extfieldsofstudy: Psychology Medicine

s2fieldsofstudy: Biology Psychology

text:
Structural hippocampal network alterations during healthy aging: a multi-modal MRI study

While hippocampal atrophy has been described during healthy aging, few studies have examined its relationship with the integrity of White Matter (WM) connecting tracts of the limbic system. This investigation examined WM structural damage specifically related to hippocampal atrophy in healthy aging subjects (n = 129), using morphological MRI to assess hippocampal volume and Diffusion Tensor Imaging (DTI) to assess WM integrity. Subjects with Mild Cognitive Impairment (MCI) or dementia were excluded from the analysis. In our sample, increasing age was significantly associated with reduced hippocampal volume and reduced Fractional Anisotropy (FA) at the level of the fornix and the cingulum bundle. The findings also demonstrate that hippocampal atrophy was specifically associated with reduced FA of the fornix bundle, but it was not related to alteration of the cingulum bundle. Our results indicate that the relationship between hippocampal atrophy and fornix FA values is not due to an independent effect of age on both structures. A recursive regression procedure was applied to evaluate sequential relationships between the alterations of these two brain structures. When both hippocampal atrophy and fornix FA values were included in the same model to predict age, fornix FA values remained significant whereas hippocampal atrophy was no longer significantly associated with age. According to this latter finding, hippocampal atrophy in healthy aging could be mediated by a loss of fornix connections. Structural alterations of this part of the limbic system, which have been associated with neurodegeneration in Alzheimer's disease, result at least in part from the aging process.

INTRODUCTION
The limbic system is considered as the cerebral network devoted to memory function and it has been extensively studied in various neurological diseases, and particularly in age-related dementia. Assuming that the hippocampus is the key component of the limbic system, it can be hypothesized that a direct link exists between hippocampal neural injury and damage to White Matter (WM) bundles of this system. Two main connecting tracts in the limbic system are the cingulum bundle which constitutes the principal afferent pathway of the hippocampus, and the fornix which constitutes the principal efferent pathway of the hippocampus. The direct relationship between hippocampal injury and WM damage in these two bundles has been previously reported in Alzheimer's disease (AD) but the results of these investigations are somewhat inconsistent. Some studies have shown no evidence for a relationship between hippocampal atrophy and disruption of the cingulum bundle (Firbank et al., 2007;Nakata et al., 2009), whereas others have highlighted an association between atrophy of the hippocampus and integrity of the cingulum bundle (Xie et al., 2005;Villain et al., 2008;Choo et al., 2010;Villain et al., 2010;Agosta et al., 2011). A recent investigation demonstrated that a part of structural changes observed in the parahippocampal cingulum were independent of hippocampal atrophy (Salat et al., 2010). Studies examining the relationship between hippocampal atrophy and disruption of its efferent pathway (i.e., the fornix bundle) in both Mild Cognitive Impaired (MCI) and AD subjects have been more consistent (Pievani et al., 2010;Firbank et al., 2011;Lee et al., 2012;Mielke et al., 2012;Zhuang et al., 2012). In these studies, fornix microstructural alteration was significantly associated with reduced hippocampal volume in both MCI and AD subjects, leading the authors to hypothesize that concomitant alterations of these structures may reflect neurodegenerative processes occurring during AD as well as constituting a specific hallmark of the disease.
Morphological changes of the brain also occur during healthy aging and age-related changes of the Gray Matter (GM), including hippocampal atrophy (Scahill et al., 2003;Raz et al., 2004;Du et al., 2006) and WM changes (Salat et al., 2005a,b;Lebel et al., 2008;Pagani et al., 2008;Lee et al., 2009;Jang et al., 2011;Lebel et al., 2012;Sala et al., 2012). However, at the cellular level, hippocampal atrophy described in elderly subjects was not related to neuronal death as it was in AD, but rather with a loss of dendritic architecture (West et al., 1994;Hof and Morrison, 2004). For this reason, it is less certain that hippocampal atrophy would have an impact on its efferent and afferent fibers in the context of aging than in neurodegenerative diseases such as AD. Moreover, a major focus of neuroclinical research concerns the discrimination of healthy aging from pathological changes that occur during the early stage of the neurodegenerative disease. Alterations of the limbic system during healthy aging have been examined by few investigations to date, and their findings have been based on relatively small samples and without consideration of GM (Yassa et al., 2010;Rogalski et al., 2012).
In the present study, we hypothesize that the limbic system presents combined gray and white matter structural alterations during healthy aging. We used structural MRI covariance analysis for the description of concomitant hippocampus and WM alterations for determining limbic system damage in healthy aging. Participants were drawn from a large community-dwelling population of older individuals without dementia or MCI. To exclude MCI subjects, we used verbal episodic memory cut-offs previously established for their predictive values of dementia (Sarazin et al., 2007). Whereas volumetric GM assessment was performed on conventional T1 scans, the assessment of WM integrity was performed through exploration of FA parameter computed from DTI images. In a first analysis, age-related effects on hippocampal fractions (corresponding to the ratio between hippocampal volumes and total intracranial volumes) and on FA parameters were described for our sample of older subjects. Statistical analyses of FA parameters were performed in two ways: using a voxelbased analysis (Tract Based Spatial Statistical, TBSS) and region of interest (ROI) analyses based on cingulum and fornix bundles, major afferent and efferent pathways of the hippocampus. The TBSS analysis allowing exploration of whole WM was chosen since the limbic system is an extended network. In a second analysis, the direct relationship between hippocampal fractions and WM integrity were assessed by partialling out the effects of age (to take into account the shared variance due to age on both parameters). We hypothesize that subjects having the same age but presenting the lowest hippocampal volumes should also present the lowest FA values specifically on the connecting tracts of the hippocampus, and independently of the global effects of age on gray and white matter. Finally, to provide information on the sequential relationship between the alterations of these brain structural parameters, a recursive regression procedure was performed.

SUBJECTS
In this study, the participants were a subset of the AMI (Agrica-MSA-IFR de Santé Publique, Aging Multidisciplinary Investigations) cohort, an epidemiological study conducted in residents of agricultural communities (Peres et al., 2012). The AMI study started in 2007 and included 1002 older individuals who were at least 65 years old at baseline, and living in rural areas. These individuals were randomly recruited from the databases of the Farmer Health Insurance System (MSA, Mutualité Sociale Agricole). A complete battery of neuropsychological tests was administrated by a neuropsychologist at baseline and at follow ups every two years. Between March 2009 and March 2011, an MRI examination was proposed to a subsample of participants, acquiring 316 MRI exams in right-handed subjects. The study was approved by the institutional human ethics review board and all individuals in the sample provided written informed consent to participate.
Before data processing, MRI data was checked in order to discard major acquisition artifacts (n = 58) and major cerebral pathologies (tumor, stroke, severe WM pathologies; n = 55). Cerebral pathologies were detected by an experienced neuroradiologist and severity of leucoaeriosis was evaluated by two trained operators on FLAIR scans according to the Fazekas rating scale (Fazekas et al., 1987). Thirty-four subjects presenting severe leucoaeriosis (rank of 3 on the Fazekas scale) were excluded from the analyses. Since we were interested in structural changes occurring in the limbic system during healthy aging, subjects with diagnoses of dementia (according to the DSM-IV criteria; n = 3), global cognitive deficits measured by the Mini Mental State Examination (MMSE < 25, n = 17), and low performances at the Free and Cued Selective Reminding Test (FCSRT, n = 29) (Grober et al., 1988) were excluded. According to a previous study (Sarazin et al., 2007), verbal episodic memory is able to discriminate patients in the prodromal AD phase from those with MCI with good specificity and sensitivity. The cut-off performances applied were 17 for free recall and 40 for total recall. Subjects presenting missing MMSE or FCSRT data were also excluded from the analysis (n = 25). A total of 129 healthy aging subjects were included in the final sample. The second neuropsychological follow-up indicates that our sample does not include incidents cases of AD, suggesting that our MRI analysis was not performed on MCI fast converter subjects.

MRI ACQUISITION
MRI scans were obtained using an ACHIEVA 3T scanner (Philips Medical System, Netherlands) with a SENSE 8-channel head coil. Anatomical high resolution MRI volumes were acquired in transverse plan for each subject using a 3D MPRAGE weighted-T1 sequence with the following parameters: TR = 8.2 ms, TE = 3.5 ms, 7-degree flip angle, FOV 256 × 256 mm 2 to cover the whole brain, yielding 180 slices, no gap, voxel size 1 × 1 × 1 mm 3 . Two diffusion-weighted images with opposite polarity, allowing elimination of diffusion imaging gradient cross-terms, were performed using a spin echo single shot EPI sequence with the following parameters: TR = 7646 ms, TE = 60 ms, 90-degree flip angle, FOV 224 × 224 mm 2 , yielding 60 slices, no gap, voxel size 2 × 2× 2 mm 3 . One b0 image was acquired and diffusion gradients were applied in 21 non-collinear directions (b-value = 1000 s/mm 2 ). To increase signal-to-noise ratio, the sequence was repeated in two successive runs for each polarity. All acquisitions were aligned on the anterior commissure-posterior commissure plan (AC-PC). For qualitative clinical readings, fluid-attenuated inversion recovery (FLAIR) images were also obtained with the following parameters: TR = 11000 ms, TE = 140 ms, TI = 2800 ms, FOV 230 × 172 mm 2 , yielding 24 slices, gap of 1 mm, voxel size 0.72 × 1.20 × 5 mm 3 . The total scan duration was 38 min.

Cerebral volumes
Cerebral volumetric assessment was performed using Voxel-Based Morphometry method (VBM) (Ashburner and Friston, 2000;Good et al., 2001). Firstly, the MRI images were spatially normalized and then segmented on their intensity distribution and spatial information derived from the ICBM prior probability maps. The unified segmentation model was extended in the VBM5 toolbox (C. Gaser; http://dbm.neuro.uni-jena.de/vbm) by applying a Hidden Markov Random Field model (Ashburner and Friston, 2005). Secondly, we applied a so-called "modulation" to each cerebral partition image. During this step, the voxel intensity of the segmented images was adjusted for the strength of deformation derived from the nonlinear spatial normalization process (Jacobian determinants). For each subject, GM, WM and CSF volumes were computed by multiplying the voxel value by the voxel size of acquisition and summing the results for all of the voxels. Total Intracranial Volume (TIV) was computed as the sum of the GM, WM, and CSF volumes.

