P values less than 0.05 were considered to indicate statistical significance. The three cell types showed highly similar DNA methylation patterns, although specific differences were identified. Gene ontology analysis revealed that one of the most significantly different gene categories was related to bone formation. Thus, expression of cell surface epitopes and osteogenic-related transcription factors as well as the bone formation capacity were compared. The results showed that compared with DFPCs and DPSCs, PDLSCs had higher transcription levels of osteogenic-related factors, a higher in vitro osteogenic potential, and an increased new bone formation capacity in vivo. In conclusion, the results of this study suggested that the differential DNA methylation profiles could be related to the osteogenic potential of these human odontogenic cell populations. Additionally, the increased osteogenic potential of PDLSCs might aid researchers or clinicians in making better choices regarding tissue regeneration and clinical therapies.Among the various sources of human autologous stem cells, stem cells isolated from dental tissues exhibit excellent properties in tissue engineering and regenerative medicine. However, the distinct potential of these odontogenic cell lines remains unclear. In this study, we analyzed DNA methylation patterns to determine whether specific differences existed among three different odontogenic cell types. Using the HumanMethylation450 Beadchip, the whole genomes of human dental pulp stem cells (DPSCs), periodontal ligament stem cells (PDLSCs), and dental follicle progenitor cells (DFPCs) were compared. Then, the osteogenic potential of these cells was evaluated both in vitro and in vivo, and the methylation levels of certain genes related to bone formation differed among the three cell lines.  Stem cells isolated from the periodontal ligament are better at making new bone tissue than other kinds of dental stem cells. Feng Chen and colleagues from Peking University, China, analyzed the profile of DNA methylation that affect gene expression in stem cells isolated from human dental pulp (found in the center of the tooth) or periodontal ligaments (which attach tooth roots to bone), as well as from dental follicle progenitor cells that eventually form periodontal ligament cells. They saw significant differences in DNA methylation among genes related to bone production. They thus tested the bone-forming ability of each cell type, both in cell culture experiments and mice. The periodontal ligament stem cells proved the best, suggesting they could be useful for tissue engineering and regenerative medicine. These stem cells are believed to be excellent candidates for tissue engineering approaches and represent the future of clinical stem-cell-based bone regeneration2. In addition, the developments in the field have yielded promising prospects for the use of MSCs in clinical trials3. The various sources of autologous stem cells include a specific postnatal stem cell line isolated from dental tissue, embryonic and adult stem cells derived from bone marrow, umbilical cord blood, and amniotic fluid4. Tooth-derived stem cell populations comprise a high percentage of progenitor cells and an excellent bone regeneration capacity. Thus, many studies have focused on odontogenic stem cells. To date, various human odontogenic stem/progenitor cell types have been isolated and identified, including dental pulp stem cells (DPSCs), periodontal ligament stem cells (PDLSCs), and dental follicle progenitor cells (DFPCs)5; all of which present MSC properties characterized by self-renewal, non-specialization, and multilineage differentiation potential; importantly, these cells display osteogenic capacity, which is one of the most crucial factors in tissue regeneration6. However, the osteogenic differentiation potential of these cells for bone regeneration may differ because these cells are derived from distinct tooth tissues and have different fates. Additionally, studies have investigated the optimal cell type for clinical use and/or basic research studies. For example, the differences between the proteomes of PDLSCs and DPSCs and the differences in other characteristics, such as the morphological properties, immune-phenotypes, or general gene expression patterns, among odontogenic stem cell lines10 have been reported. However, the conclusions of the above-mentioned studies were inconsistent. Thus, there is no basis for the application of various tooth-derived stem cell lines in tissue bioengineering.Due to advances in biological tissue engineering, the use of autologous mesenchymal stem/stromal cells (MSCs) as biological material seed has become increasingly popular. MSCs have recently been a particular focus in many areas of scientific research11. The epigenetic regulation of tissue-specific gene expression includes DNA methylation and histone modifications, which are both highly crucial. The recent characterization of the human DNA methylome and CpG islands has accelerated the development of the field of epigenetics12. DNA methylation is essential for the regulation of gene expression profiles13. Early embryonic development and differentiation are regulated by and dependent on epigenetic markers, including DNA methylation.16 Additionally, DNA methylation provides a potential epigenetic mechanism for the preservation of the somatic progenitor state through repeated cell divisions17. Moreover, aberrant DNA methylation (hyper- or hypomethylation) could impact related gene expression and, thus, influence disease processes, such as cancer18. Thus, the alterations in DNA methylation patterns observed in certain conditions or diseases have increased the interest in the development of large-scale DNA methylation profiling methods and, hence, have facilitated technological breakthroughs15.Epigenetics is one of the most rapidly developing fields in the biological sciencesTherefore, the primary goal of this study was to identify the differences in the DNA methylation states among three dental stem cell lines. In addition, we aimed to determine whether the differential methylation profiles of these stem cells influence their potential.Three human-impacted third molars were used to obtain dental follicle tissue. Three premolars were extracted during orthodontic treatment and used to obtain dental pulp and periodontal ligaments. All subjects were generally systemically healthy. This study was approved by the Biomedical Ethics Committee of Peking University. Each subject signed an informed consent form before participating in the study. The mean age and gender distribution in each group were matched and did not significantly differ  three times. The PDL tissues were separated from the root surface. Then, the collected PDL tissues were minced and digested in a solution of 3 mg/mL collagenase I  and 4 mg/mL dispase  for 1 h at 37 °C. PDLSCs from each donor were cultivated individually, and single-cell suspensions were obtained after centrifugation. The cell suspensions were then transferred to and seeded in 10-cm culture dishes  containing minimum essential medium (a-MEM) supplemented with 15% fetal bovine serum, 2 mmol/L glutamine, 100 U/mL penicillin, and 100 µg/mL streptomycin . The tissues were then incubated at 37 °C in a humidified atmosphere containing 5% CO4 cells/mL and supplemented with a-MEM with 10% FBS. The images were captured under a phase-contrast inverted microscope  after the cells had reached 80% confluency. The observed cell morphologies were similar to those previously reported and used to identify PDLSCs19, DPSCs, and DFPCs.After the isolation, suspension and seeding of the human DFPCs, PDLSCs, and DPSCs from the corresponding tissues of each donor, all three primary culture cell types were subjected to morphological identification and characterization. In our study, we mainly followed the detailed methods described in the Lancet paper published by Seo et al. for the identification and characterization of the three stem cell types. PDLSCs, DFPCs, and DPSCs were seeded separately in culture plates  at a cell density of 5 × 1015). The genomic DNA was extracted using a QIAamp DNA mini kit  accompanied by the recommended proteinase K and RNase A digestion. The genomic DNA (800 ng) was then treated with sodium bisulfite using a Zymo EZ DNA Methylation Kit™  according to the manufacturer’s instructions. An Illumina Infinium methylation assay was performed using 4 μL of bisulfite-converted genomic DNA at 50 ng/μL according to the Infinium HD methylation assay protocol. The data quality was confirmed using the GenomeStudio™ methylation module software (2010.3), and all samples conformed to the quality control. Uncorrected b values were extracted using the same software. The raw data were submitted to the Gene Expression Omnibus (GSE29290) database.The DNA methylation state in Passage 2 of the DPSCs, PDLSCs, and DFPCs was investigated using Infinium HumanMethylation450  to assess the methylation status of the whole genome. This 450K beadchip provides genome-wide coverage of 99% of the RefSeq genes characterized by more than 450,000 methylation sites, including both within and outside of CpG islands. Importantly, the coverage was targeted across genetic regions with sites in the promoter, 5′-untranslated region (UTR), first exon, gene body, and 3′-UTR, thereby providing a comprehensive view of the methylation status /(Nf/N), where nf is the number of differential genes within a particular category, n is the total number of genes within the same category, Nf is the number of differential genes in the entire microarray, and N is the total number of genes in the microarray. Studying the distribution of proteins in GO can illustrate the functional representation of the differential proteins. Technical expertise regarding the systemic bioinformatic analysis was provided by Novel Bioinformatics Co., Ltd. (Shanghai).After the methylation analysis, a gene ontology analysis was conducted to further classify the genes that significantly differentially expressed among the three Passage 2 cell groups. Novelbio software, which was obtained from the Novel Bioinformatics Co., Ltd. (Shanghai), was used for this analysis. This software integrates information from several databases, including NCBI, SwissProt/UniProt, PIR, IPI, GO, etc., marks the source and removes the repeated GO information. Then, a functional significance analysis was performed to classify the differential proteins, and the classification results were based on the significance of the discrete distribution analysis, misjudgment rate analysis, and enrichment analysis. Generally, Fisher’s exact test was performed to classify the GO categories, and the false discovery rate (FDR) was calculated to correct the 5 cells (Passage 4) were harvested, washed with PBS containing 1% bovine serum albumin (BSA), and incubated with antibodies against human STRO-1, CD146, and CD109  at 4 °C in the dark. The