- Email: [email protected]
Comparison and optimization of methods for the simultaneous extraction of DNA, RNA, proteins, and metabolites
Accepted Manuscript Comparison and Optimization of Methods for the Simultaneous Extraction of DNA, RNA, Proteins, and Metabolites Fränze Vorreiter, Silke Richter, Michel Peter, Sven Baumann, Martin von Bergen, Janina M. Tomm PII:
S0003-2697(16)30086-0
DOI:
10.1016/j.ab.2016.05.011
Reference:
YABIO 12384
To appear in:
Analytical Biochemistry
Received Date: 12 February 2016 Revised Date:
12 May 2016
Accepted Date: 16 May 2016
Please cite this article as: F. Vorreiter, S. Richter, M. Peter, S. Baumann, M. von Bergen, J.M. Tomm, Comparison and Optimization of Methods for the Simultaneous Extraction of DNA, RNA, Proteins, and Metabolites, Analytical Biochemistry (2016), doi: 10.1016/j.ab.2016.05.011. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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ACCEPTED MANUSCRIPT Comparison and Optimization of Methods for the Simultaneous Extraction of DNA,
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RNA, Proteins, and Metabolites
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Fränze Vorreiter a, Silke Richter a, Michel Peter a, Sven Baumann a, Martin von
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Bergen a,b,c Janina M. Tomm a,*
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a
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Research - UFZ, Permoser Str. 15, 04318 Leipzig, Germany
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b
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Brüderstrasse 32, 04103 Leipzig, Germany c
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Faculty of Biosciences, Pharmacy and Psychology, University of Leipzig,
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Department of Molecular Systems Biology, Helmholtz-Centre for Environmental
Department of Chemistry and Biosciences, Aalborg University, Denmark
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* Corresponding author.
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E-mail address: [email protected] (J. Tomm)
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Janina M. Tomm, Helmholtz-Centre for Environmental Research - UFZ, Department of Proteomics, Permoser Str. 15, 04318 Leipzig, Germany Tel.: +49-341-2351819 Fax: +49-341-2351787
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ACCEPTED MANUSCRIPT ABSTRACT
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The challenge of performing a time-resolved comprehensive analysis of molecular
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systems has led to the quest to optimize extraction methods. When the size of a
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biological sample is limited, there is demand for the simultaneous extraction of
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molecules representing the four areas of ‘omics,’ genomics, transcriptomics,
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proteomics, and metabolomics. Here,we optimized a protocol for the simultaneous
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extraction of RNA, proteins, and metabolites and a compared it to tow existing
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protocols.second for the concurrent recovery of DNA, RNA, and proteins and
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compared it to two existing protconducted a previouslty described method. Our
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optimisation comprised the addition of a methanol/chloroform metabolite purification
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before the separation of DNA/RNA and proteins . Extracted DNA, RNA, proteins, and
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metabolites were quantitatively and/or qualitatively analyzed. Of the three methods,
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only the newly developed protocol yielded all biomolecule classes of adequate
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quantity and quality.
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Keywords: Molecular systems biology, genomics, transcriptomics, proteomics,
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metabolomics
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Highlights:
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- The optimized method allows genomic, transcriptomic, proteomic, and metabolic
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analysis from the identical sample
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- The quality of the extracted different classes of molecules were checked and also
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compared to well established methods for the purification of single molecule classes
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ACCEPTED MANUSCRIPT - The method was validated on two different cell types, namely immune cells and
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hepatocytes
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Introduction Systems biology is as an inter-disciplinary field focussed on the understanding of
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cellular systems at the molecular level. Various ‘omic’ technologies are utilized to
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gain insight into the complex interactions of biomolecules within biological systems
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on a comprehensive scale [1]. Technical developments in genomics, transcriptomics,
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proteomics, and metabolomics enable monitoring and quantification of biomolecules
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in a high-throughput manner [2; 3; 4]. The integration of omic-technologies is difficult
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when not the very same sample is used for comprehensive molecular analysis.
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Hence it is necessary to development methods for the simultaneous extraction and
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effective recovery of the target biomolecules DNA, RNA, proteins, and metabolites.
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So far protocols exist for isolating three of the four molecule classes [5; 6] or all four
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from prokaryotes [7], but there is currently no reliable method for the simultaneous
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extraction of the four molecule classes from eukaryotic cells.
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The goal of this study was to optimize a method for the simultanous extraction of
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DNA, RNA, proteins, and metabolites test and compare it to the already existing two
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well established methods that were designed to extract only one class of molecules
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specifically. We applied it to the analysis of Jurkat T cells as a model for native
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human T cells [8], and in order to rule out cell line specific effects we also tested the
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process by analysing murine hepatocyte cells.
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Our method (C) was based on our good experience with the simultanous
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purification of RNA, DNA and proteins starting with a phenol/chloroform-based
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extraction. In order to purify also metabolites we added a methanol/chloroform based
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extraction of metabolites prior to the phenol/chloroform based steps.
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ACCEPTED MANUSCRIPT Our method was compared to the method (here method A) reported by
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Weckwerth et al. (2004) describing the concomitant extraction of RNA, proteins, and
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metabolites from plant material [9]. We subsequently probed the quality of the
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remaining DNA fractionated by this protocol. Also the results of a third method
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(method B) based on the manufacturer’s protocol of the TRI Reagent® for RNA,
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DNA, and protein isolation, with an additional step included to extract metabolites
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was tested (Sigma-Aldrich.com) was tested for the two different cell lines.
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The suitability of the extraction methods for the biomolecule classes was
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evaluated by assessing the quantity and quality of DNA and RNA, the number of
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proteins and the proteome coverage, and the detection of hydrophilic metabolites of
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the central carbon and nitrogen metabolism. Since the protocols tested resulted in
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differing extraction efficacies for the omic-technologies, this study will aid in selecting
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the most suitable method for a specific research question.
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Materials and Methods
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Cell culture
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Human Jurkat T-cells (clone E6-1, ATCC, Germany) were cultured in RPMI-1640
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medium containing 10% (v/v) foetal calf serum, 1% (v/v) streptomycin (100
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mg/mL)/penicillin (100 U/mL), and 1% (v/v) L-glutamine in a CO2 incubator (MCO-
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18AIC, Sanyo Electric Co Ltd, Japan) at 37 °C and a n atmosphere of 5% CO2. The
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cells were cultured at a density of 1x106 cells/mL. Murine Hepa 1c1c7 cells (clone
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CRL-2026, ATCC, Germany) were cultured in DMEM medium containing 10% (v/v)
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(v/v) L-glutamine in a CO2 incubator at a density of 1x104 cells/cm². Cell viability and
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cell numbers were determined using trypan blue and a Neubauer-improved-chamber
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(Optic Labor, Germany). Aliquots of 1x107 cells were washed twice with 1x PBS and
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centrifuged at 300 x g for 5min. The obtained cell pellets were resuspended in 50 µL
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PBS and processed via method A, B, C or well established protocols. Each method
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was conducted in triplicate.
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Method A
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The pelleted Jurkat T or Hepa cells were processed as described in Weckwerth
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et al. [9] with modification as follows: The RNA buffer phase was directly subjected to
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acetic acid/ethanol precipitation of nucleic acids. An extraction buffer (EB) of 0.05 M
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Tris (pH 7.6), 0.5% SDS, and 1% ß-mercaptoethanol was used. The precipitated
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nucleic acids were resuspended in 100 µL water, and proteins in 300 µL 1M urea,
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0.05 M Tris (pH 7.6), for further analysis. DNA and RNA samples were stored at -80
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°C, and metabolite and protein samples were stored at -20 °C until further analysis.
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Method B
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To a pellet of Jurkat T or Hepa cells, 50 µL of 1x PBS and 1 ml of TRI Reagent®
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(Sigma-Aldrich Chemie GmbH, Steinheim, Germany) were added and processed
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according to the manufacturer’s instructions with modifications as follows: After TRI
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Reagent/chloroform extraction, RNA was precipitated by addition of 0.5 ml ice-cold
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isopropanol and incubation for 10 min at room temperature followed by centrifugation
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for 10 min at 4 °C and 4000 x g. The supernatant containing the metabolites was
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subsequently transferred to a fresh tube and dried under vacuum. DNA was
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resuspended in 300 µL 8 mM NaOH, RNA in 50 µL H2O, and proteins in 100 µL 1%
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SDS.
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Method C
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An aliquot of Jurkat T or Hepa cells was dissolved in 1 mL of a 45% (v/v)
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methanol/5% (v/v) chloroform solution and incubated for 30 min at 4 °C, while
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rotating. The cell suspension was centrifuged at 500 x g for 10 min, and the
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metabolite-containing supernatant was transferred to a new tube and dried under
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vacuum.
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The remaining pellet was resuspended in 100 µL 1x PBS. Approximately 1 mL of
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H2O saturated phenol was added for separation of RNA, DNA, and proteins, and the
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sample was incubated for 5 min at 4 °C, while rotat ing. For phase separation, 200 µL
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of chloroform were added, and the sample was incubated for 5 min at room
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temperature (RT) followed by centrifugation at 12 000 x g for 15 min at 4 °C. After
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phase separation, the upper RNA-containing phase was mixed with 500 µL ice-cold
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isopropanol, incubated for 10 min at RT, and centrifuged for 20 min at 12,000 x g at 4
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°C. The obtained RNA pellet was washed using 75% (v /v) ethanol, air dried for 10-15
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min at RT, and resuspended in 50 µL H20. To the remaining middle and lower phase
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of the phenol chloroform extraction, 500 µL of DNA extraction buffer (4 M
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guanidinium thiocyanate, 50 mM sodium citrate, 1 M Tris-base = DEB) was added.
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The solution was mixed by inversion, incubated for 30 min at RT, and centrifuged for
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20 min at 12 000 x g at 4 °C. For DNA precipitation, 500 µL of ice-cold isopropanol
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incubation for 10 min at RT, the solution was centrifuged for 20 min at 12,000 x g at 4
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°C. The DNA-containing pellet was washed twice by a dding 1.5 mL of 75% (v/v)
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ethanol and centrifuged for 10 min at 7,500 x g. The pellet was dried at room
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temperature for 10 min and resuspended in 100 µL TE-buffer.
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For protein extraction, 1.5 mL of ice-cold isopropanol was added to the remaining
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lower phase, and the sample was incubated overnight at -20 °C to precipitate the
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proteins. The solution was then centrifuged for 15 min at 12,000 x g at 4 °C. The
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protein pellet was washed by addition of 1 mL of 0.3 M guanidinium chloride in 90%
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(v/v) ethanol, incubation for 10 min at room temperature, and subsequent
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centrifugation for 5 min at 7,500 x g at 4°C. The pellet was washed a second time
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with 1 mL ethanol. The protein pellet was dried for 20-30 min at RT and dissolved in
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100 µL 6 M urea/2 M thio-urea in 100 mM ammonium bicarbonate buffer.
