PB1-F2 amyloid-like fibers correlate with proinflammatory signaling and respiratory distress in influenza-infected mice

PB1-F2 is a virulence factor of influenza A virus known to increase viral pathogenicity in mammalian hosts. PB1-F2 is an intrinsically disordered protein displaying a propensity to form amyloid-like fibers. However, the correlation between PB1-F2 structures and the resulting inflammatory response is unknown. Here, we used synchrotron-coupled Fourier transform-IR and deep UV microscopies to determine the presence of PB1-F2 fibers in influenza A virus–infected mice. In order to study the correlation between PB1-F2 structure and the inflammatory response, transgenic mice expressing luciferase under the control of an NF-κB promotor, allowing in vivo monitoring of inflammation, were intranasally instilled with monomeric, fibrillated, or truncated forms of recombinant PB1-F2. Our intravital NF-κB imaging, supported by cytokine quantification, clearly shows the proinflammatory effect of PB1-F2 fibers compared with N-terminal region of PB1-F2 unable to fibrillate. It is noteworthy that instillation of monomeric PB1-F2 of H5N1 virus induced a stronger inflammatory response when compared with prefibrillated PB1-F2 of H1N1 virus, suggesting mechanisms of virulence depending on PB1-F2 sequence. Finally, using whole-body plethysmography to measure volume changes in the lungs, we quantified the effects of the different forms of PB1-F2 on respiratory parameters. Thus, we conclude that PB1-F2–induced inflammation and respiratory distress are tightly correlated with sequence polymorphism and oligomerization status of the protein.     

Discovery and mapping of a new expressed sequence tag-single nucleotide polymorphism and simple sequence repeat panel for large-scale genetic studies and breeding of Theobroma cacao L

Theobroma cacao is an economically important tree of several tropical countries. Its genetic improvement is essential to provide protection against major diseases and improve chocolate quality. We discovered and mapped new expressed sequence tag-single nucleotide polymorphism (EST-SNP) and simple sequence repeat (SSR) markers and constructed a high-density genetic map. By screening 149 650 ESTs, 5246 SNPs were detected in silico, of which 1536 corresponded to genes with a putative function, while 851 had a clear polymorphic pattern across a collection of genetic resources. In addition, 409 new SSR markers were detected on the Criollo genome. Lastly, 681 new EST-SNPs and 163 new SSRs were added to the pre-existing 418 co-dominant markers to construct a large consensus genetic map. This high-density map and the set of new genetic markers identified in this study are a milestone in cocoa genomics and for marker-assisted breeding. The data are available at http://tropgenedb.cirad.fr.     

Identification of drugs including a dopamine receptor antagonist that selectively target cancer stem cells

Selective targeting of cancer stem cells (CSCs) offers promise for a new generation of therapeutics. However, assays for both human CSCs and normal stem cells that are amenable to robust biological screens are limited. Using a discovery platform that reveals differences between neoplastic and normal human pluripotent stem cells (hPSC), we identify small molecules from libraries of known compounds that induce differentiation to overcome neoplastic self-renewal. Surprisingly, thioridazine, an antipsychotic drug, selectively targets the neoplastic cells, and impairs human somatic CSCs capable of in vivo leukemic disease initiation while having no effect on normal blood SCs. The drug antagonizes dopamine receptors that are expressed on CSCs and on breast cancer cells as well. These results suggest that dopamine receptors may serve as a biomarker for diverse malignancies, demonstrate the utility of using neoplastic hPSCs for identifying CSC-targeting drugs, and provide support for the use of differentiation as a therapeutic strategy.     

Teaching baroreflex physiology to medical students: a comparison of quiz-based and conventional teaching strategies in a laboratory exercise

Quiz-based and collaborative teaching strategies have previously been found to be efficient for the improving meaningful learning of physiology during lectures. These approaches have, however, not been investigated during laboratory exercises. In the present study, we compared the impact of solving quizzes individually and in groups with conventional teaching on the immediate learning during a laboratory exercise. We implemented two quizzes in a mandatory 4-h laboratory exercise on baroreflex physiology. A total of 155 second-year medical students were randomized to solve quizzes individually (intervention group I, n = 57), in groups of three to four students (intervention group II, n = 56), or not to perform any quizzes (control; intervention group III, n = 42). After the laboratory exercise, all students completed an individual test, which encompassed two recall questions, two intermediate questions, and two integrated questions. The integrated questions were of moderate and advanced difficulty, respectively. Finally, students completed an evaluation form. Intervention group I reached the highest total test scores and proved best at answering the integrated question of advanced difficulty. Moreover, there was an overall difference between groups for student evaluations of the quality of the teaching, which was highest for intervention group II. In conclusion, solving quizzes individually during a laboratory exercise may enhance learning, whereas solving quizzes in groups is associated with higher student satisfaction.     

A systems biology approach to drug targets in Pseudomonas aeruginosa biofilm

Antibiotic resistance is an increasing problem in the health care system and we are in a constant race with evolving bacteria. Biofilm-associated growth is thought to play a key role in bacterial adaptability and antibiotic resistance. We employed a systems biology approach to identify candidate drug targets for biofilm-associated bacteria by imitating specific microenvironments found in microbial communities associated with biofilm formation. A previously reconstructed metabolic model of Pseudomonas aeruginosa (PA) was used to study the effect of gene deletion on bacterial growth in planktonic and biofilm-like environmental conditions. A set of 26 genes essential in both conditions was identified. Moreover, these genes have no homology with any human gene. While none of these genes were essential in only one of the conditions, we found condition-dependent genes, which could be used to slow growth specifically in biofilm-associated PA. Furthermore, we performed a double gene deletion study and obtained 17 combinations consisting of 21 different genes, which were conditionally essential. While most of the difference in double essential gene sets could be explained by different medium composition found in biofilm-like and planktonic conditions, we observed a clear effect of changes in oxygen availability on the growth performance. Eight gene pairs were found to be synthetic lethal in oxygen-limited conditions. These gene sets may serve as novel metabolic drug targets to combat particularly biofilm-associated PA. Taken together, this study demonstrates that metabolic modeling of human pathogens can be used to identify oxygen-sensitive drug targets and thus, that this systems biology approach represents a powerful tool to identify novel candidate antibiotic targets.