scholarly journals Image-based high-throughput mapping of TGF-β-induced phosphocomplexes at a single-cell level

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Peter Lönn ◽  
Rasel A. Al-Amin ◽  
Ehsan Manouchehri Doulabi ◽  
Johan Heldin ◽  
Radiosa Gallini ◽  
...  
Keyword(s):  
Single Cell ◽  
High Throughput ◽  
Protein Interactions ◽  
Posttranslational Modifications ◽  
Large Scale ◽  
Cell Cycle Progression ◽  
Drug Effects ◽  
Automated System ◽  
Phosphatase Inhibitors ◽  
Dynamic Events

AbstractProtein interactions and posttranslational modifications orchestrate cellular responses to e.g. cytokines and drugs, but it has been difficult to monitor these dynamic events in high-throughput. Here, we describe a semi-automated system for large-scale in situ proximity ligation assays (isPLA), combining isPLA in microtiter wells with automated microscopy and computer-based image analysis. Phosphorylations and interactions are digitally recorded along with subcellular morphological features. We investigated TGF-β-responsive Smad2 linker phosphorylations and complex formations over time and across millions of individual cells, and we relate these events to cell cycle progression and local cell crowding via measurements of DNA content and nuclear size of individual cells, and of their relative positions. We illustrate the suitability of this protocol to screen for drug effects using phosphatase inhibitors. Our approach expands the scope for image-based single cell analyses by combining observations of protein interactions and modifications with morphological details of individual cells at high throughput.

scholarly journals Deciphering and engineering chromodomain-methyllysine peptide recognition

2018 ◽  
Vol 4 (11) ◽  
pp. eaau1447 ◽  
Author(s):  
Ryan Hard ◽  
Nan Li ◽  
Wei He ◽  
Brian Ross ◽  
Gary C. H. Mo ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Posttranslational Modifications ◽  
Large Scale ◽  
Regulation Of Gene Expression ◽  
Live Cells ◽  
Lysine Methylation ◽  
Dynamic Regulation ◽  
Peptide Recognition ◽  
Protein Functions ◽  
Domain Peptide

Posttranslational modifications (PTMs) play critical roles in regulating protein functions and mediating protein-protein interactions. An important PTM is lysine methylation that orchestrates chromatin modifications and regulates functions of non-histone proteins. Methyllysine peptides are bound by modular domains, of which chromodomains are representative. Here, we conducted the first large-scale study of chromodomains in the human proteome interacting with both histone and non-histone methyllysine peptides. We observed significant degenerate binding between chromodomains and histone peptides, i.e., different histone sites can be recognized by the same set of chromodomains, and different chromodomains can share similar binding profiles to individual histone sites. Such degenerate binding is not dictated by amino acid sequence or PTM motif but rather rooted in the physiochemical properties defined by the PTMs on the histone peptides. This molecular mechanism is confirmed by the accurate prediction of the binding specificity using a computational model that captures the structural and energetic patterns of the domain-peptide interaction. To further illustrate the power and accuracy of our model, we used it to effectively engineer an exceptionally strong H3K9me3-binding chromodomain and to label H3K9me3 in live cells. This study presents a systematic approach to deciphering domain-peptide recognition and reveals a general principle by which histone modifications are interpreted by reader proteins, leading to dynamic regulation of gene expression and other biological processes.

scholarly journals An ultrasensitive fiveplex activity assay for cellular kinases

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Christian M. Smolko ◽  
Kevin A. Janes
Keyword(s):  
Protein Kinase ◽  
Protein Interactions ◽  
Posttranslational Modifications ◽  
Large Scale ◽  
Cell Types ◽  
Mitogen Activated Protein Kinase ◽  
Activity Measurement ◽  
Kinase Substrate ◽  
Iκb Kinase ◽  
Mitogen Activated Protein

