Biology subjects

Guo, M.

Publications and source records attributed to Guo, M..

160 records · Page 9Linked to original sources

bioRxiv2019

Nanomorphological and mechanical reconstruction of mesenchymal stem cells during early apoptosis detected by atomic force microscopy

Stem cell apoptosis exists widely in embryonic development, tissue regeneration, repair, aging and pathophysiology of disease. The molecular mechanism of stem cell apoptosis has been extensively investigated. However, alterations in biomechanics and nanomorphology have rarely been studied. Therefore, an apoptosis model was established for bone marrow mesenchymal stem cells (BMSCs) and the reconstruction of the mechanical properties and nanomorphology of the cells were investigated in detail. Atomic force microscopy (AFM), scanning electron microscopy (SEM), laser scanning confocal microscopy (LSCM), flow cytometry and Cell Counting Kit-8 analysis were applied to assess the cellular elasticity modulus, geometry, nanomorphology, cell surface ultrastructure, biological viability and early apoptotic signal (phosphatidylserine, PS). The results indicated that the cellular elastic modulus and volume significantly decreased, whereas the cell surface roughness obviously increased during the first 3 h of cytochalasin B (CB) treatment. Moreover, these alterations preceded the exposure of biological apoptotic signal PS. These findings suggested that cellular mechanical damage is connected with the apoptosis of BMSCs, and the alterations in mechanics and nanomorphology may be a sensitive index to detect alterations in cell viability during apoptosis. The results contribute to a further understanding of the apoptosis from the perspective of cell mechanics.

cell biology↗

bioRxiv2019

Automated Lifespan Determination Across Caenorhabditis Strains and Species Reveals Assay-Specific Effects of Chemical Interventions

The goal of the Caenorhabditis Intervention Testing Program is to identify robust and reproducible pro-longevity interventions that are efficacious across genetically diverse cohorts in the Caenorhabditis genus. The project design features multiple experimental replicates collected by three different laboratories. Our initial effort employed fully manual survival assays. With an interest in increasing throughput, we explored automation with flatbed scanner-based Automated Lifespan Machines (ALMs). We used ALMs to measure survivorship of 22 Caenorhabditis strains spanning three species. Additionally, we tested five chemicals that we previously found extended lifespan in manual assays. Overall, we found similar sources of variation among trials for the ALM and our previous manual assays, verifying reproducibility of outcome. Survival assessment was generally consistent between the manual and the ALM assays, although we did observe radically contrasting results for certain compound interventions. We found that particular lifespan outcome differences could be attributed to protocol elements such as enhanced light exposure of specific compounds in the ALM, underscoring that differences in technical details can influence outcomes and therefore interpretation. Overall, we demonstrate that the ALMs effectively reproduce a large, conventionally scored dataset from a diverse test set, independently validating ALMs as a robust and reproducible approach towards aging-intervention screening.

physiology↗

bioRxiv2019

A systematic survey of PRMT interactomes reveals the key roles of arginine methylation in the global control of RNA splicing and translation

Thousands of proteins undergo arginine methylation, a widespread post-translational modification catalyzed by various protein arginine methyltransferases (PRMTs). However, a full picture of the catalytic network for each PRMT is lacking and the global understanding of their biological roles remains limited. Here we systematically identified interacting proteins for all human PRMTs and demonstrated that they are functionally important for mRNA splicing and translation. We showed that the interactomes of human PRMTs are significantly overlapped with the known methylarginine containing proteins, and different PRMTs are functionally complementary with a high degree of overlap in their substrates and high similarities between their putative methylation motifs. Importantly, arginine methylation is significantly enriched in RNA binding proteins involved in regulating RNA splicing and translation, and inhibition of PRMTs leads to global alteration of alternative splicing and suppression of translation. In particular, ribosomal proteins are pervasively modified with methylarginine, and mutations on their methylation sites suppress ribosome assembly, translation, and eventually cell growth. Collectively, our study provides a novel global view of different PRMT networks and uncovers critical functions of arginine methylation in the regulation of mRNA splicing and translation.

