Biology subjects

Fu, L.

Publications and source records attributed to Fu, L..

81 records · Page 5Linked to original sources

bioRxiv2020

Indole acetic acid and lipopeptide-producing endophytic bacteria from Taxus chinesis: toxicity evaluation of metabolic products

Endophytes play an important role in plant growth and development. Some one can produce auxins, ACCs, iron carriers, and so on to help plants grow and resist unhealthy growth environments. In addition, they can produce certain antimicrobial substances to resist pests and diseases. Among them, Bacillus is the most common beneficial endophytic bacterium in plants. In this paper, 20 IAA-producing strains were screened from endophytic bacteria isolated from Taxus chinensis var. mairei plant tissues by high-performance liquid-chromatography (HPLC). Based on the 20 IAA-producing strains, LC-TOF-MS technology was used to screen lipopeptide-producing Bacillus sp. As a result, three strains (KLBMPTC01, KLBMPTC10, and KLBMPTC29) of Bacillus-producing lipopeptides with abundant contents and species were obtained. According to the situation of the IAA and lipopeptides produced by these strains, KLBMPTC10 was selected as the experimental strain for later toxicological tests. In an Ames test and oral toxicity experiments in mice, we did not detect mutagenicity and other physiological toxicity. This is hoping to provide a theoretical basis for forest resource protection and biofertiliser production therewith.

microbiology↗

bioRxiv2020

A potent neutralizing human antibody reveals the N-terminal domain of the Spike protein of SARS-CoV-2 as a site of vulnerability

The pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presents a global public health threat. Most research on therapeutics against SARS-CoV-2 focused on the receptor binding domain (RBD) of the Spike (S) protein, whereas the vulnerable epitopes and functional mechanism of non-RBD regions are poorly understood. Here we isolated and characterized monoclonal antibodies (mAbs) derived from convalescent COVID-19 patients. An mAb targeting the N-terminal domain (NTD) of the SARS-CoV-2 S protein, named 4A8, exhibits high neutralization potency against both authentic and pseudotyped SARS-CoV-2, although it does not block the interaction between angiotensin-converting enzyme 2 (ACE2) receptor and S protein. The cryo-EM structure of the SARS-CoV-2 S protein in complex with 4A8 has been determined to an overall resolution of 3.1 Angstrom and local resolution of 3.4 Angstrom for the 4A8-NTD interface, revealing detailed interactions between the NTD and 4A8. Our functional and structural characterizations discover a new vulnerable epitope of the S protein and identify promising neutralizing mAbs as potential clinical therapy for COVID-19.

biochemistry↗

bioRxiv2020

Glycosaminoglycan binding motif at S1/S2 proteolytic cleavage site on spike glycoprotein may facilitate novel coronavirus (SARS-CoV-2) host cell entry

Severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) has resulted in a pandemic and continues to spread around the globe at an unprecedented rate. To date, no effective therapeutic is available to fight its associated disease, COVID-19. Our discovery of a novel insertion of glycosaminoglycan (GAG)-binding motif at S1/S2 proteolytic cleavage site (681-686 (PRRARS)) and two other GAG-binding-like motifs within SARS-CoV-2 spike glycoprotein (SGP) led us to hypothesize that host cell surface GAGs might be involved in host cell entry of SARS-CoV-2. Using a surface plasmon resonance direct binding assay, we found that both monomeric and trimeric SARS-CoV-2 spike more tightly bind to immobilized heparin (KD = 40 pM and 73 pM, respectively) than the SARS-CoV and MERS-CoV SGPs (500 nM and 1 nM, respectively). In competitive binding studies, the IC50 of heparin, tri-sulfated non-anticoagulant heparan sulfate, and non-anticoagulant low molecular weight heparin against SARS-CoV-2 SGP binding to immobilized heparin were 0.056 M, 0.12 M, and 26.4 M, respectively. Finally, unbiased computational ligand docking indicates that heparan sulfate interacts with the GAG-binding motif at the S1/S2 site on each monomer interface in the trimeric SARS-CoV-2 SGP, and at another site (453-459 (YRLFRKS)) when the receptor-binding domain is in an open conformation. Our study augments our knowledge in SARS-CoV-2 pathogenesis and advances carbohydrate-based COVID-19 therapeutic development.

