This work is supported by the European Commission's 7th Framework Programme under Grant Agreement Number 287382. SY is a beneficiary of a European Commission's 7th Framework Programme Grant Agreement Number 287382. IK is a beneficiary of a FIRST doctoral school grant from the Fondazione Edmund Mach. For his work at University of Foggia, VC is supported by the Apulian Region in the framework of 'Future In Research' program (practice code 9OJ4W81).

The protocol follows the guidelines of our institutional committee on human research ethics.
1. Sample Preparation and Autosampler Conditions
<ol>
	<li>On-line bioprocess monitoring: detecting VOCs released during lactic acid fermentation of yogurt 
	NOTE: This section of the protocol represents part of the procedure reported by Benozzi et al.32
	<ol>
		<li>Add 5 mL of pasteurized milk to each vial (20 mL glass vials equipped with PTFE/silicone septa). Note the type of milk used and quickly heat the samples to 45 &#176;C. Transfer them to a multifunctional GC autosampler equipped with a temperature controlled tray (45 &#176;C).</li>
		<li>Use the robotic arm of the autosampler to inoculate the vials with the microbial starter cultures (according to the specifications of the starter culture manufacturer). Set the incubation time according to the typology of the desired yogurt and to the specifications reported by starter culture manufacturer. Set the autosampler to conveniently analyze one sample after the other, obtaining an on-line VOC monitoring of lactic acid fermentation during yogurt preparation.</li>
	</ol>
	</li>
	<li>Large-scale screening: monitoring VOCs associated with different apple genotypes 
	NOTE: This section of the protocol represents part of the procedure reported by Farneti et al.33,36
	<ol>
		<li>Sample apples at the desired phase of ripening/conservation (e.g. at commercial harvest stage). Select at least five homogeneous fruits without any visible damage for each clone. Store the apples for the desired period at room temperature (25 &#176;C) or refrigerate (4 &#176;C).</li>
		<li>Collect five cylindrical discs (1.7 cm diameter and 1 cm thickness) from each apple with a flesh blade sampler. Include a part of cortex tissue, and avoid the core portion with seeds. Immediately homogenize the samples and freeze in liquid nitrogen. Store at -80 &#176;C until analysis.</li>
		<li>Before analysis, place three replicates of the 2.5 g apple sample from each biological replicate into the vials (20 mL glass vials equipped with PTFE/silicone septa). Mix the sample with 2.5 mL of deionized water, 1 g of sodium chloride, 12.5 mg of ascorbic acid, and 12.5 mg of citric acid, and keep the samples at 4 &#176;C until analysis (maximum 3 days).</li>
		<li>Incubate the samples at 40 &#176;C and then set the autosampler to automatically analyze the VOCs.</li>
	</ol>
	</li>
	<li>Nosespace analysis: studying retronasal release of VOCs during coffee drinking 
	NOTE: This section of the protocol represents part of the procedure reported by Romano et al.28
	<ol>
		<li>Prepare brewed coffee from ground coffee samples.
		<ol>
			<li>Use a coffee machine: report the water/powder ratio, the type of mineral water used, the type of coffee maker, and the procedure adopted to obtain the coffee beverage (quantities are a function of the dimension of the coffee machine).</li>
			<li>Use a six-cup stove-top coffee maker, known in Italy as a &#34;moka&#34;, using 450 mL water and 30 g of coffee powder. Put the brewed coffee in a vessel and transfer it in a thermostatic water bath (60 &#176;C).</li>
		</ol>
		</li>
		<li>For each coffee brew, transfer 7.5 mL aliquots to a polystyrene cup (40 mL) with a plastic cap. Have each panelist taste the beverage according to the protocol: i) 30 s of free breathing, ii) a single sip of coffee, followed by a fast swallow, and iii) 3 min of breathing into an ergonomic glass nosepiece28.</li>
		<li>Repeat the whole experiment for three consecutive days, randomizing the order of coffee samples and panelists each day.</li>
		<li>Perform sampling by applying a single-use ergonomic nosepiece in silicon rubber to the nose of the panelists. Connect the nosepiece to the PTR-ToF-MS by means of a PEEK tube that is unheated only in the first part in contact with the panelist body, then heated at 110 &#176;C in an inlet hose, which connects the sampling interface with the PTR-MS instrument. 
		NOTE: In Table 2 a list of products analyzed with analogous procedures to those reported by Benozzi et al.32, Farneti et al.33,36, and Romano et al.28 is reported.</li>
	</ol>
	</li>
</ol>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Food matrix</td>
