E3 ligases for CENP-A in species with regional centromeres.
\r\n\tHydrogen gas is the key energy source for hydrogen-based society. Ozone dissolved water is expected as the sterilization and cleaning agent that can comply with the new law enacted by the US Food and Drug Administration (FDA). The law “FDA Food Safety Modernization Act” requires sterilization and washing of foods to prevent food poisoning and has a strict provision that vegetables, meat, and fish must be washed with non-chlorine cleaning agents to make E. coli adhering to food down to “zero”. If ozone dissolved water could be successively applied in this field, electrochemistry would make a significant contribution to society.
\r\n\r\n\t
\r\n\tOxygen-enriched water is said to promote the growth of farmed fish. Hydrogen dissolved water is said to be able to efficiently remove minute dust on the silicon wafer when used in combination with ultrasonic irradiation.
\r\n\tAt present researches on direct water electrolysis have shown significant progress. For example, boron-doped diamonds and complex metal oxides are widely used as an electrode, and the interposing polymer electrolyte membrane (PEM) between electrodes has become one of the major processes of water electrolysis.
\r\n\t
\r\n\tThe purpose of this book is to show the latest water electrolysis technology and the future of society applying it.
Unknown plant parameters or, more generally, plant uncertainty and the preferences in which the system dynamics are purposely represented by simplifications, such as the use of linearized friction model, lead to model imprecision [1]. Control engineering classifies the model inaccuracies, which were used here as synonym of imprecision, into two main categories as structured and unstructured uncertainties. The first one implies inaccuracies within the model and the second one corresponds to inaccuracies on the system order (i.e., underestimated system order). Modeling inaccuracies can have adverse effect on nonlinear control systems [1].
\nRobotic manipulators represent the best examples for strongly coupled, highly nonlinear, time-varying dynamical systems [2]. These qualities alongside structured uncertainties caused by model imprecision of link parameters and payload variation, and unstructured uncertainties produced by unmodeled dynamics such as nonlinear friction, compliance in gearing, sensor noise, external disturbances, and the high-frequency part of the dynamics turn the motion control of rigid-link manipulators into a complex problem [2]. Particularly, robotic manipulators suffer so much from these structured and unstructured uncertainties. The consequence of having to deal with various uncertainties in their dynamics and the necessity to manage the various tools and, hence, the variation of dynamic parameters during operation make it difficult for robots to introduce a mathematical model suitable for employing model-based control strategies.
\nThe theory of conventional sliding mode control (SMC) as a simple robust nonlinear control scheme has been applied to robotic manipulators successfully since the 1980s. In those studies, the advantages of the SMC properties such as its robustness against disturbances and variation of parameters, and its fast dynamic response have been utilized greatly. Two important approaches, such as robust control and adaptive control, can deal with modeling uncertainty [1]. Particularly, adaptive control is effective in solving the structured and unstructured uncertainties and is capable of maintaining a uniformly good performance over a limited range.
\nSMC as a special class of the variable structure systems (VSS) has been preferred in practical applications for over 50 years due to its simplicity and robustness against parameter variations and disturbances [3]. VSS concept was first evolved from the pioneering work of Emel’yanov and Barbashin in the early 1960s in Russia [4]. Especially, VSS and SMC have received a great attention by the control research community worldwide since the published 1977 article [4]. SMC methodology is used to design a control law that imposes all system trajectories to converge on a surface in the state space, the so-called sliding surface \n
Despite its advantages such as simplicity and robustness, SMC suffers from a rather widespread and well-known chattering problem, which is generally perceived as motion oscillating about the predefined switching manifold(s) [3, 6]. There are two reasons behind the chattering phenomenon: first, under the absence of switching nonidealities such as delays, that is, in a situation where the switching device ideally switches at an infinite frequency, the presence of parasitic dynamics in series with the plant causes a small amplitude high-frequency oscillation to occur around the sliding manifold. If the closed loop pole locations are well defined or the closed loop poles are well assigned with the aid of the pole placement design technique, these parasitic dynamics which represent the fast actuator and sensor dynamics are often neglected in the open loop model used for control design in control applications. In general, the motion of the real system is closer to an ideal system where the parasitic dynamics are neglected, and the difference between the ideal and the real motion, which is at negligible time constants, shows a rapid decline. However, the parasitic dynamics interacted with variable structure control (VSC) in particular produce a nondecreasing oscillatory component with a finite amplitude and a frequency, referred previously to as chattering phenomenon already. Second, the switching nonidealities alone can cause such high-frequency oscillations around the sliding surface \n
SMC design procedure is split into two major steps corresponding to the two main phases [3]: reaching phase is defined to derive the system state from initial state to reach the switching manifolds in finite time; and sliding-mode phase is defined to induce the system into the sliding motion on the switching manifolds like an attractor.
\nNo matter how active the research on SMC has been during the last 50 years, the key technical challenges such as chattering, the elimination of the effects caused by unmodeled dynamics, disturbances and uncertainties, adaptive learning, and improved robustness can still remain to be addressed to reach a perfect solution [3]. An ideal sliding mode can only be achieved when the dynamic equation governing the sliding mode is satisfied by the system state for all time. This implies an infinite switching to assure the sliding motion [3]. Although the switching rate of the switching control device of the SMC system (design) is infinite ideally, it is much lower than that in practice due to the physical limitations of switching [6]. Physical limitations of switching have been tried to be explained in the previous paragraphs.
\nUsually, intelligent control approaches can mitigate the effects of structured parametric uncertainty and unstructured disturbance with their effective learning ability without requiring a detailed knowledge of the controlled plant within the design process. SMC research has recently been integrated with intelligent control approaches such as neural networks, fuzzy logic, genetic algorithms, and probabilistic reasoning, just a few of them, to make it more intelligent [3, 7, 8, 9, 10, 11]. Another goal behind the combination of the intelligent control with the attractive features of this traditional control is to create more powerful control algorithms. Nevertheless, it appears that many intelligent control algorithms do not take into account actuator dynamics in robot control systems, which play a critical role in overall robot dynamics and their negligence can cause adverse effects, especially in the case of high-speed torque, respectable load variations, friction, and actuator saturations [2]. Electrical actuators are very much controllable than others and are more suitable for driving robot manipulators [2, 12].
\nSliding mode control strategy is the simple approach to robust control. By intuition, controlling first-order systems is much easier than controlling general \n
The concepts will first be presented for systems that have a single control input that allows us to develop an intuition about the fundamental aspects of nonlinear controller design.
\nConsider the single-input dynamic system given below:
\nwhere the scalar \n
For example, in a second-order system, the position or speed cannot bounce; as a result of this fact, any desired trajectory that can be workable from time \n
Let us define \n
where \n
that is, it simply consists of a weighted sum of the position and the velocity errors; thus, we can express \n
More specifically, a \n
Additionally, the bounds on \n
where \n
Computing bounds on
In general, a first-order low-pass filter’s input-output relationship is given as follows:
\nwhere \n
Using \n
We can apply similar reasoning to the second filter, et cetera, until we reach \n
Similarly, \n
Computing bounds on
One can easily make another similar relationship, \n
One sees that the remaining \n
where the first multiplier to the right of inequality sign includes the first \n
where term comes from the result derived for the sequential blocks each of which is represented by \n
Finally, we can write,
\nsince \n
i.e., the bounds of (5) are proven. Finally, in the case where \n
Hence, we, indeed, have replaced an \n
Keeping the scalar \n
where \n
The sliding condition.
Another appealing feature of the invariant set \n
That is to say, the surface \n
Finally, if condition (2) is not fully validated, i.e., if \n
which means that
\nThis result can simply be proven to be true by starting to integrate both sides of (6) between \n
Making the necessary simplifications within the integrals, we get the following:
\nNow, the integrals are taken and evaluated for the lower and upper limits as shown below:
\nFinally from here,
\nis written, and the same result as (7) is hereby obtained. Even if \n
Furthermore, definition (3) implies that once on the surface, the tracking error tends exponentially to zero, with a time constant \n
The typical system behavior implied by satisfying sliding condition (6) is shown in Figure 4 for \n
Graphically represented
In conclusion, the idea behind (3) and (6) is to obtain an appropriate function of the tracking error, \n
Chattering caused by the switching delays.
As mentioned previously, the discontinuous control law causes chattering of the trajectories to take place around the surface \n
Boundary layer with thickness
To maintain the system work in the sliding surface, a switching action term, \n
and overall control law can be expressed as:
\nwhich will be explained in more detail in Section 5.1. Here, the nonlinear saturation function \n
where \n
A continuous-time dynamical equation of an \n
where \n
Sliding surface defined below is considered in the design of SMC controller:
\nwhere \n
Hence, one can define the sliding surface as follows:
\nNow, the following lemma refers to the sliding mode controller design.
\nsuch that
\nand
\n\n
\n
Since \n
Using (11), we get:
\nTaking \n
Then, taking \n
In the above equation, the second term is zero due to the
Next, applying (12) and (13) successively for \n
In robot modeling, the terms \n
where \n
where the operator \n
where \n
At this point, we can briefly verify that the terms on the right side of (14) are positive. First of all, it is easiest to say that the first term on the right, \n
The first, second and third terms on the right side of the equation above are negative in varying amounts and contribute to the final term, which is \n
This shows that \n
VSC systems include a group of different, generally fairly simple, feedback control laws and a decision rule. Depending on the system condition, a decision rule, usually called the
in a finite time with a small amount of overshoot with regard to the switching manifold [18].
