Neuroscience Letters 562 (2014) 34–38
Contents lists available at ScienceDirect
Neuroscience Letters journal homepage: www.elsevier.com/locate/neulet
Autophagy-related gene16L2, a potential serum biomarker of multiple sclerosis evaluated by bead-based proteomic technology Linlin Yin a,∗,1 , Jianghong Liu b,1 , Huiqing Dong b , Erhe Xu b , Yuchen Qiao b , Lin Wang b , Lan Zhang a , Jianping Jia b , Lin Li a,∗∗ , Xingchao Geng c,∗∗,1 a Department of Pharmacology, Xuan Wu Hospital of Capital Medical University, Beijing Geriatric Medical Research Center, Key Laboratory for Neurodegenerative Disease of Ministry of Education, PR China b Department of Neurology, Xuan Wu Hospital of Capital Medical University, 45 Changchun Street, Beijing, 100053, PR China c National Institute for Food and Drug Control, Beijing 100050, P. R. China
h i g h l i g h t s • • • •
Serum of Multiple sclerosis (MS) patients were evaluated by bead-based proteomic technology. Decreased levels of Atg16L2 in MS patients compared to controls were found. We further validated the decreased Atg16L2 by immunoblotting and real-time PCR. Decreased Atg16L2 may affect autophagy of T cells and contribute to MS relapse.
a r t i c l e
i n f o
Article history: Received 26 November 2013 Received in revised form 27 December 2013 Accepted 30 December 2013 Keywords: Atg16L2 multiple sclerosis proteomic technology T cells
a b s t r a c t Multiple sclerosis (MS) is an autoimmune disease characterized by neuroinflammation and demyelination that are mediated by T cells. The prolonged survival of autoreactive T cells acts as a primary event to trigger an inflammatory cascade that mediates myelin loss and clinical relapse in MS. Recently, T cell survival has been shown to be modulated by the autophagy-related gene (Atg). In the present study, we performed bead fractionation/matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry analyses using serum from 54 MS patients and 55 healthy controls. Eleven peptides were significantly different between the two groups with one being identified as a fragment of Atg16L2. Then the decreased levels of Atg16L2 peptides in MS patients were validated by immunoblotting and real-time PCR. As the Atg12-Atg5·Atg16 multimeric complex plays an essential role in autophagy, our results suggest that Atg16L2 may play an important role in autophagy of T cells and serve as a potential biomarker to predict clinical relapse of MS. © 2014 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Multiple sclerosis (MS) is an autoimmune disease of the central nervous system (CNS) that is characterized by inflammation and demyelination, afflicting approximately 2.5 million people worldwide. The clinical presentation of MS is heterogeneous including relapsing-remitting MS (RRMS), secondary progressive MS (SPMS) and primary progressive MS (PPMS) [16]. Identification of MS-specific biomarkers is clinically useful because these markers would allow relapse prediction and the early initiation
∗ Corresponding author. Tel.: +86 10 8319 8881; fax: +86 10 8315 4745. ∗∗ Corresponding authors. E-mail addresses: [email protected] (L. Yin), [email protected] (L. Li), [email protected] (X. Geng). 1 These authors contributed equally to this work. 0304-3940/$ – see front matter © 2014 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.neulet.2013.12.070
of therapeutic interventions. Although many studies have investigated serum and cerebrospinal fluid (CSF) biomarkers [7,12], including cytokines [17], chemokines and their receptors [3,19] and antibodies [20], serum biomarkers are more convenient for monitoring disease development in clinical practice. Therefore, it is of utmost importance to develop a new method to detect serum peptide biomarkers in MS patients. Peptidome analyses based on mass spectrometric screening methods have been developed and offer a high-throughput approach to discover new potential biomarkers in various body fluids [4,10]. In the present study, we used affinity-bead purification and nano-liquid chromatography–electrospray ionization-tandem (Nano-LC/ESI) mass spectrometry to detect serum markers in patients with MS compared with healthy controls. Three peptides were identified and one of them was validated by immunoblotting and real-time PCR assay.
L. Yin et al. / Neuroscience Letters 562 (2014) 34–38 Table 1 Clinical characteristics of patients with MS and healthy controls.
