Dead or Alive? Molecular life-dead distinction in human stool samples reveals significantly different composition of the microbial community

The gut microbiome is strongly interwoven with human health. Conventional gut microbiome analysis generally involves 16S rRNA gene targeting next generation sequencing (NGS) of stool microbial communities, and correlation of results with clinical parameters. However, some microorganisms may not be alive at the time of sampling, and thus their impact on the human health is potentially less significant. As conventional NGS methods do not differentiate between viable and dead microbial components, retrieved results provide only limited information. Propidium monoazide (PMA) is frequently used in food safety monitoring and other disciplines to discriminate living from dead cells. PMA binds to free DNA and masks it for subsequent procedures. In this article we show the impact of PMA on the results of 16S rRNA gene-targeting NGS from human stool samples and validate the optimal applicable concentration to achieve a reliable detection of the living microbial communities. Fresh stool samples were treated with a concentration series of zero to 300 μM PMA, and were subsequently subjected to amplicon-based NGS. The results indicate that a substantial proportion of the human microbial community is not intact at the time of sampling. PMA treatment significantly reduced the diversity and richness of the sample depending on the concentration and impacted the relative abundance of certain important microorganisms (e.g. Akkermansia, Bacteroides). Overall, we found that a concentration of 100 μM PMA was sufficient to quench signals from disrupted microbial cells. The optimized protocol proposed here can be easily implemented in classical microbiome analyses, and helps to retrieve an improved and less blurry picture of the microbial community composition by excluding signals from background DNA.

Introduction
The function of microbial communities depends on which community members are dead or alive, and the information about their status can be crucial for questions concerning microbial ecology or clinical relevance. For example a viable pathogenic bacterium poses a different risk to humans when present in pharmaceuticals or food as it might cause infection 1 , whereas contamination with dead microorganisms poses a potential risk for intoxication. Furthermore, clinical efficiency of fecal microbiota transplants depends on the living bacterial fraction of the preparation as only these bacteria could colonize the gut of the receiving patient 2 .
Several techniques have been developed to differentiate between live and dead microbes, focusing on three basic principles: To be considered alive, a microbial cell must be (1) intact, (2) able to reproduce, and (3) metabolically active (Emerson et al, 2017). The capability to reproduce can be ultimately assessed by cultivation-dependent methods, as, for the formation of colony forming units, cells have to divide and grow. However, only a comparatively small fraction of the Earth's microbiology can be cultivated using standard laboratory techniques at all 3,4 . Metabolic activity can be estimated by metabolomics analyses or by analysing the content of (r)RNA, as it reflects the activity of microbial transcription; however, also dead cells can contain a considerable amount of RNA, blurring the results and conclusions 5 . Besides these vague approaches, the intactness of a cell is an unquestionable prerequisite for life, as life outside of a cell compartment does not exist.
One methodology to assess the intactness of a cell relies on the application of propidium monoazide (PMA). PMA masks free DNA and DNA of non-intact cells 6 , as it can pass disrupted cell walls and intercalate into the DNA double helix. Upon light exposure, PMA is covalently bound, blocking this DNA from subsequent PCR amplification 6 . When applied prior to DNA extraction, sequencing or qPCR, PMA treatment results in exclusive detection of the intact microbial fraction. By this principle, PMA treatment may also improve detection of rare community members as it helps to exclude background DNA from analysis 7 . PMA has been applied in a wide variety of environmental and clinical microbiome studies, including research on the human microbiome [7][8][9] , indoor environments and built systems 10,11 as well as on food products [12][13][14] . PMA is most typically used in standard PCR-based assays, but has also been successfully applied in combination with e.g. qPCR [15][16][17] , metagenomics 18 , fluorescence in situ hybridization (FISH) 19 , fluorescence microscopy 20 and microarrays 21 . Another application aimed at the treatment of commercial PCR reagents to mask DNA contaminations (the "kitome"; 12 .
The original method foresees sample treatment with defined PMA concentration (50 µM), incubation in the dark (5 min, agitation) and a subsequent light exposure (2 min, 650 W lamp; 22 . However, the efficiency of PMA treatment is highly affected by density, homogeneity and turbidity of the handled sample 23,24 and thus the original methodology might not be applicable to e.g. stool samples, although PMA treatment of faeces samples is as well a desired goal and has already been applied 2,25,26 . However, despite the high biomass and the complexity of faeces, optimal conditions of PMA treatment of faeces samples have not been elaborated yet. As a consequence, we wanted to know, whether an increased PMA concentration could compensate the problems of turbid and complex biosamples, such as faeces.
We herein analyze the effect of increasing PMA concentrations on the microbial community composition in human stool samples using amplicon-based next generation, with the goal to establish a guideline on how to reliably apply PMA in complex biosamples.

Samples and general organisation of experiments
Fresh human feces was obtained from a healthy human individual and kept on ice until processing. The samples were diluted 1:10 (w/v) in DNA-free, sterile 1x phosphate buffered saline (PBS), and 500 µl aliquots of the thoroughly mixed dilution were treated separately with increasing concentrations of PMA. We performed two subsequent experiments, experiment A and B. In experiment A, we studied the effects of PMA with 11 different concentrations between 0 µM and 100 µM PMA, and in experiment B we tested five different concentrations of PMA between 0 µM and 300 µM. The fecal samples for experiment A and B were obtained from the same person, but at different time-points. The samples were sequenced in the same Illumina MiSeq run.

PMA cross-linking and DNA isolation
PMA was dissolved in PCR grade water to create a stock concentration of 20 mM and stored at -20°C in dark until usage. PMA was added directly to 500 µl sample aliquots applying the following PMA concentrations in experiment A: 0 µM, 10 µM, 20 µM, 30 µM, 40 µM, 50 µM, 60 µM, 70 µM, 80 µM, 90 µM and 100 µM, and the following concentrations in experiment B: 0 µM, 50 µM, 100 µM, 150 µM, and 300 µM. The samples were shaken on ice in dark for 10 minutes (IKA Rocker, 60 rpm) and light-exposed for 15 minutes in a standard PMA-Lite™ LED photolysis device with occasional shaking. After photo-induced crosslinking, DNA was extracted using the PowerSoil DNA extraction kit (Mo Bio Lab, Inc.) following the manufacturer's instructions. DNA concentrations were measured using the Qubit (Thermo Fisher Scientific) method and each assay was diluted to 10ng/µl in PCR grade water as template for subsequent PCR reactions. All experiments were performed in triplicates. DNA extraction blank samples were used to control for the sterility of reagents and equipment.

Library preparation for next generation sequencing (NGS)
Variable region V4 of the 16S rRNA gene was amplified with universal PCR primers 515F (5′-GTGCCAGCMGCCGCGGTAA-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) using TaKaRa Ex Taq polymerase (Clontech, Japan) 27 . The cycling conditions were: initial denaturation at 94 °C for 3 min, followed by 35 cycles of denaturing at 94 °C for 45 s, annealing at 60 °C for 60 s, and elongation at 72 °C for 90 s. The final elongation step lasted 10 min. Negative controls (no template) were included in PCR. Library preparation and sequencing were carried out at the Core Facility Molecular Biology at the Center for Medical Research, Graz, Austria. Briefly, DNA concentrations were normalized using a SequalPrep™ normalization plate (Invitrogen), and each sample was indexed with a unique barcode sequence (8 cycles index PCR). Pooled samples were purified with gel-cut procedure. Sequencing was conducted using Illumina MiSeq device. Sequence data were deposited in The European Nucleotide Archive (ENA) with study accession number PRJEB25855.

Sequence data processing and analysis
Raw sequence reads were preprocessed and filtered using the R package dada2 (version 1.4.0) according to the proposed processing pipeline 28 . Briefly, reads were demultiplexed, forward and reverse reads were quality filtered (min. score: 30), merged, and the dada2 core algorithm was applied. Taxonomic affiliations were assigned according to SILVA v123 database 29 . All ribosomal sequence variants (RSVs) which were present in negative controls were removed from the dataset; Normalization was performed by transformation to relative abundances. The downstream analyses were performed using R software package (version 1.0.136) 30 . Alpha and beta diversities were calculated using the R packages phyloseq (version 1.20.0) 31 and vegan (version 2.4) 32 .
To compare microbial diversity in samples treated with different PMA concentrations, alpha diversity was calculated using the Shannon, Observed and Inverse Simpson index. Normal distribution was tested by the Shapiro-Wilk test, and statistical significance was tested either by Kruskal-Wallis (if not normally distributed) or ANOVA (if normally distributed). The Dunn's test was used as post-hoc test (Benjamin Hochberg correction).
Beta diversity analyses were performed to examine differences between microbial community profiles at different PMA concentrations. Principal coordinate analysis (PCoA) was performed to study the relationships and variation between samples. Statistical significance was tested using adonis (seed 1) and further confirmed by dispersion test (permutations: 999). Nonmetric multidimensional scaling (NMDS) was applied to visualise these differences. The data were also subjected to linear discriminant analysis effect size (LEfSe) analysis 33 to determine specific microbial markers for PMA treatment of different concentrations.

