Biology subjects

Huang, Z.

Publications and source records attributed to Huang, Z..

At least 361 records · Page 20Linked to original sources

bioRxiv2020

Integrated profiling of single cell epigenomic and transcriptomic landscape of Parkinson's disease mouse brain

Parkinsons disease (PD) is a neurodegenerative disease leading to the impairment of execution of movement. PD pathogenesis has been largely investigated, but either restricted in bulk level or at certain cell types, which failed to capture cellular heterogeneity and intrinsic interplays among distinct cell types. To overcome this, we applied single-nucleus RNA-seq and single cell ATAC-seq on cerebellum, midbrain and striatum of PD mouse and matched control. With 74,493 cells in total, we comprehensively depicted the dysfunctions under PD pathology covering proteostasis, neuroinflammation, calcium homeostasis and extracellular neurotransmitter homeostasis. Besides, by multi-omics approach, we identified putative biomarkers for early stage of PD, based on the relationships between transcriptomic and epigenetic profiles. We located certain cell types that primarily contribute to PD early pathology, narrowing the gap between genotypes and phenotypes. Taken together, our study provides a valuable resource to dissect the molecular mechanism of PD pathogenesis at single cell level, which could facilitate the development of novel methods regarding diagnosis, monitoring and practical therapies against PD at early stage.

cell biology↗

bioRxiv2020

Ultra-deep sequencing differentiates patterns of skin clonogenic mutations associated with sun-exposure status

Non-melanoma skin cancer is the most common human malignancy and is primarily caused by exposure to ultraviolet (UV) radiation. The earliest detectable precursor of UV-mediated skin cancer is the growth of cell groups harboring clonal mutation (CM) in clinically normal appearing skin. Systematic evaluation of CMs is crucial to understand early photo-carcinogenesis. Previous studies confirmed the presence of CMs in sun-exposed skin. However, the relationship between UV-exposure and the accumulation of CMs, and the correlation of CMs with skin cancer risk remain poorly understood. To elucidate the exact molecular and clinical effects of long-term UV-exposure on skin, we performed targeted ultra-deep sequencing in 450 individual-matched sun-exposed (SE) and non-sun-exposed (NE) epidermal punch biopsies obtained from clinically normal skin from 13 donors. A total of 638 CMs were identified, including 298 UV-signature mutations (USMs). The numbers of USMs per sample were three times higher in the SE samples and were associated with significantly higher variant allele frequencies (VAFs), compared with the NE samples. We identified genomic regions in TP53, NOTCH1 and GRM3 where mutation burden was significantly associated with UV-exposure. Six mutations were almost exclusively present in SE epidermis and accounted for 42% of the overall difference between SE and NE mutation burden. We defined Cumulative Relative Clonal Area (CRCA), a single metric of UV-damage calculated by the overall relative percentage of the sampled skin area affected by CMs. The CRCA was dramatically elevated by a median of 11.2 fold in SE compared to NE samples. In an extended cohort of SE normal skin samples from patients with a high- or low-burden of cutaneous squamous cell carcinoma (cSCC), the SE samples in high-cSCC patients contained significantly more USMs than SE samples in low-cSCC patients, with the difference mostly conferred by mutations from low-frequency clones (defined by VAF≤1%) but not expanded clones (VAF>1%). Our studies of differential mutational features in normal skin between paired SE/NE body sites and high/low-cSCC patients provide novel insights into the carcinogenic effect of UV exposure, and suggest CMs might be used to develop novel biomarkers for predicting cancer risk.Significance statement In UV radiation exposed skin, mutations fuel clonal cell growth. We established a sequencing-based method to objectively assess the mutational differences between sun-exposed (SE) and non-sun-exposed (NE) areas of normal human skin. Striking differences, in both the numbers of mutations and variant allele frequencies, were found between SE and NE areas. Furthermore, we identified specific genomic regions where mutation burden is significantly associated with UV-exposure status. These findings revealed previously unknown mutational patterns associated with UV-exposure, providing important insights into UV radiation’s early carcinogenic effects. Additionally, in an extended cohort, we identified preliminary association between normal skin mutation burden and cancer risk. These findings pave the road for future development of quantitative measurement of subclinical UV damage and skin cancer risk.Competing Interest StatementThe authors have declared no competing interest.Common AbbreviationsUVUltravioletCMClonogenic mutationNMSCNonmelanoma skin cancerSESun-exposedNENon-sun-exposedUSMUV-signature mutationNUSMNon-UV-signature mutationCRCACumulative Relative Clonal AreacSCCCutaneous squamous cell carcinomaAKActinic keratosisSNVSingle nucleotide variant Indels – Insertions/deletionsDNVDinucleotide variantCSNVCluster of single nucleotide variantMACMulti-Nucleotide Variant Annotation CorrectorVAFVariant allele frequencyView Full Text

