Thin Film Chemical Deposition Techniques as a Tool for

Subscriber access provided by TULANE UNIVERSITY

Article

Thin film chemical deposition techniques as a tool for fingerprinting of free fatty acids by MALDI-TOF-MS Ekaterina P. Podolskaya, Alexey S. Gladchuk, Olga A Keltsieva, Polina S. Dubakova, Elena Silyavka, Elena Lukasheva, Vladimir Zhukov, Natalia Lapina, Manizha R. Makhmadalieva, Alexander M. Gzgzyan, Nikolai G. Sukhodolov, Konstantin A. Krasnov, Artem A. Selyutin, and Andrej Frolov Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.8b05296 • Publication Date (Web): 11 Dec 2018 Downloaded from http://pubs.acs.org on December 12, 2018

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 25 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Analytical Chemistry

Graphical abstract 47x26mm (300 x 300 DPI)

ACS Paragon Plus Environment

Analytical Chemistry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 2 of 25

Thin film chemical deposition techniques as a tool for fingerprinting of free fatty acids by MALDI-TOF-MS

Ekaterina P. Podolskaya,1,2§ Alexey S. Gladchuk,1,3§ Olga A. Keltsieva,1,2 Polina S. Dubakova,1,3 Elena S. Silyavka,4 Elena Lukasheva,5 Vladimir Zhukov,6 Natalia Lapina,1 Manizha R. Makhmadalieva,7 Alexander M. Gzgzyan,7 Nikolai G. Sukhodolov,2,4 Konstantin A. Krasnov,1Artem A. Selyutin4*and Andrej Frolov5,8*

1Institute

of Toxicology, Russian Federal Medical Biological Agency, 2Institute of Analytical

Instrumentation, Russian Academy of Science, 3St. Petersburg Peter the Great Polytechnic University,

4Institute

of Chemistry, St. Petersburg State University,

5Department

of

Biochemistry, St. Petersburg State University, 6All-Russia Research Institute for Agricultural Microbiology, 7Research Institute of Obstetrics, Gynecology and Reproductology named after D.O. Ott, 8Department of Bioorganic Chemistry, Leibniz Institute of Plant Biochemistry

§These

authors contributed equally to the manuscript

*Corresponding authors: Dr. Artem Selyutin

Dr. Andrej Frolov

St. Petersburg State University

Leibniz Institute of Plant Biochemistry

Universitetskaya nab.7-9

Department of Bioorganic Chemistry

199034 St. Petersburg, Russian Federation

Weinberg 3, 06120, Halle/Saale, Germany

Tel. +7 (812) 4286733

Tel. +49 (345) 55821350

Fax. +7 (812) 4286733

Fax. +49 (345) 55821309

Email: [email protected],

Email: [email protected]

ACS Paragon Plus Environment

Page 3 of 25 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


1

Abstract

2

Metabolic fingerprinting is a powerful analytical technique, giving access to a high-

3

throughput identification and relative quantification of multiple metabolites. Due to short

4

analysis times, MALDI-TOF-MS is the preferred instrumental platform for fingerprinting,

5

although its power in analysis of free fatty acids (FFAs) is limited. However, these

6

metabolites are the biomarkers of human pathologies and indicators of food quality. Hence, a

7

high-throughput method for their fingerprinting is required. Therefore, here we propose a

8

MALDI-TOF-MS method for identification and relative quantification of FFAs in biological

9

samples of different origin. Our approach relies on formation of monomolecular Langmuir

10

films (LFs) at the interphase of aqueous barium acetate solution, supplemented with low

11

amounts of 2,5-dihydroxybenzoic acid, and hexane extracts of biological samples. This

12

resulted in detection limits of 10-13 - 10-14 mol and overall method linear dynamic range of at

13

least four orders of magnitude with accuracy and precision within 2 and 17%, respectively.

14

The method precision was verified with eight sample series of different taxonomy that

15

indicates a universal applicability of our approach. Thereby, 31 and 22 FFA signals were

16

annotated by exact mass and identified by tandem MS, respectively. Among 20 FFAs

17

identified in Fucus algae, 14 could be confirmed by GC-MS.

18 19 20 21 22 23

Keywords

24

Barium monocarboxylates, free fatty acids (FFAs), Langmuir film technology, matrix-assisted

25

laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF-MS), metabolic

26

fingerprinting, monomolecular Langmuir layers 2 ACS Paragon Plus Environment


1

Introduction

2

During the recent decades, mass spectrometry (MS)-based metabolic profiling emerged as a

3

powerful tool for characterization of complex biological systems [1]. Free fatty acids (FFAs)

4

represent a metabolite class, attracting a special attention of analysts [2]. These compounds

5

are the markers of lipid metabolism status [3], and their profiling in body fluids delivers

6

valuable information for diagnostics of multiple human disorders [4]. Not less importantly,

7

FFAs are well-known as reliable food quality markers [5]. Currently, GC-MS/MS is the main

8

methodological platform, routinely applied for analysis of FFAs [6]. However, despite of a

9

high sensitivity and robustness of this technique, it ultimately requires derivatization of not

10

sufficiently volatile analytes [7]. It negatively affects sample throughput and might trigger

11

transesterification of lipids, isomerization and oxidation of unsaturated FFAs [8,9]. Although

12

reversed phase high-performance liquid chromatography (RP-HPLC), coupled on-line to

13

electrospray ionization (ESI-MS) or tandem MS (MS/MS) can be also applied to analysis of

14

FFAs [10], these methods are less sensitive (LC-ESI-MS) or more specific (LC-ESI-MS/MS),

15

than comprehensive GC-MS techniques [11].

16

Metabolic fingerprinting, i.e. a fast high-throughput screening of a whole metabolome or

17

specific groups of metabolites [12], provides an efficient solution of the above mentioned

18

problems. This powerful approach does not assume extensive sample preparation or

19

implementation of any separation techniques, and typically relies on flow injection analysis

20

(FIA) [13] or matrix-assisted laser desorption/ionization-time of flight mass spectrometry

21

(MALDI-TOF-MS) [14], which is less amenable to ion suppression [15] and might provide,

22

hence, better sensitivity and reproducibility. In analysis of FFAs, MALDI-TOF-MS typically

23

relies on detection in negative ion mode using 1,8-di(piperidinyl)naphthalene (DPN), N1,N4-

24

dibenzylidenebenzene-1,4-diamine (DBDA), or graphene oxide (GO) as matrices [16-18].

