DNA methylation is an important epigenetic modification that is known to be altered in rheumatoid arthritis synovial fibroblasts (RASF). Here, we compared the status of promoter DNA methylation of SF from patients with very early RA with SF from patients with resolving arthritis, fully established RA and from non-arthritic patients. DNA was hybridized to Infinium Human methylation 450k and 850k arrays and differential methylated genes and pathways were identified. We could identify a significant number of CpG sites that differed between the SF of different disease stages, showing that epigenetic changes in SF occur early in RA development. Principal component analysis confirmed that the different groups of SF were separated according to their DNA methylation state. Furthermore, pathway analysis showed that important functional pathways were altered in both very early and late RASF. By focusing our analysis on CpG sites in CpG islands within promoters, we identified genes that have significant hypermethylated promoters in very early RASF. Our data show that changes in DNA methylation differ in RASF compared to other forms of arthritis and occur at a very early, clinically yet unspecific stage of disease. The identified differential methylated genes might become valuable prognostic biomarkers for RA development. Even though these individuals have an increased risk of developing RA, not all of them do and it remains a challenge to discriminate patients at a very early stage of RA from patients with resolving arthritis.Rheumatoid arthritis (RA) is a chronic, destructive autoimmune arthritis that affects 0.5–1% of the population worldwide. The development of RA begins long before patients present with the characteristic symptoms of RA. Many patients develop unspecific symptoms and signs of systemic autoimmunity i.e. auto-antibodies years before disease onset4 and pathway analysis of differentially methylated sites (DMS) suggested that these changes affect genes previously implicated in the pathogenesis of RA5. Thus, it is assumed that changes in DNA methylation contribute to the activated and destructive phenotype of RASF.Synovial fibroblasts are major contributors to joint inflammation and destruction in RA. Changes in DNA methylation have long been recognized in synovial fibroblasts of RA patients (RASF)6. A number of hypomethylated and hypermethylated regions have been found to be involved with disease pathogenesis. Recent research has shown that the 5-mC modification of DNA can be converted into 5- hydroxyl-methylcytosine (5-hmC), 5-formyl-cytosine (5-fC), 5-carboxyl-cytosine (5-caC), and reconverted into 5-mC through the activation of ten-eleven translocation family enzymes (TET1–3) and thymine DNA glycosylase (TDG)7. This mechanism of DNA demethylation and 5-hmC is associated frequently with active gene expression.DNA methylation involves a methyl group attached in the 5′ position of the cytosine base pair ring called 5-methylcytosine (5-mC). This chemical modification is catalysed by a family of enzymes called DNA methyltransferases.In humans, the enzymes DNMT1, DNMT3A and DNMT3B have been shown to methylate genomic DNA. Most methylation of DNA is found at CpG dinucleotides. Sequences that have high percentage of C and G nucletoides and have a length of 1000 bp constitute genomic regions called CpG islands. When these regions are methylated, they cause gene silencing. DNA methylation has been analysed in different disease such as fibrosis, cardiovascular and cancer9. Thus, it is difficult to estimate which changes in DNA methylation are RA specific and which are OA specific and it is unknown up to now how changes found in RASF compare to other inflammatory arthitides.Two aspects in the analysis of DNA methylation in RASF, however, have not been addressed until now. Firstly, it is not known whether changes in DNA methylation are a cause or a consequence of the chronic inflammatory process in RA. Published studies so far have used SF from patients who have already fulfilled classification criteria for the diagnosis of RA; it is not known how early in the disease process changes of DNA methylation occur in SF. Secondly, current studies mostly analyzed differences in the DNA methylation profile of RASF compared to OASF. Synovial inflammation frequently occurs in OA and while not growing invasively like RASF, transcriptome studies comparing OASF with healthy SF and RASF show clear differences between healthy SF and OASF, indicating that OASF also display an altered phenotypeTo address these questions we analyzed the DNA methylation profile of SF isolated from patients with total symptom duration of three months or less who fulfilled the 1987 ARA criteria by 18 months after the biopsy was taken. The DNA methylation profile of these very, early RASF (veRASF) was compared to SF isolated from healthy individuals experiencing transient joint pain without histological signs of arthritis (nSF) as well as to SF isolated from patients with transient, non-destructive arthritis of varying etiology, which resolved within 18 months (rSF) of biopsy taken. Furthermore, SF from patients with established, long-standing RA (estRA) were included. With this approach, very early changes of SF in the RA disease process compared to normal SF as well as to other types of arthritis could be identified.DNA methylation patterns of nSF were compared to DNA methylation of rSF, veRASF and estRASF. We focused our analysis on promoter regions, as promoter DNA methylation is most likely to have an impact on gene expression. Analysis of differentially methylated CpG sites in promoter regions (DMP) revealed 772 significantly differentially methylated CpGs between nSF and rSF, 1792 between nSF and veRASF and 2168 between nSF and estRASF  within promoter regions. These changes in DNA methylation are believed to directly affect gene transcription. For each disease stage, we found a specific set of CpG islands with differences in DNA methylation Table . CpG islLast, we used the individual DMS , a member of the Wnt signaling pathway compared to patients with resolving arthritis12. Also in studies analyzing changes in DNA methylation of SF isolated from TNF transgenic mice at different time points and of patients with treated established early and late RA, the Wnt signaling pathway showed stage specific changes14. Most interestingly, DNA methylation in antigen presentation network processes was specifically altered in veRASF and estRASF, but not in rSF. SF are recognized as antigen presenting cells that can induce adaptive immune functions16. Our data strongly suggest that antigen presentation by SF is activated early in RA and thus might be a crucial contributor to the propagation and chronification of the autoimmune response in RA. Together, these data consistently demonstrate that despite presentation in very early or undifferentiated forms, distinct pathways already operate in the synovium of RA patients at very early stages.Our data confirm findings of studies analyzing RA patients in this very early window of clinically apparent disease. In synovial fluids of RA patients of this stage, levels of several cytokines and growth factors were higher than in patients with other causes of arthritis and with established RA17 and we also detected global hypomethylation in veRASF (data not shown). It is important to stress that the experimental and bioinformatics tools, applied by us in the current study and by others in previous studies, are not suitable for measurements of global methylation. Global DNA hypomethylation as found in RASF mainly originates from a loss of DNA methylation in non-coding, repetitive and LINE retrotransposable sequences, which is not captured with methylation arrays18. Thus, similar to findings in cancer cells, RASF present with global DNA hypomethylation, but promoter-specific hyper and hypomethylation.Our analysis showed a shift towards hypermethylation of gene promoters in RASF compared to nSF. Previously, we observed global hypomethylation in SF from RA patients in late disease stages19, suggesting a role of MFAP2 in regulating the release and activity of these factors that were previously implicated in arthritis development. The enzyme PM20D1 recently has been shown to play a role in glucose homeostasis and energy expenditure by controlling the biosynthesis of lipid metabolites in the body20. SHROOM1 has been found differential methylated in knee chondrocytes of OA patients21 and was connected to microtubule rearrangements during cell elongation22. DDR1 tyrosine kinase was found to bind collagens23 and can regulate various cellular processes such as migration, invasion and cell proliferation. Overall, our data provide promising targets for further functional experiments that could elucidate the phenotypic changes of RASF and their invasive behavior.Our study identified several CpG islands that were specifically hypermethylated in SF from very, early and/or established RA, but not in resolving arthritis. MFAP2 (MAGP1) binds TGFβ and members of the bone morphogenic protein (BMP) family24. Currently, studies are initiated to test the suitability of these sites to predict RA development in synovial biopsies of patients with undifferentiated arthritis.More importantly, we identified a set of genes with substantial differences in DNA methylation between very early RA and resolving arthritis, in particular SHROOM1. These differences could serve as valuable biomarkers for early diagnosis of RA. Methylated DNA is very stable. It can been detected in archived clinical samples, such as paraffin embedded tissue samples and is already used as biomarker in clinical practice, for instance in glioblastoma patientsIn summary, this is the first study providing evidence that DNA methylation in RASF is changed in the very earliest stages of untreated RA. Furthermore, our data confirm several previous studies suggesting that cell adhesion, cytoskeletal rearrangement and alterations in the Wnt signaling pathway in SF play a role in RA disease development. Future studies will explore how such changes in DNA methylation are induced, how the identified genes and pathways contribute to the pathogenesis of RA and whether the changes in DNA methylation can be used as prognostic biomarkers for the development of RA.11 after written informed consent and permission from the West Midlands Black Country Research Ethics Committee. In addition, we confirm that all the experiments were performed in accordance with the relevant guidelines and regulations. SF were isolated and cultured as previously described25. Normal SF were obtained from individuals experiencing transient joint pain without histological signs of arthritis. VeRASF and rSF were isolated from treatment naïve patients presenting with inflamed joints with a symptom duration of 3 months or