Multi-Agent Based Attack-Resilient System Integrity Protection for Smart Grid
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Engineering↗
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A Typology of Decision-Making Tasks for Visualization
Despite decision-making being a vital goal of data visualization, little work has been done to differentiate decision-making tasks within the field. While visualization task taxonomies and typologies exist, they often focus on more granular analytical tasks that are too low-level to describe large complex decisions, which can make it difficult to reason about and design decision-support tools. In this paper, we contribute a typology of decision-making tasks that were iteratively refined from a list of design goals distilled from a literature review. Our typology is concise and consists of only three tasks: CHOOSE, ACTIVATE, and CREATE. Although decision types originating in other disciplines exist, we provide definitions for these tasks that are suitable for the visualization community. Our proposed typology offers two benefits. First, the ability to compose and hierarchically organize the tasks enables flexible and clear descriptions of decisions with varying levels of complexities. Second, the typology encourages productive discourse between visualization designers and domain experts by abstracting the intricacies of data, thereby promoting clarity and rigorous analysis of decision-making processes. We demonstrate the benefits of our typology through four case studies, and present an evaluation of the typology from semi-structured interviews with experienced members of the visualization community who have contributed to developing or publishing decision support systems for domain experts. Our interviewees used our typology to delineate the decision-making processes supported by their systems, demonstrating its descriptive capacity and effectiveness. Finally, we present preliminary findings on the usefulness of our typology for visualization design.
97 MATHEMATICS AND COMPUTING↗
Composition, Growth, Succession, and Function in the Cladophora Microbiome: Insights From Quantitative Stable Isotope Probing and NanoSIMS Imaging
The branching green macroalga Cladophora glomerata and its epiphytic microbiome dominate summer biomass in the Eel River, a Northern California river under Mediterranean (summer drought, winter rain) seasonality. Green Cladophora streamers proliferate in early summer, then change to yellow and then red-brown as epiphyte loads increase. Here, we characterised successional changes in epiphytic bacteria on Cladophora, examining both community composition and growth rates, using quantitative Stable Isotope Probing (qSIP) and 16S rRNA gene amplicon sequencing. The number of bacterial taxa increased with succession while growth rates peaked in the middle stage. NanoSIMS imaging confirmed high sulphur (S) concentrations in Cladophora cell walls relative to surrounding biomass, coinciding with a bloom of sulphur bacteria (bacteria that reduce or oxidise sulphur/sulphates). In general, relative abundances and growth rates were independent, indicating that either metric alone is insufficient for understanding how taxonomy and functional groups affect ecosystem processes. For instance, the relative abundance of nitrogen fixers peaked in the late summer when their relative growth rates were slowest. Such patterns may be driven by space competition limiting growth. Together, changes in abundance and relative growth rates suggest different limiting factors for different functional groups in the Cladophora microbiome at multiple successional stages.
Biological and medical sciences↗
taxadb: A high‐performance local taxonomic database interface
Abstract A familiar and growing challenge in ecological and evolutionary research is that of establishing consistent taxonomy when combining data from separate sources. While this problem is already well understood and numerous naming authorities have been created to address the issue, most researchers lack a fast, consistent, and intuitive way to retrieve taxonomic names. We present taxadb R package which creates a local database, managed automatically from within R, to provide fast operations on millions of taxonomic names. taxadb provides access to established naming authorities to resolve synonyms, taxonomic identifiers, and hierarchical classification in a consistent and intuitive data format. taxadb makes operation on millions of taxonomic names fast and manageable.
Norman, Kari E. A.↗
State of the Art in Time‐Dependent Flow Topology: Interpreting Physical Meaningfulness Through Mathematical Properties
Abstract We present a state‐of‐the‐art report on time‐dependent flow topology. We survey representative papers in visualization and provide a taxonomy of existing approaches that generalize flow topology from time‐independent to time‐dependent settings. The approaches are classified based upon four categories: tracking of steady topology, reference frame adaption, pathline classification or clustering, and generalization of critical points. Our unique contributions include introducing a set of desirable mathematical properties to interpret physical meaningfulness for time‐dependent flow visualization, inferring mathematical properties associated with selective research papers, and utilizing such properties for classification. The five most important properties identified in the existing literature include coincidence with the steady case, induction of a partition within the domain, Lagrangian invariance, objectivity, and Galilean invariance.
