DNA intermediate structures are formed in all major pathways of DNA metabolism. Transmission electron microscopy (TEM) is a tool of choice to study their choreography and has led to major advances in the understanding of these mechanisms, particularly those of homologous recombination (HR) and replication. In this article, we describe specific TEM procedures dedicated to the structural characterization of DNA intermediates formed during these processes. These particular DNA species contain single-stranded DNA regions and/or branched structures, which require controlling both the DNA molecules spreading and their staining for subsequent visualization using dark-field imaging mode. Combining BAC  film hyperphase with positive staining and dark-field TEM allows characterizing synthetic DNA substrates, joint molecules formed during not only  DNA metabolism pathways including transcription, replication, repair, and recombination involve DNA transactions with transient conformational states and intermediates structures formation. The fine regulation of these DNA intermediates is not only critical for accurate genome duplication, expression, but also strongly participates in the genome maintenance and plasticity. DNA is constantly threatened by exogenous or endogenous challenges producing damages that can alter its structure and consequently the progression of the replication fork, leading to potential genomic instability. Cells have, therefore, evolved several DNA damage response (DDR) pathways to limit the accumulation of damages, insoluble DNA intermediates, and DNA breakages . Precise2+, Ethidium Bromide, PolyHistidine, PolyLysine, Spermidine or Pentylamine/Amylamine). The dsDNA, which is negatively charged, is then absorbed onto the surface , 2928, 2Five microliters of DNA or DNA–protein complexes as indicated (at 0.5 µg/ml DNA) were deposited on the carbon-coated grid for 1 min and then rinsed with two drops of a 2% (w/vol) solution of aqueous UrAc which allowed a fine staining of DNA molecules , 28. AftFresh cleaved mica sheet (rectangles of 1 cm per 2 cm) was partially immersed (45° angle) in a petri dish with 14 cm diameter containing MilliQ water. Two separated drops were deposited in a 1.5 ml Eppendorf tube: a drop containing 2 µl of formamide (Sigma Aldrich), 0.8 µl of 10% BAC  (Sigma Aldrich) and 0.4 µl of glyoxal (Sigma Aldrich), and another drop containing 2.5 µl of ultrapure DNA sample at 25 µg/ml. Just before initiating the spreading, some graphite powder was loaded on the water surface near the mica sheet in order to visually delimit the hyperphase film. After the two drops were quickly spun down forming the hyperphase, the mix was loaded on the mica, slipped along the ramp and therefore onto the water surface, creating the spreading film. The DNA was picked up on functionalized carbon-coated grids by briefly touching the film surface. Grids were washed in a large volume of purified MilliQ water and then 100% ethanol and dried with filter paper. Finally, grids were stained with three drops of 2% UrAc and dried.Samples were visualized in annular or crystallographic dark-field mode using Zeiss TEM902 or Zeiss TEM912 microscopes, respectively. TEM902 was equipped with a magnetic prism electron filter and TEM912 with an Omega energy filter allowing energy-filtered imaging. Such imaging techniques use the energy loss spectrum properties to increase the contrast. In dark-field mode, only electrons scattered at wide angles are collected while the central beam is eliminated. This mode was obtained using either an annular condenser aperture combined with an objective aperture of 40 µm (for Zeiss 902) or a tilted beam combined with an objective aperture of 60 µm (for Zeiss 912). Finally, only zero-loss electrons were selected (zero-loss filtering), which prevents inelastically scattered electrons from contributing to image formation and improves image contrast and resolution. Electron micrographs were acquired using a Veleta or Tengra high-resolution 2k × 2k CCD camera associated with a dedicated iTEM software  at ×30 000 to ×140 000 magnification.+/K+) or divalent (Mg2+ or Mn2+) in buffer solutions. Indeed, DNA conformation and/or topology can be analyzed in various conditions of ionic strength, pH, and in the presence of ligands. Digitizing and contour tracking allows calculating local curvature and flexibility along large linear DNA molecules or on small ones containing specific sites such as a curved region, single-strand break, or abasic site using the appropriate algorithms [Our direct absorption method associated with positive staining allows DNA molecules to deploy rather than being projected on the surface of the carbon film, thus maintaining their conformational properties. In these conditions, the DNA adsorption properties are independent of the presence of counterions, both monovalent  . Toroidal form of supercoiled DNA was obtained at very low ionic strength , the mutual repulsion of the negative charges of the phosphate backbone conferring rigidity to DNA. Addition of monovalent salt restored the canonical plectonemic form of the plasmid without altering its adsorption properties. PhiX174 ssDNA virion diluted in water and spread by direct adsorption and positive staining, appeared to be partially deployed , while the addition of counterions caused its collapse on the surface due to its high flexibility and its folding with the formation of secondary structures . Covering ssDNA with specific ssDNA-binding (SSB) proteins was another way to identify and characterize ssDNA . This combination allowed the deployment and stretching of dsDNA . Importantly, we observed that the BAC film integrity could be affected by the presence of proteins or other contaminants remaining in the DNA sample. With regard to the imaging conditions, we noticed that the positive staining is slightly affected using BPS compared to direct adsorption. First, the background appeared slightly brighter probably due to the interaction between small UrAc clusters with the BAC film on the carbon surface. Second, DNA stretching reduces UrAc staining, which makes DNA thinner. The dark-field mode is essential for such imaging.To develop the analysis of ssDNA containing intermediates, we combined this direct absorption with the usual BAC film hyperphase . It alloof dsDNA , linear of dsDNA . Importain vitro investigations can be efficiently analyzed using both direct absorption and BPS approaches.Synthetic ss–dsDNA substrates (1–3 kb) designed for replication/recombination in vitro HR experiments [in vitro with those from in vivo experiments.We set up protocols to design and prepare ss–ds hybrid and ds–ss–ds (gapped) DNA molecules that could be used to mimic part of DNA intermediates, such as postreplicative gaps formed during replication, and other recombination intermediates. We prepared dsDNA linear fragments extended with a long single-stranded overhang (3′ or 5′) mimicking the double-strand break after the resection step on the early stages of HR (see “Following HR intermediates using a TEM-suitable D-loop assay” section) , or singeriments , 24. MorIn a similar approach, we constructed synthetic four ways DNA substrates also known as Holliday Junctions (HJ) . BPS sprTEM quantitative analysis demonstrated that these DNA substrates were never destructured upon both spreading methods.in vitro approaches to generate and identify specific HR intermediates formed during homology search, strand invasion, and strand transfer mechanistic steps.HR uses a DNA template to repair damaged DNA by finding and copying the intact homologous DNA sequence of the sister chromatid. Rad51 recombinase forms an ATP-dependent presynaptic helical filament on ssDNA resulting from resection and able to catalyze homology search, strand invasion, and strand transfer . We have.The nucleoprotein filament performs homology search by probing duplex DNA throughout the whole genome. Mechanistically, when homology is found, the interaction between the nucleoprotein filament on ssDNA and the duplex DNA donor results in their incorporation into a three-stranded intermediate, the synaptic complex . Then th.in vitro strand exchange between circular ssDNA and linear homologous dsDNA by catalyzing the strand transfer from the extremity of the linear dsDNA to the circular DNA strand originally unpaired [). After addition of the donor dsDNA to the preformed presynaptic filaments, direct adsorption spreading of the sample revealed the formation of different joint molecules due to the capture of linear dsDNA by the Rad51 filament on circular ssDNA , template switching in yeast, meiotic HR, but also identification of the till then theoretical telomeric loop (T-loop) in humans [in vivo sample preparation of these fragile structures to the BPS procedure, we improved their fine visualization.Various endogenous and exogenous damages induce replication fork stalling and collapse, a source of genomic instability. The study of DNA intermediates generated at replication fork represents a crucial point to understand how the replication machinery coordinates with DNA repair and Damage Tolerance (DDT) mechanisms. Efforts have been made to decipher replication dynamics at the molecular level , but structural evidences are often lacking. TEM constitutes a unique tool allowing the fine characterization of n humans . TEM pron humans , 65, 66.in vivo cross-linking, which generates interstrand DNA covalent link (interstrand cross-link) into gDNA sites that are not protected by the presence of nucleosomes or other chromatin-associated proteins. This procedure avoids further slippage or denaturation of DNA intermediates upon the subsequent sample preparation [In order to stabilize the structures, cells were first subjected to UVA/trioxsalen paration . The effparation   and CPT (200 nM) treatments induced a recruitment of RPA70 in the first hour, but the recruitment profiles evolved differently over the time  photoproducts . On the  compare .To provide information on DDR mechanisms used by the cells to cope with the damages, DNA intermediates were characterized by TEM early (1 h) and later (2 h) after both equivalent treatments. In UVC-treated cells, we showed an early accumulation of ssDNA regions at and behind the elongation point of the replication forks . Conversin vitro strand-exchange reaction described above (Two hours following both treatments, multibranched DNA intermediates were observed . Intrigued above . We propin vitro DNA and nucleoprotein machineries related to DNA repair pathways and in vivo replication DNA intermediates. It ranges from the preparation of in vitro and in vivo samples to imaging developments. The use of positive staining approach allows imaging in low-dye condition and will open perspectives to move toward a low-dose acquisition mode in order to improve resolution. These developments will be reinforced by the use of new generation of CCD or direct cameras associated with automatic acquisition system and adequate image analysis software. In this way, our team is actually developing the automatic digitization of DNA molecules by contour tracking, taking into account the different trajectories of the DNA.TEM has a long history of success in characterizing the architecture of DNA intermediates through their direct visualization, which has undeniably provided a unique perspective for drawing the molecular basis of DNA replication and repair mechanisms. We present here methods specifically dedicated to structural analysis of replication and recombination DNA intermediates, including in vitro and in vivo offers unique perspectives for the understanding of these complex molecular choreographies.Finally, while the method described herein represents an original and robust approach to characterize the molecular features of DDR pathways, we now have to explore new strategies to enrich and purify specific intermediate structures to enlarge and precise our application field. Coupled with other biochemical approaches, our method allowed dissecting-specific HR molecular mechanism, highlighting pioneering observations of resection and recombination events. Facing the structures observed bpaa012_Supplementary_DataClick here for additional data file.


