These pigments only partially matched the opsin repertoire detected by query of the Atlantic halibut genome. We conclude that the Atlantic halibut undergoes a complex re-organization of photoreceptors at metamorphosis resulting in a multi-mosaic retina adapted for a demersal life style.Fishes often have cone photoreceptors organized in lattice-like mosaic formations. In flatfishes, these lattices undergo dramatic changes during metamorphosis whereby a honeycomb mosaic of single cones in the larva is replaced by a square mosaic of single and double cones in the adult. The spatio-temporal dynamics of this transition are not well understood. Here, we describe the photoreceptors and mosaic formations that occur during the larva to juvenile transition of Atlantic halibut from the beginning of eye migration to its completion. To gauge the possibility of colour vision, visual pigments in juveniles were measured by microspectrophotometry and the opsin repertoire explored using bioinformatics. At the start of eye migration, the larva had a heterogeneous retina with honeycomb mosaic in the dorsonasal and ventrotemporal quadrants and a square mosaic in the ventronasal and dorsotemporal quadrants. By the end of metamorphosis, the square mosaic was present throughout the retina except in a centrodorsotemporal area where single, double and triple cones occurred randomly. Six cone visual pigments were found with maximum absorbance (λ During this period of transformation, which can last from days to weeks depending on the species3, the animal experiences a progressive change in the perception of its surroundings resulting from the shifting visual fields of both eyes and increasing proximity to the ocean floor. In parallel, the diet changes from a preponderance of pelagic plankton consumed by pre-metamorphic larvae to small benthic invertebrates favoured by post-metamorphic juveniles3. In some species, like the common sole (Solea solea) and the Senegalese sole , metamorphosis further entails a shift in circadian rhythm from diurnal to nocturnal4.Flatfishes (order Pleuronectiformes) are peculiar among teleosts in that they undergo a pronounced metamorphosis whereby a bilaterally symmetric, pelagic larva transforms into a flattened, demersal juvenile with both eyes on the same side of the headPseudopleronectes americanus, and Atlantic halibut, Hippoglossus hippoglossus, have shown the presence of a single morphological type of cone photoreceptor prior to the start of eye migration6. This cone forms a honeycomb  mosaic throughout the retina characterized by six neighbours surrounding each photoreceptor. Microspectrophotometric measurements from cone photoreceptors of pre-metamorphic winter flounder larvae revealed a single visual pigment with maximum wavelength of absorption (λmax) at 519 nm7. Post-metamorphosis, the retina comprised two types of morphological cone types (single and doubles) forming a square mosaic whose repeating unit consisted of a single, centre cone, surrounded by four double cones (the latter made up of two cones apposed together sharing a double membrane partition)5. The visual pigment in the single cones peaked at 457 nm, whereas the double cones could be equal members, with a visual pigment peaking at 531 nm, or unequal, with one member possessing a visual pigment with λmax at 531 nm and the other at 547 nm7. Thus, the retina of winter flounder transformed its cone mosaic and visual pigment repertoire during metamorphosis. In addition, rod photoreceptors were only present after metamorphosis, with a visual pigment peaking at 506 nm7.Despite these profound alterations to the anatomy and ecology of flatfishes, their visual system during metamorphosis has seldom been examined and is poorly understood. Morphological investigations into the larval retina of winter flounder, in-situ hybridization with riboprobes against the various opsin  mRNAs in winter flounder showed a single rh2 opsin being expressed in the cones prior to metamorphosis and four others  post-metamorphosis8. In the post-metamorphic flounder, single cones expressed sws2 transcript whereas double cones expressed rh2 or lws (a single opsin transcript per member) and rods expressed rh1. By raising larvae in water containing 3H thymidine and analyzing its retinal uptake, these authors further concluded that double cones central to the peripheral growth zone should form from coalescing single cones8. As such, two mechanisms of square mosaic formation would exist during metamorphosis of flatfishes: one operating at the peripheral growth zone producing a square mosaic from differentiation of progenitor cells, and the other more centrally, requiring the re-arrangement of pre-existing, differentiated single cones.Further work using in-situ hybridization observations from Atlantic halibut larvae toward the end of yolk sac absorption  showed expression of four opsin transcripts  in the single cone retina9. The vast majority (> 90%) of cones expressed rh2 whereas sws2 and lws were only found in about 10% of photoreceptors. Nonetheless, like rh2, sws2 and lws were expressed throughout the retina, whereas sws1 was restricted to the ventral retina10. A square mosaic formation showing rh2 and lws transcript expression was later reported in the juvenile (6 month old) retina11. Thus, the chromatic organization of photoreceptors during the time of metamorphosis in this species remains unknown. Furthermore, although the appearance of double cones and a square mosaic were reported by morphology around the start of eye migration, and such mosaic was present in the central retina 30 days later (100 days post-hatching)6, the spatial dynamics of square mosaic formation remain unresolved.In contrast to the findings in winter flounder, This study was undertaken to reveal the morphological organization of photoreceptors during the larval to juvenile transition of Atlantic halibut, from the start of eye migration to its completion. Combining these observations and morphometric measures of the lens, the spatial resolving power was derived for different regions of the retina. Microspectrophotometric measurements of visual pigment absorbance from post-metamorphic fish and opsin bioinformatic analyses were also undertaken to gain insight into photoreceptor chromatic diversity and opsin evolution with respect to other flatfishes.The youngest Atlantic halibut examined  and days from fertilization, 96) were bilaterally quasi-symmetrical with a compressed, oval shaped body and similar pigmentation on either side of the body Fig. A,E. In tAll fish examined had elliptically shaped eyes and retinas Fig. . The eyeThe morphological trends were the same for the migrating and non-migrating eye. At 720 ATU, the retina had two main types of cone photoreceptors: single and double cones , the honeycomb mosaic was absent from the retina and other cone formations had emerged Figs. , 4 and 5As per the trends in the dorsonasal retina, the ventral retina at 878 ATU consisted of square mosaics with variable jitter in the lattice Fig. A,B,D. Atin-situ hybridization experiments were performed with two previously established riboprobes, one tagging rh2 opsin transcript and the other rod (rh1) opsin transcript9. At all locations, whether characterized by the honeycomb mosaic or by the presence of double cones, the retina of Atlantic halibut at 720 ATU labelled prominently with the rh2 riboprobe along the inner segment myoids of cones  revealed profound retinal transformations  ± SD at 431 ± 7 nm (n = 8)    and zebrafish (Danio rerio), the positions of the predicted opsins and their flanking genes were in similar orientations   was incorrectly annotated as it had an unusual six exon structure and overlapped the regions of two other rh2 sequences , SWS2 (accession: XP_034440595.1) (99%), RH1 (100%), RH2 (accession: XP_034442261.1) (100%), and LWS (99%)  and barfin flounder (Verasper moseri) all had a valine residue at site 300, but Atlantic halibut differed from these other two flatfishes with an A124G substitution. However, this A124G substitution does not impact the λmax of the corresponding visual pigment12.Based on phylogenetic analyses, Atlantic halibut opsins were classified as SWS1, SWS2A (accession: XP_034440595.1), SWS2B (accession: XP_034441481.1), RH1, RH2B (accession: XP_034442261.1), RH2C (accession: XP_034442262.1), and LWS and are referred to as such for the remainder of the manuscript Fig. –S9. An Amax of reconstituted barfin flounder opsins13 corresponded well with some of our microspectrophotometry records of associated visual pigments and were therefore used as references for inferring the λmax of Atlantic halibut opsins when bound to retinal as the chromophore. Therefore, the λmax values of these opsins were predicted to be around 367 nm (SWS1), 416 nm (SWS2B), 494 nm (RH1), 506 nm (RH2B), and 490 nm (RH2C)  and reached the centre of the retina by 100 days post-hatching6.The retina of Atlantic halibut undergoing eye migration experienced major changes in photoreceptor types and distributions. The single cone type organized in honeycomb mosaic reported at the end of the yolk sac period (40 days post-hatching)ics Fig.  toward t6 can be resolved by realizing that there are two independent mechanisms that create double cones and the square mosaic in the retinas of flatfishes8. One, common to all fishes, operates at the peripheral growth zone (ora serrata) through differentiation of progenitor cells into photoreceptors that become part of established (adult) mosaics, like the square mosaic16. The other appears to occur only among fishes with indirect development . Here, there seems to be a re-arrangement of existing cones in central parts of the retina (present prior to the onset of metamorphosis8) that leads to square mosaic lattices with substantially more jitter than those forming directly at the periphery, as per our study. In other words, previous authors6 did not disambiguate between these two mechanisms leading to potential confusion over the progression of square mosaic formation in the non-peripheral retina prior to the start of metamorphosis.The seeming controversy between our study and previous work8. As in our study, these authors observed that, at the start of eye migration, the ventronasal