Dataset Information

Assays for precise quantification of total (including short) and elongated HIV-1 transcripts.

ABSTRACT: Despite intensive study, it is unclear which mechanisms are responsible for latent HIV infection in vivo. One potential mechanism is inhibition of HIV transcriptional elongation, which results in short abortive transcripts containing the trans-activation response (TAR) region. Because the relative levels of total (including short) and processive transcripts provide measures of HIV transcriptional initiation and elongation, there is a compelling need for techniques that accurately measure both. Nonetheless, prior assays for total transcripts have been semi-quantitative and have seen limited application to patient samples. This manuscript reports the validation of quantitative reverse transcription (RT) droplet digital PCR assays for measurement of total (TAR) and processive (R-U5/gag) HIV transcripts. Traditional RT priming strategies can efficiently detect the TAR region on long HIV transcripts but detect <4% of true short transcripts. The TAR assay presented here utilizes an initial polyadenylation step, which provides an accessible RT priming site and detects short and long transcripts with approximately equal efficiency (70%). By applying these assays to blood samples from 8 ART-treated HIV+ individuals, total HIV transcripts were detected at levels >10-fold higher than elongated transcripts, implying a substantial block to transcriptional elongation in vivo. This approach may be applied to other difficult-to-prime RNA targets.

SUBMITTER: Kaiser P

PROVIDER: S-EPMC5560404 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Assays for precise quantification of total (including short) and elongated HIV-1 transcripts.

Kaiser Philipp P Joshi Sunil K SK Kim Peggy P Li Peilin P Liu Hongbing H Rice Andrew P AP Wong Joseph K JK Yukl Steven A SA

Journal of virological methods 20161227

Despite intensive study, it is unclear which mechanisms are responsible for latent HIV infection in vivo. One potential mechanism is inhibition of HIV transcriptional elongation, which results in short abortive transcripts containing the trans-activation response (TAR) region. Because the relative levels of total (including short) and processive transcripts provide measures of HIV transcriptional initiation and elongation, there is a compelling need for techniques that accurately measure both. N ...[more]

PMID: 28034670

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Project description:BackgroundMass spectrometry based quantification of peptides can be performed using the iTRAQ reagent in conjunction with mass spectrometry. This technology yields information about the relative abundance of single peptides. A method for the calculation of reliable quantification information is required in order to obtain biologically relevant data at the protein expression level.ResultsA method comprising sound error estimation and statistical methods is presented that allows precise abundance analysis plus error calculation at the peptide as well as at the protein level. This yields the relevant information that is required for quantitative proteomics. Comparing the performance of our method named Quant with existing approaches the error estimation is reliable and offers information for precise bioinformatic models. Quant is shown to generate results that are consistent with those produced by ProQuant, thus validating both systems. Moreover, the results are consistent with that of Mascot 2.2. The MATLAB scripts of Quant are freely available via http://www.protein-ms.de and http://sourceforge.net/projects/protms/, each under the GNU Lesser General Public License.ConclusionThe software Quant demonstrates improvements in protein quantification using iTRAQ. Precise quantification data can be obtained at the protein level when using error propagation and adequate visualization. Quant integrates both and additionally provides the possibility to obtain more reliable results by calculation of wise quality measures. Peak area integration has been replaced by sum of intensities, yielding more reliable quantification results. Additionally, Quant allows the combination of quantitative information obtained by iTRAQ with peptide and protein identifications from popular tandem MS identification tools. Hence Quant is a useful tool for the proteomics community and may help improving analysis of proteomic experimental data. In addition, we have shown that a lognormal distribution fits the data of mass spectrometry based relative peptide quantification.

Dataset Information

Assays for precise quantification of total (including short) and elongated HIV-1 transcripts.

Publications

Assays for precise quantification of total (including short) and elongated HIV-1 transcripts.

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