Biology subjects

Fu, Y.

Publications and source records attributed to Fu, Y..

At least 289 records · Page 16Linked to original sources

bioRxiv2020

Conversion of marginal land into switchgrass conditionally accrues soil carbon and reduces methane consumption

Switchgrass (Panicum virgatum L.) is a perennial C4 grass native to tallgrass prairies of the Central US, and a promising bioenergy feedstock. Switchgrass can be cultivated on soils with low nutrient contents and its rooting depth, of up to 2 m, has brought attention to the crop as a potential mechanism to sequester and build soil carbon (C). Switchgrass, therefore, offers multifaceted benefits on degraded soils by enhancing soil organic matter content. However, to evaluate the sustainability of switchgrass-based biofuel production, it is crucial to understand the impacts of land conversion and switchgrass establishment on biotic/abiotic characteristics of various soils. In this study, we characterized the ecosystem-scale consequences of switchgrass growing at two highly-eroded, Dust Bowl remnant field sites from Oklahoma US, with silt-loam (SL) or clay-loam (CL) soil textures having low nitrogen (N), phosphorus (P), and C contents. Paired plots at each site, including fallow control and switchgrass-cultivated, were assessed. Our results indicated that switchgrass significantly increased soil C at the SL site and reduced microbial diversity at the CL site. The CL site exhibited significantly higher CO2 flux and higher respiration from switchgrass plots. Strikingly, switchgrass significantly reduced the CH4 consumption by an estimated 39% for the SL site and 47% for the CL site. Structural equation modeling identified soil temperature, P content, and soil moisture levels as the most influential factors regulating both CO2 and CH4 fluxes. CO2 flux was also influenced by microbial biomass while CH4 flux was influenced by microbial diversity. Together, our results suggest that site selection by soil type is a crucial factor in improving soil C stocks and mitigating greenhouse gas (GHG) fluxes, especially considering our finding that switchgrass reduced methane consumption, implying that carbon balance considerations should be accounted for to fully evaluate the sustainability of switchgrass cultivation.

molecular biology↗

bioRxiv2020

The dominance hierarchy of the female Yunnan snub-nosed monkeys (Rhinopithecus bieti)

Dominance hierarchies are common in social mammals, especially primates. The formation of social hierarchies is conducive to solving the problem of the allocation of scarce resources among individuals. From August 2015 to July 2016, we observed a wild, provisioned Yunnan snub-nosed monkey (Rhinopithecus bieti) group at Xiangguqing in Baimaxueshan National Nature Reserve, Yunnan Province, China. Aggressive and submissive behaviors were used to investigate dominance hierarchies between female individuals in the same one-male unit (OMU), and the grooming reciprocity index was used to detect reciprocal relationships between these females within the OMU. The results showed that loose social hierarchies exist among the females in each OMU, and more dominant individuals have higher grooming incomes. These results are consistent with the aggressive-submissive hypothesis and the resource control hypothesis.

animal behavior and cognition↗

bioRxiv2020

DNA methylation is indispensable for leukemia inhibitory factor dependent embryonic stem cells reprogramming

Naive pluripotency can be maintained by the 2i/LIF supplements (CHIR99021, PD0325901 and LIF), which primarily affect canonical WNT, FGF/ERK, and JAK/STAT3 signaling. However, whether one of these tripartite supplements alone is sufficient to maintain naive self-renewal remain unclear. Here we show that LIF alone is sufficient to induce reprogramming of 2i/LIF cultured ESCs (2i/L-ESCs) to ESCs with hypermethylated state (L-ESCs). In vitro, upon withdrawal of 2i, 2i/L-ESCs overcome the epigenetic barrier and DNA hypermethylated, which accompanies transcriptional changes and subsequent establishment of epigenetic memory. Global transcriptome features also show that L-ESCs are close to 2i/L-ESCs and in a stable state between naive and primed pluripotency. Notably, our results demonstrate that DNA methylation was indispensable for LIF-dependent mouse ESCs reprogramming and self-renew. LIF-dependent ESCs reprogramming efficiency is significantly increased in serum treatment and reduced in Dnmt3a or Dnmt3l knockout ESCs. Importantly, unlike epiblast and EpiSCs, L-ESCs contribute to somatic tissues and germ cells in chimaeras. Such simple culture system of ESCs is more conducive to clarify the molecular mechanism of ESCs in vitro culture. SignificanceEmbryonic stem cell (ESCs) exhibit naive pluripotency which reflects their ability to contribute to all embryonic lineages upon injection into blastocyst. ESCs were originally derived by co-culture with feeder cells and fetal calf serum. In this manuscript, we took a detailed approach to dissect the roles of LIF alone in ESC reprogramming of 2i/LIF cultured ESCs (2i/L-ESCs). Here, for the first time, we derived stable hypermethylated pluripotent ESCs under culture of LIF alone (L-ESCs). We further assessed L-ESCs properties both in vitro and in vivo, and provide molecular insights to the mechanism which allows LIF alone to maintain pluripotency and a hypermethylated state. We believe these findings are novel and valuable for future ESCs study.

