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  • 1.
    Benfeitas, Rui
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Uhlén, Mathias
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Nielsen, Jens
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Mardinoglu, A.
    New challenges to study heterogeneity in cancer redox metabolism2017In: Frontiers in Cell and Developmental Biology, ISSN 2296-634X, Vol. 5, no JUL, article id 65Article in journal (Refereed)
    Abstract [en]

    Reactive oxygen species (ROS) are important pathophysiological molecules involved in vital cellular processes. They are extremely harmful at high concentrations because they promote the generation of radicals and the oxidation of lipids, proteins, and nucleic acids, which can result in apoptosis. An imbalance of ROS and a disturbance of redox homeostasis are now recognized as a hallmark of complex diseases. Considering that ROS levels are significantly increased in cancer cells due to mitochondrial dysfunction, ROS metabolism has been targeted for the development of efficient treatment strategies, and antioxidants are used as potential chemotherapeutic drugs. However, initial ROS-focused clinical trials in which antioxidants were supplemented to patients provided inconsistent results, i.e., improved treatment or increased malignancy. These different outcomes may result from the highly heterogeneous redox responses of tumors in different patients. Hence, population-based treatment strategies are unsuitable and patient-tailored therapeutic approaches are required for the effective treatment of patients. Moreover, due to the crosstalk between ROS, reducing equivalents [e.g., NAD(P)H] and central metabolism, which is heterogeneous in cancer, finding the best therapeutic target requires the consideration of system-wide approaches that are capable of capturing the complex alterations observed in all of the associated pathways. Systems biology and engineering approaches may be employed to overcome these challenges, together with tools developed in personalized medicine. However, ROS- and redox-based therapies have yet to be addressed by these methodologies in the context of disease treatment. Here, we review the role of ROS and their coupled redox partners in tumorigenesis. Specifically, we highlight some of the challenges in understanding the role of hydrogen peroxide (H2O2), one of the most important ROS in pathophysiology in the progression of cancer. We also discuss its interplay with antioxidant defenses, such as the coupled peroxiredoxin/thioredoxin and glutathione/glutathione peroxidase systems, and its reducing equivalent metabolism. Finally, we highlight the need for system-level and patient-tailored approaches to clarify the roles of these systems and identify therapeutic targets through the use of the tools developed in personalized medicine. © 2017 Benfeitas, Uhlen, Nielsen and Mardinoglu.

  • 2. Bosley, Jim
    et al.
    Borén, Christofer
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lee, Sunjae
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Grotli, Morten
    Nielsen, Jens
    KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers University of Technology, Sweden.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Boren, Jan
    Mardinoglu, Adil
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers University of Technology, Sweden.
    Improving the economics of NASH/NAFLD treatment through the use of systems biology2017In: Drug Discovery Today, ISSN 1359-6446, E-ISSN 1878-5832, Vol. 22, no 10, p. 1532-1538Article, review/survey (Refereed)
    Abstract [en]

    Nonalcoholic steatohepatitis (NASH) is a severe form of nonalcoholic fatty liver disease (NAFLD). We surveyed NASH therapies currently in development, and found a significant variety of targets and approaches. Evaluation and clinical testing of these targets is an expensive and time-consuming process. Systems biology approaches could enable the quantitative evaluation of the likely efficacy and safety of different targets. This motivated our review of recent systems biology studies that focus on the identification of targets and development of effective treatments for NASH. We discuss the potential broader use of genome-scale metabolic models and integrated networks in the validation of drug targets, which could facilitate more productive and efficient drug development decisions for the treatment of NASH.

  • 3. Caspeta, Luis
    et al.
    Chen, Yun
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Thermotolerant yeasts selected by adaptive evolution express heat stress response at 30 degrees C2016In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 6, article id 27003Article in journal (Refereed)
    Abstract [en]

    Exposure to long-term environmental changes across >100s of generations results in adapted phenotypes, but little is known about how metabolic and transcriptional responses are optimized in these processes. Here, we show that thermotolerant yeast strains selected by adaptive laboratory evolution to grow at increased temperature, activated a constitutive heat stress response when grown at the optimal ancestral temperature, and that this is associated with a reduced growth rate. This preventive response was perfected by additional transcriptional changes activated when the cultivation temperature is increased. Remarkably, the sum of global transcriptional changes activated in the thermotolerant strains when transferred from the optimal to the high temperature, corresponded, in magnitude and direction, to the global changes observed in the ancestral strain exposed to the same transition. This demonstrates robustness of the yeast transcriptional program when exposed to heat, and that the thermotolerant strains streamlined their path to rapidly and optimally reach post-stress transcriptional and metabolic levels. Thus, long-term adaptation to heat improved yeasts ability to rapidly adapt to increased temperatures, but this also causes a trade-off in the growth rate at the optimal ancestral temperature.

  • 4. Chen, Y.
    et al.
    Nielsen, Jens
    KTH, Centres, Science for Life Laboratory, SciLifeLab. Novo Nordisk Foundation Center for Biosustainability.
    Advances in metabolic pathway and strain engineering paving the way for sustainable production of chemical building blocks2013In: Current Opinion in Biotechnology, ISSN 0958-1669, E-ISSN 1879-0429, Vol. 24, no 6, p. 965-972Article, review/survey (Refereed)
    Abstract [en]

    Bio-based production of chemical building blocks from renewable resources is an attractive alternative to petroleum-based platform chemicals. Metabolic pathway and strain engineering is the key element in constructing robust microbial chemical factories within the constraints of cost effective production. Here we discuss how the development of computational algorithms, novel modules and methods, omics-based techniques combined with modeling refinement are enabling reduction in development time and thus advance the field of industrial biotechnology. We further discuss how recent technological developments contribute to the development of novel cell factories for the production of the building block chemicals: adipic acid, succinic acid and 3-hydroxypropionic acid.

  • 5. Elsemman, Ibrahim E.
    et al.
    Mardinoglu, Adil
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers University of Technology, Sweden.
    Shoaie, Saeed
    Soliman, Taysir H.
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers University of Technology, Sweden.
    Systems biology analysis of hepatitis C virus infection reveals the role of copy number increases in regions of chromosome 1q in hepatocellular carcinoma metabolism2016In: Molecular Biosystems, ISSN 1742-206X, E-ISSN 1742-2051, Vol. 12, no 5, p. 1496-1506Article in journal (Refereed)
    Abstract [en]

    Hepatitis C virus (HCV) infection is a worldwide healthcare problem; however, traditional treatment methods have failed to cure all patients, and HCV has developed resistance to new drugs. Systems biology-based analyses could play an important role in the holistic analysis of the impact of HCV on hepatocellular metabolism. Here, we integrated HCV assembly reactions with a genome-scale hepatocyte metabolic model to identify metabolic targets for HCV assembly and metabolic alterations that occur between different HCV progression states (cirrhosis, dysplastic nodule, and early and advanced hepatocellular carcinoma (HCC)) and healthy liver tissue. We found that diacylglycerolipids were essential for HCV assembly. In addition, the metabolism of keratan sulfate and chondroitin sulfate was significantly changed in the cirrhosis stage, whereas the metabolism of acyl-carnitine was significantly changed in the dysplastic nodule and early HCC stages. Our results explained the role of the upregulated expression of BCAT1, PLOD3 and six other methyltransferase genes involved in carnitine biosynthesis and S-adenosylmethionine metabolism in the early and advanced HCC stages. Moreover, GNPAT and BCAP31 expression was upregulated in the early and advanced HCC stages and could lead to increased acyl-CoA consumption. By integrating our results with copy number variation analyses, we observed that GNPAT, PPOX and five of the methyltransferase genes (ASH1L, METTL13, SMYD2, TARBP1 and SMYD3), which are all located on chromosome 1q, had increased copy numbers in the cancer samples relative to the normal samples. Finally, we confirmed our predictions with the results of metabolomics studies and proposed that inhibiting the identified targets has the potential to provide an effective treatment strategy for HCV-associated liver disorders.

