1
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Miao H, Xiang X, Han N, Wu Q, Huang Z. Improving the Thermostability of Serine Protease PB92 from Bacillus alcalophilus via Site-Directed Mutagenesis Based on Semi-Rational Design. Foods 2023; 12:3081. [PMID: 37628080 PMCID: PMC10453622 DOI: 10.3390/foods12163081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 08/11/2023] [Accepted: 08/15/2023] [Indexed: 08/27/2023] Open
Abstract
Proteases have been widely employed in many industrial processes. In this work, we aimed to improve the thermostability of the serine protease PB92 from Bacillus alcalophilus to meet the high-temperature requirements of biotechnological treatments. Eight mutation sites (N18, S97-S101, E110, and R143) were identified, and 21 mutants were constructed from B-factor comparison and multiple sequence alignment and expressed via Bacillus subtilis. Among them, fifteen mutants exhibited increased half-life (t1/2) values at 65 °C (1.13-31.61 times greater than that of the wild type). Based on the composite score of enzyme activity and thermostability, six complex mutants were implemented. The t1/2 values of these six complex mutants were 2.12-10.05 times greater than that of the wild type at 65 °C. In addition, structural analysis revealed that the increased thermal stability of complex mutants may be related to the formation of additional hydrophobic interactions due to increased hydrophobicity and the decreased flexibility of the structure. In brief, the thermal stability of the complex mutants N18L/R143L/S97A, N18L/R143L/S99L, and N18L/R143L/G100A was increased 4-fold, which reveals application potential in industry.
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Affiliation(s)
- Huabiao Miao
- Engineering Research Center of Sustainable Development and Utilization of Biomass Energy, Ministry of Education, Kunming 650500, China
- School of Life Science, Yunnan Normal University, Kunming 650500, China
| | - Xia Xiang
- School of Life Science, Yunnan Normal University, Kunming 650500, China
| | - Nanyu Han
- Engineering Research Center of Sustainable Development and Utilization of Biomass Energy, Ministry of Education, Kunming 650500, China
- School of Life Science, Yunnan Normal University, Kunming 650500, China
| | - Qian Wu
- Engineering Research Center of Sustainable Development and Utilization of Biomass Energy, Ministry of Education, Kunming 650500, China
- School of Life Science, Yunnan Normal University, Kunming 650500, China
| | - Zunxi Huang
- Engineering Research Center of Sustainable Development and Utilization of Biomass Energy, Ministry of Education, Kunming 650500, China
- School of Life Science, Yunnan Normal University, Kunming 650500, China
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2
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Fang J. Predicting thermostability difference between cellular protein orthologs. Bioinformatics 2023; 39:btad504. [PMID: 37572303 PMCID: PMC10457660 DOI: 10.1093/bioinformatics/btad504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 05/02/2023] [Accepted: 08/11/2023] [Indexed: 08/14/2023] Open
Abstract
MOTIVATION Protein thermostability is of great interest, both in theory and in practice. RESULTS This study compared orthologous proteins with different cellular thermostability. A large number of physicochemical properties of protein were calculated and used to develop a series of machine learning models for predicting cellular thermostability differences between orthologous proteins. Most of the important features in these models are also highly correlated to relative cellular thermostability. A comparison between the present study with previous comparison of orthologous proteins from thermophilic and mesophilic organisms found that most highly correlated features are consistent in these studies, suggesting they may be important to protein thermostability. AVAILABILITY AND IMPLEMENTATION Data freely available for download at https://github.com/fangj3/cellular-protein-thermostability-dataset.
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Affiliation(s)
- Jianwen Fang
- Computational & Systems Biology Branch, Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD 20850, United States
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3
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Hait S, Basu S, Kundu S. Charge reversal mutations in mesophilic-thermophilic orthologous protein pairs and their role in enhancing coulombic interaction energy. J Biomol Struct Dyn 2023; 41:1745-1752. [PMID: 34996344 DOI: 10.1080/07391102.2021.2024258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
Proteins from thermophilic organisms are a matter of immense interest for decades because of its application in fields like de-novo protein design, thermostable variants of biocatalysts etc. Previous studies have found several sequence and structural adaptations related to thermal stability, while charge reversal study remains ignored. Here we address whether charge reversal mutations naturally occur in mesophilic-thermophilic/hyperthermophilic orthologous proteins. Do they contribute to thermal stability? Our systematic study on 1550 mesophilic-thermophilic/hyperthermophilic orthologous protein pairs with remarkable structural and topological similarity, shows gain in coulombic interaction energy in thermophilic/hyperthermophilic proteins at short range associated with partially exposed and buried charge reversal mutations, which may enhance thermostability. Our findings call forth its application in future protein engineering studies. Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Suman Hait
- Department of Biophysics, Molecular Biology and Bioinformatics, University of Calcutta, Kolkata, India
| | - Sudipto Basu
- Department of Biophysics, Molecular Biology and Bioinformatics, University of Calcutta, Kolkata, India
| | - Sudip Kundu
- Department of Biophysics, Molecular Biology and Bioinformatics, University of Calcutta, Kolkata, India
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4
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Kumar S, Duggineni VK, Singhania V, Misra SP, Deshpande PA. Unravelling and Quantifying the Biophysical– Biochemical Descriptors Governing Protein Thermostability by Machine Learning. ADVANCED THEORY AND SIMULATIONS 2023. [DOI: 10.1002/adts.202200703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Affiliation(s)
- Shashi Kumar
- Quantum and Molecular Engineering Laboratory Department of Chemical Engineering Indian Institute of Technology Kharagpur Kharagpur 721302 India
| | - Vinay Kumar Duggineni
- Quantum and Molecular Engineering Laboratory Department of Chemical Engineering Indian Institute of Technology Kharagpur Kharagpur 721302 India
| | - Vibhuti Singhania
- Quantum and Molecular Engineering Laboratory Department of Chemical Engineering Indian Institute of Technology Kharagpur Kharagpur 721302 India
| | - Swayam Prabha Misra
- Quantum and Molecular Engineering Laboratory Department of Chemical Engineering Indian Institute of Technology Kharagpur Kharagpur 721302 India
| | - Parag A. Deshpande
- Quantum and Molecular Engineering Laboratory Department of Chemical Engineering Indian Institute of Technology Kharagpur Kharagpur 721302 India
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5
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Sourcing thermotolerant poly(ethylene terephthalate) hydrolase scaffolds from natural diversity. Nat Commun 2022; 13:7850. [PMID: 36543766 PMCID: PMC9772341 DOI: 10.1038/s41467-022-35237-x] [Citation(s) in RCA: 39] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 11/21/2022] [Indexed: 12/24/2022] Open
Abstract
Enzymatic deconstruction of poly(ethylene terephthalate) (PET) is under intense investigation, given the ability of hydrolase enzymes to depolymerize PET to its constituent monomers near the polymer glass transition temperature. To date, reported PET hydrolases have been sourced from a relatively narrow sequence space. Here, we identify additional PET-active biocatalysts from natural diversity by using bioinformatics and machine learning to mine 74 putative thermotolerant PET hydrolases. We successfully express, purify, and assay 51 enzymes from seven distinct phylogenetic groups; observing PET hydrolysis activity on amorphous PET film from 37 enzymes in reactions spanning pH from 4.5-9.0 and temperatures from 30-70 °C. We conduct PET hydrolysis time-course reactions with the best-performing enzymes, where we observe differences in substrate selectivity as function of PET morphology. We employed X-ray crystallography and AlphaFold to examine the enzyme architectures of all 74 candidates, revealing protein folds and accessory domains not previously associated with PET deconstruction. Overall, this study expands the number and diversity of thermotolerant scaffolds for enzymatic PET deconstruction.
