The Parkinson’s disease kinase LRRK2 autophosphorylates its GTPase domain at multiple sites

Mutations in leucine-rich repeat kinase 2 (LRRK2) are a common cause of inherited Parkinson’s disease (PD). The protein is large and complex, but pathogenic mutations cluster in a region containing GTPase and kinase domains. LRRK2 can autophosphorylate in vitro within a dimer pair, although the significance of this reaction is unclear. Here, we mapped the sites of autophosphorylation within LRRK2 and found several potential phosphorylation sites within the GTPase domain. Using mass spectrometry, we found that Thr1343 is phosphorylated and, using kinase dead versions of LRRK2, show that this is an autophosphorylation site. However, we also find evidence for additional sites in the GTPase domain and in other regions of the protein suggesting that there may be multiple autophosphorylation sites within LRRK2. These data suggest that the kinase and GTPase activities of LRRK2 may exhibit complex autoregulatory interdependence.     

过去20年中国耕地生长季起始期的时空变化

多时相遥感数据能够较好地描述区域尺度的植被物候和生长季节的变化特征.利用NDVI时序数据,采用非对称性高斯函数拟合方法重建平滑曲线,分别提取了我国20世纪80年代初、90年代初和21世纪初等3个时期为我国耕地第一生长季起始期,计算3个时期平均生长起始期,并分析了我国耕地第一生长季起始期的区域空间分异规律;然后,从区域和省份两个尺度分析了20世纪80年代初至90年代初和20世纪90年代初至21世纪初两个阶段我国耕地生长季起始期动态变化趋势和空间格局.结果表明,我国不同区域耕地第一生长季起始期存在十分明显的空间差异,清楚地呈现出一个从南向北逐渐推迟的空间特征;从不同区域看,在20世纪80年代初至90年代初和20世纪90年代初至21世纪初两个时期,我国耕地第一生长季起始期变化都是提前和推迟并存,不同区域变化程度不一;从不同省份看,在过去20年间,我国绝大多数省份耕地第一生长季起始期都表现为总体提前的趋势,但不同省份的起始期变化具有差异性.影响我国耕地生长季起始期变化的因素很多,如何区别气候变化等自然因子和人类活动因子对耕地生长季起始期变化的影响是一个值得深入研究的问题.     

Taurine prevents cardiomyocyte death by inhibiting NADPH oxidase-mediated calpain activation

Taurine has been shown to prevent cardiomyocyte apoptosis. This study investigated the effects of taurine on NADPH oxidase and calpain activation in mediating apoptosis in cardiomyocytes. Apoptosis was induced by norepinephrine (NE) in cultured adult rat ventricular cardiomyocytes. NE (5 microM) increased NADPH oxidase activation and reactive oxygen species (ROS) production and induced apoptosis. These effects of NE on cardiomyocytes were diminished by taurine (0.5 mg/kg) but not beta-alanine. Inhibition of gp91(phox)-NADPH oxidase or ROS production protected cardiomyocytes from apoptosis. NE also induced calpain-1 activation in cardiomyocytes. This effect of NE on calpain was abrogated by gp91(phox)-NADPH oxidase inhibition or ROS scavengers and was mimicked by H(2)O(2) (25 microM) in cardiomyocytes. Pharmacological inhibitors of calpain or overexpression of calpastatin, a specific calpain inhibitor, blocked calpain activation and prevented cardiomyocyte apoptosis during NE stimulation. Furthermore, taurine treatment inhibited NE- or H(2)O(2)-induced calpain activation in cardiomyocytes. In conclusion, NADPH oxidase induces calpain activation, leading to apoptosis in NE-induced cardiomyocytes. Taurine inhibits NADPH oxidase and calpain activation. Thus, inhibition of NADPH oxidase-mediated calpain activation may be an important mechanism for taurine's antiapoptotic action in cardiomyocytes.     

Impact of Vitamin D Replacement on Markers of Glucose Metabolism and Cardio-Metabolic Risk in Women with Former Gestational Diabetes—A Double-Blind,Randomized Controlled Trial

Gestational Diabetes Mellitus (GDM) and vitamin D deficiency are related to insulin resistance and impaired beta cell function, with heightened risk for future development of diabetes. We evaluated the impact of vitamin D supplementation on markers of glucose metabolism and cardio metabolic risk in Asian women with former GDM and hypovitaminosis D. In this double blind, randomized controlled trial, 26 participants were randomized to receive either daily 4000 IU vitamin D3 or placebo capsules. 75g Oral Glucose Tolerance Test (OGTT) and biochemistry profiles were performed at baseline and 6 month visits. Mathematical models, using serial glucose, insulin and C peptide measurements from OGTT, were employed to calculate insulin sensitivity and beta cell function. Thirty three (76%) women with former GDM screened had vitamin D level of <50 nmol/L at baseline. Supplementation, when compared with placebo, resulted in increased vitamin D level (+51.1 nmol/L vs 0.2 nmol/L, p<0.001) and increased fasting insulin (+20% vs 18%, p = 0.034). The vitamin D group also demonstrated a 30% improvement in disposition index and an absolute 0.2% (2 mmol/mol) reduction in HbA_1c. There was no clear change in insulin sensitivity or markers of cardio metabolic risk. This study highlighted high prevalence of vitamin D deficiency among Asian women with former GDM. Six months supplementation with 4000 IU of vitamin D3 safely restored the vitamin D level, improved basal pancreatic beta-cell function and ameliorated the metabolic state. There was no effect on markers of cardio metabolic risk. Further mechanistic studies exploring the role of vitamin D supplementation on glucose homeostasis among different ethnicities may be needed to better inform future recommendations for these women with former GDM at high risk of both hypovitaminosis D and future diabetes.     

Using an Adenosine Triphosphate Bioluminescent Assay to Determine Effective Antibiotic Combinations against Carbapenem-Resistant Gram Negative Bacteria within 24 Hours

Background

Current in vitro combination testing methods involve enumeration by bacterial plating, which is labor-intensive and time-consuming. Measurement of bioluminescence, released when bacterial adenosine triphosphate binds to firefly luciferin-luciferase, has been proposed as a surrogate for bacterial counts. We developed an ATP bioluminescent combination testing assay with a rapid turnaround time of 24h to determine effective antibiotic combinations.

Methods

100 strains of carbapenem-resistant (CR) GNB [30 Acinetobacter baumannii (AB), 30 Pseudomonas aeruginosa (PA) and 40 Klebsiella pneumoniae (KP)] were used. Bacterial suspensions (10⁵ CFU/ml) were added to 96-well plates containing clinically achievable concentrations of multiple single and two-antibiotic combinations. At 24h, the luminescence intensity of each well was measured. Receiver operator characteristic curves were plotted to determine optimal luminescence threshold (T_RLU) to discriminate between inhibitory/non-inhibitory combinations when compared to viable plating. The unweighted accuracy (UA) [(sensitivity + specificity)/2] of T_RLU values was determined. External validation was further done using 50 additional CR-GNB.

Results

Predictive accuracies of T_RLU were high for when all antibiotic combinations and species were collectively analyzed (T_RLU = 0.81, UA = 89%). When individual thresholds for each species were determined, UA remained high. Predictive accuracy was highest for KP (T_RLU = 0.81, UA = 91%), and lowest for AB (T_RLU = 0.83, UA = 87%). Upon external validation, high overall accuracy (91%) was observed. The assay distinguished inhibitory/non-inhibitory combinations with UA of 80%, 94% and 93% for AB, PA and KP respectively.

Conclusion

We developed an assay that is robust at identifying useful combinations with a rapid turn-around time of 24h, and may be employed to guide the timely selection of effective antibiotic combinations.     

