Biology subjects

He, S.

Publications and source records attributed to He, S..

296 records · Page 17Linked to original sources

bioRxiv2017

Instructive starPEG-Heparin biohybrid 3D cultures for modeling human neural stem cell plasticity, neurogenesis, and neurodegeneration

Three-dimensional models of human neural development and neurodegeneration are crucial when exploring stem-cell-based regenerative therapies in a tissue-mimetic manner. However, existing 3D culture systems are not sufficient to model the inherent plasticity of NSCs due to their ill-defined composition and lack of controllability of the physical properties. Adapting a glycosaminoglycan-based, cell-responsive hydrogel platform, we stimulated primary and induced human neural stem cells (NSCs) to manifest neurogenic plasticity and form extensive neuronal networks in vitro. The 3D cultures exhibited neurotransmitter responsiveness, electrophysiological activity, and tissue-specific extracellular matrix (ECM) deposition. By whole transcriptome sequencing, we identified that 3D cultures express mature neuronal markers, and reflect the in vivo make-up of mature cortical neurons compared to 2D cultures. Thus, our data suggest that our established 3D hydrogel culture supports the tissue-mimetic maturation of human neurons. We also exemplarily modeled neurodegenerative conditions by treating the cultures with A{beta}42 peptide and observed the known human pathological effects of Alzheimers disease including reduced NSC proliferation, impaired neuronal network formation, synaptic loss and failure in ECM deposition as well as elevated Tau hyperphosphorylation and formation of neurofibrillary tangles. We determined the changes in transcriptomes of primary and induced NSC-derived neurons after A{beta}42, providing a useful resource for further studies. Thus, our hydrogel-based human cortical 3D cell culture is a powerful platform for studying various aspects of neural development and neurodegeneration, as exemplified for A{beta}42 toxicity and neurogenic stem cell plasticity.\n\nSignificanceNeural stem cells (NSC) are reservoir for new neurons in human brains, yet they fail to form neurons after neurodegeneration. Therefore, understanding the potential use of NSCs for stem cell-based regenerative therapies requires tissue-mimetic humanized experimental systems. We report the adaptation of a 3D bio-instructive hydrogel culture system where human NSCs form neurons that later form networks in a controlled microenvironment. We also modeled neurodegenerative toxicity by using Amyloid-beta4 peptide, a hallmark of Alzheimers disease, observed phenotypes reminiscent of human brains, and determined the global gene expression changes during development and degeneration of neurons. Thus, our reductionist humanized culture model will be an important tool to address NSC plasticity, neurogenicity, and network formation in health and disease.

neuroscience↗

bioRxiv2017

Ennet: exert enhaner-only somatic mutations to discover potential cancer-driving biological networks

Whole genome sequencing technology has facilitated the discovery of a large number of somatic mutations in enhancers (SMEs), whereas the utility of SMEs in tumorigenesis has not been fully explored. Here we present Ennet, a method to comprehensively investigate SMEs enriched networks (SME-networks) in cancer by integrating SMEs, enhancer-gene interactions and gene-gene interactions. Using Ennet, we performed a pan-cancer analysis in 2004 samples from 8 cancer types and found many well-known cancer drivers were involved in the SME-networks, including ESR1, SMAD3, MYC, EGFR, BCL2 and PAX5. Meanwhile, Ennet also identified many new networks with less characterization but have potentially important roles in cancer, including a large SME-network in medulloblastoma (MB), which contains genes enriched in the glutamate receptor and neural development pathways. Interestingly, SME-networks are specific across cancer types, and the vast majority of the genes identified by Ennet have few mutations in gene bodies. Collectively, our work suggests that using enhancer-only somatic mutations can be an effective way to discover potential cancer-driving networks. Ennet provides a new perspective to explore new mechanisms for tumor progression from SMEs.

bioinformatics↗

bioRxiv2017

Interoperable and scalable metabolomics data analysis with microservices

Developing a robust and performant data analysis workflow that integrates all necessary components whilst still being able to scale over multiple compute nodes is a challenging task. We introduce a generic method based on the microservice architecture, where software tools are encapsulated as Docker containers that can be connected into scientific workflows and executed in parallel using the Kubernetes container orchestrator. The access point is a virtual research environment which can be launched on-demand on cloud resources and desktop computers. IT-expertise requirements on the user side are kept to a minimum, and established workflows can be re-used effortlessly by any novice user. We validate our method in the field of metabolomics on two mass spectrometry studies, one nuclear magnetic resonance spectroscopy study and one fluxomics study, showing that the method scales dynamically with increasing availability of computational resources. We achieved a complete integration of the major software suites resulting in the first turn-key workflow encompassing all steps for mass-spectrometry-based metabolomics including preprocessing, multivariate statistics, and metabolite identification. Microservices is a generic methodology that can serve any scientific discipline and opens up for new types of large-scale integrative science.

bioinformatics↗

bioRxiv2017

Extracting active modules from multilayer PPI network: a continuous optimization approach

Active modules identification has received much attention due to its ability to reveal regulatory and signaling mechanisms of a given cellular response. Most existing algorithms identify active modules by extracting connected nodes with high activity scores from a graph. These algorithms do not consider other topological properties such as community structure, which may correspond to functional units. In this paper, we propose an active module identification algorithm based on a novel objective function, which considers both and network topology and nodes activity. This objective is formulated as a constrained quadratic programming problem, which is convex and can be solved by iterative methods. Furthermore, the framework is extended to the multilayer dynamic PPI networks. Empirical results on the single layer and multilayer PPI networks show the effectiveness of proposed algorithms.\n\nAvailability: The package and code for reproducing all results and figures are available at https://github.com/fairmiracle/ModuleExtraction.

