Characterization of Staphylococcus aureus biofilms via crystal violet binding and biochemical composition assays of isolates from hospitals, raw meat, and biofilm-associated gene mutants.

Staphylococcus aureus (SA) is a gram-positive coccus and an opportunistic pathogen of humans. The ability of SA to form biofilms is an important virulence mechanism because biofilms are protected from host immune responses and antibiotic treatment. This study examines the relative biofilm strength of a variety of hospital and meat-associated strains of SA, using a crystal violet (CV) staining assay. Biofilms were treated with either DNase or proteinase K prior to CV staining, and compared to mock-treated results, to better understand the biochemical composition. Biofilm polysaccharide concentration was also measured using the phenol sulfuric-acid assay which was normalized to base biofilm strength. We found that hospital-associated isolates have biofilms that bind significantly more CV than for meat isolates and are significantly more protein and polysaccharide-based while meat isolates have significantly more DNA-based biofilms. This study also investigates the effects that biofilm-related genes have on biofilm formation and composition by analyzing specific transposon mutants of genes previously shown to play a role in biofilm development. agrA, atl, clfA, fnbA, purH, and sarA mutants produce significantly weaker biofilms (bind less CV) as compared to a wild-type control, whereas the acnA mutant produces a significantly stronger biofilm. Biofilms formed from these mutant strains were treated (or mock-treated) with DNase or proteinase K and tested with phenol and sulfuric acid to determine what role these genes play in biofilm composition. The acnA, clfA, fnbA, and purH mutants showed significant reduction in biofilm staining after either proteinase K or DNase treatment, agrA and sarA mutants showed significant biofilm reduction after only proteinase K treatment, and an atl mutant did not show significant biofilm reduction after either proteinase K or DNase treatment. These data suggest that biofilms that form without acnA, clfA, fnbA, and purH are DNA- and protein-based, that biofilms lacking agrA and sarA are mainly protein-based, and biofilms lacking atl are mainly polysaccharide-based. These results help to elucidate how these genes affect biofilm formation and demonstrate how mutating biofilm-related genes in SA can cause a change in biofilm composition.

Sensory environment affects Icelandic threespine stickleback's anti-predator escape behaviour.

Human-induced changes in climate and habitats push populations to adapt to novel environments, including new sensory conditions, such as reduced visibility. We studied how colonizing newly formed glacial lakes with turbidity-induced low-visibility affects anti-predator behaviour in Icelandic threespine sticklebacks. We tested nearly 400 fish from 15 populations and four habitat types varying in visibility and colonization history in their reaction to two predator cues (mechano-visual versus olfactory) in high versus low-visibility light treatments. Fish reacted differently to the cues and were affected by lighting environment, confirming that cue modality and light levels are important for predator detection and evasion. Fish from spring-fed lakes, especially from the highlands (likely more diverged from marine fish than lowland fish), reacted fastest to mechano-visual cues and were generally most active. Highland glacial fish showed strong responses to olfactory cues and, counter to predictions from the flexible stem hypothesis, the greatest plasticity in response to light levels. This study, leveraging natural, repeated invasions of novel sensory habitats, (i) illustrates rapid changes in anti-predator behaviour that follow due to adaptation, early life experience, or both, and (ii) suggests an additional role for behavioural plasticity enabling population persistence in the face of frequent changes in environmental conditions.

Application of information theory to a three-body coarse-grained representation of proteins in the PDB: insights into the structural and evolutionary roles of residues in protein structure.

Knowledge-based methods for analyzing protein structures, such as statistical potentials, primarily consider the distances between pairs of bodies (atoms or groups of atoms). Considerations of several bodies simultaneously are generally used to characterize bonded structural elements or those in close contact with each other, but historically do not consider atoms that are not in direct contact with each other. In this report, we introduce an information-theoretic method for detecting and quantifying distance-dependent through-space multibody relationships between the sidechains of three residues. The technique introduced is capable of producing convergent and consistent results when applied to a sufficiently large database of randomly chosen, experimentally solved protein structures. The results of our study can be shown to reproduce established physico-chemical properties of residues as well as more recently discovered properties and interactions. These results offer insight into the numerous roles that residues play in protein structure, as well as relationships between residue function, protein structure, and evolution. The techniques and insights presented in this work should be useful in the future development of novel knowledge-based tools for the evaluation of protein structure.

Are distance-dependent statistical potentials considering three interacting bodies superior to two-body statistical potentials for protein structure prediction?

Distance-based statistical potentials have long been used to model condensed matter systems, e.g. as scoring functions in differentiating native-like protein structures from decoys. These scoring functions are based on the assumption that the total free energy of the protein can be calculated as the sum of pairwise free energy contributions derived from a statistical analysis of pair-distribution functions. However, this fundamental assumption has been challenged theoretically. In fact the free energy of a system with N particles is only exactly related to the N-body distribution function. Based on this argument coarse-grained multi-body statistical potentials have been developed to capture higher-order interactions. Having a coarse representation of the protein and using geometric contacts instead of pairwise interaction distances renders these models insufficient in modeling details of multi-body effects. In this study, we investigated if extending distance-dependent pairwise atomistic statistical potentials to corresponding interaction functions that are conditional on a third interacting body, defined as quasi-three-body statistical potentials, could model details of three-body interactions. We also tested if this approach could improve the predictive capabilities of statistical scoring functions for protein structure prediction. We analyzed the statistical dependency between two simultaneous pairwise interactions and showed that there is surprisingly little if any dependency of a third interacting site on pairwise atomistic statistical potentials. Also the protein structure prediction performance of these quasi-three-body potentials is comparable with their corresponding two-body counterparts. The scoring functions developed in this study showed better or comparable performances compared to some widely used scoring functions for protein structure prediction.

Thoracic splenosis more than 40 years after thoracoabdominal trauma.

Splenosis is a rare occurrence that is defined as autotransplantation of splenic tissue usually after splenic rupture due to trauma and subsequent splenectomy. Although splenosis most commonly occurs in the abdomen, the authors report a rare case of thoracic splenosis after remote thoracoabdominal trauma. A 62-year-old woman was found to have lower-lobe, pleural-based nodular lesions in juxtaposition to the posteromedial segment of the lung during workup for an abdominal hernia. Surgical excision of the mass confirmed the diagnosis of ectopic splenic tissue, and splenosis was diagnosed. This woman was among the rare 18% of people who are found to have splenosis in the intrathoracic space. In the workup of pulmonary nodules in patients with a history of trauma, splenosis should be a consideration.

Solvent interaction energy calculations on molecular dynamics trajectories: increasing the efficiency using systematic frame selection.

End-point methods such as linear interaction energy (LIE) analysis, molecular mechanics generalized Born solvent-accessible surface (MM/GBSA), and solvent interaction energy (SIE) analysis have become popular techniques to calculate the free energy associated with protein-ligand binding. Such methods typically use molecular dynamics (MD) simulations to generate an ensemble of protein structures that encompasses the bound and unbound states. The energy evaluation method (LIE, MM/GBSA, or SIE) is subsequently used to calculate the energy of each member of the ensemble, thus providing an estimate of the average free energy difference between the bound and unbound states. The workflow requiring both MD simulation and energy calculation for each frame and each trajectory proves to be computationally expensive. In an attempt to reduce the high computational cost associated with end-point methods, we study several methods by which frames may be intelligently selected from the MD simulation including clustering and address the question of how the number of selected frames influences the accuracy of the SIE calculations.