Novel Peak Shift Correction Method Based on the Retention Index for Peak Alignment in Untargeted Metabolomics.

Peak alignment is a crucial step in liquid chromatography-mass spectrometry (LC-MS)-based large-scale untargeted metabolomics workflows, as it enables the integration of metabolite peaks across multiple samples, which is essential for accurate data interpretation. Slight differences or fluctuations in chromatographic separation conditions, however, can cause the chromatographic retention time (RT) shift between consecutive analyses, ultimately affecting the accuracy of peak alignment between samples. Here, we introduce a novel RT shift correction method based on the retention index (RI) and apply it to peak alignment. We synthesized a series of N-acyl glycine (C2-C23) homologues via the amidation reaction between glycine with normal saturated fatty acids (C2-C23) as calibrants able to respond proficiently in both mass spectrometric positive- and negative-ion modes. Using these calibrants, we established an N-acyl glycine RI system. This RI system is capable of covering a broad chromatographic space and addressing chromatographic RT shift caused by variations in flow rate, gradient elution, instrument systems, and LC separation columns. Moreover, based on the RI system, we developed a peak shift correction model to enhance peak alignment accuracy. Applying the model resulted in a significant improvement in the accuracy of peak alignment from 15.5 to 80.9% across long-term data spanning a period of 157 days. To facilitate practical application, we developed a Python-based program, which is freely available at https://github.com/WHU-Fenglab/RI-based-CPSC.

Uncovering the Carboxylated Metabolome in Gut Microbiota-Host Co-metabolism: A Chemical Derivatization-Molecular Networking Approach.

Gut microbiota-host co-metabolites serve as essential mediators of communication between the host and gut microbiota. They provide nutrient sources for host cells and regulate gut microenvironment, which are associated with a variety of diseases. Analysis of gut microbiota-host co-metabolites is of great significance to explore the host-gut microbiota interaction. In this study, we integrated chemical derivatization, liquid chromatography-mass spectrometry, and molecular networking (MN) to establish a novel CD-MN strategy for the analysis of carboxylated metabolites in gut microbial-host co-metabolism. Using this strategy, 261 carboxylated metabolites from mouse feces were detected, which grouped to various classes including fatty acids, bile acids, N-acyl amino acids, benzoheterocyclic acids, aromatic acids, and other unknown small-scale molecular clusters in MN. Based on the interpretation of the bile acid cluster, a novel type of phenylacetylated conjugates of host bile acids was identified, which were mediated by gut microbiota and exhibited a strong binding ability to Farnesoid X receptor and Takeda G protein-coupled receptor 5. Our proposed strategy offers a promising platform for uncovering carboxylated metabolites in gut microbial-host co-metabolism.

Phyllosphere fungal communities of rubber trees exhibited biogeographical patterns, but not bacteria.

Phyllosphere microbiomes play an essential role in maintaining host health and productivity. Still, the diversity patterns and the drivers for the phyllosphere microbial community of the tropical cash crop Rubber tree (Hevea brasiliensis) - are poorly understood. We sampled the phyllosphere of field-grown rubber trees in South China. We examined the phyllosphere bacterial and fungal composition, diversity and main drivers of these microbes using the Illumina® sequencing and assembly. Fungal communities were distinctly different in different climatic regions (i.e. Xishuangbanna and Hainan Island) and climatic factors, especially mean annual temperature, and they were the main driving factors of foliar fungal communities, indicating fungal communities showed a geographical pattern. Significant differences of phyllosphere bacterial communities were detected in different habitats (i.e. endophytic and epiphytic). Most of the differences in taxa composition came from Firmicutes spp., which have been assigned as nitrogen-fixing bacteria. Since these bacteria cannot penetrate the cuticle like fungi, the abundant epiphytic Firmicutes spp. may supplement the deficiency of nitrogen acquisition. And the main factor influencing endophytic bacteria were internal factors, such as total nitrogen, total phosphorus and water content of leaves. External factors (i.e. climate) were the main driving force for epiphytic bacteria community assembly. Our work provides empirical evidence that the assembly of phyllosphere bacterial and fungal differed, which creates a precedent for preventing and controlling rubber tree diseases and pests and rubber tree yield improvement.

