Sequence-specific protein aggregation generates defined protein knockdowns in plants

Protein aggregation is determined by short (5-15 amino acids) aggregation-prone regions (APRs) of the polypeptide sequence that self-associate in a specific manner to form beta-structured inclusions. Here, we demonstrate that the sequence specificity of APRs can be exploited to selectively knock down proteins with different localization and function in plants. Synthetic aggregation-prone peptides derived from the APRs of either the negative regulators of the brassinosteroid (BR) signaling, the glycogen synthase kinase 3/Arabidopsis SHAGGY-like kinases (GSK3/ASKs), or the starch-degrading enzyme alpha-glucan water dikinase were designed. Stable expression of the APRs in Arabidopsis (Arabidopsis thaliana) and maize (Zea mays) induced aggregation of the target proteins, giving rise to plants displaying constitutive BR responses and increased starch content, respectively. Overall, we show that the sequence specificity of APRs can be harnessed to generate aggregation-associated phenotypes in a targeted manner in different subcellular compartments. This study points toward the potential application of induced targeted aggregation as a useful tool to knock down protein functions in plants and, especially, to generate beneficial traits in crops

ThermoPhyl : a software tool for selecting phylogenetically optimized conventional and quantitative-PCR taxon-targeted assays for use with complex samples

The ability to specifically and sensitively target genotypes of interest is critical for the success of many PCR-based analyses of environmental or clinical samples that contain multiple templates.Next-generation sequence data clearly show that such samples can harbour hundreds to thousands of operational taxonomic units; a richness which precludes the manual evaluation of candidate assay specificity and sensitivity using multiple sequence alignments. To solve this problem we have developed and validated a free software tool which automates the identification of PCR assays targeting specific genotypes in complex samples. ThermoPhyl uses user-defined target and non-target sequence databases to assess the phylogenetic sensitivity and specificity of thermodynamically optimised candidate assays derived from primer design software packages. ThermoPhyl takes its name from its central premise of testing Thermodynamically optimal assays for Phylogenetic specificity and sensitivity and can be used for two primer (traditional PCR) or two primers with an internal probe (e.g. TaqMan® qPCR) applications and potentially for oligonucleotide probes.Here we describe the use of ThermoPhyl for traditional PCR and qPCR assays. PCR assays selected using ThermoPhyl were validated using 454 pyrosequencing of a traditional specific PCR assay and with a set of four genotype-specific qPCR assays applied to estuarine sediment samples

Labeling of Unique Sequences in Double-Stranded DNA at Sites of Vicinal Nicks Generated by Nicking Endonucleases

We describe a new approach for labeling of unique sequences within dsDNA under nondenaturing conditions. The method is based on the site-specific formation of vicinal nicks, which are created by nicking endonucleases (NEases) at specified DNA sites on the same strand within dsDNA. The oligomeric segment flanked by both nicks is then substituted, in a strand displacement reaction, by an oligonucleotide probe that becomes covalently attached to the target site upon subsequent ligation. Monitoring probe hybridization and ligation reactions by electrophoretic mobility retardation assay, we show that selected target sites can be quantitatively labeled with excellent sequence specificity. In these experiments, predominantly probes carrying a target-independent 3′ terminal sequence were employed. At target labeling, thus a branched DNA structure known as 3′-flap DNA is obtained. The single-stranded terminus in 3′-flap DNA is then utilized to prime the replication of an externally supplied ssDNA circle in a rolling circle amplification (RCA) reaction. In model experiments with samples comprised of genomic λ-DNA and human herpes virus 6 type B (HHV-6B) DNA, we have used our labeling method in combination with surface RCA as reporter system to achieve both high sequence specificity of dsDNA targeting and high sensitivity of detection. The method can find applications in sensitive and specific detection of viral duplex DNA.Wallace A. Coulter Foundatio

An entropy based heuristic model for predicting functional sub-type divisions of protein families

