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Open Access 17.11.2019 | Short Communication

Development and application of a forensic toxicological library for identification of 56 natural toxic substances by liquid chromatography–quadrupole time-of-flight mass spectrometry

verfasst von: Tadashi Ogawa, Kei Zaitsu, Tetsuo Kokaji, Kayako Suga, Fumio Kondo, Masae Iwai, Takayoshi Suzuki, Akira Ishii, Hiroshi Seno

Erschienen in: Forensic Toxicology

Abstract

Purpose

The present study aims to develop a forensic toxicological library to identify 56 natural toxic substances by liquid chromatography–quadrupole time-of-flight tandem mass spectrometry (LC–QTOF-MS/MS).

Methods

For setting up the library of product ion spectra, individual substances (31 plant toxins, 7 mushroom toxins, 5 marine toxins, 5 frog venoms, 4 mycotoxins, and 4 substances derived from plants) were analyzed by LC–QTOF-MS/MS with positive and negative ionization. The product ion spectra were acquired at the collision energies (CEs) of 20, 35, and 50 eV in single enhanced product ion mode and then in collision energy spread mode in which the CE ramp range was set to 35 ± 15 eV.

Results

To test the performance of the library, human blood plasma samples were spiked with a mixture of lycorine and domoic acid, extracted by acetonitrile deproteinization and analyzed by LC–QTOF-MS/MS. Identification by our library search could be achieved for these toxins at the purity scores of 79.1 and 67.2, respectively. The method was also applied to postmortem blood from a death case with an aconite intake, and showed that four toxins in an aconite could be identified in the blood sample at the purity scores of 54.6–60.3.

Conclusions

This library will be more effective for the screening of natural toxic substances in routine forensic toxicological analysis. To our knowledge, there are no reports dealing with development of library for natural toxic substances by LC–QTOF-MS/MS.
Hinweise

Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1007/​s11419-019-00506-w) contains supplementary material, which is available to authorized users.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Introduction

Natural toxins are chemicals that are naturally produced by living organisms such as some plants, mushrooms, marine animals, and so on [1]. These toxins are not harmful to the organisms themselves but they may be toxic to other creatures, including humans, when eaten [1]. For example, tetrodotoxin in pufferfish and some marine animals is a powerful sodium channel blocker in excitable tissues such as nerves and muscles, and is about 10,000 times more lethal than cyanide by weight [2]. Forensic toxicology is a part of the pharmacological science, which is concerned with the identification/quantification and effects of various drugs and poisons in human beings [3]. Natural toxins are very important analytical targets in forensic toxicology [46]. It is difficult to attribute a cause of death to natural toxin(s) in routine toxicological analysis because there is currently no effective routine screening method for a variety of natural toxins [7].
In the last decade, liquid chromatography–tandem mass spectrometry (LC–MS/MS) has been developing its importance for the screening of drugs and/or poisons, most of which is based on triple quadrupole mass spectrometers employing multiple reaction monitoring survey scan followed by a product ion scan by electrospray ionization [811]. The application of this method is limited because of disturbances by high matrix burden and co-eluting peaks, indicating that analytes can be detected only if they are abundantly contained in the samples and that the method can easily lead to false positive/negative detection [12]. This drawback prompts the need for additional approaches achieving unambiguous identification of analytes.
Recently, liquid chromatography–quadrupole time-of-flight tandem mass spectrometry (LC–QTOF-MS/MS) has been utilized to develop libraries of compounds relevant to clinical and forensic toxicology [1321]. However, to the best of our knowledge, there are no reports on development of library for natural toxic substances by LC–QTOF-MS/MS. In this paper, we describe the development and application of forensic toxicological library of 56 natural toxic substances using LC–QTOF-MS/MS.

