Ecological Trait-Based Digital Categorization of Microbial Genomes for Denitrification Potential.

Microorganisms encode proteins that function in the transformations of useful and harmful nitrogenous compounds in the global nitrogen cycle. The major transformations in the nitrogen cycle are nitrogen fixation, nitrification, denitrification, anaerobic ammonium oxidation, and ammonification. The focus of this report is the complex biogeochemical process of denitrification, which, in the complete form, consists of a series of four enzyme-catalyzed reduction reactions that transforms nitrate to nitrogen gas. Denitrification is a microbial strain-level ecological trait (characteristic), and denitrification potential (functional performance) can be inferred from trait rules that rely on the presence or absence of genes for denitrifying enzymes in microbial genomes. Despite the global significance of denitrification and associated large-scale genomic and scholarly data sources, there is lack of datasets and interactive computational tools for investigating microbial genomes according to denitrification trait rules. Therefore, our goal is to categorize archaeal and bacterial genomes by denitrification potential based on denitrification traits defined by rules of enzyme involvement in the denitrification reduction steps. We report the integration of datasets on genome, taxonomic lineage, ecosystem, and denitrifying enzymes to provide data investigations context for the denitrification potential of microbial strains. We constructed an ecosystem and taxonomic annotated denitrification potential dataset of 62,624 microbial genomes (866 archaea and 61,758 bacteria) that encode at least one of the twelve denitrifying enzymes in the four-step canonical denitrification pathway. Our four-digit binary-coding scheme categorized the microbial genomes to one of sixteen denitrification traits including complete denitrification traits assigned to 3280 genomes from 260 bacteria genera. The bacterial strains with complete denitrification potential pattern included Arcobacteraceae strains isolated or detected in diverse ecosystems including aquatic, human, plant, and Mollusca (shellfish). The dataset on microbial denitrification potential and associated interactive data investigations tools can serve as research resources for understanding the biochemical, molecular, and physiological aspects of microbial denitrification, among others. The microbial denitrification data resources produced in our research can also be useful for identifying microbial strains for synthetic denitrifying communities.

Bioinformatics Investigations of Universal Stress Proteins from Mercury-Methylating Desulfovibrionaceae.

The presence of methylmercury in aquatic environments and marine food sources is of global concern. The chemical reaction for the addition of a methyl group to inorganic mercury occurs in diverse bacterial taxonomic groups including the Gram-negative, sulfate-reducing Desulfovibrionaceae family that inhabit extreme aquatic environments. The availability of whole-genome sequence datasets for members of the Desulfovibrionaceae presents opportunities to understand the microbial mechanisms that contribute to methylmercury production in extreme aquatic environments. We have applied bioinformatics resources and developed visual analytics resources to categorize a collection of 719 putative universal stress protein (USP) sequences predicted from 93 genomes of Desulfovibrionaceae. We have focused our bioinformatics investigations on protein sequence analytics by developing interactive visualizations to categorize Desulfovibrionaceae universal stress proteins by protein domain composition and functionally important amino acids. We identified 651 Desulfovibrionaceae universal stress protein sequences, of which 488 sequences had only one USP domain and 163 had two USP domains. The 488 single USP domain sequences were further categorized into 340 sequences with ATP-binding motif and 148 sequences without ATP-binding motif. The 163 double USP domain sequences were categorized into (1) both USP domains with ATP-binding motif (3 sequences); (2) both USP domains without ATP-binding motif (138 sequences); and (3) one USP domain with ATP-binding motif (21 sequences). We developed visual analytics resources to facilitate the investigation of these categories of datasets in the presence or absence of the mercury-methylating gene pair (hgcAB). Future research could utilize these functional categories to investigate the participation of universal stress proteins in the bacterial cellular uptake of inorganic mercury and methylmercury production, especially in anaerobic aquatic environments.

Integrating Datasets on Public Health and Clinical Aspects of Sickle Cell Disease for Effective Community-Based Research and Practice.