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Well established control Methods
For isolation of DNA from Jurkat and Hepa cells, the genomic DNA isolation kit
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from Zymo Research (California, USA) was used following manufacturer instructions.
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The DNA was eluted from columns in 100 µL TE-buffer.
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RNA from Jurkat and Hepa cells was extracted using the Qiagen RNeasy Mini Kit (Hilden, Germany). For elution of RNA from the columns, 50µL H2O was used.
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Extraction of Jurkat and Hepa cell proteins was performed by lysing the cells with
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6 M urea/2 M thio-urea in 100 mM ammonium bicarbonate for 5 min at RT followed
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by ultra-sonication for 30 sec. Samples were subsequently centrifuged for 5 min at
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12,000 x g at 4 °C, and the protein-containing supernatant wa s transferred to a new
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tube.
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For extraction of metabolites, a hot water method (G1) and a boiling ethanol method (G2) were conducted as described by Canelas et al. [10].
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DNA quality control
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The quantity of isolated DNA was determined for all methods by ND
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spectrophotometer (Thermo Scientific, Germany), and the quality was tested by 0.8%
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(w/v) agarose gel electrophoresis. A 16.7 µL sample of DNA extracted via method A
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and 600 ng samples of DNA extracted via methods B and C were each mixed with 6x
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DNA Loading Dye (Thermo Scientific, Germany). Genomic DNA showing a distinct
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signal in the high molecular range of ~20 kB was considered to be intact or only
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partially degraded at the end of the extraction procedure.
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For evaluation of DNA quality, Jurkat DNA samples were further analyzed by
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Polymerase Chain Reaction (PCR) using the DNA quality Ready Kit (Bio-Budget
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Technologies GmbH, Krefeld, Germany) following manufacturer’s instructions. PCR
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batches were calculated on a total volume of 12 µL. A sample of 48 ng of gDNA
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(methods B, C, and GS) and 2.4 µL of 1:10 diluted gDNA extracted via method A
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were inserted into the gDNA quality control PCR. PCR products were separated on a
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1.8% (w/v) agarose gel. The amplification of 6 PCR fragments of 100 bp, 200 bp, 300
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bp, 400 bp, 500 bp (control fragment), and 600 bp of genomic DNA indicates that the
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corresponding DNA was not found degraded after the extraction process. Fewer than
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six amplicons showed DNA with any degree of degradation.
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RNA quality control
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The quantity of extracted RNA was determined by ND spectrophotometer
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(Thermo Scientific, Germany), and its quality was assessed by analyzing 10 µL
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(method A) or 1.5 µg (methods B, C, and GS) on 1.8% (w/v) agarose gel. Each
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sample was mixed with 2x RNA Loading Dye (Thermo Scientific, Germany), applied
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to a gel, and run for 45 minutes at 100V. RNA samples showing the characteristic
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ribosomal RNA bands of 5070 bp and 1869 bp with no background noise were
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considered to be intact, or only slightly degraded, at the end of the extraction
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procedure.
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One µL of 1:3 diluted RNA (method A) and 50 ng of extracted RNA (methods B,
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C, and GS) were applied to an RNA Nano Chip (Agilent Technologies, Waldbronn,
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Germany) and run on an Agilent 2100 Bioanalyzer following the manufacturer’s
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instructions. RNA with RNA integrity number (RIN) values greater than eight were
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considered to be intact and usable for qPCR and other follow-up experiments.
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Protein quality control
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The quantity of isolated proteins was determined using Quick Start – Bradford
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Dye Reagent according to the manufacturer’s instructions (Bio-Rad Laboratories
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GmbH, Germany). The quality of extracted proteins was evaluated by separation of
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30 µg proteins by SDS-PAGE followed by Coomassie Brilliant Blue staining
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according to the method described in [11]. The protein lane of each sample was cut
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into four slices and each slice (~7.5 µg protein) was digested with 150 ng trypsin .
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Generated peptides were extracted from the gel pieces and analyzed via LC-MS/MS
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LTQ Orbitrap XL mass spectrometer (Thermo Fisher Scientific, San Jose, CA, USA),
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and liquid chromatography was carried out using a 110 min gradient with 0.1% formic
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acid in 100% water (solvent A) and 100% acetonitrile (solvent B). After sample
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injection into a trapping column (nanoAcquity UPLC column, C18, 180 µm x 20 mm,
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5 µm particles, Waters), peptides were separated on a C18 column (nanoAquity
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UPLC column, C18, 7 µm x 150 mm, 1.7 µm particles, Waters) using the following
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gradient of solvent B in solvent A: starting at 2%, reaching 6% after 5 min, 20% after
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45 min, 30% after 70 min, 40% after 75 min, 85% after 80 min, 2% after 95 min and
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washing for 15 min at 2%.with a flow rate of 300 nL/min.
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Full-scan MS spectra (from 300 to 2000 m/z, R = 60000) were acquired in a
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positive ion mode in the LTQ-Velos Orbitrap. Up to 10 most intense ions per scan
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with a charge >2 were fragmented and analysed in the linear trap. Peptide ions
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exceeding intensity of 3000 were chosen for collision-induced dissociation within the
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linear ion trap (isolation width 4 m/z, normalized collision energy 35%, activation time
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30 ms, activation q = 0.25). For MS/MS acquisition, a dynamic exclusion of 2 min
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was applied. For a more detailed description see Baumann et al., 2014 [12]. Data
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analysis of the mass spectrometric results was performed using MaxQuant (version
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1.3.0.5) including the following search parameters: ion mass tolerance of 0.5 Da and
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a parent ion tolerance of 20 ppm. Carbamidomethylation of cysteine was specified as
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a fixed modification. Oxidation of methionine and acetylation of the protein N-
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terminus were specified as variable modifications. MaxQuant was set up to search a
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reverse concatenated database of all human proteins annotated in the SwissProt
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database (version 10/01/2013) assuming the digestion enzyme trypsin. Only proteins
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found in two of three replicates were considered unambiguously identified.
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Metabolite analysis
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For ion chromatography-tandem mass spectrometry (IC-MS/MS)-based analysis
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of metabolites, extracts were dissolved in a total volume of 25 µL and analyzed on an
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ICS-5000 (Thermo Fisher Scientific, Dreieich, Germany) coupled to an API 5500
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QTrap (AB Sciex) as described elsewhere [13]. Separation was obtained on an
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IonPac AS11-HC column (2 x 250mm, Thermo Fisher Scientific) with an increasing
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potassium hydroxide gradient. Mass spectrometry analysis was performed in MRM
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mode
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carbohydrates, and nucleotides involved in central metabolite pathways. Metabolites
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were considered to be detectable above a signal-to-noise ratio of three, within a
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retention time window of 0.5 min.
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Results and Discussion
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Time and material required for performing the three extraction methods
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The optimized protocols used to separate the target biomolecules from a single
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sample of Jurkat T cells or Hepa cells is shown in Fig. 1., the others are shown in
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the supplement (Fig. S1 and Fig. S2)
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Method A was based on a study describing the simultaneous extraction of RNA,
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proteins, and metabolites from plant material [9]. Metabolites are extracted by a
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methanol/chloroform treatment, leaving a pellet that can be used for further protein,
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DNA, and RNA extraction using phenol-based phase separation [9]. Notably, this
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protocol does not produce separation of RNA from DNA. Method B was based on the TRI Reagent® manufacturer’s protocol (Sigma-
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Aldrich) for RNA, DNA, and protein isolation. The cell pellet was resuspended in TRI
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Reagent®, enabling the successive isolation of RNA, DNA, and proteins. Metabolites
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were obtained from the supernatant remaining after precipitation of RNA, and
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proteins by vacuum-drying of the respective fraction.
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Method C involved a novel process of methanol/chloroform-based extraction of
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metabolites followed by RNA, DNA, and protein extraction using a phenol/chloroform
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extraction.
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The three methods required similar time and materials. Protocol A could be
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performed in 4 h plus an additional hour the following day for centrifugation and
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ethanol washing to remove remaining phenol from proteins isopropanol-precipitated
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overnight. Using method B, it was possible to extract all four biomolecule classes in
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4 h, since proteins were not precipitated overnight. Protocol C could be carried out in
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3 h plus an additional 1.5 h the following day for pelleting and phenol depletion of
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proteins
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phenol/chloroform-based phase partitioning, enabling the separation of nucleic acids
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from proteins. Protocols A and C involved methanol/chloroform-based metabolite
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extraction steps prior to DNA, RNA and protein isolation. Considering only time and
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material required, method B would be the protocol of choice, the disadvantage being
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that only three of the four molecule classes, namely DNA, RNA and proteins can be
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isolated.
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DNA isolation: enrichment strategies, purity, and yield
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DNA samples from method A contained also RNA when separated on an agarose
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gel, since no further partitioning of the nucleic acid classes was conducted. In
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addition, DNA extracted via method A was found to be partially degraded at the end
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of the purifiation on the agarose gel. With methods B, C, and the well established
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method (GS), the extracted DNA did not show RNA content as judged by agarose
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gel, or signs of degradation in Jurkat or Hepa cells (data not shown). For assessing
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quality and integrity, the extracted Jurkat DNA was further analyzed by PCR using
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the DNA quality Ready Kit (Bio-Budget Technologies GmbH, Krefeld, Germany).
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PCR products were analyzed by agarose gel electrophoresis. DNA extracted via
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method A showed weaker signal intensities for the expected PCR products than that
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derived from methods B, C, and GS (Fig. 2A). The kit is designed for human
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samples, and application to murine Hepa cell DNA was unsuccessful. Methods B and
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C can be used for the extraction of genomic DNA, showing acceptable DNA integrity
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and purity for further applications.
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The resulting quantifies of extraction fo the different molecule classes are
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summerized in table 1. The gDNA content determined via nanodrop for method A
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cannot be considered accurate, as both RNA and DNA were present in the sample.
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In addition, the DNA obtained by method B was difficult to dissolve and remained
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viscous, making the determined quantity questionable. Nevertheless, the volume of
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DNA isolated with the tested methods was more than sufficient for standard genomic
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applications such as PCR or DNA-sequencing, which need approximately 60 ng and
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1 µg of genomic DNA, respectively.
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RNA isolation: enrichment strategies, integrity, and yield
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When using method A, the RNA was mixed with DNA and partially degraded as
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showe by the 1.8% agarose gel. For methods B, C, and GS, no RNA degradation
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was detected (data not shown), and Bioanalyzer measurements confirmed its
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integrity, with RIN values ranging from 8.4 to 10, while values were 3.3 to 3.8 for
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method A (Fig 2B). For downstream transcriptomic analyses, including qPCR
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applications, it is generally recommended to use RNA samples with a minimum RIN
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of 7 [14]. Methods B, C, and GS are suitable for the extraction of high quality RNA
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that can be used in downstream applications.
