Alterations of human plasma proteome profile on adaptation to high

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Alterations of human plasma proteome profile on adaptation to high-altitude hypobaric hypoxia Xi Du, Rong Zhang, Shengliang Ye, Fengjuan Liu, Peng Jiang, Xiaochuan Yu, Jin Xu, Li Ma, Haijun Cao, Yuanzhen Shen, Fangzhao Lin, Zongkui Wang, and Changqing Li J. Proteome Res., Just Accepted Manuscript • Publication Date (Web): 25 Mar 2019 Downloaded from http://pubs.acs.org on March 26, 2019

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Journal of Proteome Research

Alterations of human plasma proteome profile on adaptation to high-altitude hypobaric hypoxia Xi Du1,†, Rong Zhang1,†, Shengliang Ye1, Fengjuan Liu1, Peng Jiang1, Xiaochuan Yu2, Jin Xu3, Li Ma1, Haijun Cao1, Yuanzhen Shen2, Fangzhao Lin1, Zongkui Wang1,4,*, Changqing Li1,4,* 1 Institute

of Blood Transfusion, Chinese Academy of Medical Sciences & Peking Union

Medical College, Chengdu, China, 610052; 2 Department

of Transfusion, Aba Prefecture People’s Hospital, Ngawa Tibetan and Qiang

Autonomous Prefecture, China, 510530; 3 Department 4 Sichuan

of Chemistry, University of Massachusetts Lowell, Massachusetts 01854, USA

Blood Safety and Blood Substitute International Science and Technology Cooperation

Base, Chengdu, China, 610052; † These authors have contributed equally to this work. * To whom correspondence should be addressed: [email protected]; [email protected]

ACS Paragon Plus Environment

Journal of Proteome Research 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ABSTRACT For individuals migrating to or residing permanently at high-altitude regions, environmental hypobaric hypoxia is a primary challenge which induces several physiological or pathological responses. It is well documented that human beings adapt to hypobaric hypoxia via some protective mechanisms, such as erythropoiesis and overproduction of hemoglobin, however little is known on the alterations of plasma proteome profiles in accommodation to high-altitude hypobaric hypoxia. In the present study, we investigated differential plasma proteomes of high altitude natives and lowland normal controls by a TMT-based proteomic approach. A total of 818 proteins were identified, of which 137 were differentially altered. Bioinformatics (including GO, KEGG, protein-protein interactions, etc.) analysis showed the differentially altered proteins were basically involved in complement and coagulation cascades, anti-oxidative stress and glycolysis. Validation results demonstrated that CCL18, C9, PF4, MPO and S100A9 were notably up-regulated, and HRG and F11 were down-regulated in high altitude natives, which were consistent with TMT-based proteomic results. Our findings highlight the contributions of complement and coagulation cascades, anti-oxidative stress and glycolysis in acclimatization to hypobaric hypoxia and provide a foundation for developing potential diagnostic or/and therapeutic biomarkers for high altitude hypobaric hypoxia-induced diseases. Keywords: proteomics; high altitude; hypobaric hypoxia; complement and coagulation cascades; antioxidant; glycolysis.


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INTRODUCTION Atmospheric pressure and partial oxygen pressure decrease (i.e., hypobaric hypoxia) at high altitude regions (> 2500 m), thus leading to decreased oxygen supply. Human beings at high altitude must adapt to the stress of decresed oxygen availability. Physiological responses to hypobaric hypoxia have been studied for many years and it is well documented that healthy subjects adopt protective mechanisms, such as overproduction of red blood cells (excessive erythropoiesis), when exposed to high altitude hypoxia (1). And this is the normal and useful physiologic response for organisms to acclimatize the high-altitude hypobaric hypoxia (2). However, inadaptation to high altitude may lead to high altitude diseases, ranging from mild mountain sickness (including nausea, dizziness, insomnia, palpitation, short breath, etc.) to the severe and life-threatening forms (eg., high altitude pulmonary edema (HAPE), high altitude polycythemia (HAPC) and high altitude cerebraledem (HACE)). The Qinghai-Tibetan plateau covering a vast area of about 2.5 million square kilometers and an average altitude > 4000 m above sea level, known as the “Roof of the World” and located in the southwest of China, is the largest and highest plateau in the world (3). So far, more than 10 000 000 people are ordinarily resident at Qinghai-Tibetan Plateau. In addition, more and more lowlanders migrate to Qinghai-Tibetan Plateau for travel or work. It should be noted that the incidence of high altitude-associated severe damages (HAPE, HAPC, HACE, etc.) is higher in migrants from low altitude regions than in the Qinghai-Tibetan plateau natives(4). The physiological or pathological responses to hypobaric hypoxia are complex and have widely studied by using genome or transcriptome techniques. Although genome and transcriptome analyses are useful to disclose the mechanism of hypobaric hypoxia stimulation, yet only examining the changes of DNA or RNA does not give an integrated view as proteome



