Neutrophil elastase (NE) is a potent serine proteinase whose expression is limited to a narrow window during myeloid development. In neutrophils, NE is stored in azurophil granules along with other serine proteinases (cathepsin G, proteinase 3 and azurocidin) at concentrations exceeding 5 mM. As a result of its capacity to efficiently degrade extracellular matrix, NE has been implicated in a variety of destructive diseases. Indeed, while much interest has focused on the pathologic effects of this enzyme, little is known regarding its normal physiologic function(s). Because previous in vitro data have shown that NE exhibits antibacterial activity, we investigated the role of NE in host defense against bacteria. Generating strains of mice deficient in NE (NE-/-) by targeted mutagenesis, we show that NE-/- mice are more susceptible than their normal littermates to sepsis and death following intraperitoneal infection with Gram negative (Klebsiella pneumoniae and Escherichia coli) but not Gram positive (Staphylococcus aureus) bacteria. Our data indicate that neutrophils migrate normally to sites of infection in the absence of NE, but that NE is required for maximal intracellular killing of Gram negative bacteria by neutrophils.

Caveolae are subcellular structures implicated in the import and transcytosis of macromolecules and in transmembrane signaling. To date, evidence for the existence of caveolae in hematopoietic cells has been ambiguous. Caveolae were detected in the microvilli and intracellular vesicles of cultured mouse bone marrow-derived mast cells (BMMCs). CD48, a receptor for FimH-expressing (type 1 fimbriated) Escherichia coli, was specifically localized to plasmalemmal caveolae in BMMCs. The involvement of caveolae in bacterial entry into BMMCs was indicated because caveolae-disrupting and -usurping agents specifically blocked E. coli entry, and markers of caveolae were actively recruited to sites of bacterial entry. The formation of bacteria-encapsulating caveolar chambers in BMMCs represents a distinct mechanism of microbial entry into phagocytes.

No abstract

Mast cells are well known for their harmful role in IgE-mediated hypersensitivity reactions, but their physiological role remains a mystery. Several recent studies have reported that mast cells play a critical role in innate immunity in mice by releasing tumor necrosis factor ␣ (TNF-␣) to recruit neutrophils to sites of enterobacterial infection. In some cases, the mast cell TNF-␣ response was triggered when these cells directly bound FimH on the surface of Escherichia coli. We have identified CD48, a glycosylphosphatidylinositol-anchored molecule, to be the complementary FimH-binding moiety in rodent mast cell membrane fractions. We showed that (i) pretreatment of mast cell membranes with antibodies to CD48 or phospholipase C inhibited binding of FimH ؉ E. coli, (ii) FimH ؉ E. coli but not a FimH ؊ derivative bound isolated CD48 in a mannose-inhibitable manner, (iii) binding of FimH ؉ bacteria to Chinese hamster ovary (CHO) cells was markedly increased when these cells were transfected with CD48 cDNA, and (iv) antibodies to CD48 specifically blocked the mast cell TNF-␣ response to FimH ؉ E. coli. Thus, CD48 is a functionally relevant microbial receptor on mast cells that plays a role in triggering inf lammation.

Strains of Escherichia coli persist within the human gut as normal commensals, but are frequent pathogens and can cause recurrent infection. Here we show that, in contrast to E. coli subjected to opsonic interactions stimulated by the host's immune response, E. coli that bind to the macrophage surface exclusively through the bacterial lectin FimH can survive inside the cell following phagocytosis. This viability is largely due to the attenuation of intracellular free-radical release and of phagosome acidification during FimH-mediated internalization, both of which are triggered by antibody-mediated internalization. This different processing of non-opsonized bacteria is supported by morphological evidence of tight-fitting phagosomes compared with looser, antibody-mediated phagosomes. We propose that non-opsonized FimH-expressing E. coli co-opt internalization of lipid-rich microdomains following binding to the FimH receptor, the glycosylphosphatidylinositol-linked protein CD48, because (1) the sterol-binding agents filipin, nystatin and methyl beta-cyclodextrin specifically block FimH-mediated internalization; (2) CD48 and the protein caveolin both accumulate on macrophage membranes surrounding bacteria; and (3) antibodies against CD48 inhibit FimH-mediated internalization. Our findings bring the traditionally extracellular E. coli into the realm of opportunistic intracellular parasitism and suggest how opportunistic infections with FimH-expressing enterobacteria could occur in a setting deprived of opsonizing antibodies.

Efficient Human Epithelial-2 cell image classification can facilitate the diagnosis of many autoimmune diseases. This paper proposes an automatic framework for this classification task, by utilizing the deep convolutional neural networks (CNNs) which have recently attracted intensive attention in visual recognition. In addition to describing the proposed classification framework, this paper elaborates several interesting observations and findings obtained by our investigation. They include the important factors that impact network design and training, the role of rotation-based data augmentation for cell images, the effectiveness of cell image masks for classification, and the adaptability of the CNN-based classification system across different datasets. Extensive experimental study is conducted to verify the above findings and compares the proposed framework with the well-established image classification models in the literature. The results on benchmark datasets demonstrate that 1) the proposed framework can effectively outperform existing models by properly applying data augmentation, 2) our CNN-based framework has excellent adaptability across different datasets, which is highly desirable for cell image classification under varying laboratory settings. Our system is ranked high in the cell image classification competition hosted by ICPR 2014.

No abstract

No abstract