Strategy for Comprehensive Identification of Acylcarnitines Based on

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A Novel Strategy for Comprehensive Identification of Acylcarnitines Based on Liquid Chromatography-High Resolution Mass Spectrometry Di Yu, Lina Zhou, Qiuhui Xuan, Lichao Wang, Xinjie Zhao, Xin Lu, and Guowang Xu Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.7b05471 • Publication Date (Web): 13 Apr 2018 Downloaded from http://pubs.acs.org on April 13, 2018

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Analytical Chemistry

A Novel Strategy for Comprehensive Identification of Acylcarnitines Based on Liquid Chromatography-High Resolution Mass Spectrometry

Di Yu,1,2,# Lina Zhou,1,# Qiuhui Xuan,1,2 Lichao Wang,1,2 Xinjie Zhao,1 Xin Lu,1 Guowang Xu1*

1. CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China. 2. University of Chinese Academy of Sciences, Beijing 100049, China.

#:

: equal contribution

* Correspondence: Prof. Dr. Guowang Xu, e-mail: [email protected], Tel: 0086-411-84379530, Fax: 0086-411-84379559

1

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

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ABSTRACT: Carnitines play important roles in fatty acid oxidation and branched chain amino acid metabolism. The disturbance of acylcarnitines is associated with occurrence and development of many diseases. Comprehensive acylcarnitine identification can greatly benefit their targeted detection, following disease differential diagnosis and possible mechanism study. In this study, we developed a novel strategy to identify as many acylcarnitines as possible based on liquid chromatography-high resolution mass spectrometry (LC-HRMS). The layer-layer progressive strategy firstly integrated the initial full scan MS/ data-dependent MS/MS monitoring (ddMS2) acquisition and the following parallel reaction monitoring (PRM) to analyze a pooled biological sample. And

733

possible

acylcarnitines

were

identified

containing

characteristic

high-resolution MS/MS features. Further, accurate mass, retention rules, and HRMS/MS information were used to define subclasses and predict undetected acylcarnitine homologues in each subclass, leading to more acylcarnitines to our newly constructed database. As a result, 758 acylcarnitines were contained in the database, having exact mass, retention time, and MS/MS information, which is the most comprehensive list of acylcarnitines reported to date. Applying this database, 241, 515, and 222 acylcarnitines were rapidly and reliably annotated in human plasma, human urine and rat liver tissue. This novel strategy enables large-scale identification of acylcarnitines, and similar method can also be used to identification of other metabolites.

2


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ABBREVIATION LC-HRMS: liquid chromatography-high resolution mass spectrometry ddMS2: data-dependent MS/MS monitoring IDA: information-dependent acquisition SRM: selected reaction monitoring MRM: multiple reaction monitoring PRM: parallel reaction monitoring tR: retention time EIC: extracted ion chromatogram ClogP: calculated oil-water partition coefficient

3



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INTRODUCTION Carnitine plays important roles in fatty acid oxidation and branched chain amino acid metabolism.1,2 It can facilitate fatty acids to shuttle the mitochondrial membrane by combining with fatty acids to form acylcarnitines.3 Acylcarnitines have been found to be associated with the occurrence and development of many diseases, such as inborn errors of metabolism, diabetes, atherosclerosis, and so on.4-10 The different acylcarnitine profiles are either shown in several molecules, or in homologues. Comprehensive short-, medium- and long-chain acylcarnitine profiles, especially annotation of unknown and diverse acylcarnitines can greatly benefit different disease diagnosis and further mechanism investigation. At present, liquid chromatography-mass spectrometry (LC-MS) is the most common approach for acylcarnitine analysis because of its high sensitivity and ability for simultaneous separation of isomeric compounds in a relatively short time.11,12 To increase the detection coverage of acylcarnitines, many efforts have been devoted to improve the ability for separation and enhance sensitivity and selectivity, such as two-dimensional chromatography and specific derivatization.13-16 Moreover, different MS monitoring modes were performed, such as parent and neutral loss monitoring,17,18 data-dependent monitoring.19 These methods have achieved some progresses, but the number of acylcarnitines detected was limited to several tens in most of analyses. Recently, by integrating solid phase extraction for sample preparation with 1 mm inner diameter column based LC separation and information-dependent acquisition (IDA) and selected reaction monitoring (SRM) modes for MS data acquisition, Li et al. identified 355 acylcarnitines from urine samples.15 The SRM mode contributed much to this excellent study. SRM and multiple reaction monitoring (MRM) were 4


