Separation technique for the determination of highly polar metabolites in biological samples

Microbiome metabolite quantification methods enabling insights into human health and disease

Many of the health-associated impacts of the microbiome are mediated by its chemical activity, producing and modifying small molecules (metabolites). Thus, microbiome metabolite quantification has a central role in efforts to elucidate and measure microbiome function. In this review, we cover general considerations when designing experiments to quantify microbiome metabolites, including sample preparation, data acquisition and data processing, since these are critical to downstream data quality. We then discuss data analysis and experimental steps to demonstrate that a given metabolite feature is of microbial origin. We further discuss techniques used to quantify common microbial metabolites, including short-chain fatty acids (SCFA), secondary bile acids (BAs), tryptophan derivatives, N-acyl amides and trimethylamine N-oxide (TMAO). Lastly, we conclude with challenges and future directions for the field.

Biological biomarkers of oral cancer

The oral squamous cell carcinoma (OSCC) 5 year survival rate of 41% has marginally improved in the last few years, with less than a 1% improvement per year from 2005 to 2017, with higher survival rates when detected at early stages. Based on histopathological grading of oral dysplasia, it is estimated that severe dysplasia has a malignant transformation rate of 7%-50%. Despite these numbers, oral dysplasia grading does not reliably predict its clinical behavior. Thus, more accurate markers predicting oral dysplasia progression to cancer would enable better targeting of these lesions for closer follow-up, especially in the early stages of the disease. In this context, molecular biomarkers derived from genetics, proteins, and metabolites play key roles in clinical oncology. These molecular signatures can help predict the likelihood of OSCC development and/or progression and have the potential to detect the disease at an early stage and, support treatment decision-making and predict treatment responsiveness. Also, identifying reliable biomarkers for OSCC detection that can be obtained non-invasively would enhance management of OSCC. This review will discuss biomarkers for OSCC that have emerged from different biological areas, including genomics, transcriptomics, proteomics, metabolomics, immunomics, and microbiomics.

Analysis of Fatty Acid Composition in Sprouted Grains

A whole-grain diet is associated with the prevention of metabolic syndromes, including obesity, diabetes, and cardiovascular diseases. Sprouting improves the nutritional profile and bioactive properties of grains, which are important for use as raw ingredients in the food industry. The aim of this review was to examine the lipid and fatty acid composition of germinated grains. The methods discussed include germination and analytical procedures for determining fat and fatty acid contents of grains. The effects of sprouting on the fat content and storage stability of grains were also assessed. Lipid levels ranged from 1.43% to 6.66% in the sprouted grains. The individual fatty acid content of grains changed depending on the germination conditions (17-37 °C, 1-9 days). Limited findings showed that sprouting grains at higher temperatures (20-25 °C) and longer times generated a healthy balance of omega-6 and omega-3 fatty acids, which is beneficial to humans. Future studies are needed to determine the optimum incubation and germination periods specific to each grain to improve the omega-6/omega-3 ratio. Free fatty acids were produced more slowly and levels of oxidation products were lower in sprouted grains than in the raw ingredients when stored for a year. Additional studies are required to investigate the oxidative stability and shelf life of sprouted grains.

Evaluation of Two Simultaneous Metabolomic and Proteomic Extraction Protocols Assessed by Ultra-High-Performance Liquid Chromatography Tandem Mass Spectrometry

Untargeted multi-omics analysis of plasma is an emerging tool for the identification of novel biomarkers for evaluating disease prognosis, and for developing a better understanding of molecular mechanisms underlying human disease. The successful application of metabolomic and proteomic approaches relies on reproducibly quantifying a wide range of metabolites and proteins. Herein, we report the results of untargeted metabolomic and proteomic analyses from blood plasma samples following analyte extraction by two frequently-used solvent systems: chloroform/methanol and methanol-only. Whole blood samples were collected from participants (n = 6) at University Hospital Sharjah (UHS) hospital, then plasma was separated and extracted by two methods: (i) methanol precipitation and (ii) 4:3 methanol:chloroform extraction. The coverage and reproducibility of the two methods were assessed by ultra-high-performance liquid chromatography-electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS). The study revealed that metabolite extraction by methanol-only showed greater reproducibility for both metabolomic and proteomic quantifications than did methanol/chloroform, while yielding similar peptide coverage. However, coverage of extracted metabolites was higher with the methanol/chloroform precipitation.