25

Alternatively, FFAs can be detected in positive ion mode in the presence of divalent metal

26

salts in liquid MALDI samples, or detection might rely on [RCOOMe+Me]+ adducts in the 3 ACS Paragon Plus Environment

Page 4 of 25

Page 5 of 25 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


1

presence of cesium or sodium acetate spiked to meso-tetrakis porphyrin matrix (F20TPP)

2

[19,20].

3

However, as the sample application techniques, conventionally used for MALDI-TOF-MS,

4

rely on solutions, containing organic solvents – i.e. acetonitrile or methanol [21], the

5

equilibrium of ion interaction is shifted in favor of the starting compounds (i.e. FFAs and

6

metal ions). It results in a low degree of salt formation and ultimately compromises the

7

sensitivity of analysis [22]. Therefore, here we propose a new analytical strategy, free of this

8

limitation and based on the technology of Langmuir [23]. Our approach is applicable to a

9

broad range of plant and animal species, does not require intensive sample preparation, well-

10

compatible with commercially available MALDI-TOF-MS instrumentation, and provides

11

reliable, sensitive and precise detection of FFAs as corresponding barium monocarboxylates,

12

i.e. cations, comprising Ba2+ ion and singly charged monocarboxylate anion.

13

Materials and methods

14

Reagents and biological materials

15

Acetonitrile was from LiChrosolv (hypergrade for LC-MS). All other reagents were

16

purchased by Sigma-Aldrich (ChimMed, St. Petersburg, Russia). Water was purified in house

17

(resistance 22 mΩ/cm) on a water conditioning and purification system Elix 3 UV (Millipore,

18

Moscow, Russia). The biological samples, i.e. seeds and root nodules of pea (Pisum sativum

19

L), thalluses of Fucus vesiculosus, muscles of Mytilus edulis, caviar of White Sea herring

20

(Clupea pallasii marisalbi), daphnia (Daphnia magna), human follicular fluid, rabbit and

21

human blood plasma, were obtained from the sources and by procedures, described in detail

22

in Supporting information 1 (Protocol S1-1). Extraction of samples relied on specific

23

procedures, listed in Protocol S1-2. The settings of gas chromatography – mass spectrometry

24

analysis are summarized in Table S1-1, whereas determination of streaming potential and

25

surface conductivity is described in Protocol S1-3. 4 ACS Paragon Plus Environment


1

Preparation of barium monocarboxylate monolayers and MALDI-TOF-MS analysis

2

Barium monocarboxylate monolayers were prepared either in a Petri dish (Figure S1-1A-D,

3

Protocol S1-4), or directly on a MALDI target. In the latter case, aliquots of 1 mg/mL barium

4

acetate solution were mixed with the equal volumes of 0.5, 2, or 10 g/L of 2,5-

5

dihydroxybenzoic acid (DHB) in water, and 0.50 – 0.75 µL of this mixture were applied on a

6

target (MTP 384 polished steel, Bruker Daltonics, Bremen, Germany, Figure S1-1E).

7

Alternatively, barium acetate solution was applied on the MALDI target without pre-mixing

8

with DHB. Afterwards, the same volumes of the 100-fold diluted standard mixture (250

9

ng/mL each component, Table S1-2) or biological extracts, were repeatedly overlaid (two-

10

three times) directly on the surface of the droplet, formed by the barium acetate/DHB solution

11

(Figure S1-1F). Thereby, a pipette tip was placed on the top of the droplet, in maximally close

12

proximity to the surface (within 1 mm, or even touching it), but not penetrating the phase

13

interface. Thus, hexane extract slowly slide from the top of the droplet downhill to the target

14

surface, and distributed on the surface of aqueous phase, forming thereby a monolayer. After

15

distribution of the sample on the drop surface (Figure S1-1G) and completeness of drop

16

drying (Figure S1-1H), applied standard mixtures and samples were overlaid with 1.5 µL of

17

0.1% (v/v) TFA in 90% (v/v) aq. acetonitrile, and dried under air flow prior to MALDI-TOF-

18

MS analysis. Visualization of the on-target sample preparation procedure relied on

19

polarization microscope Leica DM4500 P (Leica Microsystems, Wetzlar, Germany) and

20

optical tensiometer Theta Lite (Biolin Scientific, Stockholm, Sweden).

21

For MALDI-TOF-MS analysis, standard mixtures and biological samples were applied on a

22

stainless steel MALDI target (n = 4) and the spectra were acquired (n = 5 per spot) with the

23

UltrafleXtreme MALDI-TOF/TOF mass spectrometer (Bruker Daltonics, Bremen, Germany)

24

using the settings, listed in Table S1-3. The signal of the mono-substituted barium salt of

25

DHB at m/z 290.924 was used for mass calibration.

26

Results 5 ACS Paragon Plus Environment

Page 6 of 25

Page 7 of 25 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


1

Formation of monomolecular LFs on MALDI target

2

Unfortunately, not all FA standards could be identified, when LFs were prepared in a Petri

3

dish format (Figure 1A). To increase the sensitivity of the analysis, we addressed the

4

possibility of monolayer formation directly on a stainless steel metal polished MALDI or LDI

5

target. As the size of LFs, generated in this case, was limited to the size of a barium acetate

6

solution droplet, spotted on a MALDI target, analyte concentrations in the standard mixture

7

were appropriately hundred-fold reduced (up to 0.25 µg/mL of each FFA). The optimal

8

efficiency of monolayer formation could be achieved when an aqueous droplet of 0.50 - 0.75

9

µL was overlaid with a sample in organic phase of the same volume (Figure S1-1F). After

10

drying the sample, a barium monocarboxylate monolayer could be seen as a thin film on the

11

surface of the target, partly attached to barium acetate crystals that did not compromise

12

spectra quality. Expectedly, switch to the on-spot overlay technology resulted in efficient and

13

sensitive detection of all six FFAs by characteristic signals of their barium monocarboxylates

14

with at least a hundred-fold reduction of sample consumption and decrease in sample

15

preparation time (Figure 1B). Thereby, analytes could be assigned by m/z, isotopic

16

distribution and MS/MS patterns with mass resolution of 5500 to 10000.