biochemistry↗

bioRxiv2020

SARS-CoV-2 invades host cells via a novel route: CD147-spike protein

Currently, COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been widely spread around the world; nevertheless, so far there exist no specific antiviral drugs for treatment of the disease, which poses great challenge to control and contain the virus. Here, we reported a research finding that SARS-CoV-2 invaded host cells via a novel route of CD147-spike protein (SP). SP bound to CD147, a receptor on the host cells, thereby mediating the viral invasion. Our further research confirmed this finding. First, in vitro antiviral tests indicated Meplazumab, an anti-CD147 humanized antibody, significantly inhibited the viruses from invading host cells, with an EC50 of 24.86 g/mL and IC50 of 15.16 g/mL. Second, we validated the interaction between CD147 and SP, with an affinity constant of 1.85x10-7M. Co-Immunoprecipitation and ELISA also confirmed the binding of the two proteins. Finally, the localization of CD147 and SP was observed in SARS-CoV-2 infected Vero E6 cells by immuno-electron microscope. Therefore, the discovery of the new route CD147-SP for SARS-CoV-2 invading host cells provides a critical target for development of specific antiviral drugs.

microbiology↗

bioRxiv2020

Predicting transcription factor binding in single cells through deep learning

Characterizing genome-wide binding profiles of transcription factor (TF) is essential for understanding many biological processes. Although techniques have been developed to assess binding profiles within a population of cells, determining binding profiles at a single cell level remains elusive. Here we report scFAN (Single Cell Factor Analysis Network), a deep learning model that predicts genome-wide TF binding profiles in individual cells. scFAN is pre-trained on genome-wide bulk ATAC-seq, DNA sequence and ChIP-seq data, and utilizes single-cell ATAC-seq to predict TF binding in individual cells. We demonstrate the efficacy of scFAN by studying sequence motifs enriched within predicted binding peaks and investigating the effectiveness of predicted TF peaks for discovering cell types. We develop a new metric "TF activity score" to characterize each cell, and show that the activity scores can reliably capture cell identities. The method allows us to discover and study cellular identities and heterogeneity based on chromatin accessibility profiles.

bioinformatics↗

bioRxiv2019

PRR14 Overexpression Promotes Cell Growth, Epithelial to Mesenchymal Transition and Metastasis of Colon Cancer via the AKT Pathway

BackgroundPRR14 (Proline rich protein 14) was firstly identified for its ability to specify and localize heterochromatin during cell cycle progression. Aberrant expression of PRR14 is associated with the tumorigenesis and progression of lung cancer. However, its involvement in colon cancer remains unknown. Herein, we report the role of PRR14 in colon cancer.\n\nMethodsColon cancer tissue microarray was used to analyze and compare the expression of PRR14 among some clinicopathological characteristics of colon cancer. HCT116 and RKO cells were transfected with siRNA to downregulate PRR14 expression. The roles of PRR14 in proliferation, migration and invasion of the cell lines were determined using cell counting kit-8, colony formation assay, wound healing assay and transwell assays respectively. The expression of PRR14 was measured by using immunofluorescence, qRT- PCR and western blot.\n\nResultsPRR14 was highly expressed in colon cancer tissues, and the expression level was correlated with tumor size, distant metastasis and Tumor Node Metastasis stages. Functional study revealed that downregulation of PRR14 inhibited colon cancer cells growth, migration and invasion. Furthermore, knockdown of PRR14 inhibited epithelial-mesenchymal transition (EMT) process, cell cycle-associated proteins expression and p-AKT level.\n\nConclusionPRR14 may promote the progression and metastasis of colon cancer, and may be a novel prognostic and therapeutic marker for the disease.

cancer biology↗

bioRxiv2018

Ultra-high throughput multiplexing and sequencing of >500 bp amplicon regions on the Illumina HiSeq 2500 platform

