scholarly journals A priori control of zeolite phase competition and intergrowth with high-throughput simulations

Science ◽  
2021 ◽  
Author(s):  
Daniel Schwalbe-Koda ◽  
Soonhyoung Kwon ◽  
Cecilia Paris ◽  
Estefania Bello-Jurado ◽  
Zach Jensen ◽  
...  
Keyword(s):  
High Throughput ◽  
A Priori ◽  
Phase Competition

scholarly journals A High-Throughput Analysis Method to Detect Regions of Interest and Quantify Zebrafish Embryo Images

2010 ◽  
Vol 15 (9) ◽  
pp. 1152-1159 ◽  
Author(s):  
Xiaoyan Xu ◽  
Xiaoyin Xu ◽  
Xin Huang ◽  
Weiming Xia ◽  
Shunren Xia
Keyword(s):  
High Throughput ◽  
Neural Development ◽  
Zebrafish Embryo ◽  
A Priori ◽  
Region Of Interest ◽  
Real Data ◽  
Zebrafish Embryos ◽  
High Throughput Analysis ◽  
Single Experiment ◽  
Priori Information

Zebrafish is widely used to understand neural development and model various neurodegenerative diseases. Zebrafish embryos are optically transparent, have a short development period, and can be kept alive in microplates for days, making them amenable to high-throughput microscopic imaging. As a result of high-throughput experiments, a large number of images can be generated in a single experiment, posing a challenge to researchers to analyze them efficiently and quantitatively. In this work, we develop an image processing focused on detecting and quantifying pigments in zebrafish embryos. The algorithm automatically detects a region of interest (ROI) enclosing an area around the pigments and then segment the pigments for quantification. In this process, the algorithm identifies the head and torso at first, and then finds the boundaries corresponding to the back and abdomen by taking advantage of a priori information about the anatomy of zebrafish embryos. The method is robust in terms that it can detect and quantify pigments even when the embryos have different orientations and curvatures. We used real data to demonstrate the performance of the method to extract phenotypic information from zebrafish embryo images and compared its results with manual analysis for verification.

scholarly journals Multi-Omics Technologies Applied to Tuberculosis Drug Discovery

2020 ◽  
Vol 10 (13) ◽  
pp. 4629 ◽  
Author(s):  
Aaron Goff ◽  
Daire Cantillon ◽  
Leticia Muraro Wildner ◽  
Simon J Waddell
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Drug Discovery ◽  
High Throughput ◽  
A Priori ◽  
Drug Action ◽  
Biological Molecules ◽  
Lead Compound ◽  
Omics Technologies ◽  
Lead Compounds ◽  
High Throughput Screens

Multi-omics strategies are indispensable tools in the search for new anti-tuberculosis drugs. Omics methodologies, where the ensemble of a class of biological molecules are measured and evaluated together, enable drug discovery programs to answer two fundamental questions. Firstly, in a discovery biology approach, to find new targets in druggable pathways for target-based investigation, advancing from target to lead compound. Secondly, in a discovery chemistry approach, to identify the mode of action of lead compounds derived from high-throughput screens, progressing from compound to target. The advantage of multi-omics methodologies in both of these settings is that omics approaches are unsupervised and unbiased to a priori hypotheses, making omics useful tools to confirm drug action, reveal new insights into compound activity, and discover new avenues for inquiry. This review summarizes the application of Mycobacterium tuberculosis omics technologies to the early stages of tuberculosis antimicrobial drug discovery.

scholarly journals High-throughput small molecule screen identifies inhibitors of aberrant chromatin accessibility

2016 ◽  
Vol 113 (11) ◽  
pp. 3018-3023 ◽  
Author(s):  
Samantha G. Pattenden ◽  
Jeremy M. Simon ◽  
Aminah Wali ◽  
Chatura N. Jayakody ◽  
Jacob Troutman ◽  
...  
Keyword(s):  
Small Molecule ◽  
High Throughput ◽  
Histone Deacetylase Inhibitors ◽  
A Priori ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Loss Of Function ◽  
Chromatin Signature ◽  
Biologically Relevant ◽  
Small Molecule Screening

Mutations in chromatin-modifying proteins and transcription factors are commonly associated with a wide variety of cancers. Through gain- or loss-of-function, these mutations may result in characteristic alterations of accessible chromatin, indicative of shifts in the landscape of regulatory elements genome-wide. The identification of compounds that reverse a specific chromatin signature could lead to chemical probes or potential therapies. To explore whether chromatin accessibility could serve as a platform for small molecule screening, we adapted formaldehyde-assisted isolation of regulatory elements (FAIRE), a chemical method to enrich for nucleosome-depleted genomic regions, as a high-throughput, automated assay. After demonstrating the validity and robustness of this approach, we applied this method to screen an epigenetically targeted small molecule library by evaluating regions of aberrant nucleosome depletion mediated by EWSR1-FLI1, the chimeric transcription factor critical for the bone and soft tissue tumor Ewing sarcoma. As a class, histone deacetylase inhibitors were greatly overrepresented among active compounds. These compounds resulted in diminished accessibility at targeted sites by disrupting transcription of EWSR1-FLI1. Capitalizing on precise differences in chromatin accessibility for drug discovery efforts offers significant advantages because it does not depend on the a priori selection of a single molecular target and may detect novel biologically relevant pathways.

