To prevent the settlement and/or the growth of fouling organisms , benthic sessile species have developed various defense mechanisms among which the production of chemical molecules. While studies have mostly focused on the release of chemical compounds by single species, there exist limited data on multi-species assemblages. We used an integrative approach to explore the potential interactive effects of distinct assemblages of two corals species and one giant clam species on biofouling appearance and composition. Remarkably, we found distinct biofouling communities suggesting the importance of benthic sessile assemblages in biofouling control. Moreover, the assemblage of 3 species led to an inhibition of biofouling, likely through a complex of secondary metabolites. Our results highlight that through their different effect on their near environment, species assemblages might be of upmost importance for their survival and therefore, should now be taken into account for sustainable management of coral reefs. Each of these interactions can be either positive or negative and are responsible to a large extent for structuring communities2. Most studies on bioactive products have focused on the competition and defense processes that may lead to the discovery and commercialization of new bioactive metabolites3.Benthic sessile communities are under direct and constant pressure of their surrounding environment. Therefore, many species have developed various mechanisms such as direct and indirect biotic interactions to maximize their survival4), saponins (e.g. muricins5), macrolides (e.g. latrunculins6), and steroids (e.g. verumbsteroids7) that can reduce the growth or even lead to the death of neighboring species. The production of such secondary metabolites, mainly non-polar, synthesized constitutively or inducible8, strongly influences sessile organisms’ behaviors in response to local competition or predation pressures. The latter are particularly pervasive in marine biofouling environments where strong developmental and organism-environment interactions take place9.In sessile coral reef organisms, numerous studies have identified a wide variety of secondary metabolites such as terpenoids , fungi and protists, which are all precursors for colonization by larger fouling organisms or macrofouling9.Biofouling is an ubiquitous phenomenon in the marine environment and a common feature of a wide variety of natural and artificial structures13. The external environment plays an important role in the biofouling formation, in particular through physical and chemical conditions15. For example, the availability of nutrients will play a critical role in the selection of early colonizers and the successive community composition of the biofouling16. Light and temperature increase also play important roles in enhancing the propagation of biofilm and biofouling18. Besides these environmental factors, many antifouling agents have been characterized from sessile marine organisms, in particular antifouling molecules produced by sponges, soft corals, and seaweeds20. Microorganisms associated with marine algae and invertebrates, such as epibionts, also possess antifouling potential12. Despite the growing knowledge that biofouling-associated antifouling compounds are damaging to both larval and adult stages of hard corals and giant clams23, there exist very limited data on the actual processes and the specific molecules involved in antifouling activities of multiple interactive coral reef species. There is now growing evidence that hard corals release antifouling active substances3, which can confer different competitive abilities to coral species against algae24.Biofouling formation onto a substrate, its growth rate and the type of species able to colonize this habitat are modulated by various interactions and involve complex biochemical, behavioral or physical mechanisms25. In coral reef ecosystems, the variety of antifouling compounds produced by sessile organisms, even among coral genera, prompted us to study the importance of species biodiversity and interaction on coral reefs’ fitness. Our work investigated their potential cumulative effect on biofouling formation and their ability to minimize the dramatic impact that uncontrolled biofouling expansions  may have on coral reef ecosystems.Studies on Antarctic marine benthos have shown that by bringing together different defense strategies, mainly regulated by chemical interactions such as deterrent or repellent molecules, species assemblages create a complex model of interaction which may help protect Antarctic organisms from competition, for space and fouling pressure notablyPocillopora damicornis and Acropora cytherea, and the giant clam Tridacna maxima were artificially grouped in distinct assemblages, exposed to varying water temperatures, and their influence on algal biofouling formation was investigated.Thus, in this study we combined cytological, metagenomic and metabolomic approaches to explore the interactive effects of multiple benthic species assemblages on the biofouling appearance and composition under normal and thermal stress conditions. Two common Indo-Pacific scleractinian coral species, Acropora cytherea (n = 4) and Pocillopora damicornis (n = 4) colonies were collected at low tide (∼2 m) in Moorea lagoon, French Polynesia . The sampled colonies were then cut into nubbins using side-cutting pliers to produce a minimum of 45 small fragments each. All the samples were grown on tables in a common garden located in the lagoon area of the InterContinental Moorea Resort & Spa during an 8 months period. The giant clams T. maxima were purchased at a French Polynesian distributor on Reao Island , and then acclimated in the common garden. The three species were placed on 3 different distant (>3 m) tables in order to avoid inter-species’ interactions. A CITES permit was obtained to allow for samples export (CITES – FR1698700087 – E).P. damicornis + A. cytherea + T. maxima (PAT); P. damicornis + A. cytherea (PA); A. cytherea + T. maxima (AT); P. damicornis (P) or T. maxima (T) alone. Three nubbins from 4 coral colonies per species  and/or 12 giant clams were used for each assemblage. Therefore, the 40 L aquariums were composed of either 12 (assemblages T and P) or 24 (assemblages PA and AT) or 36 (assemblages PAT) organisms , spaced two weeks apart, except for the AT assemblage which was also studied in duplicate but during the same experiment (exp. C). In each of A and B experiments, 4 distinct assemblages were studied in parallel . After an acclimation period of 12 days, for each set of assemblage, one of the two aquariums was maintained at the ambient lagoon temperature , and the second one was submitted to a stress temperature (ST). The stress temperature was performed as follows: increased 1 °C per day from day 12 to day 17 up to 32 °C where it was maintained for 3 days (from day 17 to day 19), before being decreased back to 27 °C (day 20). Similarly, in experiment C, after the acclimation period, two aquariums of AT assemblages were placed at lagoon temperature and the remaining two were exposed to the stress temperature (n = 4 aquariums).2−), nitrate (NO3−), phosphate (PO42−), ammonium (NH4+) and silicate . We chose to analyze samples from day 12 (T0) during the experiments A, B and C; samples from day 17 (T1) during experiment B and from day 19 (T2) samples during experiment B and C. A synthesis of the tested samples as well as the statistics used are on Supplementary S1b and S1c.During the experiments, biofilm deposited on each aquarium wall was scraped at day 12 and 20 using a cover glass slide, and stored in 70% ethanol at −20 °C until further DNA analysis. Three replicates of water samples (40 mL) from aquariums were sampled at the same time and kept at −20 °C until the analysis of nitrite  and daily observations of the biofouling were recorded.At beginning of each experimental run, two sterile microscope cover glasses and two sterile glass slides were placed in each aquarium. At the end of the experiment, the slides were observed in order to identify the most predominant genera per assemblage  and Bakt_805 reverse (5′-GACTACHVGGGTATCTAATCC- 3′) primers28. The 18S ribosomal RNA V4 region was amplified with the primer pair D512for18S forward (5′-ATTCCAGCTCCAATAGCG-3′) and the D978rev18S reverse (5′-GACTACGATGGTATCTAATC-3′), specifically designed for characterizing diatom communities29. The primers were modified to include IlluminaTM overhang adaptors as described by Kozich et al.30.Biofilm DNAs were extracted using the CTAB-based protocol described in Rouzé Ciona savignyi and Asterias amurensis) from a previous study31, were used as internal quality controls. Nuclease-free UltraPure™ water  was used as negative control. The samples were sent to New Zealand Genomics Limited at the University of Auckland for final high-throughput sequencing library preparation. Libraries were sequenced on a MiSeq Illumina™ platform using a 2 × 250 base-pair (bp) paired-end protocol.The polymerase chain reactions were performed (Supplementary Seawater samples from input pipes (n = 5) were collected through a tap placed before the aquariums, and seawater samples from aquariums (n = 23) were individually siphoned and filtered using cartridges Strata-XL 100 u polymeric reversed phase . Six liters of seawater per sample were filtered using an extraction chamber.Samples were extracted from the Strata-XL cartridges and then centrifuged to separate the residual water. The organic phase was transferred in a glass hemolysis tube before drying under nitrogen flow and freeze-dried overnight. Before LC-MS analysis, organic extracts were prepared at a concentration of 1 mg/mL in methanol and filtrated on Uptidisk .m/z. A quality control strategy was carried out using a Latin square design for samples, quality control and methanol blank samples in order to reduce the potential error of instrumental drift.LC-MS analyses were performed with an LCQ Fleet 2300 (Thermo Scientific) to determine metabolites in the seawater of each assemblages. The samples were analyzed using a positive ion mode with full scan MS window of 200-2000 34.To determine the exact mass of secondary metabolites selected, LC-HRMS analyses were performed on a UHPLC system  interfaced to a QTOF mass spectrometer . Finally, to strengthen the putative identification of selected metabolites, LC-HRMS and LC-HRMSMS analyses were performed on a UHPLC system  interfaced to an Orbitrap mass spectrometer  or between assemblages. Whatever the experiments, NH4+ and NO2− concentrations were systematically higher in all assemblages containing giant clams (Tukey test p < 0.05). Moreover, NH4+ concentrations were higher in PAT assemblages than in T assemblages. However, while in the experiment A, the range of NH4+ concentrations in PAT and T assemblages were of [1.493-3.016] µmol/L and of [1.059-1.287] µmol/L, respectively, NH4+ concentrations in the experiment B were less than 1 µmol/L (except for 1 sample) in PAT assemblages, which is lower than the range in T assemblage of the experiment A. Overall, the differences of water composition (relative and absolute concentrations) within experiments remained lower than the differences of water composition between experiments.The principal component analysis of the seawater nutrients , cyanobacteria (Cyanophyta), dinoflagellates (Dinoflagellata), Ochrophyta, Rhodophyta and undetermined. Within these, identifications were assigned at the lowest possible taxonomic level (family or genus). We characterized 201 distinct associated taxa across all assemblages. Classical multidimensional scaling analysis of the 6 assemblages based on the Jaccard’s Index Fig.  showed aWe analysed the biofouling of PAT, PA, P and T assemblages using metabarcoding. After data processing of 1 202 179 paired-end reads, 711 313 contigs (16 505–83 708 per assemblage) with an average length of 420 bp  and 340 076 contigs (3 862–38 158 per assemblage) with an average length of 428 bp  were selected for taxonomic and functional analysis.As the three main steps of biofouling are