Biology subjects

Zhan, L.

Publications and source records attributed to Zhan, L..

36 records · Page 2Linked to original sources

bioRxiv2023

Dissecting embryonic and extra-embryonic lineage crosstalk with stem cell co-culture

Faithful embryogenesis requires precise coordination between embryonic and extraembryonic tissues. Although stem cells from embryonic and extraembryonic origins have been generated for several mammalian species(Bogliotti et al., 2018; Choi et al., 2019; Cui et al., 2019; Evans and Kaufman, 1981; Kunath et al., 2005; Li et al., 2008; Martin, 1981; Okae et al., 2018; Tanaka et al., 1998; Thomson et al., 1998; Vandevoort et al., 2007; Vilarino et al., 2020; Yu et al., 2021b; Zhong et al., 2018), they are grown in different culture conditions with diverse media composition, which makes it difficult to study cross-lineage communication. Here, by using the same culture condition that activates FGF, TGF-{beta} and WNT signaling pathways, we derived stable embryonic stem cells (ESCs), extraembryonic endoderm stem cells (XENs) and trophoblast stem cells (TSCs) from all three founding tissues of mouse and cynomolgus monkey blastocysts. This allowed us to establish embryonic and extraembryonic stem cell co-cultures to dissect lineage crosstalk during early mammalian development. Co-cultures of ESCs and XENs uncovered a conserved and previously unrecognized growth inhibition of pluripotent cells by extraembryonic endoderm cells, which is in part mediated through extracellular matrix signaling. Our study unveils a more universal state of stem cell self-renewal stabilized by activation, as opposed to inhibition, of developmental signaling pathways. The embryonic and extraembryonic stem cell co-culture strategy developed here will open new avenues for creating more faithful embryo models and developing more developmentally relevant differentiation protocols.

developmental biology↗

bioRxiv2023

Enhanced simulations of whole-brain dynamics using hybrid resting-state structural connectomes

The human brain, composed of billions of neurons and synaptic connections, is an intricate network coordinating a sophisticated balance of excitatory and inhibitory activity between brain regions. The dynamical balance between excitation and inhibition is vital for adjusting neural input/output relationships in cortical networks and regulating the dynamic range of their responses to stimuli. To infer this balance using connectomics, we recently introduced a computational framework based on the Ising model, first developed to explain phase transitions in ferromagnets, and proposed a novel hybrid resting-state structural connectome (rsSC). Here, we show that a generative model based on the Kuramoto phase oscillator can be used to simulate static and dynamic functional connectomes (FC) with rsSC as the coupling weight coefficients, such that the simulated FC well aligns with the observed FC when compared to that simulated with traditional structural connectome. Simulations were performed using the open source framework The Virtual Brain on High Performance Computing infrastructure.

neuroscience↗

bioRxiv2022

Large scale production of human blastoids amenable to modeling blastocyst development and maternal-fetal crosstalk

Recent advances in human blastoids generated from naive pluripotent stem cells have opened a new avenue for modelling early human development and implantation. Despite the success, however, existing protocols have several limitations, e.g., the use of custom-built microwell arrays impedes wide adoption by the research community, and mass production of human blastoids is hampered by low-output or low-efficiency methods. To address these issues, here we developed an optimized protocol based on commercially available microwell plates, which enabled efficient generation of high-fidelity human blastoids at a large scale. Leveraging on the improved protocol, we identified MAPK. PI3K/AKT and mTOR signaling pathways were activated in both blastoids and blastocyst, and discovered endometrial stromal effects in promoting trophoblast cell survival, proliferation and syncytialization during extended co-culture with blastoids. Our optimized protocol will facilitate broader use of human blastoids as an accessible, perturbable, scalable, tractable, and ethical model for human blastocysts.

developmental biology↗

bioRxiv2022

Formulation of substrates with agricultural and forestry wastes for Camellia oleifera Abel seedling cultivation

