Outcome measures included pulsatility index (PI), cerebral blood flow/velocity (CBF), resistance index (RI), cerebral autoregulation, and cerebrovascular reactivity. Meta-analysis was carried out on HRT studies. PI significantly decreased  in post-menopausal women undergoing HRT compared to post-menopausal women who were not, though there was considerable heterogeneity (I2 = 96.8%). No effects of HRT were seen in CBF (p = 0.24) or RI (p = 0.77). This review indicates that HRT improves PI in post-menopausal women. However, there remains insufficient evidence to determine how changing ovarian sex steroid hormone levels affects cerebrovascular function in women during other hormonal phases .Sex differences in cerebrovascular disease rates indicate a possible role for ovarian sex steroid hormones in cerebrovascular function. To synthesise and identify knowledge gaps, a systematic review and meta-analysis was conducted to assess how ovarian sex steroid hormone changes across the lifespan affect cerebrovascular function in women. Three databases  were systematically searched for studies on adult cerebrovascular function and ovarian sex steroid hormones. Forty-five studies met pre-defined inclusion criteria. Studied hormone groups included hormone replacement therapy (HRT;  Sex differences in the rate and occurrence of cerebrovascular diseases  indicate a possible role for ovarian sex steroid hormones in brain vascular function and regulation. For example, despite women having a lower risk of stroke than men during midlife their risk doubles in the decade after menopause  guidelines  framework  independently searched the literature using three databases and the defined keywords. All citations identified in the search were independently screened by the reviewers on the basis of the title and the abstract to assess their match with inclusion criteria. To ensure the inclusion/exclusion criteria were applied consistently, 20% of identified citations were screened by both reviewers and the results compared. Disagreements regarding eligibility of studies were resolved by discussion and consensus with a third reviewer (RAIL). The reviewers checked the references of included studies to identify any relevant papers not captured in the search. Included title and abstracts were then screened for their full texts.Full texts deemed eligible for inclusion underwent data extraction using a data extraction form. This included participant demographics , study characteristics , outcome measures  and results. Where possible, results were expressed as absolute values (mean ± SD) in order to determine percentage change across time points/experimental groups. To minimise bias, and ensure the accuracy of the study selection procedure, a random sample of 20% of included studies were extracted by both reviewers and results compared. The two independent reviewers graded all identified studies as either a high , moderate  or low  level of evidence. The criterion for each level of evidence can be found in Reviewers applied a modified version of the National Heart, Lung, and Blood Institute quality assessment tool for observational cohort and cross-sectional studies , and cerebral autoregulation . If measures were presented as mean difference with 95% confidence intervals, then standard deviation was calculated using the method described in the Cochrane Handbook  and heterogeneity (I2). The I2 statistic was examined to evaluate heterogeneity, with I2 > 50% and I2 > 75% indicative of substantial and considerable heterogeneity, respectively ; covariance from the mean; residual heterogeneity test statistics; overall result influence , and study weight , followed by pregnancy (n = 12), menstrual cycle (n = 7), menopause (n = 5), oral contraception (n = 2), and ovarian hyperstimulation (n = 2). Eleven studies were assessed to be of high quality and therefore, low risk of bias. Thirty-two studies were deemed to be of moderate quality and two of low quality. Of the studies included in the quantitative synthesis, 29 were based in Europe, eight in North America, five in Asia, and three in South America. Six of these were randomised controlled trials, 15 were non-randomised controlled trials or cohort studies, 14 were cross-sectional, nine were longitudinal and one was an observational study. Hormone replacement therapy (HRT) was the most frequently studied hormone group (n = 22), with fewer studies reporting PI of the middle cerebral artery , external carotid artery , common carotid artery , and posterior cerebral artery .Twenty-six studies were identified that reported PI in low and high hormone phases . PI was p = 0.01; I2 = 96.8%; p = 0.303; and 0%, p = 0.952, respectively).Fourteen studies investigated changes with HRT and showed that PI was 4.6 ± 10.2% lower in the high hormone phase as compared to the low phase. Twelve studies reporting PI changes with HRT were suitable for inclusion in the meta-analysis. Within these 12 studies, three reported outcomes in two experimental groups , and six reported outcomes in two or more vessels, resulting in a total of 25 cohorts. The combined effects of the 25 cohorts showed an estimated mean difference of −0.05  from a low to high hormone phase, which was significant and showed considerable levels of heterogeneity (n = 2), and increased by 14% in the one study observing changes in PI from a low to high hormone phase in ovarian hyperstimulation.Four studies examined changes in PI with pregnancy, showing a 22 ± 8% higher PI in a high hormone phase compared to a low hormone phase. Five studies examining changes across the menstrual cycle, showed PI was 3 ± 6% higher in the high hormone phase compared to the low hormone phase, while two studies showed PI to be 8 ± 12% lower post-menopause compared to pre-menopause. PI increased by 14 ± 2% in the high hormone phase compared to the low hormone phase in oral contraceptive use (n = 14), with fewer studies reporting CBF in the ICA (n = 12), PCA (n = 2), CCA (n = 2), ECA (n = 1), and vertebral artery .A total of 25 included studies reported an index of CBF, the characteristics of which are summarised in n = 5) showed CBF was 3 ± 12% lower during HRT compared to pre-HRT or control groups. All five studies were included in the meta-analysis, with one study reporting outcomes in two groups using different HRT and two studies reporting outcomes in two vessels . No effects were found in CBF between the high and low hormone phase .HRT studies (n = 2) CBF was 12 ± 7% higher in the high hormone phase compared to the low. Four studies investigating menopause showed CBF was 23 ± 25% higher in the high hormone phase, while oral contraceptive studies (n = 2) reported that CBF was 15 ± 4% lower in the high hormone phase as compared to the low.Eight studies reported CBF was 10 ± 15% lower in the high hormones phase during pregnancy as compared to the low. Four studies examining CBF across the menstrual cycle showed CBF was 3 ± 10% lower in a high hormone phase compared to a low hormone phase. Across different stages of ovarian hyperstimulation (n = 7), with fewer studies reporting the MCA (n = 5), ECA (n = 4), CCA (n = 4), PCA (n = 1), and VA (n = 1).Eleven included studies reported RI in a low and high hormone phase . RI was p = 0.77, I2 = 57.5%].Five studies reported RI with HRT was 1 ± 3% lower in the high hormone phase compared to the low hormone phase. Of these studies, four were suitable for inclusion in the meta-analysis with two studies reporting outcomes in three vessels, resulting in eight cohorts in total. No effects were found in RI between a high and low hormone phase [−0.00 ; n = 3) and pregnancy (n = 2), respectively. One study investigated changes in RI with ovarian hyperstimulation, reporting a 29% lower RI during high hormone phases compared to low.RI was 2 ± 3% and 12 ± 13% higher in the high hormone phase when looking across menstrual cycle  was 1% lower in the high hormone phase as compared to the low. Comparing pre- to post-menopausal women, CVR  was 7% higher in pre-menopausal women.Two studies examined CVR using COFour studies reported CA measures . Two stuTo the best of our knowledge, this is the first systematic review and meta-analysis to examine the interaction between brain vascular function and changing ovarian sex steroid hormones. This review identifies the current gaps in the literature and provides a clear basis from which future research can be established. Most commonly, included studies examined the effects of HRT or pregnancy using either PI or CBF as a measure of brain vascular function. The main outcome from the meta-analyses was that women undergoing HRT had a significant reduction in PI compared to post-menopausal women not on HRT. However, CBF and RI were found to have no changes with HRT.The following discussion will assess the outcome measures examined in this review in the context of cerebrovascular health and function across the different hormone groups reported.The HRT-PI meta-analysis indicated that administration of HRT improved  PI in post-menopausal women when compared to post-menopausal women not receiving HRT. This is consistent with previous studies that have shown increases in PI positively correlate with time elapsed since menopause in women not on HRT . CVR is an indication of the vasodilatory reserve capacity  reported hormone levels. Thus, it was not possible to formally compare changes in cerebrovascular function to changes in absolute hormone levels, levels which covered a wide range. For example, plasma progesterone levels during the “high hormone phase” of pregnancy  is 150 ng/ml as compared to the high hormone phase of the menstrual cycle , which is 25 ng/ml Elliott, . ReportiIn order to help address the considerable heterogeneity observed in HRT studies, future studies should consider time since menopause and/or time on HRT when recruiting participants. Recording and reporting of this information will allow for assessment of its impact as a moderating factor for the effects of HRT on cerebrovascular function. Additionally, further research should examine the importance of timing, and whether cerebrovasculature benefits occur if HRT is initiated closer to the onset of menopause.in-vitro fertilisation (IVF) and the effect of supraphysiological changes in ovarian sex steroid hormones on cerebrovascular function. Furthermore, only two studies investigated changes with oral contraceptive use. A recent NHS England report . In fact, both duration of the CO2 stimulus and the timepoint used for analysis has recently been shown to significantly alter CVR values  there can be multiple modes of assessment  and therefore a moderate risk of bias. In fact, only some HRT studies were categorised as being of a high level of evidence due to the often clinical-based setting of these studies and the research question being frequently suited to a randomised controlled trial design. It is important to consider the differing quality of evidence across hormone groups when interpreting the results of this review.The substantial heterogeneity reported within hormone groups should also be considered. The meta-regression performed on HRT studies reporting PI and included in the meta-analysis were unable to identify the moderators driving this heterogeneity. Meta-regression could not be performed in those studies reporting CBF and RI due to the low number of included studies.This review did not exclude studies based on country or location, and as a result confounding factors such as dietary behaviours or cultural lifestyle differences may account for some of the heterogeneity seen. For example, phytoestrogens, evidenced to cause increases in CBF . Despite this, this review provides a foundation for future research through the clear identification of gaps in the current literature. Future research in ovarian sex steroid hormones and cerebrovascular function should aim to improve the consistency and generalisability of findings through reporting of hormone levels and implementation of standardised methodology to assess cerebrovascular function.The original contributions presented in the study are included in the article/Conceptualisation and study design were carried out by BS, SL, and RL. Literature searches and data analysis were carried out by BS, RD, and SW. All authors contributed to the drafting and critical revision of the work.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.


