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Engskog, Mikael K R
Alternative names
Publications (10 of 13) Show all publications
Elmsjö, A., Haglöf, J., Engskog, M. K., Erngren, I., Nestor, M., Arvidsson, T. & Pettersson, C. (2018). Method selectivity evaluation using the co-feature ratio in LC/MS metabolomics: Comparison of HILIC stationary phase performance for the analysis of plasma, urine and cell extracts.. Journal of Chromatography A, 1568, 49-56
Open this publication in new window or tab >>Method selectivity evaluation using the co-feature ratio in LC/MS metabolomics: Comparison of HILIC stationary phase performance for the analysis of plasma, urine and cell extracts.
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2018 (English)In: Journal of Chromatography A, ISSN 0021-9673, E-ISSN 1873-3778, Vol. 1568, p. 49-56Article in journal (Refereed) Published
Abstract [en]

Evaluation of the chromatographic separation in metabolomics studies has primarily been done using preselected sets of standards or by counting the number of detected features. An alternative approach is to calculate each feature's co-feature ratio, which is a combined selectivity measurement for the separation (i.e. extent of co-elution) and the MS-signal (i.e. adduct formation and in-source fragmentation). The aim of this study was to demonstrate how the selectivity of different HILIC stationary phases can be evaluated using the co-feature ratio approach. The study was based on three sample types; plasma, urine and cell extracts. Samples were analyzed on an UHPLC-ESI-Q-ToF system using an amide, a bare silica and a sulfobetaine stationary phase. For each feature, a co-feature ratio was calculated and used for multivariate analysis of the selectivity differences between the three stationary phases. Unsupervised PCA models indicated that the co-feature ratios were highly dependent on type of stationary phase. For several metabolites a 15-30 fold difference in the co-feature ratio were observed between the stationary phases. Observed selectivity differences related primarily to the retention patterns of unwanted matrix components such as inorganic salts (detected as salt clusters), glycerophospholipids, and polyethylene glycols. These matrix components affected the signal intensity of co-eluting metabolites by interfering with the ionization efficiency and/or their adduct formation. Furthermore, the retention pattern of these matrix components had huge influence on the number of detected features. The co-feature ratio approach has successfully been applied for evaluation of the selectivity performance of three HILIC stationary phases. The co-feature ratio could therefore be used in metabolomics for developing selective methods fit for their purpose, thereby avoiding generic analytical approaches, which are often biased, as type and amount of interfering matrix components are metabolome dependent.

Keywords
Co-feature ratio (CFR), Hydrophilic interaction chromatography, Mass spectrometry, Metabolomics, Salt clusters
National Category
Analytical Chemistry Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-364208 (URN)10.1016/j.chroma.2018.05.007 (DOI)000443669600006 ()29789170 (PubMedID)
Available from: 2018-10-24 Created: 2018-10-24 Last updated: 2018-10-29Bibliographically approved
Pierre, P. V., Haglöf, J., Linder, B., Engskog, M. K., Arvidsson, T., Pettersson, C., . . . Laurell, G. (2017). Cisplatin-induced metabolome changes in serum: an experimental approach to identify markers for ototoxicity. Acta Oto-Laryngologica, 137(10), 1024-1030
Open this publication in new window or tab >>Cisplatin-induced metabolome changes in serum: an experimental approach to identify markers for ototoxicity
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2017 (English)In: Acta Oto-Laryngologica, ISSN 0001-6489, E-ISSN 1651-2251, Vol. 137, no 10, p. 1024-1030Article in journal (Refereed) Published
Abstract [en]

BACKGROUND: Ototoxicity from treatment with the anticancer drug cisplatin remains a clinical problem. A wide range of intracellular targets of cisplatin has been found in vivo.

AIM: To investigate cisplatin-induced change of the serum metabolite profile and its association with ototoxicity.

