scholarly journals Sparcle: assigning transcripts to cells in multiplexed images

2021 ◽  
Author(s):  
Sandhya Prabhakaran ◽  
Tal Nawy ◽  
Dana Pe’er’
Keyword(s):  
Single Molecule ◽  
Technical Noise ◽  
Spatial Features ◽  
Cell Quantification ◽  
Gene Count ◽  
Cell Gene Expression ◽  
Or Gene ◽  
Technological Platform ◽  
Cell Gene

AbstractBackgroundImaging-based spatial transcriptomics has the power to reveal patterns of single-cell gene expression by detecting mRNA transcripts as individually resolved spots in multiplexed images. However, molecular quantification has been severely limited by the computational challenges of segmenting poorly outlined, overlapping cells, and of overcoming technical noise; the majority of transcripts are routinely discarded because they fall outside the segmentation boundaries. This lost information leads to less accurate gene count matrices and weakens downstream analyses, such as cell type or gene program identification.ResultsHere, we present Sparcle, a probabilistic model that reassigns transcripts to cells based on gene covariation patterns and incorporates spatial features such as distance to nucleus. We demonstrate its utility on both multiplexed error-robust fluorescence in situ hybridization (MERFISH) and single-molecule FISH (smFISH) data.ConclusionsSparcle improves transcript assignment, providing more realistic per-cell quantification of each gene, better delineation of cell boundaries, and improved cluster assignments. Critically, our approach does not require an accurate segmentation and is agnostic to technological platform.

scholarly journals In situelectro-sequencing in three-dimensional tissues

2021 ◽  
Author(s):  
Qiang Li ◽  
Zuwan Lin ◽  
Ren Liu ◽  
Xin Tang ◽  
Jiahao Huang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Three Dimensional ◽  
Cell Types ◽  
Developmental Trajectory ◽  
Single Cell Level ◽  
Cell Level ◽  
Cell Gene Expression ◽  
Cell Gene

AbstractPairwise mapping of single-cell gene expression and electrophysiology in intact three-dimensional (3D) tissues is crucial for studying electrogenic organs (e.g., brain and heart)1–5. Here, we introducein situelectro-sequencing (electro-seq), combining soft bioelectronics within situRNA sequencing to stably map millisecond-timescale cellular electrophysiology and simultaneously profile a large number of genes at single-cell level across 3D tissues. We appliedin situelectro-seq to 3D human induced pluripotent stem cell-derived cardiomyocyte (hiPSC-CM) patches, precisely registering the CM gene expression with electrophysiology at single-cell level, enabling multimodalin situanalysis. Such multimodal data integration substantially improved the dissection of cell types and the reconstruction of developmental trajectory from spatially heterogeneous tissues. Using machine learning (ML)-based cross-modal analysis,in situelectro-seq identified the gene-to-electrophysiology relationship over the time course of cardiac maturation. Further leveraging such a relationship to train a coupled autoencoder, we demonstrated the prediction of single-cell gene expression profile evolution using long-term electrical measurement from the same cardiac patch or 3D millimeter-scale cardiac organoids. As exemplified by cardiac tissue maturation,in situelectro-seq will be broadly applicable to create spatiotemporal multimodal maps and predictive models in electrogenic organs, allowing discovery of cell types and gene programs responsible for electrophysiological function and dysfunction.

scholarly journals Single Cell RNA Sequencing of Serial Tumor and Blood Biopsies from Lymphoma Patients on an in Situ Vaccination Clinical Trial

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 4107-4107
Author(s):  
Tanaya Shree ◽  
Anuja Sathe ◽  
Debra K. Czerwinski ◽  
Steven R. Long ◽  
Hanlee Ji ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Peripheral Blood ◽  
Fine Needle ◽  
Fine Needle Aspirates ◽  
Single Cell Rna Sequencing ◽  
Cell Gene Expression ◽  
Cell Gene

