Introduction

XueBiJing injection (XBJ) was comprised of extracts from five Chinese herbals: Carthami Flos, Paeoniae Radix Rubra, Chuanxiong Rhizoma, Salviae miltiorrhizae and Angelicae Sinensis Radix. It has been widely used in China as a blood-activating and anti-endotoxicity drug for the treatment of sepsis and the associated multiple organ dysfunction syndrome (MODS)1,2. Modern pharmacological studies indicate that XBJ could protect the endothelium, improve microcirculation, alleviate coagulation and inflammation, and regulate immune response3,4. In clinical, XBJ could significantly reduce significantly the value of serum procalcitonin, C-reactive protein and the level of white blood cells in sepsis patients. In addition, the XBJ had an antagonistic effect on inflammatory markers, which could interdict the pathological process of systemic inflammatory response syndrome and reduce the incidence of MODS in order to further improve the prognosis of sepsis patients and reduce the mortality5,6. Although XBJ is an effective traditional Chinese medicine (TCM) in treating sepsis, the constituents of which remain largely unknown, and the bioactive components are not completely clear.

According to previous phytochemical and HPLC or UPLC-MS researches, glycosides, flavonoids and phenolic acids were the predominant constituents in XBJ. To date, a few reports have developed a method for qualitative or/and quantitative analysis of compounds in XBJ7–10. Ji et al.7 established a HPLC method coupled with an ultraviolet detector for the determination of 11 essential compounds in XBJ within 70 min, deficiency existed in terms of analysis time and sensitivity. Huang et al.9 developed an ultra performance liquid chromatographic (UPLC) method for simultaneous identification and quantification of 13 main components in XBJ and an UPLC/Q-TOF method for identification of 8 major metabolites in XBJ. Huang et al.11 established an HPLC/DAD/TOF method to identify 23 compounds in XBJ, including amino acids, phenolic acids, flavonoid glycosides, terpene glycosides and phthalides. However, due to the limitation of applied instruments, only high level components were studied in previous studies. To develop a sensitive and accurate method for the comprehensive chemical identification of XBJ, Q-Exactive hybrid quadrupole-orbitrap high-resolution mass spectrometer (Q-Orbitrap HRMS) was employed in the present study.

In this paper, qualitative and quantitative analyses were combined together for the integrated quality control strategy of XBJ. In qualitative analysis, Q orbitrap MS revealed its remarkable high resolution and sensitivity in the chemical identification of XBJ. Q-orbitrap HRMS was employed in the analysis of Chinese medicinal formula for the first time, and it overcame the drawbacks of HPLC and UPLC-MS. In present investigation, 162 unknown compounds were identified, based on their high resolution MS data and the cleavage patterns of 38 reference standards. Meanwhile, in order to avoid the ion response discrimination to different types constituents in XBJ, the fast polarity swinging was realized in one analysis. In addition, the utilization of Q orbitrap HRMS could realize simultaneously qualitative and quantitative determination in one analysis, which shortened analysis time. To the best of our knowledge, this is the first time to report the application of Q-Orbitrap HRMS in simultaneously determining and quantifying so many bioactive constituents in XBJ. The quantitative determination method had been validated and applied for an assay of 10 bathes XBJ samples, and the result could evaluated by fingerprinting and multivariate data analyses (principal component analysis, PCA). Finally, a rapid and simple UPLC-MS/MS method was developed for determination of five markers in XBJ. In one word, we provided a promising and integrated approach for the quality control of XBJ and a solid foundation for the pharmacological and pharmacokinetic study of XBJ.

Results and Discussions

Qualitative analysis of XBJ

A specific UHPLC-Q-Orbitrap HRMS method was developed as a reliable, sensitive and high-throughput method for rapid identification of the components of XBJ regardless of the macro- and micro-constituents. The total ion chromatograms (TIC) of the XBJsample both in positive and negative ion mode are presented in Fig. 1 38 compounds were unambiguously identified based on comparison of retention time and high-resolution accurate mass with that of available reference standards and their chemical structures were shown in Fig. 2. Moreover, the fragmentation patterns and pathways of the standards were investigated in depth to further confirm the structure of their derivatives. For the compounds without available references, the structures were presumed based on the following steps so as to increase the credibility: (1) the molecular formula was established based on high-accuracy protonated precursors such as [M + H]+, [M + Na]+, [M−H]−, or [M + HCOO]− within a mass error of 10 ppm and the fractional isotope abundance; (2) A class of compounds has the same law of cracking, therefore, the standards were utilized to characterize the fragment pathways and diagnostic fragment ions that could be applied for structural elucidation of their derivatives. In addition, some literatures about the compositions of XBJ and five Chinese herbals could be referred. (3) The fragment ions from mass spectrometry were used to further confirm the chemical structure with the aid of Thermo ScientificTM Mass Frontier 7.012.

