Variants in the circadian clock genes PER2 and PER3 associate with familial sleep phase disorders.

Delayed sleep phase disorder and advanced sleep phase disorder cause disruption of the circadian clock and present with extreme morning/evening chronotype with unclear role of the genetic etiology, especially for delayed sleep phase disorder. To assess if genotyping can aid in clinical diagnosis, we examined the presence of genetic variants in circadian clock genes previously linked to both sleep disorders in Slovenian patient cohort. Based on Morning-evening questionnaire, we found 15 patients with extreme chronotypes, 13 evening and 2 morning, and 28 controls. Sanger sequencing was used to determine the presence of carefully selected candidate SNPs in regions of the CSNK1D, PER2/3 and CRY1 genes. In a patient with an extreme morning chronotype and a family history of circadian sleep disorder we identified two heterozygous missense variants in PER3 gene, c.1243C>G (NM_001377275.1 (p.Pro415Ala)) and c.1250A>G (NM_001377275.1 (p.His417Arg)). The variants were significantly linked to Advanced sleep phase disorder and were also found in proband's father with extreme morningness. Additionally, a rare SNP was found in PER2 gene in a patient with clinical picture of Delayed sleep phase disorder. The novel variant in PER2 (NM_022817.3):c.1901-218 G>T was found in proband's parent with eveningness, indicating an autosomal dominant inheritance. We identified a family with autosomal dominant inheritance of two PER3 heterozygous variants that can be linked to Advanced sleep phase disorder. We revealed also a rare hereditary form of Delayed sleep phase disorder with a new PER2 variant with autosomal dominant inheritance, shedding the light into the genetic causality.

Circadian characteristics of term and preterm labors.

The labor is a physiological event considered to have its own circadian (diurnal) rhythm, but some of the data remain conflicting, especially for preterm births. In this retrospective study, we analyzed the circadian trends of labor onset times in the Slovenian birth cohort from 1990 to 2018 with over 550,000 cases of singleton births. The number of term and preterm labor onsets was calculated for each hour in a day and circadian trends were evaluated for each of the study groups by modeling with a generalized Poisson distribution linked with the cosinor regression model using logarithmic link function. The induced labors were taken as the control group since the timing of labor depends mostly on the working schedule of personnel and not on the intrinsic rhythmic characteristics. For induced labors, the main peak in the number of labor cases was observed in the late morning hours (around 10 AM) for all gestational ages. The prominence of this peak becomes smaller in spontaneous premature labors with gradually disrupting rhythmicity in very preterm and extremely preterm cases. Labors starting with spontaneous contractions peak between 6 and 7 AM and lose the rhythmicity at 35 weeks of gestation while labors starting with a spontaneous rupture of membranes peak at 1 AM and lose the rhythmicity at 31 weeks of gestation, suggesting differences in underlying mechanisms. According to our knowledge, this is the first study that shows differences of circadian trends between different types of spontaneous labors, i.e., labors initiated with contraction and labors initiated with a spontaneous rupture of membranes. Moreover, the obtained results represent evidence of gradual disruption of rhythmicity from mild to extreme prematurity.

Mechanisms of pathogenicity and the quest for genetic modifiers of kidney disease in branchiootorenal syndrome.

