\r\n\t
",isbn:"978-1-83962-718-7",printIsbn:"978-1-83962-717-0",pdfIsbn:"978-1-83962-754-5",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,hash:"4df95c7f295de7f6003e635d9a309fe9",bookSignature:"Dr. Yajuan Zhu, Dr. Qinghong Luo and Dr. Yuguo Liu",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/8969.jpg",keywords:"Water Cycle, Water Use Strategy, Vegetation Dynamics, Plant Community, Precipitation, Carbon Emission, Soil Respiration, Autotrophic Respiration, Algae Crust, Wind, Temperature, Vegetation Stability",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"January 26th 2021",dateEndSecondStepPublish:"February 23rd 2021",dateEndThirdStepPublish:"April 24th 2021",dateEndFourthStepPublish:"July 13th 2021",dateEndFifthStepPublish:"September 11th 2021",remainingDaysToSecondStep:"a month",secondStepPassed:!1,currentStepOfPublishingProcess:2,editedByType:null,kuFlag:!1,biosketch:"Dr. Zhu holds a Ph.D. in Ecology and is currently an Associate Research Professor at the Chinese Academy of Forestry at the Institute of Desertification Studies, she has led a number of national projects while working there.",coeditorOneBiosketch:"Dr. Luo holds a Ph.D. in Physical Geography and is currently a Research Professor at the Institute of Afforestation and Sand Control, Xinjiang Academy of Forestry. She is a holder of several technological patents in her area of research.",coeditorTwoBiosketch:"Dr. Liu holds a Ph.D. in Ecology and is currently an Assistant Professor at the Institute of Desertification Studies, Chinese Academy of Forestry. He has published several international works that have been recognized.",coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"180427",title:"Dr.",name:"Yajuan",middleName:null,surname:"Zhu",slug:"yajuan-zhu",fullName:"Yajuan Zhu",profilePictureURL:"https://mts.intechopen.com/storage/users/180427/images/system/180427.jpg",biography:"Dr. Yajuan Zhu obtained her Bachelor's degree in Agriculture from Northwest Agriculture and Forestry University in 2002 and PhD in Ecology from Chinese Academy of Sciences in 2007. She was a postdoctoral fellow working on the topic of land desertification control in the Research Institute of Forestry, Chinese Academy of Forestry, followed by her appointment as an Assistant Professor at the Institute of Desertification Studies, Chinese Academy of Forestry and currently she is an Associate Research Professor at the same institute. She is a Master's supervisor with interests in plant ecology in deserts, biodiversity, stable isotope ecology, isohydrology and desertification control.",institutionString:"Chinese Academy of Forestry",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Chinese Academy of Forestry",institutionURL:null,country:{name:"China"}}}],coeditorOne:{id:"340564",title:"Dr.",name:"Qinghong",middleName:null,surname:"Luo",slug:"qinghong-luo",fullName:"Qinghong Luo",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000032N5e7QAC/Profile_Picture_1605773886590",biography:"Dr. Qinghong Luo holds a Master's degree from Life Science College, Shihezi University (2006) and PhD in Physical geography from Xinjiang Ecology and Geography Institute, Chinese Academy of Sciences (2018). She was initially an Assistant Research Professor at Institute of Afforestation and Sand Control, Xinjiang Academy of Forestry, after an Associate Research Professor and currently she is a Research Professor at the same institute. Her research interests include desert vegetation dynamics, plant-soil interaction and desertification control among others. She has participated in a number of funded and non funded projects and is a holder of several patents.",institutionString:"Chinese Academy of Forestry",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Chinese Academy of Forestry",institutionURL:null,country:{name:"China"}}},coeditorTwo:{id:"340567",title:"Dr.",name:"Yuguo",middleName:null,surname:"Liu",slug:"yuguo-liu",fullName:"Yuguo Liu",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000032N5hEQAS/Profile_Picture_1605774524148",biography:"Dr. Yuguo Liu obtained his bachelor's degree, majoring in Environmental Sciences from Inner Mongolia University in 2007 and doctoral degree, majoring in Ecology from Institute of Botany, the Chinese Academy of Sciences in 2013. He has been working as an Assistant Professor at the Institute of Desertification Studies, Chinese Academy of Forestry ever since. His research interests include ecological protection and restoration of fragile areas, and karst vegetation and rocky desertification control.",institutionString:"Chinese Academy of Forestry",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Chinese Academy of Forestry",institutionURL:null,country:{name:"China"}}},coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"10",title:"Earth and Planetary Sciences",slug:"earth-and-planetary-sciences"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"194667",firstName:"Marijana",lastName:"Francetic",middleName:null,title:"Ms.",imageUrl:"https://mts.intechopen.com/storage/users/194667/images/4752_n.jpg",email:"marijana@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. 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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"878",title:"Phytochemicals",subtitle:"A Global Perspective of Their Role in Nutrition and Health",isOpenForSubmission:!1,hash:"ec77671f63975ef2d16192897deb6835",slug:"phytochemicals-a-global-perspective-of-their-role-in-nutrition-and-health",bookSignature:"Venketeshwer Rao",coverURL:"https://cdn.intechopen.com/books/images_new/878.jpg",editedByType:"Edited by",editors:[{id:"82663",title:"Dr.",name:"Venketeshwer",surname:"Rao",slug:"venketeshwer-rao",fullName:"Venketeshwer Rao"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"4816",title:"Face Recognition",subtitle:null,isOpenForSubmission:!1,hash:"146063b5359146b7718ea86bad47c8eb",slug:"face_recognition",bookSignature:"Kresimir Delac and Mislav Grgic",coverURL:"https://cdn.intechopen.com/books/images_new/4816.jpg",editedByType:"Edited by",editors:[{id:"528",title:"Dr.",name:"Kresimir",surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"72770",title:"Modeling of the Two-Dimensional Thawing of Logs in an Air Environment",doi:"10.5772/intechopen.93177",slug:"modeling-of-the-two-dimensional-thawing-of-logs-in-an-air-environment",body:'\nThe duration and the energy consumption of the thermal treatment of frozen logs aimed at their thawing and plasticizing for the production of veneer in winter are very high [1, 2, 3, 4, 5, 6, 7, 8, 9]. For example, thawing and plasticizing of poplar and pine logs with an initial temperature of –10°C and moisture content of 0.6 kg·kg−1 about 53 kWh·m−3 and 64 kWh·m−3 thermal energy, respectively, are needed [9].
\nIn the specialized literature, there are few reports about the temperature fields subjected to thawing in agitated water or steam frozen logs [7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21], and there is very scarce information about research of the temperature distribution in frozen logs during their thawing in an air environment given by the authors only [22].
\nThe computation of the temperature field in logs during their thawing in water or steam is carried out using mathematical models, which solve the so-called direct task of the heat transfer. This is the task when all variables in the model are known, and this allows computing the temperature field in the body [23, 24].
\nThe computation of the temperature field in logs during their thawing in an air environment requires solving of the so-called inverse task of the heat transfer. This is the task when the model of the studied object and the experimentally obtained temperature field in it are known, but one or more variables in the model need to be determined during the solving and validation of the model [24].
\nThe results from investigations of the temperature change subjected to thawing frozen logs only at conductive boundary conditions (i.e., at prescribed surface temperature) have been reported [2, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21].
\nThe modeling and the multiparameter study of the thawing process of logs in air environment is of considerable scientific and practical interest. For example, as a result of such a study, it is possible to determine the real initial temperature of logs depending on their dimensions, wood species, moisture content, and the temperature of the air near the logs during their many days staying in an open warehouse before the thermal treatment in the production of veneer. The information about the real value of that immeasurable parameter can be used for scientifically based computing of the optimal, energy saving regimes for thermal treatment of each specific batch of logs.
\nThis chapter presents the creation, numerical solving and validation of a two-dimensional nonlinear mathematical model of the transient heat conduction in frozen logs during their thawing at convective boundary conditions in an air environment. A validation of the models towards own experimentally determined 2D temperature distribution in poplar logs with a diameter of 0.24 m, length of 0.48 m, initial temperature of approximately –30°C, and moisture content above the hygroscopic range during their 70 h thawing at room temperature has been carried out.
\nDuring the validation of the model, the inverse task has been solved for the determination of the unknown logs’ heat transfer coefficients in radial and longitudinal directions. This task has been solved also in regard to the logs’ surface temperature, which depends on the mentioned coefficients.
