Clinical and molecular spectrum of v-lesion.

Isolated v-lesion presents diagnostic stratification and clinical challenges. We characterized allograft outcomes for this entity based on posttransplant time (early: ≤1 month vs late: >1 month) and compared its molecular phenotype with other v+ rejection forms. Using the NanoString B-HOT panel, we analyzed 92 archival formalin-fixed paraffin-embedded tissue kidney biopsies from 3 centers: isolated v-lesion (n = 23), antibody-mediated rejection (ABMR) v+ (n = 26), T cell-mediated rejection (TCMR) v+ (n = 10), mixed rejection v+ (n = 23), and normal tissue (n = 10). Six gene sets (ABMR, DSAST, ENDAT, TCMR, early/acute injury, late injury) were assessed. Early isolated v-lesions had the poorest 1-year death-censored graft survival compared with late isolated v-lesions or other rejections (P = .034). Gene set analysis showed lower TCMR-related gene expression in isolated v+ groups than TCMR and mixed rejection (P < .001). Both early- and late isolated v-lesions had lower ABMR-related gene expression than ABMR, mixed rejection, and TCMR (P ≤ .022). Late isolated v-lesions showed reduced DSAST and ENDAT gene expression versus ABMR (P ≤ .046) and decreased early/acute injury gene expression than early isolated v+, ABMR, TCMR, and mixed rejection (P ≤ .026). In conclusion, isolated v-lesions exhibit distinct gene expression patterns versus other rejection v+ forms. Early isolated v+ is associated with poorer prognosis and increased early/acute injury gene expression than late isolated v+, suggesting distinct etiologies.

A case of hepatitis-associated aplastic anaemia following living-donor liver transplantation for fulminant hepatitis showing loss of heterozygosity in the 6p chromosome in the affected liver.

The mechanisms underlying hepatitis-associated aplastic anaemia (HAAA) that occurs several weeks after the development of acute hepatitis are unknown. A 20-year-old male developed HAAA following living-donor liver transplantation for fulminant hepatitis. The patient's leucocytes lacked HLA-class I due to loss of heterozygosity in the short arm of chromosome 6p (6pLOH). Interestingly, the patient's liver cells resected during the transplantation also exhibited 6pLOH that affected the same HLA haplotype as the leucocytes, suggesting that CD8+ T cells recognizing antigens presented by specific HLA molecules on liver cells may have attacked the haematopoietic stem cells of the patient, leading to the HAAA development.

Prediction model for pheochromocytoma/paraganglioma using nCounter assay.

BACKGROUND: World Health Organization defined pheochromocytomas/paragangliomas (PPGL) as malignant tumors in 2017 because the existing classification system could not reflect locally aggressive behavior sufficiently. However, predicting the likelihood of metastasis remains a crucial part of the treatment strategy. METHODS: From one tertiary care hospital and one secondary hospital, 97 PPGL cases were selected. Medical records of PPGL cases with the presence of formalin-fixed and paraffin-embedded (FFPE) tissue of primary lesion were reviewed. For FFPE tissues, a nCounter assay was conducted to determine differently expressed genes between metastatic and non-metastatic PPGL groups. Performances of prediction models for the likelihood of metastasis were calculated. RESULTS: Of a total of 97 PPGL cases, 39, 20, and 38 were classified as benign, malignant, and validation, respectively. In the nCounter assay, CDK1, TYMS, and TOP2A genes showed significant differences in expression. Tumor size was positively correlated with CDK1 expression level. The Lasso regression model showed supreme performance of sensitivity 91.7% and specificity 95.5% when those significant factors were considered. CONCLUSION: Machine learning of multi-modal classifiers can be used to create a prediction model for metastasis of PPGL with high sensitivity and specificity using nCounter assay. Moreover, CDK1 inhibitors could be considered for developing drug treatment.

Targeted Proteomics Reveals Quantitative Differences in Low-Abundance Glycosyltransferases of Patients with Congenital Disorders of Glycosylation.

