Fe3O4-assisted laser desorption ionization mass spectrometry for typical metabolite analysis and localization: Influencing factors, mechanisms, and environmental applications

Journal Pre-proof Fe3 O4 -assisted laser desorption ionization mass spectrometry for typical metabolite analysis and localization: influencing factors, mechanisms, and environmental applications Wen-Wen Wei (Writing - original draft) (Formal analysis) (Investigation) (Methodology), Yuanhong ZhongWriting - Original draft) (Funding acquisition) (Formal analysis) (Conceptualization) (Methodology), Ting Zou (Formal analysis) (Investigation), Xiao-Fan Chen (Formal analysis) (Investigation), Li Ren (Formal analysis) (Investigation), Zenghua Qi (Resources) (Project administration), Guoguang Liu (Resources) (Supervision), Zhi-Feng Chen (Writing - review and editing) (Funding acquisition) (Conceptualization) (Methodology) (Resources) (Formal analysis) (Project administration), Zongwei Cai (Conceptualization) (Resources) (Funding acquisition) (Supervision)

PII:

S0304-3894(19)31771-6

DOI:

https://doi.org/10.1016/j.jhazmat.2019.121817

Reference:

HAZMAT 121817

To appear in:

Journal of Hazardous Materials

Received Date:

10 October 2019

Revised Date:

19 November 2019

Accepted Date:

2 December 2019

Please cite this article as: Wei W-Wen, Zhong Y, Zou T, Chen X-Fan, Ren L, Qi Z, Liu G, Chen Z-Feng, Cai Z, Fe3 O4 -assisted laser desorption ionization mass spectrometry for typical metabolite analysis and localization: influencing factors, mechanisms, and environmental applications, Journal of Hazardous Materials (2019), doi: https://doi.org/10.1016/j.jhazmat.2019.121817

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Fe3O4-assisted laser desorption ionization mass spectrometry for typical metabolite analysis and localization: influencing factors, mechanisms, and environmental applications

Wen-Wen Weia,†, Yuanhong Zhongb, †, Ting Zoua, Xiao-Fan Chena, Li Renb, Zenghua

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Qia, Guoguang Liua, Zhi-Feng Chena,*, Zongwei Caia,c,**

Guangzhou Key Laboratory of Environmental Catalysis and Pollution Control,

Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control,

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School of Environmental Science and Engineering, Institute of Environmental Health

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and Pollution Control, Guangdong University of Technology, Guangzhou 510006, China

School of Chemical Engineering and Light Industry, Guangdong University of

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c

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Technology, Guangzhou 510006, China

State Key Laboratory of Environmental and Biological Analysis, Department of

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Chemistry, Hong Kong Baptist University, Hong Kong SAR, China

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* Corresponding author at: Guangdong University of Technology, Guangzhou, China. E-mail address: [email protected] (Z.-F. Chen)

** Corresponding author at: Hong Kong Baptist University, Hong Kong SAR, China. E-mail address: [email protected] (Z. Cai) †

These authors contributed equally.

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Graphical abstract

Highlights

Particle size and surface hydroxyl amount affected Fe3O4-LDI-MS

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

performance.

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Thermally driven desorption process played a vital role in LDI performance.



Good intra- or inter-spot repeatability and linearity of analytes were

obtained. 

Endogenous metabolites were identified in biofluids by the developed method.

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Distribution maps of metabolites in zebrafish tissue section were

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generated.

ABSTRACT

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Fe3O4 has been suggested as an efficient matrix for small-molecule analysis by laser

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desorption ionization mass spectrometry (LDI-MS), but thus far there has been no systematic study exploring the influencing factors of nano-Fe3O4 on the detection of

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typical metabolites, or the mechanism by which nano-Fe3O4 assists the desorption and

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ionization of analytes after receiving laser energy. In this study, Fe3O4 nanoparticles with different physicochemical properties were synthesized and characterized. The

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results revealed that smaller particle size and greater surface hydroxyl amount of nano-spherical Fe3O4 could improve the intensity and relative standard deviation of

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typical metabolites by LDI-MS. The thermally driven desorption process played a vital role in LDI performance, but the chemical interactions between nano-Fe3O4 and analytes did not. Good intra- or inter-spot repeatability and linearity of analytes were obtained by the optimum Fe3O4-assisted LDI-MS. Finally, the developed method was successfully used for the rapid analysis and localization of endogenous metabolites in

biofluids and whole zebrafish tissue section samples. Our results not only elucidate the influencing factors and mechanisms of nano-Fe3O4 for the detection of typical metabolites in LDI-MS but also reveal an innovative tool for the imaging of chemicals in the regions of interest in terms of eco-toxicological research.