MATERIAL AND METHODS: Guinea pigs (n = 14) were treated with cisplatin (8 mg/kg b.w., i.v.) 30 min after administration of the otoprotector candidate sodium thiosulfate (group STS; n = 7) or sodium chloride (group NaCl; n = 7). Ototoxicity was evaluated by ABR (3-30 kHz) before and 4 d after drug treatment, and by assessment of hair cell loss. A blood sample was drawn before and 4 d after drug treatment and the polar metabolome in serum was analyzed using LC-MS.

RESULTS: Cisplatin-treatment caused significant threshold elevations and outer hair cell (OHC) loss in both groups. The ototoxicity was generally lower in group STS, but a significant difference was reached only at 30 kHz (p = .007). Cisplatin treatment altered the metabolite profile significantly and similarly in both groups. A significant inverse correlation was found between L-acetylcarnitine, N-acetylneuraminic acid, ceramide, and cysteinylserine and high frequency hearing loss in group NaCl. The implication of these correlations should be explored in targeted studies.

Keywords
ABR, cisplatin, hair cell, metabolite profiling, ototoxicity, sodium thiosulfate
National Category
Basic Medicine Analytical Chemistry Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-328151 (URN)10.1080/00016489.2017.1325006 (DOI)000407072000002 ()28537102 (PubMedID)
Funder
AFA Insurance
Available from: 2017-08-18 Created: 2017-08-18 Last updated: 2018-09-07Bibliographically approved
Häggblad Sahlberg, S., Mortensen, A. C., Haglöf, J., Engskog, M. K. R., Arvidsson, T., Pettersson, C., . . . Nestor, M. (2017). Different functions of AKT1 and AKT2 in molecular pathways, cell migration and metabolism in colon cancer cells. International Journal of Oncology, 50(1), 5-14
Open this publication in new window or tab >>Different functions of AKT1 and AKT2 in molecular pathways, cell migration and metabolism in colon cancer cells
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2017 (English)In: International Journal of Oncology, ISSN 1019-6439, Vol. 50, no 1, p. 5-14Article in journal (Refereed) Published
Abstract [en]

AKT is a central protein in many cellular pathways such as cell survival, proliferation, glucose uptake, metabolism, angiogenesis, as well as radiation and drug response. The three isoforms of AKT (AKT1, AKT2 and AKT3) are proposed to have different physiological functions, properties and expression patterns in a cell type-dependent manner. As of yet, not much is known about the influence of the different AKT isoforms in the genome and their effects in the metabolism of colorectal cancer cells. In the present study, DLD-1 isogenic AKT1, AKT2 and AKT'/2 knockout colon cancer cell lines were used as a model system in conjunction with the parental cell line in order to further elucidate the differences between the AKT isoforms and how they are involved in various cellular pathways. This was done using genome wide expression analyses, metabolic profiling and cell migration assays. In conclusion, downregulation of genes in the cell adhesion, extracellular matrix and Notch-pathways and upregulation of apoptosis and metastasis inhibitory genes in the p53-pathway, confirm that the knockout of both AKT1 and AKT2 will attenuate metastasis and tumor cell growth. This was verified with a reduction in migration rate in the AKT1 KO and AKT2 KO and most explicitly in the AKT1/2 KO. Furthermore, the knockout of AKT1, AKT2 or both, resulted in a reduction in lactate and alanine, suggesting that the metabolism of carbohydrates and glutathione was impaired. This was further verified in gene expression analyses, showing downregulation of genes involved in glucose metabolism. Additionally, both AKT1 KO and AKT2 KO demonstrated an impaired fatty acid metabolism. However, genes were upregulated in the Wnt and cell proliferation pathways, which could oppose this effect. AKT inhibition should therefore be combined with other effectors to attain the best effect.

