Abstract

   Cerebrospinal fluid (CSF) microRNAs (miRNAs) have emerged as potential
   biomarkers for minimally invasive diagnosis of central nervous system
   malignancies. However, despite significant advances in recent years,
   this field still suffers from poor data reproducibility. This is
   especially true in cases of infants, considered a new subject group.
   Implementing efficient methods to study miRNAs from clinically
   realistic CSF volumes is necessary for the identification of new
   biomarkers.

   Methods: We compared six protocols for characterizing miRNAs, using
   200-µL CSF from infants (aged 0-7). Four of the methods employed
   extracellular vesicle (EV) enrichment step and the other two obtained
   the miRNAs directly from cleared CSF. The efficiency of each method was
   assessed using real-time PCR and small RNA sequencing. We also
   determined the distribution of miRNAs among different CSF shuttles,
   using size-exclusion chromatography.

   Results: We identified 281 CSF miRNAs from infants. We demonstrated
   that the miRNAs could be efficiently detected using only 200 µL of
   biofluid in case of at least two of the six methods. In the exosomal
   fraction, we found 12 miRNAs that might be involved in
   neurodevelopment.

   Conclusion: The Norgen and Invitrogen protocols appear suitable for the
   analysis of a large number of miRNAs using small CSF samples.

   Keywords: CSF miRNAs, CSF exosomes, microRNA profiling, infants,
   clinical samples

Introduction

   Cerebrospinal fluid (CSF) is a potential source for minimally invasive
   diagnostic analysis of neurological disorders, including viral
   infections [47]^1, Alzheimer's disease [48]^2^, [49]^3, traumatic brain
   injury [50]^4, and brain tumors [51]^5^-[52]^7. The CSF contains cells,
   extracellular vesicles (EVs), and biomolecules such as proteins,
   nucleic acids, and metabolites. These biomolecules can be either
   associated with the cells or EVs [53]^3^, [54]^4 or circulate freely
   within the fluid [55]^8. Among these components, the microRNAs (miRNAs)
   have been attracting increasing attention in recent years [56]^8^,
   [57]^9. miRNAs are short (∼22 nucleotides) non-coding RNAs that
   modulate gene expression at the post-transcriptional level [58]^10.
   They regulate more than 50% of human genes, including many that are
   related to cancer [59]^11^, [60]^12. Some changes in the levels of
   certain miRNAs have already been associated with various pathologies
   [61]^8. Teplyuk et al. have found high levels of miR-10b and miR-21 in
   the CSF of patients with glioblastoma (GBM). Interestingly, the
   increased levels of these two miRNAs are also associated with the
   metastasis to the brain in patients with primary breast and lung
   cancers [62]^13. Baraniskin et al. have reported that miR-21 and
   miR-15b are upregulated in CSF samples from patients with glioma
   [63]^14.

   However, these studies analyzed CSF miRNAs without examining their
   transport in the fluid. The distribution of miRNAs among miRNA shuttles
   in the CSF, i.e., proteins, lipoproteins, and EVs (exosomes,
   microvesicles, and apoptotic bodies), can differ between normal and
   pathological conditions [64]^8. Yagi et al. have recently observed that
   the CSF miRNAs can vary between the vesicular and non-vesicular
   fractions. They have shown that the miRNAs associated with EVs are
   different from those found in free circulation. miR-1911-5p, miR-1264,
   and miR-34b, among others, are abundant in CSF EVs and not in the
   EV-depleted CSF [65]^15. EVs are released by all types of cells and can
   enter the bodily fluids [66]^16. Cancer cells also actively release EVs
   carrying miRNAs, which communicate with near and distal cells in the
   tumor microenvironment and affect tumor progression [67]^17^, [68]^18,
   contributing to the final vesicular composition of biofluids.
   Therefore, miRNAs carried by CSF EVs might constitute a good source of
   biomarkers for minimally invasive diagnosis and prognosis of brain
   cancer. Although the CSF is often obtained for diagnosis in the
   clinical practice, the EVs that this fluid contains are not routinely
   examined, neglecting most of its biomarker potential. Only one study
   has currently reported a robust CSF EV-associated miRNA signature
   (nine-miRNA catalog) for minimally invasive diagnosis of GBM [69]^19.