Disruptions of white matter microstructure have been widely reported in schizophrenia. However, the emergence of these alterations during preclinical stages remains poorly understood. 22q11.2 Deletion Syndrome (22q11.2DS) represents a unique model to study the interplay of different risk factors that may impact neurodevelopment in premorbid psychosis. To identify the impact of genetic predisposition for psychosis on white matter development, we acquired longitudinal MRI data in 201 individuals  aged 5–35 years with 1–3 time points and reconstructed 18 white matter tracts using TRACULA. Mixed model regression was used to characterize developmental trajectories of four diffusion measures—fractional anisotropy (FA), axial (AD), radial (RD), and mean diffusivity (MD) in each tract. To disentangle the impact of additional environmental and developmental risk factors on white matter maturation, we used a multivariate approach  correlation) in a subset of 39 individuals with 22q11.2DS. Results revealed no divergent white matter developmental trajectories in patients with 22q11.2DS compared to controls. However, 22q11.2DS showed consistently increased FA and reduced AD, RD, and MD in most white matter tracts. PLS correlation further revealed a significant white matter-clinical risk factors relationship. These results indicate that while age-related changes are preserved in 22q11.2DS, white matter microstructure is widely disrupted, suggesting that genetic high risk for psychosis involves early occurring neurodevelopmental insults. In addition, multivariate modeling showed that clinical risk factors further impact white matter development. Together, these findings suggest that genetic, developmental, and environmental risk factors may play a cumulative role in altering normative white matter development during premorbid stages of psychosis. While extensive research has been performed to uncover the etiological mechanisms of the illness, the complexity and heterogeneity of the disorder have made this extremely challenging. It has become increasingly clear, however, that schizophrenia is a progressive neurodevelopmental disorder prompted by the cumulation of genetic, developmental and environmental “hits” that collectively alter the normal course of brain maturation4. Studying the developmental stages preceding the emergence of psychosis is therefore key if we are to unravel the etiological pathways of the disorder. A better understanding of the neuropathological substrates underlying schizophrenia may, in turn, provide important markers for early detection and targets for intervention, which could significantly improve the outcome of patients4 and prevent a downward cascade towards a full-blown psychosis.Schizophrenia is a severe chronic psychiatric disorder affecting ~1% of the world population and involving a very high societal cost5, supporting the “dysconnectivity theory” of schizophrenia7. More specifically, anomalies of white matter structure have been shown to undergo a progressive aggravation as the illness progresses from preclinical to chronic stages9, suggesting an involvement of aberrant white matter development in the neuropathology of schizophrenia. However, research on the early phases of the trajectory to psychosis has been limited by the fact that individuals are mostly identified at the onset of psychosis.Evidence from genetic, postmortem, and neuroimaging studies have increasingly pointed to disrupted white matter structure and function as central neuropathological mechanisms in psychosis10, a neurogenetic developmental disorder occurring with a prevalence of one in 2000–4000 live births11 and with a conversion rate to psychosis of around 40%12. Neuroimaging studies have consistently reported extensive structural and functional brain alterations in the syndrome, and involve thicker cortex and reduced surface area13, reduced whole-brain volume and gyrification, as well as decreased functional connectivity , affecting predominantly frontal and posterior brain regions15. Furthermore, similar to the findings on schizophrenia reported above, volumetric reductions18, widespread alterations of white matter microstructure19, and anomalies of white matter development21 have also been widely reported in 22q11.2DS, suggesting the involvement of a common white matter pathology. However, due to the relatively small size of these studies, the direction of alterations varied considerably and prevented a clear identification of disruptions associated with 22q11.2DS19. A critical advance on white matter alterations in 22q11.2DS was recently made by a large-scale cross-sectional multisite study, which revealed a more consistent pattern of alterations in syndromic individuals involving reduced diffusivity and a combination of increased and decreased anisotropy22. The study further reported older age at white matter maturation peak in 22q11.2DS, suggesting delayed white matter development. However, the cross-sectional nature of neuroimaging studies performed so far in 22q11.2DS may be suboptimal to accurately delineate trajectories of white matter development, as they do not account for within-subject change23. This is even more likely given that longitudinal studies on typically developing individuals have shown complex, non-linear developmental curves of white matter maturation extending through adulthood26. Therefore, a longitudinal delineation of white matter development in 22q11.2DS is needed to clarify the maturational profile of white matter microstructure related to genetic risk for psychosis.Genetic syndromes represent a unique opportunity to study the interplay of different risk factors involved in the unfolding of psychosis during development, as syndromic individuals carry a homogenous risk for the illness and are usually diagnosed early in life. One of the strongest genetic risk factors for psychosis is 22q11.2 deletion syndrome (22q11.2DS)27. In 22q11.2DS, it has been shown that individuals who develop schizophrenia typically present a lower IQ29 and display a cognitive decline starting from 11 years28. Similarly, other studies showed that patients with 22q11.2DS born before term (<37 weeks of gestation)31 or presenting an anxiety disorder at their baseline assessment29 are more likely to develop schizophrenia. Finally, the ultra high-risk (UHR) status , brief intermittent psychotic syndrome (BIPS), and genetic risk plus recent deterioration (GRD))32 has also been identified as a strong predictor of psychosis in these patients33.While genetic factors such as the 22q11.2 deletion can account for an initial vulnerability to psychosis, additional insults occurring during infancy, childhood, and/or adolescence may play a cumulative role in triggering psychosis36 or a cognitive decline37, the impact of the above-mentioned risk factors on white matter maturation remains largely unknown. Evidence increasingly shows that white matter alterations associated with psychosis are widespread and subtle39, suggesting that multivariate approaches may be better suited to capture the complex nature of brain alterations related to premorbid stages. Given that prediction of conversion based solely on clinical markers has proven limited success40, the addition of such multivariate neuroimaging-based biomarkers has the potential to significantly improve the early detection of psychosis.Apart from univariate studies that investigated white matter microstructure in patients with 22q11.2DS presenting psychotic symptoms41. Based on previous findings reported in cross-sectional studies, we hypothesized that the genetic risk conveyed by 22q11.2DS would be associated with widespread alterations in DTI metrics and abnormal age-related changes. Our second objective was to determine whether identified clinical risk factors of psychosis  were associated with specific patterns of brain alterations. We used partial least squares (PLS) correlation42, a multivariate approach specifically tailored to capture complex patterns of association between clinical and brain measures. We hypothesized that clinical risk factors of psychosis would be associated with a widespread pattern of white matter alterations affecting multiple tracts and diffusion measures, reflecting a specific effect of additional developmental and environmental risk factors on white matter maturation.Thus, to clarify the nature of white matter alterations in individuals at genetic high risk of psychosis, our first objective was to delineate the developmental trajectories of long-range white matter tracts’ microstructure in 22q11.2DS using a longitudinal design involving repeated diffusion tensor imaging (DTI) assessments per participant and mixed model regressionThe study was approved by the Geneva Ethics Committee. Written informed consent was given by the participants and their parents. Individuals with 22q11.2DS and controls were recruited in the context of an ongoing longitudinal study, using parent associations or through word of mouth.N = 100 controls , N = 101 22q11.2DS ) aged 5–35 years who contributed a total of 302 scans  47, the psychosis supplement from the Kiddie-Schedule for Affective Disorders and Schizophrenia Present and Lifetime version (K-SADS-PL)48, and the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I)49 for adult patients (starting from 18 years). The Structured Interview for Psychosis-Risk Syndromes (SIPS)50 was used to assess the UHR criteria i.e., attenuated positive symptoms (APS), brief intermittent psychotic syndrome (BIPS), and genetic risk plus recent deterioration (GRD) in individuals with 22q11.2DS starting from 10 years of age.Pregnancy duration was assessed using a medical questionnaire completed by the parents of patients with 22q11.2DS. Preterm birth was established when pregnancy duration was <37 weeks. Full-scale IQ (FSIQ) was evaluated in all participants using age-adapted versions of the Wechsler intelligence scale Preterm birth. Prematurity was established in patients born earlier than 37 weeks of pregnancy .Low baseline FSIQ. To dichotomize FSIQ at the first visit, we followed a similar approach to Vorstman and colleagues28 and divided the sample into two groups using FSIQ = 75 as the cut-off .Cognitive decline. The presence of a cognitive decline was determined as a negative difference between the latest and earliest FSIQ assessments; null or positive changes indicated an absence of cognitive degradation .Presence of an anxiety disorder at baseline. Patients were considered at risk when they presented any type of anxiety disorder at their baseline evaluation . Subtypes of included anxiety disorders are described elsewhere12.UHR. Patients belonged to the UHR category when they met the UHR criteria at least once during their development and, conversely, patients were considered non-UHR when they had never received a UHR diagnosis .Information collected using the above-described assessment methods was subsequently used to define five dichotomized clinical risk factors of psychosis:b = 1000 s/mm2, TR = 8800 ms, TE = 84 ms, flip angle = 90°, acquisition matrix = 128 × 128, field of view = 25.6 cm, GRAPPA acceleration = 2, 64 axial slices, slice thickness = 2 mm.Structural T1-weighted and DTI images were acquired at the Center for Biomedical Imaging (CIBM) in Geneva, using a Siemens Trio (191 scans) or a Siemens Prisma (111 scans) 3 Tesla MRI scanner (see Supplementary Table FreeSurfer v6.0 (http://surfer.nmr.mgh.harvard.edu). Briefly, the longitudinal stream uses all available scans of a given individual to create an unbiased within-subject template51. This method has been shown to increase reliability and statistical power, thereby improving the estimation of within-subject age-related changes52.T1-weighted structural scans were visually examined for motion artefacts and processed using the longitudinal pipeline of 53 from FreeSurfer v6.0 to reconstruct 18 major white matter paths in each subjects’ time points  and forceps minor (FMIN)Anterior thalamic radiation (ATR)Corticospinal tract (CST)Superior