cDNA library preparation from total RNA extracts of Single-cell marine protists (e.g. Acantharia, Strombidium basimorphum, and Prymnesium parvum) for transcriptome sequencing v2

2022 ◽  
Author(s):  
Joost S S. Mansour ◽  
Konstantinos Anestis ◽  
Fabrice Not ◽  
Uwe John
Keyword(s):  
Single Cell ◽  
Cdna Library ◽  
Mammalian Cells ◽  
Single Cells ◽  
Rna Extraction ◽  
Cdna Libraries ◽  
Prymnesium Parvum ◽  
Large Variability ◽  
Total Rna ◽  
Marine Protists

Many marine protists are not culturable and therefore challenging to study, nonetheless, they are essential in all marine ecosystems. The development of single-cell techniques is allowing for more marine protists to be studied. Such genomic approaches aim to help to disentangle heterotrophic processes such as phagotrophy from osmotrophy and phototrophic-induced anabolic activities. This information will then support cellular and metabolic modeling by better elucidating the physiological mechanisms and quantifying their importance in different scenarios. However, single-cell protocols and low input RNA kits for transcriptomics are usually made for and tested with mammalian cells, as such the feasibility and efficiency of single-cell transcriptomics on highly diverse mixotrophic protists is not always known. Often single-cell transcriptomics of microbial eukaryotes shows low transcript recovery rates and large variability. We report on transcriptomic methods that we have successfully performed on single cells of Acantharia, Strombidium basimorphum, and Prymnesium parvum. This protocol follows up after total RNA extraction (from the protocol at dx.doi.org/10.17504/protocols.io.bp6xmrfn) to prepare cDNA libraries for Illumina sequencing. The described protocol uses the SMART-Seq4 kit (Takara #634891) for cDNA synthesis and amplification, but this can also be successfully performed with the NEBNext kit (NEB #E6421). The NEBNext kit protocol is very similar to the protocol described here and generally the manufacture's protocol can be followed but see the notes at step 4 and step 18 of this protocol, and do the final elution after cDNA purification in 10 mM Tris (pH 8.0). The subsequent cDNA library is prepared following the .

scholarly journals Glyoxal fixation facilitates transcriptome analysis after antigen staining and cell sorting by flow cytometry

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0240769
Author(s):  
Prasanna Channathodiyil ◽  
Jonathan Houseley
Keyword(s):  
Flow Cytometry ◽  
Transcriptome Analysis ◽  
Mammalian Cells ◽  
Single Cells ◽  
Rna Extraction ◽  
Cyclin B1 ◽  
Immunofluorescent Staining ◽  
Rna Seq ◽  
Simple Method ◽  
Staining Methods

A simple method for extraction of high quality RNA from cells that have been fixed, stained and sorted by flow cytometry would allow routine transcriptome analysis of highly purified cell populations and single cells. However, formaldehyde fixation impairs RNA extraction and inhibits RNA amplification. Here we show that good quality RNA can be readily extracted from stained and sorted mammalian cells if formaldehyde is replaced by glyoxal—a well-characterised fixative that is widely compatible with immunofluorescent staining methods. Although both formaldehyde and glyoxal efficiently form protein-protein crosslinks, glyoxal does not crosslink RNA to proteins nor form stable RNA adducts, ensuring that RNA remains accessible and amenable to enzymatic manipulation after glyoxal fixation. We find that RNA integrity is maintained through glyoxal fixation, permeabilisation with methanol or saponin, indirect immunofluorescent staining and flow sorting. RNA can then be extracted by standard methods and processed into RNA-seq libraries using commercial kits; mRNA abundances measured by poly(A)+ RNA-seq correlate well between freshly harvested cells and fixed, stained and sorted cells. We validate the applicability of this approach to flow cytometry by staining MCF-7 cells for the intracellular G2/M-specific antigen cyclin B1 (CCNB1), and show strong enrichment for G2/M-phase cells based on transcriptomic data. Switching to glyoxal fixation with RNA-compatible staining methods requires only minor adjustments of most existing staining and sorting protocols, and should facilitate routine transcriptomic analysis of sorted cells.

scholarly journals Expression Profiling of Single Mammalian Cells – Small is Beautiful

Yeast ◽  
2000 ◽  
Vol 1 (3) ◽  
pp. 211-217 ◽  
Author(s):  
Gerard Brady
Keyword(s):  
Mrna Expression ◽  
Single Cell ◽  
Mammalian Cells ◽  
Single Cell Analysis ◽  
Single Cells ◽  
Expression Patterns ◽  
Global Gene Expression ◽  
Small Samples ◽  
Biological Research ◽  
Cell Expression

Increasingly mRNA expression patterns established using a variety of molecular technologies such as cDNA microarrays, SAGE and cDNA display are being used to identify potential regulatory genes and as a means of providing valuable insights into the biological status of the starting sample. Until recently, the application of these techniques has been limited to mRNA isolated from millions or, at very best, several thousand cells thereby restricting the study of small samples and complex tissues. To overcome this limitation a variety of amplification approaches have been developed which are capable of broadly evaluating mRNA expression patterns in single cells. This review will describe approaches that have been employed to examine global gene expression patterns either in small numbers of cells or, wherever possible, in actual isolated single cells. The first half of the review will summarize the technical aspects of methods developed for single-cell analysis and the latter half of the review will describe the areas of biological research that have benefited from single-cell expression analysis.

