The draft nuclear genome sequence of the snail-transmitted, dimorphic, parasitic, platyhelminth Schistosoma mansoni revealed eight genes encoding proteins that contain the Universal Stress Protein (USP) domain. Schistosoma mansoni is a causative agent of human schistosomiasis, a severe and debilitating Neglected Tropical Disease (NTD) of poverty, which is endemic in at least 76 countries. The availability of the genome sequences of Schistosoma species presents opportunities for bioinformatics and genomics analyses of associated gene families that could be targets for understanding schistosomiasis ecology, intervention, prevention and control. Proteins with the USP domain are known to provide bacteria, archaea, fungi, protists and plants with the ability to respond to diverse environmental stresses. In this research investigation, the functional annotations of the USP genes and predicted nucleotide and protein sequences were initially verified. Subsequently, sequence clusters and distinctive features of the sequences were determined. A total of twelve ligand binding sites were predicted based on alignment to the ATP-binding universal stress protein from Methanocaldococcus jannaschii. In addition, six USP sequences showed the presence of ATP-binding motif residues indicating that they may be regulated by ATP. Public domain gene expression data and RT-PCR assays confirmed that all the S. mansoni USP genes were transcribed in at least one of the developmental life cycle stages of the helminth. Six of these genes were up-regulated in the miracidium, a free-swimming stage that is critical for transmission to the snail intermediate host. It is possible that during the intra-snail stages, S. mansoni gene transcripts for universal stress proteins are low abundant and are induced to perform specialized functions triggered by environmental stressors such as oxidative stress due to hydrogen peroxide that is present in the snail hemocytes. This report serves to catalyze the formation of a network of researchers to understand the function and regulation of the universal stress proteins encoded in genomes of schistosomes and their snail intermediate hosts.

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.

Obesity is a major global public health problem requiring multifaceted interventional approaches including dietary interventions with probiotic bacteria. High-throughput genome sequencing of microbial communities in the mammalian gastrointestinal system continues to present diverse protein function information to understand the bacterial determinants that influence obesity development. The goal of the research reported in this article was to identify biological processes in probiotic bacteria that could influence the mechanisms for the extraction of energy from diet in the human gastrointestinal system. Our research strategy of combining bioinformatics and visual analytics methods was based on the identification of operon gene arrangements in genomes of Lactobacillus species and Akkermansia muciniphila that include at least a gene for a universal stress protein. The two major findings from this research study are related to Lactobacillus plantarum and Akkermansia muciniphila bacteria species which are associated with weight-loss. The first finding is that Lactobacillus plantarum strains have a two-gene operon that encodes a universal stress protein for stress response and the membrane translocator protein (TSPO), known to function in mitochondrial fatty acid oxidation in humans. The second finding is the presence of a three-gene operon in Akkermansia muciniphila that includes a gene whose human mitochondrial homolog is associated with waist-hip ratio and fat distribution. From a public health perspective, elucidation of the bacterial determinants influencing obesity will help in educating the public on optimal probiotic use for anti-obesity effects.

Exposure to inorganic arsenic induces skin cancer and abnormal pigmentation in susceptible humans. High-throughput gene transcription assays such as DNA microarrays allow for the identification of biological pathways affected by arsenic that lead to initiation and progression of skin cancer and abnormal pigmentation. The overall purpose of the reported research was to determine knowledge building insights on biomarker genes for arsenic toxicity to human epidermal cells by integrating a collection of gene lists annotated with biological information. The information sets included toxicogenomics gene-chemical interaction; enzymes encoded in the human genome; enriched biological information associated with genes; environmentally relevant gene sequence variation; and effects of non-synonymous single nucleotide polymorphisms (SNPs) on protein function. Molecular network construction for arsenic upregulated genes TNFSF18 (tumor necrosis factor [ligand] superfamily member 18) and IL1R2 (interleukin 1 Receptor, type 2) revealed subnetwork interconnections to E2F4, an oncogenic transcription factor, predominantly expressed at the onset of keratinocyte differentiation. Visual analytics integration of gene information sources helped identify RAC1, a GTP binding protein, and TFRC, an iron uptake protein as prioritized arsenic-perturbed protein targets for biological processes leading to skin hyperpigmentation. RAC1 regulates the formation of dendrites that transfer melanin from melanocytes to neighboring keratinocytes. Increased melanocyte dendricity is correlated with hyperpigmentation. TFRC is a key determinant of the amount and location of iron in the epidermis. Aberrant TFRC expression could impair cutaneous iron metabolism leading to abnormal pigmentation seen in some humans exposed to arsenicals. The reported findings contribute to insights on how arsenic could impair the function of genes and biological pathways in epidermal cells. Finally, we developed visual analytics resources to facilitate further exploration of the information and knowledge building insights on arsenic toxicity to human epidermal keratinocytes and melanocytes.

The aim of this article is to promote the use of knowledge visualization frameworks in the creation and transfer of complex public health knowledge. The accessibility to healthy food items is an example of complex public health knowledge. The United States Department of Agriculture Food Access Research Atlas (FARA) dataset contains 147 variables for 72,864 census tracts and includes 16 food accessibility variables with binary values (0 or 1). Using four-digit and 16-digit binary patterns, we have developed data analytical procedures to group the 72,684 U.S. census tracts into eight and forty groups respectively. This value-added FARA dataset facilitated the design and production of interactive knowledge visualizations that have a collective purpose of knowledge transfer and specific functions including new insights on food accessibility and obesity rates in the United States. The knowledge visualizations of the binary patterns could serve as an integrated explanation and prediction system to help answer why and what-if questions on food accessibility, nutritional inequality and nutrition therapy for diabetic care at varying geographic units. In conclusion, the approach of knowledge visualizations could inform coordinated multi-level decision making for improving food accessibility and reducing chronic diseases in locations defined by patterns of food access measures.