scholarly journals Decode the Stable Cell Communications Based on Neuropeptide-Receptors Network in 36746 Tumor Cells

Biomedicines ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 14
Author(s):  
Yining Liu ◽  
Min Zhao
Keyword(s):  
Single Cell ◽  
Molecular Mechanisms ◽  
Cell Communication ◽  
The Cancer Genome Atlas ◽  
Single Cell Level ◽  
Cell Level ◽  
Therapy Strategy ◽  
The Status ◽  
Cancer Types ◽  
Cell Transcriptome

Background: As chemical signals of hormones, neuropeptides are essential to regulate cell growth by interacting with their receptors to achieve cell communications in cancer tissues. Previously, neuropeptide transcriptome analysis was limited to tissue-based bulk expression levels. The molecular mechanisms of neuropeptides and their receptors at the single-cell level remain unclear. We conducted a systematic single-cell transcriptome data integration analysis to clarify the similarities and variations of neuropeptide-mediated cell communication between various malignancies. Methods: Based on the single-cell expression information in 72 cancer datasets across 24 cancer types, we characterized actively expressed neuropeptides and receptors as having log values of the quantitative transcripts per million ≥ 1. Then, we created the putative cell-to-cell communication network for each dataset by using the known interaction of those actively expressed neuropeptides and receptors. To focus on the stable cell communication events, we identified neuropeptide and downstream receptors whose interactions were detected in more than half of all conceivable cell-cell interactions (square of the total cell population) in a dataset. Results: Focusing on those actively expressed neuropeptides and receptors, we built over 76 million cell-to-cell communications across 70 cancer datasets. Then the stable cell communication analyses were applied to each dataset, and about 14 million stable cell-to-cell communications could be detected based on 16 neuropeptides and 23 receptors. Further functional analysis indicates these 39 genes could regulate blood pressure and are significantly associated with patients’ survival among over ten thousand The Cancer Genome Atlas (TCGA)pan-cancer samples. By zooming in lung cancer-specific clinical features, we discovered the 39 genes appeared to be enriched in the patients with smoking. In skin cancer, they may differ in the patients with the distinct histological subtype and molecular drivers. Conclusions: At the single-cell level, stable cell communications across cancer types demonstrated some common and distinct neuropeptide-receptor patterns, which could be helpful in determining the status of neuropeptide-based cell communication and developing a peptide-based therapy strategy.

scholarly journals Single-cell transcriptomic analysis elucidates APOE genotype specific changes across cell types in two brain regions in Alzheimer’s disease

2021 ◽  
Author(s):  
Stella Belonwu ◽  
Yaqiao Li ◽  
Daniel Bunis ◽  
Arjun Arkal Rao ◽  
Caroline Warly Solsberg ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Single Cell ◽  
Molecular Mechanisms ◽  
Apoe Genotype ◽  
Cell Types ◽  
Brain Regions ◽  
Single Cell Level ◽  
Cell Level ◽  
Single Nucleus

Abstract Alzheimer’s Disease (AD) is a complex neurodegenerative disease that gravely affects patients and imposes an immense burden on caregivers. Apolipoprotein E4 (APOE4) has been identified as the most common genetic risk factor for AD, yet the molecular mechanisms connecting APOE4 to AD are not well understood. Past transcriptomic analyses in AD have revealed APOE genotype-specific transcriptomic differences; however, these differences have not been explored at a single-cell level. Here, we leverage the first two single-nucleus RNA sequencing AD datasets from human brain samples, including nearly 55,000 cells from the prefrontal and entorhinal cortices. We observed more global transcriptomic changes in APOE4 positive AD cells and identified differences across APOE genotypes primarily in glial cell types. Our findings highlight the differential transcriptomic perturbations of APOE isoforms at a single-cell level in AD pathogenesis and have implications for precision medicine development in the diagnosis and treatment of AD.

Circulating melanoma cells isolated from clinical blood samples and characterized by full-length mRNA sequencing at single-cell level.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 10539-10539 ◽  
Author(s):  
Yu-Chieh Wang ◽  
Daniel Ramskold ◽  
Shujun Luo ◽  
Robin Li ◽  
Qiaolin Deng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Melanoma Cells ◽  
Clinical Samples ◽  
Single Cell Level ◽  
Cell Level ◽  
Blood Samples