Backgound: Branchiootorenal (BOR) syndrome is an autosomal dominant disorder caused by pathogenic EYA1 variants and clinically characterized by auricular malformations with hearing loss, branchial arch anomalies, and congenital anomalies of the kidney and urinary tract. BOR phenotypes are highly variable and heterogenous. While random monoallelic expression is assumed to explain this phenotypic heterogeneity, the potential role of modifier genes has not yet been explored. Methods: Through thorough phenotyping and exome sequencing, we studied one family with disease presentation in at least four generations in both clinical and genetic terms. Functional investigation of the single associated EYA1 variant c.1698+1G>A included splice site analysis and assessment of EYA1 distribution in patient-derived fibroblasts. The candidate modifier gene CYP51A1 was evaluated by histopathological analysis of murine Cyp51+/- and Cyp51-/- kidneys. As the gene encodes the enzyme lanosterol 14α-demethylase, we assessed sterol intermediates in patient blood samples as well. Results: The EYA1 variant c.1698+1G>A resulted in functional deletion of the EYA domain by exon skipping. The EYA domain mediates protein-protein interactions between EYA1 and co-regulators of transcription. EYA1 abundance was reduced in the nuclear compartment of patient-derived fibroblasts, suggesting impaired nuclear translocation of these protein complexes. Within the affected family, renal phenotypes spanned from normal kidney function in adulthood to chronic kidney failure in infancy. By analyzing exome sequencing data for variants that potentially play roles as genetic modifiers, we identified a canonical splice site alteration in CYP51A1 as the strongest candidate variant. Conclusion: In this study, we demonstrate pathogenicity of EYA1 c.1698+1G>A, propose a mechanism for dysfunction of mutant EYA1, and conjecture CYP51A1 as a potential genetic modifier of renal involvement in BOR syndrome.

COVID-19 and cholesterol biosynthesis: Towards innovative decision support systems.

With COVID-19 becoming endemic, there is a continuing need to find biomarkers characterizing the disease and aiding in patient stratification. We studied the relation between COVID-19 and cholesterol biosynthesis by comparing 10 intermediates of cholesterol biosynthesis during the hospitalization of 164 patients (admission, disease deterioration, discharge) admitted to the University Medical Center of Ljubljana. The concentrations of zymosterol, 24-dehydrolathosterol, desmosterol, and zymostenol were significantly altered in COVID-19 patients. We further developed a predictive model for disease severity based on clinical parameters alone and their combination with a subset of sterols. Our machine learning models applying 8 clinical parameters predicted disease severity with excellent accuracy (AUC = 0.96), showing substantial improvement over current clinical risk scores. After including sterols, model performance remained better than COVID-GRAM. This is the first study to examine cholesterol biosynthesis during COVID-19 and shows that a subset of cholesterol-related sterols is associated with the severity of COVID-19.

Integrative computational modeling to unravel novel potential biomarkers in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a major health problem around the world. The management of this disease is complicated by the lack of noninvasive diagnostic tools and the few treatment options available. Better clinical outcomes can be achieved if HCC is detected early, but unfortunately, clinical signs appear when the disease is in its late stages. We aim to identify novel genes that can be targeted for the diagnosis and therapy of HCC. We performed a meta-analysis of transcriptomics data to identify differentially expressed genes and applied network analysis to identify hub genes. Fatty acid metabolism, complement and coagulation cascade, chemical carcinogenesis and retinol metabolism were identified as key pathways in HCC. Furthermore, we integrated transcriptomics data into a reference human genome-scale metabolic model to identify key reactions and subsystems relevant in HCC. We conclude that fatty acid activation, purine metabolism, vitamin D, and E metabolism are key processes in the development of HCC and therefore need to be further explored for the development of new therapies. We provide the first evidence that GABRP, HBG1 and DAK (TKFC) genes are important in HCC in humans and warrant further studies.

Is obstructive sleep apnea a circadian rhythm disorder?

Obstructive sleep apnea is the most common sleep-related breathing disorder worldwide and remains underdiagnosed. Its multiple associated comorbidities contribute to a decreased quality of life and work performance as well as an increased risk of death. Standard treatment seems to have limited effects on cardiovascular and metabolic aspects of the disease, emphasising the need for early diagnosis and additional therapeutic approaches. Recent evidence suggests that the dysregulation of circadian rhythms, processes with endogenous rhythmicity that are adjusted to the environment through various cues, is involved in the pathogenesis of comorbidities. In patients with obstructive sleep apnea, altered circadian gene expression patterns have been demonstrated. Obstructive respiratory events may promote circadian dysregulation through the effects of sleep disturbance and intermittent hypoxia, with subsequent inflammation and disruption of neural and hormonal homeostasis. In this review, current knowledge on obstructive sleep apnea, circadian rhythm regulation, and circadian rhythm sleep disorders is summarised. Studies that connect obstructive sleep apnea to circadian rhythm abnormalities are critically evaluated. Furthermore, pathogenetic mechanisms that may underlie this association, most notably hypoxia signalling, are presented. A bidirectional relationship between obstructive sleep apnea and circadian rhythm dysregulation is proposed. Approaching obstructive sleep apnea as a circadian rhythm disorder may prove beneficial for the development of new, personalised diagnostic, therapeutic and prognostic tools. However, further studies are needed before the clinical approach to obstructive sleep apnea includes targeting the circadian system.