and dorsotemporal quadrants had double cones as part of emerging square mosaics whereas the dorsonasal and ventrotemporal quadrants had single cones in honeycomb formation8.The progression of double cone and square mosaic appearance reported here agrees with similar observations in winter flounder where two patches of retina, located in the ventronasal and dorsotemporal regions, were the first to express new opsin transcripts simultaneously  from the start of metamorphosis6 pertains to the appearance of triple cones in the central retina as metamorphosis progressed. Upon completion of eye migration, these cones occupied a large area of central retina as part of random distributions along with double and single cones, whose distributions were also random. Triple cones have never been reported during metamorphosis of flatfishes8 but are present in the centrodorsal retina of several fish species during metamorphosis20. Some fishes, which are demersal or live in low light environments as adults, retain a high density of triple cones in a restricted area of centrodorsotemporal retina21 often located next to a fovea22. Other, nocturnal fishes, like some species of holocentrids, also have triple cones. They are primarily located in regions of high cone density, along a central meridian, but constitute less than 0.5% of the total cone population23.Another major discrepancy between our study and previous work18. Two observations suggest otherwise, however. First, in Atlantic halibut, triple cones were rare in the ventral retina and scarce in the nasal compared to the temporal retina. If triple cones were part of a necessary transitional mosaic leading to the square mosaic, then the ventral and nasal regions of the central retina would not have developed such a mosaic or, at least, not fully. Second, triple cones are retained in the centrodorsotemporal retina of adults of other fish species22 suggesting a functional role within the random mosaics that they are a part of.Based on the appearance of triple cones around the time when double cones and square mosaics start forming in the retinas of some marine fishes, it has been hypothesized that triple cones may be part of a transitional mosaic between the larval honeycomb mosaic and the adult square mosaic8, existing single cones must have coalesced to form the square mosaic (a conclusion previously reached for the winter flounder by other authors8). Electron microscopy evidence suggesting such cone fusion has been provided for the black bream, Acanthopagrus butcheri, and the West Australian dhufish, Glaucosoma hebraicum, two marine fishes that also undergo metamorphosis19.Our results support two different mechanisms of square mosaic formation in the retina of Atlantic halibut during metamorphosis. At 720 ATU, the centrodorsonasal and centroventrotemporal areas had only singles cones and these were arranged in honeycomb formation. Because a square mosaic was present in these regions of the retina by the end of metamorphosis, and no new cones are known to differentiate in the main retina of flatfishesSalmo salar16. These observations suggest a direct path of square mosaic formation, as established for other fishes.Near the periphery, the regularity of the square lattice contrasted with the jitter present in multiple square mosaic regions of the central retina. At the growth zone, the square mosaic contained corner cones  was ~ 0.5º at the start of metamorphosis and ~ 0.3º by the end24.In the non-peripheral retina, spatial resolving power, our theoretical measure of visual acuity, was greatest in the ventrotemporal retina of the youngest Atlantic halibut examined. At the end of metamorphosis, the area of highest resolving power had shifted to the dorsotemporal retina. The values computed were nearly identical to those published for the plaice, 27. Demersal fishes, on the other hand, often strike at prey that contrasts against the bottom of the water body28. As such, the observed shift in area of greatest resolving power would be expected to maximize prey capture, the strongest determinant of fish growth and survival.The shift in area of greatest resolving power conforms with the foraging needs of the fish as it transforms from a bilaterally symmetric larva to a flattened, demersal juvenile. Pelagic fishes, including larvae, often have the highest cone densities in the ventrotemporal retina and strike at prey that contrast against the water background located in front of them or slightly above22. Spatial analyses of flatfish mosaics show that greater cone packing can be achieved through a combination of different cone morphologies (including the triple cone) compared to that from the square mosaic21. It has been argued, however, that a regular mosaic should provide better chromatic visual acuity due to the regular distribution of spectral inputs across the visual field30. For a fish that lives in habitats with low light, visual acuity based on chromatic contrast may not be as important as improving photon catch and, potentially, achromatic detection of targets.That the highest visual acuity in the postmetamorphic fish coincided with the area of densest triple cone presence suggests that the random mosaic associated with triple cones is not an unintentional by-product of development but serves a specific function. The adults of other demersal fishes have a similar triple cone area in the centrodorsotemporal retina, in the vicinity of where the highest cone densities are found21, we propose that triple cones serve an achromatic area of high visual acuity. Because of the ventral position of the optic nerve head, the area of random mosaic appears to view the forward horizon. It may therefore represent a specialized region for the early detection of large groundfish predators, like many species of elasmobranchs, that cruise the ocean floor in search of demersal prey. Such predators lack significant colour and would be readily detected achromatically by improving photon catch. Interestingly, photoreceptors in this area also have among the longest outer segments, further improving photon catch.In the random mosaic region, the ratio of the sum of triple and double cones to single cones is the same (~ 2) as that of double to single cones in nearby square mosaic regions. As such, the total ratio of longer to shorter wavelength input should be similar regardless of the mosaic, the major difference being the regularity of chromatic input. Based on these observations and the greater cone packing achievable with the random mosaicmax and bandwidth at half maximum of the rod visual pigment  suggested retinal  as the only chromophore in the retina31, as has been measured by High Performance Liquid Chromatography in starry flounder, Platichthys stellatus33. Co-expression of the S(431) pigment with another visual pigment [potentially the M(500) or M(514)] in a given single cone was common and may illustrate a progressive switch toward the longer wavelength-associated opsin as the juvenile moves to greater depths. A progression toward longer wavelength-absorbing visual pigments occurs in multiple cone types of the juvenile starry flounder33.Absorbance measurements from postmetamorphic retinas indicated the presence of at least two opsins, with associated visual pigments peaking at 431 nm and 457 nm, among the single cone population. The λ11. The updated opsin repertoire is consistent with those of other flatfish species, with six visual opsins reported for the common sole and the Senegalese sole21, eight for starry flounder32 and marbled sole, Pseudopleuronectes yokohamae34, and nine for turbot, Scophthalmus maximus35. In particular, expansion of the rh2 repertoire in Atlantic halibut follows findings in other flatfishes where rh2b and rh2c genes are common and rh2a is often absent or present as a pseudogene 35. Tandem duplications of sws2 genes are also commonly found in flatfishes34 and other teleosts36.The predicted proteins from the Atlantic halibut genome provided evidence for six visual opsin genes. Phylogenetic and tuning site analyses revealed that these opsins correspond to SWS1, SWS2A, SWS2B, RH1, RH2B, RH2C, and LWS. This expands the previous opsin repertoire known for Atlantic halibut which included SWS1, SWS2, RH1, RH2, and LWSmax of their visual pigments when bound to retinal only partially matched microspectrophotometric records. The predicted SWS2A opsin matched the S(457) visual pigment, RH1 corresponded to the rod(491) visual pigment, and the LWS opsin matched the L(550) visual pigment. The S and M pigments found by microspectrophotometry were not a good match for the SWS2B or RH2 opsins. Previous work comparing the λmax of M visual pigments in the starry flounder32 and the common sole21 to those of barfin flounder13 or marbled sole34  showed that the in-vivo measured pigments were significantly long wavelength shifted with respect to in-vitro determinations or predictions. With some opsins, this was the case despite having identical amino acids at all tuning sites between species21. These results suggest that alternative tuning sites or interactions between multiple tuning sites play important roles in determining the λmax of S and M visual pigments in flatfishes.Both the number of predicted opsins and the surmised λRetinal transformation at metamorphosis in Atlantic halibut is a complex process that prepares the animal for the visual ecology demands of a demersal life style. Photoreceptors organization changes from a honeycomb mosaic consisting of single cones to two novel formations: the square mosaic, which occupies most of the post-metamorphic retina, and a random mosaic consisting of single, double and triple cones located in a restricted region of the dorsotemporal retina. In parallel, a square mosaic of greater regularity forms directly from progenitor cells in the peripheral growth zone, and both mosaics coalesce during metamorphosis. The central region of greatest visual acuity shifts from the ventrotemporal to the dorsotemporal retina in accordance with the change in foraging behaviour that accompanies the transition from pelagic to benthic life style. The retina has the potential for colour vision containing a minimum of six cone visual pigments and one rod visual pigment. Such