B cell-activating factor belonging to the TNF family acts through separate receptors to support B cell survival and T cell-independent antibody formation

The TNF-related ligand, B cell-activating factor belonging to the TNF family (BAFF), is necessary for normal B cell development and survival, and specifically binds the receptors transmembrane activator and calcium-modulator and cyclophilin ligand interactor (TACI), B cell maturation Ag (BCMA), and BAFF-R. Similarities between mice completely lacking BAFF and A/WySnJ strain mice that express a naturally occurring mutant form of BAFF-R suggest that BAFF acts primarily through BAFF-R. However, the nearly full-length BAFF-R protein expressed by A/WySnJ mice makes unambiguous interpretation of receptor function in these animals impossible. Using homologous recombination we created mice completely lacking BAFF-R and compared them directly to A/WySnJ mice and to mice lacking BAFF. BAFF-R-null mice exhibit loss of mature B cells similar to that observed in BAFF(-/-) and A/WySnJ mice. Also, mice lacking both TACI and BCMA simultaneously exhibit no B cell loss, thus confirming that BAFF-R is the primary receptor for transmitting the BAFF-dependent B cell survival signal. However, while BAFF-R-null mice cannot carry out T cell-dependent Ab formation, they differ from BAFF-deficient mice in generating normal levels of Ab to at least some T cell-independent Ags. These studies clearly demonstrate that BAFF regulates Ab responses in vivo through receptors in addition to BAFF-R.     

Routing misfolded proteins through the multivesicular body (MVB) pathway protects against proteotoxicity

The secretory pathway maintains multiple quality control checkpoints. Initially, endoplasmic reticulum-associated degradation pathways monitor protein folding to retain and eliminate aberrant products. Despite its broad client range, some molecules escape detection and traffic to Golgi membranes. There, a poorly understood mechanism termed Golgi quality control routes aberrant proteins for lysosomal/vacuolar degradation. To better understand Golgi quality control, we examined the processing of the obligate substrate Wsc1p. Misfolded Wsc1p does not use routes of typical vacuolar membrane proteins. Instead, it partitions into intralumenal vesicles of the multivesicular body (MVB) pathway, mediated by the E3 ubiquitin ligase Rsp5p. Its subsequent transport to the vacuolar lumen is essential for complete molecule breakdown. Surprisingly, the transport mode plays a second crucial function in neutralizing potential substrate toxicity. Eliminating the MVB sorting signal diverted molecules to the vacuolar limiting membrane, resulting in the generation of toxic by-products. These data demonstrate a new role of the MVB pathway in protein quality control.     

Molecular pattern discovery based on penalized matrix decomposition

A reliable and precise identification of the type of tumors is crucial to the effective treatment of cancer. With the rapid development of microarray technologies, tumor clustering based on gene expression data is becoming a powerful approach to cancer class discovery. In this paper, we apply the penalized matrix decomposition (PMD) to gene expression data to extract metasamples for clustering. The extracted metasamples capture the inherent structures of samples belong to the same class. At the same time, the PMD factors of a sample over the metasamples can be used as its class indicator in return. Compared with the conventional methods such as hierarchical clustering (HC), self-organizing maps (SOM), affinity propagation (AP) and nonnegative matrix factorization (NMF), the proposed method can identify the samples with complex classes. Moreover, the factor of PMD can be used as an index to determine the cluster number. The proposed method provides a reasonable explanation of the inconsistent classifications made by the conventional methods. In addition, it is able to discover the modules in gene expression data of conterminous developmental stages. Experiments on two representative problems show that the proposed PMD-based method is very promising to discover biological phenotypes.     

Prediction of dengue incidence using search query surveillance

Background

The use of internet search data has been demonstrated to be effective at predicting influenza incidence. This approach may be more successful for dengue which has large variation in annual incidence and a more distinctive clinical presentation and mode of transmission.

Methods

We gathered freely-available dengue incidence data from Singapore (weekly incidence, 2004–2011) and Bangkok (monthly incidence, 2004–2011). Internet search data for the same period were downloaded from Google Insights for Search. Search terms were chosen to reflect three categories of dengue-related search: nomenclature, signs/symptoms, and treatment. We compared three models to predict incidence: a step-down linear regression, generalized boosted regression, and negative binomial regression. Logistic regression and Support Vector Machine (SVM) models were used to predict a binary outcome defined by whether dengue incidence exceeded a chosen threshold. Incidence prediction models were assessed using and Pearson correlation between predicted and observed dengue incidence. Logistic and SVM model performance were assessed by the area under the receiver operating characteristic curve. Models were validated using multiple cross-validation techniques.

Results

The linear model selected by AIC step-down was found to be superior to other models considered. In Bangkok, the model has an , and a correlation of 0.869 between fitted and observed. In Singapore, the model has an , and a correlation of 0.931. In both Singapore and Bangkok, SVM models outperformed logistic regression in predicting periods of high incidence. The AUC for the SVM models using the 75th percentile cutoff is 0.906 in Singapore and 0.960 in Bangkok.