MS
RRMS SPMS PPMS NDa Sex (Male: Female) Mean age (range) EDSS (number of subjects) 0–3.5 4.0–5.5 6.0–8.0 Mean (range) Immunomodulatory treatments Corticosteroids Interferon- Mitoxantrone
Healthy control Sex (Male: Female) Mean age (range) a
Training group
Validation group
10 11 8 1 11:19 39.3 (19 – 60)
9 7 5 3 6:18 39.4 (21 – 60)
21 6 3 2.9 (0 – 6.0)
13 7 4 3.7 (2 – 6.5)
22 2 2 32
15 0 2 23
12:20 39.1 (22 – 67)
10:13 38.5 (22 – 56)
ND, the MS subtype was not determined.
2. Materials and methods 2.1. Patients and blood samples Serum samples were donated by 54 patients (37 females and 17 males) who had been diagnosed with MS by the Department of Neurology, Xuan Wu Hospital of Capital Medical University. The blood samples were collected in the morning from MS patients (before they had breakfast) at active phase, according to their magnetic resonance image (MRI) scans. All clinical data, including past medical history, medication, stage at diagnosis, immunological data and MRI information about the brain and spinal cord on the day (± 2 days) of serum sample collection, were obtained and examined. Age, gender, disease course and duration, expanded disability status scale (EDSS) and the number of relapses were all recorded. The patients aged 19–60 years (median 39) fulfilled the revised McDonald criteria for MS [23]. The healthy control group consisted of 55 individuals who were selected from the Physical Health Center of the hospital. All participants gave informed consent to enter into the study, which was conducted according to the provisions of the Helsinki Declaration in 1975 and approved by the Ethics Committee of Xuan Wu Hospital. A summary of the clinical information about the patients and healthy controls is presented in Table 1. The samples used for proteomic analysis and western blotting were all collected, processed and stored according to standard protocols. Samples used for real-time PCR were collected as previously described [8]. The blood sample for T cell isolation was drawn in 2 ml sodium methylglucamine Ficoll 400 gradient blood vacutainers (Tianjin Hao Yang Biological Manufacture CO., Ltd.). The whole lymphocyte samples were collected into Axygen® microcentrifuge tube. Highly purified T cells were isolated from lymphocytes by negative selection using T cell isolation kits (R&D). 2.2. Proteomic fractionation, peptide sequencing and data processing The serum samples were subjected to fractionation using a functionalized magnetic bead-based kit (ClinProtTM , Bruker Daltonics) as our previously described method [13]. According
35
to area under the curve, 3 features had the best performance in discriminating patients with MS from the control. The 1532.82, 1935.04 and 2081.99 m/z peptides were identified using a Nano-LC/ESI mass spectrometry system consisting of an Acquity UPLC system (Waters) and an LTQ Orbitrap XL mass spectrometer (Thermo Fisher) equipped with a nano-ESI source. The obtained chromatograms were analyzed with BioWorks Browser 3.3.1 SP1, and the resulting mass lists were used for database searching using SequestTM (IPI Human [ver. 3.45, 71983 entries]).
2.3. Western blot analysis for validation The serum samples for immunoblotting assay were denatured, and the protein concentrations were measured using a bicinchoninic acid (BCA) kit assay (Pierce). Equal amounts of protein were electrophoresed on 4–20% SDS-polyacrylamide gradient gels and transferred onto HybondTM nitrocellulose membranes (Amersham). Two primary antibodies against the Atg16L2 protein (Abcam) were used for immunoblotting to avoid non-specific labeling. The blots were also probed for -actin as a loading control. The quantified data were expressed as % relative density.
2.4. RNA isolation, reverse transcription and real-time polymerase chain reaction (PCR) Total RNA was extracted from the T-cell populations isolated from individual cases using a commercial kit (CWBio. Co. Ltd) according to the manufacturer’s protocol. Please set the spacing between lines as in others> A 5 g aliquot of RNA was reverse-transcribed in a volume of 20 l at 37 ◦ C for 40 min and maintained for 10 min at 70 ◦ C (all chemicals were obtained from Promega). Real-time PCR detects the accumulation of a PCR product at every cycle of amplification via an optical imaging system that records the binding of a fluorescent dye (UltraSYBR Mixture) to double-stranded DNA [9]. The relative quantification of the change in Atg16L2 mRNA expression was determined by real-time PCR analysis, using GAPDH as the internal control. The specific primers designed for real-time PCR analysis are: forward 5’-GAATGTTGTGGGAAGTCGCCTG3’, reverse 5’-GTTGTAAGTTGCTGCTAAAACCTGG-3’ for Atg16L2 and forward 5’-CCTCTGACTTCAACAGCGACAC-3’, reverse 5’TGGTCCAGGGGTCTTACTCC-3’ for GAPDH. The real-time PCR was performed with the following profile using Taq DNA polymerase (Takara Biotech): 95 ◦ C for 10 min, followed by 40 cycles of 95 ◦ C for 15 sec and 60 ◦ C for 60 sec. All amplifications were done in triplicate. Threshold cycle (Ct) scores were averaged for subsequent calculations of relative expression values. Quantification of gene expression was made relative to GAPDH by calculating the differences in Ct (Ct) and relative values determined by 2(−Ct) method [15].
