Comparative Analysis of Dynamic Proteomic Profiles between in Vivo

Jul 10, 2013 - Our study, for the first time, provides a comparative proteomic analysis between embryos after in vivo fertilization and development (I...
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Comparative Analysis of Dynamic Proteomic Profiles between in Vivo and in Vitro Produced Mouse Embryos during Postimplantation Period Jingzhou Nie,†,§ Lei An,†,§ Kai Miao,†,§ Zhuocheng Hou,† Yong Yu,† Kun Tan,† Linlin Sui,† Shuzhi He,† Qian Liu,‡ Xing Lei,‡ Zhonghong Wu,† and Jianhui Tian*,† †

Ministry of Agriculture Key Laboratory of Animal Genetics, Breeding and Reproduction, National Engineering Laboratory for Animal Breeding, College of Animal Sciences and Technology, China Agricultural University, No. 2 Yuanmingyuan Xi Lu, Haidian, Beijing 100193, China ‡ BGI Tech Solutions Co., Ltd., Main Building of Beishan Industrial Zone, Yantian District, Shenzhen 518083, China S Supporting Information *

ABSTRACT: Assisted reproductive technology (ART) increasingly is associated with long-term side-effects on postnatal development and behaviors. High-throughput gene expression analysis has been extensively used to explore mechanisms responsible for these disorders. Our study, for the first time, provides a comparative proteomic analysis between embryos after in vivo fertilization and development (IVO, control) and in vitro fertilization and culture (IVP). By comparing the dynamic proteome during the postimplantation period, we identified 300 and 262 differentially expressed proteins (DEPs) between IVO and IVP embryos at embryonic day 7.5 (E7.5) and E10.5, respectively. Bioinformatic analysis showed many DEPs functionally associated with post-transcriptional, translational, and post-translational regulation, and these observations were consistent with correlation analysis between mRNA and protein abundance. In addition to altered gene expression due to IVP procedures, our findings suggest that aberrant processes at these various levels also contributed to proteomic alterations. In addition, numerous DEPs were involved in energy and amino acid metabolism, as well as neural and sensory development. These DEPs are potential candidates for further exploring the mechanism(s) of ART-induced intrauterine growth restriction and neurodevelopmental disorders. Moreover, significant enrichment of DEPs in pathways of neurodegenerative diseases implies the potentially increased susceptibility of ART offspring to these conditions as adults. KEYWORDS: in vitro fertilization and culture, proteome, postimplantation, dynamic, mouse embryo



INTRODUCTION Epidemiological or cohort studies have indicated that assisted reproductive technology (ART) can predispose offspring to a series of health problems, including preterm birth,1 perinatal mortality,1 low birth weight,1,2 congenital malformations,3 as well as long-term risk of disease.4 Barker and Osmond first proposed the “fetal origins of adult disease” hypothesis, which states that aspects of fetal development may predispose offspring to a range of diseases in adulthood.5 Comprehensive and detailed understanding of gene and protein expression patterns of in vitro produced embryos would help us to explore the underlying mechanism(s) associated with the abnormal phenotypes observed in ART embryos and offspring. Using various high-throughput methods, such as microarrays and RNA-seq, global gene expression patterns of in vitro produced (IVP) embryos have been analyzed in species such as mice,6,7 cows,8−11 and pigs.12,13 However, considering the crucial role of post-transcriptional14 and translational15 regulation in embry© 2013 American Chemical Society

onic development, proteomic analysis, which focuses on direct functional molecules, would provide a more direct reference for understanding the molecular origins and underlying mechanism(s) that lead to multiple aberrations of ART offspring. Since considerable lethality of IVP embryos occurs during the pre- and peri-implantation periods,16 postimplantation embryos may be more representative than preimplantation embryos for investigating the origins of those aberrations. In addition, postimplantation is a crucial period for the embryonic development and onset of organogenesis. In our current study, embryonic days 7.5 (E7.5) and E10.5 were selected. At E7.5, the amniotic cavity is sealed off, the neural plate begins to enlarge, the notochodal plate and neural groove are visible, and the allantoic bud elongates; meanwhile, at E10.5, the integumentary system, renal system, neural crest, hearing, Received: November 5, 2012 Published: July 10, 2013 3843

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Figure 1. Overview of experimental design. Blastocysts from in vivo fertilization and development (IVO groups) and in vitro fertilization and culture (IVP groups) were collected and then transferred into pseudopregnant females. Both IVO and IVP embryos were collected at E7.5 (IVO7.5 and IVP7.5 groups) and E10.5 (IVO10.5 and IVP10.5 groups).

accepted procedure.21 All technical procedures were performed by skilled technicians under strictly controlled conditions and optimized environment. In addition, as previous studies,18,19 superovulation and embryo transfers were performed in both IVO and IVP groups to eliminate the effects of these factors on the quality of embryos. Due to the small amount of protein in one embryo, and the limited source of IVP embryos, a single pooling strategy was used in our study as previous similar studies reported.19,22−25 Karp et al. also pointed that the pooling strategy is appropriate in experiments with low sample yield, and could reduce the biological variance, increasing the power to detect changes.26 Moreover, the use of single pooling strategy was also dependent on the purpose of our study, which is mainly focusing on the potential mechanism(s) responsible for the long-term effects of IVP on postnatal offspring. Single pooling is a rational strategy to ensure a relative large sample size, which is critical for our study to make sure that the pooled sample was a representative population of IVP embryos. Additionally, considering the requirement of high stability for individual pools, each pool was detected three times as technical replicates.22

balance, and gastrointestinal tract develop along with allantoic fusion.17 The aim of our study was to investigate the differences in protein profiles between embryos after in vivo fertilization and development (IVO) and in vitro fertilization and culture (IVP), mainly focusing on the potential mechanism(s) responsible for the long-term effects of IVP to postnatal offspring. To our knowledge, this is the first comparative analysis of proteomic profiles between in vivo and in vitro produced embryos, which will provide a dynamic proteomic reference for understanding the molecular origins and underlying mechanism(s) that lead to multiple aberrations in ART offspring. We found numerous dysregulated proteins that were functionally associated with metabolism and neural development, as well as regulation of gene and protein expression. These proteins need to be further studied as potential candidates for exploring the molecular origins of ART-induced disorders.



MATERIALS AND METHODS

Animals

Five- to six-week-old F1 female mice (ICR) and eight- to nineweek-old F1 male mice (ICR) were maintained in an animal facility at normal temperature (20 ± 2 °C) and 12 h light (7:00−19:00)/12 h dark (19:00−7:00) photoperiods with free access to water and food. All studies adhered to procedures consistent with the China Agricultural University Guide for the care and use of laboratory animals.

Superovulation

Females were superovulated by intraperitoneal (i.p.) injection of 5 IU Pregnant Mare Serum Gonadotropin (PMSG, Ningbo Second Hormone Factory, Ningbo, China), followed 48 h later by an i.p. injection of 5 IU of human Chorionic Gonadotropin (hCG, Ningbo Second Hormone Factory, Ningbo, China).

Experimental Design

Natural Mating

A well-established experimental design18−20 was adopted to test the effect of in vitro fertilization and culture on the proteome of postimplantation embryos. As illustrated in Figure 1, all female mice were superovulated and divided into two segments randomly. After either in vivo fertilization and development (IVO groups as control) or in vitro fertilization and culture (IVP groups), blastocysts were collected and transferred to pseudopregnant recipients. At E7.5, some of the recipient females in each segment were randomly selected to be sacrificed, and embryos with normal morphology were collected from the uterus of recipients (defined as IVO7.5 and IVP7.5 group). At E10.5, the other recipients were sacrificed, and morphologically normal embryos were sampled (defined as IVO10.5 and IVP10.5 groups). The production of IVP embryos was carried out according to a standard and well-

In IVO groups, F1 females were mated individually with F1 males after the hCG injection. The following morning, females were checked for the presence of the vaginal copulation plug. In Vitro Fertilization

In vitro fertilization was performed according to standard procedures.21 In IVP groups, all media and culture dishes (Nunc, Rochester, NY) were equilibrated overnight in an incubator (Thermo, San Jose, CA) under a humidified atmosphere of 5% CO2 at 37 °C before use. At 14 h posthCG treatment, cumulus-enclosed oocyte complexes (COCs) were recovered from oviducts in M2 medium (Sigma-Aldrich, St. Louis, MO). Cumulus cells were removed by digesting with hyaluronidase (Sigma-Aldrich) for 3−5 min, and the MII oocytes that displayed a clear, bright and homogeneous 3844

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min and then centrifuged at 4 °C, 30 000g for 15 min. The supernatant was mixed well with 10% trichloroacetic acid (TCA) and chilled acetone (1:5, v/v) and incubated at −20 °C overnight. After centrifugation at 4 °C, 30 000g, the supernatant was discarded. The precipitate was washed with chilled acetone three times. The pellet was air-dried and dissolved in 1 mL lysis buffer (7 M urea, 2 M thiourea, 4% NP40, 20 mM Tris-HCl, pH 8.0−8.5). The suspension was sonicated at 200 W for 15 min and centrifuged at 4 °C, 30 000g for 15 min. The supernatant was transferred to another tube. To reduce disulfide bonds in proteins of the supernatant, 10 mM DTT (final concentration) was added and incubated at 56 °C for 1 h. Subsequently, cysteines were blocked by the addition of 55 mM iodoacetamide (IAM) (final concentration) in the darkroom for 45 min. The supernatant was mixed well with chilled acetone (1:5, v/v) for 2 h at −20 °C to precipitate proteins. After centrifugation at 4 °C, 30 000g, the supernatant was discarded, and the pellet was air-dried for 5 min, dissolved in 500 μL 0.5 M triethylammonium bicarbonate (TEAB, Applied Biosystems, Milan, Italy), and sonicated at 200 W for 15 min. Finally, samples were centrifuged at 4 °C, 30 000g for 15 min. The supernatant was transferred to a new tube and quantified, using the 2-D Quant Kit (GE Healthcare, Amersham Biosciences, Piscataway, NJ) with BSA as a standard according to the manufacturer’s instructions, for the subsequent protein digestion.