Alternating Dual-Collision Energy Scanning Mass Spectrometry Approach: Discovery of Novel Microbial Bile-Acid Conjugates.

Bile acids (BAs) are a type of gut microbiota-host cometabolites with abundant structural diversity, and they play critical roles in maintaining host-microbiota homeostasis. In this study, we developed a new N-(4-aminomethylphenyl) pyridinium (AMPP) derivatization-assisted alternating dual-collision energy scanning mass spectrometry (AMPP-dual-CE MS) method for the profiling of BAs derived from host-gut microbiota cometabolism in mice. Using the proposed method, we discovered two new types of amino acid conjugations (alanine conjugation and proline conjugation) and acetyl conjugation with host BAs, for the first time, from mouse intestine contents and feces. Additionally, we also determined and identified nine new leucine- and phenylalanine-conjugated BAs. These findings broaden our knowledge of the composition of the BA pool and provide insight into the mechanism of host-gut microbiota cometabolism of BAs.

Gene commander in the trash heap: Transcriptional regulation and ubiquitination modification mediated by RNF6 in carcinogenesis.

RING finger protein 6 (RNF6), a RING finger protein, has been identified as a potential tumor promoter in several cancers. However, the exact mechanism of RNF6 in cancer remains elusive. As in various diseases, RNF6 may be involved in regulating cell growth, cell proliferation, invasion, cell cycle progression, apoptosis and cell adhesion through E3 ligase-mediated ubiquitination. Thus, the research on RNF6 is mainly focused on the ubiquitination of RNF6 in recent years. This article summarizes the role of RNF6 ubiquitination in various physiological and pathological mechanisms, such as Akt/mTOR signaling pathway, Wnt/ß-catenin pathway, RNF6/ERα/Bcl-xL axis, and provides knowledge and understanding for the treatment of diseases.

Rapid and Economical Chemoselective Metabolomics Using Boronate Ester Formation on a Monolithic Substrate.

Although chemoselective labeling strategies show great potential in in-depth description of metabolomics, the associated time and expense limit applications in high-throughput and routine analysis. We report a fast and effective chemoselective labeling strategy based on multifunctionalized monolithic probes. A rapid pH-responsive boronate ester reaction was employed to immobilize and release probe molecules from substrate in 5 min. The mesoporous surface and hierarchically porous channels of the substrate allowed for accelerated labeling reactions. Moreover, the discernible boron beacons allowed for recognition of labeled metabolites with no need for expensive isotopic encoding. This new strategy has been successfully used for submetabolome analysis of yeast cells, serum, and faeces samples, with improved sensitivity for short chain fatty acids up to 1 600 times compared with non-labeled liquid chromatography-mass spectrometry (LC-MS) methods.

Screening and Identification of Epoxy/Dihydroxy-Oxylipins by Chemical Labeling-Assisted Ultrahigh-Performance Liquid Chromatography Coupled with High-Resolution Mass Spectrometry.

Epoxy/dihydroxy-oxylipins are important biologically active compounds that are mainly formed from polyunsaturated fatty acids (PUFAs) in the reactions catalyzed by the cytochrome P450 (CYP 450) enzyme. The analysis of epoxy/dihydroxy-oxylipins would be helpful to gain insights into their landscape in living organisms and provide a reference for the biological studies of these compounds. In this work, we employed chemical labeling-assisted liquid chromatography (LC) coupled with high-resolution mass spectrometry (CL-LC-HRMS) to establish a highly sensitive and specific method for screening and annotating epoxy/dihydroxy-oxylipins in biological samples. The isotope reagents 2-dimethylaminoethylamine (DMED) and DMED-d4 were employed to label epoxy/dihydroxy-oxylipins containing carboxyl groups so as to improve the analysis selectivity and MS detection sensitivity of epoxy/dihydroxy-oxylipins. Based on a pair of diagnostic ions with a mass-to-charge ratio (m/z) difference of 15.995 originating from the fragmentation of derivatives via high-energy collision dissociation (HCD), the potential epoxy/dihydroxy-oxylipins were rapidly screened from the complex matrix. Furthermore, the epoxy/dihydroxy groups could be readily localized by the diagnostic ion pairs, which enabled us to accurately annotate the epoxy/dihydroxy-oxylipins detected in biological samples. The applicability of our method was demonstrated by profiling epoxy/dihydroxy-oxylipins in human serum and heart samples from mice with high-fat diet (HFD). By the proposed method, a total of 32 and 62 potential epoxy/dihydroxy-oxylipins including 42 unreported ones were detected from human serum and the mice heart sample, respectively. Moreover, the relative quantitative results showed that most of the potential epoxy/dihydroxy-oxylipins, especially the oxidation products of linoleic acid (LA) or α-linolenic acid (ALA), were significantly decreased in the heart of mice with HFD. Our developed method is of high specificity and sensitivity and thus is a promising tool for the identification of novel epoxy/dihydroxy-oxylipins in biological samples.

