Significant changes in individual CpG methylation occurred in RNApol II binding regions of small non-coding RNA (snRNA) genes, which implicates alternative splicing as a mechanism involved in transgenerational transmission of the effects of antenatal sGC. This study provides novel perspectives on the mechanisms involved in transgenerational transmission and highlights the importance of human studies to determine the longer-term effects of antenatal sGC on hippocampal-related function.Synthetic glucocorticoids (sGC) are administered to women at risk for pre-term delivery, to mature the fetal lung and decrease neonatal morbidity. sGC also profoundly affect the fetal brain. The hippocampus expresses high levels of glucocorticoid (GR) and mineralocorticoid receptor (MR), and its development is affected by elevated fetal glucocorticoid levels. Antenatal sGC results in neuroendocrine and behavioral changes that persist in three generations of female guinea pig offspring of the paternal lineage. We hypothesized that antenatal sGC results in transgenerational changes in gene expression that correlate with changes in DNA methylation. We used RNASeq and capture probe bisulfite sequencing to investigate the transcriptomic and epigenomic effects of antenatal sGC exposure in the hippocampus of three generations of juvenile female offspring from the paternal lineage. Antenatal sGC exposure (F The mammalian brain, particularly the hippocampus, is highly sensitive to the fetal-maternal environment. The hippocampus has the highest concentration of glucocorticoid receptors (GR) in the brain2, and is therefore highly sensitive to the effects of glucocorticoids3.The hippocampus is critical for many higher brain functions, including learning and memory and regulation of stress responsiveness. In the human, the fetal hippocampus begins to develop at 13–14 weeks, resembling the adult hippocampus by 18–20 weeks of gestation4, DNA methylation machinery6, dopaminergic7, serotonergic4, and glutamatergic signaling7, and affects the expression of GR and mineralocorticoid receptors (MR) in the hippocampus14. Altered hippocampal gene expression has been associated with modified regulation of the hypothalamic-pituitary-adrenal (HPA) axis, leading to altered stress responsiveness, and mood and anxiety disorders in animals15 and in humans16.We and others have shown that prenatal exposure to excess glucocorticoids in mice, rats and guinea pigs can alter gene expression related to synaptic plasticity17. Various factors such as maternal anxiety and stress and placental dysfunction can increase fetal glucocorticoid exposure19. In addition, the fetus can be exposed to synthetic glucocorticoids (sGC), which are administered to pregnant women at risk for pre-term delivery . This treatment promotes lung maturation and reduces morbidity and mortality associated with respiratory distress syndrome in preterm infants20. Several studies have demonstrated that exposure of the fetus to high levels of glucocorticoid, prior to the natural glucocorticoid surge, can lead to long-term programming effects on neurocognitive, behavioural, endocrine, and cardiometabolic function23.Fetal plasma glucocorticoid is maintained at low levels through the majority of pregnancy; however, there is a natural ‘surge’ in fetal glucocorticoid levels at the end of gestation in most mammalian species. This surge is important for maturation of fetal organs, including the lung, kidney and brain24. Administration of antenatal sGCs resulted in alterations in histone-3-lysine-9 acetylation in gene promoter regions5 and global DNA methylation changes in fetal organ systems that occurred in first- and persisted to second-generation offspring25. In the fetal hippocampus, sGC exposure resulted in acute demethylation of promotor regions 24 h after final exposure. However, promotor hypermethylation in a completely different set of genes was identified 14 days after the last exposure to sGC, as well as major changes in gene expression6. These studies suggest that prenatal sGC exposure causes dynamic epigenetic changes which may affect both DNA and histone modifications5. We have recently shown that antenatal sGC exposure results in transgenerational changes in behavior and gene expression in the paraventricular nucleus (PVN) of the hypothalamus and medial prefrontal cortex (PFC)26, however transgenerational epigenetic signatures of exposure have yet to be investigated.The mechanisms by which premature exposure to elevated levels of glucocorticoids program hippocampal development are poorly understood. Emerging evidence suggests these changes may be mediated through epigenetic mechanisms such as DNA methylation or histone modification. DNA methylation regulates chromatin states and is transmitted through cell division29. However, recent research has shown that enhancer DNA methylation is more closely associated with gene expression in cancer than promoter methylation24. Further, correlations of enhancer DNA methylation and expression of developmental genes have been observed during mouse tissue differentiation30, as well as in hippocampal tissue31.Gene expression is regulated by epigenetic modifications and transcription factor binding at promotor regions, CpG islands, and enhancer regions. Generally, promoters and CpG islands with high levels of DNA methylation are not transcriptionally active, while genes with demethylated promoters are expressed21. In the present study, we hypothesized that; (1) antenatal sGC induces changes in hippocampal transcriptional and DNA methylation landscapes across three generations of juvenile female offspring from the paternal lineage, as we have previously demonstrated that young females across three generations show the strongest behavioral and neuroendocrine phenotype26; (2) Modification of DNA methylation signatures in promoter and enhancer regions relate to changes in hippocampal gene expression.Determining the relationship between DNA methylation and transcriptional effects following prenatal sGC exposure will help elucidate the mechanisms by which sGC can permanently program neural function over multiple generations1, 285 genes were significantly differentially expressed in the hippocampi of sGC animals compared to control . An example of the vesicular docking gene set is presented in Fig. In F3, 496 genes were significantly differentially expressed in sGC animals compared to control   with 184 DMRs hypomethylated  and 222 DMRs hypermethylated  in sGC offspring relative to control  with 74 DMRs hypomethylated  and 65 DMRs hypermethylated  in sGC animals relative to control  with 170 DMRs hypomethylated  involved in glutamatergic and ion channel activity and 210 DMRs hypermethylated related to acetylcholine receptor binding and neuron recognition  in sGC animals relative to controls  that were both significantly differentially expressed (FDR < 0.05) and differentially methylated  were both significantly differentially expressed (FDR < 0.05) and differentially methylated . There were 13 differentially methylated CpGs in unannotated regions, 5 were in regions related to coding genes, and 45 related to snRNA encoding genes. In F2 sGC animals, there were 21 CpGs that were significantly differentially methylated . There were 4 differentially methylated CpGs in unannotated regions, 4 were in regions related to coding genes and 13 were related to snRNA genes. In F3 sGC animals, there were 51 CpGs that were significantly differentially methylated . There were 12 differentially methylated CpGs in unannotated regions, 8 in regions related to coding genes, and 31 were related to snRNA genes. The significantly differentially methylated CpGs were distributed amongst promoter and enhancer regions. A list of affected snRNA genes is presented in Supplementary Table To elucidate how antenatal sGC affect DNA methylation at the individual CpG level, we performed DNA methylation analysis with single-nucleotide resolution. In F1 , F2 , and F3 . In all three generations, differentially methylated CpGs occurred in promoter/RNAPol II-PS5 binding regions; F1 , F2 , and F3   was significantly different from the expected distribution generated by the custom probe capture design (which captured more enhancer regions than promoter regions) in F1 sGC offspring, five genes from our a priori list  were differentially expressed. To test our hypothesis that the genes from our a priori list were most affected by antenatal sGC, we performed χ2 to determine whether more genes from our a priori list were significantly differentially expressed than would be expected by chance. Contrary to our hypothesis, the number of observed genes was not significantly different than would be expected by chance . There were no genes differentially expressed from the a priori list in F2. In the F3 sGC offspring, 16 genes from the a priori list were significantly differentially expressed , more than would be expected by chance .Since many studies have shown that antenatal sGC exposure alters gene expression in the hippocampus, we used these findings to generate a list of genes  from the a priori list were significantly differentially methylated in F1 offspring  which is not more than would be expected by chance . In F2, eight genes from the list were significantly differentially methylated , which is not more than would be expected by chance . In F3, 6 genes from the a priori list were significantly differentially methylated , also not more than expected by chance .To test our hypothesis that the genes from our 2 sGC offspring, there were over 280 genes differentially expressed in F1 sGC offspring, and over 490 genes were differentially expressed in F3 sGC offspring. There was no overlap between differentially expressed genes across all 3 generations. Furthermore, we observe generation-specific hippocampal methylation signatures in animals from the sGC-exposed lineage. Importantly, changes in methylation that are associated with changes in gene expression occur at enhancer regions, and methylation changes at the individual CpG level are enriched in RNApol II-PS5 binding regions of small non-coding RNAs (snRNAs). Thus, antenatal sGC exposure results in generation-specific methylation signatures in the hippocampus, which may function in concert with transcriptional machinery to alter phenotypes and transmit effects to subsequent generations.We have demonstrated, for the first time, that transgenerational changes in hippocampal gene expression and methylation occur over three generations in female offspring following antenatal sGC and paternal transmission. Strikingly, while only 3 genes were differentially expressed in the F1 offspring exposed to prenatal sGC, 285 genes were significantly differentially expressed in the hippocampus. Previous research has shown that the expression of genes related to key signaling pathways are altered by prenatal exposures to excess glucocorticoids14. In the present study, using an in silico approach, we identified 199 genes linked to key hippocampal signaling pathways that related to published phenotypic outcomes in offspring following prenatal sGC exposure or maternal stress in pregnancy. At an individual gene level, only five genes from the a priori list  were differentially expressed in the hippocampus of F1 offspring following prenatal exposure to sGC. Notwithstanding, we did observe down-regulation of gene set pathways related to the corticosteroid response. The hippocampus exerts inhibitory control over the PVN33, thus down-regulation of genes related to corticosteroid response (50 days after sGC exposure) may result in decreased inhibition of the PVN, and an increased HPA-response to stress. This would be consistent with the increased HPA-response observed in the F1 sGC offspring after exposure to the open-field21.In F2 female offspring in the sGC group  compared to controls. Interestingly, these animals showed the strongest behavioral phenotype (of the three generations), as well as substantial