Bacterial DNA Recognition by SERS Active Plasma-Coupled Nanogold.

It is shown that surface-enhanced Raman spectroscopy (SERS) can identify bacteria based on their genomic DNA composition, acting as a "sample-distinguishing marker". Successful spectral differentiation of bacterial species was accomplished with nanogold aggregates synthesized through single-step plasma reduction of the ionic gold-containing vapored precursor. A high enhancement factor (EF = 107) in truncated coupled plasmonic particulates allowed SERS-probing at nanogram sample quantities. Simulations confirmed the occurrence of the strongest electric field confinement within nanometric gaps between gold dimers/chains from where the molecular fingerprints of bacterial DNA fragments gained photon scattering enhancement. The most prominent Raman modes linked to fundamental base-pair molecular vibrations were deconvoluted and used to proceed with nitrogenous base content estimation. The genomic composition (percentage of guanine-cytosine and adenine-thymine) was successfully validated by third-generation sequencing using nanopore technology, further proving that the SERS technique can be employed to swiftly specify bioentities by the discriminative principal-component statistical approach.

Circular RNA hsa_circ_0062682 Binds to YBX1 and Promotes Oncogenesis in Hepatocellular Carcinoma.

Circular RNAs (circRNAs) have been shown to play an important role in the pathogenesis of hepatocellular carcinoma (HCC). By implementing available transcriptomic analyses of HCC patients, we identified an upregulated circRNA hsa_circ_0062682. Stable perturbations of hsa_circ_0062682 in Huh-7 and SNU-449 cell lines influenced colony formation, migration, cell proliferation, sorafenib sensitivity, and additionally induced morphological changes in cell lines, indicating an important role of hsa_circ_0062682 in oncogenesis. Pathway enrichment analysis and gene set enrichment analysis of the transcriptome data from hsa_circ_0062682 knockdown explained the observed phenotypes and exposed transcription factors E2F1, Sp1, HIF-1α, and NFκB1 as potential downstream targets. Biotinylated oligonucleotide pulldown combined with proteomic analyses identified protein interaction partners of which YBX1, a known oncogene, was confirmed by RNA immunoprecipitation. Furthermore, we discovered a complex cell-type-specific phenotype in response to the oncogenic potential of hsa_circ_0062682. This finding is in line with different classes of HCC tumours, and more studies are needed to shed a light on the molecular complexity of liver cancer.

Whole transcriptome expression array analysis of human colon fibroblasts culture treated with Helichrysum italicum supports its use in traditional medicine.

ETHNOPHARMACOLOGICAL RELEVANCE: Helichrysum italicum (HI) is a Mediterranean plant with well-reported use in traditional medicine for a wide range of applications, including digestive and liver disorders, intestinal parasitic infections, wound healing, stomach ache and asthma. However, little is known about the global mechanism behind its pleiotropic activity. AIM OF THE STUDY: The aim of this study was to explain the mechanism behind the previously demonstrated effects of HI and to justify its use in traditional medicine. MATERIALS AND METHODS: A microarray-based transcriptome analysis was used to discover the global transcriptional alterations in primary colon fibroblasts after exposure to HI infusion for 6 h and 24 h. In addition, quantitative real-time PCR was used to verify the microarray results. RESULTS: Altogether we identified 217 differentially expressed genes compared to non-treated cells, and only 8 were common to both treatments. Gene ontology analysis revealed that 24 h treatment with HI infusion altered the expression of genes involved in cytoskeletal rearrangement and cell growth, whereas pathway analysis further showed the importance of interleukin signaling and transcriptional regulation by TP53. For the 6 h treatment only the process of hemostasis appeared in the results of both enrichment analyses. In functional assays, HI infusion increased cell migration and decreased blood clotting and prothrombin time. CONCLUSIONS: With the careful evaluation of the role of individual genes, especially SERPING1, ARHGAP1, IL33 and CDKN1A, represented in the enriched pathways and processes, we propose the main mode of HI action, which is wound healing. In addition to its indirect prevention of diseases resulting from the impaired barrier integrity, HI also effects inflammation and metabolic processes directly, as it regulates genes such as LRPPRC, LIPA, ABCA12, PRKAR1A and ANXA6.