   Despite significant advances in recent years, this field suffers from
   poor data reproducibility [70]^20^, [71]^21. The main reason for this
   persistent problem is the complexity of CSF miRNA detection procedures,
   with many unresolved technical issues [72]^8. First, it is crucial to
   preserve the integrity of CSF specimens between their collection and
   laboratory processing and storage. The samples should be processed
   within 2 hours of collection, and freeze-thaw cycles should be avoided
   [73]^20. Second, various existing miRNA isolation protocols have
   different yields. To date, various methods and kits have been used to
   isolate EVs from CSF samples [74]^15^, [75]^19^, [76]^22^-[77]^28 and
   to extract miRNAs from CSF EVs [78]^15^, [79]^19^, [80]^22^-[81]^27^,
   [82]^29 and from cleared CSF [83]^9^, [84]^13^, [85]^14^,
   [86]^30^-[87]^39. However, it is difficult to compare the data obtained
   using such a varying array of techniques, kits, and samples. Third,
   different miRNA profiling platforms and data normalization approaches
   can result in distinct miRNA catalogs [88]^20^, [89]^36. In view of the
   above, the unresolved technical issues in the analysis and
   standardization of protocols are still the obstacles to be overcome.
   Another important problem to be considered is the limited amount of CSF
   that can be obtained for the diagnosis. In the case of pediatric
   patients, this problem is even more acute since the amount of CSF
   routinely withdrawn for clinical tests is smaller than from the adults.
   For this reason, these patients constitute a largely unexplored subject
   group for which new biomarkers are desperately needed [90]^21. In
   addition, very little is known of the biological variability of the CSF
   microRNAome; it might be affected by the diet, health status, age, and
   development. Establishing a standardized, efficient protocol for miRNA
   detection in small CSF samples would facilitate the necessary large
   studies with statistically sufficient numbers of subjects. The
   availability of such methods might also help to clarify other issues
   and identify new biomarkers, especially in infants, where they are
   desperately needed [91]^21.

   Thus, it is necessary to adapt the existing protocols to small CSF
   sample volumes and find the most appropriate method for miRNA analysis.
   Here, we performed a comprehensive comparative analysis of six existing
   protocols to establish a simple and effective method for detecting
   miRNAs from a minimum CSF volume of clinical specimens. We placed
   particular emphasis on identifying miRNAs associated with EVs. We
   believe that our study contributes some valuable data to the search of
   new low-invasive biomarkers for pediatric brain cancers and to their
   implementation in clinical practice.

Methods

Experimental design

   In this study, we performed a comprehensive comparative analysis of six
   existing methods to define a simple and effective strategy for
   detecting miRNAs from 200-µL samples of CSF. Four of the protocols
   included an initial EVs enrichment step. The other two were designed to
   extract miRNAs directly from cleared CSF. First, the efficiency of each
   method was assessed using the real-time PCR (RT-qPCR). Eight miRNAs
   previously detected in the CSF by Yagi et al. were selected as
   reference [92]^15. We used small RNA sequencing (smallRNAseq) data from
   Yagi et al. as a reference throughout our study since they isolated
   miRNAs from a large volume of CSF (7 mL). The eight miRNAs had variable
   concentrations in the exosomal fractions of Yagi et al. (Figure
   [93]S1A) [94]^15. Our aim was to establish the detection limit of each
   of the methods for small CSF volumes (200 µL). Then, the methods
   capable of identifying the majority of the eight miRNAs (using RT-qPCR)
   were examined employing the smallRNAseq to find the technique detecting
   the largest number of miRNAs.