\nThe reaching law is a differential equation that determines the dynamics of a switching function \n
where \n
The design principle of the SMC law for the plants of arbitrary order is to force a variable’s error and its derivative to zero. Tracking of a desired motion \n
and then, an \n
where \n
that determines the system bandwidth. Next, the time derivative of (28) is taken as follows [18]:
\nNow, constant plus proportional rate reaching law as represented by
\nis adapted. Substituting (30) into (29) and setting \n
Finally, substituting (31) into the non-linear plant of continuous-time dynamic model of robot systems in (8) results in:
\nThis is also known as the
In this section, the proofs of the boundedness and convergence properties of the smooth sliding mode controllers are introduced. In particular, the convergence analysis of smooth sliding mode controllers will be explained and discussed to the finest detail. Lyapunov’s direct method is used to handle the finite-time convergence of the tracking error vector to the boundary layer. Also, once in the boundary layer, the tracking error vector is said to have exponentially converged to a bounded region, as proven analytically.
\nConsider the following non-linear system class of \n
where \n
The following assumptions will be made in terms of the dynamic system presented in (33).
\nIn the proposed state space control problem, the \n
The following assumptions should also be made during the development of the control law.
\nNow, let \n
Let us define a sliding surface \n
which can be plainly rewritten as
\nwhere \n
which makes \n
It can be easily verified from (35) that \n
i.e.,
\nwhere, here, as used for the first time above, there is a definition in the form of \n
from which \n
Now, Let the problem of controlling the uncertain nonlinear system expressed by (33) be handled for review through the classical sliding mode approach that defines a control rule consisted of an equivalent control \n
where \n
Based on Assumptions 1 and 2 given above and taking into account the fact that \n
where \n
If each side is multiplied by \n
In this inequality, if inversion is applied to all terms, inequalities will be completely displaced, that is to say, it will become \n
In order to ensure \n
When we derive the expression \n
For \n
In fact, to see this result, the first thing to do is to draw \n
The control rule \n
Once the previously determined \n
The organized form of this statement will be as follows:
\nSuch that \n
We can really achieve this condition by following the steps below:
\nHere, it was previously described that \n
Note here that \n
Thus, it can be easily verified that the control rule \n
which indeed guarantees the convergence of the tracking error vector to the sliding surface \n
Here we can now guarantee that the sliding condition will be verified by choosing \n
This last operation is important; because we have reached this point by using the equations \n
If we continue where we were,
\nTherefore, since \n
So that, when \n
However, although the definition of \n
In fact, note that here the expression \n
We will now carry out the following case studies for the Eq. (41):
\n\n
\n
However, the presence of a discontinuous term (i.e., \n
Here \n
The boundary layer is accomplished by replacing the sign function with a continuous interpolation in \n
Various options are available to smooth out the ideal switch. But the closest choices are the saturation function expressed by
\nand the hyperbolic tangent function expressed by \n
The attractiveness and invariance properties of the boundary layer are introduced in the following theorem:
\nHere, as a measure of the distance of the current error to the boundary layer, \n
Noting that \n
Next, considering that the control rule given by (44) is written as
\noutside the boundary layer and noting that \n
Thus, by taking the Assumptions 1 and 2 into consideration, and defining \n
Because the Lyapunov function candidate, which we initially defined with (45) as positive definite, essentially inspired by the inequality in the form of \n
Finite-time convergence of the tracking error vector to the boundary layer can be shown remembering the expression,
\nThen, dividing both sides into \n
guaranteeing the convergence of the tracking error vector to the boundary layer in a time interval less than \n
Therefore, to keep the reaching time, \n
Time evolution of the distance of the current tracking error to the boundary layer
Lastly, the proof of the boundedness of the tracking error vector is based on Theorem 2.
\nThus,
\nor the following,
\ncan be written. If (49) is multiplied by \n
In fact, this expression is equal to
\nThat is to say,
\nWe can confirm this form of (51) for small \n
is written. Hence,
\nAt this point, we can make a confirmation by taking \n
For \n
Here, the coefficients of the three terms from left to right are 1, 2, 1. This gives the elements of the two-down row from the top of the Pascal triangle. If the expression \n
is obtained. If the result for \n
or the following expression is obtained:
\nThis verifies the multiplication of \n
If the inequality (50) is integrated between 0 and \n
and one step later,
\nand finally the following expression is reached:
\nWhen the term \n
Since we can always write,
\nas a result of replacing the derivative terms in the inequality (54) with their equivalents expressed with an absolute value one above, the inequality conditions will be preserved exactly as the term with the absolute value will be smaller than the term that satisfies the “less than or equal to” condition on the left and greater than the term that provides “greater than or equal to” condition on the right in the equality (54). Furthermore, aside from the absence of a violation, the conditions of inequality have been further reinforced. Therefore, it is possible to write the following under these conditions,
\nAlso, since both \n
The same reasoning can be applied repeatedly until the \n
In determining the generalized cases below, we would like to state in advance that we do not focus on other terms that will appear in the shape of increasing powers of \n
For
For
For
Starting with (50), when the term in the middle of inequality, \n
is written. However, due to the reason we have explained above, we would like to remind that we do not take into account other terms that will appear in the shape of increasing powers of \n
is obtained. Based on the previous similar practice, the term \n
is written. Also, if (55) is divided into \n
From here, it can be easily verified that
\nTaking into account the \n
and the derivative expression,
\nby having (56)‘s bounds accepted to (57) and dividing it back into \n
and finally from here,
\nis obtained. However, in order to determine the bounds of (58) based on only \n
expression is obtained. Now then, if the effect of \n
Similarly, taking into account the \n
and the derivative expression,
\nby imposing the bounds of (56) and (60) on (61) and dividing this expression once again to \n
Now, the bounds for \n
by multiplying each side of the inequality of (56) by the term \n
by multiplying each side of inequality of (60) by the term \n
and hence in brief, the result,
\nis concluded. As in obtaining (56), (60) and (65), the following general conclusion is reached if the similar procedure is applied sequentially until the bounds of \n
Here, the coefficients \n
In this way, by examining Eqs. (56), (60), (65), and (66) and, as much as other skipped boundaries, the integrals of (50), the tracking error will be kept within the bounds of \n
\nFigure 8 describes the \n
Convergence region
The plant is an armature-controlled dc servo motor, the scheme of which is given in Figure 9 [19].
\nDC motor schematic diagram.
In order to derive the state-space mathematical model from the physics of the motor, we first start by writing Kirchoff’s voltage equation around the armature current:
\nwhere \n
The torque, \n
where \n
Defining the state variables \n
and substituting into Eq. (69), we get
\nSolving for \n
Using Eqs. (70), (71) and (73), the state equations are written as
\nHence, in vector-matrix form,
\nNow, let us consider a position control system and assume a case of varying external disturbance torque to the dc motor. In other words, we assume that a varying external disturbance can enter into the system in the form of varying torque \n
where \n
The numerical values of motor’s parameters have been taken from the case study in [20]:
\nFinally, we try several varying external disturbance torque \n
\n\n
\n\n
\n\n
as examples, and we decide that the torque of \n
Sliding mode surface is defined as:
\nwhere \n
Taking the second row from Eq. (76) and replacing it with \n
Next, we obtain the control law \n
Once Eq. (80) is substituted into Eq. (79), we obtain the following:
\nwhere \n
Here, the following can always be written:
\nIn order to decrease the chattering phenomenon caused by sliding mode control law, saturation function is adapted in this work, and the controller becomes
\nwhere saturation function \n
where \n
Position tracking under SMC of the position control system.
Speed tracking under SMC of the position control system.
Tracking error under SMC of the position control system.
Torque vs. speed curve under SMC of the position control system.
Sliding mode surface under SMC of the position control system.
Control input under SMC of the position control system.
Phase trajectory under SMC of the position control system.
Position tracking under PD control of the position control system.
Speed tracking under PD control of the position control system.
Let us also see how the results will change if PID control is used as an alternative to the SMC. Although, in the comparisons given in the literature, the pros and cons of both strategies are mentioned, it is generally observed that SMC performs better than PID [22, 23, 24, 25]. Nevertheless, PID control can still be used as an alternative to SMC. The results given here do not contradict the view that one can use it instead of the other without losing too much performance. In the case where only the PD control strategy is applied, let us state that we need to emphasize the following points for the tracking error performance indicated by Figure 19.
\nTracking error under PD control of the position control system.
We can prefer PD control strategy mostly to advance faster between intermediate points of the entire trajectory, i.e. from waypoint to waypoint at which course is changed for following a reference trajectory in which we have to move end-effector along a predefined path. Speaking of which, the end-effector is crucial for the entire trajectory tracking problem in catching up a desired position within shortest time. In other words, accuracy is highly desirable for the end-effector to be positioned accurately under unknown disturbances and payload variations. Basically, the desired position is a function of time and continuously changes with respect to time. Therefore, conventional PD control strategy does not always exhibit good accuracy and robustness properties for trajectory tracking problem. However, we can still choose the PD control strategy because of the advantages it offers [26]. We should emphasize that the errors between the actual points and the waypoints, each of which can also be viewed as intermediate setpoints, do not necessarily have to be eliminated completely. As a result, we have decided to use the PD control because of the advantages it offers and to move faster between the waypoints by tolerating or neglecting the steady-state error computations that would bring extra computational burden (Figures 20–22).
\nTorque vs. speed curve under PD control of the position control system.
Control input under PD control of the position control system.
Phase trajectory under PD control of the position control system.
A manipulator consists of an open kinematic chain of rigid links. Power is supplied to each degree of freedom of the manipulator by independent torques. The dynamical equations of motion of an \n
\n
\n
The model given in Figure 23 is known as a two-Link (2-DOF) planar robot, as it corresponds to the two-dimensional special case, where \n
A two-link robot manipulator model.
The dynamic model chosen for the simulations is given by
\nand the dynamic equation is given by
\nwhere
\n\n
\n\n\n
Initial conditions:
\n
\n\n\n
Matlab-Simulink implementation options used in the simulations (Figures 24–31) as in [28]:
Tracking error of Joint 1 displacement under SMC of the robot manipulator.
Tracking error of Joint 2 displacement under SMC of the robot manipulator.
Tracking error of Joint 1 velocity under SMC of the robot manipulator.
Tracking error of Joint 2 velocity under SMC of the robot manipulator.
Torque at Joint 1 under SMC of the robot manipulator.