\nIn [8] the following common form of a model, which describes the 2D nonstationary temperature distribution subjected to thawing frozen logs in an air environment, has been suggested:
\nwith an initial condition
\nand boundary conditions for convective heat transfer:
Along the radial coordinate r on the logs’ frontal surface during thawing
\n
Along the longitudinal coordinate z on the logs’ cylindrical surface during thawing
In [8] solutions of Eq. (1) only at conductive boundary conditions for the case of autoclave steaming of logs aimed at their plasticizing in the production of veneer have been realized and graphically presented.
\nAn approach for solving Eq. (1) at much more complicated convective boundary conditions and verification of model (1) to (4) is considered below.
\nIn Figure 1 the three temperature ranges are presented, at which the process of the logs’ thawing above the hygroscopic range is carried out, i.e., when u >\n
Temperature ranges of the logs’ thawing process at u > u\nfsp and thermophysical characteristics of the wood and of the frozen and nonfrozen bound and free water in it.
There thermophysical characteristics of the logs and of both the frozen and nonfrozen free and bound water in them during the separate temperature ranges are also shown. The information on these characteristics is very important for the solving of the model given above.
\nThe mathematical descriptions of the thermal conductivities of nonfrozen wood, \n
The coefficients γ and β in Eq. (5) are calculated using the next equations:
For nonfrozen wood at \n
\n
For frozen wood at \n
The fiber saturation points of the wood species, u\nfsp and \n
and consequently
\nwhere \n
The effective specific heat capacities of the logs during the pointed three ranges of the thawing process, \n
According to the suggested in [8, 9, 22] mathematical description, the effective specific heat capacities of the logs during their thawing can be calculated with the help of the following equations for \n
The wood density, ρ\nw, which participates in Eq. (1), is determined above the hygroscopic range according to the following Equation [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 27]:
\nFor solving of the 2D mathematical model given above, it is needed to have values for the heat transfer coefficients of the logs in radial and longitudinal directions, α\nwr and α\nwp, respectively, which participate in Eqs. (3) and (4).
\nAs it was mentioned in the Introduction, the values of α\nwr and α\nwp can be computed by solving the inverse task of the heat transfer between the logs and surrounding air environment.
\nThe calculation of α\nwr and α\nwp can be carried out with the help of the following equations of the similarity theory, which are valid for the cases of heating of horizontally situated cylindrical bodies in conditions of free air convection [28]:
\nFor the usage of Eqs. (19)–(26), it is needed to have a mathematical description of the thermophysical characteristics of the air, λ, β, w, and а, depending on T and φ. The temperature of the air near the logs subjected to thawing during our experiments described below changes in the range from 243.15 to 303.15 K (i.е., from –30°С to 30°С), and φ changes from 40–100% (see Figures 2 and 3).
\nExperimentally determined change in tm, φm, and t in four points of the studied poplar log P1 during its 70 h thawing.
Experimentally determined change in tm, φm, and t in four points of the studied poplar log P2 during its 70 h thawing.
For the calculation of λa, β\na, w\na, and а\na, the temperature of the air, Т\na, must be used, but for the calculation of w\ns and а\ns in Eq. (26), the temperature of the surface of the logs, T\ns, has to be used.
\nIn the accessible specialized sources, we did not find suitable mathematical descriptions of λ, β, w, and а of the air, depending on T and φ, which could be applied for the precise determination of α\nwr and α\nwp according to Eqs. (19)–(26).
\nOur further study has shown that for solving the inverse task of the heat transfer between the logs and surrounding air, i.e., for the calculation of the heat transfer coefficients of the logs, which participate in the boundary conditions (3) and (4) of the model, the following equations are suitable [29]:
In the radial direction on the cylindrical surface of the logs
\n
In the longitudinal direction on the frontal surface of the logs
where x is an exponent, whose values are determined during the solving and validation of the model through the minimization of the root-square-mean error (RSME) between the calculated model and experimentally obtained results about the change of the temperature fields subjected to thawing logs.
\nFor solving the inverse task of the heat transfer aimed at validation of the suggested above mathematical model, it is necessary to have experimentally obtained data about the 2D temperature distribution in logs during their thawing. That is why we realized such experiments using poplar (Populus nigra L.) logs with D = 0.24 m, L = 0.48 m, and u > u\nfsp [26].
\nIn Figure 4 the coordinates of four representative points of the logs, in which the 2D change in the temperature was measured and registered during the logs’ thawing, are shown.
\nRadial (left) and longitudinal (right) coordinates of four characteristic points for the measurement of the temperature in logs subjected to thawing.
For the freezing of the logs before their thawing, a horizontal freezer was used with adjustable temperature range from –1 to –30°C. Sensors Pt100 with long metal casings were positioned in the drilled four holes of the logs. After 50 h separately freezing each logs, the freezer was switched off. Then its lid was opened, and 70 h thawing of the log at room temperature was carried out.
\nThe automatic measurement and record of t\nm, φ\nm, and t in the representative points of the logs during the experiments was accomplished by Data Logger type HygroLog NT3 produced by the Swiss firm ROTRONIC AG.
\nIn Figures 2 and 3, the change in the temperature of the processing air medium, t\nm, and in its humidity, φ\nm, and also in the temperature in four representative points of two poplar logs, named below as P1 and P2, respectively, during their separate 70 h thawing is presented.
\nAll curves of the experimentally obtained data on these figures are drawn using the licensed software HW4 of the Data Logger. The left coordinate axis on the figures is graduated at % of φ\nm, and the right one is graduated at °C of t.
\nThe change shown in Figures 2 and 3 air medium temperature T\nm during the logs’ thawing with correlation 0.98 and root-square-mean error, σ < 1.5°C, has been approximated with the help of the software package Table Curve 2D by the following equation:
\nwhose coefficients are equal to:
For log P1: а = 293.3637194, b = −0.00236425, c = −0.69281743.
For log P2: a = 299.2738855, b = −0.00245303, c = −0.73047119.
and τ is the sum of the time of logs’ freezing, equal to 50 h = 180,000 s, and the current time of the subsequent thawing of the logs, s.
\n\nEq. (29) was used for solving Eqs. (3) and (4) of the model.
\nThe mathematical descriptions of the thermophysical characteristics of the logs and also of T\nm considered above were introduced in the mathematical model (1) to (4). An explicit form of the finite-difference method was used for solving of the model without any simplifications [7, 8].
\nThe presentation of Eq. (1) of the model suitable for programming discrete analogue has been carried out using the given in Figures 5 and 6 coordinate system. These figures show the positioning of the knots of the calculation mesh and four representative points, in which the nonstationary 2D distribution of the temperature in the longitudinal section subjected to thawing log has been calculated. The mesh has been built on ¼ of the longitudinal section of the log due to the fact that this ¼ is mirrored symmetrical towards the remaining ¾ of the same section.
\nPositioning of the knots of 2D calculation mesh on ¼ of longitudinal section of a log subjected to thawing (left) and calculation mesh for solving of the model (right).
Calculation mesh and representative points T1, T2, T3, and T4 on ¼ of the longitudinal section subjected to thawing log.
Taking into consideration Eqs. (5) and (6), it can be written that
\nand using the coefficient
\nThe discrete finite-difference analogue of the left-hand part of Eq. (1), which is suitable for programming in FORTRAN, has the following form [7, 30]:
\nTaking into account Eqs. (30), (31), and (32), the discrete analogue of the right-hand part of Eq. (1) has the following form:
\nAfter alignment of Eq. (34) with Eq. (35) and taking into account Eq. (33), at Δz = Δr, it is obtained that Eq. (1) is transformed into the following system of algebraic equations:
\nThe term \n
The temperature in these surface knots is calculated with the help of Eqs. (38) and (42) given below. Since Eq. (36) calculates the temperature in the knots, which are located inside the logs, i.e., in the knots with i ≥ 2 and k ≥ 2, the denominator of the term \n
It can be noted that the effective specific heat capacities of the log during the pointed above three ranges of its thawing process (see Figure 1), \n
The initial condition (2) of the model of logs’ thawing process obtains the following discrete finite-difference form:
\nwhere T\nw0-avg is the experimentally determined average mass temperature of the log at the beginning of the thawing process, K.
\nThe boundary condition (3) of the logs’ thawing process obtains the following final form, suitable for programming in FORTRAN:
\nThe variable \n
where according to Eqs. (28) and (29)\n
\nwhere
\nAnalogously, the boundary condition (4) of the logs’ thawing process obtains the following final form, suitable for programming in FORTRAN:
\nThe variable \n
where according to Eq. (27)\n
\nand \n
The numerical solving and verification of the model (1) to (4) has been realized in the calculation environment of Visual FORTRAN Professional.
