Drosophila airway tree, the interplay of apical extracellular matrix (ECM) components with the underlying membrane and cytoskeleton controls tube elongation, but the link between ECM composition with apical membrane morphogenesis and tube size regulation is elusive. Here, we characterized Emp , a Drosophila CD36 homolog belonging to the scavenger receptor class B protein family. emp mutant embryos fail to internalize the luminal chitin deacetylases Serp and Verm at the final stages of airway maturation and die at hatching with liquid filled airways. Emp localizes in apical epithelial membranes and shows cargo selectivity for LDLr-domain containing proteins. emp mutants also display over elongated tracheal tubes with increased levels of the apical proteins Crb, DE-cad, and phosphorylated Src (p-Src). We show that Emp associates with and organizes the βH-Spectrin cytoskeleton and is itself confined by apical F-actin bundles. Overexpression or loss of its cargo protein Serp lead to abnormal apical accumulations of Emp and perturbations in p-Src levels. We propose that during morphogenesis, Emp senses and responds to luminal cargo levels by initiating apical membrane endocytosis along the longitudinal tube axis and thereby restricts airway elongation.The acquisition of distinct branch sizes and shapes is a central aspect in tubular organ morphogenesis and function. In the  Drosophila respiratory network, the trachea, provides a well-characterized system for the genetic dissection of tubular organ maturation. Like mammalian lungs, the trachea undergoes a precisely timed series of maturation events to convert the nascent branches into functional airways. First, a transient secretion burst of luminal proteins (kkv) or matrix assembly  show irregular tube shapes, diametric expansion and tube maturation defects  shows the highest similarity with CD36 and is selectively expressed in embryonic epithelial tissues  belongs to class B scavenger receptor family, which includes scavenger receptor B1 (SRB1) and lysosomal integral membrane protein 2 (LIMP2). CD36 is expressed on the surface of many cell types including epithelial, endothelial cells, and macrophages. Disruption of CD36 function in mice can lead to inflammation, atherosclerosis, metabolic disorders, tumor growth, and metastasis . CD36 hafunction . The Dro tissues .emp mutants display over elongated tracheal tubes with increased levels of junctional Crb, DE-cad, and phospho-Src. Reduction of Src42A in emp mutants, rescues the tube elongation phenotype indicating that Emp modulates junctional p-Src42A levels to control apical membrane expansion and tube length. The organization of the beta-heavy spectrin (βH-Spectrin) cytoskeletal network is compromised in emp mutants. Emp binds to βH-Spectrin directly, suggesting that it provides a direct link between ECM, apical membrane, and cytoskeleton during tube maturation process. Re-expression of human CD36 in emp mutants can ameliorate the mutant tube phenotypes suggesting conserved functions of Emp.Here, we show that Emp is a selective receptor for internalization, endosomal targeting, and tracheal luminal clearance of proteins with LDLr-domains. emp (or CG2727 in Flybase) encodes a class-B scavenger receptor expressed in embryonic ectodermal epithelial tissues including the tracheal system  was generated using the FLP/FRT recombinase system  (emp mutants (emp RNA in the mutants (emp homozygous or Df(2R)BSC608/emp mutants were embryonic lethal with few escapers surviving to first instar larvae. This embryonic lethality could be rescued by the re-expression of a transgenic emp construct using the ectodermal driver 69BGal4. This suggests that the deletion generates a strong loss-of function mutation in emp and does not affect any neighboring genes required for embryo viability. To examine a potential role of Emp in airway maturation, we visualized the tracheal tubes during embryonic development in wild-type and emp mutants. emp embryos at stage 16 showed a 30% over-elongation of the dorsal trunk (DT) compared to the wild-type  , failed  mutants . Similar mutants . emp homild-type , but shoild-type . emp muthatching . Both ph mutants . These dwith Emp . We gene of CD36 .wild-type and emp mutants for the luminal proteins Serp, Verm, and Gasp. These secretory proteins were internalized from the lumen by late stage 17 in wild-type embryos. Serp and Verm, but not Gasp were selectively retained in the emp DT airways   . The thrclathrin (1chc) null mutants show defects in luminal ANF-GFP clearance  or expression of a dominant negative form of DAAM (btl>C-DAAM) disrupt the transverse actin bundle arrays and prematurely initiate luminal protein clearance. Similarly, Latrunculin A (Lat-A) injection in embryos destroys the actin bundles and leads to luminal protein uptake. These experiments had suggested that the transverse F-actin bundles restrict the endocytic uptake of luminal cargoes (btl>moe-GFP) in tracheal cells stained for Emp and GFP. This showed low colocalization  suggesting distinct apical membrane domains of Emp and actin bundles (GFP)  . We infeild-type . This suild-type , furtherbtl>Emp-GFP in the time interval of luminal protein clearance (early stage 17) showed an increase of Emp intracellular puncta compared to stage 15 or late stage 17 embryos , expressed at endogenous levels. Co-staining for Emp and GFP  showed a embryos . Overallemp mutants and the partial localization of Emp with endosomal markers led us to examine if Emp mediates the endosomal uptake and subsequent trafficking of luminal Serp. We co-stained for endogenous YFP-tagged endosomal markers and Serp in wild-type and emp mutant embryos. This analysis showed that intracellular Serp puncta co-stained for the early endosomal marker Rab5 (r2 = 0.29) and late endosomal marker, Rab7 (r2 = 0.27) in wild-type embryos. In the emp mutants, the colocalization of Serp with both early and late endocytic markers was significantly decreased   , we cannwild-type embryos and emp mutants  increased the overall levels of cytoplasmic Emp, without a major influence on the accumulation of Crb  of emp mutant tracheal cells significantly increased, while the length of junctions along the transverse tube axis was not affected  of stainings for the AJs component α-CAT (α-Catenin)   and the Catenin)  were ind embryos , suggestntegrity . Overallemp mutants. We first examined the apical F-actin in DTs of late stage embryos by live imaging using btl>Moe-GFP. At 17.5 h AEL, at the time interval of airway protein clearance, emp mutants showed a more diffuse and continuous apical actin bundle density compared to wild-type embryos  as bait in a yeast two hybrid (Y2H) screen at Hybrigenics. This uncovered three potential interacting proteins, CG32506 encoding a RabGAP protein, CG34376 encoding a protein with a predicted Zinc Finger motif and βH-Spec/Kst . We furt tissues . The α-  tissues . We usedal sides . To confSpec/Kst  consiste and Kst . To furtild-type . The loc mutants . Togetheemp mutants showed higher Crb accumulation in longitudinal junctions and an overall increase in the apical levels of DAAM, we compared Src phosphorylation (p-Src) levels by immunostainings and by western blot in wild-type, emp mutants, btl>Serp-GFP and emp;btl>Serp-GFP embryos  in emp mutant embryos . Embryos trans-heterozygous for Df(2R)BSC08 and emp were lethal showing identical phenotypes to emp homozygous embryos  was cloned using Hifi DNA assembly kit (NEB E5520S) into the pJFRC-MUH vector . bglII and XbaI were used to clone the amplified PCR fragment. UAS-Emp transgene was generated by cloning the cDNA sequencing of CG2727 by PCR amplification with primers containing EcoRI and KpnI. The UAS-Gasp construct was generated by sequential cloning of Gasp cDNA using primers containing EcoRI and XhoI. Further, LDLr-domain and mCherry were subcloned using enzymes XhoI and XbaI. The FL-GFPUAS-Serp and LDLr-GFPUAS-Serp constructs were generated according to CBD-GFPUAS-Serp was provided by S. Luschning. mCherry-Emp-V5His construct was cloned using Hifi DNA assembly kit NEB E5520S into the pAc5.1/V5-His A vector (Invitrogen) using the following enzymes Acc65I and XhoI. The different Kst constructs were generously provided by N. Tapon. All the plasmids were confirmed by sequencing. Polyclonal antibody (anti-Emp) obtained by immunization with bacterially expressed recombinant polypeptides corresponding to amino acids 46–460 of Emp-A. Anti-sera obtained from immunized rats (Genscript).Complementary DNA (cDNA) encoding for Drosophila S2 cell extracts and Co-IP were prepared as previously described (Drosophila embryos were collected 12–20 h AEL and lysed in 20 μl of lysis buffer containing 50 mM HEPES (pH 7.6), 1 mM MgCl2, 1 mM ethylene glycol-bis(β-aminoethyl ether)-N,N,N′,N′-tetraacetic acid (EGTA), 50  mM KCl, 1% NP40, Protease inhibitor cocktail tablets (Roche #11697498001), and Phosphatase inhibitor cocktail 2 (Sigma-Aldrich #P5726). The lysates were centrifuged at maximum speed  for 10 min at 4 °C. Protein loading buffer , 5% glycerol, 0.002% bromophenol blue) was added to the supernatant and samples were analyzed by SDS–polyacrylamide gel electrophoresis and immunoblotting according to standard protocols, using the ChemiDoc XRS  + system (Bio-Rad), after application of the SuperSignal West Femto Maximum Sensitivity Substrate . The following primary antibodies were used at the indicated dilutions: rabbit anti-α-tubulin , rabbit anti-Phospho-Src , and Lamin ADL195 .escribed  and .moe-GFP were dechorionated, devitellinized by hand and fixed in 4% PFA or formaldehyde (methanol free) in phosphate-buffered saline–heptane or PEM (PIPES-EGTA-MgCl2)–heptane mix,  (PIPES) pH 6.9, 2.5 mM EGTA, 1 mM MgCl2) for 20 min. Embryos were de-hydrated and mounted in pure methyl-salicylate  was inserted into the pB27 vector (N-LexA–bait-C fusion) and was used to screen 167 million clones., Merk), for genomic DNA removal. Then 400 ng of RNA was reverse transcribed using High-Capacity RNA to cDNA kit (4387406 Thermo Fisher). The cDNA products were subsequently diluted 1:5 and 2 μl were used as a template in each qPCR reaction. qPCR was performed using iTaq Universal SYBR Green Supermix (Bio-Rad). Generation of specific PCR products was confirmed by melting-curve analysis. Ct values for all genes were normalized to the levels of Rp49. For data analysis, the delta-delta Ct values were applied. The sequences of primers used are provided in Embryos dechorionated in bleach, hand-sorted for GFP expression, collected in 300 ml of TRizol LS Reagent and stored at −80°C until further use. For RNA extraction, the embryos were homogenized in TRIzol LS Reagent using a 1.5-ml tube pestle and the total RNA was purified using the Direct-zol RNA MicroPrep kit . RNA was resuspended in RNase-free water and subsequently treated with DNAse I  was used. Z-stacks (0.16–0.2 μm step size) were taken every 15 min over a 2–4 hr period using a Plan-Apo 63 ×/1.40 DIC oil or a C-Apochromat ×63/1.2 NA water objective (Zeiss). Raw data were processed with the Airy-scan processing tool available on the Zen Black software version 2.3 (Carl Zeiss). Images were converted to tiff format using the Zen Black or ImageJ/Fiji software.Dechorionated embryos mounted in a glass-slide with a gas permeable membrane . WidefieTube length measurements were