Materials and methods

Chemicals and reagents

Target natural toxic substances were selected on the basis of previously reported poisoning cases as follows: 31 plant toxins (coniine, lycorine, galantamine, atropine, picrotoxinin, scopolamine, picrotin, strychnine, colchicine, veratramine, cyclopamine, jervine, amygdalin, aconine, cymarin, convallatoxin, cucurbitacin E, oleandrin, benzoylmesaconine, benzoylaconine, tubocurarine, hypaconitine, mesaconitine, 14-anisoylaconine, aconitine, jesaconitine, digitoxin, digoxin, α-chaconine, α-solanine, and dioscin), 7 mushroom toxins (muscimol, ibotenic acid, muscarine, phalloidin, γ-amanitin, α-amanitin, and β-amanitin), 4 mycotoxins (aflatoxin B1, aflatoxin B2, aflatoxin G1 and aflatoxin G2), 5 marine toxins (domoic acid, tetrodotoxin, okadaic acid, dinophysistoxin-1, and brevetoxin b), and 5 frog venoms (bufotenine, resibufogenin, bufalin, cinobufagin, and batrachotoxin). In addition to the natural toxins, berberine, cinchonidine, diosgenin, and quinine were selected as target substances, which are considered to be important materials of herbal medicines. Scopolamine, aflatoxin B1, aflatoxin B2, tetrodotoxin, quinine, aflatoxin G1, aflatoxin G2, resibufogenin, bufalin, colchicine, cyclopamine, diosgenin, cinobufagin, amygdalin, benzoylmesaconine, tubocurarine, mesaconitine, 14-anisoylaconine, jesaconitine, okadaic acid, and dinophysistoxin-1 were purchased from Fujifilm Wako Pure Chemical (Osaka, Japan); muscimol, coniine, ibotenic acid, muscarine, bufotenine, cinchonidine, strychnine, cymarin, convallatoxin, cucurbitacin E, oleandrin, digitoxin, digoxin, and α-solanine from Sigma-Aldrich (St. Louis, MO, USA); picrotoxinin, picrotin, domoic acid, γ-amanitin, and β-amanitin from Abcam Biochemicals (Cambridge, UK); berberine, aconine, and benzoylaconine from Cayman Chemical (Ann Arbor, MI, USA); galantamine, atropine, and jervine from Tokyo Chemical Industry (Tokyo, Japan); α-chaconine and dioscin from Extrasynthese (Lyon, France); batrachotoxin and aconitine from Latoxan (Valence, France); phalloidin and α-amanitin from Merck Millipore (Billerica, MA, USA); lycorine, hypaconitine, brevetoxin b, and veratramine from Enzo Life Sciences (New York, NY, USA); Kishida Chemical (Osaka, Japan), LKT Laboratories (St. Paul, MN, USA), and Toronto Research Chemicals (Toronto, Canada), respectively. The stock solutions of all substances were prepared at a concentration of 10–1000 μg/mL. Muscarine, lycorine, cinchonidine, scopolamine, tetrodotoxin, quinine, berberine, resibufogenin, cinobufagin, amygdalin, hypaconitine, and α-amanitin were dissolved in distilled water (DW). Aconitine and benzoylaconine were dissolved in acetonitrile. Other toxins were dissolved in methanol solution. Stock solutions were stored at − 80 °C until analysis. Methanol, acetonitrile and DW of the HPLC grade were purchased from Kanto Chemical (Tokyo, Japan). Other common chemicals used were of the highest purity commercially available. Human whole blood was obtained from Tennessee Blood Services (Memphis, TN, USA).

LC–QTOF-MS (/MS) conditions

Sciex Triple TOF 5600 mass spectrometer (Sciex, Framingham, MA, USA) and Shimadzu NexeraX2 LC system (Shimadzu Co., Kyoto, Japan) were used for analysis. The column used for chromatographic separation was L-column ODS (150 × 1.5 mm i.d., particle size 5.0 μm; Chemicals Evaluation and Research Institute, Sugito, Saitama, Japan). The column temperature was maintained at 40 °C, and the gradient system was used with a mobile phase (A) 10 mM ammonium formate in 5% methanol aqueous solution and (B) 10 mM ammonium formate in 95% methanol solution. Linear gradient elution was started from 100% A to 100% B over 15 min. The 100% B was held for 5 min. It was then returned to 100% A over 10 min for the next run. The autosampler was maintained at 4 °C and the injection volume was 10 µL. Electrospray ionization was used in both positive and negative modes. The optimal MS parameters were declustering potential at 80 V and information dependent acquisition (IDA) criteria set at over 50 cps. The LC–QTOF-MS system allowed the acquisition of highly sensitive full scan MS spectra with high resolution and mass accuracy. In addition, IDA can be used to collect MS/MS spectra for compound identification based on MS/MS library searching.
This LC–QTOF-MS (/MS) method had several advantages for accurate detection of natural toxic substances. For instance, the mass spectrometer used in this study, triple TOF 5600, had high throughput which enabled very fast MS/MS acquisition rates at as low as 20 ms accumulation time in IDA mode. To fully leverage the instrument speed and obtain the best depth of coverage, the IDA workflow was optimized such that software overhead is minimized. The IDA method consisted of a high-resolution TOF-MS survey scan could follow up to 50 MS/MS ions. The combined use of high-resolution MS and IDA were extremely effective for the simultaneous detection of natural toxic substances in forensic samples. The instrument gave the resolution of 35,000.
Data acquisition and processing were performed by Analyst software and Peak View incorporated with the XIC Manager application (Sciex). The XIC Manager can be used for targeted processing of high-resolution MS and MS/MS data allowing for screening and identification with the highest confidence based on retention time (RT), mass error of molecular ion, isotopic pattern, and automatic MS/MS library searching.