Amplification, sequencing and analysis of the 16S rRNA gene affords characterization of microbial community composition. As this tool has become more popular and amplicon-sequencing applications have grown in the total number of samples, growth in sample multiplexing is becoming necessary while maintaining high sequence quality and sequencing depth. Here, modifications to the Illumina HiSeq 2500 platform are described which produce greater multiplexing capabilities and 300 bp paired-end reads of higher quality than produced by the current Illumina MiSeq platform. To improve the feasibility and flexibility of this method, a 2-Step PCR amplification protocol is also described that allows for targeting of different amplicon regions, thus improving amplification success from low bacterial bioburden samples.\n\nImportanceAmplicon sequencing has become a popular and widespread tool for surveying microbial communities. Lower overall costs associated with high throughput sequencing have made it a widely-adopted approach, especially for projects which necessitate sample multiplexing to eliminate batch effect and reduced time to acquire data. The method for amplicon sequencing on the Illumina HiSeq 2500 platform described here provides improved multiplexing capabilities while simultaneously producing greater quality sequence data and lower per sample cost relative to the Illumina MiSeq platform, without sacrificing amplicon length. To make this method more flexible to various amplicon targeted regions as well as improve amplification from low biomass samples, we also present and validate a 2-Step PCR library preparation method.

microbiology↗

bioRxiv2018

Temporal Evolution of Cortical Ensembles Promoting Remote Memory Retrieval

Studies of amnesic patients and animal models support a systems consolidation model, which posits that explicit memories formed in hippocampus are transferred to cortex over time1-6. Prelimbic cortex (PL), a subregion of the medial prefrontal cortex, is required for the expression of learned fear memories from hours after learning until weeks later7-12. While some studies suggested that prefrontal cortical neurons active during learning are required for memory retrieval13-15, others provided evidence for ongoing cortical circuit reorganization during memory consolidation10,16,17. It has been difficult to causally relate the activity of cortical neurons during learning or recent memory retrieval to their function in remote memory, in part due to a lack of tools18. Here we show that a new version of targeted recombination in active populations, TRAP2, has enhanced efficiency over the past version, providing brain-wide access to neurons activated by a particular experience. Using TRAP2, we accessed PL neurons activated during fear conditioning or 1-, 7-, or 14-day memory retrieval, and assessed their contributions to 28-day remote memory. We found that PL neurons TRAPed at later retrieval times were more likely to be reactivated during remote memory retrieval, and more effectively promoted remote memory retrieval. Furthermore, reducing PL activity during learning blunted the ability of TRAPed PL neurons to promote remote memory retrieval. Finally, a series of whole-brain analyses identified a set of cortical regions that were densely innervated by memory-TRAPed PL neurons and preferentially activated by PL neurons TRAPed during 14-day retrieval, and whose activity co-varied with PL and correlated with memory specificity. These findings support a model in which PL ensembles underlying remote memory undergo dynamic changes during the first two weeks after learning, which manifest as increased functional recruitment of cortical targets.

neuroscience↗

bioRxiv2017

Identifying weak signals in inhomogeneous neuronal images for large-scale tracing of neurites

Reconstructing neuronal morphology across different regions or even the whole brain is important in many areas of neuroscience research. Large-scale tracing of neurites constitutes the core of this type of reconstruction and has many challenges. One key challenge is how to identify a weak signal from an inhomogeneous background. Here, we addressed this problem by constructing an identification model. In this model, empirical observations made from neuronal images are summarized into rules, which are used to design feature vectors that display the differences between the foreground and background, and a support vector machine is used to learn these feature vectors. We embedded this identification model into a tool that we previously developed, SparseTracer, and termed this integration SparseTracer-Learned Feature Vector (ST-LFV). ST-LFV can trace neurites with extremely weak signals (signal-to-background-noise ratio <1.1) against an inhomogeneous background. By testing 12 sub-blocks extracted from a whole imaging dataset, ST-LFV can achieve an average recall rate of 0.99 and precision rate of 0.97, which is superior to that of SparseTracer (which has an average recall rate of 0.93 and average precision rate of 0.86), indicating that this method is well suited to weak signal identification. We applied ST-LFV to trace neurites from large-scale images (approximately 105 GB). During the tracing process, obtaining results equivalent to the ground truth required only one round of manual editing for ST-LFV compared to 20 rounds of manual editing for SparseTracer. This improvement in the level of automatic reconstruction indicates that ST-LFV has the potential to rapidly reconstruct sparsely distributed neurons at the scale of an entire brain.

bioinformatics↗