scholarly journals LifeTime and improving European healthcare through cell-based interceptive medicine

Nature ◽  
2020 ◽  
Vol 587 (7834) ◽  
pp. 377-386 ◽  
Author(s):  
Nikolaus Rajewsky ◽  
◽  
Geneviève Almouzni ◽  
Stanislaw A. Gorski ◽  
Stein Aerts ◽  
...  

AbstractHere we describe the LifeTime Initiative, which aims to track, understand and target human cells during the onset and progression of complex diseases, and to analyse their response to therapy at single-cell resolution. This mission will be implemented through the development, integration and application of single-cell multi-omics and imaging, artificial intelligence and patient-derived experimental disease models during the progression from health to disease. The analysis of large molecular and clinical datasets will identify molecular mechanisms, create predictive computational models of disease progression, and reveal new drug targets and therapies. The timely detection and interception of disease embedded in an ethical and patient-centred vision will be achieved through interactions across academia, hospitals, patient associations, health data management systems and industry. The application of this strategy to key medical challenges in cancer, neurological and neuropsychiatric disorders, and infectious, chronic inflammatory and cardiovascular diseases at the single-cell level will usher in cell-based interceptive medicine in Europe over the next decade.

2021 ◽  
Author(s):  
Stella Belonwu ◽  
Yaqiao Li ◽  
Daniel Bunis ◽  
Arjun Arkal Rao ◽  
Caroline Warly Solsberg ◽  
...  

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.


2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 10539-10539 ◽  
Author(s):  
Yu-Chieh Wang ◽  
Daniel Ramskold ◽  
Shujun Luo ◽  
Robin Li ◽  
Qiaolin Deng ◽  
...  

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.


Biomedicines ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 14
Author(s):  
Yining Liu ◽  
Min Zhao

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.


Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 2626-2626
Author(s):  
Marie Lue Antony ◽  
Klara Noble-Orcutt ◽  
Karen Sachs ◽  
Anna Khoroshilov ◽  
Daniel Chang ◽  
...  

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.


Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 2588-2588
Author(s):  
Guillermo Montalban-Bravo ◽  
Feiyang Ma ◽  
Irene Ganan-Gomez ◽  
Rashmi Kanagal-Shamanna ◽  
Vera Adema ◽  
...  

Abstract Despite advances in the genetic characterization of chronic myelomonocytic leukemia (CMML), the molecular mechanisms that drive the disease during its distinct phases remain unclear. To uncover vulnerabilities in CMML that could be therapeutically targeted to halt its evolution, we sought to dissect at the single-cell level the cellular and transcriptomic changes that occur in the hematopoietic system at the time of CMML's initiation and its progression after hypomethylating agent (HMA) therapy. To evaluate the molecular mechanisms underlying CMML maintenance, we performed single-cell RNA sequencing (scRNA-seq) analysis of lineage-negative (Lin -)CD34 + hematopoietic stem and progenitor cells (HSPCs) and bone marrow (BM) mononuclear cells (MNCs) isolated from untreated CMML patients (n=5 and 6, respectively) and age-matched healthy donors (HDs; n=2 and 3, respectively). Our integrated analysis revealed that CMML Lin -CD34 + HSPCs had a predominant granulomonocytic differentiation route with an increased frequency of early and committed myeloid-monocytic progenitors at the expense of HSCs and megakaryocyte/erythroid progenitors (Fig. 1a). Differential expression analysis among the clusters revealed that most transcriptomic differences occurred in CMML HSCs, which were characterized by the upregulation of genes involved in oxidative phosphorylation, type I interferon (IFN) and IFNγ response, myeloid development, and inflammatory signaling and had downregulated expression of genes involved in TNFα-mediated NF-κB activation (Fig. 1b). These data suggest that CMML HSCs undergo metabolic reprogramming and demand a higher level of mitochondrial activity to maintain activated monocytic differentiation in response to inflammatory signaling. Consistent with these results, scRNA-seq analysis of MNCs isolated from the same HD and CMML BM samples showed that monocytes were significantly increased at the expense of erythroid precursors and B cells in CMML (Fig. 1c). CMML monocytes had upregulated genes involved in IFNγ response, oxidative phosphorylation, MYC targets, NF-κB activation, and inflammation (e.g., S100A9, CCL3, IL1B). Interestingly, among the anti-apoptotic BCL2 family members, only the NF-κB transcriptional target BCL2A1 was significantly overexpressed. To investigate the mechanisms of resistance to HMA therapy, we performed integrated scRNA-seq analysis of sequential Lin -CD34 + cells and BM MNCs isolated from CMML patients at the time of disease initiation and progression after HMA therapy failure. CMML progression was driven by a significant expansion of lympho-myeloid progenitors (LMPPs) at the expense of earlier HSCs , which exacerbated myelomonocytic differentiation in the HSPC compartment (Fig. 1d). Expanded LMPPs were characterized by higher levels of IFNγ response, NF-κB survival signaling, and cell cycle regulators. Accordingly, scRNA-seq analysis of MNCs cells from the same patients showed significantly increased frequencies of monocytes and a reduction of naïve CD4 +/CD8 + T cells and effector memory CD8 + T cells. Differential expression analysis of the 2 sample groups in the monocyte population identified five different cellular clusters, one of which emerged only at progression (Fig. 1e). This population was characterized by high expression levels of inflammatory cytokines and the anti-apoptotic modulators MCL1 and BCL2A1. Together, these data suggest that CMML progression arises from immature myeloid progenitors at the stem cell level and that downstream monocytes undergo transcriptomic rewiring and acquire survival mechanisms that induce therapy resistance and further accelerate disease progression. In conclusion, our results elucidate the differentiation hierarchies and transcriptional programs associated with CMML's initiation and its progression after HMA therapy. Our data suggest that therapies targeting downstream effectors of NF-kB-mediated survival signaling could overcome treatment failure. Figure 1 Figure 1. Disclosures Wei: Daiichi Sanko: Research Funding. Kantarjian: AbbVie: Honoraria, Research Funding; Immunogen: Research Funding; KAHR Medical Ltd: Honoraria; Jazz: Research Funding; Ipsen Pharmaceuticals: Honoraria; Astellas Health: Honoraria; NOVA Research: Honoraria; Pfizer: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Astra Zeneca: Honoraria; Ascentage: Research Funding; Aptitude Health: Honoraria; Daiichi-Sankyo: Research Funding; Amgen: Honoraria, Research Funding; BMS: Research Funding; Precision Biosciences: Honoraria; Taiho Pharmaceutical Canada: Honoraria.