			<td>Number and kind of samples</td>
			<td>Reference</td>
		</tr>
		<tr>
			<td>Apple</td>
			<td>The authors screened a collection represented by 190 accessions, composed by both old and new apple cultivars</td>
			<td>33</td>
		</tr>
		<tr>
			<td>Yogurt</td>
			<td>Four starters were analyzed in terms of VOCs released during lactic fermentation of yogurt (A, FD-DVS YF-L812 Yo-Flex, Chr. Hansen; B, FD-DVS YC-380 Yo-Flex, Chr. Hansen; C, FD-DVS YC-X11 Yo-Flex, Chr. Hansen; D, YO-MIX 883, Danisco)</td>
			<td>32</td>
		</tr>
		<tr>
			<td>Coffee</td>
			<td>Three different kind of ground coffee obtained from a single pure Arabica coffee blend were used: medium roast, dark roast and decaffeinated medium roast</td>
			<td>28</td>
		</tr>
	</tbody>
</table>
Table 2: List of products analyzed. List of products analyzed with analogous procedures to the ones reported by Benozzi et al.32, Farneti et al.33,36, and Romano et al.28
2. Experimental Design and Practical Precautions
<ol>
	<li>Perform at least three inter-day biological replicates, each with three technical replicates, for each experimental mode.</li>
	<li>Prior to sample incubation and analysis, flush the headspace with clean air for 1 min at 200 sccm for each vial.</li>
	<li>Prepare a blank for every experimental mode, incubate and analyze the blank under the same conditions of the samples.</li>
	<li>Randomize the order of samples/blanks for analysis.</li>
	<li>Similarly to other methods used to detect VOCs, limit the use of perfumed personal care products, as well as gum and cigarettes, before using the instrument. Tightly cap all volatile chemicals in the lab, and control air drafts as much as possible during testing37.</li>
</ol>
3. PTR-MS Instrument Optimization and Analysis
NOTE: The instrumental conditions are described in the references (e.g. Makhoul et al.27).
<ol>
	<li>Perform headspace measurements of the samples with a commercial PTR-ToF-MS apparatus in the standard configuration mode.</li>
	<li>Directly inject air into the PTR-MS drift tube headspace without any treatment. There is a continuous flow of sample air through the PTR-MS so injection is achieved by simply inserting the end of the PTR-MS inlet into the sample headspace.</li>
	<li>Set and constantly verify the following ionization conditions in the drift tube: 110 &#176;C drift tube temperature, 2.30 mbar drift pressure, 550 V drift voltage. This leads to an E/N ratio of about 140 Td (1 Td = 10&#8722;17 cm2 V&#8722;1 s&#8722;1). The inlet line consists of a PEEK capillary tube (internal diameter 0.04 in.) heated at 110 &#176;C. By default, set the inlet flow to 40 sccm.</li>
	<li>Set sampling time per channel of ToF acquisition to 0.1 ns, amounting to 350,000 channels for a mass spectrum ranging up to m/z = 400. Every single spectrum is the sum of about 28,600 acquisitions lasting 35 &#181;s each, resulting in a time resolution of 1 s. 
	NOTE: Spectra are then continuously stored. Spectrometric signals grow from a background level to a stable value in a few seconds (the time needed to replace the gas in the inlet lines) and only the spectra acquired after this transient are considered in further analysis.</li>
</ol>
4. Tailored Data Analysis
NOTE: Tailored data analysis has been developed using a procedure in MATLAB.
<ol>
	<li>Correct the count losses due to the ion detector dead time via a methodology based on Poisson statistics as described by Cappellin et al.10.</li>
	<li>Perform internal calibration according to a procedure described by Cappellin et al.38 to achieve a good mass accuracy (up to 0.001 Th).</li>
	<li>Carry out compound annotation comparing obtained spectral data with fragmentation data of reference standards and with data reported in the scientific literature.</li>
	<li>Perform noise reduction, baseline removal and peak intensity extraction according to Cappellin et al.39, using modified Gaussians to fit the peaks.</li>
	<li>Calculate peak intensity in ppbv (parts per billion by volume) via the formula described by Lindinger et al.5, using the appropriate reaction rate coefficient or a constant value for the reaction rate coefficient (k = 2.10&#8722;9 cm3 s&#8722;1), when the underlying compound is not known. The latter introduces a systematic error of up to 30% that can be accounted for if the actual coefficient is known40.</li>
	<li>Mine the data by performing Principal Component Analysis, Analysis of Variance, Tukey&#39;s post-hoc test, and other statistical test/analysis adapting existing packages developed using R (e.g. Cappellin et al.10).</li>
</ol>

The authors have nothing to disclose.

