piRNA-Triggered MIWI Ubiquitination and Removal by APC/C in Late Spermatogenesis

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Highlights? MIWI is a substrate of APC/C, and piRNA loading is essential for MIWI ubiquitination ? piRNA loading promotes MIWI binding to the APC/C substrate-binding subunit ? MIWI and piRNAs are coordinately eliminated in late spermatids ? Inhibition of MIWI destruction in late spermatids prevents sperm maturation     

Increased In Situ Intestinal Absorption of Phytoestrogenic Diarylheptanoids from Curcuma comosa in Nanoemulsions

Curcuma comosa has long been used as a gynecological medicine. Several diarylheptanoids have been purified from this plant, and their pharmacological effects were proven. However, there is no information about the absorption of C. comosa components to support the formulation usage. In the present study, C. comosa hexane extract and the mixture of its two major compounds, (4E,6E)-1,7-diphenylhepta-4,6-dien-3-ol (DA1) and (6E)-1,7-diphenylhept-6-en-3-ol (DA2), were formulated into nanoemulsions. The physical properties of the nanoemulsions and the in situ intestinal absorptions of DA1 and DA2 were evaluated. The results demonstrated the mean particle sizes at 0.207 ± 0.001 and 0.408 ± 0.014 μm, and the zeta potential at −14.57 ± 0.85 and −10.47 ± 0.32 mV for C. comosa nanoemulsion (C.c-Nano) and mixture of diarlylheptanoid nanoemulsions (DA-Nano), respectively. The entrapments of DA1 and DA2 were 76.61% and 75.41%, and 71.91% and 71.63% for C.c-Nano and DA-Nano, respectively. The drug loading ratios of DA1 and DA2 were 351.47 and 614.53 μg/mg, and 59.48 and 126.72 μg/mg for C.c-Nano and DA-Nano. The intestinal absorption rates of DA1 and DA2 were 0.329 ± 0.015 and 0.519 ± 0.026 μg/min/cm² in C.c-Nano, and 0.380 ± 0.006 and 0.428 ± 0.036 μg/min/cm² in DA-Nano, which were five to ten times faster than those in oil. In conclusion, the formulation in nanoemulsion forms obviously increased the intestinal absorption rate of diarylheptanoids.KEY WORDS: Curcuma comosa, diarylheptanoids, intestinal absorption, nanoemulsion, phytoestrogen     

Application of Semipermeable Membrane Devices (SPMDs) and Benthic Mussels to Evaluate the Bioavailability of Sediment-associated DDTs

Bioavailability of dichlorodiphenyltrichloroethanes (DDTs) in surface sediments was evaluated with semipermeable membrane devices (SPMDs) and two different sediment-dwelling benthic mussels, Bellamya aeruginosa (B. aeruginosa) and Corbicula fluminea (C. fluminea). After 28d laboratory exposure, the positive correlations of DDT concentrations between both SPMDs and benthic mussels with sediments documented that the bioavailability of DDTs was mainly affected by surrounding sediments, while the observed differences of DDT concentrations and congener proportions between B. aeruginosa and C. fluminea were due to the specific physiological characteristics of organisms and different physico-chemical properties of contaminants. Comparisons between SPMDs and benthic mussels showed higher values of biota-sediment accumulation factors (BSAF, 0.63-3.61 for B. aeruginosa and 2.19-17.08 for C. fluminea) than device accumulation factors (DAF, 1.00-1.74). This indicated that living organisms bioaccumulated much more DDTs from sediments than SPMDs due to the different exposure and uptake routes. Strong positive associations between DDTs in SPMDs and benthic mussels indicated SPMDs could mimic the bioaccumulation of DDTs, especially in C. fluminea. However, given the distinct differences observed for both concentrations and congener proportions of DDTs in SPMDs and B. aeruginosa, future study should be directed to develop reliable models with various sediment-dwelling organisms before SPMDs are routinely used in field study.     

