Biology subjects

Tao, Y.

Publications and source records attributed to Tao, Y..

At least 127 records · Page 7Linked to original sources

bioRxiv2020

MosaicBase: A Knowledgebase of Postzygotic Mosaic Variants in Noncancer Diseases and Asymptomatic Human Individuals

Mosaic variants resulting from postzygotic mutations are prevalent in the human genome and play important roles in human diseases. However, except for cancer-related variant collections, there are no collections of mosaic variants in noncancer diseases and asymptomatic individuals. Here, we present MosaicBase (http://mosaicbase.cbi.pku.edu.cn/ or http://49.4.21.8:8000/), a comprehensive database that includes 6,698 mosaic variants related to 269 noncancer diseases and 27,991 mosaic variants identified in 422 asymptomatic individuals. The genomic and phenotypic information for each variant was manually extracted and curated from 383 publications. MosaicBase supports the query of variants with Online Mendelian Inheritance in Man (OMIM) entries, genomic coordinates, gene symbols, or Entrez IDs. We also provide an integrated genome browser for users to easily access mosaic variants and their related annotations within any genomic region. By analyzing the variants collected in MosaicBase, we found that mosaic variants that directly contribute to disease phenotype showed features distinct from those of variants in individuals with a mild or no phenotype in terms of their genomic distribution, mutation signatures, and fraction of mutant cells. MosaicBase will not only assist clinicians in genetic counseling and diagnosis but also provide a useful resource to understand the genomic baseline of postzygotic mutations in the general human population.

bioinformatics↗

bioRxiv2020

Isolation and characterization of SARS-CoV-2 from the first US COVID-19 patient

The etiologic agent of the outbreak of pneumonia in Wuhan China was identified as severe acute respiratory syndrome associated coronavirus 2 (SARS-CoV-2) in January, 2020. The first US patient was diagnosed by the State of Washington and the US Centers for Disease Control and Prevention on January 20, 2020. We isolated virus from nasopharyngeal and oropharyngeal specimens, and characterized the viral sequence, replication properties, and cell culture tropism. We found that the virus replicates to high titer in Vero-CCL81 cells and Vero E6 cells in the absence of trypsin. We also deposited the virus into two virus repositories, making it broadly available to the public health and research communities. We hope that open access to this important reagent will expedite development of medical countermeasures. Article SummaryScientists have isolated virus from the first US COVID-19 patient. The isolation and reagents described here will serve as the US reference strain used in research, drug discovery and vaccine testing.

microbiology↗

bioRxiv2020

Tumor heterogeneity assessed by sequencing and fluorescence in situ hybridization (FISH) data

Computational reconstruction of clonal evolution in cancers has become a crucial tool for understanding how tumors initiate and progress and how this process varies across patients. The field still struggles, however, with special challenges of applying phylogenetic methods to cancers, such as the prevalence and importance of copy number alteration (CNA) and structural variation (SV) events in tumor evolution, which are difficult to profile accurately by prevailing sequencing methods in such a way that subsequent reconstruction by phylogenetic inference algorithms is accurate. In the present work, we develop computational methods to combine sequencing with multiplex interphase fluorescence in situ hybridization (miFISH) to exploit the complementary advantages of each technology in inferring accurate models of clonal CNA evolution accounting for both focal changes and aneuploidy at whole-genome scales. We demonstrate on simulated data that incorporation of FISH data substantially improves accurate inference of focal CNA and ploidy changes in clonal evolution from deconvolving bulk sequence data. Analysis of real glioblastoma data for which FISH, bulk sequence, and single cell sequence are all available confirms the power of FISH to enhance accurate reconstruction of clonal copy number evolution in conjunction with bulk and optionally single-cell sequence data. Availabilitygithub.com/CMUSchwartzLab/FISH_deconvolution Contactrussells@andrew.cmu.edu

bioinformatics↗

bioRxiv2019

SSnet - Secondary Structure based End-to-End Learning model for Protein-Ligand Interaction Prediction

