Biology subjects

Tang, S.

Publications and source records attributed to Tang, S..

15 recordsLinked to original sources

bioRxiv2018

Virus infection might cause cells producing black swimming dots

Black swimming dots (BSDs) are nanoscale dot-like contaminants in the dishes of cultured cells. Until now, the identity of BSDs has not yet been determined. In our recent study, we proposed that BSDs per se are nonliving inorganic nanoparticles yet should derive from the cells infected with an unidentified airborne pathogen. We showed the pathogen possessed the characteristics including airborne transmitted, cell-dependent, insensitive to antibiotics, filterable through 0.1 m membrane. These properties prompt us to speculate that the pathogen of BSDs might be one kind of unidentified virus-like organism. However, the imperfection is that we have not isolated this putative pathogen from BSD+ samples [1]. Here, we report a further investigation of finding the virus-like pathogen in the serum and tissue extracts from BSD+ mice. Most importantly, this virus-like pathogen can be reisolated from the BSD+ extracts-inoculated, diseased BSD- cells.\n\nTo de ...

cell biology↗

bioRxiv2018

MetaPGN: a pipeline for construction and graphical visualization of annotated pangenome networks

Pangenome analyses facilitate the interpretation of genetic diversity and evolutionary history of a taxon. However, there is an urgent and unmet need to develop new tools for advanced pangenome construction and visualization, especially for metagenomic data. Here we present an integrated pipeline, named MetaPGN, for construction and graphical visualization of pangenome network from either microbial genomes or metagenomes. Given either isolated genomes or metagenomic assemblies coupled with a reference genome of the targeted taxon, MetaPGN generates a pangenome in a topological network, consisting of genes (nodes) and gene-gene genomic adjacencies (edges) of which biological information can be easily updated and retrieved. MetaPGN also includes a self-developed Cytoscape plugin for layout of and interaction with the resulting pangenome network, providing an intuitive and interactive interface for full exploration of genetic diversity. We demonstrate the utility of MetaPGN by constructing Escherichia coli (E. coli) pangenome networks from five E. coli pathogenic strains and 760 human gut microbiomes respectively, revealing extensive genetic diversity of E. coli within both isolates and gut microbial populations. With the ability to extract and visualize gene contents and gene-gene physical adjacencies of a specific taxon from large-scale metagenomic data, MetaPGN provides advantages in expanding pangenome analysis to uncultured microbial taxa. MetaPGN is available at https://github.com/peng-ye/MetaPGN.

genomics↗

bioRxiv2018

The crossover function of MutSγ is activated via Cdc7-dependent stabilization of Msh4

The MutS{gamma} complex, Msh4-Msh5, binds DNA joint-molecule (JM) intermediates during homologous recombination to promote crossing over and accurate chromosome segregation at the first division of meiosis. MutS{gamma} facilitates the formation and biased resolution of crossover-specific JM intermediates called double Holliday junctions. Here we show that these activities are governed by regulated proteasomal degradation. MutS{gamma} is initially inactive for crossing over due to an N-terminal degron on Msh4 that renders it unstable. Activation of MutS{gamma} requires the Dbf4-dependent kinase, Cdc7 (DDK), which directly phosphorylates and thereby neutralizes the Msh4 degron. Phosphorylated Msh4 is chromatin bound and requires DNA strand exchange and chromosome synapsis, implying that DDK specifically targets MutS{gamma} that has already bound nascent JMs. Our study establishes regulated protein degradation as a fundamental mechanism underlying meiotic crossover control.

genetics↗

bioRxiv2018

Black swimming dots in cell culture: the identity, detection method and judging criteria

Black swimming dots (BSDs) -- the biological UFO in cell culture -- have perplexed biologists for decades. BSDs are extremely tiny dots found in dishes of cultured cells. It is still controversial on their origin and identity. BSDs are very hard to be removed and bring adverse impact to cell experiments (Supplementary Table 1). Here we wish to answer three urgent questions about BSDs. First, is the identity of BSDs nonliving matter or living organism? Second, is there any reliable method to tell whether the donor cattle for FBS production or the animals for primary cells isolation carry BSDs? Third, what are the judging criteria for BSDs when \"tiny black dots\" were observed? In 2015, we happened to observe BSDs in the perivitelline space of mouse oocytes and embryos; and the cells derived from these mice exhibited typical properties of BSDs infected cells (described in Supplementary Information). With these BSDs infected (BSD+) mice, we demonstrate that BSDs per se are ...