Identification and Validation of Urinary Metabolite Biomarkers for Major Depressive Disorder

Major depressive disorder (MDD) is a widespread and debilitating mental disorder. However, there are no biomarkers available to aid in the diagnosis of this disorder. In this study, a nuclear magnetic resonance spectroscopy–based metabonomic approach was employed to profile urine samples from 82 first-episode drug-naïve depressed subjects and 82 healthy controls (the training set) in order to identify urinary metabolite biomarkers for MDD. Then, 44 unselected depressed subjects and 52 healthy controls (the test set) were used to independently validate the diagnostic generalizability of these biomarkers. A panel of five urinary metabolite biomarkers—malonate, formate, N-methylnicotinamide, m-hydroxyphenylacetate, and alanine—was identified. This panel was capable of distinguishing depressed subjects from healthy controls with an area under the receiver operating characteristic curve (AUC) of 0.81 in the training set. Moreover, this panel could classify blinded samples from the test set with an AUC of 0.89. These findings demonstrate that this urinary metabolite biomarker panel can aid in the future development of a urine-based diagnostic test for MDD.Major depressive disorder (MDD)¹ is a debilitating mental disorder affecting up to 15% of the general population and accounting for 12.3% of the global burden of disease (1, 2). Currently, the diagnosis of MDD still relies on the subjective identification of symptom clusters rather than empirical laboratory tests. The current diagnostic modality results in a considerable error rate (3), as the clinical presentation of MDD is highly heterogeneous and the current symptom-based method is not capable of adequately characterizing this heterogeneity (4). An approach that can be used to circumvent these limitations is to identify disease biomarkers to support objective diagnostic laboratory tests for MDD.Metabonomics, which can measure the small molecules in given biosamples such as plasma and urine without bias (5), has been extensively used to characterize the metabolic changes of diseases and thus facilitate the identification of novel disease-specific signatures as putative biomarkers (6–10). Nuclear magnetic resonance (NMR) spectroscopy–based metabonomic approaches characterized by sensitive, high-throughput molecular screening have been employed previously in identifying novel biomarkers for a variety of neuropsychiatric disorders, including stroke, bipolar disorder, and schizophrenia (11–13).Specifically with regard to MDD, several animal studies have already characterized the metabolic changes in the blood and urine (14–19). These studies provide valuable clues as to the pathophysiological mechanism of MDD. However, no study has been designed with the aim of diagnosing this disease. Recently, using an NMR-based metabonomic approach, this research group identified a unique plasma metabolic signature that enables the discrimination of MDD from healthy controls with both high sensitivity and specificity (20). These findings motivated further study on urinary diagnostic metabolite biomarkers for MDD, which would be more valuable from a clinical applicability standpoint, as urine can be more non-invasively collected. Moreover, previous studies have also demonstrated the feasibility of identifying diagnostic metabolite biomarkers of psychiatric disorders in the urine. For example, using an NMR-based metabonomics approach, Yap et al. (21) identified a unique urinary metabolite signature that clearly discriminated autism patients from healthy controls. As systemic metabolic disturbances have been observed in the urine of a depressed animal model, it is likely that diagnostic metabolite markers for MDD can be detected in human urine.Therefore, in this study, NMR spectroscopy combined with multivariate pattern recognition techniques were used to profile 82 first-episode drug-naïve MDD subjects and 82 healthy controls (the training set) in order to identify potential metabolite biomarkers for MDD. Furthermore, 44 unselected MDD subjects and 52 healthy controls (the test set) were employed to independently validate the diagnostic performance of these urinary metabolite biomarkers.     

