De Novo Design and Experimental Characterization of Ultrashort Self-Associating Peptides

Self-association is a common phenomenon in biology and one that can have positive and negative impacts, from the construction of the architectural cytoskeleton of cells to the formation of fibrils in amyloid diseases. Understanding the nature and mechanisms of self-association is important for modulating these systems and in creating biologically-inspired materials. Here, we present a two-stage de novo peptide design framework that can generate novel self-associating peptide systems. The first stage uses a simulated multimeric template structure as input into the optimization-based Sequence Selection to generate low potential energy sequences. The second stage is a computational validation procedure that calculates Fold Specificity and/or Approximate Association Affinity (K^*_association) based on metrics that we have devised for multimeric systems. This framework was applied to the design of self-associating tripeptides using the known self-associating tripeptide, Ac-IVD, as a structural template. Six computationally predicted tripeptides (Ac-LVE, Ac-YYD, Ac-LLE, Ac-YLD, Ac-MYD, Ac-VIE) were chosen for experimental validation in order to illustrate the self-association outcomes predicted by the three metrics. Self-association and electron microscopy studies revealed that Ac-LLE formed bead-like microstructures, Ac-LVE and Ac-YYD formed fibrillar aggregates, Ac-VIE and Ac-MYD formed hydrogels, and Ac-YLD crystallized under ambient conditions. An X-ray crystallographic study was carried out on a single crystal of Ac-YLD, which revealed that each molecule adopts a β-strand conformation that stack together to form parallel β-sheets. As an additional validation of the approach, the hydrogel-forming sequences of Ac-MYD and Ac-VIE were shuffled. The shuffled sequences were computationally predicted to have lower K^*_association values and were experimentally verified to not form hydrogels. This illustrates the robustness of the framework in predicting self-associating tripeptides. We expect that this enhanced multimeric de novo peptide design framework will find future application in creating novel self-associating peptides based on unnatural amino acids, and inhibitor peptides of detrimental self-aggregating biological proteins.     

Clinical and Molecular Characterization of Patients with Distal 11q Deletions

Jacobsen syndrome is caused by segmental aneusomy for the distal end of the long arm of chromosome 11. Typical features include mild to moderate psychomotor retardation, trigonocephaly, facial dysmorphism, cardiac defects, and thrombocytopenia, though none of these features are invariably present. To define the critical regions responsible for these abnormalities, we studied 17 individuals with de novo terminal deletions of 11q. The patients were characterized in a loss-of-heterozygosity analysis using polymorphic dinucleotide repeats. The breakpoints in the complete two-generation families were localized with an average resolution of 3.9 cM. Eight patients with the largest deletions extending from 11q23.3 to 11qter have breakpoints, between D11S924 and D11S1341. This cytogenetic region accounts for the majority of 11q⁻ patients and may be related to the FRA11B fragile site in 11q23.3. One patient with a small terminal deletion distal to D11S1351 had facial dysmorphism, cardiac defects, and thrombocytopenia, suggesting that the genes responsible for these features may lie distal to D11S1351. Twelve of 15 patients with deletion breakpoints as far distal as D11S1345 had trigonocephaly, while patients with deletions distal to D11S912 did not, suggesting that, if hemizygosity for a single gene is responsible for this dysmorphic feature, the gene may lie distal to D11S1345 and proximal to D11S912.     

De novo deletion of chromosome 20q13.33 in a patient with tracheo-esophageal fistula, cardiac defects and genitourinary anomalies implicates GTPBP5 as a candidate gene

BACKGROUND

Tracheo‐esophageal fistula (TEF) with/or without esophageal atresia (EA) is a common congenital malformation that is often accompanied by other anomalies. The causes of this condition are thought to be heterogeneous but are overall not well understood.

CASE REPORT

We identified a patient with a TEF/EA, as well as cardiac and genitourinary anomalies, who was found to have a 0.7 Mb de novo deletion of chromosome 20q13.33. One gene within the deleted interval, GTPBP5, is of particular interest as a candidate gene.