molecular biology↗

bioRxiv2019

Pathway and network embedding methods for prioritizing psychiatric drugs

One in five Americans experience mental illness, and roughly 75% of psychiatric prescriptions do not successfully treat the patients condition. Extensive evidence implicates genetic factors and signaling disruption in the pathophysiology of these diseases. Changes in transcription often underlie this molecular pathway dysregulation; individual patient transcriptional data can improve the efficacy of diagnosis and treatment. Recent large-scale genomic studies have uncovered shared genetic modules across multiple psychiatric disorders--providing an opportunity for an integrated multi-disease approach for diagnosis. Moreover, network-based models informed by gene expression can represent pathological biological mechanisms and suggest new genes for diagnosis and treatment. Here, we use patient gene expression data from multiple studies to classify psychiatric diseases, integrate knowledge from expert-curated databases and publicly available experimental data to create augmented disease-specific gene sets, and use these to recommend disease-relevant drugs. From Gene Expression Omnibus, we extract expression data from 145 cases of schizophrenia, 82 cases of bipolar disorder, 190 cases of major depressive disorder, and 307 shared controls. We use pathway-based approaches to predict psychiatric disease diagnosis with a random forest model (78% accuracy) and derive important features to augment available drug and disease signatures. Using protein-protein-interaction networks and embedding-based methods, we build a pipeline to prioritize treatments for psychiatric diseases that achieves a 3.4-fold improvement over a background model. Thus, we demonstrate that gene-expression-derived pathway features can diagnose psychiatric diseases and that molecular insights derived from this classification task can inform treatment prioritization for psychiatric diseases.

bioinformatics↗

bioRxiv2019

A Literature-Based Knowledge Graph Embedding Method for Identifying Drug Repurposing Opportunities in Rare Diseases

One in ten people are affected by rare diseases, and three out of ten children with rare diseases will not live past age five. However, the small market size of individual rare diseases, combined with the time and capital requirements of pharmaceutical R&D, have hindered the development of new drugs for these cases. A promising alternative is drug repurposing, whereby existing FDA-approved drugs might be used to treat diseases different from their original indications. In order to generate drug repurposing hypotheses in a systematic and comprehensive fashion, it is essential to integrate information from across the literature of pharmacology, genetics, and pathology. To this end, we leverage a newly developed knowledge graph, the Global Network of Biomedical Relationships (GNBR). GNBR is a large, heterogeneous knowledge graph comprising drug, disease, and gene (or protein) entities linked by a small set of semantic themes derived from the abstracts of biomedical literature. We apply a knowledge graph embedding method that explicitly models the uncertainty associated with literature-derived relationships and uses link prediction to generate drug repurposing hypotheses. This approach achieves high performance on a gold-standard test set of known drug indications (AUROC = 0.89) and is capable of generating novel repurposing hypotheses, which we independently validate using external literature sources and protein interaction networks. Finally, we demonstrate the ability of our model to produce explanations of its predictions.

bioinformatics↗

bioRxiv2019

Accelerating iterative deconvolution and multiview fusion by orders of magnitude

We describe theoretical and practical advances in algorithm and software design, resulting in ten to several thousand-fold faster deconvolution and multiview fusion than previous methods. First, we adapt methods from medical imaging, showing that an unmatched back projector accelerates Richardson-Lucy deconvolution by at least 10-fold, in most cases requiring only a single iteration. Second, we show that improvements in 3D image-based registration with GPU processing result in speedups of 10-100-fold over CPU processing. Third, we show that deep learning can provide further accelerations, particularly for deconvolution with a spatially varying point spread function. We illustrate the power of our methods from the subcellular to millimeter spatial scale, on diverse samples including single cells, nematode and zebrafish embryos, and cleared mouse tissue. Finally, we show that our methods facilitate the use of new microscopes that improve spatial resolution, including dual-view cleared tissue light-sheet microscopy and reflective lattice light-sheet microscopy.

bioengineering↗

bioRxiv2019

Simplified Molecular Classification of Lung Adenocarcinomas Based on EGFR, KRAS, and TP53 Mutations

