Functional Analysis of Host Factors that Mediate the Intracellular Lifestyle of Cryptococcus neoformans

Cryptococcus neoformans (Cn), the major causative agent of human fungal meningoencephalitis, replicates within phagolysosomes of infected host cells. Despite more than a half-century of investigation into host-Cn interactions, host factors that mediate infection by this fungal pathogen remain obscure. Here, we describe the development of a system that employs Drosophila S2 cells and RNA interference (RNAi) to define and characterize Cn host factors. The system recapitulated salient aspects of fungal interactions with mammalian cells, including phagocytosis, intracellular trafficking, replication, cell-to-cell spread and escape of the pathogen from host cells. Fifty-seven evolutionarily conserved host factors were identified using this system, including 29 factors that had not been previously implicated in mediating fungal pathogenesis. Subsequent analysis indicated that Cn exploits host actin cytoskeletal elements, cell surface signaling molecules, and vesicle-mediated transport proteins to establish a replicative niche. Several host molecules known to be associated with autophagy (Atg), including Atg2, Atg5, Atg9 and Pi3K59F (a class III PI3-kinase) were also uncovered in our screen. Small interfering RNA (siRNA) mediated depletion of these autophagy proteins in murine RAW264.7 macrophages demonstrated their requirement during Cn infection, thereby validating findings obtained using the Drosophila S2 cell system. Immunofluorescence confocal microscopy analyses demonstrated that Atg5, LC3, Atg9a were recruited to the vicinity of Cn containing vacuoles (CnCvs) in the early stages of Cn infection. Pharmacological inhibition of autophagy and/or PI3-kinase activity further demonstrated a requirement for autophagy associated host proteins in supporting infection of mammalian cells by Cn. Finally, systematic trafficking studies indicated that CnCVs associated with Atg proteins, including Atg5, Atg9a and LC3, during trafficking to a terminal intracellular compartment that was decorated with the lysosomal markers LAMP-1 and cathepsin D. Our findings validate the utility of the Drosophila S2 cell system as a functional genomic platform for identifying and characterizing host factors that mediate fungal intracellular replication. Our results also support a model in which host Atg proteins mediate Cn intracellular trafficking and replication

Structure-Based Predictive Models for Allosteric Hot Spots

In allostery, a binding event at one site in a protein modulates the behavior of a distant site. Identifying residues that relay the signal between sites remains a challenge. We have developed predictive models using support-vector machines, a widely used machine-learning method. The training data set consisted of residues classified as either hotspots or non-hotspots based on experimental characterization of point mutations from a diverse set of allosteric proteins. Each residue had an associated set of calculated features. Two sets of features were used, one consisting of dynamical, structural, network, and informatic measures, and another of structural measures defined by Daily and Gray [1]. The resulting models performed well on an independent data set consisting of hotspots and non-hotspots from five allosteric proteins. For the independent data set, our top 10 models using Feature Set 1 recalled 68–81% of known hotspots, and among total hotspot predictions, 58–67% were actual hotspots. Hence, these models have precision P = 58–67% and recall R = 68–81%. The corresponding models for Feature Set 2 had P = 55–59% and R = 81–92%. We combined the features from each set that produced models with optimal predictive performance. The top 10 models using this hybrid feature set had R = 73–81% and P = 64–71%, the best overall performance of any of the sets of models. Our methods identified hotspots in structural regions of known allosteric significance. Moreover, our predicted hotspots form a network of contiguous residues in the interior of the structures, in agreement with previous work. In conclusion, we have developed models that discriminate between known allosteric hotspots and non-hotspots with high accuracy and sensitivity. Moreover, the pattern of predicted hotspots corresponds to known functional motifs implicated in allostery, and is consistent with previous work describing sparse networks of allosterically important residues

Snails have stronger indirect positive effects on submerged macrophyte growth attributes than zooplankton

Phytoplankton and epiphyton often compete with submerged macrophytes. Grazing by zooplankton and/or epiphyton grazers should promote an indirect positive effect on submerged macrophyte growth rate. Hence, we mimicked shallow lakes conditions in mesocosms using a factorial design to evaluate the indirect effects of no grazers, zooplankton, snails or both grazers on macrophyte growth attributes. After 16 weeks, both snails and zooplankton had positive effects on macrophyte stem length and biomass. However, only snails had positive effects on macrophyte number of sprouts and root biomass. In addition, the positive effect size of snails on the submerged macrophytes was twice as large as the effect size of the zooplankton. Our study suggests that benthic food chains might be more capable of increasing resilience and affecting the stability of the clear-water state in shallow lakes than pelagic food chains. However, long-term experiments with varying relative proportions of herbivores and different macrophyte species, as well as in situ experiments, will be necessary to test the generality of our findings. Understanding the relative effects of benthic versus pelagic grazers on submerged macrophytes may increase the success of shallow lake restoration and should be taken into account when designing management and restoration efforts for shallow lake systems