cytoplasm, and retained the intact first polar body were selected for in vitro fertilization. After rinsing in HTF medium (Sage, Bedminster, NJ), oocytes were kept in the incubator in 60 μL drops of HTF medium covered with paraffin oil (SigmaAldrich). Sperm was collected from the cauda epididymis and capacitated for 1 h in HTF medium at 37 °C and 5% CO2. Sperm insemination was realized 15 h post-hCG treatment. After 4 h in the incubator, oocytes/embryos were washed several times in KSOM medium (Millipore, Billerica, MA) and then transferred to 60 μL drops of KSOM medium covered with paraffin oil. The embryos were cultured to the blastocyst stage at 37 °C with 5% CO2 atmosphere. Blastocyst Collection and Embryo Transfer

In IVO groups, embryos at the blastocyst stage were obtained from recipient females by flushing the uterus with M2 medium. The criteria for harvesting blastocysts for embryo transfer was based on the developmental progress and morphology. According to previous reports, in vitro embryos show delayed preimplantation development.27−30 Here we designed our study based on research by Giritharan et al.30 In detail, to obtain blastocysts of identical morphology, the collection was performed at different times. The IVP blastocysts were harvested at 106−112 h post-hCG after culturing in KSOM medium, while control IVO blastocysts were harvested at 96− 100 h post-hCG. In each group, well-developed late-cavitating blastocysts of similar morphology were selected for embryo transfer. Pseudopregnant female mice were mated to vasectomized males 3.5 days prior to embryo transfer. The morning after mating, females were checked for the presence of a vaginal plug, and this was considered day 0.5 of pseudopregnancy. Twelve blastocysts were transferred to one recipient, with six embryos in each uterine horn.

Protein Digestion

One hundred micrograms of each protein sample in 0.5 M TEAB was carefully taken for digestion with Trypsin Gold at the protein/trypsin ratio of 20:1 at 37 °C for 4 h. Trypsin Gold at the same protein/trypsin ratio of 20:1 was added again for a further 8 h of digestion at 37 °C. LC-ESI-MS/MS Analysis by LTQ-Orbitrap CID

Collection of Postimplantation Embryos

After protein digestion, each peptide sample was desalted using a Strata X column (Phenomenex, Torrance, CA), vacuumdried, and then resuspended in a 200 μL volume of buffer A (2% ACN, 0.1% FA). After centrifugation at 20 000g for 10 min, the supernatant was recovered to obtain a peptide solution with a final concentration of approximately 0.5 μg/μL. Ten microliters of the supernatant was loaded into a Shimadzu LC20AD nanoHPLC by the autosampler onto a 2 cm C18 trap column (inner diameter 200 μm), and the peptides were eluted onto a resolving 10 cm analytical C18 column (inner diameter 75 μm) made in-house. The samples were loaded at 15 μL/min for 4 min, and then the 91 min gradient was run at 400 nL/min starting from 2 to 35% buffer B (98% ACN, 0.1% FA), followed by a 5 min linear gradient to 80%, maintenance with 80% buffer B for 8 min, and finally returning to 2% within 2 min. The peptides were subjected to nanoelectrospray ionization followed by tandem mass spectrometry (MS/MS) in an LTQ Orbitrap Velos (Thermo Fisher Scientific, San Jose, CA) coupled online to the HPLC. Intact peptides were detected in the Orbitrap at a resolution of 60 000. Peptides were selected for MS/MS using the collision induced dissociation (CID) operating mode with a normalized collision energy setting of 35%, and ion fragments were detected in the LTQ at a resolution of 7500. A data-dependent procedure that alternated between one MS scan followed by 10 MS/MS scans was applied for the 10 most abundant precursor ions above a threshold ion count of 5000 in the MS survey scan with the following Dynamic Exclusion settings: repeat counts, 2; repeat duration, 30 s; and exclusion duration, 120 s. The electrospray

The criteria for selecting embryos for pooling were based on morphology. At E7.5 and E10.5, embryos showing typical morphological features according to the well-established landmarks31,32 were selected for pooling. In detail, at E7.5, well-developed embryos at the gastrulation stage were characterized by the sealed-off amniotic cavity and the formation of three distinct cavities (amniotic cavity, exocoelom, and ectoplacetal cleft). The epiblast was separated from the extraembryonic ectoderm. At E10.5, a definitive placenta was formed, and the well-developed embryos were characterized by the deepening of the lens pit and the appearance of the physiological umbilical hernia. Embryos were collected after removing the placenta and amnion. All sampled embryos were serially washed with phosphate-buffered saline (GIBCO, Life Technologies, Grand Island, NY) and stored immediately in liquid nitrogen for further use. Protein Extraction

All sampled embryos in each group were pooled, and then the pooled sample was analyzed in triplicate in parallel as three technical replicates. Samples were ground to powder in liquid nitrogen using a mortar and pestle. One milliliter of lysis buffer (7 M urea, 2 M thiourea, 4% NP40, 20 mM Tris-HCl, pH 8.0− 8.5) was added, with phenylmethanesulfonyl fluoride (PMSF) and ethylene diamine tetraacetic acid (EDTA) at final concentrations of 1 and 2 mM, respectively. After 5 min, DLdithiothreitol (DTT) was added to the samples at 10 mM final concentration. The suspension was sonicated at 200 W for 15 3845

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of technical replicates, as previous similar study reported.22 This methodology was also approved by previous methodological reviews.39,40 We integrated t test and fold change, as well as functional clustering to select biologically meaningful DEPs. In detail, if the technical replicates were not consistent with each other, that is, large variation among three replicates, the protein would not be considered a DEP. Therefore, a small number of proteins with one or two “0” among three replicates were not included for bioinformatic analysis, since any significant differences in levels of those proteins may be caused from errors in detection. It should be noted that the true independent biological unit in this case should be one embryo or a group of embryos from one particular donor.22 In the present study, each pool contains from 70 to over 300 samples, which originated from more than 50 donors and multiple experimental batches. The large sample size of embryos and donors, as well as multiple batches should be sufficient to yield biologically meaningful results. Considering that only embryos with normal morphology, which are more likely to result in a live birth, were sampled for analysis, as well as the fact that even minor abnormalities or perturbation during fetal development would lead to a profound impact on the long-term health of offspring,41 a relative relaxed criterion of fold change (2-fold) and P value (0.05) was used in our study. This strategy could increase the power to detect biologically meaningful DEPs that may be potential candidates responsible for postnatal disorders of IVP offspring. To assess the similarities of the different replicates, and to obtain a visual understanding of the relationship between the different experimental groups, hierarchical clustering was carried out using the Multi Experiment Viewer 3.1 (MeV) data analysis tool based on the clusters of DEPs in the four groups of embryos. The Database for Annotation, Visualization and Integrated Discovery (DAVID v6.7; http://david.abcc. ncifcrf.gov) was used to annotate biological themes in response to different physiological conditions. Kyoto Encyclopedia of Genes and Genomes (KEGG; http://www.genome.jp/kegg/) was used to determine associated pathways of DEPs. In addition, DEPs were sent to the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING; http://string.embl. de/) to build a functional protein association network, and for comparison.

voltage applied was 1.5 kV. Automatic gain control (AGC) was used to prevent overfilling of the ion trap; 1 × 104 ions were accumulated in the ion trap for generation of the CID spectra. For MS scans, the m/z scan range was 350−2000 Da. Proteomic Analysis

Mass spectra were analyzed using the software MaxQuant33 (version 1.2.0.18). MS/MS spectra were searched using the Andromeda search engine34 against the International Protein Index (IPI) mouse database version 3.84 containing forward and reverse sequences (119 990 entries in total, including forward and reverse sequences). Additionally, the database included 404 common contaminants. All three technical replicates were merged at the MS/MS spectra level prior to analysis by MaxQuant. For mass recalibration, MaxQuant analysis included an initial search with a precursor mass tolerance of 20 ppm. In the main Andromeda search, precursor mass and fragment mass had an initial mass tolerance of 6 ppm and 0.5 Da, respectively. The search included a fixed modification of cysteine carbamidomethylation and variable modifications of methionine oxidation and protein N-terminal acetylation. The minimal peptide length was set to six amino acids, and a maximum of two miscleavages was allowed. The false discovery rate (FDR) was set to 0.01 for peptide and protein identifications. Proteins were considered identified when at least two peptides were identified and at least one of which was uniquely assignable to the corresponding sequence. In the case of identified peptides that were all shared between two proteins, these were combined and reported as one protein group. Contents of the protein table were filtered to eliminate identifications from the reverse database and common contaminants. Label-free quantitation analysis was performed in MaxQuant. Briefly, total peptide signals were determined in the mass to charge, elution time, and intensity space. For every peptide, corresponding total signals from multiple runs were compared to determine peptide ratios. Pair-wise peptide ratios were only determined when the corresponding peak was detected in both LC−MS runs. For comparison between samples, label-free quantification was performed with a minimum of two ratio counts to determine the normalized protein intensities, which were averaged from the three replicates as the protein abundance for each group. To facilitate data analysis, all protein IDs were mapped to the Ensembl Mus musculus gene IDs or gene symbol using the corresponding tools for data analysis. The correlation coefficient is frequently used to evaluate the relationship between protein abundance and mRNA expression on a genomic scale or a specific gene.35−38 In our study, the Pearson’s correlation coefficients (PCC) and corresponding Pvalues were calculated using the R software, an free online software environment for statistical computing (http://www.rproject.org), The correlation between the normalized mRNA (Reads Per Kilobase of exon model per Million mapped reads, RPKM) and protein abundance (Label Free Quantification, LFQ) between IVP and IVO embryos were calculated at E7.5 and E10.5, respectively. The significance of difference of protein abundance between IVO and IVP embryos was evaluated using a two-sample heteroscedastic t test (two-tailed), and DEPs were considered significant at probability values of P < 0.05. As only one biological replicate represented by a single pool containing from 70 to over 300 embryos was available for each time point studied, our selection of DEPs was based on statistical analysis