Even several thousands of DNA lesions are induced in one cell within one day. DNA damage may lead to mutations, formation of chromosomal aberrations, or cellular death. A particularly cytotoxic type of DNA damage is single- and double-strand breaks . In this work, we followed DNA conformational transitions induced by the disruption of DNA backbone. Conformational changes of chromatin in living cells were induced by a bleomycin (BLM), an anticancer drug, which generates SSBs and DSBs. Raman micro-spectroscopy enabled to observe chemical changes at the level of single cell and to collect hyperspectral images of molecular structure and composition with sub-micrometer resolution. We applied multivariate data analysis methods to extract key information from registered data, particularly to probe DNA conformational changes. Applied methodology enabled to track conformational transition from B-DNA to A-DNA upon cellular response to BLM treatment. Additionally, increased expression of proteins within the cell nucleus resulting from the activation of repair processes was demonstrated. The ongoing DNA repair process under the BLM action was also confirmed with confocal laser scanning fluorescent microscopy. In every single cell, even several tens of thousands of DNA lesions occur each day . SeveralDNA lesions may appear spontaneously or can be induced by various physicochemical factors including ionizing radiation ,7,8, freDNA conformation plays a crucial role in DNA susceptibility to damage formation and repair . Under pIn this article we report on conformational transition of DNA in living cells resulting from pharmacologically induced strand breaks. DNA damage was induced in HeLa cells treated with various concentrations of bleomycin. Chemical changes occurring in the cell in response to drug treatment were detected with the Raman micro-spectroscopy. To reduce dimensionality of spectroscopic data and extract the most important information, we applied multivariate data analysis. Raman maps of individual HeLa cells were analyzed with Hierarchical Cluster Analysis (HCA), Non-negative Matrix Factorization (NMF), and Principal Components Analysis (PCA) algorithms. Additionally, for spectra attributed to cellular nuclei (after HCA clustering of Raman maps) we performed PCA to follow concentration-dependent and incubation time-dependent spectral changes induced via BLM. The ongoing repair processes in response to chemical treatment were confirmed with fluorescence imaging. Specific fluorescent markers were used to visualize the presence of H2A.X histone phosphorylation, which is a hallmark of genetic material repair see  19,20].,20.19,20In the presented paper, we follow the response of HeLa cells to bleomycin treatment. Detection of molecular changes of DNA in living cells require high chemical selectivity, which is provided by Raman spectroscopy. This approach allows to carry out experiments with samples immersed in liquid, and thus, to study of living cells in their native environment . Raman mMethods of vibrational spectroscopy, in particular Raman hyperspectral imaging, provide multidimensional data. Appropriate interpretation of the obtained data requires reduction of its dimensionality. Application of a multivariate data analysis ensures reduction of data dimensionality and what is more allows extraction of useful information regarding the structure of data set, spectral similarity and variability.Sub-micrometric spatial resolution of acquired Raman maps enabled to distinguish cellular organelles such as nucleus and nucleolus and to separately analyze DNA damage occurring in these structures. HCA was applied in order to divide spectra acquired from the cell into groups, that could be classified as separate organelles. HCA  is a metHyperspectral maps of HeLa cells were independently analyzed with NMF  and PCA −1, which corresponds to water distribution.In this study, NMF analysis was applied to discover the sparse and meaningful features from the data, characteristic for each map component, including nucleic acids, lipids, proteins, and water. In comparison to HCA, NMF demonstrates main components of the Raman spectra from collected maps. Each of the presented components corresponds to different chemical composition present in particular regions of the cell . In contrast to HCA, NMF allows following spectral changes easier, for example in DNA, by direct comparison of DNA-related components of Raman maps acquired from various cellular samples. We presented three main components of spectra acquired from each individual HeLa cell, and visualized as NMF maps. The first component corresponds to cellular nucleus, while the second one is related to lipid-rich cytoplasmic structure. The last component visualized the distribution of O-H bending at 1643 cmHCA and NMF results are presented in The analysis of spectral maps was additionally performed with PCA. The PCA is a linear transformation method that outlines the data into a new orthogonal space described by the axes of Principal Components (PCs) ,29,30,31PCA enabled highlighting spectral differences between various regions of individual cells. PCA focuses on variables with strong correlation allow grouping both positively correlated and negatively correlated components together. On the other hand, NMF finds patterns with the same direction of correlation. Therefore, NMF allows efficient extraction of components associated to individual biomolecules while PCA visualizes rather their combinations by distributions of positively and negatively correlated loadings .−1, is visible in the 3rd loading plot for control and 2nd loading plot for bleomycin treated cells (For each cell we decided to present three main PCA components of the acquired Raman images. The results are presented in the ed cells . These ls(PO2−) is demonstrated since the spectral position of this band is one of the main spectral markers of the DNA conformation. Moreover, second derivatives of NMF loadings are presented in A detailed analysis of bleomycin-induced changes in the DNA backbone was also performed. To avoid baseline influence and clearly demonstrate bleomycin-induced conformational changes, second derivatives of the averaged Raman spectra from HCA clusters attributed to cell nuclei were calculated and compared. A comparison of the second derivatives of averaged spectra acquired from control group and cells treated with various concentrations of BLM is presented in Fluorescence imaging was performed to confirm repairing processes of chromatin in cell nucleus after the induction of DSBs with bleomycin. To visualize chromatin (in the whole areas of cellular nuclei) DAPI staining was applied. The applied fluorescence dye binds to phosphorylated H2A.X histone, which allows a direct visualization of DNA repair focal points ,20. CellTo achieve the highest possible spatial resolution, the experiment was performed using the confocal laser scanning microscopy (CLSM) system. Examples of fluorescent images of stained fixed HeLa cells are presented in In this part of the work, the Principal Component Analysis (PCA) was performed as well to determine the effect of bleomycin on the cellular genetic material. In order to investigate effect of bleomycin on cellular chromatin, several models of PCA were performed on Raman spectra from the nuclei of at least three cells from different samples. These spectra were separated from the hyperspectral images through the previously used hierarchical cluster analysis (HCA). To visualize spectral changes resulting from the application of various bleomycin concentrations and different incubation times, several models of PCA were applied. For monitoring a concentration-dependent effect of BLM on cells, we analyzed spectra acquired from the cells treated with various concentrations of BLM with a single selected incubation time: 24 or 48 h. Additionally, to follow incubation time-dependent effect, we applied three other PCA models, each one for the selected BLM concentration. The results demonstrating the dose-dependent analysis (3D scores plot and loading plots) are shown in −1 [−1 to 1350 cm−1 [2, CH3) at 1450 cm−1 [2, CH3) band, in comparing to the spectra extracted from the nucleus region. In addition, the Phe band had similar intensity in the spectra of cellular nuclei and some cytoplasmic areas (cyan). This observation indicates high concentration of lipids and proteins suggesting the presence of lipid droplets [s(PO2−) at 1098 cm−1 [−1 [The applied data analysis, specifically HCA, allowed to demonstrate the spatial location of main cellular compounds including nucleus, nucleolus, cytoplasm, and membrane edge see b,c. The −1 ,34, amid350 cm−1 , or δ vibrations are higher in the spectra acquired from nucleoli. In case of bleomycin-treated cell, intensities of Phe and amide III bands from the whole nuclei region are enhanced in comparison to the bands from cytoplasm. This indicates high protein expression in nuclei of cells treated with BLM. The high protein content is likely related to synthesis of enzymes, participating in the ongoing repair of DNA damage [HCA performed on the Raman hyperspectral map of the cell treated with 150 µM BLM allowed nucleolus (yellow cluster) to be spatially localized. The reason of that may be the cell was stopped at G1 phase, due to G1/S DNA damage checkpoint . High prA damage .2, CH3 bands in the central region was observed. This might indicate condensation of lipid droplets and formation of apoptotic bodies [The separation of cellular organelles is not clearly visible at the typical map acquired from the early apoptotic, spheroidal cell, which was incubated with 500 µM bleomycin for 24 h . This isc bodies ,44.−1 [2 and CH3 deformation at 1450 cm−1 [−1 was dominant [The second statistical approach to spectral maps consists of NMF analysis. The first NMF component, which corresponds to nucleus demonstrates relatively high (in comparison to other components) intensity of the bands from nucleic acids such as the symmetric stretching of phosphate at 1098 cm−1 ,34. The 450 cm−1 ,35,37. T−1 in the spectra of control cells. This spectral position indicates B-DNA conformation [−1 was observed, indicating the partial conformational change from B-DNA to A-DNA. This conformational change is a hallmark of DNA repair processes [The analysis of bleomycin-induced changes in the DNA backbone  enabled ormation . In the rocesses ,16,46,47−1 for control cells to 1100 cm−1 for 150 µM BLM-treated cell and 1102 cm−1 for apoptotic cell were observed. This result indicates the conformational change from B-DNA to A-DNA, due to cellular repair processes [A comparison of second derivatives of NMF loadings corresponding to nucleic acids is presented in rocesses ,46,47. NFluorescence microscopy imaging confirmed activation of DNA repair process induced by BLM treatment, which was not detected in control cells. Imaging of cells incubated with the lowest studied concentration of bleomycin 50 µM) enabled to observe a fluorescence from phosphorylated histones, visible as foci . Similar µM enabl2, CH3 at 1450 cm−1 [−1 [−1 [PCA was performed on the population of Raman spectra acquired from cellular nuclei area to provide chemical changes related to bleomycin-induced DNA damage. 450 cm−1 ,35,37, acm−1 [−1  and the  [−1 [−1 ,34. The  [−1 [−1 . However−1, which we attribute to random coils [−1 attributed to β-sheets and β-turns [PC1 also indicates a change of the spectral shape in the range of the amide I as presented in om coils . This ba β-turns  is more  β-turns .