| 1. |
- Feizi, Amir, 1980, et al.
(författare)
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HCSD: The human cancer secretome database
- 2015
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Ingår i: Database : the journal of biological databases and curation. - : Oxford University Press (OUP). - 1758-0463. ; 2015
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Tidskriftsartikel (refereegranskat)abstract
- The human cancer secretome database (HCSD) is a comprehensive database for human cancer secretome data. The cancer secretome describes proteins secreted by cancer cells and structuring information about the cancer secretome will enable further analysis of how this is related with tumor biology. The secreted proteins from cancer cells are believed to play a deterministic role in cancer progression and therefore may be the key to find novel therapeutic targets and biomarkers for many cancers. Consequently, huge data on cancer secretome have been generated in recent years and the lack of a coherent database is limiting the ability to query the increasing community knowledge. We therefore developed the Human Cancer Secretome Database (HCSD) to fulfil this gap. HCSD contains >80 000 measurements for about 7000 nonredundant human proteins collected from up to 35 high-throughput studies on 17 cancer types. It has a simple and user friendly query system for basic and advanced search based on gene name, cancer type and data type as the three main query options. The results are visualized in an explicit and interactive manner. An example of a result page includes annotations, cross references, cancer secretome data and secretory features for each identified protein.
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| 2. |
- Feizi, Neda, et al.
(författare)
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Autophagy induction regulates influenza virus replication in a time-dependent manner
- 2017
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Ingår i: Journal of Medical Microbiology. - : Microbiology Society. - 0022-2615 .- 1473-5644. ; 66:4, s. 536-541
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Tidskriftsartikel (refereegranskat)abstract
- Purpose. Autophagy plays a key role in host defence responses against microbial infections by promoting degradation of pathogens and participating in acquired immunity. The interaction between autophagy and viruses is complex, and this pathway is hijacked by several viruses. Influenza virus (IV) interferes with autophagy through its replication and increases the accumulation of autophagosomes by blocking lysosome fusion. Thus, autophagy could be an effective area for antiviral research. Methodology. In this study, we evaluated the effect of autophagy on IV replication. Two cell lines were transfected with Beclin-1 expression plasmid before (prophylactic approach) and after (therapeutic approach) IV inoculation. Results/Key findings. Beclin-1 overexpression in the cells infected by virus induced autophagy to 26 %. The log10 haemagglutinin titre and TCID50 (tissue culture infective dose giving 50% infection) of replicating virus were measured at 24 and 48 h post-infection. In the prophylactic approach, the virus titre was enhanced significantly at 24 h post-infection (P?0.01), but it was not significantly different from the control at 48 h post-infection. In contrast, the therapeutic approach of autophagy induction inhibited the virus replication at 24 and 48 h post-infection. Additionally, we showed that inhibition of autophagy using 3-methyladenine reduced viral replication. Conclusion. This study revealed that the virus (H1N1) titre was controlled in a time-dependent manner following autophagy induction in host cells. Manipulation of autophagy during the IV life cycle can be targeted both for antiviral aims and for increasing viral yield for virus production.
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| 3. |
- Bengtsson-Palme, Johan, 1985, et al.
(författare)
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Strategies to improve usability and preserve accuracy in biological sequence databases
- 2016
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Ingår i: Proteomics. - : Wiley. - 1615-9853 .- 1615-9861. ; 16:18, s. 2454-2460
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Tidskriftsartikel (refereegranskat)abstract
- Biology is increasingly dependent on large-scale analysis, such as proteomics, creating a requirement for efficient bioinformatics. Bioinformatic predictions of biological functions rely upon correctly annotated database sequences, and the presence of inaccurately annotated or otherwise poorly described sequences introduces noise and bias to biological analyses. Accurate annotations are, for example, pivotal for correct identifications of polypeptide fragments. However, standards for how sequence databases are organized and presented are currently insufficient. Here, we propose five strategies to address fundamental issues in the annotation of sequence databases: (i) to clearly separate experimentally verified and unverified sequence entries; (ii) to enable a system for tracing the origins of annotations; (iii) to separate entries with high-quality, informative annotation from less useful ones; (iv) to integrate automated quality-control software whenever such tools exist; and (v) to facilitate post-submission editing of annotations and metadata associated with sequences. We believe that implementation of these strategies, for example as requirements for publication of database papers, would enable biology to better take advantage of large-scale data.
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| 4. |
- Blockhuys, Stephanie, 1983, et al.
(författare)
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Defining the human copper proteome and analysis of its expression variation in cancers.
