The E3 ubiquitin-protein ligase UHRF1 promotes adipogenesis and limits fibrosis by suppressing GPNMB-mediated TGF-ß signaling.

The E3 ubiquitin-ligase UHRF1 is an epigenetic regulator coordinating DNA methylation and histone modifications. However, little is known about how it regulates adipogenesis or metabolism. In this study, we discovered that UHRF1 is a key regulatory factor for adipogenesis, and we identified the altered molecular pathways that UHRF1 targets. Using CRISPR/Cas9-based knockout strategies, we discovered the whole transcriptomic changes upon UHRF1 deletion. Bioinformatics analyses revealed that key adipogenesis regulators such PPAR-γ and C/EBP-α were suppressed, whereas TGF-ß signaling and fibrosis markers were upregulated in UHRF1-depleted differentiating adipocytes. Furthermore, UHRF1-depleted cells showed upregulated expression and secretion of TGF-ß1, as well as the glycoprotein GPNMB. Treating differentiating preadipocytes with recombinant GPNMB led to an increase in TGF-ß protein and secretion levels, which was accompanied by an increase in secretion of fibrosis markers such as MMP13 and a reduction in adipogenic conversion potential. Conversely, UHRF1 overexpression studies in human cells demonstrated downregulated levels of GPNMB and TGF-ß, and enhanced adipogenic potential. In conclusion, our data show that UHRF1 positively regulates 3T3-L1 adipogenesis and limits fibrosis by suppressing GPNMB and TGF-ß signaling cascade, highlighting the potential relevance of UHRF1 and its targets to the clinical management of obesity and linked metabolic disorders.

Repeated Exposure to High-THC Cannabis Smoke during Gestation Alters Sex Ratio, Behavior, and Amygdala Gene Expression of Sprague Dawley Rat Offspring.

Because of the legalization of Cannabis in many jurisdictions and the trend of increasing Δ9-tetrahydrocannabinol (THC) content in Cannabis products, an urgent need exists to understand the impact of Cannabis use during pregnancy on fetal neurodevelopment and behavior. To this end, we exposed female Sprague Dawley rats to Cannabis smoke daily from gestational day 6 to 20 or room air. Maternal reproductive parameters, offspring behavior, and gene expression in the offspring amygdala were assessed. Body temperature was decreased in dams following smoke exposure and more fecal boli were observed in the chambers before and after smoke exposure in dams exposed to smoke. Maternal weight gain, food intake, gestational length, litter number, and litter weight were not altered by exposure to Cannabis smoke. A significant increase in the male-to-female ratio was noted in the Cannabis-exposed litters. In adulthood, male and female Cannabis smoke-exposed offspring explored the inner zone of an open field significantly less than control offspring. Gestational Cannabis smoke exposure did not affect behavior on the elevated plus maze test or social interaction test in the offspring. Cannabis offspring were better at visual pairwise discrimination and reversal learning tasks conducted in touchscreen-equipped operant conditioning chambers. Analysis of gene expression in the adult amygdala using RNA sequencing revealed subtle changes in genes related to development, cellular function, and nervous system disease in a subset of the male offspring. These results demonstrate that repeated exposure to high-THC Cannabis smoke during gestation alters maternal physiological parameters, sex ratio, and anxiety-like behaviors in the adulthood offspring.

Signal Transducer and Activator of Transcription 3 (STAT3) Suppresses STAT1/Interferon Signaling Pathway and Inflammation in Senescent Preadipocytes.

