The effects of image reconstruction algorithms on topographic characteristics,diagnostic performance and clinical correlation of metabolic brain networks in Parkinson’s disease

PurposeThe purpose of this study was to evaluate the effects of different image reconstruction algorithms on topographic characteristics and diagnostic performance of the Parkinson’s disease related pattern (PDRP).MethodsFDG-PET brain scans of 20 Parkinson’s disease (PD) patients and 20 normal controls (NC) were reconstructed with six different algorithms in order to derive six versions of PDRP. Additional scans of 20 PD, 25 atypical parkinsonism (AP) patients and 20 NC subjects were used for validation. PDRP versions were compared by assessing differences in topographies, individual subject scores and correlations with patient’s clinical ratings. Discrimination of PD from NC and AP subjects was evaluated across cohorts.ResultsThe region weights of the six PDRPs highly correlated (R ≥ 0.991; p < 0.0001). All PDRPs’ expressions were significantly elevated in PD relative to NC and AP subjects (p < 0.0001) and correlated with clinical ratings (R ≥ 0.47; p < 0.05). Subject scores of the six PDRPs highly correlated within each of individual healthy and parkinsonian groups (R ≥ 0.972, p < 0.0001) and were consistent across the algorithms when using the same reconstruction methods in PDRP derivation and validation. However, when derivation and validation reconstruction algorithms differed, subject scores were notably lower compared to the reference PDRP, in all subject groups.ConclusionPDRP proves to be highly reproducible across FDG-PET image reconstruction algorithms in topography, ability to differentiate PD from NC and AP subjects and clinical correlation. When calculating PDRP scores in scans that have different reconstruction algorithms and imaging systems from those used for PDRP derivation, a calibration with NC subjects is advisable.     

Monitoring the early aggregatory behaviour and size of Aβ1-42 in the absence & presence of metal ions using dynamic light scattering

Background and aimAβ₁₋₄₂ is an amyloidogenic peptide found within senile plaques extracted from those who died with a diagnosis of Alzheimer’s disease. The potent neurotoxicity of this peptide is related to its propensity to form aggregated conformations in vivo, a process that is influenced by the species and concentration of metal ions present within the local environment. This study examines the impact of different metals upon the early aggregatory behaviour and size of Aβ₁₋₄₂ under simulated physiological conditions.MethodsThe size and aggregatory behaviour of Aβ₁₋₄₂ in the presence and absence of metal ions was monitored during the initial 30 min of fibril formation in real-time using dynamic light scattering.ResultsIntensity scattering measurements showed a clear tendency towards aggregation with regards to Aβ₁₋₄₂ only solutions (10 μM). Both equimolar Al³⁺ & Cu²⁺ lowered and stabilised the dimensions of Aβ₁₋₄₂ aggregates; however, a diminutive but significant increase in size was still observed over a 30-min period. While excess Al³⁺ continued to supress the size of Aβ_1−42, a 10-fold increase in the concentration of Cu²⁺ accelerated peptide aggregation relative to that observed for equimolar metal but not compared to Aβ₁₋₄₂ alone.ConclusionThese results infer that Al³⁺ ions stabilise and aid in the maintenance of smaller, toxic intermediates while excess Cu²⁺ facilitates the formation of larger, more inert, amorphous species exceeding 1 μm in size. Furthermore, we propose that metal-induced toxicity of Aβ₁₋₄₂ is reflective of their ability to preserve smaller oligomeric species in vitro.     

Identification of Novel Kinases of Tau Using Fluorescence Complementation Mass Spectrometry (FCMS)

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A New Monoclonal Antibody Enables BAR Analysis of Subcellular Importin β1 Interactomes

Importin β1 (KPNB1) is a nucleocytoplasmic transport factor with critical roles in both cytoplasmic and nucleocytoplasmic transport, hence there is keen interest in the characterization of its subcellular interactomes. We found limited efficiency of BioID in the detection of importin complex cargos and therefore generated a highly specific and sensitive anti-KPNB1 monoclonal antibody to enable biotinylation by antibody recognition analysis of importin β1 interactomes. The monoclonal antibody recognizes an epitope comprising residues 301-320 of human KPBN1 and strikingly is highly specific for cytoplasmic KPNB1 in diverse applications, with little reaction with KPNB1 in the nucleus. Biotinylation by antibody recognition with this novel antibody revealed numerous new interactors of importin β1, expanding the KPNB1 interactome to cytoplasmic and signaling complexes that highlight potential new functions for the importins complex beyond nucleocytoplasmic transport. Data are available via ProteomeXchange with identifier PXD032728.     

