Low Erythrocyte Levels of Proteasome and Acyl-Peptide Hydrolase (APEH) Activities in Alzheimer’s Disease: A Sign of Defective Proteostasis?

Abstract

Alzheimer’s disease (AD) is a progressive, multifactorial neurodegenerative disorder that is the main cause of dementia. To date, there are no definitive diagnostic tests that can predict or assess onset and progression of the disease. Blood biomarkers for AD are being sought for many years but their identification remains a challenging task. In this study, we investigated the potential relationship between AD and levels of acyl-peptide hydrolase (APEH) and proteasome in erythrocyte samples of 52 participants (26 AD and 26 cognitively healthy controls). A statistically significant decrease in proteasome and exopeptidase/endopeptidase APEH activities was found in AD samples compared to those of healthy controls. Moreover, in contrast to what was observed for proteasome transcripts, APEH activities reduction in AD patients was unrelated to its gene expression levels, suggesting the occurrence of posttranslational modifications or the expression of endogenous inhibitors that might impair enzyme activity. These preliminary data further support a relationship between the APEH-proteasome system and AD molecular players, providing the first evidence of its potential use as a novel blood-based indicator for the routine detection of AD.

Keywords

Alzheimer’s disease APEH blood-based indicator system oxidized peptide hydrolase activity proteasome protein quality control

INTRODUCTION

Many neurodegenerative disorders, such as Alzheimer’s disease (AD), are associated with the accumulation and aggregation of neurotoxic proteins that perturb cellular homeostasis and neuronal functions [1]. Specifically, AD is an age-related neurodegenerative disease, characterized by the functional impairment and loss of neurons that translate into a progressive decline in memory and other cognitive functions, culminating to dementia [2 –4]. At present, AD represents a serious social and economic threat to most societies. Histopathologically, AD brain is defined by the accumulation of two types of insoluble fibrous material, the extracellular amyloid-β (Aβ) peptide deposited in senile plaques and the intracellular neurofibrillary tangles composed principally of abnormal and hyperphosphorylated tau proteins [5 –7]. Among the different Aβ species, the Aβ_1 - 42 peptide is the most neurotoxic isoform, being more prone to aggregation and fibrilization [8], and it is believed to influence the pathogenesis of AD [9, 10], due to oxidation of a methionine at position 35 [9 , 12]. The accumulation of Aβ and tau aggregates makes AD a protein misfolding disease, or a proteopathy, and suggests that a downregulation of many or all proteolytic pathways in the brain is involved in the pathogenesis of the disease, allowing the aggregated, oxidized, and misfolded harmful proteins to build up to toxic levels [13 –15]. In the study of neurodegenerative disorders, a great consideration has been devoted to 26S ubiquitin proteasome system (UPS), due to its role as a critical regulator of protein homeostasis in eukaryotic cells [16 –19], and its involvement as co-factor in AD development seems somehow evident [4, 17]. Blockade of UPS by disease-associated proteins would result in global accumulation of proteasome substrates, thus leading to even more proteasome impairments in a snowball effect that could explain the self-replicative, exponential progression in AD [20 –22]. A growing body of evidence has been obtained concerning the involvement of oxidative stress in the AD neuronal loss and the accumulation of oxidized proteins, which may be responsible for the decreased proteasomal activity [12 , 23]. However, the exact mechanism that impairs the UPS in AD remains obscure, although the general pathways underlying this pathology might have a direct effect on this system [17 , 25]. Recently, it has been reported that acyl-peptide hydrolase (APEH) plays a key role in the protein degradation machinery and in the antioxidant defense systems, in cooperation with the UPS [26 –29]. APEH is a ubiquitous cytosolic enzyme that belongs to the prolyl oligopeptidase family of serine peptidases (clan SC, family S9) and catalyzes the removal of Nα-acetylated amino acids from blocked peptides, acting as a key regulator of N-terminally acetylated proteins in human cells [29 –33]. To date, APEH has been studied in different organisms [27 , 34–38], but its biological role has not yet been completely elucidated. Interestingly, it has been proposed that it can promote cell protection under oxidative stress conditions by a mechanism of hydrolysis of oxidized protein aggregates, which are normally poor substrates for proteasome [27, 29]. Indeed, APEH behaves as a bifunctional enzyme, exhibiting exopeptidase activity towards N-acyl peptides and endoprotease activity towards oxidized proteins [27, 38]. Very little is known about the role of APEH in the central nervous system and on its involvement in AD as compared to the proteasome system. However, it has been reported that APEH gene expression is improved in AD brain areas rich in Aβ plaques, as a possible biological response to remove excess Aβ peptides, since APEH is able to degrade these proteinaceous species [39, 40]. Evidences on the identification of APEH as an alternative ‘non-cholinergic’ target in AD treatment [41 –44] and on the relationship between oxidative stress and APEH functions [26 , 46], have also been described. Moreover, APEH, besides being present in the brain, is one of the major serine hydrolases found in human erythrocytes and the two isoforms are equivalent [39 , 48]. This supports the notion of a potential usefulness of erythrocyte APEH as a novel indicator of neuropsychological deterioration associated with the pathogenic process occurring in AD brains [49], being a perfect reflection of the neuronal counterpart.

Furthermore, AD can be considered a multifactorial disorder that is not completely restricted to pathology and biomarkers within the brain, but it is a systemic disease that induces significant biological changes also in non-neural tissues [50]. At present, a decline in Aβ levels in conjunction with an accumulation of phosphorylated microtubule-associated protein tau (p-tau) in cerebrospinal fluid (CSF) represents the most hopeful source of validated AD biomarkers, and it has been advocated for use in the diagnosis of AD [51]. However, this diagnostic approach has several drawbacks: the collection of CSF is an invasive method with potential side effects, and screening and follow-up analysis of patients is often difficult and problematic over several years. Thus, there is a great interest in searching for new biomarkers in other peripheral body fluids to diagnose AD, and blood is for many reasons the one of choice. Specifically, red blood-based biomarkers are the most clinically useful due to the important role that the erythrocytes (RBCs) play in a variety of physiological processes, the easiness of availability (approximately 99% of the cells are red blood cells), the detection and quantitation without risk of complications, and the suitability for the population-wide diseasescreening.

In this context, the aim of this pilot study was to investigate the relationship between the APEH-proteasome levels and AD in RBCs, in which both enzymes are mostly present, in order to explore the possibility of using this enzymatic system as a new sensitive indicator for diagnosis and treatmentof AD.

MATERIALS AND METHODS

Study population

Fifty-two participants were recruited from the Centre for Research and Training in Medicine for Aging (CeRMA), University of Molise (Italy). They were divided into two groups based on their clinical profiles: 26 participants with probable AD (10 males, 16 females, mean age + SD: 77.04±8.83 y) and 26 cognitively healthy controls (HC; 9 males, 17 females, mean age + SD: 66.7±12 y). The characteristics of participants are summarized in Table 2. Patients with probable AD were diagnosed according to National Institute on Aging / Alzheimer’s Association (NIA-AA) criteria [52] and fulfilled the criteria for “probable AD with documented decline” category. They presented Mini Mental State Examination (MMSE) score <24 and Clinical Dementia Rating (CDR) score >0.5. This study was conducted in accordance with ethical principles stated in the Declaration of Helsinki, as well as with approved national and international guidelines for human research. The Ethics Committee of the University of Molise reviewed and approved this study, and a written informed consent was obtained from participants or caregivers.

Preparation of hemolysates and batch-based purification protocol of APEH and proteasome

Venous blood samples were taken from HC and AD donors between 8:00 and 8:30 AM, after an overnight fasting of at least 12 h, using syringes vacutainer serum tubes (Becton & Dickinson, Milan, Italy). The whole blood samples were centrifuged at 1800×g for 5 min at 4°C in order to separate the plasma, that sits on top of the pellet, and the buffy coat (the white cells and platelets), which was carefully aspirated with a syringe, from the erythrocytes that collect at the very bottom of the tube. The erythrocytes were washed twice with an isotonic solution (10 mMTris-HCl pH 7.6, 1.7% NaCl; 4°C). Lysis of erythrocytes was carried out by incubation in hypotonic solution (25 mM Tris-HCl, pH 7.5) for 30 min on ice. The hemolysates were obtained by centrifugation of the lysates at 9200×g for 40 min at 4°C. The ‘soluble fraction’ was used to set up a batch-based purification protocol. Specifically, 0.5 mL of hemolysate was incubated (10 min at room temperature under gentle agitation) with 1 mL of DEAE Sepharose Fast Flow resin (GE Healthcare Bio-sciences, Sweden) in a 2 mL eppendorf tube. After incubation, the sample was centrifuged at 4°C, 13000 rpm for 10 min to discard the supernatant. Then, the resin was incubated with 0.5 mL of 100 mM NaCl in 25 mM Tris-HCl, pH 7.5 for 10 min at room temperature under gentle agitation and after centrifugation (4°C, 13000 rpm for 10 min), the supernatant was discarded and the resin incubated with 800 mM NaCl in 25 mM Tris-HCl, pH 7.5 for 10 min to recover APEH and proteasome. Active samples were analyzed by electrophoretic techniques in order to evaluate the purification fold.

Exopeptidase APEH and CT-like (Chymotrypsin-like) proteasome assays

The aminopeptidase activity of APEH was spectrofluorimetrically measured, in both the crude extract and in the partially purified samples, using the fluorogenic Ac-Met-AMC (acetyl-Met-7-amido-4-methylcoumarin) (Bachem, Switzerland) as substrate. The release of the fluorescent product (7-amino-4-methylcoumarin) was monitored using a Jasco FP-8200 spectrofluorimeter. Excitation and emission wavelengths were 380 nm and 460 nm, respectively. Reaction mixtures (1 mL) containing the partially purified APEH (10 and 20 μg) or an appropriate amount of crude extract (70 and 140 μg) in 50 mM Tris-HCl pH 7.5, were preincubated at 37°C for 2 min. Then, the substrate (at a final concentration of 0.5 mM) was added, and the release of the product was measured. Calculated activities were based on the initial linear phase of release.

The synthetic fluorescent substrate Suc-LLVY-AMC (N-succinyl-Leu-Leu-Val-Tyr-7-amido-4-met-hylcoumarin; Sigma-Aldrich, Italy) was used for the measurement of the CT-like activity (β5 subunit) of the proteasome, at a final concentration of 0.080 mM, both in the crude extract and in the partially purified samples. The reaction mixture (0.9 mL) containing the appropriate amount of proteasome (10 and 20 μg for the partially purified samples or 70 and 140 μg for the crude extract) was preincubated in 50 mM Tris-HCl pH 7.5. Suc-LLVY-AMC was added, and the release of the fluorescent product (7-AMC) was monitored for 5 min using a Jasco FP-8200 spectrofluorimeter. Excitation and emission wavelengths were 380 nm and 460 nm, respectively.