−1 to 1750 cm−1 corresponded to vibrations of water molecules [−1 may indicate a loss of water within the cell nuclei due to ongoing apoptosis [It is worth noting, that the spectral region from 1550 cmolecules . Therefopoptosis ,43.−1 and 1344 cm−1, as well the band at 1445 cm−1 related to deformation of thymine, are dominative in loadings of the second principal component [−1, which corresponds to νs(PO2−) in A-DNA [s(PO2−) band was observed in control group at 1085 cm−1 indicating B conformation of DNA, as expected, please see loading plot corresponding to PC2 presented in The first principal component distinguished the recorded spectra mainly due to the changes in protein concentration within the nucleus. The separation along PC2 was also observed. Significant part of the entire population of spectra from bleomycin-treated cells are located on the negative side of the PC2 as can be seen in omponent . This suin A-DNA ,16,46. T−1, amide I at 1661 cm−1, and Phe at 1004 cm−1 [Clustering along PC3 was less evident for spectra acquires from cells after 24-h bleomycin-treatment. Only spectra from the control group were well separated. The loading plot of PC3, similarly to PC1, indicated the separation of spectra due to differences in bands from proteins, including amide III band at 1340 and 1270 cm004 cm−1 .Similar PCA results as those obtained for the spectra acquired from cells incubated with BLM for 24 h were also obtained for the second applied incubation time—48 h. The shape of all three loading plots displays a relatively high level of similarity confirming that the same bands are responsible for the clustering visible on the score plots. However, score plots obtained for these two models are slightly different. In both models, the cluster of control spectra is well separated. However, no clear separation along PC1 for spectra acquired from bleomycin-treated cells was observed. The increase of incubation time to 48 h did not result in additional biochemical changes of proteins upon BLM treatment.s(PO2−) band is at 1104 cm−1 indicating A-DNA conformation [s(PO2−) in these spectra is observed at 1085 cm−1 confirming B-DNA conformation. The observed shift of the phosphate bands indicated partial conformational transition from B- to A-DNA in the cells treated with all of the applied doses of BLM.The loading plot of PC2, which explains that the separation along PC2 is mainly related to spectral position of phosphate bands from DNA backbone and also vibrations of DNA bases including guanine and thymine. In the spectra of BLM-treated cells, that are located at the negative side of PC2 the νormation ,16,46. A2, CH3 at 1450 cm−1 [−1 [−1 [The three other models of PCA were applied to follow time-dependent molecular changes for each applied BLM concentrations separately . A clear450 cm−1 ,35,37, acm−1 [−1  and Phe  [−1 [−1 ,34), con [−1 [−1 . Again, PCA calculated for the control group and the concentration of 150 µM gave very similar results as the previous model investigating an influence of 50 µM BLM on HeLa cells. However, looking at the separation along PC1 and PC3, one may notice that the spectra acquired from cells incubated for 24 h are partially clustered with the control spectra and partially with the spectra of cells incubated for 48 h. This suggests that the DNA repair process does not take place in all cells simultaneously. According to the literature, several factors may influence the time scale of DNA repair process, including phase of cell cycle  and leveThe last PCA model was performed for control spectra and spectra acquired from the nuclei area of cells treated with 500 mM of BLM. The separation along each PCs was more evident. This suggests significant time-dependent biochemical changes induced upon cellular response to the applied concentration of the drug. Similar to the results of previous models loading plots of PC1 and PC3 indicate that separation along these components is related to changes of the molecular structure of protein and peptides and their expression. PC2 loading plot indicates that the observed clustering of spectra is also associated with differences in DNA conformation, that is expected due to apoptosis, as observed elsewhere ,51.2.In this study the immortalized cell line HeLa  was used. Cells were cultured in Dulbecco’s Modified Eagle’s Medium–high glucose  buffer with addition of 5% BSA and 1% antibiotics (penicillin and streptomycin). Incubation was carried out at 37 °C with 5% COCells were subcultured using the following procedure. In the first step, cultured cells were washed with DMEM buffer (without FBS and antibiotics), and next cells were treated with 0.25% trypsin with EDTA for 3 to 5 min until all cells were detached. Then, trypsin in a cell solution was deactivated with adding full DMEM HG medium (with additions).Samples for Raman micro-spectroscopy experiment were prepared by seeding cells on silicon substrate with metallic coating (gold and titanium), previously covered by poly-L-lysine. Cells were incubated with bleomycin for 24 or 48 h. At least 3 cells were measured for each parameter set .Prior to the fluorescence imaging experiment, cells were plated in a 35 mm glass bottom dishes with thickness 0.16–0.19 mm designed for high resolution imaging (Cellvis) and incubated with a bleomycin under analogous conditions (bleomycin concentration and incubation time) as in experiments involving Raman imaging. Cells were fixed with 4% formaldehyde solutions  for 10 min, permeabilized for 10 min in 0.5% Triton X-100 . Fixed cells were incubated in a PBS buffer with 3% BSA  for 45 min, then stained for anti-phospho Histone H2A.X  for 35 min. For nucleus staining, cells were additionally incubated with DAPI  for 5 min.−1) with the spectral resolution of 2 cm−1. An exposure time for each pixel was 6 s (2 accumulations with 3 s acquisition). Mapping step size in x-y directions was between 0.5–0.7 µm (dependent from cell size). Raman mapping with the confocal system allowed registration of spectra from well-defined volume at each pixel of the acquired maps. This allowed to create a hyperspectral images of cells [Measurements were performed using a Horiba LabRam confocal micro-spectroscopy system  equipped with a green laser (λ = 532 nm), electron-multiplying charge-coupled device (EM-CCD) cooled to −70 °C, and water immersion 60× 1.0 NA objective . During spectra acquisition, the cell culture was immersed in physiological saline solution. Spectra were acquired in the fingerprint spectral region  using an oil immersion 40× 1.4 NA Plan-Apochromat objective. The microscope was driven by Zen Black software . DAPI and Alexa Fluor 488 dyes were excited with 405 nm diode laser and 488 Ar laser, respectively.The preparation protocol of bleomycin solution was adapted from .To initiate cleavage events of DNA backbone, bleomycin needs to be transferred into so called “activated” bleomycin, which requires the presence of ion metal, usually Fe(II) or Cu(I), and oxygen. In our work, bleomycin sulfate  was activated by adding ammonium iron (III) sulfate dodecahydrate . The mass ratio of bleomycin to iron salt was 1:1.1. The resulting solution was neutralized by adding 0.1 M NaOH. The concentration of the obtained bleomycin solution was 10 mM. For incubation with the cell culture, the prepared BLM solution was further diluted in DMEM to obtain the following BLM concentrations: 50 µM, 150 µM and 500 µM.−1, unique for biological molecules.Prior to multivariate statistical analysis, specifically Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA) and Non-negative Matrix Factorization (NMF), the Raman spectra were baseline corrected , smoothed  and normalized  using MATLAB R2019b software . When necessary, a cosmic ray removal procedure was applied. The analysis was performed in the spectral range of 1800–900 cmMicroscopic images analysis was performed using Fiji ImageJ environment ,58.In the presented paper, the cellular response to bleomycin-induced DNA strand breaks in living HeLa cells was investigated. Raman micro-spectroscopic mapping of individual cells was applied to follow molecular changes induced upon the cellular response to bleomycin treatment . This enabled us to identify spectral markers of DNA damage repair and apoptosis. The dimensionality of the obtained hyperspectral maps was reduced using several methods of multivariate data analysis. An application the two independent experimental approaches such as molecular spectroscopic mapping and fluorescent microscopy supported with multivariate data analysis enabled to achieve a complementary overview of molecular modifications in cells responding to bleomycin treatment. The applied comprehensive approach was confirmed to be an efficient tool in research on molecular modifications of the DNA structure exposed to the influence of damaging factor. This approach could be applied in further studies on structural modifications of DNA or other cellular components under the action of various external factors.s(PO2−), which indicates the change in DNA conformation.HCA allowed to extract spectra from cellular organelles including nuclei and analyze molecular changes, induced in chromatin upon DNA repair and apoptosis. For the each acquired spectral map we demonstrated three main components of NMF and PCA: related to the area of the nucleus, cytoplasm and surrounding medium. Comparison of the NMF components plots corresponding to cell nucleus showed blueshift of the νTo observe systematic changes caused by bleomycin treatment, PCA was performed on the population of Raman spectra distinguished by HCA. Several groups of spectra were selected and compared to separately follow spectral changes dependent on bleomycin concentration and incubation time.The application of the three various statistical approaches allowed to compare and discuss their advantages and limitations in analysis of hyperspectral Raman maps. NMF provided the most straightforward visualization of conformational transition induced by bleomycin. On the other hand, PCA classified spectra extracted by HCA and pointed marker bands of cellular response to bleomycin treatment.A strong correlation was observed between the increasing concentration of bleomycin and protein expression in the nucleus area. This observation may be related to the activation of DNA repair processes. The conformational transition from B-DNA to A-DNA resulting from strand breaks (SSBs and DSBs) of DNA induced by bleomycin was observed after 24 and 48 h of treatment with 50, 150 and 500 µM of BLM. Moreover, the process of DNA restoration to its native form after extended incubation  was demonstrated. The activation of repair processes was additionally confirmed by fluorescence microscopy. DNA repair foci were observed as histone gammaH2AX phosphorylation—a hallmark of DNA repair process. The number of DSBs being under repair increased significantly with bleomycin concentration.Bleomycin treatment with the highest applied concentration led to cell apoptosis, which was detected as characteristic spectral changes indicating water loss, increase of cellular material density and formation of apoptotic bodies. Additionally, a hallmark of cell death, specifically chromatin fragmentation was observed with fluorescence imaging.