changes in gene expression in the hypothalamic paraventricular nucleus, and prefrontal cortex26. While individual genes may not have been significantly differentially expressed, we used gene set enrichment analysis, which examines whether there are small changes in gene expression in the same direction (up or down) for multiple genes related to the same pathway, to identify gene networks that are differentially regulated as a result of antenatal sGC. We observed that pathways involved in vesicular docking are down-regulated in the F2 descendants of sGC-exposed pregnancies. In addition, pathways involved in blood-brain barrier integrity (collagen and extracellular matrix) were down-regulated in the F2 sGC offspring hippocampus. Similar gene sets have previously been shown to be altered by antenatal glucocorticoids in the PVN34. Thus, very few individual genes are significantly differentially expressed in the F2 sGC offspring, however, dysregulated gene networks may suggest altered hippocampus gene function in these animals.Unexpectedly, we observed changes in the hippocampal expression of only three genes in F3 offspring, descendent of sGC treated mothers, 16 genes from the a priori list were significantly differentially expressed, which was more than was expected by chance. Furthermore, while the effects of antenatal sGC decrease in the F3 compared to F1 offspring in the PVN and PFC26 in the present study, we demonstrated that in the hippocampus, more genes are significantly affected by sGC in the F3 animals compared to the F1 and F2 offspring. Interestingly, we observed downregulation of Mr (Nr3c2), in the F3 sGC exposed animals. Mr expression in the hippocampus plays an important role in HPA negative feedback regulation35, and decreased Mr signaling may be indicative of decreased HPA-inhibition. However, the F3 sGC offspring did not display altered HPA response to stress, though they did demonstrate a hyperactive phenotype in the open-field21. These findings suggest that glucocorticoid signaling may be altered in the hippocampus of F3 sGC animals and may relate to phenotypic outcomes. In the present study, we also observed down regulation of genes that are important for learning and memory . Gad1 and Gad2 are enzymes involved in γ-aminobutyric acid (GABA) signaling36, and decreased expression of these genes in the hippocampus has previously been observed in patients with schizophrenia and bipolar disorder37. Syp is involved in regulating activity-dependent synapse formation38, and Gria1 expression is essential in new memory formation40. Though behavioral tests related to cognition were not performed in the present study, the gene expression changes observed in F3 sGC offspring suggest these animals may have had learning deficits, and this can be tested in future studies.In Fpoised enhancers31. However, the mRNA measure of transcription level is confounded by several regulatory processes downstream to transcription initiation41, meaning that enhancer methylation and mRNA content do not always correlate. This may be why there were so few changes in DNA methylation that correlate with steady-state expression. However, changes in methylation that are associated with changes in steady-state gene expression did occur in enhancer regions, consistent with the notion that DNA methylation in enhancer regions is more correlated with gene expression than promoter methylation30. Epigenetic mechanisms play a role in regulating gene expression patterns in response to environmental cues42. The animals in this study were euthanized in an unstressed basal state, and methylation signatures left by antenatal sGC may indicate that genes are poised to be expressed differently following environmental stimuli. It may be that stronger correlations between gene expression and methylation would occur when the animals are in an activated state (i.e. a stressful environment). Interestingly, very few genes from our a priori list displayed significant changes in methylation. Though previous research has demonstrated that antenatal sGC alters the methylation status of promoter regions of genes from this list6, these changes have also been shown to be dynamic, and may not remain as a permanent signature 50-days after final exposure to sGC6. Only two genes were differentially methylated across all three generations of offspring: Kif26b, a motor protein involved in organelle transport and intracellular signaling43; and St6galnac5, a glycosyltransferase involved in cell-cell interactions44. Both genes demonstrated generation-specific changes in methylation but were not differentially expressed due to sGC exposure. Unlike our previous work in the PFC26, we did not observe consistent changes in DNA methylation and gene expression in the hippocampus, suggesting region-specific responses following prenatal sGC exposure.We observed generation-specific effects of antenatal sGC exposure, with distinct methylation signatures occurring in each of the generations. We observed very little overlap between gene expression and methylation changes. We have previously shown that transcriptionally active enhancers are less methylated than 1 and F3 sGC offspring, hypomethylated DMRs were related to glutamatergic signaling. While glutamate release is essential for cellular signaling processes, including learning and memory, the hippocampus is especially vulnerable to excitotoxicity from excess glutamate release. Chronic stress, and chronic exposure to glucocorticoids, is known to be a potent trigger of glutamate excitotoxicity, and results in cell death and mood disorders45. Corticosteroids potentiate the excitability of the hippocampus46 and prime the hippocampal circuit for subsequent stimulation47. Corticosteroids have been shown to result in a rapid release of glutamate46 and increased glutamatergic synaptic signaling has been shown to coincide with decreased levels of methylation49. Taken together, these findings suggest that the hypomethylation observed in the F1 and F3 sGC offspring is indicative of altered glutamatergic sensitivity, which may lead to decreased excitotoxicity resilience in the hippocampi of these animals. Surprisingly, this DNA methylation signature was not present in the F2 sGC animals. In the F2 sGC animals, hypomethylation was observed in genes related to GTP activity which is an essential part of G-coupled protein receptor signaling50. Rab GTPase activity has been shown to be involved in signal transduction of glutamate receptors51, thus it is possible that glutamate receptor activity may also be altered in F2 sGC animals, but via a different mechanism.Analyzing DMRs (100 bp windows of DNA methylation changes) provides an overview of the methylation signatures that result from antenatal sGC exposure. In the F53. Promoter methylation levels have been shown to regulate snRNA expression54, and expression of snRNAs has been shown to be dysregulated in the adult mouse brain after fetal alcohol exposure, which may suggest that altered snRNA expression can influence phenotype resulting from early life exposure52. In the current study, mRNA-enriched analyses were performed to quantify gene expression, which precludes us from assessing changes in the expression of snRNA and represents a limitation of this study. However, we observed differential methylation for snRNAs (Snora2) responsible for post-transcriptional modifications of spliceosomal RNA (U6) across all three generations of sGC offspring. U6 is involved in the removal of intronic regions of RNA primary transcript and assembly of exons to form mRNA55. Though the exact mechanisms remain to be elucidated, recent evidence suggests that altered snRNA activity is involved in alternative splicing55. Alternative splicing, a conserved process that increases the diversity of the transcriptome and proteome by allowing multiple mRNA products to result from a single gene, has been shown to be regulated by interplay between chromatin and DNA methylation58. Over 90% of human genes undergo alternative splicing58, and alternative splicing patterns have been shown to be sex-specific59, and heritable in a Mendelian fashion60. Thus, antenatal sGC results in transgenerational changes in DNA methylation in RNApol II-PS5 binding regions of snRNA genes involved in transcription machinery, implicating alternative splicing as a potential mechanism involved in the transgenerational transmission of the effects of antenatal sGC in the hippocampus. However, this important possibility needs to be tested in further detailed experiments.The significantly differentially methylated CpGs in all three generations of sGC offspring were enriched in RNApol II-PS5 binding sites of small noncoding nucleolar and spliceosomal RNA genes. Small noncoding RNAs (snRNAs) are a secondary level of epigenetic control involved in the fine-tuning of gene expression1 offspring, but that no differences in methylation were maintained into the F2 generation61. Another potential route of paternal transmission may be through small RNAs, including microRNA (miRNA) and transfer RNA. Sperm contain miRNA which can be delivered to the oocyte on fertilization62. Early life stress in males, resulted in an altered compliment of miRNA in sperm in adulthood, and an elegant series of subsequent studies determined that a number of these miRNA were driving phenotypic differences in subsequent offspring63. Other studies have indicated that histone modifications in sperm as a potential route for paternal inheritance. While the majority of histones in sperm are replaced by protamines, some histones remain64. After fertilization, paternal protamines are replaced by heavily acetylated maternal histones, while paternal histones remain largely untouched65. Thus, it is possible for epigenetic marks on these histones to be inherited.In the present study, the fact that there are behavioural changes accompanied by changes in hippocampal DNA methylation and gene expression across three generations implicates male germ-line epigenetic transmission. A number of potential mechanisms, both direct and indirect, by which this might occur are emerging. Persistent changes in germline DNA methylation, as a mode of transgenerational transmission, are unlikely given the broad waves of DNA demethylation that occur during embryonic development. In support of this, a previous study has shown maternal malnutrition to be associated with differentially methylated regions within the sperm of Fde novo cytosine methylation and alterations in chromatin structure66. Such integrated processes may be occurring in the model described in the present study, allowing the transmission of the effects of sGC exposure across multiple generations. The dynamic nature of the changes across 3 generations suggest that an initial epigenetic signal transmitted by the F1 sperm is not a static epigenetic memory that is inherited across future generations. The picture that is emerging is more consistent with the initial epigenetic signal triggering a cascade of epigenetic events that include DNA methylation which keep changing dynamically across tissues and generations. Clearly further studies are required to determine the specific processes involved in this model.Epigenetic inheritance paradigms have often considered potential mechanisms in isolation; however, it is likely that there is interplay between processes. In this regard, small RNAs can drive There are some limitations with the present study. Focus was placed on DNA methylation and gene transcription and future studies should address the relationship of altered gene transcription with altered protein levels in the hippocampi across multiple generations. Analysis of DNA methylation was limited to 5-methylcytosine. We did not undertake analysis of downstream modifications by oxidation of 5 methylcytosine such as 5-hydroxymethylcytosine, 5-formylcytosine and 5-carboxylcytosine, which may also play a role in transgenerational transmission. We also acknowledge that our use of