text:
Investigating the sequence-dependent mechanical properties of DNA nicks for applications in twisted DNA nanostructure design

Abstract DNA nick can be used as a design motif in programming the shape and reconfigurable deformation of synthetic DNA nanostructures, but its mechanical properties have rarely been systematically characterized at the level of base sequences. Here, we investigated sequence-dependent mechanical properties of DNA nicks through molecular dynamics simulation for a comprehensive set of distinct DNA oligomers constructed using all possible base-pair steps with and without a nick. We found that torsional rigidity was reduced by 28–82% at the nick depending on its sequence and location although bending and stretching rigidities remained similar to those of regular base-pair steps. No significant effect of a nick on mechanically coupled deformation such as the twist-stretch coupling was observed. These results suggest that the primary structural role of nick is the relaxation of torsional constraint by backbones known to be responsible for relatively high torsional rigidity of DNA. Moreover, we experimentally demonstrated the usefulness of quantified nick properties in self-assembling DNA nanostructure design by constructing twisted DNA origami structures to show that sequence design of nicks successfully controls the twist angle of structures. Our study illustrates the importance as well as the opportunities of considering sequence-dependent properties in structural DNA nanotechnology.

where represents the coordinate vector of BP step parameters as = [τ ρ ω Dx Dy Dz] , whose average is denoted as the angle bracket, is displacement vector whose components indicate the displacement from average configuration, and is a positive definite stiffness matrix where the six diagonal and remaining symmetric off-diagonal terms represent mechanical stiffness (bending, torsion, shearing, and stretching) and coupling stiffness, respectively.
The probability distribution of BP step parameters can be approximated to an N-dimensional Gaussian function assuming moderate fluctuations under harmonic potential in contact with a heat bath of a certain temperature. The covariance matrix of the BP step parameters was used to induce the stiffness matrix of a BP step (1-3) as = k B T −1 (2) where k B is the Boltzmann constant, T is the absolute temperature used in MD simulation, and is the covariance matrix. Here, the covariance matrix was obtained using from the sampled MD trajectories of the BP step parameters (4) as The strain energy can be rewritten as the sum of diagonal and off-diagonal components as (4) where i and j represent the BP step parameters as τ, ρ, ω, Dx, Dy , and Dz . Diagonal terms contribute to mechanical rigidities corresponding to the six BP step parameters, and mechanical coupling coefficients are derived from off-diagonal terms between two BP step parameters. Mechanical rigidities of a BP step were then obtained by multiplying the diagonal stiffness components to the axial length of a BP step from linear elastic theory as Likewise, mechanical coupling coefficients of a BP step were calculated by multiplying the offdiagonal stiffness to the axial length of the BP step as g ij = K ij 〈Dz〉 (8) where g ij represents the mechanical coupling coefficients of two different BP step parameters. For example, g ωDz represents the mechanical coupling coefficient of twist and rise, implying the twiststretch coupling.

Supplementary Method S2. Derivation of mechanical rigidities of a base-pair (BP) step.
Mechanical rigidities were derived as assuming DNA structures of a homogeneous linear elastic material. The initial shape was assumed to have an area (A) and length (L) with axial z-direction. Then, the representative mechanical rigidities (B τ , B ρ , C, Y Dx , Y Dy , and S) were derived by elastic theory.
Bending rigidity (EI) is then evaluated as where k bending is the stiffness defined by the ratio of applied bending moment and corresponding bending deformation. Bending rigidities of DNA, therefore, can be calculated in terms of components of stiffness matrix and BP step parameters as where B τ and B ρ represent tilt and roll bending rigidities, and K ττ and K ρρ indicate the diagonal tilt and roll components in the stiffness matrix, respectively.
(B) Torsional rigidity. Torsional moment (M z ) is obtained by integrating the shear stress (σ τ ) multiplied by the moment arm (r) over the cross-section area (A) as where shear stress (σ τ ), shear strain (γ), and the second polar moment of area (J) are defined as Then, the torsional rigidity (GJ) is evaluated as where k torsion is the stiffness defined by the ratio of applied torsional moment and corresponding torsional deformation. Therefore, we obtained the torsional rigidity of DNA corresponding to the twist parameter as where C is generally referred to torsional rigidity of DNA, and K ωω is the diagonal twist component in the stiffness matrix.
(C) Shearing rigidities. Shearing rigidity is derived from the shear modulus (G) defined by the ratio of shear stress (σ τ ) to the shear strain (γ) as where F and ∆L are the applied shear force and corresponding shear displacement. The shearing rigidity (GA) is then obtained as where k shearing is the stiffness defined by the ratio of applied shear force and corresponding displacement. We then obtained the shearing rigidities of DNA as where Y Dx and Y Dy denote shearing rigidities corresponding to the shift and slide, and K DxDx and K DyDy are the diagonal shift and slide components in the stiffness matrix, respectively.
where k stretching is the stiffness defined by the ratio of applied axial force and corresponding displacement. Therefore, the stretching rigidity of DNA is obtained corresponding to the rise mode as where S is generally referred to the axial rigidity of DNA, and K DzDz is the diagonal component corresponding to the rise parameter in the stiffness matrix.

Supplementary Method S3. Derivation of an equivalent isotropic rigidity in bending and shearing.
Assuming a homogeneous linear elastic material, if a transverse load was applied to a beam, whose axis system coincides with the principal axes of bending, three-dimensional beam theory implies the following displacement field as where z is the axial direction of the beam, x and y are the planar directions on the cross-section of the beam, and θ x and θ y are rigid body rotations of the cross-section respectively. The strain field can be evaluated by the differentiation of the displacement field as ε xx = ε yy = γ xy = γ yz = γ xz = 0 where the curvatures are defined as The axial stress is described by Hooke's law as The strain energy (π) stored in the beam with anisotropic bending rigidities is evaluated as where I x and I y are the second moment of area with respect to x-and y-directions on the crosssection.
When an equivalent isotropic beam is assumed, the force equation under a bending moment is found as If the strain energy stored in anisotropic and equivalent beams is the same, the following equation is satisfied π = ∫ We performed MD simulations of 6HB DNA origami structures with BP-insertion (Supplementary Figure   S9). At each end of the simulated structure, 7-BP-long strands were added to eliminate the boundary effect. Since it was difficult to observe the effects of sequence control of nicked BP steps due to the limited system size, MD result of an arbitrary sequence was used to predict an approximately twist angle of 6HB structures. For the fast convergence of equilibrium states, the initial all-atom structures were developed after 100-ps-long the elastic network-guided simulation (5). All-atom explicit solvent simulations were then performed after energy minimization as previously described for DNA oligomers.
To smoothly convert the induced strain energy by BP-insertion into global torsion of structures, we applied weak harmonic constraints to Watson-Crick base-pairing from 0.5 kcal mol -1 Å -2 to zero during 60-ns-long simulation as previous MD studies on DNA origami structures (5,6). Final 20-ns-long equilibrated trajectories were sampled to calculate twist angle (Supplementary Method S5).

structure.
The twist angle of a 6HB structure was calculated by the summation of local twist angles of twisting blocks between sequential hexagonal cross-sections locating at Holliday-junctions. To obtain the local twist angle between hexagonal cross-sections, we defined six vertexes locating at helices of the 6HB structure as the averaged point of local origins in four neighboring BPs next to the hexagonal crosssection. A hexagonal cross-section was determined to satisfy the smallest sum of the distance between each vertex and an arbitrary plane. Auxiliary vectors (A ⃗ ⃗ 1 , A ⃗ ⃗ 2 , A ⃗ ⃗ 3 ) were defined in hexagonal crosssections: A ⃗ ⃗ 1 , A ⃗ ⃗ 2 , and A ⃗ ⃗ 3 were defined as the vectors from vertex 1 to 4, 2 to 5, and 3 to 6, respectively.
Subsequently, the triads in hexagonal cross-sections were determined: x-vector ( x ⃗ ) representing normalized axial direction was defined as a normal vector of each cross-section, y-vector (y ⃗ ) in the hexagonal cross-sections was described as a normalized vector with projection of an averaged vector of auxiliary vectors on the cross-section, and the z-vector (z ) was calculated using the cross product of x-and y-vector. A rotation matrix ( ) between sequential triads was then obtained using the triads as where i and i + 1 represent successive hexagonal cross-sections. The rotation vector ( ⃗ ⃗ ) equivalent to the rotation matrix was obtained as where W ij is a component of the skew-symmetric matrix ( ) defined as = 1 2 ( − T ). The local twist angle between sequential hexagonal cross-sections (Ω) was finally calculated as We obtained the Gaussian mean and standard deviation of the twist angle in the unit twisting block from MD simulation (Supplementary Figure S9). If the twist angle of the unit twisting block (Φ u ) follows Gaussian distribution (N u ) as where Φ u0 and σ u are the Gaussian mean and standard deviation of the twist angle of the twisting block, we could calculate the twist angle (Φ) of a DNA structure, in which same twisting blocks are connected in sequence and the number of twisting blocks is m, as the sum of the independent Gaussian distributions of the twisting blocks based on the probability theory as Since ten twisting blocks were employed in the entire structure, the approximate range of twist angle of the structure was estimated as the mean of 10Φ u0 and the standard deviation of √10σ u using those of unit twisting blocks (Φ u0 and σ u ) by MD simulation.