17

MALDI-TOF-MS analysis of FFA barium monocarboxylates in monomolecular LFs

18

In the next step, we addressed the applicability of our MALDI-TOF-MS approach to

19

biologically relevant matrices. In the first line, we considered brown algae (F. vesiculosus), as

20

the organisms with high tissue levels of FFAs [24]. The analysis showed that ionization of

21

biogenic FFAs required harsh conditions: 85 – 90 and 90 - 95% of the maximal laser energy

22

(MLE) when ionization was performed from the surface of barium acetate crystals and

23

degraded barium monocarboxylate monolayer, respectively. Thus, barium acetate could not

24

provide efficient re-distribution of the laser energy in a sample crystal. In this context,

25

supplementation with appropriate matrix additives could improve energy transfer. On the

26

other hand, although no unwanted reactions were observed, under high laser energies lower 6 ACS Paragon Plus Environment


1

laser life times could be expected. Therefore, reduction of operational laser energies was

2

desired.

3

To address this possibility, we supplemented a 0.5 g/L barium acetate solution with variable

4

amounts of 2,5-dihydroxybenzoicacid (DHB, final concentration of 0.25, 1, and 5 g/L), and

5

spotted 0.6 µL of these mixtures directly on the MALDI target (n = 4) prior to overlay with

6

0.6 µL of F. vesiculosus hexane extracts. The spectra were acquired with laser intensity

7

starting from 30% with a 4-5% increment. When a DHB solution was added at the highest

8

concentration (5 g/L), MS signals could be reliably detected at 45 – 50% of MLE. However,

9

the spectra dominated with the peaks not corresponding to barium monocarboxylate salts of

10

fatty acids (m/z 410.073, 426.973, 444.998, 466.971, Figure 2A), and did not contain signals,

11

corresponding to barium monocarboxylates. The intermediate DHB concentration (1 g/L)

12

yielded well-interpretable mass spectra, represented the signals of barium monocarboxylates

13

and DHB adducts (53 – 58% of MLE, Figure S1-2). A decrease of DHB concentration to 0.25

14

g/L required an increase of laser intensity to 65 – 75% of MLE. This resulted, however, in a

15

quantitative suppression of DHB-related signals and detection solely the signals of FFA

16

barium monocarboxylates in the spectra (Figure 2B).

17 18

Standardization and validation of the MALDI-TOF-MS method

19

The method limits of detection (LODs), determined with LF in the presence of DHB, ranged

20

from 10 (myristic, pentadecanoic and palmitic acids) to 50 fmol (lauric and tridecanoic acids),

21

whereas the LOQs did not exceed 500 fmol (Table 1). For estimation of the method linearity

22

and precision, individual authentic standards were mixed in different ratios and serially

23

diluted. Thereby, the intensities of analytes were normalized to m/z 393.138, corresponding to

24

the barium palmitate cation (see Supporting information 2 for details). After plotting of

25

normalized intensities against the corresponding logarithmically transformed concentration

26

ratios, linear dynamic range (LDR) could be determined. For all analytes it covered at least 7 ACS Paragon Plus Environment

Page 8 of 25

Page 9 of 25 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


1

four orders of magnitude with the coefficient of determination (R2) of at least 0.95 and

2

accuracy ranging from 99.6 to 101.7 % (Table 1 and Supporting information 2). A similar

3

normalization strategy was validated also for a highly-unsaturated FA (arachidonic acid).

4

The intra-spot precision, expressed as relative standard deviations (RSDs), did not exceed

5

10.0%, reaching 13.1% only for myristic acid (Table 2). The RSDs for intra-day precision

6

were about 10% or slightly higher, whereas inter-day variations reached maximally 17.5%

7

(С16:1). This result was confirmed in vivo in other biological matrices using the same sample

8

application scheme (Table S1-4). Remarkably, the observed good precision, sensitivity and

9

linearity were obtained after incubation in mass spectrometer (under vacuum) overnight that

10

might result if effective removal of water from deeper parts of the sample. In contrast, all

11

parameters were slightly compromised, when the samples were measured directly after

12

spotting (Supporting information 2, Table S2-11).

13

To address, if isotopic distribution of barium is able to invalidate quantitative result, we

14

analyzed dilution series of a standard mixture containing interfering pairs of fatty acids

15

(16:0/16:1 and 18:0/18:1). As can be exemplified by an overlay of isotopic distributions of

16

barium monostearate and barium monooleate (Figure S1-3A-C), there is approximately 5%

17

interference of the third isotopomers of saturated acids with monoisotopic signals of the

18

corresponding monounsaturated counterparts. However, in general, the ratios of monoisotopic

19

peak intensities correspond well to the ratios of FFAs in a sample (Figure S1-3D), and both

20

groups of analytes demonstrate linear response (R2 ≥ 0.97) for potentially affected acids

21

(Supporting information 3, Figure S1-4). It is comparable with a less than 5% contamination

22

of reagents with stearic acid, often observable in analyses. Thus, isotopic distribution of

23

barium does not invalidate quantitative results.

24

To address the correlation of our results with FFA patterns obtained by other analytical

25

techniques, we analyzed the extracts from F. vesiculosus thalluses by gas chromatography-

26

electron ionization-quadrupole-mass spectrometry (GC-EI-Q-MS) in parallel to our approach. 8 ACS Paragon Plus Environment


1

The GC-MS profiles (Figure S1-5A) were in agreement with the profiles, observed in

2

MALDI-TOF spectra, although the latter showed higher numbers of confidently identified

3

individual FFAs (20 vs 14, Figure S1-5B).