Obesity promotes premature aging and dysfunction of white adipose tissue (WAT) through the accumulation of cellular senescence. The senescent cells burden in WAT has been linked to inflammation, insulin-resistance (IR), and type 2 diabetes (T2D). There is limited knowledge about molecular mechanisms that sustain inflammation in obese states. Here, we describe a robust and physiologically relevant in vitro system to trigger senescence in mouse 3T3-L1 preadipocytes. By employing transcriptomics analyses, we discovered up-regulation of key pro-inflammatory molecules and activation of interferon/signal transducer and activator of transcription (STAT)1/3 signaling in senescent preadipocytes, and expression of downstream targets was induced in epididymal WAT of obese mice, and obese human adipose tissue. To test the relevance of STAT1/3 signaling to preadipocyte senescence, we used Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR associated protein 9 (CRISPR/Cas9) technology to delete STAT1/3 and discovered that STAT1 promoted growth arrest and cooperated with cyclic Guanosine Monophosphate-Adenosine Monophosphate (GMP-AMP) synthase-stimulator of interferon genes (cGAS-STING) to drive the expression of interferon ß (IFNß), C-X-C motif chemokine ligand 10 (CXCL10), and interferon signaling-related genes. In contrast, we discovered that STAT3 was a negative regulator of STAT1/cGAS-STING signaling-it suppressed senescence and inflammation. These data provide insights into how STAT1/STAT3 signaling coordinates senescence and inflammation through functional interactions with the cGAS/STING pathway.

Increased MicroRNA Levels in Women With Polycystic Ovarian Syndrome but Without Insulin Resistance: A Pilot Prospective Study.

Background: Small noncoding microRNA (miRNA) have regulatory functions in polycystic ovary syndrome (PCOS) that differ to those in women without PCOS. However, little is known about miRNA expression in women with PCOS who are not insulin resistant (IR). Methods: Circulating miRNAs were measured using quantitative polymerase chain reaction (qPCR) in 24 non-obese BMI and age matched women with PCOS and 24 control women. A miRNA data set was used to determine miRNA levels. Results: Women with PCOS showed a higher free androgen index (FAI) and anti-mullerian hormone (AMH) but IR did not differ. Four miRNAs (miR-1260a, miR-18b-5p, miR-424-5p, and miR let-7b-3p) differed between control and PCOS women that passed the false discovery rate (FDR) out of a total of 177 circulating miRNAs that were detected. MiRNA let-7b-3p correlated with AMH in PCOS (p < 0.05). When the groups were combined, miR-1260a correlated with FAI and let-7b-3p correlated with body mass index (BMI) (p < 0.05). There was no correlation to androgen levels. Ingenuity pathway analysis showed that nine of the top 10 miRNAs reported were associated with inflammatory pathways. Conclusion: When IR did not differ between PCOS and control women, only four miRNA differed significantly suggesting that IR may be a driver for many of the miRNA changes reported. Let-7b-3p was related to AMH in PCOS, and to BMI as a group, whilst miR-1260a correlated with FAI. Androgen levels, however, had no effect upon circulating miRNA profiles. The expressed miRNAs were associated with the inflammatory pathway involving TNF and IL6.

Corrigendum: microRNA Expression in Women With and Without Polycystic Ovarian Syndrome Matched for Body Mass Index.

[This corrects the article DOI: 10.3389/fendo.2020.00206.].

Long non-coding RNA expression in non-obese women with polycystic ovary syndrome and weight-matched controls.

RESEARCH QUESTION: Long non-coding RNA (lncRNA) do not show protein translation but do have gene regulatory functions in several disease states. Studies have shown that lncRNA differ in overweight women with polycystic ovary syndrome (PCOS), increased insulin resistance and hyperandrogenaemia. The objective of this study was to determine the lncRNA in serum in age- and weight-matched non-obese women with and without PCOS. METHODS: In this prospective pilot cohort study, lncRNA were measured in serum in 13 non-obese women with PCOS and 10 control women undergoing IVF. RESULTS: There was no difference between groups in terms of age, body mass index or insulin resistance. Women with PCOS showed a higher free androgen index (FAI; P = 0.03) and anti-Müllerian hormone (AMH) concentration (P = 0.001). A total of 29 lncRNA (P ≤ 0.05) differed between PCOS groups. lncRNA AC095350.1 correlated with age (r = 0.79, P = 0.04), but no correlation was seen between the significantly different lncRNA and FAI or AMH values. Functional pathway assessment using the Ingenuity Pathway Assessment tool showed no relationships for the lncRNA. CONCLUSION: lncRNA in serum differed between non-obese women with PCOS and the control group, and the pattern of expression differed from that reported in obese women with PCOS from the same ethnic population; however, it but did not correlate with androgen or insulin resistance.

