Literature DB >> 30917850

Network approach identifies Pacer as an autophagy protein involved in ALS pathogenesis.

S Beltran1,2, M Nassif1,2, E Vicencio1,2, J Arcos1,2, L Labrador1,2, B I Cortes1,2, C Cortez2, C A Bergmann1,2, S Espinoza1, M F Hernandez1,2, J M Matamala3,4, L Bargsted4, S Matus4,5,6,7, D Rojas-Rivera1,8,9, M J M Bertrand8,9, D B Medinas4,7,10, C Hetz4,7,11,10,12, P A Manque13,14,15, U Woehlbier16,17.   

Abstract

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a multifactorial fatal motoneuron disease without a cure. Ten percent of ALS cases can be pointed to a clear genetic cause, while the remaining 90% is classified as sporadic. Our study was aimed to uncover new connections within the ALS network through a bioinformatic approach, by which we identified C13orf18, recently named Pacer, as a new component of the autophagic machinery and potentially involved in ALS pathogenesis.
METHODS: Initially, we identified Pacer using a network-based bioinformatic analysis. Expression of Pacer was then investigated in vivo using spinal cord tissue from two ALS mouse models (SOD1G93A and TDP43A315T) and sporadic ALS patients. Mechanistic studies were performed in cell culture using the mouse motoneuron cell line NSC34. Loss of function of Pacer was achieved by knockdown using short-hairpin constructs. The effect of Pacer repression was investigated in the context of autophagy, SOD1 aggregation, and neuronal death.
RESULTS: Using an unbiased network-based approach, we integrated all available ALS data to identify new functional interactions involved in ALS pathogenesis. We found that Pacer associates to an ALS-specific subnetwork composed of components of the autophagy pathway, one of the main cellular processes affected in the disease. Interestingly, we found that Pacer levels are significantly reduced in spinal cord tissue from sporadic ALS patients and in tissues from two ALS mouse models. In vitro, Pacer deficiency lead to impaired autophagy and accumulation of ALS-associated protein aggregates, which correlated with the induction of cell death.
CONCLUSIONS: This study, therefore, identifies Pacer as a new regulator of proteostasis associated with ALS pathology.

Entities:  

Keywords:  ALS; Autophagy; Beclin1; C13orf18, KIAA0226-like; Pacer; Rubicon; Rubicon-like; SOD1; TDP43

Mesh:

Substances:

Year:  2019        PMID: 30917850      PMCID: PMC6437924          DOI: 10.1186/s13024-019-0313-9

Source DB:  PubMed          Journal:  Mol Neurodegener        ISSN: 1750-1326            Impact factor:   14.195


Background

Amyotrophic lateral sclerosis (ALS) is the most common adult motoneuron disease that causes a progressive paralysis due to the selective loss of motoneurons in the motor cortex, brainstem motor nucleus, and spinal cord [1]. In recent years, a growing number of genetic loci have been associated with ALS and other complex diseases (reviewed in [2, 3]). The first mutations identified as a cause of familial ALS (fALS) mapped to SOD1 (superoxide dismutase 1), whereas mutations in the TARDBP gene, coding for Tar DNA binding protein 43 (TDP43), one of the most common components of protein aggregates in ALS cases, were identified years later [4]. Since then, the number of genes associated with ALS has significantly increased (reviewed in [2]). The recent discovery of hexanucleotide G4C2 repeat expansions in the intronic region of C9orf72 as a common genetic cause of fALS [5] and frontotemporal dementia (FTD) has profoundly changed our understanding of ALS, explaining almost 40% of the familial cases, in addition to near 10% of sporadic ALS (sALS) [5, 6]. ALS is now considered to be part of a spectrum of neurological disorders instead of simply a neuromuscular disease. Understanding shared pathophysiological mechanisms of sALS and fALS promises the finding of effective therapies for both forms of the disease. Defective cellular processes identified thus far to be responsible for the ALS and the related FTD include (i) alterations to proteostasis control (protein quality control, including proteasomal degradation, autophagy and endoplasmic reticulum (ER) stress), (ii) mitochondrial dysfunction, (iii) cytoskeletal dynamics and axonal transport, (iv) RNA homeostasis, and (v) DNA damage response (reviewed in [3, 7, 8]). Macroautophagy, here referred to as autophagy, is an evolutionarily conserved process that consists of vesicles termed autophagosomes to deliver intracellular cargo to the lysosome, including long-lived cytosolic proteins, damaged organelles, and protein aggregates [9, 10]. Most cell types, including neurons, operate under constitutive autophagy [11], which is thought to have a vital role in maintaining their metabolic and proteostatic balance [12-14]. In this context, defects in the endolysosomal pathway or autophagy-related genes have been associated with diverse neurodegenerative diseases, including Alzheimer’s disease (AD), Huntington’s disease (HD), Parkinson’s disease (PD), as well as ALS [15, 16]. Mutations in several genes coding for proteins involved in autophagy or other membrane trafficking pathways have been found in ALS patients, including SQSTM1 and OPTN, which encode the selective autophagy receptors SQSTM1/p62 and optineurin, respectively, and ALS2 that encodes alsin2, which participates in membrane trafficking, as well as TBK1 (TANK-binding kinase 1), a kinase involved in autophagy-mediated degradation of ubiquitinated cargos [17-19]. C9orf72 was also shown to participate in the autophagy process [20]. Targeting autophagy with genetic and pharmacological approaches has indicated that the pathway may have pathogenic or protective roles depending on the disease stage and cell type analyzed [21-23]. Thus, defects in autophagy and endolysosomal pathways may underlay an important part of the etiology of the disease. The rise of high-throughput experimental approaches such as genomics, transcriptomics, and proteomics provides new datasets for ALS and other neurodegenerative diseases. Recent comprehensive studies proofed that network-based analysis offers the means to unravel new genes, pathways and disease networks associated with complex disorders similar to ALS [24-29]. The convergent analysis approach, which is loosely defined as the combination of multi-dimensional datasets with network modeling of gene and protein interactions, provides a new way to identify genes involved in disease pathways or mechanisms even with little or no previous evidence [26, 27]. We applied this approach to the data available for ALS and selected the C13orf18 gene for further experimental studies, based on (i) its suggested participation in the human autophagy network through interaction with Beclin1, one of the main components of this pathway [30] that is known to be dysregulated in ALS [22], (ii) a single-nucleotide polymorphism (SNP) in the 3’UTR of the C13orf18 gene (polymorphism ID: rs2478046) found in a higher allele frequency in a sALS patient cohort [31], and (iii) the fact that the C13orf18 protein was uncharacterized and had no cellular function assigned to it. Due to its sequence homology with Rubicon (Run domain protein Beclin1 interacting and cysteine-rich domain or KIAA0226), C13orf18 is also referred to as Rubicon-like or KIAA0226-L. However, recently, Cheng et al. reported that C13orf18 positively regulates autophagosome maturation by complex association with UVRAG and stimulation of Vps34 kinase activity, hence it was named Pacer (protein associated with UVRAG as autophagy enhancer) [32]. Here we report that Pacer displays decreased expression in the terminal stage of the disease in two fALS mouse models and notably in post-mortem spinal cord tissue from sALS patients. Interestingly, we found Pacer to be expressed exclusively in neurons in the spinal cord. Using cellular models, we demonstrate that targeting Pacer results in reduced autophagy activity, augmented SOD1 aggregation, and sensitization of motoneurons to cell death. Hence, our study identifies Pacer as a new protein involved in neuronal autophagy, whose loss is related to the selective vulnerability of motoneurons during ALS pathogenesis.

Methods

Convergent analysis

Copy number variation (CNV) data were collected from 4 published studies [33-36]. A total of 338 genes associated with ALS were included in the analysis. Additionally, genes linked to ALS were collected from The Huge Navigator (an integrated knowledge base of human genome epidemiology). We specifically searched the Phenopedia page for ALS related association studies and reported genes. Using the exact match of term “ALS” or “motoneuron disease,” we retrieved 143 genes annotated in the HuGE database (2011). From those, 128 genes were finally included in the analysis (14 genes were excluded from the analysis because there were not associated with the disease upon revision) (Additional file 1: Table S1). We uploaded the selected CNV and HuGE genes into the Ingenuity Pathway Analysis (IPA) system (Qiagen), which contains protein/protein interaction (PPI) and expression datasets. We ran a “core analysis” approach and obtained 241 genes in 12 ALS-associated subnetworks (Additional file 2: Table S2).

Animals

We employed the SOD1G93A (strain 002726) and TDP43A315T (strain 010700) transgenic mice both obtained from The Jackson Laboratory as ALS mouse models [37, 38]. The TDP43A315T received jellified food to prevent the premature death by intestinal dysmotility and allowed the motor degeneration phenotype to develop [39]. The animal care and all animal experiments were performed according to procedures approved by “Guide for the Care and Use of Laboratory Animals” (Commission on Life Sciences, National Research Council. National Academy Press 1996) and approved by the Bioethical Committee of the Universidad Mayor and from Neurounion Biomedical Foundation (Protocol CBA #05010).

Histology and immunostaining

Mice were sacrificed and perfused with PBS, and spinal cords were collected. Spinal cords were fixed in paraformaldehyde (PFA, Merck, 30,525–89-4) 4% for 24 h and then paraffin embedded. The spinal cords were sectioned transversely in the lumbar section on a microtome at 10 μm and were collected in positively charged slides. Then, the slides were deparaffinized with xylol and hydrated with descending concentrations of alcohol until reaching distilled water. The epitopes were exposed with citrate buffer at 96 °C for 40 min. After this, slides were washed three times with 0.05% Tween20 in PBS. The blocking of non-specific binding sites was done with 3% BSA in PBS solution for 40 min at room temperature. Slides were incubated with primary antibodies diluted in 1% BSA-0.05% Tween20 in PBS solution overnight at 4 °C. Primary antibodies and dilutions were as follows: mouse anti-Pacer (custom-made from Abmart), 1:100, rabbit anti-Rubicon (Invitrogen, PA5–38017), 1:100, rabbit anti-GFAP (EMD Millipore Corp., AB5804), 1:1000, rabbit anti-NeuN (EMD Millipore Corp., ABN78), 1:1000 and anti-MMP9 (Abcam, ab38898). Secondary antibodies and dilutions were: anti-mouse Alexa 555 (Thermo Fisher Scientific, A28180), 1:1000 and anti-rabbit Alexa 488 (Thermo Fisher Scientific, A27034), 1:1000 prepared in a 1% BSA-0.05% Tween20 in PBS solution with DAPI (Invitrogen, D1306), 1:1000 or Hoechst (Life Technologies, H3570), 1:1000 incubated for 2 h. Then, slides were washed and mounted with Fluoromount-G (Invitrogen). Images were taken with a Leica TCS SP8 confocal microscope with a 10X, 40X and 63X objective magnifications. ImageJ and LAS X software were used to process the stacked images.

Processing of human tissues

Frozen tissue was a generous gift from Dr. Robert H. Brown, Jr. (University of Massachusetts Medical School). Briefly, frozen post-­mortem spinal cord tissue from sALS patients and control subjects were obtained from the Alzheimer Disease Research Center at Massachusetts General Hospital and Dr. Robert H. Brown laboratory at the Neurology Department of University of Massachusetts Medical School under approved Institutional Review Board protocol (FWA#00004009). The biochemical analysis of the human samples was also authorized by the Ethics Committee of the Faculty of Medicine of the University of Chile.

RNA extraction and quantitative real-time PCR

Total RNA was extracted from mouse tissue (liver, muscle, cortex, cerebellum, hippocampus, spinal cord) by first homogenizing tissues in saline phosphate buffer (100 μl of PBS, pH 7.4) with protease inhibitors (Thermo Fisher Scientific, A32955 in a weight per volume ratio of 1:1. The same protocol was followed for post-mortem human spinal cord samples preparation. 1 ml of TRIzol LS (Invitrogen, 10,296,028) was added to 50 μl of homogenate. The remaining 50 μl were kept for Western blot assays (see below). For RNA extraction from the mouse motoneuron cell line NSC34 (Neuroblastoma Spinal Cord 34) cells were pelleted, washed once with cold PBS and directly resuspended in 700 μl of TRIzol LS. Total RNA was isolated using the protocol recommended by the manufacturer. cDNAs were synthesized using the First Strand cDNA Synthesis Kit (Thermo Fisher Scientific, K1621). qRT-PCR was carried out via SYBR Green assays (Kappa biosystem, KK4601) using the Eco™ Real-Time PCR System (Illumina) according to the manufacturer’s instructions. Each sample was run in triplicates. mRNA expression was normalized to the 18 s (cells) or actin (tissues) rRNA expression. Transcript levels were quantified by using the ΔΔCt value method. The following primers were used for quantitative RT-PCR: Pacer forward 5′-TTCACCCACCAATCAAGAGGGACA-3 and reverse 5′-ACAAGACTCTGCAGATGAGTGGCA-3′; Beclin1 forward 5′-CAGGAACTCACAGCTCCATTAC-3′ and reverse 5′-CCATCCTGGCGAGTTTCAATA-3′; 18S forward 5′-GTAACCCGTTGAACCCCATT-3′ and reverse 5′-CCATCCAATCGGTAGTAGGG-3′, Rubicon forward 5′- TTCAGCATCTCCGAGTCCTT-3′ and reverse 5′- AATCCCGTGAACTGAACTGG-3′. For human samples, the primers used were: hPacer forward 5′-ATGGTGTCACAATCTACAGTCAGg-3′, reverse 5′-GGGAGAGGCAGCATCTGTC-3′; hRubicon forward 5′- CTGGCAGTTCGTGAAAGACA -3′ and reverse 5′- TTAGCAGGAAGGCAGCATCT-3′. β-actin forward 5′-AAGATCATTGCTCCTCCTGA-3′ and reverse 5′-TACTCCTGCTTGCTGATCCA-3′ primers were used for both mouse and human samples. RT-PCR conditions were: 1 cycle at 95 °C for 5 min, followed by 40 cycles at 95 °C for 30 s, 58 °C for 45 s.

Plasmid constructs

To generate the plasmid vector encoding mPacer-V5 mouse Pacer mRNA was extracted from C57BL/6 spinal cord tissue and cloned into the pcDNA3.1/V5-His TOPO vector (Invitrogen, 460,083). The PCR was carried out in a final volume of 30 μl, containing 0.8 Units of DreamTaq (Thermo Fisher Scientific, EP0701), 3 μl of Dreamtaq Buffer (5x, Thermo Fisher, K1071), 0.6 μl of dNTPs (10 μM) and 0.45 μl (10 μM) of each primer, Pacer forward 5′- ATGAATTCAAGAGTCACGCCCAG -3′ and reverse 5′-TGTTGCTGCAGTGGGCAA -3′. PCR conditions were: 1 cycle at 95 °C for 5 min, followed by 35 cycles at 95 °C for 30 s, 55 °C for 30 s, and 72 °C for 2 min. The final extension step was carried out at 72 °C for 10 min. The PCR products were analyzed on 1% agarose gel. The ligation of the PCR product into the pcDNA3.1/V5-His TOPO vector was performed according to the manufacturer’s recommendation. The resulting pcDNA3.1/mPacer-V5-His plasmid was amplified in E. coli DH5α, and the correct insertion of the Pacer gene was verified by sequencing. The vector encoding hPacer-V5 was designed using the VectorBuilder online tool (Cyagen) and subsequently completely synthesized by and purchased from Cyagen. Plasmid for FLAG-tagged Beclin1 were kindly provided by Beth Levine [40].

Cell culture, transfection, and viral transduction

We used HEK293T cells for immunoprecipitation assays and the NSC34 cell line as a motoneuron-cell like a model [41] for autophagy experiments, subcellular localization studies and mutant SOD1 aggregation and cell death analysis. NSC34 and HEK 293 T cells were grown in Dulbecco’s modified Eagle’s medium (DMEM, Gibco, 12,800,017) supplemented with 10% fetal bovine serum (FBS, Gibco, 10,438,026) and 1% penicillin/streptomycin (Biological Industries, DW1012), in a 5% CO2 incubator at 37 °C. All transfections were performed using the Effectene reagent (Qiagen, 301,427) according to the manufacturer’s recommendations. Plasmid DNAs were prepared using the Qiagen plasmid midi kit (Qiagen, 12,143) or the Axygen miniprep kit (Axygen, AP-MN-P-250). For viral transductions, lentivirus production was performed with Lenti-vpak (Origene, TR30037), according to the manufacturer’s recommendation. Briefly, HEK293T cells were transfected with scramble control (shCtrl) and shPacer constructs. Medium was replaced with fresh DMEM after 12 h, and viral supernatant was collected after 36 h and again after another 24 h. NSC34 cells were transduced with 2 ml viral supernatant. Stable NSC34 shCtrl and shPacer cell lines were established with Puromycin (Sigma, P8833-25 mg) (10 μg/ml) selection.