The role of bile acids in carcinogenesis.

Bile acids are soluble derivatives of cholesterol produced in the liver that subsequently undergo bacterial transformation yielding a diverse array of metabolites. The bulk of bile acid synthesis takes place in the liver yielding primary bile acids; however, other tissues have also the capacity to generate bile acids (e.g. ovaries). Hepatic bile acids are then transported to bile and are subsequently released into the intestines. In the large intestine, a fraction of primary bile acids is converted to secondary bile acids by gut bacteria. The majority of the intestinal bile acids undergo reuptake and return to the liver. A small fraction of secondary and primary bile acids remains in the circulation and exert receptor-mediated and pure chemical effects (e.g. acidic bile in oesophageal cancer) on cancer cells. In this review, we assess how changes to bile acid biosynthesis, bile acid flux and local bile acid concentration modulate the behavior of different cancers. Here, we present in-depth the involvement of bile acids in oesophageal, gastric, hepatocellular, pancreatic, colorectal, breast, prostate, ovarian cancer. Previous studies often used bile acids in supraphysiological concentration, sometimes in concentrations 1000 times higher than the highest reported tissue or serum concentrations likely eliciting unspecific effects, a practice that we advocate against in this review. Furthermore, we show that, although bile acids were classically considered as pro-carcinogenic agents (e.g. oesophageal cancer), the dogma that switch, as lower concentrations of bile acids that correspond to their serum or tissue reference concentration possess anticancer activity in a subset of cancers. Differences in the response of cancers to bile acids lie in the differential expression of bile acid receptors between cancers (e.g. FXR vs. TGR5). UDCA, a bile acid that is sold as a generic medication against cholestasis or biliary surge, and its conjugates were identified with almost purely anticancer features suggesting a possibility for drug repurposing. Taken together, bile acids were considered as tumor inducers or tumor promoter molecules; nevertheless, in certain cancers, like breast cancer, bile acids in their reference concentrations may act as tumor suppressors suggesting a Janus-faced nature of bile acids in carcinogenesis.

Integration of omics data to generate and analyse COVID-19 specific genome-scale metabolic models.

COVID-19 presents a complex disease that needs to be addressed using systems medicine approaches that include genome-scale metabolic models (GEMs). Previous studies have used a single model extraction method (MEM) and/or a single transcriptomic dataset to reconstruct context-specific models, which proved to be insufficient for the broader biological contexts. We have applied four MEMs in combination with five COVID-19 datasets. Models produced by GIMME were separated by infection, while tINIT preserved the biological variability in the data and enabled the best prediction of the enrichment of metabolic subsystems. Vitamin D3 metabolism was predicted to be down-regulated in one dataset by GIMME, and in all by tINIT. Models generated by tINIT and GIMME predicted downregulation of retinol metabolism in different datasets, while downregulated cholesterol metabolism was predicted only by tINIT-generated models. Predictions are in line with the observations in COVID-19 patients. Our data indicated that GIMME and tINIT models provided the most biologically relevant results and should have a larger emphasis in further analyses. Particularly tINIT models identified the metabolic pathways that are a part of the host response and are potential antiviral targets. The code and the results of the analyses are available to download from https://github.com/CompBioLj/COVID_GEMs_and_MEMs.

