Name: identifying per- and polyfluorinated chemical species with a combined targeted and non-targeted-screening high-resolution mass spectrometry workflow
Uploaded: 2019-04-18T14:00:00.000+00:00
Duration: 9 min 4 s
Description: Watch this Scientific Journal Video about Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow at JoVE.c

The U.S. Environmental Protection Agency, through its Office of Research and Development, funded and managed the research described here. This document has been reviewed by the U.S. Environmental Protection Agency, Office of Research and Development, and approved for publication. The views expressed in this article are those of the authors and do not necessarily represent the views or policies of the U.S. Environmental Protection Agency. This research was supported in part by an appointment to the Postdoctoral Research Program at the National Exposure Research Laboratory administered by the Oak Ridge Institute for Science and Education through Interagency Agreement DW89992431601 between the U.S. Department of Energy and the U.S. Environmental Protection Agency.

1. Collection of water samples
<ol>
	<li>Preparation of PFAS Standard Stocks
	<ol>
		<li>Prepare a PFAS standard mixture in methanol containing any targeted compounds of interest (e.g., PFOA, PFOS, HFPO-DA) at 1 ng/&#181;L. This is the Native PFAS Mixture. Commercially prepared mixtures are also available (i.e., PFAC Mix A and Mix B).</li>
		<li>Prepare a standard mixture containing matched stable isotope labeled (SIL) PFAS compounds (e.g., 13C4-PFOA, 13C8-PFOS, 13C3-HFPO-DA) at 1 ng/&#181;L. This is the IS PFAS Mixture. Commercially prepared mixtures are also available (i.e., MPAFC Mix A and Mix B). 
		NOTE: If an SIL version of the targeted PFAS is unavailable, a surrogate with similar structure and chain length can be used (e.g., 13C2-PFHxA for HFPO-DA)</li>
	</ol>
	</li>
	<li>Preparation of Field Blank (FB), Spike Blank (SB) samples
	<ol>
		<li>Fill two, clean high-density polypropylene (HDPE) or polypropylene (PP) bottles with 1,000 mL of laboratory deionized (DI) water, known to be PFAS free. 
		CAUTION: PFAS materials frequently have undefined toxicity and/or carcinogenicity. Care should be taken to avoid oral or skin exposure to standards or stock solutions.</li>
		<li>Add a quantity of PFAS standard mixture to one of the bottles at a final concentration equivalent to the expected sample concentrations (e.g., 100 ng/L). This is the Spike Blank (SB).</li>
		<li>Add 5 mL of 35% nitric acid preservative to the Spike Blank.</li>
		<li>Carry both SB sample and the unspiked field blank to the sampling location as controls.</li>
	</ol>
	</li>
	<li>Field sampling 
	NOTE: Sample collector should wear nitrile gloves and sample from flowing systems where possible. Tap samples should be allowed to flow and equilibrate prior to sampling (2-3 min).
	<ol>
		<li>Collect 500-1,000 mL of water from the field location in a clean HDPE or PP bottle.</li>
		<li>Add 5 mL of 35% nitric acid preservative to sample bottles and field blank. 
		CAUTION: Nitric acid is corrosive and a strong oxidizer</li>
	</ol>
	</li>
</ol>
2. Sample extraction
NOTE: PFAS are ubiquitous and persistent. Ensure that all solvents are of the highest grade and have been analyzed for low level PFAS contamination. Thoroughly rinse all laboratory equipment used for preparing standards before preparing blanks and samples.
<ol>
	<li>Sample pretreatment
	<ol>
		<li>Pour each sample into a separate, pre-cleaned 1 L HDPE graduated cylinder and record the exact volume.</li>
		<li>Add 10 mL of methanol to the emptied sample bottle, cap it, and shake well to rinse adsorbed PFAS from the bottle interior.</li>
		<li>Return the measured water sample to the rinsed bottle with the methanolic rinse.</li>
	</ol>
	</li>
	<li>Standard curve for quantitation
	<ol>
		<li>Fill eight, 1 L HDPE/PP bottles with PFAS-free DI water.</li>
		<li>Select eight evenly spaced concentrations covering the desired quantitation range. For example: 10, 25, 50, 100, 250, 500, 750 and 1,000 ng/L for a range of 10-1,000 ng/L.</li>
		<li>Add a quantity of Native PFAS mix to each bottle to yield the final PFAS concentrations in 2.2.2 (e.g., 100 &#181;L PFAS Mix A to 1L of DI water = 100 ng/L).</li>
	</ol>
	</li>
	<li>Internal standard addition 
	NOTE: Addition of stable isotope labeled internal standard (IS) is necessary only if quantitative results are desired in addition to non-targeted analysis.
	<ol>
		<li>Add the IS PFAS mixture to each sample at a concentration approximating the midpoint of the calibration curve (e.g., 250 &#181;L of IS PFAS mix = 250 ng/L)</li>
	</ol>
	</li>
	<li>Filtration
	<ol>
		<li>Filter samples through GF/A glass fiber filters (47 mm, 1.6 &#181;m pore size) under gentle vacuum into a pre-cleaned 1 L HDPE vacuum flask.</li>
		<li>If particulate matter remains in the bottle, rinse with additional deionized water into the filter. Return the filtered water to the sample bottle or a new container for solid phase extraction.</li>
	</ol>
	</li>
	<li>Solid phase extraction (SPE) 
	NOTE: Cartridge concentration described here uses a constant flow piston pump. Alternative methods of concentration using a vacuum manifold20 or using an on-line SPE-LC-MS17 setup are possible but not discussed.
	<ol>
		<li>Condition a weak anion exchange (WAX) cartridge with 25 mL of methanol.</li>
		<li>Condition the WAX cartridge with an additional 25 mL of deionized water.</li>
		<li>Position pump draw tubing in filtered sample bottles and label SPE cartridges with corresponding sample names.</li>
		<li>Pump 500 mL of sample water through the cartridge at a steady flow rate of 10 mL/min (500 mL total), discarding flow-through liquid to waste. 
		NOTE: Larger or smaller volumes can be concentrated depending on expected sample concentrations.</li>
		<li>Remove the cartridge from piston pump for elution. 
		NOTE: If concentrating additional samples using the same pump, the piston pump should be flushed with 25 mL of methanol before installing the next cartridge for equilibration.</li>
		<li>Transfer SPE cartridge to a vacuum manifold and equip with external glass reservoir.</li>
		<li>Flush SPE cartridge with 4 mL of 25 mM, pH 4.0 sodium acetate buffer under gentle vacuum. Discard flow through. Wash SPE cartridge with 4 mL of neutral methanol. 
		NOTE: Neutral wash fraction can be collected if specific nonionic polar analytes are expected. Otherwise, discard to waste</li>
		<li>Place a 15 mL polypropylene centrifuge tube beneath each SPE cartridge to collect eluent. Elute sample with 4 mL of 0.1% ammonium hydroxide in methanol.</li>
		<li>Remove elution tube and reduce eluate volume to 500 - 1,000 &#181;L by evaporation under dry nitrogen stream in a water bath at slightly elevated temperature (40 &#176;C).</li>
		<li>Concentrated sample extracts can be stored prior to analysis at room temperature.</li>
	</ol>
	</li>
	<li>Targeted LC-MS/MS quantitation
	<ol>
		<li>Dilute 100 &#181;L of sample extract with 300 &#181;L of 2 mM ammonium acetate buffer into an HPLC sample vial.</li>
		<li>Calibrate and equilibrate an HPLC and MS systems according to manufacturer&#39;s instructions. 
		NOTE: Background PFAS are commonly detected due to the use of fluoropolymer components of most LC systems and in sample vial septa. Confirm that the detectable levels in blanks is negligible before use. Modification of the LC system to replace Teflon components is suggested where possible. The use of an analytical &#34;hold-up&#34; column adjacent to the LC mixing valve is also suggested29.</li>
		<li>Prepare an analytical worklist consisting of the standard curve, samples, and an additional replicate of the standard curve to assess instrumental drift across the run. An example worklist is shown in Table 1.</li>
		<li>Analyze the samples using LC and MS methods established for the targeted compound(s) of interest. The example LC gradient is shown in Table 2 and MS method parameters are shown in Table 3 and Table 4. Further detailed discussion can be found in McCord et al.21.</li>
		<li>Generate a standard curve from the standard samples using the peak area ratio of the analyte to the internal standard versus the concentration of analyte. Generate a quadratic regression formula with 1/x weighting for concentration prediction9.</li>
		<li>Quantitate targeted analytes in each sample using the prepared standard curves and area ratio (standard area/IS area) for each measurement.</li>
