Filling the gap between experimentalists and modelers by determining a mammalian cell\u27s metabolic capabilities based on transcriptomic data

Large-scale omics experiments are now standard in many biological studies, and many methods exist to interpret these data. One emerging approach uses genome-scale metabolic models (GEMs) for model-guided data analysis, since they provide cellular context to these large data sets by establishing a mechanistic link from genotype to phenotype. GEMs include all reactions in an organism, but not all enzymes are active in each tissue, cell line or culture condition. Therefore, algorithms have been developed to build context-specific models that recapitulate the metabolism of specific cell types under specific conditions, based on omics data measurements1. While these context-specific models improve the ability to predict genotype-phenotype relationships, the physiological accuracy and relevance of these models are often overlooked, due to gaps in our knowledge of context-specific metabolism functionalities. Indeed, many cell types have unique metabolic functions they natively accomplish. However, since these functions are often poorly defined for specific cell types, it can be difficult to evaluate a cell’s metabolic activities in an unbiased fashion within a modeling context. To overcome this, we curated a list of previously published metabolic tasks2,3 and obtained a collection of 210 tasks covering 7 major metabolic activities of a cell (energy generation, nucleotide, carbohydrates, amino acid, lipid, vitamin & cofactor and glycan metabolism). Using published genome-scale metabolic models for human and CHO cells, we identified all metabolic genes that are used for each metabolic function. Thus, by using these lists of genes to analyze omics data (e.g., RNA-Seq), one can estimate the metabolic capabilities of a cell without modeling. Please click Additional Files below to see the full abstract

A user-friendly tool using systems biology models to infer cell functions from omics

Please click Additional Files below to see the full abstract

Modulating carbohydrate–protein interactions through glycoengineering of monoclonal antibodies to impact cancer physiology

Diverse glycans on proteins help impact cell and organism physiology along with drug activity. Since many protein-based biotherapeutics are glycosylated and these glycans have biological activity, there is a desire to engineer glycosylation for recombinant protein-based biotherapeutics. Engineered glycosylation can impact the recombinant protein efficacy and also influence many cell pathways by first changing glycan-protein interactions and consequently modulating disease physiologies. However, its complexity is enormous. Due to recent advances in glycoengineering, modulating protein-glycan interactions become more amenable to therapeutic approaches. Here, we discuss how engineered glycans contribute to therapeutic monoclonal antibodies (mAbs) in the treatment of cancers, how these glycoengineered therapeutic mAbs affect the transformed phenotypes and downstream cell pathways, and how systems biology can help in the next generation mAb glycoengineering process by aiding in data analysis and guiding engineering efforts to tailor mAb glycan and ultimately drug efficacy, safety and affordability

Associations between lifestyle factors and levels of per- and polyfluoroalkyl substances (PFASs), phthalates and parabens in follicular fluid in women undergoing fertility treatment

Background: Concerns have been raised whether exposure to endocrine-disrupting chemicals (EDCs) can alter reproductive functions and play a role in the aetiology of infertility in women. With increasing evidence of adverse effects, information on factors associated with exposure is necessary to form firm recommendations aiming at reducing exposure.Objective: Our aim was to identify associations between lifestyle factors including the home environment, use of personal care products (PCP), and dietary habits and concentrations of EDCs in ovarian follicular fluid.Methods: April-June 2016, 185 women undergoing ovum pick-up for in vitro fertilisation in Sweden were recruited. Correlation analyses were performed between self-reported lifestyle factors and concentration of EDCs analysed in follicular fluid. Habits related to cleaning, PCPs, and diet were assessed together with concentration of six per- and polyfluoroalkyl substances (PFASs) [PFHxS, PFOA, PFOS, PFNA, PFDA and PFUnDA], methyl paraben and eight phthalate metabolites [MECPP, MEHPP, MEOHP, MEHP, cxMinCH, cxMiNP, ohMiNP, MEP, MOHiBP]. Spearman's partial correlations were adjusted for age, parity and BMI.Results: Significant associations were discovered between multiple lifestyle factors and concentrations of EDCs in ovarian follicular fluid. After correcting p values for multiple testing, frequent use of perfume was associated with MEP (correlation rho = 0.41 (confidence interval 0.21-0.47), p < 0.001); hens' egg consumption was positively associated with PFOS (rho = 0.30 (0.15-0.43), p = 0.007) and PFUnDA (rho = 0.27 (0.12-0.40), p = 0.036). White fish consumption was positively associated with PFUnDA (rho = 0.34 (0.20-0.47), p < 0.001) and PFDA (rho = 0.27 (0.13-0.41), p = 0.028). More correlations were discovered when considering the raw uncorrected p values. Altogether, our results suggest that multiple lifestyle variables affect chemical contamination of follicular fluid.Impact statement: This study shows how lifestyle factors correlate with the level of contamination in the ovary by both persistent and semi-persistent chemicals in women of reproductive age. Subsequently, these data can be used to form recommendations regarding lifestyle to mitigate possible negative health outcomes and fertility problems associated with chemical exposure, and to inform chemical policy decision making. Our study can also help form the basis for the design of larger observational and intervention studies to examine possible effects of lifestyle changes on exposure levels, and to unravel the complex interactions between biological factors, lifestyle and chemical exposures in more detail