Metabolic Signatures of Tumor Responses to Doxorubicin Elucidated by Metabolic Profiling in Ovo.

BACKGROUND: Dysregulated cancer metabolism is associated with acquired resistance to chemotherapeutic treatment and contributes to the activation of cancer survival mechanisms. However, which metabolic pathways are activated following treatment often remains elusive. The combination of chicken embryo tumor models (in ovo) with metabolomics phenotyping could offer a robust platform for drug testing. Here, we assess the potential of this approach in the treatment of an in ovo triple negative breast cancer with doxorubicin. METHODS: MB-MDA-231 cells were grafted in ovo. The resulting tumors were then treated with doxorubicin or dimethyl sulfoxide (DMSO) for six days. Tumors were collected and analyzed using a global untargeted metabolomics and comprehensive lipidomics. RESULTS: We observed a significant suppression of tumor growth in the doxorubicin treated group. The metabolic profiles of doxorubicin and DMSO-treated tumors were clearly separated in a principle component analysis. Inhibition of glycolysis, nucleotide synthesis, and glycerophospholipid metabolism appear to be triggered by doxorubicin treatment, which could explain the observed suppressed tumor growth. In addition, metabolic cancer survival mechanisms could be supported by an acceleration of antioxidative pathways. CONCLUSIONS: Metabolomics in combination with in ovo tumor models provide a robust platform for drug testing to reveal tumor specific treatment targets such as the antioxidative tumor capacity.

microRNA Expression in Women With and Without Polycystic Ovarian Syndrome Matched for Body Mass Index.

Background: Despite several authors who have hypothesized that alterations of small noncoding RNAs (miR) are implicated in the etiopathogenesis of polycystic ovarian syndrome (PCOS), contrasting findings have been reported so far. Discrepancies in body mass index (BMI) levels may account for these differences; therefore, the aim of the present study was to determine whether miR differed in serum samples collected from age- and BMI-matched control and PCOS women. Methods: In a cross-sectional study, miR were measured using quantitative polymerase chain reaction in 29 women with anovulatory PCOS women and 29 control women who were in the follicular phase of their menstrual cycle, from the local biobank. Results: One hundred seventy-six miR were detected, of which 15 miR passed the false discovery rate (FDR; p < 0.05) that differed between PCOS and control women. There was no association of the top 9 miR (p < 0.02) (miR-486-5p, miR-24-3p, miR-19b-3p, miR-22-3p, miR-19a-3p, miR-339-5p, miR-185-5p, miR-101-3p, miR-let-7i-5p) with BMI, androgen levels, insulin resistance, or antimullerian hormone (AMH) in either PCOS or normal women. Ingenuity pathway assessment showed the pathways were interrelated for abnormalities of the reproductive system. Conclusion: When the confounding influence of weight was accounted for, miR levels differed between anovulatory PCOS women and control women in the follicular phase of the menstrual cycle. Interestingly, the differing miR were associated with the pathways of reproductive abnormalities but did not associate with AMH or metabolic parameters.

Expression of microRNA in follicular fluid in women with and without PCOS.

Several studies have shown the expression of small non-coding microRNA (miRNA) changes in PCOS and their expression in follicular fluid has been described, though the number of studies remains small. In this prospective cohort study, miRNA were measured using quantitative polymerase chain reaction (qPCR) in 29 weight and aged matched anovulatory women with PCOS and 30 women without from follicular fluid taken at the time of oocyte retrieval who were undergoing in vitro fertilization (IVF); miRNA levels were determined from a miRNA data set. 176 miRNA were detected, of which 29 differed significantly between normal women and PCOS women. Of these, the top 7 (p < 0.015) were miR-381-3p, miR-199b-5p, miR-93-3p, miR-361-3p, miR-127-3p, miR-382-5p, miR-425-3p. In PCOS, miR-382-5p correlated with age and free androgen index (FAI), miR-199b-5p correlated with anti-mullerian hormone (AMH) and miR-93-3p correlated with C-reactive protein (CRP). In normal controls, miR-127-3p, miR-382-5p and miR-425-3p correlated with the fertilisation rate; miR-127-3p correlated with insulin resistance and miR-381-3p correlated with FAI. Ingenuity pathway assessment revealed that 12 of the significantly altered miRNA related to reproductive pathways, 12 miRNA related to the inflammatory disease pathway and 6 were implicated in benign pelvic disease. MiRNAs differed in the follicular fluid between PCOS and normal control women, correlating with age, FAI, inflammation and AMH in PCOS, and with BMI, fertilization rate (3 miRNA), insulin resistance, FAI and inflammation in control women, according to Ingenuity Pathway Analysis.

