\r\n\tSynthetic zeolites can be formed from different raw materials and among these many wastes represent some interesting sources due to their chemical and mineralogical composition. Today, a large number of different types of waste resulting from many human activities are produced in the world (e.g. industrial, municipal, agricultural waste) and most of them are deposed of in landfills thus determining a great environmental problem.
\r\n
\r\n\tThis book intends to provide the reader with a comprehensive overview of the current state-of-the-art on the possibility to transform the different types of waste materials into useful products, zeolites, through conventional processes and innovative methods. The aim is to demonstrate that waste can be a problem or a resource depending on how it is managed.
",isbn:"978-1-80356-426-5",printIsbn:"978-1-80356-425-8",pdfIsbn:"978-1-80356-427-2",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,isNomenclature:!1,hash:"3ed0dfd842de9cd1143212415903e6ad",bookSignature:"Dr. Claudia Belviso",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11561.jpg",keywords:"Structure, Properties, Natural Material, Synthetic Product, Type, Composition, Production, Disposal, Hydrothermal Method, Pre-fusion Process, Sonication, Multiple Steps",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"February 25th 2022",dateEndSecondStepPublish:"March 25th 2022",dateEndThirdStepPublish:"May 24th 2022",dateEndFourthStepPublish:"August 12th 2022",dateEndFifthStepPublish:"October 11th 2022",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"3 months",secondStepPassed:!0,areRegistrationsClosed:!0,currentStepOfPublishingProcess:4,editedByType:null,kuFlag:!1,biosketch:"Since 2002, Dr. Claudia Belviso has been carrying out research activity in the field of mineralogy and geochemistry aimed at environmental protection. She is responsible for the research activity on zeolite synthesis from waste materials and natural sources which has allowed her to be the inventor of an International Patent, publish numerous scientific articles in peer-reviewed journals, and carry out scientific research in national and international projects.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"61457",title:"Dr.",name:"Claudia",middleName:null,surname:"Belviso",slug:"claudia-belviso",fullName:"Claudia Belviso",profilePictureURL:"https://mts.intechopen.com/storage/users/61457/images/system/61457.jpg",biography:"Claudia Belviso is a researcher at the Institute of Methodologies of Environmental Analysis (IMAA) of CNR. After graduating in Geological Sciences and qualifying as a professional geologist, she earned a Ph.D. in Earth Sciences. Since 2002 has been carrying out her research activity in the field of mineralogy and geochemistry aimed at environmental protection. She is responsible for the research activity on zeolite synthesis from waste materials and natural sources as well as their application to solving environmental problems and as new raw material. These research activities have allowed her to be the inventor of an International Patent, publish numerous scientific articles in peer-reviewed journals, participate in national and international conferences, take part in the organization of international congresses, and carry out scientific research in national and international projects.",institutionString:"National Research Council",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"National Research Council",institutionURL:null,country:{name:"Italy"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"8",title:"Chemistry",slug:"chemistry"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"453622",firstName:"Tea",lastName:"Jurcic",middleName:null,title:"Ms.",imageUrl:"//cdnintech.com/web/frontend/www/assets/author.svg",email:"tea@intechopen.com",biography:null}},relatedBooks:[{type:"book",id:"5306",title:"Zeolites",subtitle:"Useful Minerals",isOpenForSubmission:!1,hash:"eec7f864baf093058440c0f56072a7cf",slug:"zeolites-useful-minerals",bookSignature:"Claudia Belviso",coverURL:"https://cdn.intechopen.com/books/images_new/5306.jpg",editedByType:"Edited by",editors:[{id:"61457",title:"Dr.",name:"Claudia",surname:"Belviso",slug:"claudia-belviso",fullName:"Claudia Belviso"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1591",title:"Infrared Spectroscopy",subtitle:"Materials Science, Engineering and Technology",isOpenForSubmission:!1,hash:"99b4b7b71a8caeb693ed762b40b017f4",slug:"infrared-spectroscopy-materials-science-engineering-and-technology",bookSignature:"Theophile Theophanides",coverURL:"https://cdn.intechopen.com/books/images_new/1591.jpg",editedByType:"Edited by",editors:[{id:"37194",title:"Dr.",name:"Theophile",surname:"Theophanides",slug:"theophile-theophanides",fullName:"Theophile Theophanides"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3161",title:"Frontiers in Guided Wave Optics and Optoelectronics",subtitle:null,isOpenForSubmission:!1,hash:"deb44e9c99f82bbce1083abea743146c",slug:"frontiers-in-guided-wave-optics-and-optoelectronics",bookSignature:"Bishnu Pal",coverURL:"https://cdn.intechopen.com/books/images_new/3161.jpg",editedByType:"Edited by",editors:[{id:"4782",title:"Prof.",name:"Bishnu",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3092",title:"Anopheles mosquitoes",subtitle:"New insights into malaria vectors",isOpenForSubmission:!1,hash:"c9e622485316d5e296288bf24d2b0d64",slug:"anopheles-mosquitoes-new-insights-into-malaria-vectors",bookSignature:"Sylvie Manguin",coverURL:"https://cdn.intechopen.com/books/images_new/3092.jpg",editedByType:"Edited by",editors:[{id:"50017",title:"Prof.",name:"Sylvie",surname:"Manguin",slug:"sylvie-manguin",fullName:"Sylvie Manguin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"371",title:"Abiotic Stress in Plants",subtitle:"Mechanisms and Adaptations",isOpenForSubmission:!1,hash:"588466f487e307619849d72389178a74",slug:"abiotic-stress-in-plants-mechanisms-and-adaptations",bookSignature:"Arun Shanker and B. 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1. Introduction
The robot Inverse Kinematics problem involves finding the joints’ variable values that match input parameters of position and direction of the end effector [1]. These matched variable values will ensure that subsequent robot control will follow the desired trajectory. This is one of the important issues in the robotic field because it is related to other aspects such as motion planning, dynamic analysis and control [2]. Traditionally, there are several methods to resolve inverse kinematics problem for robots such as: geometry method is the method using geometric and trigonometric relationships to solve; the iterative method is often required inversion of a Jacobian matrix, etc. However, when applying these methods to solve the IK problem for robots, especially with redundant robots, it is often much more complicated and time-consuming. The reason is the nonlinearity of the formulas and the geometry between the workspace and the joint space. In addition, the difficult point is in the singularity, the multiple solutions of these formulas as well as the necessary variation of the formulas corresponding to the changes of different robot structures [3, 4, 5].
In addition to those existing methods of solving the IK problems, in recent years, the application of meta-heuristic optimization algorithms has become increasingly common. 8 optimization algorithms applied in [5] in the cases of a single point or a whole trajectory endpoint. The simulation results showed that the PSO algorithm can effectively solve the IK problem. In [6] the authors used algorithms such as ABC, PSO, and FA to solve the inverse kinematic requirement for Kawasaki RS06L 6-DoF robot in the task of picking and place objects. Ayyıldız et al. compared the results of all IK tests for a 4-DOF serial robot using 4 different algorithms: PSO, QPSO, GA and GSA [7]. Two versions of the PSO algorithm have been used to solve the IK problem for robots with a number of degrees of freedom from 9 to 180 [8]. In recent research [9], Malek et al. used PSO algorithm to handle inverse kinematics for a 7-DoF robot arm manipulator. The study mentioned both the requirements for the location and the direction of the endpoint, however, it only solved for 2 different end effector positions. Laura et al., in [10] used DE algorithm for the IK problem of 7-DoF robot. The problem was solved for specific points, but the quality evaluation parameters such as endpoint position deviation, execution time as well as the values of the joints’ variable did not reach impressive quality. Ahmed El-Sherbiny et al. [11] proposed to use ABC variant algorithm for solving inverse kinematics problem in 5 DoFs robot arm. Serkan Dereli et al. [12] used a quantum behave partial algorithm (QPSO) for a 7-DoF serial manipulator and compare the results with other techniques such as firefly algorithm (FA), PSO and ABC.
In this study, the self-adaptive control parameters in Differential Evolution (ISADE) algorithm, that developed [13, 14] by authors, was applied to solve the problem of inverse kinematic for a 7-DOF serial robot. To compare the results, this IK problem was also handled by applying DE and PSO algorithms. In addition, the study also compared the results in the application of the above algorithms with the search space improvement of joints’ variables (Pro-ISADE, Pro-PSO and Pro-DE) [15].
The remainder of the paper is divided into the following sections: Section II describes the experimental model. The theory of the PSO, DE and ISADE algorithms as well as the algorithms with improved search area, Pro-PSO, Pro-DE and Pro-ISADE, will then be presented in Section III. Section IV covers scenarios and object functions that will be applied to calculate the IK. The results after applying the algorithm are shown and compared in Section V. Finally, the conclusions are outlined in Section VI.
2. Testing model
The residual driven robots have many advantages such as easy escape from obstacles, flexible movement as well as a large operation space. However, their disadvantage is the complexity of the robot structure [16]. In this study, a serial redundant manipulator robot was used to evaluate the algorithm in resolving the inverse kinematics requirements. The simplified robot model was shown in the Figure 1. As in the figure, this serial robot manipulator is of type 7R (R: Revolute). The parameters of the D-H table of the robot are given in Table 1.
Figure 1.
The 7-DFO robot Scheme and coordinate systems used in the study.
Joint
θ(rad)
d(mm)
a(mm)
α(rad)
1
-π <q1 <π
d1 = 500
0
- π/2
2
-π/2 <q2<π/6
0
l2 = 200
π/2
3
-π/2 <q3 <2π/3
0
l3 = 250
- π/2
4
-π/2<q4 <π/2
0
l4 = 300
π/2
5
-π/2<q5 <π/2
0
l5 = 200
- π/2
6
-π/2<q6 <π/2
0
l6 = 200
0
7
-π/2 <q7 <π/2
d7=5
l7 = 100
0
Table 1.
D-H parameters.
The homogeneous transformation matrix can be used to obtain the forward kinematics of the robot manipulator, using the DH parameters in Eq. (1) [17].
Where, T07 is matrix to produce a Catesian coordinate for any seven joint values. In the Eq. (10), xEyEzE denote the elements of position vector whereas, nxnynzsxsyszaxayaz are the rotational elements of transformation matrix. In this study, only position vectors were used to calculate the distance error. After the computation, the end-effector coordinate in the manipulation space is determined by:
When solving the problem of inverse kinematics, with the endpoint coordinates as on the left side of Eq. (10), we need to find the values of the matching variable q. However, according to the Equation, the number of equations is much less than the number of variables. This makes it very difficult to find a unique and exact matching solution. In this study, ISADE algorithm and ISADE with searching space improvement algorithm (Pro-ISADE) were used to solve the IK problem for the robot. To compare the results, the study also used some other optimization algorithms such as PSO, DE as well as Pro-PSO and Pro-DE to solve the same IK problem for the robot above.
3. Applied algorithms and object functions
3.1 PSO
Particle swarm optimization was developed flying Kenney and Eberhart [18, 19] based on observing the moving characteristics of bird flock and fish school. In this algorithm the individual of the population is called particle. The particle of the population (Called swarm) can move in its space and offer a potential solution. Particles can memorize best condition and find and exchange information to other members. Each particle in the population has two characteristics: position and velocity. Starting with the particle population, each particle monitors its coordinates and updates position and speed according to the best solution for each iteration. The velocity and position values are shown in the following equation:
In particular, xxi,vi are the position and velocity of the particle i-th, respectively; d is number of dimension; w is the inertia weight factor, c1and c2are cognitive learning rate and social learning rate, respectively; pi is the pbest value of i_th particle; What is gbest value of the population.
3.2 DE
Differential Evolution (DE) algorithm is a population-based stochastic optimization algorithm recently introduced. DE works with two populations; old generation and new generation of the same population. The population is randomly initialized within the initial parameter bounds individuals in the population has two characteristics: position and velocity. Starting with the individual population, each individual monitors its coordinates and updates position and speed according to the best solution for each iteration. Velocity values (V) is randomly created in one of eight ways:
In particular, F is Scaling factor, r1,r2,r3,r4,r5 is random solution, r1,r2,r3,r4,r5∈123…Np and r1≠r2≠r3≠r4≠r5≠i, Xbest is population filled with the best member.
