extfieldsofstudy: Medicine Biology

s2fieldsofstudy: Biology Medicine

text:
Maternal Exposure to Non-nutritive Sweeteners Impacts Progeny’s Metabolism and Microbiome

Non-nutritive sweeteners (NNS) are marketed as sugar alternatives providing sweet taste with few or no calories. Yet their consumption has been linked to metabolic dysfunction and changes in the gut microbiome. NNS exposure mostly originates from diet beverages and sweetener packages in adults or breastmilk in infants. Consequences of early life exposure remain largely unknown. We exposed pregnant and lactating mice to NNS (sucralose, acesulfame-K) at doses relevant for human consumption. While the pups’ exposure was low, metabolic changes were drastic, indicating extensive downregulation of hepatic detoxification mechanisms and changes in bacterial metabolites. Microbiome profiling confirmed a significant increase in firmicutes and a striking decrease of Akkermansia muciniphila. Similar microbiome alterations in humans have been linked to metabolic disease and obesity. While our findings need to be reproduced in humans, they suggest that NNS consumption during pregnancy and lactation may have adverse effects on infant metabolism.

INTRODUCTION
Non-nutritive sweeteners such as sucralose and acesulfame-K are highly prevalent in the diet of United States adults and children (Sylvetsky and Rother, 2016). This is in part due to growing awareness of sugar's adverse health effects. Yet, multiple clinical studies have reported similar detrimental health effects related to NNS as seen with sugar, even when NNS are used at doses below the acceptable daily intake (ADI) limit determined by the FDA (Swithers, 2013). Herein are some of the plausible mechanisms explaining this apparently paradoxical relationship. For example, ingestion of a NNS sweetened products elicits less reward response in the central nervous system than sugar sweetened foods or beverages (Tellez et al., 2016). NNS also alter incretin and insulin secretion (Jang et al., 2007;Mace et al., 2007;Margolskee et al., 2007;Brown and Rother, 2012), and may upregulate pro-inflammatory and adipogenesis promoting pathways (Simon et al., 2013;Bian et al., 2017a). NNS also impact glucose metabolism (Abou-Donia et al., 2008) and the gut microbiome (Abou-Donia et al., 2008;Cowan et al., 2013;Palmnäs et al., 2014;Suez et al., 2014;Bian et al., 2017b).
However, NNS are still widely used despite missing critical experimental data ensuring their safety. First, none of the existing literature investigated the effect of combined sweeteners exposure, when this is mostly the case in commercial products. Secondly, high-dose NNS diets are often administered in animal models, reducing the relevance of those studies for human health. Finally, least is known about the consequences of NNS use during pregnancy and lactation (American Dietetic Association, 2004).
Human exposure to NNS begins early through breastmilk, infant rehydration solutions and medications (Freedman et al., 2010;Sylvetsky et al., 2015). To date, a higher infant BMI at 1 year of age has been associated with maternal NNS consumption during pregnancy in a recent epidemiology study (Azad et al., 2016). Studies in animals suggest that acesulfame-K crosses the placenta, and in utero exposure results in increased sweet preference in adulthood Chen et al., 2013). In other animal studies, sucralose exposure during pregnancy showed no deleterious effects on fetal organogenesis (Kille et al., 2000) but increased the risk of hematopoietic neoplasia in male offspring (Soffritti et al., 2016).
In light of the reported NNS effects on the gut microbiome (Abou-Donia et al., 2008;Cowan et al., 2013;Palmnäs et al., 2014;Suez et al., 2014;Bian et al., 2017b) and metabolism (Brown and Rother, 2012;Cowan et al., 2013;Simon et al., 2013;Swithers, 2013;Palmnäs et al., 2014;Suez et al., 2014;Bian et al., 2017b), it is important to investigate the relationship between NNS consumption in pregnancy and lactation and the offspring's microbiome and metabolism. Indeed, transmission of the microbiome from mother to child is a key factor, which influences metabolic regulation from early on, and is related to an increased risk of obesity, asthma and celiac disease (Faith et al., 2013;Bäckhed et al., 2015). In this study, we exposed pregnant and lactating mice to a mixed solution of sucralose and acesulfame-K at physiological concentrations and observed the impact on pre-weaned offspring (d20). Despite the low exposure through breastmilk, pups showed major alterations of metabolites in plasma and feces. In addition to amino acid alterations, deregulation of hepatic detoxification occurred in pups exposed to NNS. The resulting inefficient liver clearance and increased oxidative stress may have deleterious consequences as pups are challenged nutritionally during weaning and beyond. In addition to major bacterial metabolite variation, an increase of firmicutes as well as loss of one major beneficial species, Akkermansia muciniphila, were confirmed by microbiome sequencing. For the first time, we have shown that pre-and post-natal exposure (∼40 days) to NNS impacts the offspring's metabolism and microbiome, predictive of relevant future metabolic dysregulation.

Mice
C57Bl6 mice (Jackson Laboratory) were ordered at 8 weeks of age and acclimated in the mouse facility for 2 weeks. Mice were maintained in a 12-h light/dark cycle with ad libitum water and regular NIH-07 chow diet (22.5% protein, 4.5% fat, 4.5% fiber). The animals were maintained and the experiment performed according to the animal protocols approved by the NIDDK Animal Care and Use Committee (NIH) (#K023-LCBB-16).
Mice were single-housed 1 week before the experiment. Pregnancy of C57Bl6 mice was assessed by visualization of the vaginal plug and defined as E0.5. Pregnant mice were fed a quarter pellet/day of Rodent BLT's TM (Bio-serv) onto which were pipetted either: (1) water (Ctrl); (2) 10 µL of water with 0.1 mg of sucralose and 0.25 mg of acesulfame-K [equivalent to upper limit of ADI for human consumption (ADI1x)]; (3) 20 µL of water with 0.2 mg of sucralose and 0.5 mg of acesulfame-K [twice the ADI (ADI2x)] ( Figure 1A). The ADI for sucralose and acesulfame-K are 5 and 15 mg/kg of bodyweight/day, respectively. Pellets were added into a plastic cup in the cage every day and supplemented the regular chow diet. Pellet ingestion was assessed visually every day.
One day prior to sacrifice, mice were fasted overnight (16 h). Glycaemia was measured at the mouse tail using a Contour apparatus (Bayer). Mice were sacrificed after isoflurane anesthesia (Baxter).

Mouse Sample Collection
Retro-orbital blood collection was performed under isoflurane anesthesia.
Following sacrifice, the entire digestive tract from stomach to rectum was dissected and flushed with 10 mL of phosphate buffer saline (PBS) buffer. The gut flush was then concentrated by collecting the retained fraction on 0.22 µm filter paper.
Milk collection was performed on gestational day 15. The litter was separated from the mother 2 h prior to milking. Under isoflurane anesthesia, mice were injected intraperitoneally with 2IU of oxytocin (VetOne). After a few minutes, milk was collected by squeezing each mammary gland (Willingham et al., 2014). All samples were flash-frozen and stored at −80 • C.

NNS Concentrations
Sucralose and acesulfame-K concentrations in plasma, urine, feces and breast milk were measured in triplicate using liquid chromatography-mass spectrometry (LC-MS). Analyses were performed with an Acquity I-Class UPLC (Waters Corp., Milford, MA, United States) and an Acquity UPLC BEH C-18 column (2.1 mm × 50 mm, 1.7 µm) coupled with a Q-Exactive MS (Thermo Scientific, Waltham, MA, United States) with a HESI-II electrospray source. Analyses were performed using isotopically labeled sucralose as the internal standard for sucralose measurements and isotopically labeled acesulfame-K for acesulfame-K measurements. The %CV for the samples throughout experiments was 4.5% for sucralose and 0.8% for acesulfame-K, respectively, and for samples between days was 5.8% for sucralose and 1.0% for acesulfame-K, respectively.

Immunohistochemistry
Liver were sectioned, paraffin-embedded and stained by Histoserv. Inc., (Germantown, MD). Control stain were performed using heart (Perl), liver with gall bladder (Hall) or FIGURE 1 | Pups born to NNS-exposed mothers have observable metabolic phenotypes. (A) Experimental design: Mothers were fed starting on day 0.5 post-coitus (E0.5) until sacrifice. Two different concentrations of sucralose and acesulfame-K (ADI1x and ADI2x) were used for the experiments. Pups were sacrificed on postnatal day 20 (d20), and mothers were sacrificed after. All mice were fasted, weighed and blood was drawn before sacrifice. (B) Fasting glucose of 20-day old pups was measured before sacrifice (n = 30) (ANOVA). (C) Pups' weights were monitored from d1 to d20 and significance was analyzed using ANOVA (n = 30). Significance values: * * * * p < 0.001, * p < 0.05. liver (PAS). Digestion of glycogen was performed in combination with PAS staining.

Metabolomics
A non-targeted metabolomics analysis was performed on feces and plasma samples by Metabolon R .

Sample Preparation
Samples were prepared using the automated MicroLab STAR R system from Hamilton Company. Several recovery standards were added prior to the first step in the extraction process for quality control purposes. To remove protein, to dissociate small molecules bound to protein or trapped in the precipitated protein matrix, and to recover chemically diverse metabolites, proteins were precipitated with methanol under vigorous shaking for 2 min (Glen Mills GenoGrinder 2000) followed by centrifugation. The resulting extract was divided into five fractions: two for analysis by two separate reverse phase (RP)/UPLC-MS/MS methods with positive ion mode electrospray ionization (ESI), one for analysis by RP/UPLC-MS/MS with negative ion mode ESI, one for analysis by HILIC/ ultra-performance liquid chromatography (UPLC)-MS/MS with negative ion mode ESI, and one sample was reserved for backup. Samples were placed briefly on a TurboVap R (Zymark) to remove the organic solvent. The sample extracts were stored overnight under nitrogen before preparation for analysis.

QA/QC
Several types of controls were analyzed in concert with the experimental samples: a pooled matrix sample generated by taking a small volume of each experimental sample (or alternatively, use of a pool of well-characterized human plasma) served as a technical replicate throughout the data set; extracted water samples served as process blanks; and a cocktail of QC standards that were carefully chosen not to interfere with the measurement of endogenous compounds were spiked into every analyzed sample, allowed instrument performance monitoring and aided chromatographic alignment. Instrument variability was determined by calculating the median relative standard deviation (RSD) for the standards that were added to each sample prior to injection into the mass spectrometers. Overall process variability was determined by calculating the median RSD for all endogenous metabolites (i.e., non-instrument standards) present in 100% of the pooled matrix samples. Experimental samples were randomized across the platform run with QC samples spaced evenly among the injections.
Ultrahigh Performance Liquid Chromatography-Tandem Mass Spectroscopy (UPLC-MS/MS) All methods utilized a Waters ACQUITY UPLC and a Thermo Scientific Q-Exactive high resolution/accurate mass spectrometer interfaced with a heated electrospray ionization (HESI-II) source and Orbitrap mass analyzer operated at 35,000 mass resolution. The sample extract was dried then reconstituted in solvents compatible to each of the four methods. Each reconstitution solvent contained a series of standards at fixed concentrations to ensure injection and chromatographic consistency. One aliquot was analyzed using acidic positive ion conditions, chromatographically optimized for more hydrophilic compounds. In this method, the extract was gradient eluted from a C18 column (Waters UPLC BEH C18-2.1 × 100 mm, 1.7 µm) using water and methanol, containing 0.05% perfluoropentanoic acid (PFPA) and 0.1% formic acid (FA). Another aliquot was also analyzed using acidic positive ion conditions, however, it was chromatographically optimized for more hydrophobic compounds. In this method, the extract was gradient eluted from the same afore mentioned C18 column using methanol, acetonitrile, water, 0.05% PFPA and 0.01% FA and was operated at an overall higher organic content. Another aliquot was analyzed using basic negative ion optimized conditions using a separate dedicated C18 column. The basic extracts were gradient eluted from the column using methanol and water, however, with 6.5 mM ammonium bicarbonate at pH 8. The fourth aliquot was analyzed via negative ionization following elution from a HILIC column (Waters UPLC BEH Amide 2.1 × 150 mm, 1.7 µm) using a gradient consisting of water and acetonitrile with 10 mM ammonium formate, pH 10.8. The MS analysis alternated between MS and data-dependent MS n scans using dynamic exclusion. The scan range varied slighted between methods but covered 70-1000 m/z. Raw data files are archived and extracted as described below.

