scholarly journals Electrophysiology prediction of single neurons based on their morphology

2020 ◽  
Author(s):  
Mario Michiels
Keyword(s):  
Data Acquisition ◽  
Large Scale ◽  
Expert Knowledge ◽  
Large Data ◽  
Cell Types ◽  
Biophysical Model ◽  
Single Neurons ◽  
Regression Problem ◽  
Sophisticated User

AbstractElectrophysiology data acquisition of single neurons represents a key factor for the understanding of neuronal dynamics. However, the traditional method to acquire this data is through patch-clamp technology, which presents serious scalability flaws due to its slowness and complexity to record at fine-grained spatial precision (dendrites and axon).In silico biophysical models are therefore created for simulating hundreds of experiments that would be impractical to recreate in vitro. The optimal way to create these models is based on the knowledge of the morphological and electrical features for each neuron. Since large-scale data acquisition is often unfeasible for electrical data, previous expert knowledge can be used but it must have an acceptable degree of similarity with the type of neurons that we are trying to model.Here, we present a data-driven machine learning approach to predict the electrophysiological features of single neurons in case of only having their morphology available. To solve this multi-output regression problem, we use an artificial neural network that has the particularity of providing a probability distribution for every output feature, to incorporate uncertainty. Input data to train the model is obtained from from the Allen Cell Types database. The electrical properties can depend on the morphology, whose acquisition technology is highly automated and scalable so there exist large data sets of them. We also provide integrations with the BluePyOpt library to create a biophysical model using the original morphology and the predicted electrical features. Finally, we connect the resulting biophysical model with the Geppetto UI software to run all the simulations in a sophisticated user interface.

scholarly journals Modulating cell state to enhance suspension expansion of human pluripotent stem cells

2018 ◽  
Vol 115 (25) ◽  
pp. 6369-6374 ◽  
Author(s):  
Yonatan Y. Lipsitz ◽  
Curtis Woodford ◽  
Ting Yin ◽  
Jacob H. Hanna ◽  
Peter W. Zandstra
Keyword(s):  
Stem Cells ◽  
Pluripotent Stem Cells ◽  
Large Scale ◽  
Cell Types ◽  
Human Pluripotent Stem Cells ◽  
The Body ◽  
Altered Expression ◽  
Pancreatic Progenitors ◽  
Erk Inhibition

The development of cell-based therapies to replace missing or damaged tissues within the body or generate cells with a unique biological activity requires a reliable and accessible source of cells. Human pluripotent stem cells (hPSC) have emerged as a strong candidate cell source capable of extended propagation in vitro and differentiation to clinically relevant cell types. However, the application of hPSC in cell-based therapies requires overcoming yield limitations in large-scale hPSC manufacturing. We explored methods to convert hPSC to alternative states of pluripotency with advantageous bioprocessing properties, identifying a suspension-based small-molecule and cytokine combination that supports increased single-cell survival efficiency, faster growth rates, higher densities, and greater expansion than control hPSC cultures. ERK inhibition was found to be essential for conversion to this altered state, but once converted, ERK inhibition led to a loss of pluripotent phenotype in suspension. The resulting suspension medium formulation enabled hPSC suspension yields 5.7 ± 0.2-fold greater than conventional hPSC in 6 d, for at least five passages. Treated cells remained pluripotent, karyotypically normal, and capable of differentiating into all germ layers. Treated cells could also be integrated into directed differentiated strategies as demonstrated by the generation of pancreatic progenitors (NKX6.1+/PDX1+ cells). Enhanced suspension-yield hPSC displayed higher oxidative metabolism and altered expression of adhesion-related genes. The enhanced bioprocess properties of this alternative pluripotent state provide a strategy to overcome cell manufacturing limitations of hPSC.

scholarly journals Mass Generation, Neuron Labeling, and 3D Imaging of Minibrains

2021 ◽  
Vol 8 ◽  
Author(s):  
Subashika Govindan ◽  
Laura Batti ◽  
Samira F. Osterop ◽  
Luc Stoppini ◽  
Adrien Roux
Keyword(s):  
Large Scale ◽  
3D Imaging ◽  
Cell Types ◽  
Mixed Population ◽  
Projection Neurons ◽  
Neuron Morphology ◽  
Mass Generation ◽  
One Step ◽  
Human Ipsc