longitudinal fasciculus–parietal bundle (SLFP)Superior longitudinal fasciculus–temporal bundle (SLFT)Inferior longitudinal fasciculus (ILF)Cingulum–cingulate gyrus bundle (CCG)Cingulum–angular bundle (CAB)Uncinate fasciculus (UNC)After visual inspection of DTI images for motion artefacts, we used the longitudinal pipeline of the TRacts Constrained by UnderLying Anatomy (TRACULA) tool53, making it a particularly adapted tool for longitudinal studies of white matter development. Once the tracts distributions have been estimated, TRACULA extracts four diffusion measures as averages per tract: (1) fractional anisotropy (FA), indicating the fraction of diffusion that is directionally constrained; (2) axial diffusivity (AD), corresponding to the main direction of diffusion; radial diffusivity (RD), indicating the amount of diffusion perpendicular to the main direction; and mean diffusivity (MD), reflecting the magnitude of diffusivity in the tissue. Of note, tracts reconstruction was unsuccessful in three subjects , resulting in a sample of 199 subjects for the characterization of white matter development. See Supplementary Material . This type of analysis has been applied in previous studies by our group with a similar longitudinal design58, as this approach is suitable for unbalanced data, i.e., with a broad age range at first visit, variable time intervals between assessments and a different number of visits per participant. Random-intercept models were fitted to the data . Within-subject variables were modeled as random effects, and population variables  were implemented as fixed effects. Normal distribution was verified in each model. Gender and scanner type were included as covariates. Different models  were fitted on each trajectory using the nlmefit function in MATLAB R2014b (MathWorks), and the best-fitting model was selected using the Bayesian information criterion (BIC). This process was performed for each tract and diffusion measure. P-values of group and interaction effects were estimated using a log-likelihood approach and corrected for multiple comparisons using the false discovery rate (FDR) method59 (significance level p < 0.05). Mixed models results contain two types of information: group effects, revealed by intercept differences; and age × group interaction effects, revealed by curve shape differences. Graphs display FDR-corrected p-values of group and interaction effects for best-model fits with 95% confidence interval error bands.Mixed models regression analyses were used to characterize the developmental trajectories of white matter pathways in 22q11.2DS and controls . PLS correlation involves the computation of a correlation matrix R = XY between a set of subject-specific brain measures  (X) and behavioral measures  (Y). In the current study, a sample of 39 subjects with 22q11DS with 2–3 scans per subject (resulting in 88 scans) was selected for the PLS correlation analysis. To ensure that the PLS correlation analysis would not be merely capturing age-related maturation processes occurring in white matter tracts, but rather would capture potentially aberrant developmental patterns related to the presence of risk factors in selected individuals, we adopted a three-step approach to create the brain matrix (X): (1) First, mixed models computing the relationship between age and each brain measure in the group of all 39 patients with 22q11.2DS were estimated through the method described above and included gender and scanner type as covariates. This provided an average developmental curve for each tract and diffusion measure. As there are 18 tracts × 4 diffusion metrics, 72 models were fitted. (2) Given that PLS is not adapted for longitudinal data, we then computed the average diffusion metric for each white matter tract across the scans of each subject, resulting in 72 diffusion metrics per subject (one average measure for 18 tracts × 4 diffusion metrics). (3) Finally, in order to account for age, we extracted the residuals  for all subjects in each of the 72 measures. These residuals can be considered as a summary measure indicating the deviation of a given subject with respect to the predicted development at corresponding ages and were used as brain measures. Thus, the resulting brain matrix (X) was a 39 (subjects) by 72 (white matter measures) matrix. Five dichotomized risk factors  were entered in the matrix (Y), resulting in a 39 (subjects) by 5 (risk factors) matrix.To detect white matter alterations associated with the presence of clinical risk factors of psychosis in patients with 22q11.2DS, we performed a PLS correlation analysis using in-house software running on MATLAB R2014b (MathWorks)  by 72 (white matter measures) matrix containing the correlation between each risk factor and each white matter measure across subjects. The main correlation components were then extracted through singular value decomposition (SVD) of the correlation matrix R = USV. As R was a 5 × 72 matrix, a total of five components was extracted.Then, S) reveals the amount of correlation explained by the component, while the behavior weights (columns of U) and brain weights (rows of V) indicate how strongly the original behavior and brain variables respectively contribute to the brain-behavior correlation. A schematic illustration of the procedure can be found in Supplementary Figure p < 0.05). For each significant correlation component, a bootstrapping procedure of 500 random samples with replacement was applied to evaluate the robustness of the brain and behavior weights and provide a bootstrap distribution of the weight values. Bootstrap scores, computed by dividing the mean of the bootstrap distribution by its standard deviation, indicate the contribution of each original variable to the brain-behavior correlation and can be interpreted similarly to z scores. Therefore, in PLS the results, we highlighted tracts with bootstrap scores >1.96 or <−1.96, corresponding to a robustness at a confidence interval of 95%. Finally, a summary “brain score” LX = XVT was computed for each individual by projecting the original brain matrix X onto the brain weights V. Similarly, individual “behavior scores” Ly = YU were computed by projecting the original behavior matrix Y onto the behavior weights U. A higher brain/behavior score indicates that the individual’s brain/behavior pattern is close to the brain/behavior pattern captured by the correlation component. Pearson correlation was computed between individual brain (Lx) and behavioral scores (Ly) of participants to reflect the strength of the correlation captured by the correlation component.For each correlation component, the singular value  and controls (N = 100) revealed an absence of age × group interaction effects, indicating that both groups followed parallel developmental trajectories  in all tracts and diffusion measures. However, significant group  differences were found in all four diffusion measures and in most white matter tracts. Detailed model fits and p-values of group effects and of age × group interaction effects for each white matter tract and diffusion measure are reported in the Supplementary Table After correcting for multiple comparisons using the FDR method, mixed models comparing 22q11.2DS  revealed one significant correlation component . Corresponding brain (white matter microstructure) and behavior  weights are displayed in Fig. PLS correlation between white matter microstructure and risk factors of psychosis within 22q11.2DS  of observed anomalies was inconsistent in previous smaller sample studies19, a recent multisite cross-sectional study provided a clearer pattern of decreased AD, RD, and MD combined with a mixed pattern of increased and decreased FA depending on the tracts22. Using the largest longitudinal DTI sample analyzed to date, our study largely confirmed these findings, as we found widespread and highly consistent reductions in AD, RD, and MD, and increased FA affecting most white matter tracts. Of note, we did not find evidence for FA reductions in 22q11.2DS. It is plausible that longitudinal analyses were optimally suited to capture complex developmental trajectories, resulting in a more consistent pattern of alterations. Alternatively, this difference may also be related to methodological differences or variations in included age ranges.Moreover, in line with previous DTI studies in 22q11.2DS, current evidence confirms the widespread nature of white matter alterations in the syndrome62, whereas reductions in AD may be driven by reduced tract organization, axonal disruption, or a reduction in the diameter of axonal tracts65. While the biological meaning of FA is still debated, increases in this metric have been suggested to reflect reduced axonal branching, which would in turn lead to a reduced amount of fiber crossings66. Interestingly, a recent study using a novel multi-tensor anisotropy measure provided further evidence in support of this hypothesis, as they found similarly increased FA in regions with major fiber crossings in 22q11.2DS67. Other speculations regarding the cellular nature of increased FA include flattened bundles allowing for increased white matter density68, or fewer arched fibers69. Importantly, however, murine models of white matter pathology show an interdependence of FA and RD64, as white matter bundles become more anisotropic when myelination is increased . Accordingly, our findings suggest that 22q11.2DS is characterized by a combination of excessive myelination processes and disrupted tract organization, where fiber bundles may be composed of thinner, less numerous, or more loosely packed axons. Of note, disrupted myelination has been critically related to impaired Glutamatergic-GABAergic neurotransmission leading to brain circuit asynchrony, a highly consistent finding in schizophrenia4 that has been recently confirmed in 22q11.2DS70. Furthermore, it is thought that myelination is partially influenced by neuronal activity71. It is possible that aberrant neurotransmission and white matter microstructure mutually influence each other throughout development to generate brain asynchrony. While the exact relationship between these mechanisms still remains to be determined, our findings add evidence suggesting that a strong genetic risk for psychosis induces profound structural alterations that likely increase the vulnerability for psychosis, potentially by participating in disruptions of brain synchrony.On a neurobiological level, murine models suggest that reductions in RD are indicative of excessive myelination of axonal tractsUsing a multivariate PLS correlation analysis, this study furthermore sought to identify the neural correlates of clinical risk factors of psychosis in 22q11.2DS. Multivariate modeling revealed that UHR was a strongly discriminating factor associated with a very distinctive neuroanatomical pattern of white matter alterations, characterized by consistently increased FA and reduced AD, RD, and MD. Other strongly contributing risk factors were preterm birth and low baseline IQ, but interestingly, these presented an opposite pattern of brain alterations involving increased AD, RD, MD, and reduced FA. While this finding was unexpected, we can speculate that the psychosis risk conveyed by the UHR risk factor involves distinct neurobiological mechanisms that are unrelated to structural alterations at play for other risk factors. The exact neurobiological underpinnings related to these clinical features are, however, yet to be uncovered. Our results also revealed that anxiety disorders at baseline and IQ decline were only weakly associated with the brain pattern, suggesting that white matter alterations are distinctively associated with some specific clinical features of high risk for transition. Overall, shifting to a multivariate approach provided a way to quantify the specific relationship of multiple clinical measures with neuroanatomical structure and revealed for the first time a differential involvement of white matter pathology in different clinical