		<li>If the concentration exceeds the calibration range, dilute the original sample with DI water spiked with the appropriate IS concentration and re-extract to bring the concentration into the appropriate range.</li>
	</ol>
	</li>
	<li>Non-targeted LC-MS/MS data collection
	<ol>
		<li>Dilute 100 &#181;L of sample extract with 300 &#181;L of 2 mM ammonium acetate buffer into an HPLC sample vial.</li>
		<li>Calibrate and equilibrate an HPLC and high-resolution MS according to manufacturer&#39;s instructions.</li>
		<li>Prepare an analytical worklist as in 2.6.2.</li>
		<li>Using the instrument software, collect LC-MS data in with a wide scan MS1 in data-dependent mode to collect MS/MS. Example LC gradient in Table 5. Further discussion of instrument settings can be found in Strynar et al.30 and Newton et al.31. 
		NOTE: For improved MS/MS quality data-dependent analysis can be carried out with a preferred ion list of a subset of features remaining after data processing in 2.8.1-2.8.8.</li>
	</ol>
	</li>
	<li>Non-targeted data processing 
	NOTE: Data analysis can be performed with a wide range of software and these methods do not reflect the only, or best method for an arbitrary dataset. Where possible, steps provide a generic description that can be carried out in alternate software. Processing of the example data used in this manuscript was carried out using vendor specific software (Software 1 and Software 2) as detailed in Newton et al.31.
	<ol>
		<li>Perform molecular feature extraction of chemical features using one of several open source software packages32,33 or vendor software to identify monoisotopic masses, retention times, and integrated peak areas of chemical features.
		<ol>
			<li>In Software 1, select Add/Remove Sample Files &#62; Add Files and select the raw data from the non-targeted experiment, then hit OK.</li>
			<li>In Software 1 select Batch Recursive Feature Extraction &#62; Open Method&#8230; to load a preestablished method, or manually edit software settings. Profinder settings for feature extraction are found in Table 6.</li>
			<li>In Software 1, after feature extraction, select File &#62; Export as CSV&#8230;, File &#62; Export as CEF&#8230;, or File &#62; Export as PFA&#8230; for further processing. CEF files are assumed for the remainder of the description.</li>
			<li>In Software 2 (MPP) create a new experiment with Type Unidentified and Workflow type Data Import Wizard and click OK.</li>
			<li>In MPP Select Data Files and locate the exported Software 1 results (either CEF or PFA) to import; then click Next until Alignment Parameter options appear.</li>
			<li>In MPP, set the Compound Alignment values to 0.0 (alignment was already performed in the feature extraction of Software 1, step 2.8.1.2) then click Next through the steps until Finish is available.</li>
		</ol>
		</li>
		<li>Filter identifications based on analytical reproducibility. Where multiple replicate samples are available, features should be present in &#62;80% of individual replicates and have an analytical coefficient of variation (CV) of &#60; 30%
		<ol>
			<li>In MPP select Experimental Setup &#62; Experiment Grouping and assign each raw file a group corresponding to its origin sample (i.e., replicates from the same source should be in the same group). Multiple groups can be created corresponding to nested variables (e.g., instrumental vs. technical replicates).</li>
			<li>In MPP select Experimental Setup &#62; Create Interpretation then select the experiment parameter (i.e., group) and click Next until Finish is available. This will create a category that future filtering can operate on.</li>
			<li>In MPP select Quality Control &#62; Filter by Frequency. Set Entity List to All Entities and the Interpretation to the sample Group(non-averaged) created in 2.8.2.2, then hit Next.</li>
			<li>For Input parameters, set entity retention at 80% of sampled in at least one condition then click Next until Finish is available. Name the list Frequency Filtered Features</li>
			<li>In MPP select Quality Control &#62; Filter on Sample Variability. Set the Entity List to the Frequency Filtered Features from 2.8.2.4 and the interpretation to Group(non-averaged), then hit Next.</li>
			<li>Select the radio button for Raw Data and the Range of Interest to Coefficient of variation &#60; 30%. Click Next &#62; Finish and save the list as CV Filtered Features.</li>
		</ol>
		</li>
		<li>Remove features where no samples have significantly higher (&#62;3 fold) abundance than the Field Blank (FB) sample.
		<ol>
			<li>In MPP select Analysis &#62; Fold Change. Set Entity List to CV Filtered Features and the Interpretation to the sample Group then hit Next. Select the fold change option to All against single condition and select condition FB or whatever the group name for the blank processed sample was.</li>
			<li>On the following screen, set the Fold-Change cutoff to 3.0 and click through to the end of the prompts. Save the list as FC Filtered List.</li>
		</ol>
		</li>
		<li>Perform binary comparisons of individual samples of interest against an appropriate background sample (e.g., upstream vs. downstream of a point source) to determine fold-changes for individual chemical features.
		<ol>
			<li>In MPP select Analysis &#62; Filter on Volcano Plot. Set the entity list to FC Filtered List and the Interpretation to Group.</li>
			<li>For the fold-change condition pair choose two samples for comparison (e.g., a paired upstream and downstream sample) and select test Mann-Whitney Unpaired.</li>
			<li>For preliminary analysis, do not select a value for multiple test correction on the following screen, click through to the result plot.</li>
			<li>On the results screen select a fold-change cutoff of 3.0 and a p-value cutoff to 0.1. Then Finish and export the list as Prelim Results.</li>
		</ol>
		</li>
		<li>For each feature remaining after filtering, generate predicted chemical formula(s) from the exact mass and composite mass spectrum.
		<ol>
			<li>In MPP, select Results Interpretation &#62; IDBrowser Identification and the Prelim Results entity list.</li>
			<li>In the IDBrowser select Identify all compounds using molecular formula generator (MFG) as the identification method.</li>
			<li>In the Generate Formula options add F to the Elements column and set the Maximum to 50, then select Finish. Following formula generation select Save and Return to return to MPP.</li>
			<li>In MPP, right click the filtered and MFG matched Entity List and select Export List. Save the results.</li>
		</ol>
		</li>
		<li>Examine the monoisotopic mass of species in the reduced significant chemical feature list for those containing mass defects indicative of fluorination; see Kind and Fiehn34.</li>
		<li>Note chemical series containing common polyfluorination motifs (CF2 (m/z 49.9968), CF2O (m/z 65.9917), CH2CF2O (m/z 80.0074), etc.) using a mass defect plot or software algorithm; see discussion section, Liu et al.17, Loos et al.35 , and Dimzon et al.36.</li>
		<li>Search predicted chemical formulas or neutral masses against the EPA Chemistry Dashboard database and/or other databases to return potential chemical structures.
		<ol>
			<li>Open the EPA Comptox Chemicals Dashboard Batch Search tool (https://comptox.epa.gov/dashboard/dsstoxdb/batch_search) and paste the list of identifiers (either formulas or masses) into the identifier box, after selecting the identifier type (i.e., MS-ready Formula or Monoisotopic Mass).</li>
			<li>Select Download Chemical Data&#8230; and also select any physical/chemical/toxicology data desired for potential matches from the dropdown.</li>
		</ol>
		</li>
		<li>Using chemical intuition and available reference data, remove unlikely matches from the potential chemical structure list for each formula based on feasibility due to chemical stability, physical properties such as ionizability or hydrophobicity, the presence of manufacturing chemicals from nearby sources, etc. In the absence of additional data, spectral feasibility can be ranked purely on the basis of literature prevalence; see McEachran et al.37.</li>
		<li>Confirm structures using available standards and/or targeted high-resolution MS/MS matching of fragments against spectra from databases, in silico theoretical spectra, or manual curation.</li>
	</ol>
	</li>
</ol>