scholarly journals High-Throughput Computational Search for Half-Metallic Oxides

Molecules ◽  
2020 ◽  
Vol 25 (9) ◽  
pp. 2010
Author(s):  
Laalitha S. I. Liyanage ◽  
Jagoda Sławińska ◽  
Priya Gopal ◽  
Stefano Curtarolo ◽  
Marco Fornari ◽  
...  
Keyword(s):  
Density Of States ◽  
High Throughput ◽  
Chemical Space ◽  
A Priori ◽  
Structural Formula ◽  
Inorganic Crystal Structure Database ◽  
Half Metallic ◽  
Half Metals ◽  
Metallic Oxides ◽  
Computational Search

Half metals are a peculiar class of ferromagnets that have a metallic density of states at the Fermi level in one spin channel and simultaneous semiconducting or insulating properties in the opposite one. Even though they are very desirable for spintronics applications, identification of robust half-metallic materials is by no means an easy task. Because their unusual electronic structures emerge from subtleties in the hybridization of the orbitals, there is no simple rule which permits to select a priori suitable candidate materials. Here, we have conducted a high-throughput computational search for half-metallic compounds. The analysis of calculated electronic properties of thousands of materials from the inorganic crystal structure database allowed us to identify potential half metals. Remarkably, we have found over two-hundred strong half-metallic oxides; several of them have never been reported before. Considering the fact that oxides represent an important class of prospective spintronics materials, we have discussed them in further detail. In particular, they have been classified in different families based on the number of elements, structural formula, and distribution of density of states in the spin channels. We are convinced that such a framework can help to design rules for the exploration of a vaster chemical space and enable the discovery of novel half-metallic oxides with properties on demand.

scholarly journals A Simple Strategy for Mitigating the Effect of Data Variability on the Identification of Active Chemotypes from High-Throughput Screening Data

2007 ◽  
Vol 12 (2) ◽  
pp. 276-284 ◽  
Author(s):  
Stephen R. Johnson ◽  
Ramesh Padmanabha ◽  
Wayne Vaccaro ◽  
Mark Hermsmeier ◽  
Angela Cacace ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
High Throughput ◽  
High Throughput Screening ◽  
A Priori ◽  
Response Curves ◽  
Simple Strategy ◽  
Data Variability ◽  
The Individual ◽  
Protein Supply

Among the several goals of a high-throughput screening campaign is the identification of as many active chemotypes as possible for further evaluation. Often, however, the number of concentration response curves (e.g., IC50s or Kis) that can be collected following a primary screen is limited by practical constraints such as protein supply, screening workload, and so forth. One possible approach to this dilemma is to cluster the hits from the primary screen and sample only a few compounds from each cluster. This introduces the question as to how many compounds must be selected from a cluster to ensure that an active compound is identified, if it exists at all. This article seeks to address this question using a Monte Carlo simulation in which the dependence of the success of sampling is directly linked to screening data variability. Furthermore, the authors demonstrate that the use of replicated compounds in the screening collection can easily assess this variability and provide a priori guidance to the screener and chemist as to the extent of sampling required to maximize chemotype identification during the triage process. The individual steps of the Monte Carlo simulation provide insight into the correspondence between the percentage inhibition and eventual IC50 curves.

scholarly journals High-throughput dynamic BH3 profiling may quickly and accurately predict effective therapies in solid tumors

2020 ◽  
Vol 13 (636) ◽  
pp. eaay1451 ◽  
Author(s):  
Patrick D. Bhola ◽  
Eman Ahmed ◽  
Jennifer L. Guerriero ◽  
Ewa Sicinska ◽  
Emily Su ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Tumor Cells ◽  
High Throughput ◽  
Tumor Regression ◽  
Ex Vivo ◽  
A Priori ◽  
Genetically Engineered ◽  
Chemical Inducers ◽  
Ex Vivo Culture ◽  
Pdx Models