Autophagy analysis

NSC34 cells were transfected with vectors encoding mouse Pacer-V5 or empty vector (pcDNA3.1/V5) (Invitrogen) or with vectors targeting mouse Pacer mRNA, shPacer A (GGACACAGAAGACGCCAGCAGGTTACGTG), shPacer B (TGGTACAACGGCCATTGGAGAGCTGTGTT) or a scramble control vector (shCtrl) (OriGene). To induce autophagy cells were treated with rapamycin (200 nM, Enzo Life Sciences, BML-A275) for 6 h. For the autophagy flux, cells were washed once with PBS and maintained with EBSS (Gibco, 24,010,043) medium for 0.5, 2, or 4 h. To inhibit autophagosome-lysosome fusion, cells were treated with a mix of bafilomycin A1 (0.5 μM), and protease inhibitors pepstatin (10 μg/ml), and E64D (10 μg/ml) for 4 h, all purchased from Merck.

Immunofluorescence assay

NSC34 cells were seeded on coverslips and grown overnight. Briefly, cells were transfected and after 24 h cells washed in PBS, fixed with 4% paraformaldehyde (Merck) for 10 min at room temperature, permeabilized with 0.1% Triton X-100 (Merck, 9036-19-5) and 5% gelatin from cold water fish (Sigma, 9000-70-8) for 2 h at room temperature in a moisture chamber. Antibodies and concentrations employed were: mouse Pacer (custom-made from Abmart), 1:100; rabbit anti-Beclin1 (Santa Cruz Biotechnology, sc-11,427), 1:100. Secondary antibodies were used as follows: anti-mouse Alexa 555 (Thermo Fisher Scientific, A28180), 1:1000 and anti-rabbit Alexa 488 (Thermo Fisher Scientific, A27034), 1:1000. Nuclei were stained with Hoechst 33342 (Life Technologies, H3570)1:1000. Coverslips were mounted with Fluoromount G. Fixed cells were imaged with a Leica TCS SP8 confocal microscope. ImageJ and LAS X were employed to process the stacked images. The co-localization analysis was performed as in [42]. Briefly, confocal images were processed using CDA software. Applying the same thresholds for all experimental conditions, the software provides a coefficient of colocalization (Pearson’s correlation coefficient), which was used comparatively.

Immunoprecipitation assay

HEK293T cells were co-transfected with vectors encoding mouse Pacer-V5 and Flag-tagged Beclin1. 48 h later, cell extracts were collected, centrifuged and resuspended in 500 μl of lysis buffer (0.2% NP40, 100 mM KCl, 50 mM Tris at pH 7.5, 150 mM NaCl, 250 mM PMSF) containing protease inhibitor cocktail 1 X (Thermo Fisher Scientific, A32955). After incubation overnight on ice, total cell extracts were subjected to immunoprecipitation (IP) with anti-V5 antibody conjugated-agarose beads (MBL International, 3315) for 2 h at 4 °C on a wheel rotor. Subsequently, beads were washed twice with lysis buffer and once with lysis buffer containing 500 mM NaCl. Protein complexes were eluted with V5 peptide. The input and IP eluate were separated by SDS-PAGE and assessed by Western blot analysis.

Western blot analysis

Cells and tissues were homogenized in Triton buffer (1.0% Triton in PBS) containing protease inhibitor cocktail 1X by sonication. Protein concentration was determined by BCA assay (Pierce Thermo Fisher Scientific, 23,225). Antibody and dilutions used were: mouse anti-human-Pacer (Novus, B01P), 1:1000, rabbit anti-Rubicon (Cell Signaling, 8465), 1:1000, rabbit anti-LC3B (Cell Signaling Technology, 2575), 1:1000, mouse anti-SQSTM1/p62 (Abcam, ab56416), 1:10000, mouse anti-V5 (Thermo Fisher Scientific, R960-CUS), 1:4000, rabbit anti-Beclin1 (Santa Cruz Biotechnology, sc-11,427),1:1000, mouse anti-GFP (Santa Cruz Biotechnology, sc-9996), 1:2000, sheep anti-SOD1 (Calbiochem, 574,597), 1:1000, and custom mouse anti-Pacer antibody manufactured by Abmart raised against a 14 aa peptide of the N-terminal domain of mouse Pacer, 1:1000. Rabbit anti-HSP90 (Santa Cruz Biotechnologies, sc-7947) or rabbit anti-β-Actin (Cell Signaling Technology, 4967) were used as loading controls, 1:3000 or 1:1000, respectively. Secondary HRP-conjugated anti-rabbit (Life Technologies, 656,120), anti-mouse (Life Technologies, 626,520) or anti-sheep (Sigma-Aldrich, A3415) antibodies were employed at a 1:3000 dilution.

Analysis of SOD1 aggregation

NSC34 cells were transiently transfected with the SOD1 expression constructs (SOD1WT and SOD1G93A) fused to EGFP. To verify the SOD1 aggregate formation, we employed three assays: (i) Insolubility in non-denaturing detergents of SOD1 species was assessed by Western blot analysis. After 48 h of transfection, total cell extracts were prepared in 1% Triton buffer in PBS, according to the Western blot protocol described above. The samples were treated with or without reducing agent 100 mM dithiothreitol (DTT) (Thermo Fisher Scientific, R0861). (ii) SOD1 aggregate formation was verified by filter trap assay as detailed in [43]. Briefly, 1 μg/μl protein NSC34 cell extracts treated with or without DTT were filtrated through a 0.2 μm cellulose acetate membrane by using a BRL dot-blot filtration unit. SOD1 aggregates were detected with anti-SOD1 antibody, following the immunological protocol described above. (iii) SOD1 inclusions were monitored by confocal microscopy. In brief, NSC34 cells were seeded on coverslips, transfected with corresponding vectors. After 48 h cells were fixed with 4% paraformaldehyde in PBS for 20 min at room temperature. Fixed cells were imaged with a Leica TCS SP8 confocal microscope with a 40X objective magnification. ImageJ and LAS X were employed to quantify EGFP-positive cells with inclusions and to process the stacked images. (iv) For the isolation of detergent-insoluble protein aggregates, NSC34 cells were seeded in 6-well plates. After 24 h cells were transiently transfected with the SOD1 expression constructs (SOD1WT and SOD1G93A) fused to EGFP together with shCtrl or shPacer and hPacer-V5. After 48 h of transfection, the cells were collected and centrifuged at 4 °C for 5 min at 900×g the cell pellet was re-suspended with 200 μl buffer TEN (10 mM Tris-HCl, 1 mM EDTA, 10 mM NaCl, pH 8.0) buffer, containing protease inhibitor cocktail 1 X (Thermo Fisher Scientific, A32955) supplemented with 0.5% of non-ionic detergent Nonidet P-40 (NP-40) (EMD Millipore Corp., 9016-45-9), the samples were sonicated 10 s on ice, 40 μl from the total lysate was saved as Input. The remaining lysate was cleared by centrifugation at 800×g for 10 min at 4 °C. To separate the soluble protein fraction and the detergent-insoluble protein aggregates the supernatant was then submitted to centrifugation at 16900×g for 45 min at 4 °C, [44]. The pellet containing the aggregates was washed by addition of TEN buffer and centrifuged again at 16900×g for 45 min at 4 °C. The washed pellet was solubilized in TEN buffer containing 0.5% SDS and protease inhibitor cocktail followed by Western blot analysis under reducing conditions.

Cell death assay

NSC34 cells stably transduced with shPacer and shCtrl constructs and then transfected with EGFP, SOD1WT, SOD1G93A, and hPacer-V5, after 48 h and 72 h the cells were collected and stained with 250 nM of SytoxBLue™ (Thermo Fisher Scientific, S34857). SytoxBlue™ positive cells were monitored by Flow cytometry using a BD FACSVerse™ flow cytometer. FlowJo software version 7.6.1. was used to analyze data.

Statistical analysis

GraphPad Prism software was used for statistical analysis. All data were analyzed by one-way ANOVA or Student’s t-test. N indicates the number of biological replicates. On all graphs, error bars represent SEM.

Results

ALS network analysis links C13orf18/Pacer to autophagy

We used a convergent network analysis approach based on [26] to integrate ALS specific high-throughput data, such as HUGE phenopedia and copy number variation (CNV) data (Additional file 1: Table S1) [33-36], with the global protein-protein interaction network. This approach allowed us to build interaction networks with all ALS associated genes, thus uncovering new connections to previously unrecognized genes/proteins as being part of the ALS disease network (Fig. 1a; Additional file 3: Figure S1 and Additional file 2: Table S2). An evidence-based output of 241 genes/proteins organized in 12 ALS-specific subnetworks was obtained (Additional file 3: Figure S1 and Additional file 2: Table S2). We selected Pacer (C13orf18) for further experimental studies, mainly because it was displayed as a component of a subnetwork composed of itself and Beclin1 (Fig. 1a and Additional file 3: Figure S1h), an interaction previously reported in a proteomic study [30]. Beclin1 is a well-characterized core subunit of distinct phosphatidylinositol 3 kinase (PI3K) complexes, which mediate multiple steps during the autophagy process. A role for Beclin1 had been implicated in ALS pathology since its levels were found to be increased in the spinal cord from ALS mouse models, as well as in postmortem sALS spinal cord samples [22, 45, 46]. Through its interaction with Beclin1, Pacer was suggested to functionally connect to the autophagy process [30], which recently was further confirmed by two studies that reported the interaction of Pacer with several components of the Beclin1 complex, including Beclin1, UVRAG, PI3KR4 and PI3KC3 [32, 47]. Hence, we hypothesized that Pacer could play a regulatory role in the autophagy pathway through interaction with Beclin1 and affect ALS pathology through this pathway. Furthermore, an SNP discovered in the 3’UTR of Pacer in a cohort of ALS patients suggests that it could be a modifier of disease [31].
Fig. 1

Pacer is identified as a protein involved in autophagy in the context of an ALS disease network. a Scheme for the convergent analysis performed for ALS data. CNV, copy number variation; IPA, Ingenuity pathway analysis. b Scheme of localization of a total of 8 peptides (dark gray boxes) used to generate an antibody specific for mouse Pacer. Only one peptide (pink box) resulted in the generation of a specific antibody. The aa sequence of this peptide is shown. c, The specificity of the antibody generated in b was tested by depleting NSC34 cells of Pacer expression using two shRNA constructs targeting mouse Pacer mRNA (shPacer A and shPacer B). As a mock control, a scrambled shRNA (shCtrl) construct was used. Pacer was detected by a custom-made antibody by Western blot, a non-transfected (NT) is shown. A representative of 3 independent experiments is shown. d, e NSC34 cells were treated with rapamycin for 6 h. d mRNA extraction and quantitative PCR was performed (n = 4). e, Extracts of NSC34 cells were subjected to Western blot analysis. Protein levels of Pacer, Beclin1, and LC3-II were verified. β-Actin serves as a loading control. f IP was performed with extracts from HEK293T cells transfected with expression vector for mouse Pacer-V5 or empty control vector for 48 h. IP was performed using the V5 tag. The interaction of V5-tagged Pacer with endogenous Beclin1 was analyzed by Western blot. The inputs and elutions are shown. g, h The colocalization of endogenous Pacer and Beclin1 in NSC34 cells under basal (NT) and Rapamycin (Rapa) treatment was was analyzed by g, confocal microscopy and h, quantified using Pearson’s coefficient (n = 3). The nuclei are visualized with Hoechst. Mean and SEM with only statistical significant p-values are shown: *, p ≤ 0.05

Pacer is identified as a protein involved in autophagy in the context of an ALS disease network. a Scheme for the convergent analysis performed for ALS data. CNV, copy number variation; IPA, Ingenuity pathway analysis. b Scheme of localization of a total of 8 peptides (dark gray boxes) used to generate an antibody specific for mouse Pacer. Only one peptide (pink box) resulted in the generation of a specific antibody. The aa sequence of this peptide is shown. c, The specificity of the antibody generated in b was tested by depleting NSC34 cells of Pacer expression using two shRNA constructs targeting mouse Pacer mRNA (shPacer A and shPacer B). As a mock control, a scrambled shRNA (shCtrl) construct was used. Pacer was detected by a custom-made antibody by Western blot, a non-transfected (NT) is shown. A representative of 3 independent experiments is shown. d, e NSC34 cells were treated with rapamycin for 6 h. d mRNA extraction and quantitative PCR was performed (n = 4). e, Extracts of NSC34 cells were subjected to Western blot analysis. Protein levels of Pacer, Beclin1, and LC3-II were verified. β-Actin serves as a loading control. f IP was performed with extracts from HEK293T cells transfected with expression vector for mouse Pacer-V5 or empty control vector for 48 h. IP was performed using the V5 tag. The interaction of V5-tagged Pacer with endogenous Beclin1 was analyzed by Western blot. The inputs and elutions are shown. g, h The colocalization of endogenous Pacer and Beclin1 in NSC34 cells under basal (NT) and Rapamycin (Rapa) treatment was was analyzed by g, confocal microscopy and h, quantified using Pearson’s coefficient (n = 3). The nuclei are visualized with Hoechst. Mean and SEM with only statistical significant p-values are shown: *, p ≤ 0.05 No functional commercial antibody was available to detect mouse Pacer. Hence an antibody targeting endogenous mouse Pacer was custom-made for this study by Abmart. Initially, eight peptides unique to the mouse sequence were tested; however, only peptide 43-SWINPLCVQQPLQE-57 generated an antibody that detected one band at the expected size of 72 kDa in the mouse motoneuron cell line NSC34 by Western blot (Fig. 1b and c). Specificity of the antibody was confirmed by knockdown of mouse Pacer using two shRNA constructs targeting its expression (Fig. 1c and Additional file 4: Figure S2a). The expression level of many autophagy genes, e.g., Beclin1, is generally upregulated upon activation of this pathway [48]. We assessed the possible regulation of Pacer expression under autophagy induction in NSC34 cells. Pacer endogenous mRNA and protein levels were increased after treatment with rapamycin, similar to Beclin1 mRNA and protein levels (Fig. 1d and e) as well as LC3B-II protein levels (Fig. 1e). To confirm the interaction of Pacer with Beclin1, we used V5-tagged mouse Pacer (Pacer-V5) in HEK293T cells and performed immunoprecipitation (IP) experiments. Using the V5-tag on Pacer, we observed that endogenous Beclin1 is found in protein complexes with Pacer-V5 (Fig. 1f). By using the custom-made Pacer antibody, we confirmed endogenous Pacer/Beclin1 colocalization in NSC34 cells (Fig. 1g). The Pearson’s correlation coefficient between the two proteins was found to increase from 0.26 under basal conditions to 0.53 under autophagy activation with rapamycin (Fig. 1h). To investigate the presence of Pacer mRNA in tissues relevant to ALS pathogenesis, we assessed Pacer, Rubicon and Beclin1 mRNA levels by quantitative PCR in different mouse tissues (cortex, cerebellum, hippocampus, spinal cord, muscle, and liver) obtained from 100 days-old wild-type C57BL/6 mice (4 males and 4 females). The three genes displayed elevated mRNA expression in the central nervous system (CNS) when compared to muscle or liver (Additional file 4: Figure S2b). Pacer and Rubicon showed higher expression in the spinal cord and cortex, while Beclin1 expression was elevated in the hippocampus, confirming previous findings (Additional file 4: Figure S2b) [49]. The same antibody described above was subsequently used to detect endogenous mouse Pacer in mouse spinal cord tissue. In the lumbar spinal cord of 60 days old wild-type mice, Pacer cell-type expression was investigated by immunofluorescent staining and confocal microscopy. Strikingly, Pacer appeared to be expressed mainly in neurons in the spinal cord, with no obvious detection in astrocytes (Additional file 4: Figure S2c).

