Publications
90 results found
Golf O, Muirhead LJ, Speller A, et al., 2015, XMS: cross-platform normalization method for multimodal mass spectrometric tissue profiling, Journal of the American Society for Mass Spectrometry, Vol: 26, Pages: 44-54, ISSN: 1044-0305
Here we present a proof of concept cross-platform normalization approach to convert raw mass spectra acquired by distinct desorption ionization methods and/or instrumental setups to cross-platform normalized analyte profiles. The initial step of the workflow is database driven peak annotation followed by summarization of peak intensities of different ions from the same molecule. The resulting compound-intensity spectra are adjusted to a method-independent intensity scale by using predetermined, compound-specific normalization factors. The method is based on the assumption that distinct MS-based platforms capture a similar set of chemical species in a biological sample, though these species may exhibit platform-specific molecular ion intensity distribution patterns. The method was validated on two sample sets of (1) porcine tissue analyzed by laser desorption ionization (LDI), desorption electrospray ionization (DESI), and rapid evaporative ionization mass spectrometric (REIMS) in combination with Fourier transformation-based mass spectrometry; and (2) healthy/cancerous colorectal tissue analyzed by DESI and REIMS with the latter being combined with time-of-flight mass spectrometry. We demonstrate the capacity of our method to reduce MS-platform specific variation resulting in (1) high inter-platform concordance coefficients of analyte intensities; (2) clear principal component based clustering of analyte profiles according to histological tissue types, irrespective of the used desorption ionization technique or mass spectrometer; and (3) accurate “blind” classification of histologic tissue types using cross-platform normalized analyte profiles.
Lamour SD, Veselkov KA, Posma JM, et al., 2014, Metabolic, Immune, and Gut Microbial Signals Mount a Systems Response to Leishmania major Infection, Journal of Proteome Research, Vol: 14, Pages: 318-329, ISSN: 1535-3907
Parasitic infections such as leishmaniasis induce a cascade of host physiological responses, includingmetabolic and immunological changes. Infection with Leishmania major parasites causes cutaneousleishmaniasis in humans, a neglected tropical disease that is difficult to manage. To understand thedeterminants of pathology, we studied L. major infection in two mouse models: the self-healingC57BL/6 strain and the nonhealing BALB/c strain. Metabolic profiling of urine, plasma, and feces viaproton NMR spectroscopy was performed to discover parasite-specific imprints on global hostmetabolism. Plasma cytokine status and fecal microbiome were also characterized as additional metricsof the host response to infection. Results demonstrated differences in glucose and lipid metabolism,distinctive immunological phenotypes, and shifts in microbial composition between the two models.We present a novel approach to integrate such metrics using correlation network analyses, wherebyself-healing mice demonstrated an orchestrated interaction between the biological measures shortlyafter infection. In contrast, the response observed in nonhealing mice was delayed and fragmented. Ourstudy suggests that trans-system communication across host metabolism, the innate immune system,and gut microbiome is key for a successful host response to L. major and provides a new concept,potentially translatable to other diseases.
Antcliffe D, Jimenez B, Veselkov K, et al., 2014, DIAGNOSING PNEUMONIA ON THE INTENSIVE CARE UNIT WITH SERUM <SUP>1</SUP>H NMR SPECTROSCOPY, 27th Annual Congress of the European-Society-of-Intensive-Care-Medicine (ESICM), Publisher: SPRINGER, Pages: S237-S238, ISSN: 0342-4642
Strittmatter N, Rebec M, Jones EA, et al., 2014, Characterization and identification of clinically relevant microorganisms using rapid evaporative ionization mass spectrometry, Analytical Chemistry, Vol: 86, Pages: 6555-6562, ISSN: 0003-2700
Rapid evaporative ionization mass spectrometry (REIMS) was investigated for its suitability as a general identification system for bacteria and fungi. Strains of 28 clinically relevant bacterial species were analyzed in negative ion mode, and corresponding data was subjected to unsupervised and supervised multivariate statistical analyses. The created supervised model yielded correct cross-validation results of 95.9%, 97.8%, and 100% on species, genus, and Gram-stain level, respectively. These results were not affected by the resolution of the mass spectral data. Blind identification tests were performed for strains cultured on different culture media and analyzed using different instrumental platforms which led to 97.8–100% correct identification. Seven different Escherichia coli strains were subjected to different culture conditions and were distinguishable with 88% accuracy. In addition, the technique proved suitable to distinguish five pathogenic Candida species with 98.8% accuracy without any further modification to the experimental workflow. These results prove that REIMS is sufficiently specific to serve as a culture condition-independent tool for the identification and characterization of microorganisms.
