Vangl2, exhibit increased perpendicular divisions and hyperthickened epidermis. Surprisingly, this is not due to defective Vangl2 function in the epidermis, but to changes in cell geometry and packing that arise from the open neural tube characteristic of PCP mutants. Through regional variations in epidermal deformation and physical manipulations, we show that local tissue architecture, rather than cortical PCP cues, regulates the decision between symmetric and stratifying divisions, allowing flexibility for basal cells to adapt to the needs of the developing tissue.The control of cell fate through oriented cell division is imperative for proper organ development. Basal epidermal progenitor cells divide parallel or perpendicular to the basement membrane to self-renew or produce differentiated stratified layers, but the mechanisms regulating the choice between division orientations are unknown. Using time-lapse imaging to follow divisions and fates of basal progenitors, we find that mouse embryos defective for the planar cell polarity (PCP) gene,  Oriented cell division is a fundamental mechanism through which multicellular organisms build complex tissue architecture . By contThe murine epidermis is a well-studied model to investigate the regulation of spindle orientation during development. The formation of the skin’s stratified layers, which serve as a barrier to protect the organism from its external environment, relies on oriented cell divisions. Unlike simple epithelia, which divide exclusively within the epithelial plane, cells of the innermost, basal layer of the epidermis divide in both planar and perpendicular orientations . PerpendDuring embryonic development, the epidermis transforms from a single layer of basal progenitors at E12.5 to a stratified and differentiated epithelium with barrier function by E17.5 . StratifVangl2 gene ; Vangl2) display increased epidermal thickness, suggesting a role for PCP in planar division orientations , which controls polarization along an epithelial plane . In the ntations . HoweverUsing live imaging to trace the orientation and positional fate of basal cell divisions, we investigate the function of PCP and tissue mechanics early in epidermal stratification. In agreement with the hypothesis that PCP promotes planar basal cell divisions, we find that Vangl2 mutant embryos display an increased proportion of stratifying divisions at the expense of planar divisions. Unexpectedly, this is not a direct result of defective PCP; rather, we show that failure of the epidermis to close over the neural tube in these mutants leads to cell crowding within the basal layer, concomitant with changes in cell width and height and a higher frequency of asymmetric cell divisions. Combining our live imaging approach with tissue-specific genetic perturbations and mechanical tissue manipulations, we show that early in epidermal development, interphase 3D cell geometry and packing, rather than cortical PCP cues, influence mitotic spindle orientation. Although it is well established that cell divisions align with the interphase long axis in two dimensions, our data show that this mechanism can also impact spindle alignment in the third, apical-basal dimension in a stratifying epithelium. We propose that by responding to changes in cell density and shape, basal cell division orientations can adjust to satisfy the needs of the tissue.The relationship between division orientation and epidermal stratification has been primarily inferred from observations made in fixed tissue sections. This method comes with some key disadvantages: it excludes divisions oriented orthogonal to the plane of sectioning and does not allow one to directly correlate mitotic spindle alignment with the final positions of daughter cells. To overcome these limitations, we performed time-lapse imaging of live, flat mounted skin explants expressing a nuclear marker, K14-H2B-GFP , which aLp/LpVangl2 mutants (27 ± 4% planar divisions), which exhibited an increased frequency of oblique and perpendicular divisions . However, this proportion was reduced in explants from ivisions . Importaivisions . The altTo explore trends in cell division orientation over developmental time, we quantified division planes in fixed whole mount skins across multiple time points from E13.5-E16.5 . ConsistLp/LpVangl2 embryos, however, the relationship between division orientation and final position was shifted toward asymmetric. Only 78% of planar divisions and 21% of oblique divisions resulted in symmetric positional fates  was slightly increased compared to WTVangl2 (41.1% of divisions), this increase is not sufficient to explain the altered division orientations   . However embryos . Thus, twildtype , perhapsAfter observing this tissue-wide correlation between 3D cell geometry and cell division orientations, we wanted to more directly assess this relationship on a per-cell basis. We therefore performed live-imaging of E14.5 skin explants expressing either a membrane-GFP or membrane-tdTomato marker , which aLp/LpVangl2 embryos could be directly or indirectly influenced by PCP function. As planar cell polarity components are highly expressed in the basal layer, they could have a direct role in regulating basal cell shape. Alternatively, changes in epidermal cell shape could arise as a secondary consequence of the open neural tube phenotype characteristic of several PCP mutants  , and cell density was unchanged  . These e,2 dcKO)  and hair,2 dcKO) . Neverthnchanged . Moreovecontrols , suggestWe also quantified division planes and cell geometries in embryos lacking Frizzled-6, which display strong planar cell polarity defects in the skin , but comΔTm/LpVangl2 mutants, basal epidermal cells of ΔTm/LpK14-Vangl2-GFP; Vangl2 embryos had decreased cross-sectional areas, were taller than WTK14-Vangl2-GFP; Vangl2 control littermates, and packed more densely into the basal layer  and a decrease in cell density  and reduced cell heights as compared to unstretched controls   .ΔTm/LpVangl2 embryos and promote planar divisions in wildtype explants through uniaxial stretch demonstrates that basal cells are able to integrate tissue dynamics with cell division orientation to respond to and influence tissue architecture.We next investigated the effect of stretch on wildtype explants to test whether basal cells can dynamically reorient division planes in response to changes in cell geometry. Instead of stretching E14.5 explants when divisions already occur in primarily planar orientations, we utilized E15.5 explants, which undergo increased oblique and perpendicular divisions relative to earlier developmental stages. When E15.5 explants were stretched over the course of 1 hr, basal cells became elongated along the axis of strain and divisions were shifted toward planar division orientations compared to unstretched controls . The abiBy live imaging of the developing epidermis, we have shown that the orientation of cell division within the skin’s basal progenitor layer is closely linked to the positional fate of daughter cells. Basal cells dividing with telophase angles greater than 45 degrees of the basement membrane will have asymmetric fates, whereas division angles less than 45 degrees will generate daughters with symmetric fates. Although this has been assumed to be true based on division planes in fixed tissue sections, these data show directly that during early phases of epidermal stratification, the angle between telophase daughter cells is a strong indicator of the final positions and fates of the two daughters. We also found, through investigation of the hyperstratification defect of a well-studied PCP mutant, that during early stratification stages, the orientation of cell division is influenced by cell shape and packing rather than cortical PCP cues or LGN localization. Basal cells that are taller along the apical-basal axis are biased towards perpendicular divisions, while flatter and wider cells tend to divide parallel to the epithelial plane. Crowding within the epithelium, a consequence that is likely due to a failure of the skin to stretch and cover the midline in PCP mutants, is associated with increased asymmetric divisions, while stretching the epithelium promotes planar divisions and expansion of the progenitor layer. These findings show that embryonic basal epidermal cells are flexible to adjust their divisions, at the level of spindle orientation, in response to changes in the tissue environment. We propose that under normal developmental conditions, this mechanism enables expansion of the progenitor layer to accommodate embryo growth while also allowing for the generation of new layers when the basal layer has reached sufficient density.Based on these observations, we propose an updated model for epidermal stratification. The epidermis begins as a single layer of progenitor cells that divide almost exclusively within the plane of the tissue, until increases in cell density and height:width ratio promote stratification through oblique/perpendicular divisions. Epithelial stretch or tension, such as that exerted on the skin by embryo growth or morphogenetic changes like neural tube closure, delays stratification, while crowding of the basal layer promotes its occurrence. These cues of stretch and crowding provide an effective way to balance basal cell division orientations and ensure proper tissue structure early in epidermal development. Notably, other studies using Cre recombinase-based lineage tracing or live imaging without a nuclear marker have suggested that stratification at this early stage is driven primarily by delamination . By contLate in embryonic development, there is a developmental shift toward generating more skin layers, as forming an effective barrier from the exterior environment becomes imperative. To facilitate this change in tissue architecture, apical mInsc polarization promotes perpendicular spindle orientations and formation of a stratified barrier . During Drosophila follicular epithelium and the chick neuroepithelium, planar spindle orientation depends on the LGN/Pins-NuMA/Mud complex, which anchors astral microtubules to the lateral cell cortex through the polarity factor Dlg  lines generated extremely high frequencies of hermaphrodites, severely limiting the availability of female animals. Therefore, females of the genotype LpVangl2 or ΔTm,Vangl2 a targeted deletion of the second transmembrane domain, were used for experiments (see Key Resources Table).All procedures involving animals were approved by Princeton University’s Institutional Animal Care and Use Committee (IACUC). Mice were housed in an AAALAC-accredited facility in accordance with the Guide for the Care and Use of Laboratory Animals. This