Torque at Joint 2 under SMC of the robot manipulator.
Phase portrait of Joint 1 under SMC of the robot manipulator.
Phase portrait of Joint 2 under SMC of the robot manipulator.
\n
Joint 1: \n
Joint 2: \n
The same parameters and initial conditions for the simulations have been chosen as in Section 6.2.1 except for the following ones which include the boundary layer thickness in particular:
Joint 1: \n
Joint 2: \n
Please note that due to the space constraint, we will be able to give only the figures whose effect is clearly observed, not eight figures as given in Section 6.2.1 (Figures 32–34).
\nTorque at of Joint 1 under SMC with a boundary layer.
Torque at of Joint 2 under SMC with a boundary layer.
Phase portrait of Joint 1 under SMC with a boundary layer.
For tracking a desired trajectory by two-link rigid planar robotic manipulator, PID control strategy will not work well under unknown disturbances and payload changes, and hence will not be represented here. In addition, the values of control input will get higher as in the case of DC motor position control and that would complicate the realization of such high gains through the proper actuators. On the other hand, SMC provides robustness against parameter uncertainties and unmodeled disturbances so long as the observed undesirable chattering effect is overcome through some modifications by simply replacing nonlinear signum function with nonlinear saturation function and introducing boundary layer thickness in there as explained in earlier sections. In order to realize this, the boundary layer has been introduced for the first time in Section 6.2.2 simulations, and consequently, no switching or chattering effect has been observed as can be verified by the phase portrait in Figure 34.
\nLater, the robustness of the SMC will be analyzed by adding an extra mass of \n
As a rule of thumb, It is possible to do tracking with more load by reducing the boundary layer to allow more switching to occur. Now, we reduce the boundary layer thickness from 0.02 to 0.005 and add the extra mass to Joint 2 by 0.75 kg to a final of 1.25 kg and we can still observe that SMC will be able to do the tracking by observing the reemerged chattering effect as can be seen in the following simulations (Figure 35):
Joint 1: \n
Joint 2: \n
\n\n
The rest of the parameters and the IC’s were kept the same as before.
Phase portrait of Joint 1 under SMC with a robustness test including more load.
In this study, a sliding mode control scheme with a bounded region and its convergence analysis are explained to the finest detail. In particular, it can easily be said that the work done here is a field study that specifically gives the relevant subject with such meticulous detail. It is our claim that this study has a guiding identity for the researchers who are interested in this control method or want to present it with the intelligent and modern control methodologies with its understandability and clarity targeted here. In this regard, the design of SMC including its finite-time convergence is handled by using Lyapunov’s direct method. The tracking error vector converges exponentially to the bounded region once in the boundary layer as proven analytically. Two examples were used for simulation studies to demonstrate the feasibility and effectiveness of the proposed control problems, i.e., the position control of a dc motor subject to a varying external disturbance, and a two-link robot manipulator. Simulations show that a fast convergence rate, and hence quick response, the ability to reject the varying external disturbances, and the robustness against the model uncertainty assumed to be unbounded and fast-varying have all achieved its purpose entirely. Chattering is eliminated by using the boundary layer whose attractiveness and invariance properties of the boundary layer were also introduced. This study also examines the advantages of SMC and PID comparably. Although, in the comparisons given in the literature, the pros and cons of both strategies are mentioned, it is generally observed that SMC performs better than PID. Nevertheless, PID control can still be used as an alternative to SMC. When the PID control strategy does not work well under unknown disturbances and payload changes, SMC provides robustness against parameter uncertainties and unmodeled disturbances so long as the observed undesirable chattering effect is overcome through some modifications as described in the text. Robustness analysis has been performed and successfully applied to the two-link rigid planar robotic manipulator. We have not observed any performance degradation of the trajectory to be maintained in the sliding surface. The results given here do not contradict the view that one can use it instead of the other without losing too much performance. Finally, a two-step simulation has been carried out, testing all the features mentioned above, and the results have confirmed the success of the presented approach. However, it is meaningful and challenging to develop new SMC theories and methods for nonlinear systems due to its broad application potentials in today’s world.
\nThe authors declare no conflict of interest.
During cell division, proper chromosome segregation must be achieved to avoid unequal distribution of chromosomes to daughter cells. Spindle microtubules must attach to a single region of each chromosome, termed the “centromere,” in most eukaryotes. The kinetochore is a complex of proteins that are located at the centromere. Defects in the centromere-kinetochore and spindle check point functions lead to aneuploidy and cancer and are often associated with a poor prognosis. Therefore, it is highly important to study the spatiotemporal regulation and the structures of centromere and kinetochore proteins to understand chromosome instability (CIN) during development and cancer progression. The key question is how the chromosomal location and function of a centromere (i.e., centromere identity) are determined and thus participate in accurate chromosome segregation. In most species with regional centromeres (see the previous chapter for an exception of the budding yeast
The structure of CENP-A-containing nucleosomes is more compact than H3-containing nucleosomes [2, 3, 4]. Although it is commonly reported that CENP-A-containing nucleosomes are formed with the canonical histones H2A, H2B, and H4 at the active centromeres, their structure remains controversial among different research groups [5]. CENP-A is at the top of a hierarchy of the pathway that determines the assembly of kinetochore components [6], and how CENP-A defines the position of the centromere in humans is the fundamental question. While the function of CENP-A protein is highly conserved among most eukaryotes, its protein sequence has apparently undergone both convergent and divergent evolution [7], and the centromere DNA repeats with which the CENPA-containing nucleosome interacts are also highly diverged. The architectures of CENP-A chromatin with quantified numbers of CENP-A (CenH3) molecules (e.g., ~400 molecules of human CENP-A/kinetochore) have been reported using fluorescence microscope assays among different species [8, 9, 10, 11]. CENP-A is also called CenH3 (centromere-specific histone H3). Its homologs in different species are summarized in Table 1.
Species | CENP-A homolog | E3 ligase (ubiquitylation or sumoylation) | Function | Preceding PTMs before ubiquitylation or sumoylation | Another proposed factor relevant to the E3 function |
---|---|---|---|---|---|
Cnp1/SpCENP-A | N.D. | Proteasomal degradation to remove non-centromeric Cnp1 | N.D. | N-terminal domain of Cnp1, Overexpression of H3/H4 | |
CID/Cid | CUL3/RDX (ubiquitylation) | Interacts with CAL3 and promotes CAL3 function, loading and stabilizing (maintenance) of CID protein at centromeres (proteasomal independent mechanism) | N.D. | N.D. | |
SCFPpa (ubiquitylation) | Prevents the promiscuous incorporation of CID across chromatin during replication, (targeting CID that is not in complex with CAL1) | S20 phosphorylation | S20 phosphorylation | ||
APC/CCdh1 (ubiquitylation) | Degradation of the CAL1-CID complex (likely regulates centromeric CID deposition) | N.D. | N.D. | ||
CENP-A | CUL4A/RBX1/COPS8 | Facilitate interaction of CENP-A with HJURP through CENP-A ubiquitylation, CENP-A deposition at the centromere (proteasomal independent mechanism) | N.D. | COPS8 as an adaptor, heterodimerization of CENP-A, SUGT1-HSP90 | |
AtCENH3 | N.D. (VHHGFP4-human SPOP as synthetic E3 ligase expressed in | Proteasomal degradation of AtCENH3 | N.D. | N.D. |
E3 ligases for CENP-A in species with regional centromeres.
Note: E3s of some species (e.g.,
CENP-A contains a short centromere targeting domain (CATD) within the histone fold region [2] in the C-terminus. Replacement of the corresponding region of histone H3 with the CATD is sufficient to direct histone H3 to the centromere [2], and this chimeric histone can rescue the viability of CENP-A-depleted cells [2, 12]. The CENP-A C-terminus contains another tail domain that recruits CENP-C to promote centromere and kinetochore assembly [13, 14]. CENP-N was also identified as the first protein to selectively bind CENP-A nucleosomes but not H3 nucleosomes during centromere assembly [15].
Meanwhile, the functions of the N-terminal CENP-A are also reported for some species [16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27] (see also previous chapter, Sections 2.1, 2.2.2, 2.4.1, 2.9 and this chapter, Sections 2.1, 2.3, 2.4, 3.1, 4.1, 4.6, and 5.1). Loading of CENP-A at centromeres and its incorporation/deposition and maintenance in centromeric chromatin is cell cycle-regulated. In cells overexpressing CENP-A, the ectopic protein incorporates throughout the chromatin in interphase [28]. By the next G1, however, mis-incorporated CENP-A seems to have been cleared from chromatin by a mechanism that likely involves ubiquitin-mediated proteolysis, as suggested by experiments in yeast and
Mechanistic scheme for
Mechanistic scheme for human CENP-A pathways. (Right) In normal conditions, CUL4A-RBX1-COPS8 E3 ligase activity is required for CENP-A mono- or di-ubiquitylation on lysine 124 (K124) and CENP-A centromere localization [
Models of epigenetic inheritance of CENP-A ubiquitylation through heterodimerization. In the octamer model, two CENP-A dimers in one nucleosome are split/diluted between the two daughter centromere-DNA sequences, and one CENP-A molecule replaces with one H3 molecule or leaves a molecule-free space during the replication/S phase. HJURP (Holliday junction recognition protein) predominantly interacts with ubiquitylated, preassembled “old” CENP-A, which resides mostly in nucleosomes. A non-ubiquitylated newly synthesized (“new”) CENP-A monomer targets ubiquitylated centromeric CENP-A through preassembled HJURP. Note that histone H4 is omitted for simplicity. (a) New CENP-A is appropriately ubiquitylated in a heterodimerization-dependent manner (i.e., dimers of old CENP-A with new CENP-A). In this way, both ubiquitylation and the location of the centromere are inherited epigenetically. (b) If K124 ubiquitylation does not occur on new CENP-A, the non-ubiquitylated CENP-A nucleosome distributed during the S phase does not recruit HJURP to the centromere because the affinity of non-ubiquitylated new CENP-A to HJURP is low. Subsequently, this loss of localization of HJURP at the centromere leads to the lack of new CENP-A targeting to ubiquitylated centromeric CENP-A through HJURP, and eventually to the lack of new CENP-A deposition. This figure is partly adapted from Niikura et al. [
Recently, many post-translational modifications of CENP-A and their functions have been reported [45]. They revealed the importance of these changes in CENP-A deposition at centromeres, proteolysis/protein stability, and recruitment of the CCAN (constitutive centromere-associated network) proteins [45]. Thus, here we focus on E3 ligase activities (i.e., on ubiquitylation and sumoylation) of CENP-A and summarize these functions for each species with regional centromeres in the following sections.