IntroductionGene expression profiling has consistently identified three molecular subtypes of lung adenocarcinoma that have prognostic implications. To facilitate stratification of patients with this disease into similar molecular subtypes, we developed and validated a simple, mutually exclusive classification.\n\nMethodsMutational status of EGFR, KRAS, and TP53 was used to define six mutually exclusive molecular subtypes. A development cohort of 283 cytology specimens of lung adenocarcinoma was used to evaluate the associations between the proposed classification and clinicopathologic variables including demographic characteristics, smoking history, fluorescence in situ hybridization and molecular results. For validation and prognostic assessment, 63 of the 283 cytology specimens with available survival data were combined with a separate cohort of 428 surgical pathology specimens of lung adenocarcinoma.\n\nResultsThe proposed classification yielded significant associations between these molecular subtypes and clinical and prognostic features. We found better overall survival in patients who underwent surgery and had tumors enriched for EGFR mutations. Worse overall survival was associated with older age, stage IV disease, and tumors with comutations in KRAS and TP53. Interestingly, neither chemotherapy nor radiation therapy showed benefit to overall survival.\n\nConclusionsThe mutational status of EGFR, KRAS, and TP53 can be used to easily classify lung adenocarcinoma patients into six subtypes that show a relationship with prognosis, especially in patients who underwent surgery, and these subtypes are similar to classifications based on more complex genomic methods reported previously.

cancer biology↗

bioRxiv2018

Noninvasive prenatal detection of fetal trisomy and single gene disease by shotgun sequencing of placenta originated exosome DNA: a proof-of-concept validation

BackgroundDuring human pregnancy, Placental trophectoderm cells can release exosomes into maternal circulation. Trophoblast cells also give rise to cell-free DNA (cfDNA) and has been used for noninvasive prenatal screening for chromosomal aneuploidy. We intended to prove the existence of exosomal DNA (exoDNA) in the exosomes of maternal blood and compared exoDNA with plasma cfDNA in terms of genome distribution, fragment length, and the possibility of detecting genetic diseases.\n\nMethodsMaternal blood from 20 euploid pregnancies, 9 T21 pregnancies, 3 T18 pregnancies, 1 T13 pregnancy and 2 pregnancies with FGFR3 mutations were obtained. Exosomes enriched from maternal plasma were confirmed by transmission electronic microscopy (TEM), western blotting and flow cytometry. ExoDNA was extracted and its fetal origin was confirmed by realtime fluorescence quantitative PCR(Q-PCR). Besides, exoDNA content was uncovered by Q-PCR. To characterize exoDNA and compare with cfDNA, pair-end whole genome sequencing was performed. Lastly, the fetal risk of genetic diseases was analyzed using the exoDNA sequencing data.\n\nResultsExoDNA span on all 23 pairs of chromosomes and mitochondria, sharing a similar distribution pattern and higher GC content comparing with cfDNA. ExoDNA showed shorter fragments yet lower fetal fraction than cfDNA. ExoDNA could be used to determine fetal gender correctly, and all trisomies as well as de novo FGFR3 mutations.\n\nConclusionsWe proved that fetal exoDNA could be identified in the exosomes extracted from maternal plasma. ExoDNA shared some similar features to cfDNA and could potentially be used to detect genetic diseases in fetus.

genetics↗

bioRxiv2018

A novel olfactometer for efficient and flexible odorant delivery

Understanding how sensory space maps to neural activity in the olfactory system requires efficiently and flexibly delivering numerous odorants within single experimental preparations. Such delivery is difficult with current olfactometer designs, which typically include limited numbers of stimulus channels and are subject to inter-trial and inter-channel contamination of odorants. Here, we present a novel olfactometer design that is easily constructed, modular, and capable of delivering an unlimited number of odorants with temporal precision and no detectable inter-trial or inter-channel contamination. The olfactometer further allows for flexible generation of odorant mixtures and flexible timing of odorant sequences. Odorant delivery from the olfactometer is turbulent but reliable from trial-to-trial, supporting operant conditioning of mice in an odorant discrimination task and permitting odorants and concentrations to be mapped to neural activity with a level of precision equivalent to that obtained with a flow dilution olfactometer. This novel design thus provides several unique advantages for interrogating olfactory perception and for mapping sensory space to neural activity in the olfactory system.

