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Amin SA, Endalur Gopinarayanan V, Nair NU, Hassoun S. Establishing synthesis pathway-host compatibility via enzyme solubility. Biotechnol Bioeng 2019; 116:1405-1416. [PMID: 30802311 DOI: 10.1002/bit.26959] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2018] [Revised: 12/18/2018] [Accepted: 02/21/2019] [Indexed: 12/12/2022]
Abstract
Current pathway synthesis tools identify possible pathways that can be added to a host to produce the desired target molecule through the exploration of abstract metabolic and reaction network space. However, not many of these tools explore gene-level information required to physically realize the identified synthesis pathways, and none explore enzyme-host compatibility. Developing tools that address this disconnect between abstract reactions/metabolic design space and physical genetic sequence design space will enable expedited experimental efforts that avoid exploring unprofitable synthesis pathways. This work describes a workflow, termed Probabilistic Pathway Assembly with Solubility Confidence Scores (ProPASS), which links synthesis pathway construction with the exploration of the physical design space as imposed by the availability of enzymes with predicted characterized activities within the host. Predicted protein solubility propensity scores are used as a confidence level to quantify the compatibility of each pathway enzyme with the host Escherichia coli (E. coli). This study also presents a database, termed Protein Solubility Database (ProSol DB), which provides solubility confidence scores in E. coli for 240,016 characterized enzymes obtained from UniProtKB/Swiss-Prot. The utility of ProPASS is demonstrated by generating genetic implementations of heterologous synthesis pathways in E. coli that target several commercially useful biomolecules.
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Affiliation(s)
- Sara A Amin
- Department of Computer Science, Tufts University, Medford, Massachusetts
| | | | - Nikhil U Nair
- Department of Chemical and Biological Engineering, Tufts University, Medford, Massachusetts
| | - Soha Hassoun
- Department of Computer Science, Tufts University, Medford, Massachusetts.,Department of Chemical and Biological Engineering, Tufts University, Medford, Massachusetts
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52
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Musil M, Konegger H, Hon J, Bednar D, Damborsky J. Computational Design of Stable and Soluble Biocatalysts. ACS Catal 2018. [DOI: 10.1021/acscatal.8b03613] [Citation(s) in RCA: 56] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Affiliation(s)
- Milos Musil
- Loschmidt Laboratories, Centre for Toxic Compounds in the Environment (RECETOX), and Department of Experimental Biology, Faculty of Science, Masaryk University, 625 00 Brno, Czech Republic
- IT4Innovations Centre of Excellence, Faculty of Information Technology, Brno University of Technology, 612 66 Brno, Czech Republic
- International Clinical Research Center, St. Anne’s University Hospital, Pekarska 53, 656 91 Brno, Czech Republic
| | - Hannes Konegger
- Loschmidt Laboratories, Centre for Toxic Compounds in the Environment (RECETOX), and Department of Experimental Biology, Faculty of Science, Masaryk University, 625 00 Brno, Czech Republic
- International Clinical Research Center, St. Anne’s University Hospital, Pekarska 53, 656 91 Brno, Czech Republic
| | - Jiri Hon
- Loschmidt Laboratories, Centre for Toxic Compounds in the Environment (RECETOX), and Department of Experimental Biology, Faculty of Science, Masaryk University, 625 00 Brno, Czech Republic
- IT4Innovations Centre of Excellence, Faculty of Information Technology, Brno University of Technology, 612 66 Brno, Czech Republic
- International Clinical Research Center, St. Anne’s University Hospital, Pekarska 53, 656 91 Brno, Czech Republic
| | - David Bednar
- Loschmidt Laboratories, Centre for Toxic Compounds in the Environment (RECETOX), and Department of Experimental Biology, Faculty of Science, Masaryk University, 625 00 Brno, Czech Republic
- International Clinical Research Center, St. Anne’s University Hospital, Pekarska 53, 656 91 Brno, Czech Republic
| | - Jiri Damborsky
- Loschmidt Laboratories, Centre for Toxic Compounds in the Environment (RECETOX), and Department of Experimental Biology, Faculty of Science, Masaryk University, 625 00 Brno, Czech Republic
- International Clinical Research Center, St. Anne’s University Hospital, Pekarska 53, 656 91 Brno, Czech Republic
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53
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Effect of C-Terminus Modification in Salmonella typhimurium FliC on Protein Purification Efficacy and Bioactivity. Mol Biotechnol 2018; 61:12-19. [DOI: 10.1007/s12033-018-0135-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
