Biomass composition: the "elephant in the room" of metabolic modelling.
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ABSTRACT:
SUBMITTER: Dikicioglu D
PROVIDER: S-EPMC4605984 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Genome-scale metabolic modeling is an important tool in the study of metabolism by enhancing the collation of knowledge, interpretation of data, and prediction of metabolic capabilities. A frequent assumption in the use of genome-scale models is that the in vivo organism is evolved for optimal growth, where growth is represented by flux through a biomass objective function (BOF). While the specific composition of the BOF is crucial, its formulation is often inherited from similar organisms due to the experimental challenges associated with its proper determination. A cell's macro-molecular composition is not fixed and it responds to changes in environmental conditions. As a consequence, initiatives for the high-fidelity determination of cellular biomass composition have been launched. Thus, there is a need for a mathematical and computational framework capable of using multiple measurements of cellular biomass composition in different environments. Here, we propose two different computational approaches for directly addressing this challenge: Biomass Trade-off Weighting (BTW) and Higher-dimensional-plane InterPolation (HIP). In lieu of experimental data on biomass composition-variation in response to changing nutrient environment, we assess the properties of BTW and HIP using three hypothetical, yet biologically plausible, BOFs for the Escherichia coli genome-scale metabolic model iML1515. We find that the BTW and HIP formulations have a significant impact on model performance and phenotypes. Furthermore, the BTW method generates larger growth rates in all environments when compared to HIP. Using acetate secretion and the respiratory quotient as proxies for phenotypic changes, we find marked differences between the methods as HIP generates BOFs more similar to a reference BOF than BTW. We conclude that the presented methods constitute a conceptual step in developing genome-scale metabolic modelling approaches capable of addressing the inherent dependence of cellular biomass composition on nutrient environments.
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Project description:Genome-scale metabolic models (GEMs) are mathematical representations of metabolism that allow for in silico simulation of metabolic phenotypes and capabilities. A prerequisite for these predictions is an accurate representation of the biomolecular composition of the cell necessary for replication and growth, implemented in GEMs as the so-called biomass objective function (BOF). The BOF contains the metabolic precursors required for synthesis of the cellular macro- and micromolecular constituents (e.g. protein, RNA, DNA), and its composition is highly dependent on the particular organism, strain, and growth condition. Despite its critical role, the BOF is rarely constructed using specific measurements of the modeled organism, drawing the validity of this approach into question. Thus, there is a need to establish robust and reliable protocols for experimental condition-specific biomass determination. Here, we address this challenge by presenting a general pipeline for biomass quantification, evaluating its performance on Escherichia coli K-12 MG1655 sampled during balanced exponential growth under controlled conditions in a batch-fermentor set-up. We significantly improve both the coverage and molecular resolution compared to previously published workflows, quantifying 91.6% of the biomass. Our measurements display great correspondence with previously reported measurements, and we were also able to detect subtle characteristics specific to the particular E. coli strain. Using the modified E. coli GEM iML1515a, we compare the feasible flux ranges of our experimentally determined BOF with the original BOF, finding that the changes in BOF coefficients considerably affect the attainable fluxes at the genome-scale.
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Project description:Many tumors sustain elevated levels of reactive oxygen species (ROS), which drive oncogenic signaling. However, ROS can also trigger anti-tumor responses, such as cell death or senescence, through induction of oxidative stress and concomitant DNA damage. To circumvent the adverse consequences of elevated ROS levels, many tumors develop adaptive responses, such as enhanced redox-protective or oxidatively-generated damage repair pathways. Targeting these enhanced oxidative stress-protective mechanisms is likely to be both therapeutically effective and highly specific to cancer, as normal cells are less reliant on such mechanisms. In this review, we discuss one such stress-protective protein human MutT Homolog1 (MTH1), an enzyme that eliminates 8-oxo-7,8-dihydro-2'-deoxyguanosine triphosphate (8-oxodGTP) through its pyrophosphatase activity, and is found to be elevated in many cancers. Our studies, and subsequently those of others, identified MTH1 inhibition as an effective tumor-suppressive strategy. However, recent studies with the first wave of MTH1 inhibitors have produced conflicting results regarding their cytotoxicity in cancer cells and have led to questions regarding the validity of MTH1 as a chemotherapeutic target. To address the proverbial "elephant in the room" as to whether MTH1 is a bona fide chemotherapeutic target, we provide an overview of MTH1 function in the context of tumor biology, summarize the current literature on MTH1 inhibitors, and discuss the molecular contexts likely required for its efficacy as a therapeutic target.
