Streptomyces sp. RO-S4 strain isolated from the polluted waters of Bejaia Bay in Algeria. Antagonistic assays against methicillin-resistant Staphylococcus aureus with RO-S4 organic extracts showed an inhibition zone of 20 mm by using the agar diffusion method, and its minimum inhibitory concentration was 16 μg/ml. A molecular network was created using GNPS and annotated through the comparison of MS/MS spectra against several databases. The predominant compounds in the RO-S4 extract belonged to the angucycline family. Three compounds were annotated as known metabolites, while all the others were putatively new to Science. Notably, all compounds had fridamycin-like aglycones, and several of them had a lactonized D ring analogous to that of urdamycin L. The whole genome of Streptomyces RO-S4 was sequenced to identify the biosynthetic gene cluster (BGC) linked to these angucyclines, which yielded a draft genome of 7,497,846 bp with 72.4% G+C content. Subsequently, a genome mining analysis revealed 19 putative biosynthetic gene clusters, including a grincamycin-like BGC with high similarity to that of Streptomyces sp. CZN-748, that was previously reported to also produce mostly open fridamycin-like aglycones. As the ring-opening process leading to these compounds is still not defined, we performed a comparative analysis with other angucycline BGCs and advanced some hypotheses to explain the ring-opening and lactonization, possibly linked to the uncoupling between the activity of GcnE and GcnM homologs in the RO-S4 strain. The combination of metabolomic and genomic approaches greatly improved the interpretation of the metabolic potential of the RO-S4 strain.Multi-omic approaches have recently made big strides toward the effective exploration of microorganisms, accelerating the discovery of new bioactive compounds. We combined metabolomic, molecular networking, and genomic-based approaches to investigate the metabolic potential of the  Staphylococcus aureus (MRSA) is the most common cause of nosocomial infections as it is very capable of developing antibiotic resistance , followed by the creation of a molecular network using the Global Natural Product Social Molecular Networking (GNPS) analysis. These analyses were combined with a genomic analysis to refine and further annotate the structural hypothesis generated, and conversely, to understand the biosynthesis of the major angucyclines produced by this strain.Here, we investigated the secreted metabolome of The RO-S4 strain was isolated from polluted seawater that was collected from the coastline of Bejaia City at S3 point (36°43'55.2 “N5°04'37.9”E) by Ouchene et al. . It was https://www.ezbiocloud.net/) recommended by Yoon and co-workers .The initial molecular identification of the RO-S4 strain was based on the 16S rRNA gene sequence. Genomic DNA was extracted from the grown strain using the Wizard® Genomic DNA Purification Kit  according to the manufacturer's instructions. PCR and sequencing were realized as previously described . This final assembly was auto-annotated using PROKKA v. 1.14.6  add the ORF corresponding to GcnM in Streptomyces sp. LR32, 2) remove partial rRNA genes and possible adapters in contig ends. The genomic sequence (JAJQKZ000000000) was compared to that of close strains based on the 16S rRNA gene analysis described above, relatives (type strains) and genomes in the NCBI GenBank, based on top blastp hits using the five housekeeping genes described by Antony-Babu and coworkers . Further genome-based taxonomic identification using estimated DNA-DNA hybridization was performed using the TYGS server . The DNA was extracted using the Bacteria Genomic DNA Extraction Kit  according to the manufacturer's instructions. Illumina whole genome sequencing was performed by the Genotoul facility in Toulouse, France. Briefly, libraries  were constructed using 200 ng of purified DNA and sequenced on a Novaseq 6000 sequencer (Illumina), generating 93 million paired 150 base pair (bp) reads. The entire dataset was assembled using SPAdes (v3.14.0)  ATCC 43300 by the agar diffusion method  guidelines and as described by Wiegand et al.  with no inoculum served as a sterility control, while wells that were not treated with the crude extract served as a negative control (column 11). The final volume of each well was adjusted to 100 μl. The microplate was shaken gently, then incubated for 24 h at 37°C. Inhibition was evaluated as well, where the growth medium appeared clear, indicating that the test extract prevented the growth or killed the bacteria.The minimal inhibitory concentration (MIC) of the RO-S4 ethyl acetate extract was evaluated against the methicillin-resistant d et al. . The ass2 analyses was adapted from previous reports  as recommended by Wang and collaborators , and culture media were converted from the RAW into mzXML file format using the Proteowizard MSConvert tool version (3.0.20104), then uploaded to GNPS. For MN construction, the precursor ion mass tolerance was set at 0.005 Da and the MS2 fragment ion tolerance was set at 0.01 Da. A network was created where edges were filtered to have a cosine score above 0.77 and 11 or more matched peaks. The maximum size of a molecular family was set at 85. The MS2 spectra in the network were searched against the 'GNPS spectra library'. All matches between network and library spectra were required to have a score above 0.7 and at least 6 matched peaks. The visualization of the molecular network was performed in Cytoscape (3.8.0), which allowed its visualization as a network of nodes and edges . For nodes gathering protonated molecular ions and in-source fragments of higher molecular weight compounds, only protonated molecular ion integrations were included for peak area information. Any ion present in the network solely due to in-source fragmentation was given the arbitrary extracted ion intensity of 0 and was white in the network. Furthermore, spectra of interest were manually annotated using different databases and tools, including Sirius , Pubchem, Sci-Finder, and Mass Bank of North America . Detailed spectral data are provided in supporting information  platform available at  using the “relaxed” option. Synteny plots of the RO-S4 angucycline BGC were performed using Clinker v 0.0.21  of the RO-S4 strain was analyzed for the prediction of secondary metabolites and biosynthetic gene clusters (BGCs) using the genome mining tool antiSMASH version 6.0.1 , d4 41.7 (39.2-44.2) and d6 55.7 (52.6-58.9); 0.06 difference in G+C content]. The genome-based tree places Streptomyces sp. RO-S4 clearly exterior to the clade containing S. albogriseolus JCM 4616T. Overall, these values indicate strain RO-S4 might represent a new Streptomyces species.The whole genome of 2 hereafter) spectra of the main constituents of the mixture indicated that most metabolite molecular ions fragmented to yield a product at m/z 487.1600 corresponding to the formula C25H27O1  by various dereplication tools. A comparison with experimental spectra from the MoNA database confirmed that compound 1 was fridamycin A or its diastereomer, fridamycin B. The MS2 spectra of fridamycin A and aquayamycin are very similar  crude extract was investigated using UPLC-HRMS. An examination of the MS and collision-induced MS/MS (MS87.1599) . The sam1599) . The MS2 spectrum obtained for the protonated molecular ion of compound 1 was compared to all other MS2 spectra of equimassic ions found whenever other more complex metabolites were fragmented in the source. The fragmentation patterns were all similar, confirming that many metabolites in the MN were fridamycin A or B analogs. It was deduced that the strain biosynthesizes the central fridamycin core and then adds various substituents to generate its diverse products. Notably, the pentacyclic aquayamycin subunit was not detected in any of the annotated metabolites. This observation was supported by the presence of a biosynthetic gene cluster very close to that of Streptomyces sp. CNZ-748  was a fridamycin bearing a C5H10 substituent. A fridamycin isopentyl ester was thought to be a reasonable putative structure based on the biosynthetic considerations below. Compound 5 could not be annotated more precisely than just with its molecular formula, but its MS2 spectrum is also one of a fridamycin analog. These considerations indicated that 5 was new to Science.The parameters for MN were set to construct the best representative network containing all fridamycin analogs . The MN 6a protonated molecular ion was at m/z 597.1973, corresponding to the formula C31H33Om/z 597.1967). The formula and fragmentation pattern were consistent with the annotation of 6a as fridamycin D, previously reported to have antibacterial activity  was also detected at a different retention time in smaller relative proportions in the strain's metabolomic profile. Another major constituent of the strain metabolome was compound 7a, whose protonated molecular ion at m/z 711.2645 corresponded to the formula C37H43O7a may be vineomycin C, a potent inhibitor of inducible nitric oxide synthase  and the aculose oxonium ions were present at m/z 115.0756 and 111.0443 (2 spectrum suggested that the sugar sequence might be different from that of vineomycin C. The protonated molecular ion lost both water (m/z for C37H41O6H12O3 fragment (m/z for C31H31O7a must be considered new to Science unless the published structure of vineomycin C requires revision. Possible annotations are reported in 2 spectrum. The proximity of 7a with fridamycin D (6a) in the MN suggested that the most probable annotation might be the one in which aculose underwent a Michael addition, as in 6a , but the fragmentation pattern was not attributable to marangucycline B. Hence, while this compound is probably not marangucycline B it could not be annotated further. Angucycline 9 was also new to Science. Its protonated molecular ion at m/z 667.2753 corresponded to the formula C36H43O2 spectrum, the fragmentation from the protonated molecular ion to the product at m/z 579.1851 corresponded to the loss of a neutral fragment the formula of which was C5H12O . This corresponded to the grincamycin H molecular formula , calcd. 