Minibrain is a 3D brain in vitro spheroid model, composed of a mixed population of neurons and glial cells, generated from human iPSC derived neural stem cells. Despite the advances in human 3D in vitro models such as aggregates, spheroids and organoids, there is a lack of labeling and imaging methodologies to characterize these models. In this study, we present a step-by-step methodology to generate human minibrain nurseries and novel strategies to subsequently label projection neurons, perform immunohistochemistry and 3D imaging of the minibrains at large multiplexable scales. To visualize projection neurons, we adapt viral transduction and to visualize the organization of cell types we implement immunohistochemistry. To facilitate 3D imaging of minibrains, we present here pipelines and accessories for one step mounting and clearing suitable for confocal microscopy. The pipelines are specifically designed in such a way that the assays can be multiplexed with ease for large-scale screenings using minibrains and other organoid models. Using the pipeline, we present (i) dendrite morphometric properties obtained from 3D neuron morphology reconstructions, (ii) diversity in neuron morphology, and (iii) quantified distribution of progenitors and POU3F2 positive neurons in human minibrains.

scholarly journals Mass Generation, Neuron Labelling and 3D Imaging of Minibrains

2020 ◽  
Author(s):  
Subashika Govindan ◽  
Laura Batti ◽  
Samira F Osterop ◽  
Luc Stoppini ◽  
Adrien Roux
Keyword(s):  
Large Scale ◽  
3D Imaging ◽  
Cell Types ◽  
Projection Neurons ◽  
Neuron Morphology ◽  
Mass Generation ◽  
One Step ◽  
Brain Organoid ◽  
Human Ipsc

AbstractMinibrain is a spherical in vitro 3D brain organoid model, composed of a mixed population of neurons and glial cells, generated from human iPSC derived neural stem cells. Despite the advances in human brain organoid models, there is a lack of labelling and imaging methodologies to characterize these models. In this study, we present a step-by-step methodology to generate human minibrain nurseries and novel strategies to subsequently label projection neurons, perform immunohistochemistry and 3D imaging of the minibrains at large multiplexable scales. To visualize projection neurons, we adapt viral transduction and to visualize the organization of cell types we implement immunohistochemistry. To facilitate 3D imaging of minibrains, we present here pipelines and accessories for one step mounting and clearing suitable for confocal microscopy. The pipelines are specifically designed in such a way that the assays can be multiplexed with ease for large-scale screenings using minibrains. Using the pipeline, we present i. dendrite morphometric properties obtained from 3D neuron morphology reconstructions and ii. distribution and quantification of cell types in 3D across whole mount organoids.

scholarly journals Microcarrier Screening and Evaluation for Dynamic Expansion of Human Periosteum-Derived Progenitor Cells in a Xenogeneic Free Medium

2021 ◽  
Vol 9 ◽  
Author(s):  
Kathleen Van Beylen ◽  
Ioannis Papantoniou ◽  
Jean-Marie Aerts
Keyword(s):  
Progenitor Cells ◽  
Cell Expansion ◽  
Progenitor Cell ◽  
Large Scale ◽  
Expansion Method ◽  
Cell Types ◽  
Free Medium ◽  
Efficient Expansion

An increasing need toward a more efficient expansion of adherent progenitor cell types arises with the advancements of cell therapy. The use of a dynamic expansion instead of a static planar expansion could be one way to tackle the challenges of expanding adherent cells at a large scale. Microcarriers are often reported as a biomaterial for culturing cells in suspension. However, the type of microcarrier has an effect on the cell expansion. In order to find an efficient expansion process for a specific adherent progenitor cell type, it is important to investigate the effect of the type of microcarrier on the cell expansion. Human periosteum-derived progenitor cells are extensively used in skeletal tissue engineering for the regeneration of bone defects. Therefore, we evaluated the use of different microcarriers on human periosteum-derived progenitor cells. In order to assess the potency, identity and viability of these cells after being cultured in the spinner flasks, this study performed several in vitro and in vivo analyses. The novelty of this work lies in the combination of screening different microcarriers for human periosteum-derived progenitor cells with in vivo assessments of the cells’ potency using the microcarrier that was selected as the most promising one. The results showed that expanding human periosteum-derived progenitor cells in spinner flasks using xeno-free medium and Star-Plus microcarriers, does not affect the potency, identity or viability of the cells. The potency of the cells was assured with an in vivo evaluation, where bone formation was achieved. In summary, this expansion method has the potential to be used for large scale cell expansion with clinical relevance.

scholarly journals An in vivo reporter for tracking lipid droplet dynamics in transparent zebrafish

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Dianne Lumaquin ◽  
Eleanor Johns ◽  
Emily Montal ◽  
Joshua M Weiss ◽  
David Ola ◽  
...  
Keyword(s):  
Nitric Oxide ◽  
Lipid Droplet ◽  
Lipid Droplets ◽  
Large Scale ◽  
Fluorescent Dyes ◽  
Cell Types ◽  
Structural Protein ◽  
Droplet Dynamics

