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qFlow Cytometry-Based Receptoromic Screening: A High-Throughput Quantification Approach Informing Biomarker Selection and Nanosensor Development

qFlow Cytometry-Based Receptoromic Screening: A High-Through...

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作者： Si Chen Jared Weddell Pavan Gupta Grace Conard James Parkin Princess I. Imoukhuede

Nanosensor-based detection of biomarkers can improve medical diagnosis; however, a critical factor in nanosensor development is deciding which biomarker to target, as most diseases present several biomarkers. Biomarker-targeting decisions can be informed via an understanding of biomarker expression. Currently, immunohistochemistry (IHC) is the accepted standard for profiling biomarker expression. While IHC provides a relative mapping of biomarker expression, it does not provide cell-by-cell readouts of biomarker expression or absolute biomarker quantification. Flow cytometry overcomes both these IHC challenges by offering biomarker expression on a cell-by-cell basis, and when combined with calibration standards, providing quantitation of biomarker concentrations: this is known as qFlow cytometry. Here, we outline the key components for applying qFlow cytometry to detect biomarkers within the angiogenic vascular endothelial growth factor receptor family. The key aspects of the qFlow cytometry methodology include: antibody specificity testing, immunofluorescent cell labeling, saturation analysis, fluorescent microsphere calibration, and quantitative analysis of both ensemble and cell-by-cell data. Together, these methods enable high-throughput quantification of biomarker expression. less

关键词： Immunolabeling Flow Cytometry Cell And Tissue Culture Immunohistochemistry Cell Labeling MATLAB Data analysis programming language Homo sapiens Angiogenesis Systems biology Background subtraction Heterogeneity qFlow cytometry Vascular Endothelial Growth Factor (VEGF) Platelet-Derived Growth Factor (PDGF) Mixture modeling

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Current Methods Used to Probe and Quantify Intracellular Total and Free Zn(II) Dynamics, and Subcellular Distribution in Cultured Neurons

Current Methods Used to Probe and Quantify Intracellular Tot...

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作者： Yan Qin Kyle R. Gee Qiaoling Jin Barry Lai Cheng Qian Robert A. Colvin

Zinc is an essential trace element and its critical role in the normal function and pathophysiology of the nervous system is firmly established. However, the study of zinc in neurons is still in its infancy when considering the many intracellular processes that may be involved in maintaining homeostatic control of zinc, possible zinc signaling pathways, and dysfunction in disease. A complete understanding of these key homeostatic and signaling mechanisms relies on accurate and reproducible measurement of the dynamics of both intracellular total and free zinc, as well as the subcellular distribution of zinc in the cytosol and organelles. The methods available to researchers to study and quantify intracellular zinc dynamics in neurons have advanced considerably over the past 10–15 years. Several quantitative methods are available that can reliably report the total levels of zinc in a neuron as well as methods that can detect and monitor the intracellular distribution and free concentration in the cytosol and various organelle compartments. In this chapter, the authors wish to bring the reader up-to-date on methods used to quantify levels and changes in intracellular concentrations of zinc in cultured neurons. Here, we will be focusing on: (1) synchrotron radiation X-ray fluorescence (SRXRF) for total cellular zinc and topographic analysis, (2) population spectrofluorometric analysis of the dynamics of cytosolic zinc, and (3) Förster resonance energy transfer (FRET) microscopic analysis of genetically encoded sensors, which can report the dynamics of free concentrations of zinc in the cytosol and organelles. less

关键词： FRET Synchrotron Radiation Dissection Trypsination Trituration TEM Image Processing Single-cell Imaging Transient Transfection Transfection Chemical Fixation Titration Fluorescence Spectroscopy Magnetic Stirring Tissue Imaging Fluorescence Microscopy ImageJ Cell And Tissue Culture programming language Saccharomyces cerevisiae Homo sapiens Arabidopsis Rattus norvegicus RWPE-1 LNCaP HEK293 Primary culture Plunge freezing Fluorescent zinc probes Ratiometric zinc sensors Microfluorometric analysis Spectrofluorometric analysis Genetically encoded zinc sensors Cryogenics

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Open-Source Software Tools, Databases, and Resources for Single-Cell and Single-Cell-Type Metabolomics

Open-Source Software Tools, Databases, and Resources for Sin...