neuroscience↗

bioRxiv2018

High stretchability, strength and toughness of living cells enabled by hyperelastic vimentin network

In many normal and abnormal physiological processes, including cellular migration during normal development and invasion in cancer metastasis, cells are required to withstand severe deformations. The structural integrity of eukaryotic cells under small deformations has been known to depend on the cytoskeleton including actin filaments (F-actin), microtubules and intermediate filaments (IFs). However, it remains unclear how cells resist severe deformations since both F-actin and microtubules fluidize or disassemble under moderate strains. Here, we demonstrate that vimentin intermediate filaments (VIFs), a marker of mesenchymal cells, dominate cytoplasmic mechanics at large deformations. Our results show that cytoskeletal VIFs form a stretchable, hyperelastic network. This network works synergistically with other dissipative cytoplasmic components, substantially enhancing the strength, stretchability, resilience and toughness of the living cytoplasm.

biophysics↗

bioRxiv2018

A membrane-depolarising toxin substrate of the Staphylococcus aureus Type VII protein secretion system targets eukaryotes and bacteria

The type VII protein secretion system (T7SS) is conserved across Staphylococcus aureus strains and plays important roles in virulence and interbacterial competition. To date only one T7SS substrate protein, encoded in a subset of S. aureus genomes, has been functionally characterized. Here, using an unbiased proteomic approach, we identify TspA as a further T7SS substrate. TspA is encoded distantly from the T7SS gene cluster and is found across all S. aureus strains as well as in Listeria and Enterococci. Heterologous expression of TspA from S. aureus strain RN6390 indicates its C-terminal domain is toxic when targeted to the Escherichia coli periplasm and that it depolarizes the cytoplasmic membrane. The membrane depolarizing activity is alleviated by co-production of the membrane-bound TsaI immunity protein, which is encoded adjacent to tspA on the S. aureus chromosome. Using a zebrafish hindbrain ventricle infection model, we demonstrate that the T7SS of strain RN6390 promotes bacterial replication in vivo, and deletion of tspA leads to increased bacterial clearance. The toxin domain of TspA is highly polymorphic and S. aureus strains encode multiple tsaI homologues at the tspA locus, suggestive of additional roles in intra-species competition. In agreement, we demonstrate TspA-dependent growth inhibition of RN6390 by strain COL in the zebrafish infection model that is alleviated by the presence of TsaI homologues. Significance statementStaphylococcus aureus, a human commensal organism that asymptomatically colonizes the nares, is capable of causing serious disease following breach of the mucosal barrier. S. aureus strains encode a Type VII secretion system (T7SS) that is required for virulence in mouse infection models, and some strains also secrete a nuclease toxin by this route that has antibacterial activity. Here we identify TspA, widely found in Staphylococci and other pathogenic bacteria, as a T7 substrate. We show that TspA has membrane-depolarizing activity and that S. aureus uses TspA to inhibit the growth of a bacterial competitor in vivo.

microbiology↗

bioRxiv2018

Triggering MSR1 promotes JNK-mediated inflammation in IL-4 activated macrophages

Alternatively activated M2 macrophages play an important role in maintenance of tissue homeostasis by scavenging dead cells, cell debris and lipoprotein aggregates via phagocytosis. Using proteomics, we investigated how alternative activation, driven by IL-4, modulated the phagosomal proteome to control macrophage function. Our data indicate that alternative activation enhances homeostatic functions such as proteolysis, lipolysis and nutrient transport. Intriguingly, we identified the enhanced recruitment of the TAK1/MKK7/JNK signalling complex to phagosomes of IL-4 activated macrophages. The recruitment of this signalling complex was mediated through K63-polyubiquitylation of the macrophage scavenger receptor 1 (MSR1). Triggering of MSR1 in IL-4 activated macrophages leads to enhanced JNK activation, thereby promoting a phenotypic switch from an anti-inflammatory to a pro-inflammatory state, which was abolished upon MSR1 deletion or JNK inhibition. Moreover, MSR1 K63-polyubiquitylation correlated with the activation of JNK signalling in ovarian cancer tissue from human patients, suggesting that it may be relevant for macrophage phenotypic shift in vivo. Altogether, we identified that MSR1 signals through JNK via K63-polyubiquitylation and provide evidence for the receptors involvement in macrophage polarization.

