Biology subjects

Song, J.

Publications and source records attributed to Song, J..

At least 289 records · Page 16Linked to original sources

bioRxiv2019

Discovery and Multi-center Verification of Prostate Cancer Protein Biomarkers using Single-shot Short Gradient Microflow SWATH and MRMHR Mass Spectrometry

We report and evaluated a microflow, single-shot, short gradient SWATH MS method intended to accelerate the discovery and verification of protein biomarkers in clinical specimens. The method uses 15-min gradient microflow-LC peptide separation, an optimized SWATH MS window configuration and OpenSWATH software for data analysis.\n\nWe applied the method to a cohort 204 of FFPE prostate tissue samples from 58 prostate cancer patients and 10 prostatic hyperplasia patients. Altogether we identified 27,976 proteotypic peptides and 4,043 SwissProt proteins from these 204 samples. Compared to a reference SWATH method with 2-hour gradient the accelerated method consumed only 27% instrument time, quantified 80% proteins and showed reduced batch effects. 3,800 proteins were quantified by both methods in two different instruments with relatively high consistency (r = 0.77). 75 proteins detected by the accelerated method with differential abundance between clinical groups were selected for further validation. A shortlist of 134 selected peptide precursors from the 75 proteins were analyzed using MRM-HR, exhibiting high quantitative consistency with the 15-min SWATH method (r = 0.89) in the same sample set. We further verified the capacity of these 75 proteins in separating benign and malignant tissues (AUC = 0.99) in an independent prostate cancer cohort (n=154).\n\nOverall our data show that the single-shot short gradient microflow-LC SWATH MS method achieved about 4-fold acceleration of data acquisition with reduced batch effect and a moderate level of protein attrition compared to a standard SWATH acquisition method. Finally, the results showed comparable ability to separate clinical groups.

cancer biology↗

bioRxiv2019

NMDA receptor in vasopressin 1b neurons is not required for short-term social memory, object memory or aggression.

The vasopressin 1b receptor (Avpr1b) plays an important role in social behaviors including aggression, social learning and memory. Genetic removal of Avpr1b from mouse models results in deficits in aggression and short-term social recognition in adults. Avpr1b gene expression is highly enriched in the pyramidal neurons of the hippocampal cornu ammonis 2 (CA2) region. Activity of the hippocampal CA2 has been shown to be required for normal short-term social recognition and aggressive behaviors. Vasopressin acts to enhance synaptic responses of CA2 neurons through a NMDA-receptor dependent mechanism. Genetic removal of the obligatory subunit of the NMDA receptor (Grin1) within distinct hippocampal regions impairs non-social learning and memory. However, the question of a direct role for NMDA receptor activity in Avpr1b neurons to modulate social behavior remains unclear. To answer this question, we first created a novel transgenic mouse line with Cre recombinase knocked into the Avpr1b coding region to genetically target Avpr1b neurons. We confirmed this line has dense Cre expression throughout the dorsal and ventral CA2 regions of the hippocampus, along with scattered expression within the caudate-putamen and olfactory bulb. Conditional removal of the NMDA receptor was achieved by crossing our line to an available floxed Grin1 line. The resulting mice were measured on a battery of social and memory behavioral tests. Surprisingly, we did not observe any differences between Avpr1b-Grin1 knockout mice and their wildtype siblings. We conclude that mice without typical NMDA receptor function in Avpr1b neurons can develop normal aggression as well as short-term social and object memory performance.\n\nSignificance StatementActivity of neurons that express vasopressin 1b receptor are essential for aggressive and social recognition behaviors. We created a novel transgenic mouse to allow selective targeting of vasopressin 1b neurons. Our studies indicate that NMDA receptor expression in vasopressin 1b neurons (including most CA2 neurons) are not required for development of the typical expression of aggression or recognition memory. Thus, CA2 neurons may have a unique way of incorporating novel stimuli into memory that deserves further investigation.

neuroscience↗

bioRxiv2019

Hydrogel platform for in vitro three-dimensional assembly of human stem cell-derived β cells and endothelial cells

