Publications

BACKGROUND

Chronic human immunodeficiency virus (HIV) infection is associated with intestinal permeability and microbial translocation that contributes to systemic immune activation, which is an independent predictor of HIV disease progression. The association of microbial translocation with clinical outcome remains unknown.

METHODS

This nested case-control study included 74 subjects who died, 120 of whom developed cardiovascular disease and 81 of whom developed AIDS during the Strategies for Management of Anti-Retroviral Therapy (SMART) study with matched control subjects. Intestinal fatty acid binding protein (I-FABP), lipopolysaccharide (LPS), soluble CD14 (sCD14), endotoxin core antibody (EndoCAb), and 16S ribosomal DNA (rDNA) were measured in baseline plasma samples.

RESULTS

Subjects with the highest quartile of sCD14 levels had a 6-fold higher risk of death than did those in the lowest quartile (95% confidence interval, 2.2-16.1; P<.001), with minimal change after adjustment for inflammatory markers, CD4(+) T cell count, and HIV RNA level. No other marker was significantly associated with clinical outcomes. I-FABP, LPS, and sCD14 were increased and EndoCAb was decreased in study subjects, compared with healthy volunteers. sCD14 level correlated with levels of IL-6, C-reactive protein, serum amyloid A and D-dimer.

CONCLUSIONS

sCD14, a marker of monocyte response to LPS, is an independent predictor of mortality in HIV infection. Therapeutic attenuation of innate immune activation may improve survival in patients with HIV infection.

Ly49 receptors in rodents, like KIRs in humans, regulate NK cell activity. Although inhibitory Ly49 receptors clearly recognize MHC-I molecules, ligands for the activating Ly49 receptors are less well defined. Here, we show that the activating Ly49s4 and the inhibitory Ly49i4 receptors recognize nonclassical MHC-I molecules on the rat macrophage cell line R2 (RT1(d)). Listeria infection of R2 macrophages led to increased expression of classical and nonclassical MHC-I molecules. Coincubation of these infected cells with reporter cells expressing Ly49i4 or Ly49s4 increased the reporter cell responses. These responses were blocked by mAb OX18 (anti-MHC-I) and AAS1 (anti-nonclassical MHC-I). IFN-γ treatment of normal R2 cells also increased the MHC-I expression and enhanced the reporter cell responses. These results suggest that activating and inhibitory Ly49 receptors monitor MHC-I expression on Listeria-infected cells.

BACKGROUND

The immune system behaves like a complex, dynamic network with interacting elements including leukocytes, cytokines, and chemokines. While the immune system is broadly distributed, leukocytes must communicate effectively to respond to a pathological challenge. The Basic Immune Simulator 2010 contains agents representing leukocytes and tissue cells, signals representing cytokines, chemokines, and pathogens, and virtual spaces representing organ tissue, lymphoid tissue, and blood. Agents interact dynamically in the compartments in response to infection of the virtual tissue. Agent behavior is imposed by logical rules derived from the scientific literature. The model captured the agent-to-agent contact history, and from this the network topology and the interactions resulting in successful versus failed viral clearance were identified. This model served to integrate existing knowledge and allowed us to examine the immune response from a novel perspective directed at exploiting complex dynamics, ultimately for the design of therapeutic interventions.

RESULTS

Analyzing the evolution of agent-agent interactions at incremental time points from identical initial conditions revealed novel features of immune communication associated with successful and failed outcomes. There were fewer contacts between agents for simulations ending in viral elimination (win) versus persistent infection (loss), due to the removal of infected agents. However, early cellular interactions preceded successful clearance of infection. Specifically, more Dendritic Agent interactions with TCell and BCell Agents, and more BCell Agent interactions with TCell Agents early in the simulation were associated with the immune win outcome. The Dendritic Agents greatly influenced the outcome, confirming them as hub agents of the immune network. In addition, unexpectedly high frequencies of Dendritic Agent-self interactions occurred in the lymphoid compartment late in the loss outcomes.

CONCLUSIONS

An agent-based model capturing several key aspects of complex system dynamics was used to study the emergent properties of the immune response to viral infection. Specific patterns of interactions between leukocyte agents occurring early in the response significantly improved outcome. More interactions at later stages correlated with persistent inflammation and infection. These simulation experiments highlight the importance of commonly overlooked aspects of the immune response and provide insight into these processes at a resolution level exceeding the capabilities of current laboratory technologies.