less. Patients were retrospectively classified as having had veRA if they fulfilled the American Rheumatism Association (ARA) 1987 revised criteria for the classification of RA within 18 months of the biopsy taken26. EstRASF were isolated from patients fulfilling the 1987 ARA criteria at presentation. A detailed description of the patients is given in Supplemental Table Ultrasound guided biopsies were taken from patients recruited to the UK Birmingham early arthritis (BEACON) cohort27. Preprocess normalization was performed using the ssNoob method. Probes from the X and Y chromosome were removed to exclude sex variability and probe type bias was corrected using the rcp method as described in the Enmix bioconductor package (1.12.0). Individual beta values for each sample were calculated for further statistical analysis. Beta values are defined as the ratio of methylated probe intensity and overall probe intensity (sum of both unmethylated and methylated probe intensity).DNA was isolated from cultured fibroblasts with the DNA blood kit (Qiagen). DNA was converted by sodium bisulfite modification and hybridized to Infinium Human methylation 450k and 850k arrays. The raw intensity data (IDAT) were imported into R version 3.4.0 and processed using the minfi (1.22.1) Bioconductor package. Since the methylation data sets were run on different Illumina array types, we combined the arrays at a probe level into a single 450k array with the minfi function ‘combine Arrays’ as previously published. All the samples passed the mean detection p-value of the minfi sample quality standard28. A CpG site was counted as methylated if the beta value was greater than 0.4 and unmethylated if it was below 0.3. Differential methylated CpG sites (DMS) in promoter regions (DMP) and/or CpG islands that showed mean beta value differences of 0.1 and p-values below 0.05 were defined as significantly differentially methylated between the different conditions. Integrative Genome Viewer (IGV) was used to visualise the DMS. Principal component analysis (PCA) and plot heatmaps were computed using the entire set of significantly differentially methylated CpGs between different conditions.The COHCAP algorithm was applied for the statistical analysis of differentially methylated CpG sites and islandsPathway analysis was performed using MetaCore software (Thomson Reuters) version 6.31 using the process networks gene ontologies default analysis in differential methylated CpGs of each comparison.Genomic DNA was prepared from fibroblasts using the QIAamp DNA Blood Mini kit (Qiagen). The DNA (1 µg) was bisulfite modified using the EpiTect bisulfite kit (Qiagen). A PCR amplification of bisulfite modified DNA (2 µl) were performed using the Pyromark PCR kit (Qiagen). The PCR program was 95 °C 4 min; 95 °C 30 s, 56 °C 30 s, 72 °C 2 min x 35 cycles; 72 °C 4 min. We use the HS-SHROOM1_06_PM pyromark primers (Qiagen).The PCR products were visualised with agarose gel electophoresis. Then, they were directly sequenced using the PyroMark Q48 Autoprep (Qiagen) according to the manufacture instructions.EstRASF were cultured in the presence of 0.5, 1 and 2 μM 5-Azacytidine (5-AzaC) for 6 days. Then, total RNA was extracted with Miniprep kit (Qiagen) and reverse transcribed to cDNA with reverse transcriptase (Applied Biosystems). Quantitative PCR reaction was performed with SYBR green (Roche) on Taqman 7500 Real-time PCR system (Applied Biosystems). Exon spanning specific primers for DNMT1 FW 5′TAACAGAAAAGGAATGTGTGAAGG3′ REV 5′TATTTCTGTTTGCAGAAATTCGTGC3′ and TET1 FW 5′TGCACCCTCAATGAAAATCGT3′- REV 5′GGGCTTGGGCTTCTACCAAA3′ were used. Cycle thresholds (Ct) were normalized to the housekeeping gene RPLO.The datasets generated during and/or analysed during the current study are available with the ArrayExpress accession code: E-MTAB-6581 and E-MTAB-6582.Supplementary informationDataset 1Dataset 2Dataset 3


Saccharomyces cerevisiae has been a workhorse of synthetic biology, owing to its genetic tractability. Here we demonstrate the ability to synthetize, in a simple manner, tandem DNA repeats of various size by Cas9-assisted oligonucleotide in vivo assembly in this organism. We show that long tandem DNA repeats of several kilobases can be assembled in one step for different monomer size and G/C content. The combinatorial nature of the approach allows exploring a wide variety of design for building synthetic tandem repeated DNA directly at a given locus in the Saccharomyces cerevisiae genome. This approach provides a simple way to incorporate tandem DNA repeat in synthetic genome designs to implement regulatory functions.DNA repeats constitute a large part of genomes of multicellular eucaryotes. For a longtime considered as junk DNA, their role in genome organization and tuning of gene expression is being increasingly documented. Synthetic biology has so far largely ignored DNA repeats as regulatory elements to manipulate functions in engineered genomes. The yeast  This fraction of eukaryotic genomes has long interested a large research community, with questions ranging from their evolutionary origin and function2, their epigenetic effect on gene expression3 to their role in three dimensional genome structure4. Interest in their evolutionary dynamics also stems from their role as markers for genetic footprinting5 and in human diseases, like Huntington disease, myotonic dystrophy type 1 and several neurodegenerative diseases7. Yeast has long been a model of choice to study the biology of tandem DNA repeats. Large cloned arrays of human tandem DNA repeats inserted into the yeast genome10 or carried by a plasmid11 are stable across a wide array of size in a wild type background, allowing for identification of genetic pathways associated to repeat instability. Analyses of yeast mutant strains carrying tandem DNA repeats have allowed a better understanding of the roles of replication, DNA repair, recombination, transcription or DNA structures in genetic stability of trinucleotide repeats12 or human G-rich minisatellites10.Tandem DNA repeats constitute a large fraction of eukaryotic genomesS. cerevisiae genome contains natural tandem DNA repeats that have been studied for their potential functional role and capacity to evolve under phenotypic selection15. A classical example is the FLO genes locus, in which copy number of FLO genes influence the flocculation phenotype and cell adherence to surface16. Another well-studied example is the copy number of rDNA genes, which can vary greatly between natural strains. Copy number variation within the rDNA locus has served as a model to understand concerted evolution of repeated DNA sequences or the role of replication stress in influencing copy number17. A measurable phenotypic effect of tandem repeat copy number variation (CNV) has also been shown for short nucleotide repeats located inside yeast promoters18. These studies highlight the potential of S. cerevisiae for testing phenotypic consequences of CNV of given tandem DNA repeats.in vitro step, either by enzymatic ligation of monomers19, by polymerase chain reaction (PCR)9 or by rolling circle amplification (RCA)11. Synthesis by ligation allows controlling the number of repetition to be assembled, whereas PCR and RCA allow generating larger repeats. In the case of PCR, sequence heterogeneity of the repeat monomer is often large, owing to PCR frequent mispriming, whereas with RCA long sizes of faithfully replicated tandem repeats can be achieved. However, this technique is not well suited to engineer polymorphic repeats. To circumvent some of the limitations offered by the existing methods, we reasoned that a more versatile approach to generate synthetic DNA repeated arrays inside the yeast genome should be advantageous for many synthetic biology projects. Thanks to the efficiency of homologous recombination in S. cerevisiae, many techniques allowing direct DNA assembly in yeast using donor DNA from plasmids, PCR products or oligonucleotides have been proposed in the past22. These also include recent technologies of genome editing relying on CRISPR/Cas9 enzymes to selectively drive assembly of donor DNA at an induced double stranded break. CRISPR/Cas9 allows easier scar-less genome editing, improves editing efficiency, and eases multiplex genome editing when compared to older techniques28.Experimental approaches to insert synthetic tandem DNA repeats in the yeast genome have been devised in the past. To generate the repeats, the main experimental approaches rely on an In this report, we show that a simple experimental approach using CRISPR/Cas9 to assist insertion of partially overlapping oligonucleotides allows to generate in one experimental step a diverse library of tandem DNA repeat arrays, ranging typically from 1 to about 100 repeats in size. We show that the efficiency depends on the size of the monomer and to a lesser extent to the G/C content of the repeats. In particular, the approach was successful for building repeated arrays from monomers ranging in size from 46 to 165 base pair (bp). The approach should be useful for synthetic chromatin or promoter engineering, or functional genomics studies.in vivo by a CRISPR/Cas9 complex. We chose to target assembly of synthetic repeats into the non essential YMR262 gene of chromosome XIII, which does not contain natural repeats . In a second step this Cas9 expressing strain was co-transformed with a 2μ plasmid constitutively transcribing a guide RNA targeting codon 79 in the YMR262 gene as the Cas9 cutting site, partially complementary oligonucleotides promoting repeat assembly, and two donor DNA fragments containing complementary regions to both genomic sequence surrounding the double DNA strand break and to the assembled repeats  in a single step experiment, for different monomer size and GC content. Interestingly, we observed that short GC rich stretches of 7–10 nucleotides are sufficient for oligonucleotide annealing. In our experience, short GC rich stretches homologous between oligonucleotides introduced sequence variability within the assembled repeats. This suggests that overlapping sequences between oligonucleotides used to drive repeat assembly could be shortened from 20 to stretches of 10 G/C nucleotides. The approach was not very efficient for building arrays of tetranucleotide repeats that were diverse in size. Therefore, alternative oligonucleotide designs could be explored for microsatellite design, for example by reducing the size of the region complementary to the assembled repeats within the donor DNA, to minimize direct repair by donor DNA without oligonucleotide insertion.The goal of this study was to provide a simple experimental way to build tandem DNA repeats of various sizes in the genome of 32.In this study, we only sequenced shorter repeats amenable to PCR amplification and Sanger sequencing, but a