Ganoderma is well known for its use in traditional Chinese medicine and is widely cultivated in China, Korea, and Japan. Increased temperatures associated with global warming are negatively influencing the growth and development of Ganoderma. Nitric oxide is reported to play an important role in alleviating fungal heat stress (HS). However, the transcriptional profiling of Ganoderma oregonense in response to HS, as well as the transcriptional response regulated by NO to cope with HS has not been reported. We used RNA-Seq technology to generate large-scale transcriptome data from G. oregonense mycelia subjected to HS (32 °C) and exposed to concentrations of exogenous NO. The results showed that heat shock proteins (HSPs), “probable stress-induced proteins”, and unigenes involved in “D-amino-acid oxidase activity” and “oxidoreductase activity” were significantly up-regulated in G. oregonense subjected to HS (P < 0.05). The significantly up-regulated HSPs, “monooxygenases”, “alcohol dehydrogenase”, and “FAD/NAD(P)-binding domain-containing proteins” (P < 0.05) regulated by exogenous NO may play important roles in the enhanced HS tolerance of G. oregonense. These results provide insights into the transcriptional response of G. oregonense to HS and the mechanism by which NO enhances the HS tolerance of fungi at the gene expression level. Ganoderma spp. is a group of white rot fungus belonging to the Ganodermataceae, Polyporales3. The medicinal effects of the Ganoderma complex have been intensively studied. Triterpenes, polysaccharide peptides, polysaccharides, ganoderic acids, and ribonucleases isolated from the fruiting bodies and fermentation of Ganoderma spp. exhibit antioxidant, antiallergic, antiinflammatory, antifungal, antitumor, immunostimulatory, and mitogenic activities12. As a species of G. lucidum complex, G. oregonense was first discovered in North America1. And this species was successfully introduced from the United States through cooperation and cultivated in southwestern China, which supported by a Ganoderma sp. breeding project. This species is associated with good agronomic traits, including a high biological conversion rate, a large cap, and high yield. It has the potential for further cultivation in both China and other parts of the world. Investigating the response of this species to stress should provide information for the successful cultivation of G. oregonense as well as other Ganoderma species under conditions of abiotic stress.Saccharomyces cerevisiae and fatty acid synthesis of Candida albicans were seriously affected by HS15. HS is one of the important environmental factors negatively affecting the growth and development of edible fungi16. The pileus diameter and biomass of the Agaricus bisporus fruiting body was severely reduced after several days of exposure to high temperatures17. HS can also induce apoptotic-like cell death in Pleurotus species and inhibit mycelium growth, impair fruiting, and affect mushroom quality18. To cope with HS, several physiological changes, such as the production of DNA methyltransferases, DNA-binding proteins, compatible solute accumulation, expression of heat shock proteins (HSPs), activation of reactive oxygen species (ROS) scavenging enzymes, and alterations in morphology induced by microorganisms play important roles in the heat stress response (HSR)21. Transcriptome or gene expression profiles reveal that some genes related to biological regulation, cellular processes, and metabolic processes are involved in HSR22. The yields of some secondary metabolites, such as ganoderic acids (GA) and triterpenes, were increased in Ganoderma sp. under HS, which indicates that Ganoderma sp. can be used as a model system for evaluating how environmental factors regulate the development and secondary metabolism of basidiomycetes24. However, the transcriptional profiles and genes related to the response of G. oregonense to HS are not yet known.Organisms are affected by environmental changes, and excessively high temperatures constitute a significant environmental challenge. Microorganisms are directly exposed to the temperature alterations associated with climate change since they cannot move to avoid high temperature stress. Heat stress (HS) is often reported to affect the physiological processes and growth of microorganisms. The survival rate of 25. NO regulates the morphogenesis, sporulation, spore germination, cellular development, apoptosis, and reproduction of fungi. NO also plays an important role in the fungal response to abiotic stress27. Kong et al. reported that NO could alleviate heat stress through the regulation of trehalose accumulation and reactive oxygen species (ROS)-scavenging enzymes in Pleurotus eryngii28. The tolerance of Ganoderma lucidum to cadmium was also enhanced by NO29. However, the transcriptional response of fungi to the abiotic stress regulated by NO, especially to heat stress, is still unknown. Since well-grown hyphae constitute the basis for successful cultivation, and the associated conditions are easier to control in the laboratory, we therefore selected to use the hyphae to investigate the NO-regulated response to heat stress. In this study, we used high-throughput RNA-Seq technology to study the transcriptional responses of G. oregonense to heat stress and the mechanism by which NO enhances fungal resistance to HS at the gene expression level. The effect of exogenous NO on hyphal gene expression under non-stress conditions was also assessed. This is the first report on the transcriptional profiling of G. oregonense in response to heat stress, as well as the transcriptional responses regulated by NO to cope with abiotic stress. This research illustrates the role of NO in enhancing fungal resistance to abiotic stress at the gene expression level and provides a potential application for the cultivation of fungi under abiotic stress.Nitric oxide (NO) is a simple, small gas molecule that can easily diffuse through cell membranes. It plays an important role in the growth and development of organismsG. oregonense treated at 28 °C was the highest among all treatments  occurred at 32 °C with K4 [Fe(CN)6], which was similar to treatment at 32 °C alone. Mycelia treated at 32 °C revealed the transcriptional responses of G. oregonense to heat stress. Samples treated at 32 °C with 100 µM nitric oxide donor revealed the mechanism by which NO enhances fungal tolerance to abiotic stress. The mycelia treated at 28 °C were assigned to CK, the mycelia treated at 32 °C were assigned to HT, the mycelia treated at 28 °C with 100 µM SNP were assigned to CKSNP, and the mycelia treated at 32 °C with 100 µM SNP were assigned to HTSNP.The biomass of nts Fig. . It was G. oregonense to heat stress and the mechanism of NO–induced enhancement of fungal resistance to abiotic stress, G. oregonense mycelia treated at 28 °C, 32 °C, and at 28 °C or 32 °C with an NO donor (100 µM SNP) were subjected to RNA-Seq analysis on the Illumina HiSeq 2000 platform. A total of 3.70 × 108 clean reads from 3.74 × 108 raw reads, and 5.43 × 1010 clean bases from 5.62 × 1010 raw bases were generated , Batrachochytrium dendrobatidis JAM81 (2.63%), Ceriporiopsis subvermispora B(1.22%), and Fibroporia radiculosa (1.11%). However, 23.52% of the unigenes did not show significant similarity with any other proteins in the Nr database.The entire set of unigenes was annotated in five frequently used databases, including the NCBI non-redundant (Nr) protein, the evolutionary genealogy of genes: Non-supervised Orthologous Groups (eggNOG), the SwissProt protein database (SwissProt), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and the Gene Ontology (GO) database. The identity and species distributions were analyzed Fig. . A totalSS1 Fig. . AdditioG. oregonense transcripts were classified with GO assignments based on the Nr annotation . Within these unigenes, 1,189 were assigned to metabolism processes in the KEGG database. The pathways containing the most unigenes were involved in “carbohydrate metabolism” (192 unigenes) and “amino acid metabolism” (175 unigenes). In addition, 760 unigenes involved in “translation” (347 unigenes) and “folding, sorting and degradation signal transduction” (203 unigenes) were assigned to the genetic information processing pathway. A total of 374 unigenes were sorted into the organismal systems pathway, containing “endocrine system” (88 unigenes), “nervous system” (69 unigenes), and others. A total of 356 unigenes were classified into cellular processes pathways, including “transport and catabolism” (183 unigenes), “cell growth and death” (115 unigenes), and others. A total of 191 unigenes were involved in the environmental information processing pathway, including “signal transduction” (184 unigenes) and “membrane transport” (seven unigenes). The KEGG pathway annotations provided a valuable resource for investigating the specific processes, functions, and pathways involved in the response of G. oregonense to heat stress regulated by NO.To further elucidate the biological functions and gene interactions of G. oregonense to heat stress (32 °C) and the NO-induced gene expression profiles regulating fungal tolerance to abiotic stress. The DEGs among the G. oregonense mycelia treated at 28 °C (CK), 32 °C (HT), 28 °C with 100 µM SNP (CKSNP), and 32 °C with 100 µM SNP (HTSNP) were mapped back onto the unigenes respectively , including 197 unigenes up-regulated in HT and 287 in CK. Among the up-regulated genes in HT, HSP genes occupied the largest proportion. A total of eight HSP genes were significantly up-regulated in HT (P < 0.05), including two HSP HSS1 genes, two HSP sti1 homologs, two small HSPs, one HSP 16 gene, and one HSP 90 gene (Table P < 0.05). Unigenes related to “FAD/NAD(P)-binding domain-containing protein”, “elongation factor 1-gamma”, and “Tom7-domain-containing protein” were significantly down-regulated in HT (P < 0.05)  Table .Table 1DP < 0.05)  Table . No DEGsP < 0.05) in HT (Table P < 0.05). In the category of metabolism, more DEGs were involved in “glycosphingolipid biosynthesis”, “glycosaminoglycan degradation”, “amino sugar and nucleotide sugar metabolism”, and “styrene degradation” in CK (P < 0.05). No DEGs were significantly enriched in the category of environmental information processing and cellular processes, indicating that the two KEGG pathways had no significant effect on the transcriptional response of G. oregonense to heat stress.The regulatory and metabolic pathways relating to the identified unigenes were analyzed using KEGG pathway analysis Fig. . The resHT Table . OrganisG. oregonense mycelia treated at 32 °C (HT) and mycelia treated at 32 °C with 100 µM SNP (HTSNP), a total of 824 unigenes were significantly differentially expressed between HT and HTSNP (P < 0.05), including 375 up-regulated and 449 down-regulated unigenes in G. oregonense mycelia treated at 32 °C with 100 µM SNP (HTSNP). In addition to the up-regulated HSP genes in HT compared with CK, many new HSPs were observed the be significantly up-regulated in HTSNP regulated by NO compared with HT (P < 0.05), including four unigenes for HSP 78, three HSP 70 genes, two genes for HSP 104, one gene for HSP 30, and one for small HSP C4 (Table P < 0.05)  Table .P < 0.05) in the category of molecular function  . In the category of organismal systems, more DEGs were involved in “longevity regulating pathway – worm” and “longevity regulating pathway - multiple species” in HTSNP (P < 0.05). No DEGs were significantly enriched in the category of environmental information processing and genetic information processing, indicating that these two KEGG pathways had no significant effect on the transcriptional response induced by NO on the regulation of G. oregonense tolerance to heat stress.KEGG pathway analysis showed that the pathways involved in “apoptosis – fly” and “apoptosis - multiple species” were significantly enriched in HTSNP in the term of cellular processes (05) Fig.  (Table S05) Fig. . MetabolP < 0.05), including 2,837 unigenes up-regulated and 1,053 down-regulated unigenes in G. oregonense mycelia treated at 28 °C with 100 µM SNP (CKSNP). Unigenes related to “NAD-dependent formate dehydrogenase”, “raffinose synthase”, “translation elongation factor”, and “carbohydrate-binding module family 20 protein”, were significantly up-regulated in CKSNP compared with CK (Table P < 0.05)  Table .P < 0.05) in the category of cellular component and molecular function (Table P < 0.05)  Table . The resTo validate gene expression profiles obtained by transcriptome analysis, real-time PCR (RT-PCR) was used to confirm the expression levels of nine selected unigenes, with RPL4 serving as the reference gene Tables  and S9. Ganoderma is an important medicinal fungus with many biological activities, and is also a model macrofungus for studying secondary metabolite synthesis and the abiotic stress response. It has attracted considerable attention in recent years31. However, the transcriptional responses of G. oregonense to heat stress and the transcriptional responses induced by NO resulting in enhanced tolerance to heat stress have not been clarified. Without reference genome, we tried to map the mRNA sequences of this species to the reference genomes of G. lucidum in NCBI database. However, the maping rate only reached 61–73%, which indicated that there are great variation in gene content between this strain and G. lucidum. The de novo assembled transcriptome of G. oregonense SLZ72 revealed that the GC content of G. oregonense unigenes was approximately 58.08%, which was higher than in the genomes of Phellinus linteus (51.49%)32, Amanita exitialis (51.58%)33, Lentinula edodes (48.3%)34, Pleurotus ostreatus genome (50.9%)35, G. lucidum G.260125-1 (56.10%)36, G. lucidum Xiangnong No.1 (55.30%)37, and G. lucidum BCRC 37177 (55.50%)38. However, its GC content was lower than Auricularia polytricha (61.3%)39. Since there is no reference genome for assembly, the transcripts of G. oregonense had to be de novo assembled. The GC content of G. oregonense calculated from unigenes of G. oregonense should provide a future reference for studying the genetic information of G. oregonense, as well as for future studies of its genome and transcriptome. The approximate transcriptome coverage of G. oregonense SLZ72 was estimated. The genome sizes of the allied species G. lucidum and G. boninense ranged from 39.95–60.33 Mb. The 37.8 Gb of the transcriptome sequence data likely represented 627- to 947-fold coverage of the G. oregonense SLZ72 genome. Therefore, a large set of G. oregonense SLZ72 unigenes can provide adequate information for additional gene investigation.40. Ganoderma oregonense is commercially grown in Asia and its yield and quality are reduced by heat stress. It has been reported that the cellular damage induced by HS is mainly due to the excessive accumulation of ROS and lipid peroxidation (LPO) products41. As high levels of ROS can result in cytotoxicity, fungi have evolved different strategies for coping with the negative impacts of ROS in response to environmental stress43. The expression of HSPs can play an important role in fungal resistance to HS40. So far, the transcriptional response of G. oregonense to HS remains unknown, which provides a theoretical basis for elucidating the response of G. oregonense to high temperature damage. When G. oregonense was subjected to HS (32 °C), its biomass was significantly affected, and 197 unigenes were significantly up-regulated (P < 0.05) in the mycelia, including several HSP genes, “P-loop containing nucleoside triphosphate hydrolase protein gene”, “vacuolar amino acid transporter gene”, “nucleotide exchange factors-like protein gene”, and “probable stress-induced protein gene”, indicating that these genes played important roles in HS responses. HSPs are a family of proteins found from bacteria to humans and are produced by cells in response to stressful conditions46. In G. oregonense they were significantly up-regulated when exposed to HS. Zhang et al.40 found that heat stress modulated the HSP expression of G. lucidum via cytosolic Ca2+, and this provided additional evidence of the importance of HSPs in the fungal response to HS.Increased temperatures associated with global warming have become a major factor affecting the growth of cultivated fungiG. oregonense mycelia (P < 0.05) subjected to HS, which showed that in G. oregonense, enhanced energy metabolism and protein processing occurred in response to adverse conditions. Streptococcus mutans also responded to HS by modulating energy metabolism with differentially expressed HSP genes22. Other unigenes, such as “vacuolar amino acid transporter gene”, “nucleotide exchange factors-like protein gene”, and “probable stress-induced protein gene” also played important roles in the response of G. oregonense to abiotic stress, providing references for the study of the responses of other fungi to abiotic stresses.GO functional enrichment analysis and KEGG pathway analysis showed that the DEGs involved in “oxidoreductase activity”, “NOD-like receptor signaling pathway”, “antigen processing and presentation”, and “protein processing in endoplasmic reticulum” were significantly enriched in G. oregonense mycelia subjected to HS increased. This increase was significant at the concentration of 100 µM SNP, which indicated that NO can enhance the tolerance of G. oregonense to HS. This result is consistent with many previous studies28. Yu reported that NO can enhance the activity of NOS and NR to reduce oxidative damage and protect the mycelia of T. harzianum from HS47. The mechanism of NO enhancement of the response of G. oregonense to HS has been revealed by RNA-Seq analysis. Unlike non-stress conditions, under which NO mainly regulates the structural constituents of the ribosomes or structural molecule activity, under heat stress a series of genes were activated and some novel HSPs of G. oregonense mycelia were significantly up-regulated in HTSNP regulated by NO compared to HT (P < 0.05) in order to adapt to the adverse environment. These up-regulated HSPs included HSP 78, HSP 70, HSP 104, HSP 30, and the small HSP C4, indicating that NO activated HSPs to protect G. oregonense against abiotic stress. HSPs of various molecular weights were activated together, aiding in protein–protein interactions, protein maintenance, and transportation of proteins across membranes within the cell51, resulting in a reduction in heat damage. Other unigenes related to “NAD(P)-binding protein”, “monooxygenase”, “alcohol dehydrogenase”, “FAD/NAD(P)-binding domain-containing protein”, “Zinc-type alcohol dehydrogenase-like protein”, “putative GTP-binding protein”, and “NAD(P)-binding protein” were also significantly up-regulated in HTSNP compared with HT. The oxidative damage induced by HS is one of the main factors inhibiting mycelial growth and causing cell death24. Monooxygenases are enzymes that scavenge ROS in organisms by the concomitant oxidation of NAD(P)H52. Alcohol dehydrogenases catalyze the opposite reaction as part of fermentation to ensure a constant supply of NAD+ in bacteria, yeast, and plants54. The co-expression of these genes could alleviate oxidative damage to G. oregonense and increase growth biomass.When treated with exogenous NO, the biomass of 57. Our results showed NO regulated protein processing in organisms responding to abiotic stress. Moreover, “apoptosis – fly”, “apoptosis - multiple species”, “longevity regulating pathway – worm”, and “longevity regulating pathway - multiple species” were found to be over-expressed in HTSNP based on KEGG pathway analysis. Heat-induced, apoptosis-like cell death was also observed in Pleurotus species subjected to HS18. Many substances are involved in NO-mediated responses to abiotic stress, including trehalose accumulation and reactive oxygen scavenging enzymes58. This is the first study of the gene expression of G. oregonense simultaneously exposed to NO and abiotic stress. Our results can be applied to similar studies on other fungal studies. Further research is needed to reveal the mechanism by which NO allows other fungi to tolerate abiotic stresses and their transcriptional regulation mechanisms. This will provide a basis for the improved cultivation and molecular breeding of macrofungi.GO functional enrichment analysis indicated that the DEGs involved in “misfolded protein binding”, “protein unfolding”, “posttranslational protein targeting to membrane, translocation”, “protein refolding”, and “diacylglycerol O-acyltransferase activity” occupied the largest proportion of the total. The unfolded protein response (UPR), mostly enriched in GO functional analysis, was reported to be a cellular stress response related to the endoplasmic reticulum (ER), which has been found to be conserved in all mammalian species, as well as in yeast and wormsG. oregonense SLZ72 was introduced by an expert from the United States through cooperation and successfully cultivated in southwestern China. G. oregonense mycelia were obtained from cultivated strain and identified by the authors based on morphology  and molecular analysis (GenBank accession numbers KY781351 and KY781352). The species is now preserved in the collection center of Institute of plant protection, Sichuan Academy of Agricultural Sciences (specimen: SLZ72). Two rounds of experiments were performed. The first aimed to assess the effect of heat stress on growth rate in order to evaluate the temperature at which the species began to show evidence of heat stress. From these preliminary tests, mycelia were selected for the “heat treated” group for further testing the transcriptional response of G. oregonense to heat stress, as well as assessing the mechanism by which NO enhances heat stress tolerance of fungi at the gene expression level. The obtained mycelia were first incubated in potato dextrose agar medium (PDA) at 28 °C for 6 d, and then 10 pieces (a 5 mm diameter punch) of the mycelia from the solid medium were transferred to 200 mL liquid potato dextrose medium (LPD) in a 500 mL flask. The cultures were incubated with shaking at 110 rmp and 24 °C, 26 °C, 28 °C, 30 °C, 32 °C, and 34 °C for 6 d respectively, and fresh mycelial biomass was tested. In the preliminary heat treatment experiments, mycelia were subjected to heat stress at 32 °C and different concentrations  of SNP  were then added to heat-stressed mycelia, which were incubated at 110 rpm and harvested after 6 d for fresh weight (FW) determination. Potassium ferrocyanide (K4[Fe(CN)6]), an analog of SNP which does not release NO, was applied as a negative control of SNP29. SNP and K4[Fe(CN)6] were directly added into the flasks after filter sterilization. Each treatment was replicated in triplicate under the same experimental conditions. The mycelia were harvested after 6 d for RNA extraction and transcriptome sequencing.59. To select cDNA fragments of the preferred 200~300 bp length, the library fragments were purified with the AMPure XP system . After adenylation of the 3’ ends of the DNA fragments, NEBNext adaptors, with hairpin loop structures, were ligated to prepare them for hybridization. Then 3 μL USER Enzyme  was used with size-selected, adaptor-ligated cDNA at 37 °C for 15 min followed by 5 min at 95 °C prior to PCR. PCR was performed with Phusion High-Fidelity DNA polymerase, Universal PCR primers, and Index (X) Primer. PCR products were purified (AMPure XP system) and library quality was assessed on an Agilent Bioanalyzer 2100 system. The library was sequenced with the Illumina HiSeq™ 2000. The entire process was commissioned and completed by the Shanghai Personal Biotechnology Co.RNA was prepared using the Qiagen RNeasy Mini Kit  with DNAase treatment according to manufacturer’s instructions. The quality and quantity of extracted RNA were assessed using 1% agarose gels and an Agilent 2100 Bioanalyzer . RNA with a RIN value greater than 9.0 was used for transcriptome library production. RNA sequencing libraries were generated using the TruSeq RNA Sample Preparation Kit  according to instructions. Briefly, the mRNA was purified from total RNA using poly-T oligo-attached magnetic beads and short fragments were obtained under elevated temperature by adding an Illumina proprietary fragmentation buffer. First strand cDNA was synthesized using random hexamer primer and M-MuLV Reverse Transcriptase (RNase H-). Second strand cDNA synthesis was performed using DNA