Mgp1, Mgp2, and Bgp in embryonic stages covering organogenesis in the small-spotted catshark Scyliorhinus canicula and present a comparative analysis with Mgp/Bgp family members previously described in bony vertebrates, highlighting ancestral features such as early embryonic, soft tissues, and neuronal expressions, but also derived features of cartilaginous fishes such as expression in fin supporting fibers. Our results support an ancestral function of Mgp in skeletal mineralization and a later derived function of Bgp in skeletal development that may be related to the divergence of bony vertebrates.Matrix Gla protein (Mgp) and bone Gla protein (Bgp) are vitamin-K dependent proteins that bind calcium in their γ-carboxylated versions in mammals. They are recognized as positive (Bgp) or negative (Mgp and Bgp) regulators of biomineralization in a number of tissues, including skeletal tissues of bony vertebrates. The Mgp/Bgp gene family is poorly known in cartilaginous fishes, which precludes the understanding of the evolution of the biomineralization toolkit at the emergence of jawed vertebrates. Here we took advantage of recently released genomic and transcriptomic data in cartilaginous fishes and described the genomic loci and gene expression patterns of the Mgp/Bgp gene family. We identified three genes, Mgp1, Mgp2, and Bgp, in cartilaginous fishes instead of the single previously reported Mgp gene. We describe their genomic loci, resulting in a dynamic evolutionary scenario for this gene family including several events of local (tandem) duplications, but also of translocation events, along jawed vertebrate evolution. We describe the expression patterns of  Vertebrates display a range of skeletal tissues that are biomineralized through the regulation of calcium phosphate crystal deposition , except Mgp and Bgp genes in mouse first appeared spatially exclusive, with Bgp expressed uniquely in osteoblasts or osteocytes but also in odontoblasts, while Mgp expression was restricted to hypertrophic chondrocytes , and dentinal matrix  Ml matrix ]. Previo genomes .Mgp/Bgp family. Here we collect transcriptomic and genomic data from different jawed vertebrates, including several cartilaginous fishes where we identify an unknown diversity of Mgp/Bgp sequences and their genomic loci. We describe their gene expression patterns in embryonic stages of the small-spotted catshark Scyliorhinus canicula and uncover highly conserved but also previously unknown sites of expression.The current explosion of genomic data, including in the cartilaginous fish lineage, allows the better description of gene complement and gene expression in this Scyliorhinus canicula) and thornback ray (Raja clavata) transcriptomic data , using TBLASTN. Additional cDNA sequences were obtained by screening accessible transcriptomic data collected by the SkateBase project1 [little skate Leucoraja erinacea transcriptome  and small-spotted catshark transcriptome (GEO:GSM643958)] using TBLASTN. Small-spotted catshark, little skate, and thornback ray sequences were then used to screen other databases for elephant shark genome assembly  (Rhincodon typus (GCA_001642345.2 ASM164234v2)  and Erp27 . Synteny data in bony fish genomes were extracted from the Ensembl database for selected genomes  and from NCBI for the caecilian Microcaecilia unicolor (aMicUni1.1).Matrix Gla protein and bone Gla protein sequences for human, mouse, and zebrafish were collected from GenBank and were used to screen locally assembled small-spotted catshark (mic data  as well i-6.1.3)  and whal64234v2) . Thornba Project , PriPec2Protein sequences for all identified Mgp and Bgp genes from the different chondrichthyan species together with sequences from osteichthyan species were used for phylogenetic tree reconstruction. These protein sequences are preproteins as they are obtained from the translation of either the cDNA sequence or of a predicted gene from available genomes. All sequences used in this study are detailed with IDs and origin in the Conservation of protein domains was evaluated by mapping previously identified functional regions  onto theEvolutionary scenario for gene duplication/loss was built minimizing the duplication and loss score with standard parameters in Treerecs , using cMgp1, Mgp2, and Bgp cDNA sequences were used to design the following primers (sequences are given in the 5′-3′ orientation): Fw TCACAGATTCACACTCGCTG and Rv GGCCGAACCAGAGC TGCTG amplifying 702 bp for Mgp1; Fw CCGATCTCAC AAACTGAGCT and Rv CACAGACTGCAGCAAATAGT amplifying 817 bp for Mgp2; Fw CCAGAGAAGATGATGG TCCT and Rv GGGGAATTAACAGAGTCGTC amplifying 675 bp for Bgp. Sequences were amplified from cDNA reverse-transcribed from total RNA extractions of a mix of embryonic stages. These PCR products were ligated into the pGEM-T easy vector using the TA cloning kit (Promega). Inserts with flanking T7 and SP6 sites were amplified using M13F/M13R primers and sequenced to verify the amplicon sequence and orientation, and these PCR products were then used as templates for the synthesis of antisense DIG riboprobes . Before in situ hybridization, all DIG-labeled riboprobes were purified on MicroSpin G50 column . The obtained expression patterns were different for each probe, excluding detectable cross-hybridization between Mgp1/Mgp2/Bgp probes, so we did not use sense probes as negative control.Identified small-spotted catshark in situ hybridization were performed on 14 μm thick cryosections of the chosen samples that had been progressively transferred back to PBS 1×, then equilibrated in sucrose 30% for 24 h before being transferred and frozen in Tissue-Tek® O.C.T.TM (Sakura Finetek France SAS). Consecutive cryosections were distributed on 10 successive slides to a maximum of 6–8 sections per slide and were stored at −20°C. In situ hybridization on sections was performed as described previously  with a 40× objective.Whole embryos of either 6 cm total length, 7.7 cm total length, or 9 cm long hatchlings, were euthanized in buffered tricaïne, eviscerated and fixed for 48 h in 4% paraformaldehyde in 1× phosphate-buffered saline (PBS) solution at 4 °C, rinsed in PBS 1× for an hour, and then transferred in 50% ethanol (EtOH)-PBS 1×, 75% EtOH-PBS 1×, and three successive bathes of 100% EtOH before storage at −20°C in EtOH 100%. We then sampled (i) the lower jaw (hatchling) and (ii) transversal slices in the posterior zone of the branchial arches to allow visualization of gene expression in, respectively, (i) teeth and the Meckel’s cartilage; and (ii) abdominal vertebrae, pectoral fin, or branchial rays. Experiments of eviously  with strHistological staining (Hematoxylin-Eosine-Saffran) was performed at the local histology platform  on 7 μm paraffin sections of non-demineralized samples on a histology automaton.Early embryos (three or four for each stage) were collected from embryonic stages 18–32 , with stEef1a and Rpl8  by geomMgp1; Fw CCTGATTCTGCTGTGCCTGT and Rv TTTTCCATAGGC CGCCATGT amplifying 277 bp for Mgp2; Fw TGATGGT CCTTTCCTCGGGA and Rv TGGTATCCAATCCTGTTTGC CA amplifying 180 bp for Bgp; Fw GGTGTGGGTGAATTT GAAGC and Rv TTGTCACCATGCCAACCAGA amplifying 245 bp for Eef1a; Fw TTCATTGCAGCGGAGGGAAT and Rv TCAATACGACCACCACCAGC amplifying 302 bp for Rpl8.We used Primer 3.0 to design all the sets of forward and reverse primers to amplify selected genes (sequences are given in the 5′-3′ orientation): Fw TCGGGAGGAGAGATGCACAT and Rv TGCCACCAAAGTATCTGCCA amplifying 183 bp for P > 0.05). We tested for heteroscedasticity of variance between developmental stages, and the null hypothesis had to be rejected only for the Bgp gene (P < 0.05), even after log transformation. Note that we are very constrained by an unbalanced protocol  and small sample size, which limits statistical power.The expression data obtained were compared over time to test if any gene was differentially expressed in time with a one-way ANOVA. A Shapiro–Wilk normality test was applied on the log transformed data, and for each gene the null hypothesis of normality was kept ]: no further approval by an ethics committee was necessary as the biological material is embryonic and no live experimental procedures were carried out. Embryos were raised in seawater tanks at 16–18 °C and euthanized by overdose of tricaine  at appropriate stages : the two chondrichthyan copies were named Mgp1 and Mgp2  or named Mgp-like in Pogona, osteocalcin-like in Xenopus laevis and other lissamphibians, osteocalcin in X. tropicalis or osteocalcin 3 in the chicken [see all references to the extracted sequences in OC3  and bgp1b [previously named OC2 , Mgp2 and Bgp genes could be assigned to a single contig together with Erp27 and Ddx47. However, the Mgp1 gene was located on another scaffold in the Amblyraja genome, outside of the locus identified by the presence of Erp27 and Ddx47  and the Bgp1 (BGLAP on chromosome 1) genes for which we highlighted the position of syntenic genes (Bgp2 gene (as identified in our phylogenetic reconstruction) are in the Mgp locus in lissamphibians and sauropsids .The comparison to the genomic data in bony fishes was made in two steps. First, an overview of the genomic locations in tetrapods shows that in the human genome, there are separated loci for the ic genes . All occBgp1 in tetrapods would not co-localize with any known sequence of either Bgp or Mgp in actinopterygians . This Bgp1 copy is identified as Bglap or Osteocalcin-like  in the available databases .In a second step, we searched the homologous loci in actinopterygians (ray-finned fishes) outside of teleost fishes: the syntenic markers linked to erygians . The actmosome 3 . In FiguThe prediction of functional protein domains by InterproScan and SMART led to the recognition of a signal peptide for all sequences, but of a general Gla domain only in Bgp and Mgp1 proteins, excluding the Mgp2 sequences of the small-spotted catshark or elephant shark. The FIMO algorithm also identified a furin cleavage site in the Mgp2 sequence see . This waThe central motif for the Gla domain ExxxExC could be identified in the Mgp2, as well as in Mgp1 and Bgp sequences . HoweverMgp1 sequences  displayed well-conserved signal peptide, phosphorylation site, and general Gla domain . The expIn Bgp protein sequences, a signal peptide was also well conserved, followed by a furin cleavage site in the elephant shark that was not predicted in the small spotted catshark sequence because of a modification to KKSKR . A well-Mgp1 and Mgp2 display conserved intron/exon structure [four exons, ATG and peptide signal coding sequence in the first exon, docking site coding sequence in the third exon, and Gla domain in the fourth exon: see By aligning each cDNA sequence with the genomic locus, we could map the exonic junctions on the full length protein sequences of the small-spotted catshark: Mgp/Bgp sequences generated distinct expression patterns in the small-spotted catshark embryos by in situ hybridization. The selected stages of development