cell biology↗

bioRxiv2018

Eight new genomes of organohalide-respiring Dehalococcoides mccartyi reveal evolutionary trends in reductive dehalogenase enzymes

BackgroundBioaugmentation is now a well-established approach for attenuating toxic groundwater and soil contaminants, particularly for chlorinated ethenes and ethanes. The KB-1 and WBC-2 consortia are cultures used for this purpose. These consortia contain organisms belonging to the Dehalococcoidia, including strains of Dehalococcoides mccartyi in KB-1 and of both D. mccartyi and Dehalogenimonas in WBC-2. These tiny anaerobic bacteria couple respiratory reductive dechlorination to growth and harbour multiple reductive dehalogenase genes (rdhA) in their genomes, the majority of which have yet to be characterized.\n\nResultsUsing a combination of Illumina mate-pair and paired-end sequencing we closed the genomes of eight new strains of Dehalococcoides mccartyi found in three related KB-1 sub-cultures that were enriched on trichloroethene (TCE), 1,2-dichloroethane (1,2-DCA) and vinyl chloride (VC), bringing the total number of genomes available in NCBI to 24. A pangenome analysis was conducted on 24 Dehalococcoides genomes and five Dehalogenimonas genomes (2 in draft) currently available in NCBI. This Dehalococcoidia pangenome generated 2875 protein families comprising of 623 core, 2203 accessory, and 49 unique protein families. In Dehalococcoides mccartyi the complement of reductive dehalogenase genes varies by strain, but what was most surprising was how the majority of rdhA sequences actually exhibit a remarkable degree of synteny across all D. mccartyi genomes. Several homologous sequences are also shared with Dehalogenimonas genomes. Nucleotide and predicted protein sequences for all reductive dehalogenases were aligned to begin to decode the evolutionary history of reductive dehalogenases in the Dehalococcoidia.\n\nConclusionsThe conserved synteny of the rdhA genes observed across Dehalococcoides genomes indicates that the major differences between strain rdhA gene complement has resulted from gene loss rather than recombination. These rdhA have a long evolutionary history and trace their origin in the Dehalococcoidia prior to the speciation of Dehalococcoides and Dehalogenimonas. The only rdhA genes suspected to have been acquired by lateral gene transfer are protein-coding rdhA that have been identified to catalyze dehalogenation of industrial pollutants. Sequence analysis suggests that evolutionary pressures resulting in new rdhA genes involve adaptation of existing dehalogenases to new substrates, mobilization of rdhA between genomes or within a genome, and to a lesser degree manipulation of regulatory regions to alter expression.

bioinformatics↗

bioRxiv2018

Proteomics reveals ablation of placental growth factor inhibits the insulin resistance pathways in diabetic mouse retina

The underlying molecular mechanisms that placental growth factor (PlGF) mediates the early complications at non-proliferative diabetic retinopathy (DR) remain largely elusive. The objective of this study is to characterize expression profile due to PlGF ablation in the retina of diabetic mice. The quantitative label-free proteomics was carried out on retinal tissues collected from mouse strains (Akita; PlGF-/- and Akita.PlGF-/-). We have identified 3176 total proteins, and 107 were significantly different between the experimental groups, followed by gene ontology, functional pathways, and protein-protein network interaction analysis. Gnb1, Gnb2, Gnb4, Gnai2, Gnao1, Snap25, Stxbp1, Vamp2 and Gngt1 proteins are involved in insulin resistance pathways, which are down-regulated in PlGF ablation in Akita diabetics (Akita.PlGF-/- vs. Akita), up-regulation in Akita vs. C57, PlGF-/- vs. C57. Prdx6, Prdx5 (up-regulation) are known of antioxidant activity; Map2 is involved in neural protection pathways which are up-regulated in Akita.PlGF-/- vs. Akita. Our results suggest that inhibition of insulin resistance pathway and the enhancement of antioxidant defence and neural function may represent the potential mechanisms of anti-PlGF compounds in the treatment of DR.

