Biology subjects

Fan, J.

Publications and source records attributed to Fan, J..

At least 109 records · Page 6Linked to original sources

bioRxiv2024

Inhibition of Alpha Interferon-Induced miR-873 Negatively Affects the Hepatitis B Virus Expression

BackgroundAlpha interferon (IFN-)-based therapy can effectively treat chronic hepatitis B virus (HBV) infection, which remains a serious public health problem. This study aims to identify the potential biomarker of IFN treatment and investigate the effects of miR-873 on chronic hepatitis B (CHB). MethodsWe utilized the random forest to screen core differentially expressed miRNAs (DEmiRNAs) based on the miRNA (GSE29911) dataset. DEmiRNAs expressions were determined in clinical samples from CHB patients and normal controls. HBV-transfected hepatoma cell lines were constructed for vitro study. Quantitative real-time reverse transcription PCR (RT-qPCR) was used to determine miRNA mRNA expressions. ELISA assays were used to detect the secretion levels of HBsAg and HBeAg. ResultsBoruta feature selection revealed miR-873 hinting at a predictive marker for IFN response. MiR-873 was significantly up-regulated in the CHB patients, as compared with normal controls (P<0.001). Increased expression of miR-873 was also found in HBV-infected cells (P<0.001). With IFN- treatment, miR-873 was significantly down-regulated in HBV-infected Huh-7 and HepG-NTCP cells (P<0.05). IFN- treatment and miR-873 inhibitor significantly reduced HBsAg and HBeAg level (P<0.05). The inhibitory effect was enhanced by blocking the IFN--induced miR-873 downregulation by inhibitor transfection (P<0.05). In miR-873 mimic-treated cells, the inhibitory effect was greatly supressed by blocking the IFN--induced miR-873 downregulation by mimic transfection (P< 0.01). ConclusionWe provide evidence that inhibition of miR-873 by IFN- enhances the antiviral effects of IFN-. Our study provides a potential strategy to enhance the anti-HBV effect of IFN- by inhibiting miR-873 expression.

molecular biology↗

bioRxiv2023

A Dataset for Deep Learning based Cleavage-stage Blastocyst Prediction with Time-lapse Images

Recent advances in deep learning and artificial intelligence techniques have obtained notable progress in automated embryo image analysis. However, most current research focuses on blastocyst-stage embryo evaluation (more than 5 days after in vitro fertilization), which may reduce the number of transferable embryos and increase the risk of canceled circles. Therefore, this paper aims to investigate the possibility of evaluating blastocyst development at the cleavage stage with deep neural networks (DNNs). To this end, we collect a dataset that consists of time-lapse images of more than 500 embryos (about 194k frames in total). We evaluate several widely used DNNs on the dataset, including those of single-frame architectures and multi-frame architectures. Experimental results show that the accuracy of different DNNs varies from 66.42% to 77.74% and we also provide the possible reasons behind the performance gap. Our dataset and code will be published soon to facilitate related research.

bioinformatics↗

bioRxiv2023

Macrophages undergo functionally significant reprograming of nucleotide metabolism upon classical activation

During an immune response, macrophages specifically rewire their metabolism to support functional changes. Using a multi-omics approach, we identified nucleotide metabolism as one of the most significantly rewired pathways across the metabolic network in classically activated macrophages. Further isotopic tracing studies revealed the substantial changes in nucleotide de novo synthesis, degradation, and salvage fluxes in stimulated macrophages, as well as the key reactions where metabolic regulation occurs: 1) de novo synthesis of purine nucleotides is shut down and particularly blocked at the last step of IMP synthesis catalyzed by ATIC; 2) de novo synthesis of pyrimidines is maintained up to UMP, but further synthesis of CTP (catalyzed by CTPS) and dTMP (catalyzed by TYMS) is greatly reduced; 3) Nucleotide degradation to nitrogenous bases is increased, but further oxidation of purine bases (catalyzed by XOR) is inhibited, causing a great accumulation of nucleosides and bases; and 4) cells switch to salvaging the nucleosides and bases as the primary means to maintain purine nucleotides. Mechanistically, we found these changes are driven by a combination of transcriptional regulation and enzyme inhibition. Nitric oxide (NO) was identified as a major regulator, driving the strong inhibition of ATIC and XOR, and the transcriptional downregulation of Tyms. To understand the functional impact of the activation-induced switch from purine de novo synthesis to salvage, we knocked out the purine salvage enzyme Hprt. Hprt knockout significantly alters functional gene expression in activated macrophages, suppresses macrophage migration, and increases pyroptosis. Furthermore, knocking out Hprt or Xor increases the proliferation of the intracellular parasite Toxoplasma gondii in macrophages. Together, these results comprehensively uncovered the dynamic rewiring of nucleotide metabolism in classically activated macrophages, elucidated the key regulatory mechanisms, and identified the functional significance of such rewiring.

