Advances in Bioscience and Biotechnology, 2013, 4, 75-88 ABB http://dx.doi.org/10.4236/abb.2013.410A3009 Published Online October 2013 (http://www.scirp.org/journal/abb/) Genetic analysis of the human hair roots as a tool for spaceflight experiments* Masahiro Terada1#, Masaya Seki2, Akira Higashibata1, Shin Yamada1, Rika Takahashi2, Hideyuki J. Majima3, Takashi Yamazaki1, Tomomi Watanabe-Asaka1, Maki Niihori1, Chiaki Mukai1, Noriaki Ishioka1 1Japan Aerospace Exploration Agency, Tsukuba City, Japan 2Advanced Engineering Services Co., Ltd., Tsukuba City, Japan 3Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima City, Japan Email: #terada.masahiro@jaxa.jp Received 5 August 2013; revised 5 September 2013; accepted 5 October 2013 Copyright © 2013 Masahiro Terada et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ABSTRACT The use of hair roots as experimental samples has been a research focus for understanding the effects of spaceflight on astronauts, because it has many advan- tages, one of which is the fact that hair matrix cells actively divide in a hair follicle and sensitively reflect the physical conditions of the human body. In 2009, a research program focusing on the analysis of astro- nauts’ hairs was initiated to examine the effects of long-term spaceflight on the gene expression and mi- neral metabolism in the human body. Since the num- ber of samples per astronaut is limited to 5 strands of hairs at each sampling point, due to the ethical view- point of astronauts or limited resources in space, it is important to develop an effective method for the mo- lecular analysis of small amounts of hair roots. In this study, mRNA successfully extracted from 1, 5, and 10 hair follicles was amplified and subjected to the DNA microarray analysis to compare the gene expression within subjects. The results indicated that (1) it was possible to perform the genetic analysis on hair sam- ples stored at −80˚C, even without a fixation buffer and (2) the newly modified method of mRNA extrac- tion and analysis was effective in detecting differen- tial gene expression in samples containing only 5 hairs. In conclusion, RNA was efficiently extracted from 5 hair roots, which is the same number of hair roots us- ed in the space experiment; therefore, this method can be applied to genetically analyze astronauts’ hair amples. s Keywords: Hair Root; Microarray; Space; Astronaut; RNA; Gene Expression 1. INTRODUCTION Examination of the human hair serves as an effective tool for determining stress levels and metabolic conditions in the human body in response to the microgravity envi- ronment and cosmic radiation. In December 2009, the Ja- pan Aerospace Exploration Agency (JAXA) initiated the “HAIR” research program to analyze the properties of and changes in astronauts’ hair during spaceflight [1], the purpose of which is to elucidate the effects of long-term exposure to spaceflight on the gene expression and min- eral metabolism in human hair. In the frame of the “HAIR” experiment, 10 astronauts from the International Space Station (ISS) crews will be subjected to hair sam- pling and analysis. Such an experiment will be the first to examine the fine clear effect of long-term exposure to spaceflight on exodermal tissues. Hair matrix cells actively divide in a hair follicle [2,3] and are known to sensitively reflect the host’s physical conditions [4-6]. Akashi et al. [2010] reported that the circadian phase of clock gene expression in hair follicle cells corresponds to that of individual behavioral rhy- thms and therefore is effective for evaluating the proper- ties of the human peripheral circadian clock. In addition, the hair shaft has also been shown to record the metabo- lic changes in the organism in response to changing envi- ronments [7,8]. For example, high levels of toxic metals, such as mercury, cadmium, arsenic, and lead, have been observed in the hair of people exposed to toxic metal pollution [9]. The hair mineral analysis has also been widely used for forensic science, the assessment of envi- *Conflict of interest: The authors declare that there is no conflict o interest. #Corresponding author. OPEN ACCESS
M. Terada et al. / Advances in Bioscience and Biotechnology 4 (2013) 75-88 76 ronmental exposure [10-13], the evaluation of nutritional statuses, and disease diagnosis [14,15]. It was previously reported that 14 days of hindlimb suspension (a simula- ted microgravity model of skeletal muscle) led to chang- es in the levels of 26 minerals in rat body hair [1], sup- porting that hair samples would be an informative tool for examining the effect of spaceflight on humans, espe- cially taking into account that no special complex hard- ware and handling are required for hair collection. In the frame of the “HAIR” experiment, both hair roots and hair shafts collected from the ISS crews are subjected to the analysis. It is known that the expression of immunoglobulin heavy-chain mRNA in the amphibian Pleurodeles waltl changes during spaceflight [16]. Space- flight has also been shown to cause gene