Peptide synthesis and characterization

A synthetic peptide, reproducing a fragment of GDF11 (Growth Differentiation Factor 11) and named EPS (Endopeptidase Peptide Substrate), was used to monitor the endopeptidase activity of APEH. It was prepared as amidated derivative by solid phase synthesis (synthesis scale, 0.1 mmol), following standard Fmoc/tBu protocols. A rink amide resin (substitution, 0.57 mmol/g) and amino acid derivatives with standard protections were used for the synthesis. Cleavage from the solid support was performed by treatment with a trifluoroacetic acid (TFA)/triisopropylsilane/water (90:5:5, v/v/v) mixture for 90 min at room temperature. The crude peptide was precipitated in cold ether, dissolved in a water/acetonitrile (1:1, v/v) mixture and lyophilized. Purification to homogeneity was afforded by reverse-phase HPLC using a semipreparative 10×1 cm ID C18 monolithic Onyx column (Phenomenex, California, USA), applying a linear gradient of 0.05% TFA in acetonitrile from 10% to 70% over 8 min at a flow rate of 15 mL/min. Peptide purity and identity were confirmed by liquid chromatography–mass spectrometry analysis. Protected amino acids for the synthesis of peptide were from GL-Biochem (Shanghai, PRC) and Novabiochem (Laufelfingen, Switzerland). Coupling agents were from GL-Biochem (Shanghai, PRC). All solvents used for the analyses were from Sigma-Aldrich (Milan, Italy).

Endopeptidase activity of APEH

Purification protocol

The endopeptidase activity of APEH was measured using an optimized purification protocol for APEH and the peptide EPS as substrate, which is split into two fragments upon internal cleavage by APEH (manuscript in preparation). Hemolysates were loaded onto a DEAE Sepharose Fast Flow column (GE Healthcare Life Sciences, Sweden), connected to an AKTA FPLC system (GE Healthcare Life Sciences, Sweden), previously equilibrated in 25 mM Tris-HCl pH 7.5 (buffer A). Bound proteins were eluted using a linear ion gradient (0 –100%) of 1 M NaCl in buffer A at a flow rate of 1 mL/min. Active fractions were collected, pooled, dialyzed in 25 mM Tris-HCl pH 7.5 and loaded on Superdex 200 PC 3.2/30 column (Pharmacia Biotech, USA) connected to a SMART System (Pharmacia, USA). Bound proteins were eluted with 25 mM Tris-HCl buffer, pH 7.5, containing 50 mM NaCl at a flow rate of 0.1 mL/min. Active fractions were collected, pooled, dialyzed in 25 mM Tris-HCl pH 7.5 and stored in the same buffer supplemented with 5% glycerol. Enzyme purification was monitored using acetyl Ac-Met-AMC as substrate. Active fractions were loaded on SDS-PAGE (10%) in order to evaluate the purification fold.

Enzyme assay

The endoprotease activity of APEH was measured by RP-HPLC monitoring the appearance of EPS fragments generated by proteolysis (manuscript in preparation). For the assay, 10 μl sample solutions of EPS at 10 mM in DMSO (10 nmoles) were incubated with APEH (0.7 μg) at 37°C for 24 h in a final volume of 200 μl of 25 mM Tris-HCl pH 7.5. Proteolytic mixtures were analyzed by a C18 reverse-phase column (Waters Corporation, Massachusetts) connected to a Dionex system using a linear gradient of 0.1 % TFA in acetonitrile from 5% to 95%. For each enzyme assay an appropriate control was run (manuscript in preparation) using the same peptide sample incubated in the absence of APEH. All solvents used for the analyses were from Sigma-Aldrich (Milan, Italy).

Western blot analysis

Aliquots of protein samples were subjected to SDS-PAGE (10% or 12%) and then electroblotted onto PVDF membranes (Immobilon; Millipore, Milan, Italy). Membranes were next incubated with the specific anti-APEH and anti-proteasome 20S β5 subunit antibodies (N-18 goat IgG, Santa Cruz Biotechnology, USA; BML-PW8895-0025, Enzo Life Science, USA) and then with a horseradish peroxidase-conjugated secondary antibody (1 h at 37°C). The immune complexes formed were visualized by enhanced chemiluminescence and autoradiography, according to the manufacturer’s protocol (Amersham Biosciences, USA).