AbstractsFive compound substrates for the cultivation of Camellia oleifera Abel seedlings were obtained by substituting the peats in conventional substrate formulas with the composts of Camellia oleifera shell, pine chips, palm fiber residues, chicken manure, and sheep manure. The changes in the physical and chemical properties of the substrate after seedling cultivation were determined and the effects of these substrates on the development of Camellia oleifera seedling were analyzed. It was found that the survival rates of the one-year-old seedlings produced from stem cuttings in all groups were greater than 97.5% after 6 months cultivation. The seedlings exhibited greater seedling heights, larger ground diameters, longer root systems and larger total root volume than those obtained with conventional substrates. The compound substrate formulated with the compost of Camellia oleifera shell+ palm fiber residue+ chicken manure (A3), vermiculite and perlite (6:3:1) is the most optimal, which gives the 100% survival rate of cultivated seedlings, the greatest seedling heights, and the largest ground diameters. In particular, the ground diameters and 26.67% of the seedling heights reach the grade 1 standard for the two-year-old seedlings.

plant biology↗

bioRxiv2021

A CRISPRi/a platform in iPSC-derived microglia uncovers regulators of disease states

Microglia are emerging as key drivers of neurological diseases. However, we lack a systematic understanding of the underlying mechanisms. Here, we present a screening platform to systematically elucidate functional consequences of genetic perturbations in human iPSC-derived microglia. We developed an efficient eight-day protocol for the generation of microglia-like cells based on the inducible expression of six transcription factors. We established inducible CRISPR interference and activation in this system and conducted three screens targeting the "druggable genome". These screens uncovered genes controlling microglia survival, activation and phagocytosis, including neurodegeneration-associated genes. A screen with single-cell RNA sequencing as the readout revealed that these microglia adopt a spectrum of states mirroring those observed in human brains and identified regulators of these states. A disease-associated state characterized by SPP1 expression was selectively depleted by CSF1R inhibition. Thus, our platform can systematically uncover regulators of microglia states, enabling their functional characterization and therapeutic targeting.

neuroscience↗

bioRxiv2021

Functional characterization of splicing regulatory elements

BackgroundRNA binding protein-RNA interactions mediate a variety of processes including pre-mRNA splicing, translation, decay, polyadenylation and many others. Previous high-throughput studies have characterized general sequence features associated with increased and decreased splicing of certain exons, but these studies are limited by not knowing the mechanisms, and in particular, the mediating RNA binding proteins, underlying these associations. ResultsHere we utilize ENCODE data from diverse data modalities to identify functional splicing regulatory elements and their associated RNA binding proteins. We identify features which make splicing events more sensitive to depletion of RNA binding proteins, as well as which RNA binding proteins act as splicing regulators sensitive to depletion. To analyze the sequence determinants underlying RBP-RNA interactions impacting splicing, we assay tens of thousands of sequence variants in a high-throughput splicing reporter called Vex-seq and confirm a small subset in their endogenous loci using CRISPR base editors. Finally, we leverage other large transcriptomic datasets to confirm the importance of RNA binding proteins which we designed experiments around and identify additional RBPs which may act as additional splicing regulators of the exons studied. ConclusionsThis study identifies sequence and other features underlying splicing regulation mediated specific RNA binding proteins, as well as validates and identifies other potentially important regulators of splicing in other large transcriptomic datasets.

genomics↗

bioRxiv2021

Microglial NF-κB drives tau spreading and toxicity in a mouse model of tauopathy

Activation of microglia, the brains innate immune cells, is a prominent pathological feature in tauopathies, including Alzheimers disease. How microglia activation contributes to tau toxicity remains largely unknown. Here we show that nuclear factor kappa-light-chain-enhancer of activated B cells (NF-{kappa}B) signaling, activated by tau, drives microglial-mediated tau propagation and toxicity. Constitutive activation of microglial NF-{kappa}B exacerbated, while inactivation diminished, tau seeding and spreading in PS19 mice, consistent with the observation that NF-{kappa}B activation accelerates processing of internalized tau fibrils in primary microglia. Remarkably, inhibition of microglial NF-{kappa}B specifically also rescued tau-mediated learning and memory deficits, and restored overall transcriptomic changes while increasing tau inclusions. On a single cell level, we discovered that tau-associated disease states in microglia were diminished by NF-{kappa}B inactivation and further transformed by constitutive NF-{kappa}B activation. Our study establishes a central role for microglial NF-{kappa}B signaling in mediating tau toxicity in tauopathy.

