Assessment of Heavy Metal Pollution in Water and Sediments from the Ghalechay River,Baychebagh Copper Mine Area,Iran

The concentrations of selected heavy metals in sediments and waters in Baychebagh copper mine were determined using ICP-OES. Except for Co, the average concentrations of Cd, Cu, Pb, and Zn in sediments from the Ghalechay River in the district exceed the world-average shale and continental upper crust value. Enrichment factors for Pb, Cu, and Cd were significantly enriched in sediments, indicating environmental contamination. Geoaccumulation index calculated for different sampling stations indicates that the sediments are unpolluted with respect to Co and Zn while unpolluted to moderately polluted with Cu and highly polluted with Pb and Cd. The Sediment Quality Guidelines (SQGs) suggest that Cd and Pb may pose the highest risk for the environment. Sequential extraction analyses of sediments revealed that Cu, Co, Pb, and Zn bound to extractable, carbonate, reducible and oxidizable fractions are lower than residual fraction. About 10% of the total Pb was associated with the exchangeable fraction, indicating remobilization, while Cd (89%), Pb (73%) Co (58%), Cu (76%), and Zn (68%) closely associated with the residual and oxidizable fractions, resulting in their environmental immobility. The residual forms are not expected to be released under normal conditions in the river and could be considered an inert phase.     

Proinflammatory cytokine gene polymorphisms in Behçet's disease

Beh?et's disease (BD) is a chronic, systemic disease, characterized by oral and genital lesions, and ocular inflammation. There is evidence indicating altered levels of proinflammatory cytokines, such as interleukin (IL)-6 and tumor necrosis factor alpha (TNF-α) in patients with BD. This study involved 150 patients with BD and 140 healthy controls, and investigated the role of proinflammatory cytokine gene polymorphisms in the disease. The frequency of the TNF-α (-238) G/G genotype was significantly higher in the patient group, compared to the controls (p < 0.001), whilst the G/A genotype was significantly lower in the patients with BD (p < 0.001). Patients with BD showed a significant increase in the TNF-α (- 308, - 238) GG haplotype (p < 0.001), whilst there was a significant decrease in the GA haplotype (p < 0.001). The heterozygous, IL-6 (- 174) C/G genotype (p = 0.005), and the IL-6 (- 174, nt565) haplotype CG (p < 0.001), were significantly decreased in the patient group. The increased production of proinflammatory cytokines in BD could be a consequence of specific, cytokine gene polymorphisms. Particular genotypes and haplotypes in TNF-α were over-represented in BD, which may, in turn, predispose individuals to this disease.     

Relationship between insertion/deletion (indel) frequency of proteins and essentiality

Background  

In a previous study, we demonstrated that some essential proteins from pathogenic organisms contained sizable insertions/deletions (indels) when aligned to human proteins of high sequence similarity. Such indels may provide sufficient spatial differences between the pathogenic protein and human proteins to allow for selective targeting. In one example, an indel difference was targeted via large scale in-silico screening. This resulted in selective antibodies and small compounds which were capable of binding to the deletion-bearing essential pathogen protein without any cross-reactivity to the highly similar human protein. The objective of the current study was to investigate whether indels were found more frequently in essential than non-essential proteins.     

Biomolecular network motif counting and discovery by color coding

Protein-protein interaction (PPI) networks of many organisms share global topological features such as degree distribution, k-hop reachability, betweenness and closeness. Yet, some of these networks can differ significantly from the others in terms of local structures: e.g. the number of specific network motifs can vary significantly among PPI networks. Counting the number of network motifs provides a major challenge to compare biomolecular networks. Recently developed algorithms have been able to count the number of induced occurrences of subgraphs with k < or = 7 vertices. Yet no practical algorithm exists for counting non-induced occurrences, or counting subgraphs with k > or = 8 vertices. Counting non-induced occurrences of network motifs is not only challenging but also quite desirable as available PPI networks include several false interactions and miss many others. In this article, we show how to apply the 'color coding' technique for counting non-induced occurrences of subgraph topologies in the form of trees and bounded treewidth subgraphs. Our algorithm can count all occurrences of motif G' with k vertices in a network G with n vertices in time polynomial with n, provided k = O(log n). We use our algorithm to obtain 'treelet' distributions for k < or = 10 of available PPI networks of unicellular organisms (Saccharomyces cerevisiae Escherichia coli and Helicobacter Pyloris), which are all quite similar, and a multicellular organism (Caenorhabditis elegans) which is significantly different. Furthermore, the treelet distribution of the unicellular organisms are similar to that obtained by the 'duplication model' but are quite different from that of the 'preferential attachment model'. The treelet distribution is robust w.r.t. sparsification with bait/edge coverage of 70% but differences can be observed when bait/edge coverage drops to 50%.     

Optimal pooling for genome re-sequencing with ultra-high-throughput short-read technologies

New generation sequencing technologies offer unique opportunities and challenges for re-sequencing studies. In this article, we focus on re-sequencing experiments using the Solexa technology, based on bacterial artificial chromosome (BAC) clones, and address an experimental design problem. In these specific experiments, approximate coordinates of the BACs on a reference genome are known, and fine-scale differences between the BAC sequences and the reference are of interest. The high-throughput characteristics of the sequencing technology makes it possible to multiplex BAC sequencing experiments by pooling BACs for a cost-effective operation. However, the way BACs are pooled in such re-sequencing experiments has an effect on the downstream analysis of the generated data, mostly due to subsequences common to multiple BACs. The experimental design strategy we develop in this article offers combinatorial solutions based on approximation algorithms for the well-known max n-cut problem and the related max n-section problem on hypergraphs. Our algorithms, when applied to a number of sample cases give more than a 2-fold performance improvement over random partitioning.