Data dependent peak model based spectrum deconvolution for analysis of high resolution LC-MS data

Enolase inhibitors as therapeutic leads for Naegleria fowleri infection

Infections with the pathogenic free-living amoebae Naegleria fowleri can lead to life-threatening illnesses including catastrophic primary amebic meningoencephalitis (PAM). Efficacious treatment options for these infections are lacking and the mortality rate remains >95% in the US. Glycolysis is very important for the infectious trophozoite lifecycle stage and inhibitors of glucose metabolism have been found to be toxic to the pathogen. Recently, human enolase 2 (ENO2) phosphonate inhibitors have been developed as lead agents to treat glioblastoma multiforme (GBM). These compounds, which cure GBM in a rodent model, are well-tolerated in mammals because enolase 1 (ENO1) is the predominant isoform used systemically. Here, we describe findings that demonstrate that these agents are potent inhibitors of N. fowleri ENO ( Nf ENO) and are lethal to amoebae. In particular, (1-hydroxy-2-oxopiperidin-3-yl) phosphonic acid (HEX) was a potent enzyme inhibitor (IC 50 value of 0.14 ± 0.04 µM) that was toxic to trophozoites (EC 50 value of 0.21 ± 0.02 µM) while the reported CC 50 was >300 µM. Molecular docking simulation revealed that HEX binds strongly to the active site of Nf ENO with a binding affinity of -8.6 kcal/mol. Metabolomic studies of parasites treated with HEX revealed a 4.5 to 78-fold accumulation of glycolytic intermediates upstream of Nf ENO. Last, nasal instillation of HEX increased longevity of amoebae-infected rodents. Two days after infection, animals were treated for 10 days with 3 mg/kg HEX, followed by one week of observation. At the conclusion of the experiment, eight of 12 HEX-treated animals remained alive (resulting in an indeterminable median survival time) while one of 12 vehicle-treated rodents remained, yielding a median survival time of 10.9 days. Brains of six of the eight survivors were positive for amoebae, suggesting the agent at the tested dose suppressed, but did not eliminate, infection. These findings suggest that HEX is a promising lead for the treatment of PAM.

Critical review on data processing algorithms in non-target screening: challenges and opportunities to improve result comparability

Non-target screening (NTS) is a powerful environmental and analytical chemistry approach for detecting and identifying unknown compounds in complex samples. High-resolution mass spectrometry has enhanced NTS capabilities but created challenges in data analysis, including data preprocessing, peak detection, and feature extraction. This review provides an in-depth understanding of NTS data processing methods, focusing on centroiding, extracted ion chromatogram (XIC) building, chromatographic peak characterization, alignment, componentization, and prioritization of features. We discuss the strengths and weaknesses of various algorithms, the influence of user input parameters on the results, and the need for automated parameter optimization. We address uncertainty and data quality issues, emphasizing the importance of incorporating confidence intervals and raw data quality assessment in data processing workflows. Furthermore, we highlight the need for cross-study comparability and propose potential solutions, such as utilizing standardized statistics and open-access data exchange platforms. In conclusion, we offer future perspectives and recommendations for developers and users of NTS data processing algorithms and workflows. By addressing these challenges and capitalizing on the opportunities presented, the NTS community can advance the field, improve the reliability of results, and enhance data comparability across different studies.

Cardiomyocyte Pdk4 response is associated with metabolic maladaptation in aging

Ischemic heart disease (IHD) is the leading cause of death, with age range being the primary factor for development. The mechanisms by which aging increases vulnerability to ischemic insult are not well understood. We aim to use single-cell RNA sequencing to discover transcriptional differences in various cell types between aged and young mice, which may contribute to aged-related vulnerability to ischemic insult. Utilizing 10× Genomics Single-Cell RNA sequencing, we were able to complete bioinformatic analysis to identity novel differential gene expression. During the analysis of our collected samples, we detected Pyruvate Dehydrogenase Kinase 4 (Pdk4) expression to be remarkably differentially expressed. Particularly in cardiomyocyte cell populations, Pdk4 was found to be significantly upregulated in the young mouse population compared to the aged mice under ischemic/reperfusion conditions. Pdk4 is responsible for inhibiting the enzyme pyruvate dehydrogenase, resulting in the regulation of glucose metabolism. Due to decreased Pdk4 expression in aged cardiomyocytes, there may be an increased reliance on glucose oxidization for energy. Through biochemical metabolomics analysis, it was observed that there is a greater abundance of pyruvate in young hearts in contrast to their aged counterparts, indicating less glycolytic activity. We believe that Pdk4 response provides valuable insight towards mechanisms that allow for the young heart to handle ischemic insult stress more effectively than the aged heart.