cell suspensions lacking the antibodies served as controls. After 45 min, the cells were washed twice with PBS containing 1% BSA. Finally, 500 μL of PBS supplemented with 1% BSA were added to the tubes, and the samples were subjected to a flow cytometric analysis using a BD Accuri™ C6 flow cytometer .To compare the expression levels of the surface antigens, the cell suspensions were analyzed by flow cytometry. Briefly, ~5 × 10−ΔΔCt method was used to evaluate and compare the expression levels . The primers and corresponding probes used for the RT-PCR analysis were synthesized by the manufacturer . The probes and primer sequences are listed in Appendix Table Total cellular RNA Passage 2) was extracted from the cultured cells from each donor before differentiation using an RNeasy mini kit . Subsequently, cDNA was synthesized after a treatment with DNase I . All reactions were performed simultaneously and included negative controls. The reaction mixtures were further incubated with RNase H at 37 °C for 20 min. Real-time PCR was performed using a SYBR Premix Ex Taq Kit (Takara) using a quantitative PCR System . GAPDH was used as a reference gene. In addition, the 2 was extr4 per well and cultured with standard medium for 24 h, followed by osteo-inductive medium a-MEM supplemented with 10 nM dexamethasone, 50 μg/mL l-ascorbic acid-2-phosphate, 10 mM beta-glycerophosphate , 10% FBS, and 1% antibiotic/antimycotic . The medium was refreshed at 2-day intervals. After 14 days of incubation, the cells were fixed with 70% ethanol for 15 min at room temperature and stained with Alizarin Red S at pH 4.2 (Sigma-Aldrich). After performing observations under an inverted phase-contrast microscope, the mineralized nodules were dissolved in hexadecylpyridinium chloride, and absorbance at 560 nm was quantified and statistically analyzed.All cell lines at Passage 4 were incubated in six-well plates at a density of 3 × 104 per well and cultured in standard medium for 24 h, followed by osteo-inductive medium refreshed at 2-day intervals. After 7 days, the cell samples were collected and disrupted ultrasonically to obtain protein, and the protein concentration was determined using a bicinchoninic acid protein assay . The alkaline phosphatase (ALP) activity was detected using an ALP assay kit following the manufacturer’s instructions .All cell groups at Passage 4 were incubated in six-well plates at a density of 3 × 106 in vitro-expanded cells (Passage 4) and 1-cm3 hydroxyapatite was transplanted subcutaneously into the dorsal region of immune-deficient mice . The mice used were 6-week-old males . Each mouse had two transplantation sites. The amount of stem cells and hydroxylapatite for each cell type transplanted into the 6-week-old mice was identical to ensure that the external conditions were consistent. The animals were killed after 8 weeks, and the transplants were fixed in EDTA for over 24 h and then subjected to micro-CT scanning. In the scanned image, the white highlighted portion is the hydroxyapatite, and the gray–green highlighted portion is osteoid climbing around the hydroxyapatite. The darkest portion is soft tissue, which has a very low density and could be negligible. We enclosed the entire highlighted mass in a rectangle. In addition, the overall density of the hydroxyapatite plus newly formed osteoid was measured to represent the osteogenic ability of the stem cells.To investigate the in vivo osteogenic capacity of human DPSCs, PDLSCs, and DFPCs, subcutaneous transplantations of a cell mixture and hydroxyapatite were performed. The animal use was approved by the Animal Care Committee of Peking University Health Science Center. A mixture of ~5 × 10P values less than 0.05 were considered to indicate statistical significance.The in vitro experiments were performed in triplicate. In this study, the significance of the differences was determined using the Kruskal–Wallis test to analyze multiple groups. β (β = M/(M + U + 100)). M and U represent the methylated and unmethylated signal intensities, respectively. Three curves and the corresponding formulae for each comparison pair were obtained according to β value scatter plots of 480,000 DNA methylation sites in the three cell types  and curve fitting suggested that the DNA methylation profiles of DFPCs, PDLSC, and DPSCs were highly consistent. Moreover, the highest correlation coefficient value (R2 = 0.965) was observed between DFPCs and PDLSCs, indicating that these cell types had the highest similarity in DNA methylation profiles. Moreover, partial hierarchical clustering and a heat map of the 450K DNA methylation data shown in Fig. The DNA methylation profiles of the genomes of the P2 DFPCs, PDLSCs, and DPSCs were investigated using Infinium HumanMethylation450. The standard index of DNA methylation at a specific CpG site is pes Fig. . The corβ value >0.2, ratio >2 or <0.5) were observed at 1–2% of all sites  between DFPCs and PDLSCs, DFPCs and DPSCs, and PDLSCs and DPSCs  among the three cell lines. Furthermore, CD109, which is a surface antigen, showed significant differences in the DNA methylation analysis in our study and is a gene associated with osteogenic function. Thus, we detected CD109 along with STRO-1 and CD146 using flow cytometry. Appendix Figure p = 0.017) and PDLSCs and DPSCs (p = 0.006), indicating that the osteogenic function of these three stem cells may differ. In addition, because SMAD3 is an important transcription factor that was among the genes with significantly different DNA methylation statuses, SMAD3 was evaluated at the transcriptional level along with CD109 using RT-PCR. The expression levels of CD109 and SMAD3 were significantly higher in PDLSCs than those in the other two cell lines, thus validating the DNA methylation profiles. Additionally, other factors in the osteogenic-related pathways that play vital roles in the regulation of bone formation were determined at the transcriptional level. The expression levels of ALP, OCN, and RUNX2 were considerably higher in PDLSCs than those in the other two cell lines (p < 0.05), which is consistent with the CD109 and SMAD3 data  surface antigens, which are important cell surface markers and microRNAs, which play a crucial role in the regulation of cell fate, exhibited differential DNA methylation statuses (Appendix Table p < 0.05) . The osteoid formed by the stem cells grown along the hydroxyapatite after the cells were transplanted. Because the density of the hydroxyapatite is the greatest and the density of the osteoid is much lower than that of mature bone, the overall density will decrease if more osteoid is formed by the stem cells. Thus, PDLSCs that showed the lowest “density of hydroxyapatite plus osteoid” possessed the highest osteogenic potential. No significant difference in mineralization was observed between DFPCs and DPSCs  and H3K27 acetylation (H3K27ac) initiation of gene activation, H3K9me3 and H3K27me3 initiation of gene repression, etc.30 Studies have showed that these histone modifications are crucial for MSC osteogenic differentiation31. In addition, another study suggested that the posttranscriptional modification of histone by acetylation plays an important role in the osteogenic differentiation of PDLSCs32. Histone acetyltransferase GCN5 has been shown to regulate the osteogenesis of PDLSCs33. Furthermore, the acetylation of H3K9 and H3K14 could promote osteogenic differentiation in PDLSCs34.In addition to DNA methylation, histone modification is a critical regulatory component of epigenetic mechanisms affecting the fate of stem cells35, the authors compared the proteomic profiles of in vivo cultured human PDLSCs, DPSCs, and BMSCs to define the molecular features of odontogenic stem cells. Their results exhibited qualitative similarities in the proteome profiles among the three stem cells. In addition, the authors concluded that oral stem cells could have a different cell lineage potency than BMSCs, which may explain their ability of neuronal differentiation, which is consistent with their neural crest origin. However, the authors did not perform relevant functional experiments for further verification. Another study8 performed by Guo et al. compared the differentiation potential of dental follicle cells (DFCs) and dental papilla cells (DPCs) and indicated that the DPSCs were better at vascular differentiation and that DFPCs possessed a stronger osteogenic differentiation potential according to the analysis of the differential protein expression. In contrast with the two above-mentioned studies, we mainly analyzed the differential DNA methylation of DFPCs, PDLSCs, and DPSCs and observed evidence of their differential osteogenic abilities. Our study performed a DNA methylation analysis and then traced the osteogenic-related activities of three different odontogenic stem cell types, which differs from most previous studies.To date, numerous studies have focused on odontogenic stem cells. However, these studies have explored different aspects. For example, in the study conducted by Eleuterio36.Overall, the general similarity and specific differences in the DNA methylation profiles of the three odontogenic cell lines likely indicated that the distinct developmental stages or microenvironment might be related to the DNA methylation patterns. For instance, the DPSCs are capable of differentiating into multilineage cells, including neuron-like cells, whereas PDLSCs are highly likely to differentiate into cementoblasts and osteoblastsThe GO classification analysis showed that various biological processes significantly differed among the three cell lines, including developmental-, differentiation-, and osteogenic-related biological processes. This finding suggests that these cell types play different roles during development and differentiation. In addition, the differences in the osteogenic capacity were demonstrated in the in vitro and in vivo experiments. Thus, the similar gene methylation profiles between DFPCs and PDLSCs and greater osteogenic capacity of PDLSCs may assist clinicians or researchers in making more appropriate decisions in clinical trials or bone regeneration research studies. The characteristics of differentiation will be explored in our future studies.37. Odontogenic stem cells are promising biomaterials for tissue engineering and regenerative medicine; their potential applications should be further explored.Notably, although the dental follicles were obtained from developing teeth at a relatively early developmental stage, their osteogenic potential was not maximal. Therefore, the early developmental stages may not be directly related to the osteogenic capacity because PDLSCs, but not DFPCs, demonstrated a greater osteogenic capability. Furthermore, the identification of dental MSCs and the factors involved in the determination of their fate is a considerable accomplishmentp < 0.05). These results suggest that the differential DNA methylation profiles may indicate the osteogenic potential of these three odontogenic cell populations.In this study, the DNA methylation profiles and distribution of three cell lines were found to be similar, and the highest similarity was observed between DFPCs and PDLSCs. However, specific differences were identified among the cell lines investigated. Specifically, various cell surface antigens and microRNAs significantly differed, and GO analysis revealed that several gene categories with significantly different DNA methylation statuses were related to osteogenic functions, suggesting that the osteogenic potential varies among the three cell lines. Moreover, compared with DFPCs and DPSCs, PDLSCs exhibited higher transcriptional levels of osteogenic-related factors, a higher osteogenic potential in vitro and an enhanced new bone formation capacity in vivo (Appendix


