Fcgamma receptor-mediated phagocytosis in macrophages lacking the Src family tyrosine kinases Hck, Fgr, and Lyn.

Macrophage Fcgamma receptors (FcgammaRs) mediate the uptake and destruction of antibody-coated viruses, bacteria, and parasites. We examined FcgammaR signaling and phagocytic function in bone marrow-derived macrophages from mutant mice lacking the major Src family kinases expressed in these cells, Hck, Fgr, and Lyn. Many FcgammaR-induced functional responses and signaling events were diminished or delayed in these macrophages, including immunoglobulin (Ig)G-coated erythrocyte phagocytosis, respiratory burst, actin cup formation, and activation of Syk, phosphatidylinositol 3-kinase, and extracellular signal-regulated kinases 1 and 2. Significant reduction of IgG-dependent phagocytosis was not seen in hck(-)(/)-fgr(-)(/)- or lyn(-)(/)- cells, although the single mutant lyn(-)(/)- macrophages did manifest signaling defects. Thus, Src family kinases clearly have roles in two events leading to FcgammaR-mediated phagocytosis, one involving initiation of actin polymerization and the second involving activation of Syk and subsequent internalization. Since FcgammaR-mediated phagocytosis did occur at modest levels in a delayed fashion in triple mutant macrophages, these Src family kinases are not absolutely required for uptake of IgG-opsonized particles

Cervicovaginal fluid acetate: a metabolite marker of preterm birth in symptomatic pregnant women

Changes in vaginal microbiota that is associated with preterm birth (PTB) leave specific metabolite fingerprints that can be detected in the cervicovaginal fluid (CVF) using metabolomics techniques. In this study, we characterize and validate the CVF metabolite profile of pregnant women presenting with symptoms of threatened preterm labor (PTL) by both 1H-nuclear magnetic resonance spectroscopy (NMR) and enzyme-based spectrophotometry. We also determine their predictive capacity for PTB, singly, and in combination, with current clinical screening tools – cervicovaginal fetal fibronectin (FFN) and ultrasound cervical length (CL). CVF was obtained by high-vaginal swabs from 82 pregnant women with intact fetal membranes presenting between 24 and 36 weeks gestation with symptoms of threatened, but not established, PTL. Dissolved CVF samples were scanned with a 400 MHz NMR spectrometer. Acetate and other metabolites were identified in the NMR spectrum, integrated for peak area, and normalized to the total spectrum integral. To confirm and validate our observations, acetate concentrations (AceConc) were also determined from a randomly-selected subset of the same samples (n = 57), by spectrophotometric absorption of NADH using an acetic acid assay kit. CVF FFN level, transvaginal ultrasound CL, and vaginal pH were also ascertained. Acetate normalized integral and AceConc were significantly higher in the women who delivered preterm compared to their term counterparts (P = 0.002 and P = 0.006, respectively). The 1H-NMR-derived acetate integrals were strongly correlated with the AceConc estimated by spectrophotometry (r = 0.69; P 0.53 g/l), and of delivery within 2 weeks of the index assessment (acetate integral: AUC = 0.77, 95% CI = 0.58–0.96; AceConc: AUC = 0.68, 95% CI = 0.5–0.9). The predictive accuracy of CVF acetate was similar to CL and FFN. The combination of CVF acetate, FFN, and ultrasound CL in a binary logistic regression model improved the prediction of PTB compared to the three markers individually, but CVF acetate offered no predictive improvement over ultrasound CL combined with CVF FFN. Elevated CVF acetate in women with symptoms of PTL appears predictive of preterm delivery, as well as delivery within 2 weeks of presentation. An assay of acetate in CVF may prove of clinical utility for predicting PTB

Spontaneous Preterm Birth Is Associated with Differential Expression of Vaginal Metabolites by Lactobacilli-Dominated Microflora