molecular biology↗

bioRxiv2018

Convolutional neural network models of V1 responses to complex patterns

In this study, we evaluated the convolutional neural network (CNN) method for modeling V1 neurons of awake macaque monkeys in response to a large set of complex pattern stimuli. CNN models outperformed all the other baseline models, such as Gabor-based standard models for V1 cells and various variants of generalized linear models. We then systematically dissected different components of the CNN and found two key factors that made CNNs outperform other models: thresholding nonlinearity and convolution. In addition, we fitted our data using a pre-trained deep CNN via transfer learning. The deep CNNs higher layers, which encode more complex patterns, outperformed lower ones, and this result was consistent with our earlier work on the complexity of V1 neural code. Our study systematically evaluates the relative merits of different CNN components in the context of V1 neuron modeling.

neuroscience↗

bioRxiv2018

N-hydroxy-pipecolic acid is a mobile signal that induces systemic disease resistance in Arabidopsis

Systemic acquired resistance (SAR) is a global response in plants induced at the site of infection that leads to long-lasting and broad-spectrum disease resistance at distal, uninfected tissues. Despite the importance of this priming mechanism, the identity of the mobile defense signal that moves systemically throughout plants to initiate SAR has remained elusive. In this paper, we describe a new metabolite, N-hydroxy-pipecolic acid (N-OH-Pip), and provide evidence that this molecule is a mobile signal that plays a central role in initiating SAR signal transduction in Arabidopsis thaliana. We demonstrate that FLAVIN-DEPENDENT MONOOXYGENASE 1 (FMO1), a key regulator of SAR-associated defense priming, can synthesize N-OH-Pip from pipecolic acid in planta, and exogenously applied N-OH-PIP moves systemically in Arabidopsis and can rescue the SAR-deficiency of fmo1 mutants. We also demonstrate that N-OH-Pip treatment causes systemic changes in the expression of pathogenesis-related genes and metabolic pathways throughout the plant, and enhances resistance to a bacterial pathogen. This work provides new insight into the chemical nature of a mobile signal for SAR and also suggests that the N-OH-Pip pathway is a promising target for metabolic engineering to enhance disease resistance.

plant biology↗

bioRxiv2018

Long-term all-optical interrogation of cortical neurons in awake-behaving non-human primates

Whereas optogenetic techniques have proven successful in their ability to manipulate neuronal populations in species ranging from insects to rodents--with high spatial and temporal fidelity--significant obstacles remain in their application to non-human primates (NHPs). Robust optogenetics-activated behavior and long-term noninvasive monitoring of target neurons, have been challenging in NHPs. Here we present a method for all-optical interrogation (AOI), integrating optical stimulation and simultaneous two-photon imaging of neuronal populations in the primary visual cortex (V1) of awake rhesus macaques. A red-shifted channel-rhodopsin transgene (C1V1) and genetically-encoded calcium indicators (GCaMP5 or GCaMP6s) were delivered by AAVs, and subsequently expressed in V1 neuronal populations for months with high stability. We achieved optogenetic stimulation using both single-photon (1P) activation of neuronal populations and two-photon (2P) activation of single-cells, while simultaneously recording 2P calcium imaging in awake monkeys. Optogenetic manipulations of V1 neuronal populations produced reliable artificial visual percepts. Together, our advances show the feasibility of precise and stable all-optical interrogation of cortical neurons in awake NHPs, which may facilitate broad applications in high-level cognition and pre-clinical testing studies.

neuroscience↗

bioRxiv2018

A catalog of microbial genes from the bovine rumen reveals the determinants of herbivory