neuroscience↗

bioRxiv2021

Treponema denticola dentilisin triggered TLR2/MyD88 activation upregulates a tissue destructive program involving MMPs via Sp1 in human oral cells

Periodontal disease is driven by dysbiosis of the oral microbiome, resulting in over-representation of species that induce the release of pro-inflammatory cytokines, chemokines, and tissue-remodeling matrix metalloproteinases (MMPs) in the periodontium. These chronic tissue-destructive inflammatory responses result in gradual loss of tooth-supporting alveolar bone. The oral spirochete Treponema denticola, is consistently found at significantly elevated levels in periodontal lesions. Host-expressed Toll-Like Receptor 2 (TLR2) senses a variety of bacterial ligands, including acylated lipopolysaccharides and lipoproteins. T. denticola dentilisin, a surface-expressed protease complex comprised of three lipoproteins has been implicated as a virulence factor in periodontal disease, primarily due to its proteolytic activity. While the role of acylated bacterial components in induction of inflammation is well-studied, little attention has been given to the potential role of the acylated nature of dentilisin. The purpose of this study was to test the hypothesis that T. denticola dentilisin activates a TLR2-dependent mechanism, leading to upregulation of tissue-destructive genes in periodontal tissue. RNA-sequencing of periodontal ligament cells challenged with T. denticola bacteria revealed a significant upregulation of genes associated with extracellular matrix organization and degradation, including tissue-specific inducible MMPs that may play novel roles in modulating host immune responses yet to be characterized within the context of oral disease. The Gram-negative oral commensal, Veillonella parvula, failed to upregulate these same MMPs. Dentilisin-induced upregulation of MMPs was mediated via TLR2 and MyD88 activation, since knockdown of either TLR2 or MyD88 abrogated these effects. Challenge with purified dentilisin upregulated the same MMPs, whereas a dentilisin-deficient T. denticola mutant had no effect. Finally, T. denticola-mediated activation of TLR2/MyD88 led to the nuclear translocation of the transcription factor Sp1, which was shown to be a critical regulator of all T. denticola-dependent MMP expression. Taken together, these data support that T. denticola dentilisin stimulates tissue-destructive cellular processes in a TLR2/MyD88/Sp1-dependent fashion. AUTHOR SUMMARYPeriodontal disease is driven by dysbiosis of the oral microbiome, which interacts with host tissues and thereby induces the release of pro-inflammatory cytokines, chemokines, and tissue-remodeling matrix metalloproteinases (MMPs), leading to destruction of the periodontal tissues. Even after clinical intervention, patients with severe periodontal disease are left with a persistent pro-inflammatory transcriptional profile throughout the periodontium. The oral spirochete, Treponema denticola, is consistently found at elevated levels in periodontal lesions and is associated with several pathophysiological effects driving periodontal disease progression. The T. denticola surface-expressed protease complex (dentilisin) has cytopathic effects consistent with periodontal disease pathogenesis. To date, few direct links have been reported between dentilisin and the cellular and tissue processes that drive periodontal tissue destruction at the transcriptional and/or epigenetic levels. Here, we utilize wild type and dentilisin-deficient T. denticola as well as purified dentilisin to characterize dentilisin-dependent activation of intracellular pathways controlling MMP expression and activity. Our results define a role for dentilisin in initiating this signal cascade. Also, our study identified tissue-specific inducible MMPs that may play novel roles in modulating as-yet uncharacterized host responses in periodontal disease. Lastly, T. denticola dentilisin stimulates tissue-destructive cellular processes in a TLR2/MyD88/Sp1-dependent fashion. Taken together, our study provides new insights into the molecular mechanisms underpinning periodontal disease progression which could lead to the development of more efficacious therapeutic treatments.

microbiology↗

bioRxiv2020

Automatic Recognition of Auditory Brainstem Response Characteristic Waveform based on BiLSTM

