A three-mode biosensor for hypoxanthine assay in aquatic products under various storage conditions.

Establishing a rapid and accurate method for monitoring the freshness of aquatic products is of great importance. Hypoxanthine has been considered an essential indicator of aquatic products' freshness. Here, a novel smartphone colorimetric / inductively coupled plasma mass spectrometry (ICP-MS) / photothermal three-mode sensing strategy was established for monitoring hypoxanthine. Hypoxanthine can be catalyzed by xanthine oxidase to H2O2 and uric acid, which can simultaneously degrade MnO2 nanosheets (NSs) to Mn2+. After filter-assisted separation, the smartphone and ICP-MS were performed by monitoring the color of the membrane and the Mn2+ in the filtrate. Additionally, MnO2 NSs can facilitate the oxidation of dopamine to form polydopamine nanoparticles, which exhibit strong photothermal efficiency. The approach successfully monitored the deterioration of aquatic products under various storage conditions through portable thermometers and smartphones with low limits of detection (LODs), providing a potential application for in-situ evaluation of the freshness of aquatic products.

Absence of association between Pfnfs1 mutation and in vitro susceptibility to lumefantrine in Plasmodium falciparum.

Artemether-lumefantrine (AL) is the most widely used antimalarial drug for treating uncomplicated falciparum malaria. This study evaluated whether the K65Q mutation in the Plasmodium falciparum cysteine desulfurase IscS (Pfnfs1) gene was associated with alternated susceptibility to lumefantrine using clinical parasite samples from Ghana and the China-Myanmar border area. Parasite isolates from the China-Myanmar border had significantly higher IC50 values to lumefantrine than parasites from Ghana. In addition, the K65 allele was significantly more prevalent in the Ghanaian parasites (34.5%) than in the China-Myanmar border samples (6.8%). However, no difference was observed in the lumefantrine IC50 value between the Pfnfs1 reference K65 allele and the non reference 65Q allele in parasites from the two regions. These data suggest that the Pfnfs1 K65Q mutation may not be a reliable marker for reduced susceptibility to lumefantrine.

Whole-body galactose oxidation as a robust functional assay to assess the efficacy of gene-based therapies in a mouse model of Galactosemia.

Despite the implementation of lifesaving newborn screening programs and a galactose-restricted diet, many patients with classic galactosemia develop long-term debilitating neurological deficits and primary ovarian insufficiency. Previously, we showed that the administration of human GALT mRNA predominantly expressed in the GalT gene-trapped mouse liver augmented the expression of hepatic GALT activity, which decreased not only galactose-1 phosphate (gal-1P) in the liver but also peripheral tissues. Since each peripheral tissue requires distinct methods to examine the biomarker and/or GALT effect, this highlights the necessity for alternative strategies to evaluate the overall impact of therapies. In this study, we established that whole-body galactose oxidation (WBGO) as a robust, noninvasive, and specific method to assess the in vivo pharmacokinetic and pharmacodynamic parameters of two experimental gene-based therapies that aimed to restore GALT activity in a mouse model of galactosemia. Although our results illustrated the long-lasting efficacy of AAVrh10-mediated GALT gene transfer, we found that GALT mRNA therapy that targets the liver predominantly is sufficient to sustain WBGO. The latter could have important implications in the design of novel targeted therapy to ensure optimal efficacy and safety.

Genetic diversity of Plasmodium vivax populations from the China-Myanmar border identified by genotyping merozoite surface protein markers.