A Fast Workflow for Identification and Quantification of Proteomes

The current in-depth proteomics makes use of long chromatography gradient to get access to more peptides for protein identification, resulting in covering of as many as 8000 mammalian gene products in 3 days of mass spectrometer running time. Here we report a fast sequencing (Fast-seq) workflow of the use of dual reverse phase high performance liquid chromatography - mass spectrometry (HPLC-MS) with a short gradient to achieve the same proteome coverage in 0.5 day. We adapted this workflow to a quantitative version (Fast quantification, Fast-quan) that was compatible to large-scale protein quantification. We subjected two identical samples to the Fast-quan workflow, which allowed us to systematically evaluate different parameters that impact the sensitivity and accuracy of the workflow. Using the statistics of significant test, we unraveled the existence of substantial falsely quantified differential proteins and estimated correlation of false quantification rate and parameters that are applied in label-free quantification. We optimized the setting of parameters that may substantially minimize the rate of falsely quantified differential proteins, and further applied them on a real biological process. With improved efficiency and throughput, we expect that the Fast-seq/Fast-quan workflow, allowing pair wise comparison of two proteomes in 1 day may make MS available to the masses and impact biomedical research in a positive way.The performance of mass spectrometry has been improved tremendously over the last few years (1–3), making mass spectrometry-based proteomics a viable approach for large-scale protein analysis in biological research. Scientists around the world are striving to fulfill the promise of identifying and quantifying almost all gene products expressed in a cell line or tissue. This would make mass spectrometry-based protein analysis an approach that is compatible to the second-generation mRNA deep-seq technique (4, 5).Two liquid chromatography (LC)-MS strategies have been employed to achieve deep proteome coverage. One is a single run with a long chromatography column and gradient to take advantage of the resolving power of HPLC to reduce the complexity of peptide mixtures; the other is a sequential run with two-dimensional separation (typically ion-exchange and reverse phase) to reduce peptide complexity. It was reported by two laboratories that 2761 and 4500 proteins were identified with a 10 h chromatography gradient on a dual pressure linear ion-trap orbitrap mass spectrometer (LTQ Orbitrap Velos)(6–8). Similarly, 3734 proteins were identified using a 8 h gradient on a 2 m long column with a hybrid triple quadrupole - time of flight (Q-TOF, AB sciex 5600 Q-TOF)(9) mass spectrometer. The two-dimensional approach has yielded more identification with longer time. For example, 10,006 proteins (representing over 9000 gene products, GPs)¹ were identified in U2OS cell (10), and 10,255 proteins (representing 9207 GPs) from HeLa cells (11). It took weeks (for example, 2–3 weeks) of machine running time to achieve such proteome coverage, pushing proteome analysis to the level that is comparable to mRNA-seq. With the introduction of faster machines, human proteome coverage now has reached the level of 7000–8500 proteins (representing 7000–8000 GPs) in 3 days (12). Notwithstanding the impressive improvement, the current approach using long column and long gradient suffers from inherent limitations: it takes long machine running time and it is challenging to keep reproducibility among repeated runs. Thus, current throughput and reproducibility have hindered the application of in-depth proteomics to traditional biological researches. A timesaving approach is in urgent need.In this study, we used the first-dimension (1D) short pH 10 RP prefractionation to reduce the complexity of the proteome (13), followed by sequential 30 min second-dimension (2D) short pH 3 reverse phase-(RP)-LC-MS/MS runs for protein identification (14). The results demonstrated that it is possible to identify 8000 gene products from mammalian cells within 12 h of total MS measurement time by applying this dual-short 2D-RPLC-MS/MS strategy (Fast sequencing, Fast-seq). The robustness of the strategy was revealed by parallel testing on different MS systems including quadrupole orbitrap mass spectrometer (Q-Exactive), hybrid Q-TOF (Triple-TOF 5600), and dual pressure linear ion-trap orbitrap mass spectrometer (LTQ-Orbitrap Velos), indicating the inherent strength of the approach as to merely taking advantage of the better MS instruments. This strategy increases the efficiency of MS sequencing in unit time for the identification of proteins. We achieved identification of 2200 proteins/30 mins on LTQ-Orbitrap Velos, 2800 proteins/30 mins on Q-Exactive and Triple-TOF 5600 respectively. We further optimized Fast-seq and worked out a quantitative-version of the Fast-seq workflow: Fast-quantification (Fast-quan) and applied it for protein abundance quantification in HUVEC cell that was treated with a drug candidate MLN4924 (a drug in phase III clinical trial). We were able to quantify > 6700 GPs in 1 day of MS running time and found 99 proteins were up-regulated with high confidence. We expect this efficient alternative approach for in-depth proteome analysis will make the application of MS-based proteomics more accessible to biological applications.     