Fission yeast (
In fission yeast, the recruitment of the CENP-A-specific chaperone to the centromere is an essential step in epigenetic inheritance. The fission yeast Scm3 could be functionally homologous to HJURP. It interacts with CENP-A, localizes to centromeres during most of the cell cycle (except in mitosis), and is required for CENP-A deposition [48, 49]. Sequence analysis revealed a shared common domain in Scm3 and HJURP proteins [29]. Dunleavy et al. identified another chaperone known as Sim3 (start independent of mitosis 3) in fission yeast [50, 51]. Sim3 is homologous to known histone binding proteins NASP (human) and N1/N2 (xenopus) and aligns with Hif1 (
Mis16 (human homologs of Mis16 are RbAp46 and RbAp48) and Mis18 (human homologs of Mis18 are Mis18α and Mis18β) are required for loading of newly synthesized Cnp1/CENP-A into centromeric chromatin [54, 55], but are absent from organisms with point centromeres [44] (see also previous chapter, Section 2.3.3 and this chapter, Sections 3.1 and 4.1). Mis16 and Mis18 are also required for the maintenance of the hypoacetylation of histone H4 specifically within the central domain of the centromere [55], and Mis16 homologs are components of several histone chaperon complexes [56]. Moreover, acetylation of histone H4 lysine 5 and 12 (H4K5ac and H4K12ac) within the pre-nucleosomal CENP-A-H4-HJURP complex mediated by the RbAp46/48-Hat1 complex is required for CENP-A deposition into centromeres in chicken and humans [57], consistent with Hat1’s role in
In
Domain-specific function, such as the N-terminal function, of fission yeast Cnp1/CENP-A is also reported as budding yeast Cse4 [24, 25] (see also previous chapter, Section 2.4). Folco et al. demonstrated that alteration of the Cnp1 N-tail does not affect Cnp1 loading at centromeres, outer kinetochore recruitment, or spindle checkpoint signaling but significantly increases chromosome loss [17]. On the other hand, their N-tail mutants exhibit centromere inactivation enhanced by an altered centromere. The N-tail mutants specifically reduced localization of the CCAN proteins CENP-TCnp20 and CENP-IMis6, but not CENP-CCnp3. Therefore, these authors suggest that the Cnp1 N-tail maintains the epigenetic stability of centromeres in fission yeast, at least in part via assembly of the CENP-T branch of the CCAN. Tan et al. identified a proline-rich “GRANT” (Genomic stability Regulating site within CENP-A N-Terminus) motif that is essential for Cnp1 centromeric targeting [24]. They showed that especially GRANT proline-15 (P15) undergoes cis-trans isomerization to drive proper chromosome segregation. This cis-trans isomerization appears to be carried out by two FK506-binding protein (FKBP) family prolyl cis-trans isomerases. In addition, they identified Sim3 as a Cnp1 NTD interacting protein that is dependent on GRANT proline residues. Together, they suggest cis-trans proline isomerization of Cnp1 is required for precise propagation of centromeric integrity in fission yeast, presumably via targeting Cnp1 to the centromere. Thus, the requirement of cis-trans proline isomerization of CenH3Cnp1 in fission yeast studies appears to be consistent with the one of CenH3Cse4 proposed in budding yeast studies [63] (see also previous chapter, Section 2.2.3). However, they suggest that the GRANT-prolines of Cnp1 do not coordinate proteolysis of the SpCENP-A protein as do proline residues in the budding yeast Cse4 NTD. In addition, Tan et al. showed that sequential truncation of the NTD did not improve the stability of the protein, suggesting that the NTD of Cnp1 does not regulate the turnover of the protein [25]. Instead, they proposed that heterochromatin integrity may contribute to Cnp1 stability and promote its chromatin incorporation.
Compared to the studies of budding yeast and some of the other species, currently, there are few studies on post-translational modifications and domain-specific functions of fission yeast CenH3/Cnp1. Further research is required on the relationships among Cnp1 post-translational modifications, structural change, interaction with its chaperones (e.g., Scm3 and Sim3), and surrounding heterochromatin regulation.
In
Li et al. reported that the DNA polymerase (Pol) epsilon catalytic subunit A (pol2), Cdc20, interacts with the Dos1-Dos2 silencing complex to facilitate heterochromatin assembly and inheritance of H3K9 methylation during the S phase [67]. We note that fission yeast
It is important to clarify how exactly the Dos1-Dos2-Cdc20 complex contributes to the inheritance of preexisting Cnp1 during centromere replication [66]. Interestingly, Rik1 is a component of silencing factors. The heterochromatic methylation of histone H3-K9 by Clr4 is promoted by silencing factors: Dos1-Dos2-Rik1-Lid2 [67]. Horn et al. reported that subunits of a cullin-dependent E3 ubiquitin ligase interact with Rik1 and Clr4, and Rik1-TAP preparations exhibit robust E3 ubiquitin ligase activity [68]. They also demonstrated that the expression of a dominant-negative allele of the Pcu4 cullin subunit (the human Cullin-4 homolog) disrupts the regulation of K4 methylation within heterochromatin. Hong et al. also reported a novel complex that associates with the Clr4 methyltransferase, termed the CLRC (CLr4-Rik1-Cul4) complex using affinity purification of Rik1, and found that Rik1 interacts with the fission yeast Cullin4 (Cul4, encoded by
Consistent with the results in budding yeast Cse4 [23, 70, 71] (see also the previous chapter, Section 2.1), Gonzalez et al. reported that the overexpression of fission yeast Cnp1 results in the assembly of Cnp1 at non-centromeric chromatin during mitosis and meiosis [18]. The non-centromeric Cnp1 is preferentially recruited near heterochromatin and is able to recruit kinetochore components, and Cnp1 overexpression leads to severe chromosome missegregation and spindle microtubule disorganization. Moreover, ectopic Cnp1-containing chromatin is inherited over multiple generations using pulse induction of Cnp1 overexpression. Interestingly, ectopic assembly of Cnp1 is suppressed by overexpression of histone H3 or H4 (Table 1), as other groups suggest that the balance between histones H3 and H4 and CENP-A is important for centromeric chromatin assembly [72, 73]. Further, Gonzalez et al. demonstrated that deletion of the N-terminal domain of Cnp1 results in an increase in the number of ectopic CENP-A sites, suggesting that the N-terminal domain of CENP-A prevents CENP-A assembly at ectopic loci via the ubiquitin-dependent proteolysis [18].
However, it is not yet clear by which E3 ligase the exogenous Cse4 expressed in the fission yeast
In most eukaryotes, the centromere is flanked and bordered by the epigenetically distinct heterochromatin domain. The establishment of centromeric heterochromatin profoundly correlates to centromere function, but the precise role of heterochromatin in centromere specification and activation is not yet clear. The transition between point centromeres (e.g., budding yeast
Yang et al. demonstrated that budding yeast Cse4 can localize to centromeres in fission yeast and partially substitute fission yeast Cnp1, however, overexpressed Cse4 localizes to heterochromatin regions [26]. Cse4 undergoes efficient ubiquitin-dependent degradation in
However, E3 ligase targets endogenous Cnp1 is still unclear, and its degradation mechanism through heterochromatin and RNAi machinery in fission yeast is still elusive. Further study is required to elucidate how E3 ligase activity is involved in RNAi-dependent heterochromatin formation and maintenance in fission yeast.
Fruit fly (
The mechanism of heterochromatin silencing in fruit flies has been reported [81], including the position-effect variegation [82], histone modification [83], and the RNAi machinery [84]. Recently, a PIWI-interacting RNAs (piRNAs) system has been implicated in heterochromatin formation [85, 86, 87, 88], and the mechanism of heterochromatic piRNA production is being elucidated in
The timing of CID incorporation occurs during metaphase/anaphase in
In
Recently, there have been more reports published on the mechanism of how these three proteins (CID, CAL1, and CENP-C) work in CID incorporation. Chen et al. showed that the constitutive centromere protein CENP-C is required for recruitment of the
CENP-A is maintained to mark paternal centromeres, whereas most histones are removed from mature sperm. In
Studies of the neocentromere have also been performed in
In
In humans, ectopic localization of CID depends on the H3.3 chaperone DAXX rather than the centromeric CENP-A specific chaperone HJURP [34] (Figure 2, left). This human CENP-A-containing ectopic nucleosome involves a heterotypic tetramer that contains CENP-A-H4 with H3.3-H4 [34] (Figure 2, left). Cells overexpressing human CENP-A are more tolerant of DNA damage induced by camptothecin or ionizing radiation, and both the survival advantage and CTCF occlusion by the aberrant nucleosome of heterotypic tetramer in these human cells are dependent on DAXX [34] (Figure 2, left). Although
Moreno-Moreno et al. reported that the F box protein partner of paired (Ppa), which is a variable component of an SCF E3-ubiquitin ligase complex, controls CenH3CID stability in
Huang et al. showed that CID is phosphorylated at serine 20 (S20) by casein kinase II (CK2) and that the phosphorylated form is enriched on chromatin during mitosis [33] (Figure 1c and g; Table 1). Their results revealed that S20 phosphorylation regulates the turnover of prenucleosomal CID through the SCFPpa-proteasome pathway (Figure 1c; Table 1) and that phosphorylation facilitates removal of CID from ectopic but not from centromeric sites in chromatin (Figure 1g and h; Table 1). They provided multiple lines of evidence for an essential role of S20 phosphorylation in regulating restricted incorporation of CID into centromeric chromatin, suggesting that modulation of the phosphorylation state of S20 may lead to fine-tuned control of CID levels to prevent malignant incorporation into non-centromeric chromatin.