RNAPolII-Ser5 ChIP to assist in the identification of promoters may lead to some biases towards active rather than silenced genes. Our studies have highlighted the possibility that prenatal sGC may lead to alterations in transcript splicing. Due to the sequencing methodology used in this study, we were unable to investigate differential splicing, though this could be a focus of future studies. Due to budgetary constraints, analysis was limited to female juvenile offspring (where greatest phenotypes were observed). Future comparative analyses in males would certainly provide insight into the relationship between alterations in methylation, gene expression and phenotype following antenatal sGC exposure, as well as sex differences in the molecular actions of prenatal sGC exposure in the developing hippocampus. Finally, future studies are required to further elaborate the mechanisms involved in transgenerational transmission.This study demonstrates transgenerational changes in transcription and DNA methylation following antenatal sGC exposure over the paternal lineage. Changes in gene transcription and DNA methylation patterns following antenatal sGC are generation-specific and are highest in the third-generation offspring. DNA methylation changes associated with sGC exposure may be involved in altered glutamatergic signaling. Significant changes in individual CpG methylation occur in RNApol II-PS5 binding regions of snRNAs and may implicate alternative splicing as a mechanism involved in transgenerational transmission of the effects of antenatal sGC. These findings demonstrate that the effects of antenatal sGC exposure alter genetic and transcriptomic regulation of the hippocampus of three generations of offspring through the paternal lineage. These findings provide new perspectives on the mechanisms involved in transgenerational transmission and show that the effects of antenatal sGC on the hippocampus may potentiate with advancing generations. Thus, it is imperative to perform future studies in human cohorts to elucidate the long-term effects of antenatal sGC on the developing brain and identify interventions to prevent transmission to subsequent generations.0: Charles River, St Constant, QC, Canada) were mated as previously described21. Pregnant guinea pigs received 3 courses of the sGC betamethasone  or saline (0.166 ml/kg) on gestational days (GD) 40 & 41, 50 & 51 and 60 & 61, as outlined previously21. Delivery in Dunkin-Hartley guinea pigs occurs at ~69 days, with an average of 3 offspring/litter in our colony. The sGC dose utilized in the present study is comparable to that given in pregnancies at risk of preterm delivery (~0.25 mg/kg), as the guinea pig glucocorticoid receptor (GR) has a 4-fold lower affinity for sGC67. While single course treatment with GC is currently standard of care, in the late 90’s and early 2000’s multiple course therapy was widespread68, and more recently the use of repeat ‘rescue’ sGC treatment has been adopted69.Twelve-week-old Dunkin-Hartley guinea pigs (F1) generation male offspring, derived from independent mothers, were mated with non-experimental females (purchased from Charles River) to generate F2 offspring, as previously described21. Third (F3) generation offspring were generated by mating the F2 males with non-experimental females. The males and non-experimental females were only bred once. Other than routine cage maintenance, F1 and F2 pregnancies were left undisturbed. A figure outlining the full breeding regimen has been published21. As we have reported previously, there was no significant effect of prenatal sGC treatment on breeding parameters in any of the generations, including litter size and sex ratio21. All protocols were approved by the Animal Care Committee at the University of Toronto in accordance with the Canadian Council on Animal Care.First . In the present study, the hippocampi from female juvenile offspring  were used for molecular analysis. Our previous studies had indicated that juvenile females showed the greatest differences in behavioural and neuroendocrine phenotypes  associated with prenatal sGC exposure21. All female offspring used in this study were derived from independent mothers, and each mother had been bred to a single F1 or F2 male.Animals were euthanized in an unstressed basal state on post-natal day 40, as previously reported31, composed of enhancer and promoter regions of the guinea pig genome. Promoter regions were identified from the Ensemble database, as well as from a previous RNAPolII-Ser5 ChIP experiment, the serine 5 phosphorylation marks RNA polymerase 2 molecules engaged in turning on transcription31. Enhancer regions were identified in a previous H3K4me1 ChIP experiment, H3K4me1 mark is enriched at enhancers31. The SeqCap probe enrichment kit from Roche allowed for the capture of 210 Mb of gDNA. 550 bp of promoter regions centered around the TSS were covered for all genes (26129 promoters equating to 6.8% of the capture). RNA PolII-Ser5 peaks were captured, along with RNA PolII-Ser5 peaks that coincided with H3K4me1 peaks . Enhancer peaks smaller than 550 base pairs were captured in their entirety  and 550 bp of larger enhancer peaks were captured to span the center of the peak . Lastly, a list of gene networks that we hypothesized would be most affected by sGC, based on previous studies14 was generated using 14 ‘seed’ genes  for which the top 20 genes related to biological process were selected61. This resulted in a list of 199 genes of interest , based on our previous study1: Veh N = 6, sGC N = 6; F2: Veh N = 6, sGC N = 6; F3: Veh N = 7, sGC N = 5) was purified using the AMPure XP beads , following the manufacturer’s instructions (1.8 v/v). Libraries were prepared from purified DNA, using the KAPA Library Prep Kit Illumina (Roche) and SeqCap Adapter kit (Roche) according to the SeqCap Epi Enrichment System User Guide. Libraries then underwent bisulfite conversion. Bisulfite conversion was performed using the EZ DNA Methylation-Gold Kit (Zymo Research), and bisulfite converted DNA was amplified using LM-PCR by a 15-cycle PCR and purified with AMPure XP beads (1 v/v) (Beckman Coulter). Size and quantity of the resulting libraries were verified using HSdna Bioanalyzer chip  and Q-PCR, respectively (Kappa Library Quantification kit for Illumina sequencing). Bisulfite libraries were hybridized with our custom SeqCap Epi Probe pool. After washing and recovery of captured DNA, an amplification using LM-PCR was performed as described above. All captured samples were sequenced by 50 bp pair end-sequencing Illumina HiSeq. 2000 sequencing at Institut de Recherches Cliniques de Montreal (IRCM).gDNA  using bsmap-2.74 v0.12.5. Picard-tools-1.93 was used to remove duplicates. Sequenced reads showed on average 68% on-target alignment with capture-probe design. Methylation levels were determined for individual CpG sites using bsmap-2.74 with a minimal coverage of 10 reads. Changes in methylation for 100 bp windows (50 bp apart) and individual CpGs were detected using the calculate DiffMeth function from MethylKit (v.1.4.0) in R (version 3.2.3). Data were annotated using Homer v4.6 with the annotatePeaks script and CavPor3 genome.1: Veh N = 6, sGC N = 5; F2: Veh N = 6, sGC N = 6; F3: Veh N = 6, sGC N = 7) at 1 × 51 bp by the Donnelly Centre for Cellular and Biomolecular Research . RNA-seq results were analyzed as previously described21. Briefly, differential gene expression was assessed using EdgeR’s (version 3.12.1)71, general linear model likelihood ratio test and FDR-corrected p < 0.05 was considered significant. Genotype permutations (1000) were computed in Broad Institute’s Gene Set Enrichment Analysis (GSEA)72 to determine FDR, nominal p-value, and normalized enrichment score (NES) of each gene set. Gene sets with FDR ≤ 0.25, p ≤ 0.01, and NES ≥ 1.6 met significance thresholds21. All sequencing data can be accessed at GEO with accession number GSE109765.RNA quality was determined by Bioanalyzer ; all RNA (1 μg) samples RIN ≥ 7. mRNA library preparation was performed using Illumina TruSeq V2 mRNA enrichment using standard protocols. High-throughput sequencing was performed on an Illumina HiSeq. 2500 sequencing system using standard run, following the protocol recommended by Illumina for sequencing mRNA samples. Sequencing was done for each biological replicate  based on Homer v4.6 using the annotatePeaks script. The expected counts were calculated with the number of CpGs that were sequenced with 10X coverage. Statistics were calculated using multinomial goodness-of-fit Chi-square test . Post-hoc Chi-square tests were run on each category (genomic region and capture design region) versus the sum of all other categories to determine which category was driving the effect.Mineralocorticoid Receptor (Nr3c2), Glutamate Ionotropic Receptor NMDA type subunit 2 A (Grin2a), Glutamate Decarboxylase 1 (Gad1), Synaptophysin (Syp)) was normalized to Gapdh (see Supplementary Table −ΔΔc(t) method. qPCR validation correlated 99% with RNAseq findings  was converted to cDNA using SensiFAST cDNA synthesis kit  as per the manufacturer’s instructions. The reaction included random hexamer primers and anchored oligo dT to ensure unbiased 3′ and 5′ coverage and reverse transcription of all regions. qRT-PCR was run using the SensiFAST SYBER Hi-ROX kit  with forward and reverse primers according to the manufacturer’s instructions. qRT-PCR was performed in a Bio Rad C1000 Thermal Cycler and quantified by a CFX96 Real-Time PCR Detection System using the following conditions: 95 °C for 30 sec; followed by 40 cycles of 95 °C for 5 s, and 60 °C for 5 s, for plate read. All samples were run in triplicate. Relative expression of target mRNA (Supplementary Figure S1Supplementary Table S1Supplementary Table S2Supplementary Table S3Supplementary Table S4Supplementary Table S5Supplementary Table S6


Background: Reduced sensation is experienced by one in two individuals following stroke, impacting both the ability to function independently and overall quality of life. Repetitive activation of sensory input using active and passive sensory-based interventions have been shown to enhance adaptive motor cortical plasticity, indicating a potential mechanism which may mediate recovery. However, rehabilitation specifically focusing on somatosensory function receives little attention.Objectives: To investigate sensory-based interventions reported in the literature and determine the effectiveness to improve sensation and sensorimotor function of individuals following stroke.Methods: Electronic databases and trial registries were searched from inception until November 2018, in addition to hand searching systematic reviews. Study selection included randomized controlled trials for adults of any stroke type with an upper and/or lower limb sensorimotor impairment. Participants all received a sensory-based intervention designed to improve activity levels or impairment, which could be compared with usual care, sham, or another intervention. The primary outcomes were change in activity levels related to sensorimotor function. Secondary outcomes were measures of impairment, participation or quality of life.Results: A total of 38 study trials were included ; 29 explored passive sensory training , 6 active  and 3 hybrid . Meta-analyses  demonstrated a moderate effect in favor of passive sensory training on improving a range of upper and lower limb activity measures following stroke. Narrative syntheses were completed for studies unable to be pooled due to heterogeneity of measures or insufficient data, evidence for active sensory training is limited however does show promise in improving sensorimotor function following stroke.Conclusions: Findings from the meta-analyses and single studies highlight some support for the effectiveness of passive sensory training in relation to sensory impairment and motor function. However, evidence for active sensory training continues to be limited. Further high-quality research with rigorous