917.3590). The MS2 spectrum indicated a loss of an aculosyl-rhodinose (or aculosyl-amicetose) moiety. Then the product at m/z 675.2443 lost the neutral group C6H8O (a dehydro-rhodinose), indicating that the aculosyl-rhodinose moiety was linked to another rhodinose. Then the aglycone ion at m/z 451.1398 was produced by the loss of another aculose. The molecular weight of this aglycone ion (fridamycin A−2 H2O) along with the proximity of other lactonic aglycones in the MN spoke in favor of 14 also being a lactone derivative, as reported in 15 was not very clear and 15 could not be annotated with enough confidence. At m/z 901.3653, compound 16 protonated molecular ion indicated the formula C49H57O2, the ion 16+H+ lost an aculosyl-rhodinose group to give the product at m/z 659.2499, which then lost dehydro-rhodinose. Further dehydration produced an ion at m/z 545.1790 which again lost aculose to yield the aglycone ion at m/z 435.1471. This aglycone was doubly dehydrated compared to fridamycin A, indicating that the C-olivosyl group in 16 may be dehydrated. The structure proposed in 16. The molecular formula of compound 17 is C49H58O18 . This molecular formula and sodium adduct fragmentation pattern, in which two successive aculosyl-rhodinose losses were recorded, were compatible with the annotation of 17 as vineomycin B2, previously reported to have antibacterial activity . Both isomers fragmented extensively in the ESI source to produce the fridamycin A protonated molecular ion [1+H]+ losing C6H8O2, i.e., a dehydro-cinerulose A moiety. The cinerulose A oxonium ion was also detected in MS2, while the aglycone fragmentation was very similar to what was recorded for [1+H]+. Angucyclins 18a and 18b were therefore annotated as cinerulosyl-fridamycin A or B. The position of the cinerulosyl side chain was not determined and may not be identical for both isomers. Compounds 19a and 19b were annotated as isomers with the molecular formula C31H36O12 . Both isomers also fragmented extensively in the ESI source to produce the fridamycin A protonated molecular ion [1+H]+ losing C6H10O2, i.e., dehydro-rhodinose/amicetose subunit, the corresponding oxonium of which was also present in MS2. As mentioned above, the MS2 spectrum of the aglycone protonated ion formed by in-source fragmentation was identical to the one of [1+H]+, therefore confirming that 19a or b should not be annotated as grincamycin L . Its MS2 spectrum showed a rhodinose/amicetose subunit and a dehydrated protonated aglycone. Therefore, compound 20 was annotated as a dehydro-19a. Compound 21 molecular formula was C37H45O13 . Its MS2 spectrum revealed the successive loss of two rhodinose/amicetose subunits, yielding a dehydrated protonated aglycone. It was thus annotated as shown in 22 molecular formula was C31H37O11 . Its MS2 spectrum showed the loss of one rhodinose/amicetose subunit, yielding a protonated deoxy-aglycone. The structure of the aglycone could not be readily inferred from the MS2 spectrum and compound 22 could not be annotated further. Compound 23's molecular formula was C37H44O14 . A rhodinose/amicetose was visible in MS, but the MS2 spectrum was impure and further annotation was not possible. Compound 24 molecular formula was C34H41NO13 . Its MS2 spectrum showed the loss of 1 rhodinose/amicetose subunit, yielding a product at m/z 558.1983 (C28H32NO2O2 (formic acid or H2O+CO), and C2H5N to generate a protonated didehydro-fridamycin A at m/z 451.1393. This fragmentation pattern was compatible with 24 being an alanine amide of 19, as shown in m/z 90.0550, corresponding to an alaninium ion . In-source fragmentation indicated the successive loss of a dehydro-rhodinose/amicetose group and a C6H10N2O2 subunit. The MS2 spectrum highlighted the loss of one dehydro-rhodinose/amicetose and two alanine subunits to generate the protonated didehydro-fridamycin A at m/z 451.1393 . The MS2 spectrum clearly indicated that the protonated molecular ion lost both dehydro-rhodinose/amicetose and a C6H8O4 neutral fragment, therefore confirming that this compound was new and should not be annotated as saprolmycin B  to determine its putative biosynthetic capabilities. A total of 19 putative biosynthetic gene clusters (BGCs) were annotated , includiAntiSMASH analysis using an unannotated genomic DNA sequence revealed that Cluster 2 in Contig RO-S4_2 of the assembly displayed a high synteny (> 65% common genes) to that of BGCs linked to several angucycline compounds, such as grincamycin (97%), saprolmycin E (83%), saquayamycin A (75%), landomycin A (71%), and saquayamycin Z (67%). All these compounds share a common tetracyclic angular benz[a]anthraquinone aglycone. Due to the predominance of tricyclic aglycones (“open” aglycone(s) hereafter) among the major metabolites of the RO-S4 strain, we performed an in-depth analysis of Cluster 2.Cluster 2 contains genes putatively involved in the biosynthesis and modification of the aglycone core. A typical set of genes responsible for an angucycline core assembly named “minimal PKS” has been identified, supporting the synthesis of angucycline-like molecules by its cluster. This included three genes: a ketoacyl synthase α (LRR80_00487), a ketoacyl synthase β/chain length factor CLF (LRR80_00488), and an acyl carrier protein (ACP) (LRR80_004989). Two possible cyclase genes (LRR80_00486 and LRR80_00491) were also annotated, which are likely responsible for the polyketide chain cyclization into the benz[a]anthracene structure. In addition, this cluster harbors two genes encoding oxygenase enzymes (LRR80_00485 and LRR80_00492) probably involved in the modification of the aglycone and possibly in the lactonization and opening of the angular aglycone cycle (see discussion below). (Keto)reductase-coding genes, including LRR80_00490 and LRR80_00470, were annotated to exhibit a high degree of sequence similarity to known enzymes involved in the modification of aromatic polyketides. Three genes  likely associated with the glycosylation steps showed high similarity to genes coding for glycosyltransferases (GTs) in other angucyclines. All the annotated genes involved in the BGC of Cluster 2 and their homologs are listed in Streptomyces lusitanus SCSIO LR32 (Gcn LR32)  in the BGC of RO_S4_2, whereas the region downstream of GcnS8 was not present in the available BGC of strain CZN-748  been linked to the We have demonstrated that many of the compounds identified by our untargeted metabolomic analysis are novel to Science, and this high diversity of novel molecules can be explained by the ability of HRMS to highlight minor compounds even though some of the major metabolites are also new to Science. Our annotation of the RO-S4 angucycline-like compounds was further supported by genomic analysis.Streptomyces CNZ-748 produce primarily tricyclic glycosylated structures, while LR32 and many other strains produce tetracyclic angucyclines, we were interested in possible enzymatic processes that could lead to the biosynthesis of these tricyclic aglycons  homologous to UrdM, that has been linked to C12b hydroxylation in the biosynthesis of urdamycins by S. fradiae TÜ 2717  that is homologous to FAD-dependent monooxygenases involved in angucycline modifications  /MtmOIV alignment was shorter and had a lower overall score, but a higher number of identical positions, whereas the LRR80_00485 (UrdE-like)/MtmOIV alignment was longer and had a higher total score, but with fewer identical positions. Phylogenetic analyses including UrdE homologs and the oxidase portion of UrdM homologs separated these oxidases into two groups, with maximum likelihood and distance methods showing that LRR80_00485 was slightly closer to MtmOIV than LRR80_00492, and in a subclade including PgaE : that the LRR80_00492 ORF would be partly transcribed due to the mRNA secondary structure, which would allow its oxidase portion to be transcribed but not the reductase, much like the case with the UrdM partial knockout mutant that produces urdamycin L : the product of LRR80_00492 would be solely responsible for the oxidation of the C12b–C1 bond. This hypothesis is supported by the prediction that this enzyme has several AAs unique to RO-S4 and CNZ-748. On the other hand, since the reductase portion of the enzyme is present, one would expect that tetracyclic angucyclines with a hydroxylated C12b would be produced. Hypothesis (2): the most likely hypothesis based on our work on the RO-S4 strain is that the LRR80_00492 ORF is inactive due to the presence of a tRNAGcnG1 [96.98%  enzymes, which show similarities to known GTs involved in angucycline biosynthesis. The first, RO-LRR80_00494, shows high homology to O-glycosylated with rhodinose/amicetose by one of the three glycosylases, and in some cases (ex. compound 9), experiencing a Michael addition, or further glycosylation as in compounds 19 and 27 (and in previously described angucyclines). Interestingly, all compounds glycosylated at position C3 in RO-S4 appear to have a rhodinose/amicetose as the sugar moiety, as do all grincamycins. It is worth noting that the composition and varying lengths of the oligosaccharide chains in angucyclines have a considerable impact on their biological potential, as previously reported by Elshahawi et al. . Amide modifications have been previously shown in fridamycin G  does not produce it. Fridamycin I contains a benzylamine moiety, the biosynthetic origin of which was not discussed. As compounds 25–28 contain multiple alanine moieties, we speculate that fridamycin-like molecules could undergo peptide-like elongation with aminoacids , perhaps via an NRPS in a manner analogous to what has been described in the biosynthesis of actinomycin-D  , https://www.ncbi.nlm.nih.gov/sra/, SRR17084181 and GitHub, https://github.com/suzumar/ROS4_manus.