Comparison of reverse transcription-quantitative polymerase chain reaction methods and platforms for single cell gene expression analysis

Performance of a scalable RNA extraction-free transcriptome profiling method for adherent cultured human cells

RNA sequencing enables high-content/high-complexity measurements in small molecule screens. Whereas the costs of DNA sequencing and RNA-seq library preparation have decreased consistently, RNA extraction remains a significant bottleneck to scalability. We evaluate the performance of a bulk RNA-seq library prep protocol optimized for analysis of many samples of adherent cultured cells in parallel. We combined a low-cost direct lysis buffer compatible with cDNA synthesis (in-lysate cDNA synthesis) with Smart-3SEQ and examine the effects of calmidazolium and fludrocortisone-induced perturbation of primary human dermal fibroblasts. We compared this method to normalized purified RNA inputs from matching samples followed by Smart-3SEQ or Illumina TruSeq library prep. Our results show the minimal effect of RNA loading normalization on data quality, measurement of gene expression patterns, and generation of differentially expressed gene lists. We found that in-lysate cDNA synthesis combined with Smart-3SEQ RNA-seq library prep generated high-quality data with similar ranked DEG lists when compared to library prep with extracted RNA or with Illumina TruSeq. Our data show that small molecule screens or experiments based on many perturbations quantified with RNA-seq are feasible at low reagent and time costs.

Optimization of small-scale sample preparation for high-throughput OpenArray analysis

OpenArray is one of the most high-throughput qPCR platforms available but its efficiency can be limited by sample preparation methods that are slow and costly. To optimize the sample workflow for high-throughput qPCR processing by OpenArray, small-scale sample preparation methods were compared for compatibility with this system to build confidence in a method that maintains quality and accuracy while using less starting material and saving time and money. This study is the first to show that the Cells-to-CT kit can be used to prepare samples within the dynamic range of OpenArray directly from cultured cells in a single well of a 96-well plate when used together with a cDNA preamplification PCR step. Use of Cells-to-CT produced results of similar quality and accuracy to that of a preparation method using purified RNA in less than half the sample preparation time. While Cells-to-CT samples also exhibited slightly increased variance, which affects the ability of OpenArray to distinguish small differences in gene expression, overall gene expression mean results correlated well between small-scale methods. This work demonstrates that Cells-to-CT with preamplification can be used to reliably prepare samples for OpenArray analysis while saving time, money, and starting material.

IoT PCR for pandemic disease detection and its spread monitoring

During infectious disease outbreaks, the centers for disease control need to monitor particular areas. Considerable effort has been invested in the development of portable, user-friendly, and cost-effective systems for point-of-care (POC) diagnostics, which could also create an Internet of Things (IoT) for healthcare via a global network. However, at present IoT based on a functional POC instrument is not available. Here we show a fast, user-friendly, and affordable IoT system based on a miniaturized polymerase chain reaction device. We demonstrated the system's capability by amplification of complementary deoxyribonucleic acid (cDNA) of the dengue fever virus. The resulting data were then automatically uploaded via a Bluetooth interface to an Android-based smartphone and then wirelessly sent to a global network, instantly making the test results available anywhere in the world. The IoT system presented here could become an essential tool for healthcare centers to tackle infectious disease outbreaks identified either by DNA or ribonucleic acid.

The Effects of Surgical Antiseptics and Time Delays on RNA Isolated From Human and Rodent Peripheral Nerves

Peripheral Nerve Injury (PNI) is common following blunt or penetrating trauma with an estimated prevalence of 2% among the trauma population. The resulting economic and societal impacts are significant. Nerve regeneration is a key biological process in those recovering from neural trauma. Real Time-quantitative Polymerase Chain Reaction (RT-qPCR) and RNA sequencing (RNA seq) are investigative methods that are often deployed by researchers to characterize the cellular and molecular mechanisms that underpin this process. However, the ethical and practical challenges associated with studying human nerve injury have meant that studies of nerve injury have largely been limited to rodent models of renervation. In some circumstances it is possible to liberate human nerve tissue for study, for example during reconstructive nerve repair. This complex surgical environment affords numerous challenges for optimizing the yield of RNA in sufficient quantity and quality for downstream RT-qPCR and/or RNA seq applications. This study characterized the effect of: (1) Time delays between surgical liberation and cryopreservation and (2) contact with antiseptic surgical reagents, on the quantity and quality of RNA isolated from human and rodent nerve samples. It was found that time delays of greater than 3 min between surgical liberation and cryopreservation of human nerve samples significantly decreased RNA concentrations to be sub-optimal for downstream RT-qPCR/RNA seq applications (<5 ng/μl). Minimizing the exposure of human nerve samples to antiseptic surgical reagents significantly increased yield of RNA isolated from samples. The detrimental effect of antiseptic reagents on RNA yield was further confirmed in a rodent model where RNA yield was 8.3-fold lower compared to non-exposed samples. In summary, this study has shown that changes to the surgical tissue collection protocol can have significant effects on the yield of RNA isolated from nerve samples. This will enable the optimisation of protocols in future studies, facilitating characterisation of the cellular and molecular mechanisms that underpin the regenerative capacity of the human peripheral nervous system.