conducted in embryos stained for the luminal markers Verm or Serp. Tracheal lengths were measured by tracing the length of the DT determined by the luminal markers using the freehand line selection tool of ImageJ/Fiji software. For metamere length measurements, we traced the DT length between the corresponding TC (transverse connective) branches. Longitudinal and transverse cell junctions were defined according to the angles from the DT axis (angle = 0°). Junctions with clear orientation angle 0° ± 30° or 90° ± 30° were defined as longitudinal or transverse, respectively. The rate of gas-filling calculated as the percentage of embryos with gas-filled tracheae divided by the total number of embryos analyzed.For dye-permeability assays, 10 kDa Dextran-TR (Thermo Fisher Scientific) was injected into late stage 16 embryos (after the maturation of SJ) as described in Freehand Line tool’, over the junctional region of the tracheal cells. The total fluorescence intensity in TCJ and LCJ of Crb and DE-cad was measured according to 2 squares on each puncture were defined as the regions of interests (ROIs). Mean fluorescent intensity within these ROIs was measured in Fiji. These values were divided by the corresponding fluorescence intensity observed in the ROI of the co-stained Crb puncta. Background signals of 0.75 μm2 square-ROIs were subtracted from the intensities. Data collected from ImageJ were transferred to an Excel file for further analysis and plotting by GraphPad Prism.The total fluorescence intensity signal of Emp, Crb, DE-cad, Dlg, and α-Cat was measured with ImageJ by manually drawing a 5-pixel line with the ‘t-test for unpaired variables unless indicated. The type of statistical test, n values and p-values are all provided in the figure legends. The experiments were replicated three to six times. All statistical analyses were performed using GraphPad Prism 9.1. The number of biological replicates for all the experiments is indicated in the figure legends. No explicit power analysis was used to estimate sample sizes for each experiment.Statistical analysis was carried out using two-tailed  Drosophila scavenger receptor Emp (homologous to human CD36) senses and responds to the levels of its cargo apical ECM proteins and triggers the initiation of apical endocytosis, thereby regulating tube length via controlling Crumbs and Src. This work will be of broad interest to cell and development biologists as well as cancer biologists.In this important work, the authors convincingly show that the  public reviews designed to be posted alongside the preprint for the benefit of readers; (ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.Our editorial process produces two outputs: (i) Decision letter after peer review:Drosophila airways" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Utpal Banerjee as the Senior Editor. The following individuals involved in the review of your submission have agreed to reveal their identity: Amin S. Ghabrial (Reviewer #1); Shigeo Hayashi (Reviewer #3).Thank you for submitting your article "Scavenger receptor endocytosis controls apical membrane morphogenesis in the The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.Essential revisions:1) One point of concern expressed by all three is the phenotype description and interpretation of Srp-GFP overexpression and its effect on Src. Since this is the critical point linking the endocytosis to the anisotropic tube elongation, the authors should be encouraged to address and clarify this.2) The authors fail to clearly show the localization of Emp at the apical membrane and its connection to apical actin structures and chitinuous aECM.3) Discussing how the junction-enriched Crumbs contribute to selective axial cell elongation will be desirable to expand the scope of this work.4) Discussing a possible molecular mechanism linking Emp to pSrc distribution would contribute to a better insight into the regulation of tube length during embryonic tracheal development.Reviewer #1 (Recommendations for the authors):This manuscript makes a valuable contribution to our understanding of tubulogenesis and of the critical role of vesicle trafficking in this process. I have a number of questions that I would like the authors to address in a revision and several errors that they can correct to improve the clarity of the manuscript.– p 5. does emp expression driven by 69BGAL4 rescue to adulthood?– What does it mean that some embryos did clear their lumens but still (I assume) showed tracheal defects?– Is it ultimately pSrc that is the target of Emp? is its distribution affected in all embryos examined (eg. a fully-penetrant defect)?– A description of chc mutant phenotype would be helpful – is there overlap with the emp loss of function phenotype?– What happens to the 25% of embryos with normal gas-filling? do they have tube length defects? How penetrant is the tube length defects?– How does Emp localization look in unicellular tubes? and are unicellular tubes also unable to gas-fill?– p 11 and 13.However, btl>GaspFL+LDLr-mCherry, but not btl>GaspFL-mCherry, was retained in the airways of emp embryos .BUT, GaspFL+LDLr is not shown in figure 3F. This needs to be added.Downregulation of src activity and the levels of luminal Serp-GFP are sensed by Emp to control apical membrane protein endocytosis and trafficking, and therebyelongation.This is a bit confusing, can it be re-phrased in a wild-type context: whatever Emp is doing normally it is not via an overexpressed transgene (Serp-GFP)? Does pSrc fall just before the surge in endocytosis? Is that dependent upon Emp? does decreased luminal Serp put the breaks on endocytosis? What about verm, serp het embryos; 50% reduction in cargo, does this affect endocytosis? If the activity of Src is regulated downstream of Emp, what is the sensing that Emp is doing? Isn't Emp acting on Src (which seems to be what is shown in the model figure)?Reviewer #2 (Recommendations for the authors):In Figure 2C it is not clear what is shown in the panel of the btl>cDAAM. Luminal borders are not visible and, if the scale is the same, the tube seems overexpanded circumferentially (same in E'). Dorsal trunks are much more expanded than the control and previously shown for the same conditions . Please revise these images.The authors say "the number of intracellular Serp puncta were reduced in emp mutant embryos compared to wild-type , whereas the total number of GFP puncta corresponding to early and late endosomes remained unchanged . This is not clear at all if you compare Figures 3A and B on the green channel. In emp mutants large YRab7 vesicles are not present, even the ones not associated with Serp, suggesting that another late endosomal trafficking is impaired. This should be discussed by the authors.In figure 3 the authors only show the clearance of SerpFL, SerpLDL, and SerpCBD in wt embryos. There are no panels showing the clearance of these constructs in emp mutants. The panels showing the clearance of GaspFL and GaspLDL in wt and emp embryos are not shown nor quantified. These experiments should be present in panels in Figure 3 figure supplement 1. A graph with quantifications of GaspLDL should be included.Drosophila airways at least partially through Emp." However, if Emp is a receptor for Serp in charge of its removal from the lumen, in conditions of Serp overexpression in the absence of Emp, we should see the increased length in emp;btl>Serp-GFP in comparison to btl>Serp-GFP, not decreased. I think the experiment should be: If Emp acts as a scavenger receptor for Serp, does overexpression of Emp rescue the tube elongation phenotype of Serp overexpression? The authors should explain why Emp downregulation improves the mutant phenotype induced by Serp overexpression.I do not agree with the authors' conclusions on the experiment of overexpressing Serp in an emp mutant background . The authors say that: "reduced DT elongation in emp;btl>Serp-GFP embryos compared to btl>Serp-GFP, suggesting that Serp overexpression controls the length of the The authors claim that Emp modulates the apical actin organization and that loss of Emp affects this F-actin organization. However, to analyse apical F-actin in DTs and compare control with emp mutants , the authors should present not just a median view of the tube lumen, but also show the cortex of the lumen in order to better analyze and visualize the F-actin bundles . In addition, this would give a better view of Emp localization in relation to the F-actin bundles. According to the model proposed Emp is clustered outside the F-actin-rich bundles. F-actin analysis in the cortex of the tubes together with Emp localization would allow for this analysis.In the discussion, the authors state that "First, emp activity is confined in apical "macro"-domains along the longitudinal tube axis by the transverse, DAAM-dependent actin filaments." This is really not shown in the manuscript. So, either the authors clarify Emp localization in "apical macro domains" and its relationship with DAAM-dependent actin filaments, or this should be removed.When discussing the model in figure 8, the authors say that "In the bundle-free membrane domains, Emp associates with Kst and establishes an endocytosis domain, where Serp mediated Emp clustering leads to internalization." This is not shown by their data and it should be made clear that this is a hypothesis and not a thesis.eLife 2016) presented a model whereby there is feedback between the chitinous aECM and the underlying cells. They reported that chitin downregulation increases the levels of p-Src in tracheal cells. There is a tight connection between chitin and the F-actin bundles, so I believe it is essential that the authors analyse the chitinous structure in the DT of Emp mutants. In addition, it would be very interesting  to analyse if the chitinous luminal filament is also internalised via Emp.Ozturk-Çolak et al. :One potentially insightful result is the phenotype of Serp-GFP overexpression, which caused a reduction of pSrc  and elevation of membrane Emp . Although down-regulation of Src and upregulation of Emp in other contexts are associated with defective tube elongation, btl>Serp-GFP caused tube over elongation . This apparent contradiction should deserve highlighted, and a deeper investigation may open a better understanding of the tube elongation mechanism. One potential clue could be to look at the anisotropy of junctional Crumbs in the btl>Serp-GFP embryos. Essential revisions:1) One point of concern expressed by all three is the phenotype description and interpretation of Srp-GFP overexpression and its effect on Src. Since this is the critical point linking the endocytosis to the anisotropic tube elongation, the authors should be encouraged to address and clarify this.serp verm mutants. We interpret that the luminal levels of Serp are tightly controlled and the tube elongation phenotype of UAS-Serp GFP reflects a dominant effect that could be due to interference with the luminal functions of Serp or it’s recycling back to the membrane or with the function of SJ components.Previous work has shown that changes in chitin synthesis or ECM integrity affects the levels of phosphorylated Src42A (pSrc) at cell junctions . Loss of Verm and Serp also causes p-Src upregulation and over-elongation and we also show that Serp overexpression