  • 6.
    Fagerberg, Linn
    et al.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hallström, Björn M.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Oksvold, Per
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Kampf, C.
    Djureinovic, D.
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Habuka, Masato
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Tahmasebpoor, S.
    Danielsson, A.
    Edlund, K.
    Asplund, A.
    Sjöstedt, E.
    Lundberg, E.
    Szigyarto, Cristina Al-Khalili
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Skogs, Marie
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Ottosson Takanen, J.
    Berling, H.
    Tegel, Hanna
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Mulder, J.
    Nilsson, Peter
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Schwenk, Jochen M.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lindskog, C.
    Danielsson, Frida
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Mardinoglu, A.
    Sivertsson, Åsa
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Von Feilitzen, Kalle
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Forsberg, Mattias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Zwahlen, Martin
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Olsson, I.
    Navani, S.
    Huss, Mikael
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Pontén, F.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Analysis of the human tissue-specific expression by genome-wide integration of transcriptomics and antibody-based proteomics2014In: Molecular & Cellular Proteomics, ISSN 1535-9476, E-ISSN 1535-9484, Vol. 13, no 2, p. 397-406Article in journal (Refereed)
    Abstract [en]

    Global classification of the human proteins with regards to spatial expression patterns across organs and tissues is important for studies of human biology and disease. Here, we used a quantitative transcriptomics analysis (RNA-Seq) to classify the tissue-specific expression of genes across a representative set of all major human organs and tissues and combined this analysis with antibody- based profiling of the same tissues. To present the data, we launch a new version of the Human Protein Atlas that integrates RNA and protein expression data corresponding to 80% of the human protein-coding genes with access to the primary data for both the RNA and the protein analysis on an individual gene level. We present a classification of all human protein-coding genes with regards to tissue-specificity and spatial expression pattern. The integrative human expression map can be used as a starting point to explore the molecular constituents of the human body.

  • 7. Fletcher, E.
    et al.
    Feizi, A.
    Bisschops, M. M. M.
    Hallström, Björn M.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Khoomrung, S.
    Siewers, V.
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers University of Technology, Sweden.
    Evolutionary engineering reveals divergent paths when yeast is adapted to different acidic environments2017In: Metabolic engineering, ISSN 1096-7176, E-ISSN 1096-7184, Vol. 39, p. 19-28Article in journal (Refereed)
    Abstract [en]

    Tolerance of yeast to acid stress is important for many industrial processes including organic acid production. Therefore, elucidating the molecular basis of long term adaptation to acidic environments will be beneficial for engineering production strains to thrive under such harsh conditions. Previous studies using gene expression analysis have suggested that both organic and inorganic acids display similar responses during short term exposure to acidic conditions. However, biological mechanisms that will lead to long term adaptation of yeast to acidic conditions remains unknown and whether these mechanisms will be similar for tolerance to both organic and inorganic acids is yet to be explored. We therefore evolved Saccharomyces cerevisiae to acquire tolerance to HCl (inorganic acid) and to 0.3 M L-lactic acid (organic acid) at pH 2.8 and then isolated several low pH tolerant strains. Whole genome sequencing and RNA-seq analysis of the evolved strains revealed different sets of genome alterations suggesting a divergence in adaptation to these two acids. An altered sterol composition and impaired iron uptake contributed to HCl tolerance whereas the formation of a multicellular morphology and rapid lactate degradation was crucial for tolerance to high concentrations of lactic acid. Our findings highlight the contribution of both the selection pressure and nature of the acid as a driver for directing the evolutionary path towards tolerance to low pH. The choice of carbon source was also an important factor in the evolutionary process since cells evolved on two different carbon sources (raffinose and glucose) generated a different set of mutations in response to the presence of lactic acid. Therefore, different strategies are required for a rational design of low pH tolerant strains depending on the acid of interest.

  • 8. Ghaffari, Pouyan
    et al.
    Mardinoglu, Adil
    Asplund, Anna
    Shoaie, Saeed
    Kampf, Caroline
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Nielsen, Jens
    KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers, Dept Biol & Biol Engn, Sweden.
    Identifying anti-growth factors for human cancer cell lines through genome-scale metabolic modeling2015In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 5, p. 8183-Article in journal (Refereed)
    Abstract [en]

    Human cancer cell lines are used as important model systems to study molecular mechanisms associated with tumor growth, hereunder how genomic and biological heterogeneity found in primary tumors affect cellular phenotypes. We reconstructed Genome scale metabolic models (GEMs) for eleven cell lines based on RNA-Seq data and validated the functionality of these models with data from metabolite profiling. We used cell line-specific GEMs to analyze the differences in the metabolism of cancer cell lines, and to explore the heterogeneous expression of the metabolic subsystems. Furthermore, we predicted 85 antimetabolites that can inhibit growth of, or even kill, any of the cell lines, while at the same time not being toxic for 83 different healthy human cell types. 60 of these antimetabolites were found to inhibit growth in all cell lines. Finally, we experimentally validated one of the predicted antimetabolites using two cell lines with different phenotypic origins, and found that it is effective in inhibiting the growth of these cell lines. Using immunohistochemistry, we also showed high or moderate expression levels of proteins targeted by the validated antimetabolite. Identified anti-growth factors for inhibition of cell growth may provide leads for the development of efficient cancer treatment strategies.

  • 9. Ghaffari, Pouyan
    et al.
    Mardinoglu, Adil
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers University of Technology, Sweden.
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers University of Technology, Sweden; Technical University of Denmark, Denmark.
    Cancer Metabolism: A Modeling Perspective2015In: Frontiers in Physiology, ISSN 1664-042X, E-ISSN 1664-042X, Vol. 6, article id 382Article, review/survey (Refereed)
    Abstract [en]

    Tumor cells alter their metabolism to maintain unregulated cellular proliferation and survival, but this transformation leaves them reliant on constant supply of nutrients and energy. In addition to the widely studied dysregulated glucose metabolism to fuel tumor cell growth, accumulating evidences suggest that utilization of amino acids and lipids contributes significantly to cancer cell metabolism. Also recent progresses in our understanding of carcinogenesis have revealed that cancer is a complex disease and cannot be understood through simple investigation of genetic mutations of cancerous cells. Cancer cells present in complex tumor tissues communicate with the surrounding microenvironment and develop traits which promote their growth, survival, and metastasis. Decoding the full scope and targeting dysregulated metabolic pathways that support neoplastic transformations and their preservation requires both the advancement of experimental technologies for more comprehensive measurement of omics as well as the advancement of robust computational methods for accurate analysis of the generated data. Here, we review cancer-associated reprogramming of metabolism and highlight the capability of genome-scale metabolic modeling approaches in perceiving a system-level perspective of cancer metabolism and in detecting novel selective drug targets.

  • 10.
    González Arcos, Angélica Viviana
    et al.
    KTH, School of Chemical Science and Engineering (CHE), Chemical Engineering and Technology, Chemical Technology.
    Rostrup-Nielsen, J.
    KTH, School of Chemical Science and Engineering (CHE), Chemical Engineering and Technology, Chemical Technology.
    Engvall, Klas
    KTH, School of Chemical Science and Engineering (CHE), Chemical Engineering and Technology, Chemical Technology.
    Pettersson, Lars J.
    KTH, School of Chemical Science and Engineering (CHE), Chemical Engineering and Technology, Chemical Technology.
    Promoted RhPt bimetallic catalyst supported on δ-Al2O3 and CeO2-ZrO2 during full-scale autothermal reforming for automotive applications: Post-mortem characterization2015In: Applied Catalysis A: General, ISSN 0926-860X, E-ISSN 1873-3875, Vol. 491, p. 8-16Article in journal (Refereed)
    Abstract [en]

    The influence of sulfur and coke formation on the steam reforming of diesel was evaluated for two promoted RhPt bimetallic catalysts, composed of 1:1 Rh:Pt/10:10 La2O3: CeO2/ δ-Al2O3 (CAT 1) and 1:1 Rh:Pt/4:5 MgO: Y2O3/CeO2 − ZrO2 (CAT 2). The intrinsic activity is related to the total Rh and Pt area observed after the exposure to sulfur. Therefore, the degree of deactivation is related to the amount of sulfur deposited on the active metal sites. Sulfur analysis on the aged catalyst washcoat showed a decreasing sulfur concentration in the axial direction of the reformer. The estimated sulfur coverage related to metal surface area after 40 h on stream reached values of 0.145 in CAT 2, below the equilibrated sulfur coverage of 0.19 after tests with DIN 590. Thus, showing a partial deactivation due to sulfur poisoning. Further catalyst characterization on carbon deposits and thermal aging was performed by TPO, TGA, BET, CO chemisorption, and TEM analysis.

