| 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. |
- Fang, Qinghua, et al.
(författare)
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Comparative Analysis on Abnormal Methylome of Differentially Expressed Genes and Disease Pathways in the Immune Cells of RA and SLE
- 2021
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Ingår i: Frontiers in Immunology. - : Frontiers Media SA. - 1664-3224. ; 12
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Tidskriftsartikel (refereegranskat)abstract
- We identified abnormally methylated, differentially expressed genes (DEGs) and pathogenic mechanisms in different immune cells of RA and SLE by comprehensive bioinformatics analysis. Six microarray data sets of each immune cell (CD19+ B cells, CD4+ T cells and CD14+ monocytes) were integrated to screen DEGs and differentially methylated genes by using R package "limma." Gene ontology annotations and KEGG analysis of aberrant methylome of DEGs were done using DAVID online database. Protein-protein interaction (PPI) network was generated to detect the hub genes and their methylation levels were compared using DiseaseMeth 2.0 database. Aberrantly methylated DEGs in CD19+ B cells (173 and 180), CD4+ T cells (184 and 417) and CD14+ monocytes (193 and 392) of RA and SLE patients were identified. We detected 30 hub genes in different immune cells of RA and SLE and confirmed their expression using FACS sorted immune cells by qPCR. Among them, 12 genes (BPTF, PHC2, JUN, KRAS, PTEN, FGFR2, ALB, SERB-1, SKP2, TUBA1A, IMP3, and SMAD4) of RA and 12 genes (OAS1, RSAD2, OASL, IFIT3, OAS2, IFIH1, CENPE, TOP2A, PBK, KIF11, IFIT1, and ISG15) of SLE are proposed as potential biomarker genes based on receiver operating curve analysis. Our study suggests that MAPK signaling pathway could potentially differentiate the mechanisms affecting T- and B- cells in RA, whereas PI3K pathway may be used for exploring common disease pathways between RA and SLE. Compared to individual data analyses, more dependable and precise filtering of results can be achieved by integrating several relevant data sets.
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