Influence of substrate curvature on osteoblast orientation and extracellular matrix deposition

Background

The effects of microchannel diameter in hydroxyapatite (HAp) substrates on osteoblast behavior were investigated in this study. Microchannels of 100, 250 and 500 μm diameter were created on hydroxyapatite disks. The changes in osteoblast precursor growth, differentiation, extra cellular matrix (ECM) secretion and cell attachment/orientation were investigated as a function of microchannel diameter.

Results

Curvature did not impact cellular differentiation, however organized cellular orientation was achieved within the 100 and 250 μm microchannels (mc) after 6 days compared to the 12 days it took for the 500mc group, while the flat substrate remained disorganized. Moreover, the 100, 250 and 500mc groups expressed a specific shift in orientation of 17.45°, 9.05°, and 22.86° respectively in 24 days. The secreted/mineralized ECM showed the 100 and 250mc groups to have higher modulus (E) and hardness (h) (E?=?42.6GPa; h?=?1.6GPa) than human bone (E?=?13.4-25.7GPa; h?=?0.47-0.74GPa), which was significantly greater than the 500mc and control groups (p?<?0.05). It was determined that substrate curvature affects the cell orientation, the time required for initial response, and the shift in orientation with time.

Conclusions

These findings demonstrate the ability of osteoblasts to organize and mineralize differentially in microchannels similar to those found in the osteons of compact bone. These investigations could lead to the development of osteon-like scaffolds to support the regeneration of organized bone.

     

Predicting the subcellular localization of human proteins using machine learning and exploratory data analysis

Identifying the subcellular localization of proteins is particularly helpful in the functional annotation of gene products. In this study, we use Machine Learning and Exploratory Data Analysis （EDA） techniques to examine and characterize amino acid sequences of human proteins localized in nine cellular compartments. A dataset of 3,749 protein sequences representing human proteins was extracted from the SWISS-PROT database. Feature vectors were created to capture specific amino acid sequence characteristics. Relative to a Support Vector Machine, a Multi-layer Perceptron, and a Naive Bayes classifier, the C4.5 Decision Tree algorithm was the most consistent performer across all nine compartments in reliably predicting the subcellular localization of proteins based on their amino acid sequences （average Precision=0.88; average Sensitivity=0.86）. Furthermore, EDA graphics characterized essential features of proteins in each compartment. As examples, proteins localized to the plasma membrane had higher proportions of hydrophobic amino acids; cytoplasmic proteins had higher proportions of neutral amino acids; and mitochondrial proteins had higher proportions of neutral amino acids and lower proportions of polar amino acids. These data showed that the C4.5 classifier and EDA tools can be effective for characterizing and predicting the subcellular localization of human proteins based on their amino acid sequences.     

An improved method for staining cell colonies in clonogenic assays

Clonogenic assay is a widely used experimental approach to test for the effects of drugs/genes on the growth and proliferative characteristics of cells in vitro. Accurate quantitation of treatment effects in clonogeneic assays depends on the ability to visualize and count cell colonies precisely. We report a novel method (referred as ETeB) for staining cell colonies grown on plastic and specially coated substrates like collagen. Using colon cancer cell lines grown on plastic and collagen, we compared the colony staining efficiencies of the widely used methylene blue, and Ethidium bromide (ETeB) stains. Results show that the ETeB protocol works well on plastic and is extremely effective for staining colonies on collagen when compared to methylene blue. The key features and advantages of ETeB technique are; (a) reduction in background for colonies grown on collagen and possibly other substrates, (b) the whole procedure takes less than a minute, (c) no post-stain washing step is required which eliminates colony losses for cell lines that are loosely adherent, (d) colony visualization and counting can be done immediately following the staining procedure using a standard UV illuminator and software, and (e) the method works across a wide variety of cell lines. The simplicity and robustness of this procedure should warrant its usage in both small and large-scale clonogenic experiments.

pTARGET [corrected] a new method for predicting protein subcellular localization in eukaryotes

MOTIVATION: There is a scarcity of efficient computational methods for predicting protein subcellular localization in eukaryotes. Currently available methods are inadequate for genome-scale predictions with several limitations. Here, we present a new prediction method, pTARGET that can predict proteins targeted to nine different subcellular locations in the eukaryotic animal species. RESULTS: The nine subcellular locations predicted by pTARGET include cytoplasm, endoplasmic reticulum, extracellular/secretory, golgi, lysosomes, mitochondria, nucleus, plasma membrane and peroxisomes. Predictions are based on the location-specific protein functional domains and the amino acid compositional differences across different subcellular locations. Overall, this method can predict 68-87% of the true positives at accuracy rates of 96-99%. Comparison of the prediction performance against PSORT showed that pTARGET prediction rates are higher by 11-60% in 6 of the 8 locations tested. Besides, the pTARGET method is robust enough for genome-scale prediction of protein subcellular localizations since, it does not rely on the presence of signal or target peptides. AVAILABILITY: A public web server based on the pTARGET method is accessible at the URL http://bioinformatics.albany.edu/~ptarget. Datasets used for developing pTARGET can be downloaded from this web server. Source code will be available on request from the corresponding author.     