Recommendations for mRNA analysis of micro-dissected glomerular tufts from paraffin-embedded human kidney biopsy samples

Background

Glomeruli are excellent pre-determined natural structures for laser micro-dissection. Compartment-specific glomerular gene expression analysis of formalin-fixed paraffin-embedded renal biopsies could improve research applications. The major challenge for such studies is to obtain good-quality RNA from small amounts of starting material, as applicable for the analysis of glomerular compartments. In this work, we provide data and recommendations for an optimized workflow of glomerular mRNA analysis.

Results

With a proper resolution of the camera and screen provided by the next generation of micro-dissection systems, we are able to separate parietal epithelial cells from glomerular tufts. Selected compartment-specific transcripts (WT1 and GLEPP1 for glomerular tuft as well as PAX2 for parietal epithelial cells) seem to be reliable discriminators for these micro-dissected glomerular substructures. Using the phenol–chloroform extraction and hemalaun-stained sections (2 µm), high amounts of Bowman’s capsule transections (> 300) reveal sufficient RNA concentrations (> 300 ng mRNA) for further analysis. For comparison, in unstained sections from a number of 60 glomerular transections upwards, a minimum amount of 157 ng mRNA with a reasonable mRNA purity [A260/A280 ratio of 1.5 (1.4/1.7) median (25th/75th percentiles)] was reversely transcribed into cDNA. Comparing the effect of input RNA (20, 60, 150 and 300 micro-dissected glomerular transections), transcript expression of POLR2A significantly correlated when 60 and 150 laser micro-dissected glomerular transections were used for analysis. There was a lower inter-assay coefficient of variability for ADAMTS13, when at least 60 glomerular transections were used. According to the algorithms of geNormPlus and NormFinder, PGK1 and PPIA are more stable glomerular reference transcripts compared to GUSB, GAPDH, POLR2A, RPLPO, TBP, B2M, ACTB, 18SrRNA and HMBS.

Conclusions

Our approach implements compartment-specific glomerular mRNA expression analysis into research applications, even regarding glomerular substructures like parietal epithelial cells. We recommend using of at least 60 micro-dissected unstained glomerular or 300 hemalaun-stained Bowman’s capsule transections to obtain sufficient input mRNA for reproducible results. Hereby, the range of RNA concentrations in 60 micro-dissected glomeruli is low and appropriate normalization of C_q values using our suggested reference transcripts (PGK1 and PPIA) allows compensation with respect to different amounts of RNA purity and quantity.

Electronic supplementary material

The online version of this article (10.1186/s12867-018-0103-x) contains supplementary material, which is available to authorized users.

RNAi revised--target mRNA-dependent enhancement of gene silencing

The discovery of RNA interference (RNAi) gave rise to the development of new nucleic acid-based technologies as powerful investigational tools and potential therapeutics. Mechanistic key details of RNAi in humans need to be deciphered yet, before such approaches take root in biomedicine and molecular therapy.

We developed and validated an in silico-based model of siRNA-mediated RNAi in human cells in order to link in vitro-derived pre-steady state kinetic data with a quantitative and time-resolved understanding of RNAi on the cellular level. The observation that product release by Argonaute 2 is accelerated in the presence of an excess of target RNA in vitro inspired us to suggest an associative mechanism for the RNA slicer reaction where incoming target mRNAs actively promote dissociation of cleaved mRNA fragments. This novel associative model is compatible with high multiple turnover rates of RNAi-based gene silencing in living cells and accounts for target mRNA concentration-dependent enhancement of the RNAi machinery.