expression changes in rat and mouse skeletal muscles [17-19]. In addition, studies have suggested that spaceflight affects the organization of microtubules and mitochondria, there- by resulting in increased apoptosis [20]. Therefore, along with the analysis of hair roots, nucleic acids (RNA and mitochondrial DNA) will be extracted from the collected hair roots and subjected to the analysis of gene expres- sion changes during spaceflight. The extracted total RNA will be analyzed by the DNA microarray technique, and the effects of spaceflight on the expression levels of stress- related genes, such as oxidative stress gene networks, will be further examined. In addition, the multiple effects of microgravity and cosmic radiation on the copy num- ber of mitochondrial DNA will also be investigated. Moreover, immune system-related genes will be ana- lyzed using a human immunological cDNA chip. Fur- thermore, to examine trace element metabolism in the human body, the contents of minerals (e.g., Na, K, and Ca) and trace elements (e.g., mercury) in the hair shaft of ISS crews will be analyzed using an electron probe mi- croanalyzer. However, in the “HAIR” experiment, the number of hair samples is limited to only 5 strands from each as- tronaut, due to the ethical viewpoint of astronauts or lim- ited resources in space. Therefore, it is essential to deve- lop a method to effectively analyze the gene expression with a limited number of hair roots. To achieve this pur- pose, in the current study, the microarray analysis was performed using RNA extracted from 1, 5, or 10 hair roots. 2. MATERIALS AND METHODS 2.1. Hair Sample Preparation One, 5, and 10 strands of hair were taken several times from each of 2 healthy voluntary male subjects (age, 33 - 36 years). Individual hairs were grasped as near to the scalp as possible and pulled out by pulling several times with tweezers in the direction of hair growth without da- maging hair roots. Samples were stored at −80˚C until analysis. Similar biological conditions for material stor- age will be employed for the HAIR experiment during spaceflight. This study was approved by the Committee on Human Care and Use at the JAXA Institutional Re- view Board. All the participants provided written inform- ed consent. 2.2. RNA Extraction Hair roots (approximately 2 - 3 mm) were used as the sources for mRNA extraction and were cut into about 15 fragments (0.1 - 0.2 mm each) using a microsurgical knife under a stereoscopic microscope. Collected frag- ments were immersed in 800 μl of ISOGEN Reagent (Nippon Gene, Toyama, Japan) in tubes and stirred (15 s × 2 times) using the sonication device, Bioruptor UCD- 250 (Cosmo Bio, Tokyo, Japan). Next, RNA was purified from hair lysates with the ISOGEN Kit as described pre- viously [21]. Briefly, tubes were kept at room tempera- ture for 5 min, followed by addition of 200 μl of chloro- form. Subsequent processes of RNA purification were performed according to the manufacturer’s instructions. After isolation, RNA pellets were washed with 70% etha- nol, air dried, and resuspended in 10 μl of RNA-free wa- ter (Gibco-BRL, Gaithersburg, MD). Total RNA was quantified at 260 nm using the NanoDrop ND-1000 spec- trophotometer (NanoDrop Technologies Inc., Wilming- ton, DE). The RNA quality was determined using the Agilent Bioanalyzer 2100 (Agilent Technologies, Palo Alto, CA). The 28S:18S rRNA ratio and the RNA integ- rity number (RIN) were calculated with the 2100 Expert software and the RIN Beta Version software (Agilent Te- chnologies), respectively. RIN was calculated by allow- ing the classification of total RNA, based on a number- ing system from 1 (most degraded) to 10 (most intact) [22,23]. 2.3. RNA Amplification Due to the small amount of RNA extracted from hair samples, a double RNA amplification step was incorpo- rated prior to microarray hybridization. Total RNA was amplified using the Ambion MessageAmp aRNA Kit as described previously [24]. Briefly, first- and second- strand cDNA was synthesized. Unlabeled aRNA was ge- nerated by in vitro transcription with unbiotinylated NTPs. For probe preparation, aRNA was reverse transcribed with second-round primers. The second-strand cDNA was synthesized with the T7 oligo (dT) primer and purified. Biotin-labeled cRNA was generated by in vitro transcrip- tion and then purified with the RNeasy Kit (Qiagen, Ven- lo, The Netherlands). Copyright © 2013 SciRes. OPEN ACCESS