Results
In order to determine the influence of increasing PMA concentration on the microbial community profile and diversity, we carried out two experiments: In experiment A, we compared the concentrations of 10 µM to 100 µM PMA (in 10 µM steps) to non PMA treated samples and analysed the possible effects of PMA, and in experiment B, we tested the concentrations of 50 µM, 100 µM, 150 µM and 300 µM PMA to confirm experiment A. In both experiments we compared the PMA treated samples to non-treated samples.
Obtained sequence data were processed using dada2 28 , and 1,597,041 sequence reads were obtained for experiment A (33 samples plus controls), and 716,611 sequence reads for experiment B (15 samples plus controls). After removing all taxa which were present in negative controls, 1,596,911 RSV counts (unique sequence reads) affiliated to 437 different taxa were left for experiment A, and 715,808 RSV counts (unique sequence reads) affiliated to 329 different taxa for experiment B. These data were analysed to show how the PMA treatment with different concentrations can influence alpha and beta diversities and the microbial community profile in specific taxonomic groups.
The analysis revealed a typical human gut microbial community profile within the studied samples. In experiment A we identified 16 microbial phyla, of which 13 were affiliated to Bacteria and 3 were affiliated to Archaea (Euryarchaeota, MSC (miscellaneous Crenarchaeotic Groups), and Thaumarchaeota). The most abundant phyla were Bacteroidetes (52.2 % of all sequence reads), Firmicutes (37.7%), and Proteobacteria (4.4%). At genus level, the most abundant identified taxa were Bacteroides (37.7% of all sequence reads), Faecalibacterium (6%), and Akkermansia (4%).
In experiment B, we identified 11 microbial phyla of which 9 were affiliated to Bacteria and 2 to Archaea (Euryarchaeaota and Thaumarchaeota). Again, the most abundant phyla were affiliated to Bacteroidetes (64.3% of all sequence reads), Firmicutes (29.1%), and Proteobacteria (5.2%), while the most abundant genera were Bacteroides (42.9%), a taxon assigned to Bacteroidales family S24 (10.1%), and Alistipes (5.4%). The most abundant phyla identified in experiment A and experiment B are depicted in Figure 1.

PMA treatment significantly decreases microbial richness and diversity (alpha diversity)
We studied how the PMA treatment might affect the alpha diversity of microbial communities in stool samples. The results show that alpha diversity (observed richness, Shannon and inverse Simpson indices) overall decreased with PMA treatment and that the effect was PMA concentration dependent. In experiment A the observed richness significantly decreased (ANOVA, p=1.57e-06) with 30 µM, 40 µM, and 50 µM PMA concentrations when compared to non PMA treated control (all p-values were <0.05, Tukey's post-hoc test, confidence level 0.95). Additionally, the Shannon diversity index decreased with 100 µM PMA treatment compared to untreated samples (ANOVA, p=0.00767). In experiment B, a significant decrease in diversity was detected in the Shannon index when 300 µM PMA was used (p=0.03121), and with inverse Simpson indices when 150 µM PMA (p=0.0498812) and 300 µM PMA (p=0.0117023) was used, compared to 0 µM PMA samples. Figure 2 summarizes the results, and highlights all statistically significant changes in alpha diversity upon PMA treatment.

PMA treatment significantly alters the microbial community profile (beta diversity)
We studied the effect of PMA treatment also on the overall microbial community profile. Therefore, we applied various beta diversity measures, including Bray-Curtis distance (unweighted) and tested for significant differences using Adonis, confirmed with a dispersion test. We visualised the beta community profile via nonmetric multidimensional scaling (NMDS).
The effect of PMA treatment was significant with respect to concentration. The results show that PMA treatment, particularly in higher concentrations, significantly shifted the microbial community profile (Figure 3, PCoA plots) (Adonis p<0.001), from 0 µM PMA to higher concentrations (Figure 3, NMDS). The significance was emphasized with a dispersion test (permutations: 999; both p-values >0.8). Additionally, we were interested in which taxa are responsible for the community shift. Using linear discriminant analysis effect size (LEfSe) algorithm we compared the median values of 100 most abundant microbial RSVs between samples without PMA treatment and different PMA concentrations. We were interested in particular if certain taxa are significantly less abundant in PMA treated samples, suggesting they are in non-intact (i.e. dead) state and consequently often overestimated regarding their relative abundance in microbiome studies, or if particular taxa are not affected by the treatment, or increase in relative abundance, indicating they are present in stool samples as intact, viable cells.
In experiment A, the 100 most abundant RSVs represented 7 phyla, and in experiment B 6 phyla, which were the same as in experiment A except the phylum Verrucomicrobia, represented by one RSV of Akkermansia. PMA treatment did not completely remove any taxon or RSV in experiment A, but in experiment B a total of 5 RSVs were not detected after PMA treatment, indicating these taxa were in nonviable state (Supplementary Table 2). In both experiments, the majority of the 100 most abundant RSVs either increased or decreased statistically significant (p<0.05) in relative abundance at one or more PMA concentrations (experiment A 75% RSVs changed significantly in their relative abundance, in experiment B 68%).
All RSVs that changed significantly in experiment A or B are presented in Table 1, and information including all identified phyla and genera in both experiments can be found in Supplementary In contrast to Firmicutes, relative abundance of the phylum Bacteroidetes increased (69% of RSVs in experiment A / 68% of RSVs in experiment B). The majority of RSVs belonging to the genera Alistipes (75% in experiment A / 100% in experiment B), Bacteroides (71% in experiment A / 77% in experiment B), and Parabacteroides (50% in experiment A / 100% in experiment B) show significant increase in relative abundance after PMA treatment (Table 1,  Supplementary table 1, Supplementary table 2). Additionally, the phylum Lentisphaerae (genus Victivallis) increased significantly in relative abundance in both experiments.
Change in relative abundance of Bifidobacterium (Actinobacteria) and Akkermansia (Verrucomicrobia) upon PMA treatment was only detectable in experiment A as these taxa were not found in experiment B. The relative abundance of Bifidobacterium decreased significantly when the sample was treated with 60 µM PMA or more; the relative abundance of Akkermansia it reduced significantly when the sample was subjected to at least 30 µM PMA treatment. The results suggest that if PMA treatment is not applied, the relative abundance or relevance of these bacteria, which are known to carry beneficial properties for human health, could be overestimated.
Notably, in both experiments we identified four proteobacterial RSVs (Bilophila, Escherichia/Shigella, Sutterella, and Thalassospira), and in both experiments Escherichia/Shigella and Thalassospira were relatively decreased and Sutterella was increased with PMA treatment. In both experiments, the abundance of genus Bilophila did not alter. These results indicate that Escherichia/Shigella and Thalassospira are found in gut also in nonviable state and their abundance can be overemphasized.

Concentration of 100 µM PMA is sufficient to discriminate intact and dead cells in stool samples
We were interested in the optimal concentration of PMA needed to mask the dead cells in stool samples, and studied with which concentration the significant changes in relative abundance are visible at RSV level.  Figure 4.  Table 1.
In experiment B we tested if increasing the amount of PMA concentration up to 300 µM would significantly change the community membership at RSV level. Of 100 most abundant RSVs which were analysed, 68 RSVs changed significantly with PMA treatment. We applied PMA at four different concentrations (50 µM, 100 µM, 150 µM, and 300 µM), and found that 49 RSVs at 50 µM PMA concentration, 44 RSVs at 100 µM PMA concentration, 43 RSVs at 150 µM PMA concentration, and 42 RSVs at 300 µM PMA concentration were increased or decreased significantly. Interestingly, for 59 out of 68 RSVs (87%) the significant change occurred already at 50 or 100 µM PMA, suggesting that using a larger concentration does not substantially affect the community profile on RSV level.

Firmicutes/Bacteroidetes ratio decreased significantly upon PMA treatment
As detected with LEfSe analysis most of the RSVs belonging to phylum Firmicutes decreased in relative abundance with PMA treatment, and RSVs in phylum Bacteroidetes increased. As Firmicutes/Bacteroidetes ratio in human gut microbiota has been connected to human health and disease, we pursued to look deeper into how the PMA treatment changed this ratio. We found that the Firmicutes/Bacteroidetes ratio decreased by 21% in experiment A at a concentration of 30 µM PMA (Student's t-test p=0.031), and even 31% at 100 µM of PMA (Student's t-test p=0.018). In experiment B the Firmicutes/Bacteroidetes ratio did not further decrease with increasing PMA concentration, but a statistically significant 30-33% reduction compared to 0 µM PMA was observed with all PMA concentrations (t-test p values range 0.0004 -0.04) (Figure 5.).