leads to p-Src downregulation as expected . Counter intuitively, Serp overexpression also results in tube over-elongation . This overexpression paradox could be explained by an indirect, src-independent effect of the overexpressed luminal Serp-GFP on tube elongation. Although Src42A is necessary and sufficient for cell shape changes during tracheal tube elongation , there are additional src-independent pathways involving septate junction components affecting normal tube elongation . The overexpression experiment is informative on the roles of Emp in shaping the apical membrane and cytoskeleton. But the tube overelongation phenotype, resembles the airway over-elongation of null verm serp loss of function (heterozygous or homozygous) and UAS-Serp GFP overexpression on Src activation and tube elongation are significant, but partly mediated by Emp endocytosis. This is supported by the quantification of the p-Src signals in Figure 7 and Figure 7—figure supplement 1. We have added few sentences addressing this issue in the text (lines: 500-504 and 723-733).In the context of this work, we are not able to delve further on the dominant effect of Serp-GFP overexpression on tube elongation. All we can state with certainty is that the normal levels of Serp are required for optimal elongation and that the Serp-GFP overexpression causes a dominant effect, which is known . Overall, the novelty of our data and interpretations lies in that there are at least two parallel, spatially segregated, mechanisms converging on the apical cytoskeleton and on the regulation of apical cell shapes . One is defined by Src phosphorylation, which promotes the formation of F-actin bundles by DAAM . The other is defined by Emp clustering by Serp and its direct association with βHeavy-Spectrin to facilitate endocytosis and apical recycling . Our data propose that the two mechanisms are antagonistic, DAAM-bundles restrict the localization of Emp and endocytosis, and Emp clustering in response to normal cargo levels organizes the localization of the actin bundles. It is possible that excessive Emp clustering and/or the interference with the ECM integrity (due to the deacetylase activity of Serp) upon Serp-GFP overexpression may cause additional dominant effects on Src activation, ECM assembly, protein endocytosis, protein and membrane recycling and thereby interfere with tube elongation. We hypothesize that the effects of 2) The authors fail to clearly show the localization of Emp at the apical membrane and its connection to apical actin structures and chitinuous aECM.We are not sure that we understood the meaning of “clearly show” without a concrete example of what experiment would constitute clear evidence for the localization of Emp in the apical membrane. Nevertheless, to address this point, we additionally co-stained wild-type embryos with anti-Emp and anti-Ptp10D  and also wild-type embryos expressing the apical membrane reporter UAS-CD4-Tom with anti-Emp and anti-RFP. These new experiments showed strong co-localization of Emp with Ptp10D and CD4-Tom in the apical membrane  by high resolution confocal microscopy. In the first version, we had shown that Emp colocalizes with the apical trans-membrane protein Crb  and the Zonula Adherens (ZA) marker pY . Emp also directly binds and colocalizes with apical cytoskeletal organizer βHeavy-Spectrin . Our analysis, and given that Emp contains two trans-membrane domains, strongly supports the apical membrane localization of Emp in the airways. Typically, an endocytosis scavenger receptor is also internalized in the endosomal compartment and recycled to the membrane or degraded.btl>moe-GFP) with anti-Emp and anti-GFP in tracheal cells. We have shown earlier that moe-GFP faithfully labels the cortical actin bundles, running perpendicular to the tube axis, during tube maturation . Analysis of xz or yz sections within Z-stacks of airy-scan confocal images in these embryos showed low colocalization  and predominantly complementary pattern of apical Emp and actin bundle domains (GFP). These results further support our interpretation that Emp, localizes in the bundle-free membrane regions in physical association with βHeavy-spectrin to promote the endocytosis and recycling of selected cargos. The new data are shown in Figure 2 suppl. 3A-D.To relate Emp localization to the apical actin bundles, we have co-stained wild type embryos over-expressing a GFP-tagged version of the actin binding domain of moesin , suggesting that the connections between Emp and Serp are functionally significant.Regarding the last point of connections between Emp and its cargo Serp, we had shown with high resolution confocal microscopy that the receptor and its cargo, Serp, colocalize in common endosomes. This is disrupted in 3) Discussing how the junction-enriched Crumbs contribute to selective axial cell elongation will be desirable to expand the scope of this work.In our manuscript, we view apical membrane, Crb or Ecad as passive cargoes of Serp/Emp endocytosis and recycling in the actin cable-free regions along the longitudinal tube axis . As previously proposed Crb may change the apical actin cytoskeleton and its tensile properties at the junctions. This is very interesting but beyond our focus.4) Discussing a possible molecular mechanism linking Emp to pSrc distribution would contribute to a better insight into the regulation of tube length during embryonic tracheal development.We have not detected any direct molecular link between Emp and Src phosphorylation. In a simple model, p-Src levels during tube elongation would be controlled by the levels of RTK signaling including Stit, InR, EGFR, PTP  , . p-Src contributes to DAAM-mediated actin cytoskeletal remodeling, tube elongation, and the construction of the perpendicular actin rings . We have shown before that these perpendicular structures inhibit endocytosis on the transverse axis . The levels of luminal Serp might be sensed by Emp in the apical membrane and Emp clustering induces apical membrane endocytosis. This apical membrane internalization constantly balances actin polymerization by DAAM activity on the bundles and tube elongation. Parts of the membrane and TM proteins are recycled to the apical junctions. We showed that Emp is directly linked to the βH-Spectrin cytoskeleton and is required for its assembly. This cytoskeletal organization indirectly interferes with DAAM localization and presumably Src activation/function as also proposed by . We have tried to incorporate the interpretation of our results in the Figure model . We have added a few more sentences in the discussion to clarify this (lines: 799-802 and 820-827).Reviewer #1 (Recommendations for the authors):This manuscript makes a valuable contribution to our understanding of tubulogenesis and of the critical role of vesicle trafficking in this process. I have a number of questions that I would like the authors to address in a revision and several errors that they can correct to improve the clarity of the manuscript.– p 5. does emp expression driven by 69BGAL4 rescue to adulthood?emp;69BGal4/UAS-Emp. In addition, we have examined the lethality of emp;btlGal4/UAS-Emp embryos. Hatching larvae of this genotype die as 3rd instar suggesting that Emp is essential in other tissues.We have not examined the survival to adulthood of this genotype. However, we have seen viable 2nd instar larvae of – What does it mean that some embryos did clear their lumens but still (I assume) showed tracheal defects?We assume that the reviewer refers to 25% of embryos with normal protein clearance and gas filling. These embryos show longer tubes. This might suggest that there may be an additional scavenger receptor required for protein clearance. There are 13 paralogs encoded by the fly genome. One of them is debris buster, which has been implicated in airway clearance . We have re-phrase our statement in the new version.– Is it ultimately pSrc that is the target of Emp? is its distribution affected in all embryos examined (eg. a fully-penetrant defect)?We did not detect any direct link between Emp and p-Src levels. Src activation is a functionally relevant aspect of the phenotypes but we don’t have any evidence that Emp biochemically controls Src phosphorylation.emp mutants compared to wild-type . This is a fully-penetrant phenotype at stage 17. Additionally, p-Src levels were also increased in the verm serp double mutant embryos and decreased in embryos overexpressing btl>Serp-GFP . This decrease by Serp overexpression was partly improved in emp mutants , suggesting that the effect of Serp-GFP overexpression on Src phosphorylation is, at least partly, mediated by Emp.Both immunostaining and western blot analysis showed increased p-Src levels in – A description of chc mutant phenotype would be helpful – is there overlap with the emp loss of function phenotype?1chc null mutant embryos have defects both in luminal protein and liquid clearance and tracheal tube length   similar to emp mutants. We have added this to the references and to the text.Yes, there is an overlap of the chc and the emp phenotypes in the trachea. – What happens to the 25% of embryos with normal gas-filling? do they have tube length defects? How penetrant is the tube length defects?We addressed this above. Tube length phenotype is fully penetrant .– How does Emp localization look in unicellular tubes? and are unicellular tubes also unable to gas-fill?btl>CD4-Tomato embryos stained for Emp and RFP. We initially detected diffused Emp in cytoplasmic dots (stage 15) but then at stage 16 Emp was progressively defined in the apical region of terminal branches. This localization pattern of Emp looks similar to the one we detected in the DT. These new data are shown in Figure 2 suppl. 2 B.We thank the reviewer for the interest. We analyzed unicellular tubes of The gas filling defects were also present in unicellular tubes.