different strategy would have to be implemented for the sequencing of longer repeats. Long read sequencing technologies like nanopore sequencing or SMRT sequencing can today circumvent issues posed by sequencing of long tandem DNA repeats33 or for bottom-up engineering of regulatory regions, like promoters and enhancers35. Indeed, the approach presented here provides an alternative to combinatorial design of promoters34, e.g. with the introduction of transcription factor binding sequences in non overlapping oligonucleotide regions. Since repeats are assembled statistically from the oligonucleotide mix provided during transformation, providing alternative oligonucleotide sequences located in non overlapping regions of the repeat should be straightforward to increase the diversity of the library assembled into the repeated array. For example, the oligonucleotide designs proposed here for 46 bp and 165 bp monomers allow respectively 9 and twice 22 non overlapping nucleotides where diverse binding sites can be incorporated. Noteworthy, this approach should also be an interesting addition to the techniques developed by the Sc2.0 project (www.syntheticyeast.org) for the synthesis of a yeast synthetic genome, allowing introduction of repeated sequences in the synthetically assembled building blocks. Our technique therefore prevents the need to design repeats in the synthetics “chunks”36, as they can be assembled directly in vivo following sequence replacement. The only limitation of our technique is that it does not allow to predetermine the exact number of repeats added. However, given the large number of repeats that can be added by this approach, it might still be cost effective to select from a large library of engineered repeats as opposed to fully construct large repeats in vitro. Finally, the approach would be easily testable in other systems than S. cerevisiae, depending on the ability of the host system to favor homologous recombination over non-homologous end joining to repair DNA double strand breaks.In conclusion, beyond building homologous tandem DNA repeats, the approach should allow engineering combinatorial libraries of heterogenous repeats that can be selected through an appropriate phenotypic screening of the recombinant cells Fig. . DrawingSaccharomyces cerevisiae strain YPH499 (ATCC # 204679) was used as a parental strain throughout the study. YPH499 derived strains and plasmids relevant to this study are listed in Supplementary Tables The in vivo from overlapping oligonucleotides (Supplementary Table DNA repeats were assembled http://crispor.tefor.net/)37 was used to select guide RNA sequences for targeting the YMR262 locus without any off-target (Supplementary Table 24) and replaced the 20 bp gRNA CAN1 target sequence by the YMR262 target sequence. First, the backbone of vector p426-SNR52p-gRNA.CAN1.Y-SUP4t was amplified by PCR with primers AL-O-44 and AL-O-45 using the Phusion HF DNA polymerase (New England Biolabs). The backbone was digested with ClaI and KpnI to create compatible ends for cloning. A claI/KpnI fragment was synthetized by PCR using primers AL-O-46 and AL-O-47 and p426-SNR52p-gRNA.CAN1.Y-SUP4t (Addgene # 42803) as a template. Upon cloning between ClaI and KpnI sites, the resulting plasmid (pAL31) contains the 20 bp gRNA genomic target sequence under control of the SNR52 promoter, followed by the tracrRNA sequence and the SUP4 terminator. To construct a Cas9 expression plasmid containing a HIS selection marker, p414-TEF1p-Cas9-CYC1t (Addgene #43802) and pRS41338 were cut with enzymes AhdI and DraIII (New England Biolabs). The backbone of pRS413 containing the CEN/ARS sequence and both AmpR and HIS3 selection markers was gel purified and ligated to the fragment of p414-TEF1p-Cas9-CYC1t containing the human optimized Cas9 gene under the TEF1p promoter (pAL30). The correct sequence of the CAS9 gene was verified by Sanger sequencing.The CRISPOR tool  using primer couples AL-O-24/25–33 and AL-O-43/34–42, with YPH499 genomic DNA as a template. The left junction was designed so that the YMR262 promoter and the beginning of the gene are lost upon recombinational insertion Fig. . The YPH32-radio-labeled probe synthetized by PCR with primers AL-O-50 and 51 (Fig. in vivo upon transformation, the size of the band revealed by this probe should be 2.92 kb plus the size of the integrated repeated array. Sanger sequencing of the repeat, including around 100 bp of surrounding genomic DNA, was performed on PCR products using primers listed in Supplementary Table Screening was done by purification of genomic DNA from yeast transformants followed by Southern blotting. Genomic DNAs from twenty clones of each repeat design were digested with BamHI and DraI, which cut at each side of the insertion locus Fig. . For the 51 Fig.  using YPSupplementary Material


Subsequent multivariate analysis of NMR data by Principal Component Analysis (PCA), and Partial Least Square Discriminant Analysis (PLS-DA) allowed data reduction and cluster analysis. This strategy ensures the definition of specific features in the metabolic content of phenotypically similar SCs sharing a common developmental origin. The metabolic fingerprints for selective metabolites or for the whole spectra demonstrated enhanced peculiarities among cell types. The key result of our work is a neat divergence between OECs and the remaining NSC cells. We also show that statistically significant differences for selective metabolites characterizes NSCs of different ages. Finally, the retrived metabolome in cell cultures correlates to the physiological SC features, thus allowing an integrated bioengineering approach for biologic fingerprints able to dissect the  SC molecular specificities.Cell metabolism is a key determinant factor for the pluripotency and fate commitment of Stem Cells (SCs) during development, ageing, pathological onset and progression. We derived and cultured selected subpopulations of rodent fetal, postnatal, adult Neural SCs (NSCs) and postnatal glial progenitors, Olfactory Ensheathing Cells (OECs), respectively from the subventricular zone (SVZ) and the olfactory bulb (OB). Cell lysates were analyzed by proton Nuclear Magnetic Resonance ( Therefore, SCs are currently used in several biomedical applications, especially to replace or repair pathological tissues in regenerative medicine, as well demonstrated for amyotrophic lateral sclerosis2. Stem cell cultures appear as a heterogeneous mixture of functional subpopulations, characterized by distinct self-renewal and differentiation biases, able to generate a progressively restricted repertoire of cell types (progenitor cells)3. Heterogeneity is also high in other SC types, such as pluripotent SCs, Embryonic Stem Cells (ESCs) and induced pluripotent stem (iPS) cells, so their application to cell therapy requires accurate selection of pure SCs populations3. To fulfill safety criteria for regenerative medicine4, the absence of residual undifferentiated SCs and preparations of pure standardized SCs should be guaranteed, as requested by the International Society for Stem Cell Research (ISSCR)6.Stem cells (SCs) are undifferentiated cells in organisms, which could indefinitely proliferate or generate differentiated cell types able to perform specific physiological functions. Their organized proliferation and cell fate determination allow the formation of both tissues and organs during embryonic development, whereas their permanence in restricted niches consents tissue repair and maintenance in adulthood7, as well as clinical trials or cell therapy products1.In this general context, the determination of  biomarkers able to define SC/cell line identities and functions along passages plays an emerging key role for validating scientific studies8, as well as by the surrounding environment. Therefore, Nuclear Magnetic Resonance (NMR)-based metabolomic analysis10 is constantly gaining importance in the study of SC biology and for the discovery of biomarkers in vitro or directly in the Central Nervous System (CNS)15. Interestingly, alterations of metabolic demands has been also linked to ageing, (neuro)degenerative diseases16 and cancer17 with potential clinical application to improve diagnostic accuracy, define prognosis as well as predict and monitor treatment efficacy19. Robustness and reliability of quantitative analysis by proton NMR (1H-NMR) in metabolomics is supported by several reports wherein SC normal/tumor subtypes or their conditioned media may be efficiently distinguished by specific NMR patterns, as well as metabolites21. In this general scenario it should be pointed out that the possible use of standard NMR spectrometers and a sample preparation without any special requirement (e.g. the use of 13C-hyperpolarized initiators) is considered a plus for metabolomic profiling23.Recently, a pivotal role of metabolic pathways has been demonstrated in dictating SC fate since each cell metabolomic profile appears directly influenced by its proliferative or differentiative state1H-NMR technique in providing effective biomarkers for cell discrimination. NSCs are undifferentiated multipotent SCs located in the SubVentricular Zone (SVZ) of adult mammalians and able to generate differentiated both neuronal and glial progeny through intermediate progenitors24. Multipotent NSCs are present all along brain development: in embryonic brains they are mainly involved in tissue formation and neuron production, whereas later (P1) they participate to the functional development and remodeling of brain’s connections. Finally, in adult life NSCs remain quiescent only in specific brain areas and can be re-activated “on demand” to generate new neurons functionally integrated into the adult mammalian brain24. Therefore, NSCs shift their main commitment in vivo from creation of a brain neural network (E12) and its refinement (P1) to physiological (single) cell substitution in damaged or aged brain tissue. NSCs can be isolated from embryonic/postnatal or adult brains and maintained in vitro, but they are undistinguishable by cellular phenotype, differentiative potential as well as antigenic markers26.Actively proliferating Neural Stem Cells (NSCs) were here compared to a selected glial subpopulation, the progenitor Olfactory Ensheathing Cells (OECs), to test the reliability of 27. Although NSCs and OECs are functionally different, they both express nestin and share a common embryonic derivation   identification and quantitation of the SC metabolites obtained from the cell cultures by 1H-NMR spectroscopy, ii) discovery of selective and statistically significant metabolic markers characterizing SCs, with focus on the specific profile of OECs in respect to NSCs, and iii) the clustering and differentiation of the SC types on the basis of their metabolic profile via multivariate analyses29– Principal Component