Biology subjects

Lee, M.

Publications and source records attributed to Lee, M..

15 recordsLinked to original sources

bioRxiv2018

Deep sequencing of circulating exosomal microRNA allows non-invasive glioblastoma diagnosis

Exosomes are nano-sized extracellular vesicles released by many cells that contain molecules characteristic of their cell-of-origin, including microRNA. Exosomes released by glioblastoma cross the blood-brain-barrier into the peripheral circulation, and carry molecular cargo distinct to that of free-circulating miRNA. In this pilot study, serum exosomal-microRNAs were isolated from glioblastoma (n=12) patients and analyzed using unbiased deep sequencing. Results were compared to sera from age- and gender-matched healthy controls, and to grades II-III (n=10) glioma patients. Significant differentially expressed microRNAs were identified, and the predictive power of individual and subsets of microRNAs were tested using univariate and multivariate analyses. Additional sera from glioblastoma patients (n=4) and independent sets of healthy (n=9) and non-glioma (n=10) controls were used to further test the specificity and predictive power of this unique exosomal-microRNA signature. Twenty-six microRNAs were differentially expressed in serum exosomes from glioblastoma patients relative to healthy controls. Random forest modeling and data partitioning selected seven miRNAs (miR-182-5p, miR-328-3p, miR-339-5p, miR-340-5p, miR-485-3p, miR-486-5p and miR-543) as the most stable for classifying glioblastoma. Strikingly, within this model, six iterations of these miRNA classifiers could distinguish glioblastoma patients from controls with perfect accuracy. The seven-miRNA panel was able to correctly classify all specimens in validation cohorts (n=23). Also identified were 23 dysregulated miRNAs in IDHMUT gliomas, a partially overlapping yet distinct signature of lower grade glioma. Serum exosomal-miRNA signatures can accurately diagnose glioblastoma preoperatively. miRNA signatures identified are distinct from previously reported free-circulating miRNA studies in GBM patients, and appear to be superior.

pathology↗

bioRxiv2018

An expanded toolkit for gene tagging based on MiMIC and scarless CRISPR tagging in Drosophila

We generated new genetic tools to efficiently tag genes in Drosophila. Double Header (DH) utilizes intronic MiMIC/CRIMIC insertions to generate artificial exons for GFP mediated protein trapping or T2A-GAL4 gene trapping in vivo based on CRE recombinase to avoid embryo injections. DH significantly increases integration efficiency compared to previous strategies and faithfully reports the expression pattern of genes and proteins. The second technique targets genes lacking coding introns using a two-step cassette exchange. First, we replace the endogenous gene with an excisable compact dominant marker using CRISPR making a null allele. Second, the insertion is replaced with a protein::tag cassette.\n\nThis sequential manipulation allows the generation of numerous tagged alleles or insertion of other DNA fragments that facilitates multiple downstream applications. Both techniques allow precise gene manipulation and facilitate detection of gene expression, protein localization and assessment of protein function, as well as numerous other applications.

genetics↗

bioRxiv2018

Single cell transcriptome profiling of mouse and hESC-derived pancreatic progenitors

Human embryonic stem cells (hESCs) are a potential unlimited source of insulin-producing {beta}-cells for diabetes treatment. A greater understanding of how {beta}-cells form during embryonic development will improve current hESC differentiation protocols. As {beta}-cells are formed from NEUROG3-expressing endocrine progenitors, this study focused on characterizing the single-cell transcriptomes of mouse and hESC-derived endocrine progenitors. To do this, 7,223 E15.5 and 6,852 E18.5 single cells were isolated from Neurog3-Cre; Rosa26mT/mG embryos, allowing for enrichment of endocrine progenitors (yellow; tdTomato + EGFP) and endocrine cells (green; EGFP). From a NEUROG3-2A-eGFP CyT49 hESC reporter line (N5-5), 4,497 hESC-derived endocrine progenitor cells were sequenced. Differential expression analysis reveals enrichment of markers that are consistent with progenitor, endocrine, or novel cell-state populations. This study characterizes the single-cell transcriptomes of mouse and hESC-derived endocrine progenitors and serves as a resource (https://lynnlab.shinyapps.io/embryonic_pancreas/) for improving the formation of functional {beta}-like cells from hESCs.