desorption ionization, time-of-flight mass spectrometry

1. Introduction

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KEYWORDS: Fe3O4, physicochemical property, small-molecule metabolite, laser

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In the 1980s, matrix-assisted laser desorption ionization (MALDI) was proposed as a

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soft ionization technique[1]. The first application of nanoparticles as a matrix for laser desorption ionization coupled with time-of-flight mass spectrometry (LDI-MS) made

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Koichi Tanaka a Nobel laureate[2]. MALDI-MS has been successfully used to detect

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biomacromolecules[3-7], including proteins, peptides, and nucleic acids, in biological samples. The remarkable advantages of MALDI-MS include simple operation, quick

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analysis, high throughput, small sample consumption, and high salt tolerance[8, 9]. Traditional organic matrices that are used in MALDI-MS, such as

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α-cyano-4-hydroxycinnamic acid (CHCA), 2,5-dihydroxybenzoic acid (DHB), and sinapic acid (SA), exhibit good performance in the analysis of biomacromolecules. However, severe background noise in the low-mass range and heterogeneous cocrystallization between traditional organic matrices and small-molecule analytes can limit the practicability of traditional MALDI-MS in vital endogenous metabolite

analysis[10-16]. Endogenous metabolites play an essential role in the growth, development, and reproduction of humans and other organisms[17, 18]. For the accurate quantification of metabolites with molecular weights below 1,000 Da, gas chromatography coupled with mass spectrometry (GC-MS)[19] and liquid chromatography coupled with mass spectrometry (LC-MS)[20] are the commonly used analytical instrument combinations,

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both of which require sample preparation and extra time for chromatographic

separation. In contrast to GC-MS and LC-MS, MALDI-MS not only enables the rapid detection of analytes but also visually displays the distribution of endogenous

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metabolites in tissue sections combined with an imaging technique[21-24]. MALDI-MS

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imaging has shown potential for the elucidation of toxicological mechanisms[25-27]. In the past few years, various types of nanostructured matrices containing silica-

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and silicon-based substrates[28, 29], metal nanoparticles (e.g., gold[30, 31], silver[32], and

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platinum[33]), metal oxides (e.g., TiO2[34], Fe3O4[35, 36], and ZnO[37]), and carbon-based materials (e.g., colloidal graphite[37, 38], graphene oxide[39], and carbon dots[40]) have

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been developed for the surface-assisted analysis of small molecules. Due to superior optical and charge-transfer performance, carbon-based materials[41, 42] have attracted

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an enormous amount of attention. However, low solubility, poor dispersity, and carbon cluster generation hinder the utilization of carbon-based materials in surface-assisted laser desorption ionization (SALDI)[43]. Yagnik et al.[44] conducted a large-scale nanoparticle screening in order to analyze the small molecules in LDI-MS and demonstrated the better performance of Fe3O4-assisted LDI-MS in the positive

ionization mode for sugars, amino acids, phospholipids, and glycerides. Thermally driven desorption was suggested to be a key factor for nano-Fe3O4 when compared to other nanomaterials[44]. In addition to the type of nanomaterial, nano-Fe3O4 particle size can affect the detection sensitivity of metabolites in LDI-MS[45], suggesting that the physicochemical properties of nano-Fe3O4 influence method sensitivity and repeatability.

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In this study, we attempted to use microwave-assisted and coprecipitation

methods for the synthesis of nano-Fe3O4 with different physicochemical properties (e.g., morphologies, particle sizes, and surface hydroxyl amounts). Based on peak

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intensities and relative standard deviations of target analytes, an ideal matrix was

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selected for LDI-MS in positive ionization mode. We compared the performance between as-prepared Fe3O4-assisted LDI-MS and traditional MALDI-MS and

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validated the repeatability and calculation curves of analytes for the developed

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method. From the results of thermal desorption calculation and the UV-visible absorption spectrum, the mechanisms of the desorption and ionization of analytes

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after laser irradiation were tentatively proposed. Finally, the developed method was successfully applied in order to identify and localize the potential metabolites in

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biofluids and whole zebrafish tissue section samples, respectively.

