Identification of Drought-Responsive Universal Stress Proteins in Viridiplantae

Genes encoding proteins that contain the universal stress protein (USP) domain are known to provide bacteria, archaea, fungi, protozoa, and plants with the ability to respond to a plethora of environmental stresses. Specifically in plants, drought tolerance is a desirable phenotype. However, limited focused and organized functional genomic datasets exist on drought-responsive plant USP genes to facilitate their characterization. The overall objective of the investigation was to identify diverse plant universal stress proteins and Expressed Sequence Tags (ESTs) responsive to water-deficit stress. We hypothesize that cross-database mining of functional annotations in protein and gene transcript bioinformatics resources would help identify candidate drought-responsive universal stress proteins and transcripts from multiple plant species. Our bioinformatics approach retrieved, mined and integrated comprehensive functional annotation data on 511 protein and 1561 ESTs sequences from 161 viridiplantae taxa. A total of 32 drought-responsive ESTs from 7 plant genera Glycine, Hordeum, Manihot, Medicago, Oryza, Pinus and Triticum were identified. Two Arabidopsis USP genes At3g62550 and At3g53990 that encode ATP-binding motif were up-regulated in a drought microarray dataset. Further, a dataset of 80 simple sequence repeats (SSRs) linked to 20 singletons and 47 transcript assembles was constructed. Integrating the datasets on SSRs and drought-responsive ESTs identified three drought-responsive ESTs from bread wheat (BE604157), soybean (BM887317) and maritime pine (BX682209). The SSR sequence types were CAG, ATA and AT respectively. The datasets from cross-database mining provide organized resources for the characterization of USP genes as useful targets for engineering plant varieties tolerant to unfavorable environmental conditions

Aberrantly Expressed Genes in HaCaT Keratinocytes Chronically Exposed to Arsenic Trioxide

Inorganic arsenic is a known environmental toxicant and carcinogen of global public health concern. Arsenic is genotoxic and cytotoxic to human keratinocytes. However, the biological pathways perturbed in keratinocytes by low chronic dose inorganic arsenic are not completely understood. The objective of the investigation was to discover the mechanism of arsenic carcinogenicity in human epidermal keratinocytes. We hypothesize that a combined strategy of DNA microarray, qRT-PCR and gene function annotation will identify aberrantly expressed genes in HaCaT keratinocyte cell line after chronic treatment with arsenic trioxide. Microarray data analysis identified 14 up-regulated genes and 21 down-regulated genes in response to arsenic trioxide. The expression of 4 up-regulated genes and 1 down-regulated gene were confirmed by qRT-PCR. The up-regulated genes were AKR1C3 (Aldo-Keto Reductase family 1, member C3), IGFL1 (Insulin Growth Factor-Like family member 1), IL1R2 (Interleukin 1 Receptor, type 2), and TNFSF18 (Tumor Necrosis Factor [ligand] SuperFamily, member 18) and down-regulated gene was RGS2 (Regulator of G-protein Signaling 2). The observed over expression of TNFSF18 (167 fold) coupled with moderate expression of IGFL1 (3.1 fold), IL1R2 (5.9 fold) and AKR1C3 (9.2 fold) with a decreased RGS2 (2.0 fold) suggests that chronic arsenic exposure could produce sustained levels of TNF with modulation by an IL-1 analogue resulting in chronic immunologic insult. A concomitant decrease in growth inhibiting gene (RGS2) and increase in AKR1C3 may contribute to chronic inflammation leading to metaplasia, which may eventually lead to carcinogenicity in the skin keratinocytes. Also, increased expression of IGFL1 may trigger cancer development and progression in HaCaT keratinocytes