Dynamics of gene introgression in the African malaria vector Anopheles gambiae

Anopheles gambiae is a major malaria vector in Africa and a popular model species for a variety of ecological, evolutionary, and genetic studies on vector control. Genetic manipulation of mosquito vectorial capacity is a promising new weapon for the control of malaria. However, the release of exotic transgenic mosquitoes will bring in novel alleles in addition to the parasite-inhibiting genes, which may have unknown effects on the local population. Therefore, it is necessary to develop methodologies that can be used to evaluate the spread rate of introduced genes in A. gambiae. In this study, the effects and dynamics of genetic introgression between two geographically distinct A. gambiae populations from western Kenya (Mbita) and eastern Tanzania (Ifakara) were investigated with amplified fragment length polymorphisms (AFLPs) and microsatellite markers. Microsatellites and polymorphic cDNA markers revealed a large genetic differentiation between the two populations (average F(ST) = 0.093, P < 0.001). When the two strains were crossed in random mating between the two populations, significant differences in the rate of genetic introgression were found in the mixed populations. Allele frequencies of 18 AFLP markers (64.3%) for Mbita and of 26 markers (92.9%) for Ifakara varied significantly from F5 to F20. This study provides basic information on how a mosquito release program would alter the genetic makeup of natural populations, which is critical for pilot field testing and ecological risk evaluation of transgenic mosquitoes.     

Molecular and structural analysis of C4-specific PEPC isoform from Pennisetum glaucum plays a role in stress adaptation

Phosphoenolpyruvate carboxylase is an ubiquitous cytosolic enzyme that catalyzes the ß-carboxylation of phosphoenolpyruvate (PEP) and is encoded by multigene family in plants. It plays an important role in carbon economy of plants by assimilating CO₂ into organic acids for subsequent C₄ or CAM photosynthesis or to perform several anaplerotic roles in non-photosynthetic tissues. In this study, a cDNA clone encoding for PEPC polypeptide possessing signature motifs characteristic to ZmC₄PEPC was isolated from Pennisetum glaucum (PgPEPC). Deduced amino acid sequence revealed its predicted secondary structure consisting of forty alpha helices and eight beta strands is well conserved among other PEPC homologs irrespective of variation in their primary amino acid sequences. Predicted PgPEPC quartenary structure is a tetramer consisting of a dimer of dimers, which is globally akin to maize PEPC crystal structure with respect to major chain folding wherein catalytically important amino acid residues of active site geometry are conserved. Recombinant PgPEPC protein expressed in E. coli and purified to homogeneity, possessed in vitro ß-carboxylation activity that is determined using a coupled reaction converting PEP into malate. Tetramer is the most active form, however, it exists in various oligomeric forms depending upon the protein concentration, pH, ionic strength of the media and presence of its substrate or effecters. Recombinant PgPEPC protein confers enhanced growth advantage to E. coli under harsh growth conditions in comparison to their respective controls; suggesting that PgPEPC plays a significant role in stress adaptation.     

ngLOC: software and web server for predicting protein subcellular localization in prokaryotes and eukaryotes

ABSTRACT: BACKGROUND: Understanding protein subcellular localization is a necessary component toward understanding the overall function of a protein. Numerous computational methods have been published over the past decade, with varying degrees of success. Despite the large number of published methods in this area, only a small fraction of them are available for researchers to use in their own studies. Of those that are available, many are limited by predicting only a small number of major organelles in the cell. Additionally, the majority of methods predict only a single location, even though it is known that a large fraction of the proteins in eukaryotic species shuttle between locations to carry out their function. FINDINGS: We present a software package and a web server for predicting subcellular localization of protein sequences based on the ngLOC method. ngLOC is an n-gram-based Bayesian classifier that predicts subcellular localization of proteins both in prokaryotes and eukaryotes. The overall prediction accuracy varies from 89.8% to 91.4% across species. This program can predict 11 distinct locations each in plant and animal species. ngLOC also predicts 4 and 5 distinct locations on gram-positive and gram-negative bacterial datasets, respectively. CONCLUSIONS: ngLOC is a generic method that can be trained by data from a variety of species or classes for predicting protein subcellular localization. The standalone software is freely available for academic use under GNU GPL, and the ngLOC web server is also accessible at http://ngloc.unmc.edu.     

Conserved motifs in voltage-sensing and pore-forming modules of voltage-gated ion channel proteins

Voltage-gated ion channels (VGCs) mediate selective diffusion of ions across cell membranes to enable many vital cellular processes. Three-dimensional structure data are lacking for VGC proteins; hence, to better understand their function, there is a need to identify the conserved motifs using sequence analysis methods. In this study, we have used a profile-to-profile alignment method to identify several new conserved motifs specific to each transmembrane segment (TMS) of the voltage-sensing and the pore-forming modules of Ca2+, Na+, and K+ channel subfamilies. For Ca2+ and Na+, the functional theme of motif conservation is similar in all segments while they differ with those of the K+ channel proteins. Nevertheless, the conservation is strikingly similar in the S4 segment of the voltage-sensing module across all subfamilies. In each subfamily and for each TMS, we have identified conserved motifs/residues and correlated their functional significance and disease associations in human, using mutational data from the literature.