Bioinformatics
The informatics system consisted of four major components, the Laboratory Information Management System (LIMS), the data extraction and peak-identification software, data processing tools for QC and compound identification, and a collection of information interpretation and visualization tools for use by data analysts. The hardware and software foundations for these informatics components were the LAN backbone, and a database server running Oracle 10.2.0.1 Enterprise Edition.

Data Extraction and Compound Identification
Raw data was extracted, peak-identified and QC processed using Metabolon's hardware and software. These systems are built on a web-service platform utilizing Microsoft's .NET technologies, which run on high-performance application servers and fiberchannel storage arrays in clusters to provide active failover and load-balancing. Compounds were identified by comparison to library entries of purified standards or recurrent unknown entities. Metabolon maintains a library based on authenticated standards that contains the retention time index (RI), mass to charge ratio (m/z), and chromatographic data (including MS/MS spectral data) on all molecules present in the library. Furthermore, biochemical identifications are based on three criteria: retention index within a narrow Resonance Ionization (RI) window of the proposed identification, accurate mass match to the library +/−10 ppm, and the MS/MS forward and reverse scores between the experimental data and authentic standards. The MS/MS scores are based on a comparison of the ions present in the experimental spectrum to the ions present in the library spectrum. While there may be similarities between these molecules based on one of these factors, the use of all three data points can be utilized to distinguish and differentiate biochemicals. More than 3300 commercially available purified standard compounds have been acquired and registered into LIMS for analysis on all platforms for determination of their analytical characteristics. Additional mass spectral entries have been created for structurally unnamed biochemicals, which have been identified by their recurrent nature (both chromatographic and mass spectral). These compounds have the potential to be identified by future acquisition of a matching purified standard or by classical structural analysis.

Curation
A variety of curation procedures were carried out to ensure that a high-quality data set was made available for statistical analysis and data interpretation. The QC and curation processes were designed to ensure accurate and consistent identification of true chemical entities, and to remove those representing system artifacts, mis-assignments, and background noise. Metabolon data analysts use proprietary visualization and interpretation software to confirm the consistency of peak identification among the various samples. Library matches for each compound were checked for each sample and corrected if necessary.

Metabolite Quantification and Data Normalization
Peaks were quantified using area-under-the-curve. For studies spanning multiple days, a data normalization step was performed to correct variation resulting from instrument inter-day tuning differences. Essentially, each compound was corrected in runday blocks by registering the medians to equal one (1.00) and normalizing each data point proportionately (termed the "block correction"). For studies that did not require more than one day of analysis, no normalization is necessary, other than for purposes of data visualization. In certain instances, biochemical data may have been normalized to an additional factor (e.g., cell counts, total protein as determined by Bradford assay, osmolality, etc.) to account for differences in metabolite levels due to differences in the amount of material present in each sample.

Liver Transcriptomics
RNeasy Mini Kit (Qiagen) was used to extract RNA from 100 mg of liver. Four microliter of qScript cDNA Supermix (Quanta bioscience) was added to 500 µg of RNA extract and run on a thermocycler to provide cDNA using the following program: 25 • C/5 min; 42 • C/30 min; 85 • C/5 min. cDNA quantity and quality were then assessed using nanodrop spectrophotometer. cDNA samples were analyzed with RT 2 Profiler PCR Array-Mouse Drug Metabolism: Phase I Enzymes or Mouse Drug Metabolism: Phase II Enzymes (Qiagen) according to the manufacturer protocol. Samples were processed on 7900HT Fast Real-Time PCR system (Applied Biosystems).

Microbiome
Feces DNA samples were obtained from gut flushes (see sample collection) using the Fast DNA Spin Kit feces (MPBio). DNA quantity and quality were then assessed using a Nanodrop spectrophotometer.
Library preparation for sequencing of the V3-V4 region of 16S ribosomal DNA was performed using two PCRs. First, 16S DNA was amplified using 1 µg of feces DNA, 2× MyTaq Red Mix (Bioline) and the following primers: 16S Forward: TCGTCGGCAGCGTCAGATGTGTATAAGAGAC AGCCTACGGG NGGCGGCWGCAG; 16S Reverse: GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACT ACH VGGGTATCTAATCC. Amplification was performed on a thermocycler using the following program: 95 • C/3 min; 95 • C/30 s; 55 • C/30 s; 72 • C/30 s (repeat three last steps 35×); 72 • C/5 min; 4 • C/∞. To assess PCR quality, samples were run on 2% agarose E-gel (Invitrogen). Then, 2 µL of PCR product was used as a matrix for the second "adapters" PCR. Each 16S amplicon was then amplified using a unique couple of barcode-containing primers for dual-indexing of samples during the sequencing process (Fadrosh et al., 2014). Addition of the adapters on 16S amplicons was checked on 2% agarose gel. Finally, amplicon bands were extracted from agarose gels using QIAquick Gel Extraction Kit (Qiagen). This step cleaned up the final PCR product and removed eventual high molecular weight primer dimers, thus increasing the sequencing yield. A mixed sample of about 30 samples (1:1 ratio) was used for sequencing.
Sequencing output was first de-multiplexed and sequences were then analyzed with macQIIME workflow in "open reference OTU picking" protocol. Alpha-and Beta-diversity (Principal Coordinate Analysis-PCoA) were performed on R Studio using the phyloseq package.

Biostatistics
Spearman correlation, t-test and ANOVA analysis, Principal Component Analysis and Volcano plots were performed and plotted using R. The scripts for the analysis were posted in GITHUB 1 .

Akkermansia muciniphila
Akkermansia muciniphila was purchased from ATCC (BAA-835) and maintained under anaerobic condition at 37 • C either in Remel PRAS Brain Heart Infusion Broth (Thermo Scientific) or on Trypticase Soy Agar plates with Sheep Blood (BD BBL). A. muciniphila growth experiment was conducted in 96-well plate liquid culture by measuring the absorbance at 600 nm on the POLARstar Omega spectrophotometer (BMG Labtech). Media was supplemented with 100 µg/mL of ampicillin, 100 ng/mL of acesulfame-K and 35 ng/mL of sucralose ("low NNS") or 100 µg/mL of acesulfame-K and 35 µg/mL of sucralose ("high NNS").

Public Repository
Microbiome and metabolomics data have been published on Open Science Framework (OSF) 2 .
All scripts for analysis and/or plotting in this article have been published on GitHub 1 .

Mothers Transmitted NNS Through Breast Milk Leading to Lower Fasting Glucose and Weight in Pups
In brief, C57Bl6 mice (n = 31) were fed either water (control), or a combination of sucralose and acesulfame-K at the ADI (Sucralose ADI: 5 mg/kg/day; Acesulfame-K ADI: 15 mg/kg/day) or twice the ADI (ADI2x) during pregnancy and lactation (Figure 1A). NNS concentrations were measured in mothers' samples (blood, feces, breastmilk) after fasting and sacrifice post-weaning (Supplementary Figures S1A,B and Supplementary Table S1). While no NNS were observed in the control group, NNS were found in mothers' blood and feces in both NNS groups. As expected, based on previous pharmacokinetic studies, sucralose was mainly found in mother's feces whereas acesulfame-K was found in equal amounts in feces and blood. Both sweeteners were found in breastmilk (d15) at considerably lower concentrations than in blood and/or feces, and concentrations were highly variable between individual animals. A total of 226 20-day old pups distributed across the 3 groups were analyzed in the present study. Pups' blood and feces samples were collected at d20 after fasting and sacrifice (Supplementary Figures S1C,D and Supplementary Table S1). Overall, both NNS were either unmeasurable or present at low concentrations in the pups' blood and feces compared to their mother's. Sucralose was found mostly in the feces and was roughly correlated with the amount of sucralose in mothers' breast milk. Acesulfame-K concentrations were below the detection limit in pups' blood and feces, but measurable in the pups' urine when analyzed in newborns and 14 day-old pups (Supplementary Figure S1E and Supplementary Table S1). These measurements confirmed that both NNS were transmitted prenatally. Litter size and sex distribution were comparable in NNS vs. Ctrl pups (Supplementary Table S2). Measurement of the pups' fasting glucose at d20 showed a decrease in ADI2x pups (p = 0.02) compared to water, while a non-significant difference was observed between the ADI1x and Ctrl groups (p = 0.16) ( Figure 1B). The weight of the ADI2x pups was also reduced compared to Ctrl animals with weight curves gradually separating in the first week of life ( Figure 1C).

Metabolomics Analysis Revealed Alterations in Amino Acid Metabolism, Detoxification Pathways and Microbiome-Linked Metabolites in NNS Pups
To further define the consequences of the NNS exposure, we analyzed both feces and plasma metabolites in the pups using a non-targeted metabolomics approach. The analysis highlighted 594 and 708 metabolites in plasma and feces, respectively, across 18 samples, (6 in each group). In the NNS pups' plasma, more than 100 metabolites were deregulated compared to the Ctrl pups and almost 200 were deregulated in feces at p <= 0.05 threshold (Supplementary Figure S2). Volcano plots representing changes of both ADI1x and ADI2x vs. control group revealed extensive metabolic deregulation in both NNS groups (Figures 2A,B and Supplementary Tables S3, S4). Compared to Ctrl, NNS feces samples showed the most deregulated metabolites (at least 5 up and 35 down) compared to plasma (at least 3 up and 9 down) for both ADI1x and ADI2x pups. All three groups of pups separated significantly in a principal component analysis (PCA) and by ADONIS test (feces r 2 = 0.30 and p < 0.001; plasma r 2 = 0.28 and p < 0.001), highlighting distinct metabolomes (Figures 2C,D). Of note, a pool of metabolites was uniquely deregulated in ADI2x compared to ADI1X (plasma: 59 ups and 28 downs; feces: 107 up and 58 down), suggesting dosedependent metabolic deregulation.
Amino acid metabolism was the most deregulated class of metabolites in NNS pups (Figures 3A, 2A,B and Supplementary Tables S3, S4). Along with primary amino acid metabolites, numerous acetylated, sulfated or methylated amino acids as well as products of amino acid metabolism (picolinate, indole-3-carboxylic acid) were downregulated in NNS pups; N-acetyl cadaverine and tyramine, products of amino acid breakdown, were highly upregulated. Many glycine-containing dipeptides were also significantly decreased in NNS pups. Similarly, numerous products of glycine metabolism were downregulated such as bile acids, heme breakdown products, hippurate and propionylglycine.
Both carbohydrate and lipid metabolism were found to be altered in the NNS pups (Figures 3A, 2A,B and Supplementary  Tables S3, S4). The presence of sucralose as well as the decreased plasma glucose levels in NNS fed pups were also confirmed by metabolomics. GlcNAc-6-sulfate was at least 6 times higher in pups' feces in both NNS groups, suggesting a glycosaminoglycan processing deficiency following NNS exposure. In the lipids, modified glycerylphosphorylcholine and glycerylphosphoethanolamine as well as myoinositol were significantly downregulated in NNS exposed pups while structural lipids such as phosphoethanolamine, hexadecasphinganine and sphinganine were upregulated.
Numerous deregulated metabolites were associated with improper liver clearance and detoxification pathways (Figures 3A, 2A,B and Supplementary Tables S3, S4). Of note, both primary and secondary bile acids, N-acetylated amino acids and sulfated metabolites were downregulated in NNS pups. In addition, accumulation of cys-glutathione disulfide was consistent with unprocessed reactive intermediary metabolites normally removed through phase 2 detoxification ( Figure 3A).

