Refined structure of c-phycocyanin from the cyanobacterium Synechococcus vulcanus at 1.6 A: insights into the role of solvent molecules in thermal stability and co-factor structure

The crystal structure of the light-harvesting phycobiliprotein, c-phycocyanin from the thermophilic cyanobacterium Synechococcus vulcanus has been refined to 1.6 A resolution based on the previously determined lower resolution structure (PDB entry 1I7Y). The improved data was collected using synchrotron radiation at 100 K. The significantly improved crystallographic data has lead to improved calculated electron density maps, allowing the unambiguous positioning of all protein and co-factor atoms and the positioning of 377 solvent molecules. The positions of solvent molecules at specific sites important for stabilization of different levels of self-assembly of the phycobilisome structure were identified and the bonding network is described. The presence of solvent molecules in the vicinity of the co-factors and in intermolecular spaces is identified and their possible roles are suggested. All three of the phycocyanobilin co-factors bind water molecules at specific sites between the propionic acid side chains. Molecular dynamic (MD) simulations support that these special waters have a role in stabilization of this conformation. On the basis of the crystal packing reported here and in comparison to other phycobiliprotein crystal forms, we have analyzed the roles of specific sites on the formation of the phycobilisome complex.     

Deregulation of oncogene‐induced senescence and p53 translational control in X‐linked dyskeratosis congenita

Defects in ribosome biogenesis and function are present in a growing list of human syndromes associated with cancer susceptibility. One example is X‐linked dyskeratosis congenita (X‐DC) in which the DKC1 gene, encoding for an enzyme that modifies ribosomal RNA, is found to be mutated. How ribosome dysfunction leads to cancer remains poorly understood. A critical cellular response that counteracts cellular transformation is oncogene‐induced senescence (OIS). Here, we show that during OIS, a switch between cap‐ and internal ribosome entry site (IRES)‐dependent translation occurs. During this switch, an IRES element positioned in the 5′untranslated region of p53 is engaged and facilitates p53 translation. We further show that in DKC1^m cells, p53 IRES‐dependent translation is impaired during OIS ex vivo and on DNA damage in vivo. This defect in p53 translation perturbs the cellular response that counteracts oncogenic insult. We extend these findings to X‐DC human patient cells in which similar impairments in p53 IRES‐dependent translation are observed. Importantly, re‐introduction of wild‐type DKC1 restores p53 expression in these cells. These results provide insight into the basis for cancer susceptibility in human syndromes associated with ribosome dysfunction.     

A Self-Directed Method for Cell-Type Identification and Separation of Gene Expression Microarrays

Gene expression analysis is generally performed on heterogeneous tissue samples consisting of multiple cell types. Current methods developed to separate heterogeneous gene expression rely on prior knowledge of the cell-type composition and/or signatures - these are not available in most public datasets. We present a novel method to identify the cell-type composition, signatures and proportions per sample without need for a-priori information. The method was successfully tested on controlled and semi-controlled datasets and performed as accurately as current methods that do require additional information. As such, this method enables the analysis of cell-type specific gene expression using existing large pools of publically available microarray datasets.     

In Vivo 7T MRI of the Non-Human Primate Brainstem

Structural brain imaging provides a critical framework for performing stereotactic and intraoperative MRI-guided surgical procedures, with procedural efficacy often dependent upon visualization of the target with which to operate. Here, we describe tools for in vivo, subject-specific visualization and demarcation of regions within the brainstem. High-field 7T susceptibility-weighted imaging and diffusion-weighted imaging of the brain were collected using a customized head coil from eight rhesus macaques. Fiber tracts including the superior cerebellar peduncle, medial lemniscus, and lateral lemniscus were identified using high-resolution probabilistic diffusion tractography, which resulted in three-dimensional fiber tract reconstructions that were comparable to those extracted from sequential application of a two-dimensional nonlinear brain atlas warping algorithm. In the susceptibility-weighted imaging, white matter tracts within the brainstem were also identified as hypointense regions, and the degree of hypointensity was age-dependent. This combination of imaging modalities also enabled identifying the location and extent of several brainstem nuclei, including the periaqueductal gray, pedunculopontine nucleus, and inferior colliculus. These clinically-relevant high-field imaging approaches have potential to enable more accurate and comprehensive subject-specific visualization of the brainstem and to ultimately improve patient-specific neurosurgical targeting procedures, including deep brain stimulation lead implantation.     

High-Throughput Single-Cell Labeling (Hi-SCL) for RNA-Seq Using Drop-Based Microfluidics

The importance of single-cell level data is increasingly appreciated, and significant advances in this direction have been made in recent years. Common to these technologies is the need to physically segregate individual cells into containers, such as wells or chambers of a micro-fluidics chip. High-throughput Single-Cell Labeling (Hi-SCL) in drops is a novel method that uses drop-based libraries of oligonucleotide barcodes to index individual cells in a population. The use of drops as containers, and a microfluidics platform to manipulate them en-masse, yields a highly scalable methodological framework. Once tagged, labeled molecules from different cells may be mixed without losing the cell-of-origin information. Here we demonstrate an application of the method for generating RNA-sequencing data for multiple individual cells within a population. Barcoded oligonucleotides are used to prime cDNA synthesis within drops. Barcoded cDNAs are then combined and subjected to second generation sequencing. The data are deconvoluted based on the barcodes, yielding single-cell mRNA expression data. In a proof-of-concept set of experiments we show that this method yields data comparable to other existing methods, but with unique potential for assaying very large numbers of cells.     