10539 Background: Melanoma is the most aggressive type of skin cancer. Late-stage melanoma is highly metastatic and currently lacks effective treatment. This discouraging clinical observation highlights the need for a better understanding of the molecular mechanisms underlying melanoma initiation and progression and for developing new therapeutic approaches based on novel targets. Although genome-wide transcriptome analyses have been frequently used to study molecular alterations in clinical samples, it has been technically challenging to obtain the transcriptomic profiles at single-cell level. Methods: Using antibody-mediated magnetic activated cell separation (MACS), we isolated and individualized putative circulating melanoma cells (CMCs) from the blood samples of the melanoma patients at advance stages. The transcriptomic analysis based on a novel and robust mRNA-Seq protocol (Smart-Seq) was established and applied to the putative CMCs for single-cell profiling. Results: We have discovered distinct gene expression patterns, including new putative markers for CMCs. Meanwhile, the gene expression profiles derived of the CMC candidates isolated from the patient’s blood samples are closely-related to the expression profiles of other cells originated from human melanocytes, including normal melanocytes in primary culture and melanoma cell lines. Compared with existing methods, Smart-Seq has improved read coverage across transcripts, which provides advantage for better analyzing transcript isoforms and SNPs. Conclusions: Our results suggest that the techniques developed in this research for cell isolation and transcriptomic analyses can potentially be used for addressing many biological and clinical questions requiring genomewide transcriptome profiling in rare cells.

scholarly journals Applications and analytical tools of cell communication based on ligand-receptor interactions at single cell level

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Fen Ma ◽  
Siwei Zhang ◽  
Lianhao Song ◽  
Bozhi Wang ◽  
Lanlan Wei ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Cell Communication ◽  
Cellular Communication ◽  
Specific Cell ◽  
Single Cell Level ◽  
Cell Level ◽  
Advantages And Disadvantages ◽  
Receptor Interactions ◽  
Single Cell Rna Sequencing

Abstract Background Cellular communication is an essential feature of multicellular organisms. Binding of ligands to their homologous receptors, which activate specific cell signaling pathways, is a basic type of cellular communication and intimately linked to many degeneration processes leading to diseases. Main body This study reviewed the history of ligand-receptor and presents the databases which store ligand-receptor pairs. The recently applications and research tools of ligand-receptor interactions for cell communication at single cell level by using single cell RNA sequencing have been sorted out. Conclusion The summary of the advantages and disadvantages of analysis tools will greatly help researchers analyze cell communication at the single cell level. Learning cell communication based on ligand-receptor interactions by single cell RNA sequencing gives way to developing new target drugs and personalizing treatment.

scholarly journals NRASG12V-Mediated Self-Renewal Signaling in Self-Renewing AML Stem Cells.

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 2626-2626
Author(s):  
Marie Lue Antony ◽  
Klara Noble-Orcutt ◽  
Karen Sachs ◽  
Anna Khoroshilov ◽  
Daniel Chang ◽  
...  
Keyword(s):  
Stem Cells ◽  
Single Cell ◽  
Molecular Mechanisms ◽  
Signaling Molecules ◽  
The Self ◽  
Single Cell Level ◽  
Mass Cytometry ◽  
Cell Level ◽  
Self Renewal ◽  
Signaling Activation

