CORO1A and DNM2 in Serum Exosomes as Biomarkers of Neural Tube Defects

doi:10.21203/rs.3.rs-1294965/v1

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CORO1A and DNM2 in Serum Exosomes as Biomarkers of Neural Tube Defects

https://doi.org/10.21203/rs.3.rs-1294965/v1

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A highly specific and sensitive biomarker in maternal serology analysis for early diagnosis of neural tube defects (NTDs) is yet to be determined. Proteomics was utilized to identify novel specific proteins for NTDs and it revealed three differentially expressed proteins in fetal development. In a rat model with NTDs, we quantified proteins in maternal serum exosomes using western blotting on gestational days E18, E16, E14, and E12; in serum on E18 and E12; in neural tubes on E18 and E12; and in fetal neural exosomes on E18. Coronin 1A and Dynamin 2 expressions were exosome-specific and associated with spina bifida aperta embryogenesis and were proved to be downregulated in maternal serum exosomes from E12 to E18, in neural tubes and fetal neural exosomes with statistical difference, and in serum with no difference. Differentially expressed proteins were further analyzed in the serum exosomes of pregnant women during gestational weeks 12–40 using ELISA. Coronin 1A and Dynamin 2 were demonstrated to possess good diagnostic efficacy during gestation weeks 12–40, particularly during early gestation (12–18 weeks), and may be used as potential NTD screening and diagnostic biomarkers during early gestation.

neural tube defects

spina bifida

prenatal diagnosis

biomarker

proteomics

exosome

Neural tube defects (NTDs) are common congenital malformations that cause severe damage to the fetus as a result of the failure of neural tube closure at 21−28 days after conception for human fetus.[1] Spina bifida aperta (SBA) is one of the most common types of NTDs that presents with urinary and neurological complications.[2] Moreover, the follow-up therapy after surgery may be present lifelong and require medical support.[3]

Currently, ultrasound is one of the most powerful diagnostic tools for NTDs;[4] however, it is less effective in general practice on low-risk pregnancies for identifying open spina bifida, especially during the first trimester,[5] as NTDs are only detected after complete defect formation. The American Congress of Obstetricians and Gynecologists recommends maternal serum alpha-fetoprotein (MSAFP) screening and specialized ultrasound examination to be offered to all pregnant women and those found at high risk for NTDs to identify the defect, respectively.[6] However, MSAFP detection rate is only between 65% and 80% using a 2.5 MoM cut-off level, as it is influenced by many factors.[7] Elevated MSAFP can also be caused by fetal abdominal wall defects, congenital kidney disease, fetal death, placenta accreta, preeclampsia, oligohydramnios, etc.[8, 9] We previously combined the analysis of serum complements (including C1QA, C1S, and C3) and MSAFP to overcome the shortcomings of AFP analysis and improve the sensitivity and specificity of NTD screening.[10] Prenatal molecular biomarkers have the potential to help early screening, diagnosis and intervention. Therefore, finding more specific and sensitive maternal serum biomarkers can help screening for NTDs in decentralized healthcare systems for the general population of pregnant women during early gestation.

Extracellular vesicles (EVs) can pack and preserve proteins, RNA, and DNA; enrich and transfer informative factors with more specificity; and are not easily degraded in bodily fluids.[11] Exosomes can transfer informative factors to target cells with high specificity during pregnancy,[12] as they are proven to be more stable than the other types of EVs.[13] They can be detected at gestational week 6 at higher levels,[14] and their contents also change in pathological pregnancies.[15] They are found in placenta[16] and amniotic fluid[17] and can transfer to the maternal side.[18] Approximately 35% of total maternal exosomes are fetal.[19] Furthermore, studies have shown that fetal neural exosomes (FNEs) change when exposed to ethyl alcohol.[20, 21] Therefore, exosomes possibly carry specific molecular biomarkers from fetus to mother, which may have potential applications in prenatal screening and diagnosis.

Proteomics is a powerful tool that can identify specific biomarkers of NTDs and their underlying molecular mechanisms in relevant animal models and clinical samples.[22] We previously found 14-3-3ζ present distinctly in fetal neural tubes,[23] APOA4 and AFP fragment changes in amniotic fluid [24], and PCSK9 changes in serum [25]. However, differentially expressed exosomal proteins as diagnostic biomarkers of NTDs are yet to be established. Here, we used proteomics and bioinformatics to screen enriched proteins in maternal serum exosomes as potential SBA biomarkers.

Clinical sample collection

Serum samples of pregnant women were collected from the biological specimen bank of the Shengjing Birth Cohort in Key Laboratory of Health Ministry for Congenital Malformation. A total of 19 pregnant women were diagnosed as carrying fetuses with NTDs using prenatal ultrasound and confirmed via autopsy after induced labor or physical examination after delivery. Serum samples of gestational age- and maternal age-matched controls were from pregnant women (n = 19) carrying normal fetuses without any abnormalities. Every pregnant woman consumed folic acid regularly under guidance during pregnancy. The clinical characteristics of the subjects are summarized in Supplemental Data 1.