Mirnezami R, Jimenez B, Li JV, et al., 2014, Rapid Diagnosis and Staging of Colorectal Cancer via High-Resolution Magic Angle Spinning Nuclear Magnetic Resonance (HR-MAS NMR) Spectroscopy of Intact Tissue Biopsies, Annals of Surgery, Vol: 259, Pages: 1138-1149, ISSN: 0003-4932
Objective: To develop novel metabolite-based models for diagnosis and staging in colorectal cancer (CRC) using high-resolution magic angle spinning nuclear magnetic resonance (HR-MAS NMR) spectroscopy.Background: Previous studies have demonstrated that cancer cells harbor unique metabolic characteristics relative to healthy counterparts. This study sought to characterize metabolic properties in CRC using HR-MAS NMR spectroscopy.Methods: Between November 2010 and January 2012, 44 consecutive patients with confirmed CRC were recruited to a prospective observational study. Fresh tissue samples were obtained from center of tumor and 5 cm from tumor margin from surgical resection specimens. Samples were run in duplicate where tissue volume permitted to compensate for anticipated sample heterogeneity. Samples were subjected to HR-MAS NMR spectroscopic profiling and acquired spectral data were imported into SIMCA and MATLAB statistical software packages for unsupervised and supervised multivariate analysis.Results: A total of 171 spectra were acquired (center of tumor, n = 88; 5 cm from tumor margin, n = 83). Cancer tissue contained significantly increased levels of lactate (P < 0.005), taurine (P < 0.005), and isoglutamine (P < 0.005) and decreased levels of lipids/triglycerides (P < 0.005) relative to healthy mucosa (R2Y = 0.94; Q2Y = 0.72; area under the curve, 0.98). Colon cancer samples (n = 49) contained higher levels of acetate (P < 0.005) and arginine (P < 0.005) and lower levels of lactate (P < 0.005) relative to rectal cancer samples (n = 39). In addition unique metabolic profiles were observed for tumors of differing T-stage.Conclusions: HR-MAS NMR profiling demonstrates cancer-specific metabolic signatures in CRC and reveals metabolic differences between colonic and rectal cancers. In addition, this approach reveals that tumor metabolism undergoes modification during local tumor advancement, offering potential in future staging and therapeu
Kinross J, Muirhead LJ, Mirnezami R, et al., 2014, Microbiome-Metabonome Linked Analysis of Ascending Colon Cancer by 1HNMR MAS Spectrometry and 16S rRNA Gene Analysis (Metataxonomics), 55th Annual Meeting of the Society-for-Surgery-of-the-Alimentary-Tract (SSAT) / Digestive Disease Week (DDW), Publisher: W B SAUNDERS CO-ELSEVIER INC, Pages: S688-S688, ISSN: 0016-5085
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- Citations: 1
Abbassi-Ghadi N, Veselkov K, Kumar S, et al., 2014, Discrimination of lymph node metastases using desorption electrospray ionisation-mass spectrometry imaging: a proof of concept study, Annual Meeting of the Society-of-Academic-and-Research-Surgery, Publisher: WILEY-BLACKWELL, Pages: 44-44, ISSN: 0007-1323
Abbassi-Ghadi N, Veselkov K, Kumar S, et al., 2014, Discrimination of lymph node metastases using desorption electrospray ionisation-mass spectrometry imaging, Chemical Communications, Vol: 50, Pages: 3661-3664, ISSN: 1359-7345
Desorption electrospray ionisation mass spectrometry imaging (DESI-MSI) has been used for the identification of cancer within lymph nodes with accurate spatial distribution in comparison to gold standard matched immuno-histopathological images. The metabolic profile of the cancerous lymph nodes was similar to that of the primary tumour site.
Veselkov KA, Mirnezami R, Strittmatter N, et al., 2014, Chemo-informatic strategy for imaging mass spectrometry-based hyperspectral profiling of lipid signatures in colorectal cancer, Proceedings of the National Academy of Sciences of the United States of America, Vol: 111, Pages: 1216-1221, ISSN: 0027-8424
Mass spectrometry imaging (MSI) provides the opportunity toinvestigate tumor biology from an entirely novel biochemicalperspective and could lead to the identification of a new pool ofcancer biomarkers. Effective clinical translation of histology-drivenMSI in systems oncology requires precise colocalization of morphologicaland biochemical features as well as advanced methodsfor data treatment and interrogation. Currently proposed MSIworkflows are subject to several limitations, including nonoptimizedraw data preprocessing, imprecise image coregistration,and limited pattern recognition capabilities. Here we outline acomprehensive strategy for histology-driven MSI, using desorptionelectrospray ionization that covers (i) optimized data preprocessingfor improved information recovery; (ii) precise imagecoregistration; and (iii) efficient extraction of tissue-specific molecularion signatures for enhanced biochemical distinction of differenttissue types. The proposed workflow has been used to investigateregion-specific lipid signatures in colorectal cancer tissue. Uniquelipid patterns were observed using this approach according totissue type, and a tissue recognition system using multivariatemolecular ion patterns allowed highly accurate (>98%) identificationof pixels according to morphology (cancer, healthy mucosa,smooth muscle, and microvasculature). This strategy offers uniqueinsights into tumor microenvironmental biochemistry and shouldfacilitate compilation of a large-scale tissue morphology-specificMSI spectral database with which to pursue next-generation, fullyautomated histological approaches.