Morphometric and Histological Analysis

E7.5 embryos were photographed and weighed (indicated by implantation site weight) at E7.5,42 while the prenatal fetuses were weighed at E19. E7.5 embryos were isolated quickly and then fixed for 24 h at room temperature by direct immersion in a 0.1 M pH 7.4 phosphate buffer (Beijing Chemical Works, Beijing, China) with 4% paraformaldehyde (Sigma-Aldrich). Samples were dehydrated with an ethanol and toluene (Beijing Chemical Works) series and embedded in paraffin (Leica, Wetzlar, Germany). Serial sections (6 μm thickness) were mounted on gelatin-coated glass slides and stained with hematoxylin and eosin (H&E).



RESULTS In the IVO7.5, IVP7.5, IVO10.5, and IVP10.5 groups, 374, 294, 77, and 76 embryos were sampled from the uterus of recipient mice, respectively. It should be mentioned that the sample size of each group in our study is considerably larger than those of recently reported studies involved in peri- or postimplantation 3846

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Figure 2. Comparisons of DEPs between E7.5 and E10.5. The Venn diagram shows DEPs specific to E7.5 or E10.5 embryos or in common with both. The table shows DEPs with >2-fold changes and corresponding fold changes at E7.5 and E10.5. Among these DEPs four proteins were dysregulated at both time points: Iars, Mybbp1a, Dync1h1 and Supt16h (highlighted in bold and underlined).

embryos.19,27,43,44 Using these embryos, we successfully identified 8102, 8127, 7688, and 8673 peptides (Supporting Information, Table S1) and a total of 1049, 1025, 1025, and 1082 proteins (Supporting Information, Tables S2−S5), respectively. Hierarchical clustering was performed on different treatments and technical replicates based on the overall similarity of gene expression patterns. Results showed a striking separation of the IVO and IVP embryos into two major opposing branches at both E7.5 and E10.5 (Supporting Information, Figure S1). At both time points, the proteomes of IVP embryos were very distinct from that of the IVO embryos. Each panel in Figure S1 represents a technical replicate, and data from each technical replicate of the same group were tightly clustered in the same branch, confirming the reliability of our detection system. In comparing the proteomes between the IVO and IVP embryos, 300 proteins were differentially expressed (P < 0.05) at E7.5 (Supporting Information, Table S6). Among these DEPs, 138 proteins were up-regulated and 162 proteins were down-regulated. For up-regulated DEPs, 11 proteins showed >2-fold change in expression, of which 7 proteins were specifically expressed in IVP embryos. For down-regulated DEPs, 43 proteins showed >2-fold change in expression, of which 9 proteins were specifically deficient in IVP embryos (Supporting Information, Figure S2). For embryos at E10.5, 262 DEPs (P < 0.05) were differentially expressed between IVO and IVP groups (Supporting Information, Table S7). Among these DEPs, 61 proteins were up-regulated, and 201 proteins were downregulated. For up-regulated DEPs, 11 proteins showed >2-fold changes, among which 9 proteins were specifically expressed in IVP embryos. For down-regulated DEPs, 33 proteins showed

>2-fold changes, of which 7 proteins were specifically deficient in IVP embryos (Supporting Information, Figure S2). Among the DEPs between IVP and IVO embryos, 109 proteins were dysregulated at both time points. The list in Figure 2 shows the DEPs with a >2-fold change at E7.5 and E10.5. Among these notably changed proteins, four showed dysregulation at both time points: Iars (isoleucine-tRNA synthetase), Mybbp1a (MYB binding protein (P160) 1a), Dync1h1 (dynein cytoplasmic 1 heavy chain 1), and Supt16h (suppressor of Ty 16 homologue in Saccharomyces cerevisiae). Analysis using DAVID was conducted to gain deeper insight into the different biological processes between IVP and IVO embryos at each time point. Figure 3 shows the Gene Ontology (GO) classification of DEPs between IVP and IVO embryos at E7.5 (A) and E10.5 (B), for which 29 and 31 subcategory terms were identified. Among these subcategories, “primary metabolic processes” (172 DEPs at E7.5 and 139 DEPs at E10.5 respectively) and “cellular metabolic processes” (165 DEPs at E7.5and 138 DEPs at E10.5, respectively) were the two most represented processes. KEGG pathway analysis was also performed based on DEPs at E7.5 and E10.5. As shown in Table 1, some pathways associated with post-transcriptional regulation and translation (such as “spliceosome”, “aminoacyl-tRNA biosynthesis”, and “ribosome”) and metabolism (such as “citrate cycle” and “glycolysis/gluconeogenesis”) were significantly enriched during the postimplantation period. In addition, with DEPs as seed nodes, a protein−protein interaction network was constructed using STRING Database version 9.0 (Figure 4). DEPs at E7.5 were mainly enriched in the terms “translation”, “chaperonin”, “tight junction”, “proteasome”, “DNA replication”, “aminoacyltRNA biosynthesis”, “spliceosome”, and “citrate cycle (TCA 3847

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Figure 3. GO classification. Analysis using DAVID supplied a simplified overview of GO subcategories based on the major category of ″biological process″ for DEPs at E7.5 (A) and E10.5 (B), and 29 and 31 terms were identified, respectively. The number for each subcategory represents the percentage of enriched DEPs in the total proteins (genes) of the subcategory.

2.2 × 10−16), 0.2472 (P = 1.1 × 10−15), and 0.2085 (P = 8.89 × 10−12) in the IVO7.5, IVP7.5, IVO10.5, and IVP10.5 groups, respectively. At both E7.5 and E10.5, IVP embryos showed a lower PCC (Figure 5), suggesting that the correlation of mRNA and protein abundance was lower in in vitro derived postimplantation embryos. At E7.5, IVP embryos showed a lower weight than IVO embryos (Figure 6A), although the difference was not statistically significant. More IVP than IVO embryos were characterized by delayed development (Figure 6B: b, c) and abnormal morphology (Figure 6B: d). The abnormal morphology of IVP embryos was also observed by histological analysis. Figure 6C shows representative sagittal histological sections of well-developed IVO embryos (Figure 6C: e) and

cycle)”, while those at E10.5 showed evident enrichment in “spliceosome”, “aminoacyl-tRNA biosynthesis”, “tight junction”, “proteasome”, “citrate cycle (TCA cycle)”, and “ribosome”. Transcriptome analysis performed between IVO and IVP embryos at E7.5 and E10.5 also showed global changes in gene expression in IVP embryos (corresponding mRNA expression level of each identified protein is listed in Supporting Information Table S9). Using transcriptomic data, the levels of mRNAs (RPKM) and corresponding proteins (LFQ) were analyzed to obtain a Pearson’s correlation coefficient (PCC) in each group. We used PCC to evaluate the correlation of mRNA and protein abundances of IVO and IVP embryos at both time points The PCCs were 0.4944 (P < 2.2 × 10−16), 0.3794 (P < 3848

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developmentally delayed and morphologically abnormal IVP embryos (Figure 6C: f−h). In the IVO7.5 group, normal primitive streak stage embryos clearly exhibited well-organized ectoderm, endoderm, and mesoderm and had formed ectoplacental, exocoelomic, and amniotic cavities (Figure 6C: e). In the IVP7.5 group, more embryos showed delayed development characterized by the presence of the proamniotic cavity, and even abnormal morphology characterized by disorganized ectoplacental cone or mesoderm.