developmental biology↗

bioRxiv2018

Constructing and visualizing cancer genomic maps in 3D spatial context by phenotype-based high-throughput laser-aided isolation and sequencing (PHLI-seq)

A spatially resolved analysis of the heterogeneous cancer genome, in which the data are connected to the three-dimensional space of a tumour, is crucial to understand cancer biology and the clinical impact of cancer heterogeneity on patients. However, despite recent progress in spatially resolved transcriptomics, spatial mapping of genomic data in a high-throughput and high-resolution manner has been challenging due to current technical limitations. Here, we describe a novel approach, phenotype-based high-throughput laser-aided isolation and sequencing (PHLI-seq), which enables high-throughput isolation of a single-cell or a small number of cells and their genome-wide sequence analysis to construct genomic maps within cancer tissue in relation to the phenotypes of the cells. By applying PHLI-seq, we reveal the heterogeneity of breast cancer tissues at a high resolution and map the genomic landscape of the cells to their corresponding spatial locations and phenotypes in the tumour mass. Additionally, with different staining modalities, the genotypes of the cells can be connected to corresponding phenotypic information of the tissue. Together with the spatially resolved genomic analysis, we can infer the histories of heterogeneous cancer cells in two or three dimensions, providing significant insight into cancer biology and precision medicine.

genomics↗

bioRxiv2018

A synthetic, three-dimensional bone marrow hydrogel

Three-dimensional (3D) synthetic hydrogels have recently emerged as desirable in vitro cell culture platforms capable of representing the extracellular geometry, elasticity, and water content of tissue in a tunable fashion. However, they are critically limited in their biological functionality. Hydrogels are typically decorated with a scant 1-3 peptide moieties to direct cell behavior, which vastly underrepresents the proteins found in the extracellular matrix (ECM) of real tissues. Further, peptides chosen are ubiquitous in ECM, and are not derived from specific proteins. We developed an approach to incorporate the protein complexity of specific tissues into the design of biomaterials, and created a hydrogel with the elasticity of marrow, and 20 marrow-specific cell-instructive peptides. Compared to generic PEG hydrogels, our marrow-inspired hydrogel improves stem cell differentiation and proliferation. We propose this tissue-centric approach as the next generation of 3D hydrogel design for applications in tissue engineering.

bioengineering↗

bioRxiv2017

Label-free non-invasive quantitative measurement of lipid contents in individual microalgal cells using refractive index tomography

Microalgae are promising candidates for biofuel production due to their high lipid content. To facilitate utilization of the microalgae for biofuel, rapid quantification of the lipid contents in microalgae is necessary. However, conventional methods based on the chemical extraction of lipids require a time-consuming destructive extraction process. Here, we demonstrate label-free, non-invasive, rapid quantification of the lipid contents in individual micro-algal cells measuring the three-dimensional refractive index tomograms. We measure three-dimensional refractive index distributions within Nannochloropsis oculata cells and find that lipid droplets are identifiable in tomograms by their high refractive index. In addition, we alter N. oculata under nitrogen deficiency by measuring the volume, lipid weight, and dry cell weight of individual cells. Characterization of individual cells allows correlative analysis between the lipid content and size of individual cells.

bioengineering↗

bioRxiv2017

A global comparison of the nutritive values of forage plants grown in contrasting environments

