Lymphotoxins (LT alpha and LT beta), LIGHT [homologous to LT, inducible expression, competes with herpes simplex virus (HSV) glycoprotein D for HSV entry mediator (HVEM), a receptor expressed on T lymphocytes], tumor necrosis factor (TNF), and their specific receptors LT beta R, HVEM, and TNF receptor 1 (TNFR1) and TNFR2, form the immediate family of the larger TNF superfamily. These cytokines establish a critical communication system required for the development of secondary lymphoid tissues; however, knowledge of the target genes activated by these signaling pathways is limited. Target genes regulated by the LT alpha beta-LT beta R pathway include the tissue-organizing chemokines, CXCL13, CCL19, and CCL21, which establish cytokine circuits that regulate LT expression on lymphocytes, leading to organized lymphoid tissue. Infectious disease models have revealed that LT alpha beta pathways are also important for innate and adaptive immune responses involved in host defense. Here, regulation of interferon-beta by LT beta R and TNFR signaling may play a crucial role in certain viral infections. Regulation of autoimmune regulator in the thymus via LT beta R implicates LT/LIGHT involvement in central tolerance. Dysregulated expression of LIGHT overrides peripheral tolerance leading to T-cell-driven autoimmune disease. Blockade of TNF/LT/LIGHT pathways as an intervention in controlling autoimmune diseases is attractive, but such therapy may have risks. Thus, identifying and understanding the target genes may offer an opportunity to fine-tune inhibitory interventions.

Toll-like receptor (TLR)-dependent pathways control the production of IFNalphabeta, a key cytokine in innate immune control of viruses including mouse cytomegalovirus (MCMV). The lymphotoxin (LT) alphabeta-LTbeta receptor signaling pathway is also critical for defense against MCMV and thought to aid in the IFNbeta response. We find that upon MCMV infection, mice deficient for lymphotoxin (LT)alphabeta signaling cannot mount the initial part of a biphasic IFNalphabeta response, but show normal levels of IFNalphabeta during the sustained phase of infection. Significantly, the LTalphabeta-dependent, IFNalphabeta response is independent of TLR signaling. B, but not T, cells expressing LTbeta are essential for promoting the initial IFNalphabeta response. LTbetaR expression is required strictly in splenic stromal cells for initial IFNalphabeta production to MCMV and is dependent upon the NF-kappaB-inducing kinase (NIK). These results reveal a TLR-independent innate host defense strategy directed by B cells in communication with stromal cells via the LTalphabeta cytokine system.

[1] End member mixing analysis (EMMA) is a commonly applied method to identify and quantify the dominant runoff producing sources of water. It employs tracers to determine the dimensionality of the hydrologic system. Many EMMA studies have been conducted using two to six tracers, with some of the main tracers being Ca, Na, Cl À , water isotopes, and alkalinity. Few studies use larger tracer sets including minor trace elements such as Li, Rb, Sr, and Ba. None of the studies has addressed the question of the tracer set size and composition, despite the fact that these determine which and how many end members (EM) will be identified. We examine how tracer set size and composition affects the conceptual model that results from an EMMA. We developed an automatic procedure that conducts EMMA while iteratively changing tracer set size and composition. We used a set of 14 tracers and 9 EMs. The validity of the resulting conceptual models was investigated under the aspects of dimensionality, EM combinations, and contributions to stream water. From the 16,369 possibilities, 23 delivered plausible results. The resulting conceptual models are highly sensitive to the tracer set size and composition. The moderate reproducibility of EM contributions indicates a still missing EM. It also emphasizes that the major elements are not always the most useful tracers and that larger tracer sets have an enhanced capacity to avoid false conclusions about catchment functioning. The presented approach produces results that may not be apparent from the traditional approach and it is a first step to add the idea of statistical significance to the EMMA approach.

Highlights d We developed a model of the human gut-liver axis, including adaptive immune cells d Interaction between gut and liver MPSs increases metabolism and reduces inflammation d SCFAs reduce innate inflammation of the UC gut in absence of Treg and Th17 cells d Acute CD4 + T cell-mediated inflammation is exacerbated by SCFAs