Supplementary Method S7. Relation of the trans ratio with the twist angle of 6HB DNA structures.
We followed the details of derivation in the previous study (10). Assuming that 6HB origami structures fluctuate in a harmonic potential, the Gaussian distribution of twist angle can be derived from the Boltzmann distribution as where N 0 is the normalization coefficient as 1/(σ√2π) , E is torsional harmonic energy as E = k t (Φ − Φ 0 ) 2 /2, Φ is the twist angle of 6HB structure, Φ 0 is the equilibrium twist angle, σ is the standard deviation of twist angle as k t /(k B T), and k B T is the product of the Boltzmann constant, k B , and the absolute temperature, T. Here, the torsional stiffness of 6HB structure (k t ) has a relation with torsional persistence length (L P ) and the length of 6HB structure (L) as where the torsional persistence length of 6HB DNA structures (L P ) was reported as 530 nm in a previous study (11), and the length of our structure is approximately 300 nm in AFM images (Supplementary The probability to deposit into trans monomer of the 6HB structures is obtained as where k is an integer as a parametric variable (⋯ , −2, −1, 0, 1, 2, ⋯ ). This probability to deposit into trans monomer is a kind of triangular function, which is plotted as The trans ratio, TR(Φ 0 ) in equilibrium is derived by the average probability of twist angle weighted in Φ 0 for all Φ domain as Using the Gaussian integrals, We then obtained the four integral terms in the equation (51) as Hence, by substituting the equation (60a-d) into the equation (51), the relation of trans ratio with twist angle is derived as Here, the arguments in the k-summation rapidly approach to zero when Φ 0 is out of the range of

Supplementary Notes
Supplementary Note S1. The sensitivity of mechanical properties in simulating environments and neighboring sequence variation.
In this study, we investigated the mechanical properties of nicked BP steps, suggesting that BP steps To verify, we simulated all the BP steps for 100 ns employing the parmbsc1 force field (12), another widely used force field in DNA oligomer simulations, to obtain the mechanical properties and the C B ⁄ ratios. As in the previous results obtained using the CHARMM36 force field, the parmbsc1 force field provided the sequence-dependent properties for regular and nicked BP steps (Supplementary Figure S8 and Supplementary Tables S8-S13). It was also confirmed that nicks led to a significant reduction in torsional rigidity regardless of the force field used. On the whole, the geometry, mechanical rigidities, and coupling coefficients predicted by two force fields were comparable for both regular and nicked BP steps. While the parmbsc1 force field predicted relatively smaller torsional and shearing rigidities than the CHARMM36 as found in previous studies (12,13), the C B ⁄ ratios predicted by the parmbsc1 were not significantly deviated from those obtained using the CHARMM36 because the torsional rigidity decreases for both regular and nicked BP steps Figure S8). Therefore, we could confirm that the trend of C B ⁄ ratio (and hence our design approach) is not sensitive to the choice of force field.
While limited, we increased the time duration from 100 to 300 ns for the GC/GnC step as a selected subset. We also performed additional simulations of 300 ns using parmbsc1 force field with 100 mM of NaCl (Supplementary Figure S5). It was apparent that RMSD values were maintained within 2-8 Å , suggesting that oligomers stayed near an equilibrium state. Results indicated that the mechanical properties of BP steps did not considerably alter compared to original simulation either the simulation time was extended or salt concentrations was changed from MgCl2 to NaCl concentration.
Furthermore, to investigate the effect of the next-nearest-neighbor sequence variation, another additional MD simulations performed for nicked GG/CnC and AA/TnT steps as a limited subgroup in order to evaluate the effect of adjacent sequence variation of a BP step (Supplementary Figures S6 and S7). The dinucleotide GG/CnC step analyzed in this study is the same with the tetranucleotide AGGA/TCnCT step when considering neighboring sequences for original DNA oligomer (Supplementary Table S1). Likewise, the AA/TnT step was identical to with the hexanucleotide GAAAAG/CTTnTTC step. We modified the sequence of the original oligomer for GG/CnC step from GACT4-GAC-TCnCT-CAG-TCAG4 to GACT4-GAC-ACnCA-CAG-TCAG4 to have the same dinucleotide GG/CnC step in the center but different tetranucleotide TGGT/ACnCA step. Likewise, the oligomer with AA/TnT step was also modified from GACT4-GA-CTTnTTC-AG-TCAG4 to GACT4-GA-GTTnTTG-AG-

Supplementary Note S2. Mechanical analysis of DNA bundle structures with BP-insertion.
We theoretically investigated mechanical parameters related to the twist angle of a DNA bundle structure with BP-insertion. A two-helix-bundles (2HB) structure was introduced as the smallest twisting structure by BP-insertion (A), where terminal ends were constraint by Holliday-junctions. It was assumed that two identical and straight helices (H1 and H2) have the radius of r, bending rigidity of B, and torsional rigidity of C. Also, there was nothing to induce strain energy since the end of two helices cross exactly at both ends.
When BPs are inserted but one of the Holliday-junctions is not constrained (B), the initial twist angle due to the helicity of DNA can be regarded as where 〈ω〉 is the mean twist angle of each helix and the number of inserted BPs was denoted as N BP .
Also, each helix is elongated to a longitudinal length of L.
In equilibrium with the constraints at both ends of the helices (C), bending and torsional strain energy is induced at each helix to align the mismatch of connectivity and the center of twist. In addition, bending and torsional angle should satisfy a geometric constraint equation (g) as where θ and Φ represent the equilibrium bending and twist angle of a helix. Then, the induced strain energy in the helix can be described using the method of Lagrange multipliers as where the bending (M b ) and torsional moment (M z ) were derived in Supplementary Method S2 as where the zero initial bending and initial twist angle by BP-insertion yield the angle deformation as Then, the strain energy is derived using the above equations as The equilibrium configuration minimizes this strain energy, suggesting that the gradient of the strain energy is zero vector. We, therefore, obtain the system of equations as Here, the bending angle (θ) can be substituted to twist angle (Φ) with the constraint equation (72), providing a relation of twist angle with rigidities of each helix and the number of inserted BPs as This relation suggests that DNA bundle structures could be more twisted when BPs are more inserted or C B ⁄ is increased in helices. We found that nicks have significant effects on the reduction of torsional rigidity (C) rather than the reduction of bending rigidity (B). It is, therefore, speculated that the twist angle of bundle structures could be controlled by adjusting the location of nicks to control C B ⁄ value. Here, we defined that C B ⁄ ratio of nicked BP steps normalized by corresponding regular BP steps as ⁄ ) regular to quantify the effects of nicks from an ideal structure consisting of all regular BP steps. Utilizing the C B ⁄ ratio data from MD simulation, the twist angle of the structures with high C B ⁄ ratio could be deliberately designed greater than that with low C B ⁄ ratio, suggesting that the torsional energy stored by BP-insertion could be controlled by adjusting nicked BP steps. Future studies based on nonlinear analysis is promising to produce a more realistic theoretical prediction on the DNA structures since our approach is limited to only provide the insight of finding parameters to affect bundle structure due to the simple and linear assumption.

