A facile scheme for biosynthesis of peptides with no length constraints

While peptide drugs have become a viable class of biomedicines, efficient peptide expression and purification remains a critical technological need. We previous discovered that a number of self-assembling peptides such as 18A (EWLKAFYEKVLEKLKELF) and ELK16 (LELELKLKLELELKLK), when fused terminally to a target protein, can drive the target protein into active protein aggregates in vivo. A simple and rapid scheme for expression and purification of recombinant proteins using Escherichia coli was thus devised, by inserting a self-cleavable intein like Mxe GyrA between the self-assembling peptide and the target protein. In this scheme, the fusion protein is first expressed in the form of active aggregates, then separated by centrifugation upon cell lysis. Subsequently, the DTT-mediated intein self-cleavage reaction releases the target protein into solution. These self-assembling peptides together with the associated inteins constitute a set of cleavable self-aggregating tags (cSA), and provide an efficient route for the production of proteins with modest purity. More recently, this scheme has been applied to the biosynthesis of peptides, in particular those with lengths greater than 20 amino acids. A more efficient intein has also been engineered to afford the generation of authentic N-termini for the peptides. We believe this scheme will facilitate the development of more peptide drug candidates, and also lowering the costs of production of peptides of any length

Deep Boosting: Layered Feature Mining for General Image Classification

Constructing effective representations is a critical but challenging problem in multimedia understanding. The traditional handcraft features often rely on domain knowledge, limiting the performances of exiting methods. This paper discusses a novel computational architecture for general image feature mining, which assembles the primitive filters (i.e. Gabor wavelets) into compositional features in a layer-wise manner. In each layer, we produce a number of base classifiers (i.e. regression stumps) associated with the generated features, and discover informative compositions by using the boosting algorithm. The output compositional features of each layer are treated as the base components to build up the next layer. Our framework is able to generate expressive image representations while inducing very discriminate functions for image classification. The experiments are conducted on several public datasets, and we demonstrate superior performances over state-of-the-art approaches.Comment: 6 pages, 4 figures, ICME 201

STATISTICAL ISSUES IN EFFICACY EVALUATION FOR COMPANION ANIMAL DRUG DEVELOPMENT

Companion animals, commonly called pets, are animals such as dogs, cats, and horses. The companion animal drug market has expanded rapidly in recent years. Two major points of focus in companion animal drug development are therapeutics and parasiticides. From a statistics point of view, experimental design, experimental unit determination, sample size estimation and reestimation, treatment design, data transformation, multiple testing, and proper modeling are major statistical issues when efficacy evaluation in a companion animal study is conducted. These major statistical issues are addressed using two clinical studies as examples: Reconcile® (Fluoxetine) for the treatment of separation anxiety in dogs and Comfortis® (Spinosad) for the control of fleas in dogs

Screening of Random Peptide Library of Hemagglutinin from Pandemic 2009 A(H1N1) Influenza Virus Reveals Unexpected Antigenically Important Regions

The antigenic structure of the membrane protein hemagglutinin (HA) from the 2009 A(H1N1) influenza virus was dissected with a high-throughput screening method using complex antisera. The approach involves generating yeast cell libraries displaying a pool of random peptides of controllable lengths on the cell surface, followed by one round of fluorescence-activated cell sorting (FACS) against antisera from mouse, goat and human, respectively. The amino acid residue frequency appearing in the antigenic peptides at both the primary sequence and structural level was determined and used to identify “hot spots” or antigenically important regions. Unexpectedly, different antigenic structures were seen for different antisera. Moreover, five antigenic regions were identified, of which all but one are located in the conserved HA stem region that is responsible for membrane fusion. Our findings are corroborated by several recent studies on cross-neutralizing H1 subtype antibodies that recognize the HA stem region. The antigenic peptides identified may provide clues for creating peptide vaccines with better accessibility to memory B cells and better induction of cross-neutralizing antibodies than the whole HA protein. The scheme used in this study enables a direct mapping of the antigenic regions of viral proteins recognized by antisera, and may be useful for dissecting the antigenic structures of other viral proteins

Functional expression of horseradish peroxidase in Saccharomyces cerevisiae and Pichia pastoris

