Zostera marina) has been designated an Ecologically Significant Species in Atlantic Canada. The development and rapid expansion of netpen finfish aquaculture into sensitive coastal habitats has raised concerns about the impacts of finfish aquaculture on eelgrass habitats. To date, no studies have been done in Atlantic Canada to examine these impacts or to identify potential monitoring variables that would aid in the development of specific conservation and management objectives. As a first step in addressing this gap, we examined differences in environmental variables, eelgrass bed structure and macroinfauna communities at increasing distances from a finfish farm in Port Mouton Bay, a reference site in adjacent Port Joli Bay, and published survey results from other sites without finfish farms along the Atlantic Coast of Nova Scotia. Drawing on research done elsewhere and our results, we then identified possible metrics for assessing and monitoring local impacts of finfish aquaculture on eelgrass habitats. Our results suggest some nutrient and organic enrichment, higher epiphyte loads, lower eelgrass cover and biomass, and lower macroinfauna biomass closer to the farm. Moreover, community structure significantly differed between sites with some species increasing and others decreasing closer to the farm. Changes in the macroinfauna community could be linked to observed differences in environmental and eelgrass bed variables. These results provide new insights into the potential impacts of finfish aquaculture on eelgrass habitats in Atlantic Canada. We recommend a suite of measures for assessment and monitoring that take into account response time to disturbance and account for different levels of eelgrass organizational response .Eelgrass ( Seagrass beds are among the most productive and diverse ecosystems on the planet ; howeverPosidonia oceanica meadows in the Mediterranean Sea . The dinean Sea .Zostera marina, commonly known as eelgrass, is the dominant species of seagrass in Atlantic Canada  assess the changes in eelgrass bed structure and associated macroinfaunal communities at increasing distances from a finfish farm in Port Mouton Bay, and a reference site in adjacent Port Joli Bay, Nova Scotia, (ii) link the observed changes in macroinfauna to changes in environmental and eelgrass bed variables, and (iii) suggest possible monitoring metrics for assessing and managing the impacts of finfish aquaculture on eelgrass habitat. We also place our results in a broader context by comparing them to published eelgrass bed surveys from other sites without fish farms on the Atlantic Coast of Canada  and to p2  until ∼2000, followed by Atlantic salmon  until 2009, fallowed from 2010–2012, and stocked with rainbow trout in 2012–2014. The farm lease has been re-licensed for Atlantic salmon and rainbow trout from March 2015 to March 2020  near Spectacle Island  occupiesrch 2020 . Informarch 2020 . Environrch 2020 . Sedimenrch 2020 . In genea concentration, percent cover of epiphytic and benthic annual algae and epiphytic fauna, (2) eelgrass tissue variables, including % nitrogen content and stable isotope ratios of δ15N and δ13C, (3) eelgrass plant and canopy structure, including canopy height, shoot density, percent cover and biomass, and (4) macroinfauna abundance, biomass, species richness and community composition between study sites with increasing distance from the finfish farm in Port Mouton Bay and a reference site in adjacent Port Joli (PJ) Bay  Bay , Table 2(PJ) Bay  to check13C, δ15N) had not been collected. These seven other NS sites had no fish farm or other major point source of pollution close the respective sampling sites . Temperature and depth were recorded on SCUBA dive computers.All sites were in relatively sheltered, shallow, soft-sediment areas , Table 2 loading  which in−2) and wet weighed (biomass WW g m−2). In the laboratory, the eelgrass blades (AG) and roots and rhizomes (BG) were rinsed again and all epiphytes were carefully scraped off the blades. AG and BG tissue was then weighed  prior to drying in an oven at 60 °C for 48 h and weighed again for dry weight (DW g m−2). Once dry, the AG and BG tissues were homogenized separately and a well-mixed 50 mg subsample of each were sent to the University of California Davis Stable Isotope facility to analyze the tissue nitrogen (%N) content as well as the carbon (δ13C) and nitrogen (δ15N) stable isotopes.Seagrass biomass as well as the abundance of sediment macroinfauna were collected using sediment cores  at each of the six sampling locations along the transects at each site. First, we examined the core to check whether we could observe a redox potential discontinuity (RPD) layer, any black or anoxic sediment and sulfur smell. Next, all aboveground (AG) and belowground (BG) eelgrass tissue was removed, rinsed in a 500 µm sieve to capture any fauna, bagged and kept on ice. Sediment type in each core was recorded , and the presence of any sulfur smell indicating hypoxia or anoxia. The remainder of the core contents were sieved (500 µm) on site and all macroinfauna species were identified to the lowest possible taxon. If organisms needed further identification, they were kept on ice and brought back to the laboratory and examined under a dissecting microscope. Individuals of each species were counted (abundance ma concentrations.Microphytobenthos (MPB) and sediment organic content (SOC) were collected using 60 ml syringe cores . At each of the six sampling locations, two samples were collected for SOC (volume of sample ∼8.83 mL) and three for MPB (volume of sample ∼3.53 mL). Both SOC samples were placed in a plastic bag and frozen until processed whereas each set of three MPB samples were combined on site, placed in plastic cryovials and stored in liquid nitrogen while in the field and in a freezer (−20 °C) until analysis in the laboratory. In the laboratory, SOC samples were processed according to p ≤ 0.05) differences were found in the paired variables, univariate PERMANOVA was used to assess the effect of site on each of the individual environmental and eelgrass parameters followed by post-hoc pairwise tests between sites if there was a significant main effect. We also considered significance levels of p ≤ 0.1 if differences were ecologically relevant with regard to observed effects in the published literature  except for the seven other sites that were grouped into NS as their site designation and included in the statistical analyses. As such, we had 1 fixed factor (site) with five levels . We used multivariate permutational analysis of variance (PERMANOVA) to assess the effect of site on the Euclidean distance matrix of each non-independent pair of canopy and environmental variables. If statistically significant  and biomass separately both with and without the inclusion of the NS sites. Abundance and biomass data were square-root transformed in order to down-weight the influence of highly abundant or large species . If a six-axis) and the cumulative percent dominance (y-axis) to compare the k- dominance curves for macroinfauna abundance and biomass at each site  curves, SIMPER and BIOENV analyses. We used ABC curves of the log species rank (ach site . In unpoach site . This me13C and δ15N) and eelgrass canopy variables  and those with high correlation (≥0.7) were never included in the same analysis. If variables were equally correlated , we chose to include the variable most relevant for infauna . Therefore, four environmental , three eelgrass tissue , and four eelgrass canopy  variables were used in the analyses. BIOENV provides a non-parametric index rho (ranging from 0 to 1) that indicates how closely different combinations of environment and eelgrass canopy variables explain the multivariate pattern of the macroinfauna community based on the abundance and biomass data and individual SIMPER species. We then used a permutation test to determine the significance level of the sample statistic (rho).To determine which species contributed most consistently (>10%) to the differences in the infauna assemblages between sites near the fish farm, we used similarity percentages (SIMPER) analysis . BIOENV Finally, to combine all variables, we ran a non-metric MDS overlaid with cluster analysis using a normalized Euclidean distance matrix of all environmental, eelgrass tissue and eelgrass canopy variables, as well as macroinfauna total abundance, total biomass and species richness to explore how the sites in Port Mouton Bay and Port Joli Bay cluster relative to the other sites in Nova Scotia. All PERMANOVA, MDS, cluster, ABC, SIMPER and BIOENV analyses were carried out using PRIMER (version 6.1.11) with PERMANOVA+ .Bottom temperature ranged from 12−15 °C between the four sites and sampling depth ranged from 1.7–2.9 m . Sedimenp > 0.05) but ecologically relevant differences were found (13C) and nitrogen (δ15N) stable-isotope ratios significantly differed between sites  and belowground (BG) tissue nitrogen (%N), no statistically significant  and total biomass , but not for species richness  of macroinfauna between sites . Cluster analysis of centroids based on infauna abundance data , with the highest abundance and biomass closest to the fish farm . In turn, Amphitrite sp. as well as Ophelia sp. only occurred at the reference site PJ, whereas the bivalves Cerastoderma pinnulatum and Tellina agilis were most abundant at CB  and the Bray–Curtis similarity matrix of macroinfauna community structure , and the assemblage based on biomass data to BG eelgrass biomass, BG %N and BG δ13C (C. capitata were most correlated to the percent cover of hydroids (%H), while the next best correlations also included SOC and MPB. In contrast, the other species were more correlated with eelgrass bed structure, with BG eelgrass biomass being the most important  and NS, and another cluster of the more polluted sites, SI and OW .Capitella capitata, a known indicator of polluted conditions, specifically organic enrichment  of 8–10‰  up to 20‰   up to >1,000 m from fish farms  are used for studying the source and fate of organic carbon in ecosystems and food webs. Under increased nutrient and organic loading which, among other effects, increases sediment organic content and decreases light conditions, the balance in carbon utilization in seagrasses shifts from inorganic carbon fixation (photosynthesis) toward belowground consumption of organic carbon (respiration)  . A more material . We founsh farms  or land sh farms . Thus, w15N) in response to changes in nutrient supply or environmental quality  occurs more quickly (days and weeks) than changes to morphology  (13C isotope signatures) and morphological (dead leaves and rot in the meristematic region) have been observed within 3 weeks  . Under hdensity) , however 3 weeks . Physiol 3 weeks .Posidonia oceanica was the sedimentation of organic material  including finfish aquaculture  followed by lower numbers at CB (∼0.7 km)  are responsible for adding topographical relief to sediments which in turn is more effective in trapping and burying Z. marina seeds and, hence, improving recruitment (C. torquata abundance was lowest at the sites closest to the fish farm (SI and CB) suggesting a potential recruitment risk to the eelgrass beds in these areas that should warrant further monitoring.In their study on the effects of fish farming on soft-bottom polychaete assemblages,  pattern . The low pattern . In our ∼0.7 km) . C. torqruitment . In our Amphitrite sp. and Ophelia sp. were present only at our reference site (PJ) and the mollusc Tellina agilis was present only at two sites closer to the fish farm (SI and CB). The occurrence and distribution of these species is not readily explained without further study. Apart from C. capitella, which is a widely used indicator of organic enrichment, a potential other biological indicator to assess the impact of fish farm waste on macroinfaunal in Z. marina habitat could include C. torquata.Other species in our data set such as 13C as an indicator for enhanced decomposition of organic material, and the cover of epiphytic and benthic annual macroalgae (%A) as a proxy for eutrophication could be linked to community composition based on biomass or abundance. The correlation between macroinfauna composition and belowground eelgrass biomass as well as detritus is well documented and has been linked to the role eelgrass roots and rhizomes have in accumulating and stabilizing sediments which in turn provide habitat and food to the associated detritivore-dominated infauna, releasing oxygen to the sediments and providing protection from predators (C. capitata was most correlated to epiphytic suspension-feeding hydroid cover (%H) as well as biogeochemical sediment conditions . Increases in epiphyte loads, both annual algae and suspension feeders, as well as annual benthic macroalgae and microphytobenthos have been associated with increased organic and nutrient loading from fish farms or other sources  to nutrient disturbances while population-level measures, such as shoot density or biomass, reflect the impact of disturbances on longer time scales (months to years)  in coastal marine environments . Consequo years) . A singlo years) .Z. marina in Atlantic Canada, the impacts of netpen finfish farming on P.  oceanica in the Mediterranean have been the subject of extensive research ; and tissue nitrogen content and isotopic signature. Our selection of indicators is consistent with the key indicators identified for the response and recovery of seagrasses to nutrient and organic loading in a recent global review and assessment (Unlike research  with theresearch . As a redecline;  and sitidecline;  have beelphides;  and morplphides;  differenlphides;  and the sessment . As for sessment . HoweverWithin the last five to ten years, there have been growing concerns about the potential significant spread and persistence of finfish aquaculture waste over large spatial areas . Our res10.7717/peerj.5630/supp-1Supplemental Information 1Click here for additional data file.