Supplementary Note S3. Comparison of the results of the reverse-phase cartridge (Bio-RP) and the polyacrylamide gel electrophoresis (PAGE) methods in the purification of staples.
We investigated whether the purification method used in the synthesis of oligonucleotides affects the trans ratio of assembled DNA origami structures. Here, 60 staples comprising ten twisting blocks of the flexible 1 design with 2-BP-insertion were purified using the polyacrylamide gel electrophoresis (PAGE) method, in which the manufacturer guarantees a higher purity of more than 95%. We obtained the matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF) data for representative ten staples (one staple per each twisting block) purified by both methods (Supplementary Table S19). According to the result of MALDI-TOF, purified staples using Bio-RP and PAGE showed almost identical mass spectrum with a single and clear peak, indicating only oligonucleotides with the desired length existed in the stock solution (Supplementary Figure S11). Noting that the maximum error of the MALDI-TOF spectrum is typically around 0.24%, we could confirm that both Bio-RP and PAGE methods were reliable to obtain the full-length and same sequence of staples. In addition, we constructed two versions of the flexible 1 design using the staples purified with Bio-RP and PAGE methods (Supplementary Figure S12). No distinguishable difference in the trans ratio was observed between these two versions of structures (Supplementary Table S16). The mean and standard deviation of the trans ratio by two methods were 0.7245 and 0.0609 for Bio-RP, and 0.7204 and 0.0272 for PAGE, respectively. Accordingly, we concluded that the trans ratio was hardly affected by the purification method for staples because both methods yield sufficiently high purity.

Supplementary Figures
Supplementary Figure S1. Root-mean-square deviation (RMSD) of DNA oligomers. Each RMSD value was calculated from the minimized structure omitting the four terminal BPs on each end. Supplementary Figure S11. The results of MALDI-TOF using Bio-RP and PAGE methods. We obtained the MALDI-TOF results for representative ten staples (one staple per each twisting block). Table   S19).  Supplementary Table S1. List of MD-simulated DNA oligomers. Each oligomer is 42-BP-long DNA double helix and has the same sequence pattern, 5'-CTGA5-MN-AGTC5-3' / 5'-GACT5-PQ-TCAG5-3'.

Supplementary Tables
MN/PQ represents one of ten regular BP steps. Since MN/PQ or PQ/MN indicate identical one of ten BP steps, we selected notations by comparing M and P in order of A > G > T > C. For example, we chose AG/CT notation in AG/CT or CT/AG case. MnN/PQ or MN/PnQ represent one of sixteen nicked BP steps.    Mean rigidity ratio of each structure was calculated by dividing the summation of multiplying each rigidity ratio and the corresponding number of nicked BP steps by sixty as the total number of nicked BP steps.
A figure below the table shows the mean rigidity ratio values for each structure.


extfieldsofstudy: Biology Medicine

s2fieldsofstudy: Biology Medicine Psychology

text:
From microcephaly to megalencephaly: determinants of brain size.

Expansion of the human brain, and specifically the neocortex, is among the most remarkable evolutionary processes that correlates with cognitive, emotional, and social abilities. Cortical expansion is determined through a tightly orchestrated process of neural stem cell proliferation, migration, and ongoing organization, synaptogenesis, and apoptosis. Perturbations of each of these intricate steps can lead to abnormalities of brain size in humans, whether small (microcephaly) or large (megalencephaly). Abnormalities of brain growth can be clinically isolated or occur as part of complex syndromes associated with other neurodevelopmental problems (eg, epilepsy, autism, intellectual disability), brain malformations, and body growth abnormalities. Thorough review of the genetic literature reveals that human microcephaly and megalencephaly are caused by mutations of a rapidly growing number of genes linked within critical cellular pathways that impact early brain development, with important pathomechanistic links to cancer, body growth, and epilepsy. Given the rapid rate of causal gene identification for microcephaly and megalencephaly understanding the roles and interplay of these important signaling pathways is crucial to further unravel the mechanisms underlying brain growth disorders and, more fundamentally, normal brain growth and development in humans. In this review, we will (a) overview the definitions of microcephaly and megalencephaly, highlighting their classifications in clinical practice; (b) overview the most common genes and pathways underlying microcephaly and megalencephaly based on the fundamental cellular processes that are perturbed during cortical development; and (c) outline general clinical molecular diagnostic workflows for children and adults presenting with microcephaly and megalencephaly.

Introduction
Th e adult human brain weighs between 1200 to C l i n i c a l r e s e a r c h the forebrain and total cortical surface area, is among the most remarkable evolutionary processes and correlates with a wide range of cognitive, social, and emotional abilities in humans. [4][5][6] The increase in cortical volume and, consequently, brain size that occurred in the genus Homo is believed to explain the emergence of human-specific cognitive and social abilities that arose with this genus, although the underlying morphologyto-function relationships that arose during evolution are not fully understood. 7 Nonetheless, this hypothesis is supported by evidence that different neuroanatomical regions followed different developmental patterns, possibly due to the relative cognitive and social functions that developed at any given time; with the visual cortex and the premotor area (associated to sight and motor control) developing at a slower rate compared to temporal lobe and prefrontal cortex (associated with memory, emotions and conceptual understanding). 7,8 Human brain size is determined through a tightly orchestrated and intricate process of neural stem cell proliferation, expansion, migration, followed by ongoing organization, synaptogenesis, and apoptosis. The molecular mechanisms underlying the positive and negative regulation of these processes -and the extreme cases of microcephaly and megalencephaly seen in humans -have provided scientists with important evolutionary insights about the brain. Identification of mutations of key genes associated with microcephaly (eg, primary microcephaly genes such as ASPM, CDK5RAP2, MCPH1, CENPJ) for example, has led evolutionary biologists and anthropologists to establish the presence of selective pressure during human evolution. 9,10 Interestingly, the development of the mammalian neocortex appears to be a species-specific process with notable differences even in species that are genetically similar. 11,12 The uniqueness of the human neocortical development and evolution seems to be due to the presence of increased heterogeneity in the neural precursors population, in particular the presence of outer radial glia cells in the outer subventricular zone, which are absent or present in very low numbers in other mammals. [12][13][14][15] This highlights a decades-long challenge for scientists trying to model neurodevelopmental disorders associated with brain growth dysregulation, as animal models often do not recapitulate all of the features of neurological disorders in humans primarily due to intrinsic differences in embryonic neocortical development. 16,17 Neurodevelopmental disorders associated with abnormal brain growth with or without cortical malformations are important causes of morbidity and mortality with multiple neurodevelopmental consequences including intellectual disability (ID), autism spectrum disorders (ASD), and epilepsy typically manifesting in infancy or early childhood. Further, expert review of large cohorts of children with malformations of cortical development (MCDs) has identified brain size to be an important predictor of the degree of neurological impairment. 18 The occipitofrontal circumference (OFC) of full term infants ranges from 32 to 37 cm at birth, increasing by 0.4 cm per week during the first several months and by ~1 cm per month during the first year of life, with the first 2 years of life characterized as the most rapid period of brain growth during development, to ultimately reach the adult human OFC of 52 to 58 cm and 52.5 to 58.5 cm in females and males, respectively. 1 Assuming head size is normally distributed in populations, 0.1% of children have a head size more than 3 SD above or below the mean. This suggests that more than 220 000 of the 74 million children living in the USA have severe megalencephaly (MEG) or microcephaly (MIC), and many more have mild MEG or MIC. 19 The prevalence of microcephaly (OFC ≤3 SD) in Europe was found to be 1.53 per 10 000 individuals between 2003 and 2012 (95% confidence interval 1.16 to 1.96) in a recent populationbased study. 20 Brain growth abnormalities can be isolated or occur in a wide range of neurodevelopmental syndromes. Microcephaly has been reported in more than 700 genetic syndromes, and macrocephaly in more than 200 genetic syndromes in the Online Mendelian Inheritance in Man (OMIM) database (the more specific clinical term for brain overgrowth, megalencephaly or MEG, is less used in this database).
In this review, we will (a) overview the definitions of microcephaly and megalencephaly, highlighting their classifications in clinical practice; (b) overview the most common genes and pathways underlying microcephaly and megalencephaly based on the fundamental cellular processes that are perturbed during cortical development; and (c) outline general clinical molecular diagnostic workflows for children and adults presenting with microcephaly and megalencephaly. Table I lists the most common genes, pathways, and syndromes known to be associated with brain growth abnormalities in humans, to date. Figure 1 presents a schematic overview of the genetic and non-genetic causes of microcephaly and megalencephaly broadly,

Definition, clinical classifications, and clinical features
Microcephaly (MIC) is classically defined as a head circumference more than two standard deviations (SD) below the mean for age and sex. However, most experts define clinically significant (ie, diagnostically useful) MIC as 3 SD or more below the mean, as many children with a head OFC between 2-3 SD are developmentally normal. 19,21,22 About 15% of children referred to child neurologists for evaluation of developmental disabilities have MIC, which is often associated with comorbidities such as epilepsy, autism, and other birth defects. 19 Genetic and non-genetic factors can cause an abnormally small brain size. Genetic causes including a  rapidly growing list of single gene disorders, copy number abnormalities (ie, deletions/duplications), and large chromosomal rearrangements (eg, triosomies) (Figure 1, Table I). Non-genetic or environmental insults include in utero or congenital infections (eg, congenital Zika virus, cytomegalovirus, and herpes simple virus, among others), teratogenic exposures (eg, alcohol, drugs such as hydantoin or aminopterin) and vascular insults (eg, placental insufficiency). 19 However, knowledge regarding the underlying causes of MIC remains limited in scope, and the diagnostic and therapeutic approaches for children with MIC are not uniform, as highlighted by the Zika virus epidemic in 2015-2016. 1,2,5,6 A confusing number of terms have been used to clinically classify MIC including "primary microcephaly" which refers to early-onset (ie, typically congenital) MIC with no other syndromic features including (classically) no additional brain abnormalities besides a simplified cortical gyral pattern. 22 "Autosomal recessive primary MIC" (or MCPH) was a clinical diagnostic term used for the earliest familial reports and loci of MIC, later defined by several key features including (a) severe congenital MIC (OFC ≤4 SD below the mean at birth), (b) ID in the absence of more severe neurological problems including spasticity, seizures or developmental regression and (c) absence of other syndromic features including body growth abnormalities or additional brain malformations. [23][24][25] To date, mutations in 23 genes have been identified as causative of primary microcephaly (Table I). However, the remarkable emerging genetic and clinical heterogeneity of MIC syndromes has challenged traditional classifications and uncovered a wide range of syndromes in which individuals can have overlapping features including brain size abnormalities, body growth abnormalities and complex malformations of cortical development. 26,27 Indeed, mutations of the same genes have now been identified in expanding spectra involving these features. Examples include MIC and cancer phenotypes due to mutations in DNA Damage Response genes, such as Nijmegan Breakage syndrome, and isolated MIC and Microce-phalic Osteodysplastic Primordial Dwarfism (MOPD) phenotypes due to centrosomal defects. 26 When the brain is small, the most common abnormality identified on brain imaging (typically magnetic resonance imaging, MRI) is a simplified cortical gyral pattern that is typically diffuse but can disproportionately affect the frontal lobes (ie, microcephaly with a simplified gyral pattern). 28 By definition, this is the most common brain MRI abnormality identified in children with most forms of MIC. However, additional brain abnormalities can co-occur with MIC, partly depending on the underlying etiology, including cortical malformations such pachygyria, polymicrogyria, dysgyria (eg, due to mutations of the tubulin genes), callosal abnormalities (including most notably a small or thin corpus callosum), as well as abnormalities of the cerebellum, brainstem, basal ganglia, white matter among others. 28 Therefore, thorough examination of neuroimaging features associated with MIC is often diagnostically very helpful, as shown in Table I.

Genes and pathways underlying human MIC
In examining the large body of literature on genes and pathways underlying human -particularly congenital -MIC, several important functional classes of defects can be clearly discerned. 26 The earliest identified MICassociated genes and loci were critical centrosomal and cell cycle defects that continue to account for the largest fraction of MIC molecular diagnoses worldwide. These include centrosome-specific proteins (eg, CEP135, CENPJ, PCNT, MCHP1), spindle-associated proteins (eg, ASPM, WDR62) and, less commonly, kinetochore associated defects (eg, CENPE). By far, mutations in the majority of these genes are inherited in an autosomal recessive fashion and are, therefore, more widely seen in in-bred or consanguineous populations. 29 Mutations of the ASPM (Abnormal Spindle Microtubule Assembly) gene alone are estimated to account for 10%-40% of the causes of autosomal recessive congenital MIC (or MCPH). 30 Mutations of this broad class of genes have been well-documented to cause a wide range of cell cycle defects including abnormal centrosome structure and function, abnormal spindle-kinetochore assembly, and abnormal microtubule structure and function. 26 More recently, mutations of a critical class of microtubule-associated genes including those belonging to the tubulin family (eg, TUBA1A, TUBB2B, TUBG1, TBCD, among many others) and the kinesin protein (eg, KIF11, KIF14) have been identified to cause complex MIC syndromes characterized by a wide range of brain malformations including cortical malformations, callosal abnormalities, and dysgenesis of the brainstem, basal ganglia, and thalami, with wide variability among affected individuals. 31,32 In contrast to the most common centrosomal defects underlying MIC, mutations of these genes are typically de novo, with consequently a low-recurrence risk. 32 The second-largest group of human functional defects associated with MIC is defects in the DNA Damage Response (DDR) pathway. The DDR is a signaling cascade critical for repairing DNA strand repairs due to endogenous and exogenous insults. The large number of associated mutations, genes, and syndromes known to be associated with congenital MIC that are related to DDR and centriole/spindle organization support the fundamental roles these pathways play in neuronal development and genomic stability. 33,34 The intimate relationship between these pathways and cancer is further supported by the association of many of these MICassociated genes with cancer phenotypes in humans, as occurs with mutations in NBN, NHEJ1, XRCC2, XRCC4 among many others, for example. 35 Collectively, the overwhelming majority of genes associated with congenital MIC are critical nodes in very early stages of neuronal development and have yielded substantial insights into their fundamental roles. 36 In contrast, acquired causes of MIC, such as Zika virus (ZIKV) related MIC, for example, appear to typically affect later stages of neuronal progenitors, inducing apoptosis and defects of differentiation rather than severe neuroproliferative defects, although the mechanisms of ZIKVrelated MIC continues to be under intense study. [37][38][39] Megalencephaly

Definition, clinical classifications and clinical features
From DeMyer's work, MEG or "large brain" has been defined as an oversized and overweight brain that ex-ceeds the mean by two SD for age and gender, consistent with standard medical practice which uses a normal range of ±2 SD for growth parameters. 40 Similar to MIC, clinically significant MEG is now defined as 3 or more SD above the mean, as most individuals with mildly large head size (+2-3 SD) have been found to have normal development. 40 The largest documented brain sizes in human reach more than 10 SD above the mean, reported more recently in individuals with mutations of the phosphatidyl inositol 3-kinase (PI3K)-AKT-MTOR pathway including AKT3. 41 Abnormalities of brain size can occur early on during fetal development and manifest at or shortly after birth (ie, congenital MEG), or evolve more slowly during infancy and early childhood (ie, postnatal MEG). 26 Clinically significant MEG has been classified into anatomic and metabolic subtypes, a classification scheme first proposed by De-Myer that continues to be of clinical use as these two large MEG groups differ substantially in their underlying genetic causes, pathomechanisms, clinical features and medical management. 40 Metabolic (or neurometabolic) syndromes associated with MEG include a wide range of disorders characterized by abnormal accumulation of metabolic substrates, typically associated with consequent neuronal hypertrophy with ballooning of the cytoplasm, and fundamentally less cellular hyperplasia. 40,42 Anatomic MEG includes a wide range of disorders characterized by a multitude of cellular defects including increased cell size and/or number.
From the early literature, brain overgrowth has been proposed to occur in several distinct "non-syndromic" clinical forms. The earliest is familial MEG (also termed "idiopathic MEG") that has been reported and proposed to be the most common form of MEG seen in children. 40 Individuals with this clinical "entity" classically had mild MEG (OFC +2-3 SD above the mean) with familial recurrence reported in up to 50% of children in large series. [43][44][45][46] Importantly, a subset of these children with familial MEG had neurodevelopmental problems including epilepsy and tone abnormalities, suggesting that brain overgrowth, even if presenting as an isolated feature, can be associated with neurological consequences. 45,[47][48][49] Further, neuroimaging on many children with this reported MEG subtype identified ventriculomegaly, enlarged extra-axial spaces, or hydrocephalus requiring shunting, overlapping with syndromic forms of MEG (such as the PI3K-AKT-MTOR related MEG syndromes) and suggesting a more com-plex process underlying head overgrowth that may involve both brain overgrowth and cerebrospinal fluid expansion causing hydrocephalus. 47,[49][50][51] MEG has also been reported as a very common clinical feature in children with autism spectrum disorders (ASD), with several studies suggesting that it is the most common physical manifestation seen in ASD. 52 Mutations of the PTEN gene have been identified in ~10% to 20% of megalencephalic children with ASD, which has led to the delineation of the "macrocephalyautism syndrome" as a subtype of the PTEN-hamartoma tumor related disorders. [53][54][55][56] However, wider scale genomic testing has now identified mutations of many other genes associated with MEG-ASD as well, including most notably MTOR, PPP2R5D, CHD8, among others, strongly suggesting that the etiologies of MEG and ASD are much more genetically heterogeneous but likely linked to some of the same critical cellular pathways. 57