Activated Cyclin-Dependent Kinase 5 Promotes Microglial Phagocytosis of Fibrillar β-Amyloid by Up-regulating Lipoprotein Lipase Expression

Amyloid plaques are crucial for the pathogenesis of Alzheimer disease (AD). Phagocytosis of fibrillar β-amyloid (Aβ) by activated microglia is essential for Aβ clearance in Alzheimer disease. However, the mechanism underlying Aβ clearance in the microglia remains unclear. In this study, we performed stable isotope labeling of amino acids in cultured cells for quantitative proteomics analysis to determine the changes in protein expression in BV2 microglia treated with or without Aβ. Among 2742 proteins identified, six were significantly up-regulated and seven were down-regulated by Aβ treatment. Bioinformatic analysis revealed strong over-representation of membrane proteins, including lipoprotein lipase (LPL), among proteins regulated by the Aβ stimulus. We verified that LPL expression increased at both mRNA and protein levels in response to Aβ treatment in BV2 microglia and primary microglial cells. Silencing of LPL reduced microglial phagocytosis of Aβ, but did not affect degradation of internalized Aβ. Importantly, we found that enhanced cyclin-dependent kinase 5 (CDK5) activity by increasing p35-to-p25 conversion contributed to LPL up-regulation and promoted Aβ phagocytosis in microglia, whereas inhibition of CDK5 reduced LPL expression and Aβ internalization. Furthermore, Aβ plaques was increased with reducing p25 and LPL level in APP/PS1 mouse brains, suggesting that CDK5/p25 signaling plays a crucial role in microglial phagocytosis of Aβ. In summary, our findings reveal a potential role of the CDK5/p25-LPL signaling pathway in Aβ phagocytosis by microglia and provide a new insight into the molecular pathogenesis of Alzheimer disease.Alzheimer disease (AD)¹ is one of the most common neurodegenerative disorders, which is characterized by pathological hallmarks such as neuronal and synaptic loss, neurofibrillary tangles (NFTs), and senile plaques. The intracellular NFTs are mainly composed of hyper-phosphorylated microtubule-associated protein tau, whereas toxic fibrillar β-amyloid (fAβ) as the main component of senile plaques is generated by sequential proteolytic cleavage of trans-membrane β-amyloid precursor protein (APP) by β- and γ-secretases. fAβ can induce oxidative stress-mediated neuronal cell death and cause cognitive impairment in mouse brains (1). Many reports suggest that fAβ induces dysregulation of two pivotal kinases CDK5 (2, 3) and GSK-3 (4), which are crucial regulators of hyperphosphorylated tau and increased production of Aβ from APP, and thereby triggers the cascade of signal transduction events underlying neuronal cell death in AD pathogenesis.As the resident immune cells in the brain, microglia can be activated in response to fAβ and often accumulate around the amyloid deposits in the brains of AD patients. Activated microglia trigger the production of inflammatory factors, reactive oxygen species, and chemokines, which may cause neuronal cell death (5). Furthermore, increasing evidence supports that activated microglia exert a vital beneficial role in the clearance of Aβ by phagocytosis. Many receptors, including scavenger receptor A (SR-A) (6), scavenger receptor class B type I (SR-BI) (7), lipopolysaccharide receptor (CD14) (8), CD33 (9), B-class scavenger receptor CD36 (10), CD47 (11), β1 integrin (12), toll-like receptor 2 (TLR2) (13), and toll-like receptor 4 (TLR4) (14), have been implicated in microglial phagocytosis of fAβ via direct or indirect binding to Aβ. Microglial phagocytosis of fAβ is also regulated by proinflammatory cytokines (15) and chemokine receptor CX3CR1 (16). Farfara et al. reported that the γ-secretase component presenilin, which is responsible for APP cleavage and Aβ production in neurons, is important for microglial fAβ clearance, indicating a dual role for presenilin in neuronal cell death and microglial phagocytosis (17). In addition, accumulating evidence suggests a critical role of lipids and lipoproteins in microglial fAβ phagocytosis and clearance. Lee et al. reported that apolipoprotein E (ApoE) enhances fAβ trafficking and degradation, indicating a role of cholesterol in fAβ degradation (18). After internalization, fAβ is degraded through the lysosome pathway (19, 20). However, the mechanism underlying microglial internalization of fAβ remains unclear.Stable isotope labeling of amino acids in cell culture (SILAC) is an accurate and reproducible mass spectrometry-based quantitative proteomics approach for examining changes in protein expression or post-translational modifications at a large scale (21, 22). Here, we used the SILAC quantitative proteomics strategy to investigate changes in the protein levels in BV2 microglia treated with fAβ. We found that 6 proteins were up-regulated and 7 were down-regulated significantly by Aβ treatment. Interestingly, bioinformatic analysis revealed that most of these up- or down-regulated proteins, including lipoprotein lipase (LPL), were mainly distributed in the cell membrane. We verified that LPL was up-regulated at both gene and protein levels in BV2 and primary microglia in response to fAβ, thereby indicating its role in the microglial phagocytosis of Aβ. Importantly, we further demonstrated that CDK5, which is a critical serine/threonine kinase in the pathogenesis of AD, regulated the expression of LPL and played a critical role in Aβ phagocytosis of microglia. Moreover, we found that increase in the p35-to-p25 conversion contributed to the enhanced CDK5 activity under Aβ stimulus and played a vital role in regulation of LPL expression and microglial Aβ phagocytosis. Our results suggest a role of the CDK5/p25-LPL signaling pathway in Aβ phagocytosis of microglia and provide valuable information to understand the molecular mechanism underlying microglial fAβ phagocytosis.     