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: National Center for Biotechnology (NCBI) GenBank, RO, DS, and MS conceived and designed the experiments, wrote the original draft, and prepared tables and figures. RO and MK collected biological material. RO performed the experiments and wrote the manuscript. AR performed the UHPLC-HRMS analysis. CV performed the DNA extraction. RO, DS, and JS performed molecular networking and metabolomics analysis. RO and MS performed the genomic analysis. MS and DS made critical revisions to the final version. All authors read and approved the final version.This work was funded by recurrent funds of the CNRS and Sorbonne University attributed to the LBBM laboratory.The 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.


Purpose: Conventional topical dosage forms face with some challenges like low intraocularbioavailability, which could be overcome by application of novel drug delivery systems.Therefore, this study was conducted to prepare azithromycin (AZM)-loaded chitosan/polyvinylalcohol/polyvinyl pyrrolidone (CS/PVA-PVP) nanofibers with the prolonged antibacterialactivity by electrospinning method.Methods: After preparation of nanofibers, they were characterized in terms of physicochemicaland morphological properties. In vitro and in vivo release of the drug from nanofibers wereevaluated using microbial assay against the Micrococcus luteus. Antibacterial efficacy of thenanofibers was assessed. The ophthalmic irritation test was also performed. MTT test wascarried out to evaluate cytotoxicity of the formulations.Results: All the formulations were found to be stable with uniform thickness, weight, and drugcontent. Nanofibers had a diameter range from 119 ± 29 to 171 ± 39 nm. The inserts were nonirritantand non-toxic to the rabbits’ eye. Based on the obtained results, the crosslinked AZMnanofibers showed slower and more controlled drug release in tear fluid compared to the noncrosslinkedones, within 184 hours.Conclusion: Our results revealed that the prepared nanofibers could be considered as suitableand non-invasive inserts for the prolonged ophthalmic delivery of AZM. The advantages of topical ophthalmic drug delivery include avoiding the first-pass metabolism, non-invasiveness, targeted delivery, high patient compliance, painlessness, and reduced side effects in comparison with systemic forms making it one of the most effective and popular routes of administration. Topical forms, especially eye drops are commonly used to treat ophthalmic diseases associated with anterior chamber. However, topical drug delivery has always faced with challenges, such as pre-corneal barriers including lacrimal drainage, blinking, tear film, and anatomical barriers reducing intraocular bioavailability of drug at the site of action. Given all these corneal–epithelial barriers, only 1-7% of the drug reaches aqueous humour and intra-ophthalmic tissues. As a result, novel drug delivery systems like hydrogels, nanofibers, liposomes, nanoemulsions, nanoparticles, etc., have been designed and developed to overcome these challenges. In the meantime, high-potential nano-based drug delivery systems have been developed including nanofibers with the increase in the use of nanotechnology in the industries. Electrospinning has always been the most popular technique for preparing the nanofibers. These systems have many advantages like high surface-area-to-volume ratio and high porosity; leading to high ability of the nanofibers to increase solubility, helping the controlled release of drug, and increasing intraocular bioavailability of drugs.Topical dosage forms have always been the most common route of administration for ophthalmic anti-infective agents.Based on the previous studies, the cornea and conjunctiva have a negatively charged structure. Hence, positively charged mucoadhesive polymeric carriers interacting with the cornea and conjunctiva could increase contact time and consequently, concentration of drugs in the cornea. However, the nanofibers could be more beneficial by addition of other polymers like polyvinyl alcohol (PVA), polyvinyl pyrrolidone (PVP), and polyethylene terephthalate (PET) to CS compared to pure CS nanofibers. Also, this addition could lead to a significant decrease in fiber diameter of electrospun CS/PVP mixed fibers attributing to an increase in solution conductivity.Chitosan (CS) is a cationic polymer with many beneficial properties, such as biodegradability, low toxicity, and biocompatibility making it one of the most popular polymers in design and preparation of the drug carriers.Glutaraldehyde (GA) is a strong crosslinker due to high activity of aldehyde groups, which could interact with amino groups of proteins. Also, it can be used as a crosslinking agent for PVA and CS.in vitro and in vivo release of the drug from the optimized nanofibers were evaluated. It was expected that the nanofibers achieve a controlled release of drug, which could decrease frequency of drug administration compared to conventional eye drops, and consequently increase the patient compliance.In this study, azithromycin (AZM), as an effective agent against the external ophthalmic infections acting by inhibiting bacterial protein synthesis was loaded in the nanofibers composed of PVA, PVP, and CS blends and GA vapor-crosslinked nanofibers. After optimization and characterization of physicochemical properties, CS (70-58% deacetylated) was obtained from Acros Organics Company. PVA  and PVP were purchased from Aldrich Chemical Company. Acetic acid 100% was obtained from Merck Company . All the other chemicals were of the best available grade.One percent (w/v) PVA and 3% (w/v) PVP solutions in distilled water were prepared at 50°C and were mixed for FZ-P formulation. Three percent (w/v) PVA and 1% (w/v) PVP solutions were prepared and were mixed for FZ-A formulation. For obtaining 2% (w/v) CS solution, CS was dissolved in acetic acid (1% v/v) at 25°C. CS/PVA-PVP solutions were obtained by addition of 20ml of CS solution to 20ml of PVA-PVP solutions with different polymer concentrations containing AZM (10% w/w of polymers) under continuous stirring at room temperature for 12 hours.AZM nanofibers were prepared using a customized electrospinning system . High voltage supply of 25 kV was applied to a stainless-steel capillary connected to a reservoir filled with polymeric solutions. Cylindrical collector was covered by a cellulose ester membrane to collect the electrospun samples. The whole electrospinning procedure was performed at 40°C. The experimental flow sheet is shown in  For preparing FZ-PG and FZ-AG formulations, FZ-P and FZ-A nanofibers were placed on a holed ceramic shelf in a desiccator containing 50%, v/v aqueous GA solution. For removing unreacted residual vapor-phase GA on the nanofibers, the formulations were initially soaked in 0.02 M glycine solution for 4 hours and then, in deionized water for 30 minutes. Finally, the fibers were dried under vacuum and were kept in a desiccator until further application.Crosslinking process was performed based on the method reported by Zhou et al.Thickness of the nanofibers was measured using digital micrometer ( ± 0.001 mm) in five different positions of nanofibers and an average was taken.Weight variation in the nanofibers (6 mm of diameter) was tested using a digital weight balance . Mean weight (n = 10) was recorded for each formulation.For observing uniformity of the nanofibers’ drug content, same pieces of ophthalmic inserts were cut and dissolved into a specific amount of acetic acid (1% v/v), then were diluted with phosphate-buffered saline (PBS) solution and were filtered by filter papers (0.45 μm). The drug content was measured using microbiological assays.Nanofibers were cut into pieces with the same size, and then were folded at the same point repeatedly until they were torn. The number of times, in which the nanofibers could be folded without tearing or breaking, was reported as folding endurance.For estimating percentage of moisture uptake and loss, nanofibers were weighed initially and then, were placed respectively in a desiccator containing a saturated solution of aluminium chloride (to keep 79.5% of humidity inside the desiccator), and anhydrous calcium chloride for 72 hours. After that, the nanofibers were reweighed and percentage of moisture uptake and loss was calculated.0 were soaked in double-distilled water for 1 hour. After removing of the water from surface of nanofibers using a paper filter, they were reweighed to obtain Wt. Swelling was calculated using the standard formula.The samples with initial weight of WThe ophthalmic insert was allowed to swell in distilled water inside a Petri dish. The pH paper was placed on surface and after 1 minute; the developed color was compared with the standard color scale to estimate surface pH.Morphology of the nanofibers