The authors have nothing to disclose.

Sample Handling and Preparation 
The inclusion of reference/spike standards are of paramount importance to any targeted analysis, as they provide a backstop for checking analytical validity. Lack of QC samples prevents any assessment of the accuracy of the results; the ubiquitous nature of fluorochemicals means that chance contamination of field samples, processing materials, or LC-MS system is not uncommon and must be accounted for. Further, it allows for the validation of the protocol regardless of variation in the day-to-day sample processing, as many of the steps can be highly variable, particularly the SPE and sample concentration steps. The extraction of both legacy and novel perfluorinated chemicals can be heavily influenced by the choice of stationary phase for concentration, and components of the source samples, such as pH and salinity46. The influence of sample conditions should be considered if particular classes of pefluorinated chemicals are of interest. Alternative sample preparation schemes for water extracts can be used if the laboratory setup is available and the downstream data analysis remains similar.
Targeted Data Analysis 
For compounds with available standards and matched, stable isotope labeled internal standards, the primary concerns for data analysis are instrumental and determination of method detection limits and suitable reporting ranges can be determined on a laboratory-by-laboratory basis using standard approaches, such as signal-to-noise ratio from low-level standard spikes47. In the absence of matched internal standards errors from mismatched matrix effects can occur, and accurate back-prediction of spiked samples can be used to estimate the accuracy of the measurements. When lacking standards to prepare a curve, a quantitative estimate of an unknown can be made by treating it identically to a closely matched standard compound, but errors in the estimate are on the order of 10+ fold with limited ability to quantify the uncertainty, see McCord, Newton, and Strynar21. In these cases, trend data can still be collected, but concentration estimates are inherently unreliable.
Non-targeted Data Analysis 
Peak picking settings have a substantial impact on the number of chemical features identified, but the quality of feature selection is also heavily impacted. The decisions of interest in peak picking are 1) intensity of individual masses to be included in spectra, the ion abundance threshold 2) the intensity of extracted chromatogram peaks to be considered features, the feature abundance threshold 3) feature detection frequency, the replicate threshold, and 4) analytical variation, the CV threshold (Figure 10).
Setting unrealistically low thresholds for peak picking results in an exponential increase in sample time to resolve additional features of increasingly low abundance (Table 7). The ion-abundance threshold filters mass spectral features where enough of the individual isotope abundances do not pass the threshold. This ideally selects only for features with quality MS spectra, ensuring they are real chemical features rather than instrumental noise, and allowing for formula prediction in downstream processing. An appropriate threshold is based on instrumental noise, ideally at least 3x the noise threshold for MS1 scans. Feature abundance threshold filters chemical features based on the intensity or area of the chromatographic feature extracted. This step enables rejection of low abundance peaks, which are typically of poor chromatographic quality, have high variances, or are the result of other poor software extraction. An appropriate threshold must be determined per experiment, and per matrix based on an acceptable level of poor feature generation (e.g., features below the threshold exhibit unacceptably poor chromatography). Further analytical QC can be used to reject features at the chromatographic level based on inconsistent identification in analytical and/or preparatory replicates (replicate threshold) or based on poor reproducibility across replicates (CV threshold). Appropriate levels depend on the quality of the peak integration software used and the chemical entities under investigation. For water soluble perfluorinated compounds and lightly optimized integration protocols, features should be identified in 80+% of analytical replicates and CVs are expected to fall below 30%, as detailed in the methods section.
The peaks detected from non-targeted analysis do not yield quantitative estimates of the concentrations of the materials detected. Further, the identity of true unknowns can be difficult to confirm because novel compounds are absent from publicly available databases. Novel structural determination requires extensive analysis with multiple methods and requires expertise in both mass spectrometry and chemistry. However, normalizing the peak areas of chemical features can provide semi-quantitative estimates of concentrations of unknowns from known species21. If consistent sampling and preparation steps are employed, time trend information for individual species can be generated to monitor the persistence of a chemical into the future as the response for an individual species should be consistent barring large variations in the matrix21.
The primary benefit of this method is the extensibility of the sample treatment to allow both targeted and nontargeted analysis. While targeted analysis provides equivalent or superior quantitative information, it greatly lacks breadth of analysis desired when dealing with new and emerging materials, as well as their relationship to matrix materials. Applying a targeted methodology, or even a suspect screening method based only on known materials and limited databases is completely blind to previously unobserved species, even if they may have significant health effects. As software improves and databases become more robust, the accuracy of unknown identification will continue to increase, with a concomitant decrease in the time investment and level of expertise necessary to analyze the multidimensional data generated by this approach. Nevertheless, data generated presently is of significant future value because data banking allows for post-hoc analysis with newly developed software and enables comparison across time even if the identity of a detected compound is currently unknown.