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more frequently used compared with other MS monitoring modes.12,20 In the latest studies, parallel reaction monitoring (PRM) was applied for acylcarnitine detection, and 117 acylcarnitines were found from plasma and urine samples.21 Due to the resulted high resolution MS/MS information, PRM can provide more confident identification for metabolites, and it has emerged as a potential alternative to MRM.22 Still the unknown number of acylcarnitines in the biological samples is a limit for the evaluation of existing excellent methods. Also, the diversity of acylcarnitines in biological samples is of interest for researchers in different fields. In this work, we proposed a novel strategy designed for comprehensive acylcarnitine annotation, mainly by firstly obtaining rich high-resolution LC-MS, MS/MS spectra, then conducting identification based on carnitine feature fragments. Further, we considered the acylcarnitines into subclass homologues to realize fine structure elucidation and homologue predictions. All of the MS, MS/MS and retention time information were stored in an acylcarnitine database, which would aid rapid acylcarnitine identification in biological samples for routine analysis.

EXPERIMENTAL SECTION Materials and Reagents. HPLC grade acetonitrile (ACN) and HPLC grade methanol (MeOH) were purchased from Merck (Darmstadt, Germany). Formic acid (FA) was purchased from J&K Scientific Ltd. (Beijing, China). Ultrapure water (H2O) was from a Milli-Q system (Millipore, Billerica, MA, U.S.A.). Fourteen acylcarnitine standards used to develop the method were carnitine (C0), acetylcarnitine

(C2),

propionylcarnitine

(C3),

isobutyrylcarnitine

(isoC4),

butyrylcarnitine (C4), 2-methylbutyrylcarnitine (2-methyl-C4), isovalerylcarnitine (isoC5), hexanoylcarnitine (C6), octanoylcarnitine (C8), decanoylcarnitine (C10), 5



lauroylvarnitine

(C12),

myristoylcarnitine

(C14),

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palmitoylcarnitine

(C16),

stearoylcarnitine (C18). These acylcarnitines standards were purchased from Sigma-Aldrich (St. Louis, MO, U.S.A.). Nine deuterated internal standards were used for retention time calibration. Acetyl-d3-carnitine (C2:0-d3), decanoyl-d3-carnitine (C10:0-d3), and hexadecanoyl-d3-carnitine (C16:0-d3) were purchased from C/D/N Isotopes

Inc.

(Quebec,

PQ,

Canada).

3-hydroxyisovaleroyl-d3-carnitine

(isoC5-OH-d3) and 3-hydroxy-9-hexadecenoyl-d3-carnitine (C16:1-OH-d3) were purchased from TRC

(Toronto, ON, Canada). Butyrylcarnitine (C4:0-d3),

hexanoylcarnitine (C6:0-d3), octanoylcarnitine (C8:0-d3), and lauroylvarnitine (C12:0-d3) were purchased from Sigma-Aldrich (St. Louis, MO, U.S.A.).

