Nikolaj Blom

Linear Motif Atlas for Phosphorylation-Dependent Signaling

Created with both in vitro and in vivo data, NetPhorest is an atlas of consensus sequence motifs for 179 kinases and 104 phosphorylation-dependent binding domains and reveals new insight into phosphorylation-dependent signaling. An Atlas of Phosphorylation NetPhorest is a community resource that uses phylogenetic trees to organize data from both in vivo and in vitro experiments to derive sequence specificities for 179 kinases and 104 domains (SH2, PTB, BRCT, WW, and 14–3–3) that bind to phosphorylated sites. The resulting atlas of linear motifs revealed that oncogenic kinases tend to be less specific in the target sequences they phosphorylate than their non-oncogenic counterparts, that autophosphorylation sites tend to be more variable than other substrates of a given kinase, and that coupling interaction domains with kinase domains may allow phosphorylation site specificity to be low while still maintaining substrate specificity. Systematic and quantitative analysis of protein phosphorylation is revealing dynamic regulatory networks underlying cellular responses to environmental cues. However, matching these sites to the kinases that phosphorylate them and the phosphorylation-dependent binding domains that may subsequently bind to them remains a challenge. NetPhorest is an atlas of consensus sequence motifs that covers 179 kinases and 104 phosphorylation-dependent binding domains [Src homology 2 (SH2), phosphotyrosine binding (PTB), BRCA1 C-terminal (BRCT), WW, and 14–3–3]. The atlas reveals new aspects of signaling systems, including the observation that tyrosine kinases mutated in cancer have lower specificity than their non-oncogenic relatives. The resource is maintained by an automated pipeline, which uses phylogenetic trees to structure the currently available in vivo and in vitro data to derive probabilistic sequence models of linear motifs. The atlas is available as a community resource (http://netphorest.info).

Identification and assembly of genomes and genetic elements in complex metagenomic samples without using reference genomes.

Most current approaches for analyzing metagenomic data rely on comparisons to reference genomes, but the microbial diversity of many environments extends far beyond what is covered by reference databases. De novo segregation of complex metagenomic data into specific biological entities, such as particular bacterial strains or viruses, remains a largely unsolved problem. Here we present a method, based on binning co-abundant genes across a series of metagenomic samples, that enables comprehensive discovery of new microbial organisms, viruses and co-inherited genetic entities and aids assembly of microbial genomes without the need for reference sequences. We demonstrate the method on data from 396 human gut microbiome samples and identify 7,381 co-abundance gene groups (CAGs), including 741 metagenomic species (MGS). We use these to assemble 238 high-quality microbial genomes and identify affiliations between MGS and hundreds of viruses or genetic entities. Our method provides the means for comprehensive profiling of the diversity within complex metagenomic samples.

Phospho.ELM: a database of experimentally verified phosphorylation sites in eukaryotic proteins.

BackgroundPost-translational phosphorylation is one of the most common protein modifications. Phosphoserine, threonine and tyrosine residues play critical roles in the regulation of many cellular processes. The fast growing number of research reports on protein phosphorylation points to a general need for an accurate database dedicated to phosphorylation to provide easily retrievable information on phosphoproteins.DescriptionPhospho.ELM http://phospho.elm.eu.org is a new resource containing experimentally verified phosphorylation sites manually curated from the literature and is developed as part of the ELM (Eukaryotic Linear Motif) resource. Phospho.ELM constitutes the largest searchable collection of phosphorylation sites available to the research community. The Phospho.ELM entries store information about substrate proteins with the exact positions of residues known to be phosphorylated by cellular kinases. Additional annotation includes literature references, subcellular compartment, tissue distribution, and information about the signaling pathways involved as well as links to the molecular interaction database MINT. Phospho.ELM version 2.0 contains 1703 phosphorylation site instances for 556 phosphorylated proteins.ConclusionPhospho.ELM will be a valuable tool both for molecular biologists working on protein phosphorylation sites and for bioinformaticians developing computational predictions on the specificity of phosphorylation reactions.

PhosphoBase, a database of phosphorylation sites: release 2.0

PhosphoBase contains information about phosphorylated residues in proteins and data about peptide phosphorylation by a variety of protein kinases. The data are collected from literature and compiled into a common format. The current release of PhosphoBase (October 1998, version 2.0) comprises 414 phosphoprotein entries covering 1052 phosphorylatable serine, threonine and tyrosine residues. The kinetic data from peptide phosphorylation assays for approximately 330 oligopeptides is also included. The database entries are cross-referenced to the corresponding records in the Swiss-Prot protein database and literature references are linked to MedLine records. PhosphoBase is available via the WWW at http://www.cbs.dtu. dk/databases/PhosphoBase/

Prediction of human protein function from post-translational modifications and localization features

We have developed an entirely sequence-based method that identifies and integrates relevant features that can be used to assign proteins of unknown function to functional classes, and enzyme categories for enzymes. We show that strategies for the elucidation of protein function may benefit from a number of functional attributes that are more directly related to the linear sequence of amino acids, and hence easier to predict, than protein structure. These attributes include features associated with post-translational modifications and protein sorting, but also much simpler aspects such as the length, isoelectric point and composition of the polypeptide chain.