Analysis (PCA) and Partial Least Square Discriminant Analysis (PLS-DA) – of the entire 1H-NMR spectra.The metabolic profile of the different SC types was acquired and analyzed via 1H NMR metabolite was performed on the four different, but related, SC types  NMR experiments  showed small but significant peaks consistent with aromatic protons. Some signals could be unambiguously assigned to aromatic amino acids, such as Tyrosine (Tyr) and Phenylalanine (Phe) ) did not show statistically significant differences within the examined set of SCs .vs all the other SC types. Furthermore, to better sharpen the separation between groups, we carried out the PLS-DA analysis, which is presented in Fig. PLS-DA is a supervised method introducing a bias regarding the total number of cell types (four in this work) so the PLS-DA model provides better cluster separation. As PCA separation is achieved only when the intra-group variability is remarkably less than the inter-group variability, it provides an unbiased biological indication. Therefore, we used PCA analysis in order to obtain initial, unbiased information on the relationships among the datasets of the SC groups. The results are graphically shown in Supplementary Fig. http://3rs.ccac.ca/en/about/three-rs.html) severely hampered the use of a training set, leading us to the choice of internal cross-validation methods32. Therefore, the analysis was cross-validated by the leave-one-out validation protocol. The obtained predictive ability Q2 and model fitness R2 were 0.44 and 0.66, respectively, thus showing a first evidence of non-overfitting of data. As suggested33, this conclusion needs further confirmation by the permutation test. The results in our case for a permutation number = 100 are reported in the Supplementary Fig. p-value. For clarity, the same test in the case of PLS-DA on NSC subset only is also reported and displayed in Fig. Our decision to reduce the number of animals used for our experiments  we found that the multivariate analysis of the obtained data may contribute to a quantitative description of biologically significant differences in complex systems35, such as SCs.Our data demonstrate that the metabolic phenotyping of related SCs with similar intracellular content can be achieved by the straightforward application of routine NMR techniques and appropriate statistical analysis. As a matter of fact, selected stem/progenitor populations derived from CNS and maintained in culture mainly share the same metabolites, although in different proportions possibly reflecting preferential biological pathways related to developmental age, stem features and/or biological properties. Therefore, only particular approaches, such as multivariate analysis of NMR data (PCA and PLS-DA), can differentiate these cell types capturing their metabolic peculiarities. Similarly to others  clearly identifies some statistical differences between P1 OECs 24; and OECs, a distinct glial cell population with specific biological and molecular properties38. Therefore, the NMR profiles we present here are deeply different from the published NMR data on (single) neurons/astrocytic populations42 as well as from data on glioblastoma stem-like cells/human OB cells44.Differently from published literature, our NMR analysis was conducted on selected/pure brain cell subpopulations maintained in cultures: NSCs isolated at different ages and cultured as neurospheres 25. Concordantly, around 75% of the nine measured metabolites in our cell populations are related to these biological networks.Proteomic analysis on cultured NSCs derived at different ages revealed that the main five canonical pathways highly altered by ageing are related to glycolysis, fatty acid metabolism, propanoate metabolism, protein ubiquitination pathway, and valine, leucine, and isoleucine degradation45. Concordantly, the Glc content was also consistent in AD NSCs and almost negligible in OECs whose glial fate has been already established.The main representative metabolite for both E12 and P1 NSCs is Glc which is related to glycolysis and is essential for modulation of (cell) development, proliferation and differentiation46. The pivotal protective role of Tau in brain physiology is also demonstrated by its altered function in several neurodegenerative diseases wherein contributes to neuronal dysfunction and death47.Additionally, substantial intracellular Tau amounts specifically characterized NSCs, irrespectively of developmental age, but not OECs. The higher levels of Tau retrieved in all NSCs may be related to the key role of this metabolite in antioxidant response, regulation of SC fate/calcium exchange well as neurotransmission/neuromodulation along neural development and neuralization jointed to a neuroprotective and regulative action on apoptotic response48 and the ATP-binding cassette (ABC) transporters pathway which is physiologically involved in the membrane trafficking of several substrates  as well as in the regulation of SC biology50. Adult NSCs are quiescent cells able to react and proliferate in response to the environmental clues deriving from the surrounding complex network of neurons, microglia, astrocytes and blood vessels45. Interestingly, Tau levels were comparable between E12 and P1 NSCs, sharing a common embryonic origin48, whereas the highest content in AD NSCs may be related to a tighter activation/regulation of ABC transporters able to contrast ageing dysfunctions as well as neurodegeneration51.Essential for the physiological function of NSCs are Tau import53. In particular, recent literature has focused on the key role of astrocytes both in brain energy metabolism as well as in regulating synaptic neurotransmission54. Astrocytes are also capable to connect neurons to the surroundings and influence energy supplementation from circulation (neuro-metabolic/vascular coupling)53. Our data suggest that the metabolic compartmentalization necessary for neuron-astrocyte cooperation53 may be, at least partially, present early along differentiation starting from stem/progenitor cells.Physiological brain function depends on a constant neuron-glia crosstalk wherein energy reserves and metabolites are actively stored and exchanged between neurons and astrocytes characterized by different, but complementary metabolic specialization53, our data suggest that they are also fundamental for both NSC and OEC maintenance, probably in relation to their key role in preserving SC state and homeostasis14.Although considerable storage of Ace and Lac is classically linked to metabolic pathways inside astrocytes55 in conjunction with Ace astroglial trafficking56. As detected by both 13C-NMR41 and in vivo1H-[13C] magnetic resonance spectroscopy (MRS)57, the cell specific Ace uptake activates a glial metabolic pathway ending with the production of glutamine which can be transported to glutamatergic and GABAergic neurons for replenishing the neurotransmitter Glu (Glu-glutamine cycle) after synaptic transmission59. Glutamate is the major excitatory neurotransmitter of the brain which connects carbohydrate and amino acid metabolism via the tricarboxylic acid (TCA) cycle53 and it may act as a regulator of adult neurogenesis/differentiation61. Interestingly, we retrieved that Glu content is significantly increased in AD NSCs probably in relation to the crosstalk between neurogenesis and neurotransmitter signaling63 required for their “on demand” activation. In the adult niche NSCs are quiescent, but require rapid proliferation followed by differentiation to guarantee tissue homeostasis and renewal, especially in the presence of brain injury/damage24. Therefore, it is not surprising that AD NSCs possess peculiar hallmarks different from both OECs and their embryonic/postnatal counterparts, such as the highest Glu content. Moreover, we retrieved relevant and comparable levels of Glu and Suc in OECs and in the younger NSC types  whereas AD NSCs contained the highest  metabolite amounts. Concordantly, the key role of Suc and other molecules related to Krebs cycle (such as Glu) on stemness has been demonstrated in the physiological proliferation of AD NSCs64 coupled to their decrease in a human immortalized striatal neural SC line along differentiation65.The shuttle of branched amino acids/ketoacids between astrocytes and neurons appears fundamental for replenishing brain Glu reservesin vivo assignation of a specific glycolytic flux to any brain cell types by NMR spectroscopy59. Our data suggest that relevant Lac content is equally fundamental for the preservation of both NSCs and glial committed OECs, probably in relation to its involvement in antioxidant defense and SC homeostasis. Concordantly, metabolism of pluripotent and multipotent stem cells depends on glycolysis with hyperlactate production45. As matter of fact, all NSCs showed lower, but comparable content for Lac, indicative of a highly glycolytic metabolism, as already demonstrated in human NSCs66, whereas a decrease in Lac content has been already linked to the process of NSC differentiation45. Concordantly, astrocytes store higher Lac amounts as energy supply to the high energy demanding neurons of surrounding areas via a specialized shuttle transport67, as our OECs statistically did in comparison to E12/P1 NSCs.The retrieved comparable intracellular Lac content between AD and OEC samples is supported by literature data on the limited 68. This latter metabolic pathway is linked to the astrocyte specific antioxidant and neuroprotective capability to contrast endogenous ROS53. Moreover, similarly to astrocytes, the metabolic content in OECs suggests a possible active role of these cells also in neuromodulation as well as neurotransmitter synthesis and function. Altogether our data indicated that OECs and astrocytes appeared to share several metabolic hallmarks and may be equally able to support neuronal activity, but in different localization of the nervous system38. Concordantly to our observations, a developmental differences in Glu metabolism and neurotransmitter synthesis between postnatal and adult brain has been reported69.Alanine is a highly gluconeogenic amino acid and was retrieved among more representative metabolites only in P1 OECs encompassing almost 40% of their main analyzed metabolites along with some aromatic amino acids, which specifically characterize OECs. Alanine appears involved in a variety of brain biological pathways including glycolysis, fatty acid and amino acid metabolism, citrate and urea cycle as well as Tau and hypotaurine metabolismInterestingly our analysis on brain SC/progenitor cells also enlightened an overlapping metabolic pathway redundancy able to guarantee a fine tuning of proliferation combined to the highest antioxidant defense.17 nor apoptotic peaks70, but these discrepancies may be related to the procedures for sample