   Moreover, the CSF samples were fractionated using an in-house
   size-exclusion chromatography (SEC) method. Two fractions representing
   the exosomal and supernatant fractions were sequenced to identify
   enriched miRNAs in the exosomal fraction of CSF of infants. Each
   procedure was carried out in triplicate (Figure [95]1).

Figure 1.

   [96]Figure 1
   [97]Open in a new tab

   Experimental design for comparison of six methods of analyzing miRNAs
   in bodily fluids. Aliquots of 200 µL of CSF were used to test each of
   the six methods in triplicate (overall, 18 aliquots were processed).
   The pellets obtained in each EV enrichment procedure were resuspended
   in 100 µL of 1X DPBS. Then, total RNA was extracted to perform the
   downstream analyses (TaqMan RT-qPCR and smallRNAseq). Abbreviations:
   size-exclusion chromatography (SEC), ultracentrifugation (UC), miRCURY
   Exosome Isolation Kit from Qiagen (QIA), Total Exosome Isolation
   Reagent from Invitrogen (INV), mirVana PARIS Kit from Ambion (PAR), and
   Plasma/Serum RNA Purification Kit from Norgen (NOR).

Human CSF samples

   Samples and data from patients included in this study were provided by
   the Basque Biobank ([98]www.biobancovasco.org) and were processed
   following standard operation procedures with appropriate approval of
   the Ethical and Scientific Committees (code CEIC E17/40). Nineteen
   non-hemorrhagic samples from children (aged 0-7) were acquired. The CSF
   samples were obtained via lumbar puncture, centrifuged to remove
   contaminant cells (500 x g for 10 minutes), aliquoted, and immediately
   stored at -80 °C until processing. To perform the main experiment and
   the analyses of reproducibility and RNase protection, three independent
   pools of samples were generated. To achieve that, the CSF samples were
   thawed at 4 °C, mixed together, centrifuged at 3,000 x g for 15 minutes
   at 4 °C, divided into 200 µL-aliquots (cleared CSF), and kept on ice
   until processing.

EVs enrichment procedures

   Four different EV enrichment methods were evaluated in triplicate:
   ultracentrifugation (UC), miRCURY Exosome Isolation Kit - Cells, Urine
   and CSF (Qiagen #76743) (QIA), Total Exosome Isolation Reagent
   (Invitrogen #4484453) (INV), and an in-house SEC. UC was carried out in
   a single step (100,000 x g for 75 minutes at 4 °C) using a
   Beckman-Coulter TLA 120.2 rotor. The QIA kit was used following the
   manufacturer's instructions. The INV method was slightly modified; the
   CSF triplicates were not initially centrifuged at 10,000 x g, as
   recommended, but at 3000 x g like in the rest of the protocols. The UC
   and QIA methods required an adjustment of the sample volume from 200 µL
   to 1.0 mL using 1X DPBS (Gibco #14190-094). In all cases, the EV
   pellets were resuspended in 100 µL of 1X DPBS. Finally, the cleared CSF
   was fractionated using the in-house SEC. This was performed as follows:
   The Poly-prep Chromatography Column (BioRad #731-1550) was filled with
   2.5 mL of Sepharose CL-2B cross-linked resin (Sigma #CL2B300-100ML) and
   left packing overnight at 4 °C. Then, the column was washed twice with
   2.5 ml of 1X DPBS. Once the sample (200 µL of CSF) was applied onto the
   column, 4.0 mL of 1X DPBS was added; 10 fractions of 200 µL and two
   final fractions of 1.0 mL were collected. The RNA was extracted from
   the isolated EVs and the SEC fractions using the mirVana PARIS Kit
   (Ambion #AM1556) (PAR), following the manufacturer's instructions for
   total RNA isolation. To account for the differences in the efficiency
   of the extraction, the samples were spiked with cel-miR-39 (2x10^-4
   nmoles added) (Invitrogen) after mixing the cleared CSF with the cell
   disruption buffer (Figure [99]1).