Protein glycosylation is an essential post-translational modification in all domains of life. Its impairment in humans can result in severe diseases named congenital disorders of glycosylation (CDGs). Most of the glycosyltransferases (GTs) responsible for proper glycosylation are polytopic membrane proteins that represent challenging targets in proteomics. We established a multiple reaction monitoring (MRM) assay to comprehensively quantify GTs involved in the processes of N-glycosylation and O- and C-mannosylation in the endoplasmic reticulum. High robustness was achieved by using an enriched membrane protein fraction of isotopically labeled HEK 293T cells as an internal protein standard. The analysis of primary skin fibroblasts from eight CDG type I patients with impaired ALG1, ALG2, and ALG11 genes, respectively, revealed a substantial reduction in the corresponding protein levels. The abundance of the other GTs, however, remained unchanged at the transcript and protein levels, indicating that there is no fail-safe mechanism for the early steps of glycosylation in the endoplasmic reticulum. The established MRM assay was shared with the scientific community via the commonly used open source Skyline software environment, including Skyline Batch for automated data analysis. We demonstrate that another research group could easily reproduce all analysis steps, even while using different LC-MS hardware.

Plasma Circulating mRNA Profile for the Non-Invasive Diagnosis of Colorectal Cancer Using NanoString Technologies.

Colorectal cancer (CRC) is one of the most prevalent cancers and the second leading cause of cancer deaths in developed countries. Early CRC may have no symptoms and symptoms usually appear with more advanced diseases. Regular screening can identify people who are at increased risk of CRC in order to offer earlier treatment. A cost-effective non-invasive platform for the screening and monitoring of CRC patients allows early detection and appropriate treatment of the disease, and the timely application of adjuvant therapy after surgical operation is needed. In this study, a cohort of 71 plasma samples that include 48 colonoscopy- and histopathology-confirmed CRC patients with TNM stages I to IV were recruited between 2017 and 2019. Plasma mRNA profiling was performed in CRC patients using NanoString nCounter. Normalized data were analyzed using a Mann-Whitney U test to determine statistically significant differences between samples from CRC patients and healthy subjects. A multiple-group comparison of clinical phenotypes was performed using the Kruskal-Wallis H test for statistically significant differences between multiple groups. Among the 27 selected circulating mRNA markers, all of them were found to be overexpressed (gene expression fold change > 2) in the plasma of patients from two or more CRC stages. In conclusion, NanoString-based targeted plasma CRC-associated mRNAs circulating the marker panel that can significantly distinguish CRC patients from a healthy population were developed for the non-invasive diagnosis of CRC using peripheral blood samples.

NanoString in the screening of genetic abnormalities associated with thyroid cancer.

In the setting of cancer pathology, molecular characterization of tumors providing diagnostic and predictive information is acquiring more and more relevance. Moreover, the advent of innovative technologies continuously improves the knowledge of the molecular landscape of tumors and strengthens the links between clinics, tumor pathology and molecular features. In the clinical management of patients with thyroid nodules and thyroid tumors, the aid of molecular testing is encouraged but still not strongly recommended by current guidelines. Also for this reason this field of study is attracting much interest. The nCounter system is a relatively new technology based on a direct hybridization of fluorescent probes to specific nucleic acid targets, followed by digital measurement of signals; the reaction is highly multiplexable and results are robust and reproducible. This review reports and discusses the available data related to the application of this specific technique to thyroid nodules and thyroid tumors samples. The available data indicate that nCounter system represents a solid approach for the research of relevant diagnostic and prognostic biomarkers in thyroid pathology.

An approach for normalization and quality control for NanoString RNA expression data.

The NanoString RNA counting assay for formalin-fixed paraffin embedded samples is unique in its sensitivity, technical reproducibility and robustness for analysis of clinical and archival samples. While commercial normalization methods are provided by NanoString, they are not optimal for all settings, particularly when samples exhibit strong technical or biological variation or where housekeeping genes have variable performance across the cohort. Here, we develop and evaluate a more comprehensive normalization procedure for NanoString data with steps for quality control, selection of housekeeping targets, normalization and iterative data visualization and biological validation. The approach was evaluated using a large cohort ($N=\kern0.5em 1649$) from the Carolina Breast Cancer Study, two cohorts of moderate sample size ($N=359$ and$130$) and a small published dataset ($N=12$). The iterative process developed here eliminates technical variation (e.g. from different study phases or sites) more reliably than the three other methods, including NanoString's commercial package, without diminishing biological variation, especially in long-term longitudinal multiphase or multisite cohorts. We also find that probe sets validated for nCounter, such as the PAM50 gene signature, are impervious to batch issues. This work emphasizes that systematic quality control, normalization and visualization of NanoString nCounter data are an imperative component of study design that influences results in downstream analyses.

