Evaluation of isolation methods and RNA integrity for bacterial RNA quantitation

Jahn, Courtney E.; Charkowski, Amy O.; Willis, David K.

doi:10.1016/j.mimet.2008.07.004

Cited by 184 publications

(145 citation statements)

References 36 publications

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“…TRIzol) bias against longer transcripts (Stead et al, 2012). TRIzol extraction has further been reported to deliver RNA in low yield for some bacterial species (Jahn et al, 2008).…”

Section: Defining the Minimal Materials Requirements For A Dual Rna-sementioning

confidence: 99%

Dual RNA-seq of pathogen and host

2012

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SummaryThe infection of a eukaryotic host cell by a bacterial pathogen is one of the most intimate examples of cross-kingdom interactions in biology. Infection processes are highly relevant from both a basic research as well as a clinical point of view. Sophisticated mechanisms have evolved in the pathogen to manipulate the host response and vice versa host cells have developed a wide range of anti-microbial defense strategies to combat bacterial invasion and clear infections.However, it is this diversity and complexity that makes infection research so challenging to technically address as common approaches have either been optimized for bacterial or eukaryotic organisms. Instead, methods are required that are able to deal with the often dramatic discrepancy between host and pathogen with respect to various cellular properties and processes. One class of cellular macromolecules that exemplify this host-pathogen heterogeneity is given by their transcriptomes: Bacterial transcripts differ from their eukaryotic counterparts in many aspects that involve both quantitative and qualitative traits. The entity of RNA transcripts present in a cell is of paramount interest as it reflects the cell's physiological state under the given condition. Genome-wide transcriptomic techniques such as RNA-seq have therefore been used for single-organism analyses for several years, but their applicability has been limited for infection studies.The present work describes the establishment of a novel transcriptomic approach for infection biology which we have termed "Dual RNA-seq". Using this technology, it was intended to shed light particularly on the contribution of non-protein-encoding transcripts to virulence, as these classes have mostly evaded previous infection studies due to the lack of suitable methods. The performance of Dual RNA-seq was evaluated in an in vitro infection model based on the important facultative intracellular pathogen Salmonella enterica serovar Typhimurium and different human cell lines. Dual RNA-seq was found to be capable of capturing all major bacterial and human transcript classes and proved reproducible. During the course of these experiments, a previously largely uncharacterized bacterial small non-coding RNA (sRNA), referred to as STnc440, was identified as one of the most strongly induced genes in intracellular Salmonella.Interestingly, while inhibition of STnc440 expression has been previously shown to cause a virulence defect in different animal models of Salmonellosis, the underlying molecular mechanisms have remained obscure. Here, classical genetics, transcriptomics and biochemical assays proposed a complex model of Salmonella gene expression control that is orchestrated by this sRNA. In particular, STnc440 was found to be involved in the regulation of multiple bacterial target mRNAs by direct base pair interaction with consequences for Salmonella virulence and

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“…TRIzol) bias against longer transcripts (Stead et al, 2012). TRIzol extraction has further been reported to deliver RNA in low yield for some bacterial species (Jahn et al, 2008).…”

Section: Defining the Minimal Materials Requirements For A Dual Rna-sementioning

confidence: 99%

Dual RNA-seq of pathogen and host

2012

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“…The level of DNA contamination may be genus/species and RNA isolation method specific. Generally 1-2 treatments of RNA sample with DNase is considered as the necessary minimum (Jahn et al 2008). From the two different primer pairs tested, the primers Peant1/Peant2 and AJ75/AJ76 were much more sensitive and allowed us to detect even small amounts of DNA in the samples where it was not detected using the primers Ea71/72.…”

Section: Resultsmentioning

confidence: 99%

“…Although laboratory methods have already been described (Mehra 1996), many researchers are using commonly available commercial kits that allow for rapid extraction of high-quality and high-quantity RNA appropriate for high-throughput analysis. However, different RNA extraction kits have proven to vary in yield and level of quality and integrity of the obtained RNA very often, depending on the type of sample (Jahn et al 2008;Nour et al 2010;Rump et al 2010;Deng et al 2005). Therefore, in order to obtain good quality RNA from the target sample/organism, the different RNA extraction methods or kits should be carefully examined prior to their use in gene expression profiling methods and other applications.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of different RNA extraction methods for high-quality total RNA and mRNA from Erwinia amylovora in planta

et al. 2016

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Obtaining a sufficient quantity of high-quality, intact RNA is the first crucial step in its study by RNA sequencing on next-generation sequencing platforms or quantitative PCR. Different RNA extraction methods or commercial kits vary in yield and in the quality and integrity of the RNA obtained, which may affect the results of downstream applications. Often, these factors depend on the organism under study and nature of the sample. Therefore, the selection of an appropriate RNA isolation method is critical. In this study, we present the results of an evaluation of three different commercial kits for the isolation of total RNA from Erwinia amylovora in apple tissue as well as the usefulness of different kinds of Deoxyribonuclease I for DNA removal and kits for rRNA depletion. To our knowledge, this is the first report on the method of isolation of high-quality E.amylovora mRNA for RNA-seq.

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“…Jahn et al assessed bacterial RNA quality by RIN and found it to be critical for obtaining meaningful gene expression data. In their study, RIN values below 7.0 resulted in high variation and loss of statistical significance when gene expression was analyzed by quantitative real-time polymerase chain reaction [13].…”

Section: Discussionmentioning

confidence: 98%