may not be totally accurately predicted by transcriptome profiles due to several factors, such as transcript stability, post-translational modifications and protein degradation (5). Furthermore, proteins, not genes, are key to biological function context. Thus, changes in specific protein expression levels or protein species are excellent indicators involved in response to high-altitude hypobaric hypoxia. To date, numerous studies have been performed focusing on the effects of hypobaric hypoxia on the expression or posttranslational modification of a single protein or a functional family. We also found several coagulation-related proteins, such as coagulation factor (F) 2, F5, F8, F9 and F11, significantly decreased in high altitude natives than in lowlanders (6). In addition, a few reports have investigated proteome-wide alterations under hypobaric hypoxia conditions, with most focusing on cell lines (7, 8) or animal models (9, 10). Several years ago, Ahmad et al.(11) discovered 35 dysregulated protein between the plasma proteome profiles of high altitude and normal altitude cohorts by 2DE-MS proteomics technique. For most of high altitude-associated sickness, there are not yet efficacious therapeutic treatments. For example, the Chinese traditional ways to treat HAPC are to transfer the patients to lower altitude regions or phlebotomy therapy. Nevertheless, these treatments are not able to achieve complete molecular remission. In our previous TMT-based proteomics study, we found that C4A, C6, MASP1, CNDP1 and CALR could serve as candidate blood plasma biomarkers of HAPC (12). Zhao et al.(13) also demonstrated that the differentially changed proteins in relation to inflammation (e.g., CRP and SAA) were involved in HAPC. Therefore, it is important and necessary to develop novel physiopathogenic candidates to reveal the underlying pathogenesis and to improve treatments for high-altitude hypobaric hypoxia-associated sicknesses.


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This research was to study alterations in the plasma proteomics profiles of high altitude (Qinghai-Tibetan plateau, > 3600 m) natives and low altitude (Chengdu, ~400m) healthy controls by using tandem mass tags (TMT)-based quantitative proteomics analysis. We identified 818 proteins, of which 137 proteins were differentially changed. Bioinformatics analysis displayed the differentially expressed proteins (DEPs) primarily participated in complement and coagulation cascades, anti-oxidative stress, metabolism, and tight junction. Our results shed light on the proteomics profiles of high altitude natives to develop candidate diagnostic or/and therapeutic biomarkers and to reveal potential mechanisms of adaptation to high-altitude hypobaric hypoxia. MATERIALS AND METHODS Participants and Blood Collection Ethics approval was provided by the Ethics Committee of the Institute of Blood Transfusion, CAMS&PUMC (Code: 201809). In accordance with the Helsinki Declaration, informed consent was obtained from the individual participants or their closest relatives. Forty-three healthy high altitude natives (HA) and 49 healthy low altitude controls (LA) were recruited in this study. TMT-based proteomic analysis was performed on blood plasma samples of HA (n = 6; male, 50.4±17.5 years) compared with ABO type-, age- and gender-matched LA (n = 6). It should be noted that the HA group (n=6) for TMT-based proteomics is the control group which was selected in our previous proteomic study on HAPC(12). And the rest specimens (37 HA and 43 LA) were served as a validation set (Table 1). As we previously reported(12), the HA natives with no visits to LA regions in at least 3 years prior to this study, were recruited from Ngawa Tibetan and Qiang Autonomous Prefecture (36004800 m). The lowland controls were enrolled from Chengdu (~400 m) with no visits to high



altitude areas in at least 3 years prior to this study. Individuals who had history of thrombus or hemorrhage, usage of oral anticoagulation therapy, HBV/HCV/HIV infection, Acute infection, pregnancy, diabetes, cardiopathy, hepatic disease, renal insufficiency and others were excluded from the present study by standardized questionnaire as we previously described (6, 12). According to our previous study (6, 12, 14, 15), two tubes of blood sample of each subject (5mL) were collected by venepuncture. One tube of blood sample was immediately for routine tests of ABO types, red blood cell count (RBC), hematocrit (Hct), hemoglobin (Hb) and platelet count (PLT). Simultaneously, another tube of blood sample was centrifuged at 4,000 g for 20 min (4°C) to collect plasma which was immediately stored at -70°C in 500μL aliquots. Sample Preparation, TMT-labeling and LC-MS/MS The basic coagulation tests of the plasma specimens, including activated partial thromboplastin time (aPTT), prothrombin time (PT), thrombin time (TT) and fibrinogen (Fbg) were tested by clotting assay on a CA-1500 automated coagulation analyzer (Sysmex Corporation, Kobe, Japan) as we previously studied(6, 14). The flow diagram of the study is shown in Supplementary Figure S1. For TMT-based proteomic analysis, six high altitude male subjects of the 43 recruited HA individuals were randomly selected and six ABO type-, age-, and gender-matched LA controls were paired. Pooled plasma samples were obtained by mixing equal volumes of the two individual plasma samples from each group (i.e., three biological repetitions) (12). To facilitate the identification of lower-abundance proteins, the high-abundance proteins were reduced using a ProteoMiner™ Protein Enrichment Introductory Large-Capacity Kit (Bio-Rad, Richmond, USA) after pooling the samples.