was observed using field-emission scanning electron microscopy . The dried samples were placed on metal stubs with adhesive tape, were sputter-coated with gold and then, were observed under a scanning electron microscope.Samples were dried in a vacuum desiccator, were mixed with micronized KBr powder, and were compressed into a manual tablet press. Then, the FT-IR spectra were detected using  FT-IR spectrometer.Specific amount of bacterial suspension was uniformly spread onto an agar plate. The nanofibrous mats were placed on the agar plates and were incubated at 35°C.Staphylococcus aureus (ATCC 6538) and the Gram-negative organism Escherichia coli (ATCC 9637), bactericidal effect of the nanofibers containing AZM was evaluated.Based on diameter of inhibition zones, against the Gram-positive organism For confirming sterility of the inserts, they were placed in thioglycollate broth, Sabouraud dextrose broth, and soybean-casein-digest broth, respectively to detect growth of aerobic bacteria, fungi, and anaerobic bacteria. The positive and negative controls were also prepared for comparison.Micrococcus luteus(ATCC 4698) by the standard disc diffusion method. The spread-plate technique was used and the culture media were incubated at 35°C for 24 hours. Bacterial suspension was prepared in PBS solution (pH = 7.4). The approximate number of bacteria in the suspension was standardized by comparing with turbidity of McFarland Standards. Then, the resultant bacterial suspension was used as culturing inoculum. The bacterial suspension was spread uniformly on a nutrient agar plate before placement of the disks. Sterile paper disks containing 30 μL of the samples were placed on the plates and then, were incubated at 35°C for 24 hours. Finally, mean diameter of the measured inhibition zones surrounding the paper disks was recorded in mm using Vernier caliper.Microbial assay was performed using the For measuring the amount of the released drug from the nanofibers, specific amounts of the nanofibers were placed into donor compartments containing 1 mL of phosphate buffer at (pH 7.4) separated by a dialysis membrane , from the receptor compartments filled with 19 mL of the phosphate buffer. The system was stirred magnetically with the speed rate of 100 rpm at temperature of 37°C. Aliquots were withdrawn and replaced with the same amount of fresh buffer at specific time intervals to maintain the sink condition and the drug concentrations of the samples were quantified using the microbial assays.Adult New Zealand rabbits were used for assessment of ophthalmic tolerance. The animals were housed individually in restraining boxes and had free access to the allowed amounts of food and water. Sterile optimized formulations were administrated to one eye of the rabbits, while the other eye remained untreated without any manipulation as a reference. The eyes were observed in specific periods of time for damage, abnormality, swelling, redness, and inflammation as signs of irritancy.L929 (mouse fibroblast) cells were cultured to evaluate cytotoxicity of the nanofibers. The 24-well plate was incubated for 48 hours. One row of 24-well plate that did not receive any formulations was considered as a control. Different concentrations of AZM-loaded nanofibers were administered to other rows followed by addition of 30 µL of MTT assay solution and 270 mL of medium to the wells. The plates were incubated for 4 hours. The precipitate was left in the wells after removing, and the solution was diluted with 150 µL of dimethyl sulfoxide (DMSO) solution and then, was observed using a microplate reader  to estimate cell viability at the wavelength of 560 nm.in vivo ocular studies. Eight rabbits were chosen as the experimental group while two of them were selected as the control group. In the experimental group, a bunch of nanofibers was placed in ocular sac of the rabbits. Sampling was done by pouring 50 μL of sterile phosphate buffer into ocular sac to dilute tear, which was collected by a paper disk. The paper disks containing tear samples were placed directly on a culture medium inoculated with standard bacterial suspension to estimate the amount of released drug in tear by the microbial assay method.Healthy rabbits were used to perform  PVP has many beneficial properties including high hydrophilicity, biocompatibility, ability to form the complex, and also fiber-forming ability. Addition of PVA/PVP to CS decreases viscosity and increases conductivity of the CS solution leading to the decreased diameter of the finally prepared nanofibers. This high conductivity suppresses varicose instability and enhances whipping instability causing formation of ultrafine fibers. Procedure of GA treatment was performed to crosslink the fiber mats using the Schiff base imine functionality to prepare insoluble nanofibers. After GA crosslinking, the nanofibers became slightly yellowish and their dimensions were decreased. The change in color occurred due to bonding of the free amine groups in the CS and PVA structures with GA. Drug loading was found to be uniform around 100% for all the formulations. Higher drug loading leads to a smaller insert size improving the patient compliance for application of AZM-loaded nanofibers. The prepared AZM-loaded nanofibers were characterized based on their physicochemical properties, such as moisture loss and uptake, thickness, degree of swelling, tensile strength, and folding endurance  were measured. There was a linear relationship between diameter of growth inhibition zone and log10 of drug concentrations for standards. Representative linear equation for Micrococcus luteus counts in analysis of AZM standards was as follows: y = 0.7308 xs+0.2109. The obtained correlation coefficient was equal to 0.9989, exhibiting good linearity. The coefficient of variation for individual standards ranged between 0.25 - 0.74%. As an example, Microbiological assay is one of the most common methods for investigation of antibacterial agents including the macrolides. FZ-P formulation had a higher degree of swelling and as a result, higher drug release rate because of its higher PVP percentage compared to the FZ-A formulation  showed 8.53-fold and 12.49-fold increased AUC0-t compared to the AZM solution, respectively. A significantly higher mean residence time (MRT) was measured for FZ-AG and FZ-PG formulations (crosslinked nanofibers) in comparison with the FZ-A and FZ-P formulations (non-crosslinked nanofibers) due to higher PVA concentration (3%) in the nanofibers besides GA crosslinking. The results suggested that formulation of AZM in the nanofibers may enhance pharmacokinetic behavior compared to the AZM solution.The measured AUCectively . Based oIn the previous studies, concentrations of AZM ranging from 0.05-4 μg/ml were considered as the minimum inhibitory concentration (MIC90) for common Gram-positive and Gram-negative organisms generally infecting the conjunctivitis. While, the AZM solution only achieved tear concentrations higher than the MIC90 for the first 10 hours, the non-crosslinked and crosslinked nanofibers were able to maintain concentrations up to the MIC range for 136 and 184 hours, respectively, which is required for treatment of ocular bacterial infections. As a result of this prolonged drug release, a less frequent administration of AZM is required and consequently, lower dosage of AZM is enough for achieving the desired therapeutic concentrations compared to the conventional AZM eye drop.in vitro drug release from the ophthalmic nanofibers indicated the sustained release of drug from all the formulations. The nanofibers were sterilized using UV radiation method and their sterility was confirmed by the sterility test. The results of MTT test carried out using the L929 fibroblast cells exhibited that neither of the formulations was significantly cytotoxic. The biodegradable nanofibers could be fixed in conjunctival sac of the rabbit’s eye as an ocular insert without the need for any invasive methods or surgery. There was no sign of significant inflammation or redness in the rabbits’ eyes after placement of the nanofibers. The drug release profile was evaluated by the microbial assay, as a non-invasive, inexpensive, and simple method and sampling was carried out using harmless sterile paper disks. The results obtained from in vivo study indicated the sustained release of drug in tear fluid for approximately 6-8 days from the AZM-loaded nanofibers, offering an enhancement in drug residence time on surface of cornea leading to an increased intraocular bioavailability in the eye. Our results revealed that the AZM-loaded nanofibers could be considered as suitable systems for ophthalmic delivery of AZM.In this study, electrospinning technique was successfully used to design and develop the CS/PVA-PVP nanofibers. The AZM was formulated in these delivery systems to provide a therapeutic amount of drug in the eye for a prolonged period. The prepared nanofibers were smooth and flexible along with sufficient hardness and weight uniformity.Studying The authors would like to acknowledge the Research Council of Kermanshah University of Medical Sciences (Grant number: 95522) for financial support of this work. Also, faithfully thank Rahesh Daru Novin knowledge-based company for cooperation in providing materials and equipment.The protocol for the use of animals in this study was in accordance with the Association for the Research in Vision and Ophthalmology (ARVO), which was approved by the Local Animal Ethics Committee of Kermanshah University of Medical Sciences .There was no conflict of interest declared.