composition resembles that of other flatfishes that have been studied which show abundant expression of multiple S and M visual pigments, but diminished expression of UV and L visual pigments with age.15 photons m-2 s-1) provided by tungsten-halogen tubes . Peak hatching occurred at 14 days post-fertilization . Hatched larvae had a prominent yolk sac which was fully absorbed around 50 days post-hatching (~  320 ATUs). Pre-metamorphic larvae were fed a combination of freeze-dried Gemma Diamond 0.5 and 0.8 mm pellets (Skretting), added every 30 min throughout the day at a density of 2 pellets per fish, and Artemia nauplii, added twice a day at a density of 10–15 metanauplii ml−1 day−1. Fish nearing complete metamorphosis, or having completed it, were fed a mixture of Gemma Diamond 0.8, 1.0 and 1.2 mm every hour at a density of 3 pellets per fish and Artemia nauplii twice a day at a density of 5 to 10 metanauplii ml−1 day−1. Clay was added to the tanks every day to recreate the turbid water conditions found in nature.Atlantic halibut were reared from the fertilized egg in 100 L recirculating saltwater indoor tanks at a temperature of 7.5  ± 1.6 °C and maintained under artificial illumination  to reveal the cone mosaic31. Digital images of sections were acquired with an E-600 Nikon microscope equipped with a DXM-100 digital camera. Photographs were obtained using a Plan/Apo 60X/1.40 objective and further amplified 1.5 × with an optical tourette on the microscope . Observations of mosaic types in different sectors were carried out on 10 retinas (5 each from migrating and non-migrating eyes). From these, four retinas with the largest tangential mosaic area (0.0106 mm-2) spanning the region of widest cone ellipsoid cross sections to the bases of the outer segments were selected for density determinations and spatial analyses.Fish were euthanized and the entire bodies fixed in primary fixative  at 4ºC for a minimum of 72 h. The retina from the migrating and non-migrating eye were individually extracted, rinsed in 0.08 M PBS, and cut into four quadrants . The quadrants were post-fixed in secondary fixative (1% osmium tetroxide in 0.08 M PBS) for 1 h at 4ºC. Following a brief rinse in distilled water, the tissue was dehydrated through a series of solutions of increasing ethanol concentration, infiltrated with mixtures of propylene oxide and EPON resin, and embedded in 100% EPON resin. Retinal blocks were cut tangentially, in 1–2 µm steps, and stained with Richardson’s solution  at 4 °C for a minimum of 72 h. For a given fish, the head was processed as a whole or the eyes were extracted from it and processed individually. Following several rinses in 0.08 M PBS, the tissue was cryoprotected in sucrose solution  and embedded in 100% OCT medium (Cedar Lane Laboratories). The resulting blocks were cryosectioned in 7–10 µm steps in either tangential  or coronal (for heads) planes to reveal the cone mosaic or photoreceptors along their lengths in the medial retina, respectively. Serial sections were deposited cyclically on poly-L-lysine coated slides and hybridized with species-specific riboprobes against the rh2 and rh1 riboprobes were 591 and 447 bp long, respectively. The primers were as follows: rh2 forward 5’-GCTCAATAGAAACAACAGAC-3’, rh2 reverse 5’-GCCAGGACGACCAGAGACCA-3’; rh1 forward 5’-CTCAACAGCCAGAAGAAACA-3’; rh1 reverse 5’-GTAACGAGACCAGCCAACAA-3’. Each probe showed 70% similarity to the non-corresponding opsin.The 38. Briefly, this involved rehydrating the sections, permeabilizing them in 10 µg/ml proteinase K for 5 min, exposure to 0.1 M triethanolamine containing 0.25% acetic anhydride, dehydration, and overnight hybridization at 56 °C with 4 µg of cRNA probe in 50% formamide, dextran sulfate and goat serum. Following immunodetection with anti-Digoxigenin Fab fragments conjugated to alkaline phosphatase (1:3000) for 2 h at room temperature, the riboprobe was visualized with NBT/ BCIP substrate38. Cross hybridization of a riboprobe with the non-corresponding opsin did not take place as evidenced by the different level of label of photoreceptor myoids in the light-adapted retina  to extract the X–Y coordinates (centroids) of every morphological cone type in the field of view. The coordinates were then imported into a customized Matlab program that computed the Delauney tessellation of the field, from which the nearest neighbour distance of each individual cell was determined, as was their Voronoi domain area 39. Each analysis excluded “border cells”, i.e., those with uncertain nearest neighbour distances or Voronoi domain areas. In each case, the regularity index was defined as the mean divided by the standard deviation.Digital micrographs of tangential sections, each covering a 52 × 52 µm39.To assess whether the cone distributions analyzed had higher order (lattice-like) periodicity, a spatial auto-correlation analysis was carried out that examined the positioning of each cell with respect to all other cells across the mosaic. The Density Recovery Profile was derived from each autocorrelogram, providing a plot of the mean density of cells as a function of distance from each cell. The autocorrelogram permits the detection of higher order patterning and the Density Recovery Profile provides a measure of the exclusion zone surrounding each cell where other homotypic cells are less likely to be found than at further distances40.To assess whether cell distributions with low regularity indices were different from random distributions, their spatial statistics were compared to those of simulated random fields of cells matched for density and constrained by soma size. Non-random retinal mosaics of cells show greater regularity indices and exclusion zones to those from corresponding random simulations resulting in effective radii that are larger than if determined by soma size aloneStatistical analyses to assess differences in mosaic regularity and cone density between retinal sectors were based on analysis of variance (ANOVA) with post-hoc grouping tests  evaluated at α = 0.05 level of significance.N) (in cycles per degree) using the equation:-2) and PND is the posterior nodal distance (in mm)22. PND was approximated as the product of lens radius and 2.55 (the mean Matthiessen’s ratio for teleost eyes41). The photoreceptor cell density was computed from the sum of all cone types measured in a 0.0106 mm-2 area, with each double cone and triple cone contributing two and three cells, respectively. Based on the resolving power, the distance at which a given region of the retina would detect a 0.5 mm size food item, such as the typical food pellet encountered in aquaculture conditions or prey copepod consumed in nature, was computed.Theoretical determinations of spatial resolving power (in degrees of arc) were calculated as the inverse of the Nyquist frequency  objectives: 32/0.4 for the condenser and 100/1.20 for the objective. With the aid of reference measurements recorded through cell-free areas, individual photoreceptor outer segments were illuminated sideways with a measuring beam of rectangular cross section of ca. 2 × 0.6 μm. Absolute absorbance spectra were computed in 2 nm increments from the obtained transmittances (each spectrum consisted of an average of 8 scans). The solid spectra (fits) were derived from experimental data by Fourier filtering43.This analysis was performed on four post-metamorphic juveniles with mean weight ± SD and total length ± SD of 3.6 ± 0.8 g and 7.5 ± 0.5 cm, respectively. Individual fish were dark adapted for 8 h, following which the fish was euthanized, and the retina extracted under infrared illumination. Small pieces of retina were teased apart and prepared for viewing with the dichroic microspectrophotometer (DMSP) as per previous studies45 was used to fit the data with a combination of visual pigment absorbance curves using the equation46:ip is the absorbance of pigment i at light of wavelength λ, and p is an exponent resulting from the mathematical requirement that the absorbance function to be fitted be differentiable at the origin46. The variables ki are coupling constants resulting from the best fit of the model to the data. The visual pigment absorbance values used in the model were generated with an eighth-order polynomial template47 based on the λmax of visual pigments measured by microspectrophotometry. The use of templates ensures β-band representation of individual visual pigments, which is not always present in microspectrophotometry records.Because the S(431) absorbance spectrum showed a “hump” in the range 450–550 nm, suggesting the presence of multiple visual pigments, the Simplex algorithm48  using BLASTp (v.2.12.0). Predicted proteins with e-values < 1e-5 and percent identities ≥ 50% were retained. Duplicated results were filtered by accession number using R (v.4.1.0)49 and RStudio (v.1.4.1717)50. Locations of the corresponding coding sequences and their immediate flanking genes were compared to those in the reference genomes of turbot 51 and zebrafish  and used to further narrow down the predicted opsins using the NCBI Genome Browser and Gene Graphics52. Coding sequences that were eliminated from further analysis can be found in Supplementary Table Zebrafish visual opsins 54 and Qiagen CLC Sequence Viewer (v.8.0) (www.qiagenbioinformatics.com). Amino acid residue numbers were standardized to bovine rhodopsin (Accession: NP_001014890.1)55.To confirm the assigned opsin classes of the predicted proteins, opsin sequences reported previously57 . Phylogenetic trees were constructed with MEGAX58 using maximum likelihood and boostrap analyses (n = 100) and visualized using R and ggtree59. Sequences used in these analyses (Supplementary Tables https://www-ncbi-nlm-nih-gov.proxy.lib.sfu.ca/genbank) and SoleaDB60, with zebrafish VA opsins used as the outgroup.The predicted Atlantic halibut opsins were assigned to opsin subclasses using phylogenetic analyses and tuning sites from key amino acid residues for each of the visual opsinsAll animal use was approved by the Animal Care committees of Simon Fraser University (protocol # 1126B-10) and the University of Victoria (protocol # 2017–005), which abide by regulations set by the Canadian Council for Animal Care.Supplementary Information.