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| S-EPMC7991835 | biostudies-literature
Project description:Macroalgae form the most extensive and productive benthic marine vegetated habitats globally but their inclusion in Blue Carbon (BC) strategies remains controversial. We review the arguments offered to reject or include macroalgae in the BC framework, and identify the challenges that have precluded macroalgae from being incorporated so far. Evidence that macroalgae support significant carbon burial is compelling. The carbon they supply to sediment stocks in angiosperm BC habitats is already included in current assessments, so that macroalgae are de facto recognized as important donors of BC. The key challenges are (i) documenting macroalgal carbon sequestered beyond BC habitat, (ii) tracing it back to source habitats, and (iii) showing that management actions at the habitat lead to increased sequestration at the sink site. These challenges apply equally to carbon exported from BC coastal habitats. Because of the large carbon sink they support, incorporation of macroalgae into BC accounting and actions is an imperative. This requires a paradigm shift in accounting procedures as well as developing methods to enable the capacity to trace carbon from donor to sink habitats in the ocean.
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Project description:The first prospective population-based study to examine risk of erectile dysfunction in men with gout in the western world has been published. It reports that following their first diagnosis of gout, men have a 31% higher risk of erectile dysfunction than matched controls, although the absolute increase in risk is small. Of interest, the incidence of erectile dysfunction reported in this study is tenfold higher than those reported in nation-wide cohort studies from Taiwan. There is a need for further prospective cohort studies to examine the possible mechanistic association between gout, hyperuricaemia and erectile dysfunction.
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Project description:BACKGROUND:Elephant grass [Cenchrus purpureus (Schumach.) Morrone] is used for bioenergy and animal feed. In order to identify candidate genes that could be exploited for marker-assisted selection in elephant grass, this study aimed to investigate changes in predictive accuracy using genomic relationship information and simple sequence repeats for eight traits (height, green biomass, dry biomass, acid and neutral detergent fiber, lignin content, biomass digestibility, and dry matter concentration) linked to bioenergetics and animal feeding. RESULTS:We used single-step, genome-based best linear unbiased prediction and genome association methods to investigate changes in predictive accuracy and find candidate genes using genomic relationship information. Genetic variability (p < 0.05) was detected for most of the traits evaluated. In general, the overall means for the traits varied widely over the cuttings, which was corroborated by a significant genotype by cutting interaction. Knowing the genomic relationships increased the predictive accuracy of the biomass quality traits. We found that one marker (M28_161) was significantly associated with high values of biomass digestibility. The marker had moderate linkage disequilibrium with another marker (M35_202) that, in general, was detected in genotypes with low values of biomass digestibility. In silico analysis revealed that both markers have orthologous regions in other C4 grasses such as Setaria viridis, Panicum hallii, and Panicum virgatum, and these regions are located close to candidate genes involved in the biosynthesis of cell wall molecules (xyloglucan and lignin), which support their association with biomass digestibility. CONCLUSIONS:The markers and candidate genes identified here are useful for breeding programs aimed at changing biomass digestibility in elephant grass. These markers can be used in marker-assisted selection to grow elephant grass cultivars for different uses, e.g., bioenergy production, bio-based products, co-products, bioactive compounds, and animal feed.
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Project description:Radiocarbon (14C) analysis of skeletal remains by accelerator mass spectrometry is an essential tool in multiple branches of science. However, bone 14C dating results can be inconsistent and not comparable due to disparate laboratory pretreatment protocols that remove contamination. And, pretreatments are rarely discussed or reported by end-users, making it an 'elephant in the room' for Quaternary scientists. Through a questionnaire survey, I quantified consensus on the reliability of collagen pretreatments for 14C dating across 132 experts (25 countries). I discovered that while more than 95% of the audience was wary of contamination and would avoid gelatinization alone (minimum pretreatment used by most 14C facilities), 52% asked laboratories to choose the pretreatment method for them, and 58% could not rank the reliability of at least one pretreatment. Ultrafiltration was highly popular, and purification by XAD resins seemed restricted to American researchers. Isolating and dating the amino acid hydroxyproline was perceived as the most reliable pretreatment, but is expensive, time-consuming and not widely available. Solid evidence supports that only molecular-level dating accommodates all known bone contaminants and guarantees complete removal of humic and fulvic acids and conservation substances, with three key areas of progress: (i) innovation and more funded research is required to develop affordable analytical chemistry that can handle low-mass samples of collagen amino acids, (ii) a certification agency overseeing dating-quality control is needed to enhance methodological reproducibility and dating accuracy among laboratories, and (iii) more cross-disciplinary work with better 14C reporting etiquette will promote the integration of 14C dating across disciplines. Those developments could conclude long-standing debates based on low-accuracy data used to build chronologies for animal domestications, human/megafauna extirpations and migrations, archaeology, palaeoecology, palaeontology and palaeoclimate models.
| S-EPMC7890471 | biostudies-literature