Position values new (U) shown in the following Equation:
U=X.∗FMmpo+V.∗FMmuiE13
FMmui are all random numbers <0.9, FMmpo is inverse mask to FMmui.
3.3 ISADE
In the [13, 14], we suggested to develop a new version of DE algorithm that can automatically adapt the learning strategies and the parameters settings during evolution. The main ideas of the ISADE algorithm are summarized below.
3.3.1 Mutation operator
ISADE probabilistically selects one out of several available learning strategies in the mutation operator for each individual in the current population. In this research, we select three learning strategies in the mutation operator as candidates: “DE/best/1/bin”, “DE/best/2/bin” and “DE/rand to best/1/bin” that are respectively expressed as:
Where: i=12…NP;j=1…D are current population and design variable, respectively.
"DE/Randtobest/1/bin" strategy usually demonstrates good diversity while the "DE/best/1/bin" and "DE/best/2/bin"strategy show good convergence property, which we also observe in our trial experiments.
3.3.2 Adaptive scaling factor F and crossover control parameter CR
In the ISADE algorithm, the author suggested to use the sigmoid function to control neighborhood parameter. we sort the particles by estimating their fitness. A ranked particle is labeled with ranked number and assigned F that corresponds with its number. The formula for F by sigmoid function as following:
Fi=11+expα∗i−NP2NPE17
Where: α,idenote the gain of the sigmoid function, particle of the ithin NP, respectively.
For better performance of ISADE, the scale factor F should be high in the beginning to have much exploration and after curtain generation F needs to be small for proper exploitation. Thus, we proposed to calculate the F as follow:
Where: Fmax,Fmin,iter,itermaxandniter are the lower boundary condition of F, upper boundary condition of F, current generation, maximum generation and nonlinear modulation index, respectively.
The author introduced a novel approach of scale factorFi of each particle with their fitness in Eq. (15). Thus, in one generation the value of Fiiteri=1…NP are not the same for all particles in the population rather they are changed in each generation. The final value of scale factor for each generation is calculated as follow:
Fiteri=Fi−Fitermean2E19
Where iter=1,…,itermaxandi=1,…,NP
The control parameter CRis adapted as following:
CRiG+1=rand2ifrand1≤τCRiGothewiseE20
The ISADE algorithm was summarized as in the Figure 2.
Figure 2.
ISADE Flowchart.
3.4 Cost functions and Algorithms with searching space improvement
As mention in the introduction part, the disadvantage of many studies using optimization algorithms to solve the IK problem of redundant robots is to focus on the results related to the optimal running process such as execution time, number of generation … but have not yet considered the feasibility of the joints’ variable values. In order to overcome these drawbacks, the author of this research [15] proposed this algorithm that is explained as following: The solution to improve the continuity of joints’ values constrains the initialization domain of X. This help the program to achieve the dual goal of increasing calculation speed, accuracy and ensuring continuity for the value of joints’ variables. In this algorithm, firstly the robot from any position moves to the first point of the trajectory. With this first point, the initialization values for the particles are randomly selected in the full Range of Motion (RoM) of joints. In addition, the target function in this case has the form:
where the values qikandqik (i = 1) are the joints’ variable values at the original position and 1st point on the trajectory, respectively; (xi, yi, zi) and (xei, yei, zei) are the End-effector coordinates for the i-point (i = 1) found by the algorithm and the desired End-effector coordinates; (Rxi, Ryi, Rzi) and (Rxei, Ryei, Rzei) are corresponding rotation cosine angles performing orientation of the end-effector which are found by Algorithm and orientation of the desired end-effector; a, b are penalty coefficients. Cost function as Eq. (21) ensures the energy spent in the joints to reach the 1st desired position is minimized. Besides, it also minimizes the distance error between the actual and desired end-effector position. The condition to stop for points of trajectory is that the Cost Func.1 value is less than value of e or the number of iterations reaches 600 and the number of times algorithm running <10.
After calculating for 1st point of the trajectory, the remaining points are calculated with a search limitation around the previous optimal joints’ values. By using this suggested range, the program’s search space will be limited while ensuring the continuity of the joint variables. In this case, the target function is still the same as the function of 1st point, but it has coefficient a = 0.
4. Scenarios
4.1 Scenario 1
In Scenario 1, an endpoint in the workspace were randomly selected; the PSO; DE and ISADE algorithms were then applied to solve the required problem. The purpose of this Scenario is to compare the convergence speed of the three algorithms. In this case, since the initial and the desired endpoints can be far apart, the Pro-PSO; Pro-DE and Pro-ISADE algorithms cannot be applied.
4.2 Scenario 2
In this case, the robot was required to move the endpoint through 100 points in the robot’s working space one after another. These points were selected at random for the purpose of testing the effectiveness of each algorithm with many distinct points. Similar to the previous case, in this Scenario we also only applied the algorithms PSO, DE and ISADE with the solution space of the matching variable which limits the motion of these joints.
4.3 Scenario 3
The manipulator robot was required to move the end effector following a certain trajectory. The selected trajectory is spiral, and it is described by the following function:
xE=200∗cos2∗zE/100yE=200∗sin2∗zE/100zE=n∗piE22
Where: xEyEzE is the desired endpoint coordinate on the trajectory. With 6 algorithms of PSO, Pro ISO, DE, Pro-DE and ISADE, Pro-ISADE, the comparison of the results on the same graph is not favorable. Therefore, the study divided this case into two smaller Scenarios:
Scenario 3.1: Results when using ISADE algorithm comparing with results from PSO and DE algorithms.
Scenario 3.2: Compare the results using Pro-ISADE algorithm with the results getting from Pro-PSO and Pro-DE algorithms
And then results from Scenario 3.1 were be compared with the results from Scenario 3.2.
5. Simulation and results
5.1 Experimental setup
The main task of this study is to find the optimal value of the joints’ variable to ensure the end effector of robots can reach the desired points. The desired point positions of the Scenario 2 and 3 are shown as the Figure 3. Research using the ISADE and Pro-ISADE algorithm, which were developed by the authors [13, 14, 15], to get simulation results of inverse kinematics problem and then compared it with the results when using PSO, DE and Pro-PSO, Pro-DE algorithms. When solving the IK problem for the 7-DoF serial robot manipulator, the study focused on three main aspects. The first of these is the sensitivity of the solution - in the other word, the amount distance error of end effector is minimum. The second criterion was the execution time. In order to avoid the endless loop, the maximum numbers of generation itermaxwere set as 600, 600 and 130 for PSO (Pro-PSO), DE (Pro-DE) and ISADE (Pro-ISADE), respectively. And the final aspect is the searching space of joints’ variables. Normally, Normally, almost all studies have been using the Range of Motion (RoM) of joints for its boundary space. Our algorithm [15] proposed to use the searching space of current generation is around previous optimal joints’ values. In the Table 2, the ubsi+1andlbsi+1 are the joints’ upper and lower boundary of the current generation.C1andC2 are weights of personal best and global best, respectively. w is the inertia weight. ρ is the number of run for each algorithm to choose the best result. Besides, after some trial runs for the algorithms, we noticed that our ISDE algorithm gave much better results than DE and the least was the PSO algorithm. Thus, when setting up the maximum distance error by the fitness value setting for the end effector position, the study set the value of 1e−14m; 1e−15m and 1e−17m for PSO (Pro-PSO); DE (Pro-DE) and ISADE (Pro-ISADE), respectively or that can be seen in the Table 2. In this research, the proposed and other methods were tested in the two different Scenarios. Both the first and second Scenario was coded by Matlab version 2019a and run on the computer equipped with an Intel Core i5-4258U @2.4GHz processor and 8 GB Ram memory.
Figure 3.
Testing scenarios. (a) Scenario 2: 100 random points in workspace; (b) Scenario 3: 100 points on a spiral trajectory.
Optimization parameters used in PSO, Pro-PSO, DE Pro-DE, and ISADE, Pro-ISADE.
5.2 Scenario 1 results
After applying the inverse kinematic problem processing algorithms for a single endpoint, the results are shown in Figures 4 and 5. All algorithms are able to handle the inverse kinetics problem, but the best results have been obtained with the ISADE algorithm as shown in Table 3.
Figure 4.
End effector distance error vs. generations in Scenario 1.
Figure 5.
End effector distance error vs. time in Scenario 1.
Max. Iteration
Position error (m)
Calculation time (s)
PSO
85
2.6815e-04
0.0941
DE
85
5.7514e-10
0.0715
ISADE
85
2.8422e-13
0.0490
Table 3.
Comparison of ISADE with other algorithms.
Figures 4 and 5 show convergence speed of algorithms corresponding to the number of iterations and processing time, respectively. The results show that the processing speed of the ISADE algorithm is the best, followed by the DE algorithm and finally with the PSO algorithm. In Table 3 the study of selecting stop conditions for algorithms is the maximum number of iterations of 85 rounds. After 10 runs, the best results are shown in the table. The ISADE algorithm gives the best processing results in terms of both quality and speed. The endpoint deviation can reach 2.8422e-13 (m) in 0.049 (s) time. For the PSO algorithm, it can handle the reverse kinematic problem for the end point with an accuracy of 2.6815e-4 in a period of 0.0941 (s). and, 5.7514e-10 (m) and 0.0715 (s) are the accuracy of end effector and execution time for DE algorithm.
5.3 Scenario 2 results
As mentioned above, in this Scenario 2, algorithms was used to resolve inverse kinematics problem for 100 randomly chosen points within the workspace of the robot. When processed at each point, the end effector started at the same initial position of [0 0 0 0 0 0 0] for 7 serial joints values. Because the end effector points all come from the same starting point to go to each of the 100 points, the study only used the ISADE algorithm and compares with the results from PSO and DE algorithms without using the Pro-ISADE algorithm as well as Pro-DE and Pro-PSO.
The 100 randomly selected points were shown in the Figure 3a. Results when applying ISADE and the other algorithm were presented in the Figure 6. As shown in the Figure, all algorithms have solved problem well. In particular, with the ISADE algorithm, although the fitness value in experimental setup required 1000 and 100 times higher than the required by applying the PSO and DE algorithms, respectively, it was not only guaranteed required precision but also showed faster processing speed and fewer iterations compared to the 2 other algorithms. Specifically, as shown in Figure 6b and c and especially Table 4, the average execution time when using ISADE to solve IK of each points was around 0.0685 second, while this value of the PSO and DE algorithm were on average 0.2307 (s) and 0.0978 (s) respectively. The main reason for this, as seen in Figure 6b and Table 4, was the number of generations to reach the optimal values much higher in PSO algorithm and slightly higher in DE algorithm, compared to in ISADE algorithm. Specifically, the PSO algorithm needed an average of 413.24 and the DE algorithm needed average of 124.45 loops to find a solution, while the ISADE algorithm used an average of 85.63 loops. Another remarkable thing is although there was not much difference in the number of iterations to solve the problem between the two algorithms DE and ISADE, but the ISADE algorithm still gave a processing speed of 1.42 times higher than DE algorithm though required 100 times more accuracy for the ISADE algorithm. This demonstrated the very high efficiency of the ISADE algorithm when it was applied to handle inverse kinematics problem for this robot. In short, in the optimization study for randomly chosen points in working space, the ISADE algorithm presented the best algorithm to resolve the IK requirement in term of accuracy, iteration and execution time.
Figure 6.
Results for Scenario 2. (a) Distance error. (b) Execution time. (c) Number of generations.
PSO
DE
ISADE
Fitness value
1e-14
1e-15
1e-17
Avg. error
7.3016e-13
2.2938e-13
2.1644e-14
STD
2.0415e-13
5.991e-14
6.2125e-15
Avg. iteration
413.24
124.45
85.63
Avg. execution time
0.2307
0.0978
0.0685
Table 4.