Pacer levels are decreased in ALS pathology

We next evaluated possible alterations in Pacer levels in human postmortem spinal cord samples derived from patients with sALS compared to non-ALS patients (Additional file 5: Table S3). We found a significant decrease in Pacer protein levels in the lumbar spinal cord of sALS patients compared to age-matched healthy control subjects (Fig. 2a). A similar trend was observed in the thoracic spinal cord, yet no tendency was found in the cervical spinal cord (Fig. 2a). However, for both cervical and thoracic sections tissues from only two control cases were available. Interestingly, in sALS patients the decrease of Pacer protein levels correlated with the increase of Rubicon protein levels in the same patient, a phenomenon observed in all spinal cord sections (Fig. 2a). While Pacer mRNA levels were not altered, Rubicon mRNA levels were increased in the lumbar spinal cord of sALS patients (Additional file 6: Figure S3a and b). These findings indicate that at least the lumbar region of the spinal cord of sALS patients displays a significant loss of Pacer protein levels, suggesting a possible involvement of Pacer in ALS pathogenesis.
Fig. 2

Pacer levels are reduced during ALS pathology. a Human Pacer (hPacer) and human Rubicon (hRubicon) protein levels were determined in post-mortem spinal cord sections from sALS patients and age-matched control subjects. Left panel, cervical spinal cord section with Controls n = 2 and sALS patients n = 6; middle panel, thoracic spinal cord section with Controls n = 2 and sALS patients n = 7; and right panel, lumbar spinal cord section with Controls n = 6 and sALS patients n = 7. β-Actin serves as a loading control. Densitometric quantifications of hPacer and hRubicon normalized to β-Actin levels are shown. b Pacer and Rubicon protein levels were determined in lumbar spinal cord samples of late symptomatic TDP43A315T transgenic mice (TDP43A315T-Tg, n = 5) and their non-transgenic littermate controls (n = 3), respectively. TDP43 aggregate levels under non-reducing (−DTT) conditions are shown as positive controls. β-Actin serves as a loading control. Densitometric quantifications of Pacer protein levels normalized to β-Actin levels are shown. c, Pacer and Rubicon protein levels were determined in the lumbar spinal cord of late symptomatic SOD1G93A transgenic mice (SOD1G93A-Tg) and their non-transgenic littermate controls (both groups n = 7). p62 protein levels were detected as a positive control of impaired autophagy. SOD1 aggregate levels under non-reduced (−DTT) conditions are shown as a positive control for SOD1G93A-Tg mice. β-Actin serves as a loading control. Densitometric quantifications of Pacer protein levels normalized to β-Actin levels are shown. In a-c Statistical analyses were performed using Student’s t-test. Mean and SEM with only statistical significant p-values are shown: *, p ≤ 0.05; **, p ≤ 0.01; and ***, p ≤ 0.001

Pacer levels are reduced during ALS pathology. a Human Pacer (hPacer) and human Rubicon (hRubicon) protein levels were determined in post-mortem spinal cord sections from sALS patients and age-matched control subjects. Left panel, cervical spinal cord section with Controls n = 2 and sALS patients n = 6; middle panel, thoracic spinal cord section with Controls n = 2 and sALS patients n = 7; and right panel, lumbar spinal cord section with Controls n = 6 and sALS patients n = 7. β-Actin serves as a loading control. Densitometric quantifications of hPacer and hRubicon normalized to β-Actin levels are shown. b Pacer and Rubicon protein levels were determined in lumbar spinal cord samples of late symptomatic TDP43A315T transgenic mice (TDP43A315T-Tg, n = 5) and their non-transgenic littermate controls (n = 3), respectively. TDP43 aggregate levels under non-reducing (−DTT) conditions are shown as positive controls. β-Actin serves as a loading control. Densitometric quantifications of Pacer protein levels normalized to β-Actin levels are shown. c, Pacer and Rubicon protein levels were determined in the lumbar spinal cord of late symptomatic SOD1G93A transgenic mice (SOD1G93A-Tg) and their non-transgenic littermate controls (both groups n = 7). p62 protein levels were detected as a positive control of impaired autophagy. SOD1 aggregate levels under non-reduced (−DTT) conditions are shown as a positive control for SOD1G93A-Tg mice. β-Actin serves as a loading control. Densitometric quantifications of Pacer protein levels normalized to β-Actin levels are shown. In a-c Statistical analyses were performed using Student’s t-test. Mean and SEM with only statistical significant p-values are shown: *, p ≤ 0.05; **, p ≤ 0.01; and ***, p ≤ 0.001 We then evaluated Pacer levels in tissue derived from two ALS mouse models, TDP43A315T and SOD1G93A transgenic mice (TDP43A315T-Tg and SOD1G93A-Tg, respectively) [37, 38, 50]. We assessed Pacer mRNA and protein levels in the lumbar spinal cords of late symptomatic transgenic mice compared to their respective non-transgenic (non-Tg) littermates in the age range of 159 to 189 days for TDP43A315T-Tg mice and 131 to 152 days for SOD1G93A-Tg mice. Pacer protein levels were significantly diminished in the spinal cords of symptomatic TDP43A315T-Tg and SOD1G93A-Tg mice compared to their respective non-Tg controls (Fig. 2b and c). In comparison, Rubicon protein levels were not affected in either mouse model (Fig. 2b and c). Both Pacer and Rubicon mRNA levels were not altered in either mouse model (Additional file 6: Figure S3c and S3d). To investigate if the localization of Pacer to neurons is affected under disease condition, we performed immunofluorescence staining and confocal microscopy of lumbar spinal cord sections of symptomatic SOD1G93A-Tg mice and their age-matched littermate controls (in the age range from 138 to 156 days). We focused on the ventral horn region of the spinal cord where motoneurons are found. In non-Tg animals, Pacer localized mainly to neurons, including motoneurons in the ventral horn (Fig. 3a and b, upper panels). In symptomatic SOD1G93A-Tg mice less overall Pacer staining in neurons was found, possibly due to a lower number of surviving neurons in the ventral horn of the spinal cord (Fig. 3a and b, lower panels). Surprisingly, in SOD1G93A-Tg mice Pacer also localized to astrocytes, which was not observed in non-Tg control mice (Fig. 3b, lower panel). Like Pacer, Rubicon was also preferentially expressed in neurons, in non-Tg control mice (Fig. 3c and d, upper panels). Similar to Pacer, Rubicon staining was diminished in neurons in symptomatic SOD1G93A-Tg mice possibly due to a motoneuronal loss in the ventral horn of the spinal cord (Fig. 3c and d, lower panels).
Fig. 3

Pacer and Rubicon localization in the spinal cord of symptomatic SOD1G93A transgenic mice. Confocal microscopy of lumbar spinal cord sections of late symptomatic (138 to 156 days old) SOD1G93A transgenic mice (SOD1G93A-Tg) compared to age-matched non-transgenic controls (non-Tg). Z-stack of confocal images, detection of Pacer, the neuronal marker NeuN in a, or the astrocytic marker GFAP in b, detection of Rubicon, the neuronal marker NeuN in c, or the astrocytic marker GFAP in d. a-d, Nuclei are stained with DAPI. Scale bar: 20 μm

Pacer and Rubicon localization in the spinal cord of symptomatic SOD1G93A transgenic mice. Confocal microscopy of lumbar spinal cord sections of late symptomatic (138 to 156 days old) SOD1G93A transgenic mice (SOD1G93A-Tg) compared to age-matched non-transgenic controls (non-Tg). Z-stack of confocal images, detection of Pacer, the neuronal marker NeuN in a, or the astrocytic marker GFAP in b, detection of Rubicon, the neuronal marker NeuN in c, or the astrocytic marker GFAP in d. a-d, Nuclei are stained with DAPI. Scale bar: 20 μm To assess if the decrease in Pacer levels under disease conditions is simply due to the loss of motoneurons in the symptomatic spinal cord or if Pacer levels are affected already earlier, we evaluated Pacer levels also in pre-symptomatic SOD1G93A-Tg and age-matched non-Tg mice (60 days). Pacer levels were reduced in pre-symptomatic SOD1G93A-Tg, similar to Rubicon, Beclin1 and LC3-II (Additional file 7: Figure S4a), which could be due to the activation of the autophagy pathway. Additionally, the localization of Pacer in the spinal cord of pre-symptomatic SOD1G93A-Tg and age-matched non-Tg mice (60 days) was investigated. Pacer was found to localize mainly to neurons in both Tg and non-Tg animals (Additional file 7: Figure S4b and S4c). No staining was observed in astrocytes in pre-symptomatic mice (Additional file 7: Figure S4c). Similar as reported in [21, 51], we used metalloproteinase-9 (MMP9) as a marker for vulnerable neurons known to degenerate in ALS mouse models. Pacer was found to localize to MMP9-positive neurons in both SOD1G93A-Tg and non-Tg mice (Additional File 8: Fig. S5a and S5b), nevertheless, in SOD1G93A-Tg mice, the immunofluorescence labeling of Pacer appeared to be decreased compared to non-Tg mice (Additional file 8: Figure S5b). Together with our results in Western blot, these data suggest that vulnerable neurons display a decrease in Pacer expression already at presymptomatic stages in the SOD1G93A ALS mouse model.

Diminished Pacer levels impair autophagy

Since Pacer was indicated by our network analysis to associate with Beclin1 and its levels were decreased in ALS-affected tissue, we assessed the possible role of Pacer expression in autophagy using a loss-of-function approach. To determine if the loss of Pacer affects the autophagy process, we monitored autophagy flux in NSC34 cells deficient for Pacer. We depleted Pacer in NSC34 cells using short-hairpin RNAs (shPacer A and B) (Fig. 1c and Additional file 4: Figure S2a) and determined the levels of key autophagy markers in NSC34 cells under serum deprivation conditions (EBSS) in the presence or absence of lysosomal inhibitors. Depletion of Pacer decreased LC3-II flux in NSC34 cells (Fig. 4a and b), suggesting an impairment of the autophagy process. Autophagy substrate p62 and Beclin1 were not significantly affected (Fig. 4a and Additional file 9: Figure S6a and S6b). Taken together, our results suggest that reduced levels of Pacer negatively affect the autophagy pathway.
Fig. 4

Depletion of Pacer impairs autophagosome formation and promotes SOD1 aggregation. a Autophagy flux under Pacer knockdown. Cells were treated with EBSS medium or/and lysosome inhibitors (Lys. Inh.) for 0.5, 2 and 4 h. Cell extracts were subjected to Western blot. As a mock control, a scrambled shRNA (shCtrl) construct was used. Pacer, Beclin1, p62 and LC3-II formation levels were determined. β-Actin serves as a loading control. b Densitometric quantifications of LC3-II flux (n = 3). One-way ANOVA and Bonferroni’s post hoc tests were performed.Mean and SEM with only statistically significant p-values are shown: *, p ≤ 0.05. c-f, NSC34 cells depleted of Pacer were transiently co-transfected with expression vectors for human wild-type or mutant SOD1G93A fused to EGFP. When indicated, human Pacer (hPacer-V5) was co-expressed. c and d, after 48 h, SOD1 aggregation was assessed under non-reducing (−DTT) conditions. Cell extracts were prepared in 1% Triton X-100 buffer or 1% SDS buffer for Western blot and filter trap assays, respectively. In c HSP90 serves as a loading control. e SOD1 inclusions in NSC34 cells were assessed by confocal microscopy. Percentages of cells with SOD1WT-EGFP or SOD1G93A-EGFP inclusions are shown. f Percentage of cell death was quantified at 72 h (SytoxBlue positive, SB+) in NSC34 stable lines expressing shPacer or shCtrl transiently transfected with EGFP, SOD1WTor SOD1G93A, and hPacer-V5. In e and f statistical analyses were performed using one-way ANOVA and Bonferroni’s post-hoc tests. Mean and SEM with only statistically significant p-values are shown: *, p ≤ 0.05; **, p ≤ 0.01; and ***, p ≤ 0.001

Depletion of Pacer impairs autophagosome formation and promotes SOD1 aggregation. a Autophagy flux under Pacer knockdown. Cells were treated with EBSS medium or/and lysosome inhibitors (Lys. Inh.) for 0.5, 2 and 4 h. Cell extracts were subjected to Western blot. As a mock control, a scrambled shRNA (shCtrl) construct was used. Pacer, Beclin1, p62 and LC3-II formation levels were determined. β-Actin serves as a loading control. b Densitometric quantifications of LC3-II flux (n = 3). One-way ANOVA and Bonferroni’s post hoc tests were performed.Mean and SEM with only statistically significant p-values are shown: *, p ≤ 0.05. c-f, NSC34 cells depleted of Pacer were transiently co-transfected with expression vectors for human wild-type or mutant SOD1G93A fused to EGFP. When indicated, human Pacer (hPacer-V5) was co-expressed. c and d, after 48 h, SOD1 aggregation was assessed under non-reducing (−DTT) conditions. Cell extracts were prepared in 1% Triton X-100 buffer or 1% SDS buffer for Western blot and filter trap assays, respectively. In c HSP90 serves as a loading control. e SOD1 inclusions in NSC34 cells were assessed by confocal microscopy. Percentages of cells with SOD1WT-EGFP or SOD1G93A-EGFP inclusions are shown. f Percentage of cell death was quantified at 72 h (SytoxBlue positive, SB+) in NSC34 stable lines expressing shPacer or shCtrl transiently transfected with EGFP, SOD1WTor SOD1G93A, and hPacer-V5. In e and f statistical analyses were performed using one-way ANOVA and Bonferroni’s post-hoc tests. Mean and SEM with only statistically significant p-values are shown: *, p ≤ 0.05; **, p ≤ 0.01; and ***, p ≤ 0.001

Pacer repression promotes SOD1 aggregate accumulation and triggers cell death

To determine the consequences of reduced Pacer levels in the ALS pathogenesis which we observed in vivo (Fig. 2), we assessed the impact of its repression on mutant SOD1 aggregation and neuronal cell death. Knocking down Pacer in NSC34 cells led to increased mutant SOD1 disulfide-dependent aggregation (Fig. 4c). Interestingly, we also observed the spontaneous aggregation of wild-type SOD1 upon loss of Pacer (Fig. 4c), a phenomenon described in sALS cases [52-54]. Similar results were obtained by determining the levels of Nonidet P-40 (NP-40) detergent-insoluble protein aggregates (Additional file 9: Figure S6c), as well as by filter trap, an assay that detects protein aggregates by size using a cellulose acetate filter membrane with 200 nm pores (Fig. 4d). Since our shRNA constructs target mouse Pacer exclusively, we restored Pacer levels by exogenous expression of human Pacer (hPacer-V5) (Additional file 9: Figure S6d and S6e). The re-expression of hPacer-V5 restored SOD1 aggregation levels to a similar extent to those observed in control cells (Fig. 4c, d and Additional file 9: Figure S6c). Furthermore, confocal microscopy of SOD1 confirmed these findings. Depletion of Pacer in NSC34 cells led to an increased number of inclusions formed by SOD1G93A (Fig. 4e and Additional file 10: Figure S7), whereas it had dramatic effects on SOD1WT, which built large de novo inclusions similar in size to aggregates observed for mutant SOD1 (Fig. 4e and Additional file 10: Fig. S7). No effect of Pacer depletion on EGFP alone was observed (Fig. 4e and Additional file 10: Figure S7). Since impaired autophagy and increased protein aggregation are correlated with neuronal death, we investigated the effect of knocking down Pacer in NSC34 cells expressing wild-type or mutant SOD1. We found that the depletion of Pacer sensitizes cells to SOD1WT or SOD1G93A toxicity, whereas cells expressing EGFP alone are unaffected (Fig. 4f and Additional file 10: Figure S7a and S7b). In comparison, the depletion of Rubicon did not result in cell death in NSC34 cells expressing mutant SOD1 (Additional file 10: Figure S7c and S7d). Furthermore, the reconstitution with hPacer-V5 rescued the survival of cells expressing SOD1WT or SOD1G93A (Fig. 4f). Human Pacer expression even improved the survival rate when compared to cells expressing scrambled shRNA construct (shCtrl cells) in the presence of SOD1G93A (Fig. 4f). Taken together these results indicate an important role for Pacer in maintaining proteostasis in motoneurons by promoting SOD1 aggregate removal and sustaining motoneuron survival.