Functional Annotation Analytics of Rhodopseudomonas palustris Genomes

Rhodopseudomonas palustris, a nonsulphur purple photosynthetic bacteria, has been extensively investigated for its metabolic versatility including ability to produce hydrogen gas from sunlight and biomass. The availability of the finished genome sequences of six R. palustris strains (BisA53, BisB18, BisB5, CGA009, HaA2 and TIE-1) combined with online bioinformatics software for integrated analysis presents new opportunities to determine the genomic basis of metabolic versatility and ecological lifestyles of the bacteria species. The purpose of this investigation was to compare the functional annotations available for multiple R. palustris genomes to identify annotations that can be further investigated for strain-specific or uniquely shared phenotypic characteristics. A total of 2,355 protein family Pfam domain annotations were clustered based on presence or absence in the six genomes. The clustering process identified groups of functional annotations including those that could be verified as strain-specific or uniquely shared phenotypes. For example, genes encoding water/glycerol transport were present in the genome sequences of strains CGA009 and BisB5, but absent in strains BisA53, BisB18, HaA2 and TIE-1. Protein structural homology modeling predicted that the two orthologous 240 aa R. palustris aquaporins have water-specific transport function. Based on observations in other microbes, the presence of aquaporin in R. palustris strains may improve freeze tolerance in natural conditions of rapid freezing such as nitrogen fixation at low temperatures where access to liquid water is a limiting factor for nitrogenase activation. In the case of adaptive loss of aquaporin genes, strains may be better adapted to survive in conditions of high-sugar content such as fermentation of biomass for biohydrogen production. Finally, web-based resources were developed to allow for interactive, user-defined selection of the relationship between protein family annotations and the R. palustris genomes

The Case for Visual Analytics of Arsenic Concentrations in Foods

Arsenic is a naturally occurring toxic metal and its presence in food could be a potential risk to the health of both humans and animals. Prolonged ingestion of arsenic contaminated water may result in manifestations of toxicity in all systems of the body. Visual Analytics is a multidisciplinary field that is defined as the science of analytical reasoning facilitated by interactive visual interfaces. The concentrations of arsenic vary in foods making it impractical and impossible to provide regulatory limit for each food. This review article presents a case for the use of visual analytics approaches to provide comparative assessment of arsenic in various foods. The topics covered include (i) metabolism of arsenic in the human body; (ii) arsenic concentrations in various foods; (ii) factors affecting arsenic uptake in plants; (ii) introduction to visual analytics; and (iv) benefits of visual analytics for comparative assessment of arsenic concentration in foods. Visual analytics can provide an information superstructure of arsenic in various foods to permit insightful comparative risk assessment of the diverse and continually expanding data on arsenic in food groups in the context of country of study or origin, year of study, method of analysis and arsenic species

Candidate Single Nucleotide Polymorphism Markers for Arsenic Responsiveness of Protein Targets

Arsenic is a toxic metalloid that causes skin cancer and binds to cysteine residues—a property that could be used to infer arsenic responsiveness of a target protein. Non-synonymous Single Nucleotide Polymorphisms (nsSNPs) result in amino acid substitutions and may alter arsenic binding with cysteine residues. Thus, the objective of this investigation was to identify and analyze nsSNPs that lead to substitutions to or from cysteine residues as an indication of increased or decreased arsenic responsiveness. We hypothesize that integration of data on molecular impacts of nsSNPs and arsenic-gene relationships will identify nsSNPs that could serve as arsenic responsiveness markers. We have analyzed functional and structural impacts data for 5,811 nsSNPs linked to 1,224 arsenic-annotated genes. In addition to the identified candidate nsSNPs for increased or reduced arsenic responsiveness, we observed i) a nsSNP that results in the breakage of a disulfide bond, as candidate marker for reduced arsenic responsiveness of KLK7, a secreted serine protease participate in normal shedding of the skin; and ii) 6 pairs of vicinal cysteines in KLK7 protein that could be binding sites for arsenic. In summary, our analysis identified non-synonymous SNPs that could be used to evaluate responsiveness of a protein target to arsenic. In particular, an epidermal expressed serine protease with crucial function in normal skin physiology was prioritized on the basis of abundance of vicinal cysteines for further research on arsenic-induced keratinocyte carcinogenesis