The monitoring of immune cells gained great significance in prognosis and prediction of therapy responses. For analyzing blood samples, the multicolor flow cytometry has become the method of choice as it combines high specificity on single cell level with multiple parameters and high throughput. Here, we present a modular assay for the detailed immunophenotyping of blood (DIoB) that was optimized for an easy and direct application in whole blood samples. The DIoB assay characterizes 34 immune cell subsets that circulate the peripheral blood including all major immune cells such as T cells, B cells, natural killer (NK) cells, monocytes, dendritic cells (DCs), neutrophils, eosinophils, and basophils. In addition, it evaluates their functional state and a few non-leukocytes that also have been associated with the outcome of cancer therapy. This DIoB assay allows a longitudinal and close-meshed monitoring of a detailed immune status in patients requiring only 2.0 mL of peripheral blood and it is not restricted to peripheral blood mononuclear cells. It is currently applied for the immune monitoring of patients with glioblastoma multiforme , pancreatic cancer , and head and neck cancer  and might pave the way for immune biomarker identification for prediction and prognosis of therapy outcome. In the last decades, immunotherapy (IT) has become a prominent part in multimodal cancer therapy complementing the classical treatments of surgery, chemotherapy (CT) and radiotherapy (RT). It has successfully been established for certain cancers, but unfortunately not all cancer therapies benefit from its promising potential. Furthermore, challenges exist in finding optimal combinations and suited time points for its inclusion. Here, the knowledge of the immune status during therapy is becoming increasingly important particularly in the prediction and prognosis of therapy responses in multimodal cancer treatments .It has become clear that classical tumor therapies such as RT and CT do not only destroy tumor cells, but also modulate their phenotype and, especially in the combination with further IT, can initiate systemic immune-mediated anti-tumor responses . Once thIndeed, the peripheral blood is of great significance for a close-meshed immune monitoring because it is relatively easy to obtain and still carries a high informative value as the immune cells pass it to reach their target tissues. Thus, immune modulations in the distant tumor microenvironment might also affect the immune status in the peripheral blood allowing the recognition of therapy responses . ConsequOver the last years, several groups have developed multicolor flow cytometry-based assays that are suitable for an immune monitoring of patients. These assays widely differ in their level of detail ranging from one cell type ,12,13 ovWe present here a multicolor flow cytometry-based assay that examines the detailed immune status covering 34 different immune cell subsets and three non-immune cell subsets in only 2 mL of human peripheral blood. It was optimized for a direct staining of whole blood samples which on the one hand allows the detection of all circulating immune cells and on the other hand reduces the required preparation steps. Thus, in addition to minimizing effort and variations in sample preparation, the direct staining procedure also is time-saving, a further prerequisite for an easy clinical application, involving less than 20 min hands-on time. The assay was designed to allow a detailed immunophenotyping of blood (DIoB) identifying almost all circulating immune cells. These cover all major immune cell types such as T cells, B cells, natural killer (NK) cells, dendritic cells (DCs), monocytes, neutrophils, eosinophils, and basophils, as well as circulating stem cells, progenitor cell and endothelial cells which already have been connected to certain cancer therapy responses. Moreover, the functional state is analyzed by the additional staining for activation markers. The DIoB assay was designed in a modular principle comprising 12 panels which each is dedicated to determine one specific type of cell and its subsets. In total, it is suited for the monitoring of the detailed immune status of patients in short intervals paving the way for optimization or even individualization of multimodal cancer therapies.The DIoB multicolor flow cytometry assay allows the identification of 34 well defined immune cell subsets in human peripheral whole blood samples . These eThe identification of all subsets was performed by the analysis of surface antigens. However, the first step in all panels was the definition of a few identical gates, which were based on the morphologic properties of the cells, to discriminate the unwanted events from leukocytes and thus creating a consistent basis for the subsequent surface marker investigations.First, the Flow-gates were defined analyzing the event count against the time parameter A to checThese few morphology gates were defined in the same manner for all panels, except P12, to ensure the examination of the same set of events in all panels. Eventually, similar gates were defined for P12 by adjusting for its scatter characteristics, meaning higher FSC properties because the sample had not been centrifuged . Besides, we observed that almost all propidium iodide (PI) positive cells were located within the cells that shifted to a lower FSC, which were excluded anyway. Nevertheless, if some users wish to include a dead cell marker, PI would be ideal since the corresponding fluorescence channel was left blank in all panels.The T cell subsets are the most intensively studied ones and with about 20%–30% also the second most common in the peripheral blood. Thus, until today a plethora of different subsets were identified and characterized. Likewise, our assay identified the most subsets within the T cells which were determined in P01, P02 and P03 (+ gate was defined (+ T helper cells (TH) and CD8+ cytotoxic T cells (TC) were distinguished whereby T cells expressing both antigens were excluded from these definitions  and subsequently merged into all TC by the definition of a Boolean gate (see −/CD8−), double positive (DPT: CD4hi/CD8hi), CD4lo/CD8−, CD4hi/CD8lo or CD8hi/CD4lo T cells (lo/CD8lo). This analysis was continued by individual subdivisions of TH and TC by their CD45RA and CD197 (CCR7) expression into naïve (CD45RA+/CD197+), effector , effector memory  and central memory  T cells , TH2 (CD183−/CD196−) and TH17 (CD183−/CD196+) subsets (H population (+/CD196+) was observed which was described to comprise TH1 and cells producing both IFNγ and IL-17 [REG) were identified by their CD25hi/CD127−/lo phenotype [+ and TCRγ/δ+ T cells [In P02 the T subsets H,I, as dnd IL-17 . Furtherhenotype  as shown T cells   and is ess them . In paraess them ).The B cells belong with about 5% of all leukocytes to the less common peripheral cells and unfortunately also their subset distinction is not always uniform. Even though their role in the circulation is not completely understood, their number was described to be altered in numerous diseases and cancers and therefore should be monitored. We distinguished six well-described subsets in P04 , naïve [−/CD38−/lo/CD5−), memory [+/CD38−/lo/CD5−/CD24+) and transitional B cells [−/CD38hi/CD5+/CD24+), as well as plasmablasts [+/CD38hi/CD5−/CD24−). In addition, we identified the rare immunosuppressive B10 regulatory B cells (BREG) which do not express a unique set of surface markers but are CD27+/CD24hi [+/CD24hi B cells after the exclusion of the other five subsets. Therefore, a Boolean gate was defined and labeled as Rest of B cells which covered all B cells that were not located in the pre-naïve, naïve, memory, transitional or plasmablast gates  FigC–G. Thus), naïve ,40  were combined into the same fluorescence channel J resultiThe distribution of the innate NK cells is with 3%–5% similar to that of B cells. In general, NK cells are identified by their CD56 expression while lacking the common T cell marker CD3  and are + NK cells and monocytes even in neutrophil-rich patient blood samples. However, this advantage might be tarnished as there is a rare mutation in the CD16a molecule leading to loss of the binding epitope for the B73.1 antibody. This rare mutation is linked to primary NK cell immunodeficiency and repeated infections by herpes viruses [Investigating the CD16 molecule on NK cells one should pay attention in choosing an antibody clone which specifically detects its isoform A. Although the antibody clone 3G8 is widely used, we included the B73.1 clone as we obtained better results in whole blood staining. In addition to NK cells also monocytes express the isoform A of the FcγRIII, but neutrophils express FcγRIIIB (summarized in ). Both i viruses . Though,+ NK cells (lo/CD16+ cells (here termed NK1) accounted with nearly 90% by far for the main subset. These NK1 cells were described as predominantly cytotoxic [hi/CD16− cells (here termed NK2) were described as having a rather supporting role by predominantly secreting cytokines [lo/CD16− NK cells as NK3 subset. This subset has functionally not been described yet, but was proposed to be in-between developmental states [In the DIoB assay, we focused on the CD56NK cells A,B and dNK cells C in bothytotoxic ,55,56. Iytokines ,55,57. Il states . All theMost NK cells express CD314  ,60,61 FD. Thus, In order to determine the activation state, the common lymphocyte activation markers CD25 G and CD6+ cells in parallel to the expression on NK cells in the panels P06 and P07  co-expression into two, three or even four subsets. These subsets could then further be subdivided by their co-expression of other markers such as HLA-DR. The nomenclature of monocyte subsets is well-summarized in [The monocytes constitute for 7%–10% of all leukocytes and have typical SSC properties in-between that of the SSCrized in . As alrerized in , PE-Cy7 rized in  and we ohi/CD16− monocytes obviously accounted with 80%–90% for the main subset. This subset is often referred to as classical monocytes, but we termed them Mo1 in our assay to avoid any confusion; the other three subsets were labelled in a similar way. Roughly 10% of all monocytes express CD16 and were subdivided into the CD14lo/CD16+ Mo2 subset  and the CD14hi/CD16+ Mo3 subset (often referred to as intermediate monocytes). Following the identification of these three monocyte subsets, a fourth subset remained which expresses CD14 at low levels and no CD16. These cells were labeled as Mo4 despite that these cells may not be monocytes per se, but rather DC precursors [+/HLA-DR−/lo monocytes in the literature and has already been associated with cancer prognosis [The DIoB assay identifies the monocytes in P08 A and subecursors . As thisrognosis .