BackgroundThe rumen microbiota provides essential services to its host and, through its role in ruminant production, contributes to human nutrition and food security. A thorough knowledge of the genetic potential of rumen microbes will provide opportunities for improving the sustainability of ruminant production systems. The availability of gene reference catalogs from gut microbiomes has advanced the understanding of the role of the microbiota in health and disease in humans and other mammals. In this work, we established a catalog of reference prokaryote genes from the bovine rumen.\n\nResultsUsing deep metagenome sequencing we identified 13,825,880 non-redundant prokaryote genes from the bovine rumen. Compared to human, pig and mouse gut metagenome catalogs, the rumen is larger and richer in functions and microbial species associated with the degradation of plant cell wall material and production of methane. Genes encoding enzymes catalyzing the breakdown of plant polysaccharides showed a particularly high richness that is otherwise impossible to infer from available genomes or shallow metagenomics sequencing. The catalog expands by several folds the dataset of carbohydrate-degrading enzymes described in the rumen. Using an independent dataset from a group of 77 cattle fed 4 common dietary regimes, we found that only <0.1% of genes were shared by all animals, which contrast with a large overlap for functions, i.e. 63% for KEGG functions. Different diets induced differences in the relative abundance rather than the presence or absence of genes explaining the great adaptability of cattle to rapidly adjust to dietary changes.\n\nConclusionsThese data bring new insights into functions, carbohydrate-degrading enzymes and microbes of the rumen that is complementing the available information on microbial genomes. The catalog is a significant biological resource enabling deeper understanding of phenotypes and biological processes and will be expanded as new data is made available.

microbiology↗

bioRxiv2018

Large-scale two-photon imaging revealed super-sparse population codes in V1 superficial layer of awake monkeys

Efficient coding has been proposed as a general principle for the sensory systems. The efficient coding hypothesis predicts that neuronal population responses should be sparse, but limited by the measurement techniques, the precise estimates of the population sparseness of visual cortical neurons are still uncertain. Here, we employed large-scale two-photon calcium imaging to examine the neuronal population activities in V1 superficial layers of awake macaques in response to a large set of natural images. We found that only 0.5% of these neurons on average responded strongly to any given natural image with response strength above half of their individual peak responses, which is more than tenfold sparse over those reported by early studies. We further showed that these sparse population activities contain sufficient information for discriminating images with high accuracy. This study provided the first accurate measure of sparseness in V1 neuronal population responses, which support super-sparse neural codes in primates.

neuroscience↗

bioRxiv2017

Improved Prokaryotic Gene Prediction Yields Insights into Transcription and Translation Mechanisms on Whole Genome Scale

In a conventional view of the prokaryotic genome organization promoters precede operons and RBS sites with Shine-Dalgarno consensus precede genes. However, recent experimental research suggesting a more diverse view motivated us to develop an algorithm with improved gene-finding accuracy. We describe GeneMarkS-2, an ab initio algorithm that uses a model derived by self-training for finding species-specific (native) genes, along with an array of pre-computed heuristic models designed to identify harder-to-detect genes (likely horizontally transferred). Importantly, we designed GeneMarkS-2 to identify several types of distinct sequence patterns (signals) involved in gene expression control, among them the patterns characteristic for leaderless transcription as well as non-canonical RBS patterns. To assess the accuracy of GeneMarkS-2 we used genes validated by COG annotation, proteomics experiments, and N-terminal protein sequencing. We observed that GeneMarkS-2 performed better on average in all accuracy measures when compared with the current state-of-the-art gene prediction tools. Furthermore, the screening of [~]5,000 representative prokaryotic genomes made by GeneMarkS-2 predicted frequent leaderless transcription in both archaea and bacteria. We also observed that the RBS sites in some species with leadered transcription did not necessarily exhibit the Shine-Dalgarno consensus. The modeling of different types of sequence motifs regulating gene expression prompted a division of prokaryotic genomes into five categories with distinct sequence patterns around the gene starts.\n\n[Supplemental material is available for this article].

genomics↗

bioRxiv2017

neoantigenR: An annotation based pipeline for tumor neoantigen identification from sequencing data

