Table_1_Investigating the mechanism of rough phenotype in a naturally attenuated Brucella strain: insights from whole genome sequencing.XLSX

ObjectiveBrucellosis, a significant zoonotic disease, not only impacts animal health but also profoundly influences the host immune responses through gut microbiome. Our research focuses on whole genome sequencing and comparative genomic analysis of these Brucella strains to understand the mechanisms of their virulence changes that may deepen our comprehension of the host immune dysregulation.MethodsThe Brucella melitensis strain CMCC55210 and its naturally attenuated variant CMCC55210a were used as models. Biochemical identification tests and in vivo experiments in mice verified the characteristics of the strain. To understand the mechanism of attenuation, we then performed de novo sequencing of these two strains.ResultsWe discovered notable genomic differences between the two strains, with a key single nucleotide polymorphism (SNP) mutation in the manB gene potentially altering lipopolysaccharide (LPS) structure and influencing host immunity to the pathogen. This mutation might contribute to the attenuated strain's altered impact on the host's macrophage immune response, overing insights into the mechanisms of immune dysregulation linked to intracellular survival. Furthermore, we explore that manipulating the Type I restriction-modification system in Brucella can significantly impact its genome stability with the DNA damage response, consequently affecting the host's immune system.ConclusionThis study not only contributes to understanding the complex relationship between pathogens, and the immune system but also opens avenues for innovative therapeutic interventions in inflammatory diseases driven by microbial and immune dysregulation.</p

The tendencies of Treg cells in PBMC after a single DFPP.

<p>A-D. Treg cell was expressed as CD4+CD25+ CD127^low/−cells in PBMC. E, F. The frequency of CD4+CD25+ Treg cells in MHD patients with CHC during the DFPP. G, H. The frequencies of CD4+CD25+ CD127^low/− Treg cells in MHD patients with CHC during the DFPP</p

The characteristics of MHD patients without and with CHC.

<p> P<0.05.</p

The percentages of NK cells in PBMC after the DFPP.

<p>A, B. NK cell was expressed as CD3–CD16+CD56+ cells in PBMCs. C. The frequencies of NK cells in MHD patients with CHC compared to those without CHC. D. The frequencies of NK cells in MHD patients with CHC during the DFPP.</p

The frequencies of monocytes in PBMC after a single DFPP.

<p>A, B. Monocyte was expressed as CD14+ cells in PBMCs. C. The frequencies of monocytes in MHD patients with CHC compared to those without CHC. D. The frequencies of monocytes in MHD patients with CHC during the DFPP.</p

The changes of Th17 cells in PBMC after the DFPP.

<p>A-C. Th17 cell was expressed as CD17+CD4+ cells in PBMC. D. The frequency of Th17 cells in MHD patients with CHC compared to those without CHC. E. The frequencies of Th17 cells in MHD patients with CHC during the DFPP.</p

The tendencies of Th1 and Th2 cells in PBMC after the DFPP.

<p>A-D. Th1 cells was expressed as IFN-γ+CD4+ cells; Th2 cells was expressed as IL-4+CD4+ cells. E, F The frequencies of Th1 cells in MHD patients with CHC during the DFPP. G, H The frequencies of Th2 cells in MHD patients with CHC during the DFPP. I, J The ratio of Th1 to Th2 cells in MHD patients with CHC.</p

The effects of different dialysis modes on clearance of circulatory mtDNA.

<p>A. The effect of LF-HD on plasma mtDNA. B. The effect of HF-HD on plasma mtDNA. C. The effect of OL-HDF on plasma mtDNA. * P<0.05.</p

Three different dialysis systems, LF-HD, HF-HD and HF were established in vitro.

<p>A. The schematic diagram of LF-HD and HF-HD in vitro. B. The schematic diagram of HF in vitro.</p

mtDNA absorbed by the dialyzer or filter in the simulated dialysis systems.

<p>A. The concentration of mtDNA in eluent of dialyzers. B. The quantity of mtDNA per fiber after soaked overnight by tissue lysis buffer. * P<0.05.</p