Detecting gene-gene interactions from GWAS using diffusion kernel principal components.

Genes and gene products do not function in isolation but as components of complex networks of macromolecules through physical or biochemical interactions. Dependencies of gene mutations on genetic background (i.e., epistasis) are believed to play a role in understanding molecular underpinnings of complex diseases such as inflammatory bowel disease (IBD). However, the process of identifying such interactions is complex due to for instance the curse of high dimensionality, dependencies in the data and non-linearity. Here, we propose a novel approach for robust and computationally efficient epistasis detection. We do so by first reducing dimensionality, per gene via diffusion kernel principal components (kpc). Subsequently, kpc gene summaries are used for downstream analysis including the construction of a gene-based epistasis network. We show that our approach is not only able to recover known IBD associated genes but also additional genes of interest linked to this difficult gastrointestinal disease.

Matching mouse models to specific human liver disease states by comparative functional genomics of mouse and human datasets.

Omics has broadened our view of transcriptional and gene regulatory networks of multifactorial diseases, such as metabolism associated liver disease and its advanced stages including hepatocellular carcinoma. Identifying liver disease biomarkers and potential treatment targets makes use of experimental models, e.g. genetically engineered mice, which show molecular features of human pathologies but are experimentally tractable. We compared gene expression profiling data from human to our studies on transgenic mice with hepatocyte deletion of Cyp51 from cholesterol synthesis with the aim of identifying the human liver disease state best matched by the Cyp51 knockout model. Gene Expression Omnibus was used to identify relevant human datasets. We identified enriched and deregulated genes, pathways and transcription factors of mouse and human disease samples. Analysis showed a closer match of the Cyp51 knockout to the female patient samples. Importantly, CYP51 was depleted in both mouse and female human data. Among the enriched genes were the oxysterol-binding protein-related protein 3 (OSBPL3), which was enriched in all datasets, and the collagen gene COL1A2, which was enriched in both the mouse and one human dataset. KEGG and Reactome analyses revealed the most enriched pathway to be ECM-receptor interaction. Numerous transcription factors were differentially expressed in mice of both sexes and in the human female dataset, while depleted HNF4α and RXRα:PPARα-isoform1 were a hallmark in all cases. Our analysis exposed novel potential biomarkers, which may provide new avenues towards more personalized approaches and different targets in females and males. The analysis was only possible because of availability of open data resources and tools and broadly consistent annotation.

Systems Biology in ELIXIR: modelling in the spotlight.

In this white paper, we describe the founding of a new ELIXIR Community - the Systems Biology Community - and its proposed future contributions to both ELIXIR and the broader community of systems biologists in Europe and worldwide. The Community believes that the infrastructure aspects of systems biology - databases, (modelling) tools and standards development, as well as training and access to cloud infrastructure - are not only appropriate components of the ELIXIR infrastructure, but will prove key components of ELIXIR's future support of advanced biological applications and personalised medicine. By way of a series of meetings, the Community identified seven key areas for its future activities, reflecting both future needs and previous and current activities within ELIXIR Platforms and Communities. These are: overcoming barriers to the wider uptake of systems biology; linking new and existing data to systems biology models; interoperability of systems biology resources; further development and embedding of systems medicine; provisioning of modelling as a service; building and coordinating capacity building and training resources; and supporting industrial embedding of systems biology. A set of objectives for the Community has been identified under four main headline areas: Standardisation and Interoperability, Technology, Capacity Building and Training, and Industrial Embedding. These are grouped into short-term (3-year), mid-term (6-year) and long-term (10-year) objectives.

Sequencing of Nucleic Acids: from the First Human Genome to Next Generation Sequencing in {COVID}-19 Pandemic.