successively the development of bacteria, diatoms and algae, we focused on these three groups. The bacterial group composed of 13 847 unique contigs was divided into 44 phyla and 856 genera . We also noticed that 12 bacterial families were present in 2 or 3 assemblages sharing or not a common species. For example, 3 families  were found in all assemblages containing P. damicornis . Other families were found in 2 assemblages such as Pseudoalteromonadaceae in PA and T assemblages but not in the PAT assemblage. Amongst the 17 identified families of diatoms, 12 were common to all assemblages, 2  were common to PA and P assemblages and 3  were found exclusively in the PA assemblage. For the algae group, 28 families were identified and 15 were common to all assemblages. No specific families were determined for the PAT assemblage but 2 were specific to PA  and to T (Ulvophyceae and Ceramiaceae) assemblages. Furthermore, Peridiniaceae, undetermined Rotaliida and Florideophyceae families were identified in all assemblages except for the PAT assemblage  were common to all assemblages except PAT. Concerning the algae group, only 29 genera were assigned and 12 were common to all assemblages  were common to all the assemblages except this one.At genus level, a qualitative analysis revealed which genera of bacteria, diatom, and algae were common or specific to different assemblages Fig. . Out of ges Fig. . SimilarRhodobacteraceae (~25-45%). Flavobacteriaceae were also found in large quantities (~5-15%) in all assemblages 38 and the brassicasterol39. Based on mass and calculated formula, the last VIP might be a sterol.To determine if secondary metabolites might account for the difference of biofouling communities, a chemical analysis of the tanks’ seawater was performed. The overall LC-MS analysis allowed for the detection of 1 488 distinct metabolites. A large majority of them (1 370), were detected in both assemblages and incoming seawater. Particularly, no specific metabolites were detected in PAT. A quantitative Partial least Square Discriminant Analysis on metabolites was then conducted to discriminate each assemblage. The first components discriminated every assemblage Fig. , with PAThis is the first study demonstrating that biofouling formation is strongly influenced by surrounding benthic sessile species. In particular, we show that in its most severe form, the resulting effect of a species-specific assemblage is biofouling inhibition. Biofouling is a complex sequential process, which can be modulated by many abiotic and biotic factors, ranging from external factors to intrinsic influence of the marine taxa participating in biofouling formation itself.40. An increase of silicates was notably observed during the wet season as well as after strong rains41, as was the case for all aquariums of the A experiment. This link with external parameters can be explained by the design of our experiment, which consisted of an open-circuit with a water flow of 20 L/h per aquarium of 40 L. Therefore, the lagoon seawater composition mainly accounted for the significant variation of nutrient composition between the 3 experiments. As the effect of species assemblage on biofouling development was reproducible, this nutrient discrepancy between experiments could not account for the observed differences in biofouling development.Among these factors, nutrients are known to influence growth and productivity of various organisms such as bacteria and algae. In our study, nutrient contents in the seawater of each aquarium were compatible with those observed in previous nutrient analyses from the Moorea lagoon43. This feeding can lead to a depletion of 30 to 45% of total chlorophyll a and picoplankton above a scleractinian coral dominated reef when compared with adjacent waters42. Tridacna species are able to filter up to 58% of algal cells from their surrounding water44. Moreover, a recent study has shown that corals are able to feed on diatoms such as Thalassiosira sp.43. In light of these results, and taking into account that giant clams filter large amounts of seawater (e.g. water filtration rate of one Tridacna crocea is 2-3 L/h)44, filtering activities could reduce the number of species participating in biofouling development and so could disrupt some steps of biofouling formation. Therefore, whenever another heterotrophic species is added to an assemblage, the community of microorganisms within the aquariums’ seawater could be modified (e.g. additive depletion of microorganisms). Such modifications could account for the differences in biofouling composition and development observed between assemblages, the stronger impact of these additive depletion effects leading to the inhibition of biofouling (e.g. lack of key species required for biofouling progression). Biofouling development was strongly inhibited in the three species assemblages, PAT, of which aquarium water was depleted of 47 bacteria, 2 diatoms and 3 algae genera when compared to the other assemblages. Among these lacking organisms, some bacterial taxa e.g. Rhodobacteraceae that are important biofilm precursors45, could be required for effective biofouling formation. Further studies of giant clam and coral filter-feeding species interactions will be helpful to better understanding their respective putative roles in depleting the microorganisms involved in biofouling progression. However, our experimental conditions with high seawater renewal and successive samplings led to four organisms per species at the end of the experiments. Therefore, corals and giant clams’ nutrition alone cannot be responsible for the disappearance of biofouling key species. Even though relevant, this hypothesis is not sufficient to account for the observed difference in biofouling development.Studies have shown that bacteria, plankton and phytoplankton as well as dissolved organic and inorganic molecules are filtered from seawater and ingested by corals and bivalves48. Because mucus contains a lot of inorganic phosphate and dissolved organic carbon, it is suspected as an effective inducer of bacterial growth49. Moreover, the diversity and quantity of the hosted bacteria differs not only between species but also according to their environment50. Dobrestov and collaborators12 have shown that numerous bacteria associated with corals possess an anti-bacterial activity, and antibacterial compounds in coral mucus have notably been found to select specific bacterial population leading to an antifouling effect51. Interestingly, 7 bacterial species were specifically found in PAT assemblages. Among them, bacteria belonging to the genus Lysobacter which are able to degrade biofilm and could contribute to the observed antifouling effect52. Corals and giant clams are known to produce bioactive compounds such as sterols which are described as chemical defensive substances54. Indeed, living corals are free of fouling and this particularity come from the production of secondary metabolites, especially sterols playing key roles in allelopathy with the ability to inhibit the growth of organisms around them54. Thereby, a fouling-resistant composition, non-toxic for the environment and applicable on immersed equipment, was made with sterols55. Even though no specific metabolite to the PAT assemblage was detected, suggesting that no new compound is produced in this context, 5 VIPs characterizing the PAT assemblage were highlighted. Among them, one was assigned to carotenoids and 4 to lipids. The carotenoid, identified as peridinin, is a specific pigment found in Symbiodinium dinoflagellates from corals and giant clams35. Interestingly, like most of the carotenoids, peridinin exhibits an inhibitory activity even at low concentration. As peridinin can inhibit cell proliferation and can exhibit a cytotoxic activity57, it might contribute to the biofouling inhibition observed in PAT assemblage. Moreover, among the lipids identified, one was assigned to brassicasterol and two to DGDG. Brassicasterol is found in various marine organisms such as cnidarians, sponges or diatoms60. In addition to having significant anti-inflammatory properties60, this sterol exhibits activity against organisms such as protozoans61. Furthermore, DGDG are also found in marine organisms, especially in Symbiodinium from both corals and giant clams63. Digalactosyldiacylglycerols possess strong nitric oxide inhibitory properties leading to antiviral activity65. Moreover, DGDG have been identified as antifouling agent demonstrating repellent activity notably of blue mussels66. These data suggest that a synergism of secondary metabolites might lead to antifouling activity as it has already been assumed in a previous study67. Therefore, in the present study, either due to their abundance as VIPs or to their synergism, carotenoid and lipids might be responsible for the biofouling inhibition specifically observed in PAT assemblage. In this regard, as mucus is continuously released by both corals and giant clams68, we cannot exclude that mucus flocs and/or secreted molecules such as antibiotics could adhere to the aquarium’s walls, playing a role in biofouling production. This effect will be, as discussed for nutrition, dependent on the different species present in the aquarium, with possible positive or negative interactions.In contrast to ingested filtered organisms, those associated with invertebrate species, bacteria and microalgae, have been well characterized. Bacteria have been found living on the surface, in the tissues and in the mucus of coral species71. The combination of these factors usually prevent resilience of coral reefs, and favour the shift from coral-dominated to algal-dominated reef ecosystems74. Our discovery of an assemblage dependent antifouling activity is all the more important that biofouling inhibition occurs even in brief increased temperature conditions. Another major point of our results is that the loss of one species in a three species assemblage leads to a change in the algal inhibition spectrum, the two species assemblage being less active against or more prone to algal development. Despite the timeliness of understanding ecological shifts towards algal-dominated tropical habitats, a gap of knowledge still exists about the mechanisms governing these shifts75. It is well known that coral reefs taxa, e.g. scleractinian corals species, are differentially sensitive to environmental stressors78 and that, among sessile species, giant clams are notably more resistant than corals to sea water warming80. Therefore, environmental stress raises sequential and differential loss of species. This selective loss of species may impact the structuration of coral reefs benthic communities, leading to a change in the species interaction network and therefore, as exemplified by our work, might strongly impact their defence mechanisms against prerequisite steps of algal development. On the contrary, maintaining the diversity may temper this coral-algal shift. Hence, our study pinpoints that sessile coral reef species diversity, distribution and fitness might strongly influence this coral-algal shift, underlining the putative dramatic consequences of the decrease in biodiversity and the health of coral reefs.Regardless of the mechanisms involved in this inhibition, our experimental results suggest that biofouling develops differently, depending on the type and complexity of the sessile species assemblages and this may have important implications in coral reef ecology. Moreover, these phenotypes were maintained throughout experimental trials, even during the five days short thermal stress, suggesting that occasional increases in seawater temperature are not sufficient to induce differences of biofouling appearances. Global warming, ocean acidification, and local human impacts are considered as the main causes of coral reefs deterioration globally81. In line with this interpretation, microbiomes in PA assemblages included species of Pseudoalteromonaceae that are able to degrade a form of polyhydroxybutyrat referred to as poly-3-hydroxybutyrate82. Other functions such as sulfur reducer, iron