\nUsing own software package in that environment, computations were carried out for the determination of the 2D nonstationary change of t in the representative points of the logs P1 and P2, whose experimentally registered temperature fields are presented in Figures 2 and 3, respectively.
\nThe initial temperature, t\nw0-avg; basic density, ρ\nb; and moisture content, u, of the logs during the experiments were as follows:
For log P1: t\nw0-avg = −29.7°C, ρ\nb = 359 kg·kg−1, and u = 1.44 kg·kg−1.
For log P2: t\nw0-avg = −28.0°C, ρ\nb = 364 kg·kg−1, and u = 1.78 kg·kg−1.
As it was mentioned above, the duration of the freezing and duration of the subsequent thawing of the logs were equal to 50 and 70 h, respectively.
\nThe model was solved with step Δr = Δz = 0.006 m along the coordinates r and z, with step Δτ = 6 s [8, 23], and with the same initial and boundary conditions, as they were during the experimental research.
\nDuring the solving of the model, mathematical descriptions of the thermophysical characteristics of poplar sapwood with \n
The model (1) to (4) was solved with various values of the exponent x in Eqs. (27) and (28). The computed by the model change of t in the four representative points of the logs with each of the tested values of the exponent x during the thawing was compared mathematically with the corresponding one experimentally registered change of t in these points with an interval of 15 min.
\nThe aim of this comparison was to determine the values of x, which ensure the best compliance between the computed and experimentally registered temperature fields in subjected to thawing logs.
\nAs a criterion of the best compliance, the minimum average value of RSME, σ\navg, was used, which is equal to
\nwhere \n
For the calculation of σ\navg, a software program in the calculation environment of MS Excel was prepared. At τthaw = 70 h = 252,000 s, RSME has been calculated with the help of the program simultaneously for a total of N·P = 1120 temperature–time points during the thawing of each log.
\nIt was determined that the minimum values of RSME overall for the studied four representative points are equal to σ\navg = 1.37°C for log P1 and to σ\navg = 1.34°C for log P2. These minimum values of σ\navg correspond to the following values of the exponent x in Eqs. (27) and (28), which were obtained during the solving of the inverse task, x = 0.22 for log P1 and x = 0.20 for log P2.
\n\nFigures 7 and 8 present the calculated change in α\nwr and α\nwp during the studied thawing process of the logs P1 and P2, respectively.
\nCalculated change in αwr and αwp of the log P1 during its 70 h thawing.
Calculated change in αwr and αwp of the log P2 during its 70 h thawing.
\nFigures 9 and 10 present the calculated change in t\nm and also in the logs’ surface temperature t\ns and t of 4 representative points of the studied logs.
\nExperimentally determined and calculated change in tm, ts, and t in four points of the log P1 during its 70 h thawing.
Experimentally determined and calculated change in tm, ts, and t in four points of the log P2 during its 70 h thawing.
It can be seen that with the decrease of the difference between t\nm and t\ns during the logs’ thawing, the heat transfer coefficients on Figures 7 and 8 gradually decrease, as follows:
At α\nwr: from 2.3 to 1.0 W·m−2·K−1 for P1 and from 1.9 to 1.2 W·m−2·K−1 for P2.
At α\nwp: from 5.1 to 2.2 W·m−2·K−1 for P1 and from 4.5 to 2.8 W·m−2·K−1 for P2.
Using the obtained change in the heat transfer coefficients, the change in the logs’ surface temperature during the thawing, t\ns, has been calculated by the model (refer to Figures 9 and 10).
\nThe comparison to each other of the analogical curves in Figures 2 and 9, and also in Figures 3 and 10, shows good conformity between the calculated and experimentally determined changes in the very complicated temperature fields of the studied logs during their thawing.
\nDuring our extensive simulations with the model (1) to (4), we established good qualitative and quantitative compliance between computed and experimentally determined temperature fields of logs from numerous wood species with different moisture content above the hygroscopic range [31].
\nThe overall RSME for the studied four representative points in the logs does not exceed 5% of the temperature ranges between the minimal and maximal temperatures of each log during its thawing.
\nThis chapter describes the creation, solving, and validation of a 2D nonlinear mathematical model for the transient heat conduction subjected to thawing frozen logs in an air environment.
\nThe mechanism of the heat distribution in logs during their thawing has been described by a 2D equation of heat conduction at convective boundary conditions. For the numerical solving of the model with the help of explicit form of the finite-difference method, a software package has been prepared in the calculation medium of Visual FORTRAN Professional developed by Microsoft.
\nA validation of the model towards our own experimentally determined 2D temperature distribution in poplar logs with a diameter of 0.24 m, length of 0.48 m, and initial temperature about –30°C during their 70 h separate thawing at room temperature has been carried out.
\nDuring the validation of the model, the inverse problem has been solved for the determination of the logs’ heat transfer coefficients in radial and longitudinal directions. This problem has been solved also in regard to the logs’ surface temperature, which depends on the mentioned coefficients.
\nThe following minimum values of the average RSME total for the temperature change in four representative points in each of the studied logs have been obtained:
\nσ\navg = 1.37°C for log P1 with ρ\nb = 359 kg·m−3 and u = 1.44 kg·kg−1.
\nσ\navg = 1.34°C for log P2 with ρ\nb = 364 kg·m−3 and u = 1.78 kg·kg−1.
During the solving of the inverse task, it was determined that the heat transfer coefficients subjected to thawing logs decrease gradually, as follows:
At α\nwr: from 2.3 to 1.0 W·m−2·K−1 for P1 and from 1.9 to 1.2 W·m−2·K−1 for P2.
At α\nwp: from 5.1 to 2.2 W·m−2·K−1 for P1 and from 4.5 to 2.8 W·m−2·K−1 for P2.
Good adequacy and precision of the model towards the results from extensive own experimental studies allow for the carrying out of various calculations with it, which are connected to the nonstationary temperature distribution in logs during their thawing in an air environment. For example, as a result of such calculations, it is possible to determine the real initial temperature of logs depending on their dimensions, wood species, moisture content, and the temperature of the air near the logs during their many days staying in an open warehouse before the thermal treatment in the production of veneer.
\nThe information about the real value of that immeasurable parameter is needed for scientifically based computing of the optimal, energy saving regimes for thermal treatment of each specific batch of logs.
\nThe model of the logs’ thawing process can be applied also in the software for controllers used for advanced model predictive automatic control [20, 21, 32] of this treatment. The approach for solving of the inverse task of the heat transfer in this chapter could be further applied in the development and solving of analogous models, for example, for the calculation of the temperature fields during freezing or thawing processes of different wooden and other capillary porous materials.
\nThis document was supported by the APVV Grant Agency as part of the project, APVV-17-0456, as a result of work of authors and the considerable assistance of the APVV agency.
\n\n temperature conductivity, m2·s−1\n specific heat capacity, J·kg−1·K−1\n diameter, m acceleration of gravity, g = 9.81 m·s−2\n Grashoff’s number of similarity length, m Nusselt’s number of similarity Prandtl’s number of similarity radius: R = D/2, m radial coordinate: 0 ≤ r ≤ R, m temperature, K temperature, oC moisture content, kg·kg−1 = %/100 kinematic viscosity coefficient, m2·s−1\n exponent, − longitudinal coordinate: 0 ≤ z ≤ L/2, m heat transfer coefficients between log’s surfaces and the surrounding air medium, W·m−2·K−1\n coefficient of the volume expansion of the air, K−1\n thermal conductivity (for wood or air), W·m−1·K−1\n density, kg·m−3\n root-square-mean error (RSME), °C time, s relative humidity, % step along the coordinates r and z for solving of the model, m step along the time coordinate for solving of the model, s
\n air average (for mass temperature of logs or for root-square-mean error) basic (for wood density, based on dry mass divided to green volume) bound water maximum possible amount of the bound water in the wood computed experimental freezing end of freezing fiber saturation point free water current number of the knot of the calculation mesh in the direction along the log’s radius: i = 1, 2, 3,…, 21 = (R/Δr + 1) current number of the knot of the calculation mesh in longitudinal direction of the logs: k = 1, 2, 3, …, 41 = (L/2/Δr + 1) medium (for temperature of the air environment near the logs during their thawing process) parallel to the wood fibers radial direction surface thawing wood wood effective (for specific heat capacity) wood with frozen water in it wood with fully liquid water in it parallel to the wood fibers at °C radial direction of wood at °C initial or at 0°C 1st, 2nd, 3rd (for temperature ranges of the logs’ thawing process) at and simultaneously with this
\n current number of the step Δτ along the time coordinate during solving of the model: n = 1, 2, 3, …, N = τthaw/Δτ at 272.15 K, i.e., at –1°C at 293.15 K, i.e., at 20°C
Ubiquitin is most clearly associated with the process of targeted protein degradation, but it is involved in many cellular processes such as chromatin regulation, immune response, and antigen processing [1]. Proteosomal degradation is mediated through polyubiquitin chains linked via lysine-48 (K48) on the ubiquitin chain, interacting with the proteasome. Other processes utilize monoubiquitination or polymerization of ubiquitin molecules via another lysine. The ubiquitination system in humans is incredibly complex, with over 1000 known factors and over 10,000 known sites of ubiquitination, enabling its many and diverse roles in cellular biology.