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54
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Hou Q, Bourgeas R, Pucci F, Rooman M. Computational analysis of the amino acid interactions that promote or decrease protein solubility. Sci Rep 2018; 8:14661. [PMID: 30279585 PMCID: PMC6168528 DOI: 10.1038/s41598-018-32988-w] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Accepted: 09/11/2018] [Indexed: 11/24/2022] Open
Abstract
The solubility of globular proteins is a basic biophysical property that is usually a prerequisite for their functioning. In this study, we probed the solubility of globular proteins with the help of the statistical potential formalism, in view of objectifying the connection of solubility with structural and energetic properties and of the solubility-dependence of specific amino acid interactions. We started by setting up two independent datasets containing either soluble or aggregation-prone proteins with known structures. From these two datasets, we computed solubility-dependent distance potentials that are by construction biased towards the solubility of the proteins from which they are derived. Their analysis showed the clear preference of amino acid interactions such as Lys-containing salt bridges and aliphatic interactions to promote protein solubility, whereas others such as aromatic, His-π, cation-π, amino-π and anion-π interactions rather tend to reduce it. These results indicate that interactions involving delocalized π-electrons favor aggregation, unlike those involving no (or few) dispersion forces. Furthermore, using our potentials derived from either highly or weakly soluble proteins to compute protein folding free energies, we found that the difference between these two energies correlates better with solubility than other properties analyzed before such as protein length, isoelectric point and aliphatic index. This is, to the best of our knowledge, the first comprehensive in silico study of the impact of residue-residue interactions on protein solubility properties.The results of this analysis provide new insights that will facilitate future rational protein design applications aimed at modulating the solubility of targeted proteins.
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Affiliation(s)
- Qingzhen Hou
- Department of BioModeling BioInformatics & BioProcesses, Université Libre de Bruxelles, Brussels, 1050, Belgium
| | - Raphaël Bourgeas
- Department of BioModeling BioInformatics & BioProcesses, Université Libre de Bruxelles, Brussels, 1050, Belgium
| | - Fabrizio Pucci
- Department of BioModeling BioInformatics & BioProcesses, Université Libre de Bruxelles, Brussels, 1050, Belgium
| | - Marianne Rooman
- Department of BioModeling BioInformatics & BioProcesses, Université Libre de Bruxelles, Brussels, 1050, Belgium.
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55
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Wang H, Feng L, Webb GI, Kurgan L, Song J, Lin D. Critical evaluation of bioinformatics tools for the prediction of protein crystallization propensity. Brief Bioinform 2018; 19:838-852. [PMID: 28334201 PMCID: PMC6171492 DOI: 10.1093/bib/bbx018] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2016] [Revised: 01/19/2017] [Indexed: 12/11/2022] Open
Abstract
X-ray crystallography is the main tool for structural determination of proteins. Yet, the underlying crystallization process is costly, has a high attrition rate and involves a series of trial-and-error attempts to obtain diffraction-quality crystals. The Structural Genomics Consortium aims to systematically solve representative structures of major protein-fold classes using primarily high-throughput X-ray crystallography. The attrition rate of these efforts can be improved by selection of proteins that are potentially easier to be crystallized. In this context, bioinformatics approaches have been developed to predict crystallization propensities based on protein sequences. These approaches are used to facilitate prioritization of the most promising target proteins, search for alternative structural orthologues of the target proteins and suggest designs of constructs capable of potentially enhancing the likelihood of successful crystallization. We reviewed and compared nine predictors of protein crystallization propensity. Moreover, we demonstrated that integrating selected outputs from multiple predictors as candidate input features to build the predictive model results in a significantly higher predictive performance when compared to using these predictors individually. Furthermore, we also introduced a new and accurate predictor of protein crystallization propensity, Crysf, which uses functional features extracted from UniProt as inputs. This comprehensive review will assist structural biologists in selecting the most appropriate predictor, and is also beneficial for bioinformaticians to develop a new generation of predictive algorithms.