were chosen in order to cover one time point before and another after the initiation of mineralization in the developing vertebrae , but its expression could not be observed in the vascular endothelium as seen with Mgp1  and 7.7 cm long embryos  to stage 32 (late organogenesis)  allowed catshark . Bgp expstage 32 . The resSyntenic and phylogenetic data gathered in this study allow drawing an evolutionary scenario for the genomic organization and diversification of the Mgp/Bgp gene family, under a most-parsimonious model of evolution . In the Bgp1 most probably occurred in the sarcopterygian or tetrapod stem lineages, while Bgp2 was lost convergently in actinopterygians and mammals , nor in Amphioxus nucleotide dataset (NCBI). Taken together, these three last arguments let us hypothesize that the evolution of Mgp/Bgp family cannot be explained by two rounds of whole genome duplications  rlication .Mgp/Bgp family are more complex than usually considered, as the Bgp gene found in cartilaginous fishes is not a one-to-one ortholog to the Bgp copy (Bgp1) found in actinopterygian (non-teleost) fishes or in mammals. In addition, the Bgp1 copy found in sarcopterygian genomes has gone through a translocation event that may have modified the transcriptional regulation, and therefore the function, of its orthologous copy in sarcopterygian fishes.With the evolutionary scenario presented here, the orthology relationships between jawed vertebrate genes of the Mgp gene was present in cartilaginous fishes  or a secondary (chondrichthyan-specific) recruitment of both genes that may share regulatory elements, given their genomic proximity. This strong expression in fin ceratotrichiae, that are not mineralized structures, is not congruent with a mineralization function of Bgp proteins in the small-spotted catshark ceratotrichiae.A specific site of expression in the small-spotted catshark was found with a very restricted site of expression of stal fin  without stal fin , and togstal fin . To our t fishes  and in tt fishes . These dBgp gene in the small-spotted catshark is not congruent either with the hypothesis of a function in the activation of mineralization: it is expressed in several soft tissues such as connective tissues surrounding muscles, nerve root and vasculature of the gills : no further approval by an ethics committee was necessary as the biological material is embryonic and no live experimental procedures were carried out.in situ expression experiments. TH performed the genome data mining. All authors contributed to the article and approved the submitted version.MD-T and TH designed the study, analyzed the data, and drafted the manuscript. NL performed the synteny and phylogenetic analyses. CM-M generated qPCR expression data. SV performed the The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


We show the primary control of temperature on silicate weathering given the monotonic increase of feldspar dissolution with it (0–30 °C), while controls of precipitation or topographic-lithological factors are regional and subordinate. We interpret the non-linear forcing of temperature on feldspar dissolution as depletion of more reactive plagioclase (relative to orthoclase) at higher temperature. Our results hint at stronger temperature-weathering feedback at lower surface temperature and support the hypothesis of increased land surface reactivity during the late Cenozoic cooling.Silicate weathering as an important negative feedback can regulate the Earth’s climate over time, but much debate concerns its response strength to each climatic factor and its evolution with land surface reorganisation. Such discrepancy arises from lacking weathering proxy validation and scarce quantitative paleo-constraints on individual forcing factors. Here we examine the catchment-scale link of silicate weathering intensity with various environmental parameters using a global compilation of modern sediment dataset ( How silicate weathering responds to and regulates Earth’s climate remain controversial. This study suggests the primary control of temperature on weathering intensity globally and the temperature-weathering feedback may be stronger in cold Earth. One long-standing hypothesis on such feedback is that an increase in volcanic CO2 emission causes a rise of surface temperature through the greenhouse effect; meanwhile, a higher temperature can enhance silicate weathering that, in turn, leads to the draw-down of atmospheric CO26. As such, the climate-weathering feedback hypothesis depends critically on the response strength of silicate weathering to temperature.Chemical weathering of silicate minerals plays a major role in maintaining the long-term habitability of Earth’s climate over geological timescales via a negative feedback mechanism7 and field studies on small watersheds10, it is commonly obscured over large spatial or temporal scales due to covariation of other factors with temperature or minor temperature variability. Many studies then seek other forcing mechanisms to interpret climate-weathering feedback, including hydrologic regulation (precipitation and runoff)11, tectonic uplift 3, and reorganization of land surface12. However, validation of these hypotheses over geological timescales is always challenging, because (1) paleo-weathering records may not be robust given the inconsistency in trends among various weathering proxies4 and (2) high-quality paleo-records on any of these individual forcing factors  are scarce for comparison.Although temperature-dependence of silicate weathering has been observed in laboratory experiments15 and weathering index of Parker (WIP)16 stand out as they are the most widely applied proxies due to their simple methodology and requirement of only major element measurements17. CIA is the proportion of immobile Al2O3 versus labile oxides  in the silicate fraction, while WIP is the sum of molar proportions of labile elements  weighted by their susceptibility to weathering (Methods). Both indices indicate the intensity of silicate weathering and partly track the hydrolysis reaction of feldspar18, which is the most abundant rock-forming mineral (53% of upper-crust)18. With an increase of weathering intensity, mobile cations in feldspar release into the dissolved phase, and immobile elements remain in solid residue by forming clay minerals19. As such, CIA and WIP increase and decrease, respectively16.As the present is a key to the past, one approach to test the link between environmental forcing factors and silicate weathering is to focus on an abundant modern dataset that covers a large environmental gradient. Two weathering proxies based on siliciclastic sediments, that are chemical index of alteration (CIA)n = 3828) across six continents for CIA-WIP calculation  were extracted to assess controls of silicate weathering and the potential of weathering index as a paleoclimate proxy.In this study, we compiled a major element dataset of fine-grained sediments from modern rivers . In principle, CIA varies within a restricted range around 40–50 for fresh bedrock20 and increases towards 100 during extreme weathering with e.g., kaolinite as the only weathering product.We restricted our analysis to silt- and clay-sized sediments to minimize mineralogical differentiation by hydraulic sortingp < 0.01 from two-sided Wilcoxon rank-sum test) to control of diverse environmental forcings (see next sub-section).We first observe a systematic decreasing trend in CIA with latitude Fig. , suggest22, river sediments23, and paleo-sedimentary archives24, and interpreted as controls of latitude-related climate variability. We confirm such large-scale latitudinal dependence based on a dataset of the highest spatial resolution ever (n > 3 × 103 compared to n < 102 in some other studies). Furthermore, the inverse correlation between CIA and latitudes echoes the pioneering study of Nesbitt and Young14 (1982) that interpreted CIA variations in the Proterozoic as changes in latitudes of depositional locations and thus in climate. Nevertheless, our observation on the latitudinal trend of CIA does not necessarily suggest any causal link between them, and the CIA is in fact controlled by environmental forcing factors as discussed in detail below.The similarly latitudinal trend in silicate weathering intensity has been observed in soil profilesn = 20) are described in Methods.Given the wide spatial coverage of our compiled dataset and thus the large gradient of each environmental variable Table , we can R) between each environmental forcing factor and CIA  or lithological factors (|R | ≤ 0.20). The enhancement of silicate weathering by plants is limited to certain environmental conditions related to soil matrix and generation of organic matters25, and weathering intensity can even be decoupled from plant productivity26. Ice cover is spatially limited to high-latitude and high-altitude regions with only local impact. Effect of source rocks likely controls weathering indices in coarse-grained sediments  given the enrichment of unaltered primary minerals, while overprints of weathering processes dominate in fine-grained sediments enriched in clay minerals27. Likewise, similar variability in mobile elements can be found in fine-grained topsoil from different rock types22. To illustrate the lithological effect more intuitively, we modeled the CIA of source rock for each sampling basin using the areal percentage of each rock type and their typical chemical compositions28. The correlation between sediment CIA and modeled CIA of the source rock is positive but rather weak  with CIA. The correlation with modeled sediment yield from BQART model29 (Methods) is also poor  positive correlation is observed between CIA and soil thickness. Globally, a higher weathering intensity corresponds to thicker soils, consistent with the notion that thick soil profiles are enriched in secondary clay minerals32.Basin-scale geomorphic characteristics such as drainage area, flow length, mean elevation, mean local slope, and regolith thickness show no strong correlations  control36. We attribute such discrepancy in data interpretation to either (1) covariation of both factors or (2) much smaller variability in one factor compared to the other in local- and regional- scale studies. Here we have the possibility to test the three mechanisms above given their poor correlation in our compiled dataset (R = 0.15) and the large gradient in each climatic factor  is the highest among all the variables investigated  to glacial processes, which can either drive the rapid supply of fresh materials for weathering via frost action and abrasion and formation of Fe-/Mg- rich secondary minerals41 such as chlorite (CIA of ~10014) or result in multiple sediment exposure-burial cycles42.Temperature control of weathering intensity is evident as the correlation coefficient between mean annual temperature (MAT) and CIA . The binning strategy is to minimize the CIA variability caused by factors other than the temperature at a regional scale  and its insensitivity to variability in chosen grain sizes, mineralogical sources, and dominant provenance lithology  is consistent with previous global-average estimates (71.6–75.5)45. When applying the MAT–CIA equation to quantitatively estimate paleo-MAT at a regional scale, it is worth noting that the CIA record could be affected by multiple non-climatic factors that may introduce a bias into the paleo-MAT reconstruction. First, changes in grain size (sand vs. silt-clay) and provenance in the given sedimentary archive can alter the CIA values47. In addition, spatial variability of other environmental variables such as topography and lithology may cause several-unit variations of CIA at a given MAT as observed in the modern sediment dataset  such impact can be largely canceled out by calculating relative changes in CIA (∆CIA). Accordingly, we can only estimate relative changes in MAT set Fig. . Hence, mates 71.