Animal sample collection

SBA was induced in Wistar rats with all-trans-retinoic acid (atRA, Sigma; 4% [wt/vol] in olive oil; 140 mg/kg body weight) at E10 (vaginal smear found sperm as E0) by gavage, and normal controls were treated with the same volume of oil, as described in previous experiments from our research group.[24, 26] animals were anesthetized with isoflurane, and the euthanasia was carried out in the CO₂ box. All animal experimental protocols were approved by the Medical Ethics Committee of the Shengjing Hospital of China Medical University.

Fetal deformities were examined using stereomicroscopy (Leica M165 FC, typical figures in Supplemental Figure S1). Blood samples were collected into vacuum tubes (BD Vacutainer^® SST™) for serum sampling. Serum samples were collected by pairing normal-SBA with E12 (n = 24), E14 (n = 12), E16 (n = 12), and E18 (n = 50) pregnant rats. We also collected 12 specially treated E18 samples to clarify whether atRA alone affects biomarker changes in pregnant rats, including normal (n = 3) samples treated with oil as the normal group; without SBA (n = 3) samples treated with 140 mg/kg atRA; SBA (n = 3) samples treated with 140 mg/kg atRA as SBA group 1; and SBA (n = 3) samples treated with 110 mg/kg atRA as SBA group 2 (Supplemental Table 1). The foetal posterior spinal cords were isolated from the 11^th somite pair to the tail ends. Samples were stored at -80°C, except tissues used for immunohistochemistry, which were preserved in 4% paraformaldehyde and then embedded in paraffin.

Total serum exosome extraction and characterization

A 200 μL aliquot of each serum adjusted to 3 mL with PBS were utilised for extraction. The diluted serum was filtered through a 0.22 μm filter (MILLEX^®GP, Millipore Express^® PES Membrane). The filtered sample was centrifuged (Micro Ultracentrifuge CS120FNX, Hitachi Koki Co., Ltd.) at 10,000 × g, 4 °C for 1 h, following which the supernatant was transferred to a fresh tube and centrifuged at 100,000 × g, 4 °C for 4 h. The pellet was resuspended in 100 µL PBS and preserved at -80°C. Characterization of extracted exosomes was confirmed by transmission electron microscope (TEM, HT7800 TEM, HITACHI), dynamic light scattering (DLS, Nano ZS90, Malvern Instruments, UK) and exosomal biomarkers (Alix, CD63 and CD9) (characterization results in Supplemental Figure 2).

FNE isolation

Exosomes from fetal neural sources were isolated as previously described.[21, 22] Briefly, 400 µL of sample was incubated for 90 min at 20°C with 50 µL of 3% bovine serum albumin (BSA, Solarbio^®) containing 2 µg polyclonal goat IgG anti-rat Contactin-2/TAG1 antibody (AF4439, R&D Systems, Inc.) that had been biotinylated (EZ-Link sulfo-NHS-biotin System, Thermo Scientific, Inc.). Then, 10 µL Streptavidin-Plus UltraLink resin (Pierce-Thermo Scientific, Inc.) in 40 µL 3% BSA was added. After centrifugation, the supernatant was transferred to Eppendorf tube and stored at -80°C.

LC-MS/MS (label-free) for potential biomarker screening

A total of three pairs of E18 samples were screened for potential biomarkers using label-free LC-MS/MS.[27, 28] Samples were first subjected to immunoaffinity depletion of high-abundance serum proteins. Then a total of 200 μg protein for each sample was processed by filter-aided sample preparation digestion. The peptide content was estimated by UV spectral density at 280 nm, calculated based on the frequency of tryptophan and tyrosine in vertebrate proteins.[28]Each fraction was then injected for nanoLC-MS/MS analysis. The peptide mixture was separated with a linear gradient controlled by IntelliFlow technology. LC-MS/MS analysis was performed on a Q Exactive mass spectrometer (Thermo Scientific) coupled to an Easy nLC (Proxeon Biosystems). The MS data were analysed using the MaxQuant software version 1.5.3.17 (Max Planck Institute of Biochemistry, Martinsried, Germany).[29]

Bioinformatics analysis

Bioinformatics analysis was carried out on WebGestalt (http://www.webgestalt.org/) using over-representation analysis (ORA) in Rattus norvegicus for enrichment with the gene ontology (GO) biological process functional database. The significance level in the advanced parameters was adjusted to FDR < 0.05. The proteins contained in the enrichment processes were further analysed using the String database (https://string-db.org/) to define protein interaction networks.

Western blotting

Exosomes and spinal cord specimen were treated with 20 µL RIPA buffer per 100 µL samples, followed by ultrasound pyrolysis. The supernatant was collected as proteins. Samples were quantitated using a BCA Protein Assay Kit (Solarbio®) and concentrations were adjusted using PBS. The diluted samples were mixed with loading buffer and degenerated, then separated on Bio-Rad gels and transferred to 0.45 μm PVDF membranes. The primary antibodies used were Alix (3A9 mouse mAb, Cell Signalling Technology®, exosome internal reference), CD9 (D3H4P rabbit mAb, Cell Signalling Technology®), CD63 (TS63 mouse mAb, Abcam), β-actin (66009-1-Ig rabbit mAb, Proteintech™, neural tube internal reference) and ACTR2 (10922-1-AP rabbit pAb, Proteintech™), CORO1A (EPR19467-36 rabbit mAb, Abcam), and DNM2 (EPR9053 rabbit mAb, Abcam). The secondary antibodies used were Goat anti-Mouse (G-21040, Invitrogen) or Goat anti-Rabbit (G-21234, Invitrogen). Fast-staining Coomassie Brilliant Blue (Solarbio®) served as an internal reference for serum. Bands were visualized using chemiluminescent HRP substrate (Immobilon®) and captured on cSeries 300 (Azure Biosystems). While the figures in manuscript only displayed 4 typical bands of Western blotting analysis, statistical analysis counted all samples tested which showed completely in supplemental figures (raw data of bands) and were described in figure legends.