cancer biology↗

bioRxiv2019

STAT3 localizes in mitochondria-associated ER membranes instead of in mitochondria

Signal Transducer and Activator of Transcription 3 (STAT3) is a transcription factor (TF) that regulates a variety of biological processes, including a key role in mediating mitochondrial metabolism. It has been shown that STAT3 performs this function by translocating in minute amounts into mitochondria and interacting with mitochondrial proteins and genome. However, whether STAT3 localizes in mitochondria is still up for debate. To decipher the role of mitochondrial STAT3 requires a detailed understanding of its cellular localization. Using Percoll density gradient centrifugation, we surprisingly found that STAT3 is not located in the mitochondrial fraction, but instead, in the mitochondria-associated endoplasmic reticulum membrane (MAM) fraction. This was confirmed by sub-diffraction image analysis of labeled mitochondria in embryonic astrocytes. Also, we find that other TFs that have been previously found to localize in mitochondria are also found instead in the MAM fraction. Our results suggest that STAT3 and other transcriptional factors are, contrary to prior studies, consolidated specifically at MAMs, and further efforts to understand mitochondrial STAT3 function must take into consideration this localization, as the associated functional consequences offer a different interpretation to the questions of STAT3 trafficking and signaling in the mitochondria.

cell biology↗

bioRxiv2019

An optimized 16S rRNA sequencing protocol for vaginal microbiome to avoid biased abundance estimation

We applied three 16S rRNA sequencing protocols on vaginal microbiome samples, to evaluate whether they produce unbiased estimation of vaginal microbiome composition. We modified the 27F primer (hereafter denoted as 27F). Using vaginal samples from 28 healthy women and 10 women with bacterial vaginosis, we sequenced three 16S rRNA sequencing protocols, i.e., 27F-338R, 27F-338R and 341F-806R protocols, naming after their PCR primer sets, to test whether the sequencing results are consistent with the clinical diagnostics, morphology and qPCR results. First, the 27F primer would not align with Gardnerlla vaginalis very well, leading to poor amplification of such species. By modifying the primer sequences, the modified 27F primer (27F) was able to amplify Gardnerlla vaginalis very well. Second, the DNA sequence of characteristic species Lactobacillus crispatus is identical with Lactobacillus garrinarum, leading to biased estimation of abundance of Lactobacillus crispatus when using V3-V4 as PCR target region; in contrast, such bias did not occur when using V1-V2 as a target region. Third, optimized 27F-338R avoided above-mentioned biases and restored the well-established community state types (CSTs) clustering. ImportanceVaginal microbiome has profound effects on the health of women and their newborns. Our study found that two well-established 16S rDNA sequencing protocols led to systementical biased estimation of characteristic species of vaginal microbiome. Subsequent analysis proved that the PCR primer fetching efficacy and target region identity were major contributor for such bias. With carefully selected target region and optimized PCR primer set, we were able to eliminate such biases and provide accurate estimation of vaginal microbiome, which showed high consistency with clinical diagnostics. We modified the 27F primer (27F). Using the optimized PCR primer set of 27F and 338R to target the V1-V2 hyper-variable region, our 16S rRNA sequencing correctly evaluate the composition of vaginal microbiome.

microbiology↗

bioRxiv2019

Stress-induced myonectin improves glucose homeostasis by inhibiting glycemic response to HPA axis