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We isolated approximately 28.7 (Jurkat) / of RNA from 1x107 cells using method
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A (Nanodrop / containing DNA), 78.9 / 380.7 µg using method B, 13.8 / 161.6 µg
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using method C, and 14.4 / 7.7 µg with GS (Table 1).
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From Jurkat cells, we isolated approximately 28.7 µg of RNA using method A
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(nanodrop), 78.9 µg using method B, 13.8 µg using method C, and 14.4 / 7.7 µg with
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the GS. Hepa cells yielded approximately 79.6 µg with method A, 380.7 µg with
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method B, 161.6 µg with method C, and 7.7 µg with GS (Table 1).
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Methods B and C and WEM yielded a quantity of RNA sufficient for further
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analyses, such as RNA sequencing (requiring 500 ng of DNase-treated RNA) and
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reverse transcription followed by quantitative PCR (recommended 5 µg of DNase-
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treated RNA). With method A, RNA and DNA were combined.
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Protein isolation: enrichment strategies, purity, physicochemical bias, and yield
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As with RNA and DNA, the yield of extracted proteins varied for the three
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protocols and the well established method (WEM): From Jurkat cells, method A
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produced 147.7 µg, method B 65.3 µg, method C 125.8 µg, and WEM 519.3 µg.
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Yield from Hepa cells was 465.4 µg for method A, 168.2 µg for method B, 323.2 µg
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for method C, and 961.3 µg for WEM (Table 1).
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Resuspension of proteins using 1% SDS (method B) was difficult to impossible,
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and a large portion of the pellet remained undissolved. This was also reported by
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Simões et al. [15], who found that further modifications of the protocol, including
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urea:SDS solubilization and sonication, increased protein yield.
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Equal volumes of protein (30 µg) extracted by the three methods and the GS
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were precipitated, resuspended in sample buffer, and separated in a 12% SDS-
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polyacrylamide gel (Fig. 2C). The peptides obtained by in-gel digestion were
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extracted and analyzed using LC-MS/MS. Coomassie-stained SDS-polyacrylamide
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gel indicated low molecular weight proteins (<35 kDa) to be underrepresented using
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method A compared to extraction via method B and C (Figure 2C). The tendency of
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proteins <25 kDa to be underrepresented in global proteome studies can be
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associated with factors such as lower efficacy of precipitation [16], loss during
357
destaining [17], or a scarcity of readily detectable tryptic peptides [18].
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Visual comparison of band patterns in SDS-gel lanes corresponding to extracts
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derived from methods A, B, and C revealed distinct similarities. High molecular
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weight proteins showed similar abundance in extracts of the three methods. For more
361
comprehensive insight into the proteome data, the proteins/peptides identified in
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Jurkat T cells and Hepa cells by methods A-C were analyzed in greater detail (Fig. 16
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ACCEPTED MANUSCRIPT 3). The detection overlap of the three methods was greater for Hepa cells than for
364
Jurkat T cells (Fig. 3a). Mass spectrum analysis yielded similar numbers of identified
365
proteins and demonstrated a broad overlap of the three protocols and Jurkat T cells
366
(A, 1318 identified proteins; B, 1253; C, 1323) (Fig. 3c). The three methods showed
367
an overlap of 873 identifications. Methods A and B show an overlap of 89+873 hits,
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the overlap of methods B and C was 85+873; and method A and C overlap was
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247+873. In addition, 109 unique proteins were extracted and identified via method
370
A, 206 using method B, and 118 with method C.
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A critical factor in extraction protocols is systematic bias due to physicochemical
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properties of the target molecules. This is not supposed to be crucial for molecules
373
like RNA and DNA whose building blocks are rather homogeneous but highly
374
relevant when the molecules differ substantially, as is the case with proteins.
375
Therefore we analysed the physicochemical parameters of the detected proteins
376
from Jurkat and Hepa cells: hydrophobicity (by GRAVY score), isoelectric point (pI),
377
and molecular weight (MW) (Fig 3B). The GRAVY scores calculated according to
378
Kyte and Dolittle (1982) [19] showed a Gaussian-type distribution pattern in the range
379
of -2 to approximately +0.5 with a maximum of -0.5 and a frequency of 120-160. The
380
pattern showed high similarity of extracted proteins to the GRAVY distribution of the
381
annotated human proteome (Uniprot 09/2013), but the GRAVY range of +0.2 to +1
382
was underrepresented, indicating that strongly hydrophobic proteins were not readily
383
targeted using the three methods. For strongly hydrophobic proteins, we recommend
384
use of dedicated protocols. Another possible reason for the relatively low recovery of
385
hydrophobic proteins might be the precipitation approach used. A study of urine
386
samples of limited complexity revealed that hydrophobic precipitation favoured the
387
enrichment of acidic and hydrophilic proteins and showed a negative bias against
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precipitation, it is not surprising that they show a similar bias. There were differences
390
in the proteomic profiles obtained by the three methods, hence the comparison of
391
proteomic analyses based on different extraction protocols is problematic.
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The pI profiles of identified proteins showed a similar distribution across
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extraction methods. They displayed two well-separated peaks: one at pI 4.0-7.0 with
394
a maximum of 5.0 and a frequency of 140, and a second at pI 7.0-12.0 with a
395
maximum of 9.0 and a frequency of 80. Compared to the pI distribution of the
396
annotated human proteome, the pI 8-10 protein fraction was underrepresented in the
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protein samples extracted via methods A, B, and C.
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The identified proteins showed similar MW distribution across methods, with a
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maximum frequency of 350-400 at 35-40 kDa and a gradual decrease in the range of
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75-200 kDa, with few proteins detected above 200 kDa. The three MW distribution
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profiles correlated well with the hypothetical distribution profile of the annotated
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human proteome.
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Metabolite extraction: enrichment strategies, purity, and yield
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As a benchmark for the efficacy of metabolite extraction, we used an established,
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targeted multi-analyte (> 40) approach [13], since we were primarily interested in the
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primary products of carbon and nitrogen metabolism. Method B was not suitable for
409
the extraction of metabolites by IC-MS/MS analysis, since the detergents of the TRI
410
Reagent® used have a negative influence on the detectability of target analytes. In
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the analysis of samples from method B, the MRM-chromatograms were
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characterized by a high level of background noise and a longer re-equilibration time
413
for consecutive runs. Method A produced 35 detectable metabolites in Jurkat cells and 23 in Hepa;
415
method C, 37 in both cell types; and GS1, 30 in Jurkat and 31 in Hepa, and 29 in
416
Jurkat and 30 in Hepa for GS2 (Fig. 4). All metabolites detected with method A were
417
present in the MRM-chromatograms of method C. The intensities were higher in
418
method C by a factor of 5 to 15, indicating clearly higher recovery of the target
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analytes by method A. At least six metabolites detected with the identical
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instrumental setup in earlier studies [12; 21] were not found after extraction method A
421
in this study.
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Conclusions
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The comparison of three methods for simultaneous extraction of DNA, RNA,
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proteins, and metabolites from Jurkat T cells and hepatocytes showed adequate
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agreement between the cell lines. Method A was found suitable for metabolite and
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protein extraction, but not for specific extraction of RNA and DNA, and produced
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slightly lower detection of metabolites than method C. Method B provided high quality
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RNA and protein samples, but nearly unresolvable DNA and protein. Our attempts to
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add metabolite extraction to method B failed, as assessed by IC-MS/MS. Only
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method C provided DNA, RNA, protein, and metabolite samples that passed all
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quality benchmarks in both tested cell lines.
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Figure legends
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ACCEPTED MANUSCRIPT Fig. 1. Schematic of extraction procedure. The newly developed process for the
437
extraction of four biomolecule classes from a single set of cells is depicted. EB =
438
extraction buffer (method A), DEB = DNA extraction buffer (method C).
439
Fig. 2. Quality assessment of three of the four molecule classes isolated. A) PCR for
440
gDNA quality determination: 48 ng gDNA (method B and C) and 1 µL of 1:10 diluted
441
gDNA extracted via method A were inserted into gDNA quality control PCR. B)
442
Results of Agilent 2100 Bioanalyzer measurements: 50 ng RNA (method B and C)
443
and 1 µL of 1:3 diluted RNA extracted via method A were applied to an RNA
444
nanochip. C) Separation of 30 µg protein extracted using the three methods in a 12%
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SDS-polyacrylamide gel, followed by Coomassie Brillant Blue G250 staining. Each
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lane was cut into 4 parts and subjected to tryptic digestion followed by LC-MS/MS.
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Fig 3. Overlap and physicochemical properties of identified proteins. Proteins
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identified by LC-MS/MS after tryptic digestion of 30 µg protein extracted by the three
450
methods from 1x107 Jurkat T cells and 1x107 Hepa 1c1c7 cells. A) number and
451
overlap of proteins identified, B) grand average of hydropathy (GRAVY), molecular
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weight and pI distribution of the corresponding proteome (human or murine) and of
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identified proteins, C) proportion of identified proteins isolated by the gold standard
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protein extraction method that was also found with method A, B, and C.
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Fig. 4. Metabolites determined by IC-MS/MS extracted by the three methods. Green
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boxes indicate potential quantitative measurements, red boxes indicate no metabolite
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detection.
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Table 1
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Yield, quality, and sensitivity of detection of the four classes of biomolecules
463
extracted from 1x107 Jurkat T cells and Hepa 1c1c7 cells by the three methods.
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Molecules marked in red have limited downstream usage. The quality of enrichment
465
is indicated by asterisks (* = low quality to *** = high quality). The number of
466
metabolites detected by each approach is indicated.