Antcliffe DB, Veselkov K, Pearce JTM, et al., 2013, TRAJECTORY ANALYSIS OF CLINICAL VARIABLES TO IMPROVE DIAGNOSIS OF VENTILATOR ASSOCIATED PNEUMONIA IN PATIENTS Wan BRAIN INJURY, ESICM 26th Annual Congress, Publisher: SPRINGER, Pages: S312-S313, ISSN: 0342-4642
Mirnezami R, Veselkov K, Goldin RD, et al., 2013, Novel mass spectrometry based imaging for accurate characterisation of tumour microenvironmental metabolism in colorectal cancer, International Surgical Congress of the Association-of-Surgeons-of-Great-Britain-and-Ireland (ASGBI), Publisher: WILEY-BLACKWELL, Pages: 3-3, ISSN: 0007-1323
Balog J, Sasi-Szabo L, Kinross J, et al., 2013, Intraoperative tissue identification using rapid evaporative ionization mass spectrometry, Science Translational Medicine, Vol: 5, Pages: 1-11, ISSN: 1946-6234
Rapid evaporative ionization mass spectrometry (REIMS) is an emerging technique that allows near–real-time characterization of human tissue in vivo by analysis of the aerosol (“smoke”) released during electrosurgical dissection. The coupling of REIMS technology with electrosurgery for tissue diagnostics is known as the intelligent knife (iKnife). This study aimed to validate the technique by applying it to the analysis of fresh human tissue samples ex vivo and to demonstrate the translation to real-time use in vivo in a surgical environment. A variety of tissue samples from 302 patients were analyzed in the laboratory, resulting in 1624 cancerous and 1309 noncancerous database entries. The technology was then transferred to the operating theater, where the device was coupled to existing electrosurgical equipment to collect data during a total of 81 resections. Mass spectrometric data were analyzed using multivariate statistical methods, including principal components analysis (PCA) and linear discriminant analysis (LDA), and a spectral identification algorithm using a similar approach was implemented. The REIMS approach differentiated accurately between distinct histological and histopathological tissue types, with malignant tissues yielding chemical characteristics specific to their histopathological subtypes. Tissue identification via intraoperative REIMS matched the postoperative histological diagnosis in 100% (all 81) of the cases studied. The mass spectra reflected lipidomic profiles that varied between distinct histological tumor types and also between primary and metastatic tumors. Thus, in addition to real-time diagnostic information, the spectra provided additional information on divergent tumor biochemistry that may have mechanistic importance in cancer.
Mirnezami R, Veselkov K, Strittmatter N, et al., 2013, Novel data processing and image co-registration algorithm for region-specific lipid profiling in colorectal cancer tissue using DESI imaging mass spectrometry, 49th Annual Meeting of the American-Society-of-Clinical-Oncology (ASCO), Publisher: LIPPINCOTT WILLIAMS & WILKINS, ISSN: 0732-183X
Pechlivanis A, Kostidis S, Saraslanidis P, et al., 2013, <SUP>1</SUP>H NMR Study on the Short- and Long-Term Impact of Two Training Programs of Sprint Running on the Metabolic Fingerprint of Human Serum, JOURNAL OF PROTEOME RESEARCH, Vol: 12, Pages: 470-480, ISSN: 1535-3893
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- Citations: 68
Strittmatter N, Jones EA, Veselkov KA, et al., 2013, Analysis of intact bacteria using rapid evaporative ionisation mass spectrometry, CHEMICAL COMMUNICATIONS, Vol: 49, Pages: 6188-6190, ISSN: 1359-7345
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- Citations: 52
McPhail MJW, Shawcross D, Coltart I, et al., 2012, METABOLIC PROFILING OF PLASMA BY NMR SPECTROSCOPY ACCURATELY PREDICTS OUTCOME IN PATIENTS WITH DECOMPENSATED CIRRHOSIS AND ACUTE ON CHRONIC LIVER FAILURE, GUT, Vol: 61, Pages: A202-A203, ISSN: 0017-5749
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- Citations: 1
Coltart I, McPhail MJW, Want EJ, et al., 2012, PROTON NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY OF PLASMA IN PATIENTS WITH CIRRHOSIS CORRELATES WITH ARTERIAL AMMONIA BUT NOT GRADE OF HEPATIC ENCEPHALOPATHY, GUT, Vol: 61, Pages: A202-A202, ISSN: 0017-5749
Cazier J-B, Kaisaki PJ, Argoud K, et al., 2012, Untargeted Metabolome Quantitative Trait Locus Mapping Associates Variation in Urine Glycerate to Mutant Glycerate Kinase, JOURNAL OF PROTEOME RESEARCH, Vol: 11, Pages: 631-642, ISSN: 1535-3893