study was compliant with all relevant ethical regulations regarding animal research. E13.5-E16.5 embryos from C57BL/6 backgrounds were used unless otherwise indicated. Both sexes were used, as sex was not determined in embryos. Mouse lines harboring the spontaneous For immunostaining, embryos were dissected in PBS and fixed in 4% paraformaldehyde. E13.5 and E14.5 embryos and embryonic explants were fixed at room temperature for 1 hr, and E15.5 and E16.5 embryos and embryonic explants were fixed at room temperature for 1.5 hr. Skins stained with anti-LGN antibodies were processed as follows: skins were dissected from fixed embryos and blocked overnight at 4°C in 2% fish skin gelatin, 1% bovine serum albumin, 2% normal donkey serum, and/or 2% normal goat serum in PBT (1X PBS with 0.2% or 0.3% Triton X-100). Skins were incubated in primary antibodies diluted in block for 24 hr at 4°C. Skins were washed with 0.2–0.3% PBT overnight, incubated with secondary antibodies for 24 hr at 4°C followed by Hoechst. All other skins were blocked for 1 hr at RT in 1% BSA, 2% NDS and/or 2% NGS then incubated in primary antibodies diluted in block overnight at 4°C. After washing with 0.2–0.3% PBT, skins were incubated in secondary antibodies followed by Hoechst. Samples were mounted in either glycerol-based anti-fade non-curing medium or Vectashield Antifade mounting medium. The following primary antibodies were used: rabbit anti-involucrin , guinea pig anti-Celsr1 , rat anti-E-Cadherin , rat anti-E-Cadherin , guinea pig anti-LGN , rabbit anti-LGN , rat anti-Vangl2 . Alexa Fluor-488,–555, −647 secondary antibodies were used at 1:2000. Hoechst  was used at 1:1000 (1 mg/mL). Images were acquired on a Nikon Ti-E Spinning Disc or A1 scanning confocal microscope controlled by NIS Elements software using a Plan Fluor 40X/1.3NA, Plan Apo 60X/1.4NA, or Plan Apo 100X/1.45 oil immersion objective. NIS elements software and Photoshop were used for image processing.A portion of live imaging for 2 during the course of imaging. In all live imaging experiments, cells close to the edge of the explants were not imaged to avoid differences in division orientations that could be induced by a wound healing response. NIS Elements software was used for movie processing.For all the other movies: E14.5 dorsal flank skin explants were dissected in PBS and transferred to a 1% agarose gel with F-media containing 10% fetal bovine serum. Explants were sandwiched between the gel on the dermal side and a 35 mm Lumox membrane dish (Sarstedt) on the epidermal side. Z-stacks with 0.5 or one micron step sizes were acquired at 10 min intervals for 8–18 hr. Images were acquired using a Nikon Ti-E Spinning Disc with a Plan Fluor 40X/1.3NA oil objective. Explants were cultured in a humid imaging chamber at 37°C with 5% COA custom-designed stretch chamber  was consDivision angle in both live and fixed imaging was determined by drawing a line connecting the two daughter nuclei during telophase or cytokinesis (using either Volocity or NIS Elements software). Skin thickness was quantified using fixed sagittal tissue sections or whole mount skins and by measuring the area of skin in an image, normalized to length. For whole mount images, area and length were measured in YZ views. Cell heights were measured using membrane signal  and XZ views of images with either 0.2 μm or 0.5 μm Z-step sizes in NIS Elements software to determine the distance from the apical surface of the cell to the basement membrane. Cell surface area was calculated using Packing Analyzer V2 software. Images were imported into the software and cells were segmented using a membrane signal, with any necessary hand corrections. Surface areas were calculated using the software’s watershed formula .Circular statistics: to compare rose plots of division angles, p values were calculated from the non-parametric Kuiper’s test to compare distributions along a circle. This test was modified to account for data limited to 0–90° range, and p values were calculated using Matlab. All other statistical analyses were performed in Prism. In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.eLife. Your article has been reviewed by Marianne Bronner as the Senior Editor, a Reviewing Editor, and two reviewers. The following individuals involved in review of your submission have agreed to reveal their identity: Yukiko M Yamashita (Reviewer #1); Yohanns Bellaïche (Reviewer #3).Thank you for submitting your article "Epithelial geometry regulates spindle orientation and progenitor fate during formation of the mammalian epidermis" 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.Summary:This study by Box et al., studies the role of PCP protein Vangl2 in division orientation of basal progenitor cells  in mouse. Overall, the conclusions (summarized below) are supported well, and the study represents important description on spindle orientation and tissue morphogenesis, including the descriptions that correct notions that might have been assumed based on previous studies. This study is the first to provide much clear-cut correlation between the spindle orientation and the fate of daughter cells. They also made an important observation that contrasts to the previous studies that suggested delamination of basal progenitor cells as a mechanism of differentiation.Essential revisions:-Comparing Figure 4I and 4J, one interesting analysis may be whether wt vs. Vangl2 mutant cells have similar height-width ratio in deciding which direction they divide. Namely, Vangl2 mutation only affects height-width ratio, and all spindle orientation phenotype is purely explained by changed height-width ratio. Alternatively, Vangl2 might possibly affecting additional aspect(s) of spindle orientation other than height-width ratio? By eye-balling Figure 4I and 4J, it looks like there is differences between wt vs. mutant for the same category of spindle orientation.-Can they explain why the previous studies proposed delamination? I am wondering the studies relied on fixed samples? If so, is it possible that maybe some daughter cells are coming back to adhere basal layer? (opposite of delamination?)Vangl2Lp/155 Lp embryos, however, the relationship between division orientation and final position was shifted toward asymmetric. Only 78% of planar divisions, and 21% of oblique divisions resulted in symmetric positional fates .". The distribution shown in the Figure 2A seems similar. The distribution difference in the Figure 2B could be due to the binning in planar, oblique, orthogonal divisions. To strengthen this statement, the authors should test whether the angular distributions of the different bins are identical.Subsection “Division plane is a strong predictor of the positional fate of daughter cells”: The following statement might be incorrect: "Results section/Discussion section: In the Results section or the Discussion section, it would be relevant to discuss the difference between this study and the ones reporting stratification by delamination.Subsection “Division plane is a strong predictor of the positional fate of daughter cells”: The authors should clarify what is novel in the analysis of the epithelium thickness in Vangl2 mutant embryos.Figure 3: "LGN Mislocalized" sounds inappropriate. An absence of correlation between LGN localization and a specific orientation does not indicate that LGN is mis-localised.WTVangl2(41.1% of divisions) to explain the altered division orientations " is awkward since the frequency is decreased. The subsequent sentence is incorrect, the conclusion should be made on Vangl2 and not LGN.Subsection “Early in epidermal development, LGN localization does not correlate with planar spindle positioning”: This sentence: "However, the occurrence of apical LGN (47.7% of divisions) was not sufficiently increased compared to Subsection “Cell division orientation is correlated with basal cell geometry”: "but this has been shown mainly in cells dividing within a two-dimensional plane ." This is an overstatement. Xiong et al., (2014) have analysed the role of 3D cell shape. This work needs to be cited and discussed.Lp/LpVangl2embryos were packed more densely into the basal layer compared to wildtype (258 cells vs 215 cells per 1200μm2 field of view) , but this increase in cell density was not due to elevated proliferation .". Small difference in the proliferation rate can have a substantial impact on cell numbers at long time scale. Please reformulate.Subsection “Cell division orientation is correlated with basal cell geometry”: "Basal cells in Subsection “Cell division orientation is correlated with basal cell geometry”: "We also observed a modest but significant relationship between division plane and height:width aspect ratio along the apical-basal axis, wherein cells that divided in a planar orientation tended to have smaller height:width ratios (average = 0.8307) compared to cells that divided perpendicularly (average height:width ratios = 1.275) . This relationship was also observed in Vangl2 mutant embryos , where perpendicular divisions were associated with larger height:width ratios". The authors need to plot cell division orientation versus height: width ratio to substantiate this conclusion.Subsection “Spatial differences in epithelial packing and shape correlate with cell division orientations and the timing of stratification”: Are the orientation distributions statistically different in the lateral, intermediate and midline regions?Subsection “Spatial differences in epithelial packing and shape correlate with cell division orientations and the timing of stratification”: "Thus, coverage of the epidermis over the spinal cord induces a gradient of cell density and elongation along the mediolateral axis, which in turn regulates cell division planes and the timing of stratification." Please weaken this conclusion.Subsection “Exogenous stretching of skin explants increases the frequency of planar cell divisions”: The 14.5 control and stretched conditions should be done in wt conditions. Accordingly, the conclusion at the end of the Results section is incorrect. The authors can only make this conclusion in a Vangl2 mutant conditions. Summary:This study by Box et al., studies the role of PCP protein Vangl2 in division orientation of basal progenitor cells  in mouse. Overall, the conclusions (summarized below) are supported well, and the study represents important description on spindle orientation and tissue morphogenesis, including the descriptions that correct notions that might have been assumed based on previous studies. This study is the first to provide much clear-cut correlation between the spindle orientation and the fate of daughter cells. They also made an important observation that contrasts