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6
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Wang D, Li J, Sun Y, Ding X, Zhang X, Liu S, Han B, Wang H, Duan X, Sun T. A Machine Learning Model for Accurate Prediction of Sepsis in ICU Patients. Front Public Health 2021; 9:754348. [PMID: 34722452 PMCID: PMC8553999 DOI: 10.3389/fpubh.2021.754348] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 09/20/2021] [Indexed: 12/23/2022] Open
Abstract
Background: Although numerous studies are conducted every year on how to reduce the fatality rate associated with sepsis, it is still a major challenge faced by patients, clinicians, and medical systems worldwide. Early identification and prediction of patients at risk of sepsis and adverse outcomes associated with sepsis are critical. We aimed to develop an artificial intelligence algorithm that can predict sepsis early. Methods: This was a secondary analysis of an observational cohort study from the Intensive Care Unit of the First Affiliated Hospital of Zhengzhou University. A total of 4,449 infected patients were randomly assigned to the development and validation data set at a ratio of 4:1. After extracting electronic medical record data, a set of 55 features (variables) was calculated and passed to the random forest algorithm to predict the onset of sepsis. Results: The pre-procedure clinical variables were used to build a prediction model from the training data set using the random forest machine learning method; a 5-fold cross-validation was used to evaluate the prediction accuracy of the model. Finally, we tested the model using the validation data set. The area obtained by the model under the receiver operating characteristic (ROC) curve (AUC) was 0.91, the sensitivity was 87%, and the specificity was 89%. Conclusions: This newly established machine learning-based model has shown good predictive ability in Chinese sepsis patients. External validation studies are necessary to confirm the universality of our method in the population and treatment practice.
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Affiliation(s)
- Dong Wang
- General Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Critical Care Medicine of Henan Province, Zhengzhou, China.,Key Laboratory for Sepsis of Zhengzhou, Zhengzhou, China
| | - Jinbo Li
- General Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada
| | - Yali Sun
- General Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Critical Care Medicine of Henan Province, Zhengzhou, China.,Key Laboratory for Sepsis of Zhengzhou, Zhengzhou, China
| | - Xianfei Ding
- General Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Critical Care Medicine of Henan Province, Zhengzhou, China.,Key Laboratory for Sepsis of Zhengzhou, Zhengzhou, China
| | - Xiaojuan Zhang
- General Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Critical Care Medicine of Henan Province, Zhengzhou, China.,Key Laboratory for Sepsis of Zhengzhou, Zhengzhou, China
| | - Shaohua Liu
- General Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Critical Care Medicine of Henan Province, Zhengzhou, China.,Key Laboratory for Sepsis of Zhengzhou, Zhengzhou, China
| | - Bing Han
- General Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Critical Care Medicine of Henan Province, Zhengzhou, China.,Key Laboratory for Sepsis of Zhengzhou, Zhengzhou, China
| | - Haixu Wang
- General Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Critical Care Medicine of Henan Province, Zhengzhou, China.,Key Laboratory for Sepsis of Zhengzhou, Zhengzhou, China
| | - Xiaoguang Duan
- General Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Critical Care Medicine of Henan Province, Zhengzhou, China.,Key Laboratory for Sepsis of Zhengzhou, Zhengzhou, China
| | - Tongwen Sun
- General Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Critical Care Medicine of Henan Province, Zhengzhou, China.,Key Laboratory for Sepsis of Zhengzhou, Zhengzhou, China
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7
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Kozuka K, Nakano S, Asano Y, Ito S. Partial Consensus Design and Enhancement of Protein Function by Secondary-Structure-Guided Consensus Mutations. Biochemistry 2021; 60:2309-2319. [PMID: 34254784 DOI: 10.1021/acs.biochem.1c00309] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Consensus design (CD) is a representative sequence-based protein design method that enables the design of highly functional proteins by analyzing vast amounts of protein sequence data. This study proposes a partial consensus design (PCD) of a protein as a derivative approach of CD. The method replaces the target protein sequence with a consensus sequence in a secondary-structure-dependent manner (i.e., regionally dependent and divided into α-helix, β-sheet, and loop regions). In this study, we generated several artificial partial consensus l-threonine 3-dehydrogenases (PcTDHs) by PCD using the TDH from Cupriavidus necator (CnTDH) as a target protein. Structural and functional analysis of PcTDHs suggested that thermostability would be independently improved when consensus mutations are introduced into the loop region of TDHs. On the other hand, enzyme kinetic parameters (kcat/Km) and average productivity would be synergistically enhanced by changing the combination of the mutations-replacement of one region of CnTDH with a consensus sequence provided only negative effects, but the negative effects were nullified when the two regions were replaced simultaneously. Taken together, we propose the hypothesis that there are protein regions that encode individual protein properties, such as thermostability and activity, and that the introduction of consensus mutations into these regions could additively or synergistically modify their functions.
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Affiliation(s)
- Kohei Kozuka
- Graduate School of Integrated Pharmaceutical and Nutritional Sciences, University of Shizuoka, 52-1 Yada, Suruga-ku, Shizuoka, 422-8526, Japan
| | - Shogo Nakano
- Graduate School of Integrated Pharmaceutical and Nutritional Sciences, University of Shizuoka, 52-1 Yada, Suruga-ku, Shizuoka, 422-8526, Japan.,PREST, Japan Science and Technology Agency, Kawaguchi, Saitama 332-0012, Japan
| | - Yasuhisa Asano
- Biotechnology Research Center and Department of Biotechnology, Toyama Prefectural University, 5180 Kurokawa, Imizu, Toyama 939-0398, Japan
| | - Sohei Ito
- Graduate School of Integrated Pharmaceutical and Nutritional Sciences, University of Shizuoka, 52-1 Yada, Suruga-ku, Shizuoka, 422-8526, Japan
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8
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Pinney MM, Mokhtari DA, Akiva E, Yabukarski F, Sanchez DM, Liang R, Doukov T, Martinez TJ, Babbitt PC, Herschlag D. Parallel molecular mechanisms for enzyme temperature adaptation. Science 2021; 371:371/6533/eaay2784. [PMID: 33674467 DOI: 10.1126/science.aay2784] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2019] [Revised: 08/23/2020] [Accepted: 01/04/2021] [Indexed: 12/13/2022]
Abstract
The mechanisms that underly the adaptation of enzyme activities and stabilities to temperature are fundamental to our understanding of molecular evolution and how enzymes work. Here, we investigate the molecular and evolutionary mechanisms of enzyme temperature adaption, combining deep mechanistic studies with comprehensive sequence analyses of thousands of enzymes. We show that temperature adaptation in ketosteroid isomerase (KSI) arises primarily from one residue change with limited, local epistasis, and we establish the underlying physical mechanisms. This residue change occurs in diverse KSI backgrounds, suggesting parallel adaptation to temperature. We identify residues associated with organismal growth temperature across 1005 diverse bacterial enzyme families, suggesting widespread parallel adaptation to temperature. We assess the residue properties, molecular interactions, and interaction networks that appear to underly temperature adaptation.
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Affiliation(s)
- Margaux M Pinney
- Department of Biochemistry, Stanford University, Stanford, CA 94305, USA.
| | - Daniel A Mokhtari
- Department of Biochemistry, Stanford University, Stanford, CA 94305, USA
| | - Eyal Akiva
- Department of Bioengineering and Therapeutic Sciences and Quantitative Biosciences Institute, University of California, San Francisco, CA 94158, USA
| | - Filip Yabukarski
- Department of Biochemistry, Stanford University, Stanford, CA 94305, USA.,Chan Zuckerberg Biohub, San Francisco, CA 94110, USA
| | - David M Sanchez
- Department of Chemistry, Stanford University, Stanford, CA 94305, USA.,Department of Photon Sciences, SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA
| | - Ruibin Liang
- Department of Chemistry, Stanford University, Stanford, CA 94305, USA.,Department of Photon Sciences, SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA
| | - Tzanko Doukov
- Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA
| | - Todd J Martinez
- Department of Chemistry, Stanford University, Stanford, CA 94305, USA.,Department of Photon Sciences, SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA
| | - Patricia C Babbitt
- Department of Bioengineering and Therapeutic Sciences and Quantitative Biosciences Institute, University of California, San Francisco, CA 94158, USA
| | - Daniel Herschlag
- Department of Biochemistry, Stanford University, Stanford, CA 94305, USA. .,Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA.,Stanford ChEM-H, Stanford University, Stanford, CA 94305, USA
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9
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Sternke M, Tripp KW, Barrick D. The use of consensus sequence information to engineer stability and activity in proteins. Methods Enzymol 2020; 643:149-179. [PMID: 32896279 DOI: 10.1016/bs.mie.2020.06.001] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
The goal of protein design is to create proteins that are stable, soluble, and active. Here we focus on one approach to protein design in which sequence information is used to create a "consensus" sequence. Such consensus sequences comprise the most common residue at each position in a multiple sequence alignment (MSA). After describing some general ideas that relate MSA and consensus sequences and presenting a statistical thermodynamic framework that relates consensus and non-consensus sequences to stability, we detail the process of designing a consensus sequence and survey reports of consensus design and characterization from the literature. Many of these consensus proteins retain native biological activities including ligand binding and enzyme activity. Remarkably, in most cases the consensus protein shows significantly higher stability than extant versions of the protein, as measured by thermal or chemical denaturation, consistent with the statistical thermodynamic model. To understand this stability increase, we compare various features of consensus sequences with the extant MSA sequences from which they were derived. Consensus sequences show enrichment in charged residues (most notably glutamate and lysine) and depletion of uncharged polar residues (glutamine, serine, and asparagine). Surprisingly, a survey of stability changes resulting from point substitutions show little correlation with residue frequencies at the corresponding positions within the MSA, suggesting that the high stability of consensus proteins may result from interactions among residue pairs or higher-order clusters. Whatever the source, the large number of reported successes demonstrates that consensus design is a viable route to generating active and in many cases highly stabilized proteins.