–75.545. n = 10) that cover well-known warming/cooling events, in order to focus on the control of temperature and minimize potential effects of other factors. Selected events include the Permian–Triassic boundary (PTB), Paleocene–Eocene thermal maximum (PETM), Middle Miocene Climate Optimum (MMCO), Last Glacial Maximum (LGM), and Holocene Climatic Optimum (HCO) . We admit that such preliminary evaluation may need further supporting evidence from more fine-grained sedimentary records with well-constrained information on regional paleo-MAT and provenance. Nevertheless, it demonstrates the great potential of the MAT–CIA equation for providing the first-order estimate on paleo-temperature changes with an uncertainty of ~3 °C, especially in the deep time (108–109 years) when other paleo-temperature proxies such as biomarkers are not readily applicable.We then assess the utility of CIA-derived paleo-temperature by comparison with synchronous regional paleo-temperature records reconstructed by an independent approach . We selected literature paleo-CIA records  + 2, Fig. fdiss with CIA (Methods). There is a nonlinear response of feldspar dissolution to temperature, that is, a weaker response at higher MAT. We attribute such non-linearity to depletion of plagioclase and thus dominance of orthoclase weathering at the advanced stage of weathering under high MAT18  to orthoclase supply for weathering according to our scenario.The quantitative relationship between surface temperature and silicate weathering intensity over large spatio-temporal scales also offers valuable insights into the climate-weathering feedback. To link temperature with weathering-driven CO2 consumption via silicate weathering, previous global carbon cycle models apply theoretical equations based on weathering reaction kinetics48, but such equations are rarely validated by large-scale field observations. Here we propose to implement our MAT-fdiss equation into such models as an alternative empirical approach. For example, our feldspar weathering model built on this equation and feldspar hydrolysis reactions . Such estimate falls within the range predicted by the Arrhenius law on the temperature dependence of weathering reactions .To quantify COons Fig. , Methods2 consumption that will be of great potential for deep-time temperature reconstruction and carbon cycle modeling.In conclusion, the nonlinear forcing of surface temperature on feldspar dissolution (constrained by CIA) is caused by depletion of plagioclase relative to orthoclase at high temperatures. In another word, the surface temperature decrease could be accompanied by a higher proportion of more reactive plagioclase available for weathering, supporting the hypothesis that land surface reactivity has increased during the late Cenozoic cooling. We also propose a first-order quantitative relationship between surface temperature, feldspar dissolution, and CO2 prior to measurements, or samples were processed by X-ray fluorescence; samples only leached by HNO3 or HCl were not eligible. (4) Samples with a molar ratio of K to Al higher than 1 were excluded in this study as such ratio is even higher than K-feldspar (K/Al = 1) and is not composed of common silicate minerals. We finally compiled 3828 samples that met all the criteria above. A full reference list of the compiled dataset is provided in Supplementary Information. It is worth mentioning that large major element dataset from certain regions were sourced from geochemical baseline database including the NAWQA program in the conterminous US50, the AGDB2 program in Alaska (US)51, FOREGS program in Europe52, and NGSA program in Australia53.We aimed to compile a geochemical dataset of all river sediment samples from peer-reviewed papers and publicly available reports based on the following criteria. (1) Only fine-grained samples were compiled in this study to minimize the effect of mineralogical differentiation and contribution of unaltered parent materials. Selected samples include surface suspended particulate matter (SPM), bedload of silt-/clay- size (based on sample description) and bedload sieved to a narrow grain-size window . (2) Concentrations of major elements including Al, Ca, Na, K, and Mg were reported for CIA and WIP calculation. (3) Sediments were fully decomposed using multiple-acid digestion method (including HF) or fusion with e.g., LiBO18. Feldspar dissolution is the most common silicate weathering reaction given its high abundance in the upper continental crust. There are three major types of feldspar including potassium feldspar , albite, and anorthite . Their hydrolysis reactions can be simplified as follows54:The weathering process can be viewed as a transformation of primary minerals (feldspar) to secondary products  by neutralizing carbonic acid derived from the atmosphere14 and weathering index of Parker (WIP)16 directly indicate the dissolved loss of mobile cations and track the feldspar hydrolysis reaction to some extent. CIA is calculated as the molar ratio of immobile metal oxide to mobile metal oxides:15 to correct for Ca contribution from non-silicate fractions. CaO was first corrected for phosphate by subtracting 10/3 of P2O5 from CaO where available. If the remaining moles were less than that of Na2O, the CaO value was adopted. Otherwise, calcium carbonate contribution may be significant and CaO* was assumed to be equivalent to Na2O for CIA calculation, as this Ca/Na ratio is reasonable in silicate minerals. McLennan15 noted that such treatment may slightly underestimate CIA values if weathering loss of Ca is more rapid than that of Na; but in catchments dominated by basic rock and weak weathering, such treatment may slightly overestimate CIA because a certain proportion of Ca is derived from Ca-silicates other than feldspar. Since a uniform data-processing procedure is a prerequisite for a global-scale comparison, we sticked to McLennan’s approach and assumed that a minor bias in CIA calculation on a local scale is much smaller than the variability caused by each forcing factor49 and can be averaged out over a global scale.Chemical index of alteration (CIA)WIP is calculated as the molar proportion of mobile elements and weighted by the bond strength of each element with oxygen as a measure of susceptibility to weathering:55. Both CIA and WIP meet such requirements but many other weathering proxies do not. Alpha (α) indices19 using a ratio of one immobile element to one mobile element can only track the mobility of a specific element and a certain stage of weathering. Isotopic tools like Li isotopes and K isotopes are limited by their small size of the dataset available due to strict requirements on precise measurement, and they either do not monotonically increase with weathering intensity56 or can show a small variability during weathering processes57. The rate ratio of weathering to denudation (W/D) based on measurements of dissolved and solid load58 is widely used and can be instructive for understanding weathering kinetics. However, its integration timescale is too short (100–101 yr). As such, this proxy may be subject to anthropogenic impact and can not be applied in the geological past for reconstructing paleo-signal of weathering and thus climate.To delineate the global pattern of silicate weathering intensity, several requirements on weathering index need to be met: (1) applicability to diverse rock types and large dataset available across the globe, (2) incorporation of elements with a range of mobility during weathering, and (3) monotonic response to silicate weathering59. The upstream basin outline of each sample was calculated using Shuttle Radar Topography Mission (SRTM) 90-m resolution Digital Elevation Model (DEM) (https://opentopography.org/). At latitudes of >~60° where no SRTM data is available, alternative sources of topographic data were adopted from http://viewfinderpanoramas.org/dem3.html. All the basin-averaged environmental control variables including climatic, geomorphic, lithological, and land cover metrics were extracted using the corresponding basin outline and based on a publicly available gridded dataset.We used Matlab-based software TopoToolBox 2 for digital terrain analysis and gridded dataset processing60) with ~1 km resolution, and actual evapotranspiration was calculated from Global High-Resolution Soil-Water Balance dataset with ~1 km resolution61. (2) Geomorphic metric: flow length (km), drainage area (km2), mean local slope (°), mean elevation (m), and maximum relief (m) were calculated from SRTM 90-m resolution DEM using TopoToolBox, and upland hillslope soil and regolith thickness (m) were calculated from a gridded global dataset with ~1 km resolution62. The regolith includes soil and weathered bedrock and is estimated as the depth to the permanent water table62. (3) Lithological metric: the areal percentage of each major rock type including acidic-intermediate rock, basic rock, clastic sedimentary rock, carbonate rock, and metamorphic rock were calculated from the global lithological map database GLiM, which represents the rock types of the Earth surface with ~1.23 × 106 polygons63 but might be less precise in locations with large lithological heterogeneity; the rock erodibility index was calculated from a gridded dataset with ~0.1 degree resolution64. (4) Land cover metric: the areal percentage of vegetation cover , tree cover , and ice-snow cover were calculated from a gridded dataset (GLC2000) with ~1 km resolution65. All the original gridded datasets were downscaled to a resolution same to DEM (90 m) for metric calculation.