RNA extraction directly from cleared CSF

   Total RNA was extracted from 200 µL of cleared CSF using PAR and the
   Plasma/Serum RNA Purification Kit (Norgen #55000) (NOR). The isolated
   RNA was eluted in 100 µL of nuclease‑free water (Ambion #AM9930).
   Before each RNA extraction, the samples were spiked with cel-miR-39
   (2x10^-4 nmoles added) (Invitrogen) (Figure [100]1).

cDNA synthesis

   The cDNA was synthesized from 2 µL of the isolated RNA using the TaqMan
   Advanced miRNA cDNA Synthesis Kit (Applied Biosystems #[101]A28007),
   following the manufacturer's recommendations. To account for
   differences in the retrotranscription reaction and for the calculation
   of relative quantities of each miRNA, 2x10^-8 nmoles of ath-miR-159a
   (Invitrogen) were added to each reaction.

Real-Time qPCR assay

   The reaction mix consisted of 5 µL of TaqMan Fast Advanced Master Mix
   (Applied Biosystems #4444557), 0.5 µL of TaqMan Advanced miRNA Assays
   (Applied Biosystems #A25576), 1.5 µL of nuclease-free water (Ambion
   #AM9930), and 3 µL of cDNA diluted at 1:3 ratio. The following assays
   were performed: ath-miR-159a (478411_mir) and cel-miR-39-3p
   (478293_mir) for detecting the spike-ins, as well as hsa-miR-21-5p
   (477975_mir), hsa-miR-451a (478107_mir), hsa-miR-92a-3p (477827_mir),
   hsa-miR-22-3p (477985_mir), hsa-miR-1911-5p (479583_mir), has-miR-1264
   (478670_mir), hsa-miR-30c-5p (478008_mir), and hsa-miR-34b-3p
   (478049_mir) (Applied Biosystems) to detect the eight miRNAs selected.
   The RT-qPCR reactions were conducted in duplicate on a ViiA 7 Real-Time
   PCR System (Applied Biosystems). The data were analyzed using the
   QuantStudio Real-Time PCR System, software version 1.3 (Applied
   Biosystems).

Western blot analysis of SEC fractions

   First, 200 µL-aliquot of CSF was fractionated using SEC as previously
   described. Then, 150 µL of each fraction was concentrated using 99.5%
   acetone (Panreac #161007) and resuspended in 20 µL of 1X DPBS. Fifteen
   µL of the suspension was mixed with 5 µL of NuPAGE LDS Sample Buffer 4X
   (Invitrogen #NP0007) and heated for 5 minutes at 37 °C, 10 minutes at
   65 °C, and 15 minutes at 95 °C. Each preparation was separated in a
   4-12% Bis-Tris gel (Invitrogen #NP0336BOX) with MOPS SDS Running Buffer
   20X (Invitrogen #NP0001). Precision Plus Protein Dual Color Standard
   (BioRad #161-0374) was used to calculate the molecular weights of the
   proteins. The proteins were transferred to an Immobilon-P Transfer
   membrane (Merck Millipore #IPVH00010) using the NuPAGE Transfer Buffer
   20X (Invitrogen #NP0006-1) and blocked for 1 hour in 5% Blotting-Grade
   Blocker (BioRad #170-6404) and 0.2% Tween-20 (Sigma Aldrich #P2287)
   diluted in 1X DPBS. Then, the primary antibodies (1:500) were added and
   incubated overnight, followed by three washes with 1X DPBS and the
   application of secondary HRP-conjugated antibodies (1:6000). Primary
   antibodies against exosomal markers, i.e., Mo αCD63 clone H5C6
   (Developmental Studies Hybridoma Bank ID AB_528158) and Mo αCD9 (R&D
   systems #MAB1880), as well as antibodies to detect the neuron-specific
   enolase (NSE) and albumin, i.e., Rb αNSE clone EPR3377 (Abcam #Ab79757)
   and Sh αHSA (Abcam #ab8940), were used. HRP-conjugated anti-Mo,
   anti-Rb, and anti-Sh antibodies were obtained from Jackson
   ImmunoResearch. Chemiluminescence detection of bands was performed
   using Pierce ECL Plus Western Blotting Substrate (Thermo Scientific
   #32132). Finally, the antigens were detected on high-performance films
   (GE Healthcare #28906844) using the AGFA Curix-60 automatic processor
   (Agfa, Cologne, Germany).