Boron Isotope Tag-Assisted Ultrahigh-Performance Liquid Chromatography Coupled with High-Resolution Mass Spectrometry for Discovery and Annotation of cis-Diol-Containing Metabolites.

cis-Diol-containing metabolites are widely distributed in living organisms, and they participate in the regulation of various important biological activities. The profiling of cis-diol-containing metabolites could help us in fully understanding their functions. In this work, based on the characteristic isotope pattern of boron, we employed a boronic acid reagent as the isotope tag to establish a sensitive and selective liquid chromatography-high-resolution mass spectrometry method for the screening and annotation of cis-diol-containing metabolites in biological samples. Boronic acid reagent 2-methyl-4-phenylaminomethylphenylboronic acid was used to label the cis-diol-containing metabolites in biological samples to improve the selectivity and MS sensitivity of cis-diol-containing metabolites. Based on the characteristic 0.996 Da mass difference of precursor ions and the peak intensity ratio of 1:4 originating from 10B and 11B natural isotopes, the potential cis-diol-containing metabolites were rapidly screened from biological samples. Potential cis-diol-containing metabolites were annotated by database searching and analysis of fragmentation patterns obtained by multistage MS (MSn) via collision-induced dissociation. Importantly, the cis-diol position could be readily resolved by the MS3 spectrum. With this method, a total of 45 cis-diol-containing metabolites were discovered in rice, including monoglycerides, polyhydroxy fatty acids, fatty alcohols, and so forth. Furthermore, the established method showed superiority in avoiding false-positive results in profiling cis-diol-containing metabolites.

Integration of Chemical Derivatization and in-Source Fragmentation Mass Spectrometry for High-Coverage Profiling of Submetabolomes.

In-source fragmentation-based high-resolution mass spectrometry (ISF-HRMS) is a potential analytical technique, which is usually used to profile some specific compounds that can generate diagnostic neutral loss (NL) or fragment ion (FI) in ion source inherently. However, the ISF-HRMS method does not work for those compounds that cannot inherently produce diagnostic NL or FI in ion source. In this study, a derivatization-based in-source fragmentation-information-dependent acquisition (DISF-IDA) strategy was proposed for profiling the metabolites with easily labeled functional groups (submetabolomes) by liquid chromatography-electrospray ionization-quadrupole time-of-flight mass spectrometry (LC-ESI-Q-TOF MS). As a proof-of-concept study, 36 carboxylated compounds labeled with N,N-dimethylethylenediamine (DMED) were selected as model compounds to examine performance of DISF-IDA strategy in screening the carboxylated metabolites and acquiring their MSn spectra. In ESI source, the DEMD-derived carboxylated compounds were fragmented to produce characteristic neutral losses of 45.0578, 63.0684, and/or 88.1000 Da that were further used as diagnostic features for screening the carboxylated metabolites by DISF-IDA-based LC-Q-TOF MS. Furthermore, high-resolution MSn spectra of the model compounds were also obtained within a single run of DISF-IDA-based LC-Q-TOF MS analysis, which contributed to the improvement of the annotation confidence. To further verify its applicability, DISF-IDA strategy was used for profiling carboxylated submetabolome in mice feces. Using this strategy, a total of 351 carboxylated metabolites were detected from mice feces, of which 178 metabolites (51% of the total) were positively or putatively identified. Moreover, DISF-IDA strategy was also demonstrated to be applicable for profiling other submetabolomes with easily labeled functional groups such as amino, carbonyl, and cis-diol groups. Overall, our proposed DISF-IDA strategy is a promising technique for high-coverage profiling of submetabolomes with easily labeled functional groups in biological samples.

