Characterization of the Molecular Mechanisms Underlying the Chronic

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Characterization of the Molecular Mechanisms Underlying the Chronic Phase of Stroke in a Cynomolgus Monkey Model of Induced Cerebral Ischemia Henry C. H. Law, Samuel S.W. Szeto, Quan Quan, Yun Zhao, Zaijun Zhang, Olga Krakovska, Leong Ting Lui, Chengyou Zheng, Simon Ming Yuen Lee, K.W. Michael Siu, Yuqiang Wang, and Ivan K Chu J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.6b00651 • Publication Date (Web): 19 Jan 2017 Downloaded from http://pubs.acs.org on January 20, 2017

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Journal of Proteome Research

Characterization of the Molecular Mechanisms Underlying the Chronic Phase of Stroke in a Cynomolgus Monkey Model of Induced Cerebral Ischemia

BY Henry C. H. Law1,#, Samuel S. W. Szeto1, #, Quan Quan1, Yun Zhao1, Zaijun Zhang2, Olga Krakovska4, Leong Ting Lui1, Chengyou Zheng2, Simon M.-Y. Lee3, K. W. Michael Siu4,5, Yuqiang Wang2 and Ivan K. Chu1,*

1

Department of Chemistry, The University of Hong Kong, Hong Kong, China

2

Institute of New Drug Research and Guangdong Province Key Laboratory of Pharmacodynamic

Constituents of Traditional Chinese Medicine, College of Pharmacy, Jinan University, Guangzhou 510632, China 3

State Key Laboratory of Quality Research in Chinese Medicine and Institute of Chinese Medical

Sciences, University of Macau, Avenue Padre Tomás Pereira S.J., Taipa, Macao, China 4

Department of Chemistry and Centre for Research in Mass Spectrometry, York University, Toronto,

Ontario, Canada 5

Department of Chemistry and Biochemistry, University of Windsor, Windsor, Ontario, Canada

#

These authors contributed equally to this work

*

Address correspondence to: Ivan K. Chu, Tel: (852) 2859 2152, Fax: (852) 2857 1586, E-

mail:[email protected]

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ABSTRACT Stroke is one of the main causes of mortality and long-term disability worldwide. The pathophysiological mechanisms underlying this disease are not well understood, particularly in the chronic phase after the initial ischemic episode. In this study, a Macaca fascicularis stroke model consisting of two sample groups, as determined by MRI-quantified infarct volumes as a measure of the stroke severity 28 days after the ischemic episode, was evaluated using qualitative and quantitative proteomics analyses. By using multiple online multidimensional liquid chromatography platforms, 8790 non-redundant proteins that condensed to 5223 protein groups at 1% global false discovery rate (FDR). After the application of a conservative criteria (5% local FDR) 4906 protein groups were identified from the analysis of cerebral cortex. Of the 2068 quantified proteins, differential proteomic analyses revealed 31 and 23 were dysregulated in the elevated- and low-infarct-volume groups, respectively. Neurogenesis, synaptogenesis, and inflammation featured prominently as the cellular processes associated with these dysregulated proteins. Protein interaction network analysis revealed that the dysregulated proteins for inflammation and neurogenesis were highly connected, suggesting potential cross-talk between these processes in modulating the cytoskeletal structure and dynamics in the chronic phase poststroke. Elucidating the longterm consequences of brain tissue injuries from a cellular prospective, as well as the molecular mechanisms that are involved, would provide a basis for the development of new potentially neurorestorative therapies. Keywords: Stroke biology, iTRAQ, cynomolgus monkey, brain proteome, ischemia, chronic phase


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INTRODUCTION Stroke is an acute neurological trauma event resulting in severe brain damage; it is a leading cause of death and long-term disability worldwide 1. Ischemic stroke, the predominant form of this cerebrovascular disease, is caused by a transient or permanent reduction of cerebral blood flow that occurs within a region of the brain

2, 3

. The decreased blood flow can result from an embolic occlusion of a cerebral artery, or

from a local thrombosis 2, 3. It deprives the brain of oxygen and nutrients (e.g., glucose) that are essential for survival of the neural cells. Those cells within the infarct region die as a result of the initial ischemic injury, while those in the penumbra are affected by secondary insults involving the influx of immune cells, reactive oxygen species (ROS), and toxic inflammatory mediators 4, 5. Currently, only thrombolytic therapy using recombinant tissue plasminogen activators has displayed therapeutic effects for the treatment of ischemic stroke

6, 7

. Nevertheless, only limited numbers of patients are administered this

therapy because of its narrow therapeutic time window. This treatment also carries an associated risk of brain hemorrhaging

6

and, despite its effectiveness, most patients will exhibit neurological deficits 8. A

greater understanding of the molecular details during the later stages of stroke progression should lead to the development of therapeutic strategies for use beyond the current time window to restore and promote neurological function 4, 9. The majority of studies related to stroke have been focused on the biochemical and physiological changes occurring during the acute phase (the first few hours) after a stroke episode, and the effects of therapeutic interventions during the corresponding time window 10. There is evidence, however, that subsequent to the acute phase—and, more specifically, during the chronic phase (i.e., days to weeks post-stroke)— significant physiological and cellular changes can still occur within the brain tissue surrounding the infarct region; for example, from longitudinal observations of changes in the levels of neurological impairments (trunk control, motor function, sensory, cognition) and in functional impairments (activity of daily living and gait)

11

. In several human patient studies, recovery from stroke symptoms has been

observed up to six months after the stroke episode, with the most significant period occurring during the



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first 30 days

11-13

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. In regards to motor recovery, it has also been demonstrated that, irrespective of the

severity of the stroke episode, the most prominent improvement is observed within four weeks

14

.

Echoing the findings in humans, the clinical examination rating scores of cynomolgus macaque (Macaca fascicularis) stroke models also significantly improved in the first month after the experimental stroke15. Consistent with the observation that functional recovery can still occur at one month post-stroke, a number of repair-related molecular and cellular processes underlying these physical and behavioral changes have been identified. Neurogenesis, angiogenesis, and synaptogenesis have been defined as the major processes occurring at the molecular level in the stroke recovery phase

16, 17

. In conjunction, cell

proliferation, differentiation, and migration occur in a coordinated manner as well. The development of new neurons is a critical and essential process for the restoration and recovery of brain function. It has been demonstrated in animal model and human autopsy studies that new neuron growth occurs in the post-stroke chronic phase

18-20

. After surviving the ischemic stroke episode, denervated neurons can

undergo synaptogenesis involving axonal and dendritic sprouting to re-establish synaptic connections 22

21,

. Newly developed neurons also develop neuronal processes that eventually become interconnected and

form functional synapses

23, 24

. Cell differentiation has also been observed after stroke in a human

postmortem study, reaching a maximum at 10–24 days and still observable at 90 days

25

. Functional

recovery and the underlying cellular processes may be induced spontaneously or due to therapeutic intervention. The extent and ability to recover is dependent on the severity of the stroke episode; a chronic stroke condition could occur if the impact is too severe. During this chronic stroke condition, the predominant processes occurring within the brain tissues would be those associated with injury (e.g., astrocytosis, inflammation). Reactive astrocytes have been observed in human brain samples after ischemic injury with the characteristic upregulation of glial fibrillary glial protein