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Affiliation(s)
- Matt Sternke
- T.C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, MD, United States; Program in Molecular Biophysics, Johns Hopkins University, Baltimore, MD, United States
| | - Katherine W Tripp
- T.C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, MD, United States
| | - Doug Barrick
- T.C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, MD, United States.
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10
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Gado JE, Beckham GT, Payne CM. Improving Enzyme Optimum Temperature Prediction with Resampling Strategies and Ensemble Learning. J Chem Inf Model 2020; 60:4098-4107. [DOI: 10.1021/acs.jcim.0c00489] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Affiliation(s)
- Japheth E. Gado
- Department of Chemical and Materials Engineering, University of Kentucky, Lexington, Kentucky 40506, United States
- National Bioenergy Center, National Renewable Energy Laboratory, Golden, Colorado 80401, United States
| | - Gregg T. Beckham
- National Bioenergy Center, National Renewable Energy Laboratory, Golden, Colorado 80401, United States
| | - Christina M. Payne
- Department of Chemical and Materials Engineering, University of Kentucky, Lexington, Kentucky 40506, United States
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11
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Sauer DB, Wang DN. Predicting the optimal growth temperatures of prokaryotes using only genome derived features. Bioinformatics 2020; 35:3224-3231. [PMID: 30689741 DOI: 10.1093/bioinformatics/btz059] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2018] [Revised: 12/20/2018] [Accepted: 01/22/2019] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION Optimal growth temperature is a fundamental characteristic of all living organisms. Knowledge of this temperature is central to the study of a prokaryote, the thermal stability and temperature dependent activity of its genes, and the bioprospecting of its genome for thermally adapted proteins. While high throughput sequencing methods have dramatically increased the availability of genomic information, the growth temperatures of the source organisms are often unknown. This limits the study and technological application of these species and their genomes. Here, we present a novel method for the prediction of growth temperatures of prokaryotes using only genomic sequences. RESULTS By applying the reverse ecology principle that an organism's genome includes identifiable adaptations to its native environment, we can predict a species' optimal growth temperature with an accuracy of 5.17°C root-mean-square error and a coefficient of determination of 0.835. The accuracy can be further improved for specific taxonomic clades or by excluding psychrophiles. This method provides a valuable tool for the rapid calculation of organism growth temperature when only the genome sequence is known. AVAILABILITY AND IMPLEMENTATION Source code, genomes analyzed and features calculated are available at: https://github.com/DavidBSauer/OGT_prediction. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- David B Sauer
- Department of Cell Biology, and The Helen L. and Martin S. Kimmel Center for Biology and Medicine, Skirball Institute of Biomolecular Medicine, New York University School of Medicine, New York, New York, USA
| | - Da-Neng Wang
- Department of Cell Biology, and The Helen L. and Martin S. Kimmel Center for Biology and Medicine, Skirball Institute of Biomolecular Medicine, New York University School of Medicine, New York, New York, USA
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12
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Hait S, Mallik S, Basu S, Kundu S. Finding the generalized molecular principles of protein thermal stability. Proteins 2019; 88:788-808. [PMID: 31872464 DOI: 10.1002/prot.25866] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2019] [Revised: 12/05/2019] [Accepted: 12/14/2019] [Indexed: 11/09/2022]
Abstract
Are there any generalized molecular principles of thermal adaptation? Here, integrating the concepts of structural bioinformatics, sequence analysis, and classical knot theory, we develop a robust computational framework that seeks for mechanisms of thermal adaptation by comparing orthologous mesophilic-thermophilic and mesophilic-hyperthermophilic proteins of remarkable structural and topological similarities, and still leads us to context-independent results. A comprehensive analysis of 4741 high-resolution, non-redundant X-ray crystallographic structures collected from 11 hyperthermophilic, 32 thermophilic and 53 mesophilic prokaryotes unravels at least five "nearly universal" signatures of thermal adaptation, irrespective of the enormous sequence, structure, and functional diversity of the proteins compared. A careful investigation further extracts a set of amino acid changes that can potentially enhance protein thermal stability, and remarkably, these mutations are overrepresented in protein crystallization experiments, in disorder-to-order transitions and in engineered thermostable variants of existing mesophilic proteins. These results could be helpful to find a precise, global picture of thermal adaptation.
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Affiliation(s)
- Suman Hait
- Department of Biophysics, Molecular Biology and Bioinformatics, University of Calcutta, Kolkata, India
| | - Saurav Mallik
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Sudipto Basu
- Department of Biophysics, Molecular Biology and Bioinformatics, University of Calcutta, Kolkata, India.,Center of Excellence in Systems Biology and Biomedical Engineering (TEQIP Phase-III), University of Calcutta, Kolkata, India
| | - Sudip Kundu
- Department of Biophysics, Molecular Biology and Bioinformatics, University of Calcutta, Kolkata, India.,Center of Excellence in Systems Biology and Biomedical Engineering (TEQIP Phase-III), University of Calcutta, Kolkata, India
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13
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Consensus sequence design as a general strategy to create hyperstable, biologically active proteins. Proc Natl Acad Sci U S A 2019; 116:11275-11284. [PMID: 31110018 DOI: 10.1073/pnas.1816707116] [Citation(s) in RCA: 84] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Consensus sequence design offers a promising strategy for designing proteins of high stability while retaining biological activity since it draws upon an evolutionary history in which residues important for both stability and function are likely to be conserved. Although there have been several reports of successful consensus design of individual targets, it is unclear from these anecdotal studies how often this approach succeeds and how often it fails. Here, we attempt to assess generality by designing consensus sequences for a set of six protein families with a range of chain lengths, structures, and activities. We characterize the resulting consensus proteins for stability, structure, and biological activities in an unbiased way. We find that all six consensus proteins adopt cooperatively folded structures in solution. Strikingly, four of six of these consensus proteins show increased thermodynamic stability over naturally occurring homologs. Each consensus protein tested for function maintained at least partial biological activity. Although peptide binding affinity by a consensus-designed SH3 is rather low, K m values for consensus enzymes are similar to values from extant homologs. Although consensus enzymes are slower than extant homologs at low temperature, they are faster than some thermophilic enzymes at high temperature. An analysis of sequence properties shows consensus proteins to be enriched in charged residues, and rarified in uncharged polar residues. Sequence differences between consensus and extant homologs are predominantly located at weakly conserved surface residues, highlighting the importance of these residues in the success of the consensus strategy.
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14
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Tian B, Talukder SK, Fu J, Fritz AK, Trick HN. Expression of a rice soluble starch synthase gene in transgenic wheat improves the grain yield under heat stress conditions. IN VITRO CELLULAR & DEVELOPMENTAL BIOLOGY. PLANT : JOURNAL OF THE TISSUE CULTURE ASSOCIATION 2018; 54:216-227. [PMID: 29780215 PMCID: PMC5954006 DOI: 10.1007/s11627-018-9893-2] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2017] [Accepted: 02/16/2018] [Indexed: 05/04/2023]
Abstract
Wheat (Triticum aestivum L.) is a temperate cereal with an optimum temperature range of 15-22°C during the grain filling stage. Heat stress is one of the major environmental constraints for wheat production worldwide. Temperatures above 25°C during the grain filling stage significantly reduced wheat yield and quality. This reduction was reported due to the inactivation of the soluble starch synthase, a key heat-labile enzyme in starch transformation of wheat endosperm. To improve wheat productivity under heat stress, the rice soluble starch synthase I, under the control of either a constitutive promoter or an endosperm-specific promoter, was expressed in wheat and the transgenic lines were monitored for expression and the effects on yield-related traits. The results showed that the transgenic wheat events expressed rice soluble starch synthase I at a high level after four generations, and transgenic plants produced grains of greater weight during heat stress. Under heat stress conditions, the thousand kernel weight increased 21-34% in T2 and T3 transgenic plants compared to the non-transgenic control plants. In addition, the photosynthetic duration of transgenic wheat was longer than in non-transgenic controls. This study demonstrated that the engineering of a heat tolerant soluble starch synthase gene can be a potential strategy to improve wheat yield under heat stress conditions.