Sickle cell disease (SCD) is a genetic disease that has multiple aspects including public health and clinical aspects. The goals of the research study were to (1) understand the public health aspects of sickle cell disease, and (2) understand the overlap between public health aspects and clinical aspects that can inform research and practice beneficial to stakeholders in sickle cell disease management. The approach involved the construction of datasets from textual data sources produced by experts on sickle cell disease including from landmark publications published in 2020 on sickle cell disease in the United States. The interactive analytics of the integrated datasets that we produced identified that community-based approaches are common to both public health and clinical aspects of sickle cell disease. An interactive visualization that we produced can aid the understanding of the alignment of governmental organizations to recommendations for addressing sickle cell disease in the United States. From a global perspective, the interactive analytics of the integrated datasets can support the knowledge transfer stage of the SICKLE recommendations (Skills transfer, Increasing self-efficacy, Coordination, Knowledge transfer, Linking to adult services, and Evaluating readiness) for effective pediatric to adult transition care for patients with sickle cell disease. Considering the increased digital transformations resulting from the COVID-19 pandemic, the constructed datasets from expert recommendations can be integrated within remote digital platforms that expand access to care for individuals living with sickle cell disease. Finally, the interactive analytics of integrated expert recommendations on sickle cell disease management can support individual and team expertise for effective community-based research and practice.

Knowledge Visualizations to Inform Decision Making for Improving Food Accessibility and Reducing Obesity Rates in the United States.

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.

Harnessing Knowledge for Improving Access to Fruits and Vegetables at Farmers Markets: Interactive Data Visualization to Inform Food Security Programs and Policy.

High consumption of fruits and vegetables leads to decreased risk of various chronic diseases, including obesity and cardiovascular disease. Community-level barriers to access fruits and vegetables include the high cost, limited availability, and transportation. Farmers markets are a priority strategy for improving community access to fresh fruits and vegetables. The U.S. Department of Agriculture (USDA) National Farmers Market Directory is a voluntary self-reported data source on farmers markets. The objective of this investigation of the USDA farmers markets data directory was to determine how farmers markets in the United States are grouped according to (1) availability of fruits and vegetables and (2) the payment accepted. We designed and implemented interactive data visualizations in visual analytics software to understand access to fruits and vegetables at farmers markets from 8,497 entries in the USDA Farmers Market Directory. Among the 665 new or updated entries in year 2018, a subset of 641 (96%) farmers markets with availability of fresh fruits and vegetables had 16 subgroups. Additionally, a subgroup of 102 (16%) farmer markets accepted all four federal nutrition assistance benefits (SFMNP, SNAP, WIC CVVs, and WIC FMNP). The interactive data visualizations including geographic maps connected to social media resources can be useful in advocacy efforts and can inform policy improvements designed to improve physical, social, and economic access to fruits and vegetables at farmers markets.

Arsenicosis in bladder pathology and schistosomiasis in Eggua, Nigeria.

Background: Chronic schistosomiasis and arsenic exposure through drinking water are some of the risk factors for bladder cancer. To determine the association of schistosomiasis and arsenicosis with bladder pathologies, 122 individuals from Eggua in southwest Nigeria were recruited for this study. Methods: Prevalence of schistosomiasis was determined by urine microscopy and PCR. Total urinary arsenic concentration and arsenic levels in three different water sources in the community were assessed by flame atomic absorption spectrometry. Bladder pathologies were investigated by ultrasonography. The data collected were evaluated with chi-square (χ2) and ANOVA tests to examine the relationships among demographic factors, infection, bladder pathologies and urinary arsenic concentrations. Results: The prevalence and mean intensity of schistosomiasis were 21.3% and 20.7 eggs/10 mL urine, respectively. Arsenic concentration in two of the water sources, River Yewa (0.46 mg/L) and borehole (0.52 mg/L), were above the WHO standard (0.01 mg/L); and the mean concentration in urine samples, 1.17 mg/L, was also above the WHO standard (0.2 mg/L). There was no evidence of an association between bladder pathology and arsenicosis, or between schistosomiasis associated-bladder pathology and arsenicosis (p=0.66). Conclusions: Arsenicosis is a public health concern in the study population. At the moment no clear roles are envisaged for it in the development of bladder pathologies or urinary schistosomiasis-associated bladder pathologies in Eggua.

