scholarly journals Optimizing multiplexed imaging experimental design through tissue spatial segregation estimation

2021 ◽  
Author(s):  
Pierre Bost ◽  
Daniel Schulz ◽  
Stefanie Engler ◽  
Clive Wasserfall ◽  
Bernd Bodenmiller
Keyword(s):  
Experimental Design ◽  
Simultaneous Detection ◽  
Cell Types ◽  
Spatial Segregation ◽  
Imaging Studies ◽  
Statistical Framework ◽  
Tumor Tissues ◽  
Multiplexed Imaging ◽  
Improved Design

Recent advances in multiplexed imaging methods allow simultaneous detection of dozens of proteins or RNAs enabling deep spatial characterization of both healthy and tumor tissues. Parameters for design of optimal sequencing-based experiments have been established, but such parameters are lacking for multiplex imaging studies. Here, using a spatial transcriptomic atlas of healthy and tumor human tissues, we developed a new statistical framework that determines the number of fields of view necessary to accurately identify all cell types that are part of the tissue. Using this strategy on imaging mass cytometry data, we identified a measurement of tissue spatial segregation that enables optimal experimental design and that is technology invariant. This strategy will enable significantly improved design of multiplexed imaging studies.

scholarly journals SuperCT: A supervised-learning-framework to enhance the characterization of single-cell transcriptomic profiles

2018 ◽  
Author(s):  
Peng Xie ◽  
Mingxuan Gao ◽  
Chunming Wang ◽  
Pawan Noel ◽  
Chaoyong Yang ◽  
...  
Keyword(s):  
Single Cell ◽  
Dimensional Space ◽  
Expression Profiles ◽  
Cell Types ◽  
Learning Framework ◽  
Tumor Tissues ◽  
Low Dimensional ◽  
Different Cell Types ◽  
Technical Framework

AbstractCharacterization of individual cell types is fundamental to the study of multicellular samples such as tumor tissues. Single-cell RNAseq techniques, which allow high-throughput expression profiling of individual cells, have significantly advanced our ability of this task. Currently, most of the scRNA-seq data analyses are commenced with unsupervised clustering of cells followed by visualization of clusters in a low-dimensional space. Clusters are often assigned to different cell types based on canonical markers. However, the efficiency of characterizing the known cell types in this way is low and limited by the investigator[s] knowledge. In this study, we present a technical framework of training the expandable supervised-classifier in order to reveal the single-cell identities based on their RNA expression profiles. Using multiple scRNA-seq datasets we demonstrate the superior accuracy, robustness, compatibility and expandability of this new solution compared to the traditional methods. We use two examples of model upgrade to demonstrate how the projected evolution of the cell-type classifier is realized.

scholarly journals A statistical simulator scDesign for rational scRNA-seq experimental design

2018 ◽  
Author(s):  
Wei Vivian Li ◽  
Jingyi Jessica Li
Keyword(s):  
Biological Sciences ◽  
Gene Expression ◽  
Experimental Design ◽  
Method Development ◽  
Cell Types ◽  
R Package ◽  
Computational Method ◽  
Statistical Framework ◽  
Reduction Methods ◽  
Sequencing Platforms

AbstractMotivationSingle-cell RNA-sequencing (scRNA-seq) has revolutionized biological sciences by revealing genome-wide gene expression levels within individual cells. However, a critical challenge faced by researchers is how to optimize the choices of sequencing platforms, sequencing depths, and cell numbers in designing scRNA-seq experiments, so as to balance the exploration of the depth and breadth of transcriptome information.ResultsHere we present a flexible and robust simulator, scDesign, the first statistical framework for researchers to quantitatively assess practical scRNA-seq experimental design in the context of differential gene expression analysis. In addition to experimental design, scDesign also assists computational method development by generating high-quality synthetic scRNA-seq datasets under customized experimental settings. In an evaluation based on 17 cell types and six different protocols, scDesign outperformed four state-of-the-art scRNA-seq simulation methods and led to rational experimental design. In addition, scDesign demonstrates reproducibility across biological replicates and independent studies. We also discuss the performance of multiple differential expression and dimension reduction methods based on the protocol-dependent scRNA-seq data generated by scDesign. scDesign is expected to be an effective bioinformatic tool that assists rational scRNA-seq experiment design based on specific research goals and compares various scRNA-seq computational methods.AvailabilityWe have implemented our method in the R package scDesign, which is freely available at https://github.com/Vivianstats/[email protected]

scholarly journals Morphological and Ultrastructural Characterization of Hemocytes in an Insect Model, the Hematophagous Dipetalogaster maxima (Hemiptera: Reduviidae)