Bujack, Roxana↗
Scalar Field Comparison with Topological Descriptors: Properties and Applications for Scientific Visualization
In topological data analysis and visualization, topological descriptors such as persistence diagrams, merge trees, contour trees, Reeb graphs, and Morse–Smale complexes play an essential role in capturing the shape of scalar field data. Herein we present a state–of–the–art report on scalar field comparison using topological descriptors. We provide a taxonomy of existing approaches based on visualization tasks associated with three categories of data: single fields, time–varying fields, and ensembles. These tasks include symmetry detection, periodicity detection, key event/feature detection, feature tracking, clustering, and structure statistics. Our main contributions include the formulation of a set of desirable mathematical and computational properties of comparative measures, and the classification of visualization tasks and applications that are enabled by these measures.
97 MATHEMATICS AND COMPUTING↗
Scalable Computation of Topological Abstractions for Scalar Data
Topological data analysis has become an important tool for large scale scalar data analysis and visualization, efficiently extracting the inherent structure and features of interest of the data. However, with growing dataset sizes and complexity, it is increasingly becoming infeasible to compute topological abstractions of interest in serial and on single machines. This paper presents the state of the art in the scalable computation of topological abstractions on scalar data, in shared memory parallel on single machines, and in distributed memory parallel on multiple machines. We highlight results for set‐based, graph‐based and complex‐based abstractions and organize the state of the art based on this taxonomy. The paper identifies parallelization and distribution techniques common in topological algorithms and highlights further areas of interest with underdeveloped efforts.
97 MATHEMATICS AND COMPUTING↗
Description of Freudenthalidium gen. nov. and Halluxium gen. nov. to Formally Recognize Clades Fr3 and H as Genera in the Family Symbiodiniaceae (Dinophyceae)
The Symbiodiniaceae are a family of marine dinoflagellates known mostly for their endosymbiotic interactions with invertebrates and protists, but facultatively and exclusively free‐living life histories in this family are also evident. A recent systematic revision of the Symbiodiniaceae replaced the clade‐based nomenclature of seven divergent lineages of “ Symbiodinium ” sensu lato with one based on formally described genera. The revised taxonomy was not extended to the whole group because type species to describe a new genus for each of the remaining clades and subclades were lacking. In an effort to characterize benthic habitats of symbiodiniaceans in sediments at Heron Island (Great Barrier Reef, Australia), we isolated >100 monoclonal Symbiodiniaceae cultures. Four of these belonged to Symbiodiniaceae ‘subclade’ Fr3, and three to Clade H, based on nucleotide sequence similarity (ITS2, LSU, cp23S, and mtCOB), representing the first cultures of these taxa. Based on these isolates, we propose two new genera: Freudenthalidium gen. nov. and Halluxium gen. nov., circumscribing Clades Fr3 and H, respectively. Three new species are described: Freudenthalidium heronense , F. endolithicum , and Halluxium pauxillum . Kofoidian tabulations of motile cells confirm previous observations that amphiesmal vesicle arrangements are generally conserved across the family. These descriptions are an important step toward completing the systematic revision of the Symbiodiniaceae. That this contribution was enabled by isolates from an endopsammic habitat highlights the potential of discovering new symbiodiniacean species in the environment, the study of which will lead to a deeper understanding of free‐living versus symbiotic life histories in this ecologically important family of dinoflagellates.