NNS Exposure Was Associated With Deregulation of Hepatic Phase 2 Detoxification, Bile Acids and a Pale Liver Phenotype
Metabolic detoxification occurs primarily in the liver and is divided into 3 phases: transformation, conjugation and transport (Almazroo et al., 2017) (Figure 3A). To confirm the unbiased metabolomics findings that NNS pups have altered detoxification metabolism, gene expression was analyzed in the livers of control and ADI1x pups by phase 1 and 2 drug metabolism qPCR array ( Figure 3B and Supplementary Tables S5, S6). Transcriptomics of 20-day old pups' livers showed downregulated transcripts encoding enzymes in phase 2 metabolism. Indeed, the bile acid-CoA: amino acid N-acetyl transferase Baat, the acyl-CoA synthetase Acsl3, the glycine modifying enzyme Gnmt and glutathione S-transferase Gstm5 were highly downregulated. These transcriptional results are consistent with improper phase 2 detoxification and accumulation of intermediary metabolites. Furthermore, whitening of NNS pups' livers was consistently observed in the ADI2x group and to a lesser degree in the ADI1x group (Supplementary Figure S3A). Intriguingly, common histologic analysis of the NNS livers did not reveal macroscopic damage to the liver (Supplementary Figure S3B -H&E and Masson). By immunohistochemistry analysis, there was no evidence of either altered glycogen (PAS), lipid droplets (H&E), iron (Perl) or bile (Hall) storages in the offspring of NNS exposed mothers (Supplementary Figure S3B).

NNS Pups Exhibited Major Changes in Gut Microbiota
In addition to major changes in metabolism, metabolomics analysis identified deregulation of specific microbial metabolites (Figures 2, 3A). These observations suggested major changes in the microbiome in addition to amino acid metabolic deregulation in the NNS pups. Many bacterial metabolites (Gottschalk, 2012) differed in their abundance in NNS pups such as N-formylmethionine, 6-oxolithocholate, 7-ketodeoxycholate, hippurate, daidzein and genistein. Considering the existing literature on NNS and adult microbiome, we hypothesized that NNS could also alter the pups' gut microbiome.
Bacteroidetes, verrucomicrobia and firmicutes represented 44.34, 30.53, and 23.62% of the Ctrl pups' microbiota, respectively ( Figure 4A and Supplementary Table S7). In NNS pups, firmicutes doubled (ADI1x = 44.45%; ADI2x = 45.91%), including clostridiales families lachnospiraceae and ruminococcaceae (g_Oscillospira). In contrast, verrucomicrobia, represented by a single species A. muciniphila, was significantly depleted in NNS pups (ADI1x = 2.97%; ADI2x = 6.88%). These observations were confirmed by analysis of the beta-diversity principal coordinate analysis (PCoA), showing separation of Ctrl, ADI1x and ADI2x pups ( Figure 4B). All three groups of pups also separated significantly by ADONIS test (Unweighted Unifrac: r 2 = 0.07 and p < 0.001; Weighted Unifrac: r 2 = 0.18, p < 0.001) (Supplementary Figure S4D). A significant increase in alpha-diversity was also observed for both NNS groups, suggesting an increased variety of the gut microbiota ( Figure 4C and Supplementary Figure S4E). This may be attributed to the loss of the highly abundant A. muciniphila in the gut in combination with increase of the firmicutes species.
Offspring's microbiome dysbiosis is often explained by changes in the mother's microbiome. Indeed, the microbiota is shaped from birth by successive exposure to the mother's vaginal, skin and breast milk microbiomes (Palmer et al., 2007). Consequently, the same phyla were found in the mothers' and pups' microbiome (Supplementary Figure S4A and Supplementary Table S8). Ctrl and NNS-fed mothers' microbiota were not statistically different. Similarly, Ctrl and NNS mothers' microbiomes did not separate on the alpha or beta-diversity analysis (PCoA plot) or by ADONIS test (Supplementary Figures S4B-E). Therefore, the divergence between Ctrl and NNS pups' microbiota cannot be explained by an alteration in the mothers' microbiota. Mother-to-pup's transmission can be analyzed by calculation of Spearman correlation coefficients for the different groups. A decrease in correlation was observed with NNS exposure, suggesting that the The changes observed in mothers and pups in verrucomicrobia levels and firmicutes/bacteroidetes ratio (Kruskal-Wallis test) (n = 24). Significance values: * * * * p < 0.001, * * * p < 0.005, * * p < 0.01, * p < 0.05. divergence between mothers' and pups' microbiomes were due to increasing NNS concentrations ( Figure 4D).
Alteration of NNS pups' microbiome also suggested metabolic imbalance, which correlated with the metabolomic data. Indeed, an increased firmicutes/bacteroidetes ratio is associated with obesity (Ley et al., 2005) while depletion of A. muciniphila is frequently a sign of metabolic dysregulation (Everard et al., 2013;Schneeberger et al., 2015; Figure 4E).

Akkermansia muciniphila Colonization Was Defective in NNS Pups
A closer look at pups' A. muciniphila level and their corresponding mothers by qPCR confirmed an improper transmission in NNS pups ( Figure 5A). It is important to understand why A. muciniphila colonization was defective in NNS fed pups since this bacterium is widely regarded as beneficial (Everard et al., 2013;Schneeberger et al., 2015). However, A. muciniphila level analyzed by qPCR showed various levels single housed mothers 1 day before mating (Supplementary Figure S5). Breastfeeding is one of the major sources of bacteria and probiotics for the pups. Nevertheless, analysis of the newborn pups showed similar level of A. muciniphila in Ctrl and ADI1x animals right after first nursing (d1), suggesting that mothers properly transmitted A. muciniphila at birth to their pups ( Figure 5B). However, pups' A. muciniphila level over time ( Figure 5C) showed an improper progression of colonization in the ADI1x group. Indeed, after the establishment of gut anaerobic environment (Pantoja-Feliciano et al., 2013), A. muciniphila colonized the Ctrl but not the ADI1x pups.
We then directly exposed A. muciniphila to various NNS concentrations or ampicillin and measured bacterial growth in vitro (Figure 5D). While ampicillin completely inhibited A. muciniphila growth, no difference was observed between control or NNS supplemented media suggesting that A. muciniphila can grow in the presence of NNS.

DISCUSSION
Use of NNS has greatly increased worldwide in the last few decades. While awareness of NNS related negative health outcomes is growing, critical knowledge gaps exist about the mechanisms and extent of NNS induced effects. Recently, a science advisory was released by the American Heart Association which encourages consumers to not replace sugar sweetened with artificially sweetened beverages but to focus on water (Johnson et al., 2009). The report also includes a description of research needs with specific mention of pediatric studies. Of note, government agencies usually prohibit the addition of NNS to baby and infant foods, but no specific recommendations exist for pregnant or lactating mothers. To fully understand NNS impact, it is necessary to conduct more studies early in life using a wider range of doses and NNS combinations. In this study, we investigated the effects of maternal consumption of a combined sweetener solution (sucralose and acesulfame-K) at concentrations relevant to human exposure, e.g., once or twice the ADI.
Gestating and lactating mouse mothers transmit the ingested NNS to the pups in utero, and through breastfeeding postnatally (McNeil Specialty Products Co., 1987;Zhang et al., 2011). Little is known about human in utero exposure, but transmission via breast milk has been established (Sylvetsky et al., 2015). The NNS exposed adult female mice showed no abnormalities. This is consistent with other studies in which NNS effects were typically observed after months of exposure (FDA, 1988(FDA, , 1999. However, NNS pups were phenotypically different. In this study, we report significantly decreased weight and fasting glucose for the ADI2x pups. In experiments submitted to the FDA prior to sucralose's approval, animals exposed to much higher concentrations had been found to have diminished weight which is mostly attributed to decreased food palatability (FDA, 1988(FDA, , 1999. Another important observation was the hepatic discoloration, most evident in the ADI2x pups. Liver whitening can be observed in numerous conditions such as fatty liver disease, anemia [previously shown in sucralose exposure at pharmacologic doses (European Commission, 2000)], mitochondrial dysfunction and improper clearance of metabolites. Whereas these pathologies can take months to develop in rodents, NNS pups showed signs of whitening at only 20 days of life. Histologic analyses ruled out fatty liver disease and fibrosis and showed no specific pathology. Since macronutrient storage was not altered, we speculate that the cause of liver whitening is due to a combination of faulty detoxification, decreases in bile acid formation, increased oxidative stress, and decreased mitochondrial function.

Metabolic Deregulation in NNS Pups
We found that NNS exposure of pregnant and nursing mothers causes critical changes in amino acid and detoxification metabolism in the progeny, identified by a non-targeted metabolomics analysis of feces and blood samples. Eleven of the significantly deregulated metabolites in NNS pups are part of standard screening tests for inborn errors of metabolism (IEM) in humans (El-Hattab, 2015). IEMs are mostly due to mutations in specific enzymes or transport proteins of important metabolic pathways. Frequently observed symptoms in IEM are growth failure, weight loss, developmental delay, liver failure and/or hypoglycemia, many of which are observed in the NNS exposed pups. Despite different etiologies (genetic mutation vs. environmental exposure), this suggests similarly interrupted processes of nutrient processing and detoxification.
Among the various deregulated metabolic pathways, the pups' amino acid metabolism is most affected particularly the glycine metabolism. Glycine is used for synthesis of glutathione, bile acids, heme, hippurate and propionylglycine (Wang et al., 2013), all under-represented in the metabolomics data. Glycine shortage has been associated with suboptimal growth, impaired immune system function (Lewis et al., 2005) as well as many other conditions (Wijekoon et al., 2004). NNS pups also have a striking deficit in numerous compounds related to detoxification. A relationship with NNS has been suggested previously, demonstrated in adult rats by the upregulation of the multidrug resistance transporter P-gp and the cytochrome P450 Cyp3a4 and Cyp2d1 following sucralose exposure (Abou-Donia et al., 2008). In our hands, Cyp3a11, the mouse homolog of Cyp3a4, is also upregulated but did not reach statistical significance, potentially due to the short exposure. Furthermore, several phase 2 detoxification metabolism enzymes are downregulated in NNS pups. Among the deregulated enzymes is bile acid-CoA: amino acid N-acetyl transferase (Baat), which catalyzes the addition of glycine or taurine to unconjugated bile acids, consistent with the observed decrease of primary bile acids (O'Byrne et al., 2003). Decreased glycine modifying enzyme Gnmt expression is consistent with a deregulated glycine metabolism and lower Acyl-CoA synthetase Acsl3 expression also implies an inefficient phase 2 metabolism. Finally, glutathione-S transferase Gstk1 plays a major role in phase 2 detoxification participating in the maintenance of oxidative balance (Deponte, 2013). The balance between phase 1 and phase 2 enzymes is critical for proper detoxification. Food, smoking, alcohol consumption, age and genetics are known factors impacting detoxification enzymes producing intermediary harmful metabolites faster than they can be detoxified, ultimately leading to increased oxidative stress and tissue damage (Liska, 1998). Our data suggest that sucralose and/or acesulfame-K also belong to these pathogenic factors. This is consistent with a previous study showing an association of sucralose consumption and microbiome-dependent liver inflammation (Bian et al., 2017a). Since our findings were most impressive in the pups, we speculate that the pre-and postnatal period represent a highly vulnerable developmental phase (Abou-Donia et al., 2008). At 20-days postpartum, pups are still developing their detoxification systems and metabolism. At this critical developmental stage exposure to NNS might be more consequential. Also, 20-days-old pups have a limited nutritional influx, mostly breast milk. At weaning, the increased variety of nutrients may further challenge metabolic detoxification. Indeed, endotoxins, end products of metabolism, bacterial as well as intermediary metabolites might accumulate, creating a toxic environment impossible to overcome.