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Affiliation(s)
- Bin Tian
- Department of Plant Pathology, 4024 Throckmorton Plant Sciences Center, Kansas State University, 1712 Claflin Road, Manhattan, KS 66506 USA
| | - Shyamal K. Talukder
- Department of Agronomy, 2004 Throckmorton Plant Sciences Center, Kansas State University, 1712 Claflin Road, Manhattan, KS 66506 USA
- Samuel Roberts Noble Research Institute, LLC, Ardmore, OK 73401 USA
| | - Jianming Fu
- Department of Agronomy, 2004 Throckmorton Plant Sciences Center, Kansas State University, 1712 Claflin Road, Manhattan, KS 66506 USA
- USDA/ARS/Hard Winter Wheat Genetics Research Unit, 4008 Throckmorton Plant Sciences Center, Kansas State University, 1712 Claflin Road, Manhattan, KS 66506 USA
| | - Allan K. Fritz
- Department of Agronomy, 2004 Throckmorton Plant Sciences Center, Kansas State University, 1712 Claflin Road, Manhattan, KS 66506 USA
| | - Harold N. Trick
- Department of Plant Pathology, 4024 Throckmorton Plant Sciences Center, Kansas State University, 1712 Claflin Road, Manhattan, KS 66506 USA
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15
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Tang H, Cui F, Liu L, Li Y. Predictive models for tyrosinase inhibitors: Challenges from heterogeneous activity data determined by different experimental protocols. Comput Biol Chem 2018; 73:79-84. [PMID: 29471263 DOI: 10.1016/j.compbiolchem.2018.02.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2017] [Revised: 02/02/2018] [Accepted: 02/08/2018] [Indexed: 10/18/2022]
Abstract
Quantitative Structure-Activity Relationship (QSAR) models of tyrosinase inhibitors were built using Random Forest (RF) algorithm and evaluated by the out-of-bag estimation (R2OOB) and 10-fold cross validation (Q2CV). We found that the performances of QSAR models were closely correlated with the systematic errors of inhibitory activities of tyrosinase inhibitors arising from the different measuring protocols. By defining ERRsys, outliers with larger errors can be efficiently identified and removed from heterogeneous activity data. A reasonable QSAR model (R2OOB of 0.74 and Q2CV of 0.80) was obtained by the exclusion of 13 outliers with larger systematic errors. It is a clear example of the challenge for QSAR model that can overwhelm heterogeneous data from different experimental protocols.
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Affiliation(s)
- Haifeng Tang
- Key Laboratory of Synthetic Rubber, Changchun Institute of Applied Chemistry (CIAC), Chinese Academy of Sciences, Changchun 130022, PR China; School of Life Science, Jilin University, Changchun 130012, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China
| | - Fengchao Cui
- Key Laboratory of Synthetic Rubber, Changchun Institute of Applied Chemistry (CIAC), Chinese Academy of Sciences, Changchun 130022, PR China.
| | - Lunyang Liu
- Key Laboratory of Synthetic Rubber, Changchun Institute of Applied Chemistry (CIAC), Chinese Academy of Sciences, Changchun 130022, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China
| | - Yunqi Li
- Key Laboratory of Synthetic Rubber, Changchun Institute of Applied Chemistry (CIAC), Chinese Academy of Sciences, Changchun 130022, PR China.
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16
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Sawle L, Huihui J, Ghosh K. All-Atom Simulations Reveal Protein Charge Decoration in the Folded and Unfolded Ensemble Is Key in Thermophilic Adaptation. J Chem Theory Comput 2017; 13:5065-5075. [DOI: 10.1021/acs.jctc.7b00545] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Lucas Sawle
- Department of Physics and
Astronomy, University of Denver, Denver, Colorado 80208, United States
| | - Jonathan Huihui
- Department of Physics and
Astronomy, University of Denver, Denver, Colorado 80208, United States
| | - Kingshuk Ghosh
- Department of Physics and
Astronomy, University of Denver, Denver, Colorado 80208, United States
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17
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Leng F, Xu C, Xia XY, Pan XM. Establishing knowledge on the sequence arrangement pattern of nucleated protein folding. PLoS One 2017; 12:e0173583. [PMID: 28273143 PMCID: PMC5342263 DOI: 10.1371/journal.pone.0173583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2016] [Accepted: 02/22/2017] [Indexed: 11/21/2022] Open
Abstract
The heat-tolerance mechanisms of (hyper)thermophilic proteins provide a unique opportunity to investigate the unsolved protein folding problem. In an attempt to determine whether the interval between residues in sequence might play a role in determining thermostability, we constructed a sequence interval-dependent value function to calculate the residue pair frequency. Additionally, we identified a new sequence arrangement pattern, where like-charged residues tend to be adjacently assembled, while unlike-charged residues are distributed over longer intervals, using statistical analysis of a large sequence database. This finding indicated that increasing the intervals between unlike-charged residues can increase protein thermostability, with the arrangement patterns of these charged residues serving as thermodynamically favorable nucleation points for protein folding. Additionally, we identified that the residue pairs K-E, R-E, L-V and V-V involving long sequence intervals play important roles involving increased protein thermostability. This work demonstrated a novel approach for considering sequence intervals as keys to understanding protein folding. Our findings of novel relationships between residue arrangement and protein thermostability can be used in industry and academia to aid the design of thermostable proteins.
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Affiliation(s)
- Fei Leng
- Key Laboratory of Bioinformatics, Ministry of Education, School of Life Sciences, Tsinghua University, Beijing, China
| | - Chao Xu
- Key Laboratory of Bioinformatics, Ministry of Education, School of Life Sciences, Tsinghua University, Beijing, China
| | - Xia-Yu Xia
- Key Laboratory of Bioinformatics, Ministry of Education, School of Life Sciences, Tsinghua University, Beijing, China
| | - Xian-Ming Pan
- Key Laboratory of Bioinformatics, Ministry of Education, School of Life Sciences, Tsinghua University, Beijing, China
- * E-mail:
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18
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Sawle L, Ghosh K. A theoretical method to compute sequence dependent configurational properties in charged polymers and proteins. J Chem Phys 2016; 143:085101. [PMID: 26328871 DOI: 10.1063/1.4929391] [Citation(s) in RCA: 144] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
A general formalism to compute configurational properties of proteins and other heteropolymers with an arbitrary sequence of charges and non-uniform excluded volume interaction is presented. A variational approach is utilized to predict average distance between any two monomers in the chain. The presented analytical model, for the first time, explicitly incorporates the role of sequence charge distribution to determine relative sizes between two sequences that vary not only in total charge composition but also in charge decoration (even when charge composition is fixed). Furthermore, the formalism is general enough to allow variation in excluded volume interactions between two monomers. Model predictions are benchmarked against the all-atom Monte Carlo studies of Das and Pappu [Proc. Natl. Acad. Sci. U. S. A. 110, 13392 (2013)] for 30 different synthetic sequences of polyampholytes. These sequences possess an equal number of glutamic acid (E) and lysine (K) residues but differ in the patterning within the sequence. Without any fit parameter, the model captures the strong sequence dependence of the simulated values of the radius of gyration with a correlation coefficient of R(2) = 0.9. The model is then applied to real proteins to compare the unfolded state dimensions of 540 orthologous pairs of thermophilic and mesophilic proteins. The excluded volume parameters are assumed similar under denatured conditions, and only electrostatic effects encoded in the sequence are accounted for. With these assumptions, thermophilic proteins are found-with high statistical significance-to have more compact disordered ensemble compared to their mesophilic counterparts. The method presented here, due to its analytical nature, is capable of making such high throughput analysis of multiple proteins and will have broad applications in proteomic studies as well as in other heteropolymeric systems.