M. Terada et al. / Advances in Bioscience and Biotechnology 4 (2013) 75-88 77 2.4. Generation and Mining of Microarray Data Amplified RNA was processed and hybridized to the Whole Human Genome (8 × 60 K) Oligo Microarray (Agilent Technologies), according to the manufacturer’s protocol. Slide scanning was performed using the Agilent DNA Microarray Scanner (Agilent Technologies) by DNA Chip Research Inc. (Yokohama, Japan). Expression profiles were collected in triplicate at each time point, and scanning data were normalized with Agilent’s Fea- ture Extraction software (Agilent Technologies). Data preprocessing and analysis were performed using the GeneSpring software 11.0.1 (Agilent Technologies). Pre- processing procedures were performed according to the manufacturer’s recommendations and the MicroArray Quality Control project reports [25]. Briefly, a decision matrix determines whether each transcript is reliably de- tected (i.e., present), marginally detected (i.e., marginal), or not detected (i.e., absent) and calculates signal intensi- ties. Normalization was carried out to the 75th percentile of each array, and each gene to the median, with Gene Spring’s normalization option. The hierarchical cluster analysis was performed using the principal component analysis (PCA), the rank correlation of log ratios, and the condition tree clustering option of GeneSpring. The pro- bability was 0.1 and was adjusted by the false-discovery rate for corrections of multiple tests. All raw fluorescen- ce intensity data and microarray image files were depos- ited within the public repository for microarray-based gene expression data, the “Gene Expression Omnibus” (GEO) (http://www.ncbi.nlm.nih.gov/geo/), complying with the minimum information requirement for microbar- ray experiments. The GEO accession number for the cur- rent experiment is GSE46809. 3. RESULTS 3.1. RNA Yield and Quality Table 1 shows the yield and quality parameters of the ex- tracted RNA. The average total yield of RNA per hair root was 317.3 ng/follicle, and the average yields of RNA from a single hair root each from 2 subjects were 286.7 ng/follicle and 409.3 ng/follicle (Table 1(a)). The average total yield of RNA from 5 strands of hair roots was 524.6 ng (128.2 ng/follicle), and the average yields of RNA from 2 subject were 882.7 ng (176.6 ng/follicle) and 273.9 ng (54.7 ng/follicle) (Table 1(b)). The average yield of 10 strands of hair roots was 418.7 ng (41.9 ng/ follicle), and the average yields of RNA from 2 subjects were 507.4 ng (50.7 ng/follicle) and 285.6 ng (28.6 ng/ follicle) (Table 1(c)). For the information, the average total yield of RNA from 3 strands of hair roots was 623.5 ng (207.8 ng/follicle), and the average yields of RNA from a single hair root each from 2 subjects were 608.2 ng (202.7 ng/follicle) and 688.7 ng (229.6 ng/follicle) (data not shown). The sample quality was determined using the Agilent Bioanalyzer 2100 by calculating the RNA integrity num- ber (RIN). However, RIN is calculated based on the bio- analyzer traces typically produced by hair follicle RNAs; therefore, when a sample had a lower 28S rRNA peak but no degradation peaks (Figure 1), the bioanalyzer could not consider the sample as a normal total RNA electropherogram trace. In consequence, RIN for most hair follicle RNA samples were not able to be calculated using default parameters (Table 1). Therefore, in addi- tion to RIN, 28S and 18S clear peaks were also used for determining the RNA quality. Based on RIN or 28S/18S ratios (2 detected peaks, Figure 1), 14 RNA samples in total were chosen for pre- amplification for microarray hybridization (6, 7, and 1 samples from 1, 5, and 10 follicles, respectively) (Tables 1 and 2). Among these 14 samples, 7 did not yield RINs, whereas others had RINs ranging from 6.1 to 7.8 (Table 1). Table 2 shows the enrichment of RNA from these samples following 2 rounds of pre-amplification prior to the microarray analysis. After the first pre-amplification performed on 100 ng of extracted RNA, the average amount of RNA was 2.56 μg (25.6 ng/μl × 100 μl), which was 25.6 fold of the starting material. The average amount of RNA after second amplification was 156.6 μg (1556 ng/μl × 100 μl), which was 78.3 fold of the amount after first amplification. Of these 14 pre-amplified samples, 13 (1 μg each) were selected for DNA microarray analysis (Table 2). 3.2. Gene Expression Affinity Analysis The RNA data from a single hair root were compared to those from 5 or 10 pieces of hair roots. Unlike the (a) (b) Figure 1. Representative electropherograms produced by the Agilent Bioanalyzer. (a) An electropherogram with RNA peaks that can be used to calculate RIN; (b) An electropherogram with RNA peaks not suitable for RIN calculation. Copyright © 2013 SciRes. OPEN ACCESS
M. Terada et al. / Advances in Bioscience and Biotechnology 4 (2013) 75-88 Copyright © 2013 SciRes. 78 OPEN ACCESS Table 1. Yield and quality of RNA samples. N.D., not detected; ○ subjected to amplification or microarray analysis. (a) Number of hair strands Subject Total RNA yield (ng)Mean yield (ng/follicle) RIN Amplification DNA microarray 2126.2 2126.2 1.5 846.2 846.2 N.D. 588.6 588.6 N.D. 37.1 37.1 N.D. 65.5 65.5 N.D. 67 67 N.D. 61.2 61.2 N.D. 80 80 6 73.7 73.7 N.D. 69.2 69.2 N.D. 711.7 711.7 N.D. 91.5 91.5 N.D. 175.8 175.8 N.D. 630.5 630.5 7.8 ○ ○ 556.9 556.9 7 ○ ○ 197.3 197.3 N.D. 270.2 270.2 N.D. ○ ○ 302.1 302.1 7.7 ○ ○ 460.2 460.2 N.D. 185 185 6.1 ○ 94.2 94.2 N.D. 365.9 365.9 6.2 93.8 93.8 N.D. 137.3 137.3 N.D. 79.4 79.4 N.D. 67 67 N.D. 122.9 122.9 N.D. 111.7 111.7 N.D. 228.8 228.8 N.D. 270.5 270.5 N.D. 124.6 124.6 N.D. 130.6 130.6 N.D. A 37.5 37.5 N.D. 277.9 277.9 N.D. 1 B 338.4 338.4 N.D.