Microbiome Alterations in NNS Pups
Following pre-and post-natal exposure to NNS, pups have a dramatically different microbial composition, which is not due to alteration of mother's microbiome. Indeed, mothers and pups' microbiome are expected to look alike, consequences of a high microbe exchange through vaginal and physical contact, breastfeeding and murine coprophagic behavior (Faith et al., 2013;Bäckhed et al., 2015).
Studies in adult mice have previously shown NNS' detrimental effects on the intestinal microbiome, mostly increases in clostridiales, lactobacilli, and enterobacteria (Abou-Donia et al., 2008;Cowan et al., 2013;Palmnäs et al., 2014;Suez et al., 2014;Bian et al., 2017b). A bacteriostatic effect has also been suggested in microbes in the oropharynx (Prashant et al., 2012). The microbiome signature of the NNS pups is a large increase in firmicutes combined with a marked depletion of Verrucomicrobia, represented exclusively by A. muciniphila. Both of these alterations are clinically relevant and have been associated with increased incidence of obesity and/or metabolic syndrome in rodents and humans (Ley et al., 2005;Hansen et al., 2012;Schneeberger et al., 2015). The increase in firmicutes observed in NNS pups is mainly due to the clostridiales order, the lachnospiraceae family and oscillospira genus. Those three clostridia class members are known to participate in normal metabolism of bile acids, carbohydrates and amino acids and participate in colonic epithelium health by producing short chain fatty acids (Donohoe et al., 2011). Therefore, increases in clostridia can influence colonocyte homeostasis. Interestingly, increases in exposed pups' phospholipids and sphingolipids also are consistent with an increase gut cell proliferation.
Akkermansia muciniphila, depleted in NNS pups, is a beneficial bacterium associated with a young and lean metabolism, inversely correlated with fat mass gain, type 1 diabetes and Inflammatory bowel syndrome (Ley et al., 2005;Hansen et al., 2012;Schneeberger et al., 2015). A decrease in A. muciniphila was previously observed in response to long saccharin exposure in adult rats (Suez et al., 2014). Interestingly, A. muciniphila encodes a GlcNAc-6-sulfatase and the reduction in A. muciniphila in the NNS-pups' gut is consistent with the abundance of GlcNAc-6-Sulfate in NNS pups' feces. In vitro culture of A. muciniphila is not affected by the presence of NNS but the colonization is clearly deficient in the pups. Therefore, the improper colonization of A. muciniphila may be the result of a change in the mucin profile, fucosylated milk oligosaccharides and/or gut pH due to changes in metabolites, microbe abundance or inflammation status (Aakko et al., 2017;Van Herreweghen et al., 2017).
Metabolomics analysis is also suggestive of substantial gut microbiome alterations. Among the deregulated metabolites, N-formyl-methionine is used for protein synthesis in bacteria only (Gottschalk, 2012). Secondary bile acids are also exclusively produced by gut microbes from primary bile acid release in the GI tract. A decrease in secondary bile acids similar to ours, has been associated with decreased fasting glucose in mice (Kuno et al., 2018). Heme breakdown products biliverdin and bilirubin are also transformed by microbes to produce urobilinogen. From dietary aromatic compounds, the gut microbiome also metabolizes benzoate, the primary source of hippurate. Finally, gut microbes convert natural isoflavone glycosides into daidzein and genistein, which are readily absorbed. Gut microbiome function is also tightly linked to detoxification mechanisms. Indeed, microbial metabolites are detoxified by the host (Spanogiannopoulos et al., 2016) and in a complementary fashion, the gut microbiota transforms drugs and bile acids (Wahlström et al., 2016). Therefore, improper detoxification might be the result or the consequence of microbiome dysbiosis.

CONCLUSION
In conclusion, pre-and post-natal exposure to sucralose and acesulfame-K via maternal ingestion causes marked metabolic and microbiome alterations in the pups (Figure 5E), which could give rise to future metabolic disease. This study adds to the growing list of negative effects linked to NNS consumption. Given that the perinatal period is a critical developmental stage for the nascent microbiome and emerging detoxification systems in the rodent and human neonate alike, our study defines potentially adverse consequences of early NNS exposure.

ETHICS STATEMENT
This study was carried out in accordance with the recommendations of NIH guideline for animal use, Animal Care and Use Committee (NIH). The protocol was approved by the NIDDK Animal Care and Use Committee (NIH) under the protocol number #K023-LCBB-16.

AUTHOR CONTRIBUTIONS
SO-VS designed and performed the experiments and wrote the manuscript. JH and KR supervised the experiments and revised the manuscript.


extfieldsofstudy: Biology Medicine

text:
MITF Regulates Downstream Genes in Response to Vibrio parahaemolyticus Infection in the Clam Meretrix Petechialis

The microphthalmia-associated transcription factor (MITF) is a basic helix-loop-helix-leucine zipper protein that plays a key role in cell proliferation, survival and immune defense through the direct transcriptional control of downstream genes. We have found that MITF participates in the immune response to Vibrio parahaemolyticus infection in the clam Meretrix petechialis. In this study, we focused on how MITF functions in immunity. First, PO, CTSK, and BCL-2 were identified as the target genes of MpMITF in the clam by RNAi. EMSAs showed direct binding between the MpMITF protein and the E-box of the MpPO, MpCTSK, and MpBCL-2 promoters. Yeast one-hybrid assays also suggested that MpMITF could activate the expression of these three downstream genes. These results demonstrated that the transcriptional expression of MpPO, MpCTSK, and MpBCL-2 is directly regulated by MpMITF. Second, we analyzed the roles of MpPO, MpCTSK, and MpBCL-2 in clam immunity. The mRNA expression of MpPO, MpCTSK, and MpBCL-2 increased significantly after V. parahaemolyticus challenge, which implied that these genes might take part in the immune defense against V. parahaemolyticus challenge in clams. The purified recombinant proteins, MpPO and MpCTSK, inhibited the growth of V. parahaemolyticus. Additionally, the apoptosis rate of clam haemocytes rose significantly when the activity of MpBCL-2 was suppressed. These results revealed that MpPO, MpCTSK, and MpBCL-2 are involved in the immune defense against V. parahaemolyticus. This study supports the idea that the MpMITF pathway plays a key role in immune defense through the direct regulation of the downstream genes MpPO, MpCTSK, and MpBCL-2 in the clam, M. petechialis.

INTRODUCTION
The microphthalmia-associated transcription factor (MITF), a member of the MYC family of transcription factors, is a basic helix-loop-helix-leucine zipper (bHLH-LZ) protein (1)(2)(3)(4). MITF directly regulates downstream genes depending on its bHLH-LZ domain, which binds to the canonical E-box sequence (CANNTG) found in the promoter regions of downstream genes (5). MITF has been found in vertebrate species including mouse, rat, chicken, hamster, and human (6). In addition, MITF has been described in some invertebrates, such as Caenorhabditis elegans, Drosophila melanogaster, and Halocynthia roretzi (7). To date, MITF has been reported to be expressed mainly in melanocytes, osteoclasts, macrophages, B cells and natural killer cells and is the key regulator of signaling pathways that control cell proliferation, survival and immune defense (8).
MITF transcriptionally regulates a number of target genes involved in the immune signaling pathways of vertebrates, such as phenoloxidase (PO), cathepsin K (CTSK), cyclin-dependent kinase 2 (CDK2), N-deacetylase/N-sulfotransferase (NDST), perforin, tryptase, and the anti-apoptotic factor BCL-2 (9)(10)(11)(12)(13)(14)(15). Among them, PO is the key enzyme in the process of melanin production, which plays a role in immune defenses, wound healing and self/non-self-recognition mechanisms (16,17). Moreover, as a member of the cysteine protease papain superfamily, the upregulation of CTSK is associated with various pathological processes in humans, such as inflammatory diseases and cancer (18). BCL-2 is an integral intracellular membrane protein, which is a critical regulator of mitochondrial membrane permeability and of the apoptotic mitochondrial pathway (19). In addition, MITF has been reported to regulate the target gene tryptase in the differentiation and functioning of mast cells (20), and mutated MITF can suppress the transactivation of perforin to reduce the natural killer activity of NK cells (13). All of these studies have demonstrated that MITF is a transcriptional regulator of innate immune signaling pathways in vertebrates, but such mechanisms in invertebrates remain poorly understood.
The clam Meretrix petechialis is a commercial mollusc found off the coast of southern and southeast Asia (21). Our laboratory has made progress in the disease and immune research of this clam (22)(23)(24)(25)(26). We found that MITF participates in the immune response to Vibrio parahaemolyticus infection and the expression of MITF was upregulated during V. parahaemolyticus infection in this clam (27). However, how MITF functions in the immune response in M. petechialis has not been investigated. Since the immune mechanism is quite different between vertebrates and invertebrates, we wondered if the immune signaling pathway regulated by MITF in clams is similar to that in vertebrates. In addition, to clarify the MITF's immune function in the clam immunity will contribute to our understanding in the clam immunity and benefit for the future clam resistance selection. In the present work, we identified PO, CTSK, and BCL-2 as the downstream target genes of MITF. We analyzed the function of these genes, demonstrating that MpPO and MpCTSK can suppress the growth of V. parahaemolyticus and that MpBCL-2 is associated with the antiapoptotic activity of the haemocyte response to V. parahaemolyticus infection. This study revealed MpMITF as a transcriptional regulator of the innate immune system in the clam M. petechialis.

Experimental Clams, Bacterial Challenge, and Tissue Collection
Adult clams (43.7 ± 0.35 mm in shell length) were sampled from our laboratory-bred strains, which were cultured in a wild pond in Zhejiang province, China. Samples were acclimated in the laboratory for 1 week and supplied with filtered aerated seawater and microalgae. For bacterial challenge assays, approximately 100 clams were placed in a 200 L water tank to be challenged by immersion in a concentration of 1 × 10 7 CFU mL −1 of V. parahaemolyticus (25). The challenge assay lasted for a sampling period of 13 days. Clams were randomly sampled and the hepatopancreases were dissected on days 0, 2, 4, 6, 8, 10, 11, and 13 after challenge, and then the hepatopancreases were preserved in liquid nitrogen before RNA extraction. There were five replicates for each time point.

Total RNA Extraction and cDNA Synthesis
Total RNA was isolated using a total RNA Kit (Omega, USA) according to the manufacturer's instructions. The extracted RNA was quantified using a NanoDrop ND1000 spectrophotometer (Thermo Scientific, USA). The firststrand cDNA was synthesized from total RNA with a PrimeScript TM 1st Strand cDNA Synthesis Kit (TaKaRa, Japan) following the manufacturer's instructions. The cDNA used for quantitative real-time PCR was synthesized from total RNA using the PrimeScript TM RT reagent Kit with a gDNA Eraser (TaKaRa, Japan).