Deciphering Spatial Protein–Protein Interactions in Brain Using Proximity Labeling

Cellular biomolecular complexes including protein–protein, protein–RNA, and protein–DNA interactions regulate and execute most biological functions. In particular in brain, protein–protein interactions (PPIs) mediate or regulate virtually all nerve cell functions, such as neurotransmission, cell–cell communication, neurogenesis, synaptogenesis, and synaptic plasticity. Perturbations of PPIs in specific subsets of neurons and glia are thought to underly a majority of neurobiological disorders. Therefore, understanding biological functions at a cellular level requires a reasonably complete catalog of all physical interactions between proteins. An enzyme-catalyzed method to biotinylate proximal interacting proteins within 10 to 300 nm of each other is being increasingly used to characterize the spatiotemporal features of complex PPIs in brain. Thus, proximity labeling has emerged recently as a powerful tool to identify proteomes in distinct cell types in brain as well as proteomes and PPIs in structures difficult to isolate, such as the synaptic cleft, axonal projections, or astrocyte–neuron junctions. In this review, we summarize recent advances in proximity labeling methods and their application to neurobiology.     

Measurement of oxidatively induced DNA damage and its repair,by mass spectrometric techniques

Abstract

Oxidatively induced damage caused by free radicals and other DNA-damaging agents generate a plethora of products in the DNA of living organisms. There is mounting evidence for the involvement of this type of damage in the etiology of numerous diseases including carcinogenesis. For a thorough understanding of the mechanisms, cellular repair, and biological consequences of DNA damage, accurate measurement of resulting products must be achieved. There are various analytical techniques, with their own advantages and drawbacks, which can be used for this purpose. Mass spectrometric techniques with isotope dilution, which include gas chromatography (GC) and liquid chromatography (LC), provide structural elucidation of products and ascertain accurate quantification, which are absolutely necessary for reliable measurement. Both gas chromatography-mass spectrometry (GC-MS) or liquid chromatography-mass spectrometry (LC-MS), in single or tandem versions, have been used for the measurement of numerous DNA products such as sugar and base lesions, 8,5’-cyclopurine-2’-deoxynucleosides, base-base tandem lesions, and DNA-protein crosslinks, in vitro and in vivo. This article reviews these techniques and their applications in the measurement of oxidatively induced DNA damage and its repair.     

A single-nucleotide mutation within the TBX3 enhancer increased body size in Chinese horses

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A current view on Tau protein phosphorylation in Alzheimer's disease

The functions of the neuronal microtubule-associated protein Tau in the central nervous system are regulated by manifold posttranslational modifications at more than 50 sites. Tau in healthy neurons carries multiple phosphate groups, mostly in its microtubule assembly domain. Elevated phosphorylation and aggregation of Tau are widely considered pathological hallmarks in Alzheimer’s disease (AD) and other tauopathies, triggering the quest for Tau posttranslational modifications in the disease context. However, the phosphorylation patterns of physiological and pathological Tau are surprisingly similar and heterogenous, making it difficult to identify specific modifications as therapeutic targets and biomarkers for AD. We present a concise summary of - and view on - important previous and recent advances in Tau phosphorylation analysis in the context of AD.     

Quantitative Metaproteomics and Activity-based Protein Profiling of Patient Fecal Microbiome Identifies Host and Microbial Serine-type Endopeptidase Activity Associated With Ulcerative Colitis

The gut microbiota plays an important yet incompletely understood role in the induction and propagation of ulcerative colitis (UC). Organism-level efforts to identify UC-associated microbes have revealed the importance of community structure, but less is known about the molecular effectors of disease. We performed 16S rRNA gene sequencing in parallel with label-free data-dependent LC-MS/MS proteomics to characterize the stool microbiomes of healthy (n = 8) and UC (n = 10) patients. Comparisons of taxonomic composition between techniques revealed major differences in community structure partially attributable to the additional detection of host, fungal, viral, and food peptides by metaproteomics. Differential expression analysis of metaproteomic data identified 176 significantly enriched protein groups between healthy and UC patients. Gene ontology analysis revealed several enriched functions with serine-type endopeptidase activity overrepresented in UC patients. Using a biotinylated fluorophosphonate probe and streptavidin-based enrichment, we show that serine endopeptidases are active in patient fecal samples and that additional putative serine hydrolases are detectable by this approach compared with unenriched profiling. Finally, as metaproteomic databases expand, they are expected to asymptotically approach completeness. Using ComPIL and de novo peptide sequencing, we estimate the size of the probable peptide space unidentified (“dark peptidome”) by our large database approach to establish a rough benchmark for database sufficiency. Despite high variability inherent in patient samples, our analysis yielded a catalog of differentially enriched proteins between healthy and UC fecal proteomes. This catalog provides a clinically relevant jumping-off point for further molecular-level studies aimed at identifying the microbial underpinnings of UC.