Hippocampal volumes
Segmentations of bilateral hippocampi and volume estimations were performed using FIRST (Patenaude et al., 2007(Patenaude et al., , 2011, part of FMRIB's Software Library (FSL) (Oxford Centre for Functional MRI of the Brain). Linear registration was performed in two stages. In the first stage, the 3D MPRAGE weighted-T1 images were registered to the non-linear Montreal Neurological Institute (MNI) 152 standard space using affine transformation with 12 degrees of freedom (DOF). Using a subcortical mask defined in MNI space, the second stage (initialized by the result of the first stage) achieves a more accurate and robust registration (12 DOF) to the MNI152 template. A segmentation based on shape models and voxel intensities was then performed using an MNI subcortical mask of hippocampus. Finally, a boundary correction method was used to determine which boundary voxels belong to the structure. Subsequently, hippocampal volumes were calculated. All images of the segmented hippocampi were visually checked for errors in registration and segmentation stages. The same procedure was applied to extract volumes of caudate nuclei, which were used as a control region. Since preliminary analysis gave similar results considering right and left hippocampal volumes separately, right and left hippocampal volumes were averaged for statistical analyses. Hippocampal fraction (hippocampal volume/TIV) was used here as an index of hippocampal atrophy. In the same manner, volumes of control regions (global GM and caudate nuclei volumes) were normalized using the TIV.

FA maps
DTI images were processed with FMRIB Software Library (FSL 4.1.9, http://www.fmrib.ox.ac.uk/fsl). For each subject, diffusion-weighted images were coregistered to the reference volume b0 with an affine transformation and were corrected for motion and eddy current distortions. Brain Extraction Tool (BET) was applied to eliminate voxels not associated with the brain. DTI-data were then averaged and a FA map was computed by fitting a tensor model to the raw diffusion data.
TBSS pipeline was then used on the FA maps. Nonlinear transformations were applied to register individual FA images on the FMRIB58-FA standard space image. A mean FA was generated using all the registered individual FA maps. The resulting mean FA image was subsequently thinned to create the mean FA skeleton which corresponds to the center of all tracts common to all subjects. A threshold FA value of 0.2 was applied to limit the effects of miswarping across subjects and to reduce inclusion of voxels that are likely to be composed of multiple tissue types. Finally, each subject's FA map was warped to the skeleton by searching for maximum FA values perpendicular to the skeleton.

Fornix and cingulum ROIs
ROIs of fornix and cingulum were created with binary masks based on the JHU ICBM-DTI-81 WM labels atlas (Mori et al., 2008). Intersections between anatomical masks and the skeleton (previously created with TBSS) were used in order to extract mean FA values in these regions. Right and left diffusion values were averaged for statistical analyses.

Age effects
The effects of age on hippocampal fraction were assessed using a linear regression model. Age was added into a model considering hippocampal fraction as the dependent variable and including gender and level of education as covariates. This analysis was performed on SPSS package (18.0.0, SPSS Inc.) and a p-value < 0.05 was considered statistically significant.
The effects of age on WM integrity were assessed in two different analyses. In the whole brain analysis, age was regressed onto FA maps in a model adjusted for gender and level of education. Permutation-based statistics with 5000 permutations and threshold-free cluster enhancement (TFCE) (Smith and Nichols, 2009) were used for statistical inference with a threshold of p < 0.05 corrected for multiple comparisons. In the ROI analysis, age was added into a model considering fornix or cingulum FA values as the dependent variable and included gender and level of education as covariates. This analysis was performed on SPSS package (18.0.0, SPSS Inc.) and a p-value < 0.05 was considered statistically significant.

Relationship between hippocampal volume and WM microstructural integrity
The relationship between hippocampal fraction and WM integrity was first assessed in a whole brain analysis. In the TBSS analysis, hippocampal fractions were regressed onto FA maps in a model adjusted for age, gender and level of education. Permutation-based statistics with 5000 permutations and TFCE with a threshold of p < 0.05 corrected for multiple comparisons were used for statistical inference. Subsequently, ROI analyses were performed using linear regression model on SPSS package. Hippocampal fractions were added into a model considering fornix or cingulum FA values as the dependent variable and including age, gender and level of education as covariates.
In a second step, the relationship between hippocampal fraction and WM microstructural integrity was reassessed by adding WM fractions (WM volume normalized by the TIV) as covariates into the previous model including age, gender and level of education as covariates. A similar analysis was performed for caudate nuclei and global GM fractions used here as control regions and were sequentially substituted in the model to hippocampal fractions. A p-value < 0.05 was considered statistically significant. Finally, to provide evidence for a temporal relationship between hippocampal damage and fornix damage, we performed recursive regression procedure with age as the dependent variable (Mormino et al., 2009). Generally speaking, a variable may be considered as a mediator if it influences the relationship between the independent variable and the dependent variable. As a result, when the mediator and the independent variable were included concomitantly in a regression analysis model, the effect of the independent variable is reduced and the effect of the mediator remains significant. A p-value < 0.05 was considered statistically significant.

RESULTS
The mean age of participants was 73.9 years old (SD = 4.8 years). As demonstrated by Table 1, the sample presented a mean MMSE score of 27.6 (SD = 1.41).

WM integrity
The whole brain TBSS analysis revealed that age was negatively associated to FA values in almost the whole WM skeleton, including fornix and cingulum bundles (p < 0.05, TFCE corrected, adjusted for gender and level of education) (Figure 1). As demonstrated by Table 1, the mean fornix FA was 0.43 (SD = 0.045) and the mean cingulum FA was 0.47 (SD = 0.033). In accordance with whole brain analysis, ROI analysis revealed a negative correlation between age and fornix FA values (R 2 = 0.165, β = −0.341, t = −3.914, p < 0.001, controlled for gender and level of education). A negative correlation was also observed between age and cingulum FA values (R 2 = 0.156, β = −0.308, t = −3.520, p = 0.001, adjusted for gender and level of education).

TBSS analysis
Only FA values in a cluster restricted to the fornix were positively associated to hippocampal fractions (p < 0.05, TFCE corrected, adjusted for age, gender, level of education) (Figure 2A). Surprisingly, the whole-brain analysis revealed that hippocampal fractions were also negatively associated to FA values at the level of cortico-spinal and arcuate fasciculi (p < 0.05, TFCE corrected) ( Figure 2B).

ROI analyses
As with TBSS analysis, a significant positive association was observed between hippocampal fractions and fornix FA values (R 2 = 0.299, β = 0.444, t = 4.876, p < 0.001, adjusted for age, gender and level of education) ( Figure 3A). When global WM fractions were added to the model, the association between hippocampal fractions and fornix FA values remained significant (R 2 = 0.428, β = 0.233, t = 2.536, p = 0.012). No significant relationship between hippocampal fractions and cingulum FA values was observed (R 2 = 0.157, β = 0.024, t = 0.235, p = 0.814) ( Figure 3B). When global GM and caudate fractions were sequentially substituted in the model to hippocampal fractions, no significant association was observed (Figures 3C,D).

DISCUSSION
In this study of a large sample of healthy aging subjects, we observed age-related changes of hippocampal volumes as well as white matter FA values. Secondly, we observed that hippocampal fraction was associated with reduced FA value at the  level of the fornix bundle, in a regression analysis partialling out for the effects of age. This analysis indicates that the relationship observed here between hippocampal volumes and FA fornix values is not only shared variance due to indirect concomitant effect of age on both type of tissue. Reinforcing this assertion, hippocampal volume was not associated with changes at the level of another main connecting tract, the cingulum bundle, which nevertheless presents age-related modifications. The ROI analysis confirmed the specificity of this association between hippocampal volume and fornix microstructure integrity in healthy aging. Moreover, the findings suggest that a part of the effects of age on hippocampal volumes is in fact mediated by fornix integrity, supporting the hypothesis that healthy aging is associated with the structural disorganization in the limbic system spreading from connecting fibers to the hippocampus.

AGE-RELATED DAMAGE
Our sample of older adults presents age-related changes at different levels of the brain. Older subjects present a lower hippocampal fraction, which could reflect an atrophy of this structure, and present a decrease of FA values across the whole WM tracts. These results are in accordance with previous studies in late adulthood. For the hippocampus, the effects related to age observed here could be related to later acceleration of atrophy as described in lifespan studies (Raz et al., 2004;Allen et al., 2005;Jernigan and Gamst, 2005;Fjell et al., 2009). Studies based on DTI clearly demonstrate that brain still matures on its WM part until the age of 40, which clearly enters the range of adulthood. Nonlinear associations between age and DTI parameters across the adult lifespan have been demonstrated depending on the tract considered. However, when healthy older subjects (over 65) are considered, FA decreased consistently with age in all tracts (Head  Pfefferbaum et al., 2005;Salat et al., 2005a,b;Lee et al., 2009;Yassa et al., 2010;Jang et al., 2011;Kantarci et al., 2011;Metzler-Baddeley et al., 2011Rogalski et al., 2012;Sasson et al., 2013) as observed here.