Computational prediction of Protein-Ligand Interaction (PLI) is an important step in the modern drug discovery pipeline as it mitigates the cost, time, and resources required to screen novel therapeutics. Deep Neural Networks (DNN) have recently shown excellent performance in PLI prediction. However, the performance is highly dependent on protein and ligand features utilized for the DNN model. Moreover, in current models, the deciphering of how protein features determine the underlying principles that govern PLI is not trivial. In this work, we developed a DNN framework named SSnet that utilizes secondary structure information of proteins extracted as the curvature and torsion of the protein backbone to predict PLI. We demonstrate the performance of SSnet by comparing against a variety of currently popular machine and non-machine learning models using various metrics. We visualize the intermediate layers of SSnet to show a potential latent space for proteins, in particular to extract structural elements in a protein that the model finds influential for ligand binding, which is one of the key features of SSnet. We observed in our study that SSnet learns information about locations in a protein where a ligand can bind including binding sites, allosteric sites and cryptic sites, regardless of the conformation used. We further observed that SSnet is not biased to any specific molecular interaction and extracts the protein fold information critical for PLI prediction. Our work forms an important gateway to the general exploration of secondary structure based deep learning, which is not just confined to protein-ligand interactions, and as such will have a large impact on protein research while being readily accessible for de novo drug designers as a standalone package.

bioinformatics↗

bioRxiv2019

Parkinson's disease associated mutation E46K of α-synuclein triggers the formation of a novel fibril structure

-Synuclein (-syn) amyloid fibril, as the major component of Lewy bodies and pathological entity spreading in human brain, is closely associated with Parkinsons disease (PD) and other synucleinopathies. Several single amino-acid mutations (e.g. E46K) of -syn have been identified causative to the early onset of familial PD. Here, we determined the cryo-EM structure of a full-length -syn fibril formed by N-terminal acetylated E46K mutant -syn (Ac-E46K). The fibril structure represents a new fold of -syn, which demonstrates that the E46K mutation breaks the electrostatic interactions in the wild type (WT) -syn fibril and thus triggers the rearrangement of the overall structure. Furthermore, we show that the Ac-E46K fibril is less resistant to harsh conditions and protease cleavage, and more prone to be fragmented with a higher capability of seeding fibril formation than that of the WT fibril. Our work provides a structural view to the severe pathology of the PD familial mutation E46K of -syn and highlights the importance of electrostatic interactions in defining the fibril polymorphs.

biophysics↗

bioRxiv2019

Large scale genome-wide association study reveals that drought induced lodging in grain sorghum is associated with plant height and traits linked to carbon remobilisation

Sorghum is generally grown in water limited conditions and often lodges under post-anthesis drought, which reduces yield and quality. Due to its complexity, our understanding on the genetic control of lodging is very limited. We dissected the genetic architecture of lodging in grain sorghum through genome-wide association study (GWAS) on 2308 unique hybrids grown in 17 Australian sorghum trials over 3 years. The GWAS detected 213 QTL, the majority of which showed a significant association with leaf senescence and plant height (72% and 71% respectively). Only 16 lodging QTL were not associated with either leaf senescence or plant height. The high incidence of multi-trait association for the lodging QTL indicates that lodging in grain sorghum is mainly associated with plant height and traits linked to carbohydrate remobilisation. This result supported the selection for stay-green (delayed leaf senescence) to reduce lodging susceptibility, rather than selection for short stature and lodging resistance per se, which likely reduces yield. Additionally, our data suggested a protective effect of stay-green on weakening the association between lodging susceptibility and plant height. Our study also showed that lodging resistance might be improved by selection for stem composition but was unlikely to be improved by selection for classical resistance to stalk rots. Key messageWe detected 213 lodging QTL and demonstrated that drought induced stem lodging in grain sorghum is substantially associated with stay-green and plant height, suggesting a critical role of carbon remobilisation.

genetics↗

bioRxiv2019

The microRNA476a/RFL module regulates adventitious root formation through a mitochondria-dependent pathway in Populus