Heart failure with preserved ejection fraction (HFpEF), affected collectively by genetic and environmental factors, is the common subtype of chronic heart failure. Although the available risk assessment methods for HFpEF have achieved some progress, they were based on clinical or genetic features alone. Here, we have developed a deep learning framework, HFmeRisk, using both 5 clinical features and 25 DNA methylation loci to predict the early risk of HFpEF in the Framingham Heart Study Cohort.P = 0.632), which outperformed models with clinical characteristics or DNA methylation levels alone, published chronic heart failure risk prediction models and other benchmark machine learning models. Out of them, the DNA methylation levels of two CpGs were significantly correlated with the paired transcriptome levels . Besides, DNA methylation locus in HFmeRisk were associated with intercellular signaling and interaction, amino acid metabolism, transport and activation and the clinical variables were all related with the mechanism of occurrence of HFpEF. Together, these findings give new evidence into the HFmeRisk model.The framework incorporates Least Absolute Shrinkage and Selection Operator and Extreme Gradient Boosting-based feature selection, as well as a Factorization-Machine based neural network-based recommender system. Model discrimination and calibration were assessed using the AUC and Hosmer–Lemeshow test. HFmeRisk, including 25 CpGs and 5 clinical features, have achieved the AUC of 0.90  and Hosmer–Lemeshow statistic was 6.17 (Our study proposes an early risk assessment framework for HFpEF integrating both clinical and epigenetic features, providing a promising path for clinical decision making.The online version contains supplementary material available at 10.1186/s13148-022-01232-8. Chronic heart failure (CHF), characterized by disorders of myocardial energy metabolism and metabolic remodeling, is widely studied by society because of its high morbidity and mortality . It is cAlthough risk prediction in CHF has been extensively studied, there are still inadequacies and limitations. Sadiya S. Khan et al. developed a 10-year risk model  but did not discuss the pathogenesis and subtypes of CHF, and the model lacked the ability to learn implicit feature interactions . Some sthttps://framinghamheartstudy.org/). It began in 1948 and has undergone six large sampling surveys [The Framingham Heart Study (FHS) cohort is a population-based, multigenerational, and longitudinal cohort study to identify common factors that contribute to cardiovascular disease  and Extreme Gradient Boosting (XGBoost)-based feature selection, and Factorization-Machine based neural network (DeepFM)-based recommended system to learn the interactions of nonlinear features automatically . Our preParticipants who were diagnosed as free of CHF at baseline  in FHS Offspring cohort, with a clear disease diagnosis within 8 years (HFpEF or no-CHF), with complete medical information, with qualified DNA methylation data were eligible for inclusion Fig. .Fig. 1OvThe early prediction observation window was defined as 8 years from baseline. During the 8 years’ follow-up, 91 HFpEF events occurred and 877 participants did not experience heart failure, which is referred to as case–control status. The whole blood samples for DNA methylation, gene expression profile and electronic health record (EHR) data were measured from FHS offspring participants who attended the eighth examination cycle.P > 0.05. When missing values were less than 20%, missing variables were imputed using nearest neighbor averaging method. If the Spearman’s correlation between two clinical features was greater than 0.8, the clinical feature with a smaller Spearman’s correlation (i.e. less correlated with HFpEF) was discarded . Detailed information on the removal of clinical features is provided in Materials and Methods Section 1 of the Additional file Following thresholds were applied to remove incomplete and non-significant clinical features in training set: missing sample > 20%, two-group comparisons of Chi-square test/Mann–Whitney U test β-value, which ranges from 0 (unmethylated) to 1 (fully methylated). DNA methylation array was normalized using the beta mixture quantile dilation algorithm by ChAMP package [P < 0.05.Using Infinium HumanMethylation450 BeadChip (Illumina), the methylation level of each cytosine-phosphate-guanine (CpG) locus is represented by the  package . DNA metIn the FHS offspring cohort, whole blood gene expression profiles were obtained from the Affymetrix Human Exon 1.0 ST GeneChip platform. Gene expression microarray data analysis was implemented through linear model fit and empirical bayes statistics for subsequent calculation of Pearson's correlations between gene expression profiles and DNA methylation for paired samples.Feature selection was performed in the training set using LASSO  and XGBoThe R package “xgboost” was used to perform the XGBoost. After parameter adjustment, we finally set the learning rate to 0.5. the minimum loss reduction is 0.5, the maximum depth of the tree is 3, the minimum sum of the required instance weights (Hessian) of the children is 2, and the maximum depth of the tree is 3.yFM is the output of the FM component, and yDNN is the output of the deep component. The FM component and deep component are factorization machine and feed-forward neural network, which are used to learn low-order feature interactions and high-order feature interactions. The output of FM is,This study superimposed DNA methylation and EHR features to form a unique matrix. DeepFM algorithm was used to build an HFpEF risk prediction model. DeepFM extracts DNA methylation and EHR features and learns the hidden feature combinations behind these features . DeepFM 2. The output of DNN is,H| is the number of hidden layers, al) using ReLU as the activation function."logloss", which measures the error between the input and the output, was chosen as the objective function. To control overfitting, we added an L2 regularization penalty on the activities of the nodes, and the parameter was set to 0.0001. To optimize the neural network, we used batch normalization and weight decay. The embedding size, batch size and decay were set to 8, 300 and 0.9, respectively. To train the DeepFM algorithm, we used Adam as the optimization algorithm and the learning rate was set to 0.0001, with 400 epochs and 60% dropout. The performance of the DeepFM models was assessed using bootstrapping method. The samples left in the training set will be approximately 63.2% of the original data set, and the remaining samples (36.8%) are used as the validation set . All netNine machine learning algorithms including linear Support Vector Machine, Bagging, Random Forest, RUSBoost, EasyEnsemble, GradientBoosting, XGBoost, LogitBoost, and Mixed Logistic Regression, were used to perform the comparisons. Model parameters are listed in Additional file We evaluated HFmeRisk and the benchmark model using the following criteria: area under the curve (AUC), sensitivity, specificity, and accuracy.To estimate the clinical utility of the HFmeRisk model, decision curve analysis (DCA) was performed using the R package rmda to calculate the net benefit of the range of threshold probabilities in the training and testing sets. The threshold probability of DCA is where the expected benefit of prediction is equal to the expected benefit of avoiding prediction. DCA is a trade-off between false positives and false negatives and is mostly used to weigh medical intervention strategies and can be used to screen for beneficiaries and to evaluate the practice value of the model as a whole.We used the HumanMethylation450 BeadChip array annotation file and Enhancer linking by methylation/expression relationships tool  to obtaiP is calculated using a hypergeometric test. All statistical tests were 2-sided, and P < 0.05 was considered significant. The adjusted P is conducted using Bonferroni corrected. All data analysis and visualization were performed using R 3.5.0 (http://www.r-project.org/) and Python 3.7.3 (https://www.python.org).Two-group comparisons of categorical and continuous variables were performed by using the Chi-square test and the Mann–Whitney U test, respectively. The Pearson’s correlation between CpG and differentially methylated genes (DMGs) is driven mainly by case–control status. Hypergeometric test was used in gene set pathway analysis. In biology functional analyses, the The clinical information and DNA methylation data of FHS participants (Offspring Cohort Exam 8) were used to develop a HFpEF risk prediction model. After excluding samples with censoring, with unqualified DNA methylation, and lack of medical information, a total of 984 eligible participants were obtained as the final samples with complete information over a follow up of 8 years Fig. . Among tAfter data pre-processing, we obtained 318 DMPs and 25 clinical characteristics , 0.78 (95% CI 0.73–0.82), and 0.65 (95% CI 0.62–0.67), respectively . However, we combined 26 age-related CpGs mentioned in Hannum G et al. study and 5 clinical features of HFmeRisk model  together and obtained AUC of 0.858 in the testing set  performed better than the Cox regression model (C statistic = 0.85). Calibration was also assessed by comparing predicted and observed risk (Hosmer–Lemeshow P = 0.199). The calibration curves for the possibility of 8-year early risk prediction of HFpEF displayed obvious concordance between the predicted and observed results . For “EHR + RNA” model and “EHR + microRNA” model, we used the consistent feature selection and modeling approach with the HFmeRisk model  were used to measure the results . The gen. proposed a 4-year risk appraisal model (using 9 EHR features) to assess the risk of CHF by gender in the FHS cohort using a mixed logistic regression algorithm [. described 10-year risk equations for CHF (using 10 EHR features) with a C-statistic of 0.71–0.87 in the validation set, and Edward Choi et al. established an early detection model  of CHF with an AUC < 0.88 in the testing set [Furthermore, we compared the performance of the HFmeRisk model with that of published CHF risk prediction models. William B. Kannel et allgorithm . Since wting set . Their AGRM4  and SLC1A4 , respectively, in HFpEF participants, while the association among normal participants were not obvious  [CYP2E1/cg21024264) [MRI1/cg25755428, GRM4/cg10083824, and GRIK4/cg06344265) [SLC1A4/cg03233656) [GARS/cg21429551) [Next, we investigated the biological function of the 25 CpGs in HFmeRisk model. Approximately 2/5 of them were located in the promoter region . Most of the CpG loci were located in CpG islands or the “Open sea” and located on 17 genes and 8 intergenic regions in total Table 5845376) , the syn1024264) , the ami1429551)   [SLC1A4, ZBTB20, and SLC25A2) [SLC1A4 and DLGAP1) [SLC25A2 and SLC1A4) [ZBTB20 and SLC25A2) [ZBTB20) [DLGAP1) [RHOBTB1) [CYP2E1) [Furthermore, we explored the relationship of the genes twenty-five CpGs located with disease or trait by intersecting with published GWAS results. All these genes were reported to be associated with risk factors for heart failure such as BMI ( ZBTB20) , systoliSLC25A2) , ejectio DLGAP1) , atrial  SLC1A4) , coronarSLC25A2) , type 2 [ZBTB20) , cardiac[DLGAP1) , diastolRHOBTB1) , gout (C[CYP2E1) , implyinP = 0.632 in the testing set. HFmeRisk leverages the recommendation system-based deepFM algorithm and feature selection-based lasso and xgboost algorithms, and learns the hidden feature combinations behind these features to provide innovative insights into early risk assessment for HFpEF. The HFmeRisk model provides a implications to