CONCLUSIONS

GTPBP5 bears further study as a cause of TEF/EA accompanied by other malformations. Birth Defects Research (Part A) 2011. © 2011 Wiley‐Liss, Inc.     

PERGA: A Paired-End Read Guided De Novo Assembler for Extending Contigs Using SVM and Look Ahead Approach

Since the read lengths of high throughput sequencing (HTS) technologies are short, de novo assembly which plays significant roles in many applications remains a great challenge. Most of the state-of-the-art approaches base on de Bruijn graph strategy and overlap-layout strategy. However, these approaches which depend on k-mers or read overlaps do not fully utilize information of paired-end and single-end reads when resolving branches. Since they treat all single-end reads with overlapped length larger than a fix threshold equally, they fail to use the more confident long overlapped reads for assembling and mix up with the relative short overlapped reads. Moreover, these approaches have not been special designed for handling tandem repeats (repeats occur adjacently in the genome) and they usually break down the contigs near the tandem repeats. We present PERGA (Paired-End Reads Guided Assembler), a novel sequence-reads-guided de novo assembly approach, which adopts greedy-like prediction strategy for assembling reads to contigs and scaffolds using paired-end reads and different read overlap size ranging from O _max to O _min to resolve the gaps and branches. By constructing a decision model using machine learning approach based on branch features, PERGA can determine the correct extension in 99.7% of cases. When the correct extension cannot be determined, PERGA will try to extend the contig by all feasible extensions and determine the correct extension by using look-ahead approach. Many difficult-resolved branches are due to tandem repeats which are close in the genome. PERGA detects such different copies of the repeats to resolve the branches to make the extension much longer and more accurate. We evaluated PERGA on both Illumina real and simulated datasets ranging from small bacterial genomes to large human chromosome, and it constructed longer and more accurate contigs and scaffolds than other state-of-the-art assemblers. PERGA can be freely downloaded at https://github.com/hitbio/PERGA.     

Parental Imbalances Involving Chromosomes 15q and 22q May Predispose to the Formation of De Novo Pathogenic Microdeletions and Microduplications in the Offspring

Microarray-based comparative genomic hybridization (array-CGH) led to the discovery of genetic abnormalities among patients with complex phenotype and normal karyotype. Also several apparently normal individuals have been found to be carriers of cryptic imbalances, hence the importance to perform parental investigations after the identification of a deletion/duplication in a proband. Here, we report the molecular cytogenetic characterization of two individuals in which the microdeletions/duplications present in their parents could have predisposed and facilitated the formation of de novo pathogenic different copy number variations (CNVs). In family 1, a 4-year-old girl had a de novo pathogenic 10.5 Mb duplication at 15q21.2q22.2, while her mother showed a 2.262 Mb deletion at 15q13.2q13.3; in family 2, a 9-year-old boy had a de novo 1.417 Mb deletion at 22q11.21 and a second paternal deletion of 247 Kb at 22q11.23 on the same chromosome 22. Chromosome 22 at band q11.2 and chromosome 15 at band q11q13 are considered unstable regions. We could hypothesize that 15q13.2q13.3 and 22q11.21 deletions in the two respective parents might have increased the risk of rearrangements in their children. This study highlights the difficulty to make genetic counseling and predict the phenotypic consequences in these situations.     

Design and Synthesis of De Novo Peptide for Manganese Binding

The de novo peptide with 63-residues (MHB) has been synthesized biochemically and used for the binding of manganese (II) ions. In designed peptide, the leucine of the peptide dA1 (prototype) was replaced by His27 and Asp41 for binding the manganese (II) ions. The different chromatography studies and mass determination showed that new peptide folds into a monomeric, highly helical with a active site structure similar to the native Mn–SOD in an aqueous solution. Electron paramagnetic resonance (EPR) study suggested that the peptide binds single manganese (II) ion per molecule loosely with K _D value of about 36 μM. The circular dichroism (CD) studies demonstrated that the helical contents of the peptide did not change significantly even after binding the metal ions. The SOD activity study of the Mn–peptide complex showed that the IC₅₀ values is 8.08 μM.     

