313 research outputs found
Low-Temperature Polymorphic Phase Transition in a Crystalline Tripeptide L-Ala-L-Pro-Gly·H2O Revealed by Adiabatic Calorimetry
We demonstrate application of precise adiabatic vacuum calorimetry to observation of phase transition in the tripeptide l-alanyl-l-prolyl-glycine monohydrate (APG) from 6 to 320 K and report the standard thermodynamic properties of the tripeptide in the entire range. Thus, the heat capacity of APG was measured by adiabatic vacuum calorimetry in the above temperature range. The tripeptide exhibits a reversible first-order solid-to-solid phase transition characterized by strong thermal hysteresis. We report the standard thermodynamic characteristics of this transition and show that differential scanning calorimetry can reliably characterize the observed phase transition with <5 mg of the sample. Additionally, the standard entropy of formation from the elemental substances and the standard entropy of hypothetical reaction of synthesis from the amino acids at 298.15 K were calculated for the studied tripeptide.National Institute of Biomedical Imaging and Bioengineering (U.S.) (EB-003151)National Institute of Biomedical Imaging and Bioengineering (U.S.) (EB-001960)National Institute of Biomedical Imaging and Bioengineering (U.S.) (EB-002026
Zinc on the edge—isotopic and geophysical evidence that cratonic edges control world-class shale-hosted zinc-lead deposits
The North Australian Zinc Belt is the largest zinc-lead province in the world, containing three of the ten largest known individual deposits (HYC, Hilton-George Fisher, and Mount Isa). The Northern Cordillera in North America is the second largest zinc-lead province, containing a further two of the world’s top ten deposits (Red Dog and Howards Pass). Despite this world-class endowment, exploration in both mineral provinces during the past 2 decades has not been particularly successful, yielding only two significant discoveries (Teena, Australia, and Boundary, Canada). One of the most important aspects of exploration is to choose mineral provinces and districts within geological belts that have the greatest potential for discovery. Here, we present results from these two zinc belts that highlight previously unused datasets for area selection and targeting. Lead isotope mapping using analyses of mineralized material has identified gradients in μ (238U/204Pb) that coincide closely with many major deposits. Locations of these deposits also coincide with a gradient in the depth of the lithosphere-asthenosphere boundary determined from calibrated surface wave tomography models converted to temperature. Furthermore, gradients in upward-continued gravity anomalies and a step in Moho depth correspond to a pre-existing major crustal boundary in both zinc belts. A spatial association of deposits with a linear mid- to lower-crustal resistivity anomaly from magnetotelluric data is also observed in the North Australian Zinc Belt. The change from thicker to thinner lithosphere is interpreted to localize prospective basins for zinc-lead mineralization and to control the gradient in lead isotope and geophysical data. These data, when combined with data indicative of paleoenvironment and changes in plate motion at the time of mineralization, provide new exploration criteria that can be used to identify prospective mineralized basins and define the most favorable parts of these basins
Contrasting patterns of evolutionary constraint and novelty revealed by comparative sperm proteomic analysis in Lepidoptera
Background: Rapid evolution is a hallmark of reproductive genetic systems and arises through the combined processes of sequence divergence, gene gain and loss, and changes in gene and protein expression. While studies aiming to disentangle the molecular ramifications of these processes are progressing, we still know little about the genetic basis of evolutionary transitions in reproductive systems. Here we conduct the first comparative analysis of sperm proteomes in Lepidoptera, a group that exhibits dichotomous spermatogenesis, in which males produce a functional fertilization-competent sperm (eupyrene) and an incompetent sperm morph lacking nuclear DNA (apyrene). Through the integrated application of evolutionary proteomics and genomics, we characterize the genomic patterns potentially associated with the origination and evolution of this unique spermatogenic process and assess the importance of genetic novelty in Lepidopteran sperm biology.
Results: Comparison of the newly characterized Monarch butterfly (Danaus plexippus) sperm proteome to those of the Carolina sphinx moth (Manduca sexta) and the fruit fly (Drosophila melanogaster) demonstrated conservation at the level of protein abundance and post-translational modification within Lepidoptera. In contrast, comparative genomic analyses across insects reveals significant divergence at two levels that differentiate the genetic architecture of sperm in Lepidoptera from other insects. First, a significant reduction in orthology among Monarch sperm genes relative to the remainder of the genome in non-Lepidopteran insect species was observed. Second, a substantial number of sperm proteins were found to be specific to Lepidoptera, in that they lack detectable homology to the genomes of more distantly related insects. Lastly, the functional importance of Lepidoptera specific sperm proteins is broadly supported by their increased abundance relative to proteins conserved across insects.
