ConcatSeq: A method for increasing throughput of single molecule sequencing by concatenating short DNA fragments.

Single molecule sequencing (SMS) platforms enable base sequences to be read directly from individual strands of DNA in real-time. Though capable of long read lengths, SMS platforms currently suffer from low throughput compared to competing short-read sequencing technologies. Here, we present a novel strategy for sequencing library preparation, dubbed ConcatSeq, which increases the throughput of SMS platforms by generating long concatenated templates from pools of short DNA molecules. We demonstrate adaptation of this technique to two target enrichment workflows, commonly used for oncology applications, and feasibility using PacBio single molecule real-time (SMRT) technology. Our approach is capable of increasing the sequencing throughput of the PacBio RSII platform by more than five-fold, while maintaining the ability to correctly call allele frequencies of known single nucleotide variants. ConcatSeq provides a versatile new sample preparation tool for long-read sequencing technologies.

Digital microfluidic assay for protein detection.

Global studies of the human proteome have revealed a plethora of putative protein biomarkers. However, their application for early disease detection remains at a standstill without suitable methods to realize their utility in the clinical setting. There thus continues to be tremendous interest in developing new technology for sensitive protein detection that is both low in cost and carries a small footprint to be able to be used at the point of care. The current gold standard method for protein biomarker detection is the ELISA, which measures protein abundance using bulky fluorescent scanners that lack portability. Here, we present a digital microfluidic platform for protein biomarker detection that is low in cost compared with standard optical detection methods, without any compromise in sensitivity. This platform furthermore makes use of simple electronics, enabling its translation into a portable handheld device, and has been developed in a manner that can easily be adapted to assay different types of proteomic biomarkers. We demonstrate its utility in quantifying not only protein abundance, but also activity. Interleukin-6 abundance could be assayed from concentrations as low as 50 pM (an order of magnitude lower than that detectable by a comparable laboratory designed ELISA) using less than 5 µL of sample, and Abelson tyrosine kinase activity was detectable in samples containing 100 pM of kinase.

Dissecting phosphorylation networks: lessons learned from yeast.

Protein phosphorylation continues to be regarded as one of the most important post-translational modifications found in eukaryotes and has been implicated in key roles in the development of a number of human diseases. In order to elucidate roles for the 518 human kinases, phosphorylation has routinely been studied using the budding yeast Saccharomyces cerevisiae as a model system. In recent years, a number of technologies have emerged to globally map phosphorylation in yeast. In this article, we review these technologies and discuss how these phosphorylation mapping efforts have shed light on our understanding of kinase signaling pathways and eukaryotic proteomic networks in general.

MOTIPS: automated motif analysis for predicting targets of modular protein domains.

BACKGROUND: Many protein interactions, especially those involved in signaling, involve short linear motifs consisting of 5-10 amino acid residues that interact with modular protein domains such as the SH3 binding domains and the kinase catalytic domains. One straightforward way of identifying these interactions is by scanning for matches to the motif against all the sequences in a target proteome. However, predicting domain targets by motif sequence alone without considering other genomic and structural information has been shown to be lacking in accuracy. RESULTS: We developed an efficient search algorithm to scan the target proteome for potential domain targets and to increase the accuracy of each hit by integrating a variety of pre-computed features, such as conservation, surface propensity, and disorder. The integration is performed using naïve Bayes and a training set of validated experiments. CONCLUSIONS: By integrating a variety of biologically relevant features to predict domain targets, we demonstrated a notably improved prediction of modular protein domain targets. Combined with emerging high-resolution data of domain specificities, we believe that our approach can assist in the reconstruction of many signaling pathways.

Deciphering protein kinase specificity through large-scale analysis of yeast phosphorylation site motifs.

Phosphorylation is a universal mechanism for regulating cell behavior in eukaryotes. Although protein kinases target short linear sequence motifs on their substrates, the rules for kinase substrate recognition are not completely understood. We used a rapid peptide screening approach to determine consensus phosphorylation site motifs targeted by 61 of the 122 kinases in Saccharomyces cerevisiae. By correlating these motifs with kinase primary sequence, we uncovered previously unappreciated rules for determining specificity within the kinase family, including a residue determining P-3 arginine specificity among members of the CMGC [CDK (cyclin-dependent kinase), MAPK (mitogen-activated protein kinase), GSK (glycogen synthase kinase), and CDK-like] group of kinases. Furthermore, computational scanning of the yeast proteome enabled the prediction of thousands of new kinase-substrate relationships. We experimentally verified several candidate substrates of the Prk1 family of kinases in vitro and in vivo and identified a protein substrate of the kinase Vhs1. Together, these results elucidate how kinase catalytic domains recognize their phosphorylation targets and suggest general avenues for the identification of previously unknown kinase substrates across eukaryotes.

Global identification of protein kinase substrates by protein microarray analysis.

Herein, we describe a protocol for the global identification of in vitro substrates targeted by protein kinases using protein microarray technology. Large numbers of fusion proteins tagged at their carboxy-termini are purified in 96-well format and spotted in duplicate onto amino-silane-coated slides in a spatially addressable manner. These arrays are incubated in the presence of purified kinase and radiolabeled ATP, and then washed, dried and analyzed by autoradiography. The extent of phosphorylation of each spot is quantified and normalized, and proteins that are reproducibly phosphorylated in the presence of the active kinase relative to control slides are scored as positive substrates. This approach enables the rapid determination of kinase-substrate relationship on a proteome-wide scale, and although developed using yeast, has since been adapted to higher eukaryotic systems. Expression, purification and printing of the yeast proteome require about 3 weeks. Afterwards, each kinase assay takes approximately 3 h to perform.