Author(s):  
Yiheng Peng ◽  
Huanyu Qiao

Meiosis is a cellular division process that produces gametes for sexual reproduction. Disruption of complex events throughout meiosis, such as synapsis and homologous recombination, can lead to infertility and aneuploidy. To reveal the molecular mechanisms of these events, transcriptome studies of specific substages must be conducted. However, conventional methods, such as bulk RNA-seq and RT-qPCR, are not able to detect the transcriptional variations effectively and precisely, especially for identifying cell types and stages with subtle differences. In recent years, mammalian meiotic transcriptomes have been intensively studied at the single-cell level by using single-cell RNA-seq (scRNA-seq) approaches, especially through two widely used platforms, Smart-seq2 and Drop-seq. The scRNA-seq protocols along with their downstream analysis enable researchers to accurately identify cell heterogeneities and investigate meiotic transcriptomes at a higher resolution. In this review, we compared bulk RNA-seq and scRNA-seq to show the advantages of the scRNA-seq in meiosis studies; meanwhile, we also pointed out the challenges and limitations of the scRNA-seq. We listed recent findings from mammalian meiosis (male and female) studies where scRNA-seq applied. Next, we summarized the scRNA-seq analysis methods and the meiotic marker genes from spermatocytes and oocytes. Specifically, we emphasized the different features of the two scRNA-seq protocols (Smart-seq2 and Drop-seq) in the context of meiosis studies and discussed their strengths and weaknesses in terms of different research purposes. Finally, we discussed the future applications of scRNA-seq in the meiosis field.


2021 ◽  
Vol 8 (9) ◽  
pp. 208-222
Author(s):  
Wanqiu Huang ◽  
Danni Wang ◽  
Yu-Feng Yao

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.


2021 ◽  
Vol 18 (2) ◽  
pp. 64-70
Author(s):  
Monika M. Gladka

Abstract Purpose of the Review Cardiovascular disease remains the leading cause of death worldwide, resulting in cardiac dysfunction and, subsequently, heart failure (HF). Single-cell RNA sequencing (scRNA-seq) is a rapidly developing tool for studying the transcriptional heterogeneity in both healthy and diseased hearts. Wide applications of techniques like scRNA-seq could significantly contribute to uncovering the molecular mechanisms involved in the onset and progression to HF and contribute to the development of new, improved therapies. This review discusses several studies that successfully applied scRNA-seq to the mouse and human heart using various methods of tissue processing and downstream analysis. Recent Findings The application of scRNA-seq in the cardiovascular field is continuously expanding, providing new detailed insights into cardiac pathophysiology. Summary Increased understanding of cardiac pathophysiology on the single-cell level will contribute to the development of novel, more effective therapeutic strategies. Here, we summarise the possible application of scRNA-seq to the adult mammalian heart.


Biology ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 288
Author(s):  
Camille Henry ◽  
Sarah S. Henrikus

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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