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At least 703 records · Page 39

Tailoring a Global Iron Regulon to a Uropathogen

Pathogenicity islands and plasmids bear genes for pathogenesis of various Escherichia coli pathotypes. Although there is a basic understanding of the contribution of these virulence factors to disease, less is known about variation in regulatory networks in determining disease phenotypes. Here, we dissected a regulatory network directed by the conserved iron homeostasis regulator, ferric uptake regulator (Fur), in uropathogenic E. coli (UPEC) strain CFT073. Comparing anaerobic genome-scale Fur DNA binding with Fur-dependent transcript expression and protein levels of the uropathogen to that of commensal E. coli K-12 strain MG1655 showed that the Fur regulon of the core genome is conserved but also includes genes within the pathogenicity/genetic islands. Unexpectedly, regulons indicative of amino acid limitation and the general stress response were also indirectly activated in the uropathogen fur mutant, suggesting that induction of the Fur regulon increases amino acid demand. Using RpoS levels as a proxy, addition of amino acids mitigated the stress. In addition, iron chelation increased RpoS to the same levels as in the fur mutant. The increased amino acid demand of the fur mutant or iron chelated cells was exacerbated by aerobic conditions, which could be partly explained by the O 2 -dependent synthesis of the siderophore aerobactin, encoded by an operon within a pathogenicity island. Taken together, these data suggest that in the iron-poor environment of the urinary tract, amino acid availability could play a role in the proliferation of this uropathogen, particularly if there is sufficient O 2 to produce aerobactin. IMPORTANCE Host iron restriction is a common mechanism for limiting the growth of pathogens. We compared the regulatory network controlled by Fur in uropathogenic E. coli (UPEC) to that of nonpathogenic E. coli K-12 to uncover strategies that pathogenic bacteria use to overcome iron limitation. Although iron homeostasis functions were regulated by Fur in the uropathogen as expected, a surprising finding was the activation of the stringent and general stress responses in the uropathogen fur mutant, which was rescued by amino acid addition. This coordinated global response could be important in controlling growth and survival under nutrient-limiting conditions and during transitions from the nutrient-rich environment of the lower gastrointestinal (GI) tract to the more restrictive environment of the urinary tract. The coupling of the response of iron limitation to increased demand for amino acids could be a critical attribute that sets UPEC apart from other E. coli pathotypes.

59 BASIC BIOLOGICAL SCIENCES↗

Hybridization capture sequencing for Vibrio spp. and associated virulence factors

ABSTRACT Proliferation ofVibriospp. in aquatic ecosystems is associated with climate change and, concomitantly, increased incidence of vibriosis. They are autochthonous to aquatic environments globally, but traditional metagenomic methods for detecting and typing pathogenicVibriospp. are challenged by their presence in relatively low abundance and ability to persist in a viable but nonculturable state. In the study reported here, hybridization capture sequencing (HCS) was employed to profile low-abundanceVibriospp. in environmental samples. The HCS panel targeted a family of molecular chaperones (CPN60) specific to 69Vibriospp. and 162Vibrio-specific virulence factors. This approach was evaluated in parallel with traditional whole-community shotgun sequencing in a metagenomic analysis of water and oyster samples collected from the Chesapeake Bay. In addition,Vibrio parahaemolyticusandVibrio vulnificusstrains isolated from the samples were subjected to whole-genome sequencing to determine the genetic characteristics of pathogenicVibriospp. circulating in an aquatic environment. HCS, employed to determine the incidence and characterization of specificVibriospp., yielded significantly greater metagenomic insight, notably a variety of otherVibriospp., including detection ofVibrio cholerae,Vibrio fluvialis, andVibrio aestuarianus, in addition toVibrio parahaemolyticusandVibrio vulnificus, and also important virulence factors not detectable using traditional molecular methods. Thus, pathogenicVibriospp. in aquatic ecosystems may be far more common than currently understood. It is concluded that environmental surveillance should include HCS, a valuable tool for the detection and characterization of pathogenic agents in aquatic ecosystems, notably vibrios. IMPORTANCE The increasing prevalence of pathogenicVibriospp. in aquatic ecosystems, driven by climate change, is closely linked to a rise in cholera and vibriosis cases, emphasizing the need for improved environmental surveillance. Vibrios are naturally occurring in aquatic environments globally, but traditional metagenomic methods for detecting and typing pathogenicVibriospp. are challenged by their presence in relatively low abundance and ability to persist in a viable but nonculturable state. In the study reported here, hybridization capture sequencing was employed to profile low-abundanceVibriospp. in metagenomic samples, namely water and oysters collected from the Chesapeake Bay. This approach was evaluated in parallel with traditional whole-community shotgun sequencing and whole-genome sequencing ofVibrio parahaemolyticusandVibrio vulnificusstrains isolated from the samples. Results suggest pathogenicVibriospp. in aquatic ecosystems may be far more common than currently understood, when multiple methods are considered for environmental surveillance.