2. Experimentation 2.1 Synthesis and characterization of Fe3O4 nanoparticles Based on our previous work[46], a type of nano-spherical Fe3O4 particle (M2) was

synthesized via the standard coprecipitation method, and 9 types of nano-Fe3O4 particles (M1, M3–M10) with different morphologies, particle sizes, and surface hydroxyl amounts were synthesized using a microwave-assisted technique. M11 was a commercial nano-Fe3O4 particle, while nano-Fe3O4 (M12) was synthesized using a method from Yagnik et al[44]. The XRD patterns of the as-prepared Fe3O4 nanoparticles were obtained by an Aeris benchtop X-ray diffractometer (PANalytical

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B.V., Netherlands) with a tube voltage of 40 kV and a current of 15 mA at room

temperature. The range of angles was set from 10o to 80o (2θ) with a scanning step width of 0.02o and a speed of 5o/min. The morphologies and particle sizes were

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determined from scanning electron microscope images (SEM). SEM measurements

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were performed on a Hitachi SU8000 with 3-kV accelerating voltage and 9,400-nA emission current (Hitachi Ltd., Japan). The surface hydroxyl amount of nano-Fe3O4

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was measured using a SDT Q600 simultaneous TGA-DSC thermal analyzer (TA

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Instruments, USA). The data were recorded from room temperature to 800oC with a heating rate of 10oC/min and a nitrogen flow rate of 50 mL/min. Specific heat

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measurements were conducted in a zero magnetic field with a temperature region of 271‒306 K and a pressure of 9.9×10-6 Torr, using the specific heat option of a

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Quantum Design physical property measurement system (Quantum Design, China). The UV-visible absorption spectrum (200-800 nm) of nano-Fe3O4 was obtained from a MAPADA UV-3200 Spectrophotometer (Shanghai Mapada Instruments Co. Ltd., China). The detailed synthesis approaches (Text S1 and Table S1) and information (Table S2) of the nano-Fe3O4 in this study are provided in Supplementary Material.

2.2 Experimental design Six metabolites with different molecular weights and categories, including DL-serine (SER), D-glucose (GLU), adenosine (ADE), arachidic acid (ARA), ceramide (d18:1/12:0) (CER), and triheptadecanoin (17:0/17:0/17:0) (TG), were chosen as target analytes. In order to compare the performances of different Fe3O4-assisted

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LDI-MS analyses with traditional MALDI-MS, the final concentrations of each

analyte in matrix solution were 50 mg/L. The basic information of these analytes is provided in Table S3. Supplier sources of chemicals and reagents can be found in

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Text S2. The UV-visible absorption spectrum was used to investigate the effects of

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the laser absorption capacity of nano-Fe3O4 on LDI-MS performance and to explore the affinity between matrices and analytes. A modified thermal desorption model[44]

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was utilized to explain the performance of Fe3O4-assisted LDI-MS (Text S3). In order

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to test method repeatability, six standard samples at concentrations of 10 mg/L and 50 mg/L were detected 7 times in the same spot (intra-spot) and at 7 distinct spots

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(inter-spot). In order to test method quantification capacity, the standard calibration curve of each analyte was determined by analyzing the standard solution at a

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concentration range of 10–50 mg/L with 13C-Glucose (GLU 13C) as an internal standard at a concentration of 10 mg/L. For method application, 2 experiments were performed: (1) biofluid samples, including fish serum, bile, and human urine, were detected by the optimum Fe3O4-assisted LDI-MS for the identification of endogenous metabolites; (2) whole zebrafish sagittal tissue sections were analyzed using the

optimum Fe3O4-assisted laser desorption ionization mass spectrometry imaging (LDI-MSI) in order to map the distribution of endogenous metabolites.

2.3 Sample preparation The detailed collection procedures of the biofluid samples, including fish serum, bile, and human urine, as well as the whole zebrafish tissue section samples, can be found

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in Text S4. For LDI-MS analysis, Fe3O4 nanoparticles were suspended in isopropanol at the required concentrations. The SA, DHB, and CHCA saturated solutions (10

mg/mL) were prepared in acetonitrile/water (1:1, v/v) containing 0.1% trifluoroacetic

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acid. Under optimum conditions, the standard solution of each analyte (1 mg/mL) or

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biofluid sample was mixed with the matrix solution (1:1, v/v), after which 1 μL of the mixture was pipetted onto a stainless-steel sample plate, air-dried, and analyzed using

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LDI-MS. For LDI-MSI analysis, the whole zebrafish sagittal tissue section was

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sprayed with 25 mL 0.05 mg/mL as-prepared Fe3O4 solution using a 0.2-mm nozzle airbrush (NEW-LP, China), with a nozzle-to-target distance of 10 cm. The final Fe3O4

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material layer was approximately 276.5 µg/cm2. The fish slide was dried in the open

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air for 15 min prior to LDI-MSI analysis.