Figure 1
figure 1

The total ion chromatograms (TIC) of the XBJ sample (A) in positive mode (B) in negative mode.

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Figure 2
figure 2

Chemical structures of 38 major components identified from XBJ injection.

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As for monoterpene glycosides, the loss of CH3, H2O and CO was observed clearly in their MS/MS spectra. The mass spectra and proposed major fragmentation of representative compounds Paeoniflorin was shown in Fig. 3A and the proposed fragmentation pathways was presented in Fig. 3B. Other constituents were tentatively deduced by the above steps and paeonisuffrone, phenanthrenequinone, senkyunolide, lactones, flavonoids and phenolic compounds dominated the chemical profiling of XBJ13,14,15,16,17,18,19,20,21,22,23. Overall, 162 components, including 19 monoterpene glycosides, 19 phenanthrenequinone, 33 lactones, 28 flavonoids and 63 phenolic acid and other compounds, in XBJ were identified or tentatively characterized with their retention times and MS data, which are summarized in Table 1.

Figure 3
figure 3

(A) The mass spectra and proposed major fragmentation of Paeoniflorin (B) Proposed fragmentation pathways of Paeoniflorin.

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Table 1 19 monoterpene glycosides (M), 19 phenanthrenequinone (P), 33 lactones (L), 28 flavonoids (F), 63 phenolic acid and other compounds (O) identified from XBJ by UHPLC-Q-Exactive.
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Identification of monoterpene glycosides in XBJ

19 monoterpene glycosides were identified and listed in Table 1. M1 gave [M−H]− ion at m/z 359.13400 (C16H23O9) in full scan mass spectrum. In it’s MS/MS2 experiment, the obtained ion produced characteristic fragment of [M−H−Glc]− at m/z 197.08099 (C10H13O4), corresponding to the paeonisuffrone, was observed, the further loss of H2O group generated the fragment of [M−H−Glc−H2O]− at m/z 179.07028 (C10H11O3) was also observed. Thus, M1 was deduced as 1-O-β- d-glucopyranosyl-paeoni-suffrone. Three isomers (M4, M5 and M7) revealed the same [M−H]− ions at m/z 527.13922 (C23H27O14). In the MS/MS2 experiment of M4, the [M−CH2OH]− ion at m/z 497.12943 (C22H25O13) and [M−CH2OH−H2O]− ion at m/z 479.11896 (C22H23O12) was produced by the loss of CH2OH unit, and the further loss of H2O. The precursor ion of M4 generated fragment at m/z 313.05627 (C13H13O9) by loss of the aglycone moiety, and the further loss of hexose moiety produced the galloyl fragment at m/z 169.01294 (C7H5O5). M5 had the same ions at m/z 313.05627 and 169.01294 in its MS/MS spectrum with M4 and M7. M4, M5 and M7 were identified as 6′-O-galloyl Desbenzoylpaeoniflorin and its isomers.

Four isomers (M12, M14, M15 and M16) revealed the same [M−H]− ions at m/z 631.16498 (C30H31O15). In the MS/MS spectrum of M12, the loss of H2O group from precursor ion at m/z 613.15570 (C30H29O14) and the further loss of benzoyl group at m/z 491.11874 (C23H23O12) was observed. The obtained ion produced fragment corresponding to galloyl attached at one hexose moiety at m/z 313.05603 (C13H13O9), and the galloyl fragment at m/z 169.01294 (C7H5O5) were found. All of M14, M15, and M16 had the same fragments at m/z 313.05603 (C13H13O9), at m/z 169.01294 (C7H5O5), and benzoyl group at m/z 121.02809 (C7H5O2) in their respective MS/MS spectra. M12, M14, M15, and M16 were identified as galloylpaeoniflorin and its isomers. M17 and M18 showed the same [M−H]− ion at m/z 599.17554 (C30H31O13). Apart from the characteristic fragments of paeoniflorin, both of their MS/MS spectra displayed the fragment at m/z 477.13870 (C23H25O11), 281.06613 (C13H13O7), 137.02303 (C7H5O3), 121.02802 (C7H5O2), indicating the existence of O-benzoyl unit, benzoyl unit, and hexose moiety. M17 and M18 were deduced as benzoyloxypaeoniflorin and its isomer. M19 displayed the [M−H]− ion at m/z 583.18210 (C30H31O12), which had one less oxygen than that of M17 and M18. By comparing and the analysis of their MS/MS spectra, the absence of ion at m/z 137.02303 (C7H5O3), and the presence of ion at m/z 121.02801 (C7H5O2), indicated the benzoyl unit in M19 instead of O-benzoyl unit in M17 and M18. Thus, M19 was identified as benzoylpaeoniflorin.

