Study design
The aim of this study was to find key factors related to microglial functional differences according to ALS progression speed using a microglia-like cell model (iMGs) as a translational research tool. First, the iMG model was shown to exhibit the signature gene patterns of brain microglia and the innate functions of microglia in healthy donors. To further validate the model, we compared iMGs to brain microglia that were obtained from the same ALS patient. Thereafter, we conducted a systematic comparative analysis to delineate the different natures of iMGs in ALS patients according to speed of clinical progression. We enrolled two distinct sporadic ALS patient groups dichotomized by clinical progression speed: one group with slowly progressing ALS [ALS(S), n = 14] and one group with rapidly progressing ALS [ALS(R), n = 15] according to the revised El Escorial criteria between September 2015 and July 2017. Second, we endeavored to identify target molecule(s) related to the functional properties of microglia that are present only in ALS(R)-iMGs. To do this, we compared transcriptome data between ALS(R)-iMGs and ALS(S)-iMGs. Subsequently, we conducted functional studies on an identified target molecule. Finally, we found a clinically applicable serologic biomarker related to activity of the target molecule that is well correlated with both levels of the target molecule and speed of progression of ALS.
Participants and Samples
We enrolled five healthy volunteers and twenty-nine patients with sporadic ALS (14 patients with slow progression and 15 patients with rapid progression) according to the revised El Escorial criteria [29] between September 2015 and July 2017. Patients with clinically definite, clinically probable, clinically probable with laboratory-supported, or possible sALS were recruited for this study. None of the participants had any evidence of recent infectious or inflammatory diseases. Individual medical records were reviewed to obtain clinical characteristics such as age, sex, family history of ALS, region of symptom onset, ALS functional rating scale-revised (ALSFRS-R) score [29], and changing pattern of ALSFRS-R score reflecting the speed of progression of ALS. The progression rate was defined as delta FS [30], (i.e., (48 - ALSFRS-R score at the time of diagnosis)/(duration from onset to diagnosis in months)). In order to enroll only participants who exhibited extremely slow or extremely rapid clinical progression, the sALS patients were categorized by using Hanyang MND registry as follows: The mean value was 0.83±0.81, slowly progressive ALS = delta FS ≤ 0.36, and rapidly progressive ALS = delta FS > 1.0. The difference between delta FS value (from onset to diagnosis vs. from onset to at the time of blood sampling) was not significant in both groups. The clinical and genetic characteristics of the participants are presented in Additional file 1: Table S1. Schematic outlines of the serial studies that are described in the Methods and Results sections are summarized in Additional file 2: Figure S1. Blood samples were obtained for generation of iMGs and post-hoc analysis of biomarkers, including inflammatory cytokines and microRNAs, after obtaining informed consent from each patient with sALS and matched controls comparable in age and sex at the ALS clinic, Hanyang University Hospital, Seoul, Republic of Korea. This study was conducted in accordance with the World Medical Association’s Declaration of Helsinki. It was approved by the Ethics Committee of Hanyang University (HYUH IRB 2013-06-012 and 2017-01-043).
Genetic analysis
Genomic DNA was extracted from peripheral blood leukocytes using a standard procedure. Next-generation sequencing (NGS) was performed with SureSelect Human All Exon V5 (SureSelect; Agilent Technologies, Santa Clara, CA) on a NextSeq500 platform (Illumina, Inc.). Alignment of sequence reads, indexing of a reference genome (GRCh37/hg19), and variant calling were performed with a pipeline based on GATK Best Practices. Variants with allele frequencies > 0.01 identified in the Genome Aggregation Database (http://gnomad.broadinstitute.org/) were filtered out. Variants found in 1,100 ethnically-matched controls from the Korean Reference Genome Database (http://152.99.75.168/KRGDB/) were also filtered out. Next, 46 genes related to frontotemporal dementia (FTD), ALS, and other dementias were screened for pathogenic or likely pathogenic variants (Additional file 1: Table S1 and Additional file 3: Table S2). These variants were classified according to the guidelines of the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP). APOE genotype was also analyzed using whole-exon sequencing data (Additional file 1: Table S1).