Differentiation of stem cells into functional replacement cells and tissues is a major goal of the regenerative medicine field. However, one limitation has been organization of differentiated cells into multi-cellular, three-dimensional assemblies. The islets of Langerhans contain many endocrine and non-endocrine cell types, such as insulin-producing {beta} cells and endothelial cells. Transplantation of exogenous islets into diabetic patients can serve as a cell replacement therapy, replacing the need for patients to inject themselves with insulin, but the number of available islets from cadaveric donors is low. We have developed a strategy of assembling human embryonic stem cell-derived {beta} cells with endothelial cells into three-dimensional aggregates on a hydrogel. The resulting islet organoids express {beta} cell markers and are functional, capable of undergoing glucose-stimulated insulin secretion. These results provide a platform for evaluating the effects of the islet tissue microenvironment on human embryonic stem cell-derived {beta} cells and other islet endocrine cells to develop tissue engineered islets.

bioengineering↗

bioRxiv2019

Long noncoding RNA AVAN promotes antiviral innate immunity by interacting with TRIM25 and enhancing the transcription of FOXO3a

Accumulating evidence has shown that long noncoding RNAs (lncRNAs) are involved in several biological processes, including immune responses. However, the role of lncRNAs in antiviral innate immune responses remains largely unexplored. Here, we identify an uncharacterized human lncRNA from influenza A virus (IAV) patients, antivirus and activate neutrophil (AVAN), that is significantly up-regulated upon virus infection. Mechanistically, nuclear lncRNA-AVAN positively regulates the transcription of forkhead box O3A (FOXO3a) by associating with its promoter and inducing chromatin remodeling to promote neutrophil chemotaxis. Furthermore, we also found that cytoplasmic lncRNA-AVAN directly binds tripartite motif containing 25 (TRIM25) and enhances the association of TRIM25 and Retinoic acid inducible gene-1 proteins (RIG-I) and the ubiquitylation of RIG-I, thereby promoting TRIM25- and RIG-I-mediated antiviral innate immune signaling. More importantly, we enforced the expression of AVAN in transgenic mice and found that it significantly alleviated IAV virulence and virus production. Collectively, these findings highlight the potential clinical implications of lncRNA-AVAN as a key positive regulator of the antiviral innate immune response and a promising target for developing broad antiviral therapeutics.

immunology↗

bioRxiv2019

Marker subset selection and decision support range identification for acute myeloid leukemia classification model development with multiparameter flow cytometry

In this study, we developed acute myeloid leukemia (AML) classification model through Wilks lambda-based important marker-identification method and stepwise-forward selection approach, and spotted important decision-support range of flow-cytometry parameter using insights provided by machine-learning algorithm. AML flow-cytometry data released from FlowCAP-II challenge in 2011 was used. In FlowCAP-II challenge, several sample classification algorithms were able to effectively classify AML and non-AML. Most algorithms extracted features from high-dimensional flow-cytometry readout comprised of multiple fluorescent parameters for a large number of antibodies. Multiple parameters with forward scatter and side scatter increase computational complexity in the feature-extraction procedure as well as in the model development. Parameter-subset selection can decrease model complexity, improve model performance, and contribute to a panel design specific for target disease. With this motivation, we estimated importance of each parameter via Wilks lambda and then identified the best subset of parameters using stepwise-forward selection. In the importance-estimation process, histogram matrix of each parameter was used. As a result, parameters, which are associated with blasts gating and identification of immature myeloid cells, were identified as important descriptors in AML classification, and combination of these markers is more effective than an individual marker. A random-forest, supervised-classification machine-learning algorithm was used for the model development. We highlighted decision-support range of the fluorescent signal for the identified important parameters, which significantly contribute to AML classification, through a mean decrease in Gini supported in random forest. These specific ranges could help with establishing diagnosis criteria and elaborate the AML classification model. Because methodology proposed in this study can not only estimate the importance of each parameter but also identify the best subset and the specific ranges, we expect that it would contribute to in silico modeling using flow- and mass-cytometry readout as well as panel design for sample classification.\n\nAuthor summaryFlow cytometry is a widely used technique to analyze multiple physical characteristics of an individual cell and diagnose and monitor human disease as well as response to therapy. Recent developments in hardware (multiple lasers and fluorescence detectors), fluorochromes, and antibodies have facilitated the comprehensive and in-depth analysis of high numbers of cells on a single cell level and led to the creation of various computational analysis methods for cell type identification, rare cell identification, and sample classification. Flow cytometry typically uses panels with a large number of antibodies, leading to high-dimensional multiparameter flow cytometry readout. It increases computational complexity and makes interpretation difficult. In this study, we identified the best subset of the parameters for AML classification model development. The subset would contribute to panel design specific for the target disease and lead to easy interpretation of the results. In addition, we spotted important decision-support range of flow-cytometry parameter via insights provided by machine-learning algorithm. We expect that profiling information of fluorescence expression over the identified decision-support range would complement existing diagnosis criteria.