Forage plants are valuable because they maintain wild and domesticated herbivores, and sustain the delivery of meat, milk and other commodities. Forage plants contain different quantities of fibre, lignin, minerals and protein, and vary in the proportion of their tissue that can be digested by herbivores. These nutritive components are important determinants of consumer growth rates, reproductive success and behaviour. A dataset was compiled to quantify variation in forage plant nutritive values within- and between-plant species, and to assess variation between plant functional groups and bioclimatic zones. 1,255 geo-located records containing 3,774 measurements of nutritive values for 136 forage plant species grown in 30 countries were obtained from published articles. Spatial variability in forage nutritive values indicated that climate modified plant nutritive values. Forage plants grown in arid and equatorial regions generally contained less digestible material than those grown in temperate and tundra regions; containing more fibre and lignin, and less protein. These patterns may reveal why herbivore body sizes, digestion and migration strategies are different in warmer and drier regions. This dataset also revealed the capacity for variation in the nutrition provided by forage plants. The proportion of the plant tissue that was digestible ranged between species from 2-91%. The amount of fibre contained within plant material ranged by 23-90%, protein by 2-36%, lignin by 1-21% and minerals by 2-22%. Water contents also varied substantially; ranging from 3-89% of standing biomass. On average, grasses and tree foliage contained the most fibre, whilst herbaceous legumes contained the most protein and tree foliage contained the most lignin. However, there were individual species within each functional group that were highly nutritious. This dataset may be used to identify forage plant species with useful traits which can be cultivated to enhance livestock productivity and inform wild herbivore conservation strategies.

plant biology↗

bioRxiv2017

Classification and characterisation of brain network changes in chronic back pain: a multicenter study.

Chronic pain is a common and often disabling condition, and is thought to involve a combination of peripheral and central neurobiological factors. However, the extent and nature of changes in the brain is poorly understood. Here, we investigated brain network architecture using resting state fMRI data collected from chronic back pain patients in UK and Japan (41 patients, 56 controls). Using a machine learning approach (support vector machine), we found that brain network patterns reliably classified chronic pain patients in a third, independent open data set with an accuracy of 63%, whilst 68% was attained in cross validation of all data. We then developed a deep learning classifier using a conditional variational autoencoder, which also yield yielded 63% generalisation and 68% cross-validation accuracy. Given the existence of reliable network changes, we next studied the graph topology of the network, and found consistent evidence of hub disruption based on clustering and betweenness centrality of brain nodes in pain patients. To examine this in more detail, we developed a multislice modularity algorithm to identify a consensus pattern of modular reorganisation of brain nodes across the entire data set. This revealed evidence of significant changes in the modular identity of several brain regions, most notably including broad regions of bilateral sensorimotor cortex, subregions of which also contributed to classifier performance. These results provide evidence of consistent and characteristic brain network changes in chronic pain, and highlight extensive reorganisaton of the network architecture of sensorimotor cortex.

neuroscience↗

bioRxiv2017

The Control of Tonic Pain by Active Relief Learning

Tonic pain after injury characterises a behavioural state that prioritises recovery. Although generally suppressing cognition and attention, tonic pain needs to allow effective relief learning so that the cause of the pain can be reduced if possible. Here, we describe a central learning circuit that supports learning of relief and concurrently suppresses the level of ongoing pain. We used computational modelling of behavioural, physiological and neuroimaging data in two experiments in which subjects learned to terminate tonic pain in static and dynamic escape-learning paradigms. In both studies, we show that active relief-seeking involves a reinforcement learning process manifest by error signals observed in the dorsal putamen. Critically, this system also uses an uncertainty ( associability) signal detected in pregenual anterior cingulate cortex that both controls the relief learning rate, and endogenously and parametrically modulates the level of tonic pain. The results define a self-organising learning circuit that allows reduction of ongoing pain when learning about potential relief.

neuroscience↗

bioRxiv2017

Junction-based lamellipodia drive endothelial cell rearrangements in vivo via a VE-cadherin/F-actin based oscillatory ratchet mechanism

