Rat IgG1 Isotype Control

Introduction: The pathophysiology and temporal dynamics of affected tissues in chronic rhinosinusitis (CRS) remain poorly understood. Here, we present a multiomics-based time-series assessment of nasal polyp biopsies from three patients with CRS, assessing natural variability over time and local response to systemic corticosteroid therapy. Methods: Polyp tissue biopsies were collected at three time points over two consecutive weeks. Patients were prescribed prednisone (30 mg daily) for 1 week between Collections 2 and 3. Polyp transcriptome, proteome, and microbiota were assessed via RNAseq, SWATH mass spectrometry, and 16S ribosomal RNA and ITS2 amplicon sequencing. Baseline interpatient variability, natural intrapatient variability over time, and local response to systemic corticosteroids, were investigated. Results: Overall, the highly abundant transcripts and proteins were associated with pathways involved in inflammation, FAS, cadherin, integrin, Wnt, apoptosis, and cytoskeletal signaling, as well as coagulation and B- and T-cell activation. Transcripts and proteins that naturally varied over time included those involved with inflammation- and epithelial-mesenchymal transition-related pathways, and a number of common candidate target biomarkers of CRS. Ten transcripts responded significantly to corticosteroid therapy, including downregulation of TNF, CCL20, and GSDMA, and upregulation of OVGP1, and PCDHGB1. Members of the bacterial genus Streptococcus positively correlated with immunoglobulin proteins IGKC and IGHG1. Conclusions: Understanding natural dynamics of CRS-associated tissues is essential to provide baseline context for all studies on putative biomarkers, mechanisms, and subtypes of CRS. These data further our understanding of the natural dynamics within nasal polypoid tissue, as well as local changes in response to systemic corticosteroid therapy.

Even though immunoglobulins are critical for immune responses and human survival, the diversity of the immunoglobulin heavy chain gene (IGH) is poorly known and mostly characterized only by serological methods. Moreover, this genomic region is not well-covered in genomic databases and genome-wide association studies due to particularities that impose technical difficulties for its analysis. Therefore, the IGH gene has never been systematically sequenced across populations. Here, we deliver an unprecedented and comprehensive characterization of the diversity of the IGHG1, IGHG2, and IGHG3 gene segments, which encode the constant region of the most abundant circulating immunoglobulins: IgG1, IgG2, and IgG3, respectively. We used Sanger sequencing to analyze 357 individuals from seven different Brazilian populations, including five Amerindian, one Japanese-descendant and one Euro-descendant population samples. We discovered 28 novel IGHG alleles and provided evidence that some of them may have been originated by gene conversion between common alleles of different gene segments. The rate of synonymous substitutions was significantly higher than the rate of the non-synonymous substitutions for IGHG1 and IGHG2 (p = 0.01 and 0.03, respectively), consistent with purifying selection. Fay and Wu's test showed significant negative values for most populations (p < 0.001), which indicates that positive selection in an adjacent position may be shaping IGHG variation by hitchhiking of variants in the vicinity, possibly the regions that encode the Ig variable regions. This study shows that the variation in the IGH gene is largely underestimated. Therefore, exploring its nucleotide diversity in populations may provide valuable information for comprehension of its evolution, its impact on diseases and vaccine research.