cell biology↗

bioRxiv2020

Laser capture microdissection-based single-cell RNA sequencing reveals optic nerve crush-related early mRNA alterations in retinal ganglion cells

Retinal ganglion cells (RGC) are the primary cell type injured in a variety of diseases of the optic nerve, and the early changes of RGCs RNA profiling may be important to understand the mechanism of optic nerve injury and axon regeneration. Here we employed the optic nerve crush (ONC) model to explore early mRNA alterations in RGCs using laser capture microdissection (LCM) and single-cell RNA sequencing. We successfully established an optimal LCM protocol using 30 m-thick retinal tissue sections mounted on glass slides and laser pressure catapulting (LPC) to collect RGCs and obtain high-quality RNA for single-cell sequencing. Based on our protocol, we identified 8744 differentially expressed genes that were involved in ONC-related early mRNA alterations in RGCs. Candidate genes included Atf3, Lgals3, LOC102551701, Plaur, Tmem140 and Maml1. The LCM-based single-cell RNA sequencing allowed new insights into the early mRNA changes in RGCs, highlighting new molecules associated with ONC.

neuroscience↗

bioRxiv2020

DeepDigest: prediction of protein proteolytic digestion with deep learning

In shotgun proteomics, it is essential to accurately determine the proteolytic products of each protein in the sample for subsequent identification and quantification, because these proteolytic products are usually taken as the surrogates of their parent proteins in the further data analysis. However, systematical studies about the commonly used proteases in proteomics research are insufficient, and there is a lack of easy-to-use tools to predict the digestibilities of these proteolytic products. Here, we propose a novel sequence-based deep learning model - DeepDigest, which integrates convolutional neural networks and long-short term memory networks for digestibility prediction of peptides. DeepDigest can predict the proteolytic cleavage sites for eight popular proteases including trypsin, ArgC, chymotrypsin, GluC, LysC, AspN, LysN and LysargiNase. Compared with traditional machine learning algorithms, DeepDigest showed superior performance for all the eight proteases on a variety of datasets. Besides, some interesting characteristics of different proteases were revealed and discussed.

bioinformatics↗

bioRxiv2020

An active chromatin interactome elucidates the biological mechanisms underlying genetic risk factors of dermatological conditions in disease relevant cell lines

Chromatin looping between regulatory elements and gene promoters presents a potential mechanism whereby disease risk variants affect their target genes. Here we use H3K27ac HiChIP, a method for assaying the active chromatin interactome in two cell lines: keratinocytes and skin derived CD8+ T cells. We integrate public datasets for a lymphoblastoid cell line and primary CD4+ T cells and identify gene targets at risk loci for skin-related disorders. Interacting genes enrich for pathways of known importance in each trait, such as cytokine response (psoriatic arthritis, psoriasis) and replicative senescence (melanoma). We show examples of how our analysis can inform changes in the current understanding of multiple psoriasis associated risk loci. For example, the variant rs10794648, which is generally assigned to IFNLR1, was linked to GRHL3 in our dataset, a gene essential in skin repair and development. Our findings, therefore, indicate a renewed importance of skin related factors in the risk of disease. O_FIG O_LINKSMALLFIG WIDTH=158 HEIGHT=200 SRC="FIGDIR/small/973271v2_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@99cd40org.highwire.dtl.DTLVardef@1725b6dorg.highwire.dtl.DTLVardef@d05d21org.highwire.dtl.DTLVardef@1924d07_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract In this article we take disease associated variants from 5 dermatological conditions and use cell type specific datasets to map genes that could be affected by these variants, providing insight into disease mechanisms. C_FIG