26, 27

. Astrocytosis has

been observed in the peri-infarct area in rat brains 30 days post-stroke 28. Inflammation appears to be a significant contributing factor to the pathogenic processes immediately affecting the infarcted tissue, and Page 4 of 47 ACS Paragon Plus Environment

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also plays a role in the long term damage appearing in the ischemic penumbra 4. Though chronic inflammation has not been observed in rodent models, inflammation features (e.g., the presence of inflammatory mononuclear cells and macrophages) have been observed in human patients during the chronic phase 29. Although the majority of stroke studies to date have implemented rodent animals, non-human primate models have recently been proposed because of discrepancies between findings derived from rodent and human studies

30, 31

. The anatomical and physiological differences between rodent and human brains are

major confounding factors as to why promising results observed in rodent models have not been translated to humans in subsequent clinical studies

32-34

. Within non-human primate models, macaque

monkeys (genus Macaca)—particularly M. fascicularis—are an ideal model because their brain structure, cortical anatomy, and neurovasculature closely resemble those of humans 32, 35, 36. This model has recently been considered a clinically relevant platform for investigations of pathophysiological alterations associated with ischemic brain injury, treatment responses, and clinically pertinent outcomes that may be more appropriate for ischemic stroke patients 15, 35. In conjunction, the easily trained animals are amenable to assessments for cognitive, motor, and sensory deficits through detailed neurobehavioral tasks 35. Both transient and permanent middle cerebral artery occlusion (t/p-MCAO) M. fascicularis models have been implemented successfully for studies examining various aspects of stroke biology 32, 37. In this study, our aim was to examine the qualitative and quantitative proteomic changes in a M. fascicularis t-MCAO surgery-induced stroke model and provide greater insight into the cellular and biochemical mechanisms occurring within the chronic phase. Using magnetic resonance imaging (MRI)quantified infarct volumes as a measure of the stroke severity, we evaluated the proteomic profiles of monkeys possessing low and elevated infarct volumes. The low-infarct-volume (LIV) group would be indicative of those monkeys possessing brain tissues undergoing neural repair

16, 17

, while the elevated-

infarct-volume (EIV) group would suggest a continuation of the cellular processes associated with a chronic stroke condition

2, 4, 5

. A number of differentially expressed proteins were systematically mapped Page 5 of 47 ACS Paragon Plus Environment


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to various aspects of neurogenesis, synaptogenesis, inflammation, reactive astrogliosis, and angiogenesis observed during the chronic stroke phase; deciphering the underlying processes could potentially reveal novel neurorestorative, non-conventional therapeutic targets or strategies that would complement currently applied acute phase interventions.


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EXPERIMENTAL PROCEDURE Experiment design The overall experiment design and workflow is illustrated in Figure S-1. At the beginning of the experiment, eight monkeys were subjected to transient middle cerebral artery occlusion (t-MCAO) to surgically mimic ischemic stroke. After the surgery, the recovery of the monkeys was monitored in terms of the magnetic resonance imaging (MRI) quantified infarct volume and neurological function assessments. According to the infarct volume observed on the 28th day after stroke, the monkeys were further classified into elevated-, intermediate-, or low-infarct volume groups. This classification was confirmed by neurological function assessments and immunohistology of the brain slides. The penumbra adjacent to the ischemic injury and the contralateral tissue in the corresponding position of each monkey were collected. Proteins were extracted from the collected tissues. The protein digest prepared from the tissue samples ipsil- and contralateral to the stroke injury were differentially labeled with isobaric tags for all eight monkeys. There were 16 samples in total and mixed into two combined iTRAQ (isobaric tag for relative and absolute quantitation) 8-plex samples (iTRAQ1 and iTRAQ2) for simultaneous qualitative and quantitative analysis. The detailed tagging strategy is illustrated in Table S-1. In the qualitative protein profiling, the underivatized tryptic digest and the enriched phosphopeptides were included in the analysis in an attempt to extend the proteome coverage. These samples, including the iTRAQ-labeled ones, the underivatized tryptic digest, and the enriched phosphopeptides, were analyzed by five different multidimensional liquid chromatography – tandem mass spectrometry (MDLC-MS/MS) platforms. These MDLC platforms employed different separation mechanisms, such that peptides with contrasting physicochemical properties could be captured during the analysis. The collected MS/MS spectra were searched against the appropriate protein sequence database to identify the proteins present in the sample. In the protein quantitation, the proteome changes in the ipsilateral tissue was estimated using the contralateral tissue as a control in each monkey. Proteins were considered to be differentially expressed in



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the low and elevated infarct groups of monkeys if the iTRAQ ratios were deemed dysregulated in >66% of the samples in each group.

Animals Eight laboratory-bred adult male cynomolgus macaques (M. fascicularis) were used in this study. They were approximately 4–5 years of age with body weights of 3.0–4.0 kg at the initiation of the experiment. All experimental procedures were performed in accordance with testing facility standards of practice and regulations of Kunming Biomedical International (Yunnan Province, China), ensuring humane and proper care of the research animals The monkeys were housed individually in stainless steel cages and had adequate auditory and visual communication with other monkeys. Before conducting the planned experiments, the test subjects were acclimatized for one week or more in individual cages; during the acclimatization period, their health conditions were monitored on a daily basis. The supporting documents of the monkey experiments (project no.: KBI K001112019-01,01; KBI K001112018-01,01; KBI K001112006-01,01) are provided in Supplementary information 1.

Transient transcranial middle cerebral artery occlusion surgery Anesthesia was induced by intramuscular injection of ketamine (10 mg/kg) immediately subsequent to an intramuscular injection of atropine sulfate (0.05 mg/kg). Anesthesia was maintained with isoflurane inhalation (0.5–2%) mixed in oxygen throughout the duration of the surgical procedure. After turning a large cranial flap and opening the dura over the left lateral frontal cortex, the right M1 segment of the middle cerebral artery, 2 mm medial to the olfactory tract, was transiently occluded to induce focal cerebral ischemia. The arterial clamp was removed after 4 h of middle cerebral artery occlusion to restore blood flow. Upon completion of the surgical procedure, an intramuscular injection of pentobarbital (30 mg/kg) was administered to maintain anesthesia for an additional 3 h.


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The monkeys used for the standard of recovery in the infarct volume analysis were treated with edavarone (EDA) after the surgery38. EDA (20 mg/kg) was administered by i.v. three hours after the t-MCAO

surgery. The drug was given twice daily for seven consecutive days.