RNase protection assay

   To detect each miRNA of interest within the EVs, we treated the cleared
   CSF with proteinase K (Sigma Aldrich #03115879001) or Triton X-100
   (TX-100) (Sigma Aldrich #T8787) plus RNase A (Sigma Aldrich #
   10109142001), as described in Shelke et al. [102]^40^, [103]^41. The
   proteinase K degrades the protein-miRNA complexes and, therefore,
   facilitates the degradation of the free-circulating miRNAs by the RNase
   [104]^41. After this treatment, all the miRNAs that are not protected
   inside the EVs should be degraded. However, the TX-100 permeabilizes
   the membrane of the EVs and allows the RNase to degrade the miRNAs
   contained in the vesicles. This assay, in combination with the
   proteinase K experiment, should show which miRNAs are associated with
   vesicles or other CSF components. Each procedure was carried out in
   triplicate. Briefly, a CSF pool of 1.8 mL was divided into nine
   aliquots of 200 µL. Three of these were incubated with proteinase K
   (the final concentration, 0.05 mg/mL) at 37 °C for 10 minutes. The
   reaction was stopped by adding phenylmethylsulfonyl fluoride (the final
   concentration, 5 mM) (Sigma Aldrich #10837091001) followed by
   additional heat inactivation (90 °C for 5 minutes). Another three
   aliquots were treated with 0.1% TX-100. Then, the samples treated with
   Proteinase K or TX-100 were incubated with RNase A (the final
   concentration, 0.5 mg/mL) at 37 °C for 20 minutes. The remaining
   aliquots constituted positive controls; they were not treated and kept
   at 4 °C until the RNA extraction step. Afterward, total RNA was
   extracted using NOR, and the levels of the eight miRNAs selected from
   Yagi et al. were determined by RT-qPCR.

Small RNA sequencing

   The quantity and profiles of obtained RNAs were examined using Agilent
   RNA 6000 Pico Chips (Agilent Technologies #5067-1513). Then, sequencing
   libraries were prepared using NEXTflex™ Small RNA-Seq Kit v3 (Bioo
   Scientific Corp. #5132-05) following the protocol for NEXTflex™ Small
   RNA-Seq Kit v3 V16.06. Briefly, using 70 of 100 µL of each extraction,
   the total RNA samples were incubated for 2 minutes at 70 °C, then 3′ 4N
   adenylated adapter and ligase enzyme were added, and ligation was
   conducted overnight at 20 °C. After removal of excess of 3′-adapter,
   5′-adapter was added with ligase enzyme and the mix was incubated at
   20°C for 1 hour. The ligation product was used for the reverse
   transcription with the M-MuLV Reverse Transcriptase in a thermocycler
   for 30 minutes at 42 °C and 10 minutes at 90 °C. Next, the enrichment
   of the cDNA was performed using PCR cycling: 2 min at 95 °C; 22-25
   cycles of 20 sec at 95 °C, 30 sec at 60 °C, and 15 sec at 72 °C; the
   final elongation for 2 min at 72 °C and the reaction was stopped at 4
   °C. PCR products were resolved on 6% Novex TBE PAGE gels (Thermo Fisher
   Scientific #EC6265BOX), and the band between 150 bp and 300 bp was cut
   out from the gel. Small RNAs were extracted from polyacrylamide gel
   using an adapted protocol, in which the DNA from gel slices was
   diffused in ddH2O. Afterward, the quantitative and qualitative analyses
   of the libraries were performed on an Agilent 2100 Bioanalyzer using
   Agilent High Sensitivity DNA Kit (Agilent Technologies, # 5067-4626)
   and Qubit dsDNA HS DNA Kit (Thermo Fisher Scientific, # [105]Q32854).
   The libraries were single-read sequenced for 51 nucleotides in a
   HiSeq2500 System (Illumina).

