scholarly journals HiCTMap: Detection and Analysis of Chromosome Territory Structure and Position by High-throughput Imaging

2017 ◽  
Author(s):  
Ziad Jowhar ◽  
Prabhakar Gudla ◽  
Sigal Shachar ◽  
Darawalee Wangsa ◽  
Jill L. Russ ◽  
...  
Keyword(s):  
High Precision ◽  
High Throughput ◽  
Large Population ◽  
Chromosome Territory ◽  
Automated Image Analysis ◽  
Nuclear Space ◽  
Chromosome Territories ◽  
Wide Range ◽  
High Throughput Imaging ◽  
2D And 3D

AbstractThe spatial organization of chromosomes in the nuclear space is an extensively studied field that relies on measurements of structural features and 3D positions of chromosomes with high precision and robustness. However, no tools are currently available to image and analyze chromosome territories in a high-throughput format. Here, we have developed High-throughput Chromosome Territory Mapping (HiCTMap), a method for the robust and rapid analysis of 2D and 3D chromosome territory positioning in mammalian cells. HiCTMap is a high-throughput imaging-based chromosome detection method which enables routine analysis of chromosome structure and nuclear position. Using an optimized FISH staining protocol in a 384-well plate format in conjunction with a bespoke automated image analysis workflow, HiCTMap faithfully detects chromosome territories and their position in 2D and 3D in a large population of cells per experimental condition. We apply this novel technique to visualize chromosomes 18, X, and Y in male and female primary human skin fibroblasts, and show accurate detection of the correct number of chromosomes in the respective genotypes. Given the ability to visualize and quantitatively analyze large numbers of nuclei, we use HiCTMap to measure chromosome territory area and volume with high precision and determine the radial position of chromosome territories using either centroid or equidistant-shell analysis. The HiCTMap protocol is also compatible with RNA FISH as demonstrated by simultaneous labeling of X chromosomes and Xist RNA in female cells. We suggest HiCTMap will be a useful tool for routine precision mapping of chromosome territories in a wide range of cell types and tissues.

scholarly journals HiCTMap: Detection and analysis of chromosome territory structure and position by high-throughput imaging

Methods ◽  
2018 ◽  
Vol 142 ◽  
pp. 30-38 ◽  
Author(s):  
Ziad Jowhar ◽  
Prabhakar R. Gudla ◽  
Sigal Shachar ◽  
Darawalee Wangsa ◽  
Jill L. Russ ◽  
...  
Keyword(s):  
High Throughput ◽  
Chromosome Territory ◽  
High Throughput Imaging

scholarly journals An automated, high-throughput method for standardizing image color profiles to improve image-based plant phenotyping

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5727 ◽  
Author(s):  
Jeffrey C. Berry ◽  
Noah Fahlgren ◽  
Alexandria A. Pokorny ◽  
Rebecca S. Bart ◽  
Kira M. Veley
Keyword(s):  
High Throughput ◽  
Linear Models ◽  
Correction Method ◽  
Automated Image Analysis ◽  
Plant Phenotyping ◽  
Image Brightness ◽  
Automated Method ◽  
Color Profile ◽  
High Throughput Phenotyping ◽  
High Throughput Imaging

High-throughput phenotyping has emerged as a powerful method for studying plant biology. Large image-based datasets are generated and analyzed with automated image analysis pipelines. A major challenge associated with these analyses is variation in image quality that can inadvertently bias results. Images are made up of tuples of data called pixels, which consist of R, G, and B values, arranged in a grid. Many factors, for example image brightness, can influence the quality of the image that is captured. These factors alter the values of the pixels within images and consequently can bias the data and downstream analyses. Here, we provide an automated method to adjust an image-based dataset so that brightness, contrast, and color profile is standardized. The correction method is a collection of linear models that adjusts pixel tuples based on a reference panel of colors. We apply this technique to a set of images taken in a high-throughput imaging facility and successfully detect variance within the image dataset. In this case, variation resulted from temperature-dependent light intensity throughout the experiment. Using this correction method, we were able to standardize images throughout the dataset, and we show that this correction enhanced our ability to accurately quantify morphological measurements within each image. We implement this technique in a high-throughput pipeline available with this paper, and it is also implemented in PlantCV.

scholarly journals An automated, high-throughput method for standardizing image color profiles to improve image-based plant phenotyping

2018 ◽  
Author(s):  
Jeffrey C. Berry ◽  
Noah Fahlgren ◽  
Alexandria A. Pokorny ◽  
Rebecca Bart ◽  
Kira M. Veley
Keyword(s):  
High Throughput ◽  
Linear Models ◽  
Correction Method ◽  
Automated Image Analysis ◽  
Plant Phenotyping ◽  
Image Brightness ◽  
Automated Method ◽  
Color Profile ◽  
High Throughput Phenotyping ◽  
High Throughput Imaging

ABSTRACTHigh-throughput phenotyping has emerged as a powerful method for studying plant biology. Large image-based datasets are generated and analyzed with automated image analysis pipelines. A major challenge associated with these analyses is variation in image quality that can inadvertently bias results. Images are made up of tuples of data called pixels, which consist of R, G, and B values, arranged in a grid. Many factors, for example image brightness, can influence the quality of the image that is captured. These factors alter the values of the pixels within images and consequently can bias the data and downstream analyses. Here, we provide an automated method to adjust an image-based dataset so that brightness, contrast, and color profile is standardized. The correction method is a collection of linear models that adjusts pixel tuples based on a reference panel of colors. We apply this technique to a set of images taken in a high-throughput imaging facility and successfully detect variance within the image dataset. In this case, variation resulted from temperature-dependent light intensity throughout the experiment. Using this correction method, we were able to standardize images throughout the dataset, and we show that this correction enhanced our ability to accurately quantify morphological measurements within each image. We implement this technique in a high-throughput pipeline available with this paper, and it is also implemented in PlantCV.

scholarly journals The Astro-D Mission

1990 ◽  
Vol 123 ◽  
pp. 81-87
Author(s):  
Y. Tanaka
Keyword(s):  
Energy Range ◽  
High Throughput ◽  
Focal Plane ◽  
Effective Area ◽  
Ccd Cameras ◽  
X Ray ◽  
Wide Range ◽  
Proportional Counters ◽  
High Throughput Imaging ◽  
Large Effective Area

AbstractAstro-D, the fourth X-ray astronomy mission of ISAS following Ginga, is a high-throughput imaging and spectroscopic X-ray observatory, scheduled for launch in early 1993. It utilizes multilayer conical X-ray mirrors which provide a large effective area over a wide range energy range up to 12 keV. The focal plane instruments comprize a set of CCD cameras and Imaging gas scintillation proportional counters. Main features of Astro-D are described, and the important astrophysical objectives are discussed.

A High-Throughput Imaging Spectrometer Based on Over-Scanning

2014 ◽  
Vol 519-520 ◽  
pp. 1247-1251
Author(s):  
Jiang Yue ◽  
Jing Han ◽  
Yi Zhang ◽  
Lian Fa Bai
Keyword(s):  
High Precision ◽  
High Throughput ◽  
Super Resolution ◽  
Original Data ◽  
Imaging Spectrometer ◽  
Reconstructed Spectrum ◽  
Electromechanical Device ◽  
High Throughput Imaging ◽  
Wide Slit

We present a novel high-throughput imaging spectrometer based on over-scanning. The traditional slit-based spectrometer cannot gather enough radiation while the source is too weak. A much wider slit is used to replace the narrow one in traditional spectrometer. Too much wide slit will cause overlapping between different wavelength lights. In order to reconstruct super-resolution spectrum of source, over-scanning is employed which is realized by high precision electromechanical device. Experiments show that the reconstructed spectrum achieved a much higher resolution than original data meanwhile the throughput has improved significantly.

scholarly journals Micro-Magellan: A flexible, open source acquisition software for high throughput biological light microscopy

2016 ◽  
Author(s):  
Henry Pinkard ◽  
Nico Stuurman ◽  
Kaitlin Corbin ◽  
Ronald Vale ◽  
Matthew F Krummel
Keyword(s):  
User Interface ◽  
Light Microscopy ◽  
Open Source ◽  
High Throughput ◽  
Biological Samples ◽  
Abstraction Layer ◽  
Wide Range ◽  
Automated Imaging ◽  
Hardware Abstraction Layer ◽  
High Throughput Imaging

We demonstrate the capabilities of μMagellan: a flexible, open source microscopy software for reproducible high throughput imaging of biological samples across heterogeneous scales of space and time. μMagellan provides a simple user interface for exploration and automated imaging of non-cuboidal regions. By utilizing the hardware abstraction layer of μManager, μMagellan provides a powerful and extensible platform for imaging heterogeneous biological samples on a wide range of existing microscopes.

scholarly journals Planetary Nebulae in M31: Abundances, and comparison with bright Planetary Nebulae in the LMC

1997 ◽  
Vol 180 ◽  
pp. 475-476
Author(s):  
M. G. Richer ◽  
G. Stasińska ◽  
M. L. McCall
Keyword(s):  
Planetary Nebula ◽  
Luminosity Function ◽  
Large Population ◽  
Wavelength Region ◽  
Planetary Nebulae ◽  
Surprising Result ◽  
Population Synthesis ◽  
Abundance Distribution ◽  
Wide Range ◽  
The Mean

We have obtained spectra of 28 planetary nebulae in the bulge of M31 using the MOS spectrograph at the Canada-France-Hawaii Telescope. Typically, we observed the [O II] λ3727 to He I λ5876 wavelength region at a resolution of approximately 1.6 å/pixel. For 19 of the 21 planetary nebulae whose [OIII]λ5007 luminosities are within 1 mag of the peak of the planetary nebula luminosity function, our oxygen abundances are based upon a measured [OIII]λ4363 intensity, so they are based upon a measured electron temperature. The oxygen abundances cover a wide range, 7.85 dex < 12 + log(O/H) < 9.09 dex, but the mean abundance is surprisingly low, 12 + log(O/H)–8.64 ± 0.32 dex, i.e., roughly half the solar value (Anders & Grevesse 1989). The distribution of oxygen abundances is shown in Figure 1, where the ordinate indicates the number of planetary nebulae with abundances within ±0.1 dex of any point on the x-axis. The dashed line indicates the mean abundance, and the dotted lines indicate the ±1 σ points. The shape of this abundance distribution seems to indicate that the bulge of M31 does not contain a large population of bright, oxygen-rich planetary nebulae. This is a surprising result, for various population synthesis studies (e.g., Bica et al. 1990) have found a mean stellar metallicity approximately 0.2 dex above solar. This 0.5 dex discrepancy leads one to question whether the mean stellar metallicity is as high as the population synthesis results indicate or if such metal-rich stars produce bright planetary nebulae at all. This could be a clue concerning the mechanism responsible for the variation in the number of bright planetary nebulae observed per unit luminosity in different galaxies (e.g., Hui et al. 1993).

scholarly journals Separate Universe calibration of the dependence of halo bias on cosmic web anisotropy

2020 ◽  
Vol 499 (3) ◽  
pp. 4418-4431 ◽  
Author(s):  
Sujatha Ramakrishnan ◽  
Aseem Paranjape
Keyword(s):  
Dark Matter ◽  
High Precision ◽  
Gaussian Distribution ◽  
Initial Perturbation ◽  
Analytical Framework ◽  
Web Environment ◽  
Wide Range ◽  
Galaxy Assembly ◽  
Very High ◽  
Good Agreement

ABSTRACT We use the Separate Universe technique to calibrate the dependence of linear and quadratic halo bias b1 and b2 on the local cosmic web environment of dark matter haloes. We do this by measuring the response of halo abundances at fixed mass and cosmic web tidal anisotropy α to an infinite wavelength initial perturbation. We augment our measurements with an analytical framework developed in earlier work that exploits the near-lognormal shape of the distribution of α and results in very high precision calibrations. We present convenient fitting functions for the dependence of b1 and b2 on α over a wide range of halo mass for redshifts 0 ≤ z ≤ 1. Our calibration of b2(α) is the first demonstration to date of the dependence of non-linear bias on the local web environment. Motivated by previous results that showed that α is the primary indicator of halo assembly bias for a number of halo properties beyond halo mass, we then extend our analytical framework to accommodate the dependence of b1 and b2 on any such secondary property that has, or can be monotonically transformed to have, a Gaussian distribution. We demonstrate this technique for the specific case of halo concentration, finding good agreement with previous results. Our calibrations will be useful for a variety of halo model analyses focusing on galaxy assembly bias, as well as analytical forecasts of the potential for using α as a segregating variable in multitracer analyses.

scholarly journals A fully automated pipeline for the dynamic at‐line morphology analysis of microscale Aspergillus cultivation