Breast cancer prognosis signature: linking risk stratification to disease subtypes.

Breast cancer is a very complex and heterogeneous disease with variable molecular mechanisms of carcinogenesis and clinical behaviors. The identification of prognostic risk factors may enable effective diagnosis and treatment of breast cancer. In particular, numerous gene-expression-based prognostic signatures were developed and some of them have already been applied into clinical trials and practice. In this study, we summarized several representative gene-expression-based signatures with significant prognostic value and separately assessed their ability of prognosis prediction in their originally targeted populations of breast cancer. Notably, many of the collected signatures were originally designed to predict the outcomes of estrogen receptor positive (ER+) patients or the whole breast cancer cohort; there are no typical signatures used for the prognostic prediction in a specific population of patients with the intrinsic subtype. We thus attempted to identify subtype-specific prognostic signatures via a computational framework for analyzing multi-omics profiles and patient survival. For both the discovery and an independent data set, we confirmed that subtype-specific signature is a strong and significant independent prognostic factor in the corresponding cohort. These results indicate that the subtype-specific prognostic signature has a much higher resolution in the risk stratification, which may lead to improved therapies and precision medicine for patients with breast cancer.

CellMarker: a manually curated resource of cell markers in human and mouse.

One of the most fundamental questions in biology is what types of cells form different tissues and organs in a functionally coordinated fashion. Larger-scale single-cell sequencing and biology experiment studies are now rapidly opening up new ways to track this question by revealing substantial cell markers for distinguishing different cell types in tissues. Here, we developed the CellMarker database (http://biocc.hrbmu.edu.cn/CellMarker/ or http://bio-bigdata.hrbmu.edu.cn/CellMarker/), aiming to provide a comprehensive and accurate resource of cell markers for various cell types in tissues of human and mouse. By manually curating over 100 000 published papers, 4124 entries including the cell marker information, tissue type, cell type, cancer information and source, were recorded. At last, 13 605 cell markers of 467 cell types in 158 human tissues/sub-tissues and 9148 cell makers of 389 cell types in 81 mouse tissues/sub-tissues were collected and deposited in CellMarker. CellMarker provides a user-friendly interface for browsing, searching and downloading markers of diverse cell types of different tissues. Furthermore, a summarized marker prevalence in each cell type is graphically and intuitively presented through a vivid statistical graph. We believe that CellMarker is a comprehensive and valuable resource for cell researches in precisely identifying and characterizing cells, especially at the single-cell level.

Identifying bifurcated paths with differential function impact in glioblastomas evolution.

The evolutionary dynamics of human cancers has been investigated popularly and several bifurcated paths in cancer evolutionary trajectories are revealed to be with differential outcomes and phenotypes. However, whether such bifurcated paths exist in glioblastoma (GBM) remains unclear. In 385 GBM samples, through determining the clonal status of cancer driver events and inferring their temporal order, we constructed a temporal map of evolutionary trajectories at the patient population level. By investigating the differential impact on clinical outcome, we identified four key bifurcated paths, namely, "chromosome 10 copy number loss (ie, 10 loss) → chromosome 19 copy number gain (ie, 19 gain): 10 loss → 13q loss"; "10 loss → 19 gain: 10 loss → 15q loss"; "10 loss → 19 gain: 10 loss → 6q loss" and "10 loss → 19 gain: 10 loss → 16q loss". They formed a core multibranches path, with 10 loss being regarded as the common earliest event followed by 19 gain and four other departure events (13q loss, 15q loss, 6q loss and 16q loss), which may account for their difference in genome instability and patient survival time. Compared to "10 loss → 19 gain", the patients with "10 loss → 13q loss" had higher telomerase activity. Notably, there were obvious discrepancies in immune activity and immune cell infiltration level between patients with "10 loss → 13q/16q loss" and "10 loss → 19 gain", highlighting the bifurcated paths' effect on tumor immune microenvironment. In summary, our study identifies four key bifurcated paths in GBM for the first time, suggesting the feasibility of patient stratification and prognosis prediction based on key bifurcated paths.