Microbiology↗

A previously uncharacterized divisome-associated lipoprotein, DalA, is needed for normal cell division in Rhodobacterales

ABSTRACT The bacterial cell envelope is a key subcellular compartment with important roles in antibiotic resistance, nutrient acquisition, and cell morphology. We seek to gain a better understanding of proteins that contribute to the function of the cell envelope in Alphaproteobacteria . Using Rhodobacter sphaeroides , we show that a previously uncharacterized protein, RSP_1200, is an outer membrane (OM) lipoprotein that non-covalently binds peptidoglycan (PG). Using a fluorescently tagged version of this protein, we find that RSP_1200 undergoes a dynamic repositioning during the cell cycle and is enriched at the septum during cell division. We show that the position of RSP_1200 mirrors the location of FtsZ rings, leading us to propose that RSP_1200 is a newly identified component of the R. sphaeroides ’ divisome. Additional support for this hypothesis includes the co-precipitation of RSP_1200 with FtsZ, the Pal protein, and several predicted PG L,D-transpeptidases. We also find that a ∆ RSP_1200 mutation leads to defects in cell division, sensitivity to PG-active antibiotics, and results in the formation of OM protrusions at the septum during cell division. Based on these results, we propose to name RSP_1200 DalA (for division-associated lipoprotein A) and postulate that DalA serves as a scaffold to position or modulate the activity of PG transpeptidases that are needed to form envelope invaginations during cell division. We find that DalA homologs are present in members of the Rhodobacterales order within Alphaproteobacteria . Therefore, we propose that further analysis of this and related proteins will increase our understanding of the macromolecular machinery and proteins that participate in cell division in Gram-negative bacteria. IMPORTANCE Multi-protein complexes of the bacterial cell envelope orchestrate key processes like growth, division, biofilm formation, antimicrobial resistance, and production of valuable compounds. The subunits of these protein complexes are well studied in some bacteria, and differences in their composition and function are linked to variations in cell envelope composition, shape, and proliferation. However, some envelope protein complex subunits have no known homologs across the bacterial phylogeny. We find that Rhodobacter sphaeroides RSP_1200 is a newly identified lipoprotein (DalA) and that loss of this protein causes defects in cell division and changes the sensitivity to compounds, affecting cell envelope synthesis and function. We find that DalA forms a complex with proteins needed for cell division, binds the cell envelope polymer peptidoglycan, and colocalizes with enzymes involved in the assembly of this macromolecule. The analysis of DalA provides new information on the cell division machinery in this and possibly other Alphaproteobacteria.

59 BASIC BIOLOGICAL SCIENCES↗

BONCAT-Live for isolation and cultivation of active environmental bacteria

In diverse environments, microbes drive a myriad of processes, from geochemical and nutrient cycling to interspecies interactions, including associations with plants and animals. Their physiological state is dynamic and impacted by abiotic and biotic conditions, responding to environmental fluctuations by changes in cellular metabolism, according to their genetic potential. Molecular, cellular, and genomic approaches can identify and measure microbial responses and adaptation to environmental changes in native communities. However, isolating individual microbial cells that respond to specific changes for cultivation has been difficult. To address this, we implemented a novel bacterial isolation approach (BONCAT-Live) by integrating bio-orthogonal non-canonical amino acid tagging (BONCAT) in diverse native communities, with isolation and cultivation of cells responding to specific stimuli, at different time scales. In frozen Arctic permafrost samples, we identified and isolated dormant bacteria that become active after thawing under native or nutrient-enriched conditions. From the Populus tree rhizosphere, we isolated strains that thrive under high concentrations of root exudates that act as defense compounds and nutrients. In the human microbiome, we identified and isolated bacteria that rapidly proliferated when exposed to metabolites provided by the host or other co-occurring microbes. Further characterization of isolated bacterial strains will provide opportunities for in-depth determination of how these microbes adapt to changes in their environments, individually and as part of model communities.

