Exploring Sequence Characteristics Related to High-Level Production of Secreted Proteins in Aspergillus niger

PLoS ONE

Volumn 7, Issue 10, 2012, Pages

  van den Berg, Bastiaan A ^a,b,d   Reinders, Marcel J T ^a,b,d   Hulsman, Marc ^a,b,d   Wu, Liang ^c   Pel, Herman J ^c   Roubos, Johannes A ^c   de Ridder, Dick ^a,b,d  

^a Delft University of Technology ^*  (Netherlands)

^b NETHERLANDS BIOINFORMATICS CENTRE   (Netherlands)

^c DSM BIOTECHNOLOGY CENTER   (Netherlands)

^d KLUYVER CENTRE FOR GENOMICS OF INDUSTRIAL FERMENTATION   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

ASPARAGINE; FUNGAL DNA; FUNGAL PROTEIN; LYSINE; METHIONINE; TYROSINE;

AMINO ACID SEQUENCE; ARTICLE; ASPERGILLUS NIGER; BIOPROCESS; CLASSIFICATION; CLASSIFIER; ENZYME SYNTHESIS; FUNGAL GENE; FUNGAL STRAIN; GENE OVEREXPRESSION; MACHINE LEARNING; MOLECULAR BIOLOGY; NONHUMAN; POLYACRYLAMIDE GEL ELECTROPHORESIS; PREDICTION; PROTEIN ENGINEERING; PROTEIN SECRETION; SUPPORT VECTOR MACHINE;

AMINO ACID SEQUENCE; ARTIFICIAL INTELLIGENCE; ASPERGILLUS NIGER; COMPUTATIONAL BIOLOGY; ELECTROPHORESIS, POLYACRYLAMIDE GEL; ENZYMES; FUNGAL PROTEINS; GENE EXPRESSION PROFILING; GENES, FUNGAL; GENETIC ENGINEERING; INDUSTRIAL MICROBIOLOGY; MOLECULAR SEQUENCE DATA;

ASPERGILLUS NIGER; FUNGI;

EID: 84866972942     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0045869     Document Type: Article

References (58)