Combination of multiple tumor-infiltrating immune cells predicts clinical outcome in colon cancer.

The infiltration of immune cells is highly associated with the development and progression of cancer. Thus, integrating the immune cell infiltrating profile into an immune cell infiltrating score may predict the survival of cancer patients. Here, by combining the infiltration proportion of 22 immune cells inferred from bulk tumor transcriptome of 879 patients, we identified an immune cell infiltrating indicator including five types of immune cells: resting T cells CD4 memory, macrophages M0-M2, and activated mast cells. The signature distinguished patients into two groups (high-risk and low-risk) with significantly different survival in the training cohort (HR = 1.96, 95% CI = 1.29-2.98, P = .0013) and two additional cohorts (HR = 1.78, 95%, CI = 1.16-2.75, P = .0079 and HR = 2.01, 95% CI = 1.28-3.14, P = .0019). The indicator remained as an independent prognostic factor after adjusting for clinicopathological factors by multivariable analysis in all cohorts. Stratification analysis showed that the signature consistently and significantly predicted survival of high-stage colon cancer patients in the training cohort (P = .00053) and validation cohorts (P = .017 and P = .0035). Moreover, we found that the low-risk patients were significantly correlated with deficient mismatch repair and the high-risk patients had a weak ability of trafficking of immune cells to tumors in the cancer immunity cycle. Overall, our results showed that integrating multiple tumor-infiltrating immune cells was an effective strategy for uncovering robust prognostic factor for tumor patients, and potentially was a promising response marker for precision oncology to be explored.

In-Depth Annotation Strategy of Saturated Hydroxy Fatty Acids Based on Their Chromatographic Retention Behaviors and MS Fragmentation Patterns.

Hydroxy fatty acids are a class of bioactive compounds in a variety of organisms. The identification of hydroxy fatty acids in biological samples has still been a challenge because of their low abundance, high structural similarity, and limited availability of authentic hydroxy fatty acid standards. Here, we present a strategy for the annotation of saturated monohydroxyl fatty acids (OH-FAs) based on the integration of chromatographic retention rules and MS2 fragmentation patterns. Thirty-nine authentic OH-FA standards were used to investigate their retention behavior on a reversed-phase stationary phase (C18) of liquid chromatography, and we found that their retention simultaneously follows two kinds of "carbon number rules". Using the "carbon number rules", the retention index (RI) of all OH-FAs that contain carbon numbers from 8 to 18 (C8-18) can be predicted. Additionally, by studying the MS2 fragmentation of OH-FAs under collision-induced dissociation, we found that the intensity ratio (IR) of the characteristic fragment ions ([M + H]+-63 and [M + H]+-45) is closely related to the position of the hydroxyl group on the OH-FA structure, which is helpful to further identify and confirm the OH-FA isomers. As a result, 97 of 107 potential OH-FAs detected in honey, human serum, and rice seedling by chemical isotope labeling-assisted liquid chromatography-mass spectrometry were annotated upon the RI matching and IR confirming. Furthermore, in order to simplify the annotation process of OH-FAs, we constructed an OH-FA library to facilitate the annotation of OH-FAs. Overall, this study provides a new and promising tool for the in-depth annotation of OH-FA isomers.

In-Silico-Generated Library for Sensitive Detection of 2-Dimethylaminoethylamine Derivatized FAHFA Lipids Using High-Resolution Tandem Mass Spectrometry.

Fatty acid esters of hydroxy fatty acids (FAHFAs) are a family of recently discovered lipids with important physiological functions in mammals and plants. However, low detection sensitivity in negative ionization mode mass spectrometry makes low-abundance FAHFA challenging to analyze. A 2-dimethylaminoethylamine (DMED) based chemical derivatization strategy was recently reported to improve the MS sensitivity of FAHFAs by labeling FAHFAs with a positively ionizable tertiary amine group. To facilitate reliable, high-throughput, and automatic annotation of these compounds, a DMED-FAHFA in silico library containing 4290 high-resolution tandem mass spectra covering 264 different FAHFA classes was developed. The construction of the library was based on the heuristic information from MS/MS fragmentation patterns of DMED-FAHFA authentic standards, and then, the patterns were applied to computer-generated DMED-FAHFAs. The developed DMED-FAHFA in silico library was demonstrated to be compatible with library search software NIST MS Search and the LC-MS/MS data processing tool MS-DIAL to guarantee high-throughput and automatic annotations. Applying the in silico library in Arabidopsis thaliana samples for profiling FAHFAs by high-resolution LC-MS/MS enabled the annotation of 19 DMED-FAHFAs from 16 families, including 3 novel compounds. Using the in silico library largely decreased the false-positive annotation rate in comparison to low-resolution LC-MS/MS. The developed library, MS/MS spectra, and development templates are freely available for commercial and noncommercial use at https://zenodo.org/record/3606905.