Proton transfer reaction-mass spectrometry (PTR-MS) coupled to time of flight (ToF) mass analyzers represent a valid compromise between the need for identification and quantification of volatile organic compounds and the necessity for rapid analytical profiling. The high mass resolution that characterizes the ToF mass analyzer gives/provides relevant sensitivity and mass spectra with considerable informational content. Furthermore, the application of PTR-ToF-MS coupled with an auto-sampler and tailored data analysis tool...

Direct-Injection Mass Spectrometric (DIMS) technologies represent a class of analytical instrumental approaches that offer considerable mass and time resolution with high sensitivity and robustness, allowing the quick detection and quantification of volatile organic compounds (VOCs)1. These instrumental approaches include, among others, MS-e-noses, Atmospheric-Pressure Chemical Ionization Mass Spectrometry (APCI-MS), Proton-Transfer-Reaction Mass Spectrometry (PTR-MS), and Selected Ion-Flow-Tube Mass Spectrometry (SIFT-MS)1. The pros and the cons of each approach depend on: the kind of sample injection, the source and control of precursor ions, the control of the ionization process, and the mass analyzer1,2.
Proton-transfer-reaction mass-spectrometry (PTR-MS) was developed more than twenty years ago to monitor in real-time and with low detection limits (usually a few ppbv, part per billion by volume) most volatile organic compounds (VOCs) in air3,4. Current uses of PTR-MS range from medical applications, to food control, to environmental research5,6. The main features of this technique are: the possibility of rapid and continuous measurement, the intense and pure source of precursor ions, and the possibility to control ionization conditions (pressure, temperature and drift voltage). These features permit combining versatile uses with a high degree of standardization1,4. In fact, the method is based on reactions of hydronium ions (H3O+), which induce non-dissociative proton transfer in most volatile compounds (particularly in those characterized by a proton affinity higher than water), protonating neutral compounds (M) according to the reaction: H3O+ + M &#8594; H2O + MH+. In contrast to other techniques, e.g., APCI-MS, precursor ion generation and sample ionization are divided in two different instrumental compartments (a schematic representation of the PTR-MS instrument is given in Figure 1). An electrical discharge by water vapor in the hollow cathode ion source generates a beam of hydronium ions. After this phase, ions cross the drift tube, where the ionization of VOCs takes place7. Ions then enter a pulse extraction section and are accelerated into the TOF section. Through flight times, it is possible to determine the mass-to-charge ratios of the ions8. Each extraction pulse leads to a complete mass spectrum8 of the selected m/z range. Ion spectra are recorded by a fast data acquisition system7. A complete spectrum is typically acquired in one second although higher time resolution can be achieved according to the signal to noise level and a quantitative estimation of the VOC headspace concentration can be provided even without calibration9,10.
<img alt="Figure 1" src="/files/ftp_upload/54075/54075fig1.jpg" /> 
Figure 1: Schematic illustration of a PTR-MS. Schematic representation of the PTR-MS instrument. HC: external ion source with hollow cathode; SD: source drift; VI, venturi-type inlet; EM, electron multiplier; FC1-2, flow controllers. Reprinted with permission from Boschetti et al.7. <a href="http://cloudflare.jove.com/files/ftp_upload/54075/54075fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
In general, the PTR technique assures fast analysis time, high detection sensitivity and a relatively compact instrument size, requires neither sample preparation nor sample destruction and thus allows real time investigations11. PTR is of considerable interest in the environmental, atmospheric, food, technological, medical and biological sciences12.
VOCs associated with food matrices are of outstanding interest in food science and technology because of their important role in the molecular basis of biological phenomena linked to odor and flavor perception and, thus, in food acceptance. Hence, our interest in real time and non-invasive detection of VOCs mainly deals with sensory qualities of food. In addition, if we consider the possibility to detect spoilage and pathogenic microorganisms by means of released VOCs13 and/or to monitor volatile organic compounds as markers following technological processes (e.g. Maillard by-products during thermal treatments)14, it becomes clear how VOC identification and quantification are fields of interest in food quality management6. Several recent uses of PTR-MS technologies for the rapid monitoring and quantification of VOCs in food matrices testify to the wide range of application of these analytical approaches (Table 1).