Nitschke, Matthew R.↗
The Vertebrate Breed Ontology: Toward Effective Breed Data Standardization
Abstract Background Limited universally-adopted data standards in veterinary medicine hinder data interoperability and therefore integration and comparison; this ultimately impedes the application of existing information-based tools to support advancement in diagnostics, treatments, and precision medicine. Hypothesis/Objectives A single, coherent, logic-based standard for documenting breed names in health, production, and research-related records will improve data use capabilities in veterinary and comparative medicine. Animals No live animals were used. Methods The Vertebrate Breed Ontology (VBO) was created from breed names and related information compiled from the Food and Agriculture Organization of the United Nations, breed registries, communities, and experts, using manual and computational approaches. Each breed is represented by a VBO term that includes breed information and provenance as metadata. VBO terms are classified using description logic to allow computational applications and Artificial Intelligence–readiness. Results VBO is an open, community-driven ontology representing over 19 500 livestock and companion animal breed concepts covering 49 species. Breeds are classified based on community and expert conventions (e.g., cattle breed) and supported by relations to the breed's genus and species indicated by National Center for Biotechnology Information (NCBI) Taxonomy terms. Relationships between VBO terms (e.g., relating breeds to their foundation stock) provide additional context to support advanced data analytics. VBO term metadata includes synonyms, breed identifiers/codes, and attributed cross-references to other databases. Conclusion and Clinical Importance The adoption of VBO as a standard for breed names in databases and veterinary electronic health records enhances veterinary data interoperability and computability, supporting precision medicine.
Veterinary Sciences↗
Genetic time traveling: sequencing old herbarium specimens, including the oldest herbarium specimen sequenced from kingdom Fungi, reveals the population structure of an agriculturally significant rust
Summary Sequencing herbarium specimens can be instrumental in answering ecological, evolutionary, and taxonomic inquiries. We developed a protocol for sequencing herbarium specimens of rust fungi (Pucciniales) and proceeded to sequence specimens ranging from 4 to 211 yr old from five different genera. We then obtained sequences from an economically important biological control agent, Puccinia suaveolens , to highlight the potential of sequencing herbarium specimens in an ecological sense and to evaluate the following hypotheses: (1) The population structure of a plant pathogen changes over time, and (2) introduced pathogens are more diverse in their native range. Our efforts resulted in sequences from 87 herbarium specimens that revealed a high level of diversity with a population structure that exhibited spatial–temporal patterns. The specimens sequenced from Europe showed more diversity than the ones from North America, uncovering an invasion pattern likely related to its European native host in North America. Additionally, to the best of our knowledge, the specimen from France collected in c. 1811 is the oldest herbarium specimen sequenced from kingdom Fungi. In conclusion, sequencing old herbarium specimens is an important tool that can be extrapolated to better understand plant–microbe evolution and to evaluate old type specimens to solidify the taxonomy of plant pathogenic fungi.
Plant Sciences↗
High-throughput genetic engineering of nonmodel and undomesticated bacteria via iterative site-specific genome integration
Efficient genome engineering is critical to understand and use microbial functions. Despite recent development of tools such as CRISPR-Cas gene editing, efficient integration of exogenous DNA with well-characterized functions remains limited to model bacteria. Here, we describe serine recombinase–assisted genome engineering, or SAGE, an easy-to-use, highly efficient, and extensible technology that enables selection marker–free, site-specific genome integration of up to 10 DNA constructs, often with efficiency on par with or superior to replicating plasmids. SAGE uses no replicating plasmids and thus lacks the host range limitations of other genome engineering technologies. We demonstrate the value of SAGE by characterizing genome integration efficiency in five bacteria that span multiple taxonomy groups and biotechnology applications and by identifying more than 95 heterologous promoters in each host with consistent transcription across environmental and genetic contexts. We anticipate that SAGE will rapidly expand the number of industrial and environmental bacteria compatible with high-throughput genetics and synthetic biology.
