Integrative protocol for quantifying cholesterol-related sterols in human serum samples and building decision support systems.

The growing interest in clinical diagnostics has recently focused on metabolic biomarkers. Here, we present a protocol for sample preparation, extraction of cholesterol-related sterols, and quantification of 10 sterols in human blood serum samples using targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS). We also describe steps of machine learning techniques to develop novel decision-making systems that offer potential benefits in disease monitoring and surveillance by measuring metabolic pathways. For complete details on the use and execution of this protocol, please refer to Kocar et al.1 and Skubic et al.2.

The Outcome of Metabolic and Bariatric Surgery in Morbidly Obese Patients with Different Genetic Variants Associated with Obesity: A Systematic Review.

Metabolic and bariatric surgery (MBS) effectively treats obesity and related comorbidities, though individual responses vary. This systematic review examines how genetic variants influence MBS outcomes in morbidly obese patients. A comprehensive search in PubMed, Embase, Medline, and the Cochrane Library identified 1572 studies, with 52 meeting the inclusion criteria. Two reviewers independently filtered and selected studies, including relevant cross-references. Research focused on polymorphisms in genes such as UCP2, UCP3, 5-HT2C, MC4R, FKBP5, FTO, CAT haplotypes, LYPAL-1, PTEN, FABP-2, CNR1, LEP656, LEP223, GLP-1R, APOA-1, APOE, ADIPOQ, IL-6, PGC1a, TM6SF2, MBOAT7, PNPLA3, TCF7L2, ESR1, GHSR, GHRL, CD40L, DIO2, ACSL5, CG, TAS2R38, CD36, OBPIIa, NPY, BDNF, CLOCK, and CAMKK2. Most studies explored associations with post-surgery weight loss, while some examined metabolic, cardiovascular, taste, and eating behavior effects as well. Understanding the role of genetic factors in weight loss and metabolic outcomes post-MBS can help tailor personalized treatment plans for improved efficacy and long-term success. Further research with larger sample sizes and extended follow-up is needed to clarify the effects of many genetic variants on MBS outcomes in morbidly obese patients.

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.

Context-Specific Genome-Scale Metabolic Modelling and Its Application to the Analysis of COVID-19 Metabolic Signatures.

Genome-scale metabolic models (GEMs) have found numerous applications in different domains, ranging from biotechnology to systems medicine. Herein, we overview the most popular algorithms for the automated reconstruction of context-specific GEMs using high-throughput experimental data. Moreover, we describe different datasets applied in the process, and protocols that can be used to further automate the model reconstruction and validation. Finally, we describe recent COVID-19 applications of context-specific GEMs, focusing on the analysis of metabolic implications, identification of biomarkers and potential drug targets.

Effect of In Vitro Maturation of Human Oocytes Obtained After Controlled Ovarian Hormonal Stimulation on the Expression of Development- and Zona Pellucida-Related Genes and Their Interactions.

In an in vitro fertilization program, approximately 10-15% of oocytes obtained after controlled ovarian stimulation are immature, with germinal vesicles (GVs). These oocytes are usually discarded in clinical practice; however, an in vitro maturation (IVM) procedure can be applied to mature them. There are scarce data in the literature on the effect of IVM on the expression of important development- and zona pellucida (ZP)-related genes in human oocytes; therefore, we wanted to determine this. One hundred nine human oocytes were collected from patients enrolled in an intracytoplasmic sperm injection program. The expression of the BMP4, GDF9, ZP1, ZP2, ZP3, and ZP4 genes was analyzed using RT-qPCR in oocytes matured in vitro with different reproductive hormones in the IVM medium (AMH, FSH + hCG, FSH + hCG + AMH), in in vivo matured oocytes and in immature oocytes with GVs. No statistically significant differences in the expression of selected genes in oocytes were observed among groups with different reproductive hormones in IVM medium. However, several interesting significant correlations were found between BMP4 and GDF9, and ZP1 and ZP4; between GDF9 and ZP1, and ZP2 and ZP4; and between ZP1 and ZP3 and ZP4 in the in vitro matured oocytes, while no such correlations were present in other groups of oocytes. The type of reproductive hormone in the maturation medium does not affect the expression of the analyzed genes in oocytes during the maturation process. However, the in vitro maturation procedure itself generated correlations among analyzed genes that were otherwise not present in in vivo matured and immature oocytes.

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.

Inflammatory landscape in Xeroderma pigmentosum patients with cutaneous melanoma.

