadian rhythm, sleep deprivation, exposure to cone light, with subsequent interference of followed spotlight, stroboscopic illumination, high temperature stress, noise disturbance and foot shock. To validate this novel manic model, we used multiple behavioural and cell biology approaches comparing the CURD-model with healthy controls and depressed mice. The depression model was created by an exposure to an improved chronic unpredictable mild stress, which we defined as chronic unpredictable mild restraint (CUMR). A novel manic mice model induced by environmental stressors and free from genetic or pharmacological interventions will benefit research into pathological mechanisms of mania.

animal behavior and cognition↗

bioRxiv2022

A Geometric View of Signal Sensitivity Metrics in multi-echo fMRI

In multi-echo fMRI (ME-fMRI), two metrics have been widely used to measure the performance of various acquisition and analysis approaches. These are temporal SNR (tSNR) and differential contrast-to-noise ratio (dCNR). A key step in ME-fMRI is the weighted combination of the data from multiple echoes, and prior work has examined the dependence of tSNR and dCNR on the choice of weights. However, most studies have focused on only one of these two metrics, and the relationship between the two metrics has not been examined. In this work, we present a geometric view that offers greater insight into the relation between the two metrics and their weight dependence. We identify three major regimes: (1) a tSNR robust regime in which tSNR is robust to the weight selection with most weight variants achieving close to optimal performance, whereas dCNR shows a pronounced dependence on the weights with most variants achieving suboptimal performance; (2) a dCNR robust regime in which dCNR is robust to the weight selection with most weight variants achieving close to optimal performance, while tSNR exhibits a strong dependence on the weights with most variants achieving significantly lower than optimal performance; and (3) a within-type robust regime in which both tSNR and dCNR achieve nearly optimal performance when the form of the weights are variants of their respective optimal weights and exhibit a moderate decrease in performance for other weight variants. Insight into the behavior observed in the different regimes is gained by considering spherical representations of the weight dependence of the components used to form each metric. For multi-echo acquisitions, dCNR is shown to be more directly related than tSNR to measures of CNR and signal-to-noise ratio (SNR) for both task-based and resting-state fMRI scans, respectively.

neuroscience↗