Construction of library of natural toxic substances by LC–QTOF-MS (/MS)

All target substances were analyzed to investigate their retention properties, isotopic ratios and high-resolution MS/MS spectra obtained by collision induced dissociation (CID) with the injected amount of each compound of 0.1 µg. The four spectra were acquired at the collision energy (CE) at 20, 35, and 50 eV in single enhanced product ion (EPI) mode together with collision energy spread (CES) mode, in which the CE ramp range was set to 35 ± 15 eV. The CES parameter, in conjunction with the CE, determined the collision energy applied to the precursor ion in a product ion scan. The CE is ramped from low to high energies. The selection ranges of the precursor ion and RT of each compound for acquiring the library search were 20 mDa and 4.0 min, respectively. Compound identification was based on chromatographic and mass spectrometric information, including RT error, mass error, isotope matching, and library search results. The product ion for library search could be chosen from four spectra by CID energies of (±) 20, 35, 50, and 35 ± 15 eV, automatically.

Limits of detection and recovery rates

To determine the limits of detection (LODs), 5 plots with different concentrations of each substance spiked into blank blood plasma were used. The LODs were defined as the concentrations giving a signal-to-ratio of 3:1. The recovery rates were calculated by the ratio of peak area obtained from a target substance spiked into ante-extraction matrix to that obtained from the substance spiked into post-extraction matrix.

Analysis of spiked samples

The blood plasma samples spiked with lycorine (1 µg/mL) and domoic acid (10 µg/mL) were prepared. A 100-μL volume of blood plasma containing the target substances was mixed with 100 μL methanol and 300 μL acetonitrile. The mixture was then mixed by vortexing for 30 s and centrifuged at 15,000 g for 10 min. The supernatant was transferred to another tube and evaporated with a centrifugal evaporator (CVE-2000; Tokyo Rikakikai, Tokyo, Japan). The residue was reconstituted in 100 μL of 10 mM ammonium formate in 5% methanol solution and mixed by vortexing for 1 min. A 10-µL of the extract solution was analyzed by LC–QTOF-MS/MS using our newly developed library.

Application to forensic autopsy samples

A 45-year-old male with groan was found at his home. He was taken to hospital by an ambulance, but died shortly afterward. Beside the body in the room, there were dried roots of an aconite plant. Femoral vein and right and left heart blood samples were collected at autopsy performed in our laboratory and stored at − 80 °C until analysis. The blood samples were treated and analyzed in the same way as spiked samples described above.