– p 11 and 13.However, btl>GaspFL+LDLr-mCherry, but not btl>GaspFL-mCherry, was retained in the airways of emp embryos .BUT, GaspFL+LDLr is not shown in figure 3F. This needs to be added.Thanks for pointing out this error. We have now included the correct graph in Figure 3F.Downregulation of src activity and the levels of luminal Serp-GFP are sensed by Emp to control apical membrane protein endocytosis and trafficking, and therebyelongation.This is a bit confusing, can it be re-phrased in a wild-type context: whatever Emp is doing normally it is not via an overexpressed transgene (Serp-GFP)?We apologize for the confusion. We have revised this sentence.Does pSrc fall just before the surge in endocytosis? Is that dependent upon Emp? does decreased luminal Serp put the breaks on endocytosis?emp mutants show strong increase in p-Src levels during this interval. Luminal Serp levels are a key aspect of Emp internalization. Our data are consistent with the model, where increased Serp accumulation during development is necessary to induce Emp receptor clustering, which culminates with luminal protein clearance. Decrease of Serp or Verm levels would lead to slower endocytosis.We observed a clear p-Src decrease at junctions concurrently with an accumulation of Emp just after luminal protein clearance (at mid-late stage 17), However, it was impossible to determine the initiation point of the pSrc decrease by stainings. There is no available live imaging reporter to precisely quantify pSrc activity in living embryos. The p-Src decrease is dependent on Emp since What about verm, serp het embryos; 50% reduction in cargo, does this affect endocytosis? If the activity of Src is regulated downstream of Emp, what is the sensing that Emp is doing?We analyzed verm, serp heterozygous embryos co-stained for Gasp and pSrc. These embryos showed about 50% reduced p-Src levels compared to the verm serp homozygous double mutants . This together with the Serp loss of function mutant analysis support that Serp levels are important for Src activation.Isn't Emp acting on Src (which seems to be what is shown in the model figure)?emp mutants showed higher DAAM and p-Src signals. We have addressed this in the discussion of the current version (lines: 799-802). See also the response of editor's comment 4.We propose that Emp indirectly interferes with Src activation. Emp directly associates and organizes the apical β heavy-sprectrin cytoskeleton. This also increases apical DAAM formin levels and enhances its function in F-actin polymerization. Formins generate linear actin polymers, whereas the Arp 2/3 complex enhances branched actin polymerization required for apical endocytosis . Earlier work shows that DAAM binds and downregulates Src . Consistent with this, Reviewer #2 (Recommendations for the authors):In Figure 2C it is not clear what is shown in the panel of the btl>cDAAM. Luminal borders are not visible and, if the scale is the same, the tube seems overexpanded circumferentially (same in E'). Dorsal trunks are much more expanded than the control and previously shown for the same conditions . Please revise these images.btl >c-DAAM expression causes irregular tubes with strong dilations of ellipsoid shape and with irregular actin bundles making difficult to capture the tube shape. We have reported these phenotypes earlier ). In the current paper, we showed the Z-projections instead of longitudinal sections to convey the localization of Emp at AJ on the apical surface . We provide now (as insets) single longitudinal sections  showing the luminal borders of the tubes.We apologize for the confusion. The Figure 2C  showing maximum intensity Z-projections in the apical cortex with identical Z-depth of 5.2 μm in both genotypes. The luminal borders are not expected to be seen in the mutant. The face see . At thisThe authors say "the number of intracellular Serp puncta were reduced in emp mutant embryos compared to wild-type , whereas the total number of GFP puncta corresponding to early and late endosomes remained unchanged . This is not clear at all if you compare Figures 3A and B on the green channel. In emp mutants large YRab7 vesicles are not present, even the ones not associated with Serp, suggesting that another late endosomal trafficking is impaired. This should be discussed by the authors.emp mutants the size of YRab7 vesicles appear reduced. We believe that this is an indirect effect of the apical endocytosis phenotype of the emp mutants as less endocytosed membrane is supplied to the endo-lysosomal system leading to smaller vesicles. We have considered reviewer's comment and we revised the text in the "Results section" (lines: 421- 427).We agree with the reviewer. Although the total number of YRab7 vesicles is not significantly affected in In figure 3 the authors only show the clearance of SerpFL, SerpLDL, and SerpCBD in wt embryos. There are no panels showing the clearance of these constructs in emp mutants. The panels showing the clearance of GaspFL and GaspLDL in wt and emp embryos are not shown nor quantified. These experiments should be present in panels in Figure 3 figure supplement 1. A graph with quantifications of GaspLDL should be included.Thank you for pointing out this error. We have now included the correct graph in Figure 3F.Drosophila airways at least partially through Emp." However, if Emp is a receptor for Serp in charge of its removal from the lumen, in conditions of Serp overexpression in the absence of Emp, we should see the increased length in emp;btl>Serp-GFP in comparison to btl>Serp-GFP, not decreased. I think the experiment should be: If Emp acts as a scavenger receptor for Serp, does overexpression of Emp rescue the tube elongation phenotype of Serp overexpression? The authors should explain why Emp downregulation improves the mutant phenotype induced by Serp overexpression.I do not agree with the authors' conclusions on the experiment of overexpressing Serp in an emp mutant background . The authors say that: "reduced DT elongation in emp;btl>Serp-GFP embryos compared to btl>Serp-GFP, suggesting that Serp overexpression controls the length of the emp mutants are difficult to interpret. Even though, lack of Emp in Serp overexpression improved the tube size phenotype the tracheal network still remained over elongated. This suggests that overexpressed Serp-GFP interferes with other mechanisms acting in parallel with Emp in restricting tracheal tube length . Please also see our response to editors comment #1 above. We have considered reviewer's comment and we have commented in the text (see lines: 499-502 and 723-733).Thank you for the comment. We agree that the effects of overexpression of Serp-GFP in wild type embryos and in The authors claim that Emp modulates the apical actin organization and that loss of Emp affects this F-actin organization. However, to analyse apical F-actin in DTs and compare control with emp mutants , the authors should present not just a median view of the tube lumen, but also show the cortex of the lumen in order to better analyze and visualize the F-actin bundles . In addition, this would give a better view of Emp localization in relation to the F-actin bundles. According to the model proposed Emp is clustered outside the F-actin-rich bundles. F-actin analysis in the cortex of the tubes together with Emp localization would allow for this analysis.emp mutant embryos over-expressing moe-GFP. We found that loss of emp affects this cortical F-actin organization. Actin bundles were diss-organized and their density was increased compared to wild type. We have added now image-projections showing this phenotype in comparison to the wild type .We have followed the reviewer's helpful suggestion. We imaged the tube cortex of wild type and btl>moe-GFP) with anti-Emp and antiGFP in tracheal cells. Analysis of xz or yz sections within Z-stacks of airy-scan confocal images in these embryos showed low colocalization  and predominantly separate pattern of apical Emp and actin bundle domains (GFP). These results further support our proposed model that Emp is clustered outside the F-actin-rich bundles to promote the endocytosis and recycling of selected cargos along the longitudinal tube axis. See also our response in editor's comment #2.We agree. We have addressed the reviewer's suggestion now and provided a new figure showing the Emp localization in the cortex in relation to the actin bundles . Briefly, we have stained wild type embryos over-expressing a GFPtagged version of the actin binding domain of moesin  and below).When discussing the model in figure 8, the authors say that "In the bundle-free membrane domains, Emp associates with Kst and establishes an endocytosis domain, where Serp mediated Emp clustering leads to internalization." This is not shown by their data and it should be made clear that this is a hypothesis and not a thesis.We agree. In the new version, the sentence reads as follows:"We hypothesize that in the bundle-free membrane domains, Emp associates with Kst and establishes an endocytosis domain, where Serp mediated Emp clustering leads to internalization" (lines: 805-808).Ozturk-Çolak et al. (eLife 2016) presented a model whereby there is feedback between the chitinous aECM and the underlying cells. They reported that chitin downregulation increases the levels of p-Src in tracheal cells. There is a tight connection between chitin and the F-actin bundles, so I believe it is essential that the authors analyse the chitinous structure in the DT of Emp mutants. In addition, it would be very interesting  to analyse if the chitinous luminal filament is also internalised via Emp.emp mutants . However, we readily detected the disorganization of the actin bundles in the same type of parallel experiment with the same resolution . Src42A phosphorylation levels has been proposed as a feedback mechanism of the aECM to the underlying cells to modulate proper cytoskeletal organization in airways. Our work is complementary to this mechanism and further argues that Emp organizes the apical cytoskeleton by its association with bH-Spectrin. Emp provides a first direct link between an ECM component, Serp, to the cytoskeleton, through βH-Spectrin. The previously proposed feedback mechanism where the ECM composition and physical properties additionally reinforce the actin bundle organization, is part of our model in the discussion.Thank you for the comment. We stained for Gasp to visualize the chitinous matrix and analyzed the stainings with high-resolution confocal-microscopy (Airyscan). We were able to visualize the "ridges" of the apical extracellular matrix  in wild type embryos and did not detect any disorganization in Furthermore, the feedback model proposed by Ozturk-Çolak et al. could be very well integrated into this new model. The link between the aECM and the underlying cells and the modulation of the feedback could be sensed by Emp. This should be discussed.We agree with the reviewer. We believe that our model complements the proposed model in . We have also added this statement in the discussion (lines: 820-827).Reviewer #3 (Recommendations for the authors):One potentially insightful result is the phenotype of Serp-GFP overexpression, which caused a reduction of pSrc  and elevation of membrane Emp . Although down-regulation of Src and upregulation of Emp in other contexts are associated with defective tube elongation, btl>Serp-GFP caused tube over elongation . This apparent contradiction should deserve highlighted, and a deeper investigation may open a better understanding of the tube elongation mechanism. One potential clue could be to look at the anisotropy of junctional Crumbs in the btl>Serp-GFP embryos.serp verm indicating that the levels of luminal Serp are important for its normal function. Nevertheless, we have followed the suggestion from the reviewer and found that btl>Serp-GFP overexpressing embryos showed decreased Crb signals along both longitudinal and transverse junctions, in contrast to emp mutants where Crb signals were only affected along the longitudinal junctions. This suggests that the "artificially" high levels of Serp may interfere with Crb levels and the general tensile properties of the junctions.Thanks for the comment and the suggestion. We agree that it is difficult to account for the tube over-elongation phenotype caused by Serp overexpression (see editor's-comment #1 and reviewer's responses above). We had shown before that Serp-GFP overexpression unexpectedly causes similar tube elongation as the double mutant of We iterate that tube elongation involves several mechanisms including SJ components, Crb retrograde transport , transcriptional control . Future experiments are needed to elucidate the mechanism by which high Serp levels interferes with tube over-elongation.