RELATIONSHIP BETWEEN HIPPOCAMPAL ATROPHY AND FORNIX DAMAGE
Aging is associated with brain structural alterations occurring together in both gray and white matter, but their relationship within the neuronal network has not been extensively studied. We observed that hippocampal atrophy is associated with alterations of fornical efferent fibers controlling for the effects of age on both types of tissue. Through a structural covariance study, we demonstrated a direct relationship between two structural alterations occurring during healthy aging at the level of the limbic system. In other words, in subjects of the same age, the one who has the lowest hippocampal fraction will also present lowest FA values at the level of the fornix bundle. The findings suggest that a part of the effects of age on the fornix, previously described in lifespan studies (Salat et al., 2005a,b;Lebel et al., 2008;Pagani et al., 2008;Lee et al., 2009;Jang et al., 2011;Lebel et al., 2012;Sala et al., 2012), is related specifically to hippocampal atrophy and not only to age-related global WM atrophy. Two sources of evidence support the specificity of this observed relationship. First, hippocampal atrophy was related to fornix FA values but not to cingulum FA values, thereby counteracting a global nonspecific effect. Second, when WM atrophy was added as a covariate, the relationship between hippocampal atrophy and fornix FA value remained significant. To date, very few studies have examined limbic network integrity during aging (Lee et al., 2012;Zhuang et al., 2012). Among them, Zhuang et al. (2012) demonstrated a relationship between normalized hippocampal volumes and FA values of the fornix. On the contrary, Lee et al. (2012) failed to demonstrate a correlation between volumes of the hippocampal CA1 and subiculum subfields with fornix FA values in a relatively large sample of older adults (n = 96). This apparent discrepancy could be explained by technical issues in that Lee et al. (2012) used a 6 directional DTI performed on a 1.5T scanner which may have contributed to poor sensitivity, compared to more than 21 directional DTI performed on 3T scanner for the investigation by Zhuang et al. (2012) as well as the current study. The question also persists concerning the cellular mechanism involved in age-related fornix bundle deterioration. The decrease of FA observed could be due simply to a demyelinization process, or to the degeneration of nerve fibers as described recently at the level of the fornix bundle in aging monkeys (Peters et al., 2010). Whereas causality between the alterations of these two parts of the network is demonstrated here, the direction (i.e., fornix fibers degeneration brought about hippocampal atrophy or fornix fibers degeneration induced hippocampal atrophy) could not be assessed robustly in this transversal analysis. However, the recursive regression procedure performed here strongly suggests that hippocampal atrophy in healthy aging could result from a disconnection process. From a functional point of view, several previous studies on humans and monkeys have highlighted the importance of structural preservation of the fornix in episodic memory performances (Gaffan et al., 1991;Gaffan, 1992;Parker and Gaffan, 1997;Aggleton et al., 2000;Tate and Bigler, 2000;Gaffan, 2001;Zahajszky et al., 2001). More recently, researchers have found that greater microstructural integrity of the fornix is related to better recollection performance (Tsivilis et al., 2008;Rudebeck et al., 2009;Metzler-Baddeley et al., 2011;Zhuang et al., 2012), andMetzler-Baddeley et al. (2012) proposed that fornix alteration could underlie, at least in part, the age-related memory decline. In the present study, we did not observe a significant correlation between fornix FA values and verbal episodic memory performance (data not shown). The absence of functional outcomes of axonal pathway damage in the limbic network may be explained by the fact that subjects were selected on the basis of high cognitive performances (particularly for episodic memory) in order to exclude subjects with early pre-symptomatic dementia. In addition, the sample may have been more likely to use compensation strategies leading to the preservation of normal memory performance despite axonal damage. It is possible that this compensatory phenomenon remained efficient when limbic network changes are minor as in our sample of healthy aging subjects, but that saturation of this compensatory process may occur with the progression of age-related network damage or ongoing neurodegeneration in the pre-dementia phase. Another explanation could be that impaired memory performance classically observed in healthy older subjects relies on executive function impairment and consequently on dysfunction of frontal networks rather than on dysfunction of the limbic system (Bernard et al., 2007;McDonough et al., 2013).
No relationship has been shown between hippocampal atrophy and DTI metrics of the cingulum bundle in healthy aging subjects. This lack of association could be explained by the topographical organization of the cingulum bundle which is complex and heterogeneous, rendering measurement difficult. When we considered its two major components separately in a supplementary analysis, we did not observe a relationship between hippocampal atrophy with either the parahippocampal cingulum or medial cingulum (data not shown). Whereas some studies demonstrated a relationship between hippocampal atrophy and the cingulum bundle in neurodegenerative diseases such as AD (Xie et al., 2005;Villain et al., 2008;Choo et al., 2010;Sexton et al., 2010;Villain et al., 2010;Agosta et al., 2011), we did not observed such a relationship in healthy aging subjects suggesting that it was selectively associated with neurodegenerative process.

METHODOLOGICAL CONSIDERATIONS
The cross-sectional design of our study did not allow us to dissociate the underlying mechanisms of weak hippocampal fraction, which may therefore reflect either age-related hippocampal atrophy or pre-existing low hippocampal volume determined early in life. To deal with this problem, 31 scans of subjects in the lowest quartile for hippocampal fraction were visually inspected by 2 raters (AP and GC) to scale hippocampal atrophy while blinded to volumetric assessment. Subjects presenting a low hippocampal fraction were described as presenting hippocampal atrophy by blinded observers (Supplementary Data 1 presents two scans to illustrate low and high hippocampal fractions). Moreover, the significant association between age and hippocampal fractions observed in our analysis supports the atrophy hypothesis rather than an interindividual variability in volume that is determined early in life. Thus, according to these observations, hippocampal fraction is taken as an index of hippocampal neural alteration whether it represents neural loss or neural shrinkage.
It has been shown that age-related GM and WM atrophy may cause partial volume effects from the CSF, particularly in fornix bundle which lies along CSF spaces (Concha et al., 2005;Jones and Cercignani, 2010). Indeed, age-related brain tissue loss can lead to CSF partial volume effects, which may lead in turn to an underestimation of diffusion MRI parameters (Ge et al., 2002). In our sample, the mean FA value of the fornix was 0.43, which is in the range of previously published study (Concha et al., 2005). Moreover, two methodological considerations argue against this potential source of error. First, when WM atrophy was added as a covariate, the relationship between hippocampal atrophy and fornix FA value remained significant. Second, we performed the same analysis using a group specific template (Keihaninejad et al., 2012), and the result of this whole brain analysis is very similar indicating a significant relationship between hippocampal fractions and fornix FA values. More importantly, to evaluate the reliability of our assessment, extracted FA values of the fornix were regressed onto GM volumetric maps. This analysis revealed an association with both the source of the fornix, i.e., the hippocampus and its main projection site, i.e., mammillary bodies (Loftus et al., 2000;Tsivilis et al., 2008), demonstrating reliable assessment of FA (Supplementary Data 2). Finally, recent studies have demonstrated that FA values, in particular the index used in this present study, were less prone to CSF contamination than diffusivity values (axial, radial and mean diffusivities) (Pasternak et al., 2009;Vos et al., 2011). Taken together, these elements argue against the interpretation of our findings are being due to a CSF partial volume effect.
Surprisingly, our voxel-based analysis indicates that hippocampal fraction is related to an increase of FA in cortico-spinal and arcuate fasciculi. Increase of FA in regions including multi fiber population (as it is the case for the above regions) could be due either to an increase of coherence of the main tract or to a decrease of coherence of the minor fibers crossing the main tract. To interpret this increase of FA, we also performed an analysis using the mode of anisotropy (MO) (Supplementary Data 3), an additional diffusion index which partially resolves the problem of crossing fiber regions (Ennis and Kindlmann, 2006). MO specifies the shape of the diffusion tensor from planar to linear. Planar shape reflects diffusion in a region holding two roughly equal fiber populations whereas linear shape reflects diffusion in a region where one fiber population orientation predominates. Regression analysis performed on MO maps indicates that lowest hippocampal fractions were significantly associated with a more linear shape of the diffusion tensor at the level of the corticospinal and of the arcuate fasciculi. The co-localized increase of FA and MO values suggests a global decrease of coherence of fibers crossing the cortico-spinal and the arcuate fasciculi with a preservation of these two main tracts. In the same way, a recent study found that the co-localized increase of FA and MO was explained by a relative preservation of one population compared with others in a region of crossing fibers (Douaud et al., 2011). In addition, ROI analysis indicated that when global WM fractions were added as a covariate, the relationship between hippocampal fractions and FA values in the posterior limb of the internal capsule (a part of the corticospinal tract) lost significance. This latter result suggests that the global degeneration of fibers crossing the cortico-spinal tract and the arcuate fasciculi is related to global WM atrophy rather than to hippocampal atrophy. Hippocampal fractions and FA values of the cortico-spinal and the arcuate fasciculi are together linked to WM fractions; they share variance related to age that drives the observed relationship. As AD has been shown to involve insidious neurodegenerative processes over many years, even the use of a FCSRT cutoff score to identify at-risk AD subjects would not be sufficient to exclude the possibility that subclinical AD pathology might underlie the relationship between hippocampal atrophy and fornix integrity disruption The second neuropsychological follow-up of the study indicates that the sample used in our analysis did not include any incident AD cases. However, consideration of this important issue requires a substantial follow-up period of up to decade that is not yet available on this cohort.

CONCLUSION
The present findings demonstrate that limbic system alterations during healthy aging involve the hippocampus, the fornix bundle, and the cingulum bundle. Moreover, age-related hippocampal atrophy may be directly associated to the loss of microstructural integrity of the fornix bundle but not of the cingulum bundle. Since the fornix is mainly constituted of efferent fibers from the hippocampus, age-related damage of the fornix could impact hippocampal structure through retrograde processes. The temporal relationship between these structural alterations could be firmly assessed on longitudinal data. Whatever, limbic system alterations at its fornix part appeared during healthy aging and should not be considered as a specific hallmark of the neurodegenerative process occurring during AD.


extfieldsofstudy: Biology Medicine

text:
Deep Sequencing of Small RNA Repertoires in Mice Reveals Metabolic Disorders-Associated Hepatic miRNAs

Obesity and associated metabolic disorders contribute importantly to the metabolic syndrome. On the other hand, microRNAs (miRNAs) are a class of small non-coding RNAs that repress target gene expression by inducing mRNA degradation and/or translation repression. Dysregulation of specific miRNAs in obesity may influence energy metabolism and cause insulin resistance, which leads to dyslipidemia, steatosis hepatis and type 2 diabetes. In the present study, we comprehensively analyzed and validated dysregulated miRNAs in ob/ob mouse liver, as well as miRNA groups based on miRNA gene cluster and gene family by using deep sequencing miRNA datasets. We found that over 13.8% of the total analyzed miRNAs were dysregulated, of which 37 miRNA species showed significantly differential expression. Further RT-qPCR analysis in some selected miRNAs validated the similar expression patterns observed in deep sequencing. Interestingly, we found that miRNA gene cluster and family always showed consistent dysregulation patterns in ob/ob mouse liver, although they had various enrichment levels. Functional enrichment analysis revealed the versatile physiological roles (over six signal pathways and five human diseases) of these miRNAs. Biological studies indicated that overexpression of miR-126 or inhibition of miR-24 in AML-12 cells attenuated free fatty acids-induced fat accumulation. Taken together, our data strongly suggest that obesity and metabolic disturbance are tightly associated with functional miRNAs. We also identified hepatic miRNA candidates serving as potential biomarkers for the diagnose of the metabolic syndrome.

Introduction
MicroRNAs (miRNAs) are a class of small non-coding RNAs that repress target gene expression by a combination of mRNA degradation and translation inhibition [1]. Extensive studies have revealed important and multiple roles of miRNAs in various biological processes, such as cell proliferation [2,3], differentiation [3], death and tumorigenesis [4,5]. Furthermore, emerging evidence also indicates that miRNAs are involved in many metabolic pathways, including adipocyte differentiation, hepatic metabolic integration, insulin resistance and appetite regulation [6][7][8].
Obesity and associated metabolic disorders conditions such as insulin resistance, type 2 diabetes (T2D), hypertension, dyslipidemia, and steatosis hepatis, are worldwide epidemic, and represent major challenges for basic medical science and clinical research. Obesity is also a crucial risk factor for cardiometabolic diseases [9]. Monogenic obesity model (e.g. leptin-deficient ob/ob mice) exhibits overweight, hyperphagia, glucose intolerance and insulin resistance, which serves as a good biomedical model for T2D and metabolic syndrome [10,11]. On the other hand, numerous studies have deciphered that miRNAs are critical regulators of metabolism. For example, the role of miRNAs in lipid metabolism was reported in Drosophila, where deletion of mir-14 increased levels of triacylglycerol and diacylglycerol [12]. miR-122 is a liverspecific miRNA which has been identified to play roles in hepatitis C virus infection [13], cholesterol metabolism [14] and hepatocellular carcinoma [15]. Other metabolic relevant miRNAs, such as miR-103 and miR-107, regulate insulin sensitivity and glucose homeostasis [16]. Interestingly, hepatic miR-34a expression is increased from steatosis to less-and more-severe nonalcoholic steatohepatitis (NASH) [17]. Jordan et al. [18] reported that transgenic over-expression of miR-143 in mice impairs insulin-stimulated AKT activation and glucose homeostasis. Therefore, dysregulation of miRNAs may contribute importantly to the metabolic abnormalities.
High-throughput sequencing of miRNAs provides a highly quantitative evaluation of known individual miRNA species [19]. Since the liver plays a central role in glucose and lipid metabolism, we attempted to identify dysregulated miRNAs by sequencing small RNAs in ob/ob mouse liver using Illumina/ Solexa sequencing platform. The hepatic miRNA candidates under metabolic disorder conditions were validated using RT-qPCR method. We then analyzed the expression of miRNA groups at the miRNA gene cluster and gene family levels. The functional enrichment analysis of the differential miRNAs was also performed to understand their potential physiological roles.