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Affiliation(s)
- Lucas Sawle
- Department of Physics and Astronomy, University of Denver, Denver, Colorado 80208, USA
| | - Kingshuk Ghosh
- Department of Physics and Astronomy, University of Denver, Denver, Colorado 80208, USA
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19
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Wahome N, Sully E, Singer C, Thomas JC, Hu L, Joshi SB, Volkin DB, Fang J, Karanicolas J, Jacobs DJ, Mantis NJ, Middaugh CR. Novel Ricin Subunit Antigens With Enhanced Capacity to Elicit Toxin-Neutralizing Antibody Responses in Mice. J Pharm Sci 2016; 105:1603-1613. [PMID: 26987947 PMCID: PMC4846473 DOI: 10.1016/j.xphs.2016.02.009] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2015] [Revised: 01/26/2016] [Accepted: 02/09/2016] [Indexed: 02/07/2023]
Abstract
RiVax is a candidate ricin toxin subunit vaccine antigen that has proven to be safe in human phase I clinical trials. In this study, we introduced double and triple cavity-filling point mutations into the RiVax antigen with the expectation that stability-enhancing modifications would have a beneficial effect on overall immunogenicity of the recombinant proteins. We demonstrate that 2 RiVax triple mutant derivatives, RB (V81L/C171L/V204I) and RC (V81I/C171L/V204I), when adsorbed to aluminum salts adjuvant and tested in a mouse prime-boost-boost regimen were 5- to 10-fold more effective than RiVax at eliciting toxin-neutralizing serum IgG antibody titers. Increased toxin neutralizing antibody values and seroconversion rates were evident at different antigen dosages and within 7 days after the first booster. Quantitative stability/flexibility relationships analysis revealed that the RB and RC mutations affect rigidification of regions spanning residues 98-103, which constitutes a known immunodominant neutralizing B-cell epitope. A more detailed understanding of the immunogenic nature of RB and RC may provide insight into the fundamental relationship between local protein stability and antibody reactivity.
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Affiliation(s)
- Newton Wahome
- Department of Pharmaceutical Chemistry, Macromolecule and Vaccine Stabilization Center, University of Kansas, Lawrence, Kansas 66047
| | - Erin Sully
- Division of Infectious Disease, Wadsworth Center, New York State Department of Health, Albany, New York 12208
| | - Christopher Singer
- Department of Physics and Optical Science, University of North Carolina at Charlotte, Charlotte, North Carolina 28223
| | - Justin C Thomas
- Department of Pharmaceutical Chemistry, Macromolecule and Vaccine Stabilization Center, University of Kansas, Lawrence, Kansas 66047
| | - Lei Hu
- Department of Pharmaceutical Chemistry, Macromolecule and Vaccine Stabilization Center, University of Kansas, Lawrence, Kansas 66047
| | - Sangeeta B Joshi
- Department of Pharmaceutical Chemistry, Macromolecule and Vaccine Stabilization Center, University of Kansas, Lawrence, Kansas 66047
| | - David B Volkin
- Department of Pharmaceutical Chemistry, Macromolecule and Vaccine Stabilization Center, University of Kansas, Lawrence, Kansas 66047
| | - Jianwen Fang
- Applied Bioinformatics Laboratory, Department of Medicinal Chemistry, University of Kansas, Lawrence, Kansas 66047
| | - John Karanicolas
- Department of Molecular Biosciences, Center for Computational Biology, University of Kansas, Lawrence, Kansas 66045
| | - Donald J Jacobs
- Department of Physics and Optical Science, University of North Carolina at Charlotte, Charlotte, North Carolina 28223.
| | - Nicholas J Mantis
- Division of Infectious Disease, Wadsworth Center, New York State Department of Health, Albany, New York 12208; Department of Biomedical Sciences, School of Public Health, University at Albany, Albany, New York 12201.
| | - C Russell Middaugh
- Department of Pharmaceutical Chemistry, Macromolecule and Vaccine Stabilization Center, University of Kansas, Lawrence, Kansas 66047.
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20
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Insights into the molecular basis of piezophilic adaptation: Extraction of piezophilic signatures. J Theor Biol 2015; 390:117-26. [PMID: 26656108 DOI: 10.1016/j.jtbi.2015.11.021] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2015] [Revised: 11/06/2015] [Accepted: 11/21/2015] [Indexed: 11/20/2022]
Abstract
Piezophiles are the organisms which can successfully survive at extreme pressure conditions. However, the molecular basis of piezophilic adaptation is still poorly understood. Analysis of the protein sequence adjustments that had taken place during evolution can help to reveal the sequence adaptation parameters responsible for protein functional and structural adaptation at such high pressure conditions. In this current work we have used SVM classifier for filtering strong instances and generated human interpretable rules from these strong instances by using the PART algorithm. These generated rules were analyzed for getting insights into the molecular signature patterns present in the piezophilic proteins. The experiments were performed on three different temperature ranges piezophilic groups, namely psychrophilic-piezophilic, mesophilic-piezophilic, and thermophilic-piezophilic for the detailed comparative study. The best classification results were obtained as we move up the temperature range from psychrophilic-piezophilic to thermophilic-piezophilic. Based on the physicochemical classification of amino acids and using feature ranking algorithms, hydrophilic and polar amino acid groups have higher discriminative ability for psychrophilic-piezophilic and mesophilic-piezophilic groups along with hydrophobic and nonpolar amino acids for the thermophilic-piezophilic groups. We also observed an overrepresentation of polar, hydrophilic and small amino acid groups in the discriminatory rules of all the three temperature range piezophiles along with aliphatic, nonpolar and hydrophobic groups in the mesophilic-piezophilic and thermophilic-piezophilic groups.
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21
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Nath A, Subbiah K. Inferring biological basis about psychrophilicity by interpreting the rules generated from the correctly classified input instances by a classifier. Comput Biol Chem 2014; 53PB:198-203. [PMID: 25462328 DOI: 10.1016/j.compbiolchem.2014.10.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2014] [Revised: 09/02/2014] [Accepted: 10/06/2014] [Indexed: 11/19/2022]
Abstract
Organisms thriving at extreme cold surroundings are called as psychrophiles and they present a wealth of knowledge about sequence adjustments in proteins that had occurred during the adaptation to low temperatures. In this paper, we propose a new cascading model to investigate the basis for psychrophilicity. In this model, a superior classifier was used to discriminate psychrophilic from mesophilic protein sequences, and then the PART rule generating algorithm was applied on the input instances that are correctly classified by the classifier, to generate human interpretable rules. These derived rules were further validated on a structural dataset and finally analyzed to discover the underlying biological basis about the psychrophilicity. In this study, we have used one of the key features of psychrophilic proteins accountable for remaining functional in extreme cold temperature surroundings i.e., global patterns of amino acid composition as the input features. The rotation forest classifier outperformed all the other classifiers with maximum accuracy of 70.5% and maximum AUC of 0.78. The effect of sequence length on the classification accuracy was also investigated. The analysis of the derived rules and interpretation of the analyzed results had revealed some interesting phenomena such as the amino acids A, D, G, F, and S are over-represented, and T is under-represented in psychrophilic proteins. These findings augment the existing domain knowledge for psychrophilic sequence features.
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Affiliation(s)
- Abhigyan Nath
- Bioinformatics Section, Mahila Mahavidyalaya, Banaras Hindu University, Varanasi 221005, India.
| | - Karthikeyan Subbiah
- Department of Computer Science, Banaras Hindu University, Varanasi 221005, India.
