SYT11, MCUR1, SOD2, ORAI2, HSDL2, PFKP, and GPRC5B. Thus, we present an extended reference set of brain RNA editing events, identify a subset that are found to be expressed at the protein level, and extend the narrative of transcriptomic perturbation in AD to RNA editing.RNA editing is a feature of RNA maturation resulting in the formation of transcripts whose sequence differs from the genome template. Brain RNA editing may be altered in Alzheimer’s disease (AD). Here, we analyzed data from 1,865 brain samples covering 9 brain regions from 1,074 unrelated subjects on a transcriptome-wide scale to identify inter-regional differences in RNA editing. We expand the list of known brain editing events by identifying 58,761 previously unreported events. We note that only a small proportion of these editing events are found at the protein level in our proteome-wide validation effort. We also identified the occurrence of editing events associated with AD dementia, neuropathological measures and longitudinal cognitive decline in:  Resources reporting RNA editing sites from brain tissue have been published. Here, the authors provide an atlas of RNA editing events found in the aged and Alzheimer’s disease human brain tissue resulting in changes at protein level. APOB gene in 19871, millions of sites have been catalogued as being edited in humans. A study of B cells from 27 individuals identified >10,000 exonic sites2; an investigation with six tissues in three healthy individuals catalogued 3,041,422 sites3; and the most recent analysis of 8551 samples covering 53 body sites from 552 individuals reported 408,580 RNA editing events across the genome4.RNA editing is a molecular process that introduces another layer of variation in RNA. Since its discovery in the human ADAR1, ADAR2, and ADAR3. ADAR-related RNA editing has been associated with autoimmune and inflammatory diseases, cancer, and cardiovascular disease5. Evidence is mounting that there may be a link between RNA editing and neuropathological traits, and ADAR2 protein has an essential role in murine brain development. In humans, a recent RNA sequencing (RNA-seq) study of human hippocampus samples showed significantly higher gene expression in six Alzheimer’s disease (AD) cases compared to six normal controls for ADAR3, but not ADAR1 or ADAR26. Also, AD patients have been reported to have significantly lower levels of RNA editing at 14 re-coding sites in 11 genes, where the editing process changes the amino acid sequence of the targets6. Half of these sites were discovered previously with targeted sequencing measurements in fewer than 30 AD cases and controls7.The most common form of RNA editing is adenosine-to-inosine (A-to-I) editing executed through Adenosine Deaminases Acting on RNA (ADAR) proteins. The three major genes encoding ADAR proteins are https://adknowledgeportal.synapse.org/Explore/Data). Based on our unique data which include multiple brain regions and proteomes from the same subjects, we are able to study the mapping of RNA editing across different brain regions as well as the extent to which coding events affect the proteome. In addition, with our sample size of 1074 independent subjects  or endophenotypes of AD may be associated with changes in gene editing. Here, we have conducted the largest genome-wide human brain study to date, creating a resource which identifies RNA editing events in 1865 samples across 9 brain regions from 1074 subjects; they are being made available through the AD Knowledge Portal website where our source RNA-seq data is already available  and the C-to-T and G-to-A types (5%). Fig. . We have). The mean RNA editing level per individual is 37.5% for ROSMAP subjects, 42% for MSBB subjects, and 38% for MAYO subjects. However, there may be variation in the average editing level among brain regions, as we see (1) a greater editing rate in the posterior cingulate cortex (PCC) than in the anterior cingulate cortex (AC) and dorsolateral prefrontal cortex (DLPFC) in the ROSMAP multi-region study, (2) a reduced editing rate in BM36 than in the other 3 brain regions  in the MSBB study, and (3) a greater level of editing in cerebellum (CBE) than in the temporal cortex (TCX) in the MAYO dataset. In terms of the total number of frequent RNA editing events called within each subject, there may be also be a region-specific difference, showing, in general, less editing events in PCC, BM22, and TCX compared to the other regions within each of the datasets   Fig. . This isns Table .Fig. 3DiP value threshold as ≤1.49 × 10−6 . Figures PECAM1 and TAOK3) showing >30% higher editing levels in AC compared to DLPFC, two genes (ACER3 and RP11-51713.2) showing a > 30% reduction in editing levels in PCC compared to AC, two genes (SMU1 and PEX13) showing >30% higher editing levels in TCX compared to cerebellum, and nine genes  showing >30% reduction in editing levels in TCX compared to CBE.We conducted linear mixed models to identify those editing events with a statistically significant difference in editing levels between 2 brain regions within each study after adjusting for biological  and technical confounding factors . Across the nine paired datasets, we tested the 33,641 frequent editing events that exist in at least 2 regions, yielding a Bonferroni-corrected significance 9. So, we explored two types of functions: (1) the cis-effects on the expression levels of the edited genes in transcripts and proteins and (2) the changes in the amino acid sequence for those re-coding RNA editing events, which can alter the coding of an amino acid. In order to remove the potentially inflated correlations between the level of % edited reads and the total reads of the genes/transcripts, we used the binary variable of RNA editing event (yes = 1 and no = 0) for the analysis. We focused on the 635 ROSMAP participants with unpaired data. There were three genes with genome-wide significant cis-effects (BETA > 3 and P < 2.8 × 10−6), which are ORAI2, APOL1, and PSMD12   for their association with protein expression for the protein that the target gene encodes  Fig. , left. Hdes Fig. , left. Ides Fig. , middle.UTR Fig. , right wn = 247, 84%) are found at low frequency in the RNA data, in less than 10% of our subjects, and only 3 of these low-frequency events were also identified in the ROSMAP proteomic dataset. The remaining 47 re-coding events (16%) are found at higher frequency (≥10%) in the RNA data, and 6 out of these 47 events were also identified in the proteomic dataset. More specifically, the 294 re-coding events found in the RNA data are predicted in silico to yield 459 unique tryptic peptides. From the 373 unique low-frequency predicted tryptic peptides, 4 peptides were detected within the proteomic dataset. From the 47 frequent re-coding events leading to 86 unique predicted peptides, 8 peptides were detected in the proteomic dataset. As a result, there are 13 unique tryptic peptides encoded by 10 RNA re-coding events identified in the proteomic datasets. The detailed annotation, RNA and peptide sequence for these hits are presented in Table In order to study the function of re-coding RNA editing events which change the amino acid sequence, we searched for the existence of the predicted amino acid sequence in two datasets: (1) the 171 ROSMAP subjects with both RNA-seq and TMT proteome-wide profiles of the same region, and (2) the 201 subjects in the Banner study who have proteomic data only. With the 171 ROSMAP subjects Fig. , left, wADAR genes  and higher expression of ADAR3 in AD cases (P = 0.01), while mild cognitive impairment (MCI) subjects are in the middle and the cognitively non-impaired controls have the highest expression of ADAR2 and lowest expression of ADAR3, a potential RNA editing inhibitor4. For the composite value including all ADARs (ADAR1 + ADAR2-ADAR3) as used in prior studies4, AD patients have the lowest value, while MCI subjects are in the middle and controls have the highest value (P = 0.03).We at first evaluated the relation of AD and the level of expression of the three nes Fig.  across tP ≤ 1.2 × 10−6). With the ROSMAP unpaired dataset only, no event passed the Bonferroni-corrected genome-wide P value threshold, but there are 55 events which met a suggestive threshold of association with P values ≤ 1 × 10−3. These 55 sites were followed up with a Stage II meta-analysis that includes the Stage I ROSMAP unpaired samples as well as samples from three independent sets of subjects: 142 BM44 samples from the MSBB, 229 TCX samples from the MAYO, and 68 DLPFC samples from ROSMAP participants with multi-region ROSMAP data. The BM44 and TCX region data were selected as being the closest available data to DLPFC which is only available in the ROSMAP subjects included in Stage I. The results of this meta-analysis are not inflated , MCUR1 , SOD2 , ORAI2 , HSDL2 , and PFKP . The regional plot, correlation matrix of different RNA editing events in the region, and the forest plot of the effects in each dataset for these six loci are presented in Figs. GPRC5B was significant , and the events in SYT11, MCUR1, and SOD2 remained significant. Directionality is fairly consistent, with greater prevalence of the alternative, edited allele in the context of AD.We then checked for evidence of association between the editing levels at individual RNA editing sites and a diagnosis of AD dementia transcriptome-wide. In Stage I of the analysis Fig. , we usedP values , and they have significant associations with the expression of at least one isoform of their corresponding gene . Perhaps more functionally relevant, the level of the SYT11 editing event has a significant negative association with its protein levels   and GPRC5B  have marginal levels of association that deserve further evaluation. The protein level of ORAI2 was not available, and none of the remaining RNA editing event showed significant association with their corresponding protein levels. We derived 7 principal components (PCs) from the top 7 RNA editing events related to AD. Like the individual editing events, these PCs were also showing significant associations with the expression of genes, isoforms, and proteins  Figs.  and 6c, ins Fig. . OverallADAR genes influence the likelihood of editing at a given site, we also evaluated whether these top 7 RNA editing events have significant associations with the expression of one or more of the ADAR genes . This suggests that change in ADAR level(s) may be part of the mechanism of the AD-related changes in editing levels.Since the level of expression of nes Fig. . SeveralP ≤ 1.2 × 10−6. Four RNA editing events were significantly associated with PHFtau aggregates: ORAI2 , KCNIP2 , GPRC5B , and YPEL1 . There is one significant RNA editing event associated with the amount of β-amyloid aggregates, which is located in AC174470.1 . There were also two events which showed significant associations with neuritic amyloid plaque burden: ORAI2  and CABP1 . Finally, two events were significantly associated with the slope of aging-related global cognitive decline: AC174470.1  and MUM1 .In secondary analyses, we conducted additional transcriptome-wide evaluations for association with neuropathological traits and aging-related cognitive decline in the discovery dataset of 635 ROSMAP participants with DLPFC data Fig.  with theORAI2 RNA editing event (chr7: 102096952) is therefore associated with multiple traits  and PHFtau accumulation (P = 4.72 × 10−8); it is also close to genome-wide significance with cognitive decline (P = 3.07 × 10−6) and has a more modest association with β-amyloid (P = 7.31 × 10−4). We further found a borderline significant effect of the ORAI2 editing event on the protein expression of MAPT (P = 0.068)  Fig. . Thus, we tested .https://www.synapse.org/#!Synapse:syn22335108) and have identified those present in the aging brain. Among the small proportion of sites where the editing event alters the coding sequence of a protein (0.2% of sites), we were able to recover some of the alternative alleles at the protein level in the same individuals as well as in an independent proteomic dataset, extending prior observations that such RNA editing events have a downstream effect. However, most of the proposed re-coding events were not observed at the protein level. Our sample size also allows us to perform an association analysis of RNA editing events in relation to AD and AD-related traits. Importantly, we find reproducible alterations of specific RNA editing events in the context of AD. This is similar to our recent report of reproducible splicing alterations in AD10 and the broader narrative of specific disruptions in RNA maturation11 and in the epigenome in relation to AD12. Our list of top genes associated with AD does not overlap with that from the genetic studies of AD, and none of the RNA editing events located in the AD relevant genes reported by the genetic studies reached a genome-wide significance threshold  the ORAI2 3′-UTR editing event which is associated with multiple diagnostic and intermediate traits, allowing us to propose where, in the causal chain of events leading to AD, RNA editing may have an effect for this gene.We have