An optimised direct lysis method for gene expression studies on low cell numbers

There is increasing interest in gene expression analysis of either single cells or limited numbers of cells. One such application is the analysis of harvested circulating tumour cells (CTCs), which are often present in very low numbers. A highly efficient protocol for RNA extraction, which involves a minimal number of steps to avoid RNA loss, is essential for low input cell numbers. We compared several lysis solutions that enable reverse transcription (RT) to be performed directly on the cell lysate, offering a simple rapid approach to minimise RNA loss for RT. The lysis solutions were assessed by reverse transcription quantitative polymerase chain reaction (RT-qPCR) in low cell numbers isolated from four breast cancer cell lines. We found that a lysis solution containing both the non-ionic detergent (IGEPAL CA-630, chemically equivalent to Nonidet P-40 or NP-40) and bovine serum albumin (BSA) gave the best RT-qPCR yield. This direct lysis to reverse transcription protocol outperformed a column-based extraction method using a commercial kit. This study demonstrates a simple, reliable, time- and cost-effective method that can be widely used in any situation where RNA needs to be prepared from low to very low cell numbers.

Concurrent host-pathogen gene expression in the lungs of pigs challenged with Actinobacillus pleuropneumoniae

Background

Actinobacillus pleuropneumoniae causes pleuropneumonia in pigs, a disease which is associated with high morbidity and mortality, as well as impaired animal welfare. To obtain in-depth understanding of this infection, the interplay between virulence factors of the pathogen and defense mechanisms of the porcine host needs to be elucidated. However, research has traditionally focused on either bacteriology or immunology; an unbiased picture of the transcriptional responses can be obtained by investigating both organisms in the same biological sample.

Results

Host and pathogen responses in pigs experimentally infected with A. pleuropneumoniae were analyzed by high-throughput RT-qPCR. This approach allowed concurrent analysis of selected genes encoding proteins known or hypothesized to be important in the acute phase of this infection. The expression of 17 bacterial and 31 porcine genes was quantified in lung samples obtained within the first 48 hours of infection. This provided novel insight into the early time course of bacterial genes involved in synthesis of pathogen-associated molecular patterns (lipopolysaccharide, peptidoglycan, lipoprotein) and genes involved in pattern recognition (TLR4, CD14, MD2, LBP, MYD88) in response to A. pleuropneumoniae. Significant up-regulation of proinflammatory cytokines such as IL1B, IL6, and IL8 was observed, correlating with protein levels, infection status and histopathological findings. Host genes encoding proteins involved in iron metabolism, as well as bacterial genes encoding exotoxins, proteins involved in adhesion, and iron acquisition were found to be differentially expressed according to disease progression. By applying laser capture microdissection, porcine expression of selected genes could be confirmed in the immediate surroundings of the invading pathogen.

Conclusions

Microbial pathogenesis is the product of interactions between host and pathogen. Our results demonstrate the applicability of high-throughput RT-qPCR for the elucidation of dual-organism gene expression analysis during infection. We showed differential expression of 12 bacterial and 24 porcine genes during infection and significant correlation of porcine and bacterial gene expression. This is the first study investigating the concurrent transcriptional response of both bacteria and host at the site of infection during porcine respiratory infection.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1557-6) contains supplementary material, which is available to authorized users.

Pre-amplification in the context of high-throughput qPCR gene expression experiment

BACKGROUND

With the introduction of the first high-throughput qPCR instrument on the market it became possible to perform thousands of reactions in a single run compared to the previous hundreds. In the high-throughput reaction, only limited volumes of highly concentrated cDNA or DNA samples can be added. This necessity can be solved by pre-amplification, which became a part of the high-throughput experimental workflow. Here, we focused our attention on the limits of the specific target pre-amplification reaction and propose the optimal, general setup for gene expression experiment using BioMark instrument (Fluidigm).