Noninvasive prenatal detection of hemoglobin Bart hydrops fetalis via maternal plasma dispensed with parental haplotyping using the semiconductor sequencing platform.

BACKGROUND: Thalassemia is one of the most common monogenetic diseases in the south of China and Southeast Asia. Hemoglobin Bart's hydrops fetalis syndrome was caused by a homozygous Southeast Asian deletion (-/-) in the HBA gene. Few studies have proved the potential of screen for Bart's hydrops fetalis using fetal cell-free DNA. However, the number of cases is still relatively small. Clinical trials of large samples would be needed. OBJECTIVE: In this study, we aimed to develop a noninvasive method of target-captured sequencing and genotyping by the Bayesian method using cell-free fetal DNA to identify the fetal genotype in pregnant women who are at risk of having hemoglobin Bart hydrops fetalis in a large-scale study. STUDY DESIGN: In total, 192,173 couples from 30 hospitals were enrolled in our study and 878 couples were recruited, among whom both the pregnant women and their husbands were detected to be carriers of Southeast Asian type (-/αα) of α-thalassemia. Prenatal diagnosis was performed by chorionic villus sampling, amniocentesis, or cordocentesis using gap-polymerase chain reaction considered as the golden standard. RESULTS: As a result, we found that the sensitivity and specificity of our noninvasive method were 98.81% and 94.72%, respectively, in the training set as well as 100% and 99.31%, respectively, in the testing set. Moreover, our method could identify all of 885 maternal samples with the Southeast Asian carrier and 36 trisomy samples with 100% of sensitivity in T13, T18, and T21 and 99.89% (1 of 917) and 99.88% (1 of 888) of specificity in T18 and T21, respectively. CONCLUSION: Our method opens the possibility of early screening for maternal genotyping of α-thalassemia, fetal aneuploidies in chromosomes 13/18/21, and hemoglobin Bart hydrops fetalis detection in 1 tube of maternal plasma.

SEECancer: a resource for somatic events in evolution of cancer genome.

Cancer cells progressively evolve from a premalignant to a malignant state, which is driven by accumulating somatic alterations that confer normal cells a fitness advantage. Improvements in high-throughput sequencing techniques have led to an increase in construction of tumor phylogenetics and identification of somatic driver events that specifically occurred in different tumor progression stages. Here, we developed the SEECancer database (http://biocc.hrbmu.edu.cn/SEECancer), which aims to present the comprehensive cancer evolutionary stage-specific somatic events (including early-specific, late-specific, relapse-specific, metastasis-specific, drug-resistant and drug-induced genomic events) and their temporal orders. By manually curating over 10 000 published articles, 1231 evolutionary stage-specific genomic events and 5772 temporal orders involving 82 human cancers and 23 tissue origins were collected and deposited in the SEECancer database. Each entry contains the somatic event, evolutionary stage, cancer type, detection approach and relevant evidence. SEECancer provides a user-friendly interface for browsing, searching and downloading evolutionary stage-specific somatic events and temporal relationships in various cancers. With increasing attention on cancer genome evolution, the necessary information in SEECancer will facilitate understanding of cancer etiology and development of evolutionary therapeutics, and help clinicians to discover biomarkers for monitoring tumor progression.

Method to Calculate the Retention Index in Hydrophilic Interaction Liquid Chromatography Using Normal Fatty Acid Derivatives as Calibrants.