Discussion

Neurodegenerative diseases, such as AD, PD, and ALS, are multifactorial, involving a combination of genetic and environmental factors, as well as age as the primary risk factor. Genetic studies in ALS have made significant advances in the understanding of disease pathogenesis by using whole genome or whole exome sequencing strategies (reviewed in [2]). However, the primary cause of approximately half of fALS cases and the majority of sALS cases remains unexplained. The use of systems biology approaches to study neurodevelopmental and neurodegenerative diseases has recently proven to aid our understanding of underlying disease mechanisms by unraveling new genes, pathways or subnetworks responsible for an illness which would not have been recognized using traditional approaches. Here we describe Pacer, a protein previously proposed as a tumor suppressor and cancer biomarker [55-57] and recently reported to be associated with autophagy [32], as being immersed in the ALS disease network. We performed a convergent analysis by merging all ALS data available to uncover pathways and associated new genes involved in the disease. By retrieving and integrating data from different model systems and patient studies, experimental bias was filtered out, and only relevant mechanisms may be uncovered. From the list of genes obtained through this analysis, we selected the protein Pacer, previously known as C13orf18, based on its putative role in autophagy, a compromised pathway during ALS pathogenesis. At the time, the only data available for Pacer was based on a proteomic study of the autophagy network, which suggested a role in the autophagy pathway via interaction with Beclin1 [30]. Furthermore, a connection to ALS was suggested by the identification of an SNP in the 3’UTR of the Pacer gene in a cohort of sALS patients [31]. The specific consequence of the SNP in the 3’UTR of the Pacer gene in ALS pathogenesis, however, need to be more explored in future studies. The likely presence of variants in the UTR or intronic regions of ALS genes has been exemplified by the most common genetic modification known to cause ALS, C9orf72 intronic repetitions [58]. Furthermore, variants in untranslated regions of well-known ALS-causing genes, including SOD1, TARDBP, FUS and UBQLN2, have been recently reported [59]. Although these variants do affect the amino acid sequence of the affected the protein, they can have important effects on other aspects, such as expression level. For instance, Al-Chalabi and co-workers showed that variants in the 3’UTR of the FUS gene found in Italian ALS patients promote mislocalization of the FUS protein and result in a dramatically increased expression of this protein [60, 61]. Similarly, variants found in the 3’UTR of the TARDBP gene also regulate its expression by affecting the RNA stability of its transcripts [62]. Here, we found Pacer levels to be decreased in sALS patients, similarly to two fALS mouse models, hence Pacer may participate in a transversal mechanism to protect neurons against disease. Recently, Pacer was described as a positive regulator of autophagosome maturation, through its binding to the functionally distinct UVRAG-Beclin1-Vsp34 and UVRAG-HOPS complexes [32]. Pacer is proposed to target both protein complexes to the autophagosome membrane for activation [32]. Beclin1 is a core subunit of distinct PI3K complexes, which mediate multiple steps during the autophagy process. Beclin1 levels were found to be increased in the spinal cord from ALS mouse models, as well as in postmortem sALS spinal cord samples [22, 45, 46]. We have shown that haploinsufficiency of Beclin1 in a mutant SOD1 mouse model increases the lifespan of double-transgenic mice, despite the increase in SOD1 aggregates [22], consistent with recent findings in Atg7 deficient animals [21]. In another study, however, targeting Beclin1 in two different mouse models of ALS showed opposite results [46]. Here, we show that Pacer is expressed in the CNS, particularly in neurons in the spinal cord, suggesting it to have an essential role in neuronal cells in this tissue. We show that Pacer levels are decreased in the lumbar region of the spinal cord in two fALS mouse models in the late stage of the disease and biopsies of sALS patients. Furthermore, we found that while Pacer protein levels decrease in the late stage of disease in both mice and humans, Rubicon protein levels are maintained in mice or increased in humans. In histological studies, we found that in late symptomatic SOD1G93A transgenic mice the Pacer staining was diminished in motoneurons, probably due to the loss of motoneurons, whereas its expression was augmented in astrocytes. Progressive reactive astrogliosis is a feature of the ALS pathogenesis, mainly found surrounding degenerating neurons [63]. Changes in the expression of autophagy proteins specifically in astrocytes during ALS have not been reported to our knowledge. Our finding that Pacer is also expressed in astrocytes in the symptomatic stage of an ALS mouse model whereas it is only found in neurons in the presymptomatic stage could imply a role of Pacer in the inflammatory response of the astrocytes during disease progression, however further investigastions are necessaries to clarify this point. Similar to Pacer, Rubicon also was localized primarily to neurons in the lumbar spinal cord in non-Tg mice. Nevertheless, in late symptomatic SOD1G93A-Tg animals Rubicon localization to motoneurons was diminished similarly to Pacer. However, its expression was augmented in another cell type, other than astrocytes, possibly microglia, which remains to be investigated further. Hence, our results suggest that the expression of both Pacer and Rubicon is highly dynamic and can change depending on the cell type as well as under ALS disease condition. Additionally, our results raise caution for the interpretation of Western blot results which represent overall protein levels and cannot distinguish changes of expression in various cell types, such we have observed in our histological analysis for both Pacer and Rubicon. To investigate whether the loss of Pacer during the late stage of disease signifies a possible involvement in ALS pathogenesis or is only representative of the loss of vulnerable neurons during the course of the disease, we also determined its levels and localization during the presymptomatic stage of the disease at age 60 days in the SOD1G93A mouse model. We found that total Pacer levels are already significantly decreased in presymptomatic SOD1G93A-Tg mice, while we do not observe any neuronal loss or signs of astrogliosis, as has been reported [64]. In the presymptomatic stage, Pacer appears to be expressed exclusively in neurons in the lumbar spinal cord in SOD1G93A-Tg mice, comparable to non-Tg littermate controls, nevertheless its overall signal seemed reduced in transgenic mice, possibly reflecting its decreased total protein level observed in Western blot. To show that Pacer localizes to the neurons that are lost later during disease progression, we performed co-staining of Pacer with MMP9, a marker for vulnerable motoneurons [21, 51]. Indeed, we found that Pacer colocalizes with MMP9, hence our data suggests a correlation between the loss of function of Pacer in spinal cord motoneurons and ALS pathogenesis. To study the role of Pacer during ALS pathogenesis, we used the mouse motoneuron-like cell line NSC34. We demonstrated that Pacer expression is up-regulated on the transcriptional and translational level upon autophagy induction, resembling the behavior of other autophagy genes [65, 66]. Furthermore, we confirmed the interaction between Pacer and Beclin1. Comparable results were obtained by Cheng et al. in U2OS cells recently [32]. Pacer shares highest sequence homology with Rubicon, which has become, in recent years, known as an important regulatory protein of autophagy and endocytosis, as well as of LC3-associated phagocytosis [67-71]. Pacer and Rubicon are part of the same protein family due to their shared Rubicon homology (RH) domain. Interestingly, they were reported to perform opposing functions in the autophagy pathway, Rubicon as a negative regulator of the UVRAG-Beclin1-Vsp34 and UVRAG-HOPS complexes through its binding to UVRAG, while Pacer antagonizes Rubicon by competing for UVRAG binding, hence positively influencing autophagy activity [32]. In concordance with these results obtained in HEK293T cells [32], we also find that motoneurons depleted of Pacer are impaired in their autophagy flux. In the current literature, the dependence of motoneurons and the neuromuscular junction (NMJ) on autophagic activity is actively discussed [21, 72, 73]. On one hand due to the importance of autophagy in maintaining the high metabolic rate of motoneurons and on the other hand the requirement of motoneuron autophagy in preserving neuromuscular innervation [21]. Motoneurons have been shown to be extremely dependent on an efficient autophagy flux, referring to an accurate degradation of the formed autophagosomes in the lysosome [21, 72]. Furthermore, during aging a progressive impairment of late endolysosomal processes is observed in neurons, resulting in increased cellular stress owing to the continuous input of new autophagosomes to cope with the turnover of organelles and other cargos (reviewed in [74, 75]). In ALS a progressive decrease in autophagic/endocytic activity in affected motoneurons has been described in fALS mouse models since early stages of the disease [76, 77]. In sALS patients, the levels of autophagy markers in spinal cord postmortem samples were described to be increased, including levels of Beclin1, LC3-II and the autophagy-substrates p62, protein aggregates, and unfunctional organelles, correlating with a dysregulation of the pathway [45, 46]. Finally, mutations in several autophagy-related genes were found associated with fALS, further supporting the notion that autophagy dysfunction is a significant pathogenic mechanism of disease (reviewed in [8]). In our study, we found that Pacer loss of function in a motoneuron cell line results in an augmentation of mutant SOD1 aggregation, as well as an unexpectedly drastic de novo aggregation of wild-type SOD1. This phenomenon may be explained by the disruption of the autophagy process due to loss of Pacer since both wild-type and mutant SOD1 are autophagy substrates [78]. Together these results suggest that Pacer is required for protein aggregate degradation under physiologic and disease conditions and that its loss could lead to a disruption of proteostasis maintenance. In this context, we found that depleting cells of Pacer not only caused the accumulation of protein aggregates in our cellular model but also sensitized cells to death induced by SOD1WT and SOD1G93A expression. Furthermore, the re-expression of Pacer protects against this sensitization and even improved the survival of the NSC34 cells expressing SOD1G93A protein. Overall, these results suggest that Pacer could be an important regulator of the cellular proteostasis and neuronal survival including of vulnerable motoneurons.

Conclusions

In summary, our results suggest a role for Pacer as an essential component of the autophagy machinery in neurons, especially motoneurons, where it promotes the clearance of protein aggregates through the autophagy pathway thereby maintaining proteostasis and sustaining neural survival. Hence, our results suggest Pacer as a potential new candidate to study its therapeutic effect in ALS. Furthermore, our experimental results also validate our unbiased bioinformatic approach, which initially suggested Pacer as a protein involved in ALS pathology through a connection with the autophagy pathway. Like Pacer, many previously uncharacterized genes were identified as part of a functional context associated with complex disorders by these type of systems biology analyses [29, 79, 80]. This approach promises to accelerate gene and/or pathway discovery in complex diseases and can help guide experimental studies that may lead to the identification of biomarkers or therapeutic targets. Table S1. Genes related to ALS in CNV and HUGE databases. (DOCX 31 kb) Table S2. Genes in 12 ALS associated networks. (DOCX 29 kb) Figure S1. ALS convergent analysis subnetworks. a-l, ALS disease subnetworks generated by IPA as an output for the convergent analysis approach presented in Fig. 1a. (PPTX 603 kb) Figure S2. Pacer is expressed in neurons in the spinal cord of wild-type mice a, mRNA levels of Pacer in NSC34 cells depleted of Pacer using shRNA constructs (shRNA A and shRNA B) compared to a scrambled control (shCtrl) were determined by real-time. 18s rRNA levels were used for normalization. Statistical analyses were performed using Student’s t-test. Mean, and SEM with only statistically significant p-values are shown: ***, p ≤ 0.001. b, mRNA levels of Pacer, Rubicon and Beclin1 were determined by quantitative PCR in the spinal cord, cortex, hippocampus, cerebellum, muscle, and liver of wild-type C57BL/6 mice (n=8, 4 females, 4 males). mRNA levels in the liver are used as a reference. c, Confocal microscopy of lumbar spinal cord sections of wild-type mice. Z-stack of confocal images, detection of Pacer, the neuron marker NeuN, or the astrocytic marker GFAP, and DAPI detection by immunofluorescence in C57BL/6 46 mice. Scale bars: 300 μm, and 20 μm. Doted inset indicates where higher magnification images were taken. (PPTX 971 kb) Table S3. Clinical and histopathological data of control and sporadic ALS cases. (DOCX 58 kb) Figure S3. Pacer mRNA levels in the lumbar spinal cord from sALS patients and fALS mouse models. a, Human Pacer (hPacer) and b, human Rubicon (hRubicon) mRNA expression was determined by qPCR in postmortem spinal cord sections from sALS patients and age-matched control subjects. Left panel, cervical spinal cord section with Controls n=2 and sALS patients n=6; middle panel, thoracic spinal cord section with Controls n=2 and sALS patients n=7; and right panel, lumbar spinal cord section with Controls n=6 and sALS patients n=7. β-Actin mRNA levels were used for normalization. c, Pacer and Rubicon mRNA expression was determined by qPCR in lumbar spinal cord samples of late symptomatic TDP43A315T transgenic mice (TDP43A315T-Tg, n=5) and their non-transgenic littermate controls (n=3), respectively. β-Actin levels were used for normalization. d, Pacer and Rubicon mRNA expression was determined in the lumbar spinal cord of late symptomatic SOD1G93A transgenic mice (SOD1G93A-Tg) and their non-transgenic littermate controls (both groups, n=7). 18S RNA levels were used for normalization. (PPTX 362 kb) Figure S4. Pacer levels and localization in the spinal cord of presymptomatic SOD1G93A transgenic mice. a, Pacer, Rubicon, Beclin1, p62, LC3II protein levels were determined in the lumbar spinal cord of presymptomatic 47 (60 days old) SOD1G93A transgenic mice (SOD1G93A-Tg, n=4) and their non-transgenic littermate controls (n=5). SOD1 human levels are shown as a positive control for SOD1G93A-Tg mice. β-Actin serves as a loading control. Densitometric quantifications of Pacer, Rubicon, Beclin1, p62 and LC3II protein levels normalized to β-Actin levels are shown. b, Confocal microscopy of lumbar spinal cord sections of presymptomatic (60 days old) SOD1G93A transgenic mice (SOD1G93A-Tg, lower panel) compared to age-matched non-transgenic controls (non-Tg, upper panel). Z-stack of confocal images, detection of Pacer, the neuronal marker NeuN in b, or the astrocytic marker GFAP in c. b and c, Nuclei are stained with Hoechst. Scale bar: 30 μm. (PPTX 2790 kb) Figure S5. Pacer is expressed in MMP9-positive cells in the presymptomatic spinal cord of SOD1G93A transgenic mice. a, Z-stack confocal images of Pacer with MMP9 in lumbar spinal cord sections of non-transgenic controls (non-Tg, 60 days old) and b, presymptomatic (60 days old) SOD1G93A transgenic mice (SOD1G93A-Tg) at 10X (upper panel, scale bar: 300 μm), 40X (middle panel, scale bar: 30 μm) and 63X (lower panel, scale bar: 15 μm) magnification. Doted insets indicate where higher magnification images were taken. (PPTX 2260 kb) Figure S6. Pacer depletion results in detergent insoluble SOD1 aggregate accumulation. a-b, Densiometric quantification of p62 and Beclin1 levels in the autophagic flux as shown in Fig. 4a. NSC34 cells depleted of Pacer and a scrambled shRNA control (shCtrl) construct were compared (n=3). â-Actin 48 served as a loading control. Statistical analyses were performed using one-way ANOVA and Bonferroni’s post-hoc tests. Mean and SEM are shown. c, NSC34 cells depleted of Pacer were transiently co-transfected with expression vectors for human wild-type or mutant SOD1G93A fused to EGFP. When indicated, human Pacer (hPacer-V5) was co-expressed. NP40-detergent insoluble protein aggregates (NP40 insoluble) were prepared as described in materials and methods. The input is shown as a reference. â-Actin levels in the input serve as a loading control. d-e, Alignment of d shRNA A and e shRNA B to the corresponding target region in mRNA of mouse Pacer and human Pacer. 100% identity between shRNAs A and B to their respective mouse Pacer target sequences. No significant similarity is found to the corresponding region of human Pacer mRNA. (PPTX 2110 kb) Figure S7. Depletion of Pacer leads to SOD1 aggregate accumulation. a, NSC34 cells were transiently transfected with constructs for shCtrl, shPacer, EGFP, SOD1WT-EGFP and SOD1G93A-EGFP, inclusions are shown with white arrows (Representative images of 3 independents experiments). Scale bar 40 μM. b-c, Stable NSC34 cell lines expressing b shPacer and c shRubicon were established. Knockdown was confirmed by Western blot. HSP90 and b-Actin were used as loading controls, respectively. d, Percentage of cell death at 48 h (SytoxBlue positive, SB+) in NSC34 stable lines expressing shPacer, shRubicon, and shCtrl constructs. Cells were transiently transfected with plasmids for EGFP or SOD1G93A-EGFP. In d statistical analyses were performed using one- 49 way ANOVA and Bonferroni’s post-hoc tests. Mean and SEM with only statistically significant p-values are shown: *, p ≤ 0.05; and **, p ≤ 0.01. (PPTX 777 kb)
  80 in total

1.  Haploinsufficiency of TBK1 causes familial ALS and fronto-temporal dementia.

Authors:  Axel Freischmidt; Thomas Wieland; Benjamin Richter; Wolfgang Ruf; Veronique Schaeffer; Kathrin Müller; Nicolai Marroquin; Frida Nordin; Annemarie Hübers; Patrick Weydt; Susana Pinto; Rayomond Press; Stéphanie Millecamps; Nicolas Molko; Emilien Bernard; Claude Desnuelle; Marie-Hélène Soriani; Johannes Dorst; Elisabeth Graf; Ulrika Nordström; Marisa S Feiler; Stefan Putz; Tobias M Boeckers; Thomas Meyer; Andrea S Winkler; Juliane Winkelman; Mamede de Carvalho; Dietmar R Thal; Markus Otto; Thomas Brännström; Alexander E Volk; Petri Kursula; Karin M Danzer; Peter Lichtner; Ivan Dikic; Thomas Meitinger; Albert C Ludolph; Tim M Strom; Peter M Andersen; Jochen H Weishaupt
Journal:  Nat Neurosci       Date:  2015-03-24       Impact factor: 24.884

2.  Positional integratomic approach in identification of genomic candidate regions for Parkinson's disease.

Authors:  Ales Maver; Borut Peterlin
Journal:  Bioinformatics       Date:  2011-05-19       Impact factor: 6.937

3.  The gene encoding alsin, a protein with three guanine-nucleotide exchange factor domains, is mutated in a form of recessive amyotrophic lateral sclerosis.

Authors:  Y Yang; A Hentati; H X Deng; O Dabbagh; T Sasaki; M Hirano; W Y Hung; K Ouahchi; J Yan; A C Azim; N Cole; G Gascon; A Yagmour; M Ben-Hamida; M Pericak-Vance; F Hentati; T Siddique
Journal:  Nat Genet       Date:  2001-10       Impact factor: 38.330

4.  Endoplasmic reticulum stress leads to accumulation of wild-type SOD1 aggregates associated with sporadic amyotrophic lateral sclerosis.