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Food matrix</td>
			<td>Kind of application</td>
			<td>Brief description</td>
			<td>Reference</td>
		</tr>
		<tr>
			<td>Butter</td>
			<td>Screening/characterization</td>
			<td>Geographical origin of European butters</td>
			<td>15</td>
		</tr>
		<tr>
			<td>Yogurt</td>
			<td>Bioprocess monitoring</td>
			<td>Evolution during lactic acid fermentation</td>
			<td>16</td>
		</tr>
		<tr>
			<td>Cereal bars</td>
			<td>In vivo measurement</td>
			<td>Nosespace during consumption of cereal bars with varying sugar composition</td>
			<td>17</td>
		</tr>
		<tr>
			<td>Liquid model systems</td>
			<td>Simulated oral conditions</td>
			<td>Evaluation of tongue pressure and oral conditions in a model mouth</td>
			<td>18</td>
		</tr>
		<tr>
			<td>Apple</td>
			<td>In vivo measurement</td>
			<td>Nosespace during consumption apple with different genetic, textural, and physicochemical parameters</td>
			<td>19</td>
		</tr>
		<tr>
			<td>Coffee</td>
			<td>Screening/characterization</td>
			<td>Differentiation of specialty coffees</td>
			<td>20</td>
		</tr>
		<tr>
			<td>Grape must</td>
			<td>Screening/characterization</td>
			<td>Effect of cooking process</td>
			<td>21</td>
		</tr>
		<tr>
			<td>Flavored candies&#160;</td>
			<td>In vivo measurement</td>
			<td>Determination on panelists using different direct mass spectrometry methods</td>
			<td>22</td>
		</tr>
		<tr>
			<td>Ham&#160;</td>
			<td>Screening/characterization</td>
			<td>Effect of the pig rearing system</td>
			<td>23</td>
		</tr>
		<tr>
			<td>Bread</td>
			<td>Simulated oral conditions</td>
			<td>Simulating bread aroma during mastication</td>
			<td>24</td>
		</tr>
		<tr>
			<td>Milk</td>
			<td>Screening/characterization</td>
			<td>Monitoring photooxidation-induced dynamic changes in milk</td>
			<td>25</td>
		</tr>
		<tr>
			<td>Coffee</td>
			<td>Screening/characterization</td>
			<td>Diversity in roasted coffees from different geographic origins</td>
			<td>26</td>
		</tr>
		<tr>
			<td>Bread</td>
			<td>Bioprocess monitoring</td>
			<td>Effect of different yeast starters during alcoholic fermentation</td>
			<td>27</td>
		</tr>
		<tr>
			<td>Coffee</td>
			<td>In vivo measurement</td>
			<td>Nosespace during consumption of different roasted coffee preparations</td>
			<td>28</td>
		</tr>
		<tr>
			<td>Tomatoes</td>
			<td>Screening/characterization</td>
			<td>Impact of Production Location, Production System, and Variety&#160;</td>
			<td>29</td>
		</tr>
		<tr>
			<td>Bread</td>
			<td>Bioprocess monitoring</td>
			<td>Effect of flour, yeast and their interaction during alcoholic fermentation</td>
			<td>30</td>
		</tr>
		<tr>
			<td>Mushrooms&#160;</td>
			<td>Screening/characterization</td>
			<td>Shelf life of dried porcini mushrooms&#160;</td>
			<td>31</td>
		</tr>
		<tr>
			<td>Yogurt</td>
			<td>Bioprocess monitoring</td>
			<td>Effect of different starter cultures during lactic fermentation</td>
			<td>32</td>
		</tr>
		<tr>
			<td>Apple</td>
			<td>Screening/characterization</td>
			<td>Diversity in an apple germplasm collection</td>
			<td>33</td>
		</tr>
		<tr>
			<td>Coffee</td>
			<td>Screening/characterization</td>
			<td>Tracing coffee origin&#160;</td>
			<td>34</td>
		</tr>
		<tr>
			<td>Coffee</td>
			<td>In vivo measurement</td>
			<td>Combination of a dynamic sensory method and in-vivo nosespace analysis to understand coffee perception</td>
			<td>35</td>
		</tr>
	</tbody>
</table>
Table 1: List of scientific studies using PTR-ToF-MS in the food sector. Non-exhaustive list of scientific studies using PTR-based approaches to monitor VOC content in food-related experiments.
In recent studies, we reported on the application of PTR-ToF-MS coupled with an automated sampling system and tailored data analysis tools to increase sampling automation and reliability and, consequently, to enhance the potential of this technique7,10,13. This allowed us to screen, in terms of VOC content, large sample sets (e.g. food of different origins with many replicates, entire germoplasms), to analyze the influence of several experimental modes on VOC release (e.g. different concentrations of a given ingredient, diverse intensities of a specific technological parameter), and to monitor VOCs associated with a given bioprocess (e.g. enzymatic oxidation, alcoholic fermentation). Here, in order to exemplify the potential of PTR-ToF-MS in the agri-food sector, we present three paradigmatic applications: the detection of VOCs released during lactic acid fermentation of yogurt induced by different microbial starter cultures (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 while drinking coffee (nosespace analysis).

