Dynamics of receptor-mediated nanoparticle internalization into endothelial cells.

International audienceNanoparticles offer a promising medical tool for targeted drug delivery, for example to treat inflamed endothelial cells during the development of atherosclerosis. To inform the design of such therapeutic strategies, we develop a computational model of nanoparticle internalization into endothelial cells, where internalization is driven by receptor-ligand binding and limited by the deformation of the cell membrane and cytoplasm. We specifically consider the case of nanoparticles targeted against ICAM-1 receptors, of relevance for treating atherosclerosis. The model computes the kinetics of the internalization process, the dynamics of binding, and the distribution of stresses exerted between the nanoparticle and the cell membrane. The model predicts the existence of an optimal nanoparticle size for fastest internalization, consistent with experimental observations, as well as the role of bond characteristics, local cell mechanical properties, and external forces in the nanoparticle internalization process

P2RP:a Web-based framework for the identification and analysis of regulatory proteins in prokaryotic genomes

BACKGROUND: Regulatory proteins (RPs) such as transcription factors (TFs) and two-component system (TCS) proteins control how prokaryotic cells respond to changes in their external and/or internal state. Identification and annotation of TFs and TCSs is non-trivial, and between-genome comparisons are often confounded by different standards in annotation. There is a need for user-friendly, fast and convenient tools to allow researchers to overcome the inherent variability in annotation between genome sequences. RESULTS: We have developed the web-server P2RP (Predicted Prokaryotic Regulatory Proteins), which enables users to identify and annotate TFs and TCS proteins within their sequences of interest. Users can input amino acid or genomic DNA sequences, and predicted proteins therein are scanned for the possession of DNA-binding domains and/or TCS domains. RPs identified in this manner are categorised into families, unambiguously annotated, and a detailed description of their features generated, using an integrated software pipeline. P2RP results can then be outputted in user-specified formats. CONCLUSION: Biologists have an increasing need for fast and intuitively usable tools, which is why P2RP has been developed as an interactive system. As well as assisting experimental biologists to interrogate novel sequence data, it is hoped that P2RP will be built into genome annotation pipelines and re-annotation processes, to increase the consistency of RP annotation in public genomic sequences. P2RP is the first publicly available tool for predicting and analysing RP proteins in users’ sequences. The server is freely available and can be accessed along with documentation at http://www.p2rp.org

P2CS: a database of prokaryotic two-component systems

P2CS (http://www.p2cs.org) is a specialized database for prokaryotic two-component systems (TCSs), virtually ubiquitous signalling proteins which regulate a wide range of physiological processes. The primary aim of the database is to annotate and classify TCS proteins from completely sequenced prokaryotic genomes and metagenomes. Information within P2CS can be accessed through a variety of routes—TCS complements can be browsed by metagenome, replicon or sequence cluster (and these genesets are available for download by users). Alternatively a variety of database-wide or taxon-specific searches are supported. Each TCS protein is fully annotated with sequence-feature information including replicon context, while properties of the predicted proteins can be queried against several external prediction servers to suggest homologues, interaction networks, sub-cellular localization and domain complements. Another unique feature of P2CS is the analysis of ORFeomes to identify TCS genes missed during genome annotation. Recent innovations for P2CS include a CGView representation of the distribution of TCS genes around a replicon, categorization of TCS genes based on gene organization, an expanded domain-based classification scheme, a P2CS ‘gene cart’ and categorization on the basis of sequence clusters

P2TF: a comprehensive resource for analysis of prokaryotic transcription factors

BACKGROUND: Transcription factors (TFs) are DNA-binding proteins that regulate gene expression by activating or repressing transcription. Some have housekeeping roles, while others regulate the expression of specific genes in response to environmental change. The majority of TFs are multi-domain proteins, and they can be divided into families according to their domain organisation. There is a need for user-friendly, rigorous and consistent databases to allow researchers to overcome the inherent variability in annotation between genome sequences. DESCRIPTION: P2TF (Predicted Prokaryotic Transcription Factors) is an integrated and comprehensive database relating to transcription factor proteins. The current version of the database contains 372,877 TFs from 1,987 completely sequenced prokaryotic genomes and 43 metagenomes. The database provides annotation, classification and visualisation of TF genes and their genetic context, providing researchers with a one-stop shop in which to investigate TFs. The P2TF database analyses TFs in both predicted proteomes and reconstituted ORFeomes, recovering approximately 3% more TF proteins than just screening predicted proteomes. Users are able to search the database with sequence or domain architecture queries, and resulting hits can be aligned to investigate evolutionary relationships and conservation of residues. To increase utility, all searches can be filtered by taxonomy, TF genes can be added to the P2TF cart, and gene lists can be exported for external analysis in a variety of formats. CONCLUSIONS: P2TF is an open resource for biologists, allowing exploration of all TFs within prokaryotic genomes and metagenomes. The database enables a variety of analyses, and results are presented for user exploration as an interactive web interface, which provides different ways to access and download the data. The database is freely available at http://www.p2tf.org/

Predictors of locating children participants in epidemiological studies 20 years after last contact: Internet resources and longitudinal research