Despite decades of effort, the sensitivity of patient tumors to individual drugs is often not predictable on the basis of molecular markers alone. Therefore, unbiased, high-throughput approaches to match patient tumors to effective drugs, without requiring a priori molecular hypotheses, are critically needed. Here, we improved upon a method that we previously reported and developed called high-throughput dynamic BH3 profiling (HT-DBP). HT-DBP is a microscopy-based, single-cell resolution assay that enables chemical screens of hundreds to thousands of candidate drugs on freshly isolated tumor cells. The method identifies chemical inducers of mitochondrial apoptotic signaling, a mechanism of cell death. HT-DBP requires only 24 hours of ex vivo culture, which enables a more immediate study of fresh primary tumor cells and minimizes adaptive changes that occur with prolonged ex vivo culture. Effective compounds identified by HT-DBP induced tumor regression in genetically engineered and patient-derived xenograft (PDX) models of breast cancer. We additionally found that chemical vulnerabilities changed as cancer cells expanded ex vivo. Furthermore, using PDX models of colon cancer and resected tumors from colon cancer patients, our data demonstrated that HT-DBP could be used to generate personalized pharmacotypes. Thus, HT-DBP appears to be an ex vivo functional method with sufficient scale to simultaneously function as a companion diagnostic, therapeutic personalization, and discovery tool.

scholarly journals Diverse and widespread contamination evident in the unmapped depths of high throughput sequencing data

2014 ◽  
Author(s):  
Richard W Lusk
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
A Priori ◽  
Low Frequency ◽  
Negative Control ◽  
Sequencing Data ◽  
Single Experiment ◽  
High Throughput Sequencing Data ◽  
Potential Contaminant ◽  
Recent Claim

BackgroundTrace quantities of contaminating DNA are widespread in the laboratory environment, but their presence has received little attention in the context of high throughput sequencing. This issue is highlighted by recent works that have rested controversial claims upon sequencing data that appear to support the presence of unexpected exogenous species.ResultsI used reads that preferentially aligned to alternate genomes to infer the distribution of potential contaminant species in a set of independent sequencing experiments. I confirmed that dilute samples are more exposed to contaminating DNA, and, focusing on four single-cell sequencing experiments, found that these contaminants appear to originate from a wide diversity of clades. Although negative control libraries prepared from "blank" samples recovered the highest-frequency contaminants, low-frequency contaminants, which appeared to make heterogeneous contributions to samples prepared in parallel within a single experiment, were not well controlled for. I used these results to show that, despite heavy replication and plausible controls, contamination can explain all of the observations used to support a recent claim that complete genes pass from food to human blood.ConclusionsContamination must be considered a potential source of signals of exogenous species in sequencing data, even if these signals are replicated in independent experiments, vary across conditions, or indicate a species which seems a priori unlikely to contaminate. Negative control libraries processed in parallel are essential to control for contaminant DNAs, but their limited ability to recover low-frequency contaminants must be recognized.

scholarly journals Integrating continuous hypermutation with high-throughput screening for optimization of cis,cis-muconic acid production in yeast

2020 ◽  
Author(s):  
Emil D. Jensen ◽  
Francesca Ambri ◽  
Marie B. Bendtsen ◽  
Alex A. Javanpour ◽  
Chang C. Liu ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Directed Evolution ◽  
High Throughput ◽  
High Throughput Screening ◽  
Biosynthetic Pathway ◽  
A Priori ◽  
Enzymatic Reaction ◽  
Search Space ◽  
Muconic Acid ◽  
Metabolic Reactions

SummaryDirected evolution is a powerful method to optimize proteins and metabolic reactions towards user-defined goals. It usually involves subjecting genes or pathways to iterative rounds of mutagenesis, selection, and amplification. While powerful, systematic searches through large sequence-spaces is a labor-intensive task, and can be further limited by a priori knowledge about the optimal initial search space, and/or limits in terms of screening throughput. Here we demonstrate an integrated directed evolution workflow for metabolic pathway enzymes that continuously generates enzyme variants using the recently developed orthogonal replication system, OrthoRep, and screens for optimal performance in high-throughput using a transcription factor-based biosensor. We demonstrate the strengths of this workflow by evolving a ratelimiting enzymatic reaction of the biosynthetic pathway for cis,cis-muconic acid (CCM), a precursor used for bioplastic and coatings, in Saccharomyces cerevisiae. After two weeks of simply iterating between passaging of cells to generate variant enzymes via OrthoRep and high-throughput sorting of best-performing variants using a transcription factor-based biosensor for CCM, we ultimately identified variant enzymes improving CCM titers >13-fold compared to reference enzymes. Taken together, the combination of synthetic biology tools as adopted in this study, is an efficient approach to debottleneck repetitive workflows associated with directed evolution of metabolic enzymes.

scholarly journals A priori Considerations When Conducting High‐Throughput Amplicon‐Based Sequence Analysis

ael ◽  
2016 ◽  
Vol 1 (1) ◽  
pp. 150010 ◽  
Author(s):  
Aditi Sengupta ◽  
Warren A. Dick
Keyword(s):  
Sequence Analysis ◽  
High Throughput ◽  
A Priori
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