<table><tbody><tr><td>PTR-TOF 8000 High-Resolution PTR-TOF-MS</td><td>Ionicon Analytik Ges.m.b.H.</td><td>PTR-TOF 8000</td><td>An detector for volatile organic compounds (VOCs) that allows for continuous VOC quantification with a very high mass resolution</td></tr><tr><td>GERSTEL&amp;nbsp;MPS 2XL</td><td>Gerstel</td><td></td><td>A multifunctional autosampler&amp;nbsp;</td></tr><tr><td>Gas Calibration Unit</td><td>Ionicon Analytik Ges.m.b.H.</td><td>GCU-s / GCU-a</td><td>A dynamic gas dilution system that provides variable but known quantities of different standard compounds in a carrier gas stream</td></tr><tr><td>TofDaq</td><td>Tofwerk AG</td><td>free available at http://soft.tofwerk.com/&amp;nbsp;&amp;nbsp;&amp;nbsp;</td><td>A data acquisition software&amp;nbsp;(for spectra&amp;nbsp; acquisition)</td></tr><tr><td>MATLAB&amp;nbsp;</td><td>MathWorks</td><td>http://it.mathworks.com/products/matlab/</td><td>A technical computing language and interactive environment for algorithm development, data visualization, and data analysis</td></tr><tr><td>R</td><td>The R Foundation</td><td>free available at https://cran.r-project.org/mirrors.html&amp;nbsp;&amp;nbsp;</td><td>A language and environment for statistical computing and graphics</td></tr></tbody></table>

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).

The volatile profile of samples resulted in a complete mass spectrum for the desired mass range acquired each second. In Figure 2, an example of the acquired average spectra during the yogurt on-line bioprocess is given32. In every spectrum, more than 300 mass peaks in the m/z range up to 250 Th can be identified32.
<img alt="Figure 2" src="/files/ftp_upload/54075/...

Watch this Scientific Journal Video about PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis at 

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 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 ...

ptr-tof-ms-coupled-with-an-automated-sampling-system-tailored-data

Research

JoVE Journal

Chemistry

12.3K Views.  Fondazione Edmund Mach (FEM). 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).

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

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Many exceptional advances have been made in mass spectrometry (MS)-based proteomics, with particular technical progress in liquid chromatography (LC) coupled to tandem mass spectrometry (LC-MS/MS) and isobaric labeling multiplexing capacity. Here, we introduce a deep-proteomics profiling protocol that combines 10-plex tandem mass tag (TMT) labeling with an extensive LC/LC-MS/MS platform, and post-MS computational interference correction to accurately quantitate whole proteomes. This protocol includes the following main steps: protein extraction and digestion, TMT labeling, 2-dimensional (2D) LC, high-resolution mass spectrometry, and computational data processing. Quality control steps are included for troubleshooting and evaluating experimental variation. More than 10,000 proteins in mammalian samples can be confidently quantitated with this protocol. This protocol can also be applied to the quantitation of post translational modifications with minor changes. This multiplexed, robust method provides a powerful tool for proteomic analysis in a variety of complex samples, including cell culture, animal tissues, and human clinical specimens.

We present a protocol to accurately quantitate proteins with isobaric labelling, extensive fractionation, bioinformatics tools, and quality control steps in combination with liquid chromatography interfaced to a high-resolution mass spectrometer.

Many exceptional advances have been made in mass spectrometry (MS)-based proteomics, with particular technical progress in liquid chromatography (LC) ...

Biochemistry

Fatty Acid 13C Isotopologue Profiling Provides Insight into Trophic Carbon Transfer and Lipid Metabolism of Invertebrate Consumers