Insects ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 640
Author(s):  
Natalia R. Moyetta ◽  
Fabián O. Ramos ◽  
Jimena Leyria ◽  
Lilián E. Canavoso ◽  
Leonardo L. Fruttero
Keyword(s):  
Cell Biology ◽  
Cell Types ◽  
Transmission Electron ◽  
Ultrastructural Characterization ◽  
Current Classification ◽  
Contrast Microscopy ◽  
First Time ◽  
Controversial Aspect

Hemocytes, the cells present in the hemolymph of insects and other invertebrates, perform several physiological functions, including innate immunity. The current classification of hemocyte types is based mostly on morphological features; however, divergences have emerged among specialists in triatomines, the insect vectors of Chagas’ disease (Hemiptera: Reduviidae). Here, we have combined technical approaches in order to characterize the hemocytes from fifth instar nymphs of the triatomine Dipetalogaster maxima. Moreover, in this work we describe, for the first time, the ultrastructural features of D. maxima hemocytes. Using phase contrast microscopy of fresh preparations, five hemocyte populations were identified and further characterized by immunofluorescence, flow cytometry and transmission electron microscopy. The plasmatocytes and the granulocytes were the most abundant cell types, although prohemocytes, adipohemocytes and oenocytes were also found. This work sheds light on a controversial aspect of triatomine cell biology and physiology setting the basis for future in-depth studies directed to address hemocyte classification using non-microscopy-based markers.

scholarly journals Connectivity characterization of the mouse basolateral amygdalar complex

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Houri Hintiryan ◽  
Ian Bowman ◽  
David L. Johnson ◽  
Laura Korobkova ◽  
Muye Zhu ◽  
...  
Keyword(s):  
Granular Cell ◽  
Cell Types ◽  
Projection Neurons ◽  
Cell Type ◽  
Connectivity Map ◽  
Analysis Techniques ◽  
Domain Specific ◽  
Cell Type Specific ◽  
Unique Domain

AbstractThe basolateral amygdalar complex (BLA) is implicated in behaviors ranging from fear acquisition to addiction. Optogenetic methods have enabled the association of circuit-specific functions to uniquely connected BLA cell types. Thus, a systematic and detailed connectivity profile of BLA projection neurons to inform granular, cell type-specific interrogations is warranted. Here, we apply machine-learning based computational and informatics analysis techniques to the results of circuit-tracing experiments to create a foundational, comprehensive BLA connectivity map. The analyses identify three distinct domains within the anterior BLA (BLAa) that house target-specific projection neurons with distinguishable morphological features. We identify brain-wide targets of projection neurons in the three BLAa domains, as well as in the posterior BLA, ventral BLA, posterior basomedial, and lateral amygdalar nuclei. Inputs to each nucleus also are identified via retrograde tracing. The data suggests that connectionally unique, domain-specific BLAa neurons are associated with distinct behavior networks.

Synthesis and characterization of 19F NMR chelators for measurement of cytosolic free Ca

1987 ◽  
Vol 252 (4) ◽  
pp. C441-C449 ◽  
Author(s):  
L. A. Levy ◽  
E. Murphy ◽  
R. E. London
Keyword(s):  
Chemical Shifts ◽  
Cell Types ◽  
Free Calcium ◽  
Tetraacetic Acid ◽  
Nmr Studies ◽  
Cytosolic Free Calcium ◽  
Fluorine Nmr ◽  
Dissociation Constant Kd

Fluorine 19 nuclear magnetic resonance (NMR) studies of intracellular fluorinated calcium chelators provide a useful strategy for the determination of cytosolic free calcium levels in cells and perfused organs. However, the fluorinated chelator with the highest affinity for calcium ions which has been described to date. 1,2-bis-(2-amino-5-fluorophenoxy)ethane-N,N,N',N'-tetraacetic acid (5FBAPTA), exhibits a dissociation constant (Kd) value 5- to 10-fold greater than the intracellular calcium concentration levels in most cell types, thus limiting the ability of fluorine NMR to report these concentrations reliably. We have consequently designed and synthesized several fluorinated calcium chelators with higher affinity for calcium. The best of these, 2-(2-amino-4-methyl-5-fluorophenoxy)-methyl-8 aminoquinidine-N,N,N',N'-tetraacetic acid (quinMF), has a Kd value approximately 10 times lower than that of 5FBAPTA. Several of the newly synthesized indicators have different chemical shifts for the calcium complexed and uncomplexed chelators to allow the simultaneous use of two indicators. In addition to providing information about the level of cytosolic free calcium, chelators containing a quinoline ring exhibit considerable sensitivity to magnesium levels and hence have potential application for the determination of cytosolic-magnesium concentrations. Application of these chelators is illustrated by determination of the cytosolic-free calcium level in erythrocytes. Use of quinMF, the chelator with the lowest Kd value, gives a calcium value of 25-30 nM.

