Cell-Free Microbial DNA Analysis: Effects of Blood Plasma and Serum Quantity, Biobanking Protocols, and Isolation Kits.

Recent studies highlight the presence of bacterial sequences in the human blood, suggesting potential clinical significance for circulating microbial signatures. These sequences could presumably serve in the diagnosis, prediction, or monitoring of various health conditions. Ensuring the similarity of samples before bacterial analysis is crucial, especially when combining samples from different biobanks prepared under varying conditions (such as different DNA extraction kits, centrifugation conditions, blood collection tubes, etc.). In this study, we aimed to analyze the impact of different sample collection and nucleic acid extraction criteria (blood collection tube, centrifugation, input volume, and DNA extraction kit) on circulating bacterial composition. Blood samples from four healthy individuals were collected into three different sample collection tubes: K2EDTA plasma tube, sodium citrate plasma tube, and gel tube for blood serum. Tubes were centrifugated at standard and double centrifugation conditions. DNA extraction was performed using 100, 200, and 500 µL plasma/serum input volumes. DNA extraction was performed using three different isolation kits: Norgen plasma/serum cell-free circulating DNA purification micro kit, Applied Biosystems MagMAX cell-free DNA isolation kit, and Qiagen QIAamp MinElute cell-free circulating DNA mini kit. All samples were subjected to 16S rRNA V1-V2 library preparation and sequencing. In total, 216 DNA and 18 water control samples were included in the study. According to PERMANOVA, PCoA, Mann-Whitney, and FDR tests the effect of the DNA extraction kit on the microbiota composition was the greatest, whereas the type of blood collection tube, centrifugation type, and sample input volume for the extraction had minor effects. Samples extracted with the Norgen DNA extraction kit were enriched with Gram-negative bacteria, whereas samples extracted with the Qiagen and MagMAX kits were enriched with Gram-positive bacteria. Bacterial profiles of samples prepared with the Qiagen and MagMAX DNA extraction kits were more similar, whereas samples prepared with the Norgen DNA extraction kit were significantly different from other groups.

Association of CX36 Protein Encoding Gene GJD2 with Refractive Errors.

Purpose: This study aimed to evaluate the associations of GJD2 (rs634990, rs524952) and RASGRF1 (rs8027411, rs4778879, rs28412916) gene polymorphisms with refractive errors. Methods: The study included 373 subjects with refractive errors (48 myopia, 239 myopia with astigmatism, 14 hyperopia, and 72 hyperopia with astigmatism patients) and 104 ophthalmologically healthy subjects in the control group. A quantitative real-time polymerase chain reaction (qPCR) method was chosen for genotyping. Statistical calculations and analysis of results were performed with IBM SPSS Statistics 27 software. Results: The correlations in monozygotic (MZ) twin pairs were higher compared to DZ pairs, indicating genetic effects on hyperopia and astigmatism. The heritability (h2) of hyperopia and astigmatism was 0.654 for the right eye and 0.492 for the left eye. The GJD2 rs634990 TT genotype increased the incidence of hyperopia with astigmatism by 2.4-fold and the CT genotype decreased the incidence of hyperopia with astigmatism by 0.51-fold (p < 0.05). The GJD2 rs524952 AT genotype reduced the incidence of hyperopia with astigmatism by 0.53-fold (p < 0.05). Haplotype analysis of SNPs in the GJD2 gene revealed two statistically significant haplotypes: ACTAGG for rs634990 and TTTAGA for rs524952, which statistically significantly reduced the incidence of hyperopia and hyperopia with astigmatism by 0.41-fold (95% CI: 0.220−0.765) and 0.383-fold (95% CI: 0.199−0.737), respectively (p < 0.05). It was also found that, in the presence of haplotypes ACTAGG for rs634990 and TATAGA for rs524952, the possibility of hyperopia was reduced by 0.4-fold (p < 0.05). Conclusions: the heritability of hyperopia and hyperopia with astigmatism was 0.654−0.492, according to different eyes in patients between 20 and 40 years. The GJD2 rs634990 was identified as an SNP, which has significant associations with the co-occurrence of hyperopia and astigmatism. Patients with the GJD2 gene rs634990 TT genotype were found to have a 2.4-fold higher risk of develop hyperopia with astigmatism.