Profiling Protein Kinases and Other ATP Binding Proteins in Arabidopsis Using Acyl-ATP Probes

Many protein activities are driven by ATP binding and hydrolysis. Here, we explore the ATP binding proteome of the model plant Arabidopsis thaliana using acyl-ATP (AcATP)¹ probes. These probes target ATP binding sites and covalently label lysine residues in the ATP binding pocket. Gel-based profiling using biotinylated AcATP showed that labeling is dependent on pH and divalent ions and can be competed by nucleotides. The vast majority of these AcATP-labeled proteins are known ATP binding proteins. Our search for labeled peptides upon in-gel digest led to the discovery that the biotin moiety of the labeled peptides is oxidized. The in-gel analysis displayed kinase domains of two receptor-like kinases (RLKs) at a lower than expected molecular weight, indicating that these RLKs lost the extracellular domain, possibly as a result of receptor shedding. Analysis of modified peptides using a gel-free platform identified 242 different labeling sites for AcATP in the Arabidopsis proteome. Examination of each individual labeling site revealed a preference of labeling in ATP binding pockets for a broad diversity of ATP binding proteins. Of these, 24 labeled peptides were from a diverse range of protein kinases, including RLKs, mitogen-activated protein kinases, and calcium-dependent kinases. A significant portion of the labeling sites could not be assigned to known nucleotide binding sites. However, the fact that labeling could be competed with ATP indicates that these labeling sites might represent previously uncharacterized nucleotide binding sites. A plot of spectral counts against expression levels illustrates the high specificity of AcATP probes for protein kinases and known ATP binding proteins. This work introduces profiling of ATP binding activities of a large diversity of proteins in plant proteomes. The data have been deposited in ProteomeXchange with the identifier PXD000188.ATP binding and hydrolysis are the driving processes in all living organisms. Hundreds of cellular proteins are able to bind and hydrolyze ATP to unfold proteins, transport molecules over membranes, or phosphorylate small molecules or proteins. Proteins with very different structures are able to bind ATP. A large and important class of ATP binding proteins is that of the kinases, which transfer the gamma phosphate from ATP to substrates. Kinases, and particularly protein kinases, play pivotal roles in signaling and protein regulation.The genome of the model plant Arabidopsis thaliana encodes for over 1099 protein kinases and hundreds of other ATP binding proteins (1, 2). Protein kinases are involved in nearly all signaling cascades and regulate processes ranging from cell cycle to flowering and from immunity to germination. Many protein kinases in plants are receptor-like kinases (RLKs), often carrying extracellular leucine-rich repeats (LRRs). The RLK class contains at least 610 members (3), including famous examples such as receptors involved in development (e.g. BRI1, ER, CLV1) and immunity (e.g. FLS2, EFR). Other important classes are mitogen-activated protein (MAP) kinases (MPKs) (20 different members), MPK kinase kinase kinases (MAP3Ks) (60 different members (4)), and calcium-dependent protein kinases (CPKs) (34 different members (5)). Because of their diverse and important roles, protein kinases have been intensively studied in plant science. The current approach is to study protein kinases individually—a daunting task, considering the remaining hundreds of uncharacterized protein kinases. New approaches are necessary in order to study protein kinases and other ATP binding proteins globally rather than individually.ATP binding activities of protein kinases and other proteins can be detected globally by acyl-ATP (AcATP) probes (6, 7) (Fig. 1A). AcATP binds to the ATP pocket of ATP binding proteins and places the acyl group in close proximity to conserved lysine residues in the ATP binding pocket. The acyl phosphonate moiety serves as an electrophilic warhead that can be