The class of per- and polyfluoroalkyl substances (PFASs) are persistent organic pollutants with significant public health concern. The specific compounds perfluorooctanoic acid (PFOA) and perfluorooctanesulfonate (PFOS) have drinking water health advisory levels set by the EPA1,2 and their major US production ceased in the 2000s3,4. To gain a significant understanding for the properties of PFAS materials in the textile and consumer product manufacturing spheres, hundreds, if not thousands, of alternate PFAS chemistries have been developed to fill product niches, including replacements for the deprecated compounds5,6,7,8. There is an ongoing need to monitor the environmental levels of straight chain perfluorinated carboxylic acids and sulfonates such PFOS, PFOA, and their related homologous series, but emerging chemical compounds are not covered by established methods such as EPA Method 5379 and frequently lack analytical standards for traditional targeted analysis. The intention of this protocol is thus two-fold. It provides a pathway for the targeted LC-MS/MS analysis of fluorochemical species in water where analytical standards are available and details the seamless integration of a non-targeted, high-resolution mass spectrometry-based approach for data analysis that enables the detection of unknown or unexpected compounds in the same samples.
Solid-phase extraction (SPE) is an established technique for the sample cleanup and concentration with applications to many analytes and sample matrices10,11. For PFAS analysis, multiple solid retentive phases including non-polar, functionalized polar, and ion exchange columns have been used to varying extents for subclasses of fluorinated species in a wide variety of matrices9,12,13,14,15,16. Advances in SPE sample analysis using on-line setups greatly increase the throughput of the approach and improve the reproducibility of sample handling, but the fundamental process remains consistent17. Some efforts to remove the offline concentration of SPE using large volume injections have also been undertaken, but these require modifications to the chromatography that place them outside the realm of casual analysis18,19. Our sample analysis uses a polymeric weak anion exchange (WAX) retentive phase to thoroughly separate acidic PFAS materials from the traditional organic contaminants while achieving substantial sample concentration factors. This WAX phase is important to capture the short chain perfluorinated acids such as perfluorobutane sulfonate (PFBS) or perfluorinated ethers such as hexafluoropropylene oxide dimer acid (HFPO-DA) which are more polar than the longer chain legacy perfluorinated species20,21. As there has been a significant shift towards shorter fluorinated chains and ether inclusion in recent PFAS chemistry5, this phase selection enables more thorough recovery of novel compounds for MS analysis.
Targeted LC-MS/MS quantitation using authenticated standards and stable isotope labeled internal standards provides an unparalleled level of specificity and sensitivity for the quantitative analysis. While this approach is desirable in many situations, it is impractical for all-too-common situations in analysis. Targeted approaches work only for species that are expected in the sample, and for which methods have previously been established. For new and emerging compounds, this approach is incapable of even detecting species that may be of interest, regardless of their chemistry or concentration, and low-resolution mass spectrometers are nearly incapable of providing enough information to make unequivocal chemical assignments of unknown compounds. Consequently, the field of non-targeted analysis has arisen, leveraging the power of high-resolution modern mass spectrometers to analyze samples without a presupposed hypothesis and retroactively assign chemicals to detectable features in the sample. This approach has been used extensively in the fields of biology22,23,24 and environmental science25,26,27 on numerous classes of chemicals. Perfluorinated chemicals are particularly straightforward to identify in this method due to their unique mass spectral patterns, and hundreds of compounds have been described in just the past few years5,28.
The protocol discussed here is intended to align targeted LC-MS/MS PFAS quantitation with the need to identify and semi-quantitatively monitor emerging compounds of interest. The SPE phase selection and sample preparation techniques are intended to ensure capture of more hydrophilic emerging PFAS acids from water and may be less suited for longer chain polymeric species and non-ionic species. Further, the data generated by non-targeted analysis is dense and of high dimensionality, which necessitates the use of data analysis software. Such software packages are frequently vendor specific and require modification to operate between instrument platforms. Where possible, the analysis process has been described in a generic fashion and open source/freeware alternatives are referenced, but the efficiency and accuracy of any software approach must be assessed on an individual basis.