Purification of total RNA and quantitative Real-Time PCR (RT-PCR) analysis

Total RNA from whole blood samples, taken from healthy and AD donors, was isolated using TRIzol^® LS Reagent (Ambion/Thermo Fisher Scientific, USA), designed for processing liquid samples, according to the procedure described in the user guide. RNA concentration was determined with a Qubit Fluorometer (Invitrogen/ Thermo Fisher Scientific, USA). RNAs were then reverse transcribed with the SuperScript^® VILO™ MasterMix (Invitrogen/ Thermo Fisher Scientific, USA). Dilution series of the cDNA was used as template for quantitative real-time PCR amplifications, to calculate the efficiency of primers. The assays were performed on an iCycler iQTM (Bio-Rad, USA) with 300 nM gene-specific primers, iTaq^TM Universal SYBR^® Green Supermix (Bio-Rad, USA), and the following PCR conditions: one cycle at 95°C for 10 min, and 40 cycles at 95°C for 15s, 60°C for 30s, and 72°C for 30s. The expression level of the β-actin gene was used as an internal control for normalization. Raw cycle threshold values (Ct values) obtained for the target genes were compared with the Ct value obtained for the β-actin gene (reference gene). All data were expressed as mean expression fold from triplicates and the final graphical data were derived from the following equation: R=(E_target)^{ΔCt _ target (control - sample)}/(E_ref)^{ΔCt _ ref (control - sample)}. Primers were designed by using “Universal Probe Library Assay Design Center” (http://lifescience.roche.com/shop/CategoryDisplay?catalogId=10001&tab=Assay+Design+Center&identifier=Universal+Probe+Library&langId=-1#tab-3). Primers used in the assay are listed in Table 1.

Table 1

Primers used in the qPCR analysis

Primer	Sequence
β-actin dir	5′-CCAACCGCGAGAAGATGA-3′
β-actin rev	5′-CCAGAGGCGTACAGGGATAG-3′
APEH dir	5′-CCCCATTCATCCTTTGTCAC-3′
APEH rev	5′-AAAGCCCATCTTGCAAAGC-3′
β5 dir	5′-CATGGGCACCATGATCTGT-3′
β5 rev	5′-GAAATCCGGTTCCCTTCACT-3′

Statistical analysis

Data were analyzed using SPSS (v. 17.0) statistical software package (SPSS Inc., Chicago, IL). Variables were examined for outliers and extreme values by means of box and normal quantile-quantile plots, Shapiro-Wilk’s, and Kolmogorov-Smirnov’s tests. When normal distribution could not be accepted, variable transformations (square, square root, logarithmic, reciprocal of the square root, or reciprocal transformations) were reviewed. The logarithm of proteasome activity in hemolysate samples and the reciprocal of square root of endopeptidase APEH activity helped to improve the distribution shape. However, the normal distribution could not be reached for exopeptidase APEH activity in purified samples and for APEH gene expression. Group differences (HC versus AD) were evaluated by analysis of covariance (ANCOVA), using age, gender, education level, Body Mass Index (BMI), comorbidities, and drugs as covariates; p-values were bootstrapped for not normally distributed variables. The assumption of equality of variance was assessed by means of Levene’s test. Chi-square test was used to evaluate differences between groups in gender, comorbidity and drug intake, and independent samples t-test to assess differences in age, education level, and BMI (Table 2).

Table 2

Demographic and clinical characteristics of study groups

	AD	HC	p-value
	(n = 26)	(n = 26)
Age (mean±SD, y)	77±8.8	66.7±12	0.001
Gender (n, %)			1.000
Male	10 (38.5%)	9 (32.0%)
Female	16 (61.5%)	17 (68.0%)
Education level (mean±SD, y)	7.1±4.7	12.9±4.4	<0.001
BMI (mean±SD, kg/m²)	24.7±4.2	25.4±3.7	0.562
MMSE	7.6±7.9	29.5±1.1	<0.001
Medical History (n, %)
Smoker^a	15; 57.7%	12; 48.0%	0.579
Dyslipidemia	6; 23.1%	6; 23.1%	1.000
Diabetes	5; 19.2%	–	0.051
Hypertension	11; 42.3%	7; 28.0%	0.382
Arrhythmia	–	2; 8.0%	0.490
Heart failure^b	4; 15.4%	1; 4.0%	0.350
TIA/Stroke	–	1; 4.0%	1.000
Psychological disorders^c	4; 15.4%	4; 15.4%	1.000
Drugs (n, %)
Antihypertensive	13; 50.0%	11; 44.0%	0.579
Lipid-lowering	5; 19.2%	6; 23.1%	1.000
Hypoglycemic	3; 11.5%	–	0.235
Thyroid-hormones	–	2; 8.0%	0.490
Antiplatelet	5; 36.3%	7; 28.0%	0.755
AChE-I	4; 15.4%	–	0.110

–, none; AD, Alzheimer’s disease; HC, cognitively healthy controls; BMI, body mass index; MMSE, Mini-Mental State Examination; TIA, transient ischemic attack; AChE-I, acetylcholinesterase inhibitors. ^acurrent or former smoker. ^bsubjects in NYHA (New York Heart Association) class I-II. ^csubjects with anxiety or depression.

Finally, correlation analysis was performed in each group by Pearson’s correlation coefficient (r) for normally distributed and Spearman rank correlation coefficient (r_s) for not normally distributed variables, using Bonferroni’s correction for multiplecomparisons.

RESULTS AND DISCUSSION

AD is typically associated with global failures of all proteolytic pathways at neuronal level [54]. To date, no APEH activity was detected in plasma and the other blood cells in human and no evidence was available on the relationship between AD and the APEH and proteasome levels in theerythrocytes (RBCs). Therefore, to investigate whether these enzymes might be used as early prognostic factors for disease onset and progression, we conducted a pilot study on RBCs from 52 subjects, consisting of 26 AD patients and 26 healthy controls (HC) (Table 2).