Hydrophilic interaction liquid chromatography-mass spectrometry (HILIC-MS) is a complementary technique to reversed-phase liquid chromatography-mass spectrometry (RPLC-MS) and has been widely used to expand the coverage of the metabolome in MS-based metabolomics. However, the use of HILIC retention time (HILIC RT) in metabolites annotation is quite limited because of its poor reproducibility. Here, we developed a method to calculate the retention index in HILIC (HILIC RI) for calibration of HILIC RT. In this method, a mixture of 2-dimethylaminoethylamine (DMED)-labeled fatty acid standards with carbon chain length from C2 to C22 were selected as calibrants to establish a linear calibration equation between HILIC RT and carbon number for the calculation of HILIC RI. The calculated HILIC RIs based on a regression equation could efficiently calibrate the retention time shifts for 28 DMED-labeled carboxyl standards and DMED-labeled carboxyl metabolites in rat urine, serum and feces on a HILIC column with different gradient elution conditions. Furthermore, the developed HILIC RI strategy was applied to RT calibration of screened metabolites, the annotation of isomers in HILIC-MS-based metabolomics analysis for real samples, and the correction of isotope effects in chemical isotope labeling HILIC-MS analysis. Taken together, the resulting HILIC RI strategy is a promising analytical technique to improve the accuracy of metabolite annotation; it would be widely used in HILIC-MS-based metabolome analysis.

Comprehensive Screening and Identification of Fatty Acid Esters of Hydroxy Fatty Acids in Plant Tissues by Chemical Isotope Labeling-Assisted Liquid Chromatography-Mass Spectrometry.

Fatty acid esters of hydroxy fatty acids (FAHFAs) are a new class of lipid mediators with promising anti-diabetic and anti-inflammatory properties. Comprehensive screening and identification of FAHFAs in biological samples would be beneficial to the discovery of new FAHFAs and enable greater understanding of their biological functions. Here, we report the comprehensive screening of FAHFAs in rice and  Arabidopsis thaliana by chemical isotope labeling-assisted liquid chromatography-mass spectrometry (CIL-LC-MS). Multiple reaction monitoring (MRM) was used for screening of FAHFAs. With the proposed method, we detected 49 potential FAHFA families, including 262 regioisomers, in tissues of rice and Arabidopsis thaliana, which greatly extends our knowledge of known FAHFAs. In addition, we proposed a strategy to identify FAHFA regioisomers based on their retention on a reversed-phase LC column. Using the proposed identification strategy, we identified 71 regioisomers from 11 FAHFA families based on commercial standards and characteristic chromatographic retention behaviors. The screening technique could allow for the discovery of new FAHFAs in biological samples. The new FAHFAs identified in this work will contribute to the in-depth study of the functions of FAHFAs.

Establishment of Liquid Chromatography Retention Index Based on Chemical Labeling for Metabolomic Analysis.

Chemical labeling (CL) in combination with liquid chromatography-mass spectrometry (LC-MS) analysis has been demonstrated to be a promising technology in metabolomic analysis. However, identification of chemically labeled metabolites remains to be challenging. Retention time (RT) is one of the most important parameters for the identification of metabolites, but it could vary greatly in LC-MS analysis. In this work, we developed a chemical labeling-based HPLC retention index (CL-HPLC RI) strategy to facilitate the identification of metabolites. In this CL-HPLC RI strategy, a series of 2-dimethylaminoethylamine (DMED)-labeled fatty acids were used as calibrants to establish RIs for DMED-labeled carboxylated compounds and a series of 4-( N, N-dimethylamino)phenyl isothiocyanate (DMAP)-labeled fatty amines were used as calibrants for DMAP-labeled amine compunds. To calculate the RIs, the whole LC chromatogram was divided into 24 time intervals by 23 DMED-labeled fatty acid standards or 15 time intervals by 14 DMAP-labeled fatty amine standards. Then, we established the RIs of 854 detected DMED-labeled carboxylated metabolites and 1057 DMAP-labeled amine metabolites in fecal samples and demonstrated that RIs were highly reproducible under different elution gradients, columns, and instrument systems. Finally, we applied this strategy to the identification of metabolites in human serum. Using RIs, 267 DMED-labeled carboxylated metabolites and 273 DMAP-labeled amine metabolites in human serum matched well with the fecal metabolome database. Taken together, the developed CL-HPLC RI strategy was demonstrated to be a promising method to facilitate the identification of metabolites in metabolomic analysis.