bims-metlip Biomed News
on Methods and protocols in metabolomics and lipidomics
Issue of 2021‒01‒17
sixteen papers selected by
Sofia Costa
Cold Spring Harbor Laboratory


  1. Mass Spectrom Rev. 2021 Jan 12.
    Harkin C, Smith KW, Cruickshank FL, Logan Mackay C, Flinders B, Heeren RMA, Moore T, Brockbank S, Cobice DF.
      Mass spectrometry imaging (MSI) combines molecular and spatial information in a valuable tool for a wide range of applications. Matrix-assisted laser desorption/ionization (MALDI) is at the forefront of MSI ionization due to its wide availability and increasing improvement in spatial resolution and analysis speed. However, ionization suppression, low concentrations, and endogenous and methodological interferences cause visualization problems for certain molecules. Chemical derivatization (CD) has proven a viable solution to these issues when applied in mass spectrometry platforms. Chemical tagging of target analytes with larger, precharged moieties aids ionization efficiency and removes analytes from areas of potential isobaric interferences. Here, we address the application of CD on tissue samples for MSI analysis, termed on-tissue chemical derivatization (OTCD). MALDI MSI will remain the focus platform due to its popularity, however, alternative ionization techniques such as liquid extraction surface analysis and desorption electrospray ionization will also be recognized. OTCD reagent selection, application, and optimization methods will be discussed in detail. MSI with OTCD is a powerful tool to study the spatial distribution of poorly ionizable molecules within tissues. Most importantly, the use of OTCD-MSI facilitates the analysis of previously inaccessible biologically relevant molecules through the adaptation of existing CD methods. Though further experimental optimization steps are necessary, the benefits of this technique are extensive.
    Keywords:  chemical derivatization; mass spectrometry imaging; matrix-assisted laser desorption ionization
    DOI:  https://doi.org/10.1002/mas.21680
  2. Anal Chem. 2021 Jan 12.
    Zhang Y, Gao B, Valdiviez L, Zhu C, Gallagher T, Whiteson K, Fiehn O.
      Stable isotope tracers are applied for in vivo and in vitro studies to reveal the activity of enzymes and intracellular metabolic pathways. Most often, such tracers are used with gas chromatography coupled to mass spectrometry (GC-MS) owing to its ease of operation and reproducible mass spectral databases. Differences in isotope tracer performance of the classic GC-quadrupole MS instrument and newer time-of-flight instruments are not well studied. Here, we used three commercially available instruments for the analysis of identical samples from a stable isotope labeling study that used [U-13C6] d-glucose to investigate the metabolism of the bacterium Rothia mucilaginosa with respect to 29 amino acids and hydroxyl acids involved in primary metabolism. The prokaryote R. mucilaginosa belongs to the family of Micrococcaceae and is present and metabolically active in the airways and sputum of cystic fibrosis patients. Overall, all three GC-MS instruments (low-resolution GC-SQ MS, low-resolution GC-TOF MS, and high-resolution GC-QTOF MS) can be used to perform stable isotope tracing studies for glycolytic intermediates, tricarboxylic acid (TCA) metabolites, and amino acids, yielding similar biological results, with high-resolution GC-QTOF MS offering additional capabilities to identify the chemical structures of unknown compounds that might show significant isotope enrichments in biological studies.
    DOI:  https://doi.org/10.1021/acs.analchem.0c04013
  3. Mol Cell Proteomics. 2020 Jan;pii: S1535-9476(20)30014-1. [Epub ahead of print]19(1): 181-197
    Barkovits K, Pacharra S, Pfeiffer K, Steinbach S, Eisenacher M, Marcus K, Uszkoreit J.