Polymerase I and RNase H. Remaining overhangs were converted into blunt ends via exonuclease/polymerase60. Gene functions were annotated based on the following databases: Nr (NCBI non-redundant protein sequences); eggNOG (Non-supervised Orthologous Groups); Swiss-Prot ; GO (Gene Ontology) and KEGG (the Kyoto Encyclopedia of Genes and Genomes).Raw data (raw reads) of fastq format were first processed through in-house perl scripts. In this step, clean data (clean reads) were obtained by removing reads containing adapters, reads containing poly-Ns, and low quality reads from the raw data. At the same time, Q20, Q30, GC-content, and the sequence duplication level of the clean data were calculated. All downstream analyses were based on clean data with high quality. The left files (read1 files) from all libraries/samples were pooled into one large left.fq file, and right files (read2 files) into one large right.fq file. Transcriptome assembly was accomplished based on the left.fq and right.fq using Trinity with min_kmer_cov set to 2 by default and all other parameters set to default61. Read counts for each gene were obtained from the mapping results. Differential expression analysis of two conditions/groups was performed using the DESeq R package (1.10.1). DESeq provides statistical routines for determining differential expression in digital gene expression data using a model based on the negative binomial distribution. The resulting P-values were adjusted using the Benjamini and Hochberg approach for controlling the false discovery rate. Genes with an adjusted P-values < 0.05 found by DESeq were designated as differentially expressed.Gene expression levels for each sample were estimated by RSEM and clean data were mapped back onto the assembled transcriptome62. KEGG is a database resource for elucidating high-level functions and utilities of the biological system63, such as the cell, the organism, and the ecosystem. KEGG is used with molecular-level information, especially large-scale molecular datasets generated by genome sequencing and other high-throughput experimental technologies (http://www.genome.jp/kegg/). We used KOBAS software to test the statistical enrichment of differential expression genes in KEGG pathways64.GO enrichment analysis of the DEGs was accomplished using the GOseq R package-based Wallenius non-central hyper-geometric distribution, which adjusts for gene length bias in DEGs65. The expression of each gene was confirmed by at least three rounds of independent RT-PCR reactions. Relative quantification of target gene expression was evaluated using the comparative cycle threshold (CT) method as previously described by Livak & Schmittgen66. The ΔCT value was determined by subtracting the target CT of each sample from its respective RPL4 CT value. Differences in expression of the target genes were determined by 2−ΔΔCT. Data were expressed as arithmetic means ± SD. Comparisons between different samples were performed using Student’s t-tests and a P-value less than 0.05 was considered as statistically significant.The expression of nine unigenes identified by RNA-Seq was validated using real time PCR (RT-qPCR) analysis. Briefly, about 3 mg of total RNA of each sample was reverse-transcribed using Super RT Kit (TaKaRa) according to manufacturer’s instructions. The gene-specific primers were designed based on the unigene sequences. RPL4 primers were used as endogenous loading controls for testing the validity of template preparationP < 0.05.Data of this study are presented as means ± SD of three replicates for each treatment. Statistical analysis was carried out by one-way analysis of variance (ANOVA) using SPSS 19.0. Least significant difference (LSD) was performed to test if the ANOVA result between different treated groups was significant at All the raw sequence data is stored in The Sequence Read Archive (SRA) database (accession number: SRR5274645- SRR5274653).Supplementary figures 1-2 and tables 1–9


Scientific Reports 10.1038/s41598-018-21067-9, published online 08 February 2018Correction to: The original version of this Article contained an error in the title, where,“REM sleep respiratory behaviours mental content in narcoleptic lucid dreamers”.now reads:“REM sleep respiratory behaviours match mental content in narcoleptic lucid dreamers”.In addition, the Discussion section contained an error, where,36”“For example, among 6 healthy lucid dreamers, who had been trained in lucid dreaming for several years, only one subject was able to perform the requested task and the ocular code after 3 full nights in a fMRInow reads:36.”“For example, among 6 healthy lucid dreamers, who had been trained in lucid dreaming for several years, only one subject was able to perform the requested task and the ocular code after 3 full nights in an fMRI scannerThese errors have now been corrected in the HTML and PDF versions of this Article.


This study aimed to determine the effects of methanolic red maca extract and its n-butanol and aqueous fractions on expression of androgen and oestrogen receptors in rats with testosterone enanthate-induced BPH. Thirty-six rats in six groups were studied. Control group received 2 mL of vehicle orally and 0.1 mL of propylene glycol intramuscularly. The second group received vehicle orally and testosterone enanthate (TE) (25 mg/0.1 mL) intramuscularly in days 1 and 7. The other four groups were BPH-induced with TE and received, during 21 days, 3.78 mg/mL of finasteride, 18.3 mg/mL methanol extract of red maca, 2 mg/mL of n-butanol fraction, or 16.3 mg/mL of aqueous fraction from red maca. Treatments with red maca extract and its n-butanol but not aqueous fraction reduced prostate weight similar to finasteride. All maca treated groups restored the expression of ERβ, but only the aqueous fraction increased androgen receptors and ERα. In conclusion, butanol fraction of red maca reduced prostate size in BPH by restoring expression of ERβ without affecting androgen receptors and ERα. This effect was not observed with aqueous fraction of methanolic extract of red maca.Benign Prostatic Hyperplasia (BPH) affects, worldwide, 50% of 60-year-old men. The Peruvian plant red maca Benign Prostatic Hyperplasia (BPH) is a disease of high relevance since, worldwide, it affects 50% of men aged 60-year-old , reachinThe etiology is still unclear, but it is largely accepted that sex hormones are fundamental. Androgen receptor (AR) has received special attention, due to its effects on prostate growth signaling pathways; for instance, androgens promote the expression of Epidermal Growth Factor, Keratinocyte Growth Factor, and Insulin-like Growth Factor , 4.α and β  are less studied than AR, it is evident that they also play a significant role on normal prostate growth [α activation is related to the inflammatory and proliferative response whereas ERβ activation has an antiproliferative and proapoptotic response, counteracting AR and ERα effects.Although oestrogens and their receptors e growth , 6. ERα Nowadays, treatments for BPH include finasteride, tamsulosin or, in severe cases, transurethral resection of the prostate. Although they ameliorate LUTS symptoms and, in case of finasteride, decrease prostatic volume, they are not exempt of side effects like hematuria, loss of sexual desire, abnormal ejaculation, among others . Evident Lepidium meyenii), as a useful agent against BPH by reducing prostate size in rats with testosterone enanthate- (TE-) induced BPH without affecting seminal vesicles, being better when compared with finasteride treatment [A particular outcome of this interest was the discovering of a Peruvian plant, red maca  were acquired from the Universidad Peruana Cayetano Heredia Animal House. The rats had an initial body weight of 300 ± 1.49 g (mean ± SEM). They were allocated in animal cages in a rate of 6 rats per cage. The rats were kept at 25°C with periods of light/darkness of 12 hours inside the experimental room. They received food and water ad libitum.Thirty-six three-month-old Holtzman strain male ratsAnimals were maintained and managed according to the United States National Institute of Health “Guide for the Care and Use of Laboratory Animals” .This is an experimental study with a follow-up of 3 weeks in which rats received two doses of testosterone enanthate to induce BPH, and then they were treated with vehicle, finasteride, RM methanolic extract, or its fractions (aqueous or n-butanol) during 21 days. All treatments were daily administered by oral inoculation.n = 36). Group 1 was control in which water was inoculated as vehicle (VH) of RM methanolic extract (RM) and propylene glycol (inert oil) was intramuscularly injected. Except for Group 1, all groups received two intramuscular injections of testosterone enanthate  at day 1 and at day 7 of treatment, resulting in a total of 50 mg of TE for each rat. Group 2 (TE) was treated with water by gavage needle with vehicle only. Group 3 (TE + F) was treated with 0.6 mg/kg of finasteride. Group 4 (TE + MetOH) received 36.1 mg of methanolic RM extract; the fifth group (TE + ButOH) was treated with a daily dose of 4.0 mg of butanol fraction, and the last group (TE + Aq) was treated with a daily dose of 32.5 mg of the aqueous fraction. At day 22, prostate glands were surgically removed and their weight was evaluated.The study included six groups of six rats each  by intraperitoneal injection. After that the rats were disposed in the cages until cardiac pulse and respiration rhythm stopped.μm thickness. Half of the sections obtained were stained with Hematoxylin and eosin. Slides were observed with a compound microscope (Leica DM1000).One of the two lobes of the ventral prostate was fixed in formaldehyde for three days and then in ethanol 75%. The organs were paraffin-embedded. Paraffin blocks were cut with a microtome at 6 α (sc-787), and goat anti-ERβ (sc-6821) . In a 1 : 50 dilution, primary antibody was incubated overnight at 4°C. Prior to primary antibody incubation, slides were soaked in Citrate buffer  at 100°C for 40 minutes to retrieve the antigen. Endogenous peroxidase deactivation was done by submerging the slides in peroxide 30%/methanol solution (1 : 5).The other half was used for IHC staining with anti-AR (sc-816), mouse anti-ERThe secondary antibody recognition and staining was performed with Histostain-Plus IHC Kit, HRP, broad spectrum® . To assess the expression of the different receptors, a ratio within positive nuclei/total nuclei was elaborated. Nuclei visualization and count was performed with a compound microscope (Leica DM1000). Four visual fields per slide were assessed and three slides per animal (prostate lobe) were evaluated.Whole organ tissue was mechanically lysed with TissueTearor® (Biospec Products). The homogenized prostate was resuspended in RIPA buffer  and centrifuged at 10000 RPM for 15 minutes at 4°C.μg of total protein from each sample was resuspended in loading buffer  and heated for 10 minutes at 60°C. Afterwards, a SDS-PAGE was performed in 10% and 15% gels. Proteins were blotted with TRANS-BLOT® SD SemiDry Transfer Cell (BioRad) into a nitrocellulose membrane. Membranes were blocked overnight with 10% skimmed milk at 4°C. All washes were done with TTBS buffer.Total proteins were quantified with Bradford assay method. Samples were stored at −80°C until use. Thirty α 1/10000, and anti-ERβ 1/5000); for normalization, anti-β-actin antibody was used . Primary antibody incubation had a length of 2 hours, following 1 hour of secondary antibody incubation  each at room temperature. Target proteins were detected by chemiluminescence in a radiographic film. Optical density quantification was performed using Image J software (http://rsb.info.nih.gov/ij/).Corresponding primary antibody was diluted in TTBS buffer , to distinguish which groups were different, Scheffé's test was applied. If data have not normal distribution, nonparametric test Kruskal-Wallis was used and post hoc Dunn test.The statistics software STATA 12.0  package was used. Variance homogeneity was evaluated by Bartlett's test and data normal distribution by Shapiro-Wilk test. If the variables were homogeneous, differences between groups were assessed by ANOVA test. If p < 0.05). Prostate weight in TE + F, TE + MetOH, and TE + ButOH showed similar values compared to VH group . Surprisingly, TE + Aq group prostate weight (927.03 ± 46.48 mg) was not different compared to TE (p > 0.05)  had a greater prostate weight compared to VH ( > 0.05) .As observed in a previous study , in the p < 0.05) and with respect to the other treatments (p < 0.05) (p < 0.05), but similar stroma area  ; the othoma area .