Molecular knots are evolving from academic curiosities to a practically useful class of mechanically interlocked molecules, capable of performing unique tasks at the nanoscale. In this comment, the author discusses the properties of molecular knots, and highlights future challenges for chemical topology. Everyone is familiar with macroscopic knots, be they bow knots in shoelaces or stopper knots used to secure sewing threads. Since it is well known that specific knots can be tied for a desired function, it is perhaps surprising it took chemists so long to realize that knotting leads to functional advantages at the molecular level as well.1 in Alexander–Briggs notation, also called a topologically trivial knot), while the simplest prime knot is the three-crossing trefoil knot (31)1. Molecular topology concerns molecules with non-planar graphs, i. e. structures that remains entangled even when the physical limitations of molecules such as bond lengths, strain and sterics are ignored. When considering the three main classes of mechanically interlocked molecules, catenanes and knots are thus topologically non-trivial, while rotaxanes are trivial 2.Mathematicians define all closed loops as knots, and characterize them by the number of persistent crossing points in their reduced 2D projection. In mathematical terms, a common non-interlocked macrocycle is an unknot  ligands around lanthanide ion templates has proven to be highly useful thanks to its dynamic nature, meaning the knotting event can be used as a molecular switch14. Alternating between entangled and loose states is possible by treating the system with lanthanide ions and hard bases, respectively. This switching system was used in the first example of interfacing knots with molecular machines. By using the bulk generated upon knotting, it was possible to stopper a pseudo-rotaxane architecture reversibly and kinetically trap a macrocycle on a thread , it is possible to use simple stimuli to fold a single strand around itself into a knotted shapeead Fig. 15.16. This nanoscale knotting event was used to reversibly invert the chiral organisation of the material up to the centimetre scale—an amplification event over seven orders of magnitude. These examples show that the dynamic behaviour of molecular knots can be practically useful. Given the importance of controlled molecular movement in other mechanically interlocked architectures such as rotaxanes2, it is reasonable to suggest molecular knots will find many future applications.Tying a knot into a strand also introduces elements of helical and topological chirality. Recently, the Leigh and Katsonis groups employed the change in chiral expression between an enantiopure point chiral strand and its corresponding enantiopure knot to switch helical screw sense in cholesteric liquid crystals17. It has been clear for two decades that knots are prevalent across a wide range of DNA hyperstructures as well as in many protein families. Yet, it would appear that nature actively tries to rid itself of such entanglements. For example, topoisomerase enzymes have evolved with the function to untie knots which have accidentally formed during supercoiling of DNA. Only 1–2% of proteins have topologically non-trivial tertiary structures, which is far less than predicted for such long and flexible chains based on statistical entangling18. So what are molecular knots really used for in nature? Knotting reduces degrees of freedom of a molecular strand and it is easy to speculate that this is useful for stabilizing catalytically active conformations in enzymes. Similarly, it has been suggested that the bulk gained by knotting protects entangled proteins from degradation by preventing uptake into the proteasome through nanosized pores19. However, there are no definitive answers to what—if any—functions knotting actually have in nature or if knotted structures are “just another conformation” that long chains can adopt.An often-cited justification for studying molecular knots is the ubiquitous presence of entanglements in nature, both at the macro , meso (knotted hyperstructures in chromatin strands) and molecular (knotted DNA and proteins) scales2 knot—was recently disclosed  and lanthanide (LuIII). It was then demonstrated for the first time that knot topologies can have different functions—while the tightly knotted 52 knot can simultaneously accommodate both a transition metal ion and a lanthanide ion, the looser 31 knot is topologically restricted and can only accommodate one at a time . Changing the topology of a strand might be useful for manipulating its mechanical strength or changing its binding affinity towards a specific guest, but further research in this area is necessary.At the macroscale it is well-recognized that different knots are suited for different functions—you would not try to secure a boat to a mooring with the same knot used to tie a decorative ribbon! It has long been speculated that similar functional differences between knots exists at the molecular level, and to link particular topologies to specific functions is a major goal of chemical topology. However, this has been hindered by the inability to synthesize topoisomeric knots, i.e. macrocycles with identical backbones but different three-dimensional topologies. The first system where a single molecular strand could be selectively tied into three different knots—an unknot, trefoil knot and three-twist 5sed Fig. 7. Diverg1. However, almost nothing is known about what happens when molecular knots are put under applied force. Theoretical studies indicate that bonds in molecular knots are weakened at the apex of the entanglement due to distortion of covalent bonds20, but this has not been confirmed experimentally. Would knotted materials also be mechanically weakened? In such a case, can that strain be practically useful, for example for activating specific bonds towards cleavage? These questions also have practical implications: for the promising technology of nanopore DNA sequencing, pore clogging by DNA knots has long been implicated as a potential problem21.Spontaneous entanglements occur on agitation of any flexible chain beyond a certain length, such as when putting earphones into a pocket. This extends to the molecular level, where Brownian motion drives the formation of knots in DNA and synthetic polymers19 knots with varying degrees of tightness provided empirical evidence of this22. Aside from intuitive results, for example that tighter knots occupy smaller conformational space, it was also found that more tightly wound knots display significantly stronger chiral expression and fragment more easily in collision-induced dissociation mass spectrometry. Cougnon also found that more-entangled knots and links have stronger chiral expression compared to their less-entangled counterparts23 and Schalley noticed that knots have far less conformational freedom compared to unknotted macrocycles when measured with ion mobility collision-induced dissociation mass spectrometry24. Several key questions in this area remain to be answered, however. At which tightness levels do typical properties arising from entangling start to appear? What is the tightest knot that can be tied? Can stochastic knotting be used for rationally designed entanglements ? Can the thermodynamics of knotting be better understood?Aside from the identity of the knot being tied (i.e. number of crossing points and their connectivity), tightness is the key parameter that determines the properties of a knotted strand. Recently, a systematic study of 825 or dynamic covalent bonds12. However, dynamics are also important for knots beyond purely synthetic aspects. A range of effects stem from conformational restriction due to knotting. For example, reptation is the snake-like motion of chains26, a phenomenon that generally gives rise to spectral broadening and averaging, as for example observed in the spectacular all-benzene trefoil knot from Itami27. However, the precise consequences of reptation in knots remain to be studied. Some knots (such as 41 and 818 entanglements) are amphichiral, i.e. they have chiral representations that can be deformed continuously into each other, so have an overall achiral topology. This effect is underexplored, and it is of high interest to understand racemization barriers between the representations and possibly prepare persistent (trapped) chiral conformations of amphichiral knots.Many complex topologies are formed through constitutional dynamic self-assembly, for example via metal–ligand coordination interactionsThe unique changes that result in a strand upon knotting—the increase in local bulk and introduction of topological chirality, for example—are elements that surely will be useful for constructing functional dynamic systems in supramolecular chemistry. To further explore knot functions and expand the field, there is still a need to simplify synthesis and increase the accessibility of knotted architectures. However, entry to molecular knots has now improved to the point where properties of this intriguing class of molecules can finally be studied in more detail. Rapid progress in this area is anticipated over the next few years, as scientists discover how knots can be as useful on the nanoscale as in the macroscopic world around us.