This study examines predictors of locating participants that were last contacted 20 years ago using public web-search directories, in order to facilitate longitudinal environmental health research. Participants (n = 3,202) resided in four distinct geographical neighborhoods in Hamilton, Ontario during childhood; they were between 15 and 17 years old when they were last contacted in 1986. Data used for tracing included available addresses, telephone numbers, given names, and parental names. Reverse and forward search strategies were used to retrieve updated contact details. 43% of the sample was traced using online directories. Following ethical approval, participants were contacted using traced data and 29% of the original cohort was located. Predictors of locating participants were: availability of paternal names, being traced to original addresses or telephone numbers, gender (male), relatively higher socioeconomic status in childhood, and not being exposed to smoking in childhood. Where participants resided in childhood was not a significant predictor of locating participants. Although 13% of the sample was traced using forward search by name, only 4% were located. For participants traced to available addresses or telephone numbers, the difference between the proportions of traced and located participants was \u3c3%. Prospective studies on children may benefit from including the listed names that pertain to each child\u27s telephone number and full parental names at recruitment, thereby increasing the likelihood of locating participants using Internet resources. Integrating the use of Internet-based public directories for cohort reconstruction can reduce financial costs related to follow-up for longitudinal research. © 2009 Springer Science+Business Media B.V

P2CS:Updates of the prokaryotic two-component systems database

International audienceThe P2CS database (http://www.p2cs.org/) is a comprehensive resource for the analysis of Prokaryotic Two-Component Systems (TCSs). TCSs are comprised of a receptor histidine kinase (HK) and a partner response regulator (RR) and control important prokaryotic behaviors. The latest incarnation of P2CS includes 164 651 TCS proteins, from 2758 sequenced prokaryotic genomes. Several important new features have been added to P2CS since it was last described. Users can search P2CS via BLAST, adding hits to their cart, and ho-mologous proteins can be aligned using MUSCLE and viewed using Jalview within P2CS. P2CS also provides phylogenetic trees based on the conserved signaling domains of the RRs and HKs from entire genomes. HK and RR trees are annotated with gene organization and domain architecture, providing insights into the evolutionary origin of the contemporary gene set. The majority of TCSs are encoded by adjacent HK and RR genes, however, 'orphan' unpaired TCS genes are also abundant and identifying their partner proteins is challenging. P2CS now provides paired HK and RR trees with proteins from the same genetic locus indicated. This allows the appraisal of evolutionary relationships across entire TCSs and in some cases the identification of candidate partners for orphan TCS proteins

Infectious Mimicry Complicates Diagnosis in Hemophagocytic Syndrome Caused by Anaplastic Large-Cell Lymphoma

Hemophagocytic syndrome (HPS) arises secondary to genetic, rheumatologic, neoplastic, and infectious causes. We discuss a patient whose presentation was consistent with systemic infection but was discovered to have HPS of unknown etiology. The presenting symptoms, as well as unremarkable malignancy and rheumatologic workups, led to the pursuit of an infectious cause, but the patient was ultimately discovered to have an occult anaplastic large-cell lymphoma (ALCL). This case demonstrates the diagnostic challenges that result from infectious mimicry in the context of HPS—first, in distinguishing noninfectious HPS from the systemic inflammation that can result from a widespread infectious process, second, in the identification of the precipitating cause of HPS. While evidence of these challenges has been suggested by the limited literature on HPS and ALCL, our case illustrates the diagnostic dilemma that arises when tissue biopsy does not quickly reveal an etiology. It is important that all physicians be aware that HPS can mimic infection and be prepared to redirect the workup when an infectious etiology for HPS cannot be identified

P2CS: a two-component system resource for prokaryotic signal transduction research

BACKGROUND: With the escalation of high throughput prokaryotic genome sequencing, there is an ever-increasing need for databases that characterise, catalogue and present data relating to particular gene sets and genomes/metagenomes. Two-component system (TCS) signal transduction pathways are the dominant mechanisms by which micro-organisms sense and respond to external as well as internal environmental changes. These systems respond to a wide range of stimuli by triggering diverse physiological adjustments, including alterations in gene expression, enzymatic reactions, or protein-protein interactions. DESCRIPTION: We present P2CS (Prokaryotic 2-Component Systems), an integrated and comprehensive database of TCS signal transduction proteins, which contains a compilation of the TCS genes within 755 completely sequenced prokaryotic genomes and 39 metagenomes. P2CS provides detailed annotation of each TCS gene including family classification, sequence features, functional domains, as well as genomic context visualization. To bypass the generic problem of gene underestimation during genome annotation, we also constituted and searched an ORFeome, which improves the recovery of TCS proteins compared to searches on the equivalent proteomes. CONCLUSION: P2CS has been developed for computational analysis of the modular TCSs of prokaryotic genomes and metagenomes. It provides a complete overview of information on TCSs, including predicted candidate proteins and probable proteins, which need further curation/validation. The database can be browsed and queried with a user-friendly web interface at

Evolutionary history expands the range of signaling interactions in hybrid multikinase networks

Two-component systems (TCSs) are ubiquitous signaling pathways, typically comprising a sensory histidine kinase (HK) and a response regulator, which communicate via intermolecular kinase-to-receiver domain phosphotransfer. Hybrid HKs constitute non-canonical TCS signaling pathways, with transmitter and receiver domains within a single protein communicating via intramolecular phosphotransfer. Here, we report how evolutionary relationships between hybrid HKs can be used as predictors of potential intermolecular and intramolecular interactions (‘phylogenetic promiscuity’). We used domain-swap genes chimeras to investigate the specificity of phosphotransfer within hybrid HKs of the GacS–GacA multikinase network of Pseudomonas brassicacearum. The receiver domain of GacS was replaced with those from nine donor hybrid HKs. Three chimeras with receivers from other hybrid HKs demonstrated correct functioning through complementation of a gacS mutant, which was dependent on strains having a functional gacA. Formation of functional chimeras was predictable on the basis of evolutionary heritage, and raises the possibility that HKs sharing a common ancestor with GacS might remain components of the contemporary GacS network. The results also demonstrate that understanding the evolutionary heritage of signaling domains in sophisticated networks allows their rational rewiring by simple domain transplantation, with implications for the creation of designer networks and inference of functional interactions