Studies indicate that more than 90% of human genes are alternatively spliced, suggesting the complexity of the transcriptome assembly and analysis. The splicing process is often disrupted, resulting in both functional and non-functional end-products (Sveen et al. 2016) in many cancers. Harnessing the immune system to fight against malignant cancers carrying aberrantly mutated or spliced products is becoming a promising approach to cancer therapy. Advances in immune checkpoint blockade have elicited adaptive immune responses with promising clinical responses to treatments against human malignancies (Tumor Neoantigens in Personalized Cancer Immunotherapy 2017). Emerging data suggest that recognition of patient-specific mutation-associated cancer antigens (i.e. from alternative splicing isoforms) may allow scientists to dissect the immune response in the activity of clinical immunotherapies (Schumacher and Schreiber 2015). The advent of high-throughput sequencing technology has provided a comprehensive view of both splicing aberrations and somatic mutations across a range of human malignancies, allowing for a deeper understanding of the interplay of various disease mechanisms.\n\nMeanwhile, studies show that the number of transcript isoforms reported to date may be limited by the short-read sequencing due to the inherit limitation of transcriptome reconstruction algorithms, whereas long-read sequencing is able to significantly improve the detection of alternative splicing variants since there is no need to assemble full-length transcripts from short reads. The analysis of these high-throughput long-read sequencing data may permit a systematic view of tumor specific peptide epitopes (also known as neoantigens) that could serve as targets for immunotherapy (Tumor Neoantigens in Personalized Cancer Immunotherapy 2017).\n\nCurrently, there is no software pipeline available that can efficiently produce mutation-associated cancer antigens from raw high-throughput sequencing data on patient tumor DNA (The Problem with Neoantigen Prediction 2017). In addressing this issue, we introduce a R package that allows the discoveries of peptide epitope candidates, which are the tumor-specific peptide fragments containing potential functional neoantigens. These peptide epitopes consist of structure variants including insertion, deletions, alternative sequences, and peptides from nonsynonymous mutations. Analysis of these precursor candidates with widely used tools such as netMHC allows for the accurate in-silico prediction of neoantigens. The pipeline named neoantigeR is currently hosted in https://github.com/ICBI/neoantigeR.

bioinformatics↗

bioRxiv2017

Gene family information facilitates variant interpretation and identification of disease-associated genes

Differentiating risk-conferring from benign missense variants, and therefore optimal calculation of gene-variant burden, represent a major challenge in particular for rare and genetic heterogeneous disorders. While orthologous gene conservation is commonly employed in variant annotation, approximately 80% of known disease-associated genes are paralogs and belong to gene families. It has not been thoroughly investigated how gene family information can be utilized for disease gene discovery and variant interpretation. We developed a paralog conservation score to empirically evaluate whether paralog conserved or nonconserved sites of in-human paralogs are important for protein function. Using this score, we demonstrate that disease-associated missense variants are significantly enriched at paralog conserved sites across all disease groups and disease inheritance models tested. Next, we assessed whether gene family information could assist in discovering novel disease-associated genes. We subsequently developed a gene family de novo enrichment framework that identified 43 exome-wide enriched gene families including 98 de novo variant carrying genes in more than 10k neurodevelopmental disorder patients. 33 gene family enriched genes represent novel candidate genes which are brain expressed and variant constrained in neurodevelopmental disorders.

genetics↗

bioRxiv2017

The Spectrum Of De Novo Variants In Neurodevelopmental Disorders With Epilepsy

Epilepsy is a frequent feature of neurodevelopmental disorders (NDD) but little is known about genetic differences between NDD with and without epilepsy. We analyzed de novo variants (DNV) in 6753 parent-offspring trios ascertained for different NDD. In the subset of 1942 individuals with NDD with epilepsy, we identified 33 genes with a significant excess of DNV, of which SNAP25 and GABRB2 had previously only limited evidence for disease association. Joint analysis of all individuals with NDD also implicated CACNA1E as a novel disease gene. Comparing NDD with and without epilepsy, we found missense DNV, DNV in specific genes, age of recruitment and severity of intellectual disability to be associated with epilepsy. We further demonstrate to what extent our results impact current genetic testing as well as treatment, emphasizing the benefit of accurate genetic diagnosis in NDD with epilepsy.

genetics↗