Magnetic resonance imaging (MRI) Before the experiment, the monkeys were anesthetized through intramuscular administration of ketamine hydrochloride (10 mg/kg) containing atropine sulfate (0.05 mg/kg). MRI of the subject animals was conducted by Kunming Biomedical International (Yunnan Province, China) using a Siemens MAGNETOM Verio 3T MRI scanner (Germany). MRI was performed from the frontal to the posterior brain regions in slices with 4-mm thickness with diffusion-weighted imaging (DWI), fluid attenuated inversion recovery (FLAIR), and T1- and T2-weighted imaging sequences. The infarct areas were defined as the white areas on the ischemic side of the brain slides versus the total area of the contralateral side. The areas were estimated using Adobe Photoshop 7.0 software (San Jose, CA, USA). The original MRI scans and the calculated infarct volume are provided in Supplementary information 2 and Table S-2, respectively. The monkeys were clustered into an elevated infarct volume (EIV) group, intermediate infarct volume (IIV) group, and low infarct volume (LIV) group. Briefly, the infarct volumes were clustered based on the k-means clustering algorithm and the elbow method.39, 40 Details of the methodology are described in Supplementary Information 3. The results of the data analysis for the elbow method are presented in Table S-3 and Figure S-2A. Neurological function assessment To access the neurological deficit after the t-MCAO surgery, a standard score was assigned to each monkey based on the assessment scheme in Supplementary information 4. The assessment scheme was modified based on the one described in Kito et al. 41 Of the 83 points available, 29, 18, 17 and 19 points Page 9 of 47 ACS Paragon Plus Environment


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were assigned to consciousness, sensory system, motor system and skeletal muscle coordination, respectively. Two researchers experienced in neurological deficit evaluation performed the assessment as described. The monkeys were assessed 7 and 28 days after the t-MCAO surgery. These results were tabulated in Table S-2. In the addition to the neurological function assessment, the upper limb motor function contralateral to the ischemic injury was also assessed by a food catching experiment. In the experiment, the monkeys were constrained, such that it could only use the right arm to reach out for food (15 pieces of apple diced into 1 cm3). Before the t-MCAO surgery, the monkeys were trained and were able to retrieve all 15 pieces of apple within 5 min. After the t-MCAO surgery, the motor functions were affected differently. Tissue sample preparation At termination of the experiment (28 days post-surgery), monkeys were euthanized with an overdosing intravenous sodium pentobarbital injection (150 mg/kg). The brains were extracted surgically and placed immediately on ice, then 4 mm brain slices (total: 12 pieces for each brain) were sectioned horizontally. The sections were then immersed in ice-cold saline solution (0.9%). Tissue samples from the penumbra (adjacent to the infarcted tissue) of the ipsilateral cerebral hemisphere and samples from the corresponding location in the normal contralateral cerebral hemisphere were extracted from the brain slices that revealed a visible infarct area. The tissues were immediately flash frozen in liquid nitrogen and stored at –80 °C; the entire procedure was complete within 15 min. Other brain sections were fixed in 4% formaldehyde for 48 h and embedded in paraffin wax. Immunohistochemical staining Slices (6 µm) were sectioned from the paraffin block, deparaffinized, and rehydrated. The slides were treated with citrate buffer (pH 6) at 90–100 °C for antigen retrieval. Endogenous peroxidase activity was quenched with 3% H2O2. To reduce the nonspecific background, endogenous biotin was blocked with Biotin Blocking System (Dako). The samples were then incubated with anti-NeuN antibodies (Cat. No. MAB377, Millipore) and anti-GFAP antibodies (Cat.No. MAB360, Millipore). Polyclonal goat anti-


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mouse immunoglobulin/HRP (Code No. P0447, Dako) was used as the secondary antibody. Diaminobenzidine was used as the chromagen and haematoxylin was used as the counterstain. Finally, the samples were dehydrated and mounted before observation under an optical microscope. Protein sample preparation To extract the protein, the frozen brain tissues were first rinsed with ice cold RIPA buffer containing 1x phosphatase and protease inhibitors. The brain slice sections were then minced into small pieces and homogenized in RIPA buffer using a Tissue Tearor (Biospec, Bartlesville, OK) at full speed on ice until the lysate was homogeneous (ca. 10–30 s). The samples were vortexed briefly, ultrasonicated at 4 °C for 10 cycles (10 s ON/10 s OFF), and then centrifuged at 4 °C and 15 000 rpm for 15 min. The supernatant was transferred into new pre-cooled tubes and protein precipitation was performed with the addition of ice-cold acetone and overnight incubation at –20 °C. The precipitated proteins were collected by centrifugation (RT, 4000 rpm, 15 min), re-dissolved in 8 M urea, and quantified using a Bradford assay kit. Sample preparation for proteome profiling and isobaric tags for relative and absolute quantitation (iTRAQ) For the samples prepared for qualitative proteomics analysis, the extracted protein lysates were dissolved in 8 M urea and reduced with 10 mM DTT in 100 mM NH4HCO3 at 60 °C for 30 min, followed by incubation with 20 mM IAA in 100 mM NH4HCO3 at room temperature in the dark for 1 h (for cysteineblocking). The samples were diluted with 100 mM NH4HCO3 so that the final concentration of urea was 2 M. Trypsin was added, at a trypsin-to-protein ratio of 1:25 (w/w), and then the samples were incubated overnight at 37 °C. The samples were lyophilized and stored at –80 °C until required for use. For the samples prepared for quantitative proteomics analysis, on-filter digestion was performed with minor modifications 42. Briefly, proteins (100 µg) designated for a specific isobaric tag in iTRAQ were denatured with 10 mM DTT in 100 mM NH4HCO3 for 30 min at 60 °C, then alkylated with 10 mM IAA in 100 mM NH4HCO3 for 1 h at room temperature. The denatured proteins were loaded on Microcon® Page 11 of 47 ACS Paragon Plus Environment


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centrifugal filters and purified through centrifugation (4000 rpm). The sample on the filter was digested with sequencing-grade trypsin [trypsin to sample ratio, 1:33 (w/w)] in 0.5 mM TEAB buffer at 37 °C overnight. The trypsinized samples were collected and labeled with the corresponding isobaric tags according to the manufacturer’s protocol. The samples were lyophilized and stored at –80 °C until required for use. Phosphorylated monkey brain protein digestion and enrichment The sample protein digestion was performed in the same manner as in the qualitative proteomic analysis. After tryptic digestion, samples were desalted offline using Sep-Pak C18 cartridges (Waters Corporation), portioned as 250-µg aliquots and dried in vacuo. Preparation of the enriched phosphopeptide samples was performed following a previously published protocol with slight modifications 43. The TiO2 gel loading tips were prepared in-house using titanium beads (Titansphere bulk media, 5 micron, GL Science, Tokyo, Japan) following the protocol described by Rappsilber et al. 43. To obtain the best enrichment efficiency of the TiO2 material 44, desalted peptides (250 µg) were loaded onto the TiO2 beads in buffer A [300 mg mL–1 lactic acid in buffer B (80% ACN, 0.1% TFA); 80 µL], and washed with buffer B (200 µL) to remove most of the non-phosphorylated content of the peptide mixture. Two aliquots (each 50 µL) of buffer C (0.5% NH4OH) were used to elute the phosphorylated peptides from the TiO2 gel loading tips. Eight enriched aliquots were pooled together as an individual injection to ensure that an adequate amount of sample was used in the subsequent proteomic analysis. Liquid chromatography iTRAQ sample types were reconstituted in 0.5% formic acid and analyzed using multiple online multidimensional liquid chromatography (MDLC) platforms. Two-dimensional RP–SCX–RP PGC–RP

46

45

and

platforms were mounted on an Eksigent nanoLC Ultra 2D Plus (AB SCIEX, Framingham,