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22
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Talukder SK, Babar MA, Vijayalakshmi K, Poland J, Prasad PVV, Bowden R, Fritz A. Mapping QTL for the traits associated with heat tolerance in wheat (Triticum aestivum L.). BMC Genet 2014. [PMID: 25384418 DOI: 10.1186/s12863-014-0097-94] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/30/2023] Open
Abstract
BACKGROUND High temperature (heat) stress during grain filling is a major problem in most of the wheat growing areas. Developing heat tolerant cultivars has become a principal breeding goal in the Southern and Central Great Plain areas of the USA. Traits associated with high temperature tolerance can be used to develop heat tolerant cultivars in wheat. The present study was conducted to identify chromosomal regions associated with thylakoid membrane damage (TMD), plasmamembrane damage (PMD), and SPAD chlorophyll content (SCC), which are indicative of high temperature tolerance. RESULTS In this study we have reported one of the first linkage maps in wheat using genotype by sequencing SNP (GBS-SNP) markers to extreme response to post anthesis heat stress conditions. The linkage map was comprised of 972 molecular markers (538 Bin, 258 AFLPs, 175 SSRs, and an EST). The genotypes of the RIL population showed strong variation for TMD, SCC and PMD in both generations (F10 and F9). Composite interval mapping identified five QTL regions significantly associated with response to heat stress. Associations were identified for PMD on chromosomes 7A, 2B and 1D, SCC on 6A, 7A, 1B and 1D and TMD on 6A, 7A and 1D. The variability (R(2)) explained by these QTL ranged from 11.9 to 30.6% for TMD, 11.4 to 30.8% for SCC, and 10.5 to 33.5% for PMD. Molecular markers Xbarc113 and AFLP AGCTCG-347 on chromosome 6A, Xbarc121 and Xbarc49 on 7A, gwm18 and Bin1130 on 1B, Bin178 and Bin81 on 2B and Bin747 and Bin1546 on 1D were associated with these QTL. CONCLUSION The identified QTL can be used for marker assisted selection in breeding wheat for improved heat tolerance in Ventnor or Karl 92 genetic background.
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Affiliation(s)
- Shyamal Krishna Talukder
- Forage Improvement Division, The Samuel Roberts Noble Foundation, Ardmore, OK, 73401, USA.
- Department of Agronomy, Kansas State University, Manhattan, KS, 66506, USA.
| | - Md Ali Babar
- Department of Agronomy, University of Florida, Gainesville, Florida, USA.
| | | | - Jesse Poland
- Department of Plant Pathology, Kansas State University, Manhattan, KS, 66506, USA.
| | | | - Robert Bowden
- USDA/ARS/Hard Winter Wheat Genetics Research Unit, Kansas State University, Manhattan, KS, 66506, USA.
| | - Allan Fritz
- Department of Agronomy, Kansas State University, Manhattan, KS, 66506, USA.
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23
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Talukder SK, Babar MA, Vijayalakshmi K, Poland J, Prasad PVV, Bowden R, Fritz A. Mapping QTL for the traits associated with heat tolerance in wheat (Triticum aestivum L.). BMC Genet 2014. [PMID: 25384418 DOI: 10.1186/s12863-014-00974] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/29/2023] Open
Abstract
BACKGROUND High temperature (heat) stress during grain filling is a major problem in most of the wheat growing areas. Developing heat tolerant cultivars has become a principal breeding goal in the Southern and Central Great Plain areas of the USA. Traits associated with high temperature tolerance can be used to develop heat tolerant cultivars in wheat. The present study was conducted to identify chromosomal regions associated with thylakoid membrane damage (TMD), plasmamembrane damage (PMD), and SPAD chlorophyll content (SCC), which are indicative of high temperature tolerance. RESULTS In this study we have reported one of the first linkage maps in wheat using genotype by sequencing SNP (GBS-SNP) markers to extreme response to post anthesis heat stress conditions. The linkage map was comprised of 972 molecular markers (538 Bin, 258 AFLPs, 175 SSRs, and an EST). The genotypes of the RIL population showed strong variation for TMD, SCC and PMD in both generations (F10 and F9). Composite interval mapping identified five QTL regions significantly associated with response to heat stress. Associations were identified for PMD on chromosomes 7A, 2B and 1D, SCC on 6A, 7A, 1B and 1D and TMD on 6A, 7A and 1D. The variability (R(2)) explained by these QTL ranged from 11.9 to 30.6% for TMD, 11.4 to 30.8% for SCC, and 10.5 to 33.5% for PMD. Molecular markers Xbarc113 and AFLP AGCTCG-347 on chromosome 6A, Xbarc121 and Xbarc49 on 7A, gwm18 and Bin1130 on 1B, Bin178 and Bin81 on 2B and Bin747 and Bin1546 on 1D were associated with these QTL. CONCLUSION The identified QTL can be used for marker assisted selection in breeding wheat for improved heat tolerance in Ventnor or Karl 92 genetic background.
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Affiliation(s)
- Shyamal Krishna Talukder
- Forage Improvement Division, The Samuel Roberts Noble Foundation, Ardmore, OK, 73401, USA.
- Department of Agronomy, Kansas State University, Manhattan, KS, 66506, USA.
| | - Md Ali Babar
- Department of Agronomy, University of Florida, Gainesville, Florida, USA.
| | | | - Jesse Poland
- Department of Plant Pathology, Kansas State University, Manhattan, KS, 66506, USA.
| | | | - Robert Bowden
- USDA/ARS/Hard Winter Wheat Genetics Research Unit, Kansas State University, Manhattan, KS, 66506, USA.
| | - Allan Fritz
- Department of Agronomy, Kansas State University, Manhattan, KS, 66506, USA.
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24
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Talukder SK, Babar MA, Vijayalakshmi K, Poland J, Prasad PVV, Bowden R, Fritz A. Mapping QTL for the traits associated with heat tolerance in wheat (Triticum aestivum L.). BMC Genet 2014; 15:97. [PMID: 25384418 PMCID: PMC4234900 DOI: 10.1186/s12863-014-0097-4] [Citation(s) in RCA: 103] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2014] [Accepted: 08/29/2014] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND High temperature (heat) stress during grain filling is a major problem in most of the wheat growing areas. Developing heat tolerant cultivars has become a principal breeding goal in the Southern and Central Great Plain areas of the USA. Traits associated with high temperature tolerance can be used to develop heat tolerant cultivars in wheat. The present study was conducted to identify chromosomal regions associated with thylakoid membrane damage (TMD), plasmamembrane damage (PMD), and SPAD chlorophyll content (SCC), which are indicative of high temperature tolerance. RESULTS In this study we have reported one of the first linkage maps in wheat using genotype by sequencing SNP (GBS-SNP) markers to extreme response to post anthesis heat stress conditions. The linkage map was comprised of 972 molecular markers (538 Bin, 258 AFLPs, 175 SSRs, and an EST). The genotypes of the RIL population showed strong variation for TMD, SCC and PMD in both generations (F10 and F9). Composite interval mapping identified five QTL regions significantly associated with response to heat stress. Associations were identified for PMD on chromosomes 7A, 2B and 1D, SCC on 6A, 7A, 1B and 1D and TMD on 6A, 7A and 1D. The variability (R(2)) explained by these QTL ranged from 11.9 to 30.6% for TMD, 11.4 to 30.8% for SCC, and 10.5 to 33.5% for PMD. Molecular markers Xbarc113 and AFLP AGCTCG-347 on chromosome 6A, Xbarc121 and Xbarc49 on 7A, gwm18 and Bin1130 on 1B, Bin178 and Bin81 on 2B and Bin747 and Bin1546 on 1D were associated with these QTL. CONCLUSION The identified QTL can be used for marker assisted selection in breeding wheat for improved heat tolerance in Ventnor or Karl 92 genetic background.
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Affiliation(s)
- Shyamal Krishna Talukder
- Forage Improvement Division, The Samuel Roberts Noble Foundation, Ardmore, OK, 73401, USA.
- Department of Agronomy, Kansas State University, Manhattan, KS, 66506, USA.
| | - Md Ali Babar
- Department of Agronomy, University of Florida, Gainesville, Florida, USA.
| | | | - Jesse Poland
- Department of Plant Pathology, Kansas State University, Manhattan, KS, 66506, USA.
| | | | - Robert Bowden
- USDA/ARS/Hard Winter Wheat Genetics Research Unit, Kansas State University, Manhattan, KS, 66506, USA.
| | - Allan Fritz
- Department of Agronomy, Kansas State University, Manhattan, KS, 66506, USA.