risk factors of psychosis, thereby supporting the existence of multiple neuropathological pathways to the disease.39. While studies have also demonstrated an involvement of white matter alterations in preclinical high-risk stages of psychosis in the general population8 and in patients with 22q11.2DS presenting psychotic symptoms36 or a cognitive decline37, results were heterogeneous and prevented the identification of a reliable biomarker, likely because of the variability and small magnitude of premorbid anomalies. Current evidence suggests that, on the other hand, a multivariate assessment of brain structure can effectively identify early, more subtle patterns of alterations. This evidence therefore supports an increasingly dominant trend in schizophrenia research, arguing that pattern-based biomarkers identified using multivariate methods offer very promising clinical applications and may greatly improve predictive accuracy72, as they can capture alterations that were likely too subtle or too variable to make sense of using univariate techniques.Importantly, multivariate modeling revealed very consistent and widespread patterns of brain alterations, in line with recent evidence indicating that white matter alterations of first-episode and chronic stages of schizophrenia are very diffuse and affect the brain on a global level73. Additional insults occurring during early brain development, such as preterm birth, can further increase this vulnerability, as shown by our multivariate analysis. On the other hand, the association between specific brain alterations and risk factors emerging during late childhood and adolescence  suggests that vulnerability for schizophrenia may also involve a “late” neurodevelopmental hit, affecting brain reorganization and white matter maturation processes occurring at subsequent developmental stages. Taken together, our results support the “two-hit” theory of schizophrenia, suggesting that the disorder results from several waves of detrimental developmental events73.Interestingly, the delineation of white matter developmental trajectories in 22q11.2DS and multivariate assessment of clinical risk factors may provide critical information regarding the timing of neurodevelopmental events associated with strong genetic and clinical vulnerability for psychosis. Specifically, the presence of widespread white matter alterations combined with normative-like developmental trajectories in 22q11.2DS suggests that syndrome-related anomalies of white matter microstructure appear very early on, during prenatal or early childhood developmental stages. Considering the major role of genetic programming during brain formation in utero and infancy, it is plausible that the haploinsufficiency caused by the 22q11.2 deletion acts like an “early hit” which already strongly increases the vulnerability for psychosis74). Next, cellular and molecular investigations of pre-and perinatal phases are needed to determine the exact underlying mechanisms and timing of developmental events that drive white matter alterations observed in this study. Particularly, the hypothesis of reduced fiber crossings in 22q11.2DS, as well as the potential presence of excessive myelination are promising areas of investigation. Of interest, several genes within the 22q11.2 locus are involved in myelin-related signaling pathways  or axonal growth and branching (ZDHHC877) and may therefore play a key role in the emergence of white matter disruptions. Finally, as some risk factors such as cognitive deficits can be readily measured in mice, it will be important to confirm their association with the emergence of additional white matter disruptions during development. Collectively, these lines of work may provide a neurobiological confirmation of the two-hit theory of schizophrenia and may further delineate mechanisms underlying white matter dysconnectivity in the illness.The current findings highlight several important translational research directions. First, white matter microstructure should be assessed in animal models of 22q11.2DS using MRI to confirm the present results, as white matter microstructure of such models has not yet been fully characterized , implying that these results should be considered as preliminary and will need confirmation in larger samples. Relatedly, larger samples may provide an opportunity for outcome prediction studies, which are strongly needed to further consolidate early detection and intervention methods. Fourth, the DTI model of diffusion may be suboptimal in assessing complex brain regions with a high amount of fiber crossings, as it forces the estimation of a single average direction of diffusion in each voxel79. Studies using more complex, high-resolution image acquisitions for white matter microstructure are currently underway. Despite this limitation, the DTI model is widely used and accepted as a valid model for assessing white matter microstructure in humans. Finally, scans were acquired using two different MRI scanners and head coils . The proportion of scans was however similar in 22q11.2DS and controls as well as in all risk factor groups (see Supplementary Material, Table This study has some limitations. First, while this is the first study delineating developmental trajectories of white matter microstructure using longitudinal data with up to three-time points, larger longitudinal samples including a higher number of time points per subject and a longer total follow-up time will be needed to further improve the characterization of white matter maturation. Second, significant differences in IQ were observed between patients with 22q11.2DS and controls. While lower IQ is an inherent characteristic of the syndrome that is difficult to disentangle from its other phenotypic features, future studies including IQ-matched controls are warranted to fully address the potential role of IQ in white matter alterations. A third limitation concerns the limited sample size available for the multivariate PLS analysis of risk factors for psychosis (To conclude, findings from this study provide strong evidence for precocious neurodevelopmental anomalies of white matter structure in 22q11.2DS, clarifying the role of genetic high risk for psychosis in white matter maturation. Results furthermore indicate that additional clinical risk factors for psychosis further impact white matter development, with a differential involvement of UHR, preterm birth, and low IQ at baseline. As such, longitudinal and multivariate approaches of white matter microstructure represent effective means to capture complex developmental brain alterations preceding psychosis and show potential for the identification of predictive and prognostic biomarkers. Future studies using larger samples should be conducted to further confirm the neurodevelopmental underpinnings of genetic and clinical risk factors of premorbid psychosis. A particular emphasis should be placed on the collection of samples that include both the preclinical stage, as well as the transition to clinical stages of psychosis. An overview of the full trajectory to psychosis will indeed provide means to assess the predictive accuracy of alterations identified in preclinical stages, which will be a critical step to further improve our understanding of the neuropathological pathways leading to psychosis.Supplemental Material


As the WNK-SPAK/OSR1 pathway reciprocally regulates NKCC and KCC, a growing body of evidence implicates over-activation and altered expression of NKCC1 in stroke pathology whilst stimulation of KCC3 during and even after a stroke event is neuroprotective. Both inhibition of NKCC1 and activation of KCC3 exert neuroprotection through reduction in intracellular chloride levels and thus could be a novel therapeutic strategy. Hence, this review summarizes the current understanding of functional regulations of the CCCs implicated in stroke with particular focus on NKCC1, KCC3, and WNK-SPAK/OSR1 signaling and discusses the current and potential pharmacological treatments for stroke.Stroke is one of the major culprits responsible for morbidity and mortality worldwide, and the currently available pharmacological strategies to combat this global disease are scanty. Cation-chloride cotransporters (CCCs) are expressed in several tissues (including neurons) and extensively contribute to the maintenance of numerous physiological functions including chloride homeostasis. Previous studies have implicated two CCCs, the Na Identification of these CCCs in several tissues such as red blood cells, epithelia, and neurons have alluded to their extensive contributions to ion and water homeostasis, both at a cellular and trans-epithelial level i) influence the modulation of their expression, and (5) the regulation of CCCs activity is achieved through phosphorylation and dephosphorylation processes i in particular, influences the movement of fluid across epithelia, the polarity of GABA, and more. The electroneutral CCCs are critical determinants of [Cl−]i [−]i gradient across the neuronal membrane is crucial for controlling the polarity of GABAergic signaling. GABAA conducts Cl− ions. The direction of Cl− movement through GABAA, which determines whether it is excitatory or inhibitory, is dependent on the [Cl−]i gradient. Entry of Cl− through GABAA results in the hyperpolarization of neurons and the extrusions of Cl− through GABAA depolarizes the neurons i in the pathways for regulatory volume increase (RVI), while the KCCs promote decrease in the [Cl−]i as one of the regulatory volume decrease (RVD) mechanisms [−]i. Their importance in physiological function is evident by the many human Mendelian disorders of the brain and renal phenotype that arise due to mutations in some members of the CCC family and their upstream regulators i ,60. The  neurons ,61,62,63 neurons ,64. NKCCchanisms ,53,65  exchange with Cl− to maintain cellular balance, regulatory mechanisms are crucial to coordinate their activity . In. In1048 recovery . Under hrecovery . Furtherl volume  65]. Th. Th1048 al edema ,86,92.+/H+, Na+/Ca2+ and Na+/HCO3− exchangers) can contribute to glial apoptosis, inflammation, demyelination, inflammation, and excitotoxicity i in the sensory neuron of adult mice. This suggests their involvement in GABAergic/glycinergic transmission as adjudged by its influence on the hyperpolarization of GABAA equilibrium potential (EGABA-A) resulting in inhibitory GABAergic neurotransmission due to a decrease in [Cl−]i. Our recent functional kinomics study alluded that regulatory phosphorylation of KCC3 (Thr991/Thr1048 residues) is essential for cell volume homeostasis in the mammalian brain [−]i and consequent influence on GABA polarization state is fascinating and suggests possible relationship between neuronal excitability and cell volume homeostasis [−]i i  which wi−/−) mice as well as its mutations in humans i, suggest its involvement in regulation of neuronal CCCs i extrusion [−]i extrusion in the neurons would facilitate GABAA receptor-mediated hyperpolarization and thus inhibit neuronal activity through combined NKCC1 inhibition and KCC3 stimulation i in neurons i in hippocampal tissue cultured from rats either during oxygen-glucose deprivation for 120 min or post-exposure. The drug improved neuronal viability during the acute ischemic episode which suggested its critical role in the modulation of transmembrane chloride transport i to the physiological level in mature hippocampal neuronal cultures of Ts65Dn mouse model Down syndrome (DS) coupled with rescued cognitive impairment in Ts65Dn with no significant diuretic effect in either the WT or Ts65Dn mice i in the sensory neurons i. Modulation of NKCC1 and KCC3 expressions by their upstream regulator, WNK-SPAK/OSR1 is implicated in the development and progression of stroke. There are several demonstrations that phosphorylation of NKCC1 and KCC3 via the WNK-SPAK/OSR1 signaling may lead to activation of NKCC1 and inhibition of KCC3 either during or post-stroke episode. In fact, the role of NKCC1 and KCC3 as well as their regulatory proteins in stroke pathogenesis suggests that they are potential targets for the treatment of stroke. The pharmacological strategies that were discussed in this review possess potential therapeutic efficacies for stroke management. Novel compounds must successfully address concerns regarding off-target effects due to the many isoforms and physiological function related to the WNK-SPAK/OSR1-CCC pathway. As advances in stroke therapy may also benefit other neurological impairments, we strongly suggest consistent follow-up actions on currently available pharmacological treatments for stroke through detailed research studies to aid further development of therapeutic drugs with a better pharmacokinetic profile. Hence, we holistically advocate for increased focus on human clinical research on this topic as informed by its paucity to that regards.The CCCs play crucial roles in regulating neuronal functions. The cotransporters are key mediators of several and important cellular functions such as cell volume regulation, trans-epithelial ion transport, and maintenance of [Cl


