A novel knowledge-based approach to design inorganic-binding peptides

MOTIVATION: The discovery of solid-binding peptide sequences is accelerating along with their practical applications in biotechnology and materials sciences. A better understanding of the relationships between the peptide sequences and their binding affinities or specificities will enable further design of novel peptides with selected properties of interest both in engineering and medicine. RESULTS: A bioinformatics approach was developed to classify peptides selected by in vivo techniques according to their inorganic solid-binding properties. Our approach performs all-against-all comparisons of experimentally selected peptides with short amino acid sequences that were categorized for their binding affinity and scores the alignments using sequence similarity scoring matrices. We generated novel scoring matrices that optimize the similarities within the strong-binding peptide sequences and the differences between the strong- and weak-binding peptide sequences. Using the scoring matrices thus generated, a given peptide is classified based on the sequence similarity to a set of experimentally selected peptides. We demonstrate the new approach by classifying experimentally characterized quartz-binding peptides and computationally designing new sequences with specific affinities. Experimental verifications of binding of these computationally designed peptides confirm our predictions with high accuracy. We further show that our approach is a general one and can be used to design new sequences that bind to a given inorganic solid with predictable and enhanced affinity.     

Personal adaptive clusters as containers for scientific jobs

We describe a system for creating personal clusters in user-space to support the submission and management of thousands of compute-intensive serial jobs to the network-connected compute resources on the NSF TeraGrid. The system implements a robust infrastructure that submits and manages job proxies across a distributed computing environment. These job proxies contribute resources to personal clusters created dynamically for a user on-demand. The personal clusters then adapt to the prevailing job load conditions at the distributed sites by migrating job proxies to sites expected to provide resources more quickly. Furthermore, the system allows multiple instances of these personal clusters to be created as containers for individual scientific experiments, allowing the submission environment to be customized for each instance. The version of the system described in this paper allows users to build large personal Condor and Sun Grid Engine clusters on the TeraGrid. Users then manage their scientific jobs, within each personal cluster, with a single uniform interface using the feature-rich functionality found in these job management environments.

PRIMAL: Fast and Accurate Pedigree-based Imputation from Sequence Data in a Founder Population

Founder populations and large pedigrees offer many well-known advantages for genetic mapping studies, including cost-efficient study designs. Here, we describe PRIMAL (PedigRee IMputation ALgorithm), a fast and accurate pedigree-based phasing and imputation algorithm for founder populations. PRIMAL incorporates both existing and original ideas, such as a novel indexing strategy of Identity-By-Descent (IBD) segments based on clique graphs. We were able to impute the genomes of 1,317 South Dakota Hutterites, who had genome-wide genotypes for ~300,000 common single nucleotide variants (SNVs), from 98 whole genome sequences. Using a combination of pedigree-based and LD-based imputation, we were able to assign 87% of genotypes with >99% accuracy over the full range of allele frequencies. Using the IBD cliques we were also able to infer the parental origin of 83% of alleles, and genotypes of deceased recent ancestors for whom no genotype information was available. This imputed data set will enable us to better study the relative contribution of rare and common variants on human phenotypes, as well as parental origin effect of disease risk alleles in >1,000 individuals at minimal cost.     

All-trans retinoic acid modifies the expression of clock and disease marker genes

Restricted feeding (RF), a regimen that restricts the duration of food availability with no calorie restriction, entrains the circadian clock in peripheral tissues. Restricted feeding leads to high-amplitude circadian rhythms, which have been shown to promote wellness and reduce disease and inflammatory markers. Retinoids, such as all-trans retinoic acid (ATRA), act as anti-inflammatory agents. Thus far, the effect of ATRA combined with RF on the ability to delay the occurrence of age-associated changes, such as cancer and inflammation, is not known. We measured circadian expression of clock genes, disease marker genes and inflammatory markers in the serum, liver and jejunum in mice fed ad libitum (AL) or RF supplemented with 15 or 250 μg/kg body/day ATRA for 16 weeks. Our results show that ATRA supplementation led to phase shifts and reduced amplitudes in clock genes. Under AL, ATRA reduced the average daily messenger RNA (mRNA) levels of some disease markers, such as liver Afp and jejunum Afp, Alt and Gadd45β and aspartate transaminase (AST) protein in the serum, but increased the expression level of liver Crp mRNA. Under RF, ATRA reduced the average daily levels of jejunum Alt and Gadd45β and AST protein in the serum, but increased liver Afp, Alt, Gadd45β and Arginase mRNA. Altogether, our findings suggest that ATRA strongly affects circadian oscillation and disease marker levels. Moreover, its impact is different depending on the feeding regimen (AL or RF).     