On the other hand, factors/components that stabilize ectopically incorporated CID and are required for neocentromere formation and its maintenance are not clear in
In most eukaryotes, including humans, the centromere has no defined DNA sequence but is associated with large arrays of repetitive DNA; in humans, this sequence is a 171-bp alpha-satellite DNA, although several other sequence types are found in this region. CENP-A-containing nucleosomes are formed with canonical histones H2A, H2B, and H4 at the active centromeres [5]. CENP-A nucleosomes localize to the inner plate of mammalian kinetochores [119] and bind to the 171-bp alpha-satellite DNA. Recently, the importance of centromeric cis-element, transcription, and centromeric long noncoding RNA (cenRNA) for centromere integrity has been suggested in various species, including humans [77, 78, 79] (see also Sections 3 and 5). Interestingly, when the CENP-B box DNA sequence is located proximal to the CENP-A nucleosome, CENP-B forms a more stable complex with the CENP-A nucleosome through specific interactions with CENP-A [120]. In humans, a centromeric long noncoding RNA (cenRNA) is required for targeting CENP-A to the centromere [80].
Currently, it is commonly reported that CENP-A-containing nucleosomes are formed with canonical histones H2A, H2B, and H4 at the active centromeres, however, their structure remains controversial among different research groups [5]. Bui et al. suggest that CENP-A nucleosomes alter from tetramers to octamers before replication and revert to tetramers after replication, using combinatory methods, including atomic force microscopy [38]. It is noteworthy that reversible chaperone binding, chromatin fiber folding changes, and CENP-A K124 acetylation (K124ac) and H4 K79 acetylation (K79ac) are concurrent with these structural transitions. Further computational modeling suggests that acetylation of K124 causes tightening of the histone core and hampers accessibility to its C-terminus, which in turn reduces CENP-C interaction [39] (see also the following paragraph about the function of histone H4 acetylation). Further study, including the solution of real-time post-translational modifications or the 3D structure of free Cse4 complexes, is required to determine how different chaperons recognize Cse4/CENP-A-H4 for incorporation into different locations of chromatin.
CENP-A contains a short centromere targeting domain (CATD) within the histone fold region [2]. Replacement of the corresponding region of H3 with the CATD is sufficient to direct H3 to the centromere [2], and this chimeric histone can rescue the viability of CENP-A-depleted cells [2, 12]. On the other hand, Logsdon et al. found contributions from small portions of the N-terminal tail and the CATD in the initial recruitment of CENP-C and CENP-T, using a LacO/LacI ectopic centromeric chromatin assembly system [20]. Jing et al. reported that deletion of the first 53 but not the first 29 residues of CENP-A from the N-terminus, resulted in its cytoplasmic localization [121]. They identified two motifs for CENP-A nuclear accumulation and one motif involved in the centromeric accumulation of CENP-A, as well as the interaction of CENP-A with core histone H4 and CENP-B.
Early studies in human cells showed that CENP-A mRNA and protein start to accumulate in the mid-S phase and peak in G2 [122, 123], however, further cell type-specific regulation of human CENP-A mRNA and protein remains to be studied.
In human cells, the incorporation of newly synthesized CENP-A occurs in telophase/early G1 [94, 95]. The incorporation of newly synthesized CENP-A into centromeric nucleosomes depends on the HJURP, which is a CENP-A-specific chromatin assembly factor [41, 42, 43]. Like CENP-A, HJURP is also assembled during early G1 to centromeres [42, 43, 94, 96]. The primary structural analysis demonstrated that human HJURP is a distant counterpart of Scm3, which is required to deposit centromeric nucleosomes in yeast [29]. CENP-A interacts with HJURP as a soluble pre-nucleosomal complex, and the unique structural dynamics of HJURP together with CENP-A/H4 heterodimer/tetramer (pre-nucleosomal CENP-A-H4-HJURP complex) have been reported [3, 124, 125, 126, 127, 128, 129, 130, 131, 132]. HJURP recruitment to centromeres depends on the activity of the Mis18 complex [41, 104], which affects the histone modification and DNA methylation status of centromeres [54, 59]. The human proteins hMis18 and M18BP1/KNL2 are recruited to the centromere at telophase/G1, suggesting that the hMis18 complex and RbAp46/48 (homologs of Mis16) prime the centromere for CENP-A localization [54, 133]. Moreover, acetylation of histone H4 lysine 5 and 12 (H4K5ac and H4K12ac) within pre-nucleosomal CENP-A-H4-HJURP complex mediated by the RbAp46/48-Hat1 complex is required for CENP-A deposition into centromeres in chickens and humans [57], consistent with the role of Hat1 shown in
Currently, the proteolysis mechanism for mis-incorporated human CENP-A and its E3 ligase is not yet clear (Figure 2d), and there are no reports to date on proteasome-mediated degradation of human CENP-A [138]. We reported that mono- or di-ubiquitylation of CENP-A K124 is required for CENP-A deposition at the centromere [35] (Figure 2, right). However, the stability of endogenous CENP-A is not affected by CUL4A or RBX1 depletion, and the stability of exogenous CENP-A K124R is the same as in wild-type cells. Rather, overexpression of a monoubiquitin-fused CENP-A mutant induces neocentromere formation, suggesting that signaling CENP-A mono- or di-ubiquitylation determines centromere location and activity [115] (see also Sections 4.2 and 4.3). Future studies are required to reveal how ectopic CENP-A is degraded and removed from the non-centromeric chromosome, and/or how the neocentromere established through CENP-A ubiquitylation is deactivated in humans (Figure 2c and d). This proteolysis could be initiated on chromatin and the machinery involved could be specifically excluded from centromeric regions. Alternatively, mis-incorporated CENP-A nucleosomes may dissociate more easily than those properly localized and be subsequently degraded in the nucleoplasm [139]. Obuse et al. performed chromatin immunoprecipitation with an anti-CENP-A monoclonal antibody using HeLa interphase nuclei and systematic identification of its interactors by mass spectrometric analyses [140]. They identified UV-damaged DNA binding protein 1 (DDB1) as a component of the CEN complex and BMI-1 that is transiently co-localized with the centromeric region in interphase.
RbAp46 forms a complex with the CRL4 ubiquitin ligase and DDB1 protein (where DDB1 mediates the association of CUL4 with its substrate-specific receptor—RbAP46) [141, 142]. RbAp46 is required for stabilizing CENP-A protein levels and the CRL4-RbAp46 complex activity promotes efficient new CENP-A deposition in humans [142]. This is in contrast to studies in yeast and fruit flies, where the association of CENP-A with the SCF E3-ubiquitin ligase complex leads to CENP-A degradation. However, our group showed that CUL4A-RBX1-COPS8 E3 ligase activity is required for CENP-A mono- or di-ubiquitylation on lysine 124 (K124) and CENP-A centromere localization, although our results suggest that DDB1 is not required for CENP-A recruitment to centromeres [35] (Figure 2, right; see also Sections 4.2–4.5). In humans, soluble CENP-A is associated with the centromeric CENP-A specific chaperone HJURP (see also Introduction). Depletion of HJURP leads to a significant decrease in CENP-A levels, suggesting that HJURP protects the fraction of CENP-A that will be incorporated at the centromere in G1 while remaining “free” CENP-A will be degraded to prevent its incorporation into non-centromeric chromatin [42, 43]. Our results also support this model, because CENP-A ubiquitylation enhances the affinity between HJURP with ubiquitylated CENP-A [35] (see also Sections 4.2–4.5).
One question is also generated about the function of H3.3 histone chaperone proteins, HIRA and DAXX, which were previously reported to promote ectopic CENP-A deposition in human cancer cells [34, 143]. Lacoste et al. found that CENP-A overexpression in human cells leads to ectopic enrichment at sites of active histone turnover involving a heterotypic tetramer that contains CENP-A-H4 with H3.3-H4 [34] (Figure 2, left). Ectopic localization of this particle (aberrant nucleosome) depends on the H3.3 chaperone DAXX rather than the centromeric CENP-A specific chaperone HJURP (Figure 2, left). Cells overexpressing CENP-A are more tolerant of DNA damage induced by camptothecin or ionizing radiation, and both the survival advantage and CTCF occlusion by the aberrant nucleosome of heterotypic tetramer in these cells are dependent on DAXX (Figure 2, left). However, post-translational modifications of human CENP-A, especially before recognition by DAXX and after incorporation into the ectopic nucleosome, must be elucidated (Figure 2a), and specific DAXX localization on these CTCF sites under CENP-A overexpression has to be confirmed experimentally (Figure 2b).
Shrestha et al. showed that mislocalization of CENP-A to chromosome arms is one of the major contributors to CIN, as depletion of histone chaperone DAXX prevents CENP-A mislocalization and rescues the reduced interkinetochore distance and CIN phenotype in CENP-A-overexpressing cells [144]. Nye et al. reported that in human colon cancer cells, the H3.3 chaperones HIRA and DAXX promote ectopic CENP-A incorporation [143]. They found that a correct balance between levels of the centromeric chaperone HJURP and CENP-A is required to prevent ectopic assembly by H3.3 chaperones. Their results also suggest that CENP-A occupancy at the 8q24 locus is significantly correlated with amplification and overexpression of the MYC gene within that locus. Together, CENP-A mislocalization into non-centromeric regions resulting from its overexpression leads to chromosomal segregation aberrations and genome instability [145]. Overexpression of CENP-A is a feature of many cancers and is likely associated with malignant progression and poor outcomes [146, 147, 148]. CENP-A overexpression is often accompanied by overexpression of its chaperone HJURP, leading to “epigenetic addiction” in which increased levels of HJURP and CENP-A become necessary to support rapidly dividing p53-deficient cancer cells [149]. In addition, the functional roles of DAXX and HIRA in the development of cancer and other diseases have been described [150, 151, 152, 153]. Elucidation of the proper mechanism of H3.3 incorporation into chromatin through DAXX and HIRA may also lead to proper CENP-A incorporation at centromeres as well as an effective disease (e.g., cancer) therapy.
