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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.

 

The human placenta is a multifunctional, disc-shaped temporary fetal organ that develops in the uterus during pregnancy, connecting the mother and the fetus. The availability of large-scale datasets on the gene expression of placental cell types and scholarly articles documenting adverse pregnancy outcomes from maternal infection warrants the use of computational resources to aid in knowledge generation from disparate data sources. Using maternal Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection as a case study in microbial infection, we constructed integrated datasets and implemented visual analytics resources to facilitate robust investigations of placental gene expression data in the dimensions of flow, curation, and analytics. The visual analytics resources and associated datasets can support a greater understanding of SARS-CoV-2-induced changes to the human placental expression levels of 18,882 protein-coding genes and at least 1233 human gene groups/families. We focus this report on the human aquaporin gene family that encodes small integral membrane proteins initially studied for their roles in water transport across cell membranes. Aquaporin-9 (AQP9) was the only aquaporin downregulated in term placental villi from SARS-CoV-2-positive mothers. Previous studies have found that (1) oxygen signaling modulates placental development; (2) oxygen tension could modulate AQP9 expression in the human placenta; and (3) SARS-CoV-2 can disrupt the formation of oxygen-carrying red blood cells in the placenta. Thus, future research could be performed on microbial infection-induced changes to (1) the placental hematopoietic stem and progenitor cells; and (2) placental expression of human aquaporin genes, especially AQP9.

 

The promotion of global sustainability within environmental science courses requires a paradigm switch from knowledge-based teaching to teaching that stimulates higher-order cognitive skills. Non-major undergraduate science courses, such as environmental science, promote critical thinking in students in order to improve the uptake of scientific information and develop the rational decision making used to make more informed decisions. Science, engineering, technology and mathematics (STEM) courses rely extensively on visuals in lectures, readings and homework to improve knowledge. However, undergraduate students do not automatically acquire visual literacy and a lack of intervention from instructors could be limiting academic success. In this study, a visual literacy intervention was developed and tested in the face-to-face (FTF) and online sections of an undergraduate non-major Introduction to Environmental Science course. The intervention was designed to test and improve visual literacy at three levels: (1) elementary—identifying values; (2) intermediate—identifying trends; and (3) advanced—using the data to make projections or conclusions. Students demonstrated a significant difference in their ability to answer elementary and advanced visual literacy questions in both course sections in the pre-test and post-test. Students in the face-to-face course had significantly higher exam scores and higher median assessment scores compared to sections without a visual literacy intervention. The online section did not show significant improvements in visual literacy or academic success due to a lack of reinforcement of visual literacy following the initial intervention. The visual literacy intervention shows promising results in improving student academic success and should be considered for implementation in other general education STEM courses. 

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. 

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.