The most common Chinese rhesus macaque MHC class I molecule shares peptide binding repertoire with the HLA-B7 supertype

Of the two rhesus macaque subspecies used for AIDS studies, the Simian immunodeficiency virus-infected Indian rhesus macaque (Macaca mulatta) is the most established model of HIV infection, providing both insight into pathogenesis and a system for testing novel vaccines. Despite the Chinese rhesus macaque potentially being a more relevant model for AIDS outcomes than the Indian rhesus macaque, the Chinese-origin rhesus macaques have not been well-characterized for their major histocompatibility complex (MHC) composition and function, reducing their greater utilization. In this study, we characterized a total of 50 unique Chinese rhesus macaques from several varying origins for their entire MHC class I allele composition and identified a total of 58 unique complete MHC class I sequences. Only nine of the sequences had been associated with Indian rhesus macaques, and 28/58 (48.3%) of the sequences identified were novel. From all MHC alleles detected, we prioritized Mamu-A1*02201 for functional characterization based on its higher frequency of expression. Upon the development of MHC/peptide binding assays and definition of its associated motif, we revealed that this allele shares peptide binding characteristics with the HLA-B7 supertype, the most frequent supertype in human populations. These studies provide the first functional characterization of an MHC class I molecule in the context of Chinese rhesus macaques and the first instance of HLA-B7 analogy for rhesus macaques.     

Detailed characterization of the peptide binding specificity of five common Patr class I MHC molecules

The chimpanzee (Pan troglodytes) is an important model for studying the immune response to several human pathogens, but the study of correlates of immunity has been hindered by the fact that little is known about the epitope-binding specificity of chimpanzee (Patr) class I MHC. In the present study we have characterized the peptide binding specificity of several common Patr class I molecules. Using single amino acid substitution analogs and large peptide libraries, quantitative peptide binding motifs have been derived for Patr A*0101, A*0701, A*0901, B*0101, and B*2401. Each molecule was found to bind peptides using position 2 and the C terminus as main anchor contacts. On the other hand, each Patr molecule is associated with a unique binding specificity, and the range of specificities is similar to that seen amongst HLA alleles. A high degree of cross-reactivity was noted between Patr A*0701 and Patr A*0901, suggesting the existence of a Patr-specific supertype. Consistent with previous studies suggesting that some cross-reactivity may exist between HLA and Patr alleles, Patr A*0901 was found to have an appreciable degree of cross-reactivity with molecules of the HLA A24-supertype. Finally, utilizing motif scans and peptide binding and intracellular cytokine staining assays, 77 hepatitis B virus (HBV)-derived epitopes were identified in five chimpanzees that were recently convalescent from acute HBV infection. Because the Patr alleles studied herein were found to be very common in two different chimpanzee populations, the present data should facilitate the use of chimpanzees for immunological studies.Electronic Supplementary Material Supplementary material is available for this article at and is accessible for authorized users.     

Connectivity independent protein-structure alignment: a hierarchical approach

Background  

Protein-structure alignment is a fundamental tool to study protein function, evolution and model building. In the last decade several methods for structure alignment were introduced, but most of them ignore that structurally similar proteins can share the same spatial arrangement of secondary structure elements (SSE) but differ in the underlying polypeptide chain connectivity (non-sequential SSE connectivity).     

Effects of 17beta-estradiol and flutamide on splenic macrophages and splenocytes after trauma-hemorrhage

Since splenic immune functions are depressed in metestrus females following trauma-hemorrhage, we hypothesized that administration of the androgen receptor antagonist flutamide at the onset of resuscitation will maintain the immune function of the spleen following trauma-hemorrhage. Female C57BL6/J mice (metestrus state, 8-12 weeks old), underwent laparotomy and hemorrhagic shock (35.0+/-5.0 mm Hg for 90 min) and received 17beta-estradiol (50 microg/25 g), flutamide (625 microg/25 g) or 17beta-estradiol+flutamide. Four hours after resuscitation, the in vitro productive capacity of different cytokines (TNF-alpha, IL-6, IL-10, and IFN-gamma) by splenic MPhi and splenocytes were determined by flow cytometry. A significantly decreased cytokine production by both splenocytes and splenic MPhi was observed following trauma-hemorrhage compared to shams. Administration of 17beta-estradiol, flutamide and 17beta-estradiol+flutamide following trauma-hemorrhage resulted in a significant increase in the in vitro IL-6 release by splenic MPhi. The TNF-alpha productive capacity, however, was only restored by 17beta-estradiol and 17beta-estradiol+flutamide administration following trauma-hemorrhage. No significant effect of either treatment was observed with regard to the suppressed splenic MPhi IL-10 release. Anti-CD3 stimulation, administration of 17beta-estradiol and 17beta-estradiol+flutamide, but not the administration of flutamide alone resulted in a significant increased release of TNF-alpha, IL-6 and IFN-gamma compared to vehicle-treated animals. No significant effect of either treatment was found on IL-10 productive capacity. These results collectively suggest that flutamide administration following trauma-hemorrhage in females has beneficial effects on splenic immune function. However, flutamide administration in combination with estrogen does not provide any significant, additional effects over 17beta-estradiol administration alone.     

