Biology subjects

Pan, Y.

Publications and source records attributed to Pan, Y..

At least 253 records · Page 14Linked to original sources

bioRxiv2019

Gut Microbiome Biomarkers in Adolescent Obesity：a Regional Study

PurposeThis study aimed to characterize the gut microbiota in obese Shenzhen adolescents, and evaluate the influence of gender on BMI-related differences in the gut microbiome.\n\nMethodsPhysical examinations, blood pressure measurement, serological assay, and body composition evaluation were conducted on two-hundred and five adolescents from Shenzhen. Fecal microbiome composition was profiled via 16S rRNA gene sequencing. A Random Forest (RF) classifier model was built to distinguish the BMI categories based on the gut bacterial composition.\n\nResultsFifty-six taxa consisting mainly of Firmicutes were identified that having significant associations with BMI; two OTUs belonging to Ruminococcaceae and one belonging to Lachnospiraceae had relatively strong positive correlations with body fate rate, waistline, and most of serum biochemical parameters. Based on the 56 BMI-associated OTUs, the RF model showed a robust classification accuracy (AUC 0.96) for predicting the obese phenotype. Gender-specific differences in the gut microbiome composition was obtained, and a lower relative abundance of Odoribacter was particularly found in obese boys. Functional analysis revealed a deficiency in bacterial gene contents related to PPAR signaling pathway in obese subjects for both genders; significantly lower levels of adipocytokine signaling pathway and ethylbenzene degradation were particularly detected in obese girls.\n\nConclusionsThis study revealed unique features of gut microbiome in terms of microbial composition and metabolic functions in obese Shenzhen adolescents. The effect of geographical location, age and gender on the gut microbiome should be carefully considered in case-control studies.

microbiology↗

bioRxiv2019

Deficiency in the endocytic adaptor protein PHETA1/2 impairs renal and craniofacial development

A critical barrier in the treatment of endosomal and lysosomal diseases is the lack of understanding of the in vivo functions of the putative causative genes. We addressed this by investigating a key pair of endocytic adaptor proteins, PH domain containing endocytic trafficking adaptor 1 and 2 (PHETA1/2, also known as FAM109A/B, Ses1/2, IPIP27A/B), which interact with the protein product of OCRL, the causative gene for Lowe syndrome. Here we conducted the first study of PHETA1/2 in vivo, utilizing the zebrafish system. We found that impairment of both zebrafish orthologs, pheta1 and pheta2, disrupted endocytosis and ciliogenesis. In addition, pheta1/2 mutant animals exhibited reduced jaw size and delayed chondrocyte maturation, indicating a role in craniofacial development. Deficiency of pheta1/2 resulted in dysregulation of cathepsin K, which led to an increased abundance of type II collagen in craniofacial cartilages. The abnormal renal and craniofacial phenotypes in the pheta1/2 mutant animals were consistent with the clinical presentations of a patient with a de novo arginine (R) to cysteine (C) variant (R6C) of PHETA1. Expressing the patient-specific variant in zebrafish exacerbated craniofacial deficits, suggesting that the R6C allele acts in a dominant-negative manner. Together, these results provide insights into the in vivo roles of PHETA1/2 and suggest that the R6C variant is contributory to the pathogenesis of disease in the patient.

developmental biology↗

bioRxiv2019

A cortico-collicular pathway for motor planning in a memory-dependent perceptual decision task

Survival in a dynamic environment requires animals to plan future actions based on past sensory evidence. However, the neural circuit mechanism underlying this crucial brain function, referred to as motor planning, remains unclear. Here, we employ projection-specific imaging and perturbation methods to investigate the direct pathway linking two key nodes in the motor planning network, the secondary motor cortex (M2) and the midbrain superior colliculus (SC), in mice performing a memory-dependent perceptual decision task. We find dynamic coding of choice information in SC-projecting M2 neurons during motor planning and execution, and disruption of this information by inhibiting M2 terminals in SC selectively impaired decision maintenance. Furthermore, cell-type-specific optogenetic circuit mapping shows that M2 terminals modulate both excitatory and inhibitory SC neurons with balanced synaptic strength. Together, our results reveal the dynamic recruitment of the premotor-collicular pathway as a circuit mechanism for motor planning.