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[1] T. Ideker, T. Galitski, and L. Hood, A new approach to decoding life: systems biology. Annu Rev Genomics Hum Genet 2 (2001) 343-72. [2] R. Aebersold, and M. Mann, Mass spectrometry-based proteomics. Nature 422 (2003) 198-207. [3] W.W. Soon, M. Hariharan, and M.P. Snyder, High-throughput sequencing for biology and medicine. Mol Syst Biol 9 (2013) 640. [4] W. Weckwerth, Metabolomics: an integral technique in systems biology. Bioanalysis 2 (2010) 82936. [5] W. Mathieson, and G.A. Thomas, Simultaneously extracting DNA, RNA, and protein using kits: is sample quantity or quality prejudiced? Anal Biochem 433 (2013) 10-8. [6] R. Radpour, M. Sikora, T. Grussenmeyer, C. Kohler, Z. Barekati, W. Holzgreve, I. Lefkovits, and X.Y. Zhong, Simultaneous isolation of DNA, RNA, and proteins for genetic, epigenetic, transcriptomic, and proteomic analysis. J Proteome Res 8 (2009) 5264-74. [7] H. Roume, A. Heintz-Buschart, E.E. Muller, and P. Wilmes, Sequential isolation of metabolites, RNA, DNA, and proteins from the same unique sample. Methods Enzymol 531 (2013) 219-36. [8] R.T. Abraham, Mutant T cell lines as model systems for the dissection of T cell antigen receptor signaling pathways. Immunol Res 22 (2000) 95-117. [9] W. Weckwerth, K. Wenzel, and O. Fiehn, Process for the integrated extraction, identification and quantification of metabolites, proteins and RNA to reveal their co-regulation in biochemical networks. Proteomics 4 (2004) 78-83. [10] A.B. Canelas, A. ten Pierick, C. Ras, R.M. Seifar, J.C. van Dam, W.M. van Gulik, and J.J. Heijnen, Quantitative evaluation of intracellular metabolite extraction techniques for yeast metabolomics. Anal Chem 81 (2009) 7379-89. [11] D. Georgieva, M. Risch, A. Kardas, F. Buck, M. von Bergen, and C. Betzel, Comparative analysis of the venom proteomes of Vipera ammodytes ammodytes and Vipera ammodytes meridionalis. J Proteome Res 7 (2008) 866-86. [12] S. Baumann, M. Rockstroh, J. Bartel, J. Krumsiek, W. Otto, H. Jungnickel, S. Potratz, A. Luch, E. Wilscher, F. Theis, M. von Bergen, and J. Tomm, Subtoxic concentrations of benzo[a]pyrene induce metabolic changes and oxidative stress in non-activated and aAect the mTOR pathway in activated Jurkat T cells. Journal of Integrated OMICS 4 (2014). [13] K. Murugesan, S. Baumann, D.K. Wissenbach, S. Kliemt, S. Kalkhof, W. Otto, I. Mogel, T. Kohajda, M. von Bergen, and J.M. Tomm, Subtoxic and toxic concentrations of benzene and toluene induce Nrf2-mediated antioxidative stress response and affect the central carbon metabolism in lung epithelial cells A549. Proteomics 13 (2013) 3211-21. [14] S. Fleige, and M.W. Pfaffl, RNA integrity and the effect on the real-time qRT-PCR performance. Mol Aspects Med 27 (2006) 126-39. [15] A.E. Simoes, D.M. Pereira, J.D. Amaral, A.F. Nunes, S.E. Gomes, P.M. Rodrigues, A.C. Lo, R. D'Hooge, C.J. Steer, S.N. Thibodeau, P.M. Borralho, and C.M. Rodrigues, Efficient recovery of proteins from multiple source samples after TRIzol((R)) or TRIzol((R))LS RNA extraction and long-term storage. BMC Genomics 14 (2013) 181. [16] B. Herbert, and E. Harry, Difficult proteins. Methods Mol Biol 519 (2009) 47-63. [17] C. Klein, M. Aivaliotis, J.V. Olsen, M. Falb, H. Besir, B. Scheffer, B. Bisle, A. Tebbe, K. Konstantinidis, F. Siedler, F. Pfeiffer, M. Mann, and D. Oesterhelt, The low molecular weight proteome of Halobacterium salinarum. J Proteome Res 6 (2007) 1510-8. [18] S.A. Muller, T. Kohajda, S. Findeiss, P.F. Stadler, S. Washietl, M. Kellis, M. von Bergen, and S. Kalkhof, Optimization of parameters for coverage of low molecular weight proteins. Anal Bioanal Chem 398 (2010) 2867-81. [19] J. Kyte, and R.F. Doolittle, A simple method for displaying the hydropathic character of a protein. J Mol Biol 157 (1982) 105-32. [20] V. Thongboonkerd, The variability in tissue proteomics. Proteomics Clin Appl 6 (2012) 340-2.
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[21] J. Murugaiyan, M. Rockstroh, J. Wagner, S. Baumann, K. Schorsch, S. Trump, I. Lehmann, M. Bergen, and J.M. Tomm, Benzo[a]pyrene affects Jurkat T cells in the activated state via the antioxidant response element dependent Nrf2 pathway leading to decreased IL-2 secretion and redirecting glutamine metabolism. Toxicol Appl Pharmacol 269 (2013) 307-16.
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Figure 1: Schematic illustration of the workflow method C used for the extraction of metabolites, proteins, RNA, and DNA. *DEB: DNA extraction buffer.
A [bp]
Ladder
ACCEPTED MANUSCRIPT Jurkat E6-1 NEG
EM
A
B
C
600 500 400 300
B
Hepa 1c1c7
Jurkat E6-1
EM A B C EM A B C 10 3.3 9.8 8.4 10 3.8 9.5 9.0 RIN
Hepa 1c1c7 EM
A
B
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[kDa]
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Jurkat E6-1
C
EM A
B
C
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200 150 120 100 85 70 60 50 40 30 25 20
Figure 2: Quality control of three of the four molecule classes isolated by method A, B, C or a well established method (EM). A) PCR for gDNA quality determination. 48 ng of gDNA (method B and C) and 1 µL of 1:10 diluted gDNA extracted via method A were inserted into a gDNA quality control PCR as described by the manufacturer. The detected band of 500 bp in the lane of the NEG is a control band derived from the kit that was used for quality determination. B) Results of the Agilent 2100 Bioanalyzer measurements, 50 ng of RNA (method B and C) and 1 µL of 1:3 diluted RNA extracted via method A were applied to a RNA Nano Chip. C) Separation of 30 µg protein extracted using the three different setups in a 12% SDS-polyacrylamide gel, followed by coomassie brillant blue G250 staining. Each lane was cut into 4 parts and subjected to tryptic digestion followed by LC-MS/MS.
ACCEPTED MANUSCRIPT Jurkat T cells
Hepa 1c1c7 cells
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A
C
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B
Figure 3: Overlap and physicochemical parameters of identified proteins. Proteins identified by LC-MS/MS after tryptic digestion of 30 µg protein extracted by the three different methods out of 1x107 Jurkat T cells and 1x107 Hepa 1c1c7 cells. A) number and overlap of proteins identified, B) grand average of hydropathy (GRAVY), molecular weight and pI distribution of the corresponding proteome (human or murine) and of identified proteins, C) proportion of identified proteins isolated by the gold standard protein extraction method that was also found when extracting proteins with method A, B or C.
ACCEPTED MANUSCRIPT
Jurkat T-cells A B
C
WEM1 WEM2
Hepatocytes A B
1.0 1.0 1.0 1.0 1.0 1.0
0.0 0.0 0.0 0.0 1.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 0.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 0.0 1.0 1.0 1.0
Gluconate 6-phosphate
1.0 1.0 0.0 0.0 1.0 0.0 1.0
0.0 0.0 0.0 0.0 0.0 0.0 1.0
1.0 1.0 0.0 1.0 1.0 1.0 1.0
1.0 1.0 0.0 0.0 1.0 1.0 1.0
1.0 0.0 0.0 0.0 0.0 0.0 1.0
1.0 0.0 0.0 0.0 0.0 0.0 1.0
1.0 1.0 1.0 1.0 1.0
1.0 0.0 0.0 0.0 0.0
1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 0.0 0.0
1.0 1.0 1.0 0.0 0.0
WEM1 WEM2
1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 0.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0
0.0 0.0 0.0 0.0 0.0 0.0 1.0
1.0 1.0 0.0 1.0 1.0 1.0 1.0
1.0 1.0 0.0 1.0 1.0 1.0 1.0
1.0 0.0 0.0 1.0 0.0 0.0 1.0
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1.0 1.0 1.0 0.0 0.0
1.0 0.0 0.0 0.0 0.0
1.0 1.0 1.0 1.0 1.0
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1.0 1.0 1.0 0.0 0.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
0.0 0.0 1.0 0.0 0.0 0.0 0.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
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0.0 0.0 1.0 0.0 0.0 0.0 0.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
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1.0 1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 0.0 1.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
0.0 1.0 1.0 0.0 0.0 0.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 0.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
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Ribulose/Ribose 5-phosphate Xylulose 5-phosphate Sedoheptulose 7-phosphate Erytrose 4-phosphate Ribose 1,5-bisphosphate Glycerol 3-phosphate Pyruvate metabolism Phosphoenolpyruvate Pyruvate Lactate Acetate Formate TCA cycle Citrate Aconitate Isocitrate Ketoglutaric acid Succinate Fumarate Malate Nucleotides Adenosine monophosphate Adenosine diphosphate Adenosine triphosphate Nicotinamide adenine dinucleotide Nicotinamide adenine dinucleotide phosphate Uridine diphosphate Uridine triphosphate Organic acids Maleate Acetate Formate Glycolate Tartrate Glyoxalate Aspartate Glutamate Ala, Asp and Glu metabolism Succinic semialdehyde
C
0.0 0.0 0.0 0.0 1.0 1.0
SC
Glucose Glucose 6-phosphate Glucose 1-phosphate Fructose 6-phosphate Fructose 1,6-bisphosphate 2-Phosphoglyceric acid Pentose phosphate pathway
RI PT
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0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1.0 1.0 1.0 0.0 1.0 0.0 1.0 0.0
1.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0
1.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0
1.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1.0 1.0 1.0 0.0 1.0 0.0 1.0 0.0
1.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0
1.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0
1.0
0.0
1.0
1.0
1.0
0.0
0.0
1.0
1.0
1.0
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Figure 4: Metabolites determined by IC-MS/MS extracted by the three different methods. Green boxes indicate possible quantitative measurements, red boxes indicate the lack of detectability.
ACCEPTED MANUSCRIPT
Protein
Metabol.
Hepa 1c1c7
RNA
WEM
µg 17.1 isolated quality *** µg 7.7 isolated quality *** µg 961.3 isolated quality *** µg 31/30 isolated quality ***
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DNA
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Protein
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Metabol.
35.8
174.9
*
*
28.7
78.9
*
***
147.7
65.3
125.8
***
***
8
37
*
***
*** 35
**
18.8
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RNA
µg 9.9 isolated quality *** µg 14.4 isolated quality *** µg 519.3 isolated quality *** µg 30/29 isolated quality ***
Method Method Method A B C
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WEM
***
13.8 ***
SC
Jurkat E6-1
Method Method Method A B C 99.5
153.6
45.2
*
*
***
79.6
380.7
161.6
*
***
***
465.4
168.2
323.2
***
***
***
23
8
37
**
*
***
Table 1: Yield, quality and sensitivity of detection of the four different classes of biomolecules after extraction from 1x107 Jurkat T cells and Hepa 1c1c7 cells by the three different methods. Molecules marked in red have limited downstream usage. The quality of enrichments is decribed here by one asterisk (low quality) up to three asterisks (high quality). For metabolites the number of detected metabolites by a targeted approach is indicated.
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Figure S1: Schematic illustration of the workflow method A used for the extraction of metabolites, proteins, RNA and DNA. *EB: extraction buffer.
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Figure S2: Schematic illustration of the workflow method B used for the extraction of metabolites, proteins, RNA, and DNA.