BackgroundAuditory brainstem response (ABR) test is widely used in newborn hearing screening and hearing disease diagnosis. Identifying and marking are challenging and repetitive tasks because of complex rules of ABR characteristic waveform and interference of background noise. MethodsThis study proposes an automatic method to recognize ABR characteristic waveform. First, binarization is created to mark 1024 sampling points accordingly. The selected characteristic area of ABR data is 0-8ms. The marking area is enlarged to expand feature information and reduce marking error. Second, a bi-directional long short-term memory (BiLSTM) network structure is established to improve relevance of sampling points, and an ABR sampling point classifier is obtained by training. Finally, mark points are obtained through thresholding. ResultsSpecific structure, related parameters, recognition effect, and noise resistance of network were explored in 614 sets of ABR clinical data, and recognition accuracy of waves I, III, and V can reach 92.91%. DiscussionThus, the proposed method can reduce the repetitive work of doctors and meet accuracy effectively. Therefore, this method has clinical potential.

bioinformatics↗

bioRxiv2020

Acute noise causes down-regulation of ECM protein expression in guinea pig cochlea

ObjectiveTo study the differences in cochlea protein expression before and after noise exposure using proteomics to reveal the pathological mechanism of noise-induced hearing loss (NIHL). MethodsA guinea pig NIHL model was established to test the ABR thresholds before and after noise exposure. The proteomics technology was used to study the mechanism of differential protein expression in the cochlea by noise stimulation. ResultsThe average hearing threshold of guinea pigs on the first day after noise exposure was 57.00{+/-}6.78dB SPL, high-frequency hearing loss was more severe than low frequency; the average hearing threshold on the seventh day after noise exposure was 45.83{+/-}6.07dB SPL, and the 4k Hz hearing threshold has the best recovery. The proteomics technology identified 3122 different inner ear proteins, of which six proteins related to the hearing were down-regulation: TenascinC, Collagen type XI alpha two chains, Collagen type II alpha one chain, Thrombospondin 2, Collagen type XI alpha one chain and Ribosomal protein L38, and are enriched in protein absorption, focal adhesion, and extracellular matrix receptor pathways. ConclusionImpulse noise can affect the expression of differential proteins through focal adhesion pathways. This data can provide an experimental basis for the research on the prevention and treatment of NIHL.

immunology↗

bioRxiv2020

IP-MS Analysis of ESX-5 and ESX-1 Substrates Enables Mycobacterial Species Identification

Pulmonary disease resulting from non-tuberculous mycobacteria (NTM) infection has emerged as an increasingly prevalent clinical entity in the past two to three decades, but there are no standardized, commercial assays available for the molecular diagnosis of NTM infections from clinical samples. Herein we discuss the development of an assay that employs immunoprecipitation coupled with mass spectrometry (IP-MS) to rapidly and accurately discriminate prevalent slow-growing mycobacterial species (i.e., M. avium and M. intracellulare, M. kansasii, M. gordonae, M. marinum and M. tuberculosis) during early growth in mycobacterial growth indicator tube (MGIT) cultures. This IP-MS assay employs antibodies specific for conserved tryptic peptides of M. tuberculosis EsxN (AQAASLEAEHQAIVR) and CFP-10 (TQIDQVESTAGSLQGQWR) to capture and identify specific mycobacterial species and allows species-specific mycobacterium identification at the first sign of MGIT culture positivity.

microbiology↗

bioRxiv2020

rest2vec: Vectorizing the resting-state functional connectome using graph embedding

Resting-state functional magnetic resonance imaging (O_SCPLOWRSC_SCPLOWO_SCPCAP-C_SCPCAPO_SCPLOWFMRIC_SCPLOW) is widely used in connectomics for studying the functional relationships between regions of the human brain. O_SCPLOWRSC_SCPLOWO_SCPCAP-C_SCPCAPO_SCPLOWFMRIC_SCPLOW connectomics, however, has inherent analytical challenges, such as accounting for negative correlations. In addition, functional relationships between brain regions do not necessarily correspond to their anatomical distance, making the intrinsic geometry of the functional connectome less well understood. Recent techniques in natural language processing and machine learning, such as word2vec, have used embedding methods to map high-dimensional data into meaningful vector spaces. Inspired by this approach, we have developed a graph embedding pipeline, rest2vec, for studying the intrinsic geometry of functional connectomes. We demonstrate how rest2vec uses the phase angle spatial embedding (O_SCPLOWPHASEC_SCPLOW) method with dimensionality reduction techniques to embed the functional connectome into lower dimensions. Rest2vec can also be linked to the maximum mean discrepancy (O_SCPLOWMMDC_SCPLOW) metric to assign functional modules of the connectome in a continuous manner, improving upon traditional binary classification methods. Together, this allows for studying the functional connectome such that the full range of correlative information is preserved and gives a more informed understanding of the functional organization of the brain.