Conclusions

Internet search terms predict incidence and periods of large incidence of dengue with high accuracy and may prove useful in areas with underdeveloped surveillance systems. The methods presented here use freely available data and analysis tools and can be readily adapted to other settings.     

Passiflin,a novel dimeric antifungal protein from seeds of the passion fruit

The intent was to isolate an antifungal protein from seeds of the passion fruit (Passiflora edulis) and to compare its characteristics with other antifungal proteins and bovine β-lactoglobulin in view of its N-terminal amino acid sequence similarity to β-lactoglobulin. The isolation procedure entailed ion-exchange chromatography on Q-Sepharose, hydrophobic interaction chromatography on Phenyl-Sepharose, ion-exchange chromatography on DEAE-cellulose, and FPLC-gel filtration on Superdex 75. The isolated 67-kDa protein, designated as passiflin, exhibited an N-terminal amino acid sequence closely resembling that of bovine β-lactoglobulin. It is the first antifungal protein found to have a β-lactoglobulin-like N-terminal sequence. Its dimeric nature is rarely found in antifungal proteins. It impeded mycelial growth in Rhizotonia solani with an IC₅₀ of 16 μM and potently inhibited proliferation of MCF-7 breast cancer cells with an IC₅₀ of 15 μM. There was no cross-reactivity of passiflin with anti-β-lactoglobulin antiserum. Intact β-lactoglobulin lacks antifungal and antiproliferative activities and is much smaller in molecular size than passiflin. However, it has been reported that hydrolyzed β-lactoglobulin shows antifungal activity. The data suggest that passiflin is distinct from β-lactoglobulin.     

Concentration of plasminogen activators and inhibitor in the human endometrium at different phases of the menstrual cycle.

The concentrations of tissue plasminogen activator (t-PA), urokinase plasminogen activator (u-PA) and plasminogen activator inhibitor (PAI-1) have been determined in endometrial curettings obtained from 46 subfertile women during proliferative, early or late secretory phases of the menstrual cycle. t-PA activity and antigen concentrations was significantly higher (P < 0.001) in late secretory endometrium than in proliferative or early secretory endometrium. Higher concentrations of PAI-1 antigen (P < 0.05) were also noted in late secretory phase than in proliferative and early secretory endometrium. However, u-PA concentration was not significantly different and no PAI activity could be demonstrated in the menstrual phases studied. Zymography studies confirmed the presence of both t-PA and u-PA in the endometrium. Ovarian hormonal patterns may therefore influence the activity of plasminogen activators especially of t-PA in the endometrium during various phases of the menstrual cycle.     

Individual cartilage aggrecan macromolecules and their constituent glycosaminoglycans visualized via atomic force microscopy

Atomic force microscopy was used in ambient conditions to directly image dense and sparse monolayers of bovine fetal epiphyseal and mature nasal cartilage aggrecan macromolecules adsorbed on mica substrates. Distinct resolution of the non-glycosylated N-terminal region from the glycosaminoglycan (GAG) brush of individual aggrecan monomers was achieved, as well as nanometer-scale resolution of individual GAG chain conformation and spacing. Fetal aggrecan core protein trace length (398+/-57 nm) and end-to-end length (257+/-87 nm) were both larger than that of mature aggrecan (352+/-88 and 226+/-81 nm, respectively). Similarly, fetal aggrecan GAG chain trace length (41+/-7 nm) and end-to-end (32+/-8 nm) length were both larger than that of mature aggrecan GAG (32+/-5 and 26+/-7 nm, respectively). GAG-GAG spacing along the core protein was significantly smaller in fetal compared to mature aggrecan (3.2+/-0.8 and 4.4+/-1.2nm, respectively). Together, these differences between the two aggrecan types were likely responsible for the greater persistence length of the fetal aggrecan (110 nm) compared to mature aggrecan (82 nm) calculated using the worm-like chain model. Measured dimensions and polymer statistical analyses were used in conjunction with the results of Western analyses, chromatographic, and carbohydrate electrophoresis measurements to better understand the dependence of aggrecan structure and properties on its constituent GAG chains.     

Structure function differences in nonpeptide CCR1 antagonists for human and mouse CCR1

A useful strategy for identifying ligand binding domains of G protein-coupled receptors has been the exploitation of species differences in antagonist potencies. We have used this approach for the CCR1 chemokine receptor with a novel series of antagonists, the 4-hydroxypiperidines, which were discovered by high throughput screening of human CCR1 and subsequently optimized. The structure-activity relationships for a number of different 4-hydroxypiperidine antagonists for human and mouse CCR1 were examined by receptor binding and functional assays. These compounds exhibit major differences in their rank order of potency for the human and mouse chemokine receptor CCR1. For example, the initial lead template, BX 510, which was a highly potent functional antagonist for human CCR1 (K(i) = 21 nM) was >400-fold less active on mouse CCR1 (K(i) = 9150 nM). However, increasing the length of the linker between the piperidine and dibenzothiepine groups by one methylene group generated a compound, BX 511, which was equipotent for both human and mouse CCR1. These and other analogs of the lead template BX 510, which have major differences in potency for human and mouse CCR1, are described, and a model for their interaction with human CCR1 is presented.