<table><tbody><tr><td>Acqity ultra-high performance liquid chromatography system&amp;nbsp;</td><td>Waters Corporation</td><td></td><td>Modified with PFCs analysis kit (176001744); equivalent UPLC system is acceptible if PFAS background is checked and confirmed to be low</td></tr><tr><td>Ammonium acetate</td><td>Fluka</td><td>17836</td><td>Mass spectrometry grade &gt;99% pure</td></tr><tr><td>Ammonium Hydroxide</td><td>Sigma-Aldrich</td><td>338818</td><td></td></tr><tr><td>Balance</td><td>Mettler</td><td>AB204S</td><td></td></tr><tr><td>BEH C18 reverse phase UPLC column, 2.1&amp;times;50&amp;nbsp;mm, 1.7&amp;nbsp;&amp;mu;m&amp;nbsp;</td><td>Waters Corporation</td><td>186002350</td><td></td></tr><tr><td>Dual piston syringe pump&amp;nbsp;</td><td>Waters Corporation</td><td>SPC10-C</td><td></td></tr><tr><td>Glacial Acetic Acid</td><td>Sigma-Aldrich</td><td>ARK2183&amp;nbsp;</td><td></td></tr><tr><td>Glass Microfiber Filters</td><td>Whatman</td><td>1820-070</td><td></td></tr><tr><td>High density polyethelye sample bottle&amp;nbsp;</td><td>Nalgene</td><td>2189-0032&amp;nbsp;</td><td></td></tr><tr><td>High Resolution Mass Spectrometer</td><td>Various</td><td></td><td>Mass Spectrometer should be capable of providing accurate mass to &amp;lt;10ppm and collecting MS/MS data.&amp;nbsp; Agilent 6530 qTOF and Thermo Fisher Orbitrap Fusion were used in this work</td></tr><tr><td>Methanol</td><td>Sigma-Aldrich</td><td></td><td></td></tr><tr><td>Nitric Acid (35% w/w)</td><td>Thermo Fisher Scientific</td><td>SVCN-5-1</td><td>Can be prepared in house using concentrated nitric acid and reagent water</td></tr><tr><td>Polypropylene Buchner funnel</td><td>ACE Glass</td><td>12557-09&amp;nbsp;</td><td></td></tr><tr><td>Polypropylene cenitrfuge tube and cap</td><td>BD Falcon</td><td>352096</td><td></td></tr><tr><td>Polypropylene Vacuum Flask (1 L)</td><td>Nalgene</td><td>DS4101-1000</td><td></td></tr><tr><td>Quattro Premier XE triple quadrupole mass spectrometer&amp;nbsp;</td><td>Waters Corporation</td><td></td><td>Equivalent triple-quadrupole or better system can be used instead, should provide high sensitivity and stability for targeted analysis</td></tr><tr><td>Reagent Water</td><td></td><td></td><td>Any source determined to be PFAS free</td></tr><tr><td>Sodium Acetate</td><td>Sigma-Aldrich</td><td>W302406</td><td></td></tr><tr><td>TurboVap nitrogen evaporator&amp;nbsp;</td><td>Caliper Life Sciences</td><td>103198</td><td>Equivalent systems or rotary vacuum evaporator may be used instead</td></tr><tr><td>Weak anion exchange SPE cartridge (Oasis WAX Plus)</td><td>Waters Corporation</td><td>186003519</td><td></td></tr><tr><td>&lt;strong&gt;Standard Solutions&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>2,3,3,3-Tetrafluoro-2-(1,1,2,2,3,3,3-heptafluoropropoxy)propanoic acid (HFPO-DA)</td><td>Wellington</td><td>HFPO-DA</td><td></td></tr><tr><td>Additional targeted compound standards of interest</td><td></td><td></td><td>to be determined based on preliminary analysis and standard availability</td></tr><tr><td>Mass labeled HFPO-DA</td><td>Wellington</td><td>M2HFPO-DA</td><td></td></tr><tr><td>Native PFCA/PFAS Mixture (2 ug/mL)</td><td>Wellington</td><td>PFAC-MXA</td><td>or PFAC-MXB; or individually prepared mixture containing compounds of interest</td></tr><tr><td>Stable Isotope Labeled PFCA/PFAS Mixture (2 ug/mL)</td><td>Wellington</td><td>MPFAC-MXA</td><td>or MPFAC-MXB; or individually prepared mixture containing compounds of interest as appropriate for Native PFASs</td></tr><tr><td>&lt;strong&gt;Software&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>Mass Profiler Professional</td><td>Agilent</td><td></td><td>Or open source software packages</td></tr><tr><td>Profinder</td><td>Agilent</td><td></td><td>Or open source software packages</td></tr></tbody></table>

identifying per- and polyfluorinated chemical species with a combined targeted and non-targeted-screening high-resolution mass spectrometry workflow

Historical and emerging per- and polyfluoroalkyl substances (PFASs) have garnered significant interest from the public and government agencies from the local to federal levels. The continuing evolution of PFAS chemistries presents a challenge to the environmental monitoring, where ongoing development of targeted methods necessarily lags the discovery of new chemical compounds. There is a need, therefore, to have forward-looking methodologies that can detect emerging and unexpected compounds, monitor these species over time, and resolve details of their chemical structure to enable future work in human health. To this end, non-targeted analysis by high-resolution mass spectrometry offers a broad base detection approach that can be combined with almost any sample preparation scheme and provides significant capabilities for compound identification after detection. Herein, we describe a solid-phase extraction (SPE) based sample concentration method tuned for shorter chain and more hydrophilic PFAS chemistries, such as per fluorinated ether acids and sulfonates, and describe analysis of samples prepared in this fashion in both targeted and non-targeted modes. Targeted methods provide superior quantification when reference standards are available but are intrinsically limited to expected compounds when performing analysis. In contrast, a non-targeted approach can identify the presence of unexpected compounds and provide some information about their chemical structure. Information about chemical features can be used to correlate compounds across sample locations and track abundance and occurrence over time.

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Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow

Here, we present a protocol for the sequential targeted quantification and non-targeted analysis of fluorinated compounds in water by mass spectrometry. This methodology provides quantitative levels of known fluorochemical compounds and identifies unknown chemicals in related samples with semi-quantitative estimates of their abundance.

Historical and emerging per- and polyfluoroalkyl substances (PFASs) have garnered significant interest from the public and government agencies from the ...

identifying-per-polyfluorinated-chemical-species-with-combined

Nanyang Technological University

Research

JoVE Journal

Environment

12.3K Views.  U.S. Environmental Protection Agency. Deze aanpak maakt het mogelijk om bekende PFAS te kwantificeren en nieuwe stoffen in dezelfde monsters te ontdekken, in vergelijking met gerichte benaderingen alleen die nieuwe verbindingen missen die zorgwekkend zijn. Dit protocol richt zich op een breder scala aan PFAS-verbindingen, die representatief zijn voor de nieuwste opkomende chemische stoffen. Als de concentratiestap voor de verbindingen wordt aangepast, kunnen de hier gebruikte meetmethoden op elke categorie chemicaliën worden toe...