conducted a systematic, transcriptome-wide evaluation of RNA editing in a large multi-region dataset derived from human cortex and cerebellum. With this sample size, we double the current reference of sites where RNA editing takes place in the human brain  channels by mediating store-operated Ca2+ entry (SOCE) in many cell types, including murine naive T cells, neutrophils, astrocytes, dendritic cells, and macrophage as well as human fibroblasts13. The neuronal SOCE pathway is important to multiple neurodegenerative diseases such as AD, Parkinson disease, and Huntington disease14 because of its regulation of synaptic plasticity. Our results emphasize the “Calcium hypothesis” of AD15 by suggesting that the frequency of RNA editing events in ORAI2 may shift Ca2+ homeostasis in synapses in a way that contributes to the accumulation of PHFtau and the downstream effects on cognitive decline; in vitro work on neuronal function will be necessary to explore these hypotheses.SYT11 encodes synaptotagmin XI, which regulates phagocytosis and cytokine secretion in macrophages and interacts with parkin, a protein found in the core of Lewy bodies. The top SYT11 AD-related editing event we found  was reported previously16 in a lymphoblastoid cell line (LCL) with a comparable mean level of editing  (5.89% in our brain samples vs. 7.9% in LCL). Besides its AD association, we further present evidence that this 3′UTR editing event has a downstream effect on protein abundance, which is in line with the proposed function of 3′-UTR editing events17. We found that those subjects carrying the editing event have a significantly lower protein level of SYT11, perhaps because of reduced RNA stability, or tRNA codon bias. Our RNA editing study links SYT11 to the narrative of altered vesicular formation that has emerged from AD genetic studies, and to potential synapse loss, which is the strongest correlate of dementia18.SOD2, MCUR1, and PFKP. SOD2 encodes superoxide dismutase 2, a mitochondrial matrix enzyme that scavenges oxygen radicals. The role of SOD2 in AD is controversial with supportive evidence in animals19 but not in protein data from humans20. The SOD2 RNA editing event  is significantly associated with AD status in all four datasets  GPRC5B encodes member B of the family C of the G protein-coupled receptor superfamily. The neuronal enrichment of the expression is controversial on the mRNA level25, but consistent on the protein level with the highest levels in the neocortex and hippocampus26. Murine Gprc5b has been shown to impact synaptic formation and neurogenesis27 and rat Gprc5b may be related to microglia activation28. In addition, our finding regarding MUM1  is noteworthy for its association with cognitive decline. Rats with intracerebroventricular injection of β-amyloid resulted in cognitive impairment and imbalance between IRF4 and IRF5, which was rescued by M2 macrophage transplantation29. An amyloid proteinopathy model has also been reported to harbor microglia with an interferon response30. However, evidence supporting a role for interferon responses in human AD has not emerged very strongly so far, although more generic anti-viral responses have been reported31. IRF4 is therefore interesting in this sense, and focuses attention on the interferon pathway in human AD. Our findings may indicate the relevance of microglia to AD pathologies with an intermediary role of RNA editing level.A couple of other genes are also significant in our meta-analysis: (1) 32. The low frequency of observation of peptide evidence for coding changes due to RNA editing in ROSMAP cases with paired RNA sequencing may reflect sparse, dissimilar editing events for the specific patient proteomes combined in TMT batches of mass spectrometry-based proteomics. The batch-wise mixtures of individuals in TMT-based quantitative proteomics dilute any peptide found in only one or a small subset of samples within a TMT batch, warranting development of additional approaches with better sensitivity for RNA-editing re-coded peptides at the individual level, e.g., selected reaction monitoring. Finally, we elected not to tally, analyze, or comment on the role of infrequent editing events (frequency < 10%) as these are more likely to include sequencing errors.Although we have a large sample size, we are limited by not having entirely identical brain regions for the meta-analysis ; however, these are all neocortical regions. The study may also have a bias towards aged samples. Further, our study still has moderate statistical power, illustrated by the fact that more sites emerge from the meta-analysis. The large number of editing events in the cerebellum, which is essentially devoid of pathology in AD suggests that many of these events may be inconsequential in AD pathology. We also did not adjust for cell-type proportion of the brain tissues in our analyses. Post hoc checking for the top disease-associated RNA editing events, their disease associations were attenuated to some extent but remained significant after adjusting for the estimated proportion of neurons derived from a neuron-specific module of co-expressed cortical genes. This attenuation may be partially driven by the smaller sample size available for this neuron-adjusted analysis or the potential confounding effects of neuron proportion. In addition, total read counts do not affect the results. Our autopsy-based, cross-sectional study design also prevents us from formally demonstrating causality. Furthermore, the mass spectrometry-based proteomic methodologies have technical factors which hinder the complete quantification and identification across samples, and they are subject to ion suppression and interference such that that there is a possibility of no identification of a peptide present in the highly complex input peptide mixture for total brain proteome. This is consistent with the idea that absence of evidence for a peptide in mass spectrometry does not allow the inference or an interpretation that such a result is evidence of absence of that peptide in the cortex. And, the reference proteomic database of 17,112 peptide sequences incorporated the situation when multiple RNA editing events happen at the same time but did not include consideration of genetic variation, as such an inclusion would inflate false discovery due to increasing numbers of decoy peptides and a more intense computational requirementhttps://www.synapse.org/#!Synapse:syn22335108. We also identified 7 AD-associated RNA editing events that meet a rigorous threshold of transcriptome-wide significance, and we elaborate the role of two of them: (1) ORAI2 in the accumulation of Tau pathology that contributes to the cascade of events leading to AD and (2) SYT11 in potential synaptic disruption from the decreased protein levels that may contribute to AD dementia. Our findings need to be replicated and validated in future experiments with model systems.In conclusion, we have significantly expanded the reference of RNA editing sites where editing occurs in the brain, and we have made this reference available through the AD Knowledge Portal data sharing platform: 33, (3) the Mount Sinai Brain Bank (MSBB) RNA-seq project34, and (4) the Mayo clinic (MAYO) RNA-seq project35. Informed consent was received from all participants or their representatives, and sample collections and data processing was approved by the institutional review board (IRB) of each cohort. This study was approved by the IRB of Columbia University (AAAR4962). All the donors of the human tissue used in this study provided informed consent where they agreed to donate their postmortem brains and antemortem clinical data related to the study.We have assembled RNA sequencing (RNA-seq) datasets derived from 1865 human aging brain samples covering 9 different brain regions from 1074 unrelated subjects. The RNA-seq datasets included in the current study come from the (1) Religious Orders Study or the Rush Memory and Aging Project (ROSMAP) multi-region project, (2) ROSMAP RNA-seq project33, dementia-free subjects were enrolled into the study with detailed longitudinal measurements of cognitive functions and their postmortem brains were collected for measurements of neuropathologies and molecular omics including RNA-seq and whole-genome sequencing (WGS). ROSMAP RNA-seq project includes postmortem dorsal-prefrontal cortex (DLPFC) samples from 635 unrelated participants in the ROSMAP longitudinal study. ROSMAP multi-region project includes 68 unrelated subjects with samples from all three regions, DLPFC, anterior cingulate (AC), and posterior cingulate (PCC). MSBB: Briefly34, the Mount Sinai/JJ Peters VA Medical Center Brain Bank (MSBB-Mount Sinai NIH Neurobiobank) cohort included/excluded subjects with stringent criteria to represent the full spectrum of cognitive and neuropathological disease severity in the absence of discernable non-AD neuropathology. The study holds over 2040 well-characterized brains, which were profiled with Brodmann areas. For the current study, MSBB RNA-seq project34 includes 142 subjects with samples from all four regions: BM10 , BM22 , BM36 , and BM44 , which were shown to be the top 4 most vulnerable regions to AD34. MAYO: The Mayo RNA-seq Study37 includes North American Caucasian subjects with neuropathological diagnosis of AD, progressive supranuclear palsy (PSP), pathologic aging (PA), or elderly controls without neurodegenerative diseases, who have donated in total 278 cerebellar cortex  and 278 temporal cortex samples , of which 238 were from the same donor, while the remaining had only one of the two tissue region samples. All AD and PSP subjects were from the Mayo Clinic Brain Bank, and all PA subjects were obtained from the Banner Sun Health Institute. Thirty-four control CER and 31 control TCX samples were from the Mayo Clinic Brain Bank, and the remaining control tissue was from the Banner Sun Health Institute.ROSMAP: In briefAt every assessment, the clinical diagnosis of cognitive status is determined in a three-stage process  based on a uniform, structured, clinical evaluation including a battery of 19 cognitive tests per subject. Clinical diagnosis of dementia and clinical AD are based on criteria of the joint working group of the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer’s Disease and Related Disorders Association (NINCDS/ADRDA). The diagnosis of AD requires evidence of a meaningful decline in cognitive function relative to a previous level of performance with impairment in memory and at least one other area of cognition. Diagnosis of MCI is rendered for persons who are judged to have cognitive impairment by the neuropsychologist but are judged to not meet criteria for dementia by the clinician. Persons without dementia or MCI are categorized as having no cognitive impairment (NCI).Clinical dementia rating scale (CDR) was conducted for assessment of dementia and cognitive status for the 6 months preceding death in a multi-step consensus-dependent approach to derive the following scores: CDR = 0 for no cognitive deficits, CDR = 0.5 for questionable dementia, CDR = 1.0 for mild dementia, CDR = 2.0 for moderate dementia, and CDR = 3.0–5.0 for severe to terminal dementia. The longitudinal neuropsychological assessment results were also considered if available in deriving the final consensus CDR score. For the current study, subjects with CDR = 0 are normal controls, CDR = 0.5 are MCI, and CDR ≥ 1 are AD patients.35. The PA and PSP subjects were excluded from the analysis of the disease associations in the current study.The diagnosis of AD is with definite diagnosis according to the NINCDS-ADRDA criteria and had Braak NFT stage of IV or greater, while the normal controls had Braak NFT stage of III or less, CERAD neuritic and cortical plaque densities of 0 (none) or 1 (sparse) and lacked any of the pathologic diagnosis of AD, Parkinson’s disease, Lewy body dementia, vascular dementia, PSP, motor neuron disease, corticobasal degeneration, Pick’s disease, Huntington’s disease, frontotemporal lobar degeneration, hippocampal sclerosis, or dementia lacking distinctive histology33. Approximately 100 mg of frozen DLPFC were sectioned while still frozen and shipped on dry ice overnight from the RADC to the Broad Institute, where these sections were partially thawed on ice prior to dissection with a scalpel to separate the gray from the white matter and vasculature, resulting in 50–100 mg of gray matter were used to extract RNA.One hemisphere is cut into coronal slabs and frozen; the other hemisphere is fixed in 4% Paraformaldehyde34. Each whole-brain specimen was divided midsagittally. The left half of the brain was cut into 0.8 cm coronal slabs which were flash frozen and kept at −80 °C. For the 4 brain regions included in the current study , procedures of dissection, pulverization and aliquotation were kept −80 °C from the fresh frozen, never-thawed 0.8 cm thick coronal tissue blocks. The dissection used a dry ice cooled reciprocating saw and the pulverization used liquid nitrogen cooled mortar and pestle. The pulverized powder is distributed into 50 mg aliquots for each region, which were barcoded and stored at −80 °C until