COL9A3 and TMPRSS3. Through exome sequencing of 108,415 cases and 329,581 controls, we observed rare coding associations with 11 Mendelian hearing loss genes, including additive effects in known hearing loss genes GJB2  and SLC26A5 . We also identified hearing loss associations with rare coding variants in FSCN2  and KLHDC7B . Our results suggest a shared etiology between Mendelian and common hearing loss in adults. This work illustrates the potential of large-scale exome sequencing to elucidate the genetic architecture of common disorders where both common and rare variation contribute to risk.To better understand the genetics of hearing loss, we performed a genome-wide association meta-analysis with 125,749 cases and 469,497 controls across five cohorts. We identified 53/c loci affecting hearing loss risk, including common coding variants in  A GWAS and exome-wide association study meta-analysis identifies 53 loci affecting hearing loss risk from over half a million individuals across five cohorts. Rare variants in Mendelian hearing loss genes contribute to hearing loss risk in adults. Disabling hearing loss is common, with ~466 million people affected worldwide . While existing technologies—such as hearing aids and cochlear implants—can ameliorate hearing loss, their use is limited by barriers to access, including cost, health policies and regulations, and social stigma associated with device use2. Furthermore, while these assistive devices typically provide some benefit, they do not address the chief complaint associated with acquired hearing loss: lack of hearing clarity, particularly in social and work environments (https://www.hearingloss.org/programs-events/patient-focused-drug-development-meeting). The Lancet Commission on dementia prevention, intervention, and care has identified untreated hearing loss in middle age as the top modifiable risk factor for dementia, but it is estimated that 67–86% of adults who may benefit from hearing aids do not use them3. These challenges, combined with a lack of therapeutics to stop or slow hearing loss progression, have contributed to its status as a growing global health issue. Novel therapies based on genetic evidence, therefore, will be crucial in addressing this unmet need.The loss of hearing can have a debilitating impact on quality of life, requiring major adjustments to day-to-day activities. Serious comorbidities are also associated with hearing loss including social isolation, depression, cognitive impairment, and dementia, which further deteriorate quality of life4. Mutations in over 150 genes (https://hereditaryhearingloss.com) account for over 50% of the cases. While autosomal recessive hearing loss is generally pre-lingual and non-progressive, autosomal dominant forms are mostly post-lingual (including adult onset) and progressive. The prevalence of hearing loss increases to 2.8/1,000 in primary school-age children and 3.5/1000 in adolescents5. The National Institute on Deafness and other Communication Disorders calculates that by the age of 45 ~2% of individuals have a disabling hearing loss, and this number increases to 50% in individuals over the age of 75. This increase in prevalence with age reflects a combination of late-onset hearing loss mutations, the cumulative effects of environmental factors such as exposure to noise and ototoxic drugs and, in aging individuals, the degenerative effects of age on the cochlea. These genetic and environmental insults primarily damage the structures of the inner ear, resulting in sensorineural hearing loss7.Hearing loss affects individuals of all ages, but its prevalence increases with age. Approximately 1-2/1000 babies are born with hearing loss12 suggesting that genetics, along with environmental factors, play a major role in determining an individual’s risk for developing hearing loss. Genome-wide association studies (GWAS) of hearing loss in adults have identified 61 common variant loci associated with the trait in Europeans20. Three of these studies20 have included genotyping and imputed data from UK Biobank as well. While the majority of these studies have established a common variant contribution to adult hearing loss, few reports have addressed the contibution of rare and low-frequency variation21.Heritability estimates for age-related hearing loss range as high as 36 and 70%18 published association results with hearing loss on ~50,000 Icelandic individuals with whole-genome sequence and ~50,000 individuals from UKB with exome sequence data, with imputation of larger samples into these variant sets. We have now expanded the rare variant analysis to exome-sequences from ~294,710 individuals in UKB and ~143,286 individuals from three other datasets. Here, we report findings from genome- and exome-wide association meta-analyses including 125,749 cases and 469,497 controls. Our analyses have identified 15 susceptibility loci that were previously not associated with hearing loss, to the best of our knowledge, and 15 rare variant associations that provide important insights into the biology of hearing loss in adults.Recently, Ivarsdottir et al.Me Personalized Medicine Cohort from Mount Sinai Health System, New York (SINAI), UK Biobank (UKB) and an additional study from Finland, FinnGen, for a total of 125,749 cases and 469,497 controls. To study rare and ultra-rare variants, we also generated exome sequence data and performed combined GWAS and exome-wide association study (ExWAS) on a subset of 108,415 cases and 329,581 controls across GHS, MALMO, SINAI, and UKB. Phenotypes were derived from ICD-10 diagnosis codes in GHS, MALMO, SINAI, and FinnGen, and combined self-report and ICD-10 codes in UKB .To study common variants, we performed association meta-analyses using genotyping and imputation across five cohorts: the Geisinger DiscovEHR study (GHS), the Malmö Diet and Cancer study from Malmö, Sweden (MALMO), the Mount Sinai’s BioP < 5 × 10−8) common (MAF ≥ 0.01) variants associated with hearing loss  and TMPRSS3 . Mutations in COL9A3, which is highly expressed in the ear, have been implicated in the autosomal recessive Stickler syndrome, in which hearing loss is prominent25, and tentatively in non-syndromic hearing loss27. High-throughput mouse knockout characterization from the International Mouse Phenotyping Consortium  indicates that Col9a3-null mice also have hearing loss28. TMPRSS3 is a type II membrane serine protease that localizes to the endoplasmic reticulum and plasma membranes, and is expressed in hair cells and supporting cells in the organ of Corti, the spiral ganglion, and the stria vascularis in the ear31. Mutations in TMPRSS3 cause congenital and childhood-onset autosomal recessive hearing loss32 but there is also evidence for hearing deficits in heterozygous carriers18.Top variants at two other loci were missense changes and thus also implicate specific genes: in 33, which indicated the presence of secondary association signals (joint P < 10−5) at eight loci . The COJO and FINEMAP methods disagreed on the presence of single vs. multiple association signals within five loci, three of which showed subthreshold (10−5 < P < 10−4) secondary associations in COJO. FINEMAP prioritized ten or fewer variants in top causal variant 95% credible sets for the top causal variant at eleven loci, including single putatively causal variants at four loci  and KLHDC7B , and intronic variants in CTBP2 (rs10901863) and PAFAH1B1 (rs12938775).The number of associated variants at the 50 autosomal loci ranged from eight to 1326. In order to assess the presence of multiple independent causal variants at each locus, we ran conditional analyses using GCTA-COJOhttps://www.gtexportal.org) project using coloc235. Across all GTEx eQTL tissues tested, we identified 19 genes mapping to 15 loci with evidence  for colocalization between the hearing loss association and an eQTL signal, in at least one tissue  making it difficult to prioritize causal genes at these loci based on eQTL data. Since GTEx did not include tissues from the ear, we used single-cell RNA sequencing data that were generated in-house from mouse cochleae to check the expression of the 19 genes in the ear  data for 48 tissues from the Genotype-Tissue Expression  rare variant (MAF < 0.01) associations in 25 genes, 15 of which had nonsynonymous variant or gene burden associations . After conditioning on independent common variants at each locus (Supplementary Data P ≤ 3 × 10−5) except for the CDH23 Asn1103Ser association . Of note, the lead common variant in CDH23 is also a missense (Ala371Thr) variant (MAF = 0.01) and is pinpointed by FINEMAP as the only causal variant at that locus with high confidence. Overall, our conditional analyses suggest that rare variant association signals are usually independent of nearby common variant associations.We identified significant  that cause recessive hearing loss, burden associations in seven genes  and single-variant associations in two genes (TBC1D24 and COL11A2) that cause autosomal dominant hearing loss . In MYO6 and COCH, we also observed genome-wide significant single-variant associations of large-effect size  that harbors other mutations causing non-syndromic hearing loss40.Of the 14 genes with independent, rare nonsynonymous and/or burden associations, 11 were previously identified as causes of Mendelian forms of hearing loss. These include associations with two genes , and SLC26A5 Leu46Pro  as well as the burden of SLC26A5 predicted loss-of-function (pLOF) and strict deleterious missense variants (excluding Leu46Pro)  , another known pathogenic variant in recessive hearing loss. The associations persisted after excluding homozygous carriers and compound heterozygous carriers of rare, coding variants in these genes  identified can cause hearing loss in heterozygote carriers. However, we also detect associations in two genes that have previously been implicated in recessive hearing loss: , with an approximately two-fold increase in risk for hearing loss . The main contributors to the gene burden were two frameshift variants, Gly302fs and Lys181fs, that are predicted to truncate the protein near the start of the Kelch domains. These variants were also significantly associated in single-variant tests . This variant was also prioritized as the sole causal variant at this locus by FINEMAP  and synaptojanin 2 (SYNJ2) with increased risk for hearing loss, both of which were recently observed in UKB18 18 variant that lies in the catalytic domain of this inositol polyphosphate 5-phosphatase44. Mice harboring homozygous mutations in Synj2 that are predicted to reduce protein levels or the 5-phosphatase catalytic activity show progressive high-frequency hearing loss and a degeneration of hair cells that is most profound in the outer hair cells46.We also identified rare coding associations in fascin actin-bundling protein 2 , we do not observe any common variants of large effect. We further estimated phenotypic variance explained by the genetic data, or heritability h2Tot, using LD score regression (LDSC) partitioning into functional categories and stratifying by minor allele frequency48. We estimated a total heritability (h2Tot) of 0.089, with contributions from common variation  and low-frequency variation  of 0.074 and 0.015, respectively  showing common coding-variant associations with hearing loss in adult humans. We also identified coding variant/gene burden associations with 15 genes through exome sequencing. We estimated that low-frequency variation contributes a non-negligible portion (16.8%) of SNP heritability for adult hearing loss, consistent with a highly polygenic genetic architecture with rare, low-frequency and common genetic variation for adult hearing loss, and where variants of large effect would be subject to purifying selection.We performed combined GWAS and ExWAS using exome-sequencing data and identified 53 independent associations, of which 15 have not previously been associated with hearing loss, to the best of our knowledge. The 15 associations included a missense lead variant in GJB2 and SLC26A5, with ORs close to typical for GWAS findings (1.2-1.3), followed by COL11A2 (2.2-7) and, at the high end of the distribution, COCH and MYO6 (31-81). COCH Cys542Phe and MYO6 His246Arg are known pathogenic variants, and consistent with this, we observe almost all carriers presenting hearing loss. The two control carriers for each variant (Supplementary Data 49), odds ratios of low-frequency and rare genetic factors may be large enough to provide mechanistic insights and to have implications for precision medicine.Notably, the majority of genes implicated by rare-variant and burden associations are already known to cause Mendelian forms of hearing loss; however, the odds ratios for these associations are wide-ranging. At the lower end of the effect spectrum are single-variant associations in CDH23), hearing function (CTBP2), or have significant rare variant associations with hearing loss (KLHDC7B). While FINEMAP helps prioritize variants, the gene that is impacted by those variants is not necessarily obvious, so we looked for colocalization with GTEx eQTL data and identified 19 genes whose expression may influence hearing loss risk (Supplementary Data 4). Analysis of single-cell expression data from mouse ears showed that 13 of the 19 genes are expressed in ear tissues. Of note, among these are LMO7 and SPTBN1 (BetaII-spectrin). Both genes code for components of the cuticular plate in the hair cells of the ear and knockout mice for either gene develop hearing loss51. LMO7 colocalizes with eQTLs for the gene in GTEx skeletal muscle and SPTBN1 in thyroid tissue, such that decreased expression of these genes is correlated with increased risk for hearing loss in humans.Ultimately, to understand the biology of hearing loss and develop testable hypotheses from our association results, we need to identify the genes driving the observed associations at each locus. For common variants, we note the high resolution of FINEMAP to prioritize causal variants in several loci, including pinpointing single variants in four genes, three of which are related to hearing loss (MYO6 and COCH) and uncharacterized variants (COL11A2 Phe80Ser), in genes that can cause autosomal dominant Mendelian hearing loss. We also identified variants and genes that cause recessive hearing loss (GJB2 Gly12fs and SLC26A5 pLOF+strict deleterious missense mutations), associated with increased risk (OR~1.2–1.3) for hearing loss in heterozygous carriers. Missense mutations in GJB2 can cause dominant, syndromic hearing loss52 but loss-of-function mutations, including Gly12fs, cause recessive non-syndromic hearing loss55. Consistent with our findings, studies have detected hearing deficiency at high frequencies and a possibly more prominent effect in female adult heterozygous carriers of Gly12fs57. Mutations in SLC26A5 cause recessive hearing loss in humans58 and mice homozygous for Slc26a5 null mutations develop hearing loss as early as 5–7 weeks of age59. Slc26a5 heterozygous null mice have a hearing deficiency that is intermediate between the controls and knockouts. While we cannot rule out the possibility of compound heterozygosity with variation in regulatory/promoter regions in heterozygous carriers, our results offer the possibility that heterozygous carriers of loss-of-function variants in GJB2 and SLC26A5 may also have increased risk for adult-onset hearing loss.One of the most compelling ways in which human genetics can establish a role for a gene in disease is when a diverse set of rare nonsynonymous or loss-of-function variants in the same gene show consistent association with disease. Coding variant and gene burden associations that we identified included associations with known pathogenic  compared to the pLOF burden (OR = 2.14), we would hypothesize that this more common missense (MAF = 0.04) is a hypomorph. KLHDC7B (Kelch-like domain containing 7B) is a relatively understudied gene; it has been characterized as a 594-amino-acid protein containing a Kelch domain that is hypermethylated and upregulated in breast cancer cell lines and may influence cell proliferation in MCF-7 cells lines61. In the mouse ear, RNAseq expression profiling62 and our real-time PCR data  self-reported hearing loss among adults, which is likely to be a heterogeneous mix of early-onset, late-onset, age-related, as well as hearing loss due to environmental insults. In general, greater phenotype precision, including environmental exposure measures, should help future genetic analyses of adult hearing loss. We note that our colocalization analyses utilized GTEx eQTL data across tissues not including ear expression data. Given the high degree of sharing of genetic regulation of expression across tissuesIn summary, this work contributes to connecting the two ends of the genetic architecture of hearing loss by detecting a common signal in genes known to cause hearing loss in Mendelian fashion and by detecting an additive signal (i.e. increased risk in heterozygous carriers) in genes known to cause autosomal recessive hearing loss. This latter finding also connects young- and adult-onset hearing loss in a single phenotypic spectrum with complex genetic underpinnings, including contributions from rare and common variation.66, the MyCode Community Health Initiative cohort from Geisinger Health System (GHS)67, the Mount Sinai BioMe cohort (SINAI) (https://icahn.mssm.edu/research/ipm/programs/biome-biobank/pioneering), the Malmö Diet and Cancer study (MALMO)68, and FinnGen R3 (https://www.finngen.fi/). Hearing loss case-control status in GHS, MALMO, and SINAI was defined using ICD-10 code diagnoses from the EHR. Cases were individuals with ICD10 H90.3-H90.8, H91.1or H91.9 diagnoses. Controls were individuals who did not meet the case criteria and did not have a diagnosis for ICD-10 Q16  or ICD-10 H93.1 (tinnitus). In UKB the phenotype was defined using ICD-10 codes as above or by self-reported hearing loss or complete deafness on the touchscreen questionnaire (Field IDs: 2247 and 2257). Controls in UKB were individuals who did not have an ICD-10 diagnosis for hearing loss or tinnitus and did not self-report hearing loss, deafness or tinnitus (Field IDs: 4803 and non-cancer illness code 1597). The FinnGen analysis used was finngen_r3_H8_CONSENHEARINGLOSS, conductive or sensorineural hearing loss defined by ICD10 codes H90[.0-8], versus controls excluding other ear disorders (H91-H95). Further details are given in the Supplementary Information.We performed meta-analysis for hearing loss on a total of 125,749 cases and 469,497 controls of European ancestry from the following cohorts: United Kingdom Biobank (UKB)All participants provided informed consent, and studies were approved by the individual Institutional Review Boards (IRBs) at the respective institutions. UK Biobank has approval from the North West Multi-Centre Research Ethics Committee , which covers the UK. It also sought the approval in England and Wales from the Patient Information Advisory Group (PIAG) for gaining access to information that would allow it to invite people to participate. The DiscovEHR study was approved by the Geisinger Health System Institutional Review Board. The BioMe Biobank is an ongoing research biorepository approved by the Icahn School of Medicine at Mount Sinai’s IRB. The Ethical Committee at Lund University approved the Malmo Diet and Cancer Study (LU 51-90). The Finngen Biobank was approved by the Coordinating Ethics Committee of the Helsinki and Uusimaa Hospital District.70. For SINAI and MALMO, DNA from participants was genotyped on the Global Screening Array (GSA), and for GHS genotyping was done on either the Illumina OmniExpress Exome (OMNI) or GSA array; the datasets (stratified by array for GHS) were imputed to the TOPMed (GHS) or HRC (MALMO and SINAI) reference panels using the University of Michigan Imputation Server (https://imputationserver.sph.umich.edu/index.html) or the TOPMed Imputation Server . Additional details are given in the Supplementary Information. We tested for association with hearing loss genetic variants or their gene burdens using REGENIE v1.0.4371. Analyses were adjusted for age, age2, sex, an age-by-sex interaction term, experimental batch-related covariates, and genetic principal components. Cohort-specific statistical analysis details are provided in the Supplementary Information. Results across cohorts were pooled using inverse-variance weighted meta-analysis.High-coverage whole-exome sequencing was performed at the Regeneron Genetics Center as previously describedr2 > 0.1) with lead variants. We defined previously associated loci by their index variants reported in previous hearing loss GWAS75, and excluded 1 Mb regions surrounding them in the identification of previously unreported, to the best of our knowledge, loci in our analysis. LD score (LDSC) regression76 was used to assess inflation (LDSC intercept) accounting for polygenic signal. Power calculations determined genotype relative risks (GRRs) providing 80 and 50 percent power given specified risk allele frequencies  and the numbers of cases and controls in our meta-analysis. Fine mapping analyses included forward stepwise conditional analyses carried out in every locus with GCTA-COJO using a UK Biobank subsample LD reference panel, with independent associations determined using a joint P-value threshold of 1 × 10−5 and r2 cutoff of 0.9, and FINEMAP34 Bayesian causal variant inference, using LD from available individual level data.We defined genome-wide significant loci in our analysis by linkage disequilibrium  cis-eQTL data derived from 48 tissues , using GWAS and eQTL summary statistics for all common (MAF ≥ 0.01) variants within each gene’s cis-region. Genes with posterior probability of colocalization H4 ≥ 0.5 were determined as having evidence for colocalization, and were visually inspected in eQTL+GWAS regional association plots77.For genes whose cis regions overlapped genome-wide significant hearing loss loci, coloc2Conditional analyses were performed for each cohort using REGENIE’s Firth-corrected logistic regression and the resulting summary statistics were meta-analyzed as described above. Rare-variant association analyses conditional on the common variant signal were carried out for four loci with both common (MAF ≥ 0.01) and single rare variant (MAF < 0.01) genome-wide significant signals, by including as covariates the dosages of variants identified in fine mapping analyses. Burden analyses conditional on rare variants were carried out for five genes with significant single rare variant and burden associations.https://github.com/odelaneau/shapeit4) phasing of merged genotype and exome data with scaffolds based on inferred close relatives79.Assessment of heterozygous effects used association analyses excluding homozygotes as well as individuals carrying pairs of exome sequenced variants (MAF < 0.02 and MAC > 1) that were called as compound heterozygous mutations (CHMs) or potential CHMs (i.e. unknown phase). CHMs were called by SHAPEIT4  with