+  and HLA-DRhi (upregulated state) as shown in ).In order to determine the activation state of the monocytes, the expressions of CD80, CD86, CD64 (FcγRI) and HLA-DR were investigated C–F. Therlo) and monocyte (SSCint) populations. They also lack the expression of a characteristic pan marker and therefore are often not examined in patient blood. However, these cells seem to have a regulatory potential [The granulocytes comprise the neutrophils, eosinophils and basophils. The first two have very characteristic high SSC properties and are therefore easy to identify; this is further improved by the expression of CD66 as a typical pan marker . In contotential  and therIn the DIoB assay the neutrophils and eosinophils were identified in panel P09 G. Then, The basophils were identified together with DCs in P10 K. Then, The DCs are spread over the whole body predominantly residing the tissues, but also circulating the periphery in an immature form. Even though they circulate in very small numbers counting for less than 1% of all leukocytes, they are potent regulators of the immune system and thus even small modulations could cause extensive effects. It is well described that blood DCs do not express any specific lineage markers, but are positive for HLA-DR and can then further be subdivided by their expression of CD11c, CD123 and CD1c .hi/CD11c−) and myeloid DCs (mDC: CD11chi/CD123−) as shown in +) and type 2  [+, but are negative for CD1c [− fraction. However, one might also add the CD141 antibody as an additional marker. Due to the very low frequency of the mDC-2 subset, we stained 300 µL of whole blood to obtain sufficient cell numbers.The DCs were determined together with basophils in P10 K. In the, CD1c−) ,105,106 for CD1c . For simEventually, the DC subsets were investigated for their expression of the immune tolerance inducing CD274 (PD-L1: Programmed Cell Death Ligand 1) ,109,110 In addition to the manifold immune cell subsets also some non-immune cells were identified which circulate the blood in a very low frequency. These include the hematopoietic stem cells (HSC), endothelial progenitor cells (EPC) and circulating endothelial cells (CEC). In healthy persons these cell types are very rare counting for less than 0.01% of all white blood cells, but were described to become more frequent in various diseases and cancer. In the steady state the HSC predominantly replenish myeloid immune cell subsets in the peripheral tissues, but an increased number was connected to immunosuppression and disease progression in various solid tumors . The EPC+ and CD133− [−/lo and CD34+. Furthermore, they normally lack CD146 and potentially express the hematopoietic marker CD133 [These rare and heterogeneous cell populations are characterized in P11 . Here, od CD133− ,118,119.d CD133− ,120,121.er CD133 ,122.− cells which also express CD133 to identify EPCs  and sum the individually identified cells using Boolean gates. Alternatively, a simplified gating strategy could be applied.Since leukocyte numbers vary during therapies and the DIoB assay will especially be used for longitudinal monitoring of patients during therapy, we additionally determined the absolute leukocyte count in panel P12 (+), B cells (CD19+ or CD20+), monocytes (FSC vs. SSC), granulocytes (FSC vs. SSC), NK cells (CD56 vs. CD16) and Rest of PBL  was created  three times separately and calculated the CV between all populations . In tota+ monocytes) had with 19.8% a CV above 15% which is an activation marker almost not expressed on resting cells in blood samples of NHD.The evaluation of the remaining 176 populations showed that most populations (67%) had a very small CV below 5% , and neaToday, the immune monitoring not only focuses on the distinction of particular cell subsets, but also on the interactions between these cells. Furthermore, as so far no single biomarkers have been identified that are connected to cancer progression or therapy outcome, one searches for groups of markers that jointly reveal their predictive or prognostic potential . ConsequIn the past, neutrophils and eosinophils were often overlooked, but recently both cell types became increasingly important as they might carry regulatory potential in various diseases ,125,126,The DIoB assay is a robust multicolor flow cytometry-based assay in a modular design allowing the identification of up to 37 different cells circulating in the peripheral blood. These include all major immune cell types and three additional non-immune cell subsets which have already been associated with therapy outcome. In addition, several activation markers are determined to evaluate the phenotype of the identified cells. The assay robustness is high as increased CV values only occurred in the very small populations. Consequently, all gates containing less than 100 events were excluded from interpretation as previously described and suggested ,130. EveOne has to stress that also some disadvantages arise with the DIoB assay: the antibody costs per measurement are not low. Additionally, the costs for cytometer and staff have to be taken into account. Furthermore, the first establishment of the assay requires experiences and consumes time. Moreover, the analysis procedures need to be coordinated, as huge amounts of data have to be analyzed.Recently, Finak et al.  reportedIn conclusion, the DIoB assay is a robust multicolor flow cytometry assay for identification of circulating immune cell subsets, as well as non-immune cells and additional activation markers in whole blood samples. The modular design makes the DIoB assay suitable for a wide range of applications as one may select, depending on the study objectives, the desired panels which each are dedicated to characterize a certain cell type. This might be important in explorative studies as one can assess a comprehensive immune status at the beginning and reduce it later on by still allowing direct comparisons. Moreover, it is relatively simple to adapt existing panels by adding or replacing certain activation or subset markers. Likewise, the blood withdrawal of only 2.0 mL is a small burden for most patients. Further, the direct staining of cell surface proteins in whole blood samples also decreases preparation effort, time, and variations. Worthy of note is that the assay is suited for the measurement on every cytometer that is capable of determining at least 8 different colors. Merely, the fluorochromes or filter settings need to be adapted to suit the local requirements. Everything else, like sample preparation, antigens, antibody clones or gating strategy could be applied directly. As a consequence, one could assess therapy effects of single patients and thus estimate individual responses. This contributes to the further development of personalized therapies and to the identification of immune biomarkers. The DIoB assay has already been applied for clinical immune monitoring of cancer patients. Analyses of patients with glioblastoma multiforme , pancreatic cancer , and head and neck cancer  are currently ongoing.For the establishment of the DIoB assay, the peripheral blood was drawn from 15 healthy volunteers using EDTA-Monovette tubes  and processed within 4 h. This was approved by the ethics committee of the Bayerische Landesärztekammer (#12131) in accordance with the principles described in the current version of the Declaration of Helsinki. All donors accepted and provided written informed consent.Based on literature review and previous experiences, we focused on 37 different immune and non-immune cell subsets for investigation. For their distinct identification, the required surface antigens and additional activation markers were assigned. Subsequently, antibodies were selected according to vendor availability and with regard to common practice for choosing fluorochromes, such as using bright fluorochromes for low expressed antigens and the other way around. We also took into consideration that antibody clones recognizing different epitopes could lead to varying signals between different cell types. The panel overview is provided in In order to determine the compensation values, we stained VersaComp Antibody Capture Beads  according to the manufacturer’s instructions and calculated them using the Kaluza analysis software . These compensation values were then cross-checked in single-staining of whole blood samples in comparison to their according fluorescence minus one (FMO) controls which make false positive events clearly visible. The FMO controls were moreover beneficial for the exact discrimination between positive and negative populations allowing the definition of gate settings for later analyses. The antibody concentrations , cytometThe samples were always handled at room temperature until fixation and kept on ice afterwards. Cooling of the blood prior to fixation can lead to degranulation of the neutrophils which might cause further damage to other cells, thereby altering the sample condition. However, following fixation they should be stored refrigerated if an immediate measurement is not possible. The measurement should be performed within 4 h. In order to standardize sample preparation, we defined SOPs allowing an easy procedure of the DIoB assay with low variations. It can be handled by any person who works according to these SOPs.Prior to the staining procedure an antibody master mix was prepared for every panel based on the previous titrations . Then, f2O) are added to the stained blood sample and gently vortexed for 10 s. Then, 265 μL of carbonate buffer , 248.1 mM NaCl  and 219.0 mM Na2SO4 (Sigma-Aldrich) in ddH2O) are added and immediately vortexed for 10 s. Finally, 100 µL of phosphate-buffered saline  containing 1% of PFA are added and also vortexed for 10 s  according to the manufacturer’s instructions. In short, first erythrocytes were lysed with formic acid, then leukocytes were re-buffered with carbonate and finally, a fixation with paraformaldehyde  was performed. This TQ-prep-Workstation from Beckman coulter provides an automated sample preparation under constant conditions. Obviously one could also manually lyse and fixate the blood. Therefore, first 600 μL of formic acid  and pellets were dissolved in 200 µL of PBS containing 1% of PFA. As far as possible, the samples were measured immediately. Otherwise, they were kept on 4 °C in the dark for a maximum of 4 h until acquisition.Finally, all samples, except P12, were washed twice with PBS  from Beckman Coulter. The cytometer settings  were based on the optimizations described above see . For allThe obtained data were analyzed using the Kaluza analysis software (version 1.3). Therefore, a composite protocol with the ability to directly link multiple acquisition files and thereby connecting the different data files of the same sample was created. This allowed an easy definition of the same gates for multiple files which reduced variations. If the local analysis software does not support such a linking feature, one of course could also transfer the gate settings from one file to the other still guaranteeing the analysis of the same populations. To define gate boarders, positive and negative populations were compared to FMOs, single and isotype stainings. Based on these definitions, the gates were adjusted for varying signals due to different cell numbers during the analyses of patient samples.All parameters were analyzed using density dot plots. The FSC signals were examined in linear scales and the SSC signals were recorded logarithmically. In contrast, all fluorescence parameters were analyzed using logicle  scales  and+ T cells) out of all cells. Then, every subset was calculated out of its major cell type . The activation states were determined by calculating all positive events in relation to their input gate. Finally, we transferred the absolute cell numbers determined for all leukocytes and the main cell types in P12 onto the other panels to determine the absolute cell number per milliliter of blood for each investigated subset.Finally, the raw data were exported into MS Excel  to calculate the proportional distribution of all determined subsets. First, we calculated the percentages of every major cell type  for all 208 obtained populations.


As expected, values for fruit size and OC in wild olives were lower than those obtained in cultivated materials, with intermediate values for cultivar × wild progenies. Wild olives showed a remarkably higher C16:0 percentage and tocopherol content in comparison to the cultivars. Contrarily, lower C18:1 percentage, squalene and sterol content were found in the wild genotypes, while no clear differences were found among the different plant materials regarding composition of the tocopherol and phytosterol fractions. Some common highly significant correlations among components of the same chemical family were found in all groups of plant materials. However, some other correlations were specific for one of the groups. The results of the study suggested that the use of wild germplasm in olive breeding programs will not have a negative impact on fatty acid composition, tocopherol content, and tocopherol and phytosterol profiles provided that selection for these compounds is conducted from early generations. Important traits such as tocopherol content could be even improved by using wild parents.A wide genetic diversity has been reported for wild olives, which could be particularly interesting for the introgression of some agronomic traits and resistance to biotic and abiotic stresses in breeding programs. However, the introgression of some beneficial wild traits may be paralleled by negative effects on some other important agronomic and quality traits. From the quality point of view, virgin olive oil (VOO) from olive cultivars is highly appreciated for its fatty acid composition (high monounsaturated oleic acid content) and the presence of several minor components. However, the composition of VOO from wild origin and its comparison with VOO from olive cultivars has been scarcely studied. In this work, the variability for fruit characters , fatty acid composition, and minor quality components  was studied in a set of plant materials involving three different origins: wild genotypes ( Olea europaea, includes six sub-species based on morphology and geographical distribution  and wild olive (var. sylvestris). A wide genetic diversity has been reported for wild olives, even higher than the observed for cultivated ones  is highly appreciated due to its fatty acid (high monounsaturated oleic acid content) and minor compounds composition. All these components are responsible of well-known healthy properties of VOO . High vaex situ conservation and evaluation of wild genotypes from different origins , cultivars (n = 62) and genotypes belonging to cultivar × wild progenies (n = 62). All the genotypes were grown in the same conditions at the IFAPA Centro Alameda del Obispo, Córdoba (Spain). Maintained in an ex situ wild olive collection , typical for olive harvesting. Previous works suggest that it seems more efficient to compare genotypes in a common date rather than to harvest the olive samples in a fixed ripening index, which is also quite difficult to achieve for large number of genotypes . From ea-1 lyophilized fruit flesh. Finally, sterols (ST) and squalene (SQ) contents in lyophilized olive flesh samples were analyzed by GLC of the unsaponifiable fraction following silylation, using a Perkin Elmer Clarus 600 Gas Chromatograph equipped with a ZB-5 capillary column . Total sterol content was expressed as mg kg-1 lyophilized fruit flesh.Twenty additional fruits were randomly chosen from each sample, stored at -80°C and then lyophilized. After lyophilization, the stones were removed and the flesh was milled in a laboratory ball mill. The samples were then stored at -20°C till analysis, usually within 48–72 h. All the analyses were performed in duplicate following previous procedures developed in our breeding program for direct analysis of fruit flesh . In shorPrincipal components analysis (PCA) was used to investigate the variability between and within the different groups of samples evaluated and the relationship among traits, and analysis of variance and box and whiskers plots were performed for the most important variables selected from PCA to analyze differences between groups. Pearson correlation and linear regression were used to test the relations among the traits measured. Unscrambler  and Statistix  software were used for the statistical analysis.Figure 1). The score biplot of PC1  and PC2 (14.8%) showed clear separation of the three groups of samples , although a wide variability was also observed within each of the three groups. PC1 was positively correlated mainly with C16:0, C16:1, and TC, and negatively with FFW, OC, and SQ content. PC2 was associated positively mainly with C18:1 and negatively with C18:2 and ST. Main separation between groups was obtained through PC1, i.e., higher values for C16:0, C16:1, and TC are expected for wilds, and higher values for FW, OC, and SQ content for cultivars, with intermediate values in progenies from crosses in accordance to the relative position of the parents in the score plot.PCA was used for a preliminary exploratory analysis of variability between and within groups of samples (Table 1). A wide and similar variability was observed in all three groups but clear differences in range of variation could be inferred from box and whiskers plots . High variability for most of the components has been reported in other cultivars and wilds collections (Table 2). For instance, C16:0 values for most of the wild genotypes would be higher than established (20% maximum). Some of them could also affront problems due to currents limits for C18:1 and C18:2. It should be noted, however, that the same problem is currently faced for traditional cultivars with some of them exceeding thresholds values for the main fatty acids set up by the International Olive Council . Wilds showed the highest mean content for C16:0 and C16:1, cultivars the opposite results, and progenies from crosses intermediate values. Not so clear results were obtained for C18:1 and C18:2, where progenies from crosses showed the highest and lowest mean values, respectively. However, it should be noted that high oleic acid ‘Picual’ cultivar was used as parent for these crosses, which may have affected these results due to the high heritability reported for this character  and subsequently higher C18:2 content (up to 33.3%) than those identified in the present research for wilds. Such contrasting results found in wild materials may be probably attributed to the different environmental factors linked to the geographical position where the genotypes were evaluated in situ . Some highly significant values among components of the same chemical family were found in all groups of plant materials, for instance between α-tocopherol and γ-tocopherol or between δ5-avenasterol and β-sitosterol (data not showed), as previously reported for other materials in our breeding program . Thus, in the regression between C16:0 and C18:1, crosses showed a lower slope compared to cultivars and wilds. A similar situation was observed in the regression between C18:1 and C18:2 . In the latter case, the coefficient of determination was considerably lower in the crosses than in the parents and wilds, attributable to the existence of lower variability for both traits in the crosses than in the cultivated and wild parents . The fatty acid composition of olive oil depends on both genetic and environmental factors, with genotypic variance having been reported as the main contributor to total variance in studies involving high genetic variability (In relation to the fatty acid profile, the most significant correlations were found between C16:0 and C16:1, which were positively correlated, and between C18:1 and both C16:0 and C18:2, in both cases negatively correlated. The evaluation of linear regressions between C18:1 and both C16:0 and C18:2 in the three groups of trees revealed marked differences in the coefficients of determination and/or the slope of the regression line (iability , as it iiability . Biosyntiability . This biiability .In summary, the results of the study seem to indicate that the use of wild germplasm in olive breeding programs could not have a negative impact on fatty acid composition, tocopherol content, and tocopherol and phytosterol profiles provided that selection for these compounds is conducted from early generations. Important traits such as TO content can be even improved by using wild parents. Conversely, our results indicated a putative negative impact on both total phytosterol and squalene contents, although this needs to be confirmed with studies involving larger populations.All authors conceived and designed the experiment. AB was in charge of plant materials selection and samples collection. LL, RdlR, and LV performed fruit traits and oil quality analysis. LL prepared the first draft of the manuscript, all authors critically reviewed the manuscript prior to submission, read and approved the final version of the manuscript and agreed to be accountable for accuracy, integrity, and appropriateness of the manuscript.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.