Genes and pathways underlying human MEG
Disorders causing an abnormally large brain size (ie, true MEG) most often occur as a result of a genetic insult that may cause isolated brain overgrowth (eg, PTEN related hamartoma tumor syndrome) or combined brain and body overgrowth as part of a generalized overgrowth disorder (eg, Sotos syndrome, PIK3CA related overgrowth disorders). 58,59 Most of these disorders are caused by defects of single genes, although a growing number of copy number abnormalities have also been identified in overgrowth syndromes ( Table I).
Mutations of key nodes in several signaling pathways regulating cellular growth and proliferation cause a wide range of human brain overgrowth disorders including the PI3K-AKT-MTOR, RAS-MAPK-ERK pathways, among others. [60][61][62][63] Importantly, a growing number of human overgrowth disorders are caused by mutations in epigenetic regulators such as NSD1, EZH2, DNTM3A, among others. 64 A broad overview of the involved genes and pathways highlights that most of these are within critical intermediary signaling pathways that are highly pleiotropic in function and, unlike MIC, the cellular effects of these pathway perturbations on neuronal development are not as well-understood ( Figure 1).
The most common genetic defects causing human MEG localize to the PI3K-AKT-MTOR pathway. Proper MTOR signaling is critical in key aspects of brain de-velopment including neuronal progenitor maintenance, differentiation, migration, synaptogenesis, and regulating protein translation. [65][66][67][68] Therefore, mutations of different nodes causing functional upregulation of this pathway are associated with a wide range of neurodevelopmental phenotypes including MEG, ID, ASD, and epilepsy in humans and animal models. These nodes include a growing number of genes located upstream (PIK3CA, PIK3R2, PTEN), midstream (AKT3) and downstream (TSC1, TSC2, MTOR, CCND2, TBC1D7, RHEB, and STRADA) within the pathway. 69 Besides diffuse brain overgrowth (MEG), a growing number of mosaic (postzygotic) mutations of this pathway are associated with focal malformations of cortical development with intractable epilepsy, including focal cortical dysplasia (FCD), hemimegalencephaly (HMEG) and dysplastic megalencephaly (DMEG). [70][71][72] The functional endpoint of all mutations associated with diffuse or focal MEG phenotypes is pathway hyperactivation. The proposed mechanisms by which PI3K-AKT-MTOR pathway mutations are believed to cause brain overgrowth include neuronal hypertrophy (eg, PTEN-and MTORrelated brain overgrowth), and increased neuronal proliferation (eg, CCND2-related brain overgrowth). [73][74][75][76] Specifically, mutations of the AKT3 gene have been associated with most severe MEG, and further shown to have very strong associations with increased intracranial volume (ICV) in a large meta-analysis of reactome gene sets in relationship to brain size, along with other MTOR pathway genes. 41,69 Recently, mutations of a new family of genesthe PP2A phosphatase family including specifically PPP2R5D-have been identified in children with congenital onset MEG, autism, and hypotonia. This class of phosphatases is believed to have a negative regulatory effect on the PI3K-AKT-MTOR pathway. Therefore, PI3K-AKT-MTOR dysregulation is believed to underlie the brain overgrowth of PPP2R5D-related disorders as well. [77][78][79] Finally, abnormalities of the evolutionarilyconserved partitioning defective protein complex, including PARD3, PARD6, and atypical protein kinase C (aPKC), that regulate asymmetric cell division of Radial Glial Progenitors (RGPs) have been proposed as a mechanism underlying MEG and heterotopia in humans. 80,81 However, no mutations of these genes have been identified in human MEG, to date. A comprehensive review of additional genes associated with human MEG are further provided in Table I.

Proposed diagnostic workflow for microcephaly to megalencephaly
Given the causal heterogeneity of MIC and MEG, and based on our broad review of the literature, we propose the following clinical diagnostic workflow for pediatriconset MIC and MEG. For any individual presenting with an abnormally small or large brain size, a careful assessment of the individual's growth (including stature and weight) are crucial as this will help delineate whether brain growth abnormalities are isolated or due to more generalized growth disorders (eg, MOPD disorders with MIC, somatic overgrowth disorders with MEG). Further, assessment of the brain magnetic resonance imaging is extremely valuable as many MIC-MEG syndromes are associated with other developmental brain disorders that can be clinically delineated by good quality imaging, such as mutations of the tubulin genes (TUBA1A, TUBB2B, TUBG1, among many others, for example).

Microcephaly
Among the most clinically useful distinguishing features of MIC is its' age of onset (ie, congenital vs postnatal). Congenital MIC, if isolated (ie, not associated with any other major structural anomalies) is typically autosomal recessive in nature (also known as Primary MIC or MCPH) caused by mutations in cell cycle genes such as ASPM most notably, among others. Congenital MIC in association with other structural defects is most often syndromic and likely extremely genetically heterogeneous. Therefore, etiologies falling under this category include microdeletion or microduplication syndromes that can be identified by chromosomal microarrays, or a growing number of single gene disorders, many of which can be delineated based on their associated key clinical features. If clinical delineation is not possible, then consideration for wide-scale genomic testing (eg, exome sequencing) is recommended. It is important to remember the non-genetic causes of congenital MIC including congenital viral infections, vascular insults or injuries and environmental exposures (eg, fetal alcohol syndrome). Postnatal MIC, on the other hand, is extremely genetically heterogeneous, as MIC occurs as a secondary features in numerous neurodevelopmental syndromes characterized by epilepsy, ID and ASD; many of which are caused by de novo mutations. Therefore, clinical delineation of the specific syndrome is recommended. If a specific syndrome is not identified based on the history and physical examination, then consideration of wide scale genomic testing (eg, exome sequencing) is similarly recommended. Detailed recommendations for clinical evaluations of children with MIC have been previously published. 19 Megalencephaly Similar to MIC, careful review of overall body growth measurements, in conjunction with a detailed neurological examination and/or brain imaging, are very useful in evaluating a child with MEG. Importantly, when a child presents with a large head size, it is imperative to rule out other important causes of macrocephaly such as hydrocephalus or progressive ventriculomegaly. True and isolated brain overgrowth -MEG -is seen most commonly with single gene disorders, most notably PI3K-AKT-MTOR pathway related disorders. 59,72 Given the likelihood of low-frequency postzygotic (mosaic) mutations in MEG disorders, careful selection of molecular diagnostic approaches needs to be made using a method that generates good quality, high depth data (eg, ultra deep targeted capture). Syndromic forms of MEG require a consideration of microdeletion-microduplication syndromes (using chromosomal arrays), followed by careful and thorough clinical assessments to delineate specific overgrowth syndromes. In the presence of diffuse MEG with multiple other congenital anomalies, exome sequencing may be utilized to efficiently and rapidly identify the underlying genetic etiology, given the emerging genetic heterogeneity of MEG. 58 In spite of wider integration of high-quality and high-depth NGS methods in clinical practice, the genetic causes of a substantial fraction of MEG in children remain unidentified, suggesting the involvement of other genes/ loci and/or low-level mosaicism challenging detection using standard molecular methods. 69

