Substrate specificities of recombinant murine Golgi alpha1, 2- mannosidases IA and IB and comparison with endoplasmic reticulum and Golgi processing alpha1,2-mannosidases

The catalytic domains of murine Golgi alpha1,2-mannosidases IA and IB that are involved in N-glycan processing were expressed as secreted proteins in P.pastoris . Recombinant mannosidases IA and IB both required divalent cations for activity, were inhibited by deoxymannojirimycin and kifunensine, and exhibited similar catalytic constants using Manalpha1,2Manalpha-O-CH3as substrate. Mannosidase IA was purified as a 50 kDa catalytically active soluble fragment and shown to be an inverting glycosidase. Recombinant mannosidases IA and IB were used to cleave Man9GlcNAc and the isomers produced were identified by high performance liquid chromatography and proton-nuclear magnetic resonance spectroscopy. Man9GlcNAc was rapidly cleaved by both enzymes to Man6GlcNAc, followed by a much slower conversion to Man5GlcNAc. The same isomers of Man7GlcNAc and Man6GlcNAc were produced by both enzymes but different isomers of Man8GlcNAc were formed. When Man8GlcNAc (Man8B isomer) was used as substrate, rapid conversion to Man5GlcNAc was observed, and the same oligosaccharide isomer intermediates were formed by both enzymes. These results combined with proton-nuclear magnetic resonance spectroscopy data demonstrate that it is the terminal alpha1, 2-mannose residue missing in the Man8B isomer that is cleaved from Man9GlcNAc at a much slower rate. When rat liver endoplasmic reticulum membrane extracts were incubated with Man9GlcNAc2, Man8GlcNAc2was the major product and Man8B was the major isomer. In contrast, rat liver Golgi membranes rapidly cleaved Man9GlcNAc2to Man6GlcNAc2and more slowly to Man5GlcNAc2. In this case all three isomers of Man8GlcNAc2were formed as intermediates, but a distinctive isomer, Man8A, was predominant. Antiserum to recombinant mannosidase IA immunoprecipitated an enzyme from Golgi extracts with the same specificity as recombinant mannosidase IA. These immunodepleted membranes were enriched in a Man9GlcNAc2to Man8GlcNAc2- cleaving activity forming predominantly the Man8B isomer. These results suggest that mannosidases IA and IB in Golgi membranes prefer the Man8B isomer generated by a complementary mannosidase that removes a single mannose from Man9GlcNAc2.      

Sweat gland density and response during high-intensity exercise in athletes with spinal cord injuries

Sweat production is crucial for thermoregulation. However, sweating can be problematic for individuals with spinal cord injuries (SCI), as they display a blunting of sudomotor and vasomotor responses below the level of the injury. Sweat gland density and eccrine gland metabolism in SCI are not well understood. Consequently, this study examined sweat lactate (S-LA) (reflective of sweat gland metabolism), active sweat gland density (SGD), and sweat output per gland (S/G) in 7 SCI athletes and 8 able-bodied (AB) controls matched for arm ergometry VO₂peak. A sweat collection device was positioned on the upper scapular and medial calf of each subject just prior to the beginning of the trial, with iodine sweat gland density patches positioned on the upper scapular and medial calf. Participants were tested on a ramp protocol (7 min per stage, 20 W increase per stage) in a common exercise environment (21±1°C, 45-65% relative humidity). An independent t-test revealed lower (p<0.05) SGD (upper scapular) for SCI (22.3 ±14.8 glands · cm⁻²) vs. AB. (41.0 ± 8.1 glands · cm⁻²). However, there was no significant difference for S/G between groups. S-LA was significantly greater (p<0.05) during the second exercise stage for SCI (11.5±10.9 mmol · l⁻¹) vs. AB (26.8±11.07 mmol · l⁻¹). These findings suggest that SCI athletes had less active sweat glands compared to the AB group, but the sweat response was similar (SLA, S/G) between AB and SCI athletes. The results suggest similar interglandular metabolic activity irrespective of overall sweat rate.     

Molecular and cellular interactions between mother and fetus. Pregnancy as a rejuvenating factor

Aging is associated with a decline of various body functions, including ability to regenerate. Over recent decades, it has been demonstrated that some of these changes could be reversed in response to factors originating from a young organism, for example, fetal stem cells or “young blood” in models of heterochronic parabiosis. Pregnancy might be considered as parabiotic model of the interaction between two organisms of different age. In this work, we analyzed and summarized data on the effects of pregnancy on the maternal organism that confirm the hypothesis that pregnancy rejuvenates the mother’s organism or slows its aging.     

