Biology subjects

Yang, R.

Publications and source records attributed to Yang, R..

At least 163 records · Page 9Linked to original sources

bioRxiv2022

Dichotomic Regulation of Striatal Plasticity by Dynorphin

Modulation of corticostriatal plasticity alters the information flow throughout basal ganglia circuits and represents a fundamental mechanism for motor learning, action selection, and reward. Synaptic plasticity in the striatal direct- and indirect-pathway spiny projection neurons (dSPNs and iSPNs) are dichotomically regulated by two distinct networks of GPCR signaling cascades. While it is well-known that dopamine D2 and adenosine A2a receptors bidirectionally regulate iSPN plasticity, it remains unclear how D1 signaling modulation of synaptic plasticity is counteracted by a dSPN-specific Gi signaling. Here, we show that striatal dynorphin selectively suppresses long-term potentiation (LTP) through Kappa Opioid Receptor (KOR) in dSPNs. Both KOR antagonism and conditional deletion of dynorphin in dSPNs enhance LTP counterbalancing with different levels of D1 receptor activation. Behaviorally, mice lacking dynorphin specifically in dSPNs show normal motor behavior and reward-based learning, but enhanced flexibility during reversal learning. These findings support a model in which D1R and KOR signaling bidirectionally modulate synaptic plasticity in striatal direct pathways and behavior.

neuroscience↗

bioRxiv2022

Physiological and molecular mechanisms regulated mesophyll conductance under severe drought in water-saving drought-resistant rice

Water-saving and drought-resistant rice (WDR) is a new type of rice varieties. It plays an important role in responding to drought with high yield and has been widely planted in central China at present. High photosynthetic production potential caused by high mesophyll conductance (gm) is the main factor promoted high yield formation in drought for WDR. But little is known about physiological and molecular mechanisms regulated gm in drought for WDR. Therefore, WDR cultivar HY73 and drought-sensitive cultivar HLY898 were used for comparative studies with three irrigation regimes before applying severe drought treatment at heading to create different differential individuals of photosynthetic potential and gm. The results showed that cultivar HY73 had lower up-regulation different expression genes (DEGs) than cultivar HLY898 in drought at transcriptional level. Conversely, DEGs of down-regulation was higher in cultivar HY73 than cultivar HLY898. In addition, 3071 DEGs were clustered in 3 modules named Midnightblue (734 DEGs), Blue (921 DEGs), and Turquoise (1416 DEGs) in severe drought merged three irrigation regimes and both cultivars, which the modules had significant correlational relationship with gm based on weighted gene co-expression network analysis (P<0.05). Only DEGs in midnightblue module were enriched in photosynthesis process and positively regulated gm (P<0.05). The main biological process were photosynthesis (GO:0015979), light harvesting in photosystem I (GO:0009768), reductive pentose-phosphate cycle (GO:0019253), protein-chromophore linkage (GO:0018298), photosynthetic electron transport in photosystem I (GO:0009773), and photosystem II repair (GO:0010206). These results indicate that gm and energy distribution in PSI and PSII systems could synergistic effect photosynthetic production potential in severe drought for rice plants. In the modules, the 18 most highly connected hub genes were screened using co-expression networks method. RT-PCR analysis indicated that CSP41B, PGLP1A, LHCA5, and GSTU6 genes had a similar variation trend with gm among treatments for both cultivar. LHCA5 and CSP41B genes were significantly up-regulated in HY73 compared with HLY898 in drought (P<0.05). And the both genes locates in thylakoid membrane in photosystems. Therefore, LHCA5 and CSP41B genes could be key genes to synergistically manage gm and energy distribution in photosystems. Our results provide some new physiological and molecular mechanisms regulated gm in severe drought for WDR.

physiology↗

bioRxiv2022

ScanExitronLR: characterization and quantification of exitron splicing events in long-read RNA-seq data