oxidizer, streptomycin producer and cellobiose degrading were, respectively, strictly found in T, PAT, P and PA. Additionally, some specific functions such as nitrite reducer and atrazine metabolism for T and PAT or degrade aromatic hydrocarbon for PAT, P and PA, are shared by some but not all of the assemblages. Therefore, the presence of nitrite reducer activities in both PAT and T assemblages could account for the systematically higher level of NH4+ in these assemblages. Such common features between some specific assemblages highlight the potential cumulative functional effect of the addition of one species in an assemblage, such as degrading aromatic hydrocarbons produced by P in PAT and PA as well as some emergent functions such as iron oxidizer in PAT. Therefore, all these combinations of functions provide a specific capacity to an assemblage for responding to changing environmental conditions. Such a trait can be related to the beneficial effect of plant assemblages for the growth, productivity and protection against pathogens and others, such as in permaculture where combinations of plants are used to enhance resistance and productivity83.Beyond the biofouling phenotypes, with its extreme form translating into biofouling inhibition, the present study also highlighted the functional interactions resulting from sessile species assemblages. Our data showed that specific communities of bacteria, diatoms and algae characterized the biofouling composition of each assemblage. The bacterial functional profiling revealed an increase of “stores polyhydroxybutyrat” in PA assemblage that could be linked to a need of energy storage molecule or to a stressConsidering the resulting functional aspects of various species assemblages, with some positive and/or negative interactions, together with their effect on biofouling development, our data support the notion that marine species assemblages should be integrally part of future coral reefs restoration plans as is already the case for terrestrial restoration.Supplementary S1Supplementary S2Supplementary S3Supplementary S4Supplementary S5Supplementary S6Supplementary S7Supplementary S8Supplementary S9


Mitochondrial haplogroups H1, H2 and UK have previously been reported to be associated with proliferative diabetic retinopathy (PDR) in Caucasian patients with diabetes. We aimed to replicate this finding with a larger sample and expand the analysis to include different severities of DR, and diabetic macular edema (DME). Caucasian participants (n = 2935) with either type 1 or type 2 diabetes from the Australian Registry of Advanced Diabetic Retinopathy were enrolled in this study. Twenty-two mitochondrial single nucleotide polymorphisms were genotyped by MassArray and haplogroups reconstructed using Haplogrep. Chi square tests and logistic regressions were used to test associations between haplogroup and DR phenotypes including any DR, non-proliferative DR (NPDR), proliferative DR (PDR) and DME. After stratifying the samples in type 1 and type 2 diabetes groups, and adjusting for sex, age, diabetes duration, concurrent HbA1c and hypertension, neither haplogroups H1, H2, UK, K or JT were associated with any DR, NPDR, PDR or DME. Globally, from 1990 to 2010, visual impairment attributable to diabetes increased by 64% from 2.3 million to 3.7 million2. Vision loss occurs from proliferative diabetic retinopathy (PDR) and diabetic macula edema (DME). PDR is the most severe form of DR and is characterized by the growth of pathological vessels in the retina. DME can occur at any stage of DR and is characterized by oedema in the macula region of the retina.Diabetic retinopathy (DR) is a leading cause of vision loss from diabetes driven damage to the retina. It is becoming increasingly prevalent in spite of better risk factor control and screening3. While several studies have explored genes involved in inflammation and angiogenesis related pathways , little research has focused on the role of mitochondrial DNA (mtDNA) in the susceptibility of DR5. It is well established that oxidative stress plays a key role in the pathogenesis of diabetic complications, including DR6. A significant source of reactive oxygen species (ROS) is from the mitochondria. Mitochondrial overproduction of ROS is hypothesized to be the single upstream event that mediates multiple mechanisms of hyperglycemia induced damage to tissues including polyol pathway flux, increased formation of advanced glycation end products (AGEs), increased expression of AGE receptors and activating ligands, activation of protein kinase C isoforms and overactivity of the hexosamine pathway7. Furthermore, mtDNA is highly sensitive to oxidative damage and has a high mutation rate with implications for electron transport chain function and endothelial cell survival, even long after the initial hyperglycemic insult10.DR has a complex genetic componentet al. reported that haplogroups H1, H2 and UK in a Caucasian sample (n = 392) were associated with PDR11. Haplogroup H1 and H2 were risk factors for the development of PDR from non-proliferative diabetic retinopathy (NPDR), while haplogroup UK was protective against PDR. Subsequently, Bregman et al. reported similar findings in a larger group from the same population (n = 637), and reported further that while mitochondrial haplogroup was associated with PDR, it was not associated with DR more generally12. A different case control study (149 with any type of DR and 78 with no DR) found a higher prevalence of haplogroup T in those with any DR 13.A common classification system for mtDNA variation is mitochondrial haplogroup, which represents the major branch points on the mitochondrial phylogenetic tree of human evolution. Estopinal We sought to replicate these studies in a larger sample (n = 2935) with increased power to explore other DR phenotypes such as DME and to evaluate this association in participants with type 1 and type 2 diabetes mellitus.This project has been approved by the human research ethics committees (HRECs) in Australia  HREC, South Eastern Sydney Illawarra HREC, Tasmania Health and Medical HREC) and the NHS Health Research Authority in London. It adheres to the tenets of the Declaration of Helsinki. Written informed consent was obtained from each participant before study enrolment.This study was carried out among Caucasian participants (identifying as of European descent) recruited in the Australian Registry of Advanced Diabetic Retinopathy (RADAR) and the Genetic Study of Diabetic Retinopathy based at Flinders University, South Australia. Multiple recruitment centres were involved and included the following Australian hospitals; Flinders Medical Centre, The Repatriation General Hospital, The Royal Adelaide Hospital, The Queen Elizabeth Hospital, The Royal Melbourne Hospital, Royal Victorian Eye and Ear Hospital, St. Vincent’s Hospital, Sydney Eye Hospital, Canberra Hospital, Royal Hobart Hospital, and from the United Kingdom; The National Institute for Health Research Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, United Kingdom.14. Clinically significant macula edema (CSME) was defined according to the Early Treatment Diabetic Retinopathy Study protocol: 1) retinal thickening within 500 μm of the center of the macula, 2) hard exudates at or within 500 μm of the centre of the macular if associated with thickening of the adjacent retina or 3) retinal thickening 1 disc area in size, within 1 disc diameter of the centre15. Sight threatening DR was defined as either severe NPDR, PDR or CSME.Eligible participants were actively recruited from ophthalmology, diabetes and renal clinics, with the following inclusion criteria: 1) type 1 (T1DM) or type 2 diabetes mellitus (T2DM). Those with T2DM must have received at least 5 years of medical treatment for diabetes  prior to enrolment, and must have been over 18 years of age. All participants underwent a questionnaire and venous blood sample collection for DNA analysis. Clinical information was collected from case notes and electronic records, including the average of three most recent, available HbA1c measurements (or three measurements immediately prior to a diagnosis of PDR), renal and lipid measures, medications and the presence of non-ocular diabetic complications. DR grading (defined as the worst ever grading) and the presence of DME were determined from documented dilated fundus exams performed by an ophthalmologist. DR grading was defined by the International Clinical DR Severity Scale16.For each participant, approximately 8 mL of blood was collected in EDTA blood collection tubes and underwent DNA extraction using the QIAamp Blood DNA Maxi Kits . More detail regarding the data collection method has been described previouslyet al. in previous studies to determine mitochondrial haplogroup , using the Agena Bioscience MassARRAY platform. We utilized the same panel of 22 mtDNA SNPs designed by Estopinal Statistical analysis was performed with Statistical Package for Social Sciences versions 23.0 . Chi Square tests were performed to analyse the association of haplogroup type with various DR phenotypes such as any DR, any NPDR, PDR, DME and CSME. Logistic regression was used to adjust for covariates age, sex, type of diabetes, duration of diabetes, HbA1c and presence of hypertension. Statistical significance was taken at p < 0.05. Further analysis was performed by stratifying the analysis into T1DM and T2DM cohorts, and the major European haplogroups .Patient demographics n = 2935) stratified by DR phenotype are presented in Table 935 stratA total of 7 European mitochondrial haplogroups were identified in our Caucasian sample. The most common ones were haplogroup H1 and H2  and UK at 50.8% and 22.5% respectively. Other types included JT (12.4%), R (7.1%), I (4.2%), W (2.0%) and X (1.0%)  were distributed similarly in each of the different phenotype groups, and that any differences when compared with no DR controls were not statistically significant after performing Chi Square association tests Table . We alsoAfter separating the samples per diabetes type, the majority were T2DM participants n = 2265) compared with T1DM participants (n = 670). The demographics of the T1DM and T2DM groups are given in Supplementary Tables  comparedThe next most common haplogroups (JT and K separately from UK) were analysed separately (frequencies 12.4% and 7.8% respectively). Significant results were: haplogroup K was nominally associated with any DR  and NPDR . JT was nominally associated with NPDR  and CSME  These results should be treated with caution as the numbers are small and the association does not survive correction for multiple hypothesis testing.In our larger Caucasian sample, unlike earlier smaller studies, we found no significant associations between mitochondrial haplogroup and the presence of any DR, DME, nor more severe phenotypes such as PDR, CSME or sight-threatening DR . This was true for analysis as a group or when stratified for type of diabetes, in spite of following the same methods of previous studies which found positive associations.et al. first demonstrated that haplogroups H1 and H2  and UK were associated with PDR when compared with NPDR in an American Caucasian sample 11. Having either haplogroup H1 or H2 was a risk factor, while haplogroup UK was protective. Bregman et al. expanded from this initial study with 513 additional diabetic controls in the same databases (Vanderbilt Eye Institute and Vanderbilt University)12. They found that haplogroup H1 and H2, and UK were not associated with any incident DR compared with no DR. Using the same cohort, Mitchell et al. found duration of diabetes and HbA1c was significantly associated with PDR in haplogroups H1 and H2, but not UK, suggesting that mitochondrial haplogroups modify these clinical risk factors for the development of PDR in type 2 diabetes18. In a different study, Kofler et al. reported haplogroup T was significantly associated with any DR compared with no DR 13.Estopinal et al. reported haplogroup cluster J/T was significantly associated with insulin resistance in a Caucasian Brazilian