Analytical Methods↗

Design Considerations for GPU-based Mixed Integer Programming on Parallel Computing Platforms

Mixed Integer Programming (MIP) is a powerful abstraction in combinatorial optimization that finds real-life application across many significant sectors. The recent proliferation of graphical processing unit (GPU)-based accelerated computing architectures in large-scale parallel computing or supercomputing presents new opportunities as well as challenges in the advancement of MIP solver technology to effectively use the new accelerated computing platforms and scale to large parallel systems. Here, we recount the conventional processor-based strategies and focus on configurations where the most promising intersection lies between parallel MIP solver approaches and the specific strengths of accelerated parallel platforms. We note that the best potential lies in solving problems whose individual matrix sizes (of the linear program relaxation) fit entirely within one accelerator's memory and whose branch-and-bound (or branch-and-cut) trees cannot be fully contained within a small number of computational nodes. Additionally, we identify ideal features of computational linear algebra support on GPU accelerators that would help advance this direction of scalable parallel solution of MIP problems on GPU-based accelerated computing architectures.

Perumalla, Kalyan↗

Conflation of Geospatial POI Data and Ground-level Imagery via Link Prediction on Joint Semantic Graph

With the proliferation of smartphone cameras and social networks, we have rich, multi-modal data about points of interest (POIs) - like cultural landmarks, institutions, businesses, etc. - within a given areas of interest (AOI) (e.g., a county, city or a neighborhood) available to us. Data conflation across multiple modalities of data sources is one of the key challenges in maintaining a geographical information system (GIS) which accumulate data about POIs. Given POI data from nine different sources, and ground-level geo-tagged and scene-captioned images from two different image hosting platforms, in this work we explore the application of graph neural networks (GNNs) to perform data conflation, while leveraging a natural graph structure evident in geospatial data. The preliminary results demonstrate the capacity of a GNN operation to learn distributions of entity (POIs and images) features, coupled with topological structure of entity's local neighborhood in a semantic nearest neighbor graph, in order to predict links between a pair of entities.

Gurav, Rutuja↗

Parameter Transfer for Quantum Approximate Optimization of Weighted MaxCut

Finding high-quality parameters is a central obstacle to using the quantum approximate optimization algorithm (QAOA). Previous work partially addresses this issue for QAOA on unweighted MaxCut problems by leveraging similarities in the objective landscape among different problem instances. However, we show that the more general weighted MaxCut problem has significantly modified objective landscapes, with a proliferation of poor local optima. Our main contribution is a simple rescaling scheme that overcomes these deleterious effects of weights. Here we show that for a given QAOA depth, a single “typical” vector of QAOA parameters can be successfully transferred to weighted MaxCut instances. This transfer leads to a median decrease in the approximation ratio of only 2.0 percentage points relative to a considerably more expensive direct optimization on a dataset of 34,701 instances with up to 20 nodes and multiple weight distributions. This decrease can be reduced to 1.2 percentage points at the cost of only 10 additional QAOA circuit evaluations with parameters sampled from a pretrained metadistribution, or the transferred parameters can be used as a starting point for a single local optimization run to obtain approximation ratios equivalent to those achieved by exhaustive optimization in 96.35% of our cases.

97 MATHEMATICS AND COMPUTING↗

Extensions to the SENSEI In situ Framework for Heterogeneous Architectures

The proliferation of GPUs and accelerators in recent supercomputing systems, so called heterogeneous architectures, has led to increased complexity in execution environments and programming models as well as to deeper memory hierarchies on these systems. In this work, we discuss challenges that arise in in situ code coupling on these heterogeneous architectures. In particular, we present data and execution model extensions to the SENSEI in situ framework that are targeted at the effective use of systems with heterogeneous architectures. We then use these new data and execution model extensions to investigate several in situ placement and execution configurations and to analyze the impact these choices have on overall performance.