Dynamics and persistence of Dead Sea microbial populations as shown by high-throughput sequencing of rRNA

16S rRNA amplicon libraries from a haloarchaeal bloom in the hypersaline Dead Sea in 1992 were analyzed together with the 2007 residual population and simulated blooms in experimental mesocosms. Significant population shifts were observed during the bloom, and surprisingly a signature from the bloom was retained 15 years later.     

Interleukin-10-induced neutrophil gelatinase-associated lipocalin production in macrophages with consequences for tumor growth

Tumor cell-derived factors, such as interleukin 10 (IL-10), polarize macrophages toward a regulatory M2 phenotype, characterized by the expression of anti-inflammatory cytokines and protumorigenic mediators. Here we explored molecular mechanisms allowing IL-10 to upregulate the protumorigenic protein NGAL in primary human macrophages. Reporter assays of full-length or deletion constructs of the NGAL promoter provided evidence that NGAL production is STAT3 dependent, activated downstream of the IL-10-Janus kinase (Jak) axis, as well as being C/EBPβ dependent. The involvement of STAT3 and C/EBPβ was shown by chromatin immunoprecipitation (ChIP) and ChIP-Western analysis, as well as decoy oligonucleotides scavenging both STAT3 and C/EBPβ in human macrophages. Furthermore, the production of NGAL in macrophages in response to IL-10 induces cellular growth and proliferation of MCF-7 breast cancer cells. We conclude that both STAT3 and C/EBPβ are needed to elicit IL-10-mediated NGAL expression in primary human macrophages. Macrophage-secreted NGAL shapes the protumorigenic macrophage phenotype to promote growth of MCF-7 breast cancer cells. Our data point to a macrophage-dependent IL-10-STAT3-NGAL axis that might contribute to tumor progression.     

Inositol phosphate-induced stabilization of inositol 1,3,4,5,6-pentakisphosphate 2-kinase and its role in substrate specificity

Inositol phosphate kinases (IPKs) sequentially phosphorylate inositol phosphates (IPs) on their inositol rings to yield an array of signaling molecules. IPKs must possess the ability to recognize their physiological substrates from among a pool of over 30 cellular IPs that differ in numbers and positions of phosphates. Crystal structures from IPK subfamilies have revealed structural determinants for IP discrimination, which vary considerably between IPKs. However, recent structures of inositol 1,3,4,5,6‐pentakisphosphate 2‐kinase (IPK1) did not reveal how IPK1 selectively recognizes its physiological substrate, IP5, while excluding others. Here, we report that limited proteolysis has revealed the presence of multiple conformational states in the IPK1 catalytic cycle, with notable protection from protease only in the presence of IP. Further, a 3.1‐Å crystal structure of IPK1 bound to ADP in the absence of IP revealed decreased order in residues 110–140 within the N‐lobe of the kinase compared with structures in which IP is bound. Using this solution and crystallographic data, we propose a model for recognition of IP substrate by IPK1 wherein phosphate groups at the 4‐, 5‐, and 6‐positions are recognized initially by the C‐lobe with subsequent interaction of the 1‐position phosphate by Arg130 that stabilizes this residue and the N‐lobe. This model explains how IPK1 can be highly specific for a single IP substrate by linking its interactions with substrate phosphate groups to the stabilization of the N‐ and C‐lobes and kinase activation.