      Currently data-dependent acquisition (DDA) is the method of choice for mass spectrometry-based proteomics discovery experiments, but data-independent acquisition (DIA) is steadily becoming more important. One of the most important requirements to perform a DIA analysis is the availability of suitable spectral libraries for peptide identification and quantification. Several studies were performed addressing the evaluation of spectral library performance for protein identification in DIA measurements. But so far only few experiments estimate the effect of these libraries on the quantitative level. In this work we created a gold standard spike-in sample set with known contents and ratios of proteins in a complex protein matrix that allowed a detailed comparison of DIA quantification data obtained with different spectral library approaches. We used in-house generated sample-specific spectral libraries created using varying sample preparation approaches and repeated DDA measurement. In addition, two different search engines were tested for protein identification from DDA data and subsequent library generation. In total, eight different spectral libraries were generated, and the quantification results compared with a library free method, as well as a default DDA analysis. Not only the number of identifications on peptide and protein level in the spectral libraries and the corresponding DIA analysis results was inspected, but also the number of expected and identified differentially abundant protein groups and their ratios. We found, that while libraries of prefractionated samples were generally larger, there was no significant increase in DIA identifications compared with repetitive non-fractionated measurements. Furthermore, we show that the accuracy of the quantification is strongly dependent on the applied spectral library and whether the quantification is based on peptide or protein level. Overall, the reproducibility and accuracy of DIA quantification is superior to DDA in all applied approaches. Data has been deposited to the ProteomeXchange repository with identifiers PXD012986, PXD012987, PXD012988 and PXD014956.
    Keywords:  Bioinformatics software; Label-free quantification; Mass Spectrometry; Quantification; Target identification; data-independent acquisition (DIA); peptide identification; proteomics; spectral library
    DOI:  https://doi.org/10.1074/mcp.RA119.001714
  4. J Chromatogr A. 2021 Jan 02. pii: S0021-9673(20)31136-5. [Epub ahead of print]1638 461862
    Reyes-Garcés N, Boyacı E, Gómez-Ríos GA, Olkowicz M, Monnin C, Bojko B, Vuckovic D, Pawliszyn J.
      This work presents an evaluation of solid-phase microextraction (SPME) SPME in combination with liquid chromatography-high resolution mass spectrometry (LC-HRMS) as an analytical approach for untargeted brain analysis. The study included a characterization of the metabolite coverage provided by C18, mixed-mode (MM, with benzene sulfonic acid and C18 functionalities), and hydrophilic lipophilic balanced (HLB) particles as sorbents in SPME coatings after extraction from cow brain homogenate at static conditions. The effects of desorption solvent, extraction time, and chromatographic modes on the metabolite features detected were investigated. Method precision and absolute matrix effects were also assessed. Among the main findings of this work, it was observed that all three tested coating chemistries were able to provide comparable brain tissue information. HLB provided higher responses for polar metabolites; however, as these fibers were prepared in-house, higher inter-fiber relative standard deviations were also observed. C18 and HLB coatings offered similar responses with respect to lipid-related features, whereas MM and C18 provided the best results in terms of method precision. Our results also showed that the use of methanol is essential for effective desorption of non-polar metabolites. Using a reversed-phase chromatographic method, an average of 800 and 1200 brain metabolite features detected in positive and negative modes, respectively, met inter-fibre RSD values below 30% (n=4) after removal of fibre and solvent artefacts from the associated datasets. For features detected using a lipidomics method, a total of 900 and 1800 features detected using C18 fibers in positive and negative mode, respectively, met the same criteria. In terms of absolute matrix effects, the majority of the model metabolites tested showed values between 80 and 120%, which are within the acceptable range. Overall, the findings of this work lay the foundation for further optimization of parameters for SPME-LC-HRMS methods suitable for in vivo and ex vivo brain (and other tissue) untargeted studies, and support the applicability of this approach for non-destructive tissue metabolomics.
    Keywords:  Biocompatible SPME; Brain metabolomics; In-vivo-SPME; LC-HRMS; Tissue metabolomics
    DOI:  https://doi.org/10.1016/j.chroma.2020.461862
  5. Sci Rep. 2021 Jan 15. 11(1): 1547
    Tian F, Qiao C, Wang C, Luo J, Guo L, Pang T, Li J, Wang R, Pang R, Xie H.
      A fast, sensitive, and reliable analytical method was developed and validated for simultaneous identification and quantification of spirodiclofen, spiromesifen, and spirotetramat and their relevant metabolites in edible fungi by ultra-performance liquid chromatography/tandem mass spectrometry (UHPLC-MS/MS). First, sample extraction was done with acetonitrile containing 1% formic acid followed by phase separation with the addition of MgSO4:NaOAc. Then, the supernatant was purified by primary secondary amine (PSA), octadecylsilane (C18), and graphitized carbon black (GCB). The linearities of the calibrations for all analytes were excellent (R2 ≥ 0.9953). Acceptable recoveries (74.5-106.4%) for all analytes were obtained with good intra- and inter- relative standard deviations of less than 14.5%. The limit of quantification (LOQs) for all analytes was 10 μg kg-1. For accurate quantification, matrix-matched calibration curve was applied to normalize the matrix effect. The results indicated that the method was suitable for detecting the three acaricides and their relevant metabolites in edible fungi.