Summary
A review of the microcephaly and megalencephaly disorders in humans highlights the remarkable genetic heterogeneity of these disorders, mutations of which perturb key cellular processes with disruption of various neurodevelopmental stages. There is a strong need for updated classifications of these disorders based on molecular pathways or underlying mechanisms rather than descrip-tive clinical parameters that may be outdated and in need of refinement, particularly in light of rapidly emerging molecular data. Most MIC-and MEG-associated pathways are critical cell signaling pathways that regulate cellular growth, proliferation, with strong overlap with cancer pathways, the aberrations of which cause complex syndromes where neurodevelopmental features and cancer phenotypes overlap (eg, DDR-associated disorders with MIC, and PI3K-AKT-MTOR related disorders with MEG). With the ever-increasing use of NGS methods in clinical molecular practice, the genetic heterogeneity of these disorders is only expected to increase, with the very strong likelihood of uncovering low frequency mosaic mutations in MEG and related disorders including focal malformations of cortical development. These genetic insights will likely shed light on more fundamental mechanisms underlying MIC and MEG that may require validation ideally using high throughput in in vivo and in vitro systems. Ultimately, MIC-MEG disorders are collectively not that rare and have substantially informed biological mechanisms underlying normal brain growth and development in humans. o


extfieldsofstudy: Medicine Chemistry

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Role of Ezrin Phosphorylation in HIV-1 Replication

Host-cell expression of the ezrin protein is required for CXCR4 (X4)-tropic HIV-1 infection. Ezrin function is regulated by phosphorylation at threonine-567. This study investigates the role of ezrin phosphorylation in HIV-1 infection and virion release. We analyzed the effects of ezrin mutations involving substitution of threonine-567 by alanine (EZ-TA), a constitutively inactive mutant, or by aspartic acid (EZ-TD), which mimics phosphorylated threonine. We also investigated the effects of ezrin silencing on HIV-1 virion release using a specific siRNA. We observed that X4-tropic HIV-1 vector infection was inhibited by expression of the EZ-TA mutant but increased by expression of the EZ-TD mutant, suggesting that ezrin phosphorylation in target cells is required for efficient HIV-1 entry. Expression of a dominant-negative mutant of ezrin (EZ-N) and ezrin silencing in HIV-1 vector-producing cells significantly reduced the infectivity of released virions without affecting virion production. This result indicates that endogenous ezrin expression is required for virion infectivity. The EZ-TD but not the EZ-TA inhibited virion release from HIV-1 vector-producing cells. Taken together, these findings suggest that ezrin phosphorylation in target cells is required for efficient HIV-1 entry but inhibits virion release from HIV-1 vector-producing cells.

INTRODUCTION
Human immunodeficiency virus type 1 (HIV-1) is the etiological agent of AIDS. In addition, the replication-defective HIV-1 vector is frequently used as a gene transfer tool in many biological fields of study. The HIV-1 vector is generally constructed by transfection of 293T or COS7 fibroblast cell lines that express the tumor antigen of simian virus 40 and have high transfection efficiency. Understanding the molecular mechanism of HIV-1 replication in these cell lines would provide novel approaches to obtaining high-efficiency HIV-1 vectors and developing new therapeutic strategies against AIDS.
Ezrin protein function is primarily regulated by phosphorylation of the threonine residue at position 567 (Tsukita and Yonemura, 1997;Matsui et al., 1998). The N-and C-terminal domains of unphosphorylated ezrin are intramolecularly and/or intermolecularly bound to each other. After ezrin phosphorylation, the interaction between these domains is abolished, allowing the binding of the N-and C-terminal termini to their membrane protein targets and the actin cytoskeleton, respectively. Because an N-terminal domain peptide of ezrin (EZ-N) binds to the membrane proteins but does not interact with the actin cytoskeleton, it acts as a dominant negative mutant of phosphorylated ezrin. Although ezrin is involved in HIV-1 entry and virion production, role of the ezrin phosphorylation in HIV-1 replication is unknown.
This study investigates the impact of ezrin phosphorylation in X4-tropic HIV-1 infection and virion release using ezrin mutants. Mutants containing amino acid substitutions of the threonine-567 residue for alanine (EZ-TA) and aspartic acid (EZ-TD) were constructed. EZ-TA functions as a constitutively inactive mutant, because it cannot be phosphorylated. EZ-TD functions as a constitutively active mutant, because the aspartic acid residue mimics phosphorylated threonine. We investigated the effect of these mutants on HIV-1 virion production.

Cells
COS7, HeLa, and 293T cells were cultured with Dulbecco's modified Eagle's medium (D-MEM) (Wako) supplemented with 8% fetal bovine serum at 37 • C in 5% CO 2 . CD4-expressing HeLa cells (HeLa/CD4) were constructed as follows. COS7 cells were transfected with the R8.91 (Naldini et al., 1996), VSV-G , and CD4-encoding lentiviral vector expression plasmids. Culture supernatants of the transfected cells were inoculated into HeLa cells. Because the lentiviral vector encodes the blastidine resistance gene, the inoculated cells were selected with blastidine (Invitrogen). The blastidine-resistant cell pool was used in this study. HeLa/CD4 cells were further inoculated with a MLV vector (Kubo et al., 2003) encoding EZ-Wt, -N, -TA, or -TD. Because the MLV vector additionally encodes the puromycin resistance gene, the inoculated cells were selected with puromycin; puromycin-resistant cell pools were used in this study.

HIV-1 Vector
COS7 cells were transfected with the R8.91 (Naldini et al., 1996), lacZ-encoding HIV-1 vector genome , and HXB2 Env expression (Yokomaku et al., 2004) plasmids together with one of the ezrin expression plasmids using the Fugene HD transfection reagent (Promega). The transfected cells were washed with fresh medium to remove the transfection complex 24 h after transfection and cultured for additional 24 h. Culture supernatants of the transfected cells were inoculated onto target cells. The cells were stained with 5-bromo-4-chloro-3-indolyl-b-D-galactopyranoside (X-Gal) (Wako) 2 days after inoculation. Blue cells were counted in 8 randomly selected microscopic fields per a 3-cm culture dish. Total of the blue cell numbers were calculated as transduction titers. Total blue cell numbers in control cells were always set to 1. Relative values to the blue cell numbers in control cells were calculated. The experiment was repeated three times. Usually 100∼300 blue cells were detected in control cells (Kamiyama et al., 2009;Yoshii et al., 2011).

Western Immunoblotting
Culture supernatants of the vector-producing cells were filtered through a 0.45-µm membrane (Millipore), and centrifuged at 16,114 × g through 20% sucrose for 5 h to collect virion pellets. Cell lysates and virion pellets were subjected to SDS polyacrylamide gel electrophoresis with or without Phos-tag reagent (Kinoshita et al., 2006), and proteins were transferred onto a PVDF membrane. Membranes treated with rabbit anti-HIV-1 p24 (BioAcademia or ZeptoMetrix), sheep anti-HIV-1 gp120 (provided by Dr. T. Murakami), or rabbit anti-ezrin antibody (Santa Cruz Biotechnology) then were treated with HRP-conjugated protein G (BioRad) to detect the proteins. Membranes treated with mouse anti-VSV-G epitope (Sigma-Aldrich) and mouse anti-actin antibodies (Santa Cruz Biotechnology) were treated with HRP-conjugated anti-mouse IgG (BioRad) as the secondary antibody. Antigen proteins were visualized using the Clarity Western ECL substrate (BioRad).

Site-Directed Mutagenesis
Site-directed mutagenesis was performed using the standard PCR-mediated protocol (TaKaRa). The primers were synthesized by Fasmac Co., The nucleotide sequences of the resulting plasmids were confirmed (Applied Biosystems).

Virus-Cell Membrane Fusion Activity
Virus-cell membrane fusion activity was measured as previously reported (Cavrois et al., 2002). COS7 cells were transfected with the HIV-1 vector construction plasmids and a plasmid encoding the BlaM-Vpr fusion protein together with pcDNA3.1, EZ-Wt, EZ-N, or siEZ. HeLa/CD4 cells were inoculated with culture supernatants from the transfected cells and stained with CCF2 (Invitrogen). Intact CCF2 releases fluorescence at 450 nm. When CCF2 is cleaved by BlaM-Vpr, the product releases fluorescence at 405 nm. Fluorescence intensities at 450 and 405 nm of the cells were measured using a microplate fluorometer (Perkin Elmer), and ratios of fluorescence intensities at 405 nm to those at 450 nm were calculated. When HIV-1 vector particles containing BlaM-Vpr enter into target cells, the fluorescence ratios are increased.

Cellular Localization of HIV-1 Gag and Ezrin Proteins
Transfected cells were permeated by methanol and stained with rabbit anti-HIV-1 p24 and mouse anti-VSV-G epitope antibodies. The cells then were treated with FITC-conjugated anti-rabbit IgG and Cy3-conjugated anti-mouse IgG antibodies. The cells were observed under a confocal fluorescent microscopy (Zeiss).