\nIn this review, we focus on four specific roles of ubiquitin in regulating chromatin: DNA repair, transcription elongation, epigenetic silencing via the polycomb repressive complex, and bookmark ubiquitination. In these processes, the ubiquitin moiety interfaces with many other epigenetic marks, such as acetylation, methylation, and histone modification to regulate a given process.
\nThe process of ubiquitination (or ubiquitylation) is the attaching of one ubiquitin protein to a substrate and is performed by a cascade of three enzymes: E1 (activating), E2 (conjugating) and E3 (ligase) [2, 3, 4, 5]. Substrates are proteins, and in the context of chromatin, histones are the most common class of substrate [6]. Histones form octamers containing two each of the four core histones (H2A, H2B, H3, H4), and when a histone octamer is wrapped with two turns of DNA, it is called a nucleosome. Each histone has a tail that extends outside the core of the nucleosome, where it is more accessible to the modifying enzymes. In addition to ubiquitination, other modifications occur, such as acetylation or methylation. The primary role of these marks is governing the localization on the genome of specific epigenetic marks as well as the compaction and decompaction of chromatin, which regulates accessibility of the transcription machinery to chromatin. Histone ubiquitination also serves as signaling molecules for other downstream regulators of transcription, which modulates transcription both directly and indirectly. Part of this concept includes histone cross-talk, where those regulators of transcription integrate signals of multiple distinct histone modifications on the same or nearby histones to generate a phenotype due to the composite signals [7]. Therefore, nucleosome modification has a fundamental function in silencing and activation of transcription. Most histone ubiquitination occurs as a monoubiquitination, but polyubiquitin chains have also been observed. There are a number of small ubiquitin-like modifier (SUMO) proteins that share structural resemblance to ubiquitin and play some similar roles [8]. SUMO proteins come in a variety of isoforms with varying capacity for chain formation and are conjugated to substrates in a similar manner as ubiquitination.
\nSurvival of organisms and their cells depends on stability and integrity of DNA, but maintaining this integrity is a challenge for cells because they are constantly subjected to DNA damage from a variety of sources [9, 10]. DNA damage can cause disease and prevent faithful transfer of genetic information from one generation to the next. DNA double strand breaks (DSB) present a difficult problem to correct since there may be no template to guide error-free repair. In the DNA damage response, cells arrest the cell cycle and activate repair machinery. There are two primary methods eukaryotic cells use to repair DSBs: nonhomologous end joining (NHEJ) and homologous recombination (HR) [11]. The NHEJ pathway occurs throughout the cell cycle (except during mitosis) and is performed more commonly, but it is error-prone since it does not utilize a template [12]. By contrast, HR is only active during S and G2 phases of the cell cycle and because it uses the template in a sister chromatid, the repair has higher fidelity. The faulty repair observed in NHEJ can cause chromosomal rearrangements and mutations, leading to cancer susceptibility. In the following paragraphs, we highlight the roles of a variety of ubiquitin ligases and ubiquitin binding proteins to regulate the DNA damage response.
\nWhen DSBs occur, ionizing radiation-induced foci form from genome-localized high concentrations of repair machinery with a host of bound factors necessary for DSB repair. To form these ionizing radiation-induced foci, histones near the damage site become modified with K63-linked polyubiquitin chains via the action of the E2 Mms2-Ubc13 and the E3 ligases RNF168 and RNF8 [13]. These K63 chains serve as markers for recruitment of downstream repair proteins and as transcriptional repressors to prevent propagation of problems caused by broken DNA strands.
\nRNF8 has a forkhead-associated domain that binds to ionizing radiation induced foci following a cascade of events starting with the MRE11-RAD50-NBS1 (MRN) complex binding to the DSB end, followed by ATM phosphorylation of a variant H2A histone called H2AX. This phosphorylated H2AX-serine139 is known as γH2AX [14]. Sequentially, MDC1 (mediator of DNA damage checkpoint 1) binds, [15, 16, 17], and MDC1 serves as scaffold protein near sites of DNA damage, which it localizes to by using its BRCT (BRCA carboxyl terminus) domains to recruit RNF8. Following RNF8 recruitment, RNF8 ubiquitinates the linker histone H1, and thereby recruits RNF168 via ubiquitin binding domains (UBDs) binding to the ubiquitin mark [13]. RNF168, in turn, ubiquitinates histone H2A (Figure 1A).
\nUbiquitination of chromatin regulates DSB repair. (A) Following RNF8 recruitment by ATM-phosphorylated MDC1, RNF8 ubiquitinates histone H1, which is necessary for RNF168 recruitment. (B) Ubiquitination regulates expression of DSB factors. UBR5 and TRIP12 are E3 ligases, which ubiquitinate RNF168 to target them for proteosomal degradation. (C) Deubiquitinases break down polyubiquitin chains, removing ubiquitin signals that recruit DSB repair factors. (D) Ubiquitination leads to factor removal from DSB sites. JMJD2A is recognized by 53BP1 and is involved in 53BP1 recruitment. When JMJD2A is ubiquitinated, segregase activity removes it from DSB sites.
Once RNF168 has been recruited by RNF8-mediated H1 ubiquitination, it can recognize its own H2A ubiquitination mark due to the UBD on its C-terminus, allowing self-propagation of the DSB repair response [18]. RNF168-mediated H2A is capable of monoubiquitination of H2AK13–15 [19]. Chain elongation by RNF168 is atypical: as mentioned, most DSB-related ubiquitination is comprised of polyubiquitin chains linked by K63, but RNF168, when overexpressed, creates K27 linked chains instead of linkages via K63 [20]. H2AK15ub is important for the recruitment of downstream factors, most importantly 53BP1, which promotes NHEJ [21]. RNF8 and RNF168 recruit more E3 ubiquitin ligases through direct interaction with HERC2 and via their ubiquitin ligase activity, but these other E3 ligases stimulate DSB repair as scaffolds, rather than as ubiquitin ligases [22]. For example, BRCA1 and BARD1 have E3 ligase function, but their role in DSB repair is independent of their ubiquitination activity [23, 24].
\nIn NHEJ, DNA broken strand ends are bound by the Ku70-Ku80 heterodimer, which in turns allows recruitment of the catalytic subunit of DNA-dependent protein kinase (DNA-PKcs) [25, 26]. Following phosphorylation of DNA-PKcs, the DNA ends are trimmed to make them ready for ligation. This trimming plays a major role in why NHEJ is error-prone and is more damaging to cells than HR. DNA ligase IV and its associated proteins are responsible for ligating these trimmed ends and finishing the NHEJ process.
\nHR is dependent on a series of posttranslational modifications, including ubiquitination, reviewed in [27]. These modifications control a carefully orchestrated system that recruits and displaces DNA repair factors at multiple different sites during the process of HR. The role of ubiquitin in regulating HR is predicated on the following well-established model of HR. When broken DNA strands are detected, the MRN complex begins end clipping via the endonuclease activity of MRE11, along with other proteins such as EXO1, CtIP, and DNA2, creating extensive ssDNA near the break site. In addition to end clipping, the MRN complex recruits ATM. Resection of these ends at the break site allows binding by single-strand DNA binding protein, replication protein A (RPA), which is then displaced by RAD51, which enables the important difference between HR and NHEJ. RAD51 searches for homology and locates a template with which to use to repair the damaged strand. Because HR depends on this template, it can only occur during the S and G2 phases of the cell cycle, when the damaged DNA has already been replicated and the copied DNA serves as a template strand. Choosing which repair pathway, NHEJ or HR, a cell uses for repair is an important determiner of genome stability and involves complex regulatory processes involving ubiquitin.