each category further stratified into a low frequency (0.001 < MAF ≤ 0.05) and common (MAF > 0.05) minor allele frequency bin as in stratified LD score regression was estimated using LD score regression (LDSC) of hearing loss association statistics on LD scores. LD scores were generated from a reference panel of https://github.com/satijalab/seurat)80. Cluster marker genes as well as canonical cell type-specific genes were used to manually label the cell type for each cluster.All protocols were approved by the Institutional Animal Care and Use Committee in accordance with the Regeneron’s Institutional Animal Care and Use Committee (IACUC). Cochlea and utricles from C57BL/6 mice at post-natal day 7 were micro-dissected and dissociated. Suspensions of 200 cells/μL were subjected to Chromium Single Cell (10x Genomics) library preparation and were sequenced on Illumina NextSeq 500. Cell Ranger Single-Cell Software Suite  was used to perform sample de-multiplexing, alignment to MM10 Genome assembly with UCSC gene models, filtering, and UMI counting. PCA, UMAP and clustering analyses used Seurat V3.2 (P < 5 × 10−8 was considered statistically significant. For simplicity and reproducibility, meta-analysis was performed to combine statistical results across cohorts rather than a multi-stage design or requiring nominal significance in multiple cohorts; sample sizes are reported above and in Supplementary Data P < 5 × 10−8 was considered as a threshold for reporting independent associations within loci. Rare-variant associations were reported as independent of common variants in the same locus when they were P < 5 × 10−3, as determined by Bonferroni correction for 10 conditional tests performed. We describe burden results conditional on individual variants within the aggregate burden counts regardless of significance, in order to determine if any variants were driving the burden signal. Further details are given above and in the Supplementary Note.For genome-wide association meta-analysis, the statistical threshold of Further information on research design is available in the Peer Review FileSupplementary InformationDescription of Additional Supplementary FilesSupplementary Data 1-11Reporting Summary


Furthermore, it was found that the binding affinity for a drug was the critical factor determining its sensitivity, and the binding energy showed little influence. This is the first study reporting the recognition mechanisms of a natural TetR protein for tetracyclines and the development of a fluorescence polarization assay for the detection of tetracyclines residues in food samples.In this study, the identity of our recently produced natural TetR protein was identified by using the LC-ESI-MS/MS technique, and its recognition mechanisms, including the binding pocket, contact amino acids, intermolecular forces, binding sites, binding energies, and affinities for 10 tetracycline drugs were studied. Then, it was evolved by site-mutagenesis of an amino acid to produce a mutant, and a fluorescence polarization assay was developed to detect the 10 drugs in milk. The sensitivities for the 10 drugs were improved with IC Due to the broad antibacterial effect, tetracycline drugs TCs,  have beeAcetobacter liquefaciens and found its two functional domains: a DNA-binding domain and a ligand-binding domain [In 1974, Levy et al. reported for the first time that the TCs-resistant mechanism was to transfer molecules of TCs out of the cell using a tetracycline repressor (TetR) regulated efflux pump . Thereafg domain . In the g domain ,7,8,9. Ig domain ,11,12, bg domain ,14,15 ang domain ,17,18, dg domain ,21.Still, the most important issue is the binding mechanisms for TCs. In several previous reports, the binding mechanisms of a TetR(D) for a tetracycline ,6,22 andIt is well known that TCs are also widely used as veterinary drugs in food-producing animals, and their residues in foods of animal origin are potential risks to consumers, e.g., causing gastrointestinal disturbance and allergic reactions. For the protection of consumer health, many countries have set the maximum residue limits for TCs in various food samples, e.g., 100 ng/mL in milk. So, it is necessary to monitor the residues of TCs in foods of animal origin. By now, many analytical methods have been developed to detect their residues. Among the reported methods, an immunoassay is the most commonly used screening tool. In the reported immunoassays for TCs, antibodies are usually used as recognition reagents . HoweverAmong different formations of immunoassays, a fluorescence polarization immunoassay is a type of homogeneous method with a simple and rapid assay procedure. For a fluorescence polarization immunoassay, the recognition reagent is directly mixed with the fluorescent tracer and the analyte solution to be incubated for several minutes, and then the fluorescence polarization value is excited to quantify the analyte. In other words, the coating, blocking, and washing steps that are required in the conventional immunoassay are avoided, so the assay can be finished within several minutes. Therefore, this method has been used to determine different analytes . To the In our recent study, a type of natural TetR protein capable of recognizing 10 TCs was obtained , but itspET32a) and the kits  gel) were the same as our recent report [The standards of tetracycline (TC), chlortetracycline (CTC), minocycline (MC), doxycycline (DC), oxytetracycline (OTC), demeclocycline (DMC), and tigecycline (TIC) were from Sigma-Aldrich . Methacycline (MTC) was from J&K Scientific Ltd. . Lymecycline (LMC) was from Toronto Research Chemicals . Sancycline (SC), fluoresceinamine (FA), and fluorescein isothiocyanate (FITC) were purchased from Shanghai Yuanye Biological Technology Co., Ltd. . All the biological reagents  was used to dock with the 10 TCs, respectively, by using YASARA 16.2.18 . During the molecular docking, the binding pocket was located, and several important parameters including key contact amino acids, main intermolecular forces, total binding energies, and specific binding sites for each drug were determined.For confirmation of the molecular docking results, the affinities of the natural TetR for the 10 TCs were tested, respectively, by using the Berthold bScreen LB 991 Microarray System, and the procedures were according to our recent report . After tBased on the results of molecular docking, the amino acids in the binding pocket were subjected to saturate virtual mutation by using YASARA. The mutagenesis site was selected according to the virtual mutation for demeclocycline (DMC), which was because the natural TetR showed the highest binding energy to it. In this study, if an amino acid was substituted with another amino acid, and the obtained virtual model showed improved binding for DMC, then this amino acid was selected as the mutagenesis site. During the virtual mutation, HIS139 was found to be the optimal mutagenesis site, and it was substituted with THR to produce the mutant.for, TAATACGACTCACTATAGG; mutant rev, GCTAGTTATTGCTCAGCGG. The amplified gene was inserted into pET28a to construct the express vector that was transformed into E. coli Rosetta-gami(BL21) to express the mutant, and these procedures were according to our recent report [The primers were designed according to the virtual model: mutant t report . The obtt report , and itsThe first fluorescent tracer FITC-MC A was synFP) value of each well was recorded . During the experiments, the two fluorescent tracers were compared, and several other parameters were optimized, including tracer concentration, mutant concentration, Mg2+ concentration and incubation time. The 10 TCs and several other classes of drugs were all tested by this method. The competitive curve was developed by plotting the 0FP/FP values  versus the concentrations of the TCs (log C). Based on the developed competitive curve, the half of inhibition (IC50) and the limit of detection (IC10) for each drug were determined, respectively.The FPA method was performed as follows. A total of 50 μL mutant, 50 μL TCs solution, and 50 μL fluorescent tracer were added into the wells of a 96-well microplate (in triplicate) and incubated for 2 min. Then the fluorescence polarization . Compared with the TetR proteins from other bacterial strains, the 100% conserved amino acids were the same, but the amino acids at other positions were different. Based on these results, it could be said that the natural TetR protein produced in our recent report was completely consistent with the previously produced TetR protein. So, the photoaffinity labeled activity-based protein profiling probe could also be used to produce the natural receptor of other drugs.As shown in In this study, the 100% homological model of the natural TetR (PDB ID: 4AC0) was used for molecular docking. As shown in As shown in 2+ showed some influences on TetR-tetracycline binding [2+ were all calculated in the present study. As shown in 2+ were in the range of 17.7–25.1, and the values without adding Mg2+ were in the range of 17.0–26.5. This meant that the presence or absence of Mg2+ showed little influence on the TetR-TCs bindings. From these KA values, it could also be said that the TetR showed comparable bindings for the 10 drugs.By now, there have been several reports studying the association/dissociation properties of the TetR protein for tetracycline ,26,27. I2+ was required. The present paper studied the recognition mechanisms of a natural TetR for 10 TCs for the first time, and the results were more comprehensive than the previous studies.By now, there have been several reports studying the TetR-TCs intermolecular mechanism (TetR(D) for tetracycline) ,6,22. InFor obtaining a TetR mutant with improved recognition ability for TCs, HIS139 was mutated to TRP139 based on the virtual mutation for DMC. As shown in As shown in BamHI and XhoI, indicating the express vector was obtained. As shown in As shown in 2+ (23.9–33.3) were generally similar to those where Mg2+ (20.3–33.1) was not added, indicating the presence or absence of Mg2+ also showed little influence on its binding for TCs. As shown in 2+) when using the mutant was higher than that when using the natural TetR, indicating the natural TetR was evolved successfully and the mutant showed improved affinities for the 10 TCs.Furthermore, its affinity parameters for the 10 TCs were also calculated. As shown in FITC and FA are the commonly used fluorescent agents, so they were used to synthesize the two fluorescent tracers in the present study A. As shoFP values of a single tracer and a single mutant were all negligible, but the FP values of their mixtures were all high, indicating the two tracers could bind with the mutant to develop an FPA method. However, the FP value when using FITC-MC was higher than that when using FA-MC. The molecular docking showed that the binding sites in the MC molecule were around its D ring  when using FA-MC (69%) was higher than when using FITC-MC (52%). This was because FA-MC showed weaker binding for the mutant than FITC-MC, thus improving the DMC’s binding for the mutant to obtain the high inhibition ratio. This indicated that the use of FA-MC could achieve a higher sensitivity, so it was used for the subsequent experiments. During the experiments, several other classes of drugs  were also tested by this method. As shown in FP values when their concentrations were 0 and 100 ng/mL were comparably high no matter which tracer was used, indicating the mutant was only specific for TCs.As shown in 