  • 11. Hu, Y.
    et al.
    Zhu, Z.
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers University of Technology, Sweden.
    Siewers, V.
    Heterologous transporter expression for improved fatty alcohol secretion in yeast2018In: Metabolic engineering, ISSN 1096-7176, E-ISSN 1096-7184, Vol. 45, p. 51-58Article in journal (Refereed)
    Abstract [en]

    The yeast Saccharomyces cerevisiae is an attractive host for industrial scale production of biofuels including fatty alcohols due to its robustness and tolerance towards harsh fermentation conditions. Many metabolic engineering strategies have been applied to generate high fatty alcohol production strains. However, impaired growth caused by fatty alcohol accumulation and high cost of extraction are factors limiting large-scale production. Here, we demonstrate that the use of heterologous transporters is a promising strategy to increase fatty alcohol production. Among several plant and mammalian transporters tested, human FATP1 was shown to mediate fatty alcohol export in a high fatty alcohol production yeast strain. An approximately five-fold increase of fatty alcohol secretion was achieved. The results indicate that the overall cell fitness benefited from fatty alcohol secretion and that the acyl-CoA synthase activity of FATP1 contributed to increased cell growth as well. This is the first study that enabled an increased cell fitness for fatty alcohol production by heterologous transporter expression in yeast, and this investigation indicates a new potential function of FATP1, which has been known as a free fatty acid importer to date. We furthermore successfully identified the functional domain of FATP1 involved in fatty alcohol export through domain exchange between FATP1 and another transporter, FATP4. This study may facilitate a successful commercialization of fatty alcohol production in yeast and inspire the design of novel cell factories.

  • 12. Huang, M.
    et al.
    Bao, J.
    Hallström, Björn M.
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Petranovic, D.
    Nielsen, Jens
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Efficient protein production by yeast requires global tuning of metabolism2017In: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 8, no 1, article id 1131Article in journal (Refereed)
    Abstract [en]

    The biotech industry relies on cell factories for production of pharmaceutical proteins, of which several are among the top-selling medicines. There is, therefore, considerable interest in improving the efficiency of protein production by cell factories. Protein secretion involves numerous intracellular processes with many underlying mechanisms still remaining unclear. Here, we use RNA-seq to study the genome-wide transcriptional response to protein secretion in mutant yeast strains. We find that many cellular processes have to be attuned to support efficient protein secretion. In particular, altered energy metabolism resulting in reduced respiration and increased fermentation, as well as balancing of amino-acid biosynthesis and reduced thiamine biosynthesis seem to be particularly important. We confirm our findings by inverse engineering and physiological characterization and show that by tuning metabolism cells are able to efficiently secrete recombinant proteins. Our findings provide increased understanding of which cellular regulations and pathways are associated with efficient protein secretion.

  • 13. Huang, Mingtao
    et al.
    Bai, Yunpeng
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab. East China University of Science and Technology, China.
    Sjöström, Staffan L.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hallström, Björn M.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Liu, Zihe
    Petranovic, Dina
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Technical University of Denmark, Denmark .
    Jönsson, Håkan N.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Andersson Svahn, Helene
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers University of Technology, Sweden; Technical University of Denmark, Denmark.
    Microfluidic screening and whole-genome sequencing identifies mutations associated with improved protein secretion by yeast2015In: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, Vol. 112, no 34, p. E4689-E4696Article in journal (Other academic)
    Abstract [en]

    There is an increasing demand for biotech-based production of recombinant proteins for use as pharmaceuticals in the food and feed industry and in industrial applications. Yeast Saccharomyces cerevisiae is among preferred cell factories for recombinant protein production, and there is increasing interest in improving its protein secretion capacity. Due to the complexity of the secretory machinery in eukaryotic cells, it is difficult to apply rational engineering for construction of improved strains. Here we used highthroughput microfluidics for the screening of yeast libraries, generated by UV mutagenesis. Several screening and sorting rounds resulted in the selection of eight yeast clones with significantly improved secretion of recombinant α-amylase. Efficient secretion was genetically stable in the selected clones. We performed wholegenome sequencing of the eight clones and identified 330 mutations in total. Gene ontology analysis of mutated genes revealed many biological processes, including some that have not been identified before in the context of protein secretion. Mutated genes identified in this study can be potentially used for reverse metabolic engineering, with the objective to construct efficient cell factories for protein secretion. The combined use of microfluidics screening and whole-genome sequencing to map the mutations associated with the improved phenotype can easily be adapted for other products and cell types to identify novel engineering targets, and this approach could broadly facilitate design of novel cell factories.

  • 14. Kampf, Caroline
    et al.
    Mardinoglu, Adil
    Fagerberg, Linn
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hallström, Björn M.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Danielsson, Angelika
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers University of Technology, Sweden.
    Pontén, Fredrik
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Defining the human gallbladder proteome by transcriptomics and affinity proteomics2014In: Proteomics, ISSN 1615-9853, E-ISSN 1615-9861, Vol. 14, no 21-22, p. 2498-2507Article in journal (Refereed)
    Abstract [en]

    Global protein analysis of human gallbladder tissue is vital for identification of molecular regulators and effectors of its physiological activity. Here, we employed a genome-wide deep RNA sequencing analysis in 28 human tissues to identify the genes overrepresented in the gallbladder and complemented it with antibody-based immunohistochemistry in 48 human tissues. We characterized human gallbladder proteins and identified 140 gallbladder-specific proteins with an elevated expression in the gallbladder as compared to the other analyzed tissues. Five genes were categorized as enriched, with at least fivefold higher levels in gallbladder, 60 genes were categorized as group enriched with elevated transcript levels in gallbladder shared with at least one other tissue and 75 genes were categorized as enhanced with higher expression than the average expression in other tissues. We explored the localization of the genes within the gallbladder through cell-type specific antibody-based protein profiling and the subcellular localization of the genes through immunofluorescent-based profiling. Finally, we revealed the biological processes and metabolic functions carried out by these genes through the use of GO, KEGG Pathway, and HMR2.0 that is compilation of the human metabolic reactions. We demonstrated the results of the combined analysis of the transcriptomics and affinity proteomics.

  • 15. Kampf, Caroline
    et al.
    Mardinoglu, Adil
    Fagerberg, Linn
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hallström, Björn M.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Edlund, Karolina
    Lundberg, Emma
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Pontén, Fredrik
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    The human liver-specific proteome defined by transcriptomics and antibody-based profiling2014In: The FASEB Journal, ISSN 0892-6638, E-ISSN 1530-6860, Vol. 28, no 7, p. 2901-2914Article in journal (Refereed)
    Abstract [en]

    Human liver physiology and the genetic etiology of the liver diseases can potentially be elucidated through the identification of proteins with enriched expression in the liver. Here, we combined data from RNA sequencing (RNA-Seq) and antibody-based immunohistochemistry across all major human tissues to explore the human liver proteome with enriched expression, as well as the cell type-enriched expression in hepatocyte and bile duct cells. We identified in total 477 protein-coding genes with elevated expression in the liver: 179 genes have higher expression as compared to all the other analyzed tissues; 164 genes have elevated transcript levels in the liver shared with at least one other tissue type; and an additional 134 genes have a mild level of increased expression in the liver. We identified the precise localization of these proteins through antibody-based protein profiling and the subcellular localization of these proteins through immunofluorescent-based profiling. We also identified the biological processes and metabolic functions associated with these proteins, investigated their contribution in the occurrence of liver diseases, and identified potential targets for their treatment. Our study demonstrates the use of RNA-Seq and antibody-based immunohistochemistry for characterizing the human liver proteome, as well as the use of tissue-specific proteins in identification of novel drug targets and discovery of biomarkers.

  • 16. Kang, M. -K
    et al.
    Nielsen, Jens
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Biobased production of alkanes and alkenes through metabolic engineering of microorganisms2016In: Journal of Industrial Microbiology & Biotechnology, ISSN 1367-5435, E-ISSN 1476-5535, p. 1-10Article in journal (Refereed)
    Abstract [en]

    Advancement in metabolic engineering of microorganisms has enabled bio-based production of a range of chemicals, and such engineered microorganism can be used for sustainable production leading to reduced carbon dioxide emission there. One area that has attained much interest is microbial hydrocarbon biosynthesis, and in particular, alkanes and alkenes are important high-value chemicals as they can be utilized for a broad range of industrial purposes as well as ‘drop-in’ biofuels. Some microorganisms have the ability to biosynthesize alkanes and alkenes naturally, but their production level is extremely low. Therefore, there have been various attempts to recruit other microbial cell factories for production of alkanes and alkenes by applying metabolic engineering strategies. Here we review different pathways and involved enzymes for alkane and alkene production and discuss bottlenecks and possible solutions to accomplish industrial level production of these chemicals by microbial fermentation.