Stable Isotope Tracing Reveals an Altered Fate of Glucose in N-Acetyltransferase 1 Knockout Breast Cancer Cells

Breast cancer is one of the leading causes of cancer death. Recent studies found that arylamine N-acetyltransferase 1 (NAT1) is frequently upregulated in breast cancer, further suggesting NAT1 could be a potential therapeutic target for breast cancer. Previous publications have established that NAT1 knockout (KO) in breast cancer cell lines leads to growth reduction both in vitro and in vivo and metabolic changes. These reports suggest that NAT1 contributes to the energy metabolism of breast cancer cells. Proteomic analysis and non-targeted metabolomics suggested that NAT1 KO may change the fate of glucose as it relates to the TCA/KREB cycle of the mitochondria of breast cancer cells. In this current study, we used [U-13C]-glucose stable isotope resolved metabolomics to determine the effect of NAT1 KO on the metabolic profile of MDA-MB-231 breast cancer cells. We incubated breast cancer cells (MDA-MB-231 cells) and NAT1 Crispr KO cells (KO#2 and KO#5) with [U-13C]-glucose for 24 h. Tracer incubation polar metabolites from the cells were extracted and analyzed by 2DLC-MS, and metabolite differences were compared between the parental and NAT1 KO cells. Differences consistent between the two KO cells were considered changes due to the loss of NAT1. The data revealed decreases in the 13C enrichment of TCA/Krebs cycle intermediates in NAT1 KO cells compared to the MDA-MB-231 cells. Specifically, 13C-labeled citrate, isocitrate, a-ketoglutarate, fumarate, and malate were all decreased in NAT1 KO cells. We also detected increased 13C-labeled L-lactate levels in the NAT1 KO cells and decreased 13C enrichment in some nucleotides. Pathway analysis showed that arginine biosynthesis, alanine, aspartate and glutamate metabolism, and the TCA cycle were most affected. These data provide additional evidence supporting the impacts of NAT1 knockout on cellular energy metabolism. The data suggest that NAT1 expression is important for the proper functioning of mitochondria and the flux of glucose through the TCA/Krebs cycle in breast cancer cells. The metabolism changes in the fate of glucose in NAT1 KO breast cancer cells offer more insight into the role of NAT1 in energy metabolism and the growth of breast cancer cells. These data provide additional evidence that NAT1 may be a useful therapeutic target for breast cancer.

A Novel Symmetrical Peak Fitting Method Based on Improved WOA Algorithm for the Analysis of Microchip Electrophoresis Signals

The problem of overlapping peaks has been a challenge in microchip electrophoresis (ME) signal analysis. However, traditional peak fitting algorithms have difficulty analyzing overlapping peaks due to the high dependence on the starting point. In this study, we propose a symmetrical peak fitting method named the tent-mapped whale optimization algorithm and Levenberg–Marquardt (TWOALM), which combines a whale optimization algorithm (WOA) improved by one of the most commonly used chaotic maps, the tent map and the Levenberg–Marquardt (LM) algorithm. Specifically, we first derive the fitted model for the overlapping peaks, showing that it is separable nonlinear least squares, significantly reducing the number of parameters to be optimized. Second, we integrate the tent map into the WOA, which improves the convergence speed of the peak fitting algorithm. Finally, we propose an efficient peak-fitting algorithm that combines the improved WOA and LM. The advantage of the proposed algorithm is that it is significantly faster than WOA and significantly more accurate than the LM algorithm. The results of fitting the synthetic peaks and ME signals showed that the combination of the chaotic map-based WOA algorithm and the LM algorithm can significantly improve the peak fitting performance and provide an effective solution for the analysis of overlapping peaks.