Immunohistochemistry staining

The UltraSensitive™ SP Kit (MXB^®Biotechnologies) was used for immunohistochemistry, processed according to the manufacturer’s protocol. The primary antibodies were the same ones used for western blotting. Sections were washed in PBS between each process and finally stained with DAB and haematoxylin, dehydrated, and resin sealed. Images were captured using a microscope (ECLIPSE 80i, Nikon).

ELISA

Serum (50 µL) was diluted with PBS (50 µL) to prepare samples for the human DNM2 ELISA Kit (abx250599, Human, 96-well, Abbexa^®) and the human CORO1A ELISA Kit (ab214032, Human, 96-well, Abcam), according to the manufacturer’s protocol. The results were measured at 450 nm by a microplate reader. The relative OD450 (OD₄₅₀ of each well − OD₄₅₀ of the blank well) values were calculated.

Statistical analysis

The data are expressed as the mean ± standard deviation. Bands of western blotting were relatively quantified by ImageJ (1.37c) and the statistical value of each protein for analyses was calculated as the ratio of the gray value of biomarker protein / the gray value of internal reference protein. Quantitative variables were analyzed by unpaired t-test, paired t-test, and one-way ANOVA, and p < 0.05 was considered statistically significant. Statistical analyses were performed using the GraphPad Prism 8.0 software. Diagnostic effect of biomarkers was analyzed by receiver operating characteristic curve (ROC), and the area under curve (AUC), specificity and sensitivity were used to evaluate it using the MedCalc 19.3.1 by the program: Statistics-ROC curve analysis.

Identification of serum exosome protein biomarkers of SBA using LC-MS/MS (Label-free)

The proteomics analyses revealed the presence of 397 proteins in the serum exosomes (complete data set in Supplemental Data 2), of which 33 were differentially expressed between the SBA and normal groups. There were 7 proteins extremely upregulated in the SBA group and 12 proteins extremely downregulated in the normal group, while 14 proteins were also at statistically different levels (one upregulated and 13 downregulated; Table 1). GO analysis was conducted to speculate the potential functions of these proteins (except 4 uncharacterized) in three categories (Fig. 1.A). ORA was used to obtain GO enrichment of biological processes with four enrichment processes (Table 2). Accordingly, ACTR2, CORO1A, DNM2, AGT, GLUL, LIMS1, PDCD6, and PKM take part in more than two biological processes.

Table 1

A list of 33 differentially expressed proteins
Protein IDs	Protein names	Gene names	Ratio
Upregulated
Q6P6T1	Complement C1s subcomponent	C1s	2.99
Downregulated
F1LZ11	Uncharacterized protein	N/A	0.65
Q62636	Ras-related protein Rap-1b	Rap1b	0.65
P01015	Angiotensinogen	Agt	0.63
D3ZPL2	Uncharacterized protein	N/A	0.59
P09606	Glutamine synthetase	Glul	0.55
F1M5X4	Ig-like domain-containing protein	N/A	0.55
P68136	Actin, alpha skeletal muscle	Acta1	0.54
Q8K3U6	Coagulation factor VII	F7	0.53
A0A0G2JV65	14-3-3 protein zeta/delta	Ywhaz	0.52
B0BNJ1	LOC683667 protein	Sri	0.50
A0A0G2K9Z5	Uncharacterized protein	N/A	0.48
G3V7W1	Programmed cell death protein 6	Pdcd6	0.45
P01883	Ig delta chain C region (Fragment)	N/A	0.09
Specific in normal samples
A0A0A0MY48	Dynamin-2	Dnm2
Q5M7U6	Actin-related protein 2	Actr2
Q6P502	T-complex protein 1 subunit gamma	Cct3
G3V9N9	alpha-1,2-Mannosidase	Man1a1
A0A0G2K393	Pleckstrin	Plek
A0A0H2UHM5	Protein disulfide-isomerase	Pdia3
C0KUC5	LIM and senescent cell antigen-like-containing domain protein	Lims1
Q7M094	Destrin-like protein p17a (Fragments)	Dstn
Q5U329	Anion exchange protein	Slc4a1
P50115	Protein S100-A8	S100a8
Q6LC76	Fibronectin (Fragment)	Fn1
Q91ZN1	Coronin-1A	Coro1a
Specific in SBA samples
A0A0G2K2X4	Olfactory receptor	LOC100911127
Q5I0L8	Angiopoietin-like 3	Angptl3
M0R7M5	Uncharacterized protein	LOC100911032
P01836	Ig kappa chain C region, A allele	N/A
P11980	Pyruvate kinase PKM	Pkm
Q08420	Extracellular superoxide dismutase [Cu-Zn]	Sod3
Q91WX0	Complement factor H-related protein	RGD1564614