Keywords
Microarray, metabolism, cell migration AKT1, AKT2, AKT, PKB, gene expression, colon-cancer, DLD-1, metabolomics, CD44, CD133
National Category
Biochemistry and Molecular Biology
Research subject
Biomedical Radiation Science; Biology with specialization in Molecular Cell Biology; Biology with specialization in Molecular Biology
Identifiers
urn:nbn:se:uu:diva-222834 (URN)10.3892/ijo.2016.3771 (DOI)000391419200001 ()
Available from: 2014-04-14 Created: 2014-04-14 Last updated: 2017-12-05Bibliographically approved
Niklison-Chirou, M. V., Erngren, I., Engskog, M. K., Haglöf, J., Picard, D., Remke, M., . . . Marino, S. (2017). TAp73 is a marker of glutamine addiction in medulloblastoma. Genes & Development, 31(17), 1738-1753
Open this publication in new window or tab >>TAp73 is a marker of glutamine addiction in medulloblastoma
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2017 (English)In: Genes & Development, ISSN 0890-9369, E-ISSN 1549-5477, Vol. 31, no 17, p. 1738-1753Article in journal (Refereed) Published
Abstract [en]

Medulloblastoma is the most common solid primary brain tumor in children. Remarkable advancements in the understanding of the genetic and epigenetic basis of these tumors have informed their recent molecular classification. However, the genotype/phenotype correlation of the subgroups remains largely uncharacterized. In particular, the metabolic phenotype is of great interest because of its druggability, which could lead to the development of novel and more tailored therapies for a subset of medulloblastoma. p73 plays a critical role in a range of cellular metabolic processes. We show overexpression of p73 in a proportion of non-WNT medulloblastoma. In these tumors, p73 sustains cell growth and proliferation via regulation of glutamine metabolism. We validated our results in a xenograft model in which we observed an increase in survival time in mice on a glutamine restriction diet. Notably, glutamine starvation has a synergistic effect with cisplatin, a component of the current medulloblastoma chemotherapy. These findings raise the possibility that glutamine depletion can be used as an adjuvant treatment for p73-expressing medulloblastoma.

Place, publisher, year, edition, pages
COLD SPRING HARBOR LAB PRESS, PUBLICATIONS DEPT, 2017
Keywords
medulloblastoma, p73, glutamine, metabolomics
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-336829 (URN)10.1101/gad.302349.117 (DOI)000412275500004 ()28971956 (PubMedID)
Available from: 2017-12-20 Created: 2017-12-20 Last updated: 2017-12-20Bibliographically approved
Elmsjö, A., Haglöf, J., Engskog, M. K. R., Nestor, M., Arvidsson, T. & Pettersson, C. (2017). The co-feature ratio, a novel method for the measurement of chromatographic and signal selectivity in LC-MS-based metabolomics.. Analytica Chimica Acta, 956, 40-47
Open this publication in new window or tab >>The co-feature ratio, a novel method for the measurement of chromatographic and signal selectivity in LC-MS-based metabolomics.
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2017 (English)In: Analytica Chimica Acta, ISSN 0003-2670, E-ISSN 1873-4324, Vol. 956, p. 40-47Article in journal (Refereed) Published
Abstract [en]

Evaluation of analytical procedures, especially in regards to measuring chromatographic and signal selectivity, is highly challenging in untargeted metabolomics. The aim of this study was to suggest a new straightforward approach for a systematic examination of chromatographic and signal selectivity in LC-MS-based metabolomics. By calculating the ratio between each feature and its co-eluting features (the co-features), a measurement of the chromatographic selectivity (i.e. extent of co-elution) as well as the signal selectivity (e.g. amount of adduct formation) of each feature could be acquired, the co-feature ratio. This approach was used to examine possible differences in chromatographic and signal selectivity present in samples exposed to three different sample preparation procedures. The capability of the co-feature ratio was evaluated both in a classical targeted setting using isotope labelled standards as well as without standards in an untargeted setting. For the targeted analysis, several metabolites showed a skewed quantitative signal due to poor chromatographic selectivity and/or poor signal selectivity. Moreover, evaluation of the untargeted approach through multivariate analysis of the co-feature ratios demonstrated the possibility to screen for metabolites displaying poor chromatographic and/or signal selectivity characteristics. We conclude that the co-feature ratio can be a useful tool in the development and evaluation of analytical procedures in LC-MS-based metabolomics investigations. Increased selectivity through proper choice of analytical procedures may decrease the false positive and false negative discovery rate and thereby increase the validity of any metabolomic investigation.