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Affiliation(s)
- Huilin Wang
- Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, China
| | | | - Geoffrey I Webb
- Monash Centre for Data Science, Faculty of Information Technology, Monash University, Australia
| | - Lukasz Kurgan
- Department of Computer Science, Virginia Commonwealth University, USA
| | - Jiangning Song
- Department of Biochemistry and Molecular Biology, Monash University, Australia
| | - Donghai Lin
- Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, China
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56
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Hebditch M, Carballo-Amador MA, Charonis S, Curtis R, Warwicker J. Protein-Sol: a web tool for predicting protein solubility from sequence. Bioinformatics 2018; 33:3098-3100. [PMID: 28575391 PMCID: PMC5870856 DOI: 10.1093/bioinformatics/btx345] [Citation(s) in RCA: 362] [Impact Index Per Article: 60.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2016] [Accepted: 05/26/2017] [Indexed: 12/04/2022] Open
Abstract
Motivation Protein solubility is an important property in industrial and therapeutic applications. Prediction is a challenge, despite a growing understanding of the relevant physicochemical properties. Results Protein–Sol is a web server for predicting protein solubility. Using available data for Escherichia coli protein solubility in a cell-free expression system, 35 sequence-based properties are calculated. Feature weights are determined from separation of low and high solubility subsets. The model returns a predicted solubility and an indication of the features which deviate most from average values. Two other properties are profiled in windowed calculation along the sequence: fold propensity, and net segment charge. The utility of these additional features is demonstrated with the example of thioredoxin. Availability and implementation The Protein–Sol webserver is available at http://protein-sol.manchester.ac.uk.
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Affiliation(s)
- Max Hebditch
- School of Chemical Engineering and Analytical Science, Manchester Institute of Biotechnology, University of Manchester, Manchester M1 7DN, UK
| | | | - Spyros Charonis
- School of Chemical Engineering and Analytical Science, Manchester Institute of Biotechnology, University of Manchester, Manchester M1 7DN, UK
| | - Robin Curtis
- School of Chemical Engineering and Analytical Science, Manchester Institute of Biotechnology, University of Manchester, Manchester M1 7DN, UK
| | - Jim Warwicker
- School of Chemistry, Manchester Institute of Biotechnology, University of Manchester, Manchester M1 7DN, UK
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57
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Masomian M, Rahman RNZRA, Salleh AB, Basri M. Solubility Analysis, Cloning and Functional Overexpression of the Lipase from Aneurinibacillus thermoaerophilus strain HZ, the First Member of True Lipases Subfamily I.9. APPL BIOCHEM MICRO+ 2018. [DOI: 10.1134/s0003683818030109] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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58
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Yang Y, Liu G, Liu M, Bai Z, Liu X, Dai X, Guo W. Correlation Between Protein Primary Structure and Soluble Expression Level of HSA dAb in Escherichia coli. Food Technol Biotechnol 2018; 56:101-109. [PMID: 29796003 DOI: 10.17113/ftb.56.01.18.5445] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
It is widely accepted that features such as pI, length, molecular mass and amino acid (AA) sequence have a significant influence on protein solubility. Here, we mainly focused on AA composition and explored those that most affected the soluble expression level of human serum albumin (HSA) domain antibody (dAb). The soluble expression and sequence of 65 dAb variants were analysed using clustering and linear modelling. Certain AAs significantly affected the soluble expression level of dAb, with the specific AA combinations being (S, R, N, D, Q), (G, R, C, N, S) and (R, S, G); these combinations respectively affected the dAb expression level in the broth supernatant, the level in the pellet lysate and total soluble dAb. Among the 20 AAs, R displayed a negative influence on the soluble expression level, whereas G and S showed positive effects. A linear model was built to predict the soluble expression level from the sequence; this model had a prediction accuracy of 80%. In summary, increasing the content of polar AAs, especially G and S, and decreasing the content of R, was helpful to improve the soluble expression level of HSA dAb.