Discussion
The purpose of this study was to analyze the correlation of PMA concentration and the microbial composition after NGS in complex biosamples such as stool, with the goal to establish a guideline for future applications.
Most studies using PMA with stool samples were performed with standard PMA concentration of 50 µM. However, testing the effect of increasing PMA concentrations on stool samples, and determining the relative abundances in correlation with live / dead status of specific microorganisms has not been studied before. Here, we applied Illumina MiSeq sequencing to decipher the effect of PMA treatment on turbid stool samples and their diverse microbial community.
This study revealed that PMA treatment significantly decreases microbial richness and diversity (alpha diversity) and alters the microbial community profile (beta diversity). The magnitude of these effects was found to be concentration dependent. Furthermore, the increase and decrease in relative abundance after PMA treatment was taxon-specific, revealing a significantly different composition of the microbial community when only intact cells were targeted.
A decrease in diversity suggests that either certain taxa totally disappeared (richness), or the evenness decreased when the relative abundances of different taxa shifted upon PMA treatment. In our experiments, the majority of 100 most abundant RSVs either increased or decreased statistically significantly in relative abundance at one or more applied PMA concentrations, but only few RSVs completely disappeared. This suggests that PMA treatment particularly affected the evenness of the microbial community. Furthermore, the change in beta diversity suggests that the community profile shifted upon PMA treatment: certain taxonomic groups became more abundant, some less abundant, and some were not detectable any more. This indicates that they were not intact, but represented in the non PMA treated samples only by fragments of free DNA or DNA within cells with fractured cell walls. Thus, we state that without using any live/dead distinction method, the active and significant microbial diversity in stool might be miscalculated.
The effect of PMA on both alpha and beta diversity was clearly concentration dependent. In particular, the application higher than 100µM PMA showed a significant decrease in the alpha diversity compared to untreated samples. Additionally, the community profile shift was stronger with higher PMA concentrations, suggesting that low PMA concentrations only can mask part of the free DNA or DNA inside fractured cells, because of turbidity.
We observed that the increase and decrease in relative abundance after PMA treatment was taxon specific, revealing a significantly different composition of the microbial community when only intact cells were targeted. Particularly the relative abundance of Firmicutes was significantly reduced and the relative abundance of Bacteroidetes significantly increased when PMA treatment was applied, leading to the conclusion that without any live/dead staining or viability testing the number of Firmicutes might be significantly overestimated while Bacteroidetes are underestimated. In particular, the Firmicutes/Bacteroidetes ratio has been connected to human health in a number of publications [34][35][36] .
Gram-positive Firmicutes are predominantly associated with energy harvest from diet 37,38 , while Gram-negative Bacteroidetes are known to perform several beneficial processes related to degradation of complex sugars and proteins into short chain fatty acids (SCFAs) 39 , and the relative proportion of Bacteroidetes has been observed to be decreased in obesity 34 . In the Bacteroidetes phylum, we detected a systematic and significant increase of the genera Bacteroides, Alistipes, and Parabacteroides upon PMA treatment. Bacteroides comprises the most substantial portion of the human gastrointestinal microbial community, and is known to play a fundamental role in processing complex molecules to succinate and acetate (major fermentation products) 40 in the host intestine 41,42 , and it contributes to the lean phenotype 43 .
Alistipes, and Parabacteroides used to belong to genus Bacteroides and thus share many metabolic features, including fermentation of complex sugars, and production of acetic and succinic acids [44][45][46] .
Within the phylum Firmicutes we observed a systematic decrease of the genus Faecalibacterium, which is one of the most abundant and important commensal bacteria of the human gut microbiota. Faecalibacterium is known to produce butyrate and other shortchain fatty acids through the fermentation of dietary fiber and to boost the immune system. Additionally, relatively low levels of F. prausnitzii in human intestines were associated with e.g. inflammatory bowel diseases (Crohn's disease) 47 and ulcerative colitis 48 , obesity 49 , asthma 50 and depression 51 .
Besides Faecalibacterium, also other important human gut bacteria were significantly affected by the PMA treatment: the genera Bifidobacterium and Akkermansia both decreased in relative abundance upon PMA treatment. These bacteria are known to carry beneficial properties for human health and their application as probiotics has been extensively studied. For example Bifidobacterium has been connected to beneficial psychological effects 52 better mental health 53 , and allergy prevention 54 . It is suggested to be effective at protecting against infectious diseases 55 , whereas Akkermansia is known to stimulate immune system, improve gut barrier function [56][57][58] , and prevent the development of obesity (fat mass development, insulin resistance and dyslipidemia) in mice studies 58 . Additionally, the level of Akkermansia muciniphila was reported to be drastically reduced in patients with Crohn's disease and ulcerative colitis, and suggested to be a health biomarker 59 .
Based on our study, supported by the results of a study aiming at the discrimination of viable and dead fecal Bacteroidales by quantitative PCR 60 , we suggest using a concentration of 100 µM of PMA to efficiently block background DNA from open or broken cells in fecal samples.
Although human faeces samples do not reflect the situation at the respective site within the intestine 61, 62 , they are used for numerous microbiome analyses and correlation studies of microbial composition and health or disease. Excluding the background signals by PMA treatment can increase the impact of such studies, as the intact microorganisms might mirror the in situ situation in more detail.

Limitations of the study
The stool samples were immediately processed and handled in the dark throughout the experiments. However, the samples were exposed to air (21% oxygen) for a short period of time during dilution and PMA treatment, which might affect the viability of the microbial community 2 . However, we cannot think of any chemical process, which would, in the dark but in presence of air, induce immediate cell wall/cell membrane damage, and thus affect the outcome of the PMA treatment 63 , so that we did not evaluate the impact of the oxygen in the ambient air on our results. In this regard, the study setup was performed according to feasibility and common practice, and the samples were treated with PMA without delay, but under normal atmosphere.

Conclusion
Treatment with propidium monoazide is a relatively simple and cheap protocol to exclude background DNA from damaged cells in DNA-based microbiome studies. Herein, we propose to use 100 µM PMA for optimal live/dead distinction in stool microbiome analyses, as we identified the standard concentration of 50 µM to be less effective in such turbid samples. In our study, we found that the intact, and thus most likely viable fraction of the microbial community, differs significantly from the overall microbial profile. This finding indicates, that many previous studies might have over-or underestimated the importance of key microbial species in gut samples, as they did not consider the live/dead situation of the cells.

Ethics approval and consent to participate
Research involving human material was performed in accordance with the Declaration of Helsinki and was approved by the local ethics committees (the Ethics Committee at the Medical University of Graz, Graz, Austria). Stool samples have been obtained covered by the ethics vote 27-151 ex 14/15.

Consent for publication
Not applicable.

Availability of data and material
Sequence data were submitted to the European Nucleotide Archive (ENA) with the study accession number PRJEB25855.
Microsoft Excel File Format, .xlsx Description of data: Summary of 100most abundant taxa in Experiment A, and the changes in relative abundance upon PMA treatment. Bacterial taxa (RSVs) that increased are marked in green, and taxa that decreased are marked in red.
Microsoft Excel File Format, .xlsx Description of data: Summary of 100most abundant taxa in Experiment B, and the changes in relative abundance upon PMA treatment. Bacterial taxa (RSVs) that increased are marked in green, and taxa that decreased are marked in red.


extfieldsofstudy:
Materials Science
Medicine

text:
Large Volume Electron Microscopy and Neural Microcircuit Analysis

One recent technical innovation in neuroscience is microcircuit analysis using three-dimensional reconstructions of neural elements with a large volume Electron microscopy (EM) data set. Large-scale data sets are acquired with newly-developed electron microscope systems such as automated tape-collecting ultramicrotomy (ATUM) with scanning EM (SEM), serial block-face EM (SBEM) and focused ion beam-SEM (FIB-SEM). Currently, projects are also underway to develop computer applications for the registration and segmentation of the serially-captured electron micrographs that are suitable for analyzing large volume EM data sets thoroughly and efficiently. The analysis of large volume data sets can bring innovative research results. These recently available techniques promote our understanding of the functional architecture of the brain.

INTRODUCTION
Electron microscopy (EM) has been used in neuroscience research for more than 60 years. EM was introduced as a cutting edge tool to observe a neural structure at super high resolution in a dimension completely different from the optical light microscope, making synaptic structure visible, and it provided unprecedented datasets and an entirely new perspective in neuroscience research. In the 1980s, with Golgi's silver staining, which sparsely stains individual neurons, or with an immunohistochemical staining method, which targets a specific brain cell population, it has been possible to analyze the ultrastructure, including synaptic contacts, of identified neural structures (Somogyi, 1977;Somogyi and Cowey, 1981;Kubota et al., 1987;Kisvárday et al., 1990). Since the early 1990s, neuronal structures have been three-dimensionally reconstructed from successive electron micrographs captured with manually-collected serial ultrathin sections (Harris et al., 1992;White et al., 1994;Kubota et al., 2007). This method allows us to obtain quantitative information from neural structure, e.g., synapse density, dendritic dimensions and organelle structure. This strategy, however, requires expert skills to cut and collect continuous ultrathin sections, and capturing serial section electron micrographs using transmission EM (TEM) is time-consuming and labor-intensive. Despite these drawbacks, the method attracted neuroscience researchers due to its capability to visualize synaptic contacts between neurons.