Results

Development of library of natural toxic substances

Registered data consisted of 56 natural toxic substances with compound name, source, formula, exact mass, polarity, exact mass of precursor ion, ion form, RT, LOD, and recovery rate (Table 1). Extracted ion chromatograms of simultaneous determination of 56 substances are shown in Fig. 1. Product ion spectra of all substances were obtained by four different CE settings (see supplementary material Fig. S1). As an example the four spectra obtained for tetrodotoxin, which is one of the important toxins in food poisoning cases in Japan, are shown in Fig. 2. The [M + H]+ (m/z 320.1088) was the most abundant ion at 20 eV (Fig. 2a), while it remarkably decreased at 35 eV (Fig. 2b) and became a very small peak at 50 eV (Fig. 2c), and the number and intensity of fragment ions increased instead (Fig. 2a–c). Product ion spectra obtained by CES mode showed both [M + H]+ and fragment ions (Fig. 2d). CES mode can collect an average MS spectrum of different CE values in one single EPI scan, resulting in a full scan spectrum with both molecular and fragment ion information that can be used in library search-based identification with increased confidence. Digoxin, α-solanine, α-chaconine, digitoxin and dioscin provided [M + HCOO], and amygdalin and cucurbitacin E showed [M + NH4]+ instead of [M + H]+ (Table 1, supplementary material Fig. S1, nos. 36, 46, 47, 51, 57, 7, and 45, respectively); therefore, it is necessary to pay attention to this phenomenon.
Table 1
Registered data in a forensic toxicological library for natural toxic substances for liquid chromatography–quadrupole time-of-flight mass spectrometry listed according to the retention times
No
Compound name
Source
Molecular formula
Exact mass (Da)
Polarity
Extracted mass (ionized form) calculated
Ion form
Retention time (min)
LOD (ng/mL)
Recovery rate (%)
1
Tetrodotoxin
Tetraodontidae
C11H17N3O8
319.1016
Pos
320.1088
[M+H]+
1.9
100
75.5
2
Muscimol
Amanita pantherina
C4H6N2O2
114.0429
Pos
115.0502
[M+H]+
2.1
500
88.4
3
Ibotenic acid
Amanita pantherina
C5H6N2O4
158.0328
Pos
159.0400
[M+H]+
2.1
100
98.6
4
Muscarine
Amanita pantherina
C9H20NO2
174.1494
Pos
174.1489
[M]+
3.2
5
68.2
5
Domoic acid
Chondria armata
C15H21NO6
311.1369
Pos
312.1442
[M+H]+
4.2
10
92.8
6
Bufotenine
Bufo gargarizans
C12H16N2O
204.1263
Pos
205.1335
[M+H]+
6.2
0.5
69.1
7
Amygdalin
Prunus armeniaca
C20H27NO11
457.1584
Pos
475.1922
[M+NH4]+
8.4
0.5
70.2
8
Coniine
Conium maculatum
C8H17N
127.1361
Pos
128.1434
[M+H]+
9.0
5
81.4
9
Aconine
Aconitum
C25H41NO9
499.2781
Pos
500.2854
[M+H]+
9.5
0.5
71.7
10
Lycorine
Lycoris radiata
C16H17NO4
287.1158
Pos
288.1230
[M+H]+
9.6
0.05
90.7
11
Galantamine
Lycoris radiata
C17H21NO3
287.1521
Pos
288.1594
[M+H]+
9.7
0.05
88.5
12
α-Amanitin
Amanita phalloides
C39H54N10O14S
918.3542
Pos
919.3615
[M+H]+
10.2
10
70.5
13
β-Amanitin
Amanita phalloides
C39H53N9O15S
919.3382
Pos
920.3455
[M+H]+
10.2
10
71.0
14
Atropine
Datura metel
C17H23NO3
289.1678
Pos
290.1751
[M+H]+
10.7
0.05
75.0
15
Tubocurarine
Chondrodendron tomentosum
C37H41N2O6
609.2965
Pos
609.2959
[M]+
10.7
5
73.8
16
γ-Amanitin
Amanita phalloides
C39H54N10O13S
902.3593
Pos
903.3665
[M+H]+
11.0
10
69.0
17
Scopolamine
Datura metel
C17H21NO4
303.1471
Pos
304.1543
[M+H]+
11.1
0.1
73.3
18
Picrotin
Anamirta cocculus
C15H18O7
310.1053
Neg
309.0980
[M-H]-
11.2
100
96.0
19
Picrotoxinin
Anamirta cocculus
C15H16O6
292.0947
Pos
293.1020
[M+H]+
11.5
50
71.1
20
Strychnine
Strychnos nux-vomica
C21H22N2O2
334.1681
Pos
335.1754
[M+H]+
11.7
0.05
78.6
21
Berberine
Coptis japonica
C20H18NO4
336.1236
Pos
336.1230
[M]+
12.8
5
76.1
22
Cinchonidine
Cinchona pubescens
C19H22N2O
294.1732
Pos
295.1805
[M+H]+
12.9
5
83.1
23
Benzoylaconine
Aconitum
C32H45NO10
603.3044
Pos
604.3116
[M+H]+
12.9
5
75.5
24
Phalloidin
Amanita phalloides
C35H48N8O11S
788.3163
Pos
789.3236
[M+H]+
12.9
100
83.4
25
Aflatoxin G2
Aspergillus flavus
C17H14O7
330.0740
Pos
331.0812
[M+H]+
13.0
1
87.5
26
Benzoylmesaconine
Aconitum
C31H43NO10