to the previous studies that suggested delamination of basal progenitor cells as a mechanism of differentiation.We thank the reviewers for their careful reading of our manuscript and their helpful suggestions. We have addressed each of their comments and concerns and provide a point-by-point response below.Essential revisions:-Comparing Figure 4I and 4J, one interesting analysis may be whether wt vs. Vangl2 mutant cells have similar height-width ratio in deciding which direction they divide. Namely, Vangl2 mutation only affects height-width ratio, and all spindle orientation phenotype is purely explained by changed height-width ratio. Alternatively, Vangl2 might possibly affecting additional aspect(s) of spindle orientation other than height-width ratio? By eyeballing Figure 4I and 4J, it looks like there is differences between wt vs. mutant for the same category of spindle orientation.Lp/LpVangl2mutant, but this difference was not significant , but this could perhaps be due to the low sample size within each bin. Thus, I don’t think we can conclude with our data set whether Vangl2 affects the spindle by variables other than shape.For this analysis, we plotted the proportion of cells dividing in each directional category binned by their H/W ratios shown in . It does-Can they explain why the previous studies proposed delamination? I am wondering the studies relied on fixed samples? If so, is it possible that maybe some daughter cells are coming back to adhere basal layer? (opposite of delamination?)In Williams et al., 2014, lineage tracing of basal cell clones was performed by injecting lentivirus expressing CreER into Brainbow transgenic lines. One, two and three cell clones were analyzed in fixed skin samples. 50% of labeled cells were found in the first suprabasal layer with no associated basal cell, and were scored as delamination events. It’s possible that the viral infection itself promotes delamination if it affects basal cell fitness. In Miroshnikova et al., 2018, some live imaging was performed on life-Act expressing embryos lacking a nuclear marker. To our eyes, the example provided resembles what we see when a cell divides in a perpendicular orientation when visualized with a membrane marker . These differences are discussed in more detail in the Discussion section of the manuscript.Subsection “Division plane is a strong predictor of the positional fate of daughter cells”: The following statement might be incorrect: "Vangl2Lp/155 Lp embryos, however, the relationship between division orientation and final position was shifted toward asymmetric. Only 78% of planar divisions, and 21% of oblique divisions resulted in symmetric positional fates .". The distribution shown in the Figure 2A seems similar. The distribution difference in the Figure 2B could be due to the binning in planar, oblique, orthogonal divisions. To strengthen this statement, the authors should test whether the angular distributions of the different bins are identical.Lp/LpVangl2embryos to be even greater, suggesting our results aren’t artifacts of how we binned division planes. We decided to keep the original binning of these data and preserve the original language used in the text. We also provide a comparison of the data binned in different ways in To test whether the way we binned division categories affected our conclusion , we binned the data in a different way (in 30 degree bins) and found the bias toward asymmetric fates in Results section/Discussion section: In the Results section or the Discussion section, it would be relevant to discuss the difference between this study and the ones reporting stratification by delamination.The differences between our study and those reporting delamination are now discussed in more detail in the Discussion section of the manuscript.Subsection “Division plane is a strong predictor of the positional fate of daughter cells”: The authors should clarify what is novel in the analysis of the epithelium thickness in Vangl2 mutant embryos.Lp/LpVangl2 mutants had thicker skin at E18.5, and images where this difference is apparent can be found in Devenport et al., 2008, we never explicitly mentioned the phenotype in prior publications. Here we quantify the increase in skin thickness for the first time and characterize how and when it emerges over the course of skin development. The novelty of these findings is now explained more clearly in the introduction and in the Results section accompanying Figure 2.Although we had previously noted that Figure 3: "LGN Mislocalized" sounds inappropriate. An absence of correlation between LGN localization and a specific orientation does not indicate that LGN is mis-localised.We now refer to this population as ‘Not correlated’.WT (41.1% of divisions) to explain the altered division orientations " is awkward since the frequency is decreased. The subsequent sentence is incorrect, the conclusion should be made on Vangl and not LGN.Subsection “Early in epidermal development, LGN localization does not correlate with planar spindle positioning”: This sentence: "However, the occurrence of apical LGN (47.7% of divisions) was not sufficiently increased compared to Vangl2Lp/LpVangl2 embryos (47.7% of divisions) was slightly increased compared to WTVangl2(41.1% of divisions), this increase is not sufficient to explain the altered division orientations , suggesting that Vangl2 does not act through LGN to orient divisions. Together, these data are consistent with a potential role for Vangl2 in an alternative mechanism that influences division planes during the early phase of epidermal stratification.”We have rephrased this result and conclusion as follows, “Although the occurrence of apical LGN in Subsection “Cell division orientation is correlated with basal cell geometry”: "but this has been shown mainly in cells dividing within a two-dimensional plane ." This is an overstatement. Xiong et al., (2014) have analysed the role of 3D cell shape. This work needs to be cited and discussed.Xenopus and zebrafish embryos have been shown to divide according to a three-dimensional long-axis rule .”Although we had cited these two studies, we now discuss Xiong et al., 2014 and Chalmers et al., 2003 more explicitly in the text. “Hertwig’s rule, also known as the ‘long axis rule’, states that a cell is most likely to divide along its longest interphase axis, and has been observed in many cell types dividing within a two-dimensional plane . In the epidermis, where basal cells divide in three-dimensional space, a cell’s longest axis may lie perpendicular to the epithelial plane, which could promote perpendicular spindle alignment and asymmetric division. Indeed, the perpendicular divisions of early Lp/Lp embryos were packed more densely into the basal layer compared to wildtype (258 cells vs 215 cells per 1200μm2 field of view) , but this increase in cell density was not due to elevated proliferation .". Small difference in the proliferation rate can have a substantial impact on cell numbers at long time scale. Please reformulate.Subsection “Cell division orientation is correlated with basal cell geometry”: "Basal cells in Vangl2Lp/LpVangl2 embryos were packed more densely into the basal layer compared to wildtype (258 cells vs 215 cells per 1200μm2 field of view) . However, we did not detect elevated proliferation in Lp/LpVangl2 embryos .We have softened this statement, which now reads “Basal cells in Subsection “Cell division orientation is correlated with basal cell geometry”: "We also observed a modest but significant relationship between division plane and height:width aspect ratio along the apical-basal axis, wherein cells that divided in a planar orientation tended to have smaller height:width ratios (average = 0.8307) compared to cells that divided perpendicularly (average height:width ratios = 1.275) . This relationship was also observed in Vangl2 mutant embryos , where perpendicular divisions were associated with larger height:width ratios". The authors need to plot cell division orientation versus height: width ratio to substantiate this conclusion.Lp/LpVangl2embryos. The plots show a positive correlation between H:W ratio and division angle (0-90 degree) for both genotypes (correlation coefficient r=0.62 for wt and r=0.57 for Lp/LpVangl2).We have added Figure 4—Figure supplement 2 showing cell division orientation vs H:W ratio for wild type and Subsection “Spatial differences in epithelial packing and shape correlate with cell division orientations and the timing of stratification”: Are the orientation distributions statistically different in the lateral, intermediate and midline regions?Lp/LpVangl2mutants, they are not. These data are now reported in Figure 7, Figure 7—figure supplement 1, and in their accompanying legends.They are. We now include a statistical analysis of orientation distributions between different skin regions and find that in WT all three regions are significantly different but in the Subsection “Spatial differences in epithelial packing and shape correlate with cell division orientations and the timing of stratification”: "Thus, coverage of the epidermis over the spinal cord induces a gradient of cell density and elongation along the mediolateral axis, which in turn regulates cell division planes and the timing of stratification." Please weaken this conclusion.The revised statement now reads, “Thus, coverage of the epidermis over the spinal cord induces a gradient of cell density and elongation along the mediolateral axis, which in turn regulates cell division planes across the epidermis.”Subsection “Exogenous stretching of skin explants increases the frequency of planar cell divisions”: The 14.5 control and stretched conditions should be done in wt conditions. Accordingly, the conclusion at the end of the Results section is incorrect. The authors can only make this conclusion in a Vangl2 mutant conditions.We apologize for not clearly articulating the rationale for the experimental design of the stretch experiments. Because wild type division planes are already strongly biased toward planar divisions at E14.5, we reasoned that stretching explants of this stage would be unlikely to have a quantifiable effect, and if anything would shift division planes to a more E13.5-like distribution, which would not have been an appropriate comparison for Vangl2 mutants. We specifically wanted to test whether stretch could rescue the planar division orientations of Vangl2 mutants such that their division planes would now resemble unstretched wild type skins. Thus, the appropriate control in this experiment is unstretched mutant skins. To determine the effect of stretch on wild type skins, we chose to stretch E15.5 when division planes are biased toward oblique and perpendicular orientations and asked whether stretch could shift that bias toward more planar orientations. Our results indicate that division planes are not fixed in either genotype, and that basal cells are able to shift division planes in response to changes in shape/tension.We have substantially revised the text accompanying Figure 8 to better explain the experimental rationale, design, and conclusions of this experiment.