    DOI:  https://doi.org/10.1038/s41598-021-81013-0
  6. Rapid Commun Mass Spectrom. 2021 Jan 15. e9045
    Abdrakhimov DA, Bubis JA, Gorshkov V, Kjeldsen F, Gorshkov MV, Ivanov MV.
      RATIONALE: One of the important steps in initial data processing of peptide mass spectra is the detection of peptide features in full-range mass spectra. Ion mobility offers advantages over previous methods performing this detection by providing additional structure-specific separation dimension. However, there is a lack of open-source software, which utilizes these advantages and detects peptide features in mass spectra acquired along with the ion mobility data using new instruments such as timsTOF and/or FAIMS-Orbitrap.METHODS: Recently, a utility called Dinosaur was presented, which provides an efficient way for feature detection in peptide ion mass spectra. In this work we extended its functionality by developing Biosaur software to fully employ the additional information provided by ion mobility data. Biosaur was developed using the Python 3.8 programming language.
    RESULTS: Biosaur supports the processing of data acquired using mass spectrometers with ion mobility capabilities, specifically timsTOF and FAIMS. In addition, it processes mass spectra obtained in negative ion mode and reports cosine correlation table for peptide features which is useful for differentiation between in-source fragments and semi-tryptic peptides.
    CONCLUSIONS: Biosaur is a utility for detecting peptide features in LC/MS spectra with ion mobility and negative ion supports. The software is distributed with an open source APACHE 2.0 licence and freely available on Github at the following link https://github.com/abdrakhimov1/Biosaur.
    DOI:  https://doi.org/10.1002/rcm.9045
  7. Eur J Pharm Sci. 2021 Jan 09. pii: S0928-0987(21)00007-5. [Epub ahead of print] 105705
    Mohamed MK, Takyi-Williams J, Baudot B, Grobler A.
      The resurgence of Cannabis therapeutic discoveries have led to the need for sensitive and selective analytical methods for the detection of cannabinoids and their metabolites in biological matrices. High resolution mass spectrometry (HRMS) enables good sensitivity and provides more selectivity due to its accurate mass measurement of the targeted compounds. The aim of this study was to develop and validate a sensitive liquid chromatography high resolution mass spectrometry (LC-HRMS) method for the quantitative analysis of cannabidiol (CBD), cannabinol (CBN), Δ9-tetrahydrocannabinol (Δ9-THC) and its major metabolites 11-Hydroxy-Δ9-THC and 11-Nor-9-carboxy-Δ9-THC in human plasma. The method utilized a simple liquid-liquid extraction of the cannabinoids from plasma samples followed by an isocratic chromatographic separation and detection by ESI-HRMS Q-Exactive plus platform. The lower limit of quantification (LLOQ) was 0.2 ng/ mL for the targeted cannabinoids and its metabolites with sample volume of 0.5 mL plasma. The method was linear from 0.2 to 100.0 ng/mL with an average correlation coefficient of >0.995 using weighted (1/x) linear least-squares regression. No significant carry-over was noticed for all analytes and the extraction recovery ranged from 60.4 % to 85.4 %. Dilution results indicated no influence on the accuracy of analysis. The method's intra-day and inter-day precision (CV %) ranged from 2.90 to 10.80 % and accuracy within -0.9 to 7.0 from nominal. Matrix effect ranged from 1.1 % to 49.8 %. The analytes were stable in the autosampler for 6 and 12 h, respectively. This method was sensitive and can be applicable to cannabinoids pharmacokinetics study.
    Keywords:  Cannabinoids; Human plasma; LC-HRMS; Method validation; Orbitrap
    DOI:  https://doi.org/10.1016/j.ejps.2021.105705
  8. J Chromatogr B Analyt Technol Biomed Life Sci. 2020 Dec 28. pii: S1570-0232(20)31393-3. [Epub ahead of print]1163 122517
    Loh GOK, Wong EYL, Tan YTF, Ong LM, Ng RS, Wee HC, Peh KK.