methods (adequately powered with consistent outcome measures) is required to determine the effectiveness of sensory retraining in stroke rehabilitation, particularly for active sensory training. Sensation is the means by which we process and interact with the world and our environment Connell, . It alloReduced sensation is experienced by one in two individuals following stroke  has been shown to enhance adaptive motor cortical plasticity, indicating a potential mechanism which may mediate recovery ; Database searching was conducted based on the predetermined criteria in Within sensory training the types of interventions and the mechanism of action differ significantly making it difficult to clearly delineate intervention effects. Sensations of interest were limited to somatic (cutaneous and proprioceptive). Sensory training was separated into three areas; passive , active (a sensory retraining approach based on graded re-education using learning principles) and hybrid (a combination of sensory stimulation and retraining) interventions see  Schabru.The search strategy of medical subject headings and keywords were developed in Ovid Medline database using variations of the term stroke and sensation, “sensory training,” “sensory education,” “sensory rehabilitation,” “sensory practice,” “sensory treatment,” “sensory awareness,” “sensory movement,” “sensory intervention,” “sensory discrimination,” “stimulation therapy,” “cutaneous stimulation,” “electrical stimulation,” “afferent stimulation,” “sensory stimulation,” “stimulation therapy,” “somatosensory stimulation” . Disagreement between reviewers was discussed to reach consensus and/or resolved by a third reviewer (S.H.).Cochrane Handbook version 5.1.0 recommendations, using a predesigned data extraction spreadsheet in Microsoft Excel 2018, version 16.16.5. Extracted data included characteristics of participants, intervention, comparator, and outcome results.Data extraction was conducted using the Two reviewers (I.S. and B.H.) independently assessed all the included studies using the standardized domain-based evaluation Cochrane Risk of Bias Tool, the preferred tool of the Cochrane Collaboration  and secondarily impairment (for example range of motion or strength). Two authors (I.S. and S.H.) extracted and entered data and cross-referenced to reduce risk of errors. The mean and standard deviation data from the first post intervention time-point (or first group from crossover studies) were used. Data from time-points other than the first post intervention assessment including follow-up data were not analyzed because of the heterogeneity between studies. When mean and standard deviation data were not available, study authors were contacted for the original data set. Those that could not be contacted but median and interquartile range were available, a formula for the standard deviation (SD) from Hillier and Inglis-Jassiem SD = 0.75 × IQR (SD = 0.75 × IQR) was used and it was assumed the median equated to the mean  and results  where appropriate were manually extracted by two independent assessors (I.S. and S.H.) and transferred into Microsoft Excel 2018 (version 16.16.5). Review Manager (RevMan 5.3.5) software was used for data synthesis and to perform meta-analyses with sufficiently homogenous data to calculate effect sizes. In the meta-analyses, data from randomized controlled trials were pooled based on comparable control groups and outcome measures. These were then grouped into the Tables 4–6). A total sample of 1,093 participants were included. Total mean age range was 39.9–72.6 years, 657 of these were males and 399 females and 366 were affected on the left-side and 404 right. Total mean time since stroke ranged from 0.87 months to 11.5 years. The most common reasons for exclusion are reported in A total of 14,446 trials were identified from preliminary searches, with the summary flow of trials outlined in Where possible, data were pooled based on outcome measures and controls. Meta-analysis of data to determine effectiveness was possible for 13 studies   see , 3 with z = 12.35; P = 0.00001). A significantly positive difference was also found for the Motor Assessment Scale (MAS) . The Box and Block Test (BBT) did not show a significant effect  with one active upper limb study (Perfetti's method) , MAS (I2 = 0%) and BBT (I2 = 0%) showed no heterogeneity.Of the data pooled based on comparisons of sensory versus usual care see , a signiz = 6.05, p = 0.00001), the passive lower limb study  . A significant effect favoring sensory training was found on the Fugl-Meyer Assessment (FMA)  with two lower limb passive studies  , BBS (I2 = 94%), and FMA (I2 = 91%) showed considerable heterogeneity.The Barthel Index (BI) showed an overall positive significant effect from sensory training , Wolf Motor Function Test (WMFT)  and FMA  all returned a significant effect (see I2 = 62%), moderate for FMA (I2 = 35%) and no heterogeneity for WMFT (I2 = 0%).The MAL  and Nottingham Sensory Assessment (NSA)  showed no significant effect on sensory training, while Stroke Impact Scale (SIS)  z = 0.92, p = 0.36) returned a negative effect (see I2 = 0%) and SIS (I2 = 0%), while considerable heterogeneity was indicated for NSA (I2 = 84%).Further meta-analyses were conducted for the comparison of sensory versus sham stimulation see . For theNarrative synthesis was used to summarize the randomized controlled trials that could not be pooled in meta-analyses.Passive sensory training interventions used a variety of frequency parameters and intensities see . Five stTraining duration and controls: Training duration varied from 20 to 180 min, 1 to 7 sessions/week over a period of 1–12 weeks, with the number of sessions ranging from 1 to 30. Fifteen studies used sham stimulation without current delivered/turned off as the control  adverse effects: clinicians need to be conscious of monitoring these effects when using any sensory-based interventions. Careful consideration must also be taken by therapists regarding the suitability of sensory training for the individual prior to clinical application to improve individual functional outcomes particularly when active participation is required.Implications for research: The significant number of individuals that continue to experience sensory deficits following stroke and the potential benefits of sensory training identified in this review indicate further research is essential. High-quality randomized controlled trials with high statistical power and rigorous methods including consistent and homogenous outcome measures are required to support or refute the effectiveness of sensory training, particularly active sensory training following stroke. Sufficient reporting of the type of intervention and training parameters are required to allow replication of the sensory training protocol.All studies included were randomized controlled trials which are considered the ‘gold standard' when determining treatment effectiveness as this robust methodological design minimizes the effects of bias. Methodological quality was reasonable across most studies, however, there were areas where methodological rigor was notably lacking introducing the potential for bias and reducing confidence in the findings. The results may have been influenced by widespread lack of blinding of participants and personnel with the potential for performance biases, lack of concealment with the potential for selection biases and the potential for other biases with seven of the included studies implementing a single treatment session. These were included as they met the selection criteria, however the therapeutic effect of a single session has heightened the risk of biases as these data cannot be extrapolated to results from repeated sessions as would occur in a clinical setting. Of the 38 randomized controlled trials, only nine studies justified the selected sample size while 23 of these sample sizes were relatively small and six only mentioned the total sample size limiting capacity to observe significant effects. This may mean the insufficient evidence in this review may be due to poor statistical power rather than ineffective intervention. Reliability and validity of measures used were strong, however, passive training studies predominantly used measures relating to motor activity , while active training focused on measures at the impairment level . The impairment-based measures may be more sensitive to detecting change and any changes are likely to be of a smaller magnitude and not reach statistical significance as easily, while changes in function are generally larger and may be the results of net improvements in sensation, proprioception and motor function rather than one single component (Schabrun and Hillier, This review sought to provide an updated review investigating the effects of sensory training protocols on somatosensory function following stroke. Although a greater number of studies have been published since the previous reviews in 2009 and 2010 (Schabrun and Hillier,  Passive sensory interventions may assist in improving activity following stroke. Evidence for active sensory training continues to be limited by research design, small sample size and heterogeneous outcome measures. Further high-quality research is required to determine the effectiveness of sensory training in stroke rehabilitation, particularly active-based therapy.All datasets generated for this study are included in the manuscript and/or the All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Discharge time series of major large-catchment European rivers are known to display significant decadal and interdecadal fluctuations. However, the hydroclimate variability causing such fluctuations remains poorly understood, particularly due to a lack of a spatio-temporal integrated assessment. Here, we demonstrate for the first time that European hydroclimate variability is dominated by a meridional delayed oscillation characterized by a lag of approximately 5 years in interdecadal discharge fluctuations of continental (northern) European rivers with respect to those of Euro-Mediterranean (southern) rivers. We demonstrate a connection of this coherent signal with the large-scale atmospheric circulation over the North Atlantic, and suggest a hitherto unexplored multiannual atmosphere-ocean mechanism in the subpolar North Atlantic at its root. Figure 8. Analysis of individual rivers has revealed that the connection between European hydroclimate variability and North Atlantic climate can be non-stationary9 and affected by temporal lags10. But such relationships need not be uniform within Europe.Observed discharge time series of major European rivers are characterized by significant variability in the interdecadal time scales (10–30 years)6 as well as Dinaric Alpine rivers  in the Po River - representative of Italian Alpine rivers11 capture the prominent interdecadal evolution of observed Mediterranean and continental river discharges as well as their associated phase lag  Europe and drying over the Mediterranean region28. Our results show prominent interdecadal river discharge variability in contrast to only sporadic significant long-term trends  program, and Office of Biological and Environmental Research (BER), and by the National Oceanic and Atmospheric Administration Climate Program Office.Reanalysis data are from the monthly NOAA-CIRES 20th Century Reanalysis V2 dataset32.Wavelet coherence spectra are calculated using the cross wavelet and wavelet coherence package by Aslak Grinsted, John Moore and Svetlana Jevrejevan peak anomaly years Y1,..,n, we generate m sets of random n integer values Vm;1,…,n obtained by rounding samples from the normal distribution N; we then sum Y and V to obtain m realizations of uncertain peak anomaly years.Temporal uncertainty in the sampling of anomalous wet and dry phases (ref. Figs Supplementary Material