SummaryExitron splicing is a type of alternative splicing where coding sequences are spliced out. Recently, exitron splicing has been shown to increase proteome plasticity and play a role in cancer. Long-read RNA-seq is well suited for quantification and discovery of alternative splicing events; however, there are currently no tools available for detection and annotation of exitrons in long-read RNA-seq data. Here we present ScanExitronLR, an application for the characterization and quantification of exitron splicing events in long-reads. From a BAM alignment file, reference genome and reference gene annotation, ScanExitronLR outputs exitron events at the transcript level. Outputs of ScanExitronLR can be used in downstream analyses of differential exitron splicing. A companion tool, AnnotateExitron, reports exitron annotations such as truncation or frameshift type, nonsense-mediated decay status, and Pfam domain interruptions. We demonstrate that ScanExitronLR performs better on noisy long-reads than currently published exitron detection algorithms designed for short-read data. Availability and ImplementationScanExitronLR is freely available at https://github.com/ylab-hi/ScanExitronLR and distributed as a pip package on the Python Package Index. Contactyang4414@umn.edu Supplementary InformationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2022

Drug design and repurposing with a sequence-to-drug paradigm

Drug development based on target proteins has been a successful approach in recent decades. A conventional structure-based drug design pipeline is a complex, human-engineered pipeline with multiple independently optimized steps. Advances in end-to-end differentiable learning suggest the potential benefits of similarly reformulating drug design. Here, we proposed a new sequence-to-drug paradigm that discovers drug-like small-molecule modulators directly from protein sequences and validated this concept for the first time in three stages. First, we designed TransformerCPI2.0 as a core tool for the sequence-to-drug paradigm, which exhibited competitive performance with conventional structure-based drug design approaches. Second, we validated the binding knowledge that TransformerCPI2.0 has learned. Third, we applied a sequence-to-drug paradigm to discover new hits for E3 ubiquitin-protein ligases: speckle-type POZ protein (SPOP), ring finger protein 130 (RNF130) which does not have a 3D structure, and repurposed proton pump inhibitors (PPIs) for ADP-ribosylation factor 1 (ARF1). This first proof of concept shows that the sequence-to-drug paradigm is a promising direction for drug development.

molecular biology↗

bioRxiv2022

Evidence for the role of music on the growth and signal response in duckweed

Sound vibration, an external mechanical force, has been proved to modulate plant growth and development like rain, wind, and vibration. However, the role of music on plants, especially on signal response, has been usually neglected in research. Herein, we investigated the growth state, gene expression, and signal response in duckweed treated with soft music. The protein content in duckweed after music treatment for 7 days was about 1.6 times that in duckweed without music treatment. Additionally, Fv/Fm in duckweed treated with music was 0.78, which was significantly higher in comparison with the control group (P < 0.01). Interestingly, music promoted the Glu and Ca signaling response. To further explore the global molecular mechanism, we performed transcriptome analysis. A total of 1296 DEGs were found for all these investigated genes in duckweed treated with music compared to the control group. Among these, up-regulation of the expression of metabolism-related genes related to glycolysis, cell wall biosynthesis, oxidative phosphorylation, and pentose phosphate pathways were found. Overall, these results provided a molecular basis to music-triggered signal response, transcriptomic, and growth changes in duckweed, which also highlighted the potential of music as an environmentally friendly stimulus to promote improved protein production in duckweed.

plant biology↗

bioRxiv2022

Invasiveness of Cancer Populations in a Two-dimensional Percolation cluster: a Stochastic Mathematical Approach

A framework for the software Unstructured Reaction-Diffusion Master Equation (URDME) was developed. A mitogenic paracrine signaling pathway was introduced phenomenologically to show how cells cooperate with one another. We modeled the emerging Allee effect using low seeding density culture (LSDC) assays to fit the model parameters. Finite time scaling (FTS) was found to be a useful tool for quantifying invasiveness in cancer populations. Through simulation, we analyzed the growth-migration dynamics of BT474 cancer cell populations in-vitro in a 2D percolation cluster and calculated the SPR (successful penetration rate). By analyzing the temporal trajectories of the SPR, we could determine the critical exponents of the critical SPR scaling relation [Formula]. Moreover, the SPR transition point defined according to the FTS theory, Pc, is negatively correlated with the invasiveness of cancer cell populations. The Pc of the three virtual cancer populations distinctly designated by varying the parameter set of the same model are 0.3408, 0.3675, and 0.4454, respectively. Therefore, the FTS algorithm may be useful in determining invasiveness. Through the simplistic phenomenological paracrine model, inter-cell cooperation and mutual mitogenic boosting are enabled, causing the Allee effect to occur. Such a method could be applied to other circumstances as an example of the quantitatively falsifiable emerging theory.