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Roman Jansen ◽  
Kira Küsters ◽  
Holger Morschett ◽  
Wolfgang Wiechert ◽  
Marco Oldiges
Keyword(s):  
Filamentous Fungi ◽  
High Throughput ◽  
Automated Image Analysis ◽  
Height Velocity ◽  
Pellet Size ◽  
Application Study ◽  
Liquid Handling ◽  
Morphology Analysis ◽  
Development And Utilization ◽  
Increasing Demand

Abstract Background Morphology, being one of the key factors influencing productivity of filamentous fungi, is of great interest during bioprocess development. With increasing demand of high-throughput phenotyping technologies for fungi due to the emergence of novel time-efficient genetic engineering technologies, workflows for automated liquid handling combined with high-throughput morphology analysis have to be developed. Results In this study, a protocol allowing for 48 parallel microbioreactor cultivations of Aspergillus carbonarius with non-invasive online signals of backscatter and dissolved oxygen was established. To handle the increased cultivation throughput, the utilized microbioreactor is integrated into a liquid handling platform. During cultivation of filamentous fungi, cell suspensions result in either viscous broths or form pellets with varying size throughout the process. Therefore, tailor-made liquid handling parameters such as aspiration/dispense height, velocity and mixing steps were optimized and validated. Development and utilization of a novel injection station enabled a workflow, where biomass samples are automatically transferred into a flow through chamber fixed under a light microscope. In combination with an automated image analysis concept, this enabled an automated morphology analysis pipeline. The workflow was tested in a first application study, where the projected biomass area was determined at two different cultivation temperatures and compared to the microbioreactor online signals. Conclusions A novel and robust workflow starting from microbioreactor cultivation, automated sample harvest and processing via liquid handling robots up to automated morphology analysis was developed. This protocol enables the determination of projected biomass areas for filamentous fungi in an automated and high-throughput manner. This measurement of morphology can be applied to describe overall pellet size distribution and heterogeneity.

scholarly journals From Multiplex Serology to Serolomics—A Novel Approach to the Antibody Response against the SARS-CoV-2 Proteome

Viruses ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 749
Author(s):  
Julia Butt ◽  
Rajagopal Murugan ◽  
Theresa Hippchen ◽  
Sylvia Olberg ◽  
Monique van Straaten ◽  
...  
Keyword(s):  
Antibody Response ◽  
High Throughput ◽  
Large Population ◽  
High Sensitivity ◽  
Population Based ◽  
Antibody Responses ◽  
Hek293 Cells ◽  
Novel Approach ◽  
Assay Performance ◽  
Multiplex Serology

The emerging SARS-CoV-2 pandemic entails an urgent need for specific and sensitive high-throughput serological assays to assess SARS-CoV-2 epidemiology. We, therefore, aimed at developing a fluorescent-bead based SARS-CoV-2 multiplex serology assay for detection of antibody responses to the SARS-CoV-2 proteome. Proteins of the SARS-CoV-2 proteome and protein N of SARS-CoV-1 and common cold Coronaviruses (ccCoVs) were recombinantly expressed in E. coli or HEK293 cells. Assay performance was assessed in a COVID-19 case cohort (n = 48 hospitalized patients from Heidelberg) as well as n = 85 age- and sex-matched pre-pandemic controls from the ESTHER study. Assay validation included comparison with home-made immunofluorescence and commercial enzyme-linked immunosorbent (ELISA) assays. A sensitivity of 100% (95% CI: 86–100%) was achieved in COVID-19 patients 14 days post symptom onset with dual sero-positivity to SARS-CoV-2 N and the receptor-binding domain of the spike protein. The specificity obtained with this algorithm was 100% (95% CI: 96–100%). Antibody responses to ccCoVs N were abundantly high and did not correlate with those to SARS-CoV-2 N. Inclusion of additional SARS-CoV-2 proteins as well as separate assessment of immunoglobulin (Ig) classes M, A, and G allowed for explorative analyses regarding disease progression and course of antibody response. This newly developed SARS-CoV-2 multiplex serology assay achieved high sensitivity and specificity to determine SARS-CoV-2 sero-positivity. Its high throughput ability allows epidemiologic SARS-CoV-2 research in large population-based studies. Inclusion of additional pathogens into the panel as well as separate assessment of Ig isotypes will furthermore allow addressing research questions beyond SARS-CoV-2 sero-prevalence.

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