Arabidopsis thaliana primary root in seedlings exposed to Cd (25 and 50 μM) for 8 days starting from germination. Root length, root meristem size, and organization were evaluated together with the behavior of some of the major molecular players in root growth and patterning. In particular, by using different GFP transgenic lines, we monitored: (i) the expression pattern of WOX5 and SCR transcription factors involved in the establishment and maintenance of stem cell niche and in the control of meristem size; (ii) the expression pattern of the IAA-inducible pDR5::GFP reporter, PIN 1, 2, 3, 7 auxin carriers and TCSn::GFP cytokinin-sensitive sensor as relevant components of hormone circuit controlling root growth. We report that Cd exposure inhibits primary root growth via affecting RAM stem cell niche and root radial pattern. At the molecular level, an impairment of auxin maximum accumulation at the root tip, related to a down-regulation and mislocalisation of PIN proteins, and an enhancement of TCSn::GFP cytokinin-sensitive sensor signal is also detected under Cd treatment, thus suggesting an alteration in the homeostasis of auxin/cytokinin signaling. Moreover, and for the first time Cd toxicity on root growth and pattern has been related to a misexpression of SCR transcription factors which is known to interplay with auxin/cytokinin cross-talk in the control of RAM maintenance and activity.Cadmium is one of the most widespread pollutant in both terrestrial and marine environment, and its inhibitory effect on plant growth has been largely demonstrated. However, the molecular mechanisms underlying Cd toxicity in plant and mainly in root, as the first organ sensing soil heavy metals, need to be better investigated. To this aim, in the present work we analyzed the growth and the organization of  In the modern world, human activities such as extensive mining, industry and improper agricultural practices have led to a release of a great amount of heavy metals to the environment. Cd, in particular, is one of the most widespread heavy metals in both terrestrial and marine environments, and represents an extremely significant pollutant due to its high toxicity and large solubility in water .In both plants and animals, Cd absorption induces complex changes at genetic, biochemical and physiological levels, which account for its toxicity . In planArabidopsis thaliana, the PIN family consists of eight members which are divided into two subclasses in relation to the length of a hydrophilic loop in the middle of their polypeptide chain. Canonical “long” PINs (PIN1–4 and 7) show mostly polar localization on plasma membrane (PM), and direct auxin transport function is strongly supported for PIN1, 2, 3, 4, and 7 , which negatively regulates PIN 1,3,7 genes (TIR1), thus stabilizing PIN expression level and therefore auxin export. Conversely, cytokinins promote SHY2 expression, through the cytokinin receptor ARABIDOPSIS HISTIDINE KINASE3 (AHK3) and the downstream signaling components ARABIDOPSIS RESPONSE REGULATOR1 (ARR1) and ARR12. Interestingly, in the framework of hormone circuits involved in root growth regulation, it is becoming even more clear that also other hormones, such as brassinosteroids (BR) and gibberellins (GA), control root growth by modulating auxin level and distribution  whether Cd-induced reduction of RAM size was related to an impact on the stem cell niche (SCN), whose maintenance is essential for root growth and pattern ; (ii) whP sensor .A. thaliana seedlings germinated in presence of this heavy metal and exposed to a prolonged treatment.So far, Cd-depending effects on plant root have been especially investigated on seedlings germinated on water and then exposed to Cd . Taking A. thaliana (L.) Heynh. ecotype Columbia (Col) and of the transgenic lines pSCR::SCR-GFP  and 8 h dark and 60% relative humidity. For Cd treatment, CdCl2 was dissolved in sterile water and 100 mM stocks were prepared. An aliquot of this stock solution was added directly to the germination medium immediately before placing it in the Petri dishes to prepare the desired Cd concentrations (25 and 50 μM).Seeds were surface sterilized and grown as reported in Arabidopsis thaliana seedlings germinated on control (Ctrl) and on Cd containing medium (25–50 μM respectively) and grown in a vertical position were used. Three independent replicates were performed and for each sample, a minimum of 70 seedlings was analyzed. Data were statistically evaluated by Student’s t-test.1.Root length was monitored until 21 days after germination (DAG) by scanning the plates and analyzing the resulting images through the open source processing program ImageJpost hoc test (P ≤ 0.05) after Shapiro–Wilk normality test.For the meristem size analysis, seedlings at 8 DAG were stained with propidium iodide following the MPS-PI-staining protocol . ConfocaA. thaliana germinated on control (Ctrl) and on Cd containing medium (25–50 μM respectively) and sampled at 8 DAG. Confocal images of median longitudinal sections were obtained using a Leica inverted TCS SP8 confocal scanning laser microscope, with a 40x oil immersion objective. The detection of Green Fluorescence Protein  was performed by combining the settings indicated in the sequential scanning facility of the microscope. Three independent replicates were performed and a minimum of 40 seedlings was analyzed for each sample.Green fluorescent protein expression was monitored in seedlings of the above transgenic lines of pDR5::GFP and TCSn::GFP, in seedlings grown in Ctrl conditions and under Cd 50 μM treatment from germination to 8 DAG. Measurements were performed separately on the different zones of the root apex: calyptra, RAM and TZ until about 500 μm from the junction calyptra-root apex. Signal intensity measurements were carried out with Leica Application Suite X software (LAS X).Measurements of GFP signal intensity were carried out on the root apex of transgenic lines t-test .A minimum of 50 seedlings for each sample from three independent replicates was analyzed. The results represent the mean value (± standard deviation) of three independent biological replicates. Asterisks indicate significant pairwise differences using Student’s A. thaliana seedlings germinated on control (Ctrl) and on Cd containing medium (25–50 μM respectively) and sampled at 8 DAG were used. Total RNA was isolated from 100 mg of plant tissue and processed with the RNeasy Plant Mini kit  according to the manufacturer’s instructions. RNA was treated with DNase I  to remove contaminating genomic DNA. DNAse I was inactivated at 70°C for 15 min. RNA was precipitated and finally resuspended in 40 μL of RNase-free water. RNA quality was checked by agarose gel electrophoresis and quantified by spectrophotometry (NanoDrop technologies). Total RNA (3 μg) from each sample was interacted with SuperScript III Reverse Trascriptase and oligo dT (22) for cDNA synthesis, according to the manufacturer’s instructions .Primary roots of SAND) produced the most reproducible results across various cDNAs, and was used as a normalization control  was performed as reported in  control . The pri-ΔΔCt method .Amplification reactions were prepared in a final volume of 20 μL: Power SYBR Green PCR Master Mix (Applied Biosystems) (2X), dATP-dCTP-dGTP (0.4 mM) and dUTP (0.8 mM), each primer (0.4 μM) and cDNA (25 ng). All reactions were run in triplicate in 48-well reaction plates, and negative controls were included. The cycling parameters were as follows: one cycle at 95°C for 3 min to activate the Taq enzyme, followed by 40 cycles of denaturation at 95°C for 10 s and annealing-extension at 60°C for 30 s. After the reaction, in order to confirm the existence of a unique PCR product, the ‘melting curve’  was evalt method . The resA. thaliana seedlings germinated: (i) on growth medium as control (Ctrl); ii) on growth medium added with 25 or 50 μM Cd. Starting from the 6th DAG, a significant and dose-dependent reduction of root length was observed in seedlings exposed to Cd compared to the Ctrl . At the end of heavy metal exposure (21 DAG), the reduction in root length was about two and three folds for seedling treated with 25 or 50 μM Cd, respectively .Root growth was monitored by measuring primary root length up to 21 days after germination (DAG) in Figures 2, 3).Preliminarily, by monitoring when root meristem reached a fixed