1. Lubertozzi D, Keasling JD, (2009) Developing Aspergillus as a host for heterologous expression. Biotechnology Advances 27: 53-75.
2. Pel HJ, de Winde JH, Archer DB, Dyer PS, Hofmann G, et al. (2007) Genome sequencing and analysis of the versatile cell factory Aspergillus niger CBS 513.88. Nature Biotechnology 25: 221-231.
3. Andersen MR, Salazar MP, Schaap PJ, van de Vondervoort PJI, Culley D, et al. (2011) Comparative genomics of citric-acid-producing Aspergillus niger ATCC 1015 versus enzyme-producing CBS 513.88. Genome Research 21: 885-897.
4. Punt PJ, van Biezen N, Conesa A, Albers A, Mangnus J, et al. (2002) Filamentous fungi as cell factories for heterologous protein production. Trends in Biotechnology 20: 200-206.
5. Nevalainen KM, Te'o VS, Bergquist PL, (2005) Heterologous protein expression in filamentous fungi. Trends in Biotechnology 23: 468-474.
6. Fleißner A, Dersch P, (2010) Expression and export: recombinant protein production systems for Aspergillus. Applied Microbiology and Biotechnology 87: 1255-1270.
7. Gouka RJ, Punt PJ, van den Hondel CAMMJ, (1997) Efficient production of secreted proteins by aspergillus: progress, limitations and prospects. Applied Microbiology and Biotechnology 47: 1-11.
8. Conesa A, Punt PJ, van Luijk N, van den Hondel CAMJJ, (2001) The secretion pathway in filamentous fungi: a biotechnological view. Fungal Genetics and Biology 33: 155-171.
9. Archer DB, Peberdy JF, (1997) The molecular biology of secreted enzyme production by fungi. Critical Reviews in Biotechnology 17: 273-306.
10. Carvalho NDSP, Arentshorst M, Kooistra R, Stam H, Sagt CM, et al. (2011) Effects of a defective ERAD pathway on growth and heterologous protein production in Aspergillus niger. Applied Microbiology and Biotechnology 89: 357-373.
11. Jacobs DI, Olsthoorn MA, Maillet I, Akeroyd M, Breestraat S, et al. (2009) Effective lead selection for improved protein production in Aspergillus niger based on integrated genomics. Fungal Genetics and Biology 46: S141- S152.
12. Guillemette T, van Peij NNME, Goosen T, Lanthaler K, Robson GD, et al. (2007) Genomic analysis of the secretion stress response in the enzyme-producing cell factory Aspergillus niger. BMC Genomics 8: 158.
13. Plotkin JB, Kudla G, (2010) Synonymous but not the same: the causes and consequences of codon bias. Nature Reviews Genetics 12: 32-42.
14. Horton P, Park KJ, Obayashi T, Nakai K (2006) Protein subcellular localization prediction with WoLF PSORT. In: Proceedings of the 4th annual Asia Pacific bioinformatics conference APBC06, Taipei, Taiwan. Citeseer, volume 39, p.48.
15. Pierleoni A, Martelli PL, Fariselli P, Casadio R, (2006) BaCelLo: a balanced subcellular localization predictor. Bioinformatics 22: e408-e416.
16. Blum T, Briesemeister S, Kohlbacher O, (2009) MultiLoc2: integrating phylogeny and gene ontology terms improves subcellular protein localization prediction. BMC Bioinformatics 10: 274.
17. Magnan CN, Randall A, Baldi P, (2009) SOLpro: accurate sequence-based prediction of protein solubility. Bioinformatics 25: 2200.
18. Sonnenburg S, Zien A, Philips P, Rätsch G, (2008) POIMs: positional oligomer importance matricesunderstanding support vector machine-based signal detectors. Bioinformatics 24: i6-i14.
19. Briesemeister S, Rahnenf̈uhrer J, Kohlbacher O, (2010) Going from where to why - interpretable prediction of protein subcellular localization. Bioinformatics 26: 1232-1238.
20. van Dijck PWM, Selten G, Hempenius RA, (2003) On the safety of a new generation of dsm aspergillus niger enzyme production strains. Regulatory Toxicology and Pharmacology 38: 27-35.
21. Dyrløv Bendtsen J, Nielsen H, von Heijne G, Brunak S, (2004) Improved prediction of signal peptides: SignalP 3.0. Journal of Molecular Biology 340: 783-795.
22. Krogh A, Larsson BÈ, Von Heijne G, Sonnhammer ELL, (2001) Predicting transmembrane protein topology with a hidden markov model: application to complete genomes. Journal of Molecular Biology 305: 567-580.
23. Käll L, Krogh A, Sonnhammer ELL, (2004) A combined transmembrane topology and signal peptide prediction method. Journal of Molecular Biology 338: 1027-1036.
24. Dondoshansky I (2002) Blastclust (NCBI Software Development Toolkit). NCBI, Bethesda, Md.
25. Petersen B, Petersen TN, Andersen P, Nielsen M, Lundegaard C, (2009) A generic method for assignment of reliability scores applied to solvent accessibility predictions. BMC Structural Biology 9: 51.
26. Jones DT, (1999) Protein secondary structure prediction based on position-specific scoring matrices. Journal of Molecular Biology 292: 195-202.
27. Chang CC, Lin CJ, (2011) LIBSVM: a library for support vector machines. ACM Transactions on Intelligent Systems and Technology (TIST) 2: 27.
28. Ben-Hur A, Ong CS, Sonnenburg S, Scḧolkopf B, Rätsch G, (2008) Support vector machines and kernels for computational biology. PLoS Computational Biology 4: e1000173.