Conclusions: Our results identify a burst of genetic novelty amongst sperm proteins that may be associated with the origin of heteromorphic spermatogenesis in ancestral Lepidoptera and/or the subsequent evolution of this system. This pattern of genomic diversification is distinct from the remainder of the genome and thus suggests that this transition has had a marked impact on lepidopteran genome evolution. The identification of abundant sperm proteins unique to Lepidoptera, including proteins distinct between specific lineages, will accelerate future functional studies aiming to understand the developmental origin of dichotomous spermatogenesis and the functional diversification of the fertilization incompetent apyrene sperm morph
MDA5 and TLR3 Initiate Pro-Inflammatory Signaling Pathways Leading to Rhinovirus-Induced Airways Inflammation and Hyperresponsiveness
Rhinovirus (RV), a single-stranded RNA picornavirus, is the most frequent cause of asthma exacerbations. We previously demonstrated in human bronchial epithelial cells that melanoma differentiation-associated gene (MDA)-5 and the adaptor protein for Toll-like receptor (TLR)-3 are each required for maximal RV1B-induced interferon (IFN) responses. However, in vivo, the overall airway response to viral infection likely represents a coordinated response integrating both antiviral and pro-inflammatory pathways. We examined the airway responses of MDA5- and TLR3-deficient mice to infection with RV1B, a minor group virus which replicates in mouse lungs. MDA5 null mice showed a delayed type I IFN and attenuated type III IFN response to RV1B infection, leading to a transient increase in viral titer. TLR3 null mice showed normal IFN responses and unchanged viral titers. Further, RV-infected MDA5 and TLR3 null mice showed reduced lung inflammatory responses and reduced airways responsiveness. Finally, RV-infected MDA5 null mice with allergic airways disease showed lower viral titers despite deficient IFN responses, and allergic MDA5 and TLR3 null mice each showed decreased RV-induced airway inflammatory and contractile responses. These results suggest that, in the context of RV infection, binding of viral dsRNA to MDA5 and TLR3 initiates pro-inflammatory signaling pathways leading to airways inflammation and hyperresponsiveness
Systems Integration of Biodefense Omics Data for Analysis of Pathogen-Host Interactions and Identification of Potential Targets
The NIAID (National Institute for Allergy and Infectious Diseases) Biodefense Proteomics program aims to identify targets for potential vaccines, therapeutics, and diagnostics for agents of concern in bioterrorism, including bacterial, parasitic, and viral pathogens. The program includes seven Proteomics Research Centers, generating diverse types of pathogen-host data, including mass spectrometry, microarray transcriptional profiles, protein interactions, protein structures and biological reagents. The Biodefense Resource Center (www.proteomicsresource.org) has developed a bioinformatics framework, employing a protein-centric approach to integrate and support mining and analysis of the large and heterogeneous data. Underlying this approach is a data warehouse with comprehensive protein + gene identifier and name mappings and annotations extracted from over 100 molecular databases. Value-added annotations are provided for key proteins from experimental findings using controlled vocabulary. The availability of pathogen and host omics data in an integrated framework allows global analysis of the data and comparisons across different experiments and organisms, as illustrated in several case studies presented here. (1) The identification of a hypothetical protein with differential gene and protein expressions in two host systems (mouse macrophage and human HeLa cells) infected by different bacterial (Bacillus anthracis and Salmonella typhimurium) and viral (orthopox) pathogens suggesting that this protein can be prioritized for additional analysis and functional characterization. (2) The analysis of a vaccinia-human protein interaction network supplemented with protein accumulation levels led to the identification of human Keratin, type II cytoskeletal 4 protein as a potential therapeutic target. (3) Comparison of complete genomes from pathogenic variants coupled with experimental information on complete proteomes allowed the identification and prioritization of ten potential diagnostic targets from Bacillus anthracis. The integrative analysis across data sets from multiple centers can reveal potential functional significance and hidden relationships between pathogen and host proteins, thereby providing a systems approach to basic understanding of pathogenicity and target identification
Postoperative serum proteomic profiles may predict recurrence-free survival in high-risk primary breast cancer
Item does not contain fulltextPURPOSE: Better breast cancer prognostication may improve selection of patients for adjuvant therapy. We conducted a retrospective longitudinal study in which we investigated sera of high-risk primary breast cancer patients, to search for proteins predictive of recurrence-free survival. METHODS: Sera of 82 breast cancer patients obtained after surgery, but prior to the administration of adjuvant therapy, were fractionated using anion-exchange chromatography, to facilitate the detection of the low-abundant serum peptides. Selected fractions were subsequently analysed by surface-enhanced laser desorption/ionisation time-of-flight mass spectrometry (SELDI-TOF MS), and the resulting protein profiles were searched for prognostic markers by appropriate bioinformatics tools. RESULTS: Four peak clusters (i.e. m/z 3073, m/z 3274, m/z 4405 and m/z 7973) were found to bear significant prognostic value (P </= 0.01). The m/z 3274 candidate marker was structurally identified as inter-alpha-trypsin inhibitor heavy chain 4 fragment(658-688) in serum. Except for the m/z 7973 peak cluster, these peaks remained independently associated with recurrence-free survival upon multivariate Cox regression analysis, including clinical parameters of known prognostic value in this study population. CONCLUSION: Investigation of the postoperative serum proteome by, e.g., anion-exchange fractionation followed by SELDI-TOF MS analysis is promising for the detection of novel prognostic factors. However, regarding the rather limited study population, validation of these results by analysis of independent study populations is warranted to assess the true clinical applicability of discovered prognostic markers. In addition, structural identification of the other markers will aid in elucidation of their role in breast cancer prognosis, as well as enable development of absolute quantitative assays
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