Image-Processing Software for High-Throughput Quantification of Colony Luminescence

ABSTRACTMany microbiological assays include colonies that produce a luminescent or fluorescent (here generalized as “luminescent”) signal, often in the form of luminescent halos around the colonies. These signals are used as reporters for a trait of interest; therefore, exact measurements of the luminescence are often desired. However, there is currently a lack of high-throughput methods for analyzing these assays, as common automatic image analysis tools are unsuitable for identifying these halos in the presence of the inherent biological noise. In this work, we have developed CFQuant—automatic, high-throughput software for the analysis of images from colony luminescence assays. CFQuant overcomes the problems of automatic identification by relying on the luminescence halo's expected shape and provides measurements of several features of the colonies and halos. We examined the performance of CFQuant using one such colony luminescence assay, where we achieved a high correlation (R = 0.85) between the measurements of CFQuant and known protein expression levels. This demonstrates CFQuant's potential as a fast and reliable tool for analysis of colony luminescence assays.IMPORTANCELuminescent markers are widely used as reporters for various biologically interesting traits. In colony luminescence assays, the levels of luminescence around each colony can be used to compare the levels of traits of interest for different strains, treatments, etc., using quantitative measurements of the luminescence. However, automatic methods of obtaining this data are underdeveloped, making this a laborious manual process, especially in analyzing large numbers of colonies. The significance of this work is in developing an automatic, high-throughput tool for quantitative analysis of colony luminescence assays, which will allow fast collection of qualitative data from these assays and thus increase their overall usability.

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AFLP-based assessment of genetic diversity among nine alfalfa germplasms using bulk DNA templates

Genome ◽

10.1139/g02-100 ◽

2003 ◽

Vol 46 (1) ◽

pp. 51-58 ◽

Cited By ~ 46

Author(s):

A Segovia-Lerma ◽

R G Cantrell ◽

J M Conway ◽

I M Ray

Keyword(s):

Genetic Diversity ◽

Medicago Sativa ◽

High Throughput ◽

Genetic Distances ◽

Group Method ◽

Aflp Analysis ◽

Dna Templates ◽

Arithmetic Average ◽

Pair Group ◽

Large Numbers

Improving commercial utilization of perennial Medicago collections requires developing approaches that can rapidly and accurately characterize genetic diversity among large numbers of populations. This study evaluated the potential of using amplified fragment length polymorphism (AFLP) DNA markers, in combination with DNA bulking over multiple genotypes, as a strategy for high-throughput characterization of genetic distances (D) among alfalfa (Medicago sativa L.) accessions. Bulked DNA templates from 30 genotypes within each of nine well-recognized germplasms (African, Chilean, Flemish, Indian, Ladak, Medicago sativa subsp. falcata, Medicago sativa subsp. varia, Peruvian, and Turkistan) were evaluated using 34 primer combinations. A total of 3754 fragments were identified, of which 1541 were polymorphic. The number of polymorphic fragments detected per primer combination ranged from 20 to 85. Pairwise D estimates among the nine germplasms ranged from 0.52 to 1.46 with M. sativa subsp. falcata being the most genetically dissimilar. Unweighted pair-group method arithmetic average (UPGMA) analysis of the marker data produced two main clusters, (i) M. sativa subsp. sativa and M. sativa subsp. varia, and (ii) M. sativa subsp. falcata. Cluster-analysis results and D estimates among the Chilean, Peruvian, Flemish, and M. sativa subsp. varia germplasms supported the hypothesis that Peruvian was more similar to original Spanish introductions into Central and South America than Chilean. Hierarchical arrangement of the nine germplasms was supported by their respective geographic, subspecific, and intersubspecific hybrid origins. Subsets of as few as seven highly informative primer pairs were identified that produced comparable D estimates and similar heirarchical arrangements compared with the complete dataset. The results indicate that use of primer-pair subsets for AFLP analysis of bulk DNA templates could serve as a high-throughput system for accurately characterizing genetic diversity among large numbers of alfalfa populations.Key words: Medicago sativa, DNA bulking, genetic distance.