Recently, the importance of the site-specific posttranslational modifications of human CENP-A and their biological functions has been reported [44, 45]. The functional roles of phosphorylation at CENP-A-Ser68 are still under active investigation [124, 125, 154, 155, 156]. How the defects of CENP-A PTMs and the dysfunction of centromere contribute to the generation and the development of cancer is an unsolved question. Takada et al. demonstrated that CENP-A Ser18 hyperphosphorylation by cyclin E1/CDK2 occurred upon loss of FBW7, a tumor suppressor whose inactivation leads to CIN [157]. This CENP-A Ser18 hyperphosphorylation reduced the CENP-A centromeric localization, increased CIN, and promoted anchorage-independent growth and xenograft tumor formation. Defects of CENP-A PTMs are significantly associated with chromosome segregation errors and CIN [149].
In budding yeast, Scm3 and Psh1 might compete for binding to Cse4. Cse4 that is not associated with Scm3 may be targeted by Psh1 for proteolysis, but Cse4 in a complex with Scm3 may be protected [71] (see also previous chapter, Section 2.1). On the other hand, in
In humans, our group found that CUL4A-RBX1-COPS8 E3 ligase activity is required for CENP-A mono- or di-ubiquitylation on lysine 124 (K124) and CENP-A centromere localization [35] (Figure 2, right). CUL4A complex targets CENP-A through the adaptor COPS8/CSN8 that has WD40 motifs in non-canonical CRL4 machinery (Figure 2, right). A mutation of CENP-A, K124R, reduces interaction with HJURP and abrogates localization of CENP-A to the centromere. The addition of monoubiquitin is sufficient to restore CENP-A K124R to centromeres and the interaction with HJURP, indicating that “signaling” ubiquitylation is required for CENP-A loading at centromeres (Figure 2, right).
However, one question remains—how does such mono- or di-ubiquitylation of CENP-A facilitate the interaction of CENP-A with HJURP? The CENP-A K124 site and its proximal residues might not directly affect CENP-A-HJURP interaction in the crystal structure of the HJURP-CENP-A-histone H4 complex, since we did not detect defects in CENP-A dimerization of K124R mutant (Figure 3; see also Section 4.3) or any ubiquitin interacting motif in HJURP. Therefore, we speculate that CENP-A mono- or di-ubiquitylation might sterically affect the overall conformational change, L112 residue (the closest CENP-A’s residue to K124 out of the seven residues reported to be important for appropriate interaction with HJURP), or C-terminal portion of the CATD on which HJURP recognition is mainly dependent. In addition, acetylated lysine 124 (K124) was previously reported by Bui et al. [38], but the functional role of K124 acetylation and its relationship with K124 ubiquitylation remains to be studied (Figure 2, right). Moreover, currently, the proteolysis mechanism for mis-incorporated human CENP-A and its E3 ligase is not clear, and there are no reports to date regarding proteasome-mediated degradation of human CENP-A [138] (Figure 2d). Future studies are required to reveal how ectopic CENP-A is degraded and removed from the non-centromeric chromosome (Figure 2c and d).
The mechanism by which centromere inheritance occurs is largely unknown. Gassmann et al. suggested that in
Our group showed that pre-existing ubiquitylated CENP-A is necessary for the recruitment of newly synthesized CENP-A to the centromere and that CENP-A ubiquitylation is inherited between cell divisions (Figure 3).
Numerous studies have found that CENP-A can be experimentally mistargeted to non-centromeric regions of chromatin and that this mistargeting leads to the formation of ectopic centromeres in model organisms [160]. Chromosome engineering has allowed the efficient isolation of neocentromeres on a wide range of both transcriptionally active and inactive sequences in chicken DT40 cells [57]. More than 100 neocentromeres in human clinical samples have been described [161]. They form on diverse DNA sequences and are associated with CENP-A localization, but not with alpha-satellite arrays; thus, these findings provide strong evidence that human centromeres result from sequence-independent epigenetic mechanisms. However, neocentromeres have not yet been created experimentally in humans; overexpression of CENP-A induces mislocalization of CENP-A, but not the formation of functional neocentromeres [162].
Our group demonstrated that overexpression of a monoubiquitin-fused CENP-A mutant induces neocentromeres at non-centromeric regions of chromosomes, and this result further supports our model in which CENP-A ubiquitylation is inherited and determines centromere location through dimerization (Figure 3). Our assay using the LacO/LacI ectopic centromeric chromatin assembly system clearly revealed that CENP-A ubiquitylation contributes to the recruitment of CENP-A chaperones (HJURP and DAXX) and outer kinetochore components (HEC1 and SKA1). It is possible that ubiquitylation of CENP-A contributes to maintain and stabilize ectopic neocentromeres in humans (Figure 2c).
However, it remains unclear how the neocentromere established through CENP-A ubiquitylation is deactivated. Future studies are required to reveal the mechanism of site-specific (centromeric and/or non-centromeric) deubiquitylation CENP-A and subsequent proteolysis in humans (Figure 2c and d). In this context, it would be interesting to test if the Ubp8-driven deubiquitylation mechanism in budding yeast [163] (see also previous chapter, Section 2.7) is conserved in humans.
The mechanism that controls the E3 ligase activity of the CUL4A-RBX1-COPS8 complex remains obscure. Our group found that the SGT1-HSP90 complex is required for recognition of CENP-A by COPS8 [164] (Figure 2, right). SGT1/SUGT1, a co-chaperone of HSP90, is involved in multiple cellular activities, including cullin E3 ubiquitin ligase activity [165]. The
Our group initially applied RNA interference (RNAi)-mediated SGT1 and/or HSP90 depletion in HeLa cells and found that the SGT1-HSP90 complex is required for CENP-A ubiquitylation
In our study, SKP1 siRNA treatment did not lead to any signal reduction of CENP-A at centromeres [164]. Therefore, we proposed that the SGT1-HSP90 complex is involved in CENP-A deposition at centromeres in an SKP1-independent and/or SCF-independent manner. This conclusion is consistent with our previous report that the CUL4A-RBX1 complex, which does not require SKP1 to function, contributes to CENP-A deposition at centromeres [35]. Because our results suggest that SKP1 is not required for the recruitment of CENP-A to centromeres, it is unlikely that SKP1 activity affects the CENP-A loading pathway. Because CENP-A is at the top of a hierarchy of the pathway that determines the assembly of kinetochore components [6], destabilization of the MIS12 complex at the kinetochore was observed by Davies et al. [173] could be partially due to the defect in CENP-A recruitment. This idea is supported by our results demonstrating that SGT1 siRNA treatment did not significantly change the recruitment of endogenous MIS12, HEC1, and SKA1 proteins in LacO arrays after ectopic loci were determined through LacO-LacI-CENP-A interactions. Collectively, these data suggest that the losses of immunofluorescence signals of the central-outer kinetochore proteins at the kinetochore caused by SGT1 siRNA defects, including ones reported previously [174], are explained by CENP-A mislocalization caused by SGT1 siRNA defects.
Our group reported that CENP-A K124 ubiquitylation, mediated by the CUL4A-RBX1-COPS8 complex, is essential for CENP-A deposition at the centromere [35] (Figure 2, right; see also Section 4.2). On the other hand, Fachinetti et al. reported that CENP-A K124R mutants show no defects in centromere localization and cell viability [156]. However, there are substantive problems with their experiments that yielded these results. We reported our response describing potential issues with the results and their conclusions [117]. A major caveat is that they used a fusion protein much larger molecular size than CENP-A. In their RPE-1 CENP-A−/F knockout system, the enhanced yellow fluorescent protein (EYFP) is approximately 30 kDa, and endogenous CENP-A is about 16 kDa. Fachinetti et al. also used SNAP-tags, and they found that SNAP-CENP-A K124R showed no defects in centromere deposition. Because the SNAP-tag (20 kDa) is also a larger tag than CENP-A (approximately 16 kDa) and has 10 lysines, SNAP-CENP-A K124R, presumably, is ubiquitylated at a site different than K124. One possibility is that the tagging of a large protein may endogenously lead to ubiquitylation at an amino acid other than K124 in the CENP-A K124R mutant protein, and this ubiquitylation at another site could suppress the mutant phenotype as a compensatory mechanism. Therefore, our group hypothesized that the presence of a large fusion protein promotes ubiquitylation at a different lysine in the CENP-A K124R mutant protein.
Indeed, our group found that EYFP tagging induces additional ubiquitylation of EYFP-CENP-A K124R, which allows the mutant protein to bind to HJURP [116]. Our immunoprecipitation mass spectrometry analysis showed that lysine 306 (K306) in the EYFP-CENP-A K124R mutant is ubiquitylated
In budding yeast, CENP-ACse4 is sumoylated on its N-terminal tail by Siz1/Siz2 SUMO E3 ligases [22] (previous chapter, Figure 1a and b) (see also previous chapter, Section 2.4.1). Cse4 is poly-sumoylated at K65 in its N-terminal domain, which recruits the yeast SUMO-targeted ubiquitin ligase (STUbl) Slx5, leading to the polyubiquitination of poly-sumoylated Cse4 and its subsequent degradation [21]. Cse4 K215/216 sumoylation in C-terminus also controls its interaction with the histone chaperones Scm3 and CAF-1, facilitating the deposition of overexpressed Cse4 into CEN and non-CEN regions, respectively [175] (previous chapter, Figure 1) (see also previous chapter, Section 2.4.2).