4

Method application: MALDI-TOF-MS analysis of FFAs in biological samples

5

To address the applicability of our method to analysis of FFAs in natural matrices, we

6

analyzed a selection of samples, listed in the Method part. The numbers of annotated FFA

7

signals varied from 9 in pea seed extracts to 25 in human follicular fluid samples (Table S1-5,

8

Figure 3). Annotation relied on exact mass, characteristic isotopic distribution and MS/MS

9

patterns (Table S1-6). The MS/MS spectra typically dominated with a Ba·+ signal, followed

10

with characteristic losses of water and CO2, peak of BaOH+, and series of σ cleavages (signals

11

a – o in Figure 4). As exemplified by the spectrum of arachidonic acid, double bonds could be

12

easily localized by characteristic increments of methylene or methyne groups (Figures 4 and

13

S1-6A). This observation was successfully confirmed for fatty acids with other degree of

14

unsaturation (Figure S1-6B-E). Importantly, isotopic distribution of barium did not create

15

irresolvable complications. Totally 22 FFAs could be identified by isotopic patterns and

16

MS/MS, whereas further nine species could be annotated only by m/z (and three by

17

combination of exact mass and MS/MS).

18

The spectra of pea seed extracts (Figure 3A) demonstrated a pattern of nine signals of barium

19

monocarboxylates (C14, C16, C18 and C19 compounds) with the base peak of linoleic acid

20

and/or its isomers (C18:2, m/z 417.134). Although the nodule spectra dominated with the

21

same peak (Figure 3B), the overall signal patterns were more abundant and dominated with

22

saturated FFAs. The spectra of F. vesiculosus dominated with m/z 419.148 (C18:1, oleic acid

23

and/or its isomers), 365.106 and 393.134 (myristic and palmitic acids, Figure 3C). The

24

intensities of the signals, related to C20 FFAs (ω-3 and ω-6 families) increased in the order

25

m/z 441.137 (C20:4) > m/z 439.124 (C20:5) > m/z 445.187 (C20:2). 9 ACS Paragon Plus Environment

Page 10 of 25

Page 11 of 25 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


1

The spectra of the animal tissue extracts demonstrated much more abundant patterns of FFAs

2

(up to 22 species in daphnia extracts, Figure 3D). Thus, only in daphnia samples, C16:2,

3

C16:3 and C16:4 compounds were detected (m/z 389.115, 387.096, and 385.077,

4

respectively). In turn, the spectra, acquired with the extracts of herring caviar and mussel

5

muscles (Figure 3E,F) demonstrated strong signals of docosahexaenoic acid with its isomers

6

(C22:6) and multiple C20 compounds, abundance of which decreased in the order C20:5 >

7

C20:1 > C20:2 > C20:4 > C20:3, indicating the most complete patterns of ɷ-3-, ɷ-6-, and ɷ-

8

9-FFAs (Figure 3F).

9

Analysis of blood plasma samples revealed an essential difference in signal patterns, observed

10

in rabbits and humans, where 15 and 22 FFAs were detected, respectively (Figure 3G and S1-

11

7). Indeed, in contrast to the rabbit samples, the mass spectra of human plasma represented a

12

pattern of C20 and C22 FFA signals (with abundances of C20:4 and C20:5 acids соmparable

13

to those of the C18:0 acid), and the signals of C21:3 and C21:4 compounds (m/z 457.134 and

14

455.115, respectively). Finally, the spectra of the human plasma extracts did not display any

15

signals of short-chained FFAs (С < 16), besides a low-intense barium myristate signal at m/z

16

365.106 (Figure S1-3). Analysis of human follicular fluid (FF) yielded 25 annotated signals,

17

representing also C19, C20 and C22 acids (Figure 3H).

18

Discussion

19

Formation of monomolecular LFs

20

During formation of LFs, carboxylic acids readily and quantitatively form salts at the

21

interphase with aqueous solutions containing cations of alkaline and alkaline earth (e.g.

22

barium) elements [25]. Barium monocarboxylate ions have positive charge, as they are

23

composed from doubly charged barium cation and singly charged carboxylate anion. Thus,

24

resulting salts can be efficiently desorbed and transferred to gas phase by a UV laser [26].

25

However, formation of carboxylate salt is often not quantitative, especially when organic

26

additives are used in sample preparation [22]. In this context, enhancement of the carboxylic 10 ACS Paragon Plus Environment


1

group dissociation might yield an essential sensitivity gain. To achieve this, we applied here

2

the Langmuir technology, which gives access to monomolecular Langmuir films [27].

3

Thereby, formation of monomolecular Langmuir films by barium salts of fatty acids occurs at

4

the aqueous-organic interphase and is accompanied with a quantitative dissociation of FFAs

5

[28]. Therefore, we assumed that formation of monomolecular Langmuir films with a sample,

6

dissolved in organic solvent (n-hexane), i.e. under the conditions providing a quantitative

7

transition of FFAs from the non-dissociated form (which cannot be ionized in positive ion

8

mode) to the form of barium monocarboxylate, which can be effectively analyzed, might

9

dramatically increase FFA dissociation, ionization efficiency and method sensitivity. Indeed,

10

when the organic phase contains a mixture of FFAs, the monolayer would comprise

11

corresponding FFA salts. Earlier we have proved this concept with Fe(III) ions [29,30]. Here

12

we decided to focus on barium, due to its large ion radius and strong ionic properties,

13

favorable for ionization of barium monocarboxylates under MALDI conditions [26]. From the

14

other hand, the appearing monocarboxylate signals can be easily distinguished in mass spectra

15

by characteristic isotope patterns of barium compounds [31]. Formation of barium

16

dicarboxylate-based LFs seems to be unlikely, as electrokinetic potential of these monolayers

17

is lower, than that of monocarboxylate-derived ones (Figure S1-8).