Table 2

A list of gene ontology analysis of the biological processes associated with the 29 differentially expressed proteins
Gene Set	Description	Size	Expect	Ratio	P Value	FDR
GO:0008064	regulation of actin polymerization or depolymerization	122	0.2374	21.058	3.30E-06	0.005217
GO:0022603	regulation of anatomical structure morphogenesis	682	1.3273	6.7805	3.19E-06	0.005217
GO:1901700	response to oxygen-containing compound	1542	3.0011	4.3317	1.50E-06	0.005217
GO:0022607	cellular component assembly	1997	3.8867	3.6021	4.34E-06	0.00563

Among these eight proteins, ACTR2,[30, 31] CORO1A,[32] GLUL,[33] and DNM2[34] have been reported to function during neural tube development, but have not been shown to be connected with neural tube defects. Analysis of the four proteins in the String database indicated that ACTR2, CORO1A, and DNM2 may be connected by the same cluster (Fig. 1.B) and require further verification.

Comparative analysis to exclude the effect of atRA on biomarkers in serum exosomes at E18

To clarify whether atRA itself could affect the expression of these biomarkers, we divided into four groups as mentioned above. The expression of ACTR2, CORO1A, and DNM2 in the non-SBA group treated with atRA was slightly decreased compared with that of normal group treated with oil, while their expression in SBA group 1 and SBA group 2 was significantly decreased compared with normal group (Fig. 1.C). The one-way ANOVA analysis with statistical difference intuitively showed this result (Fig. 1.D). The above results indicated that the decreased expression of ACTR2, CORO1A, and DNM2 in serum exosomes were related to the embryogenesis of SBA, and not a result of transcriptional repression by atRA.

Analysis of differential expression of ACTR2, CORO1A, and DNM2 in serum exosomes at E18, E16, E14, and E12

A total of 19 paired E18 serum exosome samples differed from those used in proteomics were examined. The expression of ACTR2, CORO1A, and DNM2 decreased significantly in SBA (Fig. 2.A). Unpaired t-test with statistical difference (ACTR2 P=0.0095, CORO1A P=0.0057, and DNM2 P<0.0001) showed downregulated expression trends in SBA at E18 (Fig. 2.B). To confirm the differential expression of proteins during early gestation, western blotting analysis was performed on serum exosomes at E16 (Fig. 2.C), E14 (Fig. 2.E), and E12 (Fig. 2.G), expressing same trends with E18. Unpaired t-test with statistical difference displayed the same differences at E16 (Fig. 2.D; ACTR2 P=0.0421, CORO1A P=0.0277, and DNM2 P=0.0059), E14 (Fig. 2.F; ACTR2 P=0.0490, CORO1A P=0.0454, and DNM2 P=0.0073) and E12 (Fig. 2.H; ACTR2 P=0.0163, CORO1A P=0.0282, and DNM2 P=0.0157) in expression as those seen at E18. Put together, these results suggest that these proteins maintain a lower expression level in the SBA group from E12 to E18, indicating their diagnostic ability for early gestation.

Analysis of differential expression of ACTR2, CORO1A, and DNM2 in serum without isolation of exosomes

To confirm specific differential expression in the serum exosomes, we quantified their expressions using western blotting in whole serum without exosome isolation. We found no obvious changes between the normal and SBA groups at E18 (Fig. 3.A) and E12 (Fig. 3.C), indicating their downregulation specific to serum exosomes. Coomassie Brilliant Blue staining of total proteins served as the internal reference (calculating the gray value of albumin bands as shown in Fig. 3.A& C by ImageJ) for serum, and staining of the complete gel is given in Supplemental Figure S7& 8. Unpaired t-test showed no statistical difference either at E18 (Fig. 3.B, ACTR2 P=0.5082, CORO1A P=0.7230, DNM2 P=0.1316) or at E12 (Fig. 3.D, ACTR2 P=0.6568, CORO1A P=0.3789, DNM2 P=0.8318).

Analysis of differential expression of ACTR2, CORO1A, and DNM2 in fetal neural tubes and FNEs

To verify whether the downregulated expression of these proteins in the serum exosomes was related to the NTDs, we quantified their expressions using western blotting in SBA neural tubes at E18 and E12. We found that their expression patterns were the same as in the serum exosomes with significantly decreased SBA expression (Fig. 3.E, G). Unpaired t-test with statistical difference showed downregulated expression trends in SBA both at E18 (Fig. 3.F; ACTR2 P=0.0012, CORO1A P=0.0264, and DNM2 P=0.0151) and E12 (Fig. 3.H; ACTR2 P=0.0301, CORO1A P=0.0247, and DNM2 P=0.0012).

Immunohistochemistry analysis was performed in E18 embryos to evaluate the location and level of protein expression in neural tubes. ACTR2 was expressed in all cells within the field of vision with increased expression in neuroepithelium, neural cells, and neural fibers (Fig. 4.A) and downregulated expression in SBA (Fig. 4.D). CORO1A was expressed increasingly in nerve fibers (Fig. 4.B) but downregulated in SBA (Fig. 4.E). DNM2 was expressed increasingly in neuroepithelium and neural cells (Fig. 4.C), but hardly detected in SBA (Fig. 4.F).