The reliability of analysis is becoming increasinglyimportantas point-of-care diagnostics are transitioning from single-analytedetection toward multiplexed multianalyte detection. Multianalytedetection benefits greatly from complementary metal-oxide semiconductor(CMOS) integrated sensing solutions, offering miniaturized multiplexedsensing arrays with integrated readout electronics and extremely largesensor counts. The development of CMOS back end of line integrationcompatible graphene field-effect transistor (GFET)-based biosensinghas been rapid during the past few years, in terms of both the fabricationscale-up and functionalization toward biorecognition from real samplematrices. The next steps in industrialization relate to improvingreliability and require increased statistics. Regarding functionalizationtoward truly quantitative sensors, on-chip bioassays with improvedstatistics require sensor arrays with reduced variability in functionalization.Such multiplexed bioassays, whether based on graphene or on othersensitive nanomaterials, are among the most promising technologiesfor label-free electrical biosensing. As an important step towardthat, we report wafer-scale fabrication of CMOS-integrated GFET arrayswith high yield and uniformity, designed especially for biosensingapplications. We demonstrate the operation of the sensing platformarray with 512 GFETs in simultaneous detection for the sodium chlorideconcentration series. This platform offers a truly statistical approachon GFET-based biosensing and further to quantitative and multianalytesensing. The reported techniques can also be applied to other fieldsrelying on functionalized GFETs, such as gas or chemical sensing orinfrared imaging. Traditionally multiplexed testing is done on enzyme-linkedimmunosorbent assays (ELISA),2 where everyanalyte and receptor pair is measured individually. More advancedmultiplexed multianalyte diagnostic solutions can be achieved on asingle chip by using sensor arrays with integrated complementary metal-oxidesemiconductor (CMOS) readout. The benefits of CMOS integration includelow cost, dense array formation, lower power consumption, label-freedetection mechanism, readout integration, and smaller device dimensions4 which all are very beneficial especially for PoC applications.Point-of-care (PoC) diagnosticsis transitioning from single-analytedetection toward multiplexed multianalyte detection, which increasesthe importance of reliable statistical analysis.5 attomolar-level DNA hybridization,6 zika-virus detection,7 and recently also for COVID-19 causative virus monitoring.9 With CMOS-integrated GFET arrays, it is possible to overcome thecommon problems in field-effect biosensing related to the limiteddetection ranges in real-life sample matrices by utilizing PEG-polymer-aidedfunctionalization schemes.10 This is all very promisingconsidering the prospects of GFETs in label-free electrical sensingfor early diagnostics and PoC applications requiring sensitive andspecific biorecognition from biological sample matrices.One of the most promising label-free biosensing technologies, compatiblewith CMOS integration, is sensitive and selective graphene field-effecttransistor (GFET) sensors based on chemical vapor deposited (CVD)graphene. The use of GFETs has been demonstrated for peptides andantibodies,11 organic semiconductor,12 and semiconductor silicon nanowire (SiNW)FETsensors.13 All of these technologies stillhave some limitations that need to be addressed to get the full potentialout. Organic FETs have lower charge sensitivity and dynamic rangewhen compared to GFETs and SiNWFETs due to larger channel dimensions.14 SiNWFETs suffer from high device-to-device variationsand low carrier mobility.15 CNTFETs havelow current output, small active areas, and heterogeneous semiconductorand metal mixtures.16 These aspects canlead to a large variation between devices and low manufacturing yieldsfor CNTFETs.16 GFETs offer at least similarsensitivity and easier fabrication when compared with the competingtechnologies. This makes GFETs a very interesting and cost-effectiveapproach for highly sensitive label-free biosensors.Otherpromising, compatible with CMOS back end of line (BEOL) integration,FET-based technologies for biosensing are based on carbon nanotube(CNT),16 ion-selective FETs (ISFETs),17 extendedgate field-effect transistors (EGFETs),18 and film bulk acoustic resonators (FBARs).19 ISFETs and EGFETs are easy to manufacture on top of the CMOS withstandard processes.18 ISFETs also suffer typicallyfrom device stability and drift issues.21 EGFETs wereoriginally proposed as a solution to solve the drift and stabilityissues of ISFETs, and the sensitivity of the devices can be improveddue to the possibility for larger sensing areas.23 CNT-based sensors and FBARs are harder to fabricate on CMOS readoutand easily suffer from low yields in fabrication.19 With CNT-based sensors, the as-grown angle of CNTs is difficultto control without deliberate alignment, and deposited films showhigh variability in contact resistance.24 FBARs suffer from low yields due to residual stresses in the suspendedmembrane and piezoelectric layer and lengthy etching processes.25 The possibility to integrate CVD graphene withCMOS readout on chip scale has been demonstrated earlier for broadbandimage detectors26 and gas sensing.27 The possibilities of graphene integration intoCMOS BEOL have been discussed by Neumaier et al.28 However, full BEOL integration of the graphene-based biosensorarrays has not been realized due to the lack of wafer-scale CMOS readoutintegration.Previously,scalable CMOS-integrated biosensor solutions have beenreported for example with carbon nanotubes,In this work, we demonstrate for the first-timewafer-scale CMOSintegration of graphene FETs for biosensing. Functionality of theintegrated GFETs for biosensing is demonstrated using simultaneousmeasurement of 512 GFETs for a series of sodium chloride concentrationmeasurement. In our approach, we integrate GFETs on a CMOS multiplexerplatform that enables the simultaneous measurement of hundreds ofGFETs. The work done here further enables a statistical approach formultianalyte biosensing since the reliable detection of a certainanalyte requires several devices and statistics for the analysis.2The CMOS wafers used for GFETintegration were manufactured using a standard commercial technologyprovided by XFAB. The 200 mm CMOS wafers utilize a 0.35 μm analogueCMOS process node with up to four metallization layers. The CMOS technologyincludes a wide range of active devices and high-performance analogdevices.The CMOS read-out platform was designed to supportseveral types of postprocessed sensors. The architecture of the CMOSsystem and the local readout for a resistive GFET are illustratedin The global digital control is used to select theGFETs by enablingpixel-level local CMOS switches. For each GFET there is an optionto select either two-wire or four-wire connection to enable a Kelvin-typeresistance measurement. The global control of the resistive GFETsoperates as follows. The digital control SPI interface is utilizedto fetch a code string to address the GFET(s) to be analyzed. Theaddress decoder selects the corresponding GFET(s) and enables analogueswitches and the output multiplexer. The multiplexer output is inthe case of the GFET read-out fed directly to ASIC pads. In this ASICdesign, the GFET resistance is measured using external laboratoryequipment. CMOS readout also enables the integration of the resistancemeter functionality on the chip level, which will be evaluated infuture designs to increase the functionality of the system.29 The selectedoptions result in 512 individual GFETs being fabricated for each chip.A microscope image of the fabricated GFET sensors is shown in The postprocessed sensors were designed to utilize half of theavailable readouts to allow space for local liquid gate electrodesand in addition to an on-chip global liquid gate electrode. Theseliquid gate electrodes can gate the graphene channels in biosensingmeasurements. The global platinum liquid gate electrode is formedof 64 stripes that are 12 μm wide and 6400 μm long. Theusage of similar pseudoreference electrodes has been demonstratedto work reliably for GFETs.2O3 grown by atomic layer deposition (ALD). ALDgrowth on graphene was seeded using an evaporated 1-nm-thick Al filmoxidized in the evaporation chamber.A schematic illustration of the postprocessed GFETon the CMOSreadout is presented in 2O3 inH3PO4 followed by etchingthe graphene in an O2 plasma. After the graphene patterning,the devices were passivated by 50-nm-thick ALD Al2O3 and 120-nm-thick plasma-enhanced chemical vapor deposition(PECVD) Si3N4. Finally, the passivation of thedevices was opened from the top of the graphene channels by dry etchingof Si3N4 and wet etching the Al2O3. The success of the channel opening step was evaluated byan etch step and surface characterization of the graphene channelsby atomic force microscopy (AFM) . The graphene quality at the end of the processing was also characterizedby Raman spectroscopy . Thewafers were then diced into single CMOS microsystem chips.Graphene patterning wasdone by wet etching the protective AlVG) is controlledby using the global on-chip Pt liquid gate. The current (I) in the graphene channel is measured with a 0.1 V source–drainbias (VSD) over the channel.For the characterization,five sensor chips were selected across the diced wafer. The chipswere wire bonded onto chip carriers for electrical measurements. Adetector chip wire bonded on a chip carrier is shown in The graphene detector surface was cleaned withisopropanol anddeionized water (DIW), before characterization of the devices in DIWand in a series of sodium chloride (NaCl) with different concentrations.The measurement in DIW was repeated once before and after the actualmeasurement series to ensure that the devices are stable. For DIWand each concentration of NaCl, the sensor surface was further washedfive times with a 100 μL droplet of the corresponding solutionto ensure that the concentration on top of the chip was correct.e. It can be calculated for the monovalent electrolytes at room temperatureaccording to the following equation:I is the ionic strengthof the solution.To evaluate the response of the sensor chip to the physiologicalsolutions, the ionic strength of the sample solution was varied. Thetests included measurements in DIW and 1, 10, and 100 mM NaCl solutions.The channel of the graphene FETs is charged, and an electrical doublelayer (EDL) is formed on the graphene–liquid interface to neutralizethe charged surface. The thickness of the EDL can be estimated byusing the Debye length, which corresponds to the distance at whichthe electric potential has decreased in magnitude by 1/31 at 25 °C, and approximately the same value applies for thelow NaCl concentration solutions.32Based on the formula, the Debye lengths forthe 1, 10, and 100mM NaCl concentrations are 9.6 3.0, and 0.96 nm, respectively. TheDebye length corresponds approximately to the gate oxide thicknessof the GFETs. The dielectric constant of the DIW is 78.43In this work, wefocused on studying 512 GFETs with a resistive readout option fromthe five selected chips numbered from #1 to #5. The resistance valuesmeasured in ambient conditions without gating from chip #4 are shownin VG was applied using an on-chip Pt electrode to all theGFETs. The results are shown in SI2. Thedata have been normalized to the average Dirac peak voltage valueof 1.45 V (SD = 0.01 V) measured in DIW. A histogram of the normalizedDirac peak voltage values is shown in The performanceand stability of the GFETs was