Authors:  Danilo B Medinas; Pablo Rozas; Francisca Martínez Traub; Ute Woehlbier; Robert H Brown; Daryl A Bosco; Claudio Hetz
Journal:  Proc Natl Acad Sci U S A       Date:  2018-07-23       Impact factor: 11.205

5.  TDP-43 mutant transgenic mice develop features of ALS and frontotemporal lobar degeneration.

Authors:  Iga Wegorzewska; Shaughn Bell; Nigel J Cairns; Timothy M Miller; Robert H Baloh
Journal:  Proc Natl Acad Sci U S A       Date:  2009-10-15       Impact factor: 11.205

6.  TARDBP 3'-UTR variant in autopsy-confirmed frontotemporal lobar degeneration with TDP-43 proteinopathy.

Authors:  Michael A Gitcho; Eileen H Bigio; Manjari Mishra; Nancy Johnson; Sandra Weintraub; Marsel Mesulam; Rosa Rademakers; Sumi Chakraverty; Carlos Cruchaga; John C Morris; Alison M Goate; Nigel J Cairns
Journal:  Acta Neuropathol       Date:  2009-07-18       Impact factor: 17.088

7.  A hexanucleotide repeat expansion in C9ORF72 is the cause of chromosome 9p21-linked ALS-FTD.

Authors:  Alan E Renton; Elisa Majounie; Adrian Waite; Javier Simón-Sánchez; Sara Rollinson; J Raphael Gibbs; Jennifer C Schymick; Hannu Laaksovirta; John C van Swieten; Liisa Myllykangas; Hannu Kalimo; Anders Paetau; Yevgeniya Abramzon; Anne M Remes; Alice Kaganovich; Sonja W Scholz; Jamie Duckworth; Jinhui Ding; Daniel W Harmer; Dena G Hernandez; Janel O Johnson; Kin Mok; Mina Ryten; Danyah Trabzuni; Rita J Guerreiro; Richard W Orrell; James Neal; Alex Murray; Justin Pearson; Iris E Jansen; David Sondervan; Harro Seelaar; Derek Blake; Kate Young; Nicola Halliwell; Janis Bennion Callister; Greg Toulson; Anna Richardson; Alex Gerhard; Julie Snowden; David Mann; David Neary; Michael A Nalls; Terhi Peuralinna; Lilja Jansson; Veli-Matti Isoviita; Anna-Lotta Kaivorinne; Maarit Hölttä-Vuori; Elina Ikonen; Raimo Sulkava; Michael Benatar; Joanne Wuu; Adriano Chiò; Gabriella Restagno; Giuseppe Borghero; Mario Sabatelli; David Heckerman; Ekaterina Rogaeva; Lorne Zinman; Jeffrey D Rothstein; Michael Sendtner; Carsten Drepper; Evan E Eichler; Can Alkan; Ziedulla Abdullaev; Svetlana D Pack; Amalia Dutra; Evgenia Pak; John Hardy; Andrew Singleton; Nigel M Williams; Peter Heutink; Stuart Pickering-Brown; Huw R Morris; Pentti J Tienari; Bryan J Traynor
Journal:  Neuron       Date:  2011-09-21       Impact factor: 17.173

8.  Network organization of the human autophagy system.

Authors:  Christian Behrends; Mathew E Sowa; Steven P Gygi; J Wade Harper
Journal:  Nature       Date:  2010-06-20       Impact factor: 49.962

9.  Discovery of new methylation markers to improve screening for cervical intraepithelial neoplasia grade 2/3.

Authors:  E Schuuring; G B A Wisman; A Boers; R Wang; R W van Leeuwen; H G Klip; G H de Bock; H Hollema; W van Criekinge; T de Meyer; S Denil; A G J van der Zee
Journal:  Clin Epigenetics       Date:  2016-03-09       Impact factor: 6.551

10.  Neuronal inhibition of the autophagy nucleation complex extends life span in post-reproductive C. elegans.

Authors:  Thomas Wilhelm; Jonathan Byrne; Rebeca Medina; Ena Kolundžić; Johannes Geisinger; Martina Hajduskova; Baris Tursun; Holger Richly
Journal:  Genes Dev       Date:  2017-09-07       Impact factor: 11.361

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  7 in total

1.  Neuronal Rubicon Represses Extracellular APP/Amyloid β Deposition in Alzheimer's Disease.

Authors:  Sandra Espinoza; Felipe Grunenwald; Wileidy Gomez; Felipe García; Lorena Abarzúa-Catalan; Sebastián Oyarce-Pezoa; Maria Fernanda Hernandez; Bastián I Cortés; Markus Uhrig; Daniela P Ponce; Claudia Durán-Aniotz; Claudio Hetz; Carol D SanMartín; Victor H Cornejo; Fernando Ezquer; Valentina Parra; Maria Isabel Behrens; Patricio A Manque; Diego Rojas-Rivera; René L Vidal; Ute Woehlbier; Melissa Nassif
Journal:  Cells       Date:  2022-06-07       Impact factor: 7.666

2.  The Autophagy Protein Pacer Positively Regulates the Therapeutic Potential of Mesenchymal Stem Cells in a Mouse Model of DSS-Induced Colitis.

Authors:  Cristian A Bergmann; Sebastian Beltran; Ana Maria Vega-Letter; Paola Murgas; Maria Fernanda Hernandez; Laura Gomez; Luis Labrador; Bastián I Cortés; Cristian Poblete; Cristobal Quijada; Flavio Carrion; Ute Woehlbier; Patricio A Manque
Journal:  Cells       Date:  2022-04-30       Impact factor: 7.666