Overview of miRNA Expression Profiles in ob/ob Mouse Liver
To examine the difference of miRNA expression between ob/ob and WT mouse liver, we used the Illumina miRNA expression profiling assay. According to short RNAs that could be mapped to mouse miRNA precursors, the most abundant length was 22 nt, as expected ( Figure 1). 510 miRNAs were detected, and over 13.8% of which showed dysregulated expression. Using a 2-fold expression difference as a cutoff, 37 miRNAs showed significantly differential expression in ob/ob mouse liver. Among which, 12 were up-regulated and 25 were down-regulated ( Figure 2). For those up-regulated, the top ten were miR-122, 24, 195a, 106b, 15b, 802, 185, 214, 378, and let-7c. miR-122 expression was most robustly dysregulated (> 6-fold) in ob/ob mouse liver ( Figure 2A). In contrast, for those down-regulated, the top ten were miR-224, 126, 7a, 128, 455, 452, 135b, 145, 18a and 196a ( Figure 2B). miR-224 expression decreased most (< -5-fold). Furthermore, multiple isomiRs (miRNA variants) have been shown to be detected from the miRNA locus due to imprecise and alternative cleavage of Drosha and Dicer. Herein, assessed fold change (log 2 ) based on the different selection of isomiRs (the most abundant isomiR and sum of all isomiRs) showed various values (Table S1).

Differentially Expressed miRNA Gene Cluster and Gene Family
Next, we performed a comprehensive analysis of isomiR expression patterns in miRNA gene clusters and families [20]. Four abundantly expressed miRNA gene clusters and four gene families were selected. Various enrichment levels could be found among members in miRNA gene cluster and gene family based on the original sequence counts (Figure 3). Clustered miRNAs and homologous miRNAs had various expression levels (even involved in larger expression divergence), but they always showed consistent dysregulation patterns (For example, mir-15b cluster and mir-193b cluster; mir-15 family) although the fold change may differ.

Functional Enrichment Analysis
Functional enrichment analysis of dysregulated miRNAs suggested that the versatile biological roles (Table 1) of these miRNAs were included. These miRNAs contributed to many essential biological processes, such as TGF-beta signaling pathway, cell cycle, Wnt signaling pathway, MAPK signaling pathway, ErbB signaling pathway, Jak-STAT signaling pathway, and etc. Furthermore, these aberrantly expressed miRNA species were involved in occurrence and development of some human diseases, including chronic myeloid leukemia, pancreatic cancer, colorectal cancer, glioma, prostate cancer, and etc.

Validation of the Differentially Expressed miRNAs by RT-qPCR
To further validate the abnormal expression of the collected miRNA species, we selected several typical miRNAs and performed RT-qPCR for double-check. As expected, the result showed similar expression patterns as observed in deep sequencing. For example, miR-122, 24, 106b, 696 and 15b were up-regulated, but miR-126, 145 and 103 were downregulated ( Figure 4).

miR-126 or miR-24 Regulates Lipid Accumulation in AML12 Hepatocytes Exposed to FFAs
To determine whether the disordered miR-126 or miR-24 levels induced by free fat acid (FFA) affect cellular triglyceride (TG) accumulation, we examined the TG levels in AML-12 cells transfected with mimic (Negative control) NC, miR-126 mimic or inhibitor NC, miR-24 inhibitor using Nile red staining. FFA significantly increased the TG accumulation in AML-12 cells compared with controls ( Figure 5). More important, overexpression of miR-126 or inhibition of miR-24 markedly improved fat accumulation in AML-12 cells expose to FFA ( Figure 5).

Discussion
Dysregulation of miRNA expression has been shown to influence glucose homeostasis, cholesterol metabolism and cause insulin resistence, which thus plays an important role in the pathogenesis of metabolic disorders such as T2D, atherosclerosis, fatty liver and Alzheimer's disease [21,22]. In the present study, deep sequencing of small RNA populations in ob/ob mice reveals metabolic disorders-associated hepatic miRNAs.
Here, we observed that 37 metabolic disorder-associated hepatic miRNAs were differentially expressed in ob/ob mouse liver, and they regulated the expression of several important downstream target genes. Overview of the miRNA expression profiles in ob/ob mouse liver, miR-122 is the most abundant miRNA ( Figure 2). It has been demonstrated that miR-370 induces the accumulation of hepatic triglycerides through interacting with miR-122 and Cpt 1α [23]. Another study showed that hepatocytes from anti-miR-122-treated mice showed increased fatty acid oxidation rates and reduced fatty acid synthesis. Accordingly, antagonist of miR-122 used in dietinduced obese mice significantly improved hepatic steatosis and reduced levels of triglyceride accumulation. Taken these previous observations and our data, miR-122 is a risk factor to induce obesity and hepatic metabolic dysfunction. On the other hand, miR-126 is known as an endothelium-specific miRNA, and has been reported to promote angiogenesis by targeting SPRED1 to inhibit VEGF signaling [24]. It also acts as an oncogene by targeting SOX2 in gastric cancer cells [25]. Our results validated that miR-126 was down-regulated in ob/ob mouse liver. Similarly, miR-33 was another down-regulated miRNA in ob/ob mouse live. Silencing of miR-33 in vivo increases hepatic expression of ABCA1 and SREBP-2 [26,27], leading to dysregulation of cholesterol homeostasis. Thus, miR-33 is critical to maintain normal cholesterol metabolism. A recent study suggested that miR-27b was responsive to lipid levels and regulated several key lipid-metabolism genes during dyslipidemia [28]. This miRNA was also detected to be decreased in ob/ob mouse liver, suggesting the impaired responsiveness to fatty acids under this pathophysiological condition. Last but not least, miR-106b was very interesting and it decreased ABCA1 levels and impairs cellular cholesterol homeostasis in neuronal cells [29]. Its function may extend to the liver system according to our data. Collectively, the abnormally expressed miRNAs in ob/ob livers were involved in lipid synthesis, fatty acid oxidation and cholesterol homeostasis through their target genes. Most miRNA studies focus on finding targets of individual miRNAs, yet half of the total miRNAs are co-expressed as clusters [30]. The expression pattern of miRNA gene clusters and gene families in ob/ob mouse liver showed that these miRNAs were coordinately regulated (Figure 3). The miR-15b/ 16-2 cluster generates miR-15b/15b* and 16-2/ 16*-2. Both miR-15b and miR-16-2 were over-expressed in ob/ob mouse liver, however, they were down-regulated in SGC790/VR cells [31]. On the other hand, miR-103 family (including miR-103 and miR-107) was dysregulated in ob/ob mouse liver. These results demonstrate that the miRNA gene family coordinate interaction with each other and function together in the pathogenesis of liver metabolic disorders with consistent dysregulation patterns.
Functional enrichment analysis showed that over six signal pathways and five human diseases were involved. In addition, miRNAs may serve as nodes cross-linking various signaling pathways by the integration of transcriptional inputs or by their functional regulatory outputs, thus highlighting the potential important roles in the epigenetic regulation of lipid metabolic abnormalities. The small non-coding regulatory molecules have opened new avenues for the treatment of metabolic diseases.
The functional analysis in AML-12 liver cells showed that dysregulation of miR-126 and miR-24 is correlated with fat accumulation ( Figure 5). In recent years, several miRNAs, such as miR-155 [32], and miR-217 [33], related fat liver disease have been identified. Although our present study supports the concept that miRNAs contribute to the fat accumulation in mice cell, further work is warranted to identify more specific hepatic miRNAs and their functions involved in lipid metabolic disorders. Whether up-regulation of reduced hepatic miR-126 using miR-126 mimic (or down-regulation of elevated hepatic miR-24 using antagomiR-24) approaches would alleviate liver steatosis in high fat diet-fed mice is currently under investigation in our laboratory.
In conclusion, the present study demonstrated that various miRNAs were differentially expressed in ob/ob mouse liver (especially for miR-126 and miR-24), suggesting that they were tightly linked to obesity and other metabolic disorders. The candidate miRNAs we identified may be potential biomarkers for the diagnose of the metabolic syndrome.

Animal Studies
Male obese ob/ob mice on a C57BL/6J background (12 weeks old) and their male WT littermates were purchased from

RNA Isolation, Construction of Small RNA Library and High-Throughput Small RNA Sequencing
Five liver samples from ob/ob or WT mice (20 mg each in weight) were equally pooled together and kept in RNAfixer (BioTeke Co. Ltd, Beijing, China) at -70 °C until use.
RNA with low molecular weight from liver was extracted using a mirVana™ miRNA isolation kit (Ambion, Austin, TX, USA) following the manufacturer's protocol. The purity and concentration of RNA samples were determined with NanoDrop ND-1000 spectrophotometer (Nano Drop Technologies, Wilmington, DE, USA) at 260/280 nm (ratio > 2.0). 60 μg of total RNA from the pooled samples was used for library preparation and sequencing. The libraries were used for the Illumina/Solexa miRNA deep sequencing which included the following steps: total RNA of each sample was sequentially ligated to 3' and 5' small RNA adapters. cDNA was then synthesized and amplified using Illumina's proprietary RT primers and amplification primers, respectively. Subsequently, PCR amplified fragments within 110-130 bp were extracted and purified from the PAGE gel. When the completed libraries were quantified with Agilent 2100 Bioanalyzer, the DNA fragments in the libraries were denatured with 0.1M NaOH to generate single-stranded DNA molecules, which were captured on Illumina flow cells, amplified in situ and finally sequenced for 36 cycles on Illumina's Genome Analyzer IIx according to the vendor's recommended protocol (Illumina, San Diego, CA, USA) [34][35][36].
Data deposition: The data reported in this paper have been deposited in the Sequence Read Archive (SRA) database, www.ncbi.nlm.nih.gov/sra (accession no. SRR987316; SRR987317)

Bioinformatic Analysis of Solexa Sequencing Data
Low-quality sequence reads failed to pass the quality filter were removed according to the criteria of Solexa/Illumina. 3' adapter sequences were trimmed from clean reads and the tags shorter than 15nt were discarded. Then reads were aligned to the latest known mouse reference miRNA precursor set (Sanger miRBase 19.0, http://www.mirbase.org/) [37][38][39] using Novoalign software (v2.07.11). In this aspect, reads (counts < 2) were discarded when calculating the miRNA expression. In order to characterize the isomiR variability, sequences matching the miRNA precursors in the mature miRNAs region ± 4 nt (no more than 1 mismatch) were accepted as mature miRNA isomiRs, which were grouped according to the 5-prime (5p) or 3-prime (3p) arm of the precursor hairpin [40].
The relative abundance of miRNAs was estimated by the number of reads for each miRNA sequenced, and the read amount of each unique sequence was normalized to reads per million according to the total read count of the mapped reads data set [41]. To compare the differential expression between ob/ob and WT mice, the log 2 ratio of miRNA (ob/ob)/miRNA (WT) was used, and miRNAs exhibiting a fold change value (log 2 ) of higher than 2 or lower than -2 in expression were considered differentially expressed.
The differentially expressed miRNAs were selected to query for their Gene Ontology Enrichment categories using the CapitalBio Molecule Annotation System V4.0 (MAS, http:// bioinfo.capitalbio.com/mas3/). The target mRNAs of these miRNAs were determined based on known experimentally validated target mRNAs from the miRTarBase database [42], the miRecords database [43] and the TarBase database [44]. If no validated target was identified in these databases, the prediction software of TargetScan [45] was used to predict target mRNAs.