AbstractProtein kinases are enzymes whose abundance, protein-protein interactions, and posttranslational modifications together determine net signaling activity in cells. Large-scale data on cellular kinase activity are limited, because existing assays are cumbersome, poorly sensitive, low throughput, and restricted to measuring one kinase at a time. Here, we surmount the conventional hurdles of activity measurement with a multiplexing approach that leverages the selectivity of individual kinase-substrate pairs. We demonstrate proof of concept by designing an assay that jointly measures activity of five pleiotropic signaling kinases: Akt, IκB kinase (IKK), c-jun N-terminal kinase (JNK), mitogen-activated protein kinase (MAPK)-extracellular regulated kinase kinase (MEK), and MAPK-activated protein kinase-2 (MK2). The assay operates in a 96-well format and specifically measures endogenous kinase activation with coefficients of variation less than 20%. Multiplex tracking of kinase-substrate pairs reduces input requirements by 25-fold, with ~75 µg of cellular extract sufficient for fiveplex activity profiling. We applied the assay to monitor kinase signaling during coxsackievirus B3 infection of two different host-cell types and identified multiple differences in pathway dynamics and coordination that warrant future study. Because the Akt–IKK–JNK–MEK–MK2 pathways regulate many important cellular functions, the fiveplex assay should find applications in inflammation, environmental-stress, and cancer research.

scholarly journals Comparison of high-throughput single-cell RNA sequencing data processing pipelines

2020 ◽  
Author(s):  
Mingxuan Gao ◽  
Mingyi Ling ◽  
Xinwei Tang ◽  
Shun Wang ◽  
Xu Xiao ◽  
...  
Keyword(s):  
Data Processing ◽  
Single Cell ◽  
Rna Sequencing ◽  
High Throughput ◽  
Large Scale ◽  
Evaluation Framework ◽  
Integrated Analysis ◽  
Sequencing Data ◽  
Single Experiment ◽  
Single Cell Rna Sequencing

Abstract With the development of single-cell RNA sequencing (scRNA-seq) technology, it has become possible to perform large-scale transcript profiling for tens of thousands of cells in a single experiment. Many analysis pipelines have been developed for data generated from different high-throughput scRNA-seq platforms, bringing a new challenge to users to choose a proper workflow that is efficient, robust and reliable for a specific sequencing platform. Moreover, as the amount of public scRNA-seq data has increased rapidly, integrated analysis of scRNA-seq data from different sources has become increasingly popular. However, it remains unclear whether such integrated analysis would be biassed if the data were processed by different upstream pipelines. In this study, we encapsulated seven existing high-throughput scRNA-seq data processing pipelines with Nextflow, a general integrative workflow management framework, and evaluated their performance in terms of running time, computational resource consumption and data analysis consistency using eight public datasets generated from five different high-throughput scRNA-seq platforms. Our work provides a useful guideline for the selection of scRNA-seq data processing pipelines based on their performance on different real datasets. In addition, these guidelines can serve as a performance evaluation framework for future developments in high-throughput scRNA-seq data processing.

scholarly journals Aging Atlas: a multi-omics database for aging biology

2020 ◽  
Vol 49 (D1) ◽  
pp. D825-D830 ◽  
Author(s):  
◽  
Guang-Hui Liu ◽  
Yiming Bao ◽  
Jing Qu ◽  
Weiqi Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
High Throughput ◽  
Large Scale ◽  
Wide Spectrum ◽  
Molecular Profile ◽  
Aging Research ◽  
Related Data ◽  
Age Related ◽  
Wide Range

Abstract Organismal aging is driven by interconnected molecular changes encompassing internal and extracellular factors. Combinational analysis of high-throughput ‘multi-omics’ datasets (gathering information from genomics, epigenomics, transcriptomics, proteomics, metabolomics and pharmacogenomics), at either populational or single-cell levels, can provide a multi-dimensional, integrated profile of the heterogeneous aging process with unprecedented throughput and detail. These new strategies allow for the exploration of the molecular profile and regulatory status of gene expression during aging, and in turn, facilitate the development of new aging interventions. With a continually growing volume of valuable aging-related data, it is necessary to establish an open and integrated database to support a wide spectrum of aging research. The Aging Atlas database aims to provide a wide range of life science researchers with valuable resources that allow access to a large-scale of gene expression and regulation datasets created by various high-throughput omics technologies. The current implementation includes five modules: transcriptomics (RNA-seq), single-cell transcriptomics (scRNA-seq), epigenomics (ChIP-seq), proteomics (protein–protein interaction), and pharmacogenomics (geroprotective compounds). Aging Atlas provides user-friendly functionalities to explore age-related changes in gene expression, as well as raw data download services. Aging Atlas is freely available at https://bigd.big.ac.cn/aging/index.