Quantitative Method for Liquid Chromatography–Mass Spectrometry Based on Multi-Sliding Window and Noise Estimation

LC-MS/MS uses information on the mass peaks and peak areas of samples to conduct quantitative analysis. However, in the detection of clinical samples, the spectrograms of the compounds are interfered with for different reasons, which makes the identification of chromatographic peaks more difficult. Therefore, to improve the chromatographic interference problem, this paper first proposes a multi-window-based signal-to-noise ratio estimation algorithm, which contains the steps of raw data denoising, peak identification, peak area calculation and curve fitting to obtain accurate quantitative analysis results of the samples. Through the chromatographic peak identification of an extracted ion chromatogram of VD2 in an 80 ng/mL standard and the spectral peak identification of data from an open-source database, the identification results show that the algorithm has a better peak detection performance. The accuracy of the quantitative analysis was verified using the LC-HTQ-2020 triple quadrupole mass spectrometer produced by our group for the application of steroid detection in human serum. The results show that the algorithm proposed in this paper can accurately identify the peak information of LC-MS/MS chromatographic peaks, which can effectively improve the accuracy and reproducibility of steroid detection results and meet the requirements of clinical testing applications such as human steroid hormone detection.

Activated Protein C Strengthens Cardiac Tolerance to Ischemic Insults in Aging

BACKGROUND

APC (activated protein C) is a plasma serine protease with anticoagulant and anti-inflammatory activities. EPCR (Endothelial protein C receptor) is associated with APC's activity and mediates its downstream signaling events. APC exerts cardioprotective effects during ischemia and reperfusion (I/R). This study aims to characterize the role of the APC-EPCR axis in ischemic insults in aging.

METHODS

Young (3-4 months) and aged (24-26 months) wild-type C57BL/6J mice, as well as EPCR point mutation (EPCR^R84A/R84A) knockin C57BL/6J mice incapable of interaction with APC and its wild type of littermate C57BL/6J mice, were subjected to I/R. Wild-type APC, signaling-selective APC-2Cys, or anticoagulant-selective APC-E170A were administrated before reperfusion.

RESULTS

The results demonstrated that cardiac I/R reduces APC activity, and the APC activity was impaired in the aged versus young hearts possibly attributable to the declined EPCR level with aging. Serum EPCR measurement showed that I/R triggered the shedding of membrane EPCR into circulation, while administration of APC attenuated the I/R-induced EPCR shedding in both young and aged hearts. Subsequent echocardiography showed that APC and APC-2Cys but not APC-E170A ameliorated cardiac dysfunction during I/R in both young and aged mice. Importantly, APC elevated the resistance of the aged heart to ischemic insults through stabilizing EPCR. However, all these cardioprotective effects of APC were blunted in the EPCR^R84A/R84A mice versus its wild-type littermates. The ex vivo working heart and metabolomics results demonstrated that AMPK (AMP-activated protein kinase) mediates acute adaptive response while AKT (protein kinase B) is involved in chronic metabolic programming in the hearts with APC treatment.

CONCLUSIONS

I/R stress causes shedding of the membrane EPCR in the heart, and administration of APC prevents I/R-induced cardiac EPCR shedding that is critical for limiting cardiac damage in aging.

Discrepancies in metabolomic biomarker identification from patient-derived lung cancer revealed by combined variation in data pre-treatment and imputation methods

INTRODUCTION

The identification of metabolomic biomarkers predictive of cancer patient response to therapy and of disease stage has been pursued as a "holy grail" of modern oncology, relying on the metabolic dysfunction that characterizes cancer progression. In spite of the evaluation of many candidate biomarkers, however, determination of a consistent set with practical clinical utility has proven elusive.

OBJECTIVE

In this study, we systematically examine the combined role of data pre-treatment and imputation methods on the performance of multivariate data analysis methods and their identification of potential biomarkers.

METHODS

Uniquely, we are able to systematically evaluate both unsupervised and supervised methods with a metabolomic data set obtained from patient-derived lung cancer core biopsies with true missing values. Eight pre-treatment methods, ten imputation methods, and two data analysis methods were applied in combination.

RESULTS

The combined choice of pre-treatment and imputation methods is critical in the definition of candidate biomarkers, with deficient or inappropriate selection of these methods leading to inconsistent results, and with important biomarkers either being overlooked or reported as a false positive. The log transformation appeared to normalize the original tumor data most effectively, but the performance of the imputation applied after the transformation was highly dependent on the characteristics of the data set.