Advances in experimental and computational methodologies for the study of microbial-surface interactions at different omics levels

The study of the biological response of microbial cells interacting with natural and synthetic interfaces has acquired a new dimension with the development and constant progress of advanced omics technologies. New methods allow the isolation and analysis of nucleic acids, proteins and metabolites from complex samples, of interest in diverse research areas, such as materials sciences, biomedical sciences, forensic sciences, biotechnology and archeology, among others. The study of the bacterial recognition and response to surface contact or the diagnosis and evolution of ancient pathogens contained in archeological tissues require, in many cases, the availability of specialized methods and tools. The current review describes advances in in vitro and in silico approaches to tackle existing challenges (e.g., low-quality sample, low amount, presence of inhibitors, chelators, etc.) in the isolation of high-quality samples and in the analysis of microbial cells at genomic, transcriptomic, proteomic and metabolomic levels, when present in complex interfaces. From the experimental point of view, tailored manual and automatized methodologies, commercial and in-house developed protocols, are described. The computational level focuses on the discussion of novel tools and approaches designed to solve associated issues, such as sample contamination, low quality reads, low coverage, etc. Finally, approaches to obtain a systems level understanding of these complex interactions by integrating multi omics datasets are presented.

Salivary Metabolomics for Oral Squamous Cell Carcinoma Diagnosis: A Systematic Review

Oral squamous cell carcinoma (OSCC) is the most common type of oral cancer in which the consumption of tobacco and alcohol is considered to be the main aetiological factor. Salivary metabolome profiling could identify novel biochemical pathways involved in the pathogenesis of various diseases. This systematic review was designed to answer the question “Are salivary metabolites reliable for the diagnosis of oral squamous cell carcinoma?”. Following the inclusion and exclusion criteria, nineteen studies were included (according to PRISMA statement guidelines). In all included studies, the diagnostic material was unstimulated whole saliva, whose metabolome changes were determined by different spectroscopic methods. At the metabolic level, OSCC patients differed significantly not only from healthy subjects but also from patients with oral leukoplakia, lichen planus or other oral potentially malignant disorders. Among the detected salivary metabolites, there were the indicators of the impaired metabolic pathways, such as choline metabolism, amino acid pathways, polyamine metabolism, urea cycle, creatine metabolism, glycolysis or glycerolipid metabolism. In conclusion, saliva contains many potential metabolites, which can be used reliably to early diagnose and monitor staging in patients with OSCC. However, further investigations are necessary to confirm these findings and to identify new salivary metabolic biomarkers.

GC-MS Metabolic Profile and α-Glucosidase-, α-Amylase-, Lipase-, and Acetylcholinesterase-Inhibitory Activities of Eight Peach Varieties

The inhibition of certain digestive enzymes by target food matrices represents a new approach in the treatment of socially significant diseases. Proving the ability of fruits to inhibit such enzymes can support the inclusion of specific varieties in the daily diets of patients with diabetes, obesity, Alzheimer's disease, etc., providing them with much more than just valuable micro- and macromolecules. The current study aimed atidentifying and comparing the GC-MS metabolic profiles of eight peach varieties ("Filina", "Ufo 4, "Gergana", "Laskava", "July Lady", "Flat Queen", "Evmolpiya", and "Morsiani 90") grown in Bulgaria (local and introduced) and to evaluate the inhibitory potential of their extracts towards α-glucosidase, α-amylase, lipase, and acetylcholinesterase. In order to confirm samples' differences or similarities, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were also applied to the identified metabolites. The results provide important insights into the metabolomic profiles of the eight peach varieties and represent a first attempt to characterize the peels of the peach varieties with respect to α-glucosidase-, α-amylase-, lipase-, and acetylcholinesterase-inhibitory activities. All of the studied peach extracts displayed inhibitory activity towards α-glucosidase (IC₅₀: 125-757 mg/mL) and acetylcholinesterase (IC₅₀: 60-739 mg/mL), but none of them affected α-amylase activity. Five of the eight varieties showed inhibitory activity towards porcine pancreatic lipase (IC₅₀: 24-167 mg/mL). The obtained results validate the usefulness of peaches and nectarines as valuable sources of natural agents beneficial for human health, although further detailed investigation should be performed in order to thoroughly identify the enzyme inhibitors responsible for each activity.