scholarly journals Ultra-High-Throughput Screening of Natural Product Extracts to Identify Proapoptotic Inhibitors of Bcl-2 Family Proteins

2014 ◽  
Vol 19 (8) ◽  
pp. 1201-1211 ◽  
Author(s):  
Christian A. Hassig ◽  
Fu-Yue Zeng ◽  
Paul Kung ◽  
Mehrak Kiankarimi ◽  
Sylvia Kim ◽  
...  
Keyword(s):  
Natural Product ◽  
High Throughput ◽  
Protein Interactions ◽  
High Throughput Screening ◽  
Large Scale ◽  
Active Components ◽  
Cellular Functions ◽  
Cellular Assays ◽  
Bioassay Guided Fractionation ◽  
Luminescent Assay

Antiapoptotic Bcl-2 family proteins are validated cancer targets composed of six related proteins. From a drug discovery perspective, these are challenging targets that exert their cellular functions through protein-protein interactions (PPIs). Although several isoform-selective inhibitors have been developed using structure-based design or high-throughput screening (HTS) of synthetic chemical libraries, no large-scale screen of natural product collections has been reported. A competitive displacement fluorescence polarization (FP) screen of nearly 150,000 natural product extracts was conducted against all six antiapoptotic Bcl-2 family proteins using fluorochrome-conjugated peptide ligands that mimic functionally relevant PPIs. The screens were conducted in 1536-well format and displayed satisfactory overall HTS statistics, with Z′-factor values ranging from 0.72 to 0.83 and a hit confirmation rate between 16% and 64%. Confirmed active extracts were orthogonally tested in a luminescent assay for caspase-3/7 activation in tumor cells. Active extracts were resupplied, and effort toward the isolation of pure active components was initiated through iterative bioassay-guided fractionation. Several previously described altertoxins were isolated from a microbial source, and the pure compounds demonstrate activity in both Bcl-2 FP and caspase cellular assays. The studies demonstrate the feasibility of ultra-high-throughput screening using natural product sources and highlight some of the challenges associated with this approach.

scholarly journals Multi-ATOM: Ultrahigh-throughput single-cell quantitative phase imaging with subcellular resolution

2019 ◽  
Author(s):  
Kelvin C. M. Lee ◽  
Andy K. S. Lau ◽  
Anson H. L. Tang ◽  
Maolin Wang ◽  
Aaron T. Y. Mok ◽  
...  
Keyword(s):  
Single Cell ◽  
High Throughput ◽  
Large Scale ◽  
Phase Retrieval ◽  
Leukemic Cells ◽  
Phase Imaging ◽  
Label Free ◽  
Quantitative Phase Imaging ◽  
Phase Gradient ◽  
Quantitative Phase

AbstractA growing body of evidence has substantiated the significance of quantitative phase imaging (QPI) in enabling cost-effective and label-free cellular assay, which provides useful insights into understanding biophysical properties of cells and their roles in cellular functions. However, available QPI modalities are limited by the loss of imaging resolution at high throughput and thus run short of sufficient statistical power at the single cell precision to define cell identities in a large and heterogeneous population of cells – hindering their utility in mainstream biomedicine and biology. Here we present a new QPI modality, coined multi-ATOM that captures and processes quantitative label-free single-cell images at ultra-high throughput without compromising sub-cellular resolution. We show that multi-ATOM, based upon ultrafast phase-gradient encoding, outperforms state-of-the-art QPI in permitting robust phase retrieval at a QPI throughput of >10,000 cell/sec, bypassing the need for interferometry which inevitably compromises QPI quality under ultrafast operation. We employ multi-ATOM for large-scale, label-free, multi-variate, cell-type classification (e.g. breast cancer sub-types, and leukemic cells versus peripheral blood mononuclear cells) at high accuracy (>94%). Our results suggest that multi-ATOM could empower new strategies in large-scale biophysical single-cell analysis with applications in biology and enriching disease diagnostics.