Aim: The aim of the study was to discover the metabolomic changes in plasma that occur during human Ischemia-Reperfusion (I/R) injury and to evaluate the diagnostic utility of plasma metabolomic biomarkers for determination of myocardial injury. Deciphering the details of plasma metabolome in ST-segment elevation myocardial infarction (STEMI) patients before and after primary percutaneous coronary interventions (PPCI) would allow for better understanding of the mechanisms involved during acute myocardial ischemia and reperfusion in humans. We performed a detailed non-targeted metabolomic analysis of plasma from 27 STEMI patients who had undergone PPCI in the first 48 hrs employing a LC-MS approach. Plasma metabolome at ischemic condition was compared to multiple time points after PPCI which allowed us to focus on changes in the reperfusion phase. Classification of the differential metabolites based on chemical taxonomy identified a major role for lipids and lipid-derived molecules. Biochemical pathway analysis identified valine, leucine and isoleucine biosynthesis, vitamin B6 metabolism and glutathione metabolism as the most significant metabolic pathways representing early response to I/R injury. We also identified phenyl alanine, tyrosine, linoleic acid and glycerophospholipid metabolism as the most significant pathways representing late response to I/R injury. A panel of three metabolites pentadecanoic acid, linoleoyl carnitine and 1-linoleoylglycerophosphocholine was discovered to have diagnostic value in determining the extent of I/R injury based on cardiac biomarkers. Using a non-targeted LC-MS approach, we have successfully generated the most comprehensive data to date on significant changes in the plasma metabolome in STEMI patients who had undergone PPCI in the first 48 hrs showing that lipid metabolites represent the largest cohort of molecules undergoing significant change. After an acute myocardial infarction, early and successful myocardial reperfusion by means of primary percutaneous coronary interventions (PPCI) is the treatment of choice for limiting the size of myocardial infarction and improving clinical outcomes. But the process of rapid restoration of blood flow to myocardium (reperfusion) can lead to additional injury, a phenomenon known as myocardial ischemia/reperfusion (I/R) injury2. The largest impact of I/R in the clinical setting is during percutaneous coronary intervention of patients presenting with an occluded coronary artery known as STEMI3 . Even with the best clinical care, the 30 day rate of Major Adverse Cardiac Events (MACE) for these patients is 10%4.Despite considerable improvements in mortality rates over the past two decades, coronary artery disease (CAD) remains the leading cause of morbidity and mortality worldwide, with myocardial infarction (MI) a common manifestation of this diseasein vitro and in vivo studies on the concept of I/R injury, there has yet to be a therapeutic option available to minimize the harmful effects of reperfusion injury. Many studies have investigated a single molecule or a single pathway as a potential therapeutic avenue. As in many other pathological processes there are multiple pathways involved in reperfusion injury. The numerous advancements in “omics” technology platforms in recent years have allowed us to determine the changes at the genome and proteome level. However, only changes in the metabolite level will allow us to understand the downstream effects of perturbed cellular pathways5. The heart is the most metabolically demanding organ in the body and its metabolic perturbation leads to changes in the metabolome of body fluids including plasma6. Therefore changes in plasma metabolites may reflect underlying cardiac diseases progression. Previous studies have reported individual metabolic biomarkers for heart failure, myocardial infarction, and CAD9. However, there is little information available on the metabolomic changes in human plasma during I/R injury.Although there have been extensive In this study we did a detailed non-targeted plasma metabolomic analysis employing a liquid chromatography coupled with mass spectrometry (LC-MS) platform. We investigated the time-effect changes in human plasma metabolome before and after PPCI during the first 48 hours in the setting of I/R injury in patients presenting with STEMI. We also identified a panel of plasma metabolite markers with potential for determining the extent of I/R injury.A total of 108 plasma samples from 27 patients presenting with STEMI enrolled from St. Boniface Hospital, Canada between June 2014 and July 2015 formed the study cohort. Both verbal and written consent were obtained from all subjects.Inclusion criteria were: ages between 18 and 75, confirmation of STE (ST segment elevation) on 12 lead ECG, presentation with chest pain and documentation of occluded coronary artery with coronary angiography. The overall study design is shown in Fig. To determine the necessary number of subjects needed to ensure the detection of a true statistical difference across different time intervals, we performed a power analysis  mixture made of pooled plasma samples were used to validate the extraction and LC-MS method11. More detail regarding blood sample collection, metabolite extraction and QC runs are provided in the Supplementary Data.Extraction of low-molecular-weight (<1500 Da) metabolites in plasma samples was done by as previously described12 software v3.0 and v4.0 , MetScape software v3.0 (http://metscape.ncibi.org), and R statistical software v3.5.2 (https://www.r-project.org) were used for data processing and statistical analysis. In addition, receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic capability of metabolites which can serve as potential biomarkers. Detailed description of LC conditions, MS parameters, compound identification, data processing and statistical analysis were provided in the Supplementary Data. Also, a summary of the metabolomic workflow was provided in Supplementary Table. The metabolites were separated on a 1290 Infinity Agilent HPLC system from Agilent Technologies  using a Zorbax Extend-C18 analytical column . Mass spectral analysis of eluting peptides from the analytical column was carried out on a 6538 UHD Accurate Q-TOF LC/MS from Agilent Technologies  controlled by MassHunter Workstation Software (v 7.0). All analyses were performed in both positive and negative mode ESI employing a dual ionization source. The acquired raw LC/MS data (‘.d files’) was preprocessed using Agilent MassHunter Qualitative Analysis  and Profinder (vB.06) software. Agilent Mass Profiler Professional , MetaboAnalyst13.Table 14 (HMDB) served as the database. We enlarged the scope of this database by adding further 350 metabolites from published literature known to be associated with cardiac diseases. In order to find missing features and to give higher confident identifications by further minimizing the false positives and false negatives identifications, batch recursive analysis was done on the already identified compounds. Subsequent to recursive analysis, the list was further reduced to 69 and 82 compounds in positive and negative modes, respectively. After adjusting for p-value after ‘Bonferroni FWER’ correction, only those feature satisfying p < 0.001 were considered as significantly differential metabolites across all the four time intervals. The final annotated list contained 130 significantly differential metabolites (p < 0.001) across all the four time intervals. Of these, 55 elements compounds were identified exclusively in “Positive” ESI mode, 64 compounds were identified exclusively in “Negative” ESI mode and 11 compounds were identified in both the modes  algorithm, by searching against the database, resulted in the identification of 765 and 670 compounds in positive and negative modes, respectively in plasma from patients presenting with STEMI undergoing PPCI. The endogenously present metabolites which are detected and quantified in blood from Human Metabolome DatabaseClassification of significant metabolites (p < 0.001) based on chemical taxonomy showed that lipids and lipid-derived molecules (38%) formed the major constituents of the altered metabolomic profile followed by organic acids, organo heterocyclic compounds, benzenoids, nucleotides and phytochemical compounds Fig. . These rTo understand the changes in plasma metabolome before and after the PPCI, we employed multivariate pattern recognition tools such as principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). These visualizing plots were built based on the metabolite concentrations of 130 differential metabolites at each time interval. The PCA plot Fig.  revealed15 (MetPA) analysis to understand the metabolic pathways that were impacted due to primary PCI , correlations were also calculated for all pairs of metabolite-clinical factors using the R statistical package ‘corrplot’. The resulting correlation plot  stronger mutual control by a single enzyme or (2) variation of a single enzyme level much above othersmap Fig.  was mademap Fig. . The patlot Fig.  between 20 and creatine kinase21 (CK) concentrations which are the ‘gold standard’ biomarkers of cardiac cell death. The sample population was classified into two groups as ‘Above median Troponin’ group and ‘Below median Troponin’ group centered on the median troponin value  of the cohort. We manually selected a combination of three metabolites namely pentadecanoic acid, 1-linoleoylglycerophosphocholine and linoleoyl carnitine to create a biomarker model to distinguish between these two groups using RF (random forest) algorithm22. This biomarker model was built using the metabolic profile at the time of admission. In order to produce a smooth ROC curve, 100 cross validations (CV) were performed and the results were averaged to generate the plot  in the first 48 hours after primary PCI which represent the reperfusion phase. To our knowledge, our study is the most comprehensive metabolomic analysis of human plasma ever undertaken during the first 48 hrs in the setting myocardial I/R injury in patients presenting with STEMI. In this study, we employed a repeated-measure research design by doing serial blood sampling from all STEMI patients both pre and post angioplasty. In repeated