BloodSpot: a database of healthy and malignant haematopoiesis updated with purified and single cell mRNA sequencing profiles

Abstract Background The development of mRNA sequencing has contributed greatly to the mechanism exploration in hematologic malignancies disease. With the advent of revolutionized single-cell mRNA sequencing (scRNA-seq), it is now possible to characterize every subset of expression programs and functional states in a comprehensive and unbiased manner. Here, we present a systematic evaluation of engineered chimeric antigen receptor T (CAR-T) products and patient bone marrow profiles in terms of primary resistance and severe cytokine release syndrome (CRS) at the single-cell level. Methods Using single-cell mRNA sequencing in conjunction with flow cytometry (FCM), we performed characterization of CD19-targeted CAR-T and mononuclear bone marrow cells from 4 on-trial B acute lymphoblastic leukemia (B-ALL) patients (NCT02965092). Bioinformatics analysis was utilized to explore diversity between patients with different grades of response or CRS. Basing on marker genes, CAR-T products were divided into four groups, which were double-positive T (DPT), CD4 positive T (CD4), CD8 positive T (CD8), and double-negative T (DNT) cells. Meanwhile, both the mononuclear bone marrow cells before and after CAR-T infusion were grouped into six clusters, which were B-ALL, stem, progenitor, B, T, and myeloid cells. The expression and enrichment analyses results were calculated by R (version 3.6.3) and then verified in a 22-sample conventional transcription sequencing cohort of the same clinical trial. Patient efficacy was assessed by the national comprehension cancer network guidelines version 2.2020 for acute lymphoblastic leukemia, and CRS was graded by CTCAE 5.0. Results By FCM detection, the variances of CAR-T infusion products between patients with different clinical outcomes were limited, and nor did mononuclear bone marrow cells. The scRNA sequencing results showed that distinct CAR-T and bone marrow cell subsets indicated differentiated expression in proliferation, cytotoxicity, and intercellular signaling pathways. Expression differentiation variances in CAR-T infusion products were minor than in mononuclear bone marrow cells. CD8+ CAR-T products of complete response (CR) patients were still significantly enriched in pathways such as cell killing (p adjust=0.0012), antigen processing and presentation (p adjust=0.0027), and cell cycle (p adjust=0.0231), exhibiting greater immune function when compared with no response patients. Also, DPT CAR-T products of the non-CRS patients were meaningfully enriched in negative regulation of cytokine production pathway (p adjust=0.0127) when compared with CRS ones. In mononuclear bone marrow cells, B-ALL cells before CAR-T treatment of CR patients presented negatively in cell-cycle (p adjust=0.0019), leading to a low malignant cell proliferation level; and stem-progenitor cells after CAR-T treatment of CR patients showed a stronger ability of neutrophil activation (p adjust<0.0001). As with comparisons between CRS and non-CRS, B-ALL cells before infusion manifested a cell cycle arrest profile (p adjust<0.0006) in non-CRS patients, whereas the immune cells at the same time point were enriched in positive regulation of cell cycle process (p adjust=0.0002). Conclusions Through single-cell RNA-seq profiling and unbiased canonical pathway analyses, our results unveil heterogeneities in the cell cycle, immune phenotype, and metabolic profiles of subsets during CAR-T therapy, providing a mechanistic basis for ameliorating clinical outcomes and individualized management. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

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Sequencing dropout-and-batch effect normalization for single-cell mRNA profiles: a survey and comparative analysis

Briefings in Bioinformatics ◽

10.1093/bib/bbaa248 ◽

2020 ◽

Author(s):

Tian Lan ◽

Gyorgy Hutvagner ◽

Qing Lan ◽

Tao Liu ◽

Jinyan Li

Keyword(s):

Single Cell ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Batch Effect ◽

Sequencing Data ◽

Accurate Analysis ◽

Mrna Sequencing ◽

Normalization Methods ◽

Future Improvement ◽

Better Than

Abstract Single-cell mRNA sequencing has been adopted as a powerful technique for understanding gene expression profiles at the single-cell level. However, challenges remain due to factors such as the inefficiency of mRNA molecular capture, technical noises and separate sequencing of cells in different batches. Normalization methods have been developed to ensure a relatively accurate analysis. This work presents a survey on 10 tools specifically designed for single-cell mRNA sequencing data preprocessing steps, among which 6 tools are used for dropout normalization and 4 tools are for batch effect correction. In this survey, we outline the main methodology for each of these tools, and we also compare these tools to evaluate their normalization performance on datasets which are simulated under the constraints of dropout inefficiency, batch effect or their combined effects. We found that Saver and Baynorm performed better than other methods in dropout normalization, in most cases. Beer and Batchelor performed better in the batch effect normalization, and the Saver–Beer tool combination and the Baynorm–Beer combination performed better in the mixed dropout-and-batch effect normalization. Over-normalization is a common issue occurred to these dropout normalization tools that is worth of future investigation. For the batch normalization tools, the capability of retaining heterogeneity between different groups of cells after normalization can be another direction for future improvement.

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A comprehensive series of temporal transcription factors in the fly visual system

10.1101/2021.06.13.448242 ◽

2021 ◽

Author(s):

Nikolaos Konstantinides ◽

Anthony M. Rossi ◽

Aristides Escobar ◽

Liébaut Dudragne ◽

Yen-Chung Chen ◽

...