preparation. Additionally, NSCs are characterized by very low intensity or absent lipid signals that are instead more frequently observed in cancer SCs43.Contrary to the literature, we did not observed NMR-detectable mobile lipids71. This tight regulation appears preserved even when cells are induced to proliferate and maintained under artificial culture conditions. Our findings also suggest that multivariate analyses of NMR spectra may be exploited as an effective tool for the selective (SC) identification in addition to the standard immuno-biochemical investigations.Altogether, the retrieved data suggest that several aspects of metabolism may distinguish NSCs from their differentiated counterparts (OECs). All the metabolites contained in OECs are functionalized to their supportive role to the surrounding neurons whereas the NSC differential activities, at least between fetal/postnatal and adult life, are mirrored by their metabolomes. Apparently, OECs and NSCs present a univocal characteristic metabolic signature, able to determinate their fate and properties, as already demonstrated for adult NSCs18, in a decade of failures of proteomics72, NMR metabolomics might turn out to also become an efficient, alternative tool in the search of human (disease) specific biomarkers.Mapping the physiological or pathological neurochemical profile of SCs by NMR may represent an invaluable tool readily transferable from research to therapeutic clinical interventions. Interestingly, as recently highlighted by Gebregiworgis and PowersOverall our data provide a detailed description of the metabolic fingerprinting of cultured brain cell subtypes which deserves to be further validated and deepened. The observed metabolome appears to be unaffected by extensive cell culturing and correlates to the specific tissue derivation, (stem) characteristics and properties. Our study also shows that NMR analysis may efficiently characterize AD NSCs, otherwise indistinguishable from embryonic/postnatal NSCs. Here we also provide a detailed metabolic characterization of cultured OECs which, at the best of our knowledge, has never been previously described. Therefore, the unambiguous clustering of NMR data either by quantitative or multivariate analysis could define the physiologic homeostasis and properties of the SC pool in different environments or describe their alterations in pathological conditions (such as ageing and neurodegeneration). Importantly, such strategy requires cooperation and integration among several methodologies and fields of expertise in order to provide a better description of biological features translatable into novel methodological or therapeutic approaches.All data generated or analyzed during this study are included in this published article (and into the related Supplementary Information files).Experiments were performed on CD1 mice obtained by Charles River Laboratories Italy). Animals were kept in a controlled environment  with a 12 h light/dark cycle with food and water available ad libitum. Experiments were performed in compliance with the Italian law and in accordance with the European Community Council Directive (86/609/EEC). All the experimental procedures were carried out and authorized in accordance with Italian Law 26/2014. The research protocol was approved by the ethics committee of IRCCS Istituto Auxologico Italiano. Animals were kept at the dedicated Animal Facility afferent to our Institute wherein we performed animal sacrifices at the specified time points. All possible efforts were made to reduce both the number of animals as well as their suffering.73. All cultures were analyzed in triplicate and 5 different cultures for each SC type were performed.Cortexes of E12.5 embryos (8–10 littermates for each experiment) and SVZs from postnatal P1 (8–10 littermates for each experiment) as well as adult (AD)  were dissociated to obtain single NSCs, as schematized in Supplementary Fig. 74. OECs were cultured in DMEM (high glucose) (Invitrogen-Thermo Fisher Scientific) +10% Fetal Bovine Serum , 2 mM L-glutamine, penicillin (50 U/ml) and streptomycin (50 µg/ml), all from Invitrogen-Thermo Fisher Scientific. All cultures were analyzed in triplicate and 3 different cultures for each SC type were performed.Primary OEC cultures were obtained from the olfactory bulbs of postnatal mice , which were dissociated, as previously described73.Stemness potential and differentiative capability of our cells were previously tested according to published literature6 cells/SC type). Adherent OECs (3 × 106 cells/SC type) were then harvested by trypsin digestion (as previously detailed74) while free-floating NSCs were collected by simple centrifugation, 200 relative centrifugal force (rcf), and rinsed with 5 ml of Phosphate-Buffered Saline buffer . Upon centrifugation at 4,000 rcf for 1 min, cell pellets were kept on ice for 5 min before being resuspended in 1 ml of ice-cold 50% acetonitrile  in PBS. Cell suspensions were kept on ice for 10 min before centrifugation at 16,000 rcf for 10 min at 4 °C. The aqueous acetonitrile extract method was chosen in accord with previous literature28. A total number of 51 samples (12 samples for each NSC type and 15 samples for OECs) were analyzed.The same amount of cells was analyzed  stock solution buffered at pH = 7.0. The solution is further diluted in 540 µl of D2O containing trimethylsilyl-3-propionic acid  1 mM as internal standard and then transferred in a 5 mm NMR tube. The PBS-D2O stock solution was obtained by dissolving a PBS tablet (Sigma-Aldrich) in D2O (Sigma-Aldrich) at a concentrations of 9.8 mg/ml.The aqueous acetonitrile extract solutions were dried down by a suitable concentrator  and the resulting white residue was dissolved in 60 µl of PBS-Deuterium Oxide  were acquired with mixing time of 200 ms, SW = 5400 Hz, D1 = 4 s, 2k data points in F2 dimension and 512 FIDs in the F1 dimension. For all the experiments, the temperature was kept constant at 305 K.All the NMR spectra were recorded on a Bruker Avance 500 spectrometer, Bremen Germany, operating at 500.13 MHz proton frequency and equipped with a QNP four-nuclei switchable probe. Standard All the one-dimensional NMR spectra were phase-corrected manually, while the baseline correction was performed automatically with a fifth order polynomial fitting routine. TSP was used as internal reference standard (0 ppm) for spectra calibration. The peak area was determined manually for each resolved peak representative of a single metabolite and then normalized respect to the TSP signal area. The final metabolite concentration is expressed as mM and reported in Fig. The assignment of the metabolite signals for each cell line was supported by the use of two-dimensional correlation NMR methods. In particular, 2D total correlation spectroscopy (TOCSY) experiments were extensively used.The first step in order to carry out PCA and PLS-DA is the so called “spectral binning”. After the NMR data processing described in the NMR section, spectral binning was performed on the 1D spectra by reducing the spectrum data points (32 k points) into a smaller number of segments (bins) of a defined width (0.04 ppm). The spectral area within each bin is then integrated to yield a vector that contains intensity based descriptors of the original spectrum. Binning was performed using MNova 6.0 software package .www.metaboanalyst.ca75. PCA and PLS-DA were performed on a wide spectral region, 0.5–9.5 ppm (the region from 4.5 to 5 ppm was blocked out due to water suppression artifact). Normalization for all of the spectral binning data is performed on the total area of the NMR spectrum. This is achieved by calculating the sum of all the variables within a spectrum and by normalizing each spectrum on such value. In this way, every single variable is converted to a fraction of the total spectral area or intensity. Pareto scaling is then applied. Accordingly, the variable mean was subtracted from each variable (column of the data) and then each variable was divided through the square root of its standard deviation. The raw data were then exported into Origin 9.0 in order to create three-dimensional graphs.The data were then imported into Metaboanalyst 3.0, an online tool freely available at PLS-DA is a supervised mathematical method able to enhance the cluster separation already obtained with the PCA method. For PLS-DA, the best linear combination of the original PCs are used as new variables. The results are shown in Fig. Analysis was conducted by a kit  for the quantification of extracellular L-Lac levels (the end product of glycolysis) which are proportionally correlated with intra-cellular glycolytic activity. Briefly, cells deriving from 2 different cultures for each NSC type (15.000 cells/well) were plated in duplicate in 96 wells and cultured for 60 hours. Afterwards, standards and samples  were processed and analyzed following the manufacturer’s instructions. L-Lac levels were calculated subtracting the absorbance levels of the corresponding cell-free media and corrected for the total cell number in each well.Quantitative analysis of Glucose (Glc) content in media was performed on 0.5 ml of NSC/OEC medium. Cells (25.000 cells/ml) were grown for the indicated times  and thereafter their media were collected and analyzed by NMR. Concentrations of Glc were calculated as difference between their value in naïve medium and the retrieved amount after cell growth. Each sample was prepared in triplicate and all data were normalized for the total cell number.www.genome.jp/kegg/pathway.html.Each experiment was run in triplicate and representative values were expressed as mean ± SD. Data were analyzed using One way ANOVA analysis followed by uncorrected Fisher’s LSD (the corresponding p is specified in the respective figure or table), using a dedicated statistical software . Metabolic pathways were investigated by the KEGG PATHWAY Database – GenomeNet, free available online at: Supplementary Information