In humans, depletion of the human Slx5 homolog ring finger protein 4 (RNF4) contributes to SUMOylation-dependent degradation of the CCAN protein CENP-I, while SENP6 stabilizes CENP-I by antagonizing RNF4 [176]. SENP6 is a desumoylation enzyme as well as a member of a large family of Sentrin-specific protease enzymes (SENP1–7) [138, 177]. In budding yeast, two SUMO proteases are known, ubiquitin-like protease 1 and 2 (Ulp1 and 2); in mammalian cells, these have diverged into the SENP family. SENP1–5 is evolutionarily conserved to Ulp1, while the more divergent SENP6 and SENP7 belong to the Ulp2 group. Depletion of SENP6 in HeLa cells leads to the loss of the CENP-H/I/K complex from the centromeres, but not an apparent reduction in centromeric CENP-A/B/C levels recognized by CREST sera [176].
Liebelt et al. identified a protein group de-modification by SENP6, including the constitutive centromere-associated network (CCAN), the CENP-A loading factors Mis18BP1 and Mis18A, and DNA damage response factors [178]. SENP6-deficient cells are severely compromised for proliferation, accumulate in the G2/M phases, and frequently form micronuclei. Centromeric assembly of CENP-T, CENP-W, and CENP-A is impaired in the absence of SENP6. However, the increase of SUMO chains is not required for ubiquitin-dependent proteasomal degradation of the CCAN subunits. Therefore, their results indicated that SUMO polymers can act in a proteolysis-independent manner and consequently, have a more diverse signaling function than previously expected. On the other hand, Mitra et al. identified the SUMO-protease SENP6 as a key factor, not only controlling CENP-A stability but virtually the entire centromere and kinetochore using a genetic screen coupled to pulse-chase labeling [179]. Loss of SENP6 results in hyper-sumoylation of CENP-C and CENP-I, but not CENP-A itself. SENP6 activity is required throughout the cell cycle, suggesting that a dynamic SUMO cycle underlies continuous surveillance of the centromere complex that in turn ensures stable transmission of CENP-A chromatin. Mitra et al. and other groups did not detect sumoylation of CENP-A, suggesting that CENP-A is not a direct substrate of SENP6 [138, 179]. However, the effect of SENP6 depletion on CENP-A stability is much greater than observed on depletion of CENP-C or -B alone [179]. This result suggests that there may be other components required for the SENP6-mediated stabilization of centromeric chromatin [138].
Studies of E3 ligases at plant centromeres-kinetochores are not as advanced as those in model animal species. The structure and organization of plant centromeric DNA have been described, and satellite repeats associated with centromeres have been reported in many plant species [76]. Plant centromeres also have mega-base-sized arrays of tandem repetitive DNA sequences, as in centromeres of humans and other mammals, and transposable elements are abundant in centromeric and paracentromeric regions [76, 180]. In early studies, Jiang et al. suggest that the retention of active transcriptional machinery within the long terminal repeat may promote demarcation of an active centromere [76]. A Ty3/gypsy class of centromere-specific retrotransposons, the centromeric retrotransposon (CR) family, was discovered in the grass species. Highly conserved motifs were found in the long terminal repeat of the CR elements from rice, maize, and barley [181]. The CR elements are highly enriched in chromatin domains associated with CENH3/CENP-A, the centromere-specific histone H3 variant. CR elements as well as their flanking centromeric satellite DNA are actively transcribed in maize. These data suggest that the deposition of centromeric histones might be a transcription-coupled event. The importance of centromeric transcription and centromeric long noncoding RNA (cenRNA) for centromere integrity has been suggested in various species, including plants [77, 78, 79] (see also Sections 3 and 4). Moreover, in maize, CENP-C binding to centromeric DNA is associated with small RNA [182], whereas in humans CENP-A loading is linked to lncRNAs [80]. It is not yet known whether the same transcript can recruit and stabilize both CENP-A and CENP-C at centromeric chromatin [77].
Plant CENH3/CENP-A and other centromere-kinetochore proteins have been reported showing high conservation among species. On the other hand, DNA sequences of plant centromeres, of which loci are determined epigenetically by centromeric histone 3 (CENH3), have revealed high structural diversity, ranging from the canonical monocentric form seen in vertebrates, to polycentric and holocentric forms [183, 184]. Plant centromeres can change position over evolutionary time or upon genomic stress, such as in McClintock’s genome shock [185] or physically damaged or broken chromosomes [183]. Jiang et al. suggested that the centromeric state is reinforced and maintained by the tension applied during spindle attachment [76]. The chromatin damaged by such mechano-force could then be marked for repair by the replication-independent mechanism similar to the one originally incorporated in CENH3. Indeed, human centromere-kinetochore proteins, including CENP-A, are involved in DNA damage/repair [186], and the incorporation of newly synthesized CENP-A occurs “right after mitosis” (i.e., telophase/early G1) [94, 95]. However, the model of CenH3 (CENP-A) incorporation upon mechano-force-induced DNA damage/repair is not yet experimentally demonstrated, and its precise mechanism needs to be elucidated. Meanwhile, there is evidence of divergent evolution originating in CenH3 in plants [187, 188] and
Plant studies of dicentric centromeres and neocentromeres have been described along with those of other eukaryotes [180, 183]. The active state of one of the two centromeres on the wheat dicentric chromosome can be epigenetically silenced [180], as in the human dicentric chromosome [191]. Neocentromeres have been described extensively in human and fruit fly chromosomes as well as in some plant species, such as barley, maize, and rice [114, 184, 192]. In
Plant studies of minichromosomes and artificial chromosomes also have been reported, as in other eukaryotes [180, 183]. The main issues of these studies are what are the size and factors required for the maintenance and stability of such special chromosomes during cell division. Harrington et al. constructed human artificial minichromosomes [197], and Ananiev et al. artificially generated minichromosomes in maize by introducing the DNA molecule containing native centromere segment, ori, and telomere repeats [198]. These studies suggested that repetitive DNA may play an important but unknown role in centromere function. The repetitive centromeric DNA may be still important, although it is not essential for centromeric function, since plant centromeric DNA does not generate functional centromeres when reintroduced into plant cells [199] and new centromeres are functional even if located in loci with non-centromeric DNA [161].
In terms of the plant CENH3 recruitment mechanism to centromeres, most CENP-A is loaded in G2 by a replication-independent mechanism in
Currently, an endogenous E3 ligase for plant CENP-A (CENH3) is not yet identified. Sorge et al. developed a synthetic biology approach to degrade plant CENP-A using E3-ligase adapter protein SPOP (Speckle-type POZ adapter protein) with a specific anti-GFP nanobody (VHHGFP4) [201] (Table 1). To determine the function of proteins, CRISPR/Cas9-based methods and antisense/RNAi strategies are commonly used to remove the selected protein from all organs in a cell- and tissue-specific manner. However, CRISPR/Cas9 and antisense/RNAi strategies are still error-prone and can show off-target effects [202]. Classical genetic strategies to knock out/down protein function in plants still have problems, such as the time-consuming process of generating homozygous transgenic lines or the risk of lethal phenotypes at early developmental stages.
Sorge et al. attempted to solve these problems by utilizing the synthetic E3 ligase activity in protein ubiquitylation and degradation pathway. They successfully recruited the 26S proteasome pathway to directly degrade CENP-A of
Each species reviewed in our articles, including the previous chapter has advantages and disadvantages for research. For example, the centromere sequence size of the budding yeast is small and the sequences can be easily mutated to identify the important functional regions [203]. Techniques such as ChIP are also possible, which cannot be easily performed on highly repetitive centromeres in other organisms. Moreover, the centromere can be shifted to other genomic regions, allowing the construction of artificial chromosomes and plasmids as well as tools, such as conditional centromeres. Fission yeast and fruit fly models have progressed more than others in studies of heterochromatin regulation and gene silencing. Plant models have advanced more in evolutionary studies of centromeric DNA structures, including CR family comparisons among different plant species.
On the other hand, in fission yeast and plant species, the E3 ligase of CENP-A (CenH3) and its specific regulation and/or function are not yet identified. The E3 ligase of CENP-A is unknown in multiple species (e.g.,
Studying the mechanisms of formation and maintenance of neocentromeres will deepen our understanding of the centromere-kinetochore formation and promote the building and establishment of artificial chromosomes. Such studies will lead to the construction of artificial cells and tissues that can be controlled by DNA levels through chromosome dynamics. As a result, the function of E3 ligase can be artificially adjusted, which will increase the effectiveness of future gene therapies. Minichromosomes generated to date suggest that the repetitive centromeric DNA may be still important, although perhaps, it is not essential for centromeric function. In addition, it is unclear whether there is causality or feedback between cenRNA transcription and overall transcriptional change after chromosome missegregation and CIN. As of now, we have little understanding of the effects of these cenRNAs on the E3 ligase of CENP-A, including how these transcriptional changes and regulation are related to the function of E3 ligase.
Although our group showed that ubiquitylation occurs at a different site than CENP-A K124 as endogenous compensatory machinery, the compensatory machinery of post-translational modifications in endogenous conditions is poorly understood. This machinery can be incorporated in a process of disease progress or development. For example, suppose a post-translational modification is required for host cancer cell development but its activity can be blocked by cancer drugs. However, another site’s post-translational modification could compensate for that change, so that host cancer cells can survive, proliferate, and eventually metastasize. For cell proliferation and differentiation in general, such compensatory machinery could be a versatile backup system. However, such backup systems may not have been detected experimentally due to our limited technology or brief experimental periods. Thus, many E3 ligases may work in similar signal pathways (see also the previous chapter, Conclusion), or the function of a post-translational modification in one site may be compensated for or complemented by another site, but it is currently unknown how likely such complementary machineries would be. Research to predict such compensatory systems and resilience could be expected as future directions to study the spatiotemporal regulation of E3 ligase of CENP-A.