18

Although monomolecular layers can be easily obtained in a Petri dish (Figure S1-1), this setup

19

results in a compromised detection of short-chained (< 15C) FFAs (Figure 1A). Indeed,

20

reproducible formation of solid monolayers (i.e. carboxylate monolayers which can be

21

collapsed on the surface of the aqueous phase) requires saturated alkylacyl moieties of at least

22

14 carbon atoms, whereas unsaturated FFAs have low potential for formation of solid

23

Langmuir films [32]. In this context, a methodology, relying on liquid monolayers would be

24

advantageous. As such structures cannot be collapsed and transferred to new tubes [33], we

25

propose here formation of monolayers directly on a MALDI target within one spot, using sub-

26

µL volumes of two phases, with subsequent degradation of monolayers and drying without 11 ACS Paragon Plus Environment

Page 12 of 25

Page 13 of 25 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


1

any transfer in between. The principle advantage of our approach is the use of organics-free

2

aqueous solutions, which underlie high constants of FFA dissociation and salt formation.

3

Combined with on-spot enrichment, it dramatically increased method sensitivity, bringing it

4

to the values, more common for MS/MS approach, simultaneously with at least a hundred-

5

fold reduction in sample consumption (Table 1).

6

An essential disadvantage of the described setup was compromised energy re-distribution in

7

dried barium matrix, and hence, high laser energies, required for analysis. To attenuate this

8

effect, we supplemented the barium acetate solution with 0.25 g/L DHB. Although this

9

amount was only 1 – 5% of conventionally used DHB concentrations, it was sufficient for

10

generation of intense barium monocarboxylate signals and to ensure a high specificity of the

11

method with 20-25% reduction of required laser energy (Figure 2B). This fact underlies

12

unexpectedly high sensitivities. Thereby, dihydroxybenzoate anions could be incorporated in

13

the monolayer structure in agreement with their molar ratio in the original n-hexane solution,

14

or can be distributed along its surface. As acidic pH suppresses dissociation of FFAs and

15

formation of monolayers, compromising thereby sensitivity of analysis, TFA cannot be added

16

directly to matrix. From the other hand, after formation of salt, the monolayer needs to be

17

destroyed to facilitate sample desorption.

18

Validation of the LF-based MALDI-TOF-MS method

19

The method sensitivities, observed here, were one or two orders of magnitude higher, than

20

those obtained with other MALDI-TOF-MS methods [34]. Generally, our LODs (tens or

21

hundreds femtomol) corresponded better to the sensitivity of LC-MS [35] or even LC-MS/MS

22

[36]. Analogously, the LOQs were two orders of magnitude lower than those reported earlier

23

for FFAs based on MALDI-TOF- and GC-MS data and comparable to results obtained by

24

LC-MS/MS-based methods [34,37,38]. Higher LODs and LOQs, observed for short-chained

25

FFAs, can be explained by a less degree of inter-chain hydrophobic interactions of their

26

shorter hydrocarbon parts. From another hand, a higher inductive effect of a longer 12 ACS Paragon Plus Environment


1

hydrocarbon chain results in less acidity of carboxylic groups, higher pKa values, and, hence,

2

higher stability of barium monocarboxylates. Although typically LDR of MALDI-TOF does

3

not exceed two orders of magnitude [39] (that was also the case here), for some TOF-based

4

laser desorption/ionization methods it can rich three orders of magnitude [40]. Having here

5

the instrumental LDR only two orders of magnitude, we succeeded to increase the overall

6

method LDR 100-fold, by normalization of the analyte signal intensities to the reference

7

compound (palmitic acid) taken in different concentrations, covering the range of 102 (i.e.

8

acquiring several spectra, Supporting information 2). Although it did not improve the

9

performance of the instrument itself, this strategy resulted in the overall LDR of our setup at

10

least one order of magnitude higher than those published earlier for MALDI-TOF-MS [16]

11

and LC-MS [41] without loss of accuracy [38]. Thus, from the point of linearity, our approach

12

can be compared only with the GC-MS procedure, reported by Kloos and co-authors [42]. Оf

13

course, as the proposed technique was designed for metabolic fingerprinting, we only roughly

14

estimated the LDRs using serial dilutions with a ten-fold increment. A fine assessment of this

15

parameter by equidistant standard dilution might result in larger LDRs. Remarkably, the

16

method demonstrated a high intra-spot precision (RSD ≤ 10%, Table 2).

17

The values for intra- and inter-day precision (RSD ≤ 15%) were comparable to MALDI-TOF-

18

MS- and LC-MS/MS data [17,43]. High precision of analysis can be, at least partly, attributed

19

to a high homogeneity of monolayers in comparison to matrix crystals. Indeed, increase of

20

spectra numbers, acquired from one spot did not affect precision (Table S1-7). From another

21

hand, high precision, might be underlied by a high stability of FFA salts under vacuum.

22

Indeed, as carboxylate salts of unsaturated fatty acids have melting points over 100°C,

23

evaporation of these analytes from sample surface is unlikely, whereas it is a common case,

24

when fatty acids are directly analyzed by MALDI-TOF-MS [44]. Another important feature

25

of our method is selectivity. Indeed, as formation of LFs is selective for FFAs, no interference

26

with other analytes is observed. Thus, lower identification rates observed for GC-Q-MS in 13 ACS Paragon Plus Environment

Page 14 of 25

Page 15 of 25 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


1

comparison to our method illustrate this fact – due to the presence of contaminating peaks of

2

co-eluting compounds, the EI-MS spectra of minor FFAs could not be confidently identified

3

by a search against spectrum libraries.

4

Taking the things together, outstanding sensitivity and LDR of the method in combination

5

with good precision and accuracy make it an excellent tool for fingerprinting of biological

6

samples of different origin varying in FFA contents.

7

Analysis of free fatty acids in biological samples

8

As our method showed a high sensitivity, linearity and precision, it could be potentially

9

applicable to metabolic fingerprinting. Therefore, we addressed its performance in analysis of

10

samples of various origins, covering not only the major taxonomic groups (plants, algae,

11

invertebrate and vertebrate animals, symbiotic associations), but also different application

12

areas – pharmaceutical and natural product chemistry, medical diagnostics, and life sciences.

13

Fortunately, the precision of the assay, determined for eight biological matrices was below

14

15% and was similar between different objects (Table S1-4), i.e. met requirements for

15

metabolomics studies [45,46] and allowed comparisons both within and between species.