Establishment of induced microglia-like cells (iMGs) from human peripheral blood
iMG cells were established based on a method previously published by Ohganani [27]. Briefly, peripheral blood was collected from healthy adult volunteers and ALS patients using a heparinized tube. PBMCs were isolated by density gradient centrifugation using Ficoll (GE Healthcare), according to our previous study [31]. The cells were resuspended in RPMI-1640 (Gibco, Waltham, MA) containing 10% FBS (Gibco) and 1% antibiotic/antimycotic (Invitrogen, Carlsbad, CA). PBMCs were plated in culture chambers at a density of 500,000 cells/ml and cultured overnight under standard culture conditions (37°C, 5% CO2). On the next day, the medium was carefully aspirated and adherent cells (monocytes) were cultured in RPMI-1640 Glutamax (Gibco) supplemented with 1% antibiotic/antimycotic, recombinant human granulocyte-macrophage colony-stimulating factor (GM-CSF) (10 ng/ml; R&D Systems, Minneapolis, MN), and recombinant human interleukin-34 (IL-34) (100 ng/ml; R&D Systems) to develop iMG cells. After 14 days, the plates were washed thoroughly to remove any unbound cells. Fresh medium with GM-CSF and IL-34 was then added. Cells were harvested or used for functional assays for up to 21 days (7 additional days). For microglia stimulation, cells were treated with 100 ng/ml lipopolysaccharide (LPS, Sigma-Aldrich, St. Louis, MO) for 18 h, 40 ng/ml IL-4 (Peprotech, Rocky Hill, NJ) for 72 h, or 2 nM dexamethasone (Sigma Aldrich) for 72 h [32].
Cell morphology
Morphological changes of microglia-like cells were examined using a phase-contrast microscope (TS100-F; Nikon Instech, Tokyo, Japan). Images were captured with a DS-Vi1 digital camera (Nikon Instech) and a DS-L3 control unit (Nikon Instech).
Flow cytometry
Fluorochrome-conjugated monoclonal antibodies specific for human CD11b (APCVio770; Miltenyi Biotec, Gladbach, Germany) and CD45 (PE; Miltenyi Biotec) were used for iMGs phenotyping. The cells were washed with MACS buffer (Miltenyi Biotec) and incubated at 4°C for 5 min in FcR-blocking reagent (Miltenyi Biotec). The cell suspension was incubated with antibodies for 30 min at 4°C, washed with calcium-magnesium-free phosphate-buffered saline (PBS), resuspended, and fixed with 1% paraformaldehyde (Wako, Osaka, Japan) in PBS. The expression ratio of CD11b to CD45 was calculated from the fluorescence intensity of each fluorochrome. All data were collected with a FACS Canto II flow cytometer (BD Biosciences) and analyzed with FACS Diva and Flow Jo software (BD Biosciences).
Immunocytochemistry
The cells were fixed with 4% paraformaldehyde and permeabilized with 0.3% Triton X-100 for 5 min, then blocked with 1% bovine serum albumin (BSA) in PBS for 1 hour. Then, the samples were incubated with primary antibodies overnight at 4°C and labeled with secondary antibodies for 30 min at room temperature. The following primary antibodies were used in this study: Rabbit anti-CX3CR1 (Abcam, ab8021, 1:200), mouse anti-CCR2 (R&D Systems, MAB150, 1:200), rabbit anti-P2RY12 (Abcam, ab140862, 1:200), rabbit anti-P2RY12 (antibodies-online, ABIN1387659, 1:200), mouse anti-IBA1 (Abcam, ab15690, 1:200), rabbit anti-IBA1 (Wako, 019-19741, 1:200), rabbit anti-TMEM119 (Abcam, ab185337, 1:200), goat anti-TMEM119 (Santa Cruz, SC-244341, 1:200), mouse anti-PU.1/Spi1 (Abcam, ab88082, 1:200), rabbit anti-PU.1/Spi1 (Cell Signaling Technology, 2266, 1:100), rabbit anti-NCKAP1 (Novus Biologicals, NBP1-83269, 1:200), mouse anti-WAVE (Santa Cruz, sc-373889, 1:200), and mouse anti-ABI (Santa Cruz, sc-398554, 1:200). Alexa 488-, Alexa 546-, or Alexa 647-conjugated secondary antibodies (Invitrogen) were used for detection. To stain actin filaments, cells were incubated with fluorescent phalloidin (Molecular Probes, 1: 1,000 dilution) for 45 min with secondary antibodies. The samples were mounted in SlowFade antifade medium (Invitrogen). Images were acquired with a confocal microscope (TCS SP5, Leica, Wetzlar, Germany). Three-dimensional reconstructions of randomly selected iMG cells (IBA-1-positive) were generated using Imaris software (Bitplane, Zurich, Switzerland). Morphometric analysis of each reconstructed cell was then performed by two blinded researchers after determining dendrite length, number of segments, branch point, terminal point, and surface volume [33].