Angiogenesis and vascular remodeling are driven by a wide range of endothelial cell behaviors, such as cell divisions, cell movements, cell shape and polarity changes. To decipher the cellular and molecular mechanism of cell movements, we have analyzed the dynamics of different junctional components during blood vessel anastomosis in vivo. We show that endothelial cell movements are associated with oscillating lamellipodia-like structures, which are orientated in the direction of these movements. These structures emerge from endothelial cell junctions and we thus call them junction-based lamellipodia (JBL). High-resolution time-lapse imaging shows that JBL are formed by F-actin based protrusions at the front end of moving cells. These protrusions also contain diffusely distributed VE-cadherin, whereas the junctional protein ZO-1 (Zona occludens 1) remains at the junction. Subsequently, a new junction is formed at the front of the JBL and the proximal junction is pulled towards the newly established distal junction. JBL function is highly dependent on F-actin dynamics. Inhibition of F-actin polymerization prevents JBL formation, whereas Rac-1 inhibition interferes with JBL oscillations. Both interventions disrupt endothelial junction formation and cell elongation. To examine the role of VE-cadherin (encoded by cdh5 gene) in this process, we generated a targeted mutation in VE-cadherin gene (cdh5ubs25), which prevents VE-cad/F-actin interaction. Although homozygous ve-cadherin mutants form JBL, these JBL are less dynamic and do not promote endothelial cell elongation. Taken together, our observations suggest a novel oscillating ratchet-like mechanism, which is used by endothelial cells to move along or over each other and thus provides the physical means for cell rearrangements.

developmental biology↗

bioRxiv2017

Measurements of three-dimensional refractive index tomography and membrane deformability of live erythrocytes from Pelophylax nigromaculatus

Unlike mammalian erythrocytes, amphibian erythrocytes have distinct morphological features including large cell sizes and the presence of nuclei. The sizes of the cytoplasm and nuclei of erythrocytes vary significantly over different species, their environments, or pathophysiology, which makes hematological studies important for investigating amphibian species. Here, we present a label-free three-dimensional optical quantification of individual amphibian erythrocytes from frogs Pelophylax nigromaculatus (Rana nigromaculata). Using optical diffraction tomography, we measured three-dimensional refractive index (RI) tomograms of the cells, which clearly distinguished the cytoplasm and nuclei inside the erythrocytes. From the measured RI tomograms, we extracted the relevant biochemical parameters of the cells, including hemoglobin contents and hemoglobin concentrations. Furthermore, we measured dynamic membrane fluctuations and investigated the mechanical properties of the cell membrane. From the statistical and correlative analysis of these retrieved parameters, we investigated interspecific differences between frogs and previously studied mammals.

biophysics↗

bioRxiv2017

Stromal Reactivity Differentially Drives Tumor Cell Evolution and Prostate Cancer Progression

We implemented a hybrid multiscale model of carcinogenesis that merges data from biology and pathology on the microenvironmental regulation of prostate cancer (PCa) cell behavior. It recapitulates the biology of stromal influence in prostate cancer progression. Our data indicate that the interactions between the tumor cells and reactive stroma shape the evolutionary dynamics of PCa cells and explain overall tumor aggressiveness. We show that the degree of stromal reactivity, when coupled with the current clinical biomarkers, significantly improves PCa prognostication, both for death and recurrence, that may alter treatment decisions. We also show that stromal reactivity correlates directly with tumor growth but inversely modulates tumor evolution. This suggests that the aggressive stromal independent PCa may be an inevitable evolutionary result of poor stromal reactivity. It also suggests that purely tumor centric metrics of aggressiveness may be misleading in terms on clinical outcome.

cancer biology↗

bioRxiv2017

Heterogeneity of normal human breast stem and progenitor cells as revealed by transcriptional profiling