HIV-1 Replication
293T cells were transfected with the infectious molecular clone of HIV-1 NL4-3. Target cells were inoculated with culture supernatants (10 µl) of the transfected cells. Inoculated cells were changed to fresh medium 1 day after inoculation. Culture supernatant concentrations of HIV-1 Gag p24 were measured by ELISA (ZeptoMetrix) 3 days after the inoculation.

Statistical Analysis
Differences between two groups of data were determined using Student's t-test. Statistical significance was set at p < 0.05 for all tests.

Ezrin Phosphorylation in Target Cells Is Required for Efficient HIV-1 Infection
To assess whether ezrin phosphorylation in target cells is required for HIV-1 infection, murine leukemia virus (MLV) vector encoding C-terminally VSV-G epitope-tagged ezrin wild type (EZ-Wt) (Algrain et al., 1993), EZ-TA, and EZ-TD were constructed. The number of puromycin-resistant cell colonies was lower in those inoculated with the EZ-TD-expressing MLV vector than with the EZ-Wt-or EZ-TA-encoding vector. Western blot analysis revealed that the amount of EZ-TD protein was less than that of EZ-Wt or EZ-TA ( Figure 1A), suggesting that EZ-TD might inhibit cell proliferation or have cytopathic activity in HeLa cells.
HIV-1 vectors containing X4-tropic HXB2 Env or VSV-G protein were inoculated onto these puromycin-resistant cell pools. The transduction titers of the X4-tropic Env-containing HIV-1 vector in EZ-TA-expressing cells were moderately lower than those in empty vector-or EZ-Wt-expressing cells ( Figure 1B). In contrast, the transduction titers of the X4-tropic Env-containing vector in EZ-TD-expressing cells were higher than those of control cells. The transduction titers of VSV-G-pseudotyped HIV-1 vector were comparable in all of these cell pools. These results suggest that ezrin phosphorylation in target cells is required for the efficient X4-tropic Env-mediated infection.

Ezrin Dominant Negative Mutant Incorporated Into HIV-1 Virions Inhibits Infection
It has been reported that ezrin protein is incorporated into HIV-1 virion (Ott et al., 1996). To analyze roles of ezrin in the HIV-1 virion production and infectivity of released particles, COS7 cells were transfected by the X4-tropic HIV-1 vector construction plasmids together with the plasmid encoding the EZ-Wt, N-terminal region (EZ-N), or C-terminal region (EZ-C). Western blot analysis of cells transfected with X4-tropic HIV-1 vector together with EZ-Wt, EZ-N, or EZ-C revealed that the amount of HIV-1 Gag protein is similar for all transfected constructs (Figure 2A). This result indicates that EZ-Wt, -N, and -C expression do not affect HIV-1 virion release.
Western blot analysis of virion pellets using anti-VSV-G epitope antibody revealed the presence of EZ-Wt and EZ-N but not EZ-C protein (Figure 2A, right panel), suggesting that the N-terminus is responsible for ezrin incorporation into viral particles.
While the transduction titers of culture supernatants from EZ-N-transfected cells were significantly lower than those of pcDNA3.1-transfected cells (Figure 2B), the levels of HIV-1 p24 and gp120 in virion pellets did not differ (Figure 2A). The transduction titers of culture supernatants from EZ-Wttransfected cells were slightly lower than those of control cells. EZ-C was not incorporated into virions, and its expression did not change the transduction titers. These results indicate that incorporation of the dominant negative EZ-N protein into virions decreases the infectivity of released HIV-1 particles.
The effect of EZ-N expression on the incorporation of wildtype ezrin protein into HIV-1 vector was examined. Cells transfected with HIV-1 vector together with both EZ-Wt and EZ-N incorporated the same amount of EZ-Wt protein in virion Frontiers in Microbiology | www.frontiersin.org pellets as those transfected with EZ-Wt alone (Figure 2C), indicating that EZ-N has no effect on EZ-Wt incorporation into HIV-1 particles.

Ezrin Silencing Decreases the Infectivity of Released HIV-1 Particles
To assess whether endogenous ezrin in HIV-1 vector-producing cells is required for HIV-1 virion production and/or infectivity of released HIV-1 virions, 293T cells were transfected with X4tropic HIV-1 vector together with an siRNA against GFP (siGFP) or ezrin (siEZ). The transduction titers of culture supernatants from siEZ-transfected cells were significantly lower than those from siGFP-transfected cells (Figure 3A), consistent with a previous report (Roy et al., 2014). The amount of HIV-1 Gag protein in cell lysates and virion pellets was not altered by siEZ ( Figure 3B). The amount of HIV-1 gp120 in virion pellets was not significantly changed. The ezrin knockdown by the siEZ was confirmed by RT-PCR but not western blotting, because anti-ezrin antibodies generally detect radixin, another member of ERM family as well as ezrin and their molecular sizes are same (Algrain et al., 1993;Kubo et al., 2008). siEZ transfection decreased the amount of ezrin mRNA ( Figure 3C). These results show that ezrin is dispensable for HIV-1 virion production but required for the infectivity of released HIV-1 virions.
To assess the effect of EZ-N and ezrin silencing on X4-tropic Env-mediated entry, we investigated the fusion of the virus-cell membranes. EZ-N and siEZ but not EZ-Wt attenuated virus-cell fusion (Figure 3D), indicating that the decreased infectivity of HIV-1 particles from EZ-N-and siEZ-expressing cells is related to the suppression of virus-cell membrane fusion.

Phosphorylated Ezrin Suppresses HIV-1 Virion Release
To analyze the effect of ezrin phosphorylation on virion release, COS7 cells were transfected with X4-tropic HIV-1 vector together with pcDNA3.1, EZ-Wt, EZ-TA, or EZ-TD. HIV-1 vector infectivity was not affected by EZ-TA expression and only slightly decreased by EZ-Wt expression ( Figure 4A). In contrast, EZ-TD expression dramatically decreased transduction titers. Although the amount of HIV-1 Gag protein expressed in the transfected cells was not affected by EZ-Wt, EZ-TA, or EZ-TD expression, no p24 protein was observed in supernatants of EZ-TD-expressing cells ( Figure 4B, right panel). The observed suppression of virion release by EZ-TD suggests that phosphorylated ezrin inhibits such release.
The phosphorylation status of endogenous ezrin was investigated by western blot analysis. Phosphorylated ezrin was detected in Jurkat T cells, but not in 293T, HeLa, or COS7 cells (Figure 4C), as already reported (Parameswaran and Gupta, 2013). Phosphorylated ezrin protein was not detected in virion pellets from the EZ-Wt-transfected cells.  When protein samples are separated in Phos-Tag reagentcontaining gel, migration speeds of phosphorylated proteins are moderately reduced than expected (Kinoshita et al., 2006). When cell lysate prepared from Jurkat cells transfected by the EZ-Wt expression plasmid was applied to Phos-Tag reagent-containing gel, a protein with higher molecular size than expected was indeed detected ( Figure 4D). However, molecular weight of the EZ-Wt protein was similar to that of the EZ-TA protein, with no higher molecular-weight proteins detected in EZ-Wt-expressing cells (Figure 4B, right panel). These results indicated that ezrin protein is not phosphorylated in 293T, HeLa, and COS7 cells, and unphosphorylated ezrin is incorporated into HIV-1 virions.

Phosphorylated Ezrin Inhibits Virion Budding but Not Gag Localization
The cell-surface expression of Gag was investigated to determine whether expression of the EZ-TD mutant affects Gag localization. Fluorescence microscopy revealed that EZ-Wt and EZ-TD proteins were concentrated at the aggregated sites of HIV-1 Gag protein (Figure 5, arrows) and that the cellular localization of the HIV-1 Gag protein in EZ-TD cells was similar to that of EZ-WT cells (Supplementary Figure 1). These results suggest that expression of the EZ-TD mutant did not alter aggregation of the HIV-1 Gag protein.  HeLa/CD4 cells were transfected with siGFP or siEZ and then inoculated with HIV-1 NL4-3. Gag p24 concentrations in culture supernatants were measured. p24 levels from the empty vector-transduced cells were always set to 1, and relative values of p24 levels are indicated. Error bars show standard deviations, and asterisks indicate statistically significant differences compared to the values of the empty vector-transduced cells. (C) HeLa/CD4 cells were transfected by EZ-Wt or EZ-TD expression plasmid, and were inoculated with replication-competent HIV-1 24 h after the transfection. The p24 levels in culture supernatants were analyzed 3 days after the inoculation.