RNA Interference (RNAi) of MpMITF in Clams
The cDNA fragment of MpMITF (GenBank: KY446553) was amplified using the T7 promoter-linked primers, MITF-T7-F and MITF-T7-R (Table 1), and was used as a template for the synthesis of the MpMITF double-stranded RNA (dsMITF). A fragment of the pEGFP vector plasmid (Clontech, USA) was amplified with EGFP-T7-F and EGFP-T7-R ( Table 1) and used as a template for the synthesis of the EGFP double-stranded RNA (dsEGFP). The dsMITF and dsEGFP were synthesized and purified using a TranscriptAid T7 High Yield Transcription Kit (Thermo Scientific, USA). The quantity and integrity of the dsRNAs were determined using a NanoDrop ND1000 spectrophotometer (Thermo Scientific, USA) and agarose gel electrophoresis, respectively.
Thirty clams used for RNAi experiments were randomly divided into two groups including the dsMITF-injected group (15 clams) and the dsEGFP-injected group (15 clams; negative control). The dsMITF/dsEGFP was injected into the hepatopancreas of each clam with a microsyringe. Each clam in the injected groups was injected with 10 µL of dsMITF or dsEGFP (3 µg/µL). The hepatopancreases of five clams in each group were collected at 12 and 48 h post-injection (hpi) and stored in liquid nitrogen before RNA extraction. Quantitative real-time PCR was used to test the efficiency of MpMITF knockdown and the expression of putative MpMITF downstream genes.

Quantitative Real-Time PCR
Quantitative real-time PCR (qRT-PCR) was carried out using appropriate primers with an ABI 7500 fast Real-Time Thermal Cycler machine (Applied Biosystems, USA). β-actin was used as the internal reference to normalize the expression levels between samples (23). Primers used in this experiment are listed in

Electrophoretic Mobility Shift Assays (EMSAs)
Full-length MpMITF protein was generated by in vitro transcription using the One-Step Human IVT kit (Thermo Scientific, USA) following the manufacturer's protocol. The MpMITF protein was confirmed by Western blot using an anti-MITF antibody (ABClonal, USA). EMSAs were carried out using the Lightshift R Chemiluminescent EMSA Kit (Thermo Scientific, USA). Briefly, binding reactions were conducted in binding buffer for 20 min at room temperature using MpMITF protein and biotin-labeled annealed doublestranded probes containing the E-box elements from the MpCTSK/MpPO/MpBCL-2 promoters. For the competition assays, unlabelled probes were added to the reaction mixture 15 min before adding the labeled probes. Then, the mixtures were loaded onto a 6% native polyacrylamide gel and electrophoresed at 4 • C for 120 min at 90 V in 0.5 × TBE. Following electrophoresis, the gel was transferred to a positively charged nylon membrane (Solarbio, China) and the shifted bands were visualized by chemiluminescence according to the manufacturer's manual.

Yeast One-Hybrid Assays
A yeast one-hybrid (Y1H) assay was performed using the Matchmaker TM Gold Yeast One-Hybrid System (Clontech, USA) as described in the manufacturer's protocol. Briefly, the promoter sequences of MpPO/MpCTSK/MpBCL-2 were cloned into the pAbAi vector, which contains an AbA resistance (AbA r ) reporter gene, to construct CTSK/PO/BCL-2-pAbAi. Then, the CTSK/PO/BCL-2-pAbAi plasmid was linearized using the BstBI restriction enzyme (NEB, USA) and integrated into the genome of the Y1HGold yeast strain. The minimal inhibitory concentration of Aureobasidin A (AbA) for the yeast strain was confirmed using 300 ng/ml. Additionally, the full coding sequence of MpMITF was cloned into the pGADT7 vector to construct MITF-pGADT7, which expressed MITF fusion proteins containing the yeast GAL4 transcriptional activation domain (AD). The MITF-pGADT7 vector was transformed into the yeast strain containing CTSK/PO/BCL-2-pAbAi and screened on SD/-Leu/AbA plates. When the MITF protein binds to the MpPO/MpCTSK/MpBCL-2 promoter sequences, the GAL4 AD will activate expression of AbA r , allowing the cells to grow on media containing the AbA antibiotic.

Expression, Purification, and Identification of MpCTSK and MpPO
To express the recombinant MpCTSK and MpPO proteins, the coding sequences of MpCTSK (GenBank: MK294530) and MpPO were separately amplified by the primer pairs MpCTSK-F/R and MpPO-F/R ( Table 1) and cloned into a pET30a or pGEX-4T-1 expression vector, respectively. The generated expression plasmids were transformed into BL21 (DE3) pLysS Chemically Competent Cells (TransGen Biotech, China) for overexpression. After induction with a final concentration of 0.2 mM isopropylb-d-thio-galactoside (IPTG) at 28 • C for 6 h, the bacteria were pelleted by centrifugation at 12,000 rpm for 10 min. The whole cell pellet suspensions were disrupted in PBS by sonication in an ice bath and then centrifuged at 12,000 rpm for 10 min. The recombinant MpCTSK and MpPO fusion proteins were purified with the His-Trap and GST-Trap affinity columns (GE Healthcare, Germany), respectively. The purified recombinant MpCTSK and MpPO proteins were analyzed via 12% SDS-PAGE (GenScript, China). After electrophoresis, the gel was stained with Coomassie brilliant blue R250. In addition, the purified MpCTSK and MpPO proteins were identified by Western blot. Briefly, the purified recombinant protein samples were separated by SDS-PAGE (12%) and transferred onto a PVDF membrane. The membrane with transferred proteins was immersed in 5% non-fat milk in TBST for 2 h at room temperature and subsequently incubated with primary rabbit anti-cathepsin K or rabbit anti-TYR antibodies (ABClonal, USA; 1:1,000) at 4 • C overnight. After washing three times for 10 min with TBST, the membranes were incubated with a diluted secondary goat anti-rabbit IgG-HRP antibody (ZSGB-BIO, China; 1:5,000). The target protein signals were detected with an Enhanced HRP-DAB Chromogenic Substrate Kit (Tiangen, China).

Antimicrobial Activity Assays
Antimicrobial activity assays were performed to detect the antimicrobial activities of the purified recombinant MpCTSK and MpPO proteins in vitro. The purified recombinant MpCTSK (r MpCTSK) and MpPO (rMpPO) proteins were obtained in section Expression, Purification, and Identification of MpCTSK and MpPO. The antimicrobial activity of purified rMpCTSK and rMpPO was tested in 96-well microtiter plates. In detail, rMpCTSK and rMpPO were diluted with PBS to 1 µM. PBS was used as the blank control. Vibrio parahaemolyticus as well as Staphylococcus aureus and Micrococcus luteus were cultured and collected by centrifugation at 800 g for 10 min. After washing twice with PBS, the bacteria were resuspended at a concentration of 1 × 10 5 CFU mL −1 in PBS. A volume of 100 µL of bacterial suspensions was mixed with 100 µL of 1 µM rMpCTSK, rMpPO or an equal volume of PBS. The 96-well microtiter plate was incubated at 30 • C for 24 h and the absorbance of the plate was measured every 8 h at an OD of 600 nm. The experiment was repeated three times.
The bacterial feedback inhibition loop was examined to verify the inhibitory activity. In brief, aliquots of 50 µL bacterial suspensions of V. parahaemolyticus and S. aureus diluted to 1 × 10 5 CFU mL −1 were spread on an agar plate. On each plate of V. parahaemolyticus or S. aureus, 10 µL of 1 µM rMpCTSK and rMpPO were spotted separately using filter papers. An equal volume of kanamycin was spotted as a positive control, while a GST-tagged protein/His-tagged protein and PBS were spotted as negative controls. Bacteria were grown on the agar plate overnight at 30 • C. Each experiment was performed with three repeats.

Apoptosis Assay
An apoptosis assay was performed to gain insights into the role of MpBCL-2 on the clam haemocytes apoptosis. Haemocytes extracted from 20 healthy clams were mixed and divided equally into two groups, i.e., the ABT199-treated group and control group. Each group was sub-divided into three replicates. The haemocytes in the ABT199-treated group were cultured in L15 medium (Solarbio, China) added with a BCL-2 specific inhibitor, ABT199 (Beyotime biotechnology, China) at 18 • C for 12 h, while the heamocytes in the control group were cultured in L15 medium added with the equal volume of DMSO at 18 • C for 12 h. Then, these haemocytes were applied to an apoptosis assay. In brief, the haemocytes were washed three times with L15 medium and then suspended in L15 medium to a final concentration of 1 × 10 6 cells mL −1 . The suspended haemocytes were subjected to flow cytometry (BD Biosciences, USA) for apoptosis rate detection using the Alexa Fluor R 488 annexin V/Dead Cell Apoptosis kit (Invitrogen, USA).
In addition, the influence of V. parahaemolyticus challenge on the clam haemocytes apoptosis was also detected. Briefly, 50 µL of V. parahaemolyticus with a concentration of 5 × 10 6 CFU mL −1 was injected into the adductor of thirty clams individually. These Vibrio-injected clams were cultivated in a 50 L water tank for 48 h, during which the haemocytes were extracted using syringes from adductors of six clams at 0, 12, 24, and 48 hpi for apoptosis rate analysis by flow cytometry using the Alexa Fluor R 488 annexin V/Dead Cell Apoptosis kit.

Statistical Analysis
All data are presented as the means ± S.D. Statistically significant differences were analyzed by one-way ANOVA using SPSS 19.0 software. The significance level was set as P < 0.05.

Knockdown of MpMITF Influences the Expression of Downstream Genes
An RNAi experiment was used to identify the potential downstream genes of MpMITF. The efficiency of interference was determined by qRT-PCR. The qRT-PCR results showed that, compared to the dsEGFP-injected group, the mRNA expression of MpMITF in the dsMITF-injected group was significantly downregulated at 48 hpi (P < 0.05) (Figure 1A), indicating that the RNAi worked. The change in mRNA expression for a series of putative MpMITF downstream genes, including MpCTSK, MpPO, MpBCL-2, MpCDK2, MpPerforin, MpNDST, and MpTryptase, was measured in the MpMITF-suppressed individuals by qRT-PCR. The results showed that, compared to the dsEGFP-injected group, the expression of MpCTSK, MpPO, and MpBCL-2 was significantly reduced at 48 hpi in the dsMITF-injected group (P < 0.05) (Figures 1B-D). No significant differences were observed in the expression of MpCDK2, MpPerforin, MpNDST, and MpTryptase before  and after RNAi (Supplementary Figures 1A-D). These results suggested that MpCTSK, MpPO, and MpBCL-2 are the potential downstream targets of MpMITF.