Metabolite profiling for biomarkers in Schistosoma haematobium infection and associated bladder pathologies.

BACKGROUND: Metabolic fingerprinting analysis can offer insights into underlying reactions in a biological system; hence it is crucial to the understanding of disease pathogenesis and could provide useful tools for discovering biomarkers. We sought to examine the urine and plasma metabolome in individuals affected by urogenital schistosomiasis and its associated-bladder pathologies. METHODOLOGY: Blood and midstream urine were obtained from volunteers who matched our inclusion criteria among residents from Eggua, southwestern Nigeria. Samples were screened by urinalysis, microscopy, PCR and ultrasonography, and categorised as advanced (urogenital schistosomiasis associated-bladder pathologies), infection-only (urogenital schistosomiasis alone) and controls (no infection and no pathology). Metabolites were extracted and data acquired with ultra high-performance liquid chromatography coupled with Thermo Q-Exactive orbitrap HRMS. Data was analysed with MetaboAnalyst, Workflow4Metabolomics, HMDB, LipidMaps and other bioinformatics tools, with univariate and multivariate statistics for metabolite selection. PRINCIPAL FINDINGS: There were low levels of host sex steroids, and high levels of several benzenoids, catechols and lipids (including ganglioside, phosphatidylcholine and phosphatidylethanolamine), in infection-only and advanced cases (FDR<0.05, VIP>2, delta>2.0). Metabolites involved in biochemical pathways related to chorismate production were abundant in controls, while those related to choline and sphingolipid metabolism were upregulated in advanced cases (FDR<0.05). Some of these human host and Schistosoma haematobium molecules, including catechol estrogens, were good markers to distinguish infection-only and advanced cases. CONCLUSIONS: Altered glycerophospholipid and sphingolipid metabolism could be key factors promoting the development of bladder pathologies and tumours during urogenital schistosomiasis.

Plant Phenology Supports the Multi-emergence Hypothesis for Ebola Spillover Events.

Ebola virus disease outbreaks in animals (including humans and great apes) start with sporadic host switches from unknown reservoir species. The factors leading to such spillover events are little explored. Filoviridae viruses have a wide range of natural hosts and are unstable once outside hosts. Spillover events, which involve the physical transfer of viral particles across species, could therefore be directly promoted by conditions of host ecology and environment. In this report, we outline a proof of concept that temporal fluctuations of a set of ecological and environmental variables describing the dynamics of the host ecosystem are able to predict such events of Ebola virus spillover to humans and animals. We compiled a data set of climate and plant phenology variables and Ebola virus disease spillovers in humans and animals. We identified critical biotic and abiotic conditions for spillovers via multiple regression and neural network-based time series regression. Phenology variables proved to be overall better predictors than climate variables. African phenology variables are not yet available as a comprehensive online resource. Given the likely importance of phenology for forecasting the likelihood of future Ebola spillover events, our results highlight the need for cost-effective transect surveys to supply phenology data for predictive modelling efforts.

Correction: The microbiome in urogenital schistosomiasis and induced bladder pathologies.

[This corrects the article DOI: 10.1371/journal.pntd.0005826.].

The microbiome in urogenital schistosomiasis and induced bladder pathologies.