3.  Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

Authors:  Daniel J Klionsky; Amal Kamal Abdel-Aziz; Sara Abdelfatah; Mahmoud Abdellatif; Asghar Abdoli; Steffen Abel; Hagai Abeliovich; Marie H Abildgaard; Yakubu Princely Abudu; Abraham Acevedo-Arozena; Iannis E Adamopoulos; Khosrow Adeli; Timon E Adolph; Annagrazia Adornetto; Elma Aflaki; Galila Agam; Anupam Agarwal; Bharat B Aggarwal; Maria Agnello; Patrizia Agostinis; Javed N Agrewala; Alexander Agrotis; Patricia V Aguilar; S Tariq Ahmad; Zubair M Ahmed; Ulises Ahumada-Castro; Sonja Aits; Shu Aizawa; Yunus Akkoc; Tonia Akoumianaki; Hafize Aysin Akpinar; Ahmed M Al-Abd; Lina Al-Akra; Abeer Al-Gharaibeh; Moulay A Alaoui-Jamali; Simon Alberti; Elísabet Alcocer-Gómez; Cristiano Alessandri; Muhammad Ali; M Abdul Alim Al-Bari; Saeb Aliwaini; Javad Alizadeh; Eugènia Almacellas; Alexandru Almasan; Alicia Alonso; Guillermo D Alonso; Nihal Altan-Bonnet; Dario C Altieri; Élida M C Álvarez; Sara Alves; Cristine Alves da Costa; Mazen M Alzaharna; Marialaura Amadio; Consuelo Amantini; Cristina Amaral; Susanna Ambrosio; Amal O Amer; Veena Ammanathan; Zhenyi An; Stig U Andersen; Shaida A Andrabi; Magaiver Andrade-Silva; Allen M Andres; Sabrina Angelini; David Ann; Uche C Anozie; Mohammad Y Ansari; Pedro Antas; Adam Antebi; Zuriñe Antón; Tahira Anwar; Lionel Apetoh; Nadezda Apostolova; Toshiyuki Araki; Yasuhiro Araki; Kohei Arasaki; Wagner L Araújo; Jun Araya; Catherine Arden; Maria-Angeles Arévalo; Sandro Arguelles; Esperanza Arias; Jyothi Arikkath; Hirokazu Arimoto; Aileen R Ariosa; Darius Armstrong-James; Laetitia Arnauné-Pelloquin; Angeles Aroca; Daniela S Arroyo; Ivica Arsov; Rubén Artero; Dalia Maria Lucia Asaro; Michael Aschner; Milad Ashrafizadeh; Osnat Ashur-Fabian; Atanas G Atanasov; Alicia K Au; Patrick Auberger; Holger W Auner; Laure Aurelian; Riccardo Autelli; Laura Avagliano; Yenniffer Ávalos; Sanja Aveic; Célia Alexandra Aveleira; Tamar Avin-Wittenberg; Yucel Aydin; Scott Ayton; Srinivas Ayyadevara; Maria Azzopardi; Misuzu Baba; Jonathan M Backer; Steven K Backues; Dong-Hun Bae; Ok-Nam Bae; Soo Han Bae; Eric H Baehrecke; Ahruem Baek; Seung-Hoon Baek; Sung Hee Baek; Giacinto Bagetta; Agnieszka Bagniewska-Zadworna; Hua Bai; Jie Bai; Xiyuan Bai; Yidong Bai; Nandadulal Bairagi; Shounak Baksi; Teresa Balbi; Cosima T Baldari; Walter Balduini; Andrea Ballabio; Maria Ballester; Salma Balazadeh; Rena Balzan; Rina Bandopadhyay; Sreeparna Banerjee; Sulagna Banerjee; Ágnes Bánréti; Yan Bao; Mauricio S Baptista; Alessandra Baracca; Cristiana Barbati; Ariadna Bargiela; Daniela Barilà; Peter G Barlow; Sami J Barmada; Esther Barreiro; George E Barreto; Jiri Bartek; Bonnie Bartel; Alberto Bartolome; Gaurav R Barve; Suresh H Basagoudanavar; Diane C Bassham; Robert C Bast; Alakananda Basu; Henri Batoko; Isabella Batten; Etienne E Baulieu; Bradley L Baumgarner; Jagadeesh Bayry; Rupert Beale; Isabelle Beau; Florian Beaumatin; Luiz R G Bechara; George R Beck; Michael F Beers; Jakob Begun; Christian Behrends; Georg M N Behrens; Roberto Bei; Eloy Bejarano; Shai Bel; Christian Behl; Amine Belaid; Naïma Belgareh-Touzé; Cristina Bellarosa; Francesca Belleudi; Melissa Belló Pérez; Raquel Bello-Morales; Jackeline Soares de Oliveira Beltran; Sebastián Beltran; Doris Mangiaracina Benbrook; Mykolas Bendorius; Bruno A Benitez; Irene Benito-Cuesta; Julien Bensalem; Martin W Berchtold; Sabina Berezowska; Daniele Bergamaschi; Matteo Bergami; Andreas Bergmann; Laura Berliocchi; Clarisse Berlioz-Torrent; Amélie Bernard; Lionel Berthoux; Cagri G Besirli; Sebastien Besteiro; Virginie M Betin; Rudi Beyaert; Jelena S Bezbradica; Kiran Bhaskar; Ingrid Bhatia-Kissova; Resham Bhattacharya; Sujoy Bhattacharya; Shalmoli Bhattacharyya; Md Shenuarin Bhuiyan; Sujit Kumar Bhutia; Lanrong Bi; Xiaolin Bi; Trevor J Biden; Krikor Bijian; Viktor A Billes; Nadine Binart; Claudia Bincoletto; Asa B Birgisdottir; Geir Bjorkoy; Gonzalo Blanco; Ana Blas-Garcia; Janusz Blasiak; Robert Blomgran; Klas Blomgren; Janice S Blum; Emilio Boada-Romero; Mirta Boban; Kathleen Boesze-Battaglia; Philippe Boeuf; Barry Boland; Pascale Bomont; Paolo Bonaldo; Srinivasa Reddy Bonam; Laura Bonfili; Juan S Bonifacino; Brian A Boone; Martin D Bootman; Matteo Bordi; Christoph Borner; Beat C Bornhauser; Gautam Borthakur; Jürgen Bosch; Santanu Bose; Luis M Botana; Juan Botas; Chantal M Boulanger; Michael E Boulton; Mathieu Bourdenx; Benjamin Bourgeois; Nollaig M Bourke; Guilhem Bousquet; Patricia Boya; Peter V Bozhkov; Luiz H M Bozi; Tolga O Bozkurt; Doug E Brackney; Christian H Brandts; Ralf J Braun; Gerhard H Braus; Roberto Bravo-Sagua; José M Bravo-San Pedro; Patrick Brest; Marie-Agnès Bringer; Alfredo Briones-Herrera; V Courtney Broaddus; Peter Brodersen; Jeffrey L Brodsky; Steven L Brody; Paola G Bronson; Jeff M Bronstein; Carolyn N Brown; Rhoderick E Brown; Patricia C Brum; John H Brumell; Nicola Brunetti-Pierri; Daniele Bruno; Robert J Bryson-Richardson; Cecilia Bucci; Carmen Buchrieser; Marta Bueno; Laura Elisa Buitrago-Molina; Simone Buraschi; Shilpa Buch; J Ross Buchan; Erin M Buckingham; Hikmet Budak; Mauricio Budini; Geert Bultynck; Florin Burada; Joseph R Burgoyne; M Isabel Burón; Victor Bustos; Sabrina Büttner; Elena Butturini; Aaron Byrd; Isabel Cabas; Sandra Cabrera-Benitez; Ken Cadwell; Jingjing Cai; Lu Cai; Qian Cai; Montserrat Cairó; Jose A Calbet; Guy A Caldwell; Kim A Caldwell; Jarrod A Call; Riccardo Calvani; Ana C Calvo; Miguel Calvo-Rubio Barrera; Niels Os Camara; Jacques H Camonis; Nadine Camougrand; Michelangelo Campanella; Edward M Campbell; François-Xavier Campbell-Valois; Silvia Campello; Ilaria Campesi; Juliane C Campos; Olivier Camuzard; Jorge Cancino; Danilo Candido de Almeida; Laura Canesi; Isabella Caniggia; Barbara Canonico; Carles Cantí; Bin Cao; Michele Caraglia; Beatriz Caramés; Evie H Carchman; Elena Cardenal-Muñoz; Cesar Cardenas; Luis Cardenas; Sandra M Cardoso; Jennifer S Carew; Georges F Carle; Gillian Carleton; Silvia Carloni; Didac Carmona-Gutierrez; Leticia A Carneiro; Oliana Carnevali; Julian M Carosi; Serena Carra; Alice Carrier; Lucie Carrier; Bernadette Carroll; A Brent Carter; 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Samrat Chatterjee; Shail K Chaube; Anu Chaudhary; Santosh Chauhan; Edward Chaum; Frédéric Checler; Michael E Cheetham; Chang-Shi Chen; Guang-Chao Chen; Jian-Fu Chen; Liam L Chen; Leilei Chen; Lin Chen; Mingliang Chen; Mu-Kuan Chen; Ning Chen; Quan Chen; Ruey-Hwa Chen; Shi Chen; Wei Chen; Weiqiang Chen; Xin-Ming Chen; Xiong-Wen Chen; Xu Chen; Yan Chen; Ye-Guang Chen; Yingyu Chen; Yongqiang Chen; Yu-Jen Chen; Yue-Qin Chen; Zhefan Stephen Chen; Zhi Chen; Zhi-Hua Chen; Zhijian J Chen; Zhixiang Chen; Hanhua Cheng; Jun Cheng; Shi-Yuan Cheng; Wei Cheng; Xiaodong Cheng; Xiu-Tang Cheng; Yiyun Cheng; Zhiyong Cheng; Zhong Chen; Heesun Cheong; Jit Kong Cheong; Boris V Chernyak; Sara Cherry; Chi Fai Randy Cheung; Chun Hei Antonio Cheung; King-Ho Cheung; Eric Chevet; Richard J Chi; Alan Kwok Shing Chiang; Ferdinando Chiaradonna; Roberto Chiarelli; Mario Chiariello; Nathalia Chica; Susanna Chiocca; Mario Chiong; Shih-Hwa Chiou; Abhilash I Chiramel; Valerio Chiurchiù; Dong-Hyung Cho; Seong-Kyu Choe; Augustine M K Choi; Mary E Choi; Kamalika Roy Choudhury; Norman S Chow; Charleen T Chu; Jason P Chua; John Jia En Chua; Hyewon Chung; Kin Pan Chung; Seockhoon Chung; So-Hyang Chung; Yuen-Li Chung; Valentina Cianfanelli; Iwona A Ciechomska; Mariana Cifuentes; Laura Cinque; Sebahattin Cirak; Mara Cirone; Michael J Clague; Robert Clarke; Emilio Clementi; Eliana M Coccia; Patrice Codogno; Ehud Cohen; Mickael M Cohen; Tania Colasanti; Fiorella Colasuonno; Robert A Colbert; Anna Colell; Miodrag Čolić; Nuria S Coll; Mark O Collins; María I Colombo; Daniel A Colón-Ramos; Lydie Combaret; Sergio Comincini; Márcia R Cominetti; Antonella Consiglio; Andrea Conte; Fabrizio Conti; Viorica Raluca Contu; Mark R Cookson; Kevin M Coombs; Isabelle Coppens; Maria Tiziana Corasaniti; Dale P Corkery; Nils Cordes; Katia Cortese; Maria do Carmo Costa; Sarah Costantino; Paola Costelli; Ana Coto-Montes; Peter J Crack; Jose L Crespo; Alfredo Criollo; Valeria Crippa; Riccardo Cristofani; Tamas Csizmadia; Antonio Cuadrado; Bing Cui; Jun Cui; Yixian Cui; Yong Cui; Emmanuel Culetto; Andrea C Cumino; Andrey V Cybulsky; Mark J Czaja; Stanislaw J Czuczwar; Stefania D'Adamo; Marcello D'Amelio; Daniela D'Arcangelo; Andrew C D'Lugos; Gabriella D'Orazi; James A da Silva; Hormos Salimi Dafsari; Ruben K Dagda; Yasin Dagdas; Maria Daglia; Xiaoxia Dai; Yun Dai; Yuyuan Dai; Jessica Dal Col; Paul Dalhaimer; Luisa Dalla Valle; Tobias Dallenga; Guillaume Dalmasso; Markus Damme; Ilaria Dando; Nico P Dantuma; April L Darling; Hiranmoy Das; Srinivasan Dasarathy; Santosh K Dasari; Srikanta Dash; Oliver Daumke; Adrian N Dauphinee; Jeffrey S Davies; Valeria A Dávila; Roger J Davis; Tanja Davis; Sharadha Dayalan Naidu; Francesca De Amicis; Karolien De Bosscher; Francesca De Felice; Lucia De Franceschi; Chiara De Leonibus; Mayara G de Mattos Barbosa; Guido R Y De Meyer; Angelo De Milito; Cosimo De Nunzio; Clara De Palma; Mauro De Santi; Claudio De Virgilio; Daniela De Zio; Jayanta Debnath; Brian J DeBosch; Jean-Paul Decuypere; Mark A Deehan; Gianluca Deflorian; James DeGregori; Benjamin Dehay; Gabriel Del Rio; Joe R Delaney; Lea M D Delbridge; Elizabeth Delorme-Axford; M Victoria Delpino; Francesca Demarchi; Vilma Dembitz; Nicholas D Demers; Hongbin Deng; Zhiqiang Deng; Joern Dengjel; Paul Dent; Donna Denton; Melvin L DePamphilis; Channing J Der; Vojo Deretic; Albert Descoteaux; Laura Devis; Sushil Devkota; Olivier Devuyst; Grant Dewson; Mahendiran Dharmasivam; Rohan Dhiman; Diego di Bernardo; Manlio Di Cristina; Fabio Di Domenico; Pietro Di Fazio; Alessio Di Fonzo; Giovanni Di Guardo; Gianni M Di Guglielmo; Luca Di Leo; Chiara Di Malta; Alessia Di Nardo; Martina Di Rienzo; Federica Di Sano; George Diallinas; Jiajie Diao; Guillermo Diaz-Araya; Inés Díaz-Laviada; Jared M Dickinson; Marc Diederich; Mélanie Dieudé; Ivan Dikic; Shiping Ding; Wen-Xing Ding; Luciana Dini; Jelena Dinić; Miroslav Dinic; Albena T Dinkova-Kostova; Marc S Dionne; Jörg H W Distler; Abhinav Diwan; Ian M C Dixon; Mojgan Djavaheri-Mergny; Ina Dobrinski; Oxana Dobrovinskaya; Radek Dobrowolski; Renwick C J Dobson; Jelena Đokić; Serap Dokmeci Emre; Massimo Donadelli; Bo Dong; Xiaonan Dong; Zhiwu Dong; Gerald W Dorn Ii; Volker Dotsch; Huan Dou; Juan Dou; Moataz Dowaidar; Sami Dridi; Liat Drucker; Ailian Du; Caigan Du; Guangwei Du; Hai-Ning Du; Li-Lin Du; André du Toit; Shao-Bin Duan; Xiaoqiong Duan; Sónia P Duarte; Anna Dubrovska; Elaine A Dunlop; Nicolas Dupont; Raúl V Durán; Bilikere S Dwarakanath; Sergey A Dyshlovoy; Darius Ebrahimi-Fakhari; Leopold Eckhart; Charles L Edelstein; Thomas Efferth; Eftekhar Eftekharpour; Ludwig Eichinger; Nabil Eid; Tobias Eisenberg; N Tony Eissa; Sanaa Eissa; Miriam Ejarque; Abdeljabar El Andaloussi; Nazira El-Hage; Shahenda El-Naggar; Anna Maria Eleuteri; Eman S El-Shafey; Mohamed Elgendy; Aristides G Eliopoulos; María M Elizalde; Philip M Elks; Hans-Peter Elsasser; Eslam S Elsherbiny; Brooke M Emerling; N C Tolga Emre; Christina H Eng; Nikolai Engedal; Anna-Mart Engelbrecht; Agnete S T Engelsen; Jorrit M Enserink; Ricardo Escalante; Audrey Esclatine; Mafalda Escobar-Henriques; Eeva-Liisa Eskelinen; Lucile Espert; Makandjou-Ola Eusebio; Gemma Fabrias; Cinzia Fabrizi; Antonio Facchiano; Francesco Facchiano; Bengt Fadeel; Claudio Fader; Alex C Faesen; W Douglas Fairlie; Alberto Falcó; Bjorn H Falkenburger; Daping Fan; Jie Fan; Yanbo Fan; Evandro F Fang; Yanshan Fang; Yognqi Fang; Manolis Fanto; Tamar Farfel-Becker; Mathias Faure; Gholamreza Fazeli; Anthony O Fedele; Arthur M Feldman; Du Feng; Jiachun Feng; Lifeng Feng; Yibin Feng; Yuchen Feng; Wei Feng; Thais Fenz Araujo; Thomas A Ferguson; Álvaro F Fernández; Jose C Fernandez-Checa; Sonia Fernández-Veledo; Alisdair R Fernie; Anthony W Ferrante; Alessandra Ferraresi; Merari F Ferrari; Julio C B Ferreira; Susan Ferro-Novick; Antonio Figueras; Riccardo Filadi; Nicoletta Filigheddu; Eduardo Filippi-Chiela; Giuseppe Filomeni; Gian Maria Fimia; Vittorio Fineschi; Francesca Finetti; Steven Finkbeiner; Edward A Fisher; Paul B Fisher; Flavio Flamigni; Steven J Fliesler; Trude H Flo; Ida Florance; Oliver Florey; Tullio Florio; Erika Fodor; Carlo Follo; Edward A Fon; Antonella Forlino; Francesco Fornai; Paola Fortini; Anna Fracassi; Alessandro Fraldi; Brunella Franco; Rodrigo Franco; Flavia Franconi; Lisa B Frankel; Scott L Friedman; Leopold F Fröhlich; Gema Frühbeck; Jose M Fuentes; Yukio Fujiki; Naonobu Fujita; Yuuki Fujiwara; Mitsunori Fukuda; Simone Fulda; Luc Furic; Norihiko Furuya; Carmela Fusco; Michaela U Gack; Lidia Gaffke; Sehamuddin Galadari; Alessia Galasso; Maria F Galindo; Sachith Gallolu Kankanamalage; Lorenzo Galluzzi; Vincent Galy; Noor Gammoh; Boyi Gan; Ian G Ganley; Feng Gao; Hui Gao; Minghui Gao; Ping Gao; Shou-Jiang Gao; Wentao Gao; Xiaobo Gao; Ana Garcera; Maria Noé Garcia; Verónica E Garcia; Francisco García-Del Portillo; Vega Garcia-Escudero; Aracely Garcia-Garcia; Marina Garcia-Macia; Diana García-Moreno; Carmen Garcia-Ruiz; Patricia García-Sanz; Abhishek D Garg; Ricardo Gargini; Tina Garofalo; Robert F Garry; Nils C Gassen; Damian Gatica; Liang Ge; Wanzhong Ge; Ruth Geiss-Friedlander; Cecilia Gelfi; Pascal Genschik; Ian E Gentle; Valeria Gerbino; Christoph Gerhardt; Kyla Germain; Marc Germain; David A Gewirtz; Elham Ghasemipour Afshar; Saeid Ghavami; Alessandra Ghigo; Manosij Ghosh; Georgios Giamas; Claudia Giampietri; Alexandra Giatromanolaki; Gary E Gibson; Spencer B Gibson; Vanessa Ginet; Edward Giniger; Carlotta Giorgi; Henrique Girao; Stephen E Girardin; Mridhula Giridharan; Sandy Giuliano; Cecilia Giulivi; Sylvie Giuriato; Julien Giustiniani; Alexander Gluschko; Veit Goder; Alexander Goginashvili; Jakub Golab; David C Goldstone; Anna Golebiewska; Luciana R Gomes; Rodrigo Gomez; Rubén Gómez-Sánchez; Maria Catalina Gomez-Puerto; Raquel Gomez-Sintes; Qingqiu Gong; Felix M Goni; Javier González-Gallego; Tomas Gonzalez-Hernandez; Rosa A Gonzalez-Polo; Jose A Gonzalez-Reyes; Patricia González-Rodríguez; Ing Swie Goping; Marina S Gorbatyuk; Nikolai V Gorbunov; Kıvanç Görgülü; Roxana M Gorojod; Sharon M Gorski; Sandro Goruppi; Cecilia Gotor; Roberta A Gottlieb; Illana Gozes; Devrim Gozuacik; Martin Graef; Markus H Gräler; Veronica Granatiero; Daniel Grasso; Joshua P Gray; Douglas R Green; Alexander Greenhough; Stephen L Gregory; Edward F Griffin; Mark W Grinstaff; Frederic Gros; Charles Grose; Angelina S Gross; Florian Gruber; Paolo Grumati; Tilman Grune; Xueyan Gu; Jun-Lin Guan; Carlos M Guardia; Kishore Guda; Flora Guerra; Consuelo Guerri; Prasun Guha; Carlos Guillén; Shashi Gujar; Anna Gukovskaya; Ilya Gukovsky; Jan Gunst; Andreas Günther; Anyonya R Guntur; Chuanyong Guo; Chun Guo; Hongqing Guo; Lian-Wang Guo; Ming Guo; Pawan Gupta; Shashi Kumar Gupta; Swapnil Gupta; Veer Bala Gupta; Vivek Gupta; Asa B Gustafsson; David D Gutterman; Ranjitha H B; Annakaisa Haapasalo; James E Haber; Aleksandra Hać; Shinji Hadano; Anders J Hafrén; Mansour Haidar; Belinda S Hall; Gunnel Halldén; Anne Hamacher-Brady; Andrea Hamann; Maho Hamasaki; Weidong Han; Malene Hansen; Phyllis I Hanson; Zijian Hao; Masaru Harada; Ljubica Harhaji-Trajkovic; Nirmala Hariharan; Nigil Haroon; James Harris; Takafumi Hasegawa; Noor Hasima Nagoor; Jeffrey A Haspel; Volker Haucke; Wayne D Hawkins; Bruce A Hay; Cole M Haynes; Soren B Hayrabedyan; Thomas S Hays; Congcong He; Qin He; Rong-Rong He; You-Wen He; Yu-Ying He; Yasser Heakal; Alexander M Heberle; J Fielding Hejtmancik; Gudmundur Vignir Helgason; Vanessa Henkel; Marc Herb; Alexander Hergovich; Anna Herman-Antosiewicz; Agustín Hernández; Carlos Hernandez; Sergio Hernandez-Diaz; Virginia Hernandez-Gea; Amaury Herpin; Judit Herreros; Javier H Hervás; Daniel Hesselson; Claudio Hetz; Volker T Heussler; Yujiro Higuchi; Sabine Hilfiker; Joseph A Hill; William S Hlavacek; Emmanuel A Ho; Idy H T Ho; Philip Wing-Lok Ho; Shu-Leong Ho; Wan Yun Ho; G Aaron Hobbs; Mark Hochstrasser; Peter H M Hoet; Daniel Hofius; Paul Hofman; Annika Höhn; Carina I Holmberg; Jose R Hombrebueno; Chang-Won Hong Yi-Ren Hong; Lora V Hooper; Thorsten Hoppe; Rastislav Horos; Yujin Hoshida; I-Lun Hsin; Hsin-Yun Hsu; Bing Hu; Dong Hu; Li-Fang Hu; Ming Chang Hu; Ronggui Hu; Wei Hu; Yu-Chen Hu; Zhuo-Wei Hu; Fang Hua; Jinlian Hua; Yingqi Hua; Chongmin Huan; Canhua Huang; Chuanshu Huang; Chuanxin Huang; Chunling Huang; Haishan Huang; Kun Huang; Michael L H Huang; Rui Huang; Shan Huang; Tianzhi Huang; Xing Huang; Yuxiang Jack Huang; Tobias B Huber; Virginie Hubert; Christian A Hubner; Stephanie M Hughes; William E Hughes; Magali Humbert; Gerhard Hummer; James H Hurley; Sabah Hussain; Salik Hussain; Patrick J Hussey; Martina Hutabarat; Hui-Yun Hwang; Seungmin Hwang; Antonio Ieni; Fumiyo Ikeda; Yusuke Imagawa; Yuzuru Imai; Carol Imbriano; Masaya Imoto; Denise M Inman; Ken Inoki; Juan Iovanna; Renato V Iozzo; Giuseppe Ippolito; Javier E Irazoqui; Pablo Iribarren; Mohd Ishaq; Makoto Ishikawa; Nestor Ishimwe; Ciro Isidoro; Nahed Ismail; Shohreh Issazadeh-Navikas; Eisuke Itakura; Daisuke Ito; Davor Ivankovic; Saška Ivanova; Anand Krishnan V Iyer; José M Izquierdo; Masanori Izumi; Marja Jäättelä; Majid Sakhi Jabir; William T Jackson; Nadia Jacobo-Herrera; Anne-Claire Jacomin; Elise Jacquin; Pooja Jadiya; Hartmut Jaeschke; Chinnaswamy Jagannath; Arjen J Jakobi; Johan Jakobsson; Bassam Janji; Pidder Jansen-Dürr; Patric J Jansson; Jonathan Jantsch; Sławomir Januszewski; Alagie Jassey; Steve Jean; Hélène Jeltsch-David; Pavla Jendelova; Andreas Jenny; Thomas E Jensen; Niels Jessen; Jenna L Jewell; Jing Ji; Lijun Jia; Rui Jia; Liwen Jiang; Qing Jiang; Richeng Jiang; Teng Jiang; Xuejun Jiang; Yu Jiang; Maria Jimenez-Sanchez; Eun-Jung Jin; Fengyan Jin; Hongchuan Jin; Li Jin; Luqi Jin; Meiyan Jin; Si Jin; Eun-Kyeong Jo; Carine Joffre; Terje Johansen; Gail V W Johnson; Simon A Johnston; Eija Jokitalo; Mohit Kumar Jolly; Leo A B Joosten; Joaquin Jordan; Bertrand Joseph; Dianwen Ju; Jeong-Sun Ju; Jingfang Ju; Esmeralda Juárez; Delphine Judith; Gábor Juhász; Youngsoo Jun; Chang Hwa Jung; Sung-Chul Jung; Yong Keun Jung; Heinz Jungbluth; Johannes Jungverdorben; Steffen Just; Kai Kaarniranta; Allen Kaasik; Tomohiro Kabuta; Daniel Kaganovich; Alon Kahana; Renate Kain; Shinjo Kajimura; Maria Kalamvoki; Manjula Kalia; Danuta S Kalinowski; Nina Kaludercic; Ioanna Kalvari; Joanna Kaminska; Vitaliy O Kaminskyy; Hiromitsu Kanamori; Keizo Kanasaki; Chanhee Kang; Rui Kang; Sang Sun Kang; Senthilvelrajan Kaniyappan; Tomotake Kanki; Thirumala-Devi Kanneganti; Anumantha G Kanthasamy; Arthi Kanthasamy; Marc Kantorow; Orsolya Kapuy; Michalis V Karamouzis; Md Razaul Karim; Parimal Karmakar; Rajesh G Katare; Masaru Kato; Stefan H E Kaufmann; Anu Kauppinen; Gur P Kaushal; Susmita Kaushik; Kiyoshi Kawasaki; Kemal Kazan; Po-Yuan Ke; Damien J Keating; Ursula Keber; John H Kehrl; Kate E Keller; Christian W Keller; Jongsook Kim Kemper; Candia M Kenific; Oliver Kepp; Stephanie Kermorgant; Andreas Kern; Robin Ketteler; Tom G Keulers; Boris Khalfin; Hany Khalil; Bilon Khambu; Shahid Y Khan; Vinoth Kumar Megraj Khandelwal; Rekha Khandia; Widuri Kho; Noopur V Khobrekar; Sataree Khuansuwan; Mukhran Khundadze; Samuel A Killackey; Dasol Kim; Deok Ryong Kim; Do-Hyung Kim; Dong-Eun Kim; Eun Young Kim; Eun-Kyoung Kim; Hak-Rim Kim; Hee-Sik Kim; Jeong Hun Kim; Jin Kyung Kim; Jin-Hoi Kim; Joungmok Kim; Ju Hwan Kim; Keun Il Kim; Peter K Kim; Seong-Jun Kim; Scot R Kimball; Adi Kimchi; Alec C Kimmelman; Tomonori Kimura; Matthew A King; Kerri J Kinghorn; Conan G Kinsey; Vladimir Kirkin; Lorrie A Kirshenbaum; Sergey L Kiselev; Shuji Kishi; Katsuhiko Kitamoto; Yasushi Kitaoka; Kaio Kitazato; Richard N Kitsis; Josef T Kittler; Ole Kjaerulff; Peter S Klein; Thomas Klopstock; Jochen Klucken; Helene Knævelsrud; Roland L Knorr; Ben C B Ko; Fred Ko; Jiunn-Liang Ko; Hotaka Kobayashi; Satoru Kobayashi; Ina Koch; Jan C Koch; Ulrich Koenig; Donat Kögel; Young Ho Koh; Masato Koike; Sepp D Kohlwein; Nur M Kocaturk; Masaaki Komatsu; Jeannette König; Toru Kono; Benjamin T Kopp; Tamas Korcsmaros; Gözde Korkmaz; Viktor I Korolchuk; Mónica Suárez Korsnes; Ali Koskela; Janaiah