59 BASIC BIOLOGICAL SCIENCES↗
Community Structure of Arbuscular Mycorrhizal Fungi in Soils of Switchgrass Harvested for Bioenergy
We assessed the different species of beneficial fungi living in agricultural fields of switchgrass, a large grass grown for biofuels, using high-resolution DNA sequencing. Contrary to our expectations, the fungi were not greatly affected by fertilization. However, we found a positive relationship between plant productivity and the number of families of beneficial fungi at one site. Furthermore, we sequenced many species that could not be identified with existing reference databases. One group of fungi was highlighted in an earlier study for being widely distributed but of unknown taxonomy. We discovered that this group belonged to a family called Pervetustaceae , which may benefit switchgrass in stressful environments. To produce higher-yielding switchgrass in a more sustainable manner, it could help to study these undescribed fungi and the ways in which they may contribute to greater switchgrass yield in the absence of fertilization.
59 BASIC BIOLOGICAL SCIENCES↗
Novel, active, and uncultured hydrocarbon-degrading microbes in the ocean
ABSTRACT Given the vast quantity of oil and gas input to the marine environment annually, hydrocarbon degradation by marine microorganisms is an essential ecosystem service. Linkages between taxonomy and hydrocarbon degradation capabilities are largely based on cultivation studies, leaving a knowledge gap regarding the intrinsic ability of uncultured marine microbes to degrade hydrocarbons. To address this knowledge gap, metagenomic sequence data from the Deepwater Horizon (DWH) oil spill deep-sea plume was assembled to which metagenomic and metatranscriptomic reads were mapped. Assembly and binning produced new DWH metagenome-assembled genomes that were evaluated along with their close relatives, all of which are from the marine environment (38 total). These analyses revealed globally distributed hydrocarbon-degrading microbes with clade-specific substrate degradation potentials that have not been reported previously. For example, methane oxidation capabilities were identified in all Cycloclasticus . Furthermore, all Bermanella encoded and expressed genes for non-gaseous n -alkane degradation; however, DWH Bermanella encoded alkane hydroxylase, not alkane 1-monooxygenase. All but one previously unrecognized DWH plume member in the SAR324 and UBA11654 have the capacity for aromatic hydrocarbon degradation. In contrast, Colwellia were diverse in the hydrocarbon substrates they could degrade. All clades encoded nutrient acquisition strategies and response to cold temperatures, while sensory and acquisition capabilities were clade specific. These novel insights regarding hydrocarbon degradation by uncultured planktonic microbes provides missing data, allowing for better prediction of the fate of oil and gas when hydrocarbons are input to the ocean, leading to a greater understanding of the ecological consequences to the marine environment. IMPORTANCE Microbial degradation of hydrocarbons is a critically important process promoting ecosystem health, yet much of what is known about this process is based on physiological experiments with a few hydrocarbon substrates and cultured microbes. Thus, the ability to degrade the diversity of hydrocarbons that comprise oil and gas by microbes in the environment, particularly in the ocean, is not well characterized. Therefore, this study aimed to utilize non-cultivation-based ‘omics data to explore novel genomes of uncultured marine microbes involved in degradation of oil and gas. Analyses of newly assembled metagenomic data and previously existing genomes from other marine data sets, with metagenomic and metatranscriptomic read recruitment, revealed globally distributed hydrocarbon-degrading marine microbes with clade-specific substrate degradation potentials that have not been previously reported. This new understanding of oil and gas degradation by uncultured marine microbes suggested that the global ocean harbors a diversity of hydrocarbon-degrading bacteria, which can act as primary agents regulating ecosystem health.
Howe, Kathryn L.↗
Genome-sequenced bacterial collection from sorghum aerial root mucilage
ABSTRACT A collection of 47 bacteria isolated from the mucilage of aerial roots of energy sorghum is available at the Great Lakes Bioenergy Research Center, Michigan State University, Michigan, USA. We enriched bacteria with putative plant-beneficial phenotypes and included information on phenotypic diversity, taxonomy, and whole genome sequences.
Mechan-Llontop, Marco E.↗
Genome-sequenced bacterial collection from sorghum epicuticular wax
ABSTRACT A collection of 44 isolates isolated from the epicuticular wax of stems of energy sorghum is available at the Great Lakes Bioenergy Researcher Center, Michigan State University, MI, USA. We enriched bacteria with putative plant-beneficial phenotypes and include information on their phenotypic diversity, taxonomy, and whole-genome sequences.