A Biochemical Approach to Understand the Pathogenesis of Advanced Pulmonary Arterial Hypertension: Metabolomic Profiles of Arginine,Sphingosine-1-Phosphate,and Heme of Human Lung

Pulmonary arterial hypertension (PAH) is a vascular disease characterized by persistent precapillary pulmonary hypertension (PH), leading to progressive right heart failure and premature death. The pathological mechanisms underlying this condition remain elusive. Analysis of global metabolomics from lung tissue of patients with PAH (n = 8) and control lung tissue (n = 8) leads to a better understanding of disease progression. Using a combination of high-throughput liquid-and-gas-chromatography-based mass spectrometry, we showed unbiased metabolomic profiles of disrupted arginine pathways with increased Nitric oxide (NO) and decreased arginine. Our results also showed specific metabolic pathways and genetic profiles with increased Sphingosine-1-phosphate (S1P) metabolites as well as increased Heme metabolites with altered oxidative pathways in the advanced stage of the human PAH lung. The results suggest that PAH has specific metabolic pathways contributing to the vascular remodeling in severe pulmonary hypertension. Profiling metabolomic alterations of the PAH lung has provided a new understanding of the pathogenic mechanisms of PAH, which benefits therapeutic targeting to specific metabolic pathways involved in the progression of PAH.     