S0003-2697(16)30086-0
DOI:
10.1016/j.ab.2016.05.011
Reference:
YABIO 12384
To appear in:
Analytical Biochemistry
Received Date: 12 February 2016 Revised Date:
12 May 2016
Accepted Date: 16 May 2016
Please cite this article as: F. Vorreiter, S. Richter, M. Peter, S. Baumann, M. von Bergen, J.M. Tomm, Comparison and Optimization of Methods for the Simultaneous Extraction of DNA, RNA, Proteins, and Metabolites, Analytical Biochemistry (2016), doi: 10.1016/j.ab.2016.05.011. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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ACCEPTED MANUSCRIPT Comparison and Optimization of Methods for the Simultaneous Extraction of DNA,
2
RNA, Proteins, and Metabolites
3
Fränze Vorreiter a, Silke Richter a, Michel Peter a, Sven Baumann a, Martin von
4
Bergen a,b,c Janina M. Tomm a,*
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5
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a
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Research - UFZ, Permoser Str. 15, 04318 Leipzig, Germany
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b
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Brüderstrasse 32, 04103 Leipzig, Germany c
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Faculty of Biosciences, Pharmacy and Psychology, University of Leipzig,
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Department of Molecular Systems Biology, Helmholtz-Centre for Environmental
Department of Chemistry and Biosciences, Aalborg University, Denmark
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* Corresponding author.
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E-mail address: [email protected] (J. Tomm)
15 16 17 18
19
Janina M. Tomm, Helmholtz-Centre for Environmental Research - UFZ, Department of Proteomics, Permoser Str. 15, 04318 Leipzig, Germany Tel.: +49-341-2351819 Fax: +49-341-2351787
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ACCEPTED MANUSCRIPT ABSTRACT
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The challenge of performing a time-resolved comprehensive analysis of molecular
22
systems has led to the quest to optimize extraction methods. When the size of a
23
biological sample is limited, there is demand for the simultaneous extraction of
24
molecules representing the four areas of ‘omics,’ genomics, transcriptomics,
25
proteomics, and metabolomics. Here,we optimized a protocol for the simultaneous
26
extraction of RNA, proteins, and metabolites and a compared it to tow existing
27
protocols.second for the concurrent recovery of DNA, RNA, and proteins and
28
compared it to two existing protconducted a previouslty described method. Our
29
optimisation comprised the addition of a methanol/chloroform metabolite purification
30
before the separation of DNA/RNA and proteins . Extracted DNA, RNA, proteins, and
31
metabolites were quantitatively and/or qualitatively analyzed. Of the three methods,
32
only the newly developed protocol yielded all biomolecule classes of adequate
33
quantity and quality.
34
Keywords: Molecular systems biology, genomics, transcriptomics, proteomics,
35
metabolomics
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Highlights:
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- The optimized method allows genomic, transcriptomic, proteomic, and metabolic
39
analysis from the identical sample
40
- The quality of the extracted different classes of molecules were checked and also
41
compared to well established methods for the purification of single molecule classes
2
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ACCEPTED MANUSCRIPT - The method was validated on two different cell types, namely immune cells and
43
hepatocytes
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Introduction Systems biology is as an inter-disciplinary field focussed on the understanding of
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cellular systems at the molecular level. Various ‘omic’ technologies are utilized to
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gain insight into the complex interactions of biomolecules within biological systems
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on a comprehensive scale [1]. Technical developments in genomics, transcriptomics,
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proteomics, and metabolomics enable monitoring and quantification of biomolecules
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in a high-throughput manner [2; 3; 4]. The integration of omic-technologies is difficult
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when not the very same sample is used for comprehensive molecular analysis.
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Hence it is necessary to development methods for the simultaneous extraction and
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effective recovery of the target biomolecules DNA, RNA, proteins, and metabolites.
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So far protocols exist for isolating three of the four molecule classes [5; 6] or all four
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from prokaryotes [7], but there is currently no reliable method for the simultaneous
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extraction of the four molecule classes from eukaryotic cells.
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The goal of this study was to optimize a method for the simultanous extraction of
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DNA, RNA, proteins, and metabolites test and compare it to the already existing two
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well established methods that were designed to extract only one class of molecules
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specifically. We applied it to the analysis of Jurkat T cells as a model for native
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human T cells [8], and in order to rule out cell line specific effects we also tested the
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process by analysing murine hepatocyte cells.
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Our method (C) was based on our good experience with the simultanous
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purification of RNA, DNA and proteins starting with a phenol/chloroform-based
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extraction. In order to purify also metabolites we added a methanol/chloroform based
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extraction of metabolites prior to the phenol/chloroform based steps.
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Weckwerth et al. (2004) describing the concomitant extraction of RNA, proteins, and
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metabolites from plant material [9]. We subsequently probed the quality of the
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remaining DNA fractionated by this protocol. Also the results of a third method
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(method B) based on the manufacturer’s protocol of the TRI Reagent® for RNA,
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DNA, and protein isolation, with an additional step included to extract metabolites
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was tested (Sigma-Aldrich.com) was tested for the two different cell lines.
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The suitability of the extraction methods for the biomolecule classes was
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evaluated by assessing the quantity and quality of DNA and RNA, the number of
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proteins and the proteome coverage, and the detection of hydrophilic metabolites of
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the central carbon and nitrogen metabolism. Since the protocols tested resulted in
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differing extraction efficacies for the omic-technologies, this study will aid in selecting
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the most suitable method for a specific research question.
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Materials and Methods
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Cell culture
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Human Jurkat T-cells (clone E6-1, ATCC, Germany) were cultured in RPMI-1640
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medium containing 10% (v/v) foetal calf serum, 1% (v/v) streptomycin (100
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mg/mL)/penicillin (100 U/mL), and 1% (v/v) L-glutamine in a CO2 incubator (MCO-
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18AIC, Sanyo Electric Co Ltd, Japan) at 37 °C and a n atmosphere of 5% CO2. The
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cells were cultured at a density of 1x106 cells/mL. Murine Hepa 1c1c7 cells (clone
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CRL-2026, ATCC, Germany) were cultured in DMEM medium containing 10% (v/v)
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(v/v) L-glutamine in a CO2 incubator at a density of 1x104 cells/cm². Cell viability and
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cell numbers were determined using trypan blue and a Neubauer-improved-chamber
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(Optic Labor, Germany). Aliquots of 1x107 cells were washed twice with 1x PBS and
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centrifuged at 300 x g for 5min. The obtained cell pellets were resuspended in 50 µL
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PBS and processed via method A, B, C or well established protocols. Each method
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was conducted in triplicate.
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Method A
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The pelleted Jurkat T or Hepa cells were processed as described in Weckwerth
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et al. [9] with modification as follows: The RNA buffer phase was directly subjected to
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acetic acid/ethanol precipitation of nucleic acids. An extraction buffer (EB) of 0.05 M
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Tris (pH 7.6), 0.5% SDS, and 1% ß-mercaptoethanol was used. The precipitated
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nucleic acids were resuspended in 100 µL water, and proteins in 300 µL 1M urea,
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0.05 M Tris (pH 7.6), for further analysis. DNA and RNA samples were stored at -80
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°C, and metabolite and protein samples were stored at -20 °C until further analysis.
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Method B
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To a pellet of Jurkat T or Hepa cells, 50 µL of 1x PBS and 1 ml of TRI Reagent®
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(Sigma-Aldrich Chemie GmbH, Steinheim, Germany) were added and processed
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according to the manufacturer’s instructions with modifications as follows: After TRI
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Reagent/chloroform extraction, RNA was precipitated by addition of 0.5 ml ice-cold
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isopropanol and incubation for 10 min at room temperature followed by centrifugation
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for 10 min at 4 °C and 4000 x g. The supernatant containing the metabolites was
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subsequently transferred to a fresh tube and dried under vacuum. DNA was
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resuspended in 300 µL 8 mM NaOH, RNA in 50 µL H2O, and proteins in 100 µL 1%
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SDS.
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Method C
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An aliquot of Jurkat T or Hepa cells was dissolved in 1 mL of a 45% (v/v)
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methanol/5% (v/v) chloroform solution and incubated for 30 min at 4 °C, while
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rotating. The cell suspension was centrifuged at 500 x g for 10 min, and the
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metabolite-containing supernatant was transferred to a new tube and dried under
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vacuum.
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The remaining pellet was resuspended in 100 µL 1x PBS. Approximately 1 mL of
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H2O saturated phenol was added for separation of RNA, DNA, and proteins, and the
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sample was incubated for 5 min at 4 °C, while rotat ing. For phase separation, 200 µL
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of chloroform were added, and the sample was incubated for 5 min at room
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temperature (RT) followed by centrifugation at 12 000 x g for 15 min at 4 °C. After
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phase separation, the upper RNA-containing phase was mixed with 500 µL ice-cold
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isopropanol, incubated for 10 min at RT, and centrifuged for 20 min at 12,000 x g at 4
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°C. The obtained RNA pellet was washed using 75% (v /v) ethanol, air dried for 10-15
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min at RT, and resuspended in 50 µL H20. To the remaining middle and lower phase
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of the phenol chloroform extraction, 500 µL of DNA extraction buffer (4 M
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guanidinium thiocyanate, 50 mM sodium citrate, 1 M Tris-base = DEB) was added.
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The solution was mixed by inversion, incubated for 30 min at RT, and centrifuged for
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20 min at 12 000 x g at 4 °C. For DNA precipitation, 500 µL of ice-cold isopropanol
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incubation for 10 min at RT, the solution was centrifuged for 20 min at 12,000 x g at 4
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°C. The DNA-containing pellet was washed twice by a dding 1.5 mL of 75% (v/v)
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ethanol and centrifuged for 10 min at 7,500 x g. The pellet was dried at room
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temperature for 10 min and resuspended in 100 µL TE-buffer.
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For protein extraction, 1.5 mL of ice-cold isopropanol was added to the remaining
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lower phase, and the sample was incubated overnight at -20 °C to precipitate the
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proteins. The solution was then centrifuged for 15 min at 12,000 x g at 4 °C. The
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protein pellet was washed by addition of 1 mL of 0.3 M guanidinium chloride in 90%
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(v/v) ethanol, incubation for 10 min at room temperature, and subsequent
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centrifugation for 5 min at 7,500 x g at 4°C. The pellet was washed a second time
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with 1 mL ethanol. The protein pellet was dried for 20-30 min at RT and dissolved in
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100 µL 6 M urea/2 M thio-urea in 100 mM ammonium bicarbonate buffer.
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For isolation of DNA from Jurkat and Hepa cells, the genomic DNA isolation kit
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from Zymo Research (California, USA) was used following manufacturer instructions.
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The DNA was eluted from columns in 100 µL TE-buffer.
