Semi-automated Magnetic Bead-Based Antibody Selection from Phage Display Libraries

Phage display of combinatorial antibody libraries is a very efficient method for selecting recombinant antibodies against a wide range of molecules. It has been applied very successfully for the generation of therapeutic antibodies for more than a decade. To increase robustness and reproducibility of the selection procedure, we developed a semi-automated selection method for the generation of recombinant antibodies from phage display libraries. In this procedure, the selection targets are specifically immobilised to magnetic particles which can then by automatically handled by a magnetic particle processor. At present up to 96 samples can be handled simultaneously. Applying the processor allows standardisation of panning parameters such as washing conditions, incubation times, or to perform parallel selections on same targets under different buffer conditions. Additionally, the whole protocol has been streamlined to carry out bead loading, phage selection, phage amplification between selection rounds and magnetic particle ELISA for confirmation of binding activity in microtiter plate formats. Until now, this method has been successfully applied to select antibody fragments against different types of target, such as peptides, recombinant or homologous proteins, or chemical compounds

Assessment and optimisation of normalisation methods for dual-colour antibody microarrays

<p>Abstract</p> <p>Background</p> <p>Recent advances in antibody microarray technology have made it possible to measure the expression of hundreds of proteins simultaneously in a competitive dual-colour approach similar to dual-colour gene expression microarrays. Thus, the established normalisation methods for gene expression microarrays, e.g. loess regression, can in principle be applied to protein microarrays. However, the typical assumptions of such normalisation methods might be violated due to a bias in the selection of the proteins to be measured. Due to high costs and limited availability of high quality antibodies, the current arrays usually focus on a high proportion of regulated targets. Housekeeping features could be used to circumvent this problem, but they are typically underrepresented on protein arrays. Therefore, it might be beneficial to select invariant features among the features already represented on available arrays for normalisation by a dedicated selection algorithm.</p> <p>Results</p> <p>We compare the performance of several normalisation methods that have been established for dual-colour gene expression microarrays. The focus is on an invariant selection algorithm, for which effective improvements are proposed. In a simulation study the performances of the different normalisation methods are compared with respect to their impact on the ability to correctly detect differentially expressed features. Furthermore, we apply the different normalisation methods to a pancreatic cancer data set to assess the impact on the classification power.</p> <p>Conclusions</p> <p>The simulation study and the data application demonstrate the superior performance of the improved invariant selection algorithms in comparison to other normalisation methods, especially in situations where the assumptions of the usual global loess normalisation are violated.</p

Uncanny Objects and the Fear of the Familiar:Hiding from Akan Witches in New York City

This article examines the cosmology and secret practices of West African traditional priests in New York City in preventing the spread of witchcraft, an evil invisible spirit transmitted between female members of the Akan matrilineage. Explored is an uncanny dynamic as everyday habitus becomes increasingly strange in the world of a young Ghanaian woman in the Bronx, who has become petrified of insinuations of witchcraft from close family members. In trying to hide the young woman from infection by her fellow witches, Akan priests attempt to ‘capture’ her habits and everyday routines, calling upon the iconic magic of New York City in order to ‘misplace’ familiarity within the anonymity of Manhattan. In this process, the transmission of the witch’s spirit to the intended victim is disturbed as the victim’s life and things are moved. Nowhere to be found, the witch shifts her attention to other victims

Cyclic AMP signalling pathways in the regulation of uterine relaxation

Studying the mechanism(s) of uterine relaxation is important and will be helpful in the prevention of obstetric difficulties such as preterm labour, which remains a major cause of perinatal mortality and morbidity. Multiple signalling pathways regulate the balance between maintaining relative uterine quiescence during gestation, and the transition to the contractile state at the onset of parturition. Elevation of intracellular cyclic AMP promotes myometrial relaxation, and thus quiescence, via effects on multiple intracellular targets including calcium channels, potassium channels and myosin light chain kinase. A complete understanding of cAMP regulatory pathways (synthesis and hydrolysis) would assist in the development of better tocolytics to delay or inhibit preterm labour. Here we review the enzymes involved in cAMP homoeostasis (adenylyl cyclases and phosphodiesterases) and possible myometrial substrates for the cAMP dependent protein kinase. We must emphasise the need to identify novel pharmacological targets in human pregnant myometrium to achieve safe and selective uterine relaxation when this is indicated in preterm labour or other obstetric complications

Mediator Subunit 12 Is Required for Neutrophil Development in Zebrafish

Hematopoiesis requires the spatiotemporal organization of regulatory factors to successfully orchestrate diverse lineage specificity from stem and progenitor cells. Med12 is a regulatory component of the large Mediator complex that enables contact between the general RNA polymerase II transcriptional machinery and enhancer bound regulatory factors. We have identified a new zebrafish med12 allele, syr, with a single missense mutation causing a valine to aspartic acid change at position 1046. Syr shows defects in hematopoiesis, which predominantly affect the myeloid lineage. Syr has identified a hematopoietic cell-specific requirement for Med12, suggesting a new role for this transcriptional regulator