Loring, Burlen↗

Tournament-Based Pretraining to Accelerate Federated Learning

Advances in hardware, proliferation of compute at the edge, and data creation at unprecedented scales have made federated learning (FL) necessary for the next leap forward in pervasive machine learning. For privacy and network reasons, large volumes of data remain stranded on endpoints located in geographically austere (or at least austere network-wise) locations. However, challenges exist to the effective use of these data. To solve the system and functional level challenges, we present an three novel variants of a serverless federated learning framework. We also present tournament-based pretraining, which we demonstrate significantly improves model performance in some experiments. Overall, these extensions to FL and our novel training method enable greater focus on science rather than ML development.

Baughman, Matt↗

A Digital Twin of Scalable Quantum Clouds

Quantum computing has emerged as a transformative technology capable of solving complex problems beyond the limit of classical systems. The rapid development of quantum processors has led to the proliferation of cloud-based quantum computing services offered by platforms such as IBM, Google, and Amazon. These platforms introduce unique challenges in resource allocation, job scheduling, and multi-device orchestration as quantum workloads become increasingly complex. In this work, we present a digital twin of quantum cloud infrastructures: a framework designed to model and simulate the behavior of real quantum cloud systems. Developed in Python using the SimPy discrete-event simulation library, the framework replicates key aspects of quantum cloud environments, including detailed quantum device modeling, job lifecycle management, and job fidelity. It incorporates noise-aware fidelity estimation, making it the first of its kind to simulate superconducting gate-based quantum cloud systems at an administrative level with job fidelity. We present use cases as proof of concept, demonstrating that our quantum cloud simulation framework can act as a digital twin of a quantum cloud and support the modeling and implementation of practical systems.

Luo, Waylon [Kent State University]↗

Integrated Biophysical Modeling and Image Analysis: Application to Neuro-Oncology

Central nervous system (CNS) tumors come with vastly heterogeneous histologic, molecular, and radiographic landscapes, rendering their precise characterization challenging. The rapidly growing fields of biophysical modeling and radiomics have shown promise in better characterizing the molecular, spatial, and temporal heterogeneity of tumors. Integrative analysis of CNS tumors, including clinically acquired multi-parametric magnetic resonance imaging (mpMRI) and the inverse problem of calibrating biophysical models to mpMRI data, assists in identifying macroscopic quantifiable tumor patterns of invasion and proliferation, potentially leading to improved (a) detection/segmentation of tumor subregions and (b) computer-aided diagnostic/prognostic/predictive modeling. This article presents a summary of (a) biophysical growth modeling and simulation,(b) inverse problems for model calibration, (c) these models' integration with imaging workflows, and (d) their application to clinically relevant studies. We anticipate that such quantitative integrative analysis may even be beneficial in a future revision of the World Health Organization (WHO) classification for CNS tumors, ultimately improving patient survival prospects.

60 APPLIED LIFE SCIENCES↗

Quantum Many-Body Scars: A Quasiparticle Perspective

Weakly interacting quasiparticles play a central role in the low-energy description of many phases of quantum matter. At higher energies, however, quasiparticles cease to be well defined in generic many-body systems owing to a proliferation of decay channels. In this review, we discuss the phenomenon of quantum many-body scars, which can give rise to certain species of stable quasiparticles throughout the energy spectrum. This goes along with a set of unusual nonequilibrium phenomena including many-body revivals and nonthermal stationary states. We provide a pedagogical exposition of this physics via a simple yet comprehensive example, that of a spin-1 XY model. We place our discussion in the broader context of symmetry-based constructions of many-body scar states, projector embeddings, and Hilbert space fragmentation. We conclude with a summary of experimental progress and theoretical puzzles.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The Chalkboard: An Introduction to Electrochemical Separations

Chemical separations are a cornerstone of industrial manufacturing processes that generate products and services that have improved the standard of living for humans across the globe. To give some context as to how ubiquitous separations are in the modern world, they are involved in the production of fuels, medicines, clean water, fertilizers, materials used in semiconductor chip manufacturing, and other goods. A 2019 report by the National Academies of Sciences, Engineering, and Medicine highlights that chemical separations account for about 10 to 15% of energy use in the United States. Of the four broad sectors (residential, transportation, industry, and commerce) that use energy in the United States, industry has the largest use at 32% and about half of the energy use in industry hails from separations. It is likely that the transportation and residential sectors will experience significant decarbonization in the next 25 years with the proliferation of wind and solar energy sources coupled with electrochemical energy storage and electrification of vehicles. Finally, industrial decarbonization, on the other hand, is far more complex and challenging and it is imperative that future engineers and scientists work hard to devise alternative processes that can be powered on renewable electrons while generating little waste to produce the goods and services that make up our modern lives.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Statistical Design of Experiments Enables Rapid Exploration of Perfluorobutane Sulfonate Degradation