Ultimately, studies of E3 ligase in CENP-A in higher mammals or humans are essential for translational research and informing future therapy. Overexpression and mislocalization of human CENP-A are presumably features of cancer development, however, the detailed mechanisms for cancer development and possible therapies still remain unclear. In addition to cancer, translational studies of CENP-A and its E3 ligase could be beneficial for CREST autoimmune diseases and other diseases. Centromere proteins, including CENP-A, have been identified as antigens from CREST patients [204, 205], but the mechanism that causes CREST syndrome and how CENP-A and other centromere-kinetochore proteins are involved is unknown. Observations of neocentromeres were also reported in patients with other developmental diseases [206], but research has been limited, in part because of the relatively smaller number of patients.
Defects in ubiquitin E3 ligases promote the pathogenesis of several human diseases, including cancer, and CRL4 [207], a well-defined E3 ligase, has been reported to be upregulated and is proposed to be a potential drug target in cancers [208]. However, the biological functions of CRL4 and the underlying mechanism regulating cancer chemoresistance are still largely elusive. In humans, proteolysis activity of CRL4 ubiquitin ligase targeting CENP-A has not been observed so far, and other E3 ligases that function in CENP-A proteolysis are unidentified (Figure 2d). It is also important to determine if ubiquitylation or sumoylation-related enzymes, including E3 ligases, can be druggable targets.
Tumors develop in complex tissue microenvironments, where they depend on for sustained growth, invasion, and metastasis [209]. We could be at a turning point to fill the gap between the detailed intracellular mechanisms of CENP-A function studied in the past and its mechanism in complex tissue microenvironments. Thus, cell type and/or tissue-specific CENP-A function involved in different types of cancer in different organs is a likely focus for future research. There are many unknowns about whether the function of E3 ligase of CENP-A represents a cell or tissue-specific difference, or whether the cell or tissue completely replaces E3 ligase itself. The utilization and application of organoid, spheroid, and coculture systems may reduce the effort, time, and cost that is required to answer these questions and ultimately yield better therapies.
We thank past and current researchers at Model Animal Research Center, School of Medicine, Nanjing University, Greehey Children’s Cancer Research Institute at UT Health Science Center San Antonio, the Research Institute at Nationwide Children’s Hospital, and St. Jude Children’s Research Hospital for their helpful discussions. Y.N. was supported by Jiangsu Province “Double-First-Class” Construction Fund, Jiangsu Province Natural Science Fund (BK20191252), Jiangsu Province 16th Six Big Talent Peaks Fund (TD-SWYY-001), Jiangsu Province “Foreign Expert Hundred Talents Program” Fund (BX2019082), and National Natural Science Foundation in China (31970665). KK was supported by the National Science Foundation under Grant No.1949653 (KK) and a Mays Cancer Center Pilot Award CCSG P30 CA054174.
The authors declare no conflict of interest.
The company was founded in Vienna in 2004 by Alex Lazinica and Vedran Kordic, two PhD students researching robotics. While completing our PhDs, we found it difficult to access the research we needed. So, we decided to create a new Open Access publisher. A better one, where researchers like us could find the information they needed easily. The result is IntechOpen, an Open Access publisher that puts the academic needs of the researchers before the business interests of publishers.
",metaTitle:"Our story",metaDescription:"The company was founded in Vienna in 2004 by Alex Lazinica and Vedran Kordic, two PhD students researching robotics. While completing our PhDs, we found it difficult to access the research we needed. So, we decided to create a new Open Access publisher. A better one, where researchers like us could find the information they needed easily. The result is IntechOpen, an Open Access publisher that puts the academic needs of the researchers before the business interests of publishers.",metaKeywords:null,canonicalURL:"/page/our-story",contentRaw:'[{"type":"htmlEditorComponent","content":"We started by publishing journals and books from the fields of science we were most familiar with - AI, robotics, manufacturing and operations research. Through our growing network of institutions and authors, we soon expanded into related fields like environmental engineering, nanotechnology, computer science, renewable energy and electrical engineering, Today, we are the world’s largest Open Access publisher of scientific research, with over 4,200 books and 54,000 scientific works including peer-reviewed content from more than 116,000 scientists spanning 161 countries. Our authors range from globally-renowned Nobel Prize winners to up-and-coming researchers at the cutting edge of scientific discovery.
\\n\\nIn the same year that IntechOpen was founded, we launched what was at the time the first ever Open Access, peer-reviewed journal in its field: the International Journal of Advanced Robotic Systems (IJARS).
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\\n\\nWe started by publishing journals and books from the fields of science we were most familiar with - AI, robotics, manufacturing and operations research. Through our growing network of institutions and authors, we soon expanded into related fields like environmental engineering, nanotechnology, computer science, renewable energy and electrical engineering, Today, we are the world’s largest Open Access publisher of scientific research, with over 4,200 books and 54,000 scientific works including peer-reviewed content from more than 116,000 scientists spanning 161 countries. Our authors range from globally-renowned Nobel Prize winners to up-and-coming researchers at the cutting edge of scientific discovery.
\n\nIn the same year that IntechOpen was founded, we launched what was at the time the first ever Open Access, peer-reviewed journal in its field: the International Journal of Advanced Robotic Systems (IJARS).
\n\n2004
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\n\n\r\n\tEducation and Human Development is an interdisciplinary research area that aims to shed light on topics related to both learning and development. This Series is intended for researchers, practitioners, and students who are interested in understanding more about these fields and their applications.
",coverUrl:"https://cdn.intechopen.com/series/covers/23.jpg",latestPublicationDate:"June 25th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:0,editor:{id:"280770",title:"Dr.",name:"Katherine K.M.",middleName:null,surname:"Stavropoulos",slug:"katherine-k.m.-stavropoulos",fullName:"Katherine K.M. Stavropoulos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRdFuQAK/Profile_Picture_2022-05-24T09:03:48.jpg",biography:"Katherine Stavropoulos received her BA in Psychology from Trinity College, in Connecticut, USA. Dr. Stavropoulos received her Ph.D. in Experimental Psychology from the University of California, San Diego. She completed her postdoctoral work at the Yale Child Study Center with Dr. James McPartland. Dr. Stavropoulos’ doctoral dissertation explored neural correlates of reward anticipation to social versus nonsocial stimuli in children with and without autism spectrum disorders (ASD). She has been a faculty member at the University of California, Riverside in the School of Education since 2016. Her research focuses on translational studies to explore the reward system in ASD, as well as how anxiety contributes to social challenges in ASD. She also investigates how behavioral interventions affect neural activity, behavior, and school performance in children with ASD. She is also involved in the diagnosis of children with ASD and is a licensed clinical psychologist in California. She is the Assistant Director of the SEARCH Center at UCR and is a Faculty member in the Graduate Program in Neuroscience.",institutionString:null,institution:{name:"University of California, Riverside",institutionURL:null,country:{name:"United States of America"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:2,paginationItems:[{id:"89",title:"Education",coverUrl:"https://cdn.intechopen.com/series_topics/covers/89.jpg",isOpenForSubmission:!1,editor:{id:"260066",title:"Associate Prof.",name:"Michail",middleName:null,surname:"Kalogiannakis",slug:"michail-kalogiannakis",fullName:"Michail Kalogiannakis",profilePictureURL:"https://mts.intechopen.com/storage/users/260066/images/system/260066.jpg",biography:"Michail Kalogiannakis is an Associate Professor of the Department of Preschool Education, University of Crete, and an Associate Tutor at School of Humanities at the Hellenic Open University. He graduated from the Physics Department of the University of Crete and continued his post-graduate studies at the University Paris 7-Denis Diderot (D.E.A. in Didactic of Physics), University Paris 5-René Descartes-Sorbonne (D.E.A. in Science Education) and received his Ph.D. degree at the University Paris 5-René Descartes-Sorbonne (PhD in Science Education). His research interests include science education in early childhood, science teaching and learning, e-learning, the use of ICT in science education, games simulations, and mobile learning. He has published over 120 articles in international conferences and journals and has served on the program committees of numerous international conferences.",institutionString:"University of Crete",institution:{name:"University of Crete",institutionURL:null,country:{name:"Greece"}}},editorTwo:{id:"422488",title:"Dr.",name:"Maria",middleName:null,surname:"Ampartzaki",slug:"maria-ampartzaki",fullName:"Maria Ampartzaki",profilePictureURL:"https://mts.intechopen.com/storage/users/422488/images/system/422488.jpg",biography:"Dr Maria Ampartzaki is an Assistant Professor in Early Childhood Education in the Department of Preschool Education at the University of Crete. Her research interests include ICT in education, science education in the early years, inquiry-based and art-based learning, teachers’ professional development, action research, and the Pedagogy of Multiliteracies, among others. She has run and participated in several funded and non-funded projects on the teaching of Science, Social Sciences, and ICT in education. She also has the experience of participating in five Erasmus+ projects.",institutionString:"University of Crete",institution:{name:"University of Crete",institutionURL:null,country:{name:"Greece"}}},editorThree:null},{id:"90",title:"Human Development",coverUrl:"https://cdn.intechopen.com/series_topics/covers/90.jpg",isOpenForSubmission:!0,editor:{id:"191040",title:"Dr.",name:"Tal",middleName:null,surname:"Dotan Ben-Soussan",slug:"tal-dotan-ben-soussan",fullName:"Tal Dotan Ben-Soussan",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSBf1QAG/Profile_Picture_2022-03-18T07:56:11.jpg",biography:"Tal Dotan Ben-Soussan, Ph.D., is the director of the Research Institute for Neuroscience, Education and Didactics (RINED) – Paoletti Foundation. Ben-Soussan leads international studies on training and neuroplasticity from neurophysiological and psychobiological perspectives. As a neuroscientist and bio-psychologist, she has published numerous articles on neuroplasticity, movement and meditation. She acts as an editor and reviewer in several renowned journals and coordinates international conferences integrating theoretical, methodological and practical approaches on various topics, such as silence, logics and neuro-education. She lives in Assisi, Italy.",institutionSt