ATUM-SEM
ATUM-SEM has several valuable features for neural microcircuit investigation (Heymann et al., 2006;Mikuni et al., 2016;Morgan et al., 2016). One of its advantages is that the same serial ultrathin sections can be observed multiple times . We took advantage of this property to image a region of interest (Figure 1) as follows. First, serial sections were imaged at very low magnification (100-200 nm/pixel) to identify all sections on the tape strips attached to a wafer. Then, an electron micrograph of an entire or partial ultrathin section at low magnification (40-50 nm/pixel), where neuronal somata and dendrites can be easily identified, was taken from each of all the sections. A mosaic electron micrograph stitched with 3 × 5 tile images of 8,000 × 8,000 pixels in low magnification covered rat cerebral cortex tissue sections from the pia to the deep layers. The mosaic images were stitched with an image analysis application, Fiji/TrakEM2 1 (Cardona et al., 2012;Schindelin et al., 2012). Finally, a region of interest in the low-magnified electron micrograph was imaged again from each section, this time at a high magnification (4 nm/pixel) for the analysis of fine neural structure. Thus, we captured electron micrographs of 25,000 × 25,000 pixels covering a large area, i.e., 100 µm × 100 µm, which has a sufficient resolution to see synaptic structures (Figure 1). The serial electron micrographs were aligned using Fiji plugins (Registration/Register Virtual Stack Slices or TrakEM2). We reconstructed neuronal elements in the EM data set threedimensionally (Figure 1). Using the ATUM procedures, Morgan et al. (2016) obtained a four by four montage of image tiles (each tile was a 25,600 × 25,600 pixel images, 4 nm pixels) from about 10,000 of 30 nm thick serial sections and the final image size was 100 TB of approximately 400 µm square × 280 µm. It took about 10 days to acquire images with in lens secondary electron (SE) detector and a dwell time of 50 ns. It is worth noting that theoretically we could get larger imaging areas with a mosaic image assembled from multiple image tiles; however, the file size of such a large volume EM data set would be huge. For example, an electron microscopic image data set of 1 mm 3 1 https://imagej.net/TrakEM2 with 5 nm/pixel lateral resolution, and 25 nm/section would result in a dataset of 1.6 petabytes (PB). Thus, it is necessary to develop an application that can efficiently analyze huge data sets and to have a file server with a sufficiently large storage capacity.

CARBON NANOTUBE TAPE
Given the practical requirements for automatically collecting sections, collection tapes for serial ultrathin sections should be optimized for the ATUM-SEM method. Tapes for the ATUM must be electrically conductive to capture images without aberrations using SEM, as well as hydrophilic and physically sturdy. Jeff Lichtman and his colleagues at Harvard University, Cambridge, MA, USA, developed a carbon-coated Kapton tape . The Kapton tape is an insulation film, so it lacks conductivity. To make its surface conductive, carbon is deposited on the tape surface using a custom-made high-vacuum carbon-deposition coater with a motorized wheelto-wheel winder. In addition, since the hydrophobic property of the tape surface causes sections to wrinkle during section collection, it is necessary to hydrophilize the tape surface using plasma discharge . Although the carboncoated Kapton tape is used for section collection with the ATUM Kasthuri et al., 2015;Morgan et al., 2016), problems remain: the carbon-coated Kapton tape shows a high surface resistance (19-6,530 MΩ/square) and surface inhomogeneities, which can interfere with imaging . Moreover, the carbon-coated Kapton tape for the ATUM is yet to be commercialized so the quality of the tape is likely inconsistent and its supply can be sporadic.
Therefore, we searched for substitutes and found a carbon nanotube (CNT)-coated polyethylene terephthalate (PET) tape, with which high-quality electron micrographs of brain tissue can be obtained . Positive features of the CNT tape include extremely high conductivity/low surface resistance (242 Ω/square), good resilience, inclusiveness of elements with a very low background signal noise, chemical and mechanical strengths, vacuum compatibility and resistance to beam damage. These features are favorable for ATUM-SEM and, for this application, are comparable or superior to the carbon-coated Kapton tape.

OPTIMUM IMAGING CONDITIONS FOR SEM
Imaging conditions greatly affect the image quality of electron micrographs. The technology to image tissues from ultrathin sections using SEM was invented a decade ago, and it has continued to undergo considerable improvement to this date. There are many factors that affect image quality, including acceleration voltage, probe current, the type of detector for capturing the image signal, aperture, working distance, tissue staining methods, section thickness, etc. It is important to know the optimal value for each imaging factor and to use the best combination thereof. Monte Carlo simulations, which FIGURE 1 | Pipeline of the automated tape-collecting ultramicrotomy (ATUM)-scanning electron microscopy (SEM) method. The pathway of a Kapton tape (orange color) in the ATUM (Boeckeler Instruments, Inc., Tucson, AZ, USA) is shown in the upper left panel. Sections on tape strings adhered on 4-inch wafer is shown in the upper right. The carbon nanotube (CNT) tape strips in the wafer appear in black, which is a color of a conductive double-sided adhesive tape. Serial sections (gray color) are irregularly clustered on the tape. Copper foil tape between the CNT tape was used to electrically ground the CNT layer to the wafer to secure an escape route for incident electrons. The electron micrographs in lower panels are taken from an ultrathin section of the brain tissue on the CNT tape. The left micrograph was taken with a backscattered electron (BSE) detector of field emission SEM (FE-SEM), Sigma (Carl Zeiss Microscopy GmbH, Oberkochen, Germany) and a large area imaging apparatus for SEM, Atlas 5 (Fibics incorporated, Ottawa, ON, Canada), while middle and right panels were taken with an acceleration voltage 1.5 keV, OnPoint BSE detector (Gatan Inc., Pleasanton, CA, USA) in an FE-SEM, GeminiSEM 300 (Carl Zeiss Microscopy GmbH, Oberkochen, Germany). Adapted from Kubota and Kawaguchi (2018) and .
simulate the trajectory of electrons projected onto and into the tissue, are used for determining optimum values (Drouin et al., 2007). However, it is not known whether the Monte Carlo simulation results exhibit actual projected electron trajectories in the plastic embedded brain tissue sections. We examined this issue using electron micrographs captured from 50-nmthick brain tissue sections embedded in epoxy resin on an open reel tape at various acceleration voltages. We found that as we increased the acceleration voltage, more magnetic crystals of the open reel tape overlapped with the section image (Figure 2; . We compared this phenomenon with the Monte Carlo simulation analysis to evaluate its validity. We varied the atomic fraction value of the material in the tissue block and found that the actual image results obtained with the open reel tape matched the simulation analysis result well with the atomic fraction value of epoxy resin (nH = 0.53, nC = 0.35, nO = 0.12) without including metals from the staining process (Hennig and Denk, 2007;. Brain tissue sections are mostly composed of epoxy resin, and stained tissue membranes are just a minor portion of the section. Therefore, we think that the Monte Carlo simulation can adequately describe the actual projected electron trajectories in stained brain tissue sections embedded in epoxy resin. We found a positive correlation between acceleration voltage and the depth of projected electrons in the tissue, i.e., the interaction volume (Figure 2), which is defined as the volume inside the tissue section in which electrons in the electron beam can interact with tissues. This suggests that a micrograph of a good quality can be obtained with an optimum acceleration voltage, with which the projected electrons interact solely within the section thickness. We assume that signal predominating electrons should be reflected from the more superficial portion of the tissue, because as electrons are projected into the deeper part of the tissue, they must lose energy. Assuming that 80% of the projected electrons carry a sufficient signal that could be detected by the SEM detector, the simulation analysis results suggest that electrons projected with an accelerating voltage of 1.5 keV or 2 keV would interact with the 50-nm-thick tissue section most efficiently (Figure 2) . In addition, the detector sensitivity of the recently-developed field emission SEM (FE-SEM) has been significantly improved compared to that in previous years, allowing acquisition of high quality electron micrographs at high magnification using a low acceleration voltage . Indeed, an electron micrograph of rat cortex tissues processed with modified rOTO protocol (Hua et al., 2015;Maclachlan et al., 2018) under these conditions shows fine ultrastructure clearly (Figure 3). The Monte Carlo simulation analysis suggests the assumption that the 80% of projected electrons can provide an efficient signal from tissue sections, and their respective interaction volumes in the tissue section could be from the surface to 15 µm depth at an acceleration voltage of 1 keV, to 33 µm depth at 1.5 keV, and to 50 µm at 2 keV (Figure 2). We can use the interaction volume estimation to find optimum imaging conditions, although these estimates could be affected by other mechanical specifications of individual SEMs.