RESULTS

For evaluating different pre-amplification factors following conditions were combined: four human blood samples from healthy donors and five transcripts having high to low expression levels; each cDNA sample was pre-amplified at four cycles (15, 18, 21, and 24) and five concentrations (equivalent to 0.078 ng, 0.32 ng, 1.25 ng, 5 ng, and 20 ng of total RNA). Factors identified as critical for a success of cDNA pre-amplification were cycle of pre-amplification, total RNA concentration, and type of gene. The selected pre-amplification reactions were further tested for optimal Cq distribution in a BioMark Array. The following concentrations combined with pre-amplification cycles were optimal for good quality samples: 20 ng of total RNA with 15 cycles of pre-amplification, 20x and 40x diluted; and 5 ng and 20 ng of total RNA with 18 cycles of pre-amplification, both 20x and 40x diluted.

CONCLUSIONS

We set up upper limits for the bulk gene expression experiment using gene expression Dynamic Array and provided an easy-to-obtain tool for measuring of pre-amplification success. We also showed that variability of the pre-amplification, introduced into the experimental workflow of reverse transcription-qPCR, is lower than variability caused by the reverse transcription step.

Self-digitization microfluidic chip for absolute quantification of mRNA in single cells

Quantification of mRNA in single cells provides direct insight into how intercellular heterogeneity plays a role in disease progression and outcomes. Quantitative polymerase chain reaction (qPCR), the current gold standard for evaluating gene expression, is insufficient for providing absolute measurement of single-cell mRNA transcript abundance. Challenges include difficulties in handling small sample volumes and the high variability in measurements. Microfluidic digital PCR provides far better sensitivity for minute quantities of genetic material, but the typical format of this assay does not allow for counting of the absolute number of mRNA transcripts samples taken from single cells. Furthermore, a large fraction of the sample is often lost during sample handling in microfluidic digital PCR. Here, we report the absolute quantification of single-cell mRNA transcripts by digital, one-step reverse transcription PCR in a simple microfluidic array device called the self-digitization (SD) chip. By performing the reverse transcription step in digitized volumes, we find that the assay exhibits a linear signal across a wide range of total RNA concentrations and agrees well with standard curve qPCR. The SD chip is found to digitize a high percentage (86.7%) of the sample for single-cell experiments. Moreover, quantification of transferrin receptor mRNA in single cells agrees well with single-molecule fluorescence in situ hybridization experiments. The SD platform for absolute quantification of single-cell mRNA can be optimized for other genes and may be useful as an independent control method for the validation of mRNA quantification techniques.

Considerations for accurate gene expression measurement by reverse transcription quantitative PCR when analysing clinical samples

Reverse transcription quantitative PCR is an established, simple and effective method for RNA measurement. However, technical standardisation challenges combined with frequent insufficient experimental detail render replication of many published findings challenging. Consequently, without adequate consideration of experimental standardisation, such findings may be sufficient for a given publication but cannot be translated to wider clinical application. This article builds on earlier standardisation work and the MIQE guidelines, discussing processes that need consideration for accurate, reproducible analysis when dealing with patient samples. By applying considerations common to the science of measurement (metrology), one can maximise the impact of gene expression studies, increasing the likelihood of their translation to clinical tools.

Validation of high-throughput single cell analysis methodology

High-throughput quantitative polymerase chain reaction (qPCR) approaches enable profiling of multiple genes in single cells, bringing new insights to complex biological processes and offering opportunities for single cell-based monitoring of cancer cells and stem cell-based therapies. However, workflows with well-defined sources of variation are required for clinical diagnostics and testing of tissue-engineered products. In a study of neural stem cell lines, we investigated the performance of lysis, reverse transcription (RT), preamplification (PA), and nanofluidic qPCR steps at the single cell level in terms of efficiency, precision, and limit of detection. We compared protocols using a separate lysis buffer with cell capture directly in RT-PA reagent. The two methods were found to have similar lysis efficiencies, whereas the direct RT-PA approach showed improved precision. Digital PCR was used to relate preamplified template copy numbers to Cq values and reveal where low-quality signals may affect the analysis. We investigated the impact of calibration and data normalization strategies as a means of minimizing the impact of inter-experimental variation on gene expression values and found that both approaches can improve data comparability. This study provides validation and guidance for the application of high-throughput qPCR workflows for gene expression profiling of single cells.

