Displaying publications 1 - 20 of 88 in total

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  1. Aizat WM, Ismail I, Noor NM
    Adv. Exp. Med. Biol., 2018 11 2;1102:1-9.
    PMID: 30382565 DOI: 10.1007/978-3-319-98758-3_1
    The central dogma of molecular biology (DNA, RNA, protein and metabolite) has engraved our understanding of genetics in all living organisms. While the concept has been embraced for many decades, the development of high-throughput technologies particularly omics (genomics, transcriptomics, proteomics and metabolomics) has revolutionised the field to incorporate big data analysis including bioinformatics and systems biology as well as synthetic biology area. These omics approaches as well as systems and synthetic biology areas are now increasingly popular as seen by the growing numbers of publication throughout the years. Several journals which have published most of these related fields are also listed in this chapter to overview their impact and target journals.
    Matched MeSH terms: Metabolomics/trends*
  2. Ismail SN, Maulidiani M, Akhtar MT, Abas F, Ismail IS, Khatib A, et al.
    Molecules, 2017 Sep 25;22(10).
    PMID: 28946701 DOI: 10.3390/molecules22101612
    Gaharu (agarwood, Aquilaria malaccensis Lamk.) is a valuable tropical rainforest product traded internationally for its distinctive fragrance. It is not only popular as incense and in perfumery, but also favored in traditional medicine due to its sedative, carminative, cardioprotective and analgesic effects. The current study addresses the chemical differences and similarities between gaharu samples of different grades, obtained commercially, using ¹H-NMR-based metabolomics. Two classification models: partial least squares-discriminant analysis (PLS-DA) and Random Forests were developed to classify the gaharu samples on the basis of their chemical constituents. The gaharu samples could be reclassified into a 'high grade' group (samples A, B and D), characterized by high contents of kusunol, jinkohol, and 10-epi-γ-eudesmol; an 'intermediate grade' group (samples C, F and G), dominated by fatty acid and vanillic acid; and a 'low grade' group (sample E and H), which had higher contents of aquilarone derivatives and phenylethyl chromones. The results showed that ¹H- NMR-based metabolomics can be a potential method to grade the quality of gaharu samples on the basis of their chemical constituents.
    Matched MeSH terms: Metabolomics/methods*
  3. Lee LK, Foo KY
    Clin. Biochem., 2014 Jul;47(10-11):973-82.
    PMID: 24875852 DOI: 10.1016/j.clinbiochem.2014.05.053
    Infertility is a worldwide reproductive health problem which affects approximately 15% of couples, with male factor infertility dominating nearly 50% of the affected population. The nature of the phenomenon is underscored by a complex array of transcriptomic, proteomic and metabolic differences which interact in unknown ways. Many causes of male factor infertility are still defined as idiopathic, and most diagnosis tends to be more descriptive rather than specific. As such, the emergence of novel transcriptomic and metabolomic studies may hold the key to more accurately diagnose and treat male factor infertility. This paper provides the most recent evidence underlying the role of transcriptomic and metabolomic analysis in the management of male infertility. A summary of the current knowledge and new discovery of noninvasive, highly sensitive and specific biomarkers which allow the expansion of this area is outlined.
    Matched MeSH terms: Metabolomics/methods
  4. Ma NL, Rahmat Z, Lam SS
    Int J Mol Sci, 2013;14(4):7515-41.
    PMID: 23567269 DOI: 10.3390/ijms14047515
    Physiological and ecological constraints that cause the slow growth and depleted production of crops have raised a major concern in the agriculture industry as they represent a possible threat of short food supply in the future. The key feature that regulates the stress signaling pathway is always related to the reactive oxygen species (ROS). The accumulation of ROS in plant cells would leave traces of biomarkers at the genome, proteome, and metabolome levels, which could be identified with the recent technological breakthrough coupled with improved performance of bioinformatics. This review highlights the recent breakthrough in molecular strategies (comprising transcriptomics, proteomics, and metabolomics) in identifying oxidative stress biomarkers and the arising opportunities and obstacles observed in research on biomarkers in rice. The major issue in incorporating bioinformatics to validate the biomarkers from different omic platforms for the use of rice-breeding programs is also discussed. The development of powerful techniques for identification of oxidative stress-related biomarkers and the integration of data from different disciplines shed light on the oxidative response pathways in plants.
    Matched MeSH terms: Metabolomics/methods*
  5. Akpunarlieva S, Weidt S, Lamasudin D, Naula C, Henderson D, Barrett M, et al.
    J Proteomics, 2017 02 23;155:85-98.
    PMID: 28040509 DOI: 10.1016/j.jprot.2016.12.009
    Leishmania parasites multiply and develop in the gut of a sand fly vector in order to be transmitted to a vertebrate host. During this process they encounter and exploit various nutrients, including sugars, and amino and fatty acids. We have previously generated a mutant Leishmania line that is deficient in glucose transport and which displays some biologically important phenotypic changes such as reduced growth in axenic culture, reduced biosynthesis of hexose-containing virulence factors, increased sensitivity to oxidative stress, and dramatically reduced parasite burden in both insect vector and macrophage host cells. Here we report the generation and integration of proteomic and metabolomic approaches to identify molecular changes that may explain these phenotypes. Our data suggest changes in pathways of glycoconjugate production and redox homeostasis, which likely represent adaptations to the loss of sugar uptake capacity and explain the reduced virulence of this mutant in sand flies and mammals. Our data contribute to understanding the mechanisms of metabolic adaptation in Leishmania and illustrate the power of integrated proteomic and metabolomic approaches to relate biochemistry to phenotype.