2+ (MgCl2) was optimized. As shown in 2, so this parameter was selected as the optimal condition. Thirdly, the competition time was optimized. As shown in For obtaining the best method performance, several parameters were optimized with DMC as the representative. Firstly, the concentrations of FA-MC and the mutant were optimized. During the experiments, the FA-MC and the mutant at different concentrations were mixed with the same concentration of DMC to perform the assay. As shown in 50 values for the 10 TCs were in the range of 15.5–55.2 ng/mL, and the limits of detection were in the range of 0.4–1.5 ng/mL. During the experiments, the natural TetR was also used to perform the FPA method as described above. As shown in 50 values for the 10 TCs when using the natural TetR were in the range of 30.8–80.1 ng/mL, indicating the natural TetR was evolved successfully and the mutant showed improved sensitivities for the 10 TCs. The representative competitive curves of DMC when using the natural TetR and the mutant are shown in This is the first study reporting an FPA method for the determination of TCs. Under the optimal conditions, the 10 TCs were diluted with the extracts of a blank milk sample to be analyzed, respectively. As shown in 50 of the 10 TCs when using the natural TetR and the mutant were integrated. As shown in 50 values of the 10 drugs when using the mutant were all lower than when using the natural TetR. These results showed that the natural TetR was evolved successfully, and the affinity for a drug determined the sensitivity for it.For a comprehensive comparison of the two proteins, the binding energy, KA, and ICThe 10 TCs were fortified into the blank milk samples to be analyzed, respectively. As shown in For the first time, this study developed a TetR mutant-based FPA method for the detection of TCs. For comparison with related methods, the previously reported TetR-based analytical methods for TCs were listed in In this study, the identity of a natural TetR protein was characterized, and its recognition mechanisms for 10 TCs were studied. It was found that the TetR showed similar binding sites, contact amino acids, and intermolecular forces for the 10 drugs. Then, the natural TetR was evolved by using the site-directed mutagenesis method, and the obtained TetR mutant was used to develop a fluorescence polarization assay for the determination of the 10 drugs in milk samples. Results showed that the binding affinity and the detection sensitivity of the mutant-TCs were all improved. The receptor mutation method reported here could help other researchers to evolve other receptors or recognition reagents, and the developed method could be used as a practical tool for routine screening of the residues of TCs in food samples.


Due to the COVID-19 pandemic, teleconsultations (TCs) have become common practice for many chronic conditions, including osteoporosis. While satisfaction with TCs among patients increases in times of emergency, we have little knowledge of whether the acceptability of TCs persists once in-person visits return to being a feasible and safe option. In this study, we assess the acceptability of TCs across five dimensions for osteoporosis care among patients who started or continued with TCs after the COVID-19 pandemic had waned. We then explore the patient characteristics associated with these perceptions.Between January and April 2022, 80 osteoporotic patients treated at the Humanitas Hospital in Milan, Italy, were recruited to answer an online questionnaire about the acceptability of TCs for their care. The acceptability of TCs was measured using a modified version of the Service User Technology Acceptability Questionnaire (SUTAQ), which identifies five domains of acceptability: perceived benefits, satisfaction, substitution, privacy and discomfort, and care personnel concerns. Multivariable ordinary least squares (OLS) linear regression analysis was performed to assess which patient characteristics in terms of demographics, socio-economic conditions, digital skills, social support, clinical characteristics and pattern of TC use were correlated with the five domains of acceptability measured through the SUTAQ.The degree of acceptability of TCs was overall good across the 80 respondents and the five domains. Some heterogeneity in perceptions emerged with respect to TCs substituting for in-person visits, negatively impacting continuity of care and reducing the length of consultations. For the most part, acceptability was not affected by patient characteristics with a few exceptions related to treatment time and familiarity with the TC service modality .TCs appear to be an acceptable option for osteoporosis care in the aftermath of the COVID-19 pandemic. This study suggests that other characteristics besides age, digital skills and social support, which are traditionally relevant to TC acceptability, should be taken into account in order to better target this care delivery modality.The online version contains supplementary material available at 10.1186/s12913-023-09224-x. The COVID-19 pandemic has caused profound disruptions globally to the delivery of healthcare services. Notably, it has affected the management of many chronic conditions as resources have been diverted to urgent care and as people have been less inclined to or prevented from attending healthcare facilities for fear of contagion . Since tIn 2021, once the pandemic decreased in severity and people started to get vaccinated, the TC modality was maintained to limit the risk of crowding healthcare facilities  does not know who will be on the other side and maybe his competence… then it is not great. (Patient #19)Other respondents indicated that not being able to see the same specialist during TC negatively impacted the continuity of their care and their overall perception of TCs. One patient commented:Table p = 0.07). Considering that women are the most affected by osteoporosis, perhaps more caution should be used when dealing with osteoporotic women than men in TC. Retired patients were also less concerned in comparison to working individuals about the issues of privacy and discomfort , and unemployed patients seemed less concerned with the quality of the relationship with the specialist than employed patients .We found some significant correlations elsewhere, although often the significance was weak. In particular, men were less concerned about issues of privacy and discomfort linked to TCs in comparison to women  and the least convinced of the substitutive capacity of TCs for in-person visits . In addition, patients who had been treated for osteoporosis for longer were more concerned about the relationship with the specialist . At the same time, patients who had experienced more TCs had greater satisfaction with TCs , suggesting that the more patients become familiar with this service modality, the more acceptable it can become. We cannot completely exclude selection bias such that those satisfied with TC were more likely to continue with successive TCs. However, we controlled for patients requesting to stop TCs and go back to in-person visits (12.5% of study participants) and found no significant association between this dummy variable and the five acceptability domains.The most interesting associations, though, referred to how suffering from a long-term condition such as osteoporosis affected the acceptability of TCs. Patients who had been treated for osteoporosis longer were the least satisfied with TCs  did not impact the acceptability of TCs across any of the five domains. This result was valid for all five acceptability domains and both the multivariable Table  and univThis study shows an overall good level of acceptability of TCs among patients with osteoporosis independently of whether they started TCs during the COVID-19 emergency phase or later on . The findings indicate that for chronic conditions requiring regular follow-ups, TCs might be a valid care delivery modality even in non-emergency situations.Despite this overall positive perception of TCs, some heterogeneity among patients was evident, especially with respect to the perception of the capacity of TCs to substitute completely for the kind of doctor–patient relationship that in-person visits engender. Specifically, several patients openly indicated concerns about TC negatively affecting the trust relationship with the specialist by reducing the continuity of care or consultation length.Patient characteristics could only partially explain this heterogeneity in the acceptability of TCs. This might be due to unobservable individual characteristics, such as personality or attitudes, that we did not include in our model. For instance, Baudier et al.  showed tThis study points to other characteristics that might be relevant to the acceptability of TCs, in particular, how long a person has received treatment for a chronic condition such as osteoporosis. Patients who have been treated for a longer amount of time may display more concern with TCs in terms of overall satisfaction, the possibility of TCs substituting for in-person visits and ensuring a high-quality relationship with the specialist. This alerts healthcare professionals to the fact that over time, people suffering from a chronic condition might feel fatigued and need a close relationship with their specialist in order to continue with the care of their chronic condition. In this, TCs might be perceived as less effective or satisfying in comparison to in-person visits.The paper is a first attempt to measure the acceptability of TCs in the aftermath of the COVID-19 pandemic and is not exempt from limitations. The retrospective design and the small size of the study group could mean that the answers are not highly representative of osteoporotic patients. Moreover, some conditioning descending from patients being recruited to the study by their own osteoporosis specialists may have biased patients’ answers about the acceptability of TCs in a positive direction. We tried to attenuate this bias by explicitly informing patients that their specialist would not have access to their answers and including this information in the informed consent form that recruited patients had to sign.Our study provides useful insights into the acceptability of TCs for chronic conditions post-COVID-19. The significance of our findings lie in showing how TCs have become largely acceptable to categories of chronic patients who in the past were sceptical about this service modality, mainly for technological reasons. However, the study indicates that when these concerns are overcome, others might arise with respect to the quality of the doctor–patient relationship afforded by TCs. This suggests that as TCs and telemedicine in general become more widely adopted by healthcare systems, it is important to strengthen doctors’ and patients’ communication capacities in addition to their digital skills. In addition, it will be necessary to continue monitoring chronic patients’ perceptions of TCs in future years to understand how persistent this acceptability actually is and what affects it the most.Additional file 1. Descriptive statistics of respondents by date of first TC and their comparability.Additional file 2. Confirmatory factor analysis showing loading factors for questions in the modified SUTAQ.Additional file 3. Modified SUTAQ descriptors.Additional file 4. Mean difference in SUTAQ acceptability domains between patients who experienced TC for the first time during and after the Covid-19 emergency phases.