Y1815F mutation abrogating SlitC but not Sema3B responsiveness, manipulations in the chicken embryo, and ex vivo live imaging. This revealed a guidance mechanism by which SlitC constantly limits growth cone exploration, imposing ordered and forward-directed progression through aligned corridors formed by FP basal ramifications.Spinal commissural axon navigation across the midline in the floor plate requires repulsive forces from local Slit repellents. The long-held view is that Slits push growth cones forward and prevent them from turning back once they became sensitized to these cues after midline crossing. We analyzed with fluorescent reporters Slits distribution and FP glia morphology. We observed clusters of Slit-N and Slit-C fragments decorating a complex architecture of glial basal process ramifications. We found that PC2 proprotein convertase activity contributes to this pattern of ligands. Next, we studied Slit-C acting via PlexinA1 receptor shared with another FP repellent, the Semaphorin3B, through generation of a mouse model baring PlexinA1 During neural circuit formation, axons are thought to navigate series of intermediate targets or choice points until they reach their final destination . This coThe formation of spinal cord commissural circuits provides a very suitable model to address the mechanisms of intermediate target navigation. Commissural axons cross the midline in a key intermediate target located at the ventral side of the neural tube, the floor plate (FP). Glial cells, composing the FP, have a typical progenitor-like bipolar morphology, with a dorsal apical anchor at the lumen of the central canal and a basal process laying ventrally on the basal lamina, even though some studies suggested these cells have complex morphology . CommissTo gain novel insights into the process of FP navigation, we focused in the present study on the SlitC-PlxnA1 signaling. Through combinations of in vivo analysis, live imaging, and super resolution microscopy, we show that SlitC does not act by pushing commissural axons after crossing. Instead, it is deposited onto remarkably complex ramifications of FP glia basal process that mark out the entire FP navigation path. Reiterated contacts with ligand-coated glial surfaces produce continuous constrains that protect the growth cones from the risk of aberrant deviations that could result from active exploration and response to other guidance cues of their local environment.Y1815F mutant receptor in commissural neurons significantly reduced their SlitC but not Sema3B induced growth cone collapse response  and premature turns (from 5% to 27%) for pHluo-PlxnA1Y1815F+ axons compared to pHluo-PlxnA1WT+ ones , which was also consistent with the lack of increased stalling phenotype in PlxnA1Y1815F/Y1815F mouse embryos. We also analyzed commissural axon trajectories to quantify their degree of deviation. As in mouse open-books, we found the percentage of straight trajectories significantly decreased from 83% in the PlxnA1WT condition to 53% in the PlxnA1Y1815F one, with correlated increase in curved shapes  nanobodies and STED microscopy that the membrane pool of PlxnA1g the FP . PlxnA1Ywth cone .Y1815F spatial distribution in commissural axons navigating the FP is altered, which reveals that the mutation might interfere with SlitC-specific traffic and signaling.Thus, PlxnA1Y1815F condition, the fluorescence recovery was significantly higher over the first time points, than in the PlxnA1WT one, and the difference established from this early step remained constant over time. Thus, PlxnA1Y1815F has a faster membrane diffusion than PlxnA1WT. The stability of the difference over time also suggests that exocytosis events might be unaffected by the mutation. Thus, Y1815F mutation results in relapse of PlxnA1 mobility at the cell membrane which, either upstream or downstream of SlitC binding, could affect the ability of the receptor to mediate SlitC signal.Next, we conducted fluorescence recovery after photobleaching (FRAP) experiments to compare exocytosis and membrane motility of WT and mutated PlxnA1 in commissural growth cones navigating the FP. The pHluo-receptor fluorescence was bleached, and then the fluorescence recovery was recorded for 20 min –8. StrikNext, to gain insights into how SlitC maintains a straight growth of commissural axons, we wanted to get a precise analysis of the topology of the axon navigation path in the FP and to characterize the spatial distribution of the different ligands . We firsWe next performed a sparse electroporation of mbTomato in chick embryos to examine individual cells and their arrangement in the three dimensions of the tissue. We observed that the basal process of the glial cell is not a simple extension but rather is a ramified structure . 3D recoNext, we studied the FP distribution patterns of PlxnA1 ligands. For Sema3B, we took advantage of our knock-in model of Sema3B-GFP fusion . TransveStudy of Slit fragments distribution is limited by the lack of antibodies allowing their individual detection and distinction from the full-length form. Thus, as in Drosophila  . We veriosophila . Amontilosophila . We treaosophila . Thus, PThen, we examined PC2 expression in transverse sections of E4 chicken embryos immunolabeled with an anti-PC2 antibody. We observed that PC2 was mostly expressed in the FP . Signal WT+ and PlxnA1Y1815F+ growth cones morphologies in the FP. In chick open-books electroporated with pHluo-PlxnA1WT and pHluo-PlxnA1Y1815F, we quantified growth cones of two classes of shape: oblong, modestly enlarged compared to the adjacent axon segment, and more complex, with visible protrusions and enlarged more than two times compared to the adjacent axon segment (Y1815F+ growth cones (17%) than pHluo-PlxnA1WT+ ones (5%)  . Strikinnes (5%) .Y1815F/Y1815F embryos when exposed to SlitC and Sema3B. Our previous work showed that at basal condition mimicking the pre-crossing context, cultured commissural growth cones express low levels of PlxnA1 at their surface and are insensitive to SlitC and Sema3B. Treatment with GDNF, a cue expressed by FP cells, to mimic the FP crossing context, results in increased cell surface PlxnA1 and gain of sensitivity to subsequent SlitC and Sema3B bath application  and exploratory (deviations from the straight axis) (Y1815F+ population (59%) than in the pHluo-PlxnA1WT+ one (15%) (Y1815F+ growth cones were much more frequent than PlxnA1WT ones (49% and 9% respectively)  of chick open-books electroporated with pHluo-PlxnA1ht axis) . Strikinne (15%) –16. Explctively) . We did th cones .Our results support a model whereby growth cone trajectories are actively kept straight over the entire FP navigation through reiterated contacts with SlitC spots of basal processes. PlxnA1 mutation altering perception of SlitC alleviates these constrains, which results in abnormally dynamic growth cones that actively explore the FP space. Such aberrant behavior compromises efficient and straight navigation across the FP leading to premature rostro-caudal deviation and turning back . Thus, rCharacterization of guidance cues spatial distribution is only beginning. Recent work revealed that spinal cord progenitors that synthesize Netrin1, a major attractant for spinal cord commissural axons, take advantage of their basal process to redistribute Netrin at a more lateral position close to the basal lamina, where it promotes commissural axon navigation toward the FP . Hence, Drosophila midline guidance for which Slit processing was reported to be dispensable . Mice were back-crossed to obtain PlxnA1Y1815F in a C57/BL6 background. Mice were hosted either in SPF  or conventional  animal facility with ad libitum feeding. This study was covered by a Genetically Modified Organisms approval  and a local ethical comity . Genotyping was performed on dissected tails lysed in NaOH 1M solution for 25 min at 95°C and digested overnight with Proteinase K at 56°C with the following primers: 5′-CTT ATA GAT CTA GAC AGG CAG GGA GAC CAT-3′ and 5′-CGG TTG TCT TCT CGA GTA TCA CAC TCC TA-3′. The PCR kit used was FastStrat PCR Master . The amplification product from mutated allele has a 341 bp size and the one obtained from a wild-type allele is 262 bp. Genotyping of PlxnA1-/- was done as in The PlxnA1Y1815F was obtained by directed mutagenesis using the In-fusion HD Cloning Plus Kit  with the following primers: 5′-AGG TAC TTT GCT GAC ATT GCC and 5′-GTC AGC AAA GTA CCT TTC AAC. The pH dependency of the fluorescence was validated as in FL mouse pHluo-PlxnA1 was generated by introducing in Nter the coding sequence of the pHluo cloned from a vector encoding GABA A pHluo-GFP . FL mousDual-tagged Slit2 was designed using the human Slit2 sequence (NM_001289135.2) and ordered from Genscript Biotech. Briefly, Cerulean was inserted after Slit2 signal peptide (MRGVGWQMLSLGLVLAILNKVAPQACPA) and Slit2 FL sequence. Venus was fused to the C-terminal part of Slit2. Dual-tagged Slit2 Δ construct was obtained by Quickchange mutagenesis procedure (Agilent), deleting nine amino acids (SPPMVLPRT) at the cleavage site. The primer used for the mutagenesis were 5′-CTT GTT CTG TGA GTTT AGC CCC TGT GAT AAT TTT G-3′ and 5′-CAA AAT TAT CAC AGG GGC T AAA CTC ACA GAA CAAG-3′. Both constructs were cloned into a PCAGEN vector using NotI and EcoRV digestion. The Hoxa1-GFP plasmid was a kind gift of Esther Stoeckli.The fusion of Slit2N and Slit2C with GFP was performed in order to express the fusion proteins resulting from the cleavage of Slit2 Dual-tagged construct: GFP-SlitN (GFP in Nter) and SlitC-GFP (GFP in Cter). The fusion of Slit2N with GFP was done by cloning the Slit2 signal peptide, the eGFP and the Slit2N sequences in a pCAGEN backbone using the In-Fusion HD cloning Plus Kit  with the following primers: 5′-GCA AAG AAT TCC TCG AGG ATA TCA TGC GCG GCG TTG GCT GG-3′ and 5′-TGC TCA CGT TAA CCG CCG GGC ACG CCT G-3′ for the signal peptide; 5′-CCC GGC GGT TAA CGT GAG CAA GGG CGA GG-3′ and 5′-AGC ACT GAC GCG TCT TGT ACA GCT CGT CCA TGC-3′ for eGFP; 5′-GTA CAA GAC GCG TCA GTG CTC TTG CTC GG-3′ and 5′-CTG AGG AGT GCG GCC GCG ATT TAA CGA GGG AGG ACC ATG GG-3′ for Slit2N. The CAG promoter was then replaced by the Hoxa1 promoter using In-Fusion with the following primers: 5′-GTG CCA CCT GGT CGA CGC TTC TTC TAG CGA TTA AAT C-3′ and 5′-AAC GCC GCG CAT GAT ATC CCC ACT AGT AAG CTT GGA GGT G-3′. The fusion of Slit2C with GFP was done by cloning the sequences into a pEGFP-N3 vector after the addition of KpnI and BamHI restriction sites using the following primers: 5′-CG GGTACC ACC AGC CCC TGT GAT AAT TTT G-3′ and 5′-CG GGATCC GGA CAC ACA CCT CGT ACA GC-3′. The Igκ Leader peptide signal was added for correct secretion by cloning the fusion fragment into a pSecTagB plasmid using KpnI and NotI digestion. The resulting sequence was cloned into a pCAGEN vector using XhoI and NotI digestion, and the In-Fusion HD Cloning Plus Kit  with the following primers: 5′-CAA AGA