BACKGROUND: Parasite diversity and population structure influence malaria control measures. Malaria transmission at international borders affects indigenous residents and migrants, defying management efforts and resulting in malaria re-introduction. Here we aimed to determine the extent and distribution of genetic variations in Plasmodium vivax populations and the complexity of infections along the China-Myanmar border. METHODS: We collected clinical P. vivax samples from local and migrant malaria patients from Laiza and Myitsone, Kachin State, Myanmar, respectively. We characterized the polymorphisms in two P. vivax merozoite surface protein markers, Pvmsp-3α and Pvmsp-3ß, by PCR-restriction fragment length polymorphism (PCR-RFLP) analysis. We sought to determine whether these genetic markers could differentiate these two neighboring parasite populations. RESULTS: PCR revealed three major size variants for Pvmsp-3α and four for Pvmsp-3ß among the 370 and 378 samples, respectively. PCR-RFLP resolved 26 fragment-size alleles by digesting Pvmsp-3α with Alu I and Hha I and 28 alleles by digesting Pvmsp-3ß with Pst I. PCR-RFLP analysis of Pvmsp-3α found that infections in migrant laborers from Myitsone bore more alleles than did infections in residents of Laiza, while such difference was not evident from genotyping Pvmsp-3ß. Infections originating from these two places contained distinct but overlapping subpopulations of P. vivax. Infections from Myitsone had a higher multiplicity of infection as judged by the size of the Pvmsp-3α amplicons and alleles after Alu I/Hha I digestion. CONCLUSIONS: Migrant laborers from Myitsone and indigenous residents from Laiza harbored overlapping but genetically distinct P. vivax parasite populations. The results suggested a more diverse P. vivax population in Myitsone than in the border town of Laiza. PCR-RFLP of Pvmsp-3α offers a convenient method to determine the complexity of P. vivax infections and differentiate parasite populations.

Different In Vitro Drug Susceptibility Profile of Plasmodium falciparum Isolates from Two Adjacent Areas of Northeast Myanmar and Molecular Markers for Drug Resistance.

The Greater Mekong Subregion (GMS) is the epicenter of antimalarial drug resistance. We determined in vitro susceptibilities to 11 drugs of culture-adapted Plasmodium falciparum isolates from adjacent areas (Laiza and Muse) along the China−Myanmar border. Parasites from this region were highly resistant to chloroquine and pyrimethamine but relatively sensitive to other antimalarial drugs. Consistently, the Dd2-like pfcrt mutations were fixed or almost fixed in both parasite populations, and new mutations mediating piperaquine resistance were not identified. Similarly, several mutations related to pfdhfr and pfdhps were also highly prevalent. Despite their geographical proximity, malaria parasites from Laiza showed significantly higher in vitro resistance to artemisinin derivatives, naphthoquine, pyronaridine, lumefantrine, and pyrimethamine than parasites from Muse. Likewise, the pfdhfr N51I, pfdhps A581G, pfmrp1 H785N, and pfk13 F446I mutations were significantly more frequent in Laiza than in Muse (p < 0.05). For the pfmdr1 mutations, Y184F was found only in Laiza (70%), whereas F1226Y was identified only in Muse (31.8%). Parasite isolates from Laiza showed a median RSA value of 5.0%, significantly higher than the 2.4% in Muse. Altogether, P. falciparum parasite populations from neighboring regions in the GMS may diverge substantially in their resistance to several antimalarial drugs. This information about different parasite populations will guide antimalarial treatment policies to effectively manage drug resistance during malaria elimination.

Application of a low-cost, specific, and sensitive loop-mediated isothermal amplification (LAMP) assay to detect Plasmodium falciparum imported from Africa.

BACKGROUND: Chinese citizens traveling abroad bring back imported malaria cases to China. Current malaria diagnostic tests, including microscopy and antigen-detecting rapid tests, cannot reliably detect low-density infections. To complement existing diagnostic methods, we aimed to develop a new loop-mediated isothermal amplification (LAMP) assay to detect and identify Plasmodium falciparum in Chinese travelers returning from Africa. METHODS: We developed a miniaturized LAMP assay to amplify the actin I gene of P. falciparum. Each reaction consumed only 25% of the reagents used in a conventional LAMP assay and the same amount of DNA templates used in nested PCR. We evaluated this LAMP assay's performance and compared it to microscopy and a nested PCR assay using 466 suspected malaria cases imported from Africa. We assessed the sensitivity of the new LAMP assay using cultured P. falciparum, clinical samples, and a plasmid construct, allowing unprecedented precision when quantifying the limit of detection. RESULTS: The new LAMP assay was highly sensitive and detected two more malaria cases than nested PCR. Compared to nested PCR, the sensitivity and specificity of the novel LAMP assay were 100% [95% confidence interval (CI) 98.5-100%] and 99.1% (95% CI 96.7-99.9%), respectively. When evaluated using serial dilutions of the plasmid construct, the detection limit of the new LAMP was as low as 102 copies/µL, 10-fold lower than PCR. The LAMP assay detected 0.01 parasites/µL of blood (equal to 0.04 parasites/µL of DNA) using cultured P. falciparum and 1-7 parasites/µL of blood (4-28 parasites/µL of DNA) in clinical samples, which is as good as or better than previously reported and commercially licensed assays. CONCLUSION: The novel LAMP assay based on the P. falciparum actin I gene was specific, sensitive, and cost-effective, as it consumes 1/4 of the reagents in a typical LAMP reaction.

