scholarly journals Transformative opportunities for single-cell proteomics

2018 ◽  
Author(s):  
Harrison Specht ◽  
Nikolai Slavov
Keyword(s):  
Mass Spectrometry ◽  
Stem Cell ◽  
Cell Differentiation ◽  
Single Cell ◽  
Single Cells ◽  
Biological Systems ◽  
Stem Cell Differentiation ◽  
New Age ◽  
Technological Developments

Many pressing medical challenges - such as diagnosing disease, enhancing directed stem cell differentiation, and classifying cancers - have long been hindered by limitations in our ability to quantify proteins in single cells. Mass-spectrometry (MS) is poised to transcend these limitations by developing powerful methods to routinely quantify thousands of proteins and proteoforms across many thousands of single cells. We outline specific technological developments and ideas that can increase the sensitivity and throughput of single cell MS by orders of magnitude and usher in this new age. These advances will transform medicine and ultimately contribute to understanding biological systems on an entirely new level.

scholarly journals Transformative opportunities for single-cell proteomics

2018 ◽  
Author(s):  
Harrison Specht ◽  
Nikolai Slavov
Keyword(s):  
Mass Spectrometry ◽  
Stem Cell ◽  
Cell Differentiation ◽  
Single Cell ◽  
Single Cells ◽  
Biological Systems ◽  
Stem Cell Differentiation ◽  
New Age ◽  
Technological Developments

Many pressing medical challenges - such as diagnosing disease, enhancing directed stem cell differentiation, and classifying cancers - have long been hindered by limitations in our ability to quantify proteins in single cells. Mass-spectrometry (MS) is poised to transcend these limitations by developing powerful methods to routinely quantify thousands of proteins and proteoforms across many thousands of single cells. We outline specific technological developments and ideas that can increase the sensitivity and throughput of single cell MS by orders of magnitude and usher in this new age. These advances will transform medicine and ultimately contribute to understanding biological systems on an entirely new level.

scholarly journals Routinely quantifying single cell proteomes: A new age in quantitative biology and medicine

2018 ◽  
Author(s):  
Harrison Specht ◽  
Nikolai Slavov
Keyword(s):  
Mass Spectrometry ◽  
Stem Cell ◽  
Cell Differentiation ◽  
Single Cell ◽  
Single Cells ◽  
Biological Systems ◽  
Stem Cell Differentiation ◽  
New Age ◽  
Quantitative Biology ◽  
Technological Developments

Many pressing medical challenges -- such as diagnosing disease, enhancing directed stem cell differentiation, and classifying cancers -- have long been hindered by limitations in our ability to quantify proteins in single cells. Mass-spectrometry (MS) is poised to transcend these limitations by developing powerful methods to routinely quantify thousands of proteins and proteoforms across many thousands of single cells. We outline specific technological developments and ideas that can increase the sensitivity and throughput of single cell MS by orders of magnitude and usher in this new age. These advances will transform medicine and ultimately contribute to understanding biological systems on an entirely new level.

scholarly journals Bioconductor workflow for single-cell RNA sequencing: Normalization, dimensionality reduction, clustering, and lineage inference

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 1158 ◽  
Author(s):  
Fanny Perraudeau ◽  
Davide Risso ◽  
Kelly Street ◽  
Elizabeth Purdom ◽  
Sandrine Dudoit
Keyword(s):  
Stem Cell ◽  
Cell Differentiation ◽  
Dimensionality Reduction ◽  
Single Cell ◽  
Single Cells ◽  
Differential Expression Analysis ◽  
Stem Cell Differentiation ◽  
Cell Types ◽  
Cell Clustering ◽  
Cell Transcriptome

Novel single-cell transcriptome sequencing assays allow researchers to measure gene expression levels at the resolution of single cells and offer the unprecendented opportunity to investigate at the molecular level fundamental biological questions, such as stem cell differentiation or the discovery and characterization of rare cell types. However, such assays raise challenging statistical and computational questions and require the development of novel methodology and software. Using stem cell differentiation in the mouse olfactory epithelium as a case study, this integrated workflow provides a step-by-step tutorial to the methodology and associated software for the following four main tasks: (1) dimensionality reduction accounting for zero inflation and over dispersion and adjusting for gene and cell-level covariates; (2) cell clustering using resampling-based sequential ensemble clustering; (3) inference of cell lineages and pseudotimes; and (4) differential expression analysis along lineages.

scholarly journals Ultra-multiplexed analysis of single-cell dynamics reveals logic rules in differentiation

2019 ◽  
Vol 5 (4) ◽  
pp. eaav7959 ◽  
Author(s):  
Ce Zhang ◽  
Hsiung-Lin Tu ◽  
Gengjie Jia ◽  
Tanzila Mukhtar ◽  
Verdon Taylor ◽  
...  
Keyword(s):  
Stem Cell ◽  
Cell Differentiation ◽  
Single Cell ◽  
Cell Fate ◽  
Single Cell Analysis ◽  
Single Cells ◽  
Critical Role ◽  
Stem Cell Differentiation ◽  
Cell Fate Decisions ◽  
Cellular Microenvironments