The ability to engineer proteins by directed evolution requires functional expression of the target polypeptide in a recombinant host suitable for construction and screening libraries of enzyme variants. Bacteria and yeast are preferred, but eukaryotic proteins often fail to express in active form in these cells. We have attempted to resolve this problem by identifying mutations in the target gene that facilitate its functional expression in a given recombinant host. Here we examined expression of HRP in Saccharomyces cerevisiae. Through three rounds of directed evolution by random point mutagenesis and screening, we obtained a 40-fold increase in total HRP activity in the S.cerevisiae culture supernatant compared with wild-type, as measured on ABTS [2,2′-azinobis(3-ethylbenzthiazoline-6-sulfonic acid)] (260 units/l/OD_(600)). Genes from wild-type and two high-activity clones were expressed in Pichia pastoris, where the total ABTS activity reached 600 units/l/OD_(600) in shake flasks. The mutants show up to 5.4-fold higher specific activity towards ABTS and 2.3-fold higher specific activity towards guaiacol

Streamlined protein expression and purification using cleavable self-aggregating tags

<p>Abstract</p> <p>Background</p> <p>Recombinant protein expression and purification remains a fundamental issue for biotechnology. Recently we found that two short self-assembling amphipathic peptides 18A (EWLKAFYEKVLEKLKELF) and ELK16 (LELELKLKLELELKLK) can induce the formation of active protein aggregates in <it>Escherichia coli </it>(<it>E. coli</it>), in which the target proteins retain high enzymatic activities. Here we further explore this finding to develop a novel, facile, matrix-free protein expression and purification approach.</p> <p>Results</p> <p>In this paper, we describe a streamlined protein expression and purification approach by using cleavable self-aggregating tags comprising of one amphipathic peptide (18A or ELK16) and an intein molecule. In such a scheme, a target protein is first expressed as active protein aggregate, separated by simple centrifugation, and then released into solution by intein-mediated cleavage. Three target proteins including lipase A, amadoriase II and β-xylosidase were used to demonstrate the feasibility of this approach. All the target proteins released after cleavage were highly active and pure (over 90% in the case of intein-ELK16 fusions). The yields were in the range of 1.6-10.4 μg/mg wet cell pellet at small laboratory scale, which is comparable with the typical yields from the classical his-tag purification, the IMPACT-CN system (New England Biolabs, Beverly, MA), and the ELP tag purification scheme.</p> <p>Conclusions</p> <p>This tested single step purification is capable of producing proteins with high quantity and purity. It can greatly reduce the cost and time, and thus provides application potentials for both industrial scale up and laboratorial usage.</p

Active protein aggregates induced by terminally attached self-assembling peptide ELK16 in Escherichia coli

<p>Abstract</p> <p>Background</p> <p>In recent years, it has been gradually realized that bacterial inclusion bodies (IBs) could be biologically active. In particular, several proteins including green fluorescent protein, β-galactosidase, β-lactamase, alkaline phosphatase, <smcaps>D</smcaps>-amino acid oxidase, polyphosphate kinase 3, maltodextrin phosphorylase, and sialic acid aldolase have been successfully produced as active IBs when fused to an appropriate partner such as the foot-and-mouth disease virus capsid protein VP1, or the human β-amyloid peptide Aβ42(F19D). As active IBs may have many attractive advantages in enzyme production and industrial applications, it is of considerable interest to explore them further.</p> <p>Results</p> <p>In this paper, we report that an ionic self-assembling peptide ELK16 (LELELKLK)₂was able to effectively induce the formation of cytoplasmic inclusion bodies in <it>Escherichia coli </it>(<it>E. coli</it>) when attached to the carboxyl termini of four model proteins including lipase A, amadoriase II, β-xylosidase, and green fluorescent protein. These aggregates had a general appearance similar to the usually reported cytoplasmic inclusion bodies (IBs) under transmission electron microscopy or fluorescence confocal microscopy. Except for lipase A-ELK16 fusion, the three other fusion protein aggregates retained comparable specific activities with the native counterparts. Conformational analyses by Fourier transform infrared spectroscopy revealed the existence of newly formed antiparallel beta-sheet structures in these ELK16 peptide-induced inclusion bodies, which is consistent with the reported assembly of the ELK16 peptide.</p> <p>Conclusions</p> <p>This has been the first report where a terminally attached self-assembling β peptide ELK16 can promote the formation of active inclusion bodies or active protein aggregates in <it>E. coli</it>. It has the potential to render <it>E. coli </it>and other recombinant hosts more efficient as microbial cell factories for protein production. Our observation might also provide hints for protein aggregation-related diseases.</p