Quantitative real time-polymerase chain reaction (qRT-PCR)
Total RNA was extracted using Trizol reagent (Invitrogen) and evaluated using a NanoDrop 2000 spectrophotometer (Thermo Scientific, ND-2000). cDNA was synthesized using an EcoDryTM cDNA kit (Clontech, CA, USA). To assess the microglia signature in HC-iMGs, we analyzed the gene expression levels of P2RY12 (Qiagen, Germany, PPH02545B), OLFML3 (PPH07681A), OLFML3 (PPH07681A), TGFBR1 (PPH00237C), TMEM119 (PPH21875A), TREM2 (PPH06065E), and GAPDH (PPH00150F). To evaluate gene expression patterns in iMG cells after treatment with LPS, IL-4, dexamethasone, or during phagocytosis, we analyzed HLA-DR (PPH00857F), CD45 (PPH01510C), TNF-α (PPH00341F), CCR7 (PPH00617A), CCL18 (PPH00574C), and CD200R (PPH16717A) mRNA levels. To assess microglia signature and senescence in ALS(S) and ALS(R)-iMGs cells, we analyzed GPR34 (PPH08814A), MERTK (PPH 16600A), CSF1R (PPH00191F), HEXB (PPH09801A), p21 (NM_000389, F– CGAAGTCAGTTCCTTGTGGAG, R-CATGGGTTCTGACGGACAT), and p16 (PPH00207C) mRNA levels. To confirm the transcriptome analysis results, NCKAP1 (PPH15666A), VAV3 (PPH0150E), MYO10 (PPH09689A), FYN (PPH15624A), ARPC1A (PPH16239A), SLC11A1 (PPH05732F), MFGE8 (PPH07218A), ANXA11 (PPH06949A), WAS (PPH07123A), PTX3 (PPH01105A), CD36 (PPH01456A), FCGR2B (PPH02368C), GAS6 (PPH00025F), TYROBP (PPH07729A), and TREM2 (PPH06065E) were analyzed. To examine alterations in the expression of pro- and anti-inflammatory cytokines after LPS stimulation (100 ng/ml for 18 h), we analyzed TNF-α (PPH00341F), IL-6 (PPH00560C), IL-1β (PPH00171C), TGF-β (PPH00524B), IL-10 (PPH00572C), NF-κB-p50 (PPH00204F), and NF-κB-p65 (PPH01812B) mRNA levels. cDNA was amplified using Power SYBR Green PCR Master Mix with primers on an Applied Biosystems Step One PlusTM system (Life Technologies) at 95°C for 10 min, followed by 40 cycles of 15 s at 95°C and 1 min at 60°C. A melting curve was generated to examine the specificity of amplification. Relative quantity (RQ) levels were calculated with the 2−ΔΔCt method using GAPDH as an internal standard control. The reported results are based on three independent experiments carried out on separate batches of cells.
