Development of an Automated Online Flow Cytometry Method to Quantify Cell Density and Fingerprint Bacterial Communities

Cell density is an important factor in all microbiome research, where interactions are of interest. It is also the most important parameter for the operation and control of most biotechnological processes. In the past, cell density determination was often performed offline and manually, resulting in a delay between sampling and immediate data processing, preventing quick action. While there are now some online methods for rapid and automated cell density determination, they are unable to distinguish between the different cell types in bacterial communities. To address this gap, an online automated flow cytometry procedure is proposed for real-time high-resolution analysis of bacterial communities. On the one hand, it allows for the online automated calculation of cell concentrations and, on the other, for the differentiation between different cell subsets of a bacterial community. To achieve this, the OC-300 automation device (onCyt Microbiology, Zürich, Switzerland) was coupled with the flow cytometer CytoFLEX (Beckman Coulter, Brea, USA). The OC-300 performs the automatic sampling, dilution, fixation and 4',6-diamidino-2-phenylindole (DAPI) staining of a bacterial sample before sending it to the CytoFLEX for measurement. It is demonstrated that this method can reproducibly measure both cell density and fingerprint-like patterns of bacterial communities, generating suitable data for powerful automated data analysis and interpretation pipelines. In particular, the automated, high-resolution partitioning of clustered data into cell subsets opens up the possibility of correlation analysis to identify the operational or abiotic/biotic causes of community disturbances or state changes, which can influence the interaction potential of organisms in microbiomes or even affect the performance of individual organisms.

Smoking Modifies the Genetic Risk for Early-Onset Periodontitis

Periodontitis has low-prevalence, highly severe disease manifestations with an early onset and rapid progression. The diagnosis is based on severe destruction of the alveolar bone in adolescents and young adults. Genetic susceptibility variants and smoking are well-established risk factors, but their interactions in modifying disease susceptibility have not been studied. We aimed to identify genetic risk variants of early-onset periodontitis that unmask their effects on tobacco smoke exposure. To this end, we analyzed 79,780,573 common variants in 741 northwest Europeans diagnosed to have >30% bone loss at >2 teeth before 35 y of age, using imputed genotypes of the OmniExpress BeadChip. Never versus ever smokers were compared in a logistic regression analysis via a case-only approach. To explore the effect of tobacco smoke on the expression of the G×S-associated genes, cultures of primary gingival fibroblasts ( n = 9) were exposed to cigarette smoke extract, and transcripts were quantified by reverse transcription polymerase chain reaction. We identified 16 loci for which our analysis suggested an association with G×S increased disease risk ( P < 5 × 10−5). Nine loci had previously been reported to be associated with spirometric measures of pulmonary function by an earlier G×S genome-wide association study. Genome-wide significant cis expression quantitative trait loci were reported for G×S-associated single-nucleotide polymorphisms at ST8SIA1 and SOST, indicating a causal role of these genes in tobacco-related etiopathology. Notably, SOST is a negative regulator of bone growth, and ST8SIA1 has a role in tissue remodeling. Cigarette smoke extract significantly altered the expression of 2 associated genes: SSH1 ( P = 5 × 10−07), which is required for NF-κB activation and innate immune responses to bacterial invasion, and ST8SIA1 ( P = 0.0048). We conclude that the genetic predisposition to early-onset periodontitis is in part triggered by smoking and that tobacco smoke directly affects the expression of genes involved in bone homeostasis, tissue repair, and immune response.