We have identified several genes of porcine oocytes , whose expression after in vitro maturation (IVM) is downregulated with different degrees. Our results may be helpful in further elucidating the molecular basis and functional significance of a number of gene markers associated with the processes of migration, proliferation and angiogenesis occurring in COCs.The growth and development of oocyte affect the functional activities of the surrounding somatic cells. These cells are regulated by various types of hormones, proteins, metabolites, and regulatory molecules through gap communication, ultimately leading to the development and maturation of oocytes. The close association between somatic cells and oocytes, which together form the cumulus-oocyte complexes (COCs), and their bi-directional communication are crucial for the acquisition of developmental competences by the oocyte. In this study, oocytes were extracted from the ovaries obtained from crossbred landrace gilts and subjected to in vitro maturation. RNA isolated from those oocytes was used for the subsequent microarray analysis. The data obtained shows, for the first time, variable levels of gene expression (fold changes higher than |2| and adjusted  The formation of fully mature oocyte consists of nuclear and cytoplasmic events, which are necessary for the acquisition of the competence for their fertilization, and further development of the embryo. Development of oocytes begins in the fetal ovary, whereas the final oocyte growth and maturation occurs during adulthood . During The growth and development of oocyte affect the functional activities of the surrounding somatic cells. These cells are regulated by various types of hormones, proteins, metabolites and regulatory molecules through gap communication, ultimately leading to the development and maturation of oocytes . The cloGrowing oocytes in the ovary acquire the ability to mature through a two-way communication between the gamete and surrounding somatic cumulus cells (CCs) ,5,6. OocMicroarray DNA technology is a useful method to examine changes in gene expression. Analysis of the oocyte transcriptome could be a powerful tool for improving our knowledge about the pathways involved in oocyte development . MicroarIn this study, the aim was to identify new gene markers involved in cellular proliferation, migration and apoptosis. In vitro cultures of porcine COCs were performed. Then the transcriptomic profile changes of oocyte genes involved in regulation of cell migration, cell proliferation, and programmed cell death, was investigated. The genes whose expression values differed significantly in porcine oocytes, when analyzed before (immature) and/or after in vitro maturation , were analyzed. Our results could provide evidence about the processes of communication between oocyte and cumulus cells and allow to define the genes responsible for the functioning of CCs, which are directly related with oocytes.p-value < 0.05. Applying these criteria yielded 419 different genes. This group was subjected to significantly enriched GO BP identification. All of the raw microarray results were uploaded to the GEO database (available at: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE97246).Whole transcriptome profiling using Affymetrix microarray allowed us to analyze the gene expression changes in freshly isolated oocytes, before in vitro procedure (“Before IVM”), in relation to after in vitro maturation (“After IVM”). Using Affymetrix® Porcine Gene 1.1 ST Array we have detected the expression of 12,258 porcine transcripts. To be taken under consideration as differentially expressed, the genes needed to express a fold change higher than |2| and with a corrected https://david.ncifcrf.gov/) software was used for extraction of the genes belonging to the “regulation of cell proliferation”, “regulation of programmed cell death”, and “regulation of cell migration” gene ontology Biological Process terms (GO BPs). We found that 42 genes from these GO BP terms were significantly represented in down-regulated gene sets. These sets of genes were subjected to hierarchical clusterization procedure and presented as heat maps . The results are shown in Finally, we investigated the functional interactions between chosen genes with REACTOME FIViz app to Cytoscape 3.6.0 software  and cumulus cells (CCs). CCs are directly related to the oocyte forming cumulus-oocyte complexes (COCs) together . GCs plaRecognition of interactions in a microenvironment of COCs is the key to understanding the physiology process at this system level. It is important to learn how the molecular interactions between the oocyte and CCs proceed. Acquisition of full developmental ability for fertilization by oocytes is accompanied by morphological and biochemical changes. These modifications occur during long stages of folliculogenesis and oogenesis in both oocytes and CCs ,18. TherMolecular interactions and their complexity between the oocyte and the environment CCs during folliculogenesis are not well known. A new method of gene expression analysis such as microarrays enabled to discover a new look at COC functions and pathways activated during follicular development. The microarray technique provides a global analysis of the tissue transcriptome and is a hypothesis-generating tool . Our stuMicroarray gene expression analysis was performed on immature and in vitro matured porcine oocytes The obtained data points to a key role of genes belonging to this functional groups. Furthermore, it is suggested that the expression of these genes can play a positive role in the future embryo development. Our study investigates how the expression of genes responsible for migration, proliferation or apoptosis changes during oocyte maturation. Considering the close interaction and type of communication between oocyte and cumulus cells, the expression of genes belonging to these four groups may have a direct impact on the occurrence of these processes in the somatic cell population directly related to the oocyte membrane.The relationship between transcription levels of expressed genes in oocytes and cumulus cells strongly indicates that the interaction between oocyte and CCs is partly modulated by the mechanisms of gene regulation . It alsoDespite above reports, there are not many cases regarding the transcriptomic profile analysis of immature and matured pig oocytes. Those available that have brought these topics closer to understanding, pointed out a new look at functions of the detected genes during maturation of pig oocytes . In our All four analyzed ontological groups show the most important processes for the maturing oocyte beginning from the early stages of folliculogenesis to form COCs and achieve nuclear maturity. CCs proliferation and COCs differentiation are thought to define the developmental competence of COCs for growth and development, as well as further embryonic viability . StudiesID2, VEGFA, BTG2, ESR1, CCND2, EDNRA, ANGPTL4, TGFBR3, GJA1, LAMA2 genes which are most downregulated and group of KIT, TPM1, VCP, GRID2, MEF2C, RPS3A, PLD1, BTG3, CD47, MITF genes which expression is less downregulated after IVM culture.In our research, using a microarray approach, we wanted to study the porcine oocyte transcriptomic profile before and after in vitro maturation (IVM) to define new molecular markers in female gametes associated with their ability to mature. It was found that all of the 42 analyzed genes belonging to the analyzed ontology groups are downregulated after IVM. From those differentially expressed genes we have selected and analyzed ID2 (inhibitor of DNA binding 2). This gene encodes a protein belonging to a DNA-binding family of inhibitors whose members are transcriptional regulators, exhibiting non-primary helix-loop-helix (HLH) domains. The protein encoded by ID2 may play a role in the negative regulation of cell differentiation [ID2 expression is regulated in response to countless stresses, including hypoxia and ischemia, suggesting a role in adaptive cellular responses to metabolic stress [VEGFA . This growth factor induces proliferation and migration of vascular endothelial cells and is upregulated in many known cancers. Its expression correlates with the degree of cancer progression. VEGFA is the main factor and regulator of angiogenesis in the ovulatory follicle and promotes endothelial cell migration [VEGFA and KIT (proto-oncogene receptor tyrosine kinase) or INSR (insulin receptor) genes. VEGFA activates KIT and INSR, which are mainly related to the positive regulation of cell proliferation and migration. Activities of this three genes can be regulated by the porcine oocyte maturation process, participating together in differentiation and development of COCs [The most downregulated gene that belongs only to the “regulation of cell proliferation” ontology group is ntiation . Level ontiation . ID2 expc stress . A definigration ,31,32. Iigration ,34. We f of COCs .BTG2 (B cell translocation gene 2) belongs to all analyzed ontology groups. BTG2 has anti-proliferative properties and belongs to the family of genes that are involved in development, death, apoptosis, differentiation and survival of cells [ESR1 (estrogen receptor 1) and ANGPTL4 (angiopoietin-like 4). ESR1 gene is involved in the ovarian response to exogenous FSH. Since the first reports about estrogens effects on the ovarian follicle growth, maturation, and release of the oocyte, ESR1 has been associated as a marker [ANGPTL4 is characterized as a gene associated with angiogenesis, it plays a key role in the late stages of folliculogenesis, taking part in providing nutrients and oxygen to growing follicles [CCND2 (cyclin D2), EDNRA (endothelin receptor type A) and GJA1 . They all belong to the “regulation of cell proliferation” ontology group. Homologous knockout studies in mice suggest the key role of CCND2 in ovarian GCs and germ cell proliferation. Cyclin D2 mRNA is presented in GCs of growing vesicles. Their expression was induced by FSH and quickly inhibited by LH surge [CCND2 in human CCs during maturation of oocytes is a marker of poor prognosis for embryo development and consequently lower fertility [EDNRA is responsible for the production of endothelin type A receptor and regulates muscle cells vasoconstriction. EDNRA protein level is significantly reduced in the uteroplacental vascular bed [GJA1 belongs to connexin gene family that encodes a protein which is a part of gap junction communication channels, allowing the diffusion of low-mass molecules from cell to cell. GJA1, also known as connexin 43, is mainly expressed in