Adventitious root (AR) formation at the base of stem cuttings determines the efficiency of clonal propagation for woody plants. Many endogenous and environmental factors influence AR formation. However, our knowledge about the regulation of AR development by mitochondrial metabolism in plants is very limited. Here we identified Populus-specific miR476a as a novel regulator of wound-induced adventitious rooting via orchestrating mitochondrial homeostasis in poplar. MiR476a exhibited inducible expression during AR formation and directly targets several Restorer of Fertility like (RFL) genes encoding mitochondrion-localized pentatricopeptide repeat proteins. Genetic modification of miR476-RFL expression revealed the miR476/RFL-mediated dynamic regulation of mitochondrial homeostasis on AR formation in transgenic poplar. Furthermore, mitochondrial perturbation via exogenous chemical inhibitor validated that the miR476a/RFL-directed AR formation depended on mitochondrial regulation though modulating the auxin pathway. Our results established a miRNA-directed mitochondrion-auxin signaling cascade required for AR development, providing novel insights into the understanding of mitochondrial regulation on plant developmental plasticity.

plant biology↗

bioRxiv2019

Improving personalized prediction of cancer prognoses with clonal evolution models

Cancer occurs via an accumulation of somatic genomic alterations in a process of clonal evolution. There has been intensive study of potential causal mutations driving cancer development and progression. However, much recent evidence suggests that tumor evolution is normally driven by a variety of mechanisms of somatic hypermutability, known as mutator phenotypes, which act in different combinations or degrees in different cancers. Here we explore the question of how and to which degree different mutator phenotypes act in a cancer predict its future progression. We develop a computational paradigm using evolutionary tree inference (tumor phylogeny) algorithms to derive features quantifying single-tumor mutational preferences, followed by a machine learning frame-work to identify key features predictive of progression. We build phylogenies tracing the evolution of subclones of cells in tumor tissues using a variety of somatic genomic alterations, including single nucleotide variations, copy number alterations, and structural variations. We demonstrate that mutation preference features derived from the phylogenies are predictive of clinical outcomes of cancer progression - overall survival and disease-free survival - based on the analyses on breast invasive carcinoma, lung adenocarcinoma, and lung squamous cell carcinoma. We further show that mutational phenotypes have predictive power even after accounting for traditional clinical and driver-centric predictors of progression. These results confirm the power of mutational phenotypes as an independent class of predictive biomarkers and suggest a strategy for enhancing the predictive power of conventional clinical or driver-centric genomic features.

cancer biology↗

bioRxiv2019

Large-scale GWAS in sorghum reveals common genetic control of grain size among cereals

O_LIGrain size is a key yield component of cereal crops and a major quality attribute. It is determined by a genotypes genetic potential and its capacity to fill the grains.\nC_LIO_LIThis study aims to dissect the genetic architecture of grain size in sorghum via an integrated genome wide association study (GWAS) using a diversity panel of 837 individuals and a BC-NAM population of 1,421 individuals.\nC_LIO_LIIn order to isolate genetic effects associated with grain size, rather than the genotypes capacity to fill grain, a field treatment of removing half of the panicle during flowering was imposed. Extensive variation in grain size with high heritability was observed in both populations across 5 field trials. Subsequent GWAS analyses uncovered 92 grain size QTL, which were significantly enriched for orthologues of known grain size genes in rice and maize. Significant overlap between the 92 QTL and grain size QTL in rice and maize was also found, supporting common genetic control of this trait among cereals. Further analysis found grain size genes with opposite effect on grain number were less likely to overlap with the grain size QTL from this study, indicating the treatment facilitated identification of genetic regions related to the genetic potential of grain size rather than the capacity to fill the grain.\nC_LIO_LIThese results enhance understanding of the genetic architecture of grain size in cereal, and pave the way for exploration of underlying molecular mechanisms in cereal crops and manipulation of this trait in breeding practices.\nC_LI

genetics↗

bioRxiv2019

Inactivation of genes in oxidative respiration and iron acquisition pathways in pediatric clinical isolates of small-colony variant Enterobactericeae