PvMSP-3α and PvMSP-3ß genotyping reveals higher genetic diversity in Plasmodium vivax parasites from migrant workers than residents at the China-Myanmar border.

BACKGROUND: The genetic diversity of malaria parasites traces the origin and spread of new variants and can be used to evaluate the effectiveness of malaria control measures. Therefore, this study aims to improve the understanding of the molecular epidemiology of Plasmodium vivax malaria at the China-Myanmar border by genotyping the PvMSP-3α and PvMSP-3ß genes. METHODS: Blood samples were collected from P. vivax malaria patients along the China-Myanmar border. The PvMSP-3α and PvMSP-3ß genes were amplified by polymerase chain reaction (PCR) and the genetic polymorphism and haplotype of the two genes were analyzed. RESULTS: A total of 422 blood samples were used for this study, of which 224 were analyzed at PvMSP-3α and 126 at PvMSP-3ß. Samples mainly were from young adults aged 18-45 years, although local patients were significantly younger than migrant laborers crossing the border at Tengchong (P < 0.0001). Molecular evolutionary analysis revealed that PvMSP-3α and PvMSP-3ß underwent diversifying natural selection, and intragenic recombination contributed to the diversity of the isolates. Based on the length of the genes, we identified three types of PvMSP-3α [1.9-2.0 kb (Type-A), 1.4-1.5 kb (Type-B), and 1.1-1.3 kb (Type-C)] and two types of PvMSP-3ß [1.7-2.2 kb (Type-A) and 1.4-1.5 kb (Type-B)]. Migrant laborers returning to China through Tengchong bore P. vivax infections displaying significantly higher genetic diversity than local residents. CONCLUSIONS: Both PvMSP-3 paralogs were subjected to diversifying selection in each sample population. Clustering of alleles supports ephemeral endemic differentiation of alleles, but the broader phylogeny suggests that alleles transit the globe, perhaps accelerated by movements of migrants such as those transiting Tengchong.

The Quantitative Assessment of Using Multiparametric MRI for Prediction of Extraprostatic Extension in Patients Undergoing Radical Prostatectomy: A Systematic Review and Meta-Analysis.

PURPOSE: To investigate the diagnostic performance of using quantitative assessment with multiparametric MRI (mpMRI) for prediction of extraprostatic extension (EPE) in patients with prostate cancer (PCa). METHODS: We performed a computerized search of MEDLINE, Embase, Cochrane Library, Web of Science, and Google Scholar from inception until July 31, 2021. Summary estimates of sensitivity and specificity were pooled with the bivariate model, and quality assessment of included studies was performed with the Quality Assessment of Diagnostic Accuracy Studies-2. We plotted forest plots to graphically present the results. Multiple subgroup analyses and meta-regression were performed to explore the variate clinical settings and heterogeneity. RESULTS: A total of 23 studies with 3,931 participants were included. The pooled sensitivity and specificity for length of capsular contact (LCC) were 0.79 (95% CI 0.75-0.83) and 0.77 (95% CI 0.73-0.80), for apparent diffusion coefficient (ADC) were 0.71 (95% CI 0.50-0.86) and 0.71 (95% CI 059-0.81), for tumor size were 0.62 (95% CI 0.57-0.67) and 0.75 (95% CI 0.67-0.82), and for tumor volume were 0.77 (95% CI 0.68-0.84) and 0.72 (95% CI 0.56-0.83), respectively. Substantial heterogeneity was presented among included studies, and meta-regression showed that publication year (≤2017 vs. >2017) was the significant factor in studies using LCC as the quantitative assessment (P=0.02). CONCLUSION: Four quantitative assessments of LCC, ADC, tumor size, and tumor volume showed moderate to high diagnostic performance of predicting EPE. However, the optimal cutoff threshold varied widely among studies and needs further investigation to establish.