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Protein concentrations of the low abundance protein enrichment plasma samples were assayed by a BCA protein assay kit (Pierce, Rockford, IL, USA), and were verified the consistency of each group by SDS-PAGE. Protein digestion and TMT-labelling were performed according to the Thermo Fisher protocol for TMT as we previously described(12, 15). Briefly, samples were reduced, alkylated, and diluted according to the protocol. Finally, approximately 100 µg proteins per sample were digested by a procedure of two-step tryptic digestion overnight with a trypsin/protein mass ratio of 1:50 for the first digestion overnight and 1:100 for a second 4 h-digestion. Then, the digested samples were labeled with the TMT label reagents according to the directions of TMT labeling kit (Thermo Fisher Scientific, Torrance, CA, USA). Samples were labeled as follows: A1: 126, A2: 127, A3: 128, B1: 129, B2: 130, and B3: 131. The labeled samples were subsequently fractionated into 60 fractions by high pH reverse-phase high-performance liquid chromatography (HPLC). According to the method of Udeshi et al. (16), the 60 fractions were combined into 18 fractions, and then vacuum-dried . The dried samples were subsequently reconstituted and tested by LC-MS/MS, and the detailed procedures of the LC-MS/MS methodology can be found in our previous studies(12, 15). MS/MS Data Analysis and Bioinformatics Analysis The raw MS/MS data were searched against human UniProt database (http://www.uniprot.org) by using MaxQuant search engine (v.1.5.2.8) with a false discovery rate (FDR)< 1% at protein, peptide and PSM levels and minimum score for peptides > 40. The peptide mass tolerance for precursors was set as 20 ppm in First search and 5 ppm in Main search, and 0.02 Da was for fragment ions. The requirements of all identified proteins were having ≥ 2 peptides with ≥ 1 unique peptide, and only the proteins at p ±1.2 and a p value of < 0.05 was regarded as a DEP. DEPs were analyzed according to GO terms for biological process, cellular component and molecular function using the UniProt-GOA database (http://www.ebi.ac.uk/GOA/). Domain functional descriptions of the DEPs were predicted by using InterProScan soft (http://www.ebi.ac.uk/interpro/). Pathway enrichment analysis was assessed using KEGG pathway database (http://www.genome.jp/kegg/ or http://www.kegg.jp/). And protein-protein interaction (PPI) networks were identified and visualized by STRING database (http://stringdb.org) and Cytoscape software (version 3.6.0), respectively. Validation of Proteomics Results Thirty-seven HA and 43 LA provided blood samples for verification. Plasma levels of CCL18, C9, PF4, IGFBP2, MPO and S100A9 were assessed using Human Magnetic Luminex® Screening Assay (6-plex; LXSAHM-06, R&D Systems, Inc., Minneapolis, USA), according to the manufacturer’s protocols. Plasma levels of HRG and HYOU1were assayed using ELISA kits (R&D Systems, Inc. and Elabscience Biotechnology Co.,Ltd.,Wuhan, China, respectively), and F11 activity was measured by one-stage clotting assay (Siemens Healthcare, Marburg, Germany) on a CA-1500 automated coagulation analyzer. Statistical Analysis Protein quantitation was calculated as the median ratio of corresponding unique or razor peptides for a given protein. For example, the ratio of groups HA/LA was calculated by mean value of the three replicate quantitative values of group HA to mean value of the three replicate quantitative values of group LA. The comparisons of expression of proteins were performed by two-tailed t-tests. For histogram, volcano plots and clustering analysis, proteomics data are log-


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transformed and normalized when appropriate. For enrichment analysis, Fisher’s exact test was applied. For comparison of participant characteristics (age, gender, RBC, Hct, etc.), unpaired two-tailed Student’s t test was used. In the validation set, unpaired student’s t test was used to compare groups HA and LA. P < 0.05 was considered statistically significant. RESULTS Demographic Characteristics of Participants Demographic characteristics of HA group and LA group are displayed in Table 1. Both groups were similar in age (p=0.176) and gender ratio (p=0.057). RBC, Hb, Hct and aPTT were obviously higher in highlanders than in LA controls, whereas PLT of high-altitude natives was slightly lower than that of LA controls. Furthermore, there is no difference in PT, TT and Fbg between groups HA and LA groups. Table 1. Demographic characteristics of participants HA

LA

p-values

50.36±17.07

48.71±16.69

0.176

(15-79)

(19-72)

Male, n (%)

31 (72.09%)

31(63.27%)

0.057

Living altitude (m)

3600‑4800 m

500 m

/

5.33±0.34

4.59±0.41

Alterations of human plasma proteome profile on adaptation to high

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