Comparative results in case 2.
5.4 Scenario 3 results
In Scenario 2, the end effector moved through the 100 points located on a specific trajectory that was defined in Eq. (22) and shown in Figure 3b. The main difference between Scenario 2 and Scenario 3 is that, instead of after solving each IK problem for each point, the end effector goes back to the original point to continue processing for the next points like in Scenario 2, in Scenario 3 the end effector starts from previous point in order to calculate for the next point. Stemming from this feature, the searching space of joints’ variable also starts previous optimal joints’ values. However, depending on the searching space we have 2 smaller cases such as:
Scenario 3.1: Searching spaces for joints’ variables are RoMs. Then, like the Scenario 2, the study compared the results when using the ISADE algorithm with the results when using the PSO and DE algorithms.
Scenario 3.2: Searching spaces for joints’ variables are around the previous optimal joints’ values. The study compared the results when using Pro-ISADE algorithm with when using Pro-PSO and Pro-DE algorithms.
The results were presented in the Figure 7 and Table 5. Similar to the Scenario 2, although the experimental installation required the ISADE (and Pro-ISADE) algorithm to be 100 and 1000 times more accurate than the algorithm DE (Pro-DE) and PSO (Pro PSSO), respectively, all of 6 algorithms gave appropriated solutions for all the points in the trajectory. It can be seen that, in both cases 3.1 and 3.2 the ISADE and Pro-ISADE algorithms showed the best ability to resolve the inverse kinematics problems in all 3 aspects: accuracy, execution time and number of generations. More specifically, in Scenario 3.1, when searching space for joints’ variables were RoMs, the average achieved accuracies for ISADE was around 2.0748e-14 (m) that is much better than the values of 7.5404e-13 (m) and 2.2260e-13 (m) corresponding for PSO and DE algorithms. Although the ISADE algorithm was set to a fitness value to achieve such higher accuracy, the execution time of the algorithm was still below the time of PSO and DE algorithm. These average execution time values were 0.0679 (s); 0.0845 (s) and 0.3478 (s) second for ISADE, DE and Pro algorithm, respectively. The above results can be partly explained based on the number of necessary iterations that each algorithm was needed to find the optimal values of joints variables. From Figure 6c, it showed that, when solving the IK problem for almost points in the spiral trajectory, the ISADE method used the least number of iterations. The Table 5 presented more clearly, on the average each point in the trajectory the ISADE needed 85.19 generations to find the optimal values, these means number for DE and PSO algorithm are 125.44 and 391.1
Figure 7.
Results for Scenario 3.1. (a) Distance error. (b) Execution time. (c) Number of generations.
PSO
Pro-PSO
DE
Pro-DE
ISADE
Pro-ISADE
Scenario 1
Fitness value
1e-9
Not applied
1e-10
Not applied
1e-12
Not applied
Avg. error (m)
2.4151e-09
Not applied
6.9655e-10
Not applied
6.8362e-11
Not applied
STD (m)
5.8117e-10
Not applied
2.0075e-10
Not applied
2.3796e-11
Not applied
Avg. iteration
357.91
Not applied
76.54
Not applied
64.34
Not applied
Avg. execution time (s)
0.2931
Not applied
0.1115
Not applied
0.0455
Not applied
Scenario 3.1 (Italic values) and Scenario 3.2
Fitness value
1e-14
1e-14
1e-15
1e-17
1e-12
Avg. error (m)
7.4140e-13
7.4650e-13
2.2260e-13
2.2950e-13
2.0748e-14
2.0103e-14
STD (m)
1.9574e-13
1.9736e-13
6.5615e-14
6.1330e-14
1.0414e-14
9.8913e-15
Avg. iteration
429.950
407.8800
125.4400
114.2700
85.1900
75.2300
Avg. execution time (s)
0.3604
0.2576
0.1015
0.0845
0.0679
0.0554
Table 5.
Comparative results between all cases.
Italics were used to differentiate the results of Scenario 3.1 and 3.2.
In Scenario 3.2, the searching space for joints’ variables were around previous optimal values that were set up as in the Table 2. Similar to the Scenario 3.1, all of the comparison parameters gotten from using Pro-ISADE algorithm were better than that values from Pro-DE and Pro-PSO algorithms. These parameters are described in the as well as Table 5. In order to comparison between Scenario 3.1 with Scenario 3.2, all average parameters was shown in the Table 5. From all comparison, the proposed ISADE or Pro-ISADE were always proved the best solution to solve the inverse kinematics requirements for the manipulator robot. Moreover, Table 5 also showed that, the Pro-ISADE had better performance compared to ISADE. By using Pro-ISADE algorithm, it reduced all of parameters including distance error, execution time and number of generations.
Another very important result gotten from Scenario 3.2 is the quality of joints’ values. Figure 8 show the joints’ value in two cases of using ISADE in Scenario 3.1 and using Pro-ISADE in Scenario 3.2. It is clear that the joints’ value in the Scenario 3.1 were change dramatically. On the contrary, the values of joints in Scenario 3.2 changed continuously and slowly. The quality of joints variable values as Figure 9b, that received by using Pro-ISADE, will ensure feasibility in the next stages of calculation and design for the robot. These values, along with the values of speed, acceleration, as well as the weight parameters of the stages, will be used in the dynamic problem as well as in future control.
Figure 8.
Joint variables’ results. (a) Joint variables’ values in Scenario 3.1 using ISADE algorithm. (b) Joint variables’ values in Scenario 3.2 using Pro-ISADE algorithm.
Figure 9.
Results for Scenario 3.2. (a) Distance error. (b) Execution time. (c) Number of generations.
In short, after comparing the results of Scenario 3.1 and 3.2, it is possible to conclude that the ISADE algorithm and Pro-ISADE are the best solutions to solve the IK problem for the robot in all aspects: endpoint accuracy, execution time and number of generation. The Pro-ISADE algorithm not only guarantees the above parameters, it also ensures the quality of the joints’ variables to serve the next computational and design stages.
Table 5 summarizes results of the average error, the standard deviation of error (STD), the average iteration and the average execution time of all Scenarios. As in the table, the algorithms of ISADE and Pro-ISADE got the better results than the other algorithms.
As mentioned at the beginning of this article, intelligent optimization techniques have been using more and more popular in difficult and complex tasks including the IK problem for redundant manipulator robots. Table 6 shows some studies used meta-heuristic optimization algorithms to resolve the inverse kinematics task for different robot models. The Table presents: the used algorithm for the IK calculation, selected manipulators for the test, the algorithms that are used to comparison. For example, El-Sherbiny et al. [11] used the Adaptive Neuro Fuzzy Inference System (ANFIS) algorithm to calculate the IK problem of a 5 DOF robot, and then compared results with GA algorithm. Both algorithms could get the appropriate solutions, but ANFIS algorithm proved to be the best one. The comparison also shows that a number of studies [12, 22, 23], using optimal algorithms such as PSO, ABC, Q-PSO … handle the inverse kinetic requirements for the model of 7 degrees of freedom. All the used algorithms have proven the ability to handle the problem, but it is not difficult to see that most of these studies have the lower accuracy and processing speed than the ISADE as well as the Pro-ISADE algorithm proposed in this study.
Italics were used to differentiate the results of Scenario 3.1 and 3.2.
6. Conclusions
In this research, inverse kinematics problem for a 7 degree of freedom serial robot manipulator was implemented to prove the accuracy and efficiency of the self-adaptive control parameters in Differential Evolution (ISADE) and the ISADE algorithm with searching space improvement (Pro-ISADE) algorithm. To evaluate the effectiveness of the two algorithms above, the results obtained from the ISADE algorithm as well as Pro-ISADE were compared with the results from the PSO (Pro-PSO) and DE (Pro-DE) algorithm. Experiments were performed with three Scenarios. In the first Scenario, an endpoint in the workspace is randomly selected. The purpose of this Scenario is to compare the convergence speed of the three algorithms. In the second Scenario, algorithm was used to calculate inverse kinematics of the robot for 100 points randomly selected in the working space. The aim of this Scenario 2 is to test the accuracy and efficiency of the algorithm when the end effector started at the same position, it went to any point in working space. Meanwhile, in the third Scenario, the algorithms solved the inverse kinematics problem when the end effector of the robot moved point to point that are located on a spiral trajectory in the workspace. The implementation experiments have shown, the ISADE algorithm gave much better results than other algorithms in term of: accuracy, execution time and number of generation. Besides, by improving the searching boundary for joints’ variable, the Pro-ISADE, Pro-DE and Pro-PSO also improve the accuracy as well as processing speed and especially the quality of the value of the joints variable compared to the ISADE, DE and PSO, respectively. These optimal joints’ values ensure the feasibility of the dynamic and control problem in the future. In short, with ISADE algorithm as well as Pro-ISADE, they have handled the inverse kinematic requirement very effectively both in term of accuracy and computation time. The Pro-ISADE algorithm not only improves the above two factors, but also improves the quality of the joints’ variables.
Conflict of interest
“The authors declare no conflict of interest.”
