Receptor Sorting within Endosomal Trafficking Pathway Is Facilitated by Dynamic Actin Filaments

Early endosomes (EEs) are known to be a sorting station for internalized molecules destined for degradation, recycling, or other intracellular organelles. Segregation is an essential step in such sorting, but the molecular mechanism of this process remains to be elucidated. Here, we show that actin is required for efficient recycling and endosomal maturation by producing a motile force. Perturbation of actin dynamics by drugs induced a few enlarged EEs containing several degradative vacuoles and also interfered with their transporting ability. Actin repolymerization induced by washout of the drug caused the vacuoles to dissociate and individually translocate toward the perinuclear region. We further elucidated that cortactin, an actin-nucleating factor, was required for transporting contents from within EEs. Actin filaments regulated by cortactin may provide a motile force for efficient sorting within early endosomes. These data suggest that actin filaments coordinate with microtubules to mediate segregation in EEs

Carbene footprinting accurately maps binding sites in protein–ligand and protein–protein interactions

Specific interactions between proteins and their binding partners are fundamental to life processes. The ability to detect protein complexes, and map their sites of binding, is crucial to understanding basic biology at the molecular level. Methods that employ sensitive analytical techniques such as mass spectrometry have the potential to provide valuable insights with very little material and on short time scales. Here we present a differential protein footprinting technique employing an efficient photo-activated probe for use with mass spectrometry. Using this methodology the location of a carbohydrate substrate was accurately mapped to the binding cleft of lysozyme, and in a more complex example, the interactions between a 100 kDa, multi-domain deubiquitinating enzyme, USP5 and a diubiquitin substrate were located to different functional domains. The much improved properties of this probe make carbene footprinting a viable method for rapid and accurate identification of protein binding sites utilizing benign, near-UV photoactivation

Genus Paracoccidioides: Species Recognition and Biogeographic Aspects

Background: Paracoccidioidomycosis is a systemic mycosis caused by Paracoccidioides brasiliensis (species S1, PS2, PS3), and Paracoccidioides lutzii. This work aimed to differentiate species within the genus Paracoccidioides, without applying multilocus sequencing, as well as to obtain knowledge of the possible speciation processes. Methodology/Principal Findings: Single nucleotide polymorphism analysis on GP43, ARF and PRP8 intein genes successfully distinguished isolates into four different species. Morphological evaluation indicated that elongated conidia were observed exclusively in P. lutzii isolates, while all other species (S1, PS2 and PS3) were indistinguishable. To evaluate the biogeographic events that led to the current geographic distribution of Paracoccidioides species and their sister species, Nested Clade and Likelihood Analysis of Geographic Range Evolution (LAGRANGE) analyses were applied. The radiation of Paracoccidioides started in northwest South America, around 11–32 million years ago, as calculated on the basis of ARF substitution rate, in the BEAST program. Vicariance was responsible for the divergence among S1, PS2 and P. lutzii and a recent dispersal generated the PS3 species, restricted to Colombia. Taking into account the ancestral areas revealed by the LAGRANGE analysis and the major geographic distribution of L. loboi in the Amazon basin, a region strongly affected by the Andes uplift and marine incursions in the Cenozoic era, we also speculate about the effect of these geological events on the vicariance between Paracoccidioides and L. loboi. Conclusions/Significance: The use of at least 3 SNPs, but not morphological criteria, as markers allows us to distinguish among the four cryptic species of the genus Paracoccidioides. The work also presents a biogeographic study speculating on how these species might have diverged in South America, thus contributing to elucidating evolutionary aspects of the genus Paracoccidioides