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- Citations: 21
Graca G, Goodfellow BJ, Barros AS, et al., 2012, UPLC-MS metabolic profiling of second trimester amniotic fluid and maternal urine and comparison with NMR spectral profiling for the identification of pregnancy disorder biomarkers, MOLECULAR BIOSYSTEMS, Vol: 8, Pages: 1243-1254, ISSN: 1742-206X
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- Citations: 84
Veselkov KA, Vingara LK, Masson P, et al., 2011, Response to Comment on "Optimized Preprocessing of Ultra-Performance Liquid Chromatography/Mass Spectrometry Urinary Metabolic Profiles for Improved Information Recovery", ANALYTICAL CHEMISTRY, Vol: 83, Pages: 9721-9722, ISSN: 0003-2700
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- Citations: 2
Veselkov KA, Vingara LK, Masson P, et al., 2011, Optimized Preprocessing of Ultra-Performance Liquid Chromatography/Mass Spectrometry Urinary Metabolic Profiles for Improved Information Recovery, ANALYTICAL CHEMISTRY, Vol: 83, Pages: 5864-5872, ISSN: 0003-2700
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- Citations: 211
Veselkov KA, Pahomov VI, Lindon JC, et al., 2010, A Metabolic Entropy Approach for Measurements of Systemic Metabolic Disruptions in Patho-Physiological States, JOURNAL OF PROTEOME RESEARCH, Vol: 9, Pages: 3537-3544, ISSN: 1535-3893
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- Citations: 24
Yap IKS, Angley M, Veselkov KA, et al., 2010, Urinary Metabolic Phenotyping Differentiates Children with Autism from Their Unaffected Siblings and Age-Matched Controls, JOURNAL OF PROTEOME RESEARCH, Vol: 9, Pages: 2996-3004, ISSN: 1535-3893
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- Citations: 220
Robinette SL, Veselkov KA, Bohus E, et al., 2009, Cluster Analysis Statistical Spectroscopy Using Nuclear Magnetic Resonance Generated Metabolic Data Sets from Perturbed Biological Systems, ANALYTICAL CHEMISTRY, Vol: 81, Pages: 6581-6589, ISSN: 0003-2700
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- Citations: 29
Saric J, Li JV, Wang Y, et al., 2009, Panorganismal Metabolic Response Modeling of an Experimental <i>Echinostoma caproni</i> Infection in the Mouse, JOURNAL OF PROTEOME RESEARCH, Vol: 8, Pages: 3899-3911, ISSN: 1535-3893
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- Citations: 29
Veselkov KA, Lindon JC, Ebbels TMD, et al., 2009, Recursive Segment-Wise Peak Alignment of Biological <SUP>1</SUP>H NMR Spectra for Improved Metabolic Biomarker Recovery, ANALYTICAL CHEMISTRY, Vol: 81, Pages: 56-66, ISSN: 0003-2700
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- Citations: 271
Holmes E, Loo RL, Stamler J, et al., 2008, Human metabolic phenotype diversity and its association with diet and blood pressure, NATURE, Vol: 453, Pages: 396-U50, ISSN: 0028-0836
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- Citations: 812
Saric J, Wang Y, Li JV, et al., 2007, Species variation in the fecal metabolome gives insight into differential gastrointestinal function, Journal of Proteome Research, Vol: 7, Pages: 352-360
Ovchinnikov DV, Baranovsky SF, Rozvadovska AO, et al., 2007, Structural basis for the binding affinity of a homologous series of synthetic phenoxazone drugs with DNA: NMR and molecular mechanics analysis, JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS, Vol: 24, Pages: 443-453, ISSN: 0739-1102
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- Citations: 4
Veselkov AN, Djimant LN, Veselkov KA, et al., 2005, [Structural analysis of the complex of phenoxazone antibiotic actinocyl-bis-(2-deoxytetranucleotide 5'-d(TpGpCpA) by the methods of two dimensional 1H-NMR-spectroscopy and molecular mechanics]., Mol Biol (Mosk), Vol: 39, Pages: 336-344, ISSN: 0026-8984
The spatial structures of intercalated complexes of synthetic phenoxazone antibiotic actinocyl-bis-(2-dimethylaminoethyl) amide with self-complementary deoxytetranucleotide 5'-d(TpGpCpA) have been investigated. Analysis has been made using two-dimensional NMR (2D-NOESY) data in aqueous solution and molecular mechanics simulation. Distinctive features of the conformation of drug-DNA complexes have been determined at two possible orientations of the chromophore of phenoxazone antibiotic at the intercalation site.
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