AUTOMATED SERIAL BLOCK FACE IMAGE ACQUISITION SCANNING ELECTRON MICROSCOPY: FIB-SEM
There are several automated image acquisition electron microscopies for obtaining three-dimensional reconstruction at the EM level (Table 1). Each type of microscope has specific features, and understanding these features will help to select the microscopy that suits best for each research project. Of the currently available techniques, the technology of the automated acquisition of serial electron micrographs for threedimensional reconstruction analysis (3D-EM) has significantly been improved in recent years. This technique has also become easier to use and become more popular among researchers than in the past.
FIB-SEM uses two beams: a FIB for milling the block surface, and a scanning electron beam to capture images of the block surface structure. For the FIB, gallium ions are used. The FIB can be extremely narrow in diameter (1-1,000 nm) and sputters a very thin layer from the tissue block surface. It can mill even hard tissues, such as tooth or bone (Tanoue et al., 2018). These features are valuable and unique to the FIB-SEM; the other microscopies cannot achieve such a thin layer cutting nor hard tissue sectioning (Briggman and Bock, 2012;Kubota, 2015). The second beam used in the FIB-SEM is a standard SEM column, and is used for capturing images of the freshly milled block surface after each milling step. There is a limitation in the size of the field of view that can be imaged. The field size is determined by the maximum effective sputtering area for the FIB, which is about 100 µm × 100 µm. Thus, in comparison to the other microscopies, FIB-SEM provides a smaller imaging field of view. A research team working on whole fly brain connectome research in Janelia Research Campus has overcome this limitation with  innovative ideas . The researchers split a fly brain into 16 µm-thick tissue slabs with hot knife and reassembled the EM volume data set after the image acquisition (Takemura et al., 2017a,b;Xu et al., 2017). However, there are additional issues with the FIB-SEM. First, the projection surface for the FIB must be very smooth without unevenness to capture a high-quality image; otherwise, the acquired image can contain the noise of curtaining effect from FIB milling traces (Liu et al., 2018). Second, it is frequently found that the orthogonal view (yz plane) of the aligned stacking image volume captured with FIB-SEM has a shape of a lozenge, not a rectangle (Figure 4). This is caused by an angle between FIB and SEM beams, typically 52 • -54 • , which, in turn, sets the SEM beam projection angle relative to the tissue block surface milled by the FIB at 52 • -54 • (Figures 4A-C). As the serial electron micrographs are actually projected images, these images are distorted with y axis for a factor of 0.786 in the 52 • angle from the actual block surface (Figures 4D-F,H,K) taken with FIB-SEM Helios G4 (voxel size: x, 2.29 nm; y, 2.91 nm; z, 2.7 nm; Thermo Fisher Scientific, Waltham, MT, USA). Therefore, captured images need to be scaled in y axis with an appropriate factor (Figures 4H,I,K,L) to restore them to the original size and proportions on the block surface. The scaled serial electron micrographs are aligned using image analysis application (for example, Fiji/Plugins/Registration/Register Virtual Stack Slices). Consequently, the original shape of volume with orthogonally lozenge shape in yz plane should be recovered (Figures 4G,J,M). Note that an elongated object parallel to the block surface gradually deviates from the imaging field of view with serial imaging (Figures 4D-F). This happens only in the yz plane, but not xz plane (Figures 4J,M,N). A FIB-SEM with 90 • angle for the two beams captures images without these drawbacks (e.g., NX-9000, Hitachi High-Technologies Corp., Tokyo, Japan). Occasionally, some jitters are found in serial section images before alignment due to the instability of the SEM beam for charging, or deformation/expansion of the block surface by the heat during imaging/sputtering, and this makes the orthogonal xz view slightly irregular ( Figure 4N). Despite these issues, the FIB-SEM has unique features that are not available with other methods as discussed in the above, and can be used to capture serial electron micrographs for various research purposes.

AUTOMATED SERIAL BLOCK FACE IMAGE ACQUISITION SCANNING ELECTRON MICROSCOPY: SBEM
SBEM is a well-designed automated serial block face electron micrograph acquisition tool and has several features that make it convenient for neuroscience research. As in FIB-SEM, SBEM uses a scanning electron beam to capture the image of the block surface structure in a chamber, but instead of the FIB, uses an ultramicrotome directly placed in the chamber. A diamond knife is used to cut the block surface, and the surface structure of the tissue block is captured with SEM automatically. Thin sections (∼20 nm) can be cut, and imaging throughput is fast (∼2 MHz or 0.5 µs/pixel). The imaging area can be larger than with FIB- SEM, because the entire block surface is cut with the diamond knife. SBEM with a custom motorized stage can capture a larger volume data set (∼450 µm; Schmidt et al., 2017) than is possible with FIB-SEM. It images the block surface located right under the SEM column, so captured serial images are expected not to be affected by movement. In reality, due to the charging or heating issues, serial images may be found to show jittering, so minimal alignment of serial section images may be necessary.
Several inconvenient issues are encountered with this microscopy. First, section debris falling on the block surface after cutting can obscure ROI during automated imaging occasionally. To address this issue, a new application was developed recently to detect and remove the debris for stable imaging (Titze et al., 2018), which helps with continuous imaging at high quality. Second, electrons impact the block surface, which can cause a crumbling at subsequent sectioning particularly when the dwell time is increased to obtain a better image, even for the tissue block treated with a heavy metal staining protocol for biological tissue samples developed for the SBEM (Deerinck et al., 2010;Ngo et al., 2016;. An electric charge is easily accumulated at the block surface, because as the diamond knife cuts the block surface, it also removes the silver paste covering the entire block surface that is used for electric to ground. To overcome the drawback, the electron dose (equation below;  should be kept between 20-40 e-/nm 2 for satisfactory serial section imaging with smooth ultrathin sectioning (Kubota, 2015). For the imaging condition with 7 nm/pixel, 3 µs/pixel dwell time, and 100 pA beam current, the estimated dose is 38.2 e-/nm 2 , which is within this range, ensuring acquisition of good quality images. Embedding the tissue using epoxy resin mixed with carbon black may reduce the charging issue especially for tissue cells loosely packed in epoxy resin, such as blood cells or yeast (Nguyen et al., 2016). Additional improvement, for example, a detector with better sensitivity or local gas injection to the block surface (Deerinck et al., 2018), can also help to reduce the charging problem. electron dose(e − /nm 2 ) = beam current (A) × pixel dwell time (s) 1.60217657 × 10 −19 × pixel size (nm) 2

AUTOMATED IMAGE ACQUISITION ELECTRON MICROSCOPY WITH SERIAL ULTRATHIN SECTIONS: TEMCA/TEM
Several microscopies using automated image acquisition of serial ultrathin sections are available. Serial thin sections at ∼25 nm thickness can be obtained stably with well polymerized hard epoxy resin embedded tissue. Remarkable features of ultrathin sections in general are that they retain for many years and can be observed many times. As illustrated in Figure 1, these features are conveniently taken advantage of in neuroscience research.
TEMCA is a custom TEM with four 4 MB CCD cameras to obtain images of 4 k × 4 k image size at the bottom of a large scintillator (Bock et al., 2011;Lee et al., 2016). The imaging area can be significantly increased using a mosaic image of many tiles (∼450 µm or larger; Lee et al., 2016). This approach is expensive, however, as it requires customized technologies and machines that are yet to be commercially available. TEMCA has been implemented at Harvard, where the TEMCA was originally developed, HHMI Janelia Research Campus, and Allen institute. Recently, a derivative of TEMCA was introduced. Serial ultrathin sections are collected on a grid array tape with ATUM. Electron micrographs of serial sections on a rolled grid tape are obtained with the TEM, which is equipped with a reel to reel motorized system equipped in its specimen chamber (GridStage ReelTM, Voxa, Seattle, WA, USA).
Automated image acquisition of serial ultrathin sections collected on grids with TEM was introduced (Bloss et al., 2018), and the features including the collection of serial sections on a silicon wafer and manual observation with SEM are also available, allowing the acquisition of large volume EM data set using (Boeckeler Instruments, Inc., Tucson, AZ, USA; JEOL Ltd., Akishima, Japan) two commonly available EM tools, namely, ultramicrotome and EM. This likely promotes the use of 3D-EM methods.