GCs, participating in connexons with other GCs or with the oocyte through CCs. Connexin 43 was identified as a gene marker for oocyte and embryo quality [GJA1 regulates communication between oocyte and CCs through its involvement in gap junctions. Lower GJA1 levels are favourable for oocyte maturation. Sheng-Hsiang proved that lower expression of GJA1 is observed in CCs obtained from matured oocytes compared to immature ones [TGFBR3 (transforming growth factor β receptor 3) and LAMA2 . TGFBR3 is important in the development of coronary arteries and various tissue blood vessels. In cancers, reduced expression of this receptor has been observed [LAMA2 gene activates ITGB1 (integrin subunit β 1) and encodes the alpha-2 chain of laminin-2. It was suggested that LAMA2 or TPM1 (tropomyosin 1) encode proteins involved in the formation of oocyte microtubule structure and may affect to the ability of porcine oocyte for maturation. TPM1, which belongs to the group of less downregulated genes can be important in connection and reorganization of the actin microfiber complex during COC maturation. The protein encoded by this gene probably plays a key role in reaching oocyte cellular maturation [MITF (melanogenesis associated transcription factor). MITF belongs to all the analyzed ontology groups except “regulation of cell migration” and has been connected with osteogenesis [CD47 (CD47 molecule) and BTG3 (BTG anti-proliferation factor 3) represent the group of genes which are only related to the regulation of proliferation. CD47 encodes a membrane protein playing an important role in transmembrane transport and signal transduction. CD47 gene is upregulated in tumours that inhibit innate immune responses, including macrophage phagocytosis [PLD1 (phospholipase D1) participates in signal transduction. Together with PLD2 (phospholipase D1), it is expressed in a wide variety of tissues and cells. A small part of PLD1 is located in the plasma membrane, where it contributes to mediating in certain signalling events [RPS3A , MEF2C (myocyte enhancer factor 2C), GRID2 (glutamate ionotropic receptor delta type subunit 2) and VCP . These genes are characterized by a very similar level of expression and belong to the programmed cell death ontology group. Expression of ribosomal protein S3A was decreased in human EAT  [GRID2 is a member of ionotropic glutamate receptor family that mediates in synaptic transmission [VCP was identified as one of the necessary genes in 25 ovarian cancer cell lines, as well as 75 non-ovarian cell lines [of cells . Next ofa marker . In turnollicles . ExpressLH surge . Presencertility . EDNRA iular bed . Microarular bed . This ma quality . GJA1 reobserved . Elevateobserved . Thus, eturation . The genogenesis . The rologenesis . CD47 (Cocytosis . In turng events . Last fo tissue) . GRID2 ismission . VCP wasll lines . So far In summary, we have identified several genes of porcine oocytes, whose expression after IVM is downregulated with different degrees. This data shows, for the first time, variable levels of gene expression belonging to four ontological groups: regulation of cell proliferation (GO:0042127), regulation of cell migration (GO:0030334), and regulation of programmed cell death (GO:0043067), that can be used together as proliferation, migration or apoptosis markers. What is more, all analyzed genes have been significantly downregulated after IVM compared to oocytes assessed before IVM. Our findings show that most of the genes expressed in oocytes are co-expressed and functionally depended on cumulus cells. Close communication between oocyte and CCs, conducted in two directions by a number of mediators and membrane receptors, is a decisive factor in the expression of oocyte genes. Our previous and current results show that the interaction that occurs between oocyte and CCs is not just an exchange of metabolites, it is mainly related to the expression of the same genes on both sides. It is interesting to note that significant expression reduction after IVM occurs, mainly involving genes that were directly or indirectly related to the functioning of the oocytes themselves as well as with CCs. These genes which are less downregulated are not specific to the oocyte itself. Our results may be helpful in further elucidating the molecular basis and functional significance of a number of gene markers associated with the processes of migration, proliferation and angiogenesis occurring in COCs.n = 300) into two groups. Half of the oocytes that were graded as BCB-positive  were qualified as “Before IVM” group. They were directly subjected to the microarray assay and RT-qPCR. The other half of the oocytes (n = 150) were in vitro matured and later analyzed using the same methods, after undergoing a second round of BCB testing and deeming positive (n = 105). This group was described as “After IVM”). The total number of oocytes in each group was divided to obtain three biological replicates. The exact processes of selection, maturation and molecular analysis were described in the further parts of the Materials and Methods section (Brilliant Cresyl Blue (BCB) test was applied to the collected oocytes, which allowed to divide their total number .At the time of slaughter, the ovaries and reproductive tracts were extracted, with their transport to the laboratory taking no more than 40 min from the moment of specimen death. To ensure material integrity, it was kept at 38 °C in 0.9% NaCl through the course of transit. A bath consisting of 5% fetal bovine serum  in PBS was applied to each animal’s ovaries, to ensure optimal conditions for oocyte in vitro maturation and fertilization that followed. A 5 mL syringe and 20-G needle were used to puncture single large follicles (>5 mm) in a sterile Petri dish, which allowed form COC recovery. Modified PBS supplemented with 36 µg/mL pyruvate, 50 µg/mL gentamycin, and 0.5 mg/mL BSA  was used for triple washing of the COCs. The COC selection, counting, and morphological evaluation were conducted using a Zeiss Axiovert 35  inverted microscope. Only grade I COCs that exhibited homogeneous ooplasm and uniform, compact cumulus cells were qualified for subsequent use, which resulted in a total of 300 grade I oocytes.Immediately after collection, 10 from 45 ovaries were fixed in Bouin’s solution for 48 h. Subsequently, they were dehydrated and embedded in paraffin blocks according to a routine procedure. Then, they were cut into 3–4 μm thick sections with a semi-automatic rotary microtome . All ovary paraffin sections were stained with a routine hematoxylin and eosin (H and E) staining method, following the protocol presented . Histolo+). Oocytes were washed twice using modified Dulbecco’s Phosphate Buffered Saline (DPBS) to prepare them for BCB staining. The DPBS was commercially supplemented with 0.9 mM calcium, 0.49 mM magnesium, 0.33 mM pyruvate, and 5.5 mM glucose , and additionally with 50 IU/mL penicillin, 50 µg/mL streptomycin , and 0.4% Bovine Serum Albumin (BSA) (w/v) . The oocytes were afterwards treated with 13 µM BCB  diluted in DPBS at 38.5 °C, 5% CO2 for 90 min. The oocytes were then, after treatment, transferred to DPBS and washed twice. The oocytes were examined under an inverted microscope during this process, which allowed for their classification as stained blue (BCB+) or colourless (BCB−). Only BCB+ oocytes that were clear of accompanying granulosa cells were used for the following molecular analyses (“Before IVM” group) or IVM followed by second BCB test and molecular analyses (“After IVM” group).To assess the quality and maturity of porcine oocytes, the Brilliant Cresyl Blue (BCB) test was used . This asl-glutamine , supplemented with 2.2 mg/mL sodium bicarbonate , 0.1 mg/mL sodium pyruvate , 10 mg/mL BSA (Bovine Serum Albumin) , 0.1 mg/mL cysteine , 10% (v/v) filtered porcine follicular fluid, and gonadotropin supplements of 2.5 IU/mL hCG (human Chorionic Gonadotropin)  and 2.5 IU/mL eCG (equine Chorionic Gonadotropin)  final concentrations. For the first 22 h of maturation, the well plates were overlaid with mineral oil and placed in 38 °C, 5% CO2. Then, the medium was changed for one without hormone supplementation, with the maturation allowed to proceed in the same conditions for another 22 h. Second BCB test was performed following the maturation, with BCB+ oocytes used for subsequent analyses.The IVM was conducted using oocytes that deemed positive in the first BCB test. Nunclon™Δ 4-well dishes  were used for the oocyte maturation in 500 μL standard porcine IVM culture medium: TCM-199 (tissue culture medium) containing Earle’s salts and v/v) for at least 24 h and stained with 1.0% orcein , After that, oocytes were examined under a phase contrast microscope, Nikon Eclipse E200, with the stages of meiotic maturation determined  was evaluated as a control of meiotic maturation from prophase to second metaphase stage. The oocytes were mounted on slides, fixed with acetic alcohol , together with RNeasy MinElute Cleanup Kit  were used for total sample RNA isolation. The final concentration of RNA in resulting batches was determined through the reading optical density at 260 nm, RNA purity was then estimated by the mean of 260/280 nm absorption ratio measurement (>1.8) . Bioanalyzer 2100  was used to confirm RNA integrity and quality. The RNA integrity numbers (RINs) obtained had an average of 9.2, varying from 8.5 to 10 between the samples. The final concentration of 100 ng/μL, as well an OD260/OD280 ratio of 1.8/2.0 were achieved in each sample through dilution. 100 ng from was taken from each sample to be used in microarray analyses. The RT-qPCR study used the remaining RNA amount.