population19, but this was refuted by two other studies of Caucasian samples21. Challenges in interpreting mitochondrial association studies include differences in study design, case and control definitions, statistical analysis, population stratification, inadequate power and lack of replication22.Inconsistent results are common in all areas of haplogroup association studies. For example Crispim et al.'s study. As expected in both studies, age, diabetes duration, type of diabetes and HbA1c were strongly associated with increasing severity of DR.Different results could be due to different populations and study design, however in examining the demographics and distribution of the haplogroups, our group appears to be similar to the group from the Vanderbilt Eye Institute and Vanderbilt University. Both groups consist of Caucasian patients of European descent. We used the same criteria for selection of retinopathy cases and controls and the same statistical analyses. The most common haplogroups were H1 and H2, and UK; 73.3% in our study, compared with 68% in Bregman 23. Our larger study size allowed us to analyse other phenotypes such as DME and CSME, as well as to separately analyse less common haplogroups such as JT, and K separate from UK. The only statistically significant results we found were haplogroup K was nominally associated with any DR, and haplogroup JT was nominally associated with NPDR and CSME. As the numbers were small in these comparisons and the result does not survive multiple hypothesis testing, this is likely to be type 1 error. Haplogroup K was not a common haplogroup in the previous two studies and is not implicated in diabetes and other associated diseases. Kofler et al. reported haplogroup T was significantly associated with any DR but this study also had a much smaller sample size (149 with any DR and 78 with no DR)13. As noted in our results, we were unable to separately analyse haplogroup T due to genotyping failure, and so direct comparison to Kofler et al.’s study could not be made.An important reason why our results are different is because our study consisted of a much larger population; 1124 diabetic retinopathy controls (no DR), 1161 NPDR cases and 650 PDR cases. Therefore our study has increased statistical power to identify any true associations. We were unable to replicate previously reported associations, suggesting that these previous association may be false. Smaller studies and sub analyses of phenotype groups lead to a higher risk of type 1 errorsIn addition to study size, strengths of this study include the inclusion of both T1DM and T2DM subjects from multiple sites, rigour of retinopathy status characterisation, wide range of levels of DR and use of the same haplotyping methods and statistical analyses as previous studies so comparisons could be made.The haplotyping method we utilized from previous studies has an important limitation. SNPs chosen to represent the H haplogroup (rCRS position 3010 and 1438) only identify haplogroups H1 and H2. Therefore 7 other major subtypes of haplogroup H were not analysed. In our study, one SNP completely failed genotyping  and therefore we could not analyse haplogroup T separately. Another 4 SNPs had a 2% failure rate, and this could have contributed to the percentage of samples with haplogroup R . We chose our Caucasian sample based on participants self-identifying as Caucasian, but a small number had non-Caucasian haplogroups . Some of the 22 SNPs chosen for haplogroup determination are also found in other ethnic populations . Therefore, all samples with a non-Caucasian haplogroup were removed to minimize any confounding effect and reduce population stratification.7 and their presence in the retina24. Mitochondrial DNA are inherited completely from the maternal line, unlike nuclear DNA which has equal maternal and paternal contributions25. Risk of T1DM in the offspring varies by parental status; being two-fold lower if the mother has T1DM rather than the father26. Epidemiology studies show that certain ethnicities are at greater risk of DR such as people of Asian, African and Indigenous ethnic groups27. Complex biological and environmental factors explain this observation, and mitochondrial genetics could also play a role, but this has not been studied.We recognise that even larger studies and studies in different ethnic groups, particularly those at high risk of diabetic retinopathy, are desirable. We only studied 7 haplogroups, while the human mitochondrial phylogenetic tree consists of hundreds of haplogroups. The hypothesis that variations in mitochondrial genetics contribute to DR risk is logical given the role that the mitochondria play in oxidative stress28. Specific mitochondrial variants that have been studied for DR include mutations in UCP2 and Mn-SOD genes4.Mitochondrial haplogroup is not a specific marker for mitochondrial genetic variability. A haplogroup consists of many genetic variants that are inherited together. Therefore, if there are specific mitochondrial variants that contribute to DR, these cannot be studied effectively. Single nucleotide polymorphisms in mitochondria cause diseases such as Leber hereditary optic neuropathy, and in complex diseases such as diabetes and cancer, it is increasingly recognised that small mitochondrial defects could lead to subtle bioenergetics alterations with major clinical implicationset al. recently reported lower respiratory chain complex activity in haplogroup N9a compared with D4j, G4a2 and Y1, using transmitochondrial technology29. Mueller et al. reported mitochondrial haplogroup T cell cybrids had a higher survival rate than haplogroup H cybrids under oxidative stress conditions such as when challenged with hydrogen peroxide30. Haplogroup K cybrids showed different gene expression levels compared with H cybrids after amyloid-beta toxicity31. Untreated retinal cell cybrids of H and J haplogroups also showed different gene expression and methylation status32. Future studies and techniques designed to explore the mitochondria genome in better detail than currently available can help us understand whether mitochondrial genetics contribute to DR risk33.Few studies have demonstrated whether mitochondrial haplogroup directly affects mitochondrial function. Fang In contrast to previous studies, our much larger study found no association between the major European mitochondrial haplogroup H1, H2, UK, and DR phenotypes in either type 1 or type 2 diabetes. No significant associations were found for different severities of DR and DME, or other subsets of mitochondrial haplogroups that were analysed by this study.Supplementary Tables


Karyotype determination has a central role in the genetic workup of pregnancy loss, as aneuploidy (trisomy and monosomy) and polyploidy (triploidy and tetraploidy) are the cause in at least 50% of first trimester, 25% of second trimester, and 11% of third trimester miscarriages. There are several limitations with the current approaches of obtaining a karyotype using traditional cytogenetics, fluorescence in situ hybridization with a limited number of probes, and chromosomal microarray. These include culture failure, incomplete results, lower sensitivity, and longer reporting time.To overcome current limitations, a novel molecular assay is developed with a Standard Resolution Interphase Chromosome Profiling probe set which is a variation of the recently developed High Resolution probe set. It generates a molecular karyotype that can detect all major changes commonly associated with pregnancy loss. Initial familiarization of signal patterns from the probe set was used, followed by validation of the method using 83 samples from miscarriages in a blind study from three different laboratories. Finally, the clinical utility of the method was tested on 291 clinical samples in two commercial reference laboratory settings on two different continents.The new molecular approach not only identified all the chromosome changes observed by current methods, but also significantly improved abnormality detection by characterizing derivative chromosomes and finding subtle subtelomeric rearrangements, balanced and unbalanced. All Robertsonian translocations were also detected. The abnormality rate was 54% on clinical samples from commercial laboratory 1 and 63% from laboratory 2.FISH panels, (3) rapid reporting time, and (4) favorable comparisons with chromosomal microarray.The attributes of this method make it an ideal choice for the genetic workup of miscarriages, namely (1) near 100% successful results, (2) greater sensitivity than conventional chromosome analysis or  TThe second stage in the clinical validation tested the clinical utility of Standard Resolution ICP in another set of 291 clinical samples, which were referred for chromosome testing in the commercial reference laboratory setting in two different laboratories. Laboratory 1 tested 41 samples and all of the samples had an ICP result (100%) with a 54% abnormality rate. There was 100% concordance with conventional cytogenetics on these 41 samples Table . LaboratAneuploidy that is generally not detected with commonly used FISH panels, but which was observed in the ICP studies, included 48 cases with trisomy 4, 7, 8, 14, 15, 19, or 20. ICP found 21 structural abnormalities, including autosomal balanced translocations and Robertsonian translocations, some of which FISH or CMA would have failed to detect or correctly characterize. Three rearrangements discovered by ICP in the initial phase of the study were not identified by conventional chromosome analysis, and one abnormality found by conventional chromosome analysis was not recognized by ICP (see next paragraph). Application of the Acrocentric ICP probe set was used in the evaluation of acrocentric trisomies  is a well‐recognized problem in POC cultures. Traditional chromosome studies detected only a normal female karyotype in case 16  are useful in detecting numerical abnormalities such as trisomy and monosomy, specific detection of balanced and unbalanced structural abnormalities, aneuploidy, and tetraploidy may be problematic depending on the methods employed. In addition, detection of Robertsonian translocations can only be accomplished currently by conventional cytogenetics.The overall abnormality rate for the clinical samples was 54% in Laboratory 1 and 63% in Laboratory 2, which is comparable with conventional cytogenetic studies when cell culture is successful. The culture failure and MCC rates for POC samples using conventional cytogenetics are high even in the best quality‐controlled laboratories. Culture failure occurs in 15%–20% of attempted studies, and another 20% or more represent maternal‐derived uterine contents, depending to some extent on the referral source  FISH assay. Some laboratories include probes for chromosomes 16 and 22, yet they still would have missed the other seven trisomies detected by ICP in this study. ICP also found balanced and unbalanced Robertsonian translocations that would not have been identified by FISH or CMA. Even though most “apparently” balanced translocations do not have any phenotype associated with them, some are associated with a submicroscopic imbalance that could lead to an abnormal phenotype ,+21[cp20].5Standard Resolution ICP appears to be an appropriate tool for first line or reflex testing in the genetic workup of POC samples. Results of this study have confirmed that ICP is (1) highly reliable, (2) more sensitive than the traditional FISH approach using a limited number of probes, (3) capable of detecting both numerical and gross structural aberrations including characterization of “add” material in the derivative chromosomes, and (4) does not require cell culture, which allows a faster reporting time. As with microarray, karyotype analysis, and FISH panels, results of Standard Resolution ICP studies will assist in genetic counseling for recurrence risks of aneuploidy, polyploidy, and balanced and unbalanced chromosome rearrangements.R.B., E.F., S.F., S.P., and S.K. are employed by InteGen LLC. The remaining authors report no conflicts of interest.