Osteoarthritis is the most common musculoskeletal disease causing chronic disability in adults. Studying cartilage aging, chondrocyte senescence, inflammation, and autophagy mechanisms have identified promising targets and pathways with clinical translatability potential. In this review, we highlight the most recent mechanistic and therapeutic preclinical models of aging with particular relevance in the context of articular cartilage and OA. Evidence supporting the role of metabolism, nuclear receptors and transcription factors, cell senescence, and circadian rhythms in the development of musculoskeletal system degeneration assure further translational efforts. This information might be useful not only to propose hypothesis and advanced models to study the molecular mechanisms underlying joint degeneration, but also to translate our knowledge into novel disease-modifying therapies for OA. Osteoarthritis (OA) is one of the most prevalent joint diseases and a leading cause of disability worldwide , 2017. OThe process of cellular senescence contributes to age-related dysfunction and chronic inflammation. Senescence essentially refers to the irreversible growth arrest that occurs when cells experience stress insults. Articular cartilage undergoes aging-associated changes in structure and biochemical composition which compromise biomechanical function and contribute to the formation of structural defects  The growth arrest, which is a replication failure due to the expression of cell cycle inhibitors, occurs in senescent cells following various stimuli. These stimuli can consist in DNA damage, telomere shortening, oncogene activation for the most widely described, but other stimuli such as inflammation, reactive oxygen species (ROS), mitotic stress or unresolved unfolded protein response can also drive cell growth arrest. Following to these stimuli, two main signaling pathways are often involved, the DDR-dependent pathway P53-P21CIP1-retinoblastoma protein (pRB) and the DDR-independent pathway P16INK4A-pRB. These pathways include cyclin-dependent kinase inhibitors (CDKIs) such as P21CIP1 (CDKN1A) or P16INK4A (CDKN2A), which respectively inhibited cyclin-dependent kinase-2 (CDK2), CDK4, and CDK6. Through CDK4 and CDK6 inhibition, the p16INK4A conserves pRB in their repressive forms, thus preventing G1/S phase cell cycle progression  Cell death resistance is also a common feature of senescent cells. Indeed, senescent human fibroblasts resist apoptosis induced by growth factor deprivation or oxidative stress  The Senescence-Associated Secretory Phenotype (SASP) is a bioactive secretome produced by senescent cells which remain metabolically active despite they are not proliferative  and the associated signaling pathways, all SASP regulators converge to the nuclear factor-κB (NF-κB) signaling  as well as HMGB1 through their interaction with the Receptor for advanced glycation end product (RAGE) . Whereas, the normal β-galactosidase activity is detectable at pH 4.5, the SAβ-gal is only detectable at pH = 6 on fresh sample with the X-gal substrate   where DDR proteins accumulate allowing the DNA-SCARS detection. These foci are detected through the staining of γH2AX, the phosphorylated form of histone H2AX. Following DNA damage, Histone H2AX is phosphorylated by the ATM/ATR protein and generates bright foci , cytokines , and chemokines  can be directly assayed in cell supernatants using Elisa or multiplex immunoassay.INK4A in various tissues. This accumulation contributes to the onset of age-related disorders and morbidity by compromising tissue function and structural integrity  and catabolic stresses  increase autophagy in chondrocytes  have less cartilage degradation, more proteoglycans and chondrocytes, as well as less signs of synovial fibrosis. Autophagy markers  are significantly increased, while apoptotic cells and catabolic factors, such as MMP-13 and MMP-induced type II collagen breakdown product C1, 2C, are reduced  associated with increased susceptibility to cell death induced by oxidative stress and reduced levels of antioxidant proteins as well as autophagy  alleviates cartilage degeneration by activating autophagy  (Berenbaum and Meng, Consistent with this idea, the recent description of a molecular dialog between clock gene BMAL1 and the energy/nutrient sensor SIRT1 has shed further light on the clinical translatability of this therapeutic concept (Dvir-Ginzberg et al., in vitro and in vivo experiments in animal model of OA or in clinical trial, notably with respect to the ambiguous role of SIRT1 in mediating the pro-inflammatory effects of IL-1β or H2O2 in chondrocytes (Guo et al., Also in line with the concept that cartilage intrinsic CR may be a pragmatic entry point for the development of integrative therapeutics in OA, is the intriguing connection between circadian genes and autophagy. As extensively described above, autophagy is a key process in the onset of OA and is thus considered a promising therapeutic target. Of interest, BMAL1 has recently been shown to positively regulate autophagy through mTOR in cardiomyocytes (Qiao et al., Despite some areas of darkness still subsist notably regarding the molecular links between CR, SIRT1/AMPK energy sensors, and autophagy, these data reinforce the notion that local clock genes may be considered as clinically relevant targets for the development of novel therapeutic intervention. See Figure Failures of autophagy homeostasis lead to cell dysfunction senescence and death and initiate the musculoskeletal degeneration and inflammation characteristic of rheumatic diseases. In this sense, preclinical models of such fundamental homeostasis mechanisms might create opportunities to build biobanks with patient derived material that can be used to perform drug screens and facilitate drug development. Clinical and preclinical models include blood, tissues from human joints and experiments in rodents showing that aging and OA of articular cartilage are invariably associated with defective autophagy and inflammation. Studying these dimensions of cartilage aging, chondrocyte senescence, inflammation and autophagy could facilitate to open the pharmacological space to novel disease-modifying therapies for OA. In this review, we highlighted what is currently known about preclinical models of OA homeostasis, the major targets and pathways identified, and its potential value for translation. See Figure Data for this review were collected by searching in PubMed database for articles published from 1965 to 2018 using the following keywords “osteoarthritis,” “inflammation,” “aging,” “senescence,” “SASP,” “chondrocyte,” “homeostasis,” “autophagy,” “therapeutics,” “metabolism,” “circadian clock” alone or in combination. English-language original publications and Review articles were selected on the basis of their relevance for the inclusion in the bibliography.All authors approved the final version to be published. CV, ED, JG, BC: manuscript design and drafting and revising 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. The handling Editor declared a past co-authorship with one of the authors BC.


Sorghum bicolor L. Moench). The objective of this study was to assess yield and quality of lignocellulosic biomass enhancement for ethanol production potential in a population of sorghum derived from two cultivars with contrasting biomass yield and compositional traits. We tested 236 recombinant inbred lines (RIL) of sorghum in a randomized complete block design (RCBD) with two replications for lignocellulosic biomass performance and determined hemicellulose, cellulose and lignin concentrations through detergent fiber analysis (DFA). The stover compositional values were used to estimate theoretical ethanol yield (ETOH on a mass basis) and production (ETOH on an area basis). Results showed that RIL carrying the brown midrib mutation had significantly higher theoretical glucose recovery . Those carrying both mutations, had high theoretical ethanol yield (>400 L ton-1) and high theoretical ethanol production . Lignin concentration was determined as most reliable predictor (R2 = 0.67) for glucose recovery. Lignin and stem sugar concentrations  were good predictors for ethanol yield. Stover yield traits (R2 = 0.89) were most important determinants for ethanol production. Our findings suggest that careful breeding of sorghum for genetic enhancement of biomass quantity and quality could double lignocellulosic ethanol yields.Public appetite for fossil fuels continues to drive energy prices and foment the build-up of intractable environmental problems. Ethanol (ETOH) production from lignocellulosic biomass grown in marginal lands offers a sustainable alternative without diverting arable land from food and feed production. The quantity and quality of lignocellulosic biomass can be enhanced by the abundant genetic diversity for biomass production as well as stem sugar and lignin composition in sorghum ( Fossil fuel dependency and increased greenhouse gases are major concerns that have caught the attention of environmentalists, economists, as well as scientists. Fossil fuel is a non-renewable source of energy, with its production and utilization generating gases, associated with environmental pollution as well as causing respiratory health problems. However, rapid expansion of the global economy sustains an insatiable hunger for energy, leading to a strong dependency on fossil fuel products. This dependency creates a growing consumer demand that raises petroleum product prices affecting the economy within and among countries .A large volume of lignocellulosic biomass is produced from a number of crops every year. Field crops produce considerable amounts of both grain and stover. Grain from crops is harvested and used for human (food) and animal (feed) consumption, while stover (lignocellulosic biomass) is often left unharvested on-farm every crop season . Though Sorghum research conducted over the last several years has generated interest in this stress-tolerant species as a potential biomass crop for lignocellulosic feedstock and energy production . KnowledZea mays) and sorghum (Sorghum bicolor) by either spontaneous or chemical mutagenesis. Five brown midrib (bm1 through bm5) loci have been identified, extensively studied, and genetically characterized in maize. The brown midrib phenotype (reddish-brown coloration) is correlated with two homologous loci in maize (bm1 and bm3) and sorghum (bmr6 and bmr12). In both grasses, the brow midrib phenotype is associated with reduced lignin concentration and increased livestock digestibility (Brown midrib mutants have been identified in maize (tibility .bmr) mutation in sorghum, caused by single-point mutations in genes involved in cell wall composition, generally reduces lignin concentration. The bmr mutants are visually identified by the reddish-brown coloration in the midrib of sorghum leaves that is associated with low lignin concentration. Several bmr mutant lines were identified at Purdue University from a chemical mutagenesis study aimed at improving sorghum forage quality  activity during lignin biosynthesis. The CAD is encoded by a multi-gene family consisting of members thought to have distinct roles  and sweet sorghums  or structural carbohydrates (hemicellulose and cellulose) to ethanol. Soluble carbohydrates  are generally referred to fermentable sugars and these accumulate in stems of crops like sugarcane  To determine the concentration of cellulose, hemicellulose and lignin  of bmr × sweet sorghum RIL; 3) To estimate theoretical glucose recovery, theoretical ethanol yield, and theoretical ethanol production from two sources of carbohydrates; and 4) To determine suitable predictors associated with theoretical ethanol.A genetically enhanced biomass that combines both sources of carbohydrates, maximizing the soluble carbohydrate pool, but also making the structural carbohydrates of cell walls readily fermentable, increases the value of a feedstock . We hypo2 population of a cross between two lines, bmr12  and Brown County (a sweet sorghum) as parents. Additionally, a