Multiplexed mRNA analysis of brain-derived extracellular vesicles upon experimental stroke in mice reveals increased mRNA content with potential relevance to inflammation and recovery processes.

Extracellular vesicles (EVs) are lipid bilayer-enclosed structures that represent newly discovered means for cell-to-cell communication as well as promising disease biomarkers and therapeutic tools. Apart from proteins, lipids, and metabolites, EVs can deliver genetic information such as mRNA, eliciting a response in the recipient cells. In the present study, we have analyzed the mRNA content of brain-derived EVs (BDEVs) isolated 72 h after experimental stroke in mice and compared them to controls (shams) using nCounter® Nanostring panels, with or without prior RNA isolation. We found that both panels show similar results when comparing upregulated mRNAs in stroke. Notably, the highest upregulated mRNAs were related to processes of stress and immune system responses, but also to anatomical structure development, cell differentiation, and extracellular matrix organization, thus indicating that regenerative mechanisms already take place at this time-point. The five top overrepresented mRNAs in stroke mice were confirmed by RT-qPCR and, interestingly, found to be full-length. We could reveal that the majority of the mRNA cargo in BDEVs was of microglial origin and predominantly present in small BDEVs (≤ 200 nm in diameter). However, the EV population with the highest increase in the total BDEVs pool at 72 h after stroke was of oligodendrocytic origin. Our study shows that nCounter® panels are a good tool to study mRNA content in tissue-derived EVs as they can be carried out even without previous mRNA isolation, and that the mRNA cargo of BDEVs indicates a possible participation in inflammatory but also recovery processes after stroke.

Fibrosis-Related Gene Profiling in Liver Biopsies of PiZZ α1-Antitrypsin Children with Different Clinical Courses.

PiZZ (Glu342Lys) α1-antitrypsin deficiency (AATD) is characterized by intrahepatic AAT polymerization and is a risk factor for liver disease development in children. The majority of PiZZ children are disease free, hence this mutation alone is not sufficient to cause the disease. We investigated Z-AAT polymers and the expression of fibrosis-related genes in liver tissues of PiZZ children with different clinical courses. Liver biopsies obtained during 1979-2010 at the Department of Paediatrics, Karolinska University Hospital, Sweden, were subjected to histological re-evaluation, immunohistochemistry and NanoString-based transcriptome profiling using a panel of 760 fibrosis plus 8 bile acid-related genes. Subjects were divided into three groups based on clinical outcomes: NCH (neonatal cholestasis, favourable outcome, n = 5), NCC (neonatal cholestasis, early cirrhosis and liver transplantation, n = 4), and NNCH (no neonatal cholestasis, favourable outcome, n = 5, six biopsies). Hepatocytes containing Z-AAT polymers were abundant in all groups whereas NCC showed higher expression of genes related to liver fibrosis/cirrhosis and lower expression of genes related to lipid, aldehyde/ketone, and bile acid metabolism. Z-AAT accumulation per se cannot explain the clinical outcomes of PiZZ children; however, changes in the expression of specific genes and pathways involved in lipid, fatty acid, and steroid metabolism appear to reflect the degree of liver injury.

Profiling of circRNAs using an enzyme-free digital counting method.