Phagocytosis assay
To quantify phagocytosis in iMGs, iMGs that had been optimally cultured for 21 days were treated with 4 µl red fluorescent latex beads for 24 h at 37°C. Phagocytic activity was halted with the addition of 2 ml ice-cold PBS. The cells were washed twice with ice-cold PBS, fixed, stained with a microglial marker (IBA-1 or P2RY12), and counterstained with DAPI. Cells were analyzed by confocal microscopy (TCS SP5, Leica). The number of phagocytized beads per IBA-1-positive or P2RY12-positive cell was counted using image J software for phagocytic activity [34]. To assess phagocytosis cup formation in iMGs, cells were fixed by adding latex beads for 2 h. For live cell imaging of phagocytosis, iMG cells were grown in imaging dishes (Chamber Slide Lab-Tek II 4; Fisher) and labeled with 100 nM SiR-actin dye (for cytoskeleton staining; Cytoskeleton Inc., North America, USA) according to the manufacturer’s protocol [35]. After washing twice with PBS, the old medium was replaced with fresh medium. Three microliters of latex beads (1.1 μm, Sigma-Aldrich) were added to the cells before analysis. Images were captured at a rate of one frame every 1 min 30 sec over a 5 h period. Live imaging was performed using a DeltaVision fluorescence microscopy system (Applied Precision) installed at the Hanyang Center for Research Facilities.
Isolation of human brain microglia from the neural tissue of sALS patients
We confirmed the microglia signature of iMGs that originated from monocytes from an sALS patient whose blood sample was collected just one day before death. We immediately isolated microglia from fresh brain tissue (brain-MG) from the same patient. The patient had no known pathogenic mutations, including FUS, C9orf72, SOD1, ALS2, SPG11, UBQLN2, DAO, GRN, SQSTM1, SETX, MAPT, TARDBP, or TAF15 gene mutations. For brain-MG culture, the immediately-obtained fresh middle temporal gyrus was washed in HBSS. The tissue was then diced into ~1 mm3 pieces using a sterile scalpel and transferred to a 50 ml falcon tube containing 10 ml enzyme dissociation mixture with 10 U/ml DNase (Invitrogen) and 2.5 U/ml papain (Worthington, NJ, USA) in Hibernate-A medium (Gibco) (per gram of tissue). The mixture was incubated at 37°C for 10 min with gentle rotation. The tissue was removed from the incubator, gently triturated to aid digestion, and returned to the incubator for a further 10 min. Dissociation was slowed by adding equal volumes of Dulbecco’s modified Eagle medium and F-12 medium (DMEM/F12; Gibco) with 1% B27 (Gibco). The cell suspension was passed through a 70 μm cell strainer (Bector Dickinson, NJ, USA). Cells were centrifuged at 160 × g for 10 min. The supernatant was discarded and the cell pellet was resuspended in 20 ml DMEM/F12 with 1% B27, 1% GlutaMAX (Gibco), and 1% penicillin-streptomycin-glutamine (PSG; Gibco). Next, one-third volume of cold Ficoll (GE Healthcare, Little Chalfont, UK) was added to the cell suspension, and the tube was centrifuged at 4000 rpm for 30 min at 4°C. The interphase containing the microglia was transferred to a new tube (the myelin and erythrocyte layers were discarded) and washed twice with DMEM supplemented with 10% FCS, 1% Pen/Strep, 1% gentamycin, and 25 mM HEPES (Invitrogen). Negative selection of granulocytes (previous method only) and positive selection of microglia with anti-CD15- and anti-CD11b-conjugated magnetic microbeads (Miltenyi Biotec), respectively, were performed by magnetic activated cell sorting (MACS) according to the manufacturer’s protocol [36]. Briefly, cells were incubated with 10 μl CD15 microbeads for 15 min at 4°C, washed, suspended in bead buffer (0.5% BSA, 2 mM EDTA in PBS, pH 7.2), and transferred to an MS column placed in a magnetic holder. The flow-through containing unlabeled cells was collected, washed, and incubated with 20 μl CD11b microbeads for 15 min at 4°C. The cells were then washed and placed on a new MS column in a magnetic holder. The CD11b+ cell fraction was eluted by removing the column from the magnet, adding bead buffer, and emptying the column with a plunger. Acutely isolated primary microglia were suspended in Trizol reagent (Invitrogen) and stored at -80°C.