Development and Validation of a Simple and Sensitive LC-MS/MS Method for Quantification of Metformin in Dried Blood Spot Its Application as an Indicator for Medication Adherence

OBJECTIVE

Metformin (MET), an oral biguanide agent, can improve insulin resistance and decrease hepatic glucose production, leading to a reduction in blood-sugar levels. The objective of the present study was to develop and validate simple and rapid LC-MS/MS method for analysis of MET in dried blood spot (DBS) sample for patient monitoring studies purposes (drug adherence).

METHODS

The chromatographic separation was achieved with Waters HSS-T3 column using gradient elution of mobile phases of two solvents: 1) solvent A, consisted of 10mM ammonium formate, 0.2% formic acid 1%; and 2) acetonitrile solvent B, contained 0.2% formic acid in acetonitrile at a flow rate of 0.2 mL/min. The total run time was 3.0 min. The effectiveness of chromatographic conditions was optimized, and afatinib was used as the internal standard. The assay method was validated using USP 26 and the ICH guidelines.

RESULTS

The method showed good linearity in the range 8-48 ng/mL for MET with correlation coefficient (r) >0.9907. The intra- and inter‑day precision values for MET met the acceptance criteria as per regulatory guidelines. MET was stable during the stability studies at ambient temperature 25 °C, at refrigerator 4 °C, at 10 °C autosampler, freeze/thaw cycles and 30 days storage in a freezer at -30 ± 0.5 °C.

CONCLUSION

This method has successfully fulfilled all validation requirements referring to EMA and FDA guidelines, and successfully can be applied for MET adherence study. All the six studied patients were approved to metformin adherence.

Metabolomic-based clinical studies and murine models for acute pancreatitis disease: A review

Acute pancreatitis (AP) is one of the most common gastroenterological disorders requiring hospitalization and is associated with substantial morbidity and mortality. Metabolomics nowadays not only help us to understand cellular metabolism to a degree that was not previously obtainable, but also to reveal the importance of the metabolites in physiological control, disease onset and development. An in-depth understanding of metabolic phenotyping would be therefore crucial for accurate diagnosis, prognosis and precise treatment of AP. In this review, we summarized and addressed the metabolomics design and workflow in AP studies, as well as the results and analysis of the in-depth of research. Based on the metabolic profiling work in both clinical populations and experimental AP models, we described the metabolites with potential utility as biomarkers and the correlation between the altered metabolites and AP status. Moreover, the disturbed metabolic pathways correlated with biological function were discussed in the end. A practical understanding of current and emerging metabolomic approaches applicable to AP and use of the metabolite information presented will aid in designing robust metabolomics and biological experiments that result in identification of unique biomarkers and mechanisms, and ultimately enhanced clinical decision-making.

LC-MS-MS Determination of 25 Antipsychotic Drugs and Metabolites in Urine for Medication Compliance Monitoring

A liquid chromatography-tandem mass spectrometry (LC-MS-MS) method was developed for 25 antipsychotic drugs and their metabolite in urine for monitoring medication compliance of mentally disordered criminals on probation. Target compounds were extracted with a solid-phase extraction technique using a newly developed hydrophilic-lipophilic balanced sorbent to remove interferences and minimize the matrix effect (ME). Extracted sample was injected into the LC-MS-MS with an electrospray ionization source in positive mode and multiple-reaction monitoring mode. The analytes were separated and detected within 10 minutes using a reversed-phase column with a gradient elution method using 0.1% formic acid in water and 0.1% formic acid in methanol as mobile phase. The validation parameters were evaluated as follows: selectivity, limit of detection, lower limit of quantification (LLOQ), linearity, accuracy and precision, stability, dilution integrity, recovery (RE), ME and process efficiency (PE). The LLOQs were 0.1 to 2.0 ng/mL, and determination coefficients of the calibration curve were above 0.9943 over the concentration ranges. The intra-and inter-day accuracy ranged from -10.4% to 9.9% and from -9.6% to 9.4%, while the intra-and inter-day precision were within 10.7% and 9.9%. The bench-top and long-term stability ranged from 92.1% to 109.5% and 88.7% to 111.6%, respectively. The reproducibility of auto-sampler stability was <10% for all analytes. The accuracy and precision of dilution integrity ranged from -11.7% to 10.5% and 0.4% to 9.9%, respectively. The relative standard deviation of RE and ME was from 0.6% to 6.6% and 0.5% to 3.9%, respectively, while that of PE was 1.3% to 4.5%. The developed LC-MS-MS method for medication compliance monitoring was successfully applied to urine samples from mentally disordered probationers and determined to be one of effective ways for preventing the recurrence of mentally disordered crimes.

Metabolomics: The Stethoscope for the Twenty-First Century

Metabolomics encompasses the systematic identification and quantification of all metabolic products in the human body. This field could provide clinicians with novel sets of diagnostic biomarkers for disease states in addition to quantifying treatment response to medications at an individualized level. This literature review aims to highlight the technology underpinning metabolic profiling, identify potential applications of metabolomics in clinical practice, and discuss the translational challenges that the field faces. We searched PubMed, MEDLINE, and EMBASE for primary and secondary research articles regarding clinical applications of metabolomics. Metabolic profiling can be performed using mass spectrometry and nuclear magnetic resonance-based techniques using a variety of biological samples. This is carried out in vivo or in vitro following careful sample collection, preparation, and analysis. The potential clinical applications constitute disruptive innovations in their respective specialities, particularly oncology and metabolic medicine. Outstanding issues currently preventing widespread clinical use are scalability of data interpretation, standardization of sample handling practice, and e-infrastructure. Routine utilization of metabolomics at a patient and population level will constitute an integral part of future healthcare provision.

Lemna minor studies under various storage periods using extended-polarity extraction and metabolite non-target screening analysis

Plant metabolomic studies cover a broad band of compounds, including various functional groups with different polarities and other physiochemical properties. For this reason, specific optimized methods are needed in order to enable efficient and non-destructive extraction of molecules over a large range of LogD values. This study presents a simple and efficient extraction procedure for Lemna minor samples demonstrating polarity extension of the molecular range. The Lemna samples chosen were kept under the following storage conditions: 1) fresh, 2) stored for a few days at -80 °C, and 3) stored for 6 months at -80 °C. The samples were extracted using five specifically chosen solvents: 100 % ethanol, 100 % methanol (MeOH), acidic 90 % MeOH (MeOH-water-formic acid (FAC) (90:9.5:0.5, v/v/v), MeOH-water (50:50, v/v), and 100 % water. The final extraction procedure was conducted subject to three solvent conditions, and the subsequent polarity-extended analysis was applied for Lemna minor samples using RPLC-HILIC-ESI-TOF-MS. The extraction yield is in descending order (acidic 90 % MeOH), 50 % MeOH, 100 % water and 100 % MeOH. The results displayed significant molecular differences, both in the extracts investigated and in the fresh Lemna samples, compared to stored samples, in terms of the extraction yield and reducing contents as well as the number of features. The storage of Lemna minor resulted in changes to the fingerprint of its metabolites as the reducing contents increased. The comparisons enable a direct view of molecule characterizations, in terms of their polarity, molecular mass, and signal intensity. This parametric information would appear ideal for further statistical data analysis. Consequently, the extraction procedure and the analysis/data evaluation are highly suitable for the so-called extended-polarity non-target screening procedure.

Acyl ethanolamides in Diabetes and Diabetic Nephropathy: Novel targets from untargeted plasma metabolomic profiles of South Asian Indian men

The pathophysiology of diabetic nephropathy (DN) in type 2 diabetes (T2D) patients is minimally understood. We compared untargeted high-resolution accurate mass (HRAM) orbitrap-based plasma metabolomic profiles of 31 T2D-DN (with estimated glomerular filtration rate ≤80 mL/min/1.73 m²), 29 T2D and 30 normal glucose tolerance (NGT) Indian men. Of the 939 plasma metabolites that were differentially abundant amongst the NGT, T2D and T2D-DN (ANOVA, False Discovery Rate – FDR adjusted p-value < 0.05), 48 were associated with T2D irrespective of the renal function of the subjects. Acyl ethanolamides and acetylcholine were decreased while monoacylglycerols (MAGs) and cortisol were elevated in both T2D and T2D-DN. Sixteen metabolites, including amino acid metabolites Imidazolelactate and N-Acetylornithine, changed significantly between NGT, T2D and T2D-DN. 192 metabolites were specifically dysregulated in T2D-DN (ratio ≥2 or ≤0.5 between T2D-DN and T2D, similar abundance in NGT and T2D). These included increased levels of multiple acylcarnitine and amino acid metabolites. We observed a significant dysregulation of amino acid and fatty acid metabolism in South Asian Indian male T2D-DN subjects. Unique to this study, we report a reduction in acyl ethanolamide levels in both T2D and T2D-DN males. Those with dysregulation in acyl ethanolamides, which are endogenous agonists of GPR119, are likely to exhibit improved glycemic control with GPR119 agonists.