Isolation of bacterial small colony variants (SCVs) from clinical specimens is not uncommon and can fundamentally change the outcome of the associated infections. Bacterial SCVs often emerge with their normal colony phenotype (NCV) co-isolates in the same sample. The genetic and biochemical basis of SCV emergence in vivo is not well understood in Gram-negative bacteria. In this study, we interrogated the causal genetic lesions of SCV growth in three pairs of NCV and SCV co-isolates of Escherichia coli, Citrobacter freundii, and Enterobacter hormaechei. We confirmed the isogenic basis of SCV emergence, as there were only 4 single nucleotide variants in SCV for E. coli, 5 in C. freundii, and 8 in E. hormaechei, with respect to their NCV co-isolate. In addition, a 10.2kb chromosomal segment containing 11 genes was deleted in the E. hormaechei SCV isolate. Intriguingly, each SCV had at least one coding change in a gene associated with bacterial oxidative respiration and another involved iron capture. Chemical rescue confirmed the causal role of heme biosynthesis in E. coli and C. freundii and lipoic acid in E. hormaechei SCV isolates. Genetic rescue restored normal growth under aerobic conditions for fes and hemL in C. freundii; hemL in E. coli; and lipA in E. hormaechei SCV isolates. Prototrophic growth in all 3 SCV Enterobacteriaceae species was unaffected under anaerobic culture conditions in vitro, illustrating how SCVs may persist in vivo by abandoning the highly energetic lifestyle in an iron-limiting environment. We propose that the selective loss of functions in oxidative respiration and iron acquisition is indicative of bacterial virulence attenuation for niche specialization and persistence in vivo.\n\nImportance\n\nSmall colony variant (SCV) bacteria are routinely isolated in the clinical microbiology laboratory and can be notoriously difficult to treat. Most studies of the genetic underpinnings of SCV clinical isolates have examined Staphylococcus aureus and few have looked at how SCV emerge in Gram-negative bacteria. Here, we undertook detailed characterization of three clinical isolates of SCV in Escherichia coli, Citrobacter freundii, and Enterobacter hormaechei along with their NCV co-isolates. Genomic sequencing revealed that each SCV had at least one coding change in genes involved in both bacterial oxidative respiration and iron capture. Chemical and genetic rescue revealed that both pathways could be responsible for the small colony variant. Each of the SCV showed no growth defect compared to NCV when incubated under anaerobic conditions, indicating a potential mechanism for SCV survival in vivo. We hypothesize that by retreating to anaerobic environments and avoiding escalating iron competition with the host, SCV have adapted to live to see another day.

microbiology↗

bioRxiv2019

Keratin-Based Epidermal Green Autofluorescence is a Common Biomarker of Organ Injury

It is critical to discover biomarkers for non-invasive evaluation of the levels of inflammation and oxidative stress in human body - two key pathological factors in numerous diseases. Our study has indicated keratin 1-based epidermal autofluorescence (AF) as a biomarker of this type: Inducers of both inflammation and oxidative stress dose-dependently increased epidermal green AF with polyhedral structure in mice, with the AF intensity being highly associated with the dosages of the inducers. Lung cancer also induced increased epidermal green AF of mice, which was mediated by inflammation. Significant and asymmetrical increases in green AF intensity with polyhedral structure were found in the Dorsal Index Fingers skin of acute ischemic stroke (AIS) patients. While the AF intensity of the subjects with high risk for developing AIS, ischemic stroke patients in recovery phase and lung cancer patients was significantly higher than that of healthy controls, both AF intensity and AF asymmetry of these four groups were markedly lower than those of the AIS patients, which have shown promise for AIS diagnosis. Several lines of evidence have indicated K1 as an origin of the AF, e.g., K1 siRNA administration attenuated the oxidative stress-induced AF increase of mice. Collectively, our study has indicated K1-based epidermal AF as a biomarker for non-invasive evaluation of the levels of inflammation and oxidative stress in the body. These findings have established a basis for novel keratins AF-based biomedical imaging technology for non-invasive, efficient and economic diagnosis and screening of such inflammation- and oxidative stress-associated diseases as AIS.

biophysics↗

bioRxiv2019

Professional Swimmers and Normal Populations have Different Patterns of Epidermal Green Autofluorescence