Kota; Yaichiro Kotake; Monica L Kotler; Yanjun Kou; Michael I Koukourakis; Evangelos Koustas; Attila L Kovacs; Tibor Kovács; Daisuke Koya; Tomohiro Kozako; Claudine Kraft; Dimitri Krainc; Helmut Krämer; Anna D Krasnodembskaya; Carole Kretz-Remy; Guido Kroemer; Nicholas T Ktistakis; Kazuyuki Kuchitsu; Sabine Kuenen; Lars Kuerschner; Thomas Kukar; Ajay Kumar; Ashok Kumar; Deepak Kumar; Dhiraj Kumar; Sharad Kumar; Shinji Kume; Caroline Kumsta; Chanakya N Kundu; Mondira Kundu; Ajaikumar B Kunnumakkara; Lukasz Kurgan; Tatiana G Kutateladze; Ozlem Kutlu; SeongAe Kwak; Ho Jeong Kwon; Taeg Kyu Kwon; Yong Tae Kwon; Irene Kyrmizi; Albert La Spada; Patrick Labonté; Sylvain Ladoire; Ilaria Laface; Frank Lafont; Diane C Lagace; Vikramjit Lahiri; Zhibing Lai; Angela S Laird; Aparna Lakkaraju; Trond Lamark; Sheng-Hui Lan; Ane Landajuela; Darius J R Lane; Jon D Lane; Charles H Lang; Carsten Lange; Ülo Langel; Rupert Langer; Pierre Lapaquette; Jocelyn Laporte; Nicholas F LaRusso; Isabel Lastres-Becker; Wilson Chun Yu Lau; Gordon W Laurie; Sergio Lavandero; Betty Yuen Kwan Law; Helen Ka-Wai Law; Rob Layfield; Weidong Le; Herve Le Stunff; Alexandre Y Leary; Jean-Jacques Lebrun; Lionel Y W Leck; Jean-Philippe Leduc-Gaudet; Changwook Lee; Chung-Pei Lee; Da-Hye Lee; Edward B Lee; Erinna F Lee; Gyun Min Lee; He-Jin Lee; Heung Kyu Lee; Jae Man Lee; Jason S Lee; Jin-A Lee; Joo-Yong Lee; Jun Hee Lee; Michael Lee; Min Goo Lee; Min Jae Lee; Myung-Shik Lee; Sang Yoon Lee; Seung-Jae Lee; Stella Y Lee; Sung Bae Lee; Won Hee Lee; Ying-Ray Lee; Yong-Ho Lee; Youngil Lee; Christophe Lefebvre; Renaud Legouis; Yu L Lei; Yuchen Lei; Sergey Leikin; Gerd Leitinger; Leticia Lemus; Shuilong Leng; Olivia Lenoir; Guido Lenz; Heinz Josef Lenz; Paola Lenzi; Yolanda León; Andréia M Leopoldino; Christoph Leschczyk; Stina Leskelä; Elisabeth Letellier; Chi-Ting Leung; Po Sing Leung; Jeremy S Leventhal; Beth Levine; Patrick A Lewis; Klaus Ley; Bin Li; Da-Qiang Li; Jianming Li; Jing Li; Jiong Li; Ke Li; Liwu Li; Mei Li; Min Li; Min Li; Ming Li; Mingchuan Li; Pin-Lan Li; Ming-Qing Li; Qing Li; Sheng Li; Tiangang Li; Wei Li; Wenming Li; Xue Li; Yi-Ping Li; Yuan Li; Zhiqiang Li; Zhiyong Li; Zhiyuan Li; Jiqin Lian; Chengyu Liang; Qiangrong Liang; Weicheng Liang; Yongheng Liang; YongTian Liang; Guanghong Liao; Lujian Liao; Mingzhi Liao; Yung-Feng Liao; Mariangela Librizzi; Pearl P Y Lie; Mary A Lilly; Hyunjung J Lim; Thania R R Lima; Federica Limana; Chao Lin; Chih-Wen Lin; Dar-Shong Lin; Fu-Cheng Lin; Jiandie D Lin; Kurt M Lin; Kwang-Huei Lin; Liang-Tzung Lin; Pei-Hui Lin; Qiong Lin; Shaofeng Lin; Su-Ju Lin; Wenyu Lin; Xueying Lin; Yao-Xin Lin; Yee-Shin Lin; Rafael Linden; Paula Lindner; Shuo-Chien Ling; Paul Lingor; Amelia K Linnemann; Yih-Cherng Liou; Marta M Lipinski; Saška Lipovšek; Vitor A Lira; Natalia Lisiak; Paloma B Liton; Chao Liu; Ching-Hsuan Liu; Chun-Feng Liu; Cui Hua Liu; Fang Liu; Hao Liu; Hsiao-Sheng Liu; Hua-Feng Liu; Huifang Liu; Jia Liu; Jing Liu; Julia Liu; Leyuan Liu; Longhua Liu; Meilian Liu; Qin Liu; Wei Liu; Wende Liu; Xiao-Hong Liu; Xiaodong Liu; Xingguo Liu; Xu Liu; Xuedong Liu; Yanfen Liu; Yang Liu; Yang Liu; Yueyang Liu; Yule Liu; J Andrew Livingston; Gerard Lizard; Jose M Lizcano; Senka Ljubojevic-Holzer; Matilde E LLeonart; David Llobet-Navàs; Alicia Llorente; Chih Hung Lo; Damián Lobato-Márquez; Qi Long; Yun Chau Long; Ben Loos; Julia A Loos; Manuela G López; Guillermo López-Doménech; José Antonio López-Guerrero; Ana T López-Jiménez; Óscar López-Pérez; Israel López-Valero; Magdalena J Lorenowicz; Mar Lorente; Peter Lorincz; Laura Lossi; Sophie Lotersztajn; Penny E Lovat; Jonathan F Lovell; Alenka Lovy; Péter Lőw; Guang Lu; Haocheng Lu; Jia-Hong Lu; Jin-Jian Lu; Mengji Lu; Shuyan Lu; Alessandro Luciani; John M Lucocq; Paula Ludovico; Micah A Luftig; Morten Luhr; Diego Luis-Ravelo; Julian J Lum; Liany Luna-Dulcey; Anders H Lund; Viktor K Lund; Jan D Lünemann; Patrick Lüningschrör; Honglin Luo; Rongcan Luo; Shouqing Luo; Zhi Luo; Claudio Luparello; Bernhard Lüscher; Luan Luu; Alex Lyakhovich; Konstantin G Lyamzaev; Alf Håkon Lystad; Lyubomyr Lytvynchuk; Alvin C Ma; Changle Ma; Mengxiao Ma; Ning-Fang Ma; Quan-Hong Ma; Xinliang Ma; Yueyun Ma; Zhenyi Ma; Ormond A MacDougald; Fernando Macian; Gustavo C MacIntosh; Jeffrey P MacKeigan; Kay F Macleod; Sandra Maday; Frank Madeo; Muniswamy Madesh; Tobias Madl; Julio Madrigal-Matute; Akiko Maeda; Yasuhiro Maejima; Marta Magarinos; Poornima Mahavadi; Emiliano Maiani; Kenneth Maiese; Panchanan Maiti; Maria Chiara Maiuri; Barbara Majello; Michael B Major; Elena Makareeva; Fayaz Malik; Karthik Mallilankaraman; Walter Malorni; Alina Maloyan; Najiba Mammadova; Gene Chi Wai Man; Federico Manai; Joseph D Mancias; Eva-Maria Mandelkow; Michael A Mandell; Angelo A Manfredi; Masoud H Manjili; Ravi Manjithaya; Patricio Manque; Bella B Manshian; Raquel Manzano; Claudia Manzoni; Kai Mao; Cinzia Marchese; Sandrine Marchetti; Anna Maria Marconi; Fabrizio Marcucci; Stefania Mardente; Olga A Mareninova; Marta Margeta; Muriel Mari; Sara Marinelli; Oliviero Marinelli; Guillermo Mariño; Sofia Mariotto; Richard S Marshall; Mark R Marten; Sascha Martens; Alexandre P J Martin; Katie R Martin; Sara Martin; Shaun Martin; Adrián Martín-Segura; Miguel A Martín-Acebes; Inmaculada Martin-Burriel; Marcos Martin-Rincon; Paloma Martin-Sanz; José A Martina; Wim Martinet; Aitor Martinez; Ana Martinez; Jennifer Martinez; Moises Martinez Velazquez; Nuria Martinez-Lopez; Marta Martinez-Vicente; Daniel O Martins; Joilson O Martins; Waleska K Martins; Tania Martins-Marques; Emanuele Marzetti; Shashank Masaldan; Celine Masclaux-Daubresse; Douglas G Mashek; Valentina Massa; Lourdes Massieu; Glenn R Masson; Laura Masuelli; Anatoliy I Masyuk; Tetyana V Masyuk; Paola Matarrese; Ander Matheu; Satoaki Matoba; Sachiko Matsuzaki; Pamela Mattar; Alessandro Matte; Domenico Mattoscio; José L Mauriz; Mario Mauthe; Caroline Mauvezin; Emanual Maverakis; Paola Maycotte; Johanna Mayer; Gianluigi Mazzoccoli; Cristina Mazzoni; Joseph R Mazzulli; Nami McCarty; Christine McDonald; Mitchell R McGill; Sharon L McKenna; BethAnn McLaughlin; Fionn McLoughlin; Mark A McNiven; Thomas G McWilliams; Fatima Mechta-Grigoriou; Tania Catarina Medeiros; Diego L Medina; Lynn A Megeney; Klara Megyeri; Maryam Mehrpour; Jawahar L Mehta; Alfred J Meijer; Annemarie H Meijer; Jakob Mejlvang; Alicia Meléndez; Annette Melk; Gonen Memisoglu; Alexandrina F Mendes; Delong Meng; Fei Meng; Tian Meng; Rubem Menna-Barreto; Manoj B Menon; Carol Mercer; Anne E Mercier; Jean-Louis Mergny; Adalberto Merighi; Seth D Merkley; Giuseppe Merla; Volker Meske; Ana Cecilia Mestre; Shree Padma Metur; Christian Meyer; Hemmo Meyer; Wenyi Mi; Jeanne Mialet-Perez; Junying Miao; Lucia Micale; Yasuo Miki; Enrico Milan; Małgorzata Milczarek; Dana L Miller; Samuel I Miller; Silke Miller; Steven W Millward; Ira Milosevic; Elena A Minina; Hamed Mirzaei; Hamid Reza Mirzaei; Mehdi Mirzaei; Amit Mishra; Nandita Mishra; Paras Kumar Mishra; Maja Misirkic Marjanovic; Roberta Misasi; Amit Misra; Gabriella Misso; Claire Mitchell; Geraldine Mitou; Tetsuji Miura; Shigeki Miyamoto; Makoto Miyazaki; Mitsunori Miyazaki; Taiga Miyazaki; Keisuke Miyazawa; Noboru Mizushima; Trine H Mogensen; Baharia Mograbi; Reza Mohammadinejad; Yasir Mohamud; Abhishek Mohanty; Sipra Mohapatra; Torsten Möhlmann; Asif Mohmmed; Anna Moles; Kelle H Moley; Maurizio Molinari; Vincenzo Mollace; Andreas Buch Møller; Bertrand Mollereau; Faustino Mollinedo; Costanza Montagna; Mervyn J Monteiro; Andrea Montella; L Ruth Montes; Barbara Montico; Vinod K Mony; Giacomo Monzio Compagnoni; Michael N Moore; Mohammad A Moosavi; Ana L Mora; Marina Mora; David Morales-Alamo; Rosario Moratalla; Paula I Moreira; Elena Morelli; Sandra Moreno; Daniel Moreno-Blas; Viviana Moresi; Benjamin Morga; Alwena H Morgan; Fabrice Morin; Hideaki Morishita; Orson L Moritz; Mariko Moriyama; Yuji Moriyasu; Manuela Morleo; Eugenia Morselli; Jose F Moruno-Manchon; Jorge Moscat; Serge Mostowy; Elisa Motori; Andrea Felinto Moura; Naima Moustaid-Moussa; Maria Mrakovcic; Gabriel Muciño-Hernández; Anupam Mukherjee; Subhadip Mukhopadhyay; Jean M Mulcahy Levy; Victoriano Mulero; 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Alberto Sanz; Pascual Sanz; Shweta Saran; Marco Sardiello; Timothy J Sargeant; Apurva Sarin; Chinmoy Sarkar; Sovan Sarkar; Maria-Rosa Sarrias; Surajit Sarkar; Dipanka Tanu Sarmah; Jaakko Sarparanta; Aishwarya Sathyanarayan; Ranganayaki Sathyanarayanan; K Matthew Scaglione; Francesca Scatozza; Liliana Schaefer; Zachary T Schafer; Ulrich E Schaible; Anthony H V Schapira; Michael Scharl; Hermann M Schatzl; Catherine H Schein; Wiep Scheper; David Scheuring; Maria Vittoria Schiaffino; Monica Schiappacassi; Rainer Schindl; Uwe Schlattner; Oliver Schmidt; Roland Schmitt; Stephen D Schmidt; Ingo Schmitz; Eran Schmukler; Anja Schneider; Bianca E Schneider; Romana Schober; Alejandra C Schoijet; Micah B Schott; Michael Schramm; Bernd Schröder; Kai Schuh; Christoph Schüller; Ryan J Schulze; Lea Schürmanns; Jens C Schwamborn; Melanie Schwarten; Filippo Scialo; Sebastiano Sciarretta; Melanie J Scott; Kathleen W Scotto; A Ivana Scovassi; Andrea Scrima; Aurora Scrivo; David Sebastian; Salwa Sebti; Simon Sedej; Laura Segatori; Nava Segev; Per O Seglen; Iban Seiliez; Ekihiro Seki; Scott B Selleck; Frank W Sellke; Joshua T Selsby; Michael Sendtner; Serif Senturk; Elena Seranova; Consolato Sergi; Ruth Serra-Moreno; Hiromi Sesaki; Carmine Settembre; Subba Rao Gangi Setty; Gianluca Sgarbi; Ou Sha; John J Shacka; Javeed A Shah; Dantong Shang; Changshun Shao; Feng Shao; Soroush Sharbati; Lisa M Sharkey; Dipali Sharma; Gaurav Sharma; Kulbhushan Sharma; Pawan Sharma; Surendra Sharma; Han-Ming Shen; Hongtao Shen; Jiangang Shen; Ming Shen; Weili Shen; Zheni Shen; Rui Sheng; Zhi Sheng; Zu-Hang Sheng; Jianjian Shi; Xiaobing Shi; Ying-Hong Shi; Kahori Shiba-Fukushima; Jeng-Jer Shieh; Yohta Shimada; Shigeomi Shimizu; Makoto Shimozawa; Takahiro Shintani; Christopher J Shoemaker; Shahla Shojaei; Ikuo Shoji; Bhupendra V Shravage; Viji Shridhar; Chih-Wen Shu; Hong-Bing Shu; Ke Shui; Arvind K Shukla; Timothy E Shutt; Valentina Sica; Aleem Siddiqui; Amanda Sierra; Virginia Sierra-Torre; Santiago Signorelli; Payel Sil; Bruno J de Andrade Silva; Johnatas D Silva; Eduardo Silva-Pavez; Sandrine Silvente-Poirot; Rachel E Simmonds; Anna Katharina Simon; Hans-Uwe Simon; Matias Simons; Anurag Singh; Lalit P Singh; Rajat Singh; Shivendra V Singh; Shrawan K Singh; Sudha B Singh; Sunaina Singh; Surinder Pal Singh; Debasish Sinha; Rohit Anthony Sinha; Sangita Sinha; Agnieszka Sirko; Kapil Sirohi; Efthimios L Sivridis; Panagiotis Skendros; Aleksandra Skirycz; Iva Slaninová; Soraya S Smaili; Andrei Smertenko; Matthew D Smith; Stefaan J Soenen; Eun Jung Sohn; Sophia P M Sok; Giancarlo Solaini; Thierry Soldati; Scott A Soleimanpour; Rosa M Soler; Alexei Solovchenko; Jason A Somarelli; Avinash Sonawane; Fuyong Song; Hyun Kyu Song; Ju-Xian Song; Kunhua Song; Zhiyin Song; Leandro R Soria; Maurizio Sorice; Alexander A Soukas; Sandra-Fausia Soukup; Diana Sousa; Nadia Sousa; Paul A Spagnuolo; Stephen A Spector; M M Srinivas Bharath; Daret St Clair; Venturina Stagni; Leopoldo Staiano; Clint A Stalnecker; Metodi V Stankov; Peter B Stathopulos; Katja Stefan; Sven Marcel Stefan; Leonidas Stefanis; Joan S Steffan; Alexander Steinkasserer; Harald Stenmark; Jared Sterneckert; Craig Stevens; Veronika Stoka; Stephan Storch; Björn Stork; Flavie Strappazzon; Anne Marie Strohecker; Dwayne G Stupack; Huanxing Su; Ling-Yan Su; Longxiang Su; Ana M Suarez-Fontes; Carlos S Subauste; Selvakumar Subbian; Paula V Subirada; Ganapasam Sudhandiran; Carolyn M Sue; Xinbing Sui; Corey Summers; Guangchao Sun; Jun Sun; Kang Sun; Meng-Xiang Sun; Qiming Sun; Yi Sun; Zhongjie Sun; Karen K S Sunahara; Eva Sundberg; Katalin Susztak; Peter Sutovsky; Hidekazu Suzuki; Gary Sweeney; J David Symons; Stephen Cho Wing Sze; Nathaniel J Szewczyk; Anna Tabęcka-Łonczynska; Claudio Tabolacci; Frank Tacke; Heinrich Taegtmeyer; Marco Tafani; Mitsuo Tagaya; Haoran Tai; Stephen W G Tait; Yoshinori Takahashi; Szabolcs Takats; Priti Talwar; Chit Tam; Shing Yau Tam; Davide Tampellini; Atsushi Tamura; Chong Teik Tan; Eng-King Tan; Ya-Qin Tan; Masaki Tanaka; Motomasa Tanaka; Daolin Tang; Jingfeng Tang; Tie-Shan Tang; Isei Tanida; Zhipeng Tao; Mohammed Taouis; Lars Tatenhorst; Nektarios Tavernarakis; Allen Taylor; Gregory A Taylor; Joan M Taylor; Elena Tchetina; Andrew R Tee; Irmgard Tegeder; David Teis; Natercia Teixeira; Fatima Teixeira-Clerc; Kumsal A Tekirdag; Tewin Tencomnao; Sandra Tenreiro; Alexei V Tepikin; Pilar S Testillano; Gianluca Tettamanti; Pierre-Louis Tharaux; Kathrin Thedieck; Arvind A Thekkinghat; Stefano Thellung; Josephine W Thinwa; V P Thirumalaikumar; Sufi Mary Thomas; Paul G Thomes; Andrew Thorburn; Lipi Thukral; Thomas Thum; Michael Thumm; Ling Tian; Ales Tichy; Andreas Till; Vincent Timmerman; Vladimir I Titorenko; Sokol V Todi; Krassimira Todorova; Janne M Toivonen; Luana Tomaipitinca; Dhanendra Tomar; Cristina Tomas-Zapico; Sergej Tomić; Benjamin Chun-Kit Tong; Chao Tong; Xin Tong; Sharon A Tooze; Maria L Torgersen; Satoru Torii; Liliana Torres-López; Alicia Torriglia; Christina G Towers; Roberto Towns; Shinya Toyokuni; Vladimir Trajkovic; Donatella Tramontano; Quynh-Giao Tran; Leonardo H Travassos; Charles B Trelford; Shirley Tremel; Ioannis P Trougakos; Betty P Tsao; Mario P Tschan; Hung-Fat Tse; Tak Fu Tse; Hitoshi Tsugawa; Andrey S Tsvetkov; David A Tumbarello; Yasin Tumtas; María J Tuñón; Sandra Turcotte; Boris Turk; Vito Turk; Bradley J Turner; Richard I Tuxworth; Jessica K Tyler; Elena V Tyutereva; Yasuo Uchiyama; Aslihan Ugun-Klusek; Holm H Uhlig; Marzena Ułamek-Kozioł; Ilya V Ulasov; Midori Umekawa; Christian Ungermann; Rei Unno; Sylvie Urbe; Elisabet Uribe-Carretero; Suayib Üstün; Vladimir N Uversky; Thomas Vaccari; Maria I Vaccaro; Björn F Vahsen; Helin Vakifahmetoglu-Norberg; Rut Valdor; Maria J Valente; Ayelén Valko; Richard B Vallee; Angela M Valverde; Greet Van den Berghe; Stijn van der Veen; Luc Van Kaer; Jorg van Loosdregt; Sjoerd J L van Wijk; Wim Vandenberghe; Ilse Vanhorebeek; Marcos A Vannier-Santos; Nicola Vannini; M Cristina Vanrell; Chiara Vantaggiato; Gabriele Varano; Isabel Varela-Nieto; Máté Varga; M Helena Vasconcelos; Somya Vats; Demetrios G Vavvas; Ignacio Vega-Naredo; Silvia Vega-Rubin-de-Celis; Guillermo Velasco; Ariadna P Velázquez; Tibor Vellai; Edo Vellenga; Francesca Velotti; Mireille Verdier; Panayotis Verginis; Isabelle Vergne; Paul Verkade; Manish Verma; Patrik Verstreken; Tim Vervliet; Jörg Vervoorts; Alexandre T Vessoni; Victor M Victor; Michel Vidal; Chiara Vidoni; Otilia V Vieira; Richard D Vierstra; Sonia Viganó; Helena Vihinen; Vinoy Vijayan; Miquel Vila; Marçal Vilar; José M Villalba; Antonio Villalobo; Beatriz Villarejo-Zori; Francesc Villarroya; Joan Villarroya; Olivier Vincent; Cecile Vindis; Christophe Viret; Maria Teresa Viscomi; Dora Visnjic; Ilio Vitale; David J Vocadlo; Olga V Voitsekhovskaja; Cinzia Volonté; Mattia Volta; Marta Vomero; Clarissa Von Haefen; Marc A Vooijs; Wolfgang Voos; Ljubica Vucicevic; Richard Wade-Martins; Satoshi Waguri; Kenrick A Waite; Shuji Wakatsuki; David W Walker; Mark J Walker; Simon A Walker; Jochen Walter; Francisco G Wandosell; Bo Wang; Chao-Yung Wang; Chen Wang; Chenran Wang; Chenwei Wang; Cun-Yu Wang; Dong Wang; Fangyang Wang; Feng Wang; Fengming Wang; Guansong Wang; Han Wang; Hao Wang; Hexiang Wang; Hong-Gang Wang; Jianrong Wang; Jigang Wang; Jiou Wang; Jundong Wang; Kui Wang; Lianrong Wang; Liming Wang; Maggie Haitian Wang; Meiqing Wang; Nanbu Wang; Pengwei Wang; Peipei Wang; Ping Wang; Ping Wang; Qing Jun Wang; Qing Wang; Qing Kenneth Wang; Qiong A Wang; Wen-Tao Wang; Wuyang Wang; Xinnan Wang; Xuejun Wang; Yan Wang; Yanchang Wang; Yanzhuang Wang; Yen-Yun Wang; Yihua Wang; Yipeng Wang; Yu Wang; Yuqi Wang; Zhe Wang; Zhenyu Wang; Zhouguang Wang; Gary Warnes; Verena Warnsmann; Hirotaka Watada; Eizo Watanabe; Maxinne Watchon; Anna Wawrzyńska; Timothy E Weaver; Grzegorz Wegrzyn; Ann M Wehman; Huafeng Wei; Lei Wei; Taotao Wei; Yongjie Wei; Oliver H Weiergräber; Conrad C Weihl; Günther Weindl; Ralf Weiskirchen; Alan Wells; Runxia H Wen; Xin Wen; Antonia Werner; Beatrice Weykopf; Sally P Wheatley; J Lindsay Whitton; Alexander J Whitworth; Katarzyna Wiktorska; Manon E Wildenberg; Tom Wileman; Simon Wilkinson; Dieter Willbold; Brett Williams; Robin S B Williams; Roger L Williams; Peter R Williamson; Richard A Wilson; Beate Winner; Nathaniel J Winsor; Steven S Witkin; Harald Wodrich; Ute Woehlbier; Thomas Wollert; Esther Wong; Jack Ho Wong; Richard W Wong; Vincent Kam Wai Wong; W Wei-Lynn Wong; An-Guo Wu; Chengbiao Wu; Jian Wu; Junfang Wu; Kenneth K Wu; Min Wu; Shan-Ying Wu; Shengzhou Wu; Shu-Yan Wu; Shufang Wu; William K K Wu; Xiaohong Wu; Xiaoqing Wu; Yao-Wen Wu; Yihua Wu; Ramnik J Xavier; Hongguang Xia; Lixin Xia; Zhengyuan Xia; Ge Xiang; Jin Xiang; Mingliang Xiang; Wei Xiang; Bin Xiao; Guozhi Xiao; Hengyi Xiao; Hong-Tao Xiao; Jian Xiao; Lan Xiao; Shi Xiao; Yin Xiao; Baoming Xie; Chuan-Ming Xie; Min Xie; Yuxiang Xie; Zhiping Xie; Zhonglin Xie; Maria Xilouri; Congfeng Xu; En Xu; Haoxing Xu; Jing Xu; JinRong Xu; Liang Xu; Wen Wen Xu; Xiulong Xu; Yu Xue; Sokhna M S Yakhine-Diop; Masamitsu Yamaguchi; Osamu Yamaguchi; Ai Yamamoto; Shunhei Yamashina; Shengmin Yan; Shian-Jang Yan; Zhen Yan; Yasuo Yanagi; Chuanbin Yang; Dun-Sheng Yang; Huan Yang; Huang-Tian Yang; Hui Yang; Jin-Ming Yang; Jing Yang; Jingyu Yang; Ling Yang; Liu Yang; Ming Yang; Pei-Ming Yang; Qian Yang; Seungwon Yang; Shu Yang; Shun-Fa Yang; Wannian Yang; Wei Yuan Yang; Xiaoyong Yang; Xuesong Yang; Yi Yang; Ying Yang; Honghong Yao; Shenggen Yao; Xiaoqiang Yao; Yong-Gang Yao; Yong-Ming Yao; Takahiro Yasui; Meysam Yazdankhah; Paul M Yen; Cong Yi; Xiao-Ming Yin; Yanhai Yin; Zhangyuan Yin; Ziyi Yin; Meidan Ying; Zheng Ying; Calvin K Yip; Stephanie Pei Tung Yiu; Young H Yoo; Kiyotsugu Yoshida; Saori R Yoshii; Tamotsu Yoshimori; Bahman Yousefi; Boxuan Yu; Haiyang Yu; Jun Yu; Jun Yu; Li Yu; Ming-Lung Yu; Seong-Woon Yu; Victor C Yu; W Haung Yu; Zhengping Yu; Zhou Yu; Junying Yuan; Ling-Qing Yuan; Shilin Yuan; Shyng-Shiou F Yuan; Yanggang Yuan; Zengqiang Yuan; Jianbo Yue; Zhenyu Yue; Jeanho Yun; Raymond L Yung; David N Zacks; Gabriele Zaffagnini; Vanessa O Zambelli; Isabella Zanella; Qun S Zang; Sara Zanivan; Silvia Zappavigna; Pilar Zaragoza; Konstantinos S Zarbalis; Amir Zarebkohan; Amira Zarrouk; Scott O Zeitlin; Jialiu Zeng; Ju-Deng Zeng; Eva Žerovnik; Lixuan Zhan; Bin Zhang; Donna D Zhang; Hanlin Zhang; Hong Zhang; Hong Zhang; Honghe Zhang; Huafeng Zhang; Huaye Zhang; Hui Zhang; Hui-Ling Zhang; Jianbin Zhang; Jianhua Zhang; Jing-Pu Zhang; Kalin Y B Zhang; Leshuai W Zhang; Lin Zhang; Lisheng Zhang; Lu Zhang; Luoying Zhang; Menghuan Zhang; Peng Zhang; Sheng Zhang; Wei Zhang; Xiangnan Zhang; Xiao-Wei Zhang; Xiaolei Zhang; Xiaoyan Zhang; Xin Zhang; Xinxin Zhang; Xu Dong Zhang; Yang Zhang; Yanjin Zhang; Yi Zhang; Ying-Dong Zhang; Yingmei Zhang; Yuan-Yuan Zhang; Yuchen Zhang; Zhe Zhang; Zhengguang Zhang; Zhibing Zhang; Zhihai Zhang; Zhiyong Zhang; Zili Zhang; Haobin Zhao; Lei Zhao; Shuang Zhao; Tongbiao Zhao; Xiao-Fan Zhao; Ying Zhao; Yongchao Zhao; Yongliang Zhao; Yuting Zhao; Guoping Zheng; Kai Zheng; Ling Zheng; Shizhong Zheng; Xi-Long Zheng; Yi Zheng; Zu-Guo Zheng; Boris Zhivotovsky; Qing Zhong; Ao Zhou; Ben Zhou; Cefan Zhou; Gang Zhou; Hao Zhou; Hong Zhou; Hongbo Zhou; Jie Zhou; Jing Zhou; Jing Zhou; Jiyong Zhou; Kailiang Zhou; Rongjia Zhou; Xu-Jie Zhou; Yanshuang Zhou; Yinghong Zhou; Yubin Zhou; Zheng-Yu Zhou; Zhou Zhou; Binglin Zhu; Changlian Zhu; Guo-Qing Zhu; Haining Zhu; Hongxin Zhu; Hua Zhu; Wei-Guo Zhu; Yanping Zhu; Yushan Zhu; Haixia Zhuang; Xiaohong Zhuang; Katarzyna Zientara-Rytter; Christine M Zimmermann; Elena Ziviani; Teresa Zoladek; Wei-Xing Zong; Dmitry B Zorov; Antonio Zorzano; Weiping Zou; Zhen Zou; Zhengzhi Zou; Steven Zuryn; Werner Zwerschke; Beate Brand-Saberi; X Charlie Dong; Chandra Shekar Kenchappa; Zuguo Li; Yong Lin; Shigeru Oshima; Yueguang Rong; Judith C Sluimer; Christina L Stallings; Chun-Kit Tong
Journal:  Autophagy       Date:  2021-02-08       Impact factor: 13.391