Set Pseudophasors to Stun for Flow Cytometry

Study of signal transduction in live cells benefits from the ability to visualize and quantify light emitted by fluorescent proteins (XFPs) fused to different signaling proteins. However, because cell signaling proteins are often present in small numbers, and because the XFPs themselves are poor fluorophores, the amount of emitted light, and the observable signal in these studies, is often small. An XFP's fluorescence lifetime contains additional information about the immediate environment of the fluorophore that can augment the information from its weak light signal. Here, we constructed and expressed in Saccharomyces cerevisiae variants of Teal Fluorescent Protein (TFP) and Citrine that were isospectral but had shorter fluorescence lifetimes, ∼ 1.5 ns vs ∼ 3 ns. We modified microscopic and flow cytometric instruments to measure fluorescence lifetimes in live cells. We developed digital hardware and a measure of lifetime called a "pseudophasor" that we could compute quickly enough to permit sorting by lifetime in flow. We used these abilities to sort mixtures of cells expressing TFP and the short-lifetime TFP variant into subpopulations that were respectively 97% and 94% pure. This work demonstrates the feasibility of using information about fluorescence lifetime to help quantify cell signaling in living cells at the high throughput provided by flow cytometry. Moreover, it demonstrates the feasibility of isolating and recovering subpopulations of cells with different XFP lifetimes for subsequent experimentation

Learning a Prior on Regulatory Potential from eQTL Data

Genome-wide RNA expression data provide a detailed view of an organism's biological state; hence, a dataset measuring expression variation between genetically diverse individuals (eQTL data) may provide important insights into the genetics of complex traits. However, with data from a relatively small number of individuals, it is difficult to distinguish true causal polymorphisms from the large number of possibilities. The problem is particularly challenging in populations with significant linkage disequilibrium, where traits are often linked to large chromosomal regions containing many genes. Here, we present a novel method, Lirnet, that automatically learns a regulatory potential for each sequence polymorphism, estimating how likely it is to have a significant effect on gene expression. This regulatory potential is defined in terms of “regulatory features”—including the function of the gene and the conservation, type, and position of genetic polymorphisms—that are available for any organism. The extent to which the different features influence the regulatory potential is learned automatically, making Lirnet readily applicable to different datasets, organisms, and feature sets. We apply Lirnet both to the human HapMap eQTL dataset and to a yeast eQTL dataset and provide statistical and biological results demonstrating that Lirnet produces significantly better regulatory programs than other recent approaches. We demonstrate in the yeast data that Lirnet can correctly suggest a specific causal sequence variation within a large, linked chromosomal region. In one example, Lirnet uncovered a novel, experimentally validated connection between Puf3—a sequence-specific RNA binding protein—and P-bodies—cytoplasmic structures that regulate translation and RNA stability—as well as the particular causative polymorphism, a SNP in Mkt1, that induces the variation in the pathway

Modeling Iridium-Based Trilayer and Bilayer Transition-Edge Sensors

We report a model that can be used to calculate superconducting transition temperature of a transition-edge sensor (TES), which is either a normal metal-superconductor-normal metal trilayer or a normal metal-superconductor bilayer. The model allows the T-{C} estimation of a trilayer when the normal metals at the bottom and at the top are different. Furthermore, the model includes the spin flip time of the normal metals. We use the T-{C} calculations from this model for selected Ir-based trilayers and bilayers to help understand potential designs of low T-{C} TESs. A Au/Ir/Au trilayer can have a low T-{C} because the superconducting order parameter is reduced with normal metals at both sides. On the other hand, an Ir/Pt bilayer can have a low T-{C} because the much larger electron density of states of Pt reduces the superconducting order parameter more effectively. Moreover, the spin flip scattering of paramagnetic Pt also contributes to the T-{C} reduction

Modeling Iridium-Based Trilayer and Bilayer Transition-Edge Sensors

We report a model that can be used to calculate superconducting transition temperature of a transition-edge sensor (TES), which is either a normal metal-superconductor-normal metal trilayer or a normal metal-superconductor bilayer. The model allows the T-{C} estimation of a trilayer when the normal metals at the bottom and at the top are different. Furthermore, the model includes the spin flip time of the normal metals. We use the T-{C} calculations from this model for selected Ir-based trilayers and bilayers to help understand potential designs of low T-{C} TESs. A Au/Ir/Au trilayer can have a low T-{C} because the superconducting order parameter is reduced with normal metals at both sides. On the other hand, an Ir/Pt bilayer can have a low T-{C} because the much larger electron density of states of Pt reduces the superconducting order parameter more effectively. Moreover, the spin flip scattering of paramagnetic Pt also contributes to the T-{C} reduction