β nuclear expression is notoriously greater , while for ERα it is similar compared to VH and the rest of groups (p > 0.05), except for TE + Aq, which exhibit an overexpression of AR and ERα (p < 0.05), while for ERβ it shows similar ratio compared to TE group (p > 0.05).Ratio values indicate that the expression of AR and ERβ levels; notwithstanding TE + MetOH extract of RM showed a greater ERβ expression levels (p < 0.05) as seen in RM methanolic extract and its n-butanol fraction restore the expression of AR. There is a similar trend in the case of the n-butanol fraction to equate ERα  in the group treated with aqueous fraction of red maca and a greater ERβ expression  in TE + MetOH group. Surprisingly, the aqueous fraction treatment displayed a restoring effect in a similar fashion as n-butanol fraction treatment on ERβ expression, becoming similar to that observed in the VH group (p > 0.05) as shown in At a protein level, similar results were obtained compared to IHC assays, showing an increase of AR and ERα, and ERβ) genetic expression. These approaches will allow comprehending the action mechanism that red maca uses to reverse BPH and also contributing to decipher the long-unknown and unclear etiology of BPH despite of scientific community efforts.The present study aimed to assess the biological effects of red maca methanolic extract and its n-butanol  and aqueous fractions on testosterone enanthate-induced BPH in rats determined by prostate gland weight, histological evaluation , and the three main hormone receptors  contributes significantly to the development of the disease. This factor and the inflammatory one are not acting alone, but synergically.α, and ERβ expression due to testosterone propionate intramuscular injections and castration in a rat model; nonetheless, their results are not similar to each other and also different from ours.One way to assess the contribution of the different hormonal receptors in the development of the disease is by evaluating their genetic expression. Two recent studies , 29 haveβ expression levels decrease in the BPH model, while ERα levels are maintained similar to those in non-BPH rats (VH group). At a protein level, by western blot analysis, all receptors are significantly diminished in the TE group compared to VH. These different outcomes might be due to the experimental models used. In our case, only two intramuscular injections of testosterone enanthate were enough and no castration was needed, so the hypothalamic-hypophyseal-gonadal axis is maintained. Two doses of TE in days 1 and 7 are enough to induce BPH as previously reported, lasting even at day 56 without more injections since day 7 [Our data shows that, at tissue level, AR and ERce day 7 , 12, 30,α-reductase and hence an accumulation of DHT, leading to a deregulation in proliferation/apoptosis balance, by the expression of androgen-dependent growth factors [κB signaling pathways promoting the expression of inflammatory cytokines such as IL-1, IL-6, and TNFα [Exogenous testosterone injections would initially provoke an increase of intraprostatic testosterone levels and thus a higher activity of the enzyme 5 factors , 32 and and TNFα , 32, 33.α and cyclooxygenase type 2 (COX-2) [β, therefore promoting proliferation in a cancer cell line. Perhaps this is the same scenario in BPH, explaining why, in TE group, ERβ levels are significantly decreased, supported by the hypothesis that ERβ activation reestablishes and, even, increases its expression levels [Moreover, high testosterone levels augment reactive oxygen levels (ROS) along with a decrease of catalase, superoxide dismutase, and glutathione peroxidase , 32, 34. (COX-2) . In a pr (COX-2) , it was n levels .The present study shows evidence of the beneficial effects of red maca on BPH being as optimal as treatment with gold standard treatment and finasteride, but, remarkably, showing that only two of the three different maca treatments  have this effect, while the aqueous fraction is not useful to treat this disease, maintaining prostate weight, epithelium height, and stromal area in values the same as TE group.Androgen receptor levels were severely increased in the group treated with the aqueous fraction of the methanolic extract of red maca, while the extract and its butanol fraction do not, indicating an acute androgenic effect. It should be noted that, despite coming from the same extract, they can have opposed biological effects. This phenomenon was also reported but with black maca, where the aqueous fraction but not the n-butanol one is effective to improve mice fertility by increasing sperm count .β expression levels in similar values as observed in the VH group and, in the case of the methanolic extract, was higher for about 30%. This outcome is related to a previous study, in which, red maca extract is effective in recovering bone density in ovariectomized rats by regulating ERβ [Red maca presents a favorable estrogenic effect, because it reestablishes ERting ERβ . This meβ expression but also to reestablish ERα levels. Keeping a stable ERα/ERβ ratio is important to maintain a proper balance in cell proliferation; even this ratio is considered as an important epithelial carcinomas aggressiveness indicator [The estrogenic effect is related not only to ERndicator .α levels. This, along with the higher levels of AR, stimulates prostate growth, thus explaining its ineffectiveness in reducing BPH indicators. This overexpression of ERα would implicate higher expression of the Proliferating Cell Nuclear Antigen (PCNA) [Aqueous fraction shows an acute increase in ERn (PCNA) , which an (PCNA) , criteriα overexpression, because both increased testosterone levels and AR overexpression not only interfere with ERβ expression and signaling pathways but also stimulates ERα expression [β compared to VH.The androgenic effect of aqueous fraction could be the cause of ERpression , hence fβ-sitosterol [α-reductase isoforms, found also in saw palmetto (Serenoa repens), plant that is widely reported to reduce BPH [It is still unclear what compounds present in maca are responsible for reducing BPH. Perhaps, it is due to its content of tosterol , a compoduce BPH . (Brassicaceae). This molecule binds specifically to DHT, thus preventing AR activation, and also it has affinity to ERβ, and this especial combination (isoflavone + ERβ) can downregulate androgen actions [Equol is an isoflavonoid present in beans, lettuce, and, more important, cabbage, a plant belonging to the same family of maca actions , 40. AssIt seems that, in the fractionation process, part of the estrogenic effect of red maca is lost, because the expression of ER-beta levels is higher compared to VH, whereas with butanolic and aqueous fractions ER-beta levels are similar to VH. Perhaps some compounds present in both fractions act synergically.This study also contributes to the hypothesis that the butanol fraction, which is one that contains alkaloids as MTCA, in opposition to that postulated by Piacente et al. , is not α and ERβ levels; nonetheless, in the case of the aqueous fraction, its androgenic effect counteracts this beneficial effect, not only by promoting cell growth via AR activation, but also by increasing ERα levels, in which mixed actions would interfere with both ERβ expression and signaling pathways (In summary, red maca methanolic extract and its butanol and aqueous fractions have a favorable estrogenic effect by reestablishing ERpathways .


Single-cell RNA-seq (scRNA-seq) provides a comprehensive measurement of stochasticity in transcription, but the limitations of the technology have prevented its application to dissect variability in RNA processing events such as splicing. Here, we present BRIE (Bayesian regression for isoform estimation), a Bayesian hierarchical model that resolves these problems by learning an informative prior distribution from sequence features. We show that BRIE yields reproducible estimates of exon inclusion ratios in single cells and provides an effective tool for differential isoform quantification between scRNA-seq data sets. BRIE, therefore, expands the scope of scRNA-seq experiments to probe the stochasticity of RNA processing.The online version of this article (doi:10.1186/s13059-017-1248-5) contains supplementary material, which is available to authorized users. Next-generation sequencing technologies have revolutionized our understanding of RNA biology, illustrating both the diversity of the transcriptome and the richness and complexity of the regulatory processes controlling transcription and RNA processing. Recently, efficient RNA amplification techniques have been coupled with next-generation sequencing to yield transcriptome sequencing protocols for measuring the abundance of transcripts within single cells, known as single-cell RNA-seq (scRNA-seq) . scRNA-sSplicing analysis has been revolutionized by the advent of (bulk) RNA-seq techniques. Early studies  quantifiR in excess of 0.8 on test sets, validating our choice of model within BRIE.Figure This architecture effectively enables BRIE to trade off two tasks simultaneously: in the absence of data (drop-out genes), the informative prior provides a way of imputing missing data, while for highly covered genes the likelihood term dominates, returning a mixture-model quantification. For intermediate levels of coverage, BRIE uses Bayes’s theorem to trade off imputation and quantification.To assess the improvement in isoform quantification afforded by BRIE’s informative prior, we simulated RNA-seq reads for 11,478 human exon-skipping events, and a correlated feature to learn the prior  ranging from 25 to 400. Figure The informative prior learned by BRIE can also be used to impute isoform usage when there is a drop-out, i.e., when no reads are sequenced for an expressed isoform. In scRNA-seq experiments, drop-outs occur widely , though R=0.6–0.7).As BRIE can transfer information from a highly expressed gene to lowly expressed genes across multiple cells, we investigated the performance of BRIE in imputing the isoform usage if a drop-out happens. Therefore, the expression profile from a bulk RNA-seq library and the drop-out probability profile estimated from 96 HCT116 human cell scRNA-seq libraries  see Add” sectionTo assess BRIE’s performance on real scRNA-seq data, we used 96 scRNA-seq libraries from individual HCT116 human cells from the benchmark scRNA-seq study of Wu et al.  see “Mef, and inThese statistical advantages are reflected in a more effective and confident quantification: considering genes with quantified uncertainty smaller than 0.3  between a model where the two data sets are treated as replicates (null hypothesis) and an alternative model where the two data sets are treated as separate. We use the Savage–Dickey density-ratio approach and relax it to obtain more robust estimates see “” sectionΔψ=0.6), we can detect a substantial fraction of differentially spliced genes already at 50 RPK, further improving when the effect size is 0.8  . This can easily be achieved by assuming a shared splicing ratio detection of alternative splicing across a population of single cells, but as far as we are aware, BRIE is the first method to be able to quantify splicing in individual single cells and to detect differential splicing between individual cells from scRNA-seq data. We notice that, since BRIE focusses on estimating splicing ratios, it is relatively immune to normalization issues, since it is essentially a relative quantification method  and quantification. While this can be a highly effective strategy, it comes at the cost of biasing results at low coverage. In particular, when used with an informative prior learned across several cells, this may lead to underestimating splicing heterogeneity at low coverage. BRIE’s probabilistic formulation, however, brings considerable advantages. In particular, BRIE can be easily combined with other probabilistic modeling strategies aimed at removing confounders such as cell-cycle stage , or at eBRIE cannot be deployed on all scRNA-seq protocols, as it assumes that sequenced reads can be distributed along whole transcripts. Naturally, protocols such as CEL-seq or STRT-seq that bias reads towards the ends of the transcript cannot provide information about exon-skipping events that may be very far from the ends of a transcript. We believe that the availability of splicing quantification approaches such as BRIE can, therefore, be an important consideration in experimental design, particularly at a time when single-cell omic technologies are about to start being more routinely employed.Located on chromosome 1-22 (1-19 for mouse) and XNot overlapped by any other AS exonSurrounding introns are no shorter than 100 bpLength of alternative exon regions between 50 and 450 bpA minimum distance of 500 bp from transcription start site (TSS) or transcription termination site (TTS)Surrounded by AG-GT, i.e., AG-AS.exon-GTGene annotations were downloaded from GENCODE human release H22 and mouse release M6. Altogether, 24,957 and 9343 exon-skipping events were extracted from protein-coding genes on human and mouse, respectively. To ensure the high quality of the splicing events, we applied six constraints following two recent studies , 23 for Consequently, 11,478 and 4549 exon-skipping events from human and mouse, respectively, were finally used for this study.