APEH and Chymotrypsin-like proteasomal activities

We examined the hemolysate samples, processed by using a previously optimized protocol [27]. Interestingly, ANCOVA revealed a statistically significant reduction of exopeptidase APEH (F = 4.269; df = (1,51); p = 0.047) (Fig. 1A) and CT-like proteasomal (F = 5.405; df = (1,51); p = 0.027) specific activities (Fig. 1B) in AD compared with HC group. Similar results were obtained when APEH and proteasome activities were measured in the erythrocytes enzyme samples, partially purified by using a new, simple, and fast batch-based protocol on DEAE Sepharose Fast Flow resin. The enrichment of the protein mixture in the APEH and proteasome amount was confirmed by SDS-PAGE analysis while the identity of both enzymes was assessed by western blot using anti-APEH and anti-β5 antibodies (Supplementary Figure 1). In the partially purified samples (n = 41; 17 AD and 24 HC), whose selection was blind, ANCOVA evidenced again a statistically significant decrease of exopeptidase APEH specific activity (F = 6.246; df = (1,40); bootstrapped p = 0.048) (Fig. 2A) and a significantly lower level of CT-like proteasomal specific activity (F = 5.543; df = (1,30); p = 0.028) (Fig. 2B) in AD group compared to HC, thus validating the data obtained from crude protein extracts. In addition, the specific activities in the hemolysates correlated well with those from partially purified samples for both APEH (HC: r_s = 0.437, p = 0.033; AD: r_s = 0.615, p = 0.009) and proteasome (HC: r = 0.654, p = 0.001; AD: r = 0.521, p = 0.032). Furthermore, a significant correlation between APEH and proteasome specific activities in the hemolysates was found only in HC group (r = 0.458; p = 0.019), suggesting that the functional relationship [31] of the two enzymes involved in the degradation machinery might be compromised in AD participants. To the best of our knowledge, this is the first report demonstrating an impairment of APEH and proteasome activities in the erythrocytes of AD subjects.

Fig.1

Exopeptidase APEH and chymotrypsin-like (CT-like) proteasome specific activities measured in the AD and HC hemolysates. A) Box plots, showing the distributions of the measurements of APEH specific activities (U/mg) across the sample groups, are identified by the ANCOVA for the analysis of differences between AD and HC. B) Box plots, showing the distributions of the measurements of CT-like proteasome specific activities (U/mg) across the sample groups, are identified by the ANCOVA for the analysis of differences between AD and HC. Median (horizontal line in the box), 25th and 75th percentiles (edges of box), maximum and minimum values (whiskers) of APEH and CT-like proteasome activities in the two groups: AD and HC, are also shown in the box plots.

Fig.2

Exopeptidase APEH and chymotrypsin-like (CT-like) proteasome specific activities measured in the partially purified AD and HC enzyme samples. A) Box plots, showing the distributions of the measurements of APEH specific activities (U/mg) across the sample groups, are identified by ANCOVA with bootstrappedp-values for the analysis of differences between AD and HC. B) Box plots, showing the distributions of the measurements of CT-like proteasome specific activities (U/mg) across the sample groups, are identified by the ANCOVA for the analysis of differences between AD and HC. Median (horizontal line in the box), 25th and 75th percentiles (edges of box), maximum and minimum values (whiskers) of APEH and CT-like proteasome activities in the two groups: AD and HC, are also shown in the box plots.

Monitoring endopeptidase activity of APEH

In order to understand if the pathology can affect the ability of APEH to degrade oxidized substrates, we selected a model peptide, named EPS, which reproduces a fragment of GDF11 (Growth Differentiation Factor 11; manuscript in preparation) and can serve as molecular probe for monitoring the APEH endopeptidase activity. EPS, upon processing by APEH, generates two specific fragments that can be detected by RP-HPLC analysis, providing a direct quantitation of the OPeH activity (OPeH, Oxidized Peptide Hydrolase) toward oxidized substrates (Supplementary Figure 2). Therefore, the estimation of OPeH in erythrocytes samples was performed, looking for a correlation with the occurrence of neurodegenerative disease. Analyses were conducted incubating the APEH purified from several subjects (n = 18; 9 AD and 9 HC), whose selection was blind, with EPS or with its unoxidized form, which was used as a negative control. The limited number of testing was due to a very time-consuming and expensive procedure necessary to perform the analyses. The enzyme was purified 10-fold, with an activity recovery of 70% and a specific activity of 317,800 U/mg. Interestingly, ANCOVA indicated a statistically significant reduction of OPeH activity (F = 7.807; df = (1,17); p = 0.031) in AD group compared to HC (Fig. 3), measured by comparing the peak area of EPS incubated in the presence or absence of enzyme. Specifically, APEH from AD group was mostly unable to process the peptide (degradation was less than 10%), while the enzyme purified from HC showed a notable OPeH activity, with peptide degradation estimated to be about 40%. As expected, the unoxidized peptide was unaffected by incubation with APEH purified from both AD and HC samples (data not shown; manuscript in preparation), underlying its suitability as substrate for monitoring APEH endopeptidase activity.

Fig.3

OPeH activity measured in the purified enzyme samples from HC and AD. APEH purified from the erythrocyte cells of AD and HC was incubated at 37°C for 24 h with the model peptide substrate EPS, using its unoxidized form as negative control. The amount of peptide degradation is expressed in percentage. Median (horizontal line in the box), 25th and 75th percentiles (edges of box), maximum and minimum values (whiskers) of APEH activity in the two groups: AD and HC, are shown in the box plot.