Sample Preparation. To prepare stock solutions, the acylcarnitine standards were dissolved in the mixture of MeOH and H2O with different ratios, then diluted to proper concentrations by 25% ACN (ACN/H2O (v/v) = 25/75), and stored at -20 ℃ until analysis. Three types of biological samples used were pooled plasma (from 36 healthy adults), pooled urine (from 24 healthy adults) and tissue (from a healthy rat liver). For plasma or urine sample, four times volume of cold ACN with proper concentrations of deuterated internal standards (IS) was added to 100 µL sample for protein precipitation and metabolite extraction. A 450 µL aliquot of the supernatant was transferred into a 1.5 mL Eppendorf tube after vortex and centrifugation (14000 g, 15 min, 4 ℃), then freeze-dried. For the tissue sample, the zirconia bead and 1 mL of 80% MeOH with proper concentrations of deuterated internal standards were successively added to 10 mg of rat tissue sample. Homogenization and metabolite extraction were simultaneously 6


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preformed in a mixed grinding apparatus (MM400, Retsch, Germany) under the condition of 25 Hz for 1 min (twice), then treated in the same way as the process for plasma and urine samples All freeze-dried samples were stored in -80 ℃ until analysis. Before injection, each sample was reconstituted with 50 µL of 25% ACN, then vortexed for 30 s, and centrifugated (14000 g, 15 min, 4 °C). The supernatant was transferred into a sample vial for LC-MS analysis. At the same time, the pooled sample was prepared by mixing equal volume supernatant of plasma, urine and tissue.

LC Separation. The LC separation was performed on a ACQUITY Ultra Performance LC (Waters, Milford, MA, U.S.A.). Through literature investigation and experimental comparison, it was found that a reversed-phase BEH C18 column (2.1 mm × 50mm, 1.7 µm, Waters, Milford, MA, U.S.A.) is more suitable for separation of acylcarnitines. The LC conditions were defined to have a good resolution of the acylcarnitines in the whole analysis. A 5 µL sample aliquot was injected with the column temperature set at 40 ℃ and the flow rate set at 0.35 ml/min. Two mobile phases were used for elution, including H2O with 0.1% FA as phase A and ACN as phase B. The elution gradient started with 10% phase B, was held for 0.5 min, then increased to 15% phase B at 3 min, and then to 30% phase B at 5 min, and to 97% phase B at 21 min, and held for 2 min. At last, the gradient was back to 10% B at 23.5 min and held for 1.5 min to stabilize the system. The sample manager temperature was set as 4 ℃.

Two-Step Progressive MS Data Acquisition. The MS data acquisition was performed by Q Exactive HF (Thermo Fisher Scientific, Rockford, IL, U.S.A.) 7



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system. In full scan MS/ddMS2 mode, the resolutions of full scan MS and ddMS2 were set at 60000 and 15000, respectively. The automatic gain control (AGC) target and maximum injection time in full scan MS settings were 1 × 106 and 200 ms, while their values were 1× 105 and 50 ms in ddMS2 settings. The TopN (N, the number of topmost abundant ions for fragmentation) was set to 10, and collision energy was set to 15%, 30% and 45%. A heated ESI source was used at positive ion mode. The spray voltage was set as 3.5 kV. The capillary temperature and aux gas heater temperature were set as 300 ℃ and 350 ℃, respectively. Sheath gas and aux gas flow rate were set at 45 and 10 (in arbitrary units), respectively. The S-lens RF level was 50. For PRM mode, the isolation width of the precursor ion was set at 0.4 m/z. Other parameters were the same as ddMS2 settings.

Data Processing. Following LC-MS analysis, raw data were collected and processed on Thermo Xcalibur Processing Setup-Quan-Identification software. The peaks of MS and MS/MS were extracted at a mass tolerance of 5 ppm and 10 ppm, respectively. TraceFinder software (version 3.2, Thermo Fisher Scientific, Rockford, IL, U.S.A.) was used for peak extraction.