Inhibiting glycemic response to HPA axis contributes to glycemic control for diabetic patients. Here, mice were subjected to high-fat diet and intermittent chronic stress, and glucose homeostasis and lipolysis were determined during the intervention. Firstly, we found that glucose intolerance appears at the earliest, followed by reduced insulin sensitivity and increased epinephrine (EPI) sensitivity in the early stage of diet-induced obesity. Next we investigated whether chronic stress impairs glycemic control and which mediates its effects. Short-term stress training raises serum and skeletal muscle myonectin (Myn) levels and improves glucose intolerance. Stress attenuates blood glucose and glycerol responses to EPI, but enhances lipolytic response to EPI in adipose tissues. Myn overexpression in vivo improves glucose tolerance and enhances insulin sensitivity at the cost of blunting glycemic responses to EPI. Myn knockdown reduces beneficial effects of stress or exercise on glucose homeostasis. Together, myonectin is a stress-induced myokine that readjusts glycemic and metabolic responses to HPA axis, and thus prevent the progression of glucose intolerance and obesity. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC="FIGDIR/small/838003v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@42b09forg.highwire.dtl.DTLVardef@59a744org.highwire.dtl.DTLVardef@1f4a01dorg.highwire.dtl.DTLVardef@13bda27_HPS_FORMAT_FIGEXP M_FIG C_FIG One Sentence SummaryChronic stress breaks glucose intolerance cycle to resist diet-induced obesity, through myonectin-mediated inhibition of glycemic response to epinephrine (EPI) and activation of insulin signaling in adipose tissues. HighlightsO_LIEPI sensitivity increases after glucose intolerance and with reduced insulin sensitivity in diet-induced obesity C_LIO_LIChronic stress blunts glycemic responses to EPI and increases myonectin levels in serum and skeletal muscle C_LIO_LIMyonectin attenuates glycemic response to EPI and improves metabolic profile in HFD-fed mice C_LIO_LIReducing myonectin reverses beneficial effects of stress on glucose homeostasis C_LI

physiology↗

bioRxiv2019

Six new reference-quality bat genomes illuminate the molecular basis and evolution of bat adaptations

Bats account for ~20% of all extant mammal species and are considered exceptional given their extraordinary adaptations, including biosonar, true flight, extreme longevity, and unparalleled immune systems. To understand these adaptations, we generated reference-quality genomes of six species representing the key divergent lineages. We assembled these genomes with a novel pipeline incorporating state-of-the-art long-read and long-range sequencing and assembly techniques. The genomes were annotated using a maximal evidence approach, de novo predictions, protein/mRNA alignments, Iso-seq long read and RNA-seq short read transcripts, and gene projections from our new TOGA pipeline, retrieving virtually all (>99%) mammalian BUSCO genes. Phylogenetic analyses of 12,931 protein coding-genes and 10,857 conserved non-coding elements identified across 48 mammalian genomes helped to resolve bats closest extant relatives within Laurasiatheria, supporting a basal position for bats within Scrotifera. Genome-wide screens along the bat ancestral branch revealed (a) selection on hearing-involved genes (e.g LRP2, SERPINB6, TJP2), which suggest that laryngeal echolocation is a shared ancestral trait of bats; (b) selection (e.g INAVA, CXCL13, NPSR1) and loss of immunity related proteins (e.g. LRRC70, IL36G), including pro-inflammatory NF-kB signalling; and (c) expansion of the APOBEC family, associated with restricting viral infection, transposon activity and interferon signalling. We also identified unique integrated viruses, indicating that bats have a history of tolerating viral pathogens, lethal to other mammal species. Non-coding RNA analyses identified variant and novel microRNAs, revealing regulatory relationships that may contribute to phenotypic diversity in bats. Together, our reference-quality genomes, high-quality annotations, genome-wide screens and in-vitro tests revealed previously unknown genomic adaptations in bats that may explain their extraordinary traits.

genomics↗

bioRxiv2019

Riboflavin Directly Mediates the Dealkylation by Microbial Cytochrome P450 Monooxygeneses

