Reshaping Echinocandin Antifungal Drugs to Circumvent Glucan Synthase Point Mutation-Mediated Resistance

Echinocandins are important antifungal drugs that inhibit the activity of the membrane-bound glucan synthase complex, which is responsible for the synthesis of the fungal cell wall β-(1,3)-glucan. Echinocandin resistance, linked to mutations in Fks, the catalytic subunit of the glucan synthase complex, is on the rise, particularly in Candida species, the most common human fungal pathogens. In this study, we used molecular docking experiments between echinocandins and the recently reported structure of Fks to propose a model in which these drugs form a ternary complex with the enzyme and membrane lipids. We then used site-selective reductive dehydration of alcohols to generate dehydroxylated echinocandin derivatives, which we evaluated against a panel of Candida strains constructed by introducing resistance-conferring mutations. We found that removing the hemiaminal alcohol that drives alterations in the three-dimensional structures of the echinocandin reduced their efficacy. Conversely, eliminating the benzylic alcohol of echinocandins enhanced their efficacy by up to two orders of magnitude, depending on the resistance-conferring mutation. Our findings provide valuable insights into how site-selective modifications of echinocandins can be used to combat resistance to these clinically important antifungal drugs

Enzymatic Activity Profiling Using an Ultra-Sensitive Array of Chemiluminescent Probes for Bacterial Classification and Characterization

Bacterial species identification and characterization in clinical and industrial settings necessitate the use of diverse, labor-intensive, and time-consuming protocols, as well as the utilization of expensive and high-maintenance equipment. Furthermore, while cutting-edge identification technologies such as mass spectrometry and PCR are highly effective in identifying bacterial pathogens, they fall short in providing crucial information for identifying bacteria that are not present in the databases on which these methods rely. In response to these challenges, we present a robust and general approach to bacterial identification based on their unique enzymatic activity profiles. This method delivers results within 90 minutes, utilizing an array of highly sensitive and enzyme-selective chemiluminescent probes. Leveraging our recently developed technology of chemiluminescent luminophores, which emit light under physiological conditions, we have crafted an array of probes designed to rapidly detect various bacterial hydrolytic enzymatic activities, including some associated with antibiotic resistance. The analysis of chemiluminescent fingerprints from a diverse panel of prominent bacterial pathogens has revealed distinct enzymatic activity profiles for each strain. The reported universally applicable identification procedure offers a highly sensitive and expeditious means to delineate bacterial enzymatic activity profiles. This breakthrough opens new avenues for characterizing and identifying pathogens in research, clinical, and industrial applications

Discrimination theory of rule-governed behavior

In rule-governed behavior, previously established elementary discriminations are combined in complex instructions and thus result in complex behavior. Discriminative combining and recombining of responses produce behavior with characteristics differing from those of behavior that is established through the effects of its direct consequences. For example, responding in instructed discrimination may be occasioned by discriminative stimuli that are temporally and situationally removed from the circumstances under which the discrimination is instructed. The present account illustrates properties of rule-governed behavior with examples from research in instructional control and imitation learning. Units of instructed behavior, circumstances controlling compliance with instructions, and rule-governed problem solving are considered

Designing and implementing sample and data collection for an international genetics study: The Type 1 Diabetes Genetics Consortium (T1DGC)

Background and Purpose The Type 1 Diabetes Genetics Consortium (T1DGC) is an international project whose primary aims are to: (a) discover genes that modify type 1 diabetes risk; and (b) expand upon the existing genetic resources for type 1 diabetes research. The initial goal was to collect 2500 affected sibling pair (ASP) families worldwide. Methods T1DGC was organized into four regional networks (Asia-Pacific, Europe, North America, and the United Kingdom) and a Coordinating Center. A Steering Committee, with representatives from each network, the Coordinating Center, and the funding organizations, was responsible for T1DGC operations. The Coordinating Center, with regional network representatives, developed study documents and data systems. Each network established laboratories for: DNA extraction and cell line production; human leukocyte antigen genotyping; and autoantibody measurement. Samples were tracked from the point of collection, processed at network laboratories and stored for deposit at National Institute for Diabetes and Digestive and Kidney Diseases (NIDDK) Central Repositories. Phenotypic data were collected and entered into the study database maintained by the Coordinating Center. Results T1DGC achieved its original ASP recruitment goal. In response to research design changes, the T1DGC infrastructure also recruited trios, cases, and controls. Results of genetic analyses have identified many novel regions that affect susceptibility to type 1 diabetes. T1DGC created a resource of data and samples that is accessible to the research community. Limitations Participation in T1DGC was declined by some countries due to study requirements for the processing of samples at network laboratories and/or final deposition of samples in NIDDK Central Repositories. Re-contact of participants was not included in informed consent templates, preventing collection of additional samples for functional studies. Conclusions T1DGC implemented a distributed, regional network structure to reach ASP recruitment targets. The infrastructure proved robust and flexible enough to accommodate additional recruitment. T1DGC has established significant resources that provide a basis for future discovery in the study of type 1 diabetes genetics. © The Author(s) 2010