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25
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Prediction of the determinants of thermal stability by linear discriminant analysis: the case of the glutamate dehydrogenase protein family. J Theor Biol 2014; 357:160-8. [PMID: 24853273 DOI: 10.1016/j.jtbi.2014.05.013] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2013] [Revised: 05/07/2014] [Accepted: 05/08/2014] [Indexed: 11/21/2022]
Abstract
Little is known about the determinants of thermal stability in individual protein families. Most of the knowledge on thermostability comes, in fact, from comparative analyses between large, and heterogeneous, sets of thermo- and mesophilic proteins. Here, we present a multivariate statistical approach aimed to detect signature sequences for thermostability in a single protein family. It was applied to the glutamate dehydrogenase (GDH) family, which is a good model for investigating this peculiar process. The structure of GDH consists of six subunits, each of them organized into two domains. Formation of ion-pair networks on the surface of the protein subunits, or increase in the inter-subunit hydrophobic interactions, have been suggested as important factors for explaining stability at high temperatures. However, identification of the amino acid changes that are involved in this process still remains elusive. Our approach consisted of a linear discriminant analysis on a set of GDH sequences from Archaea and Bacteria (33 thermo- and 36 mesophilic GDHs). It led to detection of 3 amino acid clusters as the putative determinants of thermal stability. They were localized at the subunit interface or in close proximity to the binding site of the NAD(P)(+) coenzyme. Analysis within the clusters led to prediction of 8 critical amino acid sites. This approach could have a wide utility, in the ligth of the notion that each protein family seems to adopt its own strategy for achieving thermostability.
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26
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Gross SM, Martin JA, Simpson J, Abraham-Juarez MJ, Wang Z, Visel A. De novo transcriptome assembly of drought tolerant CAM plants, Agave deserti and Agave tequilana. BMC Genomics 2013; 14:563. [PMID: 23957668 PMCID: PMC3765226 DOI: 10.1186/1471-2164-14-563] [Citation(s) in RCA: 82] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2013] [Accepted: 08/13/2013] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND Agaves are succulent monocotyledonous plants native to xeric environments of North America. Because of their adaptations to their environment, including crassulacean acid metabolism (CAM, a water-efficient form of photosynthesis), and existing technologies for ethanol production, agaves have gained attention both as potential lignocellulosic bioenergy feedstocks and models for exploring plant responses to abiotic stress. However, the lack of comprehensive Agave sequence datasets limits the scope of investigations into the molecular-genetic basis of Agave traits. RESULTS Here, we present comprehensive, high quality de novo transcriptome assemblies of two Agave species, A. tequilana and A. deserti, built from short-read RNA-seq data. Our analyses support completeness and accuracy of the de novo transcriptome assemblies, with each species having a minimum of approximately 35,000 protein-coding genes. Comparison of agave proteomes to those of additional plant species identifies biological functions of gene families displaying sequence divergence in agave species. Additionally, a focus on the transcriptomics of the A. deserti juvenile leaf confirms evolutionary conservation of monocotyledonous leaf physiology and development along the proximal-distal axis. CONCLUSIONS Our work presents a comprehensive transcriptome resource for two Agave species and provides insight into their biology and physiology. These resources are a foundation for further investigation of agave biology and their improvement for bioenergy development.
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Affiliation(s)
- Stephen M Gross
- DOE Joint Genome Institute, Walnut Creek, CA, USA
- Genomics Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA, 94720, USA
| | - Jeffrey A Martin
- DOE Joint Genome Institute, Walnut Creek, CA, USA
- Genomics Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA, 94720, USA
| | - June Simpson
- Department of Genetic Engineering, CINVESTAV, Irapuato, Guanajuato, Mexico
| | | | - Zhong Wang
- DOE Joint Genome Institute, Walnut Creek, CA, USA
- Genomics Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA, 94720, USA
| | - Axel Visel
- DOE Joint Genome Institute, Walnut Creek, CA, USA
- Genomics Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA, 94720, USA
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27
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Graham LD, Glattauer V, Li D, Tyler MJ, Ramshaw JAM. The adhesive skin exudate of Notaden bennetti frogs (Anura: Limnodynastidae) has similarities to the prey capture glue of Euperipatoides sp. velvet worms (Onychophora: Peripatopsidae). Comp Biochem Physiol B Biochem Mol Biol 2013; 165:250-9. [PMID: 23665109 DOI: 10.1016/j.cbpb.2013.04.008] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2013] [Revised: 04/09/2013] [Accepted: 04/30/2013] [Indexed: 11/30/2022]
Abstract
The dorsal adhesive secretion of the frog Notaden bennetti and the prey-capture "slime" ejected by Euperipatoides sp. velvet worms look and handle similarly. Both consist largely of protein (55-60% of dry weight), which provides the structural scaffold. The major protein of the onychophoran glue (Er_P1 for Euperipatoides rowelli) and the dominant frog glue protein (Nb-1R) are both very large (260-500 kDa), and both give oddly "turbulent" electrophoresis bands. Both major proteins, which are rich in Gly (16-17 mol%) and Pro (7-12 mol%) and contain 4-hydroxyproline (Hyp, 4 mol%), have the composition of intrinsically unstructured proteins. Their propensities for elastomeric or amyloid structures are discussed in light of Er_P1's large content of intrinsically disordered long tandem repeats. The low carbohydrate content of both glues is consistent with conventional protein glycosylation, which in the N. bennetti adhesive was explored by 2D PAGE. The N-linked sugars of Nb-1R appear to prevent inappropriate self-aggregation. Some peptide sequences from Nb-1R are presented. Overall, there are enough similarities between the frog and the velvet worm glues to suspect that they employ related mechanisms for setting and adhesion. A common paradigm is proposed for amphibian and onychophoran adhesives, which, if correct, points to convergent evolution.
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Affiliation(s)
- Lloyd D Graham
- CSIRO Animal, Food and Health Sciences, PO Box 52, North Ryde, Sydney, New South Wales 1670, Australia.
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Thomas JC, O'Hara JM, Hu L, Gao FP, Joshi SB, Volkin DB, Brey RN, Fang J, Karanicolas J, Mantis NJ, Middaugh CR. Effect of single-point mutations on the stability and immunogenicity of a recombinant ricin A chain subunit vaccine antigen. Hum Vaccin Immunother 2013; 9:744-52. [PMID: 23563512 DOI: 10.4161/hv.22998] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
There is great interest in the design and development of highly thermostable and immunogenic protein subunit vaccines for biodefense. In this study, we used two orthogonal and complementary computational protein design approaches to generate a series of single-point mutants of RiVax, an attenuated recombinant ricin A chain (RTA) protein subunit vaccine antigen. As assessed by differential scanning calorimetry, the conformational stabilities of the designed mutants ranged from 4°C less stable to 4.5°C more stable than RiVax, depending on solution pH. Two more thermostable (V18P, C171L) and two less thermostable (T13V, S89T) mutants that displayed native-like secondary and tertiary structures (as determined by circular dichroism and fluorescence spectral analysis, respectively) were tested for their capacity to elicit RTA-specific antibodies and toxin-neutralizing activity. Following a prime-boost regimen, we found qualitative differences with respect to specific antibody titers and toxin neutralizing antibody levels induced by the different mutants. Upon a second boost with the more thermostable mutant C171L, a statistically significant increase in RTA-specific antibody titers was observed when compared with RiVax-immunized mice. Notably, the results indicate that single residue changes can be made to the RiVax antigen that increase its thermal stability without adversely impacting the efficacy of the vaccine.
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Affiliation(s)
- Justin C Thomas
- Macromolecule and Vaccine Stabilization Center; Department of Pharmaceutical Chemistry; University of Kansas; Lawrence, KS USA
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Holder T, Basquin C, Ebert J, Randel N, Jollivet D, Conti E, Jékely G, Bono F. Deep transcriptome-sequencing and proteome analysis of the hydrothermal vent annelid Alvinella pompejana identifies the CvP-bias as a robust measure of eukaryotic thermostability. Biol Direct 2013; 8:2. [PMID: 23324115 PMCID: PMC3564776 DOI: 10.1186/1745-6150-8-2] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2012] [Accepted: 01/11/2013] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Alvinella pompejana is an annelid worm that inhabits deep-sea hydrothermal vent sites in the Pacific Ocean. Living at a depth of approximately 2500 meters, these worms experience extreme environmental conditions, including high temperature and pressure as well as high levels of sulfide and heavy metals. A. pompejana is one of the most thermotolerant metazoans, making this animal a subject of great interest for studies of eukaryotic thermoadaptation. RESULTS In order to complement existing EST resources we performed deep sequencing of the A. pompejana transcriptome. We identified several thousand novel protein-coding transcripts, nearly doubling the sequence data for this annelid. We then performed an extensive survey of previously established prokaryotic thermoadaptation measures to search for global signals of thermoadaptation in A. pompejana in comparison with mesophilic eukaryotes. In an orthologous set of 457 proteins, we found that the best indicator of thermoadaptation was the difference in frequency of charged versus polar residues (CvP-bias), which was highest in A. pompejana. CvP-bias robustly distinguished prokaryotic thermophiles from prokaryotic mesophiles, as well as the thermophilic fungus Chaetomium thermophilum from mesophilic eukaryotes. Experimental values for thermophilic proteins supported higher CvP-bias as a measure of thermal stability when compared to their mesophilic orthologs. Proteome-wide mean CvP-bias also correlated with the body temperatures of homeothermic birds and mammals. CONCLUSIONS Our work extends the transcriptome resources for A. pompejana and identifies the CvP-bias as a robust and widely applicable measure of eukaryotic thermoadaptation.