MASH Suite Pro: A Comprehensive Software Tool for Top-Down Proteomics

Top-down mass spectrometry (MS)-based proteomics is arguably a disruptive technology for the comprehensive analysis of all proteoforms arising from genetic variation, alternative splicing, and posttranslational modifications (PTMs). However, the complexity of top-down high-resolution mass spectra presents a significant challenge for data analysis. In contrast to the well-developed software packages available for data analysis in bottom-up proteomics, the data analysis tools in top-down proteomics remain underdeveloped. Moreover, despite recent efforts to develop algorithms and tools for the deconvolution of top-down high-resolution mass spectra and the identification of proteins from complex mixtures, a multifunctional software platform, which allows for the identification, quantitation, and characterization of proteoforms with visual validation, is still lacking. Herein, we have developed MASH Suite Pro, a comprehensive software tool for top-down proteomics with multifaceted functionality. MASH Suite Pro is capable of processing high-resolution MS and tandem MS (MS/MS) data using two deconvolution algorithms to optimize protein identification results. In addition, MASH Suite Pro allows for the characterization of PTMs and sequence variations, as well as the relative quantitation of multiple proteoforms in different experimental conditions. The program also provides visualization components for validation and correction of the computational outputs. Furthermore, MASH Suite Pro facilitates data reporting and presentation via direct output of the graphics. Thus, MASH Suite Pro significantly simplifies and speeds up the interpretation of high-resolution top-down proteomics data by integrating tools for protein identification, quantitation, characterization, and visual validation into a customizable and user-friendly interface. We envision that MASH Suite Pro will play an integral role in advancing the burgeoning field of top-down proteomics.With well-developed algorithms and computational tools for mass spectrometry (MS)¹ data analysis, peptide-based bottom-up proteomics has gained considerable popularity in the field of systems biology (1–9). Nevertheless, the bottom-up approach is suboptimal for the analysis of protein posttranslational modifications (PTMs) and sequence variants as a result of protein digestion (10). Alternatively, the protein-based top-down proteomics approach analyzes intact proteins, which provides a “bird''s eye” view of all proteoforms (11), including those arising from sequence variations, alternative splicing, and diverse PTMs, making it a disruptive technology for the comprehensive analysis of proteoforms (12–24). However, the complexity of top-down high-resolution mass spectra presents a significant challenge for data analysis. In contrast to the well-developed software packages available for processing data from bottom-up proteomics experiments, the data analysis tools in top-down proteomics remain underdeveloped.The initial step in the analysis of top-down proteomics data is deconvolution of high-resolution mass and tandem mass spectra. Thorough high-resolution analysis of spectra by horn (THRASH), which was the first algorithm developed for the deconvolution of high-resolution mass spectra (25), is still widely used. THRASH automatically detects and evaluates individual isotopomer envelopes by comparing the experimental isotopomer envelope with a theoretical envelope and reporting those that score higher than a user-defined threshold. Another commonly used algorithm, MS-Deconv, utilizes a combinatorial approach to address the difficulty of grouping MS peaks from overlapping isotopomer envelopes (26). Recently, UniDec, which employs a Bayesian approach to separate mass and charge dimensions (27), can also be applied to the deconvolution of high-resolution spectra. Although these algorithms assist in data processing, unfortunately, the deconvolution results often contain a considerable amount of misassigned peaks as a consequence of the complexity of the high-resolution MS and MS/MS data generated in top-down proteomics experiments. Errors such as these can undermine the accuracy of protein identification and PTM localization and, thus, necessitate the implementation of visual components that allow for the validation and manual correction of the computational outputs.Following spectral deconvolution, a typical top-down proteomics workflow incorporates identification, quantitation, and characterization of proteoforms; however, most of the recently developed data analysis tools for top-down proteomics, including ProSightPC (28, 29), Mascot Top Down (also known as Big-Mascot) (30), MS-TopDown (31), and MS-Align+ (32), focus almost exclusively on protein identification. ProSightPC was the first software tool specifically developed for top-down protein identification. This software utilizes “shotgun annotated” databases (33) that include all possible proteoforms containing user-defined modifications. Consequently, ProSightPC is not optimized for identifying PTMs that are not defined by the user(s). Additionally, the inclusion of all possible modified forms within the database dramatically increases the size of the database and, thus, limits the search speed (32). Mascot Top Down (30) is based on standard Mascot but enables database searching using a higher mass limit for the precursor ions (up to 110 kDa), which allows for the identification of intact proteins. Protein identification using Mascot Top Down is fundamentally similar to that used in bottom-up proteomics (34), and, therefore, it is somewhat limited in terms of identifying unexpected PTMs. MS-TopDown (31) employs the spectral alignment algorithm (35), which matches the top-down tandem mass spectra to proteins in the database without prior knowledge of the PTMs. Nevertheless, MS-TopDown lacks statistical evaluation of the search results and performs slowly when searching against large databases. MS-Align+ also utilizes spectral alignment for top-down protein identification (32). It is capable of identifying unexpected PTMs and allows for efficient filtering of candidate proteins when the top-down spectra are searched against a large protein database. MS-Align+ also provides statistical evaluation for the selection of proteoform spectrum match (PrSM) with high confidence. More recently, Top-Down Mass Spectrometry Based Proteoform Identification and Characterization (TopPIC) was developed (http://proteomics.informatics.iupui.edu/software/toppic/index.html). TopPIC is an updated version of MS-Align+ with increased spectral alignment speed and reduced computing requirements. In addition, MSPathFinder, developed by Kim et al., also allows for the rapid identification of proteins from top-down tandem mass spectra (http://omics.pnl.gov/software/mspathfinder) using spectral alignment. Although software tools employing spectral alignment, such as MS-Align+ and MSPathFinder, are particularly useful for top-down protein identification, these programs operate using command line, making them difficult to use for those with limited knowledge of command syntax.Recently, new software tools have been developed for proteoform characterization (36, 37). Our group previously developed MASH Suite, a user-friendly interface for the processing, visualization, and validation of high-resolution MS and MS/MS data (36). Another software tool, ProSight Lite, developed recently by the Kelleher group (37), also allows characterization of protein PTMs. However, both of these software tools require prior knowledge of the protein sequence for the effective localization of PTMs. In addition, both software tools cannot process data from liquid chromatography (LC)-MS and LC-MS/MS experiments, which limits their usefulness in large-scale top-down proteomics. Thus, despite these recent efforts, a multifunctional software platform enabling identification, quantitation, and characterization of proteins from top-down spectra, as well as visual validation and data correction, is still lacking.Herein, we report the development of MASH Suite Pro, an integrated software platform, designed to incorporate tools for protein identification, quantitation, and characterization into a single comprehensive package for the analysis of top-down proteomics data. This program contains a user-friendly customizable interface similar to the previously developed MASH Suite (36) but also has a number of new capabilities, including the ability to handle complex proteomics datasets from LC-MS and LC-MS/MS experiments, as well as the ability to identify unknown proteins and PTMs using MS-Align+ (32). Importantly, MASH Suite Pro also provides visualization components for the validation and correction of the computational outputs, which ensures accurate and reliable deconvolution of the spectra and localization of PTMs and sequence variations.     