Prostate organogenesis involves epithelial growth controlled by inductive signalling from specialised mesenchymal subsets. To identify pathways active in mesenchyme we used tissue and single cell transcriptomics to define mesenchymal subsets and subset-specific transcript expression. We documented transcript expression using Tag-seq and RNA-seq in female rat Ventral Mesenchymal Pad (VMP) as well as adjacent urethra comprised of smooth muscle and peri-urethral mesenchyme. Transcripts enriched in female VMP were identified with Tag-seq of microdissected tissue, RNA-seq of cell populations, and single cells. We identified 400 transcripts as enriched in the VMP using bio-informatic comparisons of Tag-seq and RNA-seq data, and 44 were confirmed by single cell RNA-seq. Cell subset analysis showed that VMP and adjacent mesenchyme were composed of distinct cell types and that each tissue contained two subgroups. Markers for these subgroups were highly subset specific. Thirteen transcripts were validated by qPCR to confirm cell specific expression in microdissected tissues, as well as expression in neonatal prostate. Immunohistochemical staining demonstrated that Ebf3 and Meis2 showed a restricted expression pattern in female VMP and prostate mesenchyme. We conclude that prostate inductive mesenchyme shows limited cellular heterogeneity and that transcriptomic analysis identified new mesenchymal subset transcripts associated with prostate organogenesis. Transcriptional profiling has been applied to whole prostate organs, both in development and adulthood6. These studies have identified dynamic expression of many pathways. However, the cellular complexity and proportions of different cell types within organs has led to difficulty in attribution of individual transcripts to defined cell subsets, as well as being confounded by changes in cell proportions over time or following hormonal manipulation. Within these datasets, it is difficult to deconvolute pathways expressed in either stromal or epithelial tissue compartments, although some studies have focussed upon mesenchymal and stromal tissue8. Since mesenchyme is known to regulate organogenesis as well as mediate the effects of hormones upon development, it is important to identify mesenchymally expressed pathways.The development of the prostate is regulated by androgens and mesenchymal:epithelial interactions. Several studies have demonstrated that paracrine acting factors made in the mesenchyme play key roles in regulating male reproductive organogenesis. Pathways such as Fgf, Wnt, TGFbeta, Shh, Notch, and others have been identified as participating in prostate development, though it is uncertain whether our knowledge of regulatory pathways is comprehensive . It has been shown that androgens control the formation of a sexually dimorphic layer of smooth muscle that separates VMP mesenchyme from nascent prostatic buds18. This layer may regulate inductive signalling from the VMP, and constitutes part of the hormonal mechanism controlling prostate organogenesis. The smooth muscle hypothesis accounts for the non-dimorphic expression of Fgf10 and other morphogens16. A prediction of this hypothesis is that morphogens are constitutively expressed in both males and females but are regulated indirectly by androgens and AR acting in the smooth muscle compartment. We have used VMP isolated from females on the day of birth as our model of prostate mesenchyme, since this is when the tissue is largest and also because female VMP lacks prostatic epithelia and is of low cellular complexity. At the same age in males, the VMP has become the Ventral Prostate, and contains a high proportion of branching epithelia, while the mesenchyme is differentiating into smooth muscle and other fibroblast types. Thus, female VMP is a model system with low cellular complexity that is optimal for identification of molecules involved in prostate development. We have previously used SAGE to identify transcripts specifically expressed in the VMP8, and noted that mesenchymal pathways may be dysregulated in cancer-associated fibroblasts, associated with EMT, or neuro-endocrine differentiation of tumours. These studies identified Ptn, Dlk1/Notch2, Scube1, EfnB1/EphB3, and Dcn in prostate development22. One of the limitations of SAGE is its low sensitivity in transcript detection, and next generation RNA sequencing based methods such as Tag-sequencing (Tag-seq) and RNA-sequencing (RNA-seq) have considerably higher sensitivity and superior transcript quantitation, as well as high resolution techniques such as single cell RNAseq.During prostate development, several morphogens are expressed in a subset of mesenchyme termed the Ventral Mesenchymal Pad (VMP) and the peri-urethral mesenchyme. The VMP is most apparent on the ventral aspect of the urethra but it encircles the urethra. Its formation precedes the formation of the ventral, lateral and dorsal prostate lobes. It has been defined as a source of inductive mesenchyme using tissue recombination studiesThe rationale for our study was to conduct a high resolution transcriptomic analysis of mesenchymal subsets and to examine homo/heterogeneity in regard to cellular composition, as well as to catalogue transcript expression. Cellular heterogeneity is a significant problem in whole organ and tissue transcriptional profiling. Comparison of transcript profiling from microdissected tissue and single cell RNA-seq (scRNA-seq) was used to identify transcripts with tissue and cell specific expression. The markers and pathways identified by such an approach can be deconvolved in whole organ datasets and prioritised for functional studies. We validated expression of VMP-specific transcripts by qPCR and also confirmed expression in neonatal prostate. Immunohistochemistry of Ebf3 and Meis2 confirmed expression in VMP and prostate mesenchyme.23. Tag-seq identified 1169 VMP and 1364 SU differentially expressed (DE) transcripts, while RNA-seq identified 761 VMP and 975 SU DE transcripts  co-identified 219 transcripts suggesting that a high proportion (54%) of DE transcripts are expressed during human prostate development  female rat urethra to isolate pure VMP mesenchyme as well as adjacent urethra comprised of smooth muscle, peri-urethral stroma and urethral epithelia (SU). Tissue pools were collected and processed for Tag-seq. As a comparator, pools of microdissected tissues were dissociated using collagenase, and 1000 cells from each pool used for RNA-seq. This dissociation enriched for mesenchymal cells in the SU sample, since epithelia remained intact and were separated from the stromal cells. VMP is wholly mesenchymal, though may contain residual traces of epithelia following dissection. Figure pts Fig. . When trpts Fig. . The fol8 8 Fig. . Gene On8 Fig. , as well8 Fig. .Figure 22 = 0.58) but not according to cell-cycle stage (PC23 R2 = 0.17) indicating that cell cycle has a minor confounding effect. We have observed that VMP cells do not grow as primary cultures, but that SU stroma will grow in vitro (unpublished), and we suggest that differences between VMP and SU tissues may include factors related to proliferation, but that differences in cell cycle are a minor component of our data. In total 49 VMP and 62 SU single cells passed quality control and were used for further analysis. The landscape of cells in 2D space is shown by principal component analysis (PCA) and showed a separation between VMP and SU cell types demonstrating that dissociated cell populations retained their different tissue identities  were used to identify DE transcripts from scRNA-seq data. 513 and 1407 DE transcripts were identified by MAST and scDD respectively with 352 transcripts common to both  of scRNA-seq identified DE transcripts are also expressed during human prostate development  to determine whether VMP and SU cells were homogeneous or composed of subgroups. With both algorithms, single cells were organized into four distinct clusters  and dorsal/dorsolateral prostate (DP) to compare expression between VMP and prostate lobes. Prostate tissue was composed of both mesenchyme and epithelia, thus mesenchyme-specific transcripts would be diluted due to the presence of epithelia in VP and DP. We examined 11 of our differentially expressed transcripts by qPCR in VMP, SU, VP and DP samples Fig. , as wellIn order to determine whether the differentially expressed transcripts were cell subset specific, we examined protein expression by immunohistochemistry upon P0 female and male urethra focussing upon the prostate and VMP. We chose two VMP enriched markers, transcription factors Ebf3 and Meis2, and documented their expression in serial sections of female and male P0 rat urogenital sinus tissue Fig. . We obse30. Signalling from the VMP and urogenital sinus mesenchyme can re-specify epithelial fate31 and partially re-differentiate prostate tumour epithelium32. Recently, we identified Asporin (ASPN) as expressed within a subset of human prostate mesenchyme20, and showed that ASPN was a marker of prostate tumour stroma associated with disease progression33. Similarly, expression of VMP specific morphogens in cancer associated fibroblasts was able to reduce tumour growth in a human prostate tumour reconstitution model34. This demonstrates the significance of the VMP as a source of stromal-specific molecules with potent capacity to regulate epithelial growth and differentiation in both development and disease. We suggest that mesenchymal subsets are enriched for regulators and morphogens, as well as factors associated with paracrine signalling between mesenchyme and epithelium or juxtacrine signalling between mesenchymal subsets. Our studies are among the first to catalogue gene expression in inductive mesenchyme, and address cellular heterogeneity within the mesenchymal compartment.The ventral mesenchymal pad (VMP) is a subset of urogenital mesenchyme which has been shown to express potent morphogens and regulate prostate organogenesis8, which served as controls for our analysis . Comparison of VMP Tag/RNA-seq libraries to SU libraries identified 400 transcripts that were differentially expressed between the two compartments. Among these were several transcripts identified as VMP-specific in a previous SAGE studysis Fig. . The ideSeveral of the markers identified in VMP and SU were validated by qPCR and simultaneously examined for their expression in male developing prostate. We propose that VMP mesenchyme provides a simpler model for the identification of mesenchyme specific molecules since it lacks branching epithelia. Inclusion of these in whole tissue transcriptomics yields more complex data in which it is difficult to deconvolve mesenchyme specific molecules. Comparison between male and female mesenchyme may be used to identify sexually dimorphic gene expression and regulation by androgens and the androgen receptor, and we chose to focus upon mesenchyme-specific expression rather than sexually dimorphic expression. We note that some of our markers exhibit differences between male and female mesenchyme which could be validated in future studies. This is important, since androgen action within the mesenchymal compartment regulates both prostate and genital tubercle growth, and we propose that identification of mesenchyme specific molecules is a first step in the discovery of such factors.36. Meis2 has been identified as essential for the development of cardiac, orofacial, gastro-esophageal and neural tissues39. Ebf3 is a DNA-binding transcription factor which is involved in the development of bone and neural tissues41. Here we have established specific expression and nuclear localisation of Meis2 and Ebf3 in developing prostate mesenchyme and are