number of cells, we were able to define that in control and Cd-treated samples root meristem development was fully accomplished at 5/6 DAG and 7/8DAG respectively. Therefore, in order to analyze comparable stages, 8 DAG age was selected to analyze the effects induced by the heavy metal on root meristem size and pattern . We observed that the distance from QC to TZ was quite comparable in treated vs. Ctrl roots . However, at the highest Cd concentration (Cd 50 μM) the number of cortical cells was significantly smaller in Cd-exposed vs. Ctrl roots . In line with this result, meristematic cells were bigger in 50 μM Cd-treated roots than in Ctrl ones . Only a slight reduction in the distance from QC to TZ was observed in root meristems exposed to Cd 25 μM although differences were not statistically significant .Firstly, we evaluated meristem length by gauging, along the single cortex layer, both the distance and the cell number extending from QC to TZ where cell elongation is starting . It resulted smaller in roots grown in presence of Cd 50 μM  mainly due to a reduction in the diameter of stele  which was formed by a lower number of cell files compared to Ctrl roots . No statistically significant differences were detected in roots exposed to Cd 25 μM.Concerning the radial pattern, root width was taken into account and evaluated as the cross diameter at the level of TZ (All together these results indicated that at 8 DAG and at the highest concentration (50 μM) Cd impacted on the size and pattern of root meristem while in roots exposed to the lowest concentration (25 μM) similar effects were not yet significant despite a similar trend.Figure 3) we used a pWOX5::GFP transgenic line of A. thaliana expressing a QC specific marker .Attention was then focused on the QC, which acts as the organizing center of SCN and root meristem . To thisc marker , exposedFigure 3A‘ arrow) and transgenic lines . The number of QC cells did not change in roots exposed to Cd 25 μM , whereas a reduction to not more than two cells , coupled to a significant increase of QC cell area , was instead detected in roots exposed to Cd 50 μM. In few cases, QC cells were totally undetectable following Cd 50 μM treatment, thus suggesting a global miss identity of QC . Globally, these results are consistent with the reduced number of cell files induced by Cd 50 μM in the stele , whose initials are directly in contact with QC.According to literature , a canonFigure 3). Moreover, in the root where QC was undetectable, three/four-layers of large cells devoid of statocytes were observable below calyptrogen place .It has also been demonstrated that differentiation fate of the cells surrounding the QC is highly dependent on the same QC . ConsistAll together, these results suggest that Cd 50 μM toxicity on root growth and both longitudinal and radial pattern is likely dependent on the impact on QC cells.pSCR::SCR-GFP transgenic line exposed or not to Cd from germination to 8 DAG.SCARECROW (SCR) is a transcription factor of the GRAS family which is involved in the specification of QC identity, and hence in stem cell niche and meristem maintenance as well as in the definition of root radial patterning . TherefoFigures 5A,A‘). No differences were detected under Cd 25 μM treatment (data not shown). By contrast, in 50 μM Cd-treated roots, a mislocalisation of GFP signal was observed since it was ectopically expressed in the stele at the level of TZ  detected also in committed cortex cells , while appeared very low in some endodermis cells proximal to QC .In Ctrl roots, GFP signal resulted to be typically confined to the QC cells, the cortex/endodermis initials and along the endodermis  . To estimate quantitative spatial differences, signal intensity was measured at the level of calyptra, RAM and TZ, separately . We observed that pDR5::GFP signal was significantly reduced in the root apex of Cd-treated vs. Ctrl roots , mainly in the RAM  and more specifically along the stele and at SCN level . This signal distribution pattern clearly indicated that the establishment of auxin gradient in the root apex was impaired following heavy metal exposure.Based on the pivotal role of auxin in root morphogenesis, we planned to investigate whether the alterations in root patterning and QC identity, detected at 8 DAG in roots exposed to Cd 50 μM, could be related to an affected auxin signaling and distribution. To this aim, we used A. thaliana transgenic reporter lines: pPIN1::PIN1-GFP, pPIN2::PIN2-GFP, pPIN3::PIN3-GFP, pPIN7::PIN7-GFP. The analysis by confocal microscopy showed that globally PINs presence and distribution clearly differed in Cd-treated vs. Ctrl roots . In particular, PIN1 canonically resided at the basal end of provascular cells extending until the SCN . No significant differences were instead detected for PIN2, whose signal was typically localized at the apical side of epidermal and lateral root cap cells and predominantly basally in the cortical cells in both treated and untreated roots . Severe changes were observed for PIN3 signal, which in Ctrl roots was detectable in SCN, in two/three cell tiers of the columella cells and at the basal side of vascular cells as previously reported . As for PIN7 expression, an intense signal was typically detected in columella and in provascular cells of Ctrl roots while it appeared weakly spread in the stele and almost absent in the columella of Cd-treated roots . In addition, a weak lateral localization of PIN1, PIN3 and PIN7  and, occasionally, an intracellular accumulation of PIN3 and PIN7 transporters  were also observed in treated roots.This observation prompted us to investigate the distribution of PIN-FORMED (PIN) proteins, the main polar auxin efflux carriers  through  the SCN , but sigreported , whereasFigure 9).In line with the downregulation of PIN proteins expression, also the genes encoding these proteins were found to be downregulated in Cd-treated vs. Ctrl roots . A quite comparable level of signal was observed when considering the whole root apex. However, and more interestingly, clear differences were evident when considering the different root zones. Namely, in Cd-treated roots vs. Ctrl roots signal intensity resulted lower in the calyptra but significantly higher in both RAM and above all in TZ. Moreover, at histological level, signal resulted more largely extended, mainly in the stele and SCN . This signal distribution pattern clearly indicated that cytokinin signaling in the root apex was strongly altered by Cd treatment.Finally, due to the antagonistic effect of auxin and cytokinin on root growth and morphogenesis we analyzed some aspects of cytokinin signaling pathway by using a pDR5::GFP auxin responsive reporter we demonstrated that the establishment of auxin maximum at the root apex was impaired in roots exposed to Cd. This result is in line with previous data in literature showing that in A. thaliana roots a short Cd exposure (12 h) at comparable concentrations caused a reduction of RAM size associated to a reduced auxin level in the root tip  at the 8 DAG. In this context, it must be highlighted that root patterning is tightly related to the activity of stem cell niche formed by initials which divide continuously, producing at each division one cell that continues to act as an initial. The number of RAM initials varies according to species , but theur cells . The useur cells . On the In this context, it appears of interest the deregulation of SCR expression observed in Cd-treated roots. It is known that SCR is involved in formative stem cell division and exerts a fine control on ARR1 levels in the roots . Namely,The present work provides evidence that Cd toxicity on root growth is dose and time dependent and strongly depends on the effects induced on RAM stem cell niche. At the molecular level for the first time Cd-induced effects has been related to a misexpression of SCR transcription factors, as well as to an altered homeostasis of auxin/cytokinin signaling which both play a relevant role in the regulatory circuit underlying RAM maintenance and activity . NotablyLB, MG, and MB designed research; LB, MP, IF, LL, and MG performed research; LB, MP, AC, and MB analyzed data and discussed results; LB, MP, and MB wrote the paper. All authors contributed to improving the paper and approved the final manuscript.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.