M. Terada et al. / Advances in Bioscience and Biotechnology 4 (2013) 75-88 79 Continued 846 846 N.D. 2110.2 2110.2 6.4 54.9 54.9 N.D. 58.1 58.1 N.D. 172.5 172.5 N.D. 57.3 57.3 N.D. 69.6 69.6 N.D. 459.2 459.2 N.D. ○ ○ B 58.2 58.2 N.D. Average 317.3272727 317.3272727 S.D. 454.2560974 454.2560974 S.E. 69.27340542 69.27340542 Average for subject A 286.669697 286.669697 Average for subject B 409.3 409.3 (b) Number of hair strands Subject Total RNA yield (ng)Mean yield (ng/follicle) RIN Amplification DNA microarray 898.8 179.8 6.8 727.8 145.6 6.7 1521.5 304.3 7.1 ○ ○ 1836.8 367.4 6.6 ○ ○ 304.8 61 7.5 ○ ○ 353.6 70.7 3.1 A 535.5 107.1 7.8 ○ ○ 363.8 72.8 N.D. ○ ○ 513.5 102.7 6.1 ○ ○ 270.9 54.2 N.D. ○ ○ 230.3 46.1 N.D. 131.2 26.2 N.D. 156.4 31.3 N.D. 163.5 32.7 N.D. 459.2 91.4 N.D. 204.7 40.9 N.D. 5 B 245.7 49.1 N.D. Average 524.5882 128.1583333 S.D. 484.5583 106.9410497 S.E. 121.1396 32.24393968 Average for subject A 882.6857 176.5571429 Average for subject B 273.92 54.74 Copyright © 2013 SciRes. OPEN ACCESS
M. Terada et al. / Advances in Bioscience and Biotechnology 4 (2013) 75-88 Copyright © 2013 SciRes. 80 OPEN ACCESS (c) Number of hair strands Subject Total RNA yield (ng) Mean yield (ng/follicle)RIN Amplification DNA microarray 613.1 61.3 1.6 260.4 26 N.D. A 648.7 64.9 N.D. ○ ○ 180.4 18 N.D. 10 B 390.8 39.1 1 Average 418.68 41.86 S.D. 208.15592 20.839938 S.E. 104.07796 10.419969 Average for subject A 507.4 50.733333 Average for subject B 285.6 28.55 Table 2. RNA yield after amplification. Amplification (ng/μl) Number of hair strands Subject Extracted concentration (ng/μl) (× 10) Mean yield (ng/follicle) 1st (× 100) 2nd (× 100) DNA microarray 63.05 630.5 67.93 1933.1 ○ 55.69 556.9 113.98 1895.43 ○ 27.02 270.2 10.15 1879.84 ○ 30.21 302.1 5.55 1562.34 ○ 1 A 18.5 185 4.87 1043.56 3.048 6.096 25.03 1787.98 ○ 5.355 10.71 15.97 1354.34 ○ 15.215 30.43 19.71 1350.56 ○ 5 A 18.368 18.368 16.26 1597.09 ○ 10 A 64.87 648.7 15.83 1676.85 ○ 1 B 4.592 45.92 12.66 1118.27 ○ 3.638 7.276 17.64 1805.3 ○ 5.135 10.27 12.42 1589.98 ○ 5 B 2.709 5.418 20.27 1330.05 ○ Average 25.5907143 1566.0493 S.D. 29.6345159 288.55833 S.E. 8.21913588 80.031682 amount of RNA initially extracted from these hair roots, the amount of amplified RNA was sufficient for mi- croarray analyses. To analyze the sample-specific pat- terns in gene expression profiles, the PCA analysis, the rank correlation of log ratios, and hierarchical clusters analysis were applied. PCA was used to demonstrate the homogeneity level of the transcriptional profiles of ana- lyzed samples. In a PCA plot, samples with similar ex- pression profiles are positioned in the proximity to each other [26,27]. The position of each sample was plotted against the X-, Y-, and Z-axes in a three-dimensional (3D) space (Figure 2), in which the closer distance of the samples to each other in 3D; therefore, the homology between samples is high. As shown in Figure 2, the ex-
M. Terada et al. / Advances in Bioscience and Biotechnology 4 (2013) 75-88 81 Figure 2. Three-dimensional images of principal component analysis (PCA). The closer the distance between samples, the higher the homology is between them. pression data from RNA samples extracted from 5 folli- cles, but not a single follicle, were found to have higher levels of homogeneity. On the other hand, large variabil- ity was observed among the samples derived from 1 fol- licle. The variability among samples was also evaluated us- ing the rank correlation of log ratios. As shown in Figure 3, spots colored in red represent discrepancy in the sam- ples; in other words, the variability among samples was relatively low. These results also suggest that the smaller the number of follicles from which RNA is extracted, the larger the variability is among samples. Notably, sample- specific differences were still present even when RNA was extracted from the same number of follicles (Figure 3). To evaluate the homogeneity among multiple genes in all samples, the hierarchical analysis was performed us- ing condition tree clustering (Figure 4). The results indi- cate clear resolution between the subjects, as well as large differences between samples originating from a single follicle. As for the samples derived from 5 follicles, the level of variability was low, and therefore, the gene Copyright © 2013 SciRes. OPEN ACCESS
