Kinetics of Salmonella typhimurium binding with antibody by immunoassays using a surface plasmon resonance biosensor

Subtractive Inhibition Assay Based on PagN-Specific Monoclonal Antibody for the Detection of Salmonella Using Surface Plasmon Resonance

Salmonella is a common foodborne zoonotic pathogen that poses a great threat to human health and breeding industry. The rapid detection of Salmonella is necessary for early prevention and control. In this study, a subtractive inhibition assay (SIA) based on surface plasmon resonance (SPR) for the rapid detection of Salmonella was developed. Mouse-specific monoclonal antibody 3B3 against Salmonella membrane protein PagN was first incubated with Salmonella. The unbound free antibody was separated using a sequential process of centrifugation and then detected using an immobilized goat anti-mouse immunoglobulin G polyclonal antibody on the SPR sensor chip. This SIA-SPR method showed excellent sensitivity for Salmonella with a limit of detection of about 300 CFU mL-1. This method is sensitive to different serotypes of Salmonella strains but not for non-Salmonella strains. It was able to detect Salmonella in the contaminated water and milk powder at less than 102 and 103 CFU mL-1, respectively, which was consistent with the bacterial plate count results. In addition, this method could be used to evaluate the lysis effect of phages on bacteria. Since the culturing detection method needs more than 48 h, this method has the potential for the rapid and sensitive clinical detection of Salmonella. For our knowledge, this is the first report for Salmonella detection using SIA-SPR method.

An Agent-Based Model of a Hepatic Inflammatory Response to Salmonella: A Computational Study under a Large Set of Experimental Data

We present an agent-based model (ABM) to simulate a hepatic inflammatory response (HIR) in a mouse infected by Salmonella that sometimes progressed to problematic proportions, known as "sepsis". Based on over 200 published studies, this ABM describes interactions among 21 cells or cytokines and incorporates 226 experimental data sets and/or data estimates from those reports to simulate a mouse HIR in silico. Our simulated results reproduced dynamic patterns of HIR reported in the literature. As shown in vivo, our model also demonstrated that sepsis was highly related to the initial Salmonella dose and the presence of components of the adaptive immune system. We determined that high mobility group box-1, C-reactive protein, and the interleukin-10: tumor necrosis factor-α ratio, and CD4+ T cell: CD8+ T cell ratio, all recognized as biomarkers during HIR, significantly correlated with outcomes of HIR. During therapy-directed silico simulations, our results demonstrated that anti-agent intervention impacted the survival rates of septic individuals in a time-dependent manner. By specifying the infected species, source of infection, and site of infection, this ABM enabled us to reproduce the kinetics of several essential indicators during a HIR, observe distinct dynamic patterns that are manifested during HIR, and allowed us to test proposed therapy-directed treatments. Although limitation still exists, this ABM is a step forward because it links underlying biological processes to computational simulation and was validated through a series of comparisons between the simulated results and experimental studies.

Mathematical Model of Innate and Adaptive Immunity of Sepsis: A Modeling and Simulation Study of Infectious Disease

Sepsis is a systemic inflammatory response (SIR) to infection. In this work, a system dynamics mathematical model (SDMM) is examined to describe the basic components of SIR and sepsis progression. Both innate and adaptive immunities are included, and simulated results in silico have shown that adaptive immunity has significant impacts on the outcomes of sepsis progression. Further investigation has found that the intervention timing, intensity of anti-inflammatory cytokines, and initial pathogen load are highly predictive of outcomes of a sepsis episode. Sensitivity and stability analysis were carried out using bifurcation analysis to explore system stability with various initial and boundary conditions. The stability analysis suggested that the system could diverge at an unstable equilibrium after perturbations if r_t2max (maximum release rate of Tumor Necrosis Factor- (TNF-) α by neutrophil) falls below a certain level. This finding conforms to clinical findings and existing literature regarding the lack of efficacy of anti-TNF antibody therapy.