Recent advances in high-throughput single-cell transcriptomics and spatial transcriptomics

Shen, Xiaohan; Zhao, Yichun; Wang, Zhuo; Shi, Qi

doi:10.1039/d2lc00633b

Cited by 22 publications

(19 citation statements)

References 101 publications

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“…Even so, spatial transcriptomics, as an intriguing and emerging technique, geniusly integrate cellular transcriptomics with their spatial coordinates within tissues, together allowing a deeper understanding of cellular composition, and heterogeneity as well as cell-cell communications ( Wolock et al, 2019 ; Anderson et al, 2022 ; Fang S. et al, 2022 ; Shen et al, 2022 ). On the other hand, neuronal activities in local neural circuits have been thought to be organized for information processing both spatially and temporally, which can be at least partially explained by spatial transcriptomics and other structural analyses ( Weisenburger and Vaziri, 2018 ; Parra-Damas and Saura, 2020 ; Endo et al, 2021 ).…”

Section: Potential Value Of Single-cell Sequencing In Studying Neuron...mentioning

confidence: 99%

Recent advances in understanding neuronal diversity and neural circuit complexity across different brain regions using single-cell sequencing

Lei¹,

Zan

Liu

2023

Front. Neural Circuits

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Neural circuits are characterized as interconnecting neuron networks connected by synapses. Some kinds of gene expression and/or functional changes of neurons and synaptic connections may result in aberrant neural circuits, which has been recognized as one crucial pathological mechanism for the onset of many neurological diseases. Gradual advances in single-cell sequencing approaches with strong technological advantages, as exemplified by high throughput and increased resolution for live cells, have enabled it to assist us in understanding neuronal diversity across diverse brain regions and further transformed our knowledge of cellular building blocks of neural circuits through revealing numerous molecular signatures. Currently published transcriptomic studies have elucidated various neuronal subpopulations as well as their distribution across prefrontal cortex, hippocampus, hypothalamus, and dorsal root ganglion, etc. Better characterization of brain region-specific circuits may shed light on new pathological mechanisms involved and assist in selecting potential targets for the prevention and treatment of specific neurological disorders based on their established roles. Given diverse neuronal populations across different brain regions, we aim to give a brief sketch of current progress in understanding neuronal diversity and neural circuit complexity according to their locations. With the special focus on the application of single-cell sequencing, we thereby summarize relevant region-specific findings. Considering the importance of spatial context and connectivity in neural circuits, we also discuss a few published results obtained by spatial transcriptomics. Taken together, these single-cell sequencing data may lay a mechanistic basis for functional identification of brain circuit components, which links their molecular signatures to anatomical regions, connectivity, morphology, and physiology. Furthermore, the comprehensive characterization of neuron subtypes, their distributions, and connectivity patterns via single-cell sequencing is critical for understanding neural circuit properties and how they generate region-dependent interactions in different context.

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Section: Potential Value Of Single-cell Sequencing In Studying Neuron...mentioning

confidence: 99%

Recent advances in understanding neuronal diversity and neural circuit complexity across different brain regions using single-cell sequencing

Lei¹,

Zan

Liu

2023

Front. Neural Circuits

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“…Based on the metadata, subsets of samples are selected for analysis, such as those from wild-type or diseased subjects (1). The workflow starts with a wet lab experiment that is then documented (2) and analyzed (3). Next, the wet lab experiment is conducted on a subset of samples based on the analysis of the first experiment (4).…”

Section: Getting Startedmentioning

confidence: 99%

Gain efficiency with streamlined and automated data processing: Examples from high-throughput monoclonal antibody production

Kotowicz,

Fengler,

Kurkowsky

et al. 2023

Preprint

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Data management and sample tracking in complex biological workflows are essential steps to ensure necessary documentation and guarantee the reusability of data and metadata. Currently, these steps pose challenges related to correct annotation and labeling, error detection, and safeguarding the quality of documentation. With growing acquisition of biological data and the expanding automatization of laboratory workflows, manual processing of samples is no longer favorable, as it is time- and resource-consuming, is prone to biases and errors, and lacks scalability and standardization. Thus, managing heterogeneous biological data calls for efficient and tailored systems, especially in laboratories run by biologists with limited computational expertise. Here, we showcase how to meet these challenges with a modular pipeline for data processing, facilitating the complex production of monoclonal antibodies from single B-cells. We present best practices for development of data processing pipelines concerned with extensive acquisition of biological data that undergoes continuous manipulation and analysis. Moreover, we assess the versatility of proposed design principles through a proof-of-concept data processing pipeline for automated induced pluripotent stem cell culture and differentiation. We show that our approach streamlines data management operations, speeds up experimental cycles and leads to enhanced reproducibility. Finally, adhering to the presented guidelines will promote compliance with FAIR principles upon publishing.

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“…Refine phenotyping and grouping with larger sample sizes could help to resolve the effects of specific factors on MSC properties. Single-cell and spatial transcriptomics could also help to delineate the specific aging cells among the heterogeneous subpopulations of MSCs [93]. The induced pluripotent (iPS) stem cells [94] is demonstrated as an example of rejuvenation.…”

Section: Challenges and Prospectsmentioning

confidence: 99%

Age effect on mesenchymal stem cell properties: a concise review

Chen

Xin

Huang

et al. 2022

APT

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Mesenchymal stem cells belong to one of the multipotent stem cell types isolated from almost all tissues in the human body. They function to maintain tissue homeostasis with their highly proliferative property, and they also possess immunomodulatory properties. The properties of mesenchymal stem cells can be influenced by multiple factors, among which donor ages have been indicated negatively correlated with the proliferation, migration, and differentiation of mesenchymal stem cells. Telomerase activity, telomere length, and cell senescence have been studied to understand the mechanisms of the age effect on mesenchymal stem cell properties. Rejuvenation treatments are the critical research direction to attenuate the deterioration of mesenchymal stem cell properties by the age effect. This review article summarized the updated research on the impact and mechanisms of aging and age-related factors on different mesenchymal stem cell properties. In addition, the treatments to rejuvenate the aged mesenchymal stem cells will also be discussed. This review article aims to enlighten scientific researchers in better preparing and nursing the autologous mesenchymal stem cells from the elderly for future applications in tissue engineering and regenerative medicine. Keywords: Mesenchymal stem cells, aging, proliferation, migration, differentiation

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Recent advances in high-throughput single-cell transcriptomics and spatial transcriptomics

Abstract: Single-cell RNA sequencing (scRNA-seq) has been developed for characterizing transcriptome of cells that are rare but of biological significance. With cell barcoding and microchip technologies, a suite of high-throughput scRNA-seq...

Cited by 22 publications

References 101 publications

Recent advances in understanding neuronal diversity and neural circuit complexity across different brain regions using single-cell sequencing

Recent advances in understanding neuronal diversity and neural circuit complexity across different brain regions using single-cell sequencing

Gain efficiency with streamlined and automated data processing: Examples from high-throughput monoclonal antibody production

Age effect on mesenchymal stem cell properties: a concise review

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