We isolated monocytes from the blood of the same patient using anti-CD14-conjugated magnetic microbeads (Miltenyi Biotec) according to the manufacturer’s protocol. The isolated monocytes were suspended in Trizol reagent (Invitrogen) and stored at -80°C for RNA-seq and qPCR.
RNA sequencing and data analysis
Total RNA was isolated using Trizol reagent (Invitrogen). RNA quality was assessed with an Agilent 2100 bioanalyzer using an RNA 6000 Nano Chip (Agilent Technologies, Amstelveen, Netherlands). Control and test RNA libraries were constructed using a SENSE 3′ mRNA-Seq Library Prep Kit (Lexogen, Inc., Austria) according to the manufacturer’s instructions. The library was amplified to add complete adapter sequences required for cluster generation. The constructed library was purified from PCR components. High-throughput sequencing was performed as single-end 75 sequencing using a NextSeq 500 platform (Illumina, Inc., USA). SENSE 3′ mRNA-Seq reads were aligned using Bowtie2 version 2.1.0 [37]. Bowtie2 indices were generated either from genome assembly sequences or from representative transcript sequences aligned with the genome and transcriptome. The alignment file was used to perform transcript assembly, estimate gene abundance, and detect differential gene expression. Differentially expressed genes (DEGs) were determined based on counts from unique and multiple alignments using EdgeR in R version 3.2.2 and BIOCONDUCTOR version 3.0 [38]. Read count (RT) data were processed based on the global normalization method using Genowiz™ version 4.0.5.6 (Ocimum Biosolutions, India). Gene classification was based on searches performed in the DAVID (http://david.abcc.ncifcrf.gov/) and Medline (http://www.ncbi.nlm.nih.gov/) databases. We used MeV 4.9.0 to perform sample and gene clustering and to visualize gene clusters and heat maps. Hierarchical cluster analyses were performed using Euclidean distance as a similarity measurement with average linkage heuristic.
Cell culture
Human microglial clone 3 cells (HMC3 cells) (ATCC®CRL-3304) were cultured in Eagle's Minimum Essential Medium containing 10% FBS (Gibco) and antibiotics. HeLa cells were cultured in Dulbecco’s modified Eagle’s medium containing 10% FBS (Gibco), sodium bicarbonate, sodium pyruvate (Sigma), and antibiotics. HeLa cells were transiently transfected with GFP-tagged human NCKAP1 cDNA constructs or with NCKAP1 shRNA using Lipofectamine® 2000 (Invitrogen) according to the manufacturer’s protocol. For human NCKAP1 overexpression or knockdown experiments, cells were transduced with pLenti-C-mGFP-Human NCK-associated protein 1 (NCKAP1, NM_013436), cDNA ORF Clone (OriGene Technologies, Rockville, MD, USA), or pGFP-C-shLenti-NCKAP1 Human shRNA lentiviral particles (Gene ID 10787, OriGene Technologies) two days before analysis according to the manufacturer’s protocol.
Immunoblotting
Cells were washed twice with PBS and incubated on ice in RIPA buffer for 10 min. Equal amounts of protein from each sample were separated by SDS-PAGE and transferred to a PVDF membrane (GE Healthcare). The membrane was blocked with 5% skim milk and incubated with the following primary antibodies: rabbit anti-NCKAP1 (Novus Biologicals, NBP1-83269, 1:1000), rabbit anti-CYFIP1 (Sigma, SAB2700152, 1:1000), mouse anti-WAVE2 (Santa Cruz, sc-373889, 1:200), rabbit anti-WAVE1 (Sigma, SAB4503508, 1:1000), mouse anti-ABI (Santa Cruz, sc-398554, 1:1000), and anti-GAPDH (Santa Cruz, SC-25778, 1:1000). Membranes were washed with Tris-buffered saline containing 0.05% Tween-20 and processed using a horseradish peroxidase (HRP)-conjugated secondary anti-rabbit or -mouse antibody (Amersham Pharmacia Biotech) followed by enhanced chemiluminescence (ECL) detection (Amersham Pharmacia Biotech). Western blot results were quantified with an image analyzer (Quantity One-4, 2, 0; Bio-Rad) and normalized to GAPDH expression. The reported results are based on three independent experiments done using separate batches of cells.