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Behavior Individuality: A Focus on Drosophila melanogaster

Frontiers in Physiology ◽

10.3389/fphys.2021.719038 ◽

2021 ◽

Vol 12 ◽

Author(s):

Rubén Mollá-Albaladejo ◽

Juan A. Sánchez-Alcañiz

Keyword(s):

Gene Expression ◽

Drosophila Melanogaster ◽

High Throughput ◽

High Throughput Sequencing ◽

Great Effort ◽

Behavioral Differences ◽

Adult Behavior ◽

Large Numbers ◽

Environmental Variations ◽

And Function

Among individuals, behavioral differences result from the well-known interplay of nature and nurture. Minute differences in the genetic code can lead to differential gene expression and function, dramatically affecting developmental processes and adult behavior. Environmental factors, epigenetic modifications, and gene expression and function are responsible for generating stochastic behaviors. In the last decade, the advent of high-throughput sequencing has facilitated studying the genetic basis of behavior and individuality. We can now study the genomes of multiple individuals and infer which genetic variations might be responsible for the observed behavior. In addition, the development of high-throughput behavioral paradigms, where multiple isogenic animals can be analyzed in various environmental conditions, has again facilitated the study of the influence of genetic and environmental variations in animal personality. Mainly, Drosophila melanogaster has been the focus of a great effort to understand how inter-individual behavioral differences emerge. The possibility of using large numbers of animals, isogenic populations, and the possibility of modifying neuronal function has made it an ideal model to search for the origins of individuality. In the present review, we will focus on the recent findings that try to shed light on the emergence of individuality with a particular interest in D. melanogaster.

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Dynamic Resource Management in High Throughput Satellite with Multi Port Amplifier (MPA)

International Journal of Interdisciplinary Telecommunications and Networking ◽

10.4018/ijitn.2016070105 ◽

2016 ◽

Vol 8 (3) ◽

pp. 66-81

Author(s):

Sunil Panthi ◽

Ahmed M. Eltawil

Keyword(s):

High Throughput ◽

Noise Temperature ◽

Efficient Utilization ◽

Commercial Aviation ◽

Radiated Power ◽

Large Numbers ◽

Small Spot ◽

Data Capacity ◽

Dynamic Resource Management ◽

Dynamic Resource

The demand for data capacity has been growing, especially in the aviation and maritime industries and is expected to continue to grow in the foreseeable future. The satellite industry is moving to High Throughput Satellite (HTS) that are characterized by large numbers of small spot beams, frequency reuse, higher Equivalent Isotropically Radiated Power (EIRP) and higher Gain to Noise Temperature (G/T) to meet growing capacity demand. Multi-Port Amplifiers (MPA) increase the flexibility of HTS systems by allowing capacity to be allocated dynamically based on changing demand. This will allow capacity requirements to be planned based on the sum of the requirements across all beams rather than the peaks in each HTS beam. The authors propose a ground based solution that will maximize resource utilization of an HTS with an MPA and deliver the capacity dynamically based on demand. Maritime, commercial aviation, satellite based cellular backhaul, and disaster recovery services are the main applications that can benefit from the solution they propose. The authors' results show significant reduction in the overall capacity requirements because of the more efficient utilization of the satellite resources.

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High Throughput Experimentation Protocol for Quantitative Measurements of Regioselectivity in Ziegler–Natta Polypropylene Catalysis

Industrial & Engineering Chemistry Research ◽

10.1021/acs.iecr.9b02801 ◽

2019 ◽

Vol 58 (32) ◽

pp. 14729-14735 ◽

Cited By ~ 9

Author(s):

Antonio Vittoria ◽

Alessio Mingione ◽

Raffaele Andrea Abbate ◽

Roberta Cipullo ◽

Vincenzo Busico

Keyword(s):

High Throughput ◽

Quantitative Measurements ◽

High Throughput Experimentation

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Patterned superhydrophobic surfaces to process and characterize biomaterials and 3D cell culture

Materials Horizons ◽

10.1039/c7mh00877e ◽

2018 ◽

Vol 5 (3) ◽

pp. 379-393 ◽

Cited By ~ 25

Author(s):

A. I. Neto ◽

P. A. Levkin ◽

J. F. Mano

Keyword(s):

Cell Culture ◽

High Throughput ◽

High Throughput Screening ◽

3D Cell Culture ◽

Superhydrophobic Surfaces ◽

Technological Breakthrough ◽

Large Numbers

Microarrays are a technological breakthrough for high-throughput screening of large numbers of assays.