MpMITF Binds to the Promoters of MpCTSK/MpPO/MpBCL-2
To evaluate if MpMITF directly binds to the MpCTSK/MpPO/MpBCL-2 promoters, we performed EMSAs using MpMITF recombinant protein and DNA fragments of the MpCTSK/MpPO/MpBCL-2 promoters. The MpCTSK, MpPO, and MpBCL-2 promoters were cloned and all three promoters were found to contain the E-box (CANNTG) sequence (Figure 2). The MpMITF protein with a molecular weight of 57 kDa was verified by Western blot (Figure 3A). Signal detection in EMSAs is based on biotin-labeled DNA in complex with proteins moving more slowly during electrophoresis forming a shifted band. Compared to the control reactions (Figures 3B-D, line 1), a shifted band was observed when labeled MpCTSK/MpPO/MpBCL-2 DNA and MITF protein were added together, indicating that the MpCTSK/MpPO/MpBCL-2 promoters formed a covalent DNA-protein complex with the MpMITF protein (Figures 3B-D, line 2). However, the band shift was prevented by the addition of excess unlabelled DNA (competitor DNA) (Figures 3B-D, line 3). The EMSA results showed that MpMITF specifically binds to the promoter regions of MpCTSK, MpPO, and MpBCL-2, further suggesting that MpCTSK, MpPO, and MpBCL-2 are transcriptionally regulated by MpMITF.  together with the pGADT7-MITF effector plasmid were cotransformed into Y1HGold cells to validate the interaction. The positive control was generated by cotransforming the pGADT7-Rec-p53 and p53-pAbAi plasmids into Y1HGold cells. The Y1HGold strain cotransformed with the MpPO/MpCTSK/MpBCL-2-pAbAi and pGADT7-AD plasmids was used as a negative control. The normal growth of all Y1HGold yeast strains on SD plates without Leu (SD/-Leu) indicated that the yeast growth status was healthy (left). Only the strains containing the effector plasmid pGADT7-MITF and the positive control showed growth on SD/-Leu containing 300 ng/ml aureobasidin A (SD/-Leu/AbA, right), suggesting a specific interaction between the MpPO/MpCTSK/MpBCL-2 promoters and MpMITF.

MpMITF Activates the Expression of MpCTSK/MpPO/MpBCL-2
To test if MpMITF could regulate the expression of MpCTSK, MpPO, and MpBCL-2, yeast one-hybrid assays were performed. In this analysis, the AbA resistance (AbA r ) reporter gene was not activated when the Y1HGold yeast strain was cotransformed with the CTSK/PO/BCL-2-pAbAi and empty pGADT7-AD plasmids because the transcription of CTSK/PO/BCL-2 was not activated, resulting in no growth on the SD/-Leu medium with AbA (Figure 4, negative control). By contrast, the Y1HGold yeast strain cotransformed with the MITF-pGADT7 and CTSK/PO/BCL-2-pAbAi plasmids could grow on the SD/-Leu medium with AbA (Figure 4), indicating that MpMITF activated the expression of CTSK/PO/BCL-2 and AbA r , which allowed the cells to grow on media containing the AbA antibiotic. These results suggested that MpMITF can directly activate the expression of MpCTSK, MpPO, and MpBCL-2.

MpCTSK, MpPO and MpBCL-2 Respond to V. parahaemolyticus Infection
To investigate if the expression of the MpMITF downstream genes was influenced by V. parahaemolyticus challenge, the mRNA expression levels of MpCTSK, MpPO, and MpBCL-2 were measured by qRT-PCR. The tissue distributions of MpCTSK, MpPO and MpBCL-2 in the hepatopancreas, mantle, foot, gill, haemolymph and adductor muscle were analyzed. The results showed that all of these genes were widely expressed in the six tissues (Supplementary Figure 2). The hepatopancreas is the main immune organ in clams and thus was selected for the further study (29). A V. parahaemolyticus immersion challenge was performed to investigate the MpCTSK, MpPO and MpBCL-2 expression response to V. parahaemolyticus infection in the clam. As Figure 5A shows, the mRNA expression level of MpCTSK was increased at 2 d post infection (dpi), reached the highest level at 4 dpi, and remained at a high level until 13 dpi. Significant differences were detected at 4, 8, 11, and 13 dpi, compared to 0 dpi (P < 0.05). The mRNA expression level of MpBCL-2 was increased at 2 dpi, peaked at 10 dpi, and then decreased to base levels at 13 dpi. Significantly different mRNA expression levels were detected at 2, 4, 6, 10, and 11 dpi compared with those at 0 dpi (P < 0.05, Figure 5B). Similarly, the expression of MpPO was significantly increased at 2, 4, 8 and 10 dpi compared with 0 dpi (P < 0.05, Figure 5C). These results indicated that MpCTSK, MpPO and MpBCL-2 are involved in the immune response toward V. parahaemolyticus infection.

MpCTSK and MpPO Inhibit the Growth of Bacteria
To determine the roles of the downstream genes MpCTSK and MpPO in response to bacteria, recombinant MpCTSK and MpPO proteins were produced in a prokaryotic expression system. SDS-PAGE results demonstrated that the molecular weights of the recombinant MpCTSK (rMpCTSK) and recombinant MpPO (rMpPO) were approximately 39 and 107 kDa, respectively (Supplementary Figures 3A,B), consistent with the mature proteins predicted from the cDNA sequences. The protein bands were confirmed by Western blot with specific anti-cathepsin K or anti-PO antibodies (ABClonal, USA) (Supplementary Figures 3C,D). The antibacterial activities of rMpCTSK and rMpPO were then evaluated by the minimal inhibitory concentration method. As shown in Figures 6A,B, the growth of V. parahaemolyticus was significantly suppressed at 8 h, 16 h and 24 h when rMpCTSK or rMpPO were added, compared to PBS (P < 0.05). Furthermore, the growth of another pathogen, Staphylococcus aureus, was also inhibited when rMpCTSK or rMpPO were added, while the growth of parahaemolyticus by qRT-PCR. Error bars represent the SD. The asterisk (*) represents significant differences found when compared to 0 dpi (P < 0.05).
Micrococcus luteus was not (Figures 6C,D). In addition, the antibacterial properties of rMpCTSK and rMpPO were also detected by an agar diffusion test. The results showed that rMpCTSK and rMpPO displayed strong antimicrobial activities against V. parahaemolyticus and S. aureus, while no antibacterial properties were detected using filter paper with PBS or GST/Histagged protein (Figures 7A-D). All of these results demonstrated that MpCTSK and MpPO have strong antibacterial activities against V. parahaemolyticus and S. aureus.

MpBCL-2 Inhibits the Apoptotic Activity of Haemocytes During Immune Defense
Our results showed that the haemocyte apoptosis rate was increased post-V. parahaemolyticus injection (Supplementary Figure 4), indicating that Vibrio-induced stress promoted the apoptosis rate in clams. The relationship between BCL-2 and the apoptosis rate was then evaluated. To inhibit the activity of BCL-2, the specific inhibitor, ABT199, was used in this study (30). The haemocytes were treated with the BCL-2 inhibitor for 12 h (ABT199, diluted with DMSO), while the haemocytes of the control group were treated with equal volume of DMSO. The data (Figure 8) showed that the percent of apoptotic cells in the ABT199-treated group (17.4%) was significantly higher than that in the control group (12.4%) (P < 0.05), implying that BCL-2 inhibits the apoptosis of haemocytes. Our results have shown that the expression of MpBCL-2 is significantly increased after V. parahaemolyticus challenge and that V. parahaemolyticus stress promotes the apoptosis rate in clams. These findings suggest that BCL-2 is involved in the immune response to V. parahaemolyticus challenge through the inhibition of haemocyte apoptosis in clams.

DISCUSSION
The microphthalmia-associated transcription factor is a crucially important transcription factor that regulates a series of downstream genes. In our previous study, we have found that MpMITF was associated with the immune defense of the clam M. petechialis (27). In this research, we investigated how MpMITF plays a key role in immune function, acting as a transcription factor in clams. According to the existing reports on MITF, we selected several MITF-regulated immune-related downstream genes, including PO, CTSK, CDK2, NDST, tryptase, perforin and BCL-2, and determined whether these genes were also regulated by MpMITF in clams. In addition, we analyzed the function of these downstream genes in the immune response of molluscs, revealing the regulatory mechanisms of MpMITF in the innate immunity of clams.
The downstream genes transcriptionally regulated by MITF have been widely reported in vertebrates but rarely reported in invertebrates. In this study, we first knocked down the expression of MpMITF and evaluated the expression levels of putative downstream genes including PO, CTSK, CDK2, NDST, tryptase, perforin and BCL-2, according to previous studies (9)(10)(11)(12)(13)(14)(15). Our results showed that among these seven genes, the expression of MpPO, MpCTSK, and MpBCL-2 was significantly reduced after knockdown of MpMITF (Figure 1). A previous study indicated that mutated MITF represses the transcription of the tyrosinase gene (31). Overexpression of MITF dramatically upregulated the expression of CTSK in human osteoclasts (10). Moreover, MITF was reported to upregulate the expression of BCL-2 in tumor cells (15). Our results indeed confirmed that several genes (PO, CTSK, and BCL-2) positively regulated by MITF in other species were also strongly upregulated by MpMITF, suggesting that they were downstream genes of MpMITF in clams.
For the potential downstream genes of MpMITF selected by RNAi, EMSAs were used to investigate their direct interactions with MpMITF. Downstream genes transcriptionally regulated by MITF are mainly governed by the bHLH-LZ domain of MITF (32). We have previously identified a bHLH-LZ structure in the MpMITF protein sequence (27). In this study, we cloned the promoter sequences of MpPO, MpBCL-2, and MpCTSK and were able to detect an E-box sequence in all three of these genes (Figure 2). The E-box sequence is an essential element for the MITF protein to bind to Hughes et al. (5). Our EMSA results showed that a shifted band was detected when labeled MpCTSK/MpPO/MpBCL-2 DNA and MITF protein were added together. Additionally, this shifted band was prevented by the addition of excess unlabelled DNA (Figure 3). These results indicated that MpMITF directly binds to the promoter regions of MpCTSK, MpPO, and MpBCL-2. This binding preference is consistent with published data demonstrating that MITF binds to E-box motifs. For example, Bently et al. showed that MITF transactivated the PO promoter via the E-box (9). BCL-2 and CTSK are also direct MITF target genes via an E-box motif CATGTG in their promoters (33,34).
Based on our results, MpMITF appeared to modulate downstream gene expression by binding to their promoters; our Y1H results further confirmed that the transcription of potential downstream genes was directly regulated by MpMITF. Our data showed that cotransformation of MpPO/MpCTSK/MpBCL-2-pAbAi and MITF-pGADT7 could activate the expression of the AbA resistance (AbA r ) reporter gene, leading to the growth of the yeast strain on SD/-Leu medium with AbA. However, the Y1HGold yeast strain cotransformed with MpPO/MpCTSK/MpBCL-2-pAbAi and empty pGADT7 could not grow on SD/-Leu medium with AbA because the CTSK/PO/BCL-2 promoters were not bound and thus the expression of AbA r could not be activated, further verifying that MpMITF could directly activate the expression of MpCTSK, MpPO and MpBCL-2 (Figure 4). Similarly, other studies have also indicated that overexpression of MITF could activate the expression of CTSK and PO (35,36). All of these results support the conclusion that MpMITF can directly regulate the transcription of MpCTSK, MpPO, and MpBCL-2.
MpPO, MpCTSK, and MpBCL-2 have been suggested to be the downstream genes of MpMITF based on the results of RNAi, EMSA and Y1H assays, but whether MpPO, MpCTSK, and MpBCL-2 are involved in the immune defense of clams has not been investigated. In the present study, we showed that during V. parahaemolyticus challenge, the mRNA expression of MpCTSK was significantly upregulated and remained at a high level until 13 dpi, indicating its participation in the immune defense against microbial infection ( Figure 5A). This notion is supported by the report that CTSK expression was significantly increased post-injection with LPS in the olive flounder Paralichthys olivaceus (37). Meanwhile, the mRNA expression of MpPO and MpBCL-2 was significantly increased at 2 dpi and then decreased back to base level at 13 dpi, however, their initially upregulated expression indicated their response to V. parahaemolyticus infection as well (Figures 5B,C). Consistently, PO activity has been found to be significantly increased after LPS stimulation, as described by Zhou et al. (38). Additionally, increased levels of BCL-2 gene expression have also been observed after V. parahaemolyticus challenge in the orange-spotted grouper Epinephelus coioides (39).
Since MpCTSK, MpPO, and MpBCL-2 were associated with the immune defense against V. parahaemolyticus infection, it was necessary to figure out the immune functions of MpCTSK, MpPO, and MpBCL-2 in the immune response to V. parahaemolyticus challenge. Here, we observed that the purified recombinant MpPO protein inhibited the growth of V. parahaemolyticus and S. aureus (Figures 6, 7). This was consistent with the notion that PO could inhibit the growth of Vibrio in the scallop Chlamys farreri, discussed previously by Xing et al. (40). Bacterial growth inhibition was also observed in the presence of PO in Crassostrea gigas (41). Additionally, PO has been characterized in the Manila clam Venerupis philippinarum and was involved in the immune response to bacterial infection (42)(43)(44). Moreover, the purified recombinant MpCTSK protein also inhibited the growth of V. parahaemolyticus and S. aureus (Figures 6, 7). Although CTSK has been reported to participate in innate immunity, its specific function has not been totally investigated to our knowledge (45). The present study is the first to explore the antibacterial value of CTSK in molluscs.
Finally, the antiapoptotic capability of MpBCL-2 was assessed in this study. We found that V. parahaemolyticus injection could promote the apoptosis of haemocytes (Supplementary Figure 4). Apoptosis is involved in many fundamental processes of the immune system, such as the regulation of the immune defense (46). The induction of apoptosis caused by pathogens has been described in other molluscs. For instance, haemocyte apoptosis in the Pacific oyster Crassostrea gigas was induced during infection with Planococcus citreus (47). To clarify the relationship between MpBCL-2 and cell apoptosis, the apoptosis rate of haemocytes was analyzed when MpBCL-2 was disrupted. Our findings showed a significant increase in the apoptosis rate of the BCL-2-interfered group compared to the control group, indicating an important role for MpBCL-2 in the immune system of clams (Figure 8). These results are in agreement with the previous report that the percentage of apoptotic cells declined when BCL-2 was overexpressed (48). Antonsson et al. found that BCL-2 could bind to proapoptotic proteins (e.g., Bax and Bim) to sequester these proapoptotic proteins in a neutralized state and prevent them from inducing apoptosis (49). The results presented here established the antiapoptotic role of MpBCL-2 and provided fundamental support to the suggested involvement of MpBCL-2 in the immune defense against V. parahaemolyticus.
In conclusion, we discovered that MpPO, MpCTSK, and MpBCL-2 are downstream genes of MpMITF. MpMITF can directly bind to the promoters of MpPO, MpCTSK, and MpBCL-2 and activate their transcriptional expression. MpPO and MpCTSK were found to suppress the growth of V. parahaemolyticus and MpBCL-2 was demonstrated to be associated with antiapoptotic activity in haemocytes. Our findings identify the clam immune-related genes regulated by MITF and reveal the immune regulatory mechanism of MITF in clams, which is unknown in invertebrates before. Some genes regulated by MITF in vertebrates were not regulated by MpMITF in clams, implying that the immune regulatory mechanism of MITF in clams differs from that in vertebrates. Overall, this study clarifies the role of MITF signaling pathway in the innate immunity of the clam M. petechialis.