  • 17. Kang, Min-Kyoung
    et al.
    Zhou, Yongjin J.
    Buijs, Nicolaas A.
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Functional screening of aldehyde decarbonylases for long-chain alkane production by Saccharomyces cerevisiae2017In: Microbial Cell Factories, ISSN 1475-2859, E-ISSN 1475-2859, Vol. 16, article id 74Article in journal (Refereed)
    Abstract [en]

    Background: Low catalytic activities of pathway enzymes are often a limitation when using microbial based chemical production. Recent studies indicated that the enzyme activity of aldehyde decarbonylase (AD) is a critical bottleneck for alkane biosynthesis in Saccharomyces cerevisiae. We therefore performed functional screening to identify efficient ADs that can improve alkane production by S. cerevisiae. Results: A comparative study of ADs originated from a plant, insects, and cyanobacteria were conducted in S. cerevisiae. As a result, expression of aldehyde deformylating oxygenases (ADOs), which are cyanobacterial ADs, from Synechococcus elongatus and Crocosphaera watsonii converted fatty aldehydes to corresponding Cn-1 alkanes and alkenes. The CwADO showed the highest alkane titer (0.13 mg/L/OD600) and the lowest fatty alcohol production (0.55 mg/L/OD600). However, no measurable alkanes and alkenes were detected in other AD expressed yeast strains. Dynamic expression of SeADO and CwADO under GAL promoters increased alkane production to 0.20 mg/L/OD600 and no fatty alcohols, with even number chain lengths from C8 to C14, were detected in the cells. Conclusions: We demonstrated in vivo enzyme activities of ADs by displaying profiles of alkanes and fatty alcohols in S. cerevisiae. Among the AD enzymes evaluated, cyanobacteria ADOs were found to be suitable for alkane biosynthesis in S. cerevisiae. This work will be helpful to decide an AD candidate for alkane biosynthesis in S. cerevisiae and it will provide useful information for further investigation of AD enzymes with improved activities.

  • 18. Lahtvee, Petri-Jaan
    et al.
    Kumar, Rahul
    Hallström, Björn M.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers University of Technology, Sweden.
    Adaptation to different types of stress converge on mitochondrial metabolism2016In: Molecular Biology of the Cell, ISSN 1059-1524, E-ISSN 1939-4586, Vol. 27, no 15, p. 2505-2514Article in journal (Refereed)
    Abstract [en]

    Yeast cell factories encounter physical and chemical stresses when used for industrial production of fuels and chemicals. These stresses reduce productivity and increase bioprocess costs. Understanding the mechanisms of the stress response is essential for improving cellular robustness in platform strains. We investigated the three most commonly encountered industrial stresses for yeast (ethanol, salt, and temperature) to identify the mechanisms of general and stress-specific responses under chemostat conditions in which specific growth rate-dependent changes are eliminated. By applying systems-level analysis, we found that most stress responses converge on mitochondrial processes. Our analysis revealed that stress-specific factors differ between applied stresses; however, they are underpinned by an increased ATP demand. We found that when ATP demand increases to high levels, respiration cannot provide sufficient ATP, leading to onset of respirofermentative metabolism. Although stress-specific factors increase ATP demand for cellular growth under stressful conditions, increased ATP demand for cellular maintenance underpins a general stress response and is responsible for the onset of overflow metabolism.

  • 19.
    Lee, Sunjae
    et al.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Korea Adv Inst Sci & Technol, South Korea.
    Mardinoglu, Adil
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers, Sweden.
    Zhang, Cheng
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lee, Doheon
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers, Sweden.
    Dysregulated signaling hubs of liver lipid metabolism reveal hepatocellular carcinoma pathogenesis2016In: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962, Vol. 44, no 12, p. 5529-5539Article in journal (Refereed)
    Abstract [en]

    Hepatocellular carcinoma (HCC) has a high mortality rate and early detection of HCC is crucial for the application of effective treatment strategies. HCC is typically caused by either viral hepatitis infection or by fatty liver disease. To diagnose and treat HCC it is necessary to elucidate the underlying molecular mechanisms. As a major cause for development of HCC is fatty liver disease, we here investigated anomalies in regulation of lipid metabolism in the liver. We applied a tailored network-based approach to identify signaling hubs associated with regulation of this part of metabolism. Using transcriptomics data of HCC patients, we identified significant dysregulated expressions of lipid-regulated genes, across many different lipid metabolic pathways. Our findings, however, show that viral hepatitis causes HCC by a distinct mechanism, less likely involving lipid anomalies. Based on our analysis we suggest signaling hub genes governing overall catabolic or anabolic pathways, as novel drug targets for treatment of HCC that involves lipid anomalies.

  • 20.
    Lee, Sunjae
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Zhang, Cheng
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Arif, Muhammad
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Liu, Zhengtao
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Benfeitas, Rui
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Bidkhori, Gholamreza
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Deshmukh, Sumit
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Shobky, Mohamed AI
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lovric, Alen
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Boren, Jan
    Nielsen, Jens
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Uhlén, Mathias
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Mardinoglu, Adil
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    TCSBN: a database of tissue and cancer specific biological networks2017In: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962Article in journal (Refereed)
  • 21.
    Lee, Sunjae
    et al.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Zhang, Cheng
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Kilicarslan, Murat
    Piening, Brian D.
    Björnson, Elias
    Hallström, Björn M.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Groen, Albert K.
    Ferrannini, Ele
    Laakso, Markku
    Snyder, Michael
    Bluher, Matthias
    Uhlèn, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. Chalmers, Sweden.
    Smith, Ulf
    Serlie, Mireille J.
    Boren, Jan
    Mardinoglu, Adil
    Integrated Network Analysis Reveals an Association between Plasma Mannose Levels and Insulin Resistance2016In: Cell Metabolism, ISSN 1550-4131, E-ISSN 1932-7420, Vol. 24, no 1, p. 172-184Article in journal (Refereed)
    Abstract [en]

    To investigate the biological processes that are altered in obese subjects, we generated cell-specific integrated networks (INs) by merging genome-scale metabolic, transcriptional regulatory and protein-protein interaction networks. We performed genome-wide transcriptomics analysis to determine the global gene expression changes in the liver and three adipose tissues from obese subjects undergoing bariatric surgery and integrated these data into the cell-specific INs. We found dysregulations in mannose metabolism in obese subjects and validated our predictions by detecting mannose levels in the plasma of the lean and obese subjects. We observed significant correlations between plasma mannose levels, BMI, and insulin resistance (IR). We also measured plasma mannose levels of the subjects in two additional different cohorts and observed that an increased plasma mannose level was associated with IR and insulin secretion. We finally identified mannose as one of the best plasma metabolites in explaining the variance in obesity-independent IR.

  • 22.
    Lee, Sunjae
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Zhang, Cheng
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Liu, Zhengtao
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Klevstig, Martina
    Mukhopadhyay, Bani
    Bergentall, Mattias
    Cinar, Resat
    Ståhlman, Marcus
    Sikanic, Natasa
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science.
    Park, Joshua K.
    Deshmukh, Sumit
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science.
    Harzandi, Azadeh M.
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Kuijpers, Tim
    KTH.
    Grotli, Morten
    Elsässer, Simon J.
    Piening, Brian D.
    Snyder, Michael
    Smith, Ulf
    Nielsen, Jens
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Bäckhed, Fredrik
    Kunos, George
    Uhlén, Mathias
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Boren, Jan
    Mardinoglu, Adil
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Network analyses identify liver-specific targets for treating liver diseases2017In: Molecular Systems Biology, ISSN 1744-4292, E-ISSN 1744-4292Article in journal (Refereed)
  • 23. Mardinoglu, A.
    et al.
    Nielsen, Jens Brehm Bagger
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    New paradigms for metabolic modeling of human cells2015In: Current Opinion in Biotechnology, ISSN 0958-1669, E-ISSN 1879-0429, Vol. 34, p. 91-97Article in journal (Refereed)
    Abstract [en]

    Abnormalities in cellular functions are associated with the progression of human diseases, often resulting in metabolic reprogramming. GEnome-scale metabolic Models (GEMs) have enabled studying global metabolic reprogramming in connection with disease development in a systematic manner. Here we review recent work on reconstruction of GEMs for human cell/tissue types and cancer, and the use of GEMs for identification of metabolic changes occurring in response to disease development. We further discuss how GEMs can be used for the development of efficient therapeutic strategies. Finally, challenges in integration of cell/tissue models for simulation of whole body functions as well as integration of GEMs with other biological networks for generating complete cell/tissue models are presented.