immunology↗

bioRxiv2018

Sequencing of Panax notoginseng genome reveals genes involved in disease resistance and ginsenoside biosynthesis

Panax notoginseng is a traditional Chinese herb with high medicinal and economic value. There has been considerable research on the pharmacological activities of ginsenosides contained in Panax spp.; however, very little is known about the ginsenoside biosynthetic pathway. We reported the first de novo genome of 2.36 Gb of sequences from P. notoginseng with 35,451 protein-encoding genes. Compared to other plants, we found notable gene family contraction of disease-resistance genes in P. notoginseng, but notable expansion for several ATP-binding cassette (ABC) transporter subfamilies, such as the Gpdr subfamily, indicating that ABCs might be an additional mechanism for the plant to cope with biotic stress. Combining eight transcriptomes of roots and aerial parts, we identified several key genes, their transcription factor binding sites and all their family members involved in the synthesis pathway of ginsenosides in P. notoginseng, including dammarenediol synthase, CYP716 and UGT71. The complete genome analysis of P. notoginseng, the first in genus Panax, will serve as an important reference sequence for improving breeding and cultivation of this important nutraceutical and medicinal but vulnerable plant species.

genomics↗

bioRxiv2017

Single-shot super-resolution total internal reflection fluorescence microscopy

We demonstrate a simple method for combining instant structured illumination microscopy (SIM) with total internal reflection fluorescence microscopy (TIRF), doubling the spatial resolution of TIRF (down to 115 +/-13 nm) and enabling imaging frame rates up to 100 Hz over hundreds of time points. We apply instant TIRF-SIM to multiple live samples, achieving rapid, high contrast super-resolution imaging in close proximity to the coverslip surface.

bioengineering↗

bioRxiv2017

Reflective imaging improves resolution, speed, andcollection efficiency in light sheet microscopy

Light-sheet fluorescence microscopy (LSFM) enables high-speed, high-resolution, gentle imaging of live biological specimens over extended periods. Here we describe a technique that improves the spatiotemporal resolution and collection efficiency of LSFM without modifying the underlying microscope. By imaging samples on reflective coverslips, we enable simultaneous collection of multiple views, obtaining 4 complementary views in 250 ms, half the period it would otherwise take to collect only two views in symmetric dual-view selective plane illumination microscopy (diSPIM). We also report a modified deconvolution algorithm that removes the associated epifluorescence contamination and fuses all views for resolution recovery. Furthermore, we enhance spatial resolution (to < 300 nm in all three dimensions) by applying our method to a new asymmetric diSPIM, permitting simultaneous acquisition of two high-resolution views otherwise difficult to obtain due to steric constraints at high numerical aperture (NA). We demonstrate the broad applicability of our method in a variety of samples of moderate (< 50 m) thickness, studying mitochondrial, membrane, Golgi, and microtubule dynamics in single cells and calcium activity in nematode embryos.

bioengineering↗

bioRxiv2017

RETA: An R Package For Whole Exome And Targeted Region Sequencing Data Analysis

Whole exome and targeted sequencing have been playing a major role in diagnoses of Mendelian diseases, but analysis of these data involves using many complicated tools and comprehensive understanding of the analysis results is difficult.Here, we report RETA, an R package to provide a one-stop analysis of these data and a comprehensive, interactive and easy-to-understand report with many advanced visualization features. It facilitates clinicians and scientists alike to better analyze and interpret this type of sequencing data for disease diagnoses.\n\nAvailability and implementationhttps://github.com/reta-s/reta/releases\n\nContactyangwl@hku.hk

genetics↗