Circular RNAs (circRNAs) have recently gained substantial attention as potential biomarkers in several human diseases, most prominently in cancer. However, the detection and quantification of circRNA biomarkers pose specific challenges owing to their circular nature. In particular, the use of enzymes, such as reverse transcriptases, may lead to impaired quantification, poor interlaboratory reproducibility and even false-positive results. Therefore, the development of methods for accurate quantification of circRNA biomarkers is a high priority. An enzyme-free and digital quantification method, named NanoString nCounter, was recently adapted for circRNA detection. In this review, I describe the advantages of using this technology for circRNA quantification as well as methodological considerations, potential pitfalls and disadvantages.

Sex-biased expression of the TLR7 gene in severe COVID-19 patients: Insights from transcriptomics and epigenomics.

There is abundant epidemiological data indicating that the incidence of severe cases of coronavirus disease (COVID-19) is significantly higher in males than females worldwide. Moreover, genetic variation at the X-chromosome linked TLR7 gene has been associated with COVID-19 severity. It has been suggested that the sex-biased incidence of COVID-19 might be related to the fact that TLR7 escapes X-chromosome inactivation during early embryogenesis in females, thus encoding a doble dose of its gene product compared to males. We analyzed TLR7 expression in two acute phase cohorts of COVID-19 patients that used two different technological platforms, one of them in a multi-tissue context including saliva, nasal, and blood samples, and a third cohort that included different post-infection timepoints of long-COVID-19 patients. We additionally explored methylation patterns of TLR7 using epigenomic data from an independent cohort of COVID-19 patients stratified by severity and sex. In line with genome-wide association studies, we provide supportive evidence indicating that TLR7 has altered CpG methylation patterns and it is consistently downregulated in males compared to females in the most severe cases of COVID-19.

Application of the NanoString nCounter System as an Alternative Method to Investigate Molecular Mechanisms Involved in Host Plant Responses to Plasmodiophora brassicae.

Clubroot, caused by the soilborne pathogen Plasmodiophora brassicae, is an important disease of canola (Brassica napus) and other crucifers. The recent application of RNA sequencing (RNA-seq) technologies to study P. brassicae−host interactions has generated large amounts of gene expression data, improving knowledge of the molecular mechanisms of pathogenesis and host resistance. Quantitative PCR (qPCR) analysis has been widely applied to examine the expression of a limited number of genes and to validate the results of RNA-seq studies, but may not be ideal for analyzing larger suites of target genes or increased sample numbers. Moreover, the need for intermediate steps such as cDNA synthesis may introduce variability that could affect the accuracy of the data generated by qPCR. Here, we report the validation of gene expression data from a previous RNA-seq study of clubroot using the NanoString nCounter System, which achieves efficient gene expression quantification in a fast and simple manner. We first confirm the robustness of the NanoString system by comparing the results with those generated by qPCR and RNA-seq and then discuss the importance of some candidate genes for resistance or susceptibility to P. brassicae in the host. The results show that the expression of genes measured using NanoString have a high correlation with the values obtained using the other two technologies, with R > 0.90 and p < 0.01, and the same expression patterns for most genes. The three methods (qPCR, RNA-seq, and NanoString) were also compared in terms of laboratory procedures, time, and cost. We propose that the NanoString nCounter System is a robust, sensitive, highly reproducible, and simple technology for gene expression analysis. NanoString could become a common alternative to qPCR to validate RNA-seq data or to create panels of genes for use as markers of resistance/susceptibility when plants are challenged with different P. brassicae pathotypes.

Multiplex Detection of Clinically Relevant Mutations in Liquid Biopsies of Cancer Patients Using a Hybridization-Based Platform.