Data analyses

Real-Time qPCR assay

   The relative quantity of each analyzed miRNA was calculated using the
   ath-miR-159a spike-in as the reference miRNA and the following formula:
   ∆Ct=2^ - (Ct miRNA - Ct ath-miR-159a).

Small RNA sequencing

   FASTQs were trimmed for the adapters following the recommendations of
   the NEXTflex™ Small RNA-Seq Kit manufacturers. We used Bowtie [106]^42
   to align the reads against the human genome with the corresponding
   annotations (GRCh38/GENCODE-v26), with a mismatch 0, to avoid false
   positives. GENCODE contains a full set of annotations including all
   protein-coding loci with alternatively transcribed variants, non-coding
   loci with transcript evidence, and pseudogenes [107]^43. Quantification
   of the transcriptome was performed using Partek expectation
   maximization, employing Partek Flow application, software version 7.0.
   Only the miRNAs with 10 or more reads in the three replicas were
   considered. To estimate the relative miRNA levels from smallRNAseq
   data, the trimmed mean of M-values normalization method (TMM) was used
   [108]^44. To visualize the miRNAs identified by each method and their
   relative abundance, normalized data were represented using the pheatmap
   package v1.0.10 (default settings) in R 3.4.1 program (2014-04-10, R
   Foundation for Statistical Computing, Vienna, Austria). UpSet plot
   showing the total size and overlaps between the miRNAs sets isolated by
   each method and SEC fractionation was obtained using UpSetR [109]^45
   (available online in https:// gehlenborglab.shinyapps.io/upsetr/). We
   used the smallRNAseq data from Yagi et al. as a reference [110]^15.
   Data were obtained from the NBDC Human Database (dataset ID:
   JGAS00000000064) (https://humandbs. biosciencedbc.jp/en/) and analyzed
   in the same way as our data, to be able to compare the two datasets.

Correlation analysis

   Correlation coefficients between RT-qPCR and smallRNAseq data were
   calculated using the cor function in R 3.4.1 software (2014-04-10, R
   Foundation for Statistical Computing).

Gene target prediction and pathway enrichment analysis

   Predicted target genes for each miRNA were obtained using miRWalk 2.0
   database [111]^46. The target genes were only selected if they were
   predicted by at least eight of the twelve miRNA-target prediction
   programs hosted in the miRWalk 2.0. Pathway enrichment analyses were
   performed using the over-representation analysis module of the
   ConsensusPathDB web tool (CPDB) [112]^47. The default collections of
   Kyoto Encyclopedia of Genes and Genomes (KEGG) [113]^48, Reactome
   [114]^49, and BioCarta (http://
   cgap.nci.nih.gov/Pathways/BioCarta_Pathways) databases were utilized to
   analyze the predicted target gene lists.

Results and Discussion

   In this study, we compared several existing methods used to enrich the
   EVs and to analyze their miRNA cargo. We attempted to establish the
   most suitable technique for detecting CSF miRNAs in 200-µL samples.
   This volume was chosen considering the realistic amount of CSF that
   could be obtained from each patient to conduct such studies (200-300
   µL).