genomics↗

bioRxiv2020

Nuclear sensing of mitochondrial DNA breaks enhances immune surveillance

Mitochondrial double-strand breaks (mtDSBs) are toxic lesions that compromise mitochondrial function. Mito-nuclear communication is essential to maintain cellular homeostasis, however, the nuclear response to mtDSBs remains unknown. Using mitochondrial-targeted TALENs, we show that mtDSBs activate a type I interferon response evidenced by phosphorylation of STAT1 and activation of interferon stimulated genes (ISG). Following mtDNA break formation, BAK-BAX mediated herniation releases mitochondrial RNA to the cytoplasm and trigger a RIG-I/MAVS-dependent immune response. In an independent set of experiments, we investigate the role of mtDSBs in interferon signaling due to genotoxic stress. Our data reveal that activation of ISGs is greatly diminished when cells lacking mtDNA are exposed to ionizing radiation. Furthermore, we show that mtDNA breaks synergize with nuclear DNA damage to mount a robust interferon response. In conclusion, cytoplasmic accumulation of mitochondrial RNA is as an intrinsic immune surveillance mechanism for cells to cope with mtDSBs, including ones inflicted by genotoxic agents.

molecular biology↗

bioRxiv2020

Interleukin-35 pretreatment attenuates lipopolysaccharide-induced heart injury by inhibition of inflammation, apoptosis and fibrosis

Previous studies have demonstrated that targeting inflammation is a promising strategy for treating lipopolysaccharide (LPS)-induced sepsis and related heart injury. Interleukin-35 (IL-35), which consists of two subunits, Epstein-Barr virus-induced gene 3 (EBI3) and p35, is an immunosuppressive cytokine of the IL-12 family and exhibits strong anti-inflammatory activity. However, the role of IL-35 in LPS-induced heart injury remains obscure. In this study, we explored the role of IL-35 in heart injury induced by LPS and its potential mechanisms. Mice were treated with a plasmid encoding IL-35 (pIL-35) and then injected intraperitoneally (ip) with LPS (10 mg/kg). Cardiac function was assessed by echocardiography 12 h later. LPS apparently decreased the expression of EBI3 and p35 and caused cardiac dysfunction and pathological changes, which were significantly improved by pIL-35 pretreatment. Moreover, pIL-35 pretreatment significantly decreased the levels of cardiac proinflammatory cytokines including TNF-, IL-6, and IL-1{beta}, and the NLRP3 inflammasome. Furthermore, increased BCL-2 levels and decreased BAX levels inhibited apoptosis, and LPS-induced upregulation of the expression of pro-fibrotic genes (MMP2 and MMP9) was inhibited. Further investigation indicated that pIL-35 pretreatment suppressed the activation of the cardiac NF-{kappa}Bp65 and TGF-{beta}1/Smad2/3 signaling pathways in LPS-treated mice. Similar cardioprotective effects of IL-35 pretreatment were observed in mouse myocardial fibroblasts challenged with LPS in vitro. In summary, IL-35 pretreatment can attenuate cardiac inflammation, apoptosis, and fibrosis induced by LPS, implicating IL-35 as a promising therapeutic target in sepsis-related cardiac injury.

molecular biology↗

bioRxiv2019

The interplay between host genetics and the gut microbiome reveals common and distinct microbiome features for human complex diseases

There is increasing interest about the interplay between host genetics and gut microbiome on human complex diseases, with prior evidence mainly derived from animal models. In addition, the shared and distinct microbiome features among human complex diseases remain largely unclear. We performed a microbiome genome-wide association study to identify host genetic variants associated with gut microbiome in a Chinese population with 1475 participants. We then conducted bi-directional Mendelian randomization analyses to examine the potential causal associations between gut microbiome and human complex diseases. We found that Saccharibacteria (also known as TM7 phylum) could potentially improve renal function by affecting renal function biomarkers (i.e., creatinine and estimated glomerular filtration rate). In contrast, atrial fibrillation, chronic kidney disease and prostate cancer, as predicted by the host genetics, had potential causal effect on gut microbiome. Further disease-microbiome feature analysis suggested that gut microbiome features revealed novel relationship among human complex diseases. These results suggest that different human complex diseases share common and distinct gut microbiome features, which may help re-shape our understanding about the disease etiology in humans.