RESULTS AND DISSCUSSION In this study, we proposed a novel strategy to enable comprehensive acylcarnitine identification. The strategy consists of four parts: (1) To obtain rich sample sourced acylcarnitines, a pooled biological sample was firstly prepared by mixing extracts from human urine, human plasma and rat liver tissue. (2) Two-step MS data acquisitions were performed to explore possibly existing acylcarnitines, including the 8


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first LC-full scan MS/ ddMS2 acquisition and the following multi-run LC-full scan MS combined with PRM acquisition. If the precursors obtained in the first-step acquisition possess characteristic MS/MS fragments and neutral loss (their detected m/z should be within the allowed tolerance), they were stored as precursors and classified according to molecular formula. The precursor list was further extended according to literature investigation and online databases. (3) Subclass homologue grouping with following unknown acylcarnitine prediction was performed further in each class. The rules for grouping of acylcarnitines in each subclass were the possibly existing linear relationships between oil-water partition coefficient (logP) and retention time of acylcarnitines and the carbon number rule. (4) The defined information of detected and predicted acylcarnitines, including m/z, tR and MS/MS fragments, was stored in a newly built acylcarnitine database for the identification of samples in routine LC-MS analysis. The workflow is shown in Figure 1.

Establishment of the High-resolution Targeted MS Method. To comprehensively identify acylcarnitines in biological samples and to elucidate the diversity of acylcarnitines, a pooled biological sample was prepared and employed. The pooled sample contains the acylcarnitine information from common human plasma, human urine and rat tissue. Then layer-layer progressive MS data acquisitions, especially for MS/MS spectra were performed by coupling LC-HRMS in full scan MS/ddMS2 mode and PRM mode. Under our MS conditions, by studying the standards we found acylcarnitines have characteristic product ions m/z 60.0808, 85.0284 and 144.1014, and the neutral loss of 59.0735 Da, which is consistent with previous studies23-25. Therefore, these fragment features were used to search acylcarnitines. After MS/MS fragment extraction, 104 9



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acylcarnitines precursor ions (Table S1) were found and divided into 17 classes according to the formula. Based on the literatures15,26 and HMDB database, three missed classes were added, therefore, totally, 20 classes of acylcarnitines are included (Table 1). For each possible homologue member in twenty classes of acylcarnitines, the exact mass was calculated, then used to extract MS peak in full scan MS mode. As a result, 298 precursor ions were extracted. In full scan MS/ddMS2 mode, only top-ten peaks in every cycle can obtain MS/MS information. Thus, some low-concentration acylcarnitines were detected in MS, but having no MS/MS spectra. After this step, they were added to the precursor ion list waiting for MS/MS information. The time window for each of precursor ion was scheduled according to the retention time information of full scan MS mode. To obtain high-resolution MS/MS spectra of all potential acylcarnitines, efforts were devoted to establishing and optimizing acquisition in PRM mode. In PRM assay, multiple precursor ions are isolated and fragmented, and the related product ions as well as precursor ions are detected in the high-resolution Orbitrap mass analyzer.27,28 Compared with SRM providing precursor-product ion pair in unit resolution, PRM could provide high-resolution MS/MS spectra, but is limited by scanning speed. Consequently, it was difficult to fulfill the need for the simultaneous MS/MS spectra acquisition for all potential acylcarnitines in a single run. Take acylcarnitines with m/z 358.2588 as an example (Figure S1), their MS/MS spectra could not get chromatography peak shapes in the single-run PRM mode when covering all the potential acylcarnitines, though their peak shapes in MS spectra were not affected. Multi-run PRM mode was considered, and about thirty precursor ions were found appropriate for one run. The extracted peak shapes of MS/MS fragments had good 10


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matches to the peak shapes of their precursors in the MS spectra (Figure S1). Moreover, precursor ions belonging to the same class (Table S2) were targeted in the same run. It would be convenient for following studies and would avoid the elution time of targeted precursor ions focusing on a certain period. Finally, 298 precursor ions were divided into ten runs according to the classes. Ten LC-HRMS methods were established and used to analyze the pooled biological sample.