Our recent studies have suggested that green autofluorescence of the fingernails and certain regions of skin may be novel biomarkers for disease diagnosis and evaluation of the injury state of cardiovascular system. Our study has also suggested that oxidative stress may produce the increased epidermal green AF by altering keratin 1. Since athletes body may have increased oxidative stress and inflammation, we proposed our hypothesis that athletes may have increased green AF in their fingernails and certain regions of their skin. In current study we tested this hypothesis by determining the green AF of professional swimmers. We found that compared with age-matched controls, both the green AF intensity and AF asymmetry in both right and left antebrachium and Ventriantebrachium of the professional swimmers is significantly higher. In left Dorsal Centremetacarpus, the green AF intensity of the professional swimmers is significantly higher than that of the age-matched controls. In contrast, the green AF intensity or AF asymmetry of the professional swimmers is not significantly different from that of the age-matched controls in Centremetacarpus, Ventroforefinger, Dorsal Index Finger and Index Fingernails. Collectively, our study has provided first evidence suggesting that athletes have increased green AF intensity and asymmetry in certain regions of their skin. Based on this finding, we may evaluate non-invasively the levels of oxidative damage and inflammation in athletes body.

biophysics↗

bioRxiv2019

The green autofluorescence intensity and asymmetry of older men is significantly higher than those of older women in their fingernails and certain regions of skin

Our recent studies have suggested that the patients of multiple diseases have characteristic Pattern of Autofluorescence (AF) in their skin and fingernails, which may become novel biomarkers for both disease diagnosis and evaluation of health state. Since male populations may have higher levels of oxidative stress and inflammation than female population, in our current study we tested our hypothesis that the green AF intensity of older men is higher than that of older women in their fingernails and skin. We found that in both left and right Index Fingernails, the green AF intensity of the men of both the age group of 61 - 70 years of old and the age group of 71 - 80 years of old is significantly higher than that of the women of the same age groups. At both left Dorsal Centremetacarpus and left Centremetacarpus, the green AF intensity of the men at the age between 71 - 80 years of old is also significantly higher than that of the women of the same age group. Moreover, in Index Fingernails, Dorsal Centremetacarpus and Centremetacarpus, the green AF asymmetry of the older men of certain age groups is significantly higher than that of the women of the same age groups. Collectively, our study has provided the first evidence indicating the gender difference between the green AF intensity and asymmetry of older men and those of older women in their fingernails and certain regions of skin, which is valuable for establishing the AF-based diagnostic method.

biophysics↗

bioRxiv2018

Lipopolysaccharide (LPS) induces increased epidermal green autofluorescence of mouse

Our recent studies have suggested that characteristic Pattern of Autofluorescence (AF) of each disease could be a novel biomarker for non-invasive diagnosis of multiple major diseases such as acute ischemic stroke. It is necessary to determine if increased epidermal green AF may be produced by major pathological factors such as inflammation. In our current study, we used C57BL/6Slac mice exposed to LPS to test our hypothesis that inflammation may induce increased epidermal green AF: LPS rapidly induced significant increases in the epidermal green AF of the mices ears at 1 hr after LPS injection. LPS also dose-dependently increased the epidermal green AF. The AF intensity had a linear relationship with the LPS dosages at both 3 and 7 days after the LPS administration. The AF images exhibited the characteristic structure of the keratinocytes in Stratum Spinosum, suggesting that the origin of the increased AF was keratin 1 and/or keratin 10. Collectively, our current study has provided the first evidence indicating that inflammation can rapidly and dose-dependently induce increased epidermal green AF, suggesting that the green AF may be the first biomarker for non-invasive and rapid detection of systemic inflammation. Since inflammation is a key pathological factor of numerous diseases, our finding has highlighted the value of the epidermal AF as a novel diagnostic biomarker for numerous diseases.

biophysics↗

bioRxiv2018

Mesenchymal stem cell derived exosomes enhance lymphangiogenesis via exosomal transfer of Ang-2/Tie2

Mesenchymal stem cell derived exosomes (MSC-Ex) are nanosized membrane-bound extracellular vesicles found in MSC conditioned medium, that have yielded beneficial effects in several experimental models of organ injury. However, the therapeutic value and mechanism of MSC-Ex in lymphedema is poorly understood. Here we find that human umbilical cord MSCs derived exosomes (hucMSC-Ex) treatment contributed to the regeneration of LYVE-1 positive lymphatic vessels and reduction of lymphedema in a mouse model of tail lymphedema. Following uptake, exosomal lymphangiogenic factors (angiopoietin (Ang)-2 and Tie2) are taken up by HDLECs and promoted HDLECs proliferation, migration, and tube formation in vitro. We also find that exosomal Ang-2 and Tie2 exert a prolymphangiogenic effect on HDLECs through upregulating Prox1 and VEGFR3/p-Akt expression. In conclusion, our result unravel a previously unappreciated prolymphangiogenic role of hucMSC-Ex in lymphedema therapy and provide a new mechanism of Ang-2 in therapeutic lymphangiogenesis.