bioinformatics↗

bioRxiv2019

Identification of Ca-rich dense granules in human platelets using scanning transmission X-ray microscopy

Whole mount (WM) platelet preparations followed by transmission electron microscopy (TEM) observation is the standard method currently used to assess dense granule (DG) deficiency (DGD). However, due to electron density-based contrast mechanism in TEM, other granules such as -granules might cause false DGs detection. Herein, scanning transmission X-ray microscopy (STXM), was used to identify DGs and minimize false DGs detection of human platelets. STXM image stacks of human platelets were collected at the calcium (Ca) L2,3 absorption edge and then converted to optical density maps. Ca distribution maps obtained by subtracting the optical density map at pre-edge region from those obtained at post-edge region were used for identification of DGs based on richness of Ca. Dense granules were successfully detected by using STXM method without false detection based on Ca maps for 4 human platelets. Spectral analysis of granules in human platelets confirmed that DGs contained richer Ca content than other granules. Image analysis of Ca maps provided quantitative parameters which would be useful for developing image-based DG diagnosis models. Therefore, we would like to propose STXM as a promising approach for better DG identification and DGD diagnosis, as a complementary tool to the current WM TEM approach.

biophysics↗

bioRxiv2019

Mass Cytometry Study on the Heterogeneity in Cellular Association and Cytotoxicity of Silver Nanoparticles in Human Immune Cells

There have been many reports about the adverse effects of nanoparticles (NPs) on the environment and human health. Conventional toxicity assessments of NPs frequently assume uniform distribution of monodisperse NPs in homogeneous cell populations, and provide information on the relationships between the administered dose of NPs and cellular responses averaged for a large number of cells. They may have limitations in describing the wide heterogeneity of cell-NP interactions, caused by cell-to-cell and NP-to-NP variances. To achieve more detailed insight into the heterogeneity of cell-NP interactions, it is essential to understand the cellular association and adverse effects of NPs at single-cell level. In this study, we applied mass cytometry to investigate the interactions between silver nanoparticles (AgNPs) and primary human immune cells. High dimensionality of mass cytometry allowed us to identify various immune cell types and observe the cellular association and toxicity of AgNPs in each population. Our findings showed that AgNPs had higher affinity with phagocytic cells like monocytes and dendritic cells and caused more severe toxic effects than with T cells, B cells and NK cells. Multi-element detection capability of mass cytometry also enabled us to simultaneously monitor cellular AgNP dose and intracellular signaling of individual cells, and subsequently investigate the dose-response relationships of each immune population at single-cell level, which are often hidden in conventional toxicity assays at bulk-cell level. Our study will assist future development of single-cell dose-response models for various NPs and will provide key information for the safe use of nanomaterials for biomedical applications.

biochemistry↗

bioRxiv2019

Identification of flowering-time genes in mast flowering plants using de novo transcriptomic analysis