National Category
Analytical Chemistry Pharmaceutical Sciences
Research subject
Analytical Pharmaceutical Chemistry
Identifiers
urn:nbn:se:uu:diva-314239 (URN)10.1016/j.aca.2016.12.022 (DOI)000393252000005 ()28093124 (PubMedID)
Available from: 2017-01-31 Created: 2017-01-31 Last updated: 2018-01-13Bibliographically approved
Engskog, M. K., Karlsson, O., Haglöf, J., Elmsjö, A., Brittebo, E., Arvidsson, T. & Pettersson, C. (2017). The cyanobacterial amino acid beta-N-methylamino-L-alanine perturbs the intermediary metabolism in neonatal rats. Amino Acids, 49(5), 905-919, Article ID 10.1007/s00726-017-2391-8.
Open this publication in new window or tab >>The cyanobacterial amino acid beta-N-methylamino-L-alanine perturbs the intermediary metabolism in neonatal rats
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2017 (English)In: Amino Acids, ISSN 0939-4451, E-ISSN 1438-2199, Vol. 49, no 5, p. 905-919, article id 10.1007/s00726-017-2391-8Article in journal (Refereed) Published
Abstract [en]

The neurotoxic amino acid β-N-methylamino-l-alanine (BMAA) is produced by most cyanobacteria. BMAA is considered as a potential health threat because of its putative role in neurodegenerative diseases. We have previously observed cognitive disturbances and morphological brain changes in adult rodents exposed to BMAA during the development. The aim of this study was to characterize changes of major intermediary metabolites in serum following neonatal exposure to BMAA using a non-targeted metabolomic approach. NMR spectroscopy was used to obtain serum metabolic profiles from neonatal rats exposed to BMAA (40, 150, 460mg/kg) or vehicle on postnatal days 9-10. Multivariate data analysis of binned NMR data indicated metabolic pattern differences between the different treatment groups. In particular five metabolites, d-glucose, lactate, 3-hydroxybutyrate, creatine and acetate, were changed in serum of BMAA-treated neonatal rats. These metabolites are associated with changes in energy metabolism and amino acid metabolism. Further statistical analysis disclosed that all the identified serum metabolites in the lowest dose group were significantly (p<0.05) decreased. The neonatal rat model used in this study is so far the only animal model that displays significant biochemical and behavioral effects after a low short-term dose of BMAA. The demonstrated perturbation of intermediary metabolism may contribute to BMAA-induced developmental changes that result in long-term effects on adult brain function.

Keywords
β-N-methylamino-L-alanine, cyanobacteria, energy metabolism, neurotoxin, metabolomics, NMR
National Category
Analytical Chemistry Pharmaceutical Sciences
Research subject
Analytical Pharmaceutical Chemistry; Pharmaceutical Science
Identifiers
urn:nbn:se:uu:diva-205735 (URN)10.1016/j.tox.2013.07.010 (DOI)000327005300002 ()23886855 (PubMedID)
Funder
Swedish Research Council Formas
Available from: 2013-08-22 Created: 2013-08-22 Last updated: 2018-01-11
Engskog, M. K. R., Ersson, L., Haglöf, J., Arvidsson, T., Pettersson, C. & Brittebo, E. (2017). β-N-Methylamino-L-alanine (BMAA) perturbs alanine, aspartate and glutamate metabolism pathways in human neuroblastoma cells as determined by metabolic profiling. Amino Acids, 49(5), 905-919
Open this publication in new window or tab >>β-N-Methylamino-L-alanine (BMAA) perturbs alanine, aspartate and glutamate metabolism pathways in human neuroblastoma cells as determined by metabolic profiling
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2017 (English)In: Amino Acids, ISSN 0939-4451, E-ISSN 1438-2199, Vol. 49, no 5, p. 905-919Article in journal (Refereed) Published
Abstract [en]