further facilitate guiding clinical risk assessment at the individual level.In this report, we established and validated the HFpEF early risk prediction model HFmeRisk using the FHS cohort. HFmeRisk evaluated the early risk prediction of HFpEF from an epigenetic perspective  and environmental exposures perspective . The HFmeRisk model demonstrated excellent discriminatory and calibration power in the early risk of HFpEF with an AUC of 0.90 (95% CI 0.89–0.90) and Hosmer–Lemeshow statistic was 6.17, with ., Sadiya S. Khan et al. and Edward Choi et al. model [.) and the DeepFM model of this study. Although the mixed logistic regression model performed well in terms of AUC (AUC = 0.83), the DeepFM model still achieved the best performance (AUC = 0.90).It is worth noting that the HFmeRisk model (EHR + DNA methylation) outperforms the “EHR only” and “DNA methylation only” models, which supports the contribution of epigenetics to the early diagnosis model of HFpEF, and the addition of epigenetic features allows the prediction model to achieve better prediction, confirming that DNA methylation provides innovative ideas for further research on the development of HFpEF .The HFmel. model , 33, 34.Additionally, 25 CpGs in the HFmeRisk model have key functions related to intercellular signaling, interaction and energy metabolism. This may suggest that intercellular signaling, interaction and energy metabolism were subjected to epigenetic regulation and were involved in driving lesion progression and the development of HFpEF. These results may provide clues to pathways related to the regulation of heart failure development by 25 DNA methylation loci. Five clinical variables included in the HFmeRisk model, including age, diuretic use, BMI, albuminuria, and serum creatinine, were all closely related to the heart failure. It is well known that HFpEF and age are closely related, the risk of HFpEF increases sharply with age . SimilarWe also obtained the significantly correlation between 2 CpGs and its DMGs expression levels. Because DNA methylation and clinical features can describe disease states in different dimensions, they may be internally correlated. In addition, Framingham Offspring cohort contains not only DNA methylation data, but also RNA and microRNA data, and we have done the similar analysis separately. Both the "EHR + RNA" model and the "EHR + microRNA" model showed less good results than the HFmeRisk model. MicroRNAs have been reported to have some predictive value for HFpEF , offerinThe most important feature of the DeepFM algorithm is its ability to learn the hidden feature combinations behind the input features. Simple feature stitching cannot achieve the deep integration of internal features, so the DeepFM model is very reasonable for the integration of multiomics data. We also showed that the DeepFM model performs better than the benchmark machine learning models. The bootstrapping method used in this study is uniform sampling with put-back from a given training set, which provides a good idea for solving the small subsample test evaluation problem.In addition, a comprehensive evaluation of the HFmeRisk model is presented in this paper. The sufficient predictive performance of HFmeRisk was demonstrated by evaluating the number of features, and the sample size of the training set. The predictive power of age was demonstrated by testing age-related DNA methylation sites, but age-related DNA methylation sites did not give better results than HFmeRisk. Adversarial validation was used to test whether the distributions of the training and testing sets were consistent to assess whether the training and testing subjects were sufficiently similar in terms of clinical parameters.In the future, we will consider both biological mechanism validation and model optimization. In aspect of biological mechanism research, we will consider adding other data, such as family information, transcriptomic and genetic data, to find the real reason why DNA methylation acts as a predictor from the perspective of expression Quantitative Trait Loci and methylation Quantitative Trait Loci analyses which will contribute to mechanisms of disease pathophysiology, and to provide evidence for functional effects for HFpEF and insight into genetic mediated epigenetic response mechanisms that modulate epigenetic effects in the whole blood and risk for HFpEF. We also will focus on epigenomic and enhancer-gene remote interactions yields new perspectives on disease-associated loci, which will also be important for understanding the dynamic interplay between epigenome in HFpEF. Another, considering that mechanisms such as fibrosis and inflammation are involved in the development of heart failure, single-cell transcriptome mapping of non-myocytes and leukocytes in the heart of adult heart failure patients is obtained using single-cell transcriptome sequencing data, which will provide theoretical basis for predictive models and new therapeutic approaches for HFpEF patients . In aspeCHF is a severe or advanced manifestation of various cardiac conditions with high mortality and readmission rates . TherefoOur research still has some limitations. We analyzed DNA methylation and RNA expression in whole blood, which may differ from the values in heart tissue samples. However, it is unrealistic to obtain tissue samples in the prospective study. In the future, we will consider providing proof of consistency between blood and target tissue results. The current study does not consider the censoring problem, and the censored samples should be retained as much as possible. In the future research, we will further explore the censoring problem, such as how to deal with the censoring problem in machine learning modeling, etc. The FHS cohort includes Caucasians and a small number of East Asians, and it is unclear whether we can reproduce our conclusions in other races. Due to the limited sample size of the training and testing sets, the reliability of the results is questioned to some extent. In addition, there is no suitable external testing set to demonstrate the effectiveness of the HFmeRisk model due to the difficulty in obtaining DNA methylation data for prospective cohorts. We sought to demonstrate that the predictive power of the HFmeRisk model for HFpEF is reliable using 38 Framingham Heart Study cohort participants who did not appear in the HFmeRisk model as a simulation test, which also appeared to demonstrate sufficient predictive power of HFmeRisk (AUC = 0.82). DNA methylation was only collected at exam 8, so we were unable to evaluate longitudinal changes. The applicability of DNA methylation arrays in extensive screening may be limited by cost. After in-depth characterization screening, sequencing may have the greatest advantages because it is cost-effective and can be used to calculate the risks for other diseases. Compared with clinical characteristics, DNA methylation is less effective in enhancing the model. For the analysis of DNA methylation, the results of differentially methylated region and differentially methylated block analysis can be considered subsequently, and large segments of methylation regions are more convincing than single methylation sites. In addition, although AUC is currently considered to be a standard approach for assessing the accuracy of predictive distribution models, it also has limitations. AUC is a trade-off between true positive rate and false positive rate, and AUC has limited clinically meaningful to clinicians . FinallyAdditional file 1. Supplementary materials and methods.Additional file 2. Supplementary tables.Additional file 3. Supplementary figures.


MdPDS, whose disruption leads to the albino phenotype, were pre-selected by in vitro cleavage assays. A construct was transferred to apple encoding for a CRISPR/Cas12a system that simultaneously targets two loci in MdPDS. Using fluorescent PCR capillary electrophoresis and amplicon deep sequencing, all identified GE events of regenerated albino shoots were characterized as deletions. Large deletions between the two neighboring target sites were not observed. Furthermore, a chimeric composition of regenerates and shoots that exhibited multiple GE events was observed frequently. By comparing both analytical methods, it was shown that fluorescent PCR capillary gel electrophoresis is a sensitive high-throughput genotyping method that allows accurate predictions of the size and proportion of indel mutations for multiple loci simultaneously. Especially for species exhibiting high frequencies of chimerism, it can be recommended as a cost-effective method for efficient selection of homohistont GE lines.The use of the novel CRISPR/Cas12a system is advantageous, as it expands the possibilities for genome editing (GE) applications due to its different features compared to the commonly used CRISPR/Cas9 system. In this work, the CRISPR/Cas12a system was applied for the first time to apple to investigate its general usability for GE applications. Efficient guide RNAs targeting different exons of the endogenous reporter gene  The improvement of crop plants is an urgent necessity in order to respond to global problems such as climate change and the rapidly growing world population. In this context, the use and further development of innovative breeding technologies that enable efficient and targeted plant breeding is of great interest. Since the discovery and functional understanding of the first CRISPR/Cas  system in 2012 , is now Streptococcus pyogenes Rosenbach belongs to class 2 subtype II and consists of the SpCas9 effector, a CRISPR RNA (crRNA) and a trans-activating CRISPR RNA (tracrRNA) [Prevotella and Francisella 1), which belongs to class 2 subtype V of CRISPR systems [Francisella novicida U112 (FnCas12a), Acidaminococcus spp. BV3L6 (AsCas12a), and Lachnospiraceae bacterium ND2006 (LbCas12a) and assessed for GE in eukaryotes [Nicotiana benthamiana Domin, Solanum lycopersicum L., Arabidopsis thaliana (L.) Heynh. [Citrus ×paradisi Macfad., Glycine max (L.) Merr., and Oryza sativa L. [Until now, two classes of CRISPR/Cas systems have been discovered, which were further divided into six subtypes. Class 1 CRISPR/Cas systems  require multiple effector proteins; in class 2 systems , only one single effector protein is required . The mosracrRNA) . For use systems . Differekaryotes . Furtherativa L. ,14. The phytoene desaturase gene (PDS) of Malus domestica Borkh [PDS is an essential gene in carotenoid and chlorophyll biosynthesis pathways and its disruption leads to albino and dwarf phenotypes [Malus sieversii (Ledeb.) Roem. was shown [The first study on GE in temperate fruit trees using CRISPR/Cas9 was reported in 2016, when this system was used for targeted mutagenesis of the endogenous ca Borkh . As PDS enotypes , to induenotypes , and to enotypes . Other Genotypes , minimizenotypes , reducinenotypes , or the enotypes . Recentlas shown . To our The screening and identification of mutations on target sites is a critical step in the workflow for the establishment of GE plants. Especially for GE applications in apple, a powerful detection method is necessary, as complex GE profiles and chimerism were frequently observed . In geneLbCas12a, demonstrating its suitability as novel tool for GE in apple. Moreover, comparing different methods for detection and characterization of mutations, fluorescent PCR capillary gel electrophoresis was shown to be a powerful high-throughput methodology that allows the precise prediction of the size and proportion of indel mutations of multiple loci in chimeric tissue in a single reaction.The results presented herein focused on the use of the CRISPR nuclease MdPDS represents