RT-qPCR Validation
To confirm the expression of miRNAs identified by the deep sequencing approach, RT-qPCR analysis was performed using the total RNA samples from five ob/ob or WT mouse livers. For miRNA quantification, Bulge-loop™ miRNA RT-qPCR Primer Sets (one RT primer and a pair of qPCR primers for each set) specific for miR-106b, 24, 122, 126, 103, 696, 15b and 145 were designed by RiboBio (Guangzhou, China). The total RNA was extracted with TRIzol Reagent (Invitrogen Corp., Carlsbad, CA). miRNA bulge-loop was then reverse transcribed with the PrimeScript RT reagent kit (Takara Bio, Tokyo, Japan) and quantified by qPCR using SYBR Premix Ex TaqTM II (Takara Bio, Tokyo, Japan) according to the indicated manufacturer's instructions. miRNA expression was normalized to snRNA U6 to get the relative abundance. Averages of three independent experiments each performed in triplicate with standard errors were presented.

Cell Culture and Treatments
The mouse AML12 hepatocyte cells were obtained from American Type Culture Collection and were cultured in DMEM/F12 (Wisent, Nanjing) containing 10% heat-inactivated fetal bovine serum (Wisent, Nanjing) and 1% penicillinstreptomycin (Invitrogen). To test the biological roles of miR-126 and miR-24, miR-126 mimic, miR-24 inhibitor or their corresponding negative controls were transfected into AML12 cells using lipofectamine 2000 reagent (Invitrogen) according to the manufacturer's protocol. After 48 hr, intracellular lipid accumulation was induced according to previously described modified methods [46] and [47]. Briefly, bovine serum albumin (BSA)-conjugated free fatty acids (FFAs; oleate/palmitate, 1/1, v/v) were mixed, and then the culture medium were added into mixture to give a final concentration of 0.4 mM. Control cell cultures were incubated with equal amount of BSA. The stimulation of FFAs lasted for 18 hr.

Nile Red Staining
Cell were fixed with 4% formaldehyde and stained with Nile Red solution (1µg/ml) for 10 min at 37 °C. Lipid-bound Nile Red fluorescence was observed with a fluorescence microscope (Ti-S, Nikon).

Statistical Analysis
Data are presented as the mean ± S.E. Unless otherwise indicated, the statistics was performed using Student's t-test when only two groups were compared. Results with a P < 0.05 were considered statistically significant.


text:
Resveratrol Induces Cell Cycle Arrest and Apoptosis in Malignant NK Cells via JAK2/STAT3 Pathway Inhibition

Natural killer (NK) cell malignancies, particularly aggressive NK cell leukaemias and lymphomas, have poor prognoses. Although recent regimens with L-asparaginase substantially improved outcomes, novel therapeutic approaches are still needed to enhance clinical response. Resveratrol, a naturally occurring polyphenol, has been extensively studied for its anti-inflammatory, cardioprotective and anti-cancer activities. In this study, we investigated the potential anti-tumour activities of resveratrol against the NK cell lines KHYG-1, NKL, NK-92 and NK-YS. Resveratrol induced robust G0/G1 cell cycle arrest, significantly suppressed cell proliferation and induced apoptosis in a dose- and time-dependent manner for all four cell lines. In addition, resveratrol suppressed constitutively active STAT3 in all the cell lines and inhibited JAK2 phosphorylation but had no effect on other upstream mediators of STAT3 activation, such as PTEN, TYK2, and JAK1. Resveratrol also induced downregulation of the anti-apoptotic proteins MCL1 and survivin, two downstream effectors of the STAT3 pathway. Finally, resveratrol induced synergistic effect on the apoptotic and antiproliferative activities of L-asparaginase against KHYG-1, NKL and NK-92 cells. These results suggest that resveratrol may have therapeutic potential against NK cell malignancies. Furthermore, our finding that resveratrol is a bonafide JAK2 inhibitor extends its potential benefits to other diseases with dysregulated JAK2 signaling.

Introduction
Natural killer (NK) cell malignancies are rare in Western countries but relatively common in Asia. These neoplasms, particularly the aggressive NK cell leukaemia/lymphoma subtype, have poor prognoses [1][2][3][4][5][6][7][8]. Even when intensive combination chemotherapies are performed, disease relapse and therapy resistance remain frequent issues. Several L-asparaginase regimens were recently shown to have curative potential but are often associated with serious side effects that can be life-threatening [5,[8][9][10][11]. Therefore, new therapeutic agents with less toxicity and greater efficacy are of particular interest.
Resveratrol, a natural polyphenol found in red grapes, berries, peanuts and other fruits, has been extensively studied for its antioxidant, anti-aging and anti-inflammatory activities. In addition, in vivo and in vitro studies showed that resveratrol possesses potent anti-tumour activity against several malignancies. These effects are mediated by targeting molecules involved in the regulation of cell proliferation and survival, such as phosphatase and tensin homologue (PTEN)/Akt, nuclear factor (NF)-kB and signal transducer and activator of transcription 3 (STAT3) [12][13][14][15][16]. Constitutive STAT3 activation plays a critical role in the growth and survival of several cancers, including NK neoplasms [17][18][19][20][21][22][23][24]. We present the first report of resveratrol efficacy in eliminating NK cell malignancies by inhibiting the Janus kinase 2 (JAK2)/STAT3 pathway, and its notable effectiveness against KHYG-1 cells resistant to L-asparaginase therapy.

Cell Proliferation Assay
Cells were cultured in the absence or presence of increasing concentrations of resveratrol for 48 h. Cell viability was determined using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT, Roche, Basel, Switzerland) according to the manufacturer's instructions. Cells were also treated with 50 mM of resveratrol and their proliferation assessed at different exposure times. The inhibitory rate was calculated as follows: inhibitory rate (%) = [(A2B)/A] 6100, where A is the mean optical density of control cells and B is the mean optical density of test sample cells.

Annexin V Staining
Cells at a density of 5610 5 /ml were treated with various concentrations of resveratrol, L-asparaginase or AG490 at the indicated times. The percentage of apoptosis was measured by flow cytometry using annexin V-FITC (Invitrogen, Carlsbad, CA, USA) and 7-aminoactinomycin D (BD Pharmingen Biosciences, San Diego, CA, USA) according to the manufacturer's instructions.
Synergistic effect between resveratrol and L-asparaginase was determined by the cooperative index (CI) based on the Chou-Talalay method [28,29]. CI = sum of apoptosis of single agent treatment/apoptosis upon combined treatment. When CI,1, CI = 1, and CI.1, the effects were defined as synergistic, additive, and antagonistic respectively.

Giemsa Staining
Cells were treated with 50 mM of resveratrol for 12, 24 and 48 h, with untreated cells as a control. The cells were then collected, resuspended in phosphate buffered solution and centrifuged using cytospin at 800 rpm for 8 min to adhere on microscopic slides. The cells were then air dried, fixed with methanol, stained with Giemsa (Merck) for 20 min, rinsed in water and air dried again. To evaluate apoptosis, morphological changes were assessed under a light microscope.

Western Blotting Analysis
Cells were treated with 50 mM of resveratrol for the indicated times. After treatment, whole cell protein samples were prepared by lysing cells in M-PERH Mammalian Protein Extraction Reagent (Pierce, Rockford, IL, USA) supplemented with phosphatase inhibitor cocktail and protease inhibitor cocktail (Sigma) for 30 min at 4uC. 50 mg of total cellular protein was separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and transferred to polyvinylidene fluoride membranes (Millipore). Milk-blocked blots were incubated at 4uC overnight with primary antibodies and then with appropriate horseradish peroxidase-conjugated secondary antibodies (anti-mouse IgG was obtained from KPL, Gaithersburg, MD, USA and anti-rabbit IgG from Vector, Burlingame, CA, USA). Proteins of interest were revealed using West Pico chemiluminescence (Pierce) and viewed in the luminescent image analyser Las-400 Mini (Fujifilm, Tokyo, Japan).

Flow Cytometry for Cell Cycle Analysis
Cells were treated with 50 mM of resveratrol for 12 h. Cells were then fixed with 70% cold ethanol and analysed after propidium iodide staining. DNA content was determined by FACSCalibur (Becton Dickinson, Franklin Lakes NJ, USA). Data analysis was performed using FlowJo software, version 7.6.3 (Ashland, OR, USA).

Data Analysis
All data are reported as the mean 6 SD of triplicate experiments. Results were analysed using the Student's t-test. All analyses were performed with GraphPad Prism software, version 5.02 (San Diego, CA, USA). A P-value ,0.05 was considered significant.

Effect of Resveratrol on NK Cell Line Proliferation, Viability and Apoptosis
To investigate its potential anti-tumour activities, malignant KHYG-1, NKL, NK-92 and NK-YS cells were cultured in the presence of resveratrol. In a dose-dependent (Fig. 1A) and timedependent manner (Fig. 1B), resveratrol significantly inhibited proliferation of all four cell lines. Resveratrol also induced dosedependent ( Fig. 1C) and time-dependent ( Fig. 1D) apoptosis in all four lines. KHYG-1 cells were notably the most sensitive to resveratrol (Figs. 1A, 1B, and 1C). To investigate morphological changes induced by resveratrol, cells were stained with Giemsa. As displayed in Figure 1E, cells undergoing resveratrol treatment showed morphological signs of apoptosis such as nuclear condensation [30] but were also preceded by cytoplasmic vacuolisation at 12 hours of treatment.