Change of Th17 Lymphocytes and Treg/Th17 in Typical and Atypical Optic Neuritis

Background

Typical and atypical optic neuritis (ON) are two clinical types of autoimmune inflammatory diseases of the optic nerve that causes acute vision loss, and are difficult to distinguish in their early stages. The disturbance in the balance of Th17 and Treg lymphocytes is thought to play an essential role in these autoimmune inflammatory diseases.

Objectives

To detect the clinical relevance of Th17 and Treg in peripheral blood and the ratio of Treg/Th17 in patients with typical and atypical ON. To determine whether analysis of Th17 and Treg lymphocytes will provides insights into the different disease phenotypes of typical and atypical ON.

Methods

We studied a consecutive series of patients aged 14–70 years who presented to our neurological department with typical ON (n = 30) or atypical ON (n = 33) within 4 weeks of their acute attacks. Routine clinical tests and ophthalmological examination were performed in all patients. Blood samples were collected from untreated patients and from gender- and age-matched healthy controls (n = 30). The proportion of peripheral blood Th17 cells and Treg cells was determined by flow cytometry.

Results

Patients with atypical ON had a higher proportion of Th17 cells than patients with typical ON (3.61±1.56 vs 2.55±1.74, P<0.01) or controls (1.45±0.86, P<0.01). The proportion of Th17 cells in patients with typical ON was also markedly higher than in controls (P<0.01). The mean percentage of Treg cells in atypical ON (6.31±2.11) and typical ON (6.80±2.00) were significantly lower when compared to controls (8.29±2.32, both P<0.01). No significant difference in Treg frequency was observed between typical ON and atypical ON (p>0.05).

Conclusions

The frequency of Th17 cells is higher in atypical ON than typical ON, and patients with atypical ON have a greater imbalance of pro-inflammatory and regulatory cells than patients with typical ON when compared with controls. These changes are indicative of distinct pathological mechanisms and may provide useful information to distinguish typical and atypical ON.     

Comparison of Risk Factor between Lacunar Stroke and Large Artery Atherosclerosis Stroke: A Cross-Sectional Study in China

Background

Stroke is the second most common cause of mortality in China. Although most subtypes of ischemic stroke share similar risk factors, they have different etiologies. Our study aimed to evaluate the different risk factor profiles between the stroke subtypes, lacunar infarcts (LI) and large-artery atherosclerosis (LAA), and clarify the characteristics of current acute ischemic stroke in China.

Methods

In this cross-sectional study, we analyzed the clinical characteristics of 1982 patients with acute ischemic stroke who were admitted to the neurology department at the Peking University First Hospital between 2007 and 2014. Ischemic stroke was further classified into LAA, LI, cardioembolism (CE) and undetermined causes of infarction (UDI) according to TOAST classification. Demographic characteristics, risk factors, as well as the findings of laboratory and imaging tests of 1773 patients with LAA and LI, were analyzed by univariate and multivariate logistic analysis.

Results

Of the 1982 ischemic stroke patients included in this study, 1207 were diagnosed with LAA, 566 with LI, 173 with cardioembolism (CE) and 36 with undetermined causes of infarction (UDI). By comparing the risk factors in multivariate logistic regression analysis, hypertension [odds ratio (OR) = 1.832] and white matter leukoaraiosis (WML) (OR = 1.865) were found to be more strongly correlated with LI than LAA. Low density lipoprotein- cholesterol (LDL-c) (OR = 0.774) were more strongly related to LAA than LI.

Conclusions

This study found that hypertension and WML were more strongly correlated with LI than LAA. LDL-c was more strongly related to LAA than LI.