Metabolomics Analysis of Mesenchymal Stem Cells

Various mesenchymal stem cells as easily accessible and multipotent cells can share different essential signaling pathways related to their stemness ability. Understanding the mechanism of stemness ability can be useful for controlling the stem cells for regenerative medicine targets. In this context, OMICs studies can analyze the mechanism of different stem cell properties or stemness ability via a broad range of current high-throughput techniques. This field is fundamentally directed toward the analysis of whole genome (genomics), mRNAs (transcriptomics), proteins (proteomics) and metabolites (metabolomics) in biological samples. According to several studies, metabolomics is more effective than other OMICs ّfor various system biology concerns. Metabolomics can elucidate the biological mechanisms of various mesenchymal stem cell function by measuring their metabolites such as their secretome components. Analyzing the metabolic alteration of mesenchymal stem cells can be useful to promote their regenerative medicine application.

Quality and Authenticity Control of Fruit Juices-A Review

Food fraud, being the act of intentional adulteration of food for financial advantage, has vexed the consumers and the food industry throughout history. According to the European Committee on the Environment, Public Health and Food Safety, fruit juices are included in the top 10 food products that are most at risk of food fraud. Therefore, reliable, efficient, sensitive and cost-effective analytical methodologies need to be developed continuously to guarantee fruit juice quality and safety. This review covers the latest advances in the past ten years concerning the targeted and non-targeted methodologies that have been developed to assure fruit juice authenticity and to preclude adulteration. Emphasis is placed on the use of hyphenated techniques and on the constantly-growing role of MS-based metabolomics in fruit juice quality control area.

Small Polar Molecules: A Challenge in Marine Chemical Ecology

Due to increasing evidence of key chemically mediated interactions in marine ecosystems, a real interest in the characterization of the metabolites involved in such intra and interspecific interactions has emerged over the past decade. Nevertheless, only a small number of studies have succeeded in identifying the chemical structure of compounds of interest. One reason for this low success rate is the small size and extremely polar features of many of these chemical compounds. Indeed, a major challenge in the search for active metabolites is the extraction of small polar compounds from seawater. Yet, a full characterization of those metabolites is necessary to understand the interactions they mediate. In this context, the study presented here aims to provide a methodology for the characterization of highly polar, low molecular weight compounds in a seawater matrix that could provide guidance for marine ecologists in their efforts to identify active metabolites. This methodology was applied to the investigation of the chemical structure of an algicidal compound secreted by the bacteria Shewanella sp. IRI-160 that was previously shown to induce programmed cell death in dinoflagellates. The results suggest that the algicidal effects may be attributed to synergistic effects of small amines (ammonium, 4-aminobutanal) derived from the catabolization of putrescine produced in large quantities (0.05–6.5 fmol/cell) by Shewanella sp. IRI-160.

Investigation of Metabolomic Changes in Sunitinib-Resistant Human Renal Carcinoma 786-O Cells by Capillary Electrophoresis-Time of Flight Mass Spectrometry

Acquired resistance to sunitinib is a challenge in the treatment of renal cell carcinoma (RCC). The dysregulation of cellular metabolism is prevalent during resistance acquisition. It is known that in sunitinib-resistant RCC 786-O (786-O Res) cells sunitinib is mainly sequestered in the intracellular lysosomes. However, the relevance between sunitinib resistance and cellular metabolism has not been examined. In this study, we examined the metabolic changes in 786-O Res by using capillary electrophoresis-time of flight mass spectrometry. The cell line 786-O Res was established via persistent treatment with sunitinib, where increase in intracellular sunitinib, and sizes of lysosomes and nuclei were enhanced as compared with those in the parental 786-O (786-O Par) cells. Metabolic analyses revealed that out of the 110 metabolites examined, 13 were up-regulated and 4 were down-regulated in the 786-O Res cells. The glycolysis, tricarboxylic acid cycle and pentose phosphate pathway (PPP) were identified as being altered in the sunitinib-resistant cells, which resulted in the enhanced metabolisms of energy, nucleic acids, and glutathione redox cycle. As sunitinib was sequestered in the enlarged lysosomes in 786-O Res, the enriched energy metabolism might contribute to the maintenance of luminal pH in lysosomes via the H+ ATPase. The changes in the PPP could contribute to nuclei enlargement through up-regulation of nucleic acid biosynthesis and protect 786-O Res from cytotoxicity induced by sunitinib through up-regulation of reduced glutathione. Though the direct link between sunitinib resistance and metabolic alternation remains to be elucidated, this metabolomics study provides fundamental insights into acquisition of sunitinib resistance.