      A simple, fast and sensitive LC-MS/MS method was developed to quantify terazosin in human plasma. The mobile phase consisted of acetonitrile-0.1% (v/v) formic acid (70:30, v/v). Prazosin was used as internal standard (IS). As deproteinization agent, acetonitrile produced a clean sample. A higher response intensity with more symmetrical peak was obtained using Agilent Poroshell 120 EC-C18 - Fast LC column (100 × 2.1mmID, 2.7 μm) compared with Kinetex XB-C18 (100 × 2.1 mm, 2.6 µm) column. The response of terazosin and IS were approximately two times in citrate phosphate dextrose (CPD) plasma compared with dipotassium ethylenediaminetetraacetic acid (K2EDTA) plasma. Plasma calibration curve was linear from 1.0 to 100.0 ng/mL, with coefficient of determination r2 ≥ 0.99. The within-run and between-run precision values (CV, %) were <5.2% and <7.8%, while accuracy values were 102.8-112.7% and 103.4-112.2%. The extended run accuracy was 98.6-102.8% and precision (CV, %) 4.3-10.4%. The recovery of analyte was >98% and IS >94%. Terazosin in plasma kept at benchtop was stable for 24 h, in autosampler tray for 48 h, in instrumentation room for 48 h, for 7 freeze-thaw cycles and in freezer for 140 days. Terazosin and IS stock standard solutions were stable for 140 days at room temperature and in the chiller. The high throughput method was successfully utilized to measure 935 samples in a bioequivalence study of terazosin.
    Keywords:  LC-MS/MS; Plasma; Prazosin; Protein precipitation; Terazosin
    DOI:  https://doi.org/10.1016/j.jchromb.2020.122517
  9. J Cheminform. 2020 Jul 22. 12(1): 45
    Baquer G, Sementé L, García-Altares M, Lee YJ, Chaurand P, Correig X, Ràfols P.
      Mass spectrometry imaging (MSI) has become a mature, widespread analytical technique to perform non-targeted spatial metabolomics. However, the compounds used to promote desorption and ionization of the analyte during acquisition cause spectral interferences in the low mass range that hinder downstream data processing in metabolomics applications. Thus, it is advisable to annotate and remove matrix-related peaks to reduce the number of redundant and non-biologically-relevant variables in the dataset. We have developed rMSIcleanup, an open-source R package to annotate and remove signals from the matrix, according to the matrix chemical composition and the spatial distribution of its ions. To validate the annotation method, rMSIcleanup was challenged with several images acquired using silver-assisted laser desorption ionization MSI (AgLDI MSI). The algorithm was able to correctly classify m/z signals related to silver clusters. Visual exploration of the data using Principal Component Analysis (PCA) demonstrated that annotation and removal of matrix-related signals improved spectral data post-processing. The results highlight the need for including matrix-related peak annotation tools such as rMSIcleanup in MSI workflows.
    Keywords:  Mass spectrometry imaging; Matrix annotation; Overlapping-signal detection; Silver-assisted laser/desorption ionization; Spatial metabolomics; Spectral processing
    DOI:  https://doi.org/10.1186/s13321-020-00449-0
  10. J Vis Exp. 2020 Dec 22.
    Veerasammy K, Chen YX, Sauma S, Pruvost M, Dansu DK, Choetso T, Zhong T, Marechal D, Casaccia P, Abzalimov R, He Y.
      Metabolomics, the study to identify and quantify small molecules and metabolites present in an experimental sample, has emerged as an important tool to investigate the biological activities during development and diseases. Metabolomics approaches are widely employed in the study of cancer, nutrition/diet, diabetes, and other physiological and pathological conditions involving metabolic processes. An advantageous tool that aids in metabolomic profiling advocated in this paper is matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI). Its ability to detect metabolites in situ without labeling, structural modifications, or other specialized reagents, such as those used in immunostaining, makes MALDI MSI a unique tool in advancing methodologies relevant in the field of metabolomics. An appropriate sample preparation process is critical to yield optimal results and will be the focus of this paper.
    DOI:  https://doi.org/10.3791/62008
  11. Mol Cell Proteomics. 2020 Jun;pii: S1535-9476(20)34991-4. [Epub ahead of print]19(6): 960-970
    Gularyan SK, Gulin AA, Anufrieva KS, Shender VO, Shakhparonov MI, Bastola S, Antipova NV, Kovalenko TF, Rubtsov YP, Latyshev YA, Potapov AA, Pavlyukov MS.