Normalization of Samples of Limited Amounts in Quantitative Metabolomics Using Liquid Chromatography Fluorescence Detection with Dansyl Labeling of Metabolites.

Quantitative metabolomics requires the analysis of the same or a very similar amount of samples in order to accurately determine the concentration differences of individual metabolites in comparative samples. Ideally, the total amount or concentration of metabolites in each sample is measured to normalize all the analyzed samples. In this work, we describe a very sensitive method to measure a subclass of metabolites as a surrogate quantifier for normalization of samples with limited amounts. This method starts with low-volume dansyl labeling of all metabolites containing a primary/secondary amine or phenol group in a sample to produce a final solution of 21 µL. The dansyl-labeled metabolites generate fluorescence signals at 520 nm with photoexcitation at 250 nm. To remove the interference of dansyl hydroxyl products (Dns-OH) formed from the labeling reagents used, a fast-gradient liquid chromatography separation is used to elute Dns-OH using aqueous solution, followed by organic solvent elution to produce a chromatographic peak of labeled metabolites, giving a measurement throughput of 6 min per sample. The integrated fluorescence signals of the peak are found to be related to the injection amount of the dansyl-labeled metabolites. A calibration curve using mixtures of dansyl-labeled amino acids is used to determine the total concentration of labeled metabolites in a sample. This concentration is used for normalization of samples in the range from 2 to 120 µM in 21 µL with only 1 µL consumed for fluorescence quantification (i.e., 2-120 pmol). We demonstrate the application of this sensitive sample normalization method in comparative metabolome analysis of human cancer cells, MCF-7 cells, treated with and without resveratrol, using a starting material of as low as 500 cells.

Diagnostic Performance of Extraprostatic Extension Grading System for Detection of Extraprostatic Extension in Prostate Cancer: A Diagnostic Systematic Review and Meta-Analysis.

PURPOSE: To evaluate the diagnostic performance of the extraprostatic extension (EPE) grading system for detection of EPE in patients with prostate cancer (PCa). MATERIALS AND METHODS: We performed a literature search of Web of Science, MEDLINE (Ovid and PubMed), Cochrane Library, EMBASE, and Google Scholar to identify eligible articles published before August 31, 2021, with no language restrictions applied. We included studies using the EPE grading system for the prediction of EPE, with histopathological results as the reference standard. The pooled sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), and diagnostic odds ratio (DOR) were calculated with the bivariate model. Quality assessment of included studies was performed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. RESULTS: A total of 4 studies with 1,294 patients were included in the current systematic review. The pooled sensitivity and specificity were 0.82 (95% CI 0.76-0.87) and 0.63 (95% CI 0.51-0.73), with the area under the hierarchical summary receiver operating characteristic (HSROC) curve of 0.82 (95% CI 0.79-0.85). The pooled LR+, LR-, and DOR were 2.20 (95% CI 1.70-2.86), 0.28 (95% CI 0.22-0.36), and 7.77 (95% CI 5.27-11.44), respectively. Quality assessment for included studies was high, and Deeks's funnel plot indicated that the possibility of publication bias was low (p = 0.64). CONCLUSION: The EPE grading system demonstrated high sensitivity and moderate specificity, with a good inter-reader agreement. However, this scoring system needs more studies to be validated in clinical practice.

High-Efficiency Metasurfaces with 2π Phase Control Based on Aperiodic Dielectric Nanoarrays.

In this study, the high-efficiency phase control Si metasurfaces are investigated based on aperiodic nanoarrays unlike widely-used period structures, the aperiodicity of which providing additional freedom to improve metasurfaces' performance. Firstly, the phase control mechanism of Huygens nanoblocks is demonstrated, particularly the internal electromagnetic resonances and the manipulation of effective electrical/magnetic polarizabilities. Then, a group of high-transmission Si nanoblocks with 2π phase control is sought by sweeping the geometrical parameters. Finally, several metasurfaces, such as grating and parabolic lens, are numerically realized by the nanostructures with high efficiency. The conversion efficiency of the grating reaches 80%, and the focusing conversion efficiency of the metalens is 99.3%. The results show that the high-efficiency phase control metasurfaces can be realized based on aperiodic nanoarrays, i.e., additional design freedom.