16

Based on such inter-species comparisons, some conclusions about FFA patterns, characteristic

17

for different organisms and tissues, could be done. Thus, from one hand, the analyzed samples

18

clearly differed both in numbers of detected signals, specific for barium monocarboxylates

19

(which varied from 9 to 25, Table S1-5) and their relative intensities in the spectra. From

20

another, the majority of the spectra contained two signal clusters, corresponding to C16

21

(mostly palmitic and hexadecenoic acids) and C18 (to a large extend corresponding to stearic,

22

oleic, linoleic and linolenic acids) compounds.

23

It is important to mention, that individual signals in the spectra of natural extracts can be

24

represented by patterns of double bond positional and/of cis/trans isomers. Obviously, the

25

proposed here method is well-suited for FFA profiling, but not ideal for structure elucidation.

26

Thus, to address the isomer composition additional GC-MS or GC-MS/MS experiments with 14 ACS Paragon Plus Environment


1

electron impact or chemical ionization, respectively, would be necessary. High efficiency of

2

GC columns would allow separation of isomers, and then at least position of double bond can

3

be assigned [47].

4

Conclusion

5

Although metabolite profiling represents a powerful analytical platform, the methods of GC-

6

and LC-based metabolomics have relatively low throughput that limits their application in

7

wide-scale screening studies. In contrast, MALDI-TOF-MS-based metabolite fingerprinting is

8

the method of choice, when large sample batches need to be analyzed. Therefore, here we

9

proposed a reliable fingerprinting method for rapid screening of FFA patterns in biological

10

samples of different origin. Due to its high sensitivity, precision and linearity, it is well-suited

11

for qualitative and semi-quantitative comparison of large sample batches. Moreover,

12

employing the stable isotope dilution technique in future might give access to absolute

13

quantification of FFAs. This method can be universally applied in clinical diagnostics, food

14

quality analysis, and in experimental biology, for example for mutant screening or wide-scale

15

ecological studies.

16

Acknowledgement

17

The authors thank Russian Science Foundation (project № 17-16-01042) for the financial

18

support. The Research Resource Centers for Molecular and Cell Technologies, for Geo-

19

Environmental Research and Modeling, for Chemical Analysis, the Material Research Center

20

of St Petersburg State University are acknowledged for technical support.

15 ACS Paragon Plus Environment

Page 16 of 25

Page 17 of 25 1 2 3 1 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 2 19 20 21 3 22 23 4 24 25 5 26 27 28 6 29 30 7 31 32 8 33 34 9 35 36 37 10 38 39 11 40 41 42 43 44 45 46


Table 1 Sensitivity and linearity parameters of the MALDI-TOF-MS method for FFA analysis

♯

Standard

Labela

m/z

Elemental composition

Error (ppm)

LOD (pmol)

LOQ (pmol)

LDRb

Slope

Intercept

R2

Accuracyc

1

Lauric acid

C12:0

337.075

C12H23O2Ba+

-44.5

0.05

0.50

1 x 104

1.60E-02

4.80E-02

0.95

99.6

2

Tridecanoic acid

C13:0

351.091

C13H25O2Ba+

6.6

0.05

0.47

1 x 104

2.20E-02

6.54E-02

0.98

99.7

3

Myristic acid

C14:0

365.106

C14H27O2Ba+

-41.9

0.01

0.04

1 x 104

9.41E-02

2.60E-01

0.99

101.7

4

Pentadecanoic acid

C15:0

379.122

C15H29O2Ba+

-26.4

0.01

0.04

1 x 104

1.15E-01

3.35E-01

0.99

100.6

5

Palmitic acidd

C16:0

393.138

C16H31O2Ba+

-6.6

0.01

0.09

-

-

-

-

-

The parameters were determined with a standard mixture, containing lauric, tridecanoic, myristic, pentadecanoic and palmitic acids dissolved in nhexane. The mixtures (0.6 µL) were overlaid on the surface of droplets, containing 0.5 g/L barium acetate and 0.25 g/L 2,5-dihydroxybenzoic acid (DHB, totally 0.6 µL), spotted directly on the MALDI target and dried. MALDI-TOF-MS spectra were acquired in positive reflector mode. Individual analyte intensities were normalized to the barium palmitate signal at the m/z 393.14 (theoretical m/z 393.138). aIndividual analytes (FFAs) are labeled by the numbers of carbon atoms in their aliphatic chains. For the determination of blinearity parameters and caccuracy, serial dilutions of authentic standards (taken in different ratios) were performed, and the analyte signal intensity ratios were plotted against the corresponding logarithmically transformed concentration ratios, as described in detail in Supporting information 2. dThe signal of palmitic acid was used for normalization. LOD, limit of detection; LOQ, limit of quantification; LDR, linear dynamic range


Analytical Chemistry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46

1

Page 18 of 25

Table 2 Quantitative validation of the MALDI-TOF-MS method with intra-spot, intra-day, inter-day precision Intra-spot precision (n = 3)

Intra-day precision (n = 27)

Inter-day precision (n = 27/day)c

Analyte labela (FFAs)

m/z [M-H+Ba]+

3

С14:0

365.106

0.178 ± 0.003 (1.4) - 0.221 ± 0.029 (13.1)

0.221 ± 0.022 (10.0)

0.216 ± 0.035 (16.0)

11

С16:1

391.129

0.103 ± 0.002 (1.9) – 0.100 ± 0.009 (9.2)

0.090 ± 0.012 (13.8)

0.105 ± 0.018 (17.5)

5

C16:0

393.134

0.434 ± 0.004 (1.0) – 0.441 ± 0.023 (5.3)

0.412 ± 0.048 (11.5)

0.477 ± 0.057 (11.9)

16

C18:2

417.136

0.411 ± 0.002 (0.5) – 0.438 ± 0.027 (6.2)

0.435 ± 0.020 (4.7)

0.421 ± 0.031 (7.5)

21

C20:5

439.123

0.149 ± 0.001 (0.5) – 0.133 ± 0.009 (7.4)

