Tranilast, an analogue of tryptophan catabolites, induces allograft tolerance by CD161+ cells

International audiencen.

Immunosuppressive role of fibrinogen-like protein 2 (FGL2) in CD8+regulatory T cells-mediated long-term graft survival

International audienc

Mutant huntingtin causes defective actin remodeling during stress: defining a new role for transglutaminase 2 in neurodegenerative disease

Huntington's disease (HD) is caused by an expanded CAG tract in the Interesting transcript 15 (IT15) gene encoding the 350 kDa huntingtin protein. Cellular stresses can trigger the release of huntingtin from the endoplasmic reticulum, allowing huntingtin nuclear entry. Here, we show that endogenous, full-length huntingtin localizes to nuclear cofilin–actin rods during stress and is required for the proper stress response involving actin remodeling. Mutant huntingtin induces a dominant, persistent nuclear rod phenotype similar to that described in Alzheimer's disease for cytoplasmic cofilin–actin rods. Using live cell temporal studies, we show that this stress response is similarly impaired when mutant huntingtin is present, or when normal huntingtin levels are reduced. In clinical lymphocyte samples from HD patients, we have quantitatively detected cross-linked complexes of actin and cofilin with complex formation varying in correlation with disease progression. By live cell fluorescence lifetime imaging measurement–Förster resonant energy transfer studies and western blot assays, we quantitatively observed that stress-activated tissue transglutaminase 2 (TG2) is responsible for the actin–cofilin covalent cross-linking observed in HD. These data support a direct role for huntingtin in nuclear actin re-organization, and describe a new pathogenic mechanism for aberrant TG2 enzymatic hyperactivity in neurodegenerative diseases

Genetic structure of fragmented southern populations of African Cape buffalo (Syncerus caffer caffer)

peer reviewedBackground African wildlife experienced a reduction in population size and geographical distribution over the last millennium, particularly since the 19th century as a result of human demographic expansion, wildlife overexploitation, habitat degradation and cattle-borne diseases. In many areas, ungulate populations are now largely confined within a network of loosely connected protected areas. These metapopulations face gene flow restriction and run the risk of genetic diversity erosion. In this context, we assessed the “genetic health” of free ranging southern African Cape buffalo populations (S.c. caffer) and investigated the origins of their current genetic structure. The analyses were based on 264 samples from 6 southern African countries that were genotyped for 14 autosomal and 3 Y-chromosomal microsatellites. Results The analyses differentiated three significant genetic clusters, hereafter referred to as Northern (N), Central (C) and Southern (S) clusters. The results suggest that splitting of the N and C clusters occurred around 6000 to 8400 years ago. Both N and C clusters displayed high genetic diversity (mean allelic richness (Ar) of 7.217, average genetic diversity over loci of 0.594, mean private alleles (Pa) of 11), low differentiation, and an absence of an inbreeding depression signal (mean FIS = 0.037). The third (S) cluster, a tiny population enclosed within a small isolated protected area, likely originated from a more recent isolation and experienced genetic drift (FIS = 0.062, mean Ar = 6.160, Pa = 2). This study also highlighted the impact of translocations between clusters on the genetic structure of several African buffalo populations. Lower differentiation estimates were observed between C and N sampling localities that experienced translocation over the last century. Conclusions We showed that the current genetic structure of southern African Cape buffalo populations results from both ancient and recent processes. The splitting time of N and C clusters suggests that the current pattern results from human-induced factors and/or from the aridification process that occurred during the Holocene period. The more recent S cluster genetic drift probably results of processes that occurred over the last centuries (habitat fragmentation, diseases). Management practices of African buffalo populations should consider the micro-evolutionary changes highlighted in the present study

Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus

A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10-20), ER-negative BC (P=1.1 × 10-13), BRCA1-associated BC (P=7.7 × 10-16) and triple negative BC (P-diff=2 × 10-5). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P=2 × 10-3) and ABHD8 (P<2 × 10-3). Chromosome conformation capture identifies interactions between four candidate SNPs and ABHD8, and luciferase assays indicate six risk alleles increased transactivation of the ADHD8 promoter. Targeted deletion of a region containing risk SNP rs56069439 in a putative enhancer induces ANKLE1 downregulation; and mRNA stability assays indicate functional effects for an ANKLE1 3′-UTR SNP. Altogether, these data suggest that multiple SNPs at 19p13 regulate ABHD8 and perhaps ANKLE1 expression, and indicate common mechanisms underlying breast and ovarian cancer risk

Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus

A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P = 9.2 x 10(-20)), ER-negative BC (P = 1.1 x 10(-13)), BRCA1-associated BC (P = 7.7 x 10(-16)) and triple negative BC (P-diff = 2 x 10(-5)). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P = 2 x 10(-3)) and ABHD8 (PPeer reviewe