  • 24.
    Mardinoglu, Adil
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Bjornson, Elias
    Zhang, Cheng
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Klevstig, Martina
    Soderlund, Sanni
    Stahlman, Marcus
    Adiels, Martin
    Hakkarainen, Antti
    Lundbom, Nina
    Kilicarslan, Murat
    Hallstrom, Bjorn M.
    Lundbom, Jesper
    Verges, Bruno
    Barrett, Peter Hugh R.
    Watts, Gerald F.
    Serlie, Mireille J.
    Nielsen, Jens
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Uhlén, Mathias
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Smith, Ulf
    Marschall, Hanns-Ulrich
    Taskinen, Marja-Riitta
    Boren, Jan
    Personal model-assisted identification of NAD(+) and glutathione metabolism as intervention target in NAFLD2017In: Molecular Systems Biology, ISSN 1744-4292, E-ISSN 1744-4292, Vol. 13, no 3, article id 916Article in journal (Refereed)
    Abstract [en]

    To elucidate the molecular mechanisms underlying non-alcoholic fatty liver disease (NAFLD), we recruited 86 subjects with varying degrees of hepatic steatosis (HS). We obtained experimental data on lipoprotein fluxes and used these individual measurements as personalized constraints of a hepatocyte genome-scale metabolic model to investigate metabolic differences in liver, taking into account its interactions with other tissues. Our systems level analysis predicted an altered demand for NAD(+) and glutathione (GSH) in subjects with high HS. Our analysis and metabolomic measurements showed that plasma levels of glycine, serine, and associated metabolites are negatively correlated with HS, suggesting that these GSH metabolism precursors might be limiting. Quantification of the hepatic expression levels of the associated enzymes further pointed to altered de novo GSH synthesis. To assess the effect of GSH and NAD(+) repletion on the development of NAFLD, we added precursors for GSH and NAD(+) biosynthesis to the Western diet and demonstrated that supplementation prevents HS in mice. In a proof-of-concept human study, we found improved liver function and decreased HS after supplementation with serine (a precursor to glycine) and hereby propose a strategy for NAFLD treatment.

  • 25.
    Mardinoglu, Adil
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers Univ Technol, Dept Biol & Biol Engn, Gothenburg, Sweden..
    Boren, Jan
    Univ Gothenburg, Dept Mol & Clin Med, Gothenburg, Sweden.;Sahlgrens Univ Hosp, Gothenburg, Sweden..
    Smith, Ulf
    Univ Gothenburg, Dept Mol & Clin Med, Gothenburg, Sweden.;Sahlgrens Univ Hosp, Gothenburg, Sweden..
    Uhlén, Mathias
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Nielsen, Jens
    KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers Univ Technol, Dept Biol & Biol Engn, Gothenburg, Sweden..
    Systems biology in hepatology: approaches and applications2018In: Nature Reviews. Gastroenterology & Hepatology, ISSN 1759-5045, E-ISSN 1759-5053, Vol. 15, no 6, p. 365-377Article, review/survey (Refereed)
    Abstract [en]

    Detailed insights into the biological functions of the liver and an understanding of its crosstalk with other human tissues and the gut microbiota can be used to develop novel strategies for the prevention and treatment of liver-associated diseases, including fatty liver disease, cirrhosis, hepatocellular carcinoma and type 2 diabetes mellitus. Biological network models, including metabolic, transcriptional regulatory, protein-protein interaction, signalling and co-expression networks, can provide a scaffold for studying the biological pathways operating in the liver in connection with disease development in a systematic manner. Here, we review studies in which biological network models were used to integrate multiomics data to advance our understanding of the pathophysiological responses of complex liver diseases. We also discuss how this mechanistic approach can contribute to the discovery of potential biomarkers and novel drug targets, which might lead to the design of targeted and improved treatment strategies. Finally, we present a roadmap for the successful integration of models of the liver and other human tissues with the gut microbiota to simulate whole-body metabolic functions in health and disease.

  • 26.
    Mardinoglu, Adil
    et al.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers University of Technology, Sweden.
    Heiker, John T.
    Gaertner, Daniel
    Bjornson, Elias
    Schoen, Michael R.
    Flehmig, Gesine
    Kloeting, Nora
    Krohn, Knut
    Fasshauer, Mathias
    Stumvoll, Michael
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers University of Technology, Sweden.
    Blueher, Matthias
    Extensive weight loss reveals distinct gene expression changes in human subcutaneous and visceral adipose tissue2015In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 5, article id 14841Article in journal (Refereed)
    Abstract [en]

    Weight loss has been shown to significantly improve Adipose tissue (AT) function, however changes in AT gene expression profiles particularly in visceral AT (VAT) have not been systematically studied. Here, we tested the hypothesis that extensive weight loss in response to bariatric surgery (BS) causes AT gene expression changes, which may affect energy and lipid metabolism, inflammation and secretory function of AT. We assessed gene expression changes by whole genome expression chips in AT samples obtained from six morbidly obese individuals, who underwent a two step BS strategy with sleeve gastrectomy as initial and a Roux-en-Y gastric bypass as second step surgery after 12 +/- 2 months. Global gene expression differences in VAT and subcutaneous (S) AT were analyzed through the use of genome-scale metabolic model (GEM) for adipocytes. Significantly altered gene expressions were PCR-validated in 16 individuals, which also underwent a two-step surgery intervention. We found increased expression of cell death-inducing DFFA-like effector a (CIDEA), involved in formation of lipid droplets in both fat depots in response to significant weight loss. We observed that expression of the genes associated with metabolic reactions involved in NAD+, glutathione and branched chain amino acid metabolism are significantly increased in AT depots after surgery-induced weight loss.

  • 27. Mardinoglu, Adil
    et al.
    Kampf, Caroline
    Asplund, Anna
    Fagerberg, Linn
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hallström, Björn M.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Edlund, Karolina
    Blüher, Matthias
    Pontén, Fredrik
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers University of Technology, Sweden.
    Defining the Human Adipose Tissue Proteome To Reveal Metabolic Alterations in Obesity2014In: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907, Vol. 13, no 11, p. 5106-5119Article in journal (Refereed)
    Abstract [en]

    White adipose tissue (WAT) has a major role in the progression of obesity. Here, we combined data from RNA-Seq and antibody-based immunohistochemistry to describe the normal physiology of human WAT obtained from three female subjects and explored WAT-specific genes by comparing WAT to 26 other major human tissues. Using the protein evidence in WAT, we validated the content of a genome-scale metabolic model for adipocytes. We employed this high-quality model for the analysis of subcutaneous adipose tissue (SAT) gene expression data obtained from subjects included in the Swedish Obese Subjects Sib Pair study to reveal molecular differences between lean and obese individuals. We integrated SAT gene expression and plasma metabolomics data, investigated the contribution of the metabolic differences in the mitochondria of SAT to the occurrence of obesity, and eventually identified cytosolic branched-chain amino acid (BCAA) transaminase 1 as a potential target that can be used for drug development. We observed decreased glutaminolysis and alterations in the BCAAs metabolism in SAT of obese subjects compared to lean subjects. We also provided mechanistic explanations for the changes in the plasma level of BCAAs, glutamate, pyruvate, and alpha-ketoglutarate in obese subjects. Finally, we validated a subset of our model-based predictions in 20 SAT samples obtained from 10 lean and 10 obese male and female subjects.