® WT Terminal Labeling and Hybridization . Biotin-labelled fragments of cDNA (5.5 μg) were hybridized to Affymetrix® Porcine Gene 1.1 ST Array Strip (48 °C/20 h). Then, microarrays were washed and stained according to the technical protocol, using Affymetrix GeneAtlas Fluidics Station. The array strips were scanned employing Imaging Station of the GeneAtlas System. The preliminary analysis of the scanned chips was performed using Affymetrix GeneAtlasTM Operating Software. Gene expression quality was examined using software provided control criteria. Downstream data analysis was performed using the obtained CEL files.The Affymetrix procedure was described previously in our papers ,11,53,54https://www.bioconductor.org/), based on the statistical R programming language, was used to conduct all the analyses. RMA (Robust Multiarray Averaging) was employed to correct background, normalize and summate the raw data. It was a part of the “affy” package of BioConductor. The “oligo” package provided the biological annotation, merging the annotated data frame object with a normalized data set, resulting in a complete gene data table. Moderated t-statistics from the empirical Bayes method were used to establish the statistical significance of the analyzed genes. Benjamini and Hochberg’s false discovery rate was used to correct the obtained p-value. The significantly changed genes were selected if they exhibited fold change higher than |2| and p-value < 0.05.BioConductor software  lower than 0.05. The enriched GO terms were subjected to hierarchical clusterization algorithm and presented as heatmaps.DAVID  was used to functionally annotate and cluster the genes that were considered differentially expressed. Up- or down-regulated gene symbols belonging to the compared groups were uploaded to DAVID by “RDAVIDWebService” BioConductor package. For further analysis, we have chosen the enriched GO terms which had at least 5 genes and Subsequently, we analyzed the relationship between the genes belonging to chosen GO terms using the GOplot package . The GOPhttps://string-db.org/). Interaction prediction was performed using the list of gene names as a query. Co-occurrences of genes/proteins in scientific texts (text mining), co-expression and experimentally observed interactions were used as a search criteria. The results of that search yielded a gene/protein interaction network, with the intensity of the edges reflecting the strength of the interaction score. Based on previously uploaded gene sets, STRING also allowed us to conduct functional enrichment of GO terms.Among genes that build chosen GO terms, we have chosen 10 most up and 10 most downregulated. Interactions between chosen differentially expressed genes/proteins belonging to the analyzed gene ontologies were investigated with the use of STRING10  software . This app serves to locate pathways and network patterns that are connected to cancer and other disease types. It allows to conduct pathway enrichment analysis for a specified gene set, visualises found pathways with the use of manually laid-out pathway diagrams, as well as to investigate the functional relations between the genes of those pathways, through accessing the Reactome database. Additionally, it can access a highly reliable, pathway-based, manually curated pathway based protein functional interaction network that covers over 60% of human proteins, the Reactome FI  networks.Finally, the functional interactions between genes that belong to the chosen GO BP terms were investigated by REACTOME FIViz application of the Cytoscape 3.6.0 software  served as an internal standard when measuring the abundance of ID2, VEGFA, BTG2, ESR1, CCND2, EDNRA, ANGPTL4, TGFBR3, GJA1, LAMA2, KIT, TPM1, VCP, GRID2, MEF2C, RPS3A, PLD1, BTG3, CD47, MITF transcripts in the analyzed samples. 2 µL of cDNA solution was mixed with 18 µL of QuantiTect® SYBR® Green PCR  and primers  into cDNA. LightCycler real-time PCR detection system  was used to perform the RQ-PCR reactions. SYBR primers  and usedPBGD and ACTB to quantify genes specific for the oocyte. An additional housekeeping gene, 18S rRNA, was used as an internal standard, to ensure result integrity. Its role was to demonstrate that, in analyzed samples, PBGD and ACTB mRNAs were not differentially expressed. 18S rRNA was previously determined appropriate as a housekeeping gene in quantitative PCR studies.Expression levels of specific oocyte mRNAs were calculated in relation to


Clinical applications of oral protein therapy for the treatment of various chronic diseases are limited due to the harsh conditions encounter the proteins during their journey in the Gastrointestinal Tract. Although nanotechnology forms a platform for the development of oral protein formulations, obtaining physiochemically stable formulations able to deliver active proteins is still challenging because of harsh preparation conditions. This study proposes the use of poly -based polymeric nanocapsules at different monomers’ ratios for protein loading and oral delivery. All formulations had a spherical shape and nano-scale size, and lysozyme encapsulation efficiency reached 80% and significantly affected by monomers’ ratio. Trehalose and physical state of lysozyme had a significant effect on its biological activity (P < 0.05). Less than 10% of the protein was released in simulated gastric fluid, and 73% was the highest recorded accumulative release percentage in simulated intestinal fluid (SIF) over 24 h. The higher caprolactone content, the higher encapsulation efficiency (EE) and the lower SIF release recorded. Therefore, the formulation factors were optimised and the obtained system was PEGylated wisely to attain EE 80%, 81% SIF release within 24 h, and 98% lysozyme biological activity. The optimum formulation was prepared to deliver DNase, and similar attributes were obtained. Although several novel protein delivery approaches have been developed, the parenteral dosage form is still the most common one2. Nanotechnology-based drug delivery systems have the potential to deliver therapeutic proteins orally3. The development of nanocarriers, e.g. liposomes, noisomes, and polymeric nanoparticles was amongst the promising approaches attempted to overcome the obstacles facing oral protein delivery6. Moreover, several studies revealed that nanoparticles have an enormous impact on the oral bioavailability of biologic drugs including therapeutic proteins9. Polymeric nanocapsules (PNCs) comprise a core-shell structure in which proteins are confined and surrounded by a biodegradable polymer11. Nanocapsules system requires less amount of polymer contents to protect the vulnerable drugs12 and has the higher efficiency to encapsulate the drugs due to enhancing drugs solubility in the nanocapsules cavity13. Moreover, the revolution of polymer synthesis technology led to the development of aliphatic polyesters polymers which are biocompatible and biodegradable, therefore, less accumulation in tissues and less immune rejection14.Drug delivery through the oral route of administration is the most common and acceptable systems due to their non-invasive and cost-effective properties. However, it is challenging to deliver the therapeutic proteins orally due to different hurdles; extreme stomach acidity, enzymatic degradation, physiological (permeability) barriers, and physicochemical instabilities of proteins15, hence, reducing the frequency of administration and protecting them from GIT harsh conditions. Various material and process parameters may affect the attributes of nanocapsules, e.g. rate of drug release or the percentage of encapsulation efficiency. Therefore, selecting proper polymers is a crucial step in formulating the nanocapsules; due to their role in the determination of release rate, the biological activity of the encapsulated proteins, and the encapsulation efficiency17. Polylactide (PLA), polycaprolactone (PCL), polyethene glycol (PEG), polyglycolic acid (PGA), their copolymers are the most commonly used biodegradable and biocompatible polymers for drug delivery purposes as they showed the promising results in term of biodistribution19. Despite the high efficiency of PCL and its copolymers to confine the drugs inside them, their release profiles of macromolecules are poor, mainly when the copolymer comprises of PCL and another hydrophobic polyester polymer, e.g. PLA. The low percentage of protein release from PCL NCs is attributed to their innate hydrophobicity and permeability for small molecules but, not for macromolecules, because of the tiny pores on the polymers’ surface20. Encapsulating therapeutic proteins in polymeric nanocapsules is accompanied by several challenges. Denaturation of encapsulating protein is considered the most common drawback of protein loaded polymeric nanocapsules21. This denaturation may be caused by the harsh formulation process parameters and materials, e.g. sonication or the used organic materials23. Insertion of extremolyte sugars showed stabilising effects for the encapsulated proteins against the destabilising conditions; e.g. the biological activity of asparaginase was improved by adding trehalose to the inner protein solution24. However, neither trehalose nor sucrose has any stabilising effect on lysozyme conformational and biological stability26. The failure of extremolytes to protect proteins may be attributed to several factors; their concentrations, the nature of polymers, or the ability of the polymers to confine the protein which may allow the leakage during and after the formulation process. Therefore, obtaining high encapsulated protein stability along with high encapsulation efficiency, high SIF release within the desired time, and protection against the gastric conditions is challenging. Thus, optimising these individual factors is crucial to attaining successful oral formulations.Polymeric nanocapsules are usually used in protein therapy to deliver the therapeutic proteins and improve their pharmacokinetics properties27.To our knowledge, no studies so far have investigated the amount and physical state of trehalose required to prevent the denaturation of encapsulated proteins. Moreover, this is the first report utilises poly  PLC to prepare PNCs intended for oral delivery. A copolymer comprised of lactide and ε-caprolactone was selected for their safety, biocompatibility biodegradability and enhanced pharmacokinetic properties as stated byIn this work, lysozyme/DNase-loaded polymeric nanocapsule formulations were prepared by modified double emulsion/evaporation method. The formulation plan of this study was according to a full design of experiment where the effect of different ratios of PLC monomers, and the quantity of added trehalose on solid and liquid lysozyme on the physicochemical properties of NCs, lysozyme release in SIG and SGF, and the biological activity of lysozyme was investigated. All factors were optimised, and PEGylated optimised formulation containing DNase as a therapeutic protein was prepared and characterised.Lysozyme containing PNCs were formulated using poly  (PLC) at two different ratios (86:14 or 40:60) to encapsulate protein in liquid or solid state with different trehalose concentrations (1 mM and 10 mM). All factors were investigated together in a full factorial design of experiment rather than testing one factor at a time. All formulations were prepared either by S/O/W or W/O/W methods, Fig. Investigation of nanocapsules morphology by TEM revealed round core-shell structure with smooth external surfaces and particles of various size. Some of the agglomerates