Characterizing amino-acid biosignatures amongst individuals with schizophrenia: a case-control study

Amino acids and derivatives participate in the biosynthesis and downstream effects of numerous neurotransmitters. Variations in specific amino acids have been implicated in the pathophysiology of schizophrenia. Herein, we sought to compare levels of amino acids and derivatives between subjects with schizophrenia and healthy controls (HC). Two hundred and eight subjects with Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria (DSM-IV)-defined schizophrenia and 175 age- and sex-matched HC were enrolled. The levels of twenty-five amino acids and seven related derivatives were measured in plasma samples using hydrophilic interaction liquid chromatography (HILIC) liquid chromatography-tandem mass spectrometry (LC-MS). After controlling for age, sex and body mass index (BMI), four amino acids and derivatives (i.e., cysteine, GABA, glutamine and sarcosine) were observed to be higher in the schizophrenia group when compared with HC; seven amino acids and derivatives were lower in the schizophrenia group (i.e., arginine, L-ornithine, threonine, taurine, tryptophan, methylcysteine, and kynurenine). Statistically significant differences in plasma amino-acid profiles between subjects with first-episode vs. recurrent schizophrenia for aspartate and glutamine were also demonstrated using generalized linear models controlling for age, sex, and BMI. The differences in amino acids and derivatives among individuals with schizophrenia when compared to HC may represent underlying pathophysiology, including but not limited to dysfunctional proteinogenic processes, alterations in excitatory and inhibitory neurotransmission, changes in ammonia metabolism and the urea cycle. Taken together, amino-acid profiling may provide a novel stratification approach among individuals with schizophrenia.

Emerging Diagnostic and Therapeutic Potentials of Human Hair Proteomics

The use of noninvasive human substrates to interrogate pathophysiological conditions has become essential in the post- Human Genome Project era. Due to its high turnover rate, and its long term capability to incorporate exogenous and endogenous substances from the circulation, hair testing is emerging as a key player in monitoring long term drug compliance, chronic alcohol abuse, forensic toxicology, and biomarker discovery, among other things. Novel high-throughput 'omics based approaches like proteomics have been underutilized globally in comprehending human hair morphology and its evolving use as a diagnostic testing substrate in the era of precision medicine. There is paucity of scientific evidence that evaluates the difference in drug incorporation into hair based on lipid content, and very few studies have addressed hair growth rates, hair forms, and the biological consequences of hair grooming or bleaching. It is apparent that protein-based identification using the human hair proteome would play a major role in understanding these parameters akin to DNA single nucleotide polymorphism profiling, up to single amino acid polymorphism resolution. Hence, this work seeks to identify and discuss the progress made thus far in the field of molecular hair testing using proteomic approaches, and identify ways in which proteomics would improve the field of hair research, considering that the human hair is mostly composed of proteins. Gaps in hair proteomics research are identified and the potential of hair proteomics in establishing a historic medical repository of normal and disease-specific proteome is also discussed.

Beyond the paradigm: Combining mass spectrometry and nuclear magnetic resonance for metabolomics

Metabolomics is undergoing tremendous growth and is being employed to solve a diversity of biological problems from environmental issues to the identification of biomarkers for human diseases. Nuclear magnetic resonance (NMR) and mass spectrometry (MS) are the analytical tools that are routinely, but separately, used to obtain metabolomics data sets due to their versatility, accessibility, and unique strengths. NMR requires minimal sample handling without the need for chromatography, is easily quantitative, and provides multiple means of metabolite identification, but is limited to detecting the most abundant metabolites (⩾1μM). Conversely, mass spectrometry has the ability to measure metabolites at very low concentrations (femtomolar to attomolar) and has a higher resolution (∼10³-10⁴) and dynamic range (∼10³-10⁴), but quantitation is a challenge and sample complexity may limit metabolite detection because of ion suppression. Consequently, liquid chromatography (LC) or gas chromatography (GC) is commonly employed in conjunction with MS, but this may lead to other sources of error. As a result, NMR and mass spectrometry are highly complementary, and combining the two techniques is likely to improve the overall quality of a study and enhance the coverage of the metabolome. While the majority of metabolomic studies use a single analytical source, there is a growing appreciation of the inherent value of combining NMR and MS for metabolomics. An overview of the current state of utilizing both NMR and MS for metabolomics will be presented.