Identification of Acylcarnitines in each class. Analysis of these 298 precursor ions in the pooled biological sample with ten above runs produced sufficient information (exact mass, tR and high-resolution MS/MS spectra) for further identification of acylcarnitines. The metabolites identified as acylcarnitines should fulfill the following conditions. First, the mass tolerance of precursor ion is within 5 ppm. Second, more than three fragment features (excluding the parent ions) are detected at a mass tolerance of 10 ppm, and retention behavior of these fragment ions should match with the precursor ion. Moreover, the existence of characteristic product ion of m/z 85.0284 is necessary. Because it is the most stable fragment for acylcarnitines, whose abundance increases with the collision energy. Here we took the precursor ion at m/z 355.2588 as an example, which was targeted for high-resolution MS/MS spectra in the sixth run in ten above runs of the PRM mode. The process of identification is shown in Figure 2A. Thirteen metabolites (peak 1 to peak 13) can fulfill above conditions, then be identified as acylcarnitines. Due to the lack of necessary product ion (m/z 85.0284), a metabolite (between peak 8 and peak 9) was excluded, it is not an acylcarnitine. 11



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Owe to high-resolution MS/MS information produced by PRM mode, further structure confirmation for these thirteen identified acylcarnitines can be performed. The related extracted ion chromatograms (EICs), MS/MS spectra and proposed fragmentation patterns are shown in Figure 2. The acylcarnitine at m/z 358.2588 corresponds to hydroxy-dodecenoylcarnitine (C12:1-OH)

or

carbonyl-lauroylcarnitine

(C12+=O).

The

hydroxy-dodecenoylcarnitine can be distinguished from the carbonyl-lauroylcarnitine with the loss of 179.1158 Da (m/z 179.1430), which corresponds to the consecutive loss of carnitine backbone and H2O. The metabolite (peak 13) was identified as carbonyl-lauroylcarnitine, while metabolites (peak 1 to 12) were identified as hydroxy-dodecenoylcarnitines beasuse of the presence of product ion at m/z 179.1430 (third grey line in Figure 2A) . Additionally, we can distinguish 3-hydroxy-dodecenoylcarnitines from other isomers (the hydroxyl group in a different position along the acyl chain) by the product ion of m/z 145.0495, which corresponds to γ-hydrogen rearrangement of m/z 299.1853.29

Therefore,

the

3-hydroxy-dodecenoylcarnitines,

peaks

9

while

,11 the

and

12

were

identified

as

peak

13

was

identified

as

3-carbonyl-lauroylcarnitine based on keto-enol tautomerization (fourth green line in Figure 2A). Moreover, we found a product ion (m/z 155.1430) with high intensity, which is the loss of 203.1158 Da corresponding to the consecutive loss of carnitine backbone and CH2CO (fifth yellow line in Figure 2A). The product ion of m/z 155.1430 demonstrated the presence of 3-hydroxy or 3-carbonyl group along the acyl chain. The MS/MS spectra and structure elucidation of peak 12 (C12:1-OH) and peak 13 (C12+=O) are shown in Figure 2B to 2E. In the previous study15, nine acylcarnitines at m/z 358 were found in urine 12


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samples, which were detected in IDA combined with SRM mode, and provided low-resolution MS/MS spectra and uncertain structure. In our study, one precursor ion at m/z 358.3588 corresponds to thirteen acylcarnitines with high-resolution MS/MS spectra, which greatly contributed to not only detection coverage but also structure confirmation. These thirteen acylcarnitines can be divided into different subclasses (hydroxy- or carbonyl-) based on structure information. But also, the pooled biological sample contributed to rich acylcarnitines, and the application of two-step MS data acquisition enhanced the sensitivity and accuracy. After analysis of 298 precursor ions in full scan MS combined with ten above runs of the PRM mode, the amount of identified acylcarnitines (Table S3) is 733, nearly doubles the detected acylcarnitine species in the most comprehensive study to date.15 The number of identified acylcarnitines in each of twenty classes is shown in Table 1.