\nRegulation of DSB repair depends on a variety of ubiquitination writers, readers and erasers. The readers and erasers require specific UBDs to recognize their specific conformations of ubiquitination. There are more than 20 unique types UBDs that are found in mammalian proteins and a few of these are enriched in proteins associated with DNA damage repair: ubiquitin-interacting motif (UIM), ubiquitin-binding zinc finger (UBZ) and motif interacting with ubiquitin (MIU) [28]. These proteins possess multiple UBDs that each bind to the target cooperatively to increase specificity and affinity. In several ubiquitin ligases, including RNF168, RNF169, RAD18, and RAP80, specificity is increased further because they possess ligand-binding regions adjacent to their UBDs, allow cooperative binding at higher specificities and affinities than otherwise possible [29].
\nRNF8 and RNF168 are important regulators of the entire DSB repair response, and require careful regulation themselves. Because these ubiquitin ligases can recognize the same mark they create, their action can cause over-recruitment and overproduction of ionizing radiation-induced foci without control mechanisms. Overproduction of these ionizing radiation-induced foci would cause widespread transcriptional repression across much larger portions of the genome than necessary. One mechanism of limitation is direct ubiquitination of RNF168 by TRIP12 and UBR5, ubiquitin ligases that recognize certain N-terminal domains and direct proteosomal protein degradation on those targets, causing a decrease in the amount of RNF168 in the cell (Figure 1B) [30].
\nAnother method of RNF8 and RNF168 regulation occurs via deubiquitinating enzymes (DUBs) (Figure 1C). Ubiquitin-specific protease 3 (USP3) has been shown to increase genomic instability and lead to spontaneous tumors when depleted in mice. This finding was supported when it was shown that UPS3 depletion led to increased levels of H2A ubiquitination, indicating the role of properly regulated H2A ubiquitination in DSB repair [31]. USP3, USP16 and USP44 and their family members also deubiquitinate H2A and thus downregulate the DSB response. One of the significant differences between these DUBs is their affinity for different lysine chains. For example, USP3 is known to target the H2A protein K13 and K15 sites that RNF168 targets as well as the K119 and K120 monoubiquitination sites of PRC1. In contrast, PSMD14 deubiqutinates K63-linked poly-ubiquitin, a different RNF8-RNF168 mediated target [32, 33]. Another DUB, USP14, downregulates DSB repair by decreasing RNF168 ubiquitination and RNF168-mediated ubiquitin signals in the setting of inhibited autophagy [34].
\nRNF8 and RNF168-mediated DSB repair can also be downregulated by phosphorylation. During mitosis, chromatin structure undergoes massive changes and most nuclear processes pause. Phosphorylation of RNF8 and MDC1 (a scaffold protein) prevents DSB repair from occurring during mitosis by blocking their interaction with 53BP1.
\nAs there are two primary pathways of DSB repair that function through entirely different mechanisms, NHEJ versus HR, cells must decide which pathway to activate. HR requires a perfect homolog to use as a template across the DSB, and for this reason HR should only function following replication of the DNA during S phase or in G2. Cells must have built-in mechanisms to suppress HR during G1, since during this stage of the cell cycle HR would use inappropriate nonhomologous DNAs as template and thus be mutagenic [35]. In addition, during mitosis, NHEJ is repressed by phosphorylation and inactivation of 53BP1 and RNF8 by the cyclin-dependent kinase CDK1 [36]. This inactivation of DNA repair is protective against chromosomal fusions at telomeres that would lead to aneuploidy. The structure of the DSB is also a factor in the decision of cells to engage in which pathway. In general, more complex DSB structures cannot be repaired via NHEJ and require the more time-consuming HR pathway [37, 38].
\nThe RNF8-RNF168 ubiquitination pathway plays an important role in determining which DSB pathway will predominate in a cell. BRCA1 stimulates HR but antagonizes NHEJ, and conversely 53BP1 antagonizes HR and promotes NHEJ [39, 40]. Ubiquitination via RNF8 and RNF168 leads to retention of 53BP1 and BRCA1 at DSB sites and the balance between these two proteins is the primary decision point between NHEJ and HR. 53BP1 functions to inhibit end resection that is necessary for HR, allowing only NHEJ to be performed. 53BP1 binds H2AK15ub (catalyzed by RNF168) through its own ubiquitin-dependent recruitment motif and also possesses Tudor domains, which recognize H4K20me2 [21, 41]. It is proposed that H4K20me2 is the signal that 53BP1 recognizes to promote its recruitment at DSB sites. RNF8–168 ubiquitinates other proteins that impact the pathway selection, including JMJD2A, JMJD3A, and L3MBTL1. When these three factors are ubiquitinated, they are released from H4K20me2. Through the action of JMJD2A, JMJD3A, and L3MBTL1 vacating H4K20me2, 53BP1 can bind freely without competition (Figure 1D) [42, 43]. H4K20me2 is another mechanism supporting the cell cycle dependent decision point between pathways. As S phase continues and more DNA is replicated, H4K20me2 becomes diluted between the two replicated DNA strands, reducing 53BP1 capacity for binding through its Tudor domains, and shifting the balance away from NHEJ to HR [44]. While 53BP1 is bound, RIF1 (and other factors) are recruited to 53BP1 and inhibit resection of the DNA ends. These factors are responsible for replacing BRCA1 at DSB sites, inhibiting HR. BRCA1, in turn, inhibits RIF1 binding at these sites, inhibiting NHEJ.
\nThe antagonist of 53BP1 is BRCA1, which promotes HR over NHEJ by way of supporting RAD51 activity. BRCA1 is a scaffold with activity that also depends on RAP80, which has a ubiquitin binding domain suspected to recognize RNF8-RNF168-mediated H2A ubiquitination and is a part of the BRCA1-A complex, which it targets to these sites of RNF8-RNF168 ubiquitination [45, 46]. However, RAP80 depletion does not lead to the expected abolishment of HR, but to increased HR activity. To explain this, it has been proposed that RAP80 is functioning to sequester BRCA1 away from DSB sites, so when RAP80 is removed, BRCA1 recruitment to DSB sites is unregulated, leading to the over activity of HR [47]. This would suggest an unknown regulator of BRCA1 recruitment to sites requiring HR activity. BRCA1 also antagonizes 53BP1 by recruiting phosphorylated UHRF1, an E3 ligase that ubiquitinates RIF1, which is bound to 53BP1 at DSB sites. Ubiquitinated RIF1 becomes displaced, reducing 53BP1 mediated repression of DNA end resection [48]. Cockayne syndrome B (CSB) protein has been proposed as fulfilling this role because it seems to antagonize 53BP1 support of NHEJ [49, 50]. In addition, when CSB is removed, DNA damage responses have been limited and CSB has been found accumulating at DSB sites.
\nOne mechanism of HR regulation is the proteasome-mediated degradation of factors important to HR, such as CtIP [51]. The decision point depends on the resection of broken DNA ends by factors such as CtIP in HR. During S and G2, when HR is stimulated, CtIP is ubiquitinated by RNF138 to promote CtIP localization to DSB sites [52]. RNF138 also ubiquitinates the NHEJ factor Ku80 during S phase, causing the Ku70/80 heterodimer to dissociate from DSB sites, and thus suppressing NHEJ during S and G2 phases [53].
\nHR is also inhibited during G1 via ubiquitination of PALB2, a factor involved in HR along with BRCA1 [54]. This ubiquitination by the E3 ligase complex CRL3 is in the BRCA1-binding domain of PALB2 and sterically blocks the two proteins from binding. The ubiquitination is antagonized by USP11, a DUB that is degraded during G1. Thus, while the balance of CRL3 to USP11 is heavily in favor of CRL3 in G1, the BRCA1-binding site on PALB2 is ubiquitinated, and so the PALB2-BRCA1 interaction is blocked, preventing BRCA1 activity, and therefore, HR.
\nA second key process regulated by ubiquitination of chromatin is transcription. As mRNA is transcribed, one protein complex that associates with the elongating RNA Polymerase II (RNAPII) is the Polymerase Associated Factor 1 Complex (PAF1) (Figure 2A) [55, 56, 57]. The PAF1 complex regulates RNAPII related transcription elongation and posttranscriptional events and is conserved across many species.