microbiology↗

bioRxiv2019

NERDSS: a non-equilibrium simulator for multibody self-assembly at the cellular scale

Currently, a significant barrier to building predictive models of cell-based self-assembly processes is that molecular models cannot capture minutes-long cellular dynamics that couple distinct components with active processes, while reaction-diffusion models lack sufficient detail for capturing assembly structures. Here we introduce the Non-Equilibrium Reaction-Diffusion Self-assembly Simulator (NERDSS), which addresses this gap by integrating a structure-resolved reaction-diffusion algorithm with rule-based model construction. By representing proteins as rigid, multi-site molecules that adopt well-defined orientations upon binding, NERDSS simulates formation of large reversible structures with sites that can be acted on by reaction rules. We show how NERDSS allows for directly comparing and optimizing models of multi-component assembly against time-dependent experimental data. Applying NERDSS to assembly steps in clathrin-mediated endocytosis, we capture how the formation of clathrin caged structures can be driven by modulating the strength of clathrin-clathrin interactions, by adding cooperativity, or by localizing clathrin to the membrane. NERDSS further predicts how clathrin lattice disassembly can be driven by enzymes that irreversibly change lipid populations on the membrane. By modeling viral lattice assembly and recapitulating oscillations in protein expression levels for a circadian clock model, we illustrate the wide usability and adaptability of NERDSS. NERDSS simulates user-defined assembly models that were previously inaccessible to existing software tools, with broad applications to predicting self-assembly in vivo and designing high-yield assemblies in vitro.

biophysics↗

bioRxiv2019

RNA Sequencing by Direct Tagmentation of RNA/DNA Hybrids

Transcriptome profiling by RNA sequencing (RNA-seq) has been widely used to characterize cellular status but it relies on second strand cDNA synthesis to generate initial material for library preparation. Here we use bacterial transposase Tn5, which has been increasingly used in various high-throughput DNA analyses, to construct RNA-seq libraries without second strand synthesis. We show that Tn5 transposome can randomly bind RNA/DNA heteroduplexes and add sequencing adapters onto RNA directly after reverse transcription. This method, Sequencing HEteRo RNA-DNA-hYbrid (SHERRY), is versatile and scalable. SHERRY accepts a wide range of starting materials, from bulk RNA to single cells. SHERRY offers a greatly simplified protocol, and produces results with higher reproducibility and GC uniformity compared with prevailing RNA-seq methods. Significance StatementRNA sequencing is widely used to measure gene expression in biomedical research; therefore, improvements in the simplicity and accuracy of the technology are desirable. All existing RNA sequencing methods rely on the conversion of RNA into double-stranded DNA through reverse transcription followed by second strand synthesis. The latter step requires additional enzymes and purification, and introduces sequence-dependent bias. Here, we show that Tn5 transposase, which randomly binds and cuts double-stranded DNA, can directly fragment and prime the RNA/DNA heteroduplexes generated by reverse transcription. The primed fragments are then subject to PCR amplification. This provides a new approach for simple and accurate RNA characterization and quantification.

molecular biology↗

bioRxiv2019

Chromatin-based techniques map DNA interaction landscapes in psoriasis susceptibility loci and highlight KLF4 as a target gene in 9q31

Genome-wide association studies (GWAS) have uncovered many genetic risk loci for psoriasis, yet many remain uncharacterised in terms of the causal gene and their biological mechanism in disease. Here, we use a disease-focused Capture Hi-C experiment to link psoriasis-associated variants with their target genes in psoriasis-relevant cell lines (HaCaT keratinocytes and My-La CD8+ T cells). We confirm previously assigned genes, suggest novel candidates and provide evidence for complexity at psoriasis GWAS loci. In the 9q31 risk locus we combine further epigenomic evidence to demonstrate how the psoriasis association forms a functional interaction with the distant (>500 kb) KLF4 gene. We use CRISPR activation coupled with RNA-seq to demonstrate how activation of psoriasis-associated enhancers upregulates KLF4 in HaCaT cells. Our study design provides a robust pipeline for following up on GWAS disease-associated variants, paving the way for functional translation of genetic findings into clinical benefit.