Assessing the efficiency of the protocols using Real-Time qPCR

   First, the efficiency of the six tested protocols was evaluated using
   RT-qPCR. Eight miRNAs previously detected by Yagi et al. that had
   variable concentrations in the exosomal fraction (using 7-mL CSF
   samples) were selected as a reference of the biofluid (Figure
   [115]S1A), including three EV-associated miRNAs (miR-1911-5p, miR-1264,
   and miR-34b-3p) and five additional miRNAs identified in both the
   exosomal and non-exosomal fractions (miR-21-5p, miR-451a, miR-92a-3p,
   miR-22-3p, and miR-30c-5p) [116]^15. Among these, miR-21-5p,
   miR-1911-5p, miR-30c- 5p, and miR-34b-3p have also been found in the
   brain and cerebellum by Meunier et al. (GEO accession number:
   [117]GSE40499) [118]^50. Here, we found that, of the eight evaluated
   miRNAs in our pool of samples, the four most abundant miRNAs were
   miR-21-5p, miR-451a, miR-92a-3p, and miR-22-3p. By contrast,
   miR-1911-5p, miR-1264, miR-34b-3p, and miR-30c-5p, were the least
   abundant miRNAs in our study (Figure [119]2). Yagi et al. have found
   the miR-1911-5p in the exosomal fraction and, to a much lesser extent,
   in the supernatant (Figure [120]S1A). Here, this miRNA was detected by
   RT-qPCR in the transcriptome obtained by all the protocols, with and
   without the enrichment step. Similarly, miR-1264, miR-30c-5p, and
   miR-34b- 3p, detected by Yagi et al. only in the exosomal fraction
   (Figure [121]S1A), were also found using the NOR and INV protocols
   (Figure [122]2A). This demonstrated that we could harvest miRNAs of
   different abundances in the CSF by analyzing as little as 200 µL of
   fluid. However, these results should be interpreted with caution since
   Yagi et al. have used the CSF from healthy adults [123]^15, not from
   infants. Additional studies of healthy infants are needed to
   corroborate our results.

Figure 2.

   [124]Figure 2
   [125]Open in a new tab

   Performance of different protocols measured using RT-qPCR. A, the
   number of TaqMan RT-qPCR replicates (from a total of 12) in which the
   studied miRNAs were detected. Twelve RT-qPCR reactions were performed
   for each method (3 EV isolations and miRNA extractions x 2 cDNA
   synthesis reactions x 2 technical duplicates of each cDNA reaction). B,
   relative quantification (in comparison with ath-miR-159a) of miR-21-5p,
   miR-451a, miR-92a-3p, and miR-22-3p and C, of miR-1911-5p, miR-1264,
   miR-30c-5p, and miR-34b-3p. Abbreviations: ultracentrifugation (UC),
   miRCURY Exosome Isolation Kit from Qiagen (QIA), Total Exosome
   Isolation Reagent from Invitrogen (INV), mirVana PARIS Kit from Ambion
   (PAR), and Plasma/Serum RNA Purification Kit from Norgen (NOR).

   Four of the assessed methods, NOR, INV, PAR, and QIA, detected the more
   abundant miRNAs in all replicas (12/12), except for miR-22-3p detection
   by QIA (10/12). The methods using total RNA from the cleared CSF (PAR
   and NOR) performed slightly better based on our eight reference miRNAs.
   PAR was the most efficient method for the most abundant miRNAs tested
   by RT-qPCR (Figure [126]2B). However, it did not detect the miR-34b-3p,
   the least abundant miRNA evaluated (Figure [127]S1A). In contrast, NOR
   was the most effective method when dealing with low copy number, based
   on the smallRNAseq data of Yagi et al. (miR-1911-5p, miR-1264,
   miR-30c-5p, miR-34b-3p), suggesting superior sensitivity (Figure
   [128]2C). Among the methods employing the EV enrichment step, INV
   obtained the lower Ct values. QIA and UC did not perform well with
   small CSF samples. However, we cannot rule out that this difference in
   performance is due to a modification in the INV procedure. INV protocol
   recommends two consecutive centrifugation steps before adding the
   exosome isolation reagent (2,000 x g for 30 minutes and 10,000 x g for
   30 minutes). In this study, all the samples were centrifuged at 3,000 x
   g for 15 minutes. Therefore, the INV procedure might have obtained both
   small (mainly exosomes) and large EVs, while QIA and UC might have
   achieved more precise exosome separation. This is supported by the fact
   that the exosomal miR-1911-5p was the most abundant species detected by
   QIA and UC. In any case, the other methods (NOR, INV, and PAR)
   performed better in the detection of the reference miRNAs when analyzed
   by RT-qPCR.