forage sorghum cultivar (bmrAtlas) with an introgressed bmr 12 gene was included as control.A population consisting of 236 RIL was evaluated in a 2-year study. The population was developed through seven generations of single-seed descent selection from the original FThe experiment was planted in late May at the Agronomy Center for Research and Education (ACRE) in West Lafayette, Indiana . The soils at ACRE consist of Drummer silty clay loam  and Raub silt loam  . Mean aibmrAtlas were each planted in two-row plots. Dimensions of each plot were 6.10 m long with 0.76 m spacing between rows. Approximately 2.5 grams sorghum seed row-1 was planted at a depth of 5 cm. The seeds were treated with a fungicide prior to planting to ensure better seedling emergence and stand establishment. Three weeks after planting, plots were thinned to 6 plants per 30 cm for an approximate plant population of 250,000 plants per hectare. Urea ammonium nitrate was applied and incorporated at a rate of 150 kg N per hectare.All RIL, both parents, and Plant maturity (PM) of grain was defined as 45 days after flowering date. Based on flowering dates, RIL were placed into three PM groups in order to minimize confounding differences of PM in biomass component and compositional traits. Stem sugar concentrations (SSC) were estimated as degrees Brix (ºBrix) of each RIL, parents and commercial control at PM. For each plot, four plants located in the middle region of each row were randomly collected and stem internodes between the fourth and the fifth node squeezed with a garlic press to obtain the stem juice. A digital refractometer (ATAGO Model PAL-1) was used to measure Brix (One degree Brix is 1 g of soluble sugars in 100 g of solution) . The aveHemicellulose and cellulose of stover of 236 RIL were analyzed by modified filter bag technology using ANKOM 2000 instrument  . Two modGlucose recovery formulas reported in the literature were inadequate for brown × midrib RIL since they did not account for the advantage of reduced lignin. Theoretical glucose recovery (TGR) from cellulose was estimated by a modified equation :where GRE is the glucose recovery efficiency, and 1.1111 is the glucan hydrolysis coefficient . The GREThese modifications adjusted for the differences in lignin concentration among the RIL.Theoretical xylan recovery (TXR) from hemicellulose was estimated as follows :where 1.1353 is the hydrolysis coefficient for xylan.-1) were estimated as follows  from cellulosic glucose and hemicellulosic-derived xylan  in L tonl et al. :* is fresh stover yield used to estimate L of ethanol per ton. On a unit basis, ml g-1 = L kg-1.where FSY is fresh stover yield, Brix% is concentration of SS in stem juice , 0.90 is soluble sugars recovery efficiency (sugar yield) and FSY-1) from two sources of carbohydrates  was calculated as:Therefore, TETOHY (L ton-1) were estimated as follows:Theoretical ethanol production (TETOHP) from cellulosic glucose and hemicellulose-derived xylan (L ha-1) in both formulas.where DSY is dry stover yield (ton ha-1) was estimated as follows:TETOHP from SS (L ha-1) from two sources of carbohydrates  was calculated as:Therefore, TETOHP  of SAS 9.3 was used to determine genetic variation and mean differences among RIL. The RIL were considered a fixed effect, Year and Year × RIL interactions were considered random effects. The RIL were assembled into four phenotypic groups to allow a more detailed analysis among contrasting phenotypes. Based on their genetic recombination status , the “normal”  group was formed by 43 RIL without brown midribs or high stem sugar concentrations (Brix < 12). The “sweet”  group was formed by 108 RIL that carried a mutation for high stem sugar concentration (Brix ≥ 12), but did not have brown midribs. The “brown”  group contained those RIL that had brown midribs but were not sweet (10 RIL). The fourth group named “brown-sweet” (recombinants of low-lignin and high stem sugar) were 75 RIL that carried both mutations, one for low lignin (brown midrib) and another for high stem sugar concentration (Brix ≥ 12). We dubbed this group the double mutant group because of the two mutations its members carry. This grouping allowed us to obtain three orthogonal contrasts. The first linear combination compared the double mutant group (“brown-sweet”) against the “normal” RIL group. The second linear combination compared the double mutant group against the “sweet” group. The last linear combination compared the double mutant group against the “brown” group.The PROC REG procedure of SAS 9.3 was used to determine suitable estimators associated with TGR, TETOHY, and TETOHP. The following formula was used to estimate the predictors:-1), SSC (ºBrix), FSY and DSY (ton ha-1). The slope of the line is b1 and b0 is the intercept.where X is the explanatory variable and Y is the dependent variable. X was represented by NDF, ADF, cellulose, hemicellulose, lignin (g kgbmr plants (“brown” RIL group) are typically smaller than those of “sweet” RIL, when the bmr mutation is combined with the sweet mutation, as in the “brown-sweet” RIL group, the low biomass quantity associated with the bmr mutation background effects appear to be compensated for  showed significantly lower lignin concentration (∼26.5 g kg-1) than the other two RIL groups (∼40 g kg-1). This represents 60% less lignin concentration in the stover of the bmr RIL relative to the others, presumably making the other structural carbohydrates more available to enzymatic hydrolysis  than cellulose and lignin 2. The mdrolysis .bmr mutation was not significantly higher than the bmr donor, bmr12, these RIL showed significantly higher estimates of TGR in comparison to the sweet parent, Brown County and the RIL without the bmr mutation , and was similar to the “brown” and “brown-sweet” RIL groups. Interestingly, bmrAtlas and Brown County showed similar TGR from cellulose. This supports our hypothesis that genetic background differences could play a major role in enzymatic hydrolysis of lignocellulosic biomass , thereby maximizing ethanol yields (bmrAtlas and bmr12 (genotypes with the bmr mutation).The TETOHY is a function of the amount of structural carbohydrates and non-structural sugars present in stover that is ultimately available for fermentation Figure 2l yields . No sign-1, respectively, and these values were not significantly different from each other  were predicted to produce 11,883 and 12,058 L ha-1 of ethanol, respectively. These amounts were not significantly different from the “brown-sweet” and “sweet” RIL groups. Predicted ethanol production of the “normal” and “brown” RIL groups similar , and these two RIL groups were not predicted to produce as much ethanol as the “brown-sweet” and the “sweet” RIL groups . Lignin, hemicellulose and cellulose concentration explained 66%, 11%, and 8% of the variation in glucose recovery, respectively. Most importantly, lignin concentration was negatively correlated with TGR, while hemicellulose and cellulose concentrations were positively correlated. Lignin concentration therefore emerged as best predictor of TGR from cellulose in our bmr × sweet sorghum population  and ADF (4%)  .The TETOHY shows a slightly different trend when compared to TGR, though lignin (46%) still emerged as a major predictor in the RIL population Table 4.bmr mutation. Within the “sweet” and “normal” RIL groups, SSC  were significant predictors of TETOHY. Here again, there was enough variation among the members lines in Brix measurements to see associations with ethanol yield. This was also true for lignin concentration, even though neither group contained individuals with brown midribs  were also the major predictors of TETOHP when the population was analyzed in groups based on presence or absence of the sweet and bmr mutations. In all groups, these two quantity measures predicted 82% to 95% of the TETOHP. In all but the “brown” RIL group, variation in SSC was significantly and positively correlated with TETOHP. This also support the hypothesis that biomass quantity traits, FSY and DSY, are the major determinant for ethanol production Table 4 COMT gene mutation to reduce lignin concentration in lignocellulosic biomass showed positive effects towards the improvement of biomass conversion efficiency of the bmr lines in this study, at the population level, consistent with previous studies , but the “brown” RIL group (383L ton-1) more so than the “sweet” RIL group (370L ton-1). This is perhaps not too surprising considering the effects of each mutation on overall availability of fermentable carbohydrates in the plant . When single mutations for lignocellulosic biomass enhancement were compared independently, the low lignin bmr mutation had a more significant effect on predicted ethanol yield than stem sugar “sweet” mutation, a result also previously reported in other studies  for a crop like sorghum, genetic changes in quality traits that improve the efficiency by which the biomass is converted to ethanol become important.Based on data from this study, biomass quantity emerges as the most important factor in determining ethanol igestion . This mabmr-sweet sorghum lignocellulosic biomass give much higher amount of ethanol production is significantly important. Miscanthus, sugar beet (Beta vulgaris), maize (Zea mays), rice (Oryza sativa), wheat (Triticum aestivum), sugarcane (Saccharum officinarum), sweet and forage sorghum (Sorghum bicolor) produce no more than 6,500 L of ethanol per ha  offered two sources of stover carbohydrates  to significantly increase ethanol yields.In summary, large-scale production of a genetically enhanced lignocellulosic biomass would help to improve bioconversion efficiency required by the bio-refineries. Traits that enhance biomass quality such as the low lignin and high stem sugar concentrations, as well as traits contributing to increased biomass quantity per unit land  can improve ethanol production, driving down cost without harmful environmental effects. In this study, we found that biomass quantity traits were the most important determinants of ethanol production, and biomass quality traits enhanced sorghum biomass conversion. The genetically enhanced sorghum biomass (LR-B designed and conducted the research, collated and analyzed the data, and produced the manuscript draft. GE developed the sorghum mapping population and suggested the research question. He also supervised the research and edited the manuscript. JV supervised the research and edited the manuscript.This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. LR-B’s graduate research support was covered by GE’s Distinguished Professor research allowance from Purdue University.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.