Video: Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow

Improved Polymerase Chain Reaction-restriction Fragment Length Polymorphism Genotyping of Toxic Pufferfish by Liquid Chromatography/Mass Spectrometry

An improved version of a polymerase chain reaction (PCR)-restriction fragment length polymorphism (RFLP) method for genotyping toxic pufferfish species by liquid chromatography/electrospray ionization mass spectrometry (LC/ESI-MS) is described. DNA extraction is carried out using a silica membrane-based DNA extraction kit. After the PCR amplification using a detergent-free PCR buffer, restriction enzymes are added to the solution without purifying the reaction solution. A reverse-phase silica monolith column and a Fourier transform high resolution mass spectrometer having a modified Kingdon trap analyzer are employed for separation and detection, respectively. The mobile phase, consisting of 400 mM 1,1,1,3,3,3-hexafluoro-2-propanol, 15 mM triethylamine (pH 7.9) and methanol, is delivered at a flow rate of 0.4 ml/min. The cycle time for LC/ESI-MS analysis is 8 min including equilibration of the column. Deconvolution software having an isotope distribution model of the oligonucleotide is used to calculate the corresponding monoisotopic mass from the mass spectrum. For analysis of oligonucleotides (range 26-79 nucleotides), mass accuracy was 0.62 &#177; 0.74 ppm (n = 280) and excellent accuracy and precision were sustained for 180 hr without use of a lock mass standard.

An improved polymerase chain reaction-restriction fragment length polymorphism method for genotyping pufferfish species by liquid chromatography/mass spectrometry is described. A reverse-phase silica monolith column is employed for separating digested amplicons. This method can elucidate the monoisotopic masses of oligonucleotides, which is useful for identifying base composition.

An improved version of a polymerase chain reaction (PCR)-restriction fragment length polymorphism (RFLP) method for genotyping toxic pufferfish species by ...

Genetics

Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry (UPLC-HRMS)

Here we present a workflow to analyze the metabolic profiles for biological samples of interest including; cells, serum, or tissue. The sample is first separated into polar and non-polar fractions by a liquid-liquid phase extraction, and partially purified to facilitate downstream analysis. Both aqueous (polar metabolites) and organic (non-polar metabolites) phases of the initial extraction are processed to survey a broad range of metabolites. Metabolites are separated by different liquid chromatography methods based upon their partition properties. In this method, we present microflow ultra-performance (UP)LC methods, but the protocol is scalable to higher flows and lower pressures. Introduction into the mass spectrometer can be through either general or compound optimized source conditions. Detection of a broad range of ions is carried out in full scan mode in both positive and negative mode over a broad m/z range using high resolution on a recently calibrated instrument. Label-free differential analysis is carried out on bioinformatics platforms. Applications of this approach include metabolic pathway screening, biomarker discovery, and drug development.

Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry UPLC-HRMS

Untargeted metabolomics provides a hypothesis generating snapshot of a metabolic profile. This protocol will demonstrate the extraction and analysis of metabolites from cells, serum, or tissue. A range of metabolites are surveyed using liquid-liquid phase extraction, microflow ultraperformance liquid chromatography/high-resolution mass spectrometry (UPLC-HRMS) coupled to differential analysis software.

Here we present a workflow to analyze the metabolic profiles for biological samples of interest including; cells, serum, or tissue. The sample is first ...

Chemistry

PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis

Proton Transfer Reaction (PTR), combined with a Time-of-Flight (ToF) Mass Spectrometer (MS) is an analytical approach based on chemical ionization that belongs to the Direct-Injection Mass Spectrometric (DIMS) technologies. These techniques allow the rapid determination of volatile organic compounds (VOCs), assuring high sensitivity and accuracy. In general, PTR-MS requires neither sample preparation nor sample destruction, allowing real time and non-invasive analysis of samples. PTR-MS are exploited in many fields, from environmental and atmospheric chemistry to medical and biological sciences. More recently, we developed a methodology based on coupling PTR-ToF-MS with an automated sampler and tailored data analysis tools, to increase the degree of automation and, consequently, to enhance the potential of the technique. This approach allowed us to monitor bioprocesses (e.g. enzymatic oxidation, alcoholic fermentation), to screen large sample sets (e.g. different origins, entire germoplasms) and to analyze several experimental modes (e.g. different concentrations of a given ingredient, different intensities of a specific technological parameter) in terms of VOC content. Here, we report the experimental protocols exemplifying different possible applications of our methodology: i.e. the detection of VOCs released during lactic acid fermentation of yogurt (on-line bioprocess monitoring), the monitoring of VOCs associated with different apple cultivars (large-scale screening), and the in vivo study of retronasal VOC release during coffee drinking (nosespace analysis).

Proton Transfer Reaction Time of Flight Mass Spectrometry allows high-sensitivity, rapid and non-invasive analysis of volatile organic compounds. To demonstrate its potential, we give three examples: lactic acid fermentation of yogurt (on-line bioprocess monitoring), different apple genotypes (large-scale screening), and retronasal space after drinking coffee (nosespace analysis).

Proton Transfer Reaction (PTR), combined with a Time-of-Flight (ToF) Mass Spectrometer (MS) is an analytical approach based on chemical ionization that ...