neuroscience↗

bioRxiv2019

Brain-to-brain coupling between instructors and learners discriminates between instructional approaches and predicts learning

The neural mechanisms that support naturalistic learning via effective pedagogical approaches remain elusive. Here we use functional near-infrared spectroscopy to measure brain activity from instructor-learner dyads simultaneously during dynamic conceptual learning. We report that brain-to-brain coupling is correlated with learning outcomes, and, crucially, appears to be driven by specific scaffolding behaviors on the part of the instructors (e.g., asking guiding questions or providing hints). Brain-to-brain coupling enhancement is absent when instructors use an explanation approach (e.g., providing definitions or clarifications). Finally, we find that machine-learning techniques are more successful when decoding instructional approaches (scaffolding vs. explanation) from brain-to-brain coupling data than when using a single-brain method. These findings suggest that brain-to-brain coupling as a pedagogically relevant measure tracks the naturalistic instructional process during instructor-learner interaction throughout constructive engagement, but not information clarification.

neuroscience↗

bioRxiv2019

Cell growth kinetics and accumulation of secondary metabolite of Bletilla striata Rchb.f. using cell suspension culture

Bletilla striata (Orchidaceae) is a well-recognized endangered medicinal plant due to inadequate natural reproduction with high market worth. To evaluate the cell growth kinetics and accumulation of secondary metabolites (SMs), the cell suspension culture is proved to be a valuable approach for acquiring the high yield of medicinal parts. An effective cell suspension culture for obtaining B. striata cell growth and its SMs was in vitro induction of callus from B. striata seeds. The cell growth kinetics and accumulation of SMs were analyzed using the mathematical model. Results cell growth kinetic model revealed that the growth curve of B. striata suspension cells was curved as sigmoid shape, indicating the changes of the growth curve of suspension cells. Improved Murashige and Skoog cell growth medium was the utmost favorable medium for B. striata callus formation with the highest cell growth during the stationary phase of cultivation period, the cell growth acceleration was started after 7 days and thereafter gradually decrease at 24 day and then reached to highest at 36 day of cultivation period in both dry weight and fresh weight. The coelonin concentration was peak during exponential growth stage and decreased afterward at the stationary phase in the cell suspension culture. The maximum content of coelonin (about 0.3323 mg/g cell dry weight) was observed on the 18th day of the cultivation cycle while the dactylorhin A and militarine reached highest at 24 day, and p-hydroxybenzyl alcohol at 39 day. This investigation also laid a foundation for multi-mathematical model to better describe the accumulation variation of SMs. The production of SMs had shown great specificity during cells growth and development. This research provided a well-organized way to more accumulation and production of SMs, on scale-up biosynthesis in B. striata cell suspension culture.

plant biology↗

bioRxiv2019

Analysis of Heterogeneous Genomic Samples Using Image Normalization and Machine Learning

BackgroundAnalysis of heterogeneous populations such as viral quasispecies is one of the most challenging bioinformatics problems. Although machine learning models are becoming to be widely employed for the analysis of sequencing data associated with such populations, their straightforward application is impeded by multiple challenges associated with technological limitations and biases, difficulty of selection of relevant features and need to compare genomic datastes of different sizes and structures.\n\nMethodsWe propose a novel preprocessing approach to transform irregular genomic data into normalized image data. Such representation allows to restate the problems of classification and comparison of heterogeneous populations as image classification problems which can be solved using variety of available machine learning tools. We then apply the proposed approach to two important molecular epidemiology problems: inference of viral infection stage and detection of viral transmission clusters and outbreaks using next-generation sequencing data.\n\nResultsThe infection staging method has been applied to HCV HVR1 samples collected from 108 recently and 257 chronically infected individuals. The SVM-based image classification approach achieved more than 95% accuracy for both recently and chronically HCV-infected individuals. Clustering has been performed on the data collected from 33 epidemiologically curated outbreaks, yielding more than 97% accuracy.\n\nAvailabilityThe developed software is freely available at https://bitbucket.org/adv_bio_coll/chronic_vs_clinic

bioinformatics↗

bioRxiv2019

Insight into dynamics of APOBEC3G protein in complexes with DNA assessed by high speed AFM