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Affiliation(s)
- Yankun Yang
- The Key Laboratory of Carbohydrate Chemistry and Biotechnology, School of Biotechnology, Jiangnan University, Ministry of Education, 1800 Lihu Avenue, 214122 Wuxi, PR China.,National Engineering Laboratory for Cereal Fermentation Technology, Jiangnan University, 1800 Lihu Avenue, 214122 Wuxi, PR China
| | - Guoqiang Liu
- The Key Laboratory of Carbohydrate Chemistry and Biotechnology, School of Biotechnology, Jiangnan University, Ministry of Education, 1800 Lihu Avenue, 214122 Wuxi, PR China.,National Engineering Laboratory for Cereal Fermentation Technology, Jiangnan University, 1800 Lihu Avenue, 214122 Wuxi, PR China
| | - Meng Liu
- National Engineering Laboratory for Cereal Fermentation Technology, Jiangnan University, 1800 Lihu Avenue, 214122 Wuxi, PR China
| | - Zhonghu Bai
- National Engineering Laboratory for Cereal Fermentation Technology, Jiangnan University, 1800 Lihu Avenue, 214122 Wuxi, PR China.,Jiangsu Provincial Research Center for Bioactive Product Processing Technology, Jiangnan University, 1800 Lihu Avenue, 214122 Wuxi, PR China
| | - Xiuxia Liu
- National Engineering Laboratory for Cereal Fermentation Technology, Jiangnan University, 1800 Lihu Avenue, 214122 Wuxi, PR China.,Jiangsu Provincial Research Center for Bioactive Product Processing Technology, Jiangnan University, 1800 Lihu Avenue, 214122 Wuxi, PR China
| | - Xiaofeng Dai
- National Engineering Laboratory for Cereal Fermentation Technology, Jiangnan University, 1800 Lihu Avenue, 214122 Wuxi, PR China.,Jiangsu Provincial Research Center for Bioactive Product Processing Technology, Jiangnan University, 1800 Lihu Avenue, 214122 Wuxi, PR China
| | - Wenwen Guo
- Jiangsu Provincial Research Center for Bioactive Product Processing Technology, Jiangnan University, 1800 Lihu Avenue, 214122 Wuxi, PR China.,The Key Laboratory of Industrial Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, 1800 Lihu Avenue, 214122 Wuxi, PR China
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59
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Negahdaripour M, Nezafat N, Eslami M, Ghoshoon MB, Shoolian E, Najafipour S, Morowvat MH, Dehshahri A, Erfani N, Ghasemi Y. Structural vaccinology considerations for in silico designing of a multi-epitope vaccine. INFECTION GENETICS AND EVOLUTION 2018; 58:96-109. [DOI: 10.1016/j.meegid.2017.12.008] [Citation(s) in RCA: 70] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2017] [Revised: 12/05/2017] [Accepted: 12/11/2017] [Indexed: 01/26/2023]
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60
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Guidelines to reach high-quality purified recombinant proteins. Appl Microbiol Biotechnol 2017; 102:81-92. [DOI: 10.1007/s00253-017-8623-8] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2017] [Revised: 10/24/2017] [Accepted: 10/27/2017] [Indexed: 10/18/2022]
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61
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Negahdaripour M, Eslami M, Nezafat N, Hajighahramani N, Ghoshoon MB, Shoolian E, Dehshahri A, Erfani N, Morowvat MH, Ghasemi Y. A novel HPV prophylactic peptide vaccine, designed by immunoinformatics and structural vaccinology approaches. INFECTION GENETICS AND EVOLUTION 2017; 54:402-416. [DOI: 10.1016/j.meegid.2017.08.002] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/24/2017] [Revised: 07/19/2017] [Accepted: 08/01/2017] [Indexed: 12/19/2022]
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62
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In silico methods for design of biological therapeutics. Methods 2017; 131:33-65. [PMID: 28958951 DOI: 10.1016/j.ymeth.2017.09.008] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2017] [Revised: 09/21/2017] [Accepted: 09/23/2017] [Indexed: 12/18/2022] Open
Abstract
It has been twenty years since the first rationally designed small molecule drug was introduced into the market. Since then, we have progressed from designing small molecules to designing biotherapeutics. This class of therapeutics includes designed proteins, peptides and nucleic acids that could more effectively combat drug resistance and even act in cases where the disease is caused because of a molecular deficiency. Computational methods are crucial in this design exercise and this review discusses the various elements of designing biotherapeutic proteins and peptides. Many of the techniques discussed here, such as the deterministic and stochastic design methods, are generally used in protein design. We have devoted special attention to the design of antibodies and vaccines. In addition to the methods for designing these molecules, we have included a comprehensive list of all biotherapeutics approved for clinical use. Also included is an overview of methods that predict the binding affinity, cell penetration ability, half-life, solubility, immunogenicity and toxicity of the designed therapeutics. Biotherapeutics are only going to grow in clinical importance and are set to herald a new generation of disease management and cure.