Alterations in long noncoding RNAs in women with and without polycystic ovarian syndrome.

Long noncoding RNAs (lncRNAs) are RNA transcripts over 200 nucleotides long that are not translated into protein; however, there is increasing evidence of their regulatory functions. To date, there are few studies measuring lncRNA in control women or women with polycystic ovary syndrome (PCOS). OBJECTIVE: To determine lncRNA differences between PCOS and control women. DESIGN: Cross sectional study. PATIENTS: Twenty four anovulatory women with all three diagnostic features of PCOS compared to 24 control women in the follicular phase of their menstrual cycle from a PCOS biobank. RESULTS: Women with PCOS were age and weight matched compared to the control women but were significantly insulin resistant and hyperandrogenemic (P < .01). Eight lncRNA (P < .05) were detected that differed between PCOS and control women, but only MIRLET7BHG correlated with body mass index (r = .66, P < .05). No lncRNA correlated with antimullerian hormone (AMH) levels, insulin resistance (HOMA-IR) or the free androgen index (FAI). Ingenuity pathway assessment (IPA) did not identify any functional pathways for the lncRNAs. CONCLUSION: LncRNAs differ between anovulatory PCOS and control women in the follicular phase of the menstrual cycle. It is unclear if this is due to inherent differences between PCOS and control women or due to changes in lncRNA that are menstrual cycle dependent. However, their IPA did not identify linked pathways, likely because few functions are as yet assigned to these lncRNAs.

A Systems-level Characterization of the Differentiation of Human Embryonic Stem Cells into Mesenchymal Stem Cells.

Mesenchymal stem/stromal cells (MSCs) are self-renewing multipotent cells with regenerative, secretory and immunomodulatory capabilities that are beneficial for the treatment of various diseases. To avoid the issues that come with using tissue-derived MSCs in therapy, MSCs may be generated by the differentiation of human embryonic stems cells (hESCs) in culture. However, the changes that occur during the differentiation process have not been comprehensively characterized. Here, we combined transcriptome, proteome and phosphoproteome profiling to perform an in-depth, multi-omics study of the hESCs-to-MSCs differentiation process. Based on RNA-to-protein correlation, we determined a set of high confidence genes that are important to differentiation. Among the earliest and strongest induced proteins with extensive differential phosphorylation was AHNAK, which we hypothesized to be a defining factor in MSC biology. We observed two distinct expression waves of developmental HOX genes and an AGO2-to-AGO3 switch in gene silencing. Exploring the kinetic of noncoding ORFs during differentiation, we mapped new functions to well annotated long noncoding RNAs (CARMN, MALAT, NEAT1, LINC00152) as well as new candidates which we identified to be important to the differentiation process. Phosphoproteome analysis revealed ESC and MSC-specific phosphorylation motifs with PAK2 and RAF1 as top predicted upstream kinases in MSCs. Our data represent a rich systems-level resource on ESC-to-MSC differentiation that will be useful for the study of stem cell biology.

A comprehensive metabolomic data set of date palm fruit.