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An approach to high-throughput X-ray diffraction analysis of combinatorial polycrystalline thin film libraries

Journal of Applied Crystallography ◽

10.1107/s0021889809003227 ◽

2009 ◽

Vol 42 (2) ◽

pp. 174-178 ◽

Cited By ~ 2

Author(s):

S. Roncallo ◽

O. Karimi ◽

K. D. Rogers ◽

D. W. Lane ◽

S. A. Ansari

Keyword(s):

High Throughput ◽

Lattice Parameter ◽

Scattering Data ◽

X Ray Diffraction ◽

X Ray ◽

Raster Scanning ◽

Area Detector ◽

Large Numbers ◽

Potential Applications ◽

Compositional Gradients

With the demand for higher rates of discovery in the materials field, characterization techniques that are capable of rapidly and reliably surveying the characteristics of large numbers of samples are essential. A chemical combinatorial approach using thin films can provide detailed phase diagrams without the need to produce multiple, individual samples. This is achieved with compositional gradients forming high-density libraries. Conventional raster scanning of chemical or structural probes is subsequently used to interrogate the libraries. A new, alternative approach to raster scanning is introduced to provide a method of high-throughput data collection and analysis using an X-ray diffraction probe. Libraries are interrogated with an extended X-ray source and the scattering data collected using an area detector. A simple technique of `partitioning' this scattering distribution enables determination of information comparable to conventional raster scanned results but in a dramatically reduced collection time. The technique has been tested using synthetic X-ray scattering distributions and those obtained from contrived samples. In all cases, the partitioning algorithm is shown to be robust and to provide reliable data; discrimination along the library principal axis is shown to be ∼500 µm and the lattice parameter resolution to be ∼10−3 Å mm−1. The limitations of the technique are discussed and future potential applications described.

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Dose-Response Modeling of High-Throughput Screening Data

CrossRef Listing of Deleted DOIs ◽

10.1177/1087057109349355 ◽

2009 ◽

Vol 14 (10) ◽

pp. 1216-1227 ◽

Cited By ~ 20

Author(s):

Fred Parham ◽

Chris Austin ◽

Noel Southall ◽

Ruili Huang ◽

Raymond Tice ◽

...

Keyword(s):

High Throughput ◽

High Throughput Screening ◽

Statistical Approach ◽

Statistical Tests ◽

Cell Types ◽

Large Numbers ◽

Rodent Cell ◽

Response Modeling ◽

Significant Concentration

The National Toxicology Program is developing a high-throughput screening (HTS) program to set testing priorities for compounds of interest, to identify mechanisms of action, and potentially to develop predictive models for human toxicity. This program will generate extensive data on the activity of large numbers of chemicals in a wide variety of biochemical- and cell-based assays. The first step in relating patterns of response among batteries of HTS assays to in vivo toxicity is to distinguish between positive and negative compounds in individual assays. Here, the authors report on a statistical approach developed to identify compounds positive or negative in an HTS cytotoxicity assay based on data collected from screening 1353 compounds for concentration-response effects in 9 human and 4 rodent cell types. In this approach, the authors develop methods to normalize the data (removing bias due to the location of the compound on the 1536-well plates used in the assay) and to analyze for concentration-response relationships. Various statistical tests for identifying significant concentration-response relationships and for addressing reproducibility are developed and presented.

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Phenomenal: An automatic open source library for 3D shoot architecture reconstruction and analysis for image-based plant phenotyping

10.1101/805739 ◽

2019 ◽

Cited By ~ 2

Author(s):

Simon Artzet ◽

Tsu-Wei Chen ◽

Jérôme Chopard ◽

Nicolas Brichet ◽

Michael Mielewczik ◽

...

