ZAP-70 genotype disrupts the relationship between microbiota and host, leading to spondyloarthritis and ileitis in SKG mice.

ObjectiveThe spondyloarthritides share genetic susceptibility, interleukin-23 (IL-23) dependence, and the involvement of microbiota. The aim of the current study was to elucidate how host genetics influence gut microbiota and the relationship between microbiota and organ inflammation in spondyloarthritides.MethodsBALB/c ZAP-70(W163C) -mutant (SKG) mice, Toll-like receptor 4 (TLR-4)-deficient SKG mice, and wild-type BALB/c mice were housed under specific pathogen-free conditions. SKG and wild-type BALB/c mice were maintained under germ-free conditions, and some of these mice were recolonized with altered Schaedler flora. All of the mice were injected intraperitoneally with microbial β-1,3-glucan (curdlan). Arthritis, spondylitis, and ileitis were assessed histologically. Microbiome composition was analyzed in serial fecal samples obtained from mice that were co-housed beginning at the time of weaning, using 454 pyrosequencing. Infiltrating cells and cytokines in the peritoneal cavity were measured by flow cytometry and enzyme-linked immunosorbent assay. Cytokine, endoplasmic reticulum (ER) stress marker, and tight junction protein transcription was measured by quantitative real-time polymerase chain reaction.ResultsMicrobiota content and response to curdlan varied according to whether T cell receptor signal strength was normal or was impaired due to the ZAP-70(W163C) mutation. Curdlan triggered acute inflammation regardless of the presence of the SKG allele or microbiota. However, no or limited microbiota content attenuated the severity of arthritis. In contrast, ileal IL-23 expression, ER stress, lymph node IL-17A production, goblet cell loss, and ileitis development were microbiota-dependent. Ileitis but not arthritis was suppressed by microbiota transfer upon co-housing SKG mice with wild-type BALB/c mice, as well as by TLR-4 deficiency.ConclusionThe interaction between immunogenetic background and host microbiota leads to an IL-23-dependent loss of mucosal function, triggering ileitis in response to curdlan

Variation graph toolkit improves read mapping by representing genetic variation in the reference

Reference genomes guide our interpretation of DNA sequence data. However, conventional linear references represent only one version of each locus, ignoring variation in the population. Poor representation of an individual's genome sequence impacts read mapping and introduces bias. Variation graphs are bidirected DNA sequence graphs that compactly represent genetic variation across a population, including large-scale structural variation such as inversions and duplications. Previous graph genome software implementations have been limited by scalability or topological constraints. Here we present vg, a toolkit of computational methods for creating, manipulating, and using these structures as references at the scale of the human genome. vg provides an efficient approach to mapping reads onto arbitrary variation graphs using generalized compressed suffix arrays, with improved accuracy over alignment to a linear reference, and effectively removing reference bias. These capabilities make using variation graphs as references for DNA sequencing practical at a gigabase scale, or at the topological complexity of de novo assemblies