In vitro and in vivo tests have revealed a good biocompatibility of ZnO/CD/Cfp coatings, which recommend them as competitive candidates for the development of antimicrobial surfaces with biomedical applications. The release of the fourth generation cephalosporin Cfp in a biologically active form from the ZnO matrix could help preventing the bacterial adhesion and the subsequent colonization and biofilm development on various surfaces, and thus decreasing the risk of biofilm-related infections.Deposition of bioactive coatings composed of zinc oxide, cyclodextrin and cefepime (ZnO/CD/Cfp) was performed by the Matrix Assisted Pulsed Laser Evaporation (MAPLE) technique. The obtained nanostructures were characterized by X-ray diffraction, IR microscopy and scanning electron microscopy. The efficient release of cefepime was correlated with an increased anti-biofilm activity of ZnO/CD/Cfp composites.  Enterobacteriaceae are key Gram-negative pathogens that are involved in serious nosocomial infections. In these Gram-negatives, resistance to all active agents have been described, and clustering of multiple resistance determinants to various classes of antimicrobial agents is a common finding which results in complex multi-drug, extended-drug and pan-drug resistance phenotypes  to dark blue formazan. The reduction is achieved by the mitochondrial enzymes  and is an indicator of the integrity of the cells. Water insoluble formazan can be solubilized with isopropanol, dimethyl sulfoxide or any other organic solvent. The optical density (OD) of formazan is spectrophotometrically evaluated, yielding a function dependent by absorbance and concentration of the cells in culture. The cells were grown in 96-well plates, with a seeding density of 3000 cells/well in different experimental conditions. Then was added 15 mL solution I and incubated at 37 °C for 4 h. Add the solution II and pipette vigorously to solubilize formazan crystals. Incubate 1 h, then pipetted to disperse and remove the bubbles in order not to interfere with the reading. The absorbance was read on a spectrophotometer at 570 nm .The CellTracker™ Red CMTPX fluorescent dye has been designed to freely pass through cell membranes into cells, where it is transformed into cell-impermeant reaction products. CellTracker™ Red CMTPX dye is retained in living cells through several generations. The dye is transferred to daughter cells but not adjacent cells in a population. CellTracker™ Red CMTPX dye is designed to display fluorescence for at least 72 h and the dye exhibits ideal tracking properties: it is stable, nontoxic at working concentrations, well retained in cells, and brightly fluorescent at physiological pH. Red CMTPX was added to the cells at a concentration of 3 μM and incubated for 30 min. The washed cells were analyzed under fluorescence microscope, having an emission spectrum in red (577/602 nm).The treated and control cells were harvested from culture by centrifugation (300 g for 2 min). The supernatant was removed and the cells were resuspended in PBS . While mixing, 2 mL ice-cold 70% ethanol was added and samples were incubated on ice for 30 min. Then the cells were spin down and washed in 5 mL of PBS, and resuspended in 400 μL PBS. Then 50 μL of propidium iodide (400 μg/mL) were added and the cells were incubated at 37 °C for 30 min. The samples were analyzed by flow cytometry.The experimental protocol was applied according with the European Council Directive No. 86/609 (24 November 1986), the European Convention for the Protection of Vertebrate Animals used for Experimental and Other Scientific Purposes (2 December 2005), and the Romanian Parliament Law No. 43 (11 April 2014) on the protection of animals used for scientific purposes. The study was approved by the Ethics Committee of the University of Medicine and Pharmacy of Craiova, Romania .Three months old BALB/c mice were aseptically injected with 100-μL of 1 mg/mL suspension of nanostructures previously sterilized by UV irradiation for 30 min in sterile saline. Intravenous administration was carried out slowly, under general anesthesia (ketamine/xylazine mixture), into the left jugular vein, using a catheter. Reference mice were injected with 100 μL saline suspension. The mice were kept in standard conditions before the organs removal. At 2 days and 10 days after the beginning of the experiment, the animals were euthanized, under general anesthesia, for the sampling of internal organs .Directly after the sampling, the biological material was washed in PBS to remove blood. Then, the internal organs were fixed in 10% buffered neutral formalin, for 72 h, at room temperature, and processed for routinely histological paraffin-embedding technique ,20.Escherichia coli ATCC 8739 was obtained from the American Type Culture Collection . Fresh glycerol stocks were streaked on nutritive agar plates and colonies were allowed to develop for 24 h at 37 °C. Fresh colonies were used to obtain a bacterial suspension of a 0.5 McFarland (corresponding to 1–3 × 108 CFU/mL) optical density in PBS. For assessing monospecific biofilm formation, 2 mL of nutritive broth were disposed in each well of a 6-wells plate, containing test (coated glass slides) and control (bare glass substrates) samples and seeded with the bacterial inoculum consisting of a volume of 20 μL from the PBS bacterial suspension. After a period of 24 h incubation at 37 °C, the materials containing attached bacteria, were washed with PBS and transferred in a fresh well, containing 2 mL sterile nutritive broth and the incubation continued for another 24 h. The same procedure was repeated at 48 and 72 h, in order to assess the biofilm formation on the materials at different time intervals . After each interval, the viable cell count (VCC) method was performed. For this, after each time point, biofilm embedded bacteria cells were detached by vigorous vortexing for 30 s. PBS suspensions containing detached bacteria cells were subjected to serial tenfold dilutions and each dilution was seeded on nutritive agar. Experiments were performed in triplicate and repeated on at least three separate occasions [The microbial strain used in this study, ccasions .The obtained results demonstrate that ZnO/CD coatings deposited by means of the MAPLE protocol exhibited appropriate features for the release of cefepime, as demonstrated by the efficient inhibition of the microbial adherence and development of a mature biofilm on the coated surfaces. These results suggest that the obtained ZnO/CD system could be successfully used as carrier and release systems for the fourth generation cephalosporins, while the MAPLE technique could serve as an appropriate tool for obtaining bioactive coatings, resistant to bacterial colonization.


To examine the relationship between pubertal timing (using measures of height tempo) and proximal femur shape in a large adolescent cohort.Hip DXA scans were obtained in offspring from the Avon Longitudinal Study of Parents and Children. To quantify hip morphology, the images were analyzed using Shape software based on a 53-point statistical shape model and independent modes of variation (hip shape mode (HSM) scores) for each image were generated. Height tempo (which corresponds to age at peak height velocity (aPHV)) was estimated from serial height measurements collected between age 5–20 years. Multivariable linear regression was used to examine cross-sectional associations between height tempo and the top ten HSMs at age 14 and 18, adjusting for sex and fat mass index (FMI).p = 4.1 × 10−50). Compared with males, the associations were generally weaker in females, with the strongest effect observed for HSM8  p = 1.6 × 10−5). The overall effect of later pubertal timing on proximal femur shape in males was a narrower femoral neck and larger superolateral head, whereas in females these changes were hard to discern. When assessed at age 18, there was little relationship between tempo and proximal femur shape in either sex.Complete outcome and covariate data were available from 3827 and 3507 participants at age 14 and 18 years, respectively. Mean aPHV was 13.5 and 11.8 years for males and females, respectively. At age 14, height tempo was associated with a majority of modes, except for HSM4 and there was strong evidence of interaction by sex. In males, all modes showed evidence of an association with tempo, independent of FMI, with the strongest observed for HSM8  Our results indicate that significant changes in hip shape occur during puberty, including aspects of shape which may be related to future risk of hip OA and/or fracture. However, puberty timing per se does not appear to exert long lasting effects on proximal femur shape. •Puberty represents an important period for the development of hip shape.•Associations between pubertal timing and hip shape at age 14 were stronger in males.•Pubertal timing does not appear to have lasting effects on hip shape. FurthOP and OA are both common age-related conditions associated with ill health, morbidity and significant economic burden . DespitePrevious studies of hip morphology have traditionally relied on measures of single geometrical indices, such as femoral neck width (FNW), neck-shaft angle or hip axis length . HoweverWhile previous studies suggest that sex differences in bone geometry emerge around the time of puberty , it is uIn the present study, we aimed to examine the relationship between pubertal timing (based on measures of height tempo) and proximal femur shape in the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. Whether puberty represents an important time for proximal femur shape development was investigated by examining relationships between height tempo and proximal femur shape at age 14. In addition, to determine whether puberty timing per se has long lasting effects on proximal femur shape, we investigated whether height tempo is related to proximal femur shape at age 18.22.1http://www.bristol.ac.uk/alspac/researchers/our-data/). The outcome data and confounders in the present study were collected during Teen Focus (TF) 2 and TF 4 research clinics, whereas tempo was generated from height measurements collected at multiple time points (see below for more details). TF 2 was carried out between January 2005 and September 2006. Of 11,351 individuals invited 6147 attended. TF 4 clinic started in December 2008 and was completed by mid-2011. Of 10,101 individuals invited, 5217 attended.Pregnant women resident in Avon, UK with expected dates of delivery 1st April 1991 to 31st December 1992 were invited to take part in the study. The initial number of pregnancies enrolled was 14,541 (for these at least one questionnaire has been returned or a “Children in Focus” clinic had