scholarly journals Single cell profiling of total RNA using Smart-seq-total

2020 ◽  
Author(s):  
Alina Isakova ◽  
Norma Neff ◽  
Stephen R. Quake
Keyword(s):  
Single Cell ◽  
Single Cells ◽  
Embryonic Stem ◽  
Cell Types ◽  
Embryoid Bodies ◽  
High Yield ◽  
Rna Seq ◽  
Mcf7 Cells ◽  
Total Rna ◽  
Non Coding Rna

ABSTRACTThe ability to interrogate total RNA content of single cells would enable better mapping of the transcriptional logic behind emerging cell types and states. However, current RNA-seq methods are unable to simultaneously monitor both short and long, poly(A)+ and poly(A)-transcripts at the single-cell level, and thus deliver only a partial snapshot of the cellular RNAome. Here, we describe Smart-seq-total, a method capable of assaying a broad spectrum of coding and non-coding RNA from a single cell. Built upon the template-switch mechanism, Smart-seq-total bears the key feature of its predecessor, Smart-seq2, namely, the ability to capture full-length transcripts with high yield and quality. It also outperforms current poly(A)–independent total RNA-seq protocols by capturing transcripts of a broad size range, thus, allowing us to simultaneously analyze protein-coding, long non-coding, microRNA and other non-coding RNA transcripts from single cells. We used Smart-seq-total to analyze the total RNAome of human primary fibroblasts, HEK293T and MCF7 cells as well as that of induced murine embryonic stem cells differentiated into embryoid bodies. We show that simultaneous measurement of non-coding RNA and mRNA from the same cell enables elucidation of new roles of non-coding RNA throughout essential processes such as cell cycle or lineage commitment. Moreover, we show that cell types can be distinguished based on the abundance of non-coding transcripts alone.

scholarly journals Single-cell quantification of a broad RNA spectrum reveals unique noncoding patterns associated with cell types and states

2021 ◽  
Vol 118 (51) ◽  
pp. e2113568118
Author(s):  
Alina Isakova ◽  
Norma Neff ◽  
Stephen R. Quake
Keyword(s):  
Single Cell ◽  
Noncoding Rna ◽  
Single Cells ◽  
Embryonic Stem ◽  
Cell Types ◽  
Embryoid Bodies ◽  
Rna Seq ◽  
Total Rna ◽  
Rna Transcripts ◽  
Rna Content

The ability to interrogate total RNA content of single cells would enable better mapping of the transcriptional logic behind emerging cell types and states. However, current single-cell RNA-sequencing (RNA-seq) methods are unable to simultaneously monitor all forms of RNA transcripts at the single-cell level, and thus deliver only a partial snapshot of the cellular RNAome. Here we describe Smart-seq-total, a method capable of assaying a broad spectrum of coding and noncoding RNA from a single cell. Smart-seq-total does not require splitting the RNA content of a cell and allows the incorporation of unique molecular identifiers into short and long RNA molecules for absolute quantification. It outperforms current poly(A)-independent total RNA-seq protocols by capturing transcripts of a broad size range, thus enabling simultaneous analysis of protein-coding, long-noncoding, microRNA, and other noncoding RNA transcripts from single cells. We used Smart-seq-total to analyze the total RNAome of human primary fibroblasts, HEK293T, and MCF7 cells, as well as that of induced murine embryonic stem cells differentiated into embryoid bodies. By analyzing the coexpression patterns of both noncoding RNA and mRNA from the same cell, we were able to discover new roles of noncoding RNA throughout essential processes, such as cell cycle and lineage commitment during embryonic development. Moreover, we show that independent classes of short-noncoding RNA can be used to determine cell-type identity.

scholarly journals Effect of design geometry, exposure energy, cytophilic molecules, cell type and load in fabrication of single-cell arrays using micro-contact printing

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Swapnil Vilas Bhujbal ◽  
Maren Dekov ◽  
Vegar Ottesen ◽  
Karen Dunker ◽  
Rahmi Lale ◽  
...  
Keyword(s):  
Single Cell ◽  
Mammalian Cells ◽  
Single Cells ◽  
Separation Distance ◽  
Patterned Surfaces ◽  
Contact Printing ◽  
Cell Arrays ◽  
Exposure Energy ◽  
Glass Surfaces ◽  
Photolithography Process

Abstract In this study a range of factors influencing the fabrication of single-cell arrays (SCAs) are identified and investigated. Micro-contact printing was used to introduce spots coated with polyethyleneimine or Matrigel on glass surfaces pre-coated with polyethylene glycol. Unmodified E. coli, Synechococcus sp., Chlamydomonas reinhardtii as well as diverse mammalian cells including HUVEC, AAV293, U87, OHS, PC3, SW480, HepG2 and AY-27 were successfully immobilised onto the chemically coated spots. The developed SCAs show high cell viability and probability for capturing single-cells. A discrepancy between the size and shape of the squares described in the design file and the actual structures obtained in the final PDMS structure is characterised and quantified. The discrepancy is found to be depending on the exposure energy used in the photolithography process as well as the size of the squares and their separation distance as detailed in the design file. In addition to these factors, the effect of the cell density loaded onto the patterned surfaces is also characterised. The systematic characterisation of key parameters that need to be optimised prior to the fabrication of SCAs is essential in order to increase the efficiency and reproducibility of future fabrication of SCAs for single-cell studies.

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