Subclass Homologue Grouping and Prediction. 733 acylcarnitines have been divided into 20 main classes, some subclasses contain more specific groups after the above MS/MS study. In this section, we further divided these identified acylcarnitines into homologue levels. Homologue members have similar and regular MS/MS spectra. Homologue grouping can be achieved by combining MS/MS spectra and the structure-retention relationship. The former have been obtained in the above study. For the latter, in the linear gradient range of our LC conditions, there should be a linear equation between the detected tR and the carbon numbers (Cn) of the acyl chain for each homologue series (carbon number rule). Our challenge was to define the measured retention time of an acylcarnitine with the specific Cn when its chemical standard is not available. To solve this problem the relationship between calculated oil-water partition 13



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coefficient (ClogP) of carnitines and retention times was investigated. Firstly, a mixture consisting of twenty-three acylcarnitine standards was analyzed using LC-HRMS. We found that tR has a linear correlation with the ClogP within the linear gradient (5~21 min), which was expressed by following Equation (1), tR=1.5587 ClogP +7.9611

(1)

The details are shown in Figure S2. When one CH2 group is increased in the homologue series the value of ClogP increases 0.529, we can know from Eq. (1) that tR will increase 0.82 min. This value can be used to define the candidate(s) of a homologue member. Further, detailed MS/MS spectra were carefully checked to confirm whether it really is a homologue member. Taking the tenth class (Cn:1-OH and Cn+=O) in Table 1 as an example to detail the homologue grouping process. According to the above conditions, three series of homologues

were

found

and

represented

by

blue

solid

circle

(4-hydroxyl-acylcarnitines), orange solid circle (3-hydroxyl-acylcarnitines) and green solid tringle (3-carbonyl-acylcarnitines) in Figure 3. Firstly, homologues should have common and/or regular MS/MS fragments (Figure S3). The MS/MS spectra of acylcarnitines labeled by blue solid circle showed the similar fragments characterized by [M-carnitine-H2O] (Figure S3a1 and S3b1). These acylcarnitines were defined as hydroxyl-acylcarnitines, but the position of hydroxy was unknown. Then, theoretical tR ranges of acylcarnitines with hydroxy at different positions were calculated using Eq. (1), and we found that only 4-hydroxyl-acylcarnitines can match the measured tR (Table S4). Thus, the acylcarnitines labeled by blue solid circle were defined as 4-ydroxyl-acylcarnitines. The MS/MS spectra of acylcarnitines labeled by orange solid circle showed the common fragment of m/z 145.0495 (due to loss of N(CH3)3 group and γ-hydrogen rearrangement), and similar fragment characterized by 14


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[M-carnitine-H2O] (Figure S3a2 and S3b3). Of note, an acylcarnitine marked by orange solid circle (C16) was defined as 3-hydroxy-9-hexadecenoylcarnitines with verification using its isotope standard. Then, the fine sub-structures for the specific homologue group were defined as 3-hydroxy-acylcarnitines (with a carbon-carbon double bond in ninth position along the acyl chain). Using only one standard, we defined a series of acylcarnitines’ structures. Moreover, the three linear relationships of detected homologues (dashed lines in Figure 3) can be used to estimate retention times of undetected homologues (red cross in Figure 3). After the study in this section, we not only found seven new memebers, and further predicted 16 undetected acylcarnitines, but also gave the more definite structures of acylcarnitines. The process is shown in Part C of Figure 1. Finally, 758 acylcarnitines are in our database (Table S3), including 16 predicted acylcarnitines, 733 acylcarnitines found in the pooled biological sample, and 9 isotope acylcarnitine standards.