\nThe PAF1 complex ubiquitinates histone H2B during transcription elongation. (A) PAF1C ubiquitinates histones following transcription by RNAPII and elongation of mRNA. (B) The PAF1C controls multiple histone modifications, including non-ubiquitination events. The two histone ubiquitinations controlled by PAF1C are H2BK34ub and H2BK120ub. Ubiquitination of H2BK120ub is stimulated by PAF1C in concert with the UBE2A/2B and RNF20/40 heterodimers. H2BK120ub is necessary for H3K79me2/3 and H3K4me2/3, catalyzed by additional methyltransferases. The other histone ubiquitination, H2BK34ub, is created by PAF1C interaction with the MSL1/2 complex and promotes H4K16ac via MOF activity. The faded arrow represents crosstalk by which H2BK34ub regulates H3K4 and H3K79 methylation.
The PAF1 complex in humans is comprised of six protein subunits: PAF1, CDC73, CTR9, LEO1, RTF1, and WDR61 [58]. WDR61 is not present in yeast, although it is present in humans. Cells without PAF1 or CTR9 have a global decrease in protein levels and exhibit growth defects [59, 60]. The complex is found on active genes, at levels directly relating to transcription [61, 62, 63]. PAF1 binds directly to the carboxy terminal domain (CTD) of RNAPII via the Cdc73 subunit when the RNAPII CTD becomes phosphorylated via CDK9, and via Rtf1 binding along with the elongation factor Spt5 [64, 65, 66]. The localization and recruitment of PAF1C to specific sites on active genes is dependent upon many factors; in humans, PAF1C recruitment is highest at the transcription start site (TSS) or immediately (~2 nucleosomes) following the TSS [62, 67].
\nThe PAF1 complex regulates transcription and the chromatin template to ensure its readiness for transcription. The impact of PAF1C on human chromatin was first established from its role in the ubiquitination of histone H2B at K120 (Figure 2B) [68]. H2Bub is an important epigenetic mark that is associated with both activating and deactivating transcription, though its primary effect on chromatin is disrupting compaction [69]. The ubiquitination at H2BK120 is catalyzed by the E3 ligase complex containing RNF20/40, which interacts directly with the PAF1 complex, and is conjugated by the E2 UBE2A/2B. In addition to H2B ubiquitination at K120, monoubiquitination can also occur at K34 on H2B, a separate mark placed by the heterodimeric E3 ligase, MSL1/2 [70]. Both H2BK120ub and H2BK34ub stimulate histone methylation at H3K79 and H3K4, which has been demonstrated via decreases in both H2BK120ub and H2BK34ub following PAF1 depletion [71]. H2BK120ub is necessary for H3K4 and H3K79 trimethylation, while H2BK34ub functions through trans-tail crosstalk to regulate these methylations. The mechanism of this effect was revealed by experiments showing that depletion of PAF1 caused a decrease in RNF20/40 and MSL1/2 association to chromatin, indicating the role of PAF1C as promoting localization of these E3 ligases, the method by which PAF1C regulates H2Bub [71]. RNF20/40 and MSL1/2 each depend on the specific binding to chromatin by the other ligase and the corresponding histone mark, demonstrating how much interdependence exists between the two co-regulated ligases. This interaction has multiples sources. CDK9 is a kinase that promotes PAF1C association to chromatin, but is itself dependent on both PAF1C-mediated chromatin marks for its chromatin association [71].
\nDeregulation of this pathway and H2B monoubiquitination is commonly found in cancers. This can occur via multiple mechanisms, such as mutations in CDC73, one of the components of PAF1C, which has been observed in multiple cancers [72]. In addition, silencing of expression by methylation of the RNF20 promoter and RNF20 enhancers has also been observed in many breast cancers [73]. However, it has also been observed that decreased levels of H2Bub have also been shown to be associated with decreased tumor growth, an apparent contradiction to H2Bub as a cancer-causing mutation [73]. Deregulation of a mark can also occur from overactive removal; there are several DUBs responsible for H2Bub deubiquitination, including USP3, USP7, USP12, USP22, USP44, USP46, USP49 [74, 75, 76, 77, 78]. Upregulation of these DUBs can cause similar phenotypes as RNF20 depletion. Errors in H2B monoubiquitination lead to errors in chromatin structure on scales larger than the aberrantly ubiquitinated nucleosome [69].
\nDysregulation of RNF20 and concomitant H2B ubiquitination has been linked to a wide variety of cancer pathways. One method for H2Bub depletion leading to cancer occurs via H2Bub regulated inflammation and the interaction with NF-κB [79]. Inflammation involves the production of cytokines and chemokines that promote oncogenic activity and NF-κB is a key regulator of the inflammatory system. Reduction in H2Bub has been shown to lead to activated NF-κB, and thus its downstream regulation targets, leading to active inflammation in mice. This was indeed shown to lead to increased colorectal cancer in these animals. Ovarian cancers also display H2Bub dysfunction. One study found that the majority of high grade serous ovarian cancers show global decreases in H2Bub [80]. The most deadly cancer worldwide is lung cancer, and one of the more common forms of lung cancer is lung adenocarcinoma. In human lung adenocarcinomas, H2Bub decreases have been associated with increased cancer burden and a less differentiated carcinoma, a marker of poor prognosis [79].
\nMixed lineage leukemia is a classification of cancers that depend on the MLL1 gene, and rearrangements of MLL1 have been shown to be dependent on RNF20 and its role in chromatin regulation [81]. Cells lacking RNF20 showed decreased tumor growth [82]. This role of RNF20 allowing cancer progression is contrary to its role in protecting against the above cancers, but does serve to highlight the fundamental role that H2B ubiquitination plays in maintenance of chromatin.
\nWhile the preceding section described how histone H2B is ubiquitinated at multiples sites as a part of active transcription process, this section describes the ubiquitination of histone H2A, which has an opposite impact on gene expression. The polycomb repressive complex 1 (PRC1) monoubiquitinates H2A at lysine 119. H2AK119ub is a repressive mark, associated with inactive transcription by condensing chromatin, making it less accessible by transcription factors and associated machinery [83]. This repressive mark is only the most common role of PRC1, as it has also been shown to have diverse effects that have the overall impact of permanently silencing chromatin as part of the differentiation process. The two polycomb group (PcG) complexes, PRC1 and PRC2, modify chromatin to repress transcription and lead to the methylation of the promoter DNA to stably repress transcription at targeted genes. PRC2 contains the methyltransferase EZH2, which methylates histone H3 on lysine 27, H3K27me3. This review will focus on PRC1. PRC2 is necessary for targeted recruitment of PRC1, as experiments have shown that knockdown of PRC2 components also decrease PRC1-mediated H2A ubiquitination. The ubiquitination function of PRC1 is antagonized by the last form of polycomb repressive complex, polycomb repressive deubiquitinase (PR-DUB), which deubiquitinates H3K119 [84, 85]. The complimentary actions of PRC1 and PR-DUB to regulate H2AK119ub suggests the fundamental role it plays in repressing transcription.
\nPRC1 complexes exist in a number of different forms that have the same general structure, with different proteins occupying each position. The core of each complex contains a RING protein and a polycomb group RING finger protein, which bind via their RING domains [86]. This core serves as the base for further PRC1 proteins to bind. There are two possible RING proteins, RING1A and RING1B, and six possible polycomb group ring finger (PCGF) proteins, PCGF1–6. All eight of these proteins possess a RAWUL (RING finger and WD40 Ubiquitin-like) domain somewhere in their structure, which bind additional proteins [87, 88]. These additional proteins include chromobox and human polyhomeotic homolog (HPH) proteins, which, when included in the PRC1, form what is known as canonical PRC1 [89]. It was previously assumed canonical PRC1 performed the H2Aub function that is associated with PRC1, but it is now known that noncanonical PRC1 also plays an important role in gene regulation [90]. Between the variability of chromobox, HPH, RING, and PCGF proteins, there are well over 100 unique combinations of canonical PRC1 complexes that can form. This diversity plays an important role in the diverse targeting and functions exhibited by PRC1. The PCGF member of the complex binds specifically to a variety of proteins, which are responsible for targeting and regulation of the PRC1 activity [91]. Accordingly, PCGF RAWUL domains exhibit more selective binding than their counterpart RAWUL domains on the RING1A or RING1B protein. The importance of the RING domains is that the RING proteins are E3 ubiquitin ligases, responsible for the primary activity of H2AK119 ubiquitination. However, PCGF-4 (also known as BMI-1) and RING1A both do not directly ubiquitinate H2A, as only RING1B directly ubiquitinates H2A. Instead complexes containing BMI-1 and RING1A serve to promote the RING1B E3 ligase activity [92].