Mast flowering is synchronised highly variable flowering by a population of perennial plants over a wide geographical area. High seeding years are seen as a threat to native and endangered species due to high predator density caused by the abundance of seed. An understanding of the molecular pathways that influence masting behaviour in plants could provide better prediction of a forthcoming masting season and enable conservation strategies to be deployed. In this study, a high-throughput large-scale RNA-sequencing was performed on two masting plant species, Celmisia lyallii (Asteraceae), and Chionochloa pallens (Poaceae) to develop a reference transcriptome for functional and molecular analysis. An average total of 33 million 150 base-paired reads, for both species, were assembled using the Trinity pipeline, resulting in 151,803 and 348,649 transcripts respectively for Celmisia and Chionochloa. The two datasets generated were blasted against the publicly available databases, TAIR, Swiss-Prot, non-redundant protein (nr), KEGG and COG for unigene annotations. On average, 56% of the unigenes were finally annotated with gene descriptions mapped to known protein sequences for both the species. Gene ontology analysis was then performed on the assembled reference transcriptomes, categorising the transcripts on the basis of putative biological processes, molecular function, and cellular localisation. A total of 543 transcripts from Celmisia and 470 transcripts from Chionochloa were also mapped to unique flowering-time proteins identified in Arabidopsis, suggesting the conservation of the flowering network in these wild alpine plants, growing in natural field conditions. These genes can further be analysed to understand the molecular regulation of the reproductive phase transition in the masting plants.

plant biology↗

bioRxiv2019

Rapid and label-free identification of individual bacterial pathogens exploiting three-dimensional quantitative phase imaging and deep learning

The healthcare industry is in dire need for rapid microbial identification techniques. Microbial infection is a major healthcare issue with significant prevalence and mortality, which can be treated effectively during the early stages using appropriate antibiotics. However, determining the appropriate antibiotics for the treatment of the early stages of infection remains a challenge, mainly due to the lack of rapid microbial identification techniques. Conventional culture-based identification and matrix-assisted laser desorption/ionization time-of-flight mass spectroscopy are the gold standard methods, but the sample amplification process is extremely time-consuming. Here, we propose an identification framework that can be used to measure minute quantities of microbes by incorporating artificial neural networks with three-dimensional quantitative phase imaging. We aimed to accurately identify the species of bacterial bloodstream infection pathogens based on a single colony-forming unit of the bacteria. The successful distinction between a total of 19 species, with the accuracy of 99.9% when ten bacteria were measured, suggests that our framework can serve as an effective advisory tool for clinicians during the initial antibiotic prescription. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/596486v2_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@786668org.highwire.dtl.DTLVardef@8b4eb4org.highwire.dtl.DTLVardef@1dc2452org.highwire.dtl.DTLVardef@1d4888c_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2019

DNA methylation, microRNA expression profiles and their relationships with transcriptome in grass-fed and grain-fed Angus Cattle rumen tissue

Rumen is a critical organ for supplying nutrients for the growth and production of bovine, which might function differently under grass-fed and grain-fed regimens considering the association of gene expression, DNA methylation, and microRNA expression. The objective of this study was to explore the potential mechanism influencing rumen function of grass-fed and grain-fed animals. Methylated DNA binding domain sequencing (MBD-Seq) and microRNA-Seq were respectively utilized to detect the DNA methylation and microRNA expression in rumen tissue of grass-fed and grain-fed Angus cattle. Integration analysis revealed that the expression of the differentially expressed genes ADAMTS3 and ENPP3 was correlated with the methylation abundance of the corresponding DMRs inside these two genes, and these two genes were reported to be respectively involved in biosynthesis and regulation of glycosyltransferase activity; the differentially expressed microRNA bta-mir-122 was predicted to possibly target the differentially expressed genes OCLN and RBM47, potentially affecting the rumen function; the microRNA bta-mir-655 was exclusively detected in grain-fed group; its targets were involved in the significantly enriched insulin and TGF-beta signaling pathways, which might worked together to regulate the function of rumen, resulting in different characteristics between grass-fed and grain-fed cattle. Collectively, our results provided insights into understanding the mechanisms determining rumen function and unraveled the biological basis underlying the economic traits to improve the productivity of animals.

genomics↗

bioRxiv2019

Shotgun metagenomics reveals an enrichment of potentially cross-reactive bacterial epitopes in ankylosing spondylitis patients, as well as the effects of TNFi therapy and the host’s genotype upon microbiome composition