APOBEC3G (A3G) is a single-stranded DNA (ssDNA) binding protein that restricts the HIV virus by deamination of dC to dU during reverse transcription of the viral genome. A3G has two zing-binding domains: the N-terminal domain (NTD), which efficiently binds ssDNA, and the C-terminal catalytic domain (CTD), which supports deaminase activity of A3G. Until now, structural information on A3G has lacked, preventing elucidation of the molecular mechanisms underlying its interaction with ssDNA and deaminase activity. We have recently built computational model for the full-length A3G monomer and validated its structure by data obtained from time-lapse High-Speed Atomic Force Microscopy (HS AFM). Here time-lapse HS AFM was applied to directly visualize the structure and dynamics of A3G in complexes with ssDNA. Our results demonstrate a highly dynamic structure of A3G, where two domains of the protein fluctuate between compact globular and extended dumbbell structures. Quantitative analysis of our data revealed a substantial increase in the number of A3G dumbbell structures in the presence of the DNA substrate, suggesting the interaction of A3G with the ssDNA substrate stabilizes this dumbbell structure. Based on these data, we developed a model explaining the interaction of globular and dumbbell structures of A3G with ssDNA and suggested a possible role of the dumbbell structure in A3G function.

biophysics↗

bioRxiv2019

Deep learning in bioinformatics: introduction, application, and perspective in big data era

Deep learning, which is especially formidable in handling big data, has achieved great success in various fields, including bioinformatics. With the advances of the big data era in biology, it is foreseeable that deep learning will become increasingly important in the field and will be incorporated in vast majorities of analysis pipelines. In this review, we provide both the exoteric introduction of deep learning, and concrete examples and implementations of its representative applications in bioinformatics. We start from the recent achievements of deep learning in the bioinformatics field, pointing out the problems which are suitable to use deep learning. After that, we introduce deep learning in an easy-to-understand fashion, from shallow neural networks to legendary convolutional neural networks, legendary recurrent neural networks, graph neural networks, generative adversarial networks, variational autoencoder, and the most recent state-of-the-art architectures. After that, we provide eight examples, covering five bioinformatics research directions and all the four kinds of data type, with the implementation written in Tensorflow and Keras. Finally, we discuss the common issues, such as overfitting and interpretability, that users will encounter when adopting deep learning methods and provide corresponding suggestions. The implementations are freely available at https://github.com/lykaust15/Deep_learning_examples.

bioinformatics↗

bioRxiv2019

Pair-wise Comparison Analysis for Multiple Pool-sep: an efficient method identified anthocyanin biosynthesis genes in rice pericarp

The complex traits are derived from multiple genes and exhibit a large variety of phenotypes. High-throughput sequencing technologies have become the new strategies for mapping the important traits of crops. However, these methods have their own disadvantages and limitations. Here we introduced Pair-wise Comparison Analysis for Multiple Pool-seq (PCAMP) for mapping the candidate genomic regions involved in anthocyanin biosynthesis in rice pericarp. In this protocol, the second filial generation (F2) populations obtained by crossing two parents with different target traits were divided into n (n>=3) subpopulations according to their phenotypes. Thirty phenotypically identical individuals were selected from each subpopulation and DNA samples were extracted to form a pool for sequencing. Finally, we compared the SNP-index between every two Pool-seqs to map the candidate genomic regions. We applied PCAMP to analyse F2 populations and successfully identified five known genes and five new candidate genomic regions for anthocyanin biosynthesis in rice pericarp. These results demonstrate that PCAMP is an efficient new method for dissecting the complex traits of crops.