measures designs, each subject serves as their own biological control25. But none of these studies have investigated the time-effect changes in plasma metabolome before and after PPCI which is crucial to provide insights into the altered metabolic pathways with clinical relevance during I/R injury.A handful of metabolomic studies have been conducted in patients presenting with STEMIOur study had three major findings. Firstly, we identified a total of 130 plasma metabolites  of the altered metabolomic profile Fig.  in the sots Figs  and 2, s30. The extent of myocardial injury sustained during reperfusion is very dependent on the effectiveness of its antioxidant defenses31. Compared to ischemic period (0 h), there were marked increase in levels of ascorbic acid and oxidized forms of ascorbate and glutathione namely dehydroascorbic acid and GSSG, following reperfusion. This suggests that these tissue hydrophilic antioxidants may be the first line of antioxidant defences to curb the generation of reactive oxygen species (ROS) following reperfusion31. The most significant pathways  is known to play an important role in the hydrolysis of phospholipids32 especially phosphatidylcholines (PC), which leads to accumulation of FFA including (non-esterified) AA and DHA33. This non-esterified AA is then rapidly esterified to available lysophospholipids, or is converted into bioactive arachidonic acid metabolites, i.e., eicosanoids via cyclooxygenase (COX), lipoxygenase (LOX), or cytochrome P450 (CYP) epoxygenase enzymes34. From our study, the observed progressive decrease in the concentration levels of AA, DHA, DPA, lysophospholipids and their downstream products such as eicosatrienoic acid after reperfusion strongly endorses the possible part that PLA2 plays in disturbed phospholipid homeostasis during the transition from reversible to irreversible ischemic myocardial injury. This evidence also underlines the current understanding that lipoprotein-associated PLA2 is a significant predictor of cardiovascular outcome independent of traditional clinical risk factors35. In addition, few other metabolites like citrulline (a participant in urea cycle), mevalonic acid, 3-octanone and pregnenolone sulfate also exhibited the same co-variation  as the above metabolites.Measures of correlation between metabolites in replicate profiles can be very informative about the underlying biological systemmap Fig.  construcAmongst highly correlated metabolites, several metabolites exhibited a pattern Fig.  which is38. In our study cohort, a combination of three metabolites namely pentadecanoic acid (15:0), linoleoyl carnitine (18:2 carnitine) and 1-linoleoylglycerophosphocholine (18:2 lysoPC) exhibited good separating capability in discriminating small and large infarct size patients with an AUC value of 86 based on peak troponin concentration  and creatine kinase (CK) or its specific MB (CKMB) isoform after primary PCI represent larger infarct size and are clearly associated with increased early and late mortalityion Fig.  and withion Fig.  based on39. But whether one or all of these known metabolic roles of 15:0 has a link to CVD risk is still debated. Though certain studies have reported the association of 15:0 with greater risk of CVD40, many studies like Elwood et al.41 showed that, in relation to coronary artery disease, it is inappropriate to accept an estimate of CVD risk based on plasma concentrations of 15:0 alone. Also, earlier studies have reported that lower serum levels of 18:2 lysoPC, a downstream product of lysophosphatidylcholine (LPC), has a tight relationship with increased arterial stiffness, increased resting heart rate and occurrence of silent myocardial ischemia43. Linoleoyl carnitine is a long-chain acyl fatty acid derivative ester of carnitine. Ischemic condition inhibits beta oxidation of fatty acids and leads to accumulation of toxic intermediates of beta oxidation, particularly long-chain acyl carnitine compounds like linoleoyl carnitine. These compounds are detrimental to cellular function and are known to enhance myocardial injury by inducing structural damage in ischemic myocytes45. From our study these three molecules were proved to be promising molecular markers for the determination of myocardial injury. To our knowledge, this is the first published report of a blood-based biomarker panel for the prediction of I/R injury following coronary intervention in patients presenting with STEMI. This has the capacity to identify novel pathways impaired during reperfusion injury and identify patients at high risk for myocardial damage after PPCI allowing for development of therapeutic intervention to minimize I/R injury.Until recently it was assumed that the existence of straight chain odd number fatty acids such as pentadecanoic acid (15:0) in normal physiological conditions were rare. Recent analytical instrumentation has proven this to be a misconception, since the presence of odd number carbon fatty acids such as 15:0 and 17:0 have been shown to occur as minor constituents in practically every natural fat and carry out many roles like synthesis of very-long-chain odd-numbered fatty acids, replenish the TCA cycle with anaplerotic intermediates and, hence, improve mitochondrial energy metabolism in natureOur study has several potential limitations that should be considered. First, though serial sampling performed in all STEMI patients both before and after PPCI helped minimize inter-individual variability and clinical confounders such as diet, drug effects, age, sex, and other co morbidities, our study population was comparatively small to identify metabolites that failed to reach minimal significance. But these metabolites which fail to reach minimum significance might be scientifically relevant. So it is important to adequately validate the identified metabolites in a relatively larger patient cohort. Second, though ROC analysis with 100 CV exhibited good prediction accuracy (better than 80%); these findings are exploratory in nature and should be confirmed in an independent patient cohort. Moreover, as with any untargeted metabolomic study, samples were analysed without authentic standards. This calls for further confirmation of these identified metabolites by employing a targeted metabolomic analysis.Using a non-targeted LC-QTOF-MS methodology, we have successfully generated the most comprehensive data to date on significant changes in the plasma metabolome in STEMI patients undergoing PPCI. The role of lipids and lipid metabolism pathways in the pathogenesis of atherosclerosis is already well understood. But there is little information about their role in reperfusion and I/R injury. From our study, we elucidated that lipid metabolism in general and phospholipid, linoleic acid and alpha linolenic acid metabolism in particular represent the largest change in the plasma metabolome post PPCI. We also identified a panel of three metabolites namely pentadecanoic acid, linoleoyl carnitine and 1-linoleoylglycerophosphocholine that could serve as plasma biomarkers in determining the extent of myocardial injury after PPCI. This knowledge could help to predict the response to PPCI and how to limit complications in STEMI patients after reperfusion. Given that there is currently no therapy available for I/R injury, we consider our results as a major step toward moving us closer to our ultimate goal of developing therapies to prevent myocardial reperfusion injury and improve clinical outcomes in patients with STEMI.Supplementary informationTable 4


Next generation sequencing (NGS) of immunoglobulin (Ig) repertoires (Rep-seq) enables examination of the adaptive immune system at an unprecedented level. Applications include studies of expressed repertoires, gene usage, somatic hypermutation levels, Ig lineage tracing and identification of genetic variation within the Ig loci through inference methods. All these applications require starting libraries that allow the generation of sequence data with low error rate and optimal representation of the expressed repertoire. Here, we provide detailed protocols for the production of libraries suitable for human Ig germline gene inference and Ig repertoire studies. Various parameters used in the process were tested in order to demonstrate factors that are critical to obtain high quality libraries. We demonstrate an improved 5′RACE technique that reduces the length constraints of Illumina MiSeq based Rep-seq analysis but allows for the acquisition of sequences upstream of Ig V genes, useful for primer design. We then describe a 5′ multiplex method for library preparation, which yields full length V(D)J sequences suitable for genotype identification and novel gene inference. We provide comprehensive sets of primers targeting IGHV, IGKV, and IGLV genes. Using the optimized protocol, we produced IgM, IgG, IgK, and IgL libraries and analyzed them using the germline inference tool IgDiscover to identify expressed germline V alleles. This process additionally uncovered three IGHV, one IGKV, and six IGLV novel alleles in a single individual, which are absent from the IMGT reference database, highlighting the need for further study of Ig genetic variation. The library generation protocols presented here enable a robust means of analyzing expressed Ig repertoires, identifying novel alleles and producing individualized germline gene databases from humans. This requires a sequence length of at least 400 base pairs (bp), thereby limiting the available sequencing platform options. In order to produce libraries of sufficient length and depth for Rep-seq analysis many groups currently utilize long-read Illumina protocols, such as the 2 × 250 bp HiSeq system or, more commonly, the 2 × 300 bp MiSeq system. Two major library production techniques, 5′ Rapid Amplification of cDNA Ends (5′RACE)  , 13 and (5′RACE) –16, are An important first step of Rep-seq analysis, which is required for correct gene assignment and somatic hypermutation (SHM) analysis, is to define the specific germline V alleles present in the subject of interest. The current public database for Ig germline genes, the international ImMunoGeneTics information system (IMGT) , includeCareful positioning of constant region primers is the primary means of minimization of amplicon length in Rep-seq library production. Primer localization in the vicinity of the proximal exonic border is commonly used to minimize the overall library sequence length. The 5′ border of the library will be determined by the methodology used, either 5′MTPX primers positioned in the leader or 5′ untranslated region (UTR) of the respective target genes, or a template switch universal amplification sequence added upstream of the 5′UTR during cDNA