Abstract In acute myeloid leukemia (AML) standard therapies often induce complete remission, but patients frequently relapse and die of the disease. Leukemia stem cells (LSCs) have self-renewal potential and ability to recapitulate the disease. Our goal is to define the molecular mechanisms that allow AML to relapse. We have previously shown that activated NRAS (NRASG12V) facilitates self-renewal in the LSC-enriched subpopulation in a mouse model of AML (Mll-AF9/NRASG12V, Sachs et al. Blood 2014). We subsequently utilized single-cell RNA sequencing of the LSCs from this model to define and validate the only subset of the LSC-enriched population that can efficiently transplant leukemia in mice. We hypothesize that NRASG12V exerts a unique signaling profile that directs self-renewal in this subset of LSCs. Understanding these pathways at the single-cell level would enable us to design rational therapeutics that would prevent relapse in AML. We used mass cytometry (CyTOF2) to define the signaling activation state of LSC subsets in our AML model. Similar to flow cytometry, mass cytometry provides quantitative measurements of cell-surface and intracellular proteins at the single-cell level. In addition, it can simultaneously and accurately measure over 40 proteins, allowing us to quantitate a panel of intracellular signaling molecules in well-defined immunophenotypic leukemia subpopulations. We previously reported that the LSC-enriched population in this leukemia model is Mac1LowKit+Sca1+ (MKS) and subsequently showed that the self-renewing subset within the MKS population is MKSCD36LowCD69High. In contrast, the MKSCD36HighCD69Low population is incapable of transplanting leukemia in mice. The MKS cells displayed elevated levels of activated signaling molecules relative to the non-MKS population. Comparing the MKS subsets to each other, we found that the self-renewing MKSCD36LowCD69High population displayed significantly higher levels of several signaling molecules including Myc, NF-kB, and β-catenin relative to MKSCD36HighCD69Low cells (which lack self-renewal capacity). We reasoned that self-renewal might be mediated through these signaling molecules uniquely elevated in MKSCD36LowCD69High cells. Next, we sought to define the global signaling activation network within individual MKS subsets to determine if the signaling cascades and dependencies vary between these populations. We used Bayesian network modeling (Sachs K et al. Science 2005) to compare the statistical relationships between these signaling molecules, at the single-cell level. Signaling molecules that impact the levels of downstream effectors can be inferred using this approach. Using this method, we found that the signaling activation network does not significantly vary between MKS subsets. These observations suggest that self-renewal may be driven by alteration in the levels of signaling intermediates rather than alternate signal transduction architecture. We previously found that NRASG12V-mediated signals drive self-renewal in this AML model (Sachs Z. et al. Blood 2014). We used this model to ask which of these self-renewal-associated signaling molecules might be NRASG12V-regulated. We abolished NRASG12V transgene expression in these mice and harvested leukemia cells 72 hours later (per our standard lab protocol). Using this approach, found that self-renewal-associated signaling molecules, including NF-kB and β-catenin, are significantly reduced after NRASG12V-withdrawal indicating that NRASG12V -dependent signaling likely leads to the increase in these signaling molecules. In conclusion, we used mass cytometry analysis to identify the LSC self-renewal-associated signaling state in a murine model of AML and show that NRASG12V activates this signaling program. These data can be used to rationally design therapeutics such as small molecule inhibitors to target self-renewal-specific signaling and prevent relapse in AML. Disclosures No relevant conflicts of interest to declare.

scholarly journals Understanding the pathogenesis of infectious diseases by single-cell RNA sequencing

2021 ◽  
Vol 8 (9) ◽  
pp. 208-222
Author(s):  
Wanqiu Huang ◽  
Danni Wang ◽  
Yu-Feng Yao
Keyword(s):  
Infectious Diseases ◽  
Single Cell ◽  
Rna Sequencing ◽  
Molecular Mechanisms ◽  
Transcriptional Profiling ◽  
Single Cell Level ◽  
Cell Level ◽  
Disease Treatment ◽  
Single Cell Rna Sequencing ◽  
Cell Diversity

Infections are highly orchestrated and dynamic processes, which involve both pathogen and host. Transcriptional profiling at the single-cell level enables the analysis of cell diversity, heterogeneity of the immune response, and detailed molecular mechanisms underlying infectious diseases caused by bacteria, viruses, fungi, and parasites. Herein, we highlight recent remarkable advances in single-cell RNA sequencing (scRNA-seq) technologies and their applications in the investigation of host-pathogen interactions, current challenges and potential prospects for disease treatment are discussed as well. We propose that with the aid of scRNA-seq, the mechanism of infectious diseases will be further revealed thus inspiring the development of novel interventions and therapies.

scholarly journals Elucidating Recombination Mediator Function Using Biophysical Tools

Biology ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 288
Author(s):  
Camille Henry ◽  
Sarah S. Henrikus
Keyword(s):  
Single Cell ◽  
Crucial Role ◽  
Genome Stability ◽  
Molecular Mechanisms ◽  
Current Knowledge ◽  
Single Cell Level ◽  
Cell Level ◽  
Interaction Partners ◽  
Single Protein

The recombination mediator proteins (RMPs) are ubiquitous and play a crucial role in genome stability. RMPs facilitate the loading of recombinases like RecA onto single-stranded (ss) DNA coated by single-strand binding proteins like SSB. Despite sharing a common function, RMPs are the products of a convergent evolution and differ in (1) structure, (2) interaction partners and (3) molecular mechanisms. The RMP function is usually realized by a single protein in bacteriophages and eukaryotes, respectively UvsY or Orf, and RAD52 or BRCA2, while in bacteria three proteins RecF, RecO and RecR act cooperatively to displace SSB and load RecA onto a ssDNA region. Proteins working alongside to the RMPs in homologous recombination and DNA repair notably belongs to the RAD52 epistasis group in eukaryote and the RecF epistasis group in bacteria. Although RMPs have been studied for several decades, molecular mechanisms at the single-cell level are still not fully understood. Here, we summarize the current knowledge acquired on RMPs and review the crucial role of biophysical tools to investigate molecular mechanisms at the single-cell level in the physiological context.

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