(1) Climatic metric: mean annual temperature , temperature seasonality , mean annual precipitation , and precipitation seasonality  were calculated from gridded climate dataset  drain a large gradient of each environmental variable, and thus their basin-averaged values can be well homogenized and it is difficult to distinguish the effect of one factor from the others. (3) The geospatial analysis requires latitude and longitude of one sample to delineate the outline of its upstream basin, and thus samples without location information could not be used. For some downstream/outlet samples we did estimate such information using Google Earth if the original study provided a geographical map. We finally processed 2989 samples that met all the criteria above.We only extracted basin-scale environmental control variables for a sub-sample set compiled in this study based on criteria as follows. (1) For samples collected at the same location but sieved to different grain sizes  or collected using different approaches , we only chose the fraction of the finest grain size for environmental variable extraction. (2) The geospatial analysis was only performed on samples with an upstream area of <1029 to derive a sediment yield of each studied basin for comparison with weathering indices, as most of our compiled dataset were from small- and median-sized basins with no hydrological information available. The BQART model has been applied in catchments with a wide range of sediment yields (100–104 t/km2/yr)29 and only requires inputs of topographic, lithological, and climatic parameters that can be extracted from the available gridded dataset. The model equations are as follows:Ys is sediment yield in t/km2/yr, ω is a coefficient as 0.0006 Mt/yr, A is drainage area in km2, Rmax is maximum relief in km and MAT is mean annual temperature in °C. Q is water discharge in km3/yr and calculated by multiplying runoff  by drainage area. B is a coefficient accounting for geological and human factors and calculated as:Ag is the areal percentage (range of 0–1) of ice and snow cover and indicates glacier erosion, Lr is the basin-wide rock erodibility index, TE is the sediment trapping efficiency and set to 0 in this case, and Eh is a human-influenced soil erosion factor and set to 1 as weathering indices commonly integrate over a timescale longer than that of human impact.We applied the BQART modelAll the input parameters were derived from the geospatial analysis mentioned above. Dataset of input parameters and modeled sediment yield are reported in Supplementary Data To test if the correlation between MAT and CIA persists for sediments of different features, we performed a sensitivity test on the MAT–CIA relationship by deriving such fitting equations separately (1) for sediments of different grain sizes, that is, SPM and clay fraction vs. bedload of <63 μm, 2) for sediments weathered from different mineralogical sources , and converted CIA to the proportion of feldspar dissolution (fdiss):We assumed that the hydrolysis reaction, that is, feldspar dissolution and formation of kaolinite, is the dominant reaction that controls variability in fine-grained CIA over a global scalefdiss relation is consistent for all types of feldspar  and weathering-driven atmospheric CO2 consumption using the following procedure.We established a simplified relation between the proportion of feldspar dissolution . Such rate ratios calculated using kinetic experiment data reproduced the weathering trend  in some soil profiles18 and may be reasonable estimates here. (2) We estimated the global annual export flux of feldspar (Ffs) by multiplying the percentage of feldspar in the upper continental crust (53% in volume)18 by the global annual riverine flux , and Ffs = 4.44 × 1013 mol/yr. (3) We calculated changes in the flux of each released cation  relative to the modern based on changes in fdiss :(1) We first estimated the relative release rate of Ca, Na, and K during feldspar dissolution as the feldspar is characterized by three endmembers  of different chemical compositions. To do so we multiplied the molar proportion of each kind of feldspar in the average upper continental crustFcation above to changes in transient CO2 consumption rate (mol C/yr). Specifically, feldspar hydrolysis reactions (eqs. 1–3) indicate the alkalinity supplied by feldspar weathering and delivered by e.g., rivers: release of 1 mol Ca consumes 2 mol CO2 and release of 1 mol Na or K consumes 1 mol of CO2. (5) The change in CO2 consumption rate was then normalized to the modern global CO2 consumption rate by silicate weathering (1.17 × 1013 mol C/yr)66. The modeling results are shown in Fig. 2 consumption could be an upper-bound limit. Nevertheless, such coarse sediment contribution and its bias on our calculation might be subordinate: (1) the suspended load may dominate in most of median- and large-sized catchments as its proportion increase with drainage area to some extent 67; (2) the fine fraction (clay-silt) can even prevail in the suspended load of small fast-eroding mountainous catchments during the flood events68.(4) We converted each ∆69:rT and r0 are the dissolution rates at temperature T (in K) and at reference temperature T0 (287.15 K or 14 °C44 in this case), respectively, Ea is the activation energy for the reaction (kJ/mol), and Rg is the gas constant (8.314 J/mol/K). We here adopted a range of Ea (36–107 kJ/mol) determined from orthoclase and plagioclase at near-neutral pH70, although discrepancies in Ea may exist in literature due to diverse experimental conditions such as solution chemistry7. In general, such a first-order estimate on temperature dependence is in agreement with our feldspar weathering model  falls within this range. Furthermore, the concave shape of the MAT-CO2 consumption relation is different from the convex form of the exponential Arrhenius law (Fig. Ea may vary with temperature in our compiled dataset across diverse geographic and lithological settings. With an increase in temperature, the mineral type available for weathering might shift from plagioclase to orthoclase and thus cause a decline in Ea7.For comparison purposes, the Arrhenius equation that describes the temperature dependence of mineral dissolution rates was also applied to estimate relative changes in silicate weathering fluxesSupplementary InformationDescription of Additional Supplementary FilesSupplementary Data 1–3


Drosophila have been historically used to provide important insights in the sleep and circadian sciences. However, no experiments to date have evaluated how immediate sleep need or recent sleep history affects their pacemaker’s phase readjustments to light. We did so in the current study by (1) forcing separate groups of animals to stay awake for 1 or 4 h after they were shown a broadspectrum pulse , or (2) placing them on a restricted sleep schedule for a week before light presentation without any subsequent sleep disruption. Forced sleep restriction, whether acute or chronic, did not alter the size of light-induced phase shifts. These data are consistent with observations made in other diurnal animals and raise the possibility, more broadly, that phototherapies applied during sleep—such as may be necessary during the winter months—may still be efficacious in individuals experiencing sleep-continuity problems such as insomnia.Previous investigations in humans and rodent animal models have assessed the interplay of sleep in the circadian system’s phase responses to nighttime light exposure. The resulting data have been mixed, but generally support a modulatory role for sleep in circadian photic resetting (not an absolute requirement).  Drosophila have long been used as platforms for reaching fundamental understandings of both circadian timekeeping and homeostatic sleep regulation [Drosophila was predicated on the animals sleeping within 4 h after presentation of a light stimulus or having a well-rested, undisturbed sleep history.Mutual interactions between the circadian pacemaker and sleep homeostat guide choreographed transitions in sleep/wake behavior each day and shape the progression of internal sleep architecture across the subjective rest period ,2. Givengulation ,11. The Sleep deprivation for 1 or 4 h pursuant to light presentation in the early part of the night at ZT14 (2 h after lights-off) did not impact circadian resetting of fly locomotor rhythms . The magnitude of delay shifts recorded in animals enduring several nights of limited sleep opportunity (4.80 ± 0.17 h) were not distinguishable from either those experiencing short-term sleep restriction or those with a normal sleep history before and after the light pulse.Animals were demonstrably active during the period in which mechanical perturbation was applied  is promising from the standpoint of using precision light emission devices to rehabilitate the circadian system during sleep ,19. ManyDrosophila ananassae were expanded from an isofemale line maintained at the National Drosophila Species Stock Center (NDSSC) at Cornell University (stock # 14024-0371.16). Through the embryonic and larval stages, the animals were maintained in DigiTherm® incubators at 25 °C  and entrained to a 12:12 light-dark (LD) cycle . For studies on sleep deprivation and phase-shifting, female flies were selected as late-stage “pharate-adult” pupae, moved onto fresh food, and housed in groups of 5 to 6. Three days post-eclosion, individual animals were placed without anesthesia into Pyrex glass chambers  containing a plug of corn flour nutritional yeast–agar medium on one end  and a cotton fitting on the other. They were then loaded into MB5 monitors, where their motion was detected and counted with 17 independent infrared beams stationed across the 80 mm length of the housing tube . Movement information from the beams was transmitted over modem/USB to a computer acquisition software every 30 s. MB5 units were situated in a climate-controlled vivarium  comparable to the ones used in colony management and under comparable ambient lighting conditions .High-resolution activity monitors were used to track and visualize circadian variations of behavioral activity in diurnal flies for each experimental protocol . DrosophAn Aschoff Type II paradigm was used to quantify the effects of light exposure (with and without sleep deprivation) on phase resetting of locomotor activity rhythms . Flies cp = 0.05. In total, 117 animals were tested.On the heels of the various treatments, flies were left to free-run in DD for 3–4 days. Actogram plots reflecting daily locomotor activity were created by binning raw 30 sec time series data of individual animals. Phase shifts of behavior were calculated by determining the horizontal distance between regression lines fitted through software-called activity onsets 2 days prior and 2–4 days after light administration  ,25. Chan