2.5. Statistical analysis A genetic algorithm (GA) was used to establish the pattern for distinguishing the MS patients from healthy controls. The data analysis was performed using GraphPad Prism (GraphPad Software Ver. 5.0) software, and the results presented as means ± SEM. The data for the two groups were compared using Mann-Whitney U test, whereas ANOVAs were performed for multiple groups; if significant, post-hoc comparisons were performed using Tukey’s test to assess potential differences between groups. A value of p < 0.05 was considered significant.
36
L. Yin et al. / Neuroscience Letters 562 (2014) 34–38
3. Results
Training set Multiple sclerosis 30; Healthy control 32
3.1. MALDI-TOF-MS analysis of peptides in sera from MS patients and healthy controls
MALDI-TOF-mass spectrometry
Thirty MS patients and 32 healthy controls were randomly assigned to a training set, and the remaining patients were used as the validation set. A total of 73 peaks were detected from the m/z spectra, ranging from 800 to 9000 Da of the training set. We used Mann–Whitney U test to obtain a p-value for each peak and to rank the peaks by their p-values. Using cut-offs of p < 0.01, p < 0.001 and p < 0.0001, we generated 3, 4 and 4 features of the 73 total peaks, respectively. A genetic algorithm (GA) was utilized to generate models to distinguish the proteomic spectra of MS patients from the controls with a sensitivity of 81.2% and a specificity of 92.3% (Fig. 1).
Total peaks 73
Mann-Whitney U test p-value filter p
Contents lists available at ScienceDirect
Neuroscience Letters journal homepage: www.elsevier.com/locate/neulet
Autophagy-related gene16L2, a potential serum biomarker of multiple sclerosis evaluated by bead-based proteomic technology Linlin Yin a,∗,1 , Jianghong Liu b,1 , Huiqing Dong b , Erhe Xu b , Yuchen Qiao b , Lin Wang b , Lan Zhang a , Jianping Jia b , Lin Li a,∗∗ , Xingchao Geng c,∗∗,1 a Department of Pharmacology, Xuan Wu Hospital of Capital Medical University, Beijing Geriatric Medical Research Center, Key Laboratory for Neurodegenerative Disease of Ministry of Education, PR China b Department of Neurology, Xuan Wu Hospital of Capital Medical University, 45 Changchun Street, Beijing, 100053, PR China c National Institute for Food and Drug Control, Beijing 100050, P. R. China
h i g h l i g h t s • • • •
Serum of Multiple sclerosis (MS) patients were evaluated by bead-based proteomic technology. Decreased levels of Atg16L2 in MS patients compared to controls were found. We further validated the decreased Atg16L2 by immunoblotting and real-time PCR. Decreased Atg16L2 may affect autophagy of T cells and contribute to MS relapse.