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RNA from Jurkat and Hepa cells was extracted using the Qiagen RNeasy Mini Kit (Hilden, Germany). For elution of RNA from the columns, 50µL H2O was used.
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Extraction of Jurkat and Hepa cell proteins was performed by lysing the cells with
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6 M urea/2 M thio-urea in 100 mM ammonium bicarbonate for 5 min at RT followed
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by ultra-sonication for 30 sec. Samples were subsequently centrifuged for 5 min at
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12,000 x g at 4 °C, and the protein-containing supernatant wa s transferred to a new
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tube.
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For extraction of metabolites, a hot water method (G1) and a boiling ethanol method (G2) were conducted as described by Canelas et al. [10].
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DNA quality control
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The quantity of isolated DNA was determined for all methods by ND
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spectrophotometer (Thermo Scientific, Germany), and the quality was tested by 0.8%
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(w/v) agarose gel electrophoresis. A 16.7 µL sample of DNA extracted via method A
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and 600 ng samples of DNA extracted via methods B and C were each mixed with 6x
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DNA Loading Dye (Thermo Scientific, Germany). Genomic DNA showing a distinct
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signal in the high molecular range of ~20 kB was considered to be intact or only
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partially degraded at the end of the extraction procedure.
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For evaluation of DNA quality, Jurkat DNA samples were further analyzed by
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Polymerase Chain Reaction (PCR) using the DNA quality Ready Kit (Bio-Budget
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Technologies GmbH, Krefeld, Germany) following manufacturer’s instructions. PCR
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batches were calculated on a total volume of 12 µL. A sample of 48 ng of gDNA
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(methods B, C, and GS) and 2.4 µL of 1:10 diluted gDNA extracted via method A
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were inserted into the gDNA quality control PCR. PCR products were separated on a
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1.8% (w/v) agarose gel. The amplification of 6 PCR fragments of 100 bp, 200 bp, 300
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bp, 400 bp, 500 bp (control fragment), and 600 bp of genomic DNA indicates that the
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corresponding DNA was not found degraded after the extraction process. Fewer than
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six amplicons showed DNA with any degree of degradation.
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RNA quality control
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The quantity of extracted RNA was determined by ND spectrophotometer
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(Thermo Scientific, Germany), and its quality was assessed by analyzing 10 µL
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(method A) or 1.5 µg (methods B, C, and GS) on 1.8% (w/v) agarose gel. Each
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sample was mixed with 2x RNA Loading Dye (Thermo Scientific, Germany), applied
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to a gel, and run for 45 minutes at 100V. RNA samples showing the characteristic
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ribosomal RNA bands of 5070 bp and 1869 bp with no background noise were
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considered to be intact, or only slightly degraded, at the end of the extraction
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procedure.
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One µL of 1:3 diluted RNA (method A) and 50 ng of extracted RNA (methods B,
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C, and GS) were applied to an RNA Nano Chip (Agilent Technologies, Waldbronn,
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Germany) and run on an Agilent 2100 Bioanalyzer following the manufacturer’s
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instructions. RNA with RNA integrity number (RIN) values greater than eight were
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considered to be intact and usable for qPCR and other follow-up experiments.
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Protein quality control
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The quantity of isolated proteins was determined using Quick Start – Bradford
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Dye Reagent according to the manufacturer’s instructions (Bio-Rad Laboratories
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GmbH, Germany). The quality of extracted proteins was evaluated by separation of
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30 µg proteins by SDS-PAGE followed by Coomassie Brilliant Blue staining
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according to the method described in [11]. The protein lane of each sample was cut
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into four slices and each slice (~7.5 µg protein) was digested with 150 ng trypsin .
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Generated peptides were extracted from the gel pieces and analyzed via LC-MS/MS
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ACCEPTED MANUSCRIPT using a nano-HPLC system (nanoAquity, Waters, Milford, MA, USA) coupled to an
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LTQ Orbitrap XL mass spectrometer (Thermo Fisher Scientific, San Jose, CA, USA),
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and liquid chromatography was carried out using a 110 min gradient with 0.1% formic
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acid in 100% water (solvent A) and 100% acetonitrile (solvent B). After sample
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injection into a trapping column (nanoAcquity UPLC column, C18, 180 µm x 20 mm,
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5 µm particles, Waters), peptides were separated on a C18 column (nanoAquity
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UPLC column, C18, 7 µm x 150 mm, 1.7 µm particles, Waters) using the following
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gradient of solvent B in solvent A: starting at 2%, reaching 6% after 5 min, 20% after
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45 min, 30% after 70 min, 40% after 75 min, 85% after 80 min, 2% after 95 min and
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washing for 15 min at 2%.with a flow rate of 300 nL/min.
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Full-scan MS spectra (from 300 to 2000 m/z, R = 60000) were acquired in a
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positive ion mode in the LTQ-Velos Orbitrap. Up to 10 most intense ions per scan
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with a charge >2 were fragmented and analysed in the linear trap. Peptide ions
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exceeding intensity of 3000 were chosen for collision-induced dissociation within the
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linear ion trap (isolation width 4 m/z, normalized collision energy 35%, activation time
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30 ms, activation q = 0.25). For MS/MS acquisition, a dynamic exclusion of 2 min
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was applied. For a more detailed description see Baumann et al., 2014 [12]. Data
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analysis of the mass spectrometric results was performed using MaxQuant (version
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1.3.0.5) including the following search parameters: ion mass tolerance of 0.5 Da and
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a parent ion tolerance of 20 ppm. Carbamidomethylation of cysteine was specified as
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a fixed modification. Oxidation of methionine and acetylation of the protein N-
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terminus were specified as variable modifications. MaxQuant was set up to search a
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reverse concatenated database of all human proteins annotated in the SwissProt
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database (version 10/01/2013) assuming the digestion enzyme trypsin. Only proteins
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found in two of three replicates were considered unambiguously identified.
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Metabolite analysis
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For ion chromatography-tandem mass spectrometry (IC-MS/MS)-based analysis
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of metabolites, extracts were dissolved in a total volume of 25 µL and analyzed on an
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ICS-5000 (Thermo Fisher Scientific, Dreieich, Germany) coupled to an API 5500
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QTrap (AB Sciex) as described elsewhere [13]. Separation was obtained on an
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IonPac AS11-HC column (2 x 250mm, Thermo Fisher Scientific) with an increasing
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potassium hydroxide gradient. Mass spectrometry analysis was performed in MRM
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mode
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carbohydrates, and nucleotides involved in central metabolite pathways. Metabolites
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were considered to be detectable above a signal-to-noise ratio of three, within a
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retention time window of 0.5 min.
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Results and Discussion
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using
Time and material required for performing the three extraction methods
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The optimized protocols used to separate the target biomolecules from a single
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sample of Jurkat T cells or Hepa cells is shown in Fig. 1., the others are shown in
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the supplement (Fig. S1 and Fig. S2)
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Method A was based on a study describing the simultaneous extraction of RNA,
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proteins, and metabolites from plant material [9]. Metabolites are extracted by a
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methanol/chloroform treatment, leaving a pellet that can be used for further protein,
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DNA, and RNA extraction using phenol-based phase separation [9]. Notably, this
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protocol does not produce separation of RNA from DNA. Method B was based on the TRI Reagent® manufacturer’s protocol (Sigma-
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Aldrich) for RNA, DNA, and protein isolation. The cell pellet was resuspended in TRI
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Reagent®, enabling the successive isolation of RNA, DNA, and proteins. Metabolites
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were obtained from the supernatant remaining after precipitation of RNA, and
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proteins by vacuum-drying of the respective fraction.
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Method C involved a novel process of methanol/chloroform-based extraction of
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metabolites followed by RNA, DNA, and protein extraction using a phenol/chloroform
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extraction.
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The three methods required similar time and materials. Protocol A could be
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performed in 4 h plus an additional hour the following day for centrifugation and
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ethanol washing to remove remaining phenol from proteins isopropanol-precipitated
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overnight. Using method B, it was possible to extract all four biomolecule classes in
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4 h, since proteins were not precipitated overnight. Protocol C could be carried out in
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3 h plus an additional 1.5 h the following day for pelleting and phenol depletion of
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proteins
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phenol/chloroform-based phase partitioning, enabling the separation of nucleic acids
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from proteins. Protocols A and C involved methanol/chloroform-based metabolite
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extraction steps prior to DNA, RNA and protein isolation. Considering only time and
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material required, method B would be the protocol of choice, the disadvantage being
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that only three of the four molecule classes, namely DNA, RNA and proteins can be
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isolated.
overnight
precipitation.
Each
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DNA isolation: enrichment strategies, purity, and yield
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DNA samples from method A contained also RNA when separated on an agarose
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gel, since no further partitioning of the nucleic acid classes was conducted. In
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addition, DNA extracted via method A was found to be partially degraded at the end
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of the purifiation on the agarose gel. With methods B, C, and the well established
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method (GS), the extracted DNA did not show RNA content as judged by agarose
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gel, or signs of degradation in Jurkat or Hepa cells (data not shown). For assessing
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quality and integrity, the extracted Jurkat DNA was further analyzed by PCR using
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the DNA quality Ready Kit (Bio-Budget Technologies GmbH, Krefeld, Germany).
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PCR products were analyzed by agarose gel electrophoresis. DNA extracted via
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method A showed weaker signal intensities for the expected PCR products than that
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derived from methods B, C, and GS (Fig. 2A). The kit is designed for human
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samples, and application to murine Hepa cell DNA was unsuccessful. Methods B and
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C can be used for the extraction of genomic DNA, showing acceptable DNA integrity
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and purity for further applications.
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The resulting quantifies of extraction fo the different molecule classes are
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summerized in table 1. The gDNA content determined via nanodrop for method A
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cannot be considered accurate, as both RNA and DNA were present in the sample.
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In addition, the DNA obtained by method B was difficult to dissolve and remained
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viscous, making the determined quantity questionable. Nevertheless, the volume of
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DNA isolated with the tested methods was more than sufficient for standard genomic
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applications such as PCR or DNA-sequencing, which need approximately 60 ng and
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1 µg of genomic DNA, respectively.
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RNA isolation: enrichment strategies, integrity, and yield
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When using method A, the RNA was mixed with DNA and partially degraded as
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showe by the 1.8% agarose gel. For methods B, C, and GS, no RNA degradation
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was detected (data not shown), and Bioanalyzer measurements confirmed its
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integrity, with RIN values ranging from 8.4 to 10, while values were 3.3 to 3.8 for
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method A (Fig 2B). For downstream transcriptomic analyses, including qPCR
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applications, it is generally recommended to use RNA samples with a minimum RIN
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of 7 [14]. Methods B, C, and GS are suitable for the extraction of high quality RNA
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that can be used in downstream applications.