′ splice site of intron 1), I1-3ss (300 nt upstream from the 3′ splice site of intron 1), A , I2-5ss (300 nt downstream from the 5′ splice site of intron 2), I2-3ss (300 nt upstream from the 3′ splice site of intron 2), and C2 (constitutive exon 2).Following Xiong et al. , we extr′ss, I1- 3′ss, I2- 5′ss, and I2- 3′ss, were calculated from mapping each sequence to its averaged position weight matrix. Here, we considered −4 nt upstream to +6 nt downstream around 5′ss , and from −16 nt to 4 nt for 3′ss. Third, we also include evolutionary conservation scores for each of the seven genomic regions, which were calculated by phastCons [From these seven regions, four types of splicing regulatory features are defined. First, eight length-related features are included, i.e., log length of C1, A, C2, I1, I2, and the ratio of the log length of A/I1, A/I2 and I1/I2. Second, the motif strengths of the four splice sites, i.e., I1- 5hastCons , and areBulk RNA-seq libraries for the K562 cell line were produced by the ENCODE project , and dowTwo single-cell RNA-seq data sets were used to validate the BRIE model. The first data set is from a benchmark study , consistTo study differential splicing across different cell types, scRNA-seq data produced by the SMART-seq2 protocol from mouse embryo at embryonic day 6.5 and day 7.75  were useAll above RNA-seq reads were aligned to the relevant genome reference by HISAT 0.1.6-beta with known splicing junctions.Three simulations were conducted to assess BRIE’s performance in quantifying isoforms with low coverages, detecting differential splicing, and imputing splicing in drop-out cases. All synthetic reads were generated by the Spanki simulator , while wψ value follows a logitNormal distribution with mean μ=0 and σ=3, i.e., First, we assessed the robust performance of BRIE in very low coverage on 11,478 human exon-skipping events. We assume that the ψ values from the Spanki simulator in its logit format, and ensured a Pearson’s correlation coefficient of 0.8 between the feature and the truth, as shown in Additional file For generating a feature to learn an informative prior, we added Gaussian noise to the output ψ from 0.1 to 0.9 (except 0.5) were equally distributed over the 400 splicing events, and opposite ψ values were assigned to two conditions, e.g., ψ=0.1 in condition 1 and ψ=0.9 in condition 2. Then, the prior was set by the same procedure as the first simulation.Second, we tested the power of BRIE in detecting differential splicing events on 400 random mouse exon-skipping events with length ranging from 300 to 800 bp. Eight categories of Third, we mimicked the drop-out situation on 11,478 human exon-skipping events, and studied the imputation of BRIE in drop-out cases. We looked at one bulk RNA-seq library and 96 single-cell libraries of HCT116 cell lines , and focZ from a bulk library and a profile of drop-out probability calculated from a group of single cells , we simulated the RPK for each isoform (or transcript) as follows. For each isoform k, we generate a binary variable Ik, i.e., either 0 or 1, following a binomial distribution with the mean as its corresponding drop-out probability. Then each isoform expression level for the simulated single cell is αIkZk, where coefficient α is included to ensure a given number of total reads. If one wants a different overall drop-out rate but keep the similarity of the drop-out probability profile, an intercept will be added to the drop-out probability in its logit space. In the simulation of drop-outs, the 735 sequence features from real data were used to learn the informative prior. We take the mean of the learned prior as the imputed ψ for those drop-out events.Given an expression profile ) ψi for observing Ni reads i, can be defined as follows Here, we formally define the BRIE statistical model. We consider exon inclusion and exclusion as two different isoforms. We start by reviewing the mixture modeling framework for isoform quantification, introduced in MISO . The likIin denotes read identity, i.e., where the isoform read n in cell i came from. For bulk RNA-seq methods like MISO [Iin|ψi is assumed to be a multinomial distribution, and the prior distribution over ψi is taken to be an uninformative uniform distribution . The pre-computed term P(Rin|Iin) encodes the probability of observing a certain read coming from a specific isoform Iin. Bulk methods then proceed usually by adopting a Markov-chain Monte Carlo strategy to sample from the posterior distribution of the ψi variables.where the latent variable ike MISO  and DICEike MISO , the conψi, i..e, yi = logit(ψi). We then model the transformed exon inclusion ratio yi as a linear function of a set of m covariates yi=W⊤X+εi, where W is a vector of weights shared by all samples and εi follows a zero-mean Gaussian distribution. All exon-skipping events are independently modeled with shared W parameters.BRIE enhances the mixture model approach by combining it with a Bayesian regression module to automatically learn an informative prior distribution by considering sequence features. First, we use a logit transformation of Λ=λI, for a positive scalar parameter λ. A graphical representation of the full model is shown in Additional file Here, we use a conjugate Gaussian prior for the weights, i.e., mentclass2pt{minimψ and W alternately. Also, to alleviate the computational burden, there is an option to merge reads from all cells to learn parameters. For simplicity, we set λ empirically, using the value λ=0.1, which gave the best predictive performance on tests on ENCODE data. Then, we collapse W and σ by taking their expected value in Bayesian regression given a set of ψ, i.e., W=(X⊤X+σ2Λ)−1X⊤Y and σ=std(Y−W⊤X). At a single exon-skipping event level, we used an adaptive Metropolis–Hastings sampler to sample Ψ, where a univariate Gaussian distribution is used for proposal with adaptive variance, i.e., η=2.38×std(ym)(1:). At this step, we could run short parallel Markov chain Monte Carlo chains on multiple events to alleviate computational costs, for example h=50 steps if the total iteration is n×h=1000. The pseudocode for sampling from the (approximate) posterior distribution of Ψ is given in Algorithm 1. Also, this model supports fixed W and σ, which can be learned from other data sets, e.g., bulk RNA-seq, in which case lines 3 and 5 are turned off in Algorithm 1. The convergence of the sampling is diagnosed using the Geweke diagnostic Z score; in our experiments 1000 burn-in steps appeared to be sufficient in all cases.As shown above, BRIE involves the whole set of exon-skipping events, thus there are thousands of parameters to infer jointly, which can lead to very high computational costs that are not easily distributed. Therefore, we introduce an approximate method to learn ψ values as well as the learned regression weights. BRIE offers functionality to visualize both such posterior distributions as histograms  using 20 CPUs, BRIE could finish a transcriptome-wide splicing quantification for a human cell  in 5 min, and for a mouse cell (4549 events) in 2 min. This running time is a linear function of the number of cells (learning separate priors for different cells), and can be reduced by using more CPUs.The BF  is a posA and B, δ=ΨA−ΨB, we introduce a null hypothesis (H0) as δ≈0, and the alternative hypothesis (H1) as δ≉0. Here, D is the data used to sample the posterior of Ψ in two cells. Then, the BF in favor of the alternative hypothesis on observing data D is defined as To detect differential splicing between two cells (or cell groups), P(H1)=P(H0), and we can clearly see that P(D|H0)=P. Therefore, by taking the Savage–Dickey density ratio [As usual, we assume that both hypotheses have the same prior, i.e., ty ratio , we can ε can be set as 0.05.where ΨA and ΨB following their posteriors, the distribution of P can be readily approximated by empirically re-sampling ΨA−ΨB. With a set of re-sampled δM1:, we take the proportion of |δi|<ε as the posterior probability P. Similarly, we could sample a set of P(−ε<δ<ε|H1). When comparing two cell groups, one can multiply the individual likelihoods . This, however, is equivalent to pooling reads across different cells, and will lose the quantification of cell-to-cell heterogeneity.As BRIE samples Additional file 1Figures S1–S11. (PDF 1940 kb)Additional file 2Tables S1 and S2. (XLSX 32.1 kb)


Isopycnic density gradient ultracentrifugation and fractionation of isolated RNA into labeled and unlabeled fractions followed by 16S rRNA sequencing showed a quick adaptation of the bacterial community in response to the added sugar, which was dominated by unclassified Lachnospiraceae species. Inspection of distinct fractions of isotope-labeled RNA revealed Allobaculum spp. as particularly active glucose utilizers in the system, as the corresponding RNA showed significantly higher proportions among the labeled RNA. With time, the labeled sugar was used by a wider spectrum of faecal bacteria. Metabolic profiling indicated rapid fermentation of [U13C]glucose, with lactate, acetate, and propionate being the principal 13C-labeled fermentation products, and suggested that “cross-feeding” occurred in the system. RNA-SIP combined with metabolic profiling of 13C-labeled products allowed insights into the microbial assimilation of a general model substrate, demonstrating the appropriateness of this technology to study assimilation processes of nutritionally more relevant substrates, for example, prebiotic carbohydrates, in the gut microbiota of mice as a model system.RNA-based stable isotope probing (RNA-SIP) and metabolic profiling were used to detect actively glucose-consuming bacteria in a complex microbial community obtained from a murine model system. A faeces-derived microbiota was incubated under anaerobic conditions for 0, 2, and 4 h with 40 mM [U It is well documented that symbiotic gut inhabitants are required for maintaining host health and well-being , 2, as tIngestion of prebiotic carbohydrates to boost health-promoting intestinal fermentation by selective enrichment and/or stimulation of the activity of commensal microorganisms that contribute to the well-being of their host is a viable strategy to improve host health through the benefits of microbial metabolism –11. In p13C) into the RNA by metabolically active microorganisms because of a high RNA synthesis rate glucose as a simple and quick fermentable model substrate, active glucose fermenters in the system were detected already after 2 h of incubation. The detected 13C-labeled metabolic products corroborated the RNA-based sequencing results. Our study represents a “proof of principle” study establishing