To further verify whether the downregulated expression of ACTR2, CORO1A, and DNM2 in total serum exosomes originated from fetal neural source, we tested the proteins in FNEs isolated from total serum exosomes of maternal rats (Fig. 4.G). The change inexpression of CORO1A and DNM2 in FNEs followed the same pattern as that in total serum exosomes, which showed downregulated expression in SBA (Fig. 4.H; CORO1A P=0.0487, and DNM2 P=0.0316), while there was no significant difference in the expression of ACTR2 between normal samples and SBA serum exosome samples (Fig. 4.H; ACTR2 P=0.4987). These suggested that CORO1A and DNM2 expression was specific to neural cells and tissues.

Analysis of differential expression of CORO1A and DNM2 in serum exosomes of pregnant women

We performed ELISA on DNM2 and CORO1A in maternal serum exosomes to validate their expression trends. Samples from pregnant women were paired by gestational week, and paired t-test was used for statistical analysis. DNM2 expression decreased significantly in all 19 pregnant women who were diagnosed as carrying fetuses with NTDs compared with normal controls (Fig. 5.A; P=0.0011) and its ROC curve showed high accuracy (specificity=78.95%, sensitivity=73.68%, AUC=0.806) (Fig. 5.B). Further analysis by the subgroups showed statistical difference of DNM2 expression both in SBA group (Fig. 5.G; P=0.0035), and anencephalus and exencephalus group (Fig. 5.H; P=0.0058). Subsequently, we focused on the expression of DNM2 during different pregnancy periods, which included two groups for statistical analysis: gestational weeks 12–18 and 19–40. There was downregulated expression with significant difference in the group of 12–18 gestational weeks (Fig. 5.C; P=0.0034), which showed extremely high accuracy (specificity=100%, sensitivity=100%, AUC=1.000) (Fig. 5.D). There was also downregulated expression, but with no significant difference, in the group of 19–40 gestational weeks (Fig. 5.E; P=0.0557), which showed lower accuracy (specificity=58.33%, sensitivity=83.33%, AUC=0.736) (Fig. 5.F).

CORO1A expression was also showed decreased significantly in the 19 pregnant women compared with that of normal controls (Fig. 5.I; P=0.0022), and its ROC curve showed high accuracy (specificity=89.47%, sensitivity=68.42%, AUC=0.817) (Fig. 5.J). Further analysis by the subgroups showed statistical difference of CORO1A expression both in SBA group (Fig. 5.O; P<0.0001), and in anencephalus and exencephalus group (Fig. 5.P; P=0.0186). The results showed that there was obvious downregulated expression with significant difference in the 12–18 gestational weeks group (Fig. 5.K; P=0.0108), which showed high accuracy (specificity=85.71%, sensitivity=85.71%, AUC=0.857) (Fig. 5.L). There was also downregulated expression, but with no significant difference in the 19–40 gestational weeks group (Fig. 5.M; P=0.0599), which showed lower accuracy (specificity=83.33%, sensitivity=75%, AUC= 0.785) (Fig. 5.N).

We further analyzed the combined performance of DNM2 and CORO1A in maternal serum exosomes using ELISA. The ROC curve showed better performance in all 19 pair samples and it showed higher accuracy (specificity= 78.95%, sensitivity= 94.74%, AUC=0.889) (Fig. 5.Q). In the 12–18 gestational weeks group, ROC curve also showed better performance and extreme accuracy (specificity= 100%, sensitivity= 100%, AUC=1.000) (Fig. 5.R). In the 19–40 gestational weeks group (n=12), ROC curve also showed better performance (specificity= 66.67%, sensitivity= 100%, AUC=0.854) (Fig. 5.S). In addition, the ROC curve showed good performance in 13 pair SBA samples and high accuracy and specificity (specificity= 92.31%, sensitivity= 76.92%, AUC=0.888) (Fig. 5.T).

We discovered, for the first time, downregulated expression of three distinct proteins (ACTR2, CORO1A, and DNM2) in the serum exosomes in an SBA rat model using LC-MS/MS (label-free) in conjunction with bioinformatics analyses. These proteins were shown to be associated with the neural tube changes and further validated to demonstrate CORO1A and DNM2 expression changes in FNEs. This indicated their direct connection with defects in neural development. We verified their downregulation in pregnant women. Thus, CORO1A and DNM2 can be considered as specific diagnostic biomarkers of NTDs during early gestation.

When focusing on the functions of these three proteins, they were shown to play crucial roles in fetal development, especially in the nervous system. CORO1A was found to be involved in axon guidance and branching to final targets by mediating actin assembly and reorganization with cofilin and the ARP2/3 complex (ARPC3).[32] It has the ability to stabilize[35] and bind[36] F-actin. DNM2, which is also a large GTPase, controls the spreading and motility of the growth cone,[34] and can regulate hormone secretion and vesicle release from neuroendocrine cells.[37] F-actin also needs DNM2 to polymerize and assemble with ARPC3.[38] Moreover, reorganization of F-actin requires the DNM2-Cortactin-ARPC3 complex.[39] ACTR2 is also named ARP2 (actin-related protein 2), a portion of ARPC3, which is essential during different phases of neural development, including neurogenesis, neuritogenesis, and neural migration.[40] ARPC3 is also critical for F-actin regulation and dynamics.[31, 41, 42] A further literature search found that F-actin involvement had been reported not only in axon and dendrite growth[43, 44] but also in neural tube closure.[45, 46] F-actin was therefore considered an effect indicator for neural development associated with these molecules.