Enhancing vacuolar sucrose cleavage within the developing potato tuber has only minor effects on metabolism

Modification of tuber carbohydrate metabolism by the tuber-specific expression of a yeast invertase targeted to the cytosol or apoplast has previously been demonstrated to have diverse effects on tuber growth and metabolism. In the current study, we generated plants exhibiting tuber-specific expression of the same enzyme targeted to the vacuole. Enzymatic analysis of the carbohydrate levels of the tuber revealed dramatic decreases in sucrose content coupled with large increases in the levels of glucose and hexose phosphates, but unaltered starch content in the transformants. Analysis of the key enzyme of glycolysis suggests that this pathway is down-regulated in the transformants. Despite these changes in metabolite pools and enzyme activity, few consistent changes could be observed in the estimated metabolic fluxes following incubation of isolated tuber discs in labelled glucose. The analysis of the relative levels of a wide range of metabolites using a gas chromatography-mass spectrometry (GC-MS)-based metabolite profiling method revealed large changes in the levels of fructose and decreases in a range of other sugars, but very few changes in the contents of organic and amino acids. This metabolic profile is remarkably consistent with that obtained following expression of the invertase in the apoplastic compartment, providing circumstantial evidence for the endocytotic trafficking of sugars within potato tuber parenchyma. Finally, the results of this study are compared with those from other plant species and the relative roles of the vacuolar isoform of the enzyme are contrasted.     

Specialized Yeast Ribosomes: A Customized Tool for Selective mRNA Translation

Evidence is now accumulating that sub-populations of ribosomes - so-called specialized ribosomes - can favour the translation of subsets of mRNAs. Here we use a large collection of diploid yeast strains, each deficient in one or other copy of the set of ribosomal protein (RP) genes, to generate eukaryotic cells carrying distinct populations of altered ‘specialized’ ribosomes. We show by comparative protein synthesis assays that different heterologous mRNA reporters based on luciferase are preferentially translated by distinct populations of specialized ribosomes. These mRNAs include reporters carrying premature termination codons (PTC) thus allowing us to identify specialized ribosomes that alter the efficiency of translation termination leading to enhanced synthesis of the wild-type protein. This finding suggests that these strains can be used to identify novel therapeutic targets in the ribosome. To explore this further we examined the translation of the mRNA encoding the extracellular matrix protein laminin β3 (LAMB3) since a LAMB3-PTC mutant is implicated in the blistering skin disease Epidermolysis bullosa (EB). This screen identified specialized ribosomes with reduced levels of RP L35B as showing enhanced synthesis of full-length LAMB3 in cells expressing the LAMB3-PTC mutant. Importantly, the RP L35B sub-population of specialized ribosomes leave both translation of a reporter luciferase carrying a different PTC and bulk mRNA translation largely unaltered.     

Unbiased and Mobile Gait Analysis Detects Motor Impairment in Parkinson's Disease

Motor impairments are the prerequisite for the diagnosis in Parkinson''s disease (PD). The cardinal symptoms (bradykinesia, rigor, tremor, and postural instability) are used for disease staging and assessment of progression. They serve as primary outcome measures for clinical studies aiming at symptomatic and disease modifying interventions. One major caveat of clinical scores such as the Unified Parkinson Disease Rating Scale (UPDRS) or Hoehn&Yahr (H&Y) staging is its rater and time-of-assessment dependency. Thus, we aimed to objectively and automatically classify specific stages and motor signs in PD using a mobile, biosensor based Embedded Gait Analysis using Intelligent Technology (eGaIT). eGaIT consist of accelerometers and gyroscopes attached to shoes that record motion signals during standardized gait and leg function. From sensor signals 694 features were calculated and pattern recognition algorithms were applied to classify PD, H&Y stages, and motor signs correlating to the UPDRS-III motor score in a training cohort of 50 PD patients and 42 age matched controls. Classification results were confirmed in a second independent validation cohort (42 patients, 39 controls). eGaIT was able to successfully distinguish PD patients from controls with an overall classification rate of 81%. Classification accuracy increased with higher levels of motor impairment (91% for more severely affected patients) or more advanced stages of PD (91% for H&Y III patients compared to controls), supporting the PD-specific type of analysis by eGaIT. In addition, eGaIT was able to classify different H&Y stages, or different levels of motor impairment (UPDRS-III). In conclusion, eGaIT as an unbiased, mobile, and automated assessment tool is able to identify PD patients and characterize their motor impairment. It may serve as a complementary mean for the daily clinical workup and support therapeutic decisions throughout the course of the disease.     

Hierarchical,Multi-Sensor Based Classification of Daily Life Activities: Comparison with State-of-the-Art Algorithms Using a Benchmark Dataset

Insufficient physical activity is the 4th leading risk factor for mortality. Methods for assessing the individual daily life activity (DLA) are of major interest in order to monitor the current health status and to provide feedback about the individual quality of life. The conventional assessment of DLAs with self-reports induces problems like reliability, validity, and sensitivity. The assessment of DLAs with small and light-weight wearable sensors (e.g. inertial measurement units) provides a reliable and objective method. State-of-the-art human physical activity classification systems differ in e.g. the number and kind of sensors, the performed activities, and the sampling rate. Hence, it is difficult to compare newly proposed classification algorithms to existing approaches in literature and no commonly used dataset exists. We generated a publicly available benchmark dataset for the classification of DLAs. Inertial data were recorded with four sensor nodes, each consisting of a triaxial accelerometer and a triaxial gyroscope, placed on wrist, hip, chest, and ankle. Further, we developed a novel, hierarchical, multi-sensor based classification system for the distinction of a large set of DLAs. Our hierarchical classification system reached an overall mean classification rate of 89.6% and was diligently compared to existing state-of-the-art algorithms using our benchmark dataset. For future research, the dataset can be used in the evaluation process of new classification algorithms and could speed up the process of getting the best performing and most appropriate DLA classification system.