a suitable reporter gene for in vivo GE experiments, as the knock-out of this gene leads to albino tissue [MdPDS specific crRNAs for LbCas12a  were designed and selected with the help of the CRISPR RGEN Tools software targeting exons two, five, and seven, respectively  could be obtained that possessed large stretches of albino tissue.A series of regenerates exhibited tissue or shoots with white color B, which henotype . For a sAs shown in other studies ,18, indeMdPDS target loci A (blue) and D (green), respectively  ‘Gala’ shown in From a total of 114 regenerates obtained within eleven months after transformation, 41 (36%) exhibited albino shoots. These shoots were further analyzed by fluorescent PCR capillary gel electrophoresis. Nine of them  contained genome edited alleles at both loci. GE of only one single locus was not observed.To verify results from fluorescent PCR capillary gel electrophoresis, indicating the presence of genome edited alleles for multiple target loci in a single reaction, the GE events were additionally characterized by amplicon deep sequencing.To characterize potential GE events of albino shoots on the sequence level, deep sequencing of PCR products amplified from loci A and D C was perAmplicon deep sequencing of locus D of the albino shoot 18219_a resulted in a total of 167,120 reads analyzed . Half 5D,E. For The deletion lengths of the GE events in 18219_a are consistent with the allele size differences observed by fragment length analysis. To proof this observation, 11 albino shoots that originated from five independent regenerates were investigated by the same methods. The results are summarized in Besides the coherence regarding the indel size, a second correlation was observed between the percentage of reads from deep sequencing and the percentage of total peak height , which eOverall, these comparisons between the two independent methods clearly showed that fluorescent PCR capillary gel electrophoresis produced robust results for genotyping and that the size differences from wt alleles and the percentage of the total peak height can be used to predict the type and proportion of GE events in the analyzed tissue.LbCas12a nuclease complex. No insertion of sequences at the target site was found. The deletion length of 14 different GE events of locus A ranged between 1 and 84 bp, with an average of 12.4 bp. The 27 different GE events of locus D contained deletions of 2 to 38 bp, with an average of 13.0 bp. A large deletion event between both loci, which are ~4 kb distant from each other (The sequences of loci A and D that resulted from independent GE events (different regenerates) are represented in the alignments shown in ch other , was notThe results summarized in Using fluorescent PCR capillary gel electrophoresis, the type and the proportion of wt and genome edited alleles were investigated in single shoots of one regenerate . For theFor locus D, the two GE alleles 357 and 368 were detected in each shoot investigated, suggesting an early and efficient GE of locus D on both chromosomal arms. In five out of eleven shoots, the wt allele could additionally be detected, indicating chimeric tissue. For the other six shoots (c–h), a bi-allelic mutation of locus D was demonstrated.MdPDS gene. To identify which of the MdPDS mutations at locus A and D occur together on one chromosomal arm, the whole segment of ~4.3 kb was amplified, cloned, and analyzed by Sanger sequencing. A common occurrence of allele 418 (−12 bp deletion) of locus A and allele 368 (−9 bp deletion) of locus B was identified in five clones. Two clones contained allele 426 (−4 bp deletion) of locus A and allele 357 (−20 bp deletion) of locus D. Based on the proportions of the alleles in the examined tissue, which is ~50% for each allele  could be identified, which contained bi-allelic mutations at two independent loci within the h allele , it can A. thaliana, has already demonstrated [LbCas12a  was engineered for high-efficient GE in plants [In this study, the CRISPR/Cas12a system was applied for the first time to apple, successfully demonstrating targeted mutagenesis of multiple loci in genome-edited apple shoots. As a result, the CRISPR/Cas12a system can be added to the toolbox for GE of apple, broadening its spectrum of potential applications due to the distinct features of Cas12a compared to Cas9. Different from Cas9, for which a G-rich protospacer adjacent motif (PAM) is preferred , Cas12a nstrated . Additionstrated  and the nstrated , allows nstrated ,39,40,41n plants .SpCas9 is wide and varies from 3–93%. Despite differences in the experimental designs, different parameters were also used to calculate mutation efficiencies, e.g., phenotypic markers such as the albino phenotype caused by the mutation of MdPDS or the early flowering phenotype mediated by the knock-out of MdTFL1.1. In this study, the mutation efficiency based on the albino phenotype was not calculated, because this phenotype was shown not to be a reliable marker for GE of apple when used in combination with, e.g., kanamycin for selection of transformants. As the sensitivity of non-transformed tissue to kanamycin also results in chlorosis prior to death of the tissue [MdPDS-mutation caused phenotype was not possible in our study. Using fluorescent PCR capillary gel electrophoresis, an indel mutation efficiency of 8% was observed in the performed transformation experiments. As summarized by Nishitani et al. , the rane tissue ,45, a clIn general, it is known that DSB repair mechanisms differ from species to species and in some species, deletion events are the preferred repair outcome . In prevFluorescent PCR capillary gel electrophoresis was used in this study for the detection of indels on CRISPR target sites. Multiple target sites can be analyzed in a single reaction, using different fluorescent dyes for primer-labeling. Two targets were analyzed simultaneously in this study, which can be expanded further. Using standard dye sets, up to four different targets sites can be analyzed in one reaction, which was already demonstrated . The metAll oligonucleotides used in this study as crRNA or DNA primers are listed in LbCas12a targeting exons two, five, and seven of the PDS gene (MD04G1023800) from Malus domestica  were used as parameters for crRNA design. The selected crRNAs contain a 23 bp target specific sequence  and elongation time (E) of the PCR program was set specifically for each primer pair . The PCR products were purified, eluted with elution buffer, and quantified using the NanoDrop 2000c . In vitro DNA cleavage assays were performed in a reaction volume of 30 µL using a final concentration of 30 nM EnGen LbaCas12a (Cpf1) . Cas12a was mixed with 30 nM crRNA in 1× NEB Buffer 2.1. After pre-assembly for 10 min at 25 °C, the respective PCR product (3 nM) was added and the reaction was incubated at 37 °C for 10 min. The reaction was stopped by addition of 1 µL Proteinase K  and the resulting DNA fragments were analyzed by gel electrophoresis using 1% TAE agarose gel.Guide RNAs for omestica A were deber 2019 ,53). Thesequence  and weresequence C from geAgrobacterium tumefaciens strain EHA105 [The binary vector p9oN-U10LbCpf1-Ex27 A was assn EHA105 . A prolin EHA105 . Regener2O. The PCR analyses were performed in a final volume of 10 µL using the Type-it Microsatellite PCR Kit adding the Q-solution and 10 ng template DNA. The presence of the LbCas12a gene was tested using the primer pair Cas12a-FW/REV  and the amplification of the nptII resistance cassette was performed with nptIIopt_F/R . For control, the endogenous gene MdEF1α coding for elongation factor 1α [Genomic DNA from whole in vitro shoots exhibiting the albino phenotype B was extactor 1α  was amplMdPDS target loci A and D were amplified in a PCR multiplex with fluorescent labeled primers . After denaturation at 95 °C for 5 min, capillary gel electrophoresis was performed on the Applied Biosystems Genetic Analyzer 3500xl system  using the POP-7 Polymer . The fragment length analysis was done with the Applied Biosystems GeneMapper Software 6.The  primers  using thPCR products intended for sequencing were amplified with the Phusion High-Fidelity Polymerase Kit using 1 µM of each primer (without fluorescent label), 10 ng template DNA, 1× HF buffer in a total volume of 50 µL, and 30 cycles. Using these conditions, the annealing temperature was optimized for each primer pair by gradient PCR . After purification of the PCR products, the DNA concentration was determined on the Qubit 4 Fluorometer. Library preparation and amplicon deep sequencing on the Illumina platform with a 2 × 250 bp configuration was performed by Genewiz Germany GmbH . The subsequent analysis of the sequencing data was done on the Galaxy platform  with a cMdPDS target loci (4.3 kb), was amplified with the primer pair A_FW/D_REV using the Phusion High-Fidelity PCR Kit . The PCR product was cloned into pCR-XL-2-TOPO using the TOPO XL-2 Complete PCR Cloning Kit and transformed into the One Shot OmniMAX 2 T1 chemically competent cells included in the cloning kit. Bacterial clones were selected on the LB medium containing kanamycin and analyzed for the presence of the MdPDS specific fragment by colony PCR . Sanger sequencing of plasmid DNA isolated from PCR positive clones was done by Eurofins Genomics Germany GmbH .The chromosomal fragment, including both


Despite solid wastes’ landfill disposal limitation due to recent European legislation, landfill leachate disposal remains a significant problem and will be for many years in the future, since its production may persist for years after a site’s closure. Among process technologies proposed for its treatment, microbial fuel cells (MFCs) can be effective, achieving both contaminant removal and simultaneous energy recovery. Start-up and operation of two dual-chamber MFCs with different electrodes’ structure, fed with mature municipal solid waste landfill leachate, are reported in this study. Influent (a mix of dairy wastewater and mature landfill leachate at varying proportions) was fed to the anodic chambers of the units, under different conditions. The maximum COD removal efficiency achieved was 84.9% at low leachate/dairy mix, and 66.3% with 7.6% coulombic efficiency (CE) at a leachate/dairy ratio of 20%. Operational issues and effects of cells’ architecture and electrode materials on systems’ performance are analyzed and discussed. Municipal solid waste (MSW) disposal is a problem with no easy or unique solution. In 2015, 242.3 Mt of MSW was produced in the European Union, 62 Mt of which discarded in landfills. Italy, in this context, produced about 29.5 Mt MSW in 2015, of which 7.8 landfilled ISPRA . DespiteLeachate characteristics are quite variable, affected by landfill construction and age, local meteorology, waste type, and composition, normally high in COD and ammonia content  that may be refractory, inhibitory, or otherwise affect such processes , were operated and closely monitored during the study. The two structurally identical cells  differed only for the constituting electrode material. MFC1 was built with graphite-coated stainless steel (GCSS) mesh (200 × 200 mm sheets) electrodes in both chambers, while MFC2 anodic and cathodic chambers’ electrodes were made of granular graphite . The final free volume of each chamber was 800 mL  in MFC1 and 450 mL (NAC and NCC) in MFC2, respectively. In order to allow external circuit connection, graphite rod electrodes (250 × 4 mm) were inserted in both chambers. A 33 Ω resistance was connected to MFC’s external circuit: this value was determined to be as close as possible to the static internal resistance of the MFCs. An Ag/AgCl reference electrode