were also shown in the images with no noticeable difference in the shell thickness was noticed. The presence of the spots at the core of PNCs is supportive of the hypothesis that trehalose is encapsulated inside the polymeric shell. The spotty core was absent in the formulations prepared with 1 mM trehalose, Fig. The hydrodynamic size obtained by dynamic light scattering was in the wide range of 325.3–865.3) nm, particle size distribution curves are provided in the supplementary information. None of the copolymers blocks ratio or the preparation method led to a statistically significant difference in PNC particle size (P > 0.05). However, high trehalose concentration increased PNC diameters 601–865 nm) significantly (P < 0.049), Table –865 nm s5.3–865.3Unencapsulated protein was removed by centrifugation and, then, freeze-dried for 48 hours before finding the percentage of encapsulation efficiency. Protein encapsulation efficiency (EE%) for all formulations was quantified by size exclusion chromatography and described in Table The release of lysozyme from the polymeric Nanocapsules was investigated over 4 and 24 hours in SGF and SIF, respectively Fig. , and the28. Afterwards, the last sustained release phase usually results due to various mechanisms, e.g. particle structures weakening due to plasticising effect, or polymer degradation and subsequent matrix erosion. Also, diffusion out of the polymer due to various causes, e.g. formation of some pores or water channels within polymer shells as medium penetrated the matrix particles may be the drug release mechanism.Lysozyme release occurred via different mechanisms; the initial burst phase may have happened due to the adsorbed proteins at the PNCs surface. The second release phase or the plateau phase has resulted when adsorbed lysozyme on the inner polymer surface had diffused out30, This allows further fluid influx into the inner core of the PNCs and eventually dissolved the protein and helped the PNCs to swell and generate some pores and increased the permeability due to its weakened and plasticised mechanical properties. Consequently, lysozyme started to efflux outside in a sustained manner with time.In this study, the shape of nanocapsules was inspected just after the release by using TEM to figure out any shape changing in the nanocapsules structure. The spherical shape of PNCs was retained after protein release; however, the particle size was increased with some distortion of the particle surface, Fig. Blasi et al.29. Blasi et al.29 stated that; Tg of PLGA had been dropped by incubating in water at two different temperatures, i.e., 23 °C and 30 °C. Moreover, the same study showed that the decline in Tg was 15 °C after 1 hour of incubation irrespective of temperatures used. This depletion in Tg value has resulted in converting the polymer structure from the glassy state into a rubbery state, thus, increased the polymer fluidity, which consequently, may increase the drug release from polymeric drug delivery systems.The explanation was consistent with the study conducted by Statistical analysis revealed that total lysozyme released in SIF was significantly affected by the monomers’ ratio, where (86:14) PLC attained higher drug release over 24 hours.g, thus plasticizes the polymer and increases the permeability. The Poly (L-Lactide) form has 35:65 of crystalline: amorphous, while poly  is entirely amorphous has a Tg value of 57 °C in comparison to pure poly(L-Lactide) (65 °C); which reflects different mechanical properties. Furthermore, forming copolymer can create new molecules with different mechanical properties, which may be able to reduce the rigidity of the polymers as described by31.D, L-lactide is the racemic form of Lactide moiety due to the presence of chiral methyl group in the Lactide. The molecule backing of racemic Lactide forms changed the mechanical properties from being crystalline or semi-crystalline to utterly amorphous form for the copolymer, which subsequently, decreases the polymer consistency. This changing in internal structure decreases Tg (16 °C)32. This depletion in Tg means that the copolymer gets plasticized and become rubbery at temperatures higher than 16 °C (body or release experiment temperature is 37 °C). However, 40:60 PLC has a melting temperature (Tm) of 31 °C32. Hence, mentioning melting temperature rather than glass transition temperature reflects that the polymer mainly consists of dominantly crystalline or semi-crystalline structure33. This means the polymer has more rigid and stable bond backing, thus confining lysozyme inside the polymeric system for a longer time due to slow release. The slow drug release of (40:60) PLC is caused by its slower softening rate when exposed to the dissolution condition at 37 °C when compared to (86:14) PLC.PLC 86%:14% has low T34. Presence of water around lysozyme can cleave amide bonds and thus, denature the protein during the process of preparation35. The rate of chemical reaction of protein in the solid state is minimum due to the internal zero energy which protects the physical and chemical integrity of proteins36. Trehalose stabilises the proteins in solutions by preferential hydration mechanism and reducing the protein mobility which keeps the protein in the folded state38. Moreover, trehalose stabilises proteins by working as a water substitute during the lyophilization process by maintaining proteins’ hydrogen bonds, which eventually reduces the unfolding and protein deactivation39.Encapsulated lysozyme retained 39.69–97.42% of their original activities, Table 40.Trehalose stabilises solid proteins by so-called “Glass Dynamic Hypothesis”. The glass dynamic hypothesis states that trehalose forms rigid and inert solid filler around the proteins, which separates the protein molecules and inhibits any chance of protein motion and collision with other protein molecules. This eventually restricts the proteins unfolding and denaturation42.However, PEGylating time is critical as blending the used polymers with a hydrophilic polymer, e.g. PEG from primary stages may significantly reduce the encapsulation efficiency due to the leakage of protein into the outer aqueous phase during the process of the formulation43. Therefore, PEG 8000 was selected due to its relatively high molecular weight and was added after the preparation and solidification of PNCs and just before the lyophilisation. The quantity of added PEG was optimised by adding different amounts to the formulation, Fig. 25% containing PEG, while 60.02% of lysozyme was released from the same formulation in SGF. Nevertheless, the release of SIF from PEG-PNC15% was 81.06%, but it suits the oral delivery more, as the release in SGF was 21.06%. Lysozyme release from the PEGylated and control (non-PEGylated) formulations was in the diphasic pattern except the release from PEG-PNC25% in SIF where triphasic was observed, Fig. Altogether no formulation appeared to have optimum properties. Therefore, an optimising equation describing the best-fitted model was applied to optimise the factors to find the best-compromised responses. The optimised formulation is predicted to be prepared from 40:60 poly to encapsulate solid lysozyme with 9 mM trehalose to obtain the following predicted responses; 70% EE% and 95% biological activity. However, release profile was predicted to stay low (36.5%) over 24 hrs even after optimisation; this is expected as high content PCL-NCs showed slow release kinetics. Several approaches could increase the release; however, not all of them are suitable for the other physicochemical properties. PEGylation is one of the most commonly used approaches in the preparation of polymeric nanocapsules due to its biocompatible nature and its ability to enhance drug release20. PEG8000 may have increased the already existing pores by improving the permeability. However, increasing the quantity of PEG8000 to 50% w/w decreased the release percentage, and even less than the control formulations. After finding out the PEGylated PNCs morphology by TEM, a shield of PEG was formed around the particles which may hinder the release significantly, Fig. Enhancing the systems’ release was caused by PNCs interaction with PEG which softened the polymer by increasing the water content it. Caprolactone is permeable to small molecules but, not macromolecules like protein because of the tiny pores on its surfaceTwo PNCs optimised PEGylated formulations (15% PEG8000) were prepared and characterised for encapsulation efficiency, drug release and biological activity. The obtained results were close to the predicted ones, where %EE 74.6%, 97% biological activity, and 82.15% SIF release were obtained.15% was prepared to deliver deoxyribonuclease I (DNase I) and then characterised. DNase is a therapeutic protein being used for the treatment of cystic fibrosis. The biological activity of encapsulated DNase I exceeded 95%, which reflects the ability of DNase to withstand during the process procedures. Interestingly, the %EE, release profile in SIF, and release profile in SGF are comparable to those obtained from encapsulating lysozyme into PNCs at the same optimum conditions. The developed PNCs may present an excellent model for developing future polymeric nanocapsules containing other macromolecules, e.g. therapeutic proteins, monoclonal antibodies, and genes.Lysozyme was used as a model protein throughout the study. After optimising the factors and PEGylating the optimum formulation, PEG-PNCsThis is the first report on the investigation of trehalose quantity role in protecting proteins during the polymeric nanoencapsulation processes. Moreover, poly  was utilised to prepare the PNCs for oral delivery, which also has never been studied before for oral delivery. Design of experiment was built to examine the effect of material attributes and optimise them to obtain PNCs with the desired %EE, release kinetics, particle size, and biological activity of proteins. The optimised formulation was capable of (i) retaining the high biological activity of encapsulated proteins, (ii) releasing high percentage of active proteins in SIF, (iii) obtaining a high percentage of encapsulation efficiency, and (iv) protecting the protein from degradation in gastric fluids. Herein, this data suggests that the biological activity of the protein was increased from 39% to 97% when the amount of trehalose used was increased from 1 mM to 10 mM. Also, high PCL content-copolymer could confine high percentage of protein. However, the extended release was observed. Therefore, high PCL-content PNCs was used to prepare the optimised formulation with