the use of RNA-SIP technology to interrogate samples of mice origin, which, to the best of our knowledge, has not been done before. Using this study as a starting point, future studies will address utilization of more complex carbohydrates, such as resistant starch (RS), by communities of mice origin in vivo to identify prebiotics assimilating bacteria directly in the intestinal environment.Animal models represent valuable and relatively easy accessible tools in gut microbiota research , 33. In 13C]glucose (≥99 atom%) , yielding a final concentration of 40 mM glucose and 7.5% (w/v) of faecal material. Samples were incubated in individual 15 mL reaction tubes at 37°C for 0 h (control), 2 h, or 4 h under anaerobic conditions, which were obtained by using airtight jars and AnaeroGen sachets  resulting in a total of three different incubation treatments. Prior to use, the M9 minimal medium was filter sterilized, deoxygenated, and prewarmed to 37°C.C57BL/6J mice were raised at the animal facility at the University of Ulm under specific pathogen-free (SPF) conditions, receiving a standard laboratory diet and water ad libitum. Fresh faecal pellets were randomly collected from 12 healthy animals within 4 h of excretion. The pellets of all animals were finally pooled and subsequently homogenized in M9 minimal medium  supplemeμL) for 1 h at 37°C with 10 μL RNase-free DNase I , 15 μL of 10x DNase I buffer , and 25 μL of nuclease-free water. Further purification of the RNA samples was performed using Qiagen RNeasy spin columns  according to the manufacturer's instructions. Subsequently, the RNA samples were quantified using a P360 Nanophotometer  and the absence of genomic DNA was confirmed by the absence of PCR products after amplification of 16S rRNA genes with universal primers 27F/907R glucose. Glucose concentrations in a double digit mM range can still be considered physiological for intestinal environments glucose yielded strong PCR products in “heavy” gradient fractions  were obtained from fraction 7 .16S rRNA from cDNA was amplified from selected gradient fractions with universal bacterial primers. Amplification of cDNA obtained from incubations for 2 h and 4 h with [U13C]glucose, that is, bacteria which were less active glucose assimilators.In order to identify the most active bacterial populations involved in glucose assimilation, fractions for sequencing-based community analyses were chosen based on the density-dependent distribution of RNA in the gradients. “Heavy” fractions (fractions 3–5 of the 2 h and 4 h incubations) contained a low but still PCR-detectable amount of isotope-labeled RNA and hence phylogenetic information about the most prolific glucose utilizer in the system. To identify these particularly active community members, the community structure in the “heavy” fractions was compared to the community structure of fractions showing peak concentrations of bacterial RNA, that is, fractions 6 and 7 for the 2 h incubations, and fractions 9 and 10 for the 4 h incubations, representing the majority of bacteria that became only slightly labeled by the added glucose was observed (p < 0.01) than the bacterial community in the “medium” fractions , Dorea (3.4%), Oscillibacter (2.6%), Allobaculum (1.4%), and Butyricicoccus (1.2%). Among the Bacteroidetes, unclassified Porphyromonadaceae (6.9%) and Barnesiella (1.6%) represented the largest groups. Unclassified Desulfovibrionaceae (1.3%) were the largest group within the Proteobacteria. The phyla Actinobacteria, Tenericutes, Verrucomicrobia, and TM7 showed a low relative abundance (<1%). A small proportion (0.5%) of the total community was defined as unclassified Bacteria  was analyzed from three “light” RNA fractions where most RNA accumulated. This microbial community in the control sample could be assigned to the Firmicutes (87.3%), Bacteroidetes (9.6%), and Proteobacteria (2.2%), representing the most abundant phyla. The most dominant taxa (≥1% relative abundance) within the Firmicutes, classified to the most detailed taxonomic level available, were unclassified Lachnospiraceae (43.8%), unclassified Clostridiales (12.6%), unclassified Ruminococcaceae (9.8%),Bacteria . The dom13C-labeled sample to that in the “medium” fractions. After 2 h of incubation with [U13C]glucose, the bacterial genus which differed most prominently between the different density fractions was Allobaculum, which was over 3-fold more abundant in the “heavy” RNA-SIP fractions than in the “medium” fractions ( Parabacteroides showed a tendency to accumulate in the “heavy” fractions (p < 0.05) in proportions of the abundant unclassified Lachnospiraceae, unclassified Porphyromonadaceae, unclassified Ruminococcaceae, Dorea, and unclassified Desulfovibrionaceae, compared with their relative abundance in the “medium” fractions (p < 0.1) in reduced numbers in the “heavy” fractions. The most significant decrease (p = 0.001) was observed for the genus Akkermansia. Approximately 10-fold fewer sequences of this genus were detected in “heavy” RNA-SIP fractions than in the “medium” counterpart fractions, although the overall relative abundance of this taxon was low (<1%).The most metabolically active bacterial populations were determined by comparing the relative abundance of individual taxa in the “heavy” fractions of the ractions . Among tractions . The obsractions . The unc13C]glucose, the diversity of bacteria relatively enriched in the “heavy” fraction was increased compared with the diversity after 2 h of incubation. The genus that showed the most prominent tendency to accumulate in “heavy” fractions was Butyricicoccus (p < 0.1)   . Among tubations . Noticeawith 2 h . The glo < 0.01) . Among t Allobaculum, a genus of the Erysipelotrichi class, was significantly higher in the “heavy” RNA-SIP fractions, indicating that the members of this genus could benefit the most from the excess glucose in the system, indicated by rapid label incorporation into their RNA. Interestingly, Allobaculum has also been found in increased numbers in prebiotic (oligofructose) treated mice in combination with a HFD (high-fat diet) but was reduced in HFD treatment lacking the prebiotic glucose, HPLC-IRMS analysis revealed 13C-labeled lactate, acetate, propionate, and butyrate as the main metabolic products; isotope-labeled isobutyrate was also measured, but in lower amounts  of the respective carbon-pools. These fractions remained approximately constant at 83.7, 55.2, 48.5 and 42.6 APE, after 4 h of incubation, respectively , yielding particularly lactate and acetate, and in addition to a lesser extent propionate and butyrate, as the main fermentation products. The profile of fermentation products corresponded to the composition of the microbial community. For example, many bacteria form lactic acid from glucose, including Lactobacillus spp., a well-known genus of the lactic acid bacteria glucose (≥99 atom%) and only to a small extent from other unlabeled sources in the faecal material. Similarly, formation of acetate, propionate, and butyrate  occurred from glucose, albeit with a relatively larger contribution of other unlabeled sources. However, formation of these acids would also be conceivable from the labeled lactate glucose origin in this system.The branched-chain SCFA isobutyrate showed a greater than 10-fold increase in concentration at 4 h, indicating amino acid fermentation in the system , 76. How13C labeled fermentation products offers an efficient approach to link the identity of bacteria to their metabolic function and the metabolic by-products they produce. Insights into the metabolic activity of a complex microbial community of mice origin were gained using glucose as a model substrate. We have shown that a wide range of bacteria were active after glucose addition, which is not surprising as glucose is an easily fermentable energy source. Nevertheless, our data showed that distinct members of the faecal community were able to use the glucose more efficiently than others. Using mice as a model system is still considered as a powerful tool in microbiota research, as the microbiota can be investigated under controlled conditions  [In this study, we demonstrated that RNA-SIP in combination with metabolic profiling of factors) . Furtherfactors) , 33 indi


In the article titled “Impaired Fertility Associated with Subclinical Hypothyroidism and Thyroid Autoimmunity: The Danish General Suburban Population Study” , there wN = 11387) and excluded participants with missing values of TSH, fT4, and tT3 (N = 50) and missing values of the number of pregnancies, the number of children born, and the number of spontaneous abortions (N = 31)” should be changed to “In this study we included participants of European origin (99% Danish) (N = 11387) and excluded participants with missing values of TSH, fT4, and tT3 (N = 50) and missing values of the number of pregnancies, the number of children born, and the number of spontaneous abortions (N = 83).”In Section “2.1. Study Population,” the sentence “All individuals older than 30 years were invited” should be changed to “All individuals older than or equal to 30 years were invited.” In addition, the sentence “In this study we included participants of European origin (99% Danish)  had mild  hypothyroidism, 9.4% prevalent hypothyroidism, and 4.2% prevalent hyperthyroidism” should be changed to “


The bamboo filter's final effluent would be 82 mg NH3-N L−1, 157 mg NO3-N L−1, and 13 NTU, which corresponds to 63% removal of total N and 99% removal of turbidity. These filter media thus present a simple option for sustainable post-treatment for nitrogen management and effluent polishing in low-resources settings.The treatment of high-strength anaerobic digester effluent in laboratory-scale trickling filters for nitrification and then anaerobic filters for denitrification is reported. Five media types were investigated in the trickling filters: biochar, granular activated carbon (GAC), zeolite, Pall rings, and gravel. Three media were tested in five denitrifying filters: sand (S), bamboo wood chips (B), eucalyptus wood chips (E), bamboo with sand (B+S), and eucalyptus with sand (E+S). The different wood chips served as a supplemental electron donor for denitrification. From six months of operation, biochar, GAC, zeolite, Pall rings, and gravel media had turbidity (NTU) removal efficiencies of 90, 91, 77, 74, and 74%, respectively, and ammonia removal efficiencies of 83, 87, 85, 30, and 80%, respectively, which was primarily by nitrification to nitrate. For the anaerobic filters, S, B, B+S, E, and E+S had nitrate removal efficiencies of 30, 66, 53, 35, and 35%, and turbidity removal efficiencies of 88, 89, 84, 89, and 88%, respectively. Biochar and bamboo were selected as the best combination of media for trickling filter and anaerobic filter sequential treatment. Based on an average initial influent of 600 mg NH  •High-strength anaerobic digester effluent was treated in biological filters.•3-N.Trickling filters packed with biochar, GAC, and zeolite showed high removal of NH•Trickling filter effluent was denitrified in submerged filters packed with different media.•Bamboo can be an effective electron donor for denitrification while acting as filter media.•High removal of N and turbidity was achieved using the proposed sequential treatment. FurtherApplication of trickling filters (TF) for the post-treatment of anaerobic reactors handling sewage is a relatively recent interest . TrickliBOD m−3 d−1. This filter treated effluent from a UASB and reached BOD removals in the range of 50–60% but authors did not monitor NH3 removal. Using pebbles with an effective size of 5.6 mm for the treatment of anaerobically digested dairy manure, 3-N for influent containing 692 mgsBOD L−1 and 1210 mg NH3-N L−1. 