4.  The neuroprotective effects of activated α7 nicotinic acetylcholine receptor against mutant copper-zinc superoxide dismutase 1-mediated toxicity.

Authors:  Taisei Ito; Masatoshi Inden; Tomoyuki Ueda; Yuta Asaka; Hisaka Kurita; Isao Hozumi
Journal:  Sci Rep       Date:  2020-12-17       Impact factor: 4.379

5.  Phosphoinositide-3-kinase regulatory subunit 4 participates in the occurrence and development of amyotrophic lateral sclerosis by regulating autophagy.

Authors:  Yue Liu; Cai-Hui Wei; Cheng Li; Wen-Zhi Chen; Yu Zhu; Ren-Shi Xu
Journal:  Neural Regen Res       Date:  2022-07       Impact factor: 6.058

Review 6.  Implications of Selective Autophagy Dysfunction for ALS Pathology.

Authors:  Emiliano Vicencio; Sebastián Beltrán; Luis Labrador; Patricio Manque; Melissa Nassif; Ute Woehlbier
Journal:  Cells       Date:  2020-02-07       Impact factor: 6.600

Review 7.  Homeostatic Roles of the Proteostasis Network in Dendrites.

Authors:  Erin N Lottes; Daniel N Cox
Journal:  Front Cell Neurosci       Date:  2020-08-14       Impact factor: 5.505

  7 in total

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