CONCLUSION

The combined choice of pre-treatment and imputation methods may need careful evaluation prior to metabolomic data analysis of human tumors, in order to enable consistent identification of potential biomarkers predictive of response to therapy and of disease stage.

miR-375 prevents high-fat diet-induced insulin resistance and obesity by targeting the aryl hydrocarbon receptor and bacterial tryptophanase (tnaA) gene

Background: Diet manipulation is the basis for prevention of obesity and diabetes. The molecular mechanisms that mediate the diet-based prevention of insulin resistance are not well understood. Here, as proof-of-concept, ginger-derived nanoparticles (GDNP) were used for studying molecular mechanisms underlying GDNP mediated prevention of high-fat diet induced insulin resistance. Methods: Ginger-derived nanoparticles (GDNP) were isolated from ginger roots and administered orally to C57BL/6 high-fat diet mice. Fecal exosomes released from intestinal epithelial cells (IECs) of PBS or GDNP treated high-fat diet (HFD) fed mice were isolated by differential centrifugation. A micro-RNA (miRNA) polymerase chain reaction (PCR) array was used to profile the exosomal miRs and miRs of interest were further analyzed by quantitative real time (RT) PCR. miR-375 or antisense-miR375 was packed into nanoparticles made from the lipids extracted from GDNP. Nanoparticles was fluorescent labeled for monitoring their in vivo trafficking route after oral administration. The effect of these nanoparticles on glucose and insulin response of mice was determined by glucose and insulin tolerance tests. Results: We report that HFD feeding increased the expression of AhR and inhibited the expression of miR-375 and VAMP7. Treatment with orally administered ginger-derived nanoparticles (GDNP) resulted in reversing HFD mediated inhibition of the expression of miR-375 and VAMP7. miR-375 knockout mice exhibited impaired glucose homeostasis and insulin resistance. Induction of intracellular miR-375 led to inhibition of the expression of AhR and VAMP7 mediated exporting of miR-375 into intestinal epithelial exosomes where they were taken up by gut bacteria and inhibited the production of the AhR ligand indole. Intestinal exosomes can also traffic to the liver and be taken up by hepatocytes, leading to miR-375 mediated inhibition of hepatic AhR over-expression and inducing the expression of genes associated with the hepatic insulin response. Altogether, GDNP prevents high-fat diet-induced insulin resistance by miR-375 mediated inhibition of the aryl hydrocarbon receptor mediated pathways over activated by HFD feeding. Conclusion: Collectively our findings reveal that oral administration of GDNP to HFD mice improves host glucose tolerance and insulin response via regulating AhR expression by GDNP induced miR-375 and VAMP7.

NMF-Based Spectral Deconvolution with a Web Platform GC Mixture Touch

Complete separation of chemicals in a complex mixture is far from being achieved even with the current high-performance separation technology, such as gas chromatography-mass spectrometry (GC-MS). Several deconvolution techniques based on multivariate curve resolution (MCR), or model peak methods, which are represented by AMDIS, have been developed to address the above-mentioned issue. The model peak methods have been developed to provide easy-to-use tools, including AMDIS, but are limited for MCR with approximation methods. The objective of this study was to provide an easy-to-use deconvolution tool based on the MCR approach for GC-MS data. The spectral deconvolution tool based on non-negative matrix factorization (NMF), which calculates outputs using an approximation method, was implemented as a free web platform, namely, GC Mixture Touch, clarifying the effects of the parameters required for the deconvolution. The GC Mixture Touch was applied to the actual mixture sample of road dust spiked with chemical standards. The recommended parameter settings for smoothing of the chromatogram, the number of ranks, and the NMF algorithm for the deconvolution were clarified through the study. The performance with the suggested parameters was evaluated with respect to compound identification for the actual sample. All of the test compounds in the sample were correctly identified with the GC Mixture Touch, outperforming AMDIS with respect to the identification. The GC Mixture Touch is easy to use on the web even for users without programming skills. This is expected to enhance the application of the NMF-based deconvolution, and it should prove helpful in finding the compounds hidden in complex mixtures that are difficult to find using conventional approaches.