molecular biology↗

bioRxiv2019

12h-clock control of central dogma information flow by XBP1s

Our group recently discovered a cell-autonomous mammalian 12h-clock regulating physiological unfolded protein response. Xbp1s ablation impairs 12h-transcript oscillations in vitro, and we now show liver-specific deletion of XBP1s globally impaired murine 12h-transcriptome, but not the circadian rhythms in vivo. XBP1s-dependent 12h-transcriptome is enriched for transcription, mRNA processing, ribosome biogenesis, translation, and protein ER-Golgi processing/sorting in a temporal order consistent with the progressive molecular processing sequence described by the central dogma information flow (CEDIF). The 12h-rhythms of CEDIF are cell-autonomous and evolutionarily conserved in circatidal marine animals. Mechanistically, we found the motif stringency of promoter XBP1s binding sites, but not necessarily XBP1s expression, dictates its ability to drive 12h-rhythms of transcription and further identified GABP as putative novel transcriptional regulator of 12h-clock. We hypothesize the 12h-rhythms of CEDIF allows rush hours gene expression and processing, with the particular genes processed at each rush hour regulated by circadian and/or tissue specific pathways.

systems biology↗

bioRxiv2019

Cold Shock Fail to Restrain Pre-formed Vibrio parahaemolyticus Biofilm

The source of persistent infections can be biofilms that occur naturally on food surfaces and medical biomaterials. Biofilm formation on these materials are likely to be affected by environmental temperature fluctuations and information on noticeable temperature shifts on the fate of pre-formed biofilm is sparse. Changes to pre-formed Vibrio parahaemolyticus biofilm under cold shock (4 {degrees}C and 10 {degrees}C) was explored in this study. We show that V. parahaemolyticus biofilm biomass increased significantly during this cold shock period and there was a gradual increase of polysaccharides and proteins content in the extracellular polymeric matrix (EPS). In addition, we demonstrate that the expression of flagella and virulence-related genes were differentially regulated. The architecture of the biofilm, quantified using mean thickness (MT), average diffusion distance (ADD), porosity (P), biofilm roughness (BR) and homogeneity (H) also changed during the cold shock and these parameters were correlated (P < 0.01). However, the correlation between biofilm architecture and biofilm-related genes expression was relatively weak (P < 0.05). Cold shock at 4 {degrees}C and 10 {degrees}C is not sufficient to reduce V. parahaemolyticus biofilm formation and strategies to reduce risk of foodborne infections should take this information into account.

microbiology↗

bioRxiv2019

Differential expression feature extraction (DEFE) and its application in RNA-seq data analysis

In differential gene expression data analysis, one objective is to identify groups of co-expressed genes from a large dataset to detect the association between such a group of genes and a phenotypic trait. This is often done through a clustering approach, such as k-means or bipartition hierarchical clustering, based on particular similarity measures in the grouping process. In such a dataset, the gene differential expression itself is an innate attribute that can be used in the feature extraction process. For example, in a dataset consisting of multiple treatments versus their controls, the expression of a gene in each treatment would have three possible behaviors, up-, down- regulated, or unchanged. We propose here a differential expression feature extraction (DEFE) method by using a string consisting of three numerical values at each character to denote such behavior, i.e. 1=up, 2=down, and 0=unchanged, which results in up to 3B differential expression patterns across all B comparisons. This approach has been successfully applied in many datasets, of which we present in this study two sets of RNA-sequencing (RNA-seq) data on wheat challenged with stress related phytohormones or Fusarium graminearum, the causal agent of fusarium head blight (FHB), a devastating wheat disease to illustrate the algorithm. Combinations of multiple schemes of DEFE patterns revealed groups of genes putatively associated with resistance or susceptibility to FHB. DEFE enabled discovery of genes closely associated with defense related signaling molecules such as JAZ10, shikimate and chorismate biosynthesis pathway and groups of wheat genes with differential effects between more or less virulent strains of Fusarium graminearum.