β-Methylamino-L-alanine (BMAA) is a non-proteinogenic amino acid that induces long-term cognitive deficits, as well as an increased neurodegeneration and intracellular fibril formation in the hippocampus of adult rodents following short-time neonatal exposure and in vervet monkey brain following long-term exposure. It has also been proposed to be involved in the etiology of neurodegenerative disease in humans. The aim of this study was to identify metabolic effects not related to excitotoxicity or oxidative stress in human neuroblastoma SH-SY5Y cells. The effects of BMAA (50, 250, 1000 µM) for 24 h on cells differentiated with retinoic acid were studied. Samples were analyzed using LC-MS and NMR spectroscopy to detect altered intracellular polar metabolites. The analysis performed, followed by multivariate pattern recognition techniques, revealed significant perturbations in protein biosynthesis, amino acid metabolism pathways and citrate cycle. Of specific interest were the BMAA-induced alterations in alanine, aspartate and glutamate metabolism and as well as alterations in various neurotransmitters/neuromodulators such as GABA and taurine. The results indicate that BMAA can interfere with metabolic pathways involved in neurotransmission in human neuroblastoma cells.

Keywords
BMAA, Global metabolite profiling, MS, Metabolism, NMR, Neurotoxin
National Category
Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-322142 (URN)10.1007/s00726-017-2391-8 (DOI)000399176200006 ()28161796 (PubMedID)
Funder
Swedish Research Council Formas
Available from: 2017-05-16 Created: 2017-05-16 Last updated: 2018-01-13Bibliographically approved
Engskog, M. K. R., Haglöf, J., Arvidsson, T. & Pettersson, C. (2016). LC-MS based global metabolite profiling: the necessity of high data quality. Metabolomics, 12(7), Article ID 114.
Open this publication in new window or tab >>LC-MS based global metabolite profiling: the necessity of high data quality
2016 (English)In: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 12, no 7, article id 114Article, review/survey (Refereed) Published
Abstract [en]

LC-MS based global metabolite profiling currently lacks detailed guidelines to demonstrate that the obtained data is of high enough analytical quality. Insufficient data quality may result in the failure to generate a hypothesis, or in the worst case, a false or skewed hypothesis. After assessing the literature, it is apparent that an analytically focused summary and critical discussion related to this subject would be beneficial for both beginners and experts engaged in this field. A particular focus will be placed on data quality, which we here define as the degree to which a set of parameters fulfills predetermined criteria, similar to the established guidelines for targeted analysis. However, several of these parameters are difficult to assess since holistic approaches measure thousands of metabolites in parallel and seldom include predefined knowledge of which metabolites will differ between sample groups. In this review, the following parameters will be discussed in detail: reproducibility, selectivity, certainty of metabolite identification and metabolite coverage. The review systematically describes the generic workflow for LC-MS based global metabolite profiling and highlights how each separate part may affect data quality. The last part of the review describes how data quality can be evaluated as well as identifies areas where additional improvement is needed. In this review, we provide our own analytical opinions in regards to evaluation and, to some extent, improvement of data quality.

Keywords
Data quality, Global metabolite profiling, LC-MS, Validation, Metabolomic workflow, Metabolomics
National Category
Endocrinology and Diabetes
Identifiers
urn:nbn:se:uu:diva-300659 (URN)10.1007/s11306-016-1058-x (DOI)000379508500006 ()
Available from: 2016-08-10 Created: 2016-08-10 Last updated: 2017-11-28Bibliographically approved
Engskog, M. K., Björklund, M., Haglöf, J., Arvidsson, T., Shoshan, M. & Pettersson, C. (2015). Metabolic profiling of epithelial ovarian cancer cell lines: evaluation of harvesting protocols for profiling using NMR spectroscopy. Bioanalysis, 7(2), 157-166
Open this publication in new window or tab >>Metabolic profiling of epithelial ovarian cancer cell lines: evaluation of harvesting protocols for profiling using NMR spectroscopy
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2015 (English)In: Bioanalysis, ISSN 1757-6180, E-ISSN 1757-6199, Vol. 7, no 2, p. 157-166Article in journal (Refereed) Published
Abstract [en]

BACKGROUND: Metabolic profiling represents a novel technology for analyzing tumor cells. Epithelial ovarian carcinoma has a low survival rate due to the development of aggressive and chemotherapy-resistant cells. A tailored and reliable protocol is presented for profiling of chemoresistant cells using the cell line SKOV3 and a multiresistant subline SKOV3R.