synthesis (5′RACE). In addition, many current Rep-seq analysis tools take advantage of UMIs added during library production –22. UMIsHere, we describe the technical limitations of some current library production techniques and we offer methodological solutions to facilitate the use of either 5′RACE or 5′MTPX methods to produce Ig libraries for Rep-seq analysis. In particular, we examine factors that may result in lack of full-length coverage of the expressed Ig repertoire as well as aspects critical to minimize PCR and instrument-associated sequencing errors. The optimized protocols described here facilitate the production of high-quality libraries for germline genotype inference and Ig Rep-seq expression analysis.To minimize the sequence length for Ig libraries, we developed an optimized 5′RACE cDNA amplification protocol to generate libraries suitable for Illumina MiSeq 2 × 300 bp paired-end sequencing. The procedure is summarized in Template switching is a relatively inefficient process in which the yield can be batch-dependent. We found that substitution of a regular 30-cycle cDNA amplification PCR protocol for a semi-nested process increased the yield and lowered the batch variability, especially for the IgM and IgK libraries . The semUsing the leader sequence information obtained from 5′RACE libraries and available genomic references, we designed sets of 5′MTPX primers positioned in the V gene leader sequences  for prodCompared to the 5′RACE protocol, the amplicon generated by 5′MTPX does not encompass the poly-cytosine segment, the 5′UTR, and part of the leader sequences, reducing the amplicon length considerably. Thus, the 5′MTPX protocol appeared to have at least two advantages: it involved fewer steps and resulted in shorter amplicons. Furthermore, with the 5′MTPX protocol described here, we obtained comparable yields of library product as when using the 5′RACE protocol, without the need of a semi-nested step and fewer PCR cycles . A protoIllumina's MiSeq 2 × 300 bp V3 kit, commonly utilized in Rep-seq analysis, has a sequencing capability of 600 nt. In theory, this should be sufficient to sequence full-length V(D)J libraries produced by either 5′RACE or 5′MTPX protocols. In practice, however, length variations due to differences in the 5′UTR and/or in the HC complementarity determining region 3 (HCDR3) result in some sequences that are too long for Read1/Read2 merging after 5′RACE library preparation. To merge the Read1 and Read2 sequences, an overlap between the reads of at least 10 nt is required . We foucsc.edu/ . We alsocsc.edu/ . These rcsc.edu/ . AlthougLibrary quality is important for optimal germline gene inference as well as for Rep-seq studies in general. In the IgM libraries produced from the six test subjects, we observed significantly more sequences with V segments that were 100% identical to the inferred germline alleles (“exact sequences”) in the libraries generated by 5′MTPX compared to the libraries generated by 5′RACE . Those sSince one objective of Rep-seq analysis is to identify the specific germline alleles expressed in a given individual using germline gene inference tools, we next investigated the output from libraries produced by the 5′RACE or 5′MTPX protocols for the six subjects. Using IgDiscover to generate individualized germline IGHV databases from each donor, we obtained more complete outputs from the libraries generated by the 5′MTPX compared to the 5′RACE protocol. We were able to identify a majority of alleles expressed in each person (mean 47) by both methods. However, we identified on average 11 alleles more per person with the 5′MTPX method , demonstIn the process of library analysis it is highly beneficial to have indicators of the overall library quality. Using a library with sub-optimal quality limits the ability to generate high-confidence inferred genotypes and can have a direct impact in Ig repertoire expression analysis. IgDiscover, display the numbers of Ds and CDR3s found associated with every allele inferred. These are displayed as “exact Ds” and “exact CDR3s,” which are the number of D alleles and unique HCDR3s associated with sequences that match an inferred allele. We have observed that these numbers are valuable indicators of the overall library quality and diversity. Moreover, polymerases with high fidelity are recommended, as the overall sequence error observed is the addition of the PCR error and the instrument associated error.The optimal quantity of RNA required for Ig library production depends on the source of cells used for RNA isolation. In our protocol, we started from total peripheral blood mononuclear cells (PBMCs) where the proportion and composition of B cells is variable . We inveOne concern when preparing libraries for NGS analysis is the generation of PCR artifacts such as chimeric sequences. The number of cycles in the PCR is known to affect chimerism . In ordeThe overall structure of the LC provides advantages and disadvantages for library production and analysis. The lack of D gene segments makes the LC Ig sequences shorter, thus removing the length limitation associated with HC libraries. However, it lowers the variability of the CDR3, which is used to identify unique recombination events during the germline inference process. The organization of the kappa and lambda LC loci differs from that of the HC Ig locus. Ig HCs have different constant regions for different Ig isotypes and subclasses, located downstream of the V, D, and J gene segments. The kappa locus has a single constant gene, but two V gene regions, one upstream of the J genes and one duplicated locus inverted downstream of the constant gene  34, 35), 3534, 3IgDiscover uses several parameters to identify candidate germline V gene sequences, one of which is the number of J genes associated with a given allele. For IgL library production we found that we could use a single constant region primer that targets a conserved sequence within the genes since we did not see any major difference to the library quality using this method compared to when using a mixture of constant-specific primers . Further*01_S5228, was identical to IGLV2-14*03 (present in IMGT), but with a segment in the 5′ end of 23 nt. We designed primers encompassing the genes of the novel alleles inferred (*02_A318G recently described (*01_S5868 and IGHV3-53*02_S0744). All the libraries and the novel alleles identified in this individual can be found in ENA (accession number ERR3004229-ERR3004232 and ERR3153714-ERR3153725) and Genbank . All the novel alleles will be submitted for consideration to the Inferred All the novel alleles will be submitted for consideration to the Inferred Allele Review Committee (IARC) and IgPdB online database  with 10% DMSO. RNA was extracted using the RNeasy Kit (Qiagen).Blood samples were collected in BD Vacutainer® K2 EDTA tubes, and PBMCs were isolated using Ficoll-paque™ . The cells were washed twice with PBS, and remaining red cells were removed with lysis buffer. The cells were washed twice again with PBS and frozen at 10 × 10Two hundred nanogram of total RNA was used for each 5′RACE cDNA synthesis reaction. Superscript II reverse transcriptase (Thermo Scientific) and 10μM Oligo dT was used to generate the first-strand cDNA at 42°C for 1 h. The template switching was performed by adding to the reaction mixture an oligonucleotide containing RNA poly-G sequence, a 12 nucleotide UMI and Illumina's Read1 sequence  was used for cDNA synthesis with chain-specific reverse primers  containiFive to ten nanogram of the gel-purified amplification product (either 5′MTPX or 5′RACE) was used for index PCR reaction. The forward indexing primer P5_R1 and reverse indexing primer P7_R2_I1-27 were added in a 10 cycle PCR reaction with KAPA HiFi Hotstart ReadyMix system (Kapa Biosystems) . The prihttps://github.com/mateuszatki/IgDiscover/) was used to pre-process the libraries for quality control, and subsequently perform expression analysis and generate individualized databases. The analysis was performed with the default settings, specifying the pre-CDR3 position , and UMI lengths of 25 nt in 5′RACE and 21 nt in 5′MTPX. The IMGT reference database (April 2018) was used, with the addition of a recently described new allele  and BLAT [UCSC genome browser .Primers encompassing the genes of the novel alleles were designed using BLAT [UCSC genome browser ] Supple. Two nanNV and MC: designed the experiments. NV, UH, GP, and MC: performed the experiments; MM and MK: wrote code for IgDiscover. NV, UH, MC, MK, and GK: analyzed the data. NV, MC, and GK: wrote the paper.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Moreover, a distinct lineage of memory T cells populates tissues (tissue-resident memory T cells or TRM cells) which orchestratea the response to pathogens re encountered at tissue sites. Recent evidence, however, has highlighted that CD4+ naive T cells are much more heterogeneous that previously thought, and that they harbor diversity in phenotypes, differentiation stages, persistence, functions, and anatomic localizations. These cells represent cellular subsets that are extremely heterogeneous and multifunctional at their very initial stages of differentiation, with the potential to become “atypical” memory and effector cells. In this mini review, we focus on recently obtained data from studies in humans, in which this newly recognized heterogeneity in the naive T cell pool was discovered in terms of surface marker expression, cytokine production, or transcriptomic profiles. The deep analysis of immune functions at the single cell level combined with a better understanding of the generation and maintenance of the various atypical memory CD4+ T cell subsets with a naive-like phenotype will be important in immune-monitoring of vaccination and immunotherapies in infectious diseases.The induction of adaptive immunological memory, mediated by T and B cells, plays an important role in protective immunity to pathogens induced by previous infections or vaccination. Naive CD4 These mature T lymphocytes, that have not yet encountered antigen (naive T cells), continuously recirculate between secondary lymphoid organs and blood. Upon recognition of specific antigen/MHC complexes naive CD4+ T cells proliferate and differentiate toward effector T cells, which provide immediate protection. Most of these effector T cells subsequently die by apoptosis, but a subset of antigen-specific T cells will persist in an individual as memory T cells (CM) and effector (TEM) memory T cells: the former show self-renewal potential, home to secondary lymphoid organs but lack effector functions, while the latter possess immediate effector functions and can rapidly migrate to peripheral tissues to