BACKGROUND: Human schistosomiasis is a highly prevalent neglected tropical disease (NTD) caused by Schistosoma species. Research on the molecular mechanisms influencing the outcomes of bladder infection by Schistosoma haematobium is urgently needed to develop new diagnostics, therapeutics and infection prevention strategies. The objective of the research study was to determine the microbiome features and changes in urine during urogenital schistosomiasis and induced bladder pathologies. METHODOLOGY: Seventy participants from Eggua, southwestern Nigeria provided morning urine samples and were screened for urogenital schistosomiasis infection and bladder pathologies in a cross-sectional study. Highthroughput NGS sequencing was carried out, targeting the 16S V3 region. Filtered reads were processed and analyzed in a bioinformatics pipeline. PRINCIPAL FINDINGS: The study participants (36 males and 34 females, between ages 15 and 65) were categorized into four groups according to status of schistosomiasis infection and bladder pathology. Data analytics of the next-generation sequencing reads revealed that Proteobacteria and Firmicutes dominated and had influence on microbiome structure of both non-infected persons and persons with urogenital schistosomiasis. Furthermore, gender and age influenced taxa abundance independent of infection or bladder pathology. Several taxa distinguished urogenital schistosomiasis induced bladder pathologies from urogenital schistosomiasis infection alone and from healthy persons, including known immune-stimulatory taxa such as Fusobacterium, Sphingobacterium and Enterococcus. Some of these significant taxa, especially Sphingobacterium were projected as markers of infection, while several genera including potentially beneficial taxa such as Trabulsiella and Weissella, were markers of the non-infected. Finally, expected changes in protein functional categories were observed to relate to cellular maintenance and lipid metabolism. CONCLUSION: The urinary microbiome is a factor to be considered in developing biomarkers, diagnostic tools, and new treatment for urogenital schistosomiasis and induced bladder pathologies.

Transcriptomic and macroevolutionary evidence for phenotypic uncoupling between frog life history phases.

Anuran amphibians undergo major morphological transitions during development, but the contribution of their markedly different life-history phases to macroevolution has rarely been analysed. Here we generate testable predictions for coupling versus uncoupling of phenotypic evolution of tadpole and adult life-history phases, and for the underlying expression of genes related to morphological feature formation. We test these predictions by combining evidence from gene expression in two distantly related frogs, Xenopus laevis and Mantidactylus betsileanus, with patterns of morphological evolution in the entire radiation of Madagascan mantellid frogs. Genes linked to morphological structure formation are expressed in a highly phase-specific pattern, suggesting uncoupling of phenotypic evolution across life-history phases. This gene expression pattern agrees with uncoupled rates of trait evolution among life-history phases in the mantellids, which we show to have undergone an adaptive radiation. Our results validate a prevalence of uncoupling in the evolution of tadpole and adult phenotypes of frogs.

Genomic Evidence for Bacterial Determinants Influencing Obesity Development.

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 Akkermansiamuciniphila 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.

Secondary Data Analytics of Aquaporin Expression Levels in Glioblastoma Stem-Like Cells.

Glioblastoma is the most common brain tumor in adults in which recurrence has been attributed to the presence of cancer stem cells in a hypoxic microenvironment. On the basis of tumor formation in vivo and growth type in vitro, two published microarray gene expression profiling studies grouped nine glioblastoma stem-like (GS) cell lines into one of two groups: full (GSf) or restricted (GSr) stem-like phenotypes. Aquaporin-1 (AQP1) and aquaporin-4 (AQP4) are water transport proteins that are highly expressed in primary glial-derived tumors. However, the expression levels of AQP1 and AQP4 have not been previously described in a panel of 92 glioma samples. Therefore, we designed secondary data analytics methods to determine the expression levels of AQP1 and AQP4 in GS cell lines and glioblastoma neurospheres. Our investigation also included a total of 2,566 expression levels from 28 Affymetrix microarray probe sets encoding 13 human aquaporins (AQP0-AQP12); CXCR4 (the receptor for stromal cell derived factor-1 [SDF-1], a potential glioma stem cell therapeutic target]); and PROM1 (gene encoding CD133, the widely used glioma stem cell marker). Interactive visual representation designs for integrating phenotypic features and expression levels revealed that inverse expression levels of AQP1 and AQP4 correlate with distinct phenotypes in a set of cell lines grouped into full and restricted stem-like phenotypes. Discriminant function analysis further revealed that AQP1 and AQP4 expression are better predictors for tumor formation and growth types in glioblastoma stem-like cells than are CXCR4 and PROM1. Future investigations are needed to characterize the molecular mechanisms for inverse expression levels of AQP1 and AQP4 in the glioblastoma stem-like neurospheres.