ETHICS STATEMENT
All experiments involving animals reported in this study were approved by the Ethics Committee of the Institute of Oceanology, Chinese Academy of Sciences.

AUTHOR CONTRIBUTIONS
BL, XY, HW, and SZ: conceived and designed the expriments. SZ, XY, and JY: performed the experiments. SZ and XY: analyzed the data. SZ, XY, and BL: wrote the paper.


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Long noncoding RNA LSINCT5 promotes endometrial carcinoma cell proliferation, cycle, and invasion by promoting the Wnt/β-catenin signaling pathway via HMGA2

Background: A review of the evidence has indicated the critical role of long noncoding RNA (lncRNA) LSINCT5 in a large number of human cancers. However, the mechanistic involvement of LSINCT5 in endometrial carcinoma (EC) is still unknown. Here the authors aim to characterize the expression status of LSINCT5 and elucidate its mechanistic relevance to EC. Methods: Relative expression of LSINCT5 and HMGA2 were quantified by a real-time polymerase chain reaction. SiRNAs were employed to specifically knockdown endogenous LSINCT5 in EC cells. Cell proliferation was measured with Cell Count Kit-8 kit (CCK-8, Dojindo, Kumamoto, Japan) and cell growth was assessed by a colony formation assay. The cell cycle was analyzed with propidium iodide (PI) staining. Apoptotic cells were determined by flow cytometry after Annexin V/PI double-staining. Cell migration was evaluated by a wound-healing assay, and cell invasion was assessed using a transwell migration assay. The protein levels of HMGA2, Wnt3a, p-β-catenin, c-myc, β-actin, and GAPDH were determined by western blot. Results: The authors observed positively correlated and aberrantly up-regulated LSINCT5 and HMGA2 in EC. LSINCT5 deficiency significantly inhibited cell proliferation, cell cycle progression, and induced apoptosis. Meanwhile, cell migration and invasion were greatly compromised by the LSINCT5 knockdown. LSINCT5 stabilized HMGA2, which subsequently stimulated activation of Wnt/β-catenin signaling and consequently contributed to the oncogenic properties of LSINCT5 in EC. Conclusions: Our data uncovered the oncogenic activities and highlighted the mechanistic contributions of the LSINCT5-HMGA2-Wnt/β-catenin signaling pathway in EC.

Introduction
Endometrial carcinoma (EC) is one of the most common gynecologic malignancies in women, and ranks as the sixth in morbidity and third in mortality worldwide. In 2012 it was reported that 320,000 new cases were diagnosed and 76,000 deaths resulted from the disease. 1 Epidemiological investigations have revealed that the majority of EC occurs after menopause. Approximately 40% of incidences are associated with obesity, and other risk factors documented include excessive estrogen exposure, high blood pressure, and diabetes. 2 In addition, approximately 2-5% of patients have been identified with specific genomic mutations in the mismatch repair pathway. 3 EC is histologically categorized into endometrioid, serous and clear-cell subtypes. 4 Diagnosis of this disease is frequently achieved by endometrial biopsy or sampling during procedures such as dilation and curettage. Despite the insufficiency in accuracy and reliability, pap smear serves as a typical method for screening purposes. Currently, abdominal hysterectomy is still the leading treatment option for EC. For more advanced disease stages, radiotherapy, chemotherapy, combined with hormone therapy, or not, are also recommended. 5 The overall prognosis of EC is relatively favorable with a five-year survival rate in the USA greater than 80%.
Long noncoding RNA (lncRNA) is defined as a transcript longer than 200 oligonucleotides without protein-coding potential. The documented biological functions of lncRNA include regulation of gene-specific transcription, basal transcription machinery, transcript splicing, translation, and epigenetic modifications. 6 The importance of lncRNA in diverse human diseases, especially cancers, has been increasingly acknowledged. The subject in terms of the pleiotropic functioning of lncRNAs in EC is discussed in several recently published reviews. [7][8][9] Long stress-induced noncoding transcript 5 (LSINCT5) was first identified to be overexpressed in breast and ovarian cancer and affected cellular proliferation. 10 Subsequent investigations have uncovered its critical role in a range of human cancers. For instance, Xu and colleagues suggested that LSINCT5 predicted a negative prognosis and exhibited oncogenic activity in gastric cancer. 11 Zhang and colleagues demonstrated that elevated B-type natriuretic peptide promoted apoptosis in myocardial cells via the B-type natriuretic peptide/LSINCT5/caspase-1/ interleukin 1β signaling pathway. 12 Long and colleagues reported that LSINCT5 promoted ovarian cancer cell proliferation, migration, and invasion by disrupting the CXCL12/CXCR4 signaling axis. 13 In bladder cancer, the study performed by Zhu and colleagues uncovered that LSINCT5 activated Wnt/β-catenin signaling by interacting with NCYM to promote cancer progression. 14 Tian and colleagues indicated that LSINCT5 promoted malignancy in non-small cell lung cancer by stabilizing HMGA2. 15 Qi and colleagues demonstrated that E2F1 induced LSINCT5 transcription and promoted cancer progression via epithelial-mesenchymal transition (EMT) in gastric carcinoma. 16 Of interest, the investigation conducted by Dong and colleagues proposed that circulating CUDR, LSINCT5, and PTEN1 lncRNAs in sera distinguished patients with gastric cancer from healthy individuals. 17 However, to date, the expression status and potential involvement of LSINCT5 in EC is still not known. In this research, the authors' aim is to address this subject with both clinical endometrial tumor tissues and cell culture and attempt to understand the underlying molecular mechanism in cancer biology of this disease.

Patient samples
Tissue specimens were obtained from 30 EC patients and from 30 uninvolved controls from August 2016 to March 2018 at the First Affiliated Hospital, Sun Yat-sen University. Normal endometrial tissue specimens were obtained from women who underwent hysterectomy or endometrial curettage for endometrial-unrelated diseases, including uterine myoma or prolapse and the clinicopathologic characteristics are presented in online supplementary Table 1. All donors gave written informed consent for the collection of tissue specimens. This investigation involving human samples was approved by the Ethics Committee of the First Affiliated Hospital, Sun Yat-sen University (#FAHLC078a). The procedure was performed in strict accordance with protocol.

Real-time polymerase chain reaction
The RNA species were extracted from either tissue samples or cell culture with Trizol reagent (Invitrogen, Waltham, MA, USA). The integrity of RNA was quality-checked by agarose electrophoresis. The RNA concentration was determined by Nanodrop 2000 (ThermoFisher, Waltham, MA, USA). cDNA was prepared from each 1 μg RNA with High-Capacity cDNA Reverse Transcription Kit (ThermoFisher) following the provider's recommendation. Quantitative real-time polymerase chain reaction (PCR) was performed with SYBR Green Mater Mix (Bio-Rad, Hercules, CA, USA) and relative expression of the target gene was calculated by 2 -∆∆Ct method. GAPDH was used for internal reference. The primers were provided as follows:

Colony formation assay
Cell growth was inspected using a colony formation assay. In short, 1000 cells (LSINCT5deficient and scramble control) were seeded into 6-well in triplicate and underwent consecutive culture for up to 2 weeks. The culture medium was replaced every 3 days. The resulting colonies were first fixed with 4% paraformaldehyde and stained with 0.25% crystal violet for 15 min. Colonies were counted under light microscope in three random areas.
Cell cycle analysis A single-cell suspension was prepared from both LSINCT5-deficient and proficient Ishikawa and HEC-1A cells [2 × 10 6 cells/ml in ice-cold phosphate-buffered saline (PBS)], which were subsequently fixed with 70% ethanol at 4°C for 12 h. The fixed cells were then stained with 500 μL PI/ Triton X-100 solution (0.02% RNAse, 0.002% PI, 0.1%, Triton X-100) at 37°C for 15 min. Cell clumps were removed by passing-through a cell strainer (BD BioSciences, CA, USA) and data was acquired using BD Accuri Cytometry (BD BioSciences, Franklin Lakes, NJ, USA).

Apoptosis analysis
Apoptotic cells were detected by Annexin V/PI double-staining in both Ishikawa and HEC-1A cell lines in response to LSINCT5 knockdown. The indicated cells were harvested by trypsin digestion and prepared into single-cell suspension in PBS. Annexin V/PI staining was performed simultaneously in the dark, at room temperature for 15 min. BD Accuri Cytometry (BD Biosciences) was used for cell analysis.

Wound-healing assay
Cell migration capacity was evaluated by wound closure rate. Straight lines were drawn in the monolayer cells using sterile tips. Gap closure was continuously monitored and recorded under a light microscope. The assay was performed three times independently.