BACKGROUND: With the advent of precision oncology, liquid biopsies are quickly gaining acceptance in the clinical setting. However, in some cases, the amount of DNA isolated is insufficient for Next-Generation Sequencing (NGS) analysis. The nCounter platform could be an alternative, but it has never been explored for detection of clinically relevant alterations in fluids. METHODS: Circulating-free DNA (cfDNA) was purified from blood, cerebrospinal fluid, and ascites of patients with cancer and analyzed with the nCounter 3 D Single Nucleotide Variant (SNV) Solid Tumor Panel, which allows for detection of 97 driver mutations in 24 genes. RESULTS: Validation experiments revealed that the nCounter SNV panel could detect mutations at allelic fractions of 0.02-2% in samples with ≥5 pg mutant DNA/µL. In a retrospective analysis of 70 cfDNAs from patients with cancer, the panel successfully detected EGFR, KRAS, BRAF, PIK3CA, and NRAS mutations when compared with previous genotyping in the same liquid biopsies and paired tumor tissues [Cohen kappa of 0.96 (CI = 0.92-1.00) and 0.90 (CI = 0.74-1.00), respectively]. In a prospective study including 91 liquid biopsies from patients with different malignancies, 90 yielded valid results with the SNV panel and mutations in EGFR, KRAS, BRAF, PIK3CA, TP53, NFE2L2, CTNNB1, ALK, FBXW7, and PTEN were found. Finally, serial liquid biopsies from a patient with NSCLC revealed that the semiquantitative results of the mutation analysis by the SNV panel correlated with the evolution of the disease. CONCLUSIONS: The nCounter platform requires less DNA than NGS and can be employed for routine mutation testing in liquid biopsies of patients with cancer.

Using systems biology approaches to identify signalling pathways activated during chronic wound initiation.

Chronic wounds are a significant health problem worldwide. However, nothing is known about how chronic wounds initiate and develop. Here we use a chronic wound model in diabetic mice and a Systems Biology Approach using nanoString nCounter technology and weighted gene correlation network analysis (WGCNA), with tissues collected at 6, 12, 24 and 48 h post-wounding, to identify metabolic signalling pathways involved in initiation of chronicity. Normalized counts obtained from the nanoString nCounter Mouse Metabolic Panel were used for the WGCNA, which groups genes into co-expression modules to visualize the correlation network. Genes with significant module membership and gene trait significance (p < 0.05) were used to identify signalling pathways that are important for the development of chronicity. The pathway analysis using the Reactome database showed stabilization of PTEN, which down-regulates PI3K/AKT1, which in turn down-regulates Nrf2, as shown by ELISA, thus disabling antioxidant production, resulting in high oxidative stress levels. We find that pathways involved in inflammation, including those that generate pro-inflammatory lipids derived from arachidonic acid metabolism, IFNγ and catecholamines, occur. Moreover, HIF3α is over-expressed, potentially blocking Hif1α and preventing activation of growth factors and cytokines that promote granulation tissue formation. We also find that FGF1 is under-expressed, while thrombospondin-1 is over-expressed, resulting in decreased angiogenesis, a process that is critical for healing. Finally, enzymes involved in glycolysis are down-regulated, resulting in decreased production of pyruvate, a molecule critical for ATP production, leading to extensive cell death and wound paralysis. These findings offer new avenues of study that may lead to the development of novel treatments of CW to be administered right after debridement.

Overwintering conditions impact insulin pathway gene expression in diapausing Megachile rotundata.

Diapause is a non-feeding state that many insects undergo to survive the winter months. With fixed resources, overall metabolism and insulin signaling (IIS) are maintained at low levels, but whether those change in response to seasonal temperature fluctuations remains unknown. The focus of this study was to determine 1) how genes in the insulin signaling pathway vary throughout diapause and 2) if that variation changes in response to temperature. To test the hypothesis that expression of IIS pathway genes vary in response to temperature fluctuations during overwintering, alfalfa leafcutting bees, Megachile rotundata, were overwintered at either a constant 4 °C in the lab or in naturally fluctuating temperatures in the field. Expression levels of genes in the IIS pathway, cell cycle regulators, and transcription factors were measured. Overall our findings showed that a few key targets of the insulin signaling pathway, along with growth regulators, change during overwintering, suggesting that only cell cycle regulators, and not the IIS pathway as a whole, change across the phases of diapause. To answer our second question, we compared gene expression levels between temperature treatments at each month for a given gene. We observed significantly more differences in expression of IIS pathway targets, indicating that overwintering conditions impact insulin pathway gene expression and leads to altered expression profiles. With differences seen between temperature treatment groups, these findings indicate that constant temperatures like those used in agricultural storage protocols, lead to different expression profiles and possibly different diapause phenotypes for alfalfa leafcutting bees.