Keyword(s):

Stem Cells ◽

Transcription Factors ◽

Single Cell ◽

Neuronal System ◽

Neuronal Diversity ◽

Temporal Patterning ◽

Neuronal Stem Cells ◽

Mrna Sequencing ◽

Neuronal Types ◽

Cell Type Specific

AbstractThe brain consists of thousands of different neuronal types that are generated through multiple divisions of neuronal stem cells. These stem cells have the capacity to generate different neuronal types at different stages of their development. In Drosophila, this temporal patterning is driven by the successive expression of temporal transcription factors (tTFs). While a number of tTFs are known in different animals and across various parts of the nervous system, these have been mostly identified by informed guesses and antibody availability. We used single-cell mRNA sequencing to identify the complete series of tTFs that specify most Drosophila medulla neurons in the optic lobe. We tested the genetic interactions among these tTFs. While we verify the general principle that tTFs regulate the progression of the series by activating the next tTFs in the series and repressing the previous ones, we also identify more complex regulations. Two of the tTFs, Eyeless and Dichaete, act as hubs integrating the input of several upstream tTFs before allowing the series to progress and in turn regulating the expression of several downstream tTFs. Moreover, we show that tTFs not only specify neuronal identity by controlling the expression of cell type-specific genes. Finally, we describe the very first steps of neuronal differentiation and find that terminal differentiation genes, such as neurotransmitter-related genes, are present as transcripts, but not as proteins, in immature larval neurons days before they are being used in functioning neurons; we show that these mechanisms are conserved in humans. Our results offer a comprehensive description of a temporal series of tTFs in a neuronal system, offering mechanistic insights into the regulation of the progression of the series and the regulation of neuronal diversity. This represents a proof-of-principle for the use of single-cell mRNA sequencing for the comparison of temporal patterning across phyla that can lead to an understanding of how the human brain develops and how it has evolved.

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Functional In vivo Single-cell Transcriptome (FIST) Analysis Reveals Molecular Properties of Light-Sensitive Neurons in Mouse V1

10.1101/382002 ◽

2018 ◽

Author(s):

Jianwei Liu ◽

Na Pan ◽

Le Sun ◽

Mengdi Wang ◽

Junjing Zhang ◽

...

Keyword(s):

Patch Clamp ◽

Single Cell ◽

Three Dimensional ◽

Whole Cell ◽

Mrna Sequencing ◽

Layer 2 ◽

Cell Transcriptome ◽

Single Cell Transcriptome ◽

Live Mouse

ABSTRACTVision formation is classically based on projections from the retinal ganglion cells (RGC) to the lateral geniculate nucleus (LGN) and the primary visual cortex (V1). Although the cellular information of the retina and the LGN has been widely studied, the transcriptome profiles of single neurons with specific functions in V1 still remain unknown. Some neurons in mouse V1 are tuned to light stimulus. To determine the molecular properties of light-stimulated neurons in layer 2/3 of V1, we developed a method of functional in vivo single-cell transcriptome (FIST) analysis that integrates sensory evoked calcium imaging, whole-cell electrophysiological patch-clamp recordings, single-cell mRNA sequencing and three-dimensional morphological characterization in a live mouse, based on a two-photon microscope system. In our study, 58 individual cells from layer 2/3 of V1 were identified as either light-sensitive (LS) or non-light-sensitive (NS) by single-cell light-evoked calcium evaluation and action potential spiking. The contents of every single cell after individual functional tests were aspirated through the patch-clamp pipette for mRNA sequencing. Furthermore, the three-dimensional (3-D) morphological characterizations of the neurons were reconstructed in the live mouse after the whole-cell recordings. Our sequencing results indicated that V1 neurons with high expression of genes related to transmission regulation, such as Rtn4r, Nr4a1, and genes involved in membrane transport, such as Na+/K+ ATPase, NMDA-type glutamatergic receptor, preferentially respond to light stimulation. Our findings demonstrate the ability of FIST analysis to characterize the functional, morphological and transcriptomic properties of a single cell in alive animal, thereby providing precise neuronal information and predicting its network contribution in the brain.

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Benchmarking Single-Cell mRNA–Sequencing Technologies Uncovers Differences in Sensitivity and Reproducibility in Cell Types With Low RNA Content

10.7171/3fc1f5fe.dbeabb2a ◽

2021 ◽

Vol 32 (4) ◽

Author(s):

Ilona Holcomb ◽

Nidhanjali Bansal ◽

Tommy Duong ◽

Paul Babb ◽

Julie Laliberte ◽

...

Keyword(s):

Single Cell ◽

Cell Types ◽

Mrna Sequencing ◽

Sequencing Technologies ◽

Rna Content

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Discrepant mRNA and Protein Expression in Immune Cells

Current Genomics ◽

10.2174/1389202921999200716103758 ◽

2020 ◽

Vol 21 (8) ◽

pp. 560-563

Author(s):

Jiawei Li ◽

Yi Zhang ◽

Cheng Yang ◽

Ruiming Rong

Keyword(s):

Protein Expression ◽

Single Cell ◽

Immune Cells ◽

Surface Proteins ◽

Mrna Levels ◽

Interesting Phenomenon ◽

Mrna Sequencing ◽

New Methods ◽

Mrna And Protein Expression ◽

Simultaneous Assessment

With the development of single-cell mRNA sequencing (scRNA-seq), researchers have attempted to identify new methods for performing in-depth studies of immune cells. However, the discrepancies between the mRNA levels and the levels of surface proteins have confused many researchers. Here, we report a significant and interesting phenomenon in which the mRNA and protein expression levels were mismatched in immune cells. We concluded that scRNA-seq should be combined with other sequencing methods in single-cell studies (e.g., CITE-seq). The simultaneous assessment of both mRNA and protein expression will enhance the precision and credibility of the results.

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