However, there were some limitations in our study. Nowadays for the routine application of folic acid during gestation, the occurrence of NTDs have reduced a lot. Therefore, it’s difficult to collect samples, which made the smaller sample size of pregnant women with NTDs in our manuscript. More data from clinical samples are required to perform combined analysis of potential biomarkers we have already found. In addition, the earliest samples of NTDs were from pregnant week 12 in the present study, and further studies should verify whether CORO1A and DNM2 can screen and diagnose NTDs before pregnant week 12. Multicenter studies are needed to evaluate the prenatal diagnostic potential of using these biomarkers. Besides, more detailed mechanism by which CORO1A and DNM2 are related to embryogenesis of SBA need to be explored in further study.

We expect that the expression levels of these proteins in exosomes extracted from maternal serum during pregnancy can be exploited for earlier clinical screening and diagnosis of NTDs with higher specificity. Our study provides new molecular biomarkers, which might be involved in the occurrence of NTDs.

Data Availability

The raw data set of LC-MS/MS (label-free) was able to be accessed on PRIDE (Proteomics IDEntifications Database, https://www.ebi.ac.uk/pride/), with URL (https://www.ebi.ac.uk/pride/archive/projects/PXD023775/private) and project ID (PXD023775).

Acknowledgments and Funding

This work was supported by the National Key Research and Development Program (2016YFC1000505); the National Natural Foundation of China (Grant numbers: 81871219 and 81671469); and the LiaoNing Revitalization Talents Program (No. XLYC1902099 and No. XLYC1908008). The authors are grateful to Ling Ma for her valuable guidance for experimental design and exosome-related experiments.

Contributions

Yanfu Wang, Ling Ma, and Zhengwei Yuan designed this study. Yanfu Wang performed the experiments with the help of Ling Ma. Yanfu Wang acquired the data, Yanfu Wang analyzed the data with the help of Shanshan Jia, Dan Liu, Wei Ma, and Xiaowei Wei, Zhengwei Yuan. Hui Gu, Wenting Luo., Yuzuo Bai, and Weilin Wang provided critical revisions. Yanfu Wang drafted the manuscript. All authors read and approved the final manuscript.

Conflicts of interest

All authors have no relevant financial or non-financial interests to disclose.

Ethics approval

Every pregnant woman consumed folic acid regularly under guidance during pregnancy. All pregnant women were informed of the study procedures and risks, and all participants consented to participate in this study. Written informed consent was obtained from all pregnant women at the time of sampling, and the study was performed in accordance with the principles of the Declaration of Helsinki and approved by the Ethics Committee of Shengjing Hospital Affiliated to China Medical University (approval no. 2017PS264K). All animal experimental protocols were approved by the Medical Ethics Committee of the Shengjing Hospital of China Medical University.