- 2017
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Ingår i: Metallomics. - : Oxford University Press (OUP). - 1756-5901 .- 1756-591X. ; 9:2, s. 112-123
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Tidskriftsartikel (refereegranskat)abstract
- Copper (Cu) is essential for living organisms, and acts as a cofactor in many metabolic enzymes. To avoid the toxicity of free Cu, organisms have specific transport systems that 'chaperone' the metal to targets. Cancer progression is associated with increased cellular Cu concentrations, whereby proliferative immortality, angiogenesis and metastasis are cancer hallmarks with defined requirements for Cu. The aim of this study is to gather all known Cu-binding proteins and reveal their putative involvement in cancers using the available database resources of RNA transcript levels. Using the database along with manual curation, we identified a total of 54 Cu-binding proteins (named the human Cu proteome). Next, we retrieved RNA expression levels in cancer versus normal tissues from the TCGA database for the human Cu proteome in 18 cancer types, and noted an intricate pattern of up- and downregulation of the genes in different cancers. Hierarchical clustering in combination with bioinformatics and functional genomics analyses allowed for the prediction of cancer-related Cu-binding proteins; these were specifically inspected for the breast cancer data. Finally, for the Cu chaperone ATOX1, which is the only Cu-binding protein proposed to have transcription factor activities, we validated its predicted over-expression in patient breast cancer tissue at the protein level. This collection of Cu-binding proteins, with RNA expression patterns in different cancers, will serve as an excellent resource for mechanistic-molecular studies of Cu-dependent processes in cancer.
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| 5. |
- Caspeta-Guadarrama, Luis, 1974, et al.
(författare)
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Altered sterol composition renders yeast thermotolerant
- 2014
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 346:6205, s. 75-78
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Tidskriftsartikel (refereegranskat)abstract
- Ethanol production for use as a biofuel is mainly achieved through simultaneous saccharification and fermentation by yeast. Operating at >= 40 degrees C would be beneficial in terms of increasing efficiency of the process and reducing costs, but yeast does not grow efficiently at those temperatures. We used adaptive laboratory evolution to select yeast strains with improved growth and ethanol production at >= 40 degrees C. Sequencing of the whole genome, genome-wide gene expression, and metabolic-flux analyses revealed a change in sterol composition, from ergosterol to fecosterol, caused by mutations in the C-5 sterol desaturase gene, and increased expression of genes involved in sterol biosynthesis. Additionally, large chromosome III rearrangements and mutations in genes associated with DNA damage and respiration were found, but contributed less to the thermotolerant phenotype.
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| 6. |
- de Jong, Jasper M. A., et al.
(författare)
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Human brown adipose tissue is phenocopied by classical brown adipose tissue in physiologically humanized mice
- 2019
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Ingår i: Nature Metabolism. - : Springer Science and Business Media LLC. - 2522-5812. ; 1:8, s. 830-843
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Tidskriftsartikel (refereegranskat)abstract
- Human and rodent brown adipose tissues (BAT) appear morphologically and molecularly different. Here we compare human BAT with both classical brown and brite/beige adipose tissues of 'physiologically humanized' mice: middle-aged mice living under conditions approaching human thermal and nutritional conditions, that is, prolonged exposure to thermoneutral temperature (approximately 30 degrees C) and to an energy-rich (high-fat, high-sugar) diet. We find that the morphological, cellular and molecular characteristics (both marker and adipose-selective gene expression) of classical brown fat, but not of brite/beige fat, of these physiologically humanized mice are notably similar to human BAT. We also demonstrate, both in silico and experimentally, that in physiologically humanized mice only classical BAT possesses a high thermogenic potential. These observations suggest that classical rodent BAT is the tissue of choice for translational studies aimed at recruiting human BAT to counteract the development of obesity and its comorbidities.
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| 7. |
- Feizi, Amir, 1980, et al.
(författare)
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Genome-Scale Modeling of the Protein Secretory Machinery in Yeast
- 2013
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203 .- 1932-6203. ; 8:5
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Tidskriftsartikel (refereegranskat)abstract
- The protein secretory machinery in Eukarya is involved in post-translational modification (PTMs) and sorting of the secretory and many transmembrane proteins. While the secretory machinery has been well-studied using classic reductionist approaches, a holistic view of its complex nature is lacking. Here, we present the first genome-scale model for the yeast secretory machinery which captures the knowledge generated through more than 50 years of research. The model is based on the concept of a Protein Specific Information Matrix (PSIM: characterized by seven PTMs features). An algorithm was developed which mimics secretory machinery and assigns each secretory protein to a particular secretory class that determines the set of PTMs and transport steps specific to each protein. Protein abundances were integrated with the model in order to gain system level estimation of the metabolic demands associated with the processing of each specific protein as well as a quantitative estimation of the activity of each component of the secretory machinery.
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| 8. |
- Feizi, Amir, 1980, et al.