Prediction of prognostic signatures in triple-negative breast cancer based on the differential expression analysis via NanoString nCounter immune panel.

BACKGROUND: Triple-Negative Breast Cancer (TNBC) is an aggressive and complex subtype of breast cancer. The current biomarkers used in the context of breast cancer treatment are highly dependent on the targeting of oestrogen receptor, progesterone receptor, or HER2, resulting in treatment failure and disease recurrence and creating clinical challenges. Thus, there is still a crucial need for the improvement of TNBC treatment; the discovery of effective biomarkers that can be easily translated to the clinics is essential. METHODS: We report an approach for the discovery of biomarkers that can predict tumour relapse and pathologic complete response (pCR) in TNBC on the basis of mRNA expression quantified using the NanoString nCounter Immunology Panel. To overcome the limited sample size, prediction models based on random Forest were constructed using the differentially expressed genes (DEGs) as selected features. We also evaluated the differences between pre- and post-treatment groups aiming for the combinatorial assessment of pCR and relapse using additive models in edgeR. RESULTS: We identify nine and 13 DEGs strongly associated with pCR and relapse, respectively, from 579 immune genes in a small number of samples (n = 55) using edgeR. An additive model for the comparison of pre- and post-treatment groups via the adjustment of the independent subject in the relapse group revealed associations for 41 genes. Comprehensive analysis indicated that our prediction models outperformed those constructed using features extracted from the existing feature selection model Elastic Net in terms of accuracy. The prediction models were assessed using a randomization test to validate the robustness (empirical P for the model of pCR = 0.015 and empirical P for the model of relapse = 0.018). Furthermore, three DEGs (FCER1A, EDNRB, and TGFBI) in the model of relapse showed prognostic significance for predicting the survival of patients with cancer through Cox proportional hazards regression model-based survival analysis. CONCLUSION: Gene expression quantified via the NanoString nCounter Immunology Panel can be seamlessly analysed using edgeR, even considering small sample sizes. Our approach provides a scalable framework that can easily be applied for the discovery of biomarkers based on the NanoString nCounter Immunology Panel. DATA AVAILABILITY: The source code will be available from github at https://github.com/sungheep/nanostring .

Xenobiotica-metabolizing enzyme induction potential of chemicals in animal studies: NanoString nCounter gene expression and peptide group-specific immunoaffinity as accelerated and economical substitutions for enzyme activity determinations?

Xenobiotica-metabolizing enzyme (XME) induction is a relevant biological/biochemical process vital to understanding the toxicological profile of xenobiotics. Early recognition of XME induction potential of compounds under development is therefore important, yet its determination by traditional XME activity measurements is time consuming and cost intensive. A proof-of-principle study was therefore designed due to the advent of faster and less cost-intensive methods for determination of enzyme protein and transcript levels to determine whether two such methods may substitute for traditional measurement of XME activity determinations. The results of the study show that determination of enzyme protein levels by peptide group-specific immunoaffinity enrichment/MS and/or determination of gene expression by NanoString nCounter may serve as substitutes for traditional evaluation methodology and/or as an early predictor of potential changes in liver enzymes. In this study, changes of XME activity by the known standard XME inducers phenobarbital, beta-naphthoflavone and Aroclor 1254 were demonstrated by these two methods. To investigate the applicability of these methods to demonstrate XME-inducing activity of an unknown, TS was also examined and found to be an XME inducer. More specifically, TS was found to be a phenobarbital-type inducer (likely mediated by CAR rather than PXR as nuclear receptor), but not due to Ah receptor-mediated or antioxidant response element-mediated beta-naphthoflavone-type induction. The results for TS were confirmed via enzymatic activity measurements. The results of the present study demonstrate the potential applicability of NanoString nCounter mRNA quantitation and peptide group-specific immunoaffinity enrichment/MS protein quantitation for predicting compounds under development to be inducers of liver XME activity.

Implementation of a Multiplex and Quantitative Proteomics Platform for Assessing Protein Lysates Using DNA-Barcoded Antibodies.