Identification of phenanthrenequinone in XBJ

19 phenanthrenequinone were identified and listed in Table 1. P1 displayed a [M + H]+ ion at m/z 297.11133 (C18H17O4). In the MS/MS2 experiment, the obtained ion produced [M−H2O]+ fragment at m/z 279.15570(C18H15O3) and [M-2H2O]+ ion at m/z 261.09055 (C18H13O). P1 was identified as tanshinone VI. Four isomers P3, P4, P5, and P14 revealed the same [M + H]+ ion at m/z 313.14249 (C19H21O4). In the MS/MS2 experiment, the obtained ion produced [M−H2O]+ fragment at m/z 295.13196 (C19H19O3), [M−CO2]+ ion at m/z 269.15262 (C18H21O2), and [M − H2O−CO2]+ ion at m/z 251.14232 (C18H19O) were found in P3. P14 had the same fragment ions with P3. In the MS/MS spectrum of P4, [M−H2O]+, [M−2H2O]+, and [M−H2O−CO2]+ ions at m/z 295.13177 (C19H19O3), m/z 277.12137 (C19H17O2), m/z 251.14224 (C18H19O3) were detected. The fragment of [M−CO]+, and [M−CO−H2O]+ ions at m/z 285.14700 (C18H21O3), and m/z 267.13751 (C18H19O2) were observed in the MS/MS2 experiment of P5. This fragmentation information were similar with that of phenanthrenequinone, and their molecular was accordance with tanshinone II B, the major constituent in tanshin, one composition of traditional Chinese medicine in XBJ. Thus, P3, P4, P5, and P14 were deduced as tanshinone II B and its isomers.

P8 gave a [M + H]+ ion at m/z 299.16432 (C19H23O3). Its MS/MS experiment generated [M−H2O]+ ion at m/z 281.15341 (C19H21O2), and the further loss of CO produced the [M−H2O−CO]+ ion at m/z 253.15788 (C18H21O). P8 was identified as miltiodiol. P9 exhibited a [M + H]+ ion at m/z 299.16339 (C19H23O3) in the positive full scan mode. The fragment at m/z 281.15314 (C19H21O2) indicated the loss of H2O from the precursor ion. The other product ion at m/z 253.15788 (C18H21O) revealed the further splitting of a CO2 group. This information led to the conclusion that P9 was deoxyneocryptotanshinone. Two isomers P13 and P18 showed the same [M + H]+ ion at m/z 297.14852. The MS/MS experiment of P13 generated [M−CO2]+ ion at m/z 249.09039 (C18H21O). P13 were identified as Cryptotanshinone by comparing with the retention time and high-resolution accurate mass and P18 was identified as its isomers.