\n',keywords:"differential evolution (DE), particle swarm optimization (PSO), inverse kinematic (IK), degree of freedom (DOF), optimization",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/76036.pdf",chapterXML:"https://mts.intechopen.com/source/xml/76036.xml",downloadPdfUrl:"/chapter/pdf-download/76036",previewPdfUrl:"/chapter/pdf-preview/76036",totalDownloads:212,totalViews:0,totalCrossrefCites:0,totalDimensionsCites:0,totalAltmetricsMentions:0,impactScore:0,impactScorePercentile:45,impactScoreQuartile:2,hasAltmetrics:0,dateSubmitted:"November 17th 2020",dateReviewed:"March 10th 2021",datePrePublished:"March 31st 2021",datePublished:"September 15th 2021",dateFinished:"March 31st 2021",readingETA:"0",abstract:"In this study, the Self-adaptive strategy algorithm for controlling parameters in Differential Evolution algorithm (ISADE) improved from the Differential Evolution (DE) algorithm, as well as the upgraded version of the algorithms has been applied to solve the Inverse Kinetics (IK) problem for the redundant robot with 7 Degree of Freedom (DoF). The results were compared with 4 other algorithms of DE and Particle Swarm Optimization (PSO) as well as Pro-DE and Pro-PSO algorithms. These algorithms are tested in three different Scenarios for the motion trajectory of the end effector of in the workspace. In the first scenario, the IK results for a single point were obtained. 100 points randomly generated in the robot’s workspace was input parameters for Scenario 2, while Scenario 3 used 100 points located on a spline in the robot workspace. The algorithms were compared with each other based on the following criteria: execution time, endpoint distance error, number of generations required and especially quality of the joints’ variable found. The comparison results showed 2 main points: firstly, the ISADE algorithm gave much better results than the other DE and PSO algorithms based on the criteria of execution time, endpoint accuracy and generation number required. The second point is that when applying Pro-ISADE, Pro-DE and Pro-PSO algorithms, in addition to the ability to significantly improve the above parameters compared to the ISADE, DE and PSO algorithms, it also ensures the quality of solved joints’ values.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/76036",risUrl:"/chapter/ris/76036",book:{id:"10416",slug:"robotics-software-design-and-engineering"},signatures:"Trung Nguyen and Tam Bui",authors:[{id:"340117",title:"Dr.",name:"Trung",middleName:null,surname:"Nguyen",fullName:"Trung Nguyen",slug:"trung-nguyen",email:"trung.nguyenthanh@hust.edu.vn",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"340952",title:"Dr.",name:"Ngoc-Tam",middleName:null,surname:"Bui",fullName:"Ngoc-Tam Bui",slug:"ngoc-tam-bui",email:"tambn@shibaura-it.ac.jp",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Shibaura Institute of Technology",institutionURL:null,country:{name:"Japan"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Testing model",level:"1"},{id:"sec_3",title:"3. Applied algorithms and object functions",level:"1"},{id:"sec_3_2",title:"3.1 PSO",level:"2"},{id:"sec_4_2",title:"3.2 DE",level:"2"},{id:"sec_5_2",title:"3.3 ISADE",level:"2"},{id:"sec_5_3",title:"3.3.1 Mutation operator",level:"3"},{id:"sec_6_3",title:"3.3.2 Adaptive scaling factor F and crossover control parameter CR",level:"3"},{id:"sec_8_2",title:"3.4 Cost functions and Algorithms with searching space improvement",level:"2"},{id:"sec_10",title:"4. Scenarios",level:"1"},{id:"sec_10_2",title:"4.1 Scenario 1",level:"2"},{id:"sec_11_2",title:"4.2 Scenario 2",level:"2"},{id:"sec_12_2",title:"4.3 Scenario 3",level:"2"},{id:"sec_14",title:"5. Simulation and results",level:"1"},{id:"sec_14_2",title:"5.1 Experimental setup",level:"2"},{id:"sec_15_2",title:"5.2 Scenario 1 results",level:"2"},{id:"sec_16_2",title:"5.3 Scenario 2 results",level:"2"},{id:"sec_17_2",title:"5.4 Scenario 3 results",level:"2"},{id:"sec_19",title:"6. Conclusions",level:"1"},{id:"sec_23",title:"Conflict of interest",level:"1"}],chapterReferences:[{id:"B1",body:'Köker R, Çakar T. A neuro-genetic simulated annealing approach to the inverse kinematics solution of robots: a simulation based study. Eng Comput. 2016;32:553–565'},{id:"B2",body:'Huang HC, Chen CP, Wang PR (2012) Particle swarm optimization for solving the inverse kinematics of 7-DOF robotic manipulators. IEEE international conference on systems, man, and cybernetics. Seoul, Korea, pp 3105–3110'},{id:"B3",body:'Rubio JJ, Bravo AG, Pacheco J, Aguilar C (2014) Passivity analysis and modeling of robotic arms. 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Hanoi University of Science and Technology, Vietnam
Hanoi University of Science and Technology, Vietnam
Shibaura Institute of Technology, Japan
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1. Introduction
Epstein-Barr virus (EBV), a ubiquitous gamma-herpesvirus, infects the vast majority of the worldwide human population. This virus was initially discovered in cultured lymphoma cells from patients with Burkitt’s lymphoma (BL) in 1964 [1]. During the primary infection, EBV infects epithelial cells of the oropharynx where it actively replicates and also infects B cells where it establishes a life-long latency in the form of an episome located in the host cell nucleus. During latency, EBV may produce nine viral latency proteins, including six so-called “Epstein-Barr Nuclear Antigens” (EBNA1, -2, -3A, -3B, -3C, and -LP), involved in transcriptional regulation, and three “Latent Membrane Proteins” (LMP1, -2A, and -2B), mimicking signals needed for B cell maturation, as well as two small noncoding RNAs (EBER-1 and EBER-2), BamHI-A rightward transcripts (BARTs), and miRNAs. Four different latency programs can be identified, based on the proteins that are expressed (Table 1). EBV primary infection, which occurs more often in childhood, is usually asymptomatic in children, whereas it may be responsible for infectious mononucleosis (IM) in teenagers or young adults in western countries. In addition to this nonmalignant disease, EBV can also be associated with diverse malignant pathologies. In particular, EBV is involved in the development of several malignancies of lymphoid origin including endemic Burkitt’s lymphoma [2], nasal NK/T lymphoma [3], some Hodgkin’s lymphoma [4], and B- or T-cell lymphoproliferations in immunocompromised patients [5]. It is also implicated in epithelial malignancies such as undifferentiated nasopharyngeal carcinoma (NPC) [6] and 10% of cases of gastric carcinoma [7]. Although populations from all geographic areas are infected by the virus, the incidence of the pathologies in which it occurs varies significantly depending on the region [8]. For example, BL occurs mainly in children living in sub-Saharan Africa [9], and the prevalence of NPC is particularly high in adults living in Southern China, Southeast Asia, and Northern Africa [10]. The differences observed in the geographic distribution of these pathologies suggest that there could be various genetic variants of EBV, of different global distributions, and with different levels of transforming capacity. This question of a specific disease variant is raised by many authors and is still being debated. In this chapter, we wish to take inventory of the state of knowledge concerning the variability observed on the most mutated genes among all EBV genes and the possible implications in human pathology.
Program
EBV expressed proteins
Active promoters
B cell type
Latency III
Growth
EBNA-1, -2, -3A, -3B, -3C, -LP
Initially Wp
Naive B cells
LMP-1, -2A-, -2B
Then Cp
LMP promoters
EBER-1 and -2p
Latency II
Default
EBNA-1
Qp, EBER-1 and -2p
LMP-1, -2A, -2B
LMP promoters
Latency I
Latency
EBNA-1
Qp, EBER-1 and -2p
Resting B cells
Latency 0
No protein or LMP-2A
LMP-2Ap
Memory B cells
Table 1.
Proteins expressed during the different latency programs.
2. Evolving knowledge of the EBV genome
The fact that the viral genome is relatively large (175 kb), that it is made up of DNA, therefore less variable than if it was an RNA genome, and that it carries repetitive regions, limited its sequencing for a long time. The first published sequences were small fragments of the B95-8 genome; then, the entire B95-8 genome was sequenced in 1984 [11]. The B95-8 strain was the first cultured EBV cell line able to secrete large amounts of viral particles into the culture medium. It was originally obtained from a spontaneous human lymphoblastoid cell line (LCL) established from a North American case of infectious mononucleosis, the 883L cell line, whose virus was used to transform lymphocytes from a cotton top marmoset. Since it was the first strain with a fully published genome, B95-8 has been extensively studied and mapped for transcripts, promoters, and open reading frames.
This first EBV whole genome sequencing was followed by others, and complete viral genome sequences of the cell lines AG876, originating from a Ghanaian case of African BL [12] and GD1, obtained from cord B cells infected with EBV from saliva of an NPC patient in Guangzhou, China [13] were published. Sequences of some genes, mainly latency genes, were also studied, especially in lines established from patients [14, 15]. B95-8, GD1, and AG876 were sequenced by conventional shotgun sequencing (Sanger’s method). The comparison of sequences obtained for various cell lines revealed the existence of two types of EBV: type 1 or A, of which B95-8 can be considered as the prototype, and type 2 or B, exemplified by AG876. The main difference between the two types concerns the EBNA2 gene, with only 70% identity at the nucleotide level and 54% identity in the protein sequence [16]. Additional variations have also been observed in the EBNA3 genes, but to a lesser extent: 10, 12, and 19% of base pair differences for EBNA3A, 3B, and 3C, respectively [17]. The comparison of viral sequences also highlighted that the B95-8 cell line has a significant 11.8 kb deletion (positions 139,724–151,554) corresponding to some of the BART miRNA genes, one of the origins of lytic replication [11], the LF2 and LF3 genes, and a part of the LF1 gene. More complete sequence comprising the B95-8 sequence supplemented with a Raji fragment at the level of deletion has been constructed. It was annotated in 2010 as RefSeq HHV4 (EBV) sequence NC_007605 and is now used as a wild-type strain reference [18].
As adaptation of the virus to in vitro culture is possible, thus generating a bias in the results, some authors have preferred to sequence the viral genome directly in samples from patients. Therefore, the sequences GD2, from a Guangzhou NPC biopsy, and HKNPC1, from a Hong Kong NPC biopsy, were published [19, 20], both using a more recent sequencing technique, “next generation sequencing” (NGS). This technology can be used directly on samples or after enrichment, which avoids artifacts due to cellular DNA. Enrichment can be achieved by PCR or cloning into F-factor plasmids, but most frequently, it is carried out using target DNA capture by hybridization. NGS delivers a wealth of information and requires extensive bioinformatic analysis. This technology has made it possible to rapidly increase the number of fully sequenced viral genomes originating from healthy subjects or patients and thus obtain more information.
3. The most variable regions of the genome
Authors who sequenced the entire viral genome and analyzed the genomic variations came to the conclusion that the latent genes harbored the highest numbers of nonsynonymous mutations [20, 21, 22, 23, 24]. For example, Liu et al. [25] compared the sequences of nine strains of EBV to GD1, of which they were most closely related, and showed that latency genes were the most mutated. In this study, latent and tegument genes were found to harbor 58.4 to 84.3% of all nonsynonymous mutations detected for each genome. Santpere et al. [26] found that latent genes were twice as mutated as lytic genes. The observation that the latent genes harbor more nucleotide diversity than lytic genes was made regardless of the type of pathology: nasopharyngeal carcinoma [20, 21], NK/T lymphoma [27], endemic Burkitt’s lymphoma [22], Hodgkin’s lymphoma [22], posttransplant lymphoproliferative disease [22], gastric carcinoma [25], lung carcinoma [23], and also strains originating from infectious mononucleosis [22] or healthy subjects [26]. Why latent genes are the most variable is not clear today. By analyzing their data according to the Yang model [28], Santpere et al. [26] showed that the lytic genes had an evolutionary constraint close to that of the host: a strong purifying selection was objectified for 11 lytic genes. However, signatures of accelerated protein evolution rates were found in coding regions related to virus attachment and entry into host cells. The latency genes, on the other hand, show a positive selection, perhaps in relation to the MHC, which can be the cause of their large diversity. Changes in amino acids (aa) often occur in immune epitopes. Amino acid changes in CD8+ epitopes were described in all latent proteins, while changes in CD4+ epitopes were shown only for EBNA1 and -2 and LMP1 and -2 [20]. However, most codons of the EBNA3 gene under positive selection are not cytotoxic T-lymphocyte epitopes: either there are epitopes not described to date or the selection relates to other functionalities. The selection of mutants may depend on a difference in immunity in relation to the geography and/or capacity of a strain to infect and persist.
4. Variability of main latency proteins
After the virus enters a host cell, the genome circularizes through recombination of the terminal repeats (TRs) located at each end of the genome to form an episome that will be chromatinized and methylated in the same way as the human genome. Latent transcription programs in B cells are due to the differential activity of epigenetically regulated promoters and take place in three successive waves. The EBNA2 and EBNA-LP, as well as BHRF1, a bcl2 homolog, are the first viral proteins to be expressed, under the dependence of Wp promoter. The two expressed EBNAs and the cellular factor recombination signal-binding protein for immunoglobulin Kappa J region (RBP-Jk) activate then the Cp promoter, which drives the expression of all of the EBNA proteins, while Wp becomes progressively hypermethylated; the transcription will gradually be under Cp control. Subsequently, LMP1, LMP2A, and LMP2B proteins are expressed due to activation of their respective promoters. During latency I or II, Qp promoter controls EBNA1 expression, and Cp methylation is responsible for the five other EBNA silencing. Methylation does not control the Qp promoter, which is switched off by binding to a repressor protein.
As previously developed, latency proteins show the most sequence variations, and among them, EBNA1, EBNA2, EBNA-LP, and LMP1 are the most mutated. The main properties of these proteins are reported in Table 2.