RESULTS: Harvesting protocols with cold methanol or MilliQ freeze/thaw cycles were compared. Increased reproducibility using MilliQ was evidenced. Importantly, both approaches resulted in similar profiles. Compared with parental SKOV3, the SKOV3R cells showed a significantly different profile.

CONCLUSION: The MilliQ protocol is preferred owing to higher reproducibility and increased sample preparation options. The resulting metabolic profiles summarize metabolic alterations in chemoresistant cells consistent with a progressed and aggressive phenotype.

National Category
Analytical Chemistry Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-243094 (URN)10.4155/bio.14.235 (DOI)000354284100003 ()25587833 (PubMedID)
Note

De två första författarna delar förstaförfattarskapet.

Available from: 2015-02-04 Created: 2015-02-04 Last updated: 2018-01-11Bibliographically approved
Elmsjö, A., Rosqvist, F., Engskog, M. K., Haglöf, J., Kullberg, J., Iggman, D., . . . Pettersson, C. (2015). NMR-based metabolic profiling in healthy individuals overfed different types of fat: links to changes in liver fat accumulation and lean tissue mass.. Nutrition & Diabetes, 5(19), e182
Open this publication in new window or tab >>NMR-based metabolic profiling in healthy individuals overfed different types of fat: links to changes in liver fat accumulation and lean tissue mass.
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2015 (English)In: Nutrition & Diabetes, ISSN 2044-4052, E-ISSN 2044-4052, Vol. 5, no 19, p. e182-Article in journal (Refereed) Published
Abstract [en]

BACKGROUND: Overeating different dietary fatty acids influence the amount of liver fat stored during weight gain, however, the mechanisms responsible are unclear. We aimed to identify non-lipid metabolites that may differentiate between saturated (SFA) and polyunsaturated fatty acid (PUFA) overfeeding using a non-targeted metabolomic approach. We also investigated the possible relationships between plasma metabolites and body fat accumulation.

METHODS: In a randomized study (LIPOGAIN study), n=39 healthy individuals were overfed with muffins containing SFA or PUFA. Plasma samples were precipitated with cold acetonitrile and analyzed by nuclear magnetic resonance (NMR) spectroscopy. Pattern recognition techniques were used to overview the data, identify variables contributing to group classification and to correlate metabolites with fat accumulation.

RESULTS: We previously reported that SFA causes a greater accumulation of liver fat, visceral fat and total body fat, whereas lean tissue levels increases less compared with PUFA, despite comparable weight gain. In this study, lactate and acetate were identified as important contributors to group classification between SFA and PUFA (P<0.05). Furthermore, the fat depots (total body fat, visceral adipose tissue and liver fat) and lean tissue correlated (P(corr)>0.5) all with two or more metabolites (for example, branched amino acids, alanine, acetate and lactate). The metabolite composition differed in a manner that may indicate higher insulin sensitivity after a diet with PUFA compared with SFA, but this needs to be confirmed in future studies.

CONCLUSION: A non-lipid metabolic profiling approach only identified a few metabolites that differentiated between SFA and PUFA overfeeding. Whether these metabolite changes are involved in depot-specific fat storage and increased lean tissue mass during overeating needs further investigation.

National Category
Medical and Health Sciences Nutrition and Dietetics
Identifiers
urn:nbn:se:uu:diva-267034 (URN)10.1038/nutd.2015.31 (DOI)000368899900002 ()26479316 (PubMedID)
Funder
Swedish Research Council, K2015-54X-22081-04-3Swedish Diabetes Association
Note

Rosqvist, Engskog, Haglöf, Riséus and Pettersson contributed equally to this work.

Available from: 2015-11-17 Created: 2015-11-17 Last updated: 2017-12-01Bibliographically approved
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