cell biology↗

bioRxiv2023

Tree-based differential testing using inferentialuncertainty for RNA-Seq

Identifying differentially expressed transcripts poses a crucial yet challenging problem in transcriptomics. Substantial uncertainty is associated with the abundance estimates of certain transcripts which, if ignored, can lead to the exaggeration of false positives and, if included, may lead to reduced power. Given a set of RNA-Seq samples, TreeTerminus arranges transcripts in a hierarchical tree structure that encodes different layers of resolution for interpretation of the abundance of transcriptional groups, with uncertainty generally decreasing as one ascends the tree from the leaves. We introduce mehenDi, which utilizes the tree structure from TreeTerminus for differential testing. The nodes output by mehenDi, called the selected nodes are determined in a data-driven manner to maximize the signal that can be extracted from the data while controlling for the uncertainty associated with estimating the transcript abundances. The identified selected nodes can include transcripts and inner nodes, with no two nodes having an ancestor/descendant relationship. We evaluated our method on both simulated and experimental datasets, comparing its performance with other tree-based differential methods as well as with uncertainty-aware differential transcript/gene expression methods. Our method detects inner nodes that show a strong signal for differential expression, which would have been overlooked when analyzing the transcripts alone.

bioinformatics↗

bioRxiv2023

Structural elucidation of how ARF small GTPases induce membrane tubulation for vesicle fission

The ADP-Ribosylation Factor (ARF) small GTPases have been found to act in vesicle fission through a direct ability to tubulate membrane. Here, we have used cryo-electron microscopy (EM) to solve the structure of an ARF6 protein lattice assembled on tubulated membrane to 3.9 [A] resolution. ARF6 forms tetramers that polymerize into helical arrays to form this lattice. We identify, and confirm functionally, protein contacts critical for this lattice formation. The solved structure also suggests how the ARF amphipathic helix is positioned in the lattice for membrane insertion, and how a GTPase-activating protein (GAP) docks onto the lattice to catalyze ARF-GTP hydrolysis in completing membrane fission. As ARF1 and ARF6 are structurally conserved, we have also modeled ARF1 onto the ARF6 lattice, which has allowed us to pursue the reconstitution of Coat Protein I (COPI) vesicles to confirm more definitively that the ARF lattice acts in vesicle fission. Our findings are notable for having achieved the first detailed glimpse of how a small GTPase bends membrane and having provided a molecular understanding of how an ARF protein acts in vesicle fission.

cell biology↗

bioRxiv2023

Heme biosynthesis regulates BCAA catabolism and thermogenesis in brown adipose tissue

With age, people tend to accumulate body fat and reduce energy expenditure1. Brown (BAT) and beige adipose tissue dissipate heat and increase energy expenditure via the activity of the uncoupling protein UCP1 and other thermogenic futile cycles2,3. The activity of brown and beige depots inversely correlates with BMI and age4-11, suggesting that promoting thermogenesis may be an effective approach for combating age-related metabolic disease12-15. Heme is an enzyme cofactor and signaling molecule that we recently showed to regulate BAT function16. Here, we show that heme biosynthesis is the primary contributor to intracellular heme levels in brown adipocytes. Inhibition of heme biosynthesis leads to mitochondrial dysfunction and reduction in UCP1. Although supplementing heme can restore mitochondrial function in heme-synthesis-deficient cells, the downregulation of UCP1 persists due to the accumulation of the heme precursors, particularly propionyl-CoA, which is a product of branched-chain amino acids (BCAA) catabolism. Cold exposure promotes BCAA uptake in BAT, and defects in BCAA catabolism in this tissue hinder thermogenesis17. However, BCAAs contribution to the TCA cycle in BAT and WAT never exceeds 2% of total TCA flux18. Our work offers a way to integrate current literature by describing heme biosynthesis as an important metabolic sink for BCAAs.