589.2887
Pos
590.2960
[M+H]+
13.1
0.05
79.8
27
Aflatoxin G1
Aspergillus flavus
C17H12O7
328.0583
Pos
329.0656
[M+H]+
13.4
1
82.0
28
Convallatoxin
Convallaria majalis
C29H42O10
550.2778
Pos
551.2851
[M+H]+
13.6
10
69.1
29
14-Anisoylaconine
Aconitum
C33H47NO11
633.3149
Pos
634.3222
[M+H]+
13.6
1
79.9
30
Aflatoxin B2
Aspergillus flavus
C17H14O6
314.0790
Pos
315.0863
[M+H]+
13.8
1
90.8
31
Quinine
Cinchona pubescens
C20H24N2O2
324.1838
Pos
325.1911
[M+H]+
13.8
5
78.6
32
Colchicine
Colchicum autumnale
C22H25NO6
399.1682
Pos
400.1755
[M+H]+
13.9
0.1
97.5
33
Veratramine
Veratrum album
C27H39NO2
409.2981
Pos
410.3054
[M+H]+
14.1
0.05
79.2
34
Jervine
Veratrum album
C27H39NO3
425.2930
Pos
426.3003
[M+H]+
14.1
50
87.2
35
Batrachotoxin
Phyllobates terribilis
C31H42N2O6
538.3043
Pos
539.3116
[M+H]+
14.1
1
86.3
36
Digoxin
Digitalis lanata
C41H64O14
780.4296
Neg
825.4278
[M+HCOO]-
14.1
500
86.0
37
Aflatoxin B1
Aspergillus flavus
C17H12O6
312.0634
Pos
313.0707
[M+H]+
14.2
1
86.3
38
Hypaconitine
Aconitum
C33H45NO10
615.3044
Pos
616.3116
[M+H]+
14.6
0.1
90.4
39
Cyclopamine
Veratrum album
C27H41NO2
411.3137
Pos
412.3210
[M+H]+
14.8
50
76.8
40
Mesaconitine
Aconitum
C33H45NO11
631.2993
Pos
632.3065
[M+H]+
14.9
5
85.9
41
Aconitine
Aconitum
C34H47NO11
645.3149
Pos
646.3222
[M+H]+
14.9
0.5
80.1
42
Jesaconitine
Aconitum
C35H49NO12
675.3255
Pos
676.3328
[M+H]+
14.9
1
75.6
43
Cymarin
Adonis ramosa
C30H44O9
548.2985
Pos
549.3058
[M+H]+
15.0
10
82.6
44
Bufalin
Bufo gargarizans
C24H34O4
386.2457
Pos
387.2530
[M+H]+
15.1
0.5
80.1
45
Cucurbitacin E
Lagenaria siceraria
C32H44O8
556.3036
Pos
574.3374
[M+NH4]+
15.3
50
72.3
46
α-Solanine
Solanum tuberosum
C45H73NO15
867.4980
Neg
912.4962
[M+HCOO]-
15.9
5000
93.9
47
α-Chaconine
Solanum tuberosum
C45H73NO14
851.5031
Neg
896.5013
[M+HCOO]-
16.0
5000
68.6
48
Oleandrin
Nerium oleander
C32H48O9
576.3298
Neg
575.3226
[M-H]-
16.7
100
97.4
49
Cinobufagin
Bufo gargarizans
C26H34O6
442.2355
Pos
443.2428
[M+H]+
16.8
5
83.1
50
Resibufogenin
Bufo gargarizans
C24H32O4
384.2301
Pos
385.2373
[M+H]+
16.9
5
72.1
51
Digitoxin
Digitalis purpurea
C41H64O13
764.4347
Neg
809.4329
[M+HCOO]-
17.5
100
73.0
52
Okadaic acid
Halichondria okadai
C44H68O13
804.4660
Pos
805.4733
[M+H]+
17.9
100
94.7
53
Dinophysistoxin-1
Dinophysis fortii
C45H70O13
818.4816
Pos
819.4889
[M+H]+
18.6
50
87.2
54
Brevetoxin b
Karenia brevis
C50H70O14
894.4766
Pos
895.4838
[M+H]+
18.9
50
82.4
55
Dioscin
Dioscorea quinqueloba
C45H72O16
868.4820
Neg
913.4802
[M+HCOO]-
19.8
5000
84.0
56
Diosgenin
Dioscorea quinqueloba
C27H42O3
414.3134
Pos
415.3207
[M+H]+
24.3
100
89.8
Reference standards (100 ng each) were used for accurate mass measurements of 56 toxic substances except for the limit of detection (LOD) and recovery rate measurements. Each LOD values was obtained using 5 plots with different concentrations of each substance spiked into blank blood plasma. For recovery rate measurement, 0.1–10 µg/mL in plasma for each substance spiked into ante-extraction and post-extraction matrices was used
Several precursor ions accompany unknown ions with strange mass defects. For example, the m/z of [M + H]+ of strychnine (compounds no. 20) is 335.1754, but 6 ions were observed in the range of 335–337 (336.2 could be the isotopic ion) (supplementary material Fig. S1, no. 20). This is also observed in the spectra of berberine (no. 21), aflatoxin G1 (no. 27), colchicine (no. 32), veratramine (no. 33), jervine (no. 34), aflatoxin B1 (no. 37), cyclopamine (no. 39), and Aconitum alkaloids (nos. 9, 23, 26, 29, 38, and 40–42). Unfortunately, the sources of the ions are still unknown. In future, it is necessary to analyze the assignment of these ions.
With respect to the chromatographic separation, water/methanol both containing 10 mM ammonium formate was used. The used conditions provided RTs ranging from 1.9 min to 24.3 min (Table 1). Although some hydrophilic substances like ibotenic acid, musimol, and muscarine eluted quickly, it had no problems to detect them by high-resolution MS analysis.