Evaluative profiling of arsenic sensing and regulatory systems in the human microbiome project genomes.

The influence of environmental chemicals including arsenic, a type 1 carcinogen, on the composition and function of the human-associated microbiota is of significance in human health and disease. We have developed a suite of bioinformatics and visual analytics methods to evaluate the availability (presence or absence) and abundance of functional annotations in a microbial genome for seven Pfam protein families: As(III)-responsive transcriptional repressor (ArsR), anion-transporting ATPase (ArsA), arsenical pump membrane protein (ArsB), arsenate reductase (ArsC), arsenical resistance operon transacting repressor (ArsD), water/glycerol transport protein (aquaporins), and universal stress protein (USP). These genes encode function for sensing and/or regulating arsenic content in the bacterial cell. The evaluative profiling strategy was applied to 3,274 genomes from which 62 genomes from 18 genera were identified to contain genes for the seven protein families. Our list included 12 genomes in the Human Microbiome Project (HMP) from the following genera: Citrobacter, Escherichia, Lactobacillus, Providencia, Rhodococcus, and Staphylococcus. Gene neighborhood analysis of the arsenic resistance operon in the genome of Bacteroides thetaiotaomicron VPI-5482, a human gut symbiont, revealed the adjacent arrangement of genes for arsenite binding/transfer (ArsD) and cytochrome c biosynthesis (DsbD_2). Visual analytics facilitated evaluation of protein annotations in 367 genomes in the phylum Bacteroidetes identified multiple genomes in which genes for ArsD and DsbD_2 were adjacently arranged. Cytochrome c, produced by a posttranslational process, consists of heme-containing proteins important for cellular energy production and signaling. Further research is desired to elucidate arsenic resistance and arsenic-mediated cellular energy production in the Bacteroidetes.

Proteomics-Based Identification of Differentially Abundant Proteins from Human Keratinocytes Exposed to Arsenic Trioxide.

INTRODUCTION: Arsenic is a widely distributed environmental toxicant that can cause multi-tissue pathologies. Proteomic assays allow for the identification of biological processes modulated by arsenic in diverse tissue types. METHOD: The altered abundance of proteins from HaCaT human keratinocyte cell line exposed to arsenic was quantified using a label-free LC-MS/MS mass spectrometry workflow. Selected proteomics results were validated using western blot and RT-PCR. A functional annotation analytics strategy that included visual analytical integration of heterogeneous data sets was developed to elucidate functional categories. The annotations integrated were mainly tissue localization, biological process and gene family. RESULT: The abundance of 173 proteins was altered in keratinocytes exposed to arsenic; in which 96 proteins had increased abundance while 77 proteins had decreased abundance. These proteins were also classified into 69 Gene Ontology biological process terms. The increased abundance of transferrin receptor protein (TFRC) was validated and also annotated to participate in response to hypoxia. A total of 33 proteins (11 increased abundance and 22 decreased abundance) were associated with 18 metabolic process terms. The Glutamate--cysteine ligase catalytic subunit (GCLC), the only protein annotated with the term sulfur amino acid metabolism process, had increased abundance while succinate dehydrogenase [ubiquinone] iron-sulfur subunit, mitochondrial precursor (SDHB), a tumor suppressor, had decreased abundance. CONCLUSION: A list of 173 differentially abundant proteins in response to arsenic trioxide was grouped using three major functional annotations covering tissue localization, biological process and protein families. A possible explanation for hyperpigmentation pathologies observed in arsenic toxicity is that arsenic exposure leads to increased iron uptake in the normally hypoxic human skin. The proteins mapped to metabolic process terms and differentially abundant are candidates for evaluating metabolic pathways perturbed by arsenicals.