  • 28.
    Mardinoglu, Adil
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Editorial: The Impact of Systems Medicine on Human Health and Disease2016In: Frontiers in Physiology, ISSN 1664-042X, E-ISSN 1664-042X, Vol. 7, article id 552Article in journal (Other academic)
  • 29.
    Mardinoglu, Adil
    et al.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers University of Technology, Sweden.
    Shoaie, Saeed
    Bergentall, Mattias
    Ghaffari, Pouyan
    Zhang, Cheng
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Larsson, Erik
    Backhed, Fredrik
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers University of Technology, Sweden.
    The gut microbiota modulates host amino acid and glutathione metabolism in mice2015In: Molecular Systems Biology, ISSN 1744-4292, E-ISSN 1744-4292, Vol. 11, no 10, article id 834Article in journal (Refereed)
    Abstract [en]

    The gut microbiota has been proposed as an environmental factor that promotes the progression of metabolic diseases. Here, we investigated how the gut microbiota modulates the global metabolic differences in duodenum, jejunum, ileum, colon, liver, and two white adipose tissue depots obtained from conventionally raised (CONV-R) and germ-free (GF) mice using gene expression data and tissue-specific genome-scale metabolic models (GEMs). We created a generic mouse metabolic reaction (MMR) GEM, reconstructed 28 tissue-specific GEMs based on proteomics data, and manually curated GEMs for small intestine, colon, liver, and adipose tissues. We used these functional models to determine the global metabolic differences between CONV-R and GF mice. Based on gene expression data, we found that the gut microbiota affects the host amino acid (AA) metabolism, which leads to modifications in glutathione metabolism. To validate our predictions, we measured the level of AAs and N-acetylated AAs in the hepatic portal vein of CONV-R and GF mice. Finally, we simulated the metabolic differences between the small intestine of the CONV-R and GF mice accounting for the content of the diet and relative gene expression differences. Our analyses revealed that the gut microbiota influences host amino acid and glutathione metabolism in mice.

  • 30. Mardinoglu, Adil
    et al.
    Ågren, Rasmus
    Kampf, Caroline
    Asplund, Anna
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Genome-scale metabolic modelling of hepatocytes reveals serine deficiency in patients with non-alcoholic fatty liver disease2014In: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 5, p. 3083-Article in journal (Refereed)
    Abstract [en]

    Several liver disorders result from perturbations in the metabolism of hepatocytes, and their underlying mechanisms can be outlined through the use of genome-scale metabolic models (GEMs). Here we reconstruct a consensus GEM for hepatocytes, which we call iHepatocytes2322, that extends previous models by including an extensive description of lipid metabolism. We build iHepatocytes2322 using Human Metabolic Reaction 2.0 database and proteomics data in Human Protein Atlas, which experimentally validates the incorporated reactions. The reconstruction process enables improved annotation of the proteomics data using the network centric view of iHepatocytes2322. We then use iHepatocytes2322 to analyse transcriptomics data obtained from patients with non-alcoholic fatty liver disease. We show that blood concentrations of chondroitin and heparan sulphates are suitable for diagnosing non-alcoholic steatohepatitis and for the staging of non-alcoholic fatty liver disease. Furthermore, we observe serine deficiency in patients with NASH and identify PSPH, SHMT1 and BCAT1 as potential therapeutic targets for the treatment of non-alcoholic steatohepatitis.

  • 31.
    Nielsen, Jens
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Engineering yeast metabolism for production of fuels and chemicals2016In: New Biotechnology, ISSN 1871-6784, E-ISSN 1876-4347, Vol. 33, p. S66-S66Article in journal (Refereed)
  • 32.
    Nielsen, Jens
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Global regulation of yeast metabolism2015In: Yeast, ISSN 0749-503X, E-ISSN 1097-0061, Vol. 32, p. S33-S33Article in journal (Other academic)
    Abstract [en]

    The yeast Saccharomyces cerevisiae is widely used for production of fuels, chemicals, pharmaceuticals andmaterials. Through metabolic engineering of this yeast a number of novel new industrial processes have beendeveloped over the last 10 years. Besides its wide industrial use, S. cerevisiae serves as an eukaryal modelorganism, and many systems biology tools have therefore been developed for this organism. Despite ourextensive knowledge of yeast metabolism and its regulation we are still facing challenges when we want tointegrate this information into mathematical models. In this presentation examples of studies on global regulationof yeast metabolism will be provided. This will include analysis of how yeast rewire its metabolism at the globallevel when exposed to various types of stress and how global regulators like Snf1 and Sir2 controls yeastmetabolism

  • 33.
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology.
    Mathematical modeling of yeast: a driver for innovation in biotechnology and human medicine2015In: Yeast, ISSN 0749-503X, E-ISSN 1097-0061, Vol. 32, p. S50-S51Article in journal (Other academic)
    Abstract [en]

    Saccharomyces cerevisiae is the most studied organism and is for this reason used widely as a model organismfor studying molecular mechanisms of relevance for human disease. Thus, several Nobel Prizes have been givento yeast researchers. Among many other discoveries studies of yeast resulted in identification of cyclins andcyclin dependent kinases that play a central role in the cell cycle of eukaryal cells and mapping of the proteinsecretory pathway in eukaryal cells. This yeast is also used for production of fuels, chemicals, pharmaceuticalsand materials, and the annual revenue derived from processes based on S. cerevisiae fermentations by farexceeds 200 billion EURO. Furthermore. through metabolic engineering of this yeast a number of novel newindustrial processes are under development resulting in an even more important role of this cell factory in thefuture. In order to advance our fundamental understanding of this important organism, but in human healthresearch and industrial biotechnology, it is important to advance our ability to integrate novel experimental datain quantitative framework. Mathematical models represent an excellent scaffold for this as they allowreconciliation of data and at the same time enable generation of novel hypothesis concerning specific molecularprocesses. Furthermore, in the field of industrial biotechnology mathematical models may be used for advancingmetabolic engineering, which will result in a reduction in development costs and hereby advance towards biosustainable production of fuels and chemicals

  • 34.
    Nielsen, Jens
    KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers University of Technology, Sweden.
    Metabolism: Built on stable catalysts2017In: Nature Microbiology, E-ISSN 2058-5276, Vol. 2, no 7, article id 17085Article in journal (Refereed)
  • 35.
    Nielsen, Jens
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Systems Biology of Metabolism: A Driver for Developing Personalized and Precision Medicine2017In: Cell Metabolism, ISSN 1550-4131, E-ISSN 1932-7420, Vol. 25, no 3, p. 572-579Article, review/survey (Refereed)
    Abstract [en]

    Systems biology uses mathematical models to analyze large datasets and simulate system behavior. It enables integrative analysis of different types of data and can thereby provide new insight into complex biological systems. Here will be discussed the challenges of using systems medicine for advancing the development of personalized and precision medicine to treat metabolic diseases like insulin resistance, obesity, NAFLD, NASH, and cancer. It will be illustrated how the concept of genome-scale metabolic models can be used for integrative analysis of big data with the objective of identifying novel biomarkers that are foundational for personalized and precision medicine.

  • 36.
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology.
    Yeast as a platform cell factory in future biorefineries2013In: 4th International Conference on Biomolecular Engineering, ICBE 2013, 2013, p. 56-79Conference paper (Refereed)
  • 37.
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers, Dept Biol & Biol Engn, SE-41296 Gothenburg, Sweden.;Tech Univ Denmark, Novo Nordisk Fdn, Ctr Biosustainabil, DK-2970 Horsholm, Denmark.;Royal Inst Technol, Sci Life Lab, SE-17121 Stockholm, Sweden..
    Yeast cell factories on the horizon2015In: Science, ISSN 0036-8075, E-ISSN 1095-9203, Vol. 349, no 6252, p. 1050-1051Article in journal (Other academic)
  • 38.
    Nielsen, Jens
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers, Sweden.
    Archer, John
    Essack, Magbubah
    Bajic, Vladimir B.
    Gojobori, Takashi
    Mijakovic, Ivan
    Building a bio-based industry in the Middle East through harnessing the potential of the Red Sea biodiversity2017In: Applied Microbiology and Biotechnology, ISSN 0175-7598, E-ISSN 1432-0614, Vol. 101, no 12, p. 4837-4851Article, review/survey (Refereed)
    Abstract [en]

    The incentive for developing microbial cell factories for production of fuels and chemicals comes from the ability of microbes to deliver these valuable compounds at a reduced cost and with a smaller environmental impact compared to the analogous chemical synthesis. Another crucial advantage of microbes is their great biological diversity, which offers a much larger "catalog" of molecules than the one obtainable by chemical synthesis. Adaptation to different environments is one of the important drives behind microbial diversity. We argue that the Red Sea, which is a rather unique marine niche, represents a remarkable source of biodiversity that can be geared towards economical and sustainable bioproduction processes in the local area and can be competitive in the international bio-based economy. Recent bioprospecting studies, conducted by the King Abdullah University of Science and Technology, have established important leads on the Red Sea biological potential, with newly isolated strains of Bacilli and Cyanobacteria. We argue that these two groups of local organisms are currently most promising in terms of developing cell factories, due to their ability to operate in saline conditions, thus reducing the cost of desalination and sterilization. The ability of Cyanobacteria to perform photosynthesis can be fully exploited in this particular environment with one of the highest levels of irradiation on the planet. We highlight the importance of new experimental and in silico methodologies needed to overcome the hurdles of developing efficient cell factories from the Red Sea isolates.