scholarly journals Ostm1 from Mouse to Human: Insights into Osteoclast Maturation

2020 ◽  
Vol 21 (16) ◽  
pp. 5600 ◽  
Author(s):  
Jean Vacher ◽  
Michael Bruccoleri ◽  
Monica Pata
Keyword(s):  
Bone Formation ◽  
Bone Mass ◽  
Bone Fractures ◽  
Bone Development ◽  
Bone Matrix ◽  
Adult Life ◽  
Cell Types ◽  
Severe Form ◽  
Isolation And Characterization

The maintenance of bone mass is a dynamic process that requires a strict balance between bone formation and resorption. Bone formation is controlled by osteoblasts, while osteoclasts are responsible for resorption of the bone matrix. The opposite functions of these cell types have to be tightly regulated not only during normal bone development, but also during adult life, to maintain serum calcium homeostasis and sustain bone integrity to prevent bone fractures. Disruption of the control of bone synthesis or resorption can lead to an over accumulation of bone tissue in osteopetrosis or conversely to a net depletion of the bone mass in osteoporosis. Moreover, high levels of bone resorption with focal bone formation can cause Paget’s disease. Here, we summarize the steps toward isolation and characterization of the osteopetrosis associated trans-membrane protein 1 (Ostm1) gene and protein, essential for proper osteoclast maturation, and responsible when mutated for the most severe form of osteopetrosis in mice and humans.

Optimized screen-printing and SEM-FIB characterization of YSZ thin films for Solid Oxide Fuel Cells and gas sensors devices

2004 ◽  
Vol 822 ◽  
Author(s):  
A. Morata ◽  
A. Tarancón ◽  
G. Dezanneau ◽  
F. Peiró ◽  
J. R. Morante
Keyword(s):  
Experimental Design ◽  
Screen Printing ◽  
Focused Ion Beam ◽  
Ion Beam ◽  
Deposition Process ◽  
Technological Parameters ◽  
Significant Information ◽  
Screen Printing Technique ◽  
Final Porosity

AbstractIn the present work, the screen printing technique has been used to deposit thick films of Zr0.84Y016O1.92 (8YSZ). In order to control the final porosity in view of a specific application (SOFCs or gas sensor), an experimental design based on analysis of variances (ANOVA) has been carried out. From this, we were able to determine the influence of several technological parameters on films porosity and grain size. The films obtained have been analysed with both Scanning Electron Microscopy (SEM) and Focused Ion Beam (FIB) combined with SEM. We show that only the combination of experimental design and advanced observation technique such as Focused Ion Beam allowed us to extract significant information for the improvement of the deposition process.

scholarly journals Systematic comparison of high-throughput single-cell RNA-seq methods for immune cell profiling

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Tracy M. Yamawaki ◽  
Daniel R. Lu ◽  
Daniel C. Ellwanger ◽  
Dev Bhatt ◽  
Paolo Manzanillo ◽  
...  
Keyword(s):  
Single Cell ◽  
High Throughput ◽  
Immune Cell ◽  
Cell Types ◽  
Data Interpretation ◽  
Detection Sensitivity ◽  
Rna Seq ◽  
Cell Recovery

Abstract Background Elucidation of immune populations with single-cell RNA-seq has greatly benefited the field of immunology by deepening the characterization of immune heterogeneity and leading to the discovery of new subtypes. However, single-cell methods inherently suffer from limitations in the recovery of complete transcriptomes due to the prevalence of cellular and transcriptional dropout events. This issue is often compounded by limited sample availability and limited prior knowledge of heterogeneity, which can confound data interpretation. Results Here, we systematically benchmarked seven high-throughput single-cell RNA-seq methods. We prepared 21 libraries under identical conditions of a defined mixture of two human and two murine lymphocyte cell lines, simulating heterogeneity across immune-cell types and cell sizes. We evaluated methods by their cell recovery rate, library efficiency, sensitivity, and ability to recover expression signatures for each cell type. We observed higher mRNA detection sensitivity with the 10x Genomics 5′ v1 and 3′ v3 methods. We demonstrate that these methods have fewer dropout events, which facilitates the identification of differentially-expressed genes and improves the concordance of single-cell profiles to immune bulk RNA-seq signatures. Conclusion Overall, our characterization of immune cell mixtures provides useful metrics, which can guide selection of a high-throughput single-cell RNA-seq method for profiling more complex immune-cell heterogeneity usually found in vivo.

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