using PEG as a release enhancer. PEGylated PLC-NCs confined more than 80% of the used protein and released 80% of the encapsulated protein in SIF. PEGylated PLC-NCs could be a promising nanocarrier system for oral delivery of therapeutic proteins. Lysozyme was used as a model protein throughout the study, in addition, PNCs containing DNase, as a therapeutic protein, were prepared at the optimised conditions.60®, DNA, Micrococcus lysodeikticus, pepsin, Poly  (40:60), Poly  (86:14), polyethylene glycol 8000 (PEG 8000), and hydrochloric acid were purchased from Sigma–Aldrich Co. . Trehalose dihydrate was purchased from VWR Co., . Electrochemical analysis grade acetonitrile was purchased from Fischer Scientific, . Nano pure water  was obtained from a Diamond Lab Water System .Lysozyme  obtained from chicken egg white, was provided by Sigma-Aldrich. Deoxy Ribonuclease I  obtained from bovine pancreas, was provided by Sigma-Aldrich. Ethyl acetate, polyvinyl alcohol PVA, Span3). The effect of the factors on the desired criteria (responses) was assessed by the preparation of formulations in triplicate and then characterise them in the light of the suggested qualities to screen the significance of each factor thus optimise them by utilising multilinear regression (MLR), Equation The design of experiment was selected to connect the overall quantitative data in the experiment in a lucid way. Therefore, the full experimental design was generated combining three factors each one has two levels to form eight different possibilities  was utilised for statistical analysis.44. However, some formulations were developed by solid in oil in water S/O/W. Briefly, the w1 phase consisting of protein and trehalose dissolved in ultra-pure water (>Ω18) was dispersed into the ethyl acetate containing 1.67% w/v copolymer and 6% Span60 by probe sonication. Then, W/O emulsion was added to 50 ml of 3% PVA/water to prepare the secondary emulsion by probe sonication. Afterwards, the double emulsion was stirred overnight at the room temperature to evaporate the organic solvent and solidify the nanocapsules. The residues of organic solvent and free proteins were removed by centrifuging and washing the nanocapsules for times for 30 minutes at 15000 rpm and 4 °C before the lyophilization for 48 hours.Polymeric nanocapsule formulations were prepared by the double emulsion solvent evaporation method via preparing water in oil in water (W/O/W) emulsion as described byFor the S/O/W preparations, the protein and trehalose were directly suspended in the organic phase and sonicated to prepare the finely dispersed S/O suspension. Then, all the remaining steps same as W/O/W preparation method.45. The polymeric shells were broken by suspending and stirring the nanocapsules in ethyl acetate under fume cupboard for 2 hours. Then, it was centrifuged 2 times for 10 minutes at 10000 rpm; the pellets were collected and left under the fume cupboard for half an hour to dry and then suspended in water and stirred for 2 hours until all the protein is dissolved. The suspension was centrifuged at 10000 rpm for 10 min, and then the supernatant was analysed, by using SEC, to determine the protein concentration in the sample.Encapsulation efficiencies of the different formulations were measured by applying the previously developed method® dynamic light scattering was utilised to determine the nanocapsules containing proteins particle size. Samples were prepared by suspending 10 mg of the freeze-dried nanocapsules in 5 ml water. Afterwards, the resulting suspensions were mixed in the vortex for 1 minute and then were left in water bath sonicator for 5 minutes. Nanocapsule diameters were measured in triplicate at 25 °C.Zeta PALSThe morphology of PNCs was investigated by TEM. The technique was applied by using negative staining technique 1% (w/v) of sodium silicotungstate solution. A drop of PNCs suspension was applied on a 400 mesh Formvar copper grid on paraffin, and the sample was adhered on the Formvar at room temperature for 15 minutes, then, a drop of 1% (w/v) of sodium silicotungstate solution was applied for 5 minutes. The obtained specimen was later observed under the TEM.Protein release from the nanocapsules was determined in simulation gastric fluids (SGF) and simulated intestinal fluid (SIF) for 4 and 24 hours, respectively. Both SIF and SGF were prepared as per British Pharmacopeia 2014. However, no digestive enzymes were added.Powder nanocapsules containing 1.5 mg entrapped protein, calculated based on relevant encapsulation efficiency, were suspended in 30 ml SIF (pH 6.8), and in SGF (pH 1.2), then this volume was divided into 10 screw cap Eppendorfs, each contains 2 ml (100 μg protein). The vials were incubated in a shaker water bath under shaking rate of 50 cycles/minute at 37 °C, and one vial was collected at each time point. All release tests were performed in triplicate.Eppendorf vials were taken, and the samples centrifuged 2 times at 10000 rpm for 10 minutes, the pellets were collected, and the shells were broken down. Then the remaining unreleased proteins were collected. Protein release was determined by quantification of protein amount remaining in pellets by using SEC after pellets disruption and subtracting the remaining from the original value (100 μg) to find out release percentage.46. The biological activity of DNase I in this study was detected by applying the enzymatic assay procedures established by Kunitz 195047. The rate of the cleaving of phosphodiester linkage of DNA is considered as a function of DNAse I activity48.The effect of the used reagents including polymers and encapsulation process on protein biological activities was examined in this study. PNCs shell was disrupted by adding ethyl acetate, and the biological activity of the encapsulated lysozyme was determined by its ability to lysis the bacterial cell wall. The calculation was performed by recording ΔA450 for the bacterial-lysozyme suspension over 5 minutes, as described previously bySupplementary Information


Il-1β, Il-6, TGF-β, and Il-10, and the enzyme myeloperoxidase as a neutrophil marker. The group that received the personalized probiotic showed reduced susceptibility to DSS-colitis as compared to a commercial probiotic. This protection was characterized by a lower disease activity index and reduced histopathological damage in the colon. Moreover, the personalized probiotic was more effective in modulating the host immune response, leading to decreased Il-1β and Il-6 and increased TGF-β and Il-10 expression. In conclusion, our study suggests that personalized probiotics may possess an advantage over commercial probiotics in treating dysbiotic-related conditions, possibly because they are derived directly from the host’s own microbiota.Modulation of the gut microbiota through the use of probiotics has been widely used to treat or prevent several intestinal diseases. However, inconsistent results have compromised the efficacy of this approach, especially in severe conditions such as inflammatory bowel disease (IBD). The purpose of our study was to develop a personalized probiotic strategy and assess its efficacy in a murine model of intestinal inflammation. Commensal bacterial strains were isolated from the feces of healthy mice and then administered back to the host as a personalized treatment in dextran sodium sulfate (DSS)-induced colitis. Colonic tissues were collected for histological analysis and to investigate inflammatory markers such as  At birth, the human gastrointestinal (GI) tract becomes colonized by a complex ecological community of microorganisms, referred to as the “gut microbiota” ,2. Most Proteobacteria phylum [The term “microbial dysbiosis” is still poorly defined, as there is much uncertainty regarding what constitutes a ‘healthy’ microbiota. Previous studies in the GI tract have claimed that a dysbiotic condition is usually characterized by a reduced diversity of microbes often in combination with a lower abundance of obligate anaerobic bacteria and an expansion of facultative anaerobic bacteria, particularly from the a phylum ,17,18,19IBDs, including Crohn’s disease (CD) and ulcerative colitis (UC) are chronic relapsing diseases characterized by intestinal inflammation and microbial dysbiosis. Besides genetics, environmental factors, such as diet and the gut microbial community, appear to be involved in IBD development. These modifiable factors have gained more attention over the last few decades since IBD incidence has increased significantly in developing countries that have recently transitioned to a more ‘Western’ diet style and lifestyle . One of Despite the beneficial effects of probiotics seen in different conditions , as well as to commercial probiotics available on the market, because they are adapted to the host microbiota and would (in theory) simply restore a healthy vaginal microbiota.Based on our understanding of how an individual’s genetics influences their physiology, a new concept termed “personalized” or “precision” medicine has emerged focusing on diagnostics and treatments that favor the specific characteristics of the host, thus avoiding the “one size fits all” approach, that has often proven ineffective . A persothe host . The met formula . This meTaken together, the aim of the current study was to introduce the concept of a personalized probiotic therapy for intestinal diseases, where commensal bacteria isolated from the gut microbiota of healthy hosts could be stored in a ‘microbiota biobank’ after having their intrinsic characteristics tested, and ultimately used as a therapy for dysbiosis-related diseases.Male C57BL/6 mice were purchased from CEMIB , kept in sterilized, filter-topped cages, and fed autoclaved food  and water ad libitum under specific-pathogen-free conditions at the Sao Paulo State University. Findings in Brazil were repeated with C57BL/6 mice bred in house at the British Columbia Children’s Hospital Research Institute (BCCHRI), Vancouver, BC, Canada. Sentinel animals were routinely tested for common pathogens at both facilities. The protocols employed were approved by the Sao Paulo State University (34/2014) and by the University of British Columbia’s Animal Care Committee (A15-0206), and were in direct accordance with guidelines provided by the Brazilian College of Animal Experimentation and by the Canadian Council on the Use of Laboratory Animals.n = 10). In brief, fresh stool pellets were homogenized in 1.0 mL phosphate buffered saline (pH 7.2), plated on Man Rogosa Sharpe agar  and Bifidobacterium iodoacetate medium 25 agar  for Lactobacillus spp. and Bifidobacterium spp. selection, respectively. The plates were incubated under anaerobic conditions at 37 °C for 48 h to 72 h. Five colonies with distinct morphologies were selected from Lactobacillus spp. and Bifidobacterium spp. genera from each mouse sample. The selected colonies were further purified by streak plating in the same media. The isolated colonies were transferred to MRS broth (Lactobacillus spp.) or MRS broth with the addition of 0.5% L-cysteine  (Bifidobacterium spp.), and then incubated under anaerobic conditions at 37 °C for 48 h to obtain a liquid culture of each individual isolate.Several commensal bacteria strains were isolated from the stool of healthy C57BL/6 mice (2O2). A positive result for catalase was confirmed with the rapid evolution of oxygen (5–10 s) as evidenced by bubbling [The isolated colonies were stained using Gram’s method  and thenbubbling .Lactobacillus spp. (Lab-0159: 5′- GGA AAC AG (A/G) TGC TAA TAC CG-3′; Lab-0677: 5′- CAC CGC TAC ACA TGG AG -3′) [Bifidobacterium spp.  [2, 0.2 mM of each deoxynucleotide, 1 μM of each primer, 2 ng of genomic DNA and 2U of Taq DNA polymerase enzyme, in a final volume of 25 μL. All reactions were assembled in duplicate and the amplification was carried out using a Veriti Thermo Cycler  under the following conditions: initial denaturation at 94 °C for 10 min, followed by 35 cycles at 94 °C for 20 s, 55 °C for 20 s, 72 °C for 30 s and then a final extension at 72 °C for 5 min. Distinct species of Lactobacillus spp. and Bifidobacterium spp. were identified by analyzing the PCR products through agarose gel electrophoresis  using a 100 bp ladder  as a molecular size marker. The gels were stained with SYBR Safe  and the images acquired under UV illumination using a Gel Doc XR System . The similarity of the RAPD profiles was compared within the isolates to distinguish possible different species, while commercially-purchased strains of Lactobacillus spp. and Bifidobacterium spp. were used as controls.All selected strains underwent a combination of colony-PCR and randomly-amplified polymorphic DNA–polymerase chain reaction (RAPD-PCR) to confirm the target genera and as a preliminary form of species identification. In brief, single colonies from each isolated strain were used directly as the template, without any DNA extraction and purification prior to PCR. Next, a set of two short arbitrary (10 bp) primers was used in the PCR reaction:  AG -3′) , BifidobA C -3′) . The RAP8 CFU/mL) were added to an acid solution , and 0.9 mg/L of lipase from porcine pancreas  to reach a pH of 2.4. Samples were incubated at 37 °C (150 rpm)  for 2 h, leading to the simulated gastric phase. Next, the pH was increased to 5.0 using an alkaline solution  and biliary salts  and porcine pancreatin  were added to reach a concentration of 10 g/L and 1 g/L, respectively. Samples were incubated again at 37 °C for 2 h under agitation (150 rpm), leading to the simulated enteric phase 1. Finally, the pH was increased to 7.0 using the same alkaline solution. Biliary salts and pancreatin were adjusted to maintain their concentrations at 10 g/L and 1 g/L, respectively, and the samples were incubated again at 37 °C for 2 h under agitation, leading to the simulated enteric phase 2, thus completing the 6 h of assay. Enumeration of Lactobacillus spp. and Bifidobacterium spp. was performed in aliquots collected in duplicate after 2 h, 4 h, and 6 h. Aliquots of 1 mL were pour-plated in MRS or BIM-25 for colony forming unites (CFU) of Lactobacillus spp. and Bifidobacterium spp., respectively.The gastrointestinal resistance of the isolated strains was tested according to the approach of Liresse and colleagues  and Buri8 CFU/mL). Five antibiotic disks were placed in MRS or BIM-25 agar plates containing 100 µL of each bacterial culture, and the plates were incubated under anaerobic conditions at 37 °C for 16 h to 18 h. The tests were conducted in duplicate, and the plates were not inverted during the incubation period. The zone diameter around each disk was measured as the inhibited bacterial growth areas, and the strains were categorized as sensitive (≥20 mm), intermediate (15–19 mm), or resistant (≤14 mm), according to criteria established by the Clinical and Laboratory Standards Institute [Each isolated strain was tested for its susceptibility against ten different antibiotics  using the disk diffusion assay ,44. Fresnstitute . See FigLactobacillus rhamonosus GG (LGG), which was used as a comparison based on its wide application in gastrointestinal disorders [n = 10) as described in The bacterial isolates were tested in the DSS-induced colitis model to assess their potential to protect mice against colitis, and thus, to function as a potential probiotic. Male 8-week-old C57BL/6 mice were provided with either the personalized combination of probiotics (PP) or the commercially obtained probiotic isorders ,46. Heal9 CFU) starting seven days prior to DSS, as well as throughout the course of the DSS exposure  (w/v). Animals were treated with DSS for seven days and then euthanized by cervical dislocation following prior anesthesia with isoflurane. Over the course of the experiment, mice were weighed daily and monitored for any signs of distress. During the DSS treatment, the severity of the colitis was determined daily using the disease activity index (DAI), which takes into account three parameters: weight loss, stool consistency, and occult bleeding in the feces, as tested using the commercial Hemoccult kit .After the isolates were selected and characterized, three strains were chosen based on their distinct species profiles obtained by RAPD-PCR. These isolates were grown separately in their specific media under the conditions described in s total) . AnimalsAfter euthanasia, mouse colonic tissues were collected for histological analysis. Colon tissues were opened longitudinally, stool was gently removed, and distal colon sections were placed in histological cassettes. The cassettes were immediately placed in 10% neutral buffered formalin   for histological processing.Colonic pathology was scored using a previously-adapted scoring system . In brieTbp (reference gene)  [Tbp as a reference gene [Following euthanization of the mice, distal colonic tissues were immediately placed in RNA-later  and stored at −80 °C. Total RNA was extracted using the Qiagen RNeasy Mini Kit according to manufacture’s instructions, and then quantified using a Nanodrop spectrophotometer . Complementary DNA (cDNA) was synthesized using 1 μg of RNA with Omniscript RT kit , followed by quantitative real-time PCR techniques. The qPCR reaction had a final volume of 20 μL, where 5 μL of cDNA was added to 15 μL of a PCR mix containing 10 μL of BioRad SsoFast EvaGreen and 5 μL of RNase- and DNase-free water and primers to a final concentration of 0.6 μM. Primer sequences and annealing temperatures were as follows: IL-10  ; TGF-β (g 59 °C) . qPCR wance gene , and wasnce gene .Colonic tissue homogenates were used to measure MPO and MDA activity. MPO activity was measured using a colorimetric activity assay kit . In brief, the tissues were homogenized in the buffer solution provided with the kit, and the assay was performed according to the manufacturer’s instructions. Colorimetric change was measured on a microplate reader  using 412 nm absorbance, and the results were used to calculate the MPO concentration in each sample as per the manufacturer’s instructions. Similarly, the lipid peroxidation in colonic tissue was investigated using a commercial kit  that assesses MDA levels though a method dependent on thiobarbituric acid (TBA). The assay was performed according to the manufacturer’s protocol where TBA was added to the homogenate supernatant, and the samples were boiled for 60 min at 95 °C before the absorbance was assessed at 532 nm using a spectrophotometer .p < 0.05.All results presented in this study are expressed as the mean value ± Standard Deviation (SD). Statistical analysis was performed using the GraphPad Prism Software Version 7.0 . One-way analysis of variance (ANOVA) and Tukey’s or Dunnett’s multiple-comparison test were used to analyze the results. Significance was declared when Lactobacillus spp. and Bifidobacterium spp. characteristics [Lactobacillus spp. and 50% were Bifidobacterium spp. All samples presented typical colony morphologies of these two genera, confirming that they were part of the murine gut microbiome as described in previous studies [Bifidobacterium spp. and only one profile for Lactobacillus spp. The similar species profile found for these mice likely reflects their inbred nature and their co-housing, resulting in similar gut microbiota. Based on the profiles found in the agarose gel, three different bacterial strains per mouse (two Bifidobacterium spp. and one Lactobacillus spp.) were chosen to proceed for further analysis, totaling 30 host-selected strains (n = 10). In summary, a personalized combination of three different commensal bacteria was prepared for each mouse after growing the strains separately in their specific media and conditions.From the different stool samples of each mouse plated either in MRS or BIM-25 media, colonies displaying typical eristics ,53 were  studies . Figure 10 CFU/mL in their population. Moreover, all strains maintained their population above 8 log10 CFU/mL after the incubation period in the gastric and intestinal simulated solutions.Prior to testing the effects of the strains isolated ex vivo, we first sought to verify their probiotic potential using established in vitro tests such as their resistance to adverse gastrointestinal conditions , and their antibiotic susceptibility. All the 30 selected strains in the previous analysis were classified as Gram-positive bacteria and catalase-negative, confirming the usual characteristics of both target bacteria genera. Furthermore, we observed that all strains showed high tolerance to the adverse conditions of the in vitro test . More spTen antibiotics from different classes and with diverse mechanisms of action were tested to assure the safety of the commensals isolated from the mice, thus guaranteeing they could be eliminated by antibiotic use if necessary. The antibiotic susceptibility of each strain is presented in 10CFU throughout the experimental protocols . This model was chosen for its wide application in testing new probiotic strains for use in the GI tract ,55,56. Frotocols . The weeectively .Mice were given equal quantities of either LGG, the PP, or sterile water via oral gavage 7 days prior to being challenged with 3% DSS in their drinking water, and then every day thereafter until they