A candidate multimodal functional genetic network for thermal adaptation.

Vertebrate ectotherms such as reptiles provide ideal organisms for the study of adaptation to environmental thermal change. Comparative genomic and exomic studies can recover markers that diverge between warm and cold adapted lineages, but the genes that are functionally related to thermal adaptation may be difficult to identify. We here used a bioinformatics genome-mining approach to predict and identify functions for suitable candidate markers for thermal adaptation in the chicken. We first established a framework of candidate functions for such markers, and then compiled the literature on genes known to adapt to the thermal environment in different lineages of vertebrates. We then identified them in the genomes of human, chicken, and the lizard Anolis carolinensis, and established a functional genetic interaction network in the chicken. Surprisingly, markers initially identified from diverse lineages of vertebrates such as human and fish were all in close functional relationship with each other and more associated than expected by chance. This indicates that the general genetic functional network for thermoregulation and/or thermal adaptation to the environment might be regulated via similar evolutionarily conserved pathways in different vertebrate lineages. We were able to identify seven functions that were statistically overrepresented in this network, corresponding to four of our originally predicted functions plus three unpredicted functions. We describe this network as multimodal: central regulator genes with the function of relaying thermal signal (1), affect genes with different cellular functions, namely (2) lipoprotein metabolism, (3) membrane channels, (4) stress response, (5) response to oxidative stress, (6) muscle contraction and relaxation, and (7) vasodilation, vasoconstriction and regulation of blood pressure. This network constitutes a novel resource for the study of thermal adaptation in the closely related nonavian reptiles and other vertebrate ectotherms.

Geminin overexpression promotes imatinib sensitive breast cancer: a novel treatment approach for aggressive breast cancers, including a subset of triple negative.

Breast cancer is the second leading cause of cancer-related deaths in women. Triple negative breast cancer (TNBC) is an aggressive subtype that affects 10-25% mostly African American women. TNBC has the poorest prognosis of all subtypes with rapid progression leading to mortality in younger patients. So far, there is no targeted treatment for TNBC. To that end, here we show that c-Abl is one of several tyrosine kinases that phosphorylate and activate geminin's ability to promote TNBC. Analysis of >800 breast tumor samples showed that geminin is overexpressed in ∼50% of all tumors. Although c-Abl is overexpressed in ∼90% of all tumors, it is only nuclear in geminin overexpressing tumors. In geminin-negative tumors, c-Abl is only cytoplasmic. Inhibiting c-Abl expression or activity (using imatinib or nilotinib) prevented geminin Y150 phosphorylation, inactivated the protein, and most importantly converted overexpressed geminin from an oncogene to an apoptosis inducer. In pre-clinical orthotopic breast tumor models, geminin-overexpressing cells developed aneuploid and invasive tumors, which were suppressed when c-Abl expression was blocked. Moreover, established geminin overexpressing orthotopic tumors regressed when treated with imatinib or nilotinib. Our studies support imatinib/nilotonib as a novel treatment option for patients with aggressive breast cancer (including a subset of TNBCs)-overexpressing geminin and nuclear c-Abl.

Application of universal stress proteins in probing the dynamics of potent degraders in complex terephthalate metagenome.