Fatty acids (FAs) are useful biomarkers in food web ecology because they are typically assimilated as a complete molecule and transferred into consumer tissue with minor or no modification, allowing the dietary routing between different trophic levels. However, the FA trophic marker approach is still hampered by the limited knowledge in lipid metabolism of the soil fauna. This study used entirely labelled palmitic acid (13C16:0, 99 atom%) as a tracer in fatty acid metabolism pathways of two widespread soil Collembola, Protaphorura fimata and Heteromurus nitidus. In order to investigate the fate and metabolic modifications of this precursor, a method of isotopologue profiling is presented, performed by mass spectrometry using single ion monitoring. Moreover, the upstream laboratory feeding experiment is described, as well as the extraction and methylation of dominant lipid fractions (neutral lipids, phospholipids) and the related formula and calculations. Isotopologue profiling does not only yield the overall 13C enrichment in fatty acids derived from the 13C labeled precursor but also produces the pattern of isotopologues exceeding the mass of the parent ion (i.e., the FA molecular ion M+) of each labeled FA by one or more mass units (M+1, M+2, M+3, etc.). This knowledge allows conclusions on the ratio of dietary routing of an entirely consumed FA in comparison to de novo biosynthesis. The isotopologue profiling is suggested as a useful tool for evaluation of fatty acid metabolism in soil animals to disentangle trophic interactions.

Fatty Acid 13C Isotopologue Profiling Provides Insight into Trophic Carbon Transfer and Lipid Metabolism of Invertebrate Consumers

The fatty acid trophic marker approach, i.e., the assimilation of fatty acids as entire molecule and transfer into consumer tissue with no or minor modification, is hampered by knowledge gaps in fatty acid metabolism of small soil invertebrates. Isotopologue profiling is provided as a valuable tool to disentangle trophic interactions.

Fatty acids (FAs) are useful biomarkers in food web ecology because they are typically assimilated as a complete molecule and transferred into consumer ...

Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures

Natural organic matter (NOM) is composed of a highly complex mixture of thousands of organic compounds which, historically, proved difficult to characterize. However, to understand the thermodynamic and kinetic controls on greenhouse gas (carbon dioxide [CO2] and methane [CH4]) production resulting from the decomposition of NOM, a molecular-level characterization coupled with microbial proteome analyses is necessary. Further, climate and environmental changes are expected to perturb natural ecosystems, potentially upsetting complex interactions that influence both the supply of organic matter substrates and the microorganisms performing the transformations. A detailed molecular characterization of the organic matter, microbial proteomics, and the pathways and transformations by which organic matter is decomposed will be necessary to predict the direction and magnitude of the effects of environmental changes. This article describes a methodological throughput for comprehensive metabolite characterization in a single sample by direct injection Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS), gas chromatography mass spectrometry (GC-MS), nuclear magnetic resonance (NMR) spectroscopy, liquid chromatography mass spectrometry (LC-MS), and proteomics analysis. This approach results in a fully-paired dataset which improves statistical confidence for inferring pathways of organic matter decomposition, the resulting CO2 and CH4 production rates, and their responses to environmental perturbation. Herein we present results of applying this method to NOM samples collected from peatlands; however, the protocol is applicable to any NOM sample (e.g., peat, forested soils, marine sediments, etc.).

This protocol describes a single throughput for complementary analytical and omics techniques culminating in a fully-paired characterization of natural organic matter and microbial proteomics in different ecosystems. This approach permits robust comparisons for identifying metabolic pathways and transformations important for describing greenhouse gas production and predicting responses to environmental change.

Natural organic matter (NOM) is composed of a highly complex mixture of thousands of organic compounds which, historically, proved difficult to ...

Environment

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.

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 ...

Enabling Real-Time Compensation in Fast Photochemical Oxidations of Proteins for the Determination of Protein Topography Changes

Fast photochemical oxidation of proteins (FPOP) is a mass spectrometry-based structural biology technique that probes the solvent-accessible surface area of proteins. This technique relies on the reaction of amino acid side chains with hydroxyl radicals freely diffusing in solution. FPOP generates these radicals in situ by laser photolysis of hydrogen peroxide, creating a burst of hydroxyl radicals that is depleted on the order of a microsecond. When these hydroxyl radicals react with a solvent-accessible amino acid side chain, the reaction products exhibit a mass shift that can be measured and quantified by mass spectrometry. Since the rate of reaction of an amino acid depends in part on the average solvent accessible surface of that amino acid, measured changes in the amount of oxidation of a given region of a protein can be directly correlated to changes in the solvent accessibility of that region between different conformations (e.g., ligand-bound versus ligand-free, monomer vs. aggregate, etc.) FPOP has been applied in a number of problems in biology, including protein-protein interactions, protein conformational changes, and protein-ligand binding. As the available concentration of hydroxyl radicals varies based on many experimental conditions in the FPOP experiment, it is important to monitor the effective radical dose to which the protein analyte is exposed. This monitoring is efficiently achieved by incorporating an inline dosimeter to measure the signal from the FPOP reaction, with laser fluence adjusted in real-time to achieve the desired amount of oxidation. With this compensation, changes in protein topography reflecting conformational changes, ligand-binding surfaces, and/or protein-protein interaction interfaces can be determined in heterogeneous samples using relatively low sample amounts.