MA). Concatenation RP–RP SA(C)X–RP

49

47

, two-/three-dimensional HILIC–SCX–RP

48

, and four-dimensional RP–

platforms were assembled with Agilent 1200 series nano pump, capillary pumps, and a

10-well-per-plate auto-sampler (Agilent Technologies, Wilmington, DE). The detailed assembly of the Page 12 of 47 ACS Paragon Plus Environment

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valve systems and specifications of the columns and operations can be found in the respective references. All columns in the system mentioned were packed in-house with the previously mentioned packing materials using an ultra-high pressure syringe pump (up to 6000 psi). For MDLC platform assembled with Agilent LCs, flow channel switching and injections were conducted using Valco valves. In total, 8 and 11 MDLC-MS/MS experiments were completed for iTRAQ1 and iTRAQ2, respectively. MS parameters and database search All MS data were acquired using a TripleTOF 5600 system (AB SCIEX, Concord, ON) fitted with a Nanospray III source (AB SCIEX, Concord, ON). The MS and independent data acquisition parameters are listed in Table S-4. The data collected were searched against the theoretical spectra generated from the sequences in the NCBI M. fascicularis reference proteome database (released in January, 2014 with 56 572 entries; http://www.ncbi.nlm.nih.gov/) using the Paragon algorithm in the ProteinPilot 4.5 software (AB SCIEX, Concord, ON). The parameters used in the database searches are listed in Table S5. The plug-in Proteomics System Performance Evaluation Pipeline (PSPEP)

50

featured on ProteinPilot

4.5 was employed for analysis of the false discovery rate (FDR). Protein groups and peptides with local FDR of less than 5% were considered as identified entries

51, 52

. All mass spectrometric data, the MGF

files, and the database search results have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository with the dataset identifier PXD003173 (Reviewer account details: Username: [email protected]; Password: DFIixLtR). The lists of the identified peptides, proteins and protein groups are provided in Table S-6 and S-7. iTRAQ ratio calculations To estimate the relative protein expression between the ipsilateral and contralateral tissues, ProteinPilot first excluded the shared peptides among the protein groups and estimated the iTRAQ reporter ion ratios in the collected MS/MS spectrum. The reporter ion ratios from different LC-MS/MS experiments of the same sample were pooled together to calculate the protein ratios. The protein ratios were calculated using the weighted average of the natural logarithm of the reporter ion ratios, as described in the ProteinPilot Page 13 of 47 ACS Paragon Plus Environment


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manual. The calculated protein ratios were based on spectra with at least 95% confidence; only proteins having at least four spectra were considered as quantified. The calculated protein ratios were then normalized by the global protein median ratio. A t-test was applied to the iTRAQ reporter ion ratios observed from the spectra for each protein; expression ratios of ≥1.23 or ≤0.81 with a p-value of ≤0.05 were considered dysregulated. The rationale of using 1.23 and 0.81 as the threshold of up- and downregulated proteins is elaborated in Supplementary Information 5. Proteins were considered to be differentially expressed in the LIV and EIV groups of monkeys if the iTRAQ ratios were deemed dysregulated in >66% of the samples in each group. The list of the quantified proteins is provided in Table S-7, with those considered dysregulated highlighted in red (upregulated) or green (downregulated). Western blot analysis For protein extraction, tissues were extracted with RIPA lysis buffer containing 1% PMSF and 1% protease inhibitor cocktail on ice for 10 min. The lysates were centrifuged (12 500 × g, 20 min, 4 ⁰C) and the supernatants were then collected and stored at –80 ⁰C until use. Protein contents were assayed using a BCA protein quantification kit (Pierce, Rockford, IL, USA). Protein samples (30 µg) were resolved using SDS-PAGE and transferred to PVDF membranes. The immunoblots were analyzed with the appropriate primary antibodies, anti-annexin V polyclonal antibodies (Abcam, Cambridge, UK, ab14196) and antiCaMKII (pan) monoclonal antibodies (Cell Signaling, Danvers, MA, 4436), in 1:1000. Horseradish peroxidase-conjugated secondary antibodies (1:2500) were used to detect the proteins of interest through enhanced chemiluminescence. Bioinformatic analysis The identified protein molecular weights and pI values were calculated using Protein Digestion Simulator (http://omics.pnl.gov). The human protein homologues of the monkey cerebral cortex tissue proteins were identified using the Basic Local Alignment Search Tool (BLAST) from the National Center for Biotechnology Information (http://blast.ncbi.nlm.nih.gov/Blast.cgi). Similarities at the protein sequence level were identified with BLASTP using the Swiss-Prot Homo sapiens protein database. The human


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protein with the highest BLAST score was selected as the representative homologue for each protein group. The list of representative human protein homologues was compared with cerebral cortex tissue proteins identified in the Human Proteome Map (HPM) 53. The amino acid alignments of selected monkey protein identified and the corresponding human protein homolog is presented in Figure S-3. The representative homologues list was also uploaded to the Database for Annotation, Visualization, and Integrated Discovery (DAVID; http://david.abcc.ncifcrf.gov/)

54, 55

and Ingenuity Pathway Analysis

(Ingenuity Systems; www.ingenuity.com) for functional annotation characterization.



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RESULTS and DISCUSSION Chronic phase neurological phenotypes of a macaque t-MCAO surgery-induced model of ischemic stroke To examine the cellular processes occurring during the chronic phase of stroke, eight monkeys were subjected to t-MCAO surgery and maintained for a period of 28 days. The progression of the stroke condition was monitored by evaluating the infarct volumes, quantified using MRI, after 7 and 28 days. Infarct volumes have been used previously as the primary outcome measure to gauge the severity of chronic stroke conditions

56-58

. In addition to the infarct volume, the neurological function for each

monkey was assessed as a measure complementary to the MRI infarct volume analysis. After a seven-day period, the infarct volumes of the eight subjects were clustered together within a narrow range, as expected because of the inherent variability of the t-MCAO surgery 32. In contrast, an independent set of four monkeys that had been subjected to the t-MCAO surgery and subsequently administered with edavarone (EDA), a free radical scavenger that provides neuroprotection in a variety of cerebrovascular injuries

59

, displayed a wide range of infarct volumes (Figure 1A). The EDA-treated monkeys were

considered as the reference point for those subjects deemed to be undergoing the recovery process. After 28 days, the monkey infract volume distributed from 5.7 to 23.1%. Concomitantly, the neurological deficit test results generally correlated (R = 0.50, p-value < 0.05) with the infarct volume in each monkey (Table S-2 and Figure S-2B). In the initial inspection of the infract volumes, one population had infarct volumes comparable with those of the EDA-treated monkeys (Figures 1B and C). When the eight subject monkeys were combined into the analysis of a cohort of 12 ischemic stroke model monkeys, three of them resided above the 75th percentile (Figures 1B and D). In order to find the optimal way to phenotype the monkeys, the k-means clustering algorithm was used to cluster the infarct volumes; the clustering method was further optimized by the elbow method (Supporting information 3, Figure S-2A)39, 40. As a results, the monkeys were classified into three groups, the elevated, intermediate and low infarct volume (EIV, IIV and LIV) groups. To corroborate our classification scheme, immunohistochemical analysis for NeuN and GFAP expression was performed in the cerebral cortex tissue of both the LIV and EIV groups. Page 16 of 47 ACS Paragon Plus Environment

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NeuN is a neuron-specific nuclear protein and well-recognized marker of mature neurons 60. The NeuN staining substantiated this classification, with the LIV group having a significantly larger number of NeuN positive cells (stained brown) when compared with that of the EIV group after 28 days (Figures 1F and G). This observation suggested that either a larger population of mature neurons survived the stroke episode or the development of new neurons had occurred within these tissues during this time period. GFAP is a classic reactive astrocyte marker, which are often triggered CNS injury. They are involved in the subsequent inflammation and impose a major barrier to regeneration61,

62

.