provide antigen elimination (RM cells) has been described in the last years, which are confined to different tissues and orchestrate the response to pathogens re encountered at tissue sites.CD4 T cells . There amination . Moreove+ T cells in humans have a lifespan of 6–10 years -recognized self peptide/MHC complexes, which however do not induce differentiation into central or effector memory T cells . Since n10 years , this ho+ T cell compartment has long been considered as consisting of a homogeneous population of antigen-inexperienced cells  cells. The T+ T cells, while having lost CD31 expression, a marker that usually has been proposed as identifier of naive cells that have undergone homeostatic division. In fact, the number of TRECs diminishes in each cell division (since TRECs are not copied during cell division) and CD31 is expressed on naive CD4+ T cells that have recently egressed from the thymus where its expression is downregulated following TCR stimulation. Moreover, T+ TWithin the human naive CD4+ (and CD8+) T cell compartment of CD45RA+, CCR7+ phenotypically naive cells, a proportion of T cells is clearly distinct from classically naive T cells as they display phenotypical and functional characteristics reminiscent of effector and memory T cells. Among these naive-like memory T cells, a subset termed stem cell memory T (TSCM) cells has been identified based on the expression of CD95, CD122, CXCR3, and the integrin CD11a  upon antigenic and homeostatic stimulation. Despite low TREC levels, high expression levels of the intracellular proliferation marker Ki-67 and a restricted TCR repertoire  in response to different M. tuberculosis antigens (+T cell population as TCNP cells (T cells that are able to produce cytokines with a naive phenotype). TCNP cells were further phenotyped as CD95lo CD28int CD49dhi CXCR3hi and a sizeable fraction (ranging from 50 to 80%) also expressed CD31. Following curative tuberculosis treatment, the size of this T cell subset significantly decreased, suggesting that these cells are markers of active tuberculosis disease during infection with M. tuberculosis and probably expand in response to actively multiplying bacilli. Accordingly, subjects with latent M. tuberculosis infection had a lower proportion of responding CD4+ TCNP cells in the peripheral blood, than tuberculosis patients.Very recently, we have identified in the peripheral blood of patients with tuberculosis a novel human effector/memory CD4antigens . We haveSCM cells, TCNP cells express higher levels of CD49d and comparable levels of CXCR3, but they do not express CD95 . Interestingly, and similar to our findings in tuberculosis, these CD8+ TMNP cells were increased in patients with active West Nile virus infection, and their frequency and numbers correlated with the severity of infection.Our findings are reminiscent of the CD8o et al. , that pr+ TCNP cells are polyfunctional T cells that differ both phenotypically and functionally from the quiescent CD4+ T naive population.Thus, our findings demonstrate that CD4+ TCNP cells (and related subsets) generated ? Sallusto  from naive T cell precursors  . The ver+ but CD45RO−? Are they only weakly activated? Are they functionally equally powerful as compared to fully differentiated memory T cells? Do they have any unique functional properties? Any thoughts why we would have such atypical cells in such high numbers? A better understanding of the mechanisms involved in the generation and differentiation of the atypical naive-like CD4+ T cells may provide novel tools for immunization in early life and in elderly individuals, and more generally for improving vaccination and immunotherapeutic strategies in human infectious disease and cancer.The big question that remains and has not been touched upon is: why would these cells persist in the naive compartment if they have seen antigen, are there any advantages to the cells to remain CD45RAAll authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Background: Secondary use of newborn screening dried blood spot samples include use for biomedical or epidemiological research. However, the effects of storage conditions on archival samples requires further examination. The objective of this study was to determine the utility of residual newborn samples for deriving reliable metabolic gestational age estimates.Methods: Residual newborn dried blood spot samples that had been stored for 2-, 4-, 6-, or 12-months in temperature controlled (21°C) conditions were re-analyzed for the full panel of newborn screening analytes offered by a provincial newborn screening lab in Ottawa, Canada. Data from re-analyzed samples were compared to corresponding baseline newborn screening values for absolute agreement, and Pearson and intraclass correlation. Performance of a gestational age estimation algorithm originally developed from baseline newborn screening values was then validated on data derived from stored samples.Results: A total of 307 samples were used for this study. 17-hydroxyprogesterone and newborn hemoglobin profiles measured by immunoassay and high-performance liquid chromatography, respectively, were among the most stable markers across all time points of analysis. Acylcarnitines exhibited the greatest degree of variation in stability upon repeat measurement. The largest shifts in newborn analyte profiles and the poorest performance of metabolic gestational age algorithms were observed when samples were analyzed 12-months after sample collection.Conclusions: Duration of sample storage, independent of temperature and humidity, affects newborn screening profiles and gestational age estimates derived from metabolic gestational dating algorithms. When considering use of dried blood spot samples either for clinical or research purposes, care should be taken when interpreting data stemming from secondary use. Newborn screening is a public health initiative that tests infants shortly after birth for rare but treatable diseases. The screening process entails the collection of 4–5 drops of newborn blood by heel prick, typically within 24–72 hours of life. Newborn samples are collected onto filter paper and sent to accredited laboratories where the dried blood spots are used to screen infants for risk of developing diseases included in the laboratory’s screening panel. Although newborn screening is typically completed within the first few days of birth, secondary use of samples is not uncommon. Beyond provision of health care, residual dried blood spot samples may be used for quality assurance to improve existing tests and programs, used under legal warrant or court order, or used for biomedical or epidemiological researchEmerging secondary uses of newborn screening data include using screening profiles for biological modelling. For example, gestational age estimation algorithms based on a combination of newborn screening analytes and clinical covariates such as sex and birthweight have emerged as novel alternatives for accurately categorizing infants across preterm birth categories. Postnatal gestational age dating based on newborn metabolic profiles generated from dried blood spot samples provides the opportunity to establish preterm birth estimatesIn this study, we sought to determine longitudinal changes in metabolic profiles derived from residual blood spot samples from a provincial newborn screening facility in Ottawa, Canada. The effects of longitudinal changes in metabolic profiles on the performance of gestational age estimation models as a result of storage were determined.The data for this study were derived from a quality assurance project run through Newborn Screening Ontario (NSO), located at the Children’s Hospital of Eastern Ontario. NSO is the provincial program that coordinates newborn screening in Ontario, Canada, screening more than 145,000 infants each year for over 90 analytes and analyte ratios.After testing at NSO, newborn dried blood spot samples from healthy infants are temporarily stored on-site at 21°C, after which they are sent to a secure off-site facility as part of the newborn medical record. These stored samples can be used for secondary purposes, including use for method development, method comparisons and transfer of screening thresholds.Archival screen-negative dried blood spot samples collected over the course of 2016-2017, that had been stored for 2-, 4-, 6-, or 12-months after initial analysis were used for this study. As per standard newborn screening policy, initial analysis of all samples occurred within two weeks of collection. The sample set was enriched to include approximately 40–50% preterm infants by random selection of available samples from infants born ≥ or <37 weeks gestation. Eight 3.2 mm diameter circular samples were punched from each dried blood spot sample for first tier testing of each of the following analytes: hemoglobin profiles; 17α hydroxyprogesterone (17-OHP); thyroid stimulating hormone (TSH); a panel of 12 amino acids and 31 acylcarnitines; t-cell receptor excision circles (TREC); biotinidase activity; and galactose-1-phosphate uridylyltransferase activity. Hemoglobin profiles were determined by high performance liquid chromatography on a Bio Rad Variantnbs system; neonatal 17-OHP, and TSH were measured using a PerkinElmer AutoDELFIA® Immunoassays; amino acid and acylcarnitine analysis was performed by electrospray ionization tandem mass spectrometry (Waters TQ Detector); total TREC copy number was measured by quantitative polymerase chain reaction using a ThermoFisher Scientific Viia 7; biotinidase and galactose-1-phosphate uridyltransferase levels were measured using the Astoria-Pacific SPOTCHECK® Pro system. For each sample included in the study, analyses conducted at each storage time point were compared with the original baseline analyses for the same newborn.Agreement between paired baseline and stored metabolic profiles. Descriptive statistics were generated for the cohort. All analyte and clinical variables were standardized to a larger Ontario reference cohort by subtracting the mean and dividing by the standard deviation of the reference cohortValidation of metabolic gestational age estimation models. Our group has previously developed and validated gestational age estimation algorithms derived from newborn screening profiles and other clinical covariatesTo determine the impact of delayed analysis and storage on the performance of gestational age estimation models, we externally validated the performance of our models in samples analyzed at baseline (time 0) and after 2-, 4-, 6- and 12- months of storage. Samples where secondary screening could not be completed due to insufficient sample volume were excluded from model testing. Model coefficient estimates from our previously published modelsModel 1: containing only the clinical factors of infant sex, birthweight, and multiple birth Model 2: Model 1 + newborn screening analytes and analyte ratios including acylcarnitines, amino acids and enzyme markers.All analyses were conducted using SAS software version 9.4A total of 307 samples were analysed for this study. 