  • 39.
    Nielsen, Jens
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Fussenegger, Martin
    Keasling, Jay
    Lee, Sang Yup
    Liao, James C.
    Prather, Kristala
    Palsson, Bernhard
    Engineering synergy in biotechnology2014In: Nature Chemical Biology, ISSN 1552-4450, E-ISSN 1552-4469, Vol. 10, no 5, p. 319-322Article in journal (Refereed)
  • 40.
    Nielsen, Jens
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Department of Biology and Biological Engineering, Chalmers University of Technology, Sweden.
    Keasling, Jay D.
    Engineering Cellular Metabolism2016In: Cell, ISSN 0092-8674, E-ISSN 1097-4172, Vol. 164, no 6, p. 1185-1197Article, review/survey (Refereed)
    Abstract [en]

    Metabolic engineering is the science of rewiring the metabolism of cells to enhance production of native metabolites or to endow cells with the ability to produce new products. The potential applications of such efforts are wide ranging, including the generation of fuels, chemicals, foods, feeds, and pharmaceuticals. However, making cells into efficient factories is challenging because cells have evolved robust metabolic networks with hard-wired, tightly regulated lines of communication between molecular pathways that resist efforts to divert resources. Here, we will review the current status and challenges of metabolic engineering and will discuss how new technologies can enable metabolic engineering to be scaled up to the industrial level, either by cutting off the lines of control for endogenous metabolism or by infiltrating the system with disruptive, heterologous pathways that overcome cellular regulation.

  • 41.
    Robinson, Jonathan L.
    et al.
    Chalmers Univ Technol, Dept Biol & Biol Engn, Kemivagen 10, Gothenburg, Sweden.;Chalmers Univ Technol, Wallenberg Ctr Prot Res, Kemivagen 10, Gothenburg, Sweden..
    Feizi, Amir
    Chalmers Univ Technol, Dept Biol & Biol Engn, Kemivagen 10, Gothenburg, Sweden.;Novo Nordisk Res Ctr Oxford, Old Campus Rd, Oxford, England..
    Uhlén, Mathias
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Nielsen, Jens
    KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers Univ Technol, Dept Biol & Biol Engn, Kemivagen 10, Gothenburg, Sweden ; Chalmers Univ Technol, Wallenberg Ctr Prot Res, Kemivagen 10, Gothenburg, Sweden ; Tech Univ Denmark, Novo Nordisk Fdn, Ctr Biosustainabil, DK-2800 Lyngby, Denmark.
    A Systematic Investigation of the Malignant Functions and Diagnostic Potential of the Cancer Secretome2019In: Cell reports, ISSN 2211-1247, E-ISSN 2211-1247, Vol. 26, no 10, p. 2622-+Article in journal (Refereed)
    Abstract [en]

    The collection of proteins secreted from a cell-the secretome-is of particular interest in cancer pathophysiology due to its diagnostic potential and role in tumorigenesis. However, cancer secretome studies are often limited to one tissue or cancer type or focus on biomarker prediction without exploring the associated functions. We therefore conducted a pan-cancer analysis of secretome gene expression changes to identify candidate diagnostic biomarkers and to investigate the underlying biological function of these changes. Using transcriptomic data spanning 32 cancer types and 30 healthy tissues, we quantified the relative diagnostic potential of secretome proteins for each cancer. Furthermore, we offer a potential mechanism by which cancer cells relieve secretory pathway stress by decreasing the expression of tissue-specific genes, thereby facilitating the secretion of proteins promoting invasion and proliferation. These results provide a more systematic understanding of the cancer secretome, facilitating its use in diagnostics and its targeting for therapeutic development.

  • 42. Robinson, Jonathan L.
    et al.
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Integrative analysis of human omics data using biomolecular networks2016In: Molecular Biosystems, ISSN 1742-206X, E-ISSN 1742-2051, Vol. 12, no 10, p. 2953-2964Article, review/survey (Refereed)
    Abstract [en]

    High-throughput '-omics' technologies have given rise to an increasing abundance of genome-scale data detailing human biology at the molecular level. Although these datasets have already made substantial contributions to a more comprehensive understanding of human physiology and diseases, their interpretation becomes increasingly cryptic and nontrivial as they continue to expand in size and complexity. Systems biology networks offer a scaffold upon which omics data can be integrated, facilitating the extraction of new and physiologically relevant information from the data. Two of the most prevalent networks that have been used for such integrative analyses of omics data are genome-scale metabolic models (GEMs) and protein-protein interaction (PPI) networks, both of which have demonstrated success among many different omics and sample types. This integrative approach seeks to unite 'top-down' omics data with 'bottom-up' biological networks in a synergistic fashion that draws on the strengths of both strategies. As the volume and resolution of high-throughput omics data continue to grow, integrative network-based analyses are expected to play an increasingly important role in their interpretation.

  • 43.
    Sjöström, Staffan
    et al.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Huang, Mingtao
    Nielsen, Jens
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Jönsson, Håkan
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Andersson Svahn, Helene
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Micro-droplet based directed evolution outperforms conventional laboratory evolution2014In: 18th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2014, Chemical and Biological Microsystems Society , 2014, p. 169-171Conference paper (Refereed)
    Abstract [en]

    We present droplet adaptive laboratory evolution (DrALE), a directed evolution method used to improve industrial enzyme producing microorganisms for e.g. feedstock digestion. DrALE is based linking a desired phenotype to growth rate allowing only desired cells to proliferate. Single cells are confined in microfluidic droplets to prevent the phenotype, e.g. secreted enzymes, from leaking between cells. The method was benchmarked against and found to significantly outperform conventional adaptive laboratory evolution (ALE) in enriching enzyme producing cells. It was furthermore applied to enrich a whole-genome mutated library of yeast cells for α-amylase activity.

  • 44.
    Sjöström, Staffan L.
    et al.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Bai, Yunpeng
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Huang, Mingtao
    Liu, Zihe
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Jönsson, Håkan N.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Andersson Svahn, Helene
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    High-throughput screening for industrial enzyme production hosts by droplet microfluidics2014In: Lab on a Chip, ISSN 1473-0197, E-ISSN 1473-0189, Vol. 14, no 4, p. 806-813Article in journal (Refereed)
    Abstract [en]

    A high-throughput method for single cell screening by microfluidic droplet sorting is applied to a whole-genome mutated yeast cell library yielding improved production hosts of secreted industrial enzymes. The sorting method is validated by enriching a yeast strain 14 times based on its a-amylase production, close to the theoretical maximum enrichment. Furthermore, a 105 member yeast cell library is screened yielding a clone with a more than 2-fold increase in a-amylase production. The increase in enzyme production results from an improvement of the cellular functions of the production host in contrast to previous droplet-based directed evolution that has focused on improving enzyme protein structure. In the workflow presented, enzyme producing single cells are encapsulated in 20 pL droplets with a fluorogenic reporter substrate. The coupling of a desired phenotype (secreted enzyme concentration) with the genotype (contained in the cell) inside a droplet enables selection of single cells with improved enzyme production capacity by droplet sorting. The platform has a throughput over 300 times higher than that of the current industry standard, an automated microtiter plate screening system. At the same time, reagent consumption for a screening experiment is decreased a million fold, greatly reducing the costs of evolutionary engineering of production strains.