M. Terada et al. / Advances in Bioscience and Biotechnology 4 (2013) 75-88 82 Figure 3. Correlation plot as a comparison of rank concordance. The more red between each sample, homology between sam- ples is high. Darker shades depict lower rank correlations. Figure 4. Hierarchical cluster analysis by condition tree clu- stering. The characteristics of individual subjects were separa- ted. expression data were considered to be reproducible and significant (Figure 4). On the other hand, the samples derived from 1 follicle showed large variability, so the sample of subject A was separated as the group of subject B. 3.3. Certification of Hair Gene Expressions To confirm the integrity of RNA extracted from the hair, the expression levels of hair-specific genes in these sam- ples were analyzed. Hair root-specific genes were chosen by referencing reports by Ohyama et al. [2006] and Klo- epper et al. [2008]. In the sub-bulge region of hair roots, 22 out of 24 reported genes were expressed in the sam- ples (Table 3(a)). As for the hair bulge region, the ex- pression of 16 out of 17 genes was confirmed (Table 3(b)). In addition, the expression of 18 out of 22 genes related to immunophenotyping of the human bulge re- gion was also detected (Table 3(c)). 4. DISCUSSION Several groups have extracted RNA from rodent and hu- man hair follicles [24,28-34]. In most cases, the hair samples were stored in dissolution buffers, such as RNA later [24] or RN easy [28], prior to the analysis. However, for the HAIR experiment, the hair samples from astro- nauts must be stored without buffers at −80˚C, due to the limited resource in space. Therefore, the same storage method was employed in this study. The quality of RNA extracted from the samples stored at −80˚C was first in- vestigated, followed by examination of whether the ex- tracted RNA was of sufficient quality and quantity for subsequent DNA microarray analysis. In this study, different RNA samples extracted from 1, 5, and 10 strands of hair follicles using ISOGEN Reagent were compared. Extracted RNA was then amplified prior to the DNA microarray analysis. As shown in Table 1, some amount of RNA could be extracted even from 1 hair follicle. Notably, the yields were somewhat variable, and the amount of extracted RNA was not dependent on the number of hair follicles. While the reason for these results is unclear, it is likely that the device (NanoDrop ND-1000 spectrophotometer) was unable to correctly de- tect the amounts of RNA that were near to or less than its limit of detection. On the other hand, the electrophero- grams of these samples indicated intactness and good quality (Figure 1). Studies have shown that less than 5 ng of total RNA could be amplified and used for micro- array hybridization [24,35,36]. With the incorporation of a pre-amplification process, the RNA samples were am- plified effectively to provide sufficient materials for mi- croarray hybridization (Table 2). In the current study, the RNA yields from the hair samples were >18 ng per hair follicle, which is similar to the results reported by some researchers [24,37]. Al- though the amount of extracted RNA was insufficient for direct microarray analysis, the RNA amplification proce- dure allowed us to perform the microarray profiling, even on the samples that had only small amounts of RNA (Tables 1 and 2) [24,38-41]. In addition, the quality of RNA is important for judging whether the samples could be applied to the microarray analysis. In this study, the quality of RNA was evaluated on the basis of RIN (Table 1). RNA, although thermodynamically stable, is rapidly degraded by ubiquitous RNase enzymes [23]; as a result, short fragments of degraded RNA appear in the samples 42,43]. Using agarose gel electrophoresis, 2 RNA bands [ Copyright © 2013 SciRes. OPEN ACCESS
M. Terada et al. / Advances in Bioscience and Biotechnology 4 (2013) 75-88 Copyright © 2013 SciRes. 83 OPEN ACCESS Table 3. List of hair root-related genes. Genes shown in dark columns were not detected in the samples. a) Sub-bulge; b) Bulge; c) Immunophenotype of the human bulge region. (a) Gene symbol Description SDC2 Homo sapiens syndecan 2 (SDC2), mRNA [NM_002998] ANGPTL7 H. sapiens angiopoietin-like 7 (ANGPTL7), mRNA [NM_021146] SLC1A4 H. sapiens solute carrier family 1 (glutamate/neutral amino acid transporter), member 4 (SLC1A4), transcript variant 1, mRNA [NM_003038] TYMS H. sapiens thymidylate synthetase (TYMS), mRNA [NM_001071] CDK1 H. sapiens cyclin-dependent kinase 1 (CDK1), transcript variant 1, mRNA [NM_001786] TOP2A H. sapiens topoisomerase (DNA) II alpha 170kDa (TOP2A), mRNA [NM_001067] VAV3 H. sapiens vav 3 guanine nucleotide