Sexual maturation causes loss of fish muscle mass and deterioration of fillet quality attributes that prevent market success. We recently showed that fillet yield and flesh quality recover in female trout after spawning. To gain insight into the molecular mechanisms regulating flesh quality recovery, we used an Agilent-based microarray platform to conduct a large-scale time course analysis of gene expression in female trout white muscle from spawning to 33 weeks post-spawning.In sharp contrast to the situation at spawning, muscle transcriptome of female trout at 33 weeks after spawning was highly similar to that of female trout of the same cohort that did not spawn, which is consistent with the post-spawning flesh quality recovery. Large-scale time course analysis of gene expression in trout muscle during flesh quality recovery following spawning led to the identification of approximately 3340 unique differentially expressed genes that segregated into four major clusters with distinct temporal expression profiles and functional categories. The first cluster contained approximately 1350 genes with high expression at spawning and downregulation after spawning and was enriched with genes linked to mitochondrial ATP synthesis, fatty acid catabolism and proteolysis. A second cluster of approximately 540 genes with transient upregulation 2 to 8 weeks after spawning was enriched with genes involved in transcription, RNA processing, translation, ribosome biogenesis and protein folding. A third cluster containing approximately 300 genes upregulated 4 to 13 weeks after spawning was enriched with genes encoding ribosomal subunits or regulating protein folding. Finally, a fourth cluster that contained approximately 940 genes with upregulation 8 to 24 weeks after spawning, was dominated by genes encoding myofibrillar proteins and extracellular matrix components and genes involved in glycolysis.Overall, our study indicates that white muscle tissue restoration and flesh quality recovery after spawning are associated with transcriptional changes promoting anaerobic ATP production, muscle fibre hypertrophic growth and extracellular matrix remodelling. The generation of the first database of genes associated with post-spawning muscle recovery may provide insights into the molecular and cellular mechanisms controlling muscle yield and fillet quality in fish and provide a useful list of potential genetic markers for these traits.The online version contains supplementary material available at 10.1186/s12864-021-08228-3. As a result of the increasing demand for fish consumption, aquaculture has become the type of animal food production with the fastest growth in recent decades . Muscle Several transcriptomic analyses have been performed to decipher the mechanisms underlying muscle changes observed during the sexual maturation. An initial microarray gene expression study showed that sexual maturation-induced atrophy of axial muscle in gravid trout compared to sterile trout was associated with (i) upregulation of genes involved in catheptic and collagenase proteolytic pathways and genes involved in mitochondrial aerobic ATP production and (ii) downregulation of genes regulating RNA processing and protein biosynthesis and genes encoding myofibrillar and extracellular matrix proteins . FurtherWe recently showed that sexual maturation-associated deterioration in flesh quality can be reversed in trout post spawning. Notably, we observed an increase in fillet yield during the post spawning period, suggesting an accretion of protein mass in muscle fibres and a significant increase in intramuscular fat content . RestoriTo gain insight into the transcriptomic changes associated with flesh quality restoration after spawning we performed microarray hybridisations using RNA extracted from the muscle tissues of mature female trout sampled at 0, 2, 4, 8, 13, 16, 24, and 33 weeks after spawning  and from the muscle tissues of immature (control) female trout. Immature (control) female trout were sampled at the beginning (C0) and at the end (C33) of the experiment and belonged to the same cohort as trout that experienced spawning.t test , we first compared the muscle transcriptomes in mature and in immature (control) trout at the beginning and end of the experiment. We found that the muscle transcriptome of trout that had just spawned (PS0) was clearly different from that of control trout (C0), as revealed by the identification of approximately 4700 unique DEGs between PS0 and C0. In contrast, the trout muscle transcriptome at 33 weeks post-spawning (PS33) was virtually the same as that found in the 33 weeks control (C33), as indicated by the lack of identification of any DEGs between PS33 and C33 via unpaired t test. This shows that the trout muscle transcriptome after spawning evolved to eventually become similar to that of trout that did not spawn, which is consistent with the post-spawning muscle restoration and flesh quality recovery we recently reported [Using an unpaired reported .Next, we aimed to characterize the changes in the female trout muscle transcriptome associated with flesh quality recovery following spawning. For this purpose, an ANOVA (Benjamini-Hochberg method with a FDR < 0.05) and a fold change > 3 were used as criteria for defining genes whose expression levels were significantly different across all the stage of sampling . This analysis led to the identification of approximately 3340 unique differentially expressed genes (DEGs). Hierarchical clustering of DEGs resulted in the formation of four major gene clusters (clusters I-IV) . In addition, GO terms linked to proteolysis were enriched for genes regulating lysosome activity and genes participating in autophagy , ribosome biogenesis (which determines translation capacity) and protein folding. Cluster II was also enriched with genes encoding components of mitochondria, such as genes encoding mitochondrial ribosomes. However, in contrast to cluster I, cluster II did not include genes involved in mitochondrial oxidative phosphorylation. Overall, cluster II was dominated by genes involved in cellular biosynthetic processes necessary for protein mass accretion  with that induced by a fasting-refeeding schedule  and thatSexual maturation causes loss of fish muscle mass and deterioration of fillet quality attributes that prevent market success. We recently showed that fillet yield and flesh quality in mature female trout that have spawned can evolve to become similar to those of control immature female trout . In thisWe have previously reported that muscle firmness decreases during the post-spawning period . Our traA striking feature of the transcriptomic signature following spawning is the upregulation (cluster IV) of a large set of genes encoding structural components such as extracellular matrix proteins that form the intricate matrix network surrounding individual myofibres and blocks of myofibres and sarcomeric proteins that assemble to generate contractile myofilaments. The overexpression of extracellular matrix proteins during the post-spawning period is likely to contribute to muscle structure rebuilding and concurrent flesh quality recovery. In keeping with this latter point, the amount and composition of the extracellular matrix have been reported to be determinants of textural quality . Thus, sThe overexpression of contractile protein-encoding genes (cluster IV) and the enrichment in functional categories related to protein biosynthesis and maturation (cluster II) suggest that accretion of protein mass occurs in muscle fibres after spawning. Further supporting the view of hypertrophic growth of muscle fibres, we also found (cluster II) strong enrichment of genes stimulating ribosome biogenesis, a crucial mechanism used by skeletal muscle to regulate protein synthesis and control muscle mass . Our obsIn this study, we show that the recovery of fillet yield and flesh quality that follows trout spawning is associated mainly with dynamic transcriptional changes promoting anaerobic ATP production, muscle fibre hypertrophic growth and extracellular matrix remodelling. Many genes from the post-spawning transcriptional signature are potentially important determinants for fish muscle growth and/or flesh quality. As such, they deserve further expression and functional analyses and could be assessed for use in marker-assisted selection of trout with superior muscle yield and fillet quality traits.(Oncorhynchus mykiss) from the same autumnal strain cohort were reared in the INRAE’s experimental facilities  France). After ovulation and stripping, females that spawned on the same date were placed into a circular 2-m-diameter tank randomly chosen containing 2 m3 of water. A total of nine experimental groups of post-spawning fish were created. The fish were fed the same diet throughout the course of the trial. During sampling, post-spawning fish (n = 20) from the same tank were sequentially slaughtered at 0, 1, 2, 4, 8, 13, 16, 24, and 33 weeks after ovulation. Immature (control) female trout (n = 20) belonging to the same cohort as trout that experienced spawning were also sampled at the beginning (C0) and at the end (C33) of the experiment. At slaughter, the fish were anaesthetized with Tricaine Pharmaq (5 g/100 L) in a 500 L tank, killed by a blow to the head, and then bled by gill cutting. After death, quality parameters of the fish were measured, and a slice of white skeletal muscle was carefully dissected from the dorsal region of the musculature, frozen in liquid nitrogen and stored at − 80 °C until RNA extraction. Muscle tissues of eight trout at different post-spawning (PS) timepoints  as well as muscle tissues of eight control (immature) trout (C0 and C33) were subjected to RNA extraction and transcriptome analysis. The fish used for transcriptome analyses were selected on the basis of their carcass weight which had to be similar to the median value of the group to which they belonged.The fish used in this study have been previously described . DiploidTotal RNA extraction was performed using TRIzol reagent  reagent following the manufacturer’s instructions. RNA integrity was assessed with an Agilent 2100 Bioanalyzer. Cy3-labelled cRNA generation and hybridization were performed as previously described . Hybridip-val < 0.05) was used to specifically compare the muscle transcriptome of trout that had just spawned (PS0) with that of control trout (C0) and to compare the muscle transcriptome of trout at 33 weeks post-spawning (PS33) with that of 33 week control trout (C33). A one-way ANOVA (Benjamini-Hochberg method with an FDR < 0.05) and a fold change > 3 were used as the criteria for defining genes whose expression levels were significantly different across all the samples  examined. For clustering analysis, the data were median-centred and average linkage clustering was carried out using CLUSTER software (version 3.0). The clusters were visualized with TreeView (version 1.1.6r4) [Hybridized slides were rinsed and scanned at a 3-μm thickness with an Agilent DNA Microarray Scanner. Fluorescence intensity was calculated using the standard procedures found in Agilent Feature Extraction (FE) software 10.7.3.1. The arrays were normalized and log-transformed using GeneSpring software (version 14.9). An unpaired t test (Benjamini-Hochberg-corrected 1.1.6r4) . GO enri1.1.6r4) , 40.Additional file 1.Additional file 2.Additional file 3.Additional file 4.Additional file 5.