Comparison of diagnostic performance between two prostate imaging reporting and data system versions: A systematic review.

OBJECTIVE: To compare the diagnostic performance between Prostate Imaging Reporting and Data System version 1(PI-RADS v1) and PI-RADS v2 for detection of prostate cancer (PCa). METHODS: A systematic literature search was performed from inception to September 31, 2018, in following databases MEDLINE, EMBASE, Cochrane Library, Google Scholar, in addition to Chinese National Knowledge Infrastructure (CNKI) and Wanfang Data database. Sensitivity and specificity of individual studies along with summary estimates were calculated and presented in forest plots. Multiple subgroup analyses and meta-regression were performed to investigate the heterogeneity. Quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. RESULTS: 14 studies involving head to head comparison between PI-RADS v1 and v2 were included, with a total of 1682 patients. The pooled sensitivity for PI-RADS v1 and PI-RADS v2 were 85.37% (95% CI 79.29%-89.89%) and 87.79% (95% CI 79.84%-92.88%), with pooled specificity of 77.26% (95% CI 57.29%-89.58%) and 76.73% (95% CI 58.69%-88.44%), respectively. There was no substantial difference in diagnostic accuracy between PI-RADS v1 and PI-RADS v2 (P = 0.57 for sensitivity and P = 0.96 for specificity). Multiple subgroup analyses and meta-regression suggested these two scoring systems had comparable diagnostic performance on magnetic field strength, zonal anatomy, and outcome assessment. For the transitional zone, it seemed that PI-RADS v2 had higher sensitivity than PI-RADS v1 (90.1% vs. 80.59%), but the difference was not substantial (P = 0.17). CONCLUSION: PI-RADS v2 has slightly higher sensitivity but at the expense of minor decreased specificity. Thus, on the whole PI-RADS v1 and PI-RADS v2 have comparable diagnostic accuracy.

Parallel Metabolomic Profiling of Cerebrospinal Fluid and Serum for Identifying Biomarkers of Injury Severity after Acute Human Spinal Cord Injury.

Suffering an acute spinal cord injury (SCI) can result in catastrophic physical and emotional loss. Efforts to translate novel therapies in acute clinical trials are impeded by the SCI community's singular dependence upon functional outcome measures. Therefore, a compelling rationale exists to establish neurochemical biomarkers for the objective classification of injury severity. In this study, CSF and serum samples were obtained at 3 time points (~24, 48, and 72 hours post-injury) from 30 acute SCI patients (10 AIS A, 12 AIS B, and 8 AIS C). A differential chemical isotope labeling liquid chromatography mass spectrometry (CIL LC-MS) with a universal metabolome standard (UMS) was applied to the metabolomic profiling of these samples. This method provided enhanced detection of the amine- and phenol-containing submetabolome. Metabolic pathway analysis revealed dysregulations in arginine-proline metabolism following SCI. Six CSF metabolites were identified as potential biomarkers of baseline injury severity, and good classification performance (AUC > 0.869) was achieved by using combinations of these metabolites in pair-wise comparisons of AIS A, B and C patients. Using the UMS strategy, the current data set can be expanded to a larger cohort for biomarker validation, as well as discovering biomarkers for predicting neurologic outcome.

Sample normalization methods in quantitative metabolomics.

To reveal metabolomic changes caused by a biological event in quantitative metabolomics, it is critical to use an analytical tool that can perform accurate and precise quantification to examine the true concentration differences of individual metabolites found in different samples. A number of steps are involved in metabolomic analysis including pre-analytical work (e.g., sample collection and storage), analytical work (e.g., sample analysis) and data analysis (e.g., feature extraction and quantification). Each one of them can influence the quantitative results significantly and thus should be performed with great care. Among them, the total sample amount or concentration of metabolites can be significantly different from one sample to another. Thus, it is critical to reduce or eliminate the effect of total sample amount variation on quantification of individual metabolites. In this review, we describe the importance of sample normalization in the analytical workflow with a focus on mass spectrometry (MS)-based platforms, discuss a number of methods recently reported in the literature and comment on their applicability in real world metabolomics applications. Sample normalization has been sometimes ignored in metabolomics, partially due to the lack of a convenient means of performing sample normalization. We show that several methods are now available and sample normalization should be performed in quantitative metabolomics where the analyzed samples have significant variations in total sample amounts.