As a vast repertoire of enzymes in nature, microbial cytochrome P450 monooxygenases require an activated form of flavin as a cofactor for the catalytic activity. Riboflavin is the precursor of FAD and FMN that serve as indispensable cofactors for flavoenzymes. In contrast to previous notion, here we describe the identification of an electron transfer process directly mediated by riboflavin for the N-dealkylation by microbial P450 monooxygenases. The electron relay from NADPH to riboflavin and then via activated oxygen to heme was proposed based on the combination of X-ray crystallography, molecular modeling and molecular dynamics simulation, site-directed mutagenesis and biochemical analysis of representative microbial P450 monooxygenases. This study provides new insights into the electron transfer mechanism in microbial P450 enzyme catalysis and likely in plants and mammals.

biochemistry↗

bioRxiv2019

Intrinsic Architecture of Global Signal Topography and Its Modulation by Tasks

Recent resting-state fMRI studies have revealed that the global signal (GS) exhibits a non-uniform spatial distribution across the gray matter. Whether this topography is informative remains largely unknown. We therefore tested rest-task modulation of global signal topography by analyzing static global signal correlation and dynamic co-activation patterns in a large sample of fMRI dataset (n=837) from the Human Connectome Project. The GS topography in the resting-state and in seven different tasks was first measured by correlating the global signal with the local timeseries (GSCORR). In the resting state, high GSCORR was observed mainly in the primary sensory and motor regions, while low GSCORR was seen in the association brain areas. This pattern changed during the seven tasks, with mainly decreased GSCORR in sensorimotor cortex. Importantly, this rest-task modulation of GSCORR could be traced to transient co-activation patterns at the peak period of global signal (GS-peak). By comparing the topography of GSCORR and respiration effects, we observed that the topography of respiration mimicked the topography of global signal in the resting-state whereas both differed during the task states; due to such partial dissociation, we assume that GSCORR could not be equated with a respiration effect. Finally, rest-task modulation of GS topography could not be exclusively explained by other sources of physiological noise. Together, we here demonstrate the informative nature of global signal topography by showing its rest-task modulation, the underlying dynamic co-activation patterns, and its partial dissociation from respiration effects during task states.

neuroscience↗

bioRxiv2019

TSUNAMI: Translational Bioinformatics Tool Suite For Network Analysis And Mining

Gene co-expression network (GCN) mining identifies gene modules with highly correlated expression profiles across samples/conditions. It helps to discover latent gene/molecular interactions, identify novel gene functions, and extract molecular features from certain disease/condition groups, thus help to identify disease biomarkers. However, there lacks an easy-to-use tool package for users to mine GCN modules that are relatively small in size with tightly connected genes that can be convenient for downstream Gene Ontology (GO) enrichment analysis, as well as modules that may share common members. To address this need, we develop a GCN mining tool package TSUNAMI (Tools SUite for Network Analysis and MIning) which incorporates our state-of-the-art lmQCM algorithm to mine GCN modules in public and user-input data (microarray, RNA-seq, or any other numerical omics data), then performs downstream GO and enrichment analysis based on the modules identified. It has several features and advantages: (i) user friendly interface and the real-time co-expression network mining through web server; (ii) direct access and search of GEO and TCGA databases as well as user-input expression matrix (microarray, RNA-seq, etc.) for GCN module mining; (iii) multiple co-expression analysis tools to choose with highly flexible of parameter selection options; (iv) identified GCN modules are summarized to eigengenes, which are convenient for user to check their correlation with other clinical traits; (v) integrated downstream Enrichr enrichment analysis and links to other GO tools; (vi) visualization of gene loci by Circos plot in any step. The web service is freely accessible through URL: http://spore.ph.iu.edu:3838/zhihuan/TSUNAMI/. Source code is available at https://github.com/huangzhii/TSUNAMI/.

bioinformatics↗

bioRxiv2019

The effects of carnosine pretreatment on the inflammatory response and the PI3K/Akt signaling pathway following hypoxia-ischemia in neonatal rats