4.1 EBNA1
EBNA1, expressed in both latent and lytic EBV infections, was the first EBV protein detected. EBNA1, whose structure (Figure 1) and functions have largely been studied [29, 30], is a 641 aa protein. However, EBNA1 proteins frequently exhibit size variations due to differing numbers of gly-ala repeats (aa 89–325). During latency, EBNA1 is the only protein expressed in all forms of latency in proliferating cells and also in all EBV associated malignancies. EBNA1, which acts as a homodimer, is essential for initiating EBV episome replication before mitosis, once per cell cycle, and mitotic segregation of EBV episomes, thus for the maintenance of EBV episome in latently infected cells [31]. The EBNA1 DNA-binding domain is essential but not sufficient for the replication function, and the N-terminal half of EBNA1 is also required. Two EBNA1 regions (aa 8–67 and aa 325–376) are particularly important for this activity, and the point mutations G81 or G425 enhance EBNA1-dependent DNA replication. Inversely, the EBNA1 aa 395–450 region mediates an interaction with the human ubiquitin-specific protease, USP7, which may negatively regulate replication. The partitioning of EBV episomes in two dividing cells requires two viral components: the ori P FR element and EBNA1, mainly the central Gly-Arg region aa 325–376 and secondarily the aa 8–67 sequence. EBNA1 also activates the expression of other latency genes participating in immortalization: the regions involved are the central Gly-Arg sequence and the 61–89 region. Interaction with the recognition sites located on FR, DS of ori P, and Bam-HI-Q takes place through binding sites located in the C-terminal of EBNA1 (aa 459-607), sequence which also mediates the dimerization of EBNA1 (aa 504–604). Through its interaction with both human casein kinase CK2 (aa 383–395) and cellular ubiquitin-specific protease USP7 (aa 442–448), EBNA1 is also able to disrupt promyelocytic leukemia protein (PML) bodies and degrade PML. In addition to its role in latent infection, EBNA1 can therefore participate in lytic infection by overcoming suppression by PML proteins [32]. Indeed, PML proteins and nuclear bodies were found to suppress lytic infection by EBV. Recently [33], organization in an oligomeric hexameric ring form was described for the EBNA1 DNA-binding domain, the oligomeric interface pivoting around residue T585. Mutations occurring on this residue had both positive and negative effects on EBNA1-dependent DNA replication and episome maintenance.
Figure 1.
Schematic representation of basic structure of EBNA1 protein with the different motifs and their position. Gly-Arg: region rich in Gly-Arg; Gly-Ala: Gly-Ala repeats; CK2: interaction with human casein kinase, CK2; USP7: interaction with the human ubiquitin specific protease, USP7; DNA binding: DNA-binding domain; Dimerization: region that mediates the dimerization of EBNA1. The different mutations discussed are noted.
Based on polymorphisms observed at 15 codons, Bhatia et al. [14] reported two strains named P (prototype) and V (variant), each having two subtypes defined by the aa at position 487 (P-ala, P-thr, V-pro, and V-leu). They detected mostly the P-thr and the V-leu variants, respectively, in African and American BL tumors, but these findings were not confirmed by another group who reported different spectra of EBNA1 subtypes according to different geographical areas in both healthy patients and BL tumors [34]. A fifth subtype, V-val, was later recognized in South-East Asia and was found to be prevalent in NPC samples by numerous authors [20, 35, 36, 37]. These findings suggest that the V-val variant might adapt particularly well to the nasopharyngeal epithelium or that this strain possesses an increased oncogenic potential. Indeed, most of the variant codons, localized in the DNA-binding domain, may have an impact on the EBV phenotype resulting in impaired ability to transform B-lymphocytes [30]. However, other reports observed that this subtype had no tumor-specific expression [38], and it is likely that it probably represents a dominant EBNA1 subtype in Asian regions, not found in other areas of the world [8, 23, 25]. The P-thr subtype is the most commonly observed in peripheral blood of American and African subjects as well as in African tumors. In our experience, P-thr is also the most prevalent in France and particularly in the course of lymphoproliferative diseases.
Apart from these mutations, others have been reported. For example, Borozan et al. [39] looked at gastric carcinomas and mainly found two mutations already described in NPC, H418L and A439T, located outside the DNA-binding domain and common in both NPC and GC but uncommon in other EBV isolates, from lymphomas or healthy subjects. They also described a new mutation, T85A, positioned in the region required for transcriptional activation of other latency genes and thus able to modify this function. Wang et al. [23] described the substitution T585I. T585 is subject to substitutions, and T585 polymorphism is found frequently in NPC tumors and Burkitt’s lymphoma. T585I was previously found, and this strain was defective in replication and maintenance of the viral episome [40], as well as deficient in suppressing lytic cycle gene transcription and lytic DNA replication.
In summary, EBNA1 V-val variant seems to be a geographic variant almost exclusively present in South-East Asia. Conversely, mutations T85 and T585, which occur in functional regions of the protein, could have biological consequences and especially the substitution T585I, which promotes lytic replication and is found in NPC.
4.2 EBNA2
EBNA2, a 487 aa protein, is expressed in vivo during latency III shortly after infection of B cells or in lymphomas occurring in immunocompromised patients and in LCL. As mentioned above, the variations in EBNA2 make it possible to classify EBV as types 1 and 2 (or A and B) since only 70% identity at the nucleotide level and 54% homology in the protein sequence were observed. The overall structure of the EBNA2 protein (Figure 2) is characterized by poly-P and poly-RG areas, this last one being a protein-protein and protein-nucleic acid interaction domain important for efficient cell growth transformation, and nine regions conserved throughout the gene [41]. EBNA2 acts principally as a transcription factor and contains three categories of domains critical for its transcription regulation function: transactivation domains (TAD), self-association domains (SAD), and nuclear localization signals (NLS). EBNA2 does not bind directly to DNA. It uses cell proteins as adapters to access viral or cellular enhancer and promoter sites. The C-terminal TAD (aa 448–471) is able to recruit components of basic transcriptional machinery as well as chromatin modifiers and can bind to the viral coactivator EBNA-LP, while the N-terminal TAD (aa 1–58) cannot bind EBNA-LP, although its activity can be enhanced by this protein. Two SADs (aa 1–58 and 97–121), separated by the poly-proline stretch, were identified in the N-terminal region [42]. An additional third one has been reported, localized in a nonconserved region, and flanked by the second SAD and the adapter region [43]. EBNA2 contributes to B-cell immortalization, and it has been demonstrated that type 1 EBV, which is predominantly found in EBV-associated diseases, immortalizes B cells in vitro much more efficiently than type 2 [44], which is predominantly determined by sequence variation in the C-terminus of EBNA2 [45]. During the early events of EBV infection in resting B cells, EBNA2 initiates the transcription of a cascade of primary and secondary viral and cellular target genes and therefore is responsible for the initiation of immortalization by reprogramming the resting state into a proliferative state. For this, EBNA2 interacts with chromatin remodelers and as a transcription factor cofactor [46]. Mühe et al. [47] demonstrated that the first 150 N-terminal aa of EBNA2 are important for the initiation of immortalization. EBNA2 is also involved in immortalization maintenance; the region implicated here (aa 295–378) includes the conserved regions CR5 (aa 295–307) and CR6 (aa 320–326), particularly important for this function. CR5 mediates the contact between EBNA2 and SKIP (Ski-interacting protein), and CR6 is the CBF1 (C promoter-binding factor 1) or RBP-Jk targeting domain. Mechanisms to initiate and maintain B cell immortalization are not completely understood today.
Figure 2.
Schematic representation of basic structure of EBNA2 protein with the different motifs and their position. The two transactivation domains (TADs), the three self-association domains (SADs), and the two nuclear localization signals (NLSs) are mentioned. Poly P: area rich in P; PolyRG: area rich in RG; CR5: conserved region 5, which interacts with SKIP (Ski-interacting protein); CR6: conserved region 6, which interacts with CBF1 (C promoter-binding factor 1). The different mutations discussed are mentioned.
Wang et al. [41], working on 25 EBV-associated GCs, 56 NPCs, and 32 throat washings from healthy donors in Northern China, described 4 EBNA2 subtypes according to the presence of a deletion, namely subtypes E2-A (no aa deletion), E2-B (aa 294Q deletion), E2-C (aa 357K and 358G deletion), and E2-D (aa 357K, 358G, and 294Q deletion). The E2-A subtype exhibited six nonsilent mutations, P291T, R413G, I438L, E476G, P484H, and I486T; the substitution P291T was present in six NPC E2-D and six NPC E2-C. The substitution R413G was detected in E2-C for one patient. They found that E2-A and E2-C were dominant in the samples they analyzed and that the E2-D pattern was detected only in the NPC specimens. The mutation R163M was detected in all samples. This mutation has previously been described worldwide and in different diseases.
Mutations 357 and 358 occurred in the RG domain (aa 335–362), a downregulator of EBNA2 activation of the LMP1 promoter [48]. Moreover, aa 357–363 (KGKSRDK) constitutes the PKC phosphorylation site, which can reduce the amounts of EBNA2/CBF1 complex formed. EBNA2 is suspected to be involved in the development of malignancies as a result of sequence variations most frequently affecting its regulation function.
Interestingly, EBNA2 entire-gene deletion has been shown in some endemic BL cell lines such as P3HR1, Daudi, Sav, Oku, and Ava [49]; it remains to determine if this deletion occurs classically in vivo in African BL.
In short, geographic variants were not formally demonstrated for EBNA2. Among the described mutations, the most interesting are those occurring in the PKC phosphorylation site because they can activate the Cp and/or LMP1p and thus increase the production of latency proteins.
4.3 EBNA-LP (EBNA-leader protein)
EBNA-LP, like EBNA2 and concomitantly with EBNA2, is expressed shortly after the infection of B cells in healthy individuals as well as in EBV-related malignant diseases in immunodeficient patients and LCLs. EBNA-LP acts mostly as a coactivator of the transcriptional activator EBNA2, thus inducing the expression of some cellular genes, including cyclin D2 [50], or viral genes, that is, LMP1 [51], LMP2b, and Cp and therefore having an important role in B cell immortalization. EBNA-LP also can directly interact with several cell proteins such as tumor suppressors or proteins involved in apoptosis or cell cycle regulation.
EBNA-LP is comprised of a variable number of 66 aa repetitive units, corresponding to the variable number of W1 and W2 exons located in the EBV internal repeat IR1, followed by a unique 45 aa domain, encoded by two unique 3′ exons Y1 and Y2 (Figure 3). Therefore, EBNA-LP protein may vary in size according to the number of W1–W2 repeats contained in each EBV isolate. By convention, the protein annotation is based on a single W repeat isoform (Figure 4). In this configuration, the protein has 110 aa. Conserved regions were identified in the N extremity of the protein (CR1 to CR3, respectively, aa 11–33, 45–52, and 55–62, implicated in EBNA2 binding), and in the C-terminal region (CR4 and CR5, respectively, aa 76–82 and 101–110). CR3 and a serine within W2 (S35) were demonstrated to be important for EBNA2 coactivation. EBV-mediated B cell immortalization maps to the W1W2 repeated domains and requires at least two IR1 repetitions to be effective, but a number greater than or equal to 5 is optimal [53]. Some interactions with cell proteins are mediated by the repeated W1W2 N-terminus [54]. EBNA-LP gene transcription initiates from the W promoter (Wp) residing in each IR1 repeat during the early stages of infection, and multiple EBNA-LP protein isoforms are produced. During the later stages of infection and in LCLs, transcription initiates from the C promotor (Cp) [55]. The level of transcription initiated by Cp compared to Wp varies according to different circumstances [56].
Figure 3.
Schematic representation of the IR1 region of EBV genome (according to Ref. [52]). The promoters Wp, Cp, and Qp are represented, as well as the different proteins expressed according to the stage of infection.
Figure 4.
Sequence of EBNA-LP protein, with the position of the corresponding exons opposite. Conserved regions are represented as well as the key positions. Phosphorylated serins are mentioned by an asterisk.
About 15% of BL tumors host a virus, which uses exclusively the W promoter, expressing an EBV atypical latency program [49], harboring EBNA1, EBNA3A, 3B, 3C, and a truncated form of EBNA-LP. In these cases, EBV genome lacks the EBNA2gene and the unique Y1Y2 exons of EBNA-LP. This was firstly described in P3HR1 and Daudi BL cell lines [57]. Subsequently, these cells were shown to be more resistant to apoptosis than cells infected by wild-type virus, what would be related to the truncated shape of EBNA-LP.