were euthanized at day 7. As expected, DSS-colitic mice given just water lost significant levels of weight (15%), whereas mice treated with LGG or PP lost much less weight (5%) during DSS exposure. Notably, PP mice showed a significantly lower disease activity index (DAI) as compared to healthy controls, beginning at the 5th day of DSS challenge and lasting until the mice were euthanized, indicating a better outcome with PP regarding the parameters of stool consistency and blood in the stool . Besidesp < 0.05; n = 10 per group)   developed severe mucosal damage in their distal colons, characterized by the widespread loss of crypts, severe ulceration, and infiltration of inflammatory cells . In contr group) . Mice thr group) . Taken tIl-1β and Il-6), as well as the anti-inflammatory cytokines (Il-10 and TGF-β) after seven days of DSS-colitis. All results are expressed as the fold-change over the gene expression in the control group. As expected, the transcript levels of Il-6 and Il-1β were higher in the DSS-vehicle treated group, confirming the more severe inflammation found through histological analysis. Moreover, both groups treated with probiotics showed evidence of attenuated inflammation, as their tissues showed lower transcript levels of Il-6 and Il-1β and higher levels of Il-10 and TGF-β as compared to vehicle treated mice. However, the most striking result from data in p < 0.05).The transcription of different cytokines was investigated to evaluate if the personalized probiotic therapy was more effective in suppressing inflammatory responses, thereby contributing to tissue homeostasis. The cytokine mRNA levels were measured in the distal colon since the histological damage was limited to this tissue area in all groups. p < 0.05). Regarding MDA levels in colonic tissues, there was no significant different within the groups, indicating that neither probiotic tested influenced this byproduct of oxidative stress.Enterobacteriaceae and a depletion of Firmicutes bacteria, which curiously are the typical features of the microbial dysbiosis observed in IBD patients [At present, it remains unclear if the microbial dysbiosis seen in IBD patients plays a role in their disease pathogenesis, or if it is simply secondary to the inflammation that develops in these conditions. A potential causative role for dysbiosis is supported by studies showing that spontaneous mouse models of IBD often show no disease development when the mice are raised under germ-free conditions. Moreover, the predominant inflamed sites in IBD patients are also the sites that hold the highest abundance of microbes in the intestine . In this case, IBD could be explained as an impaired immune response to gut microbes in genetically-predisposed individuals. However, an inflammatory environment itself seems to favor an expansion of patients .Although the microbiota imbalance seen in the stool of IBD patients has yet to be defined as either the cause or a consequence in IBD, it almost certainly plays a role in these conditions, as IBD patients usually show a significant decrease in commensal bacteria diversity. A healthy and diverse microbiota is important for several intestinal physiological processes, such as protection against pathogens and pathobionts, food digestion, and vitamin biosynthesis, as well as the production of key metabolites and anti-inflammatory mediators such as transforming growth factor-β (TGF-β), retinoic acid, and thymic stromal lymphopoietin (TSLP) . ImportaOur work demonstrates that a personalized probiotic therapy can protect mice against DSS-induced colitis to a greater extent than that seen with the commercial probiotic LGG, and this better outcome—if replicated in clinical studies—could make a tremendous difference to the treatment of severe diseases such as IBD, IBS, type 2 diabetes, among others. Although probiotic bacteria are thought to benefit hosts through several mechanisms of actions, the ability to persistently colonize the gut may be critical for the ability of probiotics to effectively treat dysbiosis-related diseases. Because the human microbiome is a complex and dynamic ecosystem, and dysbiosis is linked to diverse diseases, we believe that beneficial bacteria need to be present in the gut for an extended period, or preferably in a permanent way, to avoid the bacterial imbalance that triggers dysbiosis. However, the majority of commercially available probiotics appear unable to accomplish this task. Recent findings outline that a combination of 11 probiotic strains (Superherb Bio-25) varies considerably in their ability to colonize the human gut, depending on the host’s indigenous microbiome, as well as on host factors and site-specific immune responses , thus hiLactobacillus spp. and Bifidobacterium spp. to be administered prior to—and during DSS challenge. However, the exact identification of each particular strain was not the focus of our study, since our current aim was to develop a personalized approach for probiotic administration focusing on the healthy microbiota composition prior to inflammation, rather than isolating particular strains to be commercialized for general health benefits. The results from this part of the study indicated that three commensals (two of Bifidobacterium spp. and one of Lactobacillus spp.) isolated from each animal in the PP group had the potential to be used as probiotic microorganisms, as they were able to survive in adverse conditions, and therefore, they were administered to the donor animal in the second part of the study .In our study, we first confirmed that the selected strains isolated from each individual mouse could be considered potentially probiotic due to their performance in preliminary screens using in vitro tests. RAPD-PCR is a practical method that provides both sensitive and rapid results. For this reason, it has been widely used in the differentiation of lactic acid bacteria ,59,60,61Lactobacillus spp. are usually susceptible to β-lactam antibiotics , protein synthesis inhibitors , and more resistant to vancomycin (extrinsic resistance). Strains from Bifidobacterium spp. are usually intrinsically resistant to mupirocin (an antibiotic used in selective media for Bifidobacterium spp.) and high concentrations of aminoglycosides. On the other hand, they are sensitive to macrolides , chloramphenicol, β-lactams, vancomycin, streptomycin, and rifampicin [High survival rates during gastrointestinal transit is one of the key requirements to classify a commensal microbe as a potential probiotic bacterium ,62, as tfampicin ,65. All fampicin .In the second part of this study, we compared the ability of the PP isolated from the host against the ability of the commercial probiotic LGG to reduce the inflammatory characteristics of DSS-induced colitis. The DSS-colitis model is one of the most widely-used mouse models of intestinal inflammation due its simplicity, reproducibility, and controllability . DSS is Il-1β and Il-6 in the colons of treated mice, which were accompanied by increased anti-inflammatory cytokine expression (Il-10 and TGF-β). Interestingly, the personalized probiotic group showed a more effective immune modulation as compared to the commercial probiotic LGG, suggesting that resident microbes of the gut may yield stronger anti-inflammatory effects since they already possess a mutualistic anti-inflammatory relationship with the host’s immune system.Under homeostatic conditions, the intestinal mucosa is able to maintain the balance between pro-inflammatory and anti-inflammatory cytokines. However, IBD patients often display increased intestinal permeability and impaired epithelial barrier function ,68,69,70Certain biochemical markers, such as myeloperoxidase (MPO) and malonaldehyde (MDA) activity, have also been investigated in IBD and in animal models of intestinal inflammation as parameters of intestinal damage. MPO is commonly used as a neutrophil marker, while MDA has been studied as a oxidative stress marker associated with the pathogenesis of IBD ,77,78. ABased on our results, commensal bacteria isolated from the host microbiota were more effective at preventing the symptoms and pathological changes seen in the DSS-colitis model. The improved efficacy of the personalized treatment in comparison with the commercial probiotic LGG suggests the benefits of using microorganisms that are already incorporated into the host microbiota to reduce the typical dysbiosis seen in DSS treatment, as well as other forms of colitis, since the personalized strategy is based on the maintenance of the initial healthy microbiota by constantly replenishing the host with these beneficial microbes. We believe that administration of these personalized probiotics has the potential to treat dysbiotic-related and multifactorial diseases based mainly on maintaining the quantitative balance of beneficial versus pathobiont and/pathogenic microbes. Moreover, we recognize that commercial probiotics, as well as novel engineered bacteria expressing specific transgenes, could prove effective in diseases where the etiology and the mechanisms of disease are better elucidated. In additional, specific populations  and their particular needs would also benefit from designed probiotics aiming at a specific beneficial effect.The current evidence supporting personalized therapies are more focused on strategies to treat specific groups of subjects and avoid the generalist approach considered outdated for many disease treatments. Although we recognize the importance of developing novel probiotics for specific populations, we believe that certain diseases linked to microbial dysbiosis could benefit more from the use of personalized probiotics, which we have named “autoprobiotics”. The novelty of our approach includes not only selecting strains from the host in a personalized way, but also by selecting these strains before disease begins, or alternatively, in the remission phase in the case of IBD. As described in In summary, these results show that personalized probiotics are a potent and promising approach to healthcare, and as such, may protect against dysbiosis-related symptoms during clinical disease. However, considering the novelty of the proposal, it is clear that additional studies need to be performed using different models of intestinal and extra-intestinal diseases, as well as different comparisons made with commercially available probiotics, before these personalized probiotics are ultimately tested in clinical trials. We emphasize that this strategy has the potential to assist in the treatment of several diseases associated with microbial dysbiosis.