Age-related hearing impairment is the most common sensory dysfunction in older adults. In osteoporosis, the mass of the ossicles will be decreased, affecting the bone density of the cochlea, and interfering with the sound transmission to the cochlea. Age related hearing loss might be closely related to osteoporosis.To determine the relationship between age-related hearing impairment and osteoporosis by investigating the relationship between hearing loss and cortical bone density evaluated from femur neck bone mineral density.We used data from the Korea National Health and Nutrition Examination Survey to examine the associations between osteoporosis and age-related hearing impairment from 2009 to 2011. Total number of participants was 4861 including 2273 men and 2588 women aged 50 years or older. Osteoporosis was defined as a bone mineral density 2.5 standard deviations below according to the World Health Organization diagnostic classification. Age-related hearing impairment was defined as the pure-tone averages of test frequencies 0.5, 1, 2, and 4 kHz at a threshold of 40 dB or higher on the more impaired hearing side.p < 0.001), lumbar-spine T-score (p < 0.001) and, femur neck T-score (p < 0.001) were significantly lower in the osteoporosis group compared to the normal group. Thresholds of pure-tone averages were significantly different in normal compared to osteopenia, and osteoporosis groups. In addition, there were significantly higher pure-tone averages thresholds in the osteoporosis group compared to other groups (p < 0.001). After adjusting for all covariates, the odds ratio for hearing loss was significantly increased by 1.7 fold with reduced femur neck bone mineral density (p < 0.01). However, lumbar spine bone mineral density was not statistically associated with hearing loss (p = 0.22).Total femur T-score (Our results suggest that osteoporosis is significantly associated with a risk of hearing loss. In addition, femur neck bone mineral density was significantly correlated with hearing loss, but lumbar spine bone mineral density was not. As population aging is occurring in many Countries, the importance of health life expectancy of elderly people is becoming a major concern. Furthermore, there is a growing interest in chronic and aging diseases that affect the health expectancy of elderly people.Recently, Yeh et al.Zehnder et al., investigating bone metabolism in the otic capsule, suggested that OPG, a potent inhibitor of osteoclasts, is present in the inner ear and is secreted as perilymph to inhibit bone remodeling of the otic capsule, and in particular the cochlea.When the sound is presented to the external ear canal, it is transmitted through the ossicles vibration to the cochlea. That ossicular vibration is directly proportional to the stiffness of the tympanic membrane, inter-ossicular joint and oval window, and inversely proportional to the mass of the tympanic membrane and ossicles.17Our hypothesis was that age related hearing loss could be closely related to osteoporosis, and that BMD levels at the femur neck, which occupies a large portion of the cortical bone, would reflect the condition more than the BMD lumbar spine levels.Therefore, the purpose of this study was to determine the relationship between ARHI and osteoporosis and to investigate the relationship between cortical bone density evaluated from lumbar spine (L-spine) and femur neck BMD, and hearing loss.Data from the 2009–2011 Korean National Health and Nutrition Examination Survey (KNHANES) was reviewed and approved by the Institutional Review Board of the Korea Centers for Disease Control and Prevention (KCDC) . Written informed consent was obtained from all participants when the 2009, 2010, and 2011 KNHANES were conducted.n = 7920), 2010 (n = 7043), and 2011 (n = 2757). Patients under 50 years of age and with no registered data on bone mineral density or pure tone audiometry were excluded. After these exclusions, a total of 4861 participants (2273 men and 2588 women) with normal tympanic membrane were analyzed  and Bone Mineral Density (BMD) from total femur, and from femoral neck and lumbar spine (L1–L4) were measured by trained technicians using DXA . Osteopenia or osteoporosis were diagnosed with supplying by the DXA manufacturerFor evaluation of hearing threshold, pure-tone audiometry was conducted with a SA 203 audiometer  in a soundproof booth and instructions were given by a trained otolaryngologist. In a soundproof booth, subjects put on a headset, and pushed a button when they heard a pure tone sound. Only air conduction threshold was measured. The pure-tone averages (PTA) were calculated as the average of threshold at 0.5, 1, 2 and 4 kHz. Hearing loss was defined as the PTA of threshold 40 dB or higher.Information on the study population including BMI, smoking, alcohol consumption, physical activity, and medical conditions were obtained from KNHANES data. BMI was calculated from the height which was measured to the nearest 0.1 cm with a stadiometer.Hypertension was defined as a systolic Blood Pressure (BP) of 140 mmHg, a diastolic BP of 90 mmHg, or treatment with antihypertensive agents. Diabetes mellitus was defined by a fasting plasma sugar level >126 mg/dL, treatment with oral hypoglycemic agents or insulin, or diagnosis by a physician.In terms of smoking, the participants were categorized either as current smokers or others. A participant was considered to have a “monthly alcohol ingestion history” if he/she drank more than once per month over the past year. A moderate physical activity done for at least 20 min a time and more than three times a week was considered to be regular exercise.Serum 25 (OH)D and parathyroid hormone (PTH) levels were measured using a gamma counter  and LIAISON (DiaSorin) with radioimmunoassay (25 (OH)D 125I RIA Kit; DiaSorin) and chemiluminescence immunoassay , respectively.To compare PTA by presence of osteoporosis, ANOVA with Bonferroni correction was performed. Multiple logistic regression analyses were also performed to estimate the association between T-score and hearing loss. Data are presented as OR (95% CI) after adjusting for certain factors in each model using hierarchical analysis .p < 0.05 were accepted as statistically significant results.To reflect the sampling weights, complex sampling analyses was performed. All statistical analyses were performed using the SAS . All data with p < 0.001). Osteopenia and osteoporosis were more common in women than men. Current smoking (p < 0.001), monthly alcohol drinking (p < 0.001), BMI (p < 0.001) were significantly higher in the normal group compared to the osteopenia and osteoporosis group. However, moderate physical activity, diabetes mellitus, and hypercholesterolemia were not significantly different.Subject characteristics are shown in p < 0.001), femur neck T-score (p < 0.001) and, total femur T-score (p < 0.001) were all significantly decreased in the osteoporosis group compared to controls. Calcium (p < 0.001), phosphorus intake (p < 0.001), serum creatinine (p < 0.001), and vitamin D (p < 0.001) were also significantly decreased in the osteoporosis group. However, alkaline phosphatase p < 0.001) and parathyroid hormone (p < 0.001) were significantly increased in the osteoporotic group.L-spine T-score (p < 0.001) . However, L-spine and femur shaft BMD were not statistically correlated with hearing loss, respectively (p = 0.22 and 0.16)  .Table 2LThe principle finding of the present study is that there is a significant correlation between osteoporosis and ARHI. Although L-spine BMD and hearing loss were not significantly related, femur neck BMD and hearing loss were significantly related.Several studies have reported an association between osteoporosis and hearing loss in the older population. However, this relationship is controversial. Jung et al. performed a case-control study using 1009 postmenopausal women. They reported no association between bone mineral density and hearing impairment in the study population.In this study, L-spine BMD was not associated with hearing loss. Seventy five percent of L-spines are composed of trabecular bone while 75% of the femur neck are composed of cortical bone.24There were several limitations to this study. First, it was a cross-sectional study and retrospective in design. Therefore, we could not evaluate the causality between bone mineral density and hearing loss. Prospectively designed studies are necessary to clarify this relationship. Second, there is a lack of explanation for the mechanism of action. Therefore, well-designed experimental studies will be necessary to clarify this mechanism. Third, we could not reflect mild hearing loss and young adults. Therefore, in the future, large-scale studies including mild hearing loss and young adults will be necessary. Finally, there are differences in biochemical factors in east Asian that can affect osteoporosis and hearing loss compared to that in Western countries. In particular, the proportion of vitamin D deficiency in elderly people is higher in Korea than in Western countries. However, in this study, biochemical factors including vitamin D were adjusted for statistical analysis.Osteoporosis is significantly associated with a risk of hearing loss. In addition, lumbar spine bone mineral density al density was not correlated with hearing loss, while femur neck bone mineral density was significantly correlated.Ministry of SMEs and Startups, Republic of Korea (Project No. P0002726).This study was funded by the The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.The authors declare no conflicts of interest.