was placed in the anodic chamber . Oxygen was the terminal electron acceptor, provided directly into the cathodic chambers by a porous diffuser connected to a fish tank air pump. The scheme of the experimental system is shown in Fig. −1 in step-feeding mode (20 min each hour). The two MFCs were inoculated with a mixture of activated sludge and effluent of a parent MFC treating only dairy wastewater (DW).Influent dosage and recirculation were controlled by peristaltic pumps  connected to a pre-programmed controller. Close-circuit recirculation was operated continuously to accomplish well-mixed conditions within anodic chambers; influent flow rate was set at 1 L day−1 NaH2PO4, 819 mg L−1 Na2HPO4, 1000 mg L−1 NaHCO3, 130 mg L−1 KCl, 310 mg L−1 NH4Cl  and DW characteristics are reported in Table V) were simultaneously recorded. Power (P) and current (I) were determined from continuous voltage measurement. Current (dI) and power (dP) densities were calculated dividing the respective value of I and P by the NAC volume of each cell. Anodic coulombic efficiency (CE) was computed using daily average data of flow rate and current intensity.Anodic potentials were monitored with an Ag/AgCl reference electrode and continuously acquired at 1-min intervals by an automated data acquisition system  connected to a computer. MFCs’ generated voltages .Determination of effluent COD (daily composite samples for each cell) and influent wastewater COD (one sample for every batch collected) was performed according to the “standard methods” APHA . Anodic S, kWh kg CODremoved−1) and per volume of treated wastewater , was calculated for each period and for the total experiment with the following equations, as proposed by Ge et al.  of the MFCs, a parameter that expresses the amount of energy recovered per removed mass of COD  and power curves .was also performed by using a potentiostat  to verify the internal resistance of the system and identify differences between the two setups and analyze energy losses.The experimental study was divided into 11 successive phases, each operated for 1 week, a period necessary for achievement of a stable electrical production. Cell inoculation occurred running the systems using the effluent of a parent MFC and sewage sludge of dairy origin as influent substrates, until establishment of a suitable microbiome was observed. In phase 0, both MFCs were fed with dairy wastewater only, afterwards—during phases 1–10—the feed consisted of a mix of LL and DW at increasing ratios, with 5% step increase of LL at each subsequent phase. The main characteristics of the influent feed during the study are reported in Table Microbial fuel cells rely on biological oxidation of wastewater, which effectiveness strongly depends on the nature of the substrate. LL used in the present experimentation is a poorly biodegradable substrate; to enhance its suitability for biological treatment DW, a highly biodegradable substrate was used as co-substrate.−3. Power density monitored throughout the experimentation is represented in Fig. −3) under all subsequent operating condition tested.Observed energy production did not reflect a specific trend correlated to the varying LL fraction in the feed; however, upon examination of the results, it can be assessed that the most favorable operating condition was observed in phase 4 (15% leachate), where maximum output power peaks were recorded for both MFCs. It must be stressed out that the characteristics of leachate remained constant during the study, while DW parameters changed slightly, as previously shown in Table In both systems, after the shift from DW-only feed to the 5% LL-DW mix, an instantaneous drop in energy production was observed, which could be attributed to ongoing acclimation of the MFCs’ anodic biomass to the new substrate composition. This acclimation is confirmed by the rapid recovery observed in the following days, with rapid exoelectrogenic biomass activity recovery, which maintained and improved high current production throughout phases 2 and 3 for MFC1, and up to phase 7 for MFC2, even at increasing leachate ratios in the feed.At this point, it seems evident that MFC2 architecture proved to be more efficient for energy recovery than MFC1’s as, both being operated under the same conditions, the latter showed a consistently lower power generation.ηCOD throughout the study was measured for each condition tested, and CE was calculated. In the first phases of the study, CE was very low for both systems, probably due to slow adjustment of the exoelectrogenic population to the substrate. Concerning MFC1, CE showed a linear incremental trend Fig. , with vaCOD removal efficiency started at 82.9% for MFC2 and 58.1% for MFC1 in phase 0. It increased in phase 1, achieving the best values for both MFCs, 84.9% and 69.1% for MFC2 and MFC1, respectively, decreasing gradually with the increase of leachate ratio in the feed. During phase 5, COD removal dropped drastically in MFC1, at 7.6%. The unit was then operated until the end of phase 6, with no increase in voltage generation and even lower ηCOD, at 5.7%; therefore, it was decided to stop the operation of this unit. MFC2 maintained high COD removal efficiency  until phase 5. At 25%, LL ratio in the feed conditions became critical: from the previous ηCOD of 66.3%, removal dropped by almost half to 36.5%. This content level of landfill leachate in the influent affected both systems and thus can be considered their operational limit in the studied conditions. MFC2 maintained, however, removal efficiency greater than 30% until phase 10 (LL/DW = 50%), when ηCOD dropped to a low of 8.6%.A final analysis concerned the systems’ polarization and power curves: in addition to representing the electrical behavior of the cells, they allow to establish the real internal resistance value; it was already reported that, to maximize energy production in MFCs, external resistance should be equal to the internal one  of these could be attributed to membrane losses, while the second largest factor affecting energy production was cathode efficiency (ηcat = 32%). Anode efficiency and pH gradient only accounted for 7% and 5% loss respectively, while ionic exchange between anode and cathode could be considered negligible (< 1% loss).The internal resistance detected for MFC2, instead, was similar to the external resistance initially applied; therefore, further analysis of energy losses in the unit was performed. It was found that the largest part  and massive  specific terms. Results are summarized in Fig. −3treated were observed. As already confirmed by the previously shown data, MFC2 showed better performance, reaching values of NERV of 0.149 kWh m−3treated during phase 6 (30% leachate). In terms of specific net energy recovery, the best rates were also obtained in phase 6, with NERS of 0.019 kWh kg COD−1.NER throughout the study was evaluated for both units, in volumetric (NER5/COD ratio (0.4–0.6) indicating good biodegradability  and high salinity, comparable with that used in the present study. During operation with diluted leachate , an air cathode MFC achieved 32% COD removal, and average power density of 6.1 ± 4.2 mW m−3. With raw leachate fed to the system, OLR increased up to 24.42 kg COD m−3, achieving up to 37% COD removal and power density of 344 mW m−3. Observed coulombic efficiency, however, remained below 2%, indicating that substrate degradation was not carried out primarily by exoelectrogenic bacteria, but possibly by methanogens, a commonly found EAB-competing species , starting from COD concentration of 1 g L−1, and reducing gradually the applied OLR up to 50 g L−1 day−1. Higher OLRs led to lower coulombic efficiency . The authors stated that, despite the overall increase in voltage output, decrease in CE may be due to uptake of organics by non-exoelectrogenic processes, such as methanogenesis. Zhang et al.  in a two chambered MFC in batch mode. COD removal of 72% was achieved, with maximum power density of 1.83 W m−3.Most MFC studies in literature concern the use of fresh landfill leachate: this is, in fact, easily biodegradable, leading to an easier and more effective biological treatment, but not necessarily to higher energy recovery efficiency. Özkaya et al.  operatedg et al. , b operas et al.  operatedThe present study shows that both units (MFC1 for part of the tests only), even though fed with diluted old, low biodegradability landfill leachate, achieved satisfactory degradation values and energy recovery parameters in line with those reported in literature for any type of leachate. It should be also noted that not all published studies examined clearly specify the period during which the observed performances were consistently maintained.To better understand the limitations of landfill leachate treatment, and the causes that led to failure of the process when the ratio LL/DW = 1 (50%) in the feed was reached, an autoptic analysis was performed on the cells at the end of the study. After conclusion of the tests, both MFCs were disassembled to analyze the effects of the continuous operation with landfill leachate mix feed on the constituent materials. Figure Results of the study showed that one of the MFCs tested for combined leachate and industrial wastewater treatment obtained initially good results both in terms of COD removal and power generation. The use of DW as co-substrate provided additional nutrients to the EABs and resulted in improved bioelectrochemical degradation of organics, compared with feed with LL only. The unit that achieved the best performance (MFC2) had electrodes built with granular graphite, while the one (MFC1) with GCSS mesh electrodes showed poor performance since start-up. As pointed out by several studies, the performance of MFCs in terms of power output and durability strongly depends on the key components of these systems, the electrodes, which are one of the limiting factors for a generalized applicability of these systems  landfill leachate and dairy wastewater as co-substrates at various mixing ratios. Both units, with similar architecture but different electrode constituting materials and net cell volumes, were operated under continuous feed. MFC1 was operated for 6 cycle phases, up to 25% leachate percentage in the feed, while MFC2 maintained residual efficiency until reaching a feed composition of 50% leachate, prior to process failure. Both systems achieved their best performance treating a mixture of 20% leachate and 80% dairy wastewater. Premature failure was ascribed to poor electrically performing anodic material in the first cell. As far as the second cell, after a posteriori autoptic examination of the unit, failure was ascribed to accumulated interference of feed-contained solids, which determined clogging of the anode cell free volume in time, favored by suboptimal internal hydrodynamic conditions. Pretreatment of leachate may be the key to operate at higher percentages in the influent solution, lowering the presence of residual non-biodegradable solids or inhibiting waste components. Despite the ultimate process failure, during the first stages of the study, MFC2 performance was quite similar to that reported by other studies.Bioelectrochemical systems have shown consistent sustained, long-term treatment performance of different substrates and good short-term treatment performance of problem substrates such as landfill leachate, especially when fed with fresh leachate. Further attempts in this direction should consider adequate substrate pretreatment or internal hydrodynamic improvements to overcome the drawbacks observed in this study, in particular when aged, poorly biodegradable leachate is fed as substrate.