2.4 LDI-MS and LDI-MSI analyses LDI-MS and LDI-MSI analyses were performed on an ultrafleXtreme II mass spectrometer (Bruker Daltonics, Germany) equipped with a 335-nm smartbeam II laser. Mass spectra were acquired over the m/z range of 100–1,000 in positive ion

reflector mode. Peptide Calibration Standard II was used for the calibration of the mass analyzer. The laser parameters, including intensity and repetition, were set to 80% and 1,000 Hz, respectively. The tissue sections were analyzed with a spatial resolution of 100 µm, and 1,000 laser shots per pixel were set at a full-scan mass spectrum.

3. Results and discussion

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3.1 Characterization of Fe3O4 Nanoparticles

According to the standard card of magnetite (JCPDS: 19-0629), the XRD patterns showed that the as-prepared Fe3O4 samples had well-crystallized spinel structures

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(Figure S1). The SEM images revealed as-prepared Fe3O4 with octahedral (M1, M2),

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spherical (M6–M11), cubic (M3), rod-like (M4), plate-like (M5), and amorphous (M12) morphologies (Figures 1 and S2). The mean particle sizes of as-prepared Fe3O4

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were confirmed in the range of 19–161 nm (Table S1), indicating their nanoscale

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Figure S3).

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diameters. The amount of surface hydroxyl ranged from 0.18–7.14% (Table S1 and

3.2 Optimization of Physicochemical Properties of Nano-Fe3O4 for Target

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Metabolite Signals

The acquired MS data demonstrated that the characteristic peaks at m/z 128, 203, 290, 335, 504, and 871 were the sodiated adducts ([M+Na]+) of SER, GLU, ADE, ARA, CER, and TG, respectively. The formation of sodiated adducts during MS ionization can be partly attributed to the low proton affinities and high cation affinities of

analytes[47-49]. In this study, these 6 characteristic peaks were subsequently used for the analysis of target metabolites. Effects of method operations and synthesis methods of Fe3O4 on small-molecule metabolite signals are discussed in detail in Text S5. Overall, the dried-droplet preparation method, 80% laser energy, 1 mg/mL Fe3O4, and microwave-assisted method were selected as the optimum conditions, and used for the subsequent evaluation of the effects of nano-Fe3O4 with different physicochemical

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properties on the performance of LDI-MS (Figures S4 and S5).

The dispersity of matrix-coating in the target plates can affect the performance of analytes in LDI-MS and can primarily be attributed to the stack status of different

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matrix morphologies. We synthesized different Fe3O4 morphologies in our previous

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work, including nano-octahedrons, nano-cubes, nano-rods, nano-plates, and nano-spheres. The results revealed that the total peak intensities of analytes from

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Fe3O4 nano-rods (M4), nano-spheres (M6), and nano-plates (M5) were almost 2 or 3

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times higher than those of Fe3O4 nano-cubes (M3) and nano-octahedrons (M1) (Figure S2). There was no apparent variation among M4, M5, and M6. Fe3O4 nano-plates

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were found to have the highest activity of the various morphologies[46]. It is challenging, however, to synthesize Fe3O4 nano-plates with different particle sizes and

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surface hydroxyl amounts. The most stable Fe3O4 morphology was reported to be the nano-sphere with the lowest energy[46]. As a compromise, the nano-sphere was selected as the ideal morphology of Fe3O4 for the following evaluation of the effects of particle size and surface hydroxyl amount on the performance of analytes in LDI-MS.

Nanoparticle size is closely related to the loading capacity of analytes. In order to assess the impact of particle size on the intensity and RSD of analytes, 4 nano-spherical Fe3O4 particles with different sizes were synthesized using a microwave-assisted method (Table S2). The surface hydroxyl amounts of M6 and M8 were similar, and those of M7 and M10 were almost the same. It can be observed from Figure 2A that the intensities and RSDs of M6 (22 nm) and M10 (45 nm) were

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better than those of M8 (45 nm) and M7 (70 nm), respectively. The small particle size increases the loading capacity of analytes, leading to increasing heat transfer from Fe3O4 to analytes during laser desorption ionization[50].