\nRING1B monoubiquitinates H2AK119 as part of the PRC1 activity following PRC2 methylation at H3K27 (Figure 3). PcG-regulated genes show aberrant transcriptional levels following removal of PRC1 via RING1B knockdown using shRNA [93]. PRC1-related ubiquitination and subsequent gene silencing is associated with multiple silencing contexts. PcG proteins are known to occupy and thus regulate, developmental genes, X-chromosome inactivation, and parent of origin imprinting. The most widely accepted model of the activity of PRC1-mediated inactivation of target genes is through chromatin compaction. Promoters of active genes become compacted in the setting of PRC1 action, preventing RNA polymerases from accessing the targeted gene, and therefore preventing transcription. This concept has been supported by in vitro experiments and in vivo experiments showing decreased nuclease digestion at genes with PRC1-mediated compaction of chromatin [94]. While the fact that PRC1-mediated ubiquitination of H2A leads to diminished transcription via chromatin compaction is indisputable, the mechanism is currently unclear. It has been shown that PRC1 does not have a role in regulating chromatin accessibility, only to nucleosome spacing and occupancy. Identifying the direct mechanism by which PRC1-mediated H2Aub inhibits transcription needs further elucidation.
\nCanonical PRC1 ubiquitinates H2AK119. Canonical PRC1 contains a RING protein and a PCGF protein, as defines PRC1, but is only called canonical in the presence of a Chromobox protein and a human polyhomeotic protein. This canonical PRC1 is responsible for the primary function of PRC1, ubiquitination of H2AK119. Recognition occurs at Polycomb Response Elements (PRE) containing specific DNA sequences that have been methylated by PRC2 at H3K27me3. PRC1-mediated H2AK119ub is a repressive mark, leading to decreased accessibility of targeted genes by transcription machinery, leading to inactivation of targeted genes.
Targeting of PcG complexes occurs via Polycomb Response Elements (PREs), which are DNA elements that cannot be recognized by any PcG protein because PcG proteins do not appear to possess any sequence specific DNA binding subunits [95]. While several proteins have been suggested to have a role in recognizing the PRE and enabling recruitment of PcG complexes, none have been confirmed to be sufficient to mediate PcG recruitment alone, suggesting the PcG recruitment is dependent on the interactions of several proteins coordinately creating a stable protein-DNA complex [96]. In addition to protein-DNA interactions to promote PcG recruitment, protein-protein interactions are important. PRC2 has histone methyltransferase function, methylating H3K27. PRC1 can directly recognize the H3K27me3 mark produced by PRC2 [97, 98]. Similarly, PRC2 can bind to H2Aub. This complementary interaction can serve to support preservation of PcG silencing across disruptive events to the genome, such as DNA synthesis, when histones are divided between the sister chromosomes [99]. Therefore, the most commonly accepted model of PcG recruitment is that PREs are recognized by adaptor proteins, which recruit PRC2 to promoters, which methylates H3K27. PRC1 recognizes H3K27me3 and is recruited to ubiquitinate H2AK119.
\nIn addition to the repressive effect of PRC1, it has been shown to have activating effects on transcription. PcG proteins mediate their activity by regulating genome architecture [100]. It has been reported in mouse embryonic stem cells that RING1A and RING1B organize genes into three-dimensional interaction networks, which maintains interactions between promoters in the network. When PRC1 was removed, promoter-enhancer interactions were affected, leading to activation of affected promoters and increased transcription. This supports the compaction-based theory of PRC1 transcriptional repression and provides a mechanism for this activity. Deep sequencing of ChIP experiments against selected PRC1 proteins, including both RING1A and RING1B, has shown their enrichment at active transcriptional sites in human fibroblasts [101]. This experiment also showed cell-type specific binding of PRC1. RING1B, the primary ubiquitin ligase involved PRC1-mediated H2Aub, has been found associated with Aurora B kinase at active promoters in lymphocytes, while RING1B knockdown decreased transcription at these sites, suggesting an important activating function of RING1B [102]. Cells that have had conditionally-inactivated RING1A and RING1B, and thus inactivated PRC1, exhibit errors in DNA replication [103]. Slow elongation and even stalling of replication forks has been observed in these cells in specific pericentromeric regions. These S phase errors were rescued by monoubiquitination events, suggesting the role of RING1A/B in S phase is dependent on their function as ubiquitin ligases. In breast cancer, RING1B has been found at oncogene promoters, playing an activating role and promoting cancer development and metastasis [104]. All these activating effects of PcG proteins suggest that there is much not known about the diverse array of proteins involved in PRC1 and that understanding PRC1 function may explain many previously unknown chromatin regulation events.
\nMitotic bookmarks are a mechanism of dividing cells that maintain the epigenetic and transcriptional state despite the rigors demanded by the mitosis process [105]. Although epigenetic marks persist from mother cell to daughter cell, the compaction of the genome during mitosis requires many epigenetic marks to be temporarily erased. Every mitosis, the epigenome is bookmarked, erased, and reestablished as the cells reenter G1. Cells need a mechanism allowing them to reestablish cell specific chromatin marks after they have been erased during mitosis. The mechanism cells use for “remembering” chromatin architecture is mitotic bookmarking, whereby specific molecules or proteins are found on promoters of genes that enable memory of the chromatin state before mitosis. By definition, bookmarks must be deposited in association with active genes before or at the beginning of mitosis, persist throughout mitosis, and transmit gene expression memory to the cell after mitosis (Figure 4). These mitotic bookmarks involve multiple chromatin changes, including histone modifications and histone variants. Transcription factors also make up a large number of mitotic bookmarks. Many of those transcription factors bookmark specific subsets of genes. One example of a highly selective mitotic bookmark is Brd4, which is found only on the transcription start sites of genes that are expressed at the end of mitosis and beginning of G1 [106]. Mitotic bookmarks can also regulate a specific biological process, as in the case of GATA1, which occupies locations on key hematopoietic genes during mitosis [107]. Ubiquitin has also been found to play a role as a mitotic bookmark, but while many mitotic bookmarks are specific for certain genes or pathways, the mitotic bookmark ubiquitination appears to be generally acting at genes with high transcriptional activity.
\nA mitotic bookmark containing ubiquitin is necessary for maintaining the active chromatin state after completion of mitosis. (A) An example of measuring the ubiquitin density on an active gene (GAPDH) during mitosis (gold) and during G1 (blue) [108]. The localization of ubiquitin on the chromatin shift from over the gene body during G1 through G2 to over the promoter during mitosis. (B) Model for mitotic bookmarking. During interphase, active genes have active chromatin has associated epigenetic marks, such as acetylation, whereas repressive marks as heterochromatin protein 1 (HP1) are present on inactive genes. When cells transition into mitosis, all of those marks are removed. Instead, mitotic bookmarks are placed on the active genes to enable cells to “remember” which genes were active. Ubiquitin is found on promoters of a subset of active genes and is necessary to support transcription following completion of mitosis. This ubiquitin bookmark is dependent on the E3 ligases RING1A and BMI-1. The HP1 localization is bookmarked by H3K9me3.
This novel role of ubiquitin was first identified through a variant of ChIP-seq experiments that found ubiquitin present on certain sites during mitosis that were previously not described [108]. Those experiments showed that during interphase, ubiquitin was present on the chromatin of transcribed regions of transcriptionally active genes, consistent with the known function of PAF1C. The novel observation was that ubiquitinated chromatin associated proteins were bound to promoters during mitosis, contrasted to interphase, when ubiquitin localized to the promoter was absent. The fundamental difference between interphase and mitosis was a shift of the ubiquitin detected near promoters of the same genes that were previously ubiquitinated on their transcribed regions. For example [109], the GAPDH gene is heavily ubiquitinated over the gene body during G1 (Figure 4A, indicated in blue), while during mitosis that ubiquitination over the gene body is absent but ubiquitination is detected over the promoter (Figure 4A, gold) [108]. The ubiquitinated promoter sites were consistently ubiquitinated at 150 bp upstream of the transcription start sites, suggesting a specific function relating each of these promoters. The fact that this ubiquitin bookmark was identified on promoters of active genes further supported the conclusion that this novel finding of ubiquitin in mitosis was playing a role as a bookmark, not just an incidental observation. This conclusion was also supported by the fact that the promoter-associated, mitotic ubiquitin was found on the same genes as those with PAF1C-associated transcriptional H2B-ubiquitin. The association between these two forms of ubiquitination suggests that the ubiquitin bookmark is dependent upon transcription, as is PAF1C-associated H2B-ubiquitin. However, the mechanisms underlying creation of these ubiquitination marks is different, suggesting that there is no direct relationship between these two transcription-associated marks.