Fast photochemical oxidation of proteins is an emerging technique for the structural characterization of proteins. Different solvent additives and ligands have varied hydroxyl radical scavenging properties. To compare the protein structure in different conditions, real-time compensation of hydroxyl radicals generated in the reaction is required to normalize reaction conditions.

Fast photochemical oxidation of proteins (FPOP) is a mass spectrometry-based structural biology technique that probes the solvent-accessible surface area ...

Shotgun Proteomics Sample Processing Automated by an Open-Source Lab Robot

Mass spectrometry-based shotgun proteomics experiments require multiple sample preparation steps, including enzymatic protein digestion and clean-up, which can take up significant person-hours of bench labor and present a source of batch-to-batch variability. Lab automation with pipetting robots can reduce manual work, maximize throughput, and increase research reproducibility. Still, the steep starting prices of standard automation stations make them unaffordable for many academic laboratories. This article describes a proteomics sample preparation workflow using an affordable, open-source automation system (The Opentrons OT-2), including instructions for setting up semi-automated protein reduction, alkylation, digestion, and clean-up steps; as well as accompanying open-source Python scripts to program the OT-2 system through its application programming interface.

Detailed protocol and three Python scripts are provided for operating an open-source robotic liquid handling system to perform semi-automated protein sample preparation for mass spectrometry experiments, covering detergent removal, protein digestion, and peptide desalting steps.

Mass spectrometry-based shotgun proteomics experiments require multiple sample preparation steps, including enzymatic protein digestion and clean-up, ...

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome

Untargeted metabolomics techniques are being widely used in recent years. However, the rapidly increasing throughput and number of samples create an enormous amount of spectra, setting challenges for quality control of the mass spectrometry spectra. To reduce the false positives, false discovery rate (FDR) quality control is necessary. Recently, we developed a software for FDR control of untargeted metabolome identification that is based on a Target-Decoy strategy named XY-Meta. Here, we demonstrated a complete analysis pipeline that integrates XY-Meta and metaX together. This protocol shows how to use XY-meta to generate a decoy database from an existing reference database and perform FDR control using the Target-Decoy strategy for large-scale metabolome identification on an open-access dataset. The differential analysis and metabolites annotation were performed after running metaX for metabolites peaks detection and quantitation. In order to help more researchers, we also developed a user-friendly cloud-based analysis platform for these analyses, without the need for bioinformatics skills or any computer languages.

We constructed an untargeted metabolomic workflow that integrated XY-Meta and metaX together. In this protocol, we displayed how to use XY-Meta to generate a decoy spectral library from open access spectra reference, and then performed FDR control and used the metaX to quantitate the metabolites after identifying the metabolomics spectra.

Untargeted metabolomics techniques are being widely used in recent years. However, the rapidly increasing throughput and number of samples create an ...

Harvesting the Orthogonality of LC and TIMS&#45;TOF MS&#47;MS to Screen Fentanyl Analogs

Fentanyl Analog Screening using LC-TIMS-TOF MS/MS

The use of fentanyl and the emergence of fentanyl analogs over recent decades has become an increasing concern to the community at large. Fentanyl and its analogs are the major contributors to fatal and nonfatal overdoses in the United States. Most recent cases of fentanyl-related overdose are linked to illicitly manufactured fentanyl and its associated extreme potency. In the present work, we describe a high-throughput analytical protocol for the screening of fentanyl analogs. The use of complementary liquid chromatography, trapped ion mobility spectrometry, and tandem mass spectrometry allow for the separation and assignment of hundreds of fentanyl analogs from a single sample in a single scan. The described approach takes advantage of the recent development of data-dependent acquisition and data-independent acquisition using parallel accumulation in the mobility trap followed by sequential fragmentation using collision-induced dissociation. The fentanyl analogs are confidently assigned based on their retention time, mobility, and MS fragmentation pattern.

Author Spotlight: An Efficient Methodology to Confidently Differentiate and Characterize Fentanyl Analogs 

A method for the screening of fentanyl analogs based on their retention time, mobility, and mass spectrometry fragmentation pattern.

The use of fentanyl and the emergence of fentanyl analogs over recent decades has become an increasing concern to the community at large. Fentanyl and its ...