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63
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Nezafat N, Eslami M, Negahdaripour M, Rahbar MR, Ghasemi Y. Designing an efficient multi-epitope oral vaccine against Helicobacter pylori using immunoinformatics and structural vaccinology approaches. MOLECULAR BIOSYSTEMS 2017; 13:699-713. [PMID: 28194462 DOI: 10.1039/c6mb00772d] [Citation(s) in RCA: 76] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Helicobacter pylori is the cunning bacterium that can live in the stomachs of many people without any symptoms, but gradually can lead to gastric cancer. Due to various obstacles, which are related to anti-H. pylori antibiotic therapy, recently developing an anti-H. pylori vaccine has attracted more attention. In this study, different immunoinformatics and computational vaccinology approaches were employed to design an efficient multi-epitope oral vaccine against H. pylori. Our multi-epitope vaccine is composed of heat labile enterotoxin IIc B (LT-IIc) that is used as a mucosal adjuvant to enhance vaccine immunogenicity for oral immunization, cartilage oligomeric matrix protein (COMP) to increase vaccine stability in acidic pH of gut, one experimentally protective antigen, OipA, and two hypothetical protective antigens, HP0487 and HP0906, and "CTGKSC" peptide motif that target epithelial microfold cells (M cells) to enhance vaccine uptake from the gut barrier. All the aforesaid segments were joined to each other by proper linkers. The vaccine construct was modeled, validated, and refined by different programs to achieve a high-quality 3D structure. The resulting high-quality model was applied for conformational B-cell epitopes selection and docking analyses with a toll-like receptor 2 (TLR2). Moreover, molecular dynamics studies demonstrated that the protein-TLR2 docked model was stable during simulation time. We believe that our vaccine candidate can induce mucosal sIgA and IgG antibodies, and Th1/Th2/Th17-mediated protective immunity that are crucial for eradicating H. pylori infection. In sum, the computational results suggest that our newly designed vaccine could serve as a promising anti-H. pylori vaccine candidate.
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Affiliation(s)
- Navid Nezafat
- Pharmaceutical Science Research Center, Shiraz University of Medical Science, Shiraz, Iran
| | - Mahboobeh Eslami
- Pharmaceutical Science Research Center, Shiraz University of Medical Science, Shiraz, Iran
| | - Manica Negahdaripour
- Pharmaceutical Science Research Center, Shiraz University of Medical Science, Shiraz, Iran and Department of Pharmaceutical Biotechnology, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran.
| | - Mohammad Reza Rahbar
- Pharmaceutical Science Research Center, Shiraz University of Medical Science, Shiraz, Iran and Department of Pharmaceutical Biotechnology, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran.
| | - Younes Ghasemi
- Pharmaceutical Science Research Center, Shiraz University of Medical Science, Shiraz, Iran and Department of Pharmaceutical Biotechnology, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran. and Department of Medical Biotechnology, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran
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64
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Marchese D, de Groot NS, Lorenzo Gotor N, Livi CM, Tartaglia GG. Advances in the characterization of RNA-binding proteins. WILEY INTERDISCIPLINARY REVIEWS. RNA 2016; 7:793-810. [PMID: 27503141 PMCID: PMC5113702 DOI: 10.1002/wrna.1378] [Citation(s) in RCA: 71] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/28/2016] [Revised: 06/14/2016] [Accepted: 06/23/2016] [Indexed: 12/14/2022]
Abstract
From transcription, to transport, storage, and translation, RNA depends on association with different RNA-binding proteins (RBPs). Methods based on next-generation sequencing and protein mass-spectrometry have started to unveil genome-wide interactions of RBPs but many aspects still remain out of sight. How many of the binding sites identified in high-throughput screenings are functional? A number of computational methods have been developed to analyze experimental data and to obtain insights into the specificity of protein-RNA interactions. How can theoretical models be exploited to identify RBPs? In addition to oligomeric complexes, protein and RNA molecules can associate into granular assemblies whose physical properties are still poorly understood. What protein features promote granule formation and what effects do these assemblies have on cell function? Here, we describe the newest in silico, in vitro, and in vivo advances in the field of protein-RNA interactions. We also present the challenges that experimental and computational approaches will have to face in future studies. WIREs RNA 2016, 7:793-810. doi: 10.1002/wrna.1378 For further resources related to this article, please visit the WIREs website.
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Affiliation(s)
- Domenica Marchese
- Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, 08003 Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Natalia Sanchez de Groot
- Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, 08003 Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Nieves Lorenzo Gotor
- Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, 08003 Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Carmen Maria Livi
- Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, 08003 Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- IFOM Foundation, FIRC Institute of Molecular Oncology Foundation, Milan, Italy
| | - Gian G Tartaglia
- Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, 08003 Barcelona, Spain.
- Universitat Pompeu Fabra (UPF), Barcelona, Spain.
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain.
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65
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da Costa JP, Carvalhais V, Ferreira R, Amado F, Vilanova M, Cerca N, Vitorino R. Proteome signatures—how are they obtained and what do they teach us? Appl Microbiol Biotechnol 2015. [DOI: 10.1007/s00253-015-6795-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
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