This article provides detailed information on the phenotypes and the metabolic profiles of 196 date fruits from 123 unique date fruit varieties. These date fruits are extensively diverse in their country of origin, variety and post harvesting conditions. We used a non-targeted mass-spectrometry based metabolomics approach to metabolically characterize date fruits, and measured 427 metabolites from a wide range of metabolic pathways. The metabolomics data for all the date fruit samples are available at the NIH Common Fund's Data Repository and Coordinating Center (supported by NIH grant, U01-DK097430) website, http://www.metabolomicsworkbench.org), under Metabolomics Workbench StudyID: ST000867. The data are directly accessible at http://www.metabolomicsworkbench.org/data/DRCCMetadata.php?Mode=Study&StudyID=ST000867&StudyType=MS&ResultType=1.

Single nucleotide variant counts computed from RNA sequencing and cellular traffic into human kidney allografts.

Advances in bioinformatics allow identification of single nucleotide polymorphisms (variants) from RNA sequence data. In an allograft biopsy, 2 genomes contribute to the RNA pool, 1 from the donor organ and the other from the infiltrating recipient's cells. We hypothesize that imbalances in genetic variants of RNA sequence data of kidney allograft biopsies provide an objective measure of cellular infiltration of the allograft. We performed mRNA sequencing of 40 kidney allograft biopsies, selected to represent a comprehensive range of diagnostic categories. We analyzed the sequencing reads of these biopsies and of 462 lymphoblastoid cell lines from the 1000 Genomes Project, for RNA variants. The ratio of heterozygous to nonreference genome homozygous variants (Het/Hom ratio) on all autosomes was determined for each sample, and the estimation of stromal and immune cells in malignant tumors using expression data (ESTIMATE) score was computed as a complementary estimate of the degree of cellular infiltration into biopsies. The Het/Hom ratios (P = .02) and the ESTIMATE scores (P < .001) were associated with the biopsy diagnosis. Both measures correlated significantly (r = .67, P < .0001), even though the Het/Hom ratio is based on mRNA sequence variation, while the ESTIMATE score uses mRNA expression. Het/Hom ratio and the ESTIMATE score may offer unbiased and quantitative parameters for characterizing cellular traffic into human kidney allografts.

Complementarity of SOMAscan to LC-MS/MS and RNA-seq for quantitative profiling of human embryonic and mesenchymal stem cells.

Dynamic range limitations are challenging to proteomics, particularly in clinical samples. Affinity proteomics partially overcomes this, yet suffers from dependence on reagent quality. SOMAscan, an aptamer-based platform for over 1000 proteins, avoids that issue using nucleic acid binders. Targets include low expressed proteins not easily accessible by other approaches. Here we report on the potential of SOMAscan for the study of differently sourced mesenchymal stem cells (MSC) in comparison to LC-MS/MS and RNA sequencing. While targeting fewer analytes, SOMAscan displays high precision and dynamic range coverage, allowing quantification of proteins not measured by the other platforms. Expression between cell types (ESC and MSC) was compared across techniques and uncovered the expected large differences. Sourcing was investigated by comparing subtypes: bone marrow-derived, standard in clinical studies, and ESC-derived MSC, thought to hold similar potential but devoid of inter-donor variability and proliferating faster in vitro. We confirmed subtype-equivalency, as well as vesicle and extracellular matrix related processes in MSC. In contrast, the proliferative nature of ESC was captured less by SOMAscan, where nuclear proteins are underrepresented. The complementary of SOMAscan allowed the comprehensive exploration of CD markers and signaling molecules, not readily accessible otherwise and offering unprecedented potential in subtype characterization. SIGNIFICANCE: Mesenchymal stem cells (MSC) represent promising stem cell-derived therapeutics as indicated by their application in >500 clinical trials currently registered with the NIH. Tissue-derived MSC require invasive harvesting and imply donor-to-donor differences, to which embryonic stem cell (ESC)-derived MSC may provide an alternative and thus warrant thorough characterization. In continuation of our previous study where we compared in depth embryonic stem cells (ESC) and MSC from two sources (bone marrow and ESC-derived), we included the aptamer-based SOMAscan assay, complementing LC-MS/MS and RNA-seq data. Furthermore, SOMAscan, a targeted proteomics platform developed for analyzing clinical samples, has been benchmarked against established analytical platforms (LC-MS/MS and RNA-seq) using stem cell comparisons as a model.