3-N removal from UASB effluent starting with 72 mgBOD L−1 and 29 mg NH3-N L−1 under OLR and HLR of 0.08 kgBOD m−3 d−1 and 1.1 m3 m−2 d−1, respectively. In a downflow hanging sponge (DHS) reactor, a setup similar to TF, 3 removal (inlet concentration up to 40 mg NH4-N L−1) while operating at 0.67 to 1.24 kgBOD m−3 d−1, respectively. Most recent work with this reactor type achieved removals of 87% and 83% of BOD and NH3-N, respectively at a loading of 1.11 kgBOD m−3 d−1 with influent concentrations of 93 mgBOD L−1 and 24.6 mg NH4-N L−1  L−1. There are no known studies of the use of GAC as a trickling filter media for domestic wastewater.The use of granular activated carbon (GAC) as a biofilm carrier was introduced in drinking water treatment and showed improvements over adsorption-only processes in that media lifespan was extended such that it did not require regeneration . In grey2 g−1 and 1.5–2.0 g cm−3, respectively . Additionally, the trickling filter effluent could be denitrified if total nitrogen removal is necessary, making it possible to consider various water reuse scenarios. Thus, potential low-cost means for denitrification of nitrified digester effluent are discussed next.2 gas. Submerged fixed beds have been successfully used for denitrification. The denitrification process requires an electron donor which can be residual BOD or provided extraneously. Generally the electron donor is the rate-limiting substrate, and a requirement of 4 g BODL/g NO3−-N is normally assumed for complete denitrification to nitrogen gas  and removal (87–99%). In an evaluation of alternative nitrogen management technologies for onsite sewage treatment, a simple single pass sand filter followed by a wood chip biofilter outperformed more complicated technologies  and/or the COD provided by the wood media themselves . This is the first study to assess these media types for sequential nitrification-denitrification of high-strength digester effluent.22.1Five different media types were selected for the trickling filter: biochar (thereafter abbreviated BC), granular activated carbon (GAC), zeolite (abbreviated Zeo), Pall rings (PR), and gravel (Gr). The submerged attached growth filters for denitrification included sand (S), chipped bamboo (B), and chipped eucalyptus (E). Biochar was chosen due to its sustainable production and availability. Because previous applications of biochar as a media for biofiltration of wastewater were not found, GAC was selected for comparison to a similar previously studied medium. Zeolite was chosen to include a medium with ammonium adsorption capabilities in a biological filter application. Pall rings and gravel were chosen for comparison to engineered  and historical (gravel) alternatives.For the denitrifying filters, sand was selected to determine if denitrification could take place without external supply of electron donors, eucalyptus was used for comparison to previous studies, and bamboo was used as a potential alternative, more sustainable, source of wood chips. Additionally, sand was mixed with wood chips  in separate columns to see if the combination would yield improved turbidity and nitrate removal.Phyllostachys edulis) was sourced locally in North Carolina and passed through a wood shredder. Eucalyptus chips were purchased from a vendor in Florida. In both cases, only wood chips passing through a sieve with 9.5 mm openings were used in the filter.The biochar was derived from pine pellets and manufactured at 900 °C for 1 h. GAC was sized at 4 × 8 mesh and derived from coconut shell. Jaeger Pall rings were in polypropylene and measured 16 mm (5/8”) in diameter. Biochar was provided by the group of Prof. Linden at the University of Colorado-Boulder. GAC, zeolite, and Pall rings were purchased from online vendors. Quarried, washed, and dried sand was sourced from Sakrete, and gravel was sourced from the Martin Marietta Plant in Durham, NC. Bamboo  in order to minimize wall effects in the filters.Trickling filter columns were filled with media to a depth of 100 cm  and were manually shaken every 20 cm to ensure uniform packing. Media were held using a plastic mesh at the bottom of the column. Natural aeration was induced through air inlet ports  drilled into the fittings below the filter bed as well as keeping the top of the bed open to the atmosphere.Submerged filter columns were filled with sand, bamboo, eucalyptus, bamboo with sand (B+S), and eucalyptus with sand (E+S), respectively, to a depth of 50 cm . Mixed wood chip and sand columns were filled in 10 cm increments until reaching the full height of 50 cm. Wood chips were added first, and then sand was added while shaking the column to minimize heterogeneous void space.D10) and uniformity coefficient (D60/D10). Bulk density, particle density, and porosity were determined for each column. Bulk density (ρB) was determined as the mass of media filling the column volume, and particle density (ρp) was determined using the volume of deionized water displaced by 25 g of each sample. Porosity (p) was calculated with equation Media physical characteristics were determined through a sieve analysis on a mechanical shaker at 30 rpm for 10 min. Results are shown in 2.2BOD L−1 and 1–3 g N L−1. The effluent from an intermittently aerated basin treating anaerobically digested swine manure system was selected as a mimic for human fecal digestate  on each filter was 2 m-3) would remain under previously established maximum operational parameters for simultaneous nitrification and BOD removal: 80 m3 m−2 d−1, 0.5 kgBOD m−3 d−1, and Each trickling and anaerobic filter was fed 1.35 L ddia−2d−1 . Due to −1) contributed to operational issues (plugging and issues with pumping thick slurries), thus the substrate was diluted 1:1 with tap water for the remainder of the study (Periods II and III). Average COD and TN concentrations during these periods were 3040 and 1830 mgCOD L−1 and 1790 and 790 mg N L−1, respectively. The denitrifying filter study began after the trickling filter study  and ran for 120 days. Operating conditions did not change for the denitrifying filters, so this study is not divided into periods as in the trickling filter study.Swine farm effluent used as substrate was undiluted for the first 8 weeks of operation (Period I). The high concentration of suspended solids . A step change from water to trickling filter substrate was used due to high conductivity of substrate . Conductivity probes were placed in the low volume vessels (∼50 mL) that collected the TF effluent before it overflowed into the secondary container. Substrate for submerged filters had a lower conductivity, and thus a NaCl solution  was pumped into these filters for one day. Conductivity was measured in the low volume vessels (∼50 mL) that collected filter effluent before it left the system. The retention time in the trickling filters was determined as the time at which 50% of the peak conductivity was measured. In the submerged filters, retention time was determined as the time in which 50% of the tracer input was recovered in the effluent.3-N, NO2−-N, NO3−-N, and COD were measured using Hach kits. Dissolved oxygen (DO) and pH were measured using digital meters , and turbidity was measured using EPA Method 180.1. Periodic tests of BOD5 and total suspended solids were performed according to EPA Methods 405.1 and 160.2, respectively.Samples were taken weekly for the study duration from the outlet of each filter and at the mid-depth of the submerged filter. Total NHFilters were not backwashed during this study. After 260 days (end of Period II), plugging at the top of the trickling filters had become a regular issue. Feeding was stopped at this time, and media was removed from each filter and washed with tap water. Period III began at this time (day 274). In Period III fresh biochar (BC-new) and fresh GAC (GAC-new) replaced Zeo and PR filters while washed BC, GAC, and G media were reused. Operating conditions in Period III were the same as in Period II.3-N concentrations in the solution. A manometer was used to measure the change of pressure in the headspace. Samples were taken at 12 h, 1, 2, 3, and 6 days and then weekly after the start of the experiment. A COD mass balance was performed to determine how the COD released from wood chips was dissolved into solution, consumed by denitrifiers, or used for CH4 production as measured in the headspace. The total COD release was calculated using the following equations:liquid is the volume of solution on the day of sampling, P is pressure of gas in headspace, %CH4 the fraction of methane in the headspace, Vheadspace is the volume of gas headspace on the day of sampling, R is the ideal gas law constant 8.314 [m3*Pa/K*mol], and T is temperature in Kelvin (295 K). The conversion of g NO3-N to g COD is based on the relationship of g COD expected to denitrify NO3-N to N2 . Only gauge pressure was considered to calculate number of moles of CH4 produced, assuming atmospheric pressure remained constant during the experiment. The conversion of CH4 to COD is based on the empirical COD of CH4, 4 mol O2 to oxidize 1 mol CH4 and 16 g/mol CH4 resulting in 64 g COD/mol CH4.COD release from wood chips was evaluated in both a batch and in a column experiment. For the batch experiment, 10 g of either bamboo or eucalyptus wood chips were added into 250 mL flasks filled with 100 mL DI water, 100 mL trickling filter effluent, and 1 mL of sludge for inoculation. Separate flasks were filled with the same solution without wood chips as a control. All flasks were prepared in triplicate and incubated on a shaker table at room temperature (22 °C) without exposure to light. Liquid samples were taken with a syringe (2 mL) to measure COD and NO-N to N2 . The %CH−1 and 400 mg NO3-N L−1) for the first three days. The feed was then switched to a solution of DI water and KNO3 (0 mg COD L−1 and 400 mg NO3-N L−1) so that all denitrification would be due to COD released from wood chips. COD and NO3-N were determined in the inlet, mid-depth, and outlet of the columns at the start and then 1, 2, 3, 6, 9, and 12 days after the start and then weekly until the outlet concentration of nitrate equaled the inlet concentration. The COD released by wood chips was determined by a mass balance, assuming steady-state conditions after the first three days (no COD accumulation) where Cin and Cout were COD concentrations measured in inlet and outlet, respectively, Q was substrate flow rate (1.35 L d−1), and t was time step between sampling days [d]. The following mass balance was solved for wood chip release, WCrelease, in g COD.A similar experiment was performed to determine COD released by operating columns with fresh bamboo and eucalyptus. Filters were fed trickling filter effluent  for these filters were 0.46, 0.61, 0.42, 0.35, and 0.45, respectively. 3-N and production for NO3-N for each filter during Periods II & III. The full nitrogen speciation concentrations can be seen in 3-N removal and NO3-N production is the amount of NH3-N that was either lost from the system through adsorption or was not fully nitrified and exited as nitrite. The greatest difference between these values was in the GAC and Zeo filters. The GAC NO2-N concentration was 38 mg N L−1 during Period II, and the fresh GAC and washed GAC in Period III both released less than 8 mg N L−1. The Zeo NO2-N concentration was 171 mg N L−1. The summation of N species from these filters does not account for all NH3-N removed from the influent; therefore, some total N was removed from solution. Zeolite had the most removal of total N, but also released the greatest concentration of NO2-N, indicating incomplete nitrification.3-N concentration and pH in the influent and effluent of each filter while turbidity data are shown in 3-N and pH in the majority of filters during Period I (first 60 days) is indicative of the build-up of the nitrifying community.3-N removal was 83, 87, 85, 30, and 80%, respectively. Treatment performance began to decline after this time. Filters were then decommissioned to be washed with tap water. Zeolite and Pall rings were replaced with fresh GAC and biochar, which were deemed more promising media. Washing the media did not result in a long re-start period for BC and GAC filters. The trickling filter packed with gravel did exhibit a reduced performance after washing when comparing the end of Period II and start of Period III. This is likely due to the biofilm being washed off resulting in reduced removal rates. Performance for all washed media at the start of Period III was better than Period I, and the performance of washed BC and GAC was better than new BC and GAC. The higher removal rates were likely due to residual microbes and biofilm in media pores that were not washed off. Based on this finding, washing filter media every 6 months may yield the best results.The filters had stable performance from the start of Period II (day 63) until day 239. During this time, average turbidity removal for BC, GAC, Zeo, PR, and Gr was 90, 91, 77, 74, and 74%, respectively, and NH3.2Tracer tests showed that the retention time in S, B, B+S, E, and E+S filters was 36.7, 53.8, 32.9, 15.8, and 25.5 h, respectively. The measured retention time to theoretical retention time ratios for these filters were 0.51, 0.75, 0.46, 0.22, and 0.34, respectively. 