Table 1. Significantly Enriched KEGG Pathways for DEPs at E7.5 and E10.5 E7.5

E10.5

aminoacyl-tRNA biosynthesis citrate cycle (TCA cycle) ribosome spliceosome tight junction glycolysis/gluconeogenesis arginine and proline metabolism antigen processing and presentation DNA replication proteasome gap junction cell cycle Huntington’s disease cysteine and methionine metabolism one carbon pool by folate glyoxylate and dicarboxylate metabolism Parkinson’s disease oocyte meiosis prion diseases pyruvate metabolism valine, leucine, and isoleucine tryptophan metabolism biosynthesis



DISCUSSION

Many previous studies have used high-throughput technology, such as RNA-seq and microarray, to analyze the mechanism(s) underlying the aberrant phenotypes of in vitro derived embryos and offspring. However, this study provides, for the first time to our knowledge, a comparative proteomic analysis between IVO and IVP embryos. Using different functional clustering methods, we found many biological processes and pathways that were deregulated in IVP embryos at both E7.5 and E10.5. The DEPs in our data were mainly functionally associated with (1) post-translational, translational, and post-transcriptional regulation; (2) energy and amino acid metabolism; (3) and early neural and sensory development. Disturbance of Post-Translational, Translational and Post-Transcriptional Processes in IVP embryos

In this study, both KEGG pathway and protein−protein interaction network analysis showed significant enrichment of terms such as “spliceosome”, “aminoacyl-tRNA biosynthesis”, “ribosome”, and “proteasome”, implying that IVP embryos may underwent an aberrant regulation of gene and protein expression at post-transcriptional, translational, or post-translational levels. This novel finding was confirmed by analyzing the correlation between mRNA expression and protein abundance, using our transcriptomic and proteomic data. As expected, IVP embryos showed an evidently lower correlation between mRNA and protein abundance than that of IVO embryos during postimplantation period, although it should be noted that PCCs of normal embryos varied widely at different time points. In humans, between 30% and 70% of genes generate multiple mRNAs by alternative splicing of their primary transcripts, and ∼80% of the alternative splicing results in changes in the encoded protein, making this mechanism one of the most important sources of proteome diversity.45 In addition, the spliceosome can remove or insert regulatory elements controlling translation, mRNA stability or localization.46 Based on our dynamic analysis, many proteins in this pathway showed up-regulation or down-regulation at both E7.5 and E10.5. For example, some splicing factors, such as Sf3a3 (splicing factor 3a, subunit 3) and Srsf6 (serine/arginine-rich splicing factor 6), were up-regulated at both E7.5 and E10.5. While proteins depressed at both time points included Prpf40a (PRP40 pre-mRNA processing factor 40 homologue A) and Hnrnpu (heterogeneous nuclear ribonucleoprotein U). Based on these observations, it can be speculated that these dysregulated DEPs may contribute largely to the disruption of post-transcriptional regulation in IVP embryos. Aminoacyl tRNA synthetases (AARS) belong to a family of 20 enzymes, one for each amino acid, which catalyze the first step of protein synthesis by aminoacylation of tRNAs.47,48 The role of aminoacyl-tRNA synthetases in translation is to define the genetic code by accurately pairing cognate tRNAs with their

Figure 4. Protein−protein interaction network. DEPs at E7.5 (A) and E10.5 (B) showed a tightly interconnected network from a web-based search of the STRING Database version 9.0 (http://string-db.org/).

3849

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Figure 5. Correlation between mRNA and protein abundances in IVO and IVP embryos at E7.5 and E10.5. At both time points, IVP embryos showed a lower correlation of mRNA and protein abundances compared with IVO embryos. (A) IVO7.5: R = 0.4944, P value < 2.2 × 10−16. IVP7.5: R = 0.3794, P value < 2.2 × 10−16. (B) IVO10.5: R = 0.2472, P value =1.1 × 10−15. IVP10.5: R = 0.2085, P value =8.89 × 10−12. Red squares and line represent IVP embryos, while the blue diamonds and line represent IVO embryos. The trend lines depict the best fit as predicted by linear regression. The Y-axis represents the normalized protein abundance, the unit of which is LFQ (Label Free Quantification) intensity; the X-axis represents the normalized mRNA expression level, the unit of which is RPKM (Reads Per Kilobase of exon model per Million mapped reads).

with IVO embryos. In previous studies, a low mRNA-protein correlation was thought to be caused by translational, translational and post-translational modifications.35,58−60 It is generally accepted that the process of ART can disrupt epigenetic modifications (e.g., methylation) during embryogenesis, resulting in changes in gene expression in IVP embryos. Here, we propose a hypothesis that based on the changed gene expression patterns, aberrant regulation at posttranscriptional, translational and post-translational levels may also contribute to, or even augment, the altered proteome in IVP embryos.

corresponding amino acids, which is extremely important for translational quality control.49 In this pathway, we also found some AARS, such as Nars (asparaginyl-tRNA synthetase), Iars (isoleucine-tRNA synthetase), and Vars (valyl-tRNA synthetase), were dysregulated at both E7.5 and E10.5. The expanded functions of tRNA synthetases are related to angiogenesis, inflammation and neuronal development,50 and aberrant aminoacyl-tRNA biosynthesis may mediate side-effects in these processes in IVP embryos. Ribosomes are the central workhorses of protein biosynthesis, the process of translating mRNA into protein. Our data also showed that numerous ribosomal proteins were dysregulated during the postimplantation period, which may lead to aberrant translational activity in IVP embryos. The dysregulated “aminoacyl-tRNA biosynthesis” and “ribosomes” pathways would likely lead to a specific or nonspecific aberration of the translation process, thereby altering protein abundance. The ubiquitin-proteasome system (UPS) is a nonlysosomal proteolysis system responsible for the degradation of irrelevant or misfolded intracellular proteins. The proteasome-dependent regulation of protein abundance plays a crucial role in both physiological and pathological processes.51 The proteasomal degradation pathway is essential for many cellular processes, including the cell cycle, cell specification, regulation of gene expression, neuronal differentiation and responses to oxidative stress.52 Previous studies have also demonstrated the participation of the proteasome in embryogenesis in many species.53−55 The dysregulation of the UPS also contributes to several diseases, including autoimmune, neurodegenerative, rheumatoid diseases and cancer.56,57 These novel findings were also confirmed by the genomic scale PCC analysis between protein abundances and mRNA expression in IVO and IVP embryos at E7.5 and E10.5. At both time points, IVP embryos showed a lower correlation compared

Alterations in Amino Acid and Energy Metabolism in IVP Embryos

It has been documented that metabolic defects of IVP embryos may lead to failed implantation.61 In the present study, embryos that survived after implantation also showed a continued abnormal metabolism. Both at E7.5 and E10.5, many DEPs were considerably enriched in GO categories and KEGG pathways associated with energy and amino acid metabolism. The two most represented GO terms were “primary metabolic processes” and “cellular metabolic processes”. At E7.5, the significantly enriched metabolism associated pathways included “citrate cycle (TCA cycle)”, “glycolysis/gluconeogenesis”, “arginine and proline metabolism”, “one carbon pool by folate”, and “valine, leucine, and isoleucine biosynthesis”. At E10.5, the significantly enriched metabolism associated pathways included “citrate cycle (TCA cycle)”, “glycolysis/gluconeogenesis”, “cysteine and methionine metabolism”, “glyoxylate and dicarboxylate metabolism”, “pyruvate metabolism”, and “tryptophan metabolism”. It should be noted that several of these pathways were dyregulated at both E7.5 and E10.5, suggesting that IVP embryo development was likely to be affected at this critical stage by the disturbance of metabolic processes, especially amino acid and energy metabolism. 3850

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Figure 6. Phenotypic comparison of IVO and IVP embryos. (A) Comparison of average embryonic weight at E7.5 and prenatal fetal weight at E19. Values are expressed as means ± SD, **P < 0.01. (B) Morphological comparison of IVO and IVP embryos collected and photographed at E7.5. (a) Representative normal IVO embryo. (b,c) Developmentally delayed IVP embryos in which the neural groove was not formed (b) or the amnion was not completely formed (c). (d) Representative abnormal IVP embryo showing disorganized embryo tissue and smaller size, with apparent arrested development at the egg-cylinder stage. (C) Histological comparison of IVO and IVP embryos. Serial sagittal sections of IVO embryos and IVP embryos at E7.5 were prepared and stained with H&E. (e) Representative IVO embryo clearly displaying the distinct germ layers and the three cavities. (f−h) IVP embryos showing delayed development and abnormal morphology. (f) Representative delayed IVP embryo characterized by the presence of anterior and posterior amniotic fold. (g) Morphologically disorganized embryo showing severely delayed growth characterized by the presence of the proamniotic cavity. (h) Embryo showing degenerated embryonic tissue. Abbreviations: EP, ectoplacental cone; EX, extra embryo; EM, embryo; epc, ectoplacental cone cavity; exc, exocoelomic cavity; ac, amniotic cavity; pac, proamniotic cavity; af, amniotic fold; al, allantois; am, amnion; ve, visceral endoderm; me, mesoderm; ec, ectoderm. Bar = 200 μm.

and even embryonic lethality (Supporting Information, Table S8). In addition, two energy metabolism associated pathways, “citrate cycle (TCA cycle)” and “glycolysis/gluconeogenesis” were disordered at both E7.5 and E10.5. In a recent metabonomic analysis of postnatal IUGR piglets, disruption of glycolysis and the TCA cycle was found to be tightly coupled with IUGR.71 During embryonic development, the glucose metabolism pattern transitions from the preferential utilization of the TCA cycle in preimplantation embryos to the predominant use of glycolysis to efficiently provide nutrients for proliferating cells in postimplantation embryos.72−74 It is likely that the IVP embryos experienced a disruption in the normal transition between these two metabolic states. To determine if the observed disturbance of amino acid and energy metabolism would lead to restricted growth of IVP embryos during postimplantation, the sampled embryos were weighed. Compared with IVO embryos, IVP embryos at E7.5

Epidemiological and cohort studies have confirmed that infants conceived with ART show an increased risk of embryonic intrauterine growth restriction (IUGR),62 low and very low birth weight63,64 and even perinatal mortality.64 IUGR is tightly associated with deficient fetal metabolism.65 According to our data, it is presumable that this deficiency could have originated during the postimplantation period and impaired both early and late embryonic growth. Shifts in amino acid transport capacity and metabolic pathways are associated with IUGR and consequent low birth weight and small body size.66 In particular, arginine deficiency plays a crucial role in IUGR, and L-arginine supplementation can prevent fetal growth retardation in humans,67 rats,68,69 and ewes.70 Moreover, using phenotype annotations in the Mouse Genome Informatics (MGI) database, we found many DEPs in metabolic pathways associated with abnormal phenotypes, such as reduced body/organ weight (size), impaired organogenesis, 3851