Dynamical control of cellular microenvironments is highly desirable to study complex processes such as stem cell differentiation and immune signaling. We present an ultra-multiplexed microfluidic system for high-throughput single-cell analysis in precisely defined dynamic signaling environments. Our system delivers combinatorial and time-varying signals to 1500 independently programmable culture chambers in week-long live-cell experiments by performing nearly 106 pipetting steps, where single cells, two-dimensional (2D) populations, or 3D neurospheres are chemically stimulated and tracked. Using our system and statistical analysis, we investigated the signaling landscape of neural stem cell differentiation and discovered “cellular logic rules” that revealed the critical role of signal timing and sequence in cell fate decisions. We find synergistic and antagonistic signal interactions and show that differentiation pathways are highly redundant. Our system allows dissection of hidden aspects of cellular dynamics and enables accelerated biological discovery.

Functional Evaluation of Neural Stem Cell Differentiation by Single Cell Calcium Imaging

2011 ◽  
Vol 6 (3) ◽  
pp. 288-296 ◽  
Author(s):  
Maria Francisca Eiriz ◽  
Sofia Grade ◽  
Alexandra Rosa ◽  
Sara Xapelli ◽  
Liliana Bernardino ◽  
...  
Keyword(s):  
Stem Cell ◽  
Cell Differentiation ◽  
Single Cell ◽  
Neural Stem Cell ◽  
Calcium Imaging ◽  
Stem Cell Differentiation ◽  
Functional Evaluation ◽  
Cell Calcium

scholarly journals Single-cell landscape of nuclear configuration and gene expression during stem cell differentiation and X inactivation

2020 ◽  
Author(s):  
Giancarlo Bonora ◽  
Vijay Ramani ◽  
Ritambhara Singh ◽  
He Fang ◽  
Dana Jackson ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stem Cell ◽  
Cell Differentiation ◽  
Single Cell ◽  
Embryonic Stem ◽  
Stem Cell Differentiation ◽  
Chromatin Accessibility ◽  
X Inactivation ◽  
Specific Structure ◽  
X Chromosomes

AbstractMammalian development is associated with extensive changes in gene expression, chromatin accessibility, and nuclear structure. Here, we follow such changes associated with mouse embryonic stem cell differentiation and X inactivation by integrating, for the first time, allele-specific data obtained by high-throughput single-cell RNA-seq, ATAC-seq, and Hi-C. In differentiated cells, contact decay profiles, which clearly distinguish the active and inactive X chromosomes, reveal loss of the inactive X-specific structure at mitosis followed by a rapid reappearance, suggesting a ‘bookkeeping’ mechanism. In differentiating embryonic stem cells, changes in contact decay profiles are detected in parallel on both the X chromosomes and autosomes, suggesting profound simultaneous reorganization. The onset of the inactive X-specific structure in single cells is notably delayed relative to that of gene silencing, consistent with the idea that chromatin compaction is a late event of X inactivation. Novel computational approaches to effectively align single-cell gene expression, chromatin accessibility, and 3D chromosome structure reveal that long-range structural changes to chromosomes appear as discrete events, unlike progressive changes in gene expression and chromatin accessibility.

scholarly journals Gene network reconstruction using single cell transcriptomic data reveals key factors for embryonic stem cell differentiation

2019 ◽  
Author(s):  
Junil Kim ◽  
Simon Toftholm Jakobsen ◽  
Kedar Nath Natarajan ◽  
Kyoung Jae Won
Keyword(s):  
Stem Cell ◽  
Cell Differentiation ◽  
Embryonic Stem Cell ◽  
Single Cell ◽  
Regulatory Networks ◽  
Target Genes ◽  
Embryonic Stem ◽  
Stem Cell Differentiation ◽  
Embryonic Stem Cell Differentiation ◽  
Expression Data

ABSTRACTGene expression data has been widely used to infer gene regulatory networks (GRNs). Recent single-cell RNA sequencing (scRNAseq) data, containing the expression information of the individual cells (or status), are highly useful in blindly reconstructing regulatory mechanisms. However, it is still not easy to understand transcriptional cascade from large amount of expression data. Besides, the reconstructed networks may not capture the major regulatory rules.Here, we propose a novel approach called TENET to reconstruct the GRNs from scRNAseq data by calculating causal relationships between genes using transfer entropy (TE). We show that known target genes have significantly higher TE values. Genes with higher TE values were more affected by various perturbations. Comprehensive benchmarking showed that TENET outperformed other GRN prediction algorithms. More importantly, TENET is uniquely capable of identifying key regulators. Applying TENET to scRNAseq during embryonic stem cell differentiation to neural cells, we show that Nme2 is a critical factor for 2i condition specific stem cell self-renewal.

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