Despite being around for more than 40 years, DNA sequencing is regarded as young technology in clinical medicine. As sequencing is becoming cheaper, faster and more accurate, it is rapidly being incorporated into clinical laboratories. In 2003, the completion of the first human genome opened the door to personalized medicine. Ever since it has been expected for genomics to widely impact clinical care and public health. However, many years can pass for genomic discoveries to reflect back and benefit the patients. DNA sequencing represents a less biased approach to diagnostics. It is not only a diagnostic tool, but can also influence clinical management and therapy. As new technologies rapidly emerge it is important for researchers and health professionals to have basic knowledge about the capabilities and drawbacks of the existing sequencing methods, and their use in clinical setting and research. This review provides an overview of nucleic acid sequencing technologies from historical perspective and later focuses on clinical utilization of sequencing. Some of the most promising areas are presented with selected examples from Slovenian researchers.

Identification of Variants Associated With Rare Hematological Disorder Erythrocytosis Using Targeted Next-Generation Sequencing Analysis.

An erythrocytosis is present when the red blood cell mass is increased, demonstrated as elevated hemoglobin and hematocrit in the laboratory evaluation. Congenital predispositions for erythrocytosis are rare, with germline variants in several genes involved in oxygen sensing (VHL, EGLN1, and EPAS1), signaling for hematopoietic cell maturation (EPOR and EPO), and oxygen transfer (HBB, HBA1, HBA2, and BPGM) that were already associated with the eight congenital types (ECYT1-8). Screening for variants in known congenital erythrocytosis genes with classical sequencing approach gives a correct diagnosis for only up to one-third of the patients. The genetic background of erythrocytosis is more heterogeneous, and additional genes involved in erythropoiesis and iron metabolism could have a putative effect on the development of erythrocytosis. This study aimed to detect variants in patients with yet unexplained erythrocytosis using the next-generation sequencing (NGS) approach, targeting genes associated with erythrocytosis and increased iron uptake and implementing the diagnostics of congenital erythrocytosis in Slovenia. Selected 25 patients with high hemoglobin, high hematocrit, and no acquired causes were screened for variants in the 39 candidate genes. We identified one pathogenic variant in EPAS1 gene and three novel variants with yet unknown significance in genes EPAS1, JAK2, and SH2B3. Interestingly, a high proportion of patients were heterozygous carriers for two variants in HFE gene, otherwise pathogenic for the condition of iron overload. The association between the HFE variants and the development of erythrocytosis is not clearly understood. With a targeted NGS approach, we determined an actual genetic cause for the erythrocytosis in one patient and contributed to better management of the disease for the patient and his family. The effect of variants of unknown significance on the enhanced production of red blood cells needs to be further explored with functional analysis. This study is of great significance for the improvement of diagnosis of Slovenian patients with unexplained erythrocytosis and future research on the etiology of this rare hematological disorder.

Identification of Novel RNA Binding Proteins Influencing Circular RNA Expression in Hepatocellular Carcinoma.

Circular RNAs (circRNAs) are increasingly recognized as having a role in cancer development. Their expression is modified in numerous cancers, including hepatocellular carcinoma (HCC); however, little is known about the mechanisms of their regulation. The aim of this study was to identify regulators of circRNAome expression in HCC. Using publicly available datasets, we identified RNA binding proteins (RBPs) with enriched motifs around the splice sites of differentially expressed circRNAs in HCC. We confirmed the binding of some of the candidate RBPs using ChIP-seq and eCLIP datasets in the ENCODE database. Several of the identified RBPs were found to be differentially expressed in HCC and/or correlated with the overall survival of HCC patients. According to our bioinformatics analyses and published evidence, we propose that NONO, PCPB2, PCPB1, ESRP2, and HNRNPK are candidate regulators of circRNA expression in HCC. We confirmed that the knocking down the epithelial splicing regulatory protein 2 (ESRP2), known to be involved in the maintenance of the adult liver phenotype, significantly changed the expression of candidate circRNAs in a model HCC cell line. By understanding the systemic changes in transcriptome splicing, we can identify new proteins involved in the molecular pathways leading to HCC development and progression.

Guided extraction of genome-scale metabolic models for the integration and analysis of omics data.