been attended by 19/07/99). Of these initial pregnancies, there was a total of 14,676 foetuses, resulting in 14,062 live births and 13,988 children who were alive at 1 year of age ,18. WhenEthical approval for the study was obtained from the ALSPAC Ethics and Law Committee and the Local Research Ethics Committees.2.2To quantify the shape of proximal femur, SSM was applied to hip DXA images performed by GE Lunar Prodigy , collected at TF 2 and TF 4 clinics. Application of this method to ALSPAC data has been described previously . Briefly2.3Height was measured to the nearest 0.1 cm using a Harpenden stadiometer with shoes removed. These measurements were collected by trained field workers during assessment clinics, between age 5 and 20 years, and were used to estimate age at peak height velocity (aPHV) using SuperImposition by Translation and Rotation (SITAR) mixed effects growth curve analysis, a method previously described by Cole et al. . This isPrevious studies suggest that fat mass or body mass index (BMI) affect the onset of puberty in males and females . To adju2.4The normality of data was explored using descriptive statistics and histograms. Descriptive statistics are expressed as means with SDs for continuous variables. Multivariable linear regression was used to examine cross-sectional associations between height tempo and the top ten HSMs at age 14 and 18, adjusting for sex (model 1) and additionally for FMI (model 2). Sex differences were explored by comparing regression coefficients and their 95% CIs in sex-stratified analysis and by formally testing for evidence of statistical interaction using likelihood-ratio tests. Additional sensitivity analyses, carried out in males and females separately, explored the differences in HSM scores at age 14 years, between individuals ≥90th and <90th sex-specific tempo percentiles and ≤10th and >10th sex-specific tempo percentiles, in unadjusted and FMI adjusted models. In order to aid comparison with regression results (when using tempo as a continuous measure), beta coefficients from sensitivity analyses were scaled to reflect one-year difference in tempo.p<0.005).To illustrate the overall relationship between pubertal timing and proximal femur shape at each time point, sex-stratified coefficients from FMI adjusted linear regression models corresponding to 10th and 90th percentiles of tempo  were simultaneously entered into Shape software, for all modes showing evidence of an association with height tempo , tempo was associated with the majority of HSMs, except for HSM4 . FollowiIn males, in unadjusted analysis there was evidence of association of tempo with all modes (model 1), and these results were essentially unchanged following FMI adjustment (model 2) .Table 3AIn females, associations between tempo and HSMs were generally weaker compared with males. There was evidence for an association with a number of modes, including HSM2, HSM3, HSM6, HSM8, HSM9 and HSM10 model 1, . FollowiWe modelled overall proximal femur shape in early versus late maturers, reflected by 10th and 90th tempo percentile respectively, adjusted for FMI . In male3.3Compared with the main results when using tempo as a continuous measure, in males, the differences in HSM scores between late maturers vs. the rest , were largely consistent in terms of the direction and size of the effect (models 1 and 2) (Supplementary Table 3).p = 3.2 × 10−5 vs. 0.04  p=0.052 when using tempo as a continuous measure).Analyses in late maturing females likewise revealed similar results to those of tempo as a continuous measure, with the exception that differences were now more pronounced in HSM5 scores  Supplementary Table 4 shows the differences in HSM scores between early maturers vs. the rest . Compared with the main results, in males, all coefficients were in the opposite direction  and broadly similar in terms of magnitude of effect (models 1 and 2), except HSM6 and HSM7 which were larger. In females, in unadjusted analysis there was some evidence for differences in HSM2 and HSM7 scores between early maturers vs. the rest, however these associations attenuated towards the null following adjustment for FMI.3.4Compared with age 14 results, associations between tempo and proximal femur shape at age 18 were generally weaker, as reflected by considerably lower beta coefficients. In sex-combined analysis, based on model 1, there was evidence of association between tempo and HSM1, HSM2, HSM5, HSM9 and HSM10 . FollowiThere was little evidence to suggest interaction by sex, however sex stratified analyses suggested that associations between tempo and HSM2 and HSM5 observed in sex combined analyses were largely driven by those in females .Table 5AWhen modelling overall proximal femur shape at age 18 according to pubertal timing, the differences between early vs. late maturers were hard to discern in both sexes .Fig. 2Th4We examined the association between pubertal timing (as measured by height tempo) and proximal femur shape in ALSPAC adolescents. In males, tempo was strongly associated with many of the top 10 HSMs derived from hip DXA scans performed at age 14, with little attenuation after adjustment for FMI. In contrast, much weaker associations were observed between tempo and proximal femur shape at this age in females. At age 18, associations between pubertal timing and proximal femur shape were considerably weaker compared with age 14 results.In the case of male participants, age of first clinic attendance closely corresponded to the mean aPHV . Therefore, in our analyses in males, we were able to examine how proximal femur shape varies across the full spectrum of pubertal development, enabling us to infer how proximal femur shape alters during puberty, despite our cross-sectional study design. Having constructed an overall effect on proximal femur shape by combining associations with all HSMs related to tempo, our results infer that as puberty advances, FNW increases, both the lesser and greater trochanters enlarge, and there is some re-shaping of the superolateral aspect of the femoral head. In contrast, in female participants, age of first clinic attendance was two years beyond mean aPHV . Therefore, our analyses in females only provided limited information as to how proximal femur shape alters during puberty, presumably explaining the considerably weaker association between tempo and proximal femur shape at age 14 in girls compared to boys. However, the availability of HSM data from post-pubertal males and females allowed us to investigate if there are any lasting effects of pubertal timing on proximal femur shape in both sexes.The relationship between FNW and variation in femoral head have been previously investigated in relation to both osteoporotic fracture and hip OA. For example, Castano-Betancourt et al. reported an association between wider FNW and higher risk of incident hip OA . In termTo our knowledge, this is the first study to investigate cross-sectional relationships between pubertal stage and proximal femur shape derived from SSM applied to hip DXA scans obtained concurrently. Our findings are consistent with a previous study by Pujol et al. in boys aged between 9 and 16 years, who found that the size of femoral head and greater and lesser trochanters increased with age . The prePubertal growth might represent a sensitive period for the development of an unfavourable bone phenotype leading to increased risk of fracture or OA in later life. As suggested by Bass et al., during periods of fast growth (as in puberty) specific bone regions might be more responsive to genetic and/or environmental stimuli, compared with periods of steady growth or with stages near or at completion of growth . ConsistPrevious research has found relationships between pubertal timing and adverse musculoskeletal outcomes in later life. For example, a study based on UK Biobank reported associations between early menarche and increased risk of OA as well as between later menarche and increased risk of OP . Similar4.1To our knowledge, this study represents the first application of SSM to describe variation in proximal femur shape in adolescents. Another strength is our use of growth tempo as a measure of pubertal timing, given its close relationship with skeletal maturation. A further advantage of growth tempo is that this relies on objective measurements, in contrast to Tanner stage, which was determined in ALSPAC by self-completed questionnaires. Use of PHV as a measure of puberty is supported by previous good agreement between PHV and secondary sexual characteristics, such as testicular volume  and age 5We investigated relationships between pubertal timing (as reflected by height tempo) and proximal femur shape in a large population-based cohort of adolescents. At age 14, we found strong cross-sectional associations between tempo and multiple HSMs in males, together suggesting that as puberty advances, FNW increases, both the lesser and greater trochanters enlarge, and there is some re-shaping of the superolateral aspect of the femoral head. Whereas these relationships were much weaker in females, this is likely to reflect the fact that the great majority had already reached PHV by this time. Taken together, our results indicate that significant changes in hip shape occur during puberty, including aspects of shape which may be related to future risk of hip OA and/or fracture. On the other hand, little relationship was observed between tempo and proximal femur shape derived from DXA scans performed at age 18, in either sex, suggesting that age of puberty does not exert lasting effect on proximal femur shape.Conceptualization JT, LP, MF; Data curation MF, JG, RA; Formal analysis MF; Funding acquisition MF, LP, JT; Investigation MF; Methodology JG, RA, MF; Software JG, RA; Supervision JT, LP; Writing - original draft MF; Writing - review & editing MF, JG, RA, LP, JT.Medical Research Council and the Wellcome Trust (ref: 102215/2/13/2) and the University of Bristol provide core support for ALSPAC. MF was supported by a Wellcome Trust PhD studentship (ref: 105504/Z/14/Z). LP works in the Medical Research Council Integrative Epidemiology Unit at the University of Bristol which is supported by the Medical Research Council and the University of Bristol (MC_UU_00011/1). A comprehensive list of grants funding is available on the ALSPAC website . Age 17 clinical assessment was specifically funded by Wellcome Trust (084632/Z/08/Z).The UK This publication is the work of the authors and MF will serve as guarantor for the contents of this paper. None of the funders had any influence on data collection, analysis, interpretation of the results, or writing of the paper.All authors have no conflicts of interest to declare.