AUTOMATED IMAGE ACQUISITION ELECTRON MICROSCOPY WITH SERIAL ULTRATHIN SECTIONS: MULTISEM
MultiSEM (Carl Zeiss Microscopy GmbH, Oberkochen, Germany) has 61 channels of SEM, and imaging is very fast (10 MHz or 100 ns/pixel ∼) with its in-lens detector (Eberle et al., 2015;. It can capture brain section prepared by ATUM with a hexagonal field of view of 108 µm × 94 µm at 4 nm/pixel with 61 rectangle tiles of 3,128 × 2,724 pixels size in 1.3 s. The imaging speed is 10 2 -10 3 times faster than with a regular single beam SEM. For instance, a large volume EM data set of 1 mm cubic brain tissue in this imaging condition with 50 nm thick serial sections can be captured in about 10 h using the MultiSEM, but it takes about a few months to a year using a single beam SEM. There are, however, a few flaws with the MultiSEM. Image resolution is 4 nm/pixel and is about five times larger than single beam SEM (0.7-1.0 nm/pixel). It captures images with the SE detector only, in contrast to the single beam SEM, which uses SE, backscattered electron (BSE) and Everhart Thoneley (ET) detectors. SE detectors may add more noise signals than BSEs do. Consequently, the captured image may show lower contrast. Imaging with the SE detector shows a substantial contaminated area likely as a result of a thin layer of adventitious carbon build up, which results in contamination inside the chamber . We assume that those features are part of the reason why the image contrast of electron micrograph obtained with the MultiSEM is somewhat inferior to that of the images captured with a single beam SEM (Figure 3; . Imaging with MultiSEM requires that the conductive properties of the tape greatly exceed those of a single beam SEM setup (∼270 pA: using In-lens SE, 20 µm aperture size, 3 nm/pixel, ∼6 keV with Sigma, Carl Zeiss Microscopy, Germany) due to the higher total beam current (61 beams version, 570 pA per beam; 35 nA total). In addition, the stage bias of 28.5 keV is also much higher than in a single beam microscope. It requires a high-quality conductive tape (<100 MΩ/square), such as the CNT tape. Although the MultiSEM requires these ingenious solutions for proper use, it can provide adequate-quality images of a large volume EM data set for neural microcircuit analysis, with extremely high throughput.

AUTOMATED IMAGE ACQUISITION ELECTRON MICROSCOPY WITH SERIAL ULTRATHIN SECTIONS: SECTION COMPRESSION PROBLEM
It is known that ultrathin sections show a compression artifact from sectioning with ultramicrotome, with compression rate typically in the range of 15%-30% in the cutting direction (Jésior, 1986). This means that ultrathin sections shrink to 70%-85% of the original length depending on cutting conditions. The compression can be reduced by using thicker sections (>30 nm thick), a low angle diamond knife (<30 • ), or a well polymerized hard epoxy resin; however, changing the cutting speed appears to have no effect (Jésior, 1986). The oscillating diamond knife (DiATOME) can reduce the compression (Studer and Gnäegi, 2000). When grids with thin support membranes are used to collect sections, ultrathin sections may be distorted further during imaging because of the expansion of support membranes by heat from the electron beam, which is usually set at very high energy levels in TEM. Furthermore, the heat can break or destroy the thin supporting membrane, leading to the loss of sections. Fortunately, if serial sections are collected on a rigid silicon wafer or a plastic tape, they are likely to be stable even during imaging with the SEM beam probably without further distortion other than the compression. Therefore, captured images could be scaled to resemble the original shape with adequate compression factor, although compression artifact would not be a problem for investigating synaptic connections in the microcircuit analysis. These features are summarized in Table 1.

COMPUTER APPLICATIONS FOR THREE-DIMENSIONAL RECONSTRUCTION INVESTIGATIONS
The automated applications for registration and segmentation of neuronal elements with high accuracy are useful for processing large-volume data sets. Clay Reid's group at the Allen Institute, USA introduced their latest research project at YouTube 2 . In this project, the entire neural elements within 100 µm cube of the mouse primary visual cortex were three-dimensionally reconstructed thoroughly for connectomic investigation. In vivo calcium imaging analysis of an orientation selectivity in the mouse visual cortex was done by Andreas Tolias at the Baylor College of Medicine, Houston, TX, USA, and the cubic EM volume data set of the cortex was obtained using the TEMCA by Clay Reid at the Allen Institute. Sebastian Seung and his colleagues at Princeton University, Princeton, NJ, USA achieved automated registration and dense segmentation of the large 2 https://www.youtube.com/watch?v=LO8xCLBv6j0&feature=youtu.be EM data sets using newly-developed computer applications (Lee et al., 2017). This dense segmentation application is based on a deep learning program that requires manually segmented sample EM data sets as ground truth. After tuning for a specific EM data set to be analyzed, they found that automated segmentations were accomplished satisfactorily with only a few mistakes, which were fixed with manual proof reading to establish the completeness of the neural elements reconstructions. The applications are partially made available to the public at Github 3 . This result was achieved for the Machine Intelligence from Cortical Networks program (MICrONS) as a part of the BRAIN Initiative, USA.
The FlyEM team at Janelia Research Campus, USA prepares a Drosophila's whole brain EM data set with 8 nm isometric voxels using FIB-SEM (Takemura et al., 2017a). Computer applications to reconstruct the neural elements three-dimensionally was developed by a research team led by Viren Jain at Google, USA. The accuracy is about the same as those achieved by the Princeton University research team described above, but their approach, ''Flood-Filling Networks'', is unique (Januszewski et al., 2018). In addition, the FlyEM team developed a webGL-based viewer, Neuroglancer, for volumetric data analysis to improve viewing performance of large EM images with raster pyramids. These deep learning applications and the Neuroglancer are open-sourced at Github for public use 4,5 . These pieces of software will undoubtedly advance brain structure analysis in neuroscience.

OUTCOMES AND CONCLUSIONS
Frontier studies with large-volume EM data have already uncovered some previously unknown neural wirings in the brain. Moritz Helmstaedter and his colleagues at Max Plank Institute, Germany described connections among neurons in the rat medial entorhinal cortex using two large volume EM data sets obtained with the SBEM (424 µm × 429 µm × 274 µm size and 183 µm × 137 µm × 158 µm size with the voxel size of 11.24 µm × 11.24 µm × 30 nm; Schmidt et al., 2017). They identified 594 synapses made by 22 excitatory neurons (ExN) following reconstruction that included axons and dendrites. About half of their targets were ExN and the other half were inhibitory non-pyramidal cells (InN). With careful observation of the three-dimensionally reconstructed synaptic contacts among the cells, they concluded that feed forward inhibitory microcircuits are established in the medial entorhinal cortex. Specifically, they showed that pre-synaptic ExNs innervated post-synaptic InNs first along the path of their axons, while innervating post-synaptic ExNs with more distal parts of their axons. Axon fibers of the InNs were frequently myelinated and had larger diameters than those of ExNs, indicating that the conduction velocity of InN axons is faster than that of the axons of presynaptic ExNs. Consequently, it was claimed that the feedforward inhibitory signal could arrive the post-synaptic ExN earlier than the feedforward excitatory signal by simulation.
Nelson Spruston and his colleagues (Bloss et al., 2018) at Janelia Research Campus, Ashburn, VA, USA analyzed the frequency of clustered synapses onto CA1 pyramidal cell dendrites using a large volume EM data set of electron micrographs taken at 3.8 nm × 3.8 nm pixel resolution from 50 nm thick serial thin-sections (x: 200 µm, y: 350 µm, z: 17 µm) containing the stratum radiatum and stratum lacunosum moleculare of the CA1 hippocampus. Ultrathin 50 nm serial sections were collected onto one-hole grids. Image tiles were taken with the TEM and assembled, montaged and aligned using custom alignment software and transformation algorithms in TrakEM2. Dendritic segments of pyramidal cells (n = 20), aspiny dendritic segments of putative interneurons (n = 5) and excitatory axons (n = 43) with their postsynaptic partners were reconstructed manually and analyzed using ''Reconstruct'' (Fiala, 2005). They found that single presynaptic axons form multiple, spatially clustered inputs onto the distal dendrites in the stratum lacunosum moleculare, but not proximal dendrites in the stratum radiatum, of CA1 pyramidal neurons. These findings enhanced our understanding of the cortical microcircuit structure.
Recent advances in the methodology in the EM and 3-dimensional serial reconstruction of large data sets have made it possible to achieve comprehensive analyses of fine brain structures at individual neuron levels. These new opportunities afford powerful research approaches in neuroscience that were not possible previously. This is an important breakthrough in neuroscience and particularly in the study of brain microcircuitry.

ETHICS STATEMENT
This study was carried out in accordance with the recommendations of ''the Guidelines for the Use of Animals'' of IBRO and of Animal Care and Use committee of the National Institute for Physiological Sciences. The protocol was approved by the ''Animal Care and Use committee.'' Every effort was made to minimize animal suffering.