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As shown in Figure 2A, although M8, M9, and M10 have the same particle sizes,

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they have different effects on the intensity and RSD of analytes. These differences can be attributed to their surface hydroxyl amounts. M10, with the highest surface

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hydroxyl amount of 4.22%, presented the best signal response and repeatability for

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LDI-MS analysis. Analyte intensity decreased with decreasing amounts of Fe3O4 surface hydroxyl. In this study, the Fe3O4 matrix was prepared by dissolving it in

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isopropanol. Hydroxyl is reported to readily cover metal oxide, which is commonly synthesized in a water medium[51-54]. The greater the surface hydroxyl amount, the

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better the Fe3O4 will disperse in isopropanol and on the LDI target plate with analytes. In addition, the surface hydroxyl may provide protons for the positive ionization of analytes and facilitate ionization efficiency. Considering all of these results, M10 was selected as the optimum matrix for the analysis and localization of metabolites in LDI-MS and LDI-MSI.

3.3 Comparison of Fe3O4-assisted LDI-MS with traditional MALDI-MS The background signal of M10 with no analytes in LDI-MS was determined and compared with traditional organic matrices under identical instrumental conditions (Figure S6). CHCA, DHB, and SA produced a large number of matrix-related peaks in the low-molecular-weight range of m/z 100–700. In contrast, a few small

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background signals in the low m/z range were observed in the mass spectrum of M10, for which the baseline was 3–6 times lower than those of the traditional organic

small-molecule analytes in biological samples.

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matrices. Accordingly, M10 possesses a greater peak capacity to detect

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Apart from background noise, we also compared the sensitivity of analytes obtained from traditional organic matrices with that of nano-Fe3O4 in LDI-MS

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(Figures 2B and S7). When SA was used, most analytes could not be found in the

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mass spectrum. For the DHB-assisted LDI-MS measurements, the number of detected analytes increased, but the analyte intensities were far below those of the background

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signals. Two types of nano-Fe3O4 were also used as matrices in LDI-MS (Table S2). M11 was a commercial product, and M12 was synthesized by a reported method[44].

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The total analyte intensity in the 3 Fe3O4-assisted LDI-MS analyses exhibited the following relative relationship: M10 > M12 > M11 (Figure 2C). Thus, the as-obtained M10 with small particle size and high surface hydroxyl amount is an ideal matrix, exhibiting the best overall performance for analytes in the positive ionization of LDI-MS among the traditional organic matrices and nano-Fe3O4 used in this study.

3.4 Mechanistic studies of Fe3O4-assisted LDI-MS Once matrices receive laser irradiation from an ionization source, laser excitation will produce photo-induced electrons within them, facilitating the ionization of nearby analytes. At the same time, these matrices can be heated to a certain temperature, leading to the desorption of nearby analytes. To investigate how laser absorption

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capacity affects the efficiency of Fe3O4 nanoparticle desorption and ionization, we

assessed the full wavelength scan (200–800 nm) of 3 Fe3O4 nanoparticles (M10, M11, and M12) in isopropanol solution. The results revealed that M10 displayed stronger

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laser absorption at 355 nm than either M11 or M12 (Figure 2D), in agreement with the

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order (M10 > M12 > M11) of total analyte intensity in Fe3O4-assisted LDI-MS (Figure 2C). These findings indicate that laser absorption capacity is positively related

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to LDI performance[55]. After laser irradiation of matrices, ionization and desorption

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are two essential processes for analytes in the ionization source. Laser excitation efficiently produces photo-induced free charge carriers or

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electron-hole pairs in Fe3O4 nanoparticles[56]. Good affinity at the analyte-matrix interface helps to enhance the rapid photo-induced electron transfer and separation

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capacities of photo-induced free charge carriers and electron-hole pairs[57], facilitating the ionization of nearby analytes in Fe3O4-assisted LDI-MS. Analysis of the UV-visible absorption spectrum is an essential approach for exploring structural change and complex formation[58, 59]. However, there was no visible red or blue shift of the maximum absorption wavelength between experimental and calculated values

of analyte-Fe3O4 mixtures (Figure 3A). The analytes may be bound to the surface of Fe3O4 by weak intermolecular interactions such as the van der Waals force, but not strong electrical interaction[60]. These results demonstrate that chemical interactions between nano-Fe3O4 and analytes do not play an essential role in the performance of Fe3O4-assisted LDI-MS. Energy transfer from matrices to analytes is considered to undergo a thermally

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driven process[50, 57]. A modified thermal desorption model described in detail in Text S3, was used to explain the performance of Fe3O4-assisted LDI-MS in this study[44].