DNA, RNA or protein isolation.Details were described before35. A hemibrain or frozen slabs were partially thawed prior to sectioning. Samples were obtained from both the cerebellar cortex (CER) and superior temporal gyrus (TCX) where both were available or from one of the two available regions. White matter and leptomeninges were sectioned away and gray matter was kept for subsequent RNA extraction.All brain regions were obtained from frozen sectionsThe RNA from the gray matter of the DLPFC samples were extracted using Qiagen’s miRNeasy mini kit (cat# 217004) and the RNase-free DNase Set (cat# 79254). The quantity and quality of the extractions were conducted with Nanodrop and Agilent Bioanalyzer. We sequence those samples if their RIN > 5 and RNA quantity >5 μg.Total RNA extractions were conducted in two RNA preparation cores in Mount Sinai, and two cores used the same kits and modified protocol. RNeasy Lipid Tissue Mini Kit from Qiagen (cat#74804) were used to extract the total RNA from the brain tissues. A slightly modifiable protocol based on manufacturer’s protocol  was used, and the detailed modifications include: (1) all brain tissues (pulverized) were kept on dry ice before adding QIAzol Lysis Reagent, (2) tissues were suspended in the lysis reagent by vortexing with tubes placed on ice, and (3) the tissues were homogenized using a Tissue Ruptor  at full speed for 20–30 s.RNA were extracted from the brain samples via Trizol/chloroform/ethanol method, followed by DNase and Cleanup of RNA using Qiagen RNeasy Mini Kit and Qiagen RNase-Free DNase Set. The Agilent RNA 6000 Nano Chip  with the Agilent 2100 Bioanalyzer was used to estimate the quantity and quality of the extracted37.RNA from all the samples. Only those samples with RIN ≥ 5.0 were sequencedRNA-seq library was prepared by the Genomics Platform at the Broad Institute using the strand-specific dUTP protocol with poly-A selection. This method begins with poly-A selection followed by first strand-specific cDNA synthesis, and then uses dUTP for second strand-specific cDNA synthesis followed by fragmentation and Illumina adapter ligation for library construction. Those samples with RIN > 5 and RNA quantity >5 μg were followed up with sequencing on the Illumina HiSeq with 101 bp paired-end reads. The first 12 samples in the “batch 0” included 2 males and 2 females from each of the three clinical AD status  and their sequence reached coverage of 150 M reads which act as a deep coverage reference. The remaining samples (batch 1 to 6 and 8) were sequenced with coverage of 50 M reads. Samples with similar RIN were pooled together to construct sequence libraries (from batch 1 to 6) because varying RIN scores leads to a larger spread of insert sizes during library construction and uneven coverage distribution throughout the pool. We noticed that samples with lower RIN scores between 5 and 6 had more adapter contamination. We have a later additional samples (batch 7) and the multi-region project samples were run with a modified low-input-quantity requirement (only 250 ng of input RNA) approach of the Illumina TruSeq method to be strand specific and also with larger insert sizes, which construct a library closely resembles the library obtained by the dUTP method. Sequencing was conducted using the Illumina HiSeq2000 with 101 bp paired-end reads for a target coverage of 50 M paired reads.Illumina TruSeq RNA Sample Preparation Kit v2  was used to construct RNA-seq library. The enrichment of the coding and long non-coding RNA was achieved by depletion of rRNA from total RNA using the Ribo-Zero rRNA Removal Kit (Human/Mouse/Rat) . Random hexamer-based synthesized cDNA was end-repaired and ligated with appropriate adaptors for sequencing. The library then underwent size selection and purification using AMPure XP beads . During PCR amplification, the appropriate Illumina recommended 6 bp barcode bases are introduced at one end of the adaptors before loading onto the sequencer, Bioanalyzer  and Qubit fluorometry  were used to measure the size and concentration of the libraries. Sequencing was run on the Illumina HiSeq 2500 System with 100 bp single-end reads, according to the standard manufacturer’s protocol .36. The library construction and sequencing were conducted in the Mayo Clinic MGF Gene Expression Core and Sequencing Core. RNA-seq libraries were prepared using the TruSeq RNA Sample Prep Kit , and the resulting library concentration and size distribution was determined on an Agilent Bioanalyzer DNA 1000 chip. All samples were run in triplicates using barcoding (3 samples per flowcell lane). Sequencing was conducted on the Illumina HiSeq4000 platform with 101 bp paired-end reads35.The RNA-seq samples were randomized across flowcells, taking into account age at death, sex, RIN, Braak stage, and diagnosisFor the unpaired 635 individuals with DLPFC samples, we applied trimming at first to trim out those low-quality bases (Q10) from beginning and end of each read and the reads of adapter and rRNA. The alignment to the human reference genome hg19 build was conducted using Tophat (v2.1.1) with a non-gap aligner (Bowtie1). For the ROSMAP paired multi-region RNA-seq project, we followed the same data processing procedures as the RNA-seq reprocessings of MSBB and MAYO described later in order to be consistent. We aligned to the reference genome of GENCODE24(GRCh38) using STAR (v2.3.0e) with “twopassMode” set as “Basic”. Picard (v2.17.4) functions of “CollectAlignmentSummaryMetrics” and “Collect RnaSeqMetrics” were used to collect quality metrics and sequencing covariates for each sample.syn9702085. In brief, the aligned BAM files from each study mentioned above were converted back to the FASTQ files using Picard SamToFastq function. Picard SortSam function was used for the MAYO paired-end libraries to ensure the correct order of R1 and R2 in the intermediate SAM file before the conversion back to FASTQ files. For the MSBB single-end library, the converted FASTQ was concatenated to the unmapped reads FASTQ and then underwent sorting. The alignment of the converted FASTQ files were conducted using STAR (v2.3.0e) with “twopassMode” set as “Basic” and the reference genome was GENCODE24 (GRCh38). Picard functions of “CollectAlignmentSummaryMetrics” and “Collect RnaSeqMetrics” were used to collect quality metrics and sequencing covariates for each sample. We downloaded the re-processed BAM files of MSBB (https://www.synapse.org/#!Synapse:syn8540822) and MAYO , while the MAYO RNA-seq reads were aligned using the SNAPR software, an RNA sequence aligner based on SNAP, using GRCh38 reference and transcriptome GRCh38.77. SNAPR filters fastq reads by Phred score (>80% of the read must have a Phred score > = 20) and simultaneously aligns each read (or read pair) to both the reference genome of GRCh38 and transcriptome of GRCh38.77. Alignment with SNAPR starts with the creation of hash indices built from both a reference genome GRCh38 and transcriptome GRCh38.77. The best alignment is written to a sorted BAM file with read counts simultaneously tabulated and written for each sample. Read counts are given by gene ID and transcript ID (two separate files). Mayo Clinic RNA-seq data was previously tested for the read counts generated by SNAPR vs. the read counts generated by HT-Seq and found to be very comparable. Considering the comparability, we downloaded the cross-consortia reprocessed RNA-seq bam files of MSBB (syn8540822) and MAYO . The details of the reprocessing are described on the Synapse platform with Synapse ID of 38 applied in 10 parallel threads based on the previously described paired-end aligned transcriptome bam files generated using STAR (v2.3.0e)39 against the reference gene annotations of GENCODE24 (GRCh38). The estimated values of transcripts per million (TPM) were used to represent the gene expression levels.The transcriptomic gene expressions were estimated by the RSEM (v1.2.31)https://www.synapse.org/#!Synapse:syn8691099.1; temporal cortex of MAYO: https://www.synapse.org/#!Synapse:syn8690799.1; and cerebellum of MAYO: https://www.synapse.org/#!Synapse:syn8690904.1). The detailed descriptions of the methods were described online  (https://www.gencodegenes.org/human/release_24.html) using STAR by setting “quantMode” as “GeneCounts”.The gene expressions of the transcriptome for MSBB and MAYO RNA-seq were downloaded from Synapse platform (MSBB: 38 according to the reference gene annotation of GENCODE v14 in hg19 build of human genome reference (https://www.gencodegenes.org/human/release_14.html). Fragments Per Kilobase of transcript per Million mapped reads (FPKM) values were the final output of our RNA-seq pipeline. Normalizations of the gene expression levels were conducted using quantile normalization within each batch followed with Combat normalization with only “Batch” covariate to remove batch effect (https://www.bu.edu/jlab/wp-assets/ComBat/Abstract.html). The unadjusted gene expressions of ADARs  were analyzed for their associations with clinical AD status  using the general linear regression models. For the top RNA editing events, we further analyzed their associations with ADARs and their annotated gene and isoforms by the general linear regression model with the lever of the top RNA editing events  were treated as exposure variable and the ADARs gene expression and the gene/isoform expression of their annotated gene were treated as dependent variable with the covariates of age at death, sex, RIN score, postmortem interval, study (ROS or MAP). The total available sample size of the normalized gene expression files is 635 while it is 542 for the file of isoform expression. The normalized FPKM values were transformed by taking log2 values for the gene expression file and those subjects with log2(FPKM) values > 10 standard deviations were set as 0. In order to focus on those isoforms with robust expression values, we removed from the analysis of those isoforms with normalized FPKM > 0 values in <100 subjects.We estimate the expression levels of genes and isoforms using RSEM (v1.2.31)ROSMAP unpaired DLPFC dataset: The RNA editing events were called by UnifiedGenotype tool from the Genome Analysis Toolkit (GATK) (v3.6) based on the Tophat (v2.1.1) aligned BAM files. The reference genome sequence and dbSNP were with hg19 build. The option of “ALLOW_N_CIGAR_READS” was turned on and all the other options are with default settings. Only the editing events with A to I conversion were included.https://www.sevenbridges.com/gatk-best-practice-rna-variant-calling/). Start with the STAR aligned BAM files to the GRCh38 reference genome build, we at first used Picard to add read groups, sort, mark duplicates, and create index with functions of “AddOrReplaceReadGroups” and “MarkDuplicates”. Then, we used GATK (v3.6) tool of “SplitNCigarReads” to split reads into exon segments and hard-clip any sequences overhanging into the intronic regions, which is more appropriate to the RNA-seq reads and reduce false variant callings derived from the mis-alignment of the exonic reads to the overhanging intronic regions. In order to solve the differences in MAPQ value meanings between STAR and GATK, we used GATK’s “ReassignOneMappingQuality” function to assign those STAR yielded MAPQ of 255 (“unknown”) with 60. We did not conduct any Indel realignment. The editing calling is conducted with GATK “HaplotypeCaller” tool with arguments of “dontUseSoftClippedBases” and “stand_call_conf” set as 20. Only the editing events with A to I conversion were included.All paired datasets : We followed the best practice of RNA editing calling pipeline recommended by Broad Institute (40.Event-level QC: We have applied posterior filters to filter out those RNA editing events with (1) total reads less than 20, and (2) alternative reads less than 5, and (3) frequency less than 10%, and (4) those overlapping with the DNA variants based on the WGS data across the subjects within ROSMAP, MSBB, and MAYO, where some subjects do not have the RNA-seq data to be involved in the study. Our posterior filters are considered to be more conservative than the recommended filters34. In brief, we have removed those suspicious or spurious samples by genetic concordance checks across different types of sequencing data . For duplicated samples, the sample with higher total reads were selected36. For MAYO RNA-seq project, the samples identified as PCA outliers and sex-mismatches were removed.Sample-level QC: We at first applied study-specific QC metrics within each study. For the ROSMAP multi-region study, we filtered two samples with less than 3 standard deviations from the mean number of total reads and aligned reads across all the samples in the study. For MSBB samples, the details were described previouslySubject-level QC: Only selecting those having samples from all different brain regions within each paired dataset.We have applied three-steps QC procedures: (1) event-level, (2) sample-level, and (3) subject-level.https://genome.ucsc.edu/cgi-bin/hgLiftOver, and then we merged the result file with all the other editing events files called within all the other datasets into a master file. We used ANNOVAR annotate_variation.pl (downloaded on 16 April 2018) with reference genome sequence of hg38 and gene annotation of ENSEMBLE to annotate the potential functions of called RNA editing events, including where are those editing events located relative to the gene , and which are the closest gene(s). We annotate our called RNA editing events as “reported” or “not reported” based on the Rigorously Annotated Database of A-to-I RNA Editing (RADAR) database (version 2 Human)41 and GTEx publication4, which were also transformed to hg38 by the same procedure mentioned above using UCSC liftOver tool. The RADAR version 2 Human database included 2,576,277 editing events reported by the 24 peer-reviewed publications of the RNA editing events in humans from 1991 to 2014, and removed ~3000 human genomic single nucleotide polymorphisms (SNPs) from the database. GTEx4 reported 408,514 RNA editing events existing in 53 body sites from 552 individuals. Those editing events not reported by the above two resources were annotated to be “not reported” ones.We have lifted over the editing events called within the ROSMAP unpaired dataset to hg38 using the liftOver tool and relevant human chain file (hg19ToHg38.over.chain.gz) downloaded from UCSC genome browser  and loaded onto an Agilent ZORBAX 300Extend-C18 column (2.1 mm × 150 mm with 3.5 µm beads). An Agilent 1100 HPLC system was used to carry out the fractionation. Solvent A consisted of 0.0175% (vol/vol) NH4OH; 0.01125% (vol/vol) formic acid; 2% (vol/vol) acetonitrile and solvent B consisted of 0.0175% (vol/vol) NH4OH; 0.01125% (vol/vol) formic acid; 90% (vol/vol) acetonitrile. The sample elution was performed by a 58.6 min gradient with a flow rate of 0.4 ml/min. The gradient goes 100% solvent A for 2 min, from 0% to 12% solvent B in 6 min, from 12% to 40% over 28 min, from 40% to 44% in 4 min, from 44% to 60% in 5 min, and then kept 60% solvent B for 13.6 min. A total of 96 individual fractions were collected across the gradient and subsequently pooled by concatenation43 into 24 fractions and dried to completeness by SpeedVac.High-pH fractionation was performed as essentially described32 with slight modifications. Peptide eluents were separated on a self-packed C18  fused silica column ; New Objective, Woburn, MA) by an Dionex UltiMate 3000 RSLCnano liquid chromatography system (ThermoFisher Scientific) and monitored on an Orbitrap Fusion mass spectrometer (ThermoFisher Scientific). Sample elution was performed over a 180 min gradient with flow rate at 225 nL/min. The gradient goes from 3% to 7% buffer B in 5 min, from 7% to 30% over 140 min, from 30% to 60% in 5 min, 60% to 99% in 2 min, kept at 99% for 8 min and back to 1% for an additional 20 min to equilibrate the column. The mass spectrometer was set to acquire in data-dependent mode using the top speed workflow with a cycle time of 3 s. Each cycle consisted of 1 full scan followed by as many MS/MS (MS2) scans that could fit within the time window. The full scan (MS1) was performed with an m/z range of 350–1500 at 120,000 resolution (at 200 m/z) with automatic gain control (AGC) set at 4 × 105 and maximum injection time 50 ms. The most intense ions were selected for higher-energy collision-induced dissociation (HCD) at 38% collision energy with an isolation of 0.7 m/z, a resolution of 30,000 and AGC setting of 5 × 104 and a maximum injection time of 100 ms.All fractions were resuspended in equal volume of loading buffer  and analyzed by liquid chromatography coupled to mass spectrometry essentially as describedn = 635). The Sequest HT search engine was used and parameters were specified as: fully tryptic specificity, maximum of two missed cleavages, minimum peptide length of 6, fixed modifications for TMT tags on lysine residues and peptide N-termini (+229.162932 Da) and carbamidomethylation of cysteine residues (+57.02146 Da), variable modifications for oxidation of methionine residues (+15.99492 Da), and deamidation of asparagine and glutamine (+0.984 Da), precursor mass tolerance of 20 ppm, and a fragment mass tolerance of 0.05 Da for MS2 spectra collected in the Orbitrap. Percolator was use to filter peptide spectral matches (PSM) and peptides to a false discovery rate (FDR) of less than 1%. Following spectral assignment, peptides were assembled into proteins and were further filtered based on the combined probabilities of their constituent peptides to a final FDR of 1%. In cases of redundancy, shared peptides were assigned to the protein sequence in adherence with the principles of parsimony. Reporter ions were quantified from MS2 scans using an integration tolerance of 20 ppm with the most confident centroid setting. The MS/MS spectra of predicted edited peptides were manually annotated . MS2 spectra were searched against the UniProt Knowledgebase (UniProtKB) containing both Swiss-Prot and TrEMBL human reference protein sequences , plus 245 contaminant proteins. The database was also augmented with 17,112 translated entries for proteoforms from all possible within-proteoform combinations of the RNA editing events called in RNA-seq datasets of ROSMAP DLPFC samples . The algorithm implements iterations of the below equation.2-transformed, and each log2(ratio) is adjusted by subtraction of sample (column)-wise median log2(ratio) for all proteins. Then, ratios are anti-logged and multiplied by the protein (row)-wise geometric mean extracted before Eq. n = 2) in each TMT batch, and the second term to all individual case samples .Normalized abundances for 250,076 peptide modification forms and 229,871 unique peptide sequences from Proteome Discoverer output were considered as an abundance matrix, of which 20 peptides corresponded to 24 editing sites affecting protein coding which were confirmed to be absent in the core database without RNA-edited entries, and manually confirmed to contain the expected variant amino acids per the edited database entries. Batch artifact removal on the full data was performed using an in-house script that implements a median polish algorithm for removing technical variance  from a two-way complete abundance-sample data table as originally described by Tukey45. Twenty-one of 360 case samples were flagged as outliers with sample connectivity beyond 3 standard deviations from the mean. Bootstrap regression of the remaining 339-case-sample TMT reporter abundance matrix was performed, explicitly modeling case status category while removing covariation with age at death, gender, and PMI. Given the relative quantitation peptide data we have, it is not possible to calculate edited/total abundance, where summing total abundance from edited and unedited peptides is not correct due to differential ionization efficiency of the distinct peptides. So, we calculated the value of edited/non-edited ratio  followed by 10 data-dependent MS/MS scans . MaxQuant v1.5.2.8 with Thermo Foundation 2.0 was used to analyze the raw data for the 201 samples and searched against the same database as described above. Quantitation of proteins was performed using the label-free quantification (LFQ) intensities given by MaxQuant46.This study includes 201  postmortem brain tissue samples of the DLPFC from the Banner Sun Health Research Institute’s Brain and Body Donation Program. Detailed methodologies are described on the Synapse platform  according to the downloaded Synapse files of “MSBB_RNAseq_covariates.csv” (syn6100548) and “MSBB_RNAseq.WES.WGS_sample_QC_info.csv” (syn12178047). We transformed the variable of age at death from character to numeric by changing their values of “90+” to 90. We have notified duplicated samples of the same brain region from the same individual but sequenced twice in different batches. For these duplicates, we selected the batch with higher total reads. If the selected batch is with missing value of their RIN score, we assign the non-missing RIN score from the lower read batch to the higher read batch. We only keep subjects who have bam files from all 4 brain regions. In our study, we include 568 bam files from 142 subjects who has passed QC and with corrected phenotype information. MAYO: For each region , we used the sequencing covariate files and then removed the subjects mentioned in the QC files. For the cerebellum, the sequencing covariate file is “MayoRNAseq_RNAseq_CBE_covariates.csv” (syn5223705) and the QC file is “MayoRNASeq_RNASeq_CBE_QCdetails.txt” (syn6126119). The filesets of the temporal cortex include: “MayoRNAseq_RNAseq_TCX_covariates.csv” (syn3817650) and “MayoRNAseq_RNAseq_TCX_QCdetails.txt” (syn612611) for the sequencing covariate and QC files, respectively. Further, we excluded those subjects with bam files from only one region. We transformed the variable of age at death from character to numeric by changing their values of “90 + ” to 90. As are result, we have included 458 samples from 229 subjects into our current study.We have ROSMAP phenotype files through Rush Alzheimer Disease Center (RADC)In order to compare the potential regional-differences of RNA editing patterns across different brain regions, we have conducted four analyses by: (1) counting the number of the same editing events co-exist in more than 2 regions within the same study; (2) comparing the distribution of the individual-based overall level of all the called frequent RNA editing events across brain regions within the same study, which was calculated by dividing the sum of the % edited reads for all the RNA editing events by the number of editing events called within that individual; (3) comparing the total number of called frequent RNA editing events within each individual across different brain regions within the same study; (4) comparing the level of each RNA editing event between 2 different brain regions within the same study by running the mixed linear regression models with subject ID as random effect, and covariates of age at death, sex, postmortem interval (PMI), and RIN score using R lme package.https://genome.sph.umich.edu/wiki/METAL_Documentation).The primary analysis was conducted within each of the 10 dataset, and a general linear model (glm) was utilized to analyze the associations between RNA editing levels  and AD status . For MAYO datasets, there is no subjects with MCI, so the AD status were coded as 0 for normal controls and 2 for AD patients. The covariates adjusted in the model are slightly different across different studies depending on data availability. For the 4 ROSMAP datasets, we adjusted for sex, age at death, PMI, RIN, experimental batch, and study (ROS vs. MAP). For the 4 MSBB datasets, we adjusted for sex, age at death, PMI, RIN, experimental batch, and race. For the 2 MAYO datasets, we adjusted for sex, age at death, PMI , RIN, and tissue source . At Stage II, we conducted the meta-analysis on the largest cohort including samples from each study of: ROSMAP unpaired DLPFC, the DLPFC dataset of the paired ROSMAP multi-region RNA-seq project, BM44 dataset of the paired MSBB RNA-seq project, and the temporal cortex dataset of the paired MAYO RNA-seq project. The beta estimates and standard errors from each dataset were meta-analyzed using an inverse variance-weighted, fixed-effects approach implemented in METAL (2) is determined using systematic sampling. The β-amyloid protein was identified by molecularly specific immunohistochemistry and quantified by image analysis to obtain a value of percent area of cortex occupied by β-amyloid protein. The neuritic plaque burden is determined by microscopic examination of silver-stained slides from 5 regions of midfrontal cortex, midtemporal cortex, inferior parietal cortex, entorhinal cortex, and hippocampus . The count of each region is scaled by dividing by the corresponding standard deviation and the 5 scaled regional measures are then averaged to obtain a summary measure for neuritic plaque burden. The cognition decline variable was defined as the variable of the random slope of global cognition tests. We run the analysis using the generalized linear model with the above mentioned variables as outcomes and the RNA editing levels  as exposures and covariates of sex, age at death, PMI, RIN, experimental batch, and study (ROS vs. MAP). The genome-wide significance P value threshold is defined as ≤1.21 × 10−6 .We conducted the analysis in ROSMAP unpaired 635 subjects with DLPFC samples to explore the associations with PHFtau (tangle density) and β-amyloid , neuritic plaque burden, and cognition decline. The variables of the PHFtau (tangle density) and β-amyloid  is the mean of PHFtau and β-amyloid protein across 8 regions of hippocampus, entorhinal cortex, midfrontal cortex, inferior temporal, angular gyrus, calcarine cortex, anterior cingulate cortex, and superior frontal cortex . The PHFtau are identified by molecularly specific immunohistochemistry  and cortical density  (mean = 0 and SD = 1) of each of the top 7 AD-related RNA editing events were input to derive 7 PCs using the R packages of “factoextra” (v1.0.7) and “prcomp” (v.3.6.2).Further information on research design is available in the Supplementary information.Peer Review File.Description of Additional Supplementary Files.Supplementary Dataset 1.Reporting summary.


The biliverdin reductase B (BLVRB) class of enzymes catalyze the NADPH-dependent reduction of multiple flavin substrates and are emerging as critical players in cellular redox regulation. However, the role of dynamics and allostery have not been addressed, prompting studies here that have revealed a position 15 Å away from the active site within human BLVRB (T164) that is inherently dynamic and can be mutated to control global micro-millisecond motions and function. By comparing the inherent dynamics through nuclear magnetic resonance (NMR) relaxation approaches of evolutionarily distinct BLVRB homologues and by applying our previously developed Relaxation And Single Site Multiple Mutations (RASSMM) approach that monitors both the functional and dynamic effects of multiple mutations to the single T164 site, we have discovered that the most dramatic mutagenic effects coincide with evolutionary changes and these modulate coenzyme binding. Thus, evolutionarily changing sites distal to the active site serve as dynamic “dials” to globally modulate motions and function. Despite the distal dynamic and functional coupling modulated by this site, micro-millisecond motions span an order of magnitude in their apparent kinetic rates of motions. Thus, global dynamics within BLVRB are a collection of partially coupled motions tied to catalytic function. The allosteric regulation of enzyme function is now recognized to occur through multiple mechanisms, which can be mechanical where physical interactions induce long-range conformational changes or dynamic where motions influence networks of partially coupled movements . Methodsvia BLVRB (NCBI Reference Sequence: NP_000704.1) is so important that this enzyme alone can dictate hematopoietic cell fate (The biliverdin reductase B (BLVRB) family of enzymes are emerging as critical flavin reductases in multiple organisms that range from pathogenic bacteria to humans, as their flavin substrates act as redox sensors and coenzymes for many other enzymes . The BLVell fate . This crell fate . Mechaniell fate , which iell fate . Howeverell fate . Anotherell fate  and we hell fate . Thus, lell fate . DHFR isell fate . Howeverell fate , such glTo determine whether distally coupled dynamic residues modulate active site motions and function in BLVRBs, here we used the RASSMM approach on human BLVRB along with comparative relaxation studies of lemur BLVRB (NCBI Reference Sequence: XP_020138941.1). Our previous studies had suggested that a distal site, T164, is both inherently dynamic and coupled to the active site, which would fulfill the requirements for selecting a residue to then mutate in accord with the RASSMM approach. For example, coenzyme binding induces chemical shift perturbations (CSPs) to active site residues such as S111 and H153, but also CSPs to distal sites that included T164 within the C-terminal lobe . Here, bWe first sought an atomic-resolution description of BLVRB dynamics through structural studies in order to identify distal residues to the active site that are inherently dynamic, which is the first criterion of the RASSMM approach. While previous relaxation studies indicate that several regions within BLVRB exhibit chemical exchange , the undvia R2 relaxation , although insect BLVRBs are dramatically different from their mammalian counterparts in primary sequence that make it more difficult to pinpoint the role of specific evolutionary changes (<50% sequence identity). Nonetheless, these binding studies immediately identify an allosteric role for position 164 within human BLVRB with the most dramatic changes to coenzyme affinity also being identical to evolutionary changes.As the first step of the RASSMM approach identified human BLVRB T164 as both inherently dynamic and coupled to the active site, we next sought to address the second step of the RASSMM approach that imparts multiple mutations to this single site. While we engineered a panel of mutations to this site that include hydrophobic residues and hydrophilic residues, evolutionarily guided mutations were also considered based on our findings above with lemur BLVRB. Specifically, the conservative mutation of T164→S was also engineered based on the evolutionary comparisons within mammalian BLVRBs. We first probed the panel of BLVRB single-site mutants for their role in coenzyme binding using isothermal titration calorimetry (ITC). Surprisingly, one of the largest imparted changes to coenzyme affinity that incurred an approximately 2-fold increase was for that of the conservative mutation of T164S . The othM values were similar for all T164 mutations  and a larger change in coenzyme affinity . Because the coenzyme binds to BLVRB several orders of magnitude tighter than the flavin substrates, the rate-limiting step has been presumed to be coenzyme binding . This isutations , this suutations , therebyutations , a similAt the heart of the RASSMM approach is the potential for identifying similar relaxation effects to multiple residues imparted by variations at the single mutation site , such as those imparted by mutations to human BLVRB T164. Thus, we once again chose to further probe human BLVRB T164A  and both BLVRB, T164I ,and T164S . CSPs can also provide a means to identify coupled networks, yet many of the perturbed residues are similar for all three mutations with variations primarily to their magnitudes . Furthervia position 164 that includes similar changes to this second group of residues.All three single site mutations induce changes to R2-CPMG dispersion profiles for residues that primarily surround the active site , left, wConsidering that both T164I and T164S mutants impact function with opposing effects to R2-CPMG dispersions, such findings reveal the localized nature  of dynamics within this μs-ms timescale that has been shown to dominate dynamics in many systems that are still partially coupled . The simvia dynamic allostery.The dynamic basis of enzyme catalysis is still an emerging field that has benefited from the advent of NMR relaxation studies such as those used here to begin identifying allosterically coupled networks within BLVRB. Allosteric regulation of enzyme function is increasingly recognized to occur through multiple mechanisms, which include mechanical coupling such as the classic case of hemoglobin but also dynamic coupling where motions influence networks of partially coupled movements. Unfortunately, the basis of long-range allosteric regulation is complicated owing to the nature of motions that are often segmental. For example, even after decades of studies on DHFR, studies are still revealing how global motions modulate this enzyme’s function . Here, w13C-aromatic R2-CPMG experiments may be important to identify their differences . 15N-labeled proteins were grown in M9 media with 15N ammonium chloride and 2H,15N-labeled proteins grown in 100% D2O with 15N ammonium chloride. Cell growths were induced with 0.1 mM isopropyl β-D-1-thiogalactopyranoside (IPTG). All proteins were purified in denaturing buffer  via Ni affinity (Sigma) and followed by application to a 3 ml Resource 15RPC  to remove any residual coenzyme prior to refolding through dialysis into 1 M arginine buffer . Finally, proteins were dialyzed to NMR buffer  and concentrated proteins were cleaved with thrombin (Sigma) to remove the 6x-His tag and applied to a superdex-75 (GE). Proteins were concentrated and frozen until further use.All BLVRB proteins were purified as previously described . Briefly+ as the titrant at 1 mM with all buffers identical to that used for NMR . ITC experiments were performed in duplicate at 20°C and processed using Origin software provided with the MicroCal VP-ITC. All reported values are the average and standard deviations of these duplicates. For UV-steady state kinetics that monitored initial velocities, a Biotek Synergy 2 multi-mode detection plate reader was used with 200 µl total volumes (pathlength of 0.625 cm), which monitored NADPH conversion to NADP+ at 340 nm, as previously described  and a linear equation (the steady-state rate) using 3 FAD concentrations of 0.5, 1.0, and 1.5 mM using GraphPad Prism. As hydride transfer rates are concentration-independent , steady-state, and pre-steady state experiments for BLVRB were performed identically to previous studies . Brieflyescribed . Initialependent , reporte2O and data were collected on a Varian 900 spectrometer equipped with a cryo-probe at 20°C. Resonance assignments for the WT BLVRB previously published were used  was used to probe for potential covariance between human BLVRB T164 mutations and WT BLVRB coenzyme binding, as previously described . Briefly15N-NOESY and 13C-NOESY spectra (Apo BLVRB ensembles were calculated with chemical shifts previously obtained  and supp spectra . Co-evol spectra . Fragmen


Cyberlindnera jadinii has great potential in the biotechnology industry due to its ability to produce a variety of compounds of interest, including carboxylic acids. In this work, we identified genes encoding carboxylate transporters from this yeast species. The functional characterization of sixteen plasma membrane carboxylate transporters belonging to the AceTr, SHS, TDT, MCT, SSS, and DASS families was performed by heterologous expression in Saccharomyces cerevisiae. The newly identified C. jadinii transporters present specificity for mono-, di-, and tricarboxylates. The transporters CjAto5, CjJen6, CjSlc5, and CjSlc13-1 display the broadest substrate specificity; CjAto2 accepts mono- and dicarboxylates; and CjAto1,3,4, CjJen1-5, CjSlc16, and CjSlc13-2 are specific for monocarboxylic acids. A detailed characterization of these transporters, including phylogenetic reconstruction, 3D structure prediction, and molecular docking analysis is presented here. The properties presented by these transporters make them interesting targets to be explored as organic acid exporters in microbial cell factories.The yeast  Cyberlindnera jadinii, an Ascomycota belonging to Phaffomycetaceae  acetic acid ; L-[U-14C] lactic acid ; and  succinic acid  and  citric acid . Working solutions presented a specific activity ranging from 300 to 4000 dpm depending on the final carboxylate concentrations. Radioactivity was measured in a Packard Tri-Carb 2200 CA liquid scintillation spectrophotometer, with dpm correction. The best-fitting for initial uptake rates was determined through computer-assisted non-linear regression analysis, performed with GraphPad Prism  version 4.0 for Windows. The values for kinetic parameters were obtained with a significance level p < 0.05. The data shown are mean values of at least three independent experiments, with three replicas each.Transport assays were performed as previously described . Cells wJEN1 of S. cerevisiae (CEP23088p (CjJen1), CEP21966p (CjJen2), CEP22358p (CjJen3), CEP21989p (CjJen4), CEP21602p (CjJen5), and CEP25129p (CjJen6)), five ORFs homologous to the ATO1 of S. cerevisiae (XP_020070445.1 (CjAto1), XP_020073179.1 (CjAto2), XP_020073031.1 (CjAto3), XP_020073178.1 (CjAto4), and XP_020067765.1 (CjAto5)), and other homologs of known carboxylate transporters identified through the presence of specific conserved domains, namely CjSlc16 (XP_020067635.1), CjSlc5 (XP_020068154.1), CjSlc13-1 (XP_020069270.1), CjSlc13-2 (XP_020073044.1), and CjTDT (XP_020068891.1) , EcoRI and HindIII (CjJen2 and CjJen4), XbaI and EcoRI (CjJen6), SpeI and SalI , SpeI and XhoI (Slc13-2 gene), and SpeI and EcoRI (CjAto5) in the forward and reverse primers, respectively  . The sixDSM 2361  under thXP_0200690.1, CjSlon hosts . The priectively . The finhttps://www.ebi.ac.uk/Tools/psa/emboss_needle/) and ClustalOmega  through pairwise sequence alignment. The TMHMM server (http://www.cbs.dtu.dk/services/TMHMM-2.0/) was used for topology prediction of transmembrane segments (TMS). Multiple sequence alignment was also performed with M-Coffee (http://tcoffee.crg.cat/apps/tcoffee/do:mcoffee) for the further validation of identified TMS regions across the protein sequences acetic acid (pH 6.0), [14C]lactic acid and succinic acid (pH 5.0)  . Cells esporters A,B. For o ScJen1 B,C, thouhe assay A.S. cerevisiae W303-1A jen1Δ ato1Δ strain expressing CjATO1-4 and CjJEN1-5  for the uptake of succinate 1.0 mM (pH 5.0) were 0.131, 0.240, 0.277, and 0.282 nmol succinate s−1 mg−1 dry wt., respectively; for the empty vector, a residual value of 0.039 nmol succinate s−1 mg−1 dry wt. was determined in cells transformed with the empty vector.We then performed a more detailed analysis of genes displaying transport activity. First, the kinetic parameters of monocarboxylic acid uptake were estimated in the CjJEN1-5 . The traS. cerevisiae IMX1000 strain, deleted in 25 genes coding for all known and putative carboxylate transporters, was used for the heterologous expression of CjSLC16, CJSLC5, CjSLC13-1, CJSLC13-2, CjTDT, CjATO5, and CjJEN6. All transformants presented activity for acetate uptake  the determination of the conserved residues found in the multiple alignment of functionally characterized homologs , (ii) 3DCitrobacter koseri Ck_SatP revealed that the central and narrowest hydrophobic constriction of the anion pathway of the channel is formed by F17-Y72-L131 residues HX[S/T]QD387, located at TMS7, and residues Q498 and N501 (TMS11) are conserved in all the CjJen homologs  and SSS (TC 2.A.21) transporter families was carried out throughout the Tree of Life. For the AceTr (TC 2.A.96) family, the analysis was limited to Ascomycota, since a broad phylogenetic analysis was already presented in a previous study . ,27. S. cE32901g) .C. jadinii protein homologs members of the SSS (CjSlc5) and DASS (CjSlc13) family revealed to be functional monocarboxylate, dicarboxylate, and tricarboxylate transporters. S. cerevisiae cells expressing CjSLC5 and CjSLC13-1 presented improved growth in all tested carbon sources , with the phenotype being more evident in CjSlc5 transformant cells. Transport assays of labelled mono-, di-, and tricarboxylates confirmed the role of CjSlc5 as a carboxylate transporter. The reported function of CjSlc13-1 is also in accordance with data reported for the DASS family SLC13 members presenting affinity for succinate, citrate, and α-ketoglutarate [The lutarate ,67.C. jadinii are needed to fully understand the existence of such high number of transporters. This knowledge will certainly shed light on the well-adapted performance of this species to environments rich in carboxylic acids.Within this work, several carboxylate transporters were functionally characterized as displaying a broad range of substrate affinities and transport capacities. Further studies on the expression regulation of these genes in CjSLC5, CjATO5, and CjJEN6 in S. cerevisiae enabled cells to grow on all tested acids. The kinetic parameters of citrate uptake  [D. hansenii [Pichia kudriavzevii [Y. lipolytica [The phylogenetic reconstruction of Ato homologs suggests that CjAto5 is distant from CjAto1-4, ScAto1, and YlGpr1, but it shares the same clade with ScAto3 , whose fhansenii , KlJen2 . lactis ,48,73, albicans) ,33 than hansenii , the diciavzevii , and thepolytica ,65. DespCjSLC5 homologs only identified members of the eukaryotic domain of life, namely ascomycetes and basidiomycetes. A high prevalence of homologs was found in Fusarium species, and none was found in S. cerevisiae. The majority of SLC5 homologs have been annotated as putative neutral amino acid transporters. This fact may be explained by the existence of two homologs functionally characterized as amino acid transporters: the Mtr/AAP1 from N. crassa [P. chrysogenum [C. jadinii that is likely to operate as a general organic permease, accepting mono-, di-, and tricarboxylates as well as amino acids, as glycine, and glutamic acid [The phylogenetic reconstruction of the . crassa  and PcMtysogenum   motif of the AceTr family  observedIn this work, we describe the first AceTr homologs in yeast with affinity for dicarboxylates and tricarboxylates . Our molRegarding Jen protein members, our results highlighted two residues in CjJen6 that were not conserved across all Jen members. On TMS1, W154 (in ScJen1) was shown to be substituted for L65 in CjJen6 and also present in the succinate transporters CaJen2 ,33 and KFuture studies will be necessary to determine the contribution of these residues to the broader specificity of CjAto5 and CjJen6.C. jadinii carboxylate transporters belonging to a total of six transporter families with specificity for short-chain carboxylic acids were uncovered and functionally characterized. Two members from the AceTr family are able to transport succinate, CjAto2, and citrate, CjAto5. This latter is the first AceTr family member described as a broad range carboxylate transporter, accepting mono-, di-, and tricarboxylates. In addition, one member from SHS transporter family (CjJen6) and the two homologs from families SSS (SLC member 5) and DASS (SLC member 13) also showed the ability to transport mono-, di-, and tricarboxylates. To our knowledge, CjSlc5 and CjSlc13 are the first members from these families characterized in yeast as carboxylate transporters.In the present study, novel In the future, it will be important to test if the activity of these membrane transporters could lead to the improved bioproduction of carboxylates. Overall, this work increases the knowledge of yeast plasma membrane transporter proteins that can ultimately lead to development of improved bio-processes with an impact in industrial biotechnology.


Viral RNAs contain the information needed to synthesize their own proteins, to replicate, and to spread to susceptible cells. However, due to their reduced coding capacity RNA viruses rely on host cells to complete their multiplication cycle. This is largely achieved by the concerted action of regulatory structural elements on viral RNAs and a subset of host proteins, whose dedicated function across all stages of the infection steps is critical to complete the viral cycle. Importantly, not only the RNA sequence but also the RNA architecture imposed by the presence of specific structural domains mediates the interaction with host RNA-binding proteins (RBPs), ultimately affecting virus multiplication and spreading. In marked difference with other biological systems, the genome of positive strand RNA viruses is also the mRNA. Here we focus on distinct types of positive strand RNA viruses that differ in the regulatory elements used to promote translation of the viral RNA, as well as in the mechanisms used to evade the series of events connected to antiviral response, including translation shutoff induced in infected cells, assembly of stress granules, and trafficking stress. RNA viruses are a major threat to human health . Their r7GTP) residue (designated cap), while the long 3′UTR folds into a complex secondary structure that includes several stem-loops critical for viral RNA replication. However, other members of the Flaviviridae family differ in the type of regulatory elements controlling their translation and replication, as exemplified by hepatitis C virus (HCV), classical swine fever virus (CSFV), and bovine viral diarrhea virus (BVDV). The genomes of these viruses harbor a functional internal ribosome entry site (IRES) element on their 5′UTR, responsible for the cap-independent translation initiation of the viral RNA . T. T123].  the RNA ,134. Althylation ,136. Thi to m6A) . Adenine(ALKHB5) . The YT5nd eIF3B . 6A modification sites of the viral genome resulted in decreased virus replication, suggesting that m6A modification might enhance EV71 life cycle [Methylation of adenosine on viral mRNAs has multiple effects on virus replication ,141. Forfe cycle . In this6A has a wide range of effects on mRNA translation, it is reasonable to assume that mechanisms influencing viral protein synthesis could be affected by m6A methylation. A recent study reported that HCV IRES-dependent translation is stimulated by m6A methylation via YTHDC2 [6A methylation favors cap-independent translation of certain cellular mRNAs [6A modification suppresses HCV viral particle production through the action of YTHDF proteins [6A in ZIKV and CHIKV RNA decreases virus replication [6A modification could regulate RNA functions in various manners. However, there are open questions for unclear results in RNA viruses that need to be elucidated in future studies. Given that ma YTHDC2 , consistar mRNAs ,145. Howproteins , whereaslication ,147. TheTo accomplish the replication cycle, viruses have developed diverse strategies taking advantage of RNA regulatory elements that recruit RBPs and other host factors in all stages of the infection cycle. Most significantly, the regulatory elements of viral RNAs contain structural features relevant for their function, such that conserved structural elements associate RBPs connected to its relevance for the viral replication cycle. Highlighting the plasticity of RNA-protein interactions to achieve a large variety of specific functions, there are many ways to complete the replication cycle. Notably, the translation field has accumulated insights into the regulatory mechanisms occurring in both the host cell and the RNA virus translation during the entire viral replication cycle, and consequently, the antiviral state. Host factors are essential at all stages of the virus life cycle. Thus, besides performing critical roles in viral RNA translation and replication, host proteins participate in early infection steps, such as internalization and uncoating ,148 and 6A methylation in viral replication. The different combinations of RNA-protein complexes executing diverse mechanisms of action suggests that there is much to learn about virus–host interaction interface, highlighting the need to explore the multifaceted role of RNA-protein and protein-protein interactome in infected cells. Ultimately, dissecting the relationship between viral RNAs and host RBPs is expected to expand our understanding of virology and RNA biology in general, and also, to guide the development of novel antiviral approaches. In this review we have revisited representative examples of positive strand viral RNA translation initiation, the strategies developed to overcome the inhibition of protein synthesis in infected cells, the role of RBPs in the assembly and evading stress granules, the involvement of ER trafficking host factors targeting regulatory elements of viral RNAs to ribosome-rich compartments, and the influence of viral mRNAs m


MDSCs can be produced in great numbers for cellular therapy, but they present a mixture of subsets whose functions in GVHD prevention are undefined. Here, we generated MDSCs in vitro from murine BM cells in the presence of GM-CSF and defined the integrin CD11c as a marker to subdivide MDSCs into two functional subgroups: CD11b+CD11c+ and CD11b+CD11c− MDSCs. Isolated CD11b+CD11c+ and CD11b+CD11c− MDSCs both inhibited alloantigen-stimulated T-cell proliferation in vitro, although CD11b+CD11c+ MDSCs were more efficient and expressed higher levels of different immunosuppressive molecules. Likewise, expression of surface markers such as MHC class II, CD80, CD86, or PD-L1 further delineated both subsets. Most importantly, only the adoptive transfer of CD11b+CD11c+ MDSCs into a single MHC class I-disparate allogeneic BMT model prevented GVHD development and strongly decreased disease-induced mortality, while CD11b+CD11c− MDSCs were totally ineffective. Surprisingly, allogeneic T-cell homing and expansion in lymphatic and GVHD target organs were not affected by cotransplanted CD11b+CD11c+ MDSCs indicating a clear contradiction between in vitro and in vivo functions of MDSCs. However, CD11b+CD11c+ MDSCs shifted immune responses towards type 2 immunity reflected by increased Th2-specific cytokine expression of allogeneic T cells. Induction of type 2 immunity was mandatory for GVHD prevention, since CD11b+CD11c+ MDSCs were ineffective if recipients were reconstituted with STAT6-deficient T cells unable to differentiate into Th2 cells. Most importantly, the beneficial graft-versus-tumor (GVT) effect was maintained in the presence of CD11b+CD11c+ MDSCs since syngeneic tumor cells were efficiently eradicated. Strong differences in the transcriptomic landscape of both subpopulations underlined their functional differences. Defining CD11b+CD11c+ MDSCs as the subset of in vitro-generated MDSCs able to inhibit GVHD development might help to increase efficiency of MDSC therapy and to further delineate relevant target molecules and signaling pathways responsible for GVHD prevention.Myeloid-derived suppressor cells (MDSCs) are a heterogeneous population of myeloid progenitor cells that dampen overwhelming adaptive immune responses through multiple mechanisms and are recognized as an attractive novel immune intervention therapy for counteracting the destructive effects of graft- In the year 2007, myeloid-derived suppressor cells (MDSCs) were introduced as a heterogeneous population of myeloid progenitors with potent immunosuppressive functions , 2 that versus-host disease (GVHD) represents a disease which develops after allogeneic bone marrow (BMT) transplantation and is induced by activation and expansion of alloantigen-activated mature transplant-derived T cells. These donor T cells attack and destroy recipient tissue finally leading to life-threatening posttransplantation complications, which dramatically limit the success of allogeneic stem cell transplantation for treatment of hematological malignancies and genetic disorders (versus-tumor effect (GVT), which ensures eradication of alloantigen expressing residual tumor cells. Therefore, GVHD treatment strategies aiming to interfere with allogenic T-cell activation, proliferation, and function should be balanced in terms to prevent allogeneic T-cell-mediated tissue destruction while simultaneously guaranteeing efficient T-cell immunity to cope with infections and destroy residual tumor cells , granulocyte-colony stimulating factor (G-CSF), or a synthetic G-CSF/Flt-3 ligand. Subsequent adoptive transfer of the isolated MDSCs in allogeneic BM recipients efficiently prevents GVHD development  MDSCs (CD11b+Ly-6G-Ly-6Chigh) and polymorphonuclear (PMN) MDSCs (CD11b+Ly-6G-Ly-6Chigh) (MDSCs either isolated -6Chigh) , 24. Sin-6Chigh) , but the-6Chigh) , 27.in vitro-generated MDSCs indicated that these cells were not a unique population but could be distinguished by the expression of the integrin CD11c. CD11b+CD11c+ MDSC subpopulations exhibited increased expression of CD301b, which expression is linked to the Th2-inducing abilities of DCs  cells were isolated with 26-gauge needle from femurs and tibias. Single-cell suspensions were prepared using a syringe with 20-gauge needle, and erythrocytes were depleted.Splenic single-cell suspensions were prepared by pouring the spleen through a 70-µm cell strainer followed by erythrocyte depletion.Liver was perfused by the injection of 5 ml liver perfusion medium , followed by 5 ml liver digest medium (Gibco) into the vena cava inferior. Without the gall bladder, liver was digested for 30 min at 37°C in 10 ml liver digest medium. Single-cell suspensions were prepared by pouring the liver through a 70-µm cell strainer. Liver cells were suspended in 35% Percoll , followed by overlaying cells onto 70% Percoll. The gradient was centrifuged at 2,000 rpm for 20 min. Interfaces containing liver leukocytes were collected, and residual erythrocytes were depleted.Serum was collected from submandibular blood. Serum was stored at −80°C in cytokine stabilization buffer  (1:20 of collected serum volume) until ProcartaPlex Multiplex immunoassays  were performed.in vitro by incubating freshly isolated BM cells with 250 U/ml murine GM-CSF for 4 days at 37°C in an atmosphere with 7.5% CO2. BM cells at 9 × 106–1 × 107 were cultured in α-minimum essential medium , 10% fetal calf serum (Sigma Aldrich), 2 mM l-glutamine (Gibco), 1 mM sodium-pyruvate (Gibco), 100 U/ml penicillin-streptomycin (Gibco), and 0.05 mM 2-mercaptoethanol (Gibco) in Ø 15 cm culture dishes “Cell+” .MDSCs were generated CD11b+CD11c+ MDSCs were positively isolated by magnetic-activated cell sorting using anti-CD11c MicroBeads  according to manufacturer’s protocol. CD11b+CD11c- MDSCs were isolated from the flow-through of CD11c isolation by loading the flow-through on a depleting LD column (Miltenyi). Purity of both MDSC subpopulations ranged between 85% and 99%.CD3+ T cells were positively isolated from splenic single-cell suspensions by magnetic-activated cell sorting using the CD3ϵ MicroBead Kit (Miltenyi) according to manufacturer’s protocol. Purity of isolated T cells was over 70%.Mouse strains used are listed in 137Cs source. BM cells were depleted from T cells as described previously (6 T-cell-depleted BM (TCD-BM) in the presence or absence of 2 × 107.spleen cells (SC). In vitro-generated CD11b+CD11c+ or CD11b+CD11c− MDSCs at 1 × 106 were coinjected with the transplant. In studies analyzing the GVT effect 5 × 104 JM6 thymoma   for 10 min at 37°C in the dark.Cells at 2 × 105 were stimulated with 2.5 × 105 irradiated (33 Gy) DBA/2-derived SCs in the absence or presence of B6-derived CD11b+CD11c+ or CD11b+CD11c− MDSCs. iNOS was inhibited using 500 µM L-NG-monomethyl-arginine-citrate (L-NMMA)  and PD-L2 was blocked using 10 μg/ml antimouse PD-L2 antibodies . Mixed lymphocyte reactions (MLRs) were cultured in α-MEM medium (Lonza) supplemented with 10% FCS (Sigma Aldrich), 2 mM l-glutamine (Gibco), 1 mM sodium-pyruvate (Gibco), 100 U/ml penicillin-streptomycin (Gibco), and 0.05 mM 2-mercaptoethanol (Gibco) for 4 days at 37°C in an atmosphere with 7.5% CO2. After 4 days, T-cell proliferation was determined using flow cytometry and percentage of T-cell suppression was calculated.CFSE-labeled B6.SJL-derived SCs at 2.5 × 105–1 × 106 were stained with respective fluorochrome-conjugated antibodies. Antibodies used are listed in Cells at 5 × 10® Green Supermix  and analysis was performed on a CFX Connect Optics Module (BIO-RAD). Relative expression was determined using the comparative CT method. Mouse aryl hydrocarbon receptor-interacting protein (AIP) was used as a housekeeping gene. Primer sets used are listed in Quantitative reverse-transcription polymerase chain reaction (qRT-PCR) was performed using the SsoAdvanced™ Universal SYBRCytokine concentrations of 12.5 µl blood serum or 25 µl cell culture supernatant were analyzed by ProcartaPlex™ multiplex immunoassays (ThermoFisher Scientific) according to manufacturer’s protocol. Analyses were performed on a BIO-RAD Bioplex 200 system (BIO-RAD).FACS-sorted CD11b+CD11c+ and CD11b+CD11c− MDSCs were collected in RLT buffer  supplemented with 2-mercaptoethanol followed by RNA extraction using the RNeasy Mini Kit (Qiagen) and adding an on-column DNA digestion step according to manufacturer’s instructions. Total RNA was quantitatively and qualitatively assessed using the absorbance-based Take3 microvolume plate system on a Cytation 5 instrument  and the Standard Sensitivity RNA Analysis DNF-471 Kit on a 12-channel Fragment Analyzer , respectively. Concentrations averaged at 310 ng/µl while RIN values ranged from 8.6 to 10, with an average of 9.8.MDSC-derived RNA samples were normalized, and a RNA input of 100 ng was used for library construction with the NEBNext Ultra II Directional RNA Library Prep Kit for Illumina #E7760, together with the NEBNext Poly(A) mRNA Magnetic Isolation Module #E7490 upstream and the NEXNext Multiplex Oligos for Illumina #E7600 downstream . Ampure XP beads  were used for double-stranded cDNA purification. mRNA sequencing libraries were quantified by the High Sensitivity dsDNA Quanti-iT Assay Kit (ThermoFisher Scientific) on a Synergy HTX (BioTek). Library molarity averaged at 134 nM. Final library size distribution was assessed  by the High Sensitivity Small Fragment DNF-477 Kit on a 12-channel Fragment Analyzer (Agilent Technologies). All sequencing libraries passed quality check, were normalized, pooled, and spiked in with PhiX Control v3 . The library pool was subsequently clustered with the HiSeq 3000/4000 SR Cluster Kit on a cBot and sequenced on a HiSeq 3000 Sequencing System (Illumina) with single index, single read at 85 bp length , reaching an average depth of 29 million Pass-Filter reads per sample (11% CV).http://www.ensembl.org) using the STAR v2.5.2 program on default settings (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/), and alignment quality metrics were calculated using the RNASeQC v1.1.8  data are available at Gene Expression Omnibus (GEO accession number: GSE182262).Illumina reads were converted to FASTQ files and aligned to the mouse reference genomes from Ensembl 70  test. Results were considered significant if p < 0.05. Statistical tests were performed with GraphPad Prism 8.Data were analyzed using Mann-Whitney in vitro  or PMN-MDSCs (Ly-6ClowLy6G+), we costained for Ly-6C and Ly-6G. CD11b+CD11c+ MDSCs consist of about 60% M-MDSCs and low percentage of PMN-MDSCs, while 20% of the cells neither expresses Ly-6G and Ly-6C. CD11b+CD11c− MDSCs represent a mixture of M-MDSCs (about 50%) and PMN-MDSCs (40%) (b), F4/80, CD40, the activating costimulatory molecules CD80 and CD86, as well as the inhibitory molecules PD-L1 (CD274) and PD-L2 (CD273)  spleen cells, which were activated by DBA/2-derived  irradiated spleen cells. Using the congenic marker CD45.1 expressed solely on CFSE-labeled effector cells, proliferation of CD45.1+CD4+ and CD45.1+CD8+ T cells was determined. Both MDSC subpopulations efficiently suppressed T-cell proliferation, but CD11b+CD11c+ MDSCs exhibited strongly increased inhibitory capacity especially towards CD8+ T-cell proliferation  mice →B6.bm1 (H-Kbm1), in which lethally irradiated B6.bm1 mice were reconstituted with TCD-BM and SCs from B6 mice. At the day of BMT, isolated CD11b+CD11c+ or CD11b+CD11c− MDSCs were cotransplanted together with TCD-BM and SCs. While 52% of mice transplanted with TCD-BM and SCs succumbed to the disease associated with high GVHD scores and weight loss of about 20%, CD11b+CD11c+ co-transplantation rescued 78% of the mice from disease-induced mortality reflected by a reduced GVHD score and less weight loss. In contrast, cotransplantation of CD11b+CD11c− MDSCs totally failed to prevent GVHD development. Surviving rates and GVHD scores were undistinguishable in mice receiving TCD-BM and SC and mice cotreated with CD11b+CD11c− MDSCs. Control mice receiving TCD-BM survived and did not develop GVHD  mice together with B6-derived TCD-BM (CD45.2+) into irradiated B6.bm1 (CD45.2+) mice, homing and expansion of allogeneic GVHD-inducing T cells were followed by staining the congenic marker CD45.1 in spleen and liver of transplanted mice. CD45.1+ T cells were detectable in spleen and the GVHD target organ liver already at day 3 after BMT in mice transplanted with TCD-BM and SCs. An increase of about 200-fold was achieved 10 days after BMT in both organs. However, cotransplantation of MDSCs did not prevent invasion and expansion of allogeneic T cells independent whether isolated CD11b+CD11c+ or CD11b+CD11c− MDSCs were transferred  or B6 WT mice and CD11b+CD11c+ MDSCs. STAT6−/− splenic T cells are unable to differentiate into type 2 T cells but retain their ability to turn into type 1 T cells and to induce GVHD indistinguishable from STAT6-expressing WT T cells as shown previously  were identified, from which 1,443 genes were upregulated and 1,340 genes were downregulated in CD11b+CD11c+ MDSCs compared with CD11b+CD11c− MDSCs. Focusing on the transcripts that were highly upregulated or downregulated in the CD11b+CD11c+ MDSC subpopulation, we performed enrichment analysis using GO database. Target genes upregulated in CD11b+CD11c+ MDSCs can be largely grouped into the biological and functional categories  of two experiments displays the degree to which the transcriptome of CD11b+CD11c+ MDSCs differs from CD11b+CD11c− MDSCs. In both experiments, PCA analysis clearly separated two clusters corresponding to the CD11b+CD11c+ and CD11b+CD11c− MDSCs , we defined which subset of MT model , indicatIn vitro or in vivo induction of MDSCs for cellular therapy of GVHD have been performed by using various approaches with different effectiveness . MDSC treatment of TxT mice strongly increased splenic T-cell numbers and proliferative capacity without impairing antigen reactivity , the fatty acid translocase CD36 or the chemokines CCL17 and CCL22 were identified. Although CD36 expression is not directly linked to elevated immunosuppressivity, increased lipid contents are reported to augment the immunosuppressive functions of MDSCs –58, and in vitro and in vivo functions of MDSCs requires thoughtful testing of MDSC functions in the relevant disease context.Taken together, we could define a small subset of GM-CSF-induced MDSCs characterized by the coexpression of Gr-1+CD11b+CD11c+ as the MDSC subpopulation able to prevent GVHD while maintaining T-cell reactivity and cytotoxicity. This might offer the possibility to identify key molecules and signaling pathways involved in disease prevention with the future perspective to substitute cellular MDSC therapy by pharmacological approaches. Furthermore, the clear discrepancy between https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE182262.The original contributions presented in the study are publicly available and are based on JS's dissertation: . mRNA SeThe animal study was reviewed and approved by the ethical committee Regierungspräsidium Tübingen, Germany.JS performed experiments, analyzed data, and generated figures. KK, HH, SP, and KF-C performed mRNA-Seq analysis and analyzed transcriptomic data. K-MD contributed to the study design and interpreted data. GS created the study design, performed data interpretation, and wrote the manuscript together with JS. All authors approved the final version of the manuscript, revised the manuscript, and are accountable for all respects of the work.This study was supported by Boehringer Ingelheim Ulm University BioCenter (TPI2) and the International Graduate School in Molecular Medicine, Ulm, Germany.KK, HH, KF-C, and SP are employed by Boehringer Ingelheim Pharma Co. KG and Boehringer Ingelheim RCV GmbH & Co. KG.The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Introduction.Consumers are getting more empowered, the process of empowerment transforming them into the partners of organizations or co-producers of services. Health care services, as well as ophthalmology services, have been a sensitive topic and raised several debates that focused on the principles of Experiential Marketing and hedonic experiences.Aim.The aim of this paper was to investigate the experiences of patients in a public ophthalmology organization by using the components of Experiential Marketing: sense, feel, think, act, and relate. Materials and methods.The case study was cross-sectional, and the sampling method was non-probabilistic, following a snowball technique. The sample was made up of 100 patients of the Clinical Emergency Eye Hospital in Bucharest. The instrument for data collection was a self-administered questionnaire. The statistical analysis was conducted in SPSS version 20 and frequencies or percentages were used for describing the qualitative data.Findings.Experiential Marketing principles may successfully be applied in public ophthalmology services if a special attention is given to the Feel and Relate components. Today we are facing a dynamic evolution of the consumers’ behaviors that have suffered significant changes, becoming more experiential oriented, with a specific interest in the hedonic type, which stimulates the senses and triggers different emotions [2]. In this context, marketing specialists must focus on new strategies that offer transparency, freedom, and easiness in the exchanging information process, in order to provide value, not in a utilitarian way, but rather in the shape of a hedonistic experience [3].Consumers have more information in their hands, getting more empowered and transforming into partners for organizations, and, in addition, even sharing valuable information so as contributing to the outcomes of an organization in a beneficial way [1]. Consequently, having in mind this concept, Schmitt divided the types of experiential marketing into five categories: sense, feel, think, act, and relate. Sense is the experience that focuses on the fact that the consumers live the moment, whereas Feel is the experience earned through a process of stimulating the emotions, feelings, and the state of mind of an individual while using the service. On one hand, Think refers to the stimulation of consumer creativity from a cognitive perspective, and Act suggests the consumer’s activities, in which he is involved, having a direct physical contact with the service, with the aim of changing different behaviors and lifestyles, and on the other hand, Relate offers the possibility of establishing connections with different communities and entities, when buying or consuming the service. Relate experience ensures that consumers build their own connections with social communities during consumption or purchase of the services. Experiential marketing has an important role in Marketing because it is based on the whole (hedonic) consumer experience of a certain service. Thus, the aim of Experiential marketing is to reach both the rational and emotional states of the people, namely living a hedonic experience. In 1999, Bernd Schmitt mentioned the concept “experiential marketing”, emphasizing the outcome of an experience being the consumer’s triggered emotions and the activated senses, not necessarily the benefits, quality, and satisfaction , service experience [5], and consumption experience [6], but few have focused on the health care services [7].Most of the scientific literature about Experiential Marketing concentrates on product experience . More exactly, in health care services, marketing may be efficiently applied considering the content and the features of services and the consumer-provider interaction, associated with prevention, patient support and health promotion.Although, the concept of the health care consumer service perception has raised attention and debates in order to eliminate the lack of information they face, the conclusion reached supported the application of experiential marketing strategies, as it is a field characterized by interdisciplinarity . As such, the questionnaire consisted of 2 sections: the first section contained several demographic questions, and the second section encompassed closed end questions related to the perception of public ophthalmologic services from an experiential marketing perspective through its components, sense, feel, think, act, and relate, respectively. All the items of the second section in the questionnaire were measured on a 5-point Likert scale ranging from 1 with Strongly Disagree to 5 to Strongly Agree.The instrument for data collection was a self-administered questionnaire during 1st of January and 15th of June 2021, that has already been tested and validated in an ophthalmology setting in a private health care organization . However, there are fields, such as health care, that are sensitive to be addressed even through experiential marketing strategies. As our research findings suggested, the experiential marketing components that require attention in Ophthalmology public services are Feel and Relate, this result being in accordance with previous literature [12].Experiential marketing is a valuable strategy that ophthalmologic organizations may use to target specific consumers, through a compelling service experience in a hedonic manner. Building personally relevant and memorable experiences will make consumers feel comfortable with their choices and will relate more easily with other peers in an online or offline environments [13].The core principles of Experiential Marketing, that may also be applied in Ophthalmology services, are connected to communication by using touch and emotions in helping consumers grasp the health care service, and promote the use and benefits of consuming the service in an aspirational manner, by delivering, in fact value in a hedonic way [Experiential Marketing principles may successfully be applied in public ophthalmology services if a special attention is given to the Feel and Relate components. The key to make consumers perceive the principles of Experiential Marketing in a positive manner is to offer them hedonic experiences. Conflict of Interest statementAuthors state no conflict of interest.Informed Consent and Human and Animal Rights statementInformed consent has been obtained from all individuals included in this study.AcknowledgementsNone.Sources of FundingNone.DisclosuresNone.