Botto LD, Moore CA, Khoury MJ, Erickson JD (1999) Neural-tube defects. N Engl J Med 341: 1509-1519. DOI 10.1056/NEJM199911113412006
Peyronnet B, Gao F, Brochard C, Oger E, Scailteux LM, Balusson F, Hascoet J, Alimi Q, Khene ZE, Bayat S, et al. (2019) Urological disorders are still the leading cause of inhospital death in patients with spina bifida. Urology. DOI 10.1016/j.urology.2019.11.006
Phillips LA, Burton JM, Evans SH (2017) Spina Bifida Management. Curr Probl Pediatr Adolesc Health Care 47: 173-177. DOI 10.1016/j.cppeds.2017.06.007
Norem CT, Schoen EJ, Walton DL, Krieger RC, O'Keefe J, To TT, Ray GT (2005) Routine ultrasonography compared with maternal serum alpha-fetoprotein for neural tube defect screening. Obstet Gynecol 106: 747-752. DOI 10.1097/01.AOG.0000178780.63956.3b
Krantz D, Hallahan T, Janik D, Carmichael J (2014) Maternal Serum Screening Markers and Adverse Outcome: A New Perspective. J Clin Med 3: 693-712. DOI 10.3390/jcm3030693
Cheschier N, Bulletins-Obstetrics ACoP (2003) ACOG practice bulletin. Neural tube defects. Number 44, July 2003. (Replaces committee opinion number 252, March 2001). Int J Gynaecol Obstet 83: 123-133. DOI 10.1016/s0020-7292(03)00390-4
Palomaki GE, Bupp C, Gregg AR, Norton ME, Oglesbee D, Best RG, Committee ABGSotLQA (2019) Laboratory screening and diagnosis of open neural tube defects, 2019 revision: a technical standard of the American College of Medical Genetics and Genomics (ACMG). Genet Med. DOI 10.1038/s41436-019-0681-0
Krantz DA, Hallahan TW, Sherwin JE (2010) Screening for open neural tube defects. Clin Lab Med 30: 721-725. DOI 10.1016/j.cll.2010.04.010
Milunsky A, Jick SS, Bruell CL, MacLaughlin DS, Tsung YK, Jick H, Rothman KJ, Willett W (1989) Predictive values, relative risks, and overall benefits of high and low maternal serum alpha-fetoprotein screening in singleton pregnancies: new epidemiologic data. Am J Obstet Gynecol 161: 291-297. DOI 10.1016/0002-9378(89)90501-2
Dong N, Gu H, Liu D, Wei X, Ma W, Ma L, Liu Y, Wang Y, Jia S, Huang J, et al. (2020) Complement factors and alpha-fetoprotein as biomarkers for noninvasive prenatal diagnosis of neural tube defects. Ann N Y Acad Sci 1478: 75-91. DOI 10.1111/nyas.14443
Kim DK, Kang B, Kim OY, Choi DS, Lee J, Kim SR, Go G, Yoon YJ, Kim JH, Jang SC, et al. (2013) EVpedia: an integrated database of high-throughput data for systemic analyses of extracellular vesicles. J Extracell Vesicles 2. DOI 10.3402/jev.v2i0.20384
Akers JC, Gonda D, Kim R, Carter BS, Chen CC (2013) Biogenesis of extracellular vesicles (EV): exosomes, microvesicles, retrovirus-like vesicles, and apoptotic bodies. J Neurooncol 113: 1-11. DOI 10.1007/s11060-013-1084-8
Panigrahi GK, Deep G (2017) Exosomes-based biomarker discovery for diagnosis and prognosis of prostate cancer. Front Biosci (Landmark Ed) 22: 1682-1696. DOI 10.2741/4565
Salomon C, Nuzhat Z, Dixon CL, Menon R (2018) Placental Exosomes During Gestation: Liquid Biopsies Carrying Signals for the Regulation of Human Parturition. Curr Pharm Des 24: 974-982. DOI 10.2174/1381612824666180125164429
Arenaccio C, Federico M (2017) The Multifaceted Functions of Exosomes in Health and Disease: An Overview. Adv Exp Med Biol 998: 3-19. DOI 10.1007/978-981-10-4397-0_1
Salomon C, Torres MJ, Kobayashi M, Scholz-Romero K, Sobrevia L, Dobierzewska A, Illanes SE, Mitchell MD, Rice GE (2014) A gestational profile of placental exosomes in maternal plasma and their effects on endothelial cell migration. PLoS One 9: e98667. DOI 10.1371/journal.pone.0098667
Mincheva-Nilsson L, Baranov V (2010) The role of placental exosomes in reproduction. Am J Reprod Immunol 63: 520-533. DOI 10.1111/j.1600-0897.2010.00822.x
Kumar P, Becker JC, Gao K, Carney RP, Lankford L, Keller BA, Herout K, Lam KS, Farmer DL, Wang A (2019) Neuroprotective effect of placenta-derived mesenchymal stromal cells: role of exosomes. FASEB J 33: 5836-5849. DOI 10.1096/fj.201800972R
Sheller-Miller S, Choi K, Choi C, Menon R (2019) Cyclic-recombinase-reporter mouse model to determine exosome communication and function during pregnancy. Am J Obstet Gynecol 221: 502 e501-502 e512. DOI 10.1016/j.ajog.2019.06.010
Sheller-Miller S, Lei J, Saade G, Salomon C, Burd I, Menon R (2016) Feto-Maternal Trafficking of Exosomes in Murine Pregnancy Models. Front Pharmacol 7: 432. DOI 10.3389/fphar.2016.00432
Goetzl L, Darbinian N, Goetzl EJ (2016) Novel window on early human neurodevelopment via fetal exosomes in maternal blood. Ann Clin Transl Neurol 3: 381-385. DOI 10.1002/acn3.296
Goetzl L, Darbinian N, Merabova N (2019) Noninvasive assessment of fetal central nervous system insult: Potential application to prenatal diagnosis. Prenat Diagn 39: 609-615. DOI 10.1002/pd.5474
Fan Y, Wang L, Zhou F, Zhang Y, Li H, Shan L, Yuan Z (2011) Comparative proteomics of spinal cords of rat fetuses with spina bifida aperta. J Proteomics 75: 668-676. DOI 10.1016/j.jprot.2011.09.006