Multiple sequence alignments of protein families are often used for locating residues that are widely apart in the sequence, which are considered as influential for determining functional specificity of proteins towards various substrates, ligands, DNA and other proteins. In this paper, we propose an entropy-score based heuristic algorithm model for predicting functional sub-family divisions of protein families, given the multiple sequence alignment of the protein family as input without any functional sub-type or key site information given for any protein sequence. Two of the experimented test-cases are reported in this paper. First test-case is Nucleotidyl Cyclase protein family consisting of guanalyate and adenylate cyclases. And the second test-case is a dataset of proteins taken from six superfamilies in Structure-Function Linkage Database (SFLD). Results from these test-cases are reported in terms of confirmed sub-type divisions with phylogeny relations from former studies in the literature

In silico prediction of mutant HIV-1 proteases cleaving a target sequence

HIV-1 protease represents an appealing system for directed enzyme re-design, since it has various different endogenous targets, a relatively simple structure and it is well studied. Recently Chaudhury and Gray (Structure (2009) 17: 1636 -- 1648) published a computational algorithm to discern the specificity determining residues of HIV-1 protease. In this paper we present two computational tools aimed at re-designing HIV-1 protease, derived from the algorithm of Chaudhuri and Gray. First, we present an energy-only based methodology to discriminate cleavable and non cleavable peptides for HIV-1 proteases, both wild type and mutant. Secondly, we show an algorithm we developed to predict mutant HIV-1 proteases capable of cleaving a new target substrate peptide, different from the natural targets of HIV-1 protease. The obtained in silico mutant enzymes were analyzed in terms of cleavability and specificity towards the target peptide using the energy-only methodology. We found two mutant proteases as best candidates for specificity and cleavability towards the target sequence

A Peptide Core Motif for Binding to Heterotrimeric G Protein α Subunits

Recently, in vitro selection using mRNA display was used to identify a novel peptide sequence that binds with high affinity to G{alpha}i1. The peptide was minimized to a 9-residue sequence (R6A-1) that retains high affinity and specificity for the GDP-bound state of G{alpha}i1 and acts as a guanine nucleotide dissociation inhibitor (GDI). Here we demonstrate that the R6A-1 peptide interacts with G{alpha} subunits representing all four G protein classes, acting as a core motif for G{alpha} interaction. This contrasts with the consensus G protein regulatory(GPR) sequence, a 28-mer peptide GDI derived from the GoLoco (G{alpha}i/0-Loco interaction)/GPR motif that shares no homology with R6A-1 and binds only to G{alpha}i1-3 in this assay. Binding of R6A-1 is generally specific to the GDP-bound state of the G{alpha} subunits and excludes association with G{beta}{gamma}. R6A-G{alpha}i1 complexes are resistant to trypsin digestion and exhibit distinct stability in the presence of Mg2+, suggesting that the R6A and GPR peptides exert their activities using different mechanisms. Studies using G{alpha}i1/G{alpha}s chimeras identify two regions of G{alpha}i1 (residues 1–35 and 57–88) as determinants for strong R6A-Gi{alpha}1 interaction. Residues flanking the R6A-1 peptide confer unique binding properties, indicating that the core motif could be used as a starting point for the development of peptides exhibiting novel activities and/or specificity for particular G protein subclasses or nucleotide-bound states

Error thresholds for self- and cross-specific enzymatic replication

The information content of a non-enzymatic self-replicator is limited by Eigen's error threshold. Presumably, enzymatic replication can maintain higher complexity, but in a competitive environment such a replicator is faced with two problems related to its twofold role as enzyme and substrate: as enzyme, it should replicate itself rather than wastefully copy non-functional substrates, and as substrate it should preferably be replicated by superior enzymes instead of less-efficient mutants. Because specific recognition can enforce these propensities, we thoroughly analyze an idealized quasispecies model for enzymatic replication, with replication rates that are either a decreasing (self-specific) or increasing (cross-specific) function of the Hamming distance between the recognition or "tag" sequences of enzyme and substrate. We find that very weak self-specificity suffices to localize a population about a master sequence and thus to preserve its information, while simultaneous localization about complementary sequences in the cross-specific case is more challenging. A surprising result is that stronger specificity constraints allow longer recognition sequences, because the populations are better localized. Extrapolating from experimental data, we obtain rough quantitative estimates for the maximal length of the recognition or tag sequence that can be used to reliably discriminate appropriate and infeasible enzymes and substrates, respectively.Comment: 23 pages, 7 figures; final version as publishe