CFI) variants, 579 with optical coherence tomography-derived macular thickness data. We stratified these variants by predicted gene expression and measured their association with retinal pigment epithelium-Bruch’s membrane (RPE-BM) complex and retinal thicknesses at nine macular subfields, as well as AMD risk, using multivariable regression models adjusted for the common complement Factor H gene (CFH) p.Y402H and age-related maculopathy susceptibility protein 2 gene (ARMS2) p.A69S risk genotypes. CFI variants associated with low Factor I levels predicted a thinner mean RPE-BM  and retina  and a higher AMD risk . CFI variants associated with normal Factor I levels did not impact mean RPE-BM/retinal thickness  or AMD risk (P = 0.97). CFH p.Y402H was associated with a thinner RPE-BM  and retina . ARMS2 p.A69S did not influence RPE-BM  or retinal thickness . p.Y402H and p.A69S exhibited a significant allele–dose response with AMD risk. Thus, CFI rare variants associated with low Factor I levels are robust predictors of reduced macular thickness and AMD. The observed association between macular thickness and CFH p.Y402H, but not ARMS2 p.A69S, highlights the importance of complement dysregulation in early pathogenesis.To evaluate potential diagnostic and therapeutic biomarkers for age-related macular degeneration (AMD), we identified 8433 UK Biobank participants with rare complement Factor I gene ( CFI) that encodes Factor I, the key negative regulatory enzyme of complement (Rare variants are increasingly recognized as an important source of genetic variation underpinning age-related macular degeneration (AMD), the commonest cause of irreversible sight loss in the developed world . Prior smplement . Complemmplement ,9, and implement . Howevermplement . Establimplement .CFI rare variants are described: Type 1 variants reduce serum Factor I levels by around 50% even in the heterozygous state and are strongly associated with AMD (CFI variants may lead to unregulated complement activation and consumptive loss of complement component 3 (C3) predisposing to non-resolving inflammation in various tissues , monocyte chemoattractant protein-1 (MCP) and complement receptor type 1 (CR1)] . In doinwith AMD . Type 2 with AMD . Both ty tissues . A third tissues . As FactCFI rare variants (RVs) and determine the genetic interactions that influence AMD risk.Optical coherence tomography (OCT) is a rapid, non-invasive imaging modality which provides cross-sectional structural information about the neurosensory retina and RPE to an axial resolution of 3–8 μm . OCT-derCFI RVs on the macular microstructure and AMD risk of healthy subjects. We hypothesized that carriers of CFI type 1 RVs would be predisposed to thinner macular RPE–BM and neural retinal layers and be at a higher risk of AMD compared with carriers of CFI VUS. We were also interested to ascertain the interaction between any additional risks conferred by CFI type 1 RVs and other well-known risk factors for AMD, including the common genetic variants complement Factor H gene (CFH) p.Y402H and age-related maculopathy susceptibility protein 2 gene (ARMS2) p.A69S. Finally, we sought to clarify the association between CFI RVs and membranoproliferative glomerulonephritis (MPGN) and thrombotic microangiopathy (TMA) which encompass, respectively, the pathological entities of C3 glomerulopathy (C3G) and atypical hemolytic uremic syndrome (aHUS) that are exemplars of systemic complement deposition  carried p.I340T (the only CFI type 2 variant represented in the UK Biobank) and 493 (1.49%) carried a CFI VUS. Seventy participants were homozygous for a CFI RV, only two of which had OCT-derived macular thickness measures  macular imaging. After the exclusion of 33 792 participants who did not meet the criteria for automatic segmentation of OCT images and 1775 (5.11%) participants with missing s 32 962 . Of thesmeasures . Twenty- alleles . No partulations .B = −0.11 μm, 95% confidence interval [CI] −0.16 to −0.06; P < 0.001). Using multivariable stepwise linear regression, we observed a significant association between increasing age and a thinner mean RPE–BM  and retina  at the macula. We also observed a significant association between current smoking status and a thinner mean retina  but not RPE–BM (P = 0.60).The mean macular RPE–BM and retinal thicknesses among all included participants were 25.3 μm (SD 2.9 μm) and 278.5 μm (SD 13.0 μm), respectively. Mean RPE–BM and retinal thicknesses by age and genotype are shown in CFI type 1 RV carrier status and a thinner mean RPE–BM  as well as at the inner superior, inner nasal and all outer Early Treatment Diabetic Retinopathy Study (ETDRS) macular subfields  as well as at the outer superior and outer nasal subfields  or at any subfield  and across all subfields compared with wild-type  and across all inner subfields at the macula  or retinal  macular thickness compared with WT. However, p.A69S heterozygosity was significantly associated with a thinner RPE–BM at the outer inferior subfield and with a thinner retina in the central and inner temporal subfields of the macula  was less than that between 50–59 and ≥60-year-olds (−1.1 μm). In contrast, the greatest difference in mean retinal thickness across age groups was observed between 50–59 and ≥60-year-olds across all genotypes, especially in CFI type 1 RV (−3.7 μm) and ARMS2 p.A69S homozygous (−3.8 μm) groups.Combined RPE–BM and retinal thicknesses at the macula were thinner with increasing age across all genotype groups  and retinal (P = 0.13) thickness with age between CFI type 1 RV carriers and non-carriers (P = 0.68) and retinal (P = 0.34) thickness with age between CFI VUS carriers and non-carriers .To further explore the relationship between age, genotype, and macular thickness, we plotted mean RPE–BM/retinal thicknesses at each year of age, stratified by genotype, and fitted linear regression models to these . Next, wcarriers . There wcarriers . There w p.Y402H , althoug p.Y402H . Similar2 p.A69S , but obs2 p.A69S . FinallyCFI type 1 RV carriers (1.7%) was greater than that among CFI VUS carriers (0.8%). The proportion of CFI type 1 RV carriers among AMD cases was 0.73%, compared with 0.33% among non-AMD cases. In contrast, the proportion of CFI VUS carriers was the same for both AMD and non-AMD cases (1.3%). No CFI RV compound heterozygotes were diagnosed with AMD  had received an inpatient diagnosis of AMD at the time of recruitment, which is less than the prevalence of advanced AMD in similar populations . The prewith AMD .CFI type 1 RV carriers, 62.2 (4.8) for CFI VUS carriers, 62.9 (5.6) and 63.4 (5.0) for CFH p.Y402H heterozygotes and homozygotes, respectively, 63.0 (5.5) and 63.8 (5.0) for ARMS2 p.A69S heterozygotes and homozygotes, respectively, compared with 63.0 (5.5) across the entire population. An overview of AMD prevalence by age and genotype is presented in The mean age of participants diagnosed with AMD was 63.1 years (SD = 5.7) for CFI type 1 RV carrier status was significantly associated with a higher odds ratio (OR) of AMD . We also showed that harboring a CFI VUS did not influence the odds of AMD in either direction . Additionally, we confirmed an allele–dose response of CFH p.Y402H and ARMS2 p.A69S on AMD risk (Multilevel logistic regression confirmed that AMD risk . UnivariCFI type 1 or type 2 RV carriers were represented. One CFI VUS carrier (p.G261D heterozygous) had a diagnosis of MPGN type 1 or 3, but none had a diagnosis of TMA.Among the 24 participants with a health record-derived diagnosis of TMA and 47 with MPGN, no CFH p.Y402H, ARMS2 p.A69S and CFI type 1 RV or VUS genotypes into our multivariable logistic regression model  to explore whether the effect of each risk genotype on AMD risk would differ in the presence of other genotypes , indicating that the combined effect of these genotypes is seven times the product of the individual effects of each genotype separately. In contrast, there was no significant interaction between CFI type 1 RV carrier status and CFH p.Y402H homozygosity . There were also no significant interaction effects between CFI type 1 RV and ARMS2 p.A69S heterozygous  or CFH p.Y402H heterozygous  states on AMD risk. In addition, we found highly significant interactions between CFH p.Y402H and ARMS2 p.A69S on AMD risk when either genotype existed in the homozygous state  and mean retinal thickness , as well as the lack of association seen between CFI VUS and mean RPE–BM  or mean retinal thickness . Removal of non-white individuals from the analysis retained