genomics↗

bioRxiv2018

Molecular characterization of the viral structural gene of the first dengue virus type 1 outbreak in Xishuangbanna, a border area of China, Burma and Laos

In the context of recent arbovirus epidemics, dengue fever is becoming a greater concern around the world. In August 2017, Xishuangbanna, which is a border city of China, Burma and Laos, had its first major dengue outbreak. A total of 156 serum samples from febrile patients were collected; 97 DENV positive serum samples were screened out, and viral RNAs were successfully and directly extracted, including 77 cases from China and 20 cases from Myanmar. Phylogenetic analysis revealed that all of the strains were classified as DENV-1. There are eight epidemic dengue strains from Myanmar and 74 from Jinghong, Xishuangbanna, that were classified as cluster 1, which are the most similar to the strain of China Guangzhou 2011. There are three epidemic strains from Xishuangbanna Mengla that were classified as cluster 2, which have the closest relationship to the strain of China Hubei 2014. However, there are 12 epidemic strains from Myanmar that were classified as cluster 3, which have the closest relationship to the strain of Laos from 2008, which shows that there is a recycling epidemic trend of DENV in China. There were 236 mutations in the base, which caused 31 nonsynonymous mutations in the DENV structural protein C/prM/E genes when the strain of Xishuangbanna and Myanmar were compared with the DENV-1SS. There is no clear homologous recombination signal among these stains. Homology modeling possibly predicted a three-dimensional structure of the structural protein of these strains and revealed that they had the same three-dimensional structure and all had five predicted protein binding sites, but there are differences in binding site 434 (DENV-1SS: Thr434, DV-Jinghong: Ser434, DV-Myanmar: Ser434, DV-Mengla: Ser434). The results of the molecular clock phylogenetic and demographic reconstruction analysis show that DENV-1 became highly diversified in 1972 followed by a slightly decreased period until 2017. In conclusion, our study lays the foundation for studying the global evolution and prevalence of DENV.\n\nAuthor SummaryDengue fever (DF) is a mosquito-borne illness caused by a flavivirus. Human infections with Dengue virus (DENV) could cause fever, cutaneous rash and malaise. Xishuangbanna, which is located in the southwestern Yunnan Province and is a border city with China, Burma and Laos, was reported to have outbreak of DENV in 2013 and 2015 with different types. However, there was a large outburst of dengue in May 2017. To understand the genetic characterization, potential source and evolution of the virus, 156 serum samples were analyzed. We focused on: (i) Phylogenetic analysis of the structural protein genes sequences; (ii) Mutation, recombination analysis and predicted protein binding sites of the structural protein genes; (iii) Molecular clock and demographic reconstruction of global dengue virus serotype 1(DENV-1). Our results indicated that this is the first outbreak of DENV-1 in Xishuangbanna, dengue epidemic strains on the Burma border of China show diversification, we found a virulence site changed from I to T(amino acid position: 440), which may lead to weakened virulence of the epidemic strains. We found that the evolution of DENV-1 is dominated by regional evolution. Whats more, DENV-1 became highly diversified in 1972 followed by a slightly decreased period until 2017.

epidemiology↗

bioRxiv2018

A molecular model of the surface-assisted protein aggregation process

The importance of cell surfaces in the self-assembly of proteins is widely accepted. One biologically significant event is the assembly of amyloidogenic proteins into aggregates, which leads to neurodegenerative disorders like Alzheimers and Parkinsons. The interaction of amyloidogenic proteins with cellular membranes appears to dramatically facilitate the aggregation process. Recent findings indicate that, in the presence of surfaces, aggregation occurs at physiologically low concentrations, suggesting interaction with surfaces plays a critical role in the disease-prone aggregation process. However, the molecular mechanisms behind on-surface aggregation remain unclear. Here we provide a theoretical model that offers a molecular explanation. According to this model, monomers transiently immobilized to surfaces increase the local monomer protein concentration and thus work as nuclei to dramatically accelerate the entire aggregation process. This theory was verified by experimental studies, using mica surfaces, to examine the aggregation kinetics of amyloidogenic-synuclein protein (-Syn) and non-amyloidogenic cytosine deaminase APOBEC3G (A3G).