In the

immunohistochemical analysis, there were larger number of GFAP positive cells in the EIV group than the LIV group, which further supported that the recovery of the EIV group monkeys were inhibited. Unbiased global proteomic analysis of the monkey cerebral cortex using MDLC–MS/MS To provide insight into the underlying cellular changes occurring within the LIV and EIV sample groups, we conducted qualitative and quantitative proteomic surveys of the macaque cerebral cortex tissue homogenate. We employed a strategy involving three sample preparation methodologies in combination with a variety of MDLC–MS/MS platforms (Figure S-1). With the samples generated from the three sample preparation methods, a total of 28 LC–MS/MS analyses were acquired. The combined data yielded a collection of 1 733 964 peptide spectral matches (PSMs), based on the targshet-decoy search results against the NCBI M. fascicularis database (Figure 2A). These PSMs translated into 134 266 highconfidence peptides (including chemical modifications) using a conservative 5% local FDR. (Table S-6). These peptides corresponded to 63 520 unique peptide sequences and were mapped to a combined set of 8790 nonredundant protein entries. The application of a conservative grouping criteria to the proteins identified from the acquired peptide sequences resulted in the identification of 4906 protein groups. To demonstrate the unbiased profiling of the macaque cerebral cortex proteome, several aspects of the identified proteome were evaluated. The identified sequence coverage profile was comparable with that of the HPM, the most recent and comprehensive consortium lead study of the human proteome (Figure 2B) 53

. The macaque cerebral cortex proteome pI and molecular weight profiles were fairly similar to those in



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the HPM. The values of pI of the identified proteins ranged from 3.9 to 12.2, with the population exhibiting a trimodal distribution pattern: peaks centered at values of pI of approximately 6, 8, and 9 (Figure 2C). This trimodal pI distribution pattern is consistent with the observed profiles for a number of in silico predicted and experimentally characterized eukaryote proteomes 63, 64. The identified proteins had a molecular weight range from 5 to 3956 kDa, with thymosin β10 as the smallest and titin-like isoform X1 as the largest protein observed (Figure 2D) 53. To characterize the overall functional and biochemical properties of the characterized proteome, the identified proteins were subjected to gene ontology (GO) and functional annotation analyses 54, 55. As expected for a proteome derived from a whole tissue lysate, a wide variety of subcellular localizations and a diverse set of molecular functions could be assigned to the identified proteins (Figures 2E and F), with a significant number being mapped to various prominent cellular processes and canonical pathways (Figure S-4). We also compared the identified cerebral cortex proteome to the one reported as part of the HPM (Figure 2G) 53 and with various other comparable brain proteomes (Figure S-5)

65-68

. A substantial portion of the observed proteins overlapped with the

corresponding homologues in the human cerebral cortex proteome (92.8%), and a large majority overlapped with the other brain proteomes examined. These systematic comparisons of the various protein properties revealed no inherent bias in our macaque cerebral cortex proteome results.

Proteomic analyses to evaluate the cellular processes occurring in the cerebral cortex of the recovered and chronically diseased monkeys after one month post-stroke Quantitative proteomic analyses of the cerebral cortex tissue homogenates from both the EIV and LIV sample groups resulted in 31 and 23 dysregulated proteins, respectively (Tables 1 and 2), with 19 proteins being upregulated in both sample groups (Table S-8). Western blot analysis were carried out to confirm the dysregulation observed in the iTRAQ analysis. The regulations of calcium/calmodulindependent protein kinase II alpha (α-CaMKII) and annexin A5 in the Western blot analysis were found to be consistent with those found in iTRAQ in the representative monkeys (Figure 3 and Table S-9). Page 18 of 47 ACS Paragon Plus Environment

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Because the protein sequence between monkeys and humans is highly conserved (Figure S-3), the human protein homologues were used in the gene ontology annotation and other bioinformatics analyses. The dysregulated proteins were annotated to the tissue injury associated processes (e.g., neurogenesis, synaptogenesis, inflammation, angiogenesis) using Ingenuity Pathway Analysis; 53 of the 73 dysregulated proteins were accounted for, indicating that these were the major cellular processes associated with the proteomic perturbations observed in both sample groups. The upregulated expression of glial acid fibrillary protein and vimentin, two components of the intermediate filament system and prominent markers for neuroglia cells (e.g., radial glial cells, reactive astrocytes), were observed among the proteins regulated in both sample groups

26, 69

. Radial glial cells are involved in neurogenesis as

precursor cells to new neurons and in neuronal migration by acting as scaffolds for migrating neurons in the cerebral cortex 69; reactive astrocytes are the key cell type indicative of a physiological response to brain tissue injury 26.

Synaptogenesis For the EIV group, a number of proteins associated with synaptic functions and markers of synaptogenesis were downregulated (Table 1), including synaptophysin, synapsin II, and syntaxin 1A. Synaptophysin is the most abundant synaptic vesicle membrane protein and regulates the kinetics of synaptic vesicle endocytosis in neurons

70

. Synapsin II is a phosphoprotein that modulates

neurotransmitter release at the pre-synaptic terminal, by reversibly tethering synaptic vesicles to the actin cytoskeleton. It is one of the most abundant proteins on synaptic vesicles and has a role in neural development and plasticity 71. Syntaxin 1A is one of three essential neuronal exocytotic fusion machinery components of the presynaptic SNARE complex involved in priming of synaptic vesicles for release 72. Glycoprotein M6a is a member of the proteolipid protein family of tetraspan proteins localized to glutamatergic axonal membranes; it induces neurite/axon outgrowth, increases filopodium/spine density, and participates in synaptogenesis 73, 74. Together, these downregulated proteins suggest that the processes associated with neuron development and synapse formation were reduced, consistent with the phenotype Page 19 of 47 ACS Paragon Plus Environment


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observed in the EIV group. Calcium/calmodulin-dependent protein kinase II alpha (α-CaMKII), one of the most abundant neuronal kinases, has been suggested to perform a neuroprotective role 75. Inhibition of the catalytic activity and abrogated expression of α-CaMKII have been demonstrated to result in increased neuronal damage following ischemia protein

78, 79

exocytosis

76, 77

. Interestingly, α-CaMKII is an autophosphorylated

. Its phosphorylated form binds with syntaxin 1A to recruit other proteins and regulate

78, 79

. Inhibition of the complex formation may lead to exocytosis frequency decrease and

delayed recycle of synaptic vesicles

78, 79

. The simultaneous downregulation of α-CaMKII and syntaxin

1A further suggested the decreased synaptic activities, echoing to elevated neurological deficit observed in the EIV monkeys.