ATT CCT CGA GAT GGA GAC AGA CAC ACT CCT GC-3′ and 5′-CTG AGG AGT GCG GCC GCT TAC TTG TAC AGC TCG TCC ATG CC-3′. The CAG promoter was replaced by the Hoxa1 promoter using SalI and XhoI digestion, and the In-Fusion HD Cloning Plus Kit with the following primers: 5′-GTG CCA CCT GGT CGA CGC TTC TTC TAG CGA TTA AAT CAA AG-3′ and 5′-CTG TCT CCA TCT CGA GCC CAC TAG TAA GCT TGG AGG TG-3′. Math-1-mbTomato construct was described previously .Spinal cords from E12.5 murine embryos were dissected and mounted as open-books prior to fixation in 4% paraformaldehyde (PFA) for 18 hr. DiI crystals  were inserted in the most dorsal part of one hemi-spinal cord for anterograde labeling of commissural tracts. Axon trajectories were analyzed 24 hr later with a spinning disk microscope (Olympus X80). For each DiI crystal, a range of phenotypes can be observed. Classes were made representing the percentage of DiI crystals showing the phenotype over the total number of observed DiI crystals. Classes were assessed independently, with percentage ranging from 0% to 100%.Cryosections from embryos collected at E12.5 were prepared and processed for staining as in The neural tube of HH14/HH15 chick embryos was electroporated as described previously . Plasmid1.5 mg/mL for dual-tagged Slit2 and dual-tagged Slit2 Δ. Lower concentration did not allow correct imaging with confocal microscopy.1.34 mg/mL for Hoxa1-Slit2N-GFP and 0.94 mg/mL for Hoxa1-Slit2C-GFP. Both concentrations match the dual-tagged plasmid molarity in order to electroporate the same amount of plasmid.Y1815F and 0,05 mg/mL for mbTomato and Hoxa1-GFP. These concentrations were selected according to our previous work . Using electrodes  three pulses  were delivered by CUY-21 generator (Sonidell). Electroporated embryos were incubated at 38.5°C. In ovo electroporation of FP cells was done on HH17/18 chick embryos as described in E12 mice embryos were collected and fixed on a SYLGARD (Dow Corning) culture plate in HBSS medium (ThermoFisher) supplemented with Glucose 1M (Sigma-Aldrich). Injection of plasmids into the lumen of the neural tube was performed using picopritzer III . Using electrodes  three pulses  were delivered by CUY-21 generator (Sonidell). Spinal cords were dissected from the embryos and cultured on Nucleopore Track-Etch membrane (Whatman) for 48 hr in Slice Culture Medium .Live imaging was performed with an Olympus IX81 microscope equipped with a spinning disk  and Okolab environmental chamber maintained at 37°C. Image was acquired with a 20× objective by EMCCD camera . Fifteen to thirty planes spaced of 0.5–3 μm were imaged for each open-book at 30 min interval for 10 hr approximately. To reduce exposure time and laser intensity, acquisitions were done using binning 2 × 2. Images were acquired using IQ3 software using multi-position and Z stack protocols. Z stack projections of the movies were analyzed in ImageJ software. The analysis of pHluo-flashes was performed from time-lapse acquisitions. In some experiments, the time interval was reduced for faster image acquisition. Time intervals of 3, 5, 8, and 12 min were tested. At 3 and 5 min, the tissues were rapidly damaged. We thus selected time interval of 8 min as the better compromise between time resolution and phototoxicity. Confocal imaging was performed with either an Olympus FV1000 with a 40× objective and zoom or a Leica TCS SP5 with a 63× objective. Deconvolution was done using the Huygens software. 3D surface reconstructions were done using the Imaris software.Spinal cords were incubated at 38°C for 20 min with F12 medium supplemented with 5% FCS , 20 mM HEPES buffer , and 1/100 GFP-nanobodies Atto647N. They were then rinsed four times with the same medium free of GFP-nanobodies and fixed at room temperature for 2 hr with PBS supplemented with 4% paraformaldehyde (PFA) and 1% BSA (A7638 Sigma-Aldrich). Open-books were observed with a STED microscope . STED illumination of ATTO 647N was performed using a 633 nm pulsed laser providing excitation, and a pulsed bi-photon laser  turned to 765 nm and going through a 100 m optical fiber to enlarge pulse width (100ps) used for depletion. A doughnut-shaped laser beam was achieved through two lambda plates. Fluorescence light between 650 and 740 nm was collected using a photomultiplier, using a HCX PL-APO CS 100/1.40 NA oil objective and a pinhole open to one time the Airy disk (60 mm). Images were acquired using Leica microsystem software and a Z stack protocol. Usually 10–20 planes spaced of 0.5 μm where imaged for each growth cone. The growth cones were delineated and the intensity signal was calculated using ImageJ.FRAP experiments were conducted on spinal cord open-books electroporated with either pHluo-receptor and mbTomato, using a Leica DMI6000  equipped with a confocal Scanner Unit CSU-X1  and a scanner FRAP system, ILAS . Images were acquired in both green and red channels using a 63× objective and an Evolve EMCCD camera . Growth cones located in the FP were first monitored for 12 s each 3 s and then bleached using a 488 nm diode laser at full power. This resulted in an 85–95% loss of the signal (mean of 89%) at t = 0. Fluorescence recovery was then monitored for 730 s with acquisitions every 3 s for 30 s, then every 10 s for 100 s, and finally every 30 s for 600 s. The images were corrected for background noise, residual fluorescence right after the bleach was set to zero, and recovery curves were normalized to the fluorescence lost after the bleach. No other corrections were applied since unbleached growth cone fluorescence showed no significant decay during the acquisition period.5 cells per well). 24 hr later, cells were transfected using jetprime transfection reagent . Four hours after starting the transfection, cell medium was changed and CMK  was added to a final concentration of 100 μM if needed. Two days after transfection, CMK treatment was repeated. After 2 hr, cells were harvested. Whole cell extracts were isolated using RIPA buffer  supplemented with protease inhibitor . Isolated protein concentration was determined using Bradford assay .To observe Slit cleavage, N2a cells were seeded into 6-well plates , anti-GFP , anti-Tubulin , and anti-PC2 . Western blot quantification was performed using Image Lab4.0 software (Bio-Rad).Dorsal spinal cord tissue was dissected out from isolated spinal cord and dissociated. Neurons were grown on laminin-polylysine-coated coverslips in Neurobasal supplemented with B27, glutamine (Gibco), and Netrin-1 (R and D) medium for 24–48 hr, as in Protein diffusion quantification: The background noise was measured in ImageJ and then subtracte. The electroporated zone was then divided into two different compartments along the dorso-ventral axis. The glial cells’ apical feet and cellular bodies were included in the apical compartment. The axons path was divided in two, the most apical compartment being basal 1, the most basal compartment being basal 2. The mean intensity of Cerulean, Venus, or GFP was measured using ImageJ in each compartment. The mean intensity was then normalized by the mean intensity in the apical compartment.Pearson coefficient: The background noise was removed by measuring it, then subtracting it in ImageJ. The electroporated zone was then divided into three different compartments as mentioned previously. Each compartment was then analyzed using the JACoP plugin in ImageJ. An empirical threshold was used, and the Pearson’s coefficient calculated.All embryos that normally developed and express pHluo-vectors at the thoracic level were included in the analysis. Number of independent experiments, embryos, stacks and growth cones (n) are indicated in figures or legends. Analysis were done in blind for the quantification of phenotype in mouse embryos and the collapse assays. Sample size and statistical significances are represented in each figure and figure legend. For each set of data, normality was tested and Student's t-test or Mann–Whitney test was performed when the distribution was normal or not, respectively. Statistical tests were performed using Biosta-TGV (CNRS) and Prism six software. In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Acceptance summary:The results from this study provide a novel view on how spinal cord commissural axons -a commonly used paradigm to study mechanism of axon guidance- grow across the floor plate, a glial-like structure positioned at the ventral spinal cord midline. The study shows that a well-known axon guidance cue, SlitC, deposited on very elaborated basal end-feet of floor plate cells, constantly limits the exploration of the commissural growth cones expressing its PlexinA1 receptor. Thus, this receptor/ligand pair imposes order to axons as they cross to the contralateral side of the spinal cord. This observation rectifies the current view whereby Slits were thought to provide a repulsive signal that prevented axons to turn back after crossing.Decision letter after peer review:eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Marianne Bronner as the Senior Editor. The reviewers have opted to remain anonymous.Thank you for submitting your article "SlitC-PlexinA1 mediates iterative inhibition for orderly passage of spinal commissural axons through the floor plate" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.eLife but that some conclusions require a modest amount of additional new data, as they do with your paper, we are asking that the manuscript be revised to either limit claims to those supported by data in hand, or to explicitly state that the relevant conclusions require additional supporting data.We would like to draw your attention to changes in our revision policy that we have made in response to COVID-19 (https://elifesciences.org/articles/57162). Specifically, when editors judge that a submitted work as a whole belongs in eLife, either of which would be linked to the original paper.Our expectation is that the authors will eventually carry out the additional experiments and report on how they affect the relevant conclusions either in a preprint on bioRxiv or medRxiv, or if appropriate, as a Research Advance in Summary:This is an interesting and elegant study that takes advantage of time-lapse imaging and interference with the Slit/Plexin interaction to obtain a dynamic view of commissural axon navigation through the floor plate midline, a model that has been extensively exploited to understand core mechanisms of axon guidance. In agreement with previous studies, the authors show that commissural axons make close contacts with floor plate cells as they navigate through it. More importantly they provide an elaborate analysis of floor plate basal processes, their changes and their differential distribution of cleaved Slit fragments, showing how these prevent commissural growth cones from exploring the environment and direct axonal trajectories forward until they exit the floor plate. The authors further show that phosphorylation of PlexinA1 at Y1815 is essential for restricting exploratory growth cone behaviors.Overall, the study is solid and provides innovative ideas on growth cone navigation and receptor/ligand interactions during axon guidance with a well performed analysis. Nevertheless, there are a number of issues that need to be addressed.Essential revisions:Y1815F). However, the functioning of the mutation is insufficiently described and its effects confusing. The authors need to clarify why and how "the Y1815 mutation alters PlxnA1 cell surface pattern". Does the mutant form when overexpressed act dominantly, altering the distribution of endogenous protein? Do the PlexinA1-Y1815F/ PlexinA1-wt mice have a phenotype? Have the authors tested a PlexinA1-Y1815 Alanin mutation as a counterpart to PlexinA1-Y1815F? The effect of the Plexin mutant form is particularly important in the electroporation experiments in chick embryos where two copies of endogenous PlexinA1 are present. How do the authors explain that these electroporated chick commissural neurons show a phenotype similar to the mutant mice that