cancer biology↗

bioRxiv2022

Oligomer-to-Monomer Transition Underlies the Chaperone Function of AAGAB in AP1/AP2 Assembly

Assembly of protein complexes is facilitated by assembly chaperones. Alpha and gamma adaptin binding protein (AAGAB) is a chaperone governing the assembly of the heterotetrameric adaptor complexes 1 and 2 (AP1 and AP2) involved in clathrin-mediated membrane trafficking. Here, we found that before AP1/2 binding, AAGAB exists as a homotetramer. AAGAB tetramerization is mediated by its C-terminal domain, which is critical for AAGAB stability and is missing in mutant proteins found in patients with the skin disease punctate palmoplantar keratoderma type 1 (PPKP1). We solved the crystal structure of the tetramerization domain (TD), revealing a dimer of dimer assembly. Interestingly, AAGAB uses the same TD to recognize and stabilize the {gamma} subunit in the AP1 complex and the subunit in the AP2 complex, forming binary complexes containing only one copy of AAGAB. These findings demonstrate a dual role of TD in stabilizing resting AAGAB and binding to substrates, providing a molecular explanation for disease-causing AAGAB mutations. The oligomerization state transition mechanism may also underlie the functions of other assembly chaperones.

biochemistry↗

bioRxiv2022

Cryo-EM structure of an active central apparatus

Accurately regulated ciliary beating in time and space is critical for diverse cellular activities, which impact the survival and development of nearly all eukaryotic species. An essential beating regulator is the conserved central apparatus (CA) of motile cilia, composed of a pair of microtubules (C1 and C2) associated with hundreds of protein subunits per repeating unit. It is largely unclear how CA plays its regulatory roles in ciliary motility. Here, we present high-resolution structures of Chlamydomonas reinhardtii CA by cryo-electron microscopy (cryo-EM) and its dynamic conformational behavior in multiple scales. The structures show how functionally related projection proteins of CA are clustered onto a spring-shaped scaffold of armadillo-repeat proteins, facilitated by elongated rachis-like proteins. The two halves of CA are brought together by elastic chain-like bridge proteins to achieve coordinated activities. We captured an array of kinesin-like protein (KLP1) in two different stepping states, which are actively correlated with beating wave propagation of cilia. These findings establish a structural framework for understanding the role of CA in cilia.

cell biology↗

bioRxiv2022

Dissociating encoding of memory and salience by manipulating long-term synaptic potentiation

Neural codes are thought to be reorganized during memory formation by long-term potentiation (LTP) of synapses. Here, using a novel approach for selectively blocking LTP, we found that eliminating LTP in hippocampal or striatal circuits only produces limited effects on learning and memory. To reconcile the discrepancy between the large physiological effect of blocking LTP and the absent effect on learning, we studied how LTP impacts neuronal computations in the hippocampus using in-vivo Ca2+-imaging. Contrary to current conceptual frameworks, we found that hippocampal CA1-region LTP is not required for accurate representations of space in hippocampal neurons, but rather endows these neurons with reward- and novelty-coding properties. Thus, instead of driving formation of cognitive maps and memory engrams, CA1-region LTP incorporates salience information into cognitive representations. One-Sentence SummaryA novel approach for studying long-term potentiation reveals its surprising and selective role in salience encoding

neuroscience↗

bioRxiv2021

Application of a simple device for "attracting" and "trapping" glioma cells in situ

Glioblastoma multiforme (GBM) is the most malignant adult brain tumor. The current adjuvant therapies for GBM are disappointing, which are based on cytotoxicity strategy. Thus, other ways should be explored to improve the curative effect. According to the strong invasive ability of GBM cells, we assume a new treatment strategy for GBM by developing a new cell trap device (CTD) with some kind of "attractive" medium loaded in it to attract and capture the tumor cells. The in vitro experiment showed that Hepatocyte Growth Factor (HGF) presented stronger chemotaxis on C6 and U87 cell line than the Epidermal Growth Factor (EGF) and Fibroblast Growth Factor (FGF). A simple in vitro CTD loaded with HGF was made and in vivo experiments results showed that HGF successfully attracted tumor cells from tumor bed in situ into the CTD. This study proposes the new strategy for GBM treatment of "attract and trap" tumor cells is proved to be feasible.

neuroscience↗

bioRxiv2021

Isolation and characterization of fucosylated extracellular vesicles based on a novel GlyExo-Capture technique

Owing to their diagnostic and therapeutic potential, extracellular vesicles (EVs) derived from tumour cells have recently garnered great interest. The presence of different glycosylation sites at the EV surface supports the need for efficient glycosylated EV isolation. Here, we developed a GlyExo-Capture technique for robustly capturing fucosylated EVs from sera and cell supernatants. Lens culinaris lectin (LCA)-immobilized magnetic complexes were found to capture approximately 60% of the total EVs from HepG2 cells. The capture efficiency was reduced to less than 40% in nontumorigenic MIHA cells. Notably, the cellular uptake pattern of highly fucosylated EVs was markedly different from that of EVs with low fucosylation. The unearthing of enriched fucosylated EV miRNA cargos by next-generation deep sequencing (NGS) revealed 75 differentially expressed miRNAs (DEMs) in hepatocellular carcinoma (HCC). Among them, a 4-miRNA panel was chosen and yielded an area under the ROC curve (AUC) of 0.86 and 0.84 for the detection of HCC from non-HCC controls in testing samples and independent validation samples, respectively. The 4-miRNA signature was independent of alpha-fetoprotein (AFP), and a combined model with AFP yielded an increased AUC of 0.92. In conclusion, we developed a high-throughput method for capturing fucosylated EVs efficiently and shed light on the use of fucosylated EVs as potential sources of miRNAs for cancer biomarker detection.

cancer biology↗

bioRxiv2021

Epiphany: predicting Hi-C contact maps from 1D epigenomic signals

Recent deep learning models that predict the Hi-C contact map from DNA sequence achieve promising accuracy but cannot generalize to new cell types and indeed do not capture cell-type-specific differences among training cell types. We propose Epiphany, a neural network to predict cell-type-specific Hi-C contact maps from five epigenomic tracks that are already available in hundreds of cell types and tissues: DNase I hypersensitive sites and ChIP-seq for CTCF, H3K27ac, H3K27me3, and H3K4me3. Epiphany uses 1D convolutional layers to learn local representations from the input tracks, a bidirectional long short-term memory (Bi-LSTM) layers to capture long term dependencies along the epigenome, as well as a generative adversarial network (GAN) architecture to encourage contact map realism. To improve the usability of predicted contact matrices, we trained and evaluated models using multiple normalization and matrix balancing techniques including KR, ICE, and HiC-DC+ Z-score and observed-over-expected count ratio. Epiphany is trained with a combination of MSE and adversarial (i.a., a GAN) loss to enhance its ability to produce realistic Hi-C contact maps for downstream analysis. Epiphany shows robust performance and generalization to held-out chromosomes within and across cell types and species, and its predicted contact matrices yield accurate TAD and significant interaction calls. At inference time, Epiphany can be used to study the contribution of specific epigenomic peaks to 3D architecture and to predict the structural changes caused by perturbations of epigenomic signals.

genomics↗

bioRxiv2021

Single-cell RNA-seq analysis reveals aberrant CSF1 expression in disease-causing synovial fibroblasts of pigmented villonodular synovitis