    BIOLOGICAL SIGNIFICANCE: This paper reports the application of comparative proteomic and metabolomic approaches to reveal the molecular basis for important phenotypic changes Leishmania parasites that are deficient in glucose uptake. Leishmania cause a very significant disease burden across the world and there are few effective drugs available for control. This work shows that proteomics and metabolomics can produce complementary data that advance understanding of parasite metabolism and highlight potential new targets for chemotherapy.

    Matched MeSH terms: Metabolomics*
  6. Enche Ady CNA, Lim SM, Teh LK, Salleh MZ, Chin AV, Tan MP, et al.
    J. Neurosci. Res., 2017 Oct;95(10):2005-2024.
    PMID: 28301062 DOI: 10.1002/jnr.24048
    The rapid increase in the older population has made age-related diseases like Alzheimer's disease (AD) a global concern. Given that there is still no cure for this neurodegenerative disease, the drastic growth in the number of susceptible individuals represents a major emerging threat to public health. The poor understanding of the mechanisms underlying AD is deemed the greatest stumbling block against progress in definitive diagnosis and management of this disease. There is a dire need for biomarkers that can facilitate early diagnosis, classification, prognosis, and treatment response. Efforts have been directed toward discovery of reliable and distinctive AD biomarkers but with very little success. With the recent emergence of high-throughput technology that is able to collect and catalogue vast datasets of small metabolites, metabolomics offers hope for a better understanding of AD and subsequent identification of biomarkers. This review article highlights the potential of using multiple metabolomics platforms as useful means in uncovering AD biomarkers from body fluids. © 2017 Wiley Periodicals, Inc.
    Matched MeSH terms: Metabolomics/methods*
  7. Jamil NAM, Rahmad N, Rosli NHM, Al-Obaidi JR
    Electrophoresis, 2018 12;39(23):2954-2964.
    PMID: 30074628 DOI: 10.1002/elps.201800185
    Wax apple is one of the underutilized fruits that is considered a good source of fibers, vitamins, minerals as well as antioxidants. In this study, a comparative analysis of the developments of wax fruit ripening at the proteomic and metabolomic level was reported. 2D electrophoresis coupled with MALDI-TOF/TOF was used to compare the proteome profile from three developmental stages named immature, young, and mature fruits. In general, the protein expression profile and the identified proteins function were discussed for their potential roles in fruit physiological development and ripening processes. The metabolomic investigation was also performed on the same samples using quadrupole LC-MS (LC-QTOF/MS). Roles of some of the differentially expressed proteins and metabolites are discussed in relation to wax apple ripening during the development. This is the first study investigating the changes in the proteins and metabolites in wax apple at different developmental stages. The information obtained from this research will be helpful in developing biomarkers for breeders and help the plant researchers to avoid wax apple cultivation problems such as fruit cracking.
    Matched MeSH terms: Metabolomics/methods*
  8. Baharum SN, Azizan KA
    Adv. Exp. Med. Biol., 2018 11 2;1102:51-68.
    PMID: 30382568 DOI: 10.1007/978-3-319-98758-3_4
    Over the last decade, metabolomics has continued to grow rapidly and is considered a dynamic technology in envisaging and elucidating complex phenotypes in systems biology area. The advantage of metabolomics compared to other omics technologies such as transcriptomics and proteomics is that these later omics only consider the intermediate steps in the central dogma pathway (mRNA and protein expression). Meanwhile, metabolomics reveals the downstream products of gene and expression of proteins. The most frequently used tools are nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS). Some of the common MS-based analyses are gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS). These high-throughput instruments play an extremely crucial role in discovery metabolomics to generate data needed for further analysis. In this chapter, the concept of metabolomics in the context of systems biology is discussed and provides examples of its application in human disease studies, plant responses towards stress and abiotic resistance and also microbial metabolomics for biotechnology applications. Lastly, a few case studies of metabolomics analysis are also presented, for example, investigation of an aromatic herbal plant, Persicaria minor metabolome and microbial metabolomics for metabolic engineering applications.
    Matched MeSH terms: Metabolomics*
  9. Amin AM, Mostafa H, Arif NH, Abdul Kader MAS, Kah Hay Y
    Clin. Chim. Acta, 2019 Jun;493:112-122.
    PMID: 30826371 DOI: 10.1016/j.cca.2019.02.030
    BACKGROUND: Coronary artery disease (CAD) claims lives yearly. Nuclear magnetic resonance (1H NMR) metabolomics analysis is efficient in identifying metabolic biomarkers which lend credence to diagnosis. We aimed to identify CAD metabotypes and its implicated pathways using 1H NMR analysis.