A Likelihood-Based Framework for Variant Calling and De Novo Mutation Detection in Families

Family samples, which can be enriched for rare causal variants by focusing on families with multiple extreme individuals and which facilitate detection of de novo mutation events, provide an attractive resource for next-generation sequencing studies. Here, we describe, implement, and evaluate a likelihood-based framework for analysis of next generation sequence data in family samples. Our framework is able to identify variant sites accurately and to assign individual genotypes, and can handle de novo mutation events, increasing the sensitivity and specificity of variant calling and de novo mutation detection. Through simulations we show explicit modeling of family relationships is especially useful for analyses of low-frequency variants and that genotype accuracy increases with the number of individuals sequenced per family. Compared with the standard approach of ignoring relatedness, our methods identify and accurately genotype more variants, and have high specificity for detecting de novo mutation events. The improvement in accuracy using our methods over the standard approach is particularly pronounced for low-frequency variants. Furthermore the family-aware calling framework dramatically reduces Mendelian inconsistencies and is beneficial for family-based analysis. We hope our framework and software will facilitate continuing efforts to identify genetic factors underlying human diseases.     

Molecular and Genetic Analyses of Drosophila Prat, Which Encodes the First Enzyme of De Novo Purine Biosynthesis

The Drosophila Prat gene encodes phosphoribosylamidotransferase (PRAT), the enzyme that performs the first committed step of the de novo purine nucleotide biosynthesis pathway. Using information from amino acid sequence alignments of PRAT from other organisms, a polymerase chain reaction-based approach was employed to clone Prat. Amino acid sequence alignment of Drosophila PRAT with PRAT from bacteria, yeast, and vertebrates indicates that it is most identical (at least 60%) to the vertebrate PRATs. It shares putative amino-terminal propeptide and ironbinding domains seen only in Bacillus subtilis and vertebrate PRATs. Prat was localized to the right arm of chromosome 3 at polytene band 84E1-2. Owing to the fact that this region had been well characterized previously, Prat was localized to a 30-kilobase region between two deficiency break-points. By making the prediction that Prat would have a similar ``purine syndrome' phenotype as mutations in the genes ade2 and ade3, which encode enzymes downstream in the pathway, five alleles of Prat were isolated. Three of the alleles were identified as missense mutations. A comparison of PRAT enzyme activity with phenotype in three of the mutants indicates that a reduction to 40% of the wild-type allele's activity is sufficient to cause the purine syndrome, suggesting that PRAT activity is limiting in Drosophila.     

A Monte Carlo EM Algorithm for De Novo Motif Discovery in Biomolecular Sequences

Motif discovery methods play pivotal roles in deciphering the genetic regulatory codes (i.e., motifs) in genomes as well as in locating conserved domains in protein sequences. The Expectation Maximization (EM) algorithm is one of the most popular methods used in de novo motif discovery. Based on the position weight matrix (PWM) updating technique, this paper presents a Monte Carlo version of the EM motif-finding algorithm that carries out stochastic sampling in local alignment space to overcome the conventional EM's main drawback of being trapped in a local optimum. The newly implemented algorithm is named as Monte Carlo EM Motif Discovery Algorithm (MCEMDA). MCEMDA starts from an initial model, and then it iteratively performs Monte Carlo simulation and parameter update until convergence. A log-likelihood profiling technique together with the top-k strategy is introduced to cope with the phase shifts and multiple modal issues in motif discovery problem. A novel grouping motif alignment (GMA) algorithm is designed to select motifs by clustering a population of candidate local alignments and successfully applied to subtle motif discovery. MCEMDA compares favorably to other popular PWM-based and word enumerative motif algorithms tested using simulated (l, d)-motif cases, documented prokaryotic, and eukaryotic DNA motif sequences. Finally, MCEMDA is applied to detect large blocks of conserved domains using protein benchmarks and exhibits its excellent capacity while compared with other multiple sequence alignment methods.