Effect of Resveratrol on NK Cell Cycle Phase Distribution
Because previous reports found that resveratrol modulates the expression of regulatory proteins involved in cell cycle progression [12,31,32], its effect on NK cell cycle status was examined. Treatment with 50 mM of resveratrol for 12 hours resulted in a significant accumulation of cells in the G0/G1 phase for all four cell lines (Figs. 2A and 2B) (P,0.05). This effect was associated with a resveratrol-induced downregulation of cell-cycle regulator proteins, such as cdc2, cdk2, and cdk3, for all four cell lines (Fig. 2C), a finding consistent with a previous report in Burkkit's lymphoma cells [33]. This finding suggests that resveratrol antitumour activity in malignant NK cells involves G0/G1 cell cycle arrest.

Effect of Resveratrol on STAT3 and Apoptotic Protein Activity
Since STAT3 signaling is required for NK cell survival and proliferation [23] and previous studies showed that resveratrol is a strong STAT3 inhibitor, the effect of resveratrol on STAT3 activation was investigated in malignant NK cells. As displayed in Figure 3A, Western blot studies showed that all NK cell lines constitutively expressed phosphorylated STAT3 at Tyr705. Resveratrol notably had time-and dose-dependent kinetic effects on inhibiting STAT3 phosphorylation in NK cell lines (Figs. 3A and 3B). Acetylated STAT3, which recently attracted attention as a tumour-promoting factor [34], was also constitutively expressed by the four cell lines and had its expression markedly reduced by resveratrol.
The effect of resveratrol on MCL1 and survivin was examined because they mediate anti-apoptotic signals downstream of STAT3 activation, and previous studies showed that malignant NK cells constitutively express these proteins [20,35,36]. The effect of resveratrol against other anti-apoptotic proteins including Bcl-2 and Bcl-10 was also investigated. As shown in Figure 3C, resveratrol strongly inhibited MCL1, Bcl-10 and survivin protein expression in all four cell lines. Induction of apoptosis by resveratrol was accompanied by cleavage of caspase 3 in all four cell lines (Fig. 3D). The relations between STAT3 inhibition and cell cycle distribution, apoptosis, MCL1 and survivin were also confirmed in Figure S4 with STAT3 knock down by transient transfection of STAT3 siRNA. These results suggest that STAT3 inhibition plays a role in resveratrol anti-tumour activities against malignant NK cells.

Downregulation of JAK2 by Resveratrol
To elucidate potential mechanisms of resveratrol in STAT3 signaling inhibition, its effect on upstream regulators of STAT3 activation (the JAK family, PTEN and Akt) was examined. Western blot studies showed that while constitutively active JAK1, JAK2, PTEN and Akt were expressed in the four NK cell lines, phosphorylated TYK2 was not detected in any of the cells studied. Resveratrol treatment resulted in consistent inhibition of JAK2 phosphorylation but had no effect on the activation state of JAK1, PTEN, Akt and TYK2 (Fig. 4). Interestingly, chemical inhibition of JAK2 phosphorylation with AG490 vigorously induced apoptosis in all four cell lines (Fig. S1A), and inhibited the expression of STAT3 and its downstream proteins such as MCL1 and survivin (Fig. S1B), thus indicating that inhibition of the JAK2/STAT3 pathway plays a crucial role in the anti-tumour activities of resveratrol against malignant NK cells.

NK Cell Apoptosis Induced by Resveratrol via a p53independent Pathway
The role of p53 in resveratrol-induced apoptosis was investigated because previous studies showed that its anti-tumour effects may be mediated in a p53-dependent or p53-independent manner [37][38][39]. Total protein extracts from NK cells treated with resveratrol were prepared, and their expression of total p53, phosphorylated p53, p53 downstream protein p21 and p53 repressor Mdm2 were analysed by Western blot. Resveratrol did not affect protein expression levels in the four cell lines studied (Fig. 5A). In addition, NK cells pre-cultured with or without pifithrin a, a p53 inhibitor which is by itself non-toxic to the NK cell lines (Fig. S2), were equally susceptible to resveratrol-induced apoptosis (Fig. 5B), indicating that functional p53 is not required for resveratrol anti-tumour activity against malignant NK cells.

Synergistic Effect of Resveratrol Combined with Lasparaginase
In vitro and clinical studies found that L-asparaginase is a promising anticancer agent against NK malignancies [39,40]. To examine potential synergistic activity between resveratrol and L-asparaginase against NK cell neoplasms, the four lines were treated with L-asparaginase alone or with resveratrol and assessed by flow cytometry to measure cell apoptosis. Consistent with previous reports [2,40], L-asparaginase sensitivity varied among the cell lines studied; NK-YS was highly sensitive, NK-92 and NKL were moderately sensitive and KHYG-1 cells were resistant to L-asparaginase (Fig. 6A). In contrast to resveratrol, apoptosis induced by L-asparaginase was not preceded by autophagy-like changes (Fig. S3), indicating that the anti-tumour activities of those compounds are mediated by different mechanisms. Remarkably, L-asparaginase with resveratrol resulted in a synergistic cytotoxic effect against KHYG-1, NKL and NK-92 cells (Figs. 6B and 6C). The synergistic effect was not observed in NK-YS cells (data not shown) presumably because of the extremely high sensitivity of this cell line to L-asparaginase (Fig. 6A).

Discussion
This study demonstrated that resveratrol, a naturally occurring polyphenol, strongly inhibited the growth and survival of malignant NK cells. Mechanism studies revealed that resveratrol inhibits constitutively active STAT3 signaling, leading to downregulation of the anti-apoptotic proteins MCL1, Bcl-10, and survivin. These events contributed to cell cycle arrest at G0/G1 and eventual loss of viability due to apoptosis.
STAT proteins function as downstream effectors of growth factor receptors and cytokine signals that participate in vital processes such as cell proliferation and apoptosis [41]. STAT3 is constitutively activated in human solid tumour cancers such as breast cancer and prostate cancer, as well as myelomas and NK  cell lymphomas [21,23,[42][43][44][45][46]. Aberrant STAT3 signaling in malignant cells thus represents a promising therapeutic target. Our findings show that resveratrol effectively inhibits STAT3 in malignant NK cells, which agrees with other studies that found the polyphenol was an efficacious inhibitor of constitutively active STAT3 in malignant cells [47,48]. Our findings that resveratrol inhibited STAT-3 as well as its downstream anti-apoptotic proteins MCL-1 and survivin are also consistent with its effect on EBV-infected B cells in our previous study [49]. The expression of the anti-apoptotic protein Bcl-2 was not affected by the resveratrol-induced JAK2 inhibition which is consistent with the report by Tsutsui et al [20], showing that JAK2 inhibition with AG490 does not down-regulate Bcl-2 protein in malignant NK cells.
A previous study showed that leukaemic cells lacking functional p53 are L-asparaginase resistant [50]. This is consistent with our finding that KHYG-1 cells with a P53 mutation [25] were resistant to L-asparaginase. Remarkably, the other three cell lines NKL, NK-92 and NK-YS, all of which express wild type P53 protein as reported in previous studies [51,52], were more sensitive to Lasparaginase treatment. Interestingly, KHYG-1 cells were the most sensitive to resveratrol treatment of the four NK cell lines. Efficient induction of apoptosis by resveratrol in NK cells lacking functional p53 is consistent with a report that resveratrol induced both p53-dependent and p53-independent apoptosis [53].
In contrast to previous studies where resveratrol enhanced the function of tumour suppressor PTEN and inhibited activated Akt in tumour cells [47,54], resveratrol treatment in this study did not affect expression of JAK1, PTEN, TYK2 and Akt. The inhibitory effect of resveratrol on STAT3 activation was mediated by inhibition of phosphorylated JAK2 in all four NK cell lines. This is consistent with our findings that the cell lines underwent apoptosis and STAT3 signaling was strongly inhibited when exposed to the JAK2 inhibitor AG490 (Fig. S1), as well as a previous report on NK-YS cells treated with AG490 [20]. Resveratrol-induced JAK2 inhibition is further supported by our findings showing reduction of phosphorylated JAK2 and resveratrol induced apoptosis in HEL cells (data not shown), a myeloid cell line with a JAK2 activation mutation [55]. These findings collectively suggest that resveratrol is a JAK2 inhibitor with considerable clinical relevance, given that dysregulated JAK2 activity is involved in the pathogenesis of hematological diseases such as myeloproliferative neoplasms [56].
One intriguing finding of this study was that resveratrol-induced apoptosis was preceded by cellular morphological changes characterized by accumulation of autophagic vacuoles in the cytoplasm. The absence of these changes in NK cells treated with L-asparaginase (Fig. S3) supports the notion that these compounds exert their anti-tumour effects through different mechanisms. Apoptotic cell death and autophagic cell death have been broadly accepted as two separate mechanisms of programmed cell death, although recent reports suggest that autophagic vacuole accumulation could precede apoptotic cell death [30]. Interestingly, similar morphological changes have been reported in human colorectal DLD1 cancer cells treated with resveratrol [57].
Previous studies revealed that resveratrol is a potent activator of sirtuin 1 (SIRT1) [58][59][60][61][62] and that SIRT1 mediates downregulation of acetylated STAT3 in various cellular systems [63,64]. This is consistent with our finding that acetylated STAT3 decreased in NK cell lines treated with resveratrol and supports  the concept that STAT3 deacetylation is a contributing antitumour property. Although this study did not investigate downstream effects of resveratrol-induced STAT3 deacetylation, a recent report demonstrated that acetylated STAT3 methylates the promoter region of tumor suppressor genes and results in gene silencing that promotes tumour cell proliferation. The same study also showed that inhibition of STAT3 acetylation by resveratrol results in promoter demethylation, restoring the expression of tumour suppressor genes [34].
In conclusion, our data indicate that resveratrol has potent antitumour effects against malignant NK cells that are mediated through inhibition of constitutively active STAT3 signals due to blocking JAK2 kinase. This study is the first to demonstrate that resveratrol is a potent JAK2 inhibitor. As a result, resveratrol may have therapeutic potential against not only NK neoplasms but also haematological disorders where dysregulated JAK2 signaling plays a critical role in pathogenesis.  Figure 6. Synergistic effect of resveratrol combined with L-asparaginase in NK cell lines. Cells (1610 6 /ml) were treated with Lasparaginase (A) or resveratrol plus L-asparaginase (B) at the indicated concentrations for 24 h. The cells were then incubated with anti-annexin V antibody conjugated to FITC and analysed by flow cytometry to evaluate apoptosis. The CI was calculated for each condition (C). The results are the mean of data, with error bars representing the SD of triplicate values. Data represent the drug-induced increase in the percentage of apoptosis cells compared to the respective values observed in parallel control cultures. When CI,1, CI = 1, and CI.1, the effects were defined as synergistic, additive, and antagonistic respectively. doi:10.1371/journal.pone.0055183.g006


extfieldsofstudy: Medicine Biology

s2fieldsofstudy: Biology Chemistry

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Computational repositioning of ethno medicine elucidated gB-gH-gL complex as novel anti herpes drug target