Discovery of High-Affinity Protein Binding Ligands – Backwards

BACKGROUND: There is a pressing need for high-affinity protein binding ligands for all proteins in the human and other proteomes. Numerous groups are working to develop protein binding ligands but most approaches develop ligands using the same strategy in which a large library of structured ligands is screened against a protein target to identify a high-affinity ligand for the target. While this methodology generates high-affinity ligands for the target, it is generally an iterative process that can be difficult to adapt for the generation of ligands for large numbers of proteins. METHODOLOGY/PRINCIPAL FINDINGS: We have developed a class of peptide-based protein ligands, called synbodies, which allow this process to be run backwards--i.e. make a synbody and then screen it against a library of proteins to discover the target. By screening a synbody against an array of 8,000 human proteins, we can identify which protein in the library binds the synbody with high affinity. We used this method to develop a high-affinity synbody that specifically binds AKT1 with a K(d)<5 nM. It was found that the peptides that compose the synbody bind AKT1 with low micromolar affinity, implying that the affinity and specificity is a product of the bivalent interaction of the synbody with AKT1. We developed a synbody for another protein, ABL1 using the same method. CONCLUSIONS/SIGNIFICANCE: This method delivered a high-affinity ligand for a target protein in a single discovery step. This is in contrast to other techniques that require subsequent rounds of mutational improvement to yield nanomolar ligands. As this technique is easily scalable, we believe that it could be possible to develop ligands to all the proteins in any proteome using this approach

Novel Peptide-Mediated Interactions Derived from High-Resolution 3-Dimensional Structures

Many biological responses to intra- and extracellular stimuli are regulated through complex networks of transient protein interactions where a globular domain in one protein recognizes a linear peptide from another, creating a relatively small contact interface. These peptide stretches are often found in unstructured regions of proteins, and contain a consensus motif complementary to the interaction surface displayed by their binding partners. While most current methods for the de novo discovery of such motifs exploit their tendency to occur in disordered regions, our work here focuses on another observation: upon binding to their partner domain, motifs adopt a well-defined structure. Indeed, through the analysis of all peptide-mediated interactions of known high-resolution three-dimensional (3D) structure, we found that the structure of the peptide may be as characteristic as the consensus motif, and help identify target peptides even though they do not match the established patterns. Our analyses of the structural features of known motifs reveal that they tend to have a particular stretched and elongated structure, unlike most other peptides of the same length. Accordingly, we have implemented a strategy based on a Support Vector Machine that uses this features, along with other structure-encoded information about binding interfaces, to search the set of protein interactions of known 3D structure and to identify unnoticed peptide-mediated interactions among them. We have also derived consensus patterns for these interactions, whenever enough information was available, and compared our results with established linear motif patterns and their binding domains. Finally, to cross-validate our identification strategy, we scanned interactome networks from four model organisms with our newly derived patterns to see if any of them occurred more often than expected. Indeed, we found significant over-representations for 64 domain-motif interactions, 46 of which had not been described before, involving over 6,000 interactions in total for which we could suggest the molecular details determining the binding

Suppression of p75 Neurotrophin Receptor Surface Expression with Intrabodies Influences Bcl-xL mRNA Expression and Neurite Outgrowth in PC12 Cells

Background: Although p75 neurotrophin receptor (p75NTR) is the first neurotrophin receptor isolated, its diverse physiological functions and signaling have remained elusive for many years. Loss-of-function phenotypic analyses for p75NTR were mainly focused at the genetic level; however these approaches were impacted by off-target effect, insufficient stability, unspecific stress response or alternative active splicing products. In this study, p75NTR surface expression was suppressed for the first time at the protein level by endoplasmic reticulum (ER) retained intrabodies. Results: Three monoclonal recombinant antibody fragments (scFv) with affinities in the low nanomolar range to murine p75NTR were isolated by antibody phage display. To suppress p75NTR cell surface expression, the encoding genes of these scFvs extended by the ER retention peptide KDEL were transiently transfected into the neuron-like rat pheochromocytoma cell line PC12 and the mouse neuroblastoma x mouse spinal cord hybrid cell line NSC19. The ER retained intrabody construct, SH325-G7-KDEL, mediated a downregulation of p75NTR cell surface expression as shown by flow cytometry. This effect was maintained over a period of at least eight days without activating an unfolded protein response (UPR). Moreover, the ER retention of p75NTR resulted in downregulation of mRNA levels of the anti-apoptotic protein Bcl-xL as well as in strong inhibition of NGF-induced neurite outgrowth in PC12 cells. Conclusion: The ER retained intrabody SH325-G7-KDEL not only induces phenotypic knockdown of this p75NTR but als

Thermodynamic Additivity of Sequence Variations: An Algorithm for Creating High Affinity Peptides Without Large Libraries or Structural Information

BACKGROUND: There is a significant need for affinity reagents with high target affinity/specificity that can be developed rapidly and inexpensively. Existing affinity reagent development approaches, including protein mutagenesis, directed evolution, and fragment-based design utilize large libraries and/or require structural information thereby adding time and expense. Until now, no systematic approach to affinity reagent development existed that could produce nanomolar affinity from small chemically synthesized peptide libraries without the aid of structural information. METHODOLOGY/PRINCIPAL FINDINGS: Based on the principle of additivity, we have developed an algorithm for generating high affinity peptide ligands. In this algorithm, point-variations in a lead sequence are screened and combined in a systematic manner to achieve additive binding energies. To demonstrate this approach, low-affinity lead peptides for multiple protein targets were identified from sparse random sequence space and optimized to high affinity in just two chemical steps. In one example, a TNF-α binding peptide with K(d) = 90 nM and high target specificity was generated. The changes in binding energy associated with each variation were generally additive upon combining variations, validating the basis of the algorithm. Interestingly, cooperativity between point-variations was not observed, and in a few specific cases, combinations were less than energetically additive. CONCLUSIONS/SIGNIFICANCE: By using this additivity algorithm, peptide ligands with high affinity for protein targets were generated. With this algorithm, one of the highest affinity TNF-α binding peptides reported to date was produced. Most importantly, high affinity was achieved from small, chemically-synthesized libraries without the need for structural information at any time during the process. This is significantly different than protein mutagenesis, directed evolution, or fragment-based design approaches, which rely on large libraries and/or structural guidance. With this algorithm, high affinity/specificity peptide ligands can be developed rapidly, inexpensively, and in an entirely chemical manner