Sestrin2 maintains OXPHOS integrity to modulate cardiac substrate metabolism during ischemia and reperfusion

Sestrin2 (Sesn2) is a stress-inducible protein that declines with aging in the heart. We reported that rescue Sesn2 levels in aged mouse hearts through gene therapy improves the resistance of aged hearts to ischemia and reperfusion (I/R) insults. We hypothesize that Sesn2 as a scaffold protein maintains mitochondrial integrity to protect heart from ischemic injury during I/R. Young C57BL/6 J (3–6 months), aged C57BL/6 J (24–26 months), and young Sesn2 KO (3–6 months, C57BL/6 J background) mice were subjected to in vivo regional ischemia and reperfusion. The left ventricle was collected for transcriptomics, proteomics and metabolomics analysis. The results demonstrated that Sesn2 deficiency leads to aging-like cardiac diastolic dysfunction and intolerance to ischemia reperfusion stress. Seahorse analysis demonstrated that Sesn2 deficiency in aged and young Sesn2 KO versus young hearts lead to impaired mitochondrial respiration rate with defects in Complex I and Complex II activity. The Sesn2 targeted proteomics analysis revealed that Sesn2 plays a critical role in maintaining mitochondrial functional integrity through modulating mitochondria biosynthesis and assembling of oxidative phosphorylation (OXPHOS) complexes. The RNA-Seq data showed that alterations in the expression of mitochondrial compositional and functional genes and substrate metabolism related genes in young Sesn2 KO and aged versus young hearts. Further immunofluorescence and immunoprecipitation analysis demonstrated that Sesn2 is translocated into mitochondria and interacts with OXPHOS components to maintain mitochondrial integrity in response to I/R stress. Biochemical analysis revealed that Sesn2 is associated with citrate cycle components to modulate pyruvate dehydrogenase and isocitrate dehydrogenase activities during I/R stress. Thus, Sesn2 serves as a scaffold protein interacting with OXPHOS components to maintain mitochondrial integrity under I/R stress. Age-related downregulation of cardiac Sesn2 fragilizes mitochondrial functional integrity in response to ischemic stress.

•

Ischemia reperfusion stress triggers Sesn2 accumulation in mitochondria.

•

Sesn2 interacts with OXPHOS complexes to modulate the adaptive substrate metabolism.

•

Age-related Sesn2 maintains mitochondrial functional integrity under stress conditions.

Technical Overview of Orbitrap High Resolution Mass Spectrometry and Its Application to the Detection of Small Molecules in Food (Update Since 2012)

Food safety and quality issues are becoming increasingly important and attract much attention, requiring the development of better analytical platforms. For example, high-resolution (especially Orbitrap) mass spectrometry simultaneously offers versatile functions such as targeted/non-targeted screening while providing qualitative and quantitative information on an almost unlimited number of analytes to facilitate routine analysis and even allows for official surveillance in the food field. This review covers the current state of Orbitrap mass spectrometry (OMS) usage in food analysis based on research reported in 2012-2019, particularly highlighting the technical aspects of OMS application and the achievement of OMS-based screening and quantitative analysis in the food field. The gained insights enhance our understanding of state-of-the-art high-resolution mass spectrometry and highlight the challenges and directions of future research.

Integrating Two-Dimensional Gas and Liquid Chromatography-Mass Spectrometry for Untargeted Colorectal Cancer Metabolomics: A Proof-of-Principle Study

Untargeted metabolomics is expected to lead to a better mechanistic understanding of diseases and thus applications of precision medicine and personalized intervention. To further increase metabolite coverage and achieve high accuracy of metabolite quantification, the present proof-of-principle study was to explore the applicability of integration of two-dimensional gas and liquid chromatography-mass spectrometry (GC × GC-MS and 2DLC-MS) platforms to characterizing circulating polar metabolome extracted from plasma collected from 29 individuals with colorectal cancer in comparison with 29 who remained cancer-free. After adjustment of multiple comparisons, 20 metabolites were found to be up-regulated and 8 metabolites were found to be down-regulated, which pointed to the dysregulation in energy metabolism and protein synthesis. While integrating the GC × GC-MS and 2DLC-MS data can dramatically increase the metabolite coverage, this study had a limitation in analyzing the non-polar metabolites. Given the small sample size, these results need to be validated with a larger sample size and with samples collected prior to diagnostic and treatment. Nevertheless, this proof-of-principle study demonstrates the potential applicability of integration of these advanced analytical platforms to improve discrimination between colorectal cancer cases and controls based on metabolite profiles in future studies.