    METHODS: We analysed plasma and urine samples of 50 stable CAD patients and 50 healthy controls using 1H NMR. Orthogonal partial least square discriminant analysis (OPLS-DA) followed by multivariate logistic regression (MVLR) models were developed to indicate the discriminating metabotypes. Metabolic pathway analysis was performed to identify the implicated pathways.

    RESULTS: Both plasma and urine OPLS-DA models had specificity, sensitivity and accuracy of 100%, 96% and 98%, respectively. Plasma MVLR model had specificity, sensitivity, accuracy and AUROC of 92%, 86%, 89% and 0.96, respectively. The MVLR model of urine had specificity, sensitivity, accuracy and AUROC of 90%, 80%, 85% and 0.92, respectively. 35 and 12 metabolites were identified in plasma and urine metabotypes, respectively. Metabolic pathway analysis revealed that urea cycle, aminoacyl-tRNA biosynthesis and synthesis and degradation of ketone bodies pathways were significantly disturbed in plasma, while methylhistidine metabolism and galactose metabolism pathways were significantly disturbed in urine. The enrichment over representation analysis against SNPs-associated-metabolite sets library revealed that 85 SNPs were significantly enriched in plasma metabotype.

    CONCLUSIONS: Cardiometabolic diseases, dysbiotic gut-microbiota and genetic variabilities are largely implicated in the pathogenesis of CAD.