the significance of the associations seen between CFI type 1 RVs and mean RPE–BM  but reduced the significance of the associations seen between CFI type 1 RVs and mean retinal thickness , while retaining the lack of association between CFI VUS and mean RPE–BM  or mean retinal thickness .Results from the multivariable analyses with RVTESTS and regenie confirmed the associations seen between CFI SNP which has been associated with AMD in previous genome-wide association studies (GWAS)  and VUS . To further confirm that this common marker does not influence our findings, we repeated our analyses in RVTESTS to include the rs10033900 genotype (coded as a two-level factor) and found that our associations were essentially unchanged for both CFI type 1 RVs  and VUS .To test whether these findings were independent of rs10033900, a common CFI rare variants (type 1 or VUS) and the binary AMD disease phenotype in the full UK Biobank cohort using RVTESTS or regenie proved too computationally prohibitive for our computer system, so we used a simpler approach whereby we removed all non-white individuals and one of each pair of related (with kinship >3rd degree) individuals. This left 321 389 individuals for analysis using multivariable logistic regression (glm function in R) with age, gender, smoking status and genotypes at CFH p.Y402H and ARMS2 p.A69S (both coded as two-level factors) as covariates. Results confirmed the associations seen between CFI type 1 RVs and AMD  as well as the lack of association seen between CFI VUS and AMD . Models including interaction terms in this smaller dataset found no significant interactions between CFI type 1 RVs or VUS and CFH (P = 0.39 between CFI type 1 RVs and CFH p.Y402H homozygotes) or ARMS2 (P = 0.47 between CFI type 1 RVs and p.A69S homozygotes) on AMD risk, although interactions between CFH p.Y402H or ARMS2 p.A69S risk genotypes were significant .Testing for association between CFI, CFH and ARMS2/HTRA1 (HtrA serine peptidase 1 gene) genes on RPE–BM and retinal thicknesses at the macula, and analyzed their interaction on AMD risk. We demonstrated strong associations between thinner RPE–BM/retinal layers and the principal AMD risk factors of increasing age and smoking ..CFI, CFHCFI type 1 RVs increase AMD risk independently of demographic and common genetic factors  and that our controls are WT participants. These study design differences are likely to have amplified the effect of ARMS2 p.A69S observed by Zouache and colleagues. With increasing age, we may expect ARMS2/HTRA1-associated retinal thinness in our cohort to also extend to most ETDRS subfields, in line with our identification of a significant association between mean RPE thickness and age among heterozygous relative to WT ARMS2/HTRA1 participants , rather than the effects of Factor H on C3 convertase dissociation (which is not Factor I-dependent)  . Indeed,pendent) . This thterature  22). Fu. FuCFI tase risk , althougCFI rare variants (type 1 or VUS) and the mean RPE–BM or mean retinal thickness phenotypes using the complementary analytical approaches provided by the RVTESTS and regenie software packages. This approach has been shown to perform similarly to linear mixed model approaches in terms of adjusting for ancestry. In principle, both analyses are expected to account for both close and distant levels of relatedness (i.e. family relationships and ethnicity); however, as an additional sensitivity check, we also repeated these analyses removing all participants that had been flagged by UK Biobank as being ‘non-white’. The results of these analyses with the full cohort confirmed that CFI type 1 RVs, but not CFI VUS, are associated with a reduction in mean RPE–BM and retinal thicknesses. On removing non-white individuals from our analyses, the association between CFI type 1 RVs and reduced mean RPE–BM thickness was robust, while the association with reduced mean retinal thickness was lost. Furthermore, after excluding all non-white individuals and one of each pair of related individuals from our cohort and repeating our multivariable logistic regression analysis, we showed that the association between CFI type 1 RVs and AMD is robust to genetic confounding and likely causal. However, the interaction between CFI type 1 RVs and ARMS2 p.A69S status on AMD risk was less robust in this smaller cohort.A potential criticism of the results as presented is that these analyses did not consider the known relatedness that exists between several UK Biobank participants, nor the known differences in genetic structure between subpopulations, which may result in increased type 1 error rates when testing for genotype–phenotype associations. To check sensitivity to these issues, we performed a more robust analysis of the association between CFI GWAS variant rs10033900. Such an explanation seems unlikely based on the relatively low level of linkage disequilibrium seen between rs10033900 and type 1 RVs in our sample  but, as an added check, we repeated the RVTESTS and regenie analyses including rs10033900 genotype (coded as a two-level factor) as an additional covariate in our analyses, observing negligible differences in the P-values obtained.One question is whether these rare variant associations can be attributable to the known CFI type 1 RV alleles in our population were lower than previously reported  readings were obtained from the UK Biobank Resource, and the mean of these was calculated for each participant. Body mass index (BMI) was also obtained from the UK Biobank Resource. Eye measures included logarithm of the minimum angle of resolution (logMAR) visual acuity, Goldmann-corrected intraocular pressure (IOPg) using the Ocular Response Analyzer®  and spherical equivalent measurements from autorefraction using the RC-5000 device  for each eye. Nonmydriatic retinal SD OCT measurements were acquired in a dim room with the Topcon 3D OCT 1000 Mk2 device , using the 6 × 6 mm raster pattern 3D macular volume scan consisting of 128 B-scans, which each B-scan comprising 512 horizontally oriented A-scans.The UK Biobank has approval from the North West Multi-centre Research Ethics Committee, which covers the UK, in accordance with the tenets of the Declaration of Helsinki. Consent in relation to the Data Protection Act 1998 and (where applicable) the Human Tissue Act 2004 has been obtained the relevant UK Biobank participants prior to enrollment. The Resource is available to all bona fide researchers for all types of health-related research that is in the public interest, and all applications to use the Resource are checked to ensure that research proposals are consistent with the Resource’s Access Procedures, the Ethics & Governance Framework and the consent that was provided by the participants.CFI rare variants represented in the UK Biobank DNA microarray  proximity and high linkage disequilibrium (r2 = 0.99) (c.205G>T(p.A69S), contained within the common ARMS2/HTRA1 AMD risk haplotype (All participants were genotyped for approximately 800 000 genetic variants using the UK Biobank Axiom Array® or the highly similar UK BiLEVE Axiom® Array from Affymetrix (now Thermo Fisher Scientific Inc.), described elsewhere . Around croarray . We also = 0.99) , and ARMaplotype .All OCT images were stored as .fds and .fda files within a central repository at Advanced Research Computing, University of Oxford, UK, via remote login. The Topcon Advanced Boundary Segmentation (TABS™) segmentation software  was used to automatically segment the retinal surfaces as previously described ,21. InteThe linkage of all UK Biobank participants to health-related records allowed us to investigate the effect of genotype on AMD diagnosis. In the absence of robust mapping to AMD within the resource, we used the four-digit codes of the International Classification of Disease (ICD-10 and ICD-9) to identify individuals who received a diagnosis of degeneration of the macula and posterior pole of retina  from hospital inpatient data and death registry data. We did not use self-reported estimates for AMD as the condition is often asymptomatic in its early stages, thus the accuracy of this measure is likely to be poorer with a greater underestimation of prevalence. We also obtained outcome data on MPGN and TMA in this manner.Participants who had undergone eye surgery less than 4 weeks ago were excluded from all ocular measurements. Subjects were excluded from segmentation analysis if they had poor OCT signal strength, poor image quality, poor centration certainty, missing thickness values from any ETDRS