biophysics↗

bioRxiv2018

Coverage-based detection of copy number alterations in mixed samples using DNA sequencing data: a theoretical framework for evaluating statistical power

1DNA sequencing can discover not only single-base variants but also copy-number alterations (CNAs). In shotgun sequencing, regions of CNAs show step-wise changes in read depth when compared to adjacent \"normal\" regions, allowing their detection by parametric statistical tests that compare the mean coverage in suspected regions against that of a baseline distribution. Traditionally, the power of such a test depends on (1) the integer number of copy number change, (2) the overall sequencing depth, (3) the length of the CNA region, (4) the read length and (5) the variation of coverage along the genome, which depends on many experimental factors, including whether the chosen platform is whole-genome, whole-exome, or targeted-panel sequencing. In cases involving inadvertent sample mixing or genuine somatic mosaicism, power also depends on the mixing ratio. However, the analysis of statistical power that considers the interplay of all these factors has not been systematically developed. Here we present a general analytical framework and a series of simulations that explore situations from the simplest to the increasingly multifactorial. Specifically, we expand the expression of power to include not just the known factors but also one or both of two complications: (1) the dispersion of read depth around the mean beyond the independent sampling-by-sequencing assumption, and (2) the reduced fraction of the CNA-bearing sample (\"purity\") as seen in studies of intratumor heterogeneity or in clinical monitoring of minimal residual disease. We describe the analytical formula and their simplifications in special cases, and share the extendable scripts for others to perform customized power analysis using study-specific parameters. As study designs vary and technologies continue to evolve, the input data and the noise characteristics will change depending on the practical situation. We present two use cases commonly encountered in cancer research: ultra-shallow whole-genome sequencing for detecting large, chromosome-scale events, and targeted ultra-deep sequencing for surveillance of known CNAs in rare tumor clones in the task of sensitive detection of cancer relapse or metastasis. We also present an online calculator at https://shiny.med.umich.edu/apps/hanyou/CNV_Detection_Power_Calculator/.

bioinformatics↗

bioRxiv2018

Cold Shock Fail to Restrain Pre-formed Bacterial Biofilm

Environmental temperature fluctuation has great impact on the formation of bacterial biofilm, while little information is available for assessing the influence of sharp temperature shifts on the fate of pre-formed biofilm. In this study, experimental evidence is firstly explored on the response of Vibrio parahaemolyticus pre-formed biofilm under cold shock (4 {degrees}C and 10 {degrees}C). Surprisingly, biofilm biomass of V. parahaemolyticus significantly increased during the period of cold shock as revealed by crystal violet staining. Polysaccharides and proteins contents in extracellular polymeric substances were gradually enhanced after cold shocks and exhibited high consistency. RT-qPCR demonstrated the expression of flagella and virulence-related genes were up-regulated. Most of QS and T3SS genes were slightly up-regulated, and three T3SS genes (vcrD1, vcrD2{beta} and vopD1) were down-regulated. Furthermore, the biofilm structure of V parahaemolyticus have been analyzed by Confocal laser scanning microscopy (CLSM), which sharply changed under cold shocks. The correlation analysis further displayed the significant correlation (P < 0.01) among biofilm structure parameters, and weak correlation (P < 0.05) between biofilm related genes and biofilm structure parameters. In conclusion, our results novel discovered that V. parahaemolyticus biofilm related genes were actively expressed and biofilm biomass was continuously increased, biofilm structure was tremendously changed after cold shock. This study underscored the risk that biofilm cells had the ability to adapt to low temperature shift.\n\nIMPORTANCEBiofilms are widespread in natural environments, especially on the surface of food and medical biomaterials, which threaten human safety from persistent infections. Previous studies simply focused on biofilm formation of microorganisms under steady state, however, the actual environment frequently fluctuated. V. parahaemolyticus is a widely distributed foodborne pathogen, temperature play a great role in its survival. Researchers generally assume that cold environment can restrain biofilm formation and bacterial activity. This study explored the effects of V. parahaemolyticus biofilm upon a shift from 37 {degrees}C to 4 {degrees}C or 10 {degrees}C from two aspects. On the one hand, the changes of biofilm biomass and EPS contents, the expression of biofilm related genes directly described that pre-formed bacterial biofilm could not be controlled efficiently in cold environment. On the other hand, the CLSM images revealed biofilm morphological structure change, the correlation analysis showed inner relationship among biofilm structure parameters and biofilm related genes. These results suggested that cold shock fail to restrain pre-formed bacterial biofilm, therefore be a potential risk in nature environment.