Validation and application of acylcarnitine database in biological samples. To assess the prediction accuracy of acylcarnitines database, the mixture of twenty-three acylcarnitine standards was analyzed using LC-full scan MS/ddMS2 mode in a single run. The untargeted MS/MS method (ddMS2) was performed with the included list of the top-priority acylcarnitine precursor ions without time-scheduling. To make use of retention time data in the database, nine deuterated carnitines as internal standards were added into the samples to calibrate the change of retention times due to different instruments, buffer minor difference and other factors. The retention times (tR_dabatase, Table S3) of all identified acylcarnitines in sub-database 15



Page 16 of 27

were adjusted to the running conditions (tR_corrected) by using a similar method as suggested by the literature

30

, the detail calibration process was described in Figure

S4. The tR_corrected was used for extracting and identifying peaks. After extracting peaks using the adjusted acylcarnitines list, 24 peaks matched with ∆ m/z of 5 ppm and ∆ tR of 10 s, they included all 23 acylcarnitine standards and 1 false positive compound. We further found that the false positive compound (m/z 472.3421) was derived from the isotope peak of the unknown compound (m/z 471.3396) which also appeared in blank sample. These chromatographic behaviors and peak intensities are shown in Figure S5. Further, we analyzed the extracts of a pooled plasma (from 36 healthy adults), a pooled urine (from 24 healthy adults) and a tissue (from a healthy rat liver) using the LC-full scan MS/ddMS2 mode. After extracting peaks, 241, 515, and 222 acylcarnitines were repeatedly obtained in human plasma, human urine and rat liver tissue, respectively. There are 45, 326 and 37 identified acylcarnitines existing only in human plasma, human urine and rat liver tissue, respectively. At the same time, we counted the acylcarnitines with different lengths of acyl chain. Compared with plasma sample and rat liver tissue sample, the urine sample had more abundant short-chain and medium-chain acylcarnitines, and less long-chain acylcarnitines, consistent with its stronger polarity. The results are shown in Figure 4, while EICs of acylcarnitines in three kinds of biological samples are shown in Figure S6. This derived large number of acylcarnitines illustrates the great diversity of the metabolites and the usefulness of the proposed strategy for large-scale identifications. In the AbsoluteIDQ® p400 HR Kit newly developed in 2017 for the broad lipid and metabolic profiling only 55 acylcarnitines are included in the list of 408 endogenous metabolites 16


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(http://www.biocrates.com/products/research-products/absoluteidq-p400-hr-kit). The information for 758 acylcarnitines in the database not only has a great value for unknown acylcarnitine identification in real biological samples, but can also aid the comprehensive quantification method development for acylcarnitines.

CONCLUSIONS In this work, layer-layer progressive MS/MS spectra acquisitions were performed, initial full scan MS/ddMS2 and the following multi-run PRM mode contributing together to the sufficient MS structure information, especially high-resolution MS/MS. Further integrating with homologue grouping and prediction in subclass level, we got the m/z, MS/MS fragments and tR information of 758 acylcarnitines, which are the most abundant acylcarnitine information to date. This deep investigation of acylcarnitine diversity reflects the limit of the existing methods for acylcarnitines and can act as a criterion for new quantification method developments and evaluations. In the meantime, the database can be used for rapid and reliable annotation of acylcarnitine in new biological samples during routine LC-MS analysis. The fine structures of acylcarnitines in database can be further annotated in the future by updating sample preparation method to provide richer sample-derived acylcarnitine information and using high-resolution LC method to isolate isomers, synthetizing more kinds of acylcarnitine standards to aid the fine homologue discriminations. In addition, in view of the great diversity of the metabolites, this large-scale identification strategy is of great reference value to the future identification of other metabolite groups, for example, fatty acids, acyl-CoAs etc.

ASSOCIATED CONTENT 17



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Supporting Information Figures and tables include a comparison of sing-run PRM mode and multi-run PRM mode, a schematic of the retention time calibration method, the false positive compound in the mixture of standards, list of precursor ions found using IDA model, list of multi-run PRM method, summary of 758 acylcarnitines, the process of grouping homologues and extract ion chromatograms of acylcarnitines in the human plasma, human urine and a rat tissue.

ACKNOWLEDGMENTS This research was supported by the foundations (81472374, 21575142 and 21505132) and key foundation (21435006) from the National Natural Science Foundation of China and the National Key Research and Development Program of China (2017YFC0906900).

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Page 22 of 27

Table 1. Summary of twenty classes of acylcarnitines detected in pooled biological samples and found in literatures15,26 Class

Proposed acyl chain

Formula

structure

Number of identified acylcarnitines

1

Cn+7 H2n+13 O4 N

Cn:0

88

2

Cn+7 H2n+11 O4 N

Cn:1

86

3

Cn+7 H2n+9 O4 N

Cn:2

71

4

Cn+7 H2n+7 O4 N

Cn:3

40

5

Cn+7 H2n+5 O4 N

Cn:4

37

6

Cn+7 H2n+3 O4 N

Cn:5

13

7HMDB

Cn+7 H2n+1 O4 N

Cn:6

2

8

Cn+7 H2n+13 O5 N

Cn-OH

48

9*

Cn+7 H2n+13 O6 N

Cn-2OH

8

10

Cn+7 H2n+11 O5 N

Cn:1-OH

75

11

Cn+7 H2n+9 O5 N

Cn:2-OH

63

12

Cn+7 H2n+7 O5 N

Cn:3-OH

35

13

Cn+7 H2n+5 O5 N

Cn:4-OH

26

14

Cn+7 H2n+11 O6 N

Cn:DC

40

15

Cn+7 H2n+9 O6 N

Cn:1:DC

35

16

Cn+7 H2n+7 O6 N

Cn:2:DC

24

17

Cn+7 H2n+5 O6 N

Cn:3:DC

18

18

Cn+7 H2n+3 O6 N

Cn:4:DC

4

19*

Cn+7 H2n+11 O7 N

Cn:DC+OH

7

20

Cn+7 H2n+9 O7 N

Cn:1:DC+OH

13

Total HMDB

733 34

: added according to HMDB information ; *: added by the literature15;

+OH : corresponding to a hydroxyl group; :DC : corresponding to a dicarboxylic acid; The letter “n” following “C” : corresponding to the number of carbon atoms in the fatty acid chain conjugated to carnitine; The colon “ : ” followed by a number : corresponding to the degrees of unsaturation along the fatty acid chain.

22


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Figures

Figure 1. A new strategy for Identification of Acylcarnitines. * The characteristic product ions and neutral loss for acylcarnitines

23



Page 24 of 27

Figure 2. Identification for acylcarnitines at m/z 358.2588, which were targeted for MS/MS in the sixth run of multi-run PRM mode in Table S2. (A) EIC of m/z 358.2588 in full scan MS mode (black), which was enlarged to highlight peak 1 to peak 10 (top). EIC of m/z 85.0284 (blue), 179.1430 (grey), 145.0495 (yellow), 155.1430 (green) in targeted m/z 358.2588 monitoring mode. (B) MS/MS spectrum of peak 12. (C) MS/MS spectrum of peak 13. (D) Structure elucidation of peak 12, 3-hydroxy-dodecenoylcarnitine.

(E)

Structure

elucidation

of

peak

13,

3-carbonyl-lauroylcarnitine.

24


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Figure 3. Identified and predicted acylcarnitines in the 10th class of Table 1. Green triangle,

blue

circle

and

orange

circle

represent

carbonyl-carnitines,

hydroxy-acylcarnitines (with a carbon-carbon double bond along the acyl chain) and 3-hydroxy-acylcarnitines (with a carbon-carbon double bond along the acyl chain), respectively. The acylcarnitines were marked with the same solid mark, which had regular MS/MS fragments, and could be regarded as homologous. Red cross represents the predicted acylcarnitines. The MS/MS spectra of acylcarnitines labeled by a1~a3 and b1~b3 were shown in Figure S3.

25



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Figure 4. Venn diagram of detected acylcarnitine numbers in different biological samples.

26


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For TOC only

27


Strategy for Comprehensive Identification of Acylcarnitines Based on

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