In vivo protection of nigral dopamine neurons by lentiviral gene transfer of the novel GDNF-family member neublastin/artemin.

The glial cell line-derived neurotrophic factor (GDNF)-family of neurotrophic factors consisted until recently of three members, GDNF, neurturin, and persephin. We describe here the cloning of a new GDNF-family member, neublastin (NBN), identical to artemin (ART), recently published (Baloh et al., 1998). Addition of NBN/ART to cultures of fetal mesencephalic dopamine (DA) neurons increased the number of surviving tyrosine hydroxylase (TH)-immunoreactive neurons by approximately 70%, similar to the maximal effect obtained with GDNF. To investigate the neuroprotective effects in vivo, lentiviral vectors carrying the cDNA for NBN/ART or GDNF were injected into the striatum and ventral midbrain. Three weeks after an intrastriatal 6-hydroxydopamine lesion only about 20% of the nigral DA neurons were left in the control group, while 80-90% of the DA neurons remained in the NBN/ART and GDNF treatment groups, and the striatal TH-immunoreactive innervation was partly spared. We conclude that NBN/ART, similarly to GDNF, is a potent neuroprotective factor for the nigrostriatal DA neurons in vivo.

Statistical analysis of protein kinase specificity determinants

The site and sequence specificity of protein kinases, as well as the role of the secondary structure and surface accessibility of the phosphorylation sites on substrate proteins, was statistically analyzed. The experimental data were collected from the literature and are available on the World Wide Web at http://www.cbs.dtu.dk/databases/PhosphoBase/. The set of data involved 1008 phosphorylatable sites in 406 proteins, which were phosphorylated by 58 protein kinases. It was found that there exists almost absolute Ser/Thr or Tyr specificity, with rare exceptions. The sequence specificity determinants were less strict and were located between positions −4 and +4 relative to the phosphorylation site. Secondary structure and surface accessibility predictions revealed that most of the phosphorylation sites were located on the surface of the target proteins.

Microbial community structure of Arctic multiyear sea ice and surface seawater by 454 sequencing of the 16S RNA gene.

Dramatic decreases in the extent of Arctic multiyear ice (MYI) suggest this environment may disappear as early as 2100, replaced by ecologically different first-year ice. To better understand the implications of this loss on microbial biodiversity, we undertook a detailed census of the microbial community in MYI at two sites near the geographic North Pole using parallel tag sequencing of the 16S rRNA gene. Although the composition of the MYI microbial community has been characterized by previous studies, microbial community structure has not been. Although richness was lower in MYI than in underlying surface water, we found diversity to be comparable using the Simpson and Shannons indices (for Simpson t=0.65, P=0.56; for Shannon t=0.25, P=0.84 for a Students t-test of mean values). Cyanobacteria, comprising 6.8% of reads obtained from MYI, were observed for the first time in Arctic sea ice. In addition, several low-abundance clades not previously reported in sea ice were present, including the phylum TM7 and the classes Spartobacteria and Opitutae. Members of Coraliomargarita, a recently described genus of the class Opitutae, were present in sufficient numbers to suggest niche occupation within MYI.

NetAcet: prediction of N-terminal acetylation sites

We present here a neural network based method for prediction of N-terminal acetylation-by far the most abundant post-translational modification in eukaryotes. The method was developed on a yeast dataset for N-acetyltransferase A (NatA) acetylation, which is the type of N-acetylation for which most examples are known and for which orthologs have been found in several eukaryotes. We obtain correlation coefficients close to 0.7 on yeast data and a sensitivity up to 74% on mammalian data, suggesting that the method is valid for eukaryotic NatA orthologs.

NetPhosYeast: prediction of protein phosphorylation sites in yeast.

UNLABELLED We here present a neural network-based method for the prediction of protein phosphorylation sites in yeast--an important model organism for basic research. Existing protein phosphorylation site predictors are primarily based on mammalian data and show reduced sensitivity on yeast phosphorylation sites compared to those in humans, suggesting the need for an yeast-specific phosphorylation site predictor. NetPhosYeast achieves a correlation coefficient close to 0.75 with a sensitivity of 0.84 and specificity of 0.90 and outperforms existing predictors in the identification of phosphorylation sites in yeast. AVAILABILITY The NetPhosYeast prediction service is available as a public web server at http://www.cbs.dtu.dk/services/NetPhosYeast/.