Given the difficulty of sequencing repetitive regions, only few authors have sequenced the IR1 region, including the EBNA-LP coding region. Previous studies identified two EBNA-LP distinct isoforms, type 1 and type 2 variants, based on the presence of G8/T12 or V8/A12 in exon W1 [58]. The Q54R substitution was also described in exon W2 from an African type 2 spontaneous lymphoblastoid cell line LCL [59]. Despite this, a high degree of conservation was reported for the Wp promoter and the W1-W2 intron, while the most diversity was observed for the BWRF1 ORF, which only shows 80% homology between various strains, and for Y exons [60]. The sequence variations in the Y exons, and especially the Y2 exon, made it possible to define four main subgroups, called A, B, C, and Z. The Akata strain belongs to subgroup A and B95-8 to subgroup B. Subgroup Z is found in type 2 EBVs, and the C subtype is characterized by V95E and V102I. Finally, it has been reported that tumor-derived strains are more prone to interstrain genetic exchange in IR1 [60].
4.4 LMP1
LMP1 is considered to be the main oncogenic protein in EBV. LMP1 is a multifunctional self-aggregating protein essential for the transformation of human B cells and rodent fibroblasts [61]. It is a 386 aa protein comprising a 24 aa cytosolic N-terminal (NT) segment, a 162 aa portion consisting of six transmembrane (TM) domains, and a 200 aa cytosolic C-terminal (CT) domain (Figure 5) [62]. The NT domain plays an important role in the orientation and anchoring of LMP1 to the membrane and its constitutive aggregation, thus contributing to the transforming function of LMP1 [63]. The TM region is involved in the localization of LMP1 at the level of lipid rafts in the membrane, thus inducing its clustering to activate signaling from the CT tail. It is remarkable that the F38LWY41 pattern in the first transmembrane fragment (TM1) and a second pattern consisting of aa W98 in TM3 are essential for the association of TM domains (1–2) with TM domains (3–6) as well as for the oligomerization and signaling of LMP1 [64]. The CT part is involved in the activation of LMP1-induced cell signaling pathways, including two important regions, CTAR1/TES1 and CTAR2/TES2 (Carboxyl-Terminal Activating Region/Transformation Effector Site) critical for EBV-mediated B-cell growth transformation [65]. Together, these regions mimic CD40, a member of the tumor necrosis factor (TNF) receptor family and key B-cell costimulatory receptor, thus enabling the recruitment of cell adapters associated with the TNF receptor family, TNF receptor-associated factors (TRAFs). The CTAR1 region includes the P204-X-Q206-X-T208 consensus pattern necessary for the attachment of TRAF adapters, specifically TRAF1, TRAF2, TRAF3, and TRAF5 [66]. Within the CTAR2 region, the Y384-Y385-D386 pattern is essential for binding the TNF receptor-associated death domain (TRADD) adapter. There is a third region, CTAR3 (aa 232–350), that is not essential for in vitro B cell immortalization and is less well known [67]. In this region located between CTAR1 and CTAR2 (aa 253–302), a variable number of repeat 11 aa elements (4 repeats for B95-8) exist.
Figure 5.
Schematic representation of basic structure of LMP1 protein with the different motifs and their position. TM1–6: transmembrane domains 1–6. The FWLY pattern in TM1 and W98 in TM3 are essential for the association of TM1–2 with TM3–6 and oligomerization signaling. CTAR1–3: carboxyl-terminal activating regions 1–3. PQQAT pattern is necessary for the attachment of TRAF adapters. YYD pattern is essential for binding the TNF receptor-associated death domain (TRADD) adapter.
LMP1 acts principally as a viral pseudoreceptor, which regulates host cell signal transduction by constitutive activation of cell pathways as mitogen-activated protein kinase (MAPK) pathways and principally the extracellular regulated kinases 1 and 2 (ERK1/2), c-Jun amino-terminal kinases 1–3 (JNK1–3), and p38 isoform pathways. LMP1 also induces the phosphatidylinositol 3-kinase (PI3K) pathway, which contributes to survival signals [68] and transcription of activator protein 1 (AP1) [69], PI3K, and AP1 pathways, therefore playing a major role in proliferation and cell cycle control. LMP1 is also responsible for the activation of JAK/STAT and interferon regulatory factor 7 (IRF7) pathways and for aberrant constitutive NF-kB activation. Indeed, the CTAR1 PXQXT pattern is able to engage TRAFs, leading finally to the activation of noncanonical NF-kB pathway that controls processing of the NF-kB2/p100 precursor [70]. The CTAR2 YYD pattern is in turn implicated in the activation of the canonical NF-kB pathway [71] after binding of tumor necrosis factor receptor superfamily member 1A (TNFRSF1A)-associated via TRADD and receptor-inter-acting protein 1 (RIP1). A wider region of LMP1 seems to be responsible for binding RIP1 (aa 351–386), compared to TRADD (aa 375–386) [72]. NF-kB is considered to be the principal factor by which LMP1 regulates gene expression and modifies cell behavior [73]. Activation of NF-kB is associated with upregulation of anti-apoptotic genes [32, 74] and downregulation of pro-apoptotic factors, as well as induction of tumorigenesis-associated B-cell activation markers [75, 76]. CTAR3, less well defined, seems to activate SUMOylation pathways and participate in the maintenance of EBV latency and control of cell migration, a hallmark of oncogenesis [77, 78].
Besides its ability to transform B cells, during the latency state, LMP1 seems also to be able to facilitate the release of virions from B cells during lytic replication [32].
Variations in the LMP1 sequence have been widely studied, particularly in the context of its impact on clinical occurrence or evolution. A 30 bp deletion (del30), resulting in a 10 aa loss in the C-terminal (aa 343–352), was first described in the Cao cell isolate from a Chinese NPC [79]. In addition, this isolate harbored numerous substitutions. A high prevalence of the same deletion, as reviewed by Chang et al. [8], was found in Asian NPC biopsy tissues [80, 81], in lymphomas and EBV-related gastric cancers from Eastern Asia [82] and in Asian nasal NK/T-cell lymphomas [83, 84]. Del30 was shown to be often associated with the G335D mutation in NPC, and such strains were reported to have a greater transforming activity in vitro than the reference LMP1 [85, 86]. If the 30 bp deletion is partly localized to CTAR2, it does not alter NF-kB activation [87] and finally does not modify signaling properties [88]. However, it is clear that strains bearing del30 are selected over the wt-LMP1 variants in NK/T-cell lymphomas [83] and NPC tumors [89]. Given that del30 strains have been currently detected in normal carriers [90] or in various EBV-associated diseases [91], and, because of a low prevalence of del30 strains in samples from Africa, North America, and Europe [8, 92], it is generally admitted that LMP1 del30 may represent a geographic polymorphism rather than a disease-associated polymorphism [93]. In a study, we carried out in France in patients with NK/T lymphoma, we found a del30 EBV in 4/4 biopsies studied and in 46.1% of total blood samples analyzed, while in a control population, the deletion was present in 4.8% of cases [94]. Other deletions were also described, such as the rare C terminal 69 bp deletion reported to weakly activate the AP1 transcription factor [95], or the 15 bp deletion (aa 275–279) frequently encountered in Western Europe [94].
Otherwise, numerous substitutions have been described in LMP1 (Table 3), particularly in the N-terminal extremity. Some authors have made attempts to classify viral strains by taking into account these substitutions with the aim of highlighting a viral implication in certain pathologies [99]. Thus, Mainou and Raab-Traub [88] classified EBV into seven variants, namely Alaskan, China 1, China 2, Med+, Med-, NC, and B95-8, all having the same in vitro transforming potential and signaling properties. Zuercher et al. [98] mentioned two polymorphisms, I124V/I152L and F144I/D150A/L151I, which seem to be markers of increased NF-kB activation in vitro. Lei et al. [96] distinguished four models according to the substitutions occurring in both the LMP1 gene and its promoter. The patients suffering from NPC that they studied all carried a strain belonging to pattern B, while the BLs were distributed among the four patterns. Many authors recognize two evolutionarily distinct clusters, Asian-derived EBV strains including GD2, HKNPC1, and Akata strains and non-Asian and African/American strains including AG876, B95-8, and Mutu strains, suggesting that the LMP1 gene could be used as a geographic marker [25, 97].
Protein
Role/localization
Main properties
EBNA1
Latency
Initiation of viral episome replication before mitosis
Mitotic segregation of EBV episomes
Transcription of other latency genes (Cp and LMPp enhancer)
Degradation of promyelocytic leukemia protein (PML) bodies
Cellular transcription regulation
EBNA2
Latency
Viral and cellular transcription factor
Initiation and maintenance of B cell immortalization
Blocking of methylation sites for BZLF-1 binding
EBNA-LP
Latency
Coactivator of the transcriptional activator EBNA2
LMP1
Latency
Similarity to constitutively activated CD40
Constitutive activation of cell pathways
Maintenance of EBV latency and control of cell migration
BNRF1
Tegument
Establishment of latency and cell immortalization
Increase in the number of cellular centrioles
BPLF1
Tegument
Downregulation of viral ribonucleotide reductase (RR)
Disruption of damaged DNA repair
Decreasing of innate immunity
BKRF3
Tegument
DNA replication and repair—viral DNA mutagenesis prevention
Table 2.
Main properties of proteins developed in this chapter.
Finally, it should be noted that LMP1 carries a molecular signature of accelerated evolution rate probably due to positive selection as deduced from a significant proportion of nonsignificant variations [26].
So, regarding LMP1, which is the most oncogenic latency protein, two geographic clusters appear to exist corresponding to an Asian variant and a non-Asiatic variant. The described 30 bp deletion is mainly present on Asian strains, and it shows an obvious tropism for nasopharynx. Although many substitutions have been described, little work is done to analyze changes in LMP1 properties based on these substitutions. NPC could be associated with a particular strain, but this remains to be confirmed.
5. Variability of tegument proteins
After the latency proteins, the tegument proteins carry the most changes, and among them, the most mutated are BNRF1, BPLF1, and BKRF3, which will be detailed, as well as BBRF2. This latter protein appears to play an important role in viral infectivity [100], but its structure and function are poorly known today. For this reason, BBRF2 will not be developed here.
5.1 BNRF1
EBV major tegument protein BNRF1 contains 1318 aa, and its structure is shown schematically in Figure 6. BNRF1 is a member of a protein family with homology to the cellular purine biosynthesis enzyme FGARAT. BNRF1 is involved in the establishment of latency and cell immortalization by hijacking the antiviral DAXX (death domain-associated protein-6) histone chaperone [101]. BNRF1 seems to have lost conventional purine biosynthesis activity. It forms a stable quaternary complex with DAXX histone-binding domain (HBD), H3.3 and H4 [102], responsible for BNRF1 localization to PML nuclear bodies involved in antiviral intrinsic resistance and transcriptional repression of host cells. In the presence of BNFR1, DAXX can no longer collaborate with ATRX to assemble histone variant H3.3 into repressive chromatin at GC-rich repetitive DNA. Binding to DAXX, histone H3.3 and histone H4 occur, respectively, via the BNRF1 DAXX interaction domain (DID) (aa 360–600) and BNRF1 residues 40–52 and 99–102. Huang et al. [102] demonstrated that the quaternary complex formation is abrogated when dual mutations V546D/L548D and D568A/D569A occurred on BRNF1 DID and is partially diminished in vitro in case of dual mutations Y390A/K461A and V546S/L548S on BNRF1 DID. BNRF1 mutations at K461A, Y390A/K461A, V546S/L548S or Y390A, V546A/L548A, and D568A/569A moderately or severely reduced BNRF1 colocalization at PML nuclear bodies, respectively. A PurM-like domain (610–976) and a GATase domain (1037–1318) were defined. It has also recently been shown that BNRF1 can cause an abnormal increase in the number of cellular centrioles [103]. This phenomenon can lead to aneuploidy or structural chromosome abnormalities and, possibly, to carcinogenesis. The gene regions concerned have not been described.
Figure 6.
Schematic representation of basic structure of BNRF1 protein with the different motifs and their position. H3.3 and H4 regions, respectively, involved in binding to H3.3 and H4. DID: DAXX-interaction domain, domain implicated in binding to DAXX (death-domain associated protein-6) histone chaperone. PurM-like domain and GATase domain were noted, as well as the different mutations discussed.
