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

Multi ’omics integration of the HIV airway epithelium : integration of the microbiome, transcriptome and methylome

RATIONALE: People living with HIV (PLWH) appear to have increased proneness to chronic obstructive pulmonary disease (COPD) independent of their cigarette smoke exposure. Previous studies have shown that HIV infection is associated with changes in the airway microbiome and host response, however, the exact mechanism of disease progression is still unknown. We hypothesize that airway epithelial dysbiosis in PLWH increases the susceptibility to COPD in this group. METHODS: Airway epithelial cell brushings were obtained from 18 COPD+HIV+,16 COPD-HIV+, 22 COPD+HIV- and 20 COPD-HIV- subjects. Microbiome, methylation, and transcriptome profiles were measured using 16s amplicon sequencing (Illumina Miseq®), Illumina Infinium Methylation EPIC chip®, and RNA sequencing (NovaSeq6000®), respectively. Microbiome analysis was performed using QIIME 2™, and transcriptome and methylation analyses were performed using R language. The three datasets were integrated using Data Integration Analysis for Biomarker discovery using Latent cOmponents (DIABLO) implemented in the mixOmics R package. Fifty repeats of 10-fold cross-validations and a correlation threshold of 0.7 were set to determine key interactions between bacterial ASVs, CpG methylation sites, and gene transcripts amongst the subjects based on their COPD, HIV, and combined COPD and HIV statuses. RESULTS: The microbiome analysis identified that the groups most associated with disease (COPD+, HIV+, and COPD+HIV+ groups) had reduced alpha diversity (Shannon Diversity Index p=0.0013, p=0023, and p=0.0002, respectively), and significantly disrupted microbial communities (Bray Curtis PERMANOVA p=0.001, p=0.007 and p=0.001, respectively) compared to their relatively ”healthy” counterparts. This was accompanied by changes in the host transcriptome and epigenome, our analysis of which identified top genes and CpG sites that were differentially regulated in patients with COPD and/or HIV. Integration of the three -omes identified features that were correlated with one another at a threshold>0.70. On combining the COPD and HIV statuses of subjects, the multiomic integration identified correlations between the bacterial ASV Bacteroidetes Prevotella and transcriptomic features FUZ, FASTKD3, and ACVR1B, and epigenetic features CpG-FUZ and CpG-PHLDB3. It may be that these features together influence host pathways regulating mucociliary clearance, respiration and energy, cell cycle, and immunity.Medicine, Faculty ofExperimental Medicine, Division ofGraduat

Microbial dysbiosis and the host airway epithelial response: insights into HIV-associated COPD using multi’omics profiling

Abstract Background People living with HIV (PLWH) are at increased risk of developing Chronic Obstructive Pulmonary Disease (COPD) independent of cigarette smoking. We hypothesized that dysbiosis in PLWH is associated with epigenetic and transcriptomic disruptions in the airway epithelium. Methods Airway epithelial brushings were collected from 18 COPD + HIV + , 16 COPD − HIV + , 22 COPD + HIV − and 20 COPD – HIV − subjects. The microbiome, methylome, and transcriptome were profiled using 16S sequencing, Illumina Infinium Methylation EPIC chip, and RNA sequencing, respectively. Multi ‘omic integration was performed using Data Integration Analysis for Biomarker discovery using Latent cOmponents. A correlation > 0.7 was used to identify key interactions between the ’omes. Results The COPD + HIV −, COPD −HIV + , and COPD + HIV + groups had reduced Shannon Diversity (p = 0.004, p = 0.023, and p = 5.5e−06, respectively) compared to individuals with neither COPD nor HIV, with the COPD + HIV + group demonstrating the most reduced diversity. Microbial communities were significantly different between the four groups (p = 0.001). Multi ‘omic integration identified correlations between Bacteroidetes Prevotella, genes FUZ, FASTKD3, and ACVR1B, and epigenetic features CpG-FUZ and CpG-PHLDB3. Conclusion PLWH with COPD manifest decreased diversity and altered microbial communities in their airway epithelial microbiome. The reduction in Prevotella in this group was linked with epigenetic and transcriptomic disruptions in host genes including FUZ, FASTKD3, and ACVR1B