0.168 ± 0.022 (13.1)

0.140 ± 0.022 (16.0)

22

C20:4

441.136

0.305 ± 0.014 (4.7) – 0.287 ± 0.020 (6.9)

0.356 ± 0.042 (11.9)

0.303 ± 0.043 (14.0)

♯

bNormalized

intensity ± SD (RSD%)

bNormalized


bNormalized


2

Validation was performed with a pooled hexane extract of Fucus vesiculosus thalluses (100 mg of tissue/mL of n-hexane). For each replicate, three

3

extracts were prepared independently, each extract was applied in three different positions on the MALDI target, and three spectra per spot were

4

acquired. aIndividual analytes (FFAs) are labeled by the numbers of carbon atoms in the aliphatic chain and the numbers of double bonds;

5

bindividual

6

can

analyte intensities were normalized to the signal of the barium monocarboxylate of oleic acid at m/z 419.15 (theoretical m/z 419.153);

inter-day precision was determined on three consecutive days; SD, standard deviation; RSD%, relative standard deviation percentage


Page 19 of 25 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

1


Figures

2 3

Figure 1 MALDI-TOF spectra of a standard mixture containing 25 (A) or 0.25 (B) µg/mL

4

lauric, tridecanoic, myristic, pentadecanoic, palmitic and stearic acids, dissolved in n-hexane.

5

The spectra were acquired with solid monolayers, collapsed on the surface of 1 mg/mL aq.

6

barium acetate, overfilled in a Petri dish (A), and with LFs formed directly on the MALDI

7

target using 0.6 µL of 1 mg/mL barium acetate, overlaid with 0.6 µL of the standard mixture

8

(B). After drying of the samples, the spectra were acquired at 89-94% laser energy in reflector

9

positive ion mode. The samples were applied in triplicates, and three spectra per spot were

10

acquired. The minor signals reflect isotopic distribution of barium.

11 12 13 14 15 16 17



1 2

Figure 2 MALDI-TOF spectra of an n-hexane extract of F. vesiculosus thalluses, acquired in

3

the presence of solid barium monocarboxylate LFs. The LFs were formed directly on the

4

MALDI target using 0.6 µL of 0.5 g/L barium acetate supplemented with 5 (A) and 0.25 (B)

5

g/L 2,5-dihydroxybenzoic acid (DHB), and overlaid with 0.6 µL of the extract

6 7 8 9 10 11 12 13


Page 20 of 25

Page 21 of 25 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


1 2

Figure 3 MALDI-TOF mass spectra of n-hexane extracts acquired with biological samples of

3

different origin. The LFs were formed directly on the MALDI target using 0.6 µL of 0.5 g/L

4

barium acetate supplemented with 0.25 g/L 2,5-dihydroxybenzoic acid (DHB), and overlaid

5

with 0.6 µL of the extracts, obtained from pea (Pisum sativum L.) seeds (A) and root nodules

6

(B), thalluses of Fucus vesiculosus (C), Daphnia magna (D), caviar of Clupea pallasii

7

marisalbi (E), muscles of Mytilus edulis (F), rabbit (Oryctolagus cuniculus, breed Soviet

8

Chinchilla) blood plasma (G), human follicular fluid (H). The spectra were acquired in

9

reflector positive mode. Inserts represent magnified views of regions marked with asterisks. 20 ACS Paragon Plus Environment


1 2

Figure 4 MS/MS spectrum of m/z 441, corresponding to the [M-H+Ba]+ ion of arachidonic

3

acid (C20:4). The spectra were acquired in reflector positive mode, using LFs, formed on the

4

interphase of 0.5 g/L barium acetate supplemented with 0.25 g/L 2,5-dihydroxybenzoic acid

5

(DHB) and n-hexane extract of F. vesiculosus thalluses (top) and authentic standard of

6

arachidonic acid (bottom), pipetted directly on MALDI target


Page 22 of 25

Page 23 of 25 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

1 2 3 4 5


References 1. Dudzik, D.; Barbas-Bernardos, C.; García, A.; Barbas, C. J. Pharm. Biomed. Anal. 2018, 147, 149–173.

6 7

2. Goettel, M.; Niessner, R.; Pluym, N.; Scherer, G.; Scherer, M. J. Chromatogr. B: Anal. Technol. Biomed. Life Sci. 2017, 1041–1042, 141–150.

8

3. Saini, R. K.; Keum, Y. S. Life Sci. 2018, 203, 255–267.

9

4. Tiuca, I.; Nagy, K.; Oprean, R. Rom. J. Lab. Med. 2015, 23 (4), 371-384.

10 11

5. Gavahian, M.; Chu, Y. H.; Khaneghah, A. M.; Barba, F. J.; Misra, N. N. Trends Food Sci. Technol. 2018, 77, 32–41.

12 13

6. Yi, L.; He, J.; Liang, Y.; Yuan, D.; Gao, H.; Zhou, H. Chem. Phys. Lipids. 2007, 150 (2), 204-216.

14 15

7. Han, L. D.; Liang, Q. L.; Wang, Y. M.; Hu, P.; Luo, G. A. Chin. Chem. Lett. 2009, 20 (9), 1103-1106.

16 17

8. Krylov, A. I.; Khlebnikova, N. S.; Poluyaktova, S. K. J. Anal. Chem. 1991, 46 (12), 24282435 [in Russian].

18 19

9. Christie, W. W. Advances in Lipid Methodology – Two; Oily Press: Dundee, U. K., 1993; Vol.2, pp 69-111.

20

10. Wei, G.; Zeng, E. Y. TrAC, Trends Anal. Chem. 2011, 30 (9), 1429-1436.

21 22

11. Milman, B. L.; Utsal′, V. A.; Lugovkina, N. V.; Kotryakhov, I. A.; Zhurkovich, I. K. J. Anal. Chem. 2015, 70 (14), 1601-1613.