Identification of Pharmaceuticals in The Aquatic Environment Using HPLC-ESI-Q-TOF-MS and Elimination of Erythromycin Through Photo-Induced Degradation

Monitoring pharmaceuticals throughout the water cycle is becoming increasingly important for the aquatic environment and eventually for human health. Targeted and non-targeted analysis are today's means of choice. Although targeted analysis usually conducted with the help of a triple quadrupole mass spectrometer may be more sensitive, only compounds previously selected can be identified. The most powerful non-targeted analysis is performed through time of flight mass spectrometers (TOF-MS) extended by a quadrupole mass analyzer (Q), as used in this study. Preceded by solid phase extraction and high-performance liquid chromatography (HPLC), the non-targeted approach allows to detect all ionizable substances with high sensitivity and selectivity. Taking full advantage of the Q-TOF-MS instrument, tandem mass spectrometry (MS/MS) experiments accelerate and facilitate the identification while a targeted MS method enhances the sensitivity but relies on reference standards for identification purposes. The identification of four pharmaceuticals from Rhine river water is demonstrated. The Rhine river originates in Tomasee, Graub&#252;nden, Switzerland and flows into the North Sea, near Southern Bight, The Netherlands. Its length amounts to 1232.7 km. Since it is of prime interest to effectively eliminate pharmaceuticals from the water cycle, the effect UV-C irradiation is demonstrated on a laboratory scale. This method allows fast degradation of pharmaceuticals, which is exemplarily shown for the macrolide antibiotic erythromycin. Using the above HPLC-Q-TOF-MS method, concentration-time diagrams are obtained for the parent drug and their photodegradation products. After establishing the equations for first-order sequential reactions, computational fitting allows the determination of kinetic parameters, which might help to predict irradiation times and conditions when potentially considered as fourth stage within wastewater treatment.

We present a protocol for non-targeted analysis using time of flight mass spectrometry as a perfect tool to identify pharmaceuticals in waters. We demonstrate the application of UV irradiation for their elimination. Analysis involving irradiation, compound isolation, identification and kinetic modelling of the degradation profiles is illustrated.

Monitoring pharmaceuticals throughout the water cycle is becoming increasingly important for the aquatic environment and eventually for human health. ...

Characterization of Synthetic Polymers via Matrix Assisted Laser Desorption Ionization Time of Flight (MALDI-TOF) Mass Spectrometry

There are many techniques that can be employed in the characterization of synthetic homopolymers, but few provide as useful of information for end group analysis as matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS). This tutorial demonstrates methods for optimization of the sample preparation, spectral acquisition, and data analysis of synthetic polymers using MALDI-TOF MS. Critical parameters during sample preparation include the selection of the matrix, identification of an appropriate cationization salt, and tuning the relative proportions of the matrix, cation, and analyte. The acquisition parameters, such as mode (linear or reflector), polarization (positive or negative), acceleration voltage, and delay time, are also important. Given some knowledge of the chemistry involved to synthesize the polymer and optimizing both the data acquisition parameters and the sample preparation conditions, spectra should be obtained with sufficient resolution and mass accuracy to enable the unambiguous determination of the end groups of most homopolymers (masses below 10,000) in addition to the repeat unit mass and the overall molecular weight distribution. Though demonstrated on a limited set of polymers, these general techniques are applicable to a much wider range of synthetic polymers for determining mass distributions, though end group determination is only possible for homopolymers with narrow dispersity.

Characterization of Synthetic Polymers via Matrix Assisted Laser Desorption Ionization Time of Flight MALDI-TOF Mass Spectrometry

A protocol for the matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS) characterization of synthetic polymers is described including the optimization of sample preparation, spectral acquisition, and data analysis.

There are many techniques that can be employed in the characterization of synthetic homopolymers, but few provide as useful of information for end group ...

Sample Preparation for Probe Electrospray Ionization Mass Spectrometry

Mass spectrometry (MS) is a powerful tool in analytical chemistry because it provides very accurate information about molecules, such as mass-to-charge ratios (m/z), which are useful to deduce molecular weights and structures. While it is essentially a destructive analytical method, recent advancements in the ambient ionization technique have enabled us to acquire data while leaving tissue in a relatively intact state in terms of integrity. Probe electrospray ionization (PESI) is a so-called direct method because it does not require complex and time-consuming pretreatment of samples. A fine needle serves as a sample picker, as well as an ionization emitter. Based on the very sharp and fine property of the probe tip, destruction of the samples is minimal, allowing us to acquire the real-time molecular information from living things in situ. Herein, we introduce three applications of PESI-MS technique that will be useful for biomedical research and development. One involves the application to solid tissue, which is the basic application of this technique for the medical diagnosis. As this technique requires only 10 mg of the sample, it may be very useful in the routine clinical settings. The second application is for in vitro medical diagnostics where human blood serum is measured. The ability to measure fluid samples is also valuable in various biological experiments where a sufficient volume of sample for conventional analytical techniques cannot be provided. The third application leans toward the direct application of probe needles in living animals, where we can obtain real-time dynamics of metabolites or drugs in specific organs. In each application, we can infer the molecules that have been detected by MS or use artificial intelligence to obtain a medical diagnosis.

This article introduces sample preparation methods for a unique real-time analytical method based on the ambient mass spectrometry. This method lets us perform real-time analysis of the biological molecules in vivo without any special pretreatments.

Mass spectrometry (MS) is a powerful tool in analytical chemistry because it provides very accurate information about molecules, such as mass-to-charge ...

Biochemistry

Investigating Long-Distance Transport of Perfluoroalkyl Acids in Wheat via a Split-Root Exposure Technique

Large amounts of perfluoroalkyl acids (PFAAs) have been introduced into the soil and accumulated by plants, posing potential risks to human health. It is imperative to investigate the accumulation and translocation of PFAAs within plants. Long-distance transport is an important pathway for PFAAs transferred from the plant leaves to the edible tissues through the phloem. However, it was previously difficult to assess the translocation potential of organic contamination in a short-term exposure period. The split-root experiment provides a solution to effectively uncover the long-distance translocation of PFAAs using a hydroponic experiment, which, in this study, was carried out in two 50 mL centrifuge tubes (A and B), of which centrifuge tube A had 50 mL of one-quarter strength Hoagland sterile nutrient solution, while centrifuge tube B had the same amount of nutrient concentration, and the target PFAAs (perfluorooctane sulfonic acid, PFOS, and perfluorooctane acid, PFOA) added at a given concentration. A whole wheat root was manually separated into two parts and inserted carefully into tubes A and B. The concentration of PFAAs in the roots, shoots of wheat, and solutions in tubes A and B were evaluated using LC-MS/MS, respectively, after being cultured in an incubator for 7 days and harvested. The results suggested that PFOA and PFOS experience a similar long-distance transport process through the phloem from the shoot to the root and could be released into the ambient environment. Thus, the split-root technique can be used to evaluate the long-distance transport of different chemicals.

Investigating Long-Distance Transport of Perfluoroalkyl Acids in Wheat via a Split-Root Exposure Technique

The present protocol describes a simple and efficient method for the long-distance transport of perfluoroalkyl acids in wheat.

Large amounts of perfluoroalkyl acids (PFAAs) have been introduced into the soil and accumulated by plants, posing potential risks to human health. It is ...