Lipid droplets are lipid storage organelles found in nearly all cell types from adipocytes to cancer cells. Although increasingly implicated in disease, current methods to study lipid droplets in vertebrate models rely on static imaging or the use of fluorescent dyes, limiting investigation of their rapid in vivo dynamics. To address this, we created a lipid droplet transgenic reporter in whole animals and cell culture by fusing tdTOMATO to Perilipin-2 (PLIN2), a lipid droplet structural protein. Expression of this transgene in transparent casper zebrafish enabled in vivo imaging of adipose depots responsive to nutrient deprivation and high-fat diet. Simultaneously, we performed a large-scale in vitro chemical screen of 1280 compounds and identified several novel regulators of lipolysis in adipocytes. Using our Tg(-3.5ubb:plin2-tdTomato) zebrafish line, we validated several of these novel regulators and revealed an unexpected role for nitric oxide in modulating adipocyte lipid droplets. Similarly, we expressed the PLIN2-tdTOMATO transgene in melanoma cells and found that the nitric oxide pathway also regulated lipid droplets in cancer. This model offers a tractable imaging platform to study lipid droplets across cell types and disease contexts using chemical, dietary, or genetic perturbations.

scholarly journals Exploiting Generative Self-Supervised Learning For The Assessment of Biological Images With Lack of Annotations: A COVID-19 Case-Study

2021 ◽  
Author(s):  
Alessio Mascolini ◽  
Dario Cardamone ◽  
Francesco Ponzio ◽  
Santa Di Cataldo ◽  
Elisa Ficarra
Keyword(s):  
Cell Lines ◽  
Large Scale ◽  
Representation Learning ◽  
Cell Types ◽  
Learning Task ◽  
Generative Adversarial Networks ◽  
Support Vector ◽  
Biological Images ◽  
Compound Screening

Abstract Computer-aided analysis of biological images typically requires extensive training on large-scale annotated datasets, which is not viable in many situations. In this paper, we present GAN-DL, a Discriminator Learner based on the StyleGAN2 architecture, which we employ for self-supervised image representation learning in the case of fluorescent biological images. We show that Wasserstein Generative Adversarial Networks combined with linear Support Vector Machines enable high-throughput compound screening based on raw images. We demonstrate this by classifying active and inactive compounds tested for the inhibition of SARS-CoV-2 infection in VERO and HRCE cell lines. In contrast to previous methods, our deep learning-based approach does not require any annotation besides the one that is normally collected during the sample preparation process. We test our technique on the RxRx19a Sars-CoV-2 image collection. The dataset consists of fluorescent images that were generated to assess the ability of regulatory-approved or late-stage clinical trials compounds to modulate the in vitro infection from SARS-CoV-2 in both VERO and HRCE cell lines. We show that our technique can be exploited not only for classification tasks but also to effectively derive a dose-response curve for the tested treatments, in a self-supervised manner. Lastly, we demonstrate its generalization capabilities by successfully addressing a zero-shot learning task, consisting of the categorization of four different cell types of the RxRx1 fluorescent images collection.

scholarly journals Geometric Sketching Compactly Summarizes the Single-Cell Transcriptomic Landscape

2019 ◽  
Author(s):  
Brian Hie ◽  
Hyunghoon Cho ◽  
Benjamin DeMeo ◽  
Bryan Bryson ◽  
Bonnie Berger
Keyword(s):  
Single Cell ◽  
Large Scale ◽  
High Sensitivity ◽  
Cell Types ◽  
Small Subset ◽  
Data Set ◽  
Cord Blood Cells ◽  
Umbilical Cord Blood Cells ◽  
Inflammatory Macrophages

SUMMARYLarge-scale single-cell RNA-sequencing (scRNA-seq) studies that profile hundreds of thousands of cells are becoming increasingly common, overwhelming existing analysis pipelines. Here, we describe how to enhance and accelerate single-cell data analysis by summarizing the transcriptomic heterogeneity within a data set using a small subset of cells, which we refer to as a geometric sketch. Our sketches provide more comprehensive visualization of transcriptional diversity, capture rare cell types with high sensitivity, and accurately reveal biological cell types via clustering. Our sketch of umbilical cord blood cells uncovers a rare subpopulation of inflammatory macrophages, which we experimentally validatedin vitro. The construction of our sketches is extremely fast, which enabled us to accelerate other crucial resource-intensive tasks such as scRNA-seq data integration. We anticipate that our algorithm will become an increasingly essential step when sharing and analyzing the rapidly-growing volume of scRNA-seq data and help enable the democratization of single-cell omics.

scholarly journals Advanced 3D Cell Culture Techniques in Micro-Bioreactors, Part I: A Systematic Analysis of the Literature Published between 2000 and 2020

Processes ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 1656
Author(s):  
Christoph Grün ◽  
Brigitte Altmann ◽  
Eric Gottwald
Keyword(s):  
Cell Culture ◽  
Large Scale ◽  
3D Cell Culture ◽  
Cell Types ◽  
Cell Contact ◽  
Systematic Analysis ◽  
Cell Culture Techniques ◽  
Culture Techniques ◽  
3D Microenvironment