Analysis of spiked samples

The present library was applied for the identification of lycorine and domoic acid spiked into blank blood plasma. Figure 3 shows the results processed using the automatic extracted ion chromatograms (XICs) and spectra by TOF-MS and TOF-MS/MS. In the XICs on the left panels of Fig. 3a and b, the peaks corresponded to the target analytes. In the TOF-MS spectra on the middle panels, the measured masses were at m/z 288.1233 for lycorine and 312.1443 for domoic acid, which matched the theoretical masses with errors of 0.9 and 0.5 ppm, respectively. In the TOF-MS/MS spectra on the right panels, the masses of the fragment ions agreed very well with those of the registered MS/MS spectra. The purity scores were 79.1 and 67.2%, respectively.

Application to forensic autopsy samples

Femoral vein and right and left heart blood samples collected from a 45-year-old male at the forensic autopsy performed in our laboratory were analyzed using the present library. In all samples, aconitine, jesaconitine, hypaconitine, and mesaconitine were identified, and Fig. 4 shows representative results from the femoral vein sample. In the previous study, Niitsu et al. [22] reported the four poisons as major substances detected from blood in the cases of suicide by aconite poisoning. In the TOF-MS spectra, the measured masses matched the registered masses with mass errors of 0.5–1.0 ppm. In the TOF-MS/MS spectra, the masses of the fragment ions agree very well with the registered MS/MS spectra. The purity score was 54.6–60.3%.