Lactobacillus species. The number of bacterial species in the chicken reproductive tract significantly increased following sexual maturation. Core genera analysis detected 21 of common genera in the maternal magnum and cloaca, descendent egg shell, egg white, and embryo gut. Some elements of the maternal oviduct microbiota appear to be transferred to the embryo through the egg white and constitute most of the embryo gut bacterial population.The transferred microbiota from mother to baby constitutes the initial infant gastrointestinal microbiota and has an important influence on the development and health of infants in human. However, the reproductive tract microbiota of avian species and its inheritance have rarely been studied. We aimed to characterize the microbial community in the chicken reproductive tract and determine the origin of the chicken embryo gut microbiota. Microbiota in four different portions of chicken oviduct were determined using 16S rRNA metagenomic approach with the IonTorrent platform. Additionally, we analyzed the mother hen’s magnum and cloaca, descendent egg, and embryo gut microbiota. The microbial composition and relative abundance of bacterial genera were stable throughout the entire chicken reproductive tract, without significant differences between the different parts of the oviduct. The chicken reproductive tract showed a relatively high abundance of  The vaginal microbiota of human changes to a Lactobacillus species- or other lactic acid bacteria-dominant community with sexual maturity and becomes less diverse and enriched for Lactobacillus species during pregnancy7. These changes in the vaginal microbiota are known to maintain a low pH and provide bactericidal substances to prevent pathogen infection and growth. In addition, the microflora of the reproductive tract is transferred to babies during natural delivery, constituting the initial gastrointestinal microbiota of infants9, which has an important influence on infant development and health10. Moreover, human studies have demonstrated the presence of microflora in the upper reproductive tract, with higher species diversity and lower frequency of Lactobacillus compared to the vaginal microbiota12. Although the core microbial features and roles of the microbiota in the upper reproductive tract have not been precisely determined, disruption of its normal composition is related to preterm birth and uterine-related diseases14. It has also been suggested that the bacterial community initially colonizes the gut of the fetus through the placenta in utero16.The presence and composition of normal microflora in the female reproductive tract have been previously studied in humans, non-human primates, and other mammals17. However, in these species, the vagina has a unique microbiota with low levels of lactobacilli and the pH of the vagina is near neutral, except in the chimpanzee and some baboon species19. In addition, the roles of the vaginal microbiota in these animal species have not been fully elucidated.Studies examining the microbiota of the reproductive tract lining, especially the vagina, have also been conducted in non-human primates and livestock animalsalmonella species, and vertical transmission of these pathogens to offspring have been described in previous studies24. Currently, the gut microbiota of newly hatched chicks is thought to originate from fecal or environmental contaminants attached to egg shells25. A recent study has suggested microbiota inheritance from mother hens to chicks based on a comparison of their fecal and gastrointestinal microflora; maternal hen-derived microbiota transmission to the embryo via the egg formation process in the oviduct has also been suggested26. However, to date, the association between the mother hen’s oviduct, feces, and egg shell microbiota and that of its offspring have not been studied simultaneously using a metagenomic approach with next-generation sequencing (NGS) technology. In this study, we aimed to investigate the microbial community throughout the chicken oviduct and its variation following sexual maturity, as well as the correlation between the maternal oviduct and chicken embryo microbiota.In contrast, the microflora in the oviduct of avian species has rarely been studied, although colonization of the reproductive tract of poultry by bacterial pathogens, including SWe analyzed the microbial communities in a total of 92 samples originating from commercial and specific pathogen-free (SPF) hens, their descendant eggs, and embryos. Following sequence processing and sample filtering, we sorted 2,843,017 quality reads  into 2,255 (165.57 ± 92.43) operational taxonomic units (OTUs) using a sequence identity cutoff of 99%. Negative control resulted 32 raw sequences, all of them were filtered out during sequence processing step. All samples were rarified to 5,000 reads.Firmicutes (43.65% ± 22.65%), Proteobacteria (39.44% ± 22.07%), Fusobacteria (8.06% ± 10.12%), Bacteroidetes (5.47% ± 3.57%), and Actinobacteria (2.86% ± 1.84%) at the phylum level , Lactobacillus (11.13 ± 7.47%), Fusobacterium (7.76 ± 9.89%), Megamonas (4.93 ± 5.70%), Bacteroides (2.37 ± 2.09%), Staphylococcus (2.15 ± 6.59%), Diaphorobacter (2.14 ± 1.71%), and Enterococcus (1.29 ± 0.89%) , unclassified Lactobacillus species (36.11%), L. reuteri (2.11%), L. delbrueckii (1.09%), and four minor (<1%) Lactobacillus species: L. agilis, L. helveticus, L. iners, and L. vaginalis.We collected 16 samples from different sections  of four oviducts of the egg-laying Korean commercial breed hens to analyze the composition of microbial communities in the chicken reproductive tract. Pairwise permutational multivariate analysis of variance (PERMANOVA) was conducted based on an unweighted UniFrac matrix. No significant differences in microbial composition along the chicken reproductive tract were observed Table . Over 999%) Fig. . At the To examine variations in the chicken reproductive tract microbiota according to breed, we collected 16 magnum samples from 34 weeks-old SPF hens. Of them, we used 13 data samples that passed quality filtering. At the phylum level, Firmicutes (32.48% ± 21.36%), Proteobacteria (31.40% ± 12.73%), Bacteroidetes (25.20% ± 15.02%), and Actinobacteria (10.09% ± 5.39%) accounted for >99% of the microbiota of magnum in SPF breed hen. Fusobacteria only accounted for 0.22% ± 0.42% of the population, while it accounted 6.902% of the microbiota from the Korean commercial breed Fig. . In contProteobacteria (56.56%), Firmicutes (26.00%), Actinobacteria (13.37%), and Bacteroidetes (3.53%) accounted for >99% of the microbiota in the immature hen magnum , Faecalibacterium (7.63 ± 5.58%), Lactobacillus (4.82 ± 5.36%), Sphingomonas (3.96 ± 4.24%), Propionibacterium (2.15 ± 2.68%), Janthinobacterium (2.05 ± 3.83%), Bradyrhizobium (1.91 ± 2.32%), Bacteroides (1.83 ± 3.57%), Acinetobacter (1.79 ± 0.75%), Corynebacterium (1.77 ± 2.34%), Oscillospira (1.43 ± 2.39%), and Staphylococcus (1.39 ± 2.50%)  Fig. .The Faith PD and Shannon index value of the immature hen group were significantly lower than those of mature hens and showed large individual variance Fig. . In the 27 to identify key genera discriminating the microbiota of mature hens from those of immature hens. Of the 281 observed taxa at the genus level, unclassified Nocardiaceae (W = 277), Bradyrhizobiaceae (W = 277), and 0319-6G20 (W = 250) and genus Flavobacterium (W = 278), Megamonas (W = 256), and Bradyrhizobium (W = 253) showed a significant difference (p < 0.05) in abundance between microbiota in the mature and immature SPF hen magnum. Unclassified Nocardiaceae, Bradyrhizobiaceae, and 0319-6G20 and genus Bradyrhizobium were relatively abundant in the immature hen magnum and genus Flavobacterium and Megamonas were relatively abundant in mature hen magnum  of mother hens, egg shells (n = 13), egg white (n = 14) from descendent eggs, and the cecum (n = 14) of descendent chicken embryos of the SPF hens used for magnum sampling.The relative taxa abundance plots at the genus level showed that egg white and embryo cecum had a similar microbial composition with lower diversity than mother hen cloaca or magnum Figs . In the 28 analysis was performed in all directions. In this analysis, egg white and embryo samples were grouped into same group for better sink prediction. The results revealed that the egg shell microbiota contributed approximately 63% of the embryo cecum and egg white microbiota. When egg shell was assigned as the sink, the magnum and cloaca microbiota contributed 28% and 17%, respectively, of the egg shell microbiota. Unknown source contribution accounted over 50% in cloaca and magnum  with 999 permutations. The result revealed that egg white and embryo cecum were very similar to each other . However, egg white and embryo combined groups were too different from other groups to be compared; the egg shell , cloaca  and magnum . To elucidate the contribution of the microbial community in the mother hen’s magnum and cloaca, or egg shell to the egg white or embryo gut microbiota, SourceTracker33. The vaginal microbiota of healthy reproductive women is dominated by Lactobacillus species1. In contrast, in other mammalian animals, Lactobacillus species make up a very small fraction of the total vaginal microbial population and alpha diversity indexes are notably higher than in the human vaginal microbiota, suggesting that Lactobacillus dominance and low species diversity are unique to the human vagina19. In addition, the dominant bacterial genera in the reproductive tract of these non-human animal species are different from one another19. However, the microbiota of non-mammalian animals, including avian species and reptiles, has rarely been studied. Our study aimed to characterize the microbiota of the chicken reproductive tract and determine the influence of sexual maturity on microbial population. Unlike in humans, where the vaginal and upper reproductive tract microbiota are significantly different, the mature hen oviduct microbiota did not show significant differences along the tract. However, in order to ensure this result, large number of samples will be needed in further study. The upper reproductive tract microbiota more closely resembled the human upper reproductive tract microbiota than the lower reproductive tract microbiota with regards to the relatively low frequency of Lactobacillus and high species diversity12. The chicken reproductive tract microbiota was predominantly comprised of Firmicutes, Proteobacteria, Bacteroidetes, and Actinobacteria. At the genus level, Pseudomonas, Lactobacillus, Megamonas, and Bacteroides were most abundant and represented the core bacterial genera in the mature hen reproductive tract. These major genera were apparently different from those present in the reproductive tract microbiota of other animals19. Lactobacilli were detected in all mature hen oviduct samples; although their relative abundance (12.19% ± 8.88%) was lower than in the mature human vaginal microbiota1, it was higher than in other mammalian species34. While human infants delivered naturally receive lactobacilli from the microbiota present in the mothers’ vagina, the chicken embryo gut had only a very low number of lactobacilli. These results suggest that the lactobacilli in the chicken oviduct do not transfer to offspring and have a different role in the chicken and human reproductive tract9.The human vaginal microbiota and its roles in the mother and infants have been described in several previous studiesPseudomonas species in the reproductive tract and embryo are uncertain. Most Pseudomonas spp. detected in this study were unclassified below the genus level (86.8% of reads assigned as Pseudomonas) and 12.4% of these were P. veronii, a member of the P. fluorescens group35. Though the role of P. veronii in animals