Towards a human proteome atlas: high-throughput generation of mono-specific antibodies for tissue profiling

A great need exists for the systematic generation of specific antibodies to explore the human proteome. Here, we show that antibodies specific to human proteins can be generated in a high-throughput manner involving stringent affinity purification using recombinant protein epitope signature tags (PrESTs) as immunogens and affinity-ligands. The specificity of the generated affinity reagents, here called mono-specific antibodies (msAb), were validated with a novel protein microarray assay. The success rate for 464 antibodies generated towards human proteins was more than 90% as judged by the protein array assay. The antibodies were used for parallel profiling of patient biopsies using tissue microarrays generated from 48 human tissues. Comparative analysis with well-characterized monoclonal antibodies showed identical or similar specificity and expression patterns. The results suggest that a comprehensive atlas containing extensive protein expression and subcellular localization data of the human proteome can be generated in an efficient manner with mono-specific antibodies.     

Automated solid-phase subcloning based on beads brought into proximity by magnetic force

In the fields of proteomics, metabolic engineering and synthetic biology there is a need for high-throughput and reliable cloning methods to facilitate construction of expression vectors and genetic pathways. Here, we describe a new approach for solid-phase cloning in which both the vector and the gene are immobilized to separate paramagnetic beads and brought into proximity by magnetic force. Ligation events were directly evaluated using fluorescent-based microscopy and flow cytometry. The highest ligation efficiencies were obtained when gene- and vector-coated beads were brought into close contact by application of a magnet during the ligation step. An automated procedure was developed using a laboratory workstation to transfer genes into various expression vectors and more than 95% correct clones were obtained in a number of various applications. The method presented here is suitable for efficient subcloning in an automated manner to rapidly generate a large number of gene constructs in various vectors intended for high throughput applications.     

L<Subscript>2</Subscript>-norm multiple kernel learning and its application to biomedical data fusion

Background  

This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields different extensions of multiple kernel learning (MKL) such as L _∞, L ₁, and L ₂ MKL. In particular, L ₂ MKL is a novel method that leads to non-sparse optimal kernel coefficients, which is different from the sparse kernel coefficients optimized by the existing L _∞ MKL method. In real biomedical applications, L ₂ MKL may have more advantages over sparse integration method for thoroughly combining complementary information in heterogeneous data sources.     

Comparative analysis of DNA polymorphisms and phylogenetic relationships among Syzygium cumini Skeels based on phenotypic characters and RAPD technique

The Indian black berry (Syzygium cumini Skeels) has a great nutraceutical and medicinal properties. As in other fruit crops, the fruit characteristics are important attributes for differentiation were also determined for different accessions of S. cumini. The fruit weight, length, breadth, length: breadth ratio, pulp weight, pulp content, seed weight and pulp: seed ratio significantly varied in different accessions. Molecular characterization was carried out using PCR based RAPD technique. Out of 80 RAPD primers, only 18 primers produced stable polymorphisms that were used to examine the phylogenetic relationship. A sum of 207 loci were generated out of which 201 loci found polymorphic. The average genetic dissimilarity was 97 per cent among jamun accessions. The phylogenetic relationship was also determined by principal coordinates analysis (PCoA) that explained 46.95 per cent cumulative variance. The two-dimensional PCoA analysis showed grouping of the different accessions that were plotted into four sub-plots, representing clustering of accessions. The UPGMA (r = 0.967) and NJ (r = 0.987) dendrogram constructed based on the dissimilarity matrix revealed a good degree of fit with the cophenetic correlation value. The dendrogram grouped the accessions into three main clusters according to their eco-geographical regions which given useful insight into their phylogenetic relationships.