An increasing number of studies have demonstrated that carnosine plays a neuroprotective role in many types of brain injury. We have previously shown that carnosine has both short-term and long-lasting neuroprotective effects in a hypoxia-ischemia(HI) rat model. In the mature brain, post-ischemia neuronal survival involves in activation of the phosphatidylinositol 3-kinase (PI3K)/Akt signaling pathway, whether the activation of PI3K/Akt pathway also plays an important role in the immature brain still remain unclear.The goal of this study is to detect the effection of carnosine on inflammation response following HI, further evidencing neuroprotection of carnosine. We measured total Akt, phospho-Akt (p-AKT) and tumor necrosis factor receptor 1 (TNFR1) protein levels by western blot assay and tumor necrosis factor- (TNF-) and TNFR1 mRNA expression using real-time RT-PCR. We found the carnosine-pretreated group had statistically significant downregulation of TNF- mRNA levels 24 h after HI (P < 0.05). Similar results were observed when we measured TNFR1 mRNA levels both 24h and 72h after HI (P < 0.05). And the TNFR1 protein expression after HI was markedly decreased at 24 and 72 h post-HI in the carnosine-pretreated rats(P < 0.05). Nevertheless, the rats pretreated with carnosine showed a marked increase in p-Akt levels (P< 0.05). And the pro-apoptotic protein Bad was also examined using immunohistochemistry after 24 and 72 h of all groups. We found significantly fewer Bad-positive cells in the carnosine-pretreated group at each time point after HI (P < 0.05). These findings suggest that carnosine pretreatment inhibits the HI-induced inflammatory response, and neuroprotection mechanism of carnosine involved in activation of the PI3K/Akt signaling pathway.

neuroscience↗

bioRxiv2019

Type-specific dendritic integration in mouse retinal ganglion cells

Neural computation relies on the integration of synaptic inputs across a neurons dendritic arbour. However, the fundamental rules that govern dendritic integration are far from understood. In particular, it is still unclear how cell type-specific differences in dendritic integration arise from general features of neural morphology and membrane properties. Here, retinal ganglion cells (RGCs), which relay the visual systems first computations to the brain, represent an exquisite model. They are functionally and morphologically diverse yet defined, and they allow studying dendritic integration in a functionally relevant context. Here, we show how four morphologically distinct types of mouse RGC with shared excitatory synaptic input (transient Off alpha, transient Off mini, sustained Off, and F-miniOff) exhibit distinct dendritic integration rules. Using two-photon imaging of dendritic calcium signals and biophysical modelling, we demonstrate that these RGC types strongly differ in their spatio-temporal dendritic integration: In transient Off alpha cells, dendritic receptive fields displayed little spatial overlap, indicative of a dendritic arbour that is partitioned in largely isolated regions. In contrast, dendritic receptive fields in the other three RGCs overlapped greatly and were offset to the soma, suggesting strong synchronization of dendritic signals likely due to backpropagation of somatic signals. Also temporal correlation of dendritic signals varied extensively among these types, with transient Off mini cells displaying the highest correlation across their dendritic arbour. Modelling suggests that morphology alone cannot explain these differences in dendritic integration, but instead specific combinations of dendritic morphology and ion channel densities are required. Together, our results reveal how neurons exhibit distinct dendritic integration profiles tuned towards their type-specific computations in their circuits, with the interplay between morphology and ion channel complement as a key contributor.

neuroscience↗

bioRxiv2019

Targeting dormant ovarian cancer cells in vitro and in an in vivo model of platinum resistance

ObjectiveOvarian cancer cells often exist in vivo as multicellular spheroids. Spheroid formation in vitro has been used to enrich for cancer stem cell populations from primary tumors. Such spheroids exhibit drug resistance and slow proliferation, suggesting involvement in disease recurrence. Our objectives were to characterize cancer spheroid phenotypes, determine gene expression profiles associated with spheroid forming capacity and to evaluate the responsiveness of spheroids to commonly used and novel therapeutic agents.\n\nMethodsTumorigenic potential was assessed using anchorage independent growth assays in 24 cell lines. Spheroids from cell lines (N=12) and from primary cancers (N=8) were grown on non-adherent tissue culture plates in serum-free media. Cell proliferation was measured using MTT assays and Ki67 immunostaining. Affymetrix HT U133A gene expression data was used to identify differentially expressed genes based on spheroid forming capacity. Matched monolayers and spheroids (N=7 pairs) were tested for response to cisplatin, paclitaxel and 7-hydroxystaurosporine (UCN-01) while mitochondrial inhibition was performed using oligomycin. Xenograft tumors from intraperitoneal injection of CAOV2-GFP/LUC ovarian cancer cells into nude mice were treated with carboplatin to reduce tumor burden followed by secondary treatment with carboplatin, UCN-01, or Oltipraz. Tumor formation and response was monitored using live imaging.\n\nResultsOf 12 cell lines with increased anchorage-independent growth, 8 also formed spheroids under serum-free spheroid culture conditions. Spheroids showed reduced proliferation (p<0.0001) and Ki67 immunostaining (8% versus 87%) relative to monolayer cells. Spheroid forming capacity was associated with increased mitochondrial pathway activity (p [≤] 0.001). The mitochondrial inhibitors, UCN-01 and Oligomycin, demonstrated effectiveness against spheroids, while spheroids were refractory to cisplatin and paclitaxel. By live in vivo imaging, ovarian cancer xenograft tumors were reduced after primary treatment with carboplatin. Continued treatment with carboplatin was accompanied by an increase in tumor signal while there was little or no increase in tumor signal observed with subsequent treatment with UCN-01 or Oltipraz.\n\nConclusionsOur findings suggest that the mitochondrial pathway in spheroids may be an important therapeutic target in preventing disease recurrence.