first evaluated by electrical measurementsin DIW. The GFETs were characterized twice in DIW to obtain resistanceof the devices as a function of the gate voltage. The gm) of the GFETsis defined as the derivative of the channel current, with respectto VG. The transconductances as a functionof the gate voltage are shown in The transconductance . The measured resistance and transconductancevalues indicate that the main response is the shift of the Dirac peakposition. The behavior can be explained with a doping change in thegraphene channel caused by the change in the gate capacitance.34 After the NaCl concentration series, an additional measurement wasdone in DIW to ensure that the devices return to the baseline establishedin the DIW characterization .Similarlyto the characterization in DIW, the GFETs were characterized to obtainresistance and transconductance values of the devices as a functionof the gate voltage for each NaCl concentration , the effect onthetotal capacitance is negligible, and only the quantum capacitanceand the double-layer capacitance at the graphene electrode need tobe considered. The experimental value of quantum capacitance is reportedto be between 2 and 11 μF cm–2, which dependson the gate potential and charged impurities.35 With a moderate charge impurity level (0.5 × 1012 cm–2) and graphene potential (±0.2 V) correspondingto the maximum and minimum transconductance point values, the quantumcapacitance is estimated to be around 4 μF cm–2. The double-layer capacitance at the graphene electrode can be calculatedby using the following equation:0 is the permittivityof free space and εr is the dielectric constant.By substituting 2/(V s) (SD = 170 cm2/(V s)) and900 cm2/(V s) (SD = 190 cm2/(V s)) for holesand electrons, respectively.The extracted transconductance values can be used to estimatethe mobility of the devices by using the following equation:36 Thesensitivity of each individual device has been estimated by usingthe measured Dirac voltage values and linear fitting, as shown in The resistance values at the Diracpeak and the corresponding Diracpeak voltage values for DIW and each NaCl concentration are shownin 48 to take the next steps toward multianalyte viral sensing.This technology enables the use of different sizes of GFET channels,with the possible number of GFETs ranging from thousands to millionsof devices depending on the ASIC circuit design and technology. Thisflexibility in the number of and size of the devices allows for awider set of applications where large amounts of biological informationneed to be evaluated, such as gene sequencing.38We demonstrate, for thefirst-time, wafer-scale GFET CMOS integrationfor biosensing with a device yield higher than 99% with a low device-to-devicevariability. We believe this approach will be crucial when commercializingGFET-based biosensors, enabling multianalyte sensing and the statisticalanalysis required for biologically quantitative on-chip bioassays.In the future, on-chip multianalyte sensing could enable efficientscreening of multiple viruses with sufficient statistics for reliabledetection from a single small analyte sample. The platform could becombined for example with the functionalization approach shown bySilvestri et al. on similar non-CMOS integration GFETsIn addition to its application in quantitative bioassays,CMOSmultiplexing can also be a valuable tool in the assay developmentphase. The most common issues in the development of FET-based biosensingare related to the reliability and repeatability of individual devicesand analysis. In many cases, the sensor chips are only used in a singlemeasurement; hence, individual faulty devices, voids in the functionalization,and small air bubbles can lead to misinterpretation of results. Thelarge-scale statistics provided by CMOS multiplexed sensor arrayson a single chip will improve the general reliability of the analysisand enable easy removal of defective devices from the data.39 Furthermore,multiplexing sensor arrays offer advantages in sensor defect exclusionand wider dynamic ranges by allowing for varying sensor design fordifferent sensitivities.37 The demonstratedtechnology also opens possibilities for the wafer-scale fabricationof CMOS-integrated GFET-based gas sensor arrays27 and infrared cameras26 thathave been demonstrated in the past. In this sense, the developmentof GFETs as a generic template that can be made specific by the choiceof functionalization allows for the adoption of this technology ina wide range of different applications.40 With CMOS integration, the readout can be tailored to fit specificneeds, which leads to a versatile sensor platform.The other benefits that the monolithic integration of GFETs offersare reduction in environmental noise and simplified connections, whencompared to hybrid off-chip sensors.


RNA folding is an inherent characteristic of RNA that plays a crucial regulatory function in all stages of post-transcriptional gene expression . This ReRecent developments in both technology and scientific knowledge have significantly promoted the Plant RNA Structure research field. This Research Topic lists two research articles and four mini-reviews with peer review. It aims to summarise the latest advances in plant RNA structure studies, emphasizing the biological significance of RNA structure and outlining potential future research directions.Jaramillo-Mesa et al.; Jin et al.; Sun et al.). Dimethyl sulfate (DMS) is a commonly used chemical that reacts with the Watson-Crick faces of single-stranded Adenine and Cytosine nucleotides . Another chemical-based profiling method is selective 2′-hydroxyl acylation analysed by primer extension (SHAPE) which detects the single-strandedness by acetylating the 2′-OH group of accessible RNA nucleotides. One widely used SHAPE chemical reagent is 2-methylnicotinic acid imidazolide (NAI) . Jin et al used DMS mutational profiling with high-throughput sequencing (DMS-MaPseq) and profiled in vivo RNA secondary structures in rice (Oryza sativa) at both target-specific and genome-wide scales. Their work revealed in vivo RNA structure features of OsPHO2, a key regulator of inorganic phosphate (Pi) homeostasis and the phosphate-starvation response pathway. Notably, the 5’UTR of OsPHO2 contains the OsmiR399 target site, where a single-stranded structure immediately downstream of the miRNA target site was observed, suggesting a regulatory function of mRNA structure on miR399-mediated Pi homeostasis. This demonstration of RNA secondary structure features under the phosphate-starvation condition in rice shows promise for future investigations of RNA structure in rice and other crops in response to nutrition deficiency.Technological breakthroughs in studying RNA secondary and tertiary structures have improved our understanding of RNA structure functionality in plants. For RNA secondary structure profiling, several chemical-based profiling methods were developed in plants . Jaramillo-Mesa et al. used SHAPE to validate the internal ribosomal entry site (IRES) structure in Triticum mosaic virus (TriMV). This guided the design of anti-sense oligonucleotides in repressing viral translation. Moreover, this work showed the role of IRES core modular RNA domains and their potential “free-for-interaction” status in both ribosomal recruitment and start codon selection in a multi-AUG viral 5’UTR. These mechanisms involving structural changes in RNA facilitate translational regulation in plants. The RNA structure profiling techniques used in this study allowed to investigate the secondary structure characteristics of plant viral RNAs, an area where earlier research was predominantly restricted to in silico and in vitro studies. The minireview of Ma and Wang provides an overview on RNA structure studies applied to viroids and how tertiary structural motifs in RNA were systematically identified and shown to have important roles in the mediation of viroid movement, including nuclear import and trafficking across diverse cellular boundaries in plants.SHAPE has been widely used to study RNA structure functionality . The authors also propose potential crop molecular breeding strategies based on the RNA structure-associated regulation of gene expression, such as translation and RNA degradation . In addition, they suggest that riboSNitches, as single nucleotide variants (SNVs) resulting in RNA structure disparities, may offer new ways for interpreting the results of genome-wide association studies (GWAS) . Moreover, riboSNitches may offer potential as molecular markers for breeding line selection to boost future molecular breeding endeavours.The review by Thomas et al.). Notably, most of these environmental conditions influence RNA structure dynamics . The authors comprehensively compared RNA secondary structure thermosensitivities between prokaryotes and eukaryotes, highlighting the role of RNA structure in mediating thermoregulation in plants. The RNA structure motif termed RNA G-quadruplex (RG4) previously known to provide thermotolerance of RNA to cold emerged as a new type of thermosensor regulating plant responses to temperature . In their minireview, Liu et al. summarize technological advances, including both chemical profiling and cell imaging, for determining the RG4 folding status in living cells. The authors also thoroughly compare different methods for RG4 detection and summarize novel functions of RG4s in regulating RNA stability and translation and, thus, plant growth and development at different temperatures. The authors suggest that the evolution of RG4 folds contributed to plant evolution and plant adaptation to the habitats found across the plant kingdom.As sessile organisms, plants are comparatively more prone than other eukaryotes to the effects of environmental conditions such as changes in temperature (The current dynamic and rapid advances in the plant RNA structure field is illustrated by the wide-ranging articles included in this Research Topic. Improving comprehension of the functional significance of RNA structure in various plant biological processes will usher a new era of research on the regulation of gene expression by modifications in RNA structure. By enhancing the research capacity for conducting genome-wide RNA structure studies across extensive plant species and viral RNAs, this progressive understanding will also facilitate the identification of both conserved and divergent RNA structures among natural variants and diverse plant species. Such studies are expected to offer opportunities for investigating the role of RNA structure in plant evolution and habitat selection. Technological advances of RNA structure probing coupled with third generation high-throughput sequencing platforms, such as Pacbio and Nanopore, will achieve high-resolution RNA structure information e.g., at single-molecular and single-cell levels. Further investigations into plant RNA structure dynamics under diverse abiotic and biotic stresses are likely to reveal more RNA structure-mediated regulations in plant responses to environmental changes. Insights into the role of RNA structure in plant thermotolerance and in thermosensing to regulate gene expression has great potential for crop enhancement strategies to mitigate the global impact of climate change on yield. The accelerating study of RNA structures will enable the scientific community to tackle these and other challenges rapidly in upcoming years, offering critical and exciting new insights into our comprehension of RNA structure-mediated regulatory mechanisms in plants.All authors listed have made a substantial, direct, and intellectual contribution to the work, and approved it for publication.