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We isolated approximately 28.7 (Jurkat) / of RNA from 1x107 cells using method
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A (Nanodrop / containing DNA), 78.9 / 380.7 µg using method B, 13.8 / 161.6 µg
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using method C, and 14.4 / 7.7 µg with GS (Table 1).
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From Jurkat cells, we isolated approximately 28.7 µg of RNA using method A
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(nanodrop), 78.9 µg using method B, 13.8 µg using method C, and 14.4 / 7.7 µg with
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the GS. Hepa cells yielded approximately 79.6 µg with method A, 380.7 µg with
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method B, 161.6 µg with method C, and 7.7 µg with GS (Table 1).
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Methods B and C and WEM yielded a quantity of RNA sufficient for further
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analyses, such as RNA sequencing (requiring 500 ng of DNase-treated RNA) and
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reverse transcription followed by quantitative PCR (recommended 5 µg of DNase-
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treated RNA). With method A, RNA and DNA were combined.
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Protein isolation: enrichment strategies, purity, physicochemical bias, and yield
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As with RNA and DNA, the yield of extracted proteins varied for the three
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protocols and the well established method (WEM): From Jurkat cells, method A
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produced 147.7 µg, method B 65.3 µg, method C 125.8 µg, and WEM 519.3 µg.
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Yield from Hepa cells was 465.4 µg for method A, 168.2 µg for method B, 323.2 µg
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for method C, and 961.3 µg for WEM (Table 1).
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Resuspension of proteins using 1% SDS (method B) was difficult to impossible,
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and a large portion of the pellet remained undissolved. This was also reported by
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Simões et al. [15], who found that further modifications of the protocol, including
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urea:SDS solubilization and sonication, increased protein yield.
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Equal volumes of protein (30 µg) extracted by the three methods and the GS
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were precipitated, resuspended in sample buffer, and separated in a 12% SDS-
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polyacrylamide gel (Fig. 2C). The peptides obtained by in-gel digestion were
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extracted and analyzed using LC-MS/MS. Coomassie-stained SDS-polyacrylamide
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gel indicated low molecular weight proteins (<35 kDa) to be underrepresented using
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method A compared to extraction via method B and C (Figure 2C). The tendency of
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proteins <25 kDa to be underrepresented in global proteome studies can be
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associated with factors such as lower efficacy of precipitation [16], loss during
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destaining [17], or a scarcity of readily detectable tryptic peptides [18].
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Visual comparison of band patterns in SDS-gel lanes corresponding to extracts
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derived from methods A, B, and C revealed distinct similarities. High molecular
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weight proteins showed similar abundance in extracts of the three methods. For more
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comprehensive insight into the proteome data, the proteins/peptides identified in
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Jurkat T cells and Hepa cells by methods A-C were analyzed in greater detail (Fig. 16
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ACCEPTED MANUSCRIPT 3). The detection overlap of the three methods was greater for Hepa cells than for
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Jurkat T cells (Fig. 3a). Mass spectrum analysis yielded similar numbers of identified
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proteins and demonstrated a broad overlap of the three protocols and Jurkat T cells
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(A, 1318 identified proteins; B, 1253; C, 1323) (Fig. 3c). The three methods showed
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an overlap of 873 identifications. Methods A and B show an overlap of 89+873 hits,
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the overlap of methods B and C was 85+873; and method A and C overlap was
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247+873. In addition, 109 unique proteins were extracted and identified via method
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A, 206 using method B, and 118 with method C.
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A critical factor in extraction protocols is systematic bias due to physicochemical
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properties of the target molecules. This is not supposed to be crucial for molecules
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like RNA and DNA whose building blocks are rather homogeneous but highly
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relevant when the molecules differ substantially, as is the case with proteins.
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Therefore we analysed the physicochemical parameters of the detected proteins
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from Jurkat and Hepa cells: hydrophobicity (by GRAVY score), isoelectric point (pI),
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and molecular weight (MW) (Fig 3B). The GRAVY scores calculated according to
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Kyte and Dolittle (1982) [19] showed a Gaussian-type distribution pattern in the range
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of -2 to approximately +0.5 with a maximum of -0.5 and a frequency of 120-160. The
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pattern showed high similarity of extracted proteins to the GRAVY distribution of the
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annotated human proteome (Uniprot 09/2013), but the GRAVY range of +0.2 to +1
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was underrepresented, indicating that strongly hydrophobic proteins were not readily
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targeted using the three methods. For strongly hydrophobic proteins, we recommend
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use of dedicated protocols. Another possible reason for the relatively low recovery of
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hydrophobic proteins might be the precipitation approach used. A study of urine
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samples of limited complexity revealed that hydrophobic precipitation favoured the
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enrichment of acidic and hydrophilic proteins and showed a negative bias against
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ACCEPTED MANUSCRIPT hydrophobic proteins [20]. Since the methods compared here used hydrophobic
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precipitation, it is not surprising that they show a similar bias. There were differences
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in the proteomic profiles obtained by the three methods, hence the comparison of
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proteomic analyses based on different extraction protocols is problematic.
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The pI profiles of identified proteins showed a similar distribution across
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extraction methods. They displayed two well-separated peaks: one at pI 4.0-7.0 with
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a maximum of 5.0 and a frequency of 140, and a second at pI 7.0-12.0 with a
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maximum of 9.0 and a frequency of 80. Compared to the pI distribution of the
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annotated human proteome, the pI 8-10 protein fraction was underrepresented in the
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protein samples extracted via methods A, B, and C.
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The identified proteins showed similar MW distribution across methods, with a
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maximum frequency of 350-400 at 35-40 kDa and a gradual decrease in the range of
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75-200 kDa, with few proteins detected above 200 kDa. The three MW distribution
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profiles correlated well with the hypothetical distribution profile of the annotated
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human proteome.
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As a benchmark for the efficacy of metabolite extraction, we used an established,
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targeted multi-analyte (> 40) approach [13], since we were primarily interested in the
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primary products of carbon and nitrogen metabolism. Method B was not suitable for
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the extraction of metabolites by IC-MS/MS analysis, since the detergents of the TRI
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Reagent® used have a negative influence on the detectability of target analytes. In
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the analysis of samples from method B, the MRM-chromatograms were
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characterized by a high level of background noise and a longer re-equilibration time
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for consecutive runs. Method A produced 35 detectable metabolites in Jurkat cells and 23 in Hepa;
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method C, 37 in both cell types; and GS1, 30 in Jurkat and 31 in Hepa, and 29 in
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Jurkat and 30 in Hepa for GS2 (Fig. 4). All metabolites detected with method A were
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present in the MRM-chromatograms of method C. The intensities were higher in
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method C by a factor of 5 to 15, indicating clearly higher recovery of the target
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analytes by method A. At least six metabolites detected with the identical
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instrumental setup in earlier studies [12; 21] were not found after extraction method A
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in this study.
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Conclusions
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The comparison of three methods for simultaneous extraction of DNA, RNA,
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proteins, and metabolites from Jurkat T cells and hepatocytes showed adequate
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agreement between the cell lines. Method A was found suitable for metabolite and
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protein extraction, but not for specific extraction of RNA and DNA, and produced
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slightly lower detection of metabolites than method C. Method B provided high quality
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RNA and protein samples, but nearly unresolvable DNA and protein. Our attempts to
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add metabolite extraction to method B failed, as assessed by IC-MS/MS. Only
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method C provided DNA, RNA, protein, and metabolite samples that passed all
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quality benchmarks in both tested cell lines.
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Figure legends
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extraction of four biomolecule classes from a single set of cells is depicted. EB =
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extraction buffer (method A), DEB = DNA extraction buffer (method C).
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Fig. 2. Quality assessment of three of the four molecule classes isolated. A) PCR for
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gDNA quality determination: 48 ng gDNA (method B and C) and 1 µL of 1:10 diluted
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gDNA extracted via method A were inserted into gDNA quality control PCR. B)
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Results of Agilent 2100 Bioanalyzer measurements: 50 ng RNA (method B and C)
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and 1 µL of 1:3 diluted RNA extracted via method A were applied to an RNA
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nanochip. C) Separation of 30 µg protein extracted using the three methods in a 12%
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SDS-polyacrylamide gel, followed by Coomassie Brillant Blue G250 staining. Each
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lane was cut into 4 parts and subjected to tryptic digestion followed by LC-MS/MS.
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Fig 3. Overlap and physicochemical properties of identified proteins. Proteins
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identified by LC-MS/MS after tryptic digestion of 30 µg protein extracted by the three
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methods from 1x107 Jurkat T cells and 1x107 Hepa 1c1c7 cells. A) number and
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overlap of proteins identified, B) grand average of hydropathy (GRAVY), molecular
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weight and pI distribution of the corresponding proteome (human or murine) and of
453
identified proteins, C) proportion of identified proteins isolated by the gold standard
454
protein extraction method that was also found with method A, B, and C.
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Fig. 4. Metabolites determined by IC-MS/MS extracted by the three methods. Green
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boxes indicate potential quantitative measurements, red boxes indicate no metabolite
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detection.
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Table 1
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Yield, quality, and sensitivity of detection of the four classes of biomolecules
463
extracted from 1x107 Jurkat T cells and Hepa 1c1c7 cells by the three methods.
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Molecules marked in red have limited downstream usage. The quality of enrichment
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is indicated by asterisks (* = low quality to *** = high quality). The number of
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metabolites detected by each approach is indicated.