Penfield’s motor homunculus describes a caricaturised yet useful representation of the map of various body parts on the pre-central cortex. We propose a supplemental map of the clinically represented areas of human body in pre-central cortex and a novel subcortical corticospinal tract map. We believe this knowledge is essential for safe surgery in patients with eloquent brain lesions. A single-institution retrospective cohort study of patients who underwent craniotomy for motor eloquent lesions with intraoperative motor neuromonitoring  between 2015 and 2020 was performed. All positive cortical and subcortical stimulation points were taken into account and cartographic maps were produced to demonstrate cortical and subcortical areas of motor representation and their configuration. A literature review in PubMed was performed. One hundred and eighty consecutive patients  were included in the study with 81.6% asleep and 18.4% awake craniotomies for motor eloquent lesions  with intraoperative cortical and subcortical motor mapping. Based on the data, we propose a supplemental clinical cortical and a novel subcortical motor map to the original Penfield’s motor homunculus, including demonstration of localisation of intercostal muscles both in the cortex and subcortex which has not been previously described. The supplementary clinical cortical and novel subcortical motor maps of the homunculus presented here have been derived from a large cohort of patients undergoing direct cortical and subcortical brain mapping. The information will have direct relevance for improving the safety and outcome of patients undergoing resection of motor eloquent brain lesions.The online version contains supplementary material available at 10.1007/s00429-021-02274-z. Homunculus as described by Penfield and Boldrey in 1937 after bipolar direct cortical stimulation (DCS) in 126 awake patients has provided the foundation for intraoperative motor mapping in patients undergoing craniotomy for brain lesions , allow accurate measurement of the distance from CST during intraoperative stimulation to achieve safe lesion resection and avoid inadvertent injury to CST central to preserving the quality of life of the patients .Despite these studies and the data gathered, no updated homunculus nor subcortical map, based on intra-operative direct cortical/subcortical stimulation, has been proposed since the original 1937 work In this study, we propose a supplemental motor cortical map and a novel motor subcortical map of the configuration of the corticospinal tract initially described by Penfield  for the patients. These helped as starting points to define the relationship between the lesions and eloquent motor brain areas, guiding intra-operative mapping with cortical/subcortical stimulation. Thereafter, all positive documented cortical and subcortical points of stimulation confirmed with intraoperative neuromonitoring were recorded and plotted over cartographical maps by utilizing the intraoperative numerically labelled pictures and correlating with intra-operative neuro-navigation MRI, corrected for intra-operative brain shift using the ioUS, and immediate post-operative anatomical T1 post gadolinium MRI. The overlap of stimulated points were also noted. Demographic, clinical and surgical data were collected from patients’ medical records. A PubMed literature review was performed, in order to investigate if a subcortical motor map was previously described, with the MeSH items [ OR  OR  AND Motor AND corticospinal tract)] with filters for “articles with abstracts, adult (19 + years), English language articles, human studies and articles published between 1990 and 2020”. The demographic and clinical data were analysed with Microsoft Excel 2020.A single-centre retrospective study was performed between January 2015 and January 2020 to collect intraoperative data on consecutive patients who underwent craniotomy for eloquent brain lesions with intraoperative cortical and subcortical motor neuromonitoring at our quaternary referral neurosurgical centre. Patients were consented for intraoperative neuromonitoring including motor mapping. Prior to the surgery, patients underwent a range of pre-operative brain mapping investigations to include fMRI, DTI and nTMS to evaluate the feasibility of lesion resection, determine the best surgical approach and help consent the patient based on individual’s risk profile. At surgery, 3-dimensional (3D) reconstructed structural MRI, tractography from DTI, fMRI hotspots and 3D reconstructed nTMS motor stimulation points were projected onto the brain with augmented reality using ZEISS KINEVOThree different tasks were performed: lip smacking, finger-tapping and foot rocking . The cortical activated areas were used to constrain the probabilistic tractography.b-value: 1500; diffusion directions: 64; diffusion mode; multi-directional diffusion weighting; field of view: 32 cm; voxel size, 2.5 × 2.5 × 2.5 mm; TR/TE:9500/86; scan time:11:35 min. The deterministic tractography was modelled in 3D with StealthViz Medtronic Software    were recorded with direct electrical monopolar stimulations of primary motor cortex Fig. . Train oSubcortical motor evoked potentials (scMEPs) were recorded using modified monopolar suction probe and monopolar probe   to delineate the margins of the tumour and post resection cavity. It provided the configuration, depth and location of the lesion with respect to the motor cortex and subcortical CST identified with subcortical stimulation and helped to correct for any intra-operative brain shift .n = 180). Cortical and subcortical mean stimulation threshold for leg , foot , intercostal muscles , arm , hand  and face  were recorded during the procedures . An example of isolated subcortical stimulation recording (scMEP) during intraoperative subcortical mapping with electrode placed in the intercostal muscles is shown in Supplemental Figure 5. These findings aided in the illustration of the proposed maps.PubMed literature review resulted in identification of 141 articles. The articles were reviewed to identify data on subcortical mapping of specific motor areas  of patients who underwent craniotomy for brain lesions. Articles that did not show individual-motor-area  subcortical mapping were excluded. Six articles were identified and have been summarised in Supplemental Table 1. There was no literature on a map for the subcortical motor areas.The proposed supplemental cortical map consists of new addition of cortical representation of intercostal muscles in the existing Penfield’s motor homunculus Fig. .The proposed subcortical novel map of the corticospinal tract along the corona radiata Fig.  providesUnderstanding the topography of the motor pathway at both cortical and subcortical levels is crucial for neurosurgeons during surgery for motor eloquent brain lesions if risk of deficits is to be minimised. Penfield’s 1937 description of the arrangement of the motor function onto the homunculus, although a simplified map, provides a representative image of the motor arrangement of function onto the precentral cortex  predominantly begins in the pre-central gyrus (M1), making its way caudally through the corona radiata into the internal capsule, condensing the fibres with a unique formation and thus producing a swirl-like configuration with the twist of the fibres subcortically Below is the link to the electronic supplementary material.


Significantly higher AGR3 and S100P immunostaining was observed in ciliated cells of the LE of women with recurrent reproductive failure compared with parous women, suggesting aberrant subcellular location-associated pathophysiology for these conditions. The nuclear localisation of S100P may allow transcriptional regulatory function, which is necessary for implantation of a viable pregnancy. Further work is thus warranted to assess their utility as diagnostic/therapeutic targets.Recurrent implantation failure (RIF) and recurrent pregnancy loss (RPL) are distressing conditions without effective treatments. The luminal epithelium (LE) is integral in determining receptivity of the endometrium, whereas functionalis glands and stroma aid in nurturing early embryo development. Calcium signalling pathways are known to be of vital importance to embryo implantation and pregnancy establishment, and anterior gradient protein 3 (AGR3) and S100 calcium-binding protein P (S100P) are involved with these pathways. We initially examined 20 full-thickness endometrial biopsies from premenopausal women across the menstrual cycle to characterize levels of AGR3 protein in each endometrial sub-region at the cellular level. A further 53 endometrial pipelle biopsies collected in the window of implantation were subsequently assessed to determine differential endometrial AGR3 and S100P levels relevant to RIF ( Recurrent reproductive failure is a devastating reproductive health issue that may manifest in two ways: (i) recurrent implantation failure (RIF) during in vitro fertilization (IVF) treatment cycles or (ii) recurrent pregnancy loss (RPL). RIF affects approximately 10% of women undergoing IVF , and theThe luminal epithelium (LE) (the uppermost layer of the endometrium) is the first maternal layer of cells that an embryo communicates with during the window of implantation (WOI) ; therefoCalcium signalling pathways are of vital importance to embryo implantation and early pregnancy establishment ,17. AnteS100 calcium-binding protein P (S100P) was originally discovered in 1992 from placental isolates and is a member of the family of S100 low molecular weight calcium binding proteins implicated in calcium sensing and signal transduction ,23. MostIn RIF, good-quality embryos fail to attach to the endometrium, potentially highlighting a defect in the LE, whereas in RPL, pregnancies fail to progress after implantation; thus, endometrial functionalis glands and stroma are anticipated to play an important role in the pathophysiology. Examining particular proteins important to these sub-endometrial areas may provide novel diagnostic and therapeutic targets. Considering the important role of AGR3 in the regulation of ciliary beat frequency and high S100P expression in the WOI, we hypothesised that women with recurrent reproductive failures (RIF or RPL) could have altered levels of these calcium-binding proteins in the WOI when compared with parous women, thus playing an important role in embryo transmission and implantation.AGR3 levels in healthy human endometrium across the menstrual cycle have not been previously demonstrated, and initially we assessed the immunoexpression of AGR3 in healthy, full-thickness premenopausal endometrium from a cohort of 20 women undergoing hysterectomy for non-endometrial pathology  included 53 patients  who underwent a pipelle biopsy in the WOI to study both the LE and functionalis layer of the endometrium. The average age of the women included in cohort 2 was 39 years ; the parp < 0.01), cilial (p < 0.05), and cytoplasmic (p < 0.01) AGR3 staining scores were seen in the LE compared with the glandular epithelium across all groups (p < 0.05) (p < 0.01) compared with the fertile controls  C. Ciliatcontrols D.p < 0.01) S100P immunostaining compared with the control samples +2 and LH+7 revealed distinct mRNA profiles that correlated with immunohistochemistry-based assessment of the corresponding protein expression levels . DespiteAlthough we only employed immunohistochemistry, and no functional studies have been conducted to confirm a role for the two calcium binding proteins we investigated in the implantation process, significant differences were identified and the importance of tissue positional integrity was highlighted. Further work is warranted to assess their utility as diagnostic and therapeutic targets. Although our initial hypothesis also included that different staining patterns would be seen between women with RPL in comparison with those with RIF, our data did not demonstrate this difference in the levels of the two proteins we examined in our cohort of women. We excogitate that further discriminatory differences will be present with increased sample size and number of molecules examined, highlighting the need for further work.The obvious differences seen between women with and without RPL or RIF highlight that both AGR3 and S100P proteins may have a functional role in fertility. This study paves the way for further targeted research regarding the LE and implantation. The endometrium cannot be treated as one entity, and care needs to be taken to ensure the individual elements involved in implantation are studied as such. Future studies require the adoption of appropriate methodologies that appreciate and highlight the cell type and region-specific differences relevant to the endometrial pathology. Only then can progress be made to demonstrate how these differences could be targeted with efficient treatment to positively influence the outcomes of millions of women suffering with recurrent reproductive failure.Full-thickness endometrial biopsies were collected from 20 women , forming cohort 1  and histological criteria ,27), andImmunohistochemistry (IHC) was performed as previously described . Section® with DAPI (Vector Laboratories). Images were captured from a Nikon Eclipse 50i microscope using NIS Elements-F software .Immunofluorescence staining was performed on 3 μm FFPE tissue sections. Following antigen retrieval in a pressure cooker for 2 min in 0.01 M citrate at pH 6.0, sections were blocked and incubated with primary antibodies ) overnight at 4 °C. Appropriate secondary antibodies were incubated for 2 h at room temperature, and sections were mounted in VECTASHIELDPercentage positive (%P) and quick score (QS) were used as previously described ,29 to scp < 0.05 (*), highly significant when p < 0.01 (**), and very highly significant when p < 0.001 (***). Box and whisker plots show the median , interquartile range (box), and data range (whiskers).Statistical analysis was performed using GraphPad-Prism Version 5. Non-parametric Mann–Whitney U tests were used to compare groups. Statistical significance was inferred when http://www.ingenuity.com, accessed on 1 February 2021). Path explorer was used to identify specific known molecular interactions between implantation of embryo, S100P, AGR3, and AGR2.A mechanistic network was created using the Ingenuity Knowledge Base via the Ingenuity Pathways Analysis software (IPA, Ingenuity Systems,