Combined Treatments Reduce Chilling Injury and Maintain Fruit Quality in Avocado Fruit during Cold Quarantine

Quarantine treatment enables export of avocado fruit (Persea americana) to parts of the world that enforce quarantine against fruit fly. The recommended cold-based quarantine treatment (storage at 1.1°C for 14 days) was studied with two commercial avocado cultivars ‘Hass’ and ‘Ettinger’ for 2 years. Chilling injuries (CIs) are prevalent in the avocado fruit after cold-quarantine treatment. Hence, we examined the effect of integrating several treatments: modified atmosphere (MA; fruit covered with perforated polyethylene bags), methyl jasmonate (MJ; fruit dipped in 2.5 μM MJ for Hass or 10 μM MJ for Ettinger for 30 s), 1-methylcyclopropene (1-MCP; fruit treated with 300 ppb 1-MCP for 18 h) and low-temperature conditioning (LTC; a gradual decrease in temperature over 3 days) on CI reduction during cold quarantine. Avocado fruit stored at 1°C suffered from severe CI, lipid peroxidation, and increased expression of chilling-responsive genes of fruit peel. The combined therapeutic treatments alleviated CI in cold-quarantined fruit to the level in fruit stored at commercial temperature (5°C). A successful therapeutic treatment was developed to protect ‘Hass’ and ‘Ettinger’ avocado fruit during cold quarantine against fruit fly, while maintaining fruit quality. Subsequently, treated fruit stored at 1°C had a longer shelf life and less decay than the fruit stored at 5°C. This therapeutic treatment could potentially enable the export of avocado fruit to all quarantine-enforcing countries. Similar methods might be applicable to other types of fruit that require cold quarantine.     

Structural basis for selective targeting of leishmanial ribosomes: aminoglycoside derivatives as promising therapeutics

Leishmaniasis comprises an array of diseases caused by pathogenic species of Leishmania, resulting in a spectrum of mild to life-threatening pathologies. Currently available therapies for leishmaniasis include a limited selection of drugs. This coupled with the rather fast emergence of parasite resistance, presents a dire public health concern. Paromomycin (PAR), a broad-spectrum aminoglycoside antibiotic, has been shown in recent years to be highly efficient in treating visceral leishmaniasis (VL)—the life-threatening form of the disease. While much focus has been given to exploration of PAR activities in bacteria, its mechanism of action in Leishmania has received relatively little scrutiny and has yet to be fully deciphered. In the present study we present an X-ray structure of PAR bound to rRNA model mimicking its leishmanial binding target, the ribosomal A-site. We also evaluate PAR inhibitory actions on leishmanial growth and ribosome function, as well as effects on auditory sensory cells, by comparing several structurally related natural and synthetic aminoglycoside derivatives. The results provide insights into the structural elements important for aminoglycoside inhibitory activities and selectivity for leishmanial cytosolic ribosomes, highlighting a novel synthetic derivative, compound 3, as a prospective therapeutic candidate for the treatment of VL.     

Collective Learning and Optimal Consensus Decisions in Social Animal Groups

Learning has been studied extensively in the context of isolated individuals. However, many organisms are social and consequently make decisions both individually and as part of a collective. Reaching consensus necessarily means that a single option is chosen by the group, even when there are dissenting opinions. This decision-making process decouples the otherwise direct relationship between animals'' preferences and their experiences (the outcomes of decisions). Instead, because an individual''s learned preferences influence what others experience, and therefore learn about, collective decisions couple the learning processes between social organisms. This introduces a new, and previously unexplored, dynamical relationship between preference, action, experience and learning. Here we model collective learning within animal groups that make consensus decisions. We reveal how learning as part of a collective results in behavior that is fundamentally different from that learned in isolation, allowing grouping organisms to spontaneously (and indirectly) detect correlations between group members'' observations of environmental cues, adjust strategy as a function of changing group size (even if that group size is not known to the individual), and achieve a decision accuracy that is very close to that which is provably optimal, regardless of environmental contingencies. Because these properties make minimal cognitive demands on individuals, collective learning, and the capabilities it affords, may be widespread among group-living organisms. Our work emphasizes the importance and need for theoretical and experimental work that considers the mechanism and consequences of learning in a social context.     

Predicting Odor Perceptual Similarity from Odor Structure

To understand the brain mechanisms of olfaction we must understand the rules that govern the link between odorant structure and odorant perception. Natural odors are in fact mixtures made of many molecules, and there is currently no method to look at the molecular structure of such odorant-mixtures and predict their smell. In three separate experiments, we asked 139 subjects to rate the pairwise perceptual similarity of 64 odorant-mixtures ranging in size from 4 to 43 mono-molecular components. We then tested alternative models to link odorant-mixture structure to odorant-mixture perceptual similarity. Whereas a model that considered each mono-molecular component of a mixture separately provided a poor prediction of mixture similarity, a model that represented the mixture as a single structural vector provided consistent correlations between predicted and actual perceptual similarity (r≥0.49, p<0.001). An optimized version of this model yielded a correlation of r = 0.85 (p<0.001) between predicted and actual mixture similarity. In other words, we developed an algorithm that can look at the molecular structure of two novel odorant-mixtures, and predict their ensuing perceptual similarity. That this goal was attained using a model that considers the mixtures as a single vector is consistent with a synthetic rather than analytical brain processing mechanism in olfaction.