29. Fawcett T, (2006) An introduction to ROC analysis. Pattern Recognition Letters 27: 861-874.
30. Taylor WR, (1986) The classification of amino acid conservation. Journal of Theoretical Biology 119: 205-218.
31. Sharp PM, Li WH, (1987) The codon adaptation index-a measure of directional synonymous codon usage bias, and its potential applications. Nucleic Acids Research 15: 1281.
32. Cock PJA, Antao T, Chang JT, Chapman BA, Cox CJ, et al. (2009) Biopython: freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics 25: 1422.
33. Jones E, Oliphant T, Peterson P (2001). SciPy: Open source scientific tools for Python. Available: http://www.scipy.org/.
34. Leslie C, Eskin E, Noble WS (2002) The spectrum kernel: a string kernel for SVM protein classification. In: Pacific Symposium on Biocomputing. Hawaii, USA., volume 575, 564-575.
35. Sonnenburg S, Rätsch G, Henschel S, Widmer C, Behr J, et al. (2010) The SHOGUN machine learning toolbox. The Journal of Machine Learning Research 99: 1799-1802.
36. Bailey TL, Williams N, Misleh C, Li WW, (2006) Meme: discovering and analyzing dna and protein sequence motifs. Nucleic Acids Research 34: W369-W373.
37. van den Berg BA, Nijkamp JF, Reinders MJT, Wu L, Pel HJ, et al. (2010) Sequence-based prediction of protein secretion success in Aspergillus niger. In: Proceedings of Pattern Recegnition in Bioinformatics 2010. Springer, 3-14.
38. Nakashima H, Nishikawa K, (1994) Discrimination of intracellular and extracellular proteins using amino acid composition and residue-pair frequencies. Journal of Molecular Biology 238: 54-61.
39. Cedano J, Aloy P, Perez-Pons JA, Querol E, (1997) Relation between amino acid composition and cellular location of proteins. Journal of Molecular Biology 266: 594-600.
40. Rätsch G, Sonnenburg S (2004) Kernel Methods in Computational Biology. The MIT Press, 277 p.
41. Toussaint N, Widmer C, Kohlbacher O, Rätsch G, (2010) Exploiting physico-chemical properties in string kernels. BMC Bioinformatics 11: S7.
42. Akashi H, Gojobori T, (2002) Metabolic efficiency and amino acid composition in the proteomes of Escherichia coli and Bacillus subtilis. Proceedings of the National Academy of Sciences 99: 3695.
43. Neduva V, Russell RB, (2005) Linear motifs: evolutionary interaction switches. FEBS letters 579: 3342-3345.
44. Hiller NL, Bhattacharjee S, van Ooij C, Liolios K, Harrison T, et al. (2004) A host-targeting signal in virulence proteins reveals a secretome in malarial infection. Science 306: 1934.
45. Sagt C, Kleizen B, Verwaal R, De Jong M, Muller W, et al. (2000) Introduction of an Nglycosylation site increases secretion of heterologous proteins in yeasts. Applied and Environmental Microbiology 66: 4940.
46. von Heijne G, (1990) The signal peptide. Journal of Membrane Biology 115: 195-201.
47. Kowalski JM, Parekh RN, Wittrup KD, (1998) Secretion efficiency in saccharomyces cerevisiae of bovine pancreatic trypsin inhibitor mutants lacking disulfide bonds is correlated with thermodynamic stability. Biochemistry 37: 1264-1273.
48. Kowalski JM, Parekh RN, Mao J, Wittrup KD, (1998) Protein folding stability can determine the efficiency of escape from endoplasmic reticulum quality control. Journal of Biological Chemistry 273: 19453.
49. Whyteside G, Alcocer MJC, Kumita JR, Dobson CM, Lazarou M, et al. (2011) Native-state stability determines the extent of degradation relative to secretion of protein variants from Pichia pastoris. PLoS ONE 6: e22692.
50. Shusta EV, Kieke MC, Parke E, Kranz DM, Wittrup KD, (1999) Yeast polypeptide fusion surface display levels predict thermal stability and soluble secretion efficiency1. Journal of Molecular Biology 292: 949-956.
51. Kjeldsen T, Ludvigsen S, Diers I, Balschmidt P, Sørensen AR, et al. (2002) Engineering-enhanced protein secretory expression in yeast with application to insulin. Journal of Biological Chemistry 277: 18245-18248.
52. Ellgaard L, Helenius A, (2003) Quality control in the endoplasmic reticulum. Nature Reviews Molecular Cell Biology 4: 181-191.
53. Helenius A, M A, (2001) Intracellular functions of N-linked glycans. Science 291: 2364.
54. Eriksen SH, Jensen B, Olsen J, (1998) Effect of N-linked glycosylation on secretion, activity, and stability of α-amylase from Aspergillus oryzae. Current Microbiology 37: 117-122.
55. van den Brink HJM, Petersen SG, Rahbek-Nielsen H, Hellmuth K, Harboe M, (2006) Increased production of chymosin by glycosylation. Journal of Biotechnology 125: 304-310.
56. Liu Y, Nguyen A, Wolfert RL, Zhuo S, (2009) Enhancing the secretion of recombinant proteins by engineering N-glycosylation sites. Biotechnology Progress 25: 1468-1475.
57. Kochetov AV, (2008) Alternative translation start sites and hidden coding potential of eukaryotic mRNAs. Bioessays 30: 683-691.
58. Strickler SS, Gribenko AV, Gribenko AV, Keiffer TR, Tomlinson J, et al. (2006) Protein stability and surface electrostatics: a charged relationship. Biochemistry 45: 2761-2766.