Robust estimation of bacterial cell count from optical density

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

Association between childhood conditions and arthritis among middle-aged and older adults in China: the China Health and Retirement Longitudinal Study

10.1017/s0144686x20000343Ageing and Society1-1

Variations in pleural microbiota and metabolic phenotype associated with malignant pleural effusion in human lung adenocarcinoma

Abstract Background Lung cancer is the most common cancer‐related death worldwide. In 2022, the number of daily deaths of lung cancer was estimated to reach around 350 in the United States. Lung adenocarcinoma is the main subtype of lung cancer and patients with malignant pleural effusion (MPE) suffer from poor prognosis. Microbiota and its metabolites are associated with cancer progression. However, the effect of pleural microbiota on pleural metabolic profile of MPE in lung adenocarcinoma patients remains largely unknown. Methods Pleural effusion samples collected from lung adenocarcinoma patients with MPE (n = 14) and tuberculosis pleurisy patients with benign pleural effusion (BPE group, n = 10) were subjected to microbiome (16S rRNA gene sequencing) and metabolome (liquid chromatography tandem mass spectrometry [LC‐MS/MS]) analyses. The datasets were analyzed individually and integrated for combined analysis using various bioinformatic approaches. Results The metabolic profile of MPE in lung adenocarcinoma patients were clearly distinguished from BPE with 121 differential metabolites across six significantly enriched pathways identified. Glycerophospholipids, fatty and carboxylic acids, and derivatives were the most common differential metabolites. Sequencing of microbial data revealed nine significantly enriched genera (i.e., Staphylococcus, Streptococcus, Lactobacillus) and 26 enriched ASVs (i.e., species Lactobacillus_delbrueckii) in MPE. Integrated analysis correlated MPE‐associated microbes with metabolites, such as phosphatidylcholine and metabolites involved in the citrate cycle pathway. Conclusion Our results provide substantial evidence of a novel interplay between the pleural microbiota and metabolome, which was drastically perturbed in MPE in lung adenocarcinoma patients. Microbe‐associated metabolites can be used for further therapeutic explorations