DnsID in MyCompoundID for rapid identification of dansylated amine- and phenol-containing metabolites in LC-MS-based metabolomics.

High-performance chemical isotope labeling (CIL) liquid chromatography-mass spectrometry (LC-MS) is an enabling technology based on rational design of labeling reagents to target a class of metabolites sharing the same functional group (e.g., all the amine-containing metabolites or the amine submetabolome) to provide concomitant improvements in metabolite separation, detection, and quantification. However, identification of labeled metabolites remains to be an analytical challenge. In this work, we describe a library of labeled standards and a search method for metabolite identification in CIL LC-MS. The current library consists of 273 unique metabolites, mainly amines and phenols that are individually labeled by dansylation (Dns). Some of them produced more than one Dns-derivative (isomers or multiple labeled products), resulting in a total of 315 dansyl compounds in the library. These metabolites cover 42 metabolic pathways, allowing the possibility of probing their changes in metabolomics studies. Each labeled metabolite contains three searchable parameters: molecular ion mass, MS/MS spectrum, and retention time (RT). To overcome RT variations caused by experimental conditions used, we have developed a calibration method to normalize RTs of labeled metabolites using a mixture of RT calibrants. A search program, DnsID, has been developed in www.MyCompoundID.org for automated identification of dansyl labeled metabolites in a sample based on matching one or more of the three parameters with those of the library standards. Using human urine as an example, we illustrate the workflow and analytical performance of this method for metabolite identification. This freely accessible resource is expandable by adding more amine and phenol standards in the future. In addition, the same strategy should be applicable for developing other labeled standards libraries to cover different classes of metabolites for comprehensive metabolomics using CIL LC-MS.

Dansylation metabolite assay: a simple and rapid method for sample amount normalization in metabolomics.

Metabolomics involves the comparison of the metabolomes of individual samples from two or more groups to reveal the metabolic differences. In order to measure the metabolite concentration differences accurately, using the same amount of starting materials is essential. In this work, we describe a simple and rapid method for sample amount normalization. It is based on dansylation labeling of the amine and phenol submetabolome of an individual sample, followed by solvent extraction of the labeled metabolites and ultraviolet (UV) absorbance measurement using a microplate reader. A calibration curve of a mixture of 17 dansyl-labeled amino acid standards is used to determine the total concentration of the labeled metabolites in a sample. According to the measured concentrations of individual samples, the volume of an aliquot taken from each sample is adjusted so that the same sample amount is taken for subsequent metabolome comparison. As an example of applications, this dansylation metabolite assay method is shown to be useful in comparative metabolome analysis of two different E. coli strains using a differential chemical isotope labeling LC-MS platform. Because of the low cost of equipment and reagents and the simple procedure used in the assay, this method can be readily implemented. We envisage that, this assay, which is analogous to the bicinchoninic acid (BCA) protein assay widely used in proteomics, will be applicable to many types of samples for quantitative metabolomics.

Comparative proteomic and metabolomic analysis of Staphylococcus warneri SG1 cultured in the presence and absence of butanol.

The complete genome of the solvent tolerant Staphylococcus warneri SG1 was recently published. This Gram-positive bacterium is tolerant to a large spectrum of organic solvents including short-chain alcohols, alkanes, esters and cyclic aromatic compounds. In this study, we applied a two-dimensional liquid chromatography (2D-LC) mass spectrometry (MS) shotgun approach, in combination with quantitative 2-MEGA (dimethylation after guanidination) isotopic labeling, to compare the proteomes of SG1 grown under butanol-free and butanol-challenged conditions. In total, 1585 unique proteins (representing 65% of the predicted open reading frames) were identified, covering all major metabolic pathways. Of the 967 quantifiable proteins by 2-MEGA labeling, 260 were differentially expressed by at least 1.5-fold. These proteins are involved in energy metabolism, oxidative stress response, lipid and cell envelope biogenesis, or have chaperone functions. We also applied differential isotope labeling LC-MS to probe metabolite changes in key metabolic pathways upon butanol stress. This is the first comprehensive proteomic and metabolomic study of S. warneri SG1 and presents an important step toward understanding its physiology and mechanism of solvent tolerance.