Keyword(s):

Open Source ◽

High Throughput ◽

Synthetic Data ◽

3D Models ◽

Plant Phenotyping ◽

Published Data ◽

Data Sets ◽

Quantitative Measurements ◽

Workflow System ◽

Architectural Features

AbstractIn the era of high-throughput visual plant phenotyping, it is crucial to design fully automated and flexible workflows able to derive quantitative traits from plant images. Over the last years, several software supports the extraction of architectural features of shoot systems. Yet currently no end-to-end systems are able to extract both 3D shoot topology and geometry of plants automatically from images on large datasets and a large range of species. In particular, these software essentially deal with dicotyledons, whose architecture is comparatively easier to analyze than monocotyledons. To tackle these challenges, we designed the Phenomenal software featured with: (i) a completely automatic workflow system including data import, reconstruction of 3D plant architecture for a range of species and quantitative measurements on the reconstructed plants; (ii) an open source library for the development and comparison of new algorithms to perform 3D shoot reconstruction and (iii) an integration framework to couple workflow outputs with existing models towards model-assisted phenotyping. Phenomenal analyzes a large variety of data sets and species from images of high-throughput phenotyping platform experiments to published data obtained in different conditions and provided in a different format. Phenomenal has been validated both on manual measurements and synthetic data simulated by 3D models. It has been also tested on other published datasets to reproduce a published semi-automatic reconstruction workflow in an automatic way. Phenomenal is available as an open-source software on a public repository.

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MARGO (Massively Automated Real-time GUI for Object-tracking), a platform for high-throughput ethology

10.1101/593046 ◽

2019 ◽

Cited By ~ 6

Author(s):

Zach Werkhoven ◽

Christian Rohrsen ◽

Chuan Qin ◽

Björn Brembs ◽

Benjamin de Bivort

Keyword(s):

Object Tracking ◽

Real Time ◽

High Throughput ◽

Large Scale ◽

Closed Loop ◽

Optomotor Response ◽

Behavioral Experiments ◽

Loop Control ◽

Flexible Control ◽

Large Numbers

AbstractFast object tracking in real time allows convenient tracking of very large numbers of animals and closed-loop experiments that control stimuli for multiple animals in parallel. We developed MARGO, a real-time animal tracking suite for custom behavioral experiments. We demonstrated that MARGO can rapidly and accurately track large numbers of animals in parallel over very long timescales. We incorporated control of peripheral hardware, and implemented a flexible software architecture for defining new experimental routines. These features enable closed-loop delivery of stimuli to many individuals simultaneously. We highlight MARGO’s ability to coordinate tracking and hardware control with two custom behavioral assays (measuring phototaxis and optomotor response) and one optogenetic operant conditioning assay. There are currently several open source animal trackers. MARGO’s strengths are 1) robustness, 2) high throughput, 3) flexible control of hardware and 4) real-time closed-loop control of sensory and optogenetic stimuli, all of which are optimized for large-scale experimentation.

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Experimental characterization and automatic identification of stridulatory sounds inside wood

10.1101/2021.09.08.459381 ◽

2021 ◽

Author(s):

Carol L. Bedoya ◽

Ximena J. Nelson ◽

Eckehard G. Brockerhoff ◽

Stephen Pawson ◽

Michael Hayes

Keyword(s):

Bark Beetles ◽

Sound Production ◽

Automatic Identification ◽

Spectral Parameters ◽

Detection And Identification ◽

Distance Dependence ◽

Animal Vocalizations ◽

Automatic Methods ◽

Spectral Ranges ◽

Wood Boring

ABSTRACTThe propagation of animal vocalizations in water and in air is a well-studied phenomenon, but sound produced by bark and wood boring insects, which feed and reproduce inside trees, is poorly understood. Often being confined to the dark and chemically-saturated habitat of wood, many bark- and woodborers have developed stridulatory mechanisms to communicate acoustically. Despite their ecological and economic importance and the unusual medium used for acoustic communication, very little is known about sound production in these insects, or their acoustic interactions inside trees. Here, we use bark beetles (Scolytinae) as a model system to study the effects of wooden tissue on the propagation of insect stridulations and propose algorithms for their automatic identification. We characterize distance-dependence of the spectral parameters of stridulatory sounds, propose data-based models for the power decay of the stridulations in both outer and inner bark, provide optimal spectral ranges for stridulation detectability, and develop automatic methods for their detection and identification. We also discuss the acoustic discernibility of species cohabitating the same log. The species tested can be acoustically identified with 99% of accuracy at distances up to 20 cm and detected to the greatest extent in the 2-6 kHz frequency band. Phloem was a better medium for sound transmission than bark.

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