3-N for each media type during the study period. There are no data points for sand and B+S filters from day 49–70 as there was regular clogging at the surface of these filters during that time. The top 1 cm of these filters was scraped and removed on day 70, and thereafter, the top surface of these filters was stirred weekly to induce free flow to remedy this issue. Effluent NO3-N concentrations from the bamboo-only filter consistently remained the lowest while effluent turbidity was similar in all filters. Turbidity removal was consistently high throughout the study, and effluent turbidity decreased moderately over time as the filters aged  in all filters. The bamboo filters had the lowest concentrations in their effluent (1.1 mg L−1 in B and 0.5 mg L−1 in B+S) (aged see  in SI. T in B+S)  in SI.Fi3.3The amount of COD released by bamboo and eucalyptus during the batch experiment is shown in 3-N L−1 on this day)  filter slowly decreased, consistent with the need for the nitrifying community to build up for NH3 removal.An indicator of nitrification is change in pH as 2 mol of Hed by pH . This de4.1.23. The performance of these two filters were similar for the duration of the experiment  that are effective in adsorbing dissolved contaminants, such as ammonium . These mduration ,GAC-II. duration . Additio3 concentrations in the effluent of the Zeo filter rapidly increased at the end of the startup phase (days 35–56), followed by a decrease of effluent NH3 concentrations during Period II to reach levels similar to that of filters packed with BC & GAC. This increase and then decrease in effluent ammonium concentration is attributed to filling adsorption sites during startup and a longer time to build up the nitrification community. Later, from days 133–252, the filter packed with Zeo had similar effluent NH3 but much lower NO3 concentrations than the BC and GAC filters. This signifies a shift in NH3 removal mechanism from ion exchange (during Period I) to nitrification and back to ion exchange (during Period II). This dynamic is likely related to the ability for zeolite to be regenerated as nitrifying bacteria consume NH4+, as was found by In comparison to filters with BC and GAC, NH3-N removal rates. With the exception of the Pall ring filter, all filters showed the ability to achieve nearly 0.10 kg N m−3 d−1. The rates achieved in this study are significantly higher than found in a previous study testing both biochar and GAC (approximately 0.03 kg NH3-N m−3 d−1 each) (−1 vs 95 mg N L−1 for the Berger study), which also show that these filters can treat high strength waste.Overall, most of the trickling filters showed high NH−1 each) . The hig2/g NH4+-N  in this experiment are more conducive to natural draft than a full-scale system which a much larger diameter.Nitrification has a significant oxygen demand (4.57 g Og NH4+-N ). Our trg NH4+-N  confirme4.23-N concentration in the influent of the anaerobic filters was 265 mg-N L−1, and outlet concentrations for S, B, B+S, E, and E+S were 187, 70, 100, 171, and 171 mg NO3-N L−1 with corresponding removals of 29, 73, 64, 35, and 35%, respectively. The NO3-N loading did not significantly change from the first half to the second half of the study, however, the inlet COD concentration decreased from first half to second half (1150 to 730 mgCOD L−1) which may have affected the denitrification performance. Another possible reason for decreased performance could be a partial exhaustion of the most available carbon released by the wood chips; however, there was no increasing trend of effluent nitrate concentrations towards the end of the study, showing that the wood chips were still providing reducing equivalents for denitrification at that time.Denitrification performance was much greater over the first two months than for the next two months. From day 1–62, the average NOCOD L−1 for S and B, respectively. In terms of BOD (3 sampling events), filters with wood chips had lower effluent concentrations than the ones packed with sand . BOD samples were taken on days 41, 106, and 132. S, E, and E+S filters had increasing BOD concentrations while B and B+S filter did not show either an increasing or decreasing trend in concentration. The similar COD effluent concentrations were likely due to high nitrate removal performance in filters with wood chips. The COD released by the wood chips was consumed by denitrifiers, and the COD remaining in the effluent was mostly not bioavailable. Based on these results, the likely limiting factor in filter performance was having sufficient electron donor for denitrification, which is consistent with general denitrification operation in that the electron donor is generally the rate-limiting substrate , showing that eucalyptus did not significantly contribute to denitrification in terms of supplementing electron donors. Removal rates in all filters were greater in the first half of the filter than in the second half. The higher rate in the first half of the filter supports the finding of 3-N L−1 at 1.35 L d−1, the resulting volumes would be 6.1 L for bamboo and 11.3 L for eucalyptus.The highest nitrate removal rates were seen in the bamboo wood chips column, 0.089 and 0.066 kg N m m−3 d−1 . Eucalyp−1, the sand filter removed 635 mg COD d−1 and 122 mg NO3-N d−1. By using sand as the control for the amount of COD from the influent consumed for denitrification, the COD provided by the bamboo and eucalyptus filters for denitrification can be predicted. B, B+S, E, and E+S filters removed 265, 215, 143, and 156 mg NO3-N d−1, respectively. The COD:NO3− ratio in the sand filter was 5.2:1. Using that same ratio for NO3-N removal in other filters yields 1,380, 1,120, 740, and 810 mg COD d−1 consumed for denitrification in the B, B+S, E, and E+S filters, respectively of which 749, 487, 110, and 179 mg COD d−1 came from the wood chips. The B filter had 978 g bamboo, resulting in a release rate of 0.765 mgCOD gbamboo−1 d−1, and the E filter had 1070 g eucalyptus, resulting in 0.103 mgCOD geucalyptus−1 d−1.At a flow of 1.35 L dCOD gbamboo−1 d−1) than found in the column (1.26 mgCOD gbamboo−1 d−1) and batch studies (1.04 mgCOD gbamboo−1 d−1). However, COD release plateaued in column and batch studies by day 73, while the COD release rate in the treatment study had still not plateaued  in the column study enhanced microbial activity, either directly extracting more COD out of the wood chips or promoting hydrolysis of the wood chips.The calculated rate of COD release from bamboo wood chips was less in the treatment study  than in the column study  and batch study . This opposite relationship for eucalyptus is unclear, but the greater release in the batch experiment than in the column experiment may be due to the shorter retention time compared to column with bamboo, and due to slow hydrolysis.Total eucalyptus COD release as well as release rate was lower in the treatment study . Bamboo and eucalyptus wood chip filters showed less turbidity removal which was attributed to higher void space compared to sand, which is why two filters were tested using a combination of sand and wood chips. However, wood chips plus sand filters did not show any significant improvement in turbidity removal. The use of sand resulted in decreased performance over time as clogging was experienced in sand and B+S filters by day 49 and day 62 for E+S. From this time on, the top layer of the filter was stirred weekly to disturb buildup and induce free flow. With this scenario, bamboo wood chips alone were the overall best performing filters by providing the greatest nitrate removal without losing turbidity removal performance while having greater longevity. Biochar could also be used as an alternative medium to improve filtration and increase nitrate removal as has been suggested by 4.33-N L−1, 50 mg NO3-N L−1, and 980 NTU and 6 d EBRT, the biochar filter's expected effluent would be 97 mg NH3-N L−1, 475 mg NO3-N L−1, and 120 NTU. The bamboo filter (3 d EBRT) would then produce an effluent of 82 mg NH3-N L−1, 157 mg NO3-N L−1, and 13 NTU. This theoretical combined performance would thus result in 63% removal of total N and 99% removal of turbidity. The limiting step to greater total N reduction in this setup would be denitrification. If more N removal is required, increasing the volume of the bamboo denitrifying filter is likely to improve performance as the electron donor was demonstrated to limit denitrification. Based on the observed nitrate removal rates, the bamboo filter volume would need to be increased to 7.2 L (or a volumetric loading of 0.19 m3 m−3 d−1) to accommodate the nitrate loading. In this scenario, total nitrogen removal efficiency of 80–90% will likely be achieved. Another approach to improve denitrification is to pre-treat wood chips to promote hydrolysis of the cellulosic structure. Particle size reduction, thermal treatment, acidic treatment, and alkali treatment are all methods of improving the biodegradability of lignocellulosic materials  in the trickling filters with BC, GAC, and Zeo were similar and ranged from 31 to 42%. Removal in the denitrifying filters ranged from 27% for the eucalyptus filter to 41% in the all-sand filter. The primary mechanism of phosphorus removal in this experiment is hypothesized to be precipitation and filtration and not biological removal which is consistent with the observation that the sand denitrifying filters performed better than those without sand. Additionally, the operational condition for these filters was unfavorable for biological phosphorus removal. For phosphorus treatment, two methods of interest are (1) incorporating media into the denitrifying filters such as iron . These same filters achieved 83–94% removal of turbidity while treating a waste stream with approximately 1000 NTU. Investigations with submerged attached growth filters evaluated the use of sand, bamboo, bamboo with sand, eucalyptus, and eucalyptus with sand as denitrification systems for treating the effluent of the nitrification trickling filters. The maximum nitrate removal was 66% of NO3-N and 89% removal of turbidity in the filter packed with bamboo. The trickling and submerged filters showed high removal rates while treating high concentrations of ammonia and nitrogen and, thus, offer promising post-treatment options for digester effluent for simultaneous organic and nitrogen removal. These systems required minimal attention as estimated time between required maintenance was 4–6 months. Both filter stages provided dramatic improvement in effluent clarity as well as odor, as there was little to no detectable offensive odor in the effluent of either filter. The improved aesthetics of the treated effluent may allow for water reuse . The trickling filter produces an effluent with high total nitrogen concentrations which could be reused as fertilizer if only this first stage of treatment was used. If local fertilizer reuse is not desired, the second stage denitrification filter can be used. If adequately sterilized, the second stage denitrification filter effluent could potentially be reused as flushing water or wash water, or be safely discharged in the environment, depending on local regulations.This study evaluated the use of various packing materials as nitrification and denitrification media for the treatment of high-strength anaerobic digester effluent. Maximum ammonia-nitrogen removal  in filters with biochar and GAC reached 81–90% (at an influent concentration of 600 mg NHThe authors declare that they have no conflicts of interest or competing financial interests.