The phase-out of long-chain PFAS has led to the proliferation of highly recalcitrant short-chain analogs, and mineralization technologies for these short-chain PFAS are needed to mitigate their deleterious effects on environmental and human health. In this study, we utilize a statistical design of experiments, specifically, response surface methodology, to rapidly evaluate the electrochemical degradation of the short-chain PFAS, perfluorobutane sulfonate (PFBS). We evaluate the impacts of the three primary electrochemical parameters (concentration of PFBS, concentration of supporting electrolyte, and applied current) over multiple orders of magnitude on the three primary reaction outcomes of electrochemical PFBS degradation (incomplete PFBS decomposition, complete PFBS mineralization as fluorine, and anodic energy consumption). Our results correspond with literature and clearly identify the well-known tradeoff between energy consumption and complete mineralization. Intriguingly, partial PFBS decomposition and energy consumption demonstrate nonlinear dependencies in the current/supporting electrolyte concentration space and the current/PFBS concentration space, respectively. These findings highlight the utility of the response surface methodology model to efficiently interrogate a large parameter space, identifying both common results and less-obvious interactions between electrochemical parameters and their influences on reaction outcomes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Resveratrol Ameliorates Lipopolysaccharide-Induced Sudden Sensorineural Hearing Loss in In Vitro Model through Multitarget Antiapoptotic Mechanism Based on Network Pharmacology and Molecular Docking

Objective. To explore the effects of resveratrol (RSV) on hair cell apoptosis caused by sudden sensorineural hearing loss (SSNHL) and its effect on lipopolysaccharide-induced apoptosis of HEI-OC1 cells. Methods. We used the network pharmacology method to screen molecules related to RSV for the treatment of SSNHL and analyzed these molecules and their enriched biological processes and signaling pathways through Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis. We selected hub genes related to apoptosis using protein-protein interaction (PPI) analysis for in vitro and molecular docking verification. Results. Eighty overlapping genes were identified as potential targets for RSV treatment of SSNHL. Further GO analysis showed that the biological processes were mainly related to toxicity, cell proliferation, and lipopolysaccharide reactions. KEGG analysis showed that the AGE-RAGE signaling pathway in diabetic complications, Kaposi’s sarcoma-associated herpesvirus infection, FoxO signaling pathway, PI3K-Akt signaling pathway, and other inflammatory signaling pathways were concentrated. AKT1, STAT3, JUN, TNF, TP53, MAPK3, CASP3, and VEGFA were screened as HUB genes using PPI analysis. The apoptosis-related proteins TNF, CASP3, AKT1, and TP53 were selected for in vitro experiments, which showed that mRNA was significantly different before and after RSV intervention, confirming that the corresponding protein receptors could bind well with RSV. Conclusion. RSV mainly affects the prognosis of SSNHL through anti-inflammatory effects and may improve hair cell apoptosis caused by inflammatory factors through multitargeted interventions involving TNF, CASP3, AKT1, and TP53.

Ye, Shiming↗

TiO 2 Nanocoatings with Controllable Crystal Type and Nanoscale Topography on Zirconia Implants to Accelerate Bone Formation