    Matched MeSH terms: Metabolomics*
  10. Watanabe M, Roth TL, Bauer SJ, Lane A, Romick-Rosendale LE
    PLoS ONE, 2016;11(5):e0156318.
    PMID: 27232336 DOI: 10.1371/journal.pone.0156318
    A variety of wildlife species maintained in captivity are susceptible to iron storage disease (ISD), or hemochromatosis, a disease resulting from the deposition of excess iron into insoluble iron clusters in soft tissue. Sumatran rhinoceros (Dicerorhinus sumatrensis) is one of the rhinoceros species that has evolutionarily adapted to a low-iron diet and is susceptible to iron overload. Hemosiderosis is reported at necropsy in many African black and Sumatran rhinoceroses but only a small number of animals reportedly die from hemochromatosis. The underlying cause and reasons for differences in susceptibility to hemochromatosis within the taxon remains unclear. Although serum ferritin concentrations have been useful in monitoring the progression of ISD in many species, there is some question regarding their value in diagnosing hemochromatosis in the Sumatran rhino. To investigate the metabolic changes during the development of hemochromatosis and possibly increase our understanding of its progression and individual susceptibility differences, the serum metabolome from a Sumatran rhinoceros was investigated by nuclear magnetic resonance (NMR)-based metabolomics. The study involved samples from female rhinoceros at the Cincinnati Zoo (n = 3), including two animals that died from liver failure caused by ISD, and the Sungai Dusun Rhinoceros Conservation Centre in Peninsular Malaysia (n = 4). Principal component analysis was performed to visually and statistically compare the metabolic profiles of the healthy animals. The results indicated that significant differences were present between the animals at the zoo and the animals in the conservation center. A comparison of the 43 serum metabolomes of three zoo rhinoceros showed two distinct groupings, healthy (n = 30) and unhealthy (n = 13). A total of eighteen altered metabolites were identified in healthy versus unhealthy samples. Results strongly suggest that NMR-based metabolomics is a valuable tool for animal health monitoring and may provide insight into the progression of this and other insidious diseases.
    Matched MeSH terms: Metabolomics*
  11. Au A
    Adv Clin Chem, 2018 03 08;85:31-69.
    PMID: 29655461 DOI: 10.1016/bs.acc.2018.02.002
    Ischemic stroke is a sudden loss of brain function due to the reduction of blood flow. Brain tissues cease to function with subsequent activation of the ischemic cascade. Metabolomics and lipidomics are modern disciplines that characterize the metabolites and lipid components of a biological system, respectively. Because the pathogenesis of ischemic stroke is heterogeneous and multifactorial, it is crucial to establish comprehensive metabolomic and lipidomic approaches to elucidate these alterations in this disease. Fortunately, metabolomic and lipidomic studies have the distinct advantages of identifying tissue/mechanism-specific biomarkers, predicting treatment and clinical outcome, and improving our understanding of the pathophysiologic basis of disease states. Therefore, recent applications of these analytical approaches in the early diagnosis of ischemic stroke were discussed. In addition, the emerging roles of metabolomics and lipidomics on ischemic stroke were summarized, in order to gain new insights into the mechanisms underlying ischemic stroke and in the search for novel metabolite biomarkers and their related pathways.
    Matched MeSH terms: Metabolomics/instrumentation; Metabolomics/methods*
  12. Mazlan O, Aizat WM, Baharum SN, Azizan KA, Noor NM
    Data Brief, 2018 Dec;21:548-551.
    PMID: 30370325 DOI: 10.1016/j.dib.2018.10.025
    Garcinia mangostana L. (mangosteen) seed is recalcitrant, prone to low temperature and drying which limit its long-term storage. Therefore, it is imperative to understand the metabolic changes throughout its development, to shed some light into the recalcitrant nature of this seed. We performed metabolomics analysis on mangosteen seed at different stages of development; six, eight, ten, twelve and fourteen weeks after anthesis. Seed samples were subjected to methanol extraction prior analysis using liquid chromatography - mass spectrometry (LC-MS). The MS data acquired were analyzed using ProfileAnalysis (version 2.1). This data article refers to the article entitled "Metabolomics analysis of developing Garcinia mangostana seed reveals modulated levels of sugars, organic acids and phenylpropanoid compounds" (Mazlan et al., 2018) [1].
    Matched MeSH terms: Metabolomics
  13. Zuther E, Lee YP, Erban A, Kopka J, Hincha DK
    Adv. Exp. Med. Biol., 2018 10 6;1081:81-98.
    PMID: 30288705 DOI: 10.1007/978-981-13-1244-1_5
    During low-temperature exposure, temperate plant species increase their freezing tolerance in a process termed cold acclimation. The molecular mechanisms involved in cold acclimation have been mostly investigated in Arabidopsis thaliana. In addition, other Brassicaceae species related to A. thaliana have been employed in recent years to study plant stress responses on a phylogenetically broader basis and in some cases with extremophile species with a much higher stress tolerance. In this paper, we briefly summarize cold acclimation responses in A. thaliana and current knowledge about cold acclimation in A. thaliana relatives with special emphasis on Eutrema salsugineum and two closely related Thellungiella species. We then present a transcriptomic and metabolomic analysis of cold acclimation in five A. thaliana and two E. salsugineum accessions that differ widely in their freezing tolerance. Differences in the cold responses of the two species are discussed.
    Matched MeSH terms: Metabolomics
  14. Mazlan O, Aizat WM, Aziz Zuddin NS, Baharum SN, Noor NM
    Data Brief, 2018 Dec;21:2221-2223.
    PMID: 30555858 DOI: 10.1016/j.dib.2018.11.072
    Metabolic regulation is important during seed germination for the establishment of seedling. The germination strategy of mangosteen (Garcinia mangostana L.) seed is thought to be unique due to its recalcitrant characteristic (sensitive to coldness and drying). To investigate the metabolic changes during seed germination, we performed metabolomics analysis on germinating mangosteen seed sown after zero, one, three, five, seven and nine days. Sampled mangosteen seeds were subjected to methanol extraction prior analysis using Liquid Chromatography-Time of Flight-Mass Spectrometry (LC-TOF-MS). MS data were further analyzed using ProfileAnalysis (version 2.1). This is one of the earliest reports in metabolite identification and profiling of mangosteen seed at different germination stages. This data article refers to the article entitled "Metabolite profiling of mangosteen seed germination highlights metabolic changes related to carbon utilization and seed protection" (Mazlan et al., 2019) [1].