Estratégias analíticas com cromatografia e espectrometria de massas para biomonitorização da exposição ao benzeno pela determinação do ácido S-fenilmercaptúrico urinário

Resumo Introdução: o benzeno é uma substância de reconhecida toxicidade e sua biomonitorização torna-se fundamental para a prevenção de danos à saúde humana, principalmente em situações de exposição ocupacional. Dentre os biomarcadores de exposição, o ácido S-fenilmercaptúrico é considerado o único específico, mas, devido a suas baixas concentrações na urina, é requerido o uso de técnicas analíticas sensíveis capazes de quantificar traços. Objetivo: revisar metodologias baseadas na cromatografia e na espectrometria de massas para a determinação do ácido S-fenilmercaptúrico. Método: revisão da literatura sobre a determinação do ácido S-fenilmercaptúrico urinário por técnicas de cromatografia e espectrometria de massas, nas principais bases de dados científicas, considerando o período entre 1951 e 2015. Resultados: 120 documentos serviram como base teórica para a construção desta revisão. A técnica analítica mais empregada foi o acoplamento da cromatografia a líquido com a espectrometria de massas. Contudo, os métodos diferem quanto ao preparo das amostras. Conclusão: o alto custo de aquisição e a manutenção de equipamentos são fatores limitantes para a difusão dos sistemas de cromatografia e espectrometria de massas. No entanto, sua elevada sensibilidade e seletividade faz com que essas técnicas, acopladas, possibilitem elucidar situações de exposição ocupacional e ambiental a poluentes, como o benzeno.

Targeted cofactor quantification in metabolically engineered E. coli using solid phase extraction and hydrophilic interaction liquid chromatography-mass spectrometry

Quantification of energy and redox cofactors is of great value to synthetic biologists to infer the balance of energy metabolism in engineered microbial strains and assess each strain's potential for further improvement. Most currently used methods for intracellular cofactor measurement suffer from incomplete coverage, low reproducibility, suboptimal sensitivity or specificity. In this study, we described an SPE-HILIC/MS approach for simultaneous determination of six cofactor targets (ATP, ADP, NAD, NADH, NADP, NADPH) in Escherichia coli cells. Sufficient linearity, precision and metabolite recoveries of this new approach justified its reliability in targeted cofactor quantification. Our approach was then compared with conventional enzymatic assays to demonstrate its superior performance. We applied the SPE-HILIC/MS approach to profile shift of cofactor balances in several engineered E. coli strains with varying isobutanol production. Our cofactor analysis clearly revealed that optimal energy fitness was achieved in the highest-yield strain through combined modulation of a transhydrogenase and a NAD(+) kinase. Apart from the targeted cofactors, the SPE enrichment procedure also allowed for confident identification of 39 groups of polar metabolites mainly involved in central carbon metabolism in E. coli cells.

Application of stable isotope-assisted metabolomics for cell metabolism studies

The applications of stable isotopes in metabolomics have facilitated the study of cell metabolisms. Stable isotope-assisted metabolomics requires: (1) properly designed tracer experiments; (2) stringent sampling and quenching protocols to minimize isotopic alternations; (3) efficient metabolite separations; (4) high resolution mass spectrometry to resolve overlapping peaks and background noises; and (5) data analysis methods and databases to decipher isotopic clusters over a broad m/z range (mass-to-charge ratio). This paper overviews mass spectrometry based techniques for precise determination of metabolites and their isotopologues. It also discusses applications of isotopic approaches to track substrate utilization, identify unknown metabolites and their chemical formulas, measure metabolite concentrations, determine putative metabolic pathways, and investigate microbial community populations and their carbon assimilation patterns. In addition, 13C-metabolite fingerprinting and metabolic models can be integrated to quantify carbon fluxes (enzyme reaction rates). The fluxome, in combination with other "omics" analyses, may give systems-level insights into regulatory mechanisms underlying gene functions. More importantly, 13C-tracer experiments significantly improve the potential of low-resolution gas chromatography-mass spectrometry (GC-MS) for broad-scope metabolism studies. We foresee the isotope-assisted metabolomics to be an indispensable tool in industrial biotechnology, environmental microbiology, and medical research.