only express the PlexinA1Y1815F/Y1815F form? It would be also helpful if the authors discuss potential problems in relying in their interpretations mostly on this paradigm as the mutant form could disrupt the dynamic/temporal control of receptor trafficking or signaling in general.1) The study heavy relies on the expression of a mutant form of Plexin (Plexin2) A phenotype similar to that described here was reported by Hutson and Chien, 2002, analyzing the zebrafish astray mutants. In that study, the authors proposed a role for Slit-Robo signaling in preventing and correcting pathfinding errors. These data need to be mentioned and discussed. Is the "straight growth" and dampening of exploration proposed here, similar to the restriction of error and error correction model proposed by Hutson and Chien?. Could PlxnA1-SliC signaling be playing a similar role at the floorplate to Robo-Slit signaling in the visual system? Furthermore, Slit signaling has been proposed to play a barrier function that is important for channeling axons along their correct path. How might this relate to the model being proposed here? How "radically different" is the mode of guidance being proposed here from that described already in other parts of the CNS?3) Throughout the manuscript, the authors refer to an "unexpectedly" complex mesh of ramified complex FP glial basal processes". However, there have been several previous studies of glia at the floor plate and other regions of the CNS midline using immunohistochemistry and electron microscopy. These studies have demonstrated that midline glia from a dense palisade and are highly branched and that complex interactions occur between the glial cells and axons traversing the midline . The finding reported here that the glial cell basal processes from a complex mesh of ramified processes is therefore not unexpected. While the 3D reconstructions are beautiful and add some detail to our understanding of the interactions between axons and glial cells at the CNS midline, it needs to be made clearer, particularly in the Results sections, that these analyses largely confirm previous work and what the specific advances made here are. In this respect, the complex end feet processes of midline glia might have important implications regarding ligand presentation. It would seem interesting to test conditions where end feet morphologies of the glia cells are lost. In a number of different studies people have used expression of dominant RhoA or cdc42 mutant proteins to prevent such cellular process formation. Do the authors consider it feasible to use here? Essential revisions:Y1815F). However, the functioning of the mutation is insufficiently described and its effects confusing. The authors need to clarify why and how "the Y1815 mutation alters PlxnA1 cell surface pattern". Does the mutant form when overexpressed act dominantly, altering the distribution of endogenous protein? Do the PlexinA1-Y1815F/ PlexinA1-wt mice have a phenotype? Have the authors tested a PlexinA1-Y1815 Alanin mutation as a counterpart to PlexinA1-Y1815F? The effect of the Plexin mutant form is particularly important in the electroporation experiments in chick embryos where two copies of endogenous PlexinA1 are present. How do the authors explain that these electroporated chick commissural neurons show a phenotype similar to the mutant mice that only express the PlexinA1Y1815F/Y1815F form? It would be also helpful if the authors discuss potential problems in relying in their interpretations mostly on this paradigm as the mutant form could disrupt the dynamic/temporal control of receptor trafficking or signaling in general.1) The study heavy relies on the expression of a mutant form of Plexin  behave abnormally.– First, growth cones preferentially engaging PlxnA1– Second, competition for cell surface sorting due to increased PlexinA1 receptor expression could lead to depletion of WT receptor in some growth cones.Y1815F could titrate PlxnA1WT receptor in contexts where both are expressed, by forming dysfunctional complexes.– Third, PlxnA1Y1815F/+ heterozygous embryos . They look similar to those observed in the PlexinA1Y1815F/Y1815F embryos. This indicates that the mutated PlxnA1 receptor can alter SlitC signaling in presence of the WT one. In contrast, PlxnA1+/- embryos do not exhibit recrossing phenotypes , which thus suggests that one copy of PlxnA1 might be sufficient to ensure SlitC-PlxnA1 signaling. This weakens the relevance of the model of depletion by competition for sorting; leaving more plausible hypotheses 1 and 3. Addressing these models is difficult because we have no ways of distinguishing PlxnA1WT and PlexinA1Y1815F receptors in the mouse model as they are both recognized by anti-PlexinA1 antibodies, in western blot and in immunohistochemistry. In the chicken, PlxnA1 antibodies that we tested recognized both chick and mouse PlxnA1, and we thus cannot specifically assess the expression of the endogenous receptor. Nevertheless, we attempted to get some more information using the chicken embryo model. We made an in vivo competition assay by diluting the dose of electroporated pHLuo-PlxnA1WT with either PlxnA1WT or PlxnA1Y1815F (using non-fluorescent receptors forms) and we compared the cell surface distribution of pHluo-PlxnA1WT in commissural axons navigating the FP. We observed a similar enrichment of the pHluo-PlxnA1WT in the growth cone compartment, compared to the adjacent axon segments. This indicates that co-expression with PlxnA1Y1815F does not affect the compartmentalization of pHluo-PlxnA1WT. Nevertheless, it did not exclude the possibility that PlxnA1Y1815F titrates PlxnA1WT if both receptors dimerize, which would result in depleting the growth cones of the PlxnA1 receptors that are normally able to transduce SlitC signal. We thus quantified the pHluo signal in the growth cones and found no significant differences in the presence or absence of the mutated receptor. Thus, these experiments support a model whereby PlxnA1Y1815 has a direct contribution to the altered growth cone behaviors, even in the presence of the PlxnA1WT receptor. These data are presented in Figure 3—figure supplement 1, subsection “The temporal and spatial pattern of PlxnA1 membrane insertion during commissural axon navigation is impacted by the Y1815 mutation” and discussed in the subsection “Tyrosine mutation alters the membrane mobility of PlxnA1 receptor”.We can discuss these hypotheses in light of the phenotypes observed in our mouse model. We do see recrossing phenotypes in the PlxnA1We did not engineer a PlxnA1 with Y1815 Alanin mutation. We thought that the fact that the Y1815F mutation only altered SlitC but not Sema3B responses was a good internal control of the substitution.2) A phenotype similar to that described here was reported by Hutson and Chien, 2002, analyzing the zebrafish astray mutants. In that study, the authors proposed a role for Slit-Robo signaling in preventing and correcting pathfinding errors. These data need to be mentioned and discussed. Is the "straight growth" and dampening of exploration proposed here, similar to the restriction of error and error correction model proposed by Hutson and Chien?. Could PlxnA1-SliC signaling be playing a similar role at the floorplate to Robo-Slit signaling in the visual system? Furthermore, Slit signaling has been proposed to play a barrier function that is important for channeling axons along their correct path. How might this relate to the model being proposed here? How "radically different" is the mode of guidance being proposed here from that described already in other parts of the CNS?We thank the reviewers for this comment and indeed we apologize for having missed the cited study. After reading, we fully agree that our findings must be discussed in light of this study, which reported in the context of retinal axon navigation observations than echo ours. Astray retinal growth cones are observed to be more complex and less streamlined than WT ones, deviating their trajectory from the normal path, already prior to reaching the midline, which correlates with Slit expression patterns framing the navigation path. Robo2-Slit might thus maintain retinal growth cones straight on their way towards and after midline crossing, as we propose PlxnA1-SlitC does so in the context of the floor plate navigation.We have now included a paragraph discussing this work in the subsection “Is PlxnA1-SlitC signaling the only player of the guidance program ensuring straight trajectory across the FP?”.3) Throughout the manuscript, the authors refer to an "unexpectedly" complex mesh of ramified complex FP glial basal processes". However, there have been several previous studies of glia at the floor plate and other regions of the CNS midline using immunohistochemistry and electron microscopy. These studies have demonstrated that midline glia from a dense palisade and are highly branched and that complex interactions occur between the glial cells and axons traversing the midline . The finding reported here that the glial cell basal processes from a complex mesh of ramified processes is therefore not unexpected. While the 3D reconstructions are beautiful and add some detail to our understanding of the interactions between axons and glial cells at the CNS midline, it needs to be made clearer, particularly in the Results sections, that these analyses largely confirm previous work and what the specific advances made here are. In this respect, the complex end feet processes of midline glia might have important implications regarding ligand presentation. It would seem interesting to test conditions where end feet morphologies of the glia cells are lost. In a number of different studies people have used expression of dominant RhoA or cdc42 mutant proteins to prevent such cellular process formation. Do the authors consider it feasible to use here?We fully agree that previous studies reported that commissural axons navigate within the network of basal processes of the floor plate glia cells. Our claim of “unexpectedly complex mesh of ramified process” was in fact referring to the multiple ramifications of the basal process, the particular asymmetric morphologies these cells have, and how they are arranged in 3D in the tissue, which were not reported so far. We modified the manuscript according to the suggestions, adding sentences to make it clearer what our observations bring to the known background, Results section and Discussion. We also extended the literature in this paragraph, citing previous studies reporting glia cell specializations and their contribution to axon guidance. We toned down the novelty of the findings in the manuscript and Abstract, removing “novel” at several places.We fully agree that manipulating the morphology of the FP cells would be very interesting to examine whether it modifies the ligands distribution and alters commissural axon navigation. The consequences of Rho ablation in the developing spinal cord have been examined using a conditional line with specific ablation of RhoA in neural progenitors. The study showed that it essentially altered the apical polarity of the progenitors, disrupting adherens junctions. In contrast, the basal polarity was reported to be unaffected . In another study, a dominant negative RhoA was electroporated in the chick neuroepithelium. The major reported consequence was an alteration of the division angle of neural progenitors at the apical side . It seems difficult from this literature to predict that altering RhoA would result in a disruption of FP glia basal processes, and we feel that addressing this point in the context of revisions would take a long time because of the technical challenges it represents.Beyond the experimental difficulty to reach the objective, the observations would be difficult to interpret because altering the basal process would not only impact the distribution of the ligands but would also change the physical properties of the navigation path that may also account for proper navigation.