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Table 2. Functions of DEPs Showing Specific Deficiency or Down-Regulation at Both E7.5 and E10.5 in IVP Embryos E7.5

protein

full name

Dctn1 Slc16a1

phenotype

E10.5

Eif5a Cadm1 Ctsb

dynactin 1 solute carrier family 16 (monocarboxylic acid transporters), member 1 eukaryotic translation initiation factor 5A cell adhesion molecule 1 cathepsin B

down-regulation (>2-fold) at both E7.5 and E10.5

Dync1h1

dynein cytoplasmic 1 heavy chain 1

partially forms neural tube81 transport lactate into and out of neural cells;102,103 located in the retina, associated with convert the light signal to an electrical signal neuronal survival; neurite extension82 astrocyte proliferation; synapse formation83 turnover of β-amyloid in Alzheimer’s disease; neuronal vulnerability; associate with glial tissue84 axonal transport; age related progressive degeneration of the motor neurons85

metabolism has been linked to neural tube defects87 and several neurodegenerative conditions, including stroke, Alzheimer’s disease, and Parkinson’s disease.88,89 In this pathway, ATIC (5-aminoimidazole-4-carboxamide ribonucleotide formyltransferase/IMP cyclohydrolase) participates in purine and pyrimidine metabolism, the dysregulation of which is associated clinically with mental retardation and neurological dysfunction.90 MTHFD1L [methylenetetrahydrofolate dehydrogenase (NADP+ dependent) 1-like] is also associated with neural tube defects91,92 and Alzheimer disease.93 DEPs in our study were also found to be significantly enriched in pathways involved in pathology of NDs. These proteins were mainly involved in mitochondrial functions, which are crucial for embryonic neurogenesis,94 as well as maintenance of the energy supply for optimal neuronal function and homeostasis in the brain.95 It should be noted that dysregulated mitochondrial functions also participate in IUGR by leading to changes in glycolysis, oxidative phosphorylation, TCA cycle, and ATP production. Among the DEPs, Atp5a1 (ATP synthase, H+ transporting, mitochondrial F1 complex, alpha subunit 1) and Atp5b (ATP synthase, H+ transporting mitochondrial F1 complex, beta subunit) are primary components of F0F1-ATP synthase, which plays a central role in synthesis of the majority of ATP required in the brain96 and is believed to participate in the pathology of Alzheimer’s disease and Parkinson’s disease.97 Slc25a4 [solute carrier family 25 (mitochondrial carrier, adenine nucleotide translocator), member 4] and Slc25a5 [solute carrier family 25 (mitochondrial carrier, adenine nucleotide translocator), member 5] mobilize mitochondrial energy by exchanging mitochondrial ATP for cytosolic ADP.98 Mutations in Slc25a4 result in deleterious effects on mtDNA maintenance and integrity,99 which can later evolve into severe neurological syndromes, including sensory and cerebellar ataxia, peripheral neuropathy, parkinsonism, and depression.100 Yu et al. has indicated that blastomere biopsy of in vitro cultured preimplantation embryos would lead to an increased risk of NDs in adult offspring, and proteomic analysis of adult brains from biopsied mice has shown many DEPs associated with NDs.101 Thus, our results, for the first time, showed the dysregulation of many ND-associated proteins in IVP embryos at the very early stage of neurogenesis. These observations led us to speculate that IVP offspring are not only sensitive to postnatal neuroal defects but also may be more susceptible to NDs in adulthood.

clearly showed a lower weight (Figure 5A), and evidently more IVP embryos displayed a smaller size as well as morphological abnormalities (Figure 5B and C). Additionally, the average weight of IVP embryos remained lower than that of IVO embryos at E19, suggesting that embryonic growth was retarded throughout the pregnancy (Figure 5A). Our results suggest that the origins of IUGR of the IVP fetus are likely to be traced back to the changes in amino acid and glucose metabolism of postimplantation embryos, and the DEPs involved in these pathways, such as Vars, Iars, Adh5 [alcohol dehydrogenase 5 (class III), chi polypeptide], and Acly (ATP citrate lyase), may be preferential candidates for further investigation into the mechanism of IUGR. Compromised Neural and Sensory Development

During the postimplantation stage, embryos undergo key processes for the onset of neural and sensory development, including formation of the neural plate, closure of the neural tube, subdivision from the forebrain vesicle into telencephalic and diencephalic vesicles, and development of the optic pit and the lens pit.17 Previous epidemiological and cohort studies have indicated increased abnormal neural and sensory development in offspring conceived by ART, resulting in neural-tube defects,75 cerebral palsy,76−79 epilepsy,77 behavioral problems,77 mental developmental disturbances,79 as well as delayed early motor development.80 The proteomic data provided us with a reference for further exploring the molecular origins of these developmental defects. In the present study, several proteins involved in early neural and sensory development were found to be specifically deficient in IVP embryos. These proteins included Dctn1 (dynactin 1), Slc16a1 [solute carrier family 16 (monocarboxylic acid transporters), member 1], and Eif5a at E7.5, and Cadm1 [cell adhesion molecule 1) and Ctsb (cathepsin B)] at E10.5. In addition, Dync1h1 (dynein cytoplasmic 1 heavy chain 1) showed down-regulation (>2-fold change) at both E7.5 and E10.5. These proteins participate in processes of neurogenesis, including neural tube formation,81 neuronal survival, neurite extension,82 astrocyte proliferation, synapse formation,83 neuronal vulnerability,84 and axonal transport85 (Table 2). The lack of these proteins in IVP embryos suggests that impairments in early neurogenesis would probably predispose offspring to prenantal/postnatal defects in neural and sensory development. Moreover, many DEPs were enriched in KEGG pathways associated with early development of the nervous system, such as “one carbon pool by folate”, as well as several NDs, including “Huntington’s disease”, “Parkinson’s disease”, and “prion diseases”. Folates function as a family of metabolic cofactors that carry and chemically activate one-carbon units for a variety of anabolic and catabolic reactions collectively known as one carbon pool by folate.86 An impaired folate status or



CONCLUSION This comparative proteomic analysis between IVO and IVP embryos identified a considerable number of DEPs mainly associated with three functional clusters. In addition to the altered gene expression, modified post-transcriptional, transla3852

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Journal of Proteome Research tional, and post-translational processes probably also contribute to changes in protein abundance in IVP embryos. Furthermore, energy and amino acid metabolism as well as neural and sensory development are also disturbed, and it is likely that mitochondrial functions play key roles in these aberrations. Disturbed embryonic nutrition and energy utilization may lead to IUGR and other metabolic diseases. Abnormal early neural and sensory development, coupled with an abnormal energy supply in neural tissue may lead to neurodevelopmental disorders in children and predispose ART offspring to a potentially increased risk of NDs in adulthood (Figure 7).



REFERENCES

(1) Bergh, T.; Ericson, A.; Hillensjo, T.; Nygren, K. G.; Wennerholm, U. B. Deliveries and children born after in-vitro fertilisation in Sweden 1982−95: a retrospective cohort study. Lancet 1999, 354 (9190), 1579−1585. (2) Schieve, L. A.; Meikle, S. F.; Ferre, C.; Peterson, H. B.; Jeng, G.; Wilcox, L. S. Low and very low birth weight in infants conceived with use of assisted reproductive technology. N. Engl. J. Med. 2002, 346 (10), 731−737. (3) Reefhuis, J.; Honein, M. A.; Schieve, L. A.; Correa, A.; Hobbs, C. A.; Rasmussen, S. A. Assisted reproductive technology and major structural birth defects in the United States. Hum. Reprod. 2009, 24 (2), 360−366. (4) Ceelen, M.; van Weissenbruch, M. M.; Vermeiden, J. P.; van Leeuwen, F. E.; Delemarre-van, D. W. H. Growth and development of children born after in vitro fertilization. Fertil. Steril. 2008, 90 (5), 1662−1673. (5) Barker, D. J.; Osmond, C. Infant mortality, childhood nutrition, and ischaemic heart disease in England and Wales. Lancet 1986, 1 (8489), 1077−1081. (6) Giritharan, G.; Talbi, S.; Donjacour, A.; Di Sebastiano, F.; Dobson, A. T.; Rinaudo, P. F. Effect of in vitro fertilization on gene expression and development of mouse preimplantation embryos. Reproduction 2007, 134 (1), 63−72. (7) Wang, S.; Cowan, C. A.; Chipperfield, H.; Powers, R. D. Gene expression in the preimplantation embryo: in-vitro developmental changes. Reprod. BioMed. Online 2005, 10 (5), 607−616. (8) Riding, G. A.; Hill, J. R.; Jones, A.; Holland, M. K.; Josh, P. F.; Lehnert, S. A. Differential proteomic analysis of bovine conceptus fluid proteins in pregnancies generated by assisted reproductive technologies. Proteomics 2008, 8 (14), 2967−2982. (9) Smith, S. L.; Everts, R. E.; Sung, L. Y.; Du, F.; Page, R. L.; Henderson, B.; Rodriguez-Zas, S. L.; Nedambale, T. L.; Renard, J. P.; Lewin, H. A.; Yang, X.; Tian, X. C. Gene expression profiling of single bovine embryos uncovers significant effects of in vitro maturation, fertilization and culture. Mol. Reprod. Dev. 2009, 76 (1), 38−47. (10) Driver, A. M.; Penagaricano, F.; Huang, W.; Ahmad, K. R.; Hackbart, K. S.; Wiltbank, M. C.; Khatib, H. RNA-Seq analysis uncovers transcriptomic variations between morphologically similar in vivo- and in vitro-derived bovine blastocysts. BMC Genomics 2012, 13, 118. (11) Kepkova, K. V.; Vodicka, P.; Toralova, T.; Lopatarova, M.; Cech, S.; Dolezel, R.; Havlicek, V.; Besenfelder, U.; Kuzmany, A.; Sirard, M. A.; Laurincik, J.; Kanka, J. Transcriptomic analysis of in vivo and in vitro produced bovine embryos revealed a developmental change in cullin 1 expression during maternal-to-embryonic transition. Theriogenology 2011, 75 (9), 1582−1595. (12) Miles, J. R.; Blomberg, L. A.; Krisher, R. L.; Everts, R. E.; Sonstegard, T. S.; Van Tassell, C. P.; Zuelke, K. A. Comparative transcriptome analysis of in vivo- and in vitro-produced porcine blastocysts by small amplified RNA-serial analysis of gene expression (SAR-SAGE). Mol. Reprod. Dev. 2008, 75 (6), 976−988. (13) Gupta, M. K.; Jang, J. M.; Jung, J. W.; Uhm, S. J.; Kim, K. P.; Lee, H. T. Proteomic analysis of parthenogenetic and in vitro fertilized porcine embryos. Proteomics 2009, 9 (10), 2846−2860. (14) Clarke, H. J. Post-transcriptional Control of Gene Expression During Mouse Oogenesis. Results Probl. Cell Differ. 2012, 55, 1−21. (15) Potireddy, S.; Midic, U.; Liang, C. G.; Obradovic, Z.; Latham, K. E. Positive and negative cis-regulatory elements directing postfertiliza-