In this manuscript, we use endogenous cell nuclei as pressuresensors by introducing a fluorescent protein localized to the nucleus andconfocal microscopy to measure the individual nuclear volumes in 3Dmulti-cellular aggregates. We calibrate this measurement of nuclear volume topressure by quantifying the nuclear volume change as a function of osmoticpressure in isolated 2D culture. Using this technique, we find that inmulticellular structures, the nuclear compressive mechanical stresses are on theorder of MPa, increase with cell number in the cluster, and that thedistribution of stresses is homogenous in spherical cell clusters, but highlyasymmetric in oblong clusters. This approach may facilitate quantitativemechanical measurements in complex and extended biological structures both These stimuli are transduced into biochemical signals, whichin turn regulate cell mechanics and behavior. New mechanotransduction interactionsare being discovered, but some known mechanisms include elements that connect thecell to its environment through focal adhesions[in vitro and in vivo is an integral part ofmodern quantitative biology, and a broad variety of techniques to measure cellforces and mechanics have been developed, particularly in the last two decades.Traction Force Microscopy has emerged as an excellent measure of cellularcontractile forces in 2D [invitro systems, and are not readily applicable to more complex 3Dstructures of multiple cells and complex mechanical structures. Recently an approachhas combined microrheology and optical tweezers to infer extracellular matrixstiffening from cell contractility[in vivo in tissues [Cells are exposed to diverse forces adhesions, 2, the adhesions.Measuries in 2D ,5 and 3es in 2D  and locaes in 2D . Additioes in 2D . These tes in 2D  and forces in 2D  of cellses in 2D .Moreoveractility. Other g tissues . This flCompressive stresses are of particular interest as they can lead to nucleardeformation As thelAn ideal probe for compressive stresses would be an endogenous, ubiquitous, uniform,and dispersed collection of compliant spheres. Indeed, the nucleus itself presents alarge spheroid, with a generally constant size in normal mammalian cells, have verysimilar sizes within a given population for many cells –23, and Mus musculus, mouse (Passage 5–30) cells (ATCC) and M6cells  were grown in culture medium with 10%FBS and 1% antibiotic (pen strep). M6 cells were transfected with NuclearLocation Sequence tagged with Green Fluorescent Protein  using Lipofectamine 2000 (Invitrogen) followingInvitrogen’s protocol. After transfection, successfully transfected cells wereisolated by FACS (MoFlo XDP Cell Sorter), and growth of untransfected cells wassuppressed by adding a selective antibiotic  to the growthmedium. After three days of selection, the positively transfected cells weregrown in full medium. Before volume measurements, cells were trypsinized andresuspended in the 3D sodium alginate gels, creating an environment with readilytuned physiological moduli, capable of supporting cell growth and proliferationfor several weeks. As these cells proliferate, they form spheroid multi-cellularaggregates (MCAs), a very simplified analog for complex tissue structures(detailed MCAs growth described in [NIH3T3 ribed in ).imagej.com).For single cell volume measurements cells were trypsinized, washed, centrifugedin full culture medium, and resuspended in full medium with differentconcentration of polyethylene glycol , cells were allowed toequilibrate for 20 minutes at room temperature, then plated on a very thin layerof agar gel on the glass bottom petri dishes to avoid adhesion. Nuclei insingle-cell pressure-volume calibration measurements were stained with DAPI(Bisbenzimide—Sigma) and reconstructed from confocal images (Leica SP8) usingimageJ (Single cell nuclei (stained with DAPI (Bisbenzimide—Sigma)) images, were acquiredusing a 40x air with NA = 0.75 objective on an inverted confocal microscope (LSMZeiss 700 or Leica TCS SP8). Each individual cell nuclei was imaged precisely byacquiring XYZ stacks with a 0.5 μm Z step and XY resolution of (72.73x72.73μm).Cells were plated on a thin layer of agar gel to avoid adhesion duringimaging.Images of nuclei within MCAs were acquired using a 10x objective on an invertedconfocal microscope (Leica TCS SP5) with a 5μm Z step size. Using this largerstep size did not decrease our volume resolution  to isotonic culture medium. The osmolality of different PEGsolutions was measured using a freezing point depression osmometer , and we then calculated the resultingosmotic pressure . These eWe have employed osmotic pressure due to steric exclusion to create ourcalibration curve for pressure-volume relationship . It is kWe have plotted the measured volume as a function of osmotic pressure appliedusing PEG . AsinglNuclear volumes were measured by direct microscope observation after exposing M6(n = 35) or NIH3T3 (n = 40) cells to a wide range osmotic pressures via theaddition of 1500-Da PEG, as described in the Methods section. As reportedpreviously , 23, theV(P) =1006∙P−0.4441 allows us to calculate thecorresponding pressure for the measured nuclei volume in multicellularaggregates (MCA) [The fitted curve (blue) in es (MCA) ,and depes (MCA) .We also find no lasting effects on cells after prolonged exposure to investigatedosmotic pressures; after 38 hours of exposure to varying concentrations of PEG,all nuclei recovered to previous control volumes see ,as repo3, 800+/-70 x 103, and 2100+/-100 x 103μm3 are shown in Nuclei transfected M6 cells were encapsulated in alginate gels and imaged overthe course of three weeks, with cell colonies forming multicellular aggregates(MCAs). The volume of nuclei within MCAs of different sizes were imaged with XYZstacks employing a 5 μm Z step. Number and volume of nuclei depends on the MCAsize, where smaller MCAs are composed of cells with larger nuclei. As MCAs grownis size, the average volume of individual nuclei decreases . Three M3μm3 .We obseHere we have shown that nuclei volumes imaged with confocal microscopy may be used aspressure sensors within multicellular aggregates, enabling previously inaccessibleregions of multicellular structures or tissues to be measured without theintroduction of an exogenous mechanical probe.We have shown that using PEG we can apply a precise osmotic pressure to produce areversible and predictable compression of the nucleus. Osmotic pressures from PEGwere verified through direct measurement and found to be consistent with literaturevalues. We employed osmotic pressure to measure the pressure-volume (PV) curve ofnuclei in isolated cells, where cells are not under compression from neighbors orfrom substrate-based contraction. The measurement of bulk moduli for cells fromosmotic compression is an established technique. It is important to note that unlikephysiological salts, there are no pumps for PEG, it does not pass through themembrane, and cells are unable to adapt osmotically; thus, using osmotic stress froma salt-based source would be inaccurate, however, PEG-based osmotic stress isaccurate in calculating bulk moduli.We evaluated the validity of this approach by applying prolonged various pressures tocells, and quantifying their mechanical responses. This demonstrates that thesenuclei do not mechanically adapt to these pressures, validating their use ascalibrated pressure probes. While these data demonstrate that this approach isrobust for measuring these cells and employing them as pressure sensors, this maynot always be the case; during early development, differentiation, and diseaseprogression nuclear mechanics may be variable as cells change expression of proteinssuch as lamins –38. OtheHaving established and validated these PV curves, we then calculate the equivalenttotal pressure in the multi-cellular aggregate from the confocal microscopy measuredvolumes.Our study reveals that these compressive stresses acting on nuclei are in the MParange, which appears quite large when considering the typical stress regimes of kPathat are reported for cell stresses. A key difference here is the application ofcompression rather than shear, as bulk moduli (~MPa) arThe pressures measured here are the sums of all forces compressing the nuclei; theseinclude compressive-stresses, as well as any osmotic pressures from diffusivegradients. We are unable to differentiate between these; as such, we report these ascumulative pressures contributing to nuclear compression. Nevertheless, previouswork has shown that compression stresses applied to cells such as throughcontractility and osmotic pressures applied through diffusive factors such as PEGprovoke identical physical and biochemical responses from cells, suggesting thattotal pressure is a metric mechanosensed by the cell and that compression from anysource was sufficient to regulate stem cell differentiation. This hiUsing these nuclear sensors, we find that stresses compressing nuclei are extremelycell cluster size dependent. Nuclei are more compressed in larger MCAs, suggestingthat cell density and MCA volume affect nuclei deformation and compression. As cellsproliferate and MCAs grow, the cells compress each other and their microenvironment;higher numbers of cells apply larger stress in the larger MCAs, therefore cells aremore deformed and compressed. Our observation is consistent with the work of Nia etal. where they observed an increased tumor size leads to elevated compressive stress.The nuclear stresses are also dependent on MCA geometry, with spherical cell clustersdisplaying very uniform stresses of approximately 3 MPa throughout the cluster. Instark contrast, elliptical MCAs have highly non-uniform nuclearstress-distributions, with nuclei along the outer major axis bearing roughly twicethe pressure (5–6 MPa) of cells in the interior, or at the distal tips of the MCA.Previous work has shown that the MCAs tend to grow in the regions of lowerstress, 41, sugDifferential pressures such as these may play a key role in mechanically regulatingcell growth and proliferation in a variety of contexts from development topathology, as nuclear deformation leads to changes in genes expression and cellfunction , making S1 TableDifferent PEG concentration w/v% in culture media column 1), create varyingosmotic pressure (column2). The osmotic pressure in column 2 corresponds toeach PEG concentration based on the literature [, create (TIFF)Click here for additional data file.S1 FigA) Volume of the nuclei measured after culturing cells under an osmoticpressure of 0.920 MPa for 21 days, without osmotic recovery, immediatelyexposed them to higher pressures. Nuclei that have been exposed to higherpressures show similar volumes as control. B) Volume of nuclei measuredafter 38 hours under each given pressure, and then 18 hours of recovery. Thepressure of 0.764 MPa corresponds to isotonic media (control). Nuclei thathave been exposed to higher pressures and then allowed to recover exhibitthe same volume as control, indicating that no permanent size alterationshave occurred during osmotic compression.(TIFF)Click here for additional data file.S2 FigA) Volumes measured with z-step sizes of 1μm or 5μm as a function of volumemeasured with 0.5μm step size. A line of x = y is added as a visual guide.B) Ratio of measured nuclear volumes as a function of volume and z-stepsize, illustrating no significant loss in precision of volume measurementsusing a 5 μm step size. Here we plot the nuclear volume measured with a 1μmstep (V1) divided by the volume measured with a 5μm z-step (V5), as afunction of the “precise” volume measured with a 0.5μm step. The volumetricratio is approximately 1 . This quantification demonstratesthat the volumetric measurements in z using a 5 micron step areaccurate.(TIFF)Click here for additional data file.S3 FigA) fluorescence image of nuclei in spherical MCAs, B) their measured volume,and C) their calculated pressure, of the nuclei relative to their positionin the MCA in a 3D projection. As the MCA size increases in the fluorescenceimages shown in panel A, the nuclei volumes decrease in the plots in panelB, however no spatial pattern of volumes is visible, nor is there a clearpattern in the distribution of pressures in panel C. These data suggest thatthe volumes and pressures throughout spherical MCAs are similar, and thatthere is not a gradient from center to edge.The perspectives in B) and C) are rotated to give a better visualisation ofthe 3D reconstruction of each MCA, and spatial dimensions are given inmicrons.(TIFF)Click here for additional data file.S4 FigA) fluorescence image of nuclei in elliptical MCAs, B) their measured volume,and C) their calculated pressure, of the nuclei relative to their positionin the MCA in a 3D projection. As the MCA size increases in the fluorescenceimages shown in panel A, the nuclei volumes decrease in the plots in panelB, and they appear more compressed near the edges of the elliptical MCAs.Their calculated pressures thus also suggested that nuclei at the peripheryof the MCAs are under higher stresses, as shown in panel C. These datasuggest that the volumes and pressures throughout spherical MCAs aredifferent, with a gradient of increasing stress from center to edge.(TIFF)Click here for additional data file.