Identification of lactones in XBJ

The detailed MS data of 33 lactones were listed in Table 1. Four isomers L1, L4, L5 and L9 revealed the same [M + H]+ ions at m/z 227.12724 (C12H19O4). In their MS/MS spectrum, the characteristic fragment ions of senkyunolide J/N, such as 209.11671 (C12H17O3), 191.10614 (C12H15O2,), 163.11134 (C11H15O), 153.05424(C8H9O) were observed. So they were assigned as senkyunolide J/N and its isomers. Similarly, L2, L3, L8 and L10 were identified as senkyunolide I/H and its isomers owing to the presence of diagnostic fragment ions related to senkyunolide I/H. L7, L11, and L12 showed the same [M + H]+ ion at m/z 207.10114 (C19H21O4) in their full scan positive mass spectrum. In their MS/MS spectra, the same ions at m/z 189.09053 (C12H13O2) produced by the loss of H2O group from precursor ion, and m/z 161.09546 (C11H13O) produced by the further loss of CO group were found. These characteristic information related to senkyunolide suggested L7, L11, and L12 to be senkyunolide F and its isomers. L13, L15, and L23 were determined as senkyunolide B/C/E, for the characteristic fragment ions of senkyunolide B/C/E, at m/z 187.07489 (C12H11O2), 177.09053 (C11H13O2,), and 163.03853 (C9H7O3), 149.02296 (C8H5O3). L18 exhibited [M + H]+ ion at m/z 209.11652 (C12H17O3) in its full scan positive mass spectrum, indicating the molecular formula of C12H16O3. The MS/MS experiment of L18 generated [M−2H2O]+ ion at m/z 173.09526 (C12H13O) by successive loss of H2O group from the precursor ion. L18 was identified as senkyunolide G/K. L21, L22, L26 and L28 exhibited the same [M + H]+ ion at m/z 193.12196 (C12H17O2) in positive ion mode, indicating the molecular formula of C12H17O2, which had one less oxygen atom than that of L18. They had one less hydroxyl than that of L18 in the structure, which was verified by the fragments at m/z 175.11171 (C12H15O), m/z 165.12669 (C11H17O), m/z 137.05954 (C8H9O2) in their MS/MS spectra. Thus, L21, L22, L26, and L28 were identified as senkyunolide A and its isomers. The same [M + H]+ ions at m/z 279.15839 (C16H23O4) of L24, L25, and L27 revealed the molecular formula of C16H22O4. The fragment ions at m/z 261.14850 (C16H21O3), 233.15289 (C15H21O2), 215.14252 (C15H19O), were generated by loss of H2O, further loss of CO, and further loss of H2O, respectively. The ion at m/z 191.10616 (C12H15O2) was produced by three times of successive loss of H2O from fragment of [M-H2O-CO]+ at m/z 233.15289 (C15H21O2), and the further loss of H2O generated ion at m/z 173.09566 (C12H13O). These ions are the characteristic neutral losses associated with the senkyunolide M. Thus, L24, L25 and L27 were indicated as senkyunolide M and its isomers.

Identification of flavonoids in XBJ

28 flavonoids were detected and deduced in positive ion mode. The detailed fragmentation information of flavonoids was listed in Table 1. F7, F12 and F9 displayed the same [M + H]+ ion at m/z 611.15912 (C27H31O16), and they were deduced as rutin and its isomers, based on the presence of diagnostic fragment ions at m/z 303.04904 (C15H11O7), 153.01854 (C7H5O4). Five isomers of F8, F16, F18, F20 and F22 displayed the same [M + H]+ ion at m/z 449.10632 (C21H21O11) with luteolin-O-glc of F17. In their MS/MS spectra, by lossing of the hexose moiety generated the [M−H−Glc]+ ion at m/z 287.05411 (C15H11O6), corresponding to the aglycone of kaempferol or luteolin. F8, F16, F18, F20, and F22 were identified as hexose glycoside of kaempferol or its isomers. F23, F25 and F28 showed the same [M + H]+ ion at m/z 287.05420 (C15H11O6). In their MS/MS spectra, the characteristic fragments at m/z 153.01807 (C7H5O4), 133.02815 (C8H5O2), and 121.02580 (C7H5O2), which were produced by the two different reaction routines of RDA cleavage, were observed. The loss of CO moiety from precursor ion generated the ion m/z 258.05179 (C14H10O5) was also found. Comparing with the retention time of reference solution, F25 was confirmed as luteolin and F28 was kaempferol. The characteristic ions of kaempferol are m/z 258.05060, 153.01787, 133.02806 and 121.02821, and the characteristic ions of luteolin are m/z 153.01747, 137.09558 and 135.04381.