bioengineering↗

bioRxiv2018

The Coordination and Jumps along C4 Photosynthesis Evolution in the Genus Flaveria

BackgroundC4 photosynthesis is a remarkable complex trait, elucidations of the evolutionary trajectory of C4 photosynthesis from its ancestral C3 pathway can help us to better understand the generic principles of complex trait evolution and guide engineering of C3 crops for higher yields. We used the genus Flaveria that contains C3, C3-C4, C4-like and C4 species as a system to study the evolution of C4 photosynthesis.\n\nResultsWe mapped transcript abundance, protein sequence, and morphological features to the phylogenetic tree of the genus Flaveria, and calculated the evolutionary correlation of different features. Besides, we predicted the relative changes of ancestral nodes of those features to illustrate the key stages during the evolution of C4 photosynthesis. Gene expression and protein sequence showed consistent modification pattern along the phylogenetic tree. High correlation coefficients ranging from 0.46 to 0.9 among gene expression, protein sequence and morphology were observed, and the greatest modification of those different features consistently occurred at the transition between C3-C4 species and C4-like species.\n\nConclusionsOur data shows highly coordinated changes in gene expression, protein sequence and morphological features. Besides, our results support an obviously evolutionary jump during the evolution of C4 metabolism.

evolutionary biology↗

bioRxiv2018

Effects of age on the green autofluorescence of the skin and fingernails of healthy persons

Our recent studies have suggested that altered Pattern of Autofluorescence (AF) of skin and fingernails are novel biomarkers of multiple major diseases. The age of all of the subjects in these studies ranges from 50 to 80 years of old. For future studies on the potential diagnostic value of green AF for age-independent diseases, it is required to answer the following question: Are there differences in the green AF of healthy persons of various age populations? In our current study, we determined the green AF of the skin and fingernails of healthy persons in several age populations, showing significant age dependence of the AF: First, the green AF intensity of the age group between 15 to 20 years of old is significantly higher than that of the age group between 50 to 80 years of old at both right and left Centremetacarpus, right Dorsal Centremetacarpus, and right Dorsal Index Finger. Second, for the green AF intensity of the age groups of 15 to 20 years of old, 60 to 70 years of old, 70 to 80 years of old, and 81 to 85 years of old, the green AF intensity is negatively correlated with the age at both right and left Centremetacarpus and right Dorsal Centremetacarpus. Collectively, our study has provided first evidence indicating the age dependence of the AF intensity of humans skin, which has established essential basis for the studies that determine the diagnostic value of the green AF for the age-independent diseases.

physiology↗

bioRxiv2018

Automatic Human-like Mining and Constructing Reliable Genetic Association Database with Deep Reinforcement Learning

The increasing amount of scientific literature in biological and biomedical science research has created a challenge in the continuous and reliable curation of the latest knowledge discovered, and automatic biomedical text-mining has been one of the answers to this chal-lenge. In this paper, we aim to further improve the reliability of biomedical text-mining by training the system to directly simulate the human behaviors such as querying the PubMed, selecting articles from queried results, and reading selected articles for knowledge. We take advantage of the efficiency of biomedical text-mining, the flexibility of deep reinforcement learning, and the massive amount of knowledge collected in UMLS into an integrative arti-ficial intelligent reader that can automatically identify the authentic articles and effectively acquire the knowledge conveyed in the articles. We construct a system, whose current pri-mary task is to build the genetic association database between genes and complex traits of the human. Our contributions in this paper are three-fold: 1) We propose to improve the reliability of text-mining by building a system that can directly simulate the behavior of a researcher, and we develop corresponding methods, such as Bi-directional LSTM for text mining and Deep Q-Network for organizing behaviors. 2) We demonstrate the effec-tiveness of our system with an example in constructing a genetic association database. 3) We release our implementation as a generic framework for researchers in the community to conveniently construct other databases.

bioinformatics↗