APEH and proteasome β5 subunit gene expression levels and their correlation with the activities in AD and HC

To determine if the reduction of proteasome and APEH activities in the RBCs of AD was due to decreased levels of gene expression, we measured the transcriptional levels of APEH and proteasome β5 subunit genes by Real-Time PCR (RT-PCR), in 34 whole blood samples withdrawn from 17 HC and 17 AD donors. As shown in Fig. 4A, no significant APEH gene alteration was observed in AD compared to HC groups (F = 0.101; df = (1,33); p = 0.759). On the contrary, ANCOVA revealed a significant reduction of β5 subunit transcript levels in AD samples compared to controls (F = 4.565; df = (1,33); p = 0.046) (Fig. 4B).

Fig.4

RT-PCR assessment of transcript expression levels of APEH and β5 proteasome subunit genes in AD and HC blood samples. A) APEH gene expression in AD versus HC blood samples. B) β5 proteasome subunit gene expression in AD versus HC blood samples. Box plots, showing the distributions of the measurements of the transcriptional levels of APEH and β5 subunit genes across the sample groups, are identified by ANCOVA for the analysis of differences between AD and HC. Median (horizontal line in the box), 25th and 75th percentiles (edges of box), maximum and minimum values (whiskers) of APEH and β5 gene expression in the two groups: AD and HC, are shown in the plots.

Notably, in contrast to that observed for proteasome, reduction of APEH activity resulted not associated with a decrease in its gene expression levels, suggesting that different posttranslational modifications, including an oxidative alteration of the enzymatic complex or the occurrence of a so far unknown endogenous inhibitor, could modulate APEH activity in the erythrocytes of AD patients.

Conclusions

Proteinopathies, such as AD, represent a large group of pathologies characterized by the presence of abnormally folded proteins in the cells of affected subjects, leading eventually to neuronal death [55, 56]. As blood–brain barrier damage in AD may enhance movement of proteins between brain and blood [57, 58], the latter may represent a rich source of potential biomarkers of this pathology.

In the present study, we provide the first evidence of an association between AD and APEH-proteasome levels in the erythrocytes. Specifically, we show that APEH and proteasome specific activities are significantly reduced in AD erythrocyte samples, thus supporting the hypothesis that this enzyme system is a promising blood-based candidate for AD diagnosis. Regardless of the precise mechanism, the different and complementary nature of these proteins suggests that the combined evaluation of their activity will be much more informative than the single ones. However, the present work can be considered a pilot study, providing the building block for future work on larger patient groups, which will be necessary to better elucidate the mechanisms through which these factors affect the pathology and to achieve an improved diagnostic accuracy.

Footnotes

ACKNOWLEDGMENTS

This work was supported by Ministero dello Sviluppo Economico (MISE) within the European project “SUstainable PLant-based Production of Extremozymes” (SUPPLE) (F/0004/02/X29; D.D.C. 3665 02/02/2016).

Authors’ disclosures available online ().

The supplementary material is available in the electronic version of this article: .

References

Popovic

, Vucic

, Dikic

(2014) Ubiquitination in disease pathogenesis and treatment. Nat Med 20, 1242–1253.

Götz

, Ittner

(2012) Tau-targeted treatment strategies in Alzheimer’s disease. Br J Pharmacol 165, 1246–1259.

Manavalan

, Mishra

, Feng

, Sze

, Akatsu

, Heese

(2013) Brain site-specific proteome changes in aging-related dementia. Exp Mol Med 45, e39.

Zheng

, Huang

, Zhang

, Zhou

, Luo

, Xu

, Wang

(2016) Dysregulation of ubiquitin-proteasome system in neurodegenerative diseases. Front Aging Neurosci 8, 303.

Bloom

(2014) Amyloid-β and tau: The trigger and bullet in Alzheimer disease pathogenesis. JAMA Neurol 71, 505–508.

Kang

, Lemaire

, Unterbeck

, Salbaum

, Masters

, Grzeschik

, Multhaup

, Beyreuther

, Müller-Hill

(1987) The precursor of Alzheimer’s disease amyloid A4 protein resembles a cell-surface receptor. Nature 325, 733–736.

, Kim

, Ikeuchi

, Xu

, Gasparini

, Wang

, Sisodia

(2001) Characterization of a presenilin-mediated amyloid precursor protein carboxyl-terminal fragment gamma. Evidence for distinct mechanisms involved in gamma-secretase processing of the APP and Notch1 transmembrane domains. J Biol Chem 276, 43756–43760.

De-Paula

, Radanovic

, Diniz

, Forlenza

(2012) Alzheimer’s disease. Subcell Biochem 65, 329–352.

Butterfield

, Sultana

(2011) Methionine-35 ofaβ(1-42): Importance for oxidative stress in Alzheimerdisease. J Amino Acids 2011, 198430.

10.

Lambert

, Barlow

, Chromy

, Edwards

, Freed

, Liosatos

, Morgan

, Rozovsky

, Trommer

, Viola

, Wals

, Zhang

, Finch

, Krafft

, Klein

(1998) Diffusible, nonfibrillar ligands derived from Abeta1-42 are potent central nervous system neurotoxins. Proc Natl Acad Sci U S A 95, 6448–6453.

11.

Butterfield

, Reed

, Newman

, Sultana

(2007) Roles of amyloid beta-peptide-associated oxidative stress and brain protein modifications in the pathogenesis of Alzheimer’s disease and mild cognitive impairment. Free Radic Biol Med 43, 658–677.