74 samples were procured 2 months after initial analysis; 77 at 4 months; 78 at 6 months; and 78 at 12 months. The majority (68.1%) of samples were obtained from infants with a birthweight of ≥2500g, and 52.8% of samples were from term infants . Newborn samples were collected earlier among term infants (63.3±117.1 hrs after birth) than preterm infants (81.4±142.6 hrs after birth). A summary of newborn characteristics is provided inBox plots depicting changes in standardized analyte concentration determined within one week of sample collection and after storage are provided inThe majority of analyte levels (30 out of 48) were consistent at 2-months when compared to baseline levels (Pearson r≥0.8). 25 out of 48 of the measured analytes were highly correlated with baseline levels both 2-months and 4-months after collection (Pearson r≥0.8). Analytes exhibiting rapid degradation between initial analysis and 2 months after collection (Pearson r<0.5) were the amino acid argininosuccinic acid, and acylcarnitines C10:1, C14:OH, C16OH, C18:1OH, C18OH, C5:1. The endocrine hormone 17-hydroxyprogesterone (17-OHP) and relative levels of fetal hemoglobin peaks, taken by the ratio (HbF+F1)/(HbF+F1+A) were consistently the top two correlated analytes across all time points of analysis. Pearson and Intra-class correlations (ICC) with 95% CIs comparing baseline values to each time point of analysis, and Wilcoxon test results are provided inThe performance of the linear regression models in providing continuous estimates of gestational age and correctly identifying gestational age within 1 and 2 weeks of ultrasound validated gestational age are summarized inWhereas the performance of metabolite models was similar for data derived after 2 and 4 months of storage compared to paired baseline values , results after 6 months and 12 months of storage were more variable. Metabolite data measured after 6 months of sample storage yielded gestational age estimates that were 0.24 weeks less accurate than estimates derived from fresh samples. Here, gestational age was correctly identified within 1 week for 21.5% fewer infants, and within 2 weeks for 3.1% fewer infants. After 12 months of storage, estimates were 0.1 week less accurate, and gestational age was correctly identified within 1 week for 7.9% more infants, but within 2 weeks for 7.9% fewer infants.We also evaluated the capacity of published models to accurately categorize samples across dichotomous gestational age categories  by logistic regression . As withA comparison of ultrasound-validated preterm birth rates and algorithm-based estimates are provided inIn this study we provide insight into the stability of residual newborn screening samples, and the impact of year-long storage on screening profiles. Hemoglobin profiles, amino acids, and endocrine and enzyme markers were largely stable from baseline to 6-months after collection. Stability of acylcarnitines was variable. Greatest changes in analyte levels were observed after 12-months of storage. As a result of shifts in newborn screening analyte levels secondary to storage, the performance of metabolic gestational age algorithms was poorest when sample analysis was conducted 12-months after collection. Our models consistently demonstrated strong performance for dichotomous classification of infants as either ‘term’ or ‘preterm’, although continuous estimates of gestational age were more affected.et al. reported that all analytes were significantly reduced following 30-day storage at high temperature (37°C) or high humidity (>90%). The enzyme activities of GALT and BIOT were particularly susceptible, losing >60% of their initial activity when stored at high temperature, and >70% of their initial activities when stored at high humidityIn North America, state and provincial policies for the retention, storage and residual use of samples collected as part of newborn screening programs vary widely, ranging from one month to decades, to indefinitelyUnique to this study is our evaluation of the impact of alterations in metabolic profiles over time on the performance of gestational age estimation models developed by our group. We have previously demonstrated the accuracy of such algorithms to estimate gestational age to within one week when applied to infants born in Ontario, CanadaWhere there are plans to implement this technology to generate preterm birth estimates in select low- and middle-income countriesThe strengths of this study include our use of a relatively large number of samples compared to other similarly structured studies, as well as our examination of four time-points over a wide interval of sample storage (2 to 12 months). Our use of a large number of samples of preterm infants - approximately 50% per time-point of analysis - permitted sound evaluation of gestational age estimation models. There are two notable limitations to this work. Although the study provides insight into the stability of newborn screening analytes stored in temperature and humidity-controlled conditions, we did not explore the effect of extreme environmental storage conditions on dried blood spot samples. Second, our study was limited to samples that had provided ‘negative’ screening results upon their first analysis. As it is unclear whether extremely low or high concentrations of analytes exhibit similar rates of degradation as analyte levels falling within the standard clinical reference range, as in our study, we cannot infer the stability of analyte concentrations from infants with congenital conditions.In this paper, we have established that duration of storage, independent of temperature and humidity affect newborn screening profiles and gestational age estimates derived from metabolic gestational dating algorithms. When considering dried blood spot samples for secondary use, either for clinical or research purposes, care should be taken to store samples in temperature and humidity-controlled environments.Data stemming from this project arose from a programmatic quality assurance initiative at Newborn Screening Ontario (NSO). As such, the authors do not have permissions to share the raw newborn screening data associated with this project. NSO is administered by the Children’s Hospital of Eastern Ontario (CHEO) and funded by the Ontario Ministry of Health and Long-term Care. NSO is committed to keeping newborn information, blood samples, and data arising from analysis safe and confidential. CHEO follows the following Canadian Standards Association privacy principles, which form the framework for Personal Health Information Protection Act, 2004 (PHIPA). PHIPA is Ontario's health information privacy legislation. It sets rules for how personal health information can be collected, used and disclosed. CHEO will not use or disclose personal information for purposes other than those for which it was collected, except with the consent of the individual or as required by law.newbornscreening@cheo.on.ca, and the request will be assessed as per NSO’s data request and secondary use policies. For more information, please visit the NSO website:https://www.newbornscreening.on.ca/en/screening-facts/screening-faq (‘What happens when a researcher wants to access stored samples for research’);https://www.newbornscreening.on.ca/en/privacy-and-confidentiality.Individuals seeking a copy of the data presented in this study should contactNSO regularly seeks to improve existing testing. This quality assurance project sought to determine the stability of newborn samples after storage in agreement with the provincial terms of secondary use of newborn screening samples. As this was a quality improvement project, the requirement for ethics review and informed participant consent was waived by the Children’s Hospital of Eastern Ontario Research Institute. et al evaluates how storage conditions on archival samples correlate with reliable metabolic gestational age estimation. The study employs a relatively large cohort (n=307) with samples analyzed, post-storage for 2-, 4-, 6-, and 12-months. Authors analyzed hemoglobin profiles as well as numerous newborn analytes' profiles and metabolic gestational age algorithms were used to evaluate their performance in estimating gestational age. The greatest levels of changes due to storage conditions, were found in samples that were stored for 12 months.The manuscript "Metabolic profiles derived from residual blood spot samples: A longitudinal analysis" by MurphyThe statement "Duration of sample storage, independent of temperature and humidity, affects newborn screening profiles and gestational age estimates derived from metabolic gestational dating algorithms" can be revised as in the present work authors only looked at one storage condition (21°C "in temperature and humidity-controlled conditions"). I also suggest, authors include details about storage humidity levels.Method details for "amino acid and acylcarnitine analysis was performed by electrospray ionization tandem mass spectrometry" can be expanded and described in detail, including details of separation conditions and MS data acquisition parameters.Details about how to get access of "metabolic gestational dating algorithms" can be added. The manuscript is well written, however I have a few suggestions:  In conclusion, the present work successfully evaluatse the impact of storage time (up to 12-months) and future longitudinal studies can look at >12 months storage and/or different storage conditions.I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. I think the authors do a great job at validating the long-term data obtained from blood spot samples. Further, the characterization of the variability over the 4 time points is a useful tool for clinicians in low resource settings.  Comparing the Model 1 vs 2 further highlights the poor quality of gestational age information that can be derived from models that only focus on clinical variables.  With respect to future direction, this project must be scaled up to include data on outliers  and characterize the variability of the analytes at the same four time points mentioned in this paper.  Overall, the authors have taken the challenge of better predicting GA using clinical and analyte variables and successfuly demontrate the performance of their model vs the classical clinical model.I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.