Diverse evidence including clinical, genetic and microbiome studies support a major role of the gut microbiome in the common immune-mediated arthropathy, ankylosing spondylitis (AS). To further investigate this we performed metagenomic analysis of a case-control cohort of 250 Han-Chinese subjects. Previous reports of gut dysbiosis in AS were re-confirmed and several notable bacterial species and functional categories were differentially abundant. TNF-inhibitor (TNFi) therapy at least partially restored the perturbed microbiome observed in untreated AS cases to that of healthy controls, including several important bacterial species that have been previously associated with AS and other related diseases. Enrichment of bacterial peptides homologous to HLA-B27-presented epitopes was observed in the stools of AS patients, suggesting that either HLA-B27 fails to clear these or that they are involved in driving HLA-B27-associated immune reactions. TNFi therapy of AS patients was also associated with a reduction of potentially arthritogenic bacterial peptides, relative to untreated patients. An AS-associated SNP in RUNX3 significantly influenced the microbiome in two independent cohorts, highlighting a host genotype (other than HLA-B27) potentially influencing AS via the microbiome. These findings emphasise the key role that the gut microbiome plays in driving the pathogenesis of AS.

microbiology↗

bioRxiv2019

3D computational models explain muscle activation patterns and energetic functions of internal structures in fish swimming

How muscles are used is a key to understanding the internal driving of fish swimming. However, the underlying mechanisms of some features of the muscle activation patterns and their differential appearance on different species are still obscure. In this study, we explain the muscle activation patterns by using 3D computational fluid dynamics models coupled to the motion of fish with prescribed deformation and examining the torque and power required along the fish body with two primary swimming modes. We find that the torque required by the hydrodynamic forces and body inertia exhibits a wave pattern that travels faster than the curvature wave in both anguilliform and carangiform swimmers, which can explain the traveling wave speeds of the muscle activations. Most interestingly, intermittent negative power (i.e., power delivered by the fluid to the body) on the posterior part, along with a timely transfer of torque and energy by tendons, explains the decrease of the duration of muscle activation towards the tail. The torque contribution from the body elasticity further solves the mystery of the wave speed increase or the reverse of the wave direction of the muscle activation on the posterior part of a carangiform swimmer. For anguilliform swimmers, the absence of the changes mentioned above in the muscle activation on the posterior part is in line with our torque prediction and the absence of long tendons from experimental observations. These results provide novel insights into the function of muscles and tendons as an integrative part of the internal driving system, especially from an energy perspective, and highlight the differences in the internal driving systems between the two primary swimming modes. Author summaryFor undulatory swimming, fish form posteriorly traveling waves of body bending by activating their muscles sequentially along the body. However, experimental observations have showed that the muscle activation wave does not simply match the bending wave. Researchers have previously computed the torque required for muscles along the body based on classic hydrodynamic theories and explained the higher wave speed of the muscle activation compared to the curvature wave. However, the origins of other features of the muscle activation pattern and their variation among different species are still obscure after decades of research. In this study, we use 3D computational fluid dynamics models to compute the spatiotemporal distributions of both the torque and power required for eel-like and mackerel-like swimming. By examining both the torque and power patterns and considering the energy transfer, storage, and release by tendons and body viscoelasticity, we can explain not only the features and variations in the muscle activation patterns as observed from fish experiments but also how tendons and body elasticity save energy. We provide a mechanical picture in which the body shape, body movement, muscles, tendons, and body elasticity of a mackerel (or similar) orchestrate to make swimming efficient.

biophysics↗

bioRxiv2019

Transcriptome Analysis of juvenile Pacific White Shrimp (Litopenaeus vannamei) with symptom of stunted growth