neuroscience↗

bioRxiv2019

Downregulation of GPR183 on Infection Restricts the Early Infection and Intracellular Survival of Mycobacterium tuberculosis in Macrophage

GPR183/EBI2 is a key chemotactic receptor for the positioning of B cells in lymphoid organs, and also for the migration of T cells and other immune cells. Here, we demonstrate that the downregulation of GPR183 in macrophage induced during Mtb infection restrains the bacterial early infection and intracellular survival. Overexpression of GPR183 or stimulation with its natural ligand favors Mtb survival in macrophage, while treatment with its antagonist represses both Mtb early infection and intracellular survival. With mutational analysis, we find that substitution of Asp-73, Arg-83, Tyr-112, Tyr-256 abolished the promotive effect of GPR183 on Mtb early infection and survival in macrophage. In conclusion, we demonstrated that beside the known role of chemotaxis receptor, GPR183 also functions directly in the interaction between macrophage and Mtb in a cell-autonomous way.

microbiology↗

bioRxiv2019

A Mac2-positive progenitor-like microglial population survives independent of CSF1R signaling in adult mouse brain

Microglia are the resident myeloid cells in the central nervous system (CNS). The majority of microglial population relies on Csf1r signaling for survival and maintenance. However, a small subset of microglia in the murine brain can survive without Csf1r signaling, and reestablishes homeostasis after Csf1r signaling returns. Using single-cell RNA-seq, we characterized the heterogeneous microglial populations under Csf1r inhibition, including microglia lacking homeostatic markers and populations with elevated markers of monocytes, granulocytes and dendritic cells. Importantly, Mac2 is distinctively expressed in a subset of Csf1r-independent microglia cells, which were highly proliferative and shared striking similarities with those of microglial progenitors in yolk sac and early embryos. Lineage-tracing revealed that the Mac2+ population is of microglial origin and does not come from periphery monocytes. In non-treated mouse brains, Mac2+ microglia exhibited progenitor transcriptomic signature indistinguishable from those survived csf1r inhibition, supporting Mac2+ progenitor-like cells are present among homeostatic microglia.

neuroscience↗

bioRxiv2018

ForestQC: quality control on genetic variants from next-generation sequencing data using random forest

Next-generation sequencing technology (NGS) enables discovery of nearly all genetic variants present in a genome. A subset of these variants, however, may have poor sequencing quality due to limitations in sequencing technology or in variant calling algorithms. In genetic studies that analyze a large number of sequenced individuals, it is critical to detect and remove those variants with poor quality as they may cause spurious findings. In this paper, we present a statistical approach for performing quality control on variants identified from NGS data by combining a traditional filtering approach and a machine learning approach. Our method uses information on sequencing quality such as sequencing depth, genotyping quality, and GC contents to predict whether a certain variant is likely to contain errors. To evaluate our method, we applied it to two whole-genome sequencing datasets where one dataset consists of related individuals from families while the other consists of unrelated individuals. Results indicate that our method outperforms widely used methods for performing quality control on variants such as VQSR of GATK by considerably improving the quality of variants to be included in the analysis. Our approach is also very efficient, and hence can be applied to large sequencing datasets. We conclude that combining a machine learning algorithm trained with sequencing quality information and the filtering approach is an effective approach to perform quality control on genetic variants from sequencing data.\n\nAuthor SummaryGenetic disorders can be caused by many types of genetic mutations, including common and rare single nucleotide variants, structural variants, insertions and deletions. Nowadays, next generation sequencing (NGS) technology allows us to identify various genetic variants that are associated with diseases. However, variants detected by NGS might have poor sequencing quality due to biases and errors in sequencing technologies and analysis tools. Therefore, it is critical to remove variants with low quality, which could cause spurious findings in follow-up analyses. Previously, people applied either hard filters or machine learning models for variant quality control (QC), which failed to filter out those variants accurately. Here, we developed a statistical tool, ForestQC, for variant QC by combining a filtering approach and a machine learning approach. We applied ForestQC to one family-based whole genome sequencing (WGS) dataset and one general case-control WGS dataset, to evaluate our method. Results show that ForestQC outperforms widely used methods for variant QC by considerably improving the quality of variants. Also, ForestQC is very efficient and scalable to large-scale sequencing datasets. Our study indicates that combining filtering approaches and machine learning approaches enables effective variant QC.