AUTHOR CONTRIBUTIONS
YKu conceived the study, designed the experiments, analyzed and interpreted the data shown in the figures, generated the figures and drafted, edited and finalized the manuscript. JS performed the simulation in Figure 2 and edited the manuscript. YKa interpreted the data shown in the figures and edited the manuscript.


extfieldsofstudy: Chemistry Medicine

text:
Expression and functions of glutamate and γ-aminobutyric acid transporters in ischemic models

Glutamate and γ-aminobutyric acid (GABA) transporters serve central roles in normal neuronal activity and are associated with numerous pathological brain conditions, including ischemia and epilepsy. However, the interplay between these transporters in ischemia remains unclear. In the present study, the expression levels of the excitatory amino acid carrier 1 (EAAC1) and GABA transporter 1 (GAT1) were analyzed in vivo and in vitro within ischemic models by immunofluorescence, western blot and RT-qPCR. Cell survival rates were analyzed following altered expression of these transporters within neuronal cells by flow cytometry. Expression levels of EAAC1 were reduced within the cerebrum of focal cerebral ischemic middle cerebral artery occlusion rat models as well as in primary neurons cultured under hypoxia. However, GAT1 expression levels were slightly elevated under ischemic conditions. The altered expression levels of EAAC1 and GAT1 were combined within neuron cells and the effects were investigated. Apoptotic analysis revealed that EAAC1 suppression and overexpression of GAT1 increased neuronal cell apoptosis under hypoxic conditions; however, EAAC1 overexpression combined with GAT1 knockdown reduced neuronal cell apoptosis under hypoxic conditions. The present study detected the expression levels of the glutamate and GABA transporters under hypoxia, in association with ischemia. The results indicated that, increased expression of EAAC1 combined with GAT1 suppression may provide protective effects in the treatment of epilepsy and ischemia.

Introduction
Cerebral hypoxic ischemia is a leading cause of numerous neurological diseases, including cerebral epilepsy, palsy and cognitive disabilities associated with high mortality and morbidity (1)(2)(3). Matsumoto et al (4) reported that ischemia may cause neuronal cell apoptosis in the central nervous system due to an excess of L-glutamate. However, ischemic-associated release of L-glutamate may be inhibited by the activation of γ-aminobutyric acid (GABA) receptors (4,5). GABA-and glutamate-associated transporters serve roles in the maintenance of extracellular GABA and glutamate levels (4). However, in abundance, these transporters have been associated with numerous pathological brain conditions, in particular ischemia and epilepsy.
Glutamate transporters serve crucial functions in the prevention of neuronal cell death by reducing glutamate-associated toxicity. Five associated glutamate transporters have been reported: Glutamate-aspartate transporter/excitatory amino acid transporter (EAAT)1, glial glutamate transporter (GLT)-1/EAAT2, EAA carrier (EAAC)1/EAAT3, EAAT4 and EAAT5 (6,7). The functional relevance of GLT-1 was clearly demonstrated in a study using GLT1 knockout mice, which developed severe epilepsy (8). However, the roles of EAAC1 in neuronal death have not been resolved compared with glial glutamate transporters, including GLT-1. In addition to maintaining extracellular glutamate, a previous study investigating EAAC1-deficient mice revealed that EAAC1 can function as a cysteine transporter and maintain neuronal glutathione homeostasis (9). Additionally, EAAC1 has been reported to protect injured motor neurons via interactions with holocytochrome c synthetase (10). EAAC1 may therefore perform additional functions in addition to glutamate homeostasis.
Sodium-and chloride-dependent GABA transporter 1 (GAT1) is primarily responsible for the removal of GABA from the synaptic cleft and termination of GABA-mediated neurotransmission (11). Chronic neurological abnormalities that develop following hypoxia at an early age may be associated with alterations of GAT functions (12)(13)(14)(15). A previous study reported that the protein expression levels of GAT1 were reduced within the brains of thrombotic infarct rat models (16). The interplay between these transporters and ischemia require further investigation. The present study aimed to investigate the expression and associated functions of GAT1 and EAAC1 under hypoxic conditions in vivo and in vitro. However, the interplay between these transporters in ischemia remains unclear. The present study aimed to investigate the expression and associated functions of GAT1 and EAAC1 under hypoxia in vivo and in vitro.

Materials and methods
Middle cerebral artery occlusion (MCAO) animal models. 14 male Sprague-Dawley rats (250-300 g; Experimental Animal Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China) were housed in a climate-controlled room (25˚C, 50% humidity), 5 rats per cage; food and water was provided ad libitum under a 12 h-light/dark cycle. The animal study protocol was approved by the ethics committee of Shanghai Pudong Hospital (Shanghai, China) and was conducted according to guidelines of the Animal Experimentation group of Shanghai Jiao Tong University School of Medicine.
Rats were randomly allocated into the following groups (n=6 in sham group, n=8 in MACO group): A sham-operated control group, which underwent the operation with no occlusion; and a 24 h post-MCAO/reperfusion group. Briefly, rats were anesthetized with an intraperitoneal (i.p.) injection of 50 mg/kg pentobarbital and placed in a stereotaxic instrument (Advanced Scientifics Inc.; Thermo Fisher Scientific, Inc., Waltham, MA, USA). A 28-gauge stainless steel injection cannula was inserted into the right lateral ventricle as previously described (17). MCAO rat models were generated as previously described (18). Briefly, a 3-0 monofilament nylon suture (Beijing Shandong Technology Co., Ltd., Beijing, China) with a heat-treated rounded tip was introduced into the right internal carotid artery via the external carotid artery until slight resistance was achieved. The suture was maintained in place for 90 min and was then withdrawn to facilitate reperfusion. 24 h following the onset of reperfusion, the rats were deeply anesthetized using sodium pentobarbital (100 mg/kg, i.p.). For mRNA and protein expression analysis, rats were transcardially perfused with 4˚C normal saline; regions corresponding to the ischemic core and penumbra were dissected on ice using previously described methods (18). For immunostaining, the rats were transcardially perfused with 4˚C normal saline and fixed with 4% paraformaldehyde (PFA; pH=7.4). Brains were extracted and post-fixed in 4% PFA, the tissues were subsequently cryoprotected in 20% sucrose, followed by 30% sucrose at 4˚C for 48 h. Serial coronal sections (25 µm) were collected between -1.80 and -4.80 mm bregma levels. Every fifth section from a total of 24 sections was selected for staining.
Cells and cell culture. Primary neurons derived from rat were cultured in Dulbecco's modified Eagle's medium (Thermo Fisher Scientific) supplemented with 10% fetal bovine serum (PAA Laboratories; GE Healthcare, Chicago, IL, USA). Briefly, brain tissue was removed from freshly euthanized rats into a cold, buffered salt solution. Using a dissecting microscope, cerebral cortex can be carefully isolated for further processing. The dissected tissue was first minced using a scalpel or scissors. The resulting tissue pieces were then transferred to a new container. A proteolytic enzyme solution including trypsin and papain were then added to digest the extracellular matrix proteins that bind cells together. Following a short incubation of 15 min in a warm incubator of 37˚C, tissue pieces were gently washed with buffer to remove the enzymes. The softened tissue pieces were dissociated by trituration, which involved passing the tissue through a pipet, multiple times so that cells become a single cell suspension. At this point, cells were counted and checked for viability by Trypan blue. Cells were cultured at 37˚C in a humidified atmosphere containing 5% CO 2 . To simulate a hypoxic environment, dissociated cells were seeded in a 10-cm dish with or without 250 µM CoCl 2 treatment for 24 or 48 h at 37˚C prior to analysis.
Lentiviral-mediated short hairpin RNA (shRNA) gene knockdown or overexpression. Primary neurons exhibiting stable knockdown of EAAC1 or GAT1 were generated via transduction with a lentiviral-mediated expression-specific target shRNA (10 9 TU/ml; HanYin Biotech, Shanghai, China). Lentivirus containing an empty vector was used as a negative control (NC, HanYin Biotech). The targeted knockdown sequence for EAAC1 was 5'-caa caa tgt ctg aga aca a-3' and for GAT1 was 5'-cca aat gac aga tgg gct a-3'. Cells were seeded in six-cm dishes at a density of 5x10 5 . Cells were then infected with the same titer virus with 8 µg/ml Polybrene ® (HanYin Biotech) on the following day. Overexpression of EAAC1 or GAT1 was generated following infection of cells with EAAC1-or GAT1-expressing lentiviruses (10 8 TU/ml, HanYin Biotech) with 8 µg/ml Polybrene ® (HanYin Biotech) on the following day. After 48 h, cells were harvested, and the knockdown or overexpression efficiency was determined using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and western blotting.
RT-qPCR. Cellular RNA was isolated using TRIzol (Invitrogen; Thermo Fisher Scientific, Inc.) according to the manufacturer's protocol. Subsequently, DNA was removed from the samples via DNase treatment (DNA-free kit; Ambion; Thermo Fisher Scientific, Inc.) and cDNA was synthesized from the purified RNA using a Moloney murine leukemia virus RT kit (Promega Corporation, Madison, WI, USA). GAPDH primer sets were used as a normalization control. Primer sequences were as follows: GAT1 forward, 5'-GCA ATC GCC GTG AAC TCT TC-3' and reverse, 5'-AGG AAA TGG AGA CAC ACT CAA AGA-3'; EAAC1 forward, 5'-CTC CAC CAC CGT CAT TGC T-3' and reverse, 5'-TGG CAG GCT TCA CTT CTT CAC-3'; GAPDH forward, 5'-GTA TGT CGT GGA GTC TAC TG-3' and reverse, 5'-CTT GAG GGA GTT GTC ATA TTT C-3'. RT-qPCR cycling conditions were: Initial denaturation for 3 min at 95˚C followed by 45 cycles of 95˚C (10 sec) and 58˚C (45 sec), and data were acquired at the end of the annealing/extension phase. RT-qPCR was performed in triplicate using the SYBR-Green PCR Master Mix (Applied Biosystems) on a 7900HT Fast Real-Time PCR machine according to the manufacturer's protocol (Applied Biosystems; Thermo Fisher Scientific, Inc.). The relative quantification method (2 -ΔΔCq ) (19) was used to analyze quantitative RT-PCR data using GAPDH as normalizer. NC were served as a reference.
Western blot analysis. Radioimmunoprecipitation assay buffer, a protease inhibitor cocktail and a phosphorylation inhibitor cocktail (Beyotime Institute of Biotechnology) were used to extract total protein from cells. Protein concentration was determined by BCA method. A total of 30 µg protein was separated by 10-15% SDS-PAGE and was transferred onto a nitrocellulose membrane (EMD Millipore, Billerica, MA, USA). The membrane was blocked with 5% non-fat milk 30 min at room temperature. The membrane was further incubated with primary antibodies [EAAC1, (1:1,000; cat. no. orb149931; Biobyt, Ltd.) GAT1 (1:1,000) and Actin (1:3,000; both Abcam)] overnight at 4˚C and subsequently incubated with HRP conjugated anti-mouse or rabbit immunoglobulin G (1:10,000) for 1 h at room temperature. The signal was observed and developed with a Kodak film (Kodak, Rochester, NY, USA) via enhanced chemiluminescence plus western blotting detection reagent (Amersham; GE Healthcare). β-actin was used as a control.