a r t i c l e
i n f o
Article history: Received 26 November 2013 Received in revised form 27 December 2013 Accepted 30 December 2013 Keywords: Atg16L2 multiple sclerosis proteomic technology T cells
a b s t r a c t Multiple sclerosis (MS) is an autoimmune disease characterized by neuroinflammation and demyelination that are mediated by T cells. The prolonged survival of autoreactive T cells acts as a primary event to trigger an inflammatory cascade that mediates myelin loss and clinical relapse in MS. Recently, T cell survival has been shown to be modulated by the autophagy-related gene (Atg). In the present study, we performed bead fractionation/matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry analyses using serum from 54 MS patients and 55 healthy controls. Eleven peptides were significantly different between the two groups with one being identified as a fragment of Atg16L2. Then the decreased levels of Atg16L2 peptides in MS patients were validated by immunoblotting and real-time PCR. As the Atg12-Atg5·Atg16 multimeric complex plays an essential role in autophagy, our results suggest that Atg16L2 may play an important role in autophagy of T cells and serve as a potential biomarker to predict clinical relapse of MS. © 2014 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Multiple sclerosis (MS) is an autoimmune disease of the central nervous system (CNS) that is characterized by inflammation and demyelination, afflicting approximately 2.5 million people worldwide. The clinical presentation of MS is heterogeneous including relapsing-remitting MS (RRMS), secondary progressive MS (SPMS) and primary progressive MS (PPMS) [16]. Identification of MS-specific biomarkers is clinically useful because these markers would allow relapse prediction and the early initiation
∗ Corresponding author. Tel.: +86 10 8319 8881; fax: +86 10 8315 4745. ∗∗ Corresponding authors. E-mail addresses: [email protected] (L. Yin), [email protected] (L. Li), [email protected] (X. Geng). 1 These authors contributed equally to this work. 0304-3940/$ – see front matter © 2014 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.neulet.2013.12.070
of therapeutic interventions. Although many studies have investigated serum and cerebrospinal fluid (CSF) biomarkers [7,12], including cytokines [17], chemokines and their receptors [3,19] and antibodies [20], serum biomarkers are more convenient for monitoring disease development in clinical practice. Therefore, it is of utmost importance to develop a new method to detect serum peptide biomarkers in MS patients. Peptidome analyses based on mass spectrometric screening methods have been developed and offer a high-throughput approach to discover new potential biomarkers in various body fluids [4,10]. In the present study, we used affinity-bead purification and nano-liquid chromatography–electrospray ionization-tandem (Nano-LC/ESI) mass spectrometry to detect serum markers in patients with MS compared with healthy controls. Three peptides were identified and one of them was validated by immunoblotting and real-time PCR assay.
L. Yin et al. / Neuroscience Letters 562 (2014) 34–38 Table 1 Clinical characteristics of patients with MS and healthy controls.
MS
RRMS SPMS PPMS NDa Sex (Male: Female) Mean age (range) EDSS (number of subjects) 0–3.5 4.0–5.5 6.0–8.0 Mean (range) Immunomodulatory treatments Corticosteroids Interferon- Mitoxantrone
Healthy control Sex (Male: Female) Mean age (range) a
Training group
Validation group
10 11 8 1 11:19 39.3 (19 – 60)
9 7 5 3 6:18 39.4 (21 – 60)
21 6 3 2.9 (0 – 6.0)
13 7 4 3.7 (2 – 6.5)
22 2 2 32
15 0 2 23
12:20 39.1 (22 – 67)
10:13 38.5 (22 – 56)
ND, the MS subtype was not determined.
2. Materials and methods 2.1. Patients and blood samples Serum samples were donated by 54 patients (37 females and 17 males) who had been diagnosed with MS by the Department of Neurology, Xuan Wu Hospital of Capital Medical University. The blood samples were collected in the morning from MS patients (before they had breakfast) at active phase, according to their magnetic resonance image (MRI) scans. All clinical data, including past medical history, medication, stage at diagnosis, immunological data and MRI information about the brain and spinal cord on the day (± 2 days) of serum sample collection, were obtained and examined. Age, gender, disease course and duration, expanded disability status scale (EDSS) and the number of relapses were all recorded. The patients aged 19–60 years (median 39) fulfilled the revised McDonald criteria for MS [23]. The healthy control group consisted of 55 individuals who were selected from the Physical Health Center of the hospital. All participants gave informed consent to enter into the study, which was conducted according to the provisions of the Helsinki Declaration in 1975 and approved by the Ethics Committee of Xuan Wu Hospital. A summary of the clinical information about the patients and healthy controls is presented in Table 1. The samples used for proteomic analysis and western blotting were all collected, processed and stored according to standard protocols. Samples used for real-time PCR were collected as previously described [8]. The blood sample for T cell isolation was drawn in 2 ml sodium methylglucamine Ficoll 400 gradient blood vacutainers (Tianjin Hao Yang Biological Manufacture CO., Ltd.). The whole lymphocyte samples were collected into Axygen® microcentrifuge tube. Highly purified T cells were isolated from lymphocytes by negative selection using T cell isolation kits (R&D). 2.2. Proteomic fractionation, peptide sequencing and data processing The serum samples were subjected to fractionation using a functionalized magnetic bead-based kit (ClinProtTM , Bruker Daltonics) as our previously described method [13]. According
35
to area under the curve, 3 features had the best performance in discriminating patients with MS from the control. The 1532.82, 1935.04 and 2081.99 m/z peptides were identified using a Nano-LC/ESI mass spectrometry system consisting of an Acquity UPLC system (Waters) and an LTQ Orbitrap XL mass spectrometer (Thermo Fisher) equipped with a nano-ESI source. The obtained chromatograms were analyzed with BioWorks Browser 3.3.1 SP1, and the resulting mass lists were used for database searching using SequestTM (IPI Human [ver. 3.45, 71983 entries]).
