Effect of posttranslational processing on the in vitro and in vivo activity of chemokines

The CXC and CC chemokine gene clusters provide an abundant number of chemotactic factors selectively binding to shared G protein-coupled receptors (GPCR). Hence, chemokines function in a complex network to mediate migration of the various leukocyte subsets, expressing specific GPCRs during the immune response. Further fine-tuning of the chemokine system is reached through specific posttranslational modifications of the mature proteins. Indeed, enzymatic processing of chemokines during an early phase of inflammation leads to activation of precursor molecules or cleavage into even more active or receptor specific chemokine isoforms. At a further stage, proteolytic processing leads to loss of GPCR signaling, thereby providing natural chemokine receptor antagonists. Finally, further NH₂-terminal cleavage results in complete inactivation to dampen the inflammatory response. During inflammatory responses, the two chemokines which exist in a membrane-bound form may be released by proteases from the cellular surface. In addition to proteolytic processing, citrullination and glycosylation of chemokines is also important for their biological activity. In particular, citrullination of arginine residues seems to reduce the inflammatory activity of chemokines in vivo. This goes along with other positive and negative regulatory mechanisms for leukocyte migration, such as chemokine synergy and scavenging by decoy receptors.     

Hepatic Hemodynamics and Fetal Growth: A Relationship of Interest for Further Research

Background

It is well known that hepatic hemodynamics is an important physiologic mechanism in the regulation of cardiac output (CO). It has been reported that maternal cardiac output relates to neonatal weight at birth.

Aims

In this study, we assessed the correlation between maternal hepatic vein Doppler flow parameters, cardiac output and neonatal birth weight.

Methods

Healthy women with uncomplicated second or third trimester pregnancy attending the outpatient antenatal clinic of Ziekenhuis Oost-Limburg in Genk (Belgium), had a standardized combined electrocardiogram-Doppler ultrasound with Impedance Cardiography, for measurement of Hepatic Vein Impedance Index (HVI  =  [maximum velocity – minimum velocity]/maximum velocity), venous pulse transit time (VPTT  =  time interval between corresponding ECG and Doppler wave characteristics) and cardiac output (heart rate x stroke volume). After delivery, a population-specific birth weight chart, established from a cohort of 27000 neonates born in the index hospital, was used to define customized birth weight percentiles (BW%). Correlations between HVI, VPTT, CO and BW% were calculated using Spearman''s ρ, linear regression analysis and R² goodness of fit in SPSS 22.0.

Results

A total of 73 women were included. There was a negative correlation between HVI and VPTT (ρ = −0.719, p<0.001). Both HVI and VPTT correlated with CO (ρ = −0.403, p<0.001 and ρ = 0.332, p<0.004 resp.) and with BW% (ρ = −0.341, p<0.003 and ρ = 0.296, p<0.011 resp.)

Conclusion

Our data illustrate that the known contribution of hepatic hemodynamics in the regulation of cardiac output is also true for women with uncomplicated pregnancies. Our study is the first to illustrate a potential link between maternal hepatic hemodynamics and neonatal birth weight. Whether this link is purely associative or whether hepatic vascular physiology has a direct impact on fetal growth is to be evaluated in more extensive clinical and experimental research.     

Genome-wide promoter methylation analysis in neuroblastoma identifies prognostic methylation biomarkers

ChIP-seq is a powerful method for obtaining genome-wide maps of protein-DNA interactions and epigenetic modifications. CHANCE (CHip-seq ANalytics and Confidence Estimation) is a standalone package for ChIP-seq quality control and protocol optimization. Our user-friendly graphical software quickly estimates the strength and quality of immunoprecipitations, identifies biases, compares the user's data with ENCODE's large collection of published datasets, performs multi-sample normalization, checks against quantitative PCR-validated control regions, and produces informative graphical reports. CHANCE is available at https://github.com/songlab/chance.     

Comprehensive analysis of two Shank3 and the Cacna1c mouse models of autism spectrum disorder

To expand, analyze and extend published behavioral phenotypes relevant to autism spectrum disorder (ASD), we present a study of three ASD genetic mouse models: Feng's Shank3^tm2Gfng model, hereafter Shank3/F, Jiang's Shank3^tm1Yhj model, hereafter Shank3/J and the Cacna1c deletion model. The Shank3 models mimick gene mutations associated with Phelan–McDermid Syndrome and the Cacna1c model recapitulates the deletion underlying Timothy syndrome. This study utilizes both standard and novel behavioral tests with the same methodology used in our previously published companion report on the Cntnap2 null and 16p11.2 deletion models. We found that some but not all behaviors replicated published findings and those that did replicate, such as social behavior and overgrooming in Shank3 models, tended to be milder than reported elsewhere. The Shank3/F model, and to a much lesser extent, the Shank3/J and Cacna1c models, showed hypoactivity and a general anxiety‐like behavior triggered by external stimuli which pervaded social interactions. We did not detect deficits in a cognitive procedural learning test nor did we observe perseverative behavior in these models. We did, however, find differences in exploratory patterns of Cacna1c mutant mice suggestive of a behavioral effect in a social setting. In addition, only Shank3/F showed differences in sensory‐gating. Both positive and negative results from this study will be useful in identifying the most robust and replicable behavioral signatures within and across mouse models of autism. Understanding these phenotypes may shed light of which features to study when screening compounds for potential therapeutic interventions.     

IDO1 Deficiency Does Not Affect Disease in Mouse Models of Systemic Juvenile Idiopathic Arthritis and Secondary Hemophagocytic Lymphohistiocytosis

Objectives

Indoleamine 2,3-dioxygenase-1 (IDO1) is an immune-modulatory enzyme that catalyzes the degradation of tryptophan (Trp) to kynurenine (Kyn) and is strongly induced by interferon (IFN)-γ. We previously reported highly increased levels of IFN-γ and corresponding IDO activity in patients with hemophagocytic lymphohistiocytosis (HLH), a hyper-inflammatory syndrome. On the other hand, IFN-γ and IDO were low in patients with systemic juvenile idiopathic arthritis (sJIA), an autoinflammatory syndrome. As HLH can occur as a complication of sJIA, the opposing levels of both IFN-γ and IDO are remarkable. In animal models for sJIA and HLH, the role of IFN-γ differs from being protective to pathogenic. In this study, we aimed to unravel the role of IDO1 in the pathogenesis of sJIA and HLH.

Methods

Wild-type and IDO1-knockout (IDO1-KO) mice were used in 3 models of sJIA or HLH: complete Freund’s adjuvant (CFA)-injected mice developed an sJIA-like syndrome and secondary HLH (sHLH) was evoked by either repeated injection of unmethylated CpG oligonucleotide or by primary infection with mouse cytomegalovirus (MCMV). An anti-CD3-induced cytokine release syndrome was used as a non-sJIA/HLH control model.

Results

No differences were found in clinical, laboratory and hematological features of sJIA/HLH between wild-type and IDO1-KO mice. As IDO modulates the immune response via induction of regulatory T cells and inhibition of T cell proliferation, we investigated both features in a T cell-triggered cytokine release syndrome. Again, no differences were observed in serum cytokine levels, percentages of regulatory T cells, nor of proliferating or apoptotic thymocytes and lymph node cells.

Conclusions

Our data demonstrate that IDO1 deficiency does not affect inflammation in sJIA, sHLH and a T cell-triggered cytokine release model. We hypothesize that other tryptophan-catabolizing enzymes like IDO2 and tryptophan 2,3-dioxygenase (TDO) might compensate for the lack of IDO1.