TOPOFIT-DB, a database of protein structural alignments based on the TOPOFIT method

TOPOFIT-DB (T-DB) is a public web-based database of protein structural alignments based on the TOPOFIT method, providing a comprehensive resource for comparative analysis of protein structure families. The TOPOFIT method is based on the discovery of a saturation point on the alignment curve (topomax point) which presents an ability to objectively identify a border between common and variable parts in a protein structural family, providing additional insight into protein comparison and functional annotation. TOPOFIT also effectively detects non-sequential relations between protein structures. T-DB provides users with the convenient ability to retrieve and analyze structural neighbors for a protein; do one-to-all calculation of a user provided structure against the entire current PDB release with T-Server, and pair-wise comparison using the TOPOFIT method through the T-Pair web page. All outputs are reported in various web-based tables and graphics, with automated viewing of the structure-sequence alignments in the Friend software package for complete, detailed analysis. T-DB presents researchers with the opportunity for comprehensive studies of the variability in proteins and is publicly available at

Structure SNP (StSNP): a web server for mapping and modeling nsSNPs on protein structures with linkage to metabolic pathways

SNPs located within the open reading frame of a gene that result in an alteration in the amino acid sequence of the encoded protein [nonsynonymous SNPs (nsSNPs)] might directly or indirectly affect functionality of the protein, alone or in the interactions in a multi-protein complex, by increasing/decreasing the activity of the metabolic pathway. Understanding the functional consequences of such changes and drawing conclusions about the molecular basis of diseases, involves integrating information from multiple heterogeneous sources including sequence, structure data and pathway relations between proteins. The data from NCBI's SNP database (dbSNP), gene and protein databases from Entrez, protein structures from the PDB and pathway information from KEGG have all been cross referenced into the StSNP web server, in an effort to provide combined integrated, reports about nsSNPs. StSNP provides ‘on the fly’ comparative modeling of nsSNPs with links to metabolic pathway information, along with real-time visual comparative analysis of the modeled structures using the Friend software application. The use of metabolic pathways in StSNP allows a researcher to examine possible disease-related pathways associated with a particular nsSNP(s), and link the diseases with the current available molecular structure data. The server is publicly available at http://glinka.bio.neu.edu/StSNP/

Protistan community patterns within the brine and halocline of deep hypersaline anoxic basins in the eastern Mediterranean Sea

Author Posting. © The Author(s), 2008. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Extremophiles 13 (2009): 151-167, doi:10.1007/s00792-008-0206-2.Environmental factors restrict the distribution of microbial eukaryotes but the exact boundaries for eukaryotic life are not known. Here we examine protistan communities at the extremes of salinity and osmotic pressure, and report rich assemblages inhabiting Bannock and Discovery, two deep-sea superhaline anoxic basins in the Mediterranean. Using a rRNA-based approach, we detected 1538 protistan rRNA gene sequences from water samples with total salinity ranging from 39 g/kg to 280 g/Kg, and obtained evidence that this DNA was endogenous to the extreme habitats sampled. Statistical analyses indicate that the discovered phylotypes represent only a fraction of species actually inhabiting both the brine and the brine-seawater interface, with as much as 82% of the actual richness missed by our survey. Jaccard indices (e.g., for a comparison of community membership) suggest that the brine/interface protistan communities are unique to Bannock and Discovery basins, and share little (0.8-2.8%) in species composition with overlying waters with typical marine salinity and oxygen tension. The protistan communities from the basins’ brine and brine/seawater interface appear to be particularly enriched with dinoflagellates, ciliates and other alveolates, as well as fungi, and are conspicuously poor in stramenopiles. The uniqueness and diversity of brine and brine-interface protistan communities make them promising targets for protistan discovery.This study was supported by grant grant STO414/2-4 of the Deutsche Forschungsgemeinschaft, the EuroDEEP program of the European Science Foundation under 06-EuroDEEP-FP-004 MIDDLE project and NSF-grant MCB- 034834

Protistan Diversity in the Arctic: A Case of Paleoclimate Shaping Modern Biodiversity?

The impact of climate on biodiversity is indisputable. Climate changes over geological time must have significantly influenced the evolution of biodiversity, ultimately leading to its present pattern. Here we consider the paleoclimate data record, inferring that present-day hot and cold environments should contain, respectively, the largest and the smallest diversity of ancestral lineages of microbial eukaryotes.We investigate this hypothesis by analyzing an original dataset of 18S rRNA gene sequences from Western Greenland in the Arctic, and data from the existing literature on 18S rRNA gene diversity in hydrothermal vent, temperate sediments, and anoxic water column communities. Unexpectedly, the community from the cold environment emerged as one of the richest observed to date in protistan species, and most diverse in ancestral lineages.This pattern is consistent with natural selection sweeps on aerobic non-psychrophilic microbial eukaryotes repeatedly caused by low temperatures and global anoxia of snowball Earth conditions. It implies that cold refuges persisted through the periods of greenhouse conditions, which agrees with some, although not all, current views on the extent of the past global cooling and warming events. We therefore identify cold environments as promising targets for microbial discovery

Structure SNP (StSNP): a web server for mapping and

modeling nsSNPs on protein structures with linkage to metabolic pathway