bioinformatics↗

bioRxiv2018

Proximal recolonization by self-renewing microglia re-establishes microglial homeostasis in the adult mouse brain

Microglia are resident immune cells that play critical roles in maintaining normal physiology of the central nervous system. Remarkably, microglia have intrinsic capacity to replenish after being acutely ablated. However, the underlying mechanisms that drive such microglial restoration remain elusive. Here, we removed microglia via CSF1R inhibitor PLX5622 and characterized repopulation both spatially and temporally. We also investigated the cellular origin of repopulated microglia and report that microglia are replenished via self-renewal, with little contribution from non-microglial lineage progenitors, including nestin+ progenitors and the circulating myeloid population. Interestingly, spatial analyses with multi-color labeling reveal that newborn microglia recolonize the parenchyma by forming distinctive clusters that maintain stable territorial boundaries over time, indicating proximal expansion nature of adult microgliogenesis and stability of microglia tiling. Temporal transcriptome profiling from newborn microglia at different repopulation stages revealed that the adult newborn microglia gradually regain steady-state maturity from an immature state that is reminiscent of neonatal stage and follow a series of maturation programs that include NF-{kappa}B activation, interferon immune activation and apoptosis, etc. Importantly, we show that the restoration of microglial homeostatic density requires NF-{kappa}B signaling as well as apoptotic egress of excessive cells. In summary, our study reports key events that take place from microgliogenesis to homeostasis re-establishment.

neuroscience↗

bioRxiv2017

High-Throughput Identification of Genetic Variation Impact on pre-mRNA Splicing Efficiency

AbstractUnderstanding the functional impact of genomic variants is a major goal of modern genetics and personalized medicine. Although many synonymous and non-coding variants act through altering the efficiency of pre-mRNA splicing, it is difficult to predict how these variants impact pre-mRNA splicing. Here, we describe a massively parallel approach we used to test the impact of 2,059 human genetic variants spanning 110 alternative exons on pre-mRNA splicing. This method yields data that reinforces known mechanisms of pre-mRNA splicing, can rapidly identify genomic variants that impact pre-mRNA splicing, and will be useful for increasing our understanding of genome function.

genomics↗

bioRxiv2017

A Large-Scale Binding and Functional Map of Human RNA Binding Proteins

Genomes encompass all the information necessary to specify the development and function of an organism. In addition to genes, genomes also contain a myriad of functional elements that control various steps in gene expression. A major class of these elements function only when transcribed into RNA as they serve as the binding sites for RNA binding proteins (RBPs), which act to control post-transcriptional processes including splicing, cleavage and polyadenylation, RNA editing, RNA localization, stability, and translation. Despite the importance of these functional RNA elements encoded in the genome, they have been much less studied than genes and DNA elements. Here, we describe the mapping and characterization of RNA elements recognized by a large collection of human RBPs in K562 and HepG2 cells. These data expand the catalog of functional elements encoded in the human genome by addition of a large set of elements that function at the RNA level through interaction with RBPs.\n\nHighlightsO_LI223 eCLIP datasets for 150 RBPs reveal a wide variety of in vivo RNA target classes.\nC_LIO_LI472 knockdown/RNA-seq profiles of 263 RBPs reveal factor-responsive targets and integration with eCLIP indicates RNA expression and splicing regulatory patterns.\nC_LIO_LI78 RNA Bind-N-Seq profiles of in vitro binding motifs reveal links between in vitro and in vivo binding and indicate that eCLIP peaks that contain in vitro motifs are more strongly associated with regulation.\nC_LIO_LI274 maps of RBP subcellular localization by immunofluorescence indicate widespread organelle-specific RNA processing regulation.\nC_LIO_LI63 ChIP-seq profiles of DNA association suggest broad interconnectivity between chromatin association and RNA processing.\nC_LI

genomics↗