Background Herpes viruses are important human pathogens that can cause mild to severe lifelong infections with high morbidity. They remain latent in the host cells and can cause recurrent infections that might prove fatal. These viruses are known to infect the host cells by causing the fusion of viral and host cell membrane proteins. Fusion is achieved with the help of conserved fusion machinery components, glycoproteins gB, heterodimer gH-gL complex along with other non-conserved components. Whereas, another important glycoprotein gD without which viral entry to the cell is not possible, acts as a co-activator for the gB-gH-gL complex formation. Thus, this complex formation interface is the most promising drug target for the development of novel anti-herpes drug candidates. In the present study, we propose a model for binding of gH-gL to gB glycoprotein leading from pre to post conformational changes during gB-gH-gL complex formation and reported the key residues involved in this binding activity along with possible binding site locations. To validate the drug targetability of our proposed binding site, we have repositioned some of the most promising in vitro, in vivo validated anti-herpes molecules onto the proposed binding site of gH-gL complex in a computational approach. Methods Hex 6.3 standalone software was used for protein-protein docking studies. Arguslab 4.0.1 and Accelrys® Discovery Studio 3.1 Visualizer softwares were used for semi-flexible docking studies and visualizing the interactions respectively. Protein receptors and ethno compounds were retrieved from Protein Data Bank (PDB) and Pubchem databases respectively. Lipinski’s Filter, Osiris Property Explorer and Lazar online servers were used to check the pharmaceutical fidelity of the drug candidates. Results Through protein-protein docking studies, it was identified that the amino acid residues VAL342, GLU347, SER349, TYR355, SER388, ASN395, HIS398 and ALA387 of gH-gL complex play an active role in its binding activity with gB. Semi flexible docking analysis of the most promising in vitro, in vivo validated anti-herpes molecules targeting the above mentioned key residues of gH-gL complex showed that all the analyzed ethno medicinal compounds have successfully docked into the proposed binding site of gH-gL glycoprotein with binding energy range between -10.4 to -6.4 K.cal./mol. Conclusions Successful repositioning of the analyzed compounds onto the proposed binding site confirms the drug targetability of gH-gL complex. Based on the free binding energy and pharmacological properties, we propose (3-chloro phenyl) methyl-3,4,5 trihydroxybenzoate as worth a small ethno medicinal lead molecule for further development as potent anti-herpes drug candidate targeting gB-gH-gL complex formation interface.

Background
Almost 85% of the world population are infected with Herpes Simplex Virus type 1 and type 2 (HSV-1 and HSV-2), which are two members of Herpesviridae family [1]. HSV infects epithelial tissues primarily and then spreads to peripheral nervous system, where it establishes latency in the neurons. Recurrent HSV-1 and HSV-2 infections typically cause oral and genital lesions respectively [2]. HSV infections are more often in people with suppressed immune system like those suffering from AIDS than others [3]. These viruses are known to infect the host cells by causing the fusion of viral and host cell membrane proteins. Fusion is achieved with the help of conserved fusion machinery components that consists of glycoproteins gB, heterodimer gH-gL complex along with other nonconserved components. Formation of gB-gH-gL complex is critical for herpes viral entry into the host cell, thus making this interface the most promising drug target. During the process of this complex formation, gB was proposed to undergo dramatic conformational rearrangements (in a umbrella fashion) as shown in Figure 1 and direct binding of gH-gL was thought to be the trigger for this conformational rearrangements. Complete structural features of gB and gH-gL glycoproteins along with their proposed mode of actions can be found elsewhere in detail [4,5]. Whereas, another important glycoprotein gD, without which viral entry to the cell is not possible, acts as a co-activator for the gB-gH-gL complex formation [6,7].

Role of ethnomedicine in finding novel antiherpes drugs
The nucleoside analog acyclovir, a widely used anti-herpes drug, is unable to cure the chronic infections and recurrence. Use of this drug often leads to the development of viral resistance coupled with side effects and viral latency [8]. Therefore discovery of novel antiherpes drugs with high specificity to inhibit the viral infection deserves great effort. On the other hand, a wide array of antimicrobial compounds with antiviral activity is described in traditional medical literature. Traditional medicine enjoys new found interest among microbiologists because of increasing antibiotic resistance and limited life span of conventional antimicrobials. It is a common practice in various fields of Biomedicine to choose plants described in traditional medicine for finding new successful therapeutic agents [9]. Most of the ethno medicinal compounds were ignored by medical practitioners despite of their proven in vitro and in vivo antiviral properties due to lack of evidence on their mode of action, effective dosage, chemical composition and toxicity [10].
Recent studies have reported promising anti Herpes viral activities of several plant extracts, some of the active constituents of this plant extracts are reported to have potential to interfere with RNA and protein synthesis, DNA replication, cellular fusion, attachment and penetration, virus entry and target cell binding, whereas some are thought to interfere in more than one step of herpes virus life cycle, resulting in complementary mechanisms of action to the existing antiviral drugs, as reviewed elsewhere in the literature [11]. In this scenario, this present work is an attempt to elucidate the possible mode of action of various promising in vitro, in vivo validated anti herpes ethno medicinal compounds to inhibit the viral fusion mechanism by attenuating the gB-gH-gL complex formation interface in a computational approach.

Preparation of protein receptor
The crystal structures of glycoprotein B (gB) (PDB ID: 2GUM) [4] and gH-gL complex (PDB ID: 3M1C) [5] of Herpes simplex virus, which were resolved using X-Ray diffraction method with a resolution factor of 2.10 Å and 3.00 Å respectively were obtained from Protein Data Bank (PDB) [12]. Methodology adapted for the preparation of protein receptor gH-gL complex for the semi flexible docking studies was described elsewhere in detail [13]. The modified structure so obtained was saved in .pdb format and used for all docking studies. Figure 1 Pictorial representation of proposed model by Heldwein, EE et.al, [4] for pre to post fusion conformational changes in gB.

Selection and preparation of ligands
Structures of the ethno medicinal compounds with proven in vitro and in vivo activity against herpes as reviewed elsewhere in literature [11] were retrieved from Pubchem database [14]. All the compounds retrieved were screened with ADME constraints according to Lipinski's rule. Finally, 29 compounds were selected for further studies, which were in accordance with Lipinski's rule. Preparation of the selected ligands was done using Arguslab 4.0.1 software [15], addition of missing hydrogen atoms and fidelity of all bonds was checked using "add hydrogens" and "Clean Hybridization" options respectively. Geometry optimization was done using UFF Molecular Mechanics (MM) method [16][17][18][19][20]. Finally, all the compounds were saved in .mol format for further docking studies.

Protein-protein docking
Protein-protein docking was performed using Hex 6.3 software [21] between Domain II of glycoprotein gB (receptor) and H2 Domain of gH-gL heterodimer complex (ligand). Out of 2000 possible solutions, the best solution binding mode is selected to identify the key residues involved in their binding activity. Following parameters are used in Docking controls of Hex 6.3 to get the best results: Correlation type-Shape only; FFT mode-3D; Post Processing-MM minimization; Grid dimension-0.4; Solutions-2000; Receptor range-180; Step size-7.5; Ligand range-180; Step size-7.5; Twist range-360; Step size-5.5; Distance range-40; Scan step-0.8; Substeps-0; Steric scan-18; Final search-25, whereas the parameters used in clustering controls to get the best results are as follows: Max Clusters-500; Sort solutions by-Cluster; Display clusters-Best; Cluster window-200; RMS threshold-3.0; Bumps threshold-0.

Semi-flexible docking
Docking between receptor gH-gL protein and ligand was performed using "Dock a Ligand" option of Arguslab 4.0.1 software. A spacing of 0.4 Å between the grid points was used. "ArgusDock" was selected as docking engine. Search was performed by enabling "High precision" option in Docking precision menu, "Dock" was chosen as the calculation type, "Flexible" for the ligand and "AScore" was used as the scoring function. A maximum of 150 poses were allowed to be analyzed, binding site box was set to 25 × 25 × 25 angstroms to encompass the entire active site, and each docking run was repeated three times to get the best results.

Analysis and visualization of docking simulation results
The docking results of Arguslab 4.0.1 were saved in .pdb format. Out of 150-model results, one with the least free energy bonding data was selected. Analysis, visualization of the interactions and rendering of all the docking images was done using Accelrys W Discovery Studio 3.1 Visualizer software [22].
Molecular descriptors, such as Log P, the number of hydrogen bond donors, the number of hydrogen bond acceptors, and the molecular mass of the compounds were analyzed by utilizing Lipinski Filter. Osiris Property Explorer and Lazar were used in analyzing various attributes of the drugs, such as toxicity and drug score.

Active site identification and validation
Chowdary TK et.al proposed a gB binding site in H2 domain of gH-gL complex for the gB-gH-gL complex formation through direct binding which is the key step in the formation of fusogen, subsequently leading to the viral entry into host cells [5]. Doina Atanasiu et.al, postulated that Domain II of gB contains the residues that are directly involved in gB binding to gH-gL [23]. Based on the postulates mentioned above and keeping in view of the proposed umbrella fashioned dramatic conformational rearrangements in gB glycoprotein, which was thought to be triggered by direct binding of gH-gL, lead author of this manuscript Syed Hussain Basha has hypothesized a model for pre to post conformational changes during gB-gH-gL complex formation as shown in Figure 2, and performed a protein-protein docking study between Domain II of gB and H2 domain of gH-gL complex using Hex 6.3 software to identify the key amino acid residues involved in initial contact between these two glycoproteins leading to their complex formation, and visualized that VAL 342, GLU 347, SER 349, TYR 355, SER 388, ASN 395, HIS 398 and ALA 387 amino acid residues of gH-gL complex forming hydrogen bonds with LYS 435, ARG 418, GLN 438, PRO 439, LEU 399, GLU 401 and GLY 437 of gB glycoprotein ( Figure 3). The proposed binding sites of gB and gH-gL glycoproteins has been shown in Figure 4. For the present study, proposed binding site of gH-gL ( Figure 4B) with amino acid residues VAL 342, GLU 347, SER 349, TYR 355, SER 388, ASN 395, HIS 398 and ALA 387 was defined as the binding site for the docking studies. To validate the drug targetability of our proposed active binding site in gH-gL, we have repositioned some of the most promising in vitro, in vivo validated anti-herpes molecules onto the proposed binding site of gH-gL complex in a computational docking simulation approach. However, further validation of proposed binding site in gH-gL as much promising drug target over proposed binding site in gB has been deduced elsewhere in detail [24].