genomics↗

bioRxiv2019

Pan-cancer computational histopathology reveals mutations, tumor composition and prognosis

The diagnosis of cancer is typically based on histopathological assessment of tissue sections, and supplemented by genetic and other molecular tests1-6. Modern computer vision algorithms have high diagnostic accuracy and potential to augment histopathology workflows7-9. Here we use deep transfer learning to quantify histopathological patterns across 17,396 hematoxylin and eosin (H&E) stained histopathology slide images from 28 cancer types and correlate these with matched genomic, transcriptomic and survival data. This approach accurately classifies cancer types and provides spatially resolved tumor and normal distinction. Automatically learned computational histopathological features correlate with a large range of recurrent genetic aberrations pan-cancer. This includes whole genome duplications, which display universal features across cancer types, individual chromosomal aneuploidies, focal amplifications and deletions as well as driver gene mutations. There are wide-spread associations between bulk gene expression levels and histopathology, which reflect tumour composition and enables localising transcriptomically defined tumour infiltrating lymphocytes. Computational histopathology augments prognosis based on histopathological subtyping and grading and highlights prognostically relevant areas such as necrosis or lymphocytic aggregates. These findings demonstrate the large potential of computer vision to characterise the molecular basis of tumour histopathology and lay out a rationale for integrating molecular and histopathological data to augment diagnostic and prognostic workflows.

bioinformatics↗

bioRxiv2019

Deletion of M-opsin prevents \"M cone\" degeneration in a mouse model of Leber congenital amaurosis

Mutations in RPE65 or lecithin-retinol acyltransferase (LRAT) disrupt 11-cis-retinal synthesis and cause Leber congenital amaurosis (LCA). In Lrat-/- mouse model, mislocalized medium (M)-wavelength sensitive opsin was degraded whereas mislocalized short (S)-wavelength sensitive opsin accumulated before the onset of cone degeneration. The mechanism for the foveal medium (M)/long (L)-wavelength-sensitive cone degeneration in LCA is unknown. By crossing Lrat-/- mice with a proteasome reporter mouse line, we showed that M-opsin enriched dorsal cones in Lrat-/- mice exhibit proteasome stress due to the degradation of large amounts of M-opsin. Deletion of M-opsin relieves the proteasome stress and completely prevents \"M cone\" degeneration in Lrat-/-Opn1sw-/- mice (a pure \"M cone\" LCA model, Opn1sw-/- encoding S-opsin) for at least 12 months. Our results suggest that M-opsin degradation associated proteasome stress plays a major role in \"M cone\" degeneration in Lrat-/- model. This finding may represent a general mechanism for \"M cone\" degeneration for multiple forms of cone degeneration due to M-opsin mislocalization and degradation. Our results have important implications for the current gene therapy strategy for LCA that emphasizes the need for a combinatorial therapy to both improve vision and slow photoreceptor degeneration.

neuroscience↗

bioRxiv2019

Dynamic 3D chromosomal landscapes in acute leukemia

Three-dimensional (3D) chromatin architectural changes can alter the integrity of topologically associated domains (TADs) and rewire specific enhancer-promoter interactions impacting gene expression. Recently, such alterations have been implicated in human disease, highlighting the need for a deeper understanding of their role. Here, we investigate the reorganization of chromatin architecture in T cell acute lymphoblastic leukemia (T-ALL) using primary human leukemia specimens and its dynamic responses to pharmacological agents. Systematic integration of matched in situ Hi-C, RNA-Seq and CTCF ChIP-Seq datasets revealed widespread changes in intra-TAD chromatin interactions and TAD boundary insulation in T-ALL. Our studies identify and focus on a TAD \"fusion\" event being associated with loss of CTCF-mediated insulation, enabling direct interactions between the MYC promoter and a distal super-enhancer. Moreover, our data show that small molecule inhibitors targeting either oncogenic signal transduction or epigenetic regulation reduce specific 3D interactions associated with transformation. Overall, our study highlights the impact, complexity and dynamic nature of 3D chromatin architecture in human acute leukemia.\n\nOne Sentence Summary3D chromatin alterations in T cell leukemia are accompanied by changes in insulation and oncogene expression and can be partially restored by targeted drug treatments.