    Matched MeSH terms: Metabolomics
  15. Maulidiani, Abas F, Khatib A, Perumal V, Suppaiah V, Ismail A, et al.
    J Ethnopharmacol, 2016 Mar 2;180:60-9.
    PMID: 26775274 DOI: 10.1016/j.jep.2016.01.001
    'Pegaga' is a traditional Malay remedy for a wide range of complaints. Among the 'pegaga', Centella asiatica has been used as a remedy for diabetes mellitus. Thus, we decided to validate this claim by evaluating the in vivo antidiabetic property of C. asiatica (CA) on T2DM rat model using the holistic (1)H NMR-based metabolomics approach.
    Matched MeSH terms: Metabolomics
  16. Mumm R, Hageman JA, Calingacion MN, de Vos RCH, Jonker HH, Erban A, et al.
    Metabolomics, 2016;12:38.
    PMID: 26848289 DOI: 10.1007/s11306-015-0925-1
    The quality of rice in terms not only of its nutritional value but also in terms of its aroma and flavour is becoming increasingly important in modern rice breeding where global targets are focused on both yield stability and grain quality. In the present paper we have exploited advanced, multi-platform metabolomics approaches to determine the biochemical differences in 31 rice varieties from a diverse range of genetic backgrounds and origin. All were grown under the specific local conditions for which they have been bred and all aspects of varietal identification and sample purity have been guaranteed by local experts from each country. Metabolomics analyses using 6 platforms have revealed the extent of biochemical differences (and similarities) between the chosen rice genotypes. Comparison of fragrant rice varieties showed a difference in the metabolic profiles of jasmine and basmati varieties. However with no consistent separation of the germplasm class. Storage of grains had a significant effect on the metabolome of both basmati and jasmine rice varieties but changes were different for the two rice types. This shows how metabolic changes may help prove a causal relationship with developing good quality in basmati rice or incurring quality loss in jasmine rice in aged grains. Such metabolomics approaches are leading to hypotheses on the potential links between grain quality attributes, biochemical composition and genotype in the context of breeding for improvement. With this knowledge we shall establish a stronger, evidence-based foundation upon which to build targeted strategies to support breeders in their quest for improved rice varieties.
    Matched MeSH terms: Metabolomics
  17. Ebrahimi F, Ibrahim B, Teh CH, Murugaiyah V, Lam CK
    Planta Med., 2017 Jan;83(1-02):172-182.
    PMID: 27399233 DOI: 10.1055/s-0042-110857
    Quassinoids, the major secondary metabolites of Eurycoma longifolia roots, improve male fertility. Hence, it is crucial to investigate their quantitative level in E. longifolia extracts. A profile was established to identify the primary metabolites and major quassinoids, and quantify quassinoids using external calibration curves. Furthermore, the metabolic discrimination of E. longifolia roots from different regions was investigated. The (1)H-NMR spectra of the quassinoids, eurycomanone, eurycomanol, 13,21-dihydroeurycomanone, and eurycomanol-2-O-β-D-glycopyranoside were obtained. The (1)H-NMR profiles of E. longifolia root aqueous extracts from Perak (n = 30) were obtained and used to identify primary metabolites and the quassinoids. Selangor, Kedah, Terengganu (n = 5 for each), and Perak samples were checked for metabolic discrimination. Hotelling's T(2) plot was used to check for outliers. Orthogonal partial least-squares discriminant analysis was run to reveal the discriminatory metabolites. Perak samples contained formic, succinic, methylsuccinic, fumaric, lactic, acetic and syringic acids as well as choline, alanine, phenylalanine, tyrosine, α-glucose, eurycomanone, eurycomanol, 13,21-dihydroeurycomanone, and eurycomanol-2-O-β-D-glycopyranoside. The extracts from other locations contained the same metabolites. The limit of quantification values were 1.96 (eurycomanone), 15.62 (eurycomanol), 3.91 (13,21-dihydroeurycomanone), and 31.25 (eurycomanol-2-O-β-D-glycopyranoside) ppm. The Hotelling's T(2) plot revealed no outlier. The orthogonal partial least-squares discriminant analysis model showed that choline, eurycomanol, eurycomanol-2-O-β-D-glycopyranoside, and lactic and succinic acid levels were different among regions. Terengganu and Perak samples contained higher amounts of eurycomanol and eurycomanol-2-O-β-D-glycopyranoside, respectively. The current approach efficiently detected E. longifolia root metabolites, quantified the quassinoids, and discriminated E. longifolia roots from different locations. These findings could be applicable to future research on E. longifolia where the higher content of quassinoids is required.
    Matched MeSH terms: Metabolomics/methods*
  18. Au A, Cheng KK, Wei LK
    Adv. Exp. Med. Biol., 2017;956:599-613.
    PMID: 27722964 DOI: 10.1007/5584_2016_79
    Hypertension is a common but complex human disease, which can lead to a heart attack, stroke, kidney disease or other complications. Since the pathogenesis of hypertension is heterogeneous and multifactorial, it is crucial to establish a comprehensive metabolomic approach to elucidate the molecular mechanism of hypertension. Although there have been limited metabolomic, lipidomic and pharmacometabolomic studies investigating this disease to date, metabolomic studies on hypertension have provided greater insights into the identification of disease-specific biomarkers, predicting treatment outcome and monitor drug safety and efficacy. Therefore, we discuss recent updates on the applications of metabolomics technology in human hypertension with a focus on metabolic biomarker discovery.
    Matched MeSH terms: Metabolomics/methods*
  19. Shahfiza N, Osman H, Hock TT, Abdel-Hamid AZ
    Acta Biochim. Pol., 2017;64(2):215-219.
    PMID: 28350402 DOI: 10.18388/abp.2015_1224
    BACKGROUND: Dengue is one of the major public health problems in the world, affecting more than fifty million cases in tropical and subtropical region every year. The metabolome, as pathophysiological end-points, provide significant understanding of the mechanism and progression of dengue pathogenesis via changes in the metabolite profile of infected patients. Recent developments in diagnostic technologies provide metabolomics for the early detection of infectious diseases.