Omics data can be integrated into a reference model using various model extraction methods (MEMs) to yield context-specific genome-scale metabolic models (GEMs). How to chose the appropriate MEM, thresholding rule and threshold remains a challenge. We integrated mouse transcriptomic data from a Cyp51 knockout mice diet experiment (GSE58271) using five MEMs (GIMME, iMAT, FASTCORE, INIT an tINIT) in a combination with a recently published mouse GEM iMM1865. Except for INIT and tINIT, the size of extracted models varied with the MEM used (t-test: p-value < 0.001). The Jaccard index of iMAT models ranged from 0.27 to 1.0. Out of the three factors under study in the experiment (diet, gender and genotype), gender explained most of the variability ( > 90%) in PC1 for FASTCORE. In iMAT, each of the three factors explained less than 40% of the variability within PC1, PC2 and PC3. Among all the MEMs, FASTCORE captured the most of the true variability in the data by clustering samples by gender. Our results show that for the efficient use of MEMs in the context of omics data integration and analysis, one should apply various MEMs, thresholding rules, and thresholding values to select the MEM and its configuration that best captures the true variability in the data. This selection can be guided by the methodology as proposed and used in this paper. Moreover, we describe certain approaches that can be used to analyse the results obtained with the selected MEM and to put these results in a biological context.

Sex-dependent dynamics of metabolism in primary mouse hepatocytes.

The liver is one of the most sexually dimorphic organs. The hepatic metabolic pathways that are subject to sexual dimorphism include xenobiotic, amino acid and lipid metabolism. Non-alcoholic fatty liver disease and hepatocellular carcinoma are among diseases with sex-dependent prevalence, progression and outcome. Although male and female livers differ in their abilities to metabolize foreign compounds, including drugs, sex-dependent treatment and pharmacological dynamics are rarely applied in all relevant cases. Therefore, it is important to consider hepatic sexual dimorphism when developing new treatment strategies and to understand the underlying mechanisms in model systems. We isolated primary hepatocytes from male and female C57BL6/N mice and examined the sex-dependent transcriptome, proteome and extracellular metabolome parameters in the course of culturing them for 96 h. The sex-specific gene expression of the general xenobiotic pathway altered and the female-specific expression of Cyp2b13 and Cyp2b9 was significantly reduced during culture. Sex-dependent differences of several signaling pathways increased, including genes related to serotonin and melatonin degradation. Furthermore, the ratios of male and female gene expression were inversed for other pathways, such as amino acid degradation, beta-oxidation, androgen signaling and hepatic steatosis. Because the primary hepatocytes were cultivated without the influence of known regulators of sexual dimorphism, these results suggest currently unknown modulatory mechanisms of sexual dimorphism in vitro. The large sex-dependent differences in the regulation and dynamics of drug metabolism observed during cultivation can have an immense influence on the evaluation of pharmacodynamic processes when conducting initial preclinical trials to investigate potential new drugs.

Escherichia coli Affects Expression of Circadian Clock Genes in Human Hepatoma Cells.

Recent research has indicated that dysbiosis of the gut microbiota can lead to an altered circadian clock of the mammalian host. Herein we developed an original system that allows real-time circadian studies of human HepG2 hepatoma cells co-cultured with bacteria. The HepG2 cells with stably integrated firefly luciferase reporter under the control of PERIOD2 promoter were co-cultured with E. coli strains isolated from human fecal samples from healthy individuals. The two E. coli strains differ in the phylogenetic group and the number of ExPEC virulence-associated genes: BJ17 has only two, and BJ23 has 15 of 23 tested. In the first 24 h, the E. coli BJ17 affected the HepG2 circadian clock more than BJ23. Cosinor analysis shows a statistically significant change in the amplitude of PER1 and 2 and the phase advance of PER3. A high percentage of necrotic and apoptotic cells occurred at 72 h, while a correlation between the number of ExPEC genes and the influence on the HepG2 core clock gene expression was observed. Our study reveals that the E. coli genetic background is important for the effect on the mammalian circadian clock genes, indicating possible future use of probiotic E. coli strains to influence the host circadian clock.