exchange factor (VAV3), transcript variant 1, mRNA [NM_006113] GPC4 H. sapiens glypican 4 (GPC4), mRNA [NM_001448] MCAM H. sapiens melanoma cell adhesion molecule (MCAM), mRNA [NM_006500] SLC4A7 H. sapiens solute carrier family 4, sodium bicarbonate cotransporter, member 7 (SLC4A7), mRNA [NM_003615] FEN1 H. sapiens flap structure-specific endonuclease 1 (FEN1), mRNA [NM_004111] TIMP3 H. sapiens TIMP metallopeptidase inhibitor 3 (TIMP3), mRNA [NM_000362] LAMB1 Laminin, beta 1 [Source: HGNC symbol; Acc:6486] [ENST00000393559] FGF18 H. sapiens fibroblast growth factor 18 (FGF18), mRNA [NM_003862] COMP H. sapiens cartilage oligomeric matrix protein (COMP), mRNA [NM_000095] PDGFC H. sapiens platelet derived growth factor C (PDGFC), transcript variant 1, mRNA [NM_016205] LAMB1 H. sapiens laminin, beta 1, mRNA (cDNA clone IMAGE: 4889995) containing frame-shift errors [BC044633] KPNA2 H. sapiens karyopherin alpha 2 (RAG cohort 1, importin alpha 1) (KPNA2), mRNA [NM_002266] PRC1 H. sapiens protein regulator of cytokinesis 1 (PRC1), transcript variant 1, mRNA [NM_003981] LAMB1 H. sapiens laminin, beta 1 (LAMB1), mRNA [NM_002291] COL11A1 H. sapiens collagen, type XI, alpha 1 (COL11A1), transcript variant B, mRNA [NM_080629] SLC7A1 H. sapiens solute carrier family 7 (cationic amino acid transporter, y+ system), member 1 (SLC7A1), mRNA [NM_003045] PCDH8 H. sapiens protocadherin 8 (PCDH8), transcript variant 1, mRNA [NM_002590] RRM2 H. sapiens ribonucleotide reductase M2 (RRM2), transcript variant 2, mRNA [NM_001034] (b) Gene symbol Description DIO2 H. sapiens deiodinase, iodothyronine, type II (DIO2), transcript variant 1, mRNA [NM_013989] DPYSL2 H. sapiens dihydropyrimidinase-like 2 (DPYSL2), transcript variant 2, mRNA [NM_001386] FST H. sapiens follistatin (FST), transcript variant FST344, mRNA [NM_013409] FZD1 H. sapiens frizzled family receptor 1 (FZD1), mRNA [NM_003505] DCT H. sapiens dopachrome tautomerase (dopachrome delta-isomerase, tyrosine-related protein 2) (DCT), transcript variant 1, mRNA [NM_001922] DPYSL3 H. sapiens dihydropyrimidinase-like 3 (DPYSL3), transcript variant 2, mRNA [NM_001387] DCN H. sapiens decorin (DCN), transcript variant A1, mRNA [NM_001920] SERPINF1 H. sapiens serpin peptidase inhibitor, clade F (alpha-2 antiplasmin, pigment epithelium derived factor), member 1 (SERPINF1), mRNA [NM_002615]
M. Terada et al. / Advances in Bioscience and Biotechnology 4 (2013) 75-88 84 Continued WIF1 H. sapiens WNT inhibitory factor 1 (WIF1), mRNA [NM_007191] KRT15 H. sapiens keratin 15 (KRT15), mRNA [NM_002275] PHLDA1 H. sapiens pleckstrin homology-like domain, family A, member 1 (PHLDA1), mRNA [NM_007350] DKK3 H. sapiens dickkopf homolog 3 (Xenopus laevis) (DKK3), transcript variant 1, mRNA [NM_015881] PHLDA1 Pleckstrin homology-like domain, family A, member 1 [Source: HGNC symbol; Acc:8933] [ENST00000266671] TGFB2 H. sapiens transforming growth factor, beta 2 (TGFB2), transcript variant 2, mRNA [NM_003238] DKK3 H. sapiens dickkopf homolog 3 (X. laevis) (DKK3), transcript variant 1, mRNA [NM_015881] ANGPTL2 H. sapiens angiopoietin-like 2 (ANGPTL2), mRNA [NM_012098] DIO2 H. sapiens deiodinase, iodothyronine, type II (DIO2), transcript variant 4, mRNA [NM_001242502] (c) Gene symbol Description TNC H. sapiens tenascin C (TNC), mRNA [NM_002160] GJA1 H. sapiens gap junction protein, alpha 1, 43kDa (GJA1), mRNA [NM_000165] FBN1 H. sapiens fibrillin 1 (FBN1), mRNA [NM_000138] NES H. sapiens nestin (NES), mRNA [NM_006617] CD200 H. sapiens CD200 molecule (CD200), transcript variant 2, mRNA [NM_001004196] ITGB1 H. sapiens integrin, beta 1 (fibronectin receptor, beta polypeptide, antigen CD29 includes MDF2, MSK12) (ITGB1), transcript variant 1E, mRNA [NM_133376] NID2 Nidogen 2 (osteonidogen) [Source: HGNC symbol; Acc:13389] [ENST00000395707] FN1 H. sapiens fibronectin 1 (FN1), transcript variant 7, mRNA [NM_054034] ITGA6 H. sapiens integrin, alpha 6 (ITGA6), transcript variant 2, mRNA [NM_000210] CD34 H. sapiens CD34 molecule (CD34), transcript variant 1, mRNA [NM_001025109] LHX2 H. sapiens LIM homeobox 2 (LHX2), mRNA [NM_004789] NID1 H. sapiens nidogen 1 (NID1), mRNA [NM_002508] FBN2 H. sapiens fibrillin 2 (FBN2), mRNA [NM_001999] LTBP1 H. sapiens latent transforming growth factor beta binding protein 1 (LTBP1), transcript variant 1, mRNA [NM_206943] NES H. sapiens nestin (NES), mRNA [NM_006617] ITGA6 H. sapiens integrin, alpha 6 (ITGA6), transcript variant 2, mRNA [NM_000210] LTBP1 H. sapiens latent transforming growth factor beta binding