is unknown, based on recent studies, it may be involved in protecting the reproductive tract against bacterial pathogens or parasite infection38.The reasons underlying the prevalence and dominance of Megamonas spp., which were not detected in the immature chicken oviduct, were detected in all mature hen oviduct samples. These species were also detected in most cloaca and egg shell samples. However, this genus was not detected in any of the egg white and embryo samples, except for one embryo sample with 0.1% abundance. These findings imply that although Megamonas species present in the mature hen reproductive tract, they cannot pass through the barrier between the egg shell surface and egg white. Similar to Megamonas species, some bacterial species originating from the mother hen oviduct were unable to pass the egg shell-shell membrane barrier resulting in low species diversity in the egg white and embryo ceca. These species could play a role in protecting the reproductive tract and eggs against infection rather than constituting part of the offspring microbiota. Therefore, the interaction between hen and these species should be studied to understand the function of the reproductive tract microbiota of hen.Microbiota in magnum samples between Korean commercial breed and SPF chicken breed showed taxonomic difference in this study. However, we used only four oviducts from Korean commercial breed chickens. This was not enough number to confirm characteristics of microbial community in those samples. To understand the relationship between reproductive tract microbiota of hen and factors influencing on it, adequate number of samples will be needed in further study. Also, though we only took account of breed as a factor that influence composition of microbiota in chicken reproductive tract. However, the other important factors, including diet, immune status, and environment should have been considered.Propionibacteria and Streptococci from chicken embryo cecum samples after enrichment, while no bacteria were cultured from egg white samples. Although it is unknown how live bacteria are transferred to the embryo gut, evading the antimicrobial substances in the egg white, we assume that some bacteria in the egg white utilize their own strategies for survival, similar to Salmonella species, until the albumen is subsequently diluted with amniotic fluid, sub-embryonic fluid, or yolk during incubation and then absorbed into the embryo42. We failed to confirm the similarity between egg white, embryo, and the other sampling groups using ANOSIM. The SourceTracker2 test results showed the possibility that the over half of the egg white and embryo microbiota originated from the egg shell and that the maternal cloaca and oviduct microbiota contribute to the egg shell microbiota though the lack of sampling of environment near eggs limits this inference. Also, small sampling size limits this inference, therefore more study with large number of samples will be needed in a further study. Nevertheless, these results are somewhat consistent with the previous study of Ding et al.26, which suggested microbiota inheritance from mother hens to chicks based on a comparison of maternal feces and embryo microbiota. However, we included reproductive tract and egg white samples in our study and Halomonas species, picked as core bacteria of the maternal and embryo gastrointestinal microbiota by Ding et al.26, were only observed in one SPF egg white and three commercial Korean chicken oviduct samples in our study, with 0.02–0.04% relative abundance per sample. Halomonas species are frequently found in the contaminated saline, and the previous study did not include clean buffer only sample. Therefore, contamination of buffer by Halomonas species could be a reason of large abundance of Halomonas species in maternal feces and embryo microbiota in the previous study.Based on results of this study, it appears that the chicken embryo obtains its intestinal microbiota from the egg white prior to birth. The embryo and egg white samples were grouped together in the PCoA plots and were not significantly different in PERMANOVA and ANOSIM. We could culture few numbers of bacterial species including In this study, 21 taxa at genus level were observed commonly across the maternal cloaca and magnum, descendent egg white, egg shell, and embryo. These species made up >99% of the embryo microbiota, implying the nearly all of the chicken embryo microbiota is inherited from the maternal cloaca and/or oviduct. Eight genera were found in the magnum, egg white, and embryo intersection, but not in the cloaca and egg shell, and two genera were found in the cloaca, egg shell, egg white and, embryo intersection, but not in the magnum. The finding that no shared phylotype was found in the egg shell, egg white, and embryo intersection, also supports the hypothesis that bacteria in the cloaca and oviduct colonize the egg shell surface and egg white prior to other environmental bacteria. The colonized bacteria become the major component of embryonic microbiota; however, how transfer of the microbiota occurs remains unknown and still it is necessary to investigate the correlation between external environmental and embryonic microbiota. The relative abundance of the 21 common species was lowest in the magnum and the phylogenetic diversity of the magnum was higher than the other groups, suggesting that the oviduct microbiota has a effect on the cloaca microbiota and hence affects the egg shell, egg white, and embryo microbiota. In our other experiment, we could suggest that microbiota in hen cloaca consists of bacteria derived from rectum and oviduct. However, cause the results of this study are based on DNA sequence analysis, large number of those bacteria could be dead or not replicable in the egg white.The presence of 110 phylotypes at the genus level found solely in the oviduct raises the question of their origin, although they only accounted for 2.4% of the bacterial population. The roles of these 110 genera and the other bacterial genera in the oviduct of host hens remain unknown.To the best of our knowledge, this is the first study to examine mother hen oviduct, descendent egg, and chicken embryo microbiota using a metagenomic approach. Our results suggest that the bacterial genera diversity of the oviduct microbiota increases as chickens mature. The mature chicken reproductive tract microbiota showed different composition patterns compared to human and non-human mammals. Certain bacterial species present in the maternal oviduct microbiota comprised most of the embryo ceca bacterial population, though a small number of them could be cultured, indicating that the maternal oviduct microbiota could be partially transferred to offspring during egg formation. These findings suggest that egg white, normally considered as sterile, contains seed of bacteria that will become gut microbiota of embryo. These results could serve as the basis for studying the reproductive tract microbiota of other chicken breeds and different avian species. In addition, our results provide a useful reference for the analysis of microbiota changes in the reproductive tract of avian species with reproductive tract diseases or egg-transmitted pathogen infections.Four fresh bodies of 32-weeks-old commercial Korean laying hens were donated by a local farm. The mucosal surface of each part of the oviduct  was aseptically scraped with the back of a scalpel blade. The exfoliated mucosa and mucus was collected in 1 mL of sterilized phosphate buffered saline (PBS).All experiments involving chickens were conducted according to the guidelines of the Institutional Animal Care and Use Committee (IACUC). The animal experiments were approved by the IACUC of Konkuk University .Twenty-five SPF hens were raised in isolation from the age of 14 weeks. The hens were fed with commercial chicken feed without any probiotics and antibiotics. Pre-lay oviduct samples (n = 8) were collected from 23 weeks-old hens. Artificial insemination was conducted every week while the hens were laying to produce fertilized eggs. The semen was donated from a local layer farm. Descendant eggs were collected from each hen and an area of at least 4 cm² on the egg shell surface was swabbed with a CLASSIQ Swab , which was then suspended in 2 mL of PBS on the day of lay. In order to investigate possibility of transfer of environmental bacteria from egg shell to chicken embryo gut, we did not disinfect the egg shell and handled egg with sterilized instruments before swabbing. The cloaca of hens was swabbed with the CLASSIQ Swab and then suspended in 2 mL of PBS; 4 mL of egg white was collected from each egg using a syringe with a 17 G needle. Some of the fertilized eggs from each mother hen were incubated for 18 days and the cecum of the 18 day-old embryos was then collected and chopped using sterilized surgical instruments. The chopped ceca were transferred into 1 mL of sterilized PBS for DNA extraction. Oviduct samples (n = 16) were collected from 34 weeks-old laying hens. The magnum of the oviducts, collected from 23 weeks-old immature SPF hens and 34 weeks-old laying SPF hens, were scraped with the backside of a scalpel blade and suspended in 1 mL of PBS and stored at −20 °C until DNA extraction. In total, 24 oviduct, 14 egg white, 14 egg shell, 14 cloaca, and 14 chicken embryo cecum samples were used for DNA extraction and sequencing.DNA was extracted from all PBS suspended samples using the DNeasy blood and tissue kit  according to the manufacturer’s instruction. DNA extraction from PBS used for sample preparation was conducted as negative control. The V2, V3, V4, V6-7, V8, and V9 regions of the 16S rRNA gene were amplified with the primer sets from the Ion 16S Metagenomics Kit . Sequencing was conducted using the Ion S5 XL sequencer and Ion 530 chip.43 was used as the analysis pipeline and Greengenes44 (13_8 release) was used as a 16S rRNA sequence reference. The first 15 bases of all reads were trimmed to achieve a length of 150 bases and Phred quality score >15. The reads were denoised using dada2 and chimeric sequences were identified using the vsearch implemented in QIIME2 with a closed-reference algorithm. The sequences flagged as non-chimeras were retained. Sequence reads with >99% identity were clustered into a single OTU by vsearch45. OTUs with <10 copies were considered as artifacts and deleted. The OTUs were then classified using the naïve-Bayes classifier. To remove sequencing effort heterogeneity, samples were rarefied to 5,000 sequences. Of the 96 sample sequencing data set, two oviduct samples, which failed to yield 5,000 high quality (>15) reads, and one oviduct and one egg shell samples, showing too-different composition compared to other samples in the same location group, were excluded from analysis.QIIME246. To assess the association between microbial community and sampling location within the oviduct, egg, and embryo gut, pairwise PERMANOVA and ANOSIM analysis implemented in QIIME2 was performed on an unweighted UniFrac distance matrix of 63 samples. The significance of PERMANOVA was obtained by 999 permutation tests.The relative taxa abundance of the groups is presented as a mean % value. Alpha diversity was measured using the Faith PD and Shannon indexes. Beta diversity plots were constructed to visualize the categorical partition of the samples using unweighted UniFracDifferential abundance analysis by Analysis of Composition of Microbiomes (ANCOM) was used to identify significantly and differentially abundant genera in each sampling location.All experiments involving chickens were conducted according to the guidelines of the Institutional Animal Care and Use Committee (IACUC). The animal experiments were approved by the IACUC of Konkuk University .Supplementary file 1Supplementary file 2