During development and pregnancy, the human mammary gland undergoes extensive remodeling in processes driven by populations of stem and progenitor cells. We recently reported that breast cancers are also hierarchically organized and driven by distinct populations of cancer stem cells characterized as CD44+CD24low/- or by expression of Aldehyde dehydrogenase (ALDH). These sets of markers identify largely non-overlapping mesenchymal and epithelial populations, each of which is capable of tumor initiation when transplanted into immunosuppressed mice. Less is known about these two populations, individually or their overlap, in the normal human mammary gland. The goal of this study was to understand the biology of the ALDH+ and CD44+CD24- populations in the normal human breast, using flow cytometry based sorting paired with functional ex vivo analyses, RNA-sequencing, and single cell RNA expression profiling. ALDH+ cells and ALDH-CD44+CD24- cells, generally, have epithelial-like and mesenchymal-like characteristics, respectively. Despite this, there are substantial similarities in the biological pathways activated in both populations when compared to differentiated cells. Additionally, we found a substantial proportion of cells that simultaneously express ALDH+ and CD44+CD24- whose abundance varies between individuals. At the single cell level, these cells have the greatest mammosphere forming capacity and express high levels of stemness and EMT-associated genes including ID1, SOX2, TWIST1, and ZEB2. Through unbiased analysis of individual ALDH+ cells, we find cells with either epithelial or mesenchymal expression phenotypes. We also identify a subpopulation of cells with a hybrid epithelial/mesenchymal expression phenotype that overexpress genes associated with aggressive triple negative breast cancers. These results highlight the utility of single cell analyses to characterize tissue heterogeneity, even in marker enriched cell populations, and further identifies the genes and pathways that define this heterogeneity.

developmental biology↗

bioRxiv2017

Refractive index as an intrinsic imaging contrast for 3-D label-free live cell imaging

Live cell imaging provides essential information in the investigation of cell biology and related pathophysiology. Refractive index (RI) can serve as intrinsic optical imaging contrast for 3-D label-free and quantitative live cell imaging, and provide invaluable information to understand various dynamics of cells and tissues for the study of numerous fields. Recently significant advances have been made in imaging methods and analysis approaches utilizing RI, which are now being transferred to biological and medical research fields, providing novel approaches to investigate the pathophysiology of cells. To provide insight how RI can be used as an imaging contrast for imaging of biological specimens, here we provide the basic principle of RI-based imaging techniques and summarize recent progress on applications, ranging from microbiology, hematology, infectious diseases, hematology, and histopathology.

cell biology↗

bioRxiv2016

Transition into inflammatory cancer-associated adipocytes in breast cancer microenvironment requires microRNA regulatory mechanism

ABSTRACTSO_ST_ABSIntroductionC_ST_ABSThe role of adipocytes in cancer microenvironment has gained focus during the recent years. However, the characteristics of the cancer-associated adipocytes (CAA) in human breast cancer tissues and the underlying regulatory mechanism are not clearly understood.\n\nMethodWe reviewed pathology specimens of breast cancer patients to understand the morphologic characteristics of CAA, and profiled the mRNA and miRNA expression of CAA by using indirect co-culture system in vitro.\n\nResultsThe CAAs in human breast cancers showed heterogeneous topographic relationship with breast cancer cells within the breast microenvironment. The CAAs exhibited the characteristics of de-differentiation determined by their microscopic appearance and the expression levels of adipogenic markers. Additionally, the 3T3-L1 adipocytes co-cultured with breast cancer cells showed up-regulation of inflammation-related genes including Il6 and Ptx3. The up-regulation of IL6 in CAA was further observed in human breast cancer tissues. miRNA array of co-cultured 3T3-L1 cells showed increased expression of mmu-miR-5112 which may target Cpeb1. Cpeb1 is a negative regulator of Il6. The suppressive role of mmu-miR-5112 was confirmed by dual luciferase reporter assay, and mmu-miR-5112-treated adipocytes showed up-regulation of Il6. The transition of adipocytes into more inflammatory CAA resulted in proliferation-promoting effect in ER positive breast cancer cells such as MCF7 and ZR-75-1 but not in ER negative cells.\n\nConclusionIn this study, we have determined the de-differentiated and inflammatory natures of CAA in breast cancer microenvironment. Additionally, we propose a miRNA-based regulatory mechanism underlying the process of acquiring inflammatory phenotypes in CAA.

cancer biology↗