Abstract The critical determinants of effective antitumor immune responses, whether native or induced by therapy, remain poorly understood due to the complexity and plasticity of the immune system. To better profile and track these responses, we have employed the novel approach of performing single cell RNA sequencing for paired gene expression and immune repertoire analysis on tumor fine needle aspirates and peripheral blood of lymphoma patients undergoing immunotherapy on a clinical trial (NCT02927964). In this in situ vaccination study, patients with low-grade lymphoma received local low-dose radiation and intratumoral SD-101 (a TLR9 agonist) to one site of disease, with systemic ibrutinib (a BTK inhibitor) added in the second week of treatment. Tumor fine needle aspirates and peripheral blood samples were obtained prior to treatment, at one week (prior to ibrutinib initiation) and at six weeks after treatment start. Single cell preparations were processed using 10X Genomics' single cell RNA transcription and library preparation protocol, followed by sequencing on the Illumina platform. Cells were sequenced to an average depth of 50,000 reads/cell for gene expression libraries and 5000 reads/cell for TCR sequencing. Identification of variable genes, principal component and/or canonical correlation analysis, graph-based clustering and differential expression analysis of single-cell gene expression data was performed using the Seurat algorithm. Single-cell TCR repertoires were analyzed using TCR-specific analysis software. This data is being integrated with data from multiparameter flow cytometry and functional immune assays for these same patients, as well as with their clinical outcomes. Sequencing libraries have been prepared from 37 samples from 4 patients thus far. We have successfully generated single cell gene expression and TCR libraries from 3,000-10,000 cells from tumor fine needle aspirates and peripheral blood, with excellent sequencing quality metrics obtained. From detailed analyses of one patient's samples thus far, we have identified distinct immune populations in blood and tumor (Figure 1), including light-chain restricted B-cells, with good concordance with flow cytometry. Preliminary results show changes occurring in immune cell frequencies and phenotypes at the treated tumor site, at distant tumor sites and in the peripheral blood when samples from before and after treatment are compared. Sample collection, sequencing, and analysis are ongoing. Deep profiling of serial biopsies during immunotherapy using single cell RNA sequencing promises to illuminate underlying cellular dynamics, and paired with clinical outcome data, determinants of response. Ultimately, this may provide a roadmap for successful translation of single-cell genomics into the clinic for treatment monitoring and response prediction. Disclosures No relevant conflicts of interest to declare.

scholarly journals Flow-FISH as a Tool for Studying Bacteria, Fungi and Viruses

BioTech ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 21
Author(s):  
Julian J. Freen-van Heeren
Keyword(s):  
Single Cell ◽  
Mammalian Cells ◽  
Genetic Material ◽  
Protein Detection ◽  
Mixed Cultures ◽  
High Throughput Analysis ◽  
Multiple Gene ◽  
Cell Gene Expression ◽  
Cell Gene

Many techniques are currently in use to study microbes. These can be aimed at detecting, identifying, and characterizing bacterial, fungal, and viral species. One technique that is suitable for high-throughput analysis is flow cytometry-based fluorescence in situ hybridization, or Flow-FISH. This technique employs (fluorescently labeled) probes directed against DNA or (m)RNA, for instance targeting a gene or microorganism of interest and provides information on a single-cell level. Furthermore, by combining Flow-FISH with antibody-based protein detection, proteins of interest can be measured simultaneously with genetic material. Additionally, depending on the type of Flow-FISH assay, Flow-FISH can also be multiplexed, allowing for the simultaneous measurement of multiple gene targets and/or microorganisms. Together, this allows for, e.g., single-cell gene expression analysis or identification of (sub)strains in mixed cultures. Flow-FISH has been used in mammalian cells but has also been extensively employed to study diverse microbial species. Here, the use of Flow-FISH for studying microorganisms is reviewed. Specifically, the detection of (intracellular) pathogens, studying microorganism biology and disease pathogenesis, and identification of bacterial, fungal, and viral strains in mixed cultures is discussed, with a particular focus on the viruses EBV, HIV-1, and SARS-CoV-2.