The embryonic development of commercial broiler chickens, which accounts for about one-third of the whole life span, has attracted increasingly more attention. Egg yolk is the main nutrient source of broiler embryos, and its metabolites change rapidly during the embryogenesis. Chicken sexual hormones may play important roles in changing the profile of metabolites in different tissues. Therefore, we compared the profiles of yolk metabolites and patterns of liver lipid-related gene expression of male and female chicken embryos. The results showed that the female yolk metabolites were mainly related to the lipid metabolism and amino acid metabolism in early embryonic stage, and vitamin metabolism in late embryonic stage, while the male yolk metabolites were mainly associated with lipid metabolism and nucleic acid metabolism in early embryonic stage, and amino acid metabolism in late embryonic stage.The metabolic processes of animals are usually affected by sex. Egg yolk is the major nutrient utilized for the growth and development of a chicken embryo. In this study, we explored the differences of yolk metabolites in male and female chicken embryos by LC–MS/MS. Furthermore, we investigated the mRNA expression of lipoprotein lipase (LPL) and fatty acid synthase (FAS) in chicken embryo liver with different sexes in different embryonic stages. The results showed that the nutrient metabolites in the yolk of female chickens were mainly related to lipid metabolism and amino acid metabolism in the early embryonic stage, and vitamin metabolism in the late embryonic stage. The male yolk metabolites were mainly associated with lipid metabolism and nucleic acid metabolism in the early developmental stage, and amino acids metabolism in the late embryonic stage. There was no significant difference in the expression of LPL or FAS in livers of male and female chicken embryos at different embryonic stages. Our results may lead to a better understanding of the sexual effect on yolk nutrient metabolism during chicken embryonic development. The main source of nutrients for chicken embryo development is the yolk, which provides more than 90% of nutrients and is dynamically metabolized to supply essential elements for the embryonic organ growth and tissue formation ,2. AboutBacteroides, Lactobacillus, Megamona, and Faecalibacterium, which are functionally related to body glycometabolism and muscle growth. The abundance of Ruminococcaceae and Enterococcus, which are mainly related to lipid metabolism in the caecum of female broilers, are relatively more abundant than those in the male birds [Animals with different sexes usually have quite distinct nutrient metabolic processes due to the regulation by sexual hormones . The sexle birds . The secle birds . HoweverA total of 100 Ross 308 fertilized eggs were purchased and incubated at 37 ± 0.5 °C with 60 ± 5% relative humidity. All the eggs were candled at embryonic day 5 (E05) to check the fertility and unfertilized eggs were eliminated. At each sampling day , 12 eggs were gently opened from the air cell by using clean scissors. The egg shell membrane was slowly peeled off with a sterilized tweezer to expose the embryo and yolk sac membrane. Yolk samples (5 mL) were collected by a syringe puncturing the yolk sac membrane and homogenized before freezing in liquid nitrogen. Embryonic liver and yolk sac samples were collected on a 4 °C sanitized working bench and stored at −80 °C after snap freezing in the liquid nitrogen. Twenty-four yolk sac samples were collected at E07, E11, E15, and E19 for sex identification, and liver samples were collected at E11, E15, and E19.The sex of chicken embryo was identified by gel electrophoresis of DNA. DNA was extracted from yolk sac using TIANamp Genomic DNA Kit  following the manufacturer’s instructions. The concentration and quality of isolated DNAs were assessed by Nano Drop spectrophotometer . Subsequently, the CHD1 gene was amplified by polymerase chain reaction (PCR) with 0.1 µg DNA and primer pair SF/SR  . The chrg, 4 °C for 10 min. Finally, the supernatant was injected into the LC–MS/MS system for further analysis [The frozen yolk samples (100 mg) were individually ground with liquid nitrogen, and the homogenate was resuspended with prechilled 80% methanol and 0.1% formic acid by well vortex. The remaining yolk samples were preserved for use. The samples were incubated on ice for 5 min and then centrifuged at 15,000 rpm, 4 °C for 5 min. A volume of 50 µL supernatant was diluted to final concentration containing 53% methanol by LC–MS grade water. The samples were subsequently transferred to a fresh Eppendorf tube and then centrifuged at 15,000× analysis .UHPLC–MS/MS analysis was performed at Novogene Co., Ltd.  using a Vanquish UHPLC system  coupled with an Orbitrap Q ExactiveTM HF mass spectrometer . Samples were injected into a Hypesil Gold column  using a 17 min linear gradient at a flow rate of 0.2 mL/min. The eluents for the positive polarity mode were eluent A1 (0.1% FA in water) and eluent B (methanol). The eluents for the negative polarity mode were eluent A2  and eluent B (methanol). The solvent gradient was set as follows: 2% B, 1.5 min; 2–100% B, 12.0 min; 100% B, 14.0 min; 100–2% B, 14.1 min; 2% B, 17 min. A model Q ExactiveTM HF mass spectrometer was operated in positive/negative polarity mode with spray voltage of 3.2 kV, capillary temperature of 320 °C, sheath gas flow rate of 40 arb, and auxiliary gas flow rate of 10 arb [https://www.mzcloud.org (accessed on 1 September 2021), mzVault, and MassList database to obtain the accurate qualitative and relative quantitative results [The raw data files generated by UHPLC–MS/MS were processed using the Compound Discoverer 3.1  to perform peak alignment, peak picking, and quantitation for each metabolite. The main parameters were set as follows: retention time tolerance, 0.2 min; actual mass tolerance, 5 ppm; signal intensity tolerance, 30%; signal/noise ratio, 3; and minimum intensity, 100,000. Next, the peak intensities were normalized to the total spectral intensity. The normalized data were used to predict the molecular formula based on additive ions, molecular ion peaks and fragment ions. Peaks were then matched with the mzCloud,  results . Statist−ΔΔCt method was used to calculate the corresponding gene expression.Total RNA was extracted from the liver tissue using the Tiangen Biotech RNA Easy Fast Tissue/Cell Kit (DP451) following the manufacturer’s instructions. The cDNA synthesis was performed using Quantscript RT Kit . RT-qPCR was performed in the Applied Biosystems 7500 Fast Real-time PCR system  with SYBR green . Based on the chicken genome sequence in NCBI, primers were designed using Primer Premier 5.0 and synthesized by Sangon Biotech Co., Ltd. . The primer information of LPL, FAS, RPL4, and β-actin are listed in t-test was performed to compare the differences of yolk metabolites between male and female chicken embryos at E7. The volcano plot was obtained by combining the fold changes and p values of each metabolite (https://www.genome.jp/kegg/pathway.html (accessed on 1 September 2021) (Different metabolites were screened by their fold changes and tabolite A. Accordtabolite . Furtherer 2021) B. The reThe same analysis for yolk metabolites of male and female chicken embryos at E11 was performed. The results show that a total of 103 significantly different metabolites were identified A. The toAccording to the results of volcano plot, there were 289 significantly different yolk metabolites identified between the male and female chicken embryos A, the nuThe results of the volcano plot showed that a total of 98 significantly different metabolites were identified A. The nuIn order to understand the sexual effect on the lipid-related gene expression during the embryogenesis, we analyzed the expression of LPL and FAS in chicken embryo livers at different embryonic days . HoweverSex is an important characteristic for animals, which significantly affects the normal growth and metabolic processes . Egg yolAccording to our results, we found that the female chicken embryos mainly metabolized the yolk nutrients through porphyrin metabolism, primary bile acid biosynthesis, and arginine biosynthesis in the early stage of embryogenesis. Estrogen was found to be an important factor in regulating porphyrin metabolism, including supporting the cardiovascular system to facilitate the function of heme oxygenase . Thus, tMetabolites in the yolk of male chicken embryos differed from those in female chicken embryos in different developmental stages. The yolk metabolites in male chicken embryos during the early developmental stage were mainly related to the lipid metabolism and nucleic acid metabolism, such as glycerolipid metabolism, fatty acid biosynthesis, pyrimidine metabolism, and purine metabolism. The yolk lipids are the major component for chicken embryo nutrition, most of which are glycerolipid . ProstagIn conclusion, during the development of chicken embryos, the metabolism of nutrients in the yolk differed between male and female birds. The nutrient metabolism in the yolk of female chicken embryos was mainly related to lipid metabolism and amino acid metabolism in the early embryonic stage, and vitamin metabolism in the late embryonic stage. The nutrient metabolism in the yolk of male chicken embryos was mainly related to lipid metabolism and nucleic acid metabolism in the early embryonic stage and amino acid metabolism in the late embryonic stage. However, the lipid metabolism of embryo livers showed no significant difference between different sexes. Our study might provide a new perspective in understanding the sexual effects on the chicken embryo nutrition, and further give a potential clue for early identification of sex through the yolk metabolite analysis.