bioinformatics↗

bioRxiv2017

Optimization of Alginante- poly-L-lysine Microencapsules Strength by Box-Behnken Model for CHO Culture in Stirred Tank Bioreactor

Summary statementBox-Behnken model is an efficient method to optimized process conditions of microencapsules strength for long-term cell culture, promotes CHO cells viability and protein production in a stirred tank bioreactor.\n\nABSTRACTCell microencapsulation technology has been proved to be a valuable technology in the fields of large-scale cell culture. It is important to accurately construct the microcapsule membranes with desired properties including a certain thickness suitable for cell growth, and maximum strength for the stability of microencapsules. As single factor experiments are time-consuming to obtain the desired membrane preparation conditions, Box-Behnken model was used to investigate the interactions among reaction conditions, predict the optimized reaction conditions for given purpose, that was membrane with maximum strength and desired thickness for microencapsulated cell culture. Significant values of R2 in this study indicated the model theoretical values are very close to the measured values. Based on the desired membrane thickness, the process of maximum strength was optimized, and the prediction agreement of measured value and model theoretical value was 91.11%. The optimized microencapsules with maximum strength and 15 m membrane thickness promote CHO cells viability and protein production in stirred tank bioreactor. The result shows that Box-Behnken model is an efficient method to optimized process conditions of microencapsules strength for long-term cell culture.

bioengineering↗

bioRxiv2017

Sex differences in gene regulation in the dorsal root ganglion after nerve injury

Pain is a subjective experience derived from complex interactions among biological, environmental, and psychosocial pathways. Sex differences in pain sensitivity and chronic pain prevalence are well established. However, the molecular causes underlying these sex dimorphisms are poorly understood particularly with regard to the role of the peripheral nervous system. Here we sought to identify shared and distinct gene networks functioning in the peripheral nervous systems that may contribute to sex differences of pain after nerve injury. We performed RNA-seq on dorsal root ganglia following chronic constriction injury of the sciatic nerve in male and female rats. Analysis from paired naive and injured tissues showed that 1456 genes were differentially expressed between sexes. Appreciating sex-related gene expression differences and similarities in neuropathic pain models may help to improve the translational relevance to clinical populations and efficacy of clinical trials of this major health issue.

neuroscience↗

bioRxiv2017

Ecophysiology of freshwater Verrucomicrobia inferred from genomes recovered through time-series metagenomics

Microbes are critical in carbon and nutrient cycling in freshwater ecosystems. Members of the Verrucomicrobia are ubiquitous in such systems, yet their roles and ecophysiology are not well understood. In this study, we recovered 19 Verrucomicrobia draft genomes by sequencing 184 time-series metagenomes from a eutrophic lake and a humic bog that differ in carbon source and nutrient availabilities. These genomes span four of the seven previously defined Verrucomicrobia subdivisions, and greatly expand the known genomic diversity of freshwater Verrucomicrobia. Genome analysis revealed their potential role as (poly)saccharide-degraders in freshwater, uncovered interesting genomic features for this life style, and suggested their adaptation to nutrient availabilities in their environments. Between the two lakes, Verrucomicrobia populations differ significantly in glycoside hydrolase gene abundance and functional profiles, reflecting the autochthonous and terrestrially-derived allochthonous carbon sources of the two ecosystems respectively. Interestingly, a number of genomes recovered from the bog contained gene clusters that potentially encode a novel porin-multiheme cytochrome c complex and might be involved in extracellular electron transfer in the anoxic humic-rich environment. Notably, most epilimnion genomes have large numbers of so-called \"Planctomycete-specific\" cytochrome c-containing genes, which exhibited nearly opposite distribution patterns with glycoside hydrolase genes, probably associated with the different environmental oxygen availability and carbohydrate complexity between lakes/layers. Overall, the recovered genomes are a major step towards understanding the role, ecophysiology and distribution of Verrucomicrobia in freshwater.\n\nIMPORTANCEFreshwater Verrucomicrobia are cosmopolitan in lakes and rivers, yet their roles and ecophysiology are not well understood, as cultured freshwater Verrucomicrobia are restricted to one subdivision of this phylum. Here, we greatly expand the known genomic diversity of this freshwater lineage by recovering 19 Verrucomicrobia draft genomes from 184 metagenomes collected from a eutrophic lake and a humic bog across multiple years. Most of these genomes represent first freshwater representatives of several Verrucomicrobia subdivisions. Genomic analysis revealed Verrucomicrobia as potential (poly)saccharide-degraders, and suggested their adaptation to carbon source of different origins in the two contrasting ecosystems. We identified putative extracellular electron transfer genes and so-called \"Planctomycete-specific\" cytochrome c-containing genes, and found their distinct distribution patterns between the lakes/layers. Overall, our analysis greatly advances the understanding of the function, ecophysiology and distribution of freshwater Verrucomicrobia, while highlighting their potential role in freshwater carbon cycling.

microbiology↗

bioRxiv2016

Helical reconstruction in RELION

We describe a new implementation for the reconstruction of helical assemblies in the empirical Bayesian framework of RELION. Our approach calculates optimal linear filters for the 3D reconstruction by embedding helical symmetry operators in Fourier-space, and deals with deviations from perfect helical symmetry through Gaussian-shaped priors on the orientations of individual segments. By incorporating our approach into the standard pipeline for single-particle analysis in RELION, our implementation aims to be easily accessible for non-experienced users. Although our implementation does not solve the problem that grossly incorrect structures can be obtained when the wrong helical symmetry is imposed, we show for four different test cases that it is capable of reconstructing structures to near-atomic resolution.\n\nAbbreviations

molecular biology↗