Clearance of dying cells and systemic lupus erythematosus: the role of C1q and the complement system

Systemic lupus erythematosus (SLE) is a multisystem autoimmune disease of unknown etiology characterized by the presence of pathogenic high-titer autoantibodies to a diverse group of autoantigens. In 88% of patients, autoantibodies are present an average of 3.3 years before diagnosis. Antinuclear, anti-Ro, anti-La, and anti-phospholipid antibodies appear first, followed by anti-DNA, anti-Smith and anti-ribonucleoprotein. These autoantibodies have features of an antigen-driven, T-cell-dependent immune response. Once present, the course of SLE is characterized by disease flares and autoimmune dysregulation. Programmed cell death (PCD), an essential developmental and homeostatic mechanism, is the preferred physiological death processes for cells as well as an important immune response regulator. Appropriate clearance of apoptotic material completes the PCD process, and is essential for regulating of inflammation and maintaining self-tolerance. Early complement proteins are important in protecting humans against the development of SLE and the protective role of C1q and complement in SLE is mainly related to their role in clearance of dying cells. However, the complement system is also an important ingredient in inflammation, which mediates SLE pathogenesis. Thus, the question remains whether complement factors have either a protective or a destructive role, or a combination of both.     

Multiple Gaussian network modes alignment reveals dynamically variable regions: The hemoglobin case

Gaussian network model (GNM) modes of motion are calculated to a dataset of h emoglobin (Hb) structures and modes with dynamics similarity to the T state are multiply aligned. The sole criterion for the alignment is the mode shape itself and not sequence or structural similarity. Standard deviation (SD) of the GNM value score along the alignment is calculated, regions with high SD are defined as dynamically variable. The analysis shows that the α1β1/α2β2 interface is a dynamically variable region but not the α1β2/α2β1 and the α1α2/β1β2 interfaces. The results are in accordance with the T → R2 transition of Hb. We suggest that dynamically variable regions are regions that are likely to undergo structural change in the protein upon binding, conformational transition, or any other relevant chemical event. The represented technique of multiple dynamics ‐ based alignment of modes is novel and may offer a new insight in proteins ' dynamics to function relation. Proteins 2014; 82:2097–2105. © 2014 Wiley Periodicals, Inc.     

Atrophic thyroid follicles and inner ear defects reminiscent of cochlear hypothyroidism in Slc26a4-related deafness

Thyroid hormone is essential for inner ear development and is required for auditory system maturation. Human mutations in SLC26A4 lead to a syndromic form of deafness with enlargement of the thyroid gland (Pendred syndrome) and non-syndromic deafness (DFNB4). We describe mice with an Slc26a4 mutation, Slc26a4 ^loop/loop , which are profoundly deaf but show a normal sized thyroid gland, mimicking non-syndromic clinical signs. Histological analysis of the thyroid gland revealed defective morphology, with a majority of atrophic microfollicles, while measurable thyroid hormone in blood serum was within the normal range. Characterization of the inner ear showed a spectrum of morphological and molecular defects consistent with inner ear pathology, as seen in hypothyroidism or disrupted thyroid hormone action. The pathological inner ear hallmarks included thicker tectorial membrane with reduced β-tectorin protein expression, the absence of BK channel expression of inner hair cells, and reduced inner ear bone calcification. Our study demonstrates that deafness in Slc26a4 ^loop/loop mice correlates with thyroid pathology, postulating that sub-clinical thyroid morphological defects may be present in some DFNB4 individuals with a normal sized thyroid gland. We propose that insufficient availability of thyroid hormone during inner ear development plays an important role in the mechanism underlying deafness as a result of SLC26A4 mutations.     

Bacteria-Based Analysis of HIV-1 Vpu Channel Activity

HIV-1 Vpu is a small, single-span membrane protein with two attributed functions that increase the virus'' pathogenicity: degradation of CD4 and inactivation of BST-2. Vpu has also been shown to posses ion channel activity, yet no correlation has been found between this attribute and Vpu''s role in viral release. In order to gain further insight into the channel activity of Vpu we devised two bacteria-based assays that can examine this function in detail. In the first assay Vpu was over-expressed, such that it was deleterious to bacterial growth due to membrane permeabilization. In the second and more sensitive assay, the channel was expressed at low levels in K⁺ transport deficient bacteria. Consequently, Vpu expression enabled the bacteria to grow at otherwise non permissive low K⁺ concentrations. Hence, Vpu had the opposite impact on bacterial growth in the two assays: detrimental in the former and beneficial in the latter. Furthermore, we show that channel blockers also behave reciprocally in the two assays, promoting growth in the first assay and hindering it in the second assay. Taken together, we investigated Vpu''s channel activity in a rapid and quantitative approach that is amenable to high-throughput screening, in search of novel blockers.     

Specificity and Effector Functions of Human RSV-Specific IgG from Bovine Milk

Background

Respiratory syncytial virus (RSV) infection is the second most important cause of death in the first year of life, and early RSV infections are associated with the development of asthma. Breastfeeding and serum IgG have been shown to protect against RSV infection. Yet, many infants depend on bovine milk-based nutrition, which at present lacks intact immunoglobulins.

Objective

To investigate whether IgG purified from bovine milk (bIgG) can modulate immune responses against human RSV.

Methods

ELISAs were performed to analyse binding of bIgG to human respiratory pathogens. bIgG or hRSV was coated to plates to assess dose-dependent binding of bIgG to human Fcγ receptors (FcγR) or bIgG-mediated binding of myeloid cells to hRSV respectively. S. Epidermidis and RSV were used to test bIgG-mediated binding and internalisation of pathogens by myeloid cells. Finally, the ability of bIgG to neutralise infection of HEp2 cells by hRSV was evaluated.

Results

bIgG recognised human RSV, influenza haemagglutinin and Haemophilus influenza. bIgG bound to FcγRII on neutrophils, monocytes and macrophages, but not to FcγRI and FcγRIII, and could bind simultaneously to hRSV and human FcγRII on neutrophils. In addition, human neutrophils and dendritic cells internalised pathogens that were opsonised with bIgG. Finally, bIgG could prevent infection of HEp2 cells by hRSV.

Conclusions

The data presented here show that bIgG binds to hRSV and other human respiratory pathogens and induces effector functions through binding to human FcγRII on phagocytes. Thus bovine IgG may contribute to immune protection against RSV.     

Discovering Social Events through Online Attention

Twitter is a major social media platform in which users send and read messages (“tweets”) of up to 140 characters. In recent years this communication medium has been used by those affected by crises to organize demonstrations or find relief. Because traffic on this media platform is extremely heavy, with hundreds of millions of tweets sent every day, it is difficult to differentiate between times of turmoil and times of typical discussion. In this work we present a new approach to addressing this problem. We first assess several possible “thermostats” of activity on social media for their effectiveness in finding important time periods. We compare methods commonly found in the literature with a method from economics. By combining methods from computational social science with methods from economics, we introduce an approach that can effectively locate crisis events in the mountains of data generated on Twitter. We demonstrate the strength of this method by using it to locate the social events relating to the Occupy Wall Street movement protests at the end of 2011.