      Glioblastoma (GBM) is one of the most aggressive human cancers with a median survival of less than two years. A distinguishing pathological feature of GBM is a high degree of inter- and intratumoral heterogeneity. Intertumoral heterogeneity of GBM has been extensively investigated on genomic, methylomic, transcriptomic, proteomic and metabolomics levels, however only a few studies describe intratumoral heterogeneity because of the lack of methods allowing to analyze GBM samples with high spatial resolution. Here, we applied TOF-SIMS (Time-of-flight secondary ion mass spectrometry) for the analysis of single cells and clinical samples such as paraffin and frozen tumor sections obtained from 57 patients. We developed a technique that allows us to simultaneously detect the distribution of proteins and metabolites in glioma tissue with 800 nm spatial resolution. Our results demonstrate that according to TOF-SIMS data glioma samples can be subdivided into clinically relevant groups and distinguished from the normal brain tissue. In addition, TOF-SIMS was able to elucidate differences between morphologically distinct regions of GBM within the same tumor. By staining GBM sections with gold-conjugated antibodies against Caveolin-1 we could visualize border between zones of necrotic and cellular tumor and subdivide glioma samples into groups characterized by different survival of the patients. Finally, we demonstrated that GBM contains cells that are characterized by high levels of Caveolin-1 protein and cholesterol. This population may partly represent a glioma stem cells. Collectively, our results show that the technique described here allows to analyze glioma tissues with a spatial resolution beyond reach of most of other omics approaches and the obtained data may be used to predict clinical behavior of the tumor.
    Keywords:  Glioblastoma; TOF-SIMS; cancer biomarker(s); caveolin-1; glioma; imaging visualization tools; mass spectrometry; stem cells
    DOI:  https://doi.org/10.1074/mcp.RA120.001986
  12. Metabolites. 2021 Jan 11. pii: E46. [Epub ahead of print]11(1):
    Kokotou MG, Batsika CS, Mantzourani C, Kokotos G.
      Oxidized saturated fatty acids, containing a hydroxyl or an oxo functionality, have attracted little attention so far. Recent studies have shown that saturated hydroxy fatty acids, which exhibit cancer cell growth inhibition and may suppress β-cell apoptosis, are present in milk. Herein, we present the application of a liquid chromatography-high-resolution mass spectrometry (LC-HRMS) method for the detection and quantification of various saturated oxo fatty acids (SOFAs) previously unrecognized in milk. This robust and rapid analytical method, which involves simple sample preparation and a single 10-min run, revealed the presence of families of oxostearic acids (OSAs) and oxopalmitic acids (OPAs) in milk. 8OSA, 9OSA, 7OSA, 10OSA and 10OPA were found to be the most abundant SOFAs in both cow and goat milk. Higher contents of SOFAs were found in cow milk in comparison to goat milk. Together with SOFAs, ricinoleic acid, which is isobaric to OSA, was detected and quantified in all milk samples, following a "suspect" HRMS analysis approach. This unique natural fatty acid, which is the main component (>90%) of castor oil triglycerides, was estimated at mean content values of 534.3 ± 6.0 μg/mL and 460 ± 8.1 μg/mL in cow and goat milk samples, respectively.
    Keywords:  determination; high-resolution mass spectrometry; liquid chromatography; milk; oxo fatty acids
    DOI:  https://doi.org/10.3390/metabo11010046
  13. J Pharm Biomed Anal. 2021 Jan 07. pii: S0731-7085(20)31733-7. [Epub ahead of print]195 113846
    Masike K, Stander MA, de Villiers A.
      Ion mobility spectrometry (IMS) is a rapid separation technique capable of extracting complementary structural information to chromatography and mass spectrometry (MS). IMS, especially in combination with MS, has experienced inordinate growth in recent years as an analytical technique, and elicited intense interest in many research fields. In natural product analysis, IMS shows promise as an additional tool to enhance the performance of analytical methods used to identify promising drug candidates. Potential benefits of the incorporation of IMS into analytical workflows currently used in natural product analysis include the discrimination of structurally similar secondary metabolites, improving the quality of mass spectral data, and the use of mobility-derived collision cross-section (CCS) values as an additional identification criterion in targeted and untargeted analyses. This review aims to provide an overview of the application of IMS to natural product analysis over the last six years. Instrumental aspects and the fundamental background of IMS will be briefly covered, and recent applications of the technique for natural product analysis will be discussed to demonstrate the utility of the technique in this field.
    Keywords:  Gas chromatography (GC); Ion mobility spectrometry (IMS); Liquid chromatography (LC); Mass spectrometry; Natural products; Secondary metabolites
    DOI:  https://doi.org/10.1016/j.jpba.2020.113846
  14. J Chromatogr Sci. 2021 Jan 13. pii: bmaa136. [Epub ahead of print]
    Tantawy MA, Hassan AM, Hegazy MA, Kelani KM.