cancer biology↗

bioRxiv2019

Analysis of the Mutant Selection Window and Killing of Mycoplasma hyopneumoniae for Doxycycline, Tylosin, Danofloxacin, Tiamulin, and Valnemulin

Mycoplasma hyopneumoniae is the major pathogenic microorganism causing enzootic pneumonia in pigs. With increasing resistance of M. hyopneumoniae to conventional antibiotics, treatment is becoming complicated. Herein, we investigated the mutant selection window (MSW) of doxycycline, tylosin, danofloxacin, tiamulin, and valnemulin for treating M. hyopneumoniae strain (ATCC 25934) to determine the likelihood of promoting resistance with continued use of these antibiotics. Minimum inhibitory concentration (MIC) values against M. hyopneumoniae were determined for each antimicrobial agent and ranged from 105 colony-forming units (CFU)/mL to 109 CFU/mL based on microdilution broth and agar dilution methods. The minimal concentration inhibiting colony formation by 99% (MIC99) and the mutant prevention concentration (MPC) were determined by the agar dilution method with three inoculum sizes. Antimicrobial killing was determined based on MIC99 and MPC values for all five agents. MIC values ranged from 0.001 to 0.25 g/mL based on the microdilution broth method, and from 0.008 to 1.0 g/mL based on the agar dilution method. MPC values ranged from 0.0016 to 10.24 g/mL. MPC/MIC99 values were ordered tylosin >doxycycline >danofloxacin >tiamulin >valnemulin. MPC achieved better bactericidal action than MIC99. Based on pharmacodynamic analyses, danofloxacin, tylosin, and doxycycline are more likely to select resistant mutants than tiamulin and valnemulin.

pharmacology and toxicology↗

bioRxiv2019

PHISDetector: a web tool to detect diverse in silico phage-host interaction signals

Phage-microbe interactions not only are appealing systems to study coevolution but also have been increasingly emphasized due to their roles in human health, diseases, and novel therapeutic development. Meanwhile, their interactions leave diverse signals in bacterial and phage genomic sequences, defined as phage-host interaction signals (PHISs), such as sequence composition, CRISPR targeting, prophage, and protein-protein interaction signals. We infer that proper detection and integration of these diverse PHISs will allow us to predict phage-host interactions. Here, we developed PHISDetector, a novel tool to predict phage-host interactions by detecting and integrating diverse in silico PHISs and scoring the probability of phage-host interactions using machine-learning models based on PHIS features. PHISDetector is available as a one-stop web service version for general users to study individual inputs. A stand-alone software version is also provided to process massive phage contigs from virome studies. PHISDetector is freely available at http://www.microbiome-bigdata.com/PHISDetector/ and https://github.com/HIT-ImmunologyLab/PHISDector.

bioinformatics↗

bioRxiv2019

Landscape and regulation of m6A and m6Am methylome across human and mouse tissues