Molecular analysis of tumors forms the basis for personalized cancer medicine and increasingly guides patient selection for targeted therapy. Future opportunities for personalized medicine are highlighted by the measurement of protein expression levels via immunohistochemistry, protein arrays, and other approaches; however, sample type, sample quantity, batch effects, and "time to result" are limiting factors for clinical application. Here, we present a development pipeline for a novel multiplexed DNA-labeled antibody platform which digitally quantifies protein expression from lysate samples. We implemented a rigorous validation process for each antibody and show that the platform is amenable to multiple protocols covering nitrocellulose and plate-based methods. Results are highly reproducible across technical and biological replicates, and there are no observed "batch effects" which are common for most multiplex molecular assays. Tests from basal and perturbed cancer cell lines indicate that this platform is comparable to orthogonal proteomic assays such as Reverse-Phase Protein Array, and applicable to measuring the pharmacodynamic effects of clinically-relevant cancer therapeutics. Furthermore, we demonstrate the potential clinical utility of the platform with protein profiling from breast cancer patient samples to identify molecular subtypes. Together, these findings highlight the potential of this platform for enhancing our understanding of cancer biology in a clinical translation setting.

Prenatal S-Adenosine Methionine (SAMe) Induces Changes in Gene Expression in the Brain of Newborn Mice That Are Prevented by Co-Administration of Valproic Acid (VPA).

In previous studies, we produced changes in gene expression in the brain of mice by early postnatal administration of valproic acid (VPA), with distinct differences between genders. The addition of S-adenosine methionine (SAMe) normalized the expression of most genes in both genders, while SAMe alone induced no changes. We treated pregnant dams with a single injection of VPA on day 12.5 of gestation, or with SAMe during gestational days 12-14, or by a combination of VPA and SAMe. In the frontal half of the brain, we studied the expression of 770 genes of the pathways involved in neurophysiology and neuropathology using the NanoString nCounter method. SAMe, but not VPA, induced statistically significant changes in the expression of many genes, with differences between genders. The expression of 112 genes was changed in both sexes, and another 170 genes were changed only in females and 31 only in males. About 30% of the genes were changed by more than 50%. One of the most important pathways changed by SAMe in both sexes was the VEGF (vascular endothelial growth factor) pathway. Pretreatment with VPA prevented almost all the changes in gene expression induced by SAMe. We conclude that large doses of SAMe, if administered prenatally, may induce significant epigenetic changes in the offspring. Hence, SAMe and possibly other methyl donors may be epigenetic teratogens.

Circular RNA profiling provides insights into their subcellular distribution and molecular characteristics in HepG2 cells.

Circular RNA (circRNA) is a novel RNA molecule that has become a research focus recently. Although some research indicated that the circRNAs in different subcellular compartments could execute different regulatory functions, a panoramic analysis of the subcellular distribution and the transport mechanism of circRNA is still required. In this study, we comprehensively analyzed the subcellular distribution/characteristics and the transport mechanism, through systemically investigating the circRNA profiles among the subcellular fractions of HepG2 cell (nucleus, cytoplasm, mitochondria, ribosome, cytosol and exosome). CircRNAs were widely distributed among the subcellular fractions except in the mitochondria, with differences in the subcellular distribution/characteristics in terms of classification, length, GC content, alternative circularization and parental gene function. Further analysis indicated this might be due to the selective transportation mediated by the transport-related RNA binding proteins (RBPs). The circRNAs may follow the same transportation mechanism of linear RNAs, in which the RBPs specially recognize/transport the RNAs with the corresponding binding motifs. Interestingly, we found that the exosome could selectively package the circRNAs containing the purine-rich 5'-GMWGVWGRAG-3' motif, with the characteristic of 'garbage dumping' and 'intercellular signaling' functions. Besides, although we observed numerous circRNAs enriched in the ribosome, we did not reliably identify any unique-peptides from circRNAs using 3D-LC-MS/MS strategy. This suggests that circRNAs rarely function as translation templates in vivo like lincRNA. Our findings not only indicates the differential distributions/characteristics among the subcellular fractions, but also reveals the possible transportation mechanism. This provides an improved understanding of the life history and molecular behavior of circRNA in cells.