  • 45. Sweetlove, Lee J.
    et al.
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Fernie, Alisdair R.
    Engineering central metabolism - a grand challenge for plant biologists2017In: The Plant Journal, ISSN 0960-7412, E-ISSN 1365-313X, Vol. 90, no 4, p. 749-763Article in journal (Refereed)
    Abstract [en]

    The goal of increasing crop productivity and nutrient-use efficiency is being addressed by a number of ambitious research projects seeking to re-engineer photosynthetic biochemistry. Many of these projects will require the engineering of substantial changes in fluxes of central metabolism. However, as has been amply demonstrated in simpler systems such as microbes, central metabolism is extremely difficult to rationally engineer. This is because of multiple layers of regulation that operate to maintain metabolic steady state and because of the highly connected nature of central metabolism. In this review we discuss new approaches for metabolic engineering that have the potential to address these problems and dramatically improve the success with which we can rationally engineer central metabolism in plants. In particular, we advocate the adoption of an iterative 'design-build-test-learn' cycle using fast-to-transform model plants as test beds. This approach can be realised by coupling new molecular tools to incorporate multiple transgenes in nuclear and plastid genomes with computational modelling to design the engineering strategy and to understand the metabolic phenotype of the engineered organism. We also envisage that mutagenesis could be used to fine-tune the balance between the endogenous metabolic network and the introduced enzymes. Finally, we emphasise the importance of considering the plant as a whole system and not isolated organs: the greatest increase in crop productivity will be achieved if both source and sink metabolism are engineered.

  • 46.
    Uhlén, Mathias
    et al.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Technical University of Denmark, Denmark.
    Hallström, Björn M.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lindskog, Cecilia
    Mardinoglu, Adil
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers University of Technology, Sweden.
    Pontén, Fredrik
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Technical University of Denmark, Denmark; Chalmers University of Technology, Sweden.
    Transcriptomics resources of human tissues and organs2016In: Molecular Systems Biology, ISSN 1744-4292, E-ISSN 1744-4292, Vol. 12, no 4, article id 862Article, review/survey (Refereed)
    Abstract [en]

    Quantifying the differential expression of genes in various human organs, tissues, and cell types is vital to understand human physiology and disease. Recently, several large-scale transcriptomics studies have analyzed the expression of protein-coding genes across tissues. These datasets provide a framework for defining the molecular constituents of the human body as well as for generating comprehensive lists of proteins expressed across tissues or in a tissue-restricted manner. Here, we review publicly available human transcriptome resources and discuss body-wide data from independent genome-wide transcriptome analyses of different tissues. Gene expression measurements from these independent datasets, generated using samples from fresh frozen surgical specimens and postmortem tissues, are consistent. Overall, the different genome-wide analyses support a distribution in which many proteins are found in all tissues and relatively few in a tissue-restricted manner. Moreover, we discuss the applications of publicly available omics data for building genome-scale metabolic models, used for analyzing cell and tissue functions both in physiological and in disease contexts.

  • 47. Varemo, Leif
    et al.
    Henriksen, Tora Ida
    Scheele, Camilla
    Broholm, Christa
    Pedersen, Maria
    Uhlen, Mathias
    Pedersen, Bente Klarlund
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Type 2 diabetes and obesity induce similar transcriptional reprogramming in human myocytes2017In: Genome Medicine, ISSN 1756-994X, E-ISSN 1756-994X, Vol. 9, article id 47Article in journal (Refereed)
    Abstract [en]

    Background: Skeletal muscle is one of the primary tissues involved in the development of type 2 diabetes (T2D). The close association between obesity and T2D makes it difficult to isolate specific effects attributed to the disease alone. Therefore, here we set out to identify and characterize intrinsic properties of myocytes, associated independently with T2D or obesity. Methods: We generated and analyzed RNA-seq data from primary differentiated myotubes from 24 human subjects, using a factorial design (healthy/T2D and non-obese/obese), to determine the influence of each specific factor on genome-wide transcription. This setup enabled us to identify intrinsic properties, originating from muscle precursor cells and retained in the corresponding myocytes. Bioinformatic and statistical methods, including differential expression analysis, gene-set analysis, and metabolic network analysis, were used to characterize the different myocytes. Results: We found that the transcriptional program associated with obesity alone was strikingly similar to that induced specifically by T2D. We identified a candidate epigenetic mechanism, H3K27me3 histone methylation, mediating these transcriptional signatures. T2D and obesity were independently associated with dysregulated myogenesis, down-regulated muscle function, and up-regulation of inflammation and extracellular matrix components. Metabolic network analysis identified that in T2D but not obesity a specific metabolite subnetwork involved in sphingolipid metabolism was transcriptionally regulated. Conclusions: Our findings identify inherent characteristics in myocytes, as a memory of the in vivo phenotype, without the influence from a diabetic or obese extracellular environment, highlighting their importance in the development of T2D.

  • 48. Väremo, Leif
    et al.
    Scheele, Camilla
    Broholm, Christa
    Mardinoglu, Adil
    Kampf, Caroline
    Asplund, Anna
    Nookaew, Intawat
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Pedersen, Bente Klarlund
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. Chalmers University of Technology, Sweden.
    Proteome- and Transcriptome-Driven Reconstruction of the Human Myocyte Metabolic Network and Its Use for Identification of Markers for Diabetes2015In: Cell reports, ISSN 2211-1247, E-ISSN 2211-1247, Vol. 11, no 6, p. 921-933Article in journal (Refereed)
    Abstract [en]

    Skeletal myocytes are metabolically active and susceptible to insulin resistance and are thus implicated in type 2 diabetes (T2D). This complex disease involves systemic metabolic changes, and their elucidation at the systems level requires genome-wide data and biological networks. Genome-scale metabolic models (GEMs) provide a network context for the integration of high-throughput data. We generated myocyte-specific RNA-sequencing data and investigated their correlation with proteome data. These data were then used to reconstruct a comprehensive myocyte GEM. Next, we performed a meta-analysis of six studies comparing muscle transcription in T2D versus healthy subjects. Transcriptional changes were mapped on the myocyte GEM, revealing extensive transcriptional regulation in T2D, particularly around pyruvate oxidation, branched-chain amino acid catabolism, and tetrahydrofolate metabolism, connected through the downregulated dihydrolipoamide dehydrogenase. Strikingly, the gene signature underlying this metabolic regulation successfully classifies the disease state of individual samples, suggesting that regulation of these pathways is a ubiquitous feature of myocytes in response to T2D.

  • 49. Yu, Tao
    et al.
    Zhou, Yongjin J.
    Wenning, Leonie
    Liu, Quanli
    Krivoruchko, Anastasia
    Siewers, Verena
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers University of Technology, Sweden.
    David, Florian
    Metabolic engineering of Saccharomyces cerevisiae for production of very long chain fatty acid-derived chemicals2017In: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 8, article id 15587Article in journal (Refereed)
    Abstract [en]

    Production of chemicals and biofuels through microbial fermentation is an economical and sustainable alternative for traditional chemical synthesis. Here we present the construction of a Saccharomyces cerevisiae platform strain for high-level production of very-long-chain fatty acid (VLCFA)-derived chemicals. Through rewiring the native fatty acid elongation system and implementing a heterologous Mycobacteria FAS I system, we establish an increased biosynthesis of VLCFAs in S. cerevisiae. VLCFAs can be selectively modified towards the fatty alcohol docosanol (C22H46O) by expressing a specific fatty acid reductase. Expression of this enzyme is shown to impair cell growth due to consumption of VLCFA-CoAs. We therefore implement a dynamic control strategy for separating cell growth from docosanol production. We successfully establish high-level and selective docosanol production of 83.5 mg l(-1) in yeast. This approach will provide a universal strategy towards the production of similar high value chemicals in a more scalable, stable and sustainable manner.

  • 50. Zhou, Yongjin J.
    et al.
    Buijs, Nicolaas A.
    Zhu, Zhiwei
    Qin, Jiufu
    Siewers, Verena
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology.
    Production of fatty acid-derived oleochemicals and biofuels by synthetic yeast cell factories2016In: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 7, article id 11709Article in journal (Refereed)
    Abstract [en]

    Sustainable production of oleochemicals requires establishment of cell factory platform strains. The yeast Saccharomyces cerevisiae is an attractive cell factory as new strains can be rapidly implemented into existing infrastructures such as bioethanol production plants. Here we show high-level production of free fatty acids (FFAs) in a yeast cell factory, and the production of alkanes and fatty alcohols from its descendants. The engineered strain produces up to 10.4 gl(-1) of FFAs, which is the highest reported titre to date. Furthermore, through screening of specific pathway enzymes, endogenous alcohol dehydrogenases and aldehyde reductases, we reconstruct efficient pathways for conversion of fatty acids to alkanes (0.8 mgl(-1)) and fatty alcohols (1.5 gl(-1)), to our knowledge the highest titres reported in S. cerevisiae. This should facilitate the construction of yeast cell factories for production of fatty acids derived products and even aldehyde-derived chemicals of high value.

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