Direct cell lysis for single-cell gene expression profiling

The interest to analyze single and few cell samples is rapidly increasing. Numerous extraction protocols to purify nucleic acids are available, but most of them compromise severely on yield to remove contaminants and are therefore not suitable for the analysis of samples containing small numbers of transcripts only. Here, we evaluate 17 direct cell lysis protocols for transcript yield and compatibility with downstream reverse transcription quantitative real-time PCR. Four endogenously expressed genes are assayed together with RNA and DNA spikes in the samples. We found bovine serum albumin (BSA) to be the best lysis agent, resulting in efficient cell lysis, high RNA stability, and enhanced reverse transcription efficiency. Furthermore, we found direct cell lysis with BSA superior to standard column based extraction methods, when analyzing from 1 up to 512 mammalian cells. In conclusion, direct cell lysis protocols based on BSA can be applied with most cell collection methods and are compatible with most analytical workflows to analyze single-cells as well as samples composed of small numbers of cells.

The future is now: single-cell genomics of bacteria and archaea

Interest in the expanding catalog of uncultivated microorganisms, increasing recognition of heterogeneity among seemingly similar cells, and technological advances in whole-genome amplification and single-cell manipulation are driving considerable progress in single-cell genomics. Here, the spectrum of applications for single-cell genomics, key advances in the development of the field, and emerging methodology for single-cell genome sequencing are reviewed by example with attention to the diversity of approaches and their unique characteristics. Experimental strategies transcending specific methodologies are identified and organized as a road map for future studies in single-cell genomics of environmental microorganisms. Over the next decade, increasingly powerful tools for single-cell genome sequencing and analysis will play key roles in accessing the genomes of uncultivated organisms, determining the basis of microbial community functions, and fundamental aspects of microbial population biology.

Methods for applying accurate digital PCR analysis on low copy DNA samples

Digital PCR (dPCR) is a highly accurate molecular approach, capable of precise measurements, offering a number of unique opportunities. However, in its current format dPCR can be limited by the amount of sample that can be analysed and consequently additional considerations such as performing multiplex reactions or pre-amplification can be considered. This study investigated the impact of duplexing and pre-amplification on dPCR analysis by using three different assays targeting a model template (a portion of the Arabidopsis thaliana alcohol dehydrogenase gene). We also investigated the impact of different template types (linearised plasmid clone and more complex genomic DNA) on measurement precision using dPCR. We were able to demonstrate that duplex dPCR can provide a more precise measurement than uniplex dPCR, while applying pre-amplification or varying template type can significantly decrease the precision of dPCR. Furthermore, we also demonstrate that the pre-amplification step can introduce measurement bias that is not consistent between experiments for a sample or assay and so could not be compensated for during the analysis of this data set. We also describe a model for estimating the prevalence of molecular dropout and identify this as a source of dPCR imprecision. Our data have demonstrated that the precision afforded by dPCR at low sample concentration can exceed that of the same template post pre-amplification thereby negating the need for this additional step. Our findings also highlight the technical differences between different templates types containing the same sequence that must be considered if plasmid DNA is to be used to assess or control for more complex templates like genomic DNA.

Overview of micro- and nano-technology tools for stem cell applications: micropatterned and microelectronic devices

In the past few decades the scientific community has been recognizing the paramount role of the cell microenvironment in determining cell behavior. In parallel, the study of human stem cells for their potential therapeutic applications has been progressing constantly. The use of advanced technologies, enabling one to mimic the in vivo stem cell microenviroment and to study stem cell physiology and physio-pathology, in settings that better predict human cell biology, is becoming the object of much research effort. In this review we will detail the most relevant and recent advances in the field of biosensors and micro- and nano-technologies in general, highlighting advantages and disadvantages. Particular attention will be devoted to those applications employing stem cells as a sensing element.

RT-qPCR work-flow for single-cell data analysis

Individual cells represent the basic unit in tissues and organisms and are in many aspects unique in their properties. The introduction of new and sensitive techniques to study single-cells opens up new avenues to understand fundamental biological processes. Well established statistical tools and recommendations exist for gene expression data based on traditional cell population measurements. However, these workflows are not suitable, and some steps are even inappropriate, to apply on single-cell data. Here, we present a simple and practical workflow for preprocessing of single-cell data generated by reverse transcription quantitative real-time PCR. The approach is demonstrated on a data set based on profiling of 41 genes in 303 single-cells. For some pre-processing steps we present options and also recommendations. In particular, we demonstrate and discuss different strategies for handling missing data and scaling data for downstream multivariate analysis. The aim of this workflow is provide guide to the rapidly growing community studying single-cells by means of reverse transcription quantitative real-time PCR profiling.