Shan L, Fan Y, Li H, Liu W, Gu H, Zhou F, Yuan Z (2012) Proteomic analysis of amniotic fluid of pregnant rats with spina bifida aperta. J Proteomics 75: 1181-1189. DOI 10.1016/j.jprot.2011.10.033
An D, Wei X, Li H, Gu H, Huang T, Zhao G, Liu B, Wang W, Chen L, Ma W, et al. (2015) Identification of PCSK9 as a novel serum biomarker for the prenatal diagnosis of neural tube defects using iTRAQ quantitative proteomics. Sci Rep 5: 17559. DOI 10.1038/srep17559
Wu LN, Wei XW, Fan Y, Miao JN, Wang LL, Zhang Y, Wu D, Yuan ZW (2013) Altered expression of 14-3-3zeta protein in spinal cords of rat fetuses with spina bifida aperta. PLoS One 8: e70457. DOI 10.1371/journal.pone.0070457
Jorrin-Novo JV (2014) Plant proteomics methods and protocols. Methods Mol Biol 1072: 3-13. DOI 10.1007/978-1-62703-631-3_1
Wisniewski JR, Zougman A, Nagaraj N, Mann M (2009) Universal sample preparation method for proteome analysis. Nat Methods 6: 359-362. DOI 10.1038/nmeth.1322
Cox J, Mann M (2008) MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat Biotechnol 26: 1367-1372. DOI 10.1038/nbt.1511
San Miguel-Ruiz JE, Letourneau PC (2014) The role of Arp2/3 in growth cone actin dynamics and guidance is substrate dependent. J Neurosci 34: 5895-5908. DOI 10.1523/JNEUROSCI.0672-14.2014
Wegner AM, Nebhan CA, Hu L, Majumdar D, Meier KM, Weaver AM, Webb DJ (2008) N-wasp and the arp2/3 complex are critical regulators of actin in the development of dendritic spines and synapses. J Biol Chem 283: 15912-15920. DOI 10.1074/jbc.M801555200
Martorella M, Barford K, Winkler B, Deppmann CD (2017) Emergent Role of Coronin-1a in Neuronal Signaling. Vitam Horm 104: 113-131. DOI 10.1016/bs.vh.2016.10.002
Zhou Y, Dhaher R, Parent M, Hu QX, Hassel B, Yee SP, Hyder F, Gruenbaum SE, Eid T, Danbolt NC (2019) Selective deletion of glutamine synthetase in the mouse cerebral cortex induces glial dysfunction and vascular impairment that precede epilepsy and neurodegeneration. Neurochem Int 123: 22-33. DOI 10.1016/j.neuint.2018.07.009
Kurklinsky S, Chen J, McNiven MA (2011) Growth cone morphology and spreading are regulated by a dynamin-cortactin complex at point contacts in hippocampal neurons. J Neurochem 117: 48-60. DOI 10.1111/j.1471-4159.2011.07169.x
Galkin VE, Orlova A, Brieher W, Kueh HY, Mitchison TJ, Egelman EH (2008) Coronin-1A stabilizes F-actin by bridging adjacent actin protomers and stapling opposite strands of the actin filament. J Mol Biol 376: 607-613. DOI 10.1016/j.jmb.2007.12.007
Chan KT, Roadcap DW, Holoweckyj N, Bear JE (2012) Coronin 1C harbours a second actin-binding site that confers co-operative binding to F-actin. Biochem J 444: 89-96. DOI 10.1042/BJ20120209
Yang Z, Li H, Chai Z, Fullerton MJ, Cao Y, Toh BH, Funder JW, Liu JP (2001) Dynamin II regulates hormone secretion in neuroendocrine cells. J Biol Chem 276: 4251-4260. DOI 10.1074/jbc.M006371200
Unsworth KE, Mazurkiewicz P, Senf F, Zettl M, McNiven M, Way M, Holden DW (2007) Dynamin is required for F-actin assembly and pedestal formation by enteropathogenic Escherichia coli (EPEC). Cell Microbiol 9: 438-449. DOI 10.1111/j.1462-5822.2006.00801.x
Krueger EW, Orth JD, Cao H, McNiven MA (2003) A dynamin-cortactin-Arp2/3 complex mediates actin reorganization in growth factor-stimulated cells. Mol Biol Cell 14: 1085-1096. DOI 10.1091/mbc.e02-08-0466
Chou FS, Wang PS (2016) The Arp2/3 complex is essential at multiple stages of neural development. Neurogenesis (Austin) 3: e1261653. DOI 10.1080/23262133.2016.1261653
Kessels MM, Schwintzer L, Schlobinski D, Qualmann B (2011) Controlling actin cytoskeletal organization and dynamics during neuronal morphogenesis. Eur J Cell Biol 90: 926-933. DOI 10.1016/j.ejcb.2010.08.011
Zhang SX, Duan LH, He SJ, Zhuang GF, Yu X (2017) Phosphatidylinositol 3,4-bisphosphate regulates neurite initiation and dendrite morphogenesis via actin aggregation. Cell Res 27: 253-273. DOI 10.1038/cr.2017.13
Zou W, Dong X, Broederdorf TR, Shen A, Kramer DA, Shi R, Liang X, Miller DM, 3rd, Xiang YK, Yasuda R, et al. (2018) A Dendritic Guidance Receptor Complex Brings Together Distinct Actin Regulators to Drive Efficient F-Actin Assembly and Branching. Dev Cell 45: 362-375 e363. DOI 10.1016/j.devcel.2018.04.008
Xu K, Zhong G, Zhuang X (2013) Actin, spectrin, and associated proteins form a periodic cytoskeletal structure in axons. Science 339: 452-456. DOI 10.1126/science.1232251
Escuin S, Vernay B, Savery D, Gurniak CB, Witke W, Greene ND, Copp AJ (2015) Rho-kinase-dependent actin turnover and actomyosin disassembly are necessary for mouse spinal neural tube closure. J Cell Sci 128: 2468-2481. DOI 10.1242/jcs.164574
Galea GL, Cho YJ, Galea G, Mole MA, Rolo A, Savery D, Moulding D, Culshaw LH, Nikolopoulou E, Greene NDE, et al. (2017) Biomechanical coupling facilitates spinal neural tube closure in mouse embryos. Proc Natl Acad Sci U S A 114: E5177-E5186. DOI 10.1073/pnas.1700934114

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CORO1A and DNM2 in Serum Exosomes as Biomarkers of Neural Tube Defects

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