23

12. Aretz, I.; Meierhofer, D. Int. J. Mol. Sci. 2016, 17 (5), 632.

24 25

13. Rodrigues, C. M.; Rinaldo, D.; dos Santos, L. C.; Montoro, P.; Piacente, S.; Pizza, C.; et al. Rapid Commun. Mass Spectrom. 2007, 21 (2), 1907-1914.

26

14. Fuchs, B.; Schiller, J. Eur. J. Lipid Sci. Technol. 2009, 111 (1), 83–98.

27

15. Holčapek, M.; Jirásko, R.; Lísa, M. J. Chromatogr. A. 2012, 1259, 3-15.

28

16. Weißflog, J.; Svatoš, A. RSC Adv. 2016, 6 (79), 75073-75081.

29 30

17. Ling, L.; Li, Y.; Wang, S.; Guo, L.; Xiao, C.; Chen, X.; et al. J. Am. Soc. Mass Spectrom. 2018, 29 (4), 704-710.

31 32

18. Zhou, D.; Guo, S.; Zhang, M.; Liu, Y.; Chen, T.; Li, Z. Anal. Chim. Acta. 2017, 962, 5259.

33

19. Hale, O. J.; Cramer, R. Anal. Bioanal. Chem. 2018, 410 (5), 1435–1444. 22 ACS Paragon Plus Environment


1 2

20. Yu, H.; Lopez, E.; Young, S. W.; Luo, J.; Tian, H.; Cao, P. Anal. Biochem. 2006, 354 (2), 182-191.

3

21. Cohen, S. L.; Chait, B. T. Anal. Chem. 1996, 68 (1), 31-37.

4

22. Megriche, A.; Belhadj, A.; Mgaidi, A. Mediterr. J. Chem. 2012, 1 (4), 200–209.

5

23. Stickland, F. G. W. J. Colloid Interface Sci. 1972, 40 (2), 142-152.

6

24. Kelly, J. R.; Scheibling, R. E. Mar. Ecol.: Prog. Ser. 2012, 446, 1–22.

7 8

25. Gaines, G. L. Insoluble monolayers at liquid-gas interfaces, 1st ed.; Wiley-Interscience: New York, 1966.

9 10

26. Podolskaya, E. P.; Serebryakova, M. V.; Krasnov, K. A.; Grachev, S.A.; Gzgzyan, A. M.; Sukhodolov, N. G. Mendeleev Commun. 2018, 28 (3), 337-339.

11 12

27. Yanklovich, M. A.; Ivanov, N. S.; Sukhodolov, N.G; Zhukov, A.N. Colloid J. 2016, 78 (2), 277-280.

13 14

28. Girard-Egrot, A. P.; Godoy, S.; Blum, L. J. Adv. Colloid Interface Sci. 2005, 116 (1-3), 205-225.

15 16

29. Rozhkova, E. A.; Krasnov, I. A.; Sukhodolov, N. G.; Ivanov, N. S.; Yanklovich, A. I.; Podolskaya, E. P.; et al. Nauchn. Priborostr. 2008, 18 (4), 54–60 [in Russian].

17 18

30. Gladilovich, V.; Greifenhagen, U.; Sukhodolov, N.; Selyutin, A.; Singer, D.; Thieme, D.; et. al. J. Chromatogr. A. 2016, 1443, 181-190.

19

31. Berglund, M.; Wieser, M. E. Pure Appl. Chem. 2011, 83 (2), 397-410.

20

32. Spink, J. A. J. Colloid Sci. 1963, 18 (6), 512-525.

21

33. Roberts, G. G. Langmuir-Blodgett Films, 1st ed.; Plenum Press: New York, 1990

22

34. Yang, M.; Fujino, T. Anal. Chem. 2014, 86 (19), 9563-9569.

23

35. Li, X.; Franke, A. A. Anal. Chem. 2011, 83 (8), 3192-3198.

24

36. Lee, S. H.; Pettinella, C.; Blair, I. A. Curr. Drug Metab. 2006, 7 (8), 929-937.

25 26

37. Pettinella, C.; Lee, S. H.; Cipollone, F.; Blair, I. A. J. Chromatogr. B: Anal. Technol. Biomed. Life Sci. 2007, 850 (1-2), 168-176.

27 28

38. Cui, Y.; Chen, X.; Liu, L.; Xie, W.; Wu, Y.; Wu, Q.; et al. Bio-Med. Mater. Eng. 2015, 26 (s1), S2165-S2177.

29

39. Hou, X.; Xie, F.; Sweedler, J. V. J. Am. Soc. Mass Spectrom. 2012, 23 (12), 2083-2093.

30 31

40. Pirkl, A.; Meier, M.; Popkova, Y.; Letzel, M.; Schnapp, A.; Schiller, J.; et. al. Anal. Chem. 2014, 86 (21), 10763-10771. 23 ACS Paragon Plus Environment

Page 24 of 25

Page 25 of 25 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


1

41. Yang, W. C.; Adamec, J.; Regnier, F. E. Anal. Chem. 2007, 79 (14), 5150-5157.

2 3

42. Kloos, D. P.; Gay, E.; Lingeman, H.; Bracher, F.; Müller, C.; Mayboroda, O. A.; et al. Rapid Commun. Mass Spectrom. 2014, 28 (13), 1507-1514.

4 5

43. Pichini, S.; Pellegrini, M.; Gareri, J.; Koren, G.; Garcia-Algar, O.; Vall O.; et al. J. Pharm. Biomed. Anal. 2008, 48 (3), 927-933.

6 7

44. Eibisch, M.; Süß, R.; Schiller, J. Rapid Commun. Mass Spectrom. 2012, 26 (13), 15731576.

8

45. Handrick, V.; Vogt, T.; Frolov, A. Anal. Bioanal. Chem. 2010, 398 (7-8), 2789-2801.

9 10

46. Frolov, A.; Henning, A.; Böttcher, C.; Tissier, A.; Strack, D. J. Agric. Food Chem. 2013, 61 (6), 1219-1227.

11 12

47. Ecker, J.; Scherer, M.; Schmitz, G.; Liebisch, G. J. Chromatography B. 2012, 897, 98104.


Thin Film Chemical Deposition Techniques as a Tool for

Recommend Documents