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[1] T. Ideker, T. Galitski, and L. Hood, A new approach to decoding life: systems biology. Annu Rev Genomics Hum Genet 2 (2001) 343-72. [2] R. Aebersold, and M. Mann, Mass spectrometry-based proteomics. Nature 422 (2003) 198-207. [3] W.W. Soon, M. Hariharan, and M.P. Snyder, High-throughput sequencing for biology and medicine. Mol Syst Biol 9 (2013) 640. [4] W. Weckwerth, Metabolomics: an integral technique in systems biology. Bioanalysis 2 (2010) 82936. [5] W. Mathieson, and G.A. Thomas, Simultaneously extracting DNA, RNA, and protein using kits: is sample quantity or quality prejudiced? Anal Biochem 433 (2013) 10-8. [6] R. Radpour, M. Sikora, T. Grussenmeyer, C. Kohler, Z. Barekati, W. Holzgreve, I. Lefkovits, and X.Y. Zhong, Simultaneous isolation of DNA, RNA, and proteins for genetic, epigenetic, transcriptomic, and proteomic analysis. J Proteome Res 8 (2009) 5264-74. [7] H. Roume, A. Heintz-Buschart, E.E. Muller, and P. Wilmes, Sequential isolation of metabolites, RNA, DNA, and proteins from the same unique sample. Methods Enzymol 531 (2013) 219-36. [8] R.T. Abraham, Mutant T cell lines as model systems for the dissection of T cell antigen receptor signaling pathways. Immunol Res 22 (2000) 95-117. [9] W. Weckwerth, K. Wenzel, and O. Fiehn, Process for the integrated extraction, identification and quantification of metabolites, proteins and RNA to reveal their co-regulation in biochemical networks. Proteomics 4 (2004) 78-83. [10] A.B. Canelas, A. ten Pierick, C. Ras, R.M. Seifar, J.C. van Dam, W.M. van Gulik, and J.J. Heijnen, Quantitative evaluation of intracellular metabolite extraction techniques for yeast metabolomics. Anal Chem 81 (2009) 7379-89. [11] D. Georgieva, M. Risch, A. Kardas, F. Buck, M. von Bergen, and C. Betzel, Comparative analysis of the venom proteomes of Vipera ammodytes ammodytes and Vipera ammodytes meridionalis. J Proteome Res 7 (2008) 866-86. [12] S. Baumann, M. Rockstroh, J. Bartel, J. Krumsiek, W. Otto, H. Jungnickel, S. Potratz, A. Luch, E. Wilscher, F. Theis, M. von Bergen, and J. Tomm, Subtoxic concentrations of benzo[a]pyrene induce metabolic changes and oxidative stress in non-activated and aAect the mTOR pathway in activated Jurkat T cells. Journal of Integrated OMICS 4 (2014). [13] K. Murugesan, S. Baumann, D.K. Wissenbach, S. Kliemt, S. Kalkhof, W. Otto, I. Mogel, T. Kohajda, M. von Bergen, and J.M. Tomm, Subtoxic and toxic concentrations of benzene and toluene induce Nrf2-mediated antioxidative stress response and affect the central carbon metabolism in lung epithelial cells A549. Proteomics 13 (2013) 3211-21. [14] S. Fleige, and M.W. Pfaffl, RNA integrity and the effect on the real-time qRT-PCR performance. Mol Aspects Med 27 (2006) 126-39. [15] A.E. Simoes, D.M. Pereira, J.D. Amaral, A.F. Nunes, S.E. Gomes, P.M. Rodrigues, A.C. Lo, R. D'Hooge, C.J. Steer, S.N. Thibodeau, P.M. Borralho, and C.M. Rodrigues, Efficient recovery of proteins from multiple source samples after TRIzol((R)) or TRIzol((R))LS RNA extraction and long-term storage. BMC Genomics 14 (2013) 181. [16] B. Herbert, and E. Harry, Difficult proteins. Methods Mol Biol 519 (2009) 47-63. [17] C. Klein, M. Aivaliotis, J.V. Olsen, M. Falb, H. Besir, B. Scheffer, B. Bisle, A. Tebbe, K. Konstantinidis, F. Siedler, F. Pfeiffer, M. Mann, and D. Oesterhelt, The low molecular weight proteome of Halobacterium salinarum. J Proteome Res 6 (2007) 1510-8. [18] S.A. Muller, T. Kohajda, S. Findeiss, P.F. Stadler, S. Washietl, M. Kellis, M. von Bergen, and S. Kalkhof, Optimization of parameters for coverage of low molecular weight proteins. Anal Bioanal Chem 398 (2010) 2867-81. [19] J. Kyte, and R.F. Doolittle, A simple method for displaying the hydropathic character of a protein. J Mol Biol 157 (1982) 105-32. [20] V. Thongboonkerd, The variability in tissue proteomics. Proteomics Clin Appl 6 (2012) 340-2.
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[21] J. Murugaiyan, M. Rockstroh, J. Wagner, S. Baumann, K. Schorsch, S. Trump, I. Lehmann, M. Bergen, and J.M. Tomm, Benzo[a]pyrene affects Jurkat T cells in the activated state via the antioxidant response element dependent Nrf2 pathway leading to decreased IL-2 secretion and redirecting glutamine metabolism. Toxicol Appl Pharmacol 269 (2013) 307-16.
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Figure 1: Schematic illustration of the workflow method C used for the extraction of metabolites, proteins, RNA, and DNA. *DEB: DNA extraction buffer.
A [bp]
Ladder
ACCEPTED MANUSCRIPT Jurkat E6-1 NEG
EM
A
B
C
600 500 400 300
B
Hepa 1c1c7
Jurkat E6-1
EM A B C EM A B C 10 3.3 9.8 8.4 10 3.8 9.5 9.0 RIN
Hepa 1c1c7 EM
A
B
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[kDa]
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Ladder
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[s]
Ladder
100
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200
Jurkat E6-1
C
EM A
B
C
AC C
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200 150 120 100 85 70 60 50 40 30 25 20
Figure 2: Quality control of three of the four molecule classes isolated by method A, B, C or a well established method (EM). A) PCR for gDNA quality determination. 48 ng of gDNA (method B and C) and 1 µL of 1:10 diluted gDNA extracted via method A were inserted into a gDNA quality control PCR as described by the manufacturer. The detected band of 500 bp in the lane of the NEG is a control band derived from the kit that was used for quality determination. B) Results of the Agilent 2100 Bioanalyzer measurements, 50 ng of RNA (method B and C) and 1 µL of 1:3 diluted RNA extracted via method A were applied to a RNA Nano Chip. C) Separation of 30 µg protein extracted using the three different setups in a 12% SDS-polyacrylamide gel, followed by coomassie brillant blue G250 staining. Each lane was cut into 4 parts and subjected to tryptic digestion followed by LC-MS/MS.
ACCEPTED MANUSCRIPT Jurkat T cells
Hepa 1c1c7 cells
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A
C
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B
Figure 3: Overlap and physicochemical parameters of identified proteins. Proteins identified by LC-MS/MS after tryptic digestion of 30 µg protein extracted by the three different methods out of 1x107 Jurkat T cells and 1x107 Hepa 1c1c7 cells. A) number and overlap of proteins identified, B) grand average of hydropathy (GRAVY), molecular weight and pI distribution of the corresponding proteome (human or murine) and of identified proteins, C) proportion of identified proteins isolated by the gold standard protein extraction method that was also found when extracting proteins with method A, B or C.
ACCEPTED MANUSCRIPT
Jurkat T-cells A B
C
WEM1 WEM2
Hepatocytes A B
1.0 1.0 1.0 1.0 1.0 1.0
0.0 0.0 0.0 0.0 1.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 0.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 0.0 1.0 1.0 1.0
Gluconate 6-phosphate
1.0 1.0 0.0 0.0 1.0 0.0 1.0
0.0 0.0 0.0 0.0 0.0 0.0 1.0
1.0 1.0 0.0 1.0 1.0 1.0 1.0
1.0 1.0 0.0 0.0 1.0 1.0 1.0
1.0 0.0 0.0 0.0 0.0 0.0 1.0
1.0 0.0 0.0 0.0 0.0 0.0 1.0
1.0 1.0 1.0 1.0 1.0
1.0 0.0 0.0 0.0 0.0
1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 0.0 0.0
1.0 1.0 1.0 0.0 0.0
WEM1 WEM2
1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 0.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0
0.0 0.0 0.0 0.0 0.0 0.0 1.0
1.0 1.0 0.0 1.0 1.0 1.0 1.0
1.0 1.0 0.0 1.0 1.0 1.0 1.0
1.0 0.0 0.0 1.0 0.0 0.0 1.0
M AN U
1.0 1.0 1.0 0.0 0.0
1.0 0.0 0.0 0.0 0.0
1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 0.0 0.0
1.0 1.0 1.0 0.0 0.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
0.0 0.0 1.0 0.0 0.0 0.0 0.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
1.0 0.0 0.0 0.0 1.0 0.0 1.0
0.0 0.0 1.0 0.0 0.0 0.0 0.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
0.0 1.0 1.0 0.0 0.0 0.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 0.0 1.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
0.0 1.0 1.0 0.0 0.0 0.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 0.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
TE D
Ribulose/Ribose 5-phosphate Xylulose 5-phosphate Sedoheptulose 7-phosphate Erytrose 4-phosphate Ribose 1,5-bisphosphate Glycerol 3-phosphate Pyruvate metabolism Phosphoenolpyruvate Pyruvate Lactate Acetate Formate TCA cycle Citrate Aconitate Isocitrate Ketoglutaric acid Succinate Fumarate Malate Nucleotides Adenosine monophosphate Adenosine diphosphate Adenosine triphosphate Nicotinamide adenine dinucleotide Nicotinamide adenine dinucleotide phosphate Uridine diphosphate Uridine triphosphate Organic acids Maleate Acetate Formate Glycolate Tartrate Glyoxalate Aspartate Glutamate Ala, Asp and Glu metabolism Succinic semialdehyde
C
0.0 0.0 0.0 0.0 1.0 1.0
SC
Glucose Glucose 6-phosphate Glucose 1-phosphate Fructose 6-phosphate Fructose 1,6-bisphosphate 2-Phosphoglyceric acid Pentose phosphate pathway
RI PT
Glycolysis
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1.0 1.0 1.0 0.0 1.0 0.0 1.0 0.0
1.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0
1.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0
1.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1.0 1.0 1.0 0.0 1.0 0.0 1.0 0.0
1.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0
1.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0
1.0
0.0
1.0
1.0
1.0
0.0
0.0
1.0
1.0
1.0
AC C
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1.0 1.0 1.0 0.0 1.0 0.0 1.0 0.0
Figure 4: Metabolites determined by IC-MS/MS extracted by the three different methods. Green boxes indicate possible quantitative measurements, red boxes indicate the lack of detectability.
ACCEPTED MANUSCRIPT
Protein
Metabol.
Hepa 1c1c7
RNA
WEM
µg 17.1 isolated quality *** µg 7.7 isolated quality *** µg 961.3 isolated quality *** µg 31/30 isolated quality ***
TE D
DNA
EP
Protein
AC C
Metabol.
35.8
174.9
*
*
28.7
78.9
*
***
147.7
65.3
125.8
***
***
8
37
*
***
*** 35
**
18.8
RI PT
RNA
µg 9.9 isolated quality *** µg 14.4 isolated quality *** µg 519.3 isolated quality *** µg 30/29 isolated quality ***
Method Method Method A B C
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DNA
WEM
***
13.8 ***
SC
Jurkat E6-1
Method Method Method A B C 99.5
153.6
45.2
*
*
***
79.6
380.7
161.6
*
***
***
465.4
168.2
323.2
***
***
***
23
8
37
**
*
***
Table 1: Yield, quality and sensitivity of detection of the four different classes of biomolecules after extraction from 1x107 Jurkat T cells and Hepa 1c1c7 cells by the three different methods. Molecules marked in red have limited downstream usage. The quality of enrichments is decribed here by one asterisk (low quality) up to three asterisks (high quality). For metabolites the number of detected metabolites by a targeted approach is indicated.
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Figure S1: Schematic illustration of the workflow method A used for the extraction of metabolites, proteins, RNA and DNA. *EB: extraction buffer.
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Figure S2: Schematic illustration of the workflow method B used for the extraction of metabolites, proteins, RNA, and DNA.