nucleophilically attacked by the amino group of the lysine, resulting in a covalent attachment of the acyl reporter of the AcATP probe on the lysine and a concomitant release of ATP. The reporter tag is usually a biotin to capture and identify the labeled proteins. Labeled proteins can be displayed on protein blots using streptavidin-HRP. However, because AcATP labels many ATP binding proteins and protein kinases are of relatively low abundance, mass spectrometry is more often used to identify and quantify labeling with AcATP probes. The analysis is preferably done using Xsite, a procedure that involves trypsination of the entire labeled proteome, followed by analysis of the biotinylated peptides rather than the biotinylated proteins (8). This “KiNativ ” approach provides enough depth and resolving power to monitor ∼160 protein kinases in a crude mammalian proteome (7). Of the 518 human protein kinases (9), 394 (76%) have been detected via AcATP labeling (6).Open in a separate windowFig. 1.Structure and mechanism of labeling with BHAcATP. A, BHAcATP contains ATP, an acyl phosphate reactive group, and a biotin tag. When BHAcATP binds to the ATP binding pocket of a protein, the amino group of the nearby lysine reacts with the carbonyl carbon, which results in the covalent binding of the biotin tag to the protein while ATP is released. B, typical BHAcATP labeling profile of Arabidopsis leaf proteome. Arabidopsis leaf extracts were labeled with BHAcATP and the biotinylated proteins were detected on protein blots using streptavidin-HRP. Coomassie Brilliant Blue staining indicates equal loading. Asterisks indicate endogenously biotinylated proteins MCCA and BCCP. White, black, and gray arrowheads indicate bands containing ATBP+RBCL, PGK1, and a mix of ATP binding proteins, respectively. Abbreviations: MCCA, 3-methylcrotonyl-CoA carboxylase; BCCP, biotin carboxyl carrier protein; ATPB, chloroplastic ATPase; RBCL, ribulose-bisphosphate carboxylase; PGK1, phosphoglycerate kinase-1.KiNativ has mostly been used to validate targets of human drugs that target protein kinases using competitive labeling experiments. This approach has been used to identify selective inhibitors of, for example, Parkinson''s disease protein kinase LRRK2 (10), the BMK1 and JNK MAP kinases (11, 12), and the mTOR kinase (13). Importantly, the correlation of the biological activity of protein-kinase-inhibiting drugs with inhibitor affinity detected using KiNativ is better than that achieved when affinities are determined by assays using heterologously expressed protein kinases (7). This improved correlation illustrates that assays in the native environment provide a more realistic measure of protein kinase function.In addition to characterizing inhibitors selectively, AcATP probes can also display differential ATP binding activities of protein kinases. For example, labeling with AcATP probes during infection with dengue virus displayed a 2- to 8-fold activation of a DNA-dependent protein kinase (14) Similarly, AcATP labeling revealed an unexpected Raf kinase activation in extracts upon protein kinase inhibitor treatment (7). In conclusion, profiling with AcATP probes is a powerful approach for monitoring protein kinases and offers unprecedented opportunities to identify selective protein kinase inhibitors and discover protein kinases with differential ATP binding activities.In this work, we introduce AcATP profiling of plant proteomes. In addition to the analysis of labeled peptides, we characterized labeling using gel-based approaches and discovered that biotin is often oxidized in this procedure. We also performed an in-depth analysis of labeling sites in proteins other than protein kinases, which had not been done before. We discuss labeling outside known nucleotide binding pockets and investigate the correlation of labeling sites with protein abundance. We describe 63 labeling sites of known nucleotide binding pockets, of which 24 represent a remarkable diversity of protein kinases, including several LRR-RLKs. This work launches a new approach to study ATP binding proteins in plant science.