Follicular fluid and blood levels of persistent organic pollutants and reproductive outcomes among women undergoing assisted reproductive technologies

Persistent organic pollutants (POPs) are industrial chemicals resistant to degradation and have been shown to have adverse effects on reproductive health in wildlife and humans. Although regulations have reduced their levels, they are still ubiquitously present and pose a global concern. Here, we studied a cohort of 185 women aged 21-43 years with a median of 2 years of infertility who were seeking assisted reproductive technology (ART) treatment at the Carl von Linne Clinic in Uppsala, Sweden. We analyzed the levels of 9 organochlorine pesticides (OCPs), 10 polychlorinated biphenyls (PCBs), 3 polybrominated diphenyl ethers (PBDEs), and 8 perfluoroalkyl substances (PFASs) in the blood and follicular fluid (FF) samples collected during ovum pick-up. Impact of age on chemical transfer from blood to FF was analyzed. Associations of chemicals, both individually and as a mixture, to 10 ART endpoints were investigated using linear, logistic, and weighted quantile sum regression, adjusted for age, body mass index, parity, fatty fish intake and cause of infertility. Out of the 30 chemicals, 20 were detected in more than half of the blood samples and 15 in FF. Chemical transfer from blood to FF increased with age. Chemical groups in blood crossed the blood-follicle barrier at different rates: OCPs > PCBs > PFASs. Hexachlorobenzene, an OCP, was associated with lower anti-Miillerian hormone, clinical pregnancy, and live birth. PCBs and PFASs were associated with higher antral follicle count and ovarian response as measured by ovarian sensitivity index, but also with lower embryo quality. As a mixture, similar findings were seen for the sum of PCBs and PFASs. Our results suggest that age plays a role in the chemical transfer from blood to FF and that exposure to POPs significantly associates with ART outcomes. We strongly encourage further studies to elucidate the underlying mechanisms of reproductive effects of POPs in humans

Association between chemical mixtures and female fertility in women undergoing assisted reproduction in Sweden and Estonia