protein 1 (LTBP1), transcript variant 1, mRNA [NM_206943] FBN3 H. sapiens fibrillin 3 (FBN3), mRNA [NM_032447] KRT15 H. sapiens keratin 15 (KRT15), mRNA [NM_002275] CD200 H. sapiens CD200 molecule (CD200), transcript variant 2, mRNA [NM_001004196] NID2 H. sapiens nidogen 2 (osteonidogen) (NID2), mRNA [NM_007361] CD34 H. sapiens CD34 molecule (CD34), transcript variant 2, mRNA [NM_001773] comprising 28S and 18S ribosomal RNA can be readily visualized in gel images. RNA is considered of high quality when the ratio of 28S: 18S bands are more than 2. The RIN numbers are calculated by allowing the classi- fication of total RNA, based on a numbering system from 1 (the most degraded) to 10 (the most intact) [22, 23]. Generally, RNA sample with a RIN number of more than 7 are considered suitable for genetic analyses [43]. Interestingly, some researchers reported that with care, meaningful microarray data could be obtained from RNA Copyright © 2013 SciRes. OPEN ACCESS
M. Terada et al. / Advances in Bioscience and Biotechnology 4 (2013) 75-88 85 samples of impaired quality [44], whereas others sugges- ted that degradation does not preclude the microarray analysis if comparison is done between samples with comparable RNA integrity [42]. In this study, Agilent Bioanalyzer 2100 was used to determine the sample quality by calculating RIN, based on the Bioanalyzer traces typically yielded by hair follicle RNAs. Therefore, when a sample had a lower 28S rRNA peak but no deg- radation peaks (Figure 1), the system could not consider the sample as a normal total RNA electropherogram trace. Another issue was the existence of a 5S rRNA or tRNA peak in the Bioanalyzer electropherogram (Figure 1), which may affect the calculation of RIN when these peaks are larger than that of 18S or 28S ribosomal RNA [23]. In this study, RNA was extracted using ISOGEN Reagent, which could not remove 5S rRNA or tRNA due to the lack of column elution steps. As a result, RIN was unable to be calculated for most hair follicle RNA sam- ples using default parameters (Table 1). Based on RIN or 28S/18S ratios, a total of 14 RNA samples (6, 7, and 1 samples from 1, 5, and 10 follicles, respectively) were chosen for pre-amplification of micro- array hybridization (Tables 1 and 2). Notably, 19,361 genes were expressed in more than 1 sample from among all samples. In total, 10,593 genes were expressed in all samples. By referencing publically available data set from previous microarray analyses [27,45,46], the differences depending on the number of hair follicles were compared by the clustering analysis of the microarray data. Using the PCA analysis, similarities and differences that were dependent on the number of hair follicles were also ob- served (Figure 2). In the PCA plot, 4 spots from 1 folli- cle of 1 subject were scattered, whereas some spots from 5 follicles of 2 subjects were located closely for respec- tive individuals. These phenomena suggest that the ho- mogeneity of gene expression is largely dependent on the number of cells from which RNA is extracted. That is, as the number of hair follicles is increased, the homology and uniformity are increased. The variability among sam- ples was also evaluated using the rank correlation of log ratios. As shown in Figure 3, the color between the sam- ples from 5 hair follicles became redder than that be- tween the samples from 1 hair follicle. In agreement with the PCA results, the rank correlation of log ratios analy- sis suggests that the homogeneity is increased, as the number of hair follicles is increased. These results seem to be reasonable, because the hereditary properties of in- dividual hair follicles would disappear when being aver- aged by the increasing number of hair cells. This finding is advantageous for the HAIR experiment on astronauts, since the goal of the experiment is to detect gene expres- sion changes in the body during spaceflight, but not the single hair-specific patterns. The hierarchical cluster ana- lysis was also performed by applying condition tree clu- stering (Figure 4), through which the mRNA expression profiles of the 2 subjects could be distinguished. This re- sult will be informative for successful implementation of the HAIR experiment, because the focus of the study is on the individual data, rather than the average data, from the subjects. Human hair analysis will be further devel- oped along the same lines as a method to evaluate the health conditions of astronauts because it allows the