The National Institute of Allergy and Infectious Diseases (NIAID) established the Bioinformatics Resource Center (BRC) program to assist researchers with analyzing the growing body of genome sequence and other omics-related data. In this report, we describe the merger of the PAThosystems Resource Integration Center (PATRIC), the Influenza Research Database (IRD) and the Virus Pathogen Database and Analysis Resource (ViPR) BRCs to form the Bacterial and Viral Bioinformatics Resource Center (BV-BRC) https://www.bv-brc.org/. The combined BV-BRC leverages the functionality of the bacterial and viral resources to provide a unified data model, enhanced web-based visualization and analysis tools, bioinformatics services, and a powerful suite of command line tools that benefit the bacterial and viral research communities.

The chronoamperometric response (I vs t) of three metallocene-doped metal–organic frameworks (MOFs) thin films (M-NU-1000, M = Fe, Ru, Os) in two different electrolytes (tetrabutyl­ammonium hexafluoro­phosphate [TBAPF6] and tetrabutylammonium tetrakis­(pentafluorophenyl)­borate [TBATFAB]) was utilized to elucidate the diffusion coefficients of electrons and ions (D e and D i, respectively) through the structure in response to an oxidizing applied bias. The application of a theoretical model for solid state voltammetry to the experimental data revealed that the diffusion of ions is the rate-determining step at the three different time stages of the electrochemical transformation: an initial stage characterized by rapid electron diffusion along the crystal-solution boundary (stage A), a second stage that represents the diffusion of electrons and ions into the bulk of the MOF crystallite (stage B), and a final period of the conversion dominated only by the diffusion of ions (stage C). Remarkably, electron diffusion (D e) increased in the order of Fe < Ru < Os using PF6 1– as the counteranion in all the stages of the voltammogram, demonstrating the strategy to modulate the rate of electron transport through the incorporation of rapidly self-exchanging molecular moieties into the MOF structure. The D e values obtained with larger TFAB1– counteranion were generally in agreement with the previous trend but were on average lower than those obtained with PF6 1–. Similarly, the ion diffusion coefficient (D i) was generally higher for TFAB1– than for PF6 1– as the ions diffuse into the crystal bulk, due to the high degree of ion-pair association between PF6 1– and the metallocenium ion, resulting in a faster penetration of the weakly associated TFAB1– anion through the MOF pores. These structure–function relationships provide a foundation for the future design, control, and optimization of electron and ion transport properties in MOF thin films.

Significance Assessing the threat posed by bacterial samples is fundamentally important to safeguarding human health. Whole-genome sequence analysis of bacteria provides a route to achieving this goal. However, this approach is fundamentally constrained by the scope, the diversity, and our understanding of the bacterial genome sequences that are available for devising threat assessment schemes. For example, genome-based strategies offer limited utility for assessing the threat associated with pathogens that exploit novel virulence mechanisms or are recently emergent. To address these limitations, we developed PathEngine, a machine learning strategy that features the use of phenotypic hallmarks of pathogenesis to assess pathogenic threat. PathEngine successfully classified potential pathogenic threats with high accuracy and thereby establishes a phenotype-based, sequence-independent pipeline for threat assessment.