Apoptosis assay. An Annexin V-phycoerythrin (PE) Apoptosis
Detection kit (BD Biosciences, Franklin Lakes, NJ, USA) was employed to assess apoptosis according to the manufacturer's protocol. Briefly, cells treated with or without CoCl2 (control, CK) were resuspended in 1X Binding Buffer at a concentration of 1x10 6 cells/ml, and 100 µl of this suspension was added to each of the following tubes: i) An empty tube, ii) a tube containing Annexin V-PE reagent (5 µl); iii) a tube containing 7-aminoactinomycin D (AAD) reagent (5 µl); and iv) a tube containing Annexin V-PE reagent (5 µl) and 7-AAD reagent (5 µl). The tubes were gently vortexed and were incubated for 15 min at room temperature in the dark. 1X Binding Buffer (400 µl) was then added to each tube and the cells were analyzed by flow cytometry (Beckman gallios, flowjo10.07).
Statistical analysis. Statistical analysis was performed using the Student's t-test for comparison between two groups and one-way analysis of variance followed by and a Tukey test for multiple comparisons. P≤0.05 was considered to indicate a statistically significant difference.

Results
Expression levels of EAAC1 and GAT1 within the penumbra in a rat model of MCAO/reperfusion. Expression levels of EAAC1 and GAT1 within the penumbra were analyzed via immunofluorescence. The results of the present study revealed that the protein expression levels of EAAC1 were markedly reduced at 24 h post-MCAO/reperfusion compared with the sham group (Fig. 1A). Protein expression levels of GAT1 were increased compared with the sham group (Fig. 1B). These results indicated that EAAC1 and GAT1 may serve different functions in hypoxia-induced ischemia.
Expression levels of EAAC1 and GAT1 are influenced by hypoxic stimuli within neuronal cells. The pathogenesis of ischemia-induced brain injury is mainly caused by neuronal death in oxygen-and energy-deficient environments. Therefore, the expression levels of EAAC1 and GAT1 under hypoxic conditions were analyzed. CoCl 2 is a commonly used agent to induce oxygen failure. Neuronal cells were treated with CoCl 2 for 24 or 48 h, and the expression levels of EAAC1 and GAT1 were detected through western blot analysis and RT-qPCR. The results revealed that the protein expression levels of EAAC1 were reduced in a time-dependent manner in response to CoCl 2 ( Fig. 2A). GAT1 protein expression levels were slightly increased following CoCl 2 treatment (Fig. 2B). The mRNA expression levels of EAAC1 and GAT1 were detected via RT-qPCR following CoCl 2 treatment for 24 and 48 h. Compared with the untreated cells, mRNA levels of EAAC1 were significantly reduced and those of GAT1 were increased in response to CoCl 2 treatment (Fig. 2C and D). The expression levels of EAAC1 and GAT1 within primary  neuronal cells were altered following exposure to hypoxia; therefore, EAAC1 and GAT1 may serve important roles in the hypoxia-induced ischemia.
EAAC1 suppression and GAT1 overexpression increases apoptosis under hypoxic conditions. Following CoCl 2 treatment, the mRNA and protein expression levels of EAAC1 and GAT1 were reduced and elevated, respectively. The effects of EAAC1 knockdown and increased GAT1 expression on neuronal cell apoptosis were subsequently investigated. EAAC1 expression was targeted within neuronal cells via a lentiviral shRNA gene knockdown system, which demonstrated a >60% decrease in EAAC1 expression (Fig. 3A). Lentivirus-mediated gene overexpression significantly increased GAT1 expression (Fig. 3B). The protein expression levels of EAAC1 and GAT1 were also confirmed via western blotting (Fig. 3C).
Subsequently, cells were treated with CoCl 2 and analyzed with a fluorescence-activated cell sorting (FACS) apoptosis assay. Analysis indicated that EAAC1 suppression with GAT1 overexpression elevated neuronal death under hypoxic conditions compared with the negative control group. As presented in Fig. 4, the percentage of apoptotic cells was significantly increased compared with control cells following CoCl 2 treatment.
Overexpression of EAAC1 with GAT1 knockdown reduces neuronal cell apoptosis. To further investigate the effects of EAAC1 and GAT1 expression on neuronal cell apoptosis, EAAC1 overexpression and GAT1 knockdown was applied. The mRNA expression levels of EAAC1 were markedly upregulated within neuronal cells (Fig. 5A), whereas >80% of GAT1 mRNA expression was reduced (Fig. 5B). The protein  expression levels of EAAC1 and GAT1 were also confirmed via western blotting (Fig. 5C).
The FACS apoptosis assay suggested that EAAC1 overexpression with GAT1 knockdown reduced neuronal cell apoptosis under hypoxic conditions. As presented in Fig. 6, the percentage of apoptotic cells was significantly reduced compared with control cells following CoCl 2 treatment compared with the negative control group. These results demonstrated the importance of EAAC1 with GAT1 within hypoxic ischemia-induced brain injury and suggested that upregulation of EAAC1 with GAT1 suppression may provide benefits for the therapy of ischemia-associated diseases.

Discussion
Hypoxic ischemia-induced brain injury is a major cause of morbidity and mortality in infants and children (3,(20)(21)(22); at present, effective treatments for these diseases are unavailable. Glutamate and GABA are important neurotransmitters in the human nervous system, however, whether glutamate/GABA transporters serve important functions in hypoxic ischemia remains unclear (23). In the present study, it was reported that EAAC1 expression was reduced within the cerebrum of focal cerebral ischemic MCAO rat models, as well as in primary neurons cultured under hypoxia. Conversely, the expression levels of GAT1 were slightly elevated under ischemic conditions. Additionally, analysis of apoptosis revealed that EAAC1 suppression with co-overexpression of GAT1 elevated neuronal cell apoptosis under hypoxia; however, EAAC1 overexpression with GAT1 knockdown reduced neuronal cell death. The present study indicated the expression of glutamate and GABA transporters may be associated with ischemia. Increasing the expression levels of EAAC1 and suppressing GAT1 expression may provide beneficial effects in the treatment of epilepsy or ischemia treatment.
Previous studies have demonstrated that the pathogenesis of ischemic injury may be due to cellular apoptosis in oxygen-and energy-deficient environments (24,25). Neuronal cell apoptosis increased following CoCl 2 treatment; however, apoptosis induced by CoCl 2 may be inhibited by increased expression levels of EAAC1 and suppressed GAT1.
In conclusion, the results of the present study demonstrated the importance of glutamate and GABA transporters in hypoxic-ischemic brain injury; therefore, targeting the functions of EAAC1 and GAT1 may provide advantages for the development of hypoxic ischemia therapies.