In dentistry, zirconia implants have emerged as a promising alternative for replacing missing teeth due to their superior aesthetic performance and chemical stability. To improve the osseointegration of zirconia implants, modifying their surface with hierarchical micro/nanotopography and bioactive chemical composition are two effective ways. In this work, a microscale topography was prepared on a zirconia surface using hydrofluoric acid etching, and then a 50 nm TiO 2 nanocoating was deposited via atomic layer deposition (ALD). Subsequently, an annealing treatment was used to transform the TiO 2 from amorphous to anatase and simultaneously generate nanoscale topography. Various investigations into the coating surface morphology, topography, wettability, and chemical composition were carried out using scanning electron microscopy, white light interferometry, contact‐angle measurement, X‐ray diffraction, and X‐ray photoelectron spectroscopy. In addition, in vitro cytocompatibility and osteogenic potential performance of the coatings were evaluated by human bone marrow mesenchymal stem cells (hBMSCs), and in vivo osseointegration performance was assessed in a rat femoral condyle model. Moreover, the possible mechanism was also investigated. The deposition of TiO 2 film with/without annealing treatment did not alter the microscale roughness of the zirconia surface, whereas the nanotopography changed significantly after annealing. The in vitro studies revealed that the anatase TiO 2 coating with regular wavelike nanostructure could promote the adhesion and proliferation of osteoblasts and further improve the osteogenic potential in vitro and osseointegration in vivo. These positive effects may be caused by nanoscale topography via the canonical Wnt/ β ‐catenin pathway. The results suggest that using ALD in combination with annealing treatment to fabricate a nanotopographic TiO 2 coating is a promising way to improve the osteogenic properties of zirconia implants.

Li, Nan (ORCID:0000000255156737)↗

BEEAM (Building Electrical Efficiency Analysis Model) [SWR-20-107]

Modern high-performance buildings exhibit an increasing number of building loads that use direct current (DC) electricity internally, rather than alternating current (AC), due to the advent of low-cost computing and advanced power electronics. Powering DC devices from the AC grid requires AC/DC power conversion, which introduces energy losses and reduces efficiency. As DC loads proliferate, the cumulative wasted energy associated with hundreds of millions of AC/DC converters has become one of the broadest energy savings opportunities in buildings. DC power distribution systems have been proposed as an elegant and transformative solution to the problem of DC devices. In a DC distribution system, the building's wires carry DC electricity, rather than AC; and a few centralized, highly efficient AC/DC converters replace the many smaller, less efficient converters that serve individual DC loads. Unfortunately, the trade-offs associated with DC distribution systems are not well understood. Reported energy savings associated with DC power distribution differ widely and have not been well validated. The Building Electrical Efficiency Analysis Model (BEEAM) is a Modelica library that simulates the efficiency of building electrical distribution systems using harmonic power flow. BEEAM can model a wide variety of building distribution topologies, including three-phase AC, single-phase AC, unipolar DC, bipolar DC, and hybrid networks under both balanced and unbalanced load conditions. BEEAM accurately models power electronic converter losses, provides granular estimates of losses throughout the distribution system, and properly models efficiency at part load conditions. Users can package BEEAM within a functional mockup unit (FMU), enabling co-simulation with other modeling platform, such as EnergyPlus. In summary, BEEAM provides a tool suite for fair and accurate comparison of the efficiency of building electrical distribution systems, including AC, DC, and hybrid systems.

Frank, Stephen↗

GENESPACE R Package (GENESPACE) v1.0

In short, the GENESPACE pipeline conducts analysis of orthology networks, constrained within syntenic regions. Since analyses are limited to local tests conducted within syntenic blocks, GENESPACE is agnostic to ploidy, duplicated regions, inversions or other whole-genome chromosomal complexities that are common across many evolutionary lineages. This advantage allows for evolutionary tests in polyploids (e.g. switchgrass, manuscript in review), species with ancient, but retained whole-genome duplications (e.g. pecan, manuscript in prep), high levels of tandem array proliferation (e.g. eukalypts, manuscript in review) and many other factors that can confound comparative genomic analyses. The major advances of GENESPACE are three-fold: First, this is the first R package to integrate visualization and analysis of large-scale comparative genomics. R, which offers a high-level environment for graphical and statistical exploration of data, is often speed- and memory-limited and not used for computationally intensive tasks such as comparative genomics. The highly efficient C++ scripts used in GENESPACE (via data.table) permit a much faster and computationally lightweight implementation of comparative genomics than is currently available. Second, the pipeline itself is novel. To the best of our knowledge, no other program accomplishes synteny-constrained and ploidy-agnostic comparative genomics. Since nearly all plants and many animals have a history of whole-genome duplications, this is a major and necessary advance to the field. Third, GENESPACE offers high-level and intuitive multi-genome graphical outputs. The dotplots and 'riparian' plots produced herein, which are produced entirely through original R code, are publication-ready and easily customizable.

Schmutz, Jeremy↗