      In a contribution to stability profiling of the recent antidiabetic drug, omarigliptin (OMR), two stability-indicating chromatographic methods were developed and validated. Stability profiling was performed for OMR under different stress conditions as acidic, alkaline, oxidative, photolytic and thermal degradations. Structures elucidation to all formed degradation products were identified using IR and mass spectrometry. Thin Layer Chromatography (TLC) and High-Performance Liquid Chromatography (HPLC) were used. In TLC-densitometric method, aluminum TLC plates precoated with silica gel G.F254 were used as stationary phase along with methanol: ethyl acetate: 33% ammonia (2:8:1,v/v/v) as mobile phase. The obtained chromatograms were scanned at 254 nm over concertation range of 5-70 μg band-1 for OMR. The second chromatographic method was an HPLC one with diode array detection and RP-C18 column with isocratic elution. Mobile phase used was composed of phosphate buffer pH 3.5: acetonitrile (80, 20, v/v), delivered at flow rate of 1.0 mL min-1. Diode array detector was adjusted at 230 nm with linearity range of 15-180 μg mL-1 for OMR. Several factors affecting TLC and HPLC efficiency have been carefully studied. The developed methods were validated according to International Conference on Harmonization guidelines and successfully applied for assessment of OMR in bulk powder and tablets.
    DOI:  https://doi.org/10.1093/chromsci/bmaa136
  15. Anal Chem. 2021 Jan 15.
    Sands CJ, Gómez-Romero M, Correia G, Chekmeneva E, Camuzeaux S, Izzi-Engbeaya C, Dhillo WS, Takats Z, Lewis MR.
      Liquid chromatography-mass spectrometry (LC-MS) is a powerful and widely used technique for measuring the abundance of chemical species in living systems. Its sensitivity, analytical specificity, and direct applicability to biofluids and tissue extracts impart great promise for the discovery and mechanistic characterization of biomarker panels for disease detection, health monitoring, patient stratification, and treatment personalization. Global metabolic profiling applications yield complex data sets consisting of multiple feature measurements for each chemical species observed. While this multiplicity can be useful in deriving enhanced analytical specificity and chemical identities from LC-MS data, data set inflation and quantitative imprecision among related features is problematic for statistical analyses and interpretation. This Perspective provides a critical evaluation of global profiling data fidelity with respect to measurement linearity and the quantitative response variation observed among components of the spectra. These elements of data quality are widely overlooked in untargeted metabolomics yet essential for the generation of data that accurately reflect the metabolome. Advanced feature filtering informed by linear range estimation and analyte response factor assessment is advocated as an attainable means of controlling LC-MS data quality in global profiling studies and exemplified herein at both the feature and data set level.
    DOI:  https://doi.org/10.1021/acs.analchem.0c03848
  16. Biomed Chromatogr. 2021 Jan 15. e5068
    Hosseini ES, Tabar Heydar K.
      A modified C18 column (Silpr-2MI-C18) was prepared using 2-methylindole and C18 reagent. The extent of C18 hydrocarbon chain, conjugative rings and anion exchange site provided multiple retention mechanisms, including reversed phase liquid chromatography (RPLC), π-π interaction, hydrophilic interaction liquid chromatography (HILIC) and anion exchange chromatography (AEC). The separation of protected amino acids was investigated on the commercial C18 and Silpr-2MI-C18 columns, while the chromatographic conditions, including methanol content and pH of the mobile phase, were studied. The separation arrangement of the hydrophilic amino acids was different on Silpr-2MI-C18 column compared to the commercial C18 column under RPLC mode. Furthermore, these amino acids were separated on the Silpr-2MI-C18 column under HILIC mode. The modified C18 column was employed to separate amino acids, alkylbenzenes, polycyclic aromatic hydrocarbons (PAHs) under RPLC mode and inorganic anion under AEC mode. The results confirm that this new stationary phase of RPLC/HILIC/AEC has multiple interactions with different analytes. The effective retention of biological sample was found on the Silpr-2MI-C18 column by comparing the results obtained from the commercial C18 column.
    Keywords:  2-methylindole; Amino acids and RPLC/HILIC/AEC mode; Mixed-Mode chromatography (MMC); Multiple interactions
    DOI:  https://doi.org/10.1002/bmc.5068