Identification of phenolic acids and other compounds in XBJ

The MS data of 63 detected phenolic acid and other compounds were listed in Table 1. O12 and O34 showed the same [M−H]− ion at m/z 197.04436 (C9H9O5) in the negative full scan mode. Both of their MS/MS spectra displayed the [M−H2O]− and [M−H2O−COOH]− ions at m/z 179.03392 (C9H7O4) and 135.04376 (C8H7O2) suggested that O12 and O34 were Tanshinol and its isomer. O17, O25 and O32 displayed the same [M−H]− ion at m/z 353.08688 (calculated 353.08781, error, −2.621 ppm) in negative full scan mode. Their MS/MS spectra showed similar ions at m/z 179.03372 (C9H7O4) and 135.04366 (C8H7O2). This fragmentation was associated with that of caffeic acid. O17, O25 and O32 were identified as chlorogenic acid and its isomers. Four isomers of O19, O20, O21 and O41 showed the same [M + H]+ ion at m/z 137.02442(C7H6O3). The MS/MS experiment of O41 generated [M−CO2]+ ion at m/z 93.03307 (C6H5O). O41 were identified as Cryptotanshinone by comparing with reference, and the O19, O20 and O21 were identified as its isomers. In the negative full scan mode, O26 showed [M−H]− ion at m/z 179.03365 (C9H7O4). The MS/MS experiment yielded [M−COOH]− ion at m/z 135.04378 (C8H7O2). O26 was identified as caffeic acid. O53 showed [M−H]− ion at m/z 359.07632 (C18H15O8). In the MS/MS experiment, the ion at m/z 179.03386 (C9H7O4) was triggered by the loss of caffeic acid residue. Further fragment at m/z 197.04462 (C9H9O5) suggested the existence of acid. Therefore, O53 was identified as rosmarinic acid.

Quantitative analysis of samples

A thorough and complete method validation for assaying 38 bioactive compounds in XBJ was done referring to ICH guidelines24. The UHPLC-Q-Orbitrap mass spectrometry was validated with respect to linearity, sensitivity, accuracy and precision, reproducibility and stability.

Method Validation

Linearity, LOD and LOQ

Standard stock solutions containing 38 analytes were prepared and diluted to seven appropriate concentrations for the construction of the calibration curves. Each solution was injected in triplicate, and then the linear regression equation was obtained by plotting the analyte peak area (Y) vs a series of analyte concentrations (X). The regression equation, coefficient of determination (R 2) and linear range are given in Supplementary Table S1. All the analytes showed good linearity with R 2 more than 0.9994 in the concentration range. The LOD and LOQ under the optimized chromatographic conditions were evaluated at a signal-to-noise ratio (S/N) of 3 and 10, respectively. The values of LODs and LOQs were in the range of 0.01~35.77 ng·mL−1 and 0.03~119.22 ng·mL−1, respectively (Supplementary Table S1).

Accuracy and precision

The precision of the established method was evaluated by intra-day and inter-day variability, and the relative standard deviations (RSD) were taken as a measure. The mixed standard solution at middle concentrations was analyzed in six replicates within one day and on 3 consecutive days. The results are shown in Supplementary Table S1, and the RSD values of the intra-day and inter-day of 38 compounds were all less than 2.97%, which showed good precision of the developed method.

The accuracy of the established method was evaluated by recovery test and RE (relative error). The samples were spiked with three concentration levels (80, 100, and 120%) of known amounts of 38 reference compounds. The spiked samples of each concentration were analyzed in triplicate. The accuracy was calculated as the quotient of the measurement and the nominal value of the analyte added to the sample. The detailed accuracy data is presented in Supplementary Table S2. The mean recoveries were ranged from 98.5% to 101.3% with RSDs less than 2.98%.

Reproducibility and Stability

In order to confirm the reproducibility, six different samples from the same batch sample were analyzed within one day and on three consecutive days. The RSDs were used as a measure and the acceptance criterion should be within 5.0%. The results are shown in Supplementary Table S1 and the RSD values of 38 compounds were all less than 3.0%, which showed good reproducibility of the developed method.

The stability of the sample solution was analyzed at room temperature on three consecutive days. The stability of the standard solutions stored at 4 °C was also examined on three consecutive days. Injections were performed at 0, 12 hour, 1, 2, 3, 5, and 7 days. The stability RSD values of 38 compounds in the sample solution were all less than 2.86% and those in standard solutions were all less than 2.0%, which showed that all analytes in the sample solution (at room temperature) and the standard solutions (at 4 °C) were found to be very stable.