Over the last several years sexually transmitted infections (STIs) have been on the rise in the United States. A potential area for improving the diagnosis of STIs is appropriate testing of extragenital (EG) sites . These sites may serve as a reservoir for infection and lead to increased transmission if not identified and treated. Prior studies have shown that in men who have sex with men, genital testing alone misses >70% of STIs. In other patient groups, this may range from 10-40%. The aims of this project were twofold: to determine the proportion of patients receiving EG STI testing, and to observe the effect of a two-phase educational intervention on EG site testing.Phase I (Jul-Dec 2021) included four urgent care clinics within a Midwest health system. Retrospective baseline data was ascertained for all adults receiving STI testing for Chlamydia trachomatis (CT) and Neisseria gonorrhea (GC) at these clinics. Next, all four clinics received access to an educational presentation regarding the importance of EG testing for STI detection. Two of these clinics served as pilot sites for the implementation of patient self-collection kits. Data was compiled for all adults undergoing STI testing at these clinics for a 6-month period. Phase II (Jul 2022-Mar 2023) involved further expansion and utilization of a site champion at several family medicine clinics including on-site promotion of multi-site testing and patient self-collection. Educational materials as in Phase I were provided to site championsPhase I baseline data indicated that less than 1% of samples from patients receiving STI testing were obtained from EG sites. There was a small increase in EG site testing after the educational intervention and implementation of self-collected swab kits (Table 1). Phase II data showed an increase in EG testing after the utilization of a clinic site champion and the sharing of testing data in family medicine clinics (Table 2).Rates of STIs have reached an all-time high in the United States. EG infections serve as potential sources for STI transmission. Adequate multi-site testing is necessary. Implementation was most effective when a clinic site champion was identified, and clinic testing data was provided to them.All Authors: No reported disclosures


Flow diverter stents (FDS) are well established in the treatment of intracranial aneurysms which are difficult to treat with conventional endovascular techniques. However, they carry a relatively high risk of specific complications compared to conventional stents. A minor but frequent finding is the occurrence of reversible in-stent-stenosis (ISS) that tend to resolve spontaneously over time. Here, we report the case of a patient in their 30s who was treated with FDS for bilateral paraophthalmic internal carotid artery (ICA) aneurysms. ISS were found at the respective early follow-up examinations on both sides and had resolved at the 1-year follow-up examinations. Surprisingly ISS reoccurred at both sides in later follow-up examinations and again resolved spontaneously. The recurrence of ISS after resolution is a finding that has not been described previously. Its incidence and further development should be investigated systematically. This might contribute to our understanding of the mechanisms underlying the effect of FDS. Reversible in-stent-stenosis (ISS) is a common finding after treatment with flow diverter stents (FDS) , 2. AnimA patient in their 30s was administered to our department because of the incidental finding of bilateral asymptomatic paraophthalmic ICA aneurysms. Aneurysms were found on a routine cranial MRI examination that was performed because of chronic headaches. There were no other pre-existing illnesses and no cardiovascular risk factors. The aneurysms were saccular broad-based with a mean diameter of 5 mm on each side Fig. . A dual We report a case of recurrent reversible ISS after treatment of intracranial aneurysms with FDS which to our knowledge has not been reported before. Reversible ISS is a well-known minor complication of FDS treatment which has been reported in several studies , 2. It iWe can only speculate about the reasons why the recurrence of ISS after initial resolution has not been reported before. First of all, it might be a very rare complication which therefore has not been observed so far. However, a review of our own institutional follow-up routine showed that follow-up examinations of patients treated with FDS are rarely performed by DSA after more than 2 years but are usually performed by MRI. This might contribute to a low rate of detection since MRI with standard sequences has reduced specificity for stenosis in arterial segments treated by FDS .The recurrence of ISS after initial resolution is a new finding that needs further investigation in clinical and experimental studies. Since intimal hyperplasia is responsible for the initial reversible ISS, it is likely that it also causes the recurrence of ISS. However, there is no available data from clinical or experimental studies regarding long-term cellular changes after FDS treatment. Long-term follow-up MRI examinations should therefore include imaging sequences that are sensitive for in-stent-stenosis such as black-blood-imaging sequences . The fur


Slowly conducting Purkinje fibers, similar to verapamil-sensitive VT, play a critical role in the VT circuit. However, the full extent of the re-entrant circuit has not been clarified.•Novel omnipolar mapping technology using an HD grid catheter provided high resolution and precise mapping in a patient with Purkinje-related VT. Arrhythmias can be localized more accurately using the omnipolar mapping technology compared with the conventional bipolar mapping.•Even with high-density mapping, the local activation time range included only about 50% of the tachycardia cycle length of the VT. In this case, the central isthmus of the VT (Purkinje-muscle junction) was located in the activation gap. Failure to record potentials via mapping on the endocardial side is most likely owing to location of the critical isthmus of the VT circuit  in the deep myocardial layer.Monomorphic sustained ventricular tachycardia (VT) in patients with ischemic heart disease is typically caused by re-entry circuits in the scarred area of the myocardium or the borders of the scar.A 56-year-old man with prior inferior wall MI and persistent atrial fibrillation (AF) was admitted to our hospital for VT recurrence. An implantable cardioverter-defibrillator was implanted and the patient was treated with oral antiarrhythmic drugs (amiodarone 200 mg/day and bisoprolol 5 mg/day). At baseline, 12-lead electrocardiography showed AF and abnormal Q waves in the inferior leads A. The elEndocardial LV voltage mapping during intrinsic AF rhythm was performed using a duodecapolar liner electrode catheter , a high-density mapping catheter , and an EnSite™ X EP system . The duodecapolar liner electrode catheter was set where the left posterior fascicle potentials could be recorded C and 1D.Endocardial electrograms (EGMs) during the intrinsic AF and the clinical VT are shown in The clinical VT induced by right ventricular (RV) burst pacing was hemodynamically stable (VT cycle length of 450 ms). Therefore, local activation time (LAT) mapping of the LV during the clinical VT was performed. Using conventional bipolar LAT mapping during the clinical VT, the earliest activation sites (EASs) were detected at 2 separate locations C. HoweveThe earliest LAT point was −48 ms and the latest LAT point was 184 ms, and the LAT range was only about 50% of the tachycardia cycle length (TCL) D. We susWe then performed entrainment pacing during the VT at the EAS, its surroundings, and the location where LPF potentials could be recorded. The difference between the PPI after VT entrainment from the RV apex and the TCL was longer than 30 ms; therefore, bundle branch re-entry VT was unlikely. Furthermore, the LPF, as the antegrade limb of the VT circuit, usually plays a role in bundle branch re-entry VT with right bundle branch block morphology. During the VT, the QRS morphology included a right bundle branch block and a superior left axis deviation. Thus, if the patient’s re-entrant mechanism was interfascicular re-entry, antegrade activation over the LPF would be observed. Therefore, we diagnosed a Purkinje-related VT mechanism as LPFVT.We positioned an 8F, 4 mm flexible irrigated-tip catheter with 2-2-2-mm interelectrode spacing  on the EAS. Application of radiofrequency energy 35 W) immediately terminated the VT . The EAS was the exit site of the VT isthmus, and the VT terminated immediately after the application of radiofrequency energy at this location.,The omnipolar mapping technology uses 3 unipolar signals and 2 orthogonal bipolar signals to analyze the voltage, activation direction, and wave speed independent of the catheter position. Furthermore, the omnipolar mapping technology avoids “bipolar-blindness,” a phenomenon in which activation wavefronts traveling perpendicular to the electrode pair are ignored during the electrophysiological mapping.The HD grid catheter may also be suitable for recording Purkinje potentials. We reported the successful ablation of Purkinje-related VT using conventional bipolar mapping with the HD grid catheter.The second major finding is that LAT mapping and the activation vector using the novel omnipolar mapping technology provide clues to help understand the mechanisms underlying this type of VT, although the full extent of the re-entrant circuit of the Purkinje-related VT remains unknown. An activation gap in the LAT mapping during the VT was observed between the exit site and the upstream of the circuit. The LAT mapping, the activation vector, and the results of the entrainment pacing indicated that the central isthmus of the VT was located in this activation gap area. Failure to record potentials via mapping on the endocardial side was most likely owing to the location of the critical isthmus of the VT circuit  in the deep myocardial layer A. HoweveA novel omnipolar mapping technology using an HD grid catheter provides good resolution and precise mapping in a patient with Purkinje-related VT.


The traumatic effects of COVID-19 pandemic is well studied in community and fragile groups. The association between COVID-19 infection and development of severe mood disorders have not well studied.Nonetheless the casual relation or stressor effects of Covid-19 pandemic on chronic psychiatric illness is not known yet. The present study is aimed to investigate the effects of pandemic as a triggering factor in first episode Bipolar disorder (BD) patients that onset after pandemic.The study included a total sample of 55 patients diagnosed with first episode BD according to DSM-5 criteria.The two groups of patients that illness onset was before (BP)and after pandemic (AP), were investigated and compared for psychopathology and life evet stressors. Impact of Event Scale-Revised (IES-R) for PTSD symptoms, Generalize Anxiety Disorder scale for anxiety symptoms, The Montgomery–Åsberg Depression Rating Scale (MADRS) to examine depressive symptoms; and Young Mania rating Scale (YMRS) for manic symptoms, Brief Psychiatric Rating Scale-18 (BPRS) was used for psychotic symptoms.The statistical analyses were performed using the Statistical Package for Social Science, version 26. Thirty-five patients that illness onset before pandemic and 20 patients that illness onset after pandemic were compared.The significant differences were come up in some clinical features between the two groups. The alcohol and substance abuse were higher in AP group. The severity of psychotic and manic symptoms were higher in AP group. The hospitalization was higher in AP group. The number of stressor events was higher and PTSD symptoms was more severe in the AP group also.The effects of Covid-19 pandemic seems have a triggering role in onset of first episode BD. This effect whether cause biological or psychological stress in onset of illness is not known yet. The casual phenomenon of Covid-19 pandemic should be investigated for chronic psychiatric illness as BD in future studies.None Declared


