Jackson Laboratories (India)

Abstract Cow milk allergy (CMA) is one of the most common infant food allergies, presenting in IgE- and non-IgE-mediated forms. Currently, the allergen-reactive CD4+ T cell inflammatory responses that distinguish CMA endotypes are not well characterized. In this study, we isolated allergen-reactive conventional (Tcon) and regulatory (Treg) CD4+ T cells from IgE and non-IgE mediated pediatric CMA patients and performed an in-depth cellular and molecular characterization of the composition and function of both T helper (TH) and TH-like subsets. Bacteria present in the gut microbiota were also analysed to assess potential differences between CMA endotypes, and associations between TH and TH-like subsets were mapped against the composition of gut bacterial species. Our findings show that alterations in the balance between allergen-reactive Tcon and Treg cells underlies the development of food allergen sensitization in both IgE- and non-IgE-mediated forms of CMA. Additionally, differences in the composition of TH and TH-like subsets, as well as in the bacterial species present, showed significant associations with the development of specific CMA endotypes. Together, these findings provide a rational explanation for the distinct immunopathologies observed in endotype-specific immune responses against a common allergen and offer insights into the development of therapeutic strategies for distinct CMA endotypes.

Abstract Model organisms have provided critical insights into the basic biology of metabolic disorders, however, one of the greatest limitations to translation has been the absence of the genetic heterogeneity that is characteristic of human populations. We examined metabolic health across three genetically diverse mouse strains fed control (low fat, no sucrose) or unhealthy (high fat, high sucrose) diets and observed a wide range of metabolic responses from overt type 2 diabetes in NZO/HlLtJ mice, to obesity and glucose intolerance in C57BL/6J mice, to complete resilience in CAST/EiJ mice. Analysis of multi-tissue gene expression revealed strain- and tissue-specific responses to diet, with strongest responses in white adipose tissue and pancreatic islets. In pancreatic islets, diet response was limited to just NZO mice, which showed high levels of inflammation and associated β cell dysfunction. Adipose tissue was responsive to diet across all three strains and revealed both common and strain-specific changes in inflammatory and metabolic pathways. Using a complementary outbred mouse resource, we mapped genetic loci associated with strain-specific diet responses, including a monocyte regulatory locus on mChr19. This multi-strain approach to modeling metabolic disease revealed a prominent role of white adipose tissue and lipid-associated inflammation in the determination of individual disease risk in response to unhealthy diets.

Models of Gene Regulatory Networks (GRNs) capture the dynamics of the regulatory processes that occur within the cell as a means to understand the variability observed in gene expression between different conditions. Arguably the simplest mathematical construct used for modeling is the Boolean network, which dictates a set of logical rules for transition between states described as Boolean vectors. Due to the complexity of gene regulation and the limitations of experimental technologies, in most cases knowledge about regulatory interactions and Boolean states is partial. In addition, the logical rules themselves are not known a-priori. Our goal in this work is to present a methodology for inferring this information from the data, and to provide a measure for comparing network states under different biological conditions. We present a novel methodology for integrating experimental data and performing a search for the optimal consistent structure via optimization of a linear objective function under a set of linear constraints. We also present a statistical approach for testing the similarity of inferred network states under different conditions. Finally, we extend our methodology into a heuristic that can handle large datasets that are generated by single-cell RNA-Sequencing(scRNA-Seq). We demonstrate the effectiveness of these tools using a public scRNA-Seq dataset and the GRN that is associated with it. Our methodology will enable researchers to obtain a better understanding of the dynamics of gene regulatory networks and their biological role.