Sequestered disc fragments do not have indistinctive features and often share the clinical and radiological presentation as spinal neoplasms making their diagnosis and treatment a clinical challenge.We report a rare case of sequestered lumbar disc fragment at the level of L2-L3 in a 70-year-old male who presented to the ER complaining of six years' history of low back pain with acute onset lower extremities weakness for six days, associated with right foot drop. He was admitted for tumor workup as the MRI showed diffuse bone high signal intensity throughout the spine with a soft tissue epidural mass at L2/3, causing severe compression on the cauda equina nerve roots. The patient underwent L2-L3 decompression and fixation, mass excision, multiple open biopsies. Soft tissue biopsy of the mass revealed fibrocartilaginous tissue consistent with the intervertebral disc, while the bone biopsy was diagnostic of acute leukemia. The patient was observed postoperatively with unremarkable complications. He did well with physiotherapy, and there was a remarkable improvement of his right lower extremity power reaching 4/5.Our case presented a rare phenomenon in which sequestered disc fragments manifested clinically and radiologically as a spinal neoplasm. Vigilant history taking and physical examination are paramount; a physician should be watchful for any red flags that may warrant further investigation such as in our case. Migration of herniated disc fragments is considered extremely rare given the contained anatomical barriers. These sequestered disc fragments do not have indistinctive features and often share the clinical and radiological presentation as spinal neoplasms making their diagnosis and treatment a clinical challenge ,2. In thThis is a 70-year-old male, known to have hypertension, diabetes, benign prostatic hyperplasia, myocardial infarction on dual antiplatelets, presented to the ER complaining of six years' history of low back pain with acute onset lower extremities weakness for six days, associated with a new right foot drop. No reported history of traumas, or infections, no change in bowel and bladder habits. His examination revealed right-sided L2, L3, L4 power of 2/5, L5, S1 of 3/5. Sensation and reflexes were normal bilaterally. He was admitted for tumor workup as the MRI showed diffuse bone high signal intensity throughout the spine with a soft tissue epidural mass at L2/3 causing severe compression on the cauda equina nerve roots Figures -1e. The A wide variety of non-neoplastic spinal diseases including sequestered intervertebral disc herniation may present as mass lesions making preoperative diagnosis and treatment a challenge for many surgeons. One of the early cases of sequestrated disc fragments was reported as protruded annulus fibrosus rotated posteriorly into the spinal canal . The patWe performed a PubMed and Google Scholar search of all reported studies of sequestrated lumbar disc herniation published to date. The following keywords were searched: Sequestered disc herniation, lumbar disc fragment, and spinal neoplasm. We identified 38 cases of lumbar disc fragments from 12 studies (Table Contrast injection is used to differentiate between avascular disc fragments from other spinal neoplasms with the presence of rim-like peripheral enhancement. This finding is suggestive more of an inflammatory and non-neoplastic process . Other cOur case presented a rare phenomenon in which sequestered disc fragments manifested clinically and radiologically as a spinal neoplasm. Vigilant history taking and physical examination are paramount; a physician should be watchful for any red flags that may warrant further investigation such as in our case. Sequestrated disc fragments should be included in the differential diagnosis of patients presenting with low back pain, radiculopathy, or cauda equina syndrome.


Gaining insight into the pharmacology of ligand engagement with G-protein coupled receptors (GPCRs) under biologically relevant conditions is vital to both drug discovery and basic research. NanoLuc-based bioluminescence resonance energy transfer (NanoBRET) monitoring competitive binding between fluorescent tracers and unmodified test compounds has emerged as a robust and sensitive method to quantify ligand engagement with specific GPCRs genetically fused to NanoLuc luciferase or the luminogenic HiBiT peptide. However, development of fluorescent tracers is often challenging and remains the principal bottleneck for this approach. One way to alleviate the burden of developing a specific tracer for each receptor is using promiscuous tracers, which is made possible by the intrinsic specificity of BRET. Here, we devised an integrated tracer discovery workflow that couples machine learning-guided in silico screening for scaffolds displaying promiscuous binding to GPCRs with a blend of synthetic strategies to rapidly generate multiple tracer candidates. Subsequently, these candidates were evaluated for binding in a NanoBRET ligand-engagement screen across a library of HiBiT-tagged GPCRs. Employing this workflow, we generated several promiscuous fluorescent tracers that can effectively engage multiple GPCRs, demonstrating the efficiency of this approach. We believe that this workflow has the potential to accelerate discovery of NanoBRET fluorescent tracers for GPCRs and other target classes. G protein-coupled receptors (GPCRs) are among the most widely studied pharmacological targets ,2. They Resonance energy transfer ligand-engagement assays offer specific and sensitive measurements of molecular proximity between fluorescent tracers and their cognate GPCRs genetically fused to an energy donor. Typically, engagement characteristics for unmodified ligands are revealed through competitive displacement of a bound fluorescent tracer. However, rapid and efficient generation of receptor specific tracers is often challenging. Conjugation of a fluorophore to a bioactive compound introduces a significant modification to the chemical structure, frequently disrupting critical binding interactions and altering physiochemical properties ,14. TherThe exquisite specificity of resonance energy transfer ligand-engagement assays governed by binding to targets tethered to an energy donor offers an opportunity to utilize promiscuous fluorescent tracers ,16. SuchLigand-based in silico screening can help to address part of this challenge by providing a means to rapidly search a vast chemical space for bioactive compounds with a promiscuous binding profile ,18,19,20Compound modification with a fluorophore provides an additional opportunity to improve the efficiency of tracer development. As mentioned above, the attachment of a fluorophore to a bioactive compound requires careful selection of a conjugation site. Often, the optimal site cannot be rationalized via structure activity relationships (SAR) and/or in silico docking analysis, requiring empirical evaluation of several conjugation sites. In addition, synthetic accessibility to such sites through de novo total synthesis is often complex and can be labor and time intensive. Recently, late-stage modification of organic compounds has emerged as a powerful approach for rapid exploration of chemical space ,22,23. CHere, we describe an integrated workflow utilizing the approaches outlined above to accelerate the generation and evaluation of fluorescent tracers for GPCRs. To demonstrate the efficiency of this workflow, we used a machine learning model to predict the binding profiles of 17 model scaffolds and a blend of synthetic strategies to conjugate these scaffolds to a fluorophore. The resulting panel of fluorescent tracer candidates was evaluated in a NanoBRET ligand-engagement screen across a library of 184 HiBiT-tagged GPCRs. The screen revealed a good overall correlation with model predictions and provided valuable feedback on tracers’ binding profile, suitable conjugation site, and ultimately potential to deliver robust ligand-engagement assays. Thus far, this strategy has resulted in several fluorescent tracers that can effectively engage multiple receptors from one or more GPCR families. We believe this workflow has the potential to accelerate tracer discovery and to broaden the target classes amenable for NanoBRET ligand-engagement analyses.The high specificity afforded by NanoBRET allows utilization of promiscuous fluorescent tracers for selective measurements at specific HiBiT-GPCRs, reducing the need to develop a specific tracer for each target. Given the abundance of available information on GPCR-ligand interactions in public databases, we sought to design an in silico screening strategy to identify compounds exhibiting a propensity for promiscuous binding interactions. We were motivated to use only chemical structures of known GPCR ligands as input data for machine learning since this would provide access to the most comprehensive compound set available, including those targeting GPCRs lacking 3-D structural information. The resulting model could be used to screen compounds with a minimal amount of chemical information needed.The intent of our model design was to recognize common structural patterns shared by ligands of specific GPCR families and then use that information to predict the target family interactions for other compounds in an automated fashion. We chose to categorize compounds based on their target GPCR families rather than individual receptors for two reasons. First, the primary application of the model is to provide guidance for identifying compounds that could interact promiscuously across a broad range of GPCRs rather than with specific receptors or GPCR families. Second, it simplifies the modeling task by providing greater differentiation between classes, under the assumption that ligands interacting with receptors from different families are more likely to exhibit larger differences, which in turn are easier to distinguish by the model. In practice, this approach has made in silico screening of large datasets more tractable. Promiscuity across different GPCR families is expected to be a rare property and by grouping compounds into larger GPCR-family target classes it was easier to identify those with a high probability for multi-target interactions.Throughout model development, we identified several steps critical to the success of this strategy including aspects of data processing as well as methods of model training and validation. Briefly, we processed our chemical structure dataset by focusing on minimizing sources of redundancy and bias while maximizing the diversity of chemical information available for machine learning. Using chemical structures encoded as molecular fingerprints we trained the model to recognize patterns of shared molecular features among compounds that bind