Microbiota and mitobiota. Putting an equal sign between mitochondria and bacteria

The recent revival of old theories and setting them on modern scientific rails to a large extent are also relevant to mitochondrial science. Given the widespread belief that mitochondria are symbionts of ancient bacterial origin, the processes inherent to mitochondrial physiology can be revised based on their comparative analysis with possible involvement of bacteria. Such comparison combined with discussion of the role of microbiota in pathogenesis allows discussion of the role of “mitobiota” (we introduce this term) as the combination of different phenotypic manifestations of mitochondria in the organism reflecting pathological changes in the mitochondrial genome. When putting an equal sign between mitochondria and bacteria, we find similarity between the mitochondrial and bacterial theories of cancer. The presence of the term “bacterial infection” suggests “mitochondrial infection”, and mitochondrial (oxidative) theory of aging can in some way be transformed into a “bacterial theory of aging”. The possible existence of such processes and the data confirming their presence are discussed in this review. If such a comparison has the right to exist, the homeostasis of “mitobiota” is of not lesser physiological importance than homeostasis of microbiota, which has been so intensively discussed recently.     

Functional claudication distance: a reliable and valid measurement to assess functional limitation in patients with intermittent claudication

Background

Pharmacological inhibition of endothelial arginase-II has been shown to improve endothelial nitric oxide synthase (eNOS) function and reduce atherogenesis in animal models. We investigated whether the endothelial arginase II is involved in inflammatory responses in endothelial cells.

Methods

Human endothelial cells were isolated from umbilical veins and stimulated with TNFα (10 ng/ml) for 4 hours. Endothelial expression of the inflammatory molecules i.e. vascular cell adhesion molecule-1 (VCAM-1), intercellular adhesion molecule-1 (ICAM-1), and E-selectin were assessed by immunoblotting.

Results

The induction of the expression of endothelial VCAM-1, ICAM-1 and E-selectin by TNFα was concentration-dependently reduced by incubation of the endothelial cells with the arginase inhibitor L-norvaline. However, inhibition of arginase by another arginase inhibitor S-(2-boronoethyl)-L-cysteine (BEC) had no effects. To confirm the role of arginase-II (the prominent isoform expressed in HUVECs) in the inflammatory responses, adenoviral mediated siRNA silencing of arginase-II knocked down the arginase II protein level, but did not inhibit the up-regulation of the adhesion molecules. Moreover, the inhibitory effect of L-norvaline was not reversed by the NOS inhibitor L-NAME and L-norvaline did not interfere with TNFα-induced activation of NF-κB, JNK, p38mapk, while it inhibited p70s6k (S6K1) activity. Silencing S6K1 prevented up-regulation of E-selectin, but not that of VCAM-1 or ICAM-1 induced by TNFα.

Conclusion

The arginase inhibitor L-norvaline exhibits anti-inflammatory effects independently of inhibition of arginase in human endothelial cells. The anti-inflammatory properties of L-norvaline are partially attributable to its ability to inhibit S6K1.     

Modeling and characterization of multi-charge mass spectra for peptide sequencing

Peptide sequencing using tandem mass spectrometry data is an important and challenging problem in proteomics. We address the problem of peptide sequencing for multi-charge spectra. Most peptide sequencing algorithms currently consider only charge one or two ions even for higher-charge spectra. We give a characterization of multi-charge spectra by generalizing existing models. Using our models, we analyzed spectra from Global Proteome Machine (GPM) [Craig R, Cortens JP, Beavis RC, J Proteome Res 3:1234-1242, 2004.] (with charges 1-5), Institute for Systems Biology (ISB) [Keller A, Purvine S, Nesvizhskii AI, Stolyar S, Goodlett DR, Kolker E, OMICS 6:207-212, 2002.] and Orbitrap (both with charges 1-3). Our analysis for the GPM dataset shows that higher charge peaks contribute significantly to prediction of the complete peptide. They also help to explain why existing algorithms do not perform well on multi-charge spectra. Based on these analyses, we claim that peptide sequencing algorithms can achieve higher sensitivity results if they also consider higher charge ions. We verify this claim by proposing a de novo sequencing algorithm called the greedy best strong tag (GBST) algorithm that is simple but considers higher charge ions based on our new model. Evaluation on multi-charge spectra shows that our simple GBST algorithm outperforms Lutefisk and PepNovo, especially for the GPM spectra of charge three or more.     

The fragile breakage versus random breakage models of chromosome evolution

For many years, studies of chromosome evolution were dominated by the random breakage theory, which implies that there are no rearrangement hot spots in the human genome. In 2003, Pevzner and Tesler argued against the random breakage model and proposed an alternative “fragile breakage” model of chromosome evolution. In 2004, Sankoff and Trinh argued against the fragile breakage model and raised doubts that Pevzner and Tesler provided any evidence of rearrangement hot spots. We investigate whether Sankoff and Trinh indeed revealed a flaw in the arguments of Pevzner and Tesler. We show that Sankoff and Trinh's synteny block identification algorithm makes erroneous identifications even in small toy examples and that their parameters do not reflect the realities of the comparative genomic architecture of human and mouse. We further argue that if Sankoff and Trinh had fixed these problems, their arguments in support of the random breakage model would disappear. Finally, we study the link between rearrangements and regulatory regions and argue that long regulatory regions and inhomogeneity of gene distribution in mammalian genomes may be responsible for the breakpoint reuse phenomenon.     