BNRF1 is reported to be one of the most frequently mutated tegument proteins. It is interesting to note that a nonsense mutation was described in C666–1, an EBV-positive NPC cell line, with no major structural alterations in the BNRF1-deleted virus [92].
So, the mutations described for BNRF1 do not appear to correspond to a particular geographical distribution. On the other hand, some mutations seem to be able to modify DNA chromatinization, thus affecting the transcription, and therefore have important consequences on cell functioning.
5.2 BPLF1
BPLF1, the largest EBV protein (3149 aa), is a late lytic tegument protein. BPLF1 possesses a deubiquitinating (DUB) activity. BPLF1 is able to downregulate viral ribonucleotide reductase (RR) activity, by deubiquitination of the large subunit RR1 [104], and to specifically deubiquitinate proliferating cell nuclear antigen (PCNA), a DNA polymerase processivity factor, thus disrupting the repair of damaged DNA [105]. By triggering activation of repair pathways and co-opting DNA repair and replication factors, the virus could create genomic instability. The DUB activity is carried by the first 246 aa of the N-terminal region, and the C61 residue of the catalytic triad (Cys-His-Asp) is essential for activity [104]. BPLF1 relocalizes Pol 𝜼 to nuclear sites of viral DNA production, thereby bypassing DNA damage [106]. This mechanism contributes to efficient production of infectious virus.
BPLF1 is also able to deubiquinate cell factors, such as TRAF6, NEMO, and IkBα, leading to TLR signaling inhibition through both MyD88- and TRIF-dependent pathways, thus decreasing innate immune responses by reduced NF-kB activation and proinflammatory cytokine production [107]. It is noteworthy that the same catalytic active site also carries a deneddylating activity shown to target cullin ring ligases, potentially affecting viral replication and infectivity [108]. The role of BPLF1 to help drive human B-cell immortalization and lymphoma formation has also been discussed [109].
Sequencing of various viral strains has shown that BPLF1 is one of the proteins with the greatest number of changes [20, 24, 110]. Most of these mutations are not analyzed in detail, but Kwok et al. [21], working on the sequences of eight NPC biopsy specimens, reported two nonsynonymous mutations in the N-terminal region of the protein that exhibit deubiquitinating activity. The same finding was reported by Simbiri et al. [110], who also described 3 C-terminal mutations (L2935P, P2987L, and R3005Q). A single-nucleotide deletion coupled with a single-nucleotide insertion three nucleotides away was reported by Zeng et al. [13] in a NPC strain. As a result, two aa substitutions (GA/EG) were predicted to occur. Tu et al. [24] undertook phylogenetic analysis based on several reported EBV genome sequences and some major genes as BPLF1. They observed that EBV Asian subtypes clustered as a separate branch from the non-Asian ones.
So, as with other proteins, it seems that the Asian strains carry a protein different from the other strains. Substitutions occurring in the region carrying the deubiquitinase activity could have biological consequences.
5.3 BKRF3
BKRF3 is a small protein (255 aa), which belongs to the early lytic gene family, and encodes an uracil-DNA glycosylase (UDG), which removes inappropriate uracil residues from DNA. BKRF3 excises uracil bases incorporated in double-stranded DNA due to uracil misincorporation or more often cytosine deamination [111, 112]. BKRF3 participates in DNA replication and repair and prevents viral DNA mutagenesis. BKRF3 shares substantial similarity in overall structure with the one UDG family. Four of the five catalytic motifs are completely conserved (aa 90–94, 110–114, 146–149, 191–192), whereas the fifth domain (aa 213–229) carries a seven-residue insertion in the leucine loop [113]. In addition, the 29 N-terminal aa carry a nuclear localization signal (sequence KRKQ). Only changes in BKRF3 that do not severely affect viral replication can be retained, but it may be considered that these mutations cause a change in virus-cell interrelations.
6. Conclusion
The aim of this chapter was to take stock of the most frequently observed variations in the EBV genome and more particularly to see if some of these variations are considered to be involved in tumor pathology. The candidate viral genes concerned are numerous; those developed here are the most affected, and the mutations reported in the literature have been identified. Some mutations have been well studied, in particular as regards their impact on the structure or functionality of the protein or the cellular consequences of these modifications. However, most mutations have only been described. If a tumorigenic impact of viral mutations is not yet certain, many authors agree that geographic variants exist, and it seems clear that Asian strains have different characteristics from non-Asian strains. Further work is necessary to complete the mass of information and analysis, not at the level of one or several genes, but at the level of the entire genome.
\n',keywords:"Epstein-Barr virus, lymphoma, carcinoma, mutation, sequence, next generation sequencing",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/73024.pdf",chapterXML:"https://mts.intechopen.com/source/xml/73024.xml",downloadPdfUrl:"/chapter/pdf-download/73024",previewPdfUrl:"/chapter/pdf-preview/73024",totalDownloads:426,totalViews:0,totalCrossrefCites:0,dateSubmitted:"May 1st 2020",dateReviewed:"June 16th 2020",datePrePublished:"August 19th 2020",datePublished:"December 22nd 2021",dateFinished:"August 19th 2020",readingETA:"0",abstract:"The Epstein-Barr virus (EBV) is a DNA virus with a relatively stable genome. Indeed, genomic variability is reported to be around 0.002%. However, some regions are more variable such as those carrying latency genes and specially EBNA1, -2, -LP, and LMP1. Tegument genes, particularly BNRF1, BPLF1, and BKRF3, are also quite mutated. For a long time, it has been considered for this ubiquitous virus, which infects a very large part of the population, that particular strains could be the cause of certain diseases. However, the mutations found, in some cases, are more geographically restricted rather than associated with proliferation. In other cases, they appear to be involved in oncogenesis. The objective of this chapter is to provide an update on changes in viral genome sequences in malignancies associated with EBV. We focused on describing the structure and function of the proteins corresponding to the genes mentioned above in order to understand how certain mutations of these proteins could increase the tumorigenic character of this virus. Mutations described in the literature for these proteins were identified by reporting viral and/or cellular functional changes as they were described.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/73024",risUrl:"/chapter/ris/73024",signatures:"Sylvie Ranger-Rogez",book:{id:"9619",type:"book",title:"Epstein-Barr Virus",subtitle:"New Trends",fullTitle:"Epstein-Barr Virus - New Trends",slug:"epstein-barr-virus-new-trends",publishedDate:"December 22nd 2021",bookSignature:"Emmanuel Drouet",coverURL:"https://cdn.intechopen.com/books/images_new/9619.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-1-83968-490-6",printIsbn:"978-1-83968-489-0",pdfIsbn:"978-1-83968-491-3",isAvailableForWebshopOrdering:!0,editors:[{id:"188773",title:"Prof.",name:"Emmanuel",middleName:null,surname:"Drouet",slug:"emmanuel-drouet",fullName:"Emmanuel Drouet"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"317161",title:"Prof.",name:"Sylvie",middleName:null,surname:"Ranger-Rogez",fullName:"Sylvie Ranger-Rogez",slug:"sylvie-ranger-rogez",email:"sylvie.rogez@unilim.fr",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Evolving knowledge of the EBV genome",level:"1"},{id:"sec_3",title:"3. The most variable regions of the genome",level:"1"},{id:"sec_4",title:"4. Variability of main latency proteins",level:"1"},{id:"sec_4_2",title:"4.1 EBNA1",level:"2"},{id:"sec_5_2",title:"4.2 EBNA2",level:"2"},{id:"sec_6_2",title:"4.3 EBNA-LP (EBNA-leader protein)",level:"2"},{id:"sec_7_2",title:"4.4 LMP1",level:"2"},{id:"sec_9",title:"5. Variability of tegument proteins",level:"1"},{id:"sec_9_2",title:"5.1 BNRF1",level:"2"},{id:"sec_10_2",title:"5.2 BPLF1",level:"2"},{id:"sec_11_2",title:"5.3 BKRF3",level:"2"},{id:"sec_13",title:"6. Conclusion",level:"1"}],chapterReferences:[{id:"B1",body:'Epstein MA, Achong BG, Barr YM. Virus particles in cultured lymphoblasts from BURKITT’S lymphoma. Lancet. 1964;1:702-703. DOI: 10.1016/s0140-6736(64)91524-7'},{id:"B2",body:'Zur Hausen H, Schulte-Holthausen H. 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New insights on the role of the gamma-herpesvirus uracil-DNA glycosylase leucine loop revealed by the structure of the Epstein-Barr virus enzyme in complex with an inhibitor protein. Journal of Molecular Biology. 2007;366:117-131. DOI: 10.1016/j.jmb.2006.11.007'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Sylvie Ranger-Rogez",address:"sylvie.rogez@unilim.fr",affiliation:'
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Open Access publication costs can often be designated directly in the grants or in specific budgets allocated for that purpose. Many of the most important funding organisations encourage, and even request, that the projects they fund are made available at no cost to the wider public. IntechOpen strives to maintain excellent relationships with these funders and ensures compliance with mandates.
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Please note that this list is not a definitive one and is updated regularly. To suggest possible modifications or the inclusion of your institution/funder, please contact us at funders@intechopen.com
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Please be aware that you must be a member, or grantee, of the institutions/funders listed in order to apply for their Open Access publication funds.
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\n\n
In order to help Authors identify appropriate funding agencies and institutions, we have created a list, based on extensive research on various OA resources (including ROARMAP and SHERPA/JULIET) of organizations that have funds available. Before consulting our list we encourage you to petition your own institution or organization for Open Access funds or check the specifications of your grant with your funder to ascertain if publication costs are included. Where you are in receipt of a grant you should clarify:
\n\n
\n\t
Does your institution already have a budget for covering Open Access publication costs?
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Does your grant list Open Access publication fees as legitimate direct/indirect costs?
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\n\n
If you are associated with any of the institutions in our list below, you can apply to receive OA publication funds by following the instructions provided in the links. Please consult the Open Access policies or grant Terms and Conditions of any institution with which you are linked to explore ways to cover your publication costs (also accessible by clicking on the link in their title).
\n\n
Please note that this list is not a definitive one and is updated regularly. To suggest possible modifications or the inclusion of your institution/funder, please contact us at funders@intechopen.com
\n\n
Please be aware that you must be a member, or grantee, of the institutions/funders listed in order to apply for their Open Access publication funds.