    METHODS: The mid-stream urine was collected from 96 patients diagnosed with dengue fever at Penang General Hospital (PGH) and 50 healthy volunteers. Urine samples were analyzed with proton nuclear magnetic resonance (1H NMR) spectroscopy, followed by chemometric multivariate analysis. NMR signals highlighted in the orthogonal partial least square-discriminant analysis (OPLS-DA) S-plots were selected and identified using Human Metabolome Database (HMDB) and Chenomx Profiler. A highly predictive model was constructed from urine profile of dengue infected patients versus healthy individuals with the total R2Y (cum) value 0.935, and the total Q2Y (cum) value 0.832.

    RESULTS: Data showed that dengue infection is related to amino acid metabolism, tricarboxylic acid intermediates cycle and β-oxidation of fatty acids. Distinct variations in certain metabolites were recorded in infected patients including amino acids, various organic acids, betaine, valerylglycine, myo-inositol and glycine.

    CONCLUSION: Metabolomics approach provides essential insight into host metabolic disturbances following dengue infection.

    Matched MeSH terms: Metabolomics*
  20. Wong EHJ, Ng CG, Goh KL, Vadivelu J, Ho B, Loke MF
    Sci Rep, 2018 01 23;8(1):1409.
    PMID: 29362474 DOI: 10.1038/s41598-018-19697-0
    The biofilm-forming-capability of Helicobacter pylori has been suggested to be among factors influencing treatment outcome. However, H. pylori exhibit strain-to-strain differences in biofilm-forming-capability. Metabolomics enables the inference of spatial and temporal changes of metabolic activities during biofilm formation. Our study seeks to examine the differences in metabolome of low and high biofilm-formers using the metabolomic approach. Eight H. pylori clinical strains with different biofilm-forming-capability were chosen for metabolomic analysis. Bacterial metabolites were extracted using Bligh and Dyer method and analyzed by Liquid Chromatography/Quadrupole Time-of-Flight mass spectrometry. The data was processed and analyzed using the MassHunter Qualitative Analysis and the Mass Profiler Professional programs. Based on global metabolomic profiles, low and high biofilm-formers presented as two distinctly different groups. Interestingly, low-biofilm-formers produced more metabolites than high-biofilm-formers. Further analysis was performed to identify metabolites that differed significantly (p-value 
    Matched MeSH terms: Metabolomics/methods*
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