\nThe presence of the ubiquitin bookmark is dependent upon the E3 ligases RING1A and BMI-1, which are both parts of the polycomb repressive complex discussed previously [109]. Surprisingly, RING1B, the primary E3 ligase involved in the PRC1 primary function has no role in bookmark ubiquitination, suggesting that the role of RING1A and BMI-1 in creating the ubiquitin bookmark is independent of their role in the PRC1 complex. However, this remains untested and what factors interact with RING1A and BMI-1 when they are involved in bookmark ubiquitination is an open question. With the discovery of the ligases responsible for the ubiquitin bookmark, it was possible to test experimentally how the process is regulated. RING1A depletion caused a decrease in phosphorylated RNAPII at promoters; the phosphorylated RNAPII was used as a surrogate for transcriptional activity, indicating that the ubiquitin bookmark was necessary for the proper transcription of the bookmarked genes, one of the criteria for mitotic bookmark. So far, what is known about the ubiquitin bookmark is that is present during mitosis, responds to changes in gene expression, and that it impacts transcription. These are the basic requirements to satisfy the definition of a mitotic bookmark.
\nBeyond the basic outline of a bookmark, there are relatively few facts known about the ubiquitin bookmark. Its localization to promoters of active genes is notable, but only a subset of active genes is found to be bookmarked, suggesting the input of more factors than active transcription and ubiquitination via RNF20/40 with PAF1C. What these factors are, even what kind of signal they are, is still unknown. Only a little is also known about the mechanism by which bookmark ubiquitination affects transcription. H3K4me3 is a histone modification known to associate with sites of active transcription. H3K4me3 has been observed decreasing when RING1A has been depleted, suggesting that the lack of ubiquitin bookmarking has caused a decrease in transcription by decreasing H3K4me3 as a signal for transcription [109]. If this phenomenon is unique to H3K4me3 or if it is common to other histone modifications correlating to active transcription is unknown. Further studies to determine this mechanism will inform the importance of this bookmark and how broadly it affects cellular function and differentiation.
\nCurrently the exact composition of the ubiquitin bookmark is undetermined. The ubiquitin bookmark must have a substrate protein that is directed to the sites identified to have ubiquitin bookmarks, and serves as the connection to chromatin. The signal has been detected via affinity-tagged ubiquitin molecules that do not discriminate between mono- or polyubiquitin, nor between the different lysine residues with which the polyubiquitin chain could be constructed. Ubiquitin is the only known component of the bookmark, but there must be other components yet to be identified. Given that most chromatin-associated proteins dissociate from the genome during mitosis, there are fewer candidates for the substrate than would be in interphase, though the possibility exists that a protein previously unknown to remain during mitosis exhibits that ability as part of the ubiquitin bookmark.
\nAnother aspect for expanding our understanding of the ubiquitin bookmark is expanding the finding of the ubiquitin bookmark to other cell lines. Thus far, all the prior work done on the ubiquitin bookmark has been done in HeLa cells, a common model system. As the ubiquitin bookmark has not been demonstrated in any other cell lines, nor in tissue samples, questions of the ubiquity of the bookmark are raised. It is formally possible that the ubiquitin bookmark is unique to HeLa cells or just cancerous cell lines and is not apparent in tissues in organisms. Obviously, the role of the ubiquitin bookmark is only relevant in an actively dividing cell, although the majority of cells in living tissues are postmitotic. Detecting the presence or lack thereof of the ubiquitin bookmark in other cell lines should be one of the most pressing directions of current research. The significance of the ubiquitin bookmark as a relatively new and poorly understood process suggests a new field in epigenetics, or at least a significant evolution in our understanding of mitotic bookmarks as primarily transcription factors that control limited selections of genes to a much larger, potentially genome-wide scale.
\nChromatin is dynamically modified as genes are silenced, as genes are expressed, as DNA damage is repaired, and as the genome is prepared for cell division. In this review, we highlighted the diverse roles of ubiquitin in each process. Understanding the complexity of the ubiquitin system is a monumental task of which the scientific community is only scratching the surface. Four important processes were reviewed here, and these processes are paramount to proper cellular functions and deregulation is generally implicated in cancers.
\nThe authors have no conflicts of interest to declare.
Authors are listed below with their open access chapters linked via author name:
",metaTitle:"IntechOpen authors on the Global Highly Cited Researchers 2018 list",metaDescription:null,metaKeywords:null,canonicalURL:null,contentRaw:'[{"type":"htmlEditorComponent","content":"New for 2018 (alphabetically by surname).
\\n\\n\\n\\n\\n\\n\\n\\n\\n\\nJocelyn Chanussot (chapter to be published soon...)
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\\n\\nKhalil Amine 2017, 2018
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\\n\\nJunhong Chen 2017, 2018
\\n\\nZhigang Chen 2016, 2018
\\n\\nMyung-Haing Cho 2016, 2018
\\n\\nMark Connors 2015-18
\\n\\nCyrus Cooper 2017, 2018
\\n\\nLiming Dai 2015-18
\\n\\nWeihua Deng 2017, 2018
\\n\\nVincenzo Fogliano 2017, 2018
\\n\\nRon de Graaf 2014-18
\\n\\nHarald Haas 2017, 2018
\\n\\nFrancisco Herrera 2017, 2018
\\n\\nJaakko Kangasjärvi 2015-18
\\n\\nHamid Reza Karimi 2016-18
\\n\\nJunji Kido 2014-18
\\n\\nJose Luiszamorano 2015-18
\\n\\nYiqi Luo 2016-18
\\n\\nJoachim Maier 2014-18
\\n\\nAndrea Natale 2017, 2018
\\n\\nAlberto Mantovani 2014-18
\\n\\nMarjan Mernik 2017, 2018
\\n\\nSandra Orchard 2014, 2016-18
\\n\\nMohamed Oukka 2016-18
\\n\\nBiswajeet Pradhan 2016-18
\\n\\nDirk Raes 2017, 2018
\\n\\nUlrike Ravens-Sieberer 2016-18
\\n\\nYexiang Tong 2017, 2018
\\n\\nJim Van Os 2015-18
\\n\\nLong Wang 2017, 2018
\\n\\nFei Wei 2016-18
\\n\\nIoannis Xenarios 2017, 2018
\\n\\nQi Xie 2016-18
\\n\\nXin-She Yang 2017, 2018
\\n\\nYulong Yin 2015, 2017, 2018
\\n"}]'},components:[{type:"htmlEditorComponent",content:'New for 2018 (alphabetically by surname).
\n\n\n\n\n\n\n\n\n\nJocelyn Chanussot (chapter to be published soon...)
\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nYuekun Lai
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\n\nAbdul Latif Ahmad 2016-18
\n\nKhalil Amine 2017, 2018
\n\nEwan Birney 2015-18
\n\nFrede Blaabjerg 2015-18
\n\nGang Chen 2016-18
\n\nJunhong Chen 2017, 2018
\n\nZhigang Chen 2016, 2018
\n\nMyung-Haing Cho 2016, 2018
\n\nMark Connors 2015-18
\n\nCyrus Cooper 2017, 2018
\n\nLiming Dai 2015-18
\n\nWeihua Deng 2017, 2018
\n\nVincenzo Fogliano 2017, 2018
\n\nRon de Graaf 2014-18
\n\nHarald Haas 2017, 2018
\n\nFrancisco Herrera 2017, 2018
\n\nJaakko Kangasjärvi 2015-18
\n\nHamid Reza Karimi 2016-18
\n\nJunji Kido 2014-18
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\n\nAndrea Natale 2017, 2018
\n\nAlberto Mantovani 2014-18
\n\nMarjan Mernik 2017, 2018
\n\nSandra Orchard 2014, 2016-18
\n\nMohamed Oukka 2016-18
\n\nBiswajeet Pradhan 2016-18
\n\nDirk Raes 2017, 2018
\n\nUlrike Ravens-Sieberer 2016-18
\n\nYexiang Tong 2017, 2018
\n\nJim Van Os 2015-18
\n\nLong Wang 2017, 2018
\n\nFei Wei 2016-18
\n\nIoannis Xenarios 2017, 2018
\n\nQi Xie 2016-18
\n\nXin-She Yang 2017, 2018
\n\nYulong Yin 2015, 2017, 2018
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