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作者： Biswapriya B. Misra

In this age of –omics data-guided big data revolution, metabolomics has received significant attention as compared to genomics, transcriptomics, and proteomics for its proximity to the phenotype, the promises it makes and the challenges it throws. Although metabolomes of entire organisms, organs, biofluids, and tissues are of immense interest, a cell-specific resolution is deemed critical for biomedical applications where a granular understanding of cellular metabolism at cell-type and subcellular resolution is desirable. Mass spectrometry (MS) is a versatile technique that is used to analyze a broad range of compounds from different species and cell-types, with high accuracy, resolution, sensitivity, selectivity, and fast data acquisition speeds. With recent advances in MS and spectroscopy-based platforms, the research community is able to generate high-throughput data sets from single cells. However, it is challenging to handle, store, process, analyze, and interpret data in a routine manner. In this treatise, I present a workflow of metabolomics data generation from single cells and single-cell types to their analysis, visualization, and interpretation for obtaining biological insights. less

关键词： Mass Spectrometry Metabolomics Statistical Calculation Genomics Transcriptomics Proteomics Lipidomics Liquid Chromatography-mass Spectrometry Gas Chromatography-mass Spectrometry Electrospray Ionization (ESI) ESI Mass Spectrometry Capillary Electrophoresis-mass Spectrometry Tandem Mass Spectrometry Machine Learning Cytoscape Functional Enrichment Fluxomics KNIME Image Processing Laser Ablation Inductively Coupled Plasma Mass Spectrometry Image Analysis ImageJ Data analysis Python programming language Homo sapiens MDA-MB-231 Analysis Software Data Plant Database Single cell Microbial Web server Computational Pathway Network Cell Animal Tool –Omics Statistical Single-cell type

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Reconstruction of Genome-Scale Metabolic Model for

Reconstruction of Genome-Scale Metabolic Model for

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作者： Francisco Zorrilla Eduard J. Kerkhoven

Genome-scale metabolic models (GEMs) provide a useful framework for modeling the metabolism of microorganisms. While the applications of GEMs are wide and far reaching, the reconstruction and continuous curation of such models can be perceived as a tedious and time-consuming task. Using RAVEN, a MATLAB-based toolbox designed to facilitate the reconstruction analysis of metabolic networks, this protocol practically demonstrates how researchers can create their own GEMs using a homology-based approach. To provide a complete example, a draft GEM for the industrially relevant yeast Hansenula polymorpha is reconstructed. less

关键词： programming language Pichia Saccharomyces cerevisiae Metabolism Genome-scale model Constraint-based model

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A Computational Tool for Analysis of Mass Spectrometry Data of Ubiquitin-Enriched Samples

A Computational Tool for Analysis of Mass Spectrometry Data ...

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作者： Rune Matthiesen Manuel S. Rodriguez Ana Sofia Carvalho

Mass spectrometry data on ubiquitin and ubiquitin-like modifiers are becoming increasingly more accessible, and the coverage progressively deepen as methodologies mature. This type of mass spectrometry data is linked to specific data analysis pipelines for ubiquitin. This chapter describes a computational tool to facilitate analysis of mass spectrometry data obtained on ubiquitin-enriched samples. For example, the analysis of ubiquitin branch site statistics and functional enrichment analysis against ubiquitin proteasome system protein sets are completed with a few functional calls. We foresee that the proposed computational methodology can aid in proximity drug design by, for example, elucidating the expression of E3 ligases and other factors related to the ubiquitin proteasome system. less

关键词： Mass Spectrometry programming language Statistical Calculation Recombinant Protein Expression Data analysis Functional Enrichment Ubiquitin proteasome system Ubiquitin enrichment Proximity drugs Proteolysis targeting chimera

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Microarray Bioinformatics

Microarray Bioinformatics

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作者： Robert P. Loewe Peter J. Nelson

Bioinformatics has become an increasingly important tool for molecular biologists, especially for the analysis of microarray data. Microarrays can produce vast amounts of information requiring a series of consecutive analyses to render the data interpretable. The direct output of microarrays cannot be directly interpreted to show differences in settings, conditions of samples, or time points. To make microarray experiments interpretable, it is necessary that a series of algorithms and approaches be applied. After normalization of generated data, which is necessary to make a comparison feasible, significance analysis, clustering of samples and biological compounds of interest and visualization are generally performed. This chapter will focus on providing a basic understanding of the generally approaches and algorithms currently employed in microarray bioinformatics. less

关键词： Microarray RNA Extraction Gene Expression Profiling Statistical Calculation Simulated Annealing Fuzzy Logic Principal Component Analysis Genomics programming language SAM PCA Normalization Bioinformatics RMA Clustering

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Analysis of Transcriptomic Data Generated from Drug-Treated Cancer Cell Line

Analysis of Transcriptomic Data Generated from Drug-Treated ...

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作者： Swarnima Kushwaha Sudeshna Mukherjee Rajdeep Chowdhury Shibasish Chowdhury

Resistance to chemotherapy is one major obstacle in current cancer treatment. Therefore, understanding the molecular basis of the acquisition of resistance is vital for the design and development of appropriate cancer therapy. Importantly, acquisition of resistance is not a single-step process, and the molecular signature of cells dynamically changes during this process. With the advent of next-generation omic technologies, today one can precisely map the molecular alterations not only in a population of tumor cells but also at the single-cell level as they attain chemo-resistance. In this chapter, we describe a detailed transcriptomic pipeline following next-generation sequencing for mapping alteration in expression during the process of attainment of resistance. We provide comprehensive information on the process to (1) track the differential expression of transcripts, (2) understand the gene ontology functions, (3) filter out candidate key genes, (4) identify the pathways regulated by them, and (5) generate a map of their probable interactions. We assume that our analytical method will be useful for research in this direction. less

关键词： RNA-seq RNA Extraction mRNA sequencing Data analysis Gel Electrophoresis Deep Sequencing High-Throughput Sequencing TopHat Bowtie programming language Cufflinks Gene Expression Analysis Cuffdiff Cytoscape Data Visualization Tools Cell And Tissue Culture Cancer Chemotherapy Drug resistance

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CCD Camera Detection of HIV Infection

CCD Camera Detection of HIV Infection

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作者： John R. Day

Rapid and precise quantification of the infectivity of HIV is important for molecular virologic studies, as well as for measuring the activities of antiviral drugs and neutralizing antibodies. An indicator cell line, a CCD camera, and image-analysis software are used to quantify HIV infectivity. The cells of the P4R5 line, which express the receptors for HIV infection as well as β-galactosidase under the control of the HIV-1 long terminal repeat, are infected with HIV and then incubated 2 days later with X-gal to stain the infected cells blue. Digital images of monolayers of the infected cells are captured using a high resolution CCD video camera and a macro video zoom lens. A software program is developed to process the images and to count the blue-stained foci of infection. The described method allows for the rapid quantification of the infected cells over a wide range of viral inocula with reproducibility, accuracy and at relatively low cost. less

关键词： Cell And Tissue Culture Image Analysis Transient Transfection programming language Human immunodeficiency virus 1 Viruses Lens HeLa Imaging Quantify HIV Rapid Infectivity Charge-coupled device (CCD)

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Quantifying the Biological Impact of Active Substances Using Causal Network Models

Quantifying the Biological Impact of Active Substances Using...

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作者： Alain Sewer Florian Martin Walter K. Schlage Julia Hoeng Manuel C. Peitsch

In this chapter a five-step strategy is described that provides comparative evaluations of the effects of biologically active substances. These evaluations constitute an integral part of the determination of the risks for the human population to exposure to these substances. The strategy is based on the concept of biological impact quantification for which novel computational methodologies have been developed in the past few years; these methodologies are reviewed in this chapter. The effects of the active substances are then described in terms of networks containing the biological mechanisms involved in the response to the exposure. As a consequence, the biological impact assessment represents a systems-wide metric of network-based perturbed biological mechanisms. The implementation of the strategy involves the generation of transcriptomics data following the exposure experiment and their evaluation in the context of causal network models. After the five-step strategy for biological impact quantification has been described in some detail, its application in a concrete case of a mouse smoking-cessation experiment is presented. The results show how mechanistic insights into the potential toxic effects of exposure to active substances can benefit the safety assessment.

关键词： Transcriptomics DNA Extraction Microarray Hybridization Proteomics Principal Component Analysis Statistical Calculation Data analysis programming language Biological impact of exposure Causal biological network models Network perturbations Mechanistic fingerprinting

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Approaches to Link RNA Secondary Structures with Splicing Regulation

Approaches to Link RNA Secondary Structures with Splicing Re...

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作者： Mireya Plass Eduardo Eyras

In higher eukaryotes, alternative splicing is usually regulated by protein factors, which bind to the pre-mRNA and affect the recognition of splicing signals. There is recent evidence that the secondary structure of the pre-mRNA may also play an important role in this process, either by facilitating or hindering the interaction with factors and small nuclear ribonucleoproteins (snRNPs) that regulate splicing. Moreover, the secondary structure could play a fundamental role in the splicing of yeast species, which lack many of the regulatory splicing factors present in metazoans. This chapter describes the steps in the analysis of the secondary structure of the pre-mRNA and its possible relation to splicing. As a working example, we use the case of yeast and the problem of the recognition of the 3′ splice site (3′ss). less

关键词： Structure Prediction RNA Structure Prediction Genome Visualization Ensembl Data analysis programming language Saccharomyces cerevisiae Saccharomyces RNA Bioinformatics Splicing Secondary structure Posttranscriptional regulation

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