cell biology↗

bioRxiv2023

One-Hour Phosphoproteome Analysis with the Orbitrap Astral Mass Spectrometer

Owing to its roles in cellular signal transduction, protein phosphorylation plays critical roles in myriad cell processes. That said, detecting and quantifying protein phosphorylation has remained a challenge. We describe the use of a novel mass spectrometer (Orbitrap Astral) coupled with data-independent acquisition (DIA) to achieve rapid and deep analysis of human and mouse phosphoproteomes. With this method we map approximately 30,000 unique human phosphorylation sites within a half-hour of data collection. The technology was benchmarked to other state-of-the-art MS platforms using both synthetic peptide standards and with EGF-stimulated HeLa cells. We applied this approach to generate a phosphoproteome multi-tissue atlas of the mouse. Altogether, we detected 81,120 unique phosphorylation sites within 12 hours of measurement. With this unique dataset, we examine the sequence, structural, and kinase specificity context of protein phosphorylation. Finally, we highlight the discovery potential of this resource with multiple examples of novel phosphorylation events relevant to mitochondrial and brain biology.

systems biology↗

bioRxiv2023

Phosphorylation in the Plasmodium falciparum proteome: A meta-analysis of publicly available data sets

Malaria is a deadly disease caused by Apicomplexan parasites of the Plasmodium genus. Several species of the Plasmodium genus are known to be infectious to human, of which P. falciparum is the most virulent. Post-translational modifications (PTMs) of proteins coordinate cell signalling and hence, regulate many biological processes in P. falciparum homeostasis and host infection, of which the most highly studied is phosphorylation. Phosphosites on proteins can be identified by tandem mass spectrometry (MS) performed on enriched samples (phosphoproteomics), followed by downstream computational analyses. We have performed a large-scale meta-analysis of 11 publicly available phosphoproteomics datasets, to build a comprehensive atlas of phosphosites in the P. falciparum proteome, using robust pipelines aimed at strict control of false identifications. We identified a total of 28,495 phosphorylated sites on P. falciparum proteins at 5% false localisation rate (FLR) and, of those, 18,100 at 1% FLR. We identified significant sequence motifs, likely indicative of different groups of kinases, responsible for different groups of phosphosites. Conservation analysis identified clusters of phosphoproteins that are highly conserved, and others that are evolving faster within the Plasmodium genus, and implicated in different pathways. We were also able to identify over 180,000 phosphosites within Plasmodium species beyond falciparum, based on orthologue mapping. We also explored the structural context of phosphosites, identifying a strong enrichment for phosphosites on fast evolving (low conservation) intrinsically disordered regions (IDRs) of proteins. In other species, IDRs have been shown to have an important role in modulating protein-protein interactions, particularly in signalling, and thus warranting further study for their roles in host- pathogen interactions. All data has made available via UniProtKB, PRIDE and PeptideAtlas, with visualisation interfaces for exploring phosphosites in the context of other data on Plasmodium proteins. Author SummaryPlasmodium parasites continue to pose a significant global health threat, with a high proportion of the world at risk of malaria. It is imperative to gain new insights into cell signalling and regulation of biological processes in these parasites to develop effective treatments. This study focused on post- translational modifications (PTMs) of proteins, specifically phosphorylation. We conducted a meta- analysis of 11 publicly available phosphoproteomics datasets, identifying over 28,000 phosphorylated sites on P. falciparum proteins, using very rigorous statistics to avoid reporting false positives, and mapping to over 180,000 phosphorylation sites on other species of Plasmodium. The analysis revealed distinct sequence motifs associated with different groups of phosphosites (and likely indicative of different upstream kinases), and differences in the downstream pathways regulated. Conservation analysis highlighted clusters of phosphoproteins evolving at different rates within the Plasmodium genus. Notably, phosphorylation was enriched in regions of proteins lacking distinct structural elements, known as intrinsically disordered regions (IDRs), which are poorly conserved across the genus - we speculate that they are important for modulating protein interactions. The findings provide valuable insights into the molecular mechanisms of P. falciparum, with potential implications for understanding host-pathogen interactions. The comprehensive dataset generated is now publicly accessible, serving as a valuable resource for the scientific community through UniProtKB, PRIDE, and PeptideAtlas.