Recent studies revealed that gut microbiota modulates the response to cancer immunotherapy and fecal microbiota transplantation has clinical benefits in melanoma patients during treatment. Understanding how microbiota affects individual responses is crucial for precision oncology. However, it is challenging to identify key microbial taxa with limited data as statistical and machine learning models often lose their generalizability. In this study, DeepGeni, a deep generalized interpretable autoencoder, is proposed to improve the generalizability and interpretability of microbiome profiles by augmenting data and by introducing interpretable links in the autoencoder. DeepGeni-based machine learning classifier outperforms state-of-the-art classifier in the microbiome-driven prediction of responsiveness of melanoma patients treated with immune checkpoint inhibitors. Moreover, the interpretable links of DeepGeni elucidate the most informative microbiota associated with cancer immunotherapy response. DeepGeni not only improves microbiome-driven prediction of immune checkpoint inhibitor responsiveness but also suggests potential microbial targets for fecal microbiota transplant or probiotics improving the outcome of cancer immunotherapy. Immune checkpoint inhibitors (ICIs) that block immunosuppressive molecules of tumor cells, thereby inducing host immune response are highly effective for only a subset of patients (~ 40%)4. The gut microbiome has been reported as a major extrinsic modulator to responses of ICIs such as anti-PD-1. In mice, fecal microbiota transplantation (FMT) from responders to non-responders promotes the efficacy of anti-PD-1 therapy in non-responders3. More recently, first-in-human clinical trials observed the clinical benefit of responder-derived FMT in melanoma patients6. Although the gut microbiome is associated with response to anti-PD-1 therapy, its composition and the specific mechanisms affecting host immune response remain unclear7.Recent studies have found that the composition of the gut microbiome modulates the response to cancer immunotherapies10, but unfortunately, there are discrepancies in the findings7. Many bacteria reported by those studies did not appear in multiple studies at the species level except Faecalibacterium prausnitzii and Bacteroides thetaiotaomicron. Also, previous attempt to train machine learning classifiers on microbiome profiles has shown relatively low accuracy in the prediction of ICI response on unseen data11. This suggests the need for the curation of massive-scale studies to obtain statistical power to generalize microbial signatures to unseen data.Determining the key microbiota affecting individual responses to cancer treatment is crucial for advancing precision oncology. However, this is challenging due to the limited available data sets, thereby a lack of generalizability in statistical and machine learning models. For example, multiple studies on small melanoma cohorts have reported gut bacteria associated with response to ICI therapy12. Domain generalization techniques usually require data from multiple domains or sufficient enough to simulate domain shifts, and the limited availability of microbiome data often restricts the application of the techniques. However, more recent studies proposed data augmentation approaches, circumventing the limitation15. Especially, DeepBioGen showed promise in augmenting limited sequencing data, including microbiome profiles, and improving the generalizability of classification models16.Nevertheless, recent advances in artificial intelligence, especially deep learning models for domain generalization may hold promise in generalizing microbial signatures. Domain generalization, also called out-of-distribution generalization, aims at learning models that can be generalized to an unseen domain without any foreknowledge18. Despite the remarkable performance, deep learning models are usually black-box and difficult to interpret, which hampers their adoption in clinical practice as clinicians and decision-makers prioritize the explainability of the predictions19. Also, interpretable models may provide insight into the underlying mechanisms connecting gut microbiome and host immune response.Well-generalized and accurate deep learning models have the potential to be a key part of clinical decision-making in precision medicine20. Also, a flexible autoencoder model has been developed for interpretable autoencoding without a significant loss of reconstruction accuracy21. By augmenting microbiome profiles and by introducing explainable links in the autoencoder, DeepGeni improved not only the generalizability but also the interpretability of the learned representation of microbiome profiles. DeepGeni-based classifiers outperform a state-of-the-art classifier in predicting ICI response using microbiome profiles. Also, interpretable links of DeepGeni reveal important taxa for ICI response prediction, and the identified taxa are either associated with prolonged progression-free survival in melanoma patients treated with ICI therapy or differentially abundant between responders and non-responders. DeepGeni source code is free and available at https://github.com/minoh0201/DeepGeni.In this study, DeepGeni, a deep generalized interpretable autoencoder, is proposed to unveil the gut microbiome associated with ICI response Fig. . A previ22. This study focused on samples gathered before ICI therapy and excluded the other samples taken after ICI administration. Patients’ responsiveness to ICI therapy was evaluated with RECIST 1.1 criteria where complete or partial responses are classified as responders and stable or progressive disease states as non-responders23. Since Peters et al.’s data did not have an explicit classification of responsiveness, patients with over 6 months of progression-free survival were regarded as responders and the others as non-responders as suggested by Limeta et al.11. In total, 130 melanoma patients (66 responders and 64 non-responders) were used  were considered in an initial input.Raw sequencing reads were filtered with FASTP and processed with mOTUs2, a phylogenetic (mOTU) profiler16, a sequencing profile augmentation procedure that generalizes the subsequent trainable models with the augmented data  and executed on a docker image running Tensorflow 1.13.2 as instructed.DeepGeni utilizes DeepBioGenace Fig. . The numAutoencoder consists of encoder and decoder functions that are approximated by neural networks. The encoder maps the input data points into latent space and the decoder reconstructs the input from the mapped latent representations. During training, the autoencoder tries to minimize the gap between the input and the reconstruction by adjusting the weights of neural networks based on back-propagated signals from the reconstruction loss term. Formally, the reconstruction loss can be written as,21. The non-linearity of the autoencoder comes from a non-linear activation function applied to the weighted sum of the preceding inputs. By removing the activation function in the decoder part, direct linear links from the latent layer to the output layer can be obtained. In this study, simple autoencoder architectures composed of three dense layers were utilized: input layer, latent layer, and output layer. The number of nodes of the input and output layers is the same as that of the input. Four different sizes of latent nodes were examined: 128, 64, 32, and 16. The augmented training data consisting of source and augmented data was used to train the autoencoder. After training, the encoder part was used to produce latent representations of the augmented training data. Test data was isolated from any steps of autoencoder training. We used Tensorflow (version 1.13.2) and Keras (version 2.3.1) libraries to implement the interpretable autoencoder.Svensson et al. suggested a flexible autoencoder model removing non-linearity in the decoder function, opening up the possibility to retain interpretability without ruining reconstruction quality22, and the remaining data pooled together as source data. The other approach is cross-study validation which iterates over datasets, leaves one dataset as test data, uses the remaining as source data, and averages over results. For both approaches, five-fold cross-validation on the learned representation of source data was conducted to optimize the hyperparameters of the classification algorithms. Hyper-parameter space was explored with grid search and the parameter grid is described in Supplementary Table To estimate the usefulness of the latent representations derived from the generalized autoencoder, prediction models classifying ICI responses were built on the representations Fig. b. Three 26. The informative signals of the selected latent variables were propagated through direct links in the decoder network .To interpret the latent representations that improve the prediction of ICI response, the most informative latent variables were selected based on feature importance estimated by extremely randomized treesork Fig. c. Out ofork Fig. , four cap < 0.01). We counted the number of permutations whose number of intersecting microbiota is greater than or equal to that of the finalist and obtained a p-value estimating the random chance of getting such an intersection.The statistical significance of the informative microbiota extracted by taking the intersection of four sets of candidates was assessed using permutation testing  has progression-free survival and was used in the analysis. For each mOTU, the second quartile (median) was used as a cut-off for high abundance. The Kaplan–Meier plot was drawn and the log-rank test was conducted for statistical significance. Wilcoxon rank-sum test was used to determine differentially abundant taxa.We evaluated the prediction performance of machine learning classifiers utilizing DeepGeni, a deep generalized interpretable autoencoder. The classifiers were learned to predict a binary class of ICI treatment (responder vs non-responder) based on the latent representation of microbiome profiles. Test data has been excluded from the whole process of generalizing and training the autoencoder of which the encoder part produces the latent representation. DeepGeni-based classifiers were compared to classifiers trained on three different settings without augmentation: (1) Initial data of 7727 mOTU features without feature selection or latent encoding, (2) Feature selected data (256 mOTU features) without latent encoding, (3) Feature selected data with latent encoding. For each approach, out of three classification algorithms , the best-performing one was selected. Also, a state-of-the-art approach that selects differentially abundant mOTU features and applies a random forest classification algorithm was included in the comparison. As an independent validation setting, the most recent study’s data (Peters) was used as test data, and the rest as source data for training classifiers.Remarkably, DeepGeni-based NN classifier surpasses not only the state-of-the-art classifier  but the best classifiers of other approaches Fig. . In addip-value = 9.0 × 10–6). The resulting list categorized into seven families was validated with the literature and statistical tests. The key microbiota identified in the study provide higher resolution in a taxonomic hierarchy and uncover specific species or genera that have not been clarified in the previous studies. Specifically, out of 14, 12 were cross-checked with literature and 11 were specified in lower taxonomic rank  . Besides, a high abundance of unknown Eubacterium species was significantly associated with prolonged progression-free survival in ICI-treated melanoma patients (Fig. The ICI-response-relevant key microbiota was identified by propagating informative signals through the interpretable links from latent variables that play a major role in inducing superior ICI response prediction. The intersection of four sets of microbiota candidates, each of which was derived from a one-study-out setting, resulted in 14 mOTUs (permutation testing 27 to understand the potential role of the augmentation (Fig. DeepGeni is a generalized interpretable autoencoder that not only boosts ICI response prediction accuracy in an independent study but provides interpretable links to identify informative taxa contributory to modulating ICI response. The improved generalizability of DeepGeni is supposed to be derived from augmented microbiome data generated by DeepBioGen, a GAN-based data augmentation procedure. We plotted the augmented data along with source and test data in 2-D space using t-SNE algorithmion Fig. . InteresThe latent representation learned by the generalized autoencoder with the augmented data seems to enable the trained classifiers more resilient to unseen data distributions. Also, DeepGeni extracted microbial species informative to predict ICI response in higher resolution than other studies. The specified species could be a helpful basis for establishing ICI-promoting FMT guidelines to specify donor and donee. Moreover, the identified species may offer a possibility to develop pre or probiotics targeting improved outcomes of ICI therapy.9. However, our understanding of how gut microbes might influence ICI response remains lacking, although some studies partially explain potential mechanisms at a high level, such as low diversity and imbalanced microbiota33. This study suggests specific bacterial taxa derived from the interpretation of deep generative models that brought the best performance in ICI response prediction and the taxa that were not able to be extracted from the available data with traditional statistical methods. The findings could help direct future studies and formulate potential mechanisms of different responses.Landmark studies showed the translational relevance of commensal gut microbiota affecting response to immune checkpoint blockades through clinical cohortsAlthough this study produces the generalized list of ICI-response-relevant key microbial taxa over the available datasets, the ability to statistically validate the identified microbial taxa is bounded by the size of the available data. This could limit the possibility of being validated for some of the key microbial taxa as they were identified by taking advantage of the out-of-distribution augmented data and it may not be eligible to use the augmented data for statistical validation. However, there still remains the possibility of being validated in larger data sets once they become available.DeepGeni was applied to examine microbiome potentially modulating ICI response in this study but it is highly extensible for identifying microbiome-driven human phenotypes or even for applying other types of biological and ecological data such as genome and metagenome profiles.34.We proposed DeepGeni, a generalized interpretable autoencoder that learns a latent representation of microbiome profiles. The learned representation can improve ICI response prediction on unseen data and suggest the most informative microbial taxa involved in modulating ICI response. In the future study, this work can be extended to other types of features extracted from the microbiome data such as functional-level features that have been shown to exhibit more discriminative powers in certain diseasesSupplementary Information.