Development of isotope labeling liquid chromatography-mass spectrometry for metabolic profiling of bacterial cells and its application for bacterial differentiation.

Quantitative and comprehensive profiling of cellular metabolites is currently a challenging task in bacterial metabolomics. In this work, a simple and robust method for profiling the amine- and phenol-containing metabolome of bacterial cells is described. The overall workflow consists of methanol-based cell lysis and metabolite extraction with ultrasonication, differential isotope dansylation labeling of cellular metabolites, and analysis of the labeled metabolites by liquid chromatography-mass spectrometry (LC-MS). Over a thousand peak pairs or putative metabolites can be detected from bacterial cells in a 25 min LC-MS run and near 2500 putative metabolites can be found in one bacterium from combined results of multiple analyses. After careful examination and optimization of the sample preparation process, this method is shown to be effective for both Gram-positive and Gram-negative bacteria. An idea of applying LC-ultraviolet (UV) detection to quantify the total amount of labeled metabolites is shown to be effective for normalizing the amounts of metabolites present in different samples for metabolome comparison. The use of differential isotopic labeling allows relative quantification of each individual metabolite, which facilitates comparative metabolomics studies and the generation of a metabolic fingerprint of a bacterium. Finally, this method is demonstrated to be useful for the differentiation of three bacterial species in cultured media and spiked human urine samples.

MyCompoundID: using an evidence-based metabolome library for metabolite identification.

Identification of unknown metabolites is a major challenge in metabolomics. Without the identities of the metabolites, the metabolome data generated from a biological sample cannot be readily linked with the proteomic and genomic information for studies in systems biology and medicine. We have developed a web-based metabolite identification tool ( http://www.mycompoundid.org ) that allows searching and interpreting mass spectrometry (MS) data against a newly constructed metabolome library composed of 8,021 known human endogenous metabolites and their predicted metabolic products (375,809 compounds from one metabolic reaction and 10,583,901 from two reactions). As an example, in the analysis of a simple extract of human urine or plasma and the whole human urine by liquid chromatography-mass spectrometry and MS/MS, we are able to identify at least two times more metabolites in these samples than by using a standard human metabolome library. In addition, it is shown that the evidence-based metabolome library (EML) provides a much superior performance in identifying putative metabolites from a human urine sample, compared to the use of the ChemPub and KEGG libraries.

Determination of total concentration of chemically labeled metabolites as a means of metabolome sample normalization and sample loading optimization in mass spectrometry-based metabolomics.

For mass spectrometry (MS)-based metabolomics, it is important to use the same amount of starting materials from each sample to compare the metabolome changes in two or more comparative samples. Unfortunately, for biological samples, the total amount or concentration of metabolites is difficult to determine. In this work, we report a general approach of determining the total concentration of metabolites based on the use of chemical labeling to attach a UV absorbent to the metabolites to be analyzed, followed by rapid step-gradient liquid chromatography (LC) UV detection of the labeled metabolites. It is shown that quantification of the total labeled analytes in a biological sample facilitates the preparation of an appropriate amount of starting materials for MS analysis as well as the optimization of the sample loading amount to a mass spectrometer for achieving optimal detectability. As an example, dansylation chemistry was used to label the amine- and phenol-containing metabolites in human urine samples. LC-UV quantification of the labeled metabolites could be optimally performed at the detection wavelength of 338 nm. A calibration curve established from the analysis of a mixture of 17 labeled amino acid standards was found to have the same slope as that from the analysis of the labeled urinary metabolites, suggesting that the labeled amino acid standard calibration curve could be used to determine the total concentration of the labeled urinary metabolites. A workflow incorporating this LC-UV metabolite quantification strategy was then developed in which all individual urine samples were first labeled with (12)C-dansylation and the concentration of each sample was determined by LC-UV. The volumes of urine samples taken for producing the pooled urine standard were adjusted to ensure an equal amount of labeled urine metabolites from each sample was used for the pooling. The pooled urine standard was then labeled with (13)C-dansylation. Equal amounts of the (12)C-labeled individual sample and the (13)C-labeled pooled urine standard were mixed for LC-MS analysis. This way of concentration normalization among different samples with varying concentrations of total metabolites was found to be critical for generating reliable metabolome profiles for comparison.