the same target class (GPCR family). The capacity of the model to use those signature patterns to classify compounds into their GPCR target families was validated using a test set comprising 30% of the compounds, which were withheld during training.Training a machine learning model to recognize patterns of molecular interactions with different GPCR families requires a large, representative dataset comprising similarly diverse ligands for each family. Among available data sources, we chose the GPCR ligand-associated (GLASS) database as it provided an easily accessible and comprehensive dataset of known GPCR ligands . HoweverData acquired from the GLASS database contained over a million ligand-receptor interactions for GPCRs from multiple species. Since we were primarily focused on developing NanoBRET tracers to interrogate ligand engagement of human GPCRs, we first filtered out all redundant molecular structures and subsequently selected for ligands known to target human receptors A. ComparThe 23,850 compounds in our Selected dataset were converted into a vector format, which can serve as input for machine learning by encoding chemical structures as molecular fingerprints. Chemical information encoded as molecular fingerprints has been successfully used in machine learning tasks  and can Given the dependence of our model’s performance on the structure of the training set, we sought to further investigate the structural relationships among compounds used for machine learning. Using the chemical information encoded by molecular fingerprints, we analyzed the underlying structure of the Selected dataset via Uniform Manifold Approximation and Projection (UMAP), an unsupervised learning algorithm . UMAP reComparing the clustering patterns in UMAP space for individual GPCR families with their model’s performance metrics provided additional insights into the influence of data structure on model fitting. For example, compounds associated with GPCR families for which the model delivered classifications with high accuracy and sensitivity, such as the Melatonin receptor family, also displayed tight clustering in UMAP space  requires either de novo total synthesis or application of sophisticated late-stage chemistries. In addition, in many cases a site suitable for modification without significant impact on binding properties is unknown, requiring empirical evaluation of several sites. Below we highlight several examples taking advantage of different synthetic strategies to generate modifiable analogues via a reasonable number of steps.Clozapine represents an example of our approach evaluating a mixture of rational and empirical modifications sites . MultiplAmitriptyline, a promiscuous tricyclic antidepressant , is anotThe modification of another scaffold AZD1283, a potent antagonist of the P2Y12 receptor  is a gooex 576 nm; Eem 589 nm) for a fluorophore due to its photochemical properties, including small size, chemical stability, and sufficient spectral overlap with NanoLuc emission, which is critical for efficient energy transfer [Using a blend of different synthetic strategies similar to those outlined above, we generated modifiable analogues for the 17 model scaffolds and conjugated them to a fluorophore via amide-type couplings. We chose the red emitting NanoBRET 590 dye  was calculated. We chose a 1.5-fold response, which translates to ≥7-fold signal over noise as the minimal threshold required to score an interaction as positive. The compiled screening results for all fluorescent tracer candidates across 184 GPCRs from 51 different families and their structures are included in the Each tracer candidate was screened across the entire library of HiBiT-GPCR constructs using NanoBRET as the detection modality. As depicted in Analyses of all three Clozapine tracers revealed specific interactions with 19 GPCRs from the five expected families, albeit with a different binding profile for each one B. These 50 values (1–600 nM). Concentration-dependent binding to the remaining GPCRs, ADRA2A and HTR1D, was specific but suffered from high background, likely due to nonspecific BRET originating from random interactions. Interestingly, in the NanoBRET screen, interactions between Clozapine-a-2-NB590 and these 17 GPCRs retained a ≥1.5-fold response at the lower 0.1 μM concentration while interactions with ADRA2A and HTR1D did not. This suggests a correlation between the retention of a ≥1.5-fold response at the lower 0.1 μM tracer concentration and the likelihood for a robust saturation ligand-engagement assay.Encouraged by the broad binding profile of Clozapine-a-2-NB590 A, it wasThe benefit of evaluating several modification sites was further demonstrated for Amitriptyline where we observed significantly different binding profiles among the five tracer candidates A,B. ThesFor AZD1283, the third tracer scaffold, late-stage alkenylation enabled conjugation of NanoBRET 590 to the phenyl ring with minimal synthetic effort C,D. NanoAltogether, the NanoBRET screen of tracer candidates for 17 different scaffolds uncovered specific binding interactions for 58 GPCRs from 18 different families . The scrFinally, we opted to compare the machine learning predictions for the 17 scaffolds to the empirical NanoBRET evaluations across 36 GPCR families investigated by both strategies . The higOverlap analysis between machine learning predictions and empirical NanoBRET evaluations C revealeThe high specificity of NanoBRET is particularly attractive when combined with the versatility of promiscuous fluorescent tracers, alleviating the burden of developing a specific tracer for each target. Here, we developed an integrated tracer discovery workflow coupling machine learning-guided in silico screening for promiscuous tracer scaffolds with a blend of synthetic strategies to rapidly generate multiple tracer candidates. Using this workflow, we developed over a dozen fluorescent tracers that can effectively engage several GPCRs from one or more families. A limited set of 10 leading tracers enabled robust saturation ligand-engagement assays for 40 GPCRs, including some overlapping coverage among them . Our scrhttps://zhanglab.ccmb.med.umich.edu/GLASS/) in 3 October 2018. All data processing was performed in R version 3.6.3. The raw interaction data was filtered to select compounds that target human GPCRs, have an assigned CHEMBL ID number, and their chemical structure represented in SMILES format [Chemical interaction data was downloaded from the GLASS database  is a general-purpose manifold algorithm for dimensional reduction . UMAP ocThe MACCS molecular fingerprint representation of the training dataset was used as input and the graph was computed using the UMAP package version 0.2.5.0 in R. Since the resulting spatial distribution following UMAP dimensionality reduction is dependent on the user-defined number of nearest neighbors, a range of settings from 10–400 neighbors were explored. A value of 50 nearest neighbors provided the optimal spread of the data in low dimensions suitable for visualization while retaining the clustering of compounds according to their target GPCR families. All UMAP visualizations were created using the ggplot2 package version 3.3.0 in R .Machine learning model training was carried out using the caret package version 6.0-86 in R. Employing the training set in molecular fingerprint format as the input, a random forest classification model was trained for accuracy using 5-fold cross-validation repeated 10 times. Software defaults were used for automatic data centering, scaling, and hyperparameter tuning during the training phase see . The traPerformance metrics such as accuracy, sensitivity, and specificity were calculated automatically from model predictions of target GPCR family for compounds in the test set using their specific interactions in the GLASS database as ground truth. Using measurements for true positive (TP), true negative (TN), false positive (FP), and false negative (FN), the formulas used were Accuracy = (TP + TN)/(TP + FN + TN + FP), Sensitivity = TP/(TP + FN), and Specificity = TN/(TN + FP). Statistics at the GPCR-family level were used to create a confusion matrix evaluating the accuracy of model prediction on target-ligand interactions for individual families. All statistical metrics were calculated automatically following model training using caret in R.To predict the GPCR target family for compounds used as scaffolds for fluorescent tracer development, the chemical structure of each unmodified compound was converted to SMILES representation using ChemDraw Professional version 16.0. Molecular fingerprints were extracted as outlined earlier in Methods using the RCPI package in R. The machine learning model was imported into an R environment and used to predict the GPCR family class probabilities for each scaffold.Class probabilities, converted to values ranging from 0 to 100% for readability, were used as a guide to search for potential interactions among compounds and GPCR families. A threshold of 4% and above for positive interactions provided the best correlation between the machine learning predictions and empirical NanoBRET data.2. A screen of each tracer across the entire library using two different concentrations requires duplicate plates of transfected cells. Depending on the number of tracers being screened, transfections can be scaled up using the same ratios. The next day, for each tracer, four 20× screening solutions in tracer dilution buffer (Promega) were prepared: two duplicates at final concentration of 20 μM and two duplicates at a final concentration of 2 μM. A competing unmodified compound was added to one of each duplicate at a final concentration of 400 μM. The four resulting solutions were diluted 4-fold in Opti-MEM without serum or phenol red to generate 5× solutions (5 µM and 0.5 µM tracer +/− 100 μM competing compound). To screen the library, a BioTek MultiFlo FX liquid dispenser was used to dispense 22.5 µL of tracer solution to the top 4 rows and 22.5 µL tracer + competing compound solution to the 4 bottom rows. Plates were briefly mixed on an orbital shaker and incubated for 1.5 h at room temperature. The MultiFlo FX liquid dispenser was used to dispense 2× detection reagent (100-fold dilution of LgBiT (Promega) and 50-fold dilution of furimazine live cell substrate (Promega) in Opti-MEM) at 125 μL/well. Plates were briefly mixed on an orbital shaker and incubated for 15 min to allow complementation. Filtered luminescence was measured using a GloMax Discover microplate reader (Promega) equipped with a 450-nm (8-nm band pass) filter (donor) and a 600-nm long pass filter (acceptor). BRET was calculated by dividing the acceptor emission by the donor emission. Fold response was calculated for each construct at each tested tracer concentration by dividing BRET from wells treated with tracer alone (BRETtracer) by BRET from duplicate wells treated with tracer + competing compound (BRETcontrol). The minimal threshold for specific interactions was 1.5-fold response, which translates to ≥7-fold signal over noise. Signal over noise was calculated for each interaction in a limited set of triplicate screens using the formulation:HiBiT-GPCR DNA constructs were diluted in 10 mM Tris pH 8 to a final concentration of 0.01 μg/μL, arrayed in 96-well plates and stored at −20 °C. For transfection, HEK293 cells were suspended in Opti-MEM (without phenol red) supplemented with 2% fetal bovine serum (Seradigm) and 100 units/mL penicillin–streptomycin (Gibco) at a final concentration of 220,000 cells/mL and dispensed into white 96-well plates at 90 μL/well. Subsequent transfections and screens were carried using an Agilent Bravo Automated Liquid Handling Platform. First, the 96-well HiBiT DNA arrays were diluted 25-fold in Opti-MEM (without serum or phenol red) to a final concentration of 0.0004 μg/μL and 20 μL of the diluted DNAs were transferred into new 96-well plates. Next, promoterless carrier DNA (1 μg/μL) was diluted 25-fold (0.04 μg/μL) and then dispensed into the diluted arrays at 20 μL/well. Following brief mixing, Viafect transfection reagent (Promega) diluted 16-fold into Opti-MEM was dispensed into the plates at 40 μL/well. After mixing by pipetting, plates were incubated for 10 min on the pipetting station deck. The DNA-transfection reagent complexes were then added to plates containing cells. To facilitate the screen, 10 μL of DNA-transfection reagent complexes were added in duplicates to the top 4 and bottom 4 rows, resulting in two identical 48-well arrays per plate. Plates with transfected cells were incubated for 18–20 h at 37 °C/5% CO