(författare)
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Human protein secretory pathway genes are expressed in a tissue-specific pattern to match processing demands of the secretome
- 2017
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Ingår i: npj Systems Biology and Applications. - : Springer Science and Business Media LLC. - 2056-7189. ; 3:1
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Tidskriftsartikel (refereegranskat)abstract
- Protein secretory pathway in eukaryal cells is responsible for delivering functional secretory proteins. The dysfunction of this pathway causes a range of important human diseases from congenital disorders to cancer. Despite the piled-up knowledge on the molecular biology and biochemistry level, the tissue-specific expression of the secretory pathway genes has not been analyzed on the transcriptome level. Based on the recent RNA-sequencing studies, the largest fraction of tissue-specific transcriptome encodes for the secretome (secretory proteins). Here, the question arises that if the expression levels of the secretory pathway genes have a tissue-specific tuning. In this study, we tackled this question by performing a meta-analysis of the recently published transcriptome data on human tissues. As a result, we detected 68 as called “extreme genes” which show an unusual expression pattern in specific gene families of the secretory pathway. We also inspected the potential functional link between detected extreme genes and the corresponding tissues enriched secretome. As a result, the detected extreme genes showed correlation with the enrichment of the nature and number of specific post-translational modifications in each tissue’s secretome. Our findings conciliate both the housekeeping and tissue-specific nature of the protein secretory pathway, which we attribute to a fine-tuned regulation of defined gene families to support the diversity of secreted proteins and their modifications.
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| 9. |
- Feizi, Amir, 1980, et al.
(författare)
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Metabolic and protein interaction sub-networks controlling the proliferation rate of cancer cells and their impact on patient survival
- 2013
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322 .- 2045-2322. ; 3
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Tidskriftsartikel (refereegranskat)abstract
- Cancer cells can have a broad scope of proliferation rates. Here we aim to identify the molecular mechanisms that allow some cancer cell lines to grow up to 4 times faster than other cell lines. The correlation of gene expression profiles with the growth rate in 60 different cell lines has been analyzed using several genome- scale biological networks and new algorithms. New possible regulatory feedback loops have been suggested and the known roles of several cell cycle related transcription factors have been confirmed. Over 100 growth- correlated metabolic sub-networks have been identified, suggesting a key role of simultaneous lipid synthesis and degradation in the energy supply of the cancer cells growth. Many metabolic sub-networks involved in cell line proliferation appeared also to correlate negatively with the survival expectancy of colon cancer patients.
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| 10. |
- Feizi, Amir, 1980
(författare)
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Systems Analysis of the Protein Secretory Pathway in Yeast and Human Cells
- 2015
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The cell was discovered by Robert Hooke in 1665, later in nineteen century the cell theory was developed as all organisms are composed of one or more cells. Since then, many tools and experimental methods have been developed to dissect and characterize the cell components which resulted in established solid scientific fields such as biochemistry, molecular cell biology and genetics. These fields provided us with accumulated reductionist knowledge of components and processes in different cells originated from organisms belonging to various kingdoms of life, as simple as prokaryotes to the higher eukaryals. By the advent of biotechnology these knowledge is used to change many aspect of our life. One of the most important cell processes that has been core to this revolution is secretory pathway which is responsible to put proteins in the cell surface or extracellular space. These protein which are called secretory proteins, encompass diverse range of proteins in each cell with critical roles in digestion, cell-cell communication, signaling, physiology, connectivity etc. Recombinant gene expression was the fruit of the revolution in molecular biology techniques such as PCR in 1970s and using of host cells secretory capacity. A decade after, expressing a heterologous (foreign) proteins in host cells have revolutionized healthcare, agricultural, fuel, food and waste industries. These cells include a wide range from bacteria, fungi, to insect cells and mammalian cells. Nowadays, there are hundreds of biopharmaceutical proteins in the market with many more under clinical trials. Sequencing of complete genomes and the availability of genome-scale reagents has changed the experimental strategies for determining gene function. Besides genome sequencing other high-throughput methods have been developed to measure transcription, translation and metabolites and therefore we are now facing a lot of data on different cellular processes that are collectively referred to as omics data. Analyzing this kind of data is inevitable demanding the use of computers integrated with statistical and mathematical algorithms. However, this is only the starting point, as all these entities in reality work together in a complex networks of interaction resulting in important biological systems which is called emergent properties. Analyzing omics data without integrating them in the context of network give us very little and unrealistic view of the cell. Here systems biology, which studies biological processes as complex systems in the context of their interaction, comes to play. Based on reductionist knowledge we have been somewhat successful in using secretory machinery to produce many different proteins. Also we know a lot how the malfunction of this pathway can results in serious diseases. As we are now able to measure the activity of secretory pathway as a whole system and connecting it with the activity of rest of the cell, we may be able to use systems biology to elevate our understanding of the protein secretory pathway to the systemic level which is todays bottle neck in both protein production and human diseases related to this pathway.
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