   Interestingly, INV and NOR were the only techniques capable of
   detecting all the miRNAs studied here by RT-qPCR, including CSF miRNAs
   associated with the vesicular fraction (miR-1911-5p, miR-1264, and
   miR-34b-3p) (Figure [129]2A) [130]^15. This suggests that these two are
   the most proficient methods for the analysis of low copy number.
   Overall, these results show that each protocol isolates a slightly
   different group of vesicles and miRNAs.

Characterization of protein and miRNA subpopulations in CSF using SEC

   The miRNAs can have different distributions among the CSF shuttles,
   such as different populations of EVs, RNA-binding proteins and
   lipoproteins. To study the distribution of miRNAs among the different
   CSF structures in infants, we fractionated 200 µL of CSF using an
   in-house SEC protocol. First, the performance of the method was
   evaluated by Western blotting (Figure [131]3A). CD63 and CD9 exosomal
   markers were predominantly detected in fractions 3 (F03) and fractions
   3 to 6 (F03-F06), respectively. These markers were found in earlier
   fractions than in most of the published reports for SEC
   [132]^51^-[133]^53. However, in our SEC method, the sample is separated
   into fewer fractions than usual, which might explain this discrepancy.
   The albumin (mostly in F05, F06, and F10) and the NSE (in F05 and
   mainly in F06) were also detected. Albumin is the most abundant protein
   in the CSF (245 mg/L) and accounts for 35-80% of the total protein
   content of this biofluid [134]^54. NSE is a valuable biomarker of brain
   tumors, used for assessing neuronal damage and formulating the
   prognosis of brain injury [135]^55. It is upregulated in the biopsies
   of GBM patients [136]^56. Here, we demonstrated that the level of NSE
   (found at 8 mg/L in the CSF of healthy individuals [137]^54 could be
   measured in 200 µL-samples of this fluid. Thus, we showed that our
   in-house SEC method could be used for fractionating small volumes of
   CSF.

Figure 3.

   [138]Figure 3
   [139]Open in a new tab

   Size-exclusion chromatography analysis of CSF. A, Western blot analysis
   of CD63, CD9, neuron-specific enolase (NSE), and human serum albumin
   (HSA) proteins. Molecular weights are shown in KDa. B, the number of
   TaqMan RT-qPCR replicates (from a total of 12) in which the studied
   miRNAs were detected. C, quantification (relative to ath-miR-159a) of
   miR-21-5p, miR-451a, and miR-92a-3p and D, of miR-1911-5p, miR-22-3p,
   and miR-30c-5p.

   We performed a RT-qPCR assay to examine the distribution of our eight
   reference miRNAs among the fractions (Figure [140]3B). We found that
   miR-21-5p, miR-451a, and miR-92a-3p were the most abundant in fractions
   F06, F07, and F09 (Figure [141]3C). In the case of miR-22-3p,
   relatively large amounts were obtained in F05, F07, and F09 (Figure
   [142]3D). Overall, these miRNAs showed a similar distribution pattern
   in 12 fractions, where the two main miRNA subpopulations were observed.
   The first subpopulation, from F05 to F08, co-fractioned with NSE and
   albumin while the second one (from F09 to F12) co-fractioned with the
   albumin. Interestingly, the miR-30c-5p was only detected in the
   fraction F03 (Figure [143]3D), co-fractionating with the exosomal
   markers. This is in agreement with the results of Yagi et al. who have
   found that this miRNA is 3 to 5 times more abundant in the vesicular
   CSF fraction than in the EV-depleted CSF [144]^15. miR-1911-5p, the
   exosome-associated miRNA, was highly expressed in the exosomal fraction
   (F03) and to a lesser extent in F09, also in accord with the enrichment
   in the vesicular fraction reported by Yagi et al. [145]^15. By
   contrast, miR-1264 and miR-34b-3p were not detected using the SEC when
   analyzing 200-µL CSF samples. These miRNAs were the least abundant
   references in our study and were detected with fewer than 10 counts by