ObjectivesAlthough the role of the CSF1/CSF1R axis in pigmented villonodular synovitis (PVNS) has been confirmed, the cells that express CSF1 and CSF1R and the underlying mechanism remain unclear. Single-cell RNA sequencing (scRNA-seq) of PVNS obtained through biopsies depicted the cellular diversity of PVNS, revealed specific CSF1/CSF1R-expressing cells and further identified novel gene expression that is associated with the development of PVNS. MethodsscRNA-seq was performed on tissues obtained from the 6 biopsies of 3 patients with PVNS. Flow cytometry, immunofluorescence and western blot validated the transcriptional results, while co-culture systems revealed the cross talk between fibroblasts and macrophages. Results8 subsets of fibroblasts and 5 subsets of macrophages were identified from the synovium of patients with PVNS and were found to be related to distinct signaling pathways. The cellular components of localized and diffuse PVNS are overall similar. Moreover, the synovium and nodule of PVNS share similar composition. The specific cells expressing CSF1/CSF1R were also identified. Other than that, unique CXCL12+CSF1+ fibroblasts were revealed to attract macrophages as disease-causing synovial fibroblasts, leading to the formation of masses in PVNS. ConclusionsPVNS consists of macrophages, fibroblasts, T cells, endothelial cells and mast cells. Among them, the CSF1-expressing fibroblasts appeared to be tumor-like cells that attract macrophages, subsequently forming tumor-like mass in PVNS. This paves the path for novel treatments of PVNS by targeting CXCL12+CSF1+ fibroblasts and the CXCL12-CXCR4 axis.

molecular biology↗

bioRxiv2021

Reference genomes of 545 silkworms enable high-throughput exploring genotype-phenotype relationships

The silkworm Bombyx mori is a domestic insect for silk production and a lepidopteran model. The currently available genomes limit a full understanding of its genetic and phenotypic diversity. Here we assembled long-read genomes of 545 domestic and wild silkworms and constructed a high-resolution pan-genome dataset. We found that the silkworm population harbors extremely variable genomes containing 7,308 new gene families, 4,260 (22%) core gene families, and 3,432,266 non-redundant SVs. We deciphered a series of causal genes and variants associated with domestication, breeding, and ecological adaptation traits, and experimentally validated two of those genes using CRISPR-Cas9 or RNA interference. This unprecedented large-scale genomic resource allows for high-throughput screening of interesting traits for functional genomic research and breeding improvement of silkworms and may serve as a guideline for traits decoding in other species.

genomics↗

bioRxiv2021

Genomic evidence for divergent co-infections of SARS-CoV-2 lineages

Recently, patients co-infected by two SARS-CoV-2 lineages have been sporadically reported. Concerns are raised because previous studies have demonstrated co-infection may contribute to the recombination of RNA viruses and cause severe clinic symptoms. In this study, we have estimated the compositional lineage(s), tendentiousness, and frequency of co-infection events in population from a large-scale genomic analysis for SARS-CoV-2 patients. SARS-CoV-2 lineage(s) infected in each sample have been recognized from the assignment of within-host site variations into lineage-defined feature variations by introducing a hypergeometric distribution method. Of all the 29,993 samples, 53 (~0.18%) co-infection events have been identified. Apart from 52 co-infections with two SARS-CoV-2 lineages, one sample with co-infections of three SARS-CoV-2 lineages was firstly identified. As expected, the co-infection events mainly happened in the regions where have co-existed more than two dominant SARS-CoV-2 lineages. However, co-infection of two sub-lineages in Delta lineage were detected as well. Our results provide a useful reference framework for the high throughput detecting of SARS-CoV-2 co-infection events in the Next Generation Sequencing (NGS) data. Although low in average rate, the co-infection events showed an increasing tendency with the increased diversity of SARS-CoV-2. And considering the large base of SARS-CoV-2 infections globally, co-infected patients would be a nonnegligible population. Thus, more clinical research is urgently needed on these patients.

microbiology↗

bioRxiv2021

HAMdetector: A Bayesian regression model that integrates information to detect HLA-associated mutations

MotivationA key process in anti-viral adaptive immunity is that the Human Leukocyte Antigen system (HLA) presents epitopes as Major Histocompatibility Complex I (MHC I) protein-peptide complexes on cell surfaces and in this way alerts CD8+ cytotoxic T-Lymphocytes (CTLs). This pathway exerts strong selection pressure on viruses, favoring viral mutants that escape recognition by the HLA/CTL system, e.g. by point mutations that decrease binding of viral peptides to MHC I. Naturally, such immune escape mutations often emerge in highly variable viruses, e.g. HIV or HBV, as HLA-associated mutations (HAMs), specific to the host HLA alleles and its MHC I proteins. The reliable identification of HAMs is not only important for understanding viral genomes and their evolution, but it also impacts the development of broadly effective anti-viral treatments and vaccines against variable viruses. By their very nature HAMs are amenable to detection by statistical methods in paired sequence / HLA data. However, HLA alleles are very polymorphic in the human host population which makes the available data relatively sparse and noisy. Under these circumstances, one way to optimize HAM detection is to integrate all relevant information in a coherent model. Bayesian inference offers a principled approach to achieve this. ResultsWe present a new regression model for the detection of HAMs. As we choose a Bayesian approach we can include the novel sparsity-inducing priors, and we obtain easily interpretable quantitative information on HAM candidates. The basic model can be extended to include prior information relevant to HAM detection, which we demonstrate by integrating predictions of epitope affinities to MHC I, predictions of epitope peptide processing, and computation of phylogenetic background. This integrative method improves performance in HAM detection considerably over state-of-the-art methods. AvailabilityThe source code of this software is available at https://github.com/HAMdetector/Escape.jl under a permissive MIT license. Contactdaniel.habermann@uni-due.de, daniel.hoffmann@uni-due.de