Network-based Analysis of Genome Wide Association Data Provides Novel Candidate Genes for Lipid and Lipoprotein Traits

Genome wide association studies (GWAS) identify susceptibility loci for complex traits, but do not identify particular genes of interest. Integration of functional and network information may help in overcoming this limitation and identifying new susceptibility loci. Using GWAS and comorbidity data, we present a network-based approach to predict candidate genes for lipid and lipoprotein traits. We apply a prediction pipeline incorporating interactome, co-expression, and comorbidity data to Global Lipids Genetics Consortium (GLGC) GWAS for four traits of interest, identifying phenotypically coherent modules. These modules provide insights regarding gene involvement in complex phenotypes with multiple susceptibility alleles and low effect sizes. To experimentally test our predictions, we selected four candidate genes and genotyped representative SNPs in the Malmö Diet and Cancer Cardiovascular Cohort. We found significant associations with LDL-C and total-cholesterol levels for a synonymous SNP (rs234706) in the cystathionine beta-synthase (CBS) gene (p = 1 × 10⁻⁵ and adjusted-p = 0.013, respectively). Further, liver samples taken from 206 patients revealed that patients with the minor allele of rs234706 had significant dysregulation of CBS (p = 0.04). Despite the known biological role of CBS in lipid metabolism, SNPs within the locus have not yet been identified in GWAS of lipoprotein traits. Thus, the GWAS-based Comorbidity Module (GCM) approach identifies candidate genes missed by GWAS studies, serving as a broadly applicable tool for the investigation of other complex disease phenotypes.Genome wide association studies (GWAS)¹ meta-analyses have pinpointed a number of new gene regions contributing to multifactorial diseases. GWAS typically find limited numbers of loci that contribute modestly to complex phenotypes (1), and GLGC meta-analysis of GWAS data has reached the limit of what can be expected (2) without the use of alternative strategies. Given that susceptibility loci for complex traits are unlikely to be randomly distributed in the genome (3), we might expect that the genes associated with a disease will be more likely to be present within the same pathways or functional groupings. In published cases, pathway based GWAS analysis provides an alternative approach to the dissection of complex disease traits (4, 5). In addition, nominal GWAS p values superimposed upon the human molecular network have been used to identify genes associated with multiple sclerosis (6), and the disease association protein–protein link evaluator (DAPPLE) has been used to find significant interactions among proteins encoded by genes in loci associated with other particular diseases (7). Other approaches incorporate heterogeneous molecular data such as linkage studies, cross species conservation measures, gene expression data and protein–protein interactions to better understand GWAS results (8, 9). Integrating molecular network information, pathway analyses, and GWAS data thus holds promise for identifying new susceptibility loci and improving the identification of relevant candidate genes.If a gene is involved in a specific functional process or disease, its molecular network neighbors might also be suspected to have some role (3). In line with this “local” hypothesis, proteins involved in the same disease show a high propensity to interact (10) or cluster together (11) with each other. Interactions between variations in multiple genes, each with strong or modest effects, perturbing the same pathways or modules, may govern complex traits (3, 6). The molecular triangulation (MT) algorithm can be applied to rank seed genes according to their common disease associated neighbors, assigning closer and more connected neighbors higher values (12). Interactions between modestly associated MT genes may be indicative of coherent disease pathways or of genes conferring susceptibility to disease in a coordinated manner. The jActiveModule method (13) combines seed gene scores with biologically relevant interactions to identify network modules where perturbations causative of disease are more likely to reside. Lastly, although not yet implemented at the module level, phenotypic coherence between interacting pairs of genes has been quantified using the combination of molecular level gene to disease relationships and Medicare comorbidity data (14, 15).We believe that GWAS significant SNPs and variants representing potential candidate genes can use the above strategies to reveal more about the missing heritability of complex phenotypes. The most important risk factors for coronary artery disease (CAD) include serum concentrations of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and triglycerides (TG). We present a GWAS-based meta-analysis Comorbid Module (GCM) approach that uses significant (p < 5 × 10⁻⁸) GWAS signals for these four traits in the context of molecular networks to prioritize modules of disease-associated candidate genes. We evaluate our approach experimentally through allelic association and genotyping within the Malmö Diet and Cancer Cardiovascular Cohort (MDC-CC) for SNPs representing top candidate genes.