Comprehensive transcriptomic and proteomic characterization of human mesenchymal stem cells reveals source specific cellular markers.

Mesenchymal stem cells (MSC) are multipotent cells with great potential in therapy, reflected by more than 500 MSC-based clinical trials registered with the NIH. MSC are derived from multiple tissues but require invasive harvesting and imply donor-to-donor variability. Embryonic stem cell-derived MSC (ESC-MSC) may provide an alternative, but how similar they are to ex vivo MSC is unknown. Here we performed an in depth characterization of human ESC-MSC, comparing them to human bone marrow-derived MSC (BM-MSC) as well as human embryonic stem cells (hESC) by transcriptomics (RNA-seq) and quantitative proteomics (nanoLC-MS/MS using SILAC). Data integration highlighted and validated a central role of vesicle-mediated transport and exosomes in MSC biology and also demonstrated, through enrichment analysis, their versatility and broad application potential. Particular emphasis was placed on comparing profiles between ESC-MSC and BM-MSC and assessing their equivalency. Data presented here shows that differences between ESC-MSC and BM-MSC are similar in magnitude to those reported for MSC of different origin and the former may thus represent an alternative source for therapeutic applications. Finally, we report an unprecedented coverage of MSC CD markers, as well as membrane associated proteins which may benefit immunofluorescence-based applications and contribute to a refined molecular description of MSC.

MetaRNA-Seq: An Interactive Tool to Browse and Annotate Metadata from RNA-Seq Studies.

The number of RNA-Seq studies has grown in recent years. The design of RNA-Seq studies varies from very simple (e.g., two-condition case-control) to very complicated (e.g., time series involving multiple samples at each time point with separate drug treatments). Most of these publically available RNA-Seq studies are deposited in NCBI databases, but their metadata are scattered throughout four different databases: Sequence Read Archive (SRA), Biosample, Bioprojects, and Gene Expression Omnibus (GEO). Although the NCBI web interface is able to provide all of the metadata information, it often requires significant effort to retrieve study- or project-level information by traversing through multiple hyperlinks and going to another page. Moreover, project- and study-level metadata lack manual or automatic curation by categories, such as disease type, time series, case-control, or replicate type, which are vital to comprehending any RNA-Seq study. Here we describe "MetaRNA-Seq," a new tool for interactively browsing, searching, and annotating RNA-Seq metadata with the capability of semiautomatic curation at the study level.

Accurate detection of subclonal single nucleotide variants in whole genome amplified and pooled cancer samples using HaloPlex target enrichment.

BACKGROUND: Target enrichment and resequencing is a widely used approach for identification of cancer genes and genetic variants associated with diseases. Although cost effective compared to whole genome sequencing, analysis of many samples constitutes a significant cost, which could be reduced by pooling samples before capture. Another limitation to the number of cancer samples that can be analyzed is often the amount of available tumor DNA. We evaluated the performance of whole genome amplified DNA and the power to detect subclonal somatic single nucleotide variants in non-indexed pools of cancer samples using the HaloPlex technology for target enrichment and next generation sequencing. RESULTS: We captured a set of 1528 putative somatic single nucleotide variants and germline SNPs, which were identified by whole genome sequencing, with the HaloPlex technology and sequenced to a depth of 792-1752. We found that the allele fractions of the analyzed variants are well preserved during whole genome amplification and that capture specificity or variant calling is not affected. We detected a large majority of the known single nucleotide variants present uniquely in one sample with allele fractions as low as 0.1 in non-indexed pools of up to ten samples. We also identified and experimentally validated six novel variants in the samples included in the pools. CONCLUSION: Our work demonstrates that whole genome amplified DNA can be used for target enrichment equally well as genomic DNA and that accurate variant detection is possible in non-indexed pools of cancer samples. These findings show that analysis of a large number of samples is feasible at low cost, even when only small amounts of DNA is available, and thereby significantly increases the chances of indentifying recurrent mutations in cancer samples.