Statistical analysis
Data was collected from at least three independent repeats. GraphPad Prism 6.0 software was used for data processing and analysis. SPSS 22.0 was used for statistical analysis. One-or two-way ANOVA followed and the Tukey test was used for statistical comparison. Pearson's correlation coefficient (r) was used for correlation analysis.
The p value was calculated and p < 0.05 was considered as significantly different.

Positively correlated and aberrantly overexpressed LSINCT5 and HMGA2 in EC
To investigate the potential involvement of LSINCT5 in EC, the authors' aim was to analyze the relative expression of this lncRNA in clinical samples (n = 30, Table S1). As shown in Figure  1(a) the amount of LSINCT5 in EC tissues were significantly higher than those in adjacent normal controls. Consistent with the previously reported positive-regulation on HMGA2 expression in lung cancer, 15 the authors noticed that HMGA2 protein expression levels were induced in EC in comparison with control, shown in Figure 1(b). Furthermore, correlation analysis demonstrated significant positivity between LSINCT5 and HMGA2 (Figure 1(c)), which implies the mechanistic relevance and potential regulatory relationship between these two genes in EC.

LSINCT5-deficiency compromised cell proliferation in EC cells
The authors' previous data disclosed the aberrant overexpression of LSINCT5 in vivo. Therefore, the authors investigated the potential oncogenic contribution of LSINCT5 to EC in cell culture. To this end, two EC cell lines journals.sagepub.com/home/tam 5 were used to exclude any bias due to cell contexts and specifically knockdown LSINCT5 with siRNAs. Interference efficiencies were experimentally confirmed by qPCR, where more than 70% knockdown was achieved with two independent siRNAs in both Ishikawa and HEC-1A cells (Figure 2(a) and (b)). Cell proliferation was continuously monitored up to 96 h upon LSINCT5 knockdown. The CCK-8 results demonstrated that cell proliferation in LSINCT5-deficient cells was significantly suppressed in both Ishikawa and HEC-1A cells (Figure 3(a) and (b)). Likewise, the colony formation capacity was greatly decreased in  response to the LSINCT5 knockdown ( Figure  3(c) and (d)). The data suggested that high LSINCT5 was critical for the malignant proliferation in EC cells.

LSINCT5-silencing elicited cell cycle arrest and cell apoptosis
In addition to the impact on cell proliferation, the potential influence of LSINCT5 on cell cycle progression and cell apoptosis was evaluated. As shown in Figure 4(a) and (b), the percentage of cells at the G1 phase was increased, accompanied by a decrease in S phase in LSINCT5-silenced EC cells, in comparison with either parental or scramble control. Quantitative results are summarized in Figure 4(c) and (d). The apoptotic percentage was measured using the Annexin V/PI double-staining method. As shown in Figure 4(e) and (f), apoptosis was greatly induced in LSINCT5-deficient cells. Notably, more intensive effects on apoptosis induction were found in si-LSINCT5-2 cells, which was consistent with the higher knockdown efficiency. Quantitative results are presented in Figure 4(g) and (h). Therefore, the data indicates the importance of LSINCT5 in cell cycle progression and apoptosis inhibition in EC.

LSINCT5-deficiency inhibited cell migration and invasion of EC cells
In addition, the possible alterations with respect to cancer metastatic characteristics upon the LSINCT5 knockdown were assessed. Cell migration behaviors were investigated using a woundhealing assay, and the scratch closure rate was continuously monitored for up to 24 h. Representative images and quantitative results were shown in Figure 5(a)-(d). It was noted that cell migration was significantly compromised in LSINCT5-deficient offspring of both cell lines. Similarly, cell invasive capacity, as indicated by the invaded cells into basement membrane, was greatly reduced upon LSINCT5 knockdown as shown in Figure 5(e)-(h). The data uncovered that LSINCT5-deficiency inhibited cell migration and invasion of EC cells.

LSINCT5 inhibited HMGA2 protein degradation
The previous results disclosed the positive correlation between LSINCT5 and HMGA2 and suggested their possibly regulatory effects in EC tissues. This research tries to characterize the relative expression of HMGA2 in response to LSINCT5 knockdown in vitro. As shown in Figure 6(a) and (b), no noticeable difference in HMGA2 transcripts was observed in both Ishikawa and HEC-1A cells upon LSINCT5 knockdown. However, the protein level of HMGA2 was significantly decreased in LSINCT5-depleted cells, in comparison with either parental cells or scramble control as shown in Figure 6(c) and (d), which indicates a posttranscriptional mechanism underlying the LSINCT5-regulated expression of HMGA2 in EC cells. Densitometric quantitation results are shown in Figure 6(e) and (f). The data suggests that LSINCT5 might suppress HMGA2 degradation, which consequently stabilized HMGA2 protein in EC cells.

Wnt/β-catenin signaling was repressed by HMGA2 downregulation upon LSINCT5 knockdown
In addition, this research aims to clarify whether up-regulated HMGA2 by LSINCT5 impacts the Wnt/β-catenin pathway in EC. The relevant protein factors including Wnt3a, p-β-catenin, β-catenin, and c-myc in response to LSINCT5 knockdown were examined. As shown in Figure  7   both western blot and immunohistochemistry results. Except for HMGA2, all other transcripts were notably up-regulated in EC as well based on real-time PCR results, which was unmistakably in support of the conclusion that LSINCT5 regulated HMGA2 at post-transcriptional level via suppressing protein degradation. Therefore, the importance of these signaling cues in EC was highlighted both in vitro and in vivo.

Discussion
Despite the increasing acknowledgment of the critical roles of LSINCT5 in human malignancies, potential involvement of this lncRNA in EC is still unknown. The authors' aim was to characterize the expression status of LSINCT5 and to attempt to understand its oncogenic properties at the molecular level. First, the authors uncovered aberrant overexpression of LSINCT5 in clinical EC patients. siRNA-mediated LSINCT5 knockdown significantly suppressed proliferation, stimulated cell cycle arrest and apoptosis. Furthermore, the authors uncovered that metastasis-related malignant behaviors, such as migration and invasion, were evidently suppressed by LSINCT5 depletion.
In view of the previously described stabilizing effect of LSINCT5 on HMGA2 in lung cancer, 15 here we analyzed the correlation between LSINCT5 and HMGA2 both in vivo and in vitro. The results disclosed a positive relationship between these two genes in clinical endometrial tumor tissues. More importantly, we characterized that HMGA1 transcripts were not subjected to the influence imposed by LSINCT5 knockdown in EC cells. In contrast, the HMGA2 protein was evidently decreased in LSINCT5-deficient cells, which suggested the post-transcriptional manner in regulating HMGA2 expression by LSINCT5. This was consistent with the stimulatory effects of HMGA2 on Wnt/βcatenin activation, 18 and remarkable decreases in key Wnt/β-catenin effectors including Wnt3a, p-βcatenin, and c-myc were observed. While ectopic introduction of HMGA2 in LSINCT5-depleted cells completely rescued the phenotype with respect to activation of Wnt/β-catenin pathway, which critically highlighted the predominant role of HMGA2 in mediating the LSINCT5 signaling transduction. Therefore, this study demonstrated the oncogenic properties of LSINCT5 in EC via stimulating cell proliferation, inhibiting cell cycle arrest and apoptosis, and promoting migration and invasion. The results also demonstrate that LSINCT5 efficiently stabilized HMGA2 protein, which subsequently activated the Wnt/β-catenin pathway and consequently contributed to EC initiation, progression, and metastasis.
HMGA2 belongs to the non-histone chromosomal high mobility group protein family, which usually functions as a structural component and important factor in facilitating enhanceosome formation on a variety of mammalian promoters. 19 HMGA2 was also suggested as a transcriptional modulator involved in cell cycle control via directly targeting CCNA2, therefore playing a critical role in chromosome compaction in the meiotic spermatocytes. 20 Cumulative evidence has implicated the indispensable roles of HMGA2 in a range of human cancers. For example, Summer and colleagues reported that HMGA2 exhibited dRP/AP site cleavage activity and protected cancer cells from DNA-damage-induced cytotoxicity during chemotherapy. 21 Klemke and colleagues suggested that overexpression of HMGA2 in uterus leiomyomas indicated its universal function in the pathogenesis of this disease. 22 The study carried out by Hristov and colleagues demonstrated that HMGA2 protein expression correlated with lymph node metastasis and increased tumor grade in pancreatic ductal adenocarcinoma. 23 Belge and colleagues proposed that up-regulated HMGA2 could serve as a novel molecular marker to distinguish between benign and malignant follicular neoplasia in thyroid carcinomas. 24 Malek and colleagues indicated HMGA2 as a candidate target for ovarian cancer siRNA therapy exploitation. 25 Langelotz and colleagues demonstrated that the expression of HMGA2 mRNA in the peripheral blood as a potential prognostic biomarker for unfavorable survival in metastatic breast cancer. 26 More recently, Tian and colleagues discovered a key role of HMGA2 in non-small cell lung cancer, which was complexed with and stabilized by lncRNA LSINCT5. 15 Consistent with the oncogenic properties of HMGA2, in this research the authors demonstrated that aberrant overexpression of LSINCT5 in EC led to stabilized HMGA2 protein, which consequently contributed to LSINCT5 pro-tumoral activity. Ectopic introduction of HMGA2 in LSINCT5-negative EC cells was sufficient to activate oncogenic signaling, which underlined the predominant role of HMGA2 in oncogenesis and progression of EC.
The Wnt signaling pathway plays a fundamental role in embryonic development and specifically programmed body axis patterning, cell fate specification, cell proliferation, and migration. Dysregulation in Wnt/β-catenin pathway has been characterized in a wide range of human cancers. 27 For example, Wnt1 was first identified as a protooncogene in a breast cancer mouse model. 28 Increased nuclear presence of β-catenin was reported to correlate with poor prognosis in breast cancer patients. 29 Changes in the β-catenincoding gene CTNNB1 was measured in breast, colorectal, melanoma, prostate, lung, and other cancers. The crucial involvement of HMGA2 in Wnt/β-catenin pathway has been uncovered by multiple investigations. Singh and colleagues reported that HMGA2 was required for canonical Wnt signaling during lung development. 18 Zha and colleagues demonstrated that HMGA2 elicited EMT process through activating the Wnt/βcatenin signaling in gastric cancer. 30 Cui and colleagues suggested that miR-337 regulated the PI3K/AKT and Wnt/β-catenin signaling pathways to inhibit hepatocellular carcinoma progression by targeting HMGA2. 31 In support of the theory that HMGA2 positively modulated Wnt/β-catenin, in this research the authors provide evidence that introducing HMGA2 in LSINCT5-deficient cells significantly restored Wnt/β-catenin activation. Of interest, the molecular mechanisms underlying the stabilizing effect of LSINCT5 on HMGA2 protein in EC still have to be defined. In addition, the mode-of-action of LSINCT5-HMGA2-Wnt/βcatenin unraveled in the in vitro study required further confirmation in vivo.

Conclusion
In summary, this data characterizes aberrant overexpression of LSINCT5 in EC, which exerts its oncogenic function via stimulating cell proliferation, promoting cell cycle, inhibiting cell apoptosis, inducing cell migration, and invasion. The authors have further uncovered the predominant role of HMGA2 downstream of LSINCT5 signaling transduction, which consequently contributes to the oncogenic properties of LSINCT5. This study has highlighted the fundamental role of LSINCT5-HMGA2-Wnt/β-catenin in EC, which may hold significant potential for diagnostic and therapeutic exploitation.

Funding
This research received no specific grant from any funding agency in the public, commercial, or notfor-profit sectors.