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Affiliation(s)
- Thomas Holder
- Max-Planck-Institute for Developmental Biology, Spemannstr, 35, Tübingen, D-72076, Germany
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Li Y, Fang J. PROTS-RF: a robust model for predicting mutation-induced protein stability changes. PLoS One 2012; 7:e47247. [PMID: 23077576 PMCID: PMC3471942 DOI: 10.1371/journal.pone.0047247] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2012] [Accepted: 09/11/2012] [Indexed: 11/19/2022] Open
Abstract
The ability to improve protein thermostability via protein engineering is of great scientific interest and also has significant practical value. In this report we present PROTS-RF, a robust model based on the Random Forest algorithm capable of predicting thermostability changes induced by not only single-, but also double- or multiple-point mutations. The model is built using 41 features including evolutionary information, secondary structure, solvent accessibility and a set of fragment-based features. It achieves accuracies of 0.799,0.782, 0.787, and areas under receiver operating characteristic (ROC) curves of 0.873, 0.868 and 0.862 for single-, double- and multiple- point mutation datasets, respectively. Contrary to previous suggestions, our results clearly demonstrate that a robust predictive model trained for predicting single point mutation induced thermostability changes can be capable of predicting double and multiple point mutations. It also shows high levels of robustness in the tests using hypothetical reverse mutations. We demonstrate that testing datasets created based on physical principles can be highly useful for testing the robustness of predictive models.
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Affiliation(s)
- Yunqi Li
- Applied Bioinformatics Laboratory, The University of Kansas, Lawrence, Kansas, United States of America
| | - Jianwen Fang
- Applied Bioinformatics Laboratory, The University of Kansas, Lawrence, Kansas, United States of America
- * E-mail:
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Fang Y, Middaugh CR, Fang J. In silico classification of proteins from acidic and neutral cytoplasms. PLoS One 2012; 7:e45585. [PMID: 23049817 PMCID: PMC3458925 DOI: 10.1371/journal.pone.0045585] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2012] [Accepted: 08/23/2012] [Indexed: 01/05/2023] Open
Abstract
Protein acidostability is a common problem in biopharmaceutical and other industries. However, it remains a great challenge to engineer proteins for enhanced acidostability because our knowledge of protein acidostabilization is still very limited. In this paper, we present a comparative study of proteins from bacteria with acidic (AP) and neutral cytoplasms (NP) using an integrated statistical and machine learning approach. We construct a set of 393 non-redundant AP-NP ortholog pairs and calculate a total of 889 sequence based features for these proteins. The pairwise alignments of these ortholog pairs are used to build a residue substitution propensity matrix between APs and NPs. We use Gini importance provided by the Random Forest algorithm to rank the relative importance of these features. A scoring function using the 10 most significant features is developed and optimized using a hill climbing algorithm. The accuracy of the score function is 86.01% in predicting AP-NP ortholog pairs and is 76.65% in predicting non-ortholog AP-NP pairs, suggesting that there are significant differences between APs and NPs which can be used to predict relative acidostability of proteins. The overall trends uncovered in the study can be used as general guidelines for designing acidostable proteins. To best of our knowledge, this work represents the first systematic comparative study of the acidostable proteins and their non-acidostable orthologs.
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Affiliation(s)
- Yaping Fang
- Applied Bioinformatics Laboratory, The University of Kansas, Lawrence, Kansas, United States of America
| | - C. Russell Middaugh
- Department of Pharmaceutical Chemistry, The University of Kansas, Lawrence, Kansas, United States of America
| | - Jianwen Fang
- Applied Bioinformatics Laboratory, The University of Kansas, Lawrence, Kansas, United States of America
- * E-mail:
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Li Y, Zhang J, Tai D, Middaugh CR, Zhang Y, Fang J. PROTS: a fragment based protein thermo-stability potential. Proteins 2011; 80:81-92. [PMID: 21976375 DOI: 10.1002/prot.23163] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2011] [Revised: 07/18/2011] [Accepted: 07/31/2011] [Indexed: 12/30/2022]
Abstract
Designing proteins with enhanced thermo-stability has been a main focus of protein engineering because of its theoretical and practical significance. Despite extensive studies in the past years, a general strategy for stabilizing proteins still remains elusive. Thus effective and robust computational algorithms for designing thermo-stable proteins are in critical demand. Here we report PROTS, a sequential and structural four-residue fragment based protein thermo-stability potential. PROTS is derived from a nonredundant representative collection of thousands of thermophilic and mesophilic protein structures and a large set of point mutations with experimentally determined changes of melting temperatures. To the best of our knowledge, PROTS is the first protein stability predictor based on integrated analysis and mining of these two types of data. Besides conventional cross validation and blind testing, we introduce hypothetical reverse mutations as a means of testing the robustness of protein thermo-stability predictors. In all tests, PROTS demonstrates the ability to reliably predict mutation induced thermo-stability changes as well as classify thermophilic and mesophilic proteins. In addition, this white-box predictor allows easy interpretation of the factors that influence mutation induced protein stability changes at the residue level.
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Affiliation(s)
- Yunqi Li
- Applied Bioinformatics Laboratory, the University of Kansas, Lawrence, Kansas 66047, USA
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King AC, Woods M, Liu W, Lu Z, Gill D, Krebs MRH. High-throughput measurement, correlation analysis, and machine-learning predictions for pH and thermal stabilities of Pfizer-generated antibodies. Protein Sci 2011; 20:1546-57. [PMID: 21710487 PMCID: PMC3190149 DOI: 10.1002/pro.680] [Citation(s) in RCA: 55] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2011] [Revised: 05/17/2011] [Accepted: 06/12/2011] [Indexed: 12/16/2022]
Abstract
Generating stable antibodies is an important goal in the development of antibody-based drugs. Often, thermal stability is assumed predictive of overall stability. To test this, we used different internally created antibodies and first studied changes in antibody structure as a function of pH, using the dye ANS. Comparison of the pH(50) values, the midpoint of the transition from the high-pH to the low-pH conformation, allowed us for the first time to rank antibodies based on their pH stability. Next, thermal stability was probed by heating the protein in the presence of the dye Sypro Orange. A new data analysis method allowed extraction of all three antibody unfolding transitions and showed close correspondence to values obtained by differential scanning calorimetry. T(1%) , the temperature at which 1% of the protein is unfolded, was also determined. Importantly, no correlations could be found between thermal stability and pH(50) , suggesting that to accurately quantify antibody stability, different measures of protein stability are necessary. The experimental data were further analyzed using a machine-learning approach with a trained model that allowed the prediction of biophysical stability using primary sequence alone. The pH stability predictions proved most successful and were accurate to within pH ±0.2.
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Affiliation(s)
| | | | | | | | | | - Mark R H Krebs
- Pfizer Global BioTherapeutic Technologies87 CambridgePark Drive, Cambridge, Massachusetts 02140
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Distance-dependent statistical potentials for discriminating thermophilic and mesophilic proteins. Biochem Biophys Res Commun 2010; 396:736-41. [PMID: 20451495 DOI: 10.1016/j.bbrc.2010.05.005] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2010] [Accepted: 05/02/2010] [Indexed: 11/22/2022]
Abstract
Identification of the characteristic structural patterns responsible for protein thermostability is theoretically important and practically useful but largely remains an open problem. These patterns may be revealed through comparative study on thermophilic and mesophilic proteins that have distinct thermostability. In this study, we constructed several distance-dependant potentials from thermophilic and mesophilic proteins. These potentials were then used to evaluate the structural difference between thermophilic and mesophilic proteins. We found that using the subtraction or division of the potentials derived from thermophilic and mesophilic proteins can dramatically increase the discriminatory ability. This approach revealed that the ability to distinct the subtle structural features responsible for protein thermostability may be effectively enhanced through rationally designed comparative study.
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