N6-methyladenosine (m6A), the most abundant internal mRNA modification, and N6,2-O-dimethyladenosine (m6Am), found at the first-transcribed nucleotide, are two examples of dynamic and reversible epitranscriptomic marks. However, the profiles and distribution patterns of m6A and m6Am across different human and mouse tissues are poorly characterized. Here we report the m6A and m6Am methylome through an extensive profiling of 42 human tissues and 16 mouse tissue samples. Globally, the m6A and m6Am peaks in non-brain tissues demonstrates mild tissue-specificity but are correlated in general, whereas the m6A and m6Am methylomes of brain tissues are clearly resolved from the non-brain tissues. Nevertheless, we identified a small subset of tissue-specific m6A peaks that can readily classify the tissue types. The number of m6A and m6Am peaks are partially correlated with the expression levels of their writers and erasers. In addition, the m6A- and m6Am-containing regions are enriched for single nucleotide polymorphisms. Furthermore, cross-species analysis of m6A and m6Am methylomes revealed that species, rather than tissue types, is the primary determinant of methylation. Collectively, our study provides an in-depth resource for dissecting the landscape and regulation of the m6A and m6Am epitranscriptomic marks across mammalian tissues.

molecular biology↗

bioRxiv2019

PD-L1:CD80 Heterodimer Triggers CD28 While Repressing Both PD-1 and CTLA4 Pathways

Combined immunotherapy with anti-PD-1/PD-L1 and anti-CTLA4 has resulted in superior clinical responses compared to single agent therapy. The underlying mechanisms for this synergy have yet to be elucidated and investigations have largely focused on cellular interactions. Herein, we report a molecular crosstalk in which the PD-1 ligand PD-L1 and the CTLA4 ligand CD80 heterodimerize in cis. This heterodimerization blocks both PD-L1:PD-1 and CD80:CTLA4 interactions, but preserves the ability of CD80 to activate the T cell costimulatory receptor CD28. Remarkably, PD-L1 expression on antigen presenting cells (APCs) protects CD80 from CTLA4 mediated trans-endocytosis, and the therapeutic PD-L1 blockade antibody atezolizumab paradoxically downregulates CD80 on APCs, presumably reducing its co-stimulatory ability. Importantly, this effect can be negated by co-blockade of CTLA4 with ipilimumab. Our study reveals an unexpected immune stimulatory role of cis-acting PD-L1 and a mechanism of anti-PD-L1/anti-CTLA4 crosstalk, providing a therapeutic rationale for combination blockade of PD-L1 and CTLA4.

immunology↗

bioRxiv2019

Raven Calls Indicate Sender’s Neural State

Vocal communication accounts for dominantly percentage within animal species. The information of vocal samples contains not only the amplitude of objects, but also the emotional states behind it. However, to extract the emotion state behind the sound remains controversial. Here we introduce an artificial network method, the Back Propagation Neural Network, BPNN, to classify the emotional states behind the sound. The results disclosed the behaviour categories, including alarm, flight, begging and singing which has been successfully classified. This artificial intelligence classification may aid us to distinguish the ecological categories via animal vocal communication and to discover its significance of evolution and nature.

bioengineering↗

bioRxiv2019

Coloring Single Nanoparticle Trajectory on Live Cell Membrane with its Own History: a Presuppositionless Approach

Analyzing single particle trajectories is a prominent issue in understanding complex dynamics such as nanoparticle-cell interactions. Existing methods treat data points as isolated \"atoms\" and use predefined mechanical models to \"frame\" their complicated relationship. Herein, we propose a \"historical evolution\" based model-free strategy. It allows spatiotemporal heterogeneity embedded in a trajectory to self-emerge as consecutive colored segments before any model assumption, provide both an overall picture and local state transitions on the particle movement with minimum information loss, and inspire further model-based investigation. We demonstrate with simulations and experiments that the underlying mechanisms of various time-series and motion states of single nanoparticles on live cell membranes could all be revealed successfully. Since complexity studies at different levels of molecules, particles, cells, human beings, vehicles, and even stars could all be reduced to analyzing spatiotemporal trajectories of \"single particles\", this presuppositionless approach will help fundamental researches on many important systems.\n\nImpact StatementA preprocessing strategy for single particle trajectory analysis is established by providing an intuitive global pattern from \"historical experiences\" of the particle without predefining any mechanical models.

biophysics↗