ASSOCIATED CONTENT

S Supporting Information *

All peptides identified in each sample are listed in Table S1. Lists of all proteins identified in each sample are shown in Tables S2−S5. Lists of DEPs in each comparison are shown in Tables S6 and S7. MGI Mouse genotype-phenotype annotations using DEPs in metabolic pathways are shown in Table S8. Correlated protein abundance and mRNA expression level are listed in Table 9. Figure S1 shows hierarchical clustering analyses based on DEPs at E7.5 and E10.5. Figure S2 shows the distribution of DEPs with different fold changes at E7.5 and E10.5. Figure S4 shows Pearson correlation coefficient between technique replicates on protein level in each group. This material is available free of charge via the Internet at http://pubs.acs.org.



ACKNOWLEDGMENTS

This work was supported by grants from the National HighTech R&D Program (Nos. 2011AA100303, 2013AA102506) and the National Key Technology R&D Program (Nos. 2011BAD19B01, 2011BAD19B03, 2011BAD19B04). We thank Dr. Chen She, National Institute of Biological Sciences for his technical assistance.

Figure 7. Summary of comparative proteomic profiles between IVO and IVP embryos. Observed functional clusters in the present study are highlighted in red text, while ART induced aberrations supported by epidemiological or cohort studies are in blue text. The gray dotted arrow points to a potentially increased risk of adult/late onset disease.





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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Fax: +86-10-62813558. Telephone: +86-10-62813558. Author Contributions §

J.N., L.A., and K.M. contributed equally to this work.

Notes

The authors declare no competing financial interest. 3853

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tion maternal mRNA translational control in mouse embryos. Am. J. Physiol. Cell Physiol. 2010, 299 (4), C818−C827. (16) Chandrakanthan, V.; Li, A.; Chami, O.; O’Neill, C. Effects of in vitro fertilization and embryo culture on TRP53 and Bax expression in B6 mouse embryos. Reprod. Biol. Endocrinol. 2006, 4, 61. (17) Theiler, K., The House Mouse: Atlas of Embryonic Development. Springer-Verlag: London Paris Tokyo, 1989. (18) Fauque, P.; Ripoche, M. A.; Tost, J.; Journot, L.; Gabory, A.; Busato, F.; Le Digarcher, A.; Mondon, F.; Gut, I.; Jouannet, P.; Vaiman, D.; Dandolo, L.; Jammes, H. Modulation of imprinted gene network in placenta results in normal development of in vitro manipulated mouse embryos. Hum. Mol. Genet. 2010, 19 (9), 1779− 1790. (19) Fauque, P.; Mondon, F.; Letourneur, F.; Ripoche, M. A.; Journot, L.; Barbaux, S.; Dandolo, L.; Patrat, C.; Wolf, J. P.; Jouannet, P.; Jammes, H.; Vaiman, D. In vitro fertilization and embryo culture strongly impact the placental transcriptome in the mouse model. PLoS One 2010, 5 (2), e9218. (20) Li, T.; Vu, T. H.; Ulaner, G. A.; Littman, E.; Ling, J. Q.; Chen, H. L.; Hu, J. F.; Behr, B.; Giudice, L.; Hoffman, A. R. IVF results in de novo DNA methylation and histone methylation at an Igf2-H19 imprinting epigenetic switch. Mol. Hum. Reprod. 2005, 11 (9), 631− 640. (21) Nagy, A., Manipulating the mouse embryo:a laboratory manual. 3rd ed. ed.; Cold Spring Harbor Laboratory Press: Cold Spring Harbor, N.Y., 2003; p 764. (22) Kepkova, K. V.; Vodicka, P.; Toralova, T.; Lopatarova, M.; Cech, S.; Dolezel, R.; Havlicek, V.; Besenfelder, U.; Kuzmany, A.; Sirard, M. A.; Laurincik, J.; Kanka, J. Transcriptomic analysis of in vivo and in vitro produced bovine embryos revealed a developmental change in cullin 1 expression during maternal-to-embryonic transition. Theriogenology 2011, 75 (9), 1582−1595. (23) Huang, W.; Khatib, H. Comparison of transcriptomic landscapes of bovine embryos using RNA-Seq. BMC Genomics 2010, 11, 711. (24) Gupta, M. K.; Jang, J. M.; Jung, J. W.; Uhm, S. J.; Kim, K. P.; Lee, H. T. Proteomic analysis of parthenogenetic and in vitro fertilized porcine embryos. Proteomics 2009, 9 (10), 2846−2860. (25) Driver, A. M.; Penagaricano, F.; Huang, W.; Ahmad, K. R.; Hackbart, K. S.; Wiltbank, M. C.; Khatib, H. RNA-Seq analysis uncovers transcriptomic variations between morphologically similar in vivo- and in vitro-derived bovine blastocysts. BMC Genomics 2012, 13, 118. (26) Karp, N. A.; Spencer, M.; Lindsay, H.; O’Dell, K.; Lilley, K. S. Impact of replicate types on proteomic expression analysis. J. Proteome Res. 2005, 4 (5), 1867−1871. (27) Delle, P. L.; Lin, W.; Liu, X.; Donjacour, A.; Minasi, P.; Revelli, A.; Maltepe, E.; Rinaudo, P. F. Effect of the method of conception and embryo transfer procedure on mid-gestation placenta and fetal development in an IVF mouse model. Hum. Reprod. 2010, 25 (8), 2039−2046. (28) Fernandez-Gonzalez, R.; de Dios, H. J.; Lopez-Vidriero, I.; Benguria, A.; De Fonseca, F. R.; Gutierrez-Adan, A. Analysis of gene transcription alterations at the blastocyst stage related to the long-term consequences of in vitro culture in mice. Reproduction 2009, 137 (2), 271−283. (29) Rivera, R. M.; Stein, P.; Weaver, J. R.; Mager, J.; Schultz, R. M.; Bartolomei, M. S. Manipulations of mouse embryos prior to implantation result in aberrant expression of imprinted genes on day 9.5 of development. Hum. Mol. Genet. 2008, 17 (1), 1−14. (30) Giritharan, G.; Talbi, S.; Donjacour, A.; Di Sebastiano, F.; Dobson, A. T.; Rinaudo, P. F. Effect of in vitro fertilization on gene expression and development of mouse preimplantation embryos. Reproduction 2007, 134 (1), 63−72. (31) Downs, K. M.; Davies, T. Staging of gastrulating mouse embryos by morphological landmarks in the dissecting microscope. Development 1993, 118 (4), 1255−1266. (32) Theiler, K. The house mouse: atlas of embryonic development; Springer-Verlag: New York, 1989; p 178.