12.

Chauhan

, Chauhan

(2006) Oxidative stress in Alzheimer’s disease. Pathophysiology 13, 195–208.

13.

Grune

, Reinheckel

, Davies

(1997) Degradation of oxidized proteins in mammalian cells. FASEB J 11, 526–534.

14.

Reinheckel

, Sitte

, Ullrich

, Kuckelkorn

, Davies

, Grune

(1998) Comparative resistance of the 20S and 26S proteasome to oxidative stress. Biochem J 335, 637–642.

15.

Tanaka

, Chiba

(1998) The proteosome: A protein-destroying machine. Genes Cells 3, 499–510.

16.

Coux

, Tanaka

, Goldberg

(1996) Structure and function of the 20S and 26S proteasomes. Annu Rev Biochem 65, 801–847.

17.

de Vrij

, Fischer

, van Leeuwen

, Hol

(2004) Protein quality control in Alzheimer’s disease by the ubiquitin proteasome system. Prog Neurobiol 74, 249–270.

18.

Dantuma

, Bott

(2014) The ubiquitin-proteasome system in neurodegenerative diseases precipitating factor, yet part of the solution. Front Mol Neurosci 7, 70.

19.

Hochstrasser

(1996) Ubiquitin-dependent protein degradation. Annu Rev Genet 30, 405–439.

20.

Deger

, Gerson

, Kayed

(2015) The interrelationship of proteasome impairment and oligomeric intermediates in neurodegeneration. Aging Cell 14, 715–724.

21.

Keller

, Hanni

, Markesbery

(2000) Impaired proteasome function in Alzheimer’s disease. J Neurochem 75, 436–439.

22.

Lopez Salon

, Morelli

, Castano

, Soto

, Pasquini

(2000) Defective ubiquitination of cerebral proteins in Alzheimer’s disease. J Neurosci Res 62, 302–310.

23.

Tramutola

, Lanzillotta

, Perluigi

, Butterfield

(2016) Oxidative stress, protein modification and Alzheimer disease. Brain Res Bull 133, 88–96.

24.

Gregori

, Fuchs

, Figueiredo-Pereira

, Van Nostrand

, Goldgaber

(1995) Amyloid beta-protein inhibits ubiquitin-dependent protein degradation in vitro. J Biol Chem 270, 19702–19708.

25.

Tseng

, Green

, Chan

, Blurton-Jones

, LaFerla

(2008) Abeta inhibits the proteasome and enhances amyloid and tau accumulation. Neurobiol Aging 29, 1607–1618.

26.

Bergamo

, Cocca

, Palumbo

, Gogliettino

, Rossi

, Palmieri

(2013) RedOx status, proteasome and APEH: Insights into anticancer mechanisms of t10,c12-conjugated linoleic acid isomer on a375 melanoma cells. PLoS One 8, e80900.

27.

Gogliettino

, Riccio

, Balestrieri

, Cocca

, Facchiano

, D’Arco

, Tesoro

, Rossi

, Palmieri

(2014) A novel class of bifunctional acylpeptide hydrolases–potential role in the antioxidant defense systems of the Antarctic fish Trematomus bernacchii. FEBS J 281, 401–415.

28.

Perrier

, Durand

, Giardina

, Puigserver

(2005) Catabolism of intracellular N-terminal acetylated proteins: Involvement of acylpeptide hydrolase and acylase. Biochimie 87, 673–685.

29.

Shimizu

, Kiuchi

, Ando

, Hayakawa

, Kikugawa

(2004) Coordination of oxidized protein hydrolase and the proteasome in the clearance of cytotoxic denatured proteins. Biochem Biophys Res Commun 324, 140–146.

30.

Palmieri

, Bergamo

, Gogliettino

, Ruvo

, Sandomenico

, Langella

, Luini

, Hedge

, Saviano

, Rossi

(2011) Acyl peptide hydrolase inhibition as targeted strategy to induce proteasomal dysfunction. PLoS One 6, e25888.

31.

Palumbo

, Gogliettino

, Cocca

, Iannitti

, Sandomenico

, Ruvo

, Balestrieri

, Rossi

, Palmieri

(2016) APEH inhibition affects osteosarcoma cell viability via downregulation of the proteasome. Int J Mol Sci 17, 1614.

32.

Jones

, Scaloni

, Manning

(1994) Acylaminoacyl-peptidase. Methods Enzymol 244, 227–231.

33.

Polgar

(2002) The prolyl oligopeptidase family. Cell Mol Life Sci 59, 349–362.

34.

Gogliettino

, Balestrieri

, Cocca

, Mucerino

, Rossi

, Petrillo

, Mazzella

, Palmieri

(2012) Identification and characterisation of a novel acylpeptide hydrolase from Sulfolobus solfataricus: Structural and functional insights. PLoS One 7, e37921.

35.

Palmieri

, Langella

, Gogliettino

, Saviano

, Pocsfalvi

, Rossi

(2010) A novel class of protease targets of phosphatidylethanolamine-binding proteins (PEBP): A study of the acyl peptide hydrolase and the PEBP inhibitor from the archaeon Sulfolobus solfataricus. Mol Bio Sys 6, 2498–2507.

36.