the first to associate these transcription factors with prostate development and expression within mesenchymal subsets. We propose that these molecules can be used as specific markers of mesenchyme or stroma and could be used to estimate the abundance of stroma vs epithelium in tissues of mixed cellular composition.We identified Meis homeobox 2 (Meis2) and early B-cell factor 3 (Ebf3) as specific to the VMP compared to SU, and also expressed in prostatic mesenchyme. Meis2 belongs to the TALE homeobox protein family and is a regulator of transcriptionIn conclusion, we present a high-resolution transcriptomic analysis of inductive prostate mesenchyme that has documented limited cellular heterogeneity within subsets and identified markers and pathways expressed in mesenchyme during early prostate organogenesis.Wistar rats were housed under a 12-hour light/dark cycle and maintained on standard laboratory diet, the study was performed under MUHC animal protocol number 2015–7670, approved by the McGill University Facility Animal Care Committee (FACC). Newborn (P0) pups were sacrificed by cervical dislocation and decapitation , followed by removal of the urogenital tract and microdissection of the urethra into VMP and SU components using a Leica MZ6 dissection microscope.Pools of microdissected tissues (VMP and SU) from over 100 animals were processed for digital gene expression Tag-profiling using NlaIII and a protocol provided by Illumina followed by sequencing on an llumina GAIIX (1 × 50 SE) at one lane per sample (25–30 m reads). PolyA + RNA was purified, cDNA synthesised, digested with NlaIII and ligated to Adaptor 1 (containing an Mme1 site). Samples were digested with Mme1, ligated to Adaptor 2, and PCR amplified, followed by gel electrophoresis and purification of 85 bp fragments that were sequenced. DNA sequencing was carried out in the GenePool genomics facility in the University of Edinburgh.Dissociated cells derived from collagenase digestion of pools of microdissected VMP and SU using collagenase 1 A at 2 mg/mL concentration  for 60 minutes at 37 °C. Dispersed fibroblasts were separated from epithelia and tissue clumps by centrifugation through a 0.7μm cell strainer .Cell suspensions were centrifuged for 10 minutes at 500 g and resuspended in LIVE/DEAD Cell Viability/Cytotoxicity Assay for mammalian cells . After a 10-minute incubation at room temperature, cells were centrifuged and resuspended in Cell Wash Buffer (Fluidigm). Cell concentration, size and viability were verified on hemocytometers (Incyto DHC-N01–5) through bright field, GFP and RFP on a EVOS FL Auto microscope (ThermoFisher). Single cell RNA libraries were constructed according to the Fluidigm protocol using C1 to generate libraries for RNA sequencing (PN 100–7168). Briefly, full length mRNA-seq libraries were generated from single-cells captured on the Fluidigm C1 platform using SMARTer Ultra Low RNA Kit (P/N 634936 Clontech). ERCC RNA Spike-In mix (P/N 4456740 ThermoFisher) was added to the lysis mix for normalization and quality control purposes. Full length cDNAs were converted into sequence ready libraries using Nextera XT DNA Sample Preparation Kit (P/N FC-131–1096 Illumina), and sequenced on an Illumina HiSeq2000/2500 with paired-end 100/125 option. In parallel, for every sample, sequencing libraries from bulk cells (200 cells) using 5 ng of purified total RNA, and a negative control were run on a thermocycler (T100 BioRad).The Fluidigm C1 platform captured 52 and 70 single cells from VMP and SU respectively. The average full length cDNA yield/min/max were 6.06ng(+/−0.12)/2.25ng/14.81ng for VMP and 8.51ng(+/−0.21)/2.55ng/26.6ng for SU. Libraries from 52 VMP and 63 SU single cells were sequenced.Cells from the cell suspensions were processed to provide a ‘bulk’ comparator for single cell studies.42 to keep only reads with a mean quality score of 20 and above. Reads were aligned to the rat genome (Ensembl Rnor_6.0) using the Bowtie2 algorithm (default settings)43. Reads aligned to random contigs and mitochondrial DNA were removed and only uniquely mapped reads with a mapping quality >=25 were used for further analysis.Raw sequencing reads were trimmed to 17 bp to remove adaptor sequences and restriction digestion sites. Reads were quality controlled using FastQC44, to a minimum length of 30 nucleotides. Illumina Nextera XT adapters were removed in palindrome mode. A minimum Phred quality score of 30 was required for the 3′ end. Single end reads as well as paired end reads failing previous minimum quality controls were discarded. Individual read groups were aligned, using TopHat45 first against the rat transcriptome as defined by the Ensembl gene models version 83, with default parameters and the remaining unmapped genes to the Ensembl Rnor_6.0 reference rat genome from Illumina iGenomes web site. Trimming rates and insert length were controlled on each read group based on metrics reported by Trimmomatic, and Picard v1.128 respectively.Raw paired-end reads were trimmed using Trimmomatic v0.3346, a faster implementation of the Samtools algorithms. Amplification duplicates were removed using Picard v1.128.Aligned reads from multiple read groups belonging to the same sample were indexed, sorted and merged using sambamba v0.5.147, including the genes detected, mapping rates, duplication rates, and intronic rate, based on metrics collected for each sample used.Various quality controls from the RNA-SeQC package were used48. Transcripts with a read count of 0 in both samples were removed. EdgeR49 was used to perform TMM normalization and only transcripts with counts per million (cpm) > 1 were used for differential analysis of genes. The NOISeq package23 was used to screen differentially expressed genes between VMP and SU tissues. Genes with a q-value of >= 0.9 were considered differentially expressed.Read counts were quantified using the summarizeOverlaps function from the GenomicAlignments R package50 on the VMP and SU enriched genes. Ontology terms with an FDR < 0.05 were considered significant.Gene Ontology (GO) enrichment analysis was conducted using the clusterProfiler R package51 was used for quality control and normalization. Low quality cells were filtered out based on library size, number of genes detected, proportion of reads mapped to mitochondrial genome and the ratio of reads mapped to spike-ins. Cells were removed if they met any of the following criteria: a median absolute deviation (MAD) value of less than 3 for library size, a MAD value of less than 3 for number of mapped genes, a MAD value of greater than 3 for the ratio of reads mapped to mitochondrial DNA and a MAD value of greater than 3 for the ratio of reads mapped to spike-in control DNA. The numbers of cells meeting these criteria are detailed in Supplementary Figure 25 and scDD26 R packages. Prior to subpopulation identification normalized read counts were converted to TPM and analysis was performed using the Seurat and SC3 R packages29. For both packages, marker genes were identified using a ROC test. All markers with an AUC < 0.75 and power < 0.4 were removed.The Scater packageTM Mini kit  following manufacturer’s instructions. Complementary DNA synthesis was performed using the High Capacity cDNA Reverse Transcription kit  and qPCR was performed on an ABI 7500 Fast machine using SYBR Select Mastermix . Transcript abundance was normalized to four housekeeping genes; Gapdh, Tbp, Gusb and Mt-atp6. Primers used are provided in Table Total RNA was extracted from pooled tissues using Qiazol followed by the RNeasy20) was performed as per24 using Ebf3 IgG  and Meis2 IgG . Primary antibody was omitted to serve as a negative control. Images were taken with an Aperio Slide Scanner .Immunostaining of Ebf3 and Meis2 on serial sections of female and male rat P0 urogenital sinus tissue (isolated as perAll data generated by this work are available in GSE103011. Differentially expressed transcripts, Gene Ontology and transcript comparisons are provided in a supplementary data file.Supplementary FiguresSupplementary data


We compared changes in balance control due to chronic inflammatory demyelinating polyneuropathy (CIDP) and non-inflammatory (non-inf) polyneuropathy (PNP) to each other and with respect to healthy controls (HCs). Differences in patients’ subjective impressions of balance capabilities were also compared.Balance control of 11 CIDP patients (mean age 61.1±(sd) 11, 8 male) and 10 non-inf PNP patients  was examined and compared to that of 18 age- and gender-matched healthy controls. Balance control during stance and gait tasks was measured as trunk sway angles and angular velocities with body-worn gyroscopes. Patients’ subjective impressions of balance were obtained using the Dizziness Handicap Inventory (DHI). The Neuropathy Impairment Score in the Lower Limbs (NIS-LL) was used to measure clinical disease status.Non-inf PNP patients had slightly lower NIS-LL (13.5±7.2 vs. 17.9±15.1) and DHI scores (22.6±17.1 vs 27.6±16.3). Gait tasks showed a significant decrease in gait speed with respect to HCs for both patient groups but reduced trunk sway for non-inf PNP patients. Trunk sway during tandem walking and walking on the heels was greater for both groups than that of HCs. Sway during 2-legged stance tasks with eyes closed on a firm or foam surface was also greater than for HCs.Compared to HCs both groups of patients have significantly greater sway for most stance and gait tasks accompanied by reduced gait speed. As for HCs, non-inf PNP patients reduced trunk sway with slower gait speed. In CIDP patients this compensatory strategy was absent, possibly due to a greater deficit of efferent and motor nerve fibers. An interpretation of these findings is that CIDP patients have reduced ability to decrease trunk sway with slower gait speed and is possibly associated with an increased risk of falls. Polyneuropathy (PNP) is a generalized, relatively homogeneous disease process of the peripheral nerves. Usually the distal nerves are affected most prominently. In PNP the sensory proprioception of the lower legs (lower-leg proprioceptive loss (LLPL)) can be affected. As this sensory system plays a key role in balance control, PNP patients experience balance impairment during stance and gait , 2. ThisTo maintain balance the central integration of proprioceptive information from the legs with other sensory information is necessary –9. In poThe prevalence of polyneuropathy has been reported to be between 2% and 7% with an increase to 13% in persons older than 80 years , 15. CliChronic inflammatory demyelinating polyneuropathy (CIDP) is a rare autoimmune mediated variant of polyneuropathy affecting both sensory and motor fibers in both proximal and distal segments of all four limbs, that is in a more length independent way. The inflammation causes damage to the myelin sheaths