reported in mice.As such, we utilized a genetically diverse population of outbred mice (DO mice) to map loci associated with RBC alloimmunization.Study Design/Methods: Baseline serum (Day 0) was collected from 570 DO mice, each of which were then transfused with RBCs expressing a well-defined model alloantigen (HOD antigen).Serum collected on days 21 and 55 and were tested for anti-HOD IgG by flow cytometry using HOD RBCs as targets and subtracting signal from B6 RBCs.Each mouse was genotyped with a Giga-Muga array ($143,000 markers).Quantitative trait loci (QTL) analysis was carried out on log transformed IgG quantities to map alleles associated with anti-HOD IgG responses.Genome-wide p-values were calculated for each QTL to adjust for multiple testing burden.Results/Findings: Five hundred seven ($89%) had detectable anti-HOD IgG at Day 21, in a range of 0-2711 (mean fluorescence intensity units).Three QTLs were identified, on chromosomes 8, 17, and 19 with additional suggestive QTLs on chromosomes 7 and 18.The strongest QTL on Chr 17 (p = .0001)mapped to the H-2 locus (equivalent of human HLA region), which contains MHC II.After conditioning on the Chr 17 peak through a covariate QTL model, the peak on Chr 19 (p = .036)mapped to a region containing the five known IFIT family genes that are downstream regulators of IFN activity and IFNAR signaling.A suggestive peak for QTL on Chr 7 (p = .19)mapped to XYLT1, a gene also known to be involved in signaling through IFNAR.Peaks on Chr 8 (p = .04)and 18 (p = .15)mapped to gene dense regions, both of which have known QTL associated with autoimmunity and immune regulation.Conclusions: These data map RBC alloimmunization to three loci in mice.The strong hit on Chr 17 is predicted, as HOD RBCs are a CD4+ T-cell-dependent immunogen affected by variant MHCII ability to present peptides.MHCII variation has also been shown to regulate RBC alloimmunization in humans.IFIT family genes function downstream of IFNAR signaling and may represent an important mechanistic regulator of RBC alloimmunization.Follow-up studies will need to assess functional roles of these gene candidates in RBC alloimmunization, both in murine models and also in human studies.

SUMMARY Using polyclonal rabbit and monoclonal mouse anti-dog IgE antibodies, we developed elisa for measurement of ragweed-specific IgE in canine serum. In the elisa, microtitration plates were coated with ragweed extract and sequentially incubated with canine-serum, purified monoclonal or polyclonal anti-dog IgE, and conjugated goat anitbody to mouse IgG or rabbit IgG. Serum ragweed-specific IgE values were measured by the 2 elisa in serum samples from 60 ragweed-allergic dogs and in serum from 10 control dogs. Passive cutaneous anaphylaxis (pca) tests were performed on these sera to compare results with those of the elisa. Mean coefficient of variation between assays was 0.20 ± 0.10 for the assay using the polyclonal antibody and was 0.17 ± 0.10 for that using monoclonal antibody. Sensitivity was 0.6 U/ml for the elisa, using polyclonal antibody, and 2.5 U/ml for the elisa, using monoclonal antibody. Serum ragweed-specific IgE values measured by the 2 elisa strongly correlated with pca titers (P < 0.0000), but the elisa using polyclonal antibody had higher correlation with pca titer (r = 0.84) than the elisa using monoclonal antibody (r = 0.59). The geometric mean ragweed-specific IgE value measured by the 2 elisa and by pca testing, was significantly higher (P < 0.0000). in allergic dogs than in control dogs. The 2 elisa were specific, sensitive, and reproducible for measurement of ragweed-specific IgE in canine serum.

We have used linker insertion-deletion mutagenesis to study the Harvey murine sarcoma virus v-ras H transforming protein. The mutants were characterized with respect to their ability to induce morphological transformation of NIH 3T3 cells and the capacity of their proteins to bind guanosine nucleotides, undergo post-translational processing, and localize to the plasma membrane. We have identified four non-overlapping segments that are dispensable for morphological transformation of NIH 3T3 cells, as well as several segments that are required for transformation and stability in mammalian cells and guanosine nucleotide binding. One essential segment that does not affect guanine nucleotide binding or stability, which appears to lie on the exterior of the protein and therefore may interact with the putative ras protein target, has been identified (the effector domain, Willumsen et al., 1986, Sigal et al., 1986). A selected group of these mutations, which leave the v-ras H protein stable, processed and correctly localized, have been transferred to the c-ras H allele; the proteins were expressed in E. coli and assayed for the susceptibility to acceleration of their intrinsic GTPase activities by the protein GAP (GTPase Activating Protein, Trahey and McCormick, 1987). The results show that only mutations in the effector domain destroy GAP susceptibility (Adari et al., 1988); however, not all mutations affect both activities coordinately. These results suggest that GAP as well as the effector mediating p21 transformation interact through the same region on p21. The identification of mutations that destroy transformation when present in the v-ras H allele which do not destroy the GAP susceptibility of p21 protein from the c-ras H allele raises the possibility that the two factors may not be the same.