In the LIV group, we observed a number of proteins associated with various processes related to the development of neurons (Table 2), including the upregulated expression of fatty acid binding protein 7 (FABP7), gelsolin, lamin B1, and profilin 1. FABP7 belongs to a family of intracellular lipid binding proteins that mediates the trafficking and physiological functions of long-chain polyunsaturated fatty acids, which are essential for brain development and are vital neural cell structural components 80. The temporal pattern of Fabp7 mRNA expression parallels neurogenesis; it is found primarily in radial glial cells, which serve as a pool of progenitor cells capable of differentiating into neurons and also acting as scaffolds for neuronal migration in the cerebral cortex

80-82

. Lamin B1 is one of the nuclear laminal

structural components, an intermediate filament meshwork residing beneath the inner nuclear membrane 83

. Lamin B1 has been implicated in neurogenesis and has an essential role in neuronal migration

84, 85

is highly expressed in immature neurons that participate in radial migration to the cerebral cortex

. It

86, 87

.

Mice lacking lamin B1 exhibit neurodevelopmental defect features, such as a very small cortex with low neuron density

85

. Gelsolin participates in neuronal cell motility by regulating the actin cytoskeleton

dynamics through the severing and capping of actin filaments 88. Several studies have demonstrated a role for gelsolin in the neurite outgrowth regulation, particularly growth cone formation and retraction Page 20 of 47 ACS Paragon Plus Environment

89-91

.

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Neuronal growth cones extend dynamic protrusions (filopodia, lamellipodia) as exploratory probes that signal the direction of neurite growth 90. Formation of these structures is dependent on remodeling of the actin cytoskeleton at the outgrowth leading edge

88

. Profilin 1 is also involved in regulating the actin

cytoskeleton by binding monomeric actin, and participates in neuronal cell motility and neuritogenesis 92, 93

; it is expressed in the dendritic synapses of cortical neurons and has been suggested to play a role in

activity-dependent remodeling of synaptic structures

94, 95

. Together, the observation of these upregulated

proteins suggests that the processes associated with the development of neurons and synapses were increased, consistent with the phenotype observed in the LIV group. Inflammation For the EIV group, several regulated proteins were associated with various aspects with the inflammatory process (Table 1). Peroxiredoxin, an antioxidant enzyme, was overexpressed in this group. Although this protein serves a neuroprotective function within cells by catalyzing ROS 96, its extracellular release can induce the expression of inflammatory cytokines in macrophages to further facilitate the inflammatory response through activation of Toll-like receptor 2 (TLR2) and TLR4 97. The presence of inflammatory cells (e.g., macrophages) has been observed in the chronic phase, with macrophage infiltration present weeks after the stroke episode in histological assessment of autopsied human brains 29. This observation would suggest that the upregulation of peroxiredoxin is associated with a more prominent inflammatory response, leading to a greater extent of inflammation and associated tissue damage, as observed in the EIV group. Some of the other upregulated proteins with anti-inflammatory functions are consistent with the self-limiting properties in the post-ischemic neuroinflammation

98

. Unlike systemic inflammation,

which diminishes due mainly to the exhaustion of inflammatory mediators, the resolution of inflammation in the brain is an active suppression process involving regulated mechanisms 98. Therefore, the presence of these regulated anti-inflammatory proteins would also suggest that the EIV group was still undergoing post-ischemic neuroinflammation to some extent. Annexin A5 was one of the upregulated antiinflammatory proteins; it exerts its effects by inhibiting phospholipase A2 activity and by binding Page 21 of 47 ACS Paragon Plus Environment


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phosphatidylserine exposed on the outer leaflet of the plasma membrane of cells 99. In a rat spinal cord injury model, where inflammation is an important secondary injury process in a manner similar to that in ischemic stroke, annexin V was upregulated up to 56 days after the injury

100

. While this protein is a

commonly used inflammatory marker in the acute phase 99, 101, its overexpression in the EIV group would suggest that some residual level of chronic inflammation remained. Alpha-2-macroglobulin (α2M) is a broad spectrum proteinase inhibitor that inhibits excess proteinases (e.g., matrix metalloproteinases, elastase) during tissue injury

4, 102

. As part of an inflammatory protein clearance system, α2M is a major

contributor to the protection of tissues from uncontrolled damage stemming from inflammatory processes 102, 103

. α2M is expressed in situations of chronic inflammation (e.g., in Alzheimer’s disease) 104. Alpha-1-

antitrypsin is a serine proteinase inhibitor with elastase as one of its major substrates

105

. Elastase

functions in a pro-inflammatory role by degrading the basal lamina and extracellular matrix proteins, and through the recruitment of leukocytes during neuroinflammation 4. As a part of the intrinsic antiinflammatory mechanism, alpha-1-antitrypsin is expressed in chronic inflammatory conditions (e.g., in Alzheimer’s disease)

106, 107

. In addition, therapeutic intervention using alpha-1-antitrypsin protected

against brain tissue injury and improved the stroke outcome in a t-MCAO rat model, further confirming its anti-inflammatory role redox-inert form

109

108

. Transferrin, an iron-binding protein that maintains Fe3+ in a soluble and

, was also upregulated in the EIV group, suggesting a significant disturbance in iron

homeostasis in the EIV group. In conjunction with transferrin receptor 1, transferrin facilitates iron transport in the brain and central nervous system 109. The presence of free iron catalyzes the formation of highly reactive and toxic OH radicals, leading to oxidative stress and subsequent neuronal damage and cell death

110

. Transferrin upregulation can resolve the iron overload in response to iron-mediated

oxidative stress resulting from brain injury stroke

112

111

and aberrant iron homeostasis in the chronic phase of

. Interestingly, α2M and alpha-1-antitrypsin attenuate the affinity of the transferrin receptor for

transferrin and block internationalization of the complex

113

. The observed upregulation of these three


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proteins suggests coordinated expression in response to the inflammatory processes occurring in the EIV group. For the LIV group, two of the dysregulated proteins—monoamine oxidase B (MAOB) and giant phosphoprotein AHNAK—are associated with inflammatory processes and are expressed in reactive astrocytes (Table 2). MAOB is upregulated predominantly in reactive astrocytes

114

and activated in

neuroinflammatory processes 115. MAOB metabolizes catecholamines, monoamine neurotransmitters that mediate the production of pro-inflammatory cytokines under stress conditions

114, 116

. While the targeted

inhibition of MAOB has been used as a therapeutic strategy in neurodegenerative diseases (e.g., Parkinson’s disease)

114

, evidence suggests that the role of MAOB may be different for acute brain

injuries (e.g., stroke). Deletion of the MAOB gene was nonprotective—in fact, detrimental—in a mouse MCAO model

117

; additional evidence has been obtained using a cryolesion induced model of brain

injury. While reactive astrocytosis has been observed along with a prominent increase in MAOB expression, its selective inhibition had no effect on the expression of cell death and inflammation-related genes, nor did it improve the motor impairment of cryolesioned mice 118. The observation of upregulated MAOB in the LIV group suggests a neuroprotective role. The giant phosphoprotein AHNAK is expressed in several cell types, including reactive astrocytes, and implicated in a variety of cellular processes 119, 120. Most notably, AHNAK plays a functional role in the formation of the blood-brain barrier (BBB) and in membrane repair