bioinformatics↗

bioRxiv2021

Inhibiting adenine synthesis attenuates glioblastoma cell stemness and temozolomide resistance

Glioblastoma (GBM) is a lethal brain cancer exhibiting high levels of drug resistance, a feature partially imparted by tumor cell stemness. Recent work shows that homozygous MTAP deletion, a genetic alteration occurring in about half of all GBMs, promotes stemness in GBM cells. Exploiting MTAP loss-conferred deficiency in adenine salvage, we demonstrate that transient adenine blockade via treatment with L-Alanosine (ALA), an inhibitor of de novo adenine synthesis, attenuates stemness of MTAP-deficient GBM cells. This ALA-induced reduction in stemness is accompanied by compromised mitochondrial function, highlighted by diminished spare respiratory capacity. Direct pharmacological inhibition of mitochondrial respiration recapitulates the effect of ALA on GBM cell stemness, suggesting ALA targets stemness partially via affecting mitochondrial function. Finally, in agreement with diminished stemness and compromised mitochondrial function, we show that ALA sensitizes GBM cells to temozolomide (TMZ) in vitro and in an orthotopic GBM model. Collectively, these results identify critical roles of adenine supply in maintaining mitochondrial function and stemness of GBM cells, highlight a critical role of mitochondrial function in sustaining GBM stemness, and implicate adenine synthesis inhibition as a complementary approach for treating MTAP-deleted GBMs.

cancer biology↗

bioRxiv2021

Distribution and vulnerability of transcriptional outputs across the genome in Myc-amplified medulloblastoma cells

Myc plays a central role in tumorigenesis by orchestrating the expression of genes essential to numerous cellular processes1-4. While it is well established that Myc functions by binding to its target genes to regulate their transcription5, the distribution of the transcriptional output across the human genome in Myc-amplified cancer cells, and the susceptibility of such transcriptional outputs to therapeutic interferences remain to be fully elucidated. Here, we analyze the distribution of transcriptional outputs in Myc-amplified medulloblastoma (MB) cells by profiling nascent total RNAs within a temporal context. This profiling reveals that a major portion of transcriptional action in these cells was directed at the genes fundamental to cellular infrastructure, including rRNAs and particularly those in the mitochondrial genome (mtDNA). Notably, even when Myc protein was depleted by as much as 80%, the impact on transcriptional outputs across the genome was limited, with notable reduction mostly only in genes involved in ribosomal biosynthesis, genes residing in mtDNA or encoding mitochondria-localized proteins, and those encoding histones. In contrast to the limited direct impact of Myc depletion, we found that the global transcriptional outputs were highly dependent on the activity of Inosine Monophosphate Dehydrogenases (IMPDHs), rate limiting enzymes for de novo guanine nucleotide synthesis and whose expression in tumor cells was positively correlated with Myc expression. Blockage of IMPDHs attenuated the global transcriptional outputs with a particularly strong inhibitory effect on infrastructure genes, which was accompanied by the abrogation of MB cells proliferation in vitro and in vivo. Together, our findings reveal a real time action of Myc as a transcriptional factor in tumor cells, provide new insight into the pathogenic mechanism underlying Myc-driven tumorigenesis, and support IMPDHs as a therapeutic vulnerability in cancer cells empowered by a high level of Myc oncoprotein.

cancer biology↗