A major challenge in preventing preterm birth (PTB) is identifying women at greatest risk. This pilot study prospectively examined the differences in vaginal microbiota and metabolite profiles of women who delivered prematurely compared to their term counterparts in a cohort of asymptomatic (studied at 20–22, n = 80; and 26–28 weeks, n = 41) and symptomatic women (studied at 24–36 weeks, n = 37). Using 16S rRNA sequencing, the vaginal microbiota from cervicovaginal fluid samples was characterized into five Community State Types (CST) dominated by Lactobacillus spp.: CSTI (Lactobacillus crispatus), CSTII (Lactobacillus gasseri), CSTIII (Lactobacillus iners), CSTV (Lactobacillus jensenii); and mixed anaerobes—CSTIV. This was then related to the vaginal metabolite profile and pH determined by 1H-Nuclear Magnetic Resonance spectroscopy and pH indicator paper, respectively. At 20–22 weeks, the term-delivered women (TDW) indicated a proportion of CSTI-dominated microbiota >2-fold higher compared to the preterm-delivered women (PTDW) (40.3 vs. 16.7%, P = 0.0002), and a slightly higher proportion at 26–28 weeks (20.7 vs. 16.7%, P = 0.03). CSTV was >2-fold higher in the PTDW compared to TDW at 20–22 (22.2 vs. 9.7%, P = 0.0002) and 26–28 weeks (25.0 vs. 10.3%, P = 0.03). Furthermore, at 26–28 weeks no PTDW had a CSTII-dominated microbiome, in contrast to 28% of TDW (P < 0.0001). CSTI-dominated samples showed higher lactate levels than CSTV at 20–22 weeks (P < 0.01), and 26–28 weeks (P < 0.05), while CSTII-dominated samples indicated raised succinate levels over CSTV at 26–28 weeks (P < 0.05). These were supported by Principal coordinates analysis, which revealed strong clustering of metabolites according to CST. In addition, the CSTI-dominated samples had an average pH of 3.8, which was lower than those of CSTII—4.4, and CSTV—4.2 (P < 0.05). Elevated vaginal lactate and succinate were associated with predominance of CSTI and II over CSTV in women who delivered at term compared with their preterm counterparts. This suggests that L. jensenii-dominance and decreased lactate and/or succinate could increase the risk of PTB, while L. crispatus/gasseri may confer some protection against inflammation-associated PTB and highlight the need for further study in this area

Effect of general risk on trust, satisfaction, and recommendation intention for halal food

The purpose of this empirical study is to investigate the effect of general risk, a multidimensional factor, on halal customer trust, satisfaction and intention to recommend halal food. The study also calculates the mean comparison of trust, satisfaction and intention recommendation across the demographic variables of halal customers. Our results from the structural analysis revealed that general risk has significant and positive effects on trust, satisfaction, and intention to recommend halal food. In addition, the results of the mean difference test advised that satisfaction and intention to recommend halal food are significantly different between male and female customers and that trust significantly varies across halal customers with different educations and marital status backgrounds. This study added a valuable contribution to the current literature of halal food consumption by performing a set of symmetric analytical approaches to assess desired responses from halal food customers

A Novel Biclustering Approach to Association Rule Mining for Predicting HIV-1–Human Protein Interactions

Identification of potential viral-host protein interactions is a vital and useful approach towards development of new drugs targeting those interactions. In recent days, computational tools are being utilized for predicting viral-host interactions. Recently a database containing records of experimentally validated interactions between a set of HIV-1 proteins and a set of human proteins has been published. The problem of predicting new interactions based on this database is usually posed as a classification problem. However, posing the problem as a classification one suffers from the lack of biologically validated negative interactions. Therefore it will be beneficial to use the existing database for predicting new viral-host interactions without the need of negative samples. Motivated by this, in this article, the HIV-1–human protein interaction database has been analyzed using association rule mining. The main objective is to identify a set of association rules both among the HIV-1 proteins and among the human proteins, and use these rules for predicting new interactions. In this regard, a novel association rule mining technique based on biclustering has been proposed for discovering frequent closed itemsets followed by the association rules from the adjacency matrix of the HIV-1–human interaction network. Novel HIV-1–human interactions have been predicted based on the discovered association rules and tested for biological significance. For validation of the predicted new interactions, gene ontology-based and pathway-based studies have been performed. These studies show that the human proteins which are predicted to interact with a particular viral protein share many common biological activities. Moreover, literature survey has been used for validation purpose to identify some predicted interactions that are already validated experimentally but not present in the database. Comparison with other prediction methods is also discussed

Evolution of response dynamics underlying bacterial chemotaxis

© 2011 Soyer and Goldstein; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background: The ability to predict the function and structure of complex molecular mechanisms underlying cellular behaviour is one of the main aims of systems biology. To achieve it, we need to understand the evolutionary routes leading to a specific response dynamics that can underlie a given function and how biophysical and environmental factors affect which route is taken. Here, we apply such an evolutionary approach to the bacterial chemotaxis pathway, which is documented to display considerable complexity and diversity.Results: We construct evolutionarily accessible response dynamics starting from a linear response to absolute levels of attractant, to those observed in current-day Escherichia coli. We explicitly consider bacterial movement as a two-state process composed of non-instantaneous tumbling and swimming modes. We find that a linear response to attractant results in significant chemotaxis when sensitivity to attractant is low and when time spent tumbling is large. More importantly, such linear response is optimal in a regime where signalling has low sensitivity. As sensitivity increases, an adaptive response as seen in Escherichia coli becomes optimal and leads to 'perfect' chemotaxis with a low tumbling time. We find that as tumbling time decreases and sensitivity increases, there exist a parameter regime where the chemotaxis performance of the linear and adaptive responses overlap, suggesting that evolution of chemotaxis responses might provide an example for the principle of functional change in structural continuity.Conclusions: Our findings explain several results from diverse bacteria and lead to testable predictions regarding chemotaxis responses evolved in bacteria living under different biophysical constraints and with specific motility machinery. Further, they shed light on the potential evolutionary paths for the evolution of complex behaviours from simpler ones in incremental fashion