bioinformatics↗

bioRxiv2023

A meta-analysis of rice phosphoproteomics data to understand variation in cell signalling across the rice pan-genome

Phosphorylation is the most studied post-translational modification, and has multiple biological functions. In this study, we have re-analysed publicly available mass spectrometry proteomics datasets enriched for phosphopeptides from Asian rice (Oryza sativa). In total we identified 15,522 phosphosites on serine, threonine and tyrosine residues on rice proteins. We identified sequence motifs for phosphosites, and link motifs to enrichment of different biological processes, indicating different downstream regulation likely caused by different kinase groups. We cross-referenced phosphosites against the rice 3,000 genomes, to identify single amino acid variations (SAAVs) within or proximal to phosphosites that could cause loss of a site in a given rice variety. The data was clustered to identify groups of sites with similar patterns across rice family groups, for example those highly conserved in Japonica, but mostly absent in Aus type rice varieties - known to have different responses to drought. These resources can assist rice researchers to discover alleles with significantly different functional effects across rice varieties. The data has been loaded into UniProt Knowledge-Base - enabling researchers to visualise sites alongside other data on rice proteins e.g. structural models from AlphaFold2, PeptideAtlas and the PRIDE database - enabling visualisation of source evidence, including scores and supporting mass spectra.

bioinformatics↗

bioRxiv2023

Genomic structures and regulation patterns at HPV integration sites in cervical cancer

Human papillomavirus (HPV) integration has been implicated in transforming HPV infection into cancer, but its genomic consequences have been difficult to study using short-read technologies. To resolve the dysregulation associated with HPV integration, we performed long-read sequencing on 63 cervical cancer genomes. We identified six categories of integration events based on HPV-human genomic structures. Of all HPV integrants, defined as two HPV-human breakpoints bridged by an HPV sequence, 24% contained variable copies of HPV between the breakpoints, a phenomenon we termed heterologous integration. Analysis of DNA methylation within and in proximity to the HPV genome at individual integration events revealed relationships between methylation status of the integrant and its orientation and structure. Dysregulation of the human epigenome and neighboring gene expression in cis with the HPV-integrated allele was observed over megabase-ranges of the genome. By elucidating the structural, epigenetic, and allele-specific impacts of HPV integration, we provide insight into the role of integrated HPV in cervical cancer.

genomics↗

bioRxiv2023

Integrating population-level and cell-based signatures for drug repositioning

Drug repositioning presents a streamlined and cost-efficient way to expand the range of therapeutic possibilities. Drugs with human genetic evidence are more likely to advance successfully through clinical trials towards FDA approval. Single gene-based drug repositioning methods have been implemented, but approaches leveraging a broad spectrum of molecular signatures remain underexplored. We propose a framework called "TReD" (Transcriptome-informed Reversal Distance) that integrates population-level disease signatures robust to reverse causality and cell-based, drug-induced transcriptome response profiles. TReD embeds the disease signature and drug response profiles in a high-dimensional normed space, quantifying the reversal potential of candidate drugs in a disease-related cell-based screening. Here, we implemented this framework to identify potential therapeutics relevant to COVID-19 and type 2 diabetes (T2D). For COVID-19, we identified 36 drugs showing potential reversal roles. Notably, nearly 70% (25/36) of the drugs have been linked to COVID-19 from other studies, with seven drugs supported by ongoing/completed clinical trials. For T2D, we observed reversal signals for 16 compounds on multiple disease signatures. Five drugs are supported by published literature, affirming potential therapeutic value. In summary, we propose a comprehensive genetics-anchored framework integrating population-level signatures and cell-based screening that has the potential to accelerate the search for new therapeutic strategies.

bioinformatics↗

bioRxiv2023

M1 Macrophage-Related Genes Model for NSCLC Immunotherapy Response Prediction

2.Patients diagnosed with non-small cell lung cancer have a limited lifespan and exhibit poor immunotherapy outcomes. M1 macrophages have been found to be essential for anti-tumor immunity. This study aimed to develop an immunotherapy response evaluation model for NSCLC patients based on transcriptional expression. RNA sequencing profiles of 254 advanced-stage NSCLC patients treated with immunotherapy were downloaded from POPLAR and OAK projects. Immune cell infiltration in NSCLC patients has been examined, and thereafter different co-expressed genes were identified. Following that, the impact of M1 macrophage related genes on the prognosis of NSCLC patients was investigated. Six M1 macrophage co-expression genes, namely NKX2-1, CD8A, SFTA3, IL2RB, IDO1, and CXCL9, exhibited a strong association with the prognosis of NSCLC and served as effective predictors for immunotherapy response. A response model was constructed using Cox regression model and Lasso Cox regression analysis. The M1 genes were validated on our previous TD- FOREKNOW NSCLC clinical trial by RT-qPCR. The response model showed excellent immunotherapy response predicting and prognosis evaluating value in advanced stage of NSCLC. The model can effectively predict advanced NSCLC prognosis and aid in identifying patients who could benefit from customized immunotherapy as well as sensitive drugs.

immunology↗

bioRxiv2023

Characterizing cell-type spatial relationships across length scales in spatially resolved omics data

Spatially resolved omics (SRO) technologies enable the identification of cell types while preserving their organization within tissues. Application of such technologies offers the opportunity to delineate cell-type spatial relationships, particularly across different length scales, and enhance our understanding of tissue organization and function. To quantify such multi-scale cell-type spatial relationships, we developed CRAWDAD, Cell-type Relationship Analysis Workflow Done Across Distances, as an open-source R package with source code and additional documentation at https://jef.works/CRAWDAD/. To demonstrate the utility of such multi-scale characterization, recapitulate expected cell-type spatial relationships, and evaluate against other cell-type spatial analyses, we applied CRAWDAD to various simulated and real SRO datasets of diverse tissues assayed by diverse SRO technologies. We further demonstrate how such multi-scale characterization enabled by CRAWDAD can be used to compare cell-type spatial relationships across multiple samples. Finally, we applied CRAWDAD to SRO datasets of the human spleen to identify consistent as well as patient and sample-specific cell-type spatial relationships. In general, we anticipate such multi-scale analysis of SRO data enabled by CRAWDAD will provide useful quantitative metrics to facilitate the identification, characterization, and comparison of cell-type spatial relationships across axes of interest.

bioinformatics↗

bioRxiv2023

Activation-induced shift in nutrient preference and function-specific nutrient dependence in human neutrophils

Neutrophils - the first responders in innate immunity - perform a variety of effector functions associated with specific metabolic demand. To maintain fitness and support functions, neutrophils have been found to utilize extracellular glucose, intracellular glycogen, and other alternative substrates. However, the quantitative contribution of these nutrients under specific conditions and the relative dependence of various cell functions on specific nutrients remain unclear. Here, using ex vivo and in vivo isotopic tracing, we reveal that under resting condition, human peripheral blood neutrophils, in contrast to in vitro cultured human neutrophil-like cell lines, rely on glycogen as a major direct source of glycolysis and pentose phosphate pathway. Upon activation with a diversity of stimuli, neutrophils undergo a significant and often rapid nutrient preference shift, with glucose becoming the dominant metabolic source thanks to a multi-fold increase in glucose uptake mechanistically mediated by the phosphorylation and translocation of GLUT1. At the same time, cycling between gross glycogenesis and glycogenolysis is also substantially increased, while the net flux favors sustained or increased glycogen storage. The shift in nutrient utilization impacts neutrophil functions in a function-specific manner. The activation of oxidative burst specifically depends on the utilization of extracellular glucose rather than glycogen. In contrast, the release of neutrophil traps can be flexibly supported by either glucose or glycogen. Neutrophil migration and fungal control is promoted by the shift away from glycogen utilization. Together, these results quantitatively characterize fundamental features of neutrophil metabolism and elucidate how metabolic remodeling shapes neutrophil functions upon activation.

biochemistry↗

bioRxiv2023

Gene count normalization in single-cell imaging-based spatially resolved transcriptomics