As shown in Figure 3B, the temperatures were produced in an increasing order: M11

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< M1 ≈ M4 < M12 < M10, which was in accordance with their high LDI efficiencies

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(Figure 2C). M10 had the highest absorption coefficient, resulting in the highest temperature (Tcal = 629 K, Table S4) by laser irradiation. The thermally driven

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desorption process should be a key factor in the performance of Fe3O4-assisted

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LDI-MS.

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3.5 Repeatability and calibration curves of optimum Fe3O4-assisted LDI-MS According to the results mentioned above, M10 is the optimum matrix for LDI-MS. In

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order to test the method repeatability, standard samples with the same concentrations, including 10 mg/L and 50 mg/L of each analyte, were detected 7 times in the same spot (intra-spot) and at 7 distinct spots (inter-spot). There was no obvious intensity change of any analyte on the seven replicates (Figure 4A). The repeatability was mostly < 20% for both intra-spot and inter-spot analyses, implying that the developed

method was robust. We conducted intra-spot imaging of each analyte with different matrices. Among the traditional organic matrices (SA and DHB) and Fe3O4 (M10, M11, and M12), better dispersity of M10 without larger multi-particle aggregation (Figure 4B) was found following the total intensity order of the analytes (Figure 2C). These findings suggest that good dispersity of mixtures of matrices and analytes on the target plate could facilitate the performance of Fe3O4-assisted LDI-MS.

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In order to test the potential quantification of small-molecule metabolites by

Fe3O4-assisted LDI-MS (M10), 6 analytes at different concentrations ranging from

10–50 mg/L and 1 internal standard (10 mg/L) were analyzed. Stable isotope labeled 13

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C-Glucose (GLU 13C) was selected as the internal standard due to its similarity in

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chemical properties to GLU as well as its commercial availability. Figure 4C shows the mass spectrum characteristic peaks for SER (m/z 128), GLU (m/z 203), ADE (m/z

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290), ARA (m/z 335), CER (m/z 504), TG (m/z 871), and GLU 13C (m/z 209). Based

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on the peak area ratios between the standards and the internal standard, good linearity of the calibration curves for most analytes was obtained, with R2 values ranging from

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0.9814 to 0.9997 (Figure 4C), with the exception of TG, which had an R2 value of 0.7785. Since the chemical structure of TG contains 3 fatty acid chains, which bond to

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glycerol via ester linkages, TG is highly hydrophobic and has a high molecular weight. For glucose, however, it is hydrophilic with the hydroxyl group structures. The weak linearity of TG can be attributed to the improper internal standard (GLU 13C), in which the chemical properties are distinct from TG. Thus, the results indicated the quantification potential of small-molecule metabolites by optimum Fe3O4-assisted

LDI-MS.

3.6 Identification of endogenous metabolites in biofluid samples LDI-MS and LDI-MSI are effective for the rapid analysis and localization of analytes in biological samples, respectively. However, the lack of proper matrices is the foremost impediment in the application of LDI-MS and LDI-MSI. In this study, the

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optimum Fe3O4 (M10) was utilized as the matrix and then shown to successfully

detect the target metabolites with different molecular weights. In order to check the

practicability of M10, we analyzed biofluid samples, including fish serum, bile, and

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human urine. In addition, we also attempted to localize metabolites in a whole

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zebrafish sagittal tissue section using optimum Fe3O4-assisted LDI-MSI. Tentative assignments of characteristic peaks were made by matching measured and predicted

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m/z values with the lowest mass error (Δppm) based on universal databases such as

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the HMDB[61], as listed in Tables S5–S8 of the supplementary material. Compared to the background baseline obtained from M10 blank, a large number

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of peaks were observed in the 3 biological samples (Figures 5A–D). A pair of characteristic peaks, in which the difference of molecular weights was 22 ([M+H]+

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and [M+Na]+) or 16 ([M+Na]+ and [M+K]+), was chosen for identification. A few proposed metabolites are presented and discussed herein. For the fish serum sample, the characteristic peaks at m/z 825.762 and 841.797 were assigned to DiMe(13,3) cholesteryl ester (CE(DiMe(13,3))), which belongs to the class of cholesteryl esters. In a certain environment, cholesteryl esters and

cholesterol can convert mutually. Since their polarity is much less than that of free cholesterol, cholesteryl esters are used for the transport of cholesterol in plasma and the storage of cholesterol[61]. In the molecular mass range of 700–900 Da, the dominant peaks belonged to triacylglycerols (TGs). Six TGs were proposed based on their corresponding characteristic peaks (Table S5). TGs can exist in blood and become constituents of lipoproteins to deliver fatty acids to adipocytes. They play an

