Bruno Walther Santos Sobral

The Colorado Immersion Training in Community Engagement (CIT) program supports a change in the research trajectory of junior faculty, early career researchers, and doctoral students toward Community-Based Participatory Research (CBPR). CIT is within the Community Engagement and Health Equity Core (CEHE) at the Colorado Clinical and Translational Sciences Institute (CCTSI), an NIH-funded Clinical and Translational Science award. This Translational Science Case Study reports on CIT’s impacts from 2010 to 2019. A team from The Evaluation Center at the University of Colorado Denver utilized four primary data sources: administrative records, participant written reflections, participant and Community Research Liaison (CRL) interviews, and community partner surveys. Data were analyzed using the framework of CBPR principles and the conceptual logic model. CIT trained 122 researchers in CBPR through embedded education within various Colorado communities. CIT Alumni secured ∼$8,723,000 in funding between CCTSI Pilot Grants and external funding. Also, CIT alumni implemented CBPR into curricula and community programming and developed deep, lasting relationships. Further key learnings include the crucial role of CRLs in building relationships between university and community partners and how CIT may serve as a mechanism to improve historical mistrust between communities and universities.

Clearance and perturbation of Amazonian forests are one of the greatest threats to tropical biodiversity conservation of our times. A better understanding of how soil communities respond to Amazonian deforestation is crucially needed to inform policy interventions that effectively protect biodiversity and the essential ecosystem services it provides. We assessed the impact of deforestation and ecosystem conversion to arable land on Amazonian soil biodiversity through a meta‐analysis. We analyzed 274 pairwise comparisons of soil biodiversity in Amazonian primary forests and sites under different stages of deforestation and land‐use conversion: disturbed (wildfire and selective logging) and slash‐and‐burnt forests, pastures, and cropping systems. Overall, 60% and 51% of responses of soil macrofauna and microbial community attributes (i.e., abundance, biomass, richness, and diversity indexes) to deforestation were negative, respectively. We found few studies on mesofauna (e.g., microarthropods) and microfauna (e.g., protozoa and nematodes), so those groups could not be analyzed. Macrofauna abundance and biomass were more vulnerable to the displacement of forests by pastures than by agricultural fields, whereas microbes showed the opposite pattern. Effects of Amazonian deforestation on macrofauna were more detrimental at sites with mean annual precipitation >1900 mm, and higher losses of microbes occurred in highly acidic soils (pH < 4.5). Limited geographic coverage, omission of meso‐ and microfauna, and low taxonomic resolution were main factors impairing generalizations from the data set. Few studies assessed the impacts of within‐forest disturbance (wildfires and selective logging) on soil species in Amazonia, where logging operations rapidly expand across public lands and more frequent severe dry seasons are increasing the prevalence of wildfires.

The migration properties of circular, covalently closed (ccc) and linear DNAs were studied in pulsed-field gel electrophoresis as a model system for resolving large plasmids in the Rhizobiaceae. The effects of varying pulse time and agarose concentration on the electrophoretic mobility cccDNAs, ranging from 2 kilobase pairs (kb) to 16 kb, was investigated. We used both field inversion gel electrophoresis (FIGE) and electrophoresis in contour-clamped homogeneous electric fields (CHEF); both ccc and linear molecules had a minimum mobility as a function of pulse time in a CHEF apparatus. Linear and cccDNAs of the same size were affected differently by pulse time. The electrophoretic mobility of cccDNAs was pulse-time dependent in both electrophoretic systems;We used pulsed-field gel electrophoresis (PFG) and statistical analysis of Rhizobiaceae DNA sequences from GENBANK to identify rare-cutting restriction endonucleases. By using FIGE and CHEF, the genome sizes of Rhizobium meliloti and Bradyrhizobium japonicum were calculated. Comparisons were made between the genomes of free-living and bacteroid forms. The stability of genomic fingerprints produced by rare-cutting enzymes was studied on B. japonicum DNA plugs. It seems likely that large-scale DNA rearrangements do not occur during B. japonicum bacteroid development, after dedifferentiation, or by maintenance on rich media;FIGE and digestion with rare-cutting restriction enzymes were used to compare the genomes of B. japonicum field isolates from the 123 serocluster, as well as serotype strains USDA 123, USDA 127, and USDA 129. Genomic fingerprints (or field inversion gel electrophoretic types (FIGETs)), produced by four restriction enzymes, showed a high degree of diversity in the sizes of restriction fragments. Isolates could be classified according to FIGETs, and this classification was correlated with a serological classification. Hybridization with a nifHD gene probe to FIGE gels of B. japonicum DNA revealed that restriction fragment length polymorphisms (RFLPs) existed within members of serocluster 123 and provided further evidence of the relatedness between members of serogroups 123 and 127.

Motivation: RNA-Seq is a method for profiling transcription using high-throughput sequencing and is an important component of many research projects that wish to study transcript isoforms, condition specific expression and transcriptional structure. The methods, tools and technologies used to perform RNA-Seq analysis continue to change, creating a bioinformatics challenge for researchers who wish to exploit these data. Resources that bring together genomic data, analysis tools, educational material and computational infrastructure can minimize the overhead required of life science researchers. Results: RNA-Rocket is a free service that provides access to RNA-Seq and ChIP-Seq analysis tools for studying infectious diseases. The site makes available thousands of pre-indexed genomes, their annotations and the ability to stream results to the bioinformatics resources VectorBase, EuPathDB and PATRIC. The site also provides a combination of experimental data and metadata, examples of pre-computed analysis, step-by-step guides and a user interface designed to enable both novice and experienced users of RNA-Seq data. Availability and implementation: RNA-Rocket is available at rnaseq.pathogenportal.org. Source code for this project can be found at github.com/cidvbi/PathogenPortal. Contact:anwarren@vt.edu Supplementary information: Supplementary materials are available at Bioinformatics online.

Motivation: We’ve developed a highly curated bacterial virulence factor (VF) library in PATRIC (Pathosystems Resource Integration Center, www.patricbrc.org ) to support infectious disease research. Although several VF databases are available, there is still a need to incorporate new knowledge found in published experimental evidence and integrate these data with other information known for these specific VF genes, including genomic and other omics data. This integration supports the identification of VFs, comparative studies and hypothesis generation, which facilitates the understanding of virulence and pathogenicity. Results: We have manually curated VFs from six prioritized NIAID (National Institute of Allergy and Infectious Diseases) category A–C bacterial pathogen genera, Mycobacterium , Salmonella , Escherichia , Shigella , Listeria and Bartonella , using published literature. This curated information on virulence has been integrated with data from genomic functional annotations, trancriptomic experiments, protein–protein interactions and disease information already present in PATRIC. Such integration gives researchers access to a broad array of information about these individual genes, and also to a suite of tools to perform comparative genomic and transcriptomics analysis that are available at PATRIC. Availability and implementation: All tools and data are freely available at PATRIC ( http://patricbrc.org ). Contact:cmao@vbi.vt.edu . Supplementary information: Supplementary data are available at Bioinformatics online.