Role of macrophage sialoadhesin in host defense against the sialylated pathogen group B <em>Streptococcus</em>

ABSTRACT: Several bacterial pathogens decorate their surfaces with sialic acid (Sia) residues within cell wall components or capsular exopolysaccharides. Sialic acid expression can promote bacterial virulence by blocking complement activation or by engagement of inhibitory sialic acid-binding immunoglobulin-like lectins (Siglecs) on host leukocytes. Expressed at high levels on splenic and lymph node macrophages, sialoadhesin (Sn) is a unique Siglec with an elongated structure that lacks intracellular signaling motifs. Sialoadhesin allows macrophage to engage certain sialylated pathogens and stimulate inflammatory responses, but the in vivo significance of sialoadhesin in infection has not been shown. We demonstrate that macrophages phagocytose the sialylated pathogen group B Streptococcus (GBS) and increase bactericidal activity via sialoadhesin-sialic-acid-mediated recognition. Sialoadhesin expression on marginal zone metallophillic macrophages in the spleen trapped circulating GBS and restricted the spread of the GBS to distant organs, reducing mortality. Specific IgM antibody responses to GBS challenge were also impaired in sialoadhesin-deficient mice. Thus, sialoadhesin represents a key bridge to orchestrate innate and adaptive immune defenses against invasive sialylated bacterial pathogens. KEY MESSAGE: Sialoadhesin is critical for macrophages to phagocytose and clear GBS. Increased GBS organ dissemination in the sialoadhesin-deficient mice. Reduced anti-GBS IgM production in the sialoadhesin-deficient mice. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00109-014-1157-y) contains supplementary material, which is available to authorized users

An Interesting Class of Porous Polymer-Revisiting the Structure of Mesoporous α-d-Polysaccharide Gels

The processes involved in the transformation of non-porous, native polysaccharides to their highly porous equivalents introduce significant molecular complexity and are not yet fully understood. In this paper, we propose that distinct changes in polysaccharide local short-range ordering promotes and directs the formation of meso- and micro-pores, which are investigated here using N2 sorption, FTIR, and solid-state 13CNMR. It is found that an increase in the overall double helical amylose content, and their local association structures, are responsible for formation of the porous polysaccharide gel phase. An exciting consequence of this local ordering change is elegantly revealed using a 19FNMR experiment, which identifies the stereochemistry-dependent diffusion of a fluorinated chiral probe molecule (1-phenyl-2,2,2-trifluoroethanol) from the meso- to the micro-pore region. This finding opens opportunities in the area of polysaccharide-based chiral stationary phases and asymmetric catalyst preparation

Preterm birth: inflammation, fetal injury and treatment strategies

Preterm birth (PTB) is the leading cause of childhood mortality in children under 5 and accounts for approximately 11% of births worldwide. Premature babies are at risk of a number of health complications, notably cerebral palsy, but also respiratory and gastrointestinal disorders. Preterm deliveries can be medically indicated/elective procedures or they can occur spontaneously. Spontaneous PTB is commonly associated with intrauterine infection/inflammation. The presence of inflammatory mediators in utero has been associated with fetal injury, particularly affecting the fetal lungs and brain. This review will outline (i) the role of inflammation in term and PTB, (ii) the effect infection/inflammation has on fetal development and (iii) recent strategies to target PTB. Further research is urgently required to develop effective methods for the prevention and treatment of PTB and above all, to reduce fetal injury

Group B <em>Streptococcus </em>engages an inhibitory siglec through sialic acid mimicry to blunt innate immune and inflammatory responses <em>in vivo</em>

Group B Streptococcus (GBS) is a common agent of bacterial sepsis and meningitis in newborns. The GBS surface capsule contains sialic acids (Sia) that engage Sia-binding immunoglobulin-like lectins (Siglecs) on leukocytes. Here we use mice lacking Siglec-E, an inhibitory Siglec of myelomonocytic cells, to study the significance of GBS Siglec engagement during in vivo infection. We found GBS bound to Siglec-E in a Sia-specific fashion to blunt NF-κB and MAPK activation. As a consequence, Siglec-E-deficient macrophages had enhanced pro-inflammatory cytokine secretion, phagocytosis and bactericidal activity against the pathogen. Following pulmonary or low-dose intravenous GBS challenge, Siglec-E KO mice produced more pro-inflammatory cytokines and exhibited reduced GBS invasion of the central nervous system. In contrast, upon high dose lethal challenges, cytokine storm in Siglec-E KO mice was associated with accelerated mortality. We conclude that GBS Sia mimicry influences host innate immune and inflammatory responses in vivo through engagement of an inhibitory Siglec, with the ultimate outcome of the host response varying depending upon the site, stage and magnitude of infection

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery