extfieldsofstudy:
Biology
Computer Science

text:
Analysis of multiple fungal sequence repositories highlights shortcomings in microbial databases

Reference genomes are essential for metagenomics studies, which require comparing short metagenomic reads with available reference genomes to identify organisms within a sample. We analyzed the current state of fungal reference databases to assess their usability as reference databases for metagenomic studies. The overlap of genera and species in the databases analyzed was alarmingly small. In other words, using only a single reference database for analysis of metagenomic samples possibly results in the failure to identify some organisms in the sample. Communication between database developers needs to be established to create a set of standards for the way reference databases are organized and distributed.

We investigated the lengths of the fungal genomes across t he three databases considered in this study ( Figure 1c ). We observed a shorter length of genomes in the 1K database. The shorter overall length of genomes in the 1K database can be attributed to the lower amount of complete genomes in the 1K database compared to other databases. We also separately investigated the length of complete and incomplete genomes (represented as a set of contigs). As expected, we observed a greater length of complete genomes compared to incomplete ones consistently across all three databases ( Figure S1 ). The percent of species represented as complete genomes are 23.5% (RefSeq), 1.4% (JGI), and 18.5% (Ensemble). The percentage of species represented as contigs are 69.6% (RefSeq), 92.2% (JGI), and 76.2% (Ensembl). The percentage of species containing both contigs and complete chromosomes are 6.8% (RefSeq), 6.3% (JGI), and 5.3% (Ensembl) ( Figure 1d ). Analysis of all three databases revealed that some species were represented as a mixture of complete and incomplete genomes ( Figure 1d ). Additionally, for the same species, RefSeq and Ensembl had mitochondrial reference genomes ( Figure 1e ). At the same time, none of the complete and incomplete genomes in the 1K database were annotated as mitochondrial reference genomes. Finally, Ensembl and RefSeq contained plasmid references while 1K did not ( Figure 1f ).
In addition to the discrepancies between fungal reference databases, we identified numerous issues that limit the usability of the databases. Namely the lack of an easy-to-use interface to download the genome references. Also, some databases provided limited documentation for the references that were difficult to find. For example, obtaining the universal taxonomic ID's for the JGI 1K fungal genomes was a non-intuitive process involving six steps. Overall, the lack of user-friendly interfaces and inconsistent use of unique identifiers in reference databases requires substantial time and effort from the user.

Discussion
Our study is the first to systematically investigate the consistency of fungal databases.
We determined that discrepancies between the fungal reference databases are alarmingly large. In the best case scenario, a researcher only using one database will be missing 38% of the reference fungal species. This unfortunate state of fungal databases perhaps explains the general lack of fungal organisms in many metagenomic analysis tools, the absence of which stalls metagenomic discoveries centering around the Fungal Kingdom. Furthermore, since the fungal reference genomes are from databases that also contain reference genomes for bacteria and other organisms, it is likely that these issues extend to general microbial databases as well.
Establishing between all parties involved an effective dialogue centered on systematic creation of microbial databases promises to accelerate metagenomics discoveries. In order to optimize metagenomic tool development, any new database should consistently incorporate information from previous efforts to avoid introducing discrepancies between the databases. Current emergent long read technologies promise to promise to deliver reads helping to assemble longer contigs and eventually obtaining full-length genomes 7 . Implementing systematic reference databases today will improve the outcome of these efforts. I t is important to impose stringent standards on the way reference microbial databases are organized and distributed, as has been successfully initiated for vertebrate genomes 8 .

Downloading the databases
We considered fungal species and genera across three reference databases: • JGI 1000 Fungal Genomes Database, https://genome.jgi.doe.gov/programs/fungi/index.jsf • Ensembl, ftp:// ftp.ensemblgenomes.org/pub/fungi/release-40/ • RefSeq, https://www.ncbi.nlm.nih.gov/ Each of these had a separate process for downloading the fungal reference genomes: • JGI 1k Fungal Genomes Database . On the download page, we downloaded only the assembled masked fungal reference database. This appeared as a zip file, which was downloaded locally. When unzipped, the file yielded 1063 directories, each representing one species (in some cases where strain information was available, each strain was represented within its own directory), inside of each was a zipped FASTA file (in 2 directories there were 2 such files) which contained the genetic reference information.
• Ensembl. There was no efficient GUI with which to download all 811 fungal reference files on the site. Each DNA FASTA link led to a FTP page with multiple .gz downloads.
Only the file that ended in dna.toplevel.fa.gz was selected. The wget command was called on each of the links that were selected for the 811 available fungal references on Ensembl.
• RefSeq. First, we have downloaded the table of available fungal reference genomes from here ftp:// ftp.ncbi.nlm.nih.gov/genomes/refseq/fungi/assembly_summary.txt . We have extracted the URLs from the table, and use wget to download corresponding FASTA files with the reference genomes.
The scripts and commands used to download the reference databases are freely available at https://github.com/smangul1/db.microbiome .

Standardize the names of the species across the fungal reference databases
In order to standardize the names of the species across all three fungal reference databases, universal taxonomic IDs were used. Once the taxonomic ID for each file was determined, the species name was found by converting the taxonomic ID to a species name on NCBI ( https://www.ncbi.nlm.nih.gov/Taxonomy/TaxIdentifier/tax_identifier.cgi ). The taxonomic IDs provided species-level information. As with downloading, the process for which taxonomic IDs needed to be determined for each file was different for each of the three databases.
• JGI 1k Fungal Genomes Database There was a six-step process necessary to obtain a Microsoft Excel document that contained taxonomic ID information that involved making an advanced search which reveals a "reports" button where the user can download an excel spreadsheet containing the taxonomic ID information. We have prepared a python script to match filenames to taxonomic IDs. The script is available at https://github.com/cloeffler745/Database_source_code/tree/changing_compare_files/ Compare/Fungus/fix_onek_csv • Ensembl On the FTP server ( ftp:// ftp.ensemblgenomes.org/pub/fungi/release-40/ ) is a file named " species_EnsemblFungi.txt" which is a mapping file that shows what Ensembl files match to which taxonomic IDs. A list of Ensembl file names and the mapping file were used to match taxonomic IDs to file names using Python ( https://github.com/cloeffler745/Database_source_code/blob/changing_compare_files /Compare/Fungus/ensmebl_prep/new_make_ensembl_taxid_table.py ).
• RefSeq The FASTA headers within each file contained the species names. These names were isolated into a text file which was used to get taxonomic IDs on the same NCBI taxonomy site that was used to get species names from taxonomic IDs.

Classify reference genome as complete or incomplete
In order to determine the presence or absence of genetic reference types (scaffolds, contigs, fully assembled chromosomes) and extra genetic references (mitochondrial and plasmid sequences), the text of the reference files was searched for predetermined patterns and words. The key words "chromosome" and "chr" were used to identify sequences that were marked as complete genomes. The key words "contig", "scaffold", and "sca" were used to identify sequences marked as incomplete.

Compare the species and genera across the fungal reference databases
To generate statistical data for cross-database species comparison, individual sequence attributes were extracted from each fungus file and stored in a structured query language relational database management system (SQL RDBM). The attributes extracted from each fungal reference sequence included database name, TAXID, species name, genus name, a flag indicating if the species is composed of chromosomes, contigs or mixture of both, a flag indicating if the species contains mitochondrial and plasmid DNAs. we have also recorded the length of contigs and chromosomes for each of the species. Individual files could have more than one sequence classification depending on the contents of the DNA sequences within. The data for sequence composition contained the number of sequences for a given sequence classification that existed within each file. Furthermore, the average, minimum, and maximum sequence lengths for each sequence classification within each file were also stored. Due to the variation in file formatting and naming conventions within each database, several flags were implemented to determine sequence classifications. In particular, the keywords "scaffold" and "contig" were used to catch instances of contig classified sequences. Variations of the keyword "chromosome" such as "chrom" and "chr" were used to catch instances of chromosome classified sequences. Variations of the keyword "mitochondria" such as "mitochondrion", were used to catch instances of mitochondria classified sequences. The keyword "plasmid" was used to catch instances of plasmid classified sequences. A link to the SQL database can be found here: https://github.com/aaronkarlsberg/db.microbiome/blob/master/Fungi/data/refSeqFungiStats. db

Data Location
The data used in this study, including the species and genera names, are available here: https://github.com/smangul1/db.microbiome/tree/master/Fungi/data


s2fieldsofstudy: Biology Medicine

text:
Cytokine Profile of Human Abdominal Aortic Aneurysm: Involvement of JAK/STAT Pathway

Objective: Abdominal aortic aneurysm (AAA) is characterized by inflammation and destruction of normal tissue architecture. The present study aimed to evaluate the inflammatory signaling cascade by analyzing the cytokines of AAA tissue. Materials and Methods: We analyzed the comprehensive cytokine secretion profiles of 52 cytokines from human AAA in four patients with AAA using fluorescent beads-based multiplex assay. Further, the effect of janus kinase (JAK) inhibition by pyridone 6 on cytokine profiles was also evaluated. Results: Cytokine secretion profiles were found to be similar among the four patients. A high level of JAK/signal transducers and activator of transcription (STAT) pathway activity in AAA tissue in culture was maintained, which may be attributed to the secretion of endogenous JAK-activating cytokines. Inhibition of JAK by pyridone 6 resulted in the suppression of STAT3 phosphorylation and secretion of a subset of chemokines and JAK-activating cytokines. However, the inhibition of JAK had no effect on the secretion of matrix metalloproteinase (MMP)-2, MMP-9, or TGF-β family that is responsible for the metabolism of extracellular matrix. Conclusion: The findings of the present study suggested that AAA tissue exhibits a stereotypical profile of cytokine secretion, where JAK/STAT pathway may play a role in regulating a subset of cytokines. Identification of such a cytokine profile may reveal potential diagnostic markers and therapeutic targets for AAA.

Introduction
Abdominal aortic aneurysm (AAA) is the most prevalent aortic disease in the elderly, with unidentified etiology. 1) AAA is primarily characterized by the weakening of aortic walls because of degradation and extensive remodeling of the load-bearing extracellular matrix (ECM), leading to progressive dilatation of the abdominal aorta. Although no symptoms are manifested in most patients, AAA progress over the time and eventually ruptures, leading to high mortality. Presently, the therapeutic strategy for AAA is limited to surgical intervention with open repair or endovascular stent-graft implantation for AAAs >5.5 cm in diameter. However, smaller AAAs are usually managed by watchful waiting, as effective non-surgical therapy is unavailable.
Recently, studies have highlighted the significance of inflammatory response in the degradation and remodeling of ECM in AAA lesions. 2,3) During vascular remodeling, inflammatory cells secrete proteolytic enzymes including matrix metalloproteinases (MMPs) that are involved in the degradation of ECM in aortic walls. 4) Various cell types have been reported to be important in this inflammatory response, including monocytes/macrophages, mast cells, neutrophils, and lymphocytes. 2,3) In addition to the secretion of tissue degrading enzymes, these cells secrete a number of cytokines that mediate complex cell-cell interactions and maintain and amplify the inflammation cascade in aortic tissue. Thus, these cytokines regulate migration, proliferation, differentiation, activation, and survival of inflammatory and interstitial cells through interactions with specific receptors on various cell types and activate janus kinase (JAK)/signal transducers and activator of transcription (STAT), nuclear factor-kappa B (NFκB), and mitogen-activated protein kinase (MAP) kinase signaling pathways, thus building a complex network of inflammatory signaling.
Despite the fact that animal studies have identified several potential therapeutic targets in the pathogenesis of AAA, pharmacotherapy for AAA is yet to be established. This is partially because of the complexity of human AAA compared to animal models of AAA. 5,6) To overcome the problem, the characterization of inflammatory system in human AAA tissue is necessary. Indeed, previous studies have demonstrated the increased expression of proinflammatory cytokines at the mRNA and protein levels in human AAA tissue. 7) However, a number of cytokines secreted from AAA tissue have not yet been analyzed.
Therefore, for better understanding of the inflammatory signaling cascade in human AAA, we examined cytokine secretions from the human AAA tissue in culture. Further, we also studied the effect of pyridone 6, a pan-JAK inhibitor, because JAK/STAT is one of the leading signaling pathways in inflammatory response, reported to be involved in human AAA, 8) and hypothesized to have a significant role in the pathogenesis of AAA. 9)

Human AAA tissue culture
The Institutional Review Board of Kurume University Hospital approved all protocols that involved human specimens, and all the samples were obtained with written informed consent from the patients. Aortic wall specimens were collected from randomly selected four patients ( Table 1) during the open aneurysm repair surgery to replace an aneurysm with the artificial graft as described before. 10) The anterior aortic wall at the site of transition from the normal diameter to the dilated lesion (approximately 30 mm in length and 15 mm in width) was collected during surgery ( Figs. 1A and 1B). The specimens were immediately immersed in ice-cold phosphate buffered saline (PBS, #10010023, Thermo Fisher Scientific, Waltham, MA, USA) containing penicillin/streptomycin (1,000 units/mL each, to minimize the proinflammatory effect of microbes, and transported to the laboratory. In the laboratory, the aortic wall specimens were transferred to Dulbecco s modified Eagle medium (DMEM) supplemented with penicillin and streptomycin (1,000 units/mL each), rinsed and cleaned of the blood clot and loose connective tissue aseptically. Because of heterogeneity in the histopathological features of the aortic aneurysmal walls, the following procedure was performed to minimize variation in tissue content in each well of the 12-well culture plate. The aortic wall was cut into three pieces; proximal, middle, and distal portions of the aortic wall. Each piece was further cut into small pieces (approximately 2 mm×2 mm). Further, the small pieces were transferred to the 12-well tissue culture plate, such that each well received an equal number of pieces from the original proximal, middle and distal portion of the aortic wall. After this preparatory procedure, the specimens were cultured in 2 mL DMEM at 37°C in a humidified incubator with 5% CO 2 and 95% room air. After 48 h, the culture media was replaced with fresh DMEM to remove blood clots and tissue debris, and further experiments were conducted. The AAA tissue culture was maintained for 48 h to obtain conditioned media to detect the basal cytokine secretions (PRE group). Furthermore, the culture media was replaced with the fresh DMEM with 0, 1, and 10 µM pyridone 6 (#420099, Millipore, Burlington, MA, USA) or 100 ng/mL IL-6 (#206-IL, R&D Systems, Minneapolis, MN, USA). After 48 h, the conditioned media was collected to measure cytokine secretion (POST group) in the presence or absence of pyridone 6 or IL-6.

Statistical analyses
All the statistical analyses were performed using Graph-Pad PRISM (Ver. 5, GraphPad Software, La Jolla, CA, USA). The data are expressed as mean±standard errors.
Mann-Whitney U test was used to compare the difference between the two groups. Kruskal-Wallis test was used to compare three or more groups with Dunn s correction for multiple comparisons. A p value ≤0.05 was considered statistically significant.

Cytokine profile in AAA tissue culture
We determined the culture media levels for 52 cytokines (soluble mediators) in the cultures of AAA derived from four patients. The cytokine profile revealed minute variation for each cytokine in a set of tissue cultures obtained from a single patient, possibly reflecting the heterogeneity of AAA tissue (Fig. 1C). However, variation among cytokines for a single patient was small as compared to the difference in cytokine levels among the four patients, and the orders of the cytokines were similar among the patients. Functional class of cytokines which had the highest level of secretion were JAK/STAT-activating cytokines: IL-6, MIF, LIF, and IFN-γ, chemokines; MCP-1, IL-8, MIG, IP-10, and GROα, growth factors; SCGF-β, HGF, and VEGF, and cell adhesion molecules; ICAM-1 and VCAM-1. These findings suggested that the intrinsic manifestation of inflammation was similar among the patients.

Effect of JAK inhibition on cytokine secretions
Further, we examined the effect of pyridone 6, a pan-JAK inhibitor, on the activation of STAT3 (phosphorylation at Y705) and cytokine secretions. Pyridone 6 suppressed the phosphorylation of STAT3 during the 48 h of culture, without affecting the expression of STAT3 ( Figs. 2A-2C). Moreover, to evaluate the role of JAK/STAT pathway in ECM degradation, we examined the effect of pyridone 6 on the secretion of MMP-2 and MMP-9 by gelatin zymography (Fig. 2D). Both MMP-2 and MMP-9 were detected at significant levels in the culture supernatant of human AAA tissue. However, the treatment of AAA culture with pyridone 6 exhibited no apparent effect on the secretion of MMP-9 or MMP-2 at 1 µM and may have caused marginal suppression of MMP-2 at 10 µM. Further, the addition of exogenous IL-6 had no significant effect on the secretion of MMP-9 or MMP-2, probably because of high endogenous IL-6 secretion level during tissue culture. These results suggested that JAK/STAT pathway does not play a significant role in the secretion of these MMPs.

Discussion
In the present study, we examined the cytokine secretion profile of AAA tissue in culture, which revealed reproducible cytokine profiles among the four sets of tissue culture derived from different patients. The results were largely consistent with previous studies that examined either the relative expression levels of a panel of cytokines using immunoassays, quantitative reverse-transcriptase poly-  Cytokine Profile of Human AAA merase chain reaction (RT-PCR), and deoxyribonucleic acid (DNA) microarray or the absolute expression levels of specific cytokines by enzyme-linked immunosorbent assays (ELISAs). 7) Furthermore, we also evaluated the effect of pyridone 6, a pan-JAK inhibitor, to determine whether or not JAK/STAT pathway regulates the secretion of a subset of cytokines in AAA tissue culture. Studies indicate that inflammatory responses may contribute to aortic wall destruction in AAA. 2,3) Because inflammatory cells and interstitial cells work in concert through various cytokines to maintain and promote inflammation, cytokines and their signaling pathways represent potential diagnostic markers and therapeutic targets. 7) It is noteworthy that cytokine therapy has already been applied in clinical practice as neutralizing antibodies and decoy receptors for TNF-α, IL-6, and other cytokines, which resulted in excellent clinical outcomes in inflammatory disorders, including rheumatoid arthritis, inflammatory bowel syndrome, and psoriasis. 11) To identify the significance of cytokine therapy for AAA, it is essential to understand how cytokines are involved in the pathogenesis of AAAs. 6,7) Previous studies have demonstrated that cytokine inhibition, including MCP-1, 12) IP-10, 13) TNF-α, 14,15) IL-1β, 16) IL-4, 17) IL-5, 18) IL-17, 19) IFN-γ, 20) SDF-1, 21) GM-CSF, 22) and VEGF, 23) was effective in suppressing the development of AAA in mice. However, other cytokines, including TGF-β, 24,25) IL-10, 25) IP-10, and IFN-γ, 13) have been reported to exhibit protective effects in experimental AAA. Furthermore, studies have also highlighted the complexity of the inflammatory network and cytokine functions as exemplified by the fact that IFN-γ and IP-10 have been reported to have either promotive or suppressive effects in experimental AAA. 13,20) Although animal studies have provided critical knowledge in understanding the mechanism of AAA, no single model recapitulates all the characteristics of human AAA. Besides, owing to the heterogeneity in histopathology 1) and clinical courses among patients, 26) cytokine profiles may be different among patients. Therefore, in addition to animal models of AAA, the role of cytokines should be characterized in the context of human AAA. 6) Notably, while the overall profile of cytokine secretions was similar in the four patients in the present study, some of the highly expressed cytokines, including MCP-1, SCGF-β, LIF, and G-CSF, exhibited a difference of >10-fold among the patients. Whether and how differences secretion profiles of specific cytokines reflect AAA activity and status remains to be elucidated in future research.
Our results indicated that STAT3 was found to be highly activated in human AAA tissue for several days in culture. Moreover, the exogenous addition of IL-6 to the tissue culture did not affect P-STAT3 levels (data not shown); it is possible that JAK/STAT pathway was already activated by the endogenous inflammatory cytokines within the AAA tissue as previously reported. 8) Indeed, IL-6 accumulated to approximately 100 ng/mL during 48 h of tissue culture, which would be sufficient to fully activate STAT3. In turn, JAK/STAT pathway in AAA tissue may promote the secretion of a subset of cytokines, as previously reported 27,28) and as demonstrated in the present study. However, consistent with previous reports, 29,30) JAK/STAT pathway did not appear to regulate the secretion of MMP-2, MMP-9, or TGF-β family.
The major limitations of the present study are the small number of patients, which precluded thorough characterization of the inflammatory network in human AAA tissue. Also, the role of cytokines that promote cell infiltration in the pathogenesis of AAA may be underestimated, because tissue in culture does not have a continuous supply of inflammatory cells from the bloodstream and surrounding tissue. Another limitation was the absence of normal tissue or tissue with other aortic diseases for comparison in the experimental group, which precluded the identification of AAA-specific cytokines. Because of these limitations, the present study should be observed as an initial screening for cytokines secreted at high levels among a panel of cytokines to characterize the inflammatory network within human AAA tissue. Besides, it should be noted that isolated tissue in culture differs starkly from aortic tissue in patients. For example, the aortic tissue in culture is free from hemodynamic stress, circulating humoral factors, or neuronal stimuli. Future studies are required to test whether cytokines secreted at high levels and their signaling pathways can serve as diagnostic markers or therapeutic targets for AAA.

Conclusion
In conclusion, we have characterized the profile of the secreted cytokines in AAA tissue, which appeared to be partly maintained by endogenous JAK/STAT pathway. Deciphering such an inflammatory network would lead to the identification of therapeutic targets, including cytokines and signaling molecules, and diagnostic markers for evaluating the activity of chronic inflammation in the pathogenesis of AAA.


extfieldsofstudy: Medicine Chemistry

text:
StAR-related lipid transfer domain 11 (STARD11)–mediated ceramide transport mediates extracellular vesicle biogenesis

Extracellular vesicles are important carriers of cellular materials and have critical roles in cell-to-cell communication in both health and disease. Ceramides are implicated in extracellular vesicle biogenesis, yet the cellular machinery that mediates the formation of ceramide-enriched extracellular vesicles remains unknown. We demonstrate here that the ceramide transport protein StAR-related lipid transfer domain 11 (STARD11) mediates the release of palmitate-stimulated extracellular vesicles having features consistent with exosomes. Using palmitate as a model of lipotoxic diseases and as a substrate for ceramide biosynthesis in human and murine liver cell lines and primary mouse hepatocytes, we found that STARD11-deficient cells release fewer extracellular vesicles. Moreover, STARD11 reciprocally regulated exosome ceramide enrichment and cellular ceramide depletion. We further observed that in STARD11 knockout cells intracellular ceramide accumulates and that this apparent inability to transfer cellular ceramide into extracellular vesicles reduces cellular viability. Using endogenous markers, we uncovered structural and functional colocalization of the endoplasmic reticulum (ER), STARD11, and multivesicular bodies. This colocalization increased following palmitate treatment, suggesting a functional association that may mediate ceramide trafficking from the ER to the multivesicular body. However, the size and number of multivesicular bodies were comparable in WT and STARD11-knockout cells. In conclusion, we propose a model of how STARD11 mediates ceramide trafficking in palmitate-treated cells and stimulates exosome biogenesis.

Extracellular vesicles are an important carrier of cell-derived information with emerging roles in cell-to-cell communication in health and disease (1)(2)(3)(4). Extracellular vesicles can be classified into exosomes, which arise from the multivesicular body, microvesicles derived from the plasma membrane, and apoptotic bodies formed by dying cells (5). Ceramides are known to play a role, in particular, in the formation of multivesicular body-derived exosomes (6). We have recently demonstrated that palmitate, a saturated fatty acid, elevated in the liver and in the circulation in obesity-associated disorders including fatty liver disease, stimulates the release of extracellular vesicles (7,8). Palmitate-stimulated extracellular vesicles are enriched in ceramide, and their release depends on the de novo synthesis of ceramide from exogenously supplied palmitate (8). De novo ceramide synthesis occurs at the endoplasmic reticulum (ER) 4 (9), and exosomes are formed as intraluminal vesicles (ILVs) of the multivesicular body (MVB) (10). However, it is not known how palmitate-stimulated ceramide is transported from the ER to the MVB to form ILVs, which give rise to exosomes upon their release from cells.
Ubiquitin-dependent cargo sorting of proteins to form ILVs requires the endosomal sorting complex required for transport (ESCRT) machinery, such that RNA silencing of ESCRT machinery components yields fewer and morphologically abnormal MVBs; yet the formation of ILVs and MVBs is not fully inhibited, indicating that ILVs can be generated by cellular processes in addition to the ESCRT machinery (11). For example, the sorting of other cargoes, such as the melanosomal protein Pmel17, remains unaffected in the absence of ESCRT components (12). Furthermore, lipids are also implicated in the formation of ILVs. The phospholipid lysobisphosphatidic acid can induce the formation of multivesicular liposomes in cellfree systems that resemble the MVB; although this lipid is found in vivo, its role in the formation of ILVs remains unexplored (13,32). The sphingolipid ceramide is implicated in the formation of ILVs and release of exosomes, such that inhibition of ceramide biosynthesis decreases exosome release (6,8). Thus, accumulated observations indicate that MVB biogenesis is diverse, and multiple mechanisms contribute to cargo packaging into the ILVs of MVBs and their release as exosomes.
The de novo biosynthesis of ceramide occurs at the ER (9). Newly formed ceramide is transported from the ER to the Golgi by nonvesicular transport mediated by ceramide transport protein (CERT), also known as StAR-related lipid transfer domain (STARD) 11, an evolutionarily conserved member of the STARD family of lipid transporting proteins with high substrate specificity (14 -17). The role of STARD11 in the formation of exosomes that are formed in a ceramide-dependent manner remains unknown.
Lipotoxicity of the saturated free fatty acid palmitate is a robust model for examining signaling pathways activated in lipotoxic hepatocytes, a cellular model germane to nonalcoholic fatty liver disease (19). In this regard, we have previously demonstrated that palmitate treatment leads to the release of extracellular vesicles from hepatocytes and that significant extracellular vesicle release occurs before the onset of palmitate-induced apoptosis (8). Furthermore, we have demonstrated that these vesicles are enriched in ceramide and dependent on the de novo synthesis of ceramide. However, the cellular trafficking machinery that mediates ceramide transport to form extracellular vesicles remains unknown. Herein, we report that in the absence of STARD11, palmitate-induced extracellular vesicle release is attenuated; correspondingly, when cells are unable to release ceramide containing extracellular vesicles, intracellular ceramide content increases with deleterious consequences. Palmitate-stimulated extracellular vesicles display markers consistent with exosomes. We demonstrate structural and functional colocalization of the ER, STARD11, and the MVB; this colocalization is increased by palmitate treatment. Thus, we have demonstrated that the ceramide transport protein STARD11 mediates the release of lipotoxic extracellular vesicles, likely via transport of newly synthesized ceramide from the ER to the MVB.

STARD11 is expressed in hepatocytes and mediates palmitateinduced extracellular vesicle release
Prolonged palmitate treatment induces hepatocyte apoptosis (19,20); therefore, we designed our experimental conditions to collect conditioned media for extracellular vesicle isolation following 16 h of treatment prior to the onset of significant palmitate-induced apoptosis, which occurred following 24 h of palmitate treatment as measured biochemically by caspase 3/7 activity (Fig. S1A). Moreover, we confirmed that palmitate-induced extracellular vesicle release was preserved in the presence of the caspase inhibitors benzyloxycarbonyl-VAD-FMK and IDN-6556 (Fig. S1B) and thus was not due to apoptotic bodies, which cannot be formed in the presence of caspase inhibitors (21). We further excluded a contribution from protein aggregates to palmitate-stimulated extracellular vesicles by floating extracellular vesicles in an iodixanol gradient, as previ-ously described by Kowal et al. (22). Palmitate-stimulated extracellular vesicles were isolated from fractions 3, 5, and 6 ( Fig. S1C).
Having established conditions for extracellular vesicle isolation, we next probed the hepatocyte expression of STARD11 in human and murine hepatocellular cell lines and primary mouse hepatocytes. STARD11 protein and mRNA were easily detected in human hepatoma cell lines HepG2 and Huh7, immortalized mouse hepatocytes (IMHs), mouse hepatoma cell line Hepa1-6, and primary mouse hepatocytes (Fig. S1, D-F). To determine the biologic significance of STARD11 in the release of palmitate-stimulated extracellular vesicles, also referred to as lipotoxic extracellular vesicles, we asked whether the release of these lipotoxic extracellular vesicles was mediated by STARD11. We used CRISPR/Cas9 genome editing technology to knock out STARD11 in mouse and human hepatocellular cell lines. Using these STARD11 knockout cell lines (STARD11 Ϫ/Ϫ ), we found that the release of lipotoxic extracellular vesicles depended on STARD11 in mouse and human hepatocytes (Fig. 1, A and B, respectively), in several distinct knockout clones. We verified the deletion of STARD11 by Western blotting (Fig. 1, A and B, bottom panels). Lipid loading can stimulate lipoprotein secretion; therefore, we interrogated our cell line for apolipoproteins A1, B100, and B48, which are requisite for the secretion of HDL and VLDL particles, respectively. We could not detect these lipoproteins in our cell line and in palmitate-stimulated extracellular vesicles excluding a contribution of coisolated HDL particles and VLDL particles to our extracellular vesicle counts (Fig. S1G).
Oleate, a monounsaturated fatty acid, is the second most physiologically abundant fatty acid in humans (7). Unlike palmitate, oleate is not a direct substrate for the formation of ceramides (23). Therefore, we asked whether oleate treatment led to extracellular vesicle release. We found no increase in extracellular vesicle release in oleate treated WT cells and similar responses in STARD11 Ϫ/Ϫ cells (Fig. 1, A and B). Thus, STARD11 is requisite for the release of palmitatestimulated lipotoxic extracellular vesicles. We did not observe any changes in the size distribution of extracellular vesicles from STARD11 Ϫ/Ϫ cells compared with WT cells in either mouse or human hepatocytes (Fig. 1, C and D). We next analyzed basal extracellular vesicle release in control and STARD11 Ϫ/Ϫ cells. We found that basal extracellular vesicle release was comparable in WT and STARD11 Ϫ/Ϫ mouse (Fig.  1E) and human (Fig. 1F) hepatocytes. Altogether these data demonstrate that STARD11 mediates extracellular vesicle release specifically following palmitate treatment. This is likely due to de novo synthesis of ceramide from palmitate, as previously reported by us (8), and possibly due to the trafficking of palmitate-stimulated ceramide to the MVB.

Extracellular vesicle and whole-cell ceramide are reciprocally related in STARD11 knockout cells
Because the release of palmitate-stimulated extracellular vesicles depends on ceramide biosynthesis as previously shown by us (8) and confirmed (Fig. S2A), we asked whether a defect in ceramide transport affects extracellular vesicle-ceramide content. We reasoned that extracellular vesicles derived from WT cells would be ceramide-enriched, whereas extracellular vesicles derived from STARD11 Ϫ/Ϫ cells, which lack ceramide transport protein, would not. To demonstrate that STARD11 is required for the biosynthesis of ceramide-enriched extracellular vesicles, we measured extracellular vesicle ceramide by tandem MS. Consistent with our previous data (8), palmitate treatment led to the release of ceramide-enriched extracellular vesicles ( Fig. 2A). However, extracellular vesicles derived from palmitate-treated STARD11 Ϫ/Ϫ cells were not enriched in ceramide. We found no increase in ceramide in oleate-stimulated extracellular vesicles (Fig. 2B). Palmitate treatment led to an increase in whole-cell ceramide in WT cells (Fig. 2C). The increase in whole-cell ceramide levels was significantly greater in STARD11 Ϫ/Ϫ cells (Fig. 2C). Oleate treatment did not increase whole-cell ceramide levels in WT or STARD11 Ϫ/Ϫ cells (Fig. 2D). These data suggest that

Palmitate-induced exosome biogenesis
STARD11-mediated trafficking of palmitate-stimulated ceramide is an important pathway for the cellular export of ceramide because STARD11 Ϫ/Ϫ cells accumulate ceramide intracellularly.

STARD11-mediated ceramide transport mitigates palmitateinduced cytotoxicity
Having demonstrated ceramide accumulation in STARD11 Ϫ/Ϫ cells, we next asked whether ceramide accumulation is toxic for cells. As discussed above, we found no increase in cell death or decrease in cell viability following 16 h of treatment with palmitate to correspond to the time that conditioned medium was collected for extracellular vesicle isolation. However, a longer duration of palmitate treatment led to a greater increase in cell death and a reduction in cell viability in STARD11 Ϫ/Ϫ cells compared with WT cells following 20 h of palmitate treatment, consistent with our previous publications, which have demonstrated a significant time dependence of palmitate-induced hepatocyte apoptosis (Fig. S2, B and C) (19,20). These data suggest that the ability to exclude ceramide from hepatocytes partially mitigates palmitate-induced toxicity.

Palmitate-stimulated extracellular vesicles have features of exosomes
Small extracellular vesicles derived from multivesicular bodies are known to express an array of markers, suggestive of their cellular origin within the MVB (22,24). These markers include Alix, syntenin, and tumor susceptibility gene 101 (TSG101), which have been demonstrated to be markers of small extracellular vesicles arising from the MVB, i.e. exosomes (22,24). We interrogated palmitate-stimulated EVs for the presence of Alix, syntenin, and TSG101 and found that these markers were enriched in palmitate-stimulated extracellular vesicles from WT cells, suggesting that these extracellular vesicles are exosomes arising within the MVB (Fig. 3). In STARD11 Ϫ/Ϫ cells, basal levels of Alix, syntenin, and TSG101 were comparable with WT cells, and there was no increase in these exosome markers following palmitate treatment. We also observed an increase in CD81 in extracellular vesicles from palmitatetreated WT cells and not in STARD11 Ϫ/Ϫ cells. Whole-cell levels of Alix, syntenin, and TSG101 were unchanged following palmitate treatment.
STARD11 is a membrane-bound protein that is known to bind with vesicle-associated membrane protein-associated protein (VAP) in the ER membrane with its FFAT motif and phosphatidylinositol-4 monophosphate in the Golgi membrane with its N-terminal pleckstrin homology domain (25,26). However, it is known to also bind phosphatidylinositol-3 monophosphate, which is enriched in endosome membranes (27). In this location, it could be internalized as a component of the ILV membrane. To address this question, we first asked whether STARD11 is a part of the extracellular vesicle cargo. As demonstrated in the Western blotting analysis, we did not  Figure 3. Palmitate-stimulated EVs are consistent with exosomes. A, EVs isolated from equal number of cells and whole-cell lysates (WCL) from immortalized mouse hepatocyte cell line were analyzed by Western blotting. Alix, TSG101, syntenin, and CD81 were used as small EV markers. GAPDH was used as a loading control. B, these expression levels were quantified by densitometry. *, p Ͻ 0.05; **, p Ͻ 0.01; ns, not significant; Veh, vehicle. All error bars are S.E. These data were obtained from three or more independent experiments.

STARD11 colocalizes with ER and MVB
We asked whether STARD11 associates with the membrane compartment where ceramide synthesis occurs (the ER) and the MVB, where exosomes are formed. As previously reported by others (29), we observed MVBs within 30 nm of the ER membrane suggestive of functional colocalization (Fig. S3A). To confirm these observations, we used immunofluorescence microscopy in mouse hepatocyte cell line transfected with GFP-tagged STARD11 (STARD11-GFP) and CD63 tagged with mCherry (CD63-mCherry) (Fig. 4A). We found that STARD11 colocalized with the MVB. Next, we performed immunofluorescence for the ER marker KDEL, an ER localization motif (30), in a mouse hepatocyte cell line transfected with STARD11-GFP. We found that STARD11 colocalized with the ER. We also confirmed that the ER and MVB were in close proximity in cells transfected with CD63-mCherry to label the MVB and KDEL immunofluorescence to label the ER. We confirmed this colocalization in human hepatoma cell line, Huh7 (Fig. 4B).

Palmitate increases the colocalization of STARD11 with the MVB
Having demonstrated a structural colocalization between the ER, MVB, and STARD11, we next asked whether STARD11 association with the MVB increases following palmitate treatment. We first validated the specificity of the STARD11 antibody (Fig. S3B). Next, as demonstrated in Fig. 5 (A and B), we found that there was significant colocalization of endogenous STARD11 with the MVB, which increased significantly further following palmitate treatment (Fig. 5B). To confirm these findings, we utilized the fluorescent sphingolipid N-Rh-PE, which efficiently labels MVBs and has been used to study MVB trafficking (31,32). Mouse hepatocyte cell line transfected with CD63 tagged with GFP (CD63-GFP) was labeled with N-Rh-PE. Both N-Rh-PE and CD63 labeled the same cellular compartment as demonstrated in Fig. 5C. Next, as demonstrated in Fig. 5 (D and E), we found that there was significant colocalization of STARD11 with the N-Rh-PE-labeled MVB, which increased significantly further following palmitate treatment. Notably, total protein and mRNA levels of STARD11 were unchanged in palmitate-treated hepatocytes (Fig. S1, D-F). We did not observe an increase in STARD11 and Golgi colocalization (Fig. 5, F and G). The increased association of STARD11 with MVBs following palmitate treatment demonstrates an increase in functional association between the ceramide transport protein STARD11 and the exosome formation compartment, the MVB, and likely mediates increased ceramide flux to the MVB, although we cannot exclude indirect trafficking of ceramide from the ER to the Golgi to the MVB.
To examine the association between the ER, the MVB, and STARD11 using endogenous markers, we used triple immunofluorescence microscopy in a mouse hepatocyte cell line with antibodies against protein disulfide isomerase (PDI) to label the ER, CD63 to label the endosome, and STARD11, which was detected in the cytosol and the nucleus, consistent with its known distribution. We found that STARD11 colocalized with both the ER and the MVB (Fig. 6A), as previously observed with

Palmitate-induced exosome biogenesis
the fluorescently tagged proteins. We quantified the colocalization of the endogenous markers and found that STARD11 colocalization with the MVB and ER increased following palmitate treatment as did ER and MVB colocalization (Fig. 6B). To further confirm in situ proximity between the ER and MVB, we performed a proximity ligation assay using antibodies against KDEL to label the ER and CD63 to label the MVB in palmitatetreated cells. There was a significant increase in the ER-MVB proximity as measured by the proximity ligation assay in palmitate-treated cells (Fig. 6, C and D). These colocaliza-

Palmitate-induced exosome biogenesis
tion data support an increase in functional association between the ER, STARD11, and the MVB following palmitate treatment.

MVB formation is unchanged in STARD11 ؊/؊ cells
To determine whether an MVB formation defect in STARD11 Ϫ/Ϫ cells is the mechanistic basis of a reduction in palmitate-induced extracellular vesicle release, we assessed MVB size and number in WT and STARD11 Ϫ/Ϫ cells. We used the sphingolipid N-Rh-PE to label MVBs as previously described by others (32,33) followed by super-resolution structured illumination microscopy and also EM to quantify the size and the number of MVBs. When quantified by this approach the size, morphology, and number of MVBs was unchanged between WT and STARD11 Ϫ/Ϫ basally and following palmitate treatment (Fig. S3, C-F), suggesting that MVB formation is unchanged in STARD11 Ϫ/Ϫ cells.
Processes that determine MVB trafficking into one of two fates either targeted to the plasma membrane for release or to the lysosomes for degradation remain incompletely understood. We asked whether STARD11, and hence ceramide enrichment, may contribute to endocytic trafficking. Therefore, we examined the endocytic fate of N-Rh-PE-labeled MVBs over time in live cells and focused on dissecting whether they were headed to lysosomes, labeled with LysoSensor Green. The colocalization of the MVBs and the lysosomes increased significantly in palmitate-treated STARD11 Ϫ/Ϫ cells (Fig. 7, A  and B).

Discussion
Our present study describes a mechanism for the release of ceramide enriched extracellular vesicles in palmitate-treated cells, a cell-based model for hepatocyte lipotoxicity. We report that (i) STARD11 is abundant in hepatocytes; (ii) STARD11 mediates the release of palmitate-stimulated ceramideenriched extracellular vesicles; (iii) STARD11 colocalizes to the ER and to the MVB; and (iv) STARD11-MVB colocalization and ER-MVB colocalization increases in palmitate-treated hepatocytes. These data suggest that STARD11-mediated ceramide transport to the MVB may lead to the formation of ceramide-enriched extracellular vesicles in palmitate-treated cells. Given the known physiologic role of STARD11 in transporting ceramide, which is the predominant cellular ceramide transport pathway, these data suggest that the intercompartmental transport of palmitate-stimulated ceramide by STARD11 from the ER leads to the formation of small extracellular vesicles that have features of exosomes. These data are germane to the liver lipotoxicity syndrome observed in human fatty liver disease. STARD11 is conserved in humans and mice (34). It is a splice variant of collagen type IV ␣-3binding protein (COL4A3BP) gene product lacking 26 amino acids encoded by exon 11, compared with the longer isoform, which is designated CERT L . STARD11 protein contains a C-terminal START domain that mediates ceramide transport and an N-terminal pleckstrin homology domain that binds to phosphoinositide in the Golgi membrane. A middle region contains an FFAT motif that targets STARD11 to VAP on the outer surface of the ER membrane (35). Our data support a role for STARD11 in mediating ER to MVB ceramide trafficking, leading to the formation of ILVs. This may occur indirectly via trafficking to the Golgi and then to the MVB or may be a result of direct trafficking from the ER to the MVB. Although we see an increase in ER-MVB colocalization following palmitate treatment, whether truly functional membrane contact sites are formed and necessary for ceramide transport in this context is a question for future studies. We did not detect STARD11 on exosomes, suggesting that it is not an integral part of the MVB membrane. Regardless of the trafficking pathway, STARD11 mediates the release of palmitate-stimulated extracellular vesicles.
In cells that lack STARD11, we found no decrease in basal extracellular vesicle release. However, palmitate-stimulated extracellular vesicles, which have features consistent with exosomes, were reduced. Thus, we conclude that STARD11 plays a role specifically in the release of palmitate-stimulated exosome formation. Consistent with a reduction in the release of ceramide-enriched extracellular vesicles, STARD11 Ϫ/Ϫ cells demonstrated an intracellular accumulation of ceramide that correlated with a reduction in cell viability. These data suggest that the release of ceramide via exosomes may be a pathway to mitigate palmitate-induced toxicity. As we were preparing this manuscript, Obata et al. (36) published a manuscript demonstrating unloading of ceramide from endothelial cells via extracellular vesicle efflux mechanisms. Given our expertise in hepatocyte lipoapoptosis (19,20), we were careful in selecting cell culture conditions where apoptosis is not significantly increased to try to understand events that occur in viable cells. Additionally, to confirm that we were not mistaking apoptotic bodies for exosomes, we confirmed that palmitate-induced extracellular vesicle release was preserved in the presence of caspase inhibitors, which are known to inhibit the release of apoptotic bodies (21).
We found that STARD11 was abundant in human and mouse hepatocytes and mouse liver. Although levels of STARD11 did not change with lipotoxic (palmitate) treatment of cells, we noted that the compartmental distribution of STARD11 was altered in palmitate-treated cells such that there was an increase in its association with the MVB following palmitate treatment. We observed no increase in STARD11 and Golgi colocalization in palmitate-treated cells. Furthermore, we observed an increase in ER-MVB colocalization by immunofluorescence microscopy and by the proximity ligation assay in palmitate-treated cells, suggesting an increase in functional association between the ER and the MVB under palmitate

Palmitate-induced exosome biogenesis
treatment. Recent studies have shown phosphorylation-dependent regulation of STARD11 contact with the ER membrane protein VAP, such that phosphorylation at serine 315 markedly enhanced STARD11-VAP interactions (37). Palmitate is a well recognized activator of the stress kinase c-Jun N-terminal kinase and other cytosolic and plasma membrane kinases (19). Whether, palmitate induces a phosphorylation-dependent increase in STARD11 interactions at the MVB is a question we will address in future experiments. We found that there were no significant decreases in MVB size and number in STARD11 Ϫ/Ϫ cells. In conclusion, this is the first report describing the importance of the ceramide transport protein, STARD11, also known as CERT in the formation of ceramide-enriched extracellular vesicles. Our data support a model wherein STARD11 promotes the efficient transfer of palmitate-stimulated ceramide from the ER to the MVB, where it drives the formation of ILVs. Elucidation of this fundamental pathway provides a potential target to modulate the release of extracellular vesicles in lipotoxic conditions. STARD11 may be important in other diseases associated with ceramide-dependent extracellular vesicles, a testable hypothesis.

Extracellular vesicle isolation and characterization
Cells were grown to 90% confluency on 150-mm tissue culture dishes. The cells were washed twice with PBS to eliminate FBS-derived extracellular vesicles. Then cells were treated with either 400 M palmitate (PA), 400 M oleate (OA), or vehicle for 16 h in growth medium supplemented with 5% extracellular vesicle-depleted FBS, which was prepared by overnight centrifugation at 100,000 ϫ g at 4°C according to standard protocols (18) and 1% BSA. The optimal concentration and duration for cellular extracellular vesicle release prior to the onset of apoptosis in IMH and Huh7 was decided as previously described (8). Differential ultracentrifugation was used to sequentially isolate small extracellular vesicles, which we have referred to simply as extracellular vesicles throughout. Briefly, collected cell culture conditioned medium was depleted of cells and cellular debris initially by low-speed centrifugations at 2,000 ϫ g for 20 min and 10,000 ϫ g for 40 min. This was followed by ultracentrifugation at 100,000 ϫ g for 90 min to pellet extracellular vesicles. The pellets were washed in PBS and centrifuged again at 100,000 ϫ g for 90 min. The obtained extracellular vesicle pellets were resuspended in PBS or lysed in radioimmune precipitation assay buffer for downstream experiments.
For each experimental condition, isolated extracellular vesicles were normalized to cell number and expressed relative to the vehicle-treated condition, unless indicated otherwise. The size distribution and concentration of isolated extracellular vesicles was assessed by nanoparticle tracking analysis as previously described by us (8). Briefly, extracellular vesicle samples were diluted in PBS at a range of concentrations between 2Eϩ08 and 8Eϩ08 particles/ml. Each sample was perfused through the sample chamber at a constant rate of 25 l/min using a syringe pump. The light scatter and Brownian motion of each sample of nanoparticles was recorded at least three times, 30 s each at constant room temperature (22.5°C); particle tracks were analyzed by NanoSight software to measure the concentration of the particles (particles/ml) and size (in nanometer). For each experimental condition, EVs isolated from equal number of cells were expressed relative to the vehicle-treated condition. For basal EV release, EV numbers were normalized to cell numbers.

Caspase 3/7 assay
Activation of caspase 3/7 is the biochemical hallmark of apoptosis (19). For caspase 3/7 assay 30,000/cm 2 IMH cells were cultured in 96-well plates. 48 h later, the cells were first pretreated with 10 M ZVAD-FMK (Santa Cruz Biotechnology, Dallas, TX) or IDN-6556 (MedKoo Biosciences, Morrisville, NC) for 1 h followed by 400 M palmitate or vehicle in the absence or presence of caspase inhibitors for 16 or 24 h. Equal volume of DMSO was used as control. After 16 or 24 h of treatment, respectively, apoptotic cell death was measured by Apo-ONE homogeneous caspase-3/7 assay (Promega, Madison, WI) following the manufacturer's protocol.

Extracellular vesicles in caspase inhibitor-treated cells
IMH cells were cultured in 10-cm dishes. Approximately 90% confluent cells were treated with 10 M of ZVAD-FMK (Santa Cruz Biotechnology) or IDN-6556 (MedKoo Biosciences, Morrisville, NC) for 1 h. Equal volume of DMSO was used as control. Before palmitate treatment, the cells were washed twice with PBS, and then the medium was changed to assay medium supplemented with palmitate or vehicle, as above, and caspase inhibitors (10 M of ZVAD-FMK or IDN-6556). After 16 h, the medium was recovered, and sequential low-speed centrifugation was performed as described above to isolate extracellular vesicles. The extracellular vesicle pellet was resuspended in 100 l of PBS and subjected to nanoparticle tracking analysis. For each experimental condition, isolated extracellular vesicles were normalized to cell number and expressed relative to the vehicle-treated condition.

De novo ceramide synthesis inhibitor
IMH cells were treated with vehicle or palmitate, with or without 10 M serine palmitoyltransferase-1 inhibitor (Myriocin; Cayman Chemicals, Ann Arbor, MI) for 16 h. Extracellular vesicles were isolated and analyzed by nanoparticle tracking analysis, as described above.

Iodixanol gradient separation of extracellular vesicles
Extracellular vesicles isolated by ultracentrifugation from palmitate or vehicle-treated IMH cells (ϳ 200 million) were Palmitate-induced exosome biogenesis diluted in 1.5 ml of buffer containing 0.25 M sucrose, 10 mM Tris, pH 8.0, 1 mM EDTA (pH 7.4). The solution was mixed 1:1 with 60% (w/v) stock solution of iodixanol (OptiPrep; Stemcell Technologies, Cambridge, MA). Then 3 ml of extracellular vesicle suspension was transferred to a SW55Ti rotor tube. A 40% iodixanol working solution was prepared (40% (w/v) iodixanol, 0.25 M sucrose, 10 mM Tris, pH 8.0, 1 mM EDTA, pH 7.4) and used to prepare 20 and 10% (w/v) iodixanol solutions. Next to make the gradient, 1.3 ml of 20% (w/v) iodixanol and 1.2 ml of 10% iodixanol were successively layered on top of the 3 ml of vesicle suspension, and tubes were centrifuged for 1 h at 4°C at 350,000 ϫ g in SW55Ti; 10 fractions of 490 l were collected from the top of the tube. Density was assessed from 5 l of each fraction using a refractometer. The remaining fractions were diluted with 4 ml of PBS and centrifuged for 30 min at 100,000 ϫ g in the same rotor. These concentrated fractions were resuspended in 30 l of PBS and subjected to nanoparticle tracking analysis. For each experimental condition, isolated extracellular vesicles were normalized to cell number and expressed relative to the vehicle-treated condition. This method was based on the protocol described by Kowal et al. (22).

Lipidomics
Ceramides were measured using tandem MS at Mayo Clinic Metabolomics Core Laboratory, as previously described by us (8). Extracellular vesicles isolated from equal numbers of cells treated with either vehicle, oleate, or palmitate were used to quantify changes in extracellular vesicle ceramides. Cell pellet ceramides were normalized to protein content.

Western blotting
Treated cells were collected by scraping and lysed in radioimmune precipitation assay buffer (50 mM Tris-HCl, 1% NP-40, 0.1% SDS, 150 nM NaCl, 1 mM EDTA, and 0.5% sodium deoxycholate) with protease and phosphatase inhibitors. The protein concentrations were determined by the Bio-Rad DC protein assay. Equal amounts of whole-cell lysate or protein isolated from extracellular vesicles derived from equal number of cells were loaded onto Criterion 4 -15% or 12.5% Tris-HCl gel (Bio-Rad) and electrotransferred to PVDF membrane. The membranes were blocked with blocking buffer (5% nonfat milk in TBS-Tween) for 1 h at room temperature. Membranes were incubated with the following primary antibodies overnight: anti-Alix (2171; Cell Signaling); anti-STARD11 (15191-1-AP; Proteintech); anti-TSG101 (ab125011) and anti-Syntenin (ab19903) from Abcam; anti-ApoA1 (sc30089), anti-actin (sc1615), and anti-CD81 (sc166029) from Santa Cruz Biotechnology; and anti-ApoB (MABS2046) and anti-GAPDH (MAB374) from EMD Millipore Corp. Antigen-bound primary antibodies were detected with horseradish peroxidase-conjugated secondary antibodies against mouse, rabbit, or goat (Santa Cruz Biotechnology). Proteins of interest were visualized with enhanced chemiluminescence reagents (Amersham Biosciences) and HyBlot CL film (Denville Scientific Inc., Metuchen, NJ). Films were scanned using a Cannon LiDe 110 scanner and converted to grayscale in Adobe Photoshop CC 2015, and brightness and contrast were adjusted equally across the entire images.

Immunofluorescence
The cells were grown on sterile glass coverslips in 6-well plates. The cells were fixed with 4% paraformaldehyde for 15 min, permeabilized with 0.1% Triton X-100 in PBS for 10 min, or fixed and permeabilized with ice-cold methanol for 15 min, and blocked with 5% BSA, 0.1% glycine in PBS for 30 min at room temperature. After incubating with anti-CD63 (MBS438072; MyBioSource), anti-STARD11 (PA5-28797; Thermo Fisher Scientific), anti-syntaxin6 (ab12370; Abcam), or anti-KDEL (ab50601; Abcam and sc-58774; Santa Cruz Biotechnology) antibodies diluted in blocking buffer overnight at 4°C, the cells were washed three times with PBS, and incubated with fluorescent secondary antibodies (Alexa Fluor 350, 488, or 594; Thermo Fisher Scientific) for 1 h at room temperature protected from light. For triple immunofluorescence anti-CD63 (564221; BD Pharmingen), anti-STARD11, and anti-PDI (MA3019; Thermo Fisher Scientific) were utilized. Then after washing with PBS, coverslips were mounted in Prolong Anti-Fade (Life Technologies) on a clean glass slide.

Labeling MVBs with fluorescent lipid
The fluorescent phospholipid analog N-Rh-PE was obtained from Thermo Fisher Scientific. The cells were labeled at 4°C with 5 M N-Rh-PE in serum-free DMEM for 1 h. After this incubation period, the medium was removed, and cells were washed with cold serum-free DMEM to remove excess unbound lipids. After the addition of treatment medium, labeled cells were incubated for 1 h and then fixed with 4% paraformaldehyde for observation by confocal microscopy.

Proximity ligation assay
The cells were cultured on glass coverslips, fixed, and permeabilized with ice-cold methanol. The cells were incubated with anti-CD63 (sc15363; Santa Cruz Biotechnology) and anti-KDEL (sc58774; Santa Cruz Biotechnology) antibodies and pro-Palmitate-induced exosome biogenesis cessed according to the manufacturer's protocol (Duolink PLA; Sigma). The images were observed by confocal microscope.

Labeling lysosome with LysoSensor Green
The cells were labeled with 1 M LysoSensor Green (Thermo Fisher Scientific) into growth medium for 30 min in the incubator. The cells were washed with PBS and then fixed.

Confocal microscopy
Fluorescence was observed with an LSM 780 confocal microscope (Zeiss) and a Plan-Apochromat 40ϫ/1.4 oil differential interference contrast M27 objective (Zeiss). A 405-nm laser was used for the blue channel. A 488-nm laser was used for the green channel, and a 561-or 594-nm laser was used for the red channel. Images were taken at room temperature. ZEN 2.3 lite software (Zeiss) was used for acquiring images. ImageJ (National Institutes of Health) was used to analyze the raw images. The quantification shows the Pearson coefficients of colocalization. To avoid artifacts from perinuclear crowding, fluorescence pixel intensity was measured in the entire observed field rather than subcellular regions of interest. 10 -20 random fields in each group were selected for quantification and statistical analysis.

Electron microscopy
Vehicle-treated IMH cells were fixed in Trump's solution (4% formaldehyde ϩ 0.1% glutaraldehyde in 0.1 M phosphate buffer). Palmitate-treated cells were fixed in 3% glutaraldehyde and 0.1 M sodium cacodylate buffer. These cells were then processed for EM analysis using standard procedures and observed with a JEOL 1400 Plus transmission electron microscope (JEOL USA, Peabody, MA) at 80 kV.

Super-resolution microscopy
IMH cells were treated with vehicle or 400 M palmitate for 6 h and then labeled with N-Rh-PE. For imaging of MVBs of IMH cells, the cells were incubated in treatment medium for 1 h and then fixed with 4% paraformaldehyde. Structure illumination microscopy images were captured using an Elyra PS.1 microscope (Zeiss) and a Plan-Apochromat 63ϫ/1.4 oil differential interference contrast M27 objective (Zeiss) at room temperature.

CRISPR/Cas9 gene editing
The online tool at (http://crispr.mit.edu) 5 was used to design the single guide RNA spanning the mouse STARD11 (sgRNA, 5Ј-CACCGCGGCTGTCGCGTCTCCATGT-3Ј) and human STARD11 (sgRNA, 5Ј-CCGGGAATCCAGCTTGCGTCG-ACA-3Ј and 5Ј-CCGGTAATCAGAGCTGGAACTCGT-3Ј). Annealed oligonucleotides of sgRNA were used to generate a lentivirus following subcloning into the lentiCRISPRv1 plasmid (Addgene) and transfected into HEK293T cells using Lipofectamine LTX reagent, as previously described by us (8). Virus was harvested at 48 h after transfection, and IMH cells were infected with STARD11 targeting lentivirus in the presence of 8 g/ml Polybrene. Infected cells were selected under 4 g/ml blasticidin (InvivoGen) selection pressure. STARD11 knockout cell lines in Huh7 cells were created by Guide-it CRISPR/Cas9 system (TaKaRa Biotechnology Inc.) according to the manufacturer's instruction.

Quantitation of apoptosis and cytotoxicity
IMH cells were stained with 4Ј,6-diamidino-2-phenylindole for 5 min and visualized using fluorescent microscope to count number of apoptotic nuclei. IMH WT and STARD11 Ϫ/Ϫ cells were plated in 96-well plates. The cells were then treated with 400 M palmitate. After 16 and 20 h of treatment, cell viability was measured by WST-1 assay (Sigma-Aldrich) per the manufacturer's instructions.

Statistical and data analyses
The data represent the means Ϯ S.E. from three or more experiments unless indicated. Two-tailed Student's t test was used for comparing groups. Statistical analyses were performed in GraphPad Prism version 6.00 for Windows (GraphPad Software, La Jolla, CA). A p value of Ͻ0.05 was considered significant.


s2fieldsofstudy: Biology Medicine Psychology

text:
Quantitative susceptibility mapping as an indicator of subcortical and limbic iron abnormality in Parkinson's disease with dementia

Late stage Parkinson's disease (PD) patients were commonly observed with other non-motor comorbidities such as dementia and psychosis. While abnormal iron level in the substantia nigra was clinically accepted as a biomarker of PD, it was also suggested that the increased iron deposition could impair other brain regions and induce non-motor symptoms. A new Magnetic Resonance Imaging (MRI) called Quantitative Susceptibility Mapping (QSM) has been found to measure iron concentration in the grey matter reliably. In this study, we investigated iron level of different subcortical and limbic structures of Parkinson's disease (PD) patients with and without dementia by QSM. QSM and volumetric analysis by MRI were performed in 10 PD dementia (PDD) patients (73 ± 6 years), 31 PD patients (63 ± 8 years) and 27 healthy controls (62 ± 7 years). No significant differences were observed in the L-Dopa equivalent dosage for the two PD groups (p = 0.125). Putative iron content was evaluated in different subcortical and limbic structures of the three groups, as well as its relationship with cognitive performance. One-way ANCOVA with FDR adjustment at level of 0.05, adjusted for age and gender, showed significant group differences for left and right hippocampus (p = 0.015 & 0.032, respectively, BH-corrected for multiple ROIs) and right thalamus (p = 0.032, BH-corrected). Post-hoc test with Bonferroni's correction suggested higher magnetic susceptibility in PDD patients than healthy controls in the left and right hippocampus (p = 0.001 & 0.047, respectively, Bonferroni's corrected), while PD patients had higher magnetic susceptibility than the healthy controls in right hippocampus and right thalamus (p = 0.006 & 0.005, respectively, Bonferroni's corrected). PDD patients also had higher susceptibility than the non-demented PD patients in left hippocampus (p = 0.046, Bonferroni's corrected). The magnetic susceptibilities of the left and right hippocampus were negatively correlated with the Mini-Mental State Examination score (r = −0.329 & -0.386, respectively; p < 0.05). This study provides support for iron accumulation in limbic structures of PDD and PD patients and its correlation with cognitive performance, however, its putative involvement in development of non-motor cognitive dysfunction in PD pathogenesis remains to be elucidated.

T manifestations in Parkinson's disease is dementia (PDD), for which the prevalence and annual incidence are estimated at respectively 30-40% (Burn and Yarnall, 2014;Emre et al., 2007;Goetz et al., 2008) and 10% (Goetz et al., 2008) of PD patients. This indicates that such potentially disabling complication of PD should be carefully addressed in clinical management. Patients with PDD generally experience significant cognitive decline, distinct from that due to Alzheimer's disease (AD), including impairment of executive function, attention, visuospatial function, constructional praxis, and memory (Burn and Yarnall, 2014;Goetz et al., 2008). Notably, greater deficits in executive and visuospatial functions and lesser in language functions are observed in PDD than AD (Burn and Yarnall, 2014;Goetz et al., 2008). While some studies propose an association between Apolipoprotein E (APOE) and the dementia symptoms of PDD (Irwin et al., 2012;Monsell et al., 2014), others do not support such claims (Burn and Yarnall, 2014;Mengel et al., 2016), thus rendering the mechanism underlying development of dementia in PD and its relationship with the AD-type dementia to be inconclusive.
Various studies have been performed to identify abnormalities in the brain of PDD patients. Imaging studies such as Magnetic Resonance Imaging (MRI) reported structural change in the hippocampus and amygdala of PDD patients, suggesting that the dementia symptom in PD might be associated with limbic atrophy (Aarsland et al., 2008); one study by Kalaitzakis et al. also suggested the involvement of limbic system in PDD, with the association between dementia and α-synuclein pathology in the limbic structures being observed (Kalaitzakis et al., 2009). These findings suggest plausible association between limbic abnormality and the dementia symptom, and that further investigation of the involvement of limbic structures in PDD is warranted.
Abnormal subcortical iron deposition in PD has been postulated to be the cause of the degeneration of dopaminergic neurons in the substantia nigra pars compacta (Hare et al., 2013;Jenner, 1991;Rouault and Cooperman, 2006). In a hypothesis of PD neurodegeneration, iron is suggested to induce α-synuclein pathology (Hare et al., 2013). αsynuclein is a presynaptic neuronal protein that is abundant in human brain and can be found in different brain regions including neocortex, hippocampus, substantia nigra, thalamus, and cerebellum. Abnormal aggregation of α-synuclein in PD patients, a clinical pathological hallmark of the disease, contributes to the formation of Lewy bodies which the major component is α-synuclein (Marques and Outeiro, 2012;Stefanis, 2012). Such pathological feature rendered PD to be considered as a type of synucleinopathies. Since α-synuclein aggregation has also been observed in limbic structures and is itself associated with the onset of dementia in PDD, we hypothesize that iron accumulation in PD could also be involved in the later overt development of neuropsychiatric symptoms in PD patients.
Quantitative Susceptibility Mapping (QSM) is a novel technique which allows the determination of tissue's bulk magnetic susceptibility distribution from gradient echo magnetic resonance phase images. A previous study by Langkammer et al. reported a strong linear correlation between chemically determined iron concentration and bulk magnetic susceptibility in grey matter structures (Langkammer et al., 2012). The objective of this study is to identify the role of abnormal iron metabolism in PD-type dementia by comparing the in vivo putative iron content measured with QSM, of different subcortical and limbic brain structures amongst healthy subjects and PD patients with or without dementia. In addition, any association between iron and the expression of dementia and psychotic symptomatology in PD is addressed. MR volumetric analysis of the subcortical and limbic brain structures is also performed.

Participants
This study was approved by the local Institutional Review Board.
The recruited participants were divided into three groups based on clinical diagnosis and result of neuropsychiatric assessments. A total of 68 participants were recruited with referral from experienced physicians. All participants or their caregivers were carefully explained for the study by the responsible medical officers before full written informed consent was obtained. The study cohort comprised of 10 PDD patients (8 males, mean age ± S.D. = 73 ± 6 years, mean illness duration ± S.D. = 13 ± 8 years), 31 non-demented PD patients (17 males, mean age ± S.D. = 63 ± 8 years, mean illness duration ± S.D. = 8 ± 5 years) and 27 healthy controls (14 males, mean age ± S.D. = 62 ± 7 years). PD was diagnosed using the UK Parkinson's Disease Society Brain Bank clinical diagnostic criteria (Hughes et al., 1992). PD patients were classified as PDD when they fulfilled the level one diagnostic criteria proposed by the Movement Disorder Society (MDS) Holden et al., 2016;Vasconcellos and Pereira, 2015). Patients with other known neurodegenerative disorders were excluded. Severity of motor deficit was assessed with both Section III of Unified Parkinson's Disease Rating Scale (UPDRS-III) and Hoehn & Yahr staging (Hoehn and Yahr, 1967). The cumulative L-Dopa Equivalence (mg) of the PD patients were also obtained for the evaluation of the differences between the study cohorts.

Neuropsychiatric assessments
Neuropsychiatric status of all subjects were assessed with the following tests: Mini-mental State Examination (MMSE) to assess cognitive impairment (Folstein et al., 1975); Parkinson Psychosis Rating Scale (PPRS) and Positive and Negative Syndrome Scale (PANSS) to examine the severity of psychosis (Friedberg et al., 1998); Self-assessment of Montgomery-Åsberg Depression Rating Scale (MADRS-S) to measure the severity of depression symptom (Kay et al., 1987;Montgomery and Asberg, 1979), and Yale-Brown Obsessive Compulsive Scale (Y-BOCS) to measure obsessive-compulsive symptoms (Goodman et al., 1989). The complete demographics and the clinical neuropsychiatric profile of all subjects are listed in Table 1.

Image post-processing
QSM computations were performed using MATLAB R2014a. The phase image was unwrapped with the Laplacian-based algorithm (Li et al., 2011;Schofield and Zhi, 2003) and was further processed for background phase removal with RE-SHARP (Sun and Wilman, 2014). QSM dipole inversion was performed with the L1-norm total-variationbased regularization algorithm with magnitude image as structural prior (Bilgic et al., 2014;Bilgic et al., 2012).
Delineation of subcortical and limbic structures was performed with FIRST in FSL. FIRST was applied to the affine-registered T1-TFE image for the segmentation of bilateral caudate nuclei, putamen, globus pallidus, amygdala, hippocampi, and thalamus ( Fig. 1), which were subsequently converted into binary masks for the region-of-interest (ROI) analysis of regional magnetic susceptibility and regional volume. Bilateral substantia nigra, red nuclei and dentate nuclei were manually defined (by DTHL supervised by a neuroradiologist, HKFM) on the average magnitude image of the control group in the MNI152 standard space. CSF of the lateral ventricle was segmented for the normalization purpose. This was performed by the segmentation of all CSF using FSL. An ROI which identified the slices of the lateral ventricle was delineated for each subject and was subsequently applied to the CSF mask to segment the CSF of the lateral ventricle. This ROI was eroded by 1.5 mm to avoid partial volume effect. The delineated structures were converted into binary masks, which were then inversely warped back to the subject's native space for ROI analysis.

Data analysis
Group differences in age and neuropsychiatric assessments were examined by one-way ANOVA and post-hoc test with Bonferroni's correction, and gender composition was tested by Pearson's Chi-Square test. Comparison of motor symptom between the two PD groups was assessed by independent sample t-test. Measurement of subcortical and limbic magnetic susceptibility was performed in the subject's native space by applying the ROIs on the QSM images. The measured susceptibility value of each structure was adjusted by normalizing the relative magnetic permeability of the structures to that of CSF in the lateral ventricle. The normalized structural susceptibility was compared between groups. The ROIs were also used to calculate the gross volumes of the subcortical and limbic structures, and the measured volumes were normalized to that of the whole brain volume for each subject before statistical comparison. All comparisons were performed with the SPSS Statistics Package v.22 (IBM Corporation, New York, U.S.) at the significance level of p < 0.05. One-way ANCOVA and post-hoc test with Bonferroni's correction were employed for multiple group comparison. Age and gender were considered as confounding factors and were adjusted in the analysis. For each significant result observed, the assumption of linear relationship between covariates and the measured susceptibility was evaluated. Group interaction effect between the covariates and the normalized structural susceptibility was incorporated into the ANCOVA model to examine the effect of covariates on the measured susceptibility. To account for the statistical analyses of multiple ROIs in this study, Benjamini-Hochberg procedure (BH) was employed to control the false discovery rate (FDR) at the level of 0.05.
Correlation between equivalent levodopa dosage and subcortical or limbic structure volume of the two PD groups was examined by Pearson's correlation test to assess the effect of medication on brain atrophy. Correlation between structural magnetic susceptibility and psychiatric status of the subjects, represented by the neuropsychiatric scores, was examined with non-parametric Spearman's rank correlation test. Effects of age and gender were adjusted in the analyses.

Demographics and neuropsychiatric assessment
Demographics and results of the neuropsychiatric assessments are tabulated in Table 1. Significant difference existed between the mean ages of the three groups. Post-hoc test showed that mean age of PDD patients was significantly higher than the other two groups (p < 0.01). No significant difference was observed in gender composition (p = 0.29). Differences in motor symptom scores and duration of illness between the two PD groups were examined. While the two PD groups showed similar duration of illness (p = 0.08) and similar PD stage by Hoehn & Yahr staging (p = 0.90), the UPDRS-III of PDD patients was found to be significantly higher than that of the non-demented PD patients (p < 0.001). No significant differences were observed in the L-Dopa equivalent dosage for the two PD groups (p = 0.125).
Neuropsychiatric assessment results were compared with one-way ANOVA, and significant differences between the three groups were observed in all tests. Post-hoc test suggested that PDD patients had significantly worse scores than the other two groups in the PPRS, PANSS and MMSE assessments (p < 0.001, all), and worse than the healthy controls for MADRS-S (p = 0.006) and Y-BOCS (p = 0.012).