microbiology↗

bioRxiv2018

Histophilus somni Survives in Bovine Macrophages by Interfering with Phagosome-Lysosome Fusion, but Requires IbpA for Optimal Serum Resistance

Histophilus somni survives intracellularly in professional phagocytic cells, but the mechanism of intracellular survival is not understood. The Fic motif within the DR1/DR2 IbpA fibrillar network protein of H. somni is cytotoxic to epithelial and phagocytic cells, which may interfere with the bactericidal activity of these cells. To determine the contribution of IbpA and Fic on resistance to host defenses, strains and mutants that lack all of or a small region of ibpA or DR1/DR2 were tested for survival in bovine monocytic cells and for serum susceptibility. A mutant lacking IbpA, but not DR1/DR2, was more susceptible to killing by antiserum than the parent. H. somni strains expressing IbpA replicated in bovine monocytes for at least 72 hours, and were toxic for these cells. Virulent strain 2336 with transposon insertions or deletions within IbpA remained toxic for bovine monocytes. However, strain 2336 mutants lacking all of ibpA or both DR1/DR2 were not toxic to the monocytes, but survived within the monocytes for at least 72 hours. Examination of intracellular trafficking of H. somni with monoclonal antibodies to early and late phagosomal markers indicated that early phagosomal marker EEA-1 colocalized with both disease isolate strain 2336 and serum-sensitve mucosal isolate strain 129Pt, but only strain 2336 did not co-localize with late lysosomal marker LAMP-2 and prevented acidification of phagosomes. These results indicate that virulent isolates of H. somni are capable of surviving within phagocytic cells through interference of phagosome-lysosome maturation. Therefore, H. somni may be considered a permissive intracellular pathogen.

microbiology↗

bioRxiv2018

EZH2 co-opts gain-of-function p53 mutants to promote cancer growth and metastasis

With the unfolding of more and more cancer-driven gain-of-function (GOF) mutants of p53, it is important to define a common mechanism to systematically target different mutants rather than develop strategies tailored to inhibit each mutant individually. Here, using RNA immunoprecipitation sequencing (RIP-seq) we identified EZH2 as a p53 mRNA-binding protein. EZH2 bound to the internal ribosome entry site (IRES) in the 5 untranslated region (5UTR) of p53 mRNA and enhanced p53 protein translation in a methyltransferase-independent manner. EZH2 augmented p53 GOF mutant-mediated cancer growth and metastasis by increasing p53 GOF mutant protein level. EZH2 overexpression associated with the worse outcome only in patients with p53-mutated cancer. Depletion of EZH2 by antisense oligonucleotides inhibited p53 GOF mutant-mediated cancer growth. Our findings reveal a non-methyltransferase function of EZH2 that controls protein translation of p53 GOF mutants, inhibition of which causes synthetic lethality in cancer cells expressing p53 GOF mutants.

cancer biology↗