Protease- and Acid-catalyzed Labeling Workflows Employing 18O-enriched Water

Stable isotopes are essential tools in biological mass spectrometry. Historically, 18O-stable isotopes have been extensively used to study the catalytic mechanisms of proteolytic enzymes1-3. With the advent of mass spectrometry-based proteomics, the enzymatically-catalyzed incorporation of 18O-atoms from stable isotopically enriched water has become a popular method to quantitatively compare protein expression levels (reviewed by Fenselau and Yao4, Miyagi and Rao5 and Ye et al.6). 18O-labeling constitutes a simple and low-cost alternative to chemical (e.g. iTRAQ, ICAT) and metabolic (e.g. SILAC) labeling techniques7. Depending on the protease utilized, 18O-labeling can result in the incorporation of up to two 18O-atoms in the C-terminal carboxyl group of the cleavage product3. The labeling reaction can be subdivided into two independent processes, the peptide bond cleavage and the carboxyl oxygen exchange reaction8. In our PALeO (protease-assisted labeling employing 18O-enriched water) adaptation of enzymatic 18O-labeling, we utilized 50% 18O-enriched water to yield distinctive isotope signatures. In combination with high-resolution matrix-assisted laser desorption ionization time-of-flight tandem mass spectrometry (MALDI-TOF/TOF MS/MS), the characteristic isotope envelopes can be used to identify cleavage products with a high level of specificity. We previously have used the PALeO-methodology to detect and characterize endogenous proteases9 and monitor proteolytic reactions10-11. Since PALeO encodes the very essence of the proteolytic cleavage reaction, the experimental setup is simple and biochemical enrichment steps of cleavage products can be circumvented. The PALeO-method can easily be extended to (i) time course experiments that monitor the dynamics of proteolytic cleavage reactions and (ii) the analysis of proteolysis in complex biological samples that represent physiological conditions. PALeO-TimeCourse experiments help identifying rate-limiting processing steps and reaction intermediates in complex proteolytic pathway reactions. Furthermore, the PALeO-reaction allows us to identify proteolytic enzymes such as the serine protease trypsin that is capable to rebind its cleavage products and catalyze the incorporation of a second 18O-atom. Such "double-labeling" enzymes can be used for postdigestion 18O-labeling, in which peptides are exclusively labeled by the carboxyl oxygen exchange reaction. Our third strategy extends labeling employing 18O-enriched water beyond enzymes and uses acidic pH conditions to introduce 18O-stable isotope signatures into peptides.

Protease- and Acid-catalyzed Labeling Workflows Employing 18O-enriched Water

Stable isotope labeling workflows employing 18O-enriched water (LeO-workflows) are versatile tools for quantitative and qualitative proteomics studies. In protease-assisted (PALeO) workflows, 18O-atoms are introduced by proteolytic cleavage and carboxyl oxygen exchange reactions mediated by proteases. In the acid-catalyzed (ALeO) workflow, 18O-atoms are introduced by carboxyl oxygen exchange at low pH.

Stable isotopes are essential tools in biological mass spectrometry. Historically, 18O-stable isotopes have been extensively used to study the catalytic ...

Biology

Comprehensive Protocol for Cell Identification and Metabolic Analysis Using OPTIR-FISH

Optical Photothermal Infrared-Fluorescence In Situ Hybridization (OPTIR-FISH)

Understanding the metabolic activities of individual cells within complex communities is critical for unraveling their role in human disease. Here, we present a comprehensive protocol for simultaneous cell identification and metabolic analysis with the OPTIR-FISH platform by combining rRNA-tagged FISH probes and isotope-labeled substrates. Fluorescence imaging provides cell identification by the specific binding of rRNA-tagged FISH probes, while OPTIR imaging provides metabolic activities within single cells by isotope-induced red shift on OPTIR spectra. Using bacteria cultured with 13C-glucose as a test bed, the protocol outlines microbial culture with isotopic labeling, fluorescence in situ hybridization (FISH), sample preparation, optimization of the OPTIR-FISH imaging setup, and data acquisition. We also demonstrate how to perform image analysis and interpret spectral data at the single-cell level with high throughput. This protocol&#39;s standardized and detailed nature will greatly facilitate its adoption by researchers from diverse backgrounds and disciplines within the broad single-cell metabolism research community.

Author Spotlight: Integrated OPTIR-FISH for Single-Cell Metabolic and Identity Analysis in Complex Environments

Here, we present a protocol using optical photothermal infrared-fluorescence in situ hybridization (OPTIR-FISH), also known as mid-infrared photothermal-FISH (MIP-FISH), to identify individual cells and understand their metabolism. This methodology can be applied broadly for diverse applications, including mapping cellular metabolism with single-cell resolution.

Understanding the metabolic activities of individual cells within complex communities is critical for unraveling their role in human disease. Here, we ...

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

Samenvatting

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