Formation of temporal association memory and context-specific fear memory is thought to require medial entorhinal cortex (MEC) inputs to the hippocampus during learning events. However, whether the MEC inputs are also involved in memory formation during a post-learning period has not been directly tested yet. To examine this possibility, we optogenetically inhibited axons and terminals originating from bilateral dorsal MEC excitatory neurons in the dorsal hippocampus for 5 min right after contextual fear conditioning (CFC). Mice expressing eNpHR3.0 exhibited significantly less freezing compared to control mice expressing EGFP alone during retrieval test in the conditioned context 1 day after learning. In contrast, the same optogenetic inhibition of MEC inputs performed 30 min before retrieval test did not affect freezing during retrieval test, excluding the possibility of non-specific deleterious effect of optical inhibition on retrieval process. These results support that contextual fear memory formation requires MEC inputs to the hippocampus during a post-learning period. The hippocampus-entorhinal cortex system is crucial for episodic memory formation . EvidencTo test whether MEC input to hippocampus is necessary during post-learning period, we adopted an optogenetic approach to silence MEC input activity in 129/C57Bl/6 hybrid mice , 12. To Though majority of MEC afferent targets hippocampus, MEC is known to send projections to medial prefrontal cortical areas such as prelimbic and infralimbic cortex . Since AOne limitation in this study is the lack of spatial specificity in used optical inhibition. Thus, it is unclear to what extent and exactly where within the hippocampal circuit the widespread MEC inputs were suppressed with the optical inhibition in our condition. Precise inhibition of MEC inputs targeting a specific subfield such as CA1 or DG of hippocampus might be necessary to elucidate the mechanism by which MEC inputs contribute to formation of contextual fear memory in the future study.Although we did not test the effect of optical inhibition of MEC inputs to the hippocampus at different time points after contextual fear conditioning in this study, previous studies report a time-dependent role of post-learning brain activities for consolidation of hippocampus-dependent memories like contextual fear conditioning. For instance, using an optogenetic strategy, a prior study artificially manipulated the induction of slow-wave sleep (SWS) at different time points following different learning tasks and it appeared that there is a critical time-window (within 30 min) during which SWS induced by light can improve hippocampal-dependent memories . InteresIt is interesting in our study that such a short period (5 min) of post-training optogenetic inhibition was enough to impair context memory formation. One interpretation is that our results may reflect a partial block of consolidation events that are required for normal memory formation. Consistent with this account, memory was partially impaired in our condition. Another possibility is that there might be a critical event occurring during this brief time point required for formation of contextual fear memory. One possibility is that MEC input may be crucial for triggering ripples or dentate spikes in the hippocampus that are correlated with replay of previously experienced events , 10, 16 Additional file 1: Fig. S1. Histological verification of optic fiber position in hippocampus. Fig. S2. Microscopic images of retrogradely-labeled MEC input to hippocampus.


Root hairs play important roles for the acquisition of nutrients, microbe interaction and plant anchorage. In addition, root hairs provide an excellent model system to study cell patterning, differentiation and growth. Arabidopsis root hairs have been thoroughly studied to understand how plants regulate cell fate and growth in response to environmental signals. Accumulating evidence suggests that a multi-layered gene regulatory network is the molecular secret to enable the flexible and adequate response to multiple signals. In this review, we describe the key transcriptional regulators controlling cell fate and/or cell growth of root hairs. We also discuss how plants integrate phytohormonal and environmental signals, such as auxin, ethylene and phosphate availability, and modulate the level of these transcriptional regulators to tune root hair development. Root hairs form by tube-like outgrowth of root epidermal cells and they contribute to efficient acquisition of nutrients, microbe interactions and plant anchorage by expanding root surface area. Since root hair development is strongly influenced by surrounding conditions, this regulation is thought to be one of the important mechanisms of environmental adaptation in plants. Indeed, multiple environmental factors, such as availability of phosphorus, nitrogen, iron, magnesium and zinc, as well as phytohormones such as auxin, ethylene and abscisic acid (ABA) alter both cell fate and growth of root hairs Figs. , 2 Grie. Root haDuring early root development, epidermal cells differentiate into either trichoblasts, i.e., root hair-forming cells or atrichoblasts, i.e., non-hair forming cells. In general, plants develop root hairs in one of the following three patterns  which functions as a negative regulator of root hair formation  and TTG1. In addition, TRIPTYCON (TRY)  which plays key roles in the determination of root hair identity   genes that are predominantly expressed in root hairs  and RSL4 binds this sequence to promote their expression in root hairs. Some RHS proteins, as well as other indirect targets of RSL4, are implicated in cell wall biogenesis and remodeling, ROS production or vesicle trafficking  promote transcription of genes encoding other bHLH transcription factors RSL2, RSL4 and Lotus japonicus ROOTHAIRLESS-LIKE 3 (LRL3) Fig. . Among trsl2 single mutation causes shorter root hairs and the rsl2 rsl4 double mutation results in complete hairlessness  was initially isolated as a repressor of trichome cell growth  is characterized as a negative regulator of root hair growth since induction of wth Fig. a. OBP4 iwth Fig.  and we wRHD6, RSL1, RSL2, LRL1 and LRL2 to prevent ectopic outgrowth of root hairs , transport inhibitor response 1 (tir1) and auxin resistant 1 (axr1-3) cause hairless or short hair phenotypes, clearly showing that auxin is essential for root hair formation  also participates in the regulation of ethylene-dependent root hair growth. Intriguingly, the ZFP5 expression is elevated by cytokinin and the zfp5-4 mutant is insensitive to cytokinin for the hair growth phenotype (An et al. CPC expression (An et al. CPC. Since ZFP5 does not affect root hair fate, it is also possible that ZFP5 regulates other factors that play more specific roles in hair growth.Cytokinin promotes root hair elongation and this regulation is independent from auxin or ethylene (Zhang et al. OBP4, which subsequently represses root hair growth (Rymen et al. RSL2 expression. Thus, OBP4 inhibits root hair growth through RSL2 in response to ABA (Rymen et al. ABA has a negative effect on root hair growth (Schnall and Quatrano phr1 phl1 double mutants are insensitive to Pi starvation since they do not show enhancement of root hair development under Pi limiting conditions (Bustos et al. PHR1 has much longer root hairs than those of wild type under Pi starvation condition (Bustos et al. PHR1 expression does not strongly respond to Pi status (Rubio et al. PHR1 expression in roots (Huang et al. Pi availability strongly influences root hair growth Fig. . RegardiETC1 expression (Chandrika et al. ETC1. Another potential regulator is WRKY75 which is upregulated in response to Pi starvation (Devaiah et al. CPC expression (Devaiah et al. Pi deficiency, in addition, affects fate of root hair cells and most likely ethylene, induced by Pi starvation, causes ectopic root hair formation. It is shown that Pi starvation increases the levels of the EIN3 protein which can promote root hair growth by direct transcriptional enhancement of root hair specific genes (Song et al. bhlh32 mutant does not inhibit root hair growth under high Pi condition and this phenotype is accompanied by up-regulation of several Pi starvation-induced genes (Chen et al. How plants transduce high Pi stress is less understood but bHLH32 suppresses root hair development to reduce Pi uptake (Chen et al. While Pi response has mostly been studied using high or low Pi medium, a new study was conducted using a micro-device, called Dual-flow-RootChip, that allows flow of different liquids on two sides of roots (Stanley et al. RSL4 expression under the changing environment. Although many core regulators of root hair development have been identified (Table In this review we highlighted the key transcriptional regulations that link developmental and/or environmental inputs to root hair identity and growth. Various exogenous cues affect root hair growth and it is becoming increasingly evident that many of these upstream cues are integrated to auxin- or ethylene-mediated signaling pathways. Central regulators acting downstream of these signaling cascades are the two bHLH transcription factors RSL2 and RSL4 that function as a hub to regulate root hair growth in response to environmental signals. For cell fate specification, two MYB transcription factors CPC and ETC1 appear to function as a hub to integrate environmental and developmental cues. Another emerging characteristic of the root hair gene regulatory network is the intimate transcriptional interaction between these positive root hair regulators and negative regulators such as GTL1 and OBP4. In particular, GTL1 and RSL4 form a mutually regulating transcriptional module, and we predict that GTL1 functions as a stabilizer in this module to minimize the fluctuation of