Recent advances in imaging-based spatially resolved transcriptomics (im-SRT) technologies now enable high-throughput profiling of targeted genes and their locations in fixed tissues. Normalization of gene expression data is often needed to account for technical factors that may confound underlying biological signals. Here, we investigate the potential impact of different gene count normalization methods with different targeted gene panels in the analysis and interpretation of im-SRT data. Using different simulated gene panels that overrepresent genes expressed in specific tissue regions or cell types, we demonstrate how normalization methods based on detected gene counts per cell differentially impact normalized gene expression magnitudes in a region- or cell type-specific manner. We show that these normalization-induced effects may reduce the reliability of downstream analyses including differential gene expression, gene fold change, and spatially variable gene analysis, introducing false positive and false negative results when compared to results obtained from gene panels that are more representative of the gene expression of the tissues component cell types. These effects are not observed with normalization approaches that do not use detected gene counts for gene expression magnitude adjustment, such as with cell volume or cell area normalization. We recommend using non-gene count-based normalization approaches when feasible and evaluating gene panel representativeness before using gene count-based normalization methods if necessary. Overall, we caution that the choice of normalization method and gene panel may impact the biological interpretation of the im-SRT data.

bioinformatics↗

bioRxiv2023

CRISPR-Hybrid: A CRISPR-Mediated Intracellular Directed Evolution Platform for RNA Aptamers

Recent advances in gene editing and precise regulation of gene expression based on CRISPR technologies have provided powerful tools for the understanding and manipulation of gene functions. Fusing RNA aptamers to the sgRNA of CRISPR can recruit cognate RNA-binding protein (RBP) effectors to target genomic sites, and the expression of sgRNA containing different RNA aptamers permit simultaneous multiplexed and multifunctional gene regulations. Here, we report an intracellular directed evolution platform for RNA aptamers against intracellularly expressed RBPs. We optimized a bacterial CRISPR-hybrid system coupled with FACS, and identified novel high affinity RNA aptamers orthogonal to existing aptamer-RBP pairs. Application of orthogonal aptamer-RBP pairs in multiplexed CRISPR allowed effective simultaneous transcriptional activation and repression of endogenous genes in mammalian cells.

synthetic biology↗

bioRxiv2023

Temporal dynamics and genomic programming of plasma cell fates

Affinity-matured plasma cells (PCs) of varying lifespans are generated through a germinal center (GC) response. The developmental dynamics and genomic programs of antigen-specific PC precursors remain to be elucidated. Using a model antigen, we demonstrate biphasic generation of PC precursors, with those generating long-lived bone marrow PCs preferentially produced in the late phase of GC response. Clonal tracing using scRNA-seq+BCR-seq in spleen and bone marrow compartments, coupled with adoptive transfer experiments, reveal a novel PC transition state that gives rise to functionally competent PC precursors. The latter undergo clonal expansion, dependent on inducible expression of TIGIT. We propose a model for the proliferation and programming of precursors of long-lived PCs, based on extended antigen encounters followed by reduced antigen availability.

immunology↗

bioRxiv2023

Large-scale population genomics of Malayan pangolins reveals deep diversification and a new species

BackgroundArchipelagos and oceanic islands often present high percentage of endemism due to rapid speciation. The Malayan pangolin is a species distributing at both mainland (southern Yunnan, China) and oceanic islands via Malayan peninsula, which may result in deep differentiation among populations. In-depth investigation of population structure and genetic consequences for such species is of vital importance for their protection and conservation, practically for the critically endangered Malayan pangolin that is suffering from poaching, illegal trade, and habitat loss. ResultsHere we carried out a large-scale population genomic analysis for Malayan pangolins, and revealed three highly distinct genetic populations in this species, two of which are now being reported for the first time. Based on multiple lines of genomic and morphological evidence, we postulate the existence of a new pangolin species (Manis_1). Genetic diversity and recent inbreeding were both at a moderate level for both Malayan pangolins and Manis_1, but mainland Malayan pangolins presented relatively lower genetic diversity, higher inbreeding and fitness cost than island populations. ConclusionsWe found extremely deep and graded differentiation in Malayan pangolins, with two newly discovered genetic populations and a new pangolin species that is closely related to the Philippine pangolin than the typical Malayan pangolin, but a distant relative of the Indian pangolin. Anthropogenic factors did not significantly weaken the basis of genetic sustainability for Malayan pangolins, but mainland Malayan pangolins should be paid more attention for conservation due to higher genetic risks than island populations.

genomics↗