macular subfields, refractive error > +6 diopters (D) or < −6 D, visual acuity worse than 0.1 logMAR, IOPg ≥ 22 or  ≤ 5 mmHg or a self-reported history of ocular illness, diabetes or neurodegenerative disease—as previously defined ,21. AddiCFI Type 1 RV  and CFI VUS , in line with previous analyses of patient samples and/or recombinant protein  and Minitab 17 Statistical Software . We used the following aggregate terms for our analyses:  protein ,18,46–49 protein . Althougα to enter = 0.05, α to remove = 0.1) using the covariates of CFI type 1 RV, CFI VUS, CFH p.Y402H and ARMS2 p.A69S carrier status—as well as age, gender, ethnicity, smoking status, Townsend index, refraction, IOPg and SBP, which have previously been associated with both RPE and retinal thickness at the macula. We also included BMI among the potential covariates for the derivation of retinal thickness as a proxy for height, as the former was available for a 10-fold greater number of participants.We used univariable linear regression to compare the relationship of genotype to RPE and retinal thickness for each position on the ETDRS macular map, adjusting for multiple testing in subgroup analyses using Tukey multiple comparisons of means with 95% family-wise confidence level . To furtThis stepwise approach encompasses the spatial variation in strength of association between macular thickness and clinical predictors, which has previously been reported . We testCFI type 1 RV, CFI VUS, CFH p.Y402H and ARMS2 p.A69S genotypes on AMD diagnosis using a multivariable logistic regression model with age, gender, ethnicity, smoking status and genotype as independent variables, and the products of selected genotypes as interactive terms.We undertook multilevel (mixed effects) logistic regression using maximum likelihood estimation (glm function in R) to investigate the relationship between each genotype and odds of AMD diagnosis adjusted for age, gender, ethnicity, smoking status and genotype and by selected genotypes as fixed effects, and for site of recruitment as a random effect to account for correlations between AMD risk and unobserved heterogeneity such as unmapped genetic variation that may segregate regionally. Finally, we examined the interactions between Our logistic regression model achieved favorable model fitting criteria, as demonstrated by the successful reduction of AIC with the sequential inclusion of covariables, a C-statistic of 0.75 indicating good-to-strong model discrimination, and non-significance of Hosmer–Lemeshow testing indicating that our model performs equally well across the range of probabilities of AMD . AdditioFor calculation of an empirical kinship matrix within RVTESTS, we used the Balding–Nicols method based on 42 757 genome-wide SNPs chosen to be in approximate equilibrium. For sensitivity analyses using the regenie package, we reduced the dimension of genetic data using ridge regression applied to blocks of 259 051 genome-wide SNPs exhibiting low levels of linkage equilibrium, and then combined the resulting predictors using a second round of linear or logistic ridge regression to produce an overall prediction for each trait. As a further sensitivity check, we also repeated the RVTESTS and regenie analyses removing all UK Biobank individuals that had been flagged by UK Biobank as being ‘non-white’.CFH p.Y402H and ARMS2 p.A69S (both coded as two-level factors). For regenie, which requires that all covariates be measured in all individuals, we included as covariates age, gender, smoking status and genotypes at CFH p.Y402H and ARMS2 p.A69S (both coded as two-level factors). Prior to undertaking these analyses, we also excluded samples flagged as failing the centrally performed quality controls for heterozygosity, and those flagged as having a mismatch between self-reported and genotype-derived gender or potential sex chromosome aneuploidy. We did not exclude participants with missing CFI genotypes from our sensitivity analyses.For RVTESTS, which mean imputes any missing covariates to the mean, we included as covariates age, gender, smoking status, Townsend index, IOP, refraction, SBP and genotypes at Supplemental_Appendix_1_ddac060Click here for additional data file.Supplemental_Appendix_2_ddac060Click here for additional data file.Supplemental_Figure_1_ddac060Click here for additional data file.Supplemental_Figure_2_ddac060Click here for additional data file.Supplemental_Figure_3_ddac060Click here for additional data file.Supplemental_Figure_4_ddac060Click here for additional data file.Supplemental_Table_1_ddac060Click here for additional data file.Supplemental_Table_2_ddac060Click here for additional data file.Supplemental_Table_3_ddac060Click here for additional data file.Supplemental_Table_4_ddac060Click here for additional data file.Supplemental_Table_5_ddac060Click here for additional data file.Supplemental_Table_6_ddac060Click here for additional data file.


While the anxiety score decreased after eating in both groups, a higher fasting sEH was associated with a lower postprandial anxiety decrease in HW . sEH characterization using direct measurements verified the relationship between the protein expression and in vivo activity of this important oxylipin modulator, while a well-controlled food challenge study design using HW and a clinical control group of women with disordered eating elucidated sEH’s role in the health of adult women.The metabolism of bioactive oxylipins by soluble epoxide hydrolase (sEH) plays an important role in inflammation, and sEH may be a risk modifier in various human diseases and disorders. The relationships that sEH has with the risk factors of these diseases remain elusive. Herein, sEH protein expression and activity in white blood cells were characterized before and after a high-fat meal in healthy women (HW) and women with anorexia nervosa (AN). sEH expression and sEH activity were significantly correlated and increased in both groups two hours after consumption of the study meal. Fasting sEH expression and activity were positively associated with body mass index (BMI) in both groups, while an inverse association with age was found in AN only ( Epoxide Hydrolase 2 (EPHX2) gene, mapped on 8p21.2–p21.1 -trans-diphenyl-propene oxide (t-DPPO) as substrate [final = 50 µM). The mixture was incubated at 37 °C for 90 min, and the reaction was quenched by the addition of 60 µL of methanol and 200 µL of isooctane, which extracts the remaining epoxide from the aqueous phase. Extractions of the stopped reaction with 200 µL of 1-hexanol were performed in parallel to assess the possible presence of glutathione transferase activity, which could also transform the substrate [Peripheral blood mononuclear cells (PBMCs) were immediately isolated by density gradient centrifugation with Ficoll-Paque . The cell suspensions were flash-frozen and kept at −80 °C until analysis. After thawing on ice, the cells were broken with a 10-second ultrasonic pulse. Protein concentration was quantified using the Pierce BCA assay , using Fraction V bovine serum albumin (BSA) as the calibrating standard. Separately, the homogenized mixture was diluted with chilled sodium phosphate buffer (20 mM pH 7.4) containing 5 mM of EDTA, 0. 1 mM of DTT, 1 mM of PMSF, 0.1 mg/mL of BSA and 0.01% Tween 20 to measure the residual sEH activity using [ubstrate . Brieflyubstrate . The actt-tests and analysis of covariance (ANCOVA) models that were adjusted for age, BMI, and sEH assay batch. Postprandial changes in sEH were assessed using one-sample t-tests within each group separately. sEH associations with age, BMI, and clinical phenotypes were examined within each group using Pearson’s correlations as well as age-and-BMI-adjusted linear regression models. The cell-count-normalized data of sEH expression and activity were used to verify the validity of the results of non-normalized (absolute) sEH levels. In HW only, sEH expression and activity were compared between White women and non-White women, as well as between White women and Asian women, at the fasting and postprandial timepoints using two-sample t-tests and ANCOVA models that were adjusted for age, BMI, and sEH assay batch. All statistical analysis was performed using R version 4.2.1 .Correlations between sEH expression and activity were analyzed in HW and women with AN using Pearson’s correlations and multiple linear regression models that were adjusted for age and BMI. sEH protein expression and enzymatic activity, and their postprandial changes, were compared between the two groups using two-sample