| 1. |
- Beal, Jacob, et al.
(författare)
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Robust estimation of bacterial cell count from optical density
- 2020
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Ingår i: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 3:1
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Tidskriftsartikel (refereegranskat)abstract
- Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data.
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| 2. |
- Christiansen, Colette, et al.
(författare)
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Adipose methylome integrative-omic analyses reveal genetic and dietary metabolic health drivers and insulin resistance classifiers
- 2022
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Ingår i: Genome Medicine. - : Springer Science and Business Media LLC. - 1756-994X. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: There is considerable evidence for the importance of the DNA methylome in metabolic health, for example, a robust methylation signature has been associated with body mass index (BMI). However, visceral fat (VF) mass accumulation is a greater risk factor for metabolic disease than BMI alone. In this study, we dissect the subcutaneous adipose tissue (SAT) methylome signature relevant to metabolic health by focusing on VF as the major risk factor of metabolic disease. We integrate results with genetic, blood methylation, SAT gene expression, blood metabolomic, dietary intake and metabolic phenotype data to assess and quantify genetic and environmental drivers of the identified signals, as well as their potential functional roles. Methods: Epigenome-wide association analyses were carried out to determine visceral fat mass-associated differentially methylated positions (VF-DMPs) in SAT samples from 538 TwinsUK participants. Validation and replication were performed in 333 individuals from 3 independent cohorts. To assess functional impacts of the VF-DMPs, the association between VF and gene expression was determined at the genes annotated to the VF-DMPs and an association analysis was carried out to determine whether methylation at the VF-DMPs is associated with gene expression. Further epigenetic analyses were carried out to compare methylation levels at the VF-DMPs as the response variables and a range of different metabolic health phenotypes including android:gynoid fat ratio (AGR), lipids, blood metabolomic profiles, insulin resistance, T2D and dietary intake variables. The results from all analyses were integrated to identify signals that exhibit altered SAT function and have strong relevance to metabolic health. Results: We identified 1181 CpG positions in 788 genes to be differentially methylated with VF (VF-DMPs) with significant enrichment in the insulin signalling pathway. Follow-up cross-omic analysis of VF-DMPs integrating genetics, gene expression, metabolomics, diet, and metabolic traits highlighted VF-DMPs located in 9 genes with strong relevance to metabolic disease mechanisms, with replication of signals in FASN, SREBF1, TAGLN2, PC and CFAP410. PC methylation showed evidence for mediating effects of diet on VF. FASN DNA methylation exhibited putative causal effects on VF that were also strongly associated with insulin resistance and methylation levels in FASN better classified insulin resistance (AUC=0.91) than BMI or VF alone. Conclusions: Our findings help characterise the adiposity-associated methylation signature of SAT, with insights for metabolic disease risk.
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