| 1. |
- 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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| 2. |
- 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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| 3. |
- 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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| 4. |
- 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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| 5. |
- 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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| 6. |
- 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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| 7. |
- 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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| 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
(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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| 10. |
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| 11. |
- Fletcher, Eugene, 1986, et al.
(författare)
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Evolutionary engineering reveals divergent paths when yeast is adapted to different acidic environments
- 2017
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Ingår i: Metabolic engineering. - : Academic Press. - 1096-7176 .- 1096-7184. ; 39, s. 19-28
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 12. |
- Fletcher, Eugene, 1986, et al.
(författare)
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RNA-seq analysis of Pichia anomala reveals important mechanisms required for survival at low pH
- 2015
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Ingår i: Microbial Cell Factories. - : Springer Science and Business Media LLC. - 1475-2859. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: The product yield and titers of biological processes involving the conversion of biomass to desirable chemicals can be limited by environmental stresses encountered by the microbial hosts used for the bioconversion. One of these main stresses is growth inhibition due to exposure to low pH conditions. In order to circumvent this problem, understanding the biological mechanisms involved in acid stress response and tolerance is essential. Characterisation of wild yeasts that have a natural ability to resist such harsh conditions will pave the way to understand the biological basis underlying acid stress resistance. Pichia anomala possesses a unique ability to adapt to and tolerate a number of environmental stresses particularly low pH stress giving it the advantage to outcompete other microorganisms under such conditions. However, the genetic basis of this resistance has not been previously studied. Results: To this end, we isolated an acid resistant strain of P. anomala, performed a gross phenotypic characterisation at low pH and also performed a whole genome and total RNA sequencing. By integrating the RNA-seq data with the genome sequencing data, we found that several genes associated with different biological processes including proton efflux, the electron transfer chain and oxidative phosphorylation were highly expressed in P. anomala cells grown in low pH media. We therefore present data supporting the notion that a high expression of proton pumps in the plasma membrane coupled with an increase in mitochondrial ATP production enables the high level of acid stress tolerance of P. anomala. Conclusions: Our findings provide insight into the molecular and genetic basis of low pH tolerance in P. anomala which was previously unknown. Ultimately, this is a step towards developing non-conventional yeasts such as P. anomala for the production of industrially relevant chemicals under low pH conditions.
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| 13. |
- Gutierrez, Jahir M., et al.
(författare)
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Genome-scale reconstructions of the mammalian secretory pathway predict metabolic costs and limitations of protein secretion
- 2020
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723 .- 2041-1723. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- In mammalian cells, >25% of synthesized proteins are exported through the secretory pathway. The pathway complexity, however, obfuscates its impact on the secretion of different proteins. Unraveling its impact on diverse proteins is particularly important for biopharmaceutical production. Here we delineate the core secretory pathway functions and integrate them with genome-scale metabolic reconstructions of human, mouse, and Chinese hamster ovary cells. The resulting reconstructions enable the computation of energetic costs and machinery demands of each secreted protein. By integrating additional omics data, we find that highly secretory cells have adapted to reduce expression and secretion of other expensive host cell proteins. Furthermore, we predict metabolic costs and maximum productivities of biotherapeutic proteins and identify protein features that most significantly impact protein secretion. Finally, the model successfully predicts the increase in secretion of a monoclonal antibody after silencing a highly expressed selection marker. This work represents a knowledgebase of the mammalian secretory pathway that serves as a novel tool for systems biotechnology.
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| 14. |
- Li, Feiran, 1993, et al.