cancer biology↗

bioRxiv2019

An implicit lipid model for efficient reaction-diffusion simulations of protein binding to surfaces of arbitrary topology

Localization of proteins to a membrane is an essential step in a broad range of biological processes such as signaling, virion formation, and clathrin-mediated endocytosis. The strength and specificity of proteins binding to a membrane depend on the lipid composition. Single-particle reaction-diffusion methods offer a powerful tool for capturing lipid-specific binding to membrane surfaces by treating lipids explicitly as individual diffusible binding sites. However, modeling lipid particle populations is expensive. Here we present an algorithm for reversible binding of proteins to continuum surfaces with implicit lipids, providing dramatic speed-ups to many body simulations. Our algorithm can be readily integrated into most reaction-diffusion software packages. We characterize changes to kinetics that emerge from explicit versus implicit lipids as well as surface adsorption models, showing excellent agreement between our method and the full explicit lipid model. Compared to models of surface adsorption, which couple together binding affinity and lipid concentration, our implicit lipid model decouples them to provide more flexibility for controlling surface binding properties and lipid inhomogeneity, and thus reproducing binding kinetics and equilibria. Crucially, we demonstrate our methods application to membranes of arbitrary curvature and topology, modeled via a subdivision limit surface, again showing excellent agreement with explicit lipid simulations. Unlike adsorption models, our method retains the ability to bind lipids after proteins are localized to the surface (through e.g. a protein-protein interaction), which can greatly increase stability of multi-protein complexes on the surface. Our method will enable efficient cell-scale simulations involving proteins localizing to realistic membrane models, which is a critical step for predictive modeling and quantification of in vitro and in vivo dynamics.

biophysics↗

bioRxiv2019

m6A-binding YTHDF proteins promote stress granule formation by modulating phase separation of stress granule proteins

Diverse RNAs and RNA-binding proteins form phase-separated, membraneless granules in cells under stress conditions. However, the role of the prevalent mRNA methylation, m6A, and its binding proteins in stress granule (SG) assembly remain unclear. Here, we show that m6A-modified mRNAs are enriched in SGs, and that m6A-binding YTHDF proteins are critical for SG formation. Depletion of YTHDF1/3 inhibits SG formation and recruitment of m6A-modified mRNAs to SGs. Both the N-terminal intrinsically disordered region and the C-terminal m6A-binding YTH domain of YTHDF proteins are crucial for SG formation. Super-resolution imaging further reveals that YTHDF proteins are in a super-saturated state, forming clusters that reside in the periphery of and at the junctions between SG core clusters, and promote SG phase separation by reducing the activation energy barrier and critical size for condensate formation. Our results reveal a new function and mechanistic insights of the m6A-binding YTHDF proteins in regulating phase separation.

biochemistry↗

bioRxiv2019

Systems-level analysis identifies key regulators driving epileptogenesis in temporal lobe epilepsy

Temporal lobe epilepsy (TLE) is the most prevalent and often devastating form of epilepsy. The molecular mechanism underlying the development of TLE remains largely unknown, which hinders the discovery of effective anti-epileptogenic drugs. In this study, we built a systems-level analytic framework which integrates gene meta-signatures, gene coexpression network and cellular regulatory network to unveil the evolution landscape of epileptogenic process and to identify key regulators that govern the transition between different epileptogenesis stages. The time-specific hippocampal transcriptomic profiles from five independent rodent TLE models were grouped into acute, latent and chronic stages of epileptogenesis, and were utilized for generating stage-specific gene expression signatures. 13 cell-type specific functional modules were identified from the epilepsy-context coexpression network, and five of them were significantly associated with the entire epileptogenic process. By inferring the differential protein activity of gene regulators in each stage, 265 key regulators underlying epileptogenesis were obtained. Among them, 122 regulators were demonstrated being associated with high seizure frequency and/or hippocampal sclerosis in human TLE patients. Importantly, we discovered four new gene regulators (ANXA5, FAM107A, SEPT2 and SPARC) whose upregulation may drive the process of epileptogenesis and further lead to chronic recurrent seizures or hippocampal sclerosis. Our findings provide a landscape of the gene network dynamics underlying epileptogenesis and uncovered candidate regulators that may serve as potential targets for future anti-epileptogenic therapy development.

bioinformatics↗