scholarly journals High-throughput single-cell gene-expression profiling with multiplexed error-robust fluorescence in situ hybridization

2016 ◽  
Vol 113 (39) ◽  
pp. 11046-11051 ◽  
Author(s):  
Jeffrey R. Moffitt ◽  
Junjie Hao ◽  
Guiping Wang ◽  
Kok Hao Chen ◽  
Hazen P. Babcock ◽  
...  
Keyword(s):  
In Situ Hybridization ◽  
Fluorescence In Situ Hybridization ◽  
Single Cell ◽  
Single Molecule ◽  
Rna Profiling ◽  
Drastic Increase ◽  
Cell Gene Expression ◽  
A Cell ◽  
Labeling Approach

Image-based approaches to single-cell transcriptomics, in which RNA species are identified and counted in situ via imaging, have emerged as a powerful complement to single-cell methods based on RNA sequencing of dissociated cells. These image-based approaches naturally preserve the native spatial context of RNAs within a cell and the organization of cells within tissue, which are important for addressing many biological questions. However, the throughput of these image-based approaches is relatively low. Here we report advances that lead to a drastic increase in the measurement throughput of multiplexed error-robust fluorescence in situ hybridization (MERFISH), an image-based approach to single-cell transcriptomics. In MERFISH, RNAs are identified via a combinatorial labeling approach that encodes RNA species with error-robust barcodes followed by sequential rounds of single-molecule fluorescence in situ hybridization (smFISH) to read out these barcodes. Here we increase the throughput of MERFISH by two orders of magnitude through a combination of improvements, including using chemical cleavage instead of photobleaching to remove fluorescent signals between consecutive rounds of smFISH imaging, increasing the imaging field of view, and using multicolor imaging. With these improvements, we performed RNA profiling in more than 100,000 human cells, with as many as 40,000 cells measured in a single 18-h measurement. This throughput should substantially extend the range of biological questions that can be addressed by MERFISH.

scholarly journals miR-9a regulates levels of both rhomboid mRNA and protein in the early Drosophila melanogaster embryo

2021 ◽  
Author(s):  
Lorenzo Gallicchio ◽  
Sam Griffiths-Jones ◽  
Matthew Ronshaugen
Keyword(s):  
Drosophila Melanogaster ◽  
Single Cell ◽  
Single Molecule ◽  
Single Cells ◽  
Temporal Regulation ◽  
Cell Quantification ◽  
Early Embryos ◽  
Proliferation And Differentiation ◽  
Noise In Gene Expression

MicroRNAs have subtle and combinatorial effects on the expression levels of their targets. Studying the consequences of a single microRNA knockout often proves difficult as many such knockouts exhibit phenotypes only under stress conditions. This has led to the hypothesis that microRNAs frequently act as buffers of noise in gene expression. Observing and understanding buffering effects requires quantitative analysis of microRNA and target expression in single cells. To this end, we have employed single molecule fluorescence in situ hybridization, immunofluorescence, and high-resolution confocal microscopy to investigate the effects of miR-9a loss on the expression of the serine-protease rhomboid in Drosophila melanogaster early embryos. Our single-cell quantitative approach shows that rhomboid mRNA exhibits the same spatial expression pattern in WT and miR-9a knockout embryos, although the number of mRNA molecules per cell is higher when miR-9a is absent. However, the level of rhomboid protein shows a much more dramatic increase in the miR-9a> knockout. Specifically, we see accumulation of rhomboid protein in miR-9a mutants by stage 5, much earlier than in WT. The data therefore show that miR-9a functions in the regulation of rhomboid activity by both inducing mRNA degradation and inhibiting translation in the blastoderm embryo. Temporal regulation of neural proliferation and differentiation in vertebrates by miR-9a is well-established. We suggest that miR-9a family microRNAs are conserved regulators of timing in neurogenic processes. This work shows the power of single-cell quantification as an experimental tool to study phenotypic consequences of microRNA mis-regulation.

Sign in / Sign up

Export Citation Format

Share Document