The culture-independent strategies to study microbial diversity and function have led to a revolution in environmental genomics, enabling fundamental questions about the distribution of microbes and their influence on bioremediation to be addressed. In this research we used the expression of universal stress proteins as a probe to determine the changes in degrading microbial population from a highly toxic terephthalate wastewater to a less toxic activated sludge bioreactor. The impact of relative toxicities was significantly elaborated at the levels of genus and species. The results indicated that 23 similar prokaryotic phyla were represented in both metagenomes irrespective of their relative abundance. Furthermore, the following bacteria taxa Micromonosporaceae, Streptomyces, Cyanothece sp. PCC 7822, Alicyclobacillus acidocaldarius, Bacillus halodurans, Leuconostoc mesenteroides, Lactococcus garvieae, Brucellaceae, Ralstonia solanacearum, Verminephrobacter eiseniae, Azoarcus, Acidithiobacillus ferrooxidans, Francisella tularensis, Methanothermus fervidus, and Methanocorpusculum labreanum were represented only in the activated sludge bioreactor. These highly dynamic microbes could serve as taxonomic biomarkers for toxic thresholds related to terephthalate and its derivatives. This paper, highlights the application of universal stress proteins in metagenomics analysis. Dynamics of microbial consortium of this nature can have future in biotechnological applications in bioremediation of toxic chemicals and radionuclides.

Identification of Functional Regulatory Residues of the ß -Lactam Inducible Penicillin Binding Protein in Methicillin-Resistant Staphylococcus aureus.

Resistance to methicillin by Staphylococcus aureus is a persistent clinical problem worldwide. A mechanism for resistance has been proposed in which methicillin resistant Staphylococcus aureus (MRSA) isolates acquired a new protein called ß -lactam inducible penicillin binding protein (PBP-2'). The PBP-2' functions by substituting other penicillin binding proteins which have been inhibited by ß -lactam antibiotics. Presently, there is no structural and regulatory information on PBP-2' protein. We conducted a complete structural and functional regulatory analysis of PBP-2' protein. Our analysis revealed that the PBP-2' is very stable with more hydrophilic amino acids expressing antigenic sites. PBP-2' has three striking regulatory points constituted by first penicillin binding site at Ser25, second penicillin binding site at Ser405, and finally a single metallic ligand binding site at Glu657 which binds to Zn(2+) ions. This report highlights structural features of PBP-2' that can serve as targets for developing new chemotherapeutic agents and conducting site direct mutagenesis experiments.

Inferences on the biochemical and environmental regulation of universal stress proteins from Schistosomiasis parasites.

BACKGROUND: Human schistosomiasis is a freshwater snail-transmitted disease caused by parasitic flatworms of the Schistosoma genus. Schistosoma haematobium, Schistosoma mansoni, and Schistosoma japonicum are the three major species infecting humans. These parasites undergo a complex developmental life cycle, in which they encounter a plethora of environmental signals. The presence of genes encoding the universal stress protein (USP) domain in the genomes of Schistosoma spp. suggests these flatworms are equipped to respond to unfavorable conditions. Though data on gene expression is available for USP genes, their biochemical and environmental regulation are incompletely understood. The identification of additional regulatory molecules for Schistosoma. USPs, which may be present in the human, snail, or water environments, could also be useful for schistosomiasis interventions. METHODS: We developed a protocol that includes a visual analytics stage to facilitate integration, visualization, and decision making, from the results of sequence analyses and data collection on a set of 13 USPs from S. mansoni and S. japonicum. RESULTS: Multiple sequence alignment identified conserved sites that could be key residues regulating the function of USPs of the Schistosoma spp. Based on the consistency and completeness of sequence annotation, we prioritized for further research the gene for a 184-amino-acid-long USP that is present in the genomes of the three human-infecting Schistosoma spp. Calcium, zinc, and magnesium ions were predicted to interact with the protein product of the gene. CONCLUSION: Given that the initial effects of praziquantel on schistosomes include the influx of calcium ions, additional investigations are required to (1) functionally characterize the interactions of calcium ions with the amino acid residues of Schistosoma USPs; and (2) determine the transcriptional response of Schistosoma. USP genes to praziquantel. The data sets produced, and the visual analytics views that were developed, can be easily reused to develop new hypotheses.