ex- amination of astronaut-specific patterns in space. Using the hierarchical cluster analysis, Kim et al. [2006] pre- viously reported no difference in the gene expression in hair roots between males and females. Interestingly, 2 subjects in this study were males, and their individual characteristics could be separated (Figure 4). While Kim et al. obtained their samples at the same time from many subjects, the samples in this study were collected at va- rious times from 2 subjects. This margin may reflect the differences between their results and ours. Next, to confirm the integrity of mRNA in the samples, the expression of hair follicle-specific genes was analyz- ed (Table 3). For hair sub-bulge-related genes, the ex- pression of 22 out of 24 reported genes was detected (Table 3(a)). Out of 17 genes of hair bulge, the expres- sion of 16 genes was confirmed (Table 3(b)). In addition, 18 out of 22 genes related to human epithelial hair folli- cle stem cells and bulge niche markers were found to be expressed (Table 3(c)). Together, these results suggest that hair root-related genes were expressed in the sam- ples tested in this study. Therefore, it is desirable that the genes of other organs except hair roots are included in our samples, and there is not any problem. In this time, because we can confirm at least the existence of genes related with hair roots in our samples, there are no me- thodologically problems. Nevertheless, the newly devel- oped methods are appropriate for analyzing biological samples derived from astronauts in the HAIR experi- ment. It is worth noting that the gene expression in the skin has been shown to be different between subjects who had hyperkeratotic skin lesions and those who did not [47]. In addition, Yin et al. also suggested that DNA damage was induced in the mouse skin upon exposure to ultra- violet radiation [48]. These results suggested that the skin, which contains hair follicles, receive the effects on gene condition by physiological changes or extraordinary environments. Although these studies were not perform- ed on human hair follicles, it is indeed possible to inves- tigate the effects of various space environments (i.e., mi- crogravity, space radiation, physiological changes, or men- tal conditions) on astronauts by analyzing the gene ex- pression in their hair follicles. 5. CONCLUSION Taken together, these results suggest the following points. First, it is possible to perform a robust gene expression Copyright © 2013 SciRes. OPEN ACCESS
M. Terada et al. / Advances in Bioscience and Biotechnology 4 (2013) 75-88 86 analysis on hair samples stored at −80˚C, even without a fixation buffer. Second, the newly modified method of mRNA extraction and analysis is effective in detecting differential genes expression in samples containing only 5 hairs. The hair samples provided useful physiological infor- mation for examining the effect of spaceflight. A novel method was developed to extract and amplify RNA from 5 hair roots, which is the same number of hair roots used in the space experiment; therefore, the method can be ap- plied for genetic analysis of astronauts’ hair samples. Currently, sufficient samples are being gathered from as- tronauts. The analysis of hair roots from the ISS crews will support the development of a simple and effective diagnostic measure for metabolic changes and help eva- luate astronauts’ health conditions in response to long- term spaceflight. 6. ACKNOWLEDGEMENTS This study was supported in part by the JAXA-ISS Space Medicine Program Grant from the Japan Aerospace Exploration Agency and a Grant-in-Aid for Young Scientists (B-21800096, M.T.) from the Japan Society for the Promotion of Science. We thank Tohko Hashizume for the useful comments on and support for our study. We would also like to express our appreciation to Dr. Hi- roshi Ohshima and Dr. Toshiko Ohta for their constructive advice and supervision of this manuscript. REFERENCES [1] Terada, M., Kawano, F., Ishioka, N., Higashibata, A., Majima, H.J., Yamazaki, T., et al. (2012) Biomedical ana- lysis of rat body hair after hindlimb suspension for 14 days. Acta Astronaut, 73, 23-29. http://dx.doi.org/10.1016/j.actaastro.2011.12.016 [2] Sperling, L.C. (1991) Hair anatomy for the clinician. Journal of the American Academy of Dermatology, 25, 1- 17. [3] Stenn, K.S. and Paus, R. (2001) Controls of hair follicle cycling. Physiological Reviews, 81, 449-494. [4] Chuong, C.M. 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