Analysis of chemical profile of XBJ sample

The developed UHPLC-Q-Orbitrap HRMS method was adopted for the routine screening of the 38 bioactive compounds in 10 XBJ samples. 38 bioactive compounds were unambiguously identified by comparing the retention times and high-resolution accurate mass of reference standards. The polarity switching in full scan modes of UHPLC-Q-Orbitrap HRMS was used to achieve the highest response intensities of various types of constituents. In addition, the Q-Orbitrap HRMS as a powerful high resolution mass spectrometry, has the function of qualitative and quantitative simultaneously, namely compounds could be qualitative and quantitative in one analysis. Table 2 showed the obtained quantitative results of each compound calculated according to calibration curves. The results shows that two compounds (Hydroxysafflor yellow A and Paeoniflorin) are the predominant constituents obviously, the contents of which are much higher than other compounds. Hydroxysafflor yellow A and Paeoniflorin are two major marker components in Carthami Flos and Paeoniae Radix Rubra. Moreover, the Q-Orbitrap HRMS has very high sensitivity, so the low-content compounds, such as Levistolide A, Tetramethylpyrazine, Butylidenephthalide and Tanshinone I, were investigated simultaneously. Thus, the constituents with high and low levels contents could be quantified in one analysis.

Table 2 Quantitative analytical results for 38 compounds in XBJ from 10 batches (n = 3, μg/mL).
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The RSD of total amounts of investigated 38 compounds in 10 batches XBJ samples was 2.81%, which showed good stability of the total content. However, significant variations were observed as well. The RSD of each compound in 10 batches XBJ samples was in range of 2.48% to 19.43%, which showed instability of the some compounds. However, multiple active components, including macro- and micro-components, are frequently considered to be responsible for the therapeutic effects25. So, the present analysis of multiple components is more reasonable for quality control of XBJ injection.

Quality assessment of XBJ with the established strategy

Fingerprinting

Fingerprinting strategies are internationally accepted as an acceptable means of quality control (QC) for TCMs26. There are significant advantages of using fingerprinting strategies for sample differentiation, as fingerprinting not only determines the characteristic patterns of each plant type but also reveals the inherent relationships between multiple compounds. The good precision, reproducibility, stability of UHPLC-Q-Orbitrap HRMS analysis were demonstrated. The chromatograms Xcalibur raw files of ten batches sample was imported into the SIEVE software. The batch of 1500181 was selected as reference chromatogram. In order to focus on the most effective information, time windows of 0–60 min was selected to generate chromatographic fingerprinting. The similarity values obtained by SIEVE software was calculated through the overall evaluation of 10 batches total ion current chromatograms. The identical peaks in 10 batches sample chromatograms can be matched in automatic and proceeded peak alignment. The retention time and peak area of all peak in 10 batches sample make a comparison with the reference chromatogram. The correlation coefficients of all introduced chromatograms relative to that of reference chromatogram would be calculated. The similarity values of 10 samples (No.1500181, 1504101, 1504111, 1504121, 1505211, 1505671, 1508171, 1508191, 1509082 and 1509132) in fingerprintings in positive and negative mode were 1, 0.990, 0.988, 0.990, 0.991, 0.989, 0.991, 0.988, 0.977 and 0.993, respectively. The similarity values were all more than 0.9 in positive and negative mode, which indicated that the samples from different batches had strong similarities with high correlation coefficients of similarities. To some degree, this results demonstrate that the fingerprinting chromatograms of these samples might be used to assess the quality of XBJ injection.

Principal component analysis

PCA was used to further classify the 10 samples. PCA is an analytical method that is used to reduce a large set of variable into a smaller set of “artificial”variables known as principal components (PCs), which account f or most of the variance in the original variables. In the present analysis, the data matrix of ten batches samples and 38 bioactive compounds was imported into the multivariate statistical analysis software SIMCA 14.0. The PCA-X model was adopted to match the data and the original 38 variable dimension generated 2 new variables through software automatically, that is the two principal components. After the data fitting, the principal component 1 of variable was accounted for larger percentage of 63.8%, which could reflect the main characteristics of the original data. So PC1 would be suitable for revealing correlations among the different variables. The Score Scatter Plot (Fig. 4A) is used to evaluate the stability of 10 batches XBJ samples. The deviation represented the degree of stability. The deviation represented the degree of stability. The smaller the deviation in the PC1 axis, the better stability. The Fig. 4A shows the bias of 10 batches was within ± 2 SD, indicating the quality of 10 batches was more stable. In addition, the bias of 8 batches in 10 batches was within ± 1 SD, while the bias of 2 batches in 10 batches was ranged from ± 1 SD to ± 2 SD.

Figure 4
figure 4

(A) PCA Score Scatter Plot. (B) PCA Loading Column Plot.