Cardiospecific Overexpression of ATPGD1 (Carnosine Synthase) Increases Histidine Dipeptide Levels and Prevents Myocardial Ischemia Reperfusion Injury

BACKGROUND Myocardial ischemia reperfusion (I/R) injury is associated with complex pathophysiological changes characterized by pH imbalance, the accumulation of lipid peroxidation products acrolein and 4-hydroxy trans-2-nonenal, and the depletion of ATP levels. Cardioprotective interventions, designed to address individual mediators of I/R injury, have shown limited efficacy. The recently identified enzyme ATPGD1 (Carnosine Synthase), which synthesizes histidyl dipeptides such as carnosine, has the potential to counteract multiple effectors of I/R injury by buffering intracellular pH and quenching lipid peroxidation products and may protect against I/R injury. METHODS AND RESULTS We report here that β-alanine and carnosine feeding enhanced myocardial carnosine levels and protected the heart against I/R injury. Cardiospecific overexpression of ATPGD1 increased myocardial histidyl dipeptides levels and protected the heart from I/R injury. Isolated cardiac myocytes from ATPGD1-transgenic hearts were protected against hypoxia reoxygenation injury. The overexpression of ATPGD1 prevented the accumulation of acrolein and 4-hydroxy trans-2-nonenal-protein adducts in ischemic hearts and delayed acrolein or 4-hydroxy trans-2-nonenal-induced hypercontracture in isolated cardiac myocytes. Changes in the levels of ATP, high-energy phosphates, intracellular pH, and glycolysis during low-flow ischemia in the wild-type mice hearts were attenuated in the ATPGD1-transgenic hearts. Two natural dipeptide analogs (anserine and balenine) that can either quench aldehydes or buffer intracellular pH, but not both, failed to protect against I/R injury. CONCLUSIONS Either exogenous administration or enhanced endogenous formation of histidyl dipeptides prevents I/R injury by attenuating changes in intracellular pH and preventing the accumulation of lipid peroxidation derived aldehydes.

Using Multiple Analytical Platforms to Investigate the Androgen Depletion Effects on Fecal Metabolites in a Mouse Model of Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by circulating autoantibodies that deposit in target organs (e.g., kidneys), resulting in chronic inflammation and eventual destruction of the organ. SLE is much more prevalent in females than males in both humans and spontaneous mouse models of lupus, such as NZBxNZW F1 (BWF1) mice. Depleting androgens by castration dramatically increases the susceptibility of BWF1 male to lupus. We compared fecal metabolite profiles of castrated BWF1 (androgen-depleted) male, intact (androgen-replete) male, and female mice. Four analytical platforms were employed to study the profiles of polar metabolites in mouse feces collected from adult BWF1 mice, and a total of 435 metabolites was identified. Of these, the abundance levels of 72 metabolites were significantly different between castrated and intact male groups, and 63 metabolites were different between female and male groups. Pathway analysis indicated that the pathway differences between castrated and intact male mice closely resembled the pathway differences between female and intact male mice, suggesting that low levels of androgens, whether due to depletion (castrated male) or endogenous (female), are associated with multiple fecal metabolomic alterations, which could potentially affect SLE progression. Our findings demonstrate that analyzing fecal metabolites using multiple analytical platforms holds great promise for detecting metabolomic alterations in complex disease model systems.

Integrating comprehensive two-dimensional gas chromatography mass spectrometry and parallel two-dimensional liquid chromatography mass spectrometry for untargeted metabolomics

The diverse characteristics and large number of entities make metabolite separation challenging in metabolomics. To date, there is not a singular instrument capable of analyzing all types of metabolites. In order to achieve a better separation for higher peak capacity and accurate metabolite identification and quantification, we integrated GC × GC-MS and parallel 2DLC-MS for analysis of polar metabolites. To test the performance of the developed system, 13 rats were fed different diets to form two animal groups. Polar metabolites extracted from rat livers were analyzed by GC × GC-MS, parallel 2DLC-MS (-) and parallel 2DLC-MS (+), respectively. By integrating all data together, 58 metabolites were detected with significant change in their abundance levels between groups (p≤ 0.05). Of the 58 metabolites, three metabolites were detected in two platforms and two in all three platforms. Manual examination showed that discrepancy of metabolite regulation measured by different platforms was mainly caused by the poor shape of chromatographic peaks resulting from low instrument response. Pathway analysis demonstrated that integrating the results from multiple platforms increased the confidence of metabolic pathway assignment.