(33) Cox, J.; Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 2008, 26 (12), 1367−1372. (34) Cox, J.; Neuhauser, N.; Michalski, A.; Scheltema, R. A.; Olsen, J. V.; Mann, M. Andromeda: a peptide search engine integrated into the MaxQuant environment. J. Proteome Res. 2011, 10 (4), 1794−1805. (35) Gry, M.; Rimini, R.; Stromberg, S.; Asplund, A.; Ponten, F.; Uhlen, M.; Nilsson, P. Correlations between RNA and protein expression profiles in 23 human cell lines. BMC Genomics 2009, 10, 365. (36) Ghazalpour, A.; Bennett, B.; Petyuk, V. A.; Orozco, L.; Hagopian, R.; Mungrue, I. N.; Farber, C. R.; Sinsheimer, J.; Kang, H. M.; Furlotte, N.; Park, C. C.; Wen, P. Z.; Brewer, H.; Weitz, K.; Camp, D. N.; Pan, C.; Yordanova, R.; Neuhaus, I.; Tilford, C.; Siemers, N.; Gargalovic, P.; Eskin, E.; Kirchgessner, T.; Smith, D. J.; Smith, R. D.; Lusis, A. J. Comparative analysis of proteome and transcriptome variation in mouse. PLoS Genet. 2011, 7 (6), e1001393. (37) Huttlin, E. L.; Chen, X.; Barrett-Wilt, G. A.; Hegeman, A. D.; Halberg, R. B.; Harms, A. C.; Newton, M. A.; Dove, W. F.; Sussman, M. R. Discovery and validation of colonic tumor-associated proteins via metabolic labeling and stable isotopic dilution. Proc. Natl. Acad. Sci. U.S.A. 2009, 106 (40), 17235−17240. (38) Yang, L. Y.; Tao, Y. M.; Ou, D. P.; Wang, W.; Chang, Z. G.; Wu, F. Increased expression of Wiskott-Aldrich syndrome protein family verprolin-homologous protein 2 correlated with poor prognosis of hepatocellular carcinoma. Clin. Cancer Res. 2006, 12 (19), 5673−5679. (39) Cui, X.; Churchill, G. A. Statistical tests for differential expression in cDNA microarray experiments. GenomeBiology 2003, 4 (4), 210. (40) Churchill, G. A. Fundamentals of experimental design for cDNA microarrays. Nat. Genet. 2002, 32 (Suppl), 490−495. (41) Barker, D. J.; Eriksson, J. G.; Forsen, T.; Osmond, C. Fetal origins of adult disease: strength of effects and biological basis. Int. J. Epidemiol. 2002, 31 (6), 1235−1239. (42) Chen, Q.; Zhang, Y.; Peng, H.; Lei, L.; Kuang, H.; Zhang, L.; Ning, L.; Cao, Y.; Duan, E. Transient {beta}2-adrenoceptor activation confers pregnancy loss by disrupting embryo spacing at implantation. J. Biol. Chem. 2011, 286 (6), 4349−4356. (43) Smith, Z. D.; Chan, M. M.; Mikkelsen, T. S.; Gu, H.; Gnirke, A.; Regev, A.; Meissner, A. A unique regulatory phase of DNA methylation in the early mammalian embryo. Nature 2012, 484 (7394), 339−344. (44) Borgel, J.; Guibert, S.; Li, Y.; Chiba, H.; Schubeler, D.; Sasaki, H.; Forne, T.; Weber, M. Targets and dynamics of promoter DNA methylation during early mouse development. Nat. Genet. 2010, 42 (12), 1093−1100. (45) Genome, S. C. I. H. Initial sequencing and analysis of the human genome. Nature 2001, 409 (6822), 860−921. (46) Will, C. L.; Luhrmann, R. Spliceosome structure and function. Cold Spring Harb. Perspect. Biol. 2011, 3 (7), a006707. (47) Lee, S. W.; Cho, B. H.; Park, S. G.; Kim, S. Aminoacyl-tRNA synthetase complexes: beyond translation. J. Cell Sci. 2004, 117 (Pt 17), 3725−3734. (48) Antonellis, A.; Green, E. D. The role of aminoacyl-tRNA synthetases in genetic diseases. Annu. Rev. Genomics Hum. Genet. 2008, 9, 87−107. (49) Ling, J.; Reynolds, N.; Ibba, M. Aminoacyl-tRNA synthesis and translational quality control. Annu. Rev. Microbiol. 2009, 63, 61−78. (50) Yang, X. L.; Kapoor, M.; Otero, F. J.; Slike, B. M.; Tsuruta, H.; Frausto, R.; Bates, A.; Ewalt, K. L.; Cheresh, D. A.; Schimmel, P. Gainof-function mutational activation of human tRNA synthetase procytokine. Chem. Biol. 2007, 14 (12), 1323−1333. (51) Lecker, S. H.; Goldberg, A. L.; Mitch, W. E. Protein degradation by the ubiquitin-proteasome pathway in normal and disease states. J. Am. Soc. Nephrol. 2006, 17 (7), 1807−1819. (52) Tuoc, T. C.; Stoykova, A. Roles of the ubiquitin-proteosome system in neurogenesis. Cell Cycle 2010, 9 (16), 3174−3180. 3854

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Journal of Proteome Research

Article

(74) Dumollard, R.; Carroll, J.; Duchen, M. R.; Campbell, K.; Swann, K. Mitochondrial function and redox state in mammalian embryos. Semin Cell Dev. Biol. 2009, 20 (3), 346−353. (75) Bergh, T.; Ericson, A.; Hillensjo, T.; Nygren, K. G.; Wennerholm, U. B. Deliveries and children born after in-vitro fertilisation in Sweden 1982−95: a retrospective cohort study. Lancet 1999, 354 (9190), 1579−1585. (76) Hvidtjorn, D.; Grove, J.; Schendel, D. E.; Vaeth, M.; Ernst, E.; Nielsen, L. F.; Thorsen, P. Cerebral palsy among children born after in vitro fertilization: the role of preterm delivery–a population-based, cohort study. Pediatrics 2006, 118 (2), 475−482. (77) Kallen, B.; Finnstrom, O.; Nygren, K. G.; Olausson, P. O. In vitro fertilization in Sweden: child morbidity including cancer risk. Fertil. Steril. 2005, 84 (3), 605−610. (78) Stromberg, B.; Dahlquist, G.; Ericson, A.; Finnstrom, O.; Koster, M.; Stjernqvist, K. Neurological sequelae in children born after in-vitro fertilisation: a population-based study. Lancet 2002, 359 (9305), 461− 465. (79) Pinborg, A.; Loft, A.; Schmidt, L.; Greisen, G.; Rasmussen, S.; Andersen, A. N. Neurological sequelae in twins born after assisted conception: controlled national cohort study. BMJ 2004, 329 (7461), 311. (80) Zhu, J. L.; Obel, C.; Basso, O.; Olsen, J. Parental infertility and developmental coordination disorder in children. Hum. Reprod. 2010, 25 (4), 908−913. (81) Lai, C.; Lin, X.; Chandran, J.; Shim, H.; Yang, W. J.; Cai, H. The G59S mutation in p150(glued) causes dysfunction of dynactin in mice. J. Neurosci. 2007, 27 (51), 13982−90. (82) Park, M. H.; Nishimura, K.; Zanelli, C. F.; Valentini, S. R. Functional significance of eIF5A and its hypusine modification in eukaryotes. Amino Acids 2010, 38 (2), 491−500. (83) Yamada, D.; Yoshida, M.; Williams, Y. N.; Fukami, T.; Kikuchi, S.; Masuda, M.; Maruyama, T.; Ohta, T.; Nakae, D.; Maekawa, A.; Kitamura, T.; Murakami, Y. Disruption of spermatogenic cell adhesion and male infertility in mice lacking TSLC1/IGSF4, an immunoglobulin superfamily cell adhesion molecule. Mol. Cell. Biol. 2006, 26 (9), 3610−3624. (84) Felbor, U.; Kessler, B.; Mothes, W.; Goebel, H. H.; Ploegh, H. L.; Bronson, R. T.; Olsen, B. R. Neuronal loss and brain atrophy in mice lacking cathepsins B and L. Proc. Natl. Acad. Sci. U.S.A. 2002, 99 (12), 7883−7888. (85) Kuzma-Kozakiewicz, M.; Usarek, E.; Ludolph, A. C.; BaranczykKuzma, A. Mice with mutation in dynein heavy chain 1 do not share the same tau expression pattern with mice with SOD1-related motor neuron disease. Neurochem. Res. 2011, 36 (6), 978−985. (86) Beaudin, A. E.; Stover, P. J. Insights into metabolic mechanisms underlying folate-responsive neural tube defects: a minireview. Birth Defects Res., Part A 2009, 85 (4), 274−284. (87) Beaudin, A. E.; Stover, P. J. Folate-mediated one-carbon metabolism and neural tube defects: balancing genome synthesis and gene expression. Birth Defects Res. Part C 2007, 81 (3), 183−203. (88) van der Put, N. M.; van Straaten, H. W.; Trijbels, F. J.; Blom, H. J. Folate, homocysteine and neural tube defects: an overview. Exp. Biol. Med. (Maywood) 2001, 226 (4), 243−270. (89) Faux, N. G.; Ellis, K. A.; Porter, L.; Fowler, C. J.; Laws, S. M.; Martins, R. N.; Pertile, K. K.; Rembach, A.; Rowe, C. C.; Rumble, R. L.; Szoeke, C.; Taddei, K.; Taddei, T.; Trounson, B. O.; Villemagne, V. L.; Ward, V.; Ames, D.; Masters, C. L.; Bush, A. I. Homocysteine, vitamin B12, and folic acid levels in Alzheimer's disease, mild cognitive impairment, and healthy elderly: baseline characteristics in subjects of the Australian Imaging Biomarker Lifestyle study. J. Alzheimers. Dis. 2011, 27 (4), 909−922. (90) Micheli, V.; Camici, M.; Tozzi, M. G.; Ipata, P. L.; Sestini, S.; Bertelli, M.; Pompucci, G. Neurological disorders of purine and pyrimidine metabolism. Curr. Top. Med. Chem. 2011, 11 (8), 923−947. (91) Pike, S. T.; Rajendra, R.; Artzt, K.; Appling, D. R. Mitochondrial C1-tetrahydrofolate synthase (MTHFD1L) supports the flow of mitochondrial one-carbon units into the methyl cycle in embryos. J. Biol. Chem. 2010, 285 (7), 4612−4620.