To gain more insight into the dynamics of lymphocyte depletion and develop new predictors of clinical response to rituximab in rheumatoid arthritis (RA).RNA-based next-generation sequencing was used to analyse the B cell receptor (BCR) repertoire in peripheral blood and synovial tissue samples collected from 24 seropositive patients with RA treated with rituximab. Clonal expansion, mutation load and clonal overlap were assessed in samples collected before, at week 4 and at week 16 or 24 after treatment and correlated to the patients’ clinical response.After 4 weeks of rituximab-induced B cell depletion, the peripheral blood BCR repertoire of treated patients consisted of fewer, more dominant and more mutated BCR clones. No significant changes in the synovial tissue BCR repertoire were detected until week 16 post-treatment, when a reduced clonal overlap with baseline and an increased mutation load were observed. In patients who were non-responders at month 3 (n=5) using the European League Against Rheumatism response criteria, peripheral blood samples taken at week 4 after rituximab treatment showed more dominant clones compared with moderate responders (n=9) (median (IQR): 36 (27–52) vs 18 (16–26); p<0.01) and more clonal overlap with the baseline (median (IQR): 5% (2%–20%) vs 0% (0%–0%); p≤0.01).Significant changes in BCR clonality are observed in peripheral blood of patients 4 weeks after rituximab treatment, while changes in synovial tissue were observed at later time points. Incomplete depletion of the dominant baseline peripheral blood BCR repertoire in the first month of treatment might predict clinical non-response at 3 months. Rituximab induces deep depletion of the B cells, but up to 35% of treated patients with rheumatoid arthritis (RA) do not achieve clinical European League Against Rheumatism response  trial).Prediction of response to this treatment remains challenging.By analysing for the first time the B cell receptor (BCR) repertoire in peripheral blood and synovial tissue samples of patients with RA before and at different time points after treatment with rituximab, we provide new insight into the spatial and temporal effects of this drug on the B cell compartment.We observed major changes in BCR clonality at 4 weeks after treatment, while the same effects are observed in synovial tissue only at later time points.We found a correlation between incomplete depletion of the pretreatment BCR repertoire in peripheral blood after 1 month of treatment and worse treatment response evaluated at 3 months after treatment.The early identification of non-responder patients based on early BCR clonality changes would allow clinicians to timely switch patients who are unlikely to respond to rituximab treatment to other therapies.Rheumatoid arthritis (RA) is a chronic autoimmune disease that affects 1% of the population worldwide. The disease aetiology is not completely understood, and current treatments have limited efficacy.During the last decades, the introduction of biologicals constituted a major step forward in the treatment of RA. From a research perspective, the use of targeted therapies offers the opportunity to study the changes in the immune system while one cellular or molecular component is temporary depleted from the system. Rituximab, a chimeric monoclonal antibody directed against the B cell surface molecule CD20, is an example of such a targeted therapy. A single treatment with rituximab induces >98% depletion of the B cells in peripheral blood lasting for at least 4–5 months, but clinical response is achieved in only 50%–65% of treated patients.The exact mechanism by which depletion of CD20-bearing B cells leads to clinical improvement is still unclear.Studies have been limited so far to the use of phenotypic cell markers. The development of RNA-based next-generation sequencing allowed us for the first time to analyse the B cell receptor (BCR) repertoire in different body compartments before and at different time points after rituximab treatment. The results presented here provide new insights into the effects of rituximab in peripheral blood and synovial tissue over time, and may help to identify new biomarkers predictive of response to treatment that could be used to optimise treatment response in the future.Twenty-four patients with active, IgM-rheumatoid factor and/or anti-cyclic citrullinated peptides 2 test (CCP2)-positive RA10.1136/annrheumdis-2018-214898.supp1Supplementary dataPeripheral blood and synovial tissue samples were collected before treatment (baseline (FU0)), at week 4 (follow-up 1 (FU1)) and at week 16 (follow-up 2 (FU2)) after rituximab treatment, as described before.Starting material for RNA extraction consisted of 10 million PBMCs for peripheral blood samples and homogenised synovial tissue biopsies for synovial tissue samples. RNA extraction, complementary DNA synthesis and quantitative amplification of BCR heavy chain molecules were performed as previously described.Data are presented as mean and SD or median and IQR after D’Agostino and Pearson omnibus test for normality. Differences between groups were evaluated using Mann-Whitney U test for unpaired data, one-way analysis of variance or Kruskal-Wallis test of ranks data; p values less than 0.05 were considered statistically significant. Prism V.7 software  and RStudio (R V.3.3.2) were used to perform the analysis.Following rituximab infusion there was deep depletion of CD19+ B cells in peripheral blood.Next, we evaluated the effects of rituximab treatment on the BCR repertoire in both peripheral blood and synovial tissue. To this end we compared the number of BCR clones and the number of dominant BCR clones  in samples collected before and after therapy. The number of BCR clones in the peripheral blood repertoire was significantly decreased after rituximab treatment compared with pretreatment conditions (median (IQR): FU0: 1738 (1476–2095); FU1: 141 (105–206); FU2: 206 (131.0–379); p<0.0001), while the number of dominant BCR clones was significantly increased (median (IQR): FU0: 3 (2–9); FU1: 24 (17–33); FU2: 28 (13–45); p<0.0001) . In contThe phenotypic characterisation of the postdepletion B cell compartment using conventional flow cytometry is hindered by the small number of cells that can be detected, but high-sensitivity flow cytometry did allow detection of rituximab-residual B cells in peripheral blood.Compared with conventional cytometric techniques, BCR repertoire analysis offers the possibility to track individual BCR clones over time. Different biomarkers for response to rituximab have been proposed, but prediction of treatment response in the context of precision medicine remains a challenge.In this experimental medicine study, we analysed the BCR repertoire to provide more insight into the effects of rituximab treatment on the peripheral blood and synovial tissue B cell compartments.Our findings confirm and extend previous work showing that persistence of specific B cells is related to lack of clinical response to rituximab treatment in individual patients.In addition, our findings raise the intriguing question as to which mechanisms are involved in the persistence and recurrence of specific BCR clones in individual patients. Future work addressing this question may pave the way for novel therapeutic strategies aimed at deep B cell intervention, for instance through innovative combination therapies.Our study has several weaknesses. First, the number of patients here analysed is low due to the requirement for repeated synovial biopsies. As a consequence, the observed correlation between early changes in peripheral BCR clonality and treatment outcome needs additional exploration to establish its test characteristics in larger cohorts with standard clinical practice. Furthermore, given the limited number of retrieved reads using the Roche platform, we focused on the dominant clones (>0.5% of the repertoire) since the sequence depth has only minor effects on their quantification . It shouIn conclusion we have shown that in peripheral blood of RA patients, the postrituximab BCR repertoire is mainly composed of fewer but more dominant and more mutated BCR clones. In the synovial tissue, changes in BCR clonality are observed at later time points compared with peripheral blood, which could explain in part the relatively slow onset of clinical efficacy of rituximab treatment. Patients who do not respond to rituximab at 3 months show incomplete depletion of the baseline BCR clonal repertoire in peripheral blood within the first month of treatment, revealing a promising early predictive marker of clinical response.


We used a previously described computational approach to identify candidate multidomain proteins from Arabidopsis thaliana that contain multiple AC centers and show, using an Arabidopsis leucine-rich repeat containing protein  as example, biochemical evidence for multienzymatic activities. Importantly, all AC-containing fragments of this protein can complement the AC-deficient mutant cyaA in Escherichia coli, while structural modeling coupled with molecular docking simulations supports catalytic feasibility albeit to varying degrees as determined by the frequency of suitable substrate binding poses predicted for the AC sites. This statistic correlates well with the enzymatic assays, which implied that the greatly reduced AC activities is due to the absence of the negatively charged [DE] amino acids previously assigned to cation-, in particular Mg2+/Mn2+-binding roles in ACs.It is increasingly clear that plant genomes encode numerous complex multidomain proteins that harbor functional adenylyl cyclase (AC) centers. These AC containing proteins have well-documented roles in development and responses to the environment. However, it is only for a few of these proteins that we are beginning to understand the intramolecular mechanisms that govern their cellular and biological functions, as detailed characterizations are biochemically and structurally challenging given that these poorly conserved AC centers typically constitute only a small fraction (<10%) of complex plant proteins. Here, we offer fresh perspectives on their seemingly cryptic activities specifically showing evidence for the presence of multiple functional AC centers in a single protein and linking their catalytic strengths to the Mg Escherichia coli) to the complex multicellular Homo sapiens , and their generating enzymes, guanylyl cyclases (GCs) and adenylyl cyclases (ACs), play critical roles in many diverse biological processes of living organisms ranging from prokaryotes -binding [DE] amino acids.Despite the recent discoveries of plant ACs, the mechanism of actions, cellular regulations, and molecular dynamics of such catalytic centers remain largely unclear. These poorly conserved ACs retain only key residues of their catalytic centers that have been incorporated into larger multidomain proteins likely through divergent evolution  containing protein that harbors four distinct AC centers   compared to the AtLRRAC148−205 and AtLRRAC11210−1365 fragments. Again, it is tempting to speculate that this might be due to the absence of the negatively charged [DE] amino acids downstream of the AC catalytic centers of the AtLRRAC1234−390 and AtLRRAC1426−583 fragments  binding residues [DE] are known to coordinate the phosphates of ATP/ADP or GTP/GDP to the catalytic site of various enzymes including but not limited to kinases, ATP-/GTP-ases and phosphodiesterases. Divalent cation (Mg2+/Mn2+) binds to conserved [DE] amino acids in bacterial- and animal-soluble GCs typically at one to three residues downstream of the catalytic centers. Our AC and GC motifs were initially constructed by extracting key functional amino acids which are conserved at catalytic sites of canonical ACs and GCs across species, including the [DE] amino acids. Our motifs have since identified several ACs and GCs, many of which have been experimentally validated, but the role of [DE] in regulating their catalytic efficiency has never been assessed experimentally. Here, we showed for the first time that AC centers missing the [DE] residues have significantly reduced activities, and these preliminary data could explain past results, e.g., AtDGK4 by Dias et al.  seedlings using the RNeasy plant mini kit, in combination with DNase 1 treatment, as instructed by the manufacturer . Copy DNA (cDNA) sequence of AtLRRAC1 or At3g14460 was retrieved from The Arabidopsis Information Resource (TAIR) (https://www.arabidopsis.org) and checked for presence of multiple AC catalytic centers using the PROSITE database located within the Expert Protein Analysis System (ExPASy) proteomics server (https://www.expasy.org). cDNA synthesis from the total RNA and subsequent amplification of each of the identified multiple AC catalytic centers from the cDNA were simultaneously performed in the presence of a set of each of the respective sequence-specific primer pairs in AtLRRAC1 fusion expression constructs with C-terminus His purification tags. Expression, purification, and refolding processes of the recombinant AtLRRAC1 proteins were undertaken as is detailed elsewhere . The purified proteins were then used for in vitro enzymatic assays.Total RNA was extracted from 6-week-old in vitro by incubating 5 μg of the protein in 50 mM Tris–Cl buffer (pH 8.0), containing at, final concentration, 5 mM Mn2+, 1 mM ATP or 1 mM GTP, and 2 mM 3-isobutyl-1-methylxanthine, followed by measurement of the generated cAMP. Since Ca2+ has been shown to enhance the activity of ACs . The methods are detailed elsewhere , thi-1]  gene, was obtained from the E. coli Genetic Stock Centre  (accession no. 7200). The strain was prepared to be chemically competent followed by its transformation with the different pTrcHis2-TOPO:AtLRRAC1 fusion constructs (through heat shock at 42°C for 2 min). The transformed bacteria were then grown at 37°C for 18–40 h on MacConkey agar supplemented with 1% lactose, 15 μg/ml kanamycin, and 0.5 mM of the transgene inducer, isopropyl-β-d-thiogalactopyranoside    method Zhang, . The fuln = 3) to analysis of variance (ANOVA) . Where ANOVA revealed significant differences between treatments, means were separated by post hoc Student–Newman–Keuls multiple range test (P < 0.05).All data of immunoassay in this work was subjected in triplicates (The datasets generated for this study are available on request to the corresponding author.OR, CG, and AW conceived and designed the study. OR performed the functional characterizations. AW undertook the structural works. All authors wrote the manuscript and read and approved its final version.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.