(författare)
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Improving recombinant protein production by yeast through genome-scale modeling using proteome constraints
- 2022
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723 .- 2041-1723. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- Eukaryotic cells are used as cell factories to produce and secrete multitudes of recombinant pharmaceutical proteins, including several of the current top-selling drugs. Due to the essential role and complexity of the secretory pathway, improvement for recombinant protein production through metabolic engineering has traditionally been relatively ad-hoc; and a more systematic approach is required to generate novel design principles. Here, we present the proteome-constrained genome-scale protein secretory model of yeast Saccharomyces cerevisiae (pcSecYeast), which enables us to simulate and explain phenotypes caused by limited secretory capacity. We further apply the pcSecYeast model to predict overexpression targets for the production of several recombinant proteins. We experimentally validate many of the predicted targets for alpha-amylase production to demonstrate pcSecYeast application as a computational tool in guiding yeast engineering and improving recombinant protein production. Due to the complexity of the protein secretory pathway, strategy suitable for the production of a certain recombination protein cannot be generalized. Here, the authors construct a proteome-constrained genome-scale protein secretory model for yeast and show its application in the production of different misfolded or recombinant proteins.
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| 15. |
- Liu, Lifang, 1979, et al.
(författare)
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Genome-scale analysis of the high-efficient protein secretion system of Aspergillus oryzae
- 2014
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Ingår i: BMC Systems Biology. - : Springer Science and Business Media LLC. - 1752-0509. ; 8:73
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Tidskriftsartikel (refereegranskat)abstract
- Background: The koji mold, Aspergillus oryzae is widely used for the production of industrial enzymes due to its particularly high protein secretion capacity and ability to perform post-translational modifications. However, systemic analysis of its secretion system is lacking, generally due to the poorly annotated proteome. Results: Here we defined a functional protein secretory component list of A. oryzae using a previously reported secretory model of S. cerevisiae as scaffold. Additional secretory components were obtained by blast search with the functional components reported in other closely related fungal species such as Aspergillus nidulans and Aspergillus niger. To evaluate the defined component list, we performed transcriptome analysis on three a-amylase over-producing strains with varying levels of secretion capacities. Specifically, secretory components involved in the ER-associated processes (including components involved in the regulation of transport between ER and Golgi) were significantly up-regulated, with many of them never been identified for A. oryzae before. Furthermore, we defined a complete list of the putative A. oryzae secretome and monitored how it was affected by overproducing amylase. Conclusion: In combination with the transcriptome data, the most complete secretory component list and the putative secretome, we improved the systemic understanding of the secretory machinery of A. oryzae in response to high levels of protein secretion. The roles of many newly predicted secretory components were experimentally validated and the enriched component list provides a better platform for driving more mechanistic studies of the protein secretory pathway in this industrially important fungus.
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| 16. |
- Manshaei, R., et al.
(författare)
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Hybrid-Controlled Neurofuzzy Networks Analysis Resulting in Genetic Regulatory Networks Reconstruction
- 2012
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Ingår i: ISRN Bioinformatics. - : Hindawi Limited. - 2090-7346.
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Tidskriftsartikel (refereegranskat)abstract
- Reverse engineering of gene regulatory networks (GRNs) is the process of estimating genetic interactions of a cellular system from gene expression data. In this paper, we propose a novel hybrid systematic algorithm based on neurofuzzy network for reconstructing GRNs from observational gene expression data when only a medium-small number of measurements are available. The approach uses fuzzy logic to transform gene expression values into qualitative descriptors that can be evaluated by using a set of defined rules. The algorithm uses neurofuzzy network to model genes effects on other genes followed by four stages of decision making to extract gene interactions. One of the main features of the proposed algorithm is that an optimal number of fuzzy rules can be easily and rapidly extracted without overparameterizing. Data analysis and simulation are conducted on microarray expression profiles of S. cerevisiae cell cycle and demonstrate that the proposed algorithm not only selects the patterns of the time series gene expression data accurately, but also provides models with better reconstruction accuracy when compared with four published algorithms: DBNs, VBEM, time delay ARACNE, and PF subjected to LASSO. The accuracy of the proposed approach is evaluated in terms of recall and F-score for the network reconstruction task.
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| 17. |
- Robinson, Jonathan, 1986, et al.
(författare)
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A Systematic Investigation of the Malignant Functions and Diagnostic Potential of the Cancer Secretome
- 2019
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Ingår i: Cell Reports. - : Elsevier BV. - 2211-1247. ; 26:10, s. 2622-2635.e5
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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