Enzyme-linked immunosorbent assay
Secretion of pro- and anti-inflammatory cytokines (TNF-α, IL-1β, IL-6, IL-10, and TGF-β1) during LPS stimulation from culture supernatants was tested using a commercially available cytokine assay kit obtained from Millipore (Billerica, MA), according to the manufacturer’s protocol. Human IL-6, interferon (IFN)-γ, IL-8, TNF-α, and CCL2/MCP-1 (R&D Systems) were used to determine cytokine concentration in plasma samples of patients with ALS and healthy controls according to the manufacturer’s instructions. Each assay was performed in triplicate.
miRNA mimics and inhibitor transfection
miR-214 and miR-34 mimics or inhibitors and control oligonucleotides were synthesized by Bioneer Corporation (Daejeon, Korea). Their sequences are as follows: miR-214-3p mimic, 5′-UGCCUGUCUACACUUGCUGUGC-3′; miR-34c-3p mimic, 5′-AAUCACUAACCACACGGC AGG-3′; miRNA mimic negative control #1 (SMC-2003); miR-214-5p inhibitor, 5′-UGCCUGUCUACACUUGCUGUGC-3′; miR-214-3p inhibitor, 5′-ACAGCAGGCACAGA CAGGCAGU-3′; miR-34c-3p inhibitor, 5′-AAUCACUAACCACACGGCCAGG-3′; and miRNA inhibitor negative control #1 (SMC-2103). Synthetic miRNA mimics, inhibitors, and the negative control were transfected into HeLa cells using Lipofectamine® RNAiMAX (Invitrogen) according to the manufacturer’s instructions. Briefly, 50 nM miRNA mimic, miRNA inhibitor, or negative control were transfected into cells plated at 3 × 105 cells/well in 6-well plates.
Plasma miRNA analysis
The small RNA-enriched fraction was extracted from 625 μl of the plasma sample using a mirVana miRNA isolation kit, following the manufacturer's instructions (Ambion, Austin, TX). The purity of the extracted RNA was quantified using a NanoDrop™ 1000 spectrophotometer. For reverse transcription and quantitative real-time PCR, a fixed volume of 5 μl of the small RNA-enriched fraction obtained from a given sample was used for the reverse transcription (RT) reaction. For synthesis of each miRNA-specific cDNA, miRNA was reverse transcribed using the TaqMan miRNA reverse transcription kit (Life Technologies). The following primers were used for endogenous controls (Life Technologies): hsa-miR-214-3p (4427975, ID002306) and hsa-miR-34c-3p (4427975, ID 241009_mat). The reaction mixture was incubated at 16°C for 30 min, 42°C for 30 min, and 85°C for 5 min. TaqMan™ (Life Technologies) assays were used to quantify mature miRNA transcripts according to the manufacturer’s recommendations. PCR experiments were performed using an Applied Biosystems Step One PlusTM system (Life Technologies) under the following cycling conditions: 95°C for 10 min with 45 cycles of 95°C for 15 s and 60°C for 1 min. Data analysis was performed to determine the threshold cycle (Ct). Relative quantities of miRNA were calculated using the 2−ΔΔCt method after normalization to hsa-miR-16 levels in plasma samples.
Statistical analysis
Data are presented as mean ± SEM. The statistical significance of differences between groups was assessed with Student’s t-test, one way-ANOVA, and two way-ANOVA using GraphPad Prism 7 (GraphPad Software, San Diego, CA). The findings were regarded as significant when *p < 0.05, **p < 0.01, ***p < 0.001, and **** p < 0.0001. In post-hoc analysis, p-values were obtained by Pearson correlation.