2.3. Western blot analysis for validation The serum samples for immunoblotting assay were denatured, and the protein concentrations were measured using a bicinchoninic acid (BCA) kit assay (Pierce). Equal amounts of protein were electrophoresed on 4–20% SDS-polyacrylamide gradient gels and transferred onto HybondTM nitrocellulose membranes (Amersham). Two primary antibodies against the Atg16L2 protein (Abcam) were used for immunoblotting to avoid non-specific labeling. The blots were also probed for -actin as a loading control. The quantified data were expressed as % relative density.
2.4. RNA isolation, reverse transcription and real-time polymerase chain reaction (PCR) Total RNA was extracted from the T-cell populations isolated from individual cases using a commercial kit (CWBio. Co. Ltd) according to the manufacturer’s protocol. Please set the spacing between lines as in others> A 5 g aliquot of RNA was reverse-transcribed in a volume of 20 l at 37 ◦ C for 40 min and maintained for 10 min at 70 ◦ C (all chemicals were obtained from Promega). Real-time PCR detects the accumulation of a PCR product at every cycle of amplification via an optical imaging system that records the binding of a fluorescent dye (UltraSYBR Mixture) to double-stranded DNA [9]. The relative quantification of the change in Atg16L2 mRNA expression was determined by real-time PCR analysis, using GAPDH as the internal control. The specific primers designed for real-time PCR analysis are: forward 5’-GAATGTTGTGGGAAGTCGCCTG3’, reverse 5’-GTTGTAAGTTGCTGCTAAAACCTGG-3’ for Atg16L2 and forward 5’-CCTCTGACTTCAACAGCGACAC-3’, reverse 5’TGGTCCAGGGGTCTTACTCC-3’ for GAPDH. The real-time PCR was performed with the following profile using Taq DNA polymerase (Takara Biotech): 95 ◦ C for 10 min, followed by 40 cycles of 95 ◦ C for 15 sec and 60 ◦ C for 60 sec. All amplifications were done in triplicate. Threshold cycle (Ct) scores were averaged for subsequent calculations of relative expression values. Quantification of gene expression was made relative to GAPDH by calculating the differences in Ct (Ct) and relative values determined by 2(−Ct) method [15].
2.5. Statistical analysis A genetic algorithm (GA) was used to establish the pattern for distinguishing the MS patients from healthy controls. The data analysis was performed using GraphPad Prism (GraphPad Software Ver. 5.0) software, and the results presented as means ± SEM. The data for the two groups were compared using Mann-Whitney U test, whereas ANOVAs were performed for multiple groups; if significant, post-hoc comparisons were performed using Tukey’s test to assess potential differences between groups. A value of p < 0.05 was considered significant.
36
L. Yin et al. / Neuroscience Letters 562 (2014) 34–38
3. Results
Training set Multiple sclerosis 30; Healthy control 32
3.1. MALDI-TOF-MS analysis of peptides in sera from MS patients and healthy controls
MALDI-TOF-mass spectrometry
Thirty MS patients and 32 healthy controls were randomly assigned to a training set, and the remaining patients were used as the validation set. A total of 73 peaks were detected from the m/z spectra, ranging from 800 to 9000 Da of the training set. We used Mann–Whitney U test to obtain a p-value for each peak and to rank the peaks by their p-values. Using cut-offs of p < 0.01, p < 0.001 and p < 0.0001, we generated 3, 4 and 4 features of the 73 total peaks, respectively. A genetic algorithm (GA) was utilized to generate models to distinguish the proteomic spectra of MS patients from the controls with a sensitivity of 81.2% and a specificity of 92.3% (Fig. 1).
Total peaks 73
Mann-Whitney U test p-value filter p