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The PCA Loading Plot could reflect the weight size of original variable in the principal component analysis. The greater the absolute value of original variable in the PCA Loading Plot, the more importance role of original variable in the overall distribution. So the PCA Loading Plot can make it possible to discover the variables leading to the difference. In the Loading Column Plot (Fig. 4B) of the scores, the variables of 13 and 15 were the farthest from the origin on the PC1 and PC2. A13 and A15 as the important quality markers, has a relationship with different batch of drugs on the scatter plot distribution location. In the Fig. 4B, A13 and A15 were positive and the absolute value is larger in Loading Plot on PC1, which make the most batch in the positive quadrant portion of the Score Scatter Plot and keep positively correlated with them. Because the level of A13 and A15 is lower than the average level, the batch 1505211 has obvious anomaly in the overall distribution. So the two components made this batch negatively correlated and this batch was spotted in the negative quadrant part of the Score Scatter Plot. That is to say that two markers responsible for the cluster formation were mainly compounds (A13 and A15) that suggested that the contents of Hydroxysafflor yellow A and Paeoniflorin had a significant relationship with quality of XBJ injection. In addition, the variables of 14, 21 and 30 had a certain statistical significance compared with other variables. The compounds were Albiflorin, Senkyunolide I/H and Benzoylpaeoniflorin, respectively. This three compounds could provide some reference meaning for quality evaluation of XBJ injection. In 2013 edition Drug Standards of China, Hydroxysafflor yellow A and Paeoniflorin were selected as markers due to the two highest levels chemical composition. However, the therapeutic effects are frequently considered to be connected with multiple active components, including macro- and micro-components. So, the five markers, Hydroxysafflor yellow A, Paeoniflorin, Albiflorin, Senkyunolide I/H and Benzoylpaeoniflorin, were more meaningful for the quality of XBJ injection.

Assay of the five markers in XBJ sample

An UPLC-MS/MS method was developed for the routine determination of five markers in XBJ samples within 5 minutes. And the method was validated according to the above section “Method validation”. Satisfactory linearity and correlation coefficient were achieved with linear ranges. The relative standard deviations of precisions, repeatability, stability and recovery were all meeting requirements. The UPLC-MS/MS method could apply for the analysis of five marks in XBJ samples. The typical chromatograms of a standard mixture of five markers (A) and an XBJ sample (B) are shown in Fig. 5. This UPLC-MS/MS method was simpler in operation and higher in data handling efficiency for widely application.

Figure 5
figure 5

The typical chromatograms of a standard mixture of five markers (A) and an XBJ sample (B).

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Methods

Reagents and materials

HPLC grade methanol and acetonitrile for qualitative analysis were obtained from Fisher Scientific (Fair Lawn, NJ, USA). Formic acid of HPLC grade purchased from Aladdin Industrial Co., Ltd. (Shanghai, China). Ammonium acetate was MS grade and purchased from Anpel scientific instrument Corporation Ltd. (Shanghai, China). All other chemicals were of analytical reagent grade. Ultra-pure water (18.2 MΩ) was purified by Millipore system (Millipore, Shanghai, China) and all solutions were filtrated 0.22 μm pore size filters.

The reference standards of compounds A1-A38 were purchased from Chengdu Must Bio-technology Co., Ltd. (Sichuan, China). The purities of all the reference standards were over 98% and their chemical structures were illustrated in Fig. 2. Ten batches commercial patent medicines of XBJ were prepared by Tianjin Chase Sun Pharmaceutical Co., Ltd. (Tianjin, China).

Standard solution and samples preparations

The stock standard solutions of 38 reference standards were dissolved in methanol with concentration of 1.0 mg/mL for each compound, respectively. Then, each stock solution was mixed with 50% methanol to prepare a final mixed standard solution. A series of working standard solutions were prepared by the successive dilution of the mixture of standard solutions with 50% methanol. All the solutions were stored at 4  °C before use. Ten batches of commercial preparations of XBJ were directly subjected to UHPLC-MS analysis after being filtered through a 0.22 μm syringe filter.