Parravicini

, Natalello

, Papaleo

, De Gioia

, Doglia

, Lotti

, Brocca

(2013) Reciprocal influence ofprotein domains in the cold-adapted acyl aminoacyl peptidase from Sporosarcina psychrophila. PLoS One 8, e56254.

37.

Sharma

, Ortwerth

(1993) Bovine lens acylpeptide hydrolase. Purification and characterization of a tetrameric enzyme resistant to urea denaturation and proteolytic inactivation. Eur J Biochem 216, 631–637.

38.

Riccio

, Gogliettino

, Palmieri

, Balestrieri

, Facchiano

, Rossi

, Palumbo

, Monti

, Cocca

(2015) A new APEH cluster with antioxidant functions in the Antarctic hemoglobinless icefish Chionodraco hamatus. PLoS One 10, e0125594.

39.

Yamin

, Bagchi

, Hildebrant

, Scaloni

, Widom

, Abraham

(2007) Acyl peptide hydrolase, a serine proteinase isolated from conditioned medium of neuroblastoma cells, degrades the amyloid-beta peptide. J Neurochem 100, 458–467.

40.

Yamin

, Zhao

, O’Connor

, McKee

, Abraham

(2009) Acyl peptide hydrolase degrades monomeric and oligomeric amyloid-beta peptide. Mol Neurodegener 4, 33.

41.

Bartus

(2000) On neurodegenerative diseases, models and treatment strategies: Lessons learned and lessons forgotten a generation following the cholinergic hypothesis. Exp Neurol 163, 495–529.

42.

Liu

, Kawai

, Berg

(2001) Beta -Amyloid peptide blocks the response of alpha 7-containing nicotinic receptors on hippocampal neurons. Proc Natl Acad Sci U S A 98, 4734–4739.

43.

Pancetti

, Olmos

, Dagnino-Subiabre

, Rozas

, Morales

(2007) Noncholinesterase effect induced by organophosphate pesticides and their relationship to cognitive processes: Implication for the action of acylpeptide hydrolase. J Toxicol Environ Health B Crit Rev 10, 623–630.

44.

Terry

Jr , Buccafusco

(2003) The cholinergic hypothesis of age and Alzheimer’s disease-related cognitive deficits: Recent challenges and their implications for novel drug development. J Pharmacol Exp Ther 306, 821–827.

45.

Gogliettino

, Balestrieri

, Cocca

, Mucerino

, Rossi

, Petrillo

, Mazzella

, Palmieri

(2012) Identification and characterisation of a novel acylpeptide hydrolase from Sulfolobus solfataricus: Structural and functional insights. PLoS One 7, e37921.

46.

Nakai

, Yamauchi

, Sumi

, Tanaka

(2012) Role of acylamino acid-releasing enzyme/oxidized protein hydrolase in sustaining homeostasis of the cytoplasmic antioxidative system. Planta 236, 427–436.

47.

Scaloni

, Jones

, Barra

, Pospischil

, Sassa

, Popowicz

, Manning

, Schneewind

, Manning

(1992) Acylpeptide hydrolase: Inhibitors and some active site residues of the human enzyme. J Biol Chem 267, 3811–3818.

48.

Jones

, Manning

(1985) Acylpeptide hydrolase activity from erythrocytes. Biochem Biophys Res Commun 126, 933–940.

49.

Ramírez-Santana

, Zúñiga

, Corral

, Sandoval

, Scheepers

, Van der Velden

, Roeleveld

, Pancetti

(2015) Assessing biomarkers and neuropsychological outcomes in ruralpopulations exposed to organophosphate pesticides in Chile–studydesign and protocol. BMC Public Health 15, 116.

50.

Mandel

, Morelli

, Halperin

, Korczyn

(2010) Biomarkers for prediction and targeted preventionof Alzheimer’s and Parkinson’s diseases: Evaluation of drug clinical efficacy. EPMA J 1, 273–292.

51.

Humpel

(2011) Identifying and validating biomarkers for Alzheimer’s disease. Trends Biotechnol 29, 26–32.

52.

McKhann

, Knopman

, Chertkow

, Hyman

, Jack

Jr , Kawas

, Klunk

, Koroshetz

, Manly

, Mayeux

, Mohs

, Morris

, Rossor

, Scheltens

, Carrillo

, Thies

, Weintraub

, Phelps

(2011) The diagnosis of dementia due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 7, 263–269.

53.

Pfaffl

(2001) A new mathematical model for relative quantification in real-time RT–PCR. Nucleic Acids Res 29, e45.

54.

Ciechanover

, Kwon

(2015) Degradation of misfolded proteins in neurodegenerative diseases: Therapeutic targets and strategies. Exp Mol Med 47, e147.

55.

Carrell

, Lomas

(1997) Conformational disease. Lancet 350, 134–138.

56.

Corey-Bloom

(2002) The ABC of Alzheimer’s disease: Cognitive changes and their management in Alzheimer’s disease and related dementias. Int Psychogeriatr 14(Suppl 1), 51–75.

57.

Ryu

, McLarnon

(2009) A leaky blood-brain barrier, fibrinogen infiltration and microglial reactivity in inflamed Alzheimer’s disease brain. J Cell Mol Med 13, 2911–2925.

58.

Zipser

, Johanson

, Gonzalez

, Berzin

, Tavares

, Hulette

, Vitek

, Hovanesian

, Stopa

(2007) Microvascular injury and blood-brain barrier leakage in Alzheimer’s disease. Neurobiol Aging 28, 977–986.