Rickettsia Phylogenomics: Unwinding the Intricacies of Obligate Intracellular Life

BACKGROUND: Completed genome sequences are rapidly increasing for Rickettsia, obligate intracellular alpha-proteobacteria responsible for various human diseases, including epidemic typhus and Rocky Mountain spotted fever. In light of phylogeny, the establishment of orthologous groups (OGs) of open reading frames (ORFs) will distinguish the core rickettsial genes and other group specific genes (class 1 OGs or C1OGs) from those distributed indiscriminately throughout the rickettsial tree (class 2 OG or C2OGs). METHODOLOGY/PRINCIPAL FINDINGS: We present 1823 representative (no gene duplications) and 259 non-representative (at least one gene duplication) rickettsial OGs. While the highly reductive (approximately 1.2 MB) Rickettsia genomes range in predicted ORFs from 872 to 1512, a core of 752 OGs was identified, depicting the essential Rickettsia genes. Unsurprisingly, this core lacks many metabolic genes, reflecting the dependence on host resources for growth and survival. Additionally, we bolster our recent reclassification of Rickettsia by identifying OGs that define the AG (ancestral group), TG (typhus group), TRG (transitional group), and SFG (spotted fever group) rickettsiae. OGs for insect-associated species, tick-associated species and species that harbor plasmids were also predicted. Through superimposition of all OGs over robust phylogeny estimation, we discern between C1OGs and C2OGs, the latter depicting genes either decaying from the conserved C1OGs or acquired laterally. Finally, scrutiny of non-representative OGs revealed high levels of split genes versus gene duplications, with both phenomena confounding gene orthology assignment. Interestingly, non-representative OGs, as well as OGs comprised of several gene families typically involved in microbial pathogenicity and/or the acquisition of virulence factors, fall predominantly within C2OG distributions. CONCLUSION/SIGNIFICANCE: Collectively, we determined the relative conservation and distribution of 14354 predicted ORFs from 10 rickettsial genomes across robust phylogeny estimation. The data, available at PATRIC (PathoSystems Resource Integration Center), provide novel information for unwinding the intricacies associated with Rickettsia pathogenesis, expanding the range of potential diagnostic, vaccine and therapeutic targets

Technology Assessment: Demand Response Technologies in the Pacific Northwest

The goal of this research is to develop a decision model that can be used to identify the technology transfer potential of a research proposal. An organization can use the model to select the proposals whose research outcomes are more likely to move into application. The model begins to close the chasm between research and application – otherwise known as the “valley of death.” A hierarchical decision model, along with desirability curves, was used to understand the complexities of the researcher and recipient relationship, specific to technology transfer. In this research, the evaluation criteria of several research organizations were assessed to understand the extent to which the success attributes that were identified in literature were considered when reviewing research proposals. The quantified model was validated using a case study involving demand response (DR) technology proposals in the Pacific Northwest

Combination systemic therapies with immune checkpoint inhibitors in pancreatic cancer: overcoming resistance to single-agent checkpoint blockade

Abstract Immune checkpoint inhibitors have demonstrated broad single-agent antitumor activity and a favorable safety profile that render them attractive agents to combine with other systemic anticancer therapies. Pancreatic cancer has been fairly resistant to monotherapy blockade of programmed cell death protein 1 receptor, programmed death ligand 1, and cytotoxic T-lymphocyte associated protein 4. However, there is a growing body of preclinical evidence to support the rational combination of checkpoint inhibitors and various systemic therapies in pancreatic cancer. Furthermore, early clinical evidence has begun to support the feasibility and efficacy of checkpoint inhibitor-based combination therapy in advanced pancreatic cancer. Despite accumulating preclinical and clinical data, there remains several questions as to the optimal dosing and timing of administration of respective agents, toxicity of combination strategies, and mechanisms by which immune resistance to single-agent checkpoint blockade are overcome. Further development of biomarkers is also important in the advancement of combination systemic therapies incorporating checkpoint blockade in pancreatic cancer. Results from an impressive number of ongoing prospective clinical trials are eagerly anticipated and will seek to validate the viability of combination immuno-oncology strategies in pancreatic cancer