Profiling of Polar Metabolites in Mouse Feces Using Four Analytical Platforms to Study the Effects Of Cathelicidin-Related Antimicrobial Peptide in Alcoholic Liver Disease

Alterations in gut bacterial homeostasis result in changes in intestinal metabolites. To investigate the effects of alcohol on fecal metabolites and the role of cathelicidin-related antimicrobial peptide (CRAMP) in alcoholic liver disease (ALD), CRAMP knockout (KO) and their control wild type (WT) mice were fed a Lieber-DeCarli liquid diet with or without alcohol. Polar metabolites in mouse feces were analyzed by GC × GC-MS and 2DLC-MS, and the concentrations of short chain fatty acids (SCFAs) were measured by GC-MS. A total of 95 and 190 metabolites were detected by GC × GC-MS and 2DLC-MS, respectively. Among the significantly changed metabolites, taurine and nicotinic acid were decreased in WT mice fed alcohol, which were also down-regulated in KO mice fed without alcohol. Interestingly, these two metabolites were increased in KO mice fed alcohol compared to them in WT controls. Additionally, SCFAs were significantly decreased in WT mice fed alcohol and in KO mice fed without alcohol, whereas two branched-chain SCFAs were increased by alcohol treatment in KO mice. In summary, the analytical platforms employed in this study successfully dissected the alterations of polar metabolites and SCFAs in fecal samples, which helped understand the effects of alcohol consumption and CRAMP in intestinal metabolism and alcohol-induced liver injury.

Simultaneous Quantification of Nucleosides and Nucleotides from Biological Samples

We report a reverse phase chromatography mass spectrometry (LC-MS) method for simultaneous quantification of nucleosides and nucleotides from biological samples, where compound identification was achieved by a tier-wise approach and compound quantification was achieved via external calibration. A total of 65 authentic standards of nucleosides and nucleotides were used for the platform development. The limit of detection (LOD) of those compounds ranged from 0.05 nmol/L to 1.25 μmol/L, and their limit of quantification (LOQ) ranged from 0.10 nmol/L to 2.50 μmol/L. Using the developed method, nucleosides and nucleotides from human plasma, human urine, and rat liver were quantified. Seventy-nine nucleosides and nucleotides were identified from human urine and 28 of them were quantified with concentrations of 13.0 nmol/L-151 μmol/L. Fifty-five nucleosides and nucleotides were identified from human plasma and 22 of them were quantified with concentrations of 1.21 nmol/L-8.54 μmol/L. Fifty-one nucleosides and nucleotides were identified from rat liver and 23 were quantified with concentrations of 1.03 nmol/L-31.7 μmol/L. These results demonstrate that the developed method can be used to investigate the concentration change of nucleosides and nucleotides in biological samples for the purposes of biomarker discovery or elucidation of disease mechanisms.

Chromatographic Retention Assisted Deconvolution of Liquid Chromatography-Mass Spectrometry Chromatogram of Natural Products

A chromatographic retention assisted denoising and peak picking algorithm (CRAD) is developed for preprocessing liquid chromatography-mass spectrometry (LC-MS) datasets of natural products. The retention behaviors of ions with the same m/z value are investigated under a series of elution conditions. The detected ions are identified as real compounds if their chromatographic retention behaviors fit well with the Snyder-Soczewinski model. Further, the ions with similar retention behaviors and isotope ratios are clustered. This method enables rapid identification of precursor ions when chemical standards or databases are unavailable. It also helps eliminate unexpected baseline disturbances and improve the resolution of LC-MS chromatograms. Unlike conventional deconvolution strategies, this method distinguishes the chemical properties of precursor ions through their dynamic retention behaviors. The algorithm is demonstrated with LC-MS datasets of control samples. In the application of such algorithms on a more complicated natural extract from Lycium ruthenicum Murr., 206 precursor ions were facilely determined.