EZ-N and siEZ Inhibit HIV-1 Replication
In the above experiments, replication-defective HIV-1 vector was used. Next, we analyzed the role of ezrin in HIV-1 replication. The level of p24 protein was determined in HeLa/CD4 cells stably expressing EZ-Wt, -N, -TA, or -TD after inoculation with replication-competent HIV-1 NL4-3 (Nomaguchi et al., 2014). The level of p24 protein was significantly lower in EZ-N-expressing cells but unchanged in EZ-Wt, -TA, and -TD-expressing cells (Figure 6A), indicating that the EZ-N mutant inhibits HIV-1 replication. Under replication-competent conditions, p24 amount was significantly lower in siEZtransfected cells (Figure 6B), suggesting that endogenous ezrin is required for the HIV-1 replication.
Although the above experiment indicates that the EZ-TD significantly inhibited HIV-1 virion production (Figure 4), EZ-TD did not affect HIV-1 replication. To understand the discrepancy, the EZ-TD protein level was again measured by western blotting. The EZ-TD level was reduced during the maintenance of EZ-TD-expressing cells (Figure 7A). This result supports the conclusion that EZ-TD inhibits cell growth and/or is cytotoxic. Transduction titers of HIV-1 vector in the EZ-TD-expressing cells became similar to those in the EZ-Wt-expressing cells (Figure 7B). When the EZ-Wtand EZ-TD-expressing HeLa cells were transfected by HIV-1 vector construction plasmids, transduction titers of culture supernatants from the EZ-TD-expressing cells were moderately lower than those from the EZ-Wt-expressing cells ( Figure 7C). Consistently, p24 amounts in culture supernatants from the EZ-TD-expressing cells were moderately decreased (Figure 7D), although p24 levels in cell lysates were similar. Because EZ-TD protein level was decreased during the culture of EZ-TD-expressing cells, HIV-1 replication was not affected in the cells.
To examine whether EZ-TD protein is incorporated into HIV-1 particles, the HeLa/CD4 cells expressing EZ-TD at a lower level were transfected by the HIV-1 vector construction plasmids, and virion pellets were prepared from the transfected cells. EZ-TD protein was not detected in virion fractions ( Figure 7E). This result supports the conclusion that EZ-TD inhibits HIV-1 virion production.
To assess the impact of EZ-TD on HIV-1 replication, HeLa/CD4 cells were transfected by the EZ-Wt or EZ-TD expression plasmid, and were inoculated with replicationcompetent HIV-1 24 h after the transfection. The levels of p24 protein in culture supernatants from the EZ-TD-transfected cells were slightly lower than those from the EZ-Wt-transfected cells ( Figure 6C). This result shows that EZ-TD has negative effect on HIV-1 replication.

DISCUSSION
We observed that X4-tropic HIV-1 vector infection was inhibited by expression of the EZ-TA mutant but increased by expression of the EZ-TD mutant, suggesting that ezrin phosphorylation in target cells is required for efficient HIV-1 entry. Expression of a dominant-negative mutant of ezrin (EZ-N) and ezrin silencing in HIV-1 vector-producing cells significantly reduced the infectivity of released virions without affecting virion production. This result indicates that endogenous ezrin expression is required for virion infectivity.
Previous reports have established that phosphorylation of moesin, another member of the ERM family, is important for HIV-1 infection (Barrero-Villar et al., 2009). Binding of the HIV-1 Env protein to target cells triggers clustering of CD4 and co-receptor molecules at the virion binding site on the actin cytoskeleton (Jolly et al., 2004(Jolly et al., , 2007. Accordingly, ezrin phosphorylation is thought to control the clustering of HIV-1 receptor proteins by linking the actin cytoskeleton to the receptors. However, we detected no phosphorylated ezrin in HeLa/CD4 cells inoculated with the X4-tropic HIV-1 vector. Thus, ezrin phosphorylation may occur locally and transiently after interaction between the Env and receptor proteins. Ezrin phosphorylation is cell-line dependent. Constitutive phosphorylation of threonine 567 has been observed in Jurkat T cells, as reported (Parameswaran and Gupta, 2013). We attempted constructing Jurkat T cells stably expressing EZ-Wt, EZ-N, EZ-TA, and EZ-TD using the MLV vector, but EZ-Nand EZ-TA-expressing Jurkat cells were not obtained. This result suggests that ezrin phosphorylation is required for Jurkat cell viability. In contrast, our results indicate that ezrin is not phosphorylated in 293T, COS7, and HeLa cells, suggesting that phosphorylated ezrin may have a negative effect on these cells. Indeed, the expression level of the EZ-TD protein was lower than that of the EZ-Wt and EZ-TA proteins in HeLa cells. Although we have reported that target cell expression of ezrin is required for efficient HIV-1 infection (Kubo et al., 2008), contradictory reports show that other members of the ERM family restrict retrovirus infection (Naghavi et al., 2007;Haedicke et al., 2008;Capalbo et al., 2011;Brégnard et al., 2013;Li et al., 2016). The The incorporation of unphosphorylated ezrin into HIV-1 particles is necessary for the infectivity of the released virions. As one of the reasons, unphosphorylated ezrin may bind to a cellular factor that is required for infection by released viral particles ( Figure 8A). We observed that HIV-1 vector particles released from ezrin-silenced cells had lower transduction titers than did those from siGFP-transfected cells, as previously reported (Roy et al., 2014). EZ-N, which functions as a dominant negative mutant of phosphorylated ezrin, was incorporated into HIV-1 particles and decreased the infectivity of the released virions. Ezrin silencing and EZ-N may inhibit incorporation of the cellular factor into virions (Figures 8B,C).
Phosphorylated ezrin inhibits HIV-1 virion release. EZ-TD constitutively serves as a linker between membrane proteins and the actin cytoskeleton. Thus, EZ-TD may inhibit HIV-1 virion release by tethering HIV-1 particles to the cell surface ( Figure 8D). For example, ICAM-1 interacts with ezrin (Barreiro et al., 2002) and is incorporated into HIV-1 particles (Tardif and Tremblay, 2003). The complex consisting of ICAM-1, phosphorylated ezrin, and the actin cytoskeleton may inhibit the release of HIV-1 particles into culture supernatants. This result is consistent with our observation that phosphorylated ezrin was not detected in HIV-1 particles. If so, HIV-1 Gag protein amount would increase in the EZ-TD-expressing cells. However, the viral protein levels were not altered by EZ-TD. Tetherin also inhibits HIV-1 particle production, but Gag protein levels are similar in the presence and absence of tetherin (Neil et al., 2008). The Gag protein may be degraded in lysosome, as already reported (Miyakawa et al., 2009).
We observed here that EZ-N expression and ezrin silencing significantly inhibit HIV-1 replication and, as we reported previously, attenuate HIV-1 entry. In addition, EZ-N expression and ezrin silencing in HIV-1-producing cells decrease the infectivity of released HIV-1 particles. Thus, EZ-N expression and ezrin silencing significantly inhibit HIV-1 replication. Expression of the EZ-TA mutant in target cells moderately inhibited X4tropic HIV-1 Env-mediated infection but not HIV-1 replication. The negative effect of EZ-TA on HIV-1 infection is not enough to inhibit HIV-1 replication. The expression of EZ-TD in target cells increased HIV-1 infection but inhibited HIV-1 virion production. EZ-TD expression moderately inhibited HIV-1 replication. The negative effect of EZ-TD on HIV-1 virion production is predominant to the positive effect on HIV-1 entry.
Taken together, our results indicate that ezrin is involved in many steps of the HIV-1 life cycle, including entry, virion production, and infectivity of the released particles. Further study is needed to determine the molecular mechanisms underlying these observations.

AUTHOR CONTRIBUTIONS
HK, MI, YU, and YK performed the experiments in this study. HK, HH, TM, and YK analyzed the data. YK wrote the manuscript.

FUNDING
This study was supported by a grant-in-aid from the Japan Society for the Promotion of Science (15K08499), the Research Program on HIV/AIDS from the Japan Agency for Medical Research and Development (AMED) (JP18fk0410004), and the Asahi Kasei Medical Co., LTD.