Iron loading by measuring magnetic susceptibility
Average magnetic susceptibility measured for each subcortical and limbic structure was compared between the three groups, and the results are summarized in Figs. 2 and 3, with Fig. 2 indicating the result of one-way ANCOVA while Fig. 3 showing the results of the post-hoc test. One-way ANCOVA at the FDR level of 0.05, adjusted for age and gender, showed significant group differences for left and right hippocampus (p = 0.015 & 0.032, respectively, BH corrected) and right thalamus (p = 0.032, BH corrected). Post-hoc test with multiple comparison correction suggested higher magnetic susceptibility in PDD patients than healthy controls in the left and right hippocampus (p = 0.001 & 0.047, respectively, Bonferroni's corrected). PDD patients also had higher susceptibility than the non-demented PD patients in left hippocampus (p = 0.046, Bonferroni's corrected). Significance observed for the right thalamus was due to the significant difference between non-demented PD patients and healthy controls (p = 0.005, Bonferroni's corrected) after post-hoc test. The PD patients were also found to had higher magnetic susceptibility than the healthy controls in the right hippocampus (p = 0.006, Bonferroni's corrected).
The linear relationship between age and measured susceptibility of bilateral hippocampus and right thalamus was evaluated with linear regression. Susceptibility of bilateral hippocampus showed a moderate correlation with age (left hippocampus: r = 0.384, p = 0.001; right hippocampus: r = 0.396, p = 0.001). For right thalamus, insignificant linear correlation was observed (r = 0.026, p = 0.836). Group interaction effects between age and the measured susceptibility of the three brain structures were examined and result of all three regions were found to be insignificant (left hippocampus: p = 0.476; right hippocampus: p = 0.494; right thalamus: p = 0.354).

Comparison of the volume of subcortical and limbic structures
The average normalized volumes of the subcortical and limbic structures were generally smaller in the PDD patients, yet no statistical significance was observed for all subcortical and limbic structures after FDR adjustment with Benjamini-Hochberg procedure. Correlation analysis showed mild positive correlation between levodopa dosage and normalized volume of left substantia nigra in the two PD groups, with Pearson's coefficient of 0.333 (p = 0.041). Similar result also observed in left and right dentate nucleus, with Pearson's coefficient of 0.345 (p = 0.034) and 0.336 (p = 0.039), respectively.

Enlargement of lateral ventricle
The size of the lateral ventricle was estimated and compared between the three groups and the general trend showed that the size increased with disease progression (Fig. 4). One-way ANCOVA showed significant group differences (p = 0.031). Post-hoc test suggested that size of lateral ventricle was significantly larger in PDD patients than healthy controls (p = 0.027) while no difference was found between the non-demented PD patients and healthy controls.

Neuropsychiatric correlation
There were significant correlations between some of the neuropsychiatric scores and bilateral thalamus and hippocampus (Fig. 5)

Discussion
Post-mortem and imaging studies pointed to abnormal iron deposition in the substantia nigra pars compacta of PD patients (Bartzokis et al., 1999;Graham et al., 2000;Griffiths et al., 1999;Hare et al., 2013;Jenner, 1991;Jin et al., 2012;Kosta et al., 2006;Rouault and Cooperman, 2006;Sofic et al., 1988), but the role of iron accumulation in PD and its involvement in the later overt development of neuropsychiatric symptoms in PDD remain elusive. In current study, we found that: firstly, increased iron concentration was observed in bilateral hippocampus of PDD patients, and right hippocampus and right thalamus of PD patients, as compared to healthy controls; secondly, the iron content of bilateral hippocampus was found to be moderately correlated with both cognitive function and psychotic symptoms of PD patients.
Our current finding of hippocampal iron accumulation and its correlation with psychotic features in PDD patients should be interpreted in the light of current research.
As a cross-sectional imaging study, causation cannot be inferred and it remains unclear if the increased iron level in the hippocampus of the PDD patients is involved in the pathogenesis or purely reflects an epiphenomenon of advancing neurodegeneration of PD patients and this warrants further investigation of the causality by a longitudinal study. Although a few previous studies also reported association of hippocampal iron with memory test performance in ageing (Rodrigue et al., 2013) and Alzheimer's disease (Ding et al., 2009), no causality between hippocampal iron accumulation and the development of dementia symptom in the PDD patients could be inferred.
Our finding of hippocampal involvement in PDD concurred with a few prior studies, but nevertheless, the role of hippocampus remains controversial. Several studies have reported the association between the limbic structures and the onset of cognitive decline or dementia in PD patients (Aarsland et al., 2008;Kalaitzakis et al., 2009). Previous studies of the similar cohort (by our team) using diffusion tensor imaging (DTI) and BOLD fMRI reported that the psychotic symptoms of visual hallucination in PD patients is related to the disruption of default mode network (DMN), particularly the functional connection between hippocampus with DMN and frontal region (Yao et al., 2016;Yao et al., 2014), suggesting that pathological changes to hippocampus is associated with the development of psychotic disorder in PD.
However, besides mesolimbic and mesocortical dopaminergic pathways being involved in cognitive functioning, a number of nondopaminergic transmitter systems are affected in PD (Aarsland et al., 2017). A Positron Emission Tomography study (Klein et al., 2010) using multiple radioactive ligands found that dementia and psychosis (visual hallucination) in both Dementia with Lewy Bodies (DLB) and PDD were related to cholinergic defects and parieto-occipital hypometabolism respectively. Another Single Photon Emission Computed Tomography study (Mori et al., 2006) using 99m Tc-HMPAO similarly found that visual hallucinations in DLB could be normalized with cholinesterase inhibitors due to increased perfusion in posterior visual association cortex.
The thalamus is known to function as a hub for information transfer between cerebral cortex and basal ganglia, the structure is highly involved in regulation of different motor and non-motor functions. In the current study, higher iron content is observed in the unilateral thalamus in the non-demented PD patients, which a similar result has been reported in a previous study (Langkammer et al., 2016). Other studies also suggested possible structural abnormalities in thalamus of PD patients (Danti et al., 2015;Deng et al., 2016;Gerrits et al., 2016). This study suggests the plausible involvement of thalamus in development of PD's motor symptoms with the deposition of iron in the structures. While the PDD group does not show significance after post-hoc test in this study, this could be possibly explained by the small sample size of the group.
We observed significant enlargement of the lateral ventricle of PDD patients vs healthy controls, which has been commonly observed and reported in AD-type dementia (Förstl et al., 1995;Luxenberg et al., 1987), and PD patients with mild cognitive impairment (MCI) (Dalaker et al., 2011). These suggest that cognitive impairment in neurodegenerative disease is closely related to the underlying brain atrophy as reflected by enlargement of lateral ventricle.
The effect of medication, i.e. prescription of levodopa for treatment of PD, and its relationship with the result of this study is uncertain. We assessed the correlation of levodopa dose with normalized volume of different brain region and controlled for age and gender of the patients. It was observed that left substantia nigra and bilateral dentate nucleus showed positive correlation with levodopa dosage, suggesting possible effect of levodopa in preserving the deep brain grey matter nuclei in the PD patients.
The effect of age on the brain iron accumulation of healthy subjects, as well as PD patients, has been previously demonstrated (Acosta-Cabronero et al., 2016;Acosta-Cabronero et al., 2017). While no significant association between age and hippocampal iron content was observed in healthy subjects (Acosta-Cabronero et al., 2016), moderate age-dependent effect of hippocampal iron was reported in PD patients (Acosta-Cabronero et al., 2017). To account for the effect of age, one- Fig. 3. Post-hoc test with Bonferroni's correction accounts for multiple comparison between the three groups. Only structures with statistical significance after oneway ANCOVA adjusted for FDR are considered for the post-hoc test. Data for left thalamus is included as a reference to that of right thalamus. way ANCOVA with age as a covariate was performed. The effect of age on the measured magnetic susceptibility of hippocampus was further examined by linear regression of age and measured susceptibility and incorporating the group interaction of the two terms into the ANCOVA model. The moderate correlation between age and measured susceptibility of hippocampus supported the use of ANCOVA to adjust the effect of age. It was also demonstrated that interaction effect was not significant in the statistical model adopted in this study, and age had the same effect on the measured susceptibilities in all three groups. This result supported the claim that the differences of hippocampal iron observed in this study shall be mainly due to the differences between groups.
One of the major limitations of our current study is the sample size of the PDD group. In this study, the PDD group consisted of 10 patients only, as opposed to 27 healthy controls and 31 non-demented PD patients. However, it should be noted that the PDD group is difficult to recruit due to the very stringent inclusion and exclusion criteria of the group. Since the current study is cross-sectional in design, the correlation of increased iron level in the hippocampus of the PDD patients and the neuropsychiatric scores could be non-specific and due to parallel association, both features simply reflecting advanced disease state. A longitudinal study is warranted to further investigate the role of iron in the pathogenesis of advancing neurodegeneration of PD patients and its plausible causality to the memory decline in PDD. In this study, we examined simultaneously quite a number of subcortical and limbic structures in each evaluation. To account for the problem of multiple statistical tests and concerned with the statistical power in the correction, FDR with Benjamini-Hochberg Procedure was adopted to keep the false discovery rate of each evaluation to significance level of 0.05. Another limitation of this study is concerned with the neuropsychiatric presentation of PD patients. Previous study suggests that demented PD patients usually exhibit other non-motor comorbidities, while over 50% of these patients might have visual hallucination or other psychotic symptoms (Burn and Yarnall, 2014). It would have been ideal to have recruited patients with PDD without psychosis; however, the high comorbidity of psychosis in late PD suggests that the former is part and parcel of disease progression. It is understood that psychotic features in PDD might be related to visuospatial impairment and the visual cortex shall be one of the region of interest for the investigation of non-motor symptoms in PDD. In this study, however, we did not measure posterior and occipital cortical iron load of the patients due to the uncertainty in measuring magnetic susceptibility at the cerebral cortex. Finally, one should also note that MMSE is only a screening test of cognitive dysfunction, it is not ideal for assessment of memory decline in the clinical sense.

Conclusion
In our current study by QSM, higher iron deposition is observed in the bilateral hippocampus of the PDD patients as compared to healthy controls. Higher iron deposition is also observed in the unilateral hippocampus of the PDD patients when compared to non-demented PD patients. Moderate correlation of iron content in the PD and PDD patients with both cognitive and other neuropsychiatric impairment is found. Our results might provide insight on the relation between the effect of iron deposition in Parkinson's disease and cognitive dysfunction. Future longitudinal study for evaluation of the role of limbic iron concentration by QSM in PD pathogenesis, its relationship to dementia and psychosis, and potential as a clinical biomarker in monitoring treatment by iron chelation therapy in clinical trials is awaited.