In search for viruses associated with Litopenaeus vannamei with symptom of stunted growth, we have undertaken a comparative transcriptome analysis of total RNA sequences using Illumina based high-throughput sequencing (HTS). We obtain 89000242 and 95126160 high-quality clean reads from cDNA libraries of L.vannamei with stunted growth symptom (sick group) and health shrimp (health group control), respectively. Totally, 108221 unigenes with an average length of 716 bp were obtained from RNA-seq data. The unigenes were annotated against NR, NT, KO, KOG, SwissProt, PFAM and GO databases. 3975 (3.67%) showed significant matches in all the above databases and 39812 (36.78%) unigenes were annotated in at least one database. Comparative transcriptomic analysis revealed that 807 significantly differentially expressed unigenes were identified, including 282 down-regulated genes and 525 up-regulated genes. Thirteen up-regulated virus-related genes were only discovered in the sick shrimp groups, but not in health ones. Five of them were closely related to virus family Picornaviridae. From phylogenetic tree, we could find five viral genes were closely related to genus Ampvirus, Falcovirus, Aquamavirus (Seal picornavirus). Some up-regulated genes in the Sick groups mainly included genes involved in virus infecting processes concerning antigen processing and presenting, apoptosis, lysosome, phagosome and inflammation. While, many down-regulated genes in the Sick groups mainly involved in the process of starch and sucrose metabolism, and protein digestion and absorption. Our research provided some useful information about pathogenic factor and mechanism on the stunted growth symptom of L.vannamei, and was significant for the control and prevention of this disease.

pathology↗

bioRxiv2019

Dynamic Erasure of Random X-Chromosome Inactivation during iPSC Reprogramming

BackgroundInduction and reversal of chromatin silencing is critical for successful development, tissue homeostasis and the derivation of induced pluripotent stem cells (iPSCs). X-chromosome inactivation (XCI) and reactivation (XCR) in female cells represent chromosome-wide transitions between active and inactive chromatin states. While XCI has long been studied and provided important insights into gene regulation, the dynamics and mechanisms underlying the reversal of stable chromatin silencing of X-linked genes are much less understood. Here, we use allele-specific transcriptomic approaches to study XCR during mouse iPSC reprogramming in order to elucidate the timing and mechanisms of chromosome-wide reversal of gene silencing. ResultsWe show that XCR is hierarchical, with subsets of genes reactivating early, late and very late. Early genes are activated before the onset of late pluripotency genes activation and the complete silencing of the long non-coding RNA (lncRNA) Xist. These genes are located genomically closer to genes that escape XCI, unlike those reactivating late. Interestingly, early genes also show increased pluripotency transcription factor (TF) binding. We also reveal that histone deacetylases (HDACs) restrict XCR in reprogramming intermediates and that the severe hypoacetylation state of the Xi persists until late reprogramming stages. ConclusionsAltogether, these results reveal the timing of transcriptional activation of mono-allelically repressed genes during iPSC reprogramming, and suggest that allelic activation involves the combined action of chromatin topology, pluripotency transcription factors and chromatin regulators. These findings are important for our understanding of gene silencing, maintenance of cell identity, reprogramming and disease.

developmental biology↗

bioRxiv2019

Deep-learning based three-dimensional label-free tracking and analysis of immunological synapses of chimeric antigen receptor T cells

We propose and experimentally validate a label-free, volumetric, and automated assessment method of immunological synapse dynamics using a combinational approach of optical diffraction tomography and deep learning-based segmentation. The proposed approach enables automatic and quantitative spatiotemporal analyses of immunological synapse kinetics regarding morphological and biochemical parameters related to the total protein densities of immune cells, thus providing a new perspective for studies in immunology.