Bioreactors have proven useful for a vast amount of applications. Besides classical large-scale bioreactors and fermenters for prokaryotic and eukaryotic organisms, micro-bioreactors, as specialized bioreactor systems, have become an invaluable tool for mammalian 3D cell cultures. In this systematic review we analyze the literature in the field of eukaryotic 3D cell culture in micro-bioreactors within the last 20 years. For this, we define complexity levels with regard to the cellular 3D microenvironment concerning cell–matrix-contact, cell–cell-contact and the number of different cell types present at the same time. Moreover, we examine the data with regard to the micro-bioreactor design including mode of cell stimulation/nutrient supply and materials used for the micro-bioreactors, the corresponding 3D cell culture techniques and the related cellular microenvironment, the cell types and in vitro models used. As a data source we used the National Library of Medicine and analyzed the studies published from 2000 to 2020.

scholarly journals Potential Clinical Applications for Human Pluripotent Stem Cell-Derived Blood Components

2011 ◽  
Vol 2011 ◽  
pp. 1-11 ◽  
Author(s):  
Erin A. Kimbrel ◽  
Shi-Jiang Lu
Keyword(s):  
Stem Cells ◽  
Stem Cell ◽  
Large Scale ◽  
Embryonic Stem ◽  
Adult Stem Cell ◽  
Cell Types ◽  
The Body ◽  
Blood Components ◽  
Induced Pluripotent

The ability of human embryonic stem cells (hESCs) and induced pluripotent stem cells (iPSCs) to divide indefinitely without losing pluripotency and to theoretically differentiate into any cell type in the body makes them highly attractive cell sources for large scale regenerative medicine purposes. The current use of adult stem cell-derived products in hematologic intervention sets an important precedent and provides a guide for developing hESC/iPSC based therapies for the blood system. In this review, we highlight biological functions of mature cells of the blood, clinical conditions requiring the transfusion or stimulation of these cells, and the potential for hESC/iPSC-derivatives to serve as functional replacements. Many researchers have already been able to differentiate hESCs and/or iPSCs into specific mature blood cell types. For example, hESC-derived red blood cells and platelets are functional in tasks such as oxygen delivery and blood clotting, respectively and may be able to serve as substitutes for their donor-derived counterparts in emergencies. hESC-derived dendritic cells are functional in antigen-presentation and may be used as off-the-shelf vaccine therapies to stimulate antigen-specific immune responses against cancer cells. However,in vitrodifferentiation systems used to generate these cells will need further optimization before hESC/iPSC-derived blood components can be used clinically.

scholarly journals In vitro Generation of Megakaryocytes and Platelets

2021 ◽  
Vol 9 ◽  
Author(s):  
Huicong Liu ◽  
Jiaqing Liu ◽  
Lingna Wang ◽  
Fangfang Zhu
Keyword(s):  
Stem Cells ◽  
Stem Cell ◽  
Hematopoietic Stem Cells ◽  
Large Scale ◽  
Blood Platelet ◽  
Cell Types ◽  
Culture Conditions ◽  
Cancer Therapies ◽  
Hematopoietic Stem

Platelets, the tiny anucleate cells responsible for stopping bleeding through thrombosis, are derived from hematopoietic stem cells through a series of differentiation steps. Thrombocytopenia, characterized by abnormally low blood platelet counts, may arise from cancer therapies, trauma, sepsis, as well as blood disorders, and could become a life-threatening problem. Platelet transfusion is the most effective strategy to treat thrombocytopenia, however, the source of platelets is in great shortage. Therefore, in vitro generation of platelets has become an important topic and numerous attempts have been made toward generating platelets from different types of cells, including hematopoietic stem cells, pluripotent stem cells, fibroblast cells, and adipose-derived cells. In this review, we will detail the efforts made to produce, in the in vitro culture, platelets from these different cell types. Importantly, as transfusion medicine requires a huge number of platelets, we will highlight some studies on producing platelets on a large scale. Although new methods of gene manipulation, new culture conditions, new cytokines and chemical compounds have been introduced in platelet generation research since the first study of hematopoietic stem cell-derived platelets nearly 30 years ago, limited success has been achieved in obtaining truly mature and functional platelets in vitro, indicating the studies of platelets fall behind those of other blood cell types. This is possibly because megakaryocytes, which produce platelets, are very rare in blood and marrow. We have previously developed a platform to identify new extrinsic and intronic regulators for megakaryocytic lineage development, and in this review, we will also cover our effort on that. In summary, stem cell-based differentiation is a promising way of generating large-scale platelets to meet clinical needs, and continuous study of the cellular development of platelets will greatly facilitate this.

Sign in / Sign up

Export Citation Format

Share Document