leading to slowing or blocking the signal conduction . The preWe performed this study to test the hypothesis that patients with length-dependent non-inflammatory (non-inf) PNP and length-independent CIDP would have different deficits in stance and gait balance control possibly due to the greater effect on motor fibres in CIDP. Furthermore, we wanted to determine if, for both groups, gait and stance balance control measured in the form of trunk sway, was equally greater than that of healthy controls. As far as we are aware, this is the first time such comparisons has been undertaken. The second objective of this study was to determine whether differences in balance changes between these two patient groups are related to the patients’ own perceptions of vertigo and as measured with the Dizziness Handicap Inventory (DHI) questionnaire.For this study balance control was examined in 11 CIDP patients  and 10 non-inflammatory (non-inf) PNP patients . All patients were diagnosed for polyneuropathy by experienced neurologists accordingly current guidelines , 26, 27.To obtain a subjective assessment of the patient’s balance problems we used the dizziness handicap inventory (DHI) questionnaire . The DHIExclusion criteria for all patients were the inability to walk without a walking aid and the presence of orthopedic problems or other diseases/disabilities e.g. a history of stroke, vestibular or extrapyramidal disorders that could affect balance. All subjects gave written informed consent in accordance with the Declaration of Helsinki prior to the experiments. The protocol was approved by the ethics committee of North-Central Switzerland (EKNZ), Approval No: 2015–096.Balance of the patients was assessed by measuring trunk sway during a sequence of 12 stance and gait tasks. Based on previous data we have equated increased (with respect to HCs) values of trunk sway angle and angular velocity during gait with gait instability for two reasons. Firstly, because the sway is measured at lumbar 1–3 is close to the position of the center of body mass . SecondlAll stance and gait tasks were performed in the same order by each patient and executed without shoes. The tasks used were chosen based on previous studies in our laboratory comparing balance for 12 stance and gait balance tasks between different patient groups and healthy controls , 39–41. 3)–and 2 eyes closed. Three 1-legged stance tasks were performed eyes open, two on a normal surface (right and left leg) and one on the foam surface. For the latter foam task, the patients were asked to use their better leg to stand on. The stance tasks were performed on foam to reduce the remaining contribution of lower-leg proprioceptive to balance control. Stance tasks were performed for 20 seconds or until the patient lost balance. The patients performed 4 walking tasks with eyes open, one with eyes closed: a tandem gait task which was performed by walking 8 tandem steps (W8tan); walking on heels for 3 meters (W3mheels); walking 3m while pitching the head up and down; walking 3 meters, eyes closed (W3mEC) and walking 8 meters, eyes open (W8mEO). Tasks were performed with eyes closed to eliminate visual inputs to balance control. For gait tasks, patients were asked to walk at their comfortable pace. At the beginning of each gait task the patients were asked to stand comfortably with feet hip-width apart to standardize the start of each test. Prior to the balance assessments patients filled out the Dizziness Handicap Inventory (DHI). The DHI is used clinically and in research to assess the impact of a person’s dizziness on their quality of life [Four 2-legged tests were performed with the feet spaced shoulder width apart. Two were performed with eyes open–on a normal surface and on a foam surface , pitch angle range (PAR), roll angular velocity range (RVR), pitch velocity range (PVR) for the complete trial and trial duration. The 90% range was determined using the histograms of pitch and roll angle and angular velocity having divided the peak to peak range into 40 bins. As there were few differences in significance for 90% and peak to peak ranges  which combines results from several different trials into one index (see details below), secondly trunk sway measures for walking eyes open and closed which we hypothesised would be different from HCs, and thirdly trunk velocity measures during stance eyes closed which we expected to differ from those of HCs based on prior research . The remTo compare the PNP and CIDP patients, ANOVAs were performed followed by post-hoc t-tests. As statistical significant differences between these patient groups were only found for the walking 8m eyes open and 3m eyes closed gait, we also pooled the patient data for comparisons with health controls (HCs) using ANOVA tests. Comparisons with healthy age- and gender-matched normal values and between patient populations were performed post-hoc using independent-samples t-tests with a Bonferroni correction for 5 comparisons per balance test. Significance was set at p<0.05 after the Bonferroni correction.As For the two-legged stance tests standing eyes closed on a normal and on a foam surface, the patients had significantly greater trunk sway velocities than HCs . Thus ouAs expected from the results with two-legged tasks, one-legged eyes open stance tests also showed highly significant differences to HCs. For common gait tests used in neurology clinics to test patients  significantly larger sway angles and velocities differences were also observed .Across all tests there was little difference between using peak-to-peak or 90% range measures. Peak-to-peak measures led to a slightly lower number of significant findings (28 versus 33 sway measures).In this study we performed stance and gait posturography on patients with non-inflammatory polyneuropathy (non-inf PNP) and CIDP in order to investigate differences in trunk sway between the patient groups. As there is evidence that patients with polyneuropathy in general have trunk instabilities during stance tests , we alsoWe found that both CIDP and non-inf PNP patients have significantly greater sway than HCs during stance tests and complex gait tasks . , Table 3During the gait task walking 8m both groups of PNP patients slowed gait presumably in order to reduce trunk sway to within normal stability (trunk sway) bounds for that gait speed . Our finGiven the contribution of both vestibular and lower leg proprioceptive inputs to postural control –4 it is In conclusion, in addition to unstable stance eyes closed, we found that patients with CIDP and patients with non-inf PNP have slower preferred gait speed than healthy persons. However, patients with non-inf PNP showed a reduction of trunk sway velocity while slowing gait which is similar to HCs when they slow their gait . In contS1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.


The endoplasmic reticulum (ER) is the main and largest intracellular Ca2+ store. At the ER two protein families of Ca2+ release channels, inositol 1,4,5-trisphosphate receptors (IP3Rs) and ryanodine receptors (RyRs), are expressed. Several studies have reported roles in the regulation of autophagy for the ubiquitously expressed IP3R. For instance, IP3R-mediated Ca2+ release supresses basal autophagic flux by promoting mitochondrial metabolism, while also promoting the rapid initial increase in autophagic flux in response to nutrient starvation. Insights into the contribution of RyRs in autophagy have been lagging significantly compared to the advances made for IP3Rs. This is rather surprising considering that RyRs are predominantly expressed in long-lived cells with specialized metabolic needs, such as neurons and muscle cells, in which autophagy plays important roles. In this review article, recent studies revealing roles for RyRs in the regulation of autophagy will be discussed. Several RyR-interacting proteins that have been established to modulate both RyR function and autophagy will also be highlighted. Finally, the involvement of RyRs in neurodegenerative diseases will be addressed. Inhibition of RyR channels has not only been shown to be beneficial for treating several of these diseases but also regulates autophagy.Intracellular Ca Within the lumen of the ER maintaining adequate Ca2+ levels is essential to promote the correct folding of proteins. Failure to do so results in ER stress and activation of the unfolded protein response  receptors  via calmodulin kinase kinase β leading to the inhibition of the mechanistic target of rapamycin (mTOR), thereby inducing autophagy  initiated at the level of the lysosomes via NAADP-sensitive Ca2+ channels. Pharmacologically RyRs can be activated by caffeine or low ryanodine concentrations (nM range), locking the channel in a sub-conductance state. Inhibition of RyRs can be obtained most specifically via a high ryanodine conentrations (>20 μM) or with dantrolene, a FDA-approved RyR blocker.RyRs are large (>500 kDa) ER-located Ca2+, Mg2+ and ATP), post translational modifications and protein interactions  domains Letai, . Anti-apL bind to and inhibit RyRs  1 and 2 are important regulators of intracellular Ca2+ oscillations in the cardiomyocytes and reduced the ER Ca2+ store content. Recently, it was shown that a decrease in PC2 expression increased the expression of RyR2 and SERCA2A in the heart while phosphorylated phospholamban, a SERCA inhibitor in its non-phosphorylated form, was decreased  is a progressive neurodegenerative disease of which several types are known to exist (Sun et al., 2+ release. It will be interesting to see whether these interactors also influence autophagy by modulating RyR-mediated Ca2+ release.RyR signaling and autophagy are two factors critically linked to the correct functioning and survival of neurons (Figure 2+ release and autophagy have also been shown to contribute to several neurodegenerative diseases. Disease causing mutant proteins, excitotoxicity and aging are not only the cause for these diseases but also change RyR function and autophagy. As RyR function and autophagy are involved in maintaining neuronal health, changes in these processes may result in aggravating disease progression (Figure 2+ release has been shown to confer beneficial effects in treating a number of these diseases. Several of the above mentioned studies used the FDA-approved drug dantrolene in order to block RyR-mediated Ca2+ release. An observation common in the studies looking at how RyRs regulate autophagy, is that RyR inhibition via dantrolene changes/normalizes autophagic flux. This may in part underlie the beneficial effects of dantrolene in several neurodegenerative diseases as by inhibiting RyR activity it may also regulate autophagic flux indirectly (Figure Alterations in RyR-mediated CaTV wrote this review article.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.