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Xavier Malcata"}]},{id:"30642",doi:"10.5772/34423",title:"Meiofauna as a Tool for Marine Ecosystem Biomonitoring",slug:"meiofauna-as-a-tool-for-marine-ecosystem-monitoring",totalDownloads:3897,totalCrossrefCites:22,totalDimensionsCites:83,abstract:null,book:{id:"1689",slug:"marine-ecosystems",title:"Marine Ecosystems",fullTitle:"Marine Ecosystems"},signatures:"Maria Balsamo, Federica Semprucci, Fabrizio Frontalini and Rodolfo Coccioni",authors:[{id:"100075",title:"Prof.",name:"Maria",middleName:null,surname:"Balsamo",slug:"maria-balsamo",fullName:"Maria Balsamo"},{id:"104309",title:"Dr.",name:"Federica",middleName:null,surname:"Semprucci",slug:"federica-semprucci",fullName:"Federica Semprucci"},{id:"104311",title:"Dr.",name:"Fabrizio",middleName:null,surname:"Frontalini",slug:"fabrizio-frontalini",fullName:"Fabrizio Frontalini"},{id:"104313",title:"Prof.",name:"Rodolfo",middleName:null,surname:"Coccioni",slug:"rodolfo-coccioni",fullName:"Rodolfo Coccioni"}]},{id:"35136",doi:"10.5772/29571",title:"Transmission Biology of the Myxozoa",slug:"transmission-biology-of-the-myxozoa",totalDownloads:2685,totalCrossrefCites:34,totalDimensionsCites:63,abstract:null,book:{id:"2052",slug:"health-and-environment-in-aquaculture",title:"Health and Environment in Aquaculture",fullTitle:"Health and Environment in Aquaculture"},signatures:"Hiroshi Yokoyama, Daniel Grabner and Sho Shirakashi",authors:[{id:"78409",title:"Dr.",name:"Hiroshi",middleName:null,surname:"Yokoyama",slug:"hiroshi-yokoyama",fullName:"Hiroshi Yokoyama"},{id:"83562",title:"Dr.",name:"Daniel",middleName:"Stefan",surname:"Grabner",slug:"daniel-grabner",fullName:"Daniel Grabner"},{id:"122643",title:"Dr.",name:"Sho",middleName:null,surname:"Shirakashi",slug:"sho-shirakashi",fullName:"Sho Shirakashi"}]},{id:"24078",doi:"10.5772/26795",title:"Photobacterium damselae subsp. damselae, an Emerging Pathogen Affecting New Cultured Marine Fish Species in Southern Spain",slug:"photobacterium-damselae-subsp-damselae-an-emerging-pathogen-affecting-new-cultured-marine-fish-speci",totalDownloads:3777,totalCrossrefCites:19,totalDimensionsCites:45,abstract:null,book:{id:"612",slug:"recent-advances-in-fish-farms",title:"Recent Advances in Fish Farms",fullTitle:"Recent Advances in Fish Farms"},signatures:"A. Labella, C. Berbel, M. Manchado, D. Castro and J.J. Borrego",authors:[{id:"67855",title:"Prof.",name:"Juan J.",middleName:null,surname:"Borrego",slug:"juan-j.-borrego",fullName:"Juan J. Borrego"},{id:"71146",title:"Dr.",name:"Alejandro",middleName:null,surname:"Labella",slug:"alejandro-labella",fullName:"Alejandro Labella"},{id:"71148",title:"Dr.",name:"Concepcion",middleName:null,surname:"Berbel",slug:"concepcion-berbel",fullName:"Concepcion Berbel"},{id:"71149",title:"Dr.",name:"Manuel",middleName:null,surname:"Manchado",slug:"manuel-manchado",fullName:"Manuel Manchado"},{id:"71151",title:"Dr.",name:"Dolores",middleName:null,surname:"Castro",slug:"dolores-castro",fullName:"Dolores Castro"}]}],mostDownloadedChaptersLast30Days:[{id:"35141",title:"Antibiotics in Aquaculture – Use, Abuse and Alternatives",slug:"antibiotics-in-aquaculture-use-abuse-and-alternatives",totalDownloads:19291,totalCrossrefCites:136,totalDimensionsCites:288,abstract:null,book:{id:"2052",slug:"health-and-environment-in-aquaculture",title:"Health and Environment in Aquaculture",fullTitle:"Health and Environment in Aquaculture"},signatures:"Jaime Romero, Carmen Gloria Feijoo and Paola Navarrete",authors:[{id:"72898",title:"Dr.",name:"Jaime",middleName:null,surname:"Romero",slug:"jaime-romero",fullName:"Jaime Romero"},{id:"79684",title:"Dr.",name:"Paola",middleName:null,surname:"Navarrete",slug:"paola-navarrete",fullName:"Paola Navarrete"},{id:"83411",title:"Dr.",name:"Carmen",middleName:null,surname:"Feijoo",slug:"carmen-feijoo",fullName:"Carmen Feijoo"}]},{id:"69948",title:"Floating Cage: A New Innovation of Seaweed Culture",slug:"floating-cage-a-new-innovation-of-seaweed-culture",totalDownloads:930,totalCrossrefCites:2,totalDimensionsCites:2,abstract:"Eucheumatoid cultivation continues to expand with a variety of methods that can increase production. This chapter will discuss an innovation in seaweed cultivation of the genus Eucheuma, which is the prime marine commodity in the tropical regions of the world. Research conducted during 2015-2017 and 2019 in Southeast Sulawesi Province, Indonesia, provided an overview of the use of floating cage that showed very significant growth results. The research result showed that the growth rates of Eucheuma denticulatum and Kappaphycus alvarezii in floating cage seemed faster and resulted in better thallus morphology. Daily production of E. denticulatum and K. alvarezii that were cultivated in floating cage was higher than daily production of E. denticulatum and K. alvarezii cultivated on longline. Specific growth rate (SGR) of E. denticulatum and K. alvarezii cultivated by using floating cage method was also higher than E. denticulatum and K. alvarezii cultivated by using longline method. Moreover, the cultivation by using floating cages produces good growth rates with no effect of herbivore attacks.",book:{id:"8928",slug:"emerging-technologies-environment-and-research-for-sustainable-aquaculture",title:"Emerging Technologies, Environment and Research for Sustainable Aquaculture",fullTitle:"Emerging Technologies, Environment and Research for Sustainable Aquaculture"},signatures:"Ma’ruf Kasim, Abdul Muis Balubi, Ahmad Mustafa, Rahman Nurdin, Rahmad Sofyan Patadjai and Wardha Jalil",authors:[{id:"309893",title:"Prof.",name:"Maruf",middleName:null,surname:"Kasim",slug:"maruf-kasim",fullName:"Maruf Kasim"},{id:"313040",title:"MSc.",name:"Abdul Muis",middleName:null,surname:"Balubi",slug:"abdul-muis-balubi",fullName:"Abdul Muis Balubi"},{id:"313041",title:"MSc.",name:"Wardha",middleName:null,surname:"Jalil",slug:"wardha-jalil",fullName:"Wardha Jalil"},{id:"313042",title:"MSc.",name:"Ahmad",middleName:null,surname:"Mustafa",slug:"ahmad-mustafa",fullName:"Ahmad Mustafa"},{id:"313043",title:"MSc.",name:"Rahman",middleName:null,surname:"Nurdin",slug:"rahman-nurdin",fullName:"Rahman Nurdin"},{id:"313044",title:"MSc.",name:"Rahmat Sofyan",middleName:null,surname:"Patadjai",slug:"rahmat-sofyan-patadjai",fullName:"Rahmat Sofyan Patadjai"}]},{id:"62842",title:"Integrated Rice and Aquaculture Farming",slug:"integrated-rice-and-aquaculture-farming",totalDownloads:1889,totalCrossrefCites:2,totalDimensionsCites:3,abstract:"The burning problems like scarcity of food for ever-growing human population in the present world are addressed by adapting various methods for production of protein, carbohydrate, oils and other food materials. One of the methods to produce high amount of food is integrated farming including rice-aquaculture farming, which produces protein and carbohydrate as major components besides others. Rice-aquaculture farming produces grain (carbohydrate) and animal protein without affecting the quality and quantity of rice yield on the same piece of land and renders additional financial gain besides main crop (rice) like conventional monoculture. The aquatic species grown in the integrated culture are mainly distinct types of fishes, selected crustaceans and other selected species. Profitable rice-aquaculture integrated farming is popular in Asian countries than in Western countries. However, the integrated rice-aquaculture farming has its own limitations. The type of methods, culture species, influencing factors, and pros and cons of rice-aquaculture integrated farming are discussed in the present chapter.",book:{id:"7229",slug:"aquaculture-plants-and-invertebrates",title:"Aquaculture",fullTitle:"Aquaculture - Plants and Invertebrates"},signatures:"Pamuru Ramachandra Reddy and Battina Kishori",authors:[{id:"242524",title:"Dr.",name:"Ramachandra Reddy",middleName:null,surname:"Pamuru",slug:"ramachandra-reddy-pamuru",fullName:"Ramachandra Reddy Pamuru"},{id:"255022",title:"Dr.",name:"Kishori",middleName:null,surname:"Battina",slug:"kishori-battina",fullName:"Kishori Battina"}]},{id:"24074",title:"Embryonic and Larval Development of Freshwater Fish",slug:"embryonic-and-larval-development-of-freshwater-fish",totalDownloads:7448,totalCrossrefCites:1,totalDimensionsCites:2,abstract:null,book:{id:"612",slug:"recent-advances-in-fish-farms",title:"Recent Advances in Fish Farms",fullTitle:"Recent Advances in Fish Farms"},signatures:"Faruk Aral, Erdinç Şahınöz and Zafer Doğu",authors:[{id:"25600",title:"Prof.",name:"Faruk",middleName:null,surname:"Aral",slug:"faruk-aral",fullName:"Faruk Aral"},{id:"29132",title:"Dr.",name:"Zafer",middleName:null,surname:"Dogu",slug:"zafer-dogu",fullName:"Zafer Dogu"},{id:"39952",title:"Dr.",name:"Erdinc",middleName:null,surname:"Sahinoz",slug:"erdinc-sahinoz",fullName:"Erdinc Sahinoz"}]},{id:"68966",title:"Novel Biofloc Technology (BFT) for Ammonia Assimilation and Reuse in Aquaculture In Situ",slug:"novel-biofloc-technology-bft-for-ammonia-assimilation-and-reuse-in-aquaculture-in-situ",totalDownloads:1926,totalCrossrefCites:1,totalDimensionsCites:7,abstract:"Ammonia is one of the most harmful risks for success of fish and shrimp culture. There is no effective solution for harmlessness of ammonia in traditional aquaculture operations except exchanging water, which would bring negative effects on environment, or fixing expensive equipment. Biofloc technology (BFT) that appeared in recent years supplies a novel solution for this issue without exchanging huge water and fixing equipment. This technology could assimilate ammonia almost in real time with many other supplemental benefits. Because of the very high nutritional value for fish and shrimp, bioflocs, the by-product of BFT, could also be reused as a complemented food in situ or a gradient for feedstuff to replace expensive fishmeal or be processed to pellet diet to feed fish and shrimp directly. However, some aspects with regard to the effective use of biofloc as a food source for fish and shrimp, such as high lipid content, productivity, and palatability, need to be further researched in detail.",book:{id:"8928",slug:"emerging-technologies-environment-and-research-for-sustainable-aquaculture",title:"Emerging Technologies, Environment and Research for Sustainable Aquaculture",fullTitle:"Emerging Technologies, Environment and Research for Sustainable Aquaculture"},signatures:"Hai-Hong Huang",authors:[{id:"305215",title:"Dr.",name:"Hai-Hong",middleName:null,surname:"Huang",slug:"hai-hong-huang",fullName:"Hai-Hong Huang"}]}],onlineFirstChaptersFilter:{topicId:"32",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:0,limit:8,total:null},allSeries:{pteSeriesList:[],lsSeriesList:[],hsSeriesList:[],sshSeriesList:[],testimonialsList:[]},series:{item:{id:"22",title:"Business, Management and Economics",doi:"10.5772/intechopen.100359",issn:"2753-894X",scope:"
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His research interests and specialties include financial econometrics, financial economics, international economics and finance, housing markets, financial markets, among others.",institutionString:null,institution:{name:"University of Southampton",institutionURL:null,country:{name:"United Kingdom"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:3,paginationItems:[{id:"86",title:"Business and Management",coverUrl:"https://cdn.intechopen.com/series_topics/covers/86.jpg",isOpenForSubmission:!0,editor:{id:"128342",title:"Prof.",name:"Vito",middleName:null,surname:"Bobek",slug:"vito-bobek",fullName:"Vito Bobek",profilePictureURL:"https://mts.intechopen.com/storage/users/128342/images/system/128342.jpg",biography:"Dr. Vito Bobek works as an international management professor at the University of Applied Sciences FH Joanneum, Graz, Austria. He has published more than 400 works in his academic career and visited twenty-two universities worldwide as a visiting professor. 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At the Ministry of Justice of Slovenia, she is a member of examination boards for court expert candidates and judicial appraisers in the following areas: economy/finance, valuation of companies, banking, and forensic investigation of economic operations/accounting. 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She specializes in the subject of brands, brand equity, and brand management in production, service, and trade enterprises. She combines this subject with marketing and marketing management in both theoretical and practical aspects. Prof. Hanna Górska-Warsewicz also analyzes brands in the context of trademarks, legal regulations and the protection of intangible. She is an author or co-author of over 200 publications in this field, including 8 books. 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