ObjectiveWomen of reproductive age are exposed to ubiquitous chemicals such as phthalates, parabens, and per- and polyfluoroalkyl substances (PFAS), which have potential endocrine disrupting properties and might affect fertility. Our objective was to investigate associations between potential endocrine-disrupting chemicals (EDCs) and female fertility in two cohorts of women attending fertility clinics.MethodsIn a total population of 333 women in Sweden and Estonia, we studied the associations between chemicals and female fertility, evaluating ovarian sensitivity index (OSI) as an indicator of ovarian response, as well as clinical pregnancy and live birth from fresh and frozen embryo transfers. We measured 59 chemicals in follicular fluid samples and detected 3 phthalate metabolites, di-2-ethylhexyl phthalate (DEHP) metabolites, 1 paraben, and 6 PFAS in >90% of the women. Associations were evaluated using multivariable-adjusted linear or logistic regression, categorizing EDCs into quartiles of their distributions, as well as with Bayesian Kernel Machine Regression.ResultsWe observed statistically significant lower OSI at higher concentrations of the sum of DEHP metabolites in the Swedish cohort (Q4 vs Q1, β = -0.21, 95% CI: −0.38, −0.05) and methylparaben in the Estonian cohort (Q3 vs Q1, β = -0.22, 95% CI: −0.44, −0.01). Signals of potential associations were also observed at higher concentrations of PFUnDA in both the combined population (Q2 vs. Q1, β = −0.16, 95% CI -0.31, −0.02) and the Estonian population (Q2 vs. Q1, β = −0.27, 95% CI -0.45, −0.08), and for PFOA in the Estonian population (Q4 vs. Q1, β = −0.31, 95% CI -0.61, −0.01). Associations of chemicals with clinical pregnancy and live birth presented wide confidence intervals.ConclusionsWithin a large chemical mixture, we observed significant inverse associations levels of DEHP metabolites and methylparaben, and possibly PFUnDA and PFOA, with OSI, suggesting that these chemicals may contribute to altered ovarian function and infertility in women

Association between chemical mixtures and female fertility in women undergoing assisted reproduction in Sweden and Estonia

Objective Women of reproductive age are exposed to ubiquitous chemicals such as phthalates, parabens, and per- and polyfluoroalkyl substances (PFAS), which have potential endocrine disrupting properties and might affect fertility. Our objective was to investigate associations between potential endocrine-disrupting chemicals (EDCs) and female fertility in two cohorts of women attending fertility clinics. Methods In a total population of 333 women in Sweden and Estonia, we studied the associations between chemicals and female fertility, evaluating ovarian sensitivity index (OSI) as an indicator of ovarian response, as well as clinical pregnancy and live birth from fresh and frozen embryo transfers. We measured 59 chemicals in follicular fluid samples and detected 3 phthalate metabolites, di-2-ethylhexyl phthalate (DEHP) metabolites, 1 paraben, and 6 PFAS in >90% of the women. Associations were evaluated using multivariable-adjusted linear or logistic regression, categorizing EDCs into quartiles of their distributions, as well as with Bayesian Kernel Machine Regression. Results We observed statistically significant lower OSI at higher concentrations of the sum of DEHP metabolites in the Swedish cohort (Q4 vs Q1, β = -0.21, 95% CI: −0.38, −0.05) and methylparaben in the Estonian cohort (Q3 vs Q1, β = -0.22, 95% CI: −0.44, −0.01). Signals of potential associations were also observed at higher concentrations of PFUnDA in both the combined population (Q2 vs. Q1, β = −0.16, 95% CI -0.31, −0.02) and the Estonian population (Q2 vs. Q1, β = −0.27, 95% CI -0.45, −0.08), and for PFOA in the Estonian population (Q4 vs. Q1, β = −0.31, 95% CI -0.61, −0.01). Associations of chemicals with clinical pregnancy and live birth presented wide confidence intervals. Conclusions Within a large chemical mixture, we observed significant inverse associations levels of DEHP metabolites and methylparaben, and possibly PFUnDA and PFOA, with OSI, suggesting that these chemicals may contribute to altered ovarian function and infertility in women

Model-based assessment of mammalian cell metabolic functionalities using omics data.

Omics experiments are ubiquitous in biological studies, leading to a deluge of data. However, it is still challenging to connect changes in these data to changes in cell functions because of complex interdependencies between genes, proteins, and metabolites. Here, we present a framework allowing researchers to infer how metabolic functions change on the basis of omics data. To enable this, we curated and standardized lists of metabolic tasks that mammalian cells can accomplish. Genome-scale metabolic networks were used to define gene sets associated with each metabolic task. We further developed a framework to overlay omics data on these sets and predict pathway usage for each metabolic task. We demonstrated how this approach can be used to quantify metabolic functions of diverse biological samples from the single cell to whole tissues and organs by using multiple transcriptomic datasets. To facilitate its adoption, we integrated the approach into GenePattern (www.genepattern.org-CellFie)