Mechan-Llontop, Marco E.↗
Complete Genome Sequence of Phormidium yuhuli AB48, Isolated from an Industrial Photobioreactor Environment
We report the genome of Phormidium yuhuli AB48, which includes a circular chromosome and a circular plasmid (4,747,469 bp and 51,599 bp, respectively). This is currently the only closed reference genome of an isolate of the Phormidium genus, based on the Genome Taxonomy Database (GTDB), providing a potential model system for sustainable biotechnology innovation.
59 BASIC BIOLOGICAL SCIENCES↗
MVP: a modular viromics pipeline to identify, filter, cluster, annotate, and bin viruses from metagenomes
While numerous computational frameworks and workflows are available for recovering prokaryote and eukaryote genomes from metagenome data, only a limited number of pipelines are designed specifically for viromics analysis. With many viromics tools developed in the last few years alone, it can be challenging for scientists with limited bioinformatics experience to easily recover, evaluate quality, annotate genes, dereplicate, assign taxonomy, and calculate relative abundance and coverage of viral genomes using state-of-the-art methods and standards. Here, we describe Modular Viromics Pipeline (MVP) v.1.0, a user-friendly pipeline written in Python and providing a simple framework to perform standard viromics analyses. MVP combines multiple tools to enable viral genome identification, characterization of genome quality, filtering, clustering, taxonomic and functional annotation, genome binning, and comprehensive summaries of results that can be used for downstream ecological analyses. Overall, MVP provides a standardized and reproducible pipeline for both extensive and robust characterization of viruses from large-scale sequencing data including metagenomes, metatranscriptomes, viromes, and isolate genomes. As a typical use case, we show how the entire MVP pipeline can be applied to a set of 20 metagenomes from wetland sediments using only 10 modules executed via command lines, leading to the identification of 11,656 viral contigs and 8,145 viral operational taxonomic units (vOTUs) displaying a clear beta-diversity pattern. Further, acting as a dynamic wrapper, MVP is designed to continuously incorporate updates and integrate new tools, ensuring its ongoing relevance in the rapidly evolving field of viromics. MVP is available at https://gitlab.com/ccoclet/mvp and as versioned packages in PyPi and Conda.
59 BASIC BIOLOGICAL SCIENCES↗
Genomic fingerprints of the world’s soil ecosystems
Despite the explosion of soil metagenomic data, we lack a synthesized understanding of patterns in the distribution and functions of soil microorganisms. These patterns are critical to predictions of soil microbiome responses to climate change and resulting feedbacks that regulate greenhouse gas release from soils. To address this gap, we assay 1,512 manually curated soil metagenomes using complementary annotation databases, read-based taxonomy, and machine learning to extract multidimensional genomic fingerprints of global soil microbiomes. Our objective is to uncover novel biogeographical patterns of soil microbiomes across environmental factors and ecological biomes with high molecular resolution. We reveal shifts in the potential for (i) microbial nutrient acquisition across pH gradients; (ii) stress-, transport-, and redox-based processes across changes in soil bulk density; and (iii) greenhouse gas emissions across biomes. We also use an unsupervised approach to reveal a collection of soils with distinct genomic signatures, characterized by coordinated changes in soil organic carbon, nitrogen, and cation exchange capacity and in bulk density and clay content that may ultimately reflect soil environments with high microbial activity. Genomic fingerprints for these soils highlight the importance of resource scavenging, plant-microbe interactions, fungi, and heterotrophic metabolisms. Across all analyses, we observed phylogenetic coherence in soil microbiomes—more closely related microorganisms tended to move congruently in response to soil factors. Collectively, the genomic fingerprints uncovered here present a basis for global patterns in the microbial mechanisms underlying soil biogeochemistry and help beget tractable microbial reaction networks for incorporation into process-based models of soil carbon and nutrient cycling.
59 BASIC BIOLOGICAL SCIENCES↗