immunology↗

bioRxiv2019

Loss of CIC promotes mitotic dysregulation and chromosome segregation defects

CIC encodes a transcriptional repressor and MAPK signalling effector that is inactivated by loss-of-function mutations in several cancer types, consistent with a role as a tumour suppressor. Here, we used bioinformatic, genomic, and proteomic approaches to investigate CICs interaction networks. We observed both previously identified and novel candidate interactions between CIC and SWI/SNF complex members, and also observed novel interactions between CIC and cell cycle regulators and RNA processing factors. We found that CIC loss is associated with an increased frequency of mitotic defects in human cell lines and an in vivo mouse model and with dysregulated expression of mitotic regulators. We also observed aberrant splicing in CIC-deficient cell lines predominantly at 3 and 5 untranslated regions of genes, including genes involved in MAPK signalling, DNA repair, and cell cycle regulation. Our study thus characterises the complexity of CICs functional network and describes the effect of its loss on cell cycle regulation, mitotic integrity, and transcriptional splicing, thereby expanding our understanding of CICs potential roles in cancers. In addition, our work exemplifies how multi-omic, network-based analyses can be used to uncover novel insights into the interconnected functions of pleiotropic genes/proteins across cellular contexts. Simple summaryCapicua (CIC) is a gene that is frequently mutated in several cancer types, including stomach cancers and certain subtypes of brain tumours and sarcomas. CIC, the protein encoded by the CIC gene, has been shown to play a multitude of roles in both normal and cancer cell functions; however, most studies exploring these roles focus on a single aspect of CIC function and may therefore overlook complex interconnected activities in which CIC is involved. In this study, we have used multiple complementary approaches to obtain a broader view of CICs complex functional networks. We observed novel interactions (genetic or physical) between CIC and genes/proteins involved in various aspects of cellular function, including regulation of cell division and processing of RNA molecules. Altogether, our work characterises the complexity of CICs functional network and expands our understanding of its potential roles in cancer.

cancer biology↗

bioRxiv2019

Genetic diversity analysis of an isolate of microsporidia infesting Athetis lepigone

In this study, PCR amplification, cloning and sequencing analysis were adopted to explore genetic diversity of microsporidia (LEP9557) infecting Athetis lepigone. The small subunit ribosomal DNA (SSU rDNA), internal transcribed spacer (ITS) and intergenic spacers (IGS) of ribosomal RNA (rRNA) were cloned from the strain and sequenced. By means of multiple sequence alignment, we found that the three gene regions had different levels of polymorphism. There was greater polymorphism in ITS (74 variable sites) and IGS (55.59%) regions than in the SSU rDNA (17 variable sites). Phylogenetic analysis was performed using Kimura 2-parameter with neighbor joining and the results showed that LEP9557 had a close relationship with Nosema bombycis. Sequences of each clone were submitted to Genbank (Accession number: MF150254-MF150258). All of the results indicated the presence of genetic diversity in LEP9557, which established the foundation for identifying the phylogeny and relationships with other microsporidian strains, and had significant biological meaning for maintaining the survival and population continuity of the strain.

microbiology↗

bioRxiv2019

PRISM: a comprehensive 3D structure database for post-translational modifications and mutations with functional impact

Post-translational modifications (PTMs) play very important roles in various cell signalling pathways and biological process. Due to PTMs extremely important roles, many major PTMs have been thoroughly studied, while the functional and mechanical characterization of major PTMs is well-documented in several databases. However, most currently available databases mainly focus on protein sequences, while the real 3D structures of PTMs have been largely ignored. Therefore, studies of PTMs 3D structural signatures have been severely limited by the deficiency of the data. Here, we develop PRISMOID, a novel publicly available and free 3D structure database for a wide range of PTMs. PRISMOID represents an up-to-date and interactive online knowledge base with specific focus on 3D structural contexts of PTMs sites and mutations that occur on PTMs and in the close proximity of PTM sites with functional impact. The first version of PRISMOID encompasses 17,145 non-redundant modification sites on 3,919 related protein 3D structure entries pertaining to 37 different types of PTMs. Our entry web page is organized in a comprehensive manner, including detailed PTM annotation on the 3D structure and biological information in terms of mutations affecting PTMs, secondary structure features and per-residue solvent accessibility features of PTM sites, domain context, predicted natively disordered regions and sequence alignments. In addition, high-definition JavaScript packages are employed to enhance information visualization in PRISMOID. PRISMOID equips a variety of interactive and customizable search options and data browsing functions; these capabilities allow users to access data via keyword, ID, and advanced options combination search in an efficient and user-friendly way. A download page is also provided to enable users to download the SQL file, computational structural features, and PTM sites data. We anticipate PRISMOID will swiftly become an invaluable online resource, assisting both biologists and bioinformaticians to conduct experiments and develop applications supporting discovery efforts in the sequence-structural-functional relationship of PTMs and providing important insight into mutations and PTM sites interaction mechanisms. The PRISMOID database is freely accessible at http://prismoid.erc.monash.edu/. The database and web interface are implemented in MySQL, JSP, JavaScript, and HTML with all major browsers supported.

bioinformatics↗