Capillary Electrophoresis Mass Spectrometry Approaches for Characterization of the Protein and Metabolite Corona Acquired by Nanomaterials

The adsorption of biomolecules from surrounding biological matrices to the surface of nanomaterials (NMs) to form the corona has been of interest for the past decade. Interest in the bio-nano interface arises from the fact that the biomolecular corona confers a biological identity to NMs and thus causes the body to identify them as &#8220;self&#8221;. For example, previous studies have demonstrated that the proteins in the corona are capable of interacting with membrane receptors to influence cellular uptake and established that the corona is responsible for cellular trafficking of NMs and their eventual toxicity. To date, most research has focused upon the protein corona and overlooked the possible impacts of the metabolites included in the corona or synergistic effects between components in the complete biomolecular corona. As such, this work demonstrates methodologies to characterize both the protein and metabolite components of the biomolecular corona using bottom-up proteomics and metabolomics approaches in parallel. This includes an on-particle digest of the protein corona with a surfactant used to increase protein recovery, and a passive characterization of the metabolite corona by analyzing metabolite matrices before and after NM exposures. This work introduces capillary electrophoresis &#8211; mass spectrometry (CESI-MS) as a new technique for NM corona characterization. The protocols outlined here demonstrate how CESI-MS can be used for the reliable characterization of both the protein and metabolite corona acquired by NMs. The move to CESI-MS greatly decreases the volume of sample required (compared to traditional liquid chromatography &#8211; mass spectrometry (LC-MS) approaches) with multiple injections possible from as little as 5 &#181;L of sample, making it ideal for volume limited samples. Furthermore, the environmental consequences of analysis are reduced with respect to LC-MS due to the low flow rates (&#60;20 nL/min) in CESI-MS, and the use of aqueous electrolytes which eliminates the need for organic solvents.

Here we present a protocol to characterize the complete biomolecular corona, proteins, and metabolites, acquired by nanomaterials from biofluids using a capillary electrophoresis &#8211; mass spectrometry approach.

The adsorption of biomolecules from surrounding biological matrices to the surface of nanomaterials (NMs) to form the corona has been of interest for the ...

Ultra High-Performance Liquid Chromatography-Mass Spectrometry and Self-established Database Analysis of Chinese Herbal Medicine Components

Chinese herbal medicine is complex and has numerous unknown compounds, making qualitative research crucial. Ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) is the most widely used method in qualitative analysis of compounds. The method includes standardized and programmed protocols for sample pretreatment, MS tune, MS acquisition, and data processing. The sample pretreatments include collection, pulverization, solvent extraction, ultrasound, centrifugation, and filtration. Data post-processing was described in detail and includes data importing, self-established database construction, method establishment, data processing, and other manual operations. The above-ground part of the alpine yarrow herb, Achillea millefolium L., is used to treat inflammation, gastrointestinal disturbances, and pain and its 3-oxa-guaianolides could be useful leads for anti-inflammatory drug development. Three representative compounds in AML were identified, combining TOF-MS with a self-established database. Moreover, the differences from existing literature, liquid-phase parameter optimization, scan mode selection, ion source suitability, collision energy adjustment, isomer screening, method limitation, and possible solutions were discussed. This standardized analysis method is universal and can be applied to identify complex compounds in Chinese herbal medicine.

We describe a general protocol and systematic design that could be applied to separate and recognize complex components in alpine yarrow herb, Achillea millefolium L., a Chinese herbal medicine.

Chinese herbal medicine is complex and has numerous unknown compounds, making qualitative research crucial. Ultra-high-performance liquid chromatography ...

Quantification of three DNA Lesions by Mass Spectrometry and Assessment of Their Levels in Tissues of Mice Exposed to Ambient Fine Particulate Matter

DNA adducts and oxidized DNA bases are examples of DNA lesions that are useful biomarkers for the toxicity assessment of substances that are electrophilic, generate reactive electrophiles upon biotransformation, or induce oxidative stress. Among the oxidized nucleobases, the most studied one is 8-oxo-7,8-dihydroguanine (8-oxoGua) or 8-oxo-7,8-dihydro-2&#39;-deoxyguanosine (8-oxodGuo), a biomarker of oxidatively induced base damage in DNA. Aldehydes and epoxyaldehydes resulting from the lipid peroxidation process are electrophilic molecules able to form mutagenic exocyclic DNA adducts, such as the etheno adducts 1,N2-etheno-2&#39;-deoxyguanosine (1,N2-&#949;dGuo) and 1,N6-etheno-2&#39;-deoxyadenosine (1,N6-&#949;dAdo), which have been suggested as potential biomarkers in the pathophysiology of inflammation. Selective and sensitive methods for their quantification in DNA are necessary for the development of preventive strategies to slow down cell mutation rates and chronic disease development (e.g., cancer, neurodegenerative diseases). Among the sensitive methods available for their detection (high performance liquid chromatography coupled to electrochemical or tandem mass spectrometry detectors, comet assay, immunoassays, 32P-postlabeling), the most selective are those based on high performance liquid chromatography coupled to tandem mass spectrometry (HPLC-ESI-MS/MS). Selectivity is an essential advantage when analyzing complex biological samples and HPLC-ESI-MS/MS evolved as the gold standard for quantification of modified nucleosides in biological matrices, such as DNA, urine, plasma and saliva. The use of isotopically labeled internal standards adds the advantage of corrections for molecule losses during the DNA hydrolysis and analyte enrichment steps, as well as for differences of the analyte ionization between samples. It also aids in the identification of the correct chromatographic peak when more than one peak is present.
We present here validated sensitive, accurate and precise HPLC-ESI-MS/MS methods that were successfully applied for the quantification of 8-oxodGuo, 1,N6-dAdo and 1,N2-dGuo in lung, liver and kidney DNA of A/J mice for the assessment of the effects of ambient PM2.5 exposure.

We describe here methods for sensitive and accurate quantification of the lesions 8-oxo-7,8-dihydro-2&#39;-deoxyguanosine (8-oxodGuo), 1,N6-etheno-2&#39;-deoxyadenosine (1,N6-dAdo) and 1,N2-etheno-2&#39;-deoxyguanosine (1,N2-dGuo) in DNA. The methods were applied to the assessment of the effects of ambient fine particulate matter (PM2.5) in tissues (lung, liver and kidney) of exposed A/J mice.

Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow

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