scholarly journals Comparison of High-Throughput Single-Cell RNA Sequencing Data Processing Pipelines

2020 ◽  
Author(s):  
Mingxuan Gao ◽  
Mingyi Ling ◽  
Xinwei Tang ◽  
Shun Wang ◽  
Xu Xiao ◽  
...  
Keyword(s):  
Data Processing ◽  
Single Cell ◽  
Rna Sequencing ◽  
High Throughput ◽  
Large Scale ◽  
Evaluation Framework ◽  
Integrated Analysis ◽  
Sequencing Data ◽  
Single Experiment ◽  
Single Cell Rna Sequencing

AbstractWith the development of single-cell RNA sequencing (scRNA-seq) technology, it has become possible to perform large-scale transcript profiling for tens of thousands of cells in a single experiment. Many analysis pipelines have been developed for data generated from different high-throughput scRNA-seq platforms, bringing a new challenge to users to choose a proper workflow that is efficient, robust and reliable for a specific sequencing platform. Moreover, as the amount of public scRNA-seq data has increased rapidly, integrated analysis of scRNA-seq data from different sources has become increasingly popular. How-ever, it remains unclear whether such integrated analysis would be biased if the data were processed by different upstream pipelines. In this study, we encapsulated seven existing high-throughput scRNA-seq data processing pipelines with Nextflow, a general integrative workflow management framework, and evaluated their performances in terms of running time, computational resource consumption, and data processing consistency using nine public datasets generated from five different high-throughput scRNA-seq platforms. Our work provides a useful guideline for the selection of scRNA-seq data processing pipelines based on their performances on different real datasets. In addition, these guidelines can serve as a performance evaluation framework for future developments in high-throughput scRNA-seq data processing.

scholarly journals An automated system for high-throughput single cell-based breeding

2013 ◽  
Vol 3 (1) ◽  
Author(s):  
Nobuo Yoshimoto ◽  
Akiko Kida ◽  
Xu Jie ◽  
Masaya Kurokawa ◽  
Masumi Iijima ◽  
...  
Keyword(s):  
Single Cell ◽  
High Throughput ◽  
Automated System

scholarly journals High Throughput strategies Aimed at Closing the GAP in Our Knowledge of Rho GTPase Signaling

Cells ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 1430
Author(s):  
Manel Dahmene ◽  
Laura Quirion ◽  
Mélanie Laurin
Keyword(s):  
High Throughput ◽  
Protein Interactions ◽  
Rho Gtpases ◽  
High Throughput Screening ◽  
Large Scale ◽  
Rho Gtpase ◽  
Cellular Migration ◽  
Cell Junctions ◽  
System Level ◽  
Culture Models

Since their discovery, Rho GTPases have emerged as key regulators of cytoskeletal dynamics. In humans, there are 20 Rho GTPases and more than 150 regulators that belong to the RhoGEF, RhoGAP, and RhoGDI families. Throughout development, Rho GTPases choregraph a plethora of cellular processes essential for cellular migration, cell–cell junctions, and cell polarity assembly. Rho GTPases are also significant mediators of cancer cell invasion. Nevertheless, to date only a few molecules from these intricate signaling networks have been studied in depth, which has prevented appreciation for the full scope of Rho GTPases’ biological functions. Given the large complexity involved, system level studies are required to fully grasp the extent of their biological roles and regulation. Recently, several groups have tackled this challenge by using proteomic approaches to map the full repertoire of Rho GTPases and Rho regulators protein interactions. These studies have provided in-depth understanding of Rho regulators specificity and have contributed to expand Rho GTPases’ effector portfolio. Additionally, new roles for understudied family members were unraveled using high throughput screening strategies using cell culture models and mouse embryos. In this review, we highlight theses latest large-scale efforts, and we discuss the emerging opportunities that may lead to the next wave of discoveries.

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