(53) Wojcik, C.; Benchaib, M.; Lornage, J.; Czyba, J. C.; Guerin, J. F. Localization of proteasomes in human oocytes and preimplantation embryos. Mol. Hum. Reprod. 2000, 6 (4), 331−336. (54) Klein, U.; Gernold, M.; Kloetzel, P. M. Cell-specific accumulation of Drosophila proteasomes (MCP) during early development. J. Cell Biol. 1990, 111 (6 Pt 1), 2275−2282. (55) Iijima, R.; Homma, K. J.; Natori, S. Participation of proteasomes in Xenopus embryogenesis. J. Biochem. 2003, 134 (3), 467−471. (56) Ciechanover, A.; Brundin, P. The ubiquitin proteasome system in neurodegenerative diseases: sometimes the chicken, sometimes the egg. Neuron 2003, 40 (2), 427−446. (57) Dahlmann, B. Role of proteasomes in disease. BMC Biochem. 2007, 8 (Suppl 1), S3. (58) Greenbaum, D.; Colangelo, C.; Williams, K.; Gerstein, M. Comparing protein abundance and mRNA expression levels on a genomic scale. Genome Biol. 2003, 4 (9), 117. (59) Pascal, L. E.; True, L. D.; Campbell, D. S.; Deutsch, E. W.; Risk, M.; Coleman, I. M.; Eichner, L. J.; Nelson, P. S.; Liu, A. Y. Correlation of mRNA and protein levels: cell type-specific gene expression of cluster designation antigens in the prostate. BMC Genomics 2008, 9, 246. (60) Chen, G.; Gharib, T. G.; Huang, C. C.; Taylor, J. M.; Misek, D. E.; Kardia, S. L.; Giordano, T. J.; Iannettoni, M. D.; Orringer, M. B.; Hanash, S. M.; Beer, D. G. Discordant protein and mRNA expression in lung adenocarcinomas. Mol. Cell. Proteomics 2002, 1 (4), 304−313. (61) Macas, E. Metabolic status of oocyte and IVF success C ̈ is there a relationship? J Fertilität Reproduktion 2006, 16, 16−18. (62) Yovich, J. L.; Parry, T. S.; French, N. P.; Grauaug, A. A. Developmental assessment of twenty in vitro fertilization (IVF) infants at their first birthday. J. In Vitro Fert. Embryo Transf. 1986, 3 (4), 253− 257. (63) Schieve, L. A.; Meikle, S. F.; Ferre, C.; Peterson, H. B.; Jeng, G.; Wilcox, L. S. Low and very low birth weight in infants conceived with use of assisted reproductive technology. N. Engl. J. Med. 2002, 346 (10), 731−717. (64) Bergh, T.; Ericson, A.; Hillensjo, T.; Nygren, K. G.; Wennerholm, U. B. Deliveries and children born after in-vitro fertilisation in Sweden 1982−95: a retrospective cohort study. Lancet 1999, 354 (9190), 1579−1585. (65) Wu, G.; Bazer, F. W.; Cudd, T. A.; Meininger, C. J.; Spencer, T. E. Maternal nutrition and fetal development. J. Nutr. 2004, 134 (9), 2169−2172. (66) Hay, W. J. Recent observations on the regulation of fetal metabolism by glucose. J. Physiol. 2006, 572 (Pt 1), 17−24. (67) Xiao, X. M.; Li, L. P. L-Arginine treatment for asymmetric fetal growth restriction. Int. J. Gynaecol. Obstet. 2005, 88 (1), 15−18. (68) Vosatka, R. J.; Hassoun, P. M.; Harvey-Wilkes, K. B. Dietary Larginine prevents fetal growth restriction in rats. Am. J. Obstet. Gynecol. 1998, 178 (2), 242−246. (69) Helmbrecht, G. D.; Farhat, M. Y.; Lochbaum, L.; Brown, H. E.; Yadgarova, K. T.; Eglinton, G. S.; Ramwell, P. W. L-arginine reverses the adverse pregnancy changes induced by nitric oxide synthase inhibition in the rat. Am. J. Obstet. Gynecol. 1996, 175 (4 Pt 1), 800− 805. (70) Lassala, A.; Bazer, F. W.; Cudd, T. A.; Datta, S.; Keisler, D. H.; Satterfield, M. C.; Spencer, T. E.; Wu, G. Parenteral administration of L-arginine prevents fetal growth restriction in undernourished ewes. J. Nutr. 2010, 140 (7), 1242−1248. (71) He, Q.; Ren, P.; Kong, X.; Xu, W.; Tang, H.; Yin, Y.; Wang, Y. Intrauterine growth restriction alters the metabonome of the serum and jejunum in piglets. Mol. BioSyst. 2011, 7 (7), 2147−2155. (72) Wakefield, S. L.; Lane, M.; Mitchell, M. Impaired mitochondrial function in the preimplantation embryo perturbs fetal and placental development in the mouse. Biol. Reprod. 2011, 84 (3), 572−580. (73) Vander, H. M.; Locasale, J. W.; Swanson, K. D.; Sharfi, H.; Heffron, G. J.; Amador-Noguez, D.; Christofk, H. R.; Wagner, G.; Rabinowitz, J. D.; Asara, J. M.; Cantley, L. C. Evidence for an alternative glycolytic pathway in rapidly proliferating cells. Science 2010, 329 (5998), 1492−1499. 3855

dx.doi.org/10.1021/pr301044b | J. Proteome Res. 2013, 12, 3843−3856

Journal of Proteome Research

Article

(92) Parle-McDermott, A.; Pangilinan, F.; O’Brien, K. K.; Mills, J. L.; Magee, A. M.; Troendle, J.; Sutton, M.; Scott, J. M.; Kirke, P. N.; Molloy, A. M.; Brody, L. C. A common variant in MTHFD1L is associated with neural tube defects and mRNA splicing efficiency. Hum. Mutat. 2009, 30 (12), 1650−1656. (93) Naj, A. C.; Beecham, G. W.; Martin, E. R.; Gallins, P. J.; Powell, E. H.; Konidari, I.; Whitehead, P. L.; Cai, G.; Haroutunian, V.; Scott, W. K.; Vance, J. M.; Slifer, M. A.; Gwirtsman, H. E.; Gilbert, J. R.; Haines, J. L.; Buxbaum, J. D.; Pericak-Vance, M. A. Dementia revealed: novel chromosome 6 locus for late-onset Alzheimer disease provides genetic evidence for folate-pathway abnormalities. PLoS Genet. 2010, 6 (9), e1001130. (94) Song, Y.; Selak, M. A.; Watson, C. T.; Coutts, C.; Scherer, P. C.; Panzer, J. A.; Gibbs, S.; Scott, M. O.; Willer, G.; Gregg, R. G.; Ali, D. W.; Bennett, M. J.; Balice-Gordon, R. J. Mechanisms underlying metabolic and neural defects in zebrafish and human multiple acylCoA dehydrogenase deficiency (MADD). PLoS One 2009, 4 (12), e8329. (95) Harish, G.; Venkateshappa, C.; Mahadevan, A.; Pruthi, N.; Bharath, M. M.; Shankar, S. K. Mitochondrial function in human brains is affected by pre and postmortem factors. Neuropathol. Appl. Neurobiol. 2013, 39, 298−315. (96) Zhao, L.; Morgan, T. E.; Mao, Z.; Lin, S.; Cadenas, E.; Finch, C. E.; Pike, C. J.; Mack, W. J.; Brinton, R. D. Continuous versus cyclic progesterone exposure differentially regulates hippocampal gene expression and functional profiles. PLoS One 2012, 7 (2), e31267. (97) Wang, H. Q.; Xu, Y. X.; Zhao, X. Y.; Zhao, H.; Yan, J.; Sun, X. B.; Guo, J. C.; Zhu, C. Q. Overexpression of F(0)F(1)-ATP synthase alpha suppresses mutant huntingtin aggregation and toxicity in vitro. Biochem. Biophys. Res. Commun. 2009, 390 (4), 1294−1298. (98) Buck, C. R.; Jurynec, M. J.; Gupta, D. K.; Law, A. K.; Bilger, J.; Wallace, D. C.; McKeon, R. J. Increased adenine nucleotide translocator 1 in reactive astrocytes facilitates glutamate transport. Exp. Neurol. 2003, 181 (2), 149−158. (99) Lamperti, C.; Zeviani, M. Encephalomyopathies caused by abnormal nuclear-mitochondrial intergenomic cross-talk. Acta Myol. 2009, 28 (1), 2−11. (100) Galassi, G.; Lamantea, E.; Invernizzi, F.; Tavani, F.; Pisano, I.; Ferrero, I.; Palmieri, L.; Zeviani, M. Additive effects of POLG1 and ANT1 mutations in a complex encephalomyopathy. Neuromuscul Disord. 2008, 18 (6), 465−470. (101) Yu, Y.; Wu, J.; Fan, Y.; Lv, Z.; Guo, X.; Zhao, C.; Zhou, R.; Zhang, Z.; Wang, F.; Xiao, M.; Chen, L.; Zhu, H.; Chen, W.; Lin, M.; Liu, J.; Zhou, Z.; Wang, L.; Huo, R.; Zhou, Q.; Sha, J. Evaluation of blastomere biopsy using a mouse model indicates the potential high risk of neurodegenerative disorders in the offspring. Mol. Cell Proteomics 2009, 8 (7), 1490−1500. (102) Simpson, I. A.; Carruthers, A.; Vannucci, S. J. Supply and demand in cerebral energy metabolism: the role of nutrient transporters. J. Cereb. Blood Flow Metab. 2007, 27 (11), 1766−1791. (103) Kleene, R.; Loers, G.; Langer, J.; Frobert, Y.; Buck, F.; Schachner, M. Prion protein regulates glutamate-dependent lactate transport of astrocytes. J. Neurosci. 2007, 27 (45), 12331−12340.

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