121, 122

. Consistent with its prescribed functions, AHNAK is persistently upregulated

after CNS injury 123. Reactive astrocytes participate in many aspects of the inflammatory response to brain tissue trauma. First, they secrete chondroitin sulfate proteoglycans in the lesion area, creating a diffusion barrier that restricts the movement of potentially neurotoxic molecules into the neighboring healthy cells

124

. A structural

barrier through the formation of a glia scar restricts and regulates the entry of inflammatory cells to the site of injury 62. In addition, astrocytes secrete anti-inflammatory factors that inhibit leukocyte infiltration and promote endothelial BBB repair

124

. The gene expression of a number of neurotrophic factors Page 23 of 47

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associated with promoting synaptogenesis has also been upregulated in reactive astrocytes in a t-MCAO mouse model

120

. Thus, the presence of reactive astrocytes in the LIV group, as indicated by the

upregulation of MAOB and AHNAK proteins, minimized the extent of t-MCAO surgery-induced inflammation. Connections between inflammation and neurogenesis as revealed by protein interaction networks of the dysregulated proteins Because neurogenesis and inflammation featured prominently in the associated functions of the observed dysregulated proteins, we speculated that there could be a connection between these two processes during the chronic phase of stroke. Such a relationship would be consistent with the growing body of evidence indicating the presence of active neuro-immune cross-talk in CNS diseases (e.g., stroke), with a crucial role in the cellular responses after brain injury

4, 125

. To further explore the interplay between these two

processes at the molecular level, we used protein-protein interaction networks to examine the interactions between the dysregulated neurogenesis- and inflammation-related proteins. The dysregulated proteins corresponding to each process were used as seed proteins to construct the initial networks (Figure S-6). Connections between these two networks were then established using the IPA knowledge database, revealing 57 interactions—46 of them involving the dysregulated proteins (Figure 4). Sixteen of these connections were direct interactions between the dysregulated proteins, with six and seven interactions connecting the dysregulated proteins of the LIV and EIV groups, respectively. There were also three interactions connecting the dysregulated proteins of the LIV group with those of the EIV group. With a significant number of connections identified between the two protein-protein interaction networks, a complex interplay appears to exist between neurogenesis and inflammation in our M. fascicularis tMCAO surgery-induced stroke model. 14-3-3ζ is a member of an adaptor protein family that comprises approximately 1% of the total soluble brain proteins

126

. Several interactions involving 14-3-3ζ (YWHAZ) and dysregulated proteins from the

inflammation network with a multitude of binding partners (Figure 4) are implicated in a wide range of Page 24 of 47 ACS Paragon Plus Environment

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neurological disorders to modulate a variety of neuronal cellular functions

126-128

. Regulation of target

protein subcellular localizations by 14-3-3 proteins is an important aspect of the various underlying molecular mechanisms associated with neuropathogenesis

128

, specifically in neurogenesis and neuronal

differentiation 129 during neuronal development and high-order brain function 130. Another observed 14-33ζ interaction involved lactate dehydrogenase (LDH), an enzyme that converts pyruvate to lactate and is best known for its involvement in anaerobic glycolysis

131

. Although lactate is mainly used as a

supplementary energy source, it has been suggested recently that it can function as a intercellular signaling molecule in the brain 131. It is possible that binding of 14-3-3ζ with LDH targets the enzyme to certain subcellular locations and modulates the ability of LDH to activate downstream signaling pathways 131

. Both proteins were downregulated in the EIV sample group, suggesting 14-3-3ζ–dependent lactate-

mediated signaling under conditions of chronic stroke (Figure 4). 14-3-3ζ also interacted with proteins associated with the cytoskeleton such as filamin A (FLNA) and tubulin β-2A (TUBB2A), which is involved in actin filament assembly and a microtubule structural component, respectively (Figure 4). 143-3 proteins have been shown to interact with a number of proteins involved in various aspects of cytoskeletal structure, regulation and connected signaling pathways 132, 133. In addition to the regulation of the individual filaments types, actin–microtubule crosstalk is essential for orchestration and maintenance of the complex neuronal cytoskeletal architecture

134

; it is plausible that 14-3-3 proteins play an

indispensable role in this intricate and coordinated process. In the disease state of stroke, this dynamic could have been perturbed and reflected in the dysregulation of 14-3-3ζ, filamin A, and tubulin β-2A expressions in the EIV sample group. Of the interactions observed, the connection between gelsolin (GSN) and calponin-3 (CNN3) is particularly interesting (Figure 4). Calponin-3, an actin filament– associated protein, is expressed in neurons; it interacts directly with gelsolin and affects its actinnucleating activity

135, 136

. The function of calponin-3 is modulated by ROCK (Rho-associated protein

kinase) phosphorylation and inflammation-dependent RhoA signaling mediated actin cytoskeletal restructuring in neurons

137, 138

. Calponin-3 has also been linked to actin stress fiber formation during



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wound healing after tissue injury 138. This observation suggests that actin cytoskeletal remodeling plays a role in both processes and, depending on the extent and type of its involvement, could contribute to either neuronal growth and survival or death. CONCLUSIONS In summary, we have performed a proteomic analysis of the M. fascicularis cerebral cortex proteome, a well-established non-human primate model for the study of ischemic stroke. To examine the proteomics changes that occurred within the chronic phase of stroke, we conducted a quantitative analysis on the EIV and LIV sample groups observed 28 days after t-MCAO surgery. A number of the observed dysregulated proteins were involved in tissue injury-related cellular processes. Our analysis also provided evidence for significant interactions of proteins involved in neurogenesis and inflammation, two key processes involved during the chronic phase of stroke, substantiating the current notion of potential cross-talk between these two processes. A better understanding of all the cellular mechanisms involved in the pathophysiology of stroke in the chronic phase, both detrimental and beneficial, should facilitate new therapeutic strategies for combating this complex and debilitating cerebrovascular disease.

ASSOCIATED CONTENT Supporting Information The Supporting Information is available free of charge on the ACS Publications website at DOI: [for JPR editors: please insert DOI here] Supporting Information. This document includes Supplementary Information 3 to 5, Figure S-1 to S-7, and Table S-1 to S-5, S-8, S-9 and S-11 mentioned in the manuscript. Supplementary information 1. Permission documents for the monkey experiments.


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Supplementary information 2. Magnetic resonance imaging (MRI) scans used in the infarct volume quantifications on the 7th and 28th days after the t-MCAO surgery. Table S-6 and S-7. The lists of the identified proteins, peptides determined from the qualitative and quantitative proteomics analyses of the M. fascicularis t-MCAO surgery-induced stroke model cerebral cortex. Of the quantified proteins, those considered dysregulated are highlighted in red (upregulated) or green (downregulated). Table S-10. List of proteins identified at 1% global FDR.