Zinc release measured over 20 minutes ranged from 32–51% of the loaded dose. Total zinc release for sets tablets of the same composition but differing hardness were not significantly different from one another with P = 0.3598 and P = 0.1270 for two tested pairs using unpaired t tests with Welch’s correction. By the same test total zinc release from two sets of tablets having similar hardness but differing composition were also not significantly significant with P = 0.2634. Future zinc tablet composition and formulation optimisation could lead to zinc supplements and therapeutics with faster drug release, which could be administered with the NSDS during breastfeeding. The use of the NSDS to deliver zinc could then lead to treatment and prevention of some of the leading causes of child mortality, including diarrheal disease and pneumonia.Zinc delivery from a nipple shield delivery system (NSDS), a novel platform for administering medicines to infants during breastfeeding, was characterised using a breastfeeding simulation apparatus. In this study, human milk at flow rates and pressures physiologically representative of breastfeeding passed through the NSDS loaded with zinc-containing rapidly disintegrating tablets, resulting in release of zinc into the milk. Inductively coupled plasma optical emission spectrometry was used to detect the zinc released, using a method that does not require prior digestion of the samples and that could be applied in other zinc analysis studies in breast milk. Four different types of zinc-containing tablets with equal zinc load but varying excipient compositions were tested in the NSDS  Zinc is an essential micronutrient for paediatric health. It is especially crucial during rapid growth due to its important role in cell division, metabolism, and protein synthesis 2]3]. I[3]. I2][. I[3]. IZinc deficiency has many consequences including increased risk of infectious disease, stunting, hypogonadism, cognitive impairment, and delayed wound healing . As a reZinc deficiency is especially prevalent among low-income populations . Plant-bA study showed that maternal zinc supplementation does not cause extra zinc secretion into human milk, except to a small extent in cases of low zinc content in breast milk of mothers less than 2 months postpartum . TherefoZinc supplementation has been shown to improve child health by increasing child weight, boosting the immune system, and decreasing the risks associated with lower respiratory tract infections and diarrheal disease . If in jZinc supplements in combination with oral rehydration salts have been shown to decrease the duration, and mortality of diarrheal disease 1] and a and a1] The NSDS consists of a silicone nipple shield, adapted to hold a therapeutic-containing (such as zinc) insert. The device is designed so that when it is worn by a mother during breastfeeding, it allows the release of active pharmaceutical ingredient(s) (APIs) into milk consumed by the infant, as illustrated in The NSDS would be disposable in settings where it would not be possible to ensure the device were cleaned appropriately, such as resource-limited settings lacking potable water. Though zinc supplements are typically administered in water, breast milk can be used as a replacement administration fluid 13]. The. The13].Using a breastfeeding simulation apparatus, Gerrard et al. have screened model compound release rates from rapidly disintegrating tablet formulations under physiologically relevant breastfeeding conditions . Specifiin vitro apparatus for simulating maternal lactation and infant suction in the world, to the best of the authors’ knowledge. Through this study, the impact of tablet composition and manufacturing conditions on API release from the NSDS was investigated.In the present study, release of a water soluble API, zinc sulfate, was investigated from multiple rapidly disintegrating therapeutic tablet formulations. This was characterised using the breastfeeding simulation apparatus developed by Gerrard et al.  to deterThe zinc content of the tablets was chosen to fall within a range of clinically tested zinc treatment values . Zinc suHuman milk was donated and mixed from 2 healthy mothers who had given written consent for their milk to be used for research . All donors were screened negative for HIV 1 and 2, HTLV I and II, Hepatitis B and C, as well as Syphilis. The use of the milk for the purposes of this study received ethical approval from the University of Cambridge’s Cambridge Human Biology Research Ethics Committee. Milk was stored at -80°C, then thawed at 3°C followed by room temperature before use in the study.Creamatocrit and protein content of the milk was experimentally determined. To measure the creamatocrit, samples were drawn into capillary tubes, then sealed with plasticine before centrifuging in a Sigma 1–14 microcentrifuge with a microcentrifuge rotor  at 12000 g for 15 min . ProteinMilk density was measured using a hydrometer  at temperatures in the range produced during the simulation apparatus tests (34.4–34.7°C) which simulate mouth temperatures that could be present during NSDS use .The composition of milk tested fell within the ranges reported in literature 14], and, and14],Biconvex directly compressed zinc-containing tablets were manufactured in-house based on two compositions using the materials outlined in Tablets were of two different compositions, and compressed with varying forces, resulting in four different types of tablet. Tablet length, height, and width were measured using vernier calipers. The crushing force of the tablets oriented diametrically was measured using an Eweka TBH200 hardness tester . This physical characterisation data is shown in Tablet disintegration testing was performed by United States Pharmacopeia (USP) methods with a basket rack assembly disintegration apparatus  .Breastfeeding practices depend on both the mother and child’s behaviours and physiology, as well as the time of day, time within the feed, and infant’s age. Infants breastfeed for nutritive and non-nutritive purposes, with feed volumes and sucking behaviours differing between the two 22]..22].in vitro [The breastfeeding simulation apparatus by Gerrard et al. mimics a mother’s lactation and infant’s suction behaviours during breastfeeding in vitro . The appThe suckling rate of an infant ranges widely, being reported as 46–126 cycles per minute  with peaThe experiment was performed in triplicate for each tablet for 20 minutes each, twice the length of time of an average breastfeed .The zinc concentrations in breast milk samples and in the tablets were determined at the MRC Human Nutrition Research Unit  using an ICP-OES (Jobin Yvon Horiba–ULTIMA 2C) equipped with a concentric glass nebulizer (0-1ml/min sample flow rate), a 50ml glass cyclonic spray chamber and a radial torch with an 3mm i.d. alumina injector. Sample solutions were introduced from an auto-sampler (Jobin Yvon Horiba AS500) using a sample probe with 0.75mm i.d. sample tubing and 0.76mm i.d. pump tubing (black/black). Instrument operating conditions were: 1300W RF power, 12 L/min plasma gas flow, 2 L/min sheath gas flow.Breast milk samples were prepared by 1:20 dilution volumetrically with diluent composed of ultra-high purity water (Sartorius Stedium Biotech Arium pro UV Water Polisher), 0.002% TritonX100 , and 1ppm molybdenum  as an internal standard. Samples were then vortexed with a Fisherbrand Whirlimixer .For the elemental zinc content analysis, tablets were ground using a mortar and pestle and added to ultra-high purity water and incubated at 37°C overnight. The samples were then vortexed and diluted 1:20 volumetrically in diluent before being analysed by ICP-OES.Calibration standards of zinc  diluted 1:20 volumetrically in diluent with a final concentration of 0.1% nitric acid were prepared to achieve a concentration range of 0.05–50 mg /L.2*s-3*A-1) and 955V (kg*m2*s-3*A-1) respectively, with an integration time of 0.5s for both.Zinc and Molybdenum were detected at 213.856 nm and 202.030 nm using a photomultiplier tube voltage of 605V . Two calibration curves, high and low range, were produced for zinc concentrations in the ranges of 0–0.5 mg/L and 0.5–50 mg/L. Zinc concentration in each sample was calculated using the respective linear regression equation from of the ratio of the mean intensity for zinc to the mean intensity for molybdenum. The zinc amount in the original sample was calculated based on the dilution, the sample weight and the milk’s density at the experimental temperature. Zinc concentrations were measured for 9 interspersed samples chosen from 30 samples collected from each breastfeeding simulation. Zinc concentrations of the remaining samples were estimated using linear interpolation. Release profiles based on cumulative zinc release over 20 minutes of running the simulation were then generated. Each experiment was performed in triplicate.The zinc content of the tablets detected by ICP-OES is shown in Based on Release of zinc from the NSDS requires the API to have either dissolved into the human milk, or to have disintegrated enough into for it to pass through the holes of the NSDS. Zinc release was quantified in breast milk using a novel inductively coupled plasma optical emission spectrometry (ICP-OES) technique, unique because it did not require sample digestion via microwave. This technique is a large step forward in rapid analysis of API release from the NSDS, as milk is inherently a complex fluid in which to detect analytes because of its heterogeneous composition . Other mThe total release of zinc that occurred during the breastfeeding simulations from the tablets loaded in the NSDS, as detected via ICP-OES, is summarised in The disintegration time of the tablets of the same composition and differing hardness was not significantly different (P = 0.3922 for Composition 1 and P = 0.1140 for Composition 2), based on an unpaired t test using Welch’s correction. The disintegration times between T2 and T4, two types of differing composition but with harness differing by just 6%, also were not statistically different by the same test (P = 0.5208).No tablet type released the full loaded dose of zinc. Ideally the full dose of API would be released from the tablets loaded into the NSDS during use. Total zinc release ranged from 32–51% of the loaded dose for the various tablet types. Although T1 released the most, and T4 the least zinc on average, unpaired t tests using Welch’s correction, indicate that neither the tablets of the same composition, nor those of the same hardness had total zinc release amounts that were statistically different from one another, with . This test, being based on single values, does not take into account the trend in the data shown in the profiles, which can indicate hardness and compositional effects on zinc release over many time points.Zinc release profiles from the NSDS under physiologically relevant conditions using the breastfeeding simulation apparatus is shown in The figures indicate that the average amount of zinc released was higher for the harder tablets of each composition for the duration of the simulations, though as mentioned the total zinc amount released was not statistically different for either pair in Figs By comparing release profiles of zinc for T2 and T4, two types with similar hardness, impact of composition can be seen, as shown in f2, the similarity factor as shown in Formula 1, was calculated. This factor, used by the Food and Drug Administration (FDA) and European Medicines Agency (EMA) is typically used in comparing the similarity of dissolution profiles for solid oral dosage forms [To compare the release profiles, ge forms .Tj, the test value, and Rj, the reference value, over all time points, n. The factor is 100 when the profiles are identical, and lowers as the profiles become less similar. The FDA and EMA suggest that the profiles can be considered similar when f2 is over 50.The similarity factor is a function of f2 = 63.5 for Composition 1 and f2 = 54.4 for Composition 2). The two tablet types of differing composition and similar hardness also had similar release profiles, with f2 = 53.3.The release profiles of the tablets tested of the same composition were found to be similar to each other Click here for additional data file.S2 File(PDF)Click here for additional data file.