Analysis of Stable Isotope Assisted Metabolomics Data Acquired by High Resolution Mass Spectrometry

Stable isotope assisted metabolomics (SIAM) uses stable isotope tracers to support studies of biochemical mechanisms. We report a suite of data analysis algorithms for automatic analysis of SIAM data acquired on a high resolution mass spectrometer. To increase the accuracy of isotopologue assignment, metabolites detected in the unlabeled samples were used as reference metabolites to generate possible isotopologue candidates for analysis of peaks detected in the labeled samples. An iterative linear regression model was developed to deconvolute the overlapping isotopic peaks of isotopologues present in a full MS spectrum, where the threshold for the weight factor was determined by a simulation study assuming different levels of Gaussian white noise contamination. A normalization method enabling isotope ratio-based normalization was implemented to study the difference of isotopologue abundance distribution between sample groups. The developed method can analyze SIAM data acquired by direct infusion MS and LC-MS, and can handle metabolite tracers containing different tracer elements. Analysis of SIAM data acquired from mixtures of known compounds showed that the developed algorithms accurately identify metabolites and quantify stable isotope enrichment. Application of SIAM data acquired from a biological study further demonstrated the effectiveness and accuracy of the developed method for analysis of complex samples.

Comparison of GC-MS and GC×GC-MS in the analysis of human serum samples for biomarker discovery

We compared the performance of gas chromatography time-of-flight mass spectrometry (GC-MS) and comprehensive two-dimensional gas chromatography mass spectrometry (GC×GC-MS) for metabolite biomarker discovery. Metabolite extracts from 109 human serum samples were analyzed on both platforms with a pooled serum sample analyzed after every 9 biological samples for the purpose of quality control (QC). The experimental data derived from the pooled QC samples showed that the GC×GC-MS platform detected about three times as many peaks as the GC-MS platform at a signal-to-noise ratio SNR ≥ 50, and three times the number of metabolites were identified by mass spectrum matching with a spectral similarity score Rsim ≥ 600. Twenty-three metabolites had statistically significant abundance changes between the patient samples and the control samples in the GC-MS data set while 34 metabolites in the GC×GC-MS data set showed statistically significant differences. Among these two groups of metabolite biomarkers, nine metabolites were detected in both the GC-MS and GC×GC-MS data sets with the same direction and similar magnitude of abundance changes between the control and patient sample groups. Manual verification indicated that the difference in the number of the biomarkers discovered using these two platforms was mainly due to the limited resolution of chromatographic peaks by the GC-MS platform, which can result in severe peak overlap making subsequent spectrum deconvolution for metabolite identification and quantification difficult.

Global spectral deconvolution based on non-negative matrix factorization in GC × GC-HRTOFMS

A global spectral deconvolution, based on non-negative matrix factorization (NMF) in comprehensive two-dimensional gas chromatography high-resolution time-of-flight mass spectrometry, was developed. We evaluated the ability of various instrumental parameters and NMF settings to derive high-performance detection in nontarget screening using a sediment sample. To evaluate the performance of the process, a NIST library search was used to identify the deconvoluted spectra. Differences of the instrumental scan rates (25 and 50 Hz) in deconvolution were evaluated and results show that a high scan rate enhanced the number of compounds detected in the sediment sample. A higher mass resolution in the range of 1,000 to 10,000 and a higher m/z precision in the deconvolution were needed to obtain an accurate mass database. After removal of multiple duplicate hits, which occurred in batch processes of NIST library search on the deconvolution result, 62 unique assignable spectra with a match factor ≥900 were obtained in the deconvoluted chromatogram from the sediment sample, including 54 spectra that were refined by the deconvolution. This method will help to detect and build up well-resolved reference spectra from various complex mixtures and will accelerate nontarget screening.

Sparse deconvolution in one and two dimensions: applications in endocrinology and single-molecule fluorescence imaging

Deconvolution of noisy signals is an important task in analytical chemistry, examples being spectral deconvolution or deconvolution in microscopy. When the number of spectral peaks or single emitters in imaging is limited, the solution of the deconvolution is required to be sparse, and desirable results are obtained using a penalized estimation techniques. We impose sparseness by using penalized regression with a penalty based on the L0-norm, as discussed in earlier work. Several extensions to this approach are presented. Results are demonstrated on pulse identification in endocrine data where the aim is to model the secretion pattern as a sparse series of spikes. An application in single-molecule fluorescence imaging demonstrates the algorithm when applied to two-dimensional data.