Interaction of the ethno compounds with active site
The docking results in pdb were visualized using Accelrys W Discovery Studio 3.1 Visualizer software. A total of 150 poses were visualized for each of the 29 ethno medicinal compounds to identify the model with best docking values, based on the binding energy interactions. The docking result showed that all the 29 compounds analyzed form hydrogen bonds with various amino acid residues in the target molecule, in the range of 0-8 hydrogen bonds (Table 1). Apart from hydrogen bonds, several other interactions like pi-cationic, pi-pi interactions and other non-covalent bonds have thought to play key role in stabilizing the docked compounds in the proposed binding site of gH-gL complex. In all the compounds analyzed, O atom on C = O and -OH functional groups were observed to play a key role in hydrogen bonds formation. Figures 5 and 6 depicts the interactions of the 6 best compounds analyzed towards the target binging site of gH-gL complex that displayed good pharmacological properties with no toxicity.

Binding free energy (ΔG binding)
As per the docking results (Table 1)  binding energy of -8.9 K.cal./mol. Whereas Lignan was unable to dock into the proposed binding site.
The argusdock values of ΔG binding given in Table 1 shows that every ligand has negative ΔG, which shows that all the ethno medicinal compounds analyzed for binding with gH-gL complex are highly stable. These negative binding free energies also evidenced that the reaction is spontaneous.

Prediction of pharmacological properties
Lipinski Filter and Osiris Property Explorer were utilized to screen the drug candidate based on Lipinski's Rule of Five and Oral Bioavailability. The pharmacological attributes prediction results are displayed in (Additional file 1: Table S1) and the structures of all the ethno medicinal compounds used for the study are shown in Additional file 1: Figure S1.
Based on the experimental values, it was inferred that all the ethno medicinal compounds successfully satisfied all the parameters of Lipinski's Rule of Five with the exception of the hydrogen donor for Caffeoylquinic acid. The parameters of the Lipinski's rule are as follows: the molecular weight must be < 500 Da, Log P < 5, the number of hydrogen donors must be < 5, the number of acceptor hydrogens must be < 10, and the refractivity molar range must be between 40-130.
As per the veber's rule, oral bioavailability of drugs could be measured by the molecular weight, number of  rotatable bonds (n rotb), number of hydrogen bonds, and the expanse of the drug's polar surface (TPSA). The oral bioavailability was marked by small molecular weight (less than 500 Da); also, the number of rotatable bond must be less than 10, the number of hydrogen bond donors and acceptors must be less than 12, and TPSA values less than 140. Additional file 1: Table S1 shows that all the compounds have a good oral bioavaibility, with the exception of Caffeoylquinic acid and Rosmarinic acid.
The hydrophobicity of drugs could be inferred from Log P value. Log P Values are directly proportional to the oral hydrophobicity of the drug. More hydrophobic the drug is, higher is the ability of the drug to circulate longer in our body. It wouldn't be easy to excrete such a drug. In the present investigation, the Log P values of the drug molecules were observed to be in the range of -0.4 to 6. The highest Log P value of 6 was observed for Bisbenzylisoquinoline, followed by 3.8 for Lignan and Yatein, which shows that Bis-benzylisoquinoline was the most hydrophobic molecule amongst all the analyzed. However, Anthraquinone, Galangin, Isoborneol, Lignan, Linalool, (3-chloro phenyl) methyl-3,4,5 trihydroxybenzoate, Oxyresveratrol, Physcion, Resveratrol, Rhein, Rosmarinic acid, Wogonin and Yatein also showed good hydrophobicity with a range of log P between 2-5. The drug score value is one such useful practical value which is a combination of variables such as drug likeness, Log P, solubility, molecular weight and toxicity risk, which could be used for the evaluation of a potential drug candidate. A drug molecule with a better drug score has a greater chance to be a drug candidate. As per the values shown in Additional file 1: Table S1, Catechin with a drug score 0.87 showed the highest possibility of being a potential drug and Zeatin with a drug score of 0.1 shown to be the least possible potential drug.

Prediction of toxicity
Osiris Property Explorer and Lazar were used to predict toxicity of the compounds in the present study. The predictions were based on the functional group similarity for the query molecule with the in vitro and in vivo validated compounds present in the database of these two online programs.
Osiris Property Explorer results were visualized using color codes. The result of toxicity analysis of all the analyzed ethno compounds is shown in Additional file 1: Table  S2. Green color shows low toxic tendency, yellow shows the midcore and red color shows high tendency of toxicity.
Additional file 1: Lazar is a software package which is used to detect mutagenic and/or carcinogenic properties based on the similarities in functional group with mutagenic and/or carcinogenic ones present in its database. Additional file 1: Table S3 shows the results of compounds toxicity analysis by lazar. The training dataset of molecules present in Lazar program were verified by conducting an assay with Salmonella typhimurium.

Screening for the best compound based on docking and drug likeliness results
It was found that (3-chloro phenyl) methyl-3,4,5 trihydroxybenzoate was the best anti herpes viral ethno medicinal compound based on its ΔG binding compared to other compounds followed by Bis-benzylisoquinoline and Rosmarinic acid with a binding energy of around -10 K.cal/ mol. However, Bis-benzylisoquinoline and Rosmarinic acid have bad pharmacological and toxicity attributes, based on pharmacological properties. Rosmarinic acid has a TPSA value more in excess of threshold Veber's rule parameter, whereas Bisbenzylisoquinoline showed considerable mutagenicity. (3-chloro phenyl) methyl-3,4,5 trihydroxybenzoate showed good pharmacological attributes, since it satisfied the Lipinski's Rule, Veber's Rule, Log P values, toxicity and drug score threshold.

Conclusion
The binding energy analysis showed that (3-chloro phenyl) methyl-3,4,5 trihydroxybenzoate had a least binding energy value of -10.4 K.cal/mol compared to other compounds followed by Bisbenzylisoquinoline and Rosmarinic acid with binding energy values of -10.1 K.cal/mol each, among all the compounds analyzed. Visualization of the interactions showed that O atom on C = O and -OH groups of all tested compounds played a major role in hydrogen bonds formation with amino acid residues of receptor molecule. Conclusively, our results strongly suggest that (3-chloro phenyl) methyl-3, 4, 5 trihydroxybenzoate is worth a lead ethno compound for developing further as a potent inhibitor against Herpes simplex virus targeting its fusion protein complex. On the other hand, successful repositioning of the analyzed compounds onto the proposed binding site of gH-gL complex shed light on its drug targetability for further investigations. However, as this present work is only a step forward towards understanding the mechanistic insights of a potent inhibitor for herpes viral entry into the host cell targeting gB-gH-gL complex interface, further in vitro and in vivo validations are required.

Additional file
Additional file 1: Table S1. The molecular descriptor values of the ethno compounds used in this study along with their pubchem compound IDs. Table S2. Toxicity of ethno compounds based on Osiris Property Explorer predictions. Table S3. Toxicity of ethno compounds based on Lazar program predictions Figure S1. Structures of the ethno compounds used in the present study.


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Intramolecular interactions control Vms1 translocation to damaged mitochondria

A highly conserved middle region of Vms1 is necessary and sufficient for mitochondrial targeting (MTD). MTD-mediated mitochondrial targeting of Vms1 is negatively regulated by a direct interaction with the Vms1 N-terminus. Under conditions in which selected mitochondria are damaged, Vms1 is selectively recruited to damaged mitochondria.

. The vms1Δ growth defects cannot be rescued by Vms1 deletion mutants.
(A) WT and the vms1Δ strains were transformed with empty vector (ev), a plasmid containing the VMS1 gene (pVMS1), or plasmids containing various deletion mutants of Vms1 as described in Figure 2 (pvms1-182-end to 182-417).
Each strain was grown to saturation in liquid medium and serial dilutions were spotted on both SD-Ura and SD-Ura + rapamycin (20ng/ml) and grown at 30°f or 3 and 7 days, respectively. (B) The vms1Δ strain was transformed with plasmids encoding Cdc48-myc and either Vms1 1-182 -HA, Vms1-HA, or empty vector as indicated. Each strain was grown to log phase in SD-Leu-Trp and harvested. The crude lysates from each strain were immunoprecipitated with anti-HA antibody and Western blots were performed with anti-HA or anti-myc antibodies as indicated.
44 Figure S3. Schematic representation of Vms1 deletion mutants generated and tested for interaction in the yeast two-hybrid assay A series of Vms1 mutants was generated as above. Mutants exhibiting interaction are shown in black while those that failed to interact are shown in red. Figure S4. Vms1 11-end exhibits similar localization pattern to the Vms1 wild type and Vms1 11-end, MutA is constitutively localized to mitochondria.
The vms1Δ strain was transformed with C-terminus GFP tagged full-length wild type Vms1, Vms1 11-end , or Vms1 11-end, MutA . Each transformant was grown to log phase in SD-Ura media and subjected to fluorescence microscopy.
Representative images are shown. Figure S5. Vms1 11-end, MutA is dysfunctional due to its instability.
(A) WT and the vms1Δ strains were transformed with either empty vector (ev), a plasmid containing C-terminus HA tagged full-length wild type Vms1, Vms1 11-end , or Vms1 11-end, MutA . Each strain was then grown to saturation in liquid medium and serial 5-fold dilutions were spotted on both SD-Ura and SD-Ura + rapamycin (20ng/ml) and grown at 30° for 3 and 7 days, respectively. (B) The same transformed cells grown to mid log phase in SD-Ura media were either left as they were or treated with rapamycin (200ng/ml) for 3 hours. The same amount of cells was then harvested to prepare a whole cell extract (WCE).
Identical amounts of WCE were subjected to SDS-PAGE followed by Western blot. The levels of each Vms1 variant were determined by using anti-HA antibody. An antibody against actin was utilized as a loading control. WT and the vms1Δ strains were transformed with empty vector (ev), a plasmid containing C-terminus HA-tagged wild type VMS1 (Vms1 WT -HA), VMS1 MutC and VMS1 MutD . Each strain was grown to saturation in SD-Ura media and a serial 5fold dilution of equal numbers of cells was spotted on both SD-Ura (control) and SD-Ura+rapamycin (20ng/ml) and grown at 30° for 3 and 7 days, respectively. Figure S7. Vms1 1-182, T48A, S127A, S132A, T137A, S138A, S139A mutant exhibits almost identical affinity to Vms1 MTD compared with that of Vms1 1-182, WT .
(A) A schematic representation of phosphorylation sites identified in purified Vms1. (B) The vms1Δ strain was transformed with either empty vector (ev), Vms1 MTD -myc, Vms1 1-182, WT -HA or Vms1 1-182, T48A, S127A, S132A, T137A, S138A, S139A -HA as indicated. Each strain was then grown to log phase and harvested. The crude lysates from each strain were immunoprecipitated with anti-HA antibody and 46 (C) The vms1Δ strain was transformed with both mtRFP and C-terminus GFPfused full-length wild type Vms1 or Vms1 S/T->A mutant. Each cell was then grown to log phase in SD-Ura-Leu medium and subjected to imaging. Representative images are shown.    Heo, Figure S1 WT+e.v.