Chromatographic conditions and Mass spectrometric conditions

In the quantitative analysis of 38 compounds, an UHPLC Dionex Ultimate 3000 with Q-Exactive hybrid quadrupole-orbitrap mass spectrometer system was utilized. Chromatographic peaks were separated on a Waters ACQUITY UPLC® HSS C18 column (2.1 mm × 100 mm, 1.8 μm) at a flow rate of 0.2 mL/min with gradient acetonitrile (A) and water containing 10 mM ammonium acetate (B) as follows: 0–10 min, 5% A, 10–45 min, 5–30% A, 45–60 min, 30–100% A, and then the column was re-equilibrated at 5% A for 2 min prior to the next injection. The injection volume was 5 μL for analysis. The Q-Exactive mass spectrometer was equipped with heat electrospray ionization (HESI), an online vacuum degasser, a quaternary pumps, an autosampler, a thermostated column compartment and ultraviolet detector (UV). The optimized parameters of mass spectrometry were illustrated as below: spray voltage: + 3.5 kV or −2.8 kV; sheath gas pressure: 40 arb; Aux gas pressure: 10 arb; sweep gas pressure: 0 arb; capillary temperature: 320 °C; auxiliary gas heater temperature: 300 °C; S-lens RF level: 50 V; scan mode: (1) full MS: Resolution: 70,000; automatic gain control (AGC) target: 3.0e;6 maximum injection time (IT): 200 ms; scan range: 80–1200 m/z; (2) dd-MS2/dd-SIM: Rsolution: 17,500; AGC target: 1.0 e5; maximum IT: 50 ms; Loop count: 5; Isolation window: 2.0 m/z; NCE/stepped: 20, 30, 40; Dynamic exclusion: 10.0 s. Nitrogen was used for spray stabilization and as the collision gas in the C-trap. All data collected in profile mode were acquired and processed using Thermo Xcalibur 3.0 software.

In the quantitative analysis of five marks, a Waters Xevo TQD UPLC-MS/MS system (Waters Corp., Milford, MA, USA) was employed. Chromatographic peaks were separated on a Waters ACQUITY UPLC® HSS C18 column (2.1 mm × 100 mm, 1.8 μm) at a flow rate of 0.2 mL/min with gradient acetonitrile (A) and water containing 10 mM ammonium acetate (B) as follows: 0–0.5 min, 5% A; 0.5–1.0 min, 5–20% A; 1–3.0 min, 20–30% A; 3.0–4.5 min, 30–100% A, 4.5–5.0 min, 100% A. A subsequent re-equilibration time (2 min) should be performed before next injection. The injection volume was 5 μL for analysis. The Waters Xevo TQD mass spectrometer with electrospray ion source (ESI) was used. The MS spectra were acquired in MRM mode using polarity switching. The capillary voltage was set to 3.5 kV, and the source temperature was maintained at 350 °C, nitrogen gas was used as desolvation gas 650 L/h and cone gas 50 L/h and argon gas was employed as collision gas. The most appropriate precursor-to-product ion pair, cone voltage (CV) and collision energy(CE) are listed in Table S3. All data was acquired and integrated by Masslynx V4.1 software.

Mass spectrometric conditions

Statistical data analysis

The fingerprinting was performed on different XBJ samples by SIEVE 2.0 software (Thermo Scientific, San Jose, USA), which was used for evaluating the similarities between different samples. The similarity was evaluated with the correlation coefficients, and the calculation of correlation coefficients was mainly based on the peak area and retention time. The base peak intensity chromatographic data obtained from the positive or negative ion UHPLC-Q-Orbitrap HRMS analyses were imported in the form of Xcalibur raw files into the SIEVE software. With SIEVE software, the chromatogram can be normalized, and the identical peaks in each chromatogram can be matched in automatic or manual mode. All the batches of XBJ samples were used to construct fingerprinting. Subsequently, the correlation coefficients of all introduced chromatograms relative to that of reference chromatogram would be calculated. In a word, the software made the analysis method accurate and rapid.

Principal component analysis (PCA) involves a mathematical procedure that transforms a number of possibly correlated variables into a smaller number of uncorrelated variables called principal components. This transformation is defined in such a way that the first principal component has as high a variance as possible or accounts for as much of the variability in the data as possible27. PCA is an unsupervised pattern recognition technique, which is a data visualization method useful for a rapid means of visualizing similarities or differences within multivariate data28. PCA makes it possible to represent objects or variables on a graph, with different objectives to study the proximity of objects in order to differentiate them and to detect atypical objects, and also to analyze the position of objects in varied representations. Thus, we could probably speculate the chemical components causing quality differences in different batches. The PCA was performed on different XBJ samples by SIMCA 14.0 software (Umetrics, Sweden).