Discussion

In this article, we have created a forensic toxicological library including 56 natural toxic substances. The drugs of abuse originated from plants, such as Δ9-tetrahydrocannabinol and cocaine have been excluded. To our knowledge, only one trial to construct libraries specific to natural toxic substances has been published [6]; but they used low-resolution LC–MS/MS instrument unable to make estimation of the molecular formulae, using its accurate mass numbers, which are very useful for tentative identification of an unknown substances. Recently, Wang et al. [23] reported high-throughput screening of more than 200 toxic substances including narcotic drugs, psychotropic drugs, pesticides, natural toxins, and other drugs; however, in their collection, only 3 substances were in common with those in our article. Moreover, they did not use a high-resolution MS instrument, but a low-resolution linear ion trap quadrupole MS coupled with a homemade extractive electrospray ionization. Broecker et al. [12] reported an article on development and application of a library for CID accurate mass spectra of more than 2500 toxic compounds by LC–QTOF-MS/MS. However, the readers cannot get access to the MS/MS spectra only with their paper. In the present article, the readers can readily gain access to the detailed high-resolution MS/MS spectra of 56 natural toxic substances located in the electronic supplementary material.
Martin et al. [24] compared the performance of three types of LC–QTOF-MS/MS platforms created by three different manufacturers including the Sciex Triple TOF 5600 system used in the present study. There are usually three parameters for compound identification by LC–QTOF-MS/MS: mass errors not greater than 4 or 5 ppm, RT differences with 0.2–0.5 min, and similarities of MS/MS spectrum profiles. The former two parameters were common to the three types of the instruments. For the similarity of the MS/MS profiles, one manufacturer did not incorporate such a parameter as of 2014. Another manufacturer provided MS/MS libraries at three collision energies for matching. The system of our instrument takes into consideration the presence/absence of all MS/MS spectral peaks and their relative abundance, which are compared to those of the MS/MS library record, calculating the purity score. In addition, the system also includes the CES mode, in which the CE ramp range is set to 35 ± 15 eV, in which a small parent peak and important small product ions are magnified automatically. Therefore, we presented three MS/MS spectra at CEs of 20, 35, and 50 eV, and one spectrum in the CES mode (Fig. 2, Fig. S1). Such algorithms adopted by Sciex for comparison of MS/MS spectrum profiles seem most sophisticated and thus reliable in current LC–QTOF-MS arena. Although some previous studies described identification of target compounds using the purity scores, their distinct criteria have not been established [16, 2527]. According to our results on the spiked and forensic autopsies (Figs. 3, 4), the purity scores more than 50% seems to be acceptable prior to considering the matches of a mass error and RT.
When the present library of natural toxic substances by LC–QTOF-MS were created, low-resolution MS/MS spectra of 54 natural toxic substances were also recorded, except for picrotoxinin and diosgenin (unpublished observation). The low-resolution MS/MS spectra at CEs of 20, 35, and 50 eV, and one spectrum in the CES mode were acquired; the low-resolution MS/MS spectra were similar to the high-resolution MS/MS spectra in this study. Therefore, the detailed high-resolution MS/MS spectra of natural toxic substances located in the electronic supplementary material in the present article (Fig. 2, Fig. S1) seems to be also useful in routine forensic toxicological screening by low-resolution LC–MS/MS.

Conclusions

We have developed a forensic toxicological library for identification of 56 natural toxic substances by LC–QTOF-MS/MS. The applicability of the library was exemplified by identifying four plant toxins in blood samples collected from an autopsy. This library may be effective for the screening of natural toxic substances and can become a powerful tool for searching natural toxic substances in routine forensic toxicological analysis. To our knowledge, this is the first trial to develop a toxicological library for natural toxic substances using high-resolution LC–MS/MS.

Acknowledgements

This work was supported by JSPS KAKENHI (Grant no. 18H03064).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

The analysis of blood samples from deceased subjects was requested by the judicial authorities.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://​creativecommons.​org/​licenses/​by/​4.​0/​), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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Electronic supplementary material

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Literatur
4.
Zurück zum Zitat Drummer OH (2018) Toxicology: overview and applications. In: Houch MM (ed) Forensic Toxicology. Academic press, London, pp 25–31 Drummer OH (2018) Toxicology: overview and applications. In: Houch MM (ed) Forensic Toxicology. Academic press, London, pp 25–31
25.
Metadaten
Titel
Development and application of a forensic toxicological library for identification of 56 natural toxic substances by liquid chromatography–quadrupole time-of-flight mass spectrometry
verfasst von
Tadashi Ogawa
Kei Zaitsu
Tetsuo Kokaji
Kayako Suga
Fumio Kondo
Masae Iwai
Takayoshi Suzuki
Akira Ishii
Hiroshi Seno
Publikationsdatum
17.11.2019
Verlag
Springer Singapore
Erschienen in
Forensic Toxicology
Print ISSN: 1860-8965
Elektronische ISSN: 1860-8973
DOI
https://doi.org/10.1007/s11419-019-00506-w

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