Acknowledgments This study was supported by grants from the Hong Kong Research Grants Council (project nos. HKU 701613P and 173306015) and the University of Hong Kong (Seed Funding Programme for Basic Research 201411159067 and 201310159043); the National Natural Science Foundation of China (NSFC 81303251); the Science and Technology Program of Guangzhou (2014J4100097) and the Fundamental Research Funds for the Central Universities (21613331). We thank Dr. Sam G. Li for his assistance in the preparation of the monkey samples and many helpful discussions.



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Table 1. Dysregulated M. fascicularis cerebral cortex tissue proteins identified using iTRAQ proteomics from the EIV sample group. The 31 dysregulated proteins are annotated and classified based on the relevant tissue injury-related cellular processes being examined. Neurogenesis and Synaptogenesis #

GI number

Protein name

Directionality

gi|544463659

Neurofilament, heavy polypeptide

↑

gi|544521119

Proprotein convertase subtilisin/kexin type 1 inhibitor

↑

gi|544440335

Calcium/calmodulin-dependent protein kinase II alpha

↓

gi|544431253

Collapsin response mediator protein 1

↓

gi|544494899

Guanine deaminase

↓

gi|544435684

Glycoprotein M6A

↓

gi|544419511

Syntaxin 1A (brain)

↓

gi|544415928

Synapsin II

↓

gi|544520665

Synaptophysin

↓

GI number

Protein name

Directionality

gi|544468054

Alpha-2-macroglobulin

↑

gi|544432802

Albumin

↑

gi|544434483

Annexin A5

↑

gi|544398441

Peroxiredoxin 6

↑

gi|544449216

Serpin peptidase inhibitor, clade A (alpha-1 antiproteinase, antitrypsin), member 1

↑

gi|544411345

Transferrin

↑

gi|544430582

Tubulin, beta 2A class Iia

↓

gi|544508173

Tubulin, beta 4A class IVa

↓

Inflammation #

Not annotated or involved in more than one tissue injury process #

GI number

Protein name

Directionality

gi|544518771

Coactosin-like F-actin binding protein 1

↑

b,c

gi|544523799

Filamin A, alpha

↑

gi|544429761

Histone cluster 1, H1e

↑

gi|544430751

Histone H2A type 1

↑ a,b,c

gi|544462096

Myosin, heavy chain 9, non-muscle

↑

gi|544515800

Myosin, heavy chain 11, smooth muscle

↑

gi|544512952

Myosin, heavy chain 14, non-muscle

↑ a,b

gi|544424506

Superoxide dismutase 2, mitochondrial

↑

gi|544490022

Transgelin

↑


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gi|544401330

Transgelin 2

↑

gi|544516010

Crystallin, mu

↓

gi|544422137

Lactate dehydrogenase B

gi|544522169

Proteolipid protein 1

gi|544453627

14-3-3 protein zeta/delta

#

↓

a,b

↓ a,c

↓

Inclusion in this list required >66% of the iTRAQ protein ratios of the elevated infarct group to display a

consistent trend of above or below the prescribed cutoff values and be statistically significant (p < 0.05). The overall upregulation was indicated by the symbol (↑) and labelled in red; the overall downregulation was indicated by the symbol (↓) and labelled in green.

a

Proteins involved in neurogenesis and

synaptogenesis; b Proteins involved in inflammation; c Proteins involved in angiogenesis. The down- and upregulation observed in CaMKII and annexin V (highlighted in yellow) were validated with Western blot analysis.



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Table 2. Dysregulated M. fascicularis cerebral cortex tissue proteins identified using iTRAQ proteomics from the LIV sample group. The 23 dysregulated proteins are annotated and classified based on the relevant tissue injury-related cellular processes being examined. Neurogenesis and synaptogenesis #

GI number

Protein name

Directionality

gi|544424969

Fatty acid binding protein 7, brain

↑

gi|544492533

Gelsolin

↑

gi|544438989

Lamin B1

↑

gi|544496509

Profilin 1

↑

gi|544509639

RAB3A, member RAS oncogene family

↓

gi|544486484

Solute carrier family 1 (glial high affinity glutamate transporter), member 2

↓

Inflammation #

GI number

Protein name

Directionality

gi|544485174

AHNAK nucleoprotein

↑

gi|544404300

Calponin 3, acidic

↑

gi|544520248

Monoamine oxidase B

↑

gi|544402468

S100 calcium binding protein A11

↑

gi|544403289

ATPase, Na+/K+ transporting, alpha 1 polypeptide

↓

gi|544477842

Tubulin, alpha 4a

↓

Angiogenesis #

GI number

Protein name

Directionality

gi|544483342

Ribonuclease/angiogenin inhibitor 1

↑

gi|544470700

ATP synthase, H+ transporting, mitochondrial F1 complex, beta polypeptide

↓

Not annotated or involved in more than one tissue injury process #

GI number

Protein name

Directionality

gi|544508071

Calcyphosine

↑

gi|544397528

Centrosomal protein 170kDa

↑

gi|544401268

Phosphoprotein enriched in astrocytes 15

↑

a,b

gi|544455098

Plectin

gi|544419969

Calmodulin

↑ ↓ a,b

gi|544449663

Creatine kinase, brain

↓

gi|544442918

Creatine kinase U-type, mitochondrial

↓

gi|544419424

Malate dehydrogenase 2, NAD (mitochondrial)

↓

gi|544417864

Purkinje cell protein 4

↓


Page 39 of 47

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#

Inclusion in this list required >66% of the iTRAQ protein ratios of the low infarct group to display a

consistent trend of above or below the prescribed cutoff values and be statistically significant (p < 0.05). The overall upregulation was indicated by the symbol (↑) and labelled in red; the overall downregulation was indicated by the symbol (↓) and labelled in green.

a

Proteins involved in neurogenesis and

synaptogenesis; b Proteins involved in inflammation.



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FIGURE LEGENDS Figure 1. Neurological phenotypes of the macaque stroke subjects after t-MCAO surgery. Quantified infarct volumes observed (A) 7 and (B) 28 days post-stroke in the monkeys subjected to t-MCAO surgery. Infarct volumes were quantified from MRI images, as described in the Experimental Procedures. On the left are the quantified infarct volumes of subject animals treated with EDA as a reference point for the indication of recovery. A box-and-whisker plot reveals the relative locations of the eight subject monkeys within the distribution of a cohort of 12 ischemia stroke model monkeys. The three labeled in green were considered recovered; the four in red were deemed to be under chronic stroke. The subject labeled in blue was considered to be in an intermediate state. Representative MRI images from subjects with low (C) and elevated (D) infarct volumes. The red circle denotes the infarction area. Representative immunohistochemical staining revealing the expression of NeuN within the cerebral cortex tissue of subjects in the contralateral (E) to the surgery side, and the ipsilateral tissues for the monkeys with low (F) and elevated (G) infarct volumes (400x). Representative immunohistochemical staining revealing the expression of GFAP within the cerebral cortex tissue of subjects in the contralateral (H) to the surgery side, and the ipsilateral tissues for the monkeys with low (I) and elevated (J) infarct volumes (200x). Figure 2. Summary of the M. fascicularis cerebral cortex tissue proteome. (A) Using the combined sample preparation strategy in conjunction with multiple MDLC–MS/MS platforms, in-depth proteomic analyses provided 1 733 964 PSMs using a

Characterization of the Molecular Mechanisms Underlying the Chronic

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