Xeroderma pigmentosum (XP) is a DNA repair disease that predisposes to early skin cancers as cutaneous melanoma. Melanoma microenvironment contains inflammatory mediators, which would be interesting biomarkers for the prognosis or for the identification of novel therapeutic targets. We used a PCR array to evaluate the transcriptional pattern of 84 inflammatory genes in melanoma tumors obtained from XP patients (XP-Mel) and in sporadic melanoma (SP-Mel) compared to healthy skin. Commonly expressed inflammatory genes were further explored via GTEx and GEPIA databases. The differentially expressed inflammatory genes in XP were compared to their expression in skin exposed to UVs, and evaluated on the basis of the overall survival outcomes of patients with melanoma. Monocyte subsets of patients with SP-Mel, XP and healthy donors were also assessed. PCR array data revealed that 34 inflammatory genes were under-expressed in XP-Mel compared to SP-Mel. Differentially expressed genes that were common in XP-Mel and SP-Mel were correlated with the transcriptomic datasets from GEPIA and GTEx and highlighted the implication of KLK1 and IL8 in the tumorigenesis. We showed also that in XP-Mel tumors, there was an overexpression of KLK6 and KLK10 genes, which seems to be associated with a bad survival rate. As for the innate immunity, we observed a decrease of intermediate monocytes in patients with SP-Mel and in XP. We highlight an alteration in the immune response in XP patients. We identified candidate biomarkers involved in the tumorigenesis, and in the survival of patients with melanoma. Intermediate monocyte's in patients at risk could be a prognostic biomarker for melanoma outcome.

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.

Recombinant anti-Müllerian hormone in the maturation medium improves the in vitro maturation of human immature (GV) oocytes after controlled ovarian hormonal stimulation.

BACKGROUND: In vitro maturation (IVM) of oocytes is a laboratory method that allows the maturation of immature (GV) oocytes retrieved from patients enrolled in the in vitro fertilization (IVF) programme. However, this method is still sparsely researched and used in clinical practice, leading to suboptimal clinical results. Anti-Müllerian hormone (AMH) is an important hormone with known effects on human ovaries, especially on follicles (follicular cells) during folliculogenesis. In contrast, the effect of AMH on the human oocyte itself is unknown. Therefore, we wanted to determine whether human oocytes express AMH receptor 2 (AMHR2) for this hormone. Recombinant AMH was added to the IVM medium to determine whether it affected oocyte maturation. METHODS: In total, 247 human oocytes (171 immature and 76 mature) were collected from patients enrolled in the intracytoplasmic sperm injection (ICSI) programme who were aged 20 to 43 years and underwent a short antagonist protocol of ovarian stimulation. The expression of AMHR2 protein and AMHR2 gene was analysed in immature and mature oocytes. Additionally, maturation of GV oocytes was performed in vitro in different maturation media with or without added AMH to evaluate the effect of AMH on the oocyte maturation rate. RESULTS: Immunocytochemistry and confocal microscopy revealed that AMHR2 protein is expressed in both immature and mature human oocytes. AMHR2 was expressed in a spotted pattern throughout the whole oocyte. The IVM procedure revealed that AMH in maturation medium improved GV oocyte maturation in vitro, as all oocytes were successfully matured in maturation medium containing recombinant AMH only. Furthermore, antagonism between AMH and follicle-stimulating hormone (FSH) during the maturation process was observed, with fewer oocytes maturing when both AMH and FSH were added to the maturation medium. Finally, AMHR2 gene expression was found in immature and in vitro matured oocytes but absent in mature oocytes. CONCLUSIONS: The positive AMHR2 protein and AMHR2 gene expression in human oocytes shows that AMH could directly act on human oocytes. This was further functionally confirmed by the IVM procedure. These findings suggest the potential clinical application of recombinant AMH to improve IVM of human oocytes in the future.

Integrative Analysis of Rhythmicity: From Biology to Urban Environments and Sustainability.

From biological to socio-technical systems, rhythmic processes are pervasive in our environment. However, methods for their comprehensive analysis are prevalent only in specific fields that limit the transfer of knowledge across scientific disciplines. This hinders interdisciplinary research and integrative analyses of rhythms across different domains and datasets. In this paper, we review recent developments in cross-disciplinary rhythmicity research, with a focus on the importance of rhythmic analyses in urban planning and biomedical research. Furthermore, we describe the current state of the art of (integrative) computational methods for the investigation of rhythmic data. Finally, we discuss the further potential and propose necessary future developments for cross-disciplinary rhythmicity analysis to foster integration of heterogeneous datasets across different domains, as well as guide data-driven decision making beyond the boundaries of traditional intradisciplinary research, especially in the context of sustainable and healthy cities.

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.

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.