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essential role in metabolism as a source of energy and as transporters of dietary fat[61]. In addition, D-glucose at m/z 203.092 was found, which is a principal source of

energy for living organisms[61]. For the fish bile sample, eight characteristic peaks

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were tentatively assigned (Table S6). It should be noted that the ion of m/z 431.318

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([M+H]+) with the corresponding m/z 453.309 ([M+Na]+) was tentatively assigned to 7α-hydroxy-3-oxo-4-cholestenoate (7-Hoca), which is one of the monohydroxy bile

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acids, alcohols, and derivatives. The presence of 7-Hoca in the fish bile proved the

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practicability of the optimum Fe3O4-assisted LDI-MS, since 7-Hoca is involved in the pathway of primary bile acid biosynthesis[61].

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Apart from the fish biological samples, human urine samples were analyzed using the developed method. The mass range of 100–300 Da is populated by small-molecule

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acids, including amino acids, sulfinic acids, and phenylsulfates. Five proposed metabolites are listed in Table S7. Two important amino acids were detected: homocysteine at m/z 158.034 and 174.006, and L-tyrosine at m/z 204.063 and 220.037. Homocysteine is associated with human disease. A previous study indicated that the levels of urinary homocysteine in children with mental retardation are higher than

those of healthy children. Urinary homocysteine levels have also been linked with premature occlusive cardiovascular disease, even in children[61]. Tyrosine is an essential amino acid in the human body, as well as a precursor for neurotransmitters (e.g., dopamine and adrenaline), hormones, and melanin. Elevated tyrosine levels in premature infants have been related to decreased motor activity, lethargy, and poor feeding[61]. The results of the current study indicate that the developed method could

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be used to identify endogenous metabolites in biofluid samples, with possible further

clinical applications in the discovery of metabolites associated with human disease. In addition, as a widely detected environmental pollutant[62], climbazole (CBZ) and its

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isotope-labeled internal standard climbazole-D4 (CBZ-D4) can be detected by the

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optimum Fe3O4-assisted LDI-MS (Figure S8). The characteristic peaks at m/z 315.137 and 319.163 were the sodiated adducts ([M+Na]+) of CBZ and CBZ-D4, respectively.

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The corresponding [M+H]+ and [M+K]+ peaks were also found, suggesting the broad

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application of optimum Fe3O4-assisted LDI-MS in other compounds like

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environmental pollutants.

3.7 Imaging of endogenous metabolites in whole zebrafish sagittal tissue sections

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We have generated distribution maps of the proposed metabolites in whole zebrafish from optimum Fe3O4-assisted LDI-MSI (Figure 5E). There was a clear distinction between reproductive, digestive, and muscular tissue types. No metabolites were found in the zone of the swim bladder due to its absence in the zebrafish tissue section. The m/z 122.023, 156.981, and 258.882 ions represented the proposed metabolites

L-cysteine, phosphoglycolic acid, and PC(P-18:0/18:0), respectively. L-cysteine is a naturally occurring amino acid found in most proteins, and PC(P-18:0/18:0) is an essential component of animal fats [61]. Thus, it is reasonable to find these metabolites localized in the digestive and muscular regions of zebrafish tissue sections. The characteristic peak at m/z 429.299 was assigned to 25-hydroxyvitamin D3-26,23-lactone, which appeared to localize not only in the digestive and muscular

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regions but also in the reproductive areas of zebrafish tissue sections. The proposed metabolite is possibly a steroid or a steroid derivative [61]. Therefore, it would be

logical to see this ion in gonads and blood. In addition, TG(18:4/15:0/25:5) at m/z

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881.649 was found at low intensities in the areas correlating with the zebrafish’s

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digestive and muscular tissues. TG(18:4/15:0/25:5) is the body’s self-synthesized triglyceride and primarily resides in the liver, followed by adipose tissue [61]. Besides,

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the distribution map of other proposed endogenous metabolites, including

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small-molecule acids, ceramides, phosphatidylserines, and triacylglycerols, in the zebrafish tissue section is given in Figure S9. In summary, the results reveal a

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promising tool for the creation of a chemical composition image of reproductive, digestive, muscular, and other tissues of whole zebrafish sagittal tissue sections, one

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that will likely promote the development of eco-toxicological research to visually co-determine the location of endogenous/exogenous chemicals in the regions of interest.

4. Conclusions

This study showed that smaller particle size and greater surface hydroxyl amount of nano-spherical Fe3O4 could raise the LDI performance for small-molecule analysis. Based on the UV-visible absorption spectrum and thermal desorption model, the thermally driven desorption process, but not the chemical interactions between nano-Fe3O4 and analytes, was proposed to assist the desorption or ionization of analytes after receiving laser energy. The as-prepared Fe3O4 attained a higher peak

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capacity by reducing the background noise when compared to traditional matrices

such as DHB and SA. Good intra- or inter-spot repeatability and linearity of analytes

were obtained by the optimum Fe3O4-assisted LDI-MS. Finally, the developed method

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was successfully used for the rapid analysis and localization of endogenous

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metabolites in biofluids and whole zebrafish tissue section samples. Our results not only indicate the critical points of accurate synthesis of effective matrices for LDI

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performance but also afford a promising tool for the more in-depth understanding of

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meaningful biological information in environmental pollutant-induced toxicity.

CRediT authorship contribution statement

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Wen-Wen Wei: Writing - Original draft preparation, Formal analysis, Investigation, Methodology. Yuanhong Zhong: Writing - Original draft preparation, Funding acquisition, Formal analysis, Conceptualization, Methodology. Ting Zou: Formal analysis, Investigation. Xiao-Fan Chen: Formal analysis, Investigation. Li Ren: Formal analysis, Investigation. Zenghua Qi: Resources, Project administration.

Guoguang Liu: Resources, Supervision. Zhi-Feng Chen: Writing - Reviewing & Editing, Funding acquisition, Conceptualization, Methodology, Resources, Formal analysis, Project administration. Zongwei Cai: Conceptualization, Resources,

Conflicts of interest

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The authors declare no competing financial interest.

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Funding acquisition, Supervision.

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Acknowledgements

We would be grateful for the financial support from the National Natural Science

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Foundation of China (21507163, 91543202 and 41602031).

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Figure captions Figure 1 SEM images of (A) M1 and (B) M10; particle size distribution plots of (C)

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M1 and (D) M10; TGA-DSC plots of (E) M1 and (F) M10.

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Figure 2 (A) Effects of particle size and surface hydroxyl amount of nano-Fe3O4 on analyte intensity. Comparison of the performances of different Fe3O4-assisted

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LDI-MS analyses and traditional MALDI-MS ([Analyte] = 50 mg/L); (B) mass spectra of analytes in LDI-MS with different matrices; (C) stacked column plot of

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analyte intensities from LDI-MS with different matrices ([Analyte] = 50 mg/L); and (D) UV-visible spectra of different nano-Fe3O4 suspensions at the same concentration of 0.1 mg/mL.

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Figure 3 Mechanistic study of Fe3O4-assisted LDI-MS: (A) UV-visible spectra of

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single analyte solution, optimum nano-Fe3O4 (M10) suspension, and analyte-M10 mixture suspension. The solid line represents the experimental data, while the dashed

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line represents the calculated data of the analyte-M10 mixture, which was estimated by the sum of a single analyte and M10; (B) histogram of calculated heating

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temperature (ΔT) and final temperature (T) produced by the optimum nano-Fe3O4

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(M10).

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Figure 4 Method performance of the optimized Fe3O4-assisted LDI-MS (M10): (A) intensities of each analyte at 10 mg/L and 50 mg/L in the intra-spots and inter-spots (n

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= 7); (B) intra-spot imaging of each analyte with different matrices. The intensity

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scale is an arbitrary relative scale ranging from red (highest) to blue (lowest); (C) calibration curves of each analyte for the concentration range 10–50 mg/L. The lower right insets are the ion peaks of the analyte and internal standard.

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Figure 5